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PMC10000341 | Malar J Malar J Malaria Journal 1475-2875 BioMed Central London 36899358 4459 10.1186/s12936-023-04459-9 Meeting Report Gaps in research and capacity development for malaria surveillance and response in the Asia-Pacific: meeting report Sirimatayanant Massaya 1 Hein Phone Si 2 Anderson Laura Fay 3 Montoya Lucia Fernandez 3 Potter Rebecca 4 Nghipumbwa Mwalenga 3 Ranaweera Prasad 5 Ngor Pengby 16 Phetsouvanh Rattanaxay 7 Maude Richard J. [email protected] 18910 1 grid.10223.32 0000 0004 1937 0490 Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand 2 Asia Pacific Malaria Elimination Network (APMEN), Singapore, Singapore 3 grid.3575.4 0000000121633745 Global Malaria Programme, World Health Organization, Geneva, Switzerland 4 grid.5510.1 0000 0004 1936 8921 University of Oslo, Oslo, Norway 5 grid.466905.8 Anti-Malaria Campaign, Ministry of Health, Colombo, Sri Lanka 6 grid.452707.3 National Centre for Parasitology, Entomology and Malaria Control, Phnom Penh, Cambodia 7 grid.415768.9 0000 0004 8340 2282 Department of Communicable Disease Control, Ministry of Health, Vientiane, Lao PDR 8 grid.4991.5 0000 0004 1936 8948 Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK 9 grid.38142.3c 000000041936754X Harvard TH Chan School of Public Health, Harvard University, Boston, USA 10 grid.10837.3d 0000 0000 9606 9301 The Open University, Milton Keynes, UK 10 3 2023 10 3 2023 2023 22 9114 1 2023 14 1 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background This report is based on the 2021 annual meeting of the Asia-Pacific Malaria Elimination Network Surveillance and Response Working Group held online on November 1-3, 2021. In light of the 2030 regional malaria elimination goal, there is an urgency for Asia-Pacific countries to accelerate progress towards national elimination and prevent re-establishment. The Asia Pacific Malaria Elimination Network (APMEN) Surveillance Response Working Group (SRWG) supports elimination goals of national malaria control programmes (NMCPs) by expanding the knowledge base, guiding the region-specific operational research agenda and addressing evidence gaps to improve surveillance and response activities. Methods An online annual meeting was hosted from 1 to 3 November 2021, to reflect on research needed to support malaria elimination in the region, challenges with malaria data quality and integration, current surveillance-related technical tools, and training needs of NMCPs to support surveillance and response activities. Facilitator-led breakout groups were held during meeting sessions to encourage discussion and share experience. A list of identified research priorities was voted on by attendees and non-attending NMCP APMEN contacts. Findings 127 participants from 13 country partners and 44 partner institutions attended the meeting, identifying strategies to address malaria transmission amongst mobile and migrant populations as the top research priority, followed by cost effective surveillance strategies in low resource settings, and integration of malaria surveillance into broader health systems. Key challenges, solutions and best practices for improving data quality and integrating epidemiology and entomology data were identified, including technical solutions to improve surveillance activities, guiding priority themes for hosting informative webinars, training workshops and technical support initiatives. Inter-regional partnerships and SRWG-led training plans were developed in consultation with members to be launched from 2022 onwards. Conclusion The 2021 SRWG annual meeting provided an opportunity for regional stakeholders, both NMCPs and APMEN partner institutions, to highlight remaining challenges and barriers and identify research priorities pertaining to surveillance and response in the region, and advocate for strengthening capacity through training and supportive partnerships. Supplementary Information The online version contains supplementary material available at 10.1186/s12936-023-04459-9. issue-copyright-statement(c) The Author(s) 2023 pmcBackground Between 2000 and 2020, estimated malaria incidence and mortality reduced significantly in the WHO South-East Asia region (SEARO) by 83% and 81%, respectively. The region met the Global Technical Strategy (GTS) 2020 milestone of reducing mortality and morbidity by 40% from a 2015 baseline . However, in the Western Pacific region (WPRO) there was an overall increase in incidence and mortality between 2015 and 2020 and malaria is expected to persist until 2030 . In light of the 2030 regional elimination goal, there is increasing urgency for Asia-Pacific countries to accelerate progress towards national malaria elimination, concentrating on high burden geographies, and prevent re-establishment . The Asia Pacific Malaria Elimination Network (APMEN) was established in 2009 and has since grown to host a forum of 21 country partner National Malaria Control Programmes (NMCPs) committed to eliminating malaria within their borders and supporting region wide elimination by 2030. Under APMEN, three working groups provide technical support and guidance on key themes of malaria control and management, namely, vector control, surveillance and response, and Plasmodium vivax. Through a network of partner institutions including non-governmental organizations, academic and research institutions, funding agencies, the private sector, United Nations agencies, and civil society organizations, APMEN provides country partners with access to technical knowledge, tools, and expertise to support their respective national and regional elimination goals. The Asia Pacific Leaders Malaria Alliance (APLMA) and APMEN Secretariats were brought together in 2015 to strengthen elimination efforts by combining the political advocacy and multi-sectoral access of APLMA with APMEN's technical expertise and direct engagement with malaria control programmes . With the transformation of malaria surveillance as a core intervention under the WHO Global Technical Strategy (GTS) , the APMEN SRWG has been supporting expansion of the knowledge base, development of a region-specific operational research agenda and addressing evidence gaps to ensure that country partners can effectively implement surveillance strategies that identify and respond to every malaria case . As a peer-led technical working group, the hosting arrangement of the SRWG rotates biannually and is currently co-chaired by Dr Rattanaxay Phetsouvanh, Director General of the Department of Communicable Disease Control, Ministry of Health in Lao PDR, and Professor Richard J. Maude, Head of the Epidemiology Department at Mahidol Oxford Tropical Medicine Research Unit (MORU) for 2021-2022. Annually, the SRWG hosts a general membership meeting bringing together country partners and experts from across the world to reflect on recent developments and address key challenges pertaining to malaria surveillance activities in the region. In line with the 2021 updated strategy highlighting the need to integrate malaria services into broader health delivery systems and strengthen countries' capacity to collect, analyse and use malaria-related data , the SRWG focused this year's annual meeting around the theme of "Moving from Data to Elimination" through building capacity in research, data quality, and integration. Due to the COVID-19 pandemic, the 2021 meeting was organized virtually on 1-3 November and was attended by 127 participants comprising 13 country partner NMCPs, and 44 partner institutions from 24 countries across the world (the meeting agenda and list of attending organizations is found in Additional Files 1, 2, respectively). This meeting report documents outcomes from the virtual meeting, key discussion points from the breakout sessions and findings from surveys conducted as part of the proceedings. Data to elimination: prioritizing gaps in research and capacity development for surveillance and response The WHO GTS outlines a key supporting element to achieving elimination requires leveraging innovation and expanding both clinical and implementation research . The last SRWG annual meeting organized in 2018 discussed challenges and barriers to identifying and implementing solutions for improving case-based surveillance and response activities and, among other goals, to review approaches and tools for improving surveillance activities . The 2021 SRWG annual meeting provided an update on partner perspectives regarding remaining challenges and barriers to implementing surveillance and response activities, what research is needed to address challenges to eliminating malaria in the region, review current surveillance-related technical tools, and reflect on training needs of national programmes to support surveillance and response activities. A summary of the session goals, outcomes and action points can be found in Table 1.Table 1 Meeting output and action points Session goals Session outputs Action points Session 1: building capacity through research Discuss, identify and prioritize what research is needed to support malaria elimination in the Asia-Pacific region - List of research questions submitted by NMCPs in different sub-regions and APMEN partner institutions (Additional File 1) - Priority research in order of votes: 1. Strategies to address malaria transmission amongst mobile and migrant populations (MMPs) 2. Cost effective surveillance strategies to maximize in low resource setting 3. Integration of malaria surveillance with the broader health system 4. Minimal surveillance package for monitoring and evaluation for sustaining malaria free status - Build capacity for elimination through research by: 1. Openly and widely disseminating identified research priorities 2. Providing linkage with APMEN research institutions to conduct the research needed in specific countries 3. Advocating to potential donors to fund the identified research priorities Session 2 & 3: building capacity through data quality, integration and technology Identify key challenges to, and solutions for, improving data quality Identify key challenges to, and solutions for, integrating epidemiology and entomology data for malaria surveillance Review technical solutions for malaria elimination - Data quality challenges: 1. Limited human resources and technological capacity for data collection and entry processes 2. Difficulty in tracing mobile and migrant populations 3. Poor or lack of Standard Operating Procedures (SOP) and monitoring and evaluation of both data collection teams and data quality 4. Competing priorities for data collectors 5. Complex reporting and poor data management systems - Data quality solutions: 1. Clear SOPs for case investigation 2. Simplified reporting systems and digitization of data collection tools 3. Improved monitoring and supervision of data collection units 4. Establishment of a national quality assurance system for malaria diagnosis 5. Routine data cleaning and review 6. Integration of private sector data and supplementing with geospatial information - Data integration challenges: 1. Divergence in spatial resolution, coverage and frequency of data collected 2. Costliness and lack of capacity to collect entomological data 3. Extrapolating vector surveillance data geographically 4. Lack of data management systems supporting integration of both types of data - Data integration solutions: 1. Correlating data collected at the same geographical location and time 2. Coordinating data collection between epidemiological and entomological data collection teams 3. Unifying data collection and management systems - Technical solutions: 1. WHO's Digital Solutions for Malaria Elimination initiative supports the use of digital tools to strengthen an integrated surveillance information system on the DHIS2 platform 2. Utilization of malaria packages under DHIS2 metadata tools to leverage the health management information system 3. Google data studio as complementary digital dashboard for malaria case-based and drug stock surveillance in Sri Lanka 4. Nationally designed and tailored web-based Malaria Information System in Cambodia supports real-time reporting through mobile applications - Build capacity for elimination through improved data quality and integration by: 1. Reviewing key challenges and barriers raised across national programs to target topics for implementing informative webinars and training workshops for the wider APMEN audience 2. Providing linkage with APMEN implementing partners to establish technical support initiatives Session 4: moving from data to elimination Identify ways to strengthen capacity to utilize data for action - Inter-regional partnerships with the Roll Back Malaria Surveillance, Monitoring and Evaluation Reference Group's Surveillance Practice and Data Quality (SMERG SP&DQ) Committee - Training topics identified from training needs assessment and breakout group discussions: 1. Malaria vector surveillance 2. Case and foci investigation 3. GIS and mapping 4. Data quality assurance in the surveillance data pipeline - Build capacity for elimination through training by: 1. Developing cross-regional training workshops 2. Designing and delivering training workshops for data quality dimensions and GIS and mapping 3. Establishing technical support initiatives to improve the quality of case and foci investigation in specific countries that have expressed interest Research needed to support malaria elimination in the Asia-Pacific region Breakout groups dividing participants by subregion and APMEN membership type allowed identification of research priorities stratified by sub-regional needs and organizational focus. Facilitators asked participants to submit research questions on Slido, an interactive application used for hybrid meetings, clarify components of the research question, and vote on the priority questions from the full list of research questions submitted within each subgroup. Research questions from all subgroups were pooled and grouped by themes, and opened for voting by all participants of the annual meeting on the Qualtrics XM platform, to derive a region-wide list of ranked research priorities. Follow-up email invitations to participate in the survey were distributed to contacts from APMEN country partners not present at the meeting (18 countries, including 7 not at the meeting). In total, the survey received 14 responses from eight country partners, and 27 responses from partner institutions deriving the list of top-ranking research priorities. The full list of research questions identified by each subgroup and ranked by priority is in Additional File 1. Strategies for malaria elimination to address malaria transmission amongst mobile and migrant populations (MMPs), including forest goers, was the highest voted research priority by both country partners and partner institutions. Transmission of malaria in near elimination settings, particularly the Greater Mekong Subregion (GMS), often happens in forests and in cross-border areas where human mobility is high . Because of this, village-based malaria control and elimination strategies common in the GMS cannot provide effective monitoring, health education or care service coverage for this vulnerable high-risk group , therefore, they may act as reservoirs of malaria . Research to determine healthcare-seeking behaviours and mobility patterns of MMPs and those populations living at the borders where transmission is harder to trace, will be essential to monitoring high risk-groups and disease transmission patterns. Break-out group participants discussed how mobile and migrant population movement mapping, within and across national borders, will be vital research to inform surveillance and response strategies for targeting the last remaining transmission foci and support elimination in many Asia-Pacific countries. The second top voted research question was determining cost effective surveillance strategies to maximize efficiency in low resource settings. To achieve elimination, the 2017 World Health Organization (WHO) Framework for Elimination suggested that surveillance systems transition from reporting aggregate case data towards case-based surveillance to rapidly identify, investigate, classify, report and respond to all individual malaria cases to effectively manage cases and implement informed vector control interventions. An effective surveillance and response system that detects and responds to every new case and focus can therefore be resource intensive . Many malaria programmes in low resource settings rely on donor or international funding which is often influenced by changing international public health landscapes and priorities that subsequently impact the consistency and sustainability of financial assistance . Contextualized surveillance strategies that are cost effective will be a priority for many malaria programmes in the region that have to maximize use of declining resources to maintain momentum for elimination or sustain efforts against re-establishment in the post elimination phase. Other top research priorities identified by country partners included integration of malaria surveillance with the broader health system, and minimal surveillance packages for monitoring and evaluation to sustain malaria free status. While guidelines for both research priorities exist in the WHO Malaria Surveillance, Monitoring and Evaluation Reference Manual , operationalization remains challenging for national programmes . Research is needed to identify the best tools and practices for how to operationally implement adaptive surveillance systems that integrates malaria services and indicators into the general health service and information systems, and standardize tools for monitoring the quality of malaria surveillance in low to zero transmission settings . Challenges and solutions to ensuring high quality surveillance data to guide decision making Dr Laura Fay Anderson (Global Malaria Programme--GMP, WHO) presented the WHO's Malaria Surveillance Assessment Toolkit as an introduction to the session on surveillance and data quality. The toolkit includes a minimum set of priority indicators that allow comparable and replicable malaria surveillance assessments across multiple countries or within the same country over time, and is adaptable to country context by allowing users to define the assessment scope. For eliminating countries with very low levels of transmission, the toolkit can be used to evaluate a surveillance system's ability to capture and respond to every case and show preparedness to prevent re-establishment. For all levels of transmission, the assessment allows for evidence-based and prioritized recommendations to strengthen surveillance systems and ensure that response activities are well targeted. Currently, the WHO is piloting the toolkit to carry out comprehensive assessments in five African countries. As this effort had not expanded to the Asia-Pacific, randomly allocated breakout groups were created in the session that followed to discuss challenges and solutions to ensuring high quality surveillance data in this region. Participants across breakout groups cited challenges in the data collection processes that impact surveillance data quality, ranging from issues with collecting data using mobile populations, within and across countries, to limitations pertaining to data collection procedures. Participants indicated difficulty in tracing MMPs leading to double counting and losses from follow-up across subnational and international borders. Participants also noted that poor or lack of standard operating procedures (SOPs) for field data collection, and diverging quality of case information and definitions impact data completeness and accuracy. Limited human resources and capacity for data collection and entry due to insufficient training, difficulty in reaching remote areas, and high workload for staff compiling and entering data also affected the timeliness of data availability and monthly reporting. Lack of monitoring and evaluation processes, including SOPs for checking data quality, were also noted as a challenge. Clear SOPs and guidelines on when and how cases are investigated, and use of simplified forms and user-friendly reporting systems were suggested as possible solutions. Participants also proposed staff monitoring and supervision through data entry feedback sessions and establishing data collection groups to review data. Good training tools and methods to motivate staff, such as by stressing the importance of surveillance data for policy responses, are other ways to improve human resources and capacity for data collection and entry when there are competing priorities. Highlighting high achieving data collection units was suggested as a way to motivate staff members. Finally, as countries move towards elimination, a national quality assurance system for malaria diagnosis was indicated as vital for ensuring malaria surveillance data quality. To ensure completeness of data, simple routine data cleaning and checking involving following up on missing and incomplete data was suggested. Involvement of the private sector, a major provider of malaria diagnosis and treatment in many countries , in the malaria surveillance system will also be vital to capture the whole picture of malaria endemicity. Limitations cited related to tools or technologies, including issues with internet connectivity and limited use of modern technology to collect and upload data in remote areas. Digitalization of data through the use of tablets or mobile phones for data collection and developing localized data entry systems were discussed as possible solutions. Additionally, participants explained that complex data collection tools, with multiple forms and reporting systems used in many countries, may lead to duplication and inconsistent data especially when comparing surveillance data collected by public and private health facilities. Inadequate storage and management of data were indicated as data quality challenges, citing difficulties in integrating multiple data streams and catchments as well as data platforms used for different types of data and/or funding sources. Designing contextualized digital data dashboards which integrate multiple data streams will be key to addressing this challenge and promoting data utilization. Participants described how suboptimal data quality impacts decision making for planning and targeting interventions, and resource management. Incorrect case classifications, non-standardization of case definitions that lead to varying interpretation across programmes, and gaps in knowledge about specific surveillance elements such as entomological, geographical or demographic were all identified to negatively impact data used to inform intervention planning and decision making by NMCPs. When data is not contextualized accurately in space and time, resources may not be efficiently prioritized and programmes may not be able to respond to the needs around RDT and drug stocks, and training. Waste of resources further reduces programme cost effectiveness. Data delays hamper ability to provide timely interventions to respond to cases and outbreaks. Challenges and solutions to integrating epidemiological and entomological data for decision making In her presentation, Dr Lucia Fernandez Montoya (GMP, WHO) highlighted the need to integrate routine entomological surveillance data with epidemiological and environmental information to provide a holistic understanding of malaria transmission dynamics and guide malaria control efforts. Malaria is transmitted by Anopheles mosquito vectors and vector control intervention are among the most effective intervention for malaria control . Each vector control intervention targets different characteristics of mosquito vectors, for example, IRS targets indoor resting adult vectors, ITNs target indoor biting adult vectors, larviciding targets immature vector stages. Different Anopheles species have varying preferences for environmental conditions (e.g. forest, forest fringe, rice field); resting and biting location (indoor/outdoor), biting times and feeding (humans or animal blood) which determine both their vulnerability to each vector control intervention and malaria transmission patterns . On its own, entomological surveillance can help to identify the main vectors that should be targetted and identify challenges to effective vector control (e.g. insecticide resistance, vector exophily or exophagy, and changes in vector composition). Combined with epidemiological and other types of data, it can help to determine receptivity and vulnerability to malaria transmission in different areas; select appropriate vector control interventions and their deployment modalities; monitor and evaluate the effectiveness of vector control interventions; investigate the causes of malaria outbreaks, unexpected patterns of transmission and drivers of transmission in transmission foci; and evaluate the risk of reintroduction of malaria into areas where it was previously eliminated . Entomological surveillance can be conducted using different vector collection methods, each of which provides different types of information and allows for the calculation of only a subset of core entomological indicators (19). Entomological surveillance systems and derived indicators must therefore be carefully designed to provide useful information for programme planning and implementation . The timing and location of entomological data collection should also be planned to address programme information needs. Participants were randomly allocated into breakout groups to identify challenges to integrating epidemiological and entomological data. The first major challenge identified was differences in the frequency and geographical scale of data making combined analyses difficult. Entomological data are generally collected during foci investigation or surveys in relatively small areas for specific time periods, whereas epidemiological data is collected continuously from every heath provider/facility. Another challenge is the difficulty and high cost of collecting entomological data, especially in deep forested areas where vulnerability to malaria transmission is generally high. Entomological data collection also requires specific equipment, that needs to be transported to the field and frequently replaced, and specialized training to use it. Challenges to analysing entomological data due to its complexity, and with extrapolating vector surveillance data across all areas, were also discussed by participants. These lead to limited utilization of entomological data in designing interventions and responses. Participants further identified lack of data sharing between entomology and epidemiology teams, and lack of feedback on reported data across the program and implementers as a challenge to data use and integration. Participants also identified differences in the systems used for the collection of epidemiological and entomological data as a challenge for data integration. In some countries, epidemiological data is collected through DHIS2, while a different system is used for collecting entomological data. In some cases, several different systems are used for the collection of entomological data within the same country, which further hampers data integration. Integration will require determining the optimal spatial and temporal granularity of different data so they can be combined to inform decision making. Ways to enhance the resolution of entomological data to better match epidemiological data scales were discussed, including by conducting vector suitability mapping using satellite data. Data may be integrated by visualizing entomological and epidemiological data together to explore patterns and trends between the two types of data. Coordination between epidemiological and entomological data collection teams, and between national programmes and partners, is also essential for successful data integration. Finally, using the same data management platform for both data was felt to be important for proper integration. Technical solutions for malaria elimination The WHO outlines a key supporting element to achieving elimination requires leveraging innovation in addition to expanding both clinical and implementation research . New technologies, such as mobile applications and digital platforms, can improve surveillance activities and quality of surveillance data. Such technologies can speed up data collection, reporting, consolidation, feedback, sharing and presentation. Moreover, information technology can enhance procurement and supply chain, service delivery, and financial and other resource mobilization. The final session of the annual meeting covered various technical solutions to improve malaria surveillance. An optimal, fully integrated malaria information system should include the collection of complete and correct data, real-time reporting, storage and integration, data analysis and visualization, data sharing and active and continuous data interpretation. Rebecca Potter (University of Oslo) presented the DHIS2 malaria toolkit which was developed in partnership with WHO GMP to reflect global normative guidance and WHO recommendations. The toolkit includes standardized metadata packages for case notification, investigation, and classification workflows, as well as foci investigation and response. The packages are designed to make it easier for NMCPs to adopt global recommendations for malaria data collection and analysis into their national information systems that are using DHSI2 software. Data-quality tools and pre-configured dashboards for malaria surveillance in elimination settings support NMCPs to implement rapid data-driven responses. Collaboration with GMP was planned to expand the DHIS2 toolkit for supporting integration of entomological data. These tools were developed to facilitate the integration of malaria data into the broader national health information system. The importance of the quality, availability, and utilization of malaria surveillance data for decision-making to better tailor and target programmatic activities is highlighted in the WHO GTS for Malaria . This has led to countries adopting online or electronic malaria systems to notify cases within 24-48 hours, support timely reporting, and implement real-time case and foci surveillance and vector mapping. Mwalenga Nghipumbwa (GMP, WHO) presented on how the WHO is supporting the enhancement and development of existing and new digital tools to strengthen these integrated near-real time surveillance systems. The digital solutions for malaria elimination (DSME) community developed effective mobile application tools connected to upgraded core DHIS2 functionalities to simplify complete, timely and accurate data reporting. The suite of tools include the DHIS2 Android Capture app and OpenSRP platform used to support real-time reporting and case notification, as well as foci investigation. NMCP applications of various digital solutions to support malaria surveillance systems were presented for Sri Lanka and Cambodia. Dr. Prasad Ranaweera (Ministry of Health and Indigenous Medicine, Sri Lanka) demonstrated the use of Google Data Studio to easily upload data and customize dashboards for tracking antimalarial drug stocks and RDTs. The use of this platform complements the DHIS2 system, and was introduced to the Anti-Malaria Campaign in Sri Lanka during the post elimination phase. Dr Pengby Ngor (MORU/National Center for Parasitology, Entomology and Malaria Control) described Cambodia's standalone malaria information system (MIS), which captures both passive and active surveillance data in real-time through health centres and village-based malaria workers, respectively, using a web-based interface and Android smartphone malaria surveillance applications. While challenges remain with device maintenance and providing regular refresher training for turnover of staff, the locally designed application is low-cost, sustainable, decentralized and tailored to the country's malaria elimination context. Plans are being made to adapt this tool for the surveillance of other diseases. Capacity and training needed for national malaria control programmes The final session focused on sharing cross-regional initiatives on accruing surveillance best practices and evaluating the barriers to, and gaps in, training for country partners needed to strengthen surveillance and response activities. Dr Arantxa Roca-Feltrer (Malaria Consortium), co-chair of the Roll Back Malaria Surveillance Monitoring and Evaluation Reference Group (RBM-SMERG) introduced upcoming initiatives and resources under the committee for Surveillance Practice and Data Quality (SP&DQ), including development of a systematic tracker of implementing partners' data quality projects, and NMCPs' use of surveillance practices. Anne-Sophie Stratil (Malaria Consortium) presented findings from a needs assessment of NMCPs in African countries, identifying priority challenges in using data for program and policy decisions, assessing data quality, reporting, collecting, visualizing and interpreting program data. While the RBM-SMERG has traditionally been an African centric group, collaborations and exchanges with the APMEN SRWG are planned to support exposure and interaction across regional bodies to capture activities and best practices from the full spectrum of endemic countries in the two regions. Findings from a survey of APMEN partner countries' training needs and partner institutions' training capacity conducted in 2021 were presented by Massaya Sirimatayanant (MORU/SRWG). The survey received 40 responses (22 from country partners and 18 from partner institutions) identifying country partners' interest in skills-based training. The survey also identified APMEN partner institutions with ability and interest to provide training in topics of interest to country partners. Virtual face-to-face follow-up discussions clarified the specifics of the training contents and target audiences. From this, five priority training topics were identified as of most interest to NMCPs: entomological surveillance, data utilization (data to action), basic statistical analysis, mapping and GIS, and case investigation. Feasibility to deliver, and interest in receiving, training on these topics were further explored in self-assigned breakout group sessions. For entomological surveillance, shortfalls and training needs in the Asia Pacific have been identified and prioritized across sub-regions by the APMEN Vector Control Working Group (VCWG). Upcoming VCWG initiatives including a 6-module online training on malaria vector surveillance and a face-to-face two-week intensive vector surveillance course were discussed for 2022. In the breakout group discussing case and foci investigation, participants acknowledged that training is already being conducted by NMCPs in countries. A framework for defining cases exists and may be used to deliver basic training across countries, but participants noted that training for classification of cases and transmission sites will be unique to each country context and require training that is adapted to each transmission setting. Participants discussed the potential to deliver training to improve the quality of case and foci investigation through bilateral NMCP-NMCP or NMCP-partner institution technical support initiatives facilitated by the SRWG. In the GIS and mapping breakout group, a survey found that a mix of NMCP staff at national and sub-national levels had already received GIS/mapping-related training. There was interest to strengthen capacity for central level staff through introductory and more advanced training to use geospatial software for malaria surveillance and monitoring, and at sub-provincial levels training should be focused on introducing geospatial data and technologies for surveillance and how to collect geographic coordinates in the field. An online training module on GIS for mapping infectious diseases is under development by Dr Steeve Ebener (Health GeoLab Group in MORU Epidemiology Department) and Prof Richard Maude (MORU), and online workshops adapted for malaria are expected to be delivered via APMEN in 2022. Finally, for the combined training themes of data utilization and basic statistical analysis, participants expressed a preference to focus on data processes, including data collection and quality checking, rather than basic statistical analyses. This focus was acknowledged by the SRWG, and training on quality assurance within the surveillance data pipeline will be a priority deliverable in 2022. Discussion and next steps While there has been steady progress towards achieving the goal of regional elimination by 2030, a number of research gaps, implementation challenges and training needs pertaining to surveillance and response activities have been identified during the SRWG annual meeting for Asia-Pacific countries. Action points resulting from the meeting outcomes are outlined in Table 1. The higher active attendance of stakeholders from the GMS region (44 percent of total attendees across all three days) may have contributed to identification of research priorities that reflect challenges currently prominent in low transmission settings. However sub-regional level breakout group discussions and voting on research priorities that were open to the wider regional audience allowed identification of other top research priorities, including cost effective surveillance strategies and integration of malaria surveillance into broader health systems, which are highly relevant for countries in all transmission settings in the region. Globally, funding for malaria has remained stagnant since 2010 , and with competing domestic public health priorities, ensuring that malaria interventions and surveillance strategies are cost effective and well-integrated into the wider public health system will be vital for sustainability of malaria programmes. Identification of key research priorities needed to support malaria elimination according to stakeholders will be critical to guiding operational research at the sub-regional level and across the Asia Pacific. Their dissemination to a wider audience to guide linkages between research institutions and NMCPs, and to potential donors, will be a target action point for the SRWG to support ongoing elimination efforts. Discussions surrounding surveillance data quality and integration challenges, particularly the limited examples of initiatives targeting improvement in these within the region, suggests that there are significant gaps in research and best practices for both themes. While there have been some piloted efforts in the GMS to improve completeness of malaria incidence data, such as through integration of private sector data , a past assessment of national surveillance systems in the Asia Pacific found malaria incidence data in many countries still misses information from a wide range of potential sources . Furthermore, while pilots of digital tools for improving timeliness of malaria case data collection have been explored [25-28], difficulty with scaling and challenges in reporting timeliness as discussed in the breakout group highlight its persistent impact on NMCP's ability to implement targeted and timely responses to outbreaks. While the GTS has emphasized the importance of high-quality routine data by redefining surveillance as a core intervention in malaria control and elimination , there have been limited efforts to evaluate programmes' ability to capture quality routine malaria surveillance data when compared to Africa [29-33]. High quality of routine surveillance data and integration of various sources and types of data are needed to provide a complete picture of malaria incidence within a country in order to successfully plan for malaria control and elimination and inform targeted response strategies. Advocacy to prioritize data quality assurance measures will be sought through hosting APMEN-supported informative webinars and workshops. Due to the unique nature of different surveillance systems and Health Management Information Systems (HMIS) adopted across countries in the region, the SRWG will seek to provide context specific technical support by linking NMCPs with partner institutions with the relevant expertise. Group brainstorming sessions complemented a previously implemented training needs assessment by offering the wider SRWG membership to clarify training content that partner countries are interested in receiving. In comparison to the pre-determined training topics list provided for respondents to select in the training needs assessment survey, the breakout group facilitated discussions between NMCPs and partner institution members to suggest deviations from the original topics based on contextual needs and regional expertise available. Both activities determined which training may be delivered to a wider APMEN audience (vector surveillance and GIS and mapping), and which require context specific technical support (case and foci investigation). Engaging RBM's Committee on Surveillance Practice and Data Quality, active in the African content, allows the SRWG to co-develop cross-regional training workshops on surveillance data quality that are of relevance to both regions. Conclusion While progress towards elimination has been made across the region, the global COVID-19 pandemic has tested the resilience of national malaria programmes and their ability to implement surveillance and response activities for malaria amidst lockdowns and competing public health priorities. The 2021 SRWG annual meeting provided an opportunity for regional stakeholders, both NMCPs and partner institutions, to highlight the remaining challenges and barriers, update on and share innovative technologies, and advocate for both region-wide as well as context specific initiatives to strengthen surveillance and response activities. Identification of research and NMCP training priorities are vital to ensuring that supportive initiatives within the region, including SRWG-led activities, are well-targeted to meet the needs of countries for building capacity to achieve elimination by 2030. Supplementary Information Additional file 1: Meeting agenda. Additional file 2: List of attending country partner National Malaria Control Programmes and partner institutions. Additional file 3: Breakout groups and identified research priorities on malaria surveillance in the region. Abbreviations SEARO South-East Asia region (SEARO) WPRO Western Pacific region APMEN Asia Pacific Malaria Elimination Network SRWG APMEN Surveillance and Response Working Group NMCP National malaria control programme APLMA Asia Pacific Leaders Malaria Alliance GTS Global technical strategy MORU Mahidol Oxford tropical medicine research unit MMP Mobile and migrant populations GMP Global malaria programme DHIS2 District health information software SOPs Standard operating procedures GMS Greater Mekong subregion DSME Digital solutions for malaria elimination MIS Malaria information system RBM-SMERG RBM surveillance monitoring and evaluation reference group SP&DQ Surveillance practice and data quality committee VCWG APMEN vector control working group HMIS Health management information system Acknowledgements We would like to thank all the National Malaria Control Programme representatives, and partner institutions from academia, private sector, international and non-government organizations for attending and providing their insightful participation during the meeting activities. We are also grateful to all the speakers included in this report for their valuable contributions to sharing knowledge and expertise within the network, and to Drs Abdul Majeed (Directorate of Malaria Control, Pakistan), Siv Sovannaroth (National Center for Parasitology, Entomology & Malaria Control, Cambodia), and Luciano Tuseo (WHO Regional Office for the Western Pacific, Philippines and WHO Cambodia) for their guidance and support as session chairs throughout the annual meeting. Author contributions MS, PH and RJM wrote the first draft. All authors read and approved the final manuscript. Funding Financial support for the meeting was provided through the Asia Pacific Malaria Elimination Network (APMEN) by the Bill and Melinda Gates Foundation and Australia's Department of Foreign Affairs and Trade (DFAT). This work was funded in part by the Wellcome Trust . For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. Availability of data and materials Data sharing not applicable as no datasets were generated or analysed in this meeting report. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interest. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. WHO Global technical strategy for malaria 2016-2030 2021 Geneva World Health Organization 2. WHO World Malaria Report 2021 2021 Geneva World Health Organization 3. Asia Pacific Leaders Malaria Alliance. What is APLMA? Accessed on 3 Feb 2022 4. Asia Pacific Malaria Elimination Network. APLMA & APMEN Partnership for Impact 2020. Accessed on 27 Apr 2022. 5. 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WHO Malaria surveillance, monitoring & evaluation: a reference manual 2018 Geneva World Health Organization 13. Louis ME Walke H Perry H Nsubuga P White ME Dowell S Lee LM Teutsch SM Thacker SB St Louis ME Surveillance in low-resource settings: challenges and opportunities in the current context of global health Principles & practice of public health surveillance 2010 3 Oxford Oxford University Press 357 380 14. Cohen JM Smith DL Cotter C Ward A Yamey G Sabot OJ Malaria resurgence: a systematic review and assessment of its causes Malar J 2012 11 122 10.1186/1475-2875-11-122 22531245 15. Roca-Feltrer A Stratil A-S Tibenderana JK Rodriguez-Morales AJ The role of adaptive surveillance as a core intervention to achieve malaria elimination Current topics and emerging issues in malaria elimination 2020 London IntechOpen 16. Malaria Policy Advisory Committee Meeting Overview of the malaria surveillance assessment toolkit. Meeting 3 december 2020 2020 Geneva World Health Organization 17. 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PMC10000343 | Air Qual Atmos Health Air Qual Atmos Health Air Quality, Atmosphere, & Health 1873-9318 1873-9326 Springer Netherlands Dordrecht 1336 10.1007/s11869-023-01336-x Article A new efficiency calibration methodology for different atmospheric filter geometries by using coaxial Ge detectors Barba-Lobo A. [email protected] Bolivar J. P. grid.18803.32 0000 0004 1769 8134 Radiation Physics and Environment Group (FRYMA), Department of Integrated Sciences, Center for Natural Resources, Health and Environment (RENSMA), University of Huelva, 21071 Huelva, Spain 10 3 2023 10 3 2023 2023 16 6 12071214 10 11 2022 28 2 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The study of the different pollutants present in atmospheric aerosols such as trace elements and radionuclides is essential to assess the air quality. To analyze the particulate matter (PM), atmospheric filters with different dimensions and geometries (rectangular, circular, slotted, and square filters) are usually employed. Regarding the pollutants existing in atmospheric aerosols, radionuclides are usually analyzed due to their multiple applications such as either in the environmental radiological control or as tracers of atmospheric processes. Therefore, this study aims to develop a new and general methodology to calibrate in efficiency coaxial Ge detectors to properly determine radionuclides present in the PM by gamma-ray spectrometry for several filter types. For this, granular certified reference materials (CRM) containing only natural radionuclides (238U-series, 232Th-series, and 40 K) were selected. Several granular solid CRMs were chosen allowing us to reproduce the same PM deposition geometry and to assure the homogeneity of the added CRMs. These are the main advantages in relation to the typical methods that use liquid CRMs. Furthermore, for filters whose surfaces are relatively large, they were cut in several pieces and placed one on top of the other, achieving the same geometry than the PM deposited onto the filter. Then, the experimental full-energy peak efficiencies (FEPEs) were obtained for each energy of interest (Eg) and they were fitted versus Eg, finding a general FEPE function for each filter type. Finally, this methodology was validated for both natural and artificial radionuclides (from 46 to 1332 keV) by using different filter types employed in proficiency test exercises, obtaining |zscore|< 2 for all cases. Supplementary Information The online version contains supplementary material available at 10.1007/s11869-023-01336-x. Keywords Atmospheric filters Particulate matter Atmospheric aerosols Efficiency calibration Gamma-ray spectrometry Ge detectors Consejeria de Conocimiento, Investigacion y Universidad, Junta de Andalucia P20_00096 FEDER-UHU-202020 Barba-Lobo A. Consejo de Seguridad Nuclear SUBV-4/2021 Ministerio de Ciencia, Innovacion y Universidades PID2020-116461RB-C21 Universidad de Huelva UHUPJ-00005-632 Universidad de HuelvaFunding for open access publishing: Universidad de Huelva/CBUA issue-copyright-statement(c) Springer Nature B.V. 2023 pmcIntroduction In the last decades, the research of the air quality and its health impacts are essential topics within the environmental and atmospheric sciences. For this, the particulate matter (PM) needs to be studied in depth since it can provide a very valuable information about the pollution levels present in the atmospheric aerosols. In addition, the assessment of the pollution associated to the atmospheric aerosols can be employed in order to get a better comprehension about the different factors involved in the global climate (Davidson et al. 2005; Fuzzi et al. 2015; Lu et al. 2016; Ouyang 2013), as well as about the evolution of certain diseases such as the ones caused by the SARS-CoV-2 virus (Mehmood et al. 2021a; Mehmood et al. 2021b; Paez-Osuna et al. 2022). The atmospheric PM is collected onto filters with different geometry and dimensions depending on the objective of the study, where the PM10, PM2.5, and PM1.0 are the most used samplers (Barba-Lobo et al. 2022; Duenas et al. 2009; Orduz 2012). Furthermore, there is another type of sampler, the cascade impactor (CI), that is very useful since it allows us to classify the particulate matter present in the atmospheric aerosols as a function of the aerodynamic diameter (ad) of the particles (Aba et al. 2020; Kwon et al. 2003). This sampler can provide us information about the affinity existing between the different pollutants present in the atmospheric aerosols and the size of the aerosol particles. In the cases of the PM10, the air flow needs to be fixed at 68 m3 h-1 following the USEPA Compendium Method IO-2.1 (EPA 1999), while for PM2.5 and PM1.0 samplers, the air flow is fixed at 30 m3 h-1 according to the European Standard UNE-EN 14,907 (EN 14,907, 2005). In order to be able to carry out samplings spending a sampling duration as short as possible, it is recommendable to make use of a very high-volume air aerosol sampler, model ASS-500 (Valkovic 2000). This sampler allows us to reach air flows ranged about 500 m3 h-1 and 600 m3 h-1. Furthermore, this last type of sampler is very recommendable to reduce the minimum detectable activity concentration (mda), since it is inversely proportional to the air flow, which makes possible to get mda values about 1 mBq m-3. Among the different types of pollutants present in atmospheric aerosols, radionuclides can be found. They can be employed for multiple purposes such as environmental radiological control, obtention of information about the origin of a certain contaminant source, calculation of the residence times of atmospheric aerosols and of the external and internal dose rates, and the trace of air masses and atmospheric processes (Abdo et al. 2021; Baskaran and Shaw 2001; Papastefanou and Bondietti 1991; Renoux 1987; Srinivas et al. 2014). For this, there are several radionuclides such as 7Be, 210Po, 214, 212, 210Pb, and 214, 212, 210Bi that are usually employed in the atmospheric studies (Dalaka et al. 2019; Papastefanou and Ioannidou 1996; Poet et al. 1972; Tokieda et al. 1996). These radionuclides can also allow us to find atmospheric deposition patterns for different regions of interest considering a wide variety of meteorological conditions (Baskaran and Swarzenski 2007; Lozano et al. 2011). Furthermore, in the case of the short-lived progenies of the 222Rn (radon) and 220Rn (thoron), that is, the 214Pb and 214Bi, and 212Pb and 212Bi, respectively, they are also useful to determine equilibrium factors (Barba-Lobo et al. 2023; Chalupnik et al. 2021) which are related to the internal dose rate. To determine the activity concentrations of radionuclides in the atmospheric aerosols, a calibration in efficiency of the selected detector is needed. For this, this study aims to develop a new and general methodology based on the use of granular solid CRMs for the efficiency calibration of coaxial Ge detectors, which are widely employed for the determination of gamma-ray emitters by using numerous atmospheric filter types. Materials and methods Materials In this study, several types of atmospheric filters were selected to develop the new methodology for the efficiency calibration, considering the great majority of the filter types employed by laboratories when analyzing the particulate matter. The filters selected in our case were quartz fiber filters characterized by having different geometries and dimensions: rectangular filters (20 x 25 cm2), circular filters (diameters = 47 mm, 150 mm), slotted filters (which are employed for the CI samplers, 13.6 x 14.3 cm2), and square polypropylene filters (44 x 44 cm2), which are used in the case of the very high-volume samplers, as the ASS-500 sampling station. Let us call these filters as R, C-47, C-150, SL, and SQ, respectively, to easily be identified. For the determination of the gamma-ray emitters, an extended energy range (XtRa) high purity germanium (HPGe) detector (model GX3519 provided by Canberra) was chosen. The XtRa detector has a relative efficiency of 38.4% at 1332 keV (60Co) in relation to a 3'' x 3'' NaI(Tl) detector, a full width at half maximum (FWHM) of 1.74 keV and 0.88 keV at 1332 keV and 122 keV, respectively, and a peak-to-Compton ratio of 67.5:1. The XtRa detector is connected to a conventional electronic chain, which is composed on a preamplifier, an amplifier, an analog-to-digital converter, and a multichannel analyzer, where the software employed for the acquisition and analysis of the gamma spectra was Genie 2000 (Canberra Industries 2004). In order to carry out the efficiency calibration of the XtRa detector, standards provided by the International Atomic Energy Agency (IAEA), RGU-1, RGTh-1, and RGK-1, were used, which are certified reference materials (CRM) and contain natural radionuclides belonging to the 238U-series, 232Th-series, and 40 K, whose certified activity concentrations were 4940(15) Bq kg-1, 3250(45) Bq kg-1, and 14,000(200) Bq kg-1, respectively, where the uncertainties are given at one sigma confidence level (IAEA 1987). For the validation of the methodology developed in this study, atmospheric filters selected to carry out the inter-comparison exercises in 2017 and 2021, which were organized by the CSN and CIEMAT, were employed, where the acronyms CSN and CIEMAT are referred to the Spanish Nuclear Safety Council ("Consejo de Seguridad Nuclear") and the Centre for Energy, Environment and Technology Research ("Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas"), respectively. Method To carry out the efficiency calibration of the detector by using the quartz fiber filters (R, C-47, C-150, and SL), some amount of RGU-1 was added and very well extended onto each filter type (see Fig. 1), achieving the homogeneity of this certified material throughout all the filter surfaces. In the case of the SL filters, the calibration was carried out using two filters, where 0.5115(2) g and 0.5014(2) g are the RGU-1 amounts added to each filter. In the case of the C-47 filters, three filters were used, where the added masses were 0.4953(2) g, 0.4941(2) g and 0.5009(2) g, respectively, while for C-150 filters, three filters were also chosen, where the added masses were 0.5029(2) g, 0.4898(2) g, and 0.5006(2) g, respectively. Then, for the R filters, three filters were used for the calibration, where the added masses were 0.6018(2) g, 0.5913(2) g, and 0.5914(2) g, respectively. In the case of the R filters, these filters were cut in several rectangular pieces which were placed one piece on top of the other, getting the same geometry than the one achieved when measuring this filter type (6.3 x 10 cm2) (see Fig. 1). Then, the RGU-1 standard is spread for each one of these pieces, covering the same regions than the ones where the particulate matter is deposited onto the R filters during the samplings. When proceeding in this way for the R filters, it is possible to make it easier to get the homogeneity of the RGU-1 standard when adding onto this filter type, as well as to get reproducing the distribution of the particulate matter when depositing onto the problem filters.Fig. 1 Scheme of the experimental procedure for the preparation of the different filter types (SL, C-150, C-47, R, and SQ filters) to carry out the efficiency calibrations In the case of the SQ filters, RGU-1, RGTh-1, and RGK-1 standards were selected for the efficiency calibration. The three standards were well mixed among them, and three filters were employed, where the amount of the added mixtures were 2.5011(2) g, 2.5017(2) g, and 2.4906(2) g, respectively, where the amount of each standard was one-third of the mass of each mixture added. Analogously to the case corresponding to the R filters, the SQ filters were also cut in pieces where each one had the same dimensions than the any problem filter ones after being folded to be measured (11 x 11 cm2) (see Fig. 1). Furthermore, the mixture of the three standards was spiked to each piece, covering the same regions than the ones covered when depositing the particulate matter onto the problem filters. By using this methodology developed in this study, a more proper efficiency calibration is achieved in comparison with the typically used methods, where certified liquid samples are added to the filters by using a pipette (Idoeta et al. 2021; Lopez-Lopez et al. 2020; Tourang et al. 2021). The usage of certified liquid samples makes it easier the existence of inhomogeneities, and it is more likely that the concentrations of the radionuclides present in these standards can be altered since they are dissolutions. Moreover, since the particulate matter is a solid sample, it is more recommendable to calibrate in efficiency by using solid samples than liquid ones. This allows us to reproduce the same distribution of the particulate matter when depositing onto the filters, as well as to obtain similar self-absorption effects for the emitted photons in the cases of the calibration and problem filters. In the case of the bigger filters (R and SQ filters), these filters were cut in several pieces following the same geometry and dimensions than the ones obtained when measuring the problem filters. This is another reason why this methodology is more proper than the typical methods which employ the calibration filters without cutting them (Idoeta et al. 2021; Lopez-Lopez et al. 2020; Tourang et al. 2021). This makes it more difficult to achieve the homogeneity of the spiked standard, not reproducing the distribution of the particulate matter deposited onto the problem filters in a proper way. To determine natural and artificial radionuclides by gamma-ray spectrometry, nowadays, the detector calibrations by Monte Carlo simulations have become generalized, even in the case of using atmospheric filters (Aba et al. 2020). There are many cases for which detectors are not characterized because of being relatively old. To proceed with it, high costs for the characterization and the new Monte Carlo software are involved. During the characterization procedure, the detectors must be outside the laboratory, and consequently, inoperative for several months. In contrast to Monte Carlo simulations, in this study, an experimental methodology has been developed by which it is possible to calibrate coaxial detectors relatively quickly for atmospheric filters using calibration standards, which do not imply so high costs. Therefore, this is the first study to address in depth the experimental calibration of coaxial Ge detectors for atmospheric filters by using granular solid CRMs, developing an exhaustive calibration filter preparation method to reproduce the particulate matter deposition geometry with a high accuracy. To carry out these calibrations, the experimental FEPEs, eexp, were calculated by using the following equation:1 eexpEg=G-B-F-IPgacmct=NPgacmct where G, B, F, I, and N are the total number (gross) of counts, the Compton continuum, the background due to environmental conditions existing in the laboratory, the interference term, and the net counts, respectively, where all of them are referred to the full-energy peak of interest. Then, Pg is the probability of gamma emission (taken from DDEP 2017); ac and mc are the activity concentration and the mass added to each filter of the calibration standard, respectively, which have been used in the calibration procedure. Then, Eg are the selected gamma emission energies and t is the measurement time. Furthermore, it has been considered that I ~ 0 for all selected Eg. After the counting of the filters by using the XtRa detector, the experimental efficiencies were calculated for each filter type. For this, the full-energy peak efficiency (FEPE) was calculated for each selected gamma emission energy (Eg). Afterwards, an average FEPE value was calculated for each energy in the case of each sampler type. Finally, the logarithms of the experimental FEPEs were fitted versus ln(Eg/E0), where E0 = 1 keV, achieving to obtain a general efficiency function for each filter type. Results and discussion Calibration in efficiency for each filter type In Tables S.1, S.3, S.5, S.7, and S.9 (see Supplementary Material), the eexpi(j) values obtained in the cases of the SL, C-150, C-47, R, and SQ filters were shown, respectively, for each filter chosen to accomplish the calibrations in efficiency, where i = SL, C-150, C-47, R, and SQ, and j = 1, 2, and 3 is the number of the filter used for each type of geometry. Furthermore, in Tables S.1, S.3, S.5, S.7, and S.9, the average experimental efficiencies, eexpi, have been provided for each filter type. The average of the full energy peak efficiency, eexpi, was plotted versus Eg for each filter type by using logarithmic scales for both axes of the graph (Fig. 2). As can be seen in this figure, the behavior of eexpi versus Eg, by using logarithmic scales for both variables, is clearly polynomial type. Consequently, the following function was chosen in order to fit ln(eexpi) versus ln(Eg/E0) (Bolivar et al. 1996; El-Daoushy and Garcia-Tenorio 1995; Gilmore and Hemingway 1995; Martinez-Ruiz et al. 2007):2 lneexpiEg=k=03akilnEgE0k where aki are the parameters resulting from the fits, k = 0, 1, 2, and 3, and I = SL, C-150, C-47, R, and SQ. Then, Eg is the gamma emission energy of interest and E0 = 1 keV. It is necessary to clarify that the Eg, which were selected to carry out the calibrations (see Tables S.1, S.3, S.5, S.7 and S.9), were chosen because of having the highest Pg values corresponding to the radionuclides belonging to the 238U-series, 232Th-series, and 40 K, achieving to obtain high counting rates and, therefore, to accomplish these calibrations relatively quickly.Fig. 2 Experimental efficiencies resulting from the efficiency calibration carried out for five types of filters: slotted filters (SL), circular filers whose diameters are 47 mm and 150 mm (C-47 and C-150, respectively), rectangular filters (R), and squared filters (SQ). Besides, the fittings accomplished for the experimental efficiencies, eexpi, versus the gamma emission energy, Eg, where i = SL, C-150, C-47, R, and SQ, have also been shown Moreover, note that the highest FEPEs were obtained for the C-47 filter. This is consistent since this filter type has a diameter close to the XtRa detector one (58.5 mm), which minimizes the number of photons not detected. On the contrary, for the SQ filter, its size is much larger than the detector window, which causes a significant increase of non-detected photons and, therefore, a decrease of the FEPEs. In the case of the SL, C-150, and R filters, it is possible to observe that the FEPEs were similar from each other which is due to the similar size of the filters after being folded. In Tables S.2, S.4, S.6, S.8, and S.10 (see Supplementary Material), the aki parameters can be found for the SL, C-150, C-47, R, and SQ filters, respectively. Furthermore, in Tables S.1, S.3, S.5, S.7, and S.9, the relative residuals, Res (%), resulting from the fits provided by Eq. 2 can be found for each selected energy in the cases of SL, C-150, C-47, R, and SQ filters, respectively, where the Res values were calculated by using the following equation:3 Res(%)=100yfitEgyexpEg-1 where yexpi and yfiti are the values obtained experimentally and the ones obtained by a fitting function for a magnitude y, respectively, for each energy Eg. As can be seen in Fig. 3, all |Res| values were less than 9.2, but it is easy to realize that the great majority of the |Res| values were less than 3 and, consequently, the fits provided by Eq. 2 agreed very well with the eexpi values for the five filter types (see Tables S.1, S.3, S.5, S.7, and S.9 in order to check numerically the values obtained for Res). Furthermore, in Tables S.2, S.4, S.6, S.8, and S.10, it is possible to find the R2 values resulting from each fitting, where R2 were 0.9995, 0.9993, 0.998, 0.9991, and 0.998 in the cases of the SL, C-150, C-47, R, and SQ filters, respectively, which further corroborate the great fits provided by Eq. 2.Fig. 3 Relative residuals, Res (%), resulting from fitting the experimental FEPEs versus the gamma emission energy, Eg, by using the general efficiency function found for each filter type (SL, C-150, C-47, R, and SQ) In addition, note that the Res values obtained at each energy for each filter type were well distributed between the positive and negative panels. This allows us to prove that the Res values do not follow any systematic tendency. Validation of the efficiency calibration methodology In this section, the validations of the methodology developed in this study are shown. For this, filters of the C-47, R, and SQ types were employed, which were selected for the Inter-comparison exercises organized by the CSN and CIEMAT in 2017 and 2021. It is necessary to clarify that the filters of the C-150 and SL types are unusually employed in the inter-comparison exercises, and for this reason, they were not included in this section. However, they have also been included in this study due to the great importance that these filter types have for a proper and complete analysis of the particulate matter present in atmospheric aerosols. Furthermore, considering the very low values obtained for Res in the case of the C-150 and SL filters when comparing the resulting experimental FEPEs for each filter type replica, it is possible to test the very good interval validation achieved at each selected Eg. In order to proceed with these validations, it was necessary to make use of the zscore, which can be obtained by the following equation:4 zscore=ai-med(ai)smedai where ai is the activity concentration value obtained for each radionuclide by using this methodology, med(ai) is the median value of the activity concentration for each radionuclide resulting from considering the values provided by all the laboratories that participate in the Inter-comparison exercise, and smedai is the absolute deviation of the med(ai). In Tables 1, 2 and 3, the validations carried out by using the filters C-47, R, and SQ, respectively, were shown, where both natural and artificial radionuclides (214, 210Pb, 214Bi and 226Ra, and 54Mn, 60, 57Co, 65Zn, 137, 134Cs and 241Am, respectively) were selected in order to achieve more complete validations.Table 1 Validation of the efficiency calibration carried out for the circular filters whose diameter is 47 mm (C-47). For this, a filter employed in an inter-comparison exercise organized by the CSN and the CIEMAT in 2017 was selected RN Eg(keV) a (Bq filter-1) meda(Bq filter-1) zscore 226Ra 185.96 0.88 (8) 0.50 (10) 2.0 214Pb 351.93 0.47 (2) 0.50 (4) - 0.3 214Bi 609.31 0.49 (4) 0.48 (5) 0.1 210Pb 46.54 1.70 (4) 1.77 (15) - 0.2 54Mn 834.84 1.06 (2) 1.10 (12) - 0.3 57Co 122.10 0.388 (8) 0.39 (4) 0.0 60Co 1332.50 0.720 (15) 0.72 (3) 0.0 134Cs 604.70 0.60 (8) 0.62 (4) - 0.2 137Cs 661.80 0.469 (9) 0.43 (3) 0.6 241Am 59.54 0.207 (6) 0.210 (15) - 0.1 Table 2 Validation of the efficiency calibration carried out for the rectangular filters (R). For this, a filter employed in an inter-comparison exercise organized by the CSN and the CIEMAT in 2017 was selected RN Eg(keV) a (Bq filter-1) meda(Bq filter-1) zscore 226Ra 185.96 1.2 (2) 1.00 (2) 0.5 54Mn 834.84 1.15 (12) 0.801 (13) 1.5 60Co 1332.50 0.85 (9) 0.704 (12) 0.9 134Cs 604.70 0.75 (8) 0.620 (13) 0.9 137Cs 661.80 0.60 (7) 0.484 (9) 0.9 Table 3 Validation of the efficiency calibration carried out for the squared filters (SQ). For this, a filter employed in an inter-comparison exercise organized by the CSN and the CIEMAT in 2021 was selected RN Eg(keV) a (Bq filter-1) meda(Bq filter-1) zscore 226Ra 185.96 1.7 (2) 2.00 (8) - 1.1 54Mn 834.84 1.06 (2) 1.00 (4) 0.4 57Co 122.10 0.173 (15) 0.203 (8) - 1.0 60Co 1332.50 1.94 (3) 2.06 (8) - 0.4 65Zn 1115.55 1.95 (13) 1.84 (8) 0.4 134Cs 801.93 0.33 (3) 0.350 (14) 0.4 137Cs 661.80 0.433 (15) 0.412 (17) 0.3 241Am 59.54 0.264 (11) 0.352 (15) - 1.3 As can be seen in Tables 1, 2, and 3, the |zscore| values obtained for each chosen artificial and natural radionuclide agreed well with the median obtained in the proficiency tests, accomplishing that all of them were less than 2. This clearly demonstrates the very good validation of the methodology proposed in this study, for both artificial and natural radionuclides as well as for both low and high energies (<= 150 keV and > 150 keV, respectively). Furthermore, making use of this satisfactory validation, it is also possible to conclude that the homogeneity accomplished during the preparation of the calibration filters was very proper. This allows us to consider it as a very recommendable methodology for the efficiency calibration of coaxial Ge detectors by using a very wide variety of filter types. Furthermore, this methodology can be applied in a very proper way for the determination of natural and artificial radionuclides whose gamma emission energies are distributed throughout all the energy range of interest (from 46 to 1332 keV). Conclusions In this study, an original methodology has been developed for the full-energy peak efficiency (FEPE) calibration of coaxial Ge detectors by using a great variety of atmospheric filters. These filters are characterized by having different geometries and dimensions (rectangular, circular, square, and slotted filters), which are usually used when carrying out research related to the particulate matter (PM) present in atmospheric aerosols. To prepare the calibration samples (filters), granular certified reference materials were selected, and they were well spread throughout the same regions than the ones covered by the PM when depositing onto the problem filters. This allows us to achieve a very high homogeneity of the calibration standard material added, reproducing the same distribution than the one followed by the PM onto the filters. Furthermore, because of the significant dimensions in the cases of the rectangular and square filters, it was necessary to cut them in several pieces which were placed one piece on top of the other. This was carried out following the same geometry and dimensions than the ones obtained when measuring the problem filters, where the calibration standards were spiked onto each one of these pieces. This makes it easier to achieve the homogeneity of the certified material spread and to reproduce the PM distribution onto the filter surface for filters whose surfaces are relatively large. After preparing the calibration filter, the different filter types were counted by gamma-ray spectrometry, obtaining the experimental FEPEs for each filter and each selected energy. Afterwards, the experimental FEPEs were fitted by using a polynomial function, allowing us to find a general FEPE function for each filter type covering a very wide gamma emission energy range (from 46 to 1765 keV). The relative average residual and R2 values resulting from these fits were very good, which were 1.6%, 3.4%, 3.2%, 2.1%, and 2.5%, and 0.9995, 0.9993, 0.998, 0.9991, and 0.998, respectively, for the SL, C-150, C-47, R, and SQ filters, respectively. This proves the good agreement between the experimental FEPEs and the values provided by the semiempirical general function found for the FEPE. Finally, the methodology developed in this study was subjected to several validation tests by using filters employed in inter-comparison exercises. A very good validation was achieved for both natural and artificial radionuclides whose gamma emission energies are well distributed throughout the energy range of interest, obtaining |zscore| values less than 2 for all cases. This allows us to conclude that this methodology is very recommendable in order to determine natural and artificial radionuclides, that are present in atmospheric aerosols, for a very wide energy range and variety of filter types. Supplementary Information Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 49 KB) Author contribution A. Barba-Lobo: conceptualization, data curation, formal analysis, investigation, methodology, validation, writing -- original draft, writing -- review and editing. J. P. Bolivar: conceptualization, data curation, formal analysis, investigation, methodology, supervision, validation, writing -- original draft, writing -- review and editing. Funding Funding for open access publishing: Universidad de Huelva/CBUA This research has partially funded by the projects of the Regional Government of Andalusia called "Treatment of acid leachates from phosphogypsum piles located at Huelva, and transport modelling of the released radionuclides" (Ref.: P20_00096) and "Valorization of inorganic wastes enriched in natural radioactivity for sustainable building materials" (Ref.: FEDER-UHU-202020); the project funded by the Spanish Nuclear Safety Council (CSN) "Radon exhalation from building materials; radiological impact and corrective measures" (Ref.: SUBV-4/2021); the project funded by the Spanish Ministry of Science, Innovation and Universities' Research Agency "Development and optimization of a process for removing natural radionuclides in phosphogypsum leachates" (Ref.: PID2020-116461RB-C21); and the Project for Novel Principal Investigators "Quantitative study of the variables involved in the radon exhalation rate for granular solids; application to rafts of granular solid phosphogypsum" (Ref.: UHUPJ-00005-632). Data availability All data and materials as well as software application or custom code support their published claims and comply with field standards. Declarations Ethics approval This study does not involve animal or human subjects. Consent to participate All authors agreed with the content, and all gave explicit consent to submit, and they obtained consent from the responsible authorities at the institute/organization where the work has been carried out, before the work is submitted. Consent for publication The authors have no financial or proprietary interests in any material discussed in this article. Competing interests The authors declare no competing interests. Highlights * A new method for Ge detector efficiency calibration by atmospheric filters was developed. * Granular solid certified reference materials to reproduce the same particulate matter deposition geometry were used. * The larger calibration filters were cut to reproduce the same geometry and dimensions of the problem filters. * A general full-energy peak efficiency function was found for each filter type. * The efficiency curves were validated by participating in proficiency test exercises. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 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PMC10000345 | Humanit Soc Sci Commun Humanit Soc Sci Commun Humanities & Social Sciences Communications 2662-9992 Palgrave Macmillan UK London 1552 10.1057/s41599-023-01552-x Article The moderating role of information technology governance in the relationship between board characteristics and continuity management during the Covid-19 pandemic in an emerging economy Almaqtari Faozi A. 1 Farhan Najib H. S. [email protected] 2 Al-Hattami Hamood Mohammed [email protected] 3 Elsheikh Tamer 14 1 grid.412255.5 0000 0000 9284 9319 Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, Kuala Nerus Terengganu, 21030 Malaysia 2 grid.443343.7 0000 0004 1800 4181 Faculty of business studies, Arab Open University, Riyadh, Saudi Arabia 3 grid.444907.a Department of Accounting, Faculty of Commerce and Economic, Hodeidah University, Al Hudaydah, Yemen 4 grid.411978.2 0000 0004 0578 3577 Faculty of Commerce, Kafrelsheikh University, Kafr El Sheikh, Egypt 10 3 2023 10 3 2023 2023 10 1 9615 8 2022 31 1 2023 (c) The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit The main aim of the current study is to investigate the relationship between governance characteristics, information technology governance, and continuity management during Covid-19 in an emerging economy. The study also examines the moderating role of information technology governance in the relationship between governance characteristics and business continuity management. The quantitative approach is used by utilising a survey questionnaire. A sample of 232 questionnaire surveys has been collected from the board of directors, top and middle management executives, external auditors, information technology experts, and some other respondents. The results were estimated using structural equation modelling. The results indicate that information technology governance has a statistically significant effect on business continuity. Board size, board independence, audit committee independence, audit committee diligence, and external audit have a statistically significant positive effect on information technology governance. Further, the results indicate that information technology governance significantly moderates the effect of board size, board independence, board diligence, audit committee independence, audit committee diligence, and external audit on business continuity. However, information technology governance does not moderate the relationship between board committees and business continuity, which indicates less board involvement in information technology governance. The current research provides insight into the role of information technology governance in business continuity management during crises. The present study provides a unique contribution as it investigates the relationship between corporate governance characteristics, information technology governance, and business continuity management during Covid-19, providing empirical evidence from an emerging country. Subject terms Library science Business and management Finance issue-copyright-statement(c) The Author(s) 2023 pmcIntroduction The coronavirus pandemic has caused a substitutional business disruption. Some firms may be forced to close permanently due to this disruption (Kaushik & Guleria, 2020). The pandemic created new challenges for global consumers, leading to the use of digital technology (Al Halbusi et al., 2022; Cifuentes-Faura, 2020). It also impacted psychological health and quality of life (Aqeel et al., 2022; Farzadfar et al., 2022; NeJhaddadgar et al., 2022; Yu et al., 2022; Zhou et al., 2022; Su et al., 2022; Hossain et al., 2020; Dong et al., 2021; Nueangnong et al., 2020). The Covid-19 pandemic triggered an economic crisis and a public health emergency, jeopardising energy efficiency consumption, long-term food diversity, and household nutrition security (Zhuang et al., 2022; Zafar et al., 2022; Jiakui et al., 2023; Hossain et al., 2020; Cifuentes-Faura, 2021b). It has consistently influenced environmental behaviour by reducing income and disrupting economies (Geng et al., 2022). Most business operations across industries and sectors, including manufacturing, services, global supply chains, commercials, travelling, hospitality, cargo traffic, tourism, and education, have either halted or slowed dramatically and significantly (Barua, 2020). Further, as the Covid-19 pandemic spreads, and it is unlikely to unfold, some firms will need years to recover (Kaushik & Guleria, 2020). This increases the business risk and affects business continuity (BC), which is becoming increasingly fragile (Zsidisin et al., 2005). Business continuity management (BCM) seeks to identify these risks to plan for, avoid, or limit them and keep business operations and services running smoothly (Gibb & Buchanan, 2006). Herbane et al. (2004) indicate that BCM is a socio-technical strategy focusing on anticipating potential continuity issues for retaining the organisation's value. Information technology (IT) is one of the most crucial aspects of BCM. Business enterprises increasingly rely on technology and their ability to integrate IT resources effectively with other organisational and administrative tasks (Lindstrom et al., 2010; Li et al., 2022). In Jordan, a survey has been conducted by Kebede et al. (2021), comprising 2039 enterprises from different geographical regions and industries. The survey found that most businesses reported decreasing demand for their products and services, resulting in revenue declines and financial challenges. Mandatory closures harmed half of the surveyed businesses, and closed marketplaces impacted more than a third. Despite government efforts to reduce layoffs and unemployment, one-third of the businesses attributed their layoffs to Covid-19. The tourism industry had the highest percentage of layoffs (48%), followed by construction (45%) and manufacturing (34%). Rent (61%), wages, social security payments (51%), and invoice payments (30%) were the most significant financial burdens on enterprises throughout the pandemic. With regard to the most significant economic impact, eight out of ten businesses reported lower sales, followed by a lack of capital and liquidity issues (six out of ten). Almost half of the respondents said they had lost money. One-quarter of the businesses surveyed had bank loans, and more than one-third had either supplier credit or informal credit from family or friends. One out of every five businesses confirmed that their debt increased. Large and medium-sized businesses, notably those in the manufacturing and construction industries, had the highest debt-to-bank ratio. Several studies have been conducted to assess various recent issues (Abbas et al., 2019; Azadi et al., 2021; Yao et al., 2022; Yu et al., 2022; Zhou et al., 2022; Li et al., 2022; Zafar et al., 2022). However, these studies did not investigate the effect of IT governance on business continuity. According to Wan and Chan (2008), the BCM approach should include both business and technological elements. The technological component of the BCM improves the firm's capability to sustain the minimum work requirements in case of a business interruption. Several studies (e.g., Pathak et al., 2020; Al-Hattami et al., 2022; Al-Hattami & Kabra, 2022; Dwivedi et al., 2020; Su et al., 2022) have stressed the importance of IT strategies in achieving corporate success, particularly during pandemics. As a result, to deal with the pandemic, most enterprises were forced to adjust their policies through digitalisation and remote working (Carroll & Conboy, 2020). Some businesses have begun to operate via the 'Work from Home' mode, utilising disruptive technology to deal with the economic disruption that happened because of Covid-19 (Kaushik & Guleria, 2020; Dwivedi et al., 2020). Zhang et al. (2016) indicate that, based on strategic choice theory, IT governance is significantly influenced by corporate governance characteristics (CGC), including board involvement, which is reflected by board knowledge of IT (Jewer, McKay, 2012). In the same context, Zhang et al. (2016) indicate that board involvement in IT is more likely to be evaluated by external auditors and audit committees. The ability of businesses to combine IT and other corporate resources must be improved, especially when the board is made up primarily of independent directors who are probably to develop a more resilient IT competence. Therefore, the current research proposes that corporate governance characteristics alone are insufficient to combat the business disruptions caused by Covid-19. IT governance is needed to maintain BC and avoid business disruptions caused by Covid-19. Based on this background, two central questions form the main focus of the present study: (1) To what extent did CGC influence BC during the Covid-19 pandemic? (2) Did IT governance moderate the effect of CGC on BC during the Covid-19 pandemic? Accordingly, the current study is motivated by the Covid-19 pandemic's consequences, due to which all businesses and enterprises were negatively impacted and business operations were interrupted. Therefore, we assume that corporate governance attributes alone are not efficient enough to run business operations smoothly during the crisis. Hence, IT governance can play an effective role in enhancing business efficiency and avoiding business interruptions during crises, contributing to an efficient, holistic, and strategic BC process. Therefore, this study contributes to the strand literature on CGC, IT governance, and BCM in several ways. First, it provides empirical evidence from an emerging country on the relationship between CGC, IT governance, and BCM. Second, it assesses the mediating role of IT governance in the relationship between CGC and BCM. We propose that during the Covid-19 crisis, corporate governance mechanisms alone are efficient in managing business interruptions and continuities. Third, there is a serious gap in the strand literature on these issues. Very few studies and limited research have been conducted on IT governance and BCM (e.g., Wan & Chan, 2008, crisis management (e.g., Sahebjamnia et al., 2015), and IT governance (e.g., Jarvelainen, 2013; Zhang et al., 2016). However, there is a scarcity of studies investigating this issue in the context of the Covid-19 pandemic. Hence, the current research makes a novel contribution to the state-of-the-art and bridges the gap in prior studies. To the researchers' knowledge, this is the first study that investigates the role of IT governors in the relationship between corporate governance attributes and BCM. Finally, as a methodological contribution, the present research assesses the perceptions of the board of directors, executives, and other respondents from different sectors during the crisis, providing valuable insights into how businesses managed their business disruptions during Covid-19. The respondents' responses have been estimated using structural equation modelling, which has high statistical power for providing clear and meaningful findings that can establish a holistic approach and framework to help businesses avoid disruptions. Accordingly, the present study is beneficial and significant for business organisations' board members, policymakers, IT specialists, and academicians. It offers valuable insights into the influence of IT governance during the crisis and how corporate governance mechanisms can be complemented by IT governance to avoid business disruptions and maintain BC. The next section discusses the background and hypotheses development; section "Methods" outlines the research method; section "Results" is devoted to the empirical results; section "Discussion and implications" provides discussions, implications, and research limitations. Background and hypotheses development Covid-19 background Covid-19, with its various variants, continues to worry the world. The story is that, by the end of 2019, an unwanted guest turned the world upside down. It began precisely in December 2019 when the Chinese government notified the World Health Organization (WHO) about the spread of an unknown disease in Wuhan (Nueangnong et al., 2020; Cifuentes-Faura, 2020; Cifuentes-Faura, 2021a). The disease spread unexpectedly fast worldwide and became a pandemic (Nueangnong et al., 2020). Covid-19 has resulted in a significant short-term economic downturn, the closure of many businesses, the unemployment of tens of millions of people, and other repercussions on commercial activities. Covid-19 is a pandemic wreaking havoc on the global economy and causing massive disruptions to lives and livelihoods. According to many assessments, it is the worst worldwide disaster since World War 2 (Engidaw, 2022; Nueangnong et al., 2020). The disease created significant and massive business and service downtime (Kaushik & Guleria, 2020; Buheji, 2020). To mitigate the spread of the disease, most countries used various regulations, including travel bans, security measures, and social distancing (Fabeil et al., 2020; Nueangnong et al., 2020). As observed by Barua (2020), Covid-19 presented a dramatic impact on international business and threatened the widespread economic well-being of entire countries to the point where delocalisation is imminent. This includes multiple industries from various sectors, such as distribution networks, transportation and cargo flow, production, commercial operations, academic learning, and tourism. The viral outbreak has brought about catastrophic destruction and company closures. Getting past these challenges will not ensure a prosperous or even a long-term positive future outlook (Donthu & Gustafsson, 2020). This forced scientists and researchers to find a way out of this crisis (Alshebami & Rengarajan, 2020). In light of this, the use of technology, like the Internet, and food and environmental security has been found beneficial to curbing the pandemic (see Al-Hattami, 2021; Cifuentes-Faura, 2020; Su et al., 2022; Jiakui et al., 2023; Zafar et al., 2022; Zhuang et al., 2022; Li et al., 2022; Liu et al., 2022). Research background and hypotheses development Several prior studies have examined BC from various aspects (e.g., Cerullo & Cerullo, 2004; Zsidisin et al., 2005). Further, some studies have been conducted on crisis management (e.g., Torabi et al., 2016; Hazaa et al., 2021; Sahebjamnia et al., 2015; Tosh et al., 2014; Liu et al., 2022). The context of these studies is narrow and limited to some crises other than Covid-19, which has caused massive effects. Furthermore, various studies have examined CGC (e.g., Hashed & Almaqtari, 2020; Youssef & Diab, 2021; Almaqtari & Hashed, et al., 2020; Farhan et al., 2020; Almaqtari & Shamim et al., 2020; Almaqtari & Al-Hattami et al., 2020; Al Maqtari & Farhan et al., 2020). However, no study has linked IT governance, BC, and CGC. While some studies focused on IT in the context of BC (e.g., Gomez et al., 2017; Haouam, 2020; Wahab & Arief, 2015; Jarvelainen, 2013), they focused more on information technology than IT governance. Similarly, very few studies have investigated IT governance (e.g., Hamdan et al., 2018); however, they paid more attention to financial issues. In addition, despite some studies on governance characteristics, BC, and IT governance, these studies did not investigate the relationship between them in the context of Covid-19. Accordingly, there is a dearth of studies in the strand literature on the relationship between IT governance and BC during Covid-19. Board characteristics and business continuity management Gibb and Buchanan (2006) indicated a relationship between BCM and information management; both focused on uncertainty. Bunjongmanomai et al. (2020) investigated the relationship between corporate governance and BC during Covid-19. They report that BCM is considered a vital element of corporate governance that functions to control disruptive incidents. Similarly, Tosh et al. (2014) provided evidence of the relationship between hospitals' ITG and BCP during Covid-19. They revealed that IT readiness is essential for connection and operations. They also contended that information technology improves hospital preparation, business operations, and the health system as a whole. As a result, a thorough BCP describing IT systems and infrastructures should be prepared. IT preparedness is critical for hospitals and health systems to maintain their operations networks, operate health and administrative information systems, and have sufficient capacity to restore and support health and administrative operations (Tosh et al., 2014). Numerous recent studies have investigated BCM in various contexts (Aragao & Fontana, 2022; Ewertowski, 2022; Ino and Watanabe, 2022; Kaur et al., 2022; Kosieradzka et al., 2022; Le and Nguyen, 2022; Robertson et al., 2022; Singh and Jain, 2022). The researchers agree that BC is critical for business organisations during disruptive incidents. Lindstrom et al. (2010) indicated that IT and information security are essential elements of BCP. Tammineedi (2010) stated that a dedicated BCM team is necessary in the case of business disruption to enable the efficient continuation of business activities. Experts in business risks, IT, and organisational activities should be included in the team. Moreover, critical business functions should collaborate with their IT application support teams to develop a comprehensive and consistent BCP. The BCM group has to be organised in a hierarchical framework. The group should consist of individuals with relevant expertise and credentials to address pandemic-related constraints. Several experiences have been provided by different studies on BCM during crises. For example, Goromaru et al. (2021) reported that Covid-19 has severely influenced many enterprises. Hence, any enterprise should establish BCP. The pandemic left consequences that will continue over the coming years. Consequently, experiences from this pandemic should be learned to avoid the negative effects and apply these lessons to future BCP. BCP is recommended during a pandemic to increase elasticity in the face of uncertain future hazards. In another context, Meechang et al. (2021) indicated that flood disasters in Thailand prompted the adoption of BC management, prompting enterprises to consider their long-term viability and sustainability. The threat of business disruption grows as firms become more reliant on IT infrastructure. The BCP strategy seeks to mitigate the impact of any major business system failures (Cerullo and Cerullo, 2004). Ostadi et al. (2021) reveal that BCM is a complete strategy for identifying risks and mitigating their effects on an organisation's operations. Product recovery and resource allocation following disruptive incidents are essential components of BCM. Organisations should prioritise resource allocation for restarting activities, minimising expenses, and returning operations to a tolerable level, so that disruptive incidents do not impede important activities. Therefore, the following hypothesis has been framed:H01. There is no significant impact of CGC on BCM during the Covid-19 pandemic. Corporate governance characteristics and IT governance ITG exists at the three hierarchical levels of an organisation involving the board and senior executives. The board of directors and the top management develop an IT strategy that will be implemented at the level of operations, including IT management in a practical sense (Haes & Grembergen, 2009). Institute (2003) indicates that developing an IT project charter is the duty of the board of corporate directors and top management. Gomez et al. (2017) argue that one of the board's responsibilities is to anticipate and monitor IT deployment strategies to increase business value by providing faster resolutions and higher-quality product delivery. They also show that ITG is flawed and externalised if there is no effective board involvement and if the board believes that ITG is not a major aspect of corporate governance. Haes and Grembergen (2005) highlight that ITG exists at several heretical levels within an organisation. It is situated at the strategic, management, and operational levels. These levels respectively represent the board of directors, C-suite, senior management, operational IT, and business management, where they involve, develop, and implement ITG strategy. According to Moeller (2013), developing high-level courses of action and conducting a comprehensive examination of overall corporate behaviour in light of ITG are the board's and audit committee's primary roles for setting the tone at the top. Risk mitigation, disclosure, and accountability all fall under information security (IS). Posthumus and Solms (2004) argue that the senior executive and the board of directors have a corporate management responsibility to deal with (IS). Hamdan et al. (2018) suggested a paradigm for interlocking boards and ITG in Jordan. According to the findings, ITG is a critical practice in the development and structuring of the board, i.e., it is important to connect the board of directors with competent managers with practical expertise in information systems. In another context, according to Lunardi et al. (2014) paper, there are indicators that ITG policies can help firms manage and utilise technology compared to those who do not employ them. Consequently, the subsequent hypothesis has been formulated:H02. There is no significant impact of CGC on ITG during the Covid-19 pandemic. Corporate governance characteristics, IT governance, and business continuity Covid-19 has put forward unique challenges in different aspects of life (Aqeel et al., 2021; Maqsood et al., 2021; Rahmat et al., 2018; Zhou et al., 2022). Since the break out of the deadly virus, Covid-19 spreads fear among people at the social level. Therefore, it is critical to implement appropriate mental and physical health prevention measures, particularly in less developed countries. Accordingly, social media could play a significant role in this regard (Abbas et al., 2019; Yu et al., 2022). People who were quarantined due to the spread of the disease could meet online (Yu et al., 2022). This is not limited to communication needs but also educational needs (Azadi et al., 2021; Maqsood et al., 2021; Rahmat et al., 2018; Yao et al., 2022). Moreover, business activities (Aqeel et al., 2021; Yu et al., 2022; Zhou et al., 2022) and the overall smoothness of life have raised the importance of technology to satisfy these needs. A number of prior studies have assessed CGC throughout the viral pestilence (Covid19) (Elmarzouky et al., 2021; Jebran, Chen (2020); Koutoupis et al., 2021; Li et al., 2021; Xuguang et al., 2021; Zattoni and Pugliese, 2021). However, these studies did not investigate the relationship between CGC and ITG, especially during the pandemic. Several studies also focused on the importance of IT management in governance frameworks. For example, Korac-Kakabadse and Kakabadse (2001) indicated that ITG is a significant component of governance characteristics that aims to establish associations and alignment among business processes. ITG is thus a significant element of an organisations' corporate governance model because it introduces critical strategic plan measures that focus on IT strategy alignment. As ITG is initiated by corporate governance, the relationship between the two becomes clear (Dittmeier, 2011). One of the most commonly used frameworks of ITG is the "Control Objectives for Information and Related Technology" (COBIT) framework (Simonsson et al., 2010; Lunardi et al., 2014). The COBIT framework considers the executive board, the chief executive director, and a few other elements as essential intra-stakeholders. Further, it emphasises the necessity of ITG and the effect of a dynamic and autonomous board of directors as a crucial aspect of the Committee of Sponsoring Organizations (COSCO) control environment (Moeller, 2013). The board of directors' size, insiders' ratio, and board members' experience in IT significantly influence the extent of the board's involvement in IT governance (Jewer & McKay, 2012). Nevertheless, Huff et al. (2006), Bart and Turel (2010), and Andriole (2009) indicate that boardrooms have less expertise in IT governance in most cases. According to Peterson (2004), IT governance has to comprise an IT organisation structure, a 'Chief Information Officer, an IT strategy committee, and an IT steering committee.' Haes and Grembergen (2009) note that the IT governance structure should include an IT strategy committee at the board level to guarantee that IT is a regular agenda item for the board of directors. Furthermore, to assess the value and risk of IT, the board of directors would need to include IT expertise and experience, as well as an independent IT audit committee. The promotion, direction, and management of IT governance procedures are within the purview of the IT governance officer. At the executive or senior management level, the IT 'steering committee' should be accessible to determine the business priorities for IT investments. Importantly, Haes and Grembergen (2005) examined IT governance through interviews and reports. They claim that consultants, rather than board members, steer IT governance issues. As a result, the following hypothesis has been proposed:H03. There is no significant moderation effect of ITG on the relationship between CGC and BCM during the Covid-19 pandemic. Methods Research framework Figure 1 illustrates the research framework. Fig. 1 Research framework. The research framework comprises three main variables: CGC, BCM, and ITG. CGCs are considered independent variables measured by board size, board independence, board diligence, audit committee independence, audit committee diligence, board committees, and external audit. BCM is treated as the independent variable, and ITG is a moderating variable. Data and sample The current study's target research population includes all Jordanian businesses from different sectors operating in Jordan. We targeted different categories, including board members, senior executives, auditors, and IT assistants of various generations. The data for the study was collected through a snowball sampling procedure. Different researchers confirm that the snowballing sampling method is effective and appropriate for multivariate data processing and estimating the results (Agyekum et al., 2021; Chan, 2020; Faugere and Stul, 2021; Noy, 2008; Wang et al., 2019; Wright and Stein, 2004). At the initial stage, we explored the required minimum sample size to estimate the results. Many studies provide formulas and rules of thumb to calculate the sample size required to estimate the results (Bollen, 1989; Christopher Westland, 2010; Long et al., 1990). Following these studies and based on PLS path modelling and the number of latent and observed variables, we calculated the minimum sample size using free online statistical software. The sample is calculated based on an anticipated effect size of 0.3, a desired statistical power level of 0.8, nine latent variables, and 37 observed variables with a probability level of 1%. This gives a minimum sample size of 184 respondents. In addition, we used G-Power software to determine the required minimum sample, which yielded a minimum sample size of 160 respondents. However, the study collected 232 surveys through an online questionnaire survey via Google Docs using convenience sampling. The online survey was administered through several social media platforms (e.g., Facebook, WhatsApp, and e-mails) to increase the possibility of data collection. All questions were made mandatory to avoid incomplete forms or missing data. In the same context, the survey is based on closed-ended questions (Westland, 2014), where all items were made with respondent-friendly statements to increase the response rate and avoid poor-quality responses (Tarran, 2010). Moreover, the response rate is enhanced by sending a short letter to targeted respondents through distribution platforms. Moreover, brevity is also used, which yielded an increase of 20% in the response rate. Therefore, 232 surveys were collected and considered the final sample for the present study. Table 1 provides the sampling and sample adequacy. The results show that the final sample is 232. As the Kaiser-Meyer-Olkin Measure of Sampling Adequacy" value is greater than 0.7, this sample is considered statistically adequate for estimating the results. Further, this test shows high significance at the level of 1% (P-value = 0.000, <0.01), indicating the suitability and adequacy of the sample. Further, the fitness of the factor analysis is indicated by Bartlett's test, which has a value of 7956.149. Consistently, the degree of freedom is 741, indicating an appropriate estimation of factor analysis.Table 1 Sampling adequacy test. Particulars No. Total number of completed surveys (Online) 232 The number of incomplete surveys (0) Total number of questionnaire forms processed 232 KMO and Bartlett's test "Kaiser-Meyer-Olkin Measure of Sampling Adequacy". 0.963 "Bartlett's Test of Sphericity" Approx. Chi-Square 7956.149 Degree of freedom 741 Sig. 0.000 Research instrument The present study utilises an online questionnaire survey distributed to board members, senior executives, auditors, and IT assistants from various sectors of Jordanian organisations. The questionnaire survey consists of thirty-nine items based on a thorough literature review. A 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) was utilised to measure and assess the respondents' perceptions. The questionnaire was divided into nine dimensions. Table 2 below provides the measurement scales along with the operational definitions of the variables.Table 2 Operational definition of the variables. Nature Variable Acronym Measurement Evidence Independent variables Board Size BSIZE 4 statements (Almaqtari et al., 2022) (Al-Thuneibat et al., 2016) (Nalukenge et al., 2017) Board Independence BIND 4 statements Board Meetings BMET 4 statements Audit Committee Independence ACIND 4 statements Audit Committee Diligence ACMET 3 statements Board Committees BCOM 3 statements External Audit AUDIT 5 statements Moderating variable ITG ITGOV 4 statements (Al-Zwyalif, 2013) (Vugec et al., 2017) (Mushtaque et al., 2014) Dependent variable Business Continuity BC 4 statements (Jarvelainen, 2013) (Jarvelainen, 2012) (Rebmann et al., 2013) (Tammineedi, 2010) Results Sample demographic analysis Table 3 shows the demographic characteristics of the participants. The findings show that gender distribution has 59 percent for males and 41 percent for females. A sizable proportion of respondents (72%) were under the age of 40 (37% and 35% from the under-40 age groups, respectively). In addition, 52% of the participants held an undergraduate degree, whereas only 45% held a higher education degree (24% were PG holders and 21% were Ph.D. holders). The results also show that while 41 percent of the respondents had less than five years of experience, 27 percent had six to ten years. Similarly, the results indicate that 22% of the respondents had eleven to fifteen years of working experience, compared to 10% with more than fifteen years of working experience.Table 3 Respondents' profile. Demographics Categories Frequency Percentage Gender Male 136 59% Female 96 41% Age Less than 30 85 37% 30-40 80 35% 41:51 49 21% Above 50 18 8% Qualification Less than UG 7 3% UG 121 52% PG 56 24% Ph.D 48 21% Experience Up to 5 Years 95 41% 6:10 62 27% 11:15 51 22% Above 15 24 10% Measurement model Several studies have addressed the choice of PLS estimation based on its pros (Al-Hattami et al., 2021; Balta et al., 2020; Banerjee, 2022; Chin, 2010; Rostamzadeh et al., 2021; Shanmugapriya and Subramanian, 2016; Westland, 2014; Al-Hattami, 2022; Al-Hattami, 2023; Zafar et al., 2022). PLS modelling is commonly used among researchers due to several advantages (Hair et al., 2013; Henseler and Sarstedt, 2013). For example, PLS path modelling can be used to estimate associations between latent variables with a variety of indicators, even with a small sample size. The PLS path modelling approach uses ordinary least squares regressions to estimate sample sizes for various components of the focused path model. As a result, sample size requirements are scarcely affected by the complexity of the overall model. SEM-PLS is an appropriate technique for assessing complicated models that attempt to anticipate associations between research variables (Memon et al., 2017). PLS-SEM can be used to forecast and evaluate key target constructions as well as identify key driver constructs. The reasons for using PLS-SEM include data characteristics such as small sample size and non-normal data. Hair et al. (2019) suggest that there are multiple reasons for PLS estimation: (a) small sample size; (b) models with formatively specified constructs; (c) PLS-SEM is preferable over regression analysis when estimating mediation; (d) researchers should use the two-stage approach to moderator analysis; (e) it is not necessary to estimate a PLS model's goodness-of-fit. Accordingly, the present study uses Smart PLS3 software to conduct confirmatory factor analysis, validity, reliability, and structural equation modelling for hypotheses testing. This approach is motivated by similar prior studies (Alsmairat et al., 2018; Awawdeh et al. (2021); Elgharbawy and Abdel-Kader, 2016; Thaker et al., 2022; Wang et al., 2022; Wijethilake, 2017; Zafar et al., 2022). For a more rigorous estimation of the results, SPSS software version 23 was used to conduct exploratory factor analysis and reliability analysis of the measurement model. This is also motivated by Balta et al. (2020), who conducted a study using both SPSS and PLS. The current study also used SPSS to filter the data and assess several assumptions and issues, including residuals, outliers, normality, and multicollinearity. Exploratory factor analysis (EFA) The results in Table 4 provide EFA results. EFA using SPSS 23 was conducted to determine whether the data was sufficient to assess a latent variable network model. The results provide the factor loading values for each indicator, which are greater than 0.40. Further, the results present the total variance, which shows the eigenvalues for the yielded latent variables. Moreover, the findings provide reliability values based on Cronbach's alpha values. Some items were deleted throughout the exploratory factor analysis due to low factor loadings (0.40) or cross-loadings. Reliability analysis (i.e., Cronbach's alpha) of the extracted factors was also conducted to ensure that each observed variable has a value greater than 0.70 (Akter et al., 2013).Table 4 Exploratory factor analysis. Items Factor loadings CA Total variance explained (initial eigenvalues) Total rotation sums of squared loadings Total % of Variance Cumulative % BSIZE1 0.769 0.891 6.455 17.445 17.445 3.589 BSIZE2 0.867 0.891 BSIZE3 0.838 0.893 BSIZE4 0.824 0.891 BSIZE5 0.733 0.892 BIND1 0.673 0.894 5.663 15.305 32.75 3.4 BIND2 0.728 0.893 BIND3 0.68 0.892 BIND4 0.548 0.892 BDEL1 0.787 0.891 2.897 7.83 40.58 3.192 BDEL2 0.796 0.892 BDEL3 0.699 0.891 BDEL4 0.712 0.892 BDEL5 0.627 0.891 ACIND1 0.731 0.892 2.077 5.614 46.194 2.493 ACIND2 0.745 0.892 ACIND3 0.716 0.892 ACIND4 0.693 0.892 ACDEL1 0.792 0.891 1.765 4.771 50.964 2.45 ACDEL2 0.793 0.891 ACDEL3 0.789 0.89 BCOM1 0.711 0.892 1.631 4.408 55.372 2.383 BCOM2 0.798 0.892 BCOM3 0.794 0.891 AUDIT1 0.806 0.893 1.274 3.444 58.816 2.283 AUDIT2 0.785 0.893 AUDIT3 0.727 0.892 AUDIT4 0.699 0.892 AUDIT5 0.473 0.892 ITGOV1 0.63 0.894 1.223 3.304 62.12 2.253 ITGOV2 0.733 0.893 ITGOV3 0.65 0.891 ITGOV4 0.679 0.89 BC1 0.566 0.892 1.168 3.158 65.278 2.109 BC2 0.68 0.891 BC3 0.799 0.892 BC4 0.721 0.893 Confirmatory factor analysis Table 5 demonstrates the results of confirmatory factor analysis using PLS. The results provide the mean values and standard deviation for each item used to measure each construct. Further, the results give the measurement model in the form of factor loadings, Cronbach's alpha, composite reliability (CR), and average variance extracted (AVE). Compared to EFA results, it is clear that two items have been deleted: BSIZE5 and BDEL5. The factor loading for these items was <0.40.Table 5 Reliability and validity. Variables Acronym Factor loading CA rho_A CR AVE BSIZE BSIZE 1 0.784 0.877 0.878 0.877 0.641 BSIZE 2 0.789 BSIZE 3 0.801 BSIZE 4 0.827 BIND BIND 1 0.86 0.92 0.92 0.92 0.741 BIND 2 0.846 BIND 3 0.883 BIND 4 0.856 BDEL BDEL 1 0.851 0.844 0.869 0.851 0.595 BDEL 2 0.845 BDEL 3 0.795 BDEL 4 0.557 ACIND ACIND 1 0.832 0.889 0.89 0.889 0.667 ACIND 2 0.829 ACIND 3 0.779 ACIND 4 0.826 ACDEL ACDEL 1 0.848 0.823 0.83 0.826 0.613 ACDEL 2 0.735 ACDEL3 0.762 BCOM BCOM 1 0.808 0.833 0.836 0.834 0.626 BCOM 2 0.819 BCOM 3 0.744 AUDIT AUDIT 1 0.853 0.907 0.908 0.907 0.663 AUDIT 2 0.776 AUDIT 3 0.843 AUDIT 4 0.794 AUDIT 5 0.801 ITGOV ITGOV 1 0.863 0.897 0.9 0.897 0.685 ITGOV 2 0.883 ITGOV 3 0.791 ITGOV 4 0.769 BC BC 1 0.845 0.888 0.89 0.889 0.667 BC 2 0.827 BC 3 0.772 BC 4 0.821 Note: BSIZE is Board Size, BIND is Board Independence, BMET is Board Meetings, ACIND is Audit Committee Independence, ACMET is Audit Committee Meetings, BCOM is Board Committees, AUDIT is External Audit, ITGOV is ITG, and BC is Business Continuity. CA is Cronbach's Alpha, CVR is Composite Reliability, CR is Average Variance Extracted. Based on the findings, it can be deduced that the factor loadings of the items have coefficients between 0.55 and 0.88. These values are higher than the acceptable criterion value (0.60) suggested by Chin (2010). CR values range between 0.82 and 0.92. These values indicate how well each construct's components reflect the latent construct. Figure 2 shows the values of CA, Roh_A, AVE, and CR. Figure 3 provides the constructs' confirmatory factor analysis (CFA). Fig. 2 Reliability and validity. This figure shows the values of CA, Roh_A, AVE, and CR. All values are higher than the criterion values, exceeding the lowest value line. Fig. 3 Confirmatory factor analysis. This figure provides the constructs' confirmatory factor analysis (CFA). The CFA has been estimated based on the conceptual framework presented in Fig. 1 . It delivers the values of the factor loading, validity, and reliability of constructs. The findings in Table 6 provide the results of discriminant validity. The results reveal high correlation values corresponding to the same construct, indicating that the items used to measure the construct are suitable and represent the same construct. This is evident as the correlation values of each construct with other constructs provide low correlations, which are less than the self-correlation values of the construct (Fornell and Larcker, 1981).Table 6 Convergent & discriminant validity. Variables BSIZE BIND BMET ACIND ACMET BCOM AUDT ITGOV BC BSIZE 0.855 BIND 0.385 0.898 BMET 0.723 0.431 0.928 ACIND 0.753 0.444 0.82 0.866 ACMET 0.67 0.402 0.662 0.679 0.86 BCOM 0.738 0.42 0.697 0.722 0.765 0.866 AUDT 0.781 0.43 0.738 0.779 0.752 0.823 0.854 ITGOV 0.774 0.303 0.674 0.734 0.723 0.747 0.804 0.874 BC 0.755 0.443 0.92 0.799 0.677 0.717 0.777 0.736 0.866 Note: BSIZE is Board Size, BIND is Board Independence, BMET is Board Meetings, ACIND is Audit Committee Independence, ACMET is Audit Committee Meetings, BCOM is Board Committees, AUDIT is External Audit, ITGOV is ITG, and BC is Business Continuity. AVE square root is remarked in bold. Structural model Figure 4 displays the study variables' hypothesised or predicted structural approach. Fig. 4 Structural equation model-direct effect. This figure displays the study variables' hypothesised or predicted structural approach. It provides a direct effect model for the influence of the explanatory variables represented by CGC and ITG on the BC predicted variable. Table 7 provides the estimates for the direct effect. The results in Panel A show that CGCs have an insignificant impact on BC except for ACIND. The results reveal that BSIZE, BIND, BDEL, ACIND, BCOM, and AUDIT exhibited an insignificant effect on BC at any significance level (P < 1%, 5%, and 10%) during the Covid-19 pandemic. While board size, board committees, and external audit exhibit statistically significant negative effects, board independence, board diligence, and audit committee diligence show a positive impact. Nonetheless, the evidence reveals that ACIND has a statistically significant positive impact on BC at 1% (b = 0.988; P-value < 0.01). Notably, the empirical findings show that ITG has a statistically significant effect on BC at 5% (b = 0.012; P-value < 0.05). The adjusted R2 is 0.68, meaning the CGC and ITG constitute about 68% of BC. Therefore, H01, which states that "there is no significant effect of CGC on BC," is rejected in terms of audit committee independence; however, it is accepted concerning BSIZE, BIND, BDEL, ACDEL, AUDIT, and BCOM.Table 7 Structural equation modelling. Path Coefficients Standard errors T-value Result Panel A: BC model BSIZE - BC -0.010 0.009 1.091 Accepted BIND - BC 0.001 0.002 0.703 Accepted BMET - BC 0.010 0.010 0.988 Accepted ACIND - BC 0.988 0.012 81.549*** Rejected ACMET - BC 0.002 0.003 0.515 Accepted BCOM - BC -0.018 0.016 1.116 Accepted AUDT - BC -0.002 0.004 0.548 Accepted ITGOV - BC 0.012 0.012 1.055** Rejected Panel B: ITGOV model BSIZE - ITGOV 0.282 0.074 3.812*** Rejected BIND - ITGOV 0.110 0.040 2.769*** Rejected BMET - ITGOV -0.149 0.121 1.233 Accepted ACIND - ITGOV 0.267 0.110 2.421** Rejected ACMET - ITGOV 0.184 0.077 2.383** Rejected BCOM - ITGOV 0.093 0.082 1.133 Rejected AUDT - ITGOV 0.320 0.101 3.184*** Rejected Notes: Hypothesis acceptance and rejection criteria are based on 0.01 and 0.10 significance levels, which indicate *** and **. BSIZE is Board Size, BIND is Board Independence, BMET is Board Meetings, ACIND is Audit Committee Independence, ACMET is Audit Committee Meetings, BCOM is Board Committees, AUDIT is External Audit, ITGOV is ITG, and BC is Business Continuity. Panel B results for the IT governance model show that board size has a statistically significant positive effect on IT governance at the 1% level (b = 3.812; P-value < 0.01). The results also show that board independence has a statistically significant positive effect on IT governance at 1% (b = 2.769; P-value < 0.01). However, the findings indicate that board diligence has an insignificant negative effect on IT governance (b = -1.233; P-value > 0.10). Further, they reveal that audit committee characteristics represented by audit committee independence and diligence have a statistically significant positive effect on IT governance at the level of 5% (P-value < 0.01). In the same context, the results show that board committees have an insignificant positive effect on IT governance (b = 1.133; P-value > 0.10). Furthermore, the findings indicate that external audit has a statistically significant positive effect on IT governance at 1% (b = 3.184; P-value < 0.01). The adjusted R2 has a 0.88 score, indicating that CGC explains about 88% of the variability of IT governance. Hence, H02, which states "there is no significant effect of CGC on IT governance," is rejected in terms of board size, board independence, audit committee independence, audit committee diligence, and external audit". However, it is accepted in the context of board diligence and board committees. The moderating effect of ITG Figure 5 presents structural equation modelling for the moderating effect of IT governance on the relationship between governance mechanisms and BC. Fig. 5 SEM model-moderation effect. This figure presents structural equation modelling for the moderating effect of IT governance on the relationship between governance mechanisms and BC. IT governance has been considered a moderating variable that moderates the relationship between CGC and BC. Table 8 shows the moderating impact of IT governance results on the association between governance attributes and BC. The results in Panel A are consistent with the findings provided in Table 7, Panel A. The study reveals that CGCs have an insignificant impact on BC except for audit committee independence, which exhibits a statistically significant impact on BC. The study findings also show that IT governance has a statistically significant effect on BC at the level of 5% (b = 0.010; P-value < 0.05). In addition, Panel B reveals findings similar to those presented in Table 7 and Panel B. The results found that board size, board independence, and external audit have a statistically significant positive effect on IT governance at 1% (P-value < 0.01). Further, the findings reveal that audit committee characteristics represented by audit committee independence and diligence have a statistically significant positive effect on IT governance at the level of 5% (P-value < 0.01). However, the results indicate that board diligence and board committees exhibit an insignificant negative effect on IT governance (P-value > 0.10).Table 8 The moderating role of ITG. Path Coefficients Standard errors T-value Result Panel A: Direct Model BSIZE - BC 0.017 0.014 1.271 Accepted BIND - BC 0.001 0.002 0.439 Accepted BMET - BC 0.007 0.007 0.903 Accepted ACIND - BC 0.991 0.010 96.213*** Rejected ACMET - BC -0.005 0.006 0.865 Accepted BCOM - BC -0.020 0.016 1.294 Accepted AUDT - BC 0.000 0.006 0.024 Accepted ITGOV - BC 0.010 0.010 1.047** Rejected Panel B: direct model BSIZE - ITGOV 0.282 0.069 4.101*** Rejected BIND - ITGOV -0.110 0.038 2.865*** Rejected BMET - ITGOV -0.149 0.123 1.214 Accepted ACIND - ITGOV 0.267 0.117 2.284** Rejected ACMET - ITGOV 0.184 0.081 2.268** Rejected BCOM - ITGOV 0.093 0.083 1.115 Accepted AUDT - ITGOV 0.320 0.102 3.155*** Rejected Panel C: indirect effect -moderation effect BSIZE > Moderator ITGOV > BC -0.019 0.017 1.138*** Rejected BIND > Moderator ITGOV > BC 0.001 0.003 0.383*** Rejected BMET > Moderator ITGOV > BC 0.010 0.011 0.912* Rejected ACIND > Moderator ITGOV > BC 0.008 0.011 0.737*** Rejected ACMET > Moderator ITGOV Business > Continuity 0.002 0.004 0.362** Rejected BCOM > Moderator ITGOV > BC -0.019 0.017 1.144 Accepted AUDT > Moderator ITGOV > BC 0.001 0.005 0.277** Rejected Notes: Hypothesis acceptance and rejection criteria are based on 0.01, 0.05, and 0.10 significance, which indicate ***, **, and *, respectively. BSIZE is Board Size, BIND is Board Independence, BMET is Board Meetings, ACIND is Audit Committee Independence, ACMET is Audit Committee Meetings, BCOM is Board Committees, AUDIT is External Audit, ITGOV is ITG, and BC is Business Continuity. In terms of the moderating effect of IT governance on the relationship between governance mechanisms and BC, Panel C's findings indicate that IT governance significantly moderates the effect of board size on BC (P-value < 0.01). However, this moderating effect is negative (b = -0.019), indicating that board size negatively moderates the IT governance's effect on BC. This could be due to the large board size, which may negatively affect the impact of IT governance on BC. The outcomes further outline that board independence has a statistically positive (b = 0.001; P-value < 0.01) moderating impact on the relationship between IT governance and BC. This indicates that board independence has a positive monitoring role that significantly strengthens the bearing of IT governance on BC. The respondents perceived that board independence plays a significant and effective monitoring role in IT governance, contributing to a better BCM. The research found that board diligence significantly and positively (b = 0.010) moderates the effect of IT governance on BC. However, this effect is weak at 10% (P-value < 0.10). This could be attributed to the fact that board meetings strengthen the efficiency of IT governance. However, the respondents perceive that board meetings do not strongly moderate BC. This could be because all companies conducted their meetings virtually during Covid-19, which negatively affected the role of board diligence in the relationship between IT governance and BC. The outcomes also reveal that audit committee independence and diligence have a statistically significant positive moderating impact on the relationship between IT governance and BC. At the same time, audit committee independence has a significant impact at a 1% level (P-value < 0.01), and diligence has a statistically significant effect at the level of 5% (P-value < 0.05). This implies that audit committees have a positive monitoring role that strengthens the relationship between IT governance and BC. The findings clarify that board committees have a statistically insignificant (P-value > 0.10) moderating impact on the relationship between IT governance and BC. The negative coefficient (b = -0.019) indicates that this effect is negative but statistically insignificant. Finally, external audit exhibits a statistically significant positive moderating effect of 5% (b = 0.001, P-value < 0.05) on the relationship between IT governance and BC. This leads to rejecting H03, which states that "there is no significant moderating effect of IT governance on the relationship between CGC and BC." Therefore, H03 is partially rejected in terms of board size, board independence, board diligence, audit committee independence, audit committee diligence, and external audit; however, it is accepted in the context of board committees. Discussion and implications Summary of findings The purpose of this study was to look into the impact of governance characteristics and IT governance on continuity management during Covid-19. The study also examined the moderating role of IT governance in the relationship between governance characteristics and BCM. A quantitative approach was used by utilising a survey questionnaire. A total of 232 questionnaire surveys were received from the board of directors, top and middle management executives, external auditors, IT experts, and some other respondents in Jordan. The study used an online questionnaire survey based on a 5-point Likert scale as the research instrument to collect the data. Finally, factor analysis and structural equation modelling were used to estimate the results. The outcomes revealed that CGCs have an insignificant impact on BC except for audit committee independence, which exhibits a statistically significant effect on BC. The results also revealed that IT governance has a statistically significant effect on BC. The study found that board size, board independence, and external audit have a statistically significant positive impact on IT governance. Furthermore, the findings revealed that audit committee characteristics, represented by audit committee independence and diligence, have a statistically significant positive effect on IT governance. However, board diligence and board committees exhibited an insignificant negative effect on IT governance. Regarding the moderating impact of IT governance on the relationship between governance mechanisms and BC, the results reported that IT governance significantly moderates the effect of board size on BC. However, this moderating effect is negative, indicating that board size moderates the effect of IT governance on BC negatively. The outcomes also show that board independence has a statistically significant positive moderating impact on the relationship between IT governance and BC. The results found that board diligence significantly and positively moderates the effect of IT governance on BC. However, this effect is weak at 10% (P-value < 0.10). In the same context, the study shows that audit committee independence and diligence have a statistically significant positive moderating impact on the relationship between IT governance and BC. Furthermore, the findings show that IT governance does not moderate the relationship between board committees and the BC. Finally, external audit exhibits a statistically significant positive moderating effect on the relationship between IT governance and BC. The research at hand provides insight into the role of IT governance in BCM during crises. It offers a unique contribution as it investigates the relationship between CGC, IT governance, and BCM during the Covid-19 era in an emerging country. The study provides empirical evidence from an emerging country on the relationship between CGC, IT governance, and BCM. Moreover, the present study makes a unique and novel contribution to investigating a critical issue encountered by all businesses during Covid-19, that affected business operations. To the researchers' knowledge, this is the first study on the role of IT governors in the relationship between corporate governance attributes and BCM. Therefore, the present study also contributes to the strand of literature and bridges a serious gap. Very few studies and limited research have been conducted on IT governance and BCM. Accordingly, the present study is beneficial and highly important for board members of corporate organisations, stakeholders, regulators, practitioners, and academicians. The study is based on empirical evidence from a developing country. Accordingly, the results of this study have wider practical applications for some other developing nations. It offers insights into using technology-based business during crises for better business continuity. Practical implications Manufacturing industries are facing numerous challenges as a result of the Covid-19 pandemic and changing market demands (Pansare et al., 2022). The Covid-19 pandemic has significantly impacted most manufacturing systems, affecting the supply chain of medicine and other products (Moosavi et al., 2022). Furthermore, the manufacturing industries are struggling to improve performance and re-establish the supply chain in the post-Covid-19 period. To improve performance, current market demands and the post-Covid-19 situation necessitate integrating IT strategies and technological capabilities (Pansare et al., 2022). The results of the present study report that all CGCs, except for audit committee independence, have an insignificant effect on BC. They also indicate that IT governance has a statistically significant effect on BC. Further, the results found that board size, board independence, audit committee independence, audit committee diligence, and external audit have a statistically significant positive effect on IT governance. However, the results show that board diligence exhibits an insignificant negative impact on IT governance. Overall, the results show that board involvement in IT governance was inefficient during the crisis in Jordan. Consistently, Moeller (2013) indicates that as a fundamental component of the Committee of Sponsoring Organizations (COSCO) control environment, the COBIT framework emphasises the importance of IT governance and the role of an effective and independent board. Thus, board members need to enhance their involvement in IT governance to improve preparedness for any crisis and improve business operations. In this regard, companies, especially board members, are suggested to incorporate both business and technological elements into their BCM process. Moreover, a detailed BC specifying IT systems and infrastructures should be created. Several studies also emphasise the board's responsibilities and involvement in monitoring and developing IT governance strategy (e.g., Gomez et al., 2017; Posthumus & Solms, 2004; Hamdan et al., 2018; Moeller, 2013). In addition, many studies report that information technology, including IT governance, is considered one of the prominent elements of a BC plan (Lindstrom et al., 2010; Korac-Kakabadse & Kakabadse, 2001; Dittmeier, 2011; Haes & Grembergen, 2009; Peterson, 2004). They indicate that IT governance is a significant element of an organisation's corporate governance model because it introduces critical measures for strategic plans focusing on IT strategy alignment. The results of the current study exhibit that CGCs have an insignificant effect on BC; however, they indicate a significant effect on IT governance. This could be because several enterprises began adopting IT governance to achieve better alignment in business operations (Haes & Grembergen, 2009). Further, IT governance has been identified as a critical concern for businesses. Companies' growing interest in the subject is justified by the changing role and relevance of IT within organisations and the need to ensure that it is properly managed. IT governance employs corporate governance concepts to drive and control IT strategically (Lunardi et al., 2014). Therefore, IT governance is high on the agenda nowadays, and many organisations are incorporating its practices into their day-to-day operations (Haes & Grembergen, 2009, Lunardi et al., 2014). Accordingly, business organisations should enhance their IT governance mechanisms as a practical implication. Moreover, board and audit committee members should have capacity programmes that enhance their expertise in IT governance. IT resources should be integrated with other organisational resources in the IT governance of business organisations to provide a competitive advantage (Zhang et al., 2016). This is necessary as a pandemic reaction (Ferreira et al., 2021). Regarding the moderating effect of IT governance on the relationship between governance mechanisms and BC, the results reported that IT governance significantly moderates the effect of board size, board independence, board diligence, audit committee independence, audit committee diligence, and external audit on BC. However, IT governance does not moderate the relationship between board committees and BC. The current study results are consistent with Lindstrom et al. (2010), who indicate that IT is one of the key drivers of BC. Further, Tosh et al. (2014) revealed that IT played a significant role in BC planning during the pandemic. Numerous studies have consistently indicated that a BC plan should be designed and implemented to avoid the unintended consequences of disruptive events (e.g., Sahebjamnia et al., 2015; Botha & Solms, 2004; Cerullo & Cerullo, 2004). Similarly, IT governance is necessary to ensure the continuity and recovery of an organisation's business operations to a predetermined acceptable level after a disruptive event (Tammineedi, 2010; Lindstrom et al., 2010; Clifton, 2000; Botha & Solms, 2004; Cerullo & Cerullo, 2004). Accordingly, business organisations should identify possible risks and establish a framework for building response and resilience as part of their business continuity. Business organisations should frame their BC plans as a process of sustaining their business operations and maintaining their continuity following a disruptive event that can impede their goals (Aleksandrova et al., 2018). Any minor disruption can cause irreversible harm to a company's reputation and public image (Botha & Solms, 2004). Accordingly, a well-designed and efficient pre-crisis BC plan should be designed and implemented (Sahebjamnia et al., 2015). Hence, the results of the current study suggest that BC plan methodology should be developed and implemented to avoid the undesirable consequences of disruptive events (Botha & Solms, 2004; Cerullo & Cerullo, 2004). To this end, the results highlight that to create a detailed BC plan, different business divisions should integrate their tasks with the support of IT application teams (Tammineedi, 2010). This is needed to ensure the continuity and recovery of a company's business operations to a predetermined acceptable level following a disruptive event (Sahebjamnia et al., 2015; Cerullo & Cerullo, 2004). According to the findings, advanced IT governance practices receive the most weight, emphasising their importance in organisations. The Covid-19 pandemic has posed new challenges for many organisations. The current results show that changing an organisation's needs complicates matters. As a result, using advanced technologies can help organisations stay competitive in this situation. The developed framework can help practitioners and managers overcome the challenges posed by the pandemic and remain competitive in the market during the difficult post-Covid-19 period (Pansare et al., 2022). Also, based on the current study results, several managerial and practical implications are offered to companies' board members, regulators, managers, and investors. Companies should have an effective and efficient IT governance structure and strategy. Members of the board, audit committees, other board committees, and external auditors should all be actively involved in IT governance and process. They should also establish an organisational IT governance structure and procedures that ensure explicit and strategic BC. IT governance should be at the top and a major focus of the board's and audit committee's agendas. Further, the effective participation of board and audit committee members could be secured by increasing board independence and expertise, which leads to effective monitoring and involvement of board members in IT governance. Board evaluation and training in IT governance issues are essential to avoid business disruption and achieve better BCM. In times of emergency and economic crises, the behaviour of business organisations is critical. In crisis survival, firms' resources, dynamic abilities, innovation, and practical strategies aid in combating the negative effects of the pandemic (Liu et al., 2021). Firms must be able to survive unprecedented threats, increase market exposure, and thrive on emerging opportunities in today's volatile and fast-paced competitive business environment. Thus, IT plays a critical role in the success of modern organisations by influencing how they create and capture value (Mikalef et al., 2021). As a result, businesses have developed new strategies for surviving the Covid-19 pandemic. This is motivated by organisations striving for long-term viability through competitive activities (Liu et al., 2021). Therefore, the Covid-19 economic crisis presented challenges and opportunities for marketing innovation and digitalisation to capitalise on business opportunities with competitive products to survive the crisis (Wang et al., 2020). Competitive firms enable business activities and provide opportunities to meet customer and business environment requirements that existed before the crisis but have increased during the Covid-19 era, such as additional services and digital solutions (Ilinova et al., 2021; Al-Hattami, 2021). As a result, the role of business firms' innovativeness, resources at hand, business networks, and dynamic capabilities in producing the best products to compete in the business competition ultimately improves firm performance. These influential factors aid firms in surviving during emergencies and global crises (Liu et al., 2021). Hence, effective IT governance would enable the implementation of decision-making structures and the efficient use of these resources to assist managers in achieving their strategic goals while minimising efforts and investments in IT (Frogeri et al., 2020). IT governance strengthens organizations' resilience to potential economic and environmental shocks. Organisations, in particular, should improve their corporate governance in order to increase their resilience and survival in such a risky environment (Awwad & El Khoury, 2021). Business organisations hire high-tech employees to help with technological innovations that aid business success, organisational competitive advantage, and long-term survival. Consequently, this necessitates the implementation of new ideas generated by high-tech employees (Li et al., 2022). Limitations and directions for future research Despite its numerous merits, this study contains several drawbacks. To begin, due to the length restriction of the questionnaire, the study was limited to a few corporate governance aspects. Thus, researchers are encouraged to investigate the other aspects of corporate governance that have not been considered here. Second, one major limitation this research encountered was collecting the data. Owing to the lockdown and Covid-19 restrictions, the study could not focus on particular sampling units. Third, this study is based on an emerging country, Jordan. Future research may investigate the same issues based on a comparison between some countries. Another limitation of this study is that it was conducted during Covid-19. A possible suggestion for future studies is to compare the findings with the post-Covid-19 situation. Finally, the current study is limited to a general sample drawn from different sectors. Future studies could compare several samples from different sectors. Acknowledgements The authors extend their appreciation to the Arab Open University for Funding this work through funding No. (AOURG-2023-004). Data availability The data is available on request. Competing interests The authors declare no competing interests. Ethical approval This article is not involved with any individual or specific organization. This article does not contain any studies with human participants performed by any of the authors. Informed consent Consent was not deemed necessary for this study, as the data collected using the anonymous identity of the respondent. All sources used in this study have been considered and cited. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 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PMC10000348 | BMC Psychol BMC Psychol BMC Psychology 2050-7283 BioMed Central London 36899413 1104 10.1186/s40359-023-01104-7 Study Protocol Evaluating programs for young people with a family member with mental health challenges: protocol for a mixed methods, longitudinal, collaborative evaluation Reupert Andrea [email protected] 1 Freeman Nerelie 1 Hine Rochelle 2 Lea Sophie 1 Nandakumar Nivedita 1 O'Grady Charlotte 3 Patlamazoglou Lefteris 1 Pettenuzzo Laura 3 Foster Kim 4 1 grid.1002.3 0000 0004 1936 7857 School of Educational Psychology and Counselling, Faculty of Education, Monash University, 19 Ancora Imparo Way, 3800 Clayton, Australia 2 grid.1002.3 0000 0004 1936 7857 Monash Rural Health, Monash University, 3820 Warragul, Australia 3 The Satellite Foundation, 22 Easey St, 3066 Collingwood, Australia 4 grid.411958.0 0000 0001 2194 1270 School of Nursing, Midwifery & Paramedicine, Australian Catholic University, Melbourne, VIC Australia 10 3 2023 10 3 2023 2023 11 6711 11 2022 27 2 2023 (c) Crown 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background Young people with a sibling or parent who experiences mental health challenges have their own support needs. Most programs designed for this population lack a strong evidence base, and the involvement of young people in the development and evaluation of programs designed to support them is unclear or lacking. Methods This paper describes a protocol for a mixed methods, longitudinal, collaborative evaluation of a suite of programs delivered by The Satellite Foundation, a not-for-profit organisation for young people (5-25 years) who have a family member with mental health challenges. Young people's lived experience and knowledge will guide the research approach. Institutional ethics approval has been obtained. Over a three year period, approximately 150 young people will be surveyed online on various wellbeing outcome measures, prior to, six and twelve months following program participation with data analysed using multi-level modelling. Groups of young people will be interviewed after participating in different Satellite programs each year. An additional group of young people will be interviewed individually over time. Transcripts will be analysed using thematic analysis. Young people's creative artworks on their experiences will be included as part of the evaluation data. Discussion This novel, collaborative evaluation will provide vital evidence on young people's experiences and outcomes during their time with Satellite. Findings will be used to inform future program development and policy. The approach used here may guide other researchers engaging in collaborative evaluations with community organisations. Keywords Evaluation Mixed methods Participatory; parental mental illness Youth mental health Department of Health, State Government of Victoria not applicable issue-copyright-statement(c) The Author(s) 2023 pmcBackground This protocol paper describes the mixed methods design and collaborative processes for a three-year external evaluation of a not-for-profit organisation, The Satellite Foundation (hereafter known as Satellite). Satellite delivers programs for children and young people aged 5-25 years who have a parent and/or sibling experiencing mental health challenges. Over a three-year period, the evaluation findings will be used to iteratively inform and further develop Satellite services. In addition to the research methods, this paper outlines steps to actively and authentically involve children and young people in a collaborative evaluation design and delivery process while simultaneously presenting meaningful insights for the funding body. Governments need evidence that the expected results of social service initiatives they fund are achieved to support quality improvement, risk management, accountability, decision-making and ongoing funding. Addressing this need requires evaluations that employ robust research methodologies and use validated outcome tools, conducted by an independent or external team. Although participatory research is increasingly being used in psychological research , tensions may arise when employing this approach with young people, who may face barriers to participation and may have different or opposing views and preferences for the evaluation process. Young people with a family member experiencing mental health challenges have diverse experiences and outcomes. Research shows that these children can experience associative stigma, caring responsibilities and stress from witnessing and responding to their relative's illness . Young people whose parent/s has/have mental health challenges describe being marginalised , are more likely than their peers to develop a mental illness , report higher rates of injuries and health difficulties such as asthma , and present with educational, social and emotional impairments . Likewise, several studies have found that those who have a sibling with mental health challenges are at risk for lower psychological functioning which can lead to mental health challenges . The COVID-19 pandemic and lockdowns have added further layers of complexity for these young people, including isolation and stress . As nearly 50% of mental health concerns begin in childhood before the age of 14 , and 21-23% of children grow up with a parent with a mental illness , developing and delivering evidence-based interventions to these young people is a public health priority. It is important to recognise that while children can experience adverse psychological or mental health outcomes in these family contexts, not all children do . Positioning young people within a risk and vulnerability lens alone has been critiqued as failing to represent a holistic view of these children . This limited perspective obscures their choice, agency, strengths and competencies. Many children derive positive benefits from undertaking caring roles and responsibilities such as increased empathy and compassion , the development of life and professional skills, and resilience, persistence and maturation . Most interventions for young people with a family member who experiences mental health challenges employ a peer support approach, which aims to promote connectedness, wellbeing, adaptive coping and mental health literacy . Many of these face-to-face interventions (for example ON FIRE ) are relatively small in scope, although in recent years online peer support programs have been developed which have the potential to promote reach and access . However, online approaches are in the early stages of development and are typically limited to young people aged 18-25 years. Additionally, most online and face-to-face programs in this field lack a strong evidence base and the involvement of young people in the development of the programs and their evaluations is unclear or lacking. Participatory program development and evaluation Engaging stakeholders in program development is critical to ensure that resulting programs are grounded in the preferences and needs of intended end users . Being actively involved and heard in this process has the potential to promote autonomy and empowerment, especially for marginalised young people . Engaging young people in program development and evaluation needs to acknowledge the intersectionality of young people who live in these families and appreciate inequalities that may impact participation . Participatory research is an umbrella term used to describe approaches that share a philosophy of inclusivity and engagement with end-users and relevant stakeholders in the research process, including evaluations . There are different frameworks of youth participation. Cargo and Mercer argued that the specific steps undertaken in participatory research will vary depending on whether the aim is to promote self-determination, translate research into practice and/or promote social justice, equity and access. The process of implementing participatory evaluations with young people is not always easy or, at times, authentically conducted since young peoples' input is often mediated through the perspective of adults and influenced by associated power imbalances . In a scoping review of 54 participatory projects, only 17 included young people on boards, 18 involved them in the preparation stage and 28 included them in data collection and/or analysis . There are many reasons why young people may not be involved in program development, some of which include funding and ethical guidelines, which tend to stipulate that a detailed methodology and timetable be submitted and approved before young people can be involved. The current study addresses a number of these concerns by gaining ethics approval prior to engaging with young people directly, then modifying the protocol based on their input and including young people's perspectives and recommendations throughout the entire study. The following section describes the participatory approach used in this study. The Satellite Foundation The research team was awarded a three-year contract by the Victorian Department of Health to evaluate the programs offered by Satellite. Satellite is an Australian not-for-profit organisation that aims to promote the mental health and wellbeing of children and young people (aged 5-25) when a family member (parent/carer or sibling) experiences mental health challenges. By delivering a range of in-person and online programs, Satellite aims to foster strong connections between young people, their families and the wider community. Satellite intends to promote positive change in young people not only by offering specific programs and follow-up activities but also through their engagement with other young people in co-designing and co-leading their programs. Satellite staff put significant time and energy into staying in contact with young people outside program delivery (e.g., after finishing one program but before starting another) to keep them connected with Satellite, an activity they refer to as "linking programs". They also deliver education programs to schools and community services about the needs of young people living in these families, intending to promote a coordinated, systems approach to supporting these young people. See Table 1 for an overview of Satellite programs. Though the programs vary in intensity (i.e. dose), approach and medium (e.g. weekend camps, Zoom meetings) the overall aims of Satellite are to promote the wellbeing, resilience and connectedness of young people, aged 5-25 years, who have a family member experiencing mental health challenges. Table 1 Satellite programs Programs Participants' Ages Brief description Possible active ingredient/s It's a Mad World 18+ An experimental, group devised project for graduates of Satellite programs to create an online showcase of different perspectives on mental health, merging lived experience, design and creativity with a passion for destigmatising mental illness Peer support and connection based on lived experience, respite from carer responsibilities and creative activities Create and connect 11-14 Facilitated by professional musicians, artists, peer facilitators, and Satellite staff, these workshops offer playful experiences that allow participants to explore collaboration while reinforcing connection. Workshops include music and song writing, photography and visual art including graffiti and meme-making, and art and craft Peer support and connection based on lived experience, respite from carer responsibilities and creative activities Satellite connect (includes retreat) 18-25 Structured peer support and peer development program that gives young people a space and place to be heard, to learn new skills, and to share their stories, as well as ways their unique lived experience can be harnessed positively to shape and influence the lives of younger children. This program expands, develops and supports Satellite's network of peer leaders and facilitators to co-design and co-facilitate programs for children and young people living in families where a family member has a mental illness. Peer support and connection based on lived experience, respite from carer responsibilities, creative activities and wellbeing education Satellite Connect Youth 14-17 Similar to that of Satellite Connect, but with a greater focus on the experience of sharing participant's stories, being heard and facilitating peer connection and wellbeing. Peer support and connection based on lived experience, respite from carer responsibilities, creative activities and wellbeing education At Home with Satellite 8-14 A program of online curated creative workshops delivered across the school holidays. Participants can choose from four curated workshops with each workshop having a .5 h Zoom session. Each workshop had a creative focus that explored ideas around mental health and wellbeing, connections and strengths. The workshops covered photography, making superheroes, song writing. Peer support and connection based on lived experience, respite from carer responsibilities and creative activities Connecting activities All While not a program, connecting include engagements with children and young people after programs to ensure they still feel part of our community even when the program has finished. Connecting activities vary, and include family fun days, visits to local attractions, post-program catch-ups and end of Year celebrations Connectedness to others Satellite works in partnership with young people in recognition of their lived experience expertise, the rights of young people to exercise self-determination and choice, and to ensure that the programs offered are relevant to the young people they aim to serve. Subsequently, interventions delivered by Satellite are the product of co-creation and co-facilitation with young people. Given that youth participation is at the heart of what Satellite does, it was considered important for the evaluation team to employ a similar approach. Taking a participatory approach in the evaluation was also seen as a means of providing further opportunities for young people to be engaged in program design and delivery. Simultaneously, we were cognisant that as external evaluators we needed to maintain an independent stance so that the resulting evaluation was credible and trustworthy. There are many ways of operationalising this independence. Some assume the empirical view that evaluators need to completely distance themselves from the program, rely exclusively on extant data, and avoid contact with program staff in order to maintain 'objectivity' . At the other end of the continuum, others argue that employing a participatory evaluation model where the evaluation team actively work with the program staff and end-users can benefit organisational learning, inform change promote self-determination , and incorporate multiple valid perspectives and interpretations of meaning. Marklewicz pointed out that participatory models extend the use of evaluation for funding accountability, by providing a process that builds the capacity of program participants, developers and facilitators. Nonetheless, adopting a participatory evaluation approach that includes program participants (young people) needs to have clearly defined expectations and boundaries of involvement from the outset . The project team were funded by the Department of Health, via Satellite, to undertake this evaluation, making the team's independence, notwithstanding the participatory approach, even more critical. Being funded by the very service we were evaluating may be problematic including feeling pressured to report results that favour Satellite and/or not publishing results that might reflect unfavourably on Satellite. To safeguard against this potential bias, six monthly meetings will be held with the Department of Health, who will provide oversight of the overall evaluation plan, including analysis and results. The funding agreement included that the methodology and results would made available so the evaluation could be judged on its validity and significance, external to the evaluation team. This allows for an assessment of whether appropriate variables are being measured, the analysis employed is appropriate and whether the data reported support the final conclusions reached . Documenting the evaluation protocol also allows for the evaluation to be replicated in other programs. Finally, it should be noted that the evaluation process allows for results to inform continual improvements to Satellite's programs. Rather than simply being provided with a report at the end of the three years, Satellite have committed to this process, which also indicates their openness to receiving evaluating data that might not necessarily be favourable. The current protocol describes the collaborative approach being used in this project and aims to provide guidance to other researchers. We are not able to 'bracket' our own ideas about the evaluation design as our contracted, predetermined approach had been approved (and funded) by the relevant government authority. Due to the timeline and process for the funding tender, we were unable to consult with young people in the initial evaluation design. As the approved tender design included seeking input from young people about the evaluation approach, immediately upon gaining the funding we sought to include young people in the design and conduct of the evaluation, including the interpretation and dissemination of findings. Our intent for working in this particular manner with young people was to ensure that the evaluation methodologies employed were inclusive, accessible and engaging, appropriate to the developmental competencies of young stakeholders, suited to their interests and, most importantly, promoted young people's empowerment. Moreover, the evaluation design is underpinned by a similar philosophy/similar stance to working with young people to that of Satellite. The collaborative process presented builds on the experience of the authors in other community projects employing this design and extends this work by focusing on the ways in which it can be built into an evaluation methodology. Adapted from other frameworks, Satellite developed a co-creation framework for their own delivery work, and asked the evaluation team to indicate where on the continuum of participation the evaluation participatory approach would sit (see Fig. 1). We have taken a "collaborate" stance in this project. Accordingly, the evaluation approach we will employ is multifaceted, with a range of opportunities for different groups of young people to collaborate. Although involving stakeholders in program development and evaluation has the potential to increase the relevance, usability, and credibility of the services and supports offered, the methods for doing so are not well understood nor often documented . The process of writing this protocol in itself may promote a shared understanding of our participatory evaluation approach amongst the stakeholders involved (with young people from the Satellite advisory group being co-authors) and one which might offer guidance to others working in the field. Fig. 1 Satellite's co-creation framework Adapted from . Aim and objectives The aim of this mixed methods, longitudinal participatory project is to evaluate the suite of programs delivered by the Satellite Foundation designed for young people (5-25 years) who have a family member with mental health challenges. Specific evaluation objectives are to: Explore the experiences of young people participating in Satellite programs, Identify the outcomes of young people participating in Satellite programs. Methods This section identifies and describes the evaluation methodology employed and the role of stakeholders. Design A mixed-methods, longitudinal, participatory design will be used. A mixed-methods approach with quantitative and qualitative data is appropriate for evaluations as it provides a range of evidence relevant to program objectives. Concurrent and sequential data collection will be used . Participatory stakeholder groups and roles There are three stakeholder groups involved, each with distinctive though at times overlapping roles in the evaluation; the evaluation team, young people and Satellite staff. The evaluation team is comprised of university researchers who have individual and collective experience working with young people. Within the team, different staff are responsible for the various project components. The evaluation team leader takes overall responsibility for the project including oversight of the budget and ensuring that ethical processes are followed. Satellite's pre-existing Youth Advisory Council (YAC) will be the main way for young people to participate in the evaluation process. The YAC is comprised of 15 young people with lived experience of having family member/s with mental health challenges. The role of the YAC is to shape the work of Satellite by providing input and advice and co-creating programs. They are remunerated for their time by Satellite. Prospective YAC members apply for membership, and are selected by current YAC members, who ensure members have diverse backgrounds and varied exposure to Satellite (some with much, some with little or none). To provide consistency and continuity, one evaluation team member (RH) will be the primary conduit between the YAC and the evaluation team. It will be their responsibility to work with and support the YAC throughout the evaluation design, interpretation and dissemination process. This team member brings substantial experience working with young people in a participatory manner. Additional evaluation team members will meet with the YAC as relevant throughout the three years. Other young people are involved in the evaluation as participants but also provide feedback on ongoing program development and the evaluation design (see below). The final group of stakeholders are Satellite staff. They bring a close knowledge of Satellite; its vision aims and approaches, and are responsible for facilitating Satellite programs. Their participation is key to enhancing relevance, ownership and unitization of the findings to inform ongoing program development. Satellite staff will action the implications of the evaluation and make any relevant changes to program content and types. Initial participatory YAC workshop A full-day workshop was held with the YAC at the beginning of the project. The day was facilitated by the evaluation team YAC contact (RH), Satellite's Youth Liaison staff member, the Evaluation lead and co-lead, and other evaluation team members, and attended by the YAC and selected Satellite staff. The workshop was held at a location and at a time that made it easy for participants to attend. To accommodate participants' capacities, priorities and preferences, including large and small group discussions, various pedagogies were used (e.g. Zoom and face-to-face; large and small group discussion). The language employed aimed to be age-appropriate, non-judgemental and jargon free, using the Mental Health Coordinating Council guide for recovery-oriented language. Consideration of trauma-informed and inclusive principles were incorporated into the physical environment, with the aim of creating a safe and supportive space. To that end, a youth-designed community space was used, in which the sensory impact has been considered and modified (e.g. gentle music, soft lighting, furniture placement that enables connection). Similarly, participants had access to, and were aware of support options as required, with breaks offered as needed, in addition to scheduled meal breaks. See Table 2 for an outline of the workshop. The workshop concluded by inviting YAC participants to evaluate how inclusive the workshop was. Their collated and de-identified feedback were provided back to the YAC with action steps, in future deliberations with the Council. Table 2 Youth Advisory Council: workshop details Session title Session aims Session topics and process Welcome and introductions To set the scene for the day * In a large group format: * Acknowledgement of country * Recognition and appreciation of lived experience of having a family member with mental health challenges * Introductions * Expectations of the day (e.g. right for others to speak/not to speak etc.) * Clarify participant roles (e.g. to speak for themselves but also represent other young people) * Present an overview of the day What is program evaluation? To gain an understanding of program evaluation Share experiences of being involved in evaluation To identify ways for promoting evaluation engagement * Overview of what program evaluation is * In small groups, identify an experience of being involved in evaluation (or not being involved) e.g. in other research projects, in the community, retail outlets etc., and what was good/not so good about that process * Suggest ways to promote young people's recruitment and engagement in evaluation Evaluation outcomes To identify what outcomes the evaluation should target and subsequently measure. * Think-pair-share: Invite participants to respond to two questions: * How would you describe how your life has changed since being part of Satellite? * How do you think Satellite will change the lives of other young people? * Encourage participants to articulate changes in terms of measurable outcomes * Using an anonymous, online poll vote to identify the most important outcomes. Interviews To elicit the types of questions we should be asking and the language and approach for the interviews * World cafe format in which participants work in small groups to respond to different questions: * What questions should we be asking for different age groups? * What language should we use for different age groups? * What approach should we use for different age groups? Ongoing YAC involvement To discuss YAC future involvement * In the large group, discuss how the YAC can assist in: * Informing program development * Informing ongoing evaluation - are we asking the right questions? o How often to meet and for how long? * Conclusion, thanks and acknowledgement of all views Evaluating the evaluators To obtain feedback on the day * Participants will be asked to complete an evaluation form asking: * what was good about the day * what could have been improved * on a Likert scale from 0, not at all, through to 10, very much so, how much they felt they had an opportunity to speak up and how much they felt heard. The feedback and advice generated from the workshop was used to inform the evaluation approach outlined here. For example, the outcomes identified by YAC participants were used to identify relevant outcome measures. Likewise, their advice about interviewing was used when deciding on approaches (focus group or individual etc.) and the types of questions that should be asked. Ongoing YAC collaboration During the three-year evaluation, we aim to meet every three months with the YAC to discuss evaluation results and ask for their feedback about (i) what the results might mean, (ii) the implication of the results for program development and (iii) appropriateness of the data collected, and what changes may be required to the evaluation process. Their views will be used to inform future rounds of the evaluation and Satellite offerings. Changes that were or were not actioned regarding Satellite programs, and why, will be discussed at subsequent YAC meetings, to ensure the evaluation and program development processes are transparent and accountable. Data collection As per Table 1, Satellite offers a range of program activities, with varying lengths (e.g. a weekend camp or one-off event) and in different mediums (e.g. online, face to face). Additionally, many young people participate in more than one activity. Thus, rather than evaluating each program activity as a distinct entity, the evaluation needs to reflect the ongoing and ecological nature of all of Satellite's offerings. Notwithstanding this, Satellite were also keen to delve deeper into some program activities which were considered to be representative of their vision and objectives. Using input from the YAC, the data collection method is outlined below. Semi-structured interviews or conversations The YAC recommended these be called conversations rather than interviews, indicating that this term would be more acceptable to young people A purposive sampling approach will be used to conduct semi-structured face-to -face, telephone or Zoom individual conversations or focus groups with Satellite participants. Though there is some debate about the efficacy of these different mediums, some have argued that there is little difference in outcomes, depending on the research questions posed . Conversations are based on a narrative approach which aims to illuminate the value of a program and highlight what needs to occur to improve it . Each year, three programs will be identified by Satellite staff that they consider to be particularly important to their overall offerings and nine young people from each of those three programs will be invited to a conversation each year. The sample size of nine per program was chosen as it is considered adequate for sampling amongst a homogenous population while also allowing for deep analysis . The YAC provided feedback on what should be asked and how. A key element of the evaluation approach is not only evaluating what Satellite does but also how successfully they work with young people in a participatory manner. Thus, questions will be asked, in an age appropriate way, about how involved the young person was in the program/s they were a part of, and whether they wanted to be more/less involved. Other questions will be around process (e.g. what parts of the program were important to you?), accessibility (e.g. how easy was it to get to the program?), safety (e.g. how safe did you feel participating in the program) and outcomes (e.g. what changed, if anything, for you, as a result of participating?). The YAC recommended a mix of individual and focus group conversations, depending on participants' ages and the particular program. In addition, we intend to conduct individual conversations longitudinally, involving yearly interviews with the same nine participants over three years, regardless of whether they remain Satellite or not. This will allow us to explore why they remained or did not remain with Satellite, the accumulative impact of Satellite's offerings (if applicable), looking for instances of continuity, change and growth over time . A longitudinal approach also allows participants to reflect on changes since the previous conversation, anticipated future trajectories and whether and how Satellite is aligned with those narratives. From these conversations, we aim to capture critical moments and processes involved in change as well as what might have been needed to better support young people at different time points. Survey outcome measures and design All young people who enter Satellite (approximately n = 150 each year) will be invited to participate in surveys on program entry, and then again six and 12 months later, using the number of programs they engage in as a variable. Using what we know from previous evaluations in this field and feedback on expected outcomes from the YAC (Table 2) we intend to use various questionnaires for the different age groups (See Table 3). Satellite have various outcomes in their charter, which relate to strengths-based areas that they hope to nurture in young people who are part of their programs. In consultation with Satellite staff and the YAC, the four most important outcomes were identified and valid, reliable measures were selected to align with these outcomes. Additionally, a similar group of Australian children/adolescents who self-identified as having caring responsibilities will be matched with young people who have participated in Satellite's programs on demographics such as age and gender. The identified Longitudinal Study of Australian Children (LSAC) cohort will be used as a quasi "usual care" group on the outcomes of interest. Commencing in 2003, the LSAC is a national longitudinal study of data collected every two years on various child, parental and family characteristics that influence children's development at different ages . An a priori power analysis was conducted using G*Power version 3.1.9.7 software to ascertain the minimum sample size required to test the study hypotheses. Results indicated that the required sample size to achieve 80% power for detecting a medium effect at a significance criterion of a = 0.05 will be 29 per group (intervention [Satellite participants] and usual care [LSAC]) Table 3 Outcome measures for children and youth Awareness/use of coping strategies Reduced isolation/increase belonging Mental wellbeing Develop agency Items from the Longitudinal Study of Australian Children Kids Coping Scale Coping Across Situations Questionnaire Children & Youth Resilience Measure Strengths & Difficulties Questionnaire Children's Hope Scale Help seeking - support services Help seeking - family Mental wellbeing Caring responsibilities Belonging Children (<= 10 years) X - X - X - - - - - Children (11-13 years) - X X X X - - - - - Adolescents (14-17 years) - X X X X Xa X Xa Xa X Young adults (18+) X X X X Xa Xa Xa Xa Xa Note. a Denotes questions that will be compared with responses from LSAC participants (i.e., control group who have not accessed services from the Satellite Foundation) Creative outputs Across the various Satellite programs, young people are engaged in many different creative activities, including song writing and photovoice. All participants will be invited at program completion to share their creative outputs with a member of the evaluation team. This process will be very different from the interviews or questionnaire evaluation components. The way the young person wants to portray their creative work, and how they want to describe it will be up to them. Nonetheless, with the permission of the young person (and if under 16 years of age, the additional permission of their parent/caregiver), these artworks will be featured in the evaluation findings and reported as a means of describing the types of activities Satellite offers and the types of experiences and possible outcomes for the people involved . Ideally, a YAC representative will be available to engage with the young person about their experiences of creating these outputs and the meaning they attribute to the pieces. The messages conveyed will be either via video or in text and photographs. Data analysis Qualitative Transcripts for the one-off conversations will be analysed within an inductive qualitative paradigm, using the six-step reflexive thematic process recommended by Braun and Clarke . Thematic analysis is flexible to the format of the collected data and theoretically independent. Participants' and researchers' sociocultural interpretations are expected to influence the structure of themes. The analysis involves becoming familiar with the data by reading and re-reading each transcript, generating initial codes, searching for and then reviewing themes and then defining and naming themes. Intercoder consistency will be employed, whereby one member of the team will identify themes and follow this up with a group (evaluation team plus YAC) discussion of overlaps and divergences . Specific data sets will be linked to particular programs and then compared and contrasted to see if there are overall patterns across programs or unique results to any particular offering. Transcripts for the longitudinal conversations over three years will be managed using a longitudinal coding matrix template. A within-case analysis will initially be conducted with each interview set, then a cross-case analysis of patterns emerging over time across interviews . Quantitative The impact of Satellite on young people will be examined using the same outcome measures across the three time points using multi-level modelling (see Table 3). This will allow examination of whether the number of programs that young people enrol in over the 12 months results in different outcomes, as well as controlling for other variables such as age and gender. This model will also allow people to be entered into the analyses even if they do not complete the questionnaire at every time point (i.e., only complete the questionnaires at two of the three time points). Outcomes of interest will also be compared across groups (participants in the Satellite programs and the "usual care" (LSAC) participants) using repeated-measures MANOVA. Ethics Working with young people, especially those living with adversity, requires several ethical considerations. Parental consent is typically needed for children and young people under the age of 16, though previously, some parents from these families have actively or inadvertently limited their children's involvement in research . For instance, previous research has found that some parents are reluctant for their children to discuss what they considered to be family problems to outsiders while others consider that the process may be too upsetting for their children . Additionally, if parents are very unwell and/or hospitalised they will not be eligible to participate, given that the parent is not able to provide informed consent. In addition to parental consent for those aged under 16, we will also seek child assent for their involvement. Age appropriate language will be used to ensure informed consent/assent. As per Reupert et al. ,young people will be given the option of not being involved (even if their parent has given consent to their involvement), e.g., "You don't have to be involved in this interview if you don't want to be, no one will be angry with you". They will be told not only about their right to withdraw, but also how they might do this (e.g. say they have changed their mind) . As recommended by Spriggs , children and young people will be able to withdraw from the evaluation at any time up to when the results are written up in reports/publications. Children and young people will be assured that unless they are at risk themselves, or may harm someone else, no one outside of the evaluation team will have access to what they said. Interviews will be conducted in a COVID safe and accessible way. In discussing their involvement with Satellite, children and young people may become upset or uncomfortable and the potential for this will be clearly communicated. Given this, the interviewer will be sensitive to the verbal and nonverbal cues of the children and young people interviewed, alert to the need to pause or end the interview and offer further assistance and/or professional support as needed. At the conclusion of each interview, the child or young person will be asked whether they had any concerns or require any additional support. They will be provided with organisations to contact if they need support at a later stage. While acknowledging the potentially distressing nature of the evaluation process for children and young people, we are simultaneously mindful of Gladstone's et al. argument that although vulnerable, these young people are often insightful and autonomous, and have a right to discuss their experiences, especially concerning services that purport to support their needs. It can be cathartic to be part of an evaluation project, as it gives young people and children an opportunity to reflect on their individual circumstances; it can also be empowering to be consulted in a genuine, authentic manner. Ethics approval has been obtained from the Monash University Human Research Ethics Committee (MUHREC):project number 31,681. Findings and dissemination Throughout the project, consistent with participatory methods, all the collected, de-identified results will be workshopped with the YAC to discuss program implications. Evaluation reports will be generated six times at six-monthly intervals over the three years with a final report submitted at the end of the project. In order to make the various evaluation reports accessible to various audiences, especially young people, findings will be presented in diverse ways, tailored to the needs of different audiences, in written form and/or through video, and infographics. Analysed data will be presented to the YAC and Satellite staff every six months over the three-year project, with subsequent recommendations made for program delivery and the evaluation design. If Satellite decides to make changes in a program, consideration will be made as to evaluation implications e.g. the addition of other measures, or additional interview questions. Thus, subsequent program changes will be monitored and reflected in the evaluation plan. The final evaluation report will be produced in multiple formats; one specifically with the funders as the intended audience, and another for the young people using accessible language, with both reports being publicly available. The YAC will be consulted as to the best ways of disseminating results to the community, with an option also of a public event with media invited at the end of the project. Along with evaluation results, the number of participants who were involved in the various programs will be recorded, as there will likely be more who participate in the programs than participate in the evaluation. This information will include a breakdown of different demographic groups and identify those groups that Satellite have not yet been successful in attracting. For example, Maybery et al. found it difficult to recruit young men into a similar early intervention program. Together with the YAC, strategies will be developed to target any missing groups into programs or efforts made to ascertain why specific demographic groups are not being recruited into Satellite programs. Referral sources will be reported, identifying those organisations referring young people to Satellite, and arguably more importantly, which services are not, which will allow for targeted messages to selective services. Discussion In program evaluation, there is a need to balance the accountability needs of funders with the needs of organisations and their clients. Evaluations need to deliver rigorous, objective data that inform government funders and organisations whether the programs being delivered are making a positive difference to those they are intended. For evaluations involving young people, their involvement in the evaluation process is critical to ensure that findings are relevant and can be used to inform ongoing quality improvement, program development and decision making about the long-term offerings of programs. There are many different ways young people may participate in program development and evaluation, ranging from being merely informed about programs through to active co-design opportunities where young people are equal partners in decision-making [20-22]. This study protocol offers an approach that provides multiple opportunities for different groups of young people to be involved, although it is at the collaborative level rather than full co-design. Nonetheless, through collaboration, involvement and consultation, we aim to provide opportunities to young people for empowerment and self and professional development while at the same time meeting the needs of government funders. Despite the broad acknowledgement that it is critical to include end-user stakeholders in program development and evaluation, many participatory designs do not explicitly describe or reflect on the specific participatory processes employed . LeRoux described how some non-for-profit organisations spend disproportionate time addressing the needs of funding agencies at the expense of client-related activities, albeit in the interests of maintaining a funding flow to sustain their client-related work. This protocol provides one example of how to balance the needs of funding departments and still include the voices and experiences of young people, a process that might be used and adapted by the broader policy community. Conclusion Data generated from this novel, mixed methods participatory evaluation will be used to further inform programs and services at Satellite for young people who have a parent or a sibling who experiences mental health challenges. The longitudinal interviews and the utilization of creative outputs have not previously been used in evaluations of this type and have the potential to shed new light on the change processes involved in similar programs. The participatory evaluation design and methodologies employed could be used by other services when conducting similar evaluations. When evaluating programs for young people, tension may exist between meeting the needs of funders and the needs and preferences of end users, especially young people. This protocol highlights how this tension might be addressed by using validated outcome measures and rigorous evaluation design alongside the provision of multiple opportunities and approaches for collaborating with young people about what is being evaluated and how. Acknowledgements The authors acknowledge Lottie O'Dea and Rose Cuff, both from Satellite, for coordinating the work with the Satellite Youth Advisory Council and providing background information about Satellite. Author Contribution AR, KF, LPa, SL, NF, NN, RH, LPe, CO were all involved in the conceptualization and proposed methodology. AR wrote the first draft. All authors contributed to the article and approved the submitted version. Funding AR, KF, LPa, SL, NF, NN, RH receive funding from the Victorian Department of Health to evaluate the Satellite Foundation. LPe and CO are members of the Satellite Youth Advisory Committee and in that capacity receive funding from Satellite. Data Availability The datasets used and analysed during the current study will be available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate Permission to conduct this project was obtained from the Monash University Human Ethics Committee, project number 31681. All methods will be conducted in accordance with the ethical standards of the declaration of Helsinki. 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PMC10000350 | Egypt J Bronchol The Egyptian Journal of Bronchology 2314-8551 Springer Berlin Heidelberg Berlin/Heidelberg 189 10.1186/s43168-023-00189-3 Research Short-term evaluation of motor and sensory nerve conduction parameters in COVID-19-associated peripheral neuropathy patients Shaddad Ahmad M. [email protected] 1 Hussein Aliae A. R. Mohammed [email protected] [email protected] 1 Tohamy Amal Mohamed Aly [email protected] 2 Khalil Waleed Gamal Elddine [email protected] 1 1 grid.252487.e 0000 0000 8632 679X Chest Department, Faculty of Medicine, Assiut University, Assiut, 71515 Egypt 2 grid.252487.e 0000 0000 8632 679X Neuropsychiatry Department, Faculty of Medicine, Assiut University, Assiut, 71515 Egypt 10 3 2023 10 3 2023 2023 17 1 1513 2 2023 4 3 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit Background Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is mostly associated with upper and lower respiratory tract manifestations. However, coronavirus disease 19 (COVID-19) can result in a wide range of other systemic symptomatology, including neuropsychiatric, psychological, and psychosocial impairments. Literature regarding neurological compromise, including neuropathy and sensory and motor affection associated with COVID-19, is still limited. This study aims to evaluate the sensory, motor neuropathy, and secondary neurological impairment among patients with mild to moderate coronavirus disease associated with peripheral neuropathy within 1 month. Methods Forty participants, including 20 mild to moderate COVID-19 patients with peripheral neuropathy and 20 age and gender-matched healthy volunteers, were recruited in this case/control study. Laboratory evaluation focused on C-reactive protein (CRP) and D-dimer levels. Oxygen saturation for all participants was recorded. The neurophysiological study included motor nerve study, sensory nerve study, and F wave study for upper and lower limbs were done. Results The two groups were similar regarding baseline data. Neurological symptoms' onset in the COVID-19 group ranged from 4 to 24 days. Levels of CRP and D-dimer levels were significantly higher in patients versus the control group. Motor nerve conduction (MNC) amplitude and latency for the median nerve were significantly compromised among the COVID-19 group. The MNC latency and F wave latency for the posterior tibial nerve were significantly higher in the COVID-19 group. The CRP and D-dimer levels were associated with a significant positive correlation with a latency of median nerve MNC, sensory nerve conduction (SNC), and f-wave; latency of MNC and F wave of the posterior tibial nerve; and SNC latency for sural nerve. Conclusion neurological involvement can occur in mild to moderate cases of SARS-COV-2 infection and add to the burden of the disease. Neurological symptoms in the course of COVID-19 disease should be interpreted cautiously, and appropriate diagnosis, including nerve conduction studies and management, should be considered. Trial registration ClinicalTrials.gov. NCT05721040. Keywords COVID-19 Nerve conduction studies Peripheral neuropathy Complication Motor and sensory function Nerve conduction velocity Nerve conduction amplitude Nerve conduction latency F wave latency issue-copyright-statement(c) The Egyptian Scientific Society of Bronchology 2023 pmcIntroduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first emerged in Wuhan, China, can result in a wide variety of symptomatology ranging from asymptomatic infection up to pneumonia, respiratory failure, or even death . Respiratory involvement is the prevalent form of COVID-19 disease; however, growing evidence suggests neurological manifestations to be a direct consequence and even the presenting manifestation in a large proportion of patients . Cerebrovascular diseases, including stroke, encephalitis, neuropathy, visual pathway abnormality, and Guillain-Barre syndrome, were recorded. Other common features encountered early in the course of infection were loss of smell (anosmia) and taste (ageusia) [3-6]. Several theories emerged to explain neurological manifestations, including direct neuroinvasion by the coronavirus, explained through the activation of the angiotensin-converting enzyme 2 (ACE-2) receptor expressed in both capillary and neuronal endothelium . Dysregulated immune response, hypoxemia, multiorgan involvement, and increased prothrombin time and coagulopathy are other explanations . This study aims to evaluate the pattern of motor and sensory, and neurological affections in mild to moderate COVID-19 with associated peripheral neuropathy patients and explore the relationship between inflammatory status and neurological deficits. Patients and methods Study design and participants This prospective case-control study was conducted in the Chest Department, Faculty of Medicine, Assiut University, and the Neurology Department, Faculty of Medicine, Assiut University, between October 2021 and April 2022. Twenty RT-PCR-confirmed mild to moderate COVID-19 patients with peripheral neuropathy presented within 1 month of acute disease at outpatient clinics of the Chest and Neurology Departments were recruited and twenty healthy age and gender-matched volunteers. Inclusion and exclusion criteria All patients with confirmed RT-PCR COVID-19 infection with mild to moderate severity based on the Egyptian Ministry of Health (MOH) protocol (version 1.4, November 2020) with neurological symptoms suggestive of peripheral neuropathy were eligible for participation in the current study. Exclusion criteria were patients presenting with neurological manifestations other than peripheral neuropathy, such as stroke, cerebral hemorrhage, encephalitis, or meningitis. Patients with any medical condition or comorbidities that may affect the result of the study as diabetes, arthritis, and carpel tunnel syndrome were excluded. Severe COVID-19 patients with a critical condition that needs hospitalization and ventilatory support were also excluded from the study. Clinical and laboratory assessment All patients were subjected to intense history taking, including the onset of the COVID-19 infection and the start of neurological symptoms, careful clinical examination, and neurological assessment. All patients and control groups had oxygen saturation, CPR, and D-dimer measurement at the time of the study. Neurophysiological study All studies were conducted using A Nihon Kohden Machine model 9400 (Tokyo, Japan). The motor nerve study was performed in the median and posterior tibial nerve to assess the motor function of the upper and lower limbs. A standard procedure with concentric needle electrodes is used to assess motor nerve conduction velocity. Supramaximal intensity stimulation with a duration of 0.2 ms with a rate of one per second was performed. Compound motor action potential (CMAP), motor nerve conduction velocity (MNCV), and nerve conduction latency were recorded. The sensory nerve study was done for the median and sural nerves to estimate the peripheral neurological function of both upper and lower limbs. The analysis was performed using stimulating ring electrodes placed over the middle and proximal phalanxes of the second and third fingers. In contrast, the recording electrode is placed over the palm in a position 1-2 cm proximal to the proximal crease of the palm. The sensory nerve conduction study of the sural nerve was performed by placing surface recording electrodes over the posterior aspect of the calf at a point between the middle and lower thirds of the leg, just lateral of the midline. Stimulating electrodes are placed behind and below the lateral malleolus over the sural nerve. Sensory motor nerve conduction amplitude, latency, and velocity were recorded. F wave study was performed for the upper limb in the median nerve by placing the recording electrode at the abductor pollices brevis muscle. In contrast, the recording electrodes were placed two cm distal near the tendon insertion. For testing the F wave in the posterior tibial nerve for the lower limb, recording electrodes were placed over the abductor hullucis muscle, and the stimulating electrodes were placed at the malleolus. For F wave recording, a supramaximal stimulus was performed, ten stimuli were given, and their average was recorded. For all parameters of neurophysiological studies, the values below the 95th percentile or +- 2SD of control are considered abnormal. Diffuse axonal neuropathy was diagnosed by the reduction of CMAP amplitude with standard shape and duration and with normal or minimal disturbance of nerve conduction velocity. In contrast, diffuse demyelinating neuropathy was diagnosed by increased nerve conduction latency, preserved amplitude, and average nerve conduction velocity. Statistical analysis and sample size were performed using the SPSS program (version 20, IBM and Armonk, New York). The Mann-Whitney test was used for continuous data, while chi2 test compared nominal data. Different correlations of continuous variables in the study were assessed with Spearman's correlation. The sample size was estimated by Open Epi V.3.01 computer program. Ethical considerations All participants subjected to the study were asked to apply informed written consent; the research's nature, procedures, and possible side effects were clearly explained. The Faculty of Medicine, Assiut University's ethical committee approved the study protocol under the Declaration of Helsinki. Results In the current study, we recruited twenty COVID-19 patients with confirmed diagnoses by RT-PCR with neurological symptoms and twenty genders and age-matched healthy volunteers. The demographic characteristics of the patients and the control group are shown in (Table 1). There was no significant difference between the two groups regarding age, gender, education, smoking, and residence. The mean onset of neurological symptoms is 11.95 +- 5.9 days and ranges from 4 to 24 days.Table 1 Demographic data of the COVID-19 patients with peripheral neuropathy and control group (n = 40) COVID-19 group N = 20 Control group N = 20 P value Gender Male 17 (85%) 16 (80%) 0.50 Female 3 (15%) 4 (20%) Age (years) Mean +- SD 45.05 +- 11.05 42.35 +- 11.05 0.745 Range (21-68) (20-59) Smoking Smoker 8 (40%) 9 (45%) 0.465 Non-smoker 11 (55%) 8 (40%) X smoker 1 (5%) 3 (15%) Education Literate 15 (75%) 17 (85%) 0.347 Illiterate 5 (25%) 3 (15%) Residence Urban 13 (65%) 16 (80%) 0.480 Rural 7 (35%) 4 (20%) The onset of neurological symptoms (Range) 11.95 +- 5.90 (4-24) -- Data expressed as frequency (percentage) and mean (SD). P value was significant if < 0.05 There were significant differences between the patient group and the control group regarding; CRP level, where the mean value in the COVID-19 group was 39.7 +- 7.46 and 6.3 +- 2.15 in the control group with a p value of < 0.001, D-dimer with a mean value in the patients' group of 983.6 +- 324.88 and the control group of 315.3 +- 63.03 with a p value of < 0.001 and oxygen saturation in the COVID-19 group with the mean of 96.95 +- 1.35 and the control group of 98.5 +- 0.61 with a p value of 0.009 (Table 2).Table 2 Laboratory data and oxygen saturation level of the COVID-19 patients with peripheral neuropathy and control group (n = 40) COVID-19 group N = 20 Control group N = 20 P value CRP 39.7 +- 7.46 6.30 +- 2.15 < 0.001* D-dimer 983.6 +- 324.88 315.30 +- 63.03 < 0.001* SpO2 96.95 +- 1.35 98.5 +- 0.61 0.009* Data expressed as frequency (percentage) and mean (SD). P value was significant if < 0.05 CRP C-reactive protein, CRP C-reactive protein, SpO2 Saturation of peripheral oxygen Regarding the nerve conduction study in both groups, there was a significant difference between the two groups in median nerve motor nerve conduction amplitude (MNCA) with a mean of 8.88 +- 2.6 and 9.04 +- 2.12 in the control group with a P value of 0.039. There was a significant statistical difference between the two groups in median nerve motor nerve conduction latency (MNCL) with a mean of 5.1 +- 1.34 and 3.29 +- 0.64 in the control group with a P value of < 0.001. There was a significant statistical difference between the two groups in posterior tibial nerve motor nerve conduction latency (MNCL) with a mean of 3.99 +- 0.99 and 3.06 +- 0.61 in the control group with a P value of 0.007. There was a significant statistical difference between the two groups in Posterior tibial nerve F wave latency with a mean of 52.28 +- 4.95 and 47.25 +- 3.17 in the control group with a P value of 0.002 (Table 3).Table 3 Electrophysiological measurements of the COVID-19 group with the peripheral neuropathy and control group (n = 40) COVID-19 group N = 20 Control group N = 20 P value MNC amplitude (mV) 8.88 +- 2.60 9.04 +- 2.12 Median nerve 5.12-13.5 6.43-17.10 0.039* MNC latency (ms) 5.1 +- 1.34 3.29 +- 0.64 Median nerve 2.59-7.45 2.16-4.78 < 0.001* MNC velocity (m/s) 58.06 +- 6.4 58.18 +- 7.30 Median nerve 42.40-69.30 45.92-70.9 0.220 SNC amplitude (mV) 21.18 +- 8.76 21.19 +- 5.94 Median nerve 11.5-45.4 12.45-38 0.091 SNC latency (ms) 4.33 +- 0.91 3.47 +- 0.72 Median nerve 3.08-6.20 2.76-5.23 0.305 SNC velocity (m/s) 51.7 +- 5.62 51.99 +- 6.84 Median nerve 42.9 - 59.24 41.29-69.2 0.753 F wave latency (ms) 33.03 +- 4.59 30.14 +- 6.16 Median nerve 26.6-39.3 24.56-44.56 0.389 MNC amplitude (mV) 12.30 +- 2.15 12.84 +- 2.70 Post Tibial nerve 7.39-17.53 8.24-19.1 0.366 MNC latency (ms) 3.99 +- 0.99 3.06 +- 0.61 Post Tibial nerve 2.25-5.6 2.29-4.22 0.007* MNC velocity (m/s) 56.6 +- 5.44 57.05 +- 5.24 Post Tibial nerve 49.2-69.1 51.2-68.3 0.703 SNC amplitude (mV) 28.1 +- 4.44 28.25 +- 4.44 Sural nerve 21.2-35.3 21.3-36.2 0.956 SNC latency (m/s) 3.81 +- 0.6 3.01 +- 0.59 Sural nerve 2.68-4.70 2.11-3.98 0.760 SNC velocity (m/s) 56.7 +- 8.25 57.15 +- 6.05 Sural nerve 43.1-76.2 47.1-68.4 0.281 F wave latency (ms) 52.28 +- 4.95 47.25 +- 3.17 Post Tibial nerve 43.2-61.6 42.3-52.1 0.002* Data expressed as frequency (percentage) and mean (SD). P value was significant if < 0.05 MNC Motor nerve conduction, SNC Sensory nerve conduction We correlated the laboratory data and age with the neurophysiological parameters. There was a positive correlation between CRP level and median nerve (MNCL) with r = 0.787, p value < 0.001; median nerve (SNCL) with r = 0.668, p value < 0.001; median nerve F wave latency with r = 0.386, p value < 0.014; posterior tibial nerve (MNCL) with r = 0.611, p value < 0.001; sural nerve (SNCL) with r = 0.624, p value < 0.001; and posterior tibial nerve F wave latency with r = 0.544, p value < 0.001. There was a positive correlation between D-dimer level and median nerve (MNCL) with r = 0.702, p value < 0.001; median nerve (SNCL) with r = 0.590, p value < 0.001; median nerve F wave latency with r = 0.418, p value < 0.007; posterior tibial nerve (MNCL) with r = 0.493, p value < 0.001; sural nerve (SNCL) with r = 0.657, p value < 0.001; and posterior tibial nerve F wave latency with r = 0.557, p value < 0.001. There was a negative correlation between oxygen saturation and median nerve (SNCL) with r = - 0.542, p value < 0.001; median nerve F wave latency with r = - 0.364, p value < 0.021; posterior tibial nerve (MNCL) with r = - 0.565, p value < 0.001; sural nerve (SNCL) with r = - 0.640, p value < 0.001; posterior tibial nerve F wave latency with r = - 0.546, p value < 0.004; and positive correlation between oxygen saturation and median nerve (MNCL) with r = 0.619, p value < 0.001; median nerve (SNCV) with r = 0.328, p value 0.039; and posterior tibial nerve (CMAP) with r = 0.312, p value 0.049) (Table 4).Table 4 Correlation of age, CRP value, D-dimer value, and SpO2 with nerve conduction study results in COVID-19 cases with peripheral neuropathy (n = 20) Age CRP D dimer SpO2 r P R P R P r P MNC amplitude Median nerve 0.055 0.735 - 0.079 0.629 - 0.143 0.379 0.149 0.358 MNC latency Median nerve - 0.089 0.585 0.787 < 0.001* 0.702 < 0.001* 0.619 < 0.001* MNC velocity Median nerve - 0.128 0.431 - 0.049 0.766 - 0.048 0.769 0.008 0.959 SNC amplitude Median nerve - 0.007 0.966 - 0.212 0.189 0.113 0.489 0.112 0.492 SNC latency Median nerve - 0.003 0.988 0.668 < 0.001* 0.590 < 0.001* - 0.542 < 0.001* SNC velocity Median nerve 0.061 0.710 - 0.082 0.616 - 0.121 0.457 0.328 0.039* F wave latency Median nerve 0.137 0.399 0.386 0.014* 0.418 0.007* - 0.364 0.021* MNC amplitude Post-tibial nerve - 0.300 0.060 - 0.051 0.757 - 0.076 0.642 0.312 0.049* MNC latency Post = tibial nerve - 0.002 0.992 0.611 < 0.001* 0.493 0.001* - 0.565 < 0.001* MNC velocity Post-tibial nerve - 0.015 0.929 - 0.068 0.676 - 0.212 0.188 0.197 0.223 SNC amplitude Sural nerve - 0.149 0.358 - 0.111 0.494 - 0.065 0.690 0.132 0.417 SNC latency Sural nerve 0.018 0.914 0.624 < 0.001* 0.657 < 0.001* - 0.640 < 0.001* SNC velocity Sural nerve 0.202 0.211 0.004 0.980 0.005 0.978 0.002 0.98 F wave latency Post-tibial nerve 0.046 0.777 0.544 < 0.001* 0.557 < 0.001* - 0.446 0.004* Correlation for variables in the study was determined with spearman's correlation. r correlation coefficient rho. P value: was significant if < 0.05 CRP C-reactive protein, SpO2 Saturation of peripheral oxygen, MNC Motor nerve conduction, SNC Sensory nerve conduction Stratification of the motor nerve conduction study of the COVID-19 group revealed that 10% of patients had motor axonal neuropathy, 15% mixed motor neuropathy, and 55% demyelinating motor neuropathy, while 20% of patients with a normal study (Fig. 1). Assessment of the sensory nerve conduction study showed that 5% of patients had sensory axonal neuropathy, 15% mixed sensory neuropathy, and 45% sensory demyelinating neuropathy, while 35% of patients with a normal study (Fig. 2).Fig. 1 Frequency and types of motor neuropathies among COVID-19 groups (n = 20) Fig. 2 Frequency and types of sensory neuropathies among COVID-19 groups (n = 20) Discussion In the current study, we enrolled twenty mild to moderate COVID-19 patients with peripheral neuropathy and compared them with 20 age and sex-matched healthy controls. Neurophysiological studies revealed a significant difference between the two groups in compound motor action potential and motor nerve conduction latency of the median nerve and motor nerve conduction latency of the posterior tibial nerve and F wave latency of the posterior tibial nerve. There was a positive correlation between oxygen saturation and SNC velocity of the median nerve, the MNC amplitude of the post-tibial nerve. There was a strong negative correlation between SpO2 and MNC latency, SNC latency, and F wave latency of the median nerve. Also, strong negative correlation between SpO2 and MNC latency of the posterior tibial nerve, SNC latency of the sural nerve, and F wave latency of the posterior tibial nerve. There was a strong positive correlation between D-dimer level and CRP level with MNC, SNC, and F wave latencies of the median nerve, MNC and F wave latencies of the posterior tibial nerve, and SNC latency of the sural nerve. Motor axonal neuropathy was observed in 10% of patients; motor demyelinating neuropathy was observed in 55%, and mixed motor neuropathy in 15%. Sensory axonal neuropathy was observed in 5% of patients; demyelinating sensory neuropathy was observed in 45%, and mixed sensory neuropathy in 15%. Neurological affection is observed throughout the course of the COVID-19 infection. A study by Mao and his colleagues on 214 COVID-19 patients observed the presence of neurological manifestations in 36% of the study group . Although SAR-COV-2 is not documented to be present in CSF of affected patients during the course of COVID-19 infection; there is a strong association between the presence of neurological symptoms and SARS-COV-2 infection . In an attempt to explain the pathophysiology of neurological affection in SARS-COV-2 infection; the international human cell atlas community has reported increased expression of two key co-receptors during SARS-COV-2 infection, namely ACE2 and TMPRSS2 co-receptors . Another theory is the para-infectious neurological syndrome due to SARS-COV-2 infection . A possible etiological explanation is the host immune response to SARS-COV-2 and the development of cytokine storms . Peripheral nervous system and muscle affection is common through the course of SARS-COV-2 infection with a median of 7 days (range 7-24) . In agreement with our study, EL-Leithy et al. enrolled 60 COVID-19 patients in 3 groups (20 mild, 20 moderate, and 20 severe cases) with a significant difference in upper and lower nerve conduction study between the patient groups and the control group, which were significantly correlated to the CRP level . Elshebawy et al. enrolled 42 patients; 23 of them were in the first wave of COVID-19, and 19 were in the second wave; the characteristics of the study groups showed the presence of acute inflammatory demyelinating neuropathy in 47.8% of the 1st wave patients, and 73.7 in the 2nd wave patients and the demyelinating with secondary axonal affection in 13% of the 1st wave patients and 10.5% of 2nd wave patients . Ellul and colleagues using data available up to May 19, 2020. COVID-19 cases based on Johns Hopkins COVID-19 Dashboard demonstrated that peripheral neuropathy is present in 0.05% of COVID-19 patients . In a Cohort of Egyptian Patients with COVID-19, Mekkawy and colleagues described peripheral nervous manifestations in 29.04% of patients early from the 1st day to 7 days of infection and late from the 8th to the 15th day of affection. Muscle injury was present in 1.37% of patients, and symmetrical lower limb distal sensory neuropathy in 1.55% of the patients . Bagnato and colleagues evaluated 21 patients after COVID-19 infection; neuromuscular affection was demonstrated in 17 patients. Affection varied between critical illness myopathy (CIM), critical illness polyneuropathy (CIP), Guillain-Barre syndrome, and peroneal nerve injury . Conclusion Neurological affection including peripheral neuropathy associated with SARS-COV-2 should not be overlooked. Affected personnel may be limited in number but during a massive pandemic, this can have a tremendous effect. Careful short-term neurological assessment is needed for symptomatic patients and can result in early detection and appropriate management. Limitations Long-term follow-up can be done in the future to identify the long-term neurological effects of SARS-COV-2. Abbreviations ACE-2 Angiotensin-converting enzyme 2 COVID-19 Coronavirus disease 2019 CRP C-reactive protein CMAP Compound motor action potential EMG Electromyography MOH Ministry of Health MNC Motor nerve conduction MNCA Motor nerve conduction amplitude MNCL Motor nerve conduction latency MNCV Motor nerve conduction velocity RT-PCR Reverse transcription-polymerase chain reaction SARS-COV-2 Severe acute respiratory syndrome coronavirus 2 SNC Sensory nerve conduction SNCA Sensory nerve conduction amplitude SNCL Sensory nerve conduction latency SNCV Sensory nerve conduction velocity SPO2 Saturation of peripheral oxygen SPSS Statistical Package for Social Sciences Acknowledgements None. Authors' contributions AMS, AARMH, AMAT, and WGEK: conception and design. AMS, AMAT, and WGEK: data collection. AMS and WGEK: statistical analysis. AMS, AARMH, AMAT, and WGEK: medical writing. The authors revised the manuscript. The authors read and approved the final manuscript. Funding None. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Declarations Ethics approval and consent to participate: The study was approved by the institutional review board and ethical committee of the Faculty of Medicine--Assiut University in compliance with the Helsinki declaration (IRB: 04-2023-300077). Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Di Gennaro F Pizzol D Marotta C Antunes M Racalbuto V Veronese N Smith L Coronavirus diseases (COVID-19) current status and future perspectives: a narrative review Int J Environ Res Public Health 2020 17 8 2690 10.3390/ijerph17082690 32295188 2. 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PMC10000351 | Sci Rep Sci Rep Scientific Reports 2045-2322 Nature Publishing Group UK London 30690 10.1038/s41598-023-30690-0 Article Inactivation and spike protein denaturation of novel coronavirus variants by CuxO/TiO2 nano-photocatalysts Tatsuma Tetsu [email protected] 12 Nakakido Makoto 1 Ichinohe Takeshi [email protected] 3 Kuroiwa Yoshinori 2 Tomioka Kengo 4 Liu Chang 4 Miyamae Nobuhiro 4 Onuki Tatsuya 1 Tsumoto Kouhei [email protected] 13 Hashimoto Kazuhito 1 Wakihara Toru 1 1 grid.26999.3d 0000 0001 2151 536X School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-Ku, Tokyo, 113-8656 Japan 2 grid.26999.3d 0000 0001 2151 536X Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-Ku, Tokyo, 153-8505 Japan 3 grid.26999.3d 0000 0001 2151 536X Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-Ku, Tokyo, 108-8639 Japan 4 grid.471196.c 0000 0004 0632 2545 Nippon Paint Co., Ltd, 4-1-15 Minamishinagawa, Shinagawa-Ku, Tokyo, 140-8675 Japan 10 3 2023 10 3 2023 2023 13 40331 4 2022 28 2 2023 (c) The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit In order to reduce infection risk of novel coronavirus (SARS-CoV-2), we developed nano-photocatalysts with nanoscale rutile TiO2 (4-8 nm) and CuxO (1-2 nm or less). Their extraordinarily small size leads to high dispersity and good optical transparency, besides large active surface area. Those photocatalysts can be applied to white and translucent latex paints. Although Cu2O clusters involved in the paint coating undergo gradual aerobic oxidation in the dark, the oxidized clusters are re-reduced under > 380 nm light. The paint coating inactivated the original and alpha variant of novel coronavirus under irradiation with fluorescent light for 3 h. The photocatalysts greatly suppressed binding ability of the receptor binding domain (RBD) of coronavirus (the original, alpha and delta variants) spike protein to the receptor of human cells. The coating also exhibited antivirus effects on influenza A virus, feline calicivirus, bacteriophage Qb and bacteriophage M13. The photocatalysts would be applied to practical coatings and lower the risk of coronavirus infection via solid surfaces. Subject terms Nanoparticles Photocatalysis Biochemistry Ministry of Education, Culture, Sports, Science and Technology of JapanJPMXP09A21UT0198 Tatsuma Tetsu Japan Agency for Medical Research and Development JP223fa627001 Ichinohe Takeshi issue-copyright-statement(c) The Author(s) 2023 pmcIntroduction Coronavirus disease 2019 (COVID-19) was first reported as a pneumonia of unknown cause in December 2019, and its pathogen was identified as a novel coronavirus (SARS-CoV-2) in January 2020. The disease caused an outbreak, and the World Health Organization (WHO) declared a pandemic in March 2020. The coronavirus is characterized by its strong infectivity. Some of the mutation variants are known to be more infectious, and were classified as variants of concern. The most major pathway of the COVID-19 transmission is believed to be airborne aerosol including viruses released from infected persons. However, there are also pathways via solid surfaces including walls, doorknobs, handrails and furniture1. Removal of viruses from the surfaces would therefore reduce the risk of transmission of the disease. Photocatalyst is one of the promising materials for virus removal. A decade ago, Hashimoto and co-workers2,3 reported that TiO2 photocatalysts modified with CuxO inactivate bacteriophage Qb. The CuxO/TiO2 composites absorb visible light and electrons are excited from the TiO2 valence band (VB) to Cu(II), and Cu(II) is reduced to Cu(I), which inactivates bacteriophage. The positive holes generated in the TiO2 VB take electrons from ambient water, so that TiO2 is initialized. Although Cu(I) in CuxO is ready to be oxidized back to Cu(II) by ambient oxygen, the CuxO with Cu(I) is renewed under illumination on the basis of the photocatalytic effect mentioned above. With these mechanisms in mind, we developed novel photocatalysts that inactivate the novel coronavirus and its variant, as well as some other viruses. White and translucent paint coatings containing those photocatalysts were also developed. In the previous work, a rutile TiO2 powder of 0.1 - 0.3 mm or larger in size was used as a typical base semiconductor material, and CuxO nanoparticles of ~ 5 - 8 nm diameter were deposited onto the TiO2 powder2,3. Considering its large composite size and high refractive index of rutile TiO2 of 2.5 - 3.0 in the visible wavelength range4, the composite particles should tend to settle in a dispersion5 and reflect or scatter visible light greatly. In the present work, we employed a sol containing rutile TiO2 nanoparticles of ~ 4 - 8 nm in size, and deposited CuxO clusters of < 2 nm in size to develop photocatalysts with a high active surface area. In addition, because of the nanoscale particle size, we can fabricate translucent coatings, films and solid substrates containing the photocatalysts, which possess high designability and allow one to irradiate them both from the frontside and backside. An additional advantage of the small nanoparticles is high suspendability without sedimentation, because sedimentation velocity of nanoparticles smaller than 10 - 100 nm is negligibly low5. This is important point because only photocatalysts exposed at the coating surface are expected to affect viruses. The present sol-based wet process for preparing nano-photocatalyst coatings would allow various types of antivirus materials including paints, varnishes, gels and spray liquids to be developed. A sol containing anatase TiO2 nanoparticles (~ 10 nm) was also used in the present study in place of the rutile TiO2 sol. We found that the nano-photocatalyst coatings renew CuxO under visible light illumination and inactivate a variety of viruses including the original and alpha variants of novel coronavirus. In order to elucidate the inactivation mechanisms, we prepared recombinant proteins of the receptor binding domain (RBD) of spike protein derived from the original, alpha and delta variants. The photocatalysts greatly suppressed binding ability of RBD to human angiotensin converting enzyme-2 (ACE2), the receptor for the coronavirus. Methods Preparation of CuxO/TiO2 nanocomposites A rutile TiO2 slurry (Tayca TS-310, TiO2 diameter ~ 4 - 8 nm) and an anatase TiO2 slurry (Taki Chemical M-6, TiO2 diameter ~ 10 nm) were employed as base semiconductor materials, and aqueous solutions of CuCl2, glucose as a reducing agent and NaOH were added to either of the slurries. The mol ratio of Cu to Ti was 1/20, unless otherwise noted (concentrations: 437 or 404 mM TiO2; 62 or 57 mM glucose; 47 or 48 mM NaOH; 22 or 20 mM CuCl2 for rutile and anatase, respectively). We raised its temperature to 90 degC and stirred it for 1 h to reduce Cu(II) ions to Cu(I) and deposit CuxO, which is a mixture of Cu2O and CuO, onto TiO2 nanoparticles. Preparation of latex paints A white pigment based on rutile TiO2 coated with Al2O3 and ZrO2 (CR-97, Ishihara Sangyo; ~ 400 nm diameter), which has no photocatalytic activity because it is coated with an inert layer, was employed as a typical pigment for practical paints. It was mixed with CaCO3, diatomite, wetting and dispersing additive (Disperbyk 190, BYK), defoamer (BYK-011, BYK) and water (weight ratio = 40:20:10:5:1:13). The slurry thus obtained was further mixed with acrylic emulsion (Watersol AC 3080, DIC), 2,2,4-trimethyl-1,3-pentanediolmonoisobutyrate and the CuxO/TiO2 slurry (weight ratio = 40:1:20) to obtain a photocatalytic latex paint. For studies on antivirus effects, the paint was applied onto a glass plate (20 x 20 mm). Characterization A solar simulator (AM1.5, ~ 100 mW cm-2; BSS-T150, Bunko Keiki) and fluorescent lamps for consumer use were used for light irradiation. Absorption spectra were collected by using a spectrophotometer V-670 (Jasco). Scanning transmission electron microscopy (STEM) and high resolution HAADF-STEM analysis were performed by using JEM-ARM200F Thermal FE STEM (JEOL). For energy dispersive X-ray spectroscopy (EDS), DRY SD100GV (JEOL) was used. Evaluation methods for antivirus activity are described in Results and discussion section. Expression and purification of recombinant proteins As for RBD protein, gene fragments encoding RBD protein were cloned into pcDNA 3.4, an expression vector for mammalian expression system (Thermo Fisher Scientific) with a signal peptide sequence, His-tag, and TEV protease recognition sequences at the N-terminal end. Expi293 cells (Thermo Fisher Scientific) were transfected with the expression vector and supernatant was collected 4 days after transfection. The supernatant was dialyzed against a binding buffer consisting of 20 mM Tris-HCl (pH 8.0), 500 mM NaCl and 5 mM imidazole and loaded on Ni-NTA resin (Qiagen) equilibrated with the binding buffer. The resin was washed with a wash buffer consisting of 20 mM Tris-HCl (pH 8.0), 500 mM NaCl and 20 mM imidazole and subsequently RBD protein was eluted by a buffer consisting of 20 mM Tris-HCl (pH 8.0), 500 mM NaCl and 500 mM imidazole. The eluted RBD protein was dialyzed against binding buffer with TEV protease to cleave the His-tag, followed by loading on Ni-NTA resin. Flowthrough fraction was collected and further purified by size exclusion chromatography using HiLoad 26/600 Superdex 75-pg column (Cytiva) equilibrated with PBS. As for ACE2 protein, a gene fragment encoding ACE2 protein was also cloned into pcDNA 3.4 vector and used for transfection of Expi293 cells. The supernatant of infected cells was collected 5 days after transfection and ACE2 protein was purified using Ni-NTA and size exclusion chromatography in the same way as RBD protein. The monomer peak fractions were collected for each protein and the purity was evaluated by SDS-PAGE followed by Coomassie staining. Protein denaturation and ELISA assay RBD proteins were incubated with a photocatalyst at 4 degC overnight. Subsequently, RBD proteins were immobilized on an ELISA plate (Corning) at 4 degC overnight. The protein immobilized wells were blocked by skimmilk containing PBS-T buffer and ACE2 proteins were added to each well and incubated at room temperature for 1 h. The wells were washed 3 times with PBS-T and bound ACE2 were detected with anti-His-tag antibody conjugated with HRP (MBL Life Science). The wells were washed 3 times with PBS-T and developed with TMB substrate mixture (Cosmobio) and stopped with TMB stop buffer (ScyTek Laboratories). The absorbance at 450 nm for each well was measured using Pherastar plate reader (BMG Labtech). Results and discussion Preparation and characterization of CuxO/TiO2 The colour of the rutile-based CuxO/TiO2 suspension was a greenish gray (Fig. 1a), and its difference spectrum after the deposition was characterized by an absorption band at 400 - 500 nm and a broad peak at ~ 800 nm (Fig. 1b). The latter broad peak suggests that the suspension contains excess Cu2+ ions. Since the former absorption band appears to be due to a semiconductor, we examined Tauc plots and obtained the band-gap values of ~ 3.0 and ~ 2.8 eV on the assumption of the direct and indirect transitions, respectively. Because Cu2O and CuO have been reported to have direct allowed transition band-gap of 2.1 - 2.6 eV and indirect allowed transition band-gap of 1.2 - 1.6 eV, respectively6-10, we conclude that the optical behaviour observed in the short wavelength range, from which absorption of TiO2 has been excluded, is attributed mainly to Cu2O. The wider band-gap in comparison with bulk Cu2O could be due to the quantum-size effect, as discussed later. Since the CuxO contains Cu2O, it is expected to exhibit an antivirus effect.Figure 1 Colour and spectral changes of the photocatalysts. (a, c) Colour changes of the (a) (c) anatase-based photocatalyst suspensions after leaving in the dark and under irradiation with simulated solar light. (b) Spectra of the as-prepared photocatalyst suspensions. (d-g) Photographs of the (d, f) (e, g) anatase-based photocatalyst coating (d, e) with or (f, g) without white pigments. (h) Spectral changes of the anatase-based coatings in the dark and under illumination (fluorescent light, > 380 nm, 500 lx). The anatase-based suspension showed a brownish gray colour (Fig. 1c) and an absorption band at 400 - 600 nm (Fig. 1b). The corresponding Tauc plots show that the band-gap is ~ 2.9 eV for direct transition and ~ 1.7 or ~ 2.3 eV for indirect transition. The optical behaviour could therefore be ascribed to both Cu2O and CuO. We also subjected the rutile-based suspension to STEM and EDS analyses after thorough evaporation of water from the suspension (Fig. 2). The STEM image (Fig. 2a) shows that the primary size of the nanoparticles is smaller than 10 nm. As a result of elemental mapping based on STEM-EDS analysis (Fig. 2d-f), we found that the major component was TiO2 nanoparticles of ~ 4 - 8 nm in size, and that clusters of Cu compounds (1 - 2 nm or less) were deposited on TiO2. High resolution HAADF-STEM analysis proved that the TiO2 nanoparticles were in rutile phase and that the Cu compound clusters contained both Cu2O and CuO (Fig. 2b, c). The quantum-sized Cu2O11,12 justifies its widened band-gap of ~ 3.0 eV mentioned above due to a quantum-size effect. Small particles generally give large specific surface area, high optical transmittance and good suspendability. Actually both anatase-based suspensions showed no sedimentation for at least 1 year.Figure 2 Photocatalyst nanoparticles. (a-d) HAADF-STEM images of the photocatalysts. (e, f) STEM-EDS elemental mapping images for (e) Ti and (f) Cu. When the suspensions were left in the dark, their colour was gradually changed to green in 24 h (Fig. 1a, c), suggesting that Cu2O was oxidized to Cu2+ by dissolved oxygen (Fig. 3, Process A). However, when we irradiated the oxidized suspensions with light from a solar simulator for 24 h, their colour was changed again to greenish gray (Fig. 1a) and brownish gray (Fig. 1c) for anatase-based photocatalysts, respectively, indicating that Cu2+ was reduced back to Cu2O. This reduction can be explained in terms of photo-induced interfacial charge transfer from the TiO2 VB to Cu2+ at the TiO2 surface (Fig. 3, Process B)2 Resultant holes in the TiO2 VB should be consumed by oxidation of water to oxygen. Electrons in the TiO2 VB could also be excited to the conduction band (CB) under the simulated solar light, which contains weak UV light, and the excited electrons could also contribute to the reduction of Cu2+ (Fig. 3, Process C). In the case where the mol ratio of Cu to Ti was 1/100 or lower, a small absorption peak was observed at ~ 580 nm after irradiation of the anatase-based photocatalyst. This could be due to localized surface plasmon resonance (LSPR) of over-reduced, metallic Cu nanoparticles. Plasmonic metal nanoparticles in contact with TiO2 inject electrons to the TiO2 conduction band, and metal is oxidized to metal ions, in the case of Ag or less noble metals13,14 including Cu15 (Fig. 3, Process D).Figure 3 Photoinduced chemical processes involved in the present photo-renewable system. (A) Aerobic oxidation of Cu(I) to Cu(II). (B) Photo-induced interfacial charge transfer from the TiO2 VB to Cu(II). (C) Photo-excitation of electrons in the TiO2 VB to CB. (D) Plasmonic excitation of over-reduced, metallic Cu nanoparticles, which inject electrons to the TiO2 CB. Process B is the major photo-process and Processes C and D are minor processes. Photocatalytic coatings Either (rutile or anatase) of the CuxO/TiO2 suspensions was added to a latex paint containing inorganic white pigments and organic binders, followed by 5-min stirring and 1-min degassing. Each photocatalyst slurry thus obtained was applied onto a glass plate (0.01 mL cm-2). Solvent in the coating was evaporated at 25 degC for 7 days, and white films were obtained (Fig. 1d, e). Colourless translucent films without the white pigment (Fig. 1f, g) were also prepared for spectroscopic measurements. The small particle size of CuxO/TiO2 is responsible for the good transmittance. Their average thickness was 50 mm for both photocatalyst films. After preparation of the coatings, those were left in the dark. As a result, their absorption in the visible wavelength range was decreased gradually (Fig. 1h). In marked contrast, the absorption was gradually increased under irradiation with fluorescent light (< 380 nm light was cut off). The peak at 440 nm reflect photo-induced interfacial charge transfer from the TiO2 VB to Cu2+16,17. The absorption decrease in the dark and the increase under illumination can be explained in terms of aerobic oxidation (Fig. 3A) and photocatalytic re-reduction (Fig. 3B), respectively, of CuxO clusters. Since Cu+ in CuxO exhibits antivirus effects, the photocatalysts are expected to retain their antivirus activities, if any, under fluorescent light, even in the paint coatings. Antivirus effects of the coatings The photocatalyst paint coatings were subjected to inactivation tests against novel coronavirus (SARS-CoV-2, original variant) according to the procedures given in International Organization for Standardization ISO 21,702 with some modifications. Coronaviruses in 5% FBS DMEM medium (25 mL) were applied onto a glass plate (20 x 20 mm) coated with the anatase-based photocatalyst coating. The plate was covered with a polypropylene film of the same size and was incubated under fluorescent lamp illumination (1000 lx) for 3 h, followed by evaluation of viral infectivity V (in pfu mL-1) by a plaque assay. Figure 4a shows the logV values together with those for control experiments in which a bare glass plate or a glass plate coated with the paint without photocatalyst was used instead of the photocatalytic plate. The rutile-based coating strongly inactivated the novel coronavirus and the obtained viral infectivity was lower than the detection limit of 5 pfu. Its antivirus activity [= (logV)ave - (logV0)ave, where V0 is viral infectivity for a bare glass plate and subscript ave stands for averaged values) is 3.8 or higher. The coronavirus was also inactivated by the anatase-based coating, whereas its antivirus activity was lower (2.0). This difference should be due to the lower interfacial charge transfer absorption band at 440 nm for the anatase-based photocatalyst in comparison with the rutile-based one (Fig. 1h). The larger band-gap of anatase TiO2 (3.2 eV) than rutile (3.0 eV), which lowers the contribution of the Cu2+ reduction pathway via the TiO2 CB (Fig. 3C), may also be responsible for the activity difference.Figure 4 Antivirus effects of the photocatalyst coatings on novel coronaviruses. Viral infectivity (V) values for (a) the original and (b) alpha variants of novel coronavirus after incubation under fluorescent light (1000 lx for 3 h) are shown. Raw data are summarized in Table S1 in Supplementary Information. Next we examined an antivirus effect of the rutile-based coating on alpha variant (also known as lineage B.1.1.7 or VOC-202012/01) of the novel coronavirus, which has mutations including N501Y (Fig. 4b). Its antivirus activity was 3.0; the photocatalyst coating is also effective against alpha variant. Possible mechanisms of inactivation by the photocatalysts are discussed at the end of this section. We also subjected the photocatalyst coatings to antivirus assays for bacteriophage Qb by Kitasato Research Center for Environmental Science and assays for bacteriophage M13 according to the procedures given in Japanese Industrial Standard JIS R1756 and those in Ref.18, respectively. Figure 5a shows the results for bacteriophage Qb after fluorescent lamp irradiation (500 lx) for 4 h. The antivirus activities of the anatase-based coatings were >= 5.0 and 3.4, respectively. The activity values were lowered to 1.6 (rutile) and 0.1 (anatase) for the control experiments without illumination (Fig. 5b). Those results show that the photo-renewing effect is very important to keep the high antivirus activities. On the other hand, the rutile-based photocatalyst keeps the significant antivirus activity even in the dark, reflecting that Cu2O remaining in the coating causes the antivirus effects because Cu2O has been known to inactivate bacteriophage Qb19,20. In addition, both of the anatase-based photocatalysts exhibited high inactivation effects on bacteriophage M13 (Fig. 5c); the antivirus activities were 3.6 and 5.0, respectively.Figure 5 Antivirus effects of the photocatalyst coatings on bacteriophages. Viral infectivity (V) values for bacteriophage Qb (a) after incubation under fluorescent light (500 lx for 4 h) or (b) in the dark and (c) those for bacteriophage M13 after incubation under fluorescent light (500 lx for 24 h) are shown. Raw data are summarized in Table S1 in Supplementary Information. Antivirus effects on influenza A virus and feline calicivirus, which is often used as a surrogate for norovirus because of the similarity in terms of a capsid-enveloped structure, were also investigated in the dark by Kitasato Research Center for Environmental Science, according to the protocol of ISO 21702. The coatings were subjected to assay 18 days after the synthesis of the photocatalysts. We observed significant inactivation effects of the anatase-based photocatalyst coatings after 24-h incubation, and the antivirus activities were > 3 for influenza A virus, and > 4 for feline calicivirus. The remaining Cu2O may also be effective for those viruses. In previous studies, it has been shown that Cu2O inactivates influenza virus through denaturation of hemagglutinin20, which is a protein at the virus surface and binds to glycans with terminal sialic acid on host cells. We infer that Cu2O might also attack surface proteins of the novel coronaviruses, the bacteriophages Qb and M13 and feline calicivirus. In the case of the novel coronavirus, it is known that there are spike proteins at the virus surface. The spike proteins bind ACE2, which is a receptor protein at the host cell surface, and lead to infection21. We therefore examined possible effects of the present photocatalyst on the binding ability of the spike proteins to human ACE2, in the following section. Effects on spike proteins of novel coronavirus We investigated if the photocatalysts containing Cu2O developed in this study denature the surface spike protein of novel coronavirus and thereby suppress its infectivity. To assess this, we prepared RBD of spike protein derived from the original, alpha and delta variants of novel coronavirus, and evaluated the denaturation effects of the photocatalysts on the protein. Since the binding of RBD to human ACE2 is an essential step in the infection21, the 5 mM recombinant RBD protein (70 mL) was mixed with the photocatalyst suspensions (70 mL) and left for 2 h at 4 degC and the binding activity toward ACE2 was examined by ELISA according to literature22. As shown in Fig. 6, the binding activity of RBD to ACE2 was significantly diminished by the incubation with the photocatalysts, indicating that the photocatalysts denatured the RBD protein. These results strongly support our conclusion that the antiviral effect of the photocatalyst on coronavirus relies, at least in part, on the protein denaturing activity. Importantly, RBD proteins derived from alpha and delta variants were also inactivated as was the original variant, indicating that the photocatalysis is effective to denature the spike protein regardless of mutation. It was suggested that the denaturation is due to disorder of electrostatic interaction in protein20. Further study to reveal the denaturing process of the proteins will provide a strategy to develop photocatalysts with even higher antiviral activity.Figure 6 Denaturation effect of the anatase-based photocatalysts on RBD domain of spike protein from (a) the original, (b) alpha and (c) delta variants of novel coronavirus. The binding activity of RBD to human ACE2 protein at various concentrations was assessed by ELISA (n = 3). Raw data are summarized in Table S2 in Supplementary Information. Conclusions Nanoscale CuxO/TiO2 photocatalysts were prepared and applied to white and translucent latex paints. Cu2O clusters involved in the paint coating are gradually oxidized by ambient oxygen, while the oxidized clusters are re-reduced under > 380 nm light. The paint coating inactivated the original and alpha variant of novel coronavirus under fluorescent lamp irradiation. The photocatalysts denatured RDB of the original, alpha and delta variants of novel coronavirus and suppressed binding ability of their spike protein to human ACE2. The coating also inactivated influenza A virus, feline calicivirus, bacteriophage Qb and bacteriophage M13. The photocatalytic paint coatings are expected to lower the risk of coronavirus infection via solid surfaces. Supplementary Information Supplementary Information. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-023-30690-0. Acknowledgements The authors are grateful to Dr. T. Ishida and Advanced Characterization Nanotechnology Platform, The University of Tokyo for HAADF-STEM and STEM-EDS measurements. Those measurements were supported in part by a Nanotechnology Platform project by the Ministry of Education, Culture, Sports, Science and Technology of Japan (No. JPMXP09A21UT0198). This work was supported in part by a grant (JP223fa627001) from the Japan Agency for Medical Research and Development (AMED). Author contributions T.T. and K.H. designed the project. M.N., T.I., Y.K., K.T., C.L., NM and T.O. performed experiments. T.T. and M.N. wrote the manuscript text. T.T., M.N. and Y.K. prepared the figures. T.T., T.I., K.T. and T.W. supervised the project. All authors reviewed and approved the final manuscript. Data availability All data generated or analysed during this study are included in this published article and its supplementary information file. Competing interests The authors declare no competing interests. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Leung NHL Transmissibility and transmission of respiratory viruses Nat. Rev. Microbiol. 2021 19 528 10.1038/s41579-021-00535-6 33753932 2. 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PMC10000352 | Trials Trials Trials 1745-6215 BioMed Central London 36899430 7210 10.1186/s13063-023-07210-6 Study Protocol Efficacy of silymarin in patients with non-alcoholic fatty liver disease -- the Siliver trial: a study protocol for a randomized controlled clinical trial de Avelar Camila Ribeiro [email protected] 1 Nunes Beatriz Vieira Coelho 1 da Silva Sassaki Betina 1 dos Santos Vasconcelos Mariana 1 de Oliveira Lucivalda Pereira Magalhaes 1 Lyra Andre Castro 2 Bueno Allain Amador 3 de Jesus Rosangela Passos 1 1 grid.8399.b 0000 0004 0372 8259 Department of Nutrition Sciences, Federal University of Bahia, Bahia, 32 Araujo Pinho Street, Canela, Salvador, Bahia 40.110-150 Brazil 2 grid.8399.b 0000 0004 0372 8259 Gastrohepatology Service, Professor Edgard Santos University Hospital, Federal University of Bahia, Salvador, Bahia Brazil 3 grid.189530.6 0000 0001 0679 8269 College of Health, Life and Environmental Sciences, University of Worcester, Worcester, WR2 6AJ UK 10 3 2023 10 3 2023 2023 24 1774 5 2022 27 2 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background Non-alcoholic fatty liver disease (NAFLD) is one of the most prevalent liver diseases globally. Pharmacological treatments for NAFLD are still limited. Silymarin, a compound extracted from Silybum marianum, is an herbal supplement traditionally used in folk medicine for liver disorders. It has been proposed that silymarin may possess hepatoprotective and anti-inflammatory properties. The present trial aims to assess the efficacy of silymarin supplementation in the adjuvant treatment of NAFLD in adult patients. Method This is a randomized double-blind placebo-controlled clinical trial recruiting adult NAFLD patients in therapy on an outpatient basis. Participants are randomized to an intervention (I) or control (C) group. Both groups receive identical capsules and are followed for 12 weeks. I receives 700mg of silymarin + 8mg vitamin E + 50mg phosphatidylcholine daily, while C receives 700mg maltodextrin + 8mg vitamin E + 50mg phosphatidylcholine daily. Patients undergo a computerized tomography (CT) scan and blood tests at the beginning and end of the study. Monthly face-to-face consultations and weekly telephone contact are carried out for all participants. The primary outcome assessed will be change in NAFLD stage, if any, assessed by the difference in attenuation coefficient between liver and spleen, obtained by upper abdomen CT. Discussion The results of this study may provide a valuable opinion on whether silymarin can be used as adjuvant therapy for the management or treatment of NAFLD. The data presented on the efficacy and safety of silymarin may provide more foundation for further trials and for a possible use in clinical practice. Trial registration This study has been approved by the Research Ethics Committee of the Professor Edgard Santos University Hospital Complex, Salvador BA, Brazil, under protocol 2.635.954. The study is carried out according to guidelines and regulatory standards for research involving humans, as set out in Brazilian legislation. Trial registration - ClinicalTrials.gov : NCT03749070. November 21, 2018 Keywords Clinical trial Silymarin Non-alcoholic fatty liver disease randomized controlled trial issue-copyright-statement(c) The Author(s) 2023 pmcStrengths and limitations of this study Placebo-controlled randomized double-blind clinical trial employing silymarin extract with greater bioavailability. The effectiveness of silymarin supplementation will be assessed by CT without contrast as reference standard for the detection and assessment of liver steatosis . Participants are recruited from a Nutrition and Hepatology Clinic of a single tertiary referral hospital. Introduction Background and rationale {6a} NAFLD is one of the most prevalent liver diseases worldwide. With a continuously increased incidence and level of complications, NAFLD has become a major public health concern worldwide [2-4], with approximately 20% to 30% of the general adult population affected. Men appear to show a higher prevalence for NAFLD than women in all age groups . Based on risk factors, NAFLD is manifested in approximately 50% of overweight individuals and in approximately 80% to 90% of obese individuals. Individuals diagnosed with metabolic syndrome (MS) are approximately twice as likely to develop NAFLD . The main risk factors associated with NAFLD overlap with those of metabolic syndrome, including central obesity, type 2 diabetes (T2D), dyslipidemia, and insulin resistance (IR). NAFLD has been associated with a pro-inflammatory background and is considered a hepatic manifestation of obesity and MS . In its first stage, NAFLD patients show lipid inclusion in the liver parenchyma without evident signs of inflammation or hepatocellular necrosis. At this stage, NAFLD management is focused on improving IR, body fat reduction, as well as MS and T2D prevention and management. Body weight reduction combined with amelioration of metabolic disarrangements can prevent the progression of steatosis to non-alcoholic steatohepatitis (NASH), cirrhosis, and cellular hepatocarcinoma . Despite our understanding of the epidemiological and pathophysiological aspects of NAFLD, the main and by far most successful treatment option available is a positive lifestyle change. The use of pharmacological agents is still limited and requires stronger evidence regarding safety and efficacy . As successful long-term adherence to positive lifestyle changes is not always achieved in full, researchers have investigated supporting pharmacotherapeutic strategies, such as herbal medicines, to ameliorate NAFLD. A few studies have suggested that silymarin supplementation may induce beneficial effects for NAFLD patients, including amelioration of biochemical markers associated with inflammation and NAFLD progression [12-15]. Silymarin is a flavonoid extracted from Silybum marianum, one of the most used medicinal herbs by individuals with liver diseases . Silybum marianum has shown good tolerance and safety, with limited adverse effects reported in liver disease patients. The hepatoprotective, anti-inflammatory, antioxidant, and anti-fibrotic effects of silymarin have been studied in patients with cirrhosis associated with viral hepatitis, exposure to environmental toxins, alcoholic steatosis and NASH [17-20]. A few studies have pointed out to a beneficial effect of silymarin therapy upon the evolution of NAFLD, but significant variability and methodological differences across available studies prevent the establishment of robust conclusions. A systematic review with meta-analysis including six clinical trials showed that silymarin reduced serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in NAFLD patients, but the studies appraised in that meta-analysis had a high degree of heterogeneity and low methodological quality. The scarcity of clinical trials employing silymarin as adjuvant therapy for liver disease and NAFLD, with a particular attention to methodological design, planning, and execution stages, has encouraged us to propose and execute the Siliver trial. Our initial hypothesis is that silymarin supplementation will improve the metabolic status and reduce liver fat content in NAFLD patients. Our hypothesis will be tested by following the protocol detailed below. Objectives {7} The present study aims to investigate the efficacy of silymarin supplementation as an adjunctive treatment for adult patients suffering with NAFLD. The primary outcome assessed will be change in NAFLD stage, if any, assessed by the difference in attenuation coefficient between liver and spleen, obtained by upper abdomen CT scan without contrast. The attenuation coefficient between the liver and spleen is a reference standard for the assessment of liver steatosis. As secondary objectives, we will assess body mass index (BMI) and waist circumference (WC); glucose metabolism biomarkers including blood glucose, insulin, glycated hemoglobin (HbA1C), and Homeostasis Model Assessment-Insulin Resistance Index (HOMA-IR); blood ferritin levels; and biomarkers of liver damage, including transaminases, gamma-glutamyl transferase (gGT), and alkaline phosphatase (AP). Trial design {8} As the trial hypothesis is to investigate whether silymarin supplementation is better than placebo for NAFLD amelioration, a framework of superiority was adopted for this double-blind randomized placebo-controlled clinical trial. Patients will be supplemented for 12 weeks (Fig. 1). The planning of this trial follows the guidelines of the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines.Fig. 1 Study flowchart Method: participants, interventions, and outcomes Study settings {9} All participants had a confirmed NAFLD diagnosis prior to participation in this trial. NAFLD patients were referred to the trial by local health centers located in the neighborhoods of the city of Salvador BA Brazil, in partnership with our outpatient recruitment unit at the Nutrition and Hepatology Outpatient Clinic of the Professor Edgard Santos University Hospital Complex (NHOC), located in the city of Salvador BA, Brazil, where the trial took place. Eligibility criteria {10} Inclusion criteria Eligibility criteria for the Siliver trial include consenting adult patients aged between 20 and 60 years of both sexes. All patients had a medically confirmed diagnosis of NAFLD prior to participation in this trial. Non-inclusion criteria Patients who meet any of the following criteria have not been included lactating or pregnant women, and women during their menacme, except for those who underwent definitive contraception such as hysterectomy or tubal ligation; patients with a previously established diagnosis of chronic disease including congestive heart failure, decompensated or severe lung disease, neoplasms, kidney disease, carriers of the human immunodeficiency virus (HIV), and advanced chronic liver diseases (Child-Pugh classification B and C) caused by any causal agent unrelated to NAFLD; recreational drug users; patients with an average intake of more than 20 g of alcohol per day and or a history of alcoholic disease in abstention for less than 6 months; use of prescribed medication including steroids, oestrogens, amiodarone, warfarin, anticonvulsants, antipsychotics, or chemotherapy drugs in the past 6 months; infections, surgery, trauma, or hospitalization in the past 30 days; chronic degenerative diseases of non-hepatic origin; and unavailability of previously obtained imaging tests with a diagnosis of NAFLD in its screening phase. Exclusion criteria The following patients will be excluded patients who at the recruitment stage do not show confirmation of NAFLD by CT scan; patients who missed any phase of the trial; and patients who during the trial were diagnosed with a condition listed in the non-inclusion criteria above. Who will provide informed consent? {26a} Patients will provide informed consent themselves. All eligible participants have received information about the study and had the opportunity to have their questions answered to their satisfaction. The blinded evaluator has obtained written informed consent (IC) from all participants prior to assessment. Additional consent provisions for collection and use of participant data and biological specimens {26b} The blood samples obtained, once analyzed for the specific purpose of this trial, are discarded following the Teaching Hospital Standard Operating Procedures (SOPs) on disposal of biological waste. Data collected from participants withdrawn from the study or lost on follow-up will be excluded and deleted, as the aim of the trial has not been completed for those participants. All participants have given their consent to the research team to share relevant data with researchers taking part in the research, as well as regulatory authorities. This set of information was explained to participants and made available in the consent form. All participants have agreed to the above. Interventions Explanation for the choice of comparators {6b} Participants are randomized to groups intervention (I) or control (C). They receive identical capsules and follow the trial instructions for 12 weeks. All participants are instructed to take two capsules per day soon after a meal. Considering the pathophysiology of NAFLD and pharmacotherapies currently available for its treatment or management, there are no specific pharmacological agents currently approved for NAFLD specifically that could be compared to the test item. Therefore, the research team adopted a methodological design using a placebo. Intervention description {11a} I participants receive 700 mg silymarin + 8 mg vitamin E + 50 mg phosphatidylcholine, daily. C participants receive 700 mg maltodextrin + 8 mg vitamin E + 50 mg phosphatidylcholine, daily. Each I capsule contains 350 mg silymarin + 4 mg vitamin E + 25 mg phosphatidylcholine. Each C capsule contains 350 mg maltodextrin + 4 mg vitamin E + 25 mg phosphatidylcholine. All participants are instructed to take two capsules per day soon after a meal. We have carefully defined the capsule composition for both groups to achieve a planned daily dosage. We employed phosphatidylcholine and vitamin E in the composition to increase silymarin bioavailability, which is based on a protocol described previously and evaluated in a systematic review with meta-analysis published by our group . Microcrystalline cellulose, corn starch, and colloidal silicon dioxide were used as standard excipients in all capsules of both I and C. The capsule composition did not include dyes, preservatives or additives in I or C, guaranteeing the standardization of their appearance. The capsule weight, size, shape, and coating were identical between I and C, and have been designed to ensure the same ease of swallowing, to minimize risks of gastric discomfort for the participants, and to ensure similar disintegration time and propensity for swelling. The capsules are visually unidentifiable between I and C. All I and C capsules were manufactured and kindly donated by Singular Pharma (Salvador, Brazil). The expiry date is three months after production. Criteria for discontinuing or modifying allocated interventions {11b} Participants are free to withdraw from the trial at any time and for any reason without penalty. Participants are withdrawn from the study if they start a different treatment elsewhere. Strategies to improve adherence to interventions {11c} Participants are monitored weekly by telephone calls to collect information on adherence. They are given the opportunity to ask the research team any question and receive reminders of upcoming appointments. In addition, participants are instructed to bring along the latest flasks with the capsules received at each appointment, favoring greater adherence and commitment to the treatment. Relevant concomitant care permitted or prohibited during the trial {11d} During the intervention and follow-up, participants are advised not to use any medication, supplement, tea or herbal supplement without prior medical and nutritional advice, and without prior notice to the research team. If they do, they are asked to inform the research team immediately, informing what was ingested and the date and dosage taken. Provisions for post-trial care {30} All study participants have the right to medical care and follow-up, and if they experience a worsening of their condition. In the final consultation, participants who no longer show fatty infiltration receive guidance on how to prevent the recurrence of NAFLD. Participants who show evidence of NAFLD, regardless of the degree of steatosis, are referred to the outpatient follow-up clinic for the continuation of their care provision with a hepatologist consultant and a nutritionist (Fig. 1). Outcomes {12} Primary outcome The primary outcome will be the assessment of NAFLD resolution, or change in its grade, as assessed by the difference in the attenuation coefficient between liver and spleen, obtained by CT of the upper abdomen, at the end (after) compared to beginning (before) the trial. In summary, the primary outcome is to investigate whether silymarin supplementation can reduce liver fat content in NAFLD patients, measured by a CT scan. Secondary outcomes The secondary outcomes investigated in this trial include:Differences in ALT, AST, gGT, and AP levels after versus before; Difference in ferritin levels after versus before; Difference in fasting glucose, insulin, HbA1C, and HOMA-IR levels after versus before; and Difference in BMI and WC after versus before. Participant timeline {13} Table 1 shows the stages of the study and which assessments will be performed throughout the study period.Table 1 Schedule of enrolment, interventions, and assessments Schedule of activities Enrolment Allocation Post-allocation Close-out Time Point Week 1 Week 2 Week 3-5 Week 6 Week 7-10 Week 11 Week 12-15 Week 16 Week 17 Enrolment Screening * Eligibility screen * Informed consent * Computed tomography (CT) and collection of laboratory tests * Baseline consultation (allocation) * Interventions Intervention start * Telephone follow-up * * * Return consultation 1 * Return consultation 2 * Return consultation 3 * Assessments Computed tomography (CT) and laboratory tests * Final consultation * Sample Size {14} The sample size was determined through an accuracy analysis of the primary outcome. A significance level of 0.05 and a power of 80% were adopted, which resulted in a minimum sample size of approximately 132 participants. Recruitment {15} Patient recruitment started in February 2019 and ended in May 2022. All participants have been diagnosed with NAFLD prior to participation in this trial. All participants were recruited directly from the NHOC, or they have been referred to the NHOC by local health centers located in the neighborhoods of the city of Salvador. The NHOC provides specialist care for patients with liver diseases, including NAFLD. However, only patients diagnosed with NAFLD have been approached to discuss their participation in the trial. All patients received in May 2022 or onwards a phone call with an invitation for a face-to-face consultation, in which their individual results will be discussed with a clinician researcher. Any current or new need for medical care will be discussed at that consultation, and a new referral will be made if necessary. The burden of this randomized controlled trial was not assessed by the patients themselves or their families. Prior to signing the consent forms, all patients were reassured that their participation in this trial was entirely voluntary. All patients were also reassured that they could withdraw at any time without giving a reason and reassured that withdrawing would not result in any penalty to them and would not interfere with any current or future medical or healthcare provision to them. Intervention assignment: allocation Sequence generation {16a} Patients who agreed to take part in the study and met all the study criteria were assigned to I or C groups by computer-generated randomization in blocks with the aid of a spreadsheet to ensure a random but uniform variation in sizes of each I and C blocks. Randomization and record keeping of all participants were carried out by a statistician researcher external to the research group. The statistician is not involved in patient clinical assessment. Concealment mechanism {16} The allocation sequence was concealed from the researchers assessing participants and their clinical outcomes. The allocation sheet hardcopies are kept in envelopes in a locked drawer of a secure filing cabinet located at the NHOC administrative office. Implementation {16c} All patients who give consent for participation and who fulfill the inclusion criteria are randomly assigned to I or C. The Principal Investigator (PI) will open the envelopes containing the allocation sequence only after the last participant included completes the trial. Assignment of interventions: blinding Who will be blinded {17a} All clinical assessments were conducted by evaluators blinded to treatment allocation. Participants were blinded to the study hypothesis and their allocation group, but were advised of the overall aspects involved in the treatment of both groups. I and C capsules were dispensed by a registered pharmacist at the clinical research pharmacy of the Teaching Hospital where the trial took place. The pharmacist was responsible for receiving and storing all batches of I and C capsules manufactured by Singular Pharma, as well as identifying the correct capsule to be dispensed according to the specific numbering of each participant. Procedure for unblinding if needed {17b} The trial design is open-label with outcome assessors being blinded. Only the pharmacist in charge of dispensing the trial capsules and the statistician have access to group allocation; neither, however, are involved in clinical assessment or data collection. Data collection and management {18a} The research team involved in this trial underwent training prior to commencement of the study regarding the protocol to be followed, to avoid biases and errors in data collection. The clinical dietitians (CRA, BVCN, BSS, MSV) in charge of seeing patients at the NHOC performed a triage of eligible patients, and the more experienced dietitian running the clinic (CRA) was responsible for double-checking that all the inclusion and non-inclusion criteria had been fully met for each patient. CRA was also responsible for explaining the study in further detail and taking verbal and written consent. The clinical trial is structured as presented in Table 1 and detailed below. Screening Patients who meet the eligibility criteria are referred to the screening consultation to receive information about the clinical trial and are given the opportunity to ask questions to the research team. Consenting participants are invited to sign the free and informed consent form. All participants are informed that they can withdraw at any time without giving reasons and that they will not be penalized for withdrawing. After signing the consent form, all participants answer questions on a standardized form filled in by the researcher. Information on sociodemographics, clinical history and clinical presentation, lifestyle data, diet intake, and feeding patterns are collected. The first anthropometric assessment is completed at that point. At the end of the screening consultation, participants receive general nutritional guidelines and a study identification card with the contact details of the researchers. Participants are encouraged to make contact should they have any late questions about the trial. Following the first appointment, participants are referred to an upper abdomen CT scan before the intervention begins. CT scans Participants undergo a scheduled upper abdomen CT scan at the Radiology Unit of the Professor Edgard Santos University Hospital Complex. NAFLD is confirmed by a radiologist consultant. Patients who do not present NAFLD at the CT scan, even if they have historical imaging tests diagnosing the disease at an earlier period, are excluded from this trial and referred to a consultation with a registered nutritionist to receive specific guidelines on how to prevent NAFLD recurrence, Blood tests After the CT scan, participants are taken a 12-h fasting venous blood sample. They are given a breakfast meal after the blood sample collection and are given the details of their next consultation. Allocation consultation At this appointment, participants receive their CT scan and blood test results and are submitted to a second anthropometric assessment. At this consultation, a new form with nutritional and dietary data is completed by the researcher, and patients are given additional nutritional guidelines to complement the advice offered in the screening appointment. Subsequently, participants are sent to the clinical research pharmacy of the Hospital Complex for capsule collection according to their randomization. Monthly follow-up visits (return visits 1, 2, and 3) All participants were followed up through face-to-face individual consultations in 4-week intervals during the 12-week supplementation period. The Return Visits were scheduled as detailed in Table 1. At these appointments, patients were asked about adherence to the study. They were asked to bring along to each consultation the flasks they receive containing the capsules from the previous 4-week period, so that the research team can more accurately estimate adherence to the protocol. At each monthly follow-up visit participants had a nutritional and dietary assessment undertaken by a registered nutritionist member of the research team. The researcher completed a form with dietary intake and dietary habits over the last 4-week period and evaluated adherence to nutritional guidelines, ingestion of capsules as prescribed, tolerance, and the occurrence of any adverse effects. Telephone follow-up except for the weeks when participants had their scheduled Return Visits, all participants were contacted weekly by telephone to monitor adherence to the protocol, clarify any questions, and report any occurrence or adverse reactions. At Return Visit 3, which took place at the end of the 12th week of intervention, patients were referred to a second CT scan and blood tests following the same protocols as the baseline tests. A final consultation was scheduled for the test results to be delivered (Table 1). In the final consultation, participants who no longer showed fatty infiltration received guidance on how to prevent the recurrence of NAFLD. Participants who showed evidence of NAFLD, regardless of the degree of steatosis, were referred to the outpatient follow-up clinic for continuation of their care provision with a hepatologist consultant and a registered nutritionist (Fig. 1). Plans to promote participant retention and complete follow-up {18b} Participants received information about the study design and the importance of completing the final follow-up. The research team contacted the participants via telephone calls, and in case of not reaching, a voice message or text message 24 h before the scheduled appointments and blood tests, aiming to minimize non-attendance. Data management {19} The data were collected in paper form and stored in binders, which are kept in a locked drawer of a secure filing cabinet located at the NHOC administrative office. Only the PI has access to the documents. After data collection, all forms will be checked by two members for data quality and missing information. The data will be entered manually into an electronic spreadsheet and subsequently checked by two researchers, one at a time. The database and electronic analyses will be stored on a secure computer server with personal login access authorized by the PI. After completion of the study, all data and study documents will be archived and stored by the PI. The data is not public and remains in the possession of the PI. Individual unidentifiable data can be made available upon reasonable request. Confidentiality {27} The data will be treated anonymously and confidentially and at no time will the personal details of the participants be disclosed at any stage of the study. Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or molecular analysis in this trial/future use {33} Blood tests were performed following standardized laboratory protocols for medical diagnosis in humans. Blood samples were not stored for genetic or molecular analysis in the current study or any other future use. Blood samples were discarded following standardized hospital protocol. Blood test results were collected from the clinical analysis laboratory of the Institute of Pharmacy of the Federal University of Bahia via a secure hospital intranet. Statistical methods Statistical methods for primary and secondary outcomes {20a} Statistical analyses will firstly be performed using descriptive analysis to characterize the distribution of the events studied. Categorical variables will be investigated using simple absolute frequencies. Continuous variables will be investigated by measures of central tendency and dispersion. Parametric or non-parametric tests will be used considering the distribution nature of the variables studied. A significance level of 5% will be adopted for all statistical tests. Tests to verify variable behavior and comparisons of proportions analyses, such as the application of the chi-square test or Fisher's exact test, will be discussed later with a qualified statistician. Tests for comparison of means between groups, analysis of correlations between continuous variables and logistic regression analysis, will also be discussed with the statistician. Data will be tabulated and analyzed using the R Project for Statistical Computing software (R-3.2.4 for Windows). Interim analyses {21b} This is a low-risk intervention, as silymarin at the dosage adopted in this trial has been considered safe and well-tolerated. All patients were carefully followed up in person and by telephone, aiming to identify any adverse event. Only patients who successfully complete the trial will have their data included in the final data analyses. Methods for additional analyses (e.g., subgroup analyses) {20b} No additional analysis will be performed. Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c} Only patients who successfully completed the trial will have their data included in the final trial data analyses, and there will be no imputations for missing data. The data will be assessed by intention-to-treat, in which all participants who completed the trial are included in the statistical analyses and analyzed according to the group they were originally assigned, regardless of which group they were assigned to. Participants who drop out of the study due to illness, moving to another city, or inability to attend appointments or perform tests will be considered as protocol deviations and will be excluded from the data analyses. Plans to give access to the full protocol, participant-level data, and statistical code {31c} The full protocol, participant-level data, and statistical code generated in this trial will be available from the corresponding author in electronic format on reasonable request. Identifiable information such as full name, address, and date of birth will not be shared for confidentiality purposes. Oversight and monitoring Composition of the coordinating center and trial steering committee {5d} The PI as a blind evaluator and a coordinator assistant will coordinate all phases of the study, the randomization, and record-keeping of I and C participants. Patient and Public Involvement Groups (PPIG) were not involved in the design, recruitment, or execution of this trial, nor will they be involved in the reporting and dissemination of this research trial, with the exception of dissemination through their own social media channels if they wish. Composition of the data monitoring committee, its role and reporting structure {21a} There will be no data monitoring committee since only the primary evaluator, the research team, and the coordinator assistant will have access to the clinical trial data. Additionally, this trial is a low-risk intervention, and participants are advised to report any unexpected or adverse effects to the research team. Adverse event reporting and harms {22} The capsules provided to patients in both groups were produced and kindly donated by Singular Pharma (Salvador BA, Brazil). Singular Pharma have contractually undertaken not to interfere in any stage of the trial and have allowed the dissemination of any trial results, even if such results do not confirm the hypothesis that silymarin may be a beneficial adjuvant compound for the treatment or management of NAFLD. The donation document was submitted to, and approved by, the Ethics Committee. Silymarin is commonly prescribed by clinicians and nutritionists and its use is considered safe . According to data available from studies included in a previously published meta-analysis , there have been no reports of serious adverse events categorized as frequent or uncommon. However, a few studies have reported episodes of nausea, vomiting, and abdominal discomfort as rare adverse events . Interestingly, a few clinical trials and meta-analyses that have investigated the effects of supplements containing silymarin did not record adverse events or complications associated with supplementation, suggesting good tolerability and safety to participants . In the current trial, participants were advised to immediately stop taking the capsules and contact the research team as soon as possible in the event of any unexpected or adverse effect, or any discomfort supposedly associated with the capsule intake. All participants were followed up and monitored every 4 weeks at the NHOC, where the data collection and weekly telephone follow-up calls took place. All possible adverse events or complications observed were recorded, evaluated, and reported in the study. Frequency and plans for auditing trial conduct {23} Fortnightly meetings were held with the group of researchers involved in the study to discuss development and question clarification. An independent researcher external to the research team will verify the data collected during the study. If any documents are missing or information is inconsistent, the Ethics Committee will be notified. Lastly, if there is any change in the study, the ethics committee, the journal, and ClinicalTrials will be notified immediately. Plans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25} This study has been approved by the Research Ethics Committee of the Professor Edgard Santos University Hospital Complex under application protocol 2.635.954. The research must be undertaken as set out in the approved documents for the approval to be valid. The Research Ethics Committee will be contacted should the research team intend to make any amendments to the approved research. Patients eligible to join the trial were invited to sign the consent form after receiving all the information regarding the trial, including potential risks, and after having their questions answered in full. The consent form was developed in compliance with guidelines and regulatory standards for research involving human beings. During all stages of this trial the standards set out in the Brazilian Resolutions 196 and 466/2012, approved by the National Health Council, were followed. The Good Clinical Practices of the Document of the Americas of 2008 were also followed. All participant information is kept confidential. At the end of the trial, all participants were advised to maintain their clinical and nutritional follow-up appointments at the NHOC of the University Hospital Complex according to their health needs. Dissemination plans {31a} The results of this randomized controlled clinical trial are expected to be disseminated through presentations at conferences and publications in peer-reviewed journals. Discussion This clinical trial aims to assess the efficacy of silymarin in adult patients diagnosed with NAFLD. The prevalence and incidence of NAFLD are expanding at an accelerated pace and currently pose a burden to public health systems. There are currently limited pharmacotherapeutical options for NAFLD . Silymarin has been hypothesized as a useful adjuvant therapeutic resource in clinical practice for NAFLD therapies, as beneficial hepatoprotective properties attributed to silymarin have been reported . A few clinical studies have observed improvement in liver function and injury biomarkers after silymarin supplementation in various liver diseases [14, 22-25]. Liver biomarker levels are a true representation of the progression of liver disease and their levels are strongly associated with greater morbidity. Amelioration of liver biomarkers attributed to silymarin therapy is of great benefit for sufferers and a promising tool worth of further investigation . Several studies investigating the effects of silymarin in patients with liver diseases unfortunately feature some methodological biases. A meta-analysis of clinical trials published by our research team found a high degree of heterogeneity and low methodological quality in the qualitative assessment of the clinical trials included in the meta-analysis. Lastly, only very few published studies recruiting reasonable sample sizes have evaluated the efficacy of silymarin supplemented as a single test item in adult patients with NAFLD; we have addressed such a problem in our study by supplementing silymarin only. The lack of robust evidence, as well as inconsistencies identified in existing publications, reinforce the need for additional clinical trials with stronger methodological designs to further elucidate the roles of silymarin, if any, in the treatment and management of NAFLD. The results of the present clinical trial may contribute to the dissemination of reliable outcomes that may or may not support the recommendation of silymarin adjuvant therapy for NAFLD patients. Trial status Patient recruitment started in February 2019 and ended in May 2022. A significant delay in study progression and data collection was attributed to the SARS-CoV-2 pandemic and subsequent lockdowns. Abbreviations NAFLD Non-alcoholic fatty liver disease T Test C Control MS Metabolic syndrome T2D Type 2 diabetes IR Insulin resistance NASH Non-alcoholic steatohepatitis ALT Alanine aminotransferase AST Aspartate aminotransferase gGT Gamma-glutamyl transferase AP Alkaline phosphatase BMI Body mass index WC Waist circumference CONSORT Consolidated Standards of Reporting Trials SPIRIT Standard Protocol for Interventional Trails HIV Human immunodeficiency virus IC Informed consent Acknowledgements We would like to thank all volunteers and their families for taking their time and effort to join us in our study. We also thank the technical support staff for their overall assistance. Authors' contributions {31b} Avelar CR, Oliveira LPM, Lyra AC, and Jesus RP contributed to the conception and design of the study. Avelar CR, Nunes BVC, Sassaki BS, and Vasconcelos MS contributed to the acquisition of data. Avelar CR, Bueno AA, Oliveira LPM, and Jesus RP contributed to critical interpretation and manuscript write-up. All authors read and approved the final manuscript. Funding {4} There is no public or private funding for this research. This clinical trial study is being developed and delivered by a team of academics, as well as clinical and support staff employed by the Professor Edgard Santos University Hospital Complex. Availability of data and materials {29} Any data required to support the protocol can be supplied on request. Declarations Ethics approval and consent to participate {24} The study was approved by the Research Ethics Committee of the Professor Edgard Santos University Hospital Complex under application protocol 2.635.954. Patients eligible to join the trial were invited to sign the consent form after receiving all the information regarding the trial, including potential risks, and after having their questions answered in full. Participants signed two copies of the consent form; one copy will remain with the participant and the other with the researcher. Consent for publication {32} All participants have consented on their data to be analyzed and published in an anonymized format. No identifying images or other personal or clinical details of participants are presented here or will be presented in reports of the trial results. Informed consent materials are available from the corresponding author on request. Competing interests {28} The authors declare that they have no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. 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Velussi M Cernigoi AM De Monte A Dapas F Caffau C Zilli M Long-term (12 months) treatment with an anti-oxidant drug (silymarin) is effective on hyperinsulinemia, exogenous insulin need and malondialdehyde levels in cirrhotic diabetic patients J Hepatol 1997 26 4 871 879 10.1016/S0168-8278(97)80255-3 9126802 23. Hajaghamohammadi AA Ziaee A Raflei R The efficacy of silymarin in decreasing transaminase activities in nonalcoholic fatty liver disease. A randomized controlled clinical trial Hepat Mon 2008 8 3 191 195 24. El-Kamary SS Shardell MD Abdel-Hamid M Ismail S El-Ateek M Metwally M A randomized controlled trial to assess the safety and efficacy of silymarin on symptoms, signs and biomarkers of acute hepatitis Phytomedicine 2009 16 5 391 400 10.1016/j.phymed.2009.02.002 19303273 25. Jacobs BP Dennehy C Ramirez G Sapp J Lawrence VA Milk thistle for the treatment of liver disease: a systematic review and meta-analysis Am J Med 2002 113 6 506 515 10.1016/s0002-9343(02)01244-5 12427501 |
PMC10000353 | Pediatr Res Pediatr Res Pediatric Research 0031-3998 1530-0447 Nature Publishing Group US New York 36899125 2478 10.1038/s41390-023-02478-5 Clinical Research Article Quadrivalent meningococcal tetanus toxoid-conjugate booster vaccination in adolescents and adults: phase III randomized study Zambrano Betzana 1 Peterson James 2 Deseda Carmen 3 Julien Katie 4 Spiegel Craig A. 5 Seyler Clifford 6 Simon Michael 7 Hoki Robert 8 Anderson Marc 9 Brabec Brad 10 Anez German 14 Shi Jiayuan 11 Pan Judy 11 Hagenbach Audrey 12 Von Barbier Dalia 13 Varghese Kucku 15 Jordanov Emilia 14 Dhingra Mandeep Singh [email protected] 14 1 Global Clinical Development Strategy, Sanofi, Montevideo, Uruguay 2 J. Lewis Research, Salt Lake City, UT USA 3 Caribbean Travel Medicine Clinic, San Juan, Puerto Rico 4 J. Lewis Research Inc, South Jordan, UT USA 5 Craig A. Spiegel, MD Bridgeton, Bridgeton, MO USA 6 Pediatric Clinical Trials Tullahoma, Tullahoma, TN USA 7 Michael W. Simon, MD, PSC, Lexington, KY USA 8 Wee Care Pediatrics, Layton, UT USA 9 Tanner Clinic, Layton, UT USA 10 grid.422767.2 0000 0001 2006 6531 Midwest Children's Health Research Institute, Lincoln, NE USA 11 grid.417555.7 0000 0000 8814 392X Global Biostatistical Sciences, Sanofi, Swiftwater, PA USA 12 grid.417924.d Sanofi, Marcy L'Etoile, France 13 grid.417555.7 0000 0000 8814 392X Sanofi, Swiftwater, PA USA 14 grid.417555.7 0000 0000 8814 392X Present Address: Global Clinical Development Strategy, Sanofi, Swiftwater, PA USA 15 grid.417555.7 0000 0000 8814 392X Present Address: Global Clinical Immunology, Sanofi, Swiftwater, PA USA 10 3 2023 10 3 2023 2023 94 3 10351043 20 7 2022 29 11 2022 3 1 2023 (c) The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Background The immunogenicity and safety of a booster dose of tetanus toxoid-conjugate quadrivalent meningococcal vaccine (MenACYW-TT), alone or co-administered with MenB vaccine, were assessed in healthy 13-25-year olds who received MenACYW-TT or a CRM-conjugate vaccine (MCV4-CRM) 3-6 years earlier. Methods This phase IIIb open-label trial (NCT04084769) evaluated MenACYW-TT-primed participants, randomized to receive MenACYW-TT alone or with a MenB vaccine, and MCV4-CRM-primed participants who received MenACYW-TT alone. Functional antibodies against serogroups A, C, W and Y were measured using human complement serum bactericidal antibody assay (hSBA). The primary endpoint was vaccine seroresponse (post-vaccination titers >=1:16 if pre-vaccination titers <1:8; or a >=4-fold increase if pre-vaccination titers >=1:8) 30 days post booster. Safety was evaluated throughout the study. Results The persistence of the immune response following primary vaccination with MenACYW-TT was demonstrated. Seroresponse after MenACYW-TT booster was high regardless of priming vaccine (serogroup A: 94.8% vs 93.2%; C: 97.1% vs 98.9%; W: 97.7% vs 98.9%; and Y; 98.9% vs 100% for MenACWY-TT-primed and MCV4-CRM-primed groups, respectively). Co-administration with MenB vaccines did not affect MenACWY-TT immunogenicity. No vaccine-related serious adverse events were reported. Conclusions MenACYW-TT booster induced robust immunogenicity against all serogroups, regardless of the primary vaccine received, and had an acceptable safety profile. Impact A booster dose of MenACYW-TT induces robust immune responses in children and adolescents primed with MenACYW-TT or another MCV4 (MCV4-DT or MCV4-CRM), respectively. Here, we demonstrate that MenACYW-TT booster 3-6 years after primary vaccination induced robust immunogenicity against all serogroups, regardless of the priming vaccine (MenACWY-TT or MCV4-CRM), and was well tolerated. Persistence of the immune response following previous primary vaccination with MenACYW-TT was demonstrated. MenACYW-TT booster with MenB vaccine co-administration did not affect MenACWY-TT immunogenicity and was well tolerated. These findings will facilitate the provision of broader protection against IMD particularly in higher-risk groups such as adolescents. issue-copyright-statement(c) International Pediatric Research Foundation, Inc 2023 pmcIntroduction Invasive meningococcal disease (IMD) is a life-threatening illness caused by the obligate human bacterium, Neisseria meningitidis. IMD is a leading cause of mortality and morbidity globally, with a fatality rate of 8-15%.1 It is often associated with long-term sequelae amongst survivors, such as neurological complications, hearing loss, loss of limbs and paralysis.2 The incidence of IMD peaks in infants under 1 year of age with a second smaller peak in incidence observed in adolescents and young adults in many countries.3 Notably, carriage rates have been observed to be highest in this latter age group.4 Of the 12 meningococcal serogroups identified, 6 (A, B, C, W, Y and X) are the causative agent in the majority of cases of IMD worldwide.5,6 The dominant serogroup varies by geographical region and fluctuates unpredictably over time. In Western Europe and Canada, meningococcal serogroup C (MenC) outbreaks in the late 1990/early 2000s led to a steep rise in the incidence of IMD, while an increased incidence of MenW has been more recently observed in these countries.7 In the US, most outbreaks over the past two decades have also been caused by C and more recently B, with a smaller proportion of IMD cases caused by Y and W.8 Vaccination campaigns with monovalent (MenC) and quadrivalent (MenACWY) polysaccharide-protein conjugate vaccines have successfully reduced IMD incidence in many countries where this has been implemented.7-12 The recent development of two novel recombinant protein vaccines against MenB offers additional protection against IMD caused by serogroup B. In the United States, the Advisory Committee on Immunization Practices (ACIP) recommends routine primary vaccination with a meningococcal conjugate vaccine (MCV4) in children aged 11 or 12 years, and a booster dose at age 16.13 Several European countries also recommend MCV4 vaccination in toddlers and/or adolescents.14 Since their launch in 2015, MenB vaccines have been introduced into routine national vaccination programs, often in infants, in a number of European countries, and other countries worldwide including the UK, US and Australia.14-17 MenACYW-TT (MenQuadfi(r); Sanofi, Swiftwater, US) is a quadrivalent meningococcal polysaccharide (Serogroups A, C, W and Y) tetanus toxoid-conjugate vaccine, and does not contain an adjuvant. It was licensed in the US for use in individuals aged >=2 years of age, and individuals aged >=12 months in the EU, Australia, Canada, Brazil, and other countries. MenACYW-TT has been extensively evaluated in toddlers, children, adolescents and adults (including those over 65 years),18-21 and more recently in infants from 6 weeks of age.22 A dose of MenACYW-TT in those primed 4-10 years previously with an MCV4 (MCV4-DT or MCV4-CRM), at age 10 years or older, was previously demonstrated to boost the immune response in adolescents and adults.23 Similarly, a dose of MenACYW-TT in children aged 4-5 years who received a primary dose of MenACYW-TT or MCV4-TT as toddlers also demonstrated robust boosting of the immune response.24 The aim of this phase IIIb study was to evaluate the immunogenicity and safety of a booster dose of MenACYW-TT 3-6 years after a priming vaccination with either MenACYW-TT or MCV4-CRM (Menveo, GSK) in adolescents and adults in the US, with and without co-administration of a MenB vaccine, and to evaluate the persistence of the immune response to MenACYW-TT and MCV4-CRM 3-6 years after vaccination. Methods Study design and participants This was a phase IIIb, open-label, partially randomized, parallel-group, active-controlled, multicenter study to evaluate the immunogenicity and safety of a booster dose of MenACYW-TT when administered alone or co-administered with licensed MenB vaccines in adolescents and adults (WHO Universal Trial Number [UTN]: U1111-1217-2137; Clinicaltrials.gov, NCT04084769). The study was conducted between September 2019 and September 2020 at 29 centers in the United States and 1 center in Puerto Rico. The study was approved by the appropriate independent ethics committees and institutional review boards before its initiation. The conduct of this study was consistent with standards established by the Declaration of Helsinki and compliant with the International Conference on Harmonization guidelines for Good Clinical Practice, including all local and/or national regulations, and directives. Participants were eligible for inclusion if they were aged >=13 to <26 years on the day of screening, and had participated in and completed any of two previous studies of MenACYW-TT (MenQuadfi(r); Sanofi, Swiftwater, Pennsylvania) in the US (MET50 [NCT02199691] or MET43 [NCT02842853]),21,25 or had received a routine MCV4-CRM vaccine (Menveo(r), GSK Vaccines, Sovicille, Italy) 3-6 years prior. Exclusion criteria included anyone who had received any vaccine in the 4 weeks preceding the study vaccine, except for influenza which could be received at least 2 weeks prior to the study, and had received any other meningococcal vaccination since the participation in the previous study of MenACYW-TT, had a known or suspected congenital/acquired immunodeficiency or had received immunosuppressive therapy or systemic corticosteroid therapy (for >=2 consecutive weeks) within 6 or 3 months prior to the study, respectively, had a personal history of Guillain-Barre syndrome, or had received oral or injectable antibiotic therapy within 72 h prior to the first blood draw. Participants aged >=13 to <18 years of age signed an assent form and their parent or guardian signed and dated the informed consent form (ICF) before any procedure or treatment associated with the trial performed. Those >=18 years of age signed and dated the ICF themselves. Procedures Participants who had previously received a priming dose of MenACYW-TT (MenACYW-TT primed) were randomized 2:1:1 to receive a booster dose of MenACYW-TT either alone (Group 1), or co-administered with a single dose of a licensed MenB vaccine, MenB-T (Trumenba(r), Pfizer, Philadelphia; Group 3) or 4CMenB (Bexsero, GSK Vaccines, Sovicille, Italy; Group 4). Participants who had previously received a priming dose of MCV4-CRM were assigned to receive a booster dose of MenACYW-TT vaccine alone (Group 2). Only laboratory technicians were blinded to treatment assignment. The booster dose of MenACYW-TT was administered intramuscularly (IM) into the deltoid muscle of the arm. Each MenACYW-TT dose was presented in 0.5 mL of saline solution containing 10 mg of each meningococcal capsular polysaccharide serogroups A, C, Y and W, and approximately 55 mg of tetanus toxoid protein carrier. MenB-T and 4CMenB were administered IM into the deltoid muscle of the opposite arm to that used for MenACYW-TT administration. Each MenB-T dose was presented in 0.5 mL containing factor H binding protein (fHBP) subfamily A, fHBP subfamily B, adsorbed on AIPO4. Each 4CMenB dose was presented as 0.5 mL containing recombinant N. meningitidis group B Neisseria Heparin Binding Antigen, group B Neisseria adhesin A protein, group B fHbp fusion protein and outer membrane vesicles from N. meningitidis group B strain NZ98/254 adsorbed on Al(OH)3. Second and third (if applicable) MenB doses were offered 30 and 180 days after the first MenB dose, respectively, in line with the US FDA-approved schedules for the respective MenB vaccines. These vaccinations were performed outside of study procedures and were not described in the study protocol. Immunogenicity Blood samples for immunogenicity analyses were obtained prior to (Day 0) and 30 (+14) days after booster vaccination. A subset of the first 50 participants enrolled into groups 1 (MenACYW-TT primed, MenACYW-TT booster) and 2 (MCV4-CRM primed, MenACYW-TT booster) provided additional post-vaccination samples on Day 6 (+-1 day). Functional antibody titers against meningococcal serogroups A, C, W and Y were measured by a serum bactericidal antibodies assay using human complement (hSBA; Global Clinical Immunology, Sanofi, Swiftwater, PA), as described previously.26 The lower limit of quantification for the hSBA assay was 1:4. Vaccine seroresponse for serogroups A, C, Y and W was defined as hSBA pre-vaccination titer <1:8 for participants with a post-vaccination titer >=1:16; or a >=4-fold increase in titer post-vaccination for participants with a pre-vaccination titer >=1:8. Vaccine seroprotection was defined as hSBA titers >=1:8. The primary immunogenicity endpoints of this study were vaccine seroresponse rates against meningococcal serogroups (A, C, W and Y) following a booster dose of MenACYW-TT in participants primed with MenACYW-TT 3-6 years previously, based on hSBA titers pre-booster and 30 days post booster. The secondary immunogenicity endpoints were hSBA seroresponse and seroprotection rates and geometric mean titers (GMTs) against serogroups A, C, W and Y in MenACYW- MCV4-CRM-primed participants, pre- (to evaluate persistence of immune response) and 30 days post-MenACYW-TT booster and, for a subset of participants, at 6 days post booster. In addition, vaccine hSBA seroresponse, seroprotection and GMTs to serogroups A, C, W and Y were determined following MenACYW-TT booster alone or co-administered with MenB-T or 4CMenB. Safety Participants were observed for 30 min after vaccination to ensure their safety, during which, any unsolicited systemic adverse event (AE) was recorded. The occurrence of solicited injection site (pain, erythema and swelling) and systemic reactions (fever, headache, malaise and myalgia) were recorded up to 7 days after vaccination in the participant's diary card provided to the parents/guardians. Parents or guardians were asked to inform the investigators of any potential serious adverse events (SAEs) immediately. Unsolicited AEs were collected from Day 0 to Day 30 and medically attended AEs (MAAEs) and (SAEs) including AEs of special interest (AESIs) were recorded throughout the study (up to the 6-month [+14 days] follow-up phone call). Adverse events classified as AESIs were generalized seizures (febrile and non-febrile), Kawasaki disease, Guillain-Barre syndrome and idiopathic thrombocytopenia purpura. Adverse events were assessed by the investigator for relatedness to the study vaccine and for intensity (grade 1 intensity [mild] to grade 3 [severe; interrupts usual daily activity]). Statistical analyses A total of approximately 600 participants were planned to be enrolled. Three full analysis sets (FAS) were defined: FAS1 included participants who received at least one study vaccine booster dose and had a valid Day 6 serology result; FAS2 included participants who received at least one booster dose and had a valid Day 30 serology result; and FAS3 (for antibody persistence) included participants who had a valid Day 0 serology result. Two per protocol analysis sets (PPAS) were defined: PPAS1 for Day 6, and PPAS2 for Day 30 samples, each comprising participants from FAS1 or FAS2, respectively, who had no protocol deviations. Participant data in the FAS and PPAS were analyzed according to the groups that the participants were randomized to. The safety analysis set (SafAS) was defined as all participants who received at least one dose of the study vaccine(s) and had safety data available. Safety was analyzed for participants in the SafAS according to the vaccine(s) they had received at Day 0. Immunogenicity analyses were performed in the FAS2 and PPAS2 for Day 30 results and in the FAS1 and PPAS1 for Day 6 results; antibody persistence was assessed on the FAS3. Vaccine seroresponse sufficiency (primary objective) was demonstrated if the lower limit of the 1-sided 97.5% confidence interval (CI) calculated using the Clopper-Pearson method for the percentage of participants with hSBA vaccine seroresponse against serogroups A, C, W and Y, was greater than 75%. Seroresponse sufficiency was evaluated separately for Group 1 (MenACYW-TT primed, MenACYW-TT booster) and Group 2 (MCV4-CRM primed, MenACYW-TT booster). Data from participants of the MET50 and MET43 studies were used to evaluate antibody persistence and overall trends over 3-6 years post-priming with MenACYW-YY or MCV4-CRM. Antibody titers and corresponding 95% CIs were calculated on Log10 transformed data, assuming a normal distribution for the transformed data, with antilog transformations applied to provide GMTs and their 95% CIs. Participants who were previously primed with MCV4-CRM outside of prior studies were not included in the assessment of antibody persistence. Results Study participants A total of 570 participants were enrolled in the study: 381 from the MET50 trial and 140 from the MET43 trial who had received either MenACYW-TT or MCV4-CRM, and 49 participants who received MCV4-CRM as part of routine immunization. Of these, 191 Group 1 (MenACYW-TT primed) participants and 190 Group 2 (MCV4-CRM primed) participants received MenACYW-TT booster alone, 95 MenACYW-TT primed participants received MenACYW-TT booster +MenB-T (Group 3) and 94 MenACYW-TT primed participants received the MenACYW-TT booster +4CMenB (Group 4) (Table 1 and Fig. 1). A total of 560 (98.2%) participants completed the trial (Fig. 1). The mean (SD) age of participants was 15.4 (1.4) years and was balanced across vaccine groups (Table 1). The majority of participants were white (87.2%), and the male:female ratio varied from 0.93 to 1.32 across the groups (Table 1).Table 1 Baseline demographics (randomized and assigned groups). Group 1 Group 2 Group 3 Group 4 (N = 191) (N = 190) (N = 95) (N = 94) Sex, n (%) Male 92 (48.2) 105 (55.3) 54 (56.8) 49 (52.1) Female 99 (51.8) 85 (44.7) 41 (43.2) 45 (47.9) Sex ratio, male:female 0.93 1.24 1.32 1.09 Age (years) Mean age, years (SD) 15.4 (1.6) 15.8 (1.4) 15.1 (1.1) 15.3 (1.3) Min, max 13.0, 24.0 13.0, 23.0 13.0, 18.0 13.0, 22.0 Race, n (%) White 163 (85.3) 165 (86.8) 83 (87.4) 86 (91.5) Asian 0 0 0 0 Black or African American 19 (9.9) 16 (8,4) 7 (7.4) 7 (7.4) American Indian or Alaska Native 0 0 0 0 Native Hawaiian or Pacific Islander 1 (0.5) 0 0 1 (1.1) Mixed 8 (4.2) 6 (3.2) 5 (5.3) 0 Not reported 0 2 (1.1) 0 0 Unknown 0 1 (0.5) 0 0 Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 2, MCV4-CRM primed: MenACYW-TT booster; Group 3, MenACYW-TT booster +MenB-T; Group 4, MenACYW-TT booster +4CMenB. n number of subjects with baseline demographic, N number of subjects in all randomized or assigned groups, SD standard deviation. Fig. 1 Participant disposition flow chart. *subset cohort+ one participant was withdrawn by parent and Day 30 visit not conducted due to COVID-19, two participants were lost to follow up and Day 30 visit not conducted due to COVID-19, and one participant was enrolled in error (previously vaccinated with another meningococcal vaccine)++ Day 30 visit was not conducted (due to COVID-19 for 3/4 participants)P Day 30 visit was not conducted for one participant due to parental concern about COVID-19, and one participant was enrolled in error (previously vaccinated with another meningococcal vaccine). Immunogenicity Immunogenicity of the MenACYW-TT booster dose The primary endpoint of the sufficiency of the vaccine seroresponse to serogroups A, C, W and Y at Day 30 following a booster dose of MenACYW-TT alone was achieved in Group 1 and 2 participants (Table 2). At 30 days after a booster dose of MenACYW-TT, seroresponse was seen in >93% of participants across serogroups, regardless of the priming vaccination (Table 2).Table 2 Sufficiencya of the proportion of participants with an hSBA vaccine seroresponseb to serogroups A, C, W and Y at Day 30 following MenACYW-TT booster in Group 1 and Group 2 (PPAS2). Group 1 (N = 174) Group 2 (N = 176) Serogroup n/M % (95% CI) Lower limit of 1-sided 97.5% CI Sufficiencya n/M % (95% CI) Lower limit of 1-sided 97.5% CI Sufficiencya A 165/174 94.8 (90.4, 97.6) 90.4 Yes 164/176 93.2 (88.4, 96.4) 88.4 Yes C 169/174 97.1 (93.4, 99.1) 93.4 Yes 174/176 98.9 (96.0, 99.9) 96.0 Yes W 170/174 97.7 (94.2, 99.4) 94.2 Yes 174/176 98.9 (96.0, 99.9) 96.0 Yes Y 172/174 98.9 (95.9, 99.9) 95.9 Yes 176/176 100 (97.9, 100) 97.9 Yes Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 2, MCV4-CRM primed: MenACYW-TT booster. CI confidence interval, n number of participants with seroresponse, N number of participants in PPAS2, M number of participants with valid serology results. ahSBA vaccine seroresponse sufficiency was demonstrated if the lower limit of the 1-sided 97.5% CI > 75%. bFor a participant with a pre-vaccination titer <1:8, the post-vaccination titer must be >=1:16; For a participant with a pre-vaccination titer >=1:8, the post-vaccination titer must be at least 4-fold greater than the pre-vaccination titer. On Day 30 after MenACYW-TT booster vaccination, nearly all participants demonstrated hSBA vaccine seroprotection against each serogroup in Groups 1 and 2 (serogroup A, 99.4% [95% CI 96.8, 100] and 99.4% [95% CI 96.9, 100]; serogroup C, 100.0% [95% CI 97.9, 100] and 100% [95% CI 07.9, 200]; serogroup W, 100% [95% CI 97.9, 100] and 100% [95% CI 97.9, 100]; and serogroup Y, 100% [95% 97.9, 100] and 100% [95% 97.9, 100], respectively). Day 30 GMTs were also comparable between Group 1 and Group 2 for serogroups A, W and Y, with higher GMTs for serogroup C in Group 1 (Table 3).Table 3 GMTs (hSBA) 30 days after a MenACYW-TT booster in MenACYW-TT-primed and MCV4-CRM primed participants (PPAS2). Group 1 (N = 174) Group 2 (N = 176) Group 1/Group 2 Serogroup M GMT (95% CI) M GMT (95% CI) GMTR (95% CI) A 174 502 (388, 649) 176 399 (318, 502) 1.26 (0.89, 1.77) C 174 3708 (3146, 4369) 176 2533 (2076, 3091) 1.46 (1.13, 1.89) W 174 2290 (1934, 2711) 176 2574 (2178, 3041) 0.89 (0.70, 1.13) Y 174 2308 (1925, 2767) 176 3036 (2547, 3620) 0.76 (0.59, 0.98) Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 2, MCV4-CRM primed: MenACYW-TT booster. CI confidence interval, GMT geometric mean titer, GMTR geometric mean titer ratio, M number of participants with valid serology results, N number of participants in PPAS2. The proportion of participants achieving a vaccine seroresponse 6 days after a booster dose of MenACYW-TT alone was high for each serogroup, regardless of the priming vaccine, ranging from 82.6% [95% CI 68.6, 92.2] to 97.8% [95% CI 88.5, 99.9] in Group 1 and from 77.8% [95% CI 62.9, 88.8] to 93.3% [95% CI 81.7, 98.6] in Group 2 (Fig. 2).Fig. 2 Proportion of participants with hSBA vaccine seroresponse at Day 6 post-MenACYW-TT booster. Proportion of participants with hSBA vaccine seroresponse at Day 6 post-MenACYW-TT booster in MenACYW-TT primed (Group 1) and MCV4-CRM primed (Group 2) participants (PPAS1). Errors bars indicate 95% confidence intervals. Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 2, MCV4-CRM primed: MenACYW-TT booster. *For a participant with a pre-vaccination titer <1:8, the post-vaccination titer must be >=1:16; for a participant with a pre-vaccination titer >=1:8, the post-vaccination titer must be at least 4-fold greater than the pre-vaccination titer Most participants in both groups demonstrated hSBA seroprotection by Day 6 post booster (Serogroup A, 91.3% [95% CI 79.2, 97.6] and 95.6% [95% CI 84.9, 99.5]; Serogroup C, 100% [95% CI 92.3, 100] and 97.8% [95% CI 88.2, 99.9]; Serogroup W, 100% [95% CI 92.3, 100] and 100% [95% CI 92.1, 100]; and Serogroup Y, 97.8% [95% CI 88.5, 99.9] and 100.0% [95% CI 92.1, 100], in Group 1 and Group 2, respectively). The Day 6 GMTs were also comparable in Group 1 and Group 2 for serogroups A and Y, and were higher for serogroups C and W in Group 1 (Supplementary Table S1). Persistence of the immune response to MenACYW-TT and MCV4-CRM priming vaccinations administered 3-6 years earlier post-primary vaccination data from the initial MET50 and MET43 studies showed increases in GMTs for all four serogroups. GMTs then declined over the 3-6 years following this priming vaccination, but remained higher than pre-vaccination levels for those participants with the available data from previous trials (Fig. 3). Three to six years following the priming vaccination the GMTs for serogroups C, W and Y were higher in those with MenACYW-TT priming vaccination (Groups 1, 3, and 4) than MCV4-CRM priming vaccination (Group 2), and comparable for serogroup A (Fig. 3). Similarly, at Day 0 before booster, more than 50% of participants in each vaccine group demonstrated hSBA vaccine seroprotection, with over 85% of those primed with MenACYW-TT demonstrating seroprotection to serogroups C and W 3-6 years after the priming vaccination (Supplementary Table S2).Fig. 3 Persistence of hSBA GMTs following priming vaccination with MenACYW-TT or MCV4-CRM. Persistence of hSBA GMTs to serogroup A (a), serogroup C (b), serogroup W (c) and serogroup Y (d) following priming vaccination with MenACYW-TT or MCV4-CRM (FAS3). CI, confidence interval; GMT, geometric mean titer; N, total subjects; hSBA human complement serum bactericidal antibody assay. MenACYW-TT primed (red line), Group 1, 3 and 4 participants who were MenACYW-TT primed in the previous studies, MET50 or MET43; MCV4-CRM primed (blue line), Group 2 participants who were MCV4-CRM primed in the previous study, MET50. Co-administration of MenACYW-TT vaccine with MenB vaccines In MenACYW-TT primed participants, seroresponse at Day 30 was comparable between Groups 1, 3 and 4 (Fig. 4). Seroprotection to each of the serogroups was also comparable across these groups (Supplementary Table S3), as were GMTs (Table 4).Fig. 4 Percentage of subjects achieving hSBA vaccine seroresponse at Day 30 post-booster with MenACYW-TT booster alone, or co-administered with MenB-T or 4CMenB. Errors bars indicate 95% confidence intervals. hSBA, human complement serum bactericidal antibody assay Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 3, MenACYW-TT primed: MenACYW-TT booster +MenB-T; Group 4, MenACYW-TT primed: MenACYW-TT booster +4CMenB *For a participant with a pre-vaccination titer <1:8, the post-vaccination titer must be >=1:16; for a participant with a pre-vaccination titer >=1:8, the post-vaccination titer must be at least 4-fold greater than the pre-vaccination titer Table 4 GMTs (hSBA) to each of the serogroups at Day 0 and Day 30 in MenACYW-TT primed participants who received MenACYW-TT booster alone or co-administered with a MenB vaccine (PPAS2). Group 1 (N = 174) Group 3 (N = 90) Group 4 (N = 89) Group 1/Group 3 Group 1/Group 4 Serogroup Time point M GMT (95% CI) M GMT (95% CI) M GMT (95% CI) GMTR (95% CI) GMTR (95% CI) A D 0 174 11.7 (9.89, 13.8) 90 12.5 (9.78, 16.0) 88 12.3 (9.37, 16.2) 0.934 (0.699, 1.25) 0.947 (0.699, 1.28) D 30 174 502 (388, 649) 90 593 (426, 825) 89 667 (477, 933) 0.847 (0.552, 1.30) 0.752 (0.489, 1.16) C D 0 174 36.6 (28.8, 46.7) 90 37.6 (26.6, 53.3) 89 42.4 (29.4, 61.0) 0.974 (0.642, 1.48) 0.865 (0.566, 1.32) D 30 174 3708 (3146, 4369) 90 4741 (3882, 5791) 88 3472 (2667, 4518) 0.782 (0.597, 1.02) 1.07 (0.795, 1.44) W D 0 174 27.0 (22.0, 33.1) 90 28.3 (22.0, 36.4) 88 30.0 (22.5, 40.1) 0.953 (0.681, 1.33) 0.897 (0.631, 1.28) D 30 174 2290 (1934, 2711) 90 2702 (2134, 3422) 89 2064 (1601, 2662) 0.847 (0.635, 1.13) 1.11 (0.824, 1.49) Y D 0 174 20.5 (16.6, 25.2) 89 25.5 (19.4, 33.6) 89 21.0 (15.4, 28.7) 0.802 (0.565, 1.14) 0.975 (0.677, 1.40) D 30 174 2308 (1925, 2767) 90 2600 (2042, 3311) 89 2469 (1881, 3241) 0.888 (0.654, 1.20) 0.935 (0.680, 1.28) Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 3, MenACYW-TT booster +MenB-T; Group 4, MenACYW-TT booster +4CMenB. CI confidence interval, GMTR geometric mean titer ratio, M number of participants with valid serology results for the particular subgroup, N number of participants in PPAS2. Safety No participants in Groups 1, 3 or 4 reported an immediate unsolicited event. One participant in Group 2 (0.5% [1/184]) experienced an immediate unsolicited AE of Grade 2 presyncope, related to the study vaccination. Solicited reactions were reported at similar frequencies between Group 1 and Group 2 participants (>=1 solicited injection site reaction, 42.5% [79/186] and 35.9% [66/184], respectively; >=1 solicited systemic reaction, 54.3% [101/186] and 54.3% [100/184], respectively. Higher frequencies of solicited reactions were reported overall for the two MenB co-administration booster groups, Groups 3 and 4 (>=1 solicited injection site reaction, 83.7% [77/92] and 92.4% [85/92]; >=1 solicited systemic reaction, 75.0% [69/92] in each group) (Table 5). Injection site pain was the most frequently reported solicited injection site reaction in each group, occurring at the highest frequency in Groups 3 and 4. The most frequent solicited systemic reactions were headache, malaise and myalgia in Group 1 and Group 2, and myalgia in Groups 3 and 4; myalgia was reported more frequently in the MenB co-administration booster groups than in the other groups (Supplementary Table S4). Solicited injection site reactions and solicited systemic reactions were mostly of mild (grade 1) intensity (Supplementary Table S5)Table 5 Safety overview. Group 1 (N = 186) Group 2 (N = 184) Group 3 (N = 93) Group 4 (N = 92) Subjects experiencing at least one: n/N % (95% CI) n/N % (95% CI) n/N % (95% CI) n/N % (95% CI) Within 30 min after vaccination Immediate unsolicited AE 0/186 0 (0, 2.0) 1/184 0.5 (0. 3.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) Immediate unsolicited AR 0/186 0 (0, 2.0) 1/184 0.5 (0. 3.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) Within 7 days after vaccination Solicited reaction 126/186 67.7 (60.5, 74.4) 11/184 59.8 (52.3, 66.9) 82/92 89.1 (80.9, 94.7) 88/92 95.7 (89.2, 98.8) Solicited injection site reaction 79/186 42.5 (35.3, 49.9) 66/184 35.9 (28.9, 43.3) 77/92 83.7 (74.5, 90.6) 85/92 92.4 (84.9, 96.9) MenACYW-TT 79/186 42.5 (35.3, 49.9) 66/184 35.9 (28.9, 43.3) 47/92 51.1 (40.4, 61.7) 52/92 56.85 (45.8, 66.8) MenB-T NA NA NA NA NA NA 69/92 75.0 (64.9, 83.4) NA NA NA 4CMenB NA NA NA NA NA NA NA NA NA 71/92 77.2 (67.2, 85.3) Solicited systemic reactions 101/186 54.3 (46.9, 61.6) 100/184 54.3 (46.9, 61.7) 69/92 75.0 (64.9, 83.4) 69/92 75.0 (64.9, 83.4) Within 30 days after vaccination Unsolicited AE 43/186 23.1 (17.3, 29.8) 49/184 26.6 (20.4, 33.6) 23/93 24.7 (16.4, 34.8) 24/92 26.1 (17.5, 36.3) Unsolicited AR 5/186 2.7 (0.9, 6.2) 7/184 3.8 (1.5, 7.7) 2/93 2.2 (0.3, 7.6) 3/92 3.3 (0.7, 9.2) Unsolicited non-serious AE 43/186 23.1 (17.3, 29.8) 49/184 26.6 (20.4, 33.6) 23/93 24.7 (16.4, 34.8) 24/92 26.1 (17.5, 36.3) Unsolicited non-serious AR 5/186 2.7 (0.9, 6.2) 7/184 3.8 (1.5, 7.7) 2/93 2.2 (0.3, 7.6) 3/92 3.3 (0.7. 9.2) Unsolicited non-serious injection site AR 4/186 2.2 (0.6, 5.4) 2/184 1.1 (0.1, 3.9) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) MenACYW-TT 4/186 2.2 (0.6, 5.4) 2/184 1.1 (0.1, 3.9) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) MenB-T NA NA NA NA NA NA 0/93 0 (0, 3.9) NA NA NA 4CMenB NA NA NA NA NA NA NA NA NA 0/92 0 (0, 3.9) Unsolicited non-serious systemic AE 39/186 21.0 (15.4, 27.5) 47/184 25.5 (19.4, 32.5) 23/93 24.7 (16.4, 34.8) 24/92 26.1 (17.5, 36.3) Unsolicited non-serious systemic AR 1/186 0.5 (0, 3.0) 5/184 2.7 (0.9, 6.2) 2/93 2.2 (0.3, 7.6) 3/92 3.3 (0, 3.9) AE leading to study discontinuation 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) AR leading to study discontinuation 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) SAE 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) Related SAE 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) Death 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) AESI 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) MAAE 9/186 4.8 (2.2, 9.0) 13/184 7.1 (3.8, 11.8) 7/93 7.5 (3.1, 14.9) 9/92 9.8 (4.6, 17.8) During the study SAE 2/186 1.1 (0.1, 3.8) 2/184 1.1 (0.1, 3.9) 2/93 2.2 (0.3, 7.6) 0/92 0 (0, 3.9) Related SAE 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) Death 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) AESI 0/186 0 (0, 2.0) 0/184 0 (0, 2.0) 0/93 0 (0, 3.9) 0/92 0 (0, 3.9) Group 1, MenACYW-TT primed: MenACYW-TT booster; Group 2, MCV4-CRM primed: MenACYW-TT booster; Group 3, MenACYW-TT booster +MenB-T; Group 4, MenACYW-TT booster +4CMen. AE adverse event, AESI adverse event of special interest, AR adverse reaction, CI confidence interval, MAAE medically attended adverse event, n number of subjects with the outcome listed, N number of subjects in Safety Analysis Set, SAE serious adverse event. No participants experienced a serious AE (SAE) within 30 days of vaccination, and no participants experienced AEs or adverse reaction (AR) which led to study discontinuation. During the study, six SAEs were reported: two cases of Grade 3 appendicitis (one each in Group 1 and Group 2), two cases of Grade 3 suicidal ideation (one each in Group 1 and Group 2), one case of Grade 3 major depression and suicidal ideation (Group 3) and one case of Grade 3 accidental overdose (Group 3). All occurred between Day 31 and the 6-month follow-up contact and were not considered related either by the investigator or by the sponsor. No deaths or AEs of special interest were reported. Discussion This phase IIIb, open-label, partially randomized, parallel-group, multicenter trial demonstrated that a booster dose of MenACYW-TT in adolescents and adults who had been vaccinated 3-6 years earlier with a single dose of MenACYW-TT or MCV4-CRM was immunogenic and well tolerated, with in the sufficiency of seroresponse demonstrated at Day 30 post booster. We observed a robust response to a booster dose of MenACYW-TT, with over 93% seroresponse for all serogroups in adolescents and adults. The seroresponse rate was greater than 75% for all serogroups in both Groups 1 and 2 by Day 6, suggesting a quick onset of the immune response, regardless of the priming vaccine (MenACYW-TT or MCV4-CRM). This observation supports previous studies of a booster dose of MenACYW-TT which have shown similar results,23,24 and is indicative of immune memory in these participants. Such a rapid anamnestic response is important to be able to rapidly boost protection against infection among groups of at-risk individuals whose protective antibody levels may have waned over time and thus may otherwise be at risk of a potential outbreak. Vaccination with MenACYW-TT as a booster in adolescents and adults vaccinated 3-6 years earlier with MenACYW-TT or MCV4-CRM was found to be well tolerated with no safety concerns identified. There were no SAEs within 30 days of the booster, or discontinuations due to AEs. When examining the persistence of the immune response, 3-6 years after the priming vaccination with either MenACYW-TT or MCV4-CRM, prior to the booster vaccination, seroprotection ranged from 52% to 91% across the serogroups and vaccine groups. GMTs at Day 0, pre-booster, were higher than those prior to the priming vaccine in participants from previous studies,20,25 suggesting the persistence of the immune response in these participants. GMTs were also higher pre-booster in those primed with MenACYW-TT compared to those primed with MCV4-CRM for serogroups C, W and Y. These results demonstrate for the first time persistence of the immune response in adolescents and young adults and are in line with previous studies of a booster dose of MenACYW-TT findings showing persistence of the immune response in a younger population.24 Based on the GMTRs at Day 30 post booster dose for Groups 1 (MenACYW-TT primed) and 2 (MCV4-CRM-primed), possible evidence of a statistically significant difference for serogroups C and Y (considering 95% CIs do not cross 1) was observed; however, it must be noted that a formal statistical hypothesis to evaluate such a difference was not a part of the planned analysis and is a post-hoc observation. The co-administration of the MenACYW-TT booster with a MenB vaccine did not affect the immunogenicity of serogroups A, C, Y and W, compared to the administration of the MenACYW-TT booster alone. Solicited AEs were mostly of mild intensity but showed a numerical increase, particularly in malaise and myalgia, likely influenced by the known reactogenic profile of MenB vaccines.27-32 Co-administration of these vaccines will be important in a number of countries globally, including the US, to facilitate the provision of broader protection against IMD particularly in higher-risk groups such as adolescents. While this study assessed the co-administration of MenACYW-TT and MenB vaccines, the immunogenicity of MenB vaccines when co-administered with MenACYW-TT was not assessed in this study due to non-availability of relevant assays. It will be important to address this in future studies. In addition, we did not have post-priming vaccine data for the 49 participants who had not participated in the previous MET50 or MET43 clinical studies and as such these participants were not included in the analysis of antibody persistence. This study may also have benefitted from the inclusion of an additional group of participants as a control to assess the response of a single dose of MenACYW-TT in vaccine-naive participants; however, studies showing robust immunogenicity of a single dose of MenACYW-TT in this age group have been published previously.20,25 This study offers key data about the immunogenicity and safety of MenACYW-TT when administered as a booster alone or co-administered with a MenB vaccine, in participants primed with MenACYW-TT or MCV4-CRM. A booster dose of MenACYW-TT produced a comparable and robust response to all serogroups in adolescents and adults who had received a priming dose of either MenACYW-TT or MCV4-CRM 3-6 years earlier. In addition, no interference of the immune response to MenACYW-TT was observed when MenACYW-TT was co-administered with MenB-T or 4CMenB vaccines. Supplementary information Supplementary Materials Supplementary information The online version contains supplementary material available at 10.1038/s41390-023-02478-5. Acknowledgements The authors would like to thank all participants who volunteered to take part in the study, and all study investigators. Editorial assistance with the preparation of the manuscript was provided by Holly McAlister and Juliette Gray, PhD, of inScience Communications, Springer Healthcare Ltd, UK, and was funded by Sanofi. The authors also wish to acknowledge and thank the Sanofi study team for the support during the conduct of this study. Author contributions All authors attest that they meet the ICMJE criteria for authorship. G.A., J.Pa., E.J. and M.S.D. were involved in the study design. J.Pe., C.D,. K.J., C.Sp., C.Se., M.S., R.H., M.A. and B.B. were involved in data acquisition. B.Z., J.S., J.Pa., A.H., D.v.V., K.V., G.A. and M.S.D were involved in data analysis and study interpretation. All authors reviewed and approved the submission of the final manuscript. Funding This study was funded by Sanofi. Data availability Qualified researchers may request access to patient-level data and related documents [including, e.g., the clinical study report, study protocol with any amendments, blank case report form, statistical analysis plan, and dataset specifications]. Patient-level data will be anonymized, and study documents will be redacted to protect the privacy of trial participants. Further details on Sanofi's data-sharing criteria, eligible studies, and process for requesting access can be found at Competing interests B.Z., J.S., J.Pa., A.H., D.V.B., K.V., E.J. and M.S.D. are employees of Sanofi and may hold stocks/shares. C.D., K.J. and J.Pe. received funding from Sanofi to support work for the trial. B.B., R.H., M.S., C.Se., C.Sp. and M.A. have no conflicts of interest to declare. G.A. was an employee of Sanofi at the time this study was conducted. Consent to participate Participants aged >=13 to <18 years of age signed an assent form and their parent or guardian signed and dated the informed consent form (ICF) before any procedure or treatment associated with the trial performed. Those >=18 years of age signed and dated the ICF themselves. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. These authors contributed equally: Betzana Zambrano, German Anez. References 1. European Centre for Disease Prevention and Control (ECDC). Factsheet about meningococcal disease. (accessed October 2021). 2. Erickson LJ De Wals P McMahon J Heim S Complications of meningococcal disease in college students Clin. Infect. Dis. 2001 33 737 739 10.1086/322587 11477523 3. Jafri RZ Global epidemiology of invasive meningococcal disease Popul. Health Metr. 2013 11 17 10.1186/1478-7954-11-17 24016339 4. 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PMC10000354 | Behav Res Methods Behav Res Methods Behavior Research Methods 1554-351X 1554-3528 Springer US New York 36897503 2063 10.3758/s13428-023-02063-y Article LEXpander: Applying colexification networks to automated lexicon expansion Di Natale Anna [email protected] 123 Garcia David 1234 1 grid.410413.3 0000 0001 2294 748X Institute of Interactive Systems and Data Science, Graz University of Technology, Inffeldgasse 16c/I, Graz, 8010 Austria 2 grid.22937.3d 0000 0000 9259 8492 Section for Science of Complex Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria 3 grid.484678.1 Complexity Science Hub Vienna, Josefstadter Strasse 39, 1080 Vienna, Austria 4 grid.9811.1 0000 0001 0658 7699 Department of Politics and Public Administration, University of Konstanz, Universitatsstrasse 10, 78464 Konstanz, Germany 10 3 2023 10 3 2023 2024 56 2 952967 6 1 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit Recent approaches to text analysis from social media and other corpora rely on word lists to detect topics, measure meaning, or to select relevant documents. These lists are often generated by applying computational lexicon expansion methods to small, manually curated sets of seed words. Despite the wide use of this approach, we still lack an exhaustive comparative analysis of the performance of lexicon expansion methods and how they can be improved with additional linguistic data. In this work, we present LEXpander, a method for lexicon expansion that leverages novel data on colexification, i.e., semantic networks connecting words with multiple meanings according to shared senses. We evaluate LEXpander in a benchmark including widely used methods for lexicon expansion based on word embedding models and synonym networks. We find that LEXpander outperforms existing approaches in terms of both precision and the trade-off between precision and recall of generated word lists in a variety of tests. Our benchmark includes several linguistic categories, as words relating to the financial area or to the concept of friendship, and sentiment variables in English and German. We also show that the expanded word lists constitute a high-performing text analysis method in application cases to various English corpora. This way, LEXpander poses a systematic automated solution to expand short lists of words into exhaustive and accurate word lists that can closely approximate word lists generated by experts in psychology and linguistics. Supplementary Information The online version contains supplementary material available at 10.3758/s13428-023-02063-y. Keywords Colexification networks Lexicon expansion Text analysis Word embeddings Medical University of Viennaissue-copyright-statement(c) The Psychonomic Society, Inc. 2024 pmcIntroduction Lists of words are widely used in many text analysis and NLP tasks, either in a pre-processing step to retrieve relevant instances in texts or as a necessary part of text analysis algorithms, for example in methods relying on word counts. Even when applying methods not based on word lists, for example neural networks, the selection of the texts to retrieve and analyze is often based on some thematic word lists to query in larger corpora. For example, in order to classify suicide-related tweets with machine learning methods, Metzler, Baginski, Niederkrotenthaler and Garcia (2022) first retrieve relevant tweets on the basis of a word list. Furthermore, established benchmarks in text analysis, such as the SemEval benchmark for sentiment analysis (Rosenthal, Farra, & Nakov, 2017) and the Tweeteval benchmark (Barbieri, Camacho-Collados, Espinosa Anke, & Neves, 2020), are based on querying large text sources (e.g., the whole of Twitter) by using pre-specified word lists. In this work, we focus on word lists dealing with a subject, i.e., categorical lexica. These word lists, or lexica, are related to a chosen topic or behavior but do not have additional variables or metadata such as valence or sentiment ratings which indicate the strength of the belonging to a certain category. Categorical lexica are either created from scratch or adapted from already published word lists used in previous studies. Already-existing word lists might be adapted to research questions which are slightly different from the original ones. In many cases, the novel setting or the research questions of a new study require a modification of the original word list. These modifications can range from the exclusion of words not suitable for the topic analyzed, as in Metzler et al., (2022) and Jaidka et al., (2020), to the translation of those word lists into other languages, as in Werlen, Imhof and Bergamin, (2021). However, some of these manipulations could result in the introduction of noise or error in the new version of the word list. Indeed, modifications like the translation of expressions and words in a different language might not convey the same meaning as the original ones (Mohammad, 2020). Additionally, novel topics have to be addressed with word lists created ad hoc, as for example coronavirus-related word lists at the beginning of the COVID-19 pandemic, as in Banda et al., (2021), or word lists used to explore modes of drug administration not previously known to the medical personnel (Balsamo, Bajardi, Salomone, & Schifanella, 2021). Extended word lists can be manually created starting from a short selection of seed words and expanding them to create a final word list via brainstorming or with the use of a thesaurus. This approach often proves to be resource-intensive and prone to inconsistent results when replicated by different groups of people (King, Lam, & Roberts, 2017). An alternative to manual lexicon expansion is the application of automated methods to find new words. One of the first approaches is the retrieval of synonyms and related words using semantic resources like WordNet (Miller, 1995). A more recent approach consists of the use of word embedding spaces to select the closest words to each seed word, as in Balsamo et al., (2021). Indeed, according to the distributional hypothesis (Firth, 1957), the retrieved words are semantically related to the chosen seed words. One of the most elaborated lexicon expansion methods is Empath (Fast, Chen, & Bernstein, 2016a), which deploys word embeddings to generate word lists from a list of seed words. In particular, Empath constructs the expanded word list considering the closest words to the cumulative vector of the seed words in the word embedding space. Although Empath is widely used in many studies (Ribeiro, Calais, Santos, Almeida, & Meira, 2018; Shing et al.,, 2018; Zirikly, Resnik, Uzuner, & Hollingshead, 2019), the method deploys an outdated word embedding model, as the algorithm has not been updated since its release. Multiple solutions have been provided to solve the problem of lexicon expansion but researchers lack a systematic comparison of existing methods that allow both to find the best-performing ones and to validate their performance in relevant application scenarios. A notable resource in this extent is Lexifield (Mpouli, Beigbeder, & Largeron, 2020), a lexicon expansion algorithm that was compared to previous existing methods. While informative, the work on Lexifield is based on a narrow set of methods (word embedding-based and knowledge-based approaches) and on a limited set of topics (sound, taste, and odor). Another effort towards the creation of a baseline is constituted by Bozarth and Budak (2022). There, the authors investigate the problem in relation to the retrieval of tweets. In this article, we aim to provide a wider benchmark that includes methods based on synonym networks, word embeddings, and colexification networks. These methods will be used to expand word lists of wide use such as emotion words, sentiment words, words for behaviors (for example cognition and social interaction), as well as words for several other topics including family, religion, death, work and leisure. Beyond a benchmark for lexicon expansion, we also present a novel approach to the problem of automatic lexicon expansion: LEXpander. LEXpander is based on a multilingual semantic network of cross-linguistic colexifications. Colexification is a linguistic phenomenon that occurs when two different concepts are conveyed using the same word in one language. This language is said to colexify the two concepts. For example, the two concepts 'medicine' and 'poison' are expressed with only one word, 'pharmacon', in Ancient Greek. Therefore, Ancient Greek colexifies the concepts of 'poison' and 'medicine'. Since its coinage, the concept of colexification has been related to semantic similarity (Francois, 2008), that is concepts that are linked by colexification share semantic meaning (Karjus, Blythe, Kirby, Wang, & Smith, 2021; Xu, Duong, Malt, Malt, & Srinivasan, 2020). Colexification occurrences have been collected from multiple linguistic resources and organized in a network structure, where concepts that are colexified by a number of languages are linked (Croft, 2022; List, Mayer, Terhalle, & Urban, 2014). The most known cross-linguistic colexification network is Clics3 (Rzymski et al., 2020) and is built from a wide range of linguistic resources. However, this network presents a small set of concepts (less than 2000 in the newest version), unsuitable for the application to lexicon expansion. In order to increase the language coverage of Clics3, colexification networks automatically built from bilingual dictionaries have been proposed in our previous work (Di Natale, Pellert, & Garcia, 2021). In Di Natale et al., (2021), we showed that these automatically built networks encode affective relationships and reach high performance when inferring the affective ratings of words, with the FreeDict colexification network being one of the most comprehensive. In this paper, we adapt the inference method based on the FreeDict colexification network from Di Natale et al., (2021) to the expansion of categorical lexica, a method we call LEXpander. We use FreeDict instead of other colexification networks because FreeDict has been shown to yield to the best performance when recovering the affective meaning of words (Di Natale et al., 2021) and because it encompasses the highest number of words, nearly 28,000. In contrast to Di Natale et al., (2021), in this work we not only focus on the affective dimension of meaning but also aim at developing a tool of lexicon expansion, which can be applied to the most various themes. Furthermore, we do not tackle the problem of the inference of ratings of words. On the contrary, we aim at expanding thematic word lists, that is at selecting words related to a specific theme without specifying the intensity of this relationship. The term colexification encompasses the two linguistic phenomena of polysemy and homonymy. While a polysemic word is defined as a word with multiple related meanings, homonyms are words with multiple senses which are not related. In order to deploy the definition of polysemy, that is the fact that meaning linked in the colexification network are related, it is necessary to filter out homonyms. As suggested by List et al., (2018), a practical solution for this problem is to filter the network according to the number or languages and/or families of languages that present the same colexification pattern. Indeed, this filtering clears the network from most spurious links, as they would appear in only one or a few records. In Clics3, the authors suggest including colexifications that occur in at least three languages and three families of languages (Rzymski et al., 2020). Since FreeDict has a lower coverage of languages and families of languages, we exclude only occurrences that appear in less than two languages, as also indicated in Di Natale et al., (2021). A novel feature of LEXpander is that, by design, it provides a multilingual solution to the problem of lexicon expansion. Indeed, the underlying structure of colexification networks is supra-lingual (Khishigsuren et al., 2022), that is it consists of concepts that go beyond single languages. This makes the system applicable to any language included in the translation data used to build the colexification network. Note that the supra-lingual feature of this method does not imply that its performance is independent from the language chosen. Rather, it means that the method can be applied to different languages without needing to adapt the framework to the specific language chosen. In this paper, we showcase this feature by testing LEXpander for the automatic expansion of lexica both in English and German. In the literature there are few attempts at expanding word lists in languages different from English. In particular, Mpouli et al., (2020) expand word lists in English and French, Zeng, Yang, Tu, Liu and Sun (2018) deploy Chinese linguistic resources and Thavareesan and Mahesan (2020) consider the expansion of sentiment-related word lists in Tamil. However, German is a language which has not yet been addressed in previous literature of lexicon expansion algorithms. The contributions of this paper are the following: We propose a novel lexicon expansion method, LEXpander, which is based on a linguistic concept; We compare LEXpander with other widely used lexicon expansion algorithms establishing a benchmark for lexicon expansion algorithms; We show that LEXpander achieves the best precision and F1 (the trade-off between precision and recall) when expanding word lists in English and in German; We show that LEXpander has either the best or is tied with the best method in terms of correlation with exhaustive manual word lists in the analysis of English texts of online and traditional communication; We present an interactive web app to allow the easy use and extension of LEXpander. Methods Lexicon expansion algorithms In this paper, we propose a novel method for lexicon expansion, LEXpander, and compare its performance with other approaches. Text analysis applications often rely on the ad hoc creation of lexica which ideally collect all the words used to refer to a topic. LEXpander automatizes the task of creating such word lists starting from a small set of seed words. LEXpander is based on a colexification network, that is a multilingual semantic network whose structure is supra-lingual. The LEXpander model is built as follows. Given the adjacency matrix of the colexification network A = {Aij}, such that: Aij=1if conceptsiandjare colexified by at least two languages0otherwise and S = {s} set of seed words, the expanded lexicon is defined as L = S W, where: 1 W=w|Asw=1,sS In other words, given a set of seed words S, LEXpander creates a longer lexicon by retrieving all the neighbors of the seed words in the colexification network, as represented in Fig. 1. Fig. 1 Representation of the LEXpander algorithm. Seed words (blue, on the left) are mapped onto the network (step 1) and the neighbors of those words (yellow, on the right) are retrieved to create the expanded word list (step 2). In the figure, we only represent the process in the case of one word, 'merry' and we label the nodes in the colexification network according to their English word Note that the method introduced in Eq. 1 hypothetically works for any language. This is a consequence of the supra-lingual feature of the colexification network. When expanding word lists in English, we pick the English word for each concept in the network, while when considering German we do the same by selecting the German words that convey the selected concepts. In order to expand word lists in German, we deploy Eq. 1 with the German version of the colexification network. The German version of the network is obtained by selecting the German word for each supra-lingual concept of the network. Links in colexification networks can be weighted by the number of languages and the number of families of languages that colexify the same pair of concepts (List et al., 2018). These weights can be used to remove spurious patterns that would contribute to noise in the network and to estimate the strength of the relationship between concepts. While we do use weights to select meaningful links in the network, we do not consider the link weights when expanding word lists. Indeed, link weights give an estimate of the intensity of the relationship between words, which was for example used in Di Natale et al., (2021) to infer the affective ratings of words. On the contrary, the present study deals with categorical lexica and LEXpander needs to identify words that belong to a chosen topic, not the intensity of the relationship with such topic. Therefore, LEXpander is based on a filtered, unweighted colexification network. We compare the performance of LEXpander with various other automatic lexicon expansion algorithms. These methods can be divided in two classes: methods based on semantic networks and methods which deploy word embeddings. As methods based on semantic networks, we consider the widely used network of synsets retrieved from WordNet (Miller, 1995) for the expansion of English word lists and an open source version of WordNet in German, OdeNet (Siegel and Bond, 2021). The lexicon expansion approach which deploys these semantic networks is similar to the one used for LEXpander in Eq. 1: the expansion of a set of seed words consists in the retrieval of the neighbors of all the seed words in the network. One necessary step of the expansion of lexica using semantic networks is the mapping of the seed words onto the network (see Fig. 1, step 1). However, in some cases the seed words cannot be mapped onto the network and the expansion of the word list is not possible. In this case, the result of the expansion is an empty word list. Thus, together with the performance of each method we also consider the number of word lists the method could expand as a way to consider this case.1 A second class of methods we consider are approaches based on word embeddings. The creation of word embeddings involves the usage of neural models which are trained on textual data. In particular, we consider methods based on the GloVe model trained on the English Wikipedia (Pennington, Socher, & Manning, 2014) and on the German Wikipedia and the FastText model trained on the English Wikipedia and on the German Wikipedia using the skipgram model (Bojanowski, Grave, Joulin, & Mikolov, 2017). The pretrained vectors for FastText were obtained from while the English GloVe word embedding was retrieved with the R package text2vec (Selivanov, Bickel, & Wang, 2020). The pretrained vectors for the German GloVe was obtained from We consider the 25,000 most used words according to Google books ) in the application of word embedding spaces to lexicon expansion. We implement the word list expansion from word embedding spaces following the method of Mpouli et al., (2020). The first method retrieves all the words in a word embedding model that have a cosine similarity above a threshold that has been calibrated in previous work (Mpouli et al., 2020). Furthermore, we consider one more elaborated method based on word embeddings: Empath (Fast et al., 2016a). This algorithm creates the extended word list by retrieving the closest words to the embedding of the cumulative vector relative to the seed words. We deploy this method via the Empath Python package (Fast, Chen, & Bernstein, 2016b) with the default size setting, which is set to an output of 100 words for the expanded word list. Since the number of words was too low for our purposes, we tried to increase this value and considered size 300, 500, 700, and 1000. However, with these specification the Python package for Empath gave an error and did not deliver any output. Moreover, Empath is based on an old word embedding model which has not been updated since its first release. As a consequence, we decided to implement a novel version of the method and consider only that in the analyses. In particular, we re-implemented the Empath method using the newer FastText word embedding space trained on the English and German Wikipedia. Thus, we obtain two new versions of Empath, one for the expansion of English lexica and one for the expansion of German lexica. We call these re-implementations Empath 2.0. Note that, while Empath allows for the selection of the size of the final word list, Empath 2.0 does not have this feature because the mechanism used in Empath for discarding words was not documented in the original paper. As a consequence, the sizes of the word lists computed by the two versions of Empath differ, but we consider only Empath 2.0 as it is based on newer and more exhaustive word embedding models. For each of the methods, we also define a random baseline method based on the length of the resulting word lists. In the baseline algorithm, we perform 1000 random samples of words from the relative networks or word embedding spaces of the same size of the expanded lexicon resulting from each method. This serves as a null model to measure what would be the performance of a random guess when expanding word lists to given sizes. Empirical analysis In this section, we introduce the framework for the comparison of the lexica expansion algorithm and describe the tests we perform for the evaluation of said algorithms. The framework here presented can be easily applied in future research to provide a state-of-the-art approach to word list expansion and to improve the replicability and validity of future text analysis. Empirical framework We test the performance of the lexicon expansion methods in expanding sets of seed words selected from the 2015 English version (Pennebaker, Boyd, Jordan, & Blackburn, 2015) and the 2007 German version of the Linguistic Inquiry and Word Count (LIWC) (Wolf et al., 2008). LIWC is a widely used proprietary dictionary-based method for the analysis of texts (Pennebaker, Francis, & Booth, 2001). The 2015 English version of LIWC collects 73 word lists relative to various topics, including for example words indicating future orientation or referring to the family sphere. Such word lists have been used in many influential studies, as for example (Kleinberg, van der Vegt, & Mozes, 2020; Shing et al.,, 2018; Zirikly et al.,, 2019). The popularity of LIWC resulted also in its translation in various languages. In particular, we consider the German version of LIWC from 2007, which collects word lists belonging to 68 different topics. Recently, a new version of LIWC has been released (Boyd, Ashokkumar, Seraj, & Pennebaker, 2022). In this new version, new categories have been added, while some classes from previous versions have been merged together. Since we use LIWC only as a means to test the performance of lexicon expansion algorithms, we do not think that the results of the paper would vastly change using the new version of LIWC. Indeed, this paper does not provide any statement about LIWC itself, rather it is a comparison between methods in a framework that takes into account LIWC word lists and only the relative performance of the methods analyzed here is important. Indeed, the single results of the methods in the various experiments when testing them on different versions of LIWC might change but the relative performances will not vary, that is the lexicon expansion methods that achieve the best performances in the framework used in this work would maintain the same ranking when tested in a framework that considers a novel version of LIWC. Words in both the English version of LIWC from 2015 and the German from 2007 are given in a shortened form with wildcards (indicated with *) to indicate all the words with different endings but starting with the same sequence of letters. In a first preprocessing step, we match the words with wildcards with entries in dictionaries in order to retrieve the full-form words from the wildcard terms. For example, the word with wildcard 'apprehens*' from the English LIWC word list for negative emotion, is matched with the following entries in the dictionary: 'apprehensible', 'apprehension', 'apprehensive', 'apprehensiveness'. We consider the lexica resulting from this matching procedure as the original LIWC word lists. After the retrieval of the words in the LIWC word lists, the experiment is performed as follows: We first select a subset of words from each word list of LIWC to use as seed words in two ways, either at random or based on expert selection of shorter lexica called EVs, as published in Vine, Boyd and Pennebaker (2020). See "Precision study" for a more detailed explanation on EVs. We then input this seed word list in the expansion algorithms with the aim of recovering the original, complete LIWC word list. By doing so, we obtain expanded word lists. We then evaluate the performance of each lexicon expansion algorithm using three different tests. Evaluation The evaluation of the lexicon expansion methods is performed according to three tests: the performance evaluation, the precision study and the convergence validity in text analysis. The performance evaluation will be performed both with English and German word lists, while the other two tests take into account only the English expansions. This is only due to the lack of resources in German, as all analyses could in principle be performed with resources in any language. A representation of such pipeline is depicted in Fig. 2. In the following sections, the tests are described in detail. Fig. 2 Representation of the pipeline used to evaluate the word list expansion methods. Seed words are selected from the original LIWC word list (blue, on the left) either at random or selected by experts. They are then used as input of the various expansion algorithms, which give an expanded word list as output (yellow, in the center). In this figure, we represent one example of such expanded word list. In order to assess the performance of each method, we perform three different evaluation tests. Blue headlines indicate steps and evaluations performed only in English Performance evaluation In this first task, we assess the performance of the methods in expanding various word lists given a set of seed words against longer lists generated by experts. In particular, given a set of seed words extracted from the thematic word lists of LIWC, we apply the lexicon expansion methods and retrieve the expanded word list. We then compare the expanded and original LIWC word lists and assess the performance of each method by computing the precision, recall and F1 of the method. In particular, given L~ original word list and L = S W expanded lexicon constructed as in Eq. 1, we define the true positives (TP) as the words of L~ which are also present in L without seed words, that is in W. The false positives (FP) are the words in W that do not appear in L~ and the false negatives (FN) are the words in L~ not present in W. In other words: 2 TP=L~W 3 FP=W\L~ 4 FN=L~\W We can define precision and recall as follows: 5 precision=|TP||TPFP| 6 recall=|TP||TPFN| F1 is the harmonic mean of the previous two quantities: 7 F1=2precisionrecallprecision+recall The set of seed words is extracted from the thematic lexica of LIWC in two ways: either at random or selected by experts. The random selection of seed words from the LIWC lists is based on the selection of a percentage between 10% and 90% of the words of each word list, as depicted in Fig. 2. We repeat the experiment 50 times for each percentage, every time selecting a new random subset of seed words. We then compute precision, recall and F1 averaging on the 50 repetitions. The expert-based approach to the choice of the seed words is based on the words selected by the authors of Vine et al., (2020) as the most representative words for the LIWC categories of negative emotion, positive emotion, anxiety/fear, anger, sadness and undifferentiated negative emotion.2Vine et al., (2020) call these word lists Emotional Vocabularies (EVs). Note that the EVs are freely available online, therefore we openly redistribute the expanded word lists obtained from the EVs in our work. The EVs were not created as a set of seed words from which to recover the LIWC word lists. However, we use them as they are a freely available selection of words from LIWC. The EVs are available only in English, therefore we expand them only with the English lexicon expansion methods. Note that the value of precision computed in the performance evaluation is a lower bound for the actual precision of the method: We only consider as successes the words that belong to the original LIWC word list. However, it can happen that the lexicon expansion method finds words which belong to the chosen topic but were not included in LIWC by the experts. Indeed, we do not consider the LIWC word lists to be exhaustive of the topic they deal with. As a consequence, in computing the precision, we consider as false positives some words which might actually be true cases. The estimate of the precision is thus a lower bound, since we cannot be completely certain that LIWC presents the most extensive word lists for each topic. Furthermore, we compare the expansion of the random selection of words from LIWC and the expansion of the EVs. This comparison has the aim of testing whether the effort of manually selecting the most representative words of one class might be an advantage to the expansion of the word list. In order to do so, we consider the expansion of a random selection of seed words of the same length of the EVs from the five emotional categories. We repeat the random selection 50 times and consider the mean performance. We compare the results in terms of precision, recall and F1 with the performance of the expansion of the EVs. Additionally, we analyze the interdependence of LEXpander with the other methods. In particular, we test whether the word lists created by the different methods capture different signals. In order to do so, we define a union and a intersection methods, which consist, respectively, of the union and intersection of the word lists resulting from the five expansion algorithms (LEXpander, WordNet, GloVe, FastText, Empath 2.0). We then analyze the performance of these methods when expanding the EVs in term of precision, recall and F1. Precision study As previously explained, the performance evaluation can only compute a lower bound for precision. To complement the analysis of lower bounds, we include an analysis of additional word annotations that do not appear in the LIWC words lists and can precisely assess the true value of precision. We call this test precision study. More in detail, we generated manual annotations of the word lists resulting from the expansion of the positive and negative EVs. Since the EVs are only available in English, this test can only be performed with English data. The first author and six other raters annotated the word lists. Five annotators are German native speakers, one speaks Italian and one Spanish as first language. They all have a near-native English proficiency. At least two annotators labeled each word in the expanded word lists and we select as relevant only the words which were accepted by both raters. In the case of FastText and Empath 2.0, the word lists resulting from the expansion procedure encompass more than 2000 words. In such cases, we annotate a random set of 300 positive and 300 negative words per method instead of the whole word list. In all other cases, all the words of the expanded word lists are annotated. In order to estimate the error of such statistic, we also compute the 95% confidence interval from the bootstrapping of the annotated word lists. The inter-rater agreement relative to the annotation of the positive words scores a Cohen's k of 0.59 (moderate agreement), while the task on the negative words achieves a Cohen's k of 0.65 (substantial agreement). Once the word lists have been annotated, we compute a more accurate estimate of the precision of each method. Convergent validity in text analysis We continue with a third task that compares the performance of the expanded lexica in an exercise of text analysis of English online communication and literary texts. In particular, we consider a simple text analysis method which consists in the computation of the frequency of words of the lexica expanded from the EVs and annotated which appear in the texts. We correlate the counts relative to each word list with the ones of the original lexica from LIWC on each single text snippet. We also compare the performance with the original EVs. We compute the correlation of the annotated word lists obtained expanding the positive and negative EVs with the counts of LIWC on the texts of each single dataset. Note that the EVs are in English, therefore the text analysis exercise can be performed only with English texts. Since we only annotated the full-length word lists for LEXpander, WordNet and GloVe we can report the results relative to these methods. However, it is important to remember that the cleaning of the word lists was not carried out with a particular type of text in mind. This strategy would be the most advisable, but in the case of this paper we did not want to bias the results, therefore we use the same annotated word list for the four different types of texts. For this analysis, we wanted to include texts of various lengths and from different sources in order to test whether the performances of the lexicon expansion methods depend on these features of the texts analyzed. In particular, we consider short texts of online communication from Reddit (in particular, all discussions, that is original post and answers, from the subreddits 'antiwork', 'TwoXChromosomes', 'family' and 'Home'), longer texts from the Brown corpus (Francis and Kucera, 1979), texts collected in the Corpus of Historical American English (COHA; Davies, 2012) and all the tweets, excluding answers, published in the UK during one single day in February 2021. The number of documents and their average length is reported in Table 1. Thus, in this task we analyze the lexicon expansion methods against short and long texts from social media (respectively, Twitter and Reddit) and texts written in American English across a representative selection of works published in 1961 (Brown Corpus) and from a curated historical dataset that balances the genre of the texts with respect to their year of publication (COHA). Table 1 Statistics of the datasets used for the text analysis exercise Dataset # Texts Mean length Brown corpus 502 2064 COHA 116,513 4852 Tweets 417,164 11 Reddit 54,499 1095 We report the number of texts in each dataset and their average length in number of words. Stop words are included in the counts Results We report the results of the study comparing LEXpander, a lexicon expansion algorithm built on colexification networks, with other lexicon expansion methods. LIWC 2015 in English In this section, we present the results of the evaluation tests relative to the 2015 version of LIWC in English. Performance evaluation In the first task, we use multiple lexicon expansion methods to retrieve the original LIWC word lists from a subset of their words. In Table 2 we report the results relative to a set of seed words chosen at random and amounting to 30% of the original LIWC word list. We also report the mean size of the expanded word lists and the results of the random baseline methods, averaged over 1000 repetitions. Additionally, the lengths of the expanded word lists for every experiment are featured in Tables 1, 2 and 3 of the Supplementary Materials. Table 2 Results of the expansion of the random choice of 30% words from the English LIWC Method Precision Recall F1 Mean size Mean bl Mean bl Mean bl LEXpander 0.16 0.01 0.14 0.02 0.13 0.01 614 WordNeta 0.10 0.00 0.07 0.00 0.07 0.00 525 Empath 2.0 b 0.08 0.01 0.22 0.03 0.10 0.01 1,293 FastText c 0.06 0.01 0.29 0.06 0.09 0.02 2,252 GloVed 0.07 0.01 0.13 0.03 0.08 0.02 773 Precision, recall and F1 of the expansions generated from random 30% seed words compared to the original lexica from the English 2015 version of LIWC. Values are means computed over 50 samples of the seed words across word lists. We also report the mean length of the expanded lexica. The results of a random baseline method (bl) averaged on 1000 repetitions of the same length are also indicated. The best performances are highlighted in boldface a Miller (1995) b Bojanowski et al., (2017), Fast et al., (2016a) c Bojanowski et al., (2017) d Pennington et al., (2014) Table 2 shows that the best precision and F1 scores are reached by LEXpander, while FastText yields to the highest recall when retrieving English word lists from a random selection of seed words. In this setting, LEXpander does not only achieve the best precision but also the best trade-off between precision and recall. Moreover, we observe that FastText and Empath 2.0 lead to the longest word lists, with a mean length of over 1,000 words. The average length of the word lists from LIWC is 417 words, therefore FastText delivers on average more than 5 times the number of words of the original lexica. In Table 5 of the Supplementary Materials we include the percentage of word lists for which it was possible to compute an expansion of the word list in at least one repetition of the 50 random drawing of seed words. All the methods manage to expand all of the 73 word lists from LIWC apart from WordNet, which expands only 66 thematic lexica. The results of Table 2 are relative to an initial set of seed words of 30% of the LIWC word lists. In the following, we analyze the dependence of the F1 value on the percentage of seed words chosen, as represented in Fig. 3. We also consider the values of the random baseline methods as a shaded area whose borders correspond to the minimum and maximum of the mean F1 scores relative to all the baseline methods. Fig. 3 Mean of the F1 scores of the expansion of seed words chosen at random from the English 2015 version of LIWC as a function of the percentage of seed words chosen. The mean is computed on the 73 different thematic categories. The grey area represents the baseline as the maximum and minimum mean F1 of the random baseline methods In Fig. 3, we see that LEXpander achieves the best F1 in the task with the English word lists when considering at least 20% random words as seed words. With 10% of seed words, Empath 2.0 and FastText have slightly better results than LEXpander and with 90% of seed words all the methods yield very similar performances. Therefore, LEXpander proves to be consistently the best method for the expansion of word lists for many size ranges. We also see that the fewer words are needed to recover the original LIWC word lists, i.e., the higher the percentage of the random selection is, the more the random baseline methods outperform the actual lexicon expansion models. Additionally, the mean F1 of LEXpander shows a steep increase between 10% and 20% of seed words. This is probably because of the higher precision of the method which counteracts the decrease of recall when increasing the number of seed words. However, the trends in precision and recall are not substantially different from the ones of the other methods, as reported in Fig. 1 of the Supplementary Materials. The previous results illustrate the performance of the lexicon expansion methods when dealing with a random subset of the word lists from the English LIWC. In order to analyze the dependence of the quality of the expanded word lists on the choice of the seed words, we perform the expansion of a manual selection of words from the five emotional categories of LIWC, called EVs (Vine et al., 2020). Similarly to the previous case, we find that LEXpander achieves the best precision and F1, while FastText the best recall. The full table of results for this case is reported in Table 2 of the Supplementary Materials, while a concise version constitutes the left side of Table 3. In contrast to the previous experiment, when expanding the EVs all methods achieve 100% coverage of the word lists, that is, it was always possible to compute an expansion of the EVs. Table 3 Dependence of the performance of the lexicon expansion algorithms on the mode of choice of the seed words: at random or chosen by experts (EVs) Method EVs as seed words Random seed words prec rec F1 prec rec F1 LEXpander 0.16 0.10 0.12 0.16 (0.02) 0.15 (0.01) 0.15 (0.01) WordNeta 0.11 0.06 0.08 0.12 (0.02) 0.08 (0.01) 0.09 (0.01) Empath 2.0b 0.07 0.29 0.11 0.07 (0.00) 0.34 (0.01) 0.12 (0.00) FastTextc 0.06 0.34 0.10 0.07 (0.00) 0.40 (0.01) 0.11 (0.01) GloVed 0.07 0.03 0.04 0.06 (0.01) 0.04 (0.01) 0.04 (0.01) Mean of precision, recall and F1 on the five emotional categories either choosing the seed words at random from the relative LIWC dictionaries or manually by experts (EVs). The standard deviation on 50 repetitions of the random choice of seed words is reported in between parentheses. We control for the length of the seed words. The best results are highlighted in boldface 1 Miller (1995) 2 Bojanowski et al., (2017), Fast et al., (2016a) 3 Bojanowski et al., (2017) 4 Pennington et al., (2014) In Table 3 we compare the performance of the methods when choosing the seed words at random from LIWC and when using a well-thought-out set of words to generate the final lexicon, the EVs. We consider as seed words exactly the same number of words for both cases, that is we control for the number of seed words. In Table 3, we see that precision, recall and F1 values are always higher or equal when taking a random sample of words from LIWC than when expanding a selection of words chosen by experts. This might be due to the fact that we repeat the random choice of seed words from LIWC 50 times, averaging the estimates for precision, recall and F1. Therefore, even if one random subset of seed words is not fully representative for the theme of the word list to reconstruct, it might be balanced by the other random choices. However, the standard deviation relative to the means of precision, recall and F1 on the 50 repetitions show that the variability in the results is minimal. One alternative explanation for the observation is that the EVs were not intended to be used to reconstruct the original LIWC. Rather, the aim of their creation was to quantify the vocabulary width of people with respect to emotions. Therefore, they might collect very frequent words, while the original LIWC word lists might have a better distribution with respect to word frequency. Note that, even when the seed words were chosen at random, they were anyways selected from a thematic set of words, that is words that convey a specific meaning. Thus, this comparison does not prove that the seed words do not have to be relevant to the desired topic, but that they do not necessarily have to be the most fitting and representative ones. We also consider the union and intersection of the expanded word lists in order to determine whether a combination of the lexica leads to better results. We find that, when expanding the EVs, the union model scores a precision value of 0.15 and a recall value of 0.04, thus leading to a F1 score of 0.06. The intersection yields to a very high precision (0.75), but the recall is 0, thus the F1 score relative to the method is 0. Therefore, the only case in which one of the combinations outperform the best scoring method consists in the precision results of the intersection model. However, this method cannot compete with the single ones with respect to recall and F1. Thus, we can conclude that the intersection and union of the word lists does not yield to better results. Precision study In Table 2 of the Supplementary Materials we compute the precision, recall and F1 score of the EVs over the original LIWC resource. Since the precision is lower than 1 (in particular, 0.86), we observe that the creators of the EVs included some words that do not appear in the original vocabulary. Thus, we can conclude that it is possible to add relevant words to LIWC, that is LIWC does not cover all the words relative to a topic. As a consequence, the precision we computed when comparing the expanded and original LIWC word lists is a lower bound for its real value. In the following precision study, we analyze this difference by collecting manual annotations of the word lists generated expanding the EVs. Since the EVs are in English, the expanded word lists can be only obtained in English. We report the lower bound for precision (indicated with *) and the estimate of its true value with respect to the annotations in Table 4. Table 4 Precision study of the lexicon expansion methods when using the EVs as seed words Method Precision* Precision Negative Positive Negative Positive LEXpander 0.21 0.20 0.64 [0.61,0.67] 0.43 [0.40,0.47] WordNeta 0.15 0.11 0.63 [0.60,0.67] 0.41 [0.40,0.47] Empath 2.0b 0.13 0.10 0.47 [0.41,0.52] 0.35 [0.30,0.40] FastTextc 0.10 0.09 0.41 [0.36,0.47] 0.28 [0.23,0.33] GloVed 0.11 0.10 0.25 [0.21,0.30] 0.18 [0.15,0.21] Comparison of the lower bound for precision (indicated with *) with the precision value adjusted according to the annotations of raters. We include 95% confidence intervals for the estimate for true precision. In bold, the best results for each computation are reported. 1 Miller (1995) 2 Bojanowski et al., (2017), Fast et al., (2016a) 3 Bojanowski et al., (2017) 4 Pennington et al., (2014) From Table 4, we see that LEXpander achieves the highest precision value for both positive and negative word lists, as also highlighted in previous results (see Table 2). However, the estimated real precision of LEXpander is not statistically different from the one of WordNet, and the two methods perform significantly better than the other models. Therefore, methods based on word networks outperform the ones constructed on word embeddings with regard to the precision of the expansion of lexica. However, the recall score of WordNet is markedly lower than the one of LEXpander, therefore we can assume that the latter continues to score the best F1 value. The adjusted precision reported in Table 4 is always at least 1.8 times higher than the lower bound for precision, thus corroborating the idea that the precision we could compute given the word lists from LIWC was only a lower bound. Moreover, the correlation between the lower bound and the adjusted precision values is 0.71 (p = 0.02). It is interesting to observe that a low value for precision does not always imply a low value in the adjusted precision: for example, in the case of the positive emotion category, methods with an estimated value for precision smaller than 0.12 yield to an estimated true value between 0.18 (GloVe) and 0.41 (WordNet). As a consequence of the new estimates for precision, we can conclude that also the values estimated for F1 in the previous tasks are lower bounds and close annotation tasks like this reveal that the true performance is higher. Convergent validity in text analysis As a last test, we perform a text analysis validation task on long and short English texts from online and offline communication. We compare the frequencies computed using the expanded word lists with the ones of the EVs and the original LIWC word lists on each dataset. We consider the annotated word lists from the precision study, which were expanded from the positive and negative EVs using LEXpander, GloVe and WordNet and report the correlations in Fig. 4. Fig. 4 Correlation of the frequency of words in the positive (top) and negative (bottom) expanded word lists from the EVs and the ones from LIWC in texts from different datasets. The performances of the EVs is considered as a baseline. The bars indicate the 95% confidence intervals. In some cases, error bars are narrower than point size In the text analysis exercise, we see that LEXpander always achieves best or tied with the best correlation on all the datasets. In particular, LEXpander, WordNet and GloVe yield statistically indistinguishable results from the ones of the EVs on the Brown corpus for the positive lexicon. With respect to negative sentiment, the three models are indistinguishable but significantly outperform the baseline given by EVs. On the other datasets, namely COHA, Reddit and the tweets published in one day, LEXpander achieves the best correlation with the positive and negative word lists from LIWC, outperforming also the EVs. LIWC 2007 in German In this section, we consider the performance evaluation of the lexicon expansion algorithms on the German version of LIWC from 2007. Performance evaluation We test the performance of LEXpander and the other lexicon expansion algorithms when dealing with seed words in German. Similarly to the case of the English word lists, we expand a random selection of seed words of the German version of LIWC from 2007. In Table 5 we report the results relative to a 30% random selection of words. Table 5 Results of the lexicon expansion task with a random selection of 30% words from the lexica of the German LIWC Method Precision Recall F1 Mean size Mean bl Mean bl Mean bl LEXpander 0.20 0.01 0.11 0.01 0.14 0.01 468 OdeNeta 0.03 0.00 0.00 0.00 0.00 0.00 170 Empath 2.0b 0.03 0.01 0.14 0.02 0.04 0.01 1,905 FastTextc 0.03 0.01 0.16 0.03 0.04 0.01 2,350 GloVed 0.05 0.01 0.13 0.02 0.05 0.01 722 Precision, recall and F1 of the word list retrieved with 30% of seed word chosen at random versus the original word lists from the German LIWC. We report the performance of the relative random baseline method (bl) and the mean size of the expanded word lists. In bold are highlighted the best performances a Siegel and Bond (2021) b Bojanowski et al., (2017), Fast et al., (2016a) c Bojanowski et al., (2017) d Pennington et al., (2014) In Table 5 we see that LEXpander yields to the best values for precision and F1 in German, while FastText achieves the best recall, thus confirming the trend already observed with English in Table 2: LEXpander features the best precision and the best trade-off between recall and precision overall. We observe that in general the mean size of the final word lists (see Table 4 of the Supplementary Materials) is larger than the one obtained in the English setting. This is probably a result of the fact that German has more word inflections than English. For example, while the word 'friend' in English can only be inflected with the plural 'friends', in German the base word 'Freund' can be inflected in several ways, as for example 'Freundin' (feminine singular), 'Freundinnen' and 'Freunde' (respectively feminine and masculine plural), 'Freunden' (masculine dative plural), 'Freunds' and 'Freundes' (masculine genitive singular) and so on. Also in this case, we find that FastText and Empath 2.0 deliver the largest word lists, while OdeNet is characterized by the shortest outcomes. Similarly to the experiment with English word lists, also in the German case we consider the value of F1 as a variable of the number of seed words, as represented in Fig. 5. Fig. 5 Mean of the F1 scores of the expansion of the German LIWC as a function of the percentage of words chosen at random from the original lexicon. The grey area represents the maximum and minimum of the random baseline methods Figure 5 shows that LEXpander reaches the best F1 for any size of seed words chosen. Moreover, the F1 results and the relative difference in performance of the methods increases the more seed words are considered until 40% of seed words, and then decreases, while the results of the random baseline methods increase steadily. We observed a similar pattern in the case of the English LIWC (see Fig. 3), with the increase stopping at around 20% of seed words. This happens because, the higher the percentage of seed words given as input, the fewer words have to be added to the expanded word list in order to recover the original one. We also observe that OdeNet delivers worse results than the random baseline method, i.e., a random model achieves better F1 than OdeNet. This is probably due to the limited size of the OdeNet network as hinted by the number of word lists the method manages to expand: 27 out of the 68 word lists in the German LIWC. All the other methods expand more than 60 word lists and LEXpander, Empath 2.0 and FastText achieve the highest number of expanded word lists: 64 out of 68. These results are reported in Table 5 of the Supplementary Materials. Discussion In this paper, we present a new lexicon expansion algorithm, LEXpander, and compare its performance in a benchmark including different automatic lexicon expansion algorithms. We show that LEXpander achieves the best precision and F1 in the lexicon expansion tasks in two linguistic settings. Moreover, it is best or tie with the best in an English text analysis exercise. LEXpander is an open-source method available as a web tool ). Moreover, the word lists expanded from the EVs are shared on the GitHub page ), as well as the code realized along with the present paper. LEXpander is a lexicon expansion algorithm based on a linguistic concept, colexification, and the present publication shows the usefulness of bridging linguistic theory and NLP applications. Incorporating linguistic theory can provide novel, interpretable models, which give insights into phenomena rather than fitting statistical features of texts with black box algorithms. Our work also shows that some linguistic ideas can solve the problem of under-performing methods for languages different from English. Indeed, when deploying concepts that are supra-lingual or independent from language, as colexification networks, to build linguistic methods, such methods can easily be applied to a plethora of languages. Indeed, in this paper we used the same architecture and the same underlying data structure (the colexification network) to solve the problem of lexicon expansion in two different languages achieving good performances in both linguistic settings. In our view, independence from language does not mean that the method yields to the same results in every language; rather that the same method can be used without adjustments to expand lexica in different languages. Moreover, the evidence that the quality of the results of LEXpander in the German setting is more pronounced than the one in English proves that the existing methods are lacking when applied to languages different from English. This is because all the other word list expansion methods considered here were developed and validated taking into account only English. By making use of the idea of colexification, which deals with supra-lingual concepts, we show the potential applications enabled by this property of the method. In addition to this, we find that lexicon expansion methods based on networks outperform the ones based on word embeddings in terms of precision and F1. We also prove that the union of the expanded word lists does not yield to better results. Indeed, the union of word lists contributes to raising the recall at the expense of precision, thus resulting in a low estimate for F1. However, the high recall can benefit applications to a different range of problems, as for example in the area of text mining. In particular, Bozarth and Budak (2022) highlight that when considering the amount of relevant tweets that keyword expansion algorithms can retrieve, the union of expanded lexica leads to better results than the ones achieved by the single word lists. While LEXpander and other lexicon expansion methods offer an easy way to improve word lists, we do not recommend using them without some degree of manual inspection and filtering. Such selection should be performed taking into account the application and the type of language of the texts considered. For example, in the text analysis exercise we showed that the positive and negative word lists obtained with LEXpander have the highest correlation with LIWC on all the dataset considered. However, the annotation of the expanded word lists had been executed without the aim of performing such an application. Therefore, we think that the performance of all the methods would have been better if the cleaning process would have been completed with a specific dataset in mind. Moreover, there are some cases where researchers might want to use other methods than LEXpander, especially when focusing on niche domains and contexts. In particular, LEXpander does not allow to explore novel ways of usage of language in a specific linguistic environment, as word embeddings do when trained on novel corpora. Therefore, when exploring the language used in a medium to find patterns never analyzed before, as in Balsamo et al., (2021), word embeddings seem to offer a better alternative. On the contrary, LEXpander is the method to use in the pre-processing of data, as for example when selecting text instances relative to a topic or when brainstorming for the creation of word lists related to general topics. Moreover, the supra-lingual feature of LEXpander makes it the preferable choice for these tasks when considering languages with lower resources compared to English. LEXpander is a resource that can be used both when brainstorming and compiling lexica and when doing text analysis after an adequate cleaning. Future work with LEXpander may include the analysis of psychological phenomena with the help of this resource. For example, the dictionary from the Moral Foundation Theory (Graham, Haidt, & Nosek, 2009; Graham et al.,, 2013) may be expanded for better capturing signals in texts. Another application may rely on the creation of novel word lists, as for example ones intended to test new concepts from psychology or sociology, as the ideas of loose and tight cultures in Jackson, Gelfand, De and Fox (2019). To summarize, we find that LEXpander combines a high coverage of the thematic categories and the best trade-off between precision and recall in the task of expanding a word list both in English and German. The absolute values of the performance might be deceivingly low: the best method, LEXpander, achieves a F1 score of 0.12 when expanding the EVs. However, this value represents only a lower bound for the actual F1 score, as proven by the precision study. Indeed, we prove that the precision value we compute is a lower bound and that, in the case of LEXpander, the real precision value is at least two times higher than its lower bound. Conclusions In this paper, we introduce a novel lexicon expansion algorithm, LEXpander. LEXpander implements a method based on a colexification network, that is a multilingual semantic network. We test the performance of LEXpander on various lexicon expansion tasks, comparing it to other widely used lexicon expansion algorithms, including methods based on the GloVe and FastText word embeddings, and algorithms deploying semantic networks, as WordNet and its German counterpart, OdeNet. We find that LEXpander is the best option when focusing on precision or F1 both in English and German. The German experiment shows the performance of the method in a non-English setting, but the tool can be applied to all the other languages featured in the colexification network, which amount to 19 languages belonging to four different families. Even if LIWC might seem the best method for some tasks, it is not open source, therefore an alternative method might be more widely used. A freely available tool is Empath (Fast et al., 2016a), often deployed in research thanks to its ease of use. However, Empath is now outdated and delivers very short expanded word lists. LEXpander is a free, open-source multilingual tool that can be found in a GitHub repository ) and can be used through an interactive page ). Moreover, we share the word lists obtained from the expansion of the EVs on GitHub ), which provide a resource comparable to the emotional LIWC word lists without using any LIWC dictionary data. These resources are freely available for download, with the aim of supporting future research on text analysis methods and their applications. Electronic supplementary material Below is the link to the electronic supplementary material. (PDF 267 KB) The research leading to these results received funding from the Vienna Science and Technology Fund (WWTF) [10.47379/VRG16005]. Funding Open access funding provided by Medical University of Vienna. The research leading to these results received funding from the from the Vienna Science and Technology Fund (WWTF) [10.47379/VRG16005]. Availability of data and materials The datasets created and/or analyzed are available in the GitHub repository, or on Zenodo, 10.5281/zenodo.7377095, with the exception of LIWC word lists, which can be purchased by any researcher from Code availability Codes for reproducing our results are available in the GitHub repository, on Zenodo 10.5281/zenodo.7377095. LEXpander is also available as an online tool for word lists expansion: Declarations Ethics approval Not applicable Consent to participate Not applicable Consent for publication Not applicable Competing interests The authors have no competing interests to declare that are relevant to the content of this article. 1 This can also happen in word embedding models, thus we report this for all methods in our benchmark. 2 We decided to exclude the undifferentiated negative emotion vocabulary of the EVs from this study because it does not match any of the original thematic word list of LIWC. 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PMC10000356 | BMC Pulm Med BMC Pulm Med BMC Pulmonary Medicine 1471-2466 BioMed Central London 36899328 2379 10.1186/s12890-023-02379-7 Research They do not have symptoms - why do they need to take medicines? Challenges in tuberculosis preventive treatment among children in Cambodia: a qualitative study An Yom [email protected] 123 Teo Alvin Kuo Jing 45 Huot Chan Yuda 6 Tieng Sivanna 6 Khun Kim Eam 36 Pheng Sok Heng 6 Leng Chhenglay 6 Deng Serongkea 7 Song Ngak 8 Nonaka Daisuke 2 Yi Siyan 34910 1 Sustaining Technical and Analytical Resources (STAR), the Public Health Institute (PHI), Phnom Penh, Cambodia 2 grid.267625.2 0000 0001 0685 5104 School of Health Sciences, Faculty of Medicine, University of the Ryukyus, Okinawa, Japan 3 grid.436334.5 School of Public Health, National Institute of Public Health, Phnom Penh, Cambodia 4 grid.4280.e 0000 0001 2180 6431 Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore 5 grid.1013.3 0000 0004 1936 834X Faculty of Medicine and Health, University of Sydney, Sydney, NSW Australia 6 National Center for Tuberculosis and Leprosy Control, Phnom Penh, Cambodia 7 World Health Organization, Phnom Penh, Cambodia 8 United States Agency for International Development, Phnom Penh, Cambodia 9 grid.513124.0 0000 0005 0265 4996 KHANA Center for Population Health Research, Phnom Penh, Cambodia 10 grid.265117.6 0000 0004 0623 6962 Center for Global Health Research, Touro University California, Vallejo, CA USA 10 3 2023 10 3 2023 2023 23 836 9 2022 3 3 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background Latent tuberculosis (TB) infection has been known as a seedbed for TB disease later in life. The interruption from latent TB infection to TB disease can be done through TB preventive treatment (TPT). In Cambodia, only 40.0% of children under five years old who were the household contacts to bacteriologically confirmed TB cases were initiated with TPT in 2021. Scientific studies of context-specific operational challenges in TPT provision and uptake among children are scarce, particularly in high TB-burden countries. This study identified challenges in TPT provision and uptake among children in Cambodia from the perspective of healthcare providers and caregivers. Methods Between October and December 2020, we conducted in-depth interviews with four operational district TB supervisors, four clinicians and four nurses in charge of TB in referral hospitals, four nurses in charge of TB in health centers, and 28 caregivers with children currently or previously on TB treatment or TPT, and those who refused TPT for their eligible children. Data were audio recorded along with field notetaking. After verbatim transcription, data analyses were performed using a thematic approach. Results The mean age of healthcare providers and caregivers were 40.19 years (SD 12.0) and 47.9 years (SD 14.6), respectively. Most healthcare providers (93.8%) were male, and 75.0% of caregivers were female. More than one-fourth of caregivers were grandparents, and 25.0% had no formal education. Identified key barriers to TPT implementation among children included TPT side effects, poor adherence to TPT, poor understanding of TPT among caregivers, TPT risk perception among caregivers, TPT's child-unfriendly formula, TPT supply-chain issues, caregivers' concern about the effectiveness of TPT, being non-parental caregivers, and poor community engagement. Conclusion Findings from this study suggest that the national TB program should provide more TPT training to healthcare providers and strengthen supply chain mechanisms to ensure adequate TPT drug supplies. Improving community awareness of TPT among caregivers should also be intensified. These context-specific interventions will play a crucial role in expanding the TPT program to interrupt the development from latent TB infection to active and ultimately lead to ending TB in the country. Supplementary Information The online version contains supplementary material available at 10.1186/s12890-023-02379-7. Keywords Preventive treatment Childhood tuberculosis Healthcare providers Caregivers Cambodia issue-copyright-statement(c) The Author(s) 2023 pmcBackground The World Health Organization (WHO) estimates that about 25% of the population globally is infected with tuberculosis (TB) or has latent TB infection, of whom 5-10% will develop active TB during their life course . Children and adolescents are high-risk groups for developing active TB . TB preventive treatment (TPT) can decrease the risk of TB disease in children by 59% and is one of the WHO's strategies to end TB . Between the 2018 and 2020, 8.7 million people of all ages initiated TPT globally, equalling only 29% of the five-year target (2018-2022) of 30 million set at the United Nations General Assembly High-Level Meeting on TB in 2018 . Children under five years old are among the populations most at risk for progressing from TB infection to TB disease , and TPT initiation among them is far behind the target. Only 1.2 million (29%) of the four million under-five children who were household contacts of bacteriologically-confirmed TB cases initiated with TPT between 2018 and 2020 . This low achievement indicates substantial efforts needed to meet the TPT targets in young children. Several barriers may influence TPT initiation in children. TPT risk perception, lack of information, limited access to TPT, and perceived poor service quality at TPT facilities have been identified as the key barriers to childhood TPT initiation among parents and caregivers [7-10]. Furthermore, caregivers' personal experience in TPT such as poor adherence and acceptability also affected TPT initiation among children under their care in many countries . From the healthcare provider side, limited knowledge of TPT was a challenge in TPT implementation in Peru , India , and Kenya . Providers' perception of TPT's efficacy and long duration, and lack of standard guidelines and support from the program management level were identified as barriers to TPT initiation in children in Kenya . Healthcare providers reported a lack of screening equipment and expertise to interpret diagnostic results, the high workload for healthcare workers, poor TPT monitoring, and fear of increasing Isoniazid resistance as barriers to child TPT implementation in several settings . In Malawi, transportation costs for chest X-ray screening were the primary reason for low TPT among children younger than six years old . Cambodia is a high TB burden country with an estimated incidence rate of 288 per 100,000 population in 2021 and has been listed as one of three countries on WHO's global TB watchlist . The country has made enormous efforts through different approaches to reduce this high burden and reach the targets to end TB by 2030 . Providing TPT is among the core interventions . The national TB program has initiated TPT using a nine-month regimen of Isoniazid for children under five years since 2008 . In 2018, the WHO updated and consolidated guidelines for latent TB infection with different choices of TPT regiments . In 2020, Cambodia's national TB program developed a standard operating procedure (SOP) for latent TB infections and TPT with the national efforts to scale up the TPT implementation. With this SOP, the national program has adopted three regiments, including six months of daily Isoniazid (6H), three months of weekly Isoniazid and Rifapentine (3HP), and three months of daily Isoniazid and Rifampicin (3RH). TPT is prescribed and monitored by healthcare providers at referral hospitals and at health centers. TPT initiation among under-five children has fluctuated in the past five years and dropped significantly in 2021, mainly due to the impact of COVID-19. Based on data from the WHO, the proportion of under-five children eligible for TPT initiated with it was 47% in 2017, 48% in 2019, 89% in 2020, and only 40% in 2021 . While suboptimal TPT implementation was reported, more is needed to understand contextual challenges influencing the implementation. Therefore, it is essential to understand the barriers to providing and receiving TPT for eligible children in the country. This study explored the challenges in TPT provision and uptake among children in Cambodia from the perspective of healthcare providers and caregivers. Findings from this study will provide insights into the challenges of TPT implementation from different angles, which will be beneficial for shaping program implementation and policy development. Methods Study design, sites, and participants We conducted this qualitative study between November and December 2020. In-depth interviews (IDIs) were performed with 16 healthcare providers, including four TB supervisors at operational districts (ODs), four clinicians in charge of TB at referral hospitals, four nurses in charge of TB at referral hospitals, and four nurses in charge of TB at health centers under the coverage of the selected ODs. ODs are a functional unit within Cambodia's health system under the provincial health departments. We also conducted IDIs with 28 caregivers aged >= 18 years who had children younger than 15 years old currently or previously with TB (n=9), accepted TPT for their eligible children (n=11), or rejected TPT for their eligible children (n=8). Sampling and recruitment The research team purposively recruited healthcare providers with experience and good knowledge of childhood TB and TPT. The knowledge was measured using a questionnaire on TB causes, transmission routes, signs, and symptoms; characteristics of lymph nodes that implied TB; diagnostic criteria for childhood TB; and TPT use, target groups, drugs, contraindication, and side effects. We have reported the detailed knowledge measures elsewhere . Caregivers were recruited using a convenient sampling method with support from local healthcare providers, community-based non-governmental organizations, and village health support groups. They pre-identified caregivers residing in the coverage area of the selected health facilities with the research team's guidance. Data collection We collected respondents' sociodemographic characteristics and perceptions of challenges in TPT provision and uptake among children through face-to-face IDIs. Trained and experienced interviewers conducted the IDIs using pre-tested semi-structured interview guides in Khmer with audio recordings and field notes. Key questions for healthcare providers included challenges in providing TPT, such as TPT guideline availability, providers' TPT knowledge, TPT drug availability, and TPT risk perceptions. For caregivers, the question guide focused on whether they had heard about TPT, thought TPT is safe and effective in TB prevention, and would allow their eligible children to take TPT. We interviewed healthcare providers at TB clinics and caregivers at their houses in private places. Each participant received a compensation gift valued at about one US dollar after the interview which took 30-40 min. Data management and analyses Audio records were transcribed into Khmer and then translated into English. Two researchers (YA and KEK) manually coded the transcription based on the question guides. Emerged themes and sub-themes on TPT provision and uptake challenges were also coded accordingly. If necessary, identified key themes were verified against Khmer transcription and with the audio records. We analyzed the data using thematic analyses, and pre-identified main themes in the question guides were saturated. Results Table 1 shows the demographic characteristics of the participants. The mean age of healthcare providers was 40.2 (SD 12.0) years, and 93.8% were male. Among the caregiver participants, the mean age was 47.9 (SD 14.6) years, and 75.0% were female. One-fourth of the caregiver participants had no formal education, and 60.7% were farmers.Table 1 Demographic characteristics of in-depth interview participants Frequency % Healthcare providers (n = 16) Age in years, mean (SD) 40.2 (12.0) Sex, male 15 93.8 Working place Operational district 4 25.0 Referral hospital 8 50.0 Health center 4 25.0 Role TB supervisor 4 25.0 Clinician at TB service at a referral hospital 4 25.0 Nurse at TB service at a referral hospital 4 25.0 Nurse in charge of TB at a health center 4 25.0 Caregivers (n = 28) Age in years, mean (SD) 47.9 (14.6) Sex, female 21 75.0 Relationship of caregivers with children Parent 20 71.4 Grandparent 8 28.6 Education No formal education 7 25.0 Primary school 8 28.6 Secondary school 10 35.7 High school or higher 3 10.7 Main occupation Farmer 17 60.7 Seller 5 17.9 Government or private sector staff 2 7.1 Other 4 14.3 Abbreviations: SD standard deviation, TB tuberculosis Barriers to TPT implementation Healthcare providers and caregivers perceived and experienced several challenges in TPT implementation and uptake among eligible children. The following main themes emerged as barriers. TPT side effects TPT side effects, such as dizziness, vomiting, blurred vision, and tiredness, were reported by many healthcare providers. "They (children) were fine before taking the medicines. But when they took them, it was like killing them... Some children felt normal when they took the medicines. But after one week, they said they weren't well with dizziness, vomiting, etc." (A nurse at a health center, IDI-8, male, 26 years). "Most patients complained that they felt unwell after taking TPT medicines, having nausea, dizziness, blurred vision, or tiredness." (A doctor at a referral hospital, IDI-11, male, 48 years). Caregivers also reported that TPT side effects were the reason for them not accepting TPT for their eligible children. "Because it had side effects. I was afraid my kid would suffer from the side effects." (A caregiver who refused TPT for their child, IDI-6, female, 30 years). ".... It was hard to make children take it, and I was worried they were too young to overcome the side effects of the medicines....." (A caregiver who refused TPT for their child, IDI-1, female, 67 years). Some healthcare providers believed that TPT's side effects, such as vomiting, dizziness, and fatigue, were the primary causes of poor adherence among children. To overcome these side effects, healthcare providers supported caregivers and children by providing medical and psychological support to improve TPT adherence. "Yes, when they (children) took the medicines, they had problems with side effects, and they complained and refused to continue taking them." (A nurse at referral hospital, IDI-14, male, 50 years). "Some children received the TPT, dropped out later, and, in many cases, stopped taking the medicines. At first, we explained to them, and they understood and took the medicines. They continued taking the medicines for about one month, then side effects happened, and they stopped taking them." (An OD TB supervisor, IDI-1, female, 35 years). Poor understanding of TPT among caregivers Caregivers raised several reasons for the acceptance or refusal of TPT for their eligible children, including that children were not sick, caregivers' busyness, or no clear explanation from healthcare providers. "We had provided TPT to children or TB close contacts for about a year, but it was still difficult to educate people to bring children in the family who were TB close contacts to receive TPT. Some caregivers said their kids were healthy, so why did they have to receive the treatment? It took quite a long time to make them understood." (An OD TB supervisor, IDI-13, male, 48 years). "Sometimes, they (caregivers) didn't accept TPT because they didn't know (about TPT). Some people were hard to explain; they refused (TPT for their kids) even their family and relatives persuaded them to take the medicines for prevention." (A nurse at referral hospital, IDI-3, female, 31 years). A caregiver also raised a concern that TPT cannot prevent TB disease. Their kids may again get TB if they are in close contact with people with TB."It's also difficult...suppose we give him TPT up to six months... and then children in the village are infected with TB, and he plays with those children, so he will get the infection again." (A caregiver who refused TPT for her child, IDI-8, female, 27 years). Almost all caregivers who received or refused TPT for their children had heard about TPT and acknowledged its importance and effectiveness. However, several caregivers with children previously or currently on TB treatment admitted that they had never heard about TPT. "I had never heard about the medicines for preventing TB" (A caregiver of a child receiving TB treatment, IDI-3, female, 65 years). "Never, never had heard about it (TPT)" (A caregiver of a child receiving TB treatment, IDI-1, female, 25 years). Some healthcare providers believed some caregivers did not accept TPT for their eligible children because of misconceptions. They were worried about TPT side effects as they thought their children were not sick and too young and likely to be harmed by the medicines. These misconceptions might be due to unclear explanations from healthcare providers. "I used to request parents to bring their children living with adults who had bacteriologically confirmed TB to health facilities for TPT, but the parents were reluctant, maybe because I didn't explain them well. I didn't know the specific reason behind that, but they refused it, not willing to take the treatment (A nurse at a health center, IDI-12, male, 28 years). "Like I said before, (challenges in providing TPT) include: first, they (children) were not sick, and we gave them medicines but didn't explain them clearly. Second, they didn't want to take the medicines because they were afraid of them, or they didn't want to take them because the kids were young." (A doctor at a referral hospital, IDI-16, male, 35 years). Some caregivers did not accept TPT because of their perception of TPT's adverse effects, as their kids were not sick or the medicines could be harmful for the children as they were too young, and there was no clear explanation from healthcare providers. "..... but the kid was too young to take the medicines, so I could not make him/her take it. .......If the doctors said it was okay for babies to take the medicines, I would let them take it despite their young age." (A caregiver who refused TPT for their grandchildren, IDI-1, female, 67 years). "I think that if they have TB, taking medicines is correct. But if they don't have symptoms, and they must take medicines too, it's dangerous." (A caregiver who refused TPT for their children, IDI-4, male, 52 years). "I didn't want him to take medicines at that time because he is young" (A caregiver who refused TPT for her child, IDI-8, female, 27 years) Child-unfriendly formula Caregivers reported that children did not like TPT's taste, which hindered TPT acceptance among children."My kid couldn't tolerate its bitterness. Because it was bitter ...... if it was a little bit sweet, he might be able to take it." (A caregiver who refused TPT for her child, IDI-6, female, 30 years). TPT supply issues Healthcare providers reported inadequate drug supplies interrupted TPT provision."Before, there were insufficient drugs, ..... but now no, ..... the challenges before included insufficient drugs (for TPT)." (An OD TB supervisor, IDI-2, male, 39 years). Being non-parental caregivers Caregivers who were grandparents reported that the sole reason for not accepting TPT was because the children's parents were living away from them. It was hard for grandparent caregivers to look after the children when they got sick."Their parents lived somewhere else... It's hard for me as their caregiver... I looked after all their three children. I didn't have time to get the medicines for all of them." (A caregiver who refused to receive TPT for her children, IDI-2, female, 62 years). Improving TPT implementation When asked how to improve TPT acceptance, most healthcare providers suggested increasing health education on TPT in the community, improving healthcare providers' capacity to provide TPT, increasing the screening of children for TPT eligibility, and ensuring adequate drug supplies. "I think the national (TB) program should help spread the information about TPT to make people understand ..." (An OD TB supervisor, IDI-7, male, 31 years). ".....first, we have to educate people with TB who have kids and advise them to bring their kids to get TPT after confirming that they do not have TB but are at high risk of having TB. We advise the parents to bring their kids to receive TPT. That is the first strategy. And second, we must advise them (caregivers) to follow the healthcare providers' advice in getting and taking the medicines regularly and try not to miss them to prevent TB transmission." (A doctor at a referral hospital, IDI-9, male, 36 years). "We need to increase our capacity to better understand TPT. We need to know more deeply about it." (An OD TB supervisor, IDI-1, female, 35 years). Discussion This study assessed the challenges in child TPT provision and uptake from the perspective of healthcare providers and caregivers. Perceived TPT side effects were commonly reported as barriers to TPT. These findings were similar to other studies. A study in Lesotho indicated that the fear of TPT's side effects was the main reason for poor TPT adherence . TPT side effects were also reported as a concern among caregivers and providers in India and Indonesia . To tackle these challenges, it is essential to explain to caregivers the importance of TPT in preventing the progression from TB infection to active TB, as TPT effectively reduces TB incidence by 60% to 90% . Furthermore, healthcare providers' clear explanation of TPT's side effects and the availability of TPT with fewer side effects is critical. Cruz and Starke found that 3HP or daily rifampin for four months (4R) had minimal side effects and was well tolerated by children . The TPT knowledge gap among caregivers was also a challenge for TPT provision. This could lead to a high proportion of TPT unacceptance for eligible children. In Southeast Asia, the TPT knowledge gap among service recipients was a reason for the slow TPT scale-up [23, 26-28]. In Australia, 31% of caregivers in the study did not believe in the importance of TB chemoprophylaxis . This misconception might be due to the lack of TPT information in the community or unclear explanations of the TPT effectiveness from healthcare providers. The poor caregivers' knowledge of TPT was identified as a barrier to TPT initiation in India , Ethiopia , Rwanda , and South Africa . This limited knowledge could also lead to low community participation in screening children for latent TB infection and low TPT provision . In our context, TPT was not prioritized by some caregivers due to their poor understanding of the importance of TPT in preventing active TB in children. Therefore, increasing community awareness of TPT benefits should be prioritized to maximize the uptake. Unclear explanations about TPT from healthcare providers could raise a concern about the TPT's effectiveness in preventing TB disease among caregivers and may lead to low TPT acceptance for their children. Limited TPT knowledge among healthcare providers is a factor hindering TPT initiation in many settings, such as South Africa , Dominican Republic , and Kenya . These findings suggest that more comprehensive TPT training for healthcare providers in charge of TB along with TPT community awareness campaigns are essential to tackle this barrier. Unclear explanations from healthcare providers on the importance of TPT may contribute to this concern which constituted a reason for TPT refusal among caregivers. This finding is similar to a study in India, where children being too young and free of TB symptoms were the reasons for TPT unacceptance, as caregivers had an insufficient understanding of the TPT . Similar findings have also been reported in Indonesia , Dominican Republic , and Southern Ethiopia . Simple and informative messages on TPT's risks and benefits should be widely communicated through leaflets and community education sessions. The information should include the high risk of developing severe forms of TB disease (e.g., TB meningitis), especially among younger children, if they do not receive TPT. Inadequate and irregular drug supplies were another challenge for TPT implementation, similar to studies in India . In Southeast Asia, inadequate TPT supplies were a reason for slow TPT scaling-up, which must be urgently addressed . To ensure stable drug supplies, a close and systematic TPT monitoring system from national to sub-national levels should be in place. At the central level, representatives from the central drug store of the Ministry of Health should regularly join quarterly or annual meetings with the national TB program to share experiences and address challenges related to TPT drug supplies. In addition, the national TB program should ensure regular supervision and work closely with relevant partners to ensure adequate drug TPT supplies, monitoring, and distribution . At the sub-national level, OD and provincial TB supervisors should discuss jointly addressing challenges. This study identified poor collaboration from caregivers as a barrier to childhood TPT implementation. The absence of parents from home was a challenge since caregivers who were grandparents or relatives could not decide to accept TPT for the children. Interventions should be contextualized to the specific reasons and local settings, such as targeted health education among non-parent caregivers on TPT in the community to improve TPT uptake and adherence. The collaboration between caregivers and healthcare providers is key to TPT implementation success. In Nigeria, caregivers lacked collaboration to regularly provide TPT to their children because TPT was less prioritized than other tasks . Therefore, improving engagements between caregivers and the community is a crucial strategy to accelerate TPT implementation and sustainably as they are a key player to enable changes in behavior, environments, and practices within their communities . In Cambodia, TPT is provided to eligible people of all age groups. Challenges to TPT implementation identified in this study may be similar in children and adults. In a survey of TB staff in 35 countries, participants reported a lack of funding to buy TPT drugs, TPT stock-out or TPT supply chain issues, perceived TPT's adverse effects, and a lack of dedicated staff for the TPT implementation . A situational analysis of TPT program management by the WHO revealed several constraints on TPT implementation in Southeast Asia. The unavailability of TPT drugs, mainly Rifapentine, inadequate TPT healthcare provider training, and inadequate TPT demand from the community were among the challenges in TPT implementation . These challenges could help inform interventions and policies to build a strong TPT program for all age groups in Cambodia. Limitations of the study This study has several limitations. First, self-reported measures may lead to social desirability bias. However, this bias could have been minimized as data collection was conducted by trained and experienced data collectors with health backgrounds. Second, the findings may be unique to the Cambodian setting since identified barriers from this study were contextually and culturally specific. Third, three-fourths of the caregiver participants in this study were women who may experience different challenges in caring for their children from men. Barriers to TPT provision faced by men caregivers may be under-reported. Forth, most healthcare providers participating in this study were male; therefore, barriers to TPT implementation identified in this study may not sufficiently reflect the perspectives of female providers. Fifth, this study included only healthcare providers with high knowledge of childhood TB and TPT, who may face different challenges from providers with less experience and knowledge. Finally, the convenience sampling method used to recruit caregivers may lead to selection bias since it was done by local healthcare providers, which may lead to bias in the results. However, all caregiver participants were well explained the research objectives and the importance of the research findings in improving TPT implementation in the country. Conclusion Critical barriers to childhood TPT implementation in Cambodia included perceived TPT's adverse effects, knowledge gaps among caregivers and healthcare providers, child-unfriendly TPT formula, inadequate and irregular TPT drug supplies, misconception about TPT's effectiveness among caregivers, absence of parents from home, and poor community engagement in TPT implementation. The national TB program should invest in building healthcare providers' TPT implementation capacity. Awareness-raising campaigns are critical in improving TPT knowledge and acceptance in the community. Since TPT implementation in Cambodia has recently expanded to all age groups , improving TPT implementation in children may also improve the national TPT program and lead to achieving the targets set at the United Nation's high-level meetings in 2018 . Supplementary Information Additional file 1. Interview guide for In-Depth Interview (IDI). Acknowledgements We thank the Cambodia Committee for TB Research members, the United States Agency for International Development (USAID), and World Health Organization Cambodia for their technical input. We also thank data collection teams, provincial health departments, operational districts, referral hospitals, health centers, and study participants for contributing to the study. Authors' contributions Conception and design of the study: YA, AKJT, SVT, KEK, SHP, SD, NS, and SY. Data acquisition: YA, KEK, CL, and CYH. Data analyses and interpretation: YA and KEK. Drafting and revision of the manuscript: YA, AKJT and SY. All authors reviewed and approved the final manuscript. Funding The United States Agency for International Development (USAID) funded this study through the World Health Organization Cambodia. Availability of data and materials Data and materials are available upon request from Dr. Yom An (Email: [email protected]). Declarations Ethics approval and consent to participate This study was approved by the National Ethics Committee for Health Research (NECHR) (ref. 234/NECHR) in Cambodia and the Ethics Review Committee of the World Health Organization Western Pacific Regional Office (ID: 2020.8.CAM.3.STB). All methods were carried out in accordance with the Declaration of Helsinki, and informed consent was obtained from all participants. 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PMC10000357 | BMC Infect Dis BMC Infect Dis BMC Infectious Diseases 1471-2334 BioMed Central London 36899326 8103 10.1186/s12879-023-08103-4 Research Article Reactogenicity within the first week after Sinopharm, Sputnik V, AZD1222, and COVIran Barekat vaccines: findings from the Iranian active vaccine surveillance system Enayatrad Mostafa [email protected] 1 Mahdavi Sepideh 2 Aliyari Roqayeh 2 Sahab-Negah Sajad 3 Nili Sairan 4 Fereidouni Mohammad 5 Mangolian Shahrbabaki Parvin 6 Ansari-Moghaddam Alireza 7 Heidarzadeh Abtin 8 Shahraki-Sanavi Fariba 9 Fateh Mansooreh 10 Khajeha Hamidreza 11 Emamian Zahra 12 Behmanesh Elahe 12 Sheibani Hossein 13 Abbaszadeh Maryam 13 Jafari Reza 14 Valikhani Maryam 13 Binesh Ehsan 13 Vahedi Hamid 13 Chaman Reza 2 Sharifi Hamid 15 Emamian Mohammad Hassan [email protected] 11 1 grid.444858.1 0000 0004 0384 8816 Clinical Research Development Unit, Bahar Hospital, Shahroud University of Medical Science, Shahroud, Iran 2 grid.444858.1 0000 0004 0384 8816 Department of Epidemiology, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran 3 grid.411583.a 0000 0001 2198 6209 Neuroscience Research Center, Mashhad University of Medical Sciences, Mashhad, Iran 4 grid.484406.a 0000 0004 0417 6812 Department of Public Health, Faculty of Health, Kurdistan University of Medical Sciences, Sanandaj, Iran 5 grid.411701.2 0000 0004 0417 4622 Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran 6 grid.412105.3 0000 0001 2092 9755 Department of Critical Care, Razi Faculty of Nursing and Midwifery, Nursing Research Center, Kerman University of Medical Sciences, Kerman, Iran 7 grid.488433.0 0000 0004 0612 8339 Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran 8 grid.411874.f 0000 0004 0571 1549 School of Medicine, Guilan University of Medical Sciences, Rasht, Iran 9 grid.488433.0 0000 0004 0612 8339 Infectious Diseases and Tropical Medicine Research Center, Zahedan University of Medical Sciences, Zahedan, Iran 10 grid.444858.1 0000 0004 0384 8816 Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran 11 grid.444858.1 0000 0004 0384 8816 Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran 12 grid.444858.1 0000 0004 0384 8816 Health Technology Incubator Center, Shahroud University of Medical Sciences, Shahroud, Iran 13 grid.444858.1 0000 0004 0384 8816 Clinical Research Development Unit, Imam Hossein Hospital, Shahroud University of Medical Science, Shahroud, Iran 14 grid.444858.1 0000 0004 0384 8816 School of Allied Medical Sciences, Shahroud University of Medical Sciences, Shahroud, Iran 15 grid.412105.3 0000 0001 2092 9755 HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran 10 3 2023 10 3 2023 2023 23 15025 8 2022 19 2 2023 (c) The Author(s) 2023 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background This study aimed to evaluate the reactogenicity effects of COVID-19 vaccines, used in Iran. Methods At least 1000 people were followed up with phone calls or self-report in a mobile application within 7 days after vaccination. Local and systemic reactogenicities were reported overall and by subgroups. Results The presence of one or more local and systemic adverse effects after the first dose of vaccines was 58.9% [(95% Confidence Intervals): 57.5-60.3)] and 60.5% (59.1-61.9), respectively. These rates were reduced to 53.8% (51.2-55.0) and 50.8% (48.8-52.7) for the second dose. The most common local adverse effect reported for all vaccines was pain in the injection site. During the first week after the first dose of vaccines, the frequency of the pain for Sinopharm, AZD1222, Sputnik V, and Barekat was 35.5%, 86.0%, 77.6%, and 30.9%, respectively. The same rates after the second dose were 27.3%, 66.5%, 63.9%, and 49.0%. The most common systemic adverse effect was fatigue. In the first dose, it was 30.3% for Sinopharm, 67.4% for AZD1222, 47.6% for Sputnik V, and 17.1% for Barekat. These rates were reduced to 24.6%, 37.1%, 36.5%, and 19.5%, in the second dose of vaccines. AZD1222 had the highest local and systemic adverse effects rates. The odds ratio of local adverse effects of the AZD1222 vaccine compared to the Sinopharm vaccine were 8.73 (95% CI 6.93-10.99) in the first dose and 4.14 (95% CI 3.32-5.17) in the second dose. Barekat and Sinopharm had the lowest frequency of local and systemic adverse effects. Compared to Sinopharm, systemic adverse effects were lower after the first dose of Barekat (OR = 0.56; 95% CI 0.46-0.67). Reactogenicity events were higher in women and younger people. Prior COVID-19 infection increased the odds of adverse effects only after the first dose of vaccines. Conclusions Pain and fatigue were the most common reactogenicities of COVID-19 vaccination. Reactogenicities were less common after the second dose of the vaccines. The adverse effects of AZD1222 were greater than those of other vaccines. Keywords Vaccine reactogenicity Sinopharm Sputnik V AZD1222 COVIran Barekat Shahroud University of Medical Sciences 99135 Emamian Mohammad Hassan Vice-chancellery for research and technology at Iranian Ministry of Health and Medical Education2302 Emamian Mohammad Hassan World Health Organization 2021/1169483-0 2022/1217943-1 Emamian Mohammad Hassan issue-copyright-statement(c) The Author(s) 2023 pmcBackground The COVID-19 pandemic has caused significant mortality and morbidity worldwide, and until now, vaccination has been the most effective and promising strategy to control the spread of this disease . More than 250 vaccine production projects for COVID-19 have been launched worldwide since 2020 . According to a recent World Health Organization (WHO) report, 176 vaccines are in clinical, and 199 vaccines are in the preclinical development phases. However, at least 27 vaccines have been clinically used or approved against SARS-CoV-2 and as of 12 January 2022, nine vaccines have been authorized for emergency use by WHO . The most common adverse effects of the vaccines include pain, swelling, redness at the injection site and fever, chills, headache, myalgia, fatigue, nausea, and joint pain as systemic adverse effects . These reactogenicity events usually last 12 h to less than 7 days; in rare cases, they continue up to a month after vaccination . The local and systemic adverse effects are common but usually mild and self-limiting. Most of these reactions should resolve within a few days . However, they may be dangerous and cause fear in some cases. Besides, concerns about the adverse effects of COVID-19 vaccines may influence people's decision to accept or reject the vaccine . COVID-19 vaccination was performed based on age groups from older to younger and prioritized high-risk groups. Many countries have commenced their vaccination program, prioritizing those most at risk due to the limited number of available vaccines . In Iran, COVID-19 vaccination was started for high-risk groups, with Sinopharm, Sputnik V, AZD1222, and COVIran Barekat vaccines in high-risk groups and rolled out to other population groups. It is essential to determine the adverse effects of new COVID-19 vaccines. The WHO has developed guidelines for safety signal detection after vaccination and recommended it in a different setting. This study was performed based on this protocol and aimed to investigate the local and systemic adverse effects in an Iranian group of vaccinated individuals. Methods Study design and participant This prospective observational study evaluated the reactogenicity adverse effects of COVID-19 vaccines, including Sinopharm (inactivated vaccine), Sputnik V (a human adenovirus vector-based vaccine), AZD1222 (a chimpanzee adenovirus vector-based vaccine), and COVIran Barekat (Inactivated vaccine), based on WHO protocol . This study was performed in seven cities in Iran (Shahroud, Rasht, Zahedan, Sanandaj, Birjand, Kerman, and Mashhad) and its protocol has been published previously . The study population included all eligible individuals who received one of the different types of COVID-19 vaccine according to the Iranian guidelines for COVID-19 vaccination. Signing the written informed consent by people vaccinated with the first dose of COVID-19 vaccines at one of the vaccination centers participating in the study was considered as inclusion criteria. Exclusion criteria were included: individuals who were already vaccinated with any COVID-19 vaccines before study enrolment, and unable to comply with study procedures. Participants had the right to withdraw from the study for any reason at any time. The necessary information, including contact information, demographic characteristics, and history of underlying diseases (diabetes, hypertension, immunodeficiency, cancer, chronic heart disease, and respiratory, renal, hepatic, neurological, and psychiatric diseases) were collected during enrolment. Also, all the details of the injected vaccine, including the vaccine brand, vaccination date, and the vaccine's batch number, were recorded in the designed registration system. Weight and height were also self-reported, and obesity was defined as a Body Mass Index (BMI) equal to or more than 30 kg/m2. Data collection This study used telephone calls and electronic methods (mobile application and web pages) to collect data for at least 1000 participants of each vaccine. The local and systemic reactions after vaccination were recorded on days 1 to 7 after each dose of the vaccine. A reminder SMS was sent if the participants did not report the adverse effect data to the application by 16:00. If the data were not entered after the SMS, the trained experts actively followed and recorded the occurrence of adverse effects using telephone calls. For participants who were reluctant to use the web application, all data were collected by daily phone calls. Participants could also enter free textual reports about their post-vaccination experience and adverse events. In order to minimize loss to follow-up rate, the participants were contacted by phone up to twice a day. If they could not be reached, their next kin was followed up, and finally, if none of these worked, the call of that day was recorded as missed. A participant was considered lost to follow up after two unsuccessful attempts to contact them by phone, followed by one unsuccessful attempt to contact their next of kin. Outcomes The main objective of this study was to estimate the reactogenicity within 7 days after each COVID-19 vaccine dose, and the primary outcome was the proportion of individuals who reported local or systemic adverse effects within 7 days of the first and second vaccine doses. The local and systemic reactogenicities included pain at the injection site, redness, swelling, induration, warmness, itching, fever, nausea, malaise, chills, headache, joint pain, myalgia, and fatigue. The severity of reactogenicities was also assessed for every reaction by asking about the extent to which adverse effects interfere with the participant's daily activities. Statistical analysis The proportion of systemic and local adverse effects within 7 days of vaccination was calculated and reported with 95% confidence intervals. Observed-to-expected analyses were performed for systemic reactogenicities using the collected data for the 3 days before vaccination. The duration (in days) was calculated for each type of event and their mean and standard deviation were reported. Separate logistic regression models were conducted for each vaccine dose to calculate and compare the odds ratio (OR) of local and systemic adverse effects while adjusting for age, sex, BMI, comorbidities and prior COVID-19 disease. The significance level was considered <= 0.05. Results Out of 4639 people who received the first dose of vaccines from April 7, 2021, to January 11, 2022, 2908 (62.7%) received the second dose. The participants completed follow up in 7 days after vaccination with each dose of vaccines. The mean age of those who received the first dose was 46.7 (Standard Deviation [SD]: 18.5) years. The age and sex distribution of participants is provided in Table 1. Participants in the Sinopharm and Barekat groups had higher mean ages than other vaccine groups. The mean BMI of participants was 25.5 (SD: 4.3), which was higher in those receiving the Barekat [26.6 (SD: 4.2)] compared to participants receiving other vaccines (Table 1).Table 1 The age and sex distribution of participants who had completed follow ups, and proportion with 95% confidence intervals (in parentheses) of at least one local and systemic adverse effects after vaccination by vaccine brands and doses Adverse effects Sputnik V Sinopharm AZD1222 COVIran Barekat Dose 1 Dose 2 Dose 1 Dose 2 Dose 1 Dose 2 Dose 1 Dose 2 Number of participants 1253 823 1429 880 1010 840 950 365 Mean (SD) age (in year) 37.6 (10.7) 37.3 (10.9) 55.5 (22.8) 55.4 (24.0) 38.2 (15.1) 37.3 (13.7) 54.3 (12.1) 52.3 (14.2) Sex [number (%)] Male 651 (52.0) 386 (46.9) 620 (43.4) 360 (41.0) 399 (39.5) 339 (40.4) 622 (65.5) 225 (61.6) Female 602 (48.0) 437 (53.1) 809 (56.6) 520 (59.0) 611 (60.5) 501 (59.6) 328 (34.5) 140(38.4) Body Mass Index 25.4 (4.0) 25.2 (4.0) 25.3 (4.6) 25.1 (4.4) 24.7 (4.0) 24.8 (4.0) 26.6 (4.2) 26.8 (4.3) At least one solicited local adverse effect Total 78.5 (76.2-80.8) 64.8 (61.5-68.0) 38.6 (36.1-41.1) 29.1 (26.1-32.1) 87.4 (85.4-89.5) 68.3 (65.2-71.5) 33.4 (30.4-36.4) 50.9 (45.8-56.1) Male 69.0 (65.4-72.5) 57.3 (52.3-62.2) 27.6 (24.1-31.2) 18.3 (14.3-22.3) 78.2 (74.1-82.3) 60.8 (55.6-66.0) 25.6 (22.1-29.0) 40.4 (34.0-46.9) Female 88.8 (86.3-91.4) 71.4 (67.2-75.6) 47.0 (43.5-50.4) 36.5 (32.4-40.6) 93.5 (91.5-95.4) 73.5 (69.6-77.3) 48.2 (42.8-53.6) 67.9 (60.1-75.6) At least one solicited systemic adverse effect Total 73.8 (71.4-76.3) 64.2 (60.9-67.4) 48.5 (45.9-51.1) 37.5 (34.3-40.7) 88.5 (86.5-90.5) 59.8 (56.4-63.0) 31.2 (28.3-34.2) 35.9 (31.0-40.8) Male 67.1 (63.5-70.7) 59.3 (54.4-64.2) 38.5 (34.7-42.4) 28.6 (23..3) 85.5 (82.0-88.9) 51.6 (46.3-57.0) 28.0 (24.4-31.5) 30.7 (24.6-36.7) Female 81.1 (77.9-84.2) 68.4 (64.1-72.8) 56.1 (52.7-59.5) 43.7 (39.4-47.9) 90.5 (88.2-92.8) 65.3 (61.1-69.4) 37.5 (32.3-42.7) 44.3 (36.0-52.5) Considering that the enrolment was started with high-risk groups and those with a history of underlying diseases, the prevalence of underlying diseases was high in participants with 62.6% (95% CI 61.2-64.0) having a history of underlying diseases. Among first-dose recipients, 58.9% (95% CI 57.5-60.3) had one or more local adverse effects, and 60.5% (95% CI 59.1-61.9) had one or more systemic adverse effects. Among second-dose recipients, 53.1% (95% CI 51.2-55.0) had one or more local adverse effects, and 50.8% (95% CI 48.8-52.7) had one or more systemic adverse effects. The frequency of one or more local and systemic adverse effects was also highest in the first dose of the AZD1222 vaccine. Except for local adverse effects in Barekat recipients, the frequency of local and systemic adverse effects was lower after the second dose of vaccines compared to the first dose (Table 1). The observed systemic adverse effects were significantly higher than the expected rates. As depicted in Fig. 1, even on the 7th day after vaccination, the ratio of observed to expected systemic reactogenicities is high (nearly four), and its lower bounds are higher than one.Fig. 1 The observed to expected ratio of systemic adverse effects in 7 days after COVID-19 vaccination Figures 2 and 3 present the local and systemic adverse effects in different vaccine brands in 7 days after the first and second doses of vaccines. The most common local adverse effect reported in all vaccines was pain at the injection site, and the most common systemic adverse effect in all vaccines was fatigue. Most adverse effects had lower frequency after the second dose of vaccines. The systemic adverse effects were higher in each dose in the first 24 h after injection (Fig. 3). Except for redness, itching, and bruising, a similar pattern was also present for local adverse effects (Fig. 2). Compared to Sinopharm and Barekat, AZD1222 and Sputnik V had a higher frequency of local and systemic adverse effects (Table 2, Figs. 2 and 3).Fig. 2 The frequency of local adverse effects in 7 days after COVID-19 vaccination by vaccine doses and vaccine brands Fig. 3 The frequency of systemic adverse effects in 7 days after COVID-19 vaccination by vaccine doses and vaccine brands Table 2 The frequency of local and systemic reactogenicity events in the 1-7 days after vaccination by vaccine doses and vaccine brands Adverse effects Sputnik V [% (95% CI)] Sinopharm [% (95% CI)] AZD1222 [% (95% CI)] COVIran Barekat [% (95% CI)] Dose 1 Dose 2 Dose 1 Dose 2 Dose 1 Dose 2 Dose 1 Dose 2 Pain 77.6 (75.2-79.9) 63.9 (60.5-67.2) 35.5 (33.0-38.0) 27.3 (24.4-30.4) 86.0 (83.7-88.1) 66.5 (63.2-69.7) 30.9 (28.0-34.0 49.0 (43.8-54.3) Redness 2.3 (1.5-3.2) 3.8 (2.5-5.3) 0.6 (0.2-1.1) 0.6 (0.1-1.32) 9.9 (8.1-11.8) 4.0 (2.8-5.6) 0.3 (0.1-0.9) 1.1 (0.3-2.7) Swelling 7.5 (6.1-9.1) 7.2 (5.5-9.1) 2.3 (1.6-3.2) 1.7 (0.9-2.8) 20.1 (17.6-22.7) 7.4 (5.7-9.3) 2.3 (1.4-3.4) 3.3 (1.7-5.6) Induration 10.6 (8.9-12.4) 6.9 (5.2-8.8) 5.0 (3.9-6.2) 1.5 (0.7-2.5) 32.8 (29.8-35.7) 9.5 (7.6-1.1) 4.3 (3.1-5.8) 3.0 (1.5-5.3) Bruise 2.7 (1.8-3.7) 2.2 (1.3-3.4) 1.5 (0.9-2.3) 1.6 (0.8-2.6) 4.3 (3.1-5.6) 3.9 (2.7-5.4) 1.2 (0.5-2.0) 1.9 (0.7-3.9) Warmness 3.8 (2.8-5.0) 2.7 (1.6-4.0) 3.7 (2.7-4.8) 0.9 (0.3-1.7) 22.7 (20.0-25.3) 6.0 (4.4-7.7) 1.9 (1.1-2.9) 0.8 (0.1-2.3) Itching 2.2 (1.4-3.1) 2.8 (1.7-4.1) 1.6 (1.0-2.4) 0.9 (0.3-1.7) 9.6 (7.8-11.5) 3.2 (2.1-4.6) 1.7 (0.9-2.7) 1.4 (0.4-3.1) Fever 35.1 (32.4-37.8) 31.1 (27.9-34.3) 14.4 (12.6-16.3) 9.7 (7.7-11.8) 63.3 (60.2-66.2) 26.4 (23.4-29.5) 8.4 (6.7-10.3) 7.9 (5.3-11.2) Nausea 13.3 (11.4-15.3) 12.5 (10.3-14.9) 7.8 (6.4-9.2) 4.8 (3.4-6.4) 26.0 (23.3-28.8) 9.0 (7.1-11.1) 2.8 (1.8-4.1) 1.9 (0.7-3.9) Malaise 43.6 (40.8-46.3) 33.7 (30.4-37.0) 25.9 (23.6-28.2) 22.6 (19.8-25.5) 61.7 (58.6-64.6) 31.7 (28.5-34.9) 12.8 (10.7-15.1) 12.6 (9.3-16.4) Chills 29.1 (26.5-31.6) 26.1 (23.1-29.2) 6.0 (4.8-7.3) 3.2 (2.1-4.5) 51.7 (48.6-54.8) 12.4 (10.2-14.7) 1.6 (0.8-2.5) 3.3 (1.7-5.6) Headache 40.2 (37.4-43.0) 35.4 (32.0-38.7) 20.6 (18.5-22.7) 15.2 (12.9-17.7) 62.4 (59.3-65.3) 32.4 (29.2-35.6) 12.7 (10.6-15.0) 13.4 (10.1-17.3) Joint pain 32.1 (29.5-34.7) 29.4 (26.3-32.6) 15.4 (13.5-17.3) 11.1 (9.1-13.4) 58.9 (55.8-61.9) 22.6 (19.8-25.6) 7.6 (5.9-9.4) 9.0 (6.3-12.4) Myalgia 41.2 (38.4-43.9) 35.5 (32.2-38.8) 18.2 (16.2-20.2) 14.0 (11.7-16.4) 63.7 (60.6-66.6) 30.9 (27.8-34.1) 9.5 (7.6-11.5) 13.4 (10.1-17.3) Fatigue 47.6 (44.8-50.4) 36.5 (33.1-39.8) 30.3 (27.9-32.7) 24.6 (21.8-27.6) 67.4 (64.4-70.3) 37.1 (33.8-40.4) 17.1 (14.7-19.6) 19.5 (15.5-23.8) The average days with at least one local adverse effect after receiving all vaccines' first and second doses was 1.81 and 1.05 days, respectively. It was higher for AZD1222 than other vaccines. Moreover, the average number of days with pain in injection site in the first and second doses were higher than other adverse effects. The average days with at least one systematic adverse effect in individuals after receiving the first and second doses of all vaccines were 3.71 and 2.87 days, respectively. Again, it was higher for AZD1222 than other vaccines. Also, the average number of days with fatigue in the first, and fever in the second dose were higher than other adverse effects (Table 3).Table 3 The mean and standard deviation (SD) of duration (in days) of adverse effects after vaccination by vaccine brands Adverse effects Sputnik V Sinopharm AZD1222 COVIran Barekat Dose 1 Dose 2 Dose 1 Dose 2 Dose 1 Dose 2 Dose 1 Dose 2 Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Local Any 1.93 (2.14) 1.45 (1.91) 0.71 (1.35) 0.49 (1.0) 4.13 (4.48) 1.62 (2.05) 0.60 (1.27) 0.94 (1.38) Pain 1.51 (1.25) 1.10 (1.12) 0.51 (0.87) 0.39 (0.78) 2.28 (1.65) 1.14 (1.10) 0.45 (0.82) 0.76 (0.98) Redness 0.03 (0.29) 0.05 (0.31) 0.01 (0.78) 0.01 (0.11) 0.21 (0.75) 0.05 (0.27) 0.01 (0.56) 0.01 (0.16) Swelling 0.10 (0.46) 0.9 (0.39) 0.3 (0.25) 0.2 (0.19) 0.37 (0.92) 0.9 (0.36) 0.2 (0.18) 0.4 (0.30) Induration 0.14 (0.50) 0.9 (0.40) 0.06 (0.31) 0.01 (0.13) 0.66 (1.20) 0.13 (0.49) 0.04 (0.24) 0.04 (0.24) Bruise 0.04 (0.35) 0.02 (0.22) 0.03 (0.32) 0.02 (0.25) 0.08 (0.48) 0.07 (0.50) 0.02 (0.27) 0.03 (0.23) Warmness 0.04 (0.26) 0.02 (0.18) 0.04 (0.24) 0.01 (0.12) 0.35 (0.82) 0.07 (0.32) 0.02 (0.18) 0.01 (0.15) Itching 0.02 (0.19) 0.04 (0.31) 0.02 (0.21) 0.01 (0.11) 0.15 (0.55) 0.04 (0.29) 0.02 (0.23) 0.02 (0.33) Systemic Any 4.01 (4.38) 3.25 (3.98) 2.17 (3.86) 1.53 (2.95) 7.40 (6.07) 2.93 (4.47) 1.01 (2.43) 1.20 (2.49) Fever 0.44 (0.69) 0.36 (0.60) 0.19 (0.55) 0.12 (0.41) 0.93 (0.91) 0.34 (0.66) 0.10 (0.39) 0.13 (0.51) Nausea 0.17 (0.51) 0.15 (0.45) 0.11 (0.50) 0.05 (0.27) 0.37 (0.78) 0.11 (0.41) 0.03 (0.21) 0.02 (0.16) Malaise 0.63 (0.90) 0.46 (0.78) 0.41 (0.86) 0.33 (0.73) 1.08 (1.19) 0.48 (0.90) 0.19 (0.58) 0.18 (0.54) Chills 0.35 (0.61) 0.30 (0.55) 0.06 (0.29) 0.03 (0.23) 0.66 (0.75) 0.14 (0.41) 0.02 (0.16) 0.03 (0.19) Headache 0.64 (0.98) 0.59 (1.02) 0.32 (0.75) 0.21 (0.58) 1.07 (1.15) 0.48 (0.88) 0.17 (0.56) 0.19 (0.57) Joint pain 0.42 (0.73) 0.37 (0.64) 0.23 (0.69) 0.15 (0.50) 0.96 (1.09) 0.32 (0.75) 0.09 (0.37) 0.13 (0.49) Myalgia 0.61 (0.89) 0.49 (0.77) 0.30 (0.78) 0.21 (0.62) 1.07 (1.10) 0.46 (0.89) 0.13 (0.47) 0.20 (0.61) Fatigue 0.69 (0.90) 0.51 (0.79) 0.50 (0.97) 0.38 (0.82) 1.24 (1.25) 0.57 (0.97) 0.25 (0.68) 0.30 (0.71) Compared to Sinopharm, both local and systemic adverse effects of AZD122 and Sputnik vaccines were higher after the first or second doses. The systemic adverse effects of Barekat were lower than Sinopharm (OR = 0.56, 95% CI 0.46-0.67) while its local adverse effects were similar to Sinopharm (P value: 0.969) after the first dose of vaccines. In the second dose, while the systemic adverse effects of Barekat were similar to Sinopharm (P value = 0.443), its local adverse effects were higher than Sinopharm (OR = 2.98, 95% CI 2.29-3.87). There were no significant differences between the local and systemic adverse effects of AZD1222 and Sputnik vaccines for the second doses. Local and systemic adverse effects of Barekat were lower than AZD1222 and Sputnik in both doses of vaccines (Table 4). Except for systemic adverse effects after the second dose of vaccines, local and systemic adverse effects decreased with an increase in age. All local and systemic adverse effects were higher in female participants. Prior COVID-19 disease increased the odds of local and systemic adverse effects only after the first dose of vaccines. Among the comorbidities, allergy and hypertension increased the odds of local adverse effects after the first dose of vaccines. Allergy, cardiac diseases, and cancers increased the odds of systemic adverse effects after the first dose of vaccines. Cancers were the only comorbidity that increased the odds of systemic adverse effects after the second dose of vaccines (OR = 1.87, 95% CI 1.25-2.80), as shown in Table 4.Table 4 The associated factors with at least one solicited local or systemic adverse effects (AE) in multiple logistic regression models Independent variables Local AE after 1st dose Systemic AE after 1st dose Local AE after 2nd dose Systemic AE after 2nd dose OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value Age 0.97 (0.97-0.98) < 0.001 0.98 (0.97-0.98) < 0.001 0.98 (0.97-0.98) < 0.001 0.99 (0.99-1.00) 0.298 Female sex 2.65 (2.29-3.07) < 0.001 1.78 (1.55-2.04) < 0.001 2.07 (1.76-2.43) < 0.001 1.69 (1.45-1.98) < 0.001 Prior COVID-19 1.32 (1.17-1.50) < 0.001 1.20 (1.07-1.35) 0.001 1.07 (0.94-1.22) 0.291 1.08 (0.96-1.23) 0.187 Vaccine brands Sinopharm Reference - Reference - Reference - Reference - Sputnik V 4.74 (3.90-5.76) < 0.001 2.54 (2.11-3.06) < 0.001 3.64 (2.91-4.55) < 0.001 3.19 (2.55-3.99) < 0.001 AZD1222 8.73 (6.93-10.99) < 0.001 6.79 (5.39-8.57) < 0.001 4.14 (3.32-5.17) < 0.001 2.56 (2.06-3.18) < 0.001 COVIran Barekat 1.00 (0.83-1.20) 0.969 0.56 (0.46-0.67) < 0.001 2.98 (2.29-3.87) < 0.001 1.10 (0.85-1.44) 0.443 Comorbidities Allergy 2.18 (1.16-4.08) 0.015 2.47 (1.34-4.56) 0.004 NR - NR - Hypertension 1.25 (1.02-1.55) 0.032 NR - NR - NR - Cardiac diseases NR - 1.55 (1.22-1.97) < 0.001 NR - NR - Cancer NR - 1.73 (1.13-1.91) 0.006 NR - 1.87 (1.25-2.80) 0.002 NR not retained in the multiple logistic regression models, OR odds ratio, CI confidence intervals Multiple Logistic regression results for the odds of local and systemic side effects after the first dose of vaccines are shown in Table 5. All local and systemic adverse effects were higher in female participants and decreased with an increase in the age of participants. The odds of redness, induration, itching and swelling were higher in obese participants. Prior COVID-19 disease increased the odds of pain at injection site and systemic adverse effects except for nausea and fever. Headache was lower in participants with comorbidities (OR = 0.81, 95% CI 0.69-0.96).Table 5 The association of age, sex, obesity, commodities, and prior COVID-19 infection with local and systemic reactogenicities following the first dose of all vaccines in multiple logistic regression Adverse effects Female sex Age (year) Commodities Prior COVID-19 disease Obesity OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value Local Pain 2.54 (2.22-2.91) < 0.001 0.95 (0.95-0.96) < 0.001 1.08 (0.92-1.27) 0.327 1.79 (1.50-2.12) < 0.001 0.85 (0.70-1.03) 0.099 Redness 3.20 (2.13-4.81) < 0.001 0.96 (0.95-0.97) < 0.001 0.80 (0.52-1.22) 0.309 1.28 (0.87-1.88) 0.199 2.05 (1.30-3.22) 0.002 Swelling 2.37 (1.85-3.04) < 0.001 0.97 (0.96-0.97) < 0.001 1.07 (0.80-1.44) 0.613 1.29 (1.00-1.67) 0.046 1.51 (1.09-2.09) 0.012 Induration 2.28 (1.87-2.77) < 0.001 0.96 (0.95-0.97) < 0.001 0.81 (0.64-1.02) 0.077 1.17 (0.94-1.44) 0.146 1.30 (1.00-1.71) 0.048 Bruise 2.11 (1.38-3.22) 0.001 0.98 (0.97-0.99) 0.007 0.67 (0.42-1.08) 0.103 1.08 (0.68-1.72) 0.725 0.60 (0.30-1.22) 0.162 Warmness 2.29 (1.79-2.93) < 0.001 0.96 (0.95-0.97) < 0.001 1.18 (0.87-1.59) 0.269 1.02 (0.78-1.33) 0.872 1.16 (0.81-1.66) 0.398 Itching 2.28 (1.60-3.24) < 0.001 0.97 (0.96-0.98) < 0.001 1.03 (0.69-1.55) 0.866 1.17 (0.80-1.69) 0.404 1.62 (1.05-2.52) 0.029 Systemic Fever 1.57 (1.37-1.80) < 0.001 0.96 (0.96-0.97) < 0.001 1.04 (0.88-1.23) 0.610 1.15 (0.98-1.35) 0.084 1.01 (0.82-1.24) 0.877 Nausea 2.91 (2.37-3.57) < 0.001 0.97 (0.96-0.97) < 0.001 0.85 (0.67-1.07) 0.176 1.04 (0.83-1.30) 0.702 0.97 (0.72-1.29) 0.839 Malaise 1.83 (1.61-2.08) < 0.001 0.97 (0.97-0.98) < 0.001 0.99 (0.84-1.16) 0.933 1.22 (1.04-1.42) 0.010 0.94 (0.78-1.14) 0.579 Chills 1.61 (1.38-1.87) < 0.001 0.96 (0.95-0.96) < 0.001 1.14 (0.94-1.38) 0.170 1.24 (1.04-1.48) 0.014 1.12 (0.89-1.40) 0.325 Headache 1.85 (1.62-2.11) < 0.001 0.96 (0.96-0.97) < 0.001 0.81 (0.69-0.96) 0.016 1.23 (1.05-1.44) 0.008 0.95 (0.78-1.16) 0.641 Joint pain 1.87 (1.62-2.15) < 0.001 0.97 (0.96-0.97) < 0.001 1.04 (0.88-1.24) 0.602 1.25 (1.06-1.47) 0.007 0.84 (0.68-1.04) 0.115 Myalgia 1.68 (1.47-1.92) < 0.001 0.96 (0.96-0.97) < 0.001 0.94 (0.80-1.11) 0.506 1.23 (1.05-1.44) 0.008 0.92 (0.76-1.13) 0.466 Fatigue 1.65 (1.45-1.86) < 0.001 0.97 (0.96-0.97) < 0.001 0.88 (0.75-1.02) 0.11 1.18 (1.01-1.37) 0.033 0.97 (0.81-1.17) 0.790 OR odds ratio, CI confidence intervals In another multiple logistic regression models the associated factors with local and systemic adverse effects after the second dose of vaccines were investigated and presented in Table 6. The results were almost similar to the above findings for the first dose. All local and systemic adverse effects were higher in female participants. Except for warmness, itching and swelling, other local and systemic adverse effects decreased with an increase in age. Comorbidities only increased the odds of pain at injection site (P value = 0.048) and were not associated with other local and systemic adverse effects. Obesity only increased the odds of redness after the second dose of vaccines. Prior COVID-19 disease increased the odds of pain at injection site and all systemic adverse effects except nausea.Table 6 The association of age, sex, obesity, commodities, and prior COVID-19 infection with local and systemic reactogenicities following the second dose of all vaccines in multiple logistic regression Adverse effects Female sex Age (year) Commodities Prior COVID-19 disease Obesity OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value Local Pain 1.81 (1.55-2.12) < 0.001 0.97 (0.96-0.99) < 0.001 1.20 (1.00-1.45) 0.048 1.43 (1.18-1.73) < 0.001 0.92 (0.73-1.17) 0.527 Redness 3.15 (1.77-5.61) < 0.001 0.97 (0.95-0.99) 0.005 1.12 (0.62-2.04) 0.698 1.11 (0.65-1.90) 0.693 1.93 (1.02-3.63) 0.042 Swelling 2.79 (1.88-4.14) < 0.001 0.98 (0.97-1.00) 0.069 1.33 (0.86-2.05) 0.195 1.07 (0.72-1.59) 0.704 1.28 (0.77-2.10) 0.331 Induration 2.20 (1.53-3.16) < 0.001 0.98 (0.97-0.99) 0.003 1.14 (0.75-1.72) 0.526 0.85 (0.57-1.27) 0.433 1.48 (0.93-2.36) 0.093 Bruise 3.22 (1.78-5.82) < 0.001 0.97 (0.96-0.99) 0.006 0.68 (0.39-1.18) 0.177 1.27 (0.75-2.16) 0.367 0.81 (0.36-1.82) 0.620 Warmness 3.22 (1.85-5.62) < 0.00 0.98 (0.97-1.00) 0.101 1.06 (0.60-1.87) 0.818 0.76 (0.43-1.36) 0.365 1.14 (0.57-2.27) 0.706 Itching 2.58 (1.43-4.65) 0.002 0.98 (0.96-1.00) 0.094 1.00 (0.53-1.86) 0.994 1.32 (0.75-2.31) 0.322 1.26 (0.62-2.68) 0.494 Systemic Fever 1.56 (1.29-1.90) < 0.001 0.97 (0.97-0.98) < 0.001 1.05 (0.84-1.33) 0.629 1.32 (1.06-1.63) 0.010 1.19 (0.90-1.58) 0.206 Nausea 2.83 (2.04-3.91) < 0.001 0.98 (0.97-0.99) < 0.001 0.82 (0.59-1.16) 0.273 1.29 (0.94-1.77) 0.106 0.60 (0.35-1.00) 0.054 Malaise 1.74 (1.47-2.07) < 0.001 0.99 (0.98-0.99) 0.008 0.90 (0.73-1.10) 0.322 1.39 (1.14-1.12) 0.001 0.86 (0.66-1.12) 0.273 Chills 1.45 (1.15-1.84) 0.002 0.97 (0.96-0.98) < 0.001 1.22 (0.91-1.63) 0.180 1.38 (1.07-1.78) 0.011 1.26 (0.89-1.77) 0.181 Headache 1.90 (1.59-2.27) < 0.001 0.98 (0.98-0.99) < 0.001 1.13 (0.91-1.40) 0.244 1.35 (1.10-1.64) 0.003 0.95 (0.73-1.25) 0.756 Joint pain 1.54 (1.27-1.88) < 0.001 0.98 (0.97-0.98) < 0.001 0.91 (0.72-1.15) 0.474 1.37 (1.11-1.70) 0.004 0.89 (0.66-1.20) 0.454 Myalgia 1.57 (1.32-1.88) < 0.001 0.98 (0.97-0.98) < 0.001 0.92 (0.74-1.13) 0.445 1.30 (1.06-1.59) 0.010 0.95 (0.73-1.25) 0.742 Fatigue 1.62 (1.37-1.91) < 0.001 0.99 (0.98-0.99) 0.001 0.88 (0.72-1.07) 0.226 1.25 (1.03-1.51) 0.020 1.03 (0.81-1.31) 0.785 OR odds ratio, CI confidence intervals The findings indicate that the local and systemic adverse effects in all vaccines did not interfere with or even partially interfere with participants' daily activities. Also, after receiving the second dose of vaccines, the interference with daily activities is less than the first dose. The severity of adverse effects in the Barekat vaccine was lower than the other three vaccines, and the malaise, chills, headache, and myalgia interfered more with people's daily activities than other adverse effects. Besides, these side effects were reported more in the first dose of AZD1222 (Fig. 4).Fig. 4 The severity of adverse effects in the first days after the first and second doses of COVID-19 vaccines Discussion In this study, performed in several cities in Iran, the local and systemic reactogenicities of the COVID-19 vaccines were investigated. AZD1222 and Sputnik had highest local and systemic adverse effects frequency, while most adverse effects were the lowest in Barekat recipients. Except for AZD1222, the incidence of local and systemic adverse effects was mild to moderate and did not interfere with the daily activities of most individuals. The adverse effects in the second dose were less than in the first. Similar to our findings other studies reported a higher rate of reactogenicity after the first dose of AstraZeneca and Sputnik V . Adverse events after the first dose of Janssen vaccine were also higher than its second dose . However, in some studies [8, 18-20], it has been shown that adverse effects in the second dose were more than in the first dose. This could be due to the nature of the vaccines used, the response of the individual's immune system, the study methods and location, and age and sex differences between studies. Considering our results and the findings of a systematic review and meta-analysis study , it can be confirmed that first dose of adenovirus vectored vaccines is more reactogenic than the second one. For the mRNA and protein subunit vaccines, the opposite is true. For the Sinopharm, we also find similar results to AZD1222 and Sputnik regarding comparing adverse effects in two doses of vaccines. This finding was similar to the results of another study in the UAE . However, in another inactivated vaccine (Barekat), the frequency of at least one local adverse effect was higher after the second dose, and for the systemic adverse effects, the difference between the two doses was not significant. This pattern was similar to the results of another study on CoronaVac, which is an inactivated COVID-19 vaccine . It seems that the pain in injection site, which was higher after the second dose of the Barekat vaccine, caused a higher frequency of at least one local adverse effect after the second dose of Barekat. Considering the limited evidence for reactogenicity events of the Barekat vaccine, more studies with a higher sample size are needed to justify the above findings. Another study in Turkey , showed a higher incidence of reactogenicities after the second dose of Covaxine (an inactivated vaccine similar to Barekat) and a lower incidence of reactogenicities after the second dose of Covishield. After each dose, the most commonly reported reactions were pain at the injection site and fatigue, followed by malaise in all vaccines. Various studies [8, 17, 25-31] showed that pain at the injection site is the most common local reactogenicity reported. Also, studies conducted in the third phase of the clinical trials indicated that pain at the injection site was reported as the most common complication. Moreover, injection site pain has been commonly reported as a local reaction in other COVID-19 vaccines . Adverse effects after the AZD1222 vaccination were higher than other vaccines. Other studies also showed similar findings . It is believed that the high local and systemic adverse effects of AZD1222 might be because it is a non-reproducible adenovirus carrier vaccine and uses a protein similar to the protein produced by the SARS-CoV2 virus following a natural infection . Lower frequency of adverse effects after vaccination with Barekat and Sinopharm can be attributed to their nature, which are inactivated vaccines. Many other studies [21-24, 35] also reported a lower frequency of local and systemic adverse effects in recipients of inactivated vaccines. Differences in vaccine platforms and structures, immunogenicity, and mechanism of action are the main reasons for the discrepancy between the reactogenicities of COVID-19 vaccines. This study found that pain at the injection site and fatigue were the most common local and systemic adverse effects of the Sinopharm vaccine, which was consistent with studies carried out in the Czech Republic , Iraq , China , and the United Arab Emirates . The most common adverse effects of the Sputnik V vaccine were also pain at the injection site and fatigue. In a clinical trial conducted in Russia , this vaccine's most common adverse effects were pain at the injection site, fever, and chills. Also, in a study conducted on health workers , it was shown that pain at the injection site and fatigue were the most common adverse effects of Sputnik V and these reactogenicities were significantly more common in women and young people. In the current study, similar to other vaccines, the most common adverse effects of Barekat were pain at the injection site and fatigue. Several risk factors related to local and systemic adverse effects after vaccination were identified in the present study. These risk factors include younger age, female sex, and BMI greater than 30 kg/m2. These findings are similar to the findings of studies carried out in the Czech Republic , Netherlands , Iraq , the United Kingdom , Saudi Arabia , Jordan , India as well as the findings of the third phase of several clinical trials . However, a study in Saudi Arabia showed that the reactogenicities were higher in men than women, possibly due to the high proportion of men participating in that study . The female gender was considered a significant risk factor for adverse effects following vaccination. Women generally have more robust immune responses than men . Hence, they are more likely to have frequent and severe adverse effects. This difference may be related to genetic or hormonal differences between women and men . In this study, allergy, hypertension, cardiac diseases and cancer were the underlying diseases that increased the odds of adverse effects. Other studies in Iraq and the Netherlands showed that asthma, hypertension, diabetes, and respiratory diseases are significant risk factors for post-vaccination adverse effects. Similarly, food and/or drug allergies and chronic diseases were associated with a higher frequency of post-vaccination side effects [45-47]. On the other hand, in a study done in France , no association was observed between disease history and vaccines' reactogenicity. Although most studies showed a positive association between the presence of chronic diseases and reactogenicities, the underlying mechanisms are unclear. Interaction of vaccines with medications used, different immunological responses, better reporting and perceptions of adverse effects, and lower tolerance to adverse effects (in the case of cancers) are among the proposed mechanisms which should be investigated exclusively. The differences in the age groups, vaccine brands, prevalence of comorbidities, and sample size may be the reasons for the difference in studies' results. Our results showed that prior COVID-19 infection increased the odds of local and systemic adverse effects only after the first dose of vaccines. A study in Mexico on people who received the BNT162b2 vaccine , and another on BNT162b2, mRNA-1273 and Ad26.COV2.S vaccines also reported similar findings. Higher T-cell and antibody responses in participants with a history of COVID-19 infection may be the reason for this finding. It has been shown that T-cell responses and anti-spike antibodies were higher after the first dose of the BNT162b2 vaccine in people with prior COVID-19 infection compared to infection-naive people. These responses were similar after two doses of the vaccine in infection-naive people and people with prior COVID-19 infection . In fact, the first vaccine dose boosts the immune responses in people with prior COVID-19 infection, while the second vaccine dose results in little increase in immune responses . Finally, other studies reported a higher frequency of adverse effects in participants with prior COVID-19 infection . In the current study, most reported local and systemic adverse effects were mild to moderate in severity. In a clinical trial on the AZD1222 vaccine and another study in Saudi Arabia , it was observed that the severity of adverse effects was mild to moderate. Also, in other studies on the Sinopharm vaccine , the adverse effects have been mild. The severity of local and systemic adverse effects is influenced by the nature of the vaccines , the number of doses received, and the age and gender of participants. The present study has various strengths, including using a standard protocol provided by WHO, active daily contact and direct monitoring of the study's implementation, comparing four different vaccines, and using online methods and telephone calls to report adverse effects. However, the sample size for the second dose of Barekat did not reach 1000 participants, which might be a limitation of the current study. As another limitation, the participants' weight and height did not measure and were based on self-reporting. Conclusions In this study, adverse effects after vaccination (both systemic and local) often had the highest incidence in 1 to 2 days after vaccination and reached their lowest level at the end of the first week. Besides, pain at the injection site and fatigue were the most common reactogenicities of COVID-19 vaccination. However, most local and systemic adverse effects were not severe and did not interfere with people's daily activities. AZD1222 and Sputnik had higher adverse effects frequencies than Sinopharm and Barekat vaccines. Furthermore, younger age, female gender, some comorbidities, and prior COVID-19 infection were associated with higher reactogenicities. Abbreviations CI Confidence intervals WHO World Health Organization CDC Centers for Disease Control and Prevention BMI Body Mass Index OR Odds ratio SD Standard deviation Acknowledgements The steering committee for COVID-19 vaccines studies at MOHME provided many technical notes on data analysis and had full supervision on this study. We really appreciate the efforts of Prof. Akbar Fotouhi, Dr. Bita Mesgarpoor, Prof. Ghobad Moradi, Prof. Farid Najafi, Prof. Masud Yunesian and Prof. Seyed Mohsen Zahraei. Author contributions SSN, SN, MF1, PMs, AA, AH, FSS, HS2 and MHE contributed to conception and design of study, acquisition and analysis of data. ME, SM, and MHE wrote the first draft of the manuscript. ME, RA and SM analyzed the data. RA, HK, ZE, EB1 and ME curated the data. HK, ZH, EB, and MHE contributed in data and software management, interpretation of results, critically revised the manuscript. MF2, HS1, MA, RJ, MV, EB2, HV, and RC verified the underlying data, contributed to design of study, analysis and interpretation of results, critically revised the manuscript. MHE acquired funding. All authors agree to be accountable for all aspects of work ensuring integrity and accuracy. All authors read and approved the final manuscript. Funding This work was supported by Shahroud University of Medical Sciences [Grant Number: 99135, 140068]; Vice-chancellery for research and technology at Iranian Ministry of Health and Medical Education [Grant Number: 2302] and World Health Organization [WHO References: 2021/1169483-0 and, 2022/1217943-1]. Availability of data and materials All data of this study can be provided at the request of the corresponding author (Prof. Mohammad Hassan Emamian, via [email protected]). All researchers around the world can send their proposed titles. After screening in a scientific committee, the new titles will be approved and the required data will be available for researchers. The new articles and reports then will be prepared by collaboration with researchers of this study. Declarations Ethics approval and consent to participate This study was approved by the ethics committee of Shahroud University of Medical Sciences, Shahroud, Iran with the reference number of IR.SHMU.REC.1400.012. Participation in this study was entirely voluntary, and after explaining the study objectives and methods, a written consent form was obtained from all participants. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. 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PMC10000358 | Sci Rep Sci Rep Scientific Reports 2045-2322 Nature Publishing Group UK London 31173 10.1038/s41598-023-31173-y Article Development of an inhibiting antibody against equine interleukin 5 to treat insect bite hypersensitivity of horses Langreder Nora 1 Schackermann Dorina 14 Meier Doris 1 Becker Marlies 1 Schubert Maren 1 Dubel Stefan 1 Reinard Thomas 2 Figge-Wegener Stefanie 3 Rossbach Kristine 4 Baumer Wolfgang 5 Ladel Simone 4 Hust Michael [email protected] 1 1 grid.6738.a 0000 0001 1090 0254 Institut fur Biochemie, Biotechnologie und Bioinformatik, Technische Universitat Braunschweig, Spielmannstr. 7, 38106 Braunschweig, Germany 2 grid.9122.8 0000 0001 2163 2777 Institut fur Pflanzengenetik Abt II, Leibniz Universitat Hannover, Herrenhauser Strasse 2, 30419 Hannover, Germany 3 Novihum Technologies GmbH, Weidenstrasse 70-72, 44147 Dortmund, Germany 4 Wirtschaftsgenossenschaft deutscher Tierarzte eG (WDT), Siemensstrasse 14, 30827 Garbsen, Germany 5 grid.14095.39 0000 0000 9116 4836 Institut fur Pharmakologie und Toxikologie, Fachbereich Veterinarmedizin, Freie Universitat Berlin, Koserstrasse 20, 14195 Berlin, Germany 10 3 2023 10 3 2023 2023 13 40293 11 2022 7 3 2023 (c) The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit Insect bite hypersensitivity (IBH) is the most common allergic skin disease of horses. It is caused by insect bites of the Culicoides spp. which mediate a type I/IVb allergy with strong involvement of eosinophil cells. No specific treatment option is available so far. One concept could be the use of a therapeutic antibody targeting equine interleukin 5, the main activator and regulator of eosinophils. Therefore, antibodies were selected by phage display using the naive human antibody gene libraries HAL9/10, tested in a cellular in vitro inhibition assay and subjected to an in vitro affinity maturation. In total, 28 antibodies were selected by phage display out of which eleven have been found to be inhibiting in the final format as chimeric immunoglobulin G with equine constant domains. The two most promising candidates were further improved by in vitro affinity maturation up to factor 2.5 regarding their binding activity and up to factor 2.0 regarding their inhibition effect. The final antibody named NOL226-2-D10 showed a strong inhibition of the interleukin 5 binding to its receptor (IC50 = 4 nM). Furthermore, a nanomolar binding activity (EC50 = 8.8 nM), stable behavior and satisfactory producibility were demonstrated. This antibody is an excellent candidate for in vivo studies for the treatment of equine IBH. Subject terms Applied immunology Inflammatory diseases Biotechnology Biologics Antibody therapy K+S and WDT fundingTechnische Universitat Braunschweig (1042)Open Access funding enabled and organized by Projekt DEAL. issue-copyright-statement(c) The Author(s) 2023 pmcIntroduction Insect bite hypersensitivity (IBH), also called summer eczema, is the most common allergic skin disease of horses1,2. It is a chronical relapsing seasonal disease caused by insect bites of the Culicoides spp.3,4. The prevalence, strongly correlating with the distribution of the Culicoides, ranges worldwide from 3% to 60%5. In particular, Icelandic horses that are imported from Iceland to e.g. Europe are affected with a prevalence of > 50% due to the fact that Culicoides spp. do not exist in Iceland5,6. Symptoms usually occur from spring until autumn depending on the mosquito flight season7. Affected horses suffer from hair loss, skin lesions, strong pruritus and possibly secondary infections, typically at the mane and tail and along the dorsal and ventral midline4,8. So far, there is no effective treatment option that can be applied long term without safety concerns. Usually, exposure to the insects is avoided by stabling the horses, covering them with rugs or using insect repellents. Symptomatic treatment with glucocorticoids can have strong side effect9 and application of a histamine receptor 1 antagonist failed to show efficacy10. Alternatively, allergen specific immunotherapy (ASIT) is a promising approach, but still needs further development and lacks well-defined allergens that are in this case a prerequisite for effective treatment4,11. Different salivary gland proteins of the Culicoides spp. act as allergens causing a type I allergy with involvement of a type IVb allergy4,5,11,12. In type I allergic reactions, T cells polarize into CD4+ TH2 cells that secrete interleukin (IL)-4 and IL-13. These interleukins trigger a B cell class switch towards immunoglobulin E (IgE) producing plasma cells. The IgE antibodies bind to the FceRI on mast cells and basophils. A re-exposure to the allergens leads to cross-linking of IgE molecules and thus a degranulation of the cells and subsequent release of inflammatory mediators like histamine and leukotrienes. In addition, chemokines and cytokines are released that cause the recruitment of effector cells like eosinophils, TH2 cells and basophils to the allergic site. In the late phase of type I allergies and in type IVb allergies, TH2 cells produce IL-5 which is responsible for the differentiation, activation, survival and chemotaxis of eosinophil cells and in this way enhances the allergic reaction4,11,13. Eosinophil cells play a crucial role in the pathogenesis of equine IBH. Besides an infiltration of eosinophils to the allergic site, a correlation of the amount of blood eosinophils and severity of IBH has been described8. IL-5 is the main activator and regulator of blood and tissue eosinophil cells14. Therefore, targeting equine IL-5 (eqIL-5) is a promising way to inhibit the allergic reaction caused by eosinophilia and thereby treating equine IBH. For humans, there are already two approved antibodies against IL-5 (Mepolizumab and Reslizumab) and one antibody against the IL-5 receptor alpha subunit (Benralizumab) for the treatment of eosinophilic asthma. All three antibodies prevent the binding of IL-5 to its receptor and were found to be effective and safe15,16. Another approach also targeting eqIL-5 to treat IBH of horses has been published recently8,17,18. There, the researchers developed an active vaccination that contains the interleukin linked to a virus-like particle (VLP) which induced the generation of neutralizing antibodies. According to the authors, their treatment resulted in a reduction of the symptoms. In addition, a decrease of circulating eosinophils after first and second year treatment and a reduced basophil count only after second year treatment was reported. Also, they reported no safety issues during their studies, in particular no difference in parasite presence prior and post vaccination during first and second year studies17,18. Despite promising results and reversible antibody titers, we assume there might be a potential risk of unpredictable future long-term consequences when autoantibodies against the body's own interleukin are generated by active vaccination. As the main regulator of eosinophil cells, IL-5 plays a significant role in the protective immune response against invading pathogens like helminths, virus and bacteria14,19. Also, antibodies generated by active vaccination could potentially enhance the allergic reaction by recruiting more immune cells due to the effector function mediated by the fragment crystallizable (Fc) region. Therefore, we consider a passive vaccination with a well-defined neutralizing monoclonal antibody as a safer option. Immunoglobulin G (IgG) antibodies have a half-life of approximately 21 days and would consequently need to be administered regularly over the summer period. This has the advantage that the treatment is better controllable and could be stopped at any time point if undesired immune reactions occurred. In order to avoid any unwanted immune reaction, we generate antibodies with all constant parts as equine domains, only the heavy chain variable domain (VH) and light chain variable domain (VL) are still of human origin. We choose the IgG6 subclass which was described to have no Fc-mediated effector function20, so an additional recruitment of immune cells to the allergic site is avoided. In the veterinary field, few therapeutic antibodies have already been approved for treatment of dogs and cats21-23. In comparison, horses have a significantly higher body weight which implies the challenge of high production costs for recurring vaccinations during the summer season. We are aware that in the long term, a low-cost production system is required for the treatment to be economical. In this report, however, we focus on the development of a potential antibody candidate for the therapeutic treatment of equine IBH. Such a therapeutic antibody must fulfill certain requirements depending on the application. In our case, we want to reduce the allergic reaction by selecting an antibody without effector function that prevents the binding of eqIL-5 to its receptor. Our main criterion for antibody selection is the inhibition effect. In this regard, specific antibody binding to the target with high binding affinity is also required. In addition to a strong inhibition, antibody stability is a necessity and a high producibility is advantageous. For the antibody development, we first produced the antigen eqIL-5 recombinantly. Then, binding antibodies were selected by antibody phage display. Selected antibodies were tested for their functionality in a cellular in vitro inhibition assay. The most promising candidates were characterized with regard to their stability and specificity and then subjected to an in vitro affinity maturation for further improvement of their inhibition effect. Results Production of recombinant eqIL-5 Target availability is a prerequisite for the development of a therapeutic antibody. In this study, the target eqIL-5 was produced recombinantly. It consists of 134 amino acids, of which the first 19 amino acids make up the signal peptide sequence (Uniprot O02699). EqIL-5 is a disulfide-linked homodimer24 with a size of about 26 kDa. The interleukin with an 8 x His-tag was successfully produced in Expi293F suspension cells (Thermo Fischer Scientific) and purified by nickel-loaded Sepharose, eluted with 250 mM Imidazole and dialyzed in 1 x PBS (Supplementary Fig. S1). Selection of antibodies against eqIL-5 via antibody phage display The next step of the development of a therapeutic antibody against eqIL-5 was the selection of antibodies that bind to this target via antibody phage display. In this study, three different panning approaches were applied in order to select a large number of diverse binders: Firstly, panning in a multititer plate (MTP) with immobilized antigen25, secondly, panning in solution with biotinylated antigen26 and thirdly, capture panning with human Fc-tagged antigen. For all three methods the human naive antibody gene libraries HAL9 (lambda) and HAL10 (kappa) were used as starting material27. Table 1 summarizes the number of individual binders selected by the three panning strategies in relation to the number of clones that was tested in the screening ELISA. With all three panning techniques, individual binders could be selected against the target eqIL-5. The average hit rate for panning in MTP was 2.0%, for panning in solution 4.1% and for capture panning 1.1%. 29 lambda binders and 7 kappa binders were selected, which results in an overall hit rate of 3.9% for the HAL9 and 1.1% for the HAL10 library. In total, 36 binders were selected against eqIL-5. One of these binders (NOL46-1-A1) was selected using all three different techniques, thereby reducing the number of unique binders to 34. In a next step, these antibodies were cloned and produced in the human single chain fragment variable (scFv)-Fc format for further analysis. Six antibodies could not be produced in this format and were therefore excluded from further analysis. This resulted in 28 remaining scFv-hFc antibodies against eqIL-5 for a first functional screening.Table 1 Selection of unique binders against eqIL-5 via different antibody phage display techniques. Library Panning in MTP Panning in solution Capture panning HAL9 12/368 15/276 2/92 HAL10 3/368 4/184 0/92 Selection of lead candidates with a cellular in vitro inhibition assay In the next step, the binding antibodies were tested regarding their functionality. For this purpose, a cellular inhibition assay was established in order to test whether the binding of the selected antibodies to the antigen inhibits the interaction of the interleukin and its receptor on a cell surface. Expi293F suspension cells were transfected transiently with the eqIL-5 receptor DNA subunits IL5RA (Uniprot A0A3Q2L5Z7) and CSF2RB (Uniprot F7DHE0) and co-transfected with eGFP (GenBank AEI54555.1) to differentiate transfected from non-transfected cells. The binding of the interleukin to its receptor on the cells was detected via the 8 x His-tag and cells were analyzed by flow cytometry (Supplementary Fig. S2). Figure 1 presents the relative binding of the interleukin to the cell after pre-incubation with the individual antibody. As a reference for 100% binding, antigen binding to the cell without application of test antibody was measured. The selected antibodies in scFv-hFc format were screened in the cellular inhibition assay using 1000 nM antibody and 5 nM antigen (molar ratio 200:1) (Fig. 1a). The cut-off for inhibiting antibodies was set at 20% so that only antibodies with a significant inhibition effect were considered for next steps. 16 out of the 28 antibodies remained below this cut-off. Nine of these antibodies were selected by panning in MTP, five by panning in solution and one by capture panning. Additionally, the antibody NOL46-1-A1 selected with all three panning strategies was one of the best three inhibiting antibodies. To further characterize the inhibition effect of these 16 antibodies, they were tested in concentrations ranging from 1000 nM to 0.32 nM with a constant antigen concentration of 5 nM (related to dimer) (molar ratio 200:1-0.064:1). Here, a comparison was made for the antibodies in the scFv-hFc format (Fig. 1b) and the final equine IgG6 (eqIgG6) format (Fig. 1c). For the eqIgG6 format all constant domains of the antibodies were replaced with equine domains (IGHC IMGC000040, IGLC28, IGKC IMGT000053), only the VH and VL remained of human origin. The antibodies NOL48-1-C10, NOL48-1-E1, NOL179-2-A8 and NOL185-C12 could not be produced as eqIgG6 and were therefore excluded from further selection. In both formats an unrelated isotype control (SH1351-C1 anti N-cadherin propeptide) was included.Figure 1 Cellular inhibition assay. (a) Screening inhibition assay with 28 scFv-hFc antibodies against eqIL-5 on receptor positive cells using 1000 nM antibody and 5 nM interleukin (related to dimer) (molar ratio 200:1). The cut-off for the selection of inhibiting antibodies is marked with a red line and antibodies for further analysis are marked in colors. (b,c) Titration inhibition assay with antibodies in (b) scFv-hFc format and (c) eqIgG6 format using 1000 nM-0.32 nM antibody and 5 nM antigen (related to dimer) (molar ratio 200:1-0.064:1). IC50 values were determined with OriginPro using the Logistic5 Fit. For the isotype control a linear fit was applied. Screening and titration assays were performed in single measurements (n = 1). n.p. not producible, n.d. not determined. In order to compare the inhibition effect, the antibody concentration necessary to reduce the relative binding to 50% (IC50) was determined. The tables presented in Fig. 1b and c summarize the IC50 values for the selected antibodies in scFv-hFc and eqIgG6 format. IC50 values for the scFv-hFc antibodies ranged from 3 nM (NOL46-1-E1) to 163 nM (NOL46-1-E4) and for eqIgG6 antibodies from 12 nM (NOL48-1-D5 and NOL162-1-F5) to 522 nM (NOL46-1-E4). The IC50 value for NOL179-1-H8 as eqIgG6 could not be determined due to its low inhibition effect. Nearly all tested scFv-hFc antibodies had lower IC50 values compared to the corresponding antibody in eqIgG6 format. To gain a better understanding of this phenomenon, two antibodies (NOL46-1-A1 and NOL46-1-E4) were compared as scFv-hFc, scFv-eqFc and eqIgG (schmatic illustration of the antibody formats presented in Supplementary Fig. S3) in this assay. Antibodies in the equine scFv-Fc and human scFv-Fc format showed a comparable inhibition effect, which was different from the inhibition effect of the eqIgG antibodies (Supplementary Fig. S4a). This indicates that the antibody format but not the Fc-part is responsible for the different inhibition behavior. Interestingly, despite the better inhibition effect in the scFv-Fc format, the same antibodies (NOL46-1-A1 and NOL46-1-E4) presented a lower binding activity as scFv-eqFc compared to the corresponding eqIgG in titration ELISA (Supplementary Fig. S4b and c). The results show a better inhibition of the scFv-Fc format compared to the IgG format. However, out of the 16 antibodies only NOL46-1-A1 and NOL46-1-E4 were producible in the scFv-eqFc format and this only in small amounts (5 mg/L and 9 mg/L). Therefore, it was not reasonable to focus on antibodies in scFv-eqFc format during the development process. Furthermore, the full IgG is the preferred format for therapeutic applications since it is most established in therapeutic and regulatory affairs. Additionally, the Fab fragments of an IgG ususally lead to higher stability than the scFv fragments of an scFv-Fc29 and an IgG has a tendency towards a a longer half-life compared to an scFv-Fc30. Hence, the selection of lead candidates for further development was based on the inhibition of the antibodies as eqIgG6. The two selected eqIgG6 antibodies were NOL48-1-D5 (selected by panning in solution) and NOL162-1-F5 (selected by panning in MTP), both with an IC50 of 12 nM (molar ratio of antibody (bivalent) to antigen (dimer): 2.4). Besides binding and inhibition, stability and specificity are also of great importance for an antibody for therapeutic application. Before further experiments were performed, these characteristics needed to be confirmed in order to enhance the chances of obtaining final candidates with the desired features. Thus, the two antibodies NOL48-1-D5 and NOL162-1-F5 were characterized in the eqIgG6 format regarding their stability in titration ELISA, inhibition assay and size exclusion chromatography (SEC) (Supplementary Fig. S5) and regarding their specificity in an unspecificity ELISA (Supplementary Fig. S6). In summary, only slight decrease of stability was detected when antibodies were stored up to 28 days at 37 degC at a concentration of 0.3 mg/mL. Also, no unspecific behavior of the antibodies was observed in the unspecificity ELISA. In vitro affinity maturation for improvement of lead candidates Next, an in vitro affinity maturation was performed with the lead candidates in order to improve their binding activity and consequently their inhibition effect. Within the scope of library generation from a single parental sequence many approaches have been developed for the introduction of random mutations at the nucleotide level, e.g. error prone PCR31, mutator bacterial strains32 and site-specific mutagenesis of the complementary determining regions33. Here, we chose several rounds of error-prone PCR to generate scFv mutagenesis libraries. With these scFv mutagenesis libraries a panning approach with low amount of antigen and extended washing and incubation steps was performed in order to select antibodies with improved binding activity. A screening ELISA with scFv supernatant was used to find clones with the highest ELISA signals. In addition, it was confirmed by Western Blot that the signals were not significantly biased by the producibility of the scFvs. In total, 3.8% of mutants derived from NOL48-1-D5 had increased signals compared to their parental scFv (up to factor 1.5). Regarding the mutants derived from NOL162-1-F5 there were 6.6% of hits with increased signals (up to factor 2.6). Seven mutants derived from NOL48-1-D5 and four mutants derived from NOL162-1-F5 were selected, all with a signal increase > 1.3 x compared to the corresponding parental scFv. An amino acid sequence alignment of the VH and VL of these affinity-matured antibodies is presented in Fig. 2.Figure 2 Sequence alignment of affinity-matured antibodies. (a) Alignment of the VH and VL region of mutants derived from NOL48-1-D5. (b) Alignment of the VH and VL region of mutants derived from NOL162-1-F5. The CDR regions are marked in boxes. The parental sequences are set as references and amino acid substitutions in other sequences are marked in color. Alignments were constructed using Unipro UGENE. The number of mutations at the amino acid level in the whole scFv region ranged for mutants derived from NOL48-1-D5 from 1 to 5 with an average of 2.7 amino acid exchanges (Fig. 2a). Mutants derived from NOL162-1-F5 had 2 to 4 amino acid exchanges with an average of 3.5 (Fig. 2b). Overall, the position of the mutations was spread over the whole sequences with no significant accumulation in the CDR regions. Only single positions of amino acid substitutions were found in several affinity-matured antibodies (NOL48-1-D5: VH at position 101, VL at position 21 and 96; NOL162-1-F5: VH at position 30 and 97). The antibody mutants were cloned and produced as equine IgG6 antibodies in Expi293F suspension cells for final characterization. The affinity-matured antibodies were analyzed by titration ELISA (Fig. 3a) and cellular inhibition assay (Fig. 3b) including the EC50 and IC50 values in order to compare their binding activity and inhibition effect.Figure 3 Titration ELISA and cellular inhibition assay for affinity-matured antibodies. (a) Titration ELISA of affinity-matured antibodies derived from the parental antibodies NOL48-1-D5 and NOL162-1-F5. Antibodies were titrated on immobilized antigen in eqIgG6 format using 316 nM-0.0032 nM antibody. As negative control, antibodies were titrated on 1% BSA (marked with dashed lines). EC50 values were determined with OriginPro using the Logistic5 Fit. Measurements were performed in triplicates (n = 3). (b) Titration inhibition assay with affinity-matured antibodies derived from the parental antibodies NOL48-1-D5 and NOL162-1-F5. Antibodies were titrated in eqIgG6 format using 1000 nM-0.32 nM antibody and 5 nM antigen (related to dimer) (molar ratio 200:1-0.064:1). IC50 values were determined with OriginPro using the Logistic5 Fit. Measurements were performed in single measurements (n = 1). parAB parental antibody. In the titration ELISA all tested antibodies bound specifically to eqIL-5 and not to BSA. Overall, the antibodies derived from NOL48-1-D5 had a stronger binding activity with EC50 values between 0.4 nM and 2.1 nM compared to the antibodies derived from NOL162-1-F5 with EC50 values ranging from 7.1 nM to 24.2 nM. Both parental antibodies belonged to the least affine antibodies compared to their respective mutants, only single mutants showed weaker binding. The affinity maturation improved the EC50 for NOL48-1-D5 from 1.0 nM to 0.4 nM (factor 2.5) and for NOL162-1-F5 from 9.0 nM to 7.1 nM (factor 1.3). In the cellular inhibition assay the IC50 values ranged from 3 nM to 9 nM including all tested antibodies. Most mutants had a reduced IC50 value compared to both parental antibodies. The affinity maturation improved the IC50 value for NOL48-1-D5 from 6 nM to 3 nM (factor 2.0) and for NOL162-1-F5 from 7 nM to 4 nM (factor 1.8). Mutants derived from the different parental antibodies against eqIL-5 were similarly effective in the inhibition assay, despite different binding behavior in the titration ELISA. This could be explained by the assumption that the antibodies recognize different epitopes. In conclusion, the weaker binding in ELISA of mutants derived from NOL162-1-F5 is no criterion for exclusion since the main aspect for selection of final antibodies is the functionality tested in the cellular inhibition assay. Many mutants were in a similar range regarding their inhibition effect. Considering the parameters IC50 value, curve progression and producibility of the antibodies, we chose NOL226-2-D10 (IC50: 4 nM; producibility: ~ 70 mg/L) and NOL231-1-A3 (IC50: 4 nM; producibility: ~ 30 mg/L) as most promising candidates. Further mutants, such as NOL225-2-C1 (IC50: 4 nM; producibility: ~ 15 mg/L) and NOL231-2-E2 (IC50: 3 nM; producibility: ~ 25 mg/L), could be considered as potential backup candidates. The two antibodies NOL226-2-D10 and NOL231-1-A3 were produced in a 250 mL scale in Expi293F suspension cells. Here, the antibody NOL231-1-A3 was not stable in concentrations > 0.8 mg/mL. The antibody solution showed turbidity indicating that aggregation of the antibody occurred. Also, the antibody concentration measured spectrophotometrically was decreasing over time. Attempts to stabilize NOL231-1-A3 by changing the pH value were not successful. Therefore, NOL226-2-D10 was chosen as final candidate for further studies. Biochemical analysis of final candidate NOL226-2-D10 NOL226-2-D10 was analyzed in regard of its stability and specificity (Supplementary Fig. 7). The long-term stability of NOL226-2-D10 was examined in titration ELSA and cellular inhibition assay with samples stored at 4 degC to reflect storage conditions at final application. NOL226-2-D10 presented hardly any loss of binding activity (Supplementary Fig. S7a) and only slight decrease of the inhibition potential (Supplementary Fig. S7b) after being stored for up to 6 months at a concentration of 1.86 mg/mL at 4 degC. Also, no formation of aggregates or fragments was observed with samples being stored at a concentration of 1.86 mg/mL for 1 month at 4 degC or 2 months at 21 degC (Supplementary Fig. S7c). Furthermore, the unspecificity ELISA displayed no unspecific binding to any of the tested antigens (Supplementary Fig. S7d). Additionally, the final antibody NOL226-2-D10 was tested in respect of its competitive inhibition potential in the in vitro inhibition assay, i.e. the antibody was not pre-incubated with eqIL-5, but applied to the eqIL-5 receptor expressing cells before adding eqIL-5. NOL226-2-D10 was still well-inhibiting with only a slight reduction of the inhibition effect (IC50 = 9 nM in the competitive inhibition assay compared to 4 nM in the original inhibition assay). In comparison, also the parental antibody NOL162-1-F5 was tested in the competitive inhibition assay and showed a reduction of its inhibition potential in the same ratio (IC50 = 15 nM in the competitive inhibition assay compared to 7 nM in the original inhibition assay) (Supplementary Fig. S8). In summary, the lead candidate NOL226-2-D10 provides all required properties for further clinical development: A strong inhibition effect (IC50 = 4 nM, in competitive assay IC50 = 9 nM), nanomolar binding activity to the target (EC50 = 8.8 nM), satisfactory producibility (~ 70 mg/L in transient expression system), high stability and no indication for unspecific behavior. Discussion IBH is the most common allergic skin disease of horses with no specific treatment option so far4. In this study, we developed an antibody against eqIL-5 that is a promising candidate for potential treatment of this disease. In total, 36 binding antibodies to eqIL-5 were selected by antibody phage display from the human naive antibody gene libraries HAL9/1027. Here, we compared three different panning procedures: panning in MTP with directly immobilized antigen, panning in solution with biotinylated antigen and capture panning with human Fc-tagged antigen. Compared to the panning in MTP the panning in solution is slightly more complex but allows the target to be present in its native form which can lead to improved epitope accessibility26,34. The protocol with captured antigen is comparable to the protocol with directly immobilized antigen but potentially allows better target accessibility. A drawback could be that the antigen is dimerized due to the coupling of two Fc-parts and therefore not in its original form. We could select antibodies with all three strategies indicating that a combination of panning strategies can increase the number and diversity of binders. In total, we selected 29 binders from the HAL9 library (lambda) and only seven binders from the HAL10 library (kappa). The higher yield of binders from the lambda library has been described before and may be caused by a better expression level of lambda scFvs compared to kappa scFvs in E. coli35,36. One binder (NOL46-1-A1) was selected using all three techniques, possibly explained by high producibility as scFv antibody fragment in E. coli and strong binding to a well accessible epitope of the antigen. Six of the 36 binders were not producible in the scFv-hFc format and were therefore excluded from further analysis. A cellular in vitro inhibition assay was established for the selection of inhibiting antibodies. Overall, this assay provides a way to easily analyze the antibodies' functionality in vitro when no native cell line expressing the desired receptor is availiable. The same assay setup was for example used successfully with ACE2 receptor expressing cells for a selection of inhibiting antibodies against SARS-CoV-2 spike protein37,38. Nevertheless, it has to be kept in mind that this assay is dependent on the state of the cells and their transfection efficiency. It was observed that absolute values could fluctuate on different measurement dates but the ranking of the antibodies within one measurement was always reproducible and therefore reliable for selection of the best inhibiting antibodies. 16 out of the 28 scFv-hFc antibodies (57%) reduced the binding of eqIL-5 to its receptor on the cell surface to less than 20%. For comparison, 13% of antibodies selected against SARS-CoV-2 RBD from the same antibody gene libraries HAL9/10 inhibited the interaction of S1-S2 with the ACE2 receptor to less than 25% in a similar cellular inhibition assay37. This high rate of inhibiting antibodies indicates that epitopes with crucial amino acids for the interaction of eqIL-5 with the receptor (described for human IL-5 by Patine et al.24) were well accessible during the panning procedure. Nine of the inhibiting antibodies derived from the panning in MTP, five from the panning in solution and one from the capture panning. This shows that important epitopes were still accessible even when the antigen was immobilized directly. Additionally, the antibody NOL46-1-A1 selected with all three panning strategies was one of the best inhibiting antibodies. In the inhibition assay we observed that scFv-Fc antibodies showed stronger inhibition than IgG antibodies. Interestingly, the comparison of two antibodies in scFv-eqFc and eqIgG format showed a better inhibition effect of the scFv-eqFc antibody compared to the corresponding eqIgG antibody while the binding activity determined by titration ELISA was lower for the scFv-eqFc than for the eqIgG. A change of the affinity and behavior in functional assays is possible due to format conversion from scFv-Fc to IgG and individual for each antibody as already shown by others37,39. The two antibodies that performed best as eqIgG6 in the inhibition assay, NOL48-1-D5 and NOL162-1-F5, were used for an in vitro affinity maturation. The affinity maturation improved the binding activity (EC50) in titration ELISA up to factor 2.5 for NOL48-1-D5 and up to factor 1.3 for NOL162-1-F5. For some antibodies, e.g. NOL226-2-D10, the titration curve seemed to be improved without significant reduction of the EC50 value compared to the parental antibody. This is due to the dependence of the EC50 on the maximum signal which was also increased in that case. In the cellular inhibition assay the inhibition effect (IC50) was improved up to factor 2.0 for NOL48-1-D5 and up to factor 1.8 for NOL162-1-F5. These improvements are relatively small compared to other reports which describe an increase of affinities for scFv antibodies by in vitro affinity maturation up to 100x40 or even 500x41. Nevertheless, in our case we consider the aforementioned decreases of the EC50 and IC50 values as significant and successful since the parental antibodies had already EC50 values in the nanomolar range and were well-inhibiting, leaving only small room for improvement. The mutants NOL226-2-D10 and NOL231-1-A3 had an IC50 value of 4 nM showing that only a molar ratio of antibody (bivalent) to antigen (dimer) of 0.8 was necessary to reduce the binding of the interleukin to its receptor to 50%. We hypothesize that the application of these antibodies in the horse would greatly reduce eqIL-5-derived eosinophilia but, depending on the applied dose, would not abolish the complete interaction of all eqIL-5 molecules with the receptor expressing cells. Dose finding in vivo will be required because in the context of equine IBH it may not be necessary to completely neutralize the binding of eqIL-5 to its receptor. It could be sufficient or even beneficial to only partially prevent binding so that natural functions in the body are still maintained. IL-5 is the main activator and regulator of blood and tissue eosinophil cells14. These cells play a crucial role in the protection against invading pathogens like helminths, virus and bacteria19. Therefore, a passive vaccination with monoclonal antibodies that have a half-life of approximately 3 weeks seems to be a safe treatment option in order to avoid an unpredictable impact on the protective immune response in the long term. Despite successful improvement of the binding activity and inhibition effect due to the in vitro affinity maturation, we observed stability issues with one of the top candidates NOL231-1-A3. Only one amino acid substitution located in the CDR3 region of the VL (Fig. 2a, compared to NOL48-1-D5) caused this difference. The amino acid histidine is replaced by asparagine (H96N), which is a change from a basic amino acid to a polar amino acid. We could not determine a specific reason for the instability caused by this amino acid substitution at this position, but in general it has been reviewed by Rabia et al.42 that mutations that increase the affinity often result in decrease of stability. The lowest affinity/stability trade-off is described for mutations in the CDR3 region of the VH42. This is in line with our second top candidate NOL226-2-D10, which has two amino acid substitutions (A97V and F100L), both located in the CDR3 region of the VH (Fig. 2b, compared to NOL162-1-F5). This antibody shows no signs of instable behavior. Previous studies have put forward the idea that during natural affinity maturation not only somatic hypermutations occur that are improving the affinity but also others that are compensating destabilizing effects43-46. If possible, a co-selection for affinity and stability during in vitro affinity maturation is recommended42,47. In our case, selection of antibodies was performed in scFv format while the final format with stability problems was the eqIgG6 format. Due to the format change at a later time point, when the antibody may have different properties, we recommend to always consider several candidates for the next step during the selection process of a final candidate. Besides addressing IL-5, other targets for treatment of equine IBH with monoclonal antibodies could be conceivable. One alternative target could be the IL-5 receptor alpha subunit which is also addressed by the approved antibody Benralizumab for humans16. Other possible options could be targeting the eosinophil chemoattractant eotaxin-1 to avoid recruitment of eosinophil cells to the allergic site48 or IL-31 to reduce the allergic pruritus49. However, in this work we have focused on IL-5 as target since it is known as main activator and regulator of eosinophil cells and has the advantage of being only little involved in other immunological pathways, thus allowing a rather specific therapy50. Also, monoclonal antibodies against IL-5 in humans have not shown any significant safety concerns16. Eventually, only a clinical trial will provide a full evaluation of the therapeutic benefit of targeting IL-5 with monoclonal antibodies in the horse. Addressing other cytokines or chemokines that are involved in the molecular pathway of equine IBH (e.g. IL-4 and IL-13 for B cell class switch) could lead to a broader less specific immune reaction and a potential therapy against IgE, like Omalizumab for humans, could result in an increased risk for parasite infections. There are many aspects to consider when developing therapeutic antibodies. Important requirements are the safety profile, efficacy, developability and biophysical parameters such as purity, stability, solubility and specificity51,52. During our selection process, we mainly focused on the inhibition effect of the antibody (IC50) and also took the binding activity (EC50) and producibility into account. In addition, the antibody stability and specificity were essential properties. In this regard, the final candidate NOL226-2-D10 features a strong inhibition effect (IC50 = 4 nM, in competitive assay IC50 = 9 nM), a nanomolar binding activity to the target (EC50 = 8.8 nM), satisfactory producibility in the transient expression system (~ 70 mg/L), stable behavior and no indication for unspecificity. The potential of NOL226-2-D10 to inhibit the binding of eqIL-5 to its receptor also in a competitive inhibition assay setup shows that the interaction of eqIL-5 to NOL226-2-D10 is more efficient than to the eqIL-5 receptor, which supports the eligibility of this antibody as candidate for IBH treatment. Regarding the producibility, transient expression in Expi293F suspension cells does not provide a sufficient amount of protein for production of a therapeutic antibody. This can be solved by developing a stable CHO cell line for production53. An alternative solution would be the switch to a different production system in order to receive high yields at low cost. Possible alternative production systems could be based on plants54 or diatoms55, yeast cells56 or insect cells57. In conclusion, we successfully selected a highly promising candidate that meets the commonly approved criteria of therapeutic antibodies regarding inhibition efficacy and stability. Additionally, the use of the eqIgG6 heavy chain could represent a new concept for the development of therapeutic antibodies against allergic diseases in the horse, as this isotype does not interact with the cellular components of the immune system and thus does not further amplify the immune reaction20. This concept will be further evaluated in in vivo studies for the treatment of equine IBH. Methods Design of expression vectors for production in Expi293F suspension cells For eqIL-5 production, the corresponding gene was ordered without the signal peptide but with an 8 x His-tag (Uniprot primary accession eqIL-5: O02699). For eqIL-5-His, the gene was cloned into the pCSE2.7-hFc-XP vector via NcoI/XbaI (NEB). By using XbaI the Fc-part is cut out of the vector. For eqIL5-hFc, the gene without 8 x His-tag was cloned into the pCSE2.7-hFc-XP vector via NcoI/NheI (NEB). For scFv-hFc production, the scFv genes were subcloned into the pCSE2.7-hFc-XP vector via NcoI/NotI (NEB). For production of eqIgG6 antibodies, the backbone vectors were constructed by replacing the constant human domains of the vectors pCSEHh1c-XP (heavy chain) and pCSL3hl-XP/pCSL3hk-XP (light chain lambda/kappa) with equine domains. For this, the genes for IGHC6 (IMGT accession number IMGT000040), IGLC728 and IGKC (IMGT accession number IMGT000053) were ordered and cloned into the human vector pCSEHh1c-XP via BssHII/XbaI (NEB) and into pCSL3hl-XP/pCSL3hk via AgeI/XbaI (NEB) respectively, resulting in the equine vectors pCSEHeq6-XP, pCSLeq7l-XP and pCSLeqk-XP. These vectors were used for the subcloning of VH and VL via Golden Gate Assembly58 with the Esp3I restriction enzyme (NEB) and T4 DNA ligase (NEB). Genes for the expression of eqIL-5 receptor subunits were ordered without signal peptide (Uniprot primary accession Interleukin 5 receptor subunit A: A0A3Q2L5Z7; Uniprot primary accession Colony stimulation factor 2 receptor subunit beta: F7DHE0) and cloned via NcoI/XbaI (NEB) into the expression vector pCSE2.7-hFc-XP. Production of antigens and antibodies in Expi293F suspension cells The antigen eqIL-5 and all antibodies were produced in Expi293F suspension cells (Thermo Fisher Scientific). The cells were cultivated in an incubation shaker (Minitron, Infors, 50 mm shaking stroke) at 37 degC, 110 rpm and 5% CO2 in Gibco FreeStyle F17 expression media (Thermo Fisher Scientific) supplemented with 8 mM L-Glutamine and 0.1% Pluronic F68 (PAN Biotech GmbH). The production scale was adjusted depending on the required protein amount and ranged between 10 and 250 mL (final volume after feeding). For transfection, cell density was between 1.5 x 106 and 2.0 x 106 cells/mL. 1 mg DNA/mL transfection volume and 5 mg 40 kDa PEI MAX (Polysciences)/mL transfection volume were first diluted separately in 5% of transfection volume, then mixed and incubated for 25 min at room temperature (RT) before adding to the cells. After 48 h incubation time, the cell culture volume was doubled by feeding with HyClone SFM4Trans-293 media (GE Healthcare) supplemented with 8 mM L-Glutamine and additionally 10% HyClone CellBoost5 (CN-F) Supplement (GE Healthcare) in relation to the final volume was added. After further five days of incubation, the cells were harvested via two centrifugation steps (first 4 min at 180 x g and 4 degC, then 20 min at 6969 x g and 4 degC). Subsequently, the supernatant was filtered for purification with a pore size of 0.2 mm. Protein purification Proteins were purified depending on the production scale and tag. For His-tag purification, the protein was bound by nickel-loaded Sepharose (GE Healthcare), eluted with 250 mM Imidazole and dialyzed in 1 x PBS. For small scale production (10 mL) of scFv-hFc antibodies, MabSelect SuRe Protein A resin (Cytivia) was used. Buffer changing was done by Zeba Spin Desalting Columns (Thermo Fisher Scientific). For larger scale production of eqIgG6 antibodies, 0.4 mL HiTrap Fibro PrismA (Cytivia), 1 mL HiTrap Protein G HP (Cytivia) and HiPrep 26/10 Desalting (Cytivia) columns were used in the AKTA go (Cytivia), AKTA pure (Cytivia) or Profinia system (Bio-Rad). Here, eqIgG6 antibodies with a VH3 domain could be purified via the HiTrap Fibro PrismA (Cytivia) column, all other eqIgG6 antibodies were purified via the Protein G HP (Cytivia) column. All purifications were performed according to the manufacturers' instructions. SDS-PAGE Protein samples were diluted in 1 x PBS and 5 x Laemmli buffer with or without beta-mercaptoethanol (reducing/non-reducing) and boiled for 5 min at 95 degC (reducing) or 10 min at 56 degC (non-reducing). Then, 1 mg of protein was applied on a 15% SDS-PAGE and run for 1 h at 180 V, followed by staining with Coomassie Brilliant Blue and unstaining with 10% acetic acid. Antibody selection via phage display Antibody selection via phage display was performed as described previously with some modifications26,59. Briefly, for panning in MTP, 2 mg antigen in 1 x PBS was immobilized in one well of a high binding 96-well MTP (Corning) at 4 degC overnight. The next day, wells were blocked for 1 h at RT with 320 mL 2% MPBST (2% (w/v) milk powder in 1 x PBS; 0.05% Tween20) and washed three times with H2O-Tween (H2O; 0.05% Tween20). In the meantime, 1 x 1011 colony forming units (cfu) of the libraries HAL9 (lambda) and HAL10 (kappa) were diluted in blocking solution (1% (w/v) milk powder and 1% (w/v) BSA in 1 x PBS; 0.05% Tween20) and pre-incubated on coated blocking solution for 1 h at RT. The libraries were then transferred into the antigen-coated wells and incubated for 2 h at RT. Next, unbound phage were removed by 10 x stringent washing with H2O-Tween and bound phage were eluted with 150 mL trypsin (10 mg/mL) for 30 min at 37 degC. The eluted phage solution was transferred to a polypropylene 96-deep-well plate (Greiner Bio-One) and incubated with 150 mL E. coli TG1 (OD600nm = 0.5) first for 30 min at 37 degC followed by 30 min at 37 degC and 650 rpm in a MTP shaker (Vortemp 56, Labnet International). Next, 1 mL 2 x YT-GA (1.6% (w/v) tryptone; 1% (w/v) yeast extract; 0.5% (w/v) NaCl (pH 7.0); 100 mM D-Glucose; 100 mg/mL ampicillin) was added and E. coli was cultured for 1 h at 37 degC and 650 rpm. Then, 1 x 1010 cfu M13K07 helper phage was added and the culture was cultivated first for 30 min at 37 degC and then for 30 min at 37 degC and 650 rpm. To exchange the media, cells were centrifuged for 10 min at 3220 x g, the supernatant was discarded and the pellet was resuspended in 2 x YT-AK (1.6% (w/v) tryptone; 1% (w/v) yeast extract; 0.5% (w/v) NaCl (pH 7.0); 100 mg/mL ampicillin; 50 mg/mL kanamycin). Antibody phage were amplified overnight at 30 degC and 650 rpm. The next day, the culture was centrifuged for 10 min at 3220 x g and 50 mL of the supernatant, containing the amplified phage particles, was used for the next panning round. For panning in solution, the antigen was biotinylated using the EZ-Link Sulfo-NHS-LC-Biotin kit (Thermo Fisher Scientific) according to the manufacturer's protocol and dialyzed in 1 x PBS. First, 1 x 1011 cfu of the libraries HAL9 (lambda) and HAL10 (kappa) were diluted in PBST (1 x PBS; 0.05% Tween20) and pre-incubated on coated 2% BSA ((w/v) in 1 x PBS) for 45 min at RT, followed by a second pre-incubation step with magnetic Streptavidin beads (Dynabeads M-280 Streptavidin, Invitrogen) in solution for 45 min rotating at RT. The supernatant containing the phage particles was separated using a magnetic stand and then mixed with 100 ng biotinylated antigen for 2 h under rotating conditions. Bound phage were captured by adding magnetic streptavidin beads for 25 min and then unbound phage were removed by washing the beads 10 x with PBST. From the elution step onwards, the protocol for panning in MTP was continued. For the capture panning, first 2 mg mouse anti human IgG (Fc-specific) antibody (MC002-M, Abcalis GmbH) in 1 x PBS was immobilized in one well of a high binding 96-well MTP (Corning) for 1.5 h at RT. Wells were then blocked with 320 mL MPBST at 4 degC overnight and washed three times with H2O-Tween before adding 1 mg of hFc-tagged antigen in 1 x PBS for 1 h at RT and washing three times again. In the meantime, 1 x 1011 cfu of the libraries HAL9 (lambda) and HAL10 (kappa) were diluted in blocking solution and first pre-incubated on coated human IgG1 Fc-part (hFc) (AG002-hFc, Abcalis GmbH) for 1 h at RT and then pre-incubated on coated mouse anti human IgG (Fc-specific) antibody (MC002-M, Abcalis GmbH) for 1 h at RT. From the panning step onwards, the protocol for panning in MTP was continued. For all three techniques, three or four panning rounds were performed with increasing stringency of the washing step to remove unbound phage (20 x in second panning round, 30 x in third and fourth panning round). The eluted phage after panning round three or four were titrated and single clones were selected for screening of monoclonal binders. Screening of monoclonal recombinant binders using E. coli scFv supernatant Soluble scFvs with a C-terminal Myc-tag and 6 x His-tag were produced in E. coli in polypropylene 96-well MTPs (Greiner Bio-One) as described previously with some modifications59. Briefly, in each well 150 mL 2 x YT-GA media was inoculated with a single clone containing the scFv phagemid. The MTPs were incubated overnight at 37 degC and 800 rpm in a MTP shaker (Vortemp 56, Labnet International). The next day, 160 mL 2 x YT-GA media was inoculated with 10 mL of the overnight culture and incubated for 2 h at 37 degC and 800 rpm to reach an OD600nm ~ 0.5. To induce the production of the scFv antibodies, cells were centrifuged for 10 min at 3220 x g and the pellets were resuspended in 160 mL 2 x YT-A supplemented with 50 mM isopropyl-b-D-thiogalactopyranoside (IPTG) and incubated overnight at 30 degC and 800 rpm. Then, cells were centrifuged for 15 min at 3220 x g and the scFv containing supernatant was used for the screening ELISA. For the screening ELISA, 100 ng/well antigen in 1 x PBS was immobilized in a high binding 96-well MTP (Corning) overnight at 4 degC. As negative control for unspecific binding 1% BSA ((w/v) in 1 x PBS) was used. Wells were blocked with 320 mL 2% MPBST for 1 h at RT and washed three times with H2O-Tween. 40 mL of scFv containing supernatant from E. coli production was mixed with 60 mL 2% MPBST and incubated in the antigen-coated wells for 1.5 h at RT. Bound scFvs were detected using Hypermyc antibody conjugated with horseradish peroxidase (HRP) (AB-Hypermyc-M-HRP, Abcalis GmbH; diluted 1:30,000 in 2% MPBST) which recognizes the C-terminal c-Myc-tag. Bound antibodies were visualized by adding tetramethylbenzidine (TMB) substrate (19 parts TMB solution A (30 mM potassium citrate; 1% (w/v) citric acid (pH 4.1)) and 1 part TMB solution B (10 mM TMB; 10% (v/v) acetone; 90% (v/v) ethanol; 80 mM H2O2 (30%)) were mixed). The reaction was stopped with 1 N H2SO4 and the absorbance was measured at 450 nm with a reference at 620 nm in an ELISA plate reader (Epoch, BioTek). Monoclonal binders with a OD450nm-620 nm > 0.1 and a signal/noise (antigen/BSA) ratio > 5 were sequenced and analyzed using VBASE2 (www.vbase2.org)60. Cellular in vitro inhibition assay Expi293F suspension cells were co-transfected according to the protocol above ("Production of antigens and antibodies in Expi293F suspension cells") with the two receptor subunits in a molar ratio 1:1 and 5% enhanced green fluorescent protein (GFP) plasmid. 48 h after transfection, pre-incubated antigen and antibody were added to 5 x 105 cells/well for 45 min on ice. In the screening, 1000 nM antibody and 5 nM eqIL-5 (related to dimer) were used (molar ratio 200:1). For the titration, 1000 nM-0.32 nM antibody and 5 nM eqIL-5 (related to dimer) were applied (molar ratio 200:1-0.064:1). All dilution and washing steps (centrifugation for 4 min at 280 x g and 4 degC) were performed with FACS buffer (2% FCS and 5 mM EDTA in 1 x PBS). Bound antigen was detected using a Penta-His antibody (3460, Qiagen; diluted 1:50) and a goat anti mouse Fc antibody coupled to APC (115-136-071, Jackson Immuno Research; diluted 1:50). Cells were analyzed in the flow cytometer (MACS Quant, Miltenyi Biotec). The setup of the cellular inhibition assay is visualized in Fig. 4.Figure 4 Setup of cellular in vitro inhibition assay. (a) EqIL-5 binding to eqIL-5 receptor expressing Expi293F suspension cells. The binding is detected via Penta-His antibody and a goat anti mouse Fc antibody coupled to APC. The APC signal represents the 100% binding reference signal. (b) Pre-incubation of antibody and antigen leads to inhibition of eqIL-5 binding to eqIL-5 receptor expressing Expi293 suspension cells. The APC signal is reduced compared to the 100% binding reference depending on the inhibition effect of the antibody. Alive, single and GFP+ cells were gated and their APC median signal was measured (Supplementary Fig. S2). Background signal of the detection antibodies (no eqIL-5 and no test antibody applied) was subtracted from all signals. The binding signal of the interleukin (no test antibody applied) was set as 100% reference (Fig. 4a). Pre-incubation of antigen and tested antibody reduced the APC signal depending on the antibody's inhibition effect (Fig. 4b). Data were analyzed with OriginPro using the Logistic5 Fit. IC50 values were calculated as the antibody concentration necessary to reduce the relative binding to 50%. The antibodies NOL226-2-D10 and NOL162-1-F5 were additionally tested in a competitive cellular in vitro inhibition assay. This assay was performed as described above with the modification that antibody and antigen were not pre-incubated before adding them to the cells. Instead, 1000 nM-0.1 nM antibody was first titrated on 5 x 105 eqIL-5 receptor expressing cells/well. Afterwards, 5 nM eqIL-5 (related to dimer) was applied (molar ratio 200:1-0.02:1) to the cell/antibody mixture for 45 min on ice. Then, the detection was performed as before using the Penta-His antibody (3460, Qiagen; diluted 1:50) and a goat anti mouse Fc antibody coupled to APC (115-136-071, Jackson Immuno Research; diluted 1:50). For selected lead candidates an ELISA was performed to confirm that the APC signal reduction resulted due to the inhibition effect of the antibody and not due to steric hindrance of the anti His detection antibody. For this, 100 ng eqIL-5/well was immobilized in a high binding 96-well MTP (Corning) overnight at 4 degC. Wells were blocked with 2% MPBST for 1 h at RT and washed three times with H2O-Tween. Then, inhibiting antibody was titrated from 316 nM-0.001 nM diluted in 2% MPBST and incubated for 1 h at RT. As positive control Penta-His antibody (3460, Qiagen) was applied. Bound antibodies were detected with an HRP-conjugated anti polyhistidine antibody (A7058, Sigma; diluted 1:50,000 in 2% MPBST). The colorimetric reaction to visualize bound antibodies was performed as described above with TMB substrate and stopped with 1 N H2SO4. Absorbance was measured at 450 nm with a reference at 620 nm in an ELISA plate reader (Epoch, BioTek). Antibodies, that are not blocking the 8 x His-tag, are expected to lead to a constant signal independent of the antibody concentration. Titration ELISA To test binding of equine antibodies to the eqIL-5 antigen, 100 ng eqIL-5/well was immobilized in a high binding 96-well MTP (Corning) overnight at 4 degC. Wells were blocked with 2% MPBST for 1 h at RT and washed three times with H2O-Tween. Then, antibodies were titrated from 316 nM to 0.001 nM diluted in 2% MPBST and incubated for 1 h at RT. Bound antibodies were detected with a goat IgG anti horse IgG (Fc-)HRP antibody (108-035-008, Jackson Immuno Research; diluted 1:1000 in 2% MPBST or SAB3700145, Sigma-Aldrich; diluted 1:5000 in 2% MPBST). The colorimetric reaction to visualize bound antibodies was performed as described above with TMB substrate and stopped with 1 N H2SO4. Absorbance was measured at 450 nm with a reference at 620 nm in an ELISA plate reader (Epoch, BioTek). Data were analyzed with OriginPro using the Logistic5 Fit. The EC50 values, which are defined as the antibody concentration at the half-maximum binding signal, were calculated for the comparison of the antibodies' binding activity. For comparison of NOL46-1-A1 and NOL46-1-E4 as scFv-eqFc and eqIgG, a second ELISA setup was performed to exclude a signal bias due to potential different binding of the detection antibody to the equine Fc-part in the two antibody formats. Here, 240 ng scFv-eqFc/well or 300 ng eqIgG/well of the antibodies NOL46-1-A1 and NOL46-1-E4 was immobilized in a high binding 96-well MTP (Corning) overnight at 4 degC. Wells were blocked with 2% MPBST for 1 h at RT and washed three times with H2O-Tween. Then, eqIL-5 was titrated from 100 nM to 0.001 nM diluted in 2% MPBST and incubated for 1 h at RT. Bound antibodies were detected with an anti polyhistidine-HRP antibody (A7058, Sigma-Aldrich; diluted 1:50,000 in 2% MPBST). Bound antigen was visualized as described above by adding TMB substrate and the reaction was stopped with 1 N H2SO4. The absorbance was measured at 450 nm with a reference at 620 nm in an ELISA plate reader (Epoch, BioTek). Data were analyzed with OriginPro using the Logistic5 Fit. Stability assays Selected antibodies (NOL48-1-D5 and NOL162-1-F5) were tested regarding their stability in titration ELISA, cellular inhibition assay and SEC. A timeline for these assays is shown in Supplementary Fig. S9. For titration ELISA, the antibodies were stored at a concentration of 0.3 mg/mL for 0, 2, 7, 14 and 28 days at 37 degC and for 28 days at 4 degC. The titration ELISA was performed as described above ("Titration ELISA"). For the cellular inhibition assay, antibodies were stored at a concentration of 0.3 mg/mL for 0 and 28 days at 37 degC. A titration assay was performed as described above ("Cellular in vitro inhibition assay"). For SEC, the antibodies were stored at a concentration of 0.3 mg/mL for 0 and 28 days at 37 degC. Samples were diluted with 150 nM sodium phosphate buffer to a concentration of 25 mg/mL and were sterile-filtered with a pore size of 0.2 mm. Measurements were performed with the Chromaster HPLC system (Hitachi) using the AdvanceBio SEC 300A 2.7 mm 4.6 x 300 mm column (Agilent Technologies) according to the manufacturer's instruction. Long-term stability assays The antibody NOL226-2-D10 was tested regarding its long-term stability in titration ELISA, cellular inhibition assay and SEC. Assays were performed as described above ("Stability assays") with a modification of the storage conditions. For titration ELISA and cellular inhibition assay, the antibody was stored at a concentration of 1.86 mg/mL for 0, 2 and 6 months at 4 degC. For SEC, the antibody was stored at a concentration of 1.86 mg/mL for 1 months at 4 degC and for 2 months at 21 degC. Unspecificity ELISA The antigens eqIL-5, 1 x PBS, BSA, DNA, lysozyme, LPS, Expi293F suspension cell lysate and unrelated scFv-His antibody were immobilized in a high binding 96-well MTP (Corning) with 10 mg/mL diluted in 1 x PBS for 3 h at RT and blocked with 2% MPBST overnight at 4 degC. After washing three times with H2O-Tween, 100 nM of the antibodies to be tested was added to the wells and incubated for 1 h at RT. The detection was performed with a goat IgG anti horse IgG (Fc-)HRP antibody (108-035-008, Jackson Immuno Research; diluted 1:1000 in 2% MPBST). The colorimetric reaction to visualize bound antibodies was performed as described above with TMB substrate and stopped with 1 N H2SO4. Absorbance was measured at 450 nm with a reference at 620 nm in an ELISA plate reader (Epoch, BioTek). The background signal, when only antigen and detection antibody were applied, was subtracted for the calculation of the DOD450nm-620 nm. In vitro affinity maturation The in vitro affinity maturation was performed as described previously in detail with some modifications61. Figure 5 illustrates the process.Figure 5 Process of in vitro affinity maturation. Briefly, three consecutive rounds of error prone PCR with the parental scFv gene were performed to insert random nucleotide mutations. For this, the GeneMorphII Random Mutagenesis Kit (Agilent Technologies) was used according to the manufacturer's instructions (in the first round 10 ng phagemid as template DNA, in the second and third round 2 ng PCR product of the previous round as template DNA; 30 PCR cycles). For the library construction, the mutated scFv genes were cloned into the pHAL30 vector via NcoI/NotI (NEB) cloning and electrocompetent E. coli ER2738 cells (Lucigen) were transformed with the library phagemid DNA. The E. coli cells were then used for packaging of the phagemids into phage particles. 2 x YT-GA media was inoculated with E. coli and cells were incubated until OD600 ~ 0.5. Then, 20 mL of the culture was infected with 2.5 x 1011 cfu M13K07 helperphage. After media exchange to 2 x YT-AK, a 50 mL culture was cultivated for 24 h at 30 degC and 210 rpm in an incubation shaker for the phage production. The next day, the phage containing supernatant was separated from the bacteria (30 min, 12,000xg, 4 degC) and phage particles were precipitated with PEG/NaCl (2.5 M NaCl; 20% (w/v) PEG 6000) (20% of final volume) overnight at 4 degC. Next, the phage suspension was centrifuged (1 h, 20,450 x g, 4 degC) and the phage pellet was resuspended in 10 mL phage dilution buffer (PDB) (10 mM Tris-HCl pH 7.5; 20 mM NaCl; 2 mM EDTA) and filtered with a pore size of 0.45 mm. A second precipitation with PEG/NaCl was performed overnight at 4 degC. Then, the phage suspension was centrifuged (30 min, 47,810 x g, 4 degC) and the pellet was resuspended in 1 mL PDB. The suspension was centrifuged again (1 min, 16,000 x g, RT) and the phage containing supernatant stored at 4 degC for further use. With this scFv mutagenesis library an off-rate panning was performed. In contrast to the panning described above ("Antibody selection via phage display"), here only one panning round was performed. 10 ng antigen in 1 x PBS was immobilized in one well of a MaxiSorp 8-well stripe (Thermo Fisher Scientific) at 4 degC overnight. Then, wells were blocked for 1 h at RT with 320 mL 2% MPBST and washed three times with H2O-Tween. In the meantime, 1 x 1010 cfu of the scFv mutagenesis libraries were diluted in blocking solution and first pre-incubated on coated blocking solution for 45 min at RT and then pre-incubated on coated unrelated scFv-His protein for 45 min at RT. The libraries were then transferred into the antigen-coated wells and incubated for 1 h at RT. Next, unbound phage were removed by 30 x stringent washing with H2O-Tween and then stripes were incubated up to 3 weeks at 4 degC in 1 x PBS under stirring conditions. Several washing steps (30 x stringent washing with H2O-Tween) were performed in between and phage were eluted at different time points (5 days, 7 days, 12 days, 14 days and 21 days) using 150 mL trypsin (10 mg/mL)/well for 30 min at 37 degC. Eluted phage were titrated and single clones were selected for screening of monoclonal binders. Screening was performed as described above ("Screening of monoclonal recombinant binders using E. coli scFv supernatant"). Now, the parental scFvs were tested in parallel as reference. Clones with significantly increased signals (> 1.3 x increased compared to the parental scFv signal) were selected and cloned into eqIgG6 format. Supplementary Information Supplementary Figures. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-023-31173-y. Acknowledgements We kindly acknowledge the financial support of K+S AG and the Wirtschaftsgenossenschaft deutscher Tierarzte eG. We thank Wolfgang Grassl for taking care of the SEC measurements. Author contributions The authors T.R., S.F.-W., K.R., W.B., S.L. and M.H. conceptualized the study. N.L., D.S., D.M., M.B. performed and designed the experiments. N.L. and D.S. analyzed the data. M.S., S.D., W.B., S.L. and M.H. advised on the experimental design and data analysis. N.L., D.S., S.L. and M.H. wrote the manuscript. Funding Open Access funding enabled and organized by Projekt DEAL. Data availability The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files. Primary data are available from the corresponding author on reasonable request. 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PMC10000361 | Cell Death Discov Cell Death Discov Cell Death Discovery 2058-7716 Nature Publishing Group UK London 1369 10.1038/s41420-023-01369-2 Review Article Ferroptosis, pyroptosis and necroptosis in acute respiratory distress syndrome Zheng Yongxin Huang Yongbo Xu Yonghao Sang Ling Liu Xiaoqing Li Yimin [email protected] grid.470124.4 Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Diseases, 510120 Guangzhou, China 10 3 2023 10 3 2023 2023 9 9121 9 2022 14 2 2023 14 2 2023 (c) The Author(s) 2023 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Acute respiratory distress syndrome (ARDS) is an acute and uncontrolled pulmonary inflammation caused by various insults. Cell death is a critical mechanism in the pathogenesis of ARDS. Ferroptosis, a novel form of cell death defined as iron-mediated lipid peroxidation, has been shown to play a role in the pathogenesis of ARDS. Additionally, pyroptosis and necroptosis are also involved in the pathophysiological process of ARDS. The crosstalk among ferroptosis, pyroptosis, and necroptosis is getting increasing attention. Therefore, this review will mainly summarize the molecular mechanisms and central pathophysiological role of ferroptosis in ARDS. We will also discuss our understanding of pyroptosis and necroptosis as they pertain to the pathogenesis of ARDS. Furthermore, we also describe the pathological processes that engage crosstalk among ferroptosis, pyroptosis, and necroptosis. We consider that individual pathways of ferroptosis, pyroptosis, and necroptosis are highly interconnected and can compensate for one another to promote cell death. Subject terms Respiratory distress syndrome Cell death National Natural Science Foundation of China (81970071)National Natural Science Foundation of China (81870069)Natural Science Foundation of Guangdong Province, China (2020A1515011459)National Natural Science Foundation of China (82070084)issue-copyright-statement(c) The Author(s) 2023 pmcFacts Ferroptosis is a unique type of cell death characterized by iron-dependent lipid accumulation. Ferroptosis, pyroptosis, and necroptosis are immunogenic forms of cell death, which are associated with uncontrolled inflammatory damage. There is interconnectivity among ferroptosis, pyroptosis, and necroptosis. Targeting ferroptosis holds great potential in treating ARDS. Open questions How does the iron-dependent lipid metabolism execute and distinguish ferroptosis from pyroptosis and necroptosis? What is the specific role of ferroptosis, pyroptosis, and necroptosis in ARDS? What is the cross-regulation among ferroptosis, pyroptosis, and necroptosis in ARDS? How can we target ferroptosis as a potential treatment for ARDS? Introduction Acute respiratory distress syndrome (ARDS) was first defined by Ashbaugh in 1967 in a case-series report . According to the Berlin definition , ARDS is a life-threatening condition that can be caused by both pulmonary (e.g., pneumonia and pulmonary embolism) and nonpulmonary (e.g., sepsis and trauma) insults, leading to hypoxemia, non-hydrostatic pulmonary edema and pulmonary extracellular matrix (ECM) remodeling . ARDS, with high morbidity and mortality rate, accounts for 10% of intensive care unit admissions and affects more than 3,000,000 patients annually worldwide. Besides, according to the US report, there are more than 200,000 cases and 75,000 deaths in the US annually . The pathogenesis of ARDS is believed to involve the accumulation of inflammatory cells, oxidative stress, cell death, and so on . Ferroptosis is a unique form of cell death that was first discovered in 2012 . Unlike apoptosis, autophagy, pyroptosis, and necroptosis, ferroptosis is characterized by the overwhelming, iron-dependent accumulation of lethal lipid reactive oxygen species (ROS) . Numerous studies have demonstrated that ferroptosis plays an important role in ARDS. The ferroptosis inhibitors (e.g., ferrostatin-1 (Fer-1) and lipoxstatin-1) can significantly ameliorate ARDS by decreasing inflammation and oxidative stress by inhibiting ferroptosis . Thus, in this review, we will focus on the molecular regulatory mechanisms of ferroptosis in ARDS, as well as the association of pyroptosis, necroptosis, and ferroptosis with the pathogenesis of ARDS. Ferroptosis, a unique form of cell death Ferroptosis is remarkably distinct from other forms of cell death in terms of morphological, biochemical, and genetic features (Table 1). It is a peroxidation-mediated form of programmed cell death (PCD) that requires abundant and accessible cellular iron. It was unknown until the discovery of ferroptosis inducers . Erastin and RSL3, the first ferroptosis inducers, were discovered by high-throughput screening of small molecule libraries . Erastin and RSL3 treatment triggered cell death with distinct morphological changes and biochemical processes which could not be attenuated or reversed by caspases inhibition, necroptosis inhibitors (e.g., necrostatin-1), or pharmacological inhibition of autophagy (e.g., chloroquine and 3-methyladenine) . However, the cell death induced by Erastin and RSL3 can be reversed by the iron chelators (e.g., deferoxamine mesylate) or antioxidants (e.g., ferrostatin-1 and glutathione (GSH)) which strongly suppress the lipid ROS generation [14-16]. Thus, the type of cell death induced by Erastin and RSL3 may be proposed to be an iron-dependent, ROS-accumulation form of PCD named ferroptosis .Table 1 A comparison of features associated with various types of programmed cell death [16, 121-125]. Type Morphological features Biochemical features Immune features Positive regulators Negative regulators Ferroptosis Cell membrane: plasma membrane blebbing and lacking rupture Cytoplasm: shrunken mitochondria, increased mitochondrial membrane density, disruption of membrane integrity. Nucleus: lack of chromatin condensation and margination. Iron and ROS accumulation. Formation of lipid peroxidation products (e.g., MDA and 4-HNE). GSH depletion. NADPH oxidases (NOXs) are activated and released by the arachidonic acid mediators. Proinflammatory due to the release of DAMPs. Activation of NF-kB and MAPK pathways VDAC2/3 NCOA4 NOXs ALOXs P53 TFR1 FTH1 ACSL4 PTGS2 GPX4 SLC7A11 GSH NRF2 HSPB1 Pyroptosis Cell membrane: cell swelling and plasma membrane blebbing. Cytoplasm: formation of vesicles and inflammasomes. Nucleus: chromatin condensation and nuclear fragmentation. Activation of caspases 1/4/5/11 and GSDMD cleavage. Releasing IL-1b and IL-18. Robust proinflammatory due to release inflammatory factors and DAMPs. Caspases 1/3/4/5/8 PRKN GSDMD IRGB10 TLR7 Necroptosis Cell membrane: cell shrinkage and plasma membrane blebbing. Cytoplasm: cytoplasmic and cytoplasmic organelles swelling. Nucleus: moderate chromatin condensation. Activation of RIPK1, RIPK3, and MLKL and formation of necrosome. Drop in ATP. Releasing DAMPs. Most often proinflammtory due to the release DAMPs. In some cases anti-inflammatory RIPK1, RIPK3 MLKL TNFR1 STUB1 A20 AURKA Protein phosphatase Apoptosis Cell membrane: plasma membrane blebbing and cell shrinkage. Cytoplasm: cleavage of cytoskeletal proteins and collapse of subcellular components. Nucleus: chromatin condensation and nuclear fragmentation. Caspases activation and cleave numerous proteins. Fragmentation of DNA. Often anti-inflammatory and immune silent. In some cases proinflammatory P53 Caspases Bax Bak Fas FasL Bcl-2 Bcl-XL Autophagy Cell membrane: lack of change and may exist the plasma membrane blebbing. Cytoplasm: swelling of cytoplasmic organelles and formation of autophagosomes. Nucleus: nuclear fragmentation and lack of chromatin condensation. LC3-I to LC3-II conversion Substrate (e.g., p62) degradation. Most often anti-inflammatory due to inhibit the inflammasome activation. Proinflammatory due to mediation of secretion of cytokines. ATG5 ATG7 ATG3 Utx Beclin 1 Rala VDAC voltage-dependent anion channel, NCOA4 nuclear receptor coactivator 4, ALOXs arachidonate lipoxygenase, TFR1 transferrin receptor 1, FTH1 ferritin heavy polypeptide 1, ACSL4 acyl-CoA synthetase long-chain family member 4 acyl-CoA synthetase long-chain family member 4, PTGS2 prostaglandin-endoperoxide synthase 2, HSPB1 heat shock protein family B (small) member 1, GPX4 glutathione peroxidase 4, SLC7A11 solute carrier family 7 member 11, GSH glutathione, NRF2 nuclear factor erythroid 2-related factor 2, PRKN parkin RBR E3 ubiquitin protein ligase, GSDMD gasdermin-D, IRGB10 immunity-related GTPase B10, TLR toll-like receptor, RIPK receptor interacting protein kinases, MLKL mixed-lineage kinase domain-like protein, TNFR1 tumor necrosis factor receptor-1, STUB1 STIP1 homology and U-Box containing protein 1, AURKA aurora kinase A, ATG autophagy related, Utx ubiquitously transcribed tetratricopeptide repeat on chromosome X, Rala RAS like Proto-Oncogene A, MDA malondialdehyde, 4-HNE 4-hydroxynonenal. Mechanisms of ferroptosis Ferroptosis is regulated by lipid peroxidation and iron accumulation. Thus, the increased free radical production, fatty acids supply, and lipid peroxidation by dedicated enzymes is critical for ferroptosis (Fig. 1) . Besides, the antioxidant system, including enzymatic and non-enzymatic antioxidants, can stabilize or scavenge free radicals to inhibit ferroptosis.Fig. 1 Molecular mechanism and signaling pathways of ferroptosis. Ferroptosis is driven primarily through two major pathways. The extrinsic or transporter-dependent pathway (e.g., increased iron uptake and decreased cysteine or glutamine uptake), and the intrinsic or enzyme-regulated pathway (e.g., the inhibition of GPX4 or activation of ALOXs in the lipid metabolic pathway). TF transferrin, LTF lactotransferrin, TFRC transferrin receptor, SLC11A2 solute carrier family 11 member 2, FTL ferritin light chain, RNS reactive nitrogen species, DPP4 dipeptidyl peptidase 4, SLC38A1 solute carrier family 38 member 1, SLC1A5 solute carrier family 1 member 5, OXPHOS oxidative phosphorylation, ACL ATP citrate lyase, Ac-CoA acetyl-CoA, AA arachidonic acid, AdA adrenic acid, CoA coenzyme A, ACSL4 acyl-CoA synthetase long-chain family member 4, PE phosphatidylethanolamine, LPCAT3 lysophosphatidylcholine acyltransferase 3, POR cytochrome p450 oxidoreductase, LOOH lipid hydroperoxides, SLC3A2 solute carrier family 3 member 2, GSSG GSH disulfide, GSR glutathione-disulfide reductase, ARE antioxidant response element, HO-1 heme oxygenase-1, DFO deferoxamine, CPX ciclopirox olamine, DPIs diphenyleneiodonium chloride. Oxidant systems Production of free radicals Free radicals, including ROS and reactive nitrogen species (RNS), are oxidants produced by redox reactions, which participate in the oxidation of cellular components and regulate cell death. Compared to the RNS, the functions, and mechanisms of ROS in ferroptosis have been well studied. ROS are byproducts of mitochondrial metabolism and include hydrogen peroxide (H2O2), hydroxyl radicals (OH*), superoxide anion (O2*-), and singlet oxygen (1O2) . ROS can interconvert from one to another by enzymatic and non-enzymatic mechanisms (Fig. 2). ROS are produced by iron-mediated Fenton reaction, NADPH oxidases (NOXs) family, and oxidative phosphorylation (OXPHOS) in mitochondrial. In the electron transport pathway, ROS can be converted to hydrogen peroxide (H2O2) by superoxide dismutase (SOD). Then, cells with high level ferric iron (Fe2+) will initiate the Fenton reaction which will further promote the conversion of H2O2 to high toxic hydroxyl radicals (OH* and O2*-) . The NOXs family participates in a membrane-bound enzyme complex that can transport electrons across the plasma membrane to yield superoxide and other downstream ROS . The production of ROS can promote lipid peroxidation to induce ferroptosis. Additionally, mitochondrial metabolism is also an important source of ROS . An imbalance of the generation and clearance of ROS leads to oxidative stress, which can damage DNA, proteins, and lipids . A full understanding of the ROS regulatory network will help us understand the mechanisms of ferroptosis. However, there is a need to further clarify the interactions and differences among different ROS sources in the regulation of ferroptosis.Fig. 2 The mechanisms and pathways for generating common ROS products. The NADPH oxidases (NOXs) family, Xanthine oxidase, Myeloperoxidase (MPO), and GSH peroxidase are important enzymes that promote ROS production in the cells. Activation of these pathways combined with the abnormal antioxidant mechanisms (e.g., superoxide dismutase (SOD)) will result in oxidative stress and ferroptosis. Fatty acids supply Fatty acids, including polyunsaturated fatty acids (PFUA) and monounsaturated fatty acids (MUFAs), have been shown to play an important role in ferroptosis. Dierge et al. have demonstrated that an excess uptake of PFUAs could lead to ferroptosis of tumor cells, which exhibits an anti-tumor effect. On the other hand, exogenous MUFAs can inhibit ferroptosis by ameliorating the lipid ROS accumulation at the plasma membrane and decreasing levels of phospholipids containing oxidizable PFUAs . In cells, ROS can react with PFUAs of lipid membranes to induce ferroptosis. Lysophosphatidylcholine acyl-transferase 3 (LPCAT3) and acyl-CoA synthetase long-chain family member 4 (ACSL4) have been identified as the critical enzymes to promote the production of PFUA derivatives. Thus, suppression of LPCAT3 and ACSL4 will decrease the oxidative PFUAs in the membrane and inhibit ferroptosis (Fig. 1). Besides, AMP-activated protein kinase (AMPK), as a sensor of cellular energy status, also regulates the ferroptosis by mediating phosphorylation of acetyl-CoA carboxylase (ACC) and PFUAs biosynthesis . However, AMPK also mediates the phosphorylation of beclin 1 to promote ferroptosis . Thus, further studies are needed to clarify the mechanisms of AMPK in regulating ferroptosis. Lipid peroxidation Lipid peroxidation is induced by both enzymatic and non-enzymatic means. The mammalian arachidonate lipoxygenase (ALOX) family, consisting of six members (ALOXE3, ALOX5, ALOX12, ALOX12B, ALOX15, and ALOX15B) , can mediate PUFA peroxidation to produce initial lipid hydroperoxides (LOOH) and subsequent reactive aldehydes, such as malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE). These aldehydes not only damage the DNA and protein but also promote and amplify inflammation . Thus, depletion of ALOXs in cells can prevent ferroptosis induced by Erastin and ameliorate inflammation . Despite the important role of ALOXs in regulating ferroptosis, other non-ALOXs may also be involved in lipid peroxidation. Cytochrome P450 oxidoreductase (POR), a non-ALOXs pathway, can promote PUFA peroxidation by directly supplying electrons to the P450 enzyme (Fig. 1). The two cofactors, flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), combine with POR which can promote auto-oxidation of PUFA to generate ROS . Additionally, prostaglandin-endoperoxide synthase 2 (PTGS2/COX2) also had been considered as a biomarker, not a driver of ferroptosis, which contributes to ferroptosis by indirectly oxidizing lysophospholipids [36-38]. However, it is still unclear whether these oxidases have a similar role in regulating ferroptosis. More research is necessary to understand the role of different oxidases in mediating ferroptosis. Antioxidant systems System GPX4 System an important antioxidant system that inhibits ferroptosis (Fig. 1). It is composed of two core subunits: the light-chain subunit SLC7A11 and the heavy-chain subunit SLC3A2. System an amino acid transporter that imports cystine and exports glutamate in a 1:1 ratio. The imported cystine can be used in the synthesis of GSH. The inhibition of SLC7A11 by small-molecule compounds (e.g., Erastin) or drugs (e.g., Sorafenib and Sulfasalazine) or glutamate will cause GSH depletion to trigger ferroptosis . GSH can regulate the activity of glutathione peroxidase 4 (GPX4) as a powerful antioxidant. GPX4, the key regulator of ferroptosis, can reduce phospholipid hydroperoxide production by reducing GSH to oxidized glutathione (Fig. 1) . Selenium is required by GPX4 to prevent ferroptosis. Active selenol is oxidized by peroxide to selenic acid and finally reduced by GSH to glutathione disulfide (GS-SG) . Some small molecule compounds (e.g., RSL3, ML162, ML210, FIN56, and FINO2) can directly or indirectly induce ferroptosis by inhibiting the activity of GPX4, whereas overexpression of GPX4 can lead to the resistance of ferroptosis [36, 41-44]. Interestingly, emerging studies have revealed that GPX4 can cause other types of cell death, including apoptosis , autophagy , necroptosis , and pyroptosis which means that there is potential interconnectivity between ferroptosis and other PCD. Therefore, it is important to further explore the potential link between cell death and GPX4 in the process of diseases. Moreover, the regulatory mechanisms among the different types of cell deaths warrant further exploration. NRF2 The transcription factor Nuclear factor E2 related factor 2 (NRF2) and its negative regulator, kelch-like ECH-associated protein 1 (Keap1), are critical to defend the oxidative stress and maintain the oxidative steady state (Fig. 1). In mammalian cells, Keap1 functions as the molecular sensor for reactive species. Under basal conditions, Keap1 readily binds with NRF2 and tethers it for ubiquitination and proteasomal, thereby maintaining a low level of NRF2. In the intense oxidative stress response, Keap1 is modified on some specific cysteine moieties which disable its E3 ligase adaptor activity. As the result, NRF2 is stabilized and increased via de novo protein synthesis. When the increased abundance of NRF2 exceeds the Keap1 abundance, NRF2 can be activated by detaching from Keap1 and translocated to the nucleus. In the nucleus, NRF2 will increase transcription of the genes that encode antioxidant proteins (e.g., heme oxygenase-1 (HO-1) and ferritin heavy chain 1 (FTH1)) by binding to the antioxidant response element (ARE) . NRF2 plays a critical role in regulating lipid peroxidation and iron/heme metabolism [50-52]. Genetic or pharmacologic inhibition of NRF2 expression or activity in hepatocellular carcinoma cells (HCC) can promote Erastin or Sorafenib-induced ferroptosis, thereby increasing the antitumor effects . Besides, studies have shown that NRF2/HO-1 pathway can regulate ferroptosis and improve inflammation. The NRF2/HO-1 pathway interacts with SLC7A11 to dramatically attenuate ferroptosis . However, some studies have pointed out that the expression of HO-1 can be upregulated by increased heme, which promotes Erastin-induced ferroptosis, suggesting HO-1 has a dual role in ferroptotic cell death . Programmed cell death in ARDS Ferroptosis in ARDS ARDS is a fatal clinical syndrome characterized by uncontrolled and self-amplifying pulmonary inflammation. ARDS involves damage to alveolar epithelial and endothelial barriers, leading to protein and liquid leakage into the alveoli and interstitium . Oxidative stress has been demonstrated to be associated with the pathogenesis of ARDS. Pathogens can induce the production of ROS to damage the balance between oxidative and antioxidant capacity, resulting in redox imbalance of the local microenvironment and induction of ferroptosis . Ferroptosis can result in the accumulation of immune cells and promote the release of proinflammatory cytokines, which can aggravate lung injury. Thus, ferroptosis is considered as an immunogenic form of cell death . Moreover, inflammation can further promote ferroptosis. Treatment cells with tumor necrosis factor (TNF)-a have been shown to suppress the expression of GPX4 and further promote ferroptosis . Therefore, ferroptosis and inflammation form a self-amplified loop, which further promotes organ damage. Numerous studies have demonstrated that ferroptosis plays an important role in various pathophysiologic models of ARDS. Inhibiting the SLCA11/GPX4/GSH signaling pathway can induce the accumulation of ROS in lung epithelial cells, which causes ferroptosis, as well as the impaired epithelial-endothelial barrier. In sepsis-induced ARDS, treatment of lipopolysaccharide (LPS) can significantly suppress the expression level of GPX4 and SLC7A11, while the level of MDA, 4-HNE, and total iron is strikingly increased. Inhibiting ferroptosis by Fer-1 can reverse these changes and improve inflammatory lung injury . Besides, intestinal ischemia/reperfusion enhanced ferroptosis in lung epithelial cells by inhibiting GPX4, which contributes to the development of ALI . Acute radiation-induced lung injury (RILI) and oleic acid-induced ALI models have also been proven that high levels of ROS-induced oxidative damage to lung tissue. Ferroptosis is a key factor in promoting the development of ALI. However, few studies have been conducted to investigate the potential role of ferroptosis in the pathogenesis of virus-induced ARDS (e.g., influenza and SARS-CoV-2-associated ARDS). Thus, it is urgent to explore the roles and mechanisms of ferroptosis in virus-induced ARDS. Inhibiting ferroptosis has been demonstrated as an effective approach to alleviate pulmonary inflammation and tissue damage in ARDS. NRF2-mediated antioxidant pathway activation can maintain cellular redox homeostasis and reduces oxidative damage . Recent studies have shown that NRF2 could increase the expression level of HO-1 and SLC7A11 and dramatically attenuate ferroptosis in the ischemia/reperfusion-induced ALI (IIR-ALI) model . Furthermore, NRF2 increases the expression of SLC7A11 by regulating STAT3, indicating that NRF2 can inhibit ferroptosis by regulating inflammation . Thus, more work is warranted to fully understand the crosstalk of NRF2 and STAT3 on ferroptosis. Additionally, iASPP, an inhibitor of p53 which is an apoptosis-stimulating protein, could inhibit ferroptosis and provide protection against ALI via the NRF2/HIF-1/TF-signaling pathway. The levels of inflammatory cytokines (TNF-a, interleukin (IL)-6, and IL-1b) were also dramatically reduced by inhibiting ferroptosis . Thus, NRF2 may be a promising therapeutic target for ARDS/ALI. The mechanisms of NRF2 in regulating ferroptosis should be further explored and clarified. Additionally, NRF2 regulates iron metabolism to decrease oxidative stress. Disruption of iron homeostasis and accumulation of iron can cause oxidative stress and tissue damage through ferroptosis . NRF2 could regulate heme-bound iron and a labile iron pool to synthesize heme or iron-sulfur clusters. Activated NRF2 could reduce cytosolic labile iron, restore homeostasis in situations of cellular iron overload and prevent oxidative stress . Thus, NRF2 is expected to protect cells against ferroptosis by regulating iron. The degradation of target genes FTL and FTH1 could promote ferroptosis. However, it remains to be uncovered how NRF2-mediated ferroptosis protects ARDS by regulating iron and how those pathways converge with iron proteins such as FTL or FTH1. In addition to the NRF2 pathway, recent studies have proven that activating the a7 nicotinic acetylcholine receptor (a7nAchR) in lung tissue or blocking mTOR signaling can significantly ameliorate the sepsis-induced ARDS by inhibiting ferroptosis. The expression of GPX4 and SLC7A11 increased and the iron level decreased. Therefore, there may be many undiscovered pathways and mechanisms related to the development of ferroptosis. Future work is needed to explore and clarify the interactions between these pathways and mechanisms in the regulation of ferroptosis. Besides, ferroptosis, as immunogenic cell death, has been demonstrated to regulate the immune response in various diseases, particularly cancer. Currently, the role of ferroptosis in tumor suppression by the immune system has been extensively studied . Immune checkpoint blockade therapy by activating T cells is a highly effective class of anti-cancer therapy. Wang et al. reported that ferroptosis-specific lipid peroxidation in tumor cells was enhanced by immunotherapy-activated CD8+ T cells. This increase of ferroptosis in tumor cells by CD8+ T cells contributes to the anti-tumor efficacy of immunotherapy . Except for T cells, ferroptosis was also associated with the immune activity of macrophages, neutrophils, and B cells [68-70]. The current evidence suggests that the differentiation and activity of immune cells might be governed by lipid peroxidation, and immune cells might participate in regulating ferroptotic inflammation. Additionally, DAMPs released from ferroptotic cells could integrate with pattern recognition receptors (PRRs), such as toll-like receptor 4 (TLR4), which might mediate ferroptosis-related inflammatory responses . Ferroptosis induced by bacterial infection might exacerbate the tissue injury in bacterial (e.g. P. aeruginosa and M. tuberculosis) pneumonia . Moreover, the ferroptotic macrophage might facilitate the spread of M. tuberculosis, which is detrimental to the host. Treatment with Fer-1 could significantly reduce bacterial load . Therefore, ferroptosis has an interaction with immunity, and the activation of ferroptosis is associated with the development of bacterial infection-induced tissue injury. ARDS is also characterized by complex immunological changes, including uncontrolled inflammation and self-amplified injury . However, the ferroptosis-triggered lung and systematic immunological changes in ARDS remain unknown. Given the important role of ferroptosis in immunomodulation, we are looking forward to future studies which explore the role of ferroptosis-induced immunological changes in ARDS. Pyroptosis in ARDS Pyroptosis is a type of cell death characterized by the formation of inflammasomes. Pyroptosis is defined as gasdermin D (GSDMD)-mediated regulated programmed necrotic cell death. GSDMD is a cytosolic protein that contains a specific cleavage site for inflammatory caspases (e.g., caspase 1, caspase 4, caspase 5, and caspase 11) [75-77]. The cleavage of GSDMD by activated caspase 1 results in the formation of a channel in the plasma membrane. Besides, inflammatory caspases cleave pro-IL-1b and pro-IL-18, converting them to the active form (IL-1b and IL-18) . The active form of these cytokines is then released through the channel or access the interstitial space upon pyroptosis execution, leading to the release of DAMPs and proinflammatory cytokines, which recruit the immune cells and amplify the inflammation. Therefore, Pyroptosis is considered as immunogenic cell death (Fig. 3).Fig. 3 Molecular mechanisms of pyroptosis. The mechanisms of pyroptosis are divided into canonical pathways mediated by caspase 1 and noncanonical pathways activated by caspase 4/5/11. LPS lipopolysaccharide, CARD recruitment domain, PRRs pattern recognition receptors, PYD pyrin domain, AIM melanoma, IL interleukin, GSDMD gasdermin D, NETs neutrophil extracellular traps, HMGB1 high-mobility group box 1. Numerous studies have demonstrated that pyroptosis has an important role in ARDS. The cytokines induced by inflammasomes and caspases are critical mediators of ARDS. The pyroptosis of macrophages, endothelial cells, and neutrophils are involved in the development of ARDS. NOD-like receptor protein 3 (NLRP3) inflammasome-mediated macrophage pyroptosis promotes high-mobility group box 1 (HMGB1) secretion . HMGB1 further augments macrophage pyroptosis, amplifies inflammation, and aggravates ARDS . Cellular pyroptosis is an important factor in the progression of COVID-19 to hypoxia and ARDS . Inflammasomes activation releases extensive amounts of proinflammatory cytokines . Furthermore, GSDMD activation in monocytes or neutrophils by inflammasome contributes to coagulation, which may explain the high rate of venous and arterial thrombosis and the high mortality in severe COVID-19 patients . Therefore, pyroptosis and tissue inflammation form a vicious cycle, ultimately leading to excessive inflammation and disease progression. Necroptosis in ARDS Necroptosis is a cell death program driven by the necrosome, resulting in necrotic morphology (Fig. 4). The necrosome is composited by receptor-interacting kinase (RIPK) 1 and RIPK3. During the RIPK1-dependent necroptosis, activated RIPK1 executes autophosphorylation and interacts with RIPK3 via the RIP homotypic interaction motif (RHIM). Upon the formation of the necrosome, RIPK3 can phosphorylate mixed-lineage kinase domain-like pseudokinase (MLKL). Phosphorylated MLKL then translocates to cell membranes and forms a channel, increasing the permeabilization of the cell membrane . Intracellular potents (e.g., HMGB1) are released through the channel and result in inflammation, accumulation of immune cells, and sustained immune response . Thus, necroptosis is also considered immunogenic cell death. Besides, toll-like receptor (TLR)3 and TLR4 activation can also promote the formation of the necrosomes and be involved in the progression of diseases (Fig. 4). Z-DNA-binding protein 1 (ZBP1) is another emerging innate immune sensor of viral Z-RNAs that recruits RIPK3 to activate necroptosis and apoptosis. Thus, the ZBP1 regulates the host defense responses during viral infection by initiating the programmed cell death pathways . Furthermore, previous studies have pointed out that RIPK1 and RIPK3 also have an important role in apoptosis and pyroptosis , making it difficult to identify the type of cell death in diseases.Fig. 4 Molecular mechanisms of necroptosis. Necroptosis can be triggered by the receptors (e.g., TNFR1 and TLR3/4), which promote the assembly of the RIPK1-RIPK3-MLKL signaling complex. The ZBP1 can recognize the cytosolic DNA released from infecting microbes, which will activate RIPK3 and MLKL to lead to necroptosis. TNF tumor necrosis factor, R receptor, TRADD TNF-R-associated death domain, RIPK receptor-interacting kinase, cIAP cellular inhibitor of apoptosis protein, TRAF TNF-R-associated factors, CYLD cylindromatosis, MLKL mixed-lineage kinase domain-like pseudokinase, HMGB1 high-mobility group box 1, TLR toll-like receptor, TRIF TLR domain-containing adaptor-inducing interferon-b, ZBP/DAI Z-DNA-binding protein/DNA-dependent activator of interferon regulatory factors, JNK c-Jun N-terminal kinase, NF-kB nuclear factor kappa-B. Increased evidence has proven that necroptosis plays an important role in the pathogenesis of ARDS. Tamada et al. have demonstrated that necroptosis was the dominant type of cell death in alveolar epithelial in LPS-induced ARDS . Bacterial infection can trigger necroptosis. For example, Staphylococcus aureus (S. aureus) and its toxins can efficiently induce necroptosis in polymorphonuclear leukocytes (PMN) or macrophages. The necroptosis of immune cells impedes bacterial clearance and increased pulmonary inflammation. The inhibition or deletion of RIPK3 and MLKL can improve bacterial pneumonia and prevent localized tissue damage . However, the role of necroptosis in virus-induced ARDS is highly controversial. SARS-CoV-2 infection can induce various inflammatory cytokines such as TNF-a and IFN-g, which is beneficial for clearing the viral infection. Nevertheless, TNF-a and IFN-g co-treatment can induce nitric oxide production and drive RIPK3/MLKL-mediated necroptosis, promoting tissue damage. Blocking the cytokine-mediated necroptosis may benefit COVID-19 patients . Interestingly, in influenza, A virus (IAV) infection, the inhibition of necroptosis in mice failed to control IAV replication and led to lethal respiratory infection . Thus, it is necessary to further identify the specific signaling axis in virus-induced necroptosis and determine the protective or detrimental effects of necroptosis in virus infection. The crosstalk among ferroptosis, pyroptosis, and necroptosis Cell death plays a crucial role in combating infections and is implicated in various diseases. Different cell death pathways are involved in the development of a particular disease. For example, in renal ischemia-reperfusion injury, Zhao et al. have proven that ferroptosis, pyroptosis, and necroptosis are the predominant contributor to acute renal injury. Ferroptosis-related genes were mainly expressed in tubular epithelial cells, while the genes associated with pyroptosis and necroptosis were mainly expressed in macrophages . Therefore, ferroptosis may exacerbate the damage. Inhibiting ferroptosis may be a more effective therapy compared to pyroptosis and necroptosis . Increasing studies have identified the crosstalk of the different cell death pathways (Fig. 5). The interaction between ferroptosis, pyroptosis, and necroptosis is complex and they can operate in synergy to eliminate cells . Several lines of evidence have proven the crosstalk between pyroptosis and necroptosis. Firstly demonstrated that RIPK3 was required for the NLRP3 inflammasome activity and the proIL-1b-associated ubiquitination was markedly increased in a RIPK3-dependent manner . Several genetic experiments have also confirmed that the necroptosis signaling pathway can trigger the RIPK3-MLKL-NLRP3-Caspase-1 axis, leading to IL-1b maturation [101-103] (Fig. 5). Besides, apoptosis, pyroptosis, and necroptosis are interconnected by shared regulatory proteins and signaling pathways to consist of PANoptosis. The PANoptosome was initially shown to contain RIPK1, RIPK3, caspase 8, ASC, and caspase 1. The subsequent study showed that ZBP1 was also a component of PANoptosis, which recognizes the IAV. Then, these PANoptosome complexes promote the activation of downstream cell death receptors, representing apoptosis (caspase 3/6/7), pyroptosis (GSDMD), and necroptosis (MLKL). Thus, these findings highlight the important roles of different cell death pathways and their synergistic operation in eliminating cells which might promote the development of ARDS [104-106].Fig. 5 The crosstalk among pyroptosis, necroptosis, and ferroptosis. Diverse initiator and effector molecules involved in ferroptosis, pyroptosis, and necroptosis are interchangeable to promote cell death. Oxidative stress is a critical mechanism contributing to PCDs. Kang et al. have demonstrated that lipid peroxidation can promote GSDMD-mediated pyroptosis in lethal polymicrobial sepsis. The conditional knockout of GPX4 has been shown to increase activation of the lipid peroxidation-dependent caspase 11 and GSDMD cleavage. Thus, GPX4 might negatively regulate pyroptosis by inhibiting lipid peroxidation, which prevents lethal polymicrobial sepsis in mice . On the other hand, mitochondrial ROS is indispensable for the pathogenesis of ferroptosis and necroptosis. Mitochondrial ROS could promote autophosphorylation of the RIPK1 which recruits RIPK3, forming the functional necrosome (Fig. 5) . The overexpression of GPX4 decreases the levels of mitochondrial ROS, thereby preventing ferroptosis and necroptosis . In addition, knockout of ACSL4 can inhibit ferroptosis in ferroptosis-sensitive murine and human cells, but increase the susceptibility to necroptosis. These studies indicate that there is an interconnectivity between ferroptosis and necroptosis . Moreover, the latest study has indicated that the release of DAMPs from the plasma membrane pore may be a common feature among ferroptosis, pyroptosis, and necroptosis . The release of the DAMPs triggered by ferroptosis may promote pyroptosis and necroptosis. Thus, it is of interest to further explore the crosstalk among pyroptosis, necroptosis, and ferroptosis and clarify the interaction mechanisms in ARDS. Furthermore, it is also interesting to explore the specific DAMPs that can be targeted for preventing PCDs. Treatment of ARDS by targeting ferroptosis As described above, ferroptosis plays a crucial role in the pathogenesis of ARDS, suggesting that there is great potential for the treatment of ARDS by targeting ferroptosis. Iron chelators and antioxidants would be effective treatments for ARDS. Iron chelators are used to remove the excess iron and inhibit the Fenton reaction, which reduces the ROS levels. Deferoxamine (DFO) is the first iron chelator approved by U.S. Food and Drug Administration (FDA) in 1968 . Numerous studies have proven that DFO is effective in treating infection caused by bacteria, fungi, and viruses . DFO can reduce the production of lipid peroxidants (e.g., MDA and 4-HNE) to prevent further damage. Thus, DFO has been hypothesized to have beneficial immunomodulatory and antiviral effects in defense against SARS-CoV-2 infection . Further studies should be conducted to explore the therapeutic potential of DFO in COVID-19. Oxidative stress is another critical mechanism to promote the accumulation of lipid peroxidants, which aggravates lung injury and contributes to the development of ARDS. Fer-1 is a specific inhibitor of ferroptosis that can ameliorate lipid peroxidation. In sepsis-induced ARDS, Fer-1 can improve inflammation and reduce the production of MDA and 4-HNE . Besides, PUFA is an important source of lipid peroxidants. The inhibition of the metabolism of PUFA or knockdown of ACSL4 may be an effective therapy for ARDS . Antioxidants, such as vitamin E and vitamin C, can work synergistically to maintain redox balance and prevent lipid peroxidation. Furthermore, supplementation of exogenous GSH can also effectively ameliorate mitochondrial dysfunction . N-acetylcysteine (NAC), a precursor of GSH, has been demonstrated to decrease the incidence and severity of influenza and influenza-like illnesses . NAC treatment attenuated pulmonary inflammation, pulmonary edema, MPO activity, and inflammatory cytokines (e.g., TNF-a, IL-6, and IL-1b) in mice with IAV-induced ARDS . Interestingly, some studies have pointed out that NAC treatment can prevent the SARS-CoV-2 infection and restore the redox balance . GSH has been proposed as a potential marker for the risk of development to severe COVID-19 and prevent oxidative damage when infection progresses . Two COVID-19-associated ARDS patients were treated with GSH and showed significant improvement in dyspnea and reduction of cytokine storm syndrome . Therefore, iron chelators and antioxidants may be effective therapies for ARDS patients. However, there is a lack of large-scale, high-quality randomized controlled trials of GSH for ARDS treatment. Future studies are needed to provide evidence for the effectiveness of GSH as a novel therapeutic approach for ARDS patients. Conclusion and perspectives The underlying regulatory mechanisms of ferroptosis and its link to diseases have been greatly explored since its discovery. Ferroptosis is a type of PCD characterized by the imbalance of iron metabolism and lipid metabolism. The accumulation of Fe2+ triggers the Fenton reaction to produce free radicals which damage the lipid membrane, resulting in lipid peroxidation. Besides, PUFAs can be oxidated by LPCAT3 and ACSL4 to generate the production of lipid ROS. Although we have understood the initiators, mediators, and regulators of ferroptosis, the ultimate executors of ferroptosis are still unclear . Thus, the complex lipid metabolic network still needs to be further clarified. As described above, ferroptosis, pyroptosis, and necroptosis synergistically promote the development of ARDS (Fig. 6). The crosstalk among ferroptosis, pyroptosis, and necroptosis has received great attention. Lipid peroxidation not only induces ferroptosis but also leads to pyroptosis and necroptosis. Pore formation in the lipid membrane is an important mechanism for pyroptosis and necroptosis, but it is unknown if pore proteins also bind to the lipid membrane to induce ferroptosis. Furthermore, increased evidence demonstrated that there is mutual regulation among ferroptosis, pyroptosis, and necroptosis in diseases, but the regulatory mechanisms remain elusive and warrant further exploration.Fig. 6 Ferroptosis, pyroptosis, and necroptosis are collaboratively involved in the development of ARDS. The cell death releasing the DAMPs (e.g., IL-1b and IL-18) that not only damage the epithelial cells and endothelial cells but also recruit and activate the immune cells to amplify the damage. Loss of epithelial-endothelial barrier integrity is associated with the development of microvascular thrombosis and lung edema. Ferroptosis, as an immunogenic form of cell death, has been extensively studied in ARDS. However, the role of ferroptosis in virus-induced ARDS is yet to be determined. Compelling evidence has proven that ferroptosis inhibitors such as Fer-1 have positive effects in regulating inflammation and improving lung injury. Inhibition of ferroptosis can dramatically decrease the expression level of proinflammatory cytokines. Despite these findings connecting ferroptosis to the immune response in ARDS, the regulatory mechanisms remain unclear. The immunomodulatory effect of ferroptosis inhibitors in ARDS should also be further clarified. Despite the important role of ferroptosis in ARDS, specific markers to evaluate the ferroptosis-mediated immune response are still lacking. Lastly, the current research is limited to cell and animal studies, the clinical trials evaluating the effectiveness of ferroptosis inhibitors are still lacking. Given the important role of ferroptosis in ARDS, we really are looking forward to exploring the therapeutic potential of ferroptosis inhibitors in ARDS patients. Furthermore, due to the presence of multiple types of cell death in ARDS, combined interventions targeting multiple pathways may be a better therapy. Acknowledgements This study was funded by the National Natural Science Foundation of China (81870069, 82070084, 81970071), the Natural Science Foundation of Guangdong Province, China (2020A1515011459), The Science and Technology Program of Guangzhou, China (202102010366). The funding sources had no involvement in the study design; collection, analysis, and interpretation of data; or writing of the report. 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PMC10000362 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050656 healthcare-11-00656 Article Factors Associated with Lack of Health Screening among People with Disabilities Using Andersen's Behavioral Model Kim Ye-Soon Conceptualization Software Validation Formal analysis Investigation Resources Data curation Writing - original draft Writing - review & editing Visualization Supervision Ho Seung Hee Conceptualization Methodology Resources Project administration Funding acquisition * Giansanti Daniele Academic Editor Department of Healthcare and Public Health Research, Rehabilitation Research Institute, Korea National Rehabilitation Center, Seoul 01022, Republic of Korea * Correspondence: [email protected]; Tel.: +82-02-901-1921 23 2 2023 3 2023 11 5 65610 1 2023 20 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 ). People with disabilities often have poorer health than the general population, and many do not participate in preventive care. This study aimed to identify the health screening participation rates of such individuals and investigate why they did not receive preventive medical services based on Andersen's behavioral model, using data from the Survey on Handicapped Persons with Disabilities. The non-participation health screening rate for people with disabilities was 69.1%. Many did not in health screening because they showed no symptoms and were considered healthy, in addition to poor transportation service and economic limitations. The binary logistic regression result indicates that younger age, lower level education, and unmarried as predisposing characteristics; non-economic activity as the enabling resources; and no chronic diseases, severe disability grade, and suicidal ideation as need factor variables were the strongest determinants of non-participation health screening. This indicates that health screening of people with disabilities should be promoted while takings into account the large individual differences in socioeconomic status and disability characteristics. It is particularly necessary to prioritize ways to adjust need factors such as chronic disease and mental health management, rather than focusing on uncontrollable predisposing characteristics and enabling resources among barriers to participation in health screening for people with disabilities. health screening people with disabilities Andersen's behavior model Ministry of Health & Welfare in South Korea2022-2023 MOHW This research was funded by a grant from the Ministry of Health & Welfare in South Korea, grant number 2022-2023 MOHW. pmc1. Introduction Health screening aims to detect and treat diseases at an early stage, thereby reducing the burden of medical expenses and ensuring a healthy life . In Korea, health screening services are divided into national and private health screenings, which differ in terms of screening items and cost burdens. National health screening mainly provides basic and essential health screening items, with little financial burden on individuals. In a private health screening, although various health screening items can be selected according to the individual's characteristics and preferences, the economic burden is high because it is fully borne by the individual . Korea's national health screening aims to detect obesity, dyslipidemia, high blood pressure, and diabetes, which are risk factors for cardiovascular and cerebrovascular diseases, early and improve quality of life through treatment or lifestyle improvement. The Korean national health screening is aimed at checking health conditions and preventing and detecting diseases at an early stage. Health screening consists of examination and consultation, physical examination, diagnostic examination, pathology examination, radiological examination, etc., through health screening institutions . The most representative health screening in Korea is that of the National Health Insurance Service. National health screenings have expanded in subjects and examination items since medical insurance health screening for public servants and teachers began in 1980. The national health screening participation rate in Korea in 2019 was 74.1% . However, the health screening participation rate of people with disabilities was 64.6% . Since the introduction of the national health screening, the increased rate of health screening participation and preparation strategies for health promotion shows its success. However, it was found that the health screening participation rate of people with disabilities was not only low, but this group also suffers from many chronic diseases . Because of this, it is important to determine the cause of this reduced rate and take countermeasures. Although the rate of health screenings for people with disabilities is reported steadily, it is clear that there are deficiencies in implementing national policies and health promotion services for people with disabilities. There are still no general or specialized health screening systems for people with disabilities to detect or prevent secondary diseases at an early stage. Article 7 of the Guarantee of the Right to Health and Medical Accessibility of Persons with Disabilities (Act on the Right to Health of Persons with Disabilities), enacted in December 2015 stipulates the "health screening project for persons with disabilities"; efforts were made at the national level to ensure customized health screening for people with disabilities . Health screening items suitable for characteristics such as gender, sex, and life cycle should be designed. To do so means that it is necessary to identify the influencing factors related to the health screening of people with disabilities. Previous studies related to health screening for people with disabilities have been reported by Park et al. , Yoon , Kim et al. , and the National Rehabilitation Center . According to a study on the health screening rate of people with disabilities, screenings were lower among women with disabilities, those of an older age, and those receiving medical aid; the higher the income, the lower the health screening rate, and there are differences in the health screening participation depending on the type and grade of disability. In particular, it is reported that the screening rate decreases as the degree of disability increase from mild to severe and if the mobility disability is greater. A study in the United States also reported that the higher the degree of disability, the lower the screening rate for diseases such as cervical cancer . In addition, the screening rate of people with disabilities is lower than that of the general population . People with disabilities have the same rights to healthcare as the general population. To improve the health screening participation rate, which is also emphasized in The 5th Policy Plan for people with disabilities in South Korea , it is necessary to identify related factors. For this study's purpose, health screening is also applied as part of medical utilization and Anderson's behavioral model of health service utilization is applied. We looked at the actual health screening participation behavior and tried to predict the factors that caused this behavior. Therefore, in this study, we tried to identify the status of health screening of people with disabilities and the factors affecting health screening by using the disability status survey, which provides sample statistical data for people with disabilities. The findings can help identify factors that affect the health screening of people with disabilities, as well as factors needed to improve the health screening rate. In addition, by identifying and addressing the factors influencing health screening by predisposing characteristics, enabling resources, and need factors, it is possible to grasp the current status of health screening for people with disabilities and re-examine it, providing evidence for follow-up tasks and research in the field of health for people with disabilities. This study aimed to examine the health screening rates of people with disabilities and the characteristics of those who did not undergo health screenings, and identify factors that affect health screening for people with disabilities. The specific research objectives were as follows: first, the sociodemographic characteristics of the people with disabilities were identified. Second, the general health screening rate of people with disabilities and reasons for not taking the examination were identified. Third, the characteristics of the predisposing characteristics, enabling resources, and need factors for general health screenings for people with disabilities and those who did not undergo health screenings were identified. Fourth, factors affecting general health screening of people with disabilities were analyzed. 2. Materials and Methods This analytical study used the 2020 Survey of People with Disabilities, (as secondary data) to identify factors that affect the health screenings for people with disabilities based on Andersen's behavioral model . Andersen's behavioral model is a conceptual model aimed at demonstrating factors that lead to the use of health services. According to the model, usage of health services (including inpatient care, etc.) is determined by three dynamics: predisposing characteristics, enabling resources, and need factors. Predisposing characteristics can be factors such as sex, age, and health beliefs. Need factors represent both perceived and actual need for health care services. The original model was expanded through numerous iterations and its most recent form models past the use of services to end at health outcomes and includes health screening . 2.1. Participants and Analysis Data This study used data from the 2020 Insolvency Survey conducted by the Ministry of Health and Welfare and the Korea Institute for Health and Social Affairs . This is reflected in Korea's Social Welfare Act, which has been renewed every three years since the 2007 legal system. The 2020 Survey on Handicapped Persons with Disabilities comprises data on contact disabilities obtained by surveying 11,210 registered persons across 248 survey areas in Korea. It is representative data that used two-stage cluster sampling considering type, degree of disability, and age of the target disabilities group. A total of 7025 people participated in this survey, of which 365 people under the age of 19 were excluded, and 6660 people were finally analyzed. 2.2. Analysis Variables 2.2.1. Dependent Variable Among the survey items for people with disabilities in 2020, based on the question "Have you had a health screening in the past two years (2018-2020)?" was used . This survey included comprehensive health examinations paid for by the individual, special health examinations at industrial sites (for workers exposed to hazardous substances), health examinations from the National Health Insurance Service (for the workplace or regional subscribers and medical benefit recipients), and free health examinations (including health screening by local governments other than the National Health Insurance Corporation). 2.2.2. Independent Variable Predisposing factors The predisposing factors included sociodemographic variables such as sex and age, and social structural variables such as occupation and education, which the individual already possesses, regardless of his or her will. Education level was divided into elementary school, middle school, high school, and university graduation. Marital status was divided into married (having a spouse) and other categories (single, widowed, divorced, separated, single mother/unmarried father, etc.). Enabling resources Enabling factors satisfy the need for medical services by enabling individuals to use medical services, such as income and medical security benefits. The enabling resources in this study were subjective economic house status, national health insurance, and economic activity. In the case of economic activity, "Did you work for income? "was identified through questions. Need factors Necessary factors are the pursuit of medical service because of the condition of the disease; in this study, the variables were disability type and grade, chronic disease, stress levels in daily life, feelings of sadness or despair, suicidal ideation, and suicide attempt. Concerning disability types, 15 categories were investigated in the survey: physical function disability, disability with a brain lesion, visual impairment, hearing impairment, speech impairment, intellectual disability, autistic disorder, mental disorder, kidney dysfunction, cardiac dysfunction, respiratory dysfunction, liver dysfunction, facial dysfunction, intestinal or urinary fistular, and epilepsy. However, these 15 disability types were adjusted to five considering the proportion: physical function disability, disability with a brain lesion, visual impairment, hearing impairment, and others considering the specific gravity. The ratings for each type of disability ranged from 1 to 6. Grade 1 refers to the most severe disability, while Grade 6 refers to the least severe disability. Usually, grades 1 to 3 represent people with severe disabilities, and grades 4 to 6 represent people with mild disabilities. 2.3. Data Analysis We used SPSS Window 26.0 for data analysis, and the significance level was set at 0.05. The general and disability-related characteristics of people with disabilities were analyzed by frequency, percentage, mean, and standard deviation. The relationship between the predisposing characteristics, enabling resources, and need factors of the participants and the health examination for people with disabilities were verified using a chi-square test. To identify the factors that affect health screenings of people with disabilities, a multiple logistic regression analysis was performed, which included predisposing characteristics, enabling resources, and need factors as independent variables. 3. Results 3.1. General Characteristics Regarding the general characteristics of the participants, 59.1% were male and 40.9% were female, with a male-to-female ratio of 6:4. Regarding age groups, 8.7% were aged 20-39 years, 28.8% were aged 40-59 years, 48.3% were aged 60-79 years, and 14.2% were aged 80 years or older. Regarding education level, 38.9% graduated from elementary school or less, 19.6% graduated from middle school, 36.2% graduated from high school, and 5.3% graduated from college or higher (including junior college). Regarding marital status, 50.7% were married and 49.3% were in "other". Regarding national health insurance, 71% were enrolled in health insurance, 27.1% in medical aid, and 1.8% in others. Regarding subjective house economic status, 70.2% of the participants belonged to "lower level", 28.9% to the middle level, and 0.9% to the upper level, which showed that people with disabilities generally experience economic difficulties. Of the participants, 24.7% said they were engaged in economic activities, and 75.3% were not. Chronic diseases were present in 75.6% of the participants and absent in 24.4%. The disability types were physical function disability (26.6%), brain lesions (11.9%), vision impairment (11.7%), hearing impairment (14.6%), developmental issues (7.6%), and others (language, mental, and height problems; 27.6%). Disability grades were severe (grades 1-3; 49.4%) and mild (grades 4-6; 50.6%). The degree of stress in daily life was slight (14%), moderate (50.5%), and high (35.5%). Of the participants, 19.8%, 12.3%, and 0.7% people experienced sadness or hopelessness, suicidal thoughts, and suicide attempts, respectively; 80.2%, 87.7%, and 99.3% did not experience sadness or hopelessness, suicidal thought, and suicidal attempts, respectively (Table 1). 3.2. Health Screening Participation Rates and Reasons for Not Participation Health Screening It was found that 69.1% of people with disabilities underwent health screening. The main reasons for not undergoing health screening were "lack of symptoms and being considered healthy" (32.9%), "convenience of transportation" (20.4%), "others reasons" (12.4%), "economic reasons" (8.2%), and "lack of time" (6.2%). In addition, there were opinions that responded: "Anxiety regarding health screening results", "difficulty in communication", "insufficient knowledge regarding health screening", "insufficient facilities for people with disabilities in medical institutions", "not having someone for the company when visiting a health screening institution." There were also reasons such as "there is no reason" and "it is difficult to make a reservation for a screening institution" (Table 2). 3.3. Comparison of Factors According to Health Screening Status There were significant differences in health screening rates related to age, education level, marital status, subjective house economic status, chronic diseases, health insurance, economic activity, disability type and grade, depressive symptoms, suicidal ideation, and suicide attempts. Regarding age groups, 60-80-year-old (52.8%) and 40-60-year-old (28.9%) participants showed higher health screening rates than those aged 80 (12.9%) and 20-40 years (5.4%). The age groups reported elsewhere were 20-39, 40-59, 60-79, >=80 years. Elementary school graduates (37.7%) showed higher health screening rates than middle school (20.9%), high school (36.4%), or college (5.1%) graduates. Health screening rates were higher for those with spouses (56.6%) than those without a spouse (43.4%), and the health screening rate was high in the group with low subjective house economic status. Regarding the existence of national health insurance, the health insurance group (75.3%) had a higher health screening rate than those with medical aid (22.8%), and the non-economically active group (70.5%) had a higher screening rate than the economically active group (29.5%). The health screening rate of those with chronic diseases (77%) was higher than that of the group without chronic diseases (23%), classified by disability type [physical disability (29.1%); brain lesion disorder (10.5%); visually impaired disability (12.9%); hearing impairment disability (15.6%)]. The screening rate for mild level (56.7%) was higher than that for severe level (43.3%) of people with disabilities. The health screening participation rate was high for people with disabilities that had relatively good mental health conditions, such as no depression (82.3%), no suicidal ideation (89.7%), and no suicide attempts (99.4%) (Table 3). 3.4. Analysis of Influencing Factors Related to Non-Participating in Health Screening The results of the multi-logistic regression analysis on the nonparticipation of people with disabilities in health screening showed that age, education, marital status, type of medical insurance, economic activity, chronic diseases, degree of disability, and suicidal ideation were statistically significant at a significance level of 0.5 (Table 4). In terms of age, compared to those aged >=80 years, the health screening rate in individuals in their twenties or thirties was approximately 2.1 times (95% CI = 1.4 to 2.9) lower. In terms of education, the probability of participation in health screening was 1.4 times lower for those with a lower education than for those with a higher education degree. The probability of not taking a health screening was approximately 1.3 times higher for people with disabilities without a spouse than for those with a spouse. Compared to national health insurance, the health screening participation rate of the medical aid group was approximately 1.2 times higher among those enrolled in health insurance schemes, and the rate of non-examination was twice as high among those who were not engaged in economic activities. Compared to those with physical disabilities, those with brain lesions and developmental disabilities were 1.6 times more likely to miss a health screening. The rate of non-examination for health screening was 1.4 times higher in cases of both no chronic diseases and severe disabilities. Those with suicidal ideation were 1.3 times more likely to fail health screening. 4. Discussion Research on health screening rates for people with disabilities is often conducted sporadically. In this study, factors affecting the nonparticipation rate in health screening for people with disabilities were classified into predisposing characteristics, enabling resources, and need factors. The study aimed to provide basic data for establishing programs and policies that can improve the rate of health screenings for people with disabilities by analyzing the factors that affect non-participation in health screening for people with disabilities. In this study, the health screening participation rate for adults with disabilities was 69.1%. Similar results were reported by Kim et al. which revealed a 70.2% health screening rate for people with disabilities . In addition, the results of this study were 4.5% higher than the 64.6% health screening rate of people with disabilities in the 2019 health statistics for people with disabilities published by the National Rehabilitation Center , which reflected the results of the national health screening. Because this study included private health screenings in addition to national examinations, the results were higher than those of the National Rehabilitation Center. However, in 2019, the health screening rate for people without disabilities in Korea was 74% . Therefore, the health screening participation rate of people with disabilities which was somewhat lower than that of the people without disabilities. A study in the United States also reported that people with disabilities had lower screening rates than those without disabilities . Few studies have quantitatively and qualitatively identified health screening rates of people with disabilities; therefore, comparison with existing studies is limited, making health screening an urgent task for people with disabilities. The first reason people with disabilities do not participate in health screening is that they have no other symptoms and think they are healthy. The prevalence of chronic diseases with disabilities is reported to be 86.4% . Rather than waiting until the reason for visiting the hospital, it is necessary to detect and treat the disease early in an asymptomatic state and inform them of the need to improve their lifestyle. It has been found that uncomfortable transportation is a major barrier for people with disabilities, leading to non-participation in health screening. The government needs to establish a transportation system by expanding convenient mobility equipment in means of transportation, passenger facilities, and on the roads, and by improving the pedestrian environment, so that people with disabilities may travel safely and conveniently. In addition, a lack of information on health screenings, absence of guardians, and communication difficulties were found to be barriers to participation in health screenings for people with disabilities. For people with disabilities who have difficulty moving, policies such as 'moving health screening service' and 'visiting health screening center' are required for improvement. In this study, the health of people with disabilities was analyzed according to age groups identified in previous studies , subjective economic status, economic activity, and degree of disability . There was a difference in health screening participation rates. Although not significant in this study, there was a sex-based difference in the health screening rates of people with disabilities Compared to men, women with disabilities had a lower health screening rate, meaning that their health is more vulnerable. In addition, a health screening strategy for people with low gross house income and severe disabilities is required. The results of the logistic regression analysis to understand the influence of variables that affect the health screening participation of people with disabilities showed that age group, subjective economic status, economic activity, and degree of disability had a statistically significant effect on the health screening rates. Older age, better subjective economic status, and milder symptoms were found to have a positive effect on the health screening participation rate. On the contrary, health screening rates were low for those with younger age, poor subjective economic status, and severe disabilities. In addition, of non-participation rate in health screening was 1.2 times higher for those without a spouse (unmarried, widowed, divorced, separated, single mother/unmarried father, etc.) than for those with a spouse. This study has some limitations First, the survey data on the actual condition of people with disabilities depended on the participants' responses to the question, "Have you had a health screening in the past two years?" In addition, it was not useful to segment and analyze various types of examinations, such as national general examinations, life transition period examinations, and cancer screening. Therefore, in the future, research identifying related factors with more diverse forms of examinations, such as health screenings during the transition period of life and cancer screenings, are required. Second, because the survey respondents were home-based people with disabilities, there could be limitations in representing all people with disabilities. Third, we cannot rule out that the critical variables of the factors affecting health screenings for people with disabilities are omitted because of the limiting variables. Various important variables, such as chronic disease status, region, and individual private insurance should be included. In this study, to increase the health screening participation rates for people with disabilities, age should be considered as a predisposing factor, economic level as an enabling factor, and severity of disability as a need factor. Based on these results, it is possible to improve the health screening rates of people with disabilities and establish health management and promotion policies to improve the health and happiness of people with disabilities, detect diseases early, and improve and promote current health conditions. Therefore, social and institutional support measures are required. In addition, appropriate rehabilitation services for people with disabilities are also required. 5. Conclusions This study identified the factors affecting the health screening of 6660 people with disabilities aged 20 years or older who responded to the 2020 Survey on People with Disabilities. It is commonly known that people with disabilities have poor access to medical services compared to people without disabilities, considering their poor health and low economic status. Therefore, although the need for preventive medical services, such as health screening, is much higher for people with disabilities, its current provision is lower than that for people without disabilities. This inevitably leads to an increase in medical expenses . Thus, the government requires active planning and design. Recently, the government invited people with disabilities to undergo health screening without any inconvenience, but the response rate was low. In general, for people with disabilities to receive health screening, facilities, equipment, and time must be customized. Accordingly, the government is building customized screening centers for people with disabilities. In addition to providing basic health screening services for people with disabilities through health screening centers, specialized health screening items should be developed and disseminated. Health promotion and disease prevention for people with disabilities can be achieved through the provision of customized health screening services for each life cycle considering the characteristics of people with disabilities, and more active and voluntary participation by the concerned people in the health screening to monitor their health at the national level. Considered that continuous efforts are also necessary to achieve a more suitable screening system for people with disabilities. Acknowledgments This research was supported by the National Rehabilitation Research Institute; a grant from the Ministry of Health & Welfare in South Korea. Author Contributions Conceptualization, S.H.H. and Y.-S.K.; methodology, S.H.H.; software, Y.-S.K.; validation, S.H.H. and Y.-S.K.; formal analysis, Y.-S.K.; investigation, Y.-S.K.; resources, S.H.H. and Y.-S.K.; data curation, S.H.H. and Y.-S.K.; writing--original draft preparation, Y.-S.K.; writing--review and editing, S.H.H. and Y.-S.K.; visualization, Y.-S.K.; supervision, Y.-S.K.; project administration, S.H.H.; funding acquisition, S.H.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study used secondary data and does not applicable for IRB approval. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The database used in this study was provided by the Korea Institute for Health and Social Affairs (KIHASA), and is required by law to be distributed to the public free of charge. Therefore, the researcher accessed the KIHASA data-sharing service page " (accessed on 13 December 2022)" and received data. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Study framework. healthcare-11-00656-t001_Table 1 Table 1 Characteristics of the subject of study (N = 6660). Variables N (%) Sex Male 3935 -59.1 Female 2725 -40.9 Age(years) (mean +- SD) 63.6 +- 15.1 20~39 579 -8.7 40~59 1916 -28.8 60~79 3217 -48.3 >=80~ 948 -14.2 Education Uneducated/Elementary 2315 -38.9 Middle school 1165 -19.6 High school 2155 -36.2 >=College 314 -5.3 Marital status Married 3376 -50.7 Others 3279 -49.3 Subjective house economic status Low level 4676 -70.2 Middle level 1926 -28.9 High level 58 -0.9 National health insurance (NHI) Health insurance 4731 -71 Medical aid 1808 -27.1 others 121 -1.8 Economic activity No 5015 -75.3 Yes 1645 -24.7 Type of disability Physical function disability 1770 -26.6 Disability of brain lesion 791 -11.9 Visual impairment 782 -11.7 Hearing impairment 975 -14.6 Developmental disability 505 -7.6 Others 1837 -27.6 Chronic disease No 1622 -24.4 Yes 5038 -75.6 Grade of disability Severe (1~3 grade) 3290 -49.4 Mild (4~6 grade) 3370 -50.6 Stress recognition Little 935 -14 Moderate 3361 -50.5 High 2364 -35.5 Depressive symptoms No 5343 -80.2 Yes 1317 -19.8 Suicidal ideation No 5840 -87.7 Yes 820 (12.3) Suicidal attempt No 6611 -99.3 Yes 49 -0.7 SD: standard deviation. healthcare-11-00656-t002_Table 2 Table 2 Participation rates and cause of non-participation in health screening experiences. Variables Health Screening Total Yes No N (%) N (%) N (%) Participation rates of untreated experiences Untreated experiences 4599 -69.1 2061 -30.9 6660 -100 Cause of non-participation in health screening experiences Lack of symptoms 678 -32.9 Poor transportation service 421 -20.4 Economic problems 170 -8.2 Lack of time 127 -6.2 Anxiety about the health screening results 90 -4.4 Communication problems 85 -4.1 Lack of knowledge about health screening 81 -3.9 Inadequate facilities for people with disabilities in medical institutions 68 -3.3 No one to accompany during visit 62 -3 Health screening problems 24 -1.2 Other 255 -12.4 healthcare-11-00656-t003_Table 3 Table 3 Comparison of factors according to participation and non-participation in health screening experiences (N = 6660). Variables Health Screening Total Chi-Square Yes No N (%) N (%) N (%) Sex Male 2753 -59.9 1182 -57.4 3935 -59.1 3.709 Female 1846 -40.1 879 -42.6 2725 -40.9 Age (years) (mean+-SD) 20~39 247 -5.4 332 -16.1 579 -8.7 270.85 * 40~59 1329 -28.9 587 -30.6 1916 -28.8 60~79 2430 -52.8 787 -38.2 3217 -48.3 >=80~ 593 -12.9 355 -17.2 948 -14.2 Education Uneducated/Elementary 1530 -37.7 785 -41.6 2315 -38.9 17.359 * Middle school 849 -20.9 316 -16.8 1165 -19.6 High school 1477 -36.4 678 -35.9 2155 -36.2 >=College 207 -5.1 107 -5.7 314 -5.3 Marital status Married 2599 -56.6 777 -37.7 3376 -50.7 202.761 * Others 1995 -43.4 1284 -62.3 3279 -49.3 Subjective house economic status Low level 3091 -67.2 1585 -76.9 4676 -70.2 64.252 * Middle level 1462 -31.8 464 -22.5 1926 -28.9 High level 46 -1 12 -0.6 58 -0.9 National health insurance (NHI) Health insurance 3463 -75.3 1268 -61.5 4731 -71 142.829 * Medical aid 1048 -22.8 760 -36.9 1808 -27.1 Others 88 -1.9 33 -1.6 121 -1.8 Economic activity No 3242 -70.5 1773 -86 5015 -75.3 184.615 * Yes 1357 -29.5 288 -14 1645 -24.7 Type of disability Physical function disability 1338 -29.1 432 -21 1770 -26.6 288,636 * Brain lesion disability 484 -10.5 307 -14.9 791 -11.9 Visually impaired 592 -12.9 190 -9.2 782 -11.7 Hearing impairment 717 -15.6 258 -12.5 975 -14.6 Developmental disability 200 -4.3 305 -14.8 505 -7.6 Others 1268 -27.6 569 -27.6 569 -27.6 Chronic disease Yes 3543 -77 1495 -72.5 5038 -75.6 15.65 * No 1056 -23 566 -27.5 1622 -24.4 Grade of disability Severe (1~3 grade) 1993 -43.3 1297 -62.9 3290 -49.4 218,618 * Mild (3~6 grade) 2606 -56.7 764 -37.1 3370 -50.6 Stress recognition Little 629 -13.7 306 -14.8 935 -14 55.415 * Moderate 2457 -53.4 904 -43.9 3361 -50.5 High 1513 -32.9 851 -41.3 2364 -35.5 Depressive symptom No 3787 -82.3 1556 -75.5 5343 -80.2 42.053 * Yes 812 -17.7 505 -24.5 1317 -19.8 Suicidal ideation No 4124 -89.7 1716 -83.3 5840 -87.7 54.182 * Yes 475 -10.3 345 -16.7 820 -12.3 Suicidal attempt No 4570 -99.4 2041 -99 6611 -99.3 2.25 Yes 29 -0.6 20 -1 49 -0.7 * significantly different, p < 0.05. healthcare-11-00656-t004_Table 4 Table 4 Factors affecting health screening non-participation among people with disabilities (N = 6660). Variables OR + 95% CI ++ Predisposing characteristics Sex Male 1 Female 1.075 (0.948~1.220) Age group 80 above 1 60~79 0.551 (0.491~0.658) 40~59 791 (0.635~0.987) 20~39 * 2.08 (1.491~2.902) Education College or higher 1 High school 1.024 (0.775~1.427) Middle school 1.049 (0.775~1.354) Uneducated/Elementary * 1.409 (1.040~1.908) Marital status Married 1 Others * 1.283 (1.124~1.466) Enabling resources Subjective house economic status High level 1 Middle level * 0.889 (0.427~2.343) Low level 1.131 (0.546~1.851) National Health insurance (NHI) Health insurance 1 Medical aid * 1.226 (1.061~1.417) Economic Yes 1 activity No * 2.078 (1.740~2.482) Need factors Type of disability Physical disability 1 Disability of brain lesion * 1.606 (1.313~1.965) Visual impairment 0.899 (0.723~1.117) Hearing impairment 0.949 (0.779~1.157) Developmental disability * 1.605 (1.222~2.109) Others 1.142 (0.962~1.356) Chronic disease Yes 1 No * 1.401 (1.204~1.630) Grade of disability Mild (4~6 grade) 1 Severe (1~3 grade) * 1.54 (1.353~1.752) Stress recognition Little 1 Moderate * 0.793 (0.664~0.947) High 1.096 (0.906~1.326) Depressive symptom Yes 1 No 1.05 (0.881~1.252) Suicidal ideation No 1 Yes * 1.324 (1.078~1.626) Suicidal attempt No 1 Yes 1.552 (0.802~3.002) * significantly different, p < 0.05. + OR: Odds ratio. ++ CI: Confidence Interval. 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. Cho B.L. Ahn E.M. Present status and problems of health screening program in Korea Health Welfare Policy Forum 2013 198 48 54 2. Yeo J.Y. Jeong H.S. Determinants of health screening and its effects on health behaviors Health Policy Manag. 2012 22 49 64 10.4332/KJHPA.2012.22.1.049 3. Kim Y.S. Lee J.A. National health examination expansion policy J. Korean Med. Assoc. 2017 60 104 107 10.5124/jkma.2017.60.2.104 4. Cho B. Lee C.M. Current situation of national health screening systems in Korea J. Korean Med. Assoc 2011 54 666 669 10.5124/jkma.2011.54.7.666 5. 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PMC10000365 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050821 diagnostics-13-00821 Interesting Images Hypoplastic Left Heart Syndrome: About a Postnatal Death Giugliano Pasquale 1 Ciamarra Paola 2 De Simone Mariavictoria 2 Feola Alessandro 2 Zangani Pierluca 2 Campobasso Carlo Pietro 2 Mansueto Gelsomina 3* Ventura Spagnolo Elvira Academic Editor Baldino Gennaro Academic Editor Mondello Cristina Academic Editor 1 A.O. Sant'Anna e San Sebastiano, 81100 Caserta, Italy 2 Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy 3 Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", 80138 Naples, Italy * Correspondence: [email protected] or [email protected] 21 2 2023 3 2023 13 5 82119 12 2022 14 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 ). Background: Hypoplastic left heart syndrome (HLHS) is a congenital heart disease that is associated with high mortality rates in the early neonatal period and during surgical treatments. This is mainly due to missed prenatal diagnosis, delayed diagnostic suspicion, and consequent unsuccessful therapeutic intervention. Case report: twenty-six hours after birth, a female newborn died of severe respiratory failure. No cardiac abnormalities and no genetic diseases had been evidenced or documented during intrauterine life. The case became of medico-legal concern for the assessment of alleged medical malpractice. Therefore, a forensic autopsy was performed. Results: the macroscopic study of the heart revealed the hypoplasia of the left cardiac cavities with the left ventricle (LV) reduced to a slot and a right ventricular cavity that simulated the presence of a single and unique ventricular chamber. The predominance of the left heart was evident. Conclusions: HLHS is a rare condition that is incompatible with life, with very high mortality from cardiorespiratory insufficiency that occurs soon after birth. The prompt diagnosis of HLHS during pregnancy is crucial in managing the disease with surgery. hypoplastic left heart syndrome respiratory insufficiency shock cardiogenic autopsy This research received no external funding. pmcFigures Figure 1 (a) Cyanosis of the buccal rim. Anterior face (b) and posterior face (c) of the heart. The red arrow points to a small and virtual auricle-like left atrial cavity (b) which is better highlighted by the introduction of a probe (d); the black arrow indicates the emergence cone of the predominant pulmonary trunk which is predominant (b). Evidence of hypoplastic aorta after rotation of the heart towards the posterior face (e). Prevalence of the right ventricle (f): the red arrow indicates a small residual left ventricular cavity with a small residual sept; the red circle is the only identified right valve; the black circle indicates the emergence of the right and left pulmonary vessels above the emergence of the common trunk. Dissection of the right anterior ventricular wall and pulmonary trunk following the outflow route. (Images from Mansueto's forensic archive). The missing intrauterin diagnosis of fetal defects could be the cause of unexpected newborn deaths. HLHS is a syndrome characterized by multiple congenital cardiac structural abnormalities, which was first described by Lev in 1952 . Currently, the mortality rate from HLHS is approximately 2-3% of all congenital heart diseases, with 23% of deaths within the first week and 15% within the first month . Treatment has enabled infants with HLHS to survive beyond the first decade of life, with a reported 15-year survival of 48% and significant mortality during the first year of life . An alteration of cardiogenesis is now clearly identified as the cause of the underdevelopment of the left heart, which is associated in most cases with mitral and ascending aortic anomalies in HLHS. Consistent with multifactorial aetiology and impaired cardiogenesis, HLHS, therefore, represents a syndrome in which the phenotypic spectrum can vary and be more or less faithful to the identified entities. In addition to defective cardiogenesis, left ventricular hypoplasia can also be explained by decreased blood flow during development. Both of these factors can coexist . During intrauterine life, the vascular system of the fetus reaches a functional balance supported by maternal-fetal circulation. The maternal-fetal balance is lost after birth, after the ductus arteriosus and foramen ovale close, resulting in rapid cardiorespiratory failure. Therefore, the early diagnosis of HLHS is essential for timely medical therapy and for the choice of surgical therapy consisting of heart transplantation and/or palliative procedures. We describe a case of HLHS-diagnosed post-mortem. A female newborn at 38 weeks of gestational age (birth weight of 2680 g; an Apgar score of 8/10/10) from a 37-year-old mother (multipara without risk factors or pathologies in the anamnesis) showed respiratory failure twenty-six hours after birth. Due to poor clinical condition (oxygen saturation 44%; metabolic acidosis), she underwent mechanical ventilation, intravenous administration of bicarbonate solution, and the administration of prostaglandins for suspected congenital heart disease. Unfortunately, despite cardiopulmonary resuscitation, cardiogenic shock occurred with death. Since no maternal disease or intrauterine heart defect was diagnosed during pregnancy, the question of a diagnosis with prompt treatment to prevent the fatal outcome was asked. Therefore, an autopsy was performed 5 days after death in accordance with the recommendations on the harmonization of forensic autopsy rules of the Committee of Ministers of the Council of Europe (1999). External examination revealed a female newborn with facies composita without phenotypic traits of genetic syndromes, with cyanotic buccal rim, and with the following growth parameters compatible with 38 weeks of gestational age: (crown-heel length 47 cm (39 +/- 2 w), partial length (head-coccyx) 33.5 cm (37 +/- 3 w), skull circumference 33 cm, chest circumference 31 cm, abdominal circumference 28 cm, foot length 6.5 cm (36 +/- 3), femur length 9 cm (>40 w)). Fetal developmental parameters were oriented for 38 weeks of gestation (brain 320.2 g, thymus 7.8 g, heart 16 g, lungs 39.3 g, spleen 7 g, liver 115 g, kidneys 20 g, adrenal glands 3.4 g, pancreas 2.9 g). Macroscopic observation of the heart showed a prevalence of the right heart with a hypoplastic left heart, which was characterized by left atrium reduction to an auricle-like cavity, LV reduced to a slit, and a right ventricle of increased volume to configure almost a single common ventricular chamber. The pulmonary trunk was clearly evident with the valves, as well as the emergence of the left and right pulmonary arteries. The patency of the foramen ovale, a clearly hypoplastic aorta with coarctation aspects, and a patent ductus arteriosus were also observed. Figure 2 All the organs were macroscopically observed, and samples were taken for each. After formalin fixation and paraffin embedding, sections stained with hematoxylin and eosin were prepared for histological diagnosis . Histology showed multiorgan congestion and lungs in the alveolar-saccular development phase with diffuse congestion with focal aspiration signs (a-f). In (a): congestion and erythrocyte extravasation in hepatic sinusoids (black arrow) (H&Ex10). In (b): congestion and erythrocyte extravasation in the bowel wall (black arrow) H&Ex20). In (c): spleen congestion (black arrow) (H&Ex4). In (d): kidney congestion (black arrow) (H&Ex20). In (e): adrenal gland congestion (black arrow) (H&Ex10). In (f): Lungs diffuse congestion (black arrow) with focal intra-alveolar eosinophilic material due to aspiration (blue arrow) (H&Ex63 magnification). (Images from Mansueto's forensic archive). HLHS is a rare type of congenital heart syndrome. Due to the great number of elective terminations of pregnancy and the spontaneous abortion of affected fetuses, the reported overall incidence is likely underestimated. HLHS is not related to maternal age, ethnicity, or geographical factors. Seven in ten patients are male, and 13.5% of siblings of HLHS patients have some form of congenital heart disease, suggesting a complex relationship with multiple genetic factors . HLHS is a spectrum of cardiac malformations characterized by a hypoplastic left heart system with atresia, stenosis, or hypoplasia of the mitral and/or aortic valves and hypoplasia of the ascending aorta and arch. In addition to the anomalies of the left heart in HLHS, the cardiac atria and extrapericardial aorta are frequently abnormal, thus constituting a very multifaceted problem that is difficult to classify in a single and only phenotype . This problem becomes even greater if we consider the existence of single ventricular cardiac anomalies that are associated with other syndromes and if we consider that, in practice, a reduction in the LV to "slit" is quite rare and can be confusing. In addition, the phenotypic variability becomes more marked if we consider the different degrees to which anomalies can occur. In any case, the left heart is insufficient and fails to sustain systemic cardiac output. Paradoxically, a functional intrauterine diagnosis is easier than an anatomopathological diagnosis if the heart is in the hands of a non-expert. As regards the physiology of the well-being of the newborn with HLHS, in order to maintain adequate systemic and pulmonary circulation, it is necessary that the exchanges between the left and right cardiac systems are open at birth: (1) the patency of the Botallo duct can ensure systemic perfusion from the right ventricle to the aorta; (2) the foramen ovale or an atrial defect can provide adequate mixing of oxygenated and deoxygenated blood. Flow from the right ventricle depends on the relative resistances of the pulmonary and systemic circuits. The newborn with HLHS may have a short asymptomatic period because the arterial duct is non-restrictive and pulmonary arteriolar resistance is relatively high. The clinical conditions can worsen quickly when the ductus arteriosus closes for the physio-logic post-delivery events, and consequentially systemic perfusion decreases while pulmonary blood flow increases. In fact, most deaths from HLHS occur in the first week of life, with the greatest risk on day 3. This short life can be explained by the closure of the arterial duct within the first 72 h of birth in healthy infants. The rapid diagnosis of HLHS at birth with subsequent prostaglandin E1 treatment can avoid cardiogenic shock and respiratory failure. Clinical classification is very important for the correct management of the newborn. The signs commonly seen in the short history of children with HLHS include cyanosis, respiratory distress, cold extremities, and reduced peripheral pulse. Peripheral cyanosis is the most obvious sign of poor blood oxygenation that cannot be resolved simply by administering oxygen. Tachypnea and respiratory distress may also be associated, and heart sounds with a single loud second heart sound reflect the absence of the aortic valve and the presence of pulmonary hypertension . In our case, the newborn showed an apparent initial adaptation to extrauterine life, as evidenced by the normality of the Apgar score. Evidently, the ductus arteriosus was still patent, which ensured both pulmonary and systemic perfusion. After 26 h of birth, heart failure occurred, and the newborn was placed in an incubator with 50% O2. The main effects of this therapeutic treatment were represented by the increase in oxygen saturation by up to 96% but also by the closure of the arterial duct, which worsened the clinical conditions until death. In fact, no patent ductus arteriosus was found during the macroscopic examination of the heart. Currently, prenatal diagnosis of HLHS can be made in approximately 50 to 75% of cases with fetal echocardiography . Classical forms with a severely hypoplastic LV can be detected at 11-14 weeks but more commonly in mid-gestation at 18-22 weeks during the standard fetal anatomy screening ultrasound . A good prenatal diagnosis allows the pregnant woman to be managed optimally in specialized centers and also to evaluate the possibility of the termination of pregnancy and treatment options that include cardiac transplantation, palliative heart surgery, and exclusive palliative care. Therefore, the screening of the first and second trimesters of gestation is very important . A postnatal diagnosis following the closure of ductus arteriosus frequently leads to cardiovascular collapse and poor systemic perfusion, requiring cardiopulmonary resuscitation . Surgical palliative treatments consist of multiple surgical interventions performed in the first few years of life. However, the possibility of surgical treatment raises an ethical dilemma. Palliative care or abortion is reserved for cases associated with other genetic syndromes which do not have a long expectancy of life. Heart transplantation is the least frequent option because of the scarcity of donors in the neonatal period, the long-term immunosuppression of side effects, and the high mortality rate . Primary heart transplantation is usually reserved for HLHS newborns who show a very high risk of undergoing a staged repair . It is evident that the management of the newborn and the mother is very complex from both a medical and ethical point of view, but it is also very important in the context of professional misconduct, and a good autopsy is essential. Author Contributions Conceptualization, G.M. and P.G.; methodology, G.M. and P.G.; software, A.F.; validation, G.M., C.P.C., P.G., A.F. and P.Z.; investigation, P.C. and M.D.S.; resources, P.C. and M.D.S.; data curation, G.M. and P.G.; writing--original draft preparation, G.M., P.C., M.D.S. and P.G.; writing--review and editing, G.M., C.P.C. and P.G.; supervision, G.M.; project administration, G.M. 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 restrictions. 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. Lev M. Pathologic anatomy and interrelationship of hypoplasia of the aortic tract complexes Lab. Investig. 1952 1 61 70 14939725 2. Metcalf M.K. Rychik J. 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PMC10000366 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050977 diagnostics-13-00977 Article A Bimodal Emotion Recognition Approach through the Fusion of Electroencephalography and Facial Sequences Muhammad Farah * Hussain Muhammad Supervision Project administration Aboalsamh Hatim Supervision Weber Frank Academic Editor Antani Sameer Academic Editor Department of Computer Science, College of Computer Science and Information, King Saud University, Riyadh 11451, Saudi Arabia * Correspondence: [email protected] 04 3 2023 3 2023 13 5 97710 12 2022 26 1 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 ). In recent years, human-computer interaction (HCI) systems have become increasingly popular. Some of these systems demand particular approaches for discriminating actual emotions through the use of better multimodal methods. In this work, a deep canonical correlation analysis (DCCA) based multimodal emotion recognition method is presented through the fusion of electroencephalography (EEG) and facial video clips. A two-stage framework is implemented, where the first stage extracts relevant features for emotion recognition using a single modality, while the second stage merges the highly correlated features from the two modalities and performs classification. Convolutional neural network (CNN) based Resnet50 and 1D-CNN (1-Dimensional CNN) have been utilized to extract features from facial video clips and EEG modalities, respectively. A DCCA-based approach was used to fuse highly correlated features, and three basic human emotion categories (happy, neutral, and sad) were classified using the SoftMax classifier. The proposed approach was investigated based on the publicly available datasets called MAHNOB-HCI and DEAP. Experimental results revealed an average accuracy of 93.86% and 91.54% on the MAHNOB-HCI and DEAP datasets, respectively. The competitiveness of the proposed framework and the justification for exclusivity in achieving this accuracy were evaluated by comparison with existing work. bimodal electroencephalography facial video clips emotion recognition CNN feature level fusion Deep CCA HCI Deputyship for Research and Innovation, Ministry of Education in Saudi ArabiaIFK-SURG-2-155 The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project no. (IFK-SURG-2-155). pmc1. Introduction An emotion, a multifaceted mental process, reflects human perceptions and plays a significant part in human interactions . Nowadays, there are many human-computer interaction (HCI) applications that require research on emotion recognition . The environment in the HCI system is complex and dynamic. In many cases, it requires coordinating its operations with the respondents; therefore, a framework with emotional intelligence can better adjust in such an environment. The HCI system will become more human-friendly if it is enabled to recognize human emotions quickly and precisely . EEG signals can actively characterize variations in the human brain during emotional activity, and emotion recognition based on these signals has become a popular trend among researchers. Humans may be unable to express their emotions in some situations, such as when they are hospitalized or have other impairments. For instance, a person with alexithymia is incapable of communicating with others about their emotional state due to emotional blindness. Researchers in the field of neuroscience have looked for a connection between alexithymia and the origins of the two hemispheres as well as deficits in the amygdala . Similarly, bipolar disorder is one of the main causes of disability in the world and is characterized by uncontrollable extreme mood swings from abnormally happy to deeply sad. Depression (also known as major depressive disorder) frequently comes with sleep issues and eating disorders. It may result in suicidal thoughts or behaviors. Depression and bipolar disorder affect three portions of the brain: temporal lobe, prefrontal cortex, and amygdala . Therefore, understanding emotions and discovering alternate means to communicate with such people would be beneficial. Alexa, Cortana, Siri, and other intelligent personal assistants (IPAs) use natural language processing to engage with people. However, when emotion detection is added to IPAs, effective communication and human-level intelligence are increased. Moreover, the automated process of identification of human emotion has become a popular trend among researchers after the development of HCI and Internet of Things (IoT)-based systems for hospitals, smart homes, and smart cities. However, existing HCI systems, in many cases, have irregularities when interacting with humans . To put it another way, the communication content of HCI systems is out of date, and their recognition ability could be improved. Enhancing emotion identification in HCI systems and facilitating quick and dependable computational solutions in these systems are essential for resolving this issue . A better model for emotion recognition is one of the important steps toward the solution. Furthermore, emotions are classified as discrete (happy, sad, or neutral) or dimensional (valence and arousal to describe the emotional scale from calmness to excitement or high/low positivity or negativity) . The literature on emotion recognition techniques is divided into approaches based on physiological and non-physiological signals. Physiological signals, out of both, are comparatively less vulnerable to subjective influences and hence depict the true state of human emotions. Consequently, it may be concluded that physiological signals are useful and reliable in identifying humans' true emotional states. The physiological signals that are widely used to detect human emotions include EEG, electrocardiogram (ECG), eye movements, and others. Several authors have reported good results in recognizing emotions using these signals individually and through the fusion of multiple modalities . Further, out of all physiological signals, the EEG is the most difficult for humans to hide or deceive and contains subject-independent data to represent true human emotions . Several studies have also looked at the substantial relationship between EEG signals and emotional states in humans . Zhang et al. investigated the connection of various human emotional states with different brain regions using EEG signals. Hence, emotion recognition models using EEG signals are more accurate and reliable as compared to other physiological signals. For humans, facial expressions are one of the most important ways to convey emotions. Recognition of facial expression is one of the most prevailing, common, instant, and accurate as compared to other signals. However, facial video clips are easy to manipulate while recording by faking the expressions, resulting in unreliable recognition . Physiological signals, such as EEG, carry instantaneous emotional variations more accurately but are vulnerable to noise obtrusion . Conclusively, emotion recognition methods based on multiple modalities can compensate for the shortcomings of unimodal methods and acquire better and more reliable results . This aspect is more consistent with the requirements of up-to-date HCI systems. It is worth exploring the methods of bimodal emotion recognition that are consistent with modern HCI systems. Additionally, each person can react differently under the same emotional condition, and one person can react differently on different occasions too. It is hard to acquire large enough datasets, and consequently, we must explore approaches for HCI systems based on relatively small datasets . Most facial expression-based emotion recognition systems require facial markers or front-facing images, which results in inefficient systems in terms of robustness . Additionally, just expecting the deep learning model to be effective at facial expression recognition is insufficient in the absence of a precise strategy to exclude extraneous data from the facial video clips, which might decrease the model's effectiveness . Additionally, the majority of EEG-based emotion recognition models have poor performance, which is brought on by some of the EEG data channels that do not contain emotion-related information . Additionally, considering all the EEG data channels in a deep learning model is not recommended when it comes to time complexity . Finally, the handcrafted fusion methods such as enumerator and Adaboost fusion proposed by Li et al. are limited in terms of performance and urge the need to explore deep learning methods to develop highly correlated features space from multiple modalities. To prove the significance of the fusion method, Liu et al. considered deep canonical correlation analysis (DCCA) to fuse the hand-crafted features from EEG, ECG, and Eye movements. However, the performance of the method using a single modality is not reported, and the study considered only hand-crafted features. While managing to keep the necessary information in the facial video clips, we have developed a method to discard the frames in each second that were below a quality threshold. Moreover, this study utilizes a deep learning approach to extract more generalized features instead of hand-crafted features to generate a more robust and accurate model for emotion recognition. This work presents an emotion recognition framework using the fusion of facial video clips and EEG trials to recognize three categories of emotions (happy, sad, and neutral). We have considered distinct convolutional neural network (CNN) models to extract features from facial video clips and EEG trials. After feature extraction, the fusion process is the key to accurate and robust emotion recognition. For that purpose, a DCCA approach was exploited to extract the highly correlated features from facial video clips and EEG feature space. Afterward, these highly correlated fused features were used for classification. In separate experiments, facial video clips and EEG features were also individually used for the classification of emotions. Finally, it was concluded that the feature-level fusion experiment using the features of EEG trials and facial video clips with the proposed fusion method was better than unimodal and other fusion methods. The results were also compared with the state-of-the-art methods in the literature to prove the significance of the proposed method. The existing bimodal emotion recognition methods based on EEG trials and facial video clips are highly complex in terms of computational cost and architecture design . To overcome the issues of these emotion recognition systems, a bimodal emotion recognition method based on the fusion of facial video clips and EEG trials is proposed. The distinctive contributions of the proposed work are summarized as follows:We proposed an efficient and lightweight multimodal emotion recognition model based on two modalities, i.e., EEG trials and facial video clips, by removing irrelevant channels from EEG trials and frames from video clips. In comparison to state-of-the-art approaches, the suggested method's computational overhead is also low. A video clip contains a large number of redundant frames, which increases the computational overhead of a deep learning model. Selecting the most representative frames helps improve the performance of the method. We proposed a technique to reduce unnecessary frames by calculating the difference between successive frames, organizing the difference frames according to their respective information, and choosing the most discriminative frames from video clips. In addition to wasting time and money by utilizing more electrodes, superfluous channels can impair performance by introducing noise and artifacts into the system. Therefore, in this work, the number of EEG channels used for emotion recognition has been reduced, which ultimately allowed us to design a light weight 1D-CNN model with a small number of learnable parameters. To achieve this, we used pooling layers instead of fully connected layers and depth-wise separable convolution to subtly reduce a large number of parameters and make our network structure simpler for low-dimensional data. We adapted ResNet50 for extracting discriminative information from video clips. Following that, DCCA was designed to fuse highly correlated features from the two modalities. In DCCA, the features from EEG and facial video clips are processed through the two 1D-NNs and then forwarded into a canonical correlation analysis (CCA) layer, which consists of two projections and a CCA loss calculator. While minimizing the CCA loss, highly correlated features are extracted that can be used for the classification. The 1D-NN model was specifically designed to transform the features into a better understanding for correlation analysis while keeping the complexity as low as possible. Extensive experiments were performed to validate the proposed method on two benchmark public datasets. The rest of the paper is organized as follows: Section 2 covers related work on EEG, facial video clips, and multimodal-based emotion recognition models. Section 3 proposes data preparation, feature extraction methods using CNN, and fusion methods for classification. Experimental results and discussions are presented in Section 4. Finally, the conclusion and future work are discussed in Section 5. 2. Related Work The traditional methods primarily depended on external sources such as facial expressions, body postures, speech, and others for emotion recognition . These sources do not require a subject to wear a set of sensors for procuring these signals, which makes such methods low-cost and less complex. The authors of used facial expressions to recognize emotions. They executed the NN model to identify valence and arousal simultaneously. In light of the accuracy of the method to recognize emotions, the authors suggested that facial expressions are an effective source of human emotion recognition. Moreover, apart from external sources, internal sources such as EEG, electromyogram (EMG), galvanic skin response (GSR), electrooculogram (EOG), electrocardiogram (ECG), and other physiological signals are also extensively discussed in the literature for emotional recognition . The methods based on physiological signals attain high accuracy in recognizing emotions because these signals can accurately reflect the emotional mood of the subject . According to the different signals discussed, the emotion recognition methods in the literature can be roughly subdivided into three categories: EEG signal-based, facial video clip-based, and multimodal emotion recognition. 2.1. Methods Based on EEG Signals Recently, several investigations have verified the benefits of EEG signals in emotion recognition. In most machine learning problems, researchers' investigations involve analysis of feature extraction, filtration, and classification tasks. In classification tasks, similar to in every other machine learning problem, EEG data-based classification tasks are also divided into supervised and unsupervised learning algorithms . Supervised learning algorithms need labels with the input data to train the model, such as support vector machines (SVM), K-nearest neighbors (KNN), and others. On the contrary, unsupervised learning algorithms do not need predefined labels and evolve clusters from raw input data on their own, such as K-means clustering, self-organizing maps, etc. EEG signals have a high temporal resolution and can demonstrate the association between emotion and brain activity. The equipment used to extract EEG signals is comparatively insubstantial, and the extraction process is also simple . The authors in performed several experiments to fuse graph convolutional neural networks (GCNN) and long-short-term memory (LSTM) neural networks. The model was tested on the DEAP dataset, which resulted in better performance than the existing state-of-the-art methods. The authors in proposed the emotion-dependent critical subnetwork selection algorithm, and the strength, clustering coefficient, and eigenvector centrality of the EEG functional connectivity network features were investigated. The authors in studied a deep, simple recurrent unit network in order to obtain the temporal features from EEG signals, and the experimental results outperformed related work in the literature. It is next to impossible to record a large dataset of EEG signals, but one can explore other methods, such as the cross-subject method. The authors in investigated a unique multisource transfer learning method to detect the emotions of a unique subject using a cross-subject training methodology. This methodology is easy to execute and reduces the need for a large dataset. The authors showed through experimental results that EEG signals can provide useful information about the emotional activity of a person. Anjana et al. converted the time-dependent signal of EEG into scalogram-encoded image data to feed it into a deep-learning model. According to the results, the proposed framework outperformed previous work in the field of emotion recognition using encoded images. Phan et al. presented a unique method to study emotions using EEG signals. The method involved time-domain features mapped into feature-homogeneous matrices. This 3D representation of EEG signals was processed through a 2D-CNN model. The model achieved good accuracy for the valence and arousal binary classification problems. Recently, most of the studies in the literature on EEG-based emotion recognition have relied on deep learning for feature extraction and emotion classification . Moreover, the focus of future research on emotion recognition using EEG is shifting from accuracy to a reduction in complexity . 2.2. Methods Based on Facial Video Clips Facial expressions data are one of the key characteristics for detecting human emotions. Numerous advancements have been made in facial expression detection techniques during the past few years. Formerly, feature mining methods included the integral method, the optical flow method, and several machine learning techniques to categorize the expressions. Recently, researchers have switched to deep learning-based methods, such as GoogleNet, for complex image-processing tasks . Deep learning models are extensively used in feature extraction and classification tasks because of their outstanding properties. Moreover, there is no limit to good performance in terms of classification and feature extraction with every unique deep learning-based model, such as SqueezeNet . A self-cure network was presented in for expression recognition, and the authors used this novel method to avoid overfitting by efficiently suppressing the uncertainties. The authors in proposed the de-expression residue learning method to recognize facial expressions. This model was capable of learning features from the middle layers of the generative model along with the end layers. Jia et al. studied a label/emotion distribution learning method in an expression recognition problem that used local label correlations in order to minimize the confusion regarding an expression's description. Recently, approaches that utilize a smaller number of trials are becoming more popular. The one-shot-only method was studied in to upgrade facial expression recognition accuracy and computational cost. Additionally, the authors in studied an efficient structural embedding methodology to reduce the emotional gap between low-level visual features and high-level semantics. Minaee et al. presented an attentional convolutional network to detect facial expressions. The authors used several datasets of facial expressions to show the significance of the suggested architecture. Moreover, the correlation of various emotions with different regions of the face was also reported in the final findings. In an attempt to prove the importance of different emotion recognition models for standard and non-standard facial expressions, Kuntzler et al. applied three different facial expression recognition systems. The results revealed the significance of the Azure Face API-based expressions recognition system that performed reasonably well in both standard and non-standard emotion recognition. Although deep learning-based models are becoming more popular day by day, hand-crafted feature extraction techniques are still dominant in the literature . Although hand-crafted feature extraction techniques have proven successful in improving the recognition of expressions, those techniques are time-consuming when it comes to emotion recognition from video clips. 2.3. Multimodal Emotion Recognition Methods Over the past few years, multimodal fusion-based approaches have been presented to facilitate accurate emotion recognition. Multimodal fusion methods acquire signals from different sources to recognize emotion after extracting relevant features from all modalities. The reciprocity amongst various signals and the accessibility of multimodal emotion recognition was proved in . text-based multimodality models were investigated in . Zadeh et al. studied the sentiment analysis method using language, visual, and acoustic modalities, and a tensor fusion network was investigated to fuse data from different modalities. Moreover, there have been several studies that combined physiological signals for emotion recognition. For instance, the authors in proposed EEG and peripheral physiological signals recognize emotions, and the results justified the improvement in accuracy using multiple modalities. Zheng et al. studied a unique multimodal method named the Emotion Meter while using eye movement and EEG signals. The authors developed a deep belief network for the recognition of emotions. Val-Calvo et al. assessed the emotional mood of the subjects while interacting with the HRI system by capturing EEG data, facial expressions, blood volume pressure, and galvanic skin response. Rutter et al. investigated the emotion recognition problem in 644 patients while incorporating self-reported depression severity. Authors reported a decline in emotion recognition accuracy with an increasing age factor in a large number of clinically identified adult subjects with emotional disorders, particularly for negative emotions such as sadness and fear. Aguinaga et al. used the facial expression as an identifier to extract features from EEG signals and fused both of them to recognize emotions. The author used several classification methods for comparison and proved the importance of one method over the other methods in the literature in a three-class classification problem. In order to detect hidden emotions, Song and Kim designed CNN models to identify the emotion. To detect hidden emotions, the method used EEG signals as primary data for emotion recognition and compared them to relevant facial data. The method performed reasonably well in detecting hidden emotions, and the fusion of two modalities resulted in an improvement in the accuracy of emotion recognition. Hassouneh et al. developed a real-time multimodal emotion recognition model using EEG and facial data. The approach involved a CNN model and LSTM accompanied by an optical flow algorithm for virtual facial markers to recognize emotions by fusing the features of two modalities. The reported results revealed that the algorithm performed well on the personal dataset. However, the method was not tested on any other publicly available datasets for comparison. While considering the importance of time complexity in feature extraction and model training, Lu et al. improved the VGG-Face network model for facial expressions and the LSTM for EEG data. Moreover, the method involved a decision-level fusion method for a multimodal emotion recognition model. Not only did the proposed method outperform the old LSTM model in a six-class classification problem in terms of emotion recognition accuracy, but it also improved the running time of the emotion recognition model. Zhao and Chen proposed a unique method of multimodal emotion recognition. The method consisted of a bilinear convolution network (BCN) to extract features from facial data, and then EEG data were transformed into three frequency bands to feed them into the BCN model. Further, an LSTM-based fusion model was designed for the fusion of features from the two modalities. The model showed improvement in terms of accuracy compared to other methods in a two-class classification model. EEG-based models show that the performance of the multiple-feature selection procedure is better than the univariate method . Furthermore, the rate of emotion recognition from EEG features extracted with deep learning models was found to be higher than with traditional methods. The methods discussed in the literature confirmed the effectiveness of EEG and facial video clips for emotion recognition. However, EEG data are comparatively sensitive and becomes attenuated due to low-quality electrodes. The subject's facial expressions are insufficient for a fair judgment if the subject's internal emotional state is different from their expressions. Meanwhile, pure external performance is only part of expressing emotion and cannot show the rich emotions of humans. The physiological variations are influenced by the nervous system of the body, which can more accurately depict the emotional mood of the person. Consequently, the fusion of the physiological and non-physiological signals for the recognition of emotion is a unique research trend among researchers around the globe. Facial video clips and EEG signals have been widely studied in a non-physiological and physiological framework and can be efficiently fused for bimodal emotion recognition. Therefore, this collaborative association allows the corresponding information to enhance the objectivity and accuracy of emotion recognition. 3. Materials and Methods In this section, we discuss the datasets, their pre-processing, and the specifics of the proposed methodology. 3.1. Emotions Scherer presented a definition of emotion in 2005, stating that organicistic reactions of the human nervous system to certain events cause emotions in human beings. Moreover, Ekman et al. and Russell resented theories for identifying and categorizing emotional stimuli. Ekman et al. proposed that regardless of the environment and background, certain emotions are inevitable in every human being, namely: happy, anger, sad, fear, disgust, and surprise. Russell presented the circumplex model, which contains levels of activation of emotions, and linked those levels of activation in valence and arousal space with the emotional states of humans. We created a three-class emotional model by combining them: happy (high arousal and valence), sad (low arousal and valence), and neutral (mid-range arousal and valence). In this work, we labeled high valence and arousal with SAM rating >= 5, low arousal and valence with a SAM rating <= 4) and mid-range arousal and valence with SAM rating between 4-5. 3.2. Datasets and Pre-Processing In this work, we executed offline experiments using MAHNOB-HCI and DEAP datasets. 3.2.1. MAHNOB-HCI Dataset The MAHNOB-HCI dataset comprises EEG, video, audio, gaze, and peripheral physiological data of 30 subjects. EEG data were collected using 32 active electrodes on a 10-20 international system with a Biosemi Active II system. Facial video clips of subjects were recorded at 60 frames per second, and the resolution of each original frame was 720 x 580 pixels. The facial video clip data were synchronized with the EEG data with a sampling rate of 256 Hz. To create this dataset, each subject was subjected to watching 20 video clips extracted from Hollywood movies and other sources. The duration of stimulant videos ranged between 35-117 s. After watching each stimulant video, the subject was given self-assessment manikins (SAMs) to rate their judged arousal/valence on a discrete scale between 1-9 . Here, we considered only 27 participants for this experiment. 3.2.2. DEAP Dataset The DEAP dataset contains the EEG, video, and other peripheral physiological data of 32 subjects. These data were recorded while the subjects were asked to watch 40 one-minute music videos. During recording, the resolution of each video frame was set to 720 x 576 pixels at 50 frames per second. Further, this dataset includes ratings from each subject for each stimulus in terms of levels of arousal/valence. Note that we used only 22 participants for whom both the facial video clips and EEG data were available for all 40 trials. 3.2.3. Data Pre-Processing and Augmentation In video data containing facial video clips and video sequences that included undesirable backgrounds, we performed some pre-processing steps to remove the undesirable background. Further, the face of the participant in the videos was not centered, which could pose a problem in extracting useful facial features. Therefore, the participant's face was centered by applying the combined processes of cropping and brightness adjustment in each video. Additionally, the height x width of video sequences was adjusted to 224 x 224 pixels in order to make them conform to our designed CNN model. Originally, the data containing facial video clips consisted of frames with redundant data. Therefore, before giving the data to the CNN model for feature extraction, it is necessary to discard such frames that contain redundant data. We can reduce not only the dimensions of the input data but also extract the frames containing meaningful data for emotion recognition in this manner. For that purpose, for T total frames, we performed a difference operation between every two consecutive frames, which resulted in T - 1 difference frames containing zeros where the data matched and non-zero where it was unmatched. Then, for each difference frame (dt), we calculated the average value (mt) by using the following Equation (1):(1) mt= x=0My=0Ndtx,yMxN, where dt (x, y) denotes the pixel value of the tth difference frame, M and N denote the length and width of the frame under consideration, respectively. Afterward, the average values are sorted in descending order to obtain the difference frames with the highest average values. This whole process is depicted in Figure 1. As the value of mt decreases, the meaningful information in the particular frame also decreases. After running multiple experiments, only 40% of the frames per second were considered adequate for emotion recognition, which helped to preserve meaningful information, and the rest were discarded. This entire process contributed to the reduction of 60% of redundant information. For the DEAP dataset, EEG data were preprocessed at 128 Hz. However, for the MAHNOB-HCI dataset, the EEG data were preprocessed by applying a bandpass filter on the EEG data to keep the band 4-45 Hz; this helped reduce the artifacts of utility frequency and eye gazing. Head-moving noise was removed by spatial filtering using independent component analysis (ICA). Several studies in the literature have proved the importance of the frontal and temporal lobes on emotion recognition using EEG data . However, most of the researchers have considered up to 62 electrodes for emotion recognition using EEG . Apart from the unnecessary time and costs of using more electrodes, the extraneous channels can cause noise and artifacts in the systems, which ultimately affect the performance. Therefore, there is a rising trend among researchers to look for alternative ways of using a smaller number of electrodes to extract EEG signals for emotion recognition . In this work, we used five pairs from the frontal and temporal lobes which helped in better recognition of emotion . Selected pairs of electrodes are: FP1, FP2, AF3, AF4, F3, F4, F7, F8, T7, and T8. It also aids in reducing the dimension of the input data as well as the computational complexity. For each trail, we considered 60 s of facial video clips and EEG data in this experiment. For training the CNN, the amount of data required to achieve respectable accuracy was not adequate. To proliferate the data, a window of 5 s was applied, which resulted in 12 samples from each trail of 60 s. 3.3. Proposed Method In the proposed method, the CNN architecture was chosen for feature extraction and emotion recognition tasks. The method consists of two distinct models for different tasks. The first CNN model is designed to extract features from EEG data, while the second CNN model is used for feature extraction from facial video clips. Once the features are extracted, feature-level fusion is introduced with the help of DCCA, and highly correlated features are fed to the SoftMax layer for classification. The proposed model is depicted in Figure 2. 3.3.1. CNN Model for EEG Some of the common CNN-based deep learning models usually contain a fully connected (FC) layer at the end for feature extraction, and the FC layer comprises a large number of parameters. For instance, VGG Net consists of FC layers at the end of its architecture, which make up around 90% of their parameters. The VGG16 succeeded in improving performance due to the increased depth of the network. Moreover, the improvement of VGG16 over the other models was also due to the use of convolution kernels of size 3 instead of larger convolution kernels. When compared to large convolution kernels, several layers of small convolution kernels perform better because the depth of the network increases due to several nonlinear layers, and it creates more complex patterns in the learning process without increasing the number of parameters. However, VGG Net uses more computing resources and contains a number of parameters, which leads to more memory usage. The first layer of this architecture makes the most of the parameters. Therefore, we performed several experiments to find a suitable lightweight 1D-CNN architecture without compromising accuracy. A 1D-CNN model is proposed for EEG data. After the input layer of EEG data, we used a temporary layer to convert the data into 1D to be used for the 1D-CNN model. As depicted in Figure 3, Layer 1 is composed of BN (batch normalization) and Conv1D. BN is known for normalizing the output from the previous layer in a CNN model in modern neural networks and for regularizing the data to avoid overfitting. After normalizing the 1D EEG data, the first convolutional layer (Conv1D), with 1 x 3 sized 64 kernels and stride 1, is applied to the normalized data to obtain features. Further, a rectified linear unit (ReLU) activation layer is implemented after the Conv1D layer to activate nonlinearity. The combined mathematical effect of the Conv1D and the ReLU can be defined as follows:(2) xjk=s(i=1Nk-1Conv1Dwi,jk,xik-1+bjk), where the features maps from previous (k - 1)th layer is denoted by xik-1; the resulting kth layer's jth feature map is represented as xjk; while wi,jk symbolizes the convolutional kernel; total number of feature maps in the preceding(k - 1)th layer is represented by Nk-1; Conv1D denotes the convolutional operation without zero padding; the bias for the kth layer and jth feature map is symbolized as bjk; the ReLU activation function is signified as s(). ReLU is defined as follows:(3) sx=0, x <= 0x, x>0, The features obtained from the Conv1D layer are processed through Layer 2. Except for MaxPooling1D, Layer 2 is similar to Layer 1 in terms of processing complexity. In Maxpooling1D, the mathematical calculations are defined as follows:(4) rjn=max(rjn':n <= n'<n+s), where the n'th neuron in the jth feature map without the max-pooling process is denoted by rjn'; resultant nth neuron in the jth feature map, after the max-pooling process, is denoted by rjn, and the size of the pooling window is represented by s. In this Maxpooling1D, s is equal to 2 with stride 2. In the proposed model, the max-pooling process causes the number of trainable parameters to reduce meaningfully, resulting in accelerating the training process. Maxpooling1D is followed by Layer 3, which is similar to the previous layer, but only the convolutional kernels in the Conv1D are set to 32. After the feature maps pass through Layer 3, the obtained feature map is fed to the dropout (0.5) layer to avoid overfitting. Finally, the FC layer is fed with the output feature maps from the preceding layer. A grid search approach was utilized to find the optimal hyperparameters. The grid search involved several hyperparameters that are listed in Table 1 with their corresponding ranges and the chosen optimal values for the architecture. We tested the influence of these parameters on the performance of the recognition accuracy and chose the parameters that helped in achieving the best accuracy. The final experimental configurations for the investigation of the EEG data in this work are as follows: the learning rate is set to 0.001, the maximum number of iterations is limited to 40, the ReLU function is used for each hidden layer, the SoftMax output is used for classification, and validation is performed through leave one subject out. The data split for training, testing, and validation was performed such that, from the data of N subjects, (N - 1) subjects*Number of trails for each subject for training (90% training set, 10% validation) and 1 subject*Number of trails for each subject for testing. Moreover, the regulation parameter was set to be 1e5, cross-entropy loss, and a stochastic gradient descent optimizer. Further, we selected 15 optimization steps based on the validation set as early stopping criteria, Xavier initializer as weight initializer, and the bias vector initialized to all zeros. 3.3.2. CNN Model for Facial Video Clips The CNN architectures are verified and very well known for image recognition in the world of researchers because of their ability to extract discriminative features for better classification . ResNet outperforms all other CNN architectures in classification by increasing the depth of the network to generate features with more relevant characteristics. In this work, ResNet50 is used to extract features from facial video clips for an emotion recognition task. Figure 4 depicts the structure of the proposed CNN model with the ResNet50 network. For feature extraction, an input layer provides sequences of facial data to CNN after preprocessing. A dimension reduction layer is added before feeding the input to Resnet50 so that the shape of the input data is transformed to 224 x 224 x 3. We removed the final FC layer of ResNet50 and replaced it with one dropout layer (0.5) and a SoftMax output layer of three emotion classes. We used stochastic gradient descent as an optimizer with a learning rate of 0.001 and a batch size of 32. Further, we replaced the average pooling layer before the FC layer in ResNet50 with the max-pooling layer to subsample the input to reduce its size, which helps decrease the calculations performed in subsequent layers. 3.3.3. Feature Level Fusion Using DCCA In this work, we used deep canonical correlation analysis (DCCA) to fuse highly correlated features from EEG and facial video clips. Initially, DCCA was presented by Andrew et al. to compute representations of several modalities by processing them through multiple stacked layers of nonlinear transformations. Figure 5 depicts the architecture of DCCA used in this work. We applied a grid search approach to find optimal hyperparameters for designing the deep learning model to be used in the DCCA method. After a series of time-consuming experiments, we selected the regulation parameter to be 1e5, cross-entropy loss, and a stochastic gradient descent optimizer. Further, we selected 15 optimization steps based on the validation set as early stopping criteria, Xavier initializer as weight initializer, and the bias vector initialized to all zeros. Moreover, Table 2 presents the tunable hyperparameters and the corresponding ranges that have been considered during the grid search approach to find the optimal values. We tested the influence of these parameters on the performance of the recognition accuracy and chose the parameters that helped in achieving the best accuracy. The 1D model is developed using CNN architecture to improve the DCCA. The model comprises an input layer, three convolutional layers, each attached with a max-pooling layer, followed by one dropout layer, and finally, a SoftMax layer. The convolutional layers are developed using 128, 256 and 512 convolution kernels with kernel sizes of 3 x 1, 5 x 1, and 3 x 1 and stride of 1 in each layer, respectively. The non-linear function ReLU is used as an activation function. Each max-pooling layer is designed with a pool size of 2 and a stride of 2. The dropout layer is designed with parameter 0.4. In this work, DCCA is used for feature transformation, and then, the transformed features are fused together to apply classification. The DCCA model is shown in Figure 5, in which we applied a deep learning model for feature transformation, where the CCA layer calculates the correlation, and we use that correlation for feature fusion and classification. Let the matrix I1RMxn1 contain trials of the EEG modality, and matrix I2RMxn2 contains trials of the facial video clip modality. Here, the total number of trials is denoted by M, and the dimensions of features in the EEG trials and facial video clips are represented by n1 and n2, respectively. To reorganize the input features in a non-linear manner, we designed a deep neural network for each modality as follows:(5) O1=f1I1; H1O2=f2I2; H2, where parameters of the nonlinear transformation are denoted as H1 and H2; the resulting features from each neural network are denoted as O1RMxn and O2RMxn and the dimension of features from DCCA is denoted as n. Mutually learned parameters H1 and H2, resulting from DCCA, have elevated the correlation between O1 and O2 as high as possible:(6) H1*,H2*=argmaxH1, H2corrf1I1; H1, f2I2; H2, Mutually learned parameters H1 and H2 were updated using the backpropagation algorithm. The gradients of the objective function were calculated as suggested by Andrew et al. to reach the desired solution. After the training of the two neural networks, the transformed features O1 and O2 S are in the joint hyperspace S. Primarily in DCCA , the authors did not clearly report the usage of transformed features. The user is free to opt for an approach to make use of the transformed features in the best interest of their application. In this work, we obtained fused features from transformed features as follows:(7) O=aO1+bO2, where a and b symbolize weights sustaining a+b=1. The features O combined through DCCA are fed to the SoftMax classifier. The classifier is trained to perform emotion recognition tasks. As previously mentioned, there are several advantages to designing DCCA for data fusion from multiple modalities. For instance, at feature-level fusion, DCCA obtains O1 and O2 explicitly for each modality to observe the characteristics and correlation of modality-centric transformations. Moreover, the nonlinear mapping functions f1(*) and f2(*) can be controlled to preserve emotion-centric information. Further, in the weighted sum fusion, we are using equal weights for both modalities. 3.3.4. Baseline Fusion Methods We considered several feature-level fusion methods to fuse the features of EEG trials and facial video clips and applied the classification to ensure the validity and competitiveness of the proposed DCCA-based fusion method for emotion recognition. The comparison shows the importance of the DCCA-based fusion approach over other fusion methods. The fusion methods considered for comparison are discussed below. (1) Simple Concatenation Fusion : It is a feature-level fusion method. First of all, the feature vectors from each modality are normalized to zero mean and unit variance. Then, the features are combined. For instance, I1 = u1,...,ukRk and I2 = v1,...,vlRl denote the feature vectors from each modality, and the combined features can be calculated as follows:(8) O=u1,...,uk,v1,...,vl, (2) Multiple kernel learning (MKL) : MKL is widespread for its capability of instantly learning kernels and can be utilized for feature-level fusion. For the MKL problem, a suitable method is to consider that K (x1, x2) is actually a convex combination of basis kernels:(9) Kx1,x2=n=1NwnKnx1,x2, where N denotes the total number of kernels, wn >= 0 and n=1N wn=1. (3) MAX Fusion : It determines the resultant class by choosing the class with the highest probability. Therefore, it is a decision-level fusion method. Suppose that there are U classifiers and V classes; the probability distribution for each trial can be defined as Pjyi|xt where j1,...,U and i1,...,V, xt denotes a trial, yi signifies the resultant class label, and Pjyi|xt symbolizes the probability of trial xt of ith class resulting from jth classifier. The mathematical formula of MAX fusion can be defined as follows:(10) Y^=argmaxi{maxjPjyi|xt}, (4) Fuzzy Integral Fusion : It is a decision-level fusion technique. Let a fuzzy measure l on the set X is a function: l : PX-0, 1, which ensures the following the two axioms: (1) l () = 0 and (2) A B X indicates l(A) <= l(B). In this work, we considered the discrete Choquet integral to join the features of the two modalities. The discrete Choquet integral of a function h : X - R+ with respect to l is defined by (11) gh=i=1nhxi-hxi-1lAi, where subscript i specifies that indices are permuted as 0 <=hx1 <= <=hxn, Ai=xi,...,xn, and hxo=0. In this work, we utilize the algorithm suggested by Tanaka and Sugeno to calculate the l. This algorithm helps in minimizing the squared error of the model by calculating l. Tanaka and Sugeno also presented that the minimization problem can be resolved through a quadratic programming technique. (5) Adaptive Fusion : It is a decision rule-based fusion method. The fusion method is accompanied by a deep learning model, as suggested in . Finally, the decision is made using the following equation:(12) y=yF+1+yE-0.4100yE if yE>0.4yE+yF2otherwise where yF denotes facial modality and yE denotes EEG modality. If the value of yE is greater than 0.4, EEG modality is given more weight; otherwise, both modalities are given equal weight. (6) Bidirectional Long-term and Short-term Memory (BLSM) Network : A three-layered bidirectional LSTM network is designed for feature-level fusion. The complete network is designed and implemented as described in . The BLSM network's first layer performs the modeling of raw features into time series representation. The subsequent layer fuses hidden features of the two modalities using linear functions, while the nonlinearity factor is introduced with a sigmoid function to represent the fused features in a new representation. The last layer of BLSM is responsible for the time series representation of the output from the preceding layer. 4. Experimental Results The proposed architecture was trained over the MAHNOB-HCI and DEAP datasets. This section provides an overview of the results of single modalities and the fusion of EEG and facial video clips in terms of accuracy. 4.1. Experimental Setup For both datasets, a three-class problem (happy, neutral, and sad) is considered for testing the proposed model. A leave-one-subject-out strategy was used to conduct experiments for each dataset, and the results were compared with several state-of-the-art methods. In a leave-one-subject-out experiment, training data comprise all subjects except one subject, which is left for testing. Moreover, the data split for training, testing, and validation was performed such that, from the data of N subjects, (N - 1) subjects x Number of trails for each subject for training (90% training set, 10% validation) and 1 subject x Number of trails for each subject for testing. 4.2. EEG-Based Results The model proposed in Section 3.2.1 was extended with a SoftMax layer at the end for the classification of emotions using EEG data. The proposed model was successfully able to recognize emotions with an average accuracy of 83.27% and 74.57% using the MAHNOB-HCI and DEAP datasets, respectively. For each user, Table 3 shows the test results using MAHNOB-HCI and DEAP datasets. It can be observed in Table 3 that there are fluctuations in accuracy between users within a dataset. This is because the training data did not include any trials from the test data. 4.3. Facial Video Clips-Based Results The proposed model in Section 3.2.2 was extended with a SoftMax layer at the end for the classification of emotions using facial video clips. The proposed model for facial video clips was able to identify emotions with an average accuracy of 92.4% and 90.5% for the MAHNOB-HCI and DEAP datasets, respectively. For each user, Table 4 shows the test results using the MAHNOB-HCI and DEAP datasets. It can be observed in Table 4 that there are fluctuations in accuracy between users within a dataset. This is because the training data did not include any trials from the test data. The average results from facial video clip data are satisfactory. 4.4. Results of Fusion of EEG and Facial Video Clips Using DCCA After collecting features using EEG and facial video clips in respective CNN models, the DCCA method from the proposed architecture was used to fuse the features for the classification of emotions. The fusion model was able to identify emotions with an average accuracy of 93.86% and 91.54% for the MAHNOB-HCI and DEAP datasets, respectively. For each user, Table 5 depicts leave-one-subject-out tests for the MAHNOB-HCI and DEAP datasets. It can be seen in Table 5 that the accuracy after the fusion of modalities has improved by up to 2% from the results of facial video clips. In this work, the multimodal fusion model did marginally better when compared to facial expression-based emotion recognition. The reason could be based on the fact that facial expression-based recognition has shown considerable improvement through the proposed preprocessing approach, but real-time emotion recognition that is only dependent on facial expressions is highly volatile since participants are able to deceive the system so long as they are skilled at acting out fake emotions on their faces. In this regard, the limitations of facial emotion recognition can be considerably offset by the EEG cannot be deceived. As a result, the EEG signals and facial expressions are complementary to one another rather than substituting for one another, and the multimodal fusion-based emotion recognition utilizing both signals is, therefore, more reliable than using just one of the two signals. In order to show the dominance of fusion over a single modality, the results of valence detection are presented in Figure 6. We can see that a happy state is easy to detect in part (a), where the facial variations are easily detectable. However, in part (b), the single modality-based facial expression detection model fails to detect the participant's happy state due to no particular variations in facial expressions. The fusion model helps detect the true state of motion with the help of the EEG modality. It can also be observed that it is unnecessary to keep all the frames of a video clip when there is no particular change in the expression. The fusion model was able to successfully detect the true emotion state of the participant by extracting highly correlated features between two modalities. Before explaining the results of emotion recognition, the results of the proposed methodology are also evaluated using accuracy, recall, precision, and f1-score metrics . We applied EEG and facial video clip data to detect three classes of emotions (happy, neutral, and sad) because these are the very basic categories of human emotions. Table 6 shows the results in terms of different evaluation metrics by applying DCCA to fuse the features of EEG trials and facial video clips. It can be observed that MAHNOB-HCI has been outstanding against the DEAP dataset in all metrics of evaluations, and this might be due to the quality of signals obtained from the MAHNOB-HCI dataset. Overall, the proposed technique of feature-level fusion on the features from deep learning methods has shown satisfactory performance. Table 7 and Table 8 present the performance factors for each emotion; happy, sad, and neutral on DEAP and MAHNOB-HCI datasets, respectively. It presents the performance in terms of accuracy, precision, recall, and F1-score. It can be observed that the proposed method shows consistency in detecting all three classes; however, it can detect a happy state more accurately as compared to the other classes, which is because of our division of SAM ratings into categories. As one can observe in Figure 6b, the happy state can be the most affected class in detection using facial data only because the facial expression can be misclassified by the model as neutral. For that reason, we have squeezed the region of rating for the neutral class (4 < rating < 5) as it can equally affect the sad class classification. This eventually contributed to better recognition of happy and sad classes while having little effect on neutral class recognition accuracy. 4.5. Comparison of Results with the State-of-the-Art In this section, we sum up our results from the previous section on the MAHNOB-HCI and DEAP datasets. Table 9 displays the comparison between the proposed DCCA-based fusion approach and four existing fusion methods in terms of accuracy using the MAHNOB-HCI and DEAP datasets. The simple concatenation-based fusion method proposed by Lu et al. resulted in the least accuracy out of all methods considered in this study. This explains why the fusion method needs to be much more sophisticated than simple concatenation when it comes to signals from modalities. Fuzzy integrals-based fusion of two modalities yields better results than the other baseline methods because it utilizes a special approach to minimize the error between the two modalities while correlating the features. The MAX fusion shows good performance on both datasets and is probably the simplest of all the methods considered in this study, but it can be easily defeated if one modality carries features of a misleading class with a strong probability. Cai et al. applied MKL to fuse audio and visual information for emotion recognition, but it does not seem to be equally good for the fusion of other modalities. Moreover, the adaptive fusion was also implemented for comparison, and the performance was similar to the fuzzy integrals. A feature-level fusion using the BLSM network has shown good performance in fusing the EEG and facial video clip features, but still, its accuracy is lower than the adaptive fusion method. As depicted in Table 9, the DCCA-based fusion method achieves the best accuracy of 93.86% and 91.54% on MAHNOB-HCI and DEAP datasets, respectively. This proves that the deep learning-based fusion method (DCCA) is the most effective in extracting the highly correlated features and a more robust method for emotion recognition in terms of the modalities under consideration. The advantage of our proposed method is proven by comparing it with state-of-the-art methods, and we ensured that the experimental setup of the methods from the literature considered the corresponding number of emotional categories. A comprehensive summary of results from the proposed method and other methods is shown in Table 10. Wu et al. propose a model for facial expression and EEG data fusion based on hierarchical LSTM. The features were combined at each time frame to identify the important signal at the next time frame until the emotion result was predicted at the last time frame. In , a CNN and decision tree-based emotion recognition model was proposed to fuse the multiple modalities by using the probability value of each category. The process uses a mixed-fusion approach on facial expressions, GSR (Galvanic skin response), and EEG data, which results in a maximum of 81.2% and 91.5% accuracy using LUMED-2 (Loughborough University Multimodal Emotion Dataset-2) and DEAP datasets, respectively. Zhang investigated a LIBSVM (library for support vector machines) model for a classification task and adopted a fuzzy logic approach for decision-level fusion of the EEG and facial expression signals. The author was able to improve the average emotion recognition rate to 85.7%. Huang et al. proposed two decision-level fusion approaches based on the enumerate weight rule and an adaptive boosting technique to combine facial expression and EEG data. The fusion results achieved 69.75% accuracy for the valence and 70.00% accuracy for the arousal space in an online experiment. Aguinaga et al. considered a three-class (happy, angry, and sad) classification problem and used the DEAP dataset to evaluate the performance. An approach including a neural network for facial expression recognition and a 1D-CNN model for EEG data was implemented and achieved a maximum accuracy of 83.33%. Zhao and Chen achieved good performance through the fusion of EEG and facial features while analyzing time series data with the help of an LSTM model. However, the proposed scheme shows the best performance against other methods in the literature. Even if several qualified research procedures were studied, the majority of closely linked research works selected the same number of emotional states. It can be observed from Figure 7 that our proposed model has performed meaningfully better than other methods in bimodal emotion recognition. The proposed model uses a DCCA-based feature-level fusion method, which can extract highly correlated features in bimodal emotion recognition. Table 11 shows the comparison of the proposed technique with the most recent state-of-the-art methods reported in , and it can be observed that the proposed method achieved competitive performance. However, it is essential to note that our method relies on discarding unnecessary information from the input data. For the sake of a fair comparison, we analyzed the computational complexity of the proposed lightweight 1D-CNN model against other lightweight models on EEG data. For this purpose, the number of network parameters and average processing time (for the feature extraction part only) are evaluated in Table 12. We see that Shi et al. and Saini et al. consumed fewer parameters than the proposed method but were not reliable in terms of results. This might be due to the lesser number of convolutional layers or poor selection of convolutional filters, and sometimes the dropout layer plays a significant role in reducing the overfitting problem. However, the proposed model not only achieved a significant performance in terms of accuracy over the other models but also utilized fewer parameters. It can be observed from Table 12 that the proposed model has fewer parameters than the other lightweight models with the least effect on performance. This is because the pooling layer does not contain parameters. We replaced the fully connected layers with the pooling layers, which significantly reduced the number of parameters. Several experimental evaluations have shown that replacing the fully connected layers has little effect on the model's accuracy. Additionally, the proposed method saves approximately 96% of the processing time compared to Cordeiro et al. . Although the methods presented by Shi et al. and Saini et al. consumed less time, they could not meet an adequate level of accuracy as compared to the proposed method. Here we deduce that: (1) models by Shi et al. and Saini et al. produced low accuracy due to their relatively simpler structure and the usage of fewer convolution layers; (2) model by Cordeiro et al. produced the best results; however, it consumed more network parameters and processing time; and (3) proposed model achieved significant performance as compared to the others. At the same time, we also monitored the utilization of the hardware resource by the proposed method and other lightweight models in the training and testing phases on EEG data. For that purpose, we ran our experiments on Intel (R) Core (TM) i7-7700K CPU @ 4.5 GHz processor, using 32 GB memory and two NVIDIA GTX 1080 GPUs. We recorded the percentage of overall processing capacity and the percentage of physical memory occupied by the proposed and other lightweight models when they were trained/tested. Table 13 presents the hardware resources utilized by the proposed and other models during the training and testing phases. Although there are no data in the papers to show the utilization of hardware resources of the models considered for comparison, it can be seen in Table 13 that some models are more complex in terms of parameters as compared to the proposed model. As a result, such models' utilization of hardware resources must be greater than those with fewer parameters. It can be observed that out of all models considered for comparison, the model proposed by Cordeiro et al. has the highest usage of processing capacity, while that of Qazi et al. has the largest memory usage. The proposed model's processing capacity utilization is slightly high, reaching above 19% during training, but memory utilization is much lower. In terms of computing overhead, it can be shown that the suggested model performs adequately when compared to alternative lightweight approaches. 5. Discussion As we know, a positive mood helps improve efficiency at work and secures the mental health of a human being. On the other hand, a negative mood causes stress, which ultimately leads to depression if not treated well/on time . Social or physical environments usually entice negative moods in humans. Moreover, relevant psychological and physiological symptoms also begin to rise inside the body along with the negative mood. Normally, these negative symptoms fade away with time if the stress does not last much longer; otherwise, it may lead to severe damage to the body if the symptoms persist. Therefore, it is necessary to distinguish between happy, sad, and neutral emotions. This study performed feature extraction and fusion using data from the two modalities. We ran simulations on the MAHNOB-HCI and DEAP datasets to see how useful the suggested approach was. Both datasets include ratings from each subject for each stimulus in the form of levels of arousal/valence on a discrete scale between 1-9 . The most fundamental and extensively used characteristics for representing an individual's emotions are valence and arousal. Valence stands for pleasure or contentment; therefore, if valence scores rise, so too would the amount of satisfaction for any given subject . However, arousal symbolizes wakefulness; therefore, if the arousal value is low, the subject is asleep, and if the arousal value rises, the subject is awake. We used these ratings to convert them into three classes, namely sad (rating <= 4), neutral (4 < rating < 5), and happy (rating >= 5). The term "autism" was first used by Asperger and Kanner to describe an organic disorder with severe behavioral, affective, communication, and social skills impairment. This disorder is characterized by a lack of interest in other people, speech disorders, attention deficits, and compulsive and repetitive behavior. A chronic neurodevelopmental illness called autism spectrum disorder (ASD) causes difficulties in social interaction and interpersonal communication as well as constrained, repetitive behaviors and interests . Several studies have revealed that people with ASD have trouble reading others' facial expressions . A lack of emotional awareness negatively affects one's ability to manage their own emotions and makes it more difficult to understand the emotions of others, which makes it challenging to interact socially. People with alexithymia are unable to express their emotions verbally, either because they are uninformed of the feelings that go along with these emotions or because they confuse emotional and physical experiences . Because of this, they struggle to build close, intimate connections with others, comprehend the motives and attitudes of others, and come to ethically sound conclusions that consider the perspectives of others. One of the most significant areas of overlap between alexithymia and ASD is these components of alexithymia, together with communication and social skill deficiencies. Communications and social interactions suffer when people find it difficult to read the expressions on others' faces. However, in this study, we have combined the features from EEG trials and facial video clips to recognize the true emotions of a person. The proposed system can enable such socially impaired people to function properly by identifying the true facial expression of others. Additionally, this research may be expanded to discover strategies for helping socially challenged individuals recognize their own emotions and develop appropriate facial expressions. Nonverbal cues in human contact, such as voice tone/pitch/cadence, body movements/kinesthetic information, gestures, and others, that reveal to others one's intentions, thoughts, and feelings have long played a significant role in human communication. However, the role of each type of communication becomes more important when a bodily/mentally challenged person wants to convey emotions. Kumar and Ponnusamy presented a multimodal technique to identify the emotions of mentally challenged people from facial expressions, voice, and body language. Further, Castellano et al. fused features from facial expressions, body movements, gestures, and speech to identify emotions using a Bayesian classifier. Therefore, combining signals from several non-verbal means of communication along with EEG and/or facial expressions can be worth studying using the proposed method. This study was conducted to examine the emotions of a human being using more than one modality while preserving the necessary information and neglecting the redundant information in the modalities under consideration. Thus, it is worth discussing the classification results after designing a bimodal emotion recognition model using EEG and facial video clips on separate deep-learning models and fusing the deep-learning features with another deep-learning-based model to develop a highly correlated feature map. The results suggest that deep learning-based emotion recognition models are worth studying, and there is always room for improvement in such models in terms of efficiency. This method consisted of deep learning models for feature extraction from EEG and facial video clip modalities. Afterward, the extracted deep features were fused again in terms of correlation using DCCA. The fused features were used to recognize the three different classes of emotions. The generalization capability of a model is better judged in a leave-one-subject-out experiment, and the proposed work executes emotion recognition by considering a leave-one-subject-out methodology for testing. The simulations have depicted that the model has attained satisfactory accuracy in bimodal emotion recognition in a leave-one-subject-out environment. Moreover, the testing of the model was performed using single modalities, and the outcomes showed that the proposed model with the feature-level fusion of features using DCCA could attain satisfactory outcomes. 6. Conclusions and Future Work This work presents a unique bimodal emotion recognition model by performing the fusion at the feature level using DCCA. The proposed model relies on a CNN. We assessed the proposed model on the DEAP and MAHNOB-HCI datasets for performance measurement. Initially, we applied pre-processing steps to remove the noise from EEG data and facial video clip data in the DEAP and MAHNOB-HCI datasets. Moreover, balancing the class distribution helped improve the normalization capacity of the classification model. In the end, leave-one-subject-out testing was performed for all subjects, and the SoftMax classifier was applied to perform classification. The simulation results proved that the features acquired from the proposed/adapted deep learning models and fused together using DCCA achieved better and more consistent performance. The proposed method helped overcome the missing key features problem and enhanced the performance of emotion recognition from bimodal data by extracting highly correlated features for classification. We proposed an emotion recognition system that was applied to all subjects separately for testing. The model is capable of recognizing the true emotional state, because it does not consider any features from either modality, which can cause ambiguity during classification and enhance the accuracy and constancy of bimodal emotion recognition. This model for bimodal emotion recognition is a powerful interface for brain-computer interaction. Even if the results obtained from simulations are good enough, cross-subject emotion recognition can be a good way to study this method further. We aim to improve this method by making it robust, optimal, and generalized for multimodal emotion recognition, and by including some emotion-related brain neurogenic analysis in the discussion section. Moreover, it is an established fact that the more data, the better the deep learning model will perform. The two considered datasets (DEAP and MAHNOB-HCI) with a limited number of subjects are not sufficient to fully train deep learning models. Therefore, it would be interesting to study the response of the proposed model with more data generated through new experiments and/or augmentation techniques. Author Contributions Conceptualization, F.M. and M.H.; Formal analysis, F.M.; Investigation, F.M.; Methodology, F.M.; Project administration, M.H.; Resources, F.M.; Supervision, M.H. and H.A.; Writing--original draft, F.M.; Writing--review & editing, F.M. 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 are available from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The process of finding frames containing meaningful information (the facial image adopted from ). Figure 2 Proposed model for emotion recognition using EEG and facial video clips (the facial image adopted from ). Figure 3 1D-CNN model for EEG data. Figure 4 RestNet50-based CNN model for facial video clips (the facial image adopted from ). Figure 5 DCCA method used for fusion of EEG and facial video clip features. Figure 6 The examples of the valence detection against time are represented for experiment number 10 using the MAHNOB-HCI dataset. (a) For participant number 26, the happy state was detected correctly. (b) For participant number 1, it was hard to detect any particular changes on the face, but the fusion model detected a happy state successfully. Figure 7 Comparison of proposed method with other state-of-the-art methods from the literature in terms of accuracy (Aguinaga et al. , Zhao and Chen , Wu et al. , Cimtay et al. , Zhang , Huang et al. ). Figure 8 Valence-Arousal chart against various human emotions. diagnostics-13-00977-t001_Table 1 Table 1 Selected hyperparameters and corresponding range to find the optimal values for a lightweight 1D-CNN model. Hyperparameter Range Optimal Value Layers 1-5 3 Batch size 18-40 32 Epochs 20-50 40 Learning rate 0.1-0.0001 0.001 Number of convolution filters (Layer 1) 16-100 64 Filter size (Layer 1) 3-5 3 Number of convolution filters (Layer 2) 16-100 64 Filter size (Layer 2) 3-5 3 Number of convolution filters (Layer 3) 16-128 32 Filter size (Layer 3) 3-5 3 Number of convolution filters (Layer 4) 16-128 - Filter size (Layer 4) 3-5 - Number of convolution filters (Layer 5) 16-128 - Filter size (Layer 5) 3-5 - diagnostics-13-00977-t002_Table 2 Table 2 Selected hyperparameters and corresponding range for the evaluation of optimal values to design a 1D neural network for DCCA. Hyperparameter Range Optimal Value Layers 1-4 3 Batch size 18-50 32 Epochs 20-60 40 Learning rate 0.1-0.0001 0.001 Number of convolution filters (Layer 1) 100-150 128 Filter size (Layer 1) 3-5 3 Number of convolution filters (Layer 2) 100-300 256 Filter size (Layer 2) 3-5 5 Number of convolution filters (Layer 3) 200-512 512 Filter size (Layer 3) 3-5 3 Number of convolution filters (Layer 4) 200-512 - Filter size (Layer 4) 3-5 - diagnostics-13-00977-t003_Table 3 Table 3 EEG-based results in terms of accuracy (%). Users MAHNOB Dataset DEAP Dataset User 1 89.3 73.7 User 2 84.9 74.5 User 3 78.8 74.1 User 4 95.1 75.6 User 5 83.7 75.9 User 6 96.4 85.4 User 7 79.7 77.5 User 8 76.1 75.3 User 9 90.2 70.9 User 10 84.8 73.6 User 11 83.1 72.5 User 12 86.5 70.8 User 13 94.2 74.9 User 14 92.8 72.8 User 15 92.6 74.2 User 16 83.6 72.1 User 17 72.4 72.5 User 18 71.1 78.3 User 19 72.9 73.1 User 20 87.8 75.2 User 21 74.8 72.8 User 22 71.9 73.3 User 23 78.7 - User 24 80.3 - User 25 72.1 - User 26 85.6 - User 27 78.8 - Average 83.27 74.57 diagnostics-13-00977-t004_Table 4 Table 4 Facial video clip based results in terms of accuracy (%). Users MAHNOB Dataset DEAP Dataset User 1 92.2 88.8 User 2 91.3 88.6 User 3 93.1 90.4 User 4 90.3 89.7 User 5 91.8 89.7 User 6 92.5 91.9 User 7 92.4 91.6 User 8 92.1 93.4 User 9 90.7 87.2 User 10 95.2 87.9 User 11 95.1 91.1 User 12 93.6 92.5 User 13 94.1 92.1 User 14 93.2 90.6 User 15 92.8 92.8 User 16 94.8 87.6 User 17 94.7 90.0 User 18 94.0 91.6 User 19 90.8 91.7 User 20 92.8 91.3 User 21 95.1 90.4 User 22 93.2 91.6 User 23 92.8 - User 24 93.7 - User 25 95.8 - User 26 90.5 - User 27 93.1 - Average 92.4 90.5 diagnostics-13-00977-t005_Table 5 Table 5 Results of fusion of EEG and facial video clips using DCCA in terms of accuracy (%). Users MAHNOB Dataset DEAP Dataset User 1 94.91 89.21 User 2 93.63 91.97 User 3 95.43 90.92 User 4 92.6 92.07 User 5 92.12 90.24 User 6 92.91 92.39 User 7 92.72 91.96 User 8 92.39 93.86 User 9 91.68 89.65 User 10 95.56 90.86 User 11 95.45 91.52 User 12 94.01 92.99 User 13 94.42 92.61 User 14 93.65 91.04 User 15 93.18 93.32 User 16 95.21 89.92 User 17 95.94 90.57 User 18 94.34 92.01 User 19 91.14 92.15 User 20 93.25 91.73 User 21 95.42 90.84 User 22 93.66 92.09 User 23 93.16 - User 24 94.98 - User 25 96.19 - User 26 92.88 - User 27 93.45 - Average 93.86 91.54 diagnostics-13-00977-t006_Table 6 Table 6 Results of fusion of EEG and facial video clips using DCCA. Accuracy (%) Recall (%) Precision (%) F1-Score MAHNOB-HCI 93.86 92.24 92.70 0.9351 DEAP 91.54 90.82 90.80 0.9107 diagnostics-13-00977-t007_Table 7 Table 7 Class-wise performance of the DCCA-based fusion method on DEAP dataset. Accuracy (%) Recall (%) Precision (%) F1-Score Happy 93.4 91.1 91.4 0.9127 Sad 90.52 91.3 90.1 0.9004 Neutral 90.7 90.06 90.9 0.919 diagnostics-13-00977-t008_Table 8 Table 8 Class-wise performance of the DCCA-based fusion method on MAHNOB-HCI dataset. Accuracy (%) Recall (%) Precision (%) F1-Score Happy 94.2 93 93.1 0.9413 Sad 94.1 92.32 92.4 0.936 Neutral 93.28 91.4 92.6 0.928 diagnostics-13-00977-t009_Table 9 Table 9 Comparison of average accuracies (%) of different fusion methods with DCCA using MAHNOB-HCI and DEAP datasets. Fusion Methods MAHNOB-HCI DEAP Simple Concatenation 88.32 85.71 MKL 88.81 86.55 MAX 89.47 87.15 Fuzzy Integral 90.83 88.08 Adaptive Fusion 90.92 88.69 BLSM 88.79 88.14 DCCA 93.86 91.54 diagnostics-13-00977-t010_Table 10 Table 10 Comparison of proposed method with other methods from literature in terms of datasets and number of emotion categories. Reference No. of Emotions Dataset Accuracy (%) Proposed 3 MAHNOB-HCI DEAP 93.86 91.54 Wu et al. 2 DEAP 85 Cimtay et al. 2 DEAP LUMED-2 79.2 82.7 Zhang 4 DEAP 85.71 Huang et al. 2 DEAP MAHNOB-HCI 80 75 Aguinaga et al. 3 DEAP 83.33 Zhao and Chen 2 DEAP MAHNOB-HCI 86.8 74.6 diagnostics-13-00977-t011_Table 11 Table 11 Comparison of state-of-the-art methods in terms of accuracy reported in . Method Accuracy (%) LIBSVM 85.71 Spiking neural networks 73.15 CNN 69.38 SVM 73.69 SVM, 3 Nearest Neighbors 66.28 Random Forest, SVM, logistic regression (LR) 73.08 LSTM-CNN 93.13 1D-CNN and neural networks 89.60 LSTM 91.00 Proposed 93.86 diagnostics-13-00977-t012_Table 12 Table 12 Comparison of performance between proposed 1D-CNN model for EEG signals and other lightweight methods. Methods Network Parameters Processing Time (s) Accuracy on DEAP Dataset (%) Accuracy on MAHNOB-HCI Dataset (%) Proposed 1D-CNN model for EEG 19,042 3.823 74.57 83.27 Shi et al. 1482 1.142 68.26 78.76 Saini et al. 2688 2.257 70.13 79.98 Cordeiro et al. 26,224,952 113.484 75.79 85.52 Qazi et al. 1,028,516 59.711 75.08 84.63 Anvarjon et al. 5,137,260 22.231 75.74 84.72 diagnostics-13-00977-t013_Table 13 Table 13 Comparison of hardware resource utilization of the proposed 1D-CNN model for EEG signals and other lightweight methods. Methods Overall Processing Capacity Usage Test/Train (%) Memory Test/Train (%) Accuracy on DEAP Dataset (%) Accuracy on MAHNOB-HCI Dataset (%) Proposed 1D-CNN model for EEG 19.5/20.5 10.9/8.7 74.57 83.27 Shi et al. 17.3/19.67 8.3/7.9 68.26 78.76 Saini et al. 18.5/21.8 9.6/9.0 70.13 79.98 Cordeiro et al. 53.4/65.2 31.9/30.1 75.79 85.52 Qazi et al. 31.49/30.9 24.1/21.4 75.08 84.63 Anvarjon et al. 31.8/29.0 32.5/29/2 75.74 84.72 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. Hossain M. Muhammad G. An Audio-Visual Emotion Recognition System Using Deep Learning Fusion for a Cognitive Wireless Framework IEEE Wirel. 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PMC10000367 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050786 cells-12-00786 Article Micrandilactone C, a Nortriterpenoid Isolated from Roots of Schisandra chinensis, Ameliorates Huntington's Disease by Inhibiting Microglial STAT3 Pathways Jang Minhee Investigation Writing - original draft 1+ Choi Jong Hee Investigation 1+ Jang Dae Sik Conceptualization Formal analysis Resources 2* Cho Ik-Hyun Conceptualization Writing - original draft Writing - review & editing 13* Suk Kyoungho Academic Editor Brustovetsky Nickolay Academic Editor 1 Department of Convergence Medical Science, College of Korean Medicine, Kyung Hee University, Seoul 02447, Republic of Korea 2 Department of Pharmaceutical Science, College of Pharmacy, Kyung Hee University, Seoul 02447, Republic of Korea 3 Institute of Korean Medicine, College of Korean Medicine, Kyung Hee University, Seoul 02447, Republic of Korea * Correspondence: [email protected] (D.S.J.); [email protected] (I.-H.C.) + These authors contributed equally to this work. 02 3 2023 3 2023 12 5 78614 9 2022 21 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 ). Huntington's disease (HD) is a neurodegenerative disease that affects the motor control system of the brain. Its pathological mechanism and therapeutic strategies have not been fully elucidated yet. The neuroprotective value of micrandilactone C (MC), a new schiartane nortriterpenoid isolated from the roots of Schisandra chinensis, is not well-known either. Here, the neuroprotective effects of MC were demonstrated in 3-nitropropionic acid (3-NPA)-treated animal and cell culture models of HD. MC mitigated neurological scores and lethality following 3-NPA treatment, which is associated with decreases in the formation of a lesion area, neuronal death/apoptosis, microglial migration/activation, and mRNA or protein expression of inflammatory mediators in the striatum. MC also inhibited the activation of the signal transducer and activator of transcription 3 (STAT3) in the striatum and microglia after 3-NPA treatment. As expected, decreases in inflammation and STAT3-activation were reproduced in a conditioned medium of lipopolysaccharide-stimulated BV2 cells pretreated with MC. The conditioned medium blocked the reduction in NeuN expression and the enhancement of mutant huntingtin expression in STHdhQ111/Q111 cells. Taken together, MC might alleviate behavioral dysfunction, striatal degeneration, and immune response by inhibiting microglial STAT3 signaling in animal and cell culture models for HD. Thus, MC may be a potential therapeutic strategy for HD. micrandilactone C microglia STAT3 Huntington's disease neuroprotection National Research Foundation of KoreaNRF-2016M3C7A1905074 NRF-2017R1A2A2A05069493 NRF-2021R1H1A2010055 NRF-2022R1A2C2009817 This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, and ICT (NRF-2016M3C7A1905074, NRF-2017R1A2A2A05069493, NRF-2021R1H1A2010055, and NRF-2022R1A2C2009817). pmc1. Introduction Huntington's disease (HD) is a genetic disorder that causes the progressive degeneration of brain cells, particularly in the basal ganglia and cerebral cortex. HD typically causes a combination of chorea, cognitive impairment, and psychiatric symptoms in patients . Neurodegeneration in HD is caused by an expansion of a CAG trinucleotide repeat in the huntingtin (Htt) gene. The CAG repeat encodes an abnormally long polyglutamine (PolyQ) tract in the huntingtin protein, specifically, striatal medium spiny neurons . The abnormal aggregation of mutant huntingtin (mHTT) protein may produce multiple pathological features, including neuronal loss, neuronal toxicity, excitotoxicity, mitochondrial dysfunction, transcriptional dysfunction, changes in axonal transport, and synaptic dysfunction within various brain areas such as the striatum . Despite there being many promising theories about the pathological mechanisms underlying HD, there are few pharmacotherapies that have been proven to effectively target these mechanisms and improve symptoms (chorea and psychosis) in clinical trials . Tetrabenazine (Xenazine(r)) is currently the only medication approved by the US Food and Drug Administration for the treatment of HD, and some newer antipsychotic agents (olanzapine and aripiprazole) might have adequate efficacy with a more favorable adverse-effect profile than older antipsychotic agents for treating chorea and psychosis. However, they might produce serious adverse effects such as akathisia, depression, dizziness, and fatigue . Nonetheless, the exact mechanism underlying neuronal death in HD has not been fully elucidated yet. As a metabolite of 3-nitropropanol, 3-nitropropionic acid (3-NPA) is a naturally occurring toxin that has been found in various fungal species, including Aspergillus flavus, Astragalus, and Arthrinium . It can irreversibly inhibit the activity of mitochondrial complex II, also known as succinate dehydrogenase, which is an essential component of both the electron transport chain and the tricarboxylic acid cycle in mitochondria . Systematically administering 3-NPA into experimental rodent models can cause striatal toxicity. It closely mimics and reproduces behavioral (hyperkinetic and hypokinetic movement), histopathological, and neurochemical pathology features seen in HD . Thus, 3-NPA has been used as an efficient chemical to induce HD-like symptoms and pathological features in animal models to study HD . The STHdhQ111/111 cell line is a striatal cell line derived from a knock-in transgenic mouse containing homozygous huntingtin (HTT) loci with a humanized Exon 1 with 111 polyglutamine repeats. The STHdhQ111/111 cell line is a well-known and commonly used model to study molecular aspects of HD . Schisandra (S.) chinensis, commonly known as 'Omija' in Korean and 'Wu wei zi' in Chinese, meaning five-flavor berry, is a plant species that belongs to the genus Schisandra of the family Schisandraceae. It is distributed and cultivated in northeastern China, far-eastern Russia, Japan, and Korea . S. chinensis has attracted much attention due to its various pharmacologic effects on different body systems, including the nervous, endocrine, immune, circulatory, and gastrointestinal systems . S. chinensis has various compounds, including lignans, nortriterpenes, sesquiterpenes, and phenolic acids . S. nortriterpenoids are a structurally intriguing group of polycyclic, highly oxygenated, and fused heterocyclic natural products isolated from S. chinensis . We isolated micrandilactone C (MC), a new schiartane nortriterpenoid, from the roots of S. chinensis in our previous study . However, the pharmacological features of MC are not known yet. A previous study has shown that MC isolated from S. micrantha exhibits an EC50 value of 7.71 mg/mL (SI > 25.94) against human immunodeficiency virus (HIV)-1 replication with minimal cytotoxicity (>200 mg/mL) . A nortriterpenoid kudsuphilactone B isolated from fruits of S. chinensis can induce caspase-dependent apoptosis in human cancer cells by regulating Bcl-2 family protein and mitogen-activated protein kinase signaling . C21 nortriterpenoid (16,17-dehydroapplanone E), isolated from Ganoderma applanatum, has shown inhibitory effects on the release of nitric oxide (NO) by the lipopolysaccharide (LPS)-induced BV-2 microglial cell line derived from C57/BL6 murine . Novel nortriterpenoid (compound 2) from fruits of Evodia rutaecarpa has shown potent neuroprotective activities against serum-deprivation-induced P12 cell damage . These results suggest that MC might have beneficial activities for various pathological statuses including neurological disorders. Herein, we report that MC could ameliorate Huntington's disease through its anti-inflammatory effects by inhibiting STAT3 pathways. 2. Materials and Methods 2.1. Animals and Ethical Approval Male adult C57BL/6 mice (Narabiotec Co., Ltd., Seoul, Republic of Korea; weight: 23-25 g; n = 105; seed mice originated from Taconic Biosciences Inc., Rensselaer, NY, USA) were kept under constant temperature (23 +- 2 degC) and humidity (55 +- 5%) conditions with a 12 h light-dark cycle (light on 08:00 to 20:00), and fed food and water ad libitum. The mice were allowed to habituate in the housing facilities for 1 week before the experiments. All experimental procedures were reviewed and approved by the Institutional Animal Care and Use Committee of Kyung Hee University (KHUASP-19-018). In this process, the proper randomization of laboratory animals and handling of data were performed in a blinded manner in accordance with the recent recommendations from a NIH Workshop on preclinical models of neurological diseases . 2.2. Experimental Group, Model Induction, and Drug Treatment The experimental group was divided into the following groups: the sham group (vehicle treatment, i.p. +saline, i.v.), 3-NPA group (70 mg/kg of 3-NPA, i.p. +saline, i.v.), 3-NPA + MC 1.25 group (70 mg/kg of 3-NPA, i.p. +1.25 mg/kg of MC, i.v.), 3-NPA + MC 2.5 group (70 mg/kg of 3-NPA, i.p. +2.5 mg/kg of MC, i.v.), and MC alone group (vehicle treatment, i.p. +2.5 mg/kg of MC, i.v.). The 3-NPA model induction was performed according to the method published in . Briefly, 3-NPA (Sigma-Aldrich, St. Louis, MO, USA) was dissolved in saline (25 mg/mL) and passed through a 0.2 mm filter. The 3-NPA was intoxicated intraperitoneally daily for five days at a dose of 70 mg/kg. MC was isolated from roots of S. chinensis as previously described . MC was administered daily for five days at one hour before every 3-NPA intoxication. 2.3. Behavioral Semi-Quantitative Assessment The severity of the neurological impairment (motor disability) induced by 3-NPA was assessed by an experimenter who was unaware of the experimental conditions under constant temperature and humidity conditions in a quiet room using the behavioral scale as previously described . The neurological impairment was evaluated at 24 h after the last (5th) 3-NPA intoxication. 2.4. Histopathological Analysis of Striatal Damage To investigate the histopathological alterations of the striatum following 3-NPA intoxication, we used a previously described protocol . Briefly, 24 h after the last (5th) 3-NPA intoxication, the mice (n = 5 per group) were anesthetized with isoflurane and then perfused intracardially with saline and iced 4% paraformaldehyde in 0.1 M of phosphate buffer (PB, pH 7.4). Sequential coronal sections (30 mm in thickness) were acquired from the corpus callosum throughout the entire striatum (bregma 1.40~-1.30 mm) using the method published in . Free-floating sections were collected in an antifreeze solution (30% sucrose in PBS) and stored at -20 degC. 2.5. Fluoro-Jade C (FJC) and Cresyl Violet Stains To assess the striatal apoptosis in the striatum after 3-NPA-intoxication, FJC staining was performed using the method published in . Briefly, 24 h after the last (5th) 3-NPA intoxication, free-floating brain sections (3 sections per brain) from all groups (n = 5 per group) were immersed in 70% ethyl alcohol, washed with distilled water (DW), and incubated in 0.06% potassium permanganate solution. The sections were washed with DW and then incubated in a solution of 0.001% FJC (Millipore, Billerica, MA, USA). After washing with DW, these sections were air-dried, immersed in 100% xylene, and coverslipped with DPX mountant (Sigma-Aldrich). The region of interest of each section was captured using a confocal laser scanning microscope (LSM 5 PASCAL, Carl Zeiss Microscopy GmbH, Munche, Germany). The number of FJC positive cells per section was manually and blindly counted. Additionally, 3 sections from the level of the mid-striatum were stained with 0.1% cresyl violet dye. Stained sections were captured using a digital camera (DP-70, Olympus Co., Tokyo, Japan). The level of 3-NPA-induced striatal damage compared to the area of the whole striatum was measured using the NIH Image J program [ (12 July 2022)]. 2.6. Immunohistochemical and Immunofluorescence Evaluation Immunohistochemistry was performed using the method published in . Briefly, 24 h after the last (5th) 3-NPA intoxication, free floating brain sections (30 mm thickness; 3 sections per brain) from all groups (n = 5 per group) were incubated with rabbit anti-ionized calcium-binding adapter molecule (Iba)-1 (1:2000; WAKO, Chuo-Ku, Japan). The stained sections from the level of the mid-striatum were captured using a digital camera (DP-70, Olympus Co.) and the mean level of Iba-1-immunopositive area to whole striatal area was analyzed using the NIH Image J program [ (12 July 2022)] Immunofluorescence analysis was performed as previously described . Briefly, free floating brain sections (30 mm thickness) from each group (n = 5 per group) were blocked with either rabbit anti-phospho (p)-STAT3 (1:200; Cell Signaling Technology, Beverly, MA, USA) and rat anti-CD11b (1:500; Serotec, Oxford, UK). Additionally, the region of interest of each section was captured using a confocal laser scanning microscope (LSM 5 PASCAL, Carl Zeiss, Microscopy GmbH) and the number of p-STAT3+ per 500 mm2 and the ratio of CD11b (+) cells containing p-STAT3 (+) signal per striatum was manually and blindly measured. 2.7. Western Blot Analysis Western blot analysis was performed using the method published in . Briefly, 24 h after the last (5th) 3-NPA intoxication, the striatal proteins from all groups (n = 5 per group) were incubated with primary antibodies, including mouse anti-succinate dehydrogenase complex subunit A (SDHA) (1:1000; Abcam, Cambridge, UK), rabbit an-ti-pro-caspase-3 (1:1000; Cell Signaling Technology), rabbit anti-cleaved caspase-3 (1:500; Cell Signaling Technology), rabbit anti-pro-caspase-9 (1:1000; Cell Signaling Technology), rabbit anti-cleaved caspase-9 (1:1000; Cell Signaling Technology), rabbit anti-B-cell lymphoma 2 (Bcl-2) (1:1000; Santa cruz Technology), rabbit anti-Iba-1 (1:500; WAKO), rabbit anti-phospho (p)-STAT3, STAT3 (1:500; Cell Signaling Technology), mouse anti-inducible nitric oxide synthases (iNOS) (1:500; Santa Cruz Biotechnology, Santa Cruz, CA, USA), rabbit anti-interleukin(IL)-1ss, IL-6, tumor necrosis factor-a (TNF-a) (1:1000; Cell Signaling Technology), mouse anti-neuronal nuclear protein (NeuN) (1:2000; Millipore), mouse anti-HTT (clone mEM48; 1:500; Millipore), and mouse anti-HTT (clone 2Q75; 1:500; LifeSpan BioSciences, Seattle, WA, USA) antibodies. For the normalization of antibody signals, membranes were stripped and reprobed with antibodies against glyceraldehyde-3-phosphate dehydrogenase (GAPDH; 1:5000; Cell Signaling Technology) or STAT3. Data are expressed as the ratio of the corresponding protein signal against GAPDH or the STAT3s signal for each sample. Original images from Western blot assay in Supplementary Data S1. 2.8. Flow Cytometry At 24 h following the last (5th) 3-NPA intoxication, mice (n = 3 per group) with representative behavioral scores in each experimental group were anesthetized by isoflurane (1-2%) and perfused intracardially with saline. The striata were then carefully cropped. To test the microglia/macrophage population, single-cell suspensions refined from striata were prepared and fluorescently stained as previously described . Microglia and macrophages were differentiated based on their relative CD45 expression levels . Briefly, after acquiring unstained and single colored control samples to calculate the compensation matrix, 1 x 104 events were acquired within the combined gate based on physical parameters (forward scatter (FSC) and side scatter (SSC)). 2.9. Real-Time Polymerase Chain Reaction (PCR) Analyses To measure the mRNA level of inflammatory factors, 24 h after the last (5th) 3-NPA intoxication, real-time PCR analysis using the striatal lysats from all groups (n = 5 per group) was performed using the SYBR Green PCR Master Mix as previously described . Reactions were performed in duplicate in a total volume of 10 mL, each containing 10 pM of primer, 4 mL of cDNA, and 5 mL of SYBR Green PCR Master Mix. The mRNA levels of each target gene were normalized to that of GAPDH mRNA. Fold-induction was calculated using the 2-DDCT method as previously described . All real-time RT-PCR experiments were performed at least three times, and the mean +- SEM values are presented unless otherwise noted. The primer sequences are listed in Supplementary Materials. The expression levels of each gene were normalized to that of GAPDH. 2.10. STHdh Cell Culture STHdh cell lines (STHdhQ111/Q111) (conditionally immortalized striatal neuron progenitor cell lines) were kindly provided by Prof. Hoon Ryu (Korea Institute of Science and Technology, Seoul, Republic of Korea) and were cultured according to the protocol from Coriell Institute for Medical Research (Camden, NJ, USA) as previously described . 2.11. Preparation of Conditioned Medium (CM) from BV2 Cells and Determination of Activity of STHdh Cells To obtain CM, cultured BV2 cells were treated with MC (5 mM) at 1 h before stimulation with 3-NPA (1 mM) for 12 h. The culture medium was replaced with fresh medium and incubated for 24 h. CM-3-NPA (conditioned medium from 3-NPA-stimulated BV2 cells) and CM-3-NPA-MC (conditioned medium from 3-NPA-stimulated BV2 cells pretreated with MC) were collected and used to investigate the expression of inflammatory factors and p-STAT3 by Western blot analysis. CM-3-NPA and CM-3-NPA-MC were treated to STHdhQ111/Q111 cells for 24 h. CM-treated STHdhQ111/Q111 cells were collected to analyze the degree of neurodegeneration (NeuN) and huntingtin aggregation (EM48 and 2Q75) by Western blot analysis. In vitro assays were repeated at least three times, with each experiment performed in triplicate. 2.12. Statistical Analysis Statistical analysis was performed using the IBM SPSS Statistics Version 26.0 (SPSS Inc., Chicago, IL, USA) for Windows. The data from experiments including the behavioral test, immunohistochemistry, Western blot, and PCR analysis were analyzed using Kruskal-Wallis test (a nonparametric test) for the comparison of three or more unmatched groups. The data are presented as mean +- SEM. p values of less than 0.05 were accepted as statistically significant. 3. Results 3.1. Effects of MC on Neurological Score and Survival Rate after 3-NPA Intoxication First, we determined whether MC could mitigate neurological signs and survival rate of mice following 3-NPA treatment. Figure 1A-C shows a representative neurological score, survival rate, and body weight (BW) of the sham, 3-NPA, 3-NPA + MC (1.25 and 2.5 mg/kg/day), and MC alone (2.5 mg/kg/day) groups. Twenty-four hours after the last (5th) intoxication of 3-NPA, the mice displayed symptoms of severe neurological deficits (score, 9.0 +- 0.4). However, the mice in 3-NPA + MC groups displayed significantly lower neurological scores (7.0 +- 0.4 and 4.8 +- 0.2 in MC 1.25 and 2.5 mg/kg/day groups, respectively) than the mice in the 3-NPA group (score, 9.0 +- 0.4) . The survival rate at the end of the representative experimental set was increased to 57.1% (n = 4/7) and 71.4% (n = 5/7), respectively, in 3-NPA + MC 1.25 mg/kg/day and 3-NPA + MC 2.5 mg/kg/day groups, respectively, as compared to that in the 3-NPA group (42.8%, n = 3/7) . The mean loss of BW was significantly alleviated by 3-NPA. However, it was not significantly affected by MC treatment at 1.25 or 2.5 mg/kg/day . Treatment with MC alone (2.5 mg/kg/day) did not significantly affect the neurological score, survival rate, or BW of normal mice. 3.2. Effects of MC on Striatal Cell Death and Apoptosis Induced Following 3-NPA-Treatment It is known that 3-NPA-induced neurological dysfunction results from striatal cell death . Thus, we explored whether MC could alleviate striatal cell death following 3-NPA-treatment. Twenty-four hours after the last (5th) 3-NPA treatment, coronal cryostat sections of brain including the striatum were subjected to cresyl violet dye . Figure 2A shows representative striatal images from the sham, 3-NPA, 3-NPA + MC (1.25 and 2.5 mg/kg/day), and MC alone (2.5 mg/kg/day) groups. In the two representative experimental sets, it was found that 85.7% (n = 6/7) of the surviving mice in the 3-NPA-treated group had visible bilateral striatal lesions (pale areas surrounded by dotted line), whereas this percentage was reduced to 71.4% (n = 5/7) and 55.5% (n = 5/9) in the groups treated with MC at 1.25 and 2.5 mg/kg/day, respectively . Furthermore, in the 3-NPA group, the ratio of the mean lesion area to the entire striatum was 80.6%, whereas this ratio remarkably decreased to 56.1% and 36.6% in the group treated with MC at 1.25 and 2.5 mg/kg/day, respectively . The results of the behavioral dysfunction and striatal cell death revealed that treatment with 2.5 mg/kg/day of MC was more effective in inhibiting 3-NPA toxicity than treatment with 1.25 mg/kg/day of MC. Thus, the dose of 2.5 mg/kg/day of MC was used in further studies. Since 3-NPA is an irreversible inhibitor of mitochondrial respiratory complex II and succinate dehydrogenase (SDH) , we explored whether MC could inhibit mitochondrial complex II activity using SDHA antibody in striatal lysate at 24 h after the last 3-NPA administration . Protein expression level of SDHA was decreased in the 3-NPA group (0.43) compared to that in the sham group (0.77) but increased after treatment with MC at 2.5 mg/kg/day (0.61) . Based on the results from the cresyl violet stain , to further compare the levels of degenerating neuronal cells, we stained coronal cryostat sections with FJC anionic fluorescent dye , a good marker of degenerating neurons . The number of FJC (+) cells was increased to 43.6 +- 1.5 per section in the 3-NPA group, but decreased to 29.6 +- 0.9 in the 3-NPA + 2.5 mg/kg/day MC group . To test whether the anti-neuronal cell death effect of MC might be related to apoptosis, we determined the protein levels of the representative apoptosis markers (cleaved caspase-9, cleaved caspase-3, and Bcl-2) in the striatum by Western blotting . The protein expression levels of cleaved caspase-9 and cleaved caspase-3 were increased in the 3-NPA group (0.85 and 0.71, respectively) compared to those in the sham group (0.15 and 0.17, respectively), but decreased after treatment with MC at 2.5 mg/kg/day (0.55 and 0.44, respectively) , similar to results of the FJC staining . The protein expression level of Bcl-2 was also decreased in the 3-NPA group (0.51) compared to that in the sham group (0.75) but increased after treatment with MC at 2.5 mg/kg/day (0.80) . 3.3. Effect of MC on Microglial Activation in the Striatum Following 3-NPA-Treatment Microglia are migrated into degenerative site in the central nervous system (CNS) in cases of neurodegenerative diseases, including HD. They are then activated within/around the lesions in the CNS. These activated microglia can produce anti-inflammatory cytokines . Thus, we explored whether MC could suppress microglial activation in the striatal lesions from all groups (n = 5 per group) following 3-NPA treatment . In the striatal sections of the 3-NPA group, Iba-1 (a marker for microglia/macrophage lineage cells)-immunoreactive cells showed a morphology of the activated type with bigger cell bodies and extended (short and thick) processes than those in the sham group of CNS, which displayed typical forms of resting cells, including relatively small soma and long, thin processes . However, the mean level of Iba-1-immunopositive area to whole striatal area was clearly decreased in striatal sections of the 3-NPA + MC group than in the 3-NPA group , in agreement with the alteration (0.53-fold in the 3-NPA group; 0.26-fold in the MC) in the protein expression of Iba-1 based on Western blot analysis . The morphology of the Iba-1 immunoreactive cells based on immunohistochemistry and the Iba-1 protein expression based on Western blot analysis were not significantly affected by treatment with MC (2.5 mg/kg/day) alone . Since Iba-1 can detect microglia and macrophage ; to discriminate both cells, flow cytometry was performed using striatum at 24 h after the last (5th) treatment of 3-NPA. Interestingly, the percentage of CD11b+/CD45+(low) cells representing microglial cells increased to 17.4 +- 1.1% in the 3-NPA group compared to that of the sham group (4.2 +- 0.6%) but decreased to 10.2 +- 0.5% in the 3-NPA + MC group compared to that of the 3-NPA group . However, the percentage of CD11b+/CD45+(high) cells representing macrophages was not significantly different between the sham group and the other groups . These findings suggest that MC might inhibit microglial migration and activation regardless of the macrophage and that MC might be closely associated with the reduction in striatal cell death and the mitigation of neurological impairment following 3-NPA treatment. 3.4. Effects of MC on Inflammatory Factors and STAT3 Pathways in the Striatum Following 3-NPA-Treatment Migrated and activated microglia around (or within) CNS lesions can release inflammatory mediators (enzymes, cytokines, and chemokines) that are either beneficial or detrimental to neuronal survival . Thus, we explored whether the inhibition of microglial activation by MC might induce changes in the mRNA expression of representative inflammatory enzymes (COX-2 and iNOS), cytokines (IL-1b, IL-6, and TNF-a), and chemokine (MCP-1) using real-time PCR analysis . The mRNA expression levels of pro-inflammatory factors were increased in the 3-NPA group compared to the sham group, with the following results: COX-2: increase by 15.9-fold; iNOS: increased by 3.5-fold; IL-1b: increased by 28.7-fold; IL-6: increased by 51.4-fold; TNF-a: increased by 55.1-fold; and MCP-1: increased by 363.8-fold . On the other hand, MC remarkably blocked these increases induced by 3-NPA with the following results: COX-2 by 8.0%, iNOS, by 3.5%, IL-1b, by 28.7%, IL-6, by 51.4%, TNF-a, by 55.1%, and MCP-1 by 89.0%, compared to those in the 3-NPA group . Since STAT3 pathways are involved in neurodegeneration, including striatal toxicity , we examined these signaling pathways in the striatum after 3-NPA treatment . The expression level of p-STAT3 protein was remarkably enhanced--by 5.3-fold--in the striatum at 24 h after the final 3-NPA treatment compared to that in the sham group. However, MC significantly inhibited the expression level of p-STAT3 protein by 49.3% . To determine whether STAT3 downregulation by MC was directly related to the reduction in neuronal cell death and microglial activation, we performed immunofluorescence staining for p-STAT3 in the striatum of the 3-NPA group. In agreement with the alteration in the expression level of p-STAT3 protein, the numbers of p-STAT3 immunoreactive cells and CD11b (+) cells were enhanced in striatal lesions after 3-NPA treatment, while these numbers were markedly reduced by MC treatment . These findings suggest that MC could inhibit inflammatory response and striatal toxicity after 3-NPA treatment by inhibiting STAT3 pathways in the striatum and microglia. 3.5. Effects of MC on Pro-Inflammatory Factors and STAT3 Pathways in 3-NPA-Induced BV2 Cells The STAT3 pathway plays an important role in microglial activation . Microglial activation is pivotally involved in neuroinflammatory and neurodegenerative events processes such as 3-NPA-induced striatal toxic, adeno-associated viruses (AAV)/viral vector-induced, and transgenic mice models for HD . Thus, we further investigated whether MC could control microglial activation in 3-NPA-induced BV-2 cell . MC significantly inhibited the enhancement in protein expression of a representative inflammatory enzyme (COX-2 and iNOS) and cytokines (IL-1b, IL-6, and TNF-a) as found using Western blot analysis: COX-2 by 48.7%, iNOS by 44.1%, IL-1b by 52.1%, IL-6 by 53.6%, and TNF-a by 43.2%, compared to those in the 3-NPA-treated group . Next, we investigated whether these anti-inflammatory effects of MC were related to the reduced expression of p-STAT3. The expression of p-STAT3 was markedly enhanced in 3-NPA-stimulated BV2 cells (by 267.5%), compared to those in the sham group. However, MC impressively inhibited this enhancement (by 35.4%) . MC itself did not significantly affect inflammatory enzyme/cytokines and STAT3 phosphorylation . These results suggest that MC might inhibit STAT3 pathways and contribute to microglial downregulation as well as neuroprotection. 3.6. Effect of MC on STHdh Cell Death via Microglial Downregulation by Inhibiting STAT3 Pathway Since the STAT3 pathway plays a critical role in neuron-microglia interactions , we further investigated whether these anti-inflammatory effects of MC could affect striatal cell death via the STAT3 pathway by controlling mHTT expression in HD . Impressively, CM-3-NPA significantly reduced the expression of NeuN protein (a marker of neuronal cells) in STHdhQ111/Q111 cells compared to the sham control. However, CM-3-NPA-MC significantly inhibited this reduction . CM-3-NPA also enhanced the expression of EM48 and 2Q75 proteins (markers of mHTT) in the STHdhQ111/Q111 cell compared to the sham control, whereas CM-3-NPA-MC intriguingly diminished their expression levels . These results indicate that MC might decrease the STHdhQ111/Q111 cell death related to the reduced expression of mHTT protein by down-regulating microglial activation. 4. Discussion The results of the present study revealed that MC, a nortriterpenoid isolated from roots of S. chinensis, could ameliorate 3-NPA-induced HD-like symptoms by inhibiting STAT3 pathways. Pretreatment with MC ameliorated the neurobehavioral disorder (motor disability), improved the survival rate, and inhibited the neurodegeneration related to apoptosis in the striatum following 3-NPA intoxication. These results were consistent with the reduction in microglial activation and inflammatory response related to the reduction in p-STAT3 expression. Intriguingly, CM-3-NPA-MC reduced STHdhQ111/Q111 cell death by inhibiting mHTT expression. These beneficial activities of MC for HD-like symptoms were associated with the inhibition of microglial STAT3 pathways. In conclusion, MC might be a potential therapeutic agent for treating HD-like symptoms by inhibiting microglial STAT3 pathways. To the best of our knowledge, this effect of MC on neurological disorders has never been reported. An inhibitor of SDH (mitochondrial complex II), 3-NPA is a source of reactive oxygen species . It is known that 3-NPA can induce striatal degeneration by neurotoxic activity in rodents and result in gait abnormalities, which mimics the behavioral dysfunction and pathology caused by mutant Htt in animal models for HD and its patients. However, the 3-NPA-induced rodent model has nothing to do with mutant Htt expression . Nevertheless, the model has been used to discover a therapeutic intervention for HD . In the present study, the protein expression level of SDHA, a marker of mitochondrial complex II activity, was decreased in the striatum following 3-NPA treatment but enhanced by administration with MC . The enhancement of the mitochondrial complex II activity of MC was associated with decreased levels of behavioral impairment and striatal cell death based on cresyl violet and FJC staining . Taken together, these results suggest that regulating mitochondrial complex II activity might be an attractive strategy to prevent striatal degeneration in 3-NPA-induced HD-like symptoms. FJC staining is commonly used to label all degenerating mature neurons, including apoptotic, necrotic, and autophagic cells in brain tissue . MC blocked the increase in the number of FJC (+) cells in the striatum induced by 3-NPA associated with reduced levels of cleaved caspase-9/caspase-3 proteins (initiators of intrinsic apoptosis) and enhanced levels of Bcl-2 protein (regulator proteins of apoptosis) . These results suggest an anti-apoptotic activity of MC in striatal degeneration. Normally, 3-NPA can induce apoptosis by generating superoxide radicals and activating the microglia surrounding apoptotic cells . Cell death caused by the latter is called 'secondary cell death' or 'delayed cell death' . STAT3-activation in microglia exacerbates neuronal apoptosis in the hippocampus of diabetic brains . Thus, controlling microglial STAT3 is considered an attractive anti-apoptosis strategy to protect neurons in various pathological environments. In the present study, MC inhibited the expression of pro-inflammatory factors and STAT3 pathways in 3-NPA-induced BV2 cells . CM-3-NPA-MC significantly reduced STHdhQ111/Q111 cell death (NeuN) associated with mHTT expression (EM48 and 2Q75) . Taken together, these results suggest an anti-apoptotic activity of MC in striatal degeneration by inhibiting microglial STAT3 signaling. Microglia, as brain-resident immune cells, are emerging as a central player in regulating the key pathways in CNS inflammation . Microglia are recruited and activated around or within neurodegenerative lesions. Activated microglia can secrete inflammatory agents that are either beneficial or deleterious to neuronal survival . Clinical studies using positron emission tomography have also demonstrated that the level of microglial activation is increased in proportion to the severity of HD symptoms . Thus, handling microglial activation might be an attractive therapeutic strategy for neurological disorders including HD . In the present study, MC inhibited microglial activation (Iba-1 immunoreactive cells) and decreased the mRNA or protein expression levels of pro-inflammatory enzymes (COX-2 and iNOS), cytokines (IL-1b, IL-6, and TNF-a), and chemokine (MCP-1) in the striata of 3-NPA-intoxicated mice and in 3-NPA-induced BV2 cells . Thus, MC might inhibit microglial activation and inflammatory responses, leading to a reduction in striatal cell death. STAT3 is a pivotal transcription factor for microglial activation and cytokine production , such as IL-1b , IL-6 , and TNF-a . These cytokines have been identified as important mediators of microglia-neuron interaction during neurodegeneration . The STAT3 signaling pathway is critically involved in behavioral dysfunction and the pathological events of HD and AD . Thus, in this study, we hypothesized that STAT3 signaling in microglia might affect microglia-neuron interactions via secreted cytokines, resulting in striatal degeneration and behavioral dysfunction. As a result of testing this hypothesis, MC inhibited the mRNA or protein expression of representative inflammatory enzyme (COX-2 and iNOS), cytokines (IL-1b, IL-6, and TNF-a), and p-STAT3 in not only 3-NPA-intoxicated striatum, but also 3-NPA-stimulated BV2 cells . MC also inhibited the level of co-staining of p-STAT3 in CD11b positive cells in striatum after 3-NPA-intoxication and protein expression of p-STAT3 in 3-NPA-stimulated BV2 cells . These findings indicate that MC might reduce inflammatory responses by inhibiting STAT3 signaling in microglia. Furthermore, we investigated whether the downregulation of microglial p-STAT3 might affect the survival of STHdhQ111/Q111 cells expressing mHTT. Interestingly, CM-3-NPA-MC (conditioned medium from 3-NPA-stimulated BV2 cells pretreated with MC) significantly reduced STHdhQ111/Q111 cell death and mHTT expression compared to CM-3-NPA treatment . Taken together, MC might reduce striatal degeneration and mHTT expression through reduced inflammatory responses by inhibiting microglial STAT3 signaling. Although the mechanisms involve in the anti-inflammatory effects of MC have not yet been reported, such effects might be indirectly explained by the positive effects of representative norteripenoids. For example, C21 nortriterpenoid (16,17-dehydroapplanone E), isolated from Ganoderma applanatum, can inhibit the secretion of NO in 3-NPA-induced BV-2 cells . Ulmoidol, an unusual nortriterpenoid from Eucommia ulmoides Oliv. leaves, can suppress the production of proinflammatory mediators (TNF-a, IL-1b, IL-1, and PGE2) and reduce the expression of iNOS and COX-2 in 3-NPA-treated BV-2 cells . Additionally, a nortriterpenoid (compound 2) from the fruits of Evodia rutaecarpa shows neuroprotective activities against serum-deprivation-induced P12 cell damage . Taken together, these findings suggest that MC from S. chinensis might possess remarkable anti-inflammatory activity, which improves the neurological disorders associated with HD-like symptoms. 5. Conclusions The exact mechanism underlying neuronal death and valuable therapeutics in HD-like symptoms has not yet been fully elucidated. Here, we found that MC could mitigate the striatal degeneration related to reduced inflammatory response and mHTT expression by inhibiting STAT3 signaling in microglia. Despite the relative lack of information on the efficacy and critical mechanisms of action of MC, our findings indicate that MC might be used as a potential therapeutic to improve HD-like symptoms by regulating the microglial STAT3 pathways. We also propose that it is necessary to determine the efficacy and mechanisms of action of MC in various pathological conditions, including neurological disease, in future works, in addition to identifying its chemical interactions in vivo. Supplementary Materials The following supporting information can be downloaded at: Supplementary Materials: Primer sequences used for real-time polymerase chain reaction (PCR) analyses; Supplementary Data S1: Original images from Western blot assay. Supplementary Data S2: MC inhibits microglial migration and activation in striatum after 3-NPA treatment (a low magnification) Click here for additional data file. Author Contributions Conceptualization, D.S.J. and I.-H.C.; investigation, M.J. and J.H.C.; resources, D.S.J.; writing--original draft preparation, M.J. and I.-H.C.; writing--review and editing, D.S.J. and I.-H.C.; funding acquisition, I.-H.C. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was approved by the Institutional Animal Care and Use Committee of Kyung Hee University (KHUASP-19-018). Informed Consent Statement This study did not involve any human participants. Data Availability Statement The data for this study are available from the corresponding authors upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 MC alleviates neurological dysfunction and improves survival rate after 3-NPA treatment. (A-C) Effects of MC on neurological score (motor disability), survival rate, and BW during 3-NPA treatment period. MC was intravenously treated once daily for 5 days 1 h before 3-NPA treatment. At 24 h after the last (5th) 3-NPA treatment, the neurological score (A), survival rate (B), and BW (C) of mice from sham (n = 7), 3-NPA (n = 7), 3-NPA + MC (1.25 mg/kg/day; n = 7), 3-NPA + MC (2.5 mg/kg/day; n = 7) and MC (2.5 mg/kg/day; n = 7) groups were measured. For the neurological score, levels of global activity, hindlimb clasping, hindlimb dystonia, truncal dystonia, and balance adjustment to a postural challenge were measured and their values were combined. N.D., not detected. In graph B, the values above the bars represent survival rates (number of surviving animals/number of total animals). Data are expressed as mean +- standard error of the mean (SEM) (Kruskal-Wallis; ## p < 0.01 versus sham group; * p < 0.05 and ** p < 0.01 versus 3-NPA group). Figure 2 MC prevents neurodegeneration and apoptosis in the striatum after 3-NPA treatment. (A-F) At 24 h following the last (5th) 3-NPA treatment, striata from sham (n = 5), 3-NPA (n = 5), 3-NPA + MC (2.5 mg/kg/day; n = 5), and MC (2.5 mg/kg/day; n = 5) groups were subjected to histopathological and Western blot analyses to investigate the effect of MC (2.5 mg/kg/day, i.v.) on striatal cell death and apoptosis. (A-C) Representative photographs showing the level of striatal lesion by cresyl violet staining (A). MC significantly reduced the number of mice with striatal lesion (B) and the lesion area (C). Asterisk, S, and C indicate striatal lesions, normal striatum, and normal cortex, respectively. Scale bar = 100 mm. N.D., not detected. Data are expressed as mean +- SEM (Kruskal-Wallis; # p < 0.05 and ## p < 0.01 versus sham group; * p < 0.05 and ** p < 0.01 versus 3-NPA group). (D,F,G) Striata from all groups were analyzed by Western blot to determine the expression level of SDHA (D), cleaved caspase-9 (G,H), cleaved caspase-3 (G,I), and Bcl-2 (G,J). MC prevented the enhancement of these protein expressions. (E,F) Representative photographs (E) and quantified graph (F) showing the level of striatal cell death by FJC staining. MC significantly reduced the number of FJC (+) cells. Scale bar = 200 mm. Data are expressed as mean +- SEM (Kruskal-Wallis; ## p < 0.01 versus sham group; * p < 0.05 and ** p < 0.01 versus 3-NPA group). Figure 3 MC inhibits microglial migration and activation in striatum after 3-NPA treatment. (A-F) Twenty-four hours after the last (5th) 3-NPA treatment, striata from sham, 3-NPA, 3-NPA + MC (2.5 mg/kg/day), and MC (2.5 mg/kg/day) groups were used to investigate the levels of migration of microglia and infiltration of macrophages. MC prevented the migration and activation of Iba-1 immunoreactive cells by immunohistochemistry ((A); n = 5 per group), the mean area of Iba-1 immunoreactive cells ((B): n = 5 per group)' the expression of Iba-1 protein by Western blot assay ((C): n = 5 group). MC reduced the level of migration of resident microglia (R3; CD11b+/CD45+low; (D,E)) by flow cytometry (n = 3 per group), but did not significantly affect the infiltration of peripheral macrophage (R4; CD11b+/CD45+high; (D,F)). Scale bar = 100 mm. The small box inside the upper panel of a was enlarged on the lower panel. N.D., not detected. Data are expressed as mean +- SEM (Kruskal-Wallis; ## p < 0.01 versus sham group; * p < 0.05 and ** p < 0.01 versus 3-NPA group). Figure 4 MC reduces the mRNA or protein expression levels of inflammatory factors and p-STAT3 in striatum or microglia after 3-NPA treatment. (A-F) Twelve hours after the last (5th) 3-NPA-treatment, striatal tissues from sham (n = 5), 3-NPA (n = 5), 3-NPA + MC (2.5 mg/kg/day; n = 5), and MC (2.5 mg/kg/day; n = 5) groups were analyzed by real-time PCR. MC reduced mRNA expression levels of representative inflammatory enzymes (COX-2 (A) and iNOS (B)), cytokines (IL-1b (C), IL-6 (D), and TNF-a (E)), and chemokine (MCP-1 (F)). (G) Twenty-four hours after the last (5th) 3-NPA-treatmentn, striatal laysats from all groups (n = 5 group) were subjected to Western blot analysis. MC reduced protein expression of p-STAT3. Data are expressed as mean +- SEM (Kruskal-Wallis; # p < 0.05 and ## p < 0.01 versus sham group; * p < 0.05 and ** p < 0.01 versus 3-NPA group). (H-J) Twenty-four hours after the last (5th) 3-NPA-treatment, 3 striatal sections from all groups (n = 5) were subjected to immunofluorescent staining using mixtures of p-STAT3/CD11b antibodies. Red, green, and yellow colors show p-STAT3+, CD11b+, and p-STAT3+/CD11b+, respectively (H). The numbers of p-STAT3 (+) cells per 500 mm2 and the ratio of CD11b (+) cells containing p-STAT3 (+) signal were measured (I,J). MC reduced p-STAT3-immunoreactivity in the striatum and CD11b (+) cells. Scale bar = 200 mm. Data are expressed as mean +- SEM (Kruskal-Wallis; ** p < 0.01 versus 3-NPA group). Figure 5 MC reduces the expression of inflammatory factors and p-STAT3 in 3-NPA-induced BV2 cells. (A-G) Cultured BV2 cells were treated with MC (5 mM) at 1 h before stimulation with 3-nitropropionic acid (3-NPA) (1.0 mM). Culture medium was replaced with fresh medium and incubated for 12 h. BV2 cells from sham, 3-NPA, 3-NPA + MC (5 mM), and MC (5 mM) groups were used for Western blot analysis to determine protein expression levels of representative inflammatory enzymes (COX-2 (A,B) and iNOS (A,C)), cytokines (IL-1b (A,D), IL-6 (A and E), and TNF-a (A,F)), and p-STAT3 (A,G). MC alleviated their expression levels (A-G). Assays were repeated at least three times, with each experiment performed in triplicate. Data are expressed as mean +- standard error of the mean (Kruskal-Wallis; # p < 0.05 and ## p < 0.01 versus sham group; * p < 0.05 and ** p < 0.01 versus 3-NPA group). Figure 6 MC enhances the activity of STHdh cells by inhibiting the expression of p-STAT3 in BV2 cells. (A-D) To obtain conditioned medium (CM) treated with MC, cultured BV2 cells were treated with MC (5 mM) before stimulation with 3-nitropropionic acid (3-NPA) (1.0 mM, 12 h). CM-3-NPA and CM-3-NPA-MC were used to treat STHdhQ111/Q111 (mutant) cells. STHdh cells were used for Western blot analysis to evaluate neurodegeneration using NeuN antibody (A,B) and huntingtin aggregation using EM48 and 2Q75 antibodies (A,C,D). Data are expressed as mean +- SEM (Kruskal-Wallis; # p < 0.05 vs. vehicle-treated Sham group; * p < 0.05 vs. 3-NPA-induced 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). 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PMC10000368 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051104 foods-12-01104 Communication Gas Chromatography with Flame-Ionization Detection-Based Analysis of Sugar Contents in Korean Agricultural Products for Patients with Galactosemia Jeong Ha-Neul 1 Kwon Ryeong Ha 1 Kim Yuri 2 Yoo Sang-Ho 3 Yoo Seon Mi 1 Wee Chi-Do 1* Castilho Paula C Academic Editor Haros Claudia Monika Academic Editor 1 Department of Agro-Food Resources, National Institute of Agricultural Sciences, Rural Development Administration, Wanju 55365, Republic of Korea 2 Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Republic of Korea 3 Department of Food Science & Biotechnology, and Carbohydrate Bioproduct Research Center, Sejong University, Seoul 05006, Republic of Korea * Correspondence: [email protected]; Tel.: +82-063-238-3719 05 3 2023 3 2023 12 5 110418 1 2023 13 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 ). Patients with galactosemia accumulate galactose in their bodies, requiring a lifelong galactose-restricted diet. Therefore, accurate information on the galactose content in commercial agro-food resources is essential. The HPLC method generally used for sugar analysis has low separation and detection sensitivity. Here, we sought to establish an accurate analytical method for determining the galactose content in commercial agro-food resources. To that aim, we employed gas chromatography with flame-ionization detection to detect trimethylsilyl-oxime (TMSO) sugar derivatives (concentration: <=0.1 mg/100 g). The galactose content in 107 Korean agro-food resources reflecting intake patterns was then analyzed. The galactose content in steamed barley rice was 5.6 mg/100 g, which was higher than that in steamed non-glutinous and glutinous rice. Moist-type and dry-type sweet potatoes, blanched zucchini, and steamed Kabocha squash had high galactose content (36.0, 12.8, 23.1, and 61.6 mg/100 g, respectively). Therefore, these foods are detrimental to patients with galactosemia. Among fruits, avocado, blueberry, kiwi, golden kiwifruit, and sweet persimmon had galactose contents of >=10 mg/100 g. Dried persimmon had 132.1 mg/100 g and should therefore be avoided. Mushrooms, meat, and aquatic products showed low galactose content (<=10 mg/100 g), making them safe. These findings will help patients to manage their dietary galactose intake. galactosemia galactose content commercial agro-food gas chromatography flame-ionization detection Cooperative Researcher Program for Agricultural Science and Technology DevelopmentPJ0156002022 Collaborative Research Program between University and RDA' of the National Institute of Agricultural Sciences, Rural Development Administration (RDA), Republic of KoreaThis study was supported by the 'Cooperative Researcher Program for Agricultural Science and Technology Development (Project No. PJ0156002022)' and 'Collaborative Research Program between University and RDA' of the National Institute of Agricultural Sciences, Rural Development Administration (RDA), Republic of Korea. pmc1. Introduction Currently, an average of about 40,000 newborns, equivalent to approximately 10% of the total number of deliveries, are born with congenital abnormalities. According to the statistics from 10,000 births over the last 10 years, there has been an approximately threefold increase in the number of newborns with congenital abnormalities. About 300 hereditary metabolic diseases are currently known, and approximately 100 of them appear in the neonatal period. Dietary substrate restriction to reduce the utilization of abnormal metabolic pathways is a necessary treatment for some hereditary metabolic diseases . Galactosemia is a genetic disease in which galactose accumulates in the body due to a deficiency of enzymes galactokinase (GALK), UDP-galactose 4-epimerase (GALE), and galactose-1-phosphate uridylyltransferase (GALT) involved in the metabolic process that converts galactose into glucose. The birth frequency of sick children in Korea calculated based on the results of the newborn screening test conducted in 2005 was reported to be approximately one in 40,000 . If treatment is delayed, galactosemia can cause fatal complications such as mental retardation, spasticity, cataracts, breastfeeding problems, hypoglycemia, stunted growth, jaundice, hepatocellular damage, hemorrhage, and E. coli sepsis. However, once treatment is started with rapid diagnosis, lifespan can be normal, and neurodevelopment can be improved . The sugars contained in food are either naturally present or added during processing . These not only improve flavor and prolong the storage period but also act as an essential energy source in the body. However, patients with galactosemia are deprived of breastfeeding and must follow a strict lifelong galactose-restricted diet . Currently, there is not much information on the trace amounts of galactose contained in agro-food resources. In Korea, patients with galactosemia manage their diet based on galactose content information (number of foods: 276), which is provided in precision units by the US Galactosemia Foundation as a standard for managing dietary intake. However, this information is for food produced and consumed in the United States, there is no information for each stage of cooking and processing, and most of the information is outdated (i.e., obtained before 2000). Therefore, it is difficult to apply to Korean patients. A simple and rapid high-performance liquid chromatography (HPLC) method has recently been adopted in many laboratories and most studies for the quantitative analysis of sugars, including galactose, in food. However, when a refractive index (RI) or evaporative light scattering (ELS) detector is used, the sensitivity and resolution are low, hindering the analysis of samples at low concentrations . Therefore, it is difficult to use the data for the management of galactosemia. In addition, carbohydrate and NH2 columns used to separate glucose and galactose, and epimer are expensive. Therefore, a more economic and accurate method using other universal instruments is sorely needed. Gas chromatography/mass spectrometry (GC/MS) equipped with a capillary column is generally used to analyze volatile organic compounds. GC analysis of saccharides with relatively low molecular weight is performed by derivatizing the hydroxyl groups present in their structures. Among them, trimethylsilyl (TMS) and trimethylsilyl-oxime (TMSO) derivatization methods are widely used . In fact, in the case of capillary GC analysis equipped with a flame ionization detector (FID), the detector's sensitivity is higher than that of HPLC analysis. Accordingly, it is possible to analyze low-concentration saccharides contained in the sample at the ppm level, and the peak resolution is superior to that of HPLC . Therefore, GC/MS is advantageous because it provides relatively high qualitative and quantitative properties in samples containing complex substrates and economic efficiency due to the long-term use of the column. For patients with galactosemia, GC/FID analysis of low-concentration galactose contained in agro-food resources is rare . Almost all available data on galactose content in foods are provided by the US Galactose Foundation. However, these data only reflect the galactose content in raw food and do not consider processing and type of intake. Furthermore, the data are very limited. Therefore, patients with galactosemia are at risk of complications because of the lack of information. Here, our aim was to analyze the content of sugars, including galactose, in agro-food resources produced and consumed in Korea to provide nutritional guidance for patients with galactosemia. 2. Materials and Methods 2.1. Sample Selection Agricultural samples are the top foods consumed according to the Korea Rural Economic Institute's food balance sheet, national reports, and statistical data. We screened for foods high in sugar requested for analysis by patients with galactosemia, guardians, and clinical nutritionists, and consumed by multiple persons during a meal survey using the 24-h recall method for children with galactosemia and general children . A total of 107 species were selected as follows: 17 cereals and their products, seven potatoes and starches, 11 beans, five mushrooms, 16 vegetables, 25 fruits, 17 meats and eggs, and nine seafoods. All samples were purchased, then freeze-dried and pulverized for use in the experiments. 2.2. Standards and Reagents Standards (glucose, galactose, fructose, sucrose, lactose, and maltose), hexamethyldisilazane (HMDS), trifluoro acetic acid (TFA), pyridine, and hydroxylamine hydrochloride were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA). Other reagent-grade chemicals and HPLC-grade solvents (ethanol, methanol, and water) were obtained from Thermo Fisher Scientific (Waltham, MA, USA). The sugar standard solution was prepared by weighing 50 mg of each of the standards in a 50 mL volumetric flask and dissolving it in 50% methanol. The solutions were stored in a refrigerator at 4 degC until further use in the experiments. Phenyl b-d-glucopyranoside (Sigma-Aldrich) was used as an internal standard. 2.3. Sample Preparation After lyophilization, 2 g of the homogenized sample was weighed, placed in 10 mL of 60% ethanol, kept in an 85 degC water bath for 30 min, and then cooled. The extract was centrifuged at 3600 rpm for 20 min. The supernatant was added to 0.5 mL of 10% lead acetate followed by centrifugation at 3600 rpm for 20 min to remove the proteins. The supernatant was added to 10% oxalic acid to precipitate the surplus lead acetate. The collected extract was filtered through a Whatman No.1 filter paper. The sample was then quantitatively transferred to a 50 mL volumetric flask and diluted to mark with 60% ethanol. One mL aliquots of each extract and 0.5 mL of the internal standard were added and concentrated using N2 gas. 2.4. TMSO Derivatization TMSO derivatization was conducted as previously described with slight modifications . Briefly, 500 mL of hydroxylamine hydrochloride solution dissolved in pyridine at a concentration of 25 mg/mL was added to the concentrated dry residue, stirred in a water bath at 75 degC for 30 min, and cooled at room temperature for 30 min. Then, 450 mL of HMDS and 50 mL of TFA were added and mixed thoroughly. The reaction mixture was subsequently derivatized in a water bath at 85 degC for 60 min and cooled at room temperature for 60 min. For GC analysis, the sample was filtered using a 0.22 mm PVDF membrane filter, placed in GC vials, and used for analysis. 2.5. GC/FID Analysis Conditions GC separation of six free sugars was performed using an Agilent 7890A GC system equipped with an automatic sampler and an FID following a previously described method with slight modifications . Two-microliter samples were injected. Free sugars were separated using a non-polar HP-5 column (30 m x 0.25 mm x 0.25 mm; Agilent Technologies). The injection and detector temperatures were set at 280 degC and 300 degC, respectively. N2 was used as a carrier gas, and samples were separated at a rate of 0.9 mL/min. Table 1 shows the heating conditions of the oven. All samples were performed in duplicate. 3. Results and Discussion 3.1. Resolution of GC for TMSO Sugar Derivatives The chromatogram of the GC/FID system for six free sugar standard solutions and an internal standard solution is shown in Figure 1. All sugars were separated without interfering peaks in the order of fructose, galactose, glucose, sucrose, maltose, and lactose. The retention time (RT) values were 14.566, 16.203, 16.699, 26.978, 28.602, 29.563, and 24.03 min for fructose, galactose, glucose, sucrose, lactose, maltose, and the internal standard, respectively. All were detected within 30 min. TMSO derivatization was performed by preparing six free sugar standard solutions at concentrations of 0.1, 0.2, 0.4, 1, 2, 5, 10, and 20 mg/100 g; a calibration curve for the standard material was prepared to validate the analytical method. The calibration curve's determination coefficients (R2) were 0.9995, 0.9992, 0.9992, 0.9992, 0.9989, and 0.9986 for fructose, galactose, glucose, sucrose, lactose, and maltose, respectively. All six free sugars showed excellent linearity . The limit of detection (LOD) and limit of quantification (LOQ) were calculated to determine the minimum detectable and quantifiable concentration of fructose, glucose, galactose, sucrose, maltose, and lactose and thus verify the accuracy of the analysis. In each standard chromatogram, the LOD was the value obtained by multiplying the standard deviation of 10 noise peak area values in the blank by three and adding the average, while the LOQ was the value obtained by adding the average to the value multiplied by 10, as in the method previously described . The LOD was 0.2137, 0.3445, 0.2972, 0.1216, 0.0361, and 0.0523 mg/100 g for fructose, galactose, glucose, sucrose, lactose, and maltose, respectively; the LOQ was 0.6477, 1.0439, 0.9005, 0.3685, 0.1093, and 0.1585 mg/100 g, respectively. These LOD and LOQ values are lower than 5-20 mg/100 g of LOD achieved by HPLC/ELSD or HPLC/RID according to previous studies , demonstrating that the GC/FID method after TMSO derivatization allows detection at lower concentrations (Table 2). 3.2. Analysis of Free Sugars in Agro-Food Resources Separation and quantification of fructose, galactose, glucose, sucrose, maltose, and lactose were simultaneously performed on 107 agro-food resource samples using the GC/FID analysis method established in this study. Table 3 shows the results of quantifying galactose in precise units for patients with galactosemia, the purpose of this study. The galactose content of cereals, including rice cakes, and their products ranged from 0 to 12.6 mg/100 g. Galactose was not detected in steamed non-glutinous rice and glutinous rice, whereas steamed barley rice contained a relatively high level of galactose (5.6 mg/100 g), which is harmful to patients with galactosemia. The galactose content in boiled somyeon was 6.8 mg/100 g, which was higher than that in spaghetti (3.20 mg/100 g) or buckwheat (0.5 mg/100 g) noodles. The galactose content in steamed corn was 5.0 mg/100 g, which was relatively high. Sirutteock had a high galactose content of 12.6 mg/100 g due to the influence of gomul. The galactose content in steamed and roasted superior potatoes was 4.6 mg/100 g and 5.5 mg/100 g, respectively. The galactose content in steamed Japanese and Garnet sweet potatoes was 12.8 mg/100 g and 36.0 mg/100 g, respectively. Therefore, these are very harmful foods for patients with galactosemia. However, galactose was not detected in starch prepared from sweet potato, potato, or corn. Beans, nuts, and seeds generally showed a low galactose content of less than 3 mg/100 g. However, boiled chestnuts had a high content (16.8), making them dangerous foods for patients with galactosemia. Boiled red beans showed a low galactose content of 0.2 mg/100 g, but red bean paste showed a high galactose content of 58.3 mg/100 g due to the influence of additives. One study stated that free galactose is affected by cultivar differences. The storage time of fruits and vegetables and galactose content in vegetables in this study also showed a wide distribution range of 0-61.6 mg/100 g. The galactose content in frequently and heavily consumed foods such as napa cabbage, ugeoji, green onion, and lettuce showed a low value of less than 5 mg/100 g. Iceberg lettuce and perilla leaf showed high galactose contents of 29.1 mg/100 g and 10.5 mg/100 g, respectively. Blanched zucchini and steamed Kabocha squash showed high galactose contents of 23.1 mg/100 g and 61.6 mg/100 g, respectively, making them very harmful to patients. The galactose content in mushrooms was relatively low, ranging from 0.2 to 3.5 mg/100 g. The galactose content in fruits showed a wide distribution, ranging from 0 to 132.1 mg/100 g. The galactose content in avocado, blueberry, kiwifruit, and golden kiwifruit was higher than 10 mg/100 g. Sweet persimmon showed a slightly higher galactose content of 13.4 mg/100 g, while dried persimmon showed an exceptionally high galactose content of 132.1 mg/100 g, making it a food that patients should avoid. Both meat and aquatic products were safe food groups for patients with galactosemia, as they showed a relatively low galactose content of less than 10 mg/100 g. The content in fried eggs was relatively high, ranging from 6.6 to 8.5 mg/100 g. In the case of meat, the galactose content in blanched meat was lower than that in grilled meat. Therefore, free sugar may be dissociated and released during steaming. Galactose, a water-soluble substance, is often released from food into the cooking water during wet cooking. Therefore, removing the used cooking water can effectively reduce the galactose content. However, since wet cooking using heat can significantly reduce the palatability of food, it is necessary to use an appropriate wet cooking method. 4. Conclusions Patients with galactosemia find it difficult to manage their diets while eliminating galactose, which is contained in trace amounts in agricultural food resources. In this study, 107 commercially available agri-food resources frequently consumed by Koreans were analyzed for galactose content according to intake type using a GC system equipped with an FID detector. Galactose, which is present in food in small amounts, was analyzed at the level of 0.01 mg/100 g, and the contents were classified according to food groups. The sensitivity of the method was much higher than that of the widely used HPLC analytical method. The galactose content in steamed pearl barley, garnet sweet potato, blanched zucchini, and steamed Kabocha squash was very high. Thus, these are harmful foods for patients with galactosemia. Among fruits, the galactose content in avocado, blueberry, kiwifruit, golden kiwifruit, and sweet persimmon was relatively high, while dried persimmon showed a remarkably high galactose content and must be avoided by patients. Mushrooms, meat, and aquatic products showed low galactose content, making them safe for patients with galactosemia. Our findings will help patients in Korea to manage their diets. However, access to processed foods has increased greatly in recent years, posing a risk to patients with galactosemia. Therefore, the galactose content in processed foods also needs to be accurately determined. Author Contributions Conceptualization: C.-D.W. and S.M.Y.; Data curation: H.-N.J., R.H.K. and C.-D.W.; Formal analysis: H.-N.J. and R.H.K.; Funding acquisition: C.-D.W. and S.M.Y.; Investigation: H.-N.J. and C.-D.W.; Methodology: H.-N.J. and S.-H.Y.; Project administration: C.-D.W. and S.M.Y.; Resources: Y.K. and H.-N.J.; Software: H.-N.J.; Supervision: C.-D.W., Y.K., S.-H.Y. and S.M.Y.; Validation: H.-N.J. and S.-H.Y.; Visualization: H.-N.J., R.H.K. and C.-D.W.; Writing--original draft: H.-N.J., Writing--review & editing: C.-D.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 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. Figure 1 Chromatogram of the separation of six major free sugars by gas chromatography/flame ionization detector (GC/FID). 1 = fructose, 2 = galactose, 3 = glucose, 4 = sucrose, 5 = lactose, 6 = maltose, IS = Internal Standard. Figure 2 Linearity and determination coefficients (R2) of the calibration curves for six major free sugars by GC/FID. (A) = lactose, (B) = fructose, (C) = galactose, (D) = glucose, (E) = sucrose, (F) = maltose, IS = Internal Standard. foods-12-01104-t001_Table 1 Table 1 GC/FID analysis conditions for accurate analysis of galactose content. Item Condition Instrument GC-FID (Agilent 7890A) Column Agilent HP-5 (30 m x 0.25 mm x 0.25 mm) Gradient Rate Value Hold Time Run Time Initial 180 degC 5 min 5 min Ramp 1 1 degC/min 195 degC 0 min 20 min Ramp 2 20 degC/min 280 degC 10 min 34.25 min Ramp 3 50 degC/min 295 degC 3 min 34.75 min Ramp 4 30 degC/min 180 degC 3 min 44.383 min Flow rate 0.9 mL/min Inlet temp. 280 degC Detector Flame Ionization Detector (FID) Injection vol. 2 mL Split ratio 10:1 foods-12-01104-t002_Table 2 Table 2 LOD and LOQ of GC/FID for six major free sugar standards. Free Sugar Standard Deviation (s) Slope of the Calibration Curve (S) Limit of Detection (LOD) (mg/100 g) Limit of Quantitation (LOQ (mg/100 g) Fructose 3.3011 5.0964 0.2137 0.6477 Galactose 7.0147 6.7199 0.3445 1.0439 Glucose 6.5372 7.2594 0.2972 0.9005 Sucrose 2.5364 6.8827 0.1216 3.68520 Lactose 0.6032 5.5205 0.0361 0.1093 Maltose 0.8429 5.3172 0.0523 0.1585 foods-12-01104-t003_Table 3 Table 3 Galactose content in different agricultural food resources according to intake type. Food Group No. Sample Galactose Content (mg/100 g FW) No. Sample Galactose Content (mg/100 g FW) Cereals and their products 1 flour (cake flour) 4.73 +- 0.11 10 corn, steamed 5.04 +- 0.40 2 flour (bread flour) 3.99 +- 0.28 11 Baek-seolgi 1.94 +- 0.46 3 non-glutinous rice, white rice nd 12 Songpyeon, sesame 0.61 +- 0.87 4 glutinous rice, steamed nd 13 Jeungpyeon 3.94 +- 0.50 5 pearl barley, steamed 5.57 +- 0.34 14 wheat Tteok-bokki rice cake (boiled) 3.49 +- 0.55 6 brown rice, steamed 2.00 +- 0.12 15 rice cake soup (boiled) nd 7 spaghetti, boiled 3.21 +- 0.03 16 Sirutteock 12.63 +- 0.91 8 somyeon, boiled 6.76 +- 5.22 17 Injeolmi nd 9 buckwheat noodles, boiled 0.53 +- 0.24 Potatoes and starches 1 superior, steamed 4.63 +- 0.03 5 sweet potato starch nd 2 superior, roasted 5.51 +- 0.22 6 potato starch nd 3 Japanese sweet potato, steamed 12.75 +- 0.29 7 corn starch nd 4 Garnet sweet potato, steamed 36.01 +- 0.38 Beans, nuts, and seeds 1 soybean, boiled 1.26 +- 0.04 7 almond, roasted nd 2 green flesh black bean, boiled 2.07 +- 0.06 8 chestnut, boiled 16.79 +- 0.18 3 red bean, boiled 0.16 +- 0.09 9 peanut, roasted 3.63 +- 0.49 4 red bean paste 58.34 +- 2.58 10 sesame, white sesame, roasted nd 5 soybean sprout, blanched 1.13 +- 0.01 11 perilla, roasted nd 6 soybean sprout, steamed 0.98 +- 0.10 Mushrooms 1 oyster mushroom, blanched 0.19 +- 0.27 4 enoki mushroom, blanched 0.08 +- 0.12 2 shiitake mushroom, blanched 3.15 +- 0.38 5 matsutake, grilled 3.54 +- 0.06 3 white button mushroom, grilled 0.57 +- 0.12 Vegetables 1 napa cabbage, boiled 2.18 +- 0.26 9 perilla leaf 10.48 +- 0.25 2 napa cabbage, ugeoji, boiled nd 10 spinach, blanched 1.89 +- 0.16 3 garlic, parboiled 1.27 +- 0.18 11 zucchini, blanched 23.09 +- 1.16 4 green onion, blanched 4.74 +- 0.05 12 broccoli, blanched 5.89 +- 0.50 5 carrot, blanched 11.36 +- 0.51 13 paprika, roasted 10.61 +- 0.46 6 tomato 6.36 +- 0.02 14 cucumber 4.30 +- 0.09 7 lettuce 3.96 +- 0.03 15 eggplant, blanched 5.27 +- 0.18 8 iceberg lettuce 29.08 +- 1.74 16 Kabocha squash, steamed 61.56 +- 4.41 Fruits 1 tangerine (citrus unshiu) nd 14 Cherry 6.90 +- 0.66 2 tangerine (dekopon) 3.88 +- 0.52 15 sweet persimmon 13.41 +- 3.37 3 tangerine (setoka) 6.30 +- 1.40 16 dried persimmon 132.09 +- 3.71 4 apple (Fuji) 5.42 +- 0.11 17 ripe persimmon 7.06 +- 0.48 5 aori apple nd 18 plum 7.47 +- 0.25 6 banana 6.47 +- 0.45 19 kiwifruit 21.05 +- 0.99 7 peach (nectarine) 3.99 +- 0.51 20 Golden kiwifruit 11.45 +- 0.49 8 peach (white peach) 3.12 +- 0.19 21 grapefruit nd 9 pear 8.52 +- 0.17 22 watermelon 4.95 +- 0.25 10 strawberry (sulhyang) 2.46 +- 0.15 23 lemon 6.67 +- 1.19 11 avocado 10.05 +- 0.21 24 pineapple 2.45 +- 0.19 12 blueberries 13.43 +- 0.70 25 green grape nd 13 mango 0.63 +- 0.89 Meat and eggs 1 beef, sirloin, grilled 5.76 +- 0.17 10 whole egg, boiled 3.64 +- 0.24 2 beef, beef plate, boiled 2.53 +- 0.09 11 whole egg, fried, hard-boiled 6.64 +- 0.46 3 pork, pork belly, grilled 6.33 +- 0.06 12 whole egg, fried, soft-boiled 7.21 +- 0.80 4 pork, sirloin, boiled 3.12 +- 0.34 13 egg yolk, boiled 5.27 +- 0.14 5 chicken, boiled 0.27 +- 0.38 14 egg yolk, fried, hard-boiled 8.48 +- 0.45 6 chicken, leg, grilled 0.27 +- 0.00 15 egg yolk, fried, soft-boiled 8.12 +- 0.51 7 chicken, breast, grilled nd 16 scrambled egg, roasted 5.55 +- 0.16 8 Tea-smoked duck (grilled) 6.73 +- 0.53 17 quail egg, boiled 2.87 +- 0.28 9 pork liver, boiled 5.97 +- 0.53 Aquatic products 1 mackerel, grilled 3.24 +- 0.16 6 pollack, dried pollack, dried 2.04 +- 0.16 2 hairtail, grilled 3.46 +- 0.79 7 mussel, boiled 0.66 +- 0.02 3 squid, blanched 0.70 +- 0.01 8 clam, boiled 1.25 +- 0.04 4 stir-fried anchovy, stir-fried baby anchovy nd 9 abalone, boiled 5.71 +- 0.72 5 anchovy broth nd 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. Sohn Y.B. A Diagnostic Algorithm of Newborn Screening for Galactosemia J. Korean Soc. Inher. Metab. Dis. 2015 15 101 109 2. Lee J.S. Treatment and management of patients with inherited metabolic diseases Korean J. Pediatr. 2006 49 1152 1157 10.3345/kjp.2006.49.11.1152 3. Kerckhove K.V. Diels M. Vanhaesebrouck S. Luyten K. Pyck N. De Meyer A. Van Driessche M. Robert M. Corthouts K. Caris A. Consensus on the guidelines for the dietary management of classical galactosemia Clin. Nutr. ESPEN 2015 10 e1 e4 10.1016/j.clnme.2014.10.001 28531441 4. Mattews R. Pehrsson P. Farhat-Sabet M. Sugar content of selected foods: Individual and total sugars Home Economics Research Report No. 48 U.S. Department of Agriculture (USDA) Hyattsville, MD, USA 1987 1 5. Havel P.J. Dietary fructose: Implications for dysregulation of energy homeostasis and lipid/carbohydrate metabolism Nutr. Rev. 2005 63 133 157 10.1111/j.1753-4887.2005.tb00132.x 15971409 6. Won S.Y. Seo J.S. Kang H.Y. Lee Y.S. Choi Y. Lee H.K. Park I.T. Rapid Quantitative Analysis for Sugars of Agricultural Products by HPLC Food Eng. Prog. 2016 20 406 410 10.13050/foodengprog.2016.20.4.406 7. Jeong D.U. Im J. Kim C.H. Kim Y.K. Park Y.J. Jeong Y.H. Om A.S. Sugar Contents Analysis of Retort Foods J. Korean Soc. Food. Sci. Nutr. 2015 44 1666 1671 10.3746/jkfn.2015.44.11.1666 8. Harvey D.J. Derivatization of carbohydrates for analysis by chromatography; electrophoresis and mass spectrometry J. Chromatogr. B Analyt. Technol. Biomed. Life. Sci. 2011 879 1196 1225 10.1016/j.jchromb.2010.11.010 9. Ruiz-Matute A.I. Hernandez-Hernandez O. Rodriguez-Sanchez S. Sanz M.L. Martinez-Castro I. Derivation of carbohydrates for GC and GC-MS analyses J. Chomatogr. B Analyt. Technol. Biomed. Life. 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A 2004 1059 143 148 10.1016/j.chroma.2004.09.095 15628134 15. Kim W. Lee H. Won M. Yoo S. Germination effect of soybean on its contents of isoflavones and oligosaccharides Food Sci. Biotechnol. 2005 14 489 502 16. Islam M.A. Lee J. Yoo S. Effect of oximation reagents on gas chromatographic separation of eight different kinds of di-saccharides Food Chem. 2022 386 132797 10.1016/j.foodchem.2022.132797 35344725 17. Thompson M. Elison S.L.R. Wood R. Harmonized guideline for single-laboratory validation of methods of analysis Pure Appl. Chem. 2002 74 835 855 10.1351/pac200274050835 18. Jim V.J.W. Analysis of Free Galactose Contents during Cold Storage of Four Apple Cultivars, in Thermally Treated Apples and Green Beans, and in Clear Apple Juices Produced Using Different Enzymatic Aids Ph.D. Thesis University of British Columbia Vancouver, BC, Canada 2002 |
PMC10000369 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050709 healthcare-11-00709 Article Improving Medical Student Anatomy Knowledge and Confidence for the Breast Surgical Oncology Rotation Wilder Chloe Conceptualization Methodology Data curation Writing - original draft Writing - review & editing 1 Kilgore Lyndsey J. 2 Fritzel Abbey Conceptualization Methodology Data curation Writing - original draft 1 Larson Kelsey E. Conceptualization Methodology Formal analysis Data curation Writing - original draft Writing - review & editing Supervision 2* Pavlik Edward J. Academic Editor 1 School of Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA 2 Breast Surgery Division, Department of Surgery, University of Kansas Medical Center, Kansas City, KS 66160, USA * Correspondence: [email protected] 27 2 2023 3 2023 11 5 70915 11 2022 13 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 ). Background: The anatomy curriculum has undergone considerable reductions in class time, resulting in decreased student anatomical knowledge retention and confidence during their surgical rotations. To counter this deficit in anatomy knowledge, a clinical anatomy mentorship program (CAMP) was developed by fourth-year medical student leaders and staff mentors in a near-peer teaching fashion prior to the surgical clerkship. This study analyzed the impact this program had on third-year medical students (MS3s) self-assessed anatomical knowledge and confidence in the operating room on the Breast Surgical Oncology rotation after this near-peer program. Methods: A single-center prospective survey study was performed at an academic medical center. post-program surveys were administered to all students who participated in the CAMP and rotated on the breast surgical oncology (BSO) service during the surgery clerkship rotation. A control group of individuals who did not rotate on the CAMP was established, and this group was administered a retrospective survey. A 5-point Likert scale was used to assess surgical anatomy knowledge, confidence in the operating room, and comfort in assisting in the operating room. Control group versus post-CAMP intervention group and post-CAMP intervention groups survey results were compared using the Student's t-test with a p-value of <0.05 statistically significant. Results: All CAMP students rated their surgical anatomy knowledge (p < 0.01), confidence in the operating room (p < 0.01), and comfort in assisting in the operating room (p < 0.01) as greater than those who did not participate in the program. Additionally, the program improved the ability of third-year medical students to prepare for operating room cases going into their third-year breast surgical oncology clerkship (p < 0.03). Conclusions: This near-peer surgical education model appears to be an effective way to prepare third-year medical students for the breast surgical oncology rotation during the surgery clerkship by improving anatomic knowledge and student confidence. The program can serve as a template for medical students, surgical clerkship directors, and other faculty interested in efficiently expanding surgical anatomy at their institution. anatomy medical education surgery education breast surgery dissection This research received no external funding. pmc1. Introduction Historically, a deep understanding of anatomy to diagnose and treat patients was considered the cornerstone of medicine. However, in recent decades, a drastic shift has occurred so that anatomy is now only a small part of modern medical education . Reports from the early 1900s indicate that American medical students spent over 800 hours mastering anatomy . In the 1950s, the number of hours had dropped to below 350 with recent data suggesting students now spend less than 150 hours in the anatomy lab . Furthermore, anatomy is often presented in self-directed and team-based learning models, which lack cadaveric dissection . Shifting the emphasis away from cadaver lab experience has led to decreased anatomical knowledge amongst medical school graduates . A survey of general surgery residency program directors demonstrated that over half of the program directors believed incoming residents were less prepared than residents ten years prior . Medical students agree that anatomy teaching is not meeting their needs and feel inadequately prepared to use their knowledge of anatomy in practice . Medical educators agree that anatomy must remain a core subject, as physicians must be experts in distinguishing normal versus pathologic variants, a skill that begins with a foundation in anatomic knowledge . Without proper anatomical knowledge, surgeons may be insufficient at investigating and intervening on behalf of their patients . In addition, anatomic errors are linked to increases in financial and litigious claims. The increase in litigious claims is related to some errors involving surrounding structures, pointing towards an inadequate understanding of anatomic relationships when performing procedures . 3D spatial reasoning is key when evaluating patient anatomical pathology, a process that begins with cadaveric dissection . Another issue that presents itself is knowledge retention. Preclinical students are known to score better on anatomical tests than surgical specialists ; however, there is a 50% drop in knowledge retention when first-year medical students begin their clinical 3rd-year rotations . Even junior doctors, who have recently graduated from medical school, are underperforming when tested on anatomy . These alarming results outline the issue of clustering anatomy education in the preclinical years and expecting students to retain or, at some level, regain anatomy sufficiency during clinical training. Ultimately, if anatomical knowledge is regained but not retained during rotations , this further stresses the critical need for repetition to ensure retention . When asked about their confidence in anatomy or their students' anatomy learning, students and faculty both express a desire for more time spent with cadavers and a longer timeline for learning . They also agree that the best way to learn during these cadaver prosections is in small student groups with qualified demonstrators . Other studies that implemented courses during or after clinical rotations reported increases in test scores when identifying anatomical structures and student confidence . More interesting is the idea that even a short refresher course is enough to increase scores greatly . Mid-course scores are not significantly improved from post-course scores, indicating that extra, post-preclinical anatomy courses do not need time from other curriculum areas to be effective. Vertical integration of continuing anatomy education throughout all years of the medical school curriculum is desired and proven to increase retention . Combining basic science anatomical content within clinical disciplines can enhance the retention of both core subjects . While this relationship is detailed, some faculty view preclinical basic science separately from clinically oriented anatomy and, therefore, teach it outside of the realm of functional understanding . Clinically relevant procedure rehearsals through small-group prosection initiate the process of surgical learning by reducing cognitive load without the added stress of patient outcomes . The transfer of anatomical knowledge past superficial memorization is increased by learning from kinetic examples in abstract problem-solving . This is exactly what small-group prosection in a clinical orientation led by qualified demonstrators aims to achieve. Near-peer teaching has been explored as a way for both tutor and tutee to become more confident when learning complex clinical anatomy . Therefore, students who receive proper training on how to teach a clinical topic become qualified demonstrators, feel more confident in themselves , and are respected as a reputable source of information from their tutees . Having an expert in the room to ask questions that the near-peer teachers may not know is recognized as necessary . However, peer teaching frees up many faculty to facilitate in-depth questions for larger groups of students while providing students an environment in which they are more comfortable engaging and asking questions of their peers. Since medical students spend less time in the anatomy lab, the Clinical Anatomy Mentorship Program (CAMP) was created to address these issues through a student-led initiative supervised by general surgery faculty. The CAMP details common operations to improve surgical anatomy confidence and spatial awareness through a clinical lens. The CAMP breast surgical oncology (BSO) prosection allows visuospatial familiarization with tangible anatomy while exposing third-year medical student (MS3) learners to the clinical functionality of the breast procedure in a low-stress, peer-teaching environment. This nested teaching of concrete examples with clinical relevance to a wider understanding of global anatomy leads to increased confidence in the learners and potentially longer retention of basic science knowledge rooted in clinical application. In this publication, we focused specifically on the BSO CAMP curriculum. We aimed to determine the impact of the curriculum on the students' self-assessed anatomical knowledge and confidence in the operating room (OR) by comparing students who did and did not experience the CAMP education. We hypothesized that the BSO CAMP would improve the students' knowledge and confidence for their subsequent MS3 surgical rotation. 2. Materials and Methods This single-institution study was approved by the Institutional Review Board (IRB). A list of MS3s who had completed the BSO rotation from June 2019 to May 2020 (prior to the implementation of the BSO CAMP education) was obtained from the clerkship director. This MS3 cohort served as the control group and was issued a retrospective, anonymous, and voluntary online survey designed to assess their knowledge and confidence during their MS3 surgery rotation. A second list of MS3s rotating on the BSO rotation during the surgery clerkship was obtained from the clerkship director prior to each eight-week clerkship from June 2020 to April 2021 in a prospective manner. This group served as the intervention group. All students assigned to the BSO rotation were invited to attend the BSO CAMP session prior to beginning their surgery clerkship and were issued anonymous post-CAMP surveys. 2.1. Establishing Baseline Data (Control Group) The control group survey explored the following themes: surgical anatomy knowledge, confidence in answering questions in the OR, comfort in assisting in the OR, and ability to prepare for surgical cases . Students were asked to give a rating in each of these areas based on a 5-point Likert rating scale (very poor, poor, fair, good, excellent). Students were asked to respond to these self-assessment questions as reflected at the end of their BSO rotation. The survey was issued in a retrospective fashion at a single point in time (June 2020); as a result, some students were closer versus further removed from their rotation. 2.2. Curriculum Details The primary teachers for the BSO CAMP were fourth-year medical students (MS4s) who had previously completed the BSO rotation. These individuals served as near-peer teachers for their MS3 colleagues prior to the start of their surgical rotation. During the CAMP sessions, the MS3 students worked directly with the MS4 teachers to review the curriculum, which included two clinical cases in conjunction with a prosection anatomy review of two common surgical cases on one Thiel-embalmed cadaver. In total, the students spent 1 hour reviewing the cases and procedures detailed below. The reference material was written by the breast surgical oncology faculty in a stepwise fashion to walk students through the patient evaluation and subsequent operation in an organized manner, mirroring what they would encounter on their surgical rotation. The two key surgical procedures were mastectomy and axillary lymph node dissection. The students were asked to identify critical anatomic landmarks on the prosection, key steps in the operation, and relevant clinical or pathophysiologic correlations at each step as the central learning objectives. 2.3. BSO CAMP Student Survey (Intervention Group) The MS3 students enrolled in the BSO rotation attended a breast surgery specific CAMP teaching session for an hour during the didactic week prior to starting their surgery clerkship. Before attending the CAMP session, the MS3s were issued a pre-CAMP survey, which mirrored the control survey . The students then attended the BSO CAMP teaching session as described above. After completing their BSO surgery rotation, the students were issued a post-CAMP survey , which contained supplemental questions assessing the influence of the BSO CAMP on their surgery rotation experience. 2.4. Statistical Analysis The survey data were securely stored in an institutional secure online REDCap database. During analysis, de-identified survey responses were converted to numerical data points based on a 5-point Likert scale (1-very poor, 2-poor, 3-fair, 4-good, 5-excellent) and agreement (1-strongly disagree, 2-disagree, 3-neutral, 4-agree, 5-strongly agree). The responses for each survey question were averaged for the purposes of analysis and reported with the standard deviation. Normality testing was not performed, and we assumed a normal distribution in our analysis. Control group versus post-CAMP intervention group and post-CAMP intervention groups survey results were compared using the Student's t-test with a p-value of <0.05 statistically significant. The validity argument for the items used in the survey include our teams' inferences and assumptions about the survey items. In particular, the validity arguments involved assumptions about how to best measure for the variables of interest in a study . It was critical to our research that we measured the students' subjective experiences. For example, we did not intend to objectively measure the students' anatomy knowledge, rather we wanted to focus on the learners' self-assessment of their knowledge, confidence, comfort, and ability to prepare for operative cases. The surveys assess one item per domain to efficiently measure the variables of interest and are more appropriate than other methods of data collection. 3. Results All eligible students who were invited to participate completed the control (n = 9), pre-CAMP (n = 11), and post-CAMP surveys (n = 11). Figure 1 compares the control group (students who did not experience the CAMP) to the intervention group (separated into post-CAMP). Table 1 details the Likert scale responses between the three groups and their associated p-values. The top p-value is measured between the control group and the post-CAMP intervention group, the bottom p-value is measured between the post-CAMP intervention groups. The first survey question sought to examine the MS3s' surgical anatomy knowledge. Prior to completing the BSO CAMP, the majority of the intervention group ranked their anatomy knowledge as poor (55%) or very poor (18%) (mean (SD) 2.18 +- 0.87). After participating in the BSO CAMP, 100% of the intervention group ranked their knowledge as good (45%) or excellent (55%) (p = 0.0001, mean (SD) 4.5 +- 0.52). The MS3s from the control group ranked their anatomy knowledge lower than those who had completed the BSO CAMP (p = 0.0001, mean (SD) 3.67 +- 0.5 vs. 4.36 +- 0.67). Following the CAMP, 73% strongly agreed, and 27% agreed that the BSO CAMP improved their surgical anatomy knowledge (mean (SD) 4.73 +- 0.47). The second question explored confidence in answering anatomy-based questions in the operating room. Students in the intervention group, prior to the CAMP, ranked their confidence in answering questions in the OR as fair (18%), poor (72%), or very poor (10%) (mean (SD) 2.09 +- 0.54). After the CAMP, the confidence of the MS3s increased greatly compared to the pre-CAMP levels (p = 0.0046, mean (SD) 4.36 +- 0.67 vs. 2.09 +- 0.54). The intervention group's confidence was greater than the control group who learned from the clinical rotation alone (p = 0.0001, mean (SD) 4.37 +- 0.67 vs. 3.11 +- 1.05). In the intervention group, all respondents strongly agreed (82%) or agreed (18%) that the BSO CAMP improved their confidence in answering questions in the operating room (mean (SD) 4.81 +- 0.40). The third question sought to analyze the MS3s' comfort in assisting surgical cases, which was considered related to anatomic and surgical case knowledge. The majority of the control group ranked their comfort assisting as good (56%) or worse (mean (SD) 3.44 +- 0.73). In contrast, all the MS3s in the intervention group felt their comfort assisting in surgical cases was good (73%) or excellent (27%) post-CAMP, a significant improvement from their pre-CAMP ranking (p = 0.0002, mean (SD) 4.27 +- 0.47 vs. 2.73 +- 1.01). The majority of students agreed (64%) or strongly agreed (18%) that the BSO CAMP improved their comfort in assisting in surgical cases (mean (SD) 4.0 +- 0.63). The fourth theme explored preparedness, defined as the ability to gather relevant information about the patient and surgery prior to the start of the procedure. The majority (53%) of the control group felt their preparedness was good or excellent, similar to the post-CAMP group (p = 0.06, mean (SD) 4.22 +- 0.67 vs. 4.73 +- 0.47). The CAMP did significantly improve the students' preparedness (p = 0.003, mean (SD) pre-CAMP 3.18 +- 1.08 vs. post-CAMP 4.73 +- 0.47). 4. Discussion As part of the MS3 clerkship education, the BSO CAMP improves medical student confidence, comfort, and ability to prepare for the surgical rotation. The BSO CAMP curriculum focuses on providing students the tools to be successful in their surgical rotation, including how to learn anatomy and not the primary retention of specific anatomy. Notably, most students attributed their improvement to completing the CAMP curriculum. The improvement in rankings and attribution of improvement to the curriculum demonstrate that the BSO CAMP was successful in its goal as an anatomy educational tool. The results of our study may be applicable to other medical schools looking to expand their clinical anatomy teaching and surgical curriculum. Our control cohort survey confirmed that the students felt that their anatomy knowledge, confidence, and comfort were less than good, reflecting prior students' self-assessments from other institutions. In particular, our control data is consistent with an earlier study performed by Fitzgerald et al. , where graduating medical students surveyed felt that they received insufficient anatomy instruction during their training. In this prior publication, nearly half of the surveyed students felt they had not received adequate anatomy teaching when departing medical school; our control group data support this same concern, reflecting a common theme across institutions. Our data reaffirms the critical need for ongoing anatomy education such as the CAMP in the medical school curriculum. The most significant gap in educational need appears to be between preclinical and clinical years. Prior studies demonstrated that medical students entering their clinical years are ill-prepared to transfer anatomical knowledge to practice and suggested a need for anatomy courses coinciding with clinical education . However, there is a paucity of data on educational endeavors to address this need. A limited number of schools have implemented clinical anatomy electives during the MS4 year with significant improvement in anatomic knowledge documented following the elective . Unfortunately, courses such as these may be designed specifically for MS4s entering surgery rather than being available to all medical students . The BSO CAMP program evaluated in this publication is open to all MS3 students regardless of potential specialty, reflecting a different timing and broader audience for our curriculum versus those previously reported. The BSO curriculum provides an opportunity for vertical integration within the medical school curriculum. Medical education strives to integrate clinical topics into preclinical years, but it does not always integrate basic science principles into the clinical years, creating a unidirectional system . Opportunities such as the BSO CAMP allow the integration of preclinical anatomy principles to be re-introduced at appropriate and relevant times in the clinical curriculum. We demonstrated that utilizing the surgery clerkship is a potentially beneficial time to review anatomy knowledge during the clinical years. The proximity of the BSO CAMP anatomy review to the breast surgery rotation allows students to contextualize and further consolidate the information being taught in the classroom. The improvements in the MS3 survey results suggest that this approach was a positive adjunct to the clerkship and a beneficial use of the students' time. In developing the BSO CAMP curriculum, we combined results from our control cohort surveys with recurring themes from similar studies to structure the educational content so that it met the needs of senior medical students . Common and reoccurring themes include the need to teach clinically oriented anatomy, emphasizing the need for anatomy courses taught by qualified demonstrators (those skilled at anatomic knowledge in a clinical context), and the need for refresher courses to highlight forgotten knowledge. From this data, we created and implemented a BSO CAMP curriculum that met three learner-directed goals: (1) teach clinically oriented anatomy from a surgical perspective, (2) teach in close proximity to the surgical rotation for better consolidation of concepts, and (3) utilize MS4 mentors as teachers for near-peer anatomy review. One challenge in developing the CAMP was to identify the hands-on learning approach that best fit our students' needs. Prior authors have widely differing proposals for how to teach anatomy in the modern era, including abandoning gross anatomy labs in favor of simulation, virtual reality, and clinical skills-based learning . Prior publications assessing prosections note the strength of this approach as more time-efficient and cost-effective than dissection with the benefit of fewer cadavers required . However, prosections as a means of anatomy education are generally utilized during MS1 and MS2 years only. To our knowledge, applying this concept to the MS3s' surgery clerkship has not robustly been described in the literature. While the positive MS3 survey results presented here are encouraging, there are several limitations to consider. First are those that relate to the CAMP curriculum itself. There are potential issues regarding the use of cadaveric dissection to teach anatomy, including expense, resource limitations, and time . In the CAMP, each of these concerns was addressed individually. Theil-embalmed cadavers are utilized as they allow prosections to be used for repeated teaching sessions over a period of several months; this saves total cost over the year despite each individual cadaver costing more . Another finite resource is the surgical faculty's time for education. By using peer mentors (MS4s), surgical faculty were present to confirm the MS4s' knowledge and prosection anatomy validity, but the MS4s led ongoing, longer, and more frequent MS3 teaching sessions throughout the year. In addition, time is also a valuable resource for medical students and the medical school curriculum. Therefore, the focus of the CAMP was specialty-specific rather than generalized. Providing a short, high-yield session prior to the clerkship allowed appropriate MS3 education while still protecting the time of the students participating. Second, with a small sample size surveyed in our study, it is unclear if the data is widely applicable to MS3s in other hospitals or across classes at our institution. While this is a limitation in our study's initial survey configuration (using a Likert scale), it can be remedied in the future with larger cohorts. We will continue collecting data prospectively to determine if the positive educational experience is reproducible for ongoing years. Third, our study design did not have a control group in real-time but rather a retrospectively surveyed control group. This design was intentional, as we did not wish to exclude any student from the CAMP as an educational opportunity. This does not negate our results, but it is noted as a potential confounding factor. Finally, we recognize that objective measurements of anatomy knowledge and retention are widely used as a concrete baseline of student learning. However, our study focused on the subjective experience of the medical students and their self-assessment of knowledge, confidence, and preparedness. Although our study did not investigate anatomy education in a concrete sense, student metacognition of the practices surrounding surgery can still be indicative of overall success. In the future, correlating the students' experience to scores can be beneficial to concretely make the association between positive self-assessments and higher scores. Despite these limitations, our results suggest that implementing the BSO CAMP curriculum improved the MS3 surgery clerkship. Based on our findings, MS3 education may benefit from a vertical integration model such as the BSO CAMP to improve surgical anatomy knowledge. Focusing content on high-yield anatomy and scheduling the session to coincide with the surgery clerkships are beneficial and efficient based on our results. Going forward, medical schools could consider the CAMP as an educational model useful for integrating anatomy and clinical concepts for MS3s. 5. Conclusions The CAMP BSO for MS3 students effectively prepares students and improves confidence prior to the breast surgical oncology clerkship rotation. Using the CAMP via near-peer mentor teaching, the students improved their knowledge, confidence, comfort, and ability. This model can serve as a template for medical students, surgical clerkship directors, and other faculty interested in expanding surgical anatomy education at their institution. Acknowledgments The authors thank Holly R. Zink, MSA of the Department of Surgery, University of Kansas, Kansas City, KS, for providing medical writing and editorial support for this research. We would like to acknowledge German Berbel and Sara Keim-Jassen as ongoing CAMP leaders along with Peter DiPasco and Jennifer Li as CAMP concept creators. Jasmine Estrada MD is also acknowledged as part of the original CAMP breast surgical oncology team, including obtaining the surveys and prior manuscript draft. As she was unavailable for on-going work on the project over the last several years, including on-going edits of the draft and approval, she does not meet authorship requirements but should be acknowledged for her contributions. Author Contributions Conceptualization, C.W., K.E.L., A.F. and L.J.K.; Methodology, C.W. and K.E.L.; Formal analysis, C.W., L.J.K., A.F. and K.E.L.; Data curation, K.E.L.; Writing--Original Draft Preparation, C.W. and A.F.; Writing--Review and Editing, C.W., L.J.K., A.F. and K.E.L.; Supervision, K.E.L. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This was classified as quality improvement and thus was deemed IRB exempt, so a documentation or study number is not indicated based on protocol in our center. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data is unavailable due to privacy restrictions. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Summary of MS3 responses to the survey items, including the control group and intervention group post-CAMP. The data is averaged. Figure 2 Survey for the control group administered to those who had completed the BSO clerkship but never participated in the CAMP. Responses were given on a 5-point Likert scale ranging from very poor to excellent. Figure 3 Pre-CAMP survey to be taken by the intervention group before the CAMP teaching session. Responses were given on a 5-point Likert scale ranging from very poor to excellent. Figure 4 Post-CAMP survey to be taken by the intervention group after the CAMP teaching session. All responses were given on a Likert scale ranging from very poor to excellent (Q1-Q4) or strongly disagree to strongly agree (Q5-Q8). healthcare-11-00709-t001_Table 1 Table 1 Likert Scale Average Response (SD) for All Cohorts. Question ID CONTROL (n = 9) PRE-CAMP (n = 11) POST-CAMP (n = 11) p-Value * Q1. Anatomy Knowledge 3.67 (0.5) 2.18 (0.87) 4.55 (0.52) 0.0001 * 0.0001 * Q2. Confidence 3.11 (1.05) 2.09 (0.54) 4.36 (0.67) 0.0046 * 0.0001 * Q3. Comfort 3.44 (0.73) 2.73 (1.01) 4.27 (0.47) 0.0065 * 0.0002 * Q4. Preparation 4.22 (0.67) 3.18 (1.08) 4.73 (0.47) 0.06 0.003 * Q5. CAMP impact on anatomy 4.73 (0.47) Q6. CAMP impact confidence 4.81 (0.40) Q7. CAMP impact comfort 4.0 (0.63) Q8. CAMP impact preparation 4.36 (1.03) * p-value <0.05 statistically significant. 1st line of p-value represents control versus post-CAMP. 2nd line of p-value represents post-CAMP. 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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PMC10000370 | Cancers (Basel) Cancers (Basel) cancers Cancers 2072-6694 MDPI 10.3390/cancers15051422 cancers-15-01422 Editorial Advances in Urological Cancer in 2022, from Basic Approaches to Clinical Management Manini Claudia 12* Lopez-Fernandez Estibaliz 34 Lopez Jose I. 5 Angulo Javier C. 67 1 Department of Pathology, San Giovanni Bosco Hospital, 10154 Turin, Italy 2 Department of Sciences of Public Health and Pediatrics, University of Turin, 10124 Turin, Italy 3 FISABIO Foundation, 46020 Valencia, Spain 4 Faculty of Health Sciences, European University of Valencia, 46023 Valencia, Spain 5 Biocruces-Bizkaia Health Research Institute, 48903 Barakaldo, Spain 6 Clinical Department, Faculty of Medical Sciences, European University of Madrid, 28005 Madrid, Spain 7 Department of Urology, University Hospital of Getafe, 28907 Madrid, Spain * Correspondence: [email protected] 23 2 2023 3 2023 15 5 142213 2 2023 14 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 ). pmcThis Special Issue includes 12 articles and 3 reviews dealing with several basic and clinical aspects of prostate, renal, and urinary tract cancer published during 2022 in Cancers, and intends to serve as a multidisciplinary chance to share the last advances in urological neoplasms. This international forum of urological cancer includes different perspectives from 14 different countries: Canada, New Zealand, Italy, the USA, Germany, South Korea, Japan, Spain, Austria, China, the Netherlands, Taiwan, Poland, and the UK. An overview of these contributions shows the great variability of topics currently impacting the urological clinical practice, from the molecular mechanisms underlying prostate cancer development, for example, to the appropriateness of the robotic surgery in radical prostatectomy or partial nephrectomy and the current role of prostate-specific membrane antigen positron-emission tomography (PSMA-PET) imaging in prostate cancer. In addition, this "Urological Cancer 2022" Issue is also an opportunity to highlight some relevant international achievements of the specialty published elsewhere during 2022. Pellerin et al. analyzed the effects of the chronic exposition to bisphenols in bladder epithelium. Bisphenols A and S are chemical compounds used in the plastic industry to produce polycarbonates necessary for generating epoxy and vinyl ester resins. These worldwide distributed composites are industrially produced by the condensation of phenol and acetone and make up part of several plastics such as PVC. These products are insoluble in water and are present in the urine in normal conditions. Importantly, they are endocrine disruptors that interfere with cellular signaling pathways in urothelial cells . Using normal urothelial cells (pediatric volunteers) and non-invasive (RT4, cell line ATCC HTB-2) and invasive (T24, cell line ATCC HTB-4) bladder cancer cells, the authors evaluate the impact of bisphenols on the energy metabolism, proliferation, migration, and pro-tumorigenic effect in human urothelium. They conclude that a chronic exposure to bisphenols A and S increases the proliferation rate and decreases the migration capacities of normal urothelial cells, which could result in urothelial hyperplasia. By contrast, these chemical products increase the energy metabolism, physiological activity, and cell proliferation, which could eventually promote urothelial cancer progression, especially from non-invasive to invasive variants. The clinical identification of aggressive variants of prostate carcinoma requires more accurate markers. Reader et al. have analyzed how the variations in the expression of Activins B and C impact the growth of PNT1A and PC3 prostate cancer cell lines. Activins are hetero-dimers belonging to the transforming growth factor-b family involved in prostate homeostasis, which are dysregulated in prostate cancer . The authors have detected that the expression of Activin B was increased in prostate cancer samples, with a higher Gleason index, and that its overexpression inhibited the growth of PNT1A cells and increased PC3 cells' growth and migration. Interestingly, Activin C showed the opposite expression, with decreased immunostainings in prostate cancer cells with high Gleason grades, an increased overexpression in PNT1A cells, and a decreased growth in PC3 cells. The authors conclude that the combination of Activin B increasing and Activin C decreasing is associated with a higher Gleason grade in prostate adenocarcinoma and suggest its potential usefulness as prognostic biomarkers in this neoplasm. Tossetta et al. focused on the role of the ciliary neurotrophic factor (CNTF) in prostate cancer. Despite the fact that several crucial pathways such as MAPK/ERK, AKT/PI3K, and Jak/STAT regulate prostate cancer progression are triggered by CNTF, little is known about the effect of this member of the IL-6 family. The authors analyze the immunohistochemical expression of CNTF and its receptor in androgen-responsive (n = 10, radical prostatectomy samples) and castration-resistant (n = 10, transurethral resection samples) prostate cancers. Additionally, CNTF and its receptor expression are analyzed in androgen-dependent (LNCaP) and androgen-independent (11Rv1) prostate cancer cell lines by Western blotting and immunofluorescence. They also show that CNTF treatment downregulates MAPK/ERK and AKT/PI3K pathways, inhibiting the matrix metalloproteinase-2 (MMP-2), a major component of the extracellular matrix degrader, and what is mainly responsible for tumor invasiveness. The authors conclude that CNTF plays a key role in the remodeling of the prostate cancer environment and suggests that this cytokine may modulate prostate cancer invasion. CNTF could represent a novel therapeutic approach in patients with castration-resistant prostate cancer. Zapala et al. investigated the usefulness of the preoperative systemic immune-inflammation index (SII) in predicting survival in a retrospective series of 421 patients with non-metastatic prostate cancer treated with radical prostatectomy. They found that a high SII was an independent predictor of overall survival. Furthermore, the combination of high age-adjusted Charlson Comorbidity Index (ACCI), the Cancer of the Prostate Risk Assessment Postsurgical score (CAPRA-S), and the SII identifies patients at the highest risk of death. The authors conclude that SII should be added to the prognosticators of patients with prostate cancer. Clear cell renal cell carcinoma (CCRCC) is a perfect example of tumor complexity and a permanent target of analysis in recent years. In this collection, Shi et al. analyzed the value of a ferroptotic gene-based signature in the prognosis of several series of CCRCC downloaded from the GEO database. The analyzed genes were obtained from the FerrDb V2 database. They identify a set of nine genes with prognostic implications differentially expressed in CCRCC, and found that the GLS2 enzyme, encoded by the GLS2 gene and regulated by p53, may be a ferroptotic suppressor in CCRCC. The authors conclude that this nine-gene signature could eventually be an independent prognosticator in this neoplasm and advice for further investigations. Aside from that, several interesting investigations have been performed this year and deserve a short mention. Intratumor heterogeneity (ITH) is a constant, extensively analyzed event in CCRCC and its level has been correlated in 2022 with tumor aggressiveness. A mathematical study based on game theory and a histological analysis confirm that aggressive variants of CCRCC typically display low levels of ITH and agree with a genomic analysis of 101 cases already published in 2018 . Additionally, several investigations have analyzed the influence of tumor growth patterns in the inter-regional genomic variability of these neoplasms , supporting the need for a personalized tumor sampling to strengthen tumor analysis . In their review, Christenson et al. revisited all the treatment modalities available so far in prostate cancer, focusing especially on the targets to interrupt the biological progression in lethal forms of prostate cancer, that now have a 5-year overall survival of only 30%. They revise current therapies, considering first low-risk and high-risk non-metastatic cancer, and then how to target metastatic cases, including hormone therapy, chemotherapy, PSMA-targeted radiation, genome-targeted precision therapy, and immunotherapy. The authors also review the ETS fusion positive (involving TMPRSS2, SLC45A3, ETV1, ETV4, and FLI1 genes) and negative (involving SPOP, FOXA1, and IDH1 genes) molecular subtypes of prostate cancer. The intimate mechanisms regulating metastatic castration-resistant prostate cancer and the androgen receptor ablation for intercepting advanced cancer are also analyzed. The intestinal microbiota as a potential promoter of castration-resistant tumor variants, the innovations in managing neuroendocrine tumors, and the difficulties of applying immune checkpoint inhibition in prostate cancer appear among the future directions in the review. Finally, the authors point also to CRISPR/Cas enzymes-assisted gene editing as a promising arena to develop further in prostate cancer management. Other clinically oriented topics have also been incorporated in this Special Issue on the advances in urologic cancer regarding patient follow-up, diagnosis, and treatment. A very interesting one is a randomized clinical trial performed in the Netherlands which deals with the transition of care between a specialist and primary care physician . Patients were randomized and allocated to specialist or general practitioner care for a head-to-head comparison. Several advantages of primary care follow-up over specialists' have been identified, including accessibility and more personalized attention, with a similar effectiveness. This study also identifies several challenges that must be addressed before the transition to primary-care follow-up can be a reality, by using quality indicators and improving communication and collaboration. However, another report from the same study shows that from the patient's perspective, hospital-based follow-up is preferred, but efforts should be made to improve physician's knowledge about personal aspects of the patient, improve symptoms management, and promote global health . A series of articles evaluate the diagnostic pitfalls of prostate cancer by using different tools including PSA, multiparametric magnetic resonance imaging (mpMRI), and new generation imaging with the PSMA-PET modality; the latter has many therapeutic implications. In this respect, a study addresses the variables associated with false-positive PSA results using real-world data in a Spanish cohort of 1664 patients followed for two years. The false-positive results were as high as 47%, resulting in a positive predictive value of merely 13% . This rate is much higher than previously reported in trials with screening data Many factors were demonstrated to be associated with the presence of false-positive results, including age, previous PSA evaluation, family history of prostate cancer, and alcohol intake, but these associations were sustained only in asymptomatic patients . These data do not serve to evaluate overdiagnoses and overtreatment but help to sustain that the PSA era in prostate cancer diagnosis should be closing. A study in this Special Issue addresses the limitations of mpMRI for primary prostate cancer diagnosis in the form of a systematic review and meta-analysis that compare mpMRI with prostate-specific membrane antigen (PSMA) positron emission tomography (PET) imaging . With the limitation of significant heterogeneity observed, PSMA-PET computerized tomography (CT) seems superior to mpMRI in primary cancer diagnosis, but not in the definition of cancer location within the gland. However, as can be expected from a whole-body procedure, PSMA-PET CT has valuable potential for tumor staging. False-positive MRI is another troublesome reality in clinical practice as it is not easy to differentiate false and real positive lesions, thus making evident the difficulty of further advancing in the MRI diagnostic ability . PSMA-PET CT has also been investigated to solve MRI Prostate Imaging Reporting and Data System (PI-RADS) 4-5 lesions and negative biopsy discordance and also the combination of PSMA-PET CT and mpMRI is being currently investigated in the MP4 clinical trial in which PI-RADS 4 or 5 lesions >=10 mm on mpMRI are given the option of a PSMA-PET CT before biopsy. The intention of this approach is to predict better aggressive prostate cancer. That opens a new perspective to evaluate the feasibility of proceeding to prostate cancer surgery directly without a biopsy . Additionally, PROSPET-BX clinical trial, currently undertaken in Italy, might confirm the superiority of PSAM-PET CT/transrectal ultrasound (TRUS) fusion prostate biopsy over mpMRI/TRUS fusion biopsy to further spare unnecessary biopsies . Inspired by all these changes of paradigm, an excellent review on the clinical applications of PSMA-PET CT examination in patients with prostate cancer has been included in this Special Issue . The article addresses the limitations and pitfalls of this new generation diagnostic imaging modality and emphasizes its therapeutic implications also. In fact, prolonged progression free and overall survival has been very recently confirmed in castration-resistant prostate cancer with lutetium Lu 177 vipivotide tetraxetan (177Lu-PSMA-617) radioligand therapy . Additionally, the PSMA-PET CT-guided intensification of radiotherapy is being investigated in a Canadian clinical trial, with special effort on cancer control, long-term toxicity, and health-related quality of life issues . Carbon-ion radiotherapy, another modality to improve the effectiveness of radiation therapy, has been also evaluated in this Special Issue, with a retrospective study focusing on the older population of patients with prostate cancer . This study confirms that carbon-ion radiotherapy is a safe and effective high-dose intensive treatment. This modality of radiation has been popular in different institutions in Japan for the treatment of different urologic cancers . This modern technology provides several unique physical and radiobiologic properties that allow low levels of energy to be deposited in tissues proximal to the target, while the majority of energy is released in the target itself. That may have important advantages, especially in the setting of recurrent disease . Another modality of radiation is extreme hypofractionation with stereotactic body radiation therapy (SBRT) in which treatment is delivered in one to five fractions, an encouraging alternative in the intermediate-risk profile of patients that competes with high-dose brachytherapy . Surgery has also seriously evolved to consider robotic prostatectomy the gold standard of surgical care for localized prostate cancer, that improves the functional outcomes of urinary continence and potency. This is also the topic of another article in the Special Issue . Still, the definition of continence "without pads" or "social continence" makes difficult the comparison of the results . New and effective modalities to surgically correct post-prostatectomy incontinence have been developed in recent decades and can be used both for stress urinary incontinence after prostatectomy and after radiation therapy . Another interesting application of robotics in surgical urologic oncology is partial nephrectomy. The clinical benefits of indocyanine green florescence in robot-assisted partial nephrectomy are discussed in another element of this Special Issue. Reduced blood loss without a negative impact in the positive surgical margin rate is suggested using green dye . However, future prospective randomized controlled trials are needed to confirm the presumed operative and functional advantages of this approach. Moreover, the issue presents another very interesting collaboration regarding metastatic renal cell carcinoma treatment, a field that has been subject to important paradigm changes in recent years . The German multicenter prospective study PAZOREAL presented by Doehn et al. reveals very interesting data on the effectiveness and safety of pazopanib (first-line), nivolumab (second-line), and everolimus ( third-line) in a real-life setting. This sequence is widely used in clinical practice. Targeted treatments for metastatic renal cell carcinoma allow for a more tailored approach, but predictive elements for immune-checkpoint inhibitors or tyrosine kinase inhibitors as a first-line treatment still lack genuine prediction markers . Many studies have faced the optimal management of bladder urothelial malignancy in recent years. Some have searched for new therapeutic alternatives in the scenario of Bacillus Calmette-Guerin (BCG) shortage to prevent urothelial cancer recurrence and progression. Device-assisted intravesical chemotherapy using recirculating hyperthermic mitomycin-C (HIVEC) has been widely used in Spain . Current new evidence favors the use of HIVEC in high-risk non-muscle-invasive bladder cancer , but not in the intermediate risk . Many other studies have extended to step beyond classical morphologic parameters and stratify the prognosis of muscle-invasive bladder cancer according to new molecular markers that take into account basal or luminal phenotypes discovered . A further step that is currently being undertaken is the evaluation of the intratumor microenvironment landscape, with implications not only in prognosis, but also in the response to systemic immunotherapy . In this sense, immune-checkpoint inhibitors have been recently approved as a second-line treatment for metastatic bladder cancer and are currently being investigated in a neoadjuvant setting in non-metastatic disease . Upper urinary tract urothelial carcinoma is another malignancy addressed in the Special Issue. Ha et al. revealed that intravesical recurrence after radical nephroureterectomy is associated with flexible but not with rigid diagnostic ureteroscopy . This specific report opens a new perspective that requires a further evaluation in large-population controlled studies. The issue of intravesical recurrence after upper urinary tract cancer diagnosis and treatment is a big unsolved problem in the comprehensive management of urothelial malignancy. Several meta-analyses have confirmed the higher rate of intravesical recurrence after radical nephroureterectomy in patients who underwent diagnostic ureteroscopy preoperatively , but with no concurrent impact on long-term survival . Probably the negative impact on intravesical recurrence free survival is due more to endoscopic biopsy than to ureteroscopy itself. As the use of flexible ureteroscopy is routinely recommended by clinical guidelines , future studies are needed to assess the role of immediate postoperative intravesical chemotherapy in patients undergoing biopsy during ureteroscopy for suspected upper tract urothelial cancer. In summary, "Urological Cancer 2022" is a remarkable piece of knowledge that presents new relevant clinical, molecular, imaging, and therapeutic data in the urological field and invites researchers in urologic malignancy to enter a multidisciplinary approach and face some of the most relevant and current topics in urology. 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). 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PMC10000371 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051025 foods-12-01025 Article Identification of Key Genes Affecting Flavor Formation in Beijing-You Chicken Meat by Transcriptome and Metabolome Analyses Gai Kai 1 Ge Yu 1 Liu Dapeng 2 Zhang He 2 Cong Bailin 1 Guo Shihao 1 Liu Yizheng 1 Xing Kai 1 Qi Xiaolong 1 Wang Xiangguo 1 Xiao Longfei 1 Long Cheng 1 Guo Yong 1 Sheng Xihui 1* Mora Leticia Academic Editor 1 Animal Science and Technology College, Beijing University of Agriculture, Beijing 102206, China 2 Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China * Correspondence: [email protected]; Tel.: +0086-010-8079-7311 28 2 2023 3 2023 12 5 102505 12 2022 01 2 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 ). The flavor of chicken meat is influenced by muscle metabolites and regulatory genes and varies with age. In this study, the metabolomic and transcriptomic data of breast muscle at four developmental stages (days 1, 56, 98, and 120) of Beijing-You chickens (BJYs) were integrated and 310 significantly changed metabolites (SCMs) and 7,225 differentially expressed genes (DEGs) were identified. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that SCMs and DEGs were enriched in amino acid, lipid, and inosine monophosphate (IMP) metabolism pathways. Furthermore, genes highly associated with flavor amino acids, lipids, and IMP were identified by a weighted gene co-expression network analysis (WGCNA), including cystathionine b-synthase (CBS), glycine amidinotransferase (GATM), glutamate decarboxylase 2 (GAD2), patatin-like phospholipasedomain containing 6 (PNPLA6), low-specificity L-threonine aldolase (ItaE), and adenylate monophosphate deaminase 1 (AMPD1) genes. A regulatory network related to the accumulation of key flavor components was constructed. In conclusion, this study provides new perspectives regarding the regulatory mechanisms of flavor metabolites in chicken meat during development. meat flavor Beijing-You chicken transcriptome metabolome regulatory network Beijing Innovation Consortium of Agriculture Research SystemBAIC06-2022 Beijing Municipal Bureau of Agriculture and Rural AffairsThis work was supported by the Beijing Innovation Consortium of Agriculture Research System (BAIC06-2022) and Beijing Municipal Bureau of Agriculture and Rural Affairs. pmc1. Introduction The growth efficiency of chickens has increased rapidly as large-scale poultry production has increased, but the quality and flavor of chicken have decreased significantly. The meat color, odor, and taste of chicken are the decisive factors that affect consumption . Among them, chicken flavor (taste and odor) is an important index to measure quality . Therefore, improving meat flavor has become an important research topic in broiler breeding. Meat flavor is attributed to a variety of volatile compounds formed during cooking by reactions between low molecular weight water-soluble compounds and lipids . However, flavor phenotypes are difficult to quantify and are strongly influenced by environmental factors , which makes it difficult to improve chicken flavor. Lipids and water-soluble components are the main flavor precursors of meat. Water-soluble components include free sugars, sugar phosphates, nucleotide-bound sugars, free amino acids, peptides, nucleotides, and sulfur-containing compounds . The umami flavor of chicken meat is primarily derived from water-soluble precursors substances such as inosine monophosphate (IMP) and glutamate . Lipids are the fat-soluble substances found in meat. The main components of intramuscular fat (IMF) and subcutaneous fat are triglycerides and phospholipids, which contain large amounts of unsaturated fatty acids such as linolenic acid, oleic acid, and arachidonic acid (ARA). It has been demonstrated that chickens with a high ARA content have better sensory quality , and oleic acid is also associated with the taste of meat . According to research by Mottram et al., phospholipids are important precursors for meat flavor, whereas triglycerides have little impact on flavor . Studies have shown that adenylosuccinate lyase (ADSL) is a key gene in regulating the IMP synthetic pathway, and fatty acid-binding proteins (FABPs) and peroxisome proliferator-activated receptor-g (PPARg) are important genes that regulate lipid transport and metabolism. However, the key metabolites and molecular mechanisms that influence chicken flavor have not been fully elucidated. The transcriptome may present different gene expression states under different conditions. Furthermore, metabolomic analysis reveals changes in metabolites caused by gene regulation. Many researchers have investigated the regulatory process of IMF formation in livestock and poultry meat through a joint analysis of the transcriptome and metabolome , which has improved our understanding of the regulatory mechanisms involved in meat flavor. The Beijing-You chicken (BJY) is a distinctive indigenous breed that is well known for its meat quality and flavor in China. The free amino acids in its muscles are significantly higher than those of other breeds , and it is also rich in essential fatty acids and phospholipids . In this study, we performed joint analyses between the transcriptome and metabolome to investigate the metabolic dynamics of flavor precursors in breast muscle samples of BJYs obtained on days 1, 56, 98, and 120, and identified key metabolites and genes that can affect meat flavor. Our results provide a theoretical foundation for the molecular mechanisms underlying chicken flavor and utilization of the germplasm resources of BJYs. 2. Materials and Methods 2.1. Ethics Approval Animal welfare practices and experimental procedures were performed in accordance with the Guide for the Care and Use of Laboratory Animals (Ministry of Science and Technology of China, 2006). All procedures were approved by the Animal Ethics Committee of the Beijing University of Agriculture. 2.2. Animals The BJYs used in this experiment were obtained from a farm in a suburb of Beijing. A total of 100 1-day-old chickens were randomly selected and raised under identical standard management conditions with free access to water. The ingredients and composition of the BJY diets at different feeding stages are shown in Table S1. The immune procedures at different developmental stages are shown in Table S2. Ten healthy chickens of similar body weight were chosen at 1 (birth stage), 56 (rapid growth stage), 98 (stage with high deposition of IMF), and 120 days of age (marketing stage), respectively, and were slaughtered by a conventional neck cut, bled, and plucked. Breast muscle without skin was then collected from similar sampling sites and stored in a refrigerator at -80 degC. The body weight and breast muscle weight at the four developmental stages of BJYs are shown in Table S3. 2.3. RNA Extraction and Sequencing Total RNA was extracted from 40 frozen breast muscle samples using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. An ARNA 6000 Nano LabChip Kit for Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA) was used to determine the purity and concentration of RNA. Forty cDNA libraries were created by reverse transcription using an mRNA-Seq Sample Preparation Kit (Illumina, San Diego, CA, USA). A HiSeq 2500 instrument was used for paired-end sequencing (Illumina). Raw data (raw reads) in fastq format were filtered to ensure quality. Reads with adapter sequences and low quality were eliminated and all reads containing A bases and reads with N ratios >10 % were eliminated to ensure quality. Using Hisat2 with the default settings, clean paired-end reads were aligned to the chicken reference genome (version: GCF_016699485.2). Stringtie (v2.1.5, accessed on 3 September 2021) was used to assemble transcripts. Gene expression levels were estimated using counts per million (CPM). 2.4. Analysis of Gene Expression Data The differentially expressed genes (DEGs) between the two stages were calculated using the edger R package, which was defined as genes with a false discovery rate (FDR) <= 0.05 and a |log2(fold change)| >= 1. The DEGs were analyzed, clustered, and visually represented using Short Time-series Expression Miner (STEM) software (Pittsburgh, PA, USA, v1.3.11). The minimum and maximum numbers of model profiles were 2 and 45, respectively. We standardized the data using Log2 (CPM), and the screening interval for a valid trend was p < 0.05. A hierarchical cluster analysis of the DEGs was performed using the ggplot2 package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R package clusterProfiler (Guangdong, China, v4.0.5). 2.5. Metabolite Extraction and LC-MS/MS Conditions 2.5.1. Metabolite Extraction A total of 40 frozen samples from four developmental stages were defrosted. Following homogenization, the samples were centrifuged at 12,000 rpm for 10 min at 4 degC and the supernatant was collected in a tube for the LC-MS/MS analysis. 2.5.2. LC-MS/MS Conditions The sample extracts were analyzed using an LC-MS/MS system (UFLC, shimadzu UFLC SHIMADZU CBM30A, available at ) (accessed on 3 September 2021) and chromatographic separations were performed. In reverse phase separation, a Waters ACQUITY UPLC HSS T3 C18 (1.8 m, 2.1 mm x 100 mm) was employed. The HPLC conditions were as follows: solvent system, water (0.04 % acetic acid): acetonitrile (0.04% acetic acid); gradient program of 95:5 V/V at 0 min, 5:95 V/V at 11.0 min, 95:5 V/V at 12.1 min, and 95:5 V/V at 14.0 min; flow rate, 0.40 mL.min-1; temperature, 40 degC; injection volume, 2 mL. A QTRAP(r) 6500+ LC-MS/MS System ) (accessed on 3 September 2021), equipped with an electrospray ionization (ESI) Turbo Ion-Spray interface and operating in positive and negative ion mode was used. The operating parameters for the ESI source were as follows: the ion spray (IS) voltage was 5500 V (positive) and -4500 V (negative) and the turbo spray source temperature was 500 degC. The ion source gas I (GSI), gas II (GSII), and curtain gas (CUR) pressures were 55, 60, and 25.0 psi, respectively. The level of the collision gas (CAD) was high. Instrument calibration and mass calibration were performed with solutions of 10 and 100 mol/L polypropylene glycol in the QQQ and LIT modes, respectively. A specific set of multiple reaction monitoring (MRM) transitions was observed based on the metabolites eluted each time. 2.6. Qualitative, Quantitative and Statistical Analysis of Metabolites Metabolites were differentiated by contrasting the m/z values of precursor ions, retention times, and fragmentation patterns with the standards in a database created by MetWare Biotechnology Co., Ltd. (Wuhan, China). An MRM pattern was used for quantitative detection. The following screening thresholds were used to identify significantly changed metabolites (SCMs): |log2(fold change)| >= 1 and variable importance in projection (VIP) >= 1. Principal component analysis (PCA) was carried out using SIMCA14.1 software. MetaboAnalyst 5.0 ) (accessed on 3 September 2021) was used to analyze metabolic pathways of the SCMs. 2.7. Integrative Analysis of Metabolomic and Transcriptomic Datasets Co-expression network modules of all DEGs were constructed using the WGCNA R package (v1.70-3) and analyzed in combination with metabolites. The automatic network creation function (blockwiseModules) with the default parameters was used to obtain co-expression modules. The parameters were minModuleSize = 30, mergeCutHeight = 0.25, and soft threshold power = 10. Screening was carried out utilizing a gene significance |GS| >= 0.7 and a module membership |MM| >= 0.7 in order to better investigate interactions between genes in the modules. The link between genes and important metabolites was determined using Pearson correlation analysis. Interaction networks were constructed using Cytoscape ) (accessed on 3 September 2021). KEGG pathways that were jointly enriched by all SCMs and DEGs were analyzed. The 'cor' package in R software (www.r-project.org) (accessed on 3 September 2021) was used to calculate Pearson correlation coefficients between the SCMs and DEGs through pairwise comparisons. 3. Results 3.1. Transcriptome and DEGs Analysis RNA-seq analyses were conducted to examine gene expression profiles of breast muscles in BJYs at different developmental stages. A total of 7225 DEGs were identified in this study: 6,521 at day 1 vs. 56, 819 at day 56 vs. 98, and 747 at day 98 vs. 120 . The results of cluster analysis revealed differential expression of genes at different stages . To identify genes that play key roles in breast muscle development, 82 critical genes were discovered at the intersection generated from a Venn diagram of DEGs . 3.2. GO and KEGG Enrichment Analysis of DEGs We investigated the functions of 7,225 DEGs using GO analysis. Biological processes contained 268 significant terms (p < 0.05), and the top five terms in this category were cellular developmental process, cell differentiation, tissue development, cell proliferation, and regulation of cell differentiation. Molecular functions involved 18 significant terms, including cytoskeletal protein binding, lipid binding, tubulin binding, and sulfur compound binding . The KEGG enrichment analysis identified 26 key KEGG pathway terms, including multiple pathways involved in muscle growth, including the Wnt, MAPK, and PPAR signaling pathways . The functions of 82 intersecting genes in a Venn diagram analysis were analyzed to determine their involvement in regulatory mechanisms surrounding meat flavor. KEGG pathway analysis showed that multiple genes were enriched in pathways associated with muscle development, including ECM-receptor interaction, PPAR signaling pathway, and fatty acid biosynthesis and degradation, in which secreted phosphoprotein 1 (SPP1), thrombospondin 1 (THBS1), thrombospondin 2 (THBS2), and acyl-CoA synthetase long chain family member 4 (ACSL4) were associated with the biological pathways of IMF deposition (Table 1). 3.3. Time Series Analysis of DEGs STEM analysis revealed that the expression patterns of 7225 DEGs in breast muscle during BJY development were enriched into forty-five profiles, of which nine profiles appeared significant, including six up-regulated and three down-regulated profiles. A total of 2931 DEGs exhibited an up-regulation trend and were significantly enriched in profiles 5, 10, 36, 38, 42, and 44, whereas 2830 DEGs showed a down-regulation trend and were significantly enriched in profiles 0, 2, and 4 . The genes enriched in profiles 2 and 38 were the most abundant, and KEGG enrichment analysis revealed that genes in profile 2 were primarily enriched in the Wnt signaling and purine metabolism pathways, whereas the genes in profile 38 were primarily enriched in cytokine-cytokine receptor interaction and cell adhesion molecular pathways (Table S7). 3.4. Metabolomic Data and SCMs Analysis We further analyzed the metabolic alterations in the breast muscle of BJYs at four developmental stages using an LC-MS/MS approach. In total, 578 compounds were identified and classified into 33 classes; primarily organic acids, carbohydrates, lipids, nucleotides and their derivatives, vitamins, and amino acid derivatives. A PCA of the metabolic data of the four developmental stages indicated a good correlation between replicates, and SCMs from day 1 were clearly distinct from those of other stages . We identified 310 SCMs using the criteria of a VIP >= 1 and a |log2(fold change)| >= 1. At day 1 vs. 56, we found 294 SCMs, of which 221 and 73 were up-accumulated metabolites, respectively. At day 56 vs. 98, a total of 19 SCMs, including 13 6 up-accumulated metabolites were detected. A total of 21 SCMs were identified at day 98 vs. 120, including 12 9 up-accumulated metabolites . KEGG enrichment analysis indicated that the majority of SCMs were involved in amino acid metabolism, such as arginine biosynthesis; arginine and proline metabolism; purine metabolism; glycine, serine, and threonine metabolism; and alanine, aspartate, and glutamate metabolism . 3.5. Joint Analysis of Transcriptomic and Metabolomic Data To better understand the gene regulation mechanism of metabolites during BJY development, nine co-expression modules of DEGs were identified using WGCNA . DEGs of BJYs from day 1 vs. 56 were mainly gathered in the blue module, whereas DEGs from day 56 vs. 98 and from day 98 vs. 120 were mostly located in the cyan module. According to the heatmap of module-trait relationships , the accumulation of transcripts of the blue module correlated with amino acids and lipid metabolites, including serine, glycine, cysteine, threonine, glutamate, and lysophosphatidylcholine (LPC), which are the main flavor compounds of BJYs. The accumulation of transcripts in the cyan module was correlated with flavor-associated metabolites such as creatine and IMP. These results indicated that the DEGs in these modules were mainly associated with flavor formation during the development of BJY breast muscle. 3.6. Generation of Flavor Metabolic Regulatory Networks To further explore the relationship between DEGs and SCMs, DEGs in the blue and cyan modules with a gene significance, |GS|, of >=0.7, and a module membership, |MM|, of >=0.7 were used to analyze interactions with SCMs. We identified 11 genes in the blue module involved in the amino acid metabolic pathway, including cystathionine b-synthase (CBS), glutamate decarboxylases (GAD1 and GAD2), glycine amidinotransferase (GATM), glycine decarboxylase (GLDC), glycine N-methyltransferase (GNMT), low-specificity L-threonine aldolase 2 (ItaE), cysteine lyase (CYLY), sarcosine dehydrogenase (SARDH), cysteine dioxygenase (CDO1), and serine racemase (SSR) genes, the expressions of which were highly correlated with the accumulation of glutamate, serine, glycine, threonine, and cysteine . LPC plays a vital role in the formation of meat flavor. We identified key regulatory genes involved in the LPC biosynthesis pathway in the blue module, including acylglycerol phosphate acyltransferases (AGPAT2 and AGPAT4), diacylglycerol kinases (DGKB, DGKH, and DGKI), glycerol-3-phosphate acyltransferases (GPAM and GPAT2), lecithin cholesterol acyltransferase (LCAT), phospholipid phosphatases (PPAP2B and PPAPDC1B), acetylcholinesterase (ACHE), ethanolamine kinase (ETNK2), patatin-like phospholipase (PNPLA6), and phospholipase (PLA2G4EL1 and PLA2G4A) genes . IMP is an important flavor substance in chickens. Seventeen genes in the cyan module were identified as good candidates encoding key genes in the IMP biosynthesis pathway, including adenylate monophosphate deaminases (AMPD1 and AMPD3), adenylosuccinate synthetase (Adssl1), ectonucleoside triphosphate diphosphohydrolases (ENTPD5 and ENTPD6), phosphodiesterases (PDE1B, PDE4B, PDE8B, PDE10A, and PDE4D), adenylate kinases (AK1 and AK3), 5',3'-nucleotidase (NT5C1A and NT5M), one ectonucleotide pyrophosphatase (ENPP3), nucleoside diphosphate kinase (NME3), and phosphoribosylglycinamide formyltransferase (GART) genes . 3.7. Integrated Analysis of Flavor Formation during BJY Development A KEGG enrichment analysis of DEGs and SCMs revealed 46 co-enriched pathways . The pathways associated with amino acids, lipids, and IMP were highlighted in this analysis, and these processes were combined in the related network . We observed that the network involved flavor metabolites including glycine, serine, cysteine, threonine, and glutamate. The content of these amino acids was higher during the early development of BJYs. In the glycerophospholipid metabolism pathway, the LPC content increased from day 1 to 56 and decreased gradually with continuing growth, and was the key compound that led to fat deposition in the late stage of BJY maturation. IMP content in the purine metabolism pathway significantly increased with the age of BJYs. There was a significant correlation between the regulatory genes and flavor metabolites in the network . For example, the correlation of CBS with cysteine and serine was 0.93 and 0.9, respectively; glycine with GATM was 0.88; IMP with AMPD1 was 0.65; and LPC with PNPLA6 was 0.54 (p < 0.05). 4. Discussion Elucidating the regulatory mechanisms involved in the synthesis and accumulation of flavor compounds is essential for improving chicken meat quality. As illustrated in this study, 310 SCMs and 7,225 DEGs were identified at four developmental stages of BJYs. The functions of DEGs and SCMs were analyzed by KEGG enrichment, and the results showed that they were co-enriched in glycerophospholipid metabolism; glycine, serine, and threonine metabolism; purine metabolism; and alanine, aspartate, and glutamate metabolism pathways. To further understand the molecular mechanisms involved in meat flavor formation during the development of BJYs, we identified genes significantly related to flavor metabolites using WGCNA and established a regulatory network related to the accumulation of key flavor components. CBS, GATM, GAD2, PNPA6, ItaE, AMPD1, glycine, serine, cysteine, and threonine have been identified as important genes and metabolites that affect flavor formation. This study not only helps to define the regulatory networks of specific flavor compounds in BJY meat but also provides a theoretical foundation for the improvement of meat flavor in broiler breeds. Amino acids are crucial components in meat flavor . The degradation of peptides and amino acids in meat improves its sensory properties and taste . Glutamate, succinic acid, and IMP are umami amino acids, whereas glycine, threonine, alanine, and serine are sweet amino acids . Cysteine is the cause of sulfur-containing flavors in meat , as it can produce meat flavors during heating . However, the precise regulatory pathways of amino acid-derived flavors in BJYs remain unknown. We identified genes related to amino acid metabolism by WGCNA, including CDO1, CYLY, CBS, GAD, GATM, and ItaE. CDO1, CYLY, and CBS are considered critical genes involved in cysteine metabolism. CDO1 regulates cysteine concentrations in mice by participating in cysteine degradation . Cysteine is the only major substrate of CYLY . CBS catalyzes the formation of cysteine by the condensation of serine and homocysteine with water . The absence of CBS increases the risk of elevated plasma homocysteine levels and severe growth retardation . In addition, we demonstrated a high correlation between CBS and cysteine (r = 0.93). The consistent expression trends of CBS and cysteine indicated that CBS may play an important role in the growth and flavor formation of BJYs. GAD transforms glutamate to g-aminobutyric acid by decarboxylation, which is then converted to succinate . This was also confirmed by the higher association between GAD2 and glutamate in this study (r = 0.72). GATM encodes a mitochondrial enzyme that belongs to the amidinotransferase family and is thought to be a key gene in the process of creatine metabolism . In this study, the creatine and glycine expression trends were opposite. A significant association between glycine and GATM supported speculation that GATM expression controls creatine metabolism and leads to glycine accumulation. Under physiological conditions, ItaE performs threonine catabolism and glycine synthesis by catalyzing the cleavage of threonine into glycine and acetaldehyde . Similarly, our results showed that decreased glycine levels were associated with a decreased ItaE expression. The coefficients of correlation of ItaE with threonine and glycine were 0.48 and 0.59, respectively. Finally, we speculated that CBS, GATM, GAD2, and ItaE were key genes involved in amino acid-derived flavor formation in breast muscle during BJY development. LPC is obtained by loss of a fatty acid group from lecithin. In vitro studies have confirmed that the ability of LPC to emulsify fat is 4-5 times higher than that of common oil. Our results showed that LPC expression levels decreased with the aging of BJYs, which may be related to fat deposition in late developmental stages of BJYs. We identified a total of 15 DEGs significantly associated with LPC in the blue module. The PNPLA6 enzyme can react with a variety of substrates, including retinol esters, triacylglycerols, and phospholipids . However, it can preferentially hydrolyze phosphatidylcholine (PC) and LPC . In both Drosophila and mice, PNPLA6 gene deletion leads to increased lipid deposition, motor impairments, and neurodegeneration . In this study, we identified the transcription level of PNPLA6 was significantly positively correlated with LPC (r = 0.54). We speculated that the decrease in LPC content under the regulation of PNPLA6 led to the accumulation of large amounts of fat during the late development of BJYs. The AGPAT enzyme catalyzes the conversion of lysophosphatidic acid (LPA) to phosphatidic acid (PA) . PA is a substrate for the synthesis of other polar phospholipids (PL) such as PC, phosphatidylserine (PS), and phosphatidylethanolamine (PE) . AGPAT2 encodes a member of the 1-acylglycerol-3-phosphate O-acyltransferase family, which is involved in the conversion of lysophosphatidic acid to phosphatidic acid during the second step of phospholipid biosynthesis. The GPAT enzyme converts glycerol-3-P to lysolecithin, which is subsequently acylated to PA . In addition, PA contains two fatty acids in its glycerol backbone at the sn-1 and sn-2 positions. Although GPAT determines fatty acid specificity at the sn-1 (carbon 1) position, AGPAT enzyme esterification causes variability at the sn-2 (carbon 2) position . As a result, these two enzymes can produce a wide range of PA species with varying fatty acids at the two carbon positions. Based on our results, we believe that these genes are involved in fat metabolism, and the regulatory effects need to be confirmed by further research The Maillard reaction refers to the polymerization, condensation, and other reactions involving compounds containing free amino groups and reducing sugars or carbonyl compounds at normal atmospheric temperatures or under heating. IMP degradation-forming ribose participates in the Maillard reaction, which is also an important reaction in flavor formation. Numerous studies have shown that IMP is one of the most important flavor components in meat . The results of this study showed that IMP content was the highest at the age of 56 days, and then decreased gradually with the increase in age, which was consistent with Katemala et al.'s study on Korat hybrid chickens . Previous studies involving the formation of IMP have confirmed that AMPD1 enzyme catalyzes the irreversible hydrolysis of adenosine 5'-monophosphate (AMP) to IMP and ammonia . Our data verified a significantly high correlation between AMPD1 and IMP (r = 0.65). Therefore, this gene was selected as a key gene that controls IMP biosynthesis by regulating AMP metabolism. In addition, we also identified DEGs involved in the IMP metabolic pathway. GART and ADSSL1 genes were able to increase the synthesis of IMP by promoting the purine de novo synthesis. Purine de novo synthesis was divided into 10 steps, in which GART was involved in Steps 2, 3, and 5, and ADSLL1 was involved in the Step 8 reaction in this pathway . AMPD3 and NT5C are involved in the degradation of purine to accelerate the de novo synthesis of purine . We found that the expression levels of these genes were significantly correlated with IMP. These results showed that these genes were related to IMP metabolism in the breast muscle of BJYs. 5. Conclusions In conclusion, we identified four crucial metabolic pathways involved in flavor formation in BJY breast muscle by combining transcriptomic and metabolomic data, including glycerophospholipid metabolism; glycine, serine, and threonine metabolism; alanine, aspartate, and glutamate metabolism; and purine metabolism pathways. We also identified a number of important metabolites and regulatory genes affecting meat quality and flavor involving these pathways, including glycine, serine, glutamate, threonine, LPC, IMP, CBS, GATM, GAD2, PNPLA6, ItaE, and AMPD1. However, the genetic mechanisms of chicken quality and flavor and the molecular function of these key genes and metabolites need to be further verified. In brief, our research provides not only new perspectives regarding the regulatory metabolism of chicken meat flavor during development, but also a theoretical foundation for the utilization of BJYs and genetic improvement in broiler meat quality and flavor. Acknowledgments Thanks to Chen Li for the project funding. Supplementary Materials The following supporting information can be downloaded at: Table S1: Composition of diets of BJYs during the rearing period; Table S2: Immune procedure of BJYs; Table S3: Body weight and breast muscle weight at 4 developmental stages in BJYs; Table S4: 82 DEGs in Venn diagram analysis; Table S5: GO enrichment analysis of DEGs; Table S6: KEGG enrichment analysis of DEGs; Table S7: KEGG pathways of time-series genes in different expression profiles; Table S8: KEGG enrichment analysis of SCMs. Click here for additional data file. Author Contributions K.G.: conceptualization, methodology, validation, formal analysis, investigation, writing--original draft, and visualization. Y.G. (Yu Ge): investigation and resources. D.L.: data analysis and software. H.Z.: data analysis and software. B.C.: data analysis and visualization. S.G.: data collection and visualization. Y.L.: data collection and visualization. K.X.: data analysis and software. X.Q., X.W., L.X. and C.L.: writing--review and editing, supervision, and visualization. Y.G. (Yong Guo): project administration, supervision, writing--review and editing. X.S.: conceptualization, methodology, validation, formal analysis, resources, writing--review and editing, supervision, and 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 Data that support the findings of this study are available upon request to the corresponding author. Conflicts of Interest The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this study. Abbreviations BJY: Beijing-You chicken; SCMs: significantly changed metabolites; DEGs: differentially expressed genes; IMP: inosinemonphosphate; WGCNA: weighted gene co-expression network analysis; ADSL: adenylosuccinate lyase; FABPs: fatty acid-binding proteins; PPARg: peroxisome proliferators-activated receptor g; CPM: counts per million; FDR: false discovery rate; STEM: short time-series expression miner; LC-MS: liquid chromatograph-mass spectrometer; ESI: electrospray ionization; IS: ion spray; CUR: curtain gas; CAD: collision gas; VIP: variable importance in projection; PCA: principal component analysis; GO: gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; SPP1: secreted phosphoprotein 1; THBS: thrombospondin; ACSL4: acyl-CoA synthetase long chain family member 4; LPC: lysophosphatidylcholine; CBS: cystathionine b-synthase; GAD: glutamate decarboxylases; GATM: glycine amidinotransferase; GLDC: glycine decarboxylase; GNMT: glycine N-methyltransferase; ItaE: low-specificity L-threonine aldolase; CYLY: cysteine lyase; SARDH: sarcosine dehydrogenase; CDO1: cysteine dioxygenase; SSR: serine racemase; AGPAT: acylglycerol phosphate acyltransferases; DGK: diacylglycerol kinases; GPA: glycerol phosphate acyltransferases; LCAT: lecithin cholesterol acyltransferase; PPAP: phospholipid phosphatases; ACHE: acetylcholinesterase; ETNK2: ethanolamine kinase 2; PNPL: patatin-like phospholipase; PLA: phospholipase; AMPD: adenylate monophosphate deaminases; Adssl: adenylosuccinate synthetase 1; ENTPD: ectonucleoside triphosphate diphosphohydrolases; PDE: phosphodiesterases; AK: adenylate kinases; NT5: 5'-nucleotidase; ENPP3: ectonucleotide pyrophosphatase 3; NME: nucleoside diphosphate kinase; GART: phosphoribosylglycinamide formyltransferase; LPA: lysophosphatidic acid; PA: phosphatidic acid; PL: polar phospholipids; PC: phosphatidylcholine; PS: phosphatidylserine; PE: phosphatidylethanolamine; GPATs: glycerol-3-phosphate acyltransferases; AMP: adenosine 5 '-monophosphate. Figure 1 Differential expression analysis of mRNAs of breast muscle at four developmental stages of Beijing-You chicken (BJY). (A) Differentially expressed genes (DEGs) between different stages. (B) Heatmap of DEGs by cluster analysis. (C) Venn diagram plot of DEGs. Figure 2 Functional analysis and sample time series analysis of differentially expressed genes (DEGs) of breast muscle at four developmental stages of Beijing-You chicken (BJY). (A) The top 10 significant GO enrichment terms. (B) The top 25 significant terms by KEGG enrichment analysis. (C) Short time-series expression miner (STEM) clustering of DEGs, the color indicates significant difference (p < 0.05) and gray indicates no significant difference (p > 0.05). Figure 3 Analysis of metabolites of breast muscle at four developmental stages of Beijing-You chicken (BJY). (A) Principal component analysis (PCA) of the identified metabolites. The X axis represents PC1 and the Y axis represents PC2. Each sample had ten biological replicates. (B) Significantly changed metabolites (SCMs) between different stages. (C) The top 25 significant terms of SCMs by KEGG analysis. Figure 4 Joint analysis of significantly changed metabolites (SCMs) and differentially expressed genes (DEGs) of breast muscle at four developmental stages of Beijing-You chicken (BJY). (A) Nine clustering modules with different expression trends of DEGs obtained by overweighted gene co-expression network analysis (WGCNA). The dendrogram shows DEG co-expression clusters. Different colors indicate DEG co-expression modules. (B) Heatmap showing module-metabolite relationships. Each row represents a different modules obtained from the WGCNA analysis. Each column represents a metabolite. Red indicates that there was a positive correlation between this cluster and the metabolite, and green indicates a negative correlation. The numbers in the module indicate the corresponding p-value and correlation coefficient. (C) Interaction network of amino acids and DEGs by cytoscape. Yellow circles represent amino acids. Pink diamonds represent DEGs involved in amino acids metabolism. (D) Interaction network of lysophosphatidylcholine (LPC) and DEGs. Yellow circles represent LPC. Pink diamonds represent DEGs involved in LPC biosynthesis. (E) Interaction network of inosine monophosphate (IMP) and DEGs. Yellow circles represent IMP. Pink diamonds represent DEGs involved in IMP biosynthesis. Figure 5 Identification of key metabolic pathways and genes related to the meat flavor of Beijing-You chicken (BJY). (A) The number of co-enrichment KEGG pathways of DEGs and SCMs. (B) Key pathways of flavor metabolites during BJY development. The blue or orange boxes below the metabolites indicate the contents during BJY development (from left to right: days 1, 56, 98, and 120). (C) Correlation between six hub DEGs and seven SCMs. Red indicates that there is a significant positive correlation between this gene and the metabolite, and green indicates a significant negative correlation (p < 0.05). The numbers indicate the corresponding correlation coefficient. foods-12-01025-t001_Table 1 Table 1 KEGG enrichment analysis of 82 intersecting genes. Pathway Pathway ID Gene_ID Differentially Expressed Genes ECM-receptor interaction gga04512 395210, 373987, 414837 SPP1, THBS1, THBS2 PPAR signaling pathway gga03320 422345 ACSL4 Focal adhesion gga04510 395210, 373987, 414837 SPP1, THBS1, THBS2 Melanogenesis gga04916 408082, 395703 EDNRB2, WNT11B Calcium signaling pathway gga04020 408082, 395971, 428149 EDNRB2, ADRB1, TBXA2R Fatty acid biosynthesis gga00061 422345 ACSL4 Apelin signaling pathway gga04371 395210 SPP1 Phagosome gga04145 373987, 414837 THBS1, THBS2 DNA replication gga03030 423688 DNA2 Fatty acid degradation gga00071 422345 ACSL4 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. Mir N.A. 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PMC10000372 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050954 diagnostics-13-00954 Article Blood Count-Derived Inflammatory Markers Correlate with Lengthier Hospital Stay and Are Predictors of Pneumothorax Risk in Thoracic Trauma Patients Vunvulea Vlad Conceptualization Methodology Validation Writing - original draft 123+ Melinte Razvan Marian Investigation Writing - review & editing Visualization 4+ Brinzaniuc Klara Validation Writing - review & editing Supervision Project administration 3 Suciu Bogdan Andrei Validation Formal analysis Investigation Data curation 3* Ivanescu Adrian Dumitru Software Validation Investigation 3 Halmaciu Ioana Validation Data curation Writing - review & editing 23 Incze-Bartha Zsuzsanna Validation Resources Supervision 3 Pastorello Ylenia Validation Resources Visualization 13 Trambitas Cristian Software Validation Data curation 3 Marginean Lucian Validation Investigation Writing - review & editing 12 Kaller Reka Software Validation Formal analysis Investigation 15 Kassas Ahmad Validation Resources Visualization 6 Hogea Timur Conceptualization Methodology Validation Writing - original draft 1 Bakir Sinan Academic Editor 1 Doctoral School of Medicine and Pharmacy, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, 540142 Targu Mures, Romania 2 Department of Radiology, Mures County Emergency Hospital, 540136 Targu Mures, Romania 3 Department of Anatomy, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540139 Targu Mures, Romania 4 Department of Orthopedics, Humanitas MedLife Hospital, 400664 Cluj Napoca, Romania 5 Clinic of Vascular Surgery, Mures County Emergency Hospital, 540136 Targu Mures, Romania 6 Faculty of Medicine in English, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540139 Targu Mures, Romania * Correspondence: [email protected] + These authors have contributed equally to this work. 02 3 2023 3 2023 13 5 95403 2 2023 22 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 ). (1) Background: Trauma is one of the leading causes of death worldwide, with the chest being the third most frequent body part injured after abdominal and head trauma. Identifying and predicting injuries related to the trauma mechanism is the initial step in managing significant thoracic trauma. The purpose of this study is to assess the predictive capabilities of blood count-derived inflammatory markers at admission. (2) Materials and Methods: The current study was designed as an observational, analytical, retrospective cohort study. It included all patients over the age of 18 diagnosed with thoracic trauma, confirmed with a CT scan, and admitted to the Clinical Emergency Hospital of Targu Mures, Romania. (3) Results: The occurrence of posttraumatic pneumothorax is highly linked to age (p = 0.002), tobacco use (p = 0.01), and obesity (p = 0.01). Furthermore, high values of all hematological ratios, such as the NLR, MLR, PLR, SII, SIRI, and AISI, are directly associated with the occurrence of pneumothorax (p < 0.001). Furthermore, increased values of the NLR, SII, SIRI, and AISI at admission predict a lengthier hospitalization (p = 0.003). (4) Conclusions: Increased neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), aggregate inflammatory systemic index (AISI), and systemic inflammatory response index (SIRI) levels at admission highly predict the occurrence of pneumothorax, according to our data. thoracic trauma chest injury pneumothorax inflammatory markers neutrophil-to-lymphocyte ratio monocyte-to-lymphocyte ratio platelet-to-lymphocyte ratio systemic inflammatory index systemic inflammatory response index aggregate inflammatory systemic index This research received no external funding. pmc1. Introduction Trauma is the world's top cause of disability and death in the first four decades of life. In this age group, the number of young adults who die from trauma exceeds all deaths from cancer combined . Thoracic injuries are highly significant in patients with severe trauma, occurring in up to 50% of patients with polytrauma . According to the current literature, the mortality rate following thoracic trauma varies between 25 and 50%, depending on the associated injuries . The assessment of thoracic trauma severity determines the choice of first therapy and the subsequent clinical course when treating patients with polytrauma. Although thoracic trauma specifically has received little attention in the literature, there is a wealth of information on the mortality-associated risk factors following trauma in general . Pathological inflammatory and anti-inflammatory responses that occur in the first hours following extensive trauma are one of the major contributing factors to mortality in post-traumatic patients and remain challenging to control and distinguish from a physiological immune reaction . The balance between these two antagonistic inflammatory responses, as predictors of outcomes in trauma patients, has received a lot of attention recently. In response to severe injury, patients frequently experience a variety of anomalies in their host defense mechanisms . Systemic inflammatory response syndrome (SIRS) is the result of an unbalanced inflammatory response that escalates and releases an excessive amount of inflammatory mediators, such as IL-1, IL-6, IL-8, and TNF . The injury burden is increased by the progression of such an uncontrolled cytokine cascade and hyperinflammation. This can lead to detrimental and frequently fatal events such as SIRS and multiple organ dysfunction syndrome (MODS) . Recently, there has been a growing interest in developing a trustworthy biomarker that can assess the prognosis of patients with thoracic trauma . The neutrophil-to-lymphocyte ratio (NLR) is one of the most accessible markers. This ratio has been proven to significantly predict the outcomes of patients with COVID-19 infection , cardiovascular diseases , and kidney disease and oncology . Another well-studied biomarker is the platelet-to-lymphocyte ratio (PLR), which has been shown to have excellent predictive value for the prognosis of patients in the fields of orthopedics and trauma care . Based on routine blood tests at admission, several other ratios can be calculated, such as the monocyte-to-lymphocyte ratio (MLR), aggregate inflammatory systemic index (AISI), systemic inflammatory response index (SIRI), and systemic inflammatory index (SII). The monocyte-to-lymphocyte ratio (MLR) has been proven to be a valid predictor of the occurrence of complication in strokes , and the outcomes and severity of hematological disorders and oncological patients . The NLR, PLR, and MLR, for example, have been the subject of a growing number of studies in recent years. However, their findings suggest that a combination of these ratios would increase their predictive value . Thus, the aggregate inflammatory systemic index (AISI), systemic inflammatory response index (SIRI), and systemic inflammatory index (SII) were discovered and proven useful when evaluating the severity and prognosis of patients with various chronic and acute pathologies . The prognosis ratios calculated from routine blood tests appear to be a helpful and cost-effective resource in trauma management. Although there are mentions in the literature of the correlation between the NLR and the outcomes of thoracic trauma patients , there are few to no papers published regarding the use of the PLR, MLR, SII, AISI, and SIRI as prognostic factors for the outcomes of patients with thoracic trauma. The purpose of this study is to establish the prognostic value of inflammatory biomarkers and the underlying risk factors in patients with thoracic trauma. 2. Materials and Methods 2.1. Study Design The present study was designed to be an observational, retrospective, analytical cohort study where we included all patients over the age of 18 who presented, were diagnosed with thoracic trauma, and admitted to the County Emergency Clinical Hospital of Targu Mures, Romania, between January 2015 and December 2022. All patients included in our study underwent a radiological examination of either a conventional X-ray or a CT scan, and all were diagnosed with thoracic trauma as the main diagnosis. We excluded patients who passed away within the first 24 h, suffered severe bone fractures with need for specialized orthopaedical care, had a history of hematological or oncological disorders, presented thromboembolic events in the last two months, and patients with pneumonia. We also excluded patients suffering from mediastinal hematoma and aortic dissection as such patients are referred to the cardiovascular surgery department, not the thoracic surgery department. All patients included in our study suffered from peacetime injuries. We initially split the patients in two categories: "Pneumothorax" and "No Pneumothorax" based on the findings at admission. 2.2. Data Collection We collected the following data from our patients: age, sex, medical history (of diabetes mellitus--DM, arterial hypertension--AH, atrial fibrillation--AF, ischemic heart disease--IHD, myocardial infarction--MI, chronic obstructive pulmonary disease--COPD, peripheral arterial disease--PAD, chronic kidney disease--CKD, tobacco use, and obesity (BMI > 30)) and length of hospital stay (LOS). Moreover, we were interested in the routine blood tests at admittance. From these results, we extracted the following data: hemoglobin levels, hematocrit, neutrophil count, monocyte count, lymphocyte count, platelet count, sodium, and potassium. We were also interested in the number and location of rib fractures. All data were collected from the hospital's integrated electronic database. 2.3. Inflammatory Biomarkers From the results of the initial blood test at admittance, we managed to calculate the following ratios: MLR = monocytes/lymphocytes NLR = neutrophils/lymphocytes PLR = platelets/lymphocytes SII = (neutrophils x platelets)/lymphocytes SIRI = (monocytes x platelets)/lymphocytes AISI = (neutrophils x monocytes x platelets)/lymphocytes 2.4. Study Outcomes The primary endpoint for our study was the risk of pneumothorax development. We also recorded the length of hospital stay as an outcome, making it our secondary endpoint. 2.5. Statistical Analysis Software-wise, we used SPSS for Mac OS (28.0.1.0) (SPSS, Inc., Chicago, IL, USA). All systemic inflammatory marker associations with category factors were evaluated using chi-square tests, whilst differences in continuous variables were evaluated using Student t-tests or Mann-Whitney tests. The receiver operating characteristic (ROC) curve analysis was used to determine the cut-off values for inflammatory markers and evaluate their predictive potential. Based on the Youden index (Youden index = sensitivity + specificity 1, ranging from 0 to 1), the suitable NLR, MLR, PLR, SII, SIRI, and AISI cut-off values were determined using the ROC curve analysis. 3. Results During our study period, we identified 611 patients suffering from thoracic trauma that met the inclusion criteria for our study. The mean age was 47.48 +- 18.66 (18-98) (Table 1). The majority of patients included were males (448, 73.32%), with 114 (25.44%) of them suffering from pneumothorax at admission. At admission, 155 patients (25.37%) presented with pneumothorax. The mean length of hospital stay was 6.73 +- 4.14 days. After splitting the patients into two lots depending on the occurrence of pneumothorax, we noticed an increase in the mean age for the "Pneumothorax" group to 51.68 +- 19.39 (p = 0.002), as well as a higher incidence of tobacco use (p = 0.019) and obesity (p = 0.038). As for the etiology of trauma, we found the majority of patients suffered from blunt trauma (539/611 patients, 88.22%). In this category, we considered all patients who suffered from motor vehicle accidents, workplace accidents, accidental falls, sport-related injuries, and suicide attempts. In terms of patients who experienced penetrating trauma, we included all patients who experienced hetero-aggression and stabbings. They accounted for 11.78% of all patients and 41.93% of pneumothorax patients. Moreover, patients who suffered from posttraumatic pneumothorax showed higher sodium levels (p = 0.024), higher neutrophil (p < 0.0001), monocyte (p < 0.0001), and platelet (p = 0.009) counts, and lower lymphocyte (p < 0.0001) counts. All hematological ratios were higher in the "Pneumothorax" group (p < 0.0001). The length of hospital stay was also longer in the "Pneumothorax" group (p = 0.003). The receiver operating characteristic curves of all hematological ratios were computed in order to assess if the initial values of these indicators were predictive for the occurrence of pneumothorax in patients with thoracic injuries . Table 2 displays the optimal cut-off value calculated using Youden's index, the areas under the curve (AUC), and the prediction accuracy of the markers. In terms of systemic inflammatory makers and the length of hospital stay, we computed the Spearman correlation, and we identified a positive correlation between the NLR, SII, SIRI, and AISI and length of hospital stay (all p < 0.05), as highlighted in Figure 2. We proceeded with the multivariate analysis of age, risk factors, all inflammatory ratios, and the occurrence of pneumothorax within the patients in the second group, as shown in Table 3. Furthermore, older patients (OR:1.01, p = 0.02), the presence of COPD (OR:2.93, p = 0.02), as well as tobacco (OR:2.20, p = 0.01), act as predictive factors for pneumothorax risk. In contrast, obesity acts as protective factor against pneumothorax (OR:0.65, p = 0.03). We considered an increased value of the NLR as being a value higher than the identified cut-off (NLR > 6, p < 0.001). This is similar for a high MLR (MLR > 0.62, p < 0.001), PLR (PLR > 165.71, p < 0.001), SII (SII > 1632.86, p < 0.001), SIRI (SIRI > 6.17, p < 0.001), and AISI (AISI > 1479, p < 0.001). 4. Discussion According to the recent literature, thoracic trauma is a frequently occurring presentation in injured patients . Post-traumatic pneumothorax is a common complication of chest injuries, occurring in between 20 and 55% of patients, associated with relatively high morbidity and mortality. The mean age reported in the literature varies between 39 and 61 years old . However, it is a preventable cause of death. Early diagnosis of pneumothorax can aid in the management of such patients, prevent hemodynamic deterioration, or occurrence of other complications. In the present study, the incidence of pneumothorax was 25.37% (n = 155/611), with a mean age of 47.48 +- 18.66, are similar findings to those found in the literature. Most studies found in the recent literature report a negative impact on the outcomes of trauma patients among smokers . In spite of all these findings, a recent paper published by Grigorian et al., which included 282,986 patients with chest injuries, reports a significantly better outcome in smokers, with a lower number of ventilator days (p = 0.009) and a lower rate of in-hospital mortality (p < 0.001). However, smokers appear to develop a higher rate of pneumonia (p < 0.001) . In our study, we identified a total of 34 chronic tobacco users (5.56%) and identified smoking as a negative predictor of outcomes, with a higher incidence of pneumothorax occurrence (OR = 2.29, p = 0.01). A plausible reason for this discrepancy can be attributed to the high proportion of smokers included in the study of Grigorian et al. totaling 57,619 patients (20.4%). The role of obesity as a risk factor for the outcomes of trauma patients is a topic of debate in the current literature. There are plenty of papers, including complex meta-analyses, that advocate for poorer outcomes of obese patients following major trauma . Some papers, however, found that obese patients suffering from trauma have a more favorable outcome with a faster recovery . According to our findings, obesity is a protective factor for the development of pneumothorax in patients suffering from chest injuries (OR = 0.65, p = 0.003). One of the reasons for such paradoxical findings can be attributed to the protective role of the adipose tissue upon blunt chest injuries. The type of trauma appears to also play an important role in the development of pneumothorax. We notice that the majority of patients included in our study suffered from blunt chest injuries, which is to be expected as we did not have any wartime injuries reported in the past few years. We also notice that the majority of patients with penetrating trauma develop pneumothorax (65/72), but as the number of patients suffering from penetrating trauma is low, we can consider these data as purely observational. The predictive values of hematological ratios in trauma patients have reportedly been researched more and more, although with conflicting results. Additionally, there has been a significant rise in the need for prognostic tools in trauma patients with unfavorable evolution and decompensation. Our study included 611 patients diagnosed with thoracic trauma. We identified the inflammatory biomarkers in patient blood samples at admission and determined the presence of pneumothorax using CT scans at admission. Our study's most important outcome is that the high baseline values for the NLR, MLR, PLR, AISI, SII, and SIRI are strong predictors for the development of post-traumatic pneumothorax. To the best of our knowledge, this is the first study to demonstrate that patients with high hematological ratios were more likely to develop pneumothorax and that the ratios predict a longer hospital stay. According to Soulaiman et al., there is a statistically proven association between the NLR at admission and the outcomes of trauma patients, where a higher NLR predicts an unfavorable outcome . According to this study, the optimal cut-off value for the NLR at admission was 4, which is a close value to our findings, with an AUC = 0.63 (70.3% sensitivity and 56.4% specificity), highlighting a satisfactory test quality. In comparison, we computed a cut-off value for the NLR of 6, with an AUC = 0.79, highlighting an increased test quality. In contrast, other studies, such as the one conducted by Dilektasli et al., revealed no statistically significant association between the NLR calculated from the blood samples at admission and the outcomes of trauma patients . These controverted findings inspired another study, conducted by Younan et al. , to investigate the association between the NLR and the outcomes of trauma patients. According to the aforementioned, an increasing trajectory of the NLR (calculated at admission, and 24 and 48 h later) is strongly associated with the outcomes of the patients (p = 0.002) and length of hospital stay (p < 0.001). The total number of patients included in their study appears to be more modest (207 patients); patients with all types of trauma were included, not just chest injuries. Despite all these limitations, the findings of their study appear to support ours. According to Jo et al., the PLR has significant prediction power for the outcomes of trauma patients (p < 0.0001) ; however, they found a higher lymphocyte count in the non-survival group compared to the survival group (183.0 [141.0;230.0] vs. 227.0 [188.0;265.0]). The PLR was also lower in the non-survival group compared to the survival group (51.3 [32.3;77.9] vs. 124.2 [79.5;187.2]). These findings are contrary to ours, where the lower the lymphocyte count and the higher the PLR, the worse the outcome. A recent study by Rau et al. , including 479 trauma patients, found that comorbidities and hematological ratios (NLRs, MLRs, and PLRs) do not possess any predicting capabilities in the outcomes of such patients. Although some of their findings appear to contradict ours, we must remember that their study included all types of trauma and survival was considered as the final outcome of patients. The fact that a majority of the patients included in their study had suffered from a head or neck injury can be an explanation for their findings. Another reason for the lack of association between the hematological ratios and the outcomes of trauma patients can be attributed to the selection criteria. Their study also included patients who underwent invasive procedures, such as surgery, or patients who required resuscitation or blood transfusion, which are factors that can alter hematological ratios. We have taken into account these possible limitations of such reputable studies; this is the reason why our study's main focus was thoracic trauma, with specific exclusion criteria. In the current study, according to the multivariate analysis, all the hematological ratios were able to predict the occurrence of pneumothorax (p < 0.0001 in all cases). Moreover, we proved that some increased hematological ratios can indirectly predict the occurrence of complications through an increased length of hospital stay (SII p = 0.022, r = 0.093; SIRI p = 0.008, r = 0.108; and AISI p = 0.009, r = 0.106). Lastly, the present paper also revealed a major risk factor for traumatic pneumothorax development in tobacco use (OR = 2.29, p = 0.019), whilst obesity is a protective factor (OR = 0.65, p = 0.038). The findings of our previous studies on the role of hematological biomarkers as predictive factors in the outcomes of both specific splenic trauma and abdominal trauma support the findings of the current paper. In the first paper, we found a significant association between the NLR and the severity of splenic injury (p = 0.02). The findings of the second paper revealed that the NLR, PLR, MLR, AISI, SII, and SIRI are powerful predictors of the development of acute kidney injury, mortality, and a composite endpoint of these two outcomes in abdominally injured patients (p < 0.001 in all cases). Nevertheless, the present study has a set of limitations. The first limitation relies on the design of the study as a retrospective monocentric study. Further improvement could be brought by extending the research to a multicentric prospective study. Secondly, due to the retrospective nature of our study, we were unable to gather enough data on chronic medications administered before admission (corticosteroids or anti-inflammatory drugs), which prevented us from assessing how various medications affect inflammatory biomarkers. Lastly, the study only analyzed the inflammatory biomarkers at admission. Repeated determination throughout the hospitalization period may better reflect the dynamics of the inflammatory process and may improve the quality of our findings. In spite of all these limitations, we consider our findings to be a stepping stone toward the development of new risk scoring systems for the improvement of the overall management of thoracic trauma patients and the early identification of patients at risk. We consider these hematological ratios to be especially important, taking into account their ease of determination and the low cost of assessment. 5. Conclusions Our data show that patients with thoracic injuries, who have elevated NLRs, PLRs, MLRs, SIIs, SIRIs, and AISIs at admission at values that are above our calculated cutoff, are likely to have sustained severe thoracic trauma, are likely to have developed pneumothorax, and will likely follow a long evolution with a long duration of hospitalization. Additionally, we proved that tobacco use is a strong predictor of the development of post-traumatic pneumothorax in such patients, whilst obesity is a protective factor. Given the ease of use of such ratios and the low cost of these metrics, they can be used in clinical practice to categorize patient treatment groups, develop predictive patterns, and classify risk groups for admission. Acknowledgments This paper was published with the support of the George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures and is part of a Ph.D. thesis from the Doctoral School of Medicine and Pharmacy within the George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, with the title "The study of the importance of pro-inflammatory factors as prognostic factors in the evolution of polytrauma studies", which will be presented by Vlad Vunvulea, with the approval of all authors. Author Contributions Conceptualization, methodology, writing--original draft preparation, V.V. and T.H.; software, C.T., R.K. and A.D.I.; formal analysis, investigation, B.A.S., R.K. and T.H.; investigation, L.M., A.D.I. and R.M.M.; resources, A.K., Z.I.-B. and Y.P.; data curation, C.T., I.H. and B.A.S.; writing--review and editing, K.B., I.H., L.M. and R.M.M.; visualization, Y.P. and A.K.; supervision, K.B. and Z.I.-B.; project administration, T.H., L.M. and K.B.; validation, all authors. 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 of Targu Mures Emergency County Hospital, Romania (protocol code 8524, on 5 April 2022). 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 ROC curve analysis concerning the pneumothorax risk: NLR (AUC: 0.798; p < 0.0001), MLR (AUC: 0.758; p < 0.0001), PLR (AUC: 0.714; p < 0.0001), SII (AUC: 0.807; p < 0.0001), SIRI (AUC: 0.799; p < 0.0001), and AISI (AUC: 0.799; p < 0.0001). Figure 2 Plot representation of the dispersion of data of the association between length of hospital stay and the inflammatory biomarkers. diagnostics-13-00954-t001_Table 1 Table 1 Demographic information, risk factors, comorbidities, laboratory data, and outcomes were compiled. The patients were divided into two lots based on the presence of pneumothorax at admission. Variables All Patients n = 611 Pneumothorax n = 155 (25.37%) No Pneumothorax n = 456 (74.63%) p Value Age mean +- SD (min-max) 47.48 +- 18.66 (18-98) 51.68 +- 19.39 (19-93) 46.12 +- 18.23 (18-98) 0.002 Male 448 (73.32%) 114 (73.54%) 334 (73.24%) 0.94 Female 163 (26.67%) 41 (25.15%) 122 (26.75%) Comorbidities and risk factors Arterial hypertension, No. (%) 160 (10.8%) 40 (25.81%) 120 (26.32%) 0.828 Ischemic heart disease, No. (%) 82 (13.42%) 24 (15.48%) 58 (12.72%) 0.269 Atrial fibrillation, No. (%) 33 (5.4%) 8 (5.16%) 25 (5.48%) 0.984 Myocardial infarction, No. (%) 20 (3.27%) 6 (3.87%) 14 (3.07%) 0.262 Diabetes mellitus, No. (%) 66 (10.8%) 12 (7,74%) 54 (11.84%) 0.122 Chronic obstructive pulmonary disease, No. (%) 55 (9%) 23 (14.84%) 32 (7.02%) 0.066 Peripheral arterial disease, No. (%) 45 (7.36%) 12 (7.74%) 33 (7.24%) 0.712 Chronic kidney disease, No. (%) 27 (4.42%) 9 (5.81%) 18 (3.95%) 0.271 Tobacco, No. (%) 34 (5.56%) 15 (9.68%) 19 (4.17%) 0.019 Obesity, No. (%) 224 (36.66%) 44 (28.39%) 180 (39.47%) 0.038 Type of trauma Blunt 539 (88.22%) 90 (58.06%) 449 (98.4%) <0.001 Penetrating 72 (11.78) 65 (41.93%) 7 (1.6%) Laboratory data Hemoglobin g/dL mean +- SD 12.54 +- 2.32 12.82 +- 2.01 12.45 +- 2.41 0.91 Hematocrit % mean +- SD 37.5 +- 7.15 38.29 +- 5.61 37.24 +- 7.56 0.12 Glucose mg/dL mean +- SD 132.46 +- 54.17 136.51 +- 47.49 131.15 +- 56.14 0.29 Sodium mean +- SD 137.31 +- 16.12 139.91 +- 12.71 136.48 +- 17 0.024 Potassium mean +- SD 4.38 +- 1.116 4.3 +- 0.88 4.4 +- 1.24 0.34 Neutrophils x103/mL mean +- SD 9.75 +- 5.07 13.13 +- 5.64 8.65 +- 4.35 <0.0001 Lymphocytes x103/mL mean +- SD 1.94 +- 1.02 1.52 +- 0.93 2.08 +- 1.01 <0.0001 Monocyte x103/mL mean +- SD 0.96 +- 0.86 1.18 +- 0.86 0.89 +- 0.84 <0.0001 Plt x103/mL mean +- SD 248.53 +- 90.46 265.39 +- 110.07 243.10 +- 82.57 0.009 MLR, mean +- SD 0.64 +- 0.63 0.96 +- 0.66 0.53 +- 0.59 <0.0001 NLR, mean +- SD 6.76 +- 6.4 12.12 +- 9.23 5.04 +- 3.83 <0.0001 PLR, mean +- SD 163.45 +- 113.55 229.41 +- 155.68 142.18 +- 86.14 <0.0001 SII, mean +- SD 1636.60 +- 1554.68 3040.74 +- 2251.73 1183.75 +- 853.06 <0.0001 SIRI, mean +- SD 6.89 +- 8.14 13.25 +- 10.4 4.83 +- 5.97 <0.0001 AISI, mean +- SD 1739.16 +- 2372.9 3421.47 +- 3097.28 1196.59 +- 1777.91 <0.0001 Outcomes Length of hospital stay, mean +- SD 6.73 +- 4.14 7.62 +- 4.26 6.45 +- 4.06 0.003 diagnostics-13-00954-t002_Table 2 Table 2 ROC curves, ideal cut-off values, AUC, and prediction accuracy of inflammatory indicators in terms of outcomes. Variables Cut-Off AUC Std. Error 95% CI Sensitivity Specificity p Value Pneumothorax NLR 6 0.798 0.024 0.751-0.845 76.5% 71% <0.0001 MLR 0.62 0.758 0.023 0.712-0.804 70.5% 72.9% <0.0001 PLR 165.71 0.714 0.025 0.665-0.763 60.4% 71.6% <0.0001 SII 1632.86 0.807 0.023 0.761-0.852 77.2% 73.4% <0.0001 SIRI 6.17 0.799 0.023 0.754-0.843 71.8% 76.2% <0.0001 AISI 1479.7 0.799 0.023 0.754-0.843 71.1% 75.8% <0.0001 diagnostics-13-00954-t003_Table 3 Table 3 Multivariate analyses of the age, risk factors, inflammatory ratios, and the occurrence of pneumothorax. Pneumothorax OR 95% CI p Value Age 1.01 1.006-1.02 0.002 COPD 2.93 1.15-7.50 0.02 Obesity 0.65 0.44-0.97 0.03 Tobacco 2.29 1.12-4.66 0.01 High NLR 6.03 3.94-9.21 <0.001 High MLR 5.97 3.97-8.97 <0.001 High PLR 3.51 2.39-5.17 <0.001 High SII 8.78 5.68-13.59 <0.001 High SIRI 8.55 5.43-13.47 <0.001 High AISI 7.73 5.06-11.85 <0.001 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. Lundin A. Akram S.K. Berg L. Goransson K.E. Enocson A. Thoracic injuries in trauma patients: Epidemiology and its influence on mortality Scand. J. Trauma Resusc. Emerg. Med. 2022 30 69 10.1186/s13049-022-01058-6 36503613 2. Bardenheuer M. Obertacke U. Waydhas C. Nast-Kolb D. 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PMC10000373 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050730 cells-12-00730 Article CRISPR/dCas9-KRAB-Mediated Suppression of S100b Restores p53-Mediated Apoptosis in Melanoma Cells Roy Choudhury Samrat 1* Heflin Billie 2 Taylor Erin 2 Koss Brian 2 Avaritt Nathan L. 2 Tackett Alan J. 2* Stricker Stefan H. Academic Editor 1 Pediatric Hematology-Oncology, Arkansas Children's Research Institute, University of Arkansas for Medical Sciences, Little Rock, AR 72202, USA 2 Department of Biochemistry & Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA * Correspondence: [email protected] (S.R.C.); [email protected] (A.J.T.); Tel.: +1-(501)-364-7531 (S.R.C.); +1-(501)-686-8152 (A.J.T.) 24 2 2023 3 2023 12 5 73015 9 2022 12 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 ). Overexpression of S100B is routinely used for disease-staging and for determining prognostic outcomes in patients with malignant melanoma. Intracellular interactions between S100B and wild-type (WT)-p53 have been demonstrated to limit the availability of free WT-p53 in tumor cells, inhibiting the apoptotic signaling cascade. Herein, we demonstrate that, while oncogenic overexpression of S100B is poorly correlated (R < 0.3; p > 0.05) to alterations in S100B copy number or DNA methylation in primary patient samples, the transcriptional start site and upstream promoter of the gene are epigenetically primed in melanoma cells with predicted enrichment of activating transcription factors. Considering the regulatory role of activating transcription factors in S100B upregulation in melanoma, we stably suppressed S100b (murine ortholog) by using a catalytically inactive Cas9 (dCas9) fused to a transcriptional repressor, Kruppel-associated box (KRAB). Selective combination of S100b-specific single-guide RNAs and the dCas9-KRAB fusion significantly suppressed expression of S100b in murine B16 melanoma cells without noticeable off-target effects. S100b suppression resulted in recovery of intracellular WT-p53 and p21 levels and concomitant induction of apoptotic signaling. Expression levels of apoptogenic factors (i.e., apoptosis-inducing factor, caspase-3, and poly-ADP ribose polymerase) were altered in response to S100b suppression. S100b-suppressed cells also showed reduced cell viability and increased susceptibility to the chemotherapeutic agents, cisplatin and tunicamycin. Targeted suppression of S100b therefore offers a therapeutic vulnerability to overcome drug resistance in melanoma. melanoma S100b CRISPR dCas9-KRAB apoptosis cell death National Cancer Institute/National Institutes of HealthR01CA236209 National Institute of General Medical Sciences/National Institutes of HealthP20GM121293 This work was funded by a grant from the National Cancer Institute/National Institutes of Health (R01CA236209) to Alan J Tackett. The study was also supported by grants from the National Institute of General Medical Sciences/National Institutes of Health (A.J.T & S.R.C, P20GM121293). pmc1. Introduction Melanoma is one of the deadliest forms of skin cancer, is particularly prevalent (2.5%) among the Caucasian population, and has almost doubled in incidence over the past three decades in the United States alone . Several serological biomarkers have been identified for early detection, staging, prognosis, and therapeutic determination of melanoma. Among them, a high serum level of S100B (S100 calcium-binding protein B) has emerged as the most reliable biomarker of progression and survival outcome of the disease . S100B (10.7 kDa) is a member of the S100 protein family that binds to its molecular targets by undergoing conformational changes at the carboxy-terminal EF-hand motif. The affinity of S100B-mediated protein-protein interactions is strengthened with the increase in intracellular Ca2+ concentrations. Ectopic upregulation of the protein has been noted in metastatic melanomas, as well as proneuronal, neural, or classic types of gliomas . In melanoma, intracellular S100B interacts with proteins of different signaling pathways , such that S100B activates the glycolytic enzyme fructose 1,6-biphosphate (aldolase) and increases metabolism of melanoma cells. The protein also interacts with cytoskeletal components such as tubulin, Rac1 (GTPase), or IQGAP1 (cdc42 effector), which alters motility of melanoma cells toward enhanced migration and invasion . In contrast, when extracellularly secreted via the receptor for advanced glycation end products (RAGE) signal transduction pathway, S100B facilitates tumor development in a mouse model of melanoma . Additionally, S100B triggers melanoma tumor growth by interacting with the C terminus of wild-type (WT)-p53, preventing protein tetramerization and covalent modifications (e.g., phosphorylation or ubiquitination) . Therefore, S100B-p53 interaction lowers the intracellular availability of free WT-p53 and limits the tumor-suppressing function of TP53 . Previously, siRNA-mediated cell-type-specific targeted inhibition of the S100B-p53 complex was shown to rescue protein levels of WT-p53, phosphorylated p53, and downstream p21 . The targeted inhibition also evoked poly-ADP ribose polymerase (PARP)-mediated apoptosis involving activation of caspase-3 or caspase-8 or aggregation of Fas death receptor upon ultraviolet irradiation . Several attempts have been made to develop small-molecule inhibitors (e.g., pentamidine) that inhibit molecular interactions between the Ca2+-S100B apoprotein and its binding proteins ; however, the small-molecule inhibitors, as well as siRNA-mediated knockdown, of S100B resulted in only transient restriction of melanoma cell growth. We aimed to develop a more stable and effective targeted approach that uses a CRISPR (clustered regularly interspaced short palindromic repeats) platform for stable suppression of S100B protein. Targeted epigenome editing previously was attempted by using a CRISPR and associated protein 9 (Cas9) endonuclease system that contained deactivated Cas9 (dCas9) fused to a transcriptional suppressor, Kruppel-associated box repressor (KRAB) . The KRAB domain exerts widespread transcriptional suppression through enrichment of H3K9me3 and condensation of chromatin . Herein, we report development of a dCas9-KRAB (DK) system for targeted perturbation of S100B expression to rescue WT-p53 and its associated tumor-suppression properties in melanoma cells. 2. Materials and Methods 2.1. TCGA Patient Cohorts Data from 28 retrospective studies available through the Cancer Genome Atlas (TCGA) were used to examine S100B expression in samples from patients with cutaneous (n = 443) or ocular (n = 80) melanoma, as well as patients with different cancer types (n = 10,071; comparison group) (Table S1). From the TCGA Firehose Legacy study, we selected a cohort of patients with skin melanoma (n = 287) on the basis of available data for DNA methylation, copy number (CN) alterations, and gene expression from the matched patient samples (Table S2) . Genetic and transcriptomic data from TCGA were extracted through the cBioPortal (www.cbioportal.org; accessed on 17 January 2022). GEP was analyzed from mRNA expression (RNA sequencing [RNA-seq]) data; we represent GEP data expressed in RNA-seq by expectation-maximization (RSEM), log2 scale. CN alterations are presented as the capped relative linear copy-number values, where we consider patients with diploid genomes for S100B, compared to those with gain (+1) or loss (-1) in CN. There were single cases for amplification (+2) or deep deletion (-2); these were excluded from the analysis. DNA methylation was assayed on an Illumina HumanMethylation450 (HM450) BeadChip platform (San Diego, CA, USA), and the average b-value from all probe sets against S100B was considered. Raw values for GEP, CN, and methylation from matched patients are summarized in Table S3. 2.2. Proteomics Data Set from Cases of Melanoma Treated with Immune Checkpoint Inhibitors (ICIs) A proteomics data set was analyzed from the consented (study #204543) and deidentified tissue biopsies from a cohort of patients with melanoma (n = 23) that was diagnosed at stage IV and treated with first-line ICIs (i.e., anti-CTLA4, PD-1, or a combination of monotherapies) at the University of Arkansas for Medical Sciences. The proteomics sample was prepared, and data were analyzed as reported earlier . Clinicopathological information of the patients, including response to ICIs, is summarized in Table S4. 2.3. Identification of DNase Hypersensitive Sites (DHSs) The chromatin state at the S100B promoter, including transcriptional start sites (TSSs) and intragenic regions, was examined by comparing DNase-sequencing data from SK-MEL-5 melanoma cell lines (accession ID: ENCFF627WEJ) to that from primary keratinocytes derived of newborn foreskin (accession ID: ENCFF910KFI); both data sets were acquired from the ENCODE database. The DHS signals were represented as read-depth normalized signal. S100B mRNA levels in the same cell line (accession ID: ENCFF249LKO) and primary keratinocytes (accession ID: ENCFF249BFY) were also analyzed. The bigwig (hg38) files for both DHSs and RNA-seq data were loaded on the integrative genomics viewer (v 2.14.0, Broad Institute, Cambridge, MA, USA) for visualization. 2.4. Prediction of Homology between Human and Murine Proteins The amino acid sequences of human (S100B) and murine (S100b) homologs of the protein were compared by using Clustal Omega (v 1.2.4) (EMBL-EBI, Hinxton, UK) function and were presented by using Jalview (v 2.11.2.0) . 2.5. Prediction of Transcription Factor (TF) Binding The putative TFs that interact with the murine single-guide RNA (m-sgRNA)-binding sites on S100b were predicted by using the target regions as input for the PROMO database accessed on 21 May 2020) that uses TRASFAC for the prediction analyses . The output was specific to Mus musculus. 2.6. Development of CRISPR/dCas9-KRAB Tool A plasmid containing the KRAB domain fused to dCas9 and the programmable sgRNA vector were obtained from Addgene, Watertown, MA, USA (#99372, and #44248, respectively). The plasmid #44248 contains an EGFP (enhancer green fluorescent protein)-specific sgRNA and has been used as an off-target control for the present study. Three murine S100b-specific sgRNAs were selected for the present study, based on their predicted efficacy of inhibition at the target site. m-sgRNA-1 and m-SgRNA-2 were selected from the sgRNA library that was recommended for the mouse genome ; m-SgRNA-3 was custom designed by using the CHOPCHOP accessed on 2 July 2020) algorithm design tool (Table S5). All sgRNA-binding sites were mapped with Mouse Genome Informatics accessed on 12 June 2020) and annotated against the GRCm38/mm10 genome. The selected sgRNAs in combination with the scaffolds were obtained as gene blocks (gblocks) from Integrated DNA Technologies, Coralville, IA, USA. The gblocks were PCR amplified (Table S6) with CloneAmpHiFi PCR Premix (Takara, Kusatsu, Shiga, Japan) and were integrated into the sgRNA plasmid, flanked by BstXI and XhoI (New England Biolabs, Ipswich, MA, USA) sites. Correct clones were confirmed with low-throughput sequencing (Table S6, sequencing primers). 2.7. Cell Lines and Transduction Murine B16-F1 (CRL-6323) melanoma and B16-F10 (CRL-6475) metastatic melanoma cells were purchased from ATCC (American Type Culture Collection, Manassas, VA, USA). Cell lines were cultured in Dulbecco's Modified Eagle Medium supplemented with 10% FBS, 1% penicillin-streptomycin (Thermo-Fisher, Waltham, MA, USA), and 1% glutamine and maintained at 37 degC and 5% CO2. Cells were transduced with plasmid encoding DK alone, or in combination with the plasmids encoding sgRNAs specific to S100b or EGFP (sgRNAEGFP). Transduction was accomplished with a one-step lentivirus packaging system (Takara, Kusatsu, Shiga, Japan) per the manufacturer's instructions. Briefly, 4-5 x 106 LentiX-293T cells (Takara) were transfected with the plasmids in Opti-MEM reduced serum medium (Thermo-Fisher, Waltham, MA, USA) and were incubated for 4-6 h. Next, each culture was supplemented with 14 mL complete medium and then incubated for 48 h. Supernatants were collected, passed through 0.45 mM syringe filters, and added dropwise to polybrene (8 mg/mL) charged F1 or F10 cells. Cells co-transduced with DK and sgRNA constructs were selected with puromycin (1 mg/mL), followed by FACS sorting (FACSARIA III, BD, San Jose, CA, USA) for mCherry+ cells (>95%). 2.8. Quantitation of Expression with Quantitative Real-Time PCR (qPCR) Expression of target genes was determined in reference to endogenous GAPDH, out of total RNA extracted from the cells. From cells that had been treated for 24 h, total RNA was extracted (RNeasy Mini Kit, QIAGEN, Hilden, Germany) and converted to c-DNA (Iscript Advanced cDNA synthesis kit, Bio-Rad, Hercules, CA, USA). The fold change in S100b expression was then determined, in triplicate, with qPCR (StepOnePlus Real-Time PCR Systems; v 2.0 Applied Biosystems, Waltham, MA, USA), compatible with SYBR green master mix (Thermo-Fisher). Amplification reactions were carried out at 95 degC for 1 min, followed by 40 cycles at 95 degC for 15 s and 60 degC for 1 min. Primers used to amplify murine S100b (qMmuCID0015305), TP53 (qMmuCIP0032520), and GAPDH (qMmuCED0027497) were purchased from commercial sources (PrimePCR SYBR Green Assay, Bio-Rad, Hercules, CA, USA). The primers for DIP2A, PRMT2, CDKN1A, AIFM1, CASP3, PARP-1, and GAPDH were custom synthesized with IDT (Integrated DNA Technologies, Coralville, IA, USA), and primer sequences are summarized in Table S7. 2.9. Western Blot Analysis of Protein Levels We prepared whole-cell lysates by using RIPA buffer (Thermo-Fisher, Waltham, MA, USA) per the manufacturer's instructions. To determine levels of S100b protein, an aliquot of lysate (40 mg total protein, determined with the BCA assay; Pierce) was loaded onto 4-20% Bis-Tris gels (Thermo-Fisher, Waltham, MA, USA); to determine levels of p21, p53, AIFM1, cleaved Caspase-3, or PARP-1 proteins, aliquots of lysate (approximately 20 mg total protein) were loaded onto 4-12% Bis-Tris gels (Thermo-Fisher, Waltham, MA, USA), and proteins were electrotransferred to PVDF membranes (Bio-Rad, Hercules, CA, USA). The blots were blocked in 5% milk in TBST for 1 h, followed by overnight incubation at 4 degC with primary antibodies in 1% milk. Blots were probed with primary antibodies (Table S8) per the manufacturer's instructions. Blots were then washed 3 times with 1% milk and incubated with HRP-tagged secondary antibody for 1 hour. Finally, blots were washed 3 times in TBST and were developed with enhanced chemiluminescence reagents (Perkin Elmer, Waltham, MA). Densitometries of the bands from the blots (wherever applicable) were prepared with ImageJ accessed on 23 February 2023), v 1.53t, National Institute of Health, Bethesda, MD, USA). 2.10. Apoptosis and Cell Death Assay F1 and F10 cells were seeded in 6-well plates (5 x 104 cells per well). After 24 h, they were treated with staurosporine (Seleckchem, Houston, TX, USA) at indicated doses for 24 h. Apoptosis and cellular mortality then were determined with flow cytometry (FACS Verse, BD Biosciences, San Jose, CA, USA); staining with annexin V-FITC (Biolegend, San Diego, CA, USA) and DAPI (Sigma, St. Louis, MO, USA) was used to determine the percent viable (i.e., Annexin V-, DAPI-) cells. 2.11. Cell Proliferation and Chemotherapeutic Sensitivity Assay Both B16 melanoma cell lines were seeded (5 x 104 cells per well) in 12-well plates and imaged (from at least 10 different fields) after 24 and 48 h to examine differences in cell proliferation between the treatment and control groups. Additionally, B16 melanoma cells were seeded in 96-well plates (5 x 103 cells per well), incubated for 24 h, and treated as indicated. Viability of co-transduced (DK + m-sgRNA-1) cells and untreated control cells was determined with a CellTiter-Glo Luminescent Cell Viability Assay kit (G7570, Promega, Madison, WI, USA) after 24 and 48 h in the presence or absence of two chemotherapeutic agents, cisplatin (13119, Cayman Chemicals, Ann Arbor, MI, USA) and tunicamycin (11445, Cayman Chemicals, Ann Arbor, MI, USA). Drugs were serially diluted from the stock solution (2 mM) and added to cell cultures in the range of 5 mM to 10 nM. At the end of 24 and 48 h of incubation, equal volumes (100 mL each) of assay solution and cell suspension were mixed and incubated at room temperature for 10 min. Relative luminescence was recorded with a spectrometer (Agilent BioTek, Winooski, VT, USA Gen5 Microplate reader), and the half-maximal inhibitory concentration (IC50) value for each drug was plotted with GraphPad Prism, v7.0, Boston, MA, USA. 2.12. Statistical Analysis We used the non-parametric Mann-Whitney U test or Dunn's multiple comparison test to determine the significance of differences between the groups being compared. Significance was defined as p < 0.05. Statistical analyses and associated graphs were generated with GraphPad Prism, Boston, MA, USA. 3. Results 3.1. Overexpression of S100B Is Linked to Copy-Number Changes and Epigenetic Alterations of the Gene We evaluated S100B expression (RNA-seq V2, RSEM, log2) in 10,071 patient-derived samples of 28 different cancers from the TCGA repository (Table S1). Expression of S100B was highest in glioblastoma, followed by skin cutaneous melanoma (SKCM). S100B expression in SKCM samples (n = 443) ranged (25-75% quartile) from 4287.6 to 16,048.4 with a median of 8959.4 +- 14,212.4 (standard deviation). In samples of ocular melanoma (UVM) (n = 80), the gene was expressed at a similar fashion to SKCM or was overexpressed (646.7 +- 1474.9), relative to other cancer types . A separate in-house proteomics study of a cohort of patient-derived SKCM samples demonstrated that, in the subgroup (n = 12) that was non-responsive to ICIs anti-CTLA-4, anti-PD1, and anti-CTLA4 + anti-PD1 combined therapy, the S100B protein was upregulated (p < 0.05, >2-fold change), compared to the subgroup (n = 10) that was responsive . These findings strongly suggest that ectopic upregulation of S100B might play a critical role in development of refractory SKCM and could contribute to therapeutic resistance in the disease. Next, we combined the data on S100B expression with data on CN alterations and DNA-methylation profiles in matched SKCM samples (n = 285), available from TCGA. We observed that 17.5% (50/285) of samples had gains in S100B CN, and 21% (60/285) of samples had heterozygous deletions in CN of S100B, while 61.4% (175/285) of samples were diploid for S100B. A significant (p < 0.01) decrease in median expression of S100B (RSEM = 5624.3) was observed in samples with CN losses, compared to those with gains (RSEM = 14,119.5) but not to those with diploidy. However, weak correlations (p > 0.05; R2 < 0.2) were observed when the relative linear values of CN for individual subgroups (gain, loss, or diploid) and their expression profiles were compared . We also investigated whether S100B expression correlates to DNA methylation (b-values, probe: cg12092309) of S100B. Methylation ranged (25-75% quartile) from 0.54 to 0.87, with a median value 0.74. We observed a moderate (R2 = 0.216; p < 0.01) negative correlation between S100B methylation level and expression in SKCM samples, such that samples with lower methylation levels have relatively higher expression and vice versa . Additionally, we analyzed signal intensities based onDHS (DNAse hypersensitive sites) to assess the chromatin state of S100B in the SK-MEL-5 cell line, which is representative of human SKCM, and compared it to that in primary keratinocytes derived from foreskin of human newborns. We observed epigenetic priming in the melanoma cells, such that DHS enrichment was observed in SK-MEL-5 cells at the S100B TSS and upstream promoter, which spans 578 bp (chr21:46,604,961-46,605,537) . The conformational change in chromatin state may be best linked to S100B upregulation in melanoma. This is supported by RNA-seq analysis of the same set of samples, which revealed no S100B transcript in primary keratinocytes but marked S100B transcript from exon (E)2 and E3 in SK-MEL-5. Next, we evaluated amino acid sequence homology between human S100B and its mouse ortholog S100b. The analysis showed that the proteins are almost identical. Each contains 92 amino acids with a single base substitution (asparagine to glutamic acid) at position 63 , which is predicted not to significantly alter the protein's secondary structure (Jalview 2.11.1.0). Mouse B16 melanoma cells have been used for expressing differential levels of S100b under different pathological conditions in conjunction with tumor development . We used the F1 and metastatic F10 melanoma cell lines to determine whether suppression of the gene can evoke anticancer phenotypes in treated cells. S100b expression (signal intensity relative to endogenous GAPDH) in F10 cells (0.58) was significantly (p < 0.05) lower than in F1 cells (1.72) . 3.2. S100b Expression Is Suppressed by CRISPR/dCAS9-KRAB We aimed to suppress the S100b expression by using CRISPR-KRAB-mediated interference at selected loci of the gene. S100b-specific m-sgRNAs were selected from the previously reported CRISPR inhibition library specific for the mouse genome or were designed with an online algorithm tool . Ref. m-SgRNA-1 and m-SgRNA-2 were targeted at 10 bp and 55 bp, respectively, downstream from the S100b TSS (chr10:76253899-76253915); m-SgRNA-3 was targeted at 49 bp upstream of the TSS (chr10:76253817-76253822) . The targeted S100b regions also contain putative binding sites (predicted by the TRANSFAC tool) for multiple TFs. In particular, we observed the prevalence of c-Fos, C/EBP-b, and NF-1 TFs within 20 bp of the target sites of the 3 m-sgRNAs, suggesting their putative regulatory roles in determining upregulation of S100b . The DK repressor protein was stably expressed in F1 and F10 cells via lentiviral transduction and was maintained under puromycin selection . Additionally, the m-sgRNA vectors harboring an mCherry fluorophore allowed the use of FACS sorting to enrich (>95%) co-transduced cells . The cells were transduced with DK module with or without three individual S100B-specific sgRNAs. Cells transduced with DK in combination with sgRNAEGFP served as an off-target control for the current study. The inherent transcription-repressive nature of the KRAB protein resulted in reduced S100b mRNA levels in both F1 and F10 cell lines, whereas combinatorial treatment with DK plus selective m-sgRNAs resulted in different degrees of reduction in the gene expression, compared to the parental lines (except for m-sgRNA-3 in F10). Therefore, to control for the effects of KRAB, we used DK-transduced cells as the baseline to which we compared the cells that were also transduced with the m-sgRNAs, for determining their effects on S100b expression. S100b expression was significantly (p < 0.05) reduced in the B16-F1 cells treated with the combination of DK plus m-sg-RNA-1, compared to the cells treated with DK alone . In contrast, S100b expression was increased in F1 cells when treated with the combinations of DK plus remaining S100b-specific sgRNAs (m-sgRNA-2/3) or sgRNAEGFP . A similar pattern was observed in the change in S100b mRNA expression in the B16-F10 cells, such that the gene expression was further reduced (p > 0.05) in cells treated with the combination of DK and m-sg-RNA-1, compared to cells transduced with DK alone. The combination of DK with m-SgRNA-2/3 or with sgRNAEGFP in either type of B16 cells remained ineffective in suppressing S100b expression. Additionally, S100b expression remained unaltered or insignificantly changed in both cell lines when transduced with vectors containing individual m-sgRNAs specific to S100b or EGFP without the KRAB module, compared to non-transduced parental lines . We observed a significant decrease in S100b mRNA expression in both the B16 cells, transduced with DK fusion alone, whereas the protein expression completely disappeared in cells transduced with the combination of DK plus m-SgRNA-1. Therefore, the S100b protein-expression changes in the similar direction to the changes in mRNA level in both F1 and F10 cells. Western blot results also corroborated the fact that S100b is much less expressed, both at the level of mRNA and protein in the F10 cells compared to the F1 cells. However, the S100b protein-expression band was totally resolved in the F10 cells treated in combination with DK plus m-SgRNA-1. Next, to examine the specificity of the CRISPR-KRAB toolbox developed here, we looked into the possible changes in expression of PRMT2 and DIP2A, two adjacent genes to S100b on Chr.10 (mm10) . We did not observe any significant (p > 0.05) reduction in the expression of PRMT2 and DIP2A, indicating that the action of CRISPR-KRAB interference was target-specific . In summary, the combination of DK plus m-SgRNA-1 imparted the greatest repressive effects on S100b expression, and CRISPR-KRAB interference was more profound in F1 cells than in F10 cells. Therefore, we continued with this combination for the downstream biological analyses. 3.3. S100b Suppression Restores WT-p53 Level and Activates Apoptotic Signaling Based on the previous literature , we hypothesized that DK-mediated suppression of S100b might increase the availability of intracellular free WT-p53 and reactivate the tumor suppressor function of TP53 . DK plus m-SgRNA-1 resulted in no observed increases in mRNA levels of TP53 in F1 or F10 cells . However, in both cell types, co-transduction with DK plus m-SgRNA-1 resulted in significantly increased (p < 0.05) p53 protein levels , while transduction with only DK resulted in no marked changes in p53 protein levels in both cell types. As previously mentioned, targeted inhibition of S100b may release intracellular S100b-bound p53, potentially increasing levels of WT-p53 and its downstream product p21 or apoptogenic proteins . Therefore, to investigate the consequences of S100b suppression, we assessed the effects of DK on induction of apoptosis in the target cells. In both F1 and F10 cells, transduction with DK plus m-SgRNA-1 resulted in significantly increased (p < 0.05) expression of CDKN1A (p21) in F1 cells both at the level of mRNA (14% increase) and protein , compared to F1-control. In contrast, a marginal (p = 0.05) increase in CDKN1A (11%) expression was observed in F10 cells . Nonetheless, the p21 protein level was significantly increased (p < 0.05) in the F10 line, compared to the control . To test the effects of elevated p53 and p21 levels on apoptosis, we treated the control (F1/F10) and DK-m-SgRNA-1 transduced cells with staurosporine (STS), a generic inducer of apoptosis. S100b-suppressed F1 cells, compared to the parental line, had increased cell death and susceptibility to serial concentrations (0.1 nM, 0.05 nM, 0.025 nM, 0.01 nM) of STS. An untreated control and exceedingly high dose (10 mM) of STS were used as negative and positive controls for cell viability assays. For instance, at 0.1 mM STS, we observed 11% less cell viability in F1 cells transduced with DK plus m-SgRNA-1 (26.1%) than in the parental cells (37.5%) ; however, we did not observe similar significant changes in cell death in studies with the F10 cells (data not shown). Next, to further investigate the observed cell death in the S100b-suppressed cells, we examined expression of key caspase and non-caspase proteases that are involved in apoptotic signaling pathways. We started by determining expression of mitochondrial apoptosis-inducing factor (AIFM1) , which was significantly increased (p < 0.05) in both mRNA and protein expression in the DK+m-SgRNA-1-transduced F1 cells, compared to non-transduced and DK+/-sgRNAEGFP control cells . The impact of differential upregulation of AIFM1 then was evaluated in conjunction with caspase-3 activation. We did not observe any significant changes in the CASP3 mRNA expression in DK+m-SgRNA-1 transduced cells . In contrast, a capase-3 protein cleavage (~17 kDa) was evident in cells transduced with DK+m-SgRNA-1 ; however, we did not observe noticeable changes in caspase-8 mRNA or protein levels (data not shown). Finally, we examined whether DK-m-SgRNA-1 affects expression of PARP-1, the substrate of caspase-3 . We detected a significant (p > 0.05) increase in PARP-1 mRNA level , while the cleaved subunit (~95 kDa) of PARP-1 protein was observed in DK+m-sgRNA-1 transduced cells but not in control cells . In contrast, F10 cells transduced with DK+/-m-sgRNA-1 or sgRNAEGFP failed to evoke any apoptogenic changes, compared to the control cells. In F10 cells, S100b suppression also did not result in altered protein levels of caspase-3/caspase-8 or in cleaved PARP-1 , indicating that an apoptotic response was not evoked. In summary, DK suppression of S100b efficiently evoked p53-mediated mitochondrial apoptotic machinery in F1 melanoma cells but not in F10 cells, despite elevation of WT-p53 and p21 proteins in these cells. This suggests a mechanistic difference in S100b regulation between the B16 lines, which needs further investigation. 3.4. S100b Suppression in Melanoma Cells Decreases Their Viability and Increases Their Susceptibility to Chemotherapeutics We observed reduced cell viability in both the F1 and F10 cells co-transduced with DK in combination with m-SgRNA-1. We determined the percentage of viability by determining the amount of ATP produced by live cells 24 h and 48 h after initial seeding of cells in a 96-well plate (1 x 104 cells per well). Compared to the control cells, co-transduced F1 cells had a 65% reduction and F10 cells had a 40% reduction (p < 0.05) in cell viability after 24 h. In contrast, after 48 h, F10 cells co-transduced with DK plus m-SgRNA-1 had only 13% less viability (p = 0.14) than control cells, but co-transduced F1 cells continued to have at least 32% less viability (p < 0.05) than control cells. Next, we treated S100b-suppressed F1 and F10 cells with chemotherapeutic agents against metastatic melanoma: cisplatin, a platinum analog, and tunicamycin, an inducer of endoplasmic reticulum stress . We determined the IC50 after incubating cells with each drug for 24 h; as control comparison groups, we used F1 and F10 cells that were not CRISPR-transformed. For controlling melanoma cell growth, tunicamycin was found to be more efficacious than cisplatin. The IC50 against cisplatin was achieved at 77.5 nM (R2 = 0.83) in the S100b-suppressed F1 cells, compared to the F1 control cells (IC50 = 851.3 nM; R2 = 0.93); the IC50 against cisplatin was achieved at 138.4 nM (R2 = 0.97) in the S100b-suppressed F10 cells, compared to the F10 control cells (IC50 = 611.8 nM; R2 = 0.92) . The IC50 against tunicamycin, however, was achieved at a concentration as low as 9 nM (R2 = 0.93) in the S100b-suppressed F1 cells, compared to 185.3 nM (R2 = 0.96) in the F1 control cells. In contrast, in the S100b-suppressed F10 cells, the IC50 of tunicamycin was attained at 50 nM (R2 = 0.91), compared to 165 nM (R2 = 0.96) in the F10 control cells . Overall, our data suggest that S100B suppression cooperatively works with the chemotherapeutic agents that trigger cell death by evoking apoptotic responses, thus potentially sensitizing melanoma cells to these inhibitors. 3.5. Discussion Overexpression of S100B and its clinicopathological relevance in melanoma has been well studied. The study reported here elucidated the role of genetic and epigenetic modifications underlying oncogenic overexpression of S100B. For instance, we demonstrated that S100B expression is significantly (p < 0.05) higher in patient-samples with gains in CN of the gene, compared to those with losses in CN of the gene . However, this observation needs further validation and inclusion of more study cohorts, because we did not observe significant alterations in gene expression levels when comparing samples with losses in S100B CN and those diploid for S100B. At the epigenetic level, we investigated alterations in DNA methylation and chromatin state of the gene. We observed a moderate negative correlation between DNA methylation and expression, suggesting that the HM450 probe possibly is targeted to the promoter of the gene, where DNA methylation is inversely proportional to gene expression . At the chromatin level, we observed an event of epigenetic priming at the S100B promoter, such that the TSS at the upstream promoter showed enrichment for DHS in SK-MEL-5 melanoma cells. This seems reliable because, in primary keratinocytes, the same region remains devoid of such DHS marks. The chromatin state alterations of S100B in melanoma cells could be logically ascribed to overexpression of the gene because it does not seem to be expressed in primary keratinocytes at levels comparable to those in melanoma cells. Enhanced molecular interactions between S100B and WT-p53 proteins in melanoma patient samples were demonstrated to impair WT-p53 function for tumor suppression through restricted cell cycle arrest , which leads to increased resistance to chemotherapeutics . In the present study, we customized inactivation of S100b expression in two murine melanoma cell lines by using a CRISPR/dCas9 system that allowed for restoring intercellular levels of WT-p53 that might otherwise be bound to the S100b protein, thereby salvaging p53-mediated cell death and apoptosis. Our approach could be broadly applicable to most melanoma cases, irrespective of S100B CN gain or loss because the CRISPR/Cas9 system can intrinsically suppress multiple copies of the same gene . We observed varying degrees of DK efficacy among the tested sgRNAs, specific to S100b or specific to EGFP and cell lines, which may be attributed to several factors. For instance, we observed little to no S100b-inhibition in either cell types transduced with a combination of DK plus m-SgRNA-2 or m-SgRNA-3. This could be partly due to the fact that the target region is already masked or occupied with endogenous TFs, leaving a relatively narrow window of DNA sequence available for binding sgRNAs or dCas9. We observed that the combination of m-SgRNA-1 and DK imparted the strongest suppression of S100b expression in both cell lines that were studied. However, combining DK with all three m-sgRNAs did not result in better suppression of S100b (data not shown), which could be partly related to the inefficacy of m-SgRNA-2 and m-SgRNA-3. For the current study, cells transduced with DK plus sgRNAEGFP were used as an off-target control. It was observed that induction of cells with DK alone or DK in combination with S100b-specific sgRNA-2/3 or gRNAEGFP reduced the gene expression, compared to the parental lines , which, however, did not correlate to the changes in downstream apoptotic responses. Therefore, the generic reduction in S100b expression may be ascribed to the lentiviral effect on cells, which was not consistent with the downstream apoptotic signaling. In contrast, reduction of S100b expression was consistent with the expression of apoptosis-responsive proteins. This makes the combination of DK plus m-sgRNA-1 a unique and selective candidate for the intended purpose. S100b suppression significantly (p < 0.05) increased levels of p53 and its downstream p21 protein. However, CRISPR interference was not evident at the mRNA level for TP53 in either cell line . This could be explained by the fact that S100B does not act upstream of the TP53 signaling cascade and, therefore, may not have significant effects on expression of the gene. The disconnect between p53 mRNA and protein levels also aligned with results of a previous study in which siRNA-based perturbation of S100b did not alter TP53 mRNA levels but significantly increased levels of total p53 and of phosphorylated p53 . Overall, our findings support the hypothesis that suppressed S100b possibly lost its affinity for intracellular p53, thereby facilitating elevated levels of WT-p53 protein. We also observed that the degree of S100b inhibition correlated with p53-mediated activation and apoptotic changes, such that S100b inactivation and apoptotic changes in the F1 cells were profound, compared to those in the F10 cells. The decreased efficacy of DK against the F10 cells may be due to intrinsically lower expression of S100b in F10, relative to F1 cells, or due to ineffective binding of m-SgRNA-1 to the target region, presumably due to occupancy by other endogenous TFs. Disparities in the degree of functional outcomes between the two cell lines also could be explained by findings from previous studies reporting differential cytogenetic properties . In this case, optimization of the KRAB suppressor system by integrating additional repressors, such as MeCP2 or EZH2, may impart superior gene inactivation effects against the F10 cells . Finally, S100b inhibition decreased cell viability and increased susceptibility of melanoma cells to the chemotherapeutics. A previous study found cisplatin to be moderately effective against melanoma patients . Similar findings were observed for the tunicamycin treatment. Similar to the S100b inhibition and apoptotic responses, chemotherapeutic susceptibility was also achieved at relatively lower concentrations in F1, compared to the F10 cells. A rational follow-up of the present study is aimed at determining the efficacy and persistence of the DK/CRISPR toolbox in other human and murine melanoma lines having high levels of S100b. Another limitation of the current study is that the S100b-specific DK/CRISPR tool needs further functional validations in vivo. Accordingly, the toolbox might need further modifications such that we may need to introduce additional suppressor domains, such as MeCP2, to the KRAB domain for better suppression efficacy . Nonetheless, based on the outcomes from the reported system, we can flexibly modify the current toolbox by introducing additional transcriptional repressors or epigenetic modulators for robust suppression of any gene or gene network. The proof of concept generated here strongly encourages studies of different signaling pathways involved in sustaining malignant growth in melanoma cells. Acknowledgments The manuscript was critically read by Tung-Chin Chiang, and Issam Makhoul. The manuscript was edited by the Science Communication Group at the University of Arkansas for Medical Sciences. Supplementary Materials The following supporting information can be downloaded at: Figure S1: S100B expression, relative to GAPDH, was determined by quantitative real time PCR in B16-F1 and B16-F10 melanoma cell lines. Cells individually transduced with S100B-specific murine single guide RNAs (m-sgRNAs) did not show significant (p > 0.05) changes in gene expression, compared to parental cells (no transduction; negative control).; Figure S2: Significant increases in mRNA levels of CDKN1A (p21), but not TP53 (p53) were observed in B16-F1 melanoma cells after transduction with dCas9-KRAB in combination with m-sgRNA-1, compared to control cells (no transduction or transduction with only dCas9-KRAB). In contrast, no significant changes in mRNA expression for both gene were observed in B16-F10 cells; Figure S3: B16-F10 melanoma cells transduced with dCas9-KRAB, with or without m-sgRNA-1, showed no noticeable apoptotic changes, such that apoptotic protein levels remained unaltered or were not cleaved; Table S1: S100B expression in PanCancer patient samples, as available in TCGA PanCancer Atlas Studies; Table S2: Age, gender and disease stage of the skin melanoma patients (n = 287), as available from the Skin Cutaneous Melanoma (TCGA, Firehose Legacy) study; Table S3: S100B expression, copy number alterations (CNA) and methylation values in skin cutaneous melanoma patients (n = 287), as available from the Skin Cutaneous Melanoma (TCGA, Firehose Legacy) study; Table S4: S100B protein expression in a cohort of melanoma patients (n = 23), who received immune checkpoint inhibitors (ICI), and their demographic and clinicopathological information; Table S5: Design of murine S100B specific sgRNA sequences, as used in the present study; Table S6: Primers used in the present study for PCR amplification of gblocks and sequencing analyses; Table S7: Primers used in the present study for PCR amplification of the target genes; Table S8: List of antibodies, used in performing Western Blotting. Click here for additional data file. Author Contributions S.R.C. conceptualized the work with A.J.T. and S.R.C. performed majority of the experiments, analyzed data, and wrote the article with A.J.T. and B.H. has helped SRC in reviving, handling, and maintaining the parental and selective CRISPR modified B16-F1 and F10 cells, lentiviral transduction of scramble constructs, and in selection of scramble sgRNA-positive clones using FACS. E.T. performed the proteomics analysis for melanoma samples from patients who received immune checkpoint inhibitors. B.K. helped in performing the flow cytometry and related analyses for the cell death study. N.L.A. helped in designing the primers for qPCR studies for apoptosis responsive genes, included in the revised version of the manuscript. N.L.A. also took part in critical reading and editing of the revised version of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement All proteomics data used from patient derived samples who underwent the immunotherapies were de-identified, and tissue biopsies were archived. This study was approved by the Institutional Review Board of the University of Arkansas for Medical Sciences under protocol number #204543 with a waiver for informed consent. Data Availability Statement The arrayed data have been provided as Supplementary Information. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A) Median mRNA expression (RNA-seq V2, RSEM, log2) of S100B in patients from 28 retrospective studies, available from the Broad GDAC Firehose database. S100B expression was measured in GBM (glioblastoma; n = 160), SKCM (skin cutaneous melanoma; n = 443), LGG (glioma; n = 514), PCPG (pheochromocytoma; n = 178), UVM (ocular melanoma; n = 80), PAAD (pancreatic cancer; n = 177), THYM (thymic epithelial tumor; n = 119), HNSC (head and neck cancer; n = 515), DLBC (mature B-cell neoplasms; n = 48), LUAD (non-small cell lung carcinoma; n = 994), CESC (cervical cancer; n = 294), TGCT (seminoma; n = 149), THCA (thyroid cancer; n = 498), STAD (esophagogastric cancer; n = 593), LAML (leukemia; n = 173), BRCA (breast cancer; n = 1082), MESO (pleural mesothelioma; n = 87), CHOL (cholangiocarcinoma; n = 36), BLCA (bladder cancer; n = 407), COADREAD (colorectal cancer; n = 592), PRAD (prostate cancer; n = 493), UCEC (endometrial cancer; n = 584), OV (ovarian epithelial tumor; n = 300), KIRC (renal clear cell carcinoma; n = 510), SARC (sarcoma; n = 253), LIHC (hepatobiliary cancer; n = 366), KICH (renal non-clear cell carcinoma; n = 348), ACC (adrenocortical carcinoma; n = 78). (B) S100B protein expression in a cohort of SKCM patients non-responsive (n = 12) to immune-checkpoint inhibitors (ICI; anti-PD-1 monotherapy, anti-CTLA-4 monotherapy, and anti-PD-1/anti-CTLA-4 combination therapy), compared to the responsive cohort (n = 10). (C) S100B expression in SKCM patient samples with gains in copy number, compared to those with heterozygous deletion of the gene (p < 0.01). (D) Correlation between linear capped copy number values and mRNA levels of S100B in SKCM samples. (E) A moderately negative correlation (R2 = 0.216, p < 0.01) was observed between DNA methylation (b-values) and mRNA expression of S100B. (F) DNase hypersensitive sites (DHSs; determined with DNase sequencing) and RNA-signal intensities (determined with RNA sequencing [RNA-seq]) in melanoma (SK-MEL-5) and in primary keratinocytes. (G) The amino acid sequence of human S100B and its murine ortholog S100b shows the degree of conservation between the species, with a single amino acid substituted (red arrowhead). (H) mRNA levels of S100b (relative to those of GAPDH) in murine B16-F1 (blue) and B16-F10 (gray) melanoma cells. * p < 0.05. Figure 2 (A) Murine single-guide RNAs (m-sgRNAs) were designed to bind proximal sites of three possible transcription start sites (TSSs) of S100b. (B) Prediction of transcription factor (TF) binding at the m-sgRNA-1 (+10 bp of the TSS94169), m-sgRNA-2 (+55 bp of the TSS94169), and m-sgRNA-3 (-33 bp of the TSS3252) target sites were mapped per Mouse Genome Informatics. (C) Schematics representing the fusion of dCas9 and KRAB proteins, S100b-specific m-sgRNAs, and plan for selecting transduced cells prior to downstream experiments. (D) Representative bright-field (dCas9-KRAB) and fluorescence (dCas9-KRAB+m-sgRNAs) micrographs (400 mM scale) of B16-F10 cells (above); fluorescence-assisted cell sorting (FACS) demonstrating enrichment (>95%) of co-transduced B16-F1 or B16-F10 cells. (E,F) Fold change in S100b expression (normalized to GADPH) in B16-F1 melanoma cell line (E) and B16-F10 melanoma cell line (F). Control (parental cell line, not transduced; black, treated with 0.1% dimethyl sulfoxide)); transduced with dCas9-KRAB only (light gray), with dCas9-KRAB+sgRNAEGFP (green), dCas9-KRAB+m-sgRNA-2 (red), with dCas9-KRAB+m-sgRNA-3 (dark blue), or with dCas9-KRAB+m-sgRNA-1 (light blue); * p < 0.05. (G) Western blot images for S100b expression in F1 and F10 cells, treated with the combination of dCas9-KRAB plus sgRNA-1, compared to cells treated with dCas9-KRAB alone and untreated cells. Figure 3 (A) Genomic coordinates of S100B and its neighboring genes PRMT2 and DIP2A. The mRNA-expression of both genes was monitored with qPCR, followed by the CRISPR-intervention with the combination of dCas9-KRAB and sgRNA, specific to S100b or EGFP. (B) Schematic representation of S100b interaction with wild type (WT)-p53 within the nucleus, potentially resulting in limited intracellular levels of p53 protein and inducing malignant cell proliferation in melanoma. (C,D) Western blot and associated densitometric plots demonstrating significant (* p < 0.05) increases in p53 and downstream p21 levels in B16-F1 and B16-F10 melanoma cell lines in response to co-transduction with dCas9-KRAB and m-sgRNA-1. Figure 4 (A) Viability of B16-F1 cells (control: parental cells with no transduction) in response to increasing concentrations of staurosporine, a potent inductor of apoptosis. Representative images (0.1 mM) demonstrating enhanced cell death (44.2%) in the dCas9-KRAB+m-sgRNA-1 suppressed cells compared to the non-transduced controls (31.2%). (B) We observed significant (* p < 0.05) increase in AIFM1 and PARP-1 mRNA expression in F1 cells, transduced in combination with DK and m-sgRNA-1, compared to the cells treated with treated with 0.1% dimethyl sulfoxide (DMSO), DK alone or in combination with EGFP-specific sgRNA. However, no significant (p > 0.05) change was observed in the mRNA level of CASP3 (Caspase-3) upon transduction with DK and different combinations of sgRNAs, compared to the parental line. (C) Changes in protein expression of apoptosis-responsive proteins, such that AIFM1 expression was increased, whereas we recognized cleaved forms of caspase-3 and poly-ADP ribose polymerase (PARP)-1 in the treated cells. (D) Schematic illustration of the potential apoptotic mechanism based on our findings that inhibition of S100b may increase the level of caspases or AIF1 to evoke apoptotic responses in cells. Figure 5 (A,B) Cell viability (%) was evaluated in B16-F1 and B16-F10 melanoma cell lines co-transduced with dCas9-KRAB and m-sgRNA-1, compared to control cells (no transduction), 24 h and 48 h after seeding the cells at a level of significance (* p < 0.05). (C,D) Viability of B16-F1 and B16-F10 melanoma cell lines in response to increasing concentrations of cisplatin or tunicamycin; control (parental cell line, transduced with dCas9+KRAB; F1: blue, F10: green); transduced with dCas9-KRAB plus sgRNA-1 (red). 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. Guy G.P. Jr. Thomas C.C. Thompson T. Watson M. Massetti G.M. Richardson L.C. 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PMC10000374 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050937 foods-12-00937 Article The Contribution of Scalded and Scalded-Fermented Rye Wholemeal Flour to Quality Parameters and Acrylamide Formation in Semi-Wheat-Rye Bread Klupsaite Dovile Methodology Investigation Data curation Writing - original draft Visualization 1 Starkute Vytaute Methodology Investigation Data curation Visualization 12 Zokaityte Egle Methodology Investigation Data curation Visualization 1 Cernauskas Darius Methodology Investigation 3 Mockus Ernestas Methodology Investigation 1 Kentra Evaldas Formal analysis 2 Sliazaite Rugile Formal analysis Investigation 2 Abramaviciute Gabriele Formal analysis Investigation 2 Sakaite Paulina Formal analysis Investigation 2 Komarova Vitalija Formal analysis Investigation 2 Tatarunaite Ieva Formal analysis Investigation 2 Radziune Sandra Formal analysis Investigation 2 Gliaubiciute Paulina Formal analysis Investigation 2 Zimkaite Monika Formal analysis Investigation 2 Kunce Julius Formal analysis Investigation 2 Avizienyte Sarune Formal analysis Investigation 2 Povilaityte Milena Formal analysis Investigation 2 Sokolova Kotryna Formal analysis Investigation 2 Rocha Joao Miguel Resources Writing - review & editing 45 Ozogul Fatih Writing - review & editing 67 Bartkiene Elena Conceptualization Resources Data curation Writing - original draft Writing - review & editing Supervision 12* Haros Claudia Monika Academic Editor 1 Institute of Animal Rearing Technologies, Faculty of Animal Sciences, Lithuanian University of Health Sciences, Tilzes Str. 18, LT-47181 Kaunas, Lithuania 2 Department of Food Safety and Quality, Veterinary Academy, Lithuanian University of Health Sciences, Tilzes Str. 18, LT-47181 Kaunas, Lithuania 3 Food Institute, Kaunas University of Technology, Radvilenu Road 19, LT-50254 Kaunas, Lithuania 4 Laboratory for Process Engineering, Environment, Biotechnology and Energy (LEPABE), Faculty of Engineering, University of Porto (FEUP), Rua Dr. Roberto Frias, 4200-465 Porto, Portugal 5 Associate Laboratory in Chemical Engineering (ALiCE), Faculty of Engineering, University of Porto (FEUP), Rua Dr. Roberto Frias, 4200-465 Porto, Portugal 6 Department of Seafood Processing Technology, Faculty of Fisheries, Cukurova University, Balcali, Adana 01330, Turkey 7 Biotechnology Research and Application Center, Cukurova University, Balcali, Adana 01330, Turkey * Correspondence: [email protected]; Tel.: +37-060135837 22 2 2023 3 2023 12 5 93719 12 2022 07 2 2023 15 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 this study was to evaluate the influence of scalded (Sc) and scalded-fermented (FSc) (with Lactiplantibacillus paracasei No. 244 strain) rye wholemeal flour on the quality parameters and acrylamide formation in semi-wheat-rye bread. To that purpose, 5, 10 and 15% of Sc and FSc were used for bread production. Results showed that scalding increased fructose, glucose and maltose content in rye wholemeal. Lower concentrations of free amino acids were found in Sc when compared with rye wholemeal, but fermentation of Sc increased the concentrations of some amino acids (on average by 1.51 times), including gamma aminobutyric acid (GABA, by 1.47 times). Addition of Sc and FSc had a significant influence (p <= 0.05) on bread shape coefficient, mass loss after baking and most bread colour coordinates. Most of the breads with Sc or FSc showed lower hardness after 72 h of storage compared with the control (i.e., without Sc or FSc). FSc improved bread colour and flavour, as well as overall acceptability. Breads with 5 and 10% of Sc had a similar level of acrylamide to the control, while its level in breads with FSc was higher (on average, 236.3 mg/kg). Finally, different types and amounts of scald had varying effects on the quality of the semi-wheat-rye bread. FSc delayed staling and improved sensory properties and acceptability, as well as the GABA level of wheat-rye bread, while the same level of acrylamide as was seen in control bread could be reached when using between 5 and 10% of scalded rye wholemeal flour. bread scalding fermentation acrylamide lactic acid bacteria This research received no external funding. pmc1. Introduction Wheat bread is the most popular bread in many countries and accepted as a very convenient form of high energy food with good digestibility . However, semi-wheat-rye bread takes a higher position in the East European market; it is also considered to be better balanced, because of the presence of various cereal varieties with differing compositions . In the production of semi-wheat-rye bread, wheat flour has a very important technological function because of its gluten network, which gives elasticity to the wheat-rye dough . This characteristic leads to better gas retention and improves the gas extension in the dough, leading to a higher porosity and specific volume of the bread . Owing to consumer interest in healthy nutrition and taking into consideration that bread is a very popular product consumed on a daily basis, bakeries are always eager to produce healthier products . One of the steps to improve bread properties is to eliminate added sugar (saccharose) from the main bread formula . However, the sensory properties of bread are very important characteristics of bread choice, and most consumers prefer a sweeter tasting product . The influence of saccharose consumption on public health continues to be a controversial topic but it is known that the consumption of added sugar is associated with the risk of developing a range of chronic diseases . To avoid numerous health problems associated with added sugar consumption, the World Health Organization (WHO) published guidelines in 2015 that recommended reducing the intake of "free sugars" to <10% of calories per day . The use of scalded flour (Sc) can be an attractive technology to increase the sweet taste of bread without addition of saccharose, and it has indeed been reported that scalded flour has a positive influence on glycaemic index . This technology is very common in Eastern Europe because it can ensure the good characteristics and sweeter taste of cereal products without any additional sugar. In addition, scalded flour is a good substrate for the growth of lactic acid bacteria (LAB), which are usually used in bread production as a microbial starter culture for sourdough fermentation. These suitable characteristics for LAB growth and multiplication are associated with the resulting hydrolysis of the flour starch and production of fermentable sugars (usually monosaccharides) that are easily available for LAB consumption and their metabolic conversion of monosaccharides to organic acids and other important metabolites. Additionally, fermentation of scalded flour leads to the desirable sweet-sour taste of bread, which is generally preferred by consumers. Furthermore, the combination of these two steps--i.e., scalding and fermentation--can lead to the extension of bread shelf-life as well as acrylamide reduction, owing to the degradation and metabolism of acrylamide precursors in baking dough. The European Food Safety Authority (EFSA) scientific opinion on acrylamide in foods concluded that dietary exposure to acrylamide potentially increases the risk of developing cancer for consumers in all age groups; thus, the food industry should reduce acrylamide concentration in foods . Acrylamide is formed in food products during their thermal treatment at temperatures > 120 degC, especially during the Maillard reaction. Formation of acrylamide in bread depends on many factors, including temperature, processing, type of flour(s), recipe, etc. . One of the possibilities for reducing acrylamide formation in bread is the use of sourdough technology because of the rapid pH drop and degradation of the main precursors of acrylamide in dough that can be achieved using selected LAB strains. However, studies on the influence of scalded flour fermented with Lactiplantibacillus paracasei on acrylamide formation in bread are limited. Moreover, it should be pointed out that the scalding technology increases acrylamide precursor (monosaccharides) formation in dough. For this reason, not only should consumer preference for a sweet-tasting product be considered, but also the safety parameters, i.e., acrylamide formation in bread prepared with scalded flour. Our previous studies focused on acrylamide concentration reduction in cereal products (mostly in bread and biscuits) using selected LAB strains and their combinations, showed very promising results, albeit by selecting the most appropriate LAB strain for each product technology . These previous findings were explained by the different composition of the fermentable substrate, which led to different metabolic activities of the employed LAB, as well as differing efficiencies in the reduction of the acrylamide precursors in dough and, subsequently, acrylamide concentration in the end product. Despite significant progress being made in this field since our research was published, in general, studies about the influence of scalded flour and scalded flour fermented with Lactiplantibacillus paracasei (FSc) on acrylamide formation in semi-wheat-rye bread are still scarce. The aim of this study was to evaluate the influence of scalded and scalded-fermented (with Lactiplantibacillus paracasei No. 244 strain) rye wholemeal flour on the quality parameters and acrylamide formation in semi-wheat-rye bread. For this purpose, different quantities of scalded (Sc) and scalded-fermented (FSc) rye wholemeal flour were tested for semi-wheat rye bread (W-R) preparation (5, 10 and 15%). In addition, Sc and FSc parameters (pH, total titratable acidity (TTA), colour characteristics, hardness, sugars (fructose, glucose, sucrose and maltose) concentration and amino acid profile), as well as W-R quality and safety characteristics (specific volume, shape coefficient, mass loss after baking, crust and crumb colour coordinates, sensory characteristics, overall acceptability, and acrylamide concentration) were analysed. 2. Materials and Methods 2.1. Materials Used for Bread Preparation Wheat flour (type 550D, gluten 26%, carbohydrate content 68%, fibre content 3.9%, protein content 11.9%, fat content 1.7% and ash 0.55-0.62%) and rye wholemeal flour (fat content 1.1%, carbohydrate content 62.2%, fibre content 16% and protein content 8.5%) obtained from 'Malsena plius' Ltd. mill (Panevezys, Lithuania) were used for the W-R preparation. The W-R samples were prepared without and with addition of Sc and FSc (5, 10 and 15%). Lactiplantibacillus paracasei No. 244 strain showing versatile carbohydrate metabolism and tolerance to acidic conditions was used for FSc preparation. Strain No. 244 was stored at -80 degC in a Microbank system (PRO-LAB DIAGNOSTICS) and propagated in a DeMan, Rogosa and Sharpe (MRS) broth (CM 0359; Oxoid Ltd., Hampshire, UK) at 30 degC for 48 h. This LAB strain was previously newly isolated and identified from a spontaneous rye sourdough, which is traditionally used in rye bread production . The characteristics of the Lp. paracasei No. 244 strain are given in Table 1. 2.2. Scald Preparation and Fermentation The Sc was prepared by using 1000 g of rye wholemeal flour mixed with 1000 mL of hot water (95 degC). The scalding process was carried out at 30 degC for 2 h. For Sc fermentation Lp. paracasei No. 244 strain was used. The Lp. paracasei No. 244 cell suspension (5 mL), containing about 8.9 log10 CFU/mL, was added into the Sc (cooled to 30 degC), followed by fermentation for 24 h at 30 degC. Prepared Sc and FSc samples were applied for W-R preparation by using 5, 10 and 15% (% of the total flour content). 2.3. Breadmaking The W-R formula consisted of 0.5 kg wheat flour, 0.5 kg rye flour, 1.5% salt, 3% instant yeast and 1000 mL water (control bread). Control W-R samples were prepared without the addition of Sc or FSc. The tested W-R groups were prepared by addition of 5, 10 and 15% Sc or FSc to the main recipe. In total, seven groups of baking dough and respective W-R samples were prepared and tested. The dough was mixed for 3 min at a low speed, then for 7 min at a high-speed regime in a dough mixer (KitchenAid Artisan, OH, USA). Then, the dough was left at 22 +- 2 degC for 15 min relaxation. Subsequently, the dough was shaped into 425 g loaves, formed and proved at 30 +- 2 degC and 80% relative humidity for 60 min. The bread was baked in a deck oven (EKA, Borgoricco, PD, Italy) at 220 degC for 25 min. The schematic representation of the experimental design is shown in Figure 1. 2.4. Evaluation of Non-Treated, Scalded (Sc) and Scalded-Fermented (FSc) Rye Wholemeal Flour Parameters The Sc and FSc samples (after 0 (FSc-0h) and 24 (FSc-24h) h of fermentation) were analysed to evaluate their pH, TTA, colour characteristics, hardness, sugar (fructose, glucose, sucrose and maltose) concentration and amino acid profile. The pH values of Sc and FSc were measured and recorded with a pH electrode (PP-15; Sartorius, Gottingen, Germany). For pH analysis, the electrode was immersed directly into the Sc or FSc sample. The TTA was determined for a 10 g sample of Sc or FSc homogenized with 90 mL of distilled water and expressed as mL of 0.1 mol/L NaOH required to achieve a pH of 8.2. Colour parameters were evaluated using a CIE L*a*b* system (CromaMeter CR-400, Konica Minolta, Japan) . The hardness of Sc and FSc samples was measured as the energy required for sample deformation (CT3 Texture Analyzer, Brookfield, Middleboro, USA), viz.: 50 g of a Sc or FSc sample was placed in a Petri dish and compressed to 10% of its original height at a crosshead speed of 0.5 mm/s; the resulting peak energy of compression was reported as Sc or FSc sample hardness. To determine the sugar concentration, 1-2 g of sample was diluted in 60 mL of distilled/de-ionized water, heated to 60 degC in a water bath for 15 min, clarified with 2.5 mL Carrez I (85 mM K4[Fe(CN)6] x 3H2O) and 2.5 mL Carrez II (250 mM ZnSO4 x 7H2O) solutions, and made up to 100 mL with distilled/de-ionized water. After 15 min, the samples were filtered through a filter paper and a 0.22 mm nylon syringe filter before further analysis. A 2 mg/mL standard solution of a sugar mixture was prepared by dissolving 0.2 g of each of fructose, glucose, sucrose and maltose (Sigma-Aldrich, Hamburg, Germany) in 100 mL of distilled/de-ionized water. Chromatographic conditions were as follows: the eluent was a mixture of 75 parts by volume of acetonitrile and 25 parts by volume of water, the flow-rate was 1.2 mL/min, 20 mL was injected. A YMC-Pack Polyamine II 250 x 4.6 mm, 5 mm (YMC Co., Ltd., Tokyo, Japan) column was used. The column temperature was set at 28 degC. The detection was performed using an Evaporative Light Scattering Detector (ELSD) LTII (Shimadzu Corp., Kyoto, Japan). For free amino acids and gamma aminobutyric acid (GABA) analysis, the homogenized sample (~100 mg) was weighed into a 1.5 mL tube and analytes were extracted with 1 mL of aqueous 0.1 M HCl solution by shaking for 1 h. The resultant mixture was centrifuged at 12,000 rpm for 5 min. For derivatization, 50 mL of the resultant supernatant was mixed with 100 mL of 100 mg/L diaminoheptane (as an internal standard) and diluted to 500 mL with 0.1 M HCl solution. The resultant mixture was alkalized by addition of 40 mL of 2 M NaOH and 70 mL of the saturated NaHCO3 solution. Derivatization was performed by adding 1 mL of 10 mg/mL dansyl chloride solution in acetonitrile and incubating the resulting mixture at 60 degC for 30 min. The reaction mixture was quenched using 50 mL of 25% ammonia solution and filtered through a 0.22 mm membrane filter into the auto-sampler vial. The concentration of analytes was determined using a Varian ProStar HPLC system (two ProStar 210 pumps and a ProStar 410 autosampler; Varian Corp., Palo Alto, CA, USA) and a Thermo Scientific LCQ Fleet Ion trap mass detector (Thermo Fisher Scientific, San Jose, CA USA). For analyte detection, the mass spectrometer was operated in positive-ionization single-ion monitoring mode for specific ions corresponding to derivatized analytes. The analyte concentration was determined from a calibration curve, which was obtained by derivatizing the analytes at different concentrations. For the separation of derivatives, a Discovery(r) HS C18 column (150 x 4.6 mm, 5 mm; SupelcoTM Analytical, Bellefonte, PA, USA) was used. Mobile phase A was 0.1% formic acid in 5% aqueous acetonitrile, and phase B was 0.1% in acetonitrile (% in volume). A flow-rate of 0.3 mL/min was used for the analysis. The injection volume was 10 mL. The analytical gradient was as follows: 0 to 10 min (linear gradient) 15 to 60% B, 10 to 40 min (linear gradient) 60 to 95% B, 40 to 48 min 95 B, followed by re-equilibration of the column for 10 min with 15% B (increased to 0.6 mL/min flowrate). The limit of quantification (according to the lowest concentration used for calibration) was 0.02 mmol/g. 2.5. Evaluation of Bread Quality After 12 h of cooling at 22 +- 2 degC, W-R samples were subjected to analysis of specific volume, crumb porosity, shape coefficient, mass loss after baking, crust and crumb colour coordinates, sensory characteristics, overall acceptability and acrylamide concentration. Bread volume was established by the AACC method , and the specific volume was calculated as the ratio of volume to weight. The bread shape coefficient was calculated as the ratio of bread slice width to height (in mm). Mass loss after baking was calculated as a percentage by measuring loaf dough mass before baking and after baking. Crust and crumb colour parameters were evaluated using a CIE L*a*b* system (CromaMeter CR-400, Konica Minolta, Tokyo, Japan) . Bread crumb hardness was determined as the energy required for sample deformation (CT3 Texture Analyzer, Brookfield, Middleboro, USA): bread slices of 2 cm thickness were compressed to 10% of their original height at a crosshead speed of 0.5 mm/s; the resulting peak energy of compression was reported as crumb hardness. Three replicates from three different sets of baking were analysed and averaged. Sensory characteristics and overall acceptability of breads was carried out by 10 trained judges according to the ISO method using a 140 mm hedonic line scale ranging from 140 (like extremely) to 0 (dislike extremely). 2.6. Determination of Acrylamide in Bread The acrylamide concentration was determined according to the method of Zhang et al. with modification. The bread samples were homogenized in a blender (Ika A10, Staufen, Germany). Two grams of sample were weighed in a 50 mL centrifuge tube and diluted with 20 mL of distilled/de-ionized water. The sampling tube was briefly vortexed (ZX3 Advanced VELP, Usmate (MB), Italy) to mix the contents for 10 min. The sample tube was centrifuged at 4000 rpm for 10 min with a centrifuge (Hermle Z 306, HERMLE Labortechnik GmbH, Wehingen Germany). Next, 10 mL samples of the clarified aqueous layer solution were transferred to 15 mL centrifuge tubes and clarified with 100 mL of Carrez I (85 mM K4[Fe(CN)6] x 3H2O) and 100 mL of Carrez II (250 mM ZnSO4 x 7H2O) solutions. The sample tubes were then centrifuged at 4000 rpm for 10 min. For the preparation of acrylamide standard solution (30.4 mg/L), 15.2 mg of acrylamide analytical standard (99.8% purity) was weighed and dissolved in a 1000 mL volumetric flask and diluted with de-ionized water. The obtained solution was diluted by pouring 2 mL of the obtained acrylamide solution into a 1000 mL measuring flask and diluted with de-ionized water. Three millilitres of the sample supernatant (or standard solution) was derivatized in a glass sample tube by adding 1.5 g of potassium bromide (KBr), 1 mL of potassium bromate solution (0.1 M, KBrO3) and 0.3 mL of sulphuric acid solution (50%, H2SO4). The mixture was mixed in a shaker and kept for 2 h in a refrigerator (~4 degC). The derivative was neutralized by adding 250 mL of sodium thiosulphate solution (1 M, Na2S2O3 x 5H2O) until the orange colour disappeared. About 1.5 g of sodium chloride (NaCl) was added to the derivatization mixture and the mixture was extracted with ethyl acetate (CH3COOC2H5) (2 x 5 mL). The collected ethyl acetate was concentrated with a concentration system (Christ CT 02-50, Frankfurt, Germany) at a temperature of 40 degC and under reduced pressure. The solvent was evaporated and dissolved in 0.5 mL of ethyl acetate (for the standard, in a volume of 3 mL). Next, 100 mg of anhydrous sodium sulphate (Na2SO4) and 20 mL of triethylamine ((C2H5)3N) (20 mL of triethylamine in 0.5 mL of a concentrated derivatization solution) were added to the solution in a 15 mL centrifuge tube, mixed and centrifuged for 10 min (4000 rpm). The supernatant was analysed with a gas chromatograph-electron capture detector (GC-ECD). A gas chromatograph (Shimadzu GC-17A, Tokyo, Japan) was equipped with an electron capture detector (ECD), an integrator to measure peak areas, and a thermostated column. The capillary column was a Rxi-5Sil MS (Restek, Germany): length 30 m; inner diameter 0.25 mm; stationary phase film thickness 0.25 mm. Working conditions were: injection volume 1 mL; column temperature gradient 70 degC (hold 1 min), 3 degC/min to 140 (hold 0.5 min), and 15 degC/min to 280 (hold 4 min). The mobile phase was nitrogen at 18.0 cm/sec flow rate, with a split of 3.0. The injector temperature was 250 degC, the detector temperature was 260 degC and the detector current was 2 nA. 2.7. Statistical Analysis The results were expressed as mean values (for baking dough and bread samples n = 3, and for bread sensory characteristics and overall acceptability n = 10 trained panellists) +- standard error (SE). In order to evaluate the effects of different quantities of scalded non-fermented and fermented rye wholemeal flour on semi-wheat-rye bread quality parameters, data were analysed using a one-way ANOVA and Tukey-HSD as post-hoc tests (statistical program R 3.2.1). Additionally, Pearson correlations were calculated between various parameters, as well as between the dough and scald characteristics with acrylamide content. The results were recognized as statistically significant at p <= 0.05. 3. Results and Discussion 3.1. Parameters of Scalded (Sc) and Scalded-Fermented (FSc) Rye Wholemeal Flour Acidity characteristics (pH and TTA), colour coordinates and hardness of Sc and FSc (after 0 and 24 h of fermentation) are shown in Table 2. When comparing the acidity parameters (pH and TTA) of the samples, the addition of pure LAB strains decreased pH and increased the TTA by 4.34 and 18.3%, respectively. After 24 h of fermentation, the pH of the samples was reduced to 4.57 and the TTA was increased to 2.53 degN. However, significant correlation between the pH and TTA of the samples was not found. The decrease in pH and increase in TTA in FSc samples are mainly related to organic acid production by lactic acid bacteria and their ability to acidify the fermentable substrates . Regarding the colour coordinates of the samples, significantly higher values of redness (a*) (by 13.8%), and similar values of lightness (L*) and yellowness (b*) in FSc samples after 24 h of fermentation were found, when compared with Sc samples. Fermentation with LAB may induce the release of such pigments as anthocyanins and phenolic compounds, which are present in the pericarp, testa and aleurone layer of the rye grains . This could cause the observed increased values of the a* coordinate in scalded-fermented rye flour. The hardness of FSc samples was around 3.5 times lower in comparison with non-fermented-scalded rye flour. This may be explained by the proteolytic activity of the LAB strain and the acidity-elicited activation of proteolytic enzymes in flour . The activity of the proteolytic enzymes induces the weakening of the gluten network structure and decreases the hardness of the fermented product . The sugar content is depicted in Table 3. Fructose and glucose were absent in non-scalded rye wholemeal flour. However, the scalding process led to fructose and glucose formation (in the Sc sample, the fructose and glucose content was, on average, 0.880 and 1.25 g/100 g, respectively). Moreover, the scalding process increased maltose concentration by 6.14 times, in comparison with non-scalded flour. In both the Sc and FSc samples, sucrose was not detected; in addition, fermentation of the scalded flour significantly increased the glucose concentration by 13.2% in comparison with Sc. Fructose and maltose content in Sc and FSc remained similar, on average, 0.850 and 6.61 g/100, respectively. Due to the gelatinization of starch during scald production, amylases in flour tend to convert starch into maltodextrins and further into maltose and glucose . This explains the results observed in our study, which are similar with those reported by Li et al. . Despite the utilization of monosaccharides by LAB, most LAB strains, including Lp. paracasei, possess amylolytic activity and this could also cause the increase in disaccharides in fermented scald . The content of free amino acids and GABA is given in Table 4. Concerning the free amino acid concentration, in the Sc and FSc samples the concentration was lower in most cases, in comparison with non-treated rye wholemeal flour: asparagine, on average, by 2.34 times; serine, on average, by 2.17 times; aspartic acid, on average, by 4.46 times; and proline, on average, by 2.31 times. In comparison, when considering arginine, glutamic acid, threonine, glycine and alanine concentrations, the highest content of these amino acids was found in non-treated flour in all cases. Moreover, when comparing Sc and FSc, the latter showed the higher content of these amino acids (on average, by 1.26, 1.14, 1.78, 1.66 and 1.71 times, respectively). An exception was observed with proline, the content of which in both the Sc and FSc samples was similar (on average, 0.968 mmol/g). The lower free amino acid content in Sc samples could be related to the protein denaturation or dilution effect . Conversely, the higher content of some free amino acids in FSc may have occurred due to proteolytic activity in the LAB strain . It has been reported that the content of such amino acids as tryptophan, glutamic acid, isoleucine, leucine and asparagine increased after fermentation of rye dough . Vis-a-vis the gamma aminobutyric acid concentration in non-treated and scalded flour, significant differences were not observed, and GABA concentration was, on average, 0.469 mmol/g. However, in FSc samples GABA concentration was found to be 1.47 times higher, in comparison with non-treated flour and Sc samples. GABA possesses anticarcinogenic, antihypertensive, antidepressant and antidiabetic properties. It is a metabolic product of plants and microorganisms such as LAB; therefore, fermented foods are a potential source of this amino acid . It has been reported that this health-promoting compound is found in rye malt sourdough after fermentation with Limosilactobacillus reuteri LTH5448 and LTH5795; wheat sourdough fermented with Levilactobacillus brevis CECT 8183; legume flour sourdough started with Lev. brevis AM7 and Lactiplantibacillus plantarum C48; and wheat, barley, chickpea, lentil and quinoa flour sourdoughs fermented with strains of Lp. plantarum, Furfurilactobacillus rossiae and Fructilactobacillus sanfranciscens ; however, no data on GABA concentration in Sc and FSc were found in the literature. The results obtained in our study show that the scalding process had no significant impact on the GABA content of rye flour, but fermentation of Sc with Lactiplantibacillus paracasei No. 244 strain increased GABA content by, on average, 1.47 times. 3.2. Bread Quality The bread specific volume, porosity, shape coefficient, mass loss after baking, colour characteristics of the bread crust and crumb, as well as bread crumb images are given in Table 5. Observing the results of the specific volume of bread samples, no significant differences were detected and, on average, bread specific volume was 1.98 cm3/g. In comparison, for bread shape coefficient, samples prepared with 15% of Sc and FSc showed a lower shape coefficient in comparison with other bread groups (on average, 30.2% lower). The scald quantity used for bread preparation, and the scald fermentation and quantity interaction, were significant (p = 0.019 and p <= 0.0001, respectively) with respect to the bread shape coefficient (Table 6). A moderate positive correlation between the bread specific volume and shape coefficient was established (r = 0.439, p = 0.47). Significant differences between the control breads and breads prepared with 5% of Sc and with 15% of FSc mass loss after baking were not found. However, other bread sample groups showed 33.6% higher mass loss after baking. The interaction between analysed factors (scald fermentation and quantity interaction) was significant for bread mass loss after baking (p = 0.025) (Table 6). As previously verified, the high temperature used during scalding affects starch gelatinization and protein denaturation, which results in greater flour viscosity and dough elasticity, and bread specific volume . The increased specific volume of bread or millet cake made with heated flours has been reported . However, gluten proteins may become denaturized as a result of scalding, and an excessively high amount of rye scald in the bread formula can diminish bread volume . Thus, it was reported that scalded wholemeal could improve bread volume, but the addition of 10% of scalded flour in wheat bread resulted in a slightly lower bread volume . Moreover, it was found that rye scald significantly affected the crumb cell diameter and area, as more cells per slice area could be obtained . A lower pH in fermented rye scald may cause peptization and swelling of the proteins in the flour, increasing the consistency and subsequently the dough's ability to retain carbon dioxide . It has also been claimed that as the acidity rises, all of the moisture in the dough is bound by the undegraded starch, which may have an impact on mass loss after baking . When comparing the colour characteristics of the bread crust, it was found that the addition of 10 and 15% of Sc, as well as 5, 10 and 15% of FSc, reduces bread crust lightness (L*), on average, by 18.2%. Analysed factors (scald fermentation and quantity) interaction were significant for bread crust L* (p = 0.0037) (Table 6). The lowest crust redness (a*) was obtained in breads prepared with 15% of Sc (in comparison with control breads and the group of breads prepared with FSc, on average, it was lower by 25.0%). Both analysed factors were significant on bread crust a* coordinates (scald fermentation p = 0.022 and scald quantity p = 0.048). Addition of Sc and FSc (except 5% of scalded flour) reduced bread crust yellowness (b*), in comparison with control samples, on average, by 14.0%. Scald quantity was a significant factor for bread crumb L* (p = 0.016) and the highest L* was recorded in samples prepared with 5 and 10% of Sc and with 10% of FSc (their L* coordinates were, on average, 57.2 NBS). The lowest crumb a* was found in the group of samples prepared with 15% of Sc (4.15 NBS). All the analysed factors and their interactions were significant for bread crumb a* (Table 6). The highest crumb b* was attained in the control group samples (19.9 NBS) and, by increasing the Sc the quantity in the main bread formula, crumb b* coordinates decreased (in samples prepared with 5% of Sc, on average, by 8.5%; in samples prepared with 10% of Sc, on average, by 19.1%; in samples prepared with 15% of Sc, on average, by 31.2%). Also, bread samples prepared with FSc showed lower b* coordinates in comparison with the control samples group (samples prepared with 5 and 15% of FSc, on average, lower by 24.1%; samples prepared with 10% of FSc, on average, lower by 20.6%). Scald quantity and scald fermentation x scald quantity interaction was significant for bread crumb b* coordinates (Table 6). It has been reported that wheat bread with the addition of dietary fibre usually has a darker colour of crust and crumb . The colour coordinates of the bread crust made with scalded rye in our study were similar with those obtained by Esteller et al. . The higher percentage of seed coat and reducing sugars in rye wholemeal scald, as well as increased levels of some free amino acids in fermented scald, may contribute to the greater browning of baked bread . This explains the lower values for the lightness of bread with Sc and FSc . Bread texture hardness after 24, 48 and 72 h of storage are shown in Figure 2. When comparing bread hardness after 24 h of storage, control bread hardness was the lowest (0.1 mJ). The hardness of bread prepared with Sc (5, 10 and 15%), as well as 15% of FSc was the highest, on average, at 0.3 mJ, and the hardness of bread prepared with 5 and 10% of FSc was, on average, 0.2 mJ. After 48 h of storage, different trends were established. Bread samples prepared with 5% of FSc showed lower hardness, in comparison with the control samples. After 72 h of storage, most of the bread groups prepared with Sc or FSc showed lower hardness in comparison with control breads (except for the bread group prepared with 15% of scalded flour). Rye flour contains arabinoxylans, whose extractability and swelling properties increase under acidic conditions . These compounds are essential in the water binding process and the formation of a viscous dough. Due to the effect of arabinoxylans and the decreased activity of amylase, rye bread made with sourdough hardens more slowly when compared with wheat bread . Moreover, the prolonged shelf-life of bread prepared with sourdough may be related to the higher content of exopolysaccharides synthesized by LAB . These effects may explain the reduced hardness of breads with Sc or FSc after 72 h of storage. 3.3. Sensory Properties and Overall Acceptability of Bread Samples Bread sensory properties are shown in Figure 3a,b--colour, taste, flavour and odour sensory characteristics; Figure 3c,d--texture sensory characteristics; and Figure 3e--overall acceptability. Comparing the colour sensory characteristics of bread, the bread sample groups prepared with FSc showed, on average, a 39.7% higher colour acceptability, in comparison with control samples and samples prepared with Sc. In addition, samples prepared with FSc showed a higher odour intensity (on average, 30.6% higher) in comparison with control samples and samples prepared with Sc. Addition of Sc to the main bread formula increased the bread odour intensity of the samples; in comparison with the Sc and FSc groups, on average a two times higher bread odour intensity was obtained in bread groups prepared with FSc. Bread sample groups prepared with FSc showed, on average, 0.6 times higher additive odour, in comparison with control samples and samples prepared with Sc. By increasing the percentage of Sc in the main bread formula, the flavour intensity of the samples was reduced; however, opposite tendencies were observed in bread prepared with FSc. The same tendencies were found in the bread flavour. The highest intensity of additive flavour was attained in bread group samples prepared with 10 and 15% of FSc (on average, 58.7). The acidity of all the tested bread groups was not sensorily felt, and the highest bitterness was exhibited in samples prepared with 15% of FSc. Analysis of between-subject effects showed that scald fermentation was a significant factor on all the analysed colour, taste, flavour and odour sensory characteristics (p <= 0.0001) (Table 7). However, scald quantity was a significant factor only for bread odour intensity and additive odour (p = 0.0003 and p <= 0.0001, respectively). Interaction of both analysed factors was significant for most of the analysed colour, taste, flavour and odour sensory characteristics (Table 7). Regarding bread texture sensory characteristics , the most acceptable porosity was evaluated in the control samples and breads prepared with 5% of FSc. All the bread groups prepared with FSc showed, on average, 2.1 times higher brittleness, in comparison with control samples and breads prepared with Sc. Significant differences in the springiness and the texture moisture between the bread groups were not found. Nevertheless, the hardest samples were obtained in the bread groups prepared with 15% Sc. Analysed factors and their interaction were significant on most of the analysed bread texture sensory characteristics except in scald fermentation. However, the interaction of factors was not significant for bread porosity, and scald quantity was not significant for bread springiness. When comparing bread overall acceptability, significantly higher overall acceptability was exhibited in bread groups prepared with FSc, in comparison with control group breads and breads prepared with Sc . Furthermore, scald fermentation and interaction of scald quantity and fermentation were significant for bread overall acceptability (Table 7). Bread flavour is highly affected by the lactic and acetic acids, free amino acids, exopolysaccharides and volatile compounds (alcohols, aldehydes, ethers, etc.) formed during sourdough fermentation . Different sourdoughs have shown to improve the sensory qualities of wheat breads . Moreover, heat treatment of flour causes variations in flavour and browning during baking. Gao et al. (2018) observed higher sensory scores of rye-wheat breads made with heat-treated rye flour . Djukic et al. (2013) reported that with the addition of rye scald to bread dough, the sensory qualities of the rye/wheat bread were enhanced . Higher scores of bitterness for breads with Sc and FSc could be explained by the presence of wholemeal flour, which contains bitter taste-eliciting bran . 3.4. Acrylamide Concentration in Bread Acrylamide concentrations (mg/kg) in the bread samples are given in Figure 4. The lowest concentration of acrylamide was found in the group of control samples and breads prepared with 5 and 10% of Sc (on average, 149.0 mg/kg). Acrylamide content in samples prepared with FSc was, on average, 236.3 mg/kg. However, samples prepared with 15% of Sc had, on average, a 61.9% higher acrylamide concentration compared with control samples and samples prepared with 5 and 10% of Sc, and, on average, a 39.6% higher acrylamide concentration compared with the groups of samples prepared with FSc. Moderate negative correlations between acrylamide concentration in bread and bread shape coefficient, bread crumb L* and b* colour coordinates were obtained (r = -0.528, p = 0.014; r = -0.680, p <= 0.001; r = -0.443, p = 0.044, respectively). Scald quantity and scald fermentation and quantity interaction were significant for acrylamide concentration in bread samples (Table 8). The potentially carcinogenic acrylamide is produced during the Maillard reaction and its main precursors are reducing sugars such as glucose and fructose, and the amino acid asparagine, which is a limiting precursor . In addition to its high nutritional value, rye flour also contains a higher content of asparagine than wheat . It has been reported that greater acrylamide formation in rye bread can also occur due to the high content of dietary fibre and ash in flour . However, fermentation with LAB can lead to a reduction in acrylamide content in bread because the LAB use free asparagine in their metabolism . Przygodzka et al. (2015) reported a weak effect of wheat flour extraction rates and their chemical components on acrylamide formation in breads baked at 240 degC, while this effect was not found in rye flour . It was also claimed that the level of acrylamide was lower when bread was baked at a lower temperature with a longer baking time. In our study, the content of asparagine and fructose were similar in Sc and FSc; only glucose content was higher in FSc compared with Sc, and that probably led to the higher content of acrylamide in breads with FSc. This could also suggest that the starter culture did not successfully lower the free asparaginase content. 4. Conclusions The addition of various cereal varieties to wheat bread could lead to healthier, but still tasty, products. The preparation of scalded rye flour is very common technology for rye bread production in Eastern Europe. It is valuable owing to its ability to increase the sweet taste of bread without addition of saccharose--a positive influence on the glycaemic index--while fermentation of scalded flour leads to a desirable sweet-sour bread taste and the extension of bread shelf-life. As studies about the rye scald fermentation with certain LAB and further uses for semi-wheat-rye bread production are still scarce, our study provides beneficial information in this field. We used the newly isolated Lactiplantibacillus paracasei No. 244 strain--which possesses versatile carbohydrate metabolism, tolerance to acidic conditions, and antimicrobial properties--for the rye scald fermentation. The outcome of this study showed that scalding caused higher levels of reducing sugars in rye wholemeal. Fermentation decreased the pH and hardness but increased the TTA and redness (a*) value of scald. In most cases, amino acid concentrations in Sc and FSc were lower than in rye wholemeal flour. However, fermentation of Sc increased the levels of certain amino acids, as well as GABA. Scald type (unfermented and fermented) and quantity (5, 10 and 15%) affected the quality of semi-wheat-rye bread in certain parameters. Colour coordinates, shape coefficient and mass loss after baking of semi-wheat-rye breads were significantly influenced by the quantity and type of scald. Reduced hardness of breads with Sc (except with 15% of Sc) or FSc was observed after 72 h of storage, compared with control samples. Scald fermentation was a significant factor on such sensory characteristics as colour, taste, flavour and odour of bread. Addition of FSc significantly improved overall acceptability of the tested bread. Compared with control bread, addition of 5 and 10% of scald to the bread formula did not enhance the formation of acrylamide in wheat-rye bread. In summary, scald fermented with Lp. paracasei No. 244 enriches bread with GABA and improves bread sensory acceptability as well as staling. Acknowledgments The authors gratefully acknowledge COST Action 18101 SOURDOMICS--Sourdough biotechnology network towards novel, healthier and sustainable food and bioprocesses accessed on 29 November 2022), and is supported by COST (European Cooperation in Science and Technology) accessed on 29 November 2022). COST is a funding agency for research and innovation networks. Regarding the author J.M.R., he is financially supported by LA/P/0045/2020 (ALiCE) and UIDB/00511/2020-UIDP/00511/2020 (LEPABE) funded by national funds through FCT/MCTES (PIDDAC). Author Contributions Conceptualization, E.B.; methodology, D.K., E.M., V.S., D.C. and E.Z.; formal analysis, E.K., R.S., G.A., P.S., V.K., I.T., S.R., P.G., M.Z., J.K., S.A., M.P. and K.S.; investigation, D.K., E.M., V.S., E.Z., D.C., R.S., G.A., P.S., V.K., I.T., S.R., P.G., M.Z., J.K., S.A., M.P. and K.S.; resources, E.B. and J.M.R.; data curation, E.B., V.S., E.Z. and D.K.; writing--original draft preparation, E.B. and D.K.; writing--review and editing, J.M.R., F.O. and E.B.; visualization, D.K., V.S. and E.Z.; supervision, E.B. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data are available from the corresponding author, upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic representation of the experimental design. Figure 2 Bread texture hardness (mJ) after 24, 48 and 72 h of storage. Control--bread prepared without scald or fermented scald; Sc--scalded rye flour; FSc--scalded-fermented rye flour; 5%, 10% and 15%--bread prepared with 5%, 10% and 15%, respectively, scalded (Sc) or scalded-fermented (FSc) rye wholemeal flour. Figure 3 Bread sensory properties ((a,c)--colour, taste, flavour and odour sensory characteristics; (b,d)--texture sensory characteristics; and (e)--overall acceptability; control--bread prepared without scald or fermented scald; Sc--scalded rye flour; FSc--scalded fermented rye flour; 5%, 10%, 15%--bread prepared with 5%, 10%, 15%, respectively, scalded or scalded-fermented rye wholemeal flour. Data expressed as mean values (n = 10) +- standard error (SE). a-e Mean values within columns with different letters are statistically significantly different (p <= 0.05)). Figure 4 Acrylamide concentration (mg/kg) in bread samples (a-c Mean values within columns with different letters are statistically significantly different (p <= 0.05)). foods-12-00937-t001_Table 1 Table 1 Characteristics of the Lactiplantibacillus paracasei No. 244 strain. 100 bp DNA-Ladder Extended Lactiplantibacillus paracasei No. 244 Gas Production, Tolerance to Temperature (10, 30, 37 and 45 degC), Low pH Conditions (pH 2.5 for 2 h) and Carbohydrate Metabolism of the Lactiplantibacillus paracasei No. 244 Strain Glycerol - Esculin +++ D-arabinose - Salicin +++ L-arabinose D-ribose D-xylose L-xylose D-adonitol Methyl-bD-xylopiranoside D-galactose D-glucose D-fructose D-mannose L-sorbose L-rhamnose Dulcitol Inositol D-mannitol D-sorbitol Methyl-aD-mannopyranoside Methyl-aD-glucopyranoside N-acetylglucosamine Amygdalin Arbutin - +++ - +++ + - +++ +++ +++ +++ - +++ +++ - +++ +++ - +++ +++ +++ +++ D-cellobiose D-maltose D-lactose D-melibiose D-saccharose D-trehalose Inulin D-melezitose D-raffinose Amidon Glycogen Xylitol Gentiobiose D-turanose D-tagatose D-fucose L-fucose D-arabitol L-arabitol Potassium gluconate Potassium 2-ketogluconate Potassium 5-ketogluconate +++ +++ +++ - +++ +++ +++ +++ - - - - +++ +++ +++ - - - - ++ - - Gas production (+/-) - Temperature tolerance 10 degC - 30 degC ++ 37 degC ++ 45 degC - pH 2.5 0 h log (CFU/mL) 9.41 +- 0.2 2 h log (CFU/mL) 9.29 +- 0.1 CFU--colony forming units; interpretation of lactic acid bacteria (LAB) growth in API 50 CH system and API 20 E system: +++ = strong growth (yellow); ++ = moderate growth (green); + = weak growth (dark green); - = no growth (blue). foods-12-00937-t002_Table 2 Table 2 Acidity characteristics (pH and total titratable acidity), colour coordinates and hardness of scalded (Sc) and scalded-fermented (FSc) (after 0 and 24 h of fermentation) rye wholemeal flour. Samples Acidity Parameters Colour Characteristics, NBS Texture Hardness, mJ pH TTA, degN L* a* b* Sc 6.22 +- 0.06 c 1.04 +- 0.46 a 35.13 +- 4.31 a 2.46 +-0.25 a 8.80 +- 1.27 a 0.700 +- 0.100 b FSc-0h 5.95 +- 0.13 b 1.23 +- 0.16 a 34.37 +- 4.25 a 2.56 +- 0.20 a 10.8 +- 1.10 b 0.770 +- 0.100 b FSc-24h 4.57 +- 0.05 a 2.53 +- 0.15 b 32.29 +- 0.08 a 2.80 +- 0.21 b 7.49 +- 0.01 a 0.200 +- 0.050 a TTA--total titratable acidity; L* lightness; a* redness or -a* greenness; b* yellowness or -b* blueness; NBS--National Bureau of Standards units. Sc--scalded rye wholemeal flour; FSc--scalded-fermented rye flour; 0h--before fermentation; 24h--after 24 h of fermentation. Data expressed as mean values (n = 3) +- standard error (SE). a-c Mean values within a row with different letters are statistically significantly different (p <= 0.05). foods-12-00937-t003_Table 3 Table 3 Sugars (fructose, glucose, sucrose, maltose) concentration in rye wholemeal flour, and scalded (Sc) and scalded-fermented (FSc) (after 24 h) rye wholemeal samples. Samples Sugars, g/100 g Monosaccharides Disaccharides Fructose Glucose Sucrose Maltose Rye wholemeal flour nd nd 1.61 +- 0.09 1.02 +- 0.09 a Sc 0.880 +- 0.034 a 1.25 +- 0.08 a nd 6.26 +- 0.14 b FSc-24h 0.820 +- 0.053 a 1.44 +- 0.03 b nd 6.95 +- 0.23 b Sc--scalded rye wholemeal flour; FSc--scalded-fermented rye flour; 24h--after 24 h of fermentation; nd--not determined. Data expressed as mean values (n = 3) +- standard error (SE). a,b Mean values within a row with different letters are statistically significantly different (p <= 0.05). foods-12-00937-t004_Table 4 Table 4 Free amino acid profile and gamma aminobutyric acid (GABA) concentration in rye wholemeal flour and in scalded (Sc) and scalded-fermented (FSc) (after 24 h) rye wholemeal samples. Compound Name Rye Wholemeal Flour Sc FSc-24h Free Amino Acids and GABA Concentration, mmol/g Asparagine 5.19 +- 0.26 b 2.32 +- 0.17 a 2.11 +- 0.16 a Arginine 1.94 +- 0.12 c 0.855 +- 0.041 a 1.08 +- 0.09 b Serine 0.785 +- 0.031 b 0.368 +- 0.025 a 0.354 +- 0.028 a Aspartic acid 2.33 +- 0.09 b 0.528 +- 0.031 a 0.517 +- 0.036 a Glutamic acid 0.896 +- 0.039 c 0.281 +- 0.019 a 0.321 +- 0.021 b Threonine 0.516 +- 0.028 c 0.173 +- 0.011 a 0.308 +- 0.018 b Glycine 0.453 +- 0.015 b 0.259 +- 0.022 a 0.429 +- 0.022 b GABA 0.456 +- 0.021 a 0.482 +- 0.034 a 0.689 +- 0.043 b Alanine 1.56 +- 0.11 c 0.684 +- 0.041 a 1.17 +- 0.08 b Proline 2.24 +- 0.15 b 0.967 +- 0.053 a 0.968 +- 0.039 a Methionine nd nd nd Valine nd nd nd Phenylalanine nd nd nd Lysine nd nd nd Histidine nd nd nd Tyrosine nd nd nd Sc--scalded rye wholemeal flour; FSc--scalded-fermented rye flour; 24h--after 24 h of fermentation; GABA--gamma aminobutyric acid; nd--not determined. Data expressed as mean values (n = 3) +- standard error (SE). a-c Mean values within a row with different letters are statistically significantly different (p <= 0.05). foods-12-00937-t005_Table 5 Table 5 Bread specific volume, porosity, shape coefficient, mass loss after baking, colour characteristics of the bread crust and crumb, and bread crumb images. Bread Samples Specific Volume, cm3/g Shape Coefficient Mass Loss after Baking, % Control 1.90 +- 0.11 a 2.38 +- 0.19 b 6.30 +- 0.83 a Sc-5% 2.09 +- 0.09 a 2.64 +- 0.22 b 6.30 +- 0.83 a Sc-10% 2.00 +- 0.12 a 2.67 +- 0.19 b 11.2 +- 0.86 b Sc-15% 2.01 +- 0.08 a 1.89 +- 0.10 a 11.0 +- 3.28 b FSc-5% 2.06 +- 0.16 a 2.56 +- 0.14 b 12.0 +- 0.55 b FSc-10% 1.87 +- 0.05 a 2.60 +- 0.36 b 11.4 +- 0.68 b FSc-15% 1.94 +- 0.17 a 1.70 +- 0.35 a 9.25 +- 4.37 a,b Bread samples Crust Crumb L* a* b* L* a* b* Control 50.7 +- 4.14 b 8.62 +- 0.54 b 17.4 +- 1.55 b 53.0 +- 3.91 a,b 6.65 +- 0.28 d 19.9 +- 0.57 f Sc-5% 52.3 +- 4.57 b 7.44 +- 0.84 a,b 16.2 +- 1.01 b 58.7 +- 4.39 b 6.98 +- 0.20 d 18.2 +- 0.58 e Sc-10% 43.7 +- 2.68 a 8.26 +- 1.41 a,b 14.6 +- 2.13 a 58.3 +- 5.75 b 4.63 +- 0.48 b,c 16.1 +- 0.24 d Sc-15% 40.1 +- 3.85 a 6.50 +- 1.49 a 13.8 +- 3.87 a 48.3 +- 1.27 a 4.15 +- 0.06 a 13.7 +- 0.36 a FSc-5% 40.8 +- 2.44 a 8.36 +- 0.39 b 13.6 +- 0.90 a 51.5 +- 1.63 a 4.71 +- 0.06 b 15.1 +- 0.36 b FSc-10% 44.3 +- 2.45 a 9.38 +- 0.62 b 15.1 +- 1.12 a,b 54.7 +- 0.19 b 4.89 +- 0.07 c 15.8 +- 0.19 c FSc-15% 41.7 +- 3.64 a 8.03 +- 0.99 b 13.1 +- 2.43 a 51.3 +- 1.15 a 4.83 +- 0.16 a,b 15.1 +- 0.41 b Control Sc-5% Sc-10% Sc-15% FSc-5% FSc-10% FSc-15% Data expressed as mean values (n = 3) +- standard error (SE). a-f Mean values within a row with different letters are statistically significantly different (p <= 0.05). L* lightness; a* redness or -a* greenness; b* yellowness or -b* blueness; NBS--National Bureau of Standards units. Control--bread prepared without scald or fermented scald; Sc--scalded rye flour; FSc--scalded-fermented rye flour; 5, 10 and 15%--bread prepared with 5, 10 and 15%, respectively, scalded or scalded-fermented rye wholemeal flour. foods-12-00937-t006_Table 6 Table 6 Influence of analysed factors (fermentation and quantity of the scald, and their interaction) on bread specific volume, porosity, shape coefficient, mass loss after baking, and crust and crumb colour coordinates. Bread Parameters Factors and Their Interaction Scald Fermentation Scald Quantity Scald Fermentation and Quantity Interaction Specific volume, cm3 g-1 0.188 0.139 0.785 Shape coefficient 0.321 0.019 0.0001 Mass loss after baking, % 0.205 0.259 0.025 Crust L* 0.153 0.111 0.037 a* 0.022 0.048 0.863 b* 0.374 0.416 0.458 Crumb L* 0.154 0.016 0.080 a* 0.004 0.0001 0.0001 b* 0.240 0.014 0.014 Influence of analysed factors (fermentation and quantity of the scald) on bread parameters is statistically significant when p <= 0.05. foods-12-00937-t007_Table 7 Table 7 Influence of analysed factors (fermentation and quantity of the scald, and their interaction) on bread sensory properties and overall acceptability. Bread Parameters Factors and Their Interaction Scald Fermentation Scald Quantity Scald Fermentation and Quantity Interaction Colour 0.0001 0.953 0.189 Odour intensity 0.0001 0.003 0.0001 Bread odour 0.0001 0.322 0.012 Additive odour 0.0001 0.413 0.002 Flavour intensity 0.0001 0.424 0.0001 Bread flavour 0.0001 0.455 0.004 Additive flavour 0.0001 0.0001 0.0001 Acidity - - - Bitterness 0.0001 0.593 0.0001 Porosity 0.405 0.0001 0.508 Brittleness 0.0001 0.007 0.0001 Springiness 0.0001 0.685 0.0001 Hardness 0.0001 0.006 0.0001 Moisture 0.0001 0.003 0.0001 Overall acceptability 0.0001 0.395 0.0001 - not detected. Influence of analysed factors (fermentation and quantity of the scald) on bread parameters is statistically significant when p <= 0.05. foods-12-00937-t008_Table 8 Table 8 Influence of analysed factors (fermentation and quantity of the scald, and their interaction) on acrylamide concentration in bread. 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PMC10000375 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13051001 diagnostics-13-01001 Article Diabetic Retinopathy and Diabetic Macular Edema Detection Using Ensemble Based Convolutional Neural Networks Sundaram Swaminathan 1 Selvamani Meganathan 1 Raju Sekar Kidambi 2* Ramaswamy Seethalakshmi 3 Islam Saiful Investigation 4 Cha Jae-Hyuk Writing - review & editing 5* Almujally Nouf Abdullah Resources Data curation 6 Elaraby Ahmed Resources 78 Han Jae-Ho Academic Editor 1 Department of CSE, SASTRA Deemed University, SRC Kumbakonam, Thanjavur 612001, India 2 School of Computing, SASTRA Deemed University, Thanjavur 613401, India 3 Department of Maths, School of SASH, SASTRA Deemed University, Thanjavur 613401, India 4 College of Engineering, King Khalid University, Abha 61421, Saudi Arabia 5 Department of Computer Science, Hanyang University, Seoul 04763, Republic of Korea 6 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi Arabia 7 Department of Computer Science, Faculty of Computer Science and Information, South Valley University, Qena 83523, Egypt 8 Department of Cybersecurity, College of Engineering and Information Technology, Buraydah Private Colleges, Buraydah 51418, Saudi Arabia * Correspondence: [email protected] (S.K.R.); [email protected] (J.-H.C.) 06 3 2023 3 2023 13 5 100128 1 2023 23 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 ). Diabetic retinopathy (DR) and diabetic macular edema (DME) are forms of eye illness caused by diabetes that affects the blood vessels in the eyes, with the ground occupied by lesions of varied extent determining the disease burden. This is among the most common cause of visual impairment in the working population. Various factors have been discovered to play an important role in a person's growth of this condition. Among the essential elements at the top of the list are anxiety and long-term diabetes. If not detected early, this illness might result in permanent eyesight loss. The damage can be reduced or avoided if it is recognized ahead of time. Unfortunately, due to the time and arduous nature of the diagnosing process, it is harder to identify the prevalence of this condition. Skilled doctors manually review digital color images to look for damage produced by vascular anomalies, the most common complication of diabetic retinopathy. Even though this procedure is reasonably accurate, it is quite pricey. The delays highlight the necessity for diagnosis to be automated, which will have a considerable positive significant impact on the health sector. The use of AI in diagnosing the disease has yielded promising and dependable findings in recent years, which is the impetus for this publication. This article used ensemble convolutional neural network (ECNN) to diagnose DR and DME automatically, with accurate results of 99 percent. This result was achieved using preprocessing, blood vessel segmentation, feature extraction, and classification. For contrast enhancement, the Harris hawks optimization (HHO) technique is presented. Finally, the experiments were conducted for two kinds of datasets: IDRiR and Messidor for accuracy, precision, recall, F-score, computational time, and error rate. diabetic retinopathy ensemble convolutional neural network diabetic macular edema Harris hawks optimization and artificial intelligence "Human Resources Program in Energy Technology" of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial resources from the Ministry of Trade, Industry & Energy, Republic of Korea20204010600090 Princess Nourah bint Abdulrahman University ResearchersPNURSP2023R410 This work was supported by "Human Resources Program in Energy Technology" of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), granted financial resources from the Ministry of Trade, Industry & Energy, Republic of Korea. (No. 20204010600090). The funding of this work was provided by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R410), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. pmc1. Introduction Computer-assisted health care, health care technology consulting, and health monitoring equipment are just a few of the current buzz words. Thanks to the connection and computing architecture that has drawn attention to the electronic era we live in, ordinary people now have the luxury of receiving diagnosis and treatment from the comforts of home with a single tap . While routine illnesses and minor illnesses can usually be treated without visiting a doctor, some more severe illnesses still necessitate a great deal of effort from the medical establishment. Technology can help, but not replace human intervention. With the advancement in AI technology, technologies can now autonomously analyze a patient's condition and identify a condition in a matter of seconds using the patient's significant history and associated data . By 2025, the amount of DR individuals suffering is predicted to rise from 382 million to 592 million. According to a study conducted in the Pakistani province of Khyber Pakhtunkhwa (KPK), 30 percent of diabetic individuals suffer from DR, with 5.6 percent going blind . If mild NPDR is not treated in the beginning phases, it might progress to PDR. In another study, 130 people with DR symptoms were found in Sindh, Pakistan . According to the findings, DR patients made up 23.85% of the overall examined patients, with PDR patients accounting for 25.8% . Patients with DR are symptomatic in the beginning phases; however, as the disease progresses, it causes blobs, vision problems, distortions, and gradual visual acuity loss. Diabetic retinopathy is one of the issues previously mentioned in the article. Diabetic retinopathy is caused by diabetes destroying the blood flow on the retina's inner, resulting in blood and other body fluids leaking into the tissues surrounding it. Soft, damaged tissue (also known as cotton wool patches) , hard exudates, microaneurysms, and hemorrhages form as little more than a result of the leaking . It is the most common cause of visual loss in the working-age population . Diabetic retinopathy (DR) is caused due to diabetes mellitus, which can damage the retina and even lead to the loss of vision. The DR has several stages of severity such as mild, moderate, and severe . The severe stage of DR is termed as proliferative diabetic retinopathy (PDR), in which the formation of new vessels in the retina is observed . However, the early detection of DR and proper diagnosis will reverse or reduce the growth of the effects caused by the disease. Diabetic macular edema (DME) is a condition in which the lesions caused by DR are observed in the middle portion of the retina called the macula. The DME is considered as a serious condition as the damage caused by it is irreversible. The identification of features such as micro-aneurysms, hard exudates, hemorrhages, etc., can be used to carry out the detection of these diseases. These micro-aneurysms refer to the red spots in the retina's blood vessels with sharp margins formed in the early stages of the disease. The exudates are caused due to abnormality in the blood vessels, which are formed as yellowish-white spots in the outer layer of the retina. Hemorrhages also occur such as micro-aneurysms but have irregular margins caused due to the leakage of capillaries. The blockage of arteries also contributes to cotton wool spots, which occur as a white region in the retinal nerve. Several methods have been developed for the detection of DR and DME to provide diagnosis, but these traditional methods were inefficient in accurately detecting diseases. Deep learning techniques have been deployed for disease detection in which the retinal image (fundus image) is used as the input in which the features are extracted for detection. These approaches have been found to be more effective in identifying features than the traditional methods; however, these approaches also suffer from inaccuracy due to the presence of noises and artifacts in the input images. Figure 1 describes the retina images for disease DR and DME. As a result, it is hard but critical to recognize DR to prevent the worst effects of later stages. Fundus imaging is utilized to diagnose DR, as mentioned in the preceding section. Manual analysis can only be performed by highly qualified subject matter experts and is thus cost and time intensive. As a result, it is critical to apply machine vision technologies to assess the retina image features and aid physicians and radiologists. Hands-on development and end-to-end learning are two types of computer vision-based methodologies. Traditional algorithms such as HoG, SIFT, LBP, Gaussian filters, and others are used to extract the features; however, they failed to preserve the scale, rotation, and brightness fluctuations . Several existing approaches have integrated the preprocessing of input images and the deep learning-based detection of diseases in which the accuracy in the detection of diseases was observed to be improved. The common processes involved in these approaches are the preprocessing of input images, enhancement in contrast, and the extraction of features for the detection of diseases. The machine learning models such as support vector machine (SVM) and K-nearest neighbor (KNN) classifiers were found to be appropriate for detecting DR and DME. The severity of the disease was determined by the number of features identified by the model; however, the imbalance in the distribution of datasets resulted in the inefficient determination of severity. In particular, an effective mechanism in the detection of DR and DME, along with the determination of severity, is still in demand. The major aim of this research work was to provide the effective detection of DR and DME and to determine the disease's severity to define the disease's damage level on the patient. The accuracy of detection was achieved by performing the proper processing of the input retinal image. End-to-end learning understands the underlying rich traits dynamically, allowing for greater identification. Inside the retina imaging databases, many hand-on engineering and end-to-end learning-based algorithms have been used to identify the DR. Still, none of them can identify the mild stage. Accurate diagnosis of the weak stage is critical for controlling this devastating disease. Utilizing end-to-end deep ensembles models, this study attempted to discover all stages of DR (including the moderate stage). The findings revealed that the proposed strategy beats the current methods. The major objective of this research is to provide precise classification between the DR and DME and to compute the severity of the diseases accurately. This objective can be achieved by fulfilling the sub-objectives, which are listed as follows, To minimize the noise level in the input image by performing effective preprocessing of the image; To maximize the precise identification of features from the preprocessed image by enhancing the contrast level; To maximize the accuracy of detection by incorporating the segmentation of lesions in the blood vessels; Effectively classify the images into three classes based on the extraction of significant features; To determine the severity of the disease based on the variation in the intensity of the features for diagnosis. The major contributions of this paper are as follows: In our work, we performed preprocessing that included three processes such as noise removal using iterative expectation maximization, artifact removal using nonlinear filtering, and contrast enhancement using Harris hawks optimization; the preprocessed image was used to enhance the quality of the images, which led to high segmentation and detection accuracy. Preprocessing was performed to reduce noise and artifacts and improve the contrast, which increased the efficiency of feature extraction and reduced the false detection rate. Segmentation was performed before feature extraction and classification, which increased the detection accuracy. For segmentation, we proposed improved OPTICS clustering, which considers particular regions of interest and takes less time for segmentation, thus reducing latency and increasing the disease detection accuracy. Improved OPTICS clustering overcomes misalignment problems due to considering the particular region of interest, thus increasing the segmentation and detection accuracy. The extraction of features was carried out in the segmented images obtained from the previous process. Features such as micro-aneurysms, hemorrhages, and hard exudates, collectively termed as structural features, are considered the essential features; along with this, the shape features, orientation features, and color features are also considered for the classification of DR and DME. The ensemble CNN architecture was implemented for this purpose, which outperformed the ensemble CNN class prediction. From this, the classification of images was carried out in several classes, namely, normal, DR, and DME. Furthermore, the severity of the disease was computed by using conditional entropy in which the number of lesions is considered for the threshold generation. Based on the threshold, the severity level of the disease was classified into three classes: mid, moderate, and severe. The proposed research work is evaluated in terms of performance metrics such as accuracy, precision, recall, F-score, computation time, and error rate. The rest of the paper is organized as follows: Section 2 illustrates the state-of-the-art in diabetic retinopathy and diabetic macular edema detection using specific approaches. Section 3 discusses the major problems that exist in this field. Section 4 describes the system model with the proposed algorithms and techniques in detail. Section 5 describes the experimental results of the proposed as well as previous methods. Section 6 concludes the paper by providing future enhancements. 2. Related Work In the literature, the diagnosis of DR has received much interest. In , researchers offered a robust system that automatically recognized and classified retinal lesions (blood vessels, microaneurysms, and exudates) from retinal imaging. Blood vessels, microaneurysms, and exudates were first discovered using image processing methods. Following this, the retina properties of the vascular system, microaneurysm count, exudate area, contrast, and homogenization were evaluated from the images obtained. These characteristics were then fed into a fuzzy classifier that uses the information to classify healthy, mild NPDR, moderate NPDR, severe NPDR, and PDR stages. A sample of 40 color fundus images was obtained from the DIARETDB0, DIARETDB1, and STARE datasets using a fuzzy classifier, correctly classifying the images with an efficiency of up to 95.63 percent. A reliable automated approach for detecting and classifying the various stages of DR has been suggested The optic disc and retina neurons are separated, and characteristics are retrieved using the gray level co-occurrence matrix (GLCM) approach. To identify various stages of DR, a fuzzy classifier and a convolutional neural network were used to classify them. DIARETDB0, STARE, and DIARETDB1 were the datasets used . The unique clustering-based automatic region growth methodology was introduced in this study. Several types of features--waveform (W), co-occurrence matrix (COM), histogram (H), and run-length matrix (RLM)--were retrieved for the texture features, and several ML algorithms were used to achieve a classification performance of 77.67 percent, 80 percent, 89.87 percent, and 96.33 percent, respectively. The information fusion approach was utilized to create a fused hybrid-feature database to improve the accuracy of the classification. Two hundred and forty-five elements of the hybrids' feature data (H, W, COM, and RLM) were extracted from each image, and 13 optimum characteristics were chosen using four methodologies: Fischer, mutual information feature selection, information gain, and the possibility of the dependent variable average correlation . The number of DR patients outnumbered the number of practitioners by a large margin. As a result, manual clinical diagnosis or screening takes a long time. To avoid this problem, follow-up scanning is performed regularly, and automated DR identification and intensity classification are required. Several strategies for detecting retinopathy and classifying its severity and likelihood are presented here . Exudates are the diagnostic indications of diabetic retinopathy, a retina condition caused by long-term diabetes that can lead to eyesight problems if not detected early. The procedure of recognizing and categorizing exudates from a retinal image has been made easier thanks to a medical screening program. The exudates are first segregated using the FCM technique and then transformed into discrete mother wavelets. The classifier is fed the texture textural properties retrieved by the grey-level co-occurrence matrix. The suggested program's efficiency was evaluated by comparing it to the data from the publicly available dataset IDRID. MATLAB was used to formulate and construct a GUI . This research has the proposed texture feature extraction characteristics of the GLDM method (contrast, angular second moments, density, median, and inverse difference moment) feature and feed-forward neural net classifier as a machine learning-based approach for DR detection and evaluation. According to the results of the trials and performance assessment, the suggested methodology had a detection performance of 95% . Diabetes is responsible for 50 deaths per 1000 live births amongst individuals over the age of 70. The identification of diabetes at a preliminary phase and the implementation of a suitable therapy may minimize the visual loss among the sufferers. Once symptoms of DR have been identified, the severity of the disease must be defined to recommend the appropriate treatment. Mild nonproliferative diabetic retinopathy (NPDR), moderate NPDR, severe NPDR, proliferative diabetic retinopathy (PDR), and no DR are the five phases of diabetic retinopathy severity. The techniques and issues associated with DR identification are summarized in this publication . In , the authors proposed diabetic retinopathy classification using retinal images through an ensemble learning algorithm. The proposed work includes the following processes: retinal image collection, preprocessing, feature extraction, and feature selection and classification. In preprocessing, the noisy images, duplicate images, and black borders are removed from the images. Tone mapping is used to increase the contrast and luminance in the images. Two sets of features are extracted from images such as the histogram-based feature and GLCM feature extraction. Then, the features are concatenated to select the relevant features. Here, the GA algorithm is used for feature selection. Finally, classification was undertaken by the XGBoost algorithm using the selected features. Here, genetic algorithm (GA) was used for feature selection; it takes a lot of time to select the features, thus increasing feature selection and classification latency. Early detection of diabetic retinopathy using retinal images for diabetes is presented in . The proposed method includes four processes: preprocessing, segmentation, feature extraction, and classification. The preprocessing includes noise removal and contrast enhancement using histogram equalization (HE). The segmentation is performed by Gaussian derivative and Coye filter, which segments the EX, MA, and HM. The features are extracted from the segmented image and extract features such as EX, MA, and HM values. Finally, SVM is used to classify the images using the extracted features. Here, SVM was used for classification, which takes a lot of time for training when considering larger datasets, thus leading to classification latency. A histogram equalization method for the early detection of diabetic retinopathy was presented in . The proposed algorithm included three methods: histogram clipping, RIHE-RVE, and RIHE-RRVE, which addressed the issues of the illumination of the retinal images. To avoid enhancement, the histogram clipping algorithm was proposed. The simulation result showed that the proposed method achieved a high performance compared to the other state-of-the-art methods. Here, the histogram equalization method was proposed, however, it is an unselective process that may increase the background noise contrast while decreasing the functional input image. The authors in proposed CANet to detect diabetic retinopathy and macular edema for diabetes. The proposed work used ResNet50 to produce a feature map with various resolutions including a cross-disease attention network, disease-specific attention module, and disease-dependent attention module. The disease-specific attention module was used to learn the features of the two diseases. In this stage, the inter special relationship was evaluated to detect the diseases. A disease dependent attention module was used to evaluate the internal relationship between the DR and DME diseases. Here, raw images were considered for training and testing, thus increasing the high false positive rate due to the presence of noise and low contrast, also reducing the detection accuracy. The authors in proposed a deep learning algorithm to detect diabetic retinopathy disease in diabetic patients. The proposed method included two processes: diagnosing DR severity and the feature extraction of DR. The proposed system hierarchical multitask learning architecture aims to detect both the DR severity and DR feature extraction. Finally, the fully connected layer provides the output, and it considers the hybrid loss, cross-entropy loss, and kappa loss for reducing the errors in the levels of DR severity. The simulation results showed that the proposed model achieved a higher performance using traditional deep learning methods. Here, the traditional deep learning method was used to detect the DR severity levels and feature extraction of DR; however, it generated multiple convolutional layers, thus increasing the complexity and latency. In , the authors proposed a modified contrast enhancement approach from the effective identification of features in detecting diabetic retinopathy and diabetic macular edema. The limitations of conventional contrast limited the adaptive histogram equalization (CLAHE) technique such as the fixed clip limit and region of context, resulting in the inefficient identification of minute features, but can be overcome by implementing modified particle swarm optimization (MPSO) to determine the optimal clip limit and region of context, thereby resulting in the precise identification of features that further help in the accurate detection of diseases. The global best solution of all the operating particles was computed by comparing the output provided by all the particles in the iteration, which resulted in enhanced image contrast. The optimization of the clip limit and region of context was performed by the MPSO algorithm for the purpose of enhancing the contrast of the input image, but the proposed algorithm possessed slow convergence and is stuck in the optimal local solution. In , the authors proposed an approach for the detection of diabetic macular edema in an automatic manner. The macular edema was identified, and the severity of the disease was determined by implementing mathematical morphology. The retinal image was used as the input from the detection process that was carried out. Initially, the preprocessing of the input image was performed from the removal of noise and enhancement of the contrast. Furthermore, the localization of the macula was executed by removing the optic disc and locating the center of the fovea. Then, the exudates in the region of the macula were identified in order to determine the severity of the disease. The removal of artifacts such as reflection due to lighting was removed as a post-processing step to achieve an accurate determination of severity. The detection of the macula in the input retinal image was carried out by using mathematical morphology, but this approach resulted in less accuracy in the detection of the macula region. In , the authors proposed a probability-based construction of the future retinal image in detecting diabetic retinopathy. The difficulty in identifying the future instances of lesions in the retinal image was addressed. Initially, the segmentation of lesions and vessels was carried out to identify the severity of the disease from the input retinal image. Then, the probability of future lesion location was computed by the construction of a probability map. Furthermore, the generated probability map, along with the structure of vessels, was considered for the systemization of future lesions in the retina. This method was found to be effective in predicting future lesions based on the progression of the severity of diseases. The future severity of diabetic retinopathy was determined by using the probability map and the features of the current vessels, but the lack of noise removal in the input image reduced the efficiency of this approach. 3. Problem Statement An input fundus image is used to perform the identification of diabetic retinopathy and diabetic macular edema; however, the accuracy of the system is decreased by the increased false detection rate of the existing techniques. In addition, the following issues are encountered in the best detection of DR and DME, which are listed as:Difficulty in feature differentiation: The detection of DR and DME is based on various features such as hard exudates, hemorrhages, and micro-aneurysms, but the differentiation of these minute features from each other is a hard task, which degrades the computation of the accurate severity of diseases. Class Overlapping: Current techniques also consider illness severity; however, the sparse training data for each severity leads to class imbalance issues that degrade the classification accuracy. Inadequate preprocessing: Using the current methods for effective contrast enhancement with traditional preprocessing leads to difficulties distinguishing features from the background. In , the authors proposed diabetic retinopathy detection using a deep convolution neural network (DCNN) for nonproliferative diabetic retinopathy. The proposed work includes three phases: preprocessing, candidate lesion detection, and candidate extraction. In preprocessing, the image contrast is enhanced using curve transformation. Then, the images are smoothened by a bandpass filter. In the lesion, the detection process includes four stages: optical disc removal, candidate lesion detection, vessel extraction, and preprocessing. In candidate extraction, the micro-aneurysms are detected to measure the coefficient between every pixel using Gaussian kernels. For this, a PCA algorithm was proposed to reduce the dimensionality. Finally, classification was undertaken by DCNN. In this way, the proposed work achieved high accuracy of nonproliferated diabetic retinopathy. The major issues determined in this paper are as follows:Here, preprocessing was performed to enhance the quality of the retinal images; however, the retina image still has noise due to the implementation of traditional contrast enhancement techniques, thus reducing the image quality, which leads to a high false detection and reduced detection accuracy. DCNN is used for feature extraction and the detection of nonproliferated diabetic retinopathy. Still, DCNN focuses on the whole image for the extraction of features without any particular region of interest, thus increasing the high latency for feature detection. The PCA algorithm was used to reduce the dimensionality, but the number of principal components must be selected otherwise it may cause information loss, thus reducing the detection accuracy. The authors in proposed a data augmentation method to improve the detection rate of proliferative diabetic retinopathy. The NVs were inserted onto pixels located on vessels. Vessel segmentation was performed by Otsu thresholding and the U-Net deep learning algorithm, and then optic disc segmentation was performed. The count of NVs was determined by selecting random values using a threshold. The next process is semi-random blood vessel generation, which is based on the tree structure. This process considers the shape and orientation of the NVs. For the vessel color assignment color, a matrix was proposed that calculates the weighted average of the RGB values of the images. Finally, DR grading and data augmentation was proposed to improve the NVs. Some of the significant problems in this research are as follows:Here, the Otsu thresholding method was used for vessel segmentation, which performed well; however, it did not provide an optimal result for noisy images. First, the noise is removed from the images, and then the thresholding is applied; otherwise, this method will fail, thus reducing the performance of vessel segmentation. The detection of diabetic retinopathy was carried out by performing the segmentation of neovessels in the retina. However, performing detection based on a single feature results in a high false detection rate. Here, the U-Net algorithm was also used for vessel segmentation, which takes a lot of time to learn the vessels from the retinal images at the middle layers, thus leading to high latency. The authors in proposed the analysis of retinal images to detect eye diseases for diabetes using the deep learning method. The proposed method considered two processes: detection and localization, and the segmentation of localized regions. For localization, the author proposed the FRCNN method, which extracts the features from the images that evaluate the affected portions. For the segmentation process, the author proposed the FKM clustering algorithm. The ground truth was generated for detecting the affected regions during training. Finally, the DME is classified into two classes such as DME and background. The serious issues in this paper are as follows:Here, raw images were considered for the localization and segmentation process, thus reducing segmentation and detection accuracy due to low contrast and the presence of noise in the retinal images. Faster RCNN was implemented for the extraction of features but the lack of pixel-to-pixel alignment in the region of interest caused misalignment, resulting in the degradation of the detection accuracy. The proposed approach was used for diabetic-based disease detection in the eye, but the detection of various diseases from the limited number of trained images resulted in class imbalances. The authors in presented an efficient framework for the detection of macular edema disease for diabetes. The proposed work used the combination of a deep convolution neural network (DCNN) and a meta-heuristic algorithm for feature extraction and feature selection, respectively. At the stage of feature extraction, the proposed work reduced the feature extraction complexity by reducing the prior knowledge. The SMOTE algorithm was used to perform class imbalance. The generic algorithm and binary particle swarm optimization algorithm were used to select the relevant features. The drawbacks in this paper are as follows:Here, the features were extracted from the noisy images, thus reducing the quality of the images and leading to poor feature extraction, thus increasing the macular edema's false detection rate. The integration of the genetic algorithm and binary particle swarm optimization was used to determine the subset size. However, implementing these two algorithms increases the complexity and time consumption, thereby increasing the latency. DCNN was used for feature extraction and the detection of nonproliferated diabetic retinopathy, however, DCNN focuses on the whole image for the extraction of features without any particular region of interest, thus increasing the high latency for feature detection. 4. Proposed Model In this research work, we concentrated on accurately detecting the DR and DME from the input fundus images. The severity of the disease is also determined based on the features extracted from the images. Figure 2 shows the architectural view of the proposed work. The description of the dataset is provided below: The properties of the blood vessels in the retinal image enable the ophthalmologist to assess retinal disease. The presence of lesions on the fundus image is the first sign of diabetic retinopathy. The preprocessing technique is mainly used to remove unwanted noise and enhance some image features. The fundamental idea underlying OPTICS is to find the points associated by density to extract the cluster structure of a dataset. The approach generates a density-based representation of the data by constructing a reachability graph, an ordered collection of points. Each location in the list has a reachability distance associated with it, which measures how simple it is to get to that site from other points in the collection. Points with comparable accessibility distances are most likely in the same category. Before sharing our preprocessed image with CNN, we converted the image to an array and mapped that array's values in the range of 0 to 1 as the epoch was set at 235 to reach a deep network. The initial learning rate was kept at 1 x 103, which is the default value for the Adam's optimizer, and the die stack size was 32. We trained our model with more pictures, obtained only a few hundred of images for training, and generated more images from the existing dataset by passing parameters such as the rotating range, width changing range, height changing range, scissors range, zoom range, and pan on image data generator. The classification of diabetic retinopathy is classified into two types: nonproliferative and proliferative. The term "proliferative" refers to whether the retina has neovascularization (abnormal blood vessel growth). Nonproliferative diabetic retinopathy refers to early illness without neovascularization (NPDR). Dataset Collection: For accurate prediction of diabetic retinopathy and diabetic macular edema, we applied two kinds of retina fundus images: IDRiD and MESSIDOR. The description of these two datasets is as follows:IDRiD: Based on the presence of DR and DME disease, 516 images were loaded in the dataset. In addition, images were acquired through the field of view and stored in JPG format, and the size of each image was 800 KB. This dataset contained 81 color fundus images with the sign of DR. With this dataset, hard exudates (EX), microaneurysms (MA), soft exudates (SE), and hemorrhage (HE) based images are stored. MESSIDOR: This dataset was used, whose scope is to develop the DR and DME detection of images. In total, 1200 eye fundus images were used with the multiple pixel rates of 1440 x 960, 2240 x 1488, and 2304 x 1536. The following steps implement a prediction of DR and DME. 4.1. Preprocessing This is an initial step for DR and DME detection. To enhance the information for the disease diagnosis system, it is necessary to use some of the preprocessing steps as follows: (a) Noise Filtering: Fundus images are cropped by salt and pepper noises, which are removed from the input images using the iterative expectation maximization (IEM) approach. In this approach, uncertainty is overwhelmed by using IEM variables. Noise is removed in the zig-zag trajectory and edge, and the corner position of the image is denoised using IEM variables. A dynamic threshold was computed and adjusted accordingly for noise removal since the acquisition of each image was different with their resolution. The proposed inverse dual tree initial ranging (IDTIR) procedure uses the iterative expectation maximization (IEM) algorithm. The IEM algorithm is an iterative method that effectively estimates the parameters of the statistical model. In the IEM algorithm, two major steps are executed to estimate the parameters accurately. These steps can be explained as follows:E-step--This step determines the current estimate of parameters by creating a function for the expectation of log-likelihood. The expectation step is the base of the proposed IEM algorithm. M-step--This step is the final step that computes the parameters in such a way that the expected log-likelihood function can be maximized (i.e., the likelihood function determined in the E-step is maximized to calculate the parameters. The above two steps were iteratively executed to determine the final parameters. Let oV,L be the parameter vector, and it can be represented as oV,L=hV,L,TV,Lm for the Lth active channel path of the given ranging code. The set of parameters is represented as m. The latest estimated parameter set is denoted as m^ and can be formulated as follows, (1) o^V,L=h^V,L,T^V,Lm^ E-Step Computation In this step, the expected value is calculated as (2) GoV,L|m^lnPY|oV,L,m^a-||Y-K^V,L-hV,LGTV,LV||2 Here, (3) K^V,A=1Ns=1NBh^A,sG(T^A,s)A-h^V,LGT^V,LV M-Step Computation In this step, the expected value is maximized as follows:(4) o^V,L=argmaxGoV,L|m^ After parameter estimation, the estimated parameters are updated in the parameter vector. These two steps are executed until the terminating condition is met. The channel coefficient is derived from the parameter vector by letting the derivative equal zero with the fixed timing offset. (b) Artifact Removal: Blurriness, poor edges, and illumination are called artifacts, which are removed using the nonlinear diffusion filtering algorithm, which eliminates all kinds of artifacts and ensures the image quality in terms of illumination correction and edge preservation. (c) Contrast Enhancement: Low contrast is one of the important issues of image classification. In this work, we considered contrast enhancement as an optimization problem with the intention of optimizing the pixel values based on the contrast level of the input image. To enhance the contrast level of the input image, we proposed the Harris hawks optimization algorithm, which improves the performance of the image brightness. H2O is a recently developed meta-heuristic algorithm that performs better in solving optimization problems. The H2O algorithm mimics the cooperative strategy and chasing style of the Harris hawks in nature. Since it has an intelligent searching strategy and fast convergence rate, it works better than the conventional genetic algorithm, particle swarm optimization algorithm, etc. Due to the benefits of the H2O algorithm, it was adapted for contrast enhancement using the pixel intensity rate in the proposed system. The proposed H2ORSS algorithm detects the optimum threshold value for replacing the pixel intensity values with normal ones. The proposed H2ORSS algorithm involves three major processes: initialization, fitness value estimation, and update of hawks. Initially, the image matrix is initialized as hawks with the population size of PS. For each hawk (Xi) in the population, the fitness function is estimated. The fitness function is determined in terms of the pixel intensity, neighbor intensity, and resolution. The fitness function of the ith hawk is expressed as follows, Once the fitness is computed for all hawks, then three sequential phases are executed to select the optimal solution. Phase 1: Exploration Phase This phase relies on waiting, searching, and detecting prey. In every step, each Harris hawk is considered as the alternative solution. Based on the fittest solution, the position for each Harris hawk is updated as follows:(5) Xiter+1=Xranditer-r1Xranditer-2r2Xiter if o>=0.5Xpiter-Xaiter-r3lb+r4ub-lb if o<0.5 The location of the hawks in the next iteration is denoted as Xiter+1 and r1, r2, r3, r4 are the present location vectors of the hawks. Furthermore, o is the random number selected in the range of 0 and 1, and ub,lb are the upper bound and lower bound, respectively. The average location of hawks (Xaiter can be estimated from the following expression:(6) Xaiter=1PSi=1PSXiiter Phase 2: Transformation from Exploration to Exploitation Next, the algorithm transforms the state from exploration to exploitation. In this transformation, the energy of the prey is dissipated due to evading behavior. The energy level of the prey is (Ep), which is expressed as follows:(7) Ep=2Eo1-iterTm Here, E0 is the initial state energy of the prey and tm is the maximum iteration. By varying the tendency of E0, the state of the prey can be judged. Phase 3: Exploitation After judging the state of the prey, the Harris hawks attack the selected prey. In practice, the prey changes the evading behavior, frequently changing the attacking behavior. Four strategies are constructed in the H2ORSS algorithm for attacking prey based on evading behavior. Here, soft besiege and hard besiege are the basic strategies to attack the prey, which is decided as follows: If Ep>=0.5, then a soft besiege occurs, and if Ep<0.5, then a hard besiege occurs. Soft Besiege This attacking strategy is selected when Ep>=0.5 and r>=0.5 by Harris hawks. This soft besiege attacking strategy is modeled as follows:(8) Xiter+1=DXiter-EpFXpiter-Xiter Here, F is the jump intensity of the prey during the evading process, and it is given as F=21-r5 and DXiter represents the difference in the location vector of prey in each iteration. This difference is estimated by using the following expression:(9) DXiter=Xpiter-Xiter Hard Besiege If Ep<0.5 and r>=0.5, the hard besiege strategy is selected to attack the prey. In general, these probability values show that the prey's energy is dissipated and has low evading energy. In this case, the position of Harris hawks is updated by the following equation:(10) Xiter+1=Xpiter-EpDXiter Soft Besiege with Progressive Rapid Dives This strategy is selected when the prey has sufficient energy to evade form the attack. This situation is explained as Ep>=0.5 and r<0.5. Based on this behavior, the next position of the hawks is updated as follows:(11) Y=Xpiter-EpFXpiter-Xiter As this strategy involves progressive dives, the hawk's dive is formulated as follows:(12) Z=Y+B*lfd where B represents the random vector; lfd represents the levy flight with the dimension d. Thus, the next position is updated as follows: (13) iter+1=Y if fY<fXiterZ if fZ<fXiter Hard Besiege with Progressive Rapid Dives This situation is defined as the prey has not sufficient energy to escape. This situation is formulated as Ep<0.5 and r<0.5. The rule for this situation is formulated as follows:(14) Xiter+1=Y if fY<fXiterZ if fZ<fXiter Here, Y is estimated using the upcoming Equation, (15) Y=Xpiter-Ep|FXpiter-Xaiter Based on the above rules, the position of each hawk is updated, and the optimal solution is derived over iteration. Finally, the optimum threshold value was computed for the prediction of contrast values throughout the images. Algorithm 1 deals with Generalized Linear Model (GLM), which is used for regression and classification tasks, is one of the key algorithms in H2O. GLM is a versatile and effective modeling approach that can deal with different data kinds and distributions. Algorithm 1 Pseudocode for H2O Input: PS,Maxite Output: Optimal Threshold Begin Initialize - hawks population Xi (C.U.i); While (Stopping Condition Not Met) do Compute - fitness function For (XiXPS)do Update -Eo and F; Update -Ep using Equation (8); End For If (Ep>=1)Then Update position using Equation (9); End If If (Ep<1)Then If (r>=0.5&&|Ep|>=0.5) Update - position using Equation (10); Else If (r>=0.5&&|Ep|<0.5)Then Update - position using Equation (11); Else If (r<0.5&&|Ep|>=0.5)Then Update - position using Equation (12); Else If (r<0.5&&|Ep|<0.5)Then Update - position using Equation (13); End If End If End While End 4.2. Blood Vessel Segmentation Blood vessels are important in computing the image intensity, edges, texture, and other analyses of image features. Analyzing the diagnosis over the segmented area increases the accuracy and precision rate of any disease. Hence, the optic disk is removed from the contrast-enhanced image, and then the blood vessels are extracted using improved mask RCNN, in which ROI alignment is the first step that predicts the region of interest from the input image. In this work, pixel-wise softmax was applied for accurate segmentation of blood vessels, which was better than the CNN, RNN, RCNN, and DCNN algorithms . OPTICS clustering stands for ordering points to identify clustering structure. It is more similar to DBSCAN clustering. OPTICS algorithm includes two measurements, which are defined as follows, Core distance: This represents the minimum values of the radius essential to classify the given point as a core point. If the considered point is not a core point, then its core distance is indeterminate. Reachability distance: This is represented with respect to another cluster data point. The reachability distance between two points (x,y) is the highest of the core distance and then the Euclidean distance between the two points (x, y). The reachability distance is not defined if the y point is not a core point. Figure 3 represents the calculation of the reachability distance. The general procedure of M-OPTICS is defined as follows: Next, the proposed M-OPTICS explanation is defined as follows: M-OPTICS considers three important conditions: maximum radius, distance, and number of cluster points including the core distance, core points, and reachability distance. In the M-OPTICS algorithm, the point P is known as the core point when the point is on MinPts. The reachability distance and core distance calculations are given as follows:(16) CDo= , o,e<MinPtsMinPts-Do, otherwise (17) R.D.p,o=maxCDo,Dp,o where p represents the object and o represents the center point. The core distance represents the lowest value, which is the radius. From the radius, the core point is different. RD represents the reachability distance, which is estimated as the highest core distance, and e represents the radius of the data. The reachability distance data are clustered separately. The data similarities were measured by Jaccard similarity, which calculates the similarity between a finite set of samples. The calculation of the Jaccard similarity is defined as follows:(18) JD=1-JmA,B (19) JmA,B=mABmAB where A and B represent the two points obtained from the blood vessels. The CNN-based ensemble learning model was incorporated due to two major unique features: shared weights and local connections. The extraction of features from the input data using convolutional layers and determining the relationship between the obtained features using the pooling layers was implemented, which can be formulated as:(20) aql=p=1Vapl-1*Jpql+yql where Jpql, yql denote the trainable parameters, and V denotes the input features. The output provided by the nonlinear layer is computed as:(21) xd=fvd where function fvd denotes the output of the rectified linear unit. The performance of the model can be further improved by executing batch normalization. The dataset comprising of fused images of R dimensions comprised of a T number of training samples can be denoted as H=hi,cli|1<=i<=T, where the classes are cliCl=1,2,...,M and the maximum count of classes is denoted as M. In the ensemble model, each model's training is performed randomly. The input of each CNN will be H =hi ,cli|1<=i<=T, which comprises r "R feature subspaces that are randomly selected. For instance, i and j are two identical features with dimension d, and for that similarity function simpdi,j, which is computed by:(22) simpdi,j=vectorixvectorj||vectori||x||vectorj|| For a different number of CNN layers and the operations involved in this study, computational complexity was evaluated, which is described as follows:(23) Pvsi=1-mxON+mxON=ON where ON represents the sum of iterations for performing the feature extraction and classification m 0,1 and then S.S.upd with respect to the fx as follows:(24) S.S.upd=argmaxipeidxifxPVsn=ON where ON represents the sum of iterations for S.S.upd, which provides the near optimum feature matches from the trained set. Once the features are extracted, they are then updated by the presented method. The output obtained from each CNN is denoted as x=CNN H ; the collective outputs obtained from the individual CNN are denoted as X=x1, x2,..., xL, where L denotes the ensemble's size, and the global output of the ensemble model is obtained by using weighted averaging of the output of the individual CNN. The weighted average of the output of the individual CNN is formulated as: G=j=1TwjsjTwith wj >= 0 (25) j=1Twj=1 where sj denotes the score and wj denotes the weight of the j-thj=1, 2, 3 model. The classifier diversity between any two CNN models is computed as:(26) CDi,j=TwNT where NT and Tw denote the total number of test samples and the difference of results caused by the samples. The diversity of the ensemble model is computed as the average of the classifier diversities, which can be formulated as:(27) ED=i=1Mj=1MCDi,jL, ij where ED denotes the diversity of the ensemble model, and CD denotes the classifier diversity. The classification output achieved from the weighted averaging of the individual CNN models possessed increased accuracy than the individual CNN models. Figure 4 presented the SMDTR-CNN-based land cover classification for identifying normal, DR and DME. Table 1 addresses the ensemble deep learning model below with their filters, filter size, stride, padding, and output image size. A CNN's fundamental building block is a convolutional layer and includes a series of filters, the parameters of which must be learned throughout the training process. The filters are often smaller in size than the real image. The pooling layer's function is to lower the spatial size of the representation in order to reduce the number of parameters and calculations in the network; it operates independently on each feature map (channels). Maximum pooling and average pooling are the two types of pooling layers. Max pooling is a procedure commonly used for the individual CNN convolution layers listed below when they are added to a model. Maxpooling minimizes the picture dimensionality by lowering the number of pixels in the preceding convolution layer's output. The rectified linear activation unit (ReLU) is one of the few milestones in the deep learning revolution. It is basic, but it is superior to the activation features of its predecessors such as sigmoid or tanh. 5. Results and Discussion The E-CNN performance was estimated with the accuracy, precision, recall, F-score, error rate, and computational time. 5.1. Accuracy Accuracy is defined as the ratio of the received input image inventive classification scheme by the assessed classification scheme, which can be formulated as:(28) A=T1+T2T1+T2+F1+F2 From the above equation, F1,F2 denote the false positive and false negative values, respectively; and T1,T2 denote the true positive and true negative values, respectively. Accuracy is the significant metric for calculating the performance of the system. 5.2. Precision Precision is computed by the ratio of excluding the significant classification result from the overall classification outcome. The meticulousness of the system can be measured using precision, which can be formulated as:(29) P=T2T1+F1 5.3. Recall The recall is defined as the ratio of excluding the same classification result to the recovered results. The recall is used for measuring the comprehensiveness of the system, which can be formulated as:(30) R=T1T1+F2 5.4. F-Score The F-score is computed by using the parameters of recall and precision by jointly assessing them. The results accuracy can be computed using F-score, which can be formulated as:(31) FS=2*P*RP+R 5.5. Computation Time Computation time is the amount of time needed to complete a computational operation. Computation time is calculated by calculating the time elapsed between the classification completion and computation. The system's efficacy is assessed in terms of computation time. It is appreciated whether the study obtained a greater accuracy with better precision of outcome in a shorter computing period. 5.6. Error Rate In Table 2, the results analysis of all models is furnished in the numerical form for better understanding. The error rate is defined as the ratio of errors in the sample to the overall samples. The error rate is used to determine the system's performance. A good system has a much lower error rate, which can be formulated as:(32) Error Rate=No of ErrorsNo of Samples As can be seen in Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10, we evaluated the proposed E-CNN to various state-of-the-art approaches such as SVM, KNN, enhanced CNN, and deep learning (DL). When analyzing performance, the optic disk (OD) is eliminated because it is a non-lesion area. The numerical findings suggest that our proposed E-CNN was superior. E-CNN had a mean accuracy of 99.84 percent, which was 4.38 percent greater than the benchmark. Although its effectiveness was equivalent to that of the Messidor database, it performed poorly in blood vessel segments. Furthermore, as shown in Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10, the accuracy, precision, recall, f-score, computational time, and error rate produced by E-CNN were much better than those acquired by other approaches. The difficulty of misclassification was exacerbated in the lesions DR and DME due to fewer samples; however, our proposed technique could still meet this obstacle. The quantitative class labels are also shown in Figure 5 to further illustrate the suggested strategy's efficiency. In the DR lesion segmentation challenge, one can see that the E-CNN was much more accurate and robust. We also performed an ablation experiment to prove the accuracy of the proposed E-CNN. The SVM is referred to as the baseline approach for convenience. The suggested strategy has been demonstrated to generate significant improvements over the baseline regarding four targets, as shown in Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10. The addition of preprocessing also improved the performance. The mean precision improved by 3.83 percent in comparison to the benchmark. Our proposed technology, in particular, can be simply integrated into other encoder-decoder networks, which we wish to conduct soon. Additionally, the proposed E-CNN achieved the greatest accuracy values in DR and DME diagnosis, demonstrating the efficacy of our proposed method. In this work, ensemble convolutional neural networks (ECNNs) were used to classify images of diabetic retinopathy. A recently developed meta-heuristic method, the Harris hawks optimization (HHO) algorithm, was used to optimize the ECNN hyperparameters. Then, the Harris hawks optimization technique was used to improve the feature extraction and classification processes to obtain the most significant features. Compared to previous systems, the deep learning model provides extremely satisfactory results regarding the specificity, precision, accuracy, and recall. 6. Conclusions All of the studies on the DR classification issue can be divided into two groups. The first is a binary DR diagnosis in which the individual possesses or does not. The problem with this technique is that after we realize a person has DR, we cannot tell how serious the disease is. Multi-class identification is the answer to this challenge. As previously mentioned, we classified DR into five classes or phases using multi-class classification. However, almost all of the associated studies, particularly in the early stages of DR, have been unable to appropriately define every one of the stages of DR. It is critical to identify the DR at a very early stage to treat the disease, as treating the disease at a much later date is challenging and can result in death. To our understanding, no other study has employed the IDRiR and Messidor databases to identify the milder phases of DR that we used in our study. Our approach outperformed the present advancements in detecting the mild stage. Furthermore, no one else has demonstrated the impact of a balanced dataset in previous research. The unbalanced dataset may have caused the classification accuracy to be skewed. The network can be trained on features correctly when samples in the classes are evenly distributed such as in a balanced dataset; however, in the case of asymmetrical distributions, the network performs for heavily tested classes. Furthermore, the present CNN architectures for DR identification do not consider the impact of varied hyperparameter tweaking (meta-learning) as well as its consequences. In the future, we plan to use some other deep-learning techniques for DR and DME disease classification. Recently, CNN-based methodology has been considered to learn features for classification. However, tuning non-trainable hyperparameters for such networks is manual, intuitive, and non-trivial. In the future, a technique based on DR and DME will be proposed to adjust the CNN architecture parameters. The convolution and pooling layer number, the kernel number, and the kernel size of the convolution layer are determined by the upcoming proposed technique. Therefore, the number of untrainable hyperparameters can be reduced. There are some challenges in adapting DR and DME to a CNN. Based on the dimension of the input image, the maximum and minimum sizes of the kernel must be specified for clear classification. Acknowledgments The authors are thankful to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R410), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Author Contributions Software, S.S.; Validation, M.S.; Formal analysis, S.R.; Investigation, S.I.; Writing--review & editing, J.-H.C.; Data curation, N.A.A.; Resources, A.E.; Writing--original draft, S.K.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 For this research work, datasets were taken from the kaggle repository site, available online at kaggle.com/datasets/mariaherrerot/idrid-dataset and (19 October 2022). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Retina images. (a) No DR and DME, (b) mild DR and DME, (c) moderate DR and DME, (d) severe DR and DME, and (e) non-PDR. Figure 2 System model. Figure 3 (a) OPTICS clustering algorithm. (b) Reachability distance. Figure 4 SMDTR-CNN-based land cover classification. Figure 5 Detection accuracy (a). IDRiR and (b). Messidor. Figure 6 Precision. (a) IDRiR and (b) Messidor. Figure 7 Recall. (a) IDRiR and (b) Messidor. Figure 8 F-Score. (a) IDRiR and (b) Messidor. Figure 9 Computation time. (a). IDRiR and (b) Messidor. Figure 10 Error Rate. (a) IDRiR and (b) Messidor. diagnostics-13-01001-t001_Table 1 Table 1 Layers of the convolutional neural network. Operational Layer Filters Filter Size Stride Padding Output Image Size Preprocessed image - - - - 224 x 224 x 3 Convolutional layer (2 times) Convolutional 64 3 x 3 x 3 1 x 1 1 x 1 224 x 224 x 64 ReLU - - - - 224 x 224 x 64 Pooling layer Max pooling 1 2 x 2 2 x 2 0 112 x 112 x 64 Convolutional layer (2 times) Convolutional 128 3 x 3 x 64 1 x 1 1 x 1 112 x 112 x 128 ReLU - - - - 112 x 112 x 128 Pooling layer Max pooling 1 2 x 2 2 x 2 0 56 x 56 x 128 Convolutional layer (4 times) Convolutional 256 3 x 3 x 128 1 x 1 1 x 1 56 x 56 x 256 ReLU - - - - 56 x 56 x 256 Pooling layer Max pooling 1 2 x 2 2 x 2 0 28 x 28 x 256 Convolutional layer (4 times) Convolutional 512 3 x 3 x 256 1 x 1 1 x 1 28 x 28 x 512 ReLU - - - - 28 x 28 x 512 Pooling layer Max pooling 1 2 x 2 2 x 2 0 14 x 14 x 512 Convolutional layer (4 times) Convolutional 512 3 x 3 x 512 1 x 1 1 x 1 14 x 14 x 512 ReLU - - - - 14 x 14 x 512 Pooling layer Max pooling 1 2 x 2 2 x 2 0 7 x 7 x 512 Inner product layer Fully connected - - - - 4096 ReLU - - - - 4096 diagnostics-13-01001-t002_Table 2 Table 2 Results analysis of Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10. Figures SVM KNN Improved CNN DL E-CNN Figure 5. Detection Accuracy. (a) IDRiR 61.3-69.96% 65-71% 79-83% 83-91% 94-98% Figure 5. Detection Accuracy. (b) Messidor 54-59% 65-71% 79-84% 84-92% 96-98% Figure 6. Precision. (a) IDRiR 60.5-69% 70-77.5% 80.12-87.5% 84-91.25% 92.5-97% Figure 6. Precision, (b) Messidor. 60.5-69% 70-77.5% 80.12-87.5% 84-91.25% 92.5-97% Figure 7. Recall. (a) IDRiR 60.5-67.5% 70.5-76.8% 80.25-88% 82.5-88.5% 91.2-97.5% Figure 7. Recall. (b) Messidor. 60.5-67.5% 70.5-76.8% 80.25-88% 82.5-88.5% 91.2-97.6% Figure 8. F-Score. (a) IDRiR 61.25-70% 70.69-79.5% 81-87.5% 85-91.2% 93-98.5% Figure 8. F-Score. (b) Messidor 61.25-70% 70.69-79.5% 81-87.5% 85-91.2% 93-98.5% Figure 9. Computation Time. (a) IDRiR (seconds) 11 14 10.5 8.8 2.6 Figure 9. Computation Time. (b) Messidor (seconds) 14 11 9.5 8.2 2.4 Figure 10. Error Rate. (a) IDRiR 0.985 0.774 0.865 0.923 0.15 Figure 10. Error Rate. 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PMC10000376 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050847 diagnostics-13-00847 Article Association of Kinesiophobia with Catastrophism and Sensitization-Associated Symptoms in COVID-19 Survivors with Post-COVID Pain Herrero-Montes Manuel 12 Fernandez-de-las-Penas Cesar 3* Ferrer-Pargada Diego 4 Izquierdo-Cuervo Sheila 4 Abascal-Bolado Beatriz 4 Valera-Calero Juan Antonio 56 Paras-Bravo Paula 12 Giannakopoulos Panteleimon Academic Editor 1 Departamento de Enfermeria, Universidad de Cantabria, 39005 Santander, Spain 2 Instituto de Investigacion Sanitaria Valdecilla (IDIVAL), Grupo de Investigacion en Enfermeria, 39005 Santander, Spain 3 Department of Physical Therapy, Occupational Therapy, Physical Medicine and Rehabilitation, Universidad Rey Juan Carlos, 28922 Madrid, Spain 4 Servicio de Neumologia, Hospital Universitario Marques de Valdecilla, 39008 Cantabria, Spain 5 Department of Radiology, Rehabilitation and Physiotherapy, Universidad Complutense de Madrid, 28040 Madrid, Spain 6 Grupo InPhysio, Instituto de Investigacion Sanitaria del Hospital Clinico San Carlos (IdISSC), 28040 Madrid, Spain * Correspondence: [email protected] 23 2 2023 3 2023 13 5 84728 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 ). Pain symptoms after the acute phase of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are present in almost 50% of COVID-19 survivors. The presence of kinesiophobia is a risk factor which may promote and perpetuate pain. This study aimed to investigate variables associated with the presence of kinesiophobia in a sample of previously hospitalized COVID-19 survivors exhibiting post-COVID pain. An observational study was conducted in three urban hospitals in Spain, including one hundred and forty-six COVID-19 survivors with post-COVID pain. Demographic (age, weight, height), clinical (intensity and duration of pain), psychological (anxiety level, depressive level, sleep quality), cognitive (catastrophizing), sensitization-associated symptoms, and health-related quality of life variables were collected in 146 survivors with post-COVID pain, as well as whether they exhibited kinesiophobia. Stepwise multiple linear regression models were conducted to identify variables significantly associated with kinesiophobia. Patients were assessed a mean of 18.8 (SD 1.8) months after hospital discharge. Kinesiophobia levels were positively associated with anxiety levels (r: 0.356, p < 0.001), depression levels (r: 0.306, p < 0.001), sleep quality (r: 0.288, p < 0.001), catastrophism (r: 0.578, p < 0.001), and sensitization-associated symptoms (r: 0.450, p < 0.001). The stepwise regression analysis revealed that 38.1% of kinesiophobia variance was explained by catastrophism (r2 adj: 0.329, B = 0.416, t = 8.377, p < 0.001) and sensitization-associated symptoms (r2 adj: 0.381, B = 0.130, t = 3.585, p < 0.001). Kinesiophobia levels were associated with catastrophism and sensitization-associated symptoms in previously hospitalized COVID-19 survivors with post-COVID pain. Identification of patients at a higher risk of developing a higher level of kinesiophobia, associated with post-COVID pain symptoms, could lead to better therapeutic strategies. COVID-19 pain post-COVID kinesiophobia sensitization catastrophism Comunidad de Madrid y la Union EuropeaRecursos REACT-UE del Programa Operativo de Madrid 2014-2020Next-Val 2021 de la Fundacion Instituto de Investigacion Marques de Valdecilla (IDIVAL)Novo Nordisk Foundation0067235 The project was supported by a grant of Comunidad de Madrid y la Union Europea, a traves del Fondo Europeo de Desarrollo Regional (FEDER), Recursos REACT-UE del Programa Operativo de Madrid 2014-2020, financiado como parte de la respuesta de la Union a la pandemia de COVID-19 (LONG-COVID-EXP-CM), by a grant from Next-Val 2021 de la Fundacion Instituto de Investigacion Marques de Valdecilla (IDIVAL), and by a grant from the Novo Nordisk Foundation 0067235. The sponsors had no role in the design, collection, management, analysis, or interpretation of the data, draft, review, or approval of the manuscript or its content. The authors were responsible for the decision to submit the manuscript for publication, and the sponsor did not participate in this decision. pmc1. Introduction Up to 60% of subjects who have survived to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the agent causing coronavirus disease, 2019 (COVID-19), can experience a plethora of symptoms after the acute phase of the infection, i.e., post-COVID or long COVID . Different meta-analyses have identified the presence of more than 50 post-COVID symptoms, e.g., fatigue, dyspnea, memory loss, brain fog, ageusia, anosmia, which can be present months , and up to one year , after infection. Pain is a post-COVID symptom experienced during the first year after the infection, with a pooled prevalence of 20% when investigated as a general symptom , or up to 60% when specifically assessed . Different studies have reported a heterogeneous location of post-COVID pain, with a prevalence of 20-25% for widespread distribution . The presence of widespread pain is associated with altered nociceptive processing, which has been recently identified in individuals with post-COVID pain . Chronic pain is a complex condition where biological, cognitive, behavioral, and social aspects contribute to its clinical presentation, as maladaptive psychological factors influence the pain experience. In fact, fear of movement, also known as kinesiophobia, is considered a relevant factor influencing the chronification, persistence, and deterioration of pain . There is evidence that higher levels of kinesiophobia are associated with greater pain intensity and related disability (strong evidence), and with lower quality of life (moderate evidence) . In addition, fear-avoidance behaviors are also associated with other cognitive factors, e.g., pain catastrophism and hypervigilance , which could result in a significant decrease in activity. Since physical activity is a protective behavior against chronic pain , and it is being advocated as an important strategy against post-COVID symptoms , identifying kinesiophobic behaviors in patients with chronic pain is highly recommended for screening subjects who may show reduced adherence to active treatments, due to an irrational and excessive fear of performing physical activity . Despite a high prevalence of kinesiophobia in musculoskeletal pain conditions , and the association between physical inactivity and a higher risk for severe COVID-19 , current evidence assessing whether COVID-19 survivors with post-COVID also exhibit these maladaptive cognitive behaviors is limited. Since the COVID-19 outbreak, associated factors have increased stress, anxiety, fear, and physical inactivity . Analyzing whether kinesiophobic behavior is present in COVID-19 survivors with post-COVID pain, as well as its association with sensitization-associated symptoms, catastrophism, and other features, will be of high interest. This study aimed to investigate the association between kinesiophobia levels and other pain-related mechanisms, e.g., sensitization-associated symptoms, catastrophism, and mood disturbances, in individuals with long-term post-COVID pain. Since being female has been found to be a risk factor associated with post-COVID pain , the study was conducted from a gender perspective. We hypothesized that those individuals with higher levels of anxiety and depression, and higher sensitization-associated symptoms, would exhibit higher levels of kinesiophobia. 2. Methods 2.1. Study Design An observational cross-sectional cohort study, following the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines , was conducted. This study was approved by the Local Institutional Ethics Committees (INDIVAL Cantabria 2020.416; HUIL/092-20, HUFA 20/126URJC0907202015920; HSO25112020). Patients were informed of the study and all provided their written informed consent prior to their inclusion. 2.2. Participants Individuals who had recovered from acute SARS-CoV-2 infection at three urban hospitals in Spain (Hospital Universitario Infanta Leonor, Hospital Universitario Fundacion Alcorcon, and Hospital Severo Ochoa), during the first wave of the COVID-19 pandemic, were screened for eligibility. The inclusion criteria were: (i) diagnosis of acute SARS-CoV-2 infection by real-time reverse transcription-polymerase chain reaction (RT-PCR) assay of nasopharyngeal, or oral swab sample, and the presence of consistent clinical and radiological findings at hospitalization; (ii) reporting "de novo" pain symptoms starting after the infection and lasting for at least three consecutive months; and (iii) absence of any potential underlying medical condition which could best explain the pain, e.g., arthritis. Although post-COVID pain exhibits mixed features of musculoskeletal and neuropathic pain, we defined post-COVID pain compatible with the diagnosis of chronic primary musculoskeletal pain as defined by the International Association for the Study of Pain (IASP) . Exclusion criteria included: (i) previous history of pain symptoms before the infection; and (ii) any other pre-existing medical comorbidity explaining pain symptoms. A structured questionnaire, including clinical data of their pain and several patient-reported outcome measures (PROMs), was used for data collection. Age, weight, height, and intensity (numerical pain rating scale, NPRS, 0-10) and duration of pain symptoms were collected. The PROMs evaluated sensitization-associated symptoms, neuropathic pain features, anxiety levels, depression levels, sleep quality, catastrophism, and health-related quality of life. In addition, kinesiophobia was used as the primary outcome of the study. 2.3. Kinesiophobia The main dependent outcome of this study was kinesiophobia (fear of movement), defined as an excessive, irrational, and debilitating fear to perform a physical movement, due to a feeling of vulnerability to a painful injury or reinjury . We used the 11-item Tampa Scale for Kinesiophobia (TSK-11) for evaluating the fear of movement . This specific PROM consists of 11 questions, where the patient chooses how much they agree or disagree with each item, 1 being "complete disagreement", and 4 "complete agreement" (total score from 11 to 44) . Although no clear cutoff score is considered for the TSK-11, we adapted the score proposed by Nicholas et al. for the TSK-17 in different chronic pain conditions . Accordingly, kinesiophobia was considered as minimal (TSK-11 score <= 22), low (TSK-11 from 23 to 28), moderate (TSK-11 from 29 to 35), or high (TSK-11 >= 36). 2.4. Sensitization-Associated Symptoms The Central Sensitization Inventory (CSI) was used to evaluate the presence of sensitization-associated symptoms. It includes 25 health-related symptoms assumed to represent aspects of sensitization, each based on 5-point Likert scale rating . The score ranges from 0 to 100, where > 40 points suggest the presence of sensitization-associated symptoms . The CSI has shown good psychometric properties for assessing sensitization-associated symptoms in patients with persistent pain . Previous studies using the CSI in individuals with post-COVID symptoms have reported conflicting results, since Goudman et al. found that 70% of individuals with long COVID exhibited a CSI score >= 40/100 points , whereas Fernandez-de-las-Penas et al. found that just 34% of patients with post-COVID pain exhibited a CSI score >= 40/100 points . 2.5. Psychological/Cognitive Variables The Hospital Anxiety and Depression Scale (HADS) was used to evaluate anxiety (HADS-A, 7-items) and depression (HADS-D, 7-items) levels . The total score of each subscale ranges from 0 to 21 points, where >=12 points on the HADS-A is indicative of anxiety symptoms, and >=10 points on the HADS-D indicates depressive symptoms . It has been observed that both scales of this questionnaire (HADS-A and HADS-D) exhibit good psychometric properties to be used for assessing psychological and emotional stress in COVID-19 survivors with long COVID . Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI) . This PROM consists of 19 self-rated questions (rated from 0 to 3) assessing different aspects of sleep (e.g., usual bedtime, wake-up time, number of hours slept, and time needed to fall asleep) during the previous month. The total score ranges from 0 to 21 points, where >=8.0 points are indicative of being a poor sleeper . Pain catastrophizing, i.e., an exaggerated negative mental state brought to bear during an actual or anticipated painful experience, was assessed with the Pain Catastrophizing Scale (PCS). This PROM includes 13-items (rated 0: never, to 4: always) evaluating rumination, magnification, and despair aspects in relation to the pain experience. The total score ranges from 0 to 52 points . 2.6. Health-Related Quality of Life The paper-based five-level version of EuroQol-5D-5L (EQ-5D-5L) was used to assess health-related quality of life . This questionnaire assesses mobility, self-care, daily activities, pain, and depression/anxiety dimensions from 1 (no problems) to 3 (severe problems) points. Responses were converted into a single index number between 0 and 1 where 0 corresponds to a health state judged to be equivalent to death and 1 corresponds to optimal health, by applying crosswalk index values for Spanish life . This questionnaire has exhibited good psychometric properties to be used as a PROM to assess health-related quality of life in hospitalized COVID-19 survivors with long-COVID . 2.7. Sample Size Determination Austin and Steyerberg suggested that linear regression models require only two subjects per variable SPV for adequate estimation of coefficients ; however, this simple calculation would lead to small sample sizes. Recently, Jenkins and Quintana-Ascencio proposed that an adequate sample size for regression models should include between 10 and 15 subjects per variable, and no more than five predictors within the model. Accordingly, for five potential predictor variables, a minimum of 75 participants would be required. A statistical calculation using the G*Power software v.3.1. (Heinrich-Heine-Universitat Dusseldorf, Dusseldorf, Germany) was also performed, setting a t-test for a linear multiple regression fixed model with a single regression coefficient. Setting two tails, with a standard effect size of 0.015, an alpha error of 0.05, a statistical power of 0.95, and two predictors, a sample size of 89 participants would result in an adequate statistical power (>0.95). To identify the highest number of variables that could be associated with kinesiophobia, and for avoiding potential type II errors, we significantly increased the estimated sample size. 2.8. Statistical Analysis Descriptive analyses (means and standard deviations (SD)) were used to describe the samples. The Kolmogorov-Smirnov test revealed that all quantitative data exhibited a normal distribution. Between-gender differences were initially assessed with independent Student t-tests. First, correlations between all variables and the dependent variable (TSK-11) were initially assessed by using Pearson correlation coefficients (r). The correlation analysis was used to identify multicollinearity and shared variance between the variables (r > 0.8). Second, statistically significant variables associated with TSK-11 were included into a stepwise multiple linear regression model (i.e., a hierarchical regression analysis), to identify those independent variables contributing significantly to the variance of the TSK-11, except the variables showing multicollinearity. The significance criterion of the F value for entry into the regression equation was set at p < 0.05. Changes in the adjusted R2 were reported after each step of the regression model, to determine the association of the additional variables. 3. Results From 200 patients with post-COVID symptoms screened for participation, finally, 146 (73%) fulfilled all criteria and agreed to participate. They were assessed a mean of 18.8 +- 1.8 months after hospital discharge. Fifty-four patients were excluded because their main post-COVID symptom was fatigue or dyspnea, but not pain. Table 1 details the demographic, clinical, sensory-related, quality of life, and psychological features of the total sample, and by gender. The males were older (p = 0.013), and had greater heights (p < 0.001) and weights (p = 0.002) than the females. Further, pain intensity (p = 0.016), sensitization-associated symptomatology (CSI, p < 0.001), sleep quality (PSQI, p < 0.001), anxiety levels (HADS-A, p = 0.02), and kinesiophobia (TSK-11, p = 0.044) were significantly higher in females when compared with males. Sixteen (10.9%) patients exhibited high kinesiophobia levels, 31 [21.3%) had moderate levels, 36 [24.6%) low to moderate levels, and the remaining 63 (43.2%) had minimal kinesiophobia levels. 3.1. Bivariate Correlation Analyses Table 2 summarizes the bivariate correlation analyses. Kinesiophobia levels (TSK-11) were positively associated with anxiety (r = 0.356, p < 0.001) and depression (r = 0.306, p < 0.001) levels, sleep quality (r = 0.288, p < 0.001), sensitization-associated symptoms (r = 0.450, p < 0.001), and catastrophism (r = 0.578, p < 0.001): higher levels of kinesiophobia were associated with higher anxiety/depression levels, worse quality of sleep, higher sensitization-associated symptomatology, and higher pain catastrophizing. Post-COVID symptom duration, pain intensity, and health-related quality of life did not show significant correlation with kinesiophobia levels. In addition, other associations were also found: (i) pain intensity was associated with female sex (p < 0.05), higher anxiety (p < 0.05), depression (p < 0.01) and sensitization-associated symptoms (p < 0.05); (ii) both anxiety and depression levels were associated with higher catastrophism (p < 0.01), sensitization-associated symptoms (p < 0.01), and poorer quality of life (p < 0.05 for HADS-A; p < 0.01 for HADS-D). Additionally, the associations of kinesiophobia levels with psychological variables, sleep quality, and sensitization-associated symptoms are illustrated in Figure 1, Figure 2 and Figure 3, respectively. 3.2. Multiple Regression Analyses The hierarchical regression analysis to determine the explained variance of the TSK-11 score is summarized in Table 3. Stepwise regression analyses revealed that the PCS score (contributing 32.9%), and CSI score (contributing an additional 5.2%) were significantly associated, and combined explained 38.1% of the variance for the TSK-11 score . 4. Discussion This study used regression analyses for investigating which factors may contribute to the variance of kinesiophobia levels in individuals exhibiting "de novo" post-COVID pain. Kinesiophobia was associated with catastrophism and sensitization-associated symptoms in previously hospitalized COVID-19 survivors with post-COVID pain. In addition, the overall prevalence of kinesiophobia in people with chronic pain ranges from 50% to 70% . We observed that almost 57% of COVID-19 survivors with post-COVID pain reported a potential kinesiophobic behavior. This finding highlights the importance of considering cognitive, in addition to biological, factors, to explain post-COVID pain. Pain processing and pain-related information in people with chronic pain could be related to how kinesiophobia is perceived. In fact, the association between kinesiophobia and pain catastrophism supports that the fear-avoidance model could be also applied to people with post-COVID pain. The fear-avoidance model proposes that a catastrophic misinterpretation of pain would lead to higher fear of movement and also hypervigilance, leading to potential maladaptive avoidance behavior resulting in reduced function, disuse, and increased symptoms . In fact, pain catastrophizing can impact the central nervous system by amplifying pain related signals, influencing descending pain inhibition, and by behavioral pathways, leading to an inability to control pain-related thoughts . These maladaptive behaviors could provoke a vicious cycle perpetuating pain. The fear-avoidance model is supported by a meta-analysis showing significant associations between cognitive behaviors, i.e., kinesiophobia, catastrophizing, and pain hypervigilance, with pain intensity and pain-related disability . Interestingly, kinesiophobia was not directly associated with the intensity of pain in our sample of individuals with post-COVID pain, in agreement with previous studies in chronic pain conditions of the lower extremities, such as knee or plantar heel pain , but contrary to observations in chronic postsurgical pain . Luque-Suarez et al. found moderate evidence supporting the association between kinesiophobia and pain intensity in musculoskeletal pain conditions. Today, we can not consider post-COVID pain as a musculoskeletal pain condition, which could explain the lack of association between kinesiophobia levels and the intensity of pain. Extensive evidence supports the idea that chronic pain is associated with sensitization . In fact, current data suggest that people with post-COVID pain exhibit altered pain processing (sensitization) . We observed that kinesiophobia levels were associated with sensitization-associated symptomatology, as assessed by the CSI. The fact that psychological and cognitive factors are associated with sensitization symptoms, agrees with previous studies in individuals with chronic pain . This finding agrees with those theories supporting the idea that sensitization-associated symptoms, based on the CSI, have a significant overlap with the cognitive/psychological construct . This can be explained since maladaptive cognitive behaviors, e.g., kinesiophobia and pain catastrophizing, are also considered central nervous system-derived symptoms . Current findings would support that both biological and cognitive mechanisms are important for patients with post-COVID pain. In fact, the presence of kinesiophobia levels and sensitization-associated symptoms would support that post-COVID pain could be considered as a nociplastic pain condition, a hypothesis which has been recently proposed . The results of this study have several clinical implications. Cognitive factors, such as pain catastrophizing and kinesiophobia, will require consideration in the management of individuals with post-COVID pain. Accordingly, clinicians managing people with post-COVID pain should listen to the patient's history for their thoughts, feelings, and behaviors that indicate either fear of movement, rumination, magnification of the threat value of pain, or a sense of helplessness. Treatments, including cognitive behavioral interventions, are recommended for the management of kinesiophobia caused by musculoskeletal pain; however, psychological interventions, such as coping strategies, are also potentially applicable . Kamonseki et al. reported that manual therapy strategies could also be equally effective as other cognitive interventions for managing cognitive maladaptative behaviors such as fear avoidance, kinesiophobia, and pain catastrophizing, again, in people with musculoskeletal pain conditions . Deciding when to address these cognitive behaviors in clinical practice remains unclear, and probably they should be managed at the same time as biological factors associated with long COVID. In fact, a recent meta-analysis concluded that the clinical effects of isolated interventions, such as pain neuroscience education, are smaller than expected, at least in the short-term . Since cognitive factors including kinesiophobia and pain catastrophizing are associated with sensitization-associated symptoms, clinicians should consider multimodal individually tailored treatments, combining pain neuroscience education with physical therapy and stress management. The presence of kinesiophobia in individuals with post-COVID pain could also limit the application of exercise programs due to this maladaptive behavior. Exercise is the therapeutic option most recommended for the management of individuals with long-COVID, including those with pain symptoms . Accordingly, the presence of higher levels of kinesiophobia could reduce the potential benefits of exercise, due to fear. In such a scenario, exercise should be adapted to each particular patient, and combined with cognitive behavior strategies, and applied based on a graded-exposure principle . Finally, these results should be considered according to their potential limitations. First, current data can be only applicable to previously hospitalized COVID-19 survivors with mild-to-moderate severity. In fact, critically ill COVID-19 survivors also develop post-COVID pain symptoms, and the role of maladaptive cognitive behaviors could be different . Second, we excluded patients with pre-existing pain symptoms before the infection, since this is a risk factor for developing post-COVID pain . We do not know if the presence of pain symptoms before the infection would lead to a facilitation of these maladaptive cognitive behaviors and sensitization features. Third, we collected different PROMs with potential overlapping between them. For instance, the CSI is also able to assess psychological/emotional constructs. Finally, due to the cross-sectional nature of the design, causal relationships between these maladaptive cognitive behaviors, post-COVID pain, and sensitization-associated symptoms cannot be determined. 5. Conclusions This study found that almost 60% of previously hospitalized COVID-19 survivors suffering from post-COVID pain exhibit kinesiophobia. In addition, kinesiophobia levels were associated with catastrophism and sensitization-associated symptoms. Identification of patients at a higher risk of developing higher levels of kinesiophobia associated with post-COVID pain symptoms could lead to therapeutic strategies targeting these cognitive behaviors able to promote and perpetuate pain. Acknowledgments The Center for Neuroplasticity and Pain (CNAP) is supported by the Danish National Research Foundation (DNRF121). Author Contributions All authors contributed to the study concept and design. M.H.-M. and C.F.-d.-l.-P. conducted the literature review and performed the statistical analysis. All authors recruited participants and collected data. P.P.-B. supervised the study. All authors contributed to interpretation of data. All authors contributed to drafting the paper. All authors revised the text for intellectual content and have read and approved the final version of 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 Review Board of INDIVAL Cantabria 2020.416, HUIL/092-20, HUFA 20/126,URJC0907202015920 and HSO25112020. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement All data derived from the study are reported in this manuscript. Conflicts of Interest No conflict of interest is declared by any of the authors. Figure 1 Association between kinesiophobia and psychological variables: anxiety (HADS-A), depression (HADS-D) and catastrophism. Red line represents the correlation coefficient whereas blue dot lines represent the confidence intervals of the coefficient. Figure 2 Association between kinesiophobia and sleep quality. Red line represents the correlation coefficient whereas blue dot lines represent the confidence intervals of the coefficient. Figure 3 Association between kinesiophobia and sensitization-associated symptoms (CSI). Red line represents the correlation coefficient whereas blue dot lines represent the confidence intervals of the coefficient. Figure 4 Scatter plot of the adjusted predicted score (r2 adjusted: 0.381) explaining kinesiophobia levels (TSK-11) score in previously hospitalized COVID-19 survivors exhibiting "de novo" post-COVID pain symptoms (n = 146). Note that some points can be overlapping. diagnostics-13-00847-t001_Table 1 Table 1 Baseline outcomes (mean +- SD) of the sample. Baseline Sample (n = 146) Males (n = 67) Females (n = 78) Between-Gender Differences Demographic Characteristics Age (years) 57.5 +- 11.8 60.0 +- 10.3 55.2 +- 12.5 4.8 (1.03; 8.65) p = 0.013 Height (m) 1.67 +- 0.09 1.73 +- 0.08 1.61 +- 0.06 0.11 (0.08; 0.13) p < 0.001 Weight (kg) 81.8 +- 17.1 86.5 +- 15.6 77.8 +- 17.4 8.7 (3.3; 14.2) p = 0.002 Clinical Characteristics Post-COVID symptoms (months) 18.8 +- 1.8 18.7 +- 2.0 18.9 +- 1.7 0.2 (-0.4; 0.8) p = 0.489 Pain-Related Features Pain intensity (0 to 10) 5.59 +- 1.72 5.23 +- 1.85 5.92 +- 1.54 0.69 (0.13; 1.25) p = 0.016 CSI (0 to 100) 33.91 +- 17.25 25.92 +- 14.33 41.06 +- 16.46 15.13 (10.02; 20.24) p < 0.001 Quality of Life EuroQol-5D-5L Questionnaire (0 to 100) 0.77 +- 0.20 0.79 +- 0.22 0.76 +- 0.17 0.02 (-0.03; 0.09) p = 0.427 Pittsburgh Sleeping Quality Index (0 to 21) 8.07 +- 4.28 6.86 +- 4.42 9.11 +- 3.91 2.24 (0.88; 3.61) p = 0.001 Psychological Characteristics HADS-A (0 to 21) 5.28 +- 4.21 4.44 +- 4.04 6.07 +- 4.22 1.62 (-0.26; 2.99) p = 0.020 HADS-D (0 to 21) 5.07 +- 4.29 4.38 +- 4.28 5.60 +- 4.27 1.21 (-0.19; 2.62) p = 0.091 Pain Catastrophizing Scale (0 to 52) 12.14 +- 11.95 10.27 +- 11.30 13.80 +- 12.40 3.52 (-0.43; 7.48) p = 0.080 Tampa Scale for Kinesiophobia (0 to 44) 24.11 +- 8.56 22.59 +- 8.74 25.47 +- 8.25 2.88 (0.07; 5.68) p = 0.044 Abbreviations: HADS, Hospital Anxiety and Depression Scale. diagnostics-13-00847-t002_Table 2 Table 2 Pearson product-moment correlation matrix between sociodemographic, psychological, neuro-physiological, and clinical characteristics. 1 2 3 4 5 6 7 8 9 10 11 12 1. Age 2. Gender -0.206 * 3. Height 0.003 -0.595 ** 4. Weight -0.090 -0.256 ** 0.509 ** 5. Post-COVID symptoms -0.122 0.058 0.010 0.127 6. Pain intensity -0.047 0.200 * -0.191 * -0.109 0.016 7. HADS-A 0.028 0.194 * -0.158 -0.090 -0.271 ** 0.175 * 8. HADS-D 0.078 0.141 -0.104 -0.091 -0.136 0.225 ** 0.750 ** 9. PSQI 0.121 0.262 ** -0.213 ** -0.102 -0.189 * 0.137 0.316 ** 0.354 ** 10. CSI -0.076 0.440 ** -0.285 ** -0.121 -0.158 0.190 * 0.551 ** 0.446 ** 0.390 ** 11. PCS 0.132 0.147 -0.128 -0.083 -0.343 ** 0.045 0.492 ** 0.483 ** 0.282 ** 0.402 ** 12. TSK-11 0.000 0.168 * -0.065 0.034 -0.092 0.150 0.356 ** 0.306 ** 0.288 ** 0.450 ** 0.578 ** 13. EuroQol-5D-5L -0.039 -0.066 0.004 0.051 0.081 -0.006 -0.143 -0.174 * -0.301 ** -0.199 * -0.210 * -0.132 Abbreviations: CSI, Central Sensitization Inventory; HADS, Hospital Anxiety and Depression Scale. * p < 0.05; ** p < 0.01. diagnostics-13-00847-t003_Table 3 Table 3 Summary of the stepwise regression analyses to determine predictors of TSK-11. 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PMC10000377 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050708 cells-12-00708 Review Role of RUNX3 in Restriction Point Regulation Lee Jung-Won 1 Lee You-Soub 1 Kim Min-Kyu 1 Chi Xin-Zi 1 Kim Dohun 2 Bae Suk-Chul 1* Hengst Ludger Academic Editor 1 Department of Biochemistry, College of Medicine and Institute for Tumour Research, Chungbuk National University, Cheongju 28644, Republic of Korea 2 Department of Thoracic and Cardiovascular Surgery, College of Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea * Correspondence: [email protected] 23 2 2023 3 2023 12 5 70826 1 2023 17 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 ). A cell cycle is a series of events that takes place in a cell as it grows and divides. At the G1 phase of cell cycle, cells monitor their cumulative exposure to specific signals and make the critical decision to pass through the restriction (R)-point. The R-point decision-making machinery is fundamental to normal differentiation, apoptosis, and G1-S transition. Deregulation of this machinery is markedly associated with tumorigenesis. Therefore, identification of the molecular mechanisms that govern the R-point decision is one of the fundamental issues in tumor biology. RUNX3 is one of the genes frequently inactivated in tumors by epigenetic alterations. In particular, RUNX3 is downregulated in most K-RAS-activated human and mouse lung adenocarcinomas (ADCs). Targeted inactivation of Runx3 in the mouse lung induces adenomas (ADs), and markedly shortens the latency of ADC formation induced by oncogenic K-Ras. RUNX3 participates in the transient formation of R-point-associated activator (RPA-RX3-AC) complexes, which measure the duration of RAS signals and thereby protect cells against oncogenic RAS. This review focuses on the molecular mechanism by which the R-point participates in oncogenic surveillance. RUNX3 K-RAS R-point cell cycle National Research Foundation (NRF) of KoreaNRF-2014R1A3A2030690 MRC-2020R1A5A2017476 Basic Science Research ProgramNRF-2021R1I1A1A01060610 NRF-2017R1A6A3A11028050 NRF-2020R1F1A1060630 S.-C.B. is supported by a Creative Research Grant (NRF-2014R1A3A2030690) and Medical Research Center (MRC-2020R1A5A2017476) through the National Research Foundation (NRF) of Korea. J.-W.L. is supported by Basic Science Research Program grant (NRF-2021R1I1A1A01060610) of Korea. M.-K.K. is supported by Basic Science Research Program grant (NRF-2017R1A6A3A11028050) of Korea. D.-H.K. is supported by Basic Science Research Program grant (NRF-2020R1F1A1060630). pmc1. The Restriction Point The major events that regulate cell proliferation occur during the G1 phase of the cell cycle. The growth of normal cells in culture is regulated by complex interactions involving growth factors, cell density, and cell attachments to substrates. Growth factors are necessary to initiate and maintain the transition through the G1 phase, leading to the S phase. Reductions in growth factor levels in cells, such as by the removal of serum, prevent the onset of the S phase . However, once the cells have moved through a certain G1 decision-making period, the removal of serum no longer affects their progress through the cell cycle, with these cells proceeding through the remainder of the G1 phase and onward through S, G2, and M phases. The point in G1 at which commitment occurs and the cell no longer requires growth factors to complete the cell cycle has been termed the restriction (R)-point . Once beyond the R-point, cells are committed to DNA synthesis and are independent of extracellular growth factors during the remainder of the cell cycle . R-point transition is regulated by R-point-associated proteins (R-proteins), including c-Myc, cyclins, CDKs, p21, p27, E2F, and pRB , with pRB serving as the primary molecular regulator . One of the most important breakthroughs in the understanding of cell cycle regulation was the finding that mitogenic stimulation was connected to the cell cycle machinery. The expression of cyclin D and its assembly with CDK4 and CDK6 into active kinase complexes are regulated by growth factors , indicating that cyclin D is a growth factor sensor. In turn, the ability of cyclin D-dependent kinases to trigger the phosphorylation of pRB during the late-G1 phase of the cell cycle makes inactivation of the growth-suppressive function of pRB a mitogen-dependent step. pRB participates in controlling the G1/S-phase transition. Cyclin E complexes with CDK2 downstream of the cyclin D-CDK4/6 complex, with the cyclin E-CDK2 complex further phosphorylating pRB. This shift from cyclin D-CDK4/6 to cyclin E-CDK2 accounts for the loss of dependency on growth factors, indicating that the R-point lies between cyclin D-CDK4/6 and cyclin E-CDK2 . The mammalian G1/S cell cycle phase transition network is a highly nonlinear network that produces seemingly paradoxical results . Numerous feedback loops lead to situations in which downstream events lie upstream of themselves. For example, pRB2/p130 and p27 are both involved in a negative feedback regulatory loop with cyclin E . Moreover, although c-Myc expression is downstream from p21, CDKs, and E2F , c-Myc is also an upstream regulator of p21 and CDKs . Similarly, the finding that cyclin E is transactivated by E2F-1 suggests that cyclin E is located downstream from pRB and E2F-1. However, cyclin E inactivates pRB and releases E2F. These positive loops ensure the irreversibility of commitments. Once expressed, cyclin E becomes independent of downstream growth-factor-dependent cyclin D1. The phosphorylation of pRB abrogates growth factor dependency, enabling the cells to pass through the R-point and commit to completing the remaining phases of the growth cycle . The nonlinear networks include c-Myc, cyclins, p21, CDKs and E2F, which play key roles in R-point regulation. Therefore, the nonlinear networks producing seemingly paradoxical results appears to be associated with R-point, which regulates cell fate. 2. Regulation of the Timing of the R-Point The R-point lies between cyclin D-CDK4/6 and cyclin E-CDK2, suggesting that cyclin E-CDK2 is responsible for pushing the cells from the R-point through to the remainder of the G1 phase. Therefore, cyclin E-CDK2 complexes should form only after the cell is committed to proliferation at the R-point. Although cyclin D expression is induced earlier than cyclin E expression, the times of their expression were found to overlap considerably , suggesting that the expression of cyclin E does not solely determine the time of exit from the R-point. Cyclin E-CDK2, however, is activated only after R-point commitment to proliferation. p21WAF1/CIP1/Kip (hereafter p21), originally identified as an inhibitor of CDKs , is encoded by an immediate-early gene, with p21 mRNA peaking approximately 2 h after stimulation with serum or growth factor . However, the biological importance of the mitogen-stimulated immediate early induction of p21 was not understood at that time. Subsequent studies revealed that p21 is not a simple CDK inhibitor; rather, members of the p21 family were found to activate cyclin D-CDK4/6 by promoting the association of its component proteins, while inhibiting cyclin E-CDK2 . Recently, it was shown that only the tyrosine-phosphorylated p21 family activates cyclin D-CDK4/6, and this tyrosine phosphorylation occurs in response to mitogenic signaling . Therefore, p21, induced early after mitogenic stimulation, promotes cell entry into the R-point at the early-/mid-G1 phase by activating cyclin D-CDK4/6, but prevents further progression through the R-point by inhibiting cyclin E-CDK2. That is, cells remain at the R-point while p21 is expressed, but exit from the R-point when p21 expression is attenuated, indicating that the p21 gene is involved in R-point regulation. Understanding the molecular mechanisms underlying the mitogen-stimulated immediate early induction of p21 should enable greater understanding of the mechanisms underlying R-point regulation. 3. Role of RUNX3 in p21 Induction and R-Point Regulation RUNX3, which plays pivotal roles in lineage determination and functions as a tumor suppressor, is frequently inactivated in various types of human cancers, including stomach and lung cancers . Conditional deletion of Runx3 from mouse lungs results in the development of lung adenomas (ADs), with these pre-invasive lesions progressing to adenocarcinomas (ADCs) following the additional introduction of heterozygous oncogenic K-Ras mutations . Deletion of Runx3 from mouse lung epithelial cells results in the development of lung Ads, and Runx3-/- mouse embryonic fibroblasts (MEFs) develop into tumors without oncogenic mutations in nude mice . Although these results indicated that cells acquire tumorigenic activity following the deletion of Runx3, the mechanism involved remained unclear. An important clue was provided by an analysis of the minimum serum exposure time required for Runx3-/- and Runx3+/+ MEFs to progress to S phase. Runx3-/- MEFs required only 1-2 hours, whereas Runx3+/+ MEFs required at least 4 hours . The short exposure time required by Runx3-/- MEFs was similar to that required by Rb-/- MEFs . Notably, Runx3 deletion abolished the immediate-early induction of p21 , suggesting that Runx3 is essential for R-point regulation in MEFs, and that p21, a key regulator of the R-point, is a target of Runx3. These findings were supported by results showing that the expression of Runx3 in Runx3-/- MEFs restored the R-point and the immediate-early induction of p21, while abolishing cell tumorigenicity . In addition, the R122C mutation (substitution of arginine 122 to cysteine) in RUNX3, which was identified from human gastric cancer , disrupts the R-point . Thus, the tumorigenicity acquired by Runx3 deletion was associated with a deregulation of the R-point. 4. Mechanism for the Induction of R-Point-Associated Genes at the R-Point Cell commitment at the R-point involves the regulation of several hundred R-point-associated genes, which are induced by exposure to serum for 1-2 h and subsequently suppressed . The p14-ARF (hereafter ARF) and p21 genes are included among the R-point-associated genes , but their mechanism of induction early after mitogenic stimulation was originally undetermined. The induction of expression of silent genes requires the target sites within their regulatory regions to be bound de novo by transcription factors. Transcription factors that bind to condensed chromatin independently of other factors, modulate chromatin accessibility, and regulate gene transcription are known as pioneer factors . To mediate these activities, pioneer factors require a complex network of other proteins, including coactivators, corepressors, histone-modifying complexes, chromatin-remodeling complexes, mediator complexes, and the basal transcription machinery. For example, proteins of the Trithorax group (TrxG) modify histones to activate transcription. TrxG proteins can be classified into two categories: histone modifiers and nucleosome remodelers . TrxG histone modifiers include members of the mixed-lineage leukemia (MLL) family, which methylate H3 at lysine 4 (H3K4-me3, -me2, and -me1), enhancing transcriptional activation. In contrast, TrxG nucleosome remodelers include the SWI-SNF complex, which facilitates binding of transcription factors and the basal transcription machinery. Mediator complexes transduce signals from the transcription activators bound to enhancer regions in the transcription machinery, which is assembled at promoters, as the preinitiation complex, to control the initiation of transcription . Members of the bromodomain (BRD) family of proteins (BRDs) are components of the mediator complex. BRDs are integral to transcription through their interactions with mediator coactivator complexes, which are required for the transcription of various genes . BRDs possess two bromodomains, BD1 and BD2, which interact with acetylated histones and acetylated transcription factors. Runx3 plays a key role in recruiting these chromatin modulators to activate signal-dependent R-point-associated gene expression at the correct target loci at the right time. Immediately after mitogenic stimulation, Runx3 binds to its target chromatin loci and recruits the pRB-E2F complex and p300 acetyltransferase . The interactions are promoted by RAS-activated MEK1 . Runx3 and histones are acetylated by p300 acetyltransferase, with BRD2 subsequently interacting with acetylated Runx3 through its BD1 domain, and with acetylated histone H4 through its BD2 domain . Therefore, RUNX3 guides the pRB-E2F complex and p300 to target loci, with BRD2 binding both acetylated RUNX3 and acetylated histones through its two bromodomains prior to the R-point . Subsequently, the C-terminal region of BRD2 interacts with the SWI/SNF chromatin-remodeling complex, MLLs, which act as activated histone modifiers, and TFIID complexes, representing basal transcription machinery . Thus, at the R-point, Runx3 forms a large complex, called the R-point-associated RUNX3-containing activator complex (Rpa-RX3-AC), at target chromatin loci . This Rpa-RX3-AC complex subsequently opens the chromatin structures of the target loci by replacing the inhibitory histone H3K27-me3 with the activating histone H3K4-me3. Runx3 is an enhancer binding protein, and TFIID is a promoter-binding complex. Therefore, the enhancer interacts with the promoter through the Rpa-RX3-AC complex during the R-point at the target loci, inducing the expression of R-point-associated genes . This Rpa-RX3-AC complex is maintained, while the RAS-MEK pathway is activated . The activities of RUNX3, including its association with condensed chromatin, its modulation of chromatin accessibility, and its activation of gene expression, fulfill the characteristics of a pioneer factor, making RUNX3 a pioneer factor of the R-point. 5. Mechanism for the Suppression of R-Point-Associated Genes after the R-Point Hypo-phosphorylated pRB is a component of the Rpa-RX3-AC complex that forms 1-2 h after mitogenic stimulation and contributes to R-point commitment . Soon after, CDK4 is recruited to the target locus by interacting with RUNX3. p21, which is induced by the Rpa-RX3-AC complex, facilitates CDK4--cyclin D1 interactions. Thus, pRB and E2F1, along with CDK4, cyclin D1, and p21, which play key roles in cell cycle regulation, are recruited to the R-point-associated target loci . At these loci, pRB is phosphorylated at Ser-795 by cyclin D1-CDK4/6. Subsequently, after the R-point, 4 h after mitogenic stimulation, the pRB-E2F1 complex is released from the Rpa-RX3-AC complex, and the expression of R-point-associated target genes is suppressed . Activation of CDK4 by the cyclin D1-CDK4 interaction triggers the suppression of previously activated R-point-associated target genes, including p21 and ARF. Proteins in the polycomb group (PcG) modify histones to suppress gene transcription. There are two kinds of PcG complexes, called polycomb repressor complexes 1 and 2 (PRC1 and PRC2). Both complexes consist of multiple proteins, with PRC1 containing BMI1 and ring finger protein 1 (RING1) or 2 (RNF2) , and PRC2 containing EED and an enhancer of zeste homologs (EZH1 and EZH2), which trimethylate H3 at lysine 27 (H3K27-me3), a characteristic of inactive chromatin . Cyclin D1, induced soon after mitogenic stimulation, forms a complex with HDAC4 and PRC1 . Therefore, when cyclin D1 binds to CDK4, HDAC4 and PRC1 are also recruited to the Rpa-RX3-AC complex. Because p300-mediated RUNX3 acetylation and histone acetylation are effectively abolished by HDAC4 , HDAC4 may play a key role in the deacetylation of RUNX3 and histones, causing the release of BRD2 and other BRD2-associated proteins. Inactivation of chromatin is associated with HDAC-mediated histone deacetylation and H2A ubiquitination at Lys-119, mediated by RNF2, a component of PRC1 . Consistently, H4K12 acetylation was reduced, and H2A-K119-Ub was enriched at the p21 and ARF loci 4-8 h after stimulation . These results demonstrate that cyclin D1, HDAC4, and PRC1 bind to the Rpa-RX3-AC complex through interactions with CDK4. These interactions are facilitated by Rpa-RX3-AC-induced p21, which contributes to the inactivation of chromatin at target loci by deacetylating H4K12 and ubiquitinating H2A . At 4-8 h after mitogen stimulation, RUNX3 and BRD2 existed in separate complexes: RUNX3 formed a complex with Cyclin D1, HDAC4, and PRC2, which remained bound to target chromatin loci, whereas BRD2 formed the BRD2-PRC1 complex, which was released from the loci . Moreover, H3K27-me3 was enriched at these loci. EZH2 is a component of PRC2 that mediates the modification of the inhibitory histone H3K27-me3, suggesting that PRC2, associated with RUNX3, may play a key role in the inactivation of chromatin loci. Because the RUNX3-Cyclin D1-HDAC4-PRC2 complex inactivates chromatin, the complex was named as the R-point-associated RUNX3-containing repressor complex (Rpa-RX3-RE) . 6. Minimally Sufficient Conditions for the Development of Lung Cancer Many studies have reported that K-RAS mutations, the genetic alterations most frequently detected in various cancers, are an early event responsible for the development of lung ADs . By contrast, the ARF-p53 pathway has been found to effectively defend cells against aberrant oncogene activation , with p53 mutations being a hallmark of cancer and a prevalent feature of human cancers . Therefore, the development of K-RAS-activated cancer might be accompanied by the inactivation of the ARF-p53 pathway. These findings, however, are contradicted by results in human cancers. Evaluation of the key genetic and epigenetic alterations that are responsible for clonal expansion following each step of colon tumorigenesis has shown that colon ADs are initiated by the inactivation of Adenomatous polyposis coli (APC) . Moreover, K-Ras is activated after AD development, with the loss of p53 occurring at an even later stage. Although the p53 pathway can defend against colon ADCs, it remains unclear as to whether this pathway can defend against K-Ras-activated colon ADs, and, if so, whether the p53 pathway can defend against high-grade, but not low-grade, cancers. These questions have been partly answered in lung cancer. The progression of lung ADCs from adenomatous growth to carcinomas was found to be similar to the multistep tumorigenesis pathway in colon cancer . Although the activation of K-Ras and inactivation of p53 are frequently detected in lung ADCs, the order of these molecular events has not been clearly established in human lung cancer patients. Rather, the relationship between K-Ras activation and p53 inactivation was analyzed by restoring p53 expression in K-Ras-activated and p53-inactivated mouse lung tumors. p53 restoration eliminated only Kras-activated lung ADCs, leaving lung ADs intact in these mice models . These results suggested that p53 is inactivated during late-stage AD or early-stage ADC, later than K-Ras activation; this is similar to findings in colon cancer . Previous studies have speculated that this was due to inherent limits in the capacity of the Arf-p53 pathway to respond to a persistent low level of oncogenic K-Ras activity . However, another possibility remained, that the failure of eliminating lung AD by p53 restoration may be due to disruption of a hidden molecular mechanism responsible for sensing the aberrant persistence of oncogenic signals. The initial step of colon AD development is the inactivation of APC, not the activation of K-Ras. Similarly, RUNX3 is frequently inactivated in human atypical adenomatous hyperplasia (AAH) and bronchioloalveolar carcinoma (BAC), which correspond to mouse lung ADs, and inactivation of Runx3 induces lung ADs in mice . A lone, heterozygous oncogenic K-Ras mutation in a large number of cells can also lead to the development of lung ADs, although only a very small number of these cells in a specific cellular context are transformed by oncogenic K-Ras , indicating that certain spontaneously occurring rare molecular events are involved in the development of K-Ras-activated lung cancer. These rare molecular events may occur in only a small percentage of K-Ras-activated cells. Thus, the likelihood of these hidden molecular events can be reduced by reducing the number of K-Ras-activated cells. Indeed, these same K-Ras mutations, with or without p53 inactivation, in an extremely small number of cells, failed to induce any pathologic lesions for up to 1 year . In contrast, when Runx3 was inactivated, and K-Ras was activated by the same targeting method, lung ADCs and other tumors were rapidly induced and caused lethality in all the targeted mice within 3 months . Therefore, under physiological conditions, in which oncogenic mutations are very rare, K-Ras activation alone is not sufficient, whereas its combination with Runx3 inactivation is sufficient, for lung cancer development. In addition, evaluation of a urethane-induced mouse lung tumor model that recapitulates the features of K-RAS-driven human lung tumors showed that Runx3 was inactivated in both ADs and ADCs, whereas K-Ras was activated only in ADCs . Mutations in p53 were an even later event than K-Ras activation . Therefore, the order of the molecular events for the development of mouse lung AD/ADC was likely Runx3 inactivation - activation of K-Ras - loss of p53 . The universal process of malignant transformation involves both genetic damage and oncogenic signaling. These two stresses are signaled to p53 through different pathways. Based on this, p53 plays two important roles in cells: "defense against genome instability", which consists of sensing and reacting to DNA damage through ATM/ATR kinases, and "defense against oncogene activation", which consists of responding to oncogenic signaling through the p53-stabilizing protein ARF . Recent genetic evidence in mice indicates that the ARF-dependent activation of p53 is critical for early-stage p53-mediated tumor suppression. In contrast, ATM/ATR-dependent activation of p53 protects late-stage tumors . Therefore, p53 mutations at relatively late stages of colon and lung tumorigenesis may be associated with the disruption of ATM/ATR-dependent p53 activation . Nevertheless, K-RAS-activated AD cells have been found to proliferate in the presence of wild-type ARF and p53. Because heterozygous oncogenic K-Ras mutations alone in a small number of cells did not induce lung AD , the process of AD development may require the inactivation of the ARF-p53 pathway. The mechanism underlying the inactivation of the ARF-p53 pathway in ADs was unclear. However, Runx3 is inactivated in most K-Ras-activated mouse and human lung ADs , with Runx3 inactivation abrogating the R-point program, which plays a key role in ARF induction in response to oncogenic K-RAS . Thus, Runx3 inactivation may inactivate the ARF-p53 pathway in lung ADs, thus providing a mechanism underlying the proliferation of K-Ras-activated lung AD cells in the absence of mutated p53 . 7. Mechanism by Which Cells Distinguish Oncogenic from Normal RAS and Defend against Tumorigenesis Mitogenic signaling activates the GTPase activity of RAS, which decreases to the basal level soon after the signal is transduced to downstream kinase pathways. Oncogenic RAS is a constitutively active form, with GTPase activity not being downregulated. Therefore, heterozygous RAS mutations yield cells with 50% of the maximum level of RAS activity . The ability of cells to sense the duration of 50% rather than maximal RAS GTPase activity may confer protection against oncogenic RAS-induced abnormal proliferation. The ability of cells to recognize the aberrant persistence of RAS activity, however, was unclear. For example, oncogenic K-Ras expressed at the endogenous level did not activate the ARF-p53 pathway in mouse lungs . Based on these results, it had been considered that the ARF-p53 pathway does not respond to the aberrant persistence of RAS activity, although the pathway responds to only abnormally high levels of RAS activity . Mammals, however, were later found to have evolved an effective defense mechanism against a persistent low level of RAS activity . When K-RAS is activated by normal mitogenic stimulation, RUNX3 forms Rpa-RX3-AC complexes in a MAPK activity-dependent manner; these complexes transiently induce ARF, which in turn transiently stabilizes p53. Soon after the mitogenic surge, MAPK activity is reduced, converting Rpa-RX3-AC complexes to Rpa-RX3-RE complexes and repressing ARF expression . Mitogen-stimulated transient activation of the ARF-p53 pathway does not affect the cell cycle because it occurs only 1-3 hours after mitogenic simulation, and is then silenced before the G1/S checkpoint. In contrast, when K-RAS is constitutively activated, the Rpa-RX3-AC complex is maintained, and the expression of ARF and p53 is maintained until the G1/S checkpoint, leading to cell death . These results indicate that cells can effectively defend against an endogenous level of RAS activity, and that the Rpa-RX3-AC complex functions as a sensor and as a decision maker regarding the abnormal persistence of RAS activity . H460 human lung cancer cells were used to determine whether the Rpa-RX3-AC complex-driven activation of the ARF-p53 pathway was sufficient to defend against oncogenic K-RAS-induced lung tumorigenesis. In these cells, K-RAS was heterozyously mutated but not amplified, and RUNX3 was inactivated by hyper-methylation. Despite these cells having wild-type ARF and p53, Rpa-RX3-AC complexes were not formed, and the ARF-p53 pathway was not activated. In contrast, exogenous expression of RUNX3 led to the formation of Rpa-RX3-AC complexes, which activated ARF expression and stabilized p53, thereby inducing cell apoptosis . Expression of mutant RUNX3, which is unable to form Rpa-RX3-AC complexes, failed to activate ARF expression . Therefore, failure of ARF-p53 pathway activation in H460 cells was due, not to the absence of a mechanism for sensing low endogenous levels of oncogenic K-Ras activity, but to the disruption of the R-point by RUNX3 inactivation. These findings indicate that cells can recognize the aberrant persistence of RAS activity through the R-point program and kill these cells by activating the ARF-p53 pathway. 8. Importance of RUNX3 in Lung Tumorigenesis Although several important regulators of cell differentiation govern lung development, deregulation of the differentiation program was generally insufficient to induce AD. Runx3 is inactivated in nearly all the human and mouse lung ADs and, to date, Runx3 is the only gene whose inactivation has been reported to induce lung AD . Cancer development is considered to be a biological process that resembles Darwinian evolution: random mutations create genetic variability in a cell population, and the force of selection favors the outgrowth of individual mutant cells that happen to be endowed with advantageous traits. Based on a combination of Darwinian theory and the concept of multistep tumor progression, tumorigenesis is now understood as a succession of clonal expansions . Great numbers of cells are required to select cells endowed with advantageous traits. The random inactivation of Runx3 in normal cells results in a deregulation of the differentiation program and disruption of the R-point program . Deregulation of the differentiation program is likely responsible for the development of AD, although it is not sufficient, whereas disruption of the R-point program likely results in the abrogation of the ARF-p53 pathway-mediated oncogene surveillance mechanism, enabling the subsequent selection of K-RAS-mutated cells. Although K-RAS-induced lung cancer development can proceed via multiple pathways, the high frequency of RUNX3 inactivation in K-RAS-induced mouse and human lung ADCs suggests that a major pathway involves R-point disruption by RUNX3 inactivation prior to K-RAS activation. To date, RUNX3 is the only gene whose inactivation has been shown to be sufficient for both the induction of AD and abrogation of the R-point. These steps may result from multiple molecular events (i.e., one involving each pathway) or a single molecular event, such as RUNX3 inactivation. Obviously, the probability of deregulation is much higher for events involving a single gene than multiple genes, explaining the importance of RUNX3 in lung tumorigenesis. 9. Tumor Suppressor Genes vs. Oncogenes Tumor suppressor genes are defined as genes that "help control cell growth," indicating that tumor suppressors act broadly to inhibit diverse aspects of both normal and neoplastic physiology. By contrast, oncogenes are genes activated by mutations or overexpression of genes that act dominantly to induce tumorigenesis. These terms, however, can overlap, as some proteins with various functions affecting a spectrum of cellular outcomes can enhance and/or suppress tumor pathogenesis. Although RUNX3 generally acts as a tumor suppressor, RUNX3 expression can be enhanced during the course of progression of some cancers, with this gene playing a tumor-promoting or oncogenic role. For example, the acquired expression of RUNX3 in head and neck carcinoma correlates with poor histologic differentiation, invasion, and metastasis . High RUNX3 expression has also been observed in ovarian cancer, basal cell carcinoma, and skin cancers . Moreover, Runx3 has been shown to inhibit the early-stage growth of pancreatic cancers but facilitates their metastatic progression at early-stage . The ability of RUNX3 to exhibit both tumor-suppressing and tumor-promoting activities has been associated with the R-point, a decision-making program for cell proliferation, differentiation, senescence, and apoptosis. The R-point could be deregulated by either the abnormally high expression or inactivation of RUNX3. For example, the tumor suppressors p21 and ARF are induced at the R-point and then subsequently suppressed, with RUNX3 playing key roles in both programs . If RUNX3 is inactivated, p21 and ARF are not induced, even when an oncogene is activated due to the failure of Rpa-RX3-AC complex formation. In this context, RUNX3 functions as a tumor suppressor. If, however, RUNX3 is overexpressed, and Rpa-RX3-AC complex formation is not possible, then RUNX3 may preferentially form Rpa-RX3-RE complexes, suppressing the expression of p21 and ARF. Under these conditions, RUNX3 functions as an oncogene. Although RUNX3 is the only gene to date that has been shown to act as a pioneer factor of the R-point, many pioneer factors of the R-point are likely present in various types of cells. For example, RUNX1 and RUNX2, which are master regulators of hematopoiesis and osteogenesis, respectively , are involved in R-point regulation . Other master regulators might also play roles in R-point regulation, since development is a sequential process with decisions made at the R-point. Many key R-point regulators may also exhibit ambipotent and context-dependent effects on tumorigenesis. Therefore, we propose designating RUNX3 and similar acting proteins as "decision makers," with their activities as tumor suppressors or oncogenes being dependent on the intactness of the decision-making machinery in cells. 10. Summary A tumor is defined as an abnormal mass of tissue that forms when cells divide more than they should or do not die when they should. The determination of whether a cell divides or dies is made at the R-point. In theory, cells that make a correct decision at the R-point and correctly execute this decision cannot develop into tumors. Deregulation of the R-point decision-making machinery is involved in the formation of most, if not all, types of tumors , suggesting the importance of the R-point in tumor development. Understanding the molecular mechanisms that underlie R-point commitment should provide important insights into how normal cells become tumorigenic. This review summarizes the method by which the R-point distinguishes normal from oncogenic RAS and determines pathways for cell survival or death. Several fundamental questions underlying cancer development remain to be resolved, including the mechanisms underlying tumor initiation and its rapid recurrence after treatment with anticancer drugs. If oncogene activation is solely responsible for tumor development, then inhibition of the activated oncogene would be able to cure that cancer without the likelihood of recurrence. Although targeted agents that inhibit activated oncogenes have yielded clinical responses, almost all of these malignancies recur. For example, gefitinib was found to effectively eliminate EGFR-mutated lung ADCs at the beginning of therapy, but the cancers recurred in 90% of patients within 2 years . Moreover, although oncogenic K-RAS-specific inhibitors have been developed , some cancer cells bypass the effects of these inhibitors and resume proliferation . In addition, the knockdown of oncogenic K-Ras in a mouse lung cancer model was found to result in rapid tumor recurrence, not because the gene knockdown was unsuccessful, but because other oncogenes were activated . Because tumor frequency is much lower in normal than in tumor-regressed mice, the rapid activation of secondary oncogenes in the latter suggests that a defense mechanism can be abrogated in established tumors. However, efforts to restore p53 expression in K-Ras-activated mouse lung cancers eliminated only malignant ADCs and failed to eliminate ADs . Therefore, it is of great therapeutic importance to understand as to why cancers recur, despite the effective inhibition of the activated oncogene. Recurrence of lung cancer is due primarily to persistent early lesions that are resistant to oncogene inhibitors. These early lesions do not contain activated oncogenes. Therefore, to eradicate cancers, it is necessary to understand their mechanisms of initiation. Inactivation of RUNX3 is thought to be responsible for the initiation of lung ADs, as well as for abrogating the R-point-regulating ARF-p53 pathway. The proliferation of K-RAS-activated lung AD cells with wild-type ARF and p53 results from RUNX3 inactivation, which abrogates the ARF-p53 pathway in lung ADs. Normal cells recognize the aberrant persistence of oncogenic K-RAS signals through their RUNX3-containing R-point-associated activator (Rp-RX3-AC) complexes, which sense the duration of RAS signals and regulate the ARF-p53 pathway. p53 deletions may be required at later stages of AD for abrogation of the ATM/ATR-p53 pathway. K-Ras-activated mouse lung ADs acquire secondary oncogene activation rapidly, because R-point associated oncogene surveillance mechanisms are abrogated in the ADs. RUNX3 restoration has been shown to eliminate K-RAS-activated tumors in a human lung cancer cell line. It would be exciting indeed if Runx3 restoration eliminates K-Ras-activated lung cancer in an animal model. If that turns out to be the case, RUNX3 will be a promising target for curative cancer therapy. Author Contributions J.-W.L. and S.-C.B. wrote the manuscript. All authors contributed to the editing of the 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 There is no data to share. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Fluctuation of levels of cyclins D and E and p21 through the cell cycle. The levels of cyclins D and E and p21 fluctuate markedly as cells progress through the cell cycle. The CDK inhibitors of the p21 family stimulate the formation of the cyclin D-CDK4/6 complex while inhibiting the formation of other cyclin-CDK complexes, including cyclin E-CDK2. Extracellular signals strongly influence the levels of D-type cyclins during the early G1 phase. However, the levels of the other cyclins, including cyclin E, are controlled by intracellular signals and precisely coordinated with cell cycle progression. The cyclin E-CDK2 complex is activated after cells pass through the R-point, followed by the formation of the remaining cyclin-CDK complexes through a cell-autonomous program. Figure 2 Sequential molecular events for R-point decisions. (A) In response to mitogenic stimulation, RUNX3 opens target loci. Upon mitogenic stimulation, RUNX3 binds to the enhancer regions of target loci within inactive chromatin, as indicated by H3K27-me3. pRB-E2F1 and p300 associate with RUNX3. p300 acetylates RUNX3 and histones. BRD2 binds to acetylated RUNX3 through its first bromodomain (BD1) and to H4K12-ac through its second bromodomain (BD2). Subsequently, SWI/SNF and MLL1/5 bind to the C-terminal region of BRD2. At this time point, inhibitory histones (H3K27-me3) are eliminated, and activating histones (H3K4-me3) are enriched at these loci. (B) RUNX3 forms an R-point-associated RUNX3-containing Activator (Rpa-RX3-AC) complex at the R-point. While RUNX3 binds to the enhancer region and recruits its coactivator (p300), histone-modifying enzymes (MLLs), and chromatin-remodeling complex (SWI/SNF), the basal transcription machinery (TFIID) is recruited to the promoter region of the target loci. The TFIID binds to the C-terminal region of BRD2 to form Rpa-RX3-AC. Moreover, the enhancer interacts with the promoter through Rpa-RX3-AC during the R-point. (C) Rpa-RX3-AC complex is converted to Rpa-RX3-RE after the R-point. Two hours after mitogenic stimulation, CDK4 (associated with p21) binds to RUNX3 and becomes an additional component of Rpa-RX3-AC. At this point, the cyclin D1-PRC1 complex forms separately from the Rpa-RX3-AC complex. Downregulation of the RAS-MEK signal results in the maturation of the cyclin D1-PRC1 complex in the cyclin D1-HDAC4-PRC1 complex, which binds to Rpa-RX3-AC through the interaction between cyclin D1 and CDK4, a component of the Rpa-RX3-AC complex, yielding Rpa-RX3-TR. Activation of CDK4 through its association with cyclin D1 is critical for the inactivation of the chromatin loci and the dissociation of the entire complex. RNF2, a component of the PRC2, contributes to the enrichment of an inactive chromatin marker (H2A-K119-Ub, H2A ubiquitination at Lys-119) at this locus. If the RAS signal is constitutively activated, the cyclin D1-PRC1 complex fails to mature into the cyclin D1-HDAC4-PRC1 complex, and consequently cannot form Rpa-RX3-TR. Therefore, if R-point commitment is normal, cells expressing constitutively active RAS cannot progress through the R-point into the S phase. If the mitogenic signal is downregulated in a normal manner, Rpa-RX3-TR dissociates (4 h after stimulation) into two complexes, the RUNX3-Cyclin D1-HDAC4 and BRD2-PRC1-SWI/SNF-TFIID complexes, which remain associated with chromatin. This is followed by the association of PRC2 with RUNX3-cyclin D1-HDAC4 to form Rpa-RX3-RE, which remains on the chromatin. EZH2, a component of PRC2, contributes to the enrichment of an inactive chromatin marker (H3K27-me3) at this locus. Figure 3 Sequential molecular events occurring during multistep tumor progression. Most colorectal and lung adenocarcinomas develop through a multistep tumorigenesis pathway. Tumors show development from normal tissue, to adenoma (AD), to adenocarcinoma (ADC), and ultimately progress to multiple types of invasive tumors. Molecular events occurring at each step are indicated. Figure 4 Inactivation of p53 tumor suppressor pathways. (A) Two major pathways trigger p53 activation. Aberrant oncogene activation is sensed by the R-point-associated complex, which induces the expression of ARF, inactivating HDM2 and stabilizing p53. DNA damage stress is sensed by the ATM/ATR kinases, activating the CHK1/CHK2 kinases, which stabilize p53. (B) Inactivation of p53 tumor suppressor pathways during multistep tumor progression. AD development is characterized by disruption of the Arf-p53 pathway due to the abrogation of the R-point, most frequently by RU3 inactivation. This may result in the selection of K-Ras-activated cells, which acquire a proliferative advantage. At the AD stage, the ATM/ATR - CHK1/2 - p53 pathway is functional. The pathway is disrupted at a late stage of AD by p53 mutation. Figure 5 Mechanism for sensing constitutive RAS activation. (A) Normal RAS activity is downregulated to the basal level soon after mitogenic stimulation. While RAS is activated, ARF is expressed. In normal cells, ARF is expressed for only a short time (1-3 h after mitogenic stimulation), followed by its suppression when RAS activity is downregulated. However, heterozygous mutations of RAS result in the maintenance of 50% of the maximum level of RAS activity. This persistent RAS activity maintains ARF expression until the G1/S checkpoint is reached. (B) Schematic illustration of the R-point-associated oncogene surveillance mechanism. Formation of the Rpa-RX3-AC complex is triggered by the RAS-MEK pathway 1 h after serum stimulation. The complex binds to the ARF promoter through RUNX-binding sites and induces ARF expression. After the R-point (4 h after mitogenic stimulation), the RAS-MEK pathway activity is downregulated. Rpa-RX3-AC complexes are converted to Rpa-RX3-RE complexes, which suppress ARF expression. However, constitutively activated RAS signaling inhibits the conversion of Rpa-RX3-AC to Rpa-RX3-RE complexes and prolongs ARF expression, which drives cells toward apoptosis. These series of molecular events enable cells to distinguish normal mitogenic signals from abnormal oncogenic K-RAS signals, thereby constituting an R-point-associated oncogene surveillance mechanism. 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PMC10000378 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050632 healthcare-11-00632 Article Treatment for Locally Resectable Stage IIIC1 Cervical Cancer: A Retrospective, Single-Institution Study Kashima Yoko Conceptualization Writing - original draft Supervision Murakami Kosuke Writing - original draft Writing - review & editing * Miyagawa Chiho Writing - review & editing Takaya Hisamitsu Formal analysis Kotani Yasushi Conceptualization Supervision Nakai Hidekatsu Supervision Matsumura Noriomi Writing - original draft Koshiyama Masafumi Academic Editor Department of Obstetrics and Gynecology, Faculty of Medicine, Kindai University, Sayama 589-8511, Japan * Correspondence: [email protected]; Tel.: +81-72-366-0221 21 2 2023 3 2023 11 5 63227 1 2023 15 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 ). According to the revision of the FIGO 2018 staging system, cervical cancer with pelvic lymph node metastases was changed to stage IIIC1. We retrospectively analyzed the prognosis and complications of locally resectable (classified as T1/T2 by TNM classification of the Union for International Cancer Control) stage IIIC1 cervical cancer. A total of 43 patients were divided into three groups: surgery with chemotherapy (CT) (ope+CT group) (T1; n = 7, T2; n = 16), surgery followed by concurrent chemoradiotherapy (CCRT), or radiotherapy (RT) (ope+RT group) (T1; n = 5, T2; n = 9), and CCRT or RT alone (RT group) (T1; n = 0, T2; n = 6). In T1 patients, recurrence was observed in three patients, but there was no difference among the treatment groups, and no patients died. In contrast, in T2 patients, recurrence and death were observed in nine patients (8 in ope+CT; 1 in ope+RT), and recurrence-free survival and overall survival were lower in the ope+CT group (p = 0.02 and 0.04, respectively). Lymphedema and dysuria were more common in the ope+RT group. A randomized controlled trial comparing CT and CCRT as an adjuvant therapy after surgery in T1/T2 patients, including those with pelvic lymph node metastases, is currently underway. However, our data suggest that performing CT alone after surgery in T2N1 patients is likely to worsen the prognosis. cervical cancer chemotherapy concurrent chemoradiotherapy lymph node surgery radiotherapy This research received no external funding. pmc1. Introduction Cervical cancer is the fourth most common cancer among women, with 604,000 reported patients and 342,000 deaths worldwide in 2020 . In Japan, the number of patients with cervical cancer is increasing among young women in their 50s or younger . Although cervical cancer cases are expected to decrease worldwide with the increased human papillomavirus (HPV) vaccination , HPV vaccination rates are low in Japan . In cervical cancer, lymph node (LN) metastasis is an important prognostic factor . According to the latest International Federation of Gynecological Organizations classification (FIGO 2018), if the tumor reaches the lower third of the vagina, extends to the pelvic wall, or if there is lymph node metastasis and no distant metastasis, it is classified as stage III. In addition, if there is metastasis in the pelvic lymph nodes by imaging or pathology, it is subclassified as stage IIIC1. Patients with para-aortic LN metastasis (N2) are now classified as stage IIIC2 . Concurrent chemoradiotherapy (CCRT) has substantially improved both the recurrence-free survival (RFS) and overall survival (OS) of locally advanced cervical cancer with LN metastases and has become the international standard of care. For example, the National Comprehensive Cancer Network 2022 guideline recommends external pelvic beam radiation therapy and brachytherapy with platinum regimens as CCRT for patients who are positive for pelvic LN metastases on a surgical biopsy . Furthermore, if the results of imaging studies are positive for pelvic LN metastases and are negative for para-aortic LN metastases, a surgical biopsy of the para-aortic LN is recommended, followed by an extended irradiation if para-aortic LN metastases are pathologically confirmed . Radiotherapy (RT)-based treatment is less invasive than surgery and can be safely performed in elderly patients and those with multiple comorbidities. RT can avoid the urinary dysfunction that is associated with extensive surgical resection. In the Japanese guidelines in 2011 and 2017, a radical hysterectomy was recommended for patients corresponding to stage IB-II of the FIGO 2008 classification (FIGO 2008), regardless of the presence or absence of LN metastases . Additionally, neoadjuvant chemotherapy (NAC) was listed as an option . Therefore, in Japan, surgery has been the main treatment for patients whose tumor is locally resectable (classified as T1/T2 by TNM classification of the Union for International Cancer Control), even for the FIGO 2018 stage IIIC. In addition, chemotherapy (pre-operative and post-operative), RT, or CCRT have been used as adjuvant therapies. In Japan, the staging was revised in 2020 following the FIGO 2018, and the new treatment guidelines were issued in 2022. However, no clear recommendation has been made as to whether surgery or CCRT should be selected as the main treatment for patients with stage IIIC . Surgery has the following advantages: the accurate detection of disease extent based on pathological diagnosis, the treatment of tumors refractory to chemotherapy and radiotherapy, and the preservation of ovarian function in young patients. Until early 2018, in our institution, an NAC plus radical hysterectomy was generally performed for patients with tumor diameters greater than 4 cm. However, there are reports that the NAC plus radical hysterectomy has a significantly lower disease-free survival rate than CCRT , and NAC has not been performed since then. As for adjuvant therapy, CCRT has generally been performed in patients who are at a very high risk of recurrence with chemotherapy alone, such as those with a positive or questionable surgical margin, while chemotherapy alone has been used in other cases. Although radical surgery is not recommended internationally for stage IIIC patients , there is currently no clear evidence for the treatment of patients with locally resectable T1/T2 tumors with pelvic LN metastases. In this study, we retrospectively examined the prognosis and complications of each treatment for stage IIIC1 cervical cancer, especially in patients with T1 or T2. To the best of our knowledge, this is the first report comparing surgery without RT and RT-based treatment for FIGO 2018 stage IIIC1 cervical cancer. 2. Materials and Methods Among cervical cancers initially treated at Kindai University Hospital between January 2013 and March 2021, we included those with FIGO 2008 stage IA2 to stage IIB. Neuroendocrine carcinomas were excluded. Among eligible patients with FIGO 2018 stage IIIC1. Those with Union for International Cancer Control (UICC) T1/T2 were selected . Age, histopathology, first-line treatment, RFS, OS, and treatment-related complications were retrospectively evaluated. Patients were divided into three groups according to treatment: the ope+CT group (surgery and chemotherapy (neoadjuvant and/or adjuvant)), the ope+RT group (surgery followed by CCRT or RT), and the RT group (CCRT or RT without surgery). In addition, patients were divided into four groups according to whether they had squamous cell carcinoma (SCC) or non-squamous cell carcinoma (non-SCC) and treatment with or without RT (CCRT or RT). Complications caused by treatment, leg lymphedema, and dysuria at least one month after completion of the initial treatment were investigated. Leg lymphedema was defined based on their medical records. Dysuria was defined as the administration of medication or self-catheterization. Statistical analyses were performed using GraphPad Prism version 9.4.1 (GraphPad Software, San Diego, CA, USA), the Kruskal-Wallis test for the age distribution. Survival curves were estimated by the Kaplan-Meier method and compared by the log-rank test. Fisher's exact test was performed using R version 4.2.2 for complication frequency. p values less than 0.05 were considered statistically significant. This study was approved by the Institutional Review Board of Kindai University Faculty of Medicine (R04-186). Patients in this study were allowed to refuse to participate in the survey by opting out on the website of the Kindai University Faculty of Medicine (accessed on 18 February 2023)). 3. Results A total of 213 patients were FIGO 2008 stage IA2-IIB, with a median age of 55 (25-97) years; the histological subtype was SCC in 145 patients (68%), adenocarcinoma in 55 patients (26%), and adenosquamous cell carcinoma in 13 patients (6%). Of the 213 patients, 61 (28%) were FIGO 2018 stage IIIC1, including 12 patients with T1 (Table 1) and 31 patients with T2 (Table 2). Among patients with T1 and T2 cancer, 33 (77%) had SCC and 10 (23%) had non-SCC, with a median age of 47 (25-73) years and a median follow-up of 52 (10-111) months (Table 1 and Table 2). The RT group had an older mean age than the ope+CT or ope+RT groups . After October 2018, when the treatment strategy changed, only two of the six patients in the RT group were older than 70 years. Among the stage IIIC1 patients, all those with T1N1 underwent surgery as the main treatment: five in the ope+RT group (surgery followed by CCRT in four patients and surgery followed by CCRT and systemic chemotherapy in one patient) and seven in the ope+CT group (surgery followed by adjuvant chemotherapy in six patients and NAC followed by surgery and adjuvant chemotherapy in one patient (case12)) (Table 1). Recurrence occurred in three patients, with metastases to the vagina, lung, and mediastinal LN, all of which responded to treatment of the recurrent tumor. There was no significant difference in RFS and OS between the ope+CT group and the ope+RT group . Among stage IIIC1 patients with T2N1, nine were in the ope+RT group (surgery followed by CCRT in three patients, surgery followed by RT alone in one patient, NAC followed by surgery and RT alone in one patient (case 23), and NAC followed by surgery and CCRT in four patients (case 24-27)) (Table 2). A total of six patients were in the ope+CT group (surgery followed by adjuvant chemotherapy in five patients and NAC followed by surgery and adjuvant chemotherapy in eleven patients (case 33-43)), and six patients were in the RT group (all received CCRT) (Table 2). Recurrence was observed in eight patients in the ope+CT group and one patient in the ope+RT group; all nine of these patients had a relapse site in the pelvis and died of the disease. There were significant differences in the RFS and OS among the three groups . Similarly, patients who did not receive CCRT or RT alone had a worse prognosis in terms of both RFS and OS among SCC and non-SCC groups . As for complications, in patients with stage IIIC1 T1/T2, lymphedema occurred in 17% (4/23) of the patients in the ope+CT group, 43% (6/14) in the ope+RT group, and 17% (1/6) in the RT group; dysuria occurred in 13% (3/23) of patients in the ope+CT group, 14% (2/14) in the ope+RT group, and 17% (1/6) in the RT group. Lymphedema was more common in the ope+RT group, although there were no significant differences between the groups for both lymphedema and dysuria . 4. Discussion The policy at our institution has been to perform surgery whenever possible for patients with resectable T1 or T2 cervical cancer, even if they are FIGO 2018 stage IIIC1. Thus, the older age in the RT group reflects the fact that RT was performed instead of surgery in older patients with poor surgical tolerance . However, since late 2018, an increasing number of patients with T2 have been treated with CCRT as the primary therapy, regardless of their surgical tolerance. In our cohort, there were no recurrences or deaths and few complications in patients who received CCRT but not surgery . In 2005, 23 patients with T1b-2a, who were found to have LN metastases intraoperatively and did not undergo hysterectomy, were reported to have a significantly lower 2-year disease-free survival rate than 35 patients who underwent a hysterectomy and had confirmed post-operative LN metastasis . However, a more extensive cohort analysis in 2021 found no significant difference in recurrence or mortality between 361 patients with T1a-2b cancer who underwent a planned hysterectomy and 154 who abandoned the procedure due to intraoperative detection of LN metastases . The analysis showed no survival benefit from a hysterectomy in any subgroup . In addition, a single-center retrospective study in Japan reported that 24 patients with T1b-2b SCC and LN metastases who received CCRT as primary therapy without surgery had RFS and OS that were comparable to those of 45 patients who underwent surgery . These results suggest that a hysterectomy may not be necessary for patients with T1/T2 cervical cancer and pelvic LN metastasis. Even if a radical hysterectomy is performed for cervical cancer, a recent phase III clinical trial rejected the strategy of NAC for locally advanced patients . In our study, all patients who died of the disease had T2 cancer, including five who underwent NAC followed by surgery and adjuvant chemotherapy and one with NAC followed by CCRT (Table 2). Unless there is new evidence in the future to prove the usefulness of NAC, NAC is not likely to be a preferred option. When pelvic LN metastases are detected after surgery, CCRT has a better prognosis than RT as adjuvant therapy and is the standard of care. However, surgery followed by CCRT is associated with a lower quality of life, with more leg lymphedema, dysuria, rectal dysfunction, sexual dysfunction, and mental impairment than surgery alone . In our study, leg lymphedema also tended to be more common in the ope+RT group, although there were no significant differences due to the small number of patients . In the phase II JGOG1067 trial, 62 patients with cervical cancer and LN metastasis received adjuvant chemotherapy with irinotecan and nedaplatin. The result was favorable, with a 5-year RFS of 77% and lymphedema in only 10% of patients . The phase III JGOG1082 trial (AFTER trial) is currently ongoing and is comparing CCRT and chemotherapy (paclitaxel plus carboplatin or cisplatin) as adjuvant therapies in FIGO 2018 stage IB-IIB patients with pelvic LN metastases and/or parametrial invasion . Our study showed no death in patients with T1N1 cancer, regardless of the treatment. However, the ope+CT group had a worse prognosis in patients with T2N1 . Knowing that post-operative CCRT increases the risk of complications , we selected CCRT in patients with a strong tendency toward invasion and a predicted high risk of recurrence. Therefore, the selection bias would be present in that surgery followed by CCRT, which would have a worse prognosis. Surprisingly, however, patients with T2N1 in the ope+CT group (with adjuvant chemotherapy) had a worse prognosis than those in the ope+RT and even the RT group, regardless of the histological subtype . Although non-SCC is less radiosensitive than SCC , the efficacy of CCRT for patients with LN metastases has been demonstrated, even for non-SCC . CCRT without surgery is the standard treatment for T2 , and therefore, the evidence for surgery followed by chemotherapy for T2N1 cancer is extremely limited in clinical trials and real-world data. In addition, a limitation of this study is that we used retrospective data for a limited number of patients at a single institution. However, the study data for patients with T2N1 cancer strongly suggest the risk of not using RT for T2N1. The JGOG1082 trial aims to test the efficacy of post-operative systemic chemotherapy, including in T2N1 . This trial may clarify the results of our study. In conclusion, CCRT without surgery may not worsen the prognosis for patients with FIGO 2018 T1/ T2 stage IIIC1 cervical cancer. Surgery with chemotherapy instead of CCRT as the main therapy or adjuvant therapy in patients with T2N1 cancer may worsen their prognosis. In the future, the JGOG1082 trial or other cohort studies may reveal the risks of not using RT for T2N1. Author Contributions Conceptualization, Y.K. (Yoko Kashima) and N.M.; analysis, H.T.; original draft preparation, Y.K. (Yoko Kashima), K.M. and N.M.; review and editing, K.M. and C.M.; supervision, H.N. and Y.K. (Yasushi Kotani). All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted following the Declaration of Helsinki and was approved by the Institutional Review Board of Kindai University (protocol code R04-186 and 30 November 2022). Informed Consent Statement Opt-out consent was obtained from all participants involved in the study. Data Availability Statement The data that support the findings of this study are available from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Patient ages by treatment group. ope+CT, patients who underwent surgery and chemotherapy (neoadjuvant or adjuvant); ope+RT, patients who underwent surgery followed by radiotherapy (including concurrent chemoradiotherapy); and RT, patients who underwent radiotherapy (including concurrent chemoradiotherapy). The p-value is based on the Kruskal-Wallis test. Figure 2 Prognosis of patients with (tumor and node) T1N1. (A) Recurrence-free survival (RFS). (B) Overall survival (OS). ope+CT, patients who underwent surgery and chemotherapy (neoadjuvant or adjuvant); ope+RT, patients who underwent surgery followed by radiotherapy (including concurrent chemoradiotherapy). N.S.: not significant. Survival curves were estimated by the Kaplan-Meier method and compared using the log-rank test. Figure 3 Prognosis of patients with (tumor and node) T2N1. (A) Recurrence free survival (RFS). (B) Overall survival (OS). ope+CT, patients who underwent surgery and chemotherapy (neoadjuvant or adjuvant); ope+RT, patients who underwent surgery followed by radiotherapy (including concurrent chemoradiotherapy); and RT, patients who underwent radiotherapy (including concurrent chemoradiotherapy). (C) RFS by histological subtype. (D) OS by histological subtype. Patients were divided according to whether they had squamous cell carcinoma (SCC) or non-squamous cell carcinoma (non-SCC), and whether radiotherapy (including concurrent chemoradiotherapy) was performed or not. Survival curves were estimated by the Kaplan-Meier method and compared by the log-rank test. Figure 4 Post-treatment complications in patients with (tumor and node) T1/T2N1. (A) Number of leg lymphedema occurrences. (B) Number of dysuria occurrences. ope+CT, patients who underwent surgery and chemotherapy (neoadjuvant or adjuvant); ope+RT, patients who underwent surgery followed by radiotherapy (including concurrent chemoradiotherapy); and RT, patients who underwent radiotherapy (including concurrent chemoradiotherapy). Complication frequency was performed the Fisher's exact test. healthcare-11-00632-t001_Table 1 Table 1 Stage IIIC1 cases classified as T1 by the TNM classification of the Union for International Cancer Control. Case Age Histological Type Treatment Recurrence Time to Recurrence (Month) Treatment at Recurrence Prognosis Lymph Edema Dysuria 1 37 SCC ope+RT - NED + 2 35 SCC ope+RT - NED + 3 54 SCC ope+RT + 20 ope NED 4 40 AdS ope+RT + 46 ope NED 5 35 AdS ope+RT - NED + + 6 25 SCC ope+CT - NED 7 31 SCC ope+CT - NED 8 31 SCC ope+CT - NED 9 44 SCC ope+CT - NED 10 47 SCC ope+CT - NED 11 49 SCC ope+CT + 14 RT NED + 12 41 SCC ope+CT - NED SCC: squamous cell carcinoma, AdS: adenosquamous cell carcinoma, ope: operation, RT: radiotherapy, CT: chemotherapy, NAC: neoadjuvant chemotherapy, NED: no evidence of disease, OS: overall survival, and RFS: recurrence-free survival. healthcare-11-00632-t002_Table 2 Table 2 Stage IIIC1 cases classified as T2 by the TNM classification of the Union for International Cancer Control. Case Age Histological Type Treatment Recurrence Time to Recurrence (Month) Treatment at Recurrence Prognosis Lymph Edema Dysuria 13 56 SCC RT - NED 14 47 SCC RT - NED 15 64 SCC RT - NED 16 67 SCC RT - NED + + 17 70 SCC RT - NED 18 70 SCC RT - NED 19 47 SCC ope+RT - NED 20 52 SCC ope+RT - NED 21 48 Ad-G ope+RT - NED 22 47 Ad-E ope+RT - NED + 23 52 SCC ope+RT - NED 24 35 SCC ope+RT - NED + + 25 48 SCC ope+RT - NED + 26 62 SCC ope+RT - NED 27 37 SCC ope+RT + 12 BSC DOD 28 65 SCC ope+CT - NED 29 37 SCC ope+CT + 28 ope DOD 30 46 Ad ope+CT - NED 31 52 Ad ope+CT + 4 RT DOD 32 56 Ad ope+CT + 9 RT DOD + 33 35 SCC ope+CT - NED 34 67 SCC ope+CT - NED 35 52 SCC ope+CT - NED + 36 54 SCC ope+CT - NED + 37 70 SCC ope+CT - NED 38 36 SCC ope+CT + 11 RT DOD 39 45 SCC ope+CT + 22 RT DOD + 40 67 SCC ope+CT + 11 RT DOD 41 69 Ad-C ope+CT - NED 42 37 Ad ope+CT + 6 RT DOD 43 73 Ad ope+CT + 11 BSC DOD + + SCC: squamous cell carcinoma, AdS: adenosquamous cell carcinoma, Ad-G: gastric adenocarcinoma, Ad-E: endometrioid adenocarcinoma, Ad: usual-type endocervical adenocarcinoma, Ad-C: clear cell adenocarcinoma, DOD: died of disease, ope: operation, RT: radiotherapy, CT: chemotherapy, NAC: neoadjuvant chemotherapy, NED: no evidence of disease, OS: overall survival, RFS: recurrence-free survival, and BSC: best supportive care. 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PMC10000379 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050673 healthcare-11-00673 Case Report Transforming Primary Care: Developing Health Precincts as Models for Sustainable Integrated Community-Based Healthcare Oprescu Florin * Fjaagesund Shauna Hardy Margaret Jones Evan Giansanti Daniele Academic Editor School of Health, University of the Sunshine Coast, Sippy Downs 4556, Australia * Correspondence: [email protected] 24 2 2023 3 2023 11 5 67331 12 2022 16 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 ). Holistic healthcare precincts are an emerging service model to address the growing health service demands of ageing consumers and an increasing prevalence of chronic diseases. In Australia and similar countries with universal publicly funded Medicare systems, the first point of access to healthcare is provided by general medical practitioners. This case report focuses on successful components of a private, integrated, patient-centred primary care model located in a low socioeconomic population in North Brisbane, Queensland. Successful components included a focus on sustainability, general practice as an anchor tenant in the health precinct, the integration of multiple services, team-based care for shared clinical services, flexible expansion options, the use of MedTech, support for small businesses and a cluster structure. The Morayfield Health Precinct (MHP) offers appropriate, safe and individualised healthcare to residents across their life continuum. Its success was built on a foundation of pre-planning, to ensure the design/build, anchor tenant and collaborative ecosystem were sustainable in the long term. MHP planning was based on an adaptation of the WHO-IPCC framework supporting true patient-centred, integrated care. Its shared vision and collaborative care are supported by its internal governance structure, tenant selection, established and emerging referral networks and partnerships. Evidence-based and informed care is further supported by internal and external research and education partnerships. health precinct health hub primary healthcare community-based healthcare This research received no external funding. pmc1. Introduction Holistic healthcare precincts are an emerging service model to address the growing health service demand of ageing consumers and an increasing prevalence of chronic diseases. Innovative patient-centred approaches and integrative place-based healthcare infrastructure are being developed to create environments that support better individual and community health outcomes . Integrated services should be tailored to the needs of each health consumer and across different life stages , including rapid and efficient referral pathways for those with complex needs requiring team-based care . In Australia and similar countries with universal publicly funded Medicare systems, the first point of access to healthcare is provided by general medical practitioners . Globally, one in five adults who required the services of a general medical practitioner (GP) did not receive care, with priority groups such as people of low socioeconomic status experiencing higher levels of inaccessibility . The World Health Organization (WHO] encourages all countries to support universal affordable health coverage and access to a range of essential services to reduce poverty, increase economic opportunity and create more stable communities . Integrated healthcare systems can support quality affordable comprehensive care for everyone, including broader social determinants of health and the empowerment of individuals and communities . During the COVID-19 pandemic, policy measures were introduced to provide Australians with access to primary care. General medical practitioners were described by patients as most accessible, either face-to-face or by telehealth. Often, however, other multidisciplinary team members were not available, such as non-urgent specialists, allied health, dental care services and in situations in which telephone appointments were viewed as inappropriate by a patient or practitioner . Sustainable health systems are necessary during pandemics to support individualised patient decisions in holistic health, safety and complex care, including initiatives that provide reassurance of infection safety and continued engagement with all multi-disciplinary team providers . This case report focuses on successful components of a private, integrated, patient-centred primary care model located in a low socioeconomic population in North Brisbane, Queensland, including its ability to provide multidisciplinary care during the COVID-19 pandemic. Though the initial facility opened in 2017 and was labelled a 'Health Hub', it was developed and built to the capacity of a large primary care health precinct . Its success can be measured by its number of growing health consumers, which has increased to more than 200,000 current patients on record . This is quite significant, given the immediate suburb of Morayfield has ~60,000 residents and is centrally located within the local government area of Moreton Bay with a population of 476,340 . In 2021, MHP was sold by its original private investors to a large real estate corporation for AUD 110 M . Thus, the proposed research question (RQ) is: What are the elements of the successful planning and implementation of a sustainable and adaptable large community-based integrated healthcare hub? The results of this case study are intended to broadly present a novel model of integrated care in primary care and elements of successful planning and implementation to inform area(s) of future evaluation. 2. Methods A case study approach was used to answer the RQ, as limited literature exists in Australia on emergent, privately funded, community-based, primary care health precincts. The selected case was chosen due to its unique elements of: (1) its rapid expansion and large health consumer base; (2) its infrastructure and governance investment, which was privately funded with no government support; (3) its focus on primary multi-disciplinary care opposed to a hospital-based setting; (4) its location in a low-socioeconomic area with a low uptake of private health insurance; and (5) its sustainable and adaptative model based on engagement. Supplementary information, such as governance committee minutes, was provided. Limitations to this case study include the fact that the results were based on the retrospective information made available to authors. 3. Results 3.1. Planning Development to Meet Community Needs The MHP was purpose-built and designed to serve a population of low socioeconomic status in Moreton Bay North that was reported to have one of the poorest health outcomes . Firstly, during the initial planning stage, a comprehensive community needs analysis was undertaken to inform which health services, including treatment modalities, met the expressed and unexpressed health needs of residents. This analysis took into consideration local population demographics and health status, which included a high prevalence of chronic disease, multimorbidity, disability, homelessness and households living in the lowest two quintiles of disadvantage (including poverty and crime). Secondly, asset mapping was conducted to inform which identified health needs were undelivered to low socioeconomic consumers within their community. Prior to the opening of the MHP, residents had to travel long distances for specialist services, which reduced accessibility and affordability . 3.2. Implementation of Evidence-Based Community Services Built for sustainability. Health consumer and asset pre-planning data informed an initial facility of 15,000 sqm to accommodate the diversity and clustering of health services needed (Table 1). Other important considerations included proximity to public transport, accessibility by car and adequate free parking and loading areas to reduce travel barriers. An existing large retail structure (the former Bunnings building) was purchased by investors and retrofitted to reduce environmental impact to the community. To further MHP's commitment to healthier communities, investment in 404 kW solar generation, rainwater recycling, electric vehicle charging, and facilities to encourage active transport were also included in the building design. Primary care access. The anchor tenants within the MHP are general medical practitioners (GPs) who provide multi-dimensional care to residents. This care delivery encompasses the emotional, physical, cultural, environmental, spiritual and other non-biomedical factors unique to the individual person, built on the foundation of a doctor-patient relationship that can provision team-based care . To create added convenience and reduce the burden of multiple appointments, a range of practitioners and complementary services was positioned within and adjacent to MHP to support an integrated, patient-centred, team-based care environment (Table 1). In alignment with precinct pre-planning, services were expanded to include a range of specialists to support diagnosis and treatment (Table 1). COVID-19 response. During the COVID-19 pandemic, Australian patients with respiratory illness were faced with disruptions in primary care and access to their regular general medical practitioner (GP) due to concerns about infection safety . The MHP patients experienced limited disruptions due to its collective tenant initiatives, which increased assurance of the safety of routine care appointments. This included a tenant investment in the front entrance screening, cleaning schedules, the alignment of workplace policies and procedures, provision of masks and external marketing to reassure that safe and appropriate care was accessible. Additionally, MHP was the first COVID-19 respiratory clinic to open in Queensland due to this preparedness, as well as its existing physical design of a quarantine clinic area with its own separate air exchange and access. This fit-for-purpose approach continued in 2021, with the custom design of a mass vaccination clinic that had a capacity of 7000 patients per week. Sustainability of integration. The MHP uses an adaptation of the WHO Integrated Person-Centred Care (WHO-IPCC) framework , which includes additional sustainability measures to maintain a shared vision of delivering true patient-centred care as a collective precinct of autonomous tenants. Shared values are supported by an overarching strategic plan, governance structure and tenant investment, which was initially developed by all stakeholders, including health consumers. Elements of the Canterbury Model of Care and Kaiser Permanente were integrated into MHP objectives to deliver coordinated, appropriate, safe and tailored individual care to health consumers. Continuing tenant investment in MHP's governance is a point of differentiation from other precincts, such as the General Practice Super Clinics . Health consumers are encouraged to be active participants. Examples include research co-design, quality improvement feedback and connection to community services. Team-based care. Multidisciplinary care delivery is underpinned by governance, tenant selection and rental agreements, which ensures managers, practitioners and support staff work together to deliver coordinated, individualised care. This coordination of clinical and non-biomedical services, including community-based services that connect patients to employment, training and social activities are supported by trusted referral networks based on established relationships created by interaction, proximity and health consumer feedback. Tenants with regular, established referrals with other providers within MHP have some level of shared patient records or processes in place, ensuring that consent is received and privacy is protected. Regular clinical meetings are held quarterly, bi-monthly and weekly [depending on each committee's terms of reference], bringing all MHP tenants and practitioners together to ensure open communication, build referral networks and improve patient experiences. Evidence-based and informed care is based on the pillars of education, research and training as foundations of good clinical practice, which supports the rapid translation of research into improve patient health outcomes. Novel delivery of shared clinical services. Some tenants within MHP choose to share space and resources (a practice within a practice) to deliver seamless care to health consumers. For example, the community pharmacy has multiple treatment rooms to deliver additional services, such as immunisations. This includes all COVID-19 vaccine types, as well as both private and public influenza . In Australia, this approach is particularly novel, as throughout the pandemic, pharmacies and/or general practices were at times restricted to the administration of certain types of COVID-19 vaccines. This shared delivery of services better accommodates health consumer preferences, as it brings vaccine services together, within the same location. Additional benefits for health consumers include better access to multiple health practitioners, increased safety in the event of anaphylaxis and the opportunity for multi-disciplinary holistic health guidance at routine vaccination appointments. Novel team-based chiropractic care. Another novel integration includes an embedded chiropractic care service within primary care. This service is delivered in partnership between multiple MHP tenants using a shared patient record within a trusted referral network to provide evidence-based team care for health consumers experiencing chronic pain . Allied health services within and adjacent to MHP provide additional care plan support, in addition to group and peer-based exercise activities to reduce the cost burden to health consumers. The regional council also provides free exercise and social activities to residents , which practitioners refer and partner with to greater assist patients in selecting activities based on their preferences. Urgent care expansion. A current expansion focused on immediate care services is in its pilot phase . The Minor Accident and Illness Centre (MAIC) and medical practitioner workforce was accredited to the New Zealand College of Urgent Care (NZCUC, 2021), as no Australian equivalent exists. This 38-bed centre provides acute services for non-life-threatening accidents and illnesses and its co-location within MHP supports continuity of care (i.e., follow-up with a family doctor, specialist, counsellor or psychologist). Due to the low-resource, high complex care population demographics of North Moreton Bay , it is important that acute services are provided at no cost to patients. This differs from private emergency and urgent care services found in more affluent suburbs of Australia. Onsite pathology and radiology are also both integral elements of a successful urgent care model, as they provides health consumers with immediate diagnosis and treatment. In other countries, urgent care in certain settings can reduce hospital wait times and congestion for minor illnesses and accidents when appropriately and safely treated in an accredited and qualified urgent care centre . Assistive technology. Emerging MedTech compliments and gives resources to practitioners in the prevention, early diagnosis and/or treatment of illness and chronic disease. Within MHP, this includes artificial intelligence and/or machine learning for ap-plications such as mole mapping to detect skin cancer or lesion changes , sound detection for diagnosis of respiratory illnesses and tailored repetitive magnetic stimulation to improve health outcomes of people living with neurological disorders . Novel chronic disease management mobile apps connect patients to services to improve access to health and wellbeing activities . The MHP pharmacy has a robotic dispensary, which greatly improves operational efficiencies by removing burdensome physical dispensing and administrative tasks . This permits pharmacists to be a single point of transaction and significantly increases the counselling time given to health consumers . Additional pharmacist time with patients builds trusted relationships, assists with the identification of risks and safety compliance in treatment and helps develop interprofessional relationships with practitioners. Health incubator. Smaller tenants may start within MPH and grow to relocate adjacent to the precinct or within the local community. These tenants remain part of the MHP referral networks and are invited to remain active participants in MPH activities. Examples include atWork Australia, which connects residents to training and meaningful employment , and Peach Tree, a peer-led organisation that supports perinatal resilience and recovery . Cluster structure. From a cluster ecosystem model, the MHP consists of a mental health cluster, including community addiction and relationship services; a muscoskeletal cluster supported by complimentary services; a skin cancer cluster with increasing assistive MedTech support; Paeds (Mums and Bubs Hub), including a focus on interventions in pre-birth and early childhood; and chronic disease management due to the high needs and low socioeconomic status of the local population. More details are available in Table 1. 4. Discussion The MHP offers appropriate, safe and individualised healthcare to residents across their life continuum, with clusters of services (Table 1) and referral pathways based on health consumer demand. Its success was built on the foundation of pre-planning, to ensure the design/build, anchor tenant and collaborative ecosystem were sustainable in the long term. MHP implementation was based on an adaptation of the WHO-IPCC framework, which continues to support an inclusive governance structure, based on the principles of sustainability, integrated care and patient-centredness. It is broadly recognised that clinical leadership is an integral part of integrated care delivery . Collective leadership, described as collaborative, shared, distributed or team-based, involves the engagement and influence of practitioners based on social interactions . The MHP is supported by each tenant's commitment and participation in internal governance as part of its adapted WHO-IPCC framework. Active participants within MHP's ecosystem also include individual health practitioners, such as specialists, GPs, pharmacists, allied health practitioners, psychologists, counsellors and nurses. Evidence-based and informed care is further supported by internal and external research and education partnerships. The proximity of services within the same location provides added convenience for health consumers, especially those with complex needs requiring multiple appointments and team-based care. This is demonstrated by the development of health clusters, including a significant presence of mental health support and muscoskeletal care. The creation of non-traditional integrative approaches, such as evidence-based chiropractors and the use of assistive medical technologies, further enhances holistic care by supporting early diagnosis, individualised treatment and self-management. The physical design of the building facilitates activities and interactions between tenants and practitioners with a centralised education and training room. This space hosts weekly stakeholder-inclusive clinical meetings, which create established referral networks among tenants and individual practitioners. This continuing ecosystem of collaboration is based on engagement and a shared common vision, which also provides health consumers with reassurance that referred provider services are known to their practitioner and can be trusted. The co-creation of community-based health systems involves academics working together with stakeholders to deliver societal impact, adaptative research processes and novel models (Table 2) to meet local needs . In alignment with its adapted WHO-IPCC strategy, the Research Education and Engagement Committee [REEC] develops internal research capacity, builds bodies of evidence and supports the co-design and translation of research into clinical practice. This includes an expansion of health consumer representation as part of a newly formed Health Research Ethics Advisory Committee. Recently, a tenant investment of AUD 90,000 into seed research grant funding has facilitated initial relationships between industry, clinicians and researchers to collaborate on small projects. These studies are ongoing and are expected to leverage outcomes for future large-scale research projects . This funding was especially important, as the MHP is not a hospital, and therefore, it receives no direct financial support from tertiary entities and is reliant on seed funding from tenancies and external research grants. Sustainability was foundational for the MHP design and a key strategic pillar of MHP's strategic plan. Financial sustainability, including the capacity to meet demand, was added to the WHO-IPCC framework to ensure scalability and flexibility to adapt to the needs of health consumers. This is an innovation, as sustainable services need to be financially sound in addition to being integrated to provide the best possible health outcomes for residents. To ensure the success of tenants, a continual review of community needs, workforce challenges and health consumer demand is undertaken at governance committees to drive new services and future tenant selection processes. During the COVID-19 pandemic, the MHP was able to respond quickly to provide safe and accessible services to health consumers. By design, an area of the building was built with its own separate air exchange system and access. This permitted the MHP to establish the first COVID-19 respiratory clinic in Queensland, and from March 2020 to February 2023, it has provided over 157,000 appointments. By tenant agreement, additional risk mitigation and infection control strategies were collectively introduced, which included an investment front entrance screening and mask distribution to patients. These actions were taken to reduce COVID-19 exposure and increase patient confidence to attend routine care appointments. Addressing current workforce shortages by the sharing of practitioners is enabled by co-location and engagement within the MHP ecosystem, as it permits separate tenants to provide services in partnership. Shared services bring mutual benefit, as this reduces unnecessary competition and duplication of services within the precinct, while also using existing space and workforce more efficiently. Additionally, working collaboratively in close proximity (i.e., nurses, doctors, pharmacists, technicians and medical administration) further develops interprofessional relationships and increases patient trust. The expansion of practitioner roles could be integrated into emerging models of care to address primary care workforce shortages. This could include scope enhancement for nurse practitioners and pharmacists in non-hospital settings to support acute services and chronic disease management. Additionally, urgent care specialist training could be tailored across a range of health practitioner types (i.e., paramedicine, practice nurses, occupational therapists). These roles within team-based care and integration between providers requires further evaluation, in order to form recommendations on how to deliver quality care, reduce fragmentation and improve continuity of care within local communities. 5. Conclusions MHP serves over 200,000 patients in an efficient, safe and appropriate manner (7 days/week, 12 h/day, 365 days per year). Its foundations are based on engagement in the community, business and clinical environment, and MHP's shared common vision is embedded within planning and implementation processes. Both health consumers and practitioners experience the convenience and benefits of a physical co-location and the integration of needed health services. The collaborative ecosystem, supported by governance structures, is instrumental in creating innovation and addressing community health challenges, and further evaluation is needed to measure societal impact and patient health outcomes. Tenant selection and committee processes are aligned with the shared vision of integration and patient-centeredness, including the foundational pillars of education, research and engagement. These pillars continue to support the delivery of evidence-based and -informed approaches, including novel models of care, to provide the best integrated (team-based) and patient-centred (individualised) care to health consumers. Further research into the interaction between clinical leadership in integrative care delivery and its emerging relationships with academics will be carried out. Collaboration has supported tenants during periods of significant and unprecedented change. Tenants have demonstrated a surge capacity for pandemic situations. State-of-the art physical design and assistive technologies were further strengthened by collaborative processes and governance. The capacity for future developments that support the need for flexible and multi-sector coordination to address the changing needs of health consumers requires further evaluation to better determine how the components of this model improve patient health outcomes. Author Contributions Conceptualization: F.O., S.F. Methodology: F.O., S.F. Validation: M.H., E.J. Writing--original draft preparation: F.O. Writing--review and editing: F.O., S.F., M.H., E.J. 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. healthcare-11-00673-t001_Table 1 Table 1 Morayfield health precinct cluster structure. Cluster Integrated Services Mental Health Counselling and psychology support Neuromodulation (tailored TMS) Peer group-based support or exercise Addiction and relationship support Holistic care and referrals to mental health services--GPs and nurse practitioners Allied health--dietetics and nutrition, exercise physiology, group/peer exercise support Onsite diagnostics Community pharmacy Access to evidence-informed treatment--clinical trials Muscoskeletal Chronic pain management--GPs and nurse practitioners Sports medicine specialists Complementary medicine specialists--prolotherapy, PRP, cannabinoids, peer group-based support/exercise Integrated chiropractic care Allied health--exercise physiology, physiotherapy, dietetics and nutrition, podiatry Rehabilitation specialists Community pharmacy Onsite diagnostics Skin Cancer Early diagnosis and prevention--GPs and nurse practitioners Oncology specialists GPs with specialist training in skin cancer Early detection tools--assistive medical technology in mole mapping, detection and changes Community pharmacy Onsite diagnostics Access to evidence-informed treatment--clinical trials Paeds--Mum and Bubs Hub Ante and post-natal holistic care--midwives, paediatricians and gynaecologists Lactation/breastfeeding support Sexual healthcare and referrals--GPs and nurse practitioners Neuromodulation (tailored TMS for autism in children) Onsite daycare Group/peer support NDIS services for children with intellectual and/or physical disabilities Allied health--dietetics and nutrition, post-partum recovery Community pharmacy Dentistry Onsite diagnostics Chronic Disease Early detection, prevention and holistic treatment--GPs, nurse practitioners and diabetes educators Specialists--oncology, cardiology, gastroenterology, orthopaedics, neurology, chiropractic Allied health--exercise physiology, physiotherapy, podiatry, dietetics and nutrition Psychology and counselling--emotional support Community services--emotional and physical health Community pharmacy--polypharmacy support Renal dialysis and nephrologists Sleep and respiratory support Wound management--including light therapy Dentistry Onsite diagnostics Disability support, including employment services No or low-cost health and wellbeing activities provided by internal and external partnerships Access to evidence-informed treatment--clinical trials healthcare-11-00673-t002_Table 2 Table 2 Novel models within Morayfield Health Precinct (MHP). Model Description Emerging Community-Based Impact Research Cluster Patient experiences, including priority groups of low socio-economic and indigenous people Disease-specific--autism, cardiac/diabetes, chronic pain, foetal alcohol syndrome, post-traumatic stress disorder Workforce development--domestic violence, integrative (team-based) clinical care, urgent care, clinical trials Patient education--reading skills for patient-child relationships Health services--GP-led urgent care model Novel mental health treatment--neuromodulation to treat neurological and sleep disorders MedTech--mobile apps (practitioner and patient user interfaces), respiratory disease diagnosis, telehealth Research and health services co-design with community and clinical leaders within MHP Integrated Chiropractic Care Evidence-based chiropractor embedded in MHP with shared patient record and referral system to deliver team-based care (i.e., care plans) Shared Services (Practice in a Practice) Shared delivery of services within community pharmacy, including embedding of nurse practitioners, practice nurses, GPs and medical reception Shared reception, workforce and physical space where appropriate to enhance utilisation of health resources Pandemic Preparedness Quarantine capacity by design Collaborative governance structure to enable shared decisions to ensure continued undisrupted primary care access and safety Consistent communication internally and externally Health Consumer Engagement Participation within governance structures, including newly formed Human Research Ethics Committee Qualitative studies that involve health consumer participants and focus on their experience or perspective Integration of Community-Based Services in Primary Care Services that connect people with disabilities to meaningful work Relationship support, including elder abuse, domestic violence and parent-child relationships Antenatal and perinatal support No or low-cost health and wellbeing activities provided by external and internal partnerships Workforce Development Co-design of new multi-disciplinary urgent care qualifications Expansion of non-traditional practitioners into primary care delivery, such as paramedicine, exercise physiologists and occupational therapists Supporting occupational work experience in primary care for students studying nursing, midwifery, medicine, allied health and paramedicine 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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PMC10000380 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050967 diagnostics-13-00967 Article Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling Naskar Indrajit Investigation * Pal Arabinda Kumar Conceptualization Writing - review & editing Jana Nandan Kumar Formal analysis Tehrani Fleur T. Academic Editor Heritage Institute of Technology, Kolkata 700107, WB, India * Correspondence: [email protected] 03 3 2023 3 2023 13 5 96702 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 ). Uncontrolled breathing is the most critical and challenging situation for a healthcare person to patients. It may be due to simple cough/cold/critical disease to severe respiratory infection of the patients and resulting directly impacts the lungs and damages the alveoli which leads to shortness of breath and also impairs the oxygen exchange. The prolonged respiratory failure in such patients may cause death. In this condition, supportive care of the patients by medicine and a controlled oxygen supply is only the emergency treatment. In this paper, as a part of emergency support, the intelligent set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) is delineated to control the oxygen supply to uncomforted breathing or respiratory infected patients. The effectiveness of the model reference adaptive controller (MRAC) is enhanced by assimilating the worthiness of fuzzy-based tuning and set-point modulation strategies. Since then, different conventional and intelligent controllers have attempted to regulate the supply of oxygen to respiratory distress patients. To overcome the limitations of previous techniques, researchers created the set-point modulated fuzzy PI-based model reference adaptive controller, which can react instantly to changes in oxygen demand in patients. Nonlinear mathematical formulations of the respiratory system and the exchange of oxygen with time delay are modeled and simulated for study. The efficacy of the proposed SFPIMRAC is tested, with transport delay and set-point variations in the devised respiratory model. respiratory distress patient respiratory failure model reference adaptive control set-point modulated fuzzy-based control mathematical modeling of the human respiratory system with exchange of oxygen This research received no external funding. pmc1. Introduction At present, respiratory distress may be due to different respiratory tract-infected viruses, which are mainly rhinoviruses and enteroviruses (Picornaviridae), influenza viruses (Orthomyxoviridae), parainfluenza, metapneumoviruses and respiratory syncytial viruses (Paramyxoviridae), coronaviruses (Coronaviridae), several adenoviruses, or maybe some critical medical conditions. Out of the above viruses, adenoviruses have a DNA genome, and all others possess an RNA genome . They are usually transmitted by direct hand-to-surface-to-hand contact or aerosol inhalation and replicate in both the upper and lower airways. Breathing exercise issues due to any one of the above are one of the most uncontrollable and uncomfortable conditions of humans due to any cause, such as chronic obstructive pulmonary disease(COPD), bronchitis, emphysema, fibrosis, asthma, any medical critical care condition, and so on. There also are other physical conditions with acute respiratory infection symptoms in particular for older people and immune-suppressed patients such as fatigue, reduced alertness, reduced mobility, and many more . As a result, there is a probability to reduce the oxygen saturation for the different above conditions of the patients. A longer duration of this condition may also extend to the end of an individual's life. In the damaged area of the respiratory tract, there is a secretion that is a plasma protein that accumulates on the alveolus wall and thickens the lining. This produces a blockage in the path of oxygen transfer to the red blood cells, resulting in difficulty breathing, which creates a deficiency of oxygen in the internal organs. In this condition, the deficiency of oxygen in the human body, malfunctioning of organs, and also immunity deficiency enhance the present condition, which aggravates the crisis . Mehedi, Ibrahim et al. implemented a fuzzy PID controller for mechanical ventilation processes. Tuning a fuzzy controller is a strenuous task due to the substantial number of control parameters involved. But Mehedi, Ibrahim et al. did not tune the controller, which is very much essential for critical processes such as the human respiratory system. Hansen et al. proposed the O2matic(r)-based closed-loop controlled oxygen supply in COVID time, which has limitations of flow rate and it adjusts flow every second based on 15 s averaging of SpO2 reading. To sort out this emergency crisis, a scheme is proposed in this paper to design a modified model-based adaptive controller that can automatically control the oxygen level with a faster response but without overshoot, which is also the most important part of the designed controller to protect the patient from the over-concentration of oxygen. To suppress the above problem, a set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) is proposed to control the oxygen level of respiratory distress patients without human intervention. The block diagram of the proposed scheme is shown in Figure 1. 2. Proposed Components of Respiratory Distress Treatments The basic components of the proposed model to control the oxygen supply to critical respiratory distress patients are briefed in Figure 1. In this critical time, patients with respiratory distress need to be treated with oxygen therapy to restore normal breathing and also receive proper medication support. The proposed model could be an answer to this problem due to its automatic control capability of oxygen supply to patients without much human intervention. Mathematical modeling of the proposed system components, as listed in Figure 1, is derived below for the simulation study. 2.1. Oxygen Cylinder/Oxygen Concentrator Oxygen therapy-related data with signs of severe respiratory distress, hypoxemia (i.e., SpO2 < 90%), or shock are initiated oxygen therapy at 5 L/min and titrated to SpO2 >= 90% in non-pregnant adults, and it will be SpO2 >= 92-95% in pregnant patients. A pulse oximeter measures the SpO2 level and checks the availability of an oxygen delivery system in the patient care unit . Ideally, in any hospital, oxygen is supplied to the patients from the dedicated oxygen plant only for medical applications with a percentage of O2 (not less than 99.5% v/v of O2) concentration in that hospital through piping as shown in Figure 2, but unfortunately, most hospitals and nursing homes do not have this facility, and thus they purchase oxygen cylinders from private vendors for treatment. In this paper, a typical oxygen cylinder is modeled for the simulation study. In Figure 3, the variables P1, P2, q, R, and C are the input oxygen pressure (from the oxygen cylinder), output oxygen pressure (to the patient), oxygen flow rate, resistance in the flow path (valve resistance), and capacity (patient oxygen requirement) of the system, respectively. Considering the above parameters, the mathematical equation is formed using the electrical analogy. (1) P1-P2R=CdP2dt The transfer function of the oxygen cylinder (TFcy) is derived by the Laplace transform of Equation (1). (2) TFcy=P2(S)P1(S)=1RCS+1=1t S+1 Equation (2) states that if a patient has severe breathing issues and needs more oxygen, then the C-value will be higher, which will make the R-value lower (i.e., the percentage of valve opening connected to the oxygen cylinder will be higher) or vice versa. In the present work, the value of the time constant (t = CR) for the simulation study is considered as 0.50 s. and its reason is studied in the result section; however, it can work for other values also. The regulation of oxygen supply is manipulated by the valve opening (here, a change in R-value). An instant supply of oxygen is very much essential for the treatment of uncontrolled acute breathing problems and thus needs immediate attention to improve and stabilize the SpO2 level. In emergency times, when traditional compressed-oxygen cylinders provide a limited amount of oxygen, it is better to equip each hospital with an oxygen concentrator/oxygen plant. Oxygen concentrators operate by drawing air from the environment to deliver a clean, continuous flow at a concentration of oxygen in the range of 82-96%. It would be better to use a high-efficiency particulate air (HEPA) filter with an oxygen concentrator to create a more protected environment for the patients. The Institute of Environmental Sciences and Technology dictates that a HEPA filter must trap 99.97% of particulates of 0.01 microns or larger, whereas the average size of any virus is not less than around 0.123 microns . 2.2. Pulse Oximeter A pulse oximeter is used to measure the oxygen concentration in a patient's blood in a non-invasive manner. The output of the pulse oximeter signal is fed to the comparator to monitor oxygen therapy in this proposed model, as outlined in Figure 1 . 3. Mathematical Model of Respiratory System The airway of the human respiratory system, comprising the nose, mouth, pharynx, larynx, trachea, bronchi, and alveoli, carries air between the lungs and the body's exterior. In this paper, the human respiratory system is modeled in two halves. In the first part of the model, the flow of oxygen from the oxygen concentrator/cylinder to the alveoli passing through the nasal cavity, trachea, and bronchi is considered . Gas exchange in the human respiratory system is modeled in the next part . Moreover, a variable transport delay is included in the model to increase effectiveness. The critical respiratory infection makes the alveolar sacs in the lungs stiff and thick. This degraded condition of the tissues makes it harder for O2-CO2 exchange to take place through the walls of the alveoli with the bloodstream. Thus, the alveolar sacs stiffen, and as a result, the characteristic compliance of the alveoli decreases . 3.1. Respiratory Model Part I The human respiratory system is broadly divided into four subgroups, starting with the nasal cavity, as shown in Figure 4. The next three subgroups, i.e., trachea-bronchial trees, are further subdivided into 24 generations (Table 1) . In Table 1, generation '0', generation 1 to 19, and generation 20 to 23 correspond to the trachea, bronchi, and alveolar sacs, respectively. In this model, each branch of a given generation is further subdivided into two identical daughters; therefore, generation 'n' has 2n branches . The electrical equivalence of each generation in terms of resistance (R), inertance (L), and compliance (C) is derived as shown in Table 1 . The transfer functions of the respiratory parts are derived from their electrical equivalent model, as depicted in Figure 4. The corresponding values in terms of R, L, and C, and their combinations, are presented in Table 2 . Different sub-groups of Figure 4 are then modeled in terms of transfer functions as follows: (3) TFN=1/(2.7x10-3S2+2.165S+1) (4) TFT=1/(3.7x10-4S2+5.4x10-3S+1) (5) TFB=1/(1.44x10-5S2+4.02x10-4S+1) (6) TFA=1/(6.72x10-8S2+5.71x10-4S+1) Change in Respiratory Model Due to Defect in Alveoli Area Abnormality in the alveoli area can be reflected in the developed model in terms of a decrement in the capacitance value of the alveoli by about 100 to 1000 times, which means that the effective impedance Z=R2+(XL-XC)2 of the circuit will increase. The model of the alveolar section represented by Equation (6) thus gets modified to:(7) TFA'=1/(1.0x10-10S2+1.15x10-6S+1) where TFA' refers to the transfer function of the alveolar section of a respiratory distress patient being affected by any of the above-mentioned viruses/critical medical conditions. The resultant model, TFM is derived from the series of combinations of the individual models, i.e., (8) TFM=TFN*TFT*TFB*TFA' 3.2. Respiratory Model Part II (Gas Exchange) From Figure 5, it is seen that the gas exchange takes place in the area of alveolar air space, lung tissue, and capillary blood accordingly. In the case of the diffusion process, the movement of the gas from a high-concentration region to a low-concentration region is followed by the gradient profile . This principle is followed during respiration, where gas exchange occurs between the blood and lungs. During this time, the concentration of oxygen is high and the carbon dioxide concentration is low in the blood, which undergoes the gas exchange with air in the lungs with a higher gradient profile than the blood. This process is the opposite of the expiration process . Each of the alveoli is surrounded by a network-like structure of very small blood vessels of diameter 5 to 10 mm. For a normal person, under resting conditions, the volume of air available for gas exchange corresponds to the alveolar zone, which sums up to around 2.5 to 3 L, and the volume of blood in the neighborhood of the exchange surface is around 70 mL . 3.3. Partial Pressure Model The concept of partial pressure is adopted to develop the mathematical model of the gas exchange part of the respiratory system. Mathematically, to find out the individual components' concentration in a mixture of gases, the partial pressure measuring method is used here, and the total pressure is calculated by the sum of the individual components . The rate of diffusion of a gas is measured by its partial pressure within the total gas mixture, and they are linearly related. In this gas exchange model, the partial pressures for the alveolar air, lung tissue, and capillary blood are illustrated by po2A, po2T, and po2B respectively . The diffusion of oxygen, as shown in Figure 5, across lung tissue/alveolar air barriers and the lung tissue/capillary blood is modeled as follows:(i) Oxygen diffusion from alveolar air space to lung tissue: (9) dpo2Adt=DTAsAVA(po2T-po2A) (ii) Similarly, oxygen exchange between lung tissue, alveolar air space, and capillary blood is derived by: (10) dpo2Tdt=DTBsTVT(po2B-po2T)+DTAsTVT(po2A-po2T) (iii) Oxygen transfer between lung tissue and capillary blood: (11) dpo2Bdt=DTBsBVB(po2T-po2B) VA, VT, and VB are the respective volumes of alveolar air space, lung tissue, and capillary blood. The parameters sA, sT, and sB are used to convert the partial pressure of oxygen in alveolar air space, lung tissue, and capillary blood regions to their corresponding molar concentrations, respectively. In the model, the diffusion rates for lung tissue to alveolar air and lung tissue to capillary blood are illustrated by DTA and DTB, respectively. The different parameter values of the model are presented in Table 3. The gas exchange with the capillary blood is a very complex process. Ideally, different biological processes are functioning in this process of gas exchange, such as diffusion of oxygen and carbon dioxide, hemoglobin uptake of oxygen, and enzymatic reactions governing carbon dioxide and bicarbonate levels . However, to make the model simple, in this work, only the rate of oxygen transfer is assumed, and some assumptions are considered as follows: Assumptions: (i) Diffusion takes place in only two zones: capillary blood/lung tissue and lung tissue/alveolar air space. (ii) The alveolar air space must be well mixed. (iii) The same diffusion rate is considered here for each section of the gas exchange module (iv) and the continuous supply of oxygen is achieved by the ventilation process that provides fresh oxygen to the lungs, whereas venous blood is periodically pumped onto the exchange zone by the heart. Electrical Analogy Model An electrical equivalent circuit of Figure 5 is drawn in Figure 6. Considering the flow of oxygen as current flow, the following equations are derived from Figure 6:(i) Flow of oxygen from the alveolar air space (AA) to the lung tissue (LT): (12) dvAAdt=vLT-vAARACA (ii) Oxygen exchange between lung tissue (LT), alveolar air space (AA), and capillary blood (CB): (13) dvLTdt=vCB-vLTRTCT+vAA-vLTRACT (iii) Oxygen transfer between LT and CB: (14) dvCBdt=vLT-vCBRBCB The following equation parameters are derived from a careful comparison of Equations (12) to (14) with (9) to (11) and the data in Table 3:RACA = 1/0.2429, RACT = 1/4.76, RTCT = 1/15.87, and RBCB = 1/88.88 The ultimate gas exchange model (TFBO2) due to the diffusion of oxygen in the capillary blood is calculated by the Laplace transform of Equations (12) to (14). The transfer function (TFBO2) is derived by putting the corresponding resistance and capacitance values in Equation (15). (15) TFBO2=(20s2+200s+62)/(s3+110s2+350s+67) The ultimate human respiratory system (TPM) in the infected area of the alveoli of the patient is modeled by a series combination of the models (TFM) and (TFBO2). (16) TPM=TFMxTFBO2 The stability of the model is checked by the Bode plot in Figure 7. The positive values of gain margin (Gm) and phase margin (Pm) ensure that the respiratory model is a stable system. 3.4. Transport Delay To make the model more realistic, in this study, a variable transport delay is included between the respiratory model and the gas exchange model. The study is carried out with various transport delays, as the time taken in gas exchange is not fixed in respiratory infected patients; it varies depending on the severity. 4. Design of the Proposed Controller In this section, the design part of the proposed set-point modulated fuzzy PI model reference adaptive controller (SFPIMRAC) is elaborated. Initially, the developed respiratory model for the respiratory distress patient is tested with a conventional PID controller and MRAC to control the oxygen supply and later MRAC is modified by incorporating the knowledge of fuzzy logic with a set-point tracking facility. 4.1. Design of MRAC The basic concept of the MIT rule is applied to the design of the MRAC to control the oxygen supply to respiratory distress patients with respiratory infections associated with breathing problems. A basic scheme of MRAC is illustrated in Figure 8. Optimization of control parameters to minimize the loss function is very important in any controller development. In this paper, the difference between patients' output (y) (pulse oximeter reading) and the model process output (ym) is measured in terms of error (e) as pictured in Figure 8. In the case of MRAC, there are two parameters: the adaptation gain (g1) control and adjustable control parameter (th) is the most important part of the design. A suitable adjustment mechanism of (th) that makes the measured error (e) to a value zero is also used to minimize the loss function F(th), as shown in Figure 8 . (17) F(th)=e22 Minimization of loss function F(th) is derived from the variation of the parameter th in the direction of the negative gradient of F(th) and adaptation gain (g1), i.e., (18) dthdt=-g1Fth=-g1eeth where e/th is expressed as the sensitivity of the system. For the large process, there are many numbers of process variables such as (th1, th2, etc.) where Equation (18) can also be applicable. But in that case, output (th) should be taken as a vector quantity in place of scalar one and mathematically the gradient of the error concerning the parameters concept is used to calculate its partial derivative e/th . In Figure 8, the patient and the reference models are represented by KG(s) and K0G(s), respectively (where K is an unknown and K0 is a known parameter). The output of the patient (y) always tracks the reference model output (ym). From the scheme shown in Figure 8, the process output (y), model output (ym), and error (e) are derived as follows:(19) y=u.KG(s)=r.th.KG(s) (20) ym=rK0G(s) (21) e=y-ym=rthKG(s)-rK0G(s) From (20):rG(S)=ymK0 where u is the controller output and r is the input to the reference model. The calculation of e/th is derived by taking a partial derivative of (21). (22) eth=rKG(s)=K.ymK0=(K/K0)ym Finally, the equation for adjusting the parameter variation in (18) is modified by (22). (23) dthdt=-g1eeth=(g1K/K0)yme=-gyme From Figure 8, it is observed that the final output of the controller, or basically input to the process u [u = rth] is obtained by the product of the reference input (r) with the adjustable control parameter (th), which is obtained by integrating (dth/dt). In Equation (23), the value of adaptation gain (g1) is a user-defined parameter that is a positive number, and its value depends on the process model . The choice of exact adaptation gain (g1) is one of the most difficult steps in MRAC. To eliminate this difficulty, a set-point modulated fuzzy PI-based scheme is incorporated with MRAC to control the oxygen supply for respiratory distress patients. 4.2. Design of Set-Point Modulated Fuzzy PI-Based MRAC A hybrid fuzzy PI logic is adopted for automatic gain adjustment of the controller. The two dynamic parameters (error and change of error) are used as the input parameters of the fuzzy system, as shown in Figure 9. 4.2.1. Fuzzy PI for Adaptive Gain (m) Adjustment It is seen from Figure 9 that the output of the designed fuzzy PI model (m) is a function of the input variables (e, De) and linguistic if-then rules. Here m is used as the alternative of the adaptation gain (g1) in the case of MRAC. A very simple, linear, equal base width, and widely used triangular type of fuzzy membership functions with the span of [-100, +100] are used for the inputs (e and De) and the span of [-1, +1] for output (m), and five fuzzy regions (termed negative big (NB), negative medium (NM), zero (ZE), positive medium (PM), and positive big (PB)) are used to develop the database and rule base of the proposed fuzzy scheme as shown in Figure 10 and Figure 11 . The adaptation gain 'm' as per Equation (24) depends on the input variables (e, De and the rule base, which consists of 25 fuzzy linguistic if-then rules shown in Table 4. The control parameter 'th' is derived by applying Equation (25) . (24) m=f (e ,De) (25) th=(-1)xmxy=-mym The analysis of the control surface of fuzzy PI (e, De vs. m) reveals the smoothness of the surface, which is very much essential for the smooth operations of the control equipment present in the loop. The study of Figure 12 and Table 5 discloses that the output (m) of the system depends on the input system parameters (e, De). The capability of the controller is established from the analysis conducted in Table 5. In this design, the adaptation gain (g1) of MRAC is replaced by m, which auto-tunes the control parameter (th = -mym), for the right amount of oxygen supply to the patients. The effectiveness of the proposed controller is further enhanced by incorporating the set-point modulated scheme with fuzzy PI gain adjustment . 4.2.2. Proposed Scheme (SFPIMRAC) The final control output u, as shown in Figure 11, is derived as the product of control output (th) and dynamic set-point r (26) u=r'xth But the dynamic set point (27) r'=r-e In the above Equations (26) and (27), the original set-point and error variables are symbolically represented as 'r' and 'e', respectively. The consequence of the new dynamic set-point on the proposed system is tabulated in Table 6. From Equations (25) and (26), it is seen that due to the dynamic variation of the inputs (e, De) of fuzzy PI, the adaptation gain (m) and final control output (u) are also altered accordingly . As the reference set-point (r) is a fixed value, the dynamic set-point (r) is modulated only by the temporary increase or decrease in the process error (e). This mechanism of set-point variation is used to boost the system's performance. It is seen from Table 6 that if the error is zero (steady-state condition), there is no variation in the dynamic set-point because r = r. In cases of undershooting or at the beginning, when the process variable tries to catch the set-point, the error is positive during that period, which indicates that the system needs more oxygen supply, which can be conducted by increasing the set-point (r'=r+e), which in turn increases the control output (u=r'xth).With the same principle, in the case of overshooting, the error is negative, and that helps to decrease the control output. 5. Results and Discussion The effectiveness of the proposed controller (SFPIMRAC) is investigated to control oxygen supply to respiratory distress patients. The proposed simulation work is demonstrated using a software tool (MATLAB R2009/SIMULINK) with the following reference (TRM) and process model (TPM). Reference Model: TRM=1S2+2.5S+1Process Model: TPM=TFMxTFBO2 As far as patient conditions are concerned, the requirement for oxygen concentration varies from patient to patient, from mild to severe. The SpO2 reading in the oximeter varies depending on the severity of the infection of the respiratory tract, and the reading in severe respiratory distress patients falls below 90%. In this context, to show the effectiveness of the proposed controller, two set points (90% and 95%) are pondered in this study. The open-loop step excitation response for both the normal respiratory model and the infected respiratory model is investigated in Figure 13. It is realized that in the case of the developed model, the response never reached the desired level without any control action. The choice of a proper time constant for a process is a difficult task. A comparative study of the different time constants in terms of the RC value of the oxygen cylinder model is highlighted in Figure 14. The study reveals that at a time constant value of 0.50 s, the developed respiratory model performs better compared to other values. Moreover, the performance of MRAC with different adaptive gains (g1) is investigated in the developed model. The adaptive gain in MRAC and its consequent effects are observed in Figure 15. A change in adaptation gain in MRAC makes the system highly oscillatory; as a result, it fails to reach the desired value quickly, which could be lethal for respiratory distress patients. Sometimes an excess supply of oxygen may create an unhealthy situation. The exact adjustment of adaptation gain in MRAC is a crucial problem, whereas in the SFPIMRAC, there is no need for any human intervention to control the oxygen concentration properly for the respiratory distress patient. The responses for conventional PID, MRAC, and SFPIMRAC are compared. The analysis of Figure 16 (set point 95% SpO2) and Figure 16a (set point 90% SpO2) reveals that the proposed SFPIMRAC is far more suitable than MRAC and conventional PID in severe respiratory distress patients. The variations in oximeter readings (% SpO2) did not impact the proposed controller performance divulged in Figure 16 and Figure 17. The model's performance with variations in the set point (oximeter reading) and time delay are also depicted in Figure 18 and Figure 19. A PID controller is not suggested here, as over-concentration of oxygen can be lethal to patients considered here. The SFPIMRAC response is better than the MRAC response in terms of faster response, low settling time, and no overshoot, which is the most desirable condition in respiratory distress treatment. The parameters of the human respiratory system model may change depending on the types of obstructive and restrictive lung diseases. The effectiveness of the proposed controller is tested with model parameter variations successfully with minimum deviations in responses. The original gas exchange model (TFBO2) is expressed in Equation (15): TFBO2=20s2+200s+62s3+110s2+350s+67. The responses of three different models (model1, model2, and model3) are shown with slight parameter variations in Equation (15), as observed in Figure 18 for a reference value of 95%SpO2. The convincingness of the proposed controller is further established even with human respiratory model parameter variations in Figure 18. TFBO2(model 1)=(10s2+300s+62)/(s3+110s2+350s+67) TFBO2(model 2)=(20s2+400s+62)/(s3+110s2+350s+67) TFBO2(model 3)=(20s2+400s+52)/(s3+110s2+350s+67) 5.1. SFPIMRAC Response with Time Delay at Input and Set-Point/Load Variations The effects of time delay and set-point/load variations at the input of the process (respiratory model of a severe patient, TPM) are observed in Figure 19 and Figure 20, respectively. Figure 19 revealed that a time delay in patients' treatment is not a good idea, though the proposed controller streamlines the flow within a few seconds. During treatment, if the SpO2 level falls below the desired value for any unwanted reason, the proposed controller can deliver the required oxygen again immediately without any human intervention, even with the presence of a time delay. 5.2. SFPIMRAC Response with Atime Delay between Two Models and Set-Point/Load Variation Figure 21 depicts the proposed controller being tested with the concept of time delay (delay due to gas exchange in infected alveolar conditions) in between primary and secondary respiratory models. The typical time delay for human respiratory gas exchange is 0.75 s at rest (transport delay of 0.30 s for inspiration and 0.45 s for expiration), and during exercise, this value comes down to 0.25 s . Given this different time delay in different conditions, the proposed controller is tested with 0.30 s, 0.50 s, and 0.70 s intermediate time delays. The proposed SFPIMRAC can counteract the gas exchange time variations and even load/set-point variation, as successfully shown in Figure 22. The proposed controller model can be useful for other simulated and real-time processes. The real-time practical implementation of the developed controller was already demonstrated successfully on a laboratory-based overhead crane [Make: FEEDBACK, UK] for both position and swing control . The control of load pendulation in an overhead crane is a very difficult task. The control strategy for the swing angle control of the overhead crane is implemented and shown in Figure 23 . A comparative study of the set-point modulated fuzzy PD-based model reference adaptive controller (SFMRAC) with the other controllers for the overhead crane model to control swing angle is illustrated in Figure 24 . 6. Conclusions An integrated mathematical model of the human respiratory system is presented in this paper for the treatment of a critical patient suffering from respiratory distress. The consideration of inherent time delays caused by the gas exchange between alveolar air space, lung tissue, and capillary blood cells added a new dimension to this study. The efficacy of the mathematical model is verified with model parameter variations, set point changes, inserting different time delays, and stability analysis. The whole study was performed in a MATLAB Simulink environment, and we performed a spirometry test in the laboratory for future studies. The human respiratory system itself exhibits the properties of regulatory control. However, this inherent regulation of the respiratory system sometimes fails due to the attack of various viruses. One of the most popular treatments for patients with lung infections is oxygen support. In this paper, for the proper regulation of external oxygen, a new control strategy is proposed based on the model reference adaptive controller. However, the effective control by MRAC purely depends on the adjustment of the adaptive gain factor. To remove this inherent problem of gain adjustment, a fuzzy knowledge-based system is initiated for the dynamic change of adaptive gain that varies with variations of respiratory system parameters. Two useful concepts are combined to improve controller design: one is a fuzzy-based MRAC scheme, and the other is a dynamic variation of the set-point that is used to automatically track variations in the process parameter. The proposed controller, SFPIMRAC, is tested on different respiratory conditions effectively, and its performance is judged with various time delays and also with load changes. All these advantages of the proposed controller make it suitable for the supplement of oxygen to respiratory distress patients suffering from acute breathing problems. In this context, it is very difficult to conclude about the effectiveness of oxygen therapy and control, but surely it can be used as a supportive treatment. Although respiratory distress of the respiratory system appears to be a complex disease, this research provides some promising avenues for future research. Author Contributions All authors have equally contributed in terms of conceptualization, methodology, software, validation, formal analysis, resource, writing and reviewing, and visualization. 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 Basic block diagram of the proposed model. Figure 2 Oxygen supply system near to patient side. Figure 3 Oxygen cylinder model with input-output. Figure 4 Equivalent electrical R, L, and C model of the human respiratory system. Figure 5 Schematic representation of the simple oxygen exchange model. Figure 6 Electrical equivalent circuit diagram of the gas exchange model. Figure 7 Stability analysis of the proposed model. Figure 8 MRAC model to control oxygen concentration for acute respiratory distress patients. Figure 9 Proposed SFPIMRAC model. Figure 10 MFs for e and De. Figure 11 MFs for adaptation gain (m). Figure 12 The control surface of fuzzy PI (e, De vs.m). Figure 13 Comparative study of healthy and infected patient with step input at 95%. Figure 14 Comparative studies of different time constants of oxygen cylinder model with the proposed controller. Figure 15 Responses with MRAC for set-point at 95% SpO2. Figure 16 Comparative studies between PID, MRAC, and SFPIMRAC with set-point at 95% SpO2. Figure 17 Comparative studies between PID, MRAC, and SFPIMRAC with set-point at 90% SpO2. Figure 18 Process responses with SFPIMRAC for model parameters variations. Figure 19 Process responses with SFPIMRAC with different time delay. Figure 20 Process responses with SFPIMRAC for time delay and load/set-point variations. Figure 21 Response with SFPIMRAC for transport delay and load/set-point variations. Figure 22 Simulink model of SFPIMRAC with transport delay in between respiratory model and gas exchange model. Figure 23 Design of SFMRAC for swing angle control in MATLAB Simulink. Figure 24 Performance response with PD, MRAC, FPDC, and SFMRAC in swing angle control. diagnostics-13-00967-t001_Table 1 Table 1 Geometrical dimensions of the morphological model of the respiratory system. Generation Number Number of Airways Per Generation Airways Diameter in cm Length in cm Total Airways Area in cm2 Avg. Air Flow Velocity in cm/s Resistance in cm of H2O/L ltr./s Calculated Using Formula Inertance in cm of H2O/L/s2 Calculated Using Formula Compliance in ltr./cm of H2O Calculated Using Formula z n(z) d = 2r l s u 8 mL/pr4 rL/s ls/rn(z)u2 0 1 1.8 12 2.54 197 0.0086 0.0059 0.06311 1 2 1.22 4.76 2.33 215 0.008 0.0025 0.0964 2 4 0.83 1.9 2.13 236 0.0075 0.0011 0.0145 3 8 0.56 0.76 2 251 0.0072 0.0004 0.0024 4 16 0.45 1.27 2.48 202 0.0145 0.0006 0.0038 5 32 0.35 1.07 3.11 161 0.0167 0.0004 0.0032 6 64 0.28 0.9 3.96 126 0.0172 0.0002 0.0028 7 128 0.23 0.76 5.1 98 0.0159 0.0001 0.0025 8 256 0.186 0.64 6.95 72 0.0157 0.0001 0.0026 9 512 0.154 0.54 9.56 52 0.0141 7.03 x 10-5 0.0029 10 1024 0.13 0.46 13.4 37 0.0118 4.27 x 10-5 0.0035 11 2048 0.109 0.39 19.6 26 0.0101 2.48 x 10-5 0.0044 12 4096 0.095 0.33 28.8 17 0.0074 1.43 x 10-5 0.0064 13 8192 0.082 0.27 44.5 11 0.0054 7.55 x 10-6 0.0097 14 16,384 0.074 0.16 69.4 7.2 0.0024 2.87 x 10-6 0.0105 15 32,768 0.05 0.13 117 4.3 0.0048 1.41 x 10-6 0.0206 16 65,536 0.049 0.11 225 2.2 0.0022 6.19 x 10-7 0.0638 17 131,072 0.04 0.09 300 1.7 0.002 3.86 x 10-7 0.0591 18 262,144 0.038 0.08 543 0.92 0.0011 1.90 x 10-7 0.1632 19 524,288 0.036 0.07 978 0.51 0.0005 8.91 x 10-8 0.4034 20 1,048,576 0.034 0.07 1740 0.29 0.0003 5.01 x 10-8 1.1099 21 2,097,152 0.031 0.07 2730 0.18 0.0002 3.19 x 10-8 2.26 22 4,194,304 0.029 0.67 5070 0.99 0.0016 1.64 x 10-7 0.664 23 8,388,608 0.025 0.07 7530 0.66 0.0001 1.24 x 10-8 0.1241 diagnostics-13-00967-t002_Table 2 Table 2 R, L, and C values. Different Section of Human Respiratory System R H2O/ltr/s L H2O/ltr/s2 C ltr/cm of H2O RC LC NASAL CAVITY 16.332700 0.0200000000 0.1320 2.156000 0.00270000000 TRACHEA 0.086000 0.0059000000 0.0631 0.005400 0.00037000000 BRONCHI 0.008700 0.0002929000 0.0461 0.000402 0.00001440000 ALVEOLI 0.000550 0.0000000647 1.0396 0.000571 0.00000006720 diagnostics-13-00967-t003_Table 3 Table 3 Parameters values of the gas exchange model. Parameters Alveolar Air Tissue Capillary Blood Volume (L) VA = 1.9 x 10-7 VT = 4.2 x 10-8 VB = 7.5 x 10-9 Molar concentration (M/mm) sA = 2.5 x 10-5 sA = 1.2 x 10-6 sB = 1.2 x 10-6 Diffusion rate (L/s) DTA = 2.4 x 10-12 DTA = (6.7 - 10) x 10-12 diagnostics-13-00967-t004_Table 4 Table 4 Rules for computing fuzzy output. e/De NB NM ZE PM PB NB NB NB NB NM ZE NM NB NB NM ZE PM ZE NB NM ZE PM PB PM PM PM PM PB PB PB PM PM PB PB PB diagnostics-13-00967-t005_Table 5 Table 5 Study of control surface . e = (y - ym) De m Output (th = -mym) +ve (high); y > ym +ve (high) +ve (high) -ve/ need to decrease oxygen flow as y > ym 0; y = ym 0 0 No change in oxygen flow, maintain the same flow -ve (high); y < ym -ve (high) -ve (high) +ve/ need to increase oxygen flow as y < ym diagnostics-13-00967-t006_Table 6 Table 6 Mathematical representation of set-point variations. e r' = r + e Remarks +ve r'-+ve r' > r -ve r'-+ve e < r and r' < r zero r' = r r' = r 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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PMC10000381 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050699 cells-12-00699 Article The Protein Network in Subcutaneous Fat Biopsies from Patients with AL Amyloidosis: More Than Diagnosis? Di Silvestre Dario Conceptualization Writing - original draft Writing - review & editing Supervision 1* Brambilla Francesca Methodology Formal analysis 1 Lavatelli Francesca Methodology Writing - review & editing 23 Chirivi Maila Methodology Validation 45 Canetti Diana Methodology Formal analysis 6 Bearzi Claudia Methodology Validation 17 Rizzi Roberto Methodology Validation 78 Bijzet Johan Methodology Resources 910 Hazenberg Bouke P. C. Methodology Resources 910 Bellotti Vittorio Writing - review & editing 611 Gillmore Julian D. 6 Mauri Pierluigi 1* Chaari Ali Academic Editor Outeiro Tiago Fleming Academic Editor 1 Institute for Biomedical Technologies (ITB), Biomedical Sciences, National Research Council (CNR), 20054 Segrate, Italy 2 Department of Molecular Medicine, University of Pavia, Via Forlanini 6, 27100 Pavia, Italy 3 Fondazione IRCCS Policlinico San Matteo, Viale Golgi 19, 27100 Pavia, Italy 4 UOC Neurology, Fondazione Ca'Granda, Ospedale Maggiore Policlinico, Via F. Sforza, 28, 20122 Milan, Italy 5 Department of Molecular Medicine, Sapienza University, Viale Regina Elena, 324, 00161 Rome, Italy 6 Centre for Amyloidosis, Division of Medicine, University College London, London NW3 2PF, UK 7 Fondazione Istituto Nazionale di Genetica Molecolare, Via F. Sforza 35, 20122 Milan, Italy 8 Department of Medical Surgical Science and Biotecnologies, Sapienza University, 04100 Latina, Italy 9 Amyloidosis Center of Expertise, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands 10 Department of Rheumatology & Clinical Immunology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands 11 Scientific Direction, Fondazione IRCSS Policlinico San Matteo, 27100 Pavia, Italy * Correspondence: [email protected] (D.D.S.); [email protected] (P.M.) 22 2 2023 3 2023 12 5 69931 1 2023 11 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 ). AL amyloidosis is caused by the misfolding of immunoglobulin light chains leading to an impaired function of tissues and organs in which they accumulate. Due to the paucity of -omics profiles from undissected samples, few studies have addressed amyloid-related damage system wide. To fill this gap, we evaluated proteome changes in the abdominal subcutaneous adipose tissue of patients affected by the AL isotypes k and l. Through our retrospective analysis based on graph theory, we have herein deduced new insights representing a step forward from the pioneering proteomic investigations previously published by our group. ECM/cytoskeleton, oxidative stress and proteostasis were confirmed as leading processes. In this scenario, some proteins, including glutathione peroxidase 1 (GPX1), tubulins and the TRiC complex, were classified as biologically and topologically relevant. These and other results overlap with those already reported for other amyloidoses, supporting the hypothesis that amyloidogenic proteins could induce similar mechanisms independently of the main fibril precursor and of the target tissues/organs. Of course, further studies based on larger patient cohorts and different tissues/organs will be essential, which would be a key point that would allow for a more robust selection of the main molecular players and a more accurate correlation with clinical aspects. amyloidosis proteomics systems biology networks PPI co-expression Cariplo Telethon GJC20212022-0578 This work was supported by Cariplo Telethon GJC2021 n. 2022-0578. pmc1. Introduction Amyloidosis is characterized by the misfolding of circulating proteins, which are progressively deposited at the extracellular level as insoluble amyloid aggregates. The relationship between the site of production of the fibril precursor protein and its deposition allows for the distinction between localized and systemic amyloidosis, although some amyloidoses show both systemic and local features. Their current classification is based on the amyloid protein type, and, to date, 42 human amyloid fibril proteins have been identified in humans . This knowledge is improving its diagnosis and, although systemic amyloidosis is classified as rare diseases, the increasing incidence in the elderly population could soon make it a new global health socio-economic problem . The deposition of amyloid aggregates can occur in several organs, including the heart, which can be severely affected in structure and function, becoming the major survival determinant . The process of amyloid formation and organ targeting and damage is multifaceted and still largely unknown. This makes understanding the pathogenic cascade complex and its control a challenge . Due to the progressive nature of the disease, early diagnosis is therefore vital, and many studies have been made toward this aim . For instance, patients with advanced heart damage have a significantly poorer outcome and more limited access to the most aggressive, yet most efficacious treatments . To date, the diagnosis and typing of the systemic amyloidosis are performed, respectively, by Congo red staining and the mass spectrometry (MS)-based proteomics analysis of tissue biopsies, mainly subcutaneous fat aspirates . No specific biomarkers of organ damage to specifically differentiate the distinct amyloidoses forms exist. However, several studies have been recently published, mainly for cardiac amyloidosis, focusing on classifying amyloid types based on circulating microRNAs , protein markers and oligomers . As for amyloidosis typing, amyloid deposits are often laser microdissected from biopsies prior to MS analysis . If, on one hand, this sampling allows for the identification of non-fibrillar proteins enriched in the amyloid deposit, on the other hand, it is not sufficiently representative of molecular and histological alterations induced in tissue resident cells by the deposition of extracellular amyloid aggregates. Thus, although microdissection aims to improve diagnosis, it has led to a poor collection of -omics profiles at global organ and tissue level. Consequently, the integration of comprehensive multi-omics analyses to dissect pathological mechanisms in systemic amyloidosis is limited to few reports . Most studies rely on proteomics data , while some of them have recently focused on RNAseq analysis and differentially expressed genes (DEGs), both in cultured cardiomyocytes exposed to amyloidogenic light chains and in plasma cells from immunoglobulin light chain (AL) amyloidosis patients and normal controls . Omics technologies and network analysis give the opportunity to investigate human diseases through data-derived system biology approaches based on graph theory . When applied to complex tissues, these approaches provide the chance to evaluate, at a global level, the pathophysiological processes underlying the investigated phenotypes . In the context of protein misfolding diseases, fruitful application examples are available for neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases . Conversely, far fewer similar studies have been conducted analyzing biopsies from patients affected by systemic amyloidosis . To fill this gap, in this perspective study, we investigated the proteome changes in abdominal subcutaneous adipose tissue of patients affected by AL amyloidosis at a system level. Along with transthyretin (TTR), myocardial infiltration by immunoglobulin light chains is the major cause of cardiac amyloidosis . In addition to helping to shed light on pathogenic mechanisms subtending AL subtypes, we provided a pipeline for evaluating how protein fibril deposition might affect the physiological protein relationships in a tissue. To reach this goal, we exploited the correlation between a protein network's structure and the functions that it supports . Therefore, the knowledge previously acquired through protein profiling and quantitation was here integrated with the new insights inferred by modeling the proteome as protein-protein interaction (PPI) and co-expression networks. In particular, these models were combined and analyzed at a topological and functional level . AL amyloidosis patients were further split into two groups based on amyloid typing as AL k or l type. This classification aimed to verify the correlation between different AL subtypes and the pathogenic mechanisms that they could trigger. 2. Materials and Methods 2.1. Collected Samples, Proteomic Analysis and Preliminary Functional Analysis Abdominal subcutaneous adipose tissue protein profiles previously collected and analyzed were re-processed and used as reference dataset . Specifically, n = 14 control subjects, n = 15 patients affected by ALk amyloidosis and n = 15 patients affected by ALl amyloidosis were considered to create a larger cohort of profiles never evaluated all together in a single study. Major details on samples origin, MS analytical parameters and raw mass spectra processing are reported in Supplementary Material. A preliminary functional evaluation of the characterized protein profiles was performed by functional annotation tool contained in STRING database . For each subject, enriched Reactome pathways were retained (FDR <= 0.05) . They were compared by linear discriminant analysis (LDA) and those with F ratio >=5 and p-value <= 0.01 were selected as differentially enriched among C, ALk and ALl groups. 2.2. Label-Free Quantitative Analysis The characterized protein profiles were semi-quantitatively compared by a label-free approach, as previously reported . To minimize the batch effect of samples collected at different times and analyzed with different instruments and methods, the spectral count (SpC) values were normalized using a total signal normalization method . Data matrix dimensionality (44 subjects and 4319 proteins) was reduced by LDA and proteins with F ratio >= 3 and p-value <= 0.05 were selected as differentially abundant (DAPs); of note, to ensure a robust extraction of differentially abundant proteins (DAPs), only those identified in at least 50% of subjects were retained. Selected DAPs were further processed by principal component analysis (PCA) and Spearman's correlation. Pairwise comparisons were finally evaluated by DAve index (see Supplementary Material). All data processing were performed using JMP 15.2 SAS software. 2.3. Reconstruction and Analysis of PPI and Co-Expression Network Models A PPI network model per group (C, ALk and ALl) was reconstructed by considering proteins identified in more than 50% of subjects (per group). The network models were reconstructed by STRING Cytoscape's APP and only protein-protein interactions annotated with "databases" and/or "experiments" with a score >=0.3 and >=0.15 were retained. Similarly, a PPI network model was reconstructed starting from DAPs selected by LDA (n = 132, p <= 0.05). The proteins were grouped in PPI functional modules by the support of STRING Cytoscape's APP and BINGO 2.44 ; Homo sapiens organism, hypergeometric test and Benjamini-Hochberg FDR correction (<=0.01) were set. A protein co-expression network model per group was reconstructed processing the characterized protein profiles by Spearman's rank correlation coefficient; only scores obtained by matching a number of measures (SpCs > 0) per protein pair greater than 50% of the subjects (per group), and with p <= 0.05, were considered. In addition, the same subset of proteins (n = 41, identification frequency = 100% per group) was processed to evaluate how the correlation changes between protein pairs in C, ALk and ALl groups. 2.4. Topological Analysis of PPI and Co-Expression Network Models 2.4.1. Hubs Selection Both reconstructed PPI and co-expression models were analyzed at topological level by Centiscape Cytoscape's APP , as previously reported . Diameter, average distance, degree, betweenness, centroid, stress, eigenvector, bridging, eccentricity, closeness, radiality and edge centralities were calculated for ppi network models, whereas diameter, average distance and degree were calculated for co-expression models. As for PPI models, nodes with both betweenness and centroid values above the average were considered hubs, whereas co-expression hubs were selected based on degree . Statistical significance of topological results was tested by randomized network models ; n = 1000 random models per group were reconstructed and analyzed by in-house R scripts based on VertexSort (to build random models), igraph (to compute centralities) and ggplot2 (to plot results) libraries. 2.4.2. Topological and Functional Modules Selection CytoCluster Cytoscape's APP and ClusterONE algorithm were used to extract protein co-expression modules (p <= 0.01) from C, ALk and ALl models reconstructed from proteins identified in all subjects (n = 41, identification frequency = 100%); minimum size = 3, minimum density = "auto" and edge weights = Spearman's rank correlation coefficient were set. Network models reconstructed by matching PPI ("databases"-annotated PPIs, score >= 0.3; "experiments"-annotated PPIs, score >= 0.15) and co-expression (Spearman's rank correlation coefficient >= |0.5|, p <= 0.05) networks were analyzed by Community Detection Cytoscape's APP ; HiDeF 1.1 beta algorithm (maximum resolution parameter = 25, consensus threshold = 75, persistent threshold = 5), while functional enrichment (reactome pathways) of the selected topological modules was performed by Enrichr algorithm (p <= 0.001, module size >= 4). Finally, the correlation change among subunits/proteins physically and functionally interacting in complexes and biological processes was evaluated in C, ALk and ALl groups. 2.5. Sub-Cutaneous Adipose Tissue Histological Analysis and TUBB4 Validation Paraffin-embedded sections of sub-cutaneous adipose tissue were used for histological analysis. Briefly, after some preparation steps, the samples were incubated with rabbit anti-beta tubulin IV (TUBBIV; Ab179504, Abcam, Cambridge, UK) antibody. A Leica SP5 laser scanning confocal microscope (Leica Microsystem, Wetzlar, Germany) was used to acquire labeled samples. Finally, the images were analyzed using Image J software. Statistical analysis was carried out using Prism 8 (GraphPad Software, La Jolla, CA, USA). Data are presented as mean +- standard deviation (SD). Differences between sample means were evaluated with Student's t-test (p <= 0.05). For major details, see Supplementary Material. 3. Results 3.1. Similarities and Differences in Amyloid-Deposition-Induced Proteome Remodeling in Abdominal Subcutaneous Adipose Tissue from ALk and ALl Patients A set of protein profiles previously published , and collected by analyzing the abdominal subcutaneous adipose tissue of control subjects (C) and patients affected by ALk and ALl amyloidosis, was reprocessed following the workflow shown in . Compared to the control group, ALk and ALl patient profiles were characterized by a higher number of proteins . This observation, which might have a link with an altered protein homeostasis , was associated with an enrichment in protein synthesis and metabolism we found in both AL patient's groups, along with the mitochondrial respiration chain, lipid metabolism and immune system . In ALk and ALl, we also found an enrichment in the amyloid fiber formation pathway . Conversely, processes related to microtubules and ECM were less represented, and were most significant for ALk tissues. Following a deeper analysis of the enrichment results, 132 out of 4319 total identified proteins resulted in being differentially abundant (DAPs) (Supplementary Tables S1 and S2). In addition, to confirm previously published DAPs , new ones were extracted thanks to a larger cohorts of subjects. Although there were some exceptions, the set of higher-confidence DAPs discriminated the investigated groups of subjects well. As expected, the correlation between AL groups was higher (r = 0.79) than that observed with respect to C . This value pointed out some slight differences in the modulation of the proteome when affected by the ALk or ALl isotype. These variations, and those identified in the comparison against control tissues, were classified and represented through 25 PPI functional modules . Besides what has already been shown by the enrichment analysis , in ALk and ALl, we observed the up-regulation of proteins involved in proteolysis, protein folding and REDOX homeostasis, while a small set of proteins involved in blood coagulation was down-regulated. Moreover, focusing on the comparison between AL groups, immune system and keratin-related proteins were more abundant in ALl, whereas ALk tissues showed a higher abundance of glutathione metabolism, protein synthesis and vesicle-transport-related proteins. Among the most confident differentially abundant proteins (p <= 0.01), we found glutathione peroxidase 1 (GPX1), an important antioxidant enzymes that has already been described as protective in various neurodegenerative disorders, including Parkinson's and Alzheimer's disease . It was identified in 80% and 47% of ALk and ALl tissues, respectively, whereas it was never found in the control group. Similarly, lon peptidase 1 (LONP1) and SNF2 histone linker PHD RING helicase (SHPRH) were mainly expressed in ALl tissues (53% and 67%, respectively), and erythrocyte membrane protein band 4.1 Like 3 (EPB41L3) was mainly expressed in ALk ones (53%). A further interesting protein was the CD81 antigen (CD81), which was more present in both patient groups (C IF = 36%, ALk IF = 73%, ALl IF = 93%). On the other hand, tubulin alpha-1C chain (TUBA1C) and hemoglobin subunit delta (HBD) were among the proteins that were less abundant in both ALk and ALl. 3.2. Protein-Protein Interaction (PPI) and Co-Expression Network Models Provide New Insights to Shed Light on Pathogenic Mechanisms Driven by Aggregation of ALk and ALl Isotypes 3.2.1. PPI and Co-Expression Hubs Characterizing C, ALk and ALl Network Models To exploit the correlation between a protein network's structure and the functions that it supports, we transformed controls and patients protein profiles in PPI and protein co-expression network models. Following their topological analysis, the greatest differences concerned the average degree, which was higher in both AL cohorts. No notable centrality differences were observed at network level; the diameter and average distance were comparable in both PPI and co-expression models, even though the ALk co-expression model had lower values that, combined with the high node degree, suggest a greater network compactness (Table 1 and Supplementary Table S3). In order to go deeper into the selection of topologically relevant nodes, we extracted a set of PPI and co-expression network hubs, as putative key proteins involved in pathophysiological processes running in ALk and ALl tissues . Regarding co-expression models, TUBA1C, GPX1 and ras-related protein Rab-1B (RAB1B) were the best ranked hubs in C, ALk, ALl models, respectively . GPX1 resulted in being highly correlated with proteins involved in cell adhesion, while both GPX1 and RAB1B correlated with proteins involved in mitochondrial metabolism and protein folding. They showed a negative correlation with hemoglobin subunit delta (HBD), and GPX1 also had a similar connection with the fibrinogen gamma chain (FGG) and fibrinogen beta chain (FGB) . Concerning the C group, a correlation between TUBA1C and collagen IV subunits emerged. Other isotype-specific co-expression hubs included thioredoxin (TXN), microtubule associated protein 4 (MAP4) and Cathepsin D (CTSD) for ALk, and ATP synthase subunit d (ATP5PD) and Mast cell carboxypeptidase A (CPA3) for ALl . TXN and CTSD were also ALk PPI hubs, whereas RAB1B, myosin-10 (MYH10) and dihydrolipoamide S-acetyltransferase (DLAT) were simultaneously ALl PPI and co-expression hubs . In this scenario, PPI models have consistently highlighted the role of mitochondria by a number of PPI hubs involved in mitochondrial metabolism and respiration (CYC1, DLAT, UQCRC1, NDUFS3, COX4I1, ACADM, ECH1, ETFA), oxidative stress (SOD2) and translation (TUFM). Along with them, another consistent set of PPI hubs featuring both ALk and ALl was involved in the unfolded protein response (NPM1, HSPA12A, CCT2, CCT3); . 3.2.2. PPI and Co-Expression Modules Affected by Aggregation of ALk and ALl Isotypes The combination of PPI and co-expression models was initially processed for the identification of a highly correlated interacting community of nodes. Most of them were enriched in pathways related to metabolism, cytoskeleton, transport and protein folding . The latter two were mainly represented in ALk and ALl, along with communities enriched in the detoxification of reactive oxygen species. Communities enriched in extracellular matrix (ECM) organization processes were found in all groups. In this context, an interesting difference emerged in the co-expression network modules. In fact, in both ALk and ALl, a weighted cluster analysis evidenced the presence of the heparan sulfate proteoglycan core protein (HSPG2) in modules enriched by ECM proteins, whereas this did not happen in the C model . This result could fit with the observation that heparan sulfate proteoglycans (HSPGs) are commonly found in amyloid deposits; therefore, they have been suggested to be functionally involved in the pathogenesis of amyloidosis . Besides the analysis of node communities, the merging of the PPI and co-expression models was performed with the aim of clarifying the question of whether proteins that are part of protein complexes and/or biological processes are also correlated in maintaining a well-defined stoichiometry. Therefore, the question of how to interpret the correlation loss or gain arises. Following these tracks, we spotted some protein complexes whose correlation changed from C to ALk and ALl groups . In particular, the ALk group showed a significant decrease in correlation among tubulins, whereas, in the ALl group, the same phenomenon was observed for the 14-3-3 proteins complex. These variations were associated with an increased correlation of proteins physically interacting and functionally involved in the redox homeostasis/detoxification of reactive oxygen species and protein folding/stress response. Their increase was much more marked for the ALk group, where the protein folding/stress response module was featured by the presence of different subunits belonging to the T-complex protein ring complex (TRiC). As TRiC is involved in tubulin folding, our attention was captured by the opposite trend of expression between its components (CCT3, CCT4, TCP1) and tubulin subunits (TUBA1C, TUBB4B) . In fact, this suggests a potential non-random correlation of events worthy of further future investigation. In addition, except for the alpha-crystallin B chain (CRYAB), other folding-related proteins were more abundant in ALk and ALl tissues, confirming a role of the endoplasmic reticulum (ER) in systemic amyloid diseases . 4. Discussion To our knowledge, our perspective study represents the first example of an investigation of systemic amyloidosis through methods based on graph theory applied to proteomic data from the analysis of complex human tissues. Due to the small number of subjects, which does not allow for more robust stratifications, the results that we extracted represent the mean emerging from groups created following the presence (or absence in healthy controls) of amyloidogenic AL chains in subcutaneous adipose tissue. However, as previously reported by Brambilla et al. , most patients were further united by heart and kidney involvement. Globally, the observations collected here draw a landscape where ALk and ALl tissues undergo a similar proteome modulation. In addition, slight and interesting differences have been noted. These findings are consistent with those previously reported by our group . Thanks to a larger cohorts of subjects, new differentially abundant proteins were extracted, while ECM/cytoskeleton, proteostasis and mitochondrial-related processes being confirmed as those most affected by amyloid deposition in subcutaneous adipose tissues. Going deeper through network approaches, here, we selected new proteins that could be central in the pathophysiological processes underlying AL amyloidosis. A case in point concerns proteins and pathways involved in oxidative stress. As reported for cultured cells from multiple target tissues, there is solid evidence that AL-induced toxicity is associated with an increase in ROS and mitochondrial alterations . In our tissues, the relevance of GPX1 in terms of protein expression and the network hub fits with its role in contrasting ROS-mediated toxic effects, as already demonstrated in Parkinson's and Alzheimer's disease . A scenario of oxidative stress is further suggested by other hubs, such as SOD2, TXN and Peroxiredoxin-2 (PRDX2). It is worth noting that we found a marked negative correlation between GPX1 and some proteins, such as FGB, FGG and HBD, related to hemostasis and blood coagulation. This observation drew our attention to a potential relationship between oxidative stress and abnormal bleeding and fibrinolysis observed in AL patients . Although this correlation has previously been reported in patients with isolated aortic stenosis , no evidence is currently available in patients with amyloidosis, but it could represent an interesting hypothesis to be explored in future studies. Oxidative stress, mitochondrial dysfunction and apoptosis represent interrelated processes known to occur in experimental models of AL amyloidosis , as well as neurodegenerative diseases . The centrality of the mitochondrion has been clearly shown in our study by a number of DAPs and PPI hubs characterizing ALk and ALl models. Among the high-confidence DAPs, we noticed LONP1, a mitochondrial protease that mediates the selective degradation of misfolded, unassembled or oxidatively damaged polypeptides ; it also works as a molecular chaperone and cooperates with heat shock 70 kDa protein 1B (HSPA1B) to promote mitochondrial protein folding and contrasting cell death in response to oxidative stress . Proteoastasis-related proteolytic processes were also correlated with the abundance and topological relevance of other proteases found in our profiles, including CTSD. As a matter of fact, it has been described as physiologically important in serum amyloid A (SAA) degradation in amyloidosis , while different studies have established its role in the process of autophagy in neurodegenerative diseases . The number of DAPs, hubs and modules enriched in heat shock proteins/chaperones could support the activation of the protein quality control (PQC) systems , as well as the implication of the endoplasmic reticulum (ER) in systemic amyloid diseases . In this context, the recurrence of some proteins belonging to the T-complex protein ring complex (TRiC) is noteworthy . TRiC is an essential and ubiquitous component of the protein-folding machinery of eukaryotic cells. It has been described as both a potential modulator of protein aggregation and neuroprotective factor in Huntington's disease by inhibiting the aggregation of the mutant huntingtin . Moreover, it is also required during sarcomere assembly in myofibers and for the folding of abundant cytoskeletal proteins, such as actin and tubulin . This last function might have a link with the decrease in correlation among tubulin subunits that we mainly observed in the ALk group. The greater expression and topological relevance of the TRiC complex subunits could support a potential tubulin stress, which is an effect already described as a common feature of many neurodegenerative diseases . A putative influence of amyloid deposition on microtubules was further suggested by the topological relevance of MAP4 in ALk and its up-regulation in both ALk and ALl groups. MAP4 is a major non-neuronal microtubule-associated protein belonging to the MAP2 and TAU family. In addition to regulating organelle transport along the cytoskeletal microtubules, it is involved in maintaining mitochondrial homeostasis, and it has been proposed as a potential candidate in multiple cardiovascular pathologies . Finally, unlike in ALk, a significant and interesting decrease in correlation in the ALl model was observed for 14-3-3 proteins, a complex that plays a pivotal role in cellular signal transduction, counting more than 200 interactors . Several studies have shown that 14-3-3 acts as a molecular adaptor to recruit chaperone-associated misfolded proteins to dynein motors for transport to aggresomes . More recently, the activity of specific 14-3-3 subunits as molecular chaperones has also been demonstrated, such as 14-3-3s transiently interacting with amyloid b (Ab) in vitro and inhibiting fibril formation , and 14-3-3e interacting with human a-synuclein aggregation intermediates, reducing their cellular toxicity . 5. Conclusions Looking at the proteome modulation from different points of view, including the network topology, appeared to be a promising approach for ranking protein candidates that may play a key role in pathophysiological mechanisms induced and affected by amyloid deposition, respectively. Many targets related to the cytoskeleton, oxidative stress and mitochondrial dysfunction overlap with molecules previously described in other protein-misfolding diseases, such as Alzheimer's, Parkinson's and Huntington's diseases. Although we are well aware of the differences that distinguish amyloidosis from more common neurodegenerative diseases, this matching could be construed as a virtual validation of our findings. At the same time, they could be indicative of the aggregation of unfolded proteins inducing similar mechanisms regardless of the amyloid protein and tissues/organs targeted, and thus an overlapping that would allow us to speculate on the use of adipose tissue as a mirror to infer potential molecular events occurring in other sites, including the heart. The number of subjects, as well as their retrospective analysis, represents one of the major limitations of our study. Although all samples were processed under the same protein extraction protocol, it is undeniable that they were analyzed using different MS instruments and methods; however, we processed our data to minimize potential batch effects and to extract the most robust and meaningful information. Also in light of this, rather than drawing conclusions, our findings represent a source of information to design new target experiments. On the other hand, our study is a proof-of-concept for future applications that will take into account a larger cohort of patients and different organs/tissues affected. This goal brings attention to the need for collaborative and multicenter studies. With the support of single-cell technologies, they would allow for a better clinical stratification, which, in turn, would improve the association with molecular data, favoring the identification of targets for diagnostic, prognostic and therapeutic purposes, as well as helping to shed light on as yet unanswered questions, such as disparities in organ damage severity, organ response to treatments and even organ tropism. Acknowledgments Special thanks to Merlini for his precious suggestions. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Reactome pathways differentially enriched in Control, ALk and ALl protein profiles; Figure S2: Protein-protein interaction (PPI) functional modules differentially expressed in Control, ALk and ALl; Figure S3: Protein-protein interaction (PPI) and Co-Expression node communities enriched in Control, ALk and ALl network models; Figure S4: Protein-protein interaction (PPI) hubs specifically found in Control, ALk and ALl; Table S1: Protein profiles from abdominal subcutaneous adipose tissue of control subjects and patients affected by AL amyloidosis; Table S2: Differentially abundant proteins (DAPs) by comparing Control, ALk and ALl profiles; Table S3: Centralities average values from Control, ALk and ALl protein-protein interaction (PPI) network models; Table S4: Co-expression network hubs; Table S5: Protein-protein interaction (PPI) network hubs. Click here for additional data file. Author Contributions D.D.S. and P.M. contributed to the conception and design of the study. F.B., F.L. and D.C. performed the proteomic analysis. M.C., C.B. and R.R. performed the immunohistochemistry (IHC) assay validations. B.P.C.H. and J.B. collected and provided new samples. D.D.S. performed the statistical and network analysis. D.D.S. wrote the first draft of the manuscript. P.M., F.L., B.P.C.H., V.B. and J.D.G. contributed to the evaluation of the results and the writing of some sections of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The use of the tissue for research purposes was approved by the Ethical Committee of Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Matteo, Pavia, Italy. All persons gave written informed consent in accordance with the Declaration of Helsinki for storing and using their biologic samples for research purposes, according to the Institutional Review Board guidelines. The protein profiling of the considered samples were characterized in the context of Fondazione Cariplo Nobel project, Proteomic platform, Operational Network for Biomedicine Excellence in Lombardy (2007-2014), involving both IRCCS Policlinico San Matteo Foundation and National Research Council), while the intellectual property rights of samples analyzed after 2014 was regulated by a scientific cooperation agreement between the IRCCS Policlinico San Matteo Foundation and the Department of Chemical Sciences and Materials Technologies-National Research Council (AMMCTN-CNR, N.0027382, 21 April 2015). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The proteomic datasets (in form of raw data) analyzed for this study are available (3 January 2023) in the MassIVE database (massive.ucsd.edu) under the ID: MSV000090875, or by ftp at link ftp://massive.ucsd.edu/MSV000090875/. Conflicts of Interest The authors declare no conflict of interest. Abbreviations The following abbreviations are used in this manuscript: AL Immunoglobulin light chain ALk Patients affected by amyloidosis k ALl Patients affected by amyloidosis l C Control subjects DAPs Differentially abundant proteins DAve Differential average DEGs Differentially expressed genes FDR False discovery rate HSPGs Heparan sulfate proteoglycans MS Mass spectrometry LDA Linear discriminant analysis PCA Principal component analysis PPI Protein-protein interaction SD Standard deviation SpC Spectral count Figure 1 Workflow applied to investigate, at the proteomic system level, abdominal sub-cutaneous adipose tissues from control subjects (C, n = 14) and patients affected by ALk (ALk, n = 15) and ALl (ALl, n = 15) amyloidosis. Figure 2 Proteomics analysis of abdominal sub-cutaneous adipose tissues from control subjects and patients affected by AL amyloidosis. (A) Comparison among the average number of proteins identified in control subjects (C, n = 14) and patients affected by AL amyloidosis (ALk, n = 15; ALl, n = 15); ANOVA and Tukey's test (* p <= 0.05). (B) Principal component analysis (PCA) by processing proteins differentially abundant (DAPs) in C, ALk and ALl groups. (C) Hierarchical clustering and heat map showing the high-confidence DAPs in C, ALk and ALl protein profiles (LDA, p <= 0.01). (D) Spearman's correlation using DAPs and the corresponding average SpC values in C and ALk, (E) C and ALl, and (F) ALk and ALl groups. Figure 3 Protein-protein interaction (PPI) and co-expression network topology. (A) Validation of co-expression hubs. Violin plot of average degree values calculated from random co-expression networks (n = 1000 per group); for each group of subjects, the average degree in the reference co-expression network is shown, whereas in (B), the validation of PPI hubs is shown. Violin plot of average betweenness values calculated from random PPI networks (n = 1000 per group); for each group of subjects, the average betweenness in the reference PPI network is shown. (C) High-confidence differentially co-expressed proteins (co-expression hubs) selected by comparing the node degree from C, ALk and ALl co-expression network models (degree > 2 x network average degree). (D) Best-ranked co-expression hubs (TUBA1C in C, GPX1 ALk and RAB1B in ALl) and their higher-confidence correlation partners (Spearman's correlation score >=0.85 for GPX1 and RAB1B, >=0.75 for TUBA1C). (E) PPI hubs, selected by betweenness and centroid values, from both ALk and ALl PPI network models. Figure 4 PPI functional modules differentially correlated. (A) Clusters of proteins highly correlated in C, ALk and ALl. (B) Correlation changes among subunits/proteins physically and functionally interacting in complexes and biological processes. (C) DAve index of DAPs involved in protein folding and microtubule-related processes. A positive DAve index indicates that protein most abundant in C, whereas negative DAve index indicates that protein most abundant in ALk and ALl. (D) Representative immunofluorescence images of sub-cutaneous adipose tissue from control subjects (C) and patients affected by AL amyloidosis (ALk and ALl) stained against beta Tubulin IV (TUBBIV, red). Nuclei were detected with Hoechst (blue). Scale bars represent 150 mm. (E) The graph highlights the quantification of TUBBIV in the immunostained samples; * p <= 0.05. cells-12-00699-t001_Table 1 Table 1 Network centralities from PPI and co-expression models. PPI Model Nodes Edges Diameter Av. Distance Degree C 256 2757 5 2.38 21.5 ALk 400 5644 5 2.35 28.2 ALl 407 5315 5 2.42 26.1 Co-Expression Model Nodes Edges Diameter Av. 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PMC10000382 | (1) Background: New therapeutic strategies have improved the prognosis of multiple myeloma (MM), changing the accepted view of this disease from being incurable to treatable. (2) Methods: We studied 1001 patients with MM between 1980 and 2020, grouping patients into ten-year periods by diagnosis 1980-1990, 1991-2000, 2001-2010 and 2011-2020. (3) Results: After 65.1 months of follow-up, the median OS of the cohort was 60.3 months, and OS increased significantly over time: 22.4 months in 1980-1990, 37.4 months in 1991-2000, 61.8 months in 2001-2010 and 103.6 months in 2011-2020 (p < 0.001). Using novel agents in the front-line setting for myeloma patients yielded a significantly better OS than in those treated with conventional therapies, especially when combinations of at least two novel agents were used. The median OS of patients treated with the combination of at least two novel agents in induction was significantly prolonged compared to those treated with a single novel agent or conventional therapy in induction: 143.3 vs. 61.0 vs. 42.2 months (p < 0.001). The improvement was apparent in all patients regardless of age at diagnosis. In addition, 132 (13.2%) patients were long-term survivors (median OS >= 10 years). Some independent clinical predictors of long-term survival were identified: ECOG < 1, age at diagnosis <= 65 years, non-IgA subtype, ISS-1 and standard-risk cytogenetic. Achieving CR and undergoing ASCT were positively associated with >10 years of survival. (4) Conclusions: The combination of novel agents appears to be the main factor for the improvement in survival in MM, which is becoming a chronic and even curable disease in a subtype of patients without high-risk features. novel agents survival long survivors This research received no external funding. pmc1. Introduction A better understanding of the biology of multiple myeloma (MM), the development of research and the introduction of new therapeutic strategies have improved the outcome of patients with MM and changed the dogma of MM from being an incurable to being a treatable or even curable disease . The combination of melphalan and prednisone (MP) was introduced in the 1960s, after which autologous stem cell transplantation (ASCT) has been the only therapeutic change in the field of myeloma until the beginning of the 21st century . We have witnessed major advances in myeloma treatment in the last twenty years, such that the introduction of novel agents, such as proteasome inhibitors (PIs) and immunomodulators (IMiDs), is regarded as the foremost cause of improved survival in myeloma patients of all age groups, but of young patients in particular . In addition, the incorporation of anti-CD38 antibodies, first in the relapse and later in the upfront settings, has prompted a paradigm shift, notably for transplant-ineligible patients. Currently, the standard of care (SoC) for MM consists of a combination of PIs and/or IMiDs and/or anti-CD38 antibodies , followed by ASCT and maintenance when the patient is eligible . Although several studies have reported the benefit to survival over time, none of them has focused on how the impact of first-line therapy on real-world outcomes has changed over the years. Various prognostic factors have been identified that allow us to distinguish high-risk patients and patients with a very durable response. In this regard, the International Staging System (ISS) and the chromosomal aberrations detected with FISH (fluorescence in situ hybridization) are the main prognostic factors used to categorize MM patients. In addition, several studies have identified an association between clinical and biological characteristics, depth of response and increased survival . These prognostic advances, along with the introduction of novel therapies, have reignited interest in whether a cure is possible in a subset of myeloma patients. Based on this background, a retrospective study of patients diagnosed and treated over 40 years was undertaken to evaluate whether the outcomes for myeloma patients have improved over this period, the potential role of novel agents introduced over time and the clinical and biological characteristics that may predict long-term survival. 2. Materials and Methods This retrospective observational study was designed to include patients correlatively diagnosed with MM and those who underwent an ASCT at the University Hospital of Salamanca between 1980 and 2020. Patients with smoldering myeloma or plasma cell leukemia were not included. The follow-up cut-off date was 31 October 2022. The ethical committee of the University Hospital of Salamanca approved the study, which was conducted in accordance with the 1964 Declaration of Helsinki. Patients were divided into four groups according to the decade in which they were diagnosed. These periods encompass distinct approaches to treatment. During the first period (1980-1990), chemotherapy, especially MP, was the SoC for most patients; in the second period (1991-2000), ASCT had become the SoC for transplant-eligible patients; the third period (2001-2010) was characterized by the increasing prevalence of treatment with PI and IMIDs; and the most recent period (2011-2020) featured the introduction of anti-CD38 monoclonal antibodies. Patients were also divided into two groups according to age at diagnosis: <=70 years and >70 years because this is the cut-off age considered for eligibility for ASCT in our clinical practice. Novel agent-based inductions include those containing PIs, IMIDs and anti-CD38 monoclonal antibodies; conventional therapy-based inductions are referred to as conventional chemotherapy. The effect of novel agents was analyzed according to their number included in the induction therapy: inductions with a single novel agent (e.g., bortezomib, melphalan and prednisone (VMP), lenalidomide and dexamethasone (Rd), etc.) and inductions with at least two novel agents (e.g., bortezomib, thalidomide and dexamethasone (VTD), bortezomib, lenalidomide and dexamethasone (VRD), daratumumab plus VMP, etc.). The cytogenetic status of patients was assessed with FISH, as previously reported, in non-separated plasma cells until 2005 and in separated plasma cells thereafter . Illegitimate translocations of the IGH gene, t (11;14), t (4;14) and t (14;16), deletion 17p (del17p) and chromosome 1 abnormalities (1q gain and 1p deletion since 2010) were analyzed. A threshold of 10% was used as a cut-off for translocations and 20% for numerical aberrations, according to the European Myeloma Network . Patients were defined as high-risk based on the International Myeloma Working Group (IMWG) . The response was evaluated according to the 2016 IMWG criteria . The overall rate response (ORR) was defined as the percentage of patients who achieved partial response (PR) or better. A single complete response (CR) category was established that pooled complete and stringent complete responses. OS was defined as the time from diagnosis until the date of death or last follow-up. Long-term survivors were defined as patients who had lived for at least 10 years following their diagnosis of MM. Early death was defined as a death occurring within 2 years of diagnosis, from whatever cause. Chi-square tests identified statistically significant differences between the proportions of categories of qualitative variables, including the ORR and percentage of CR, and the associated odds ratio (OR) and 95% confidence interval (CI) were estimated using logistic regression. An ANOVA test was used to compare the median of quantitative variables. The differences in OS were defined using the log-rank test, and the corresponding hazard ratio (HR) and 95% CI were estimated using Cox regression. Univariable and multivariable logistic regression was used to compare long-term survivors and early-death patients. Values of p < 0.05 were considered statistically significant. Statistical analyses were performed with IBM SPSS Statistics version 26. 3. Results A total of 1001 patients were diagnosed between 1980 and 2020: 93 (9.3%) during 1980-1990, 178 (17.8%) during 1991-2000, 314 (31.4%) during 2001-2010 and 416 (41.5%) in the most recent period (2011-2020). The median age at diagnosis was 64 years (range, 28-93 years); 297 (31.0%) patients were diagnosed at more than 70 years of age, and 567 (56.6%) were men. The median follow-up period of the entire cohort was 65.1 months (range, 2.4-382.7 months), and the median number of the lines of treatment was 1 (1-14). Four-hundred and ninety-eight patients (49.8%) underwent ASCT. Table 1 shows the baseline characteristics of patients by diagnostic period. Patients diagnosed in the early decades more frequently presented anemia, hypercalcemia, renal failure and a poorer ECOG (European Cooperative Oncology Group) PS (performance status) than those diagnosed more recently. The median OS of the entire cohort was 60.3 months (95% CI, 54.2-62.4 months). A progressive increase in OS was observed over time . The median OS improved from 22.4 months in 1980-1990 (HR 3.5 [95% CI, 2.5-4.4]; p < 0.001), to 37.4 months in 1991-2000 (HR 2.1 [95% CI, 1.7-2.7]; p < 0.001), to 61.8 months in 2001-2010 (HR 1.4 [95% CI, 1.2-1.8]; p = 0.001) and to 103.6 months in 2011-2020 (reference decade). Patients diagnosed when they were <=70 years of age tended to have a longer OS than those diagnosed at >70 years (93.0 vs. 28.2 months; HR 3.0 [95% CI, 2.5-3.5]; p < 0.001). OS improved in both groups over time. Young patients (<=70 years) diagnosed in the last decade (2011-2020) had a longer median OS (127.6 months) than those diagnosed in the other periods: 39.9 months during 1980-1990 (HR 4.2 [95% CI, 2.8-6.2]; p < 0.001); 53.5 months during 1991-2000 (HR 2.5 [95% CI, 1.8-3.5]; p < 0.001); and 96.6 months during 2001-2010 (HR 1.6 [95% CI, 1.2-2.2]; p = 0.002) . In addition, a modest but significant benefit was found in elderly-diagnosed patients (>70 years). The median OS of elderly patients diagnosed between 2011 and 2020 (32.4 months) was longer than that of patients diagnosed in the other decades: 18.8 months during 1980-1990 (HR 1.9 [95% CI, 1.2-3.2]; p = 0.007) and 16.4 months during 1991-2000 (HR 1.8 [95% CI, 1.2-2.7]; p = 0.002). Furthermore, the median OS of patients diagnosed in 2011-2020 tended to be longer than that of those diagnosed during 2001-2010 (28.3 months; HR 1.3 [95% CI, 1.0-1.8]; p = 0.060) . 3.1. Impact of the Introduction of Novel Agents on Outcomes Having observed a significantly increasing benefit to the survival of MM patients diagnosed over time, we analyzed the effect on survival of receiving novel agents in the upfront setting over the forty-year period. Considering the entire cohort, 503 patients (50.2%) were treated with novel agents in the first line, 480 (48.0%) received conventional therapies, and 18 (1.8%) did not receive any treatment due to poor performance status. Of the patients who received novel agents, 230 (45.8%) were treated with single novel agent inductions and 272 (54.2%) received a combination of at least two novel agents in induction. The first line of treatment of the entire cohort, by age and decade of diagnosis, is summarized in Table 2. Overall, there was an increase in the use of novel agent-based inductions over time. Ninety percent of patients diagnosed in the most recent decade were treated with new drugs in the first line. Notably, the combination of at least two novel agents in induction was more frequent in the 2011-2020 period than in the previous decade (67.5% vs. 13.7%; p < 0.001). ASCT has been progressively more often incorporated into clinical practice for the treatment of younger patients over time. Only 10.2% of patients with a diagnosis at age <= 70 years underwent ASCT during the first period (1980-1990) compared with 59.6% during 1991-2000 and 83.4% of patients in the last twenty years (p < 0.001). In terms of response, PR or better was more likely to be achieved through the use of novel agents in induction than with conventional therapies (91.3% vs. 73.0%, OR 3.9 [95% CI, 2.7-5.7]; p < 0.001). In addition, the probability of achieving CR after induction was significantly higher in patients treated with novel agents (38.3% vs. 17.7%; OR 2.9 [95% CI, 2.1-3.9]; p < 0.001). Patients treated with the combination of at least two novel agents in induction responded better than those who received single novel agent inductions, with respect to achieving PR or better (97.4% vs. 83.8%; OR 7.2 [95% CI, 3.1-16.5]; p < 0.001) and CR (46.8% vs. 27.8%; OR 2.3 [95% CI, 1.6-3.4]; p < 0.001). This improved response led to an increase in OS in MM patients treated with novel agents in the first line: 107.6 vs. 42.2 months (HR 2.1 [95% CI, 1.7-2.4]; p < 0.001). However, it is worth noting that the improvement observed in patients treated with novel agents arose mainly from treatments with at least two novel new drugs in the first line. The median OS of those treated with the combination of at least two novel agents in induction was significantly longer than that of patients who received single novel agent inductions: 143.3 vs. 61.0 months (HR 2.2 [95% CI, 1.6-2.9]; p < 0.001) . Furthermore, we analyzed the effect of novel agents on the response (supplementary Table S1) and survival of young and elderly patients, to overcome the transplant-eligibility and comorbidity biases. In the <=70-year group, the likelihood of achieving PR or better and CR after induction was greater in patients treated with novel agent-based inductions compared with those receiving conventional therapies (92.8% vs. 80.3%; OR 3.1 [95% CI, 1.9-5.2]; p < 0.001; and 39.6% vs. 20.1%; OR 2.6 [95% CI, 1.8-3.7]; p < 0.001). Both responses were significantly stronger in patients treated with the combination of at least two novel agents in induction compared with those who received single novel agent inductions (PR or better: 96.9% vs. 85.7%, OR 5.2 [95% CI, 2.1-12.8], p < 0.001; and CR: 46.0% vs. 28.6%, OR 2.1 [95% CI, 1.3-3.4], p = 0.001). In addition, the median OS was significantly longer in young patients treated with novel agents in induction than those who received conventional therapies: 143.3 vs. 65.7 months (HR 2.0 [95% CI, 1.6-2.5]; p < 0.001). The combination of at least two novel agents in induction led to a longer OS (143.3 months) than in those treated with single novel agent inductions (113.0 months; HR 1.8 [95% CI, 1.2-2.6]; p = 0.004) . Considering patients older than 70 years at diagnosis, those who received novel agents had better responses than those receiving conventional therapies, achieving at least PR (87.1% vs. 68.0%; OR 3.2 [95 CI%, 1.7-6.1]; p < 0.001) and CR after induction (34.7% vs. 16.8%; OR 2.6 [95% CI, 1.4-4.8]; p = 0.002). Both responses were better among the patients treated with a combination of at least two novel agents in induction than among patients treated with single novel agent inductions (PR or better: 100.0% vs. 80.7%, OR not estimated, p = 0.001; and CR: 51.2% vs. 26.5%, OR 2.9 [95% CI, 1.3-6.4], p = 0.007). The introduction of novel agents boosted OS with respect to the outcome of patients treated with conventional therapies: 49.5 vs. 26.8 months (HR 1.9 [95% CI, 1.4-2.5]; p < 0.001). In addition, patients treated with a combination of at least two novel agents in induction had a significantly longer OS than those receiving single novel agent inductions: 101.8 vs. 43.7 months (HR 1.7 [95% CI, 1.1-2.8]; p = 0.034) . 3.2. Long-Term Survivors Overall, 132 (13.2%) patients were considered long-term survivors (median OS >= 10 years) in our entire cohort. Five patients (3.8%) were diagnosed between 1980 and 1990, twenty-five (18.9%) during 1991-2000, seventy-six (57.6%) during 2001-2010 and twenty-six (19.7%) in the most recent decade (2011-2020). The median age at diagnosis was 57 years (range, 29-79 years) and 66 (50.0%) were men. The median number of treatment lines was 2 (range, 1-14) and 105 (79.5%) underwent ASCT (OR 4.6 [95% CI, 2.9-7.1]; p < 0.001). In addition, achieving CR or better after the first line of treatment was positively associated with living at least 10 years following an MM diagnosis (19.0% vs. 10.6%; OR 2.0 [95% CI, 1.4-2.9]; p < 0.001). To identify clinical predictors of long-term survival, we compared baseline clinical characteristics at the time of diagnosis of long-term survivors with those of patients who died early (OS <= 2 years, 252 patients (25.2%) in the complete cohort). In the univariable model (Table 3), age at diagnosis <= 65 years, IgG and non-IgA subtypes, bone marrow plasma cell infiltration < 30%, ECOG PS 0-1, hemoglobin levels >= 10 g/dL, creatinine levels <= 2 mg/dL, calcium levels < 11 mg/dL, albumin levels >= 3.5 g/dL, b2 microglobulin levels < 3.5 and 5 mg/dL, standard-risk cytogenetics, being ISS-1 and not being ISS-3 were characteristics associated with over 10-year survival. In the multivariable model (Table 4), age at diagnosis <=65 years, the non-IgA subtype, ECOG PS 0-1, standard risk cytogenetics and being ISS-1 were characteristics associated with a 10-year survival. 4. Discussion This retrospective study confirms the continuing improvement in the survival of myeloma patients over time. The combination of new drugs in the first-line setting appears to be the main factor driving improvement in the most recent period. Moreover, to our knowledge, this is the first historical study to report the effect on outcomes of the combination of PIs and IMiDs and the positioning of anti-CD38-based inductions in first-line therapy. In this regard, patients in our cohort treated with the combination of at least two novel agents in induction showed an encouraging median OS of more than 10 years. In addition, age at diagnosis <=65 years, non-IgA subtype, ECOG PS 0-1, standard risk cytogenetics and being ISS-1 were identified as favorable prognostic factors associated with long-term survival (>=10 years). Many retrospective and population-based investigations have reported that the improvement in survival of patients with MM over time was due to the introduction of ASCT and novel agents. Notably, the increase in OS was observed in younger-diagnosed patients (<=65 years) . Kumar and colleagues reported the OS of almost 3000 patients diagnosed at the Mayo Clinic, dividing patients into two groups according to the year of diagnosis: 1971-1996 and 1997-2006. Sixty percent of patients diagnosed in the most recent period received novel agents in the first line, and this group presented better survival (44.8 vs. 22.9 months; p < 0.001) but was limited to patients aged <= 65 years (60.0 vs 33.0 months; p < 0.05) . Consistent results were also reported by the Greek group of myeloma. In this study, patients diagnosed between 1985 and 1999 were compared with those diagnosed in >=2000, in which only 30% received novel agents. The median OS of patients diagnosed in 2000 or after was significantly longer (44,8 vs. 22.9 months; p < 0.001). This benefit in OS was exclusively shown in patients <= 65 years (not reached vs. 42,0 months; p < 0.001) . The lack of benefit of novel agents in older patients was limited by their underuse in this population. However, various studies have shown the benefit of using novel agents in the more elderly population . Kumar et al. first reported improved survival in patients older than 65 years due to the novel agents . In this retrospective study at the Mayo Clinic, 1038 patients diagnosed between 2001 and 2010 were analyzed, grouping patients into two 5-year periods by diagnosis (2001-2005 and 2006-2010). Sixty percent of the cohort was treated with novel agents in the first line. Patients diagnosed in the most recent period achieved significantly prolonged OS (6.1 vs. 4,6 years; p = 0.002), including patients aged >65 years (5.0 vs. 3.2 years; p < 0.05). No differences were observed in younger patients because of the effect of ASCT and probably the lack of follow-up. A historic study on the Hospital Clinic of Barcelona showed a significant improvement in OS over decades, regardless of the age at diagnosis, but especially in younger patients . In addition, the population-based studies indirectly support the benefit of different milestones in MM treatment. Although these studies did not include clinical and treatment data, the survival of patients improved over time, indicating the positive impact of the new approach on myeloma patients . Indeed, this progressive improvement in survival was also observed in our cohort. Figure 1 illustrates how outcomes have improved decade upon decade, reflecting the therapeutic advances in myeloma treatment. Thus, the median OS of the second calendar period (1991-2000) is longer than that of the first decade (1980-1990) due to the introduction of ASCT (59.6% vs. 10.2%); patients diagnosed in the third period (2001-2010) generally had better OS because of the introduction of novel agents; and finally, in the most recent decade (2011-2020), the combination of novel agents in induction led to longer survival than patients diagnosed in the third decade. The improved results over time, especially since 2000, were replicated when we stratified the population by age at diagnosis . This is a reflection of the increased use of novel agent-based inductions among younger and older patients, and future approaches will require frail-adapted therapy for the elderly to be planned in order to obtain population outcomes comparable with those of the younger population. As might be expected, patients who received novel-agent inductions presented twice the median OS of those treated with chemotherapy or polychemotherapy in the younger and older groups. Therefore, our results are in line with those reported by other authors, whereby the new agents have improved the outcomes of myeloma patients, regardless of age at diagnosis. However, the number of novel agents is important: a notable finding from our analysis is that the increasingly widespread use of combinations with at least two novel agents in induction is one of the main factors that has improved survival in recent years. In this regard, almost 100% and 50% of patients treated with the combination of at least two novel agents in induction achieved at least PR and CR, respectively, and presented excellent OS . Thus, patients aged <= 70 years and >70 years treated using this approach presented a striking median OS of 12 and 8 years, respectively . These results are consistent with the phase 3 trials conducted in transplant-eligible and ineligible patients . However, considering the older group, the OS in the last decade (32.4 months) was lower than expected. Although some of our elderly patients participated in the aforementioned trials, most of them had not been selected. Therefore, for the sample of elderly patients treated with a combination of at least two novel agents (n = 39), their heterogeneity, comorbidities and age-related frailty were the main reasons for the poorer survival. Notably, increased mortality was observed in patients aged > 70 years in the first 24 months, regardless of the induction therapy. Establishing frailty scales in daily practice is necessary if each patient is to be offered the most appropriate treatment , given that the progressive introduction of novel drugs seems to improve their outcomes. In addition, the snowball approach would be a useful strategy in frail patients. This strategy consists of adding drugs progressively as the patient's performance status improves until the optimal treatment is achieved. An ongoing phase 3, multicenter, randomized trial by the Spanish Myeloma Group, the GEM2017FIT trial, aims to determine the optimal treatment for newly diagnosed elderly MM patients aged between 65 and 80 years. Another study (IBERDARADEX) is testing iberdomide-based combinations in elderly patients, although 30% of the different cohorts are frail patients to enable safety and efficacy to be evaluated in this specific subgroup of patients. A further noteworthy finding is the progressive increase over the 40 years of the study in the proportion of patients considered to be long-term survivors. There was a five-fold increase in the number of patients living 10 years from 1980-1990 to 1991-2000 and a three-fold increase from 1991-2000 to 2001-2010. The number of long-term survivors in the decade 2011-2020 could not be reliably evaluated due to the intrinsically insufficient follow-up (51.4 months). However, despite this limitation, the same number of patients have already survived more than 10 years in the last decade as in 1991-2000. This increase in the number of long-term survivors is mainly due to the introduction of new therapies, both in induction and relapse. Many of these patients have received second-generation PIs and IMiDs, anti-CD38 monoclonal antibodies and targeted therapies in the relapsed/refractory setting. Moreover, eight out of ten patients underwent ASCT, which was associated with an almost five-fold greater probability of achieving prolonged survival. Two studies have reported that 20-30% of transplanted patients achieved an OS longer than 10 years . One in five patients who achieved CR or better after the first line of treatment were long-term survivors. Some authors have already directly associated the achievement of CR with longer survival in transplant-eligible and ineligible patients . This finding is very encouraging given that the introduction of new drugs in the first line has been shown to increase the likelihood of achieving CR, especially if patients receive the combination of at least two novel agents in induction. In addition, age at diagnosis <= 65 years, non-IgA subtype, ECOG PS 0-1, standard risk cytogenetics and ISS-1 favorably and independently affected the probability of long-term survival (>=10 years) compared with early death (<=2 years). The main baseline characteristics associated with the tumor burden (hemoglobin, calcium, renal failure, plasmacytosis, etc.) have been reported as independent prognostic factors of long-term survival , but the loss of diagnostic data could have influenced the estimates of the multivariable model. The foremost limitation of the present study is its retrospective nature, especially with respect to the lack of some clinical or laboratory data, and the intrinsically short follow-up of patients diagnosed in the most recent decade. The cohort studied is younger than expected, probably due to the fact that it is a transplant referral center. No distinction was made between fixed-duration and continuous treatments in the survival analysis. In addition, no specific survival sub-analysis of anti-CD38 was performed. However, many elderly patients treated with the combination of at least two novel agents in induction received anti-CD38-based regimens. The strength of this study lies in it involving a large cohort with a long follow-up that provides real-world evidence and shows the evolution of myeloma patients over time. Nevertheless, our findings should be confirmed in independent studies and with further follow-up. 5. Conclusions In summary, this study shows the continuing increase in survival in MM as time goes by, regardless of the age at diagnosis, although improvements are particularly marked in the younger population. The most recent improvements in the response and survival of myeloma patients are due to the introduction of novel agents in the front-line setting, especially when at least two novel agents are combined in induction. This finding emphasizes the importance of using the most effective combinations in first-line therapy, as previously reported . The likelihood of being a long-term MM survivor is increasing because of the use of more, better and less toxic therapies in the first line and relapse. Achieving CR and undergoing ASCT were positively associated with survival longer than 10 years. Patients with good performance status diagnosed with <=65 years of non-IgA myeloma, ISS-1 and without high-risk cytogenetics had excellent survival. These findings lead us to conclude that myeloma has become a chronic disease, and even a curable one, in a subset of patients. To achieve this goal, we have begun to incorporate risk and response-adapted therapy into our clinical practice, mainly through the Spanish Myeloma Group's clinical research. This allows us to stratify the elderly population according to their frailty and to treat standard and high-risk patients in different ways, as appropriate, or even to intensify or de-escalate treatment based on the presence of measurable residual disease detected using highly sensitive techniques for assessing response. These new factors will be incorporated into the analyses of our forthcoming studies. Acknowledgments The authors would like to thank Philip Mason for the English revision of the manuscript, and the "Fundacion para el Desarrollo de la Hematologia y Hemoterapia de Salamanca" for financial support. Supplementary Materials The following supporting information can be downloaded at: Table S1: Response after induction according to the treatment divided by age at diagnosis. Click here for additional data file. Author Contributions B.P. and V.G.-C. have contributed equally to this publication. E.S.-F. and V.G.-C. conceived the idea. E.S.-F. contributed to providing most of the study material. B.P., V.G.-C. and the last author (M.-V.M.) had full access to all the study data. B.P., V.G.-C. and M.-V.M. analyzed and interpreted the data and wrote the original draft of the manuscript. The rest of the authors (E.S.-F., F.E., J.A.Q., A.B., J.L., J.M.A.-A., A.G.d.C., A.C., T.V., C.A.-F., E.A.-A., B.R.-B., L.L.-C., R.G.-S., N.P. and N.C.G.), treated the patients and reviewed, edited and approved the final version of the manuscript. 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 Ethics Committee of the University Hospital of Salamanca (protocol code 2022 07 1136 and 26 September 2022). Informed Consent Statement Patient consent was waived due to the retrospective nature of the study. Data Availability Statement Due to the sensitive nature of the data, information created during and/or analyzed during the current study is available from the first and corresponding authors. Conflicts of Interest B.P. has received honoraria from Janssen and Aptitude Health. V.G.-C. has received honoraria from Janssen and Celgene, research funding from Janssen; and consulting or advisory roles for Prothena and Janssen. E.S.F. has received speaker's fees from Amgen and Janssen and consultancies from Janssen. F.E.-B. has received speaker's fees from Janssen, Sanofi, Amgen and Sanofi, and honoraria from consulting or advisory roles from Janssen, Biogene, Sanofi, GSK, Takeda, Amgen y BMS. EAA has received honoraria from Janssen. BRB has received speaker's fees from Janssen. RGS has received honoraria from Janssen, Takeda and Amgen; and has received research funding from Gilead Sciences and Incyte. NP has received honoraria for consulting or advisory roles from Amgen, Celgene, Janssen, Takeda, The Binding Site, GSK and Sanofi. NGG has received honoraria from Janssen and Amgen. M.-V.M. has received honoraria derived from lectures and advisory boards from Janssen, BMS-Celgene, Amgen, Takeda, Abbvie, Sanofi, Oncopeptides, Adaptive, Roche, Pfizer, Regeneron, GSK, Bluebird Bio, Sea-Gen. The remaining authors declare no competing financial interests. Figure 1 Overall survival by decades. Abbreviations: CI: confidence interval; HR: hazard ratio. Figure 2 Overall survival by decades and age at diagnosis: (A) <=70 years and (B) >70 years. Abbreviations: CI: confidence interval; HR: hazard ratio. Figure 3 Overall survival by induction therapy. Abbreviations: CI: confidence interval; HR: hazard ratio. Figure 4 Overall survival by induction therapy and age at diagnosis: (A) <=70 years and (B) >70 years. Abbreviations: CI: confidence interval; HR: hazard ratio. cancers-15-01558-t001_Table 1 Table 1 Baseline characteristics of the entire cohort. All Patients (n = 1001) Group 1 (1980-1990) (n = 93) Group 2 (1991-2000) (n = 178) Group 3 (2001-2010) (n = 314) Group 4 (2011-2020) (n = 416) p Value Follow-up in months, median (range) 65.1 (2.4-382.1) 121.3 (3.0-121.7) 119.0 (15.0-382.1) 157.8 (10.3-263.8) 51.4 (2.4-142.9) Age at diagnosis, median (range) a 64 (28-93) 68 (38-86) 64 (31-88) 63 (28-89) 65 (30-93) 0.153 Age at diagnosis <=70, n (%) Older than 70, n (%) 662 (69.0) 297 (31.0) 49 (66.2) 25 (26.9) 114 (72.6) 43 (27.4) 215 (68.9) 97 (31.1) 284 (68.3) 132 (31.7) 0.722 Gender, male, n (%) 567 (56.6) 44 (47.3) 96 (53.9) 173 (55.1) 254 (61.1) 0.059 Ig isotype, n (%) b IgG IgA IgM IgD Light chains only Non-secretory 557 (56.6) 252 (25.6) 2 (0.2) 7 (0.7) 145 (14.7) 21 (2.1) 45 (49.5) 33 (36.3) 0 (0.0) 0 (0.0) 13 (14.3) 0 (0.0) 87 (49.7) 54 (30.9) 0 (0.0) 7 (4.0) 27 (15.4) 0 (0.0) 187 (59.9) 72 (23.1) 1 (0.3) 0 (0.0) 37 (11.9) 15 (4.8) 238 (58.6) 93 (22.9) 1 (0.2) 0 (0.0) 68 (16.7) 6 (1.5) 0.061 0.014 - - 0.328 - Light chain isotype Kappa, n (%) c 575 (59.1) 39 (46.4) 100 (57.8) 187 (60.9) 249 (60.9) 0.026 ECOG PS 0-1, n (%) d 497 (64.0) 27 (34.6) 53 (44.5) 132 (64.7) 285 (75.8) 0.000 Hb <= 10 g/dL, n (%) e 366 (39.6) 51 (56.0) 75 (46.9) 113 (38.6) 127 (33.3) 0.000 Cr >= 2 mg/dL, n (%) f 185 (19.6) 25 (27.8) 33 (20.4) 50 (16.9) 77 (19.4) 0.157 Ca >= 11 mg/dL, n (%) g 144 (16.2) 27 (30.7) 25 (16.4) 36 (13.2) 56 (14.8) 0.001 Lytic lesions, n (%) h 617 (69.2) 68 (76.4) 106 (66.3) 164 (59.9) 279 (75.8) 0.000 Elevated LDH, n (%) i 230 (43.5) No data 24 (72.7) 136 (72.0) 70 (22.8) 0.000 Albumin, g/dL, mean (SD) 3.6 (+-0.7) 3.6 (+-0.7) 3.7 (+-0.7) 3.5 (+-0.7) 3.6 (+-0.7) 0.476 b2 microglobulin, mg/dL, mean (SD) 5.8 (+-5.4) 5.5 (+-4.1) 6.6 (+-7.6) 4.7 (+-4.2) 6.5 (+-5.2) 0.000 ISS, n (%) j I II III 280 (33.5) 280 (33.5) 277 (33.0) 15 (38.5) 10 (25.6) 14 (35.9) 62 (42.5) 37 (25.3) 47 (32.2) 94 (34.6) 115 (42.3) 63 (23.2) 109 (28.7) 118 (31.1) 153 (40.3) 0.020 0.001 0.000 High-risk cytogenetic k,*, n (%) 116 (18.3) No data 4 (25.0) 39 (16.0) 73 (19.8) 0.396 Abbreviations: Ig: immunoglobulin; ECOG: European Cooperative Oncology Group; PS: performance status; Hb: hemoglobin; Cr: creatinine; Ca: calcium; LDH: lactate dehydrogenase; ISS: International Staging System; SD: standard deviation. Data were available in 959 (a), 984 (b), 973 (c), 777 (d), 925 (e), 944 (f), 891 (g), 891 (h), 529 (i), 837 (j) and 627 patients (k). * High-risk cytogenetic was considered t(4;14), t(14;16) and del17p. cancers-15-01558-t002_Table 2 Table 2 Treatments used by age and decade of diagnosis. Age <= 70 Years (n = 662) Age Older than 70 Years (n = 279) 1980-1990 (n = 49) 1991-2000 (n = 114) 2001-2010 (n = 215) 2011-2020 (n = 284) 1980-1990 (n = 21) a 1991-2000 (n = 40) b 2001-2010 (n = 94) c 2011-2020 (n = 124) d Lines of therapy, median (range) 1 (1-4) 2 (1-7) 2 (1-14) 1 (1-9) 1 (1-2) 1 (1-2) 2 (1-5) 2 (1-8) Chemotherapy (CyP, MP) 25 (51.0) 15 (13.1) 6 (2.8) 2 (0.7) 13 (61.9) 32 (80.0) 57 (60.6) 18 (14.5) Polychemotherapy (VBCMP, VBAD, VAD) 24 (49.0) 97 (85.1) 116 (54.0) 9 (3.2) 8 (38.1) 8 (20.0) 4 (4.3) 0 (0.0) Novel agents in first line 0 (0.0) 0 (0.0) 93 (43.2) 273 (96.1) 0 (0.0) 0 (0.0) 32 (34.0) 105 (84.7) 1 novel agent in first line 0 (0.0) 0 (0.0) 80 (37.2) 57 (20.1) 0 (0.0) 0 (0.0) 27 (28.7) 66 (53.2) >=2 novel agents in first line 0 (0.0) 0 (0.0) 13 (6.0) 216 (76.1) 0 (0.0) 0 (0.0) 5 (5.3) 39 (31.5) PI-based scheme (VD, VMP, VCD, PAD...) 0 (0.0) 0 (0.0) 69 (32.1) 54 (19.0) 0 (0.0) 0 (0.0) 22 (23.4) 58 (46.8) IMID-based scheme (TD, TCD, TAD, Rd...) 0 (0.0) 0 (0.0) 11 (5.2) 3 (1.1) 0 (0.0) 0 (0.0) 5 (5.3) 11 (8.9) PI plus IMID (VTD, VRD...) 0 (0.0) 0 (0.0) 13 (6.0) 195 (68.7) 0 (0.0) 0 (0.0) 5 (5.3) 10 (8.1) Anti-CD38-based scheme (Any combination which included anti-CD38) 0 (0.0) 0 (0.0) 0 (0.0) 19 (6.7) 0 (0.0) 0 (0.0) 0 (0.0) 26 (21.0) Others 0 (0.0) 2 (1.8) 0 (0.0) 2 (0.7) 0 (0.0) 0 (0.0) 1 (1.1) 1 (0.8) ASCT 5 (10.2) 68 (59.6) 179 (83.3) 237 (83.5) 0 (0.0) 0 (0.0) 0 (0.0) 3 (2.3) Abbreviations: CyP: Cyclophosphamide and prednisone; MP: Melphalan and prednisone; VBCMP: vincristine, carmustine, cyclophosphamide, melphalan, prednisone; VBAD: vincristine, bleomicine, adriamycine, dexamethasone; VAD: vincristine, adriamycine, dexamethasone; PI: proteasome inhibitor; VD: bortezomib, dexamethasone; VMP: bortezomib, melphalan, dexamethasone; VCD: bortezomib, cyclophosphamide, dexamethasone; PAD: bortezomib, adriamycine, dexamethasone; IMID: immunomodulator; TD: thalidomide, dexamethasone; TCD: thalidomide, cyclophosphamide, dexamethasone; TAD: thalidomide, adriamycine, dexamethasone; Rd: lenalidomide, dexamethasone; VTD: bortezomib, thalidomide, dexamethasone; VRD: bortezomib, lenalidomide, dexamethasone; ASCT: autologous stem cell transplantation. * Age at diagnosis was unknown in 42; ** and 4 (a), 3 (b), 3 (c) and 8 patients (d) did not receive treatment due to performance status at the moment of diagnosis. cancers-15-01558-t003_Table 3 Table 3 Univariable analysis: long survivors vs. early death patients. Long Survivors (n = 132) Early-Death (n = 252) OR (95% CI), p Value Age at diagnosis > 65 years, n (%) 22/132 (16.7) 163/224 (72.8) 13.4 (7.8-23.0), 0.000 Male, n (%) 66/132 (50.0) 136/252 (54.0) 1.2 (0.8-1.8), 0.460 IgG subtype, n (%) 82/129 (63.6) 122/248 (49.2) 1.8 (1.2-2.8), 0.008 IgA subtype, n (%) 21/129 (16.3) 167/248 (67.3) 2.5 (1.5-4.3), 0.001 Bence-Jones subtype, n (%) 18/129 (14.0) 36/248 (14.5) 1.0 (0.6-1.9), 0.882 Paraprotein >= 3 g/dL, n (%) 57/102 (55.9) 120/225 (53.3) 0.9 (1.6-1.4), 0.668 PCs in BM >= 30, n (%) 50/109 (45.9) 134/226 (59.3) 1.7 (1.1-2.7), 0.021 ECOG PS 2-4, n (%) 12/71 (16.9) 133/220 (60.5) 7.5 (3.8-14.8), 0.000 Hb <= 10 g/dL, n (%) 34/120 (28.3) 126/244 (51.6) 2.7 (1.7-4.3), 0.000 Cr >= 2 mg/dL, n (%) 10/126 (7.9) 84/244 (34.4) 6.1 (3.0-12.2), 0.000 Ca >= 11 mg/dL, n (%) 12/108 (11.1) 63/240 (26.3) 2.8 (1.5-5.5), 0.002 Lytic lesions, n (%) 82/125 (65.6) 151/223 (67.7) 1.1 (0.7-1.8), 0.688 Albumine < 3.5 g/dL, n (%) 37/112 (33.0) 125/240 (52.1) 2.2 (1.4-3.5), 0.001 b2 microglobulin >= 3.5 mg/dL, n (%) 28/98 (28.6) 144/190 (75.8) 7.8 (4.5-13.7), 0.000 b2 microglobulin >= 5 mg/dL, n (%) 11/98 (11.2) 106/190 (55.8) 10.0 (5.0-19.9), 0.000 Elevated LDH, n (%) 27/64 (42.2) 76/136 (55.9) 1.7 (1.0-3.2), 0.072 High-risk cytogenetic *, n (%) 11/97 (11.3) 30/107 (28.0) 3.0 (1.4-6.5), 0.004 ISS-1, n (%) 55/106 (51.9) 33/200 (16.5) 5.5 (3.2-9.3), 0.000 ISS-2. n (%) 40/106 (37.7) 56/200 (28.0) 0.6 (0.4-1.1), 0.082 ISS-3, n (%) 11/106 (10.4) 111/200 (55.5) 10.8 (5.4-21.3), 0.000 Abbreviations: OR: odds ratio; CI: confidence interval; ECOG: Eastern Cooperative Oncology Group; PCs: plasma cells; BM: bone marrow; PS: performance status; Hb: hemoglobin; Hb: hemoglobin; Cr: creatinine; Ca: calcium; LDH: lactate dehydrogenase; ISS: International Staging System. * High-risk cytogenetic included t(4;14), t(14;16) and del17p. cancers-15-01558-t004_Table 4 Table 4 Multivariable analysis: long survivors vs. early death. Long Survivors (n = 43) Early Death (n = 82) OR (95% CI), p Value Age at diagnosis > 65 years, n (%) 29/43 (67.4) 19/82 (23.2) 12.2 (3.6-41.5), 0.000 Male, n (%) - - - IgG subtype, n (%) - - - IgA subtype, n (%) 5/82 (11.6) 26/82 (31.7) 5.3 (1.2-23.4), 0.028 Bence-Jones subtype, n (%) - - - Paraprotein >= 3 g/dL, n (%) - - - PCs in BM >= 30, n (%) 22/43 (51.2) 52/82 (63.2) 1.1 (0.3-3.3); 0.904 ECOG PS 2-4, n (%) 7/43 (16.3) 39/82 (47.6) 4.0 (1.1-14.2), 0.030 Hb <= 10 g/dL, n (%) 11/43 (25.6) 41/82 (50.0) 1.5 (0.5-4.8), 0.492 Cr >= 2 mg/dL, n (%) 2/43 (4.7) 23/82 (28.0) 3.5 (0.6-21.3), 0.170 Ca >= 11 mg/dL, n (%) 2/43 (4.7) 18/82 (22.0) 7.1 (1.2-23.4), 0.074 Lytic lesions, n (%) - - - Albumine < 3.5 g/dL, n (%) - - - b2 microglobulin >= 3.5 mg/dL, n (%) - - - b2 microglobulin >= 5 mg/dL, n (%) - - - Elevated LDH, n (%) - - - High-risk cytogenetic *, n (%) 5/43 (11.6) 25/82 (30.5) 6.1 (1.2-31.0), 0.028 ISS-1, n (%) 24/43 (55.8) 8/82 (9.8) 4.8 (1.4-16.6), 0.012 ISS-2. n (%) - - - ISS-3, n (%) - - - Abbreviations: OR: odds ratio; CI: confidence interval; ECOG: Eastern Cooperative Oncology Group; PCs: plasma cells; BM: bone marrow; PS: performance status; Hb: hemoglobin; Hb: hemoglobin; Cr: creatinine; Ca: calcium; LDH: lactate dehydrogenase; ISS: International Staging System. * High-risk cytogenetic included t(4;14), t(14;16) and del17p. 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PMC10000383 | In the past two decades, molecular targeted therapy has revolutionized the treatment landscape of several malignancies. Lethal malignancies such as non-small cell lung cancer (NSCLC) have become a model for precision-matched gene-targeted therapies. Multiple small subgroups of NSCLC defined by their genomic aberrations are now recognized; remarkably, taken together, almost 70% of NSCLCs now have a druggable anomaly. Cholangiocarcinoma (CCA) is a rare tumor with a poor prognosis. Novel molecular alterations have been recently identified in patients with CCA, and the potential for targeted therapy is being realized. In 2019, a fibroblast growth factor receptor 2 (FGFR2) inhibitor, pemigatinib, was the first approved targeted therapy for patients with locally advanced or metastatic intrahepatic CCA who had FGFR2 gene fusions or rearrangement. More regulatory approvals for matched targeted therapies as second-line or subsequent treatments in advanced CCA followed, including additional drugs that target FGFR2 gene fusion/rearrangement. Recent tumor-agnostic approvals include (but are not limited to) drugs that target mutations/rearrangements in the following genes and are hence applicable to CCA: isocitrate dehydrogenase 1 (IDH1); neurotrophic tropomyosin-receptor kinase (NTRK); the V600E mutation of the BRAF gene (BRAFV600E); and high tumor mutational burden, high microsatellite instability, and gene mismatch repair-deficient (TMB-H/MSI-H/dMMR) tumors. Ongoing trials investigate HER2, RET, and non-BRAFV600E mutations in CCA and improvements in the efficacy and safety of new targeted treatments. This review aims to present the current status of molecularly matched targeted therapy for advanced CCA. cholangiocarcinoma targeted therapy molecular biomarkers 5U01CA180888-08 5UG1CA233198-05 RK is funded in part by 5U01CA180888-08 and 5UG1CA233198-05, 3/1/2023-2/28/2024. pmc1. Introduction In the past two decades, molecular targeted and immune therapy has revolutionized the treatment landscape of several malignancies. Recent findings highlighted that matched targeted therapy improved the response rate and prolonged the survival of patients with advanced cancers . Some of the most notable achievements are in non-small cell lung cancer (NSCLC), a disease for which the number of actionable biomarkers has increased rapidly. Indeed, NSCLC is now almost a poster child for the benefits of precision medicine, with almost 70% of NSCLCs having a biomarker-based therapy (including but not limited to EGFR and ERBB2 alterations, mismatch repair gene defects, high tumor mutational burden, BRAF V600E, NTRK fusions, ALK fusions, ROS1 fusions, and RET alterations) . Moreover, molecular diagnostics have supported the development of drugs and therapeutic antibodies targeting specific receptors, antigens, or molecular pathways crucial for tumor cell proliferation and invasion, tumor growth, immunity, and metastases across various malignancies . Cholangiocarcinoma (CCA) is a promising candidate for targeted therapy due to its diverse molecular features . The incidence of CCA is low in the Western world, with between 0.35 and 2 cases per a 100,000 population per year . The global incidence of CCA has steadily increased over the last 30 years, from 0.1 to 0.6 cases per a 100,000 population . CCA is a highly aggressive malignancy, with a 5-year OS for locally advanced or metastatic disease of less than 10% . CCA arises from the intrahepatic and extrahepatic biliary epithelium . Anatomically, 60-70% of cases are classified as perihilar CCA (pCCA); 20-30% of cases are distal CCA (dCCA); and 5-10% of cases are intrahepatic CCA (iCAA) . Current population statistics show an increased prevalence of CCA . In early-stage CCA, the primary treatment includes surgical resection and adjuvant chemotherapy, while systemic chemotherapy is the standard treatment for advanced-stage CCA . Patients with CCA often present with late-stage disease, and the prognosis is poor . Molecular techniques, including next-generation sequencing (NGS), have identified novel mutations in tumors from patients with CCA . Patients with CCA show substantial variations in their molecular profiling and genetic aberrations according to their anatomic locations (Table 1). Promising therapeutic molecular targets for CCA have been identified and include isocitrate dehydrogenases 1 and 2 (IDH1 and 2) and products of fusions of the fibroblast growth factor receptor 2 (FGFR2) gene . In 2019, the US Food and Drug Administration (FDA) granted accelerated approval for pemigatinib, an FGFR2 inhibitor, as the first targeted therapy for locally advanced or metastatic iCCA with FGFR2 fusions or rearrangement . Another approval for a targeted therapy specifically for CCA was on 28 May 2021 . The FDA granted accelerated approval to infigratinib, a kinase inhibitor approved for adults with previously treated, locally advanced, unresectable, or metastatic CCA with an FGFR2 gene fusion or rearrangement . This specific approval for CCA required confirmation that an FDA-approved diagnostic test detected FGFR2 gene fusion or rearrangement in CCA . More recently, the FDA granted accelerated approval to futibatinib, an irreversible FGFR1-4 Inhibitor, for previously treated, locally advanced, unresectable, or metastatic CCA with an FGFR2 gene fusion or rearrangement on 30 September 2022 . In support of the recent developments in targeted therapies, in August 2021, the FDA approved ivosidenib as a targeted therapy for adult patients with unresectable locally advanced or metastatic CCA with a mutation in the IDH1 gene detected by an FDA-approved diagnostic test . Finally, ALK and ROS1 mutations occur in between 3% and 9% of patients with CCA, and ALK-positive and ROS1-positive CCA may also be treated with ALK inhibitors . There are also several tumor-agnostic approvals that encompass CCA. For example, in May 2017, the FDA granted accelerated approval for the therapeutic monoclonal antibody, pembrolizumab, for microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) unresectable or metastatic solid tumors that have progressed despite prior treatment . In 2020, pembrolizumab received FDA approval for adults and children with high tumor mutational burden (TMB-H) solid tumors . In August 2021, accelerated approval was granted for dostarlimab for adult patients with recurrent or advanced solid tumors identified as mismatch repair deficient (dMMR) as determined by an FDA-approved diagnostic test . In 2018 and 2019, two therapies targeting neurotrophic tyrosine receptor kinase (NTRK) gene fusion, entrectinib and larotrectinib, were approved for locally advanced or metastatic solid tumors . In June 2022, the FDA approved dabrafenib combined with trametinib to treat unresectable or metastatic solid tumors with a BRAFV600E mutation . This review aims to present and discuss the advances in molecular targeted therapy for patients with advanced CCA. 2. The Options for Molecular Targeted Therapy 2.1. Neurotrophic Tyrosine Receptor Kinase (NTRK) Gene Fusion-Positive Cholangiocarcinoma (CCA) Molecular profiling of solid tumors has identified clinically actionable fusions of the NTRK1, NTRK2, and NTRK3 genes, which encode neurotrophic tropomyosin receptor kinase (NTRK) . NTRK fusion products activate the TRK gene and, subsequently, the downstream signaling pathways, PI3K and MAPK, leading to tumor cell proliferation and invasion . Therefore, NTRK inhibitors are promising targeted therapies for patients with NTRK fusion-positive cancers and have shown antitumor responses in NCSLC, melanoma, and other tumors . NTRK gene fusions have been identified in 1-3% of patients with CCA . Table 2 shows the results of pivotal clinical trials that assessed the outcomes of NTRK inhibitors in NTRK fusion-positive metastatic or unresectable locally advanced solid tumors. Larotrectinib is a first-generation, highly selective pan-NTRK competitive inhibitor that suppresses cancer cell proliferation . It has shown immediate, robust, and long-lasting anticancer efficacy in pediatric and adult patients with solid tumors harboring TRK fusions . Drilon and colleagues conducted a phase 1 trial in adults (NCT02122913), a phase 1/2 trial in children (NCT02637687), and a phase 2 trial in children and adults (NCT02576431) with locally advanced or metastatic solid tumors who had received previous standard systemic therapy and were then given larotrectinib (100 mg twice daily), see Table 1 . A total of 55 patients with 17 TRK fusion-positive tumor types included two patients (4%) with CCA . The objective response rate (ORR) was high, at 80% (95% CI, 67-90) . At one year, 55% of patients were still progression-free . The median duration of response (MDR) and the progression-free survival (PFS) remain unmet . The most common toxicities >= grade 3 included a raised ALT or AST level (9%), anemia (3.6%), reduced neutrophil count (3.6%), and nausea (3.6%) . Based on these findings, larotrectinib was granted accelerated approval by the FDA in November 2018 for adult and pediatric patients with NTRK-positive solid malignant tumors, either metastatic or where surgical resection is unfeasible due to severe morbidity, who have progressed on systematic therapy . Larotrectinib is also approved for patients with no satisfactory alternative treatments . Currently, the MD Anderson Cancer Center and the National Cancer Institute (NCI) are conducting a phase 2 trial to investigate the efficacy of larotrectinib in previously treated patients with locally advanced or metastatic solid tumors and NTRK gene amplification (NCT04879121). Another ongoing phase 2 trial aims to assess the efficacy of larotrectinib in pediatric patients with relapsed or refractory advanced solid tumors with NTRK gene fusion (NCT03213704), Table 3. Entrectinib is another selective pan-TRK inhibitor with activity against ROS1 and ALK . In two phase I studies (ALKA-372-001 and STARTRK-1), entrectinib was administered to 119 patients with relapsed or refractory advanced/metastatic solid tumors harboring NTRK1/2/3, ROS1, or ALK gene fusions . Entrectinib was well-tolerated and only 15% of patients required a dose modification . The most common grade >= 3 toxicities included fatigue/asthenia (4%), weight increase (2%), diarrhea (1%), and eosinophilic myocarditis (1%), Table 2 . The phase 2 STARTRK-2 trial was an open-label, multicenter, global basket study that included patients with solid tumors harboring NTRK1/2/3, ROS1, or ALK gene fusions (NCT02568267). A focused integrated analysis on NTRK fusion-positive tumors showed that at a median follow-up of 12.9 months (interquartile range (IQR), 8.77-18.76), the median duration of response was 10 months (95% confidence interval (CI), 7.1-not reached) and the objective response rate (ORR) was 57% (95% CI, 43.2-70.8) . The median overall survival (OS) was 21 months (95% CI, 14.9-NE) and the median progression-free survival (PFS) was 11.2 months (95% CI, 8.0-14.9) . Major adverse events (>=3 grade) were reported in 61.6% of patients and included anemia (12%), an increase in weight (10%), and fatigue (7%), with no patient mortality, Table 2 . Based on these findings, entrectinib gained accelerated approval by the FDA in August 2019 at a dose of 600 mg once daily . Approval was for use in patients with NTRK gene fusion and metastatic or unresectable locally advanced solid tumors, who have progressed on systemic therapy or have no satisfactory alternative treatment . The approval of entrectinib provides an additional treatment option for patients with advanced cancer, potentially creating the opportunity for patients and their physicians to choose between different therapies . Larotrectinib is available in a liquid formulation approved for children younger than 12 years old, whereas entrectinib is not. However, entrectinib may be effective for children with brain tumors, while the efficacy of larotrectinib for primary and metastatic brain tumors is currently being evaluated . The two drugs also have different side effect profiles. The adverse events seen most frequently in the larotrectinib trials include increased ALT or AST, fatigue, and vomiting. Warnings and precautions for larotrectinib include neurotoxicity, hepatotoxicity, and embryo-fetal toxicity. Entrectinib has additional warnings and precautions, including congestive heart failure, CNS effects, and skeletal fractures . The National Comprehensive Cancer Network (NCCN) guidelines recommend larotrectinib and entrectinib as first-line or subsequent-line (following disease progression) treatment options for unresectable or metastatic iCCA and eCCA with NTRK gene fusions. Both entrectinib and larotrectinib are approved in the United States and Europe for the treatment of unresectable or metastatic solid tumors with NTRK gene fusion and progression after previous therapy . However, there are currently limited data for patients with CCA. 2.2. Cholangiocarcinoma (CCA) with BRAFV600E Mutations Mitogen-activated protein kinase (MAPK) signaling is essential for cell growth and survival through the RAS/RAF/MEK/ERK pathway . The BRAF gene is an oncogene whose protein product upregulates the RAS/RAR/MEK pathway . BRAF mutations have been identified in several solid malignancies, including colorectal cancer, NSCLC, and melanoma . More than 50 different BRAF mutations have been reported, with the V600E point mutation being the most common mutation (BRAFV600E) . In BRAFV600E, valine (V) is substituted by glutamic acid (E) at amino acid 600, resulting in activating BRAF with subsequent tumor growth and spread . In CCA, BRAF mutations are uncommon, occurring almost exclusively in iCCAs, with a prevalence ranging between 5% and 7%, and with the BRAFV600E mutation in 1.5% of patients with iCCA . Dabrafenib is a competitive inhibitor of the RAF protein, which causes apoptosis by decreasing downstream phosphorylation of MEK and ERK, arresting the cell cycle in G1, and activating caspase-3/7 . Even if a tumor initially responds to dabrafenib alone, it may eventually become resistant to treatment if another pathway activates the MEK protein . Trametinib is a selective inhibitor of MEK1/MEK2 and is used with dabrafenib, which prevents tumors from using this escape mechanism . Trametinib reduces cell proliferation, causes G1 cell-cycle arrest, and induces apoptosis . The combination of these drugs in targeting MEK and BRAF has yielded promising results (Table 2). In the phase 2, single-arm, open-label trial ROAR, the BRAF cohort included 43 adult patients with BRAFV600E-mutated CCA with metastatic, locally advanced, unresectable, or recurrent disease that had progressed on prior therapy . Patients received trametinib 2 mg once daily and dabrafenib 150 mg twice daily, with a mean follow-up of 10 months . The ORR was 51% (95% CI, 36-67), the mean OS was 14 months (95% CI, 10-33), the mean PFS was 9 months (95% CI, 5-10), and the MDR was 9 months (95% CI, 6-14) . Increased gamma-glutamyl transferase (GGT) (12%), low WBC count (7%), and pyrexia (7%) were the most common grade >= 3 adverse events, Table 2 . Salama et al. reported results from the NCI-MATCH trial, a single-arm, open-label study that enrolled 29 patients with different solid tumors that progressed on standard lines of therapy, including four patients with iCCA . Patients were given a continued dosing of dabrafenib (150 mg twice a day) and trametinib (2 mg once daily) . The ORR was 38% (90% CI, 22.9 -54.9%), the median OS was 28.6 months, the median PFS was 11.4 months (90% CI, 8.4-16.3), and the median MDR was 25.1 months (90% CI, 12.8-NE) . Three of the four patients with CCA had a partial response and grade >= 3 adverse events occurred in 65.7% of the enrolled patients . Fatigue (11.4%), decreased neutrophil count (8.6%), and decreased WBC count (8.6%) were the most frequently reported grade >= 3 adverse events associated with the treatment, Table 2 . The results of these trials supported the FDA approval of the combination of dabrafenib and trametinib for treating adults and children >6 years with BRAFV600E mutation-positive, unresectable, or metastatic solid tumors who have progressed on prior therapy . Other BRAF Inhibitors Currently Undergoing Clinical Trials In a phase 1 study, patients with BRAFV600-mutated solid tumors (including CCA) are currently being evaluated for a response to ABM-1310, a selective inhibitor of BRAFV600E mutation tumors (NCT04190628). Patients with advanced solid tumors, including biliary tract cancers, with BRAF mutations, are the focus of a phase 1 study of BGB-3245, a second-generation BRAF inhibitor (NCT04249843), Table 3. Combining the selective ERK1/2 inhibitor JSI-1187 with a BRAF inhibitor is another potential study strategy. Despite the significant advances in managing patients with BRAFV600 mutations, further studies are required. For example, in studying the efficacy of dabrafenib and trametinib and concurrent mutations of TP53 and BRAFV600E, early studies reported that this was associated with a more aggressive disease, resulting in less clinical benefits from dabrafenib and trametinib . In addition, patients with BRAFV600E/TP53 mutations were associated with reduced PFS and OS . 2.3. Cholangiocarcinoma (CCA) with Fibroblast Growth Factor Receptor 2 (FGFR2) Gene Fusion or Rearrangement Alterations in the FGFR gene and dysregulated FGFR signaling play a role in the development and progression of several types of cancer, including CCA. Four receptors belong to the FGFR family, including FGFR1, 2, 3, and 4, which share a cytoplasmic tyrosine kinase domain . FGFR2 alterations include rearrangements, amplifications, and mutations, present in 10-16% of patients with iCCA . These alterations activate mitogen-activated protein kinases (MAPKs), triggering constitutive signaling cascades that prompt tumor cell proliferation, survival, migration, and angiogenesis . Therefore, FGFR inhibitors are promising targeted therapies that can potentially improve the survival of patients with CCA. Initially, non-selective tyrosine kinase inhibitors (TKIs) were investigated in phase 1/2 clinical trials and showed low antitumor activity and a limited survival benefit . More recently, selective FGFR inhibitors were introduced for patients with FGFR2 fusion-positive iCCA and resulted in a significant clinical response, prompting phase 2/3 trials and accelerated FDA approvals . Pemigatinib is a selective inhibitor of FGFR1, 2, and 3 that competitively inhibits the autophosphorylation and FGFR-mediated signaling cascades in tumor cells . In the phase 2, multicenter, open-label FIGHT-202 trial, previously treated patients with metastatic CCA with FGFR2 fusions or FGFR2 rearrangements (n = 107), other FGFR mutations (n = 20), or wild-type FGFR (n = 18) received 13.5 mg of pemigatinib once daily on day 1-14 of a 21-day cycle . In patients with FGFR2 fusions or FGFR2 rearrangements, the objective response rate (ORR) was 35.5% (95% CI, 26.5-45.4%) . The median PFS and OS were 6.9 and 21.1 months, respectively . Up to 64% of the patients had grade >= 3 toxicities that included hyper/hypophosphatemia (12%), arthralgia (6%), fatigue (5%), and retinal detachment (4%), Table 2 . Based on these results, pemigatinib became the first FDA-approved targeted therapy for previously treated metastatic CCA with FGFR2 fusions or FGFR2 rearrangements . Currently, FIGHT-302 is an ongoing phase 3 clinical study comparing pemigatinib with gemcitabine and cisplatin chemotherapy to determine the drug's efficacy in the first-line treatment of CCA (NCT03656536), Table 3. Infigratinib is another highly selective ATP-competitive FGFR1-3 inhibitor that showed promising antitumor activity in patients with FGFR2 fusions in early-phase trials . Patients with advanced iCCA resistant to chemotherapy were enrolled in a phase 2 study of infigratinib in a multicenter, open-label, phase 2 trial . Of the 122 enrolled patients, 108 had positive FGFR2 fusions or FGFR2 rearrangements . Patients received 25 mg once daily infigratinib for 21 days in a 28-day cycle . In patients with FGFR2 fusions or FGFR2 rearrangements, the ORR was 23.1% (95% CI, 15.6-32.3%), indicating clinically significant activity after treatment . In this trial, one patient had a complete response (CR) and 24 patients had partial responses . The median duration of response (DOR) was five months (95% CI, 3.7-9.3), and eight patients had a maintained response for more than six months . Two-thirds of the patients (66.2%) had grade >= 3 toxicities, with hypophosphatemia (14.1%) and hyperphosphatemia (12.7%) being the most common adverse events, Table 2 . A phase 1 dose-escalation study showed that the risk of hyperphosphatemia in patients receiving infigratinib increased with higher drug exposure and was associated with higher antitumor activity . On May 2021, the FDA granted accelerated approval to infigratinib for previously treated locally advanced CCA or for patients with metastatic CCA with FGFR2 fusions or FGFR2 rearrangements . Infigratinib is also a potential targeted therapy for patients with untreated CCA with FGFR2 fusions or FGFR2 rearrangements. PROOF-301 is an ongoing phase 3 trial that recruited patients with untreated locally advanced CCA or patients with metastatic CCA with FGFR2 fusions or FGFR2 rearrangements . In PROOF-301, patients received either infigratinib or a standard chemotherapy regimen of gemcitabine and cisplatin . Infigratinib may potentiate the apoptotic activities of chemotherapies in multidrug-resistant tumor cells . Therefore, there is a potential future role for infigratinib in combination therapy for patients with advanced CCA, and the results of further clinical trials are awaited with interest. Futibatinib is an irreversible FGFR1-4 inhibitor that binds to the conserved cysteine residues of the P-loop of the kinase domain . Previous studies showed that futibatinib exhibited highly selective antitumor activities against tumor cells harboring FGFR mutations, particularly against mutations commonly associated with resistance to ATP-dependent FGFR inhibitors . In addition, the oral futibatinib molecule was associated with a comparatively lower number of drug-resistant clones than ATP-dependent FGFR inhibitors . Futibatinib was studied in a phase I trial that recruited 197 patients with previously-treated advanced solid tumors, 83 of which had CCA with a mutation, fusion, or amplification of FGFR2 (NCT02052778) . In this trial, 64 patients were treated with futibatinib at 20 mg and 19 patients at 16 mg . The results showed that futibatinib at 20 mg daily resulted in an ORR of 15.6%, a disease control rate (CDR) of 71.9%, a median DOR of 5.3 months, and a median PFS of 5.1 months . The updated analysis of the single-arm FOENIX-CCA2 phase 2 trial included 103 patients with previously-treated advanced or metastatic iCCA with FGFR2 fusions or FGFR2 rearrangements (NCT02052778) . Futibatinib 20 mg daily led to an ORR of 41.7% at a median follow-up period of 25.0 months . The DC was 82.5%, the median PFS was 8.9 months, and the median OS was 20.0 months, Table 2 . Based on these findings, on September 30, 2022, the FDA granted accelerated approval for futibatinib for adult patients with previously treated locally advanced or metastatic iCCA with FGFR2 gene fusion or rearrangement . Derazantinib is another potent anti-FGFR1-3 that showed promising antitumor activity in iCCA harboring FGFR2 fusions or FGFR2 rearrangement. In the phase 2 FIDES, 143 patients with iCCA harboring FGFR2 fusions (n = 103) or FGFR2 mutations or amplifications (n = 40) received derazantinib 300 mg once daily . In the cohort with FGFR2 fusions, the ORR was 21.4% (95% CI 13.9-30.5), with a median PFS and OS of 8.0 (95% CI 5.5-8.3) and 17.2 (95% CI 12.5-22.4) months, respectively . In the FGFR2 mutations or amplifications cohort, the ORR and DCR were 6.5% (95% CI 0.8-21.4) and 58.1% (95% CI 39.1-75.5). The median PFS was 8.3 (95% CI 1.9-16.7) and the median OS was 15.9 (95% CI 8.4-not estimated) . The most common grade >= 3 adverse events in the overall cohort were hyperphosphatemia (3%), asthenia/fatigue (5%), nausea (1%), and transaminase elevations (12%) . The phase 1/2 ReFocus trial evaluated RLY-4008, a selective FGFR2 inhibitor that can target FGFR resistance mutations, in CCA patients with FGFR2 fusions or FGFR2 rearrangements who did not receive FGFR inhibitors before. The preliminary analysis of 38 patients showed an ORR of 63.2% (95% CI 46.0-78.2) and a DCR of 94.7%. There was no observation of grade 4/5 adverse events . Despite the promising findings of selective FGFR inhibitors in patients with CCA and FGFR2 fusions or FGFR2 rearrangements, several issues remained unanswered. More than 150 fusion partners are associated with FGFR2 gene rearrangement, which results in significant molecular diversity in patients with FGFR2 fusions and rearrangements . Furthermore, nearly 50% of the gene fusion and rearrangement partners are present within the same chromosome of the FGFR2 gene . It is still unclear which patients might respond to FGFR2-targeted therapies and whether fusion partners can affect the response and survival with FGFR2-targeted therapies . Therefore, future research should focus on the effect of combined genetic alterations on the responses to FGFR2 inhibitors and their role in the development of acquired resistance, as well as identifying reliable response biomarkers for FGFR2-targeted therapies . 2.4. High Tumor Mutational Burden (TMB-H) as a Predictive and Prognostic Biomarker TMB is a recently identified biomarker of the response to immune checkpoint inhibitors (ICIs) in several types of cancer . The TMB is the number of somatic mutations per megabase (Mb) of the genomic sequence of a tumor . A TMB score of >=10 mutations/Mb has been proposed as a threshold with a high likelihood of neoantigen formation and represents TMB-H status . In patients with several tumor types, including melanoma, NSCLC, and bladder cancer, patients with TMB-H had better outcomes when treated with programmed death protein-1 and programmed cell death ligand-1 (PD-1/PD-L1) checkpoint inhibitors, or a cytotoxic T lymphocyte antigen 4 (CTLA-4) blockade . TMB-H has been detected in 27.3% of patients with iCCA . Pembrolizumab is a humanized antibody that inhibits the PD-1 receptors on lymphocytes by inhibiting the ligands that would block the receptor and inhibit an immune response . In a subgroup analysis of 102 patients with TMB-H, who were enrolled in the phase 2 KEYNOTE-158 trial and received pembrolizumab, the ORR was 29% (95% CI, 21-39%), the median OS was 11.7 months (95% CI, 9.1-19.1), and the median PFS was 2.1 months (95% CI, 2.1-4.1) . Notably, there were no patients with CCA in the TMB-H subgroup of this trial . However, based on these findings, in 2017, the FDA approved pembrolizumab to treat adult and pediatric patients with unresectable or metastatic solid tumors (including CCA) . The indications for this approval also required that the tumor tissue was TMB-H (>=10 mutations/megabase), and that the patients had progressed following prior therapy and for whom there were no satisfactory alternative treatment options . However, it is unclear if the TMB levels for predicting the response to the PD-1 blockade are consistent throughout the spectrum of solid tumors. There are situations in which a high TMB does not indicate a response. Therefore, novel biomarkers are required that reflect the complexity of the tumor immune microenvironment and consider the effects of tumor mutations on the immune response. 2.5. High Microsatellite Instability and Mismatch Repair Deficient (MSI-H/dMMR) Cholangiocarcinoma (CCA) The production of neoantigens and CD8+ T cell infiltrations into the tumor microenvironment are both increased in tumors with dMMR or high levels of MSI . MSI-H/dMMR makes the errors produced during DNA replication difficult to repair, which leads to mutations . The prevalence of MSI-H/dMMR in patients with iCCA ranges from 4.7-18.2% . As part of the phase 2 KEYNOTE-158 study, pembrolizumab 200 mg intravenously once every three weeks was administered to 233 patients with advanced solid tumors and confirmed MSI-H/dMMR . In this study, 22 (9.4%) patients had CCA . With a median follow-up of 13.4 months, the ORR was 34.3% (95% CI, 28.3-40.8%), the median OS was 23.5 months (95% CI, 13.5-NR), and the median PFS was 4.1 months (95% CI, 2.4-4.9 months . The median duration of the response was not reached (range, 2.9-31.3 months) . A subgroup analysis of CCA showed that the ORR was 40.9% (95% CI, 20.7-63.6), the median OS was 24.3 months (95% CI: 6.5-NE), and the median PFS was 4.2 months (95% CI, 2.1-NE) . Adverse events >= grade 3 occurred in 34 patients (14.6%) . Pneumonitis (1.3%), severe skin reactions (1.3%), and colitis (0.9%) were the most common adverse events, Table 2 . In an open-label, single-arm, phase 2 clinical trial, 86 patients with 12 types of cancer, including four patients with CCA, with at least one prior cancer therapy and MSI-H/dMMR mutations, were included . The patients received 10 mg/kg of pembrolizumab every 14 days . The ORR was 53% (95% CI, 42-64%), the 2-year OS was 64% (95% CI, 53-78%), and the 2-year PFS was 53% (95% CI, 42-68%) . A subgroup analysis of patients with CCA showed that the ORR was 50%, the CR was 25%, the SD was 75%, and the disease control rate was 100% . Minor adverse events were reported in 20%, with the most common being diarrhea/colitis (6%), pancreatitis/hyperamylasemia (6%), fatigue (2%), and anemia (2%), Table 2 . Based on these findings, in 2020, the FDA approved the use of pembrolizumab in adults and pediatric patients who have unresectable or metastatic MSI-H/dMMR solid tumors that have progressed despite prior treatment, without satisfactory alternative treatment options . The results of other trials for MSI-H patients in solid tumors are awaited. For example, a phase 1/2 trial of pevonedistat, a selective NEDD8 inhibitor, in combination with pembrolizumab in patients with dMMR/MSI-H solid cancers is ongoing (NCT04800627), Table 3. Dostarlimab is another anti-PD-1 monoclonal antibody . The phase 1 GARNET study was a non-randomized, multicenter, open-label trial to evaluate the safety and efficacy of dostarlimab (500 mg every 3 weeks for four cycles, then 1000 mg every 6 weeks) in 106 patients with advanced solid tumors (two of whom had CCA) with confirmed MSI-H/dMMR, one of whom had a biliary tract cancer . The ORR was 38.7% (95% CI, 29.4-48.6) . With a median duration of follow-up of 12.4 months, the median DOR was not reached . At 12 months, the Kaplan-Meier estimate for the chance of response preservation was 91%, and at 18 months it was 80% . Approximately 8.3% of patients reported at least one grade 3 adverse event, including anemia (3.9%), elevated lipase (2.3%), elevated ALT (1.6%), and diarrhea (1.6%), Table 2 . Based on the findings from this study, the FDA approved dostarlimab in adult patients with MSI-H/dMMR recurrent or advanced solid tumors that progressed on or following prior treatment and were not candidates for satisfactory alternative treatment options . Given the limited single-agent activity and the limited number of patients with CCA included in these clinical trials, further studies are required to investigate novel immunotherapy combinations to enhance the treatment efficacy in patients with CCA. 2.6. Isocitrate Dehydrogenase Isoenzyme (IDH1) Gene Mutations in Cholangiocarcinoma (CCA) IDH1 gene mutations commonly occur in CCA . Missense mutations in the IDH1 R132 codon leads to the overproduction of the oncometabolite R-2-hydroxyglutarate (R-2HG) . In tumor progenitor cells, an increase in the R-2HG levels inhibits cellular differentiation and drives oncogenesis by promoting histone methylation and DNA methylation . The prevalence of an IDH1 mutation in iCCA has been estimated at 13% . Ivosidenib is a small molecule inhibitor of IDH1. In a phase 1, multicenter, open-label study, 73 patients with IDH1-mutant CCA (89% iCCA and 11% eCCA), refractory to other systemic therapy, were enrolled and received ivosidenib (200-1200 mg daily in 28-day cycles) . The ORR was 5% (95% CI, 1.5-13.4), the median OS was 13.8 months (95% CI, 11.1-29.3), and the median PFS was 3.8 months (95% CI, 3.6-7.3) . Approximately 23% of the included patients had grade >= 3 adverse events, including ascites (5%), anemia (4%), and fatigue (3%), Table 2 . This trial led to a multicenter, randomized, double-blind, placebo-controlled phase 3 study (ClarIDHy), which included 185 adult patients with advanced CCA with IDH1 mutations who had progressed on previous therapy . Patients were randomly assigned to oral ivosidenib 500 mg or matched placebo once daily in continuous 28-day cycles . In the intervention group, with a median follow-up of 6.9 months, the ORR was 2% (95% CI, 0.5-6.9), and the median PFS was significantly improved (median PFS 2.7 months; 95% CI, 1.6-4.2) . The median OS after accounting for the cross-over was 10.3 months (95% CI, 7.8-12.4), which was significantly better than the placebo (median OS = 5.1 months) . Grade >= 3 adverse events were reported in 30% of the patients . The most frequently reported adverse event grades >= 3 were ascites (7%), increased AST (5%), anemia (3%), and fatigue (3%), Table 2 . Based on this trial, the FDA approved ivosidenib for the treatment of adult patients with unresectable locally advanced or metastatic IDH1-mutated CCA who had been previously treated . PARP inhibitors are also being studied in this subgroup of patients as they exhibit dysregulated homologous recombination repair. The National Cancer Institute (NCI) is conducting a phase 2 clinical trial that aims to investigate the safety and efficacy of olaparib as a subsequent line therapy for patients with advanced solid tumors (including CCA) with IDH1 or IDH2 mutations (NCT03212274). Another ongoing study combined ceralasertib and olaparib in patients with refractory CCA and advanced solid tumors with IDH1/2 (NCT03878095), Table 3. The use of IDH1 inhibitors as single treatments has shown promising results in targeted therapy of malignancies harboring IDH1 mutations in preclinical and clinical settings. However, these studies are preliminary and currently include small numbers of patients with CCA. 2.7. Erb-B2 Receptor Tyrosine Kinase 2 (ERBB2)/Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Cholangiocarcinoma (CCA) The ERBB2 gene encodes HER2, a receptor tyrosine kinase found in the plasma membrane . ERBB2 triggers several signaling pathways involved in tumor growth . Tumorigenesis is associated with HER2 and MAPK pathway dysregulation . The overexpression of HER2 has been reported in 5.8% of iCCA and 13-20% of eCCA . Pertuzumab and trastuzumab are monoclonal antibodies that target HER2 and are used to treat HER2-positive malignancies . The combination of pertuzumab and trastuzumab suppresses HER2-AKT signaling by inhibiting both the ligand-induced and ligand-independent HER2-HER3 complex formations . A phase 2, single-arm, multicenter trial called MyPathway included 39 patients with previously treated HER2-positive metastatic CCA . Patients were treated with pertuzumab (840 mg loading dose and 420 mg every three weeks) plus trastuzumab (8 mg/kg loading dose, 6 mg/kg every three weeks) . The ORR was 23% (95% CI, 11-39), the median PFS was 4.0 months (95% CI, 1.8-5.7), and the MDR was 10.8 months (95% CI, 0.7-25.4) . Grade >=3 adverse events were reported in 46% of patients, with the most common being an increase in the ALT and AST (13%) and an increase in ALP (10%), Table 2 . These were promising results for patients with HER2-mutated CCA. However, regulatory approval for patients with CCA is awaited. More recently, trastuzumab deruxtecan (T-DXd) showed promising antitumor activity in HER2-positive advanced solid tumors, including CCA. In a phase 1 trial of 60 patients with advanced, non-breast/non-gastric, HER2-mutant solid tumors (NCT02564900), the ORR was 28.3% and the median PFS was 7.2 (95% CI 4.8-11.1) months . The phase 2 HERB trial recruited 32 patients (24 with HER2-positive and eight with HER2-low) BTCs who received T-DXd. The efficacy cohort included 22 patients (9 had CCA). In patients with HER2-positive BTCs, the ORR was 36.4%, the median PFS was 4.4 months, and the median OS was 7.1 months. In the HER2-low group, the ORR, median PFS, and median OS were 12.5%, 4.2 months, and 8.9 months, respectively. The rate of grade >= 3 adverse events was 81.3% . Several ongoing studies aim to investigate targeted HER2 agents in treating patients with CCA with ERBB2 mutations (Table 3). In the front-line setting, gemcitabine combined with cisplatin and trastuzumab and the combination of gemcitabine, cisplatin, and varlitinib are currently being studied in two clinical trials (NCT03613168 and NCT02992340). In addition, HER2-targeting agents are currently being studied for subsequent lines of therapy, either as monotherapy or in combination with standard chemotherapy agents. Ongoing trials include: the oral HER2 covalent inhibitor, TAS0728, (NCT03410927); the HER2 antibody-drug conjugate, trastuzumab deruxtecan (NCT04482309 and JMA-IIA00423); the antibody-drug conjugate, RC48-ADC, (NCT04329429); capecitabine plus the dual HER2 and EGFR inhibitor, varlitinib (NCT03093870); chemotherapy (5-FU or IRI or Cape) plus trastuzumab (NCT03185988); and chemotherapy plus the HER2-targeted bispecific antibody, zanidatamab (NCT02892123). The results of these ongoing trials may provide multiple options for targeted treatments for patients with CCA in the molecular subgroup and improve patient survival. 2.8. RET Gene Fusion-Positive Cholangiocarcinoma More than three decades have passed since the discovery of the gene encoding the receptor tyrosine kinase, RET . RET rearrangements and mutations are recognized as treatable drivers of oncogenesis . Certain RET fusion proteins and activating point mutations can drive oncogenesis and tumor progression by activating downstream signaling pathways, leading to uncontrolled cell proliferation . RET gene fusions are present in between 1% and 2% of NSCLC and thyroid cancers and represent potential targets for therapeutic inhibition of RET kinase . However, RET fusions seem rare in CCA, and data regarding their exact prevalence in CCA are limited . Pralsetinib is a selective inhibitor of the RET receptor tyrosine kinase. In the phase 1/2, open-label ARROW trial, 29 patients with RET fusion-positive solid tumors were included, with three patients with CCA . Patients received a starting dose of pralsetinib of 400 mg QD . The ORR was 57% (95% CI, 35-77%), the median OS was 13.6 months (95% CI, 7.5-NE), the median PFS was 7.4 months (95% CI, 5.1-13.6), and the median duration of response was 11.7 months (95% CI, 5.5-19.0) . Altogether, 69% of patients had grade >= 3 adverse events that included neutropenia (31%), anemia (14%), and increased AST (10%), Table 2 . Based on the findings of this trial, the FDA approved pralsetinib for adult and pediatric patients with advanced or metastatic RET-fusion-positive lung and thyroid cancers for whom systemic therapy is indicated . Selpercatinib is another highly selective inhibitor of the RET receptor tyrosine kinase, with CNS activity . In the phase 1/2, open-label LIBRETTO-001 trial, 45 patients with RET fusion-positive solid tumors other than lung or thyroid tumors were included, with two patients with CCA . Of the 45 patients, 43 received a starting recommended dose of 160 mg BID. In the 41 patients who were evaluated for efficacy, the ORR was 43.9% (95% CI, 28.5-60.3), the median OS was 18.0 months (95% CI, 10.), the median PFS was 13.2 months (95% CI, 7.4-26.2), and the median duration of response was 24.5 months (95% CI: 9.2-NE). One patient with CCA was evaluated for efficacy; the ORR was 100% and the duration of response was 5.6 months . Altogether, 49% of patients had grade >= 3 adverse events that included hypertension (22%), increased ALT (16%), and increased AST (13%), Table 2 . Selpercatinib is currently approved for locally advanced or metastatic RET-fusion-positive solid tumors . Again, further studies are needed to focus on CCA to validate these findings in this group of patients. 3. Liquid Biopsy for Assessment of Circulating Tumor DNA (ctDNA) and Cholangiocarcinoma (CCA) Liquid biopsies refer to blood sampling to detect circulating tumor DNA (ctDNA), circulating cell-free RNA (ccfRNA), and cell-free DNA (cfDNA) . Liquid biopsy as an adjunctive diagnostic method has gained popularity over the last decade due to its potential benefits for cancer patients . The most commonly interrogated element in liquid biopsies is ctDNA or DNA fragments produced from tumors . Treatment resistance tracking, response monitoring, target selection, relapse detection, and early diagnosis are the potential benefits of identifying tumor-derived material in liquid biopsies . Although liquid biopsy is a potentially useful diagnostic tool for patients with CCA, this modality remains underexplored in CCA. Advances in this diagnostic area for patients with CCA have been limited by several practical factors, including the small amounts of ctDNA shed into the bloodstream in patients with localized tumors . On the other hand, CCA is an internal malignancy and it is often difficult to obtain a tissue biopsy. It is also challenging to acquire sufficient tumor cells for diagnosis on aspiration cytology, and these challenges can prevent adequate molecular tumor profiling for CCA . Therefore, blood-derived ctDNA may play an important role in identifying molecular alterations in patients with CCA who may not have an adequate biopsy or cytology sample available for analysis . Consistent mutation findings between tumor tissue and ctDNA were reported in 2015 by Zill et al. in a prospective study of 26 pancreaticobiliary cancers, including eight patients with CCA . In this preliminary study, 93% of mutations found in tissue samples were also identified by cfDNA . In 2019, Mody et al. analyzed ctDNA from 138 patients with biliary tract cancers and identified genetic alterations in 89% of the samples . Recently, Kumari et al. evaluated the diagnostic role of cfDNA in gallbladder carcinoma . Serum was obtained from 34 patients with gallbladder carcinoma and 39 matched controls without malignancy . This study showed that the cfDNA levels were lower in healthy individuals than in patients with gallbladder cancer . In addition, there was a significant correlation between the cfDNA and the presence of jaundice, lymph node metastases, and overall disease TNM stage . Therefore, the quantitative analysis of cfDNA may have the potential to be a unique marker for the molecular detection of targeted therapies in CCA. Furthermore, the analysis of cfDNA may have a role in distinguishing between neoplastic and inflammatory conditions of the gallbladder and biliary tract identified by imaging but without available biopsy material. However, concerns remain about the overall sensitivity of ctDNA mutations for diagnosing early-stage CCA . An additional feature of ctDNA/cfDNA is to track the development of resistance to chemotherapy and targeted treatments . In 2019, Ettrich and colleagues sequenced 15 common gene mutations in ctDNA samples from patients with biliary tract cancer throughout their chemotherapy . In the iCCA cohort (n = 13), there was a 92% agreement between tissue samples and blood-derived ctDNA . The level of agreement for the overall cohort was 74% . A change in the mutational profile was also seen in 63% of chemotherapy-naive individuals after treatment . A study reported in 2017 showed that the integrative genomic analysis of cfDNA could identify acquired treatment resistance due to multiple recurrent point mutations in the FGFR2 kinase domain during tumor progression . 4. Conclusions Until recently, clinical studies considered CCA a homogeneous entity, which may have led to the limited antitumor activity of conventional treatment regimens. It is now apparent that the behavior and responses of CCA vary substantially according to the underlying molecular profile. These relatively recent findings highlight the crucial role of precision medicine in guiding the treatment selection for patients with CCA. The number of investigational and approved targeted therapies for CCA has increased exponentially in the past decade. Several targeted agents are now approved as first-line and subsequent treatments for patients with locally advanced or metastatic CCA. The selective FGFR inhibitors pemigatinib and infigratinib and the IDH1 inhibitor ivosidenib are now approved for previously treated patients with FGFR2 fusions or FGFR2 rearrangements and IDH1 mutations, respectively. These gene fusions, rearrangements, and mutations are present in a subset of patients with iCCA. Pemigatinib and infigratinib are also currently being investigated in the first-line setting. Other targeted therapies are available across solid tumors, including CCA, and include: NTRK inhibitors (entrectinib and larotrectinib); a BRAF/MEK inhibitor combination (dabrafenib and trametinib); pembrolizumab (for high >= 10 mutations/mb tumor mutational burden or mismatch repair defect cancers); and RET inhibitors (selpercatinib). Targeted therapies for other genomic alterations in CCA and solid tumors in general continue to be developed and explored. Further therapeutic possibilities for patients with CCA may emerge as our knowledge of the tumor microenvironment and its impact on tumor growth increases. Combined treatments that target both actionable mutations and the tumor microenvironment is another approach that assists with patient selection for the most appropriate molecular targeted therapy. The value of blood-derived ctDNA in the clinic is currently being explored in CCA, especially since tissue biopsies can be difficult in this type of cancer. 5. Future Directions Despite multiple FDA approved targeted therapies for patients with CCA, the overall survival for these patients remains dismal. Utilizing combination approaches with targeted therapies may offer some patients more benefit than single agents . Mechanisms of resistance to single agent therapies may include RNA silencing as well as multiple gene driven pathogenesis, which could be overcome with 'multiomic' patient diagnostics using genomic, proteomic, transcriptomic, and immunomic data as well as n-of-1 customized combination therapeutic approaches . Further, using patient-specific immunomic data may allow for a tailored immunotherapy-targeted treatment as well as being informed by specific genomic aberrations and the most logical immunotherapeutic target . A next step in improving outcomes in these patients likely involves identifying more therapeutic targets as well as overcoming secondary resistance mechanisms via targeting as many genomic alterations present within a specific tumor as possible . Author Contributions Conceptualization, J.J.A. Methodology, A.G. and J.J.A.; data curation, A.G.; writing--original draft preparation, A.G., R.K. and J.J.A.; writing--review and editing, A.G., R.K. and J.J.A.; visualization, J.J.A.; supervision, J.J.A. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest Amol Gupta declares no conflict of interest. Jacob J. Adashek serves on the advisory board for CureMatch, Inc. Kurzrock has received research funding from Boehringer Ingelheim, Debiopharm, Foundation Medicine, Genentech, Grifols, Guardant, Incyte, Konica Minolta, Medimmune, Merck Serono, Omniseq, Pfizer, Sequenom, Takeda, and TopAlliance and from the NCI; as well as consultant and/or speaker fees and/or advisory board for Actuate Therapeutics, AstraZeneca, Bicara Therapeutics, Inc., Biological Dynamics, Caris, Datar Cancer Genetics, Daiichi, EISAI, EOM Pharmaceuticals, Iylon, Merck, NeoGenomics, Neomed, Pfizer, Prosperdtx, Regeneron, Roche, TD2/Volastra, Turning Point Therapeutics, X-Biotech; has an equity interest in CureMatch Inc. and IDbyDNA; serves on the Board of CureMatch and CureMetrix, and is a co-founder of CureMatch. Figure 1 FDA-approved targets found in patients with cholangiocarcinoma. Current genomic targets with FDA-approved therapies in cholangiocarcinoma. MSI-H, microsatellite instability-high; dMMR, deficiency in mismatch repair; TMB-H, tumor mutation burden-high (>=10 mutations/mb). cancers-15-01578-t001_Table 1 Table 1 The frequency of genetic alterations according to the anatomic location of CCA. CCA Subtype iCCA (Affects Bile Ducts within the Liver) eCCA (Affects Bile Ducts Outside of the Liver) ARID1A 18-23% 14% BAP1 15-20% -- BRAF V600E 1.5% -- BRCA1 0.4% 2% BRCA2 2.8% 2.5% CDH1 11.8% -- CDKN2A/B 9-27% 9-28% ERBB2/HER2 5.8% 1.3-20% FGFR2 fusion 10-16% 0 IDH1/2 13-30% 4.7% KRAS 7-54% 36.7-46% MSI-H/dMMR 4.7-18.2% 4% PI3K 7% 5% SMAD4 -- 10.7% TP53 18-27% 18-68% Abbreviations: ARID1A: AT-rich interaction domain 1A; BAP1: BRCA1-associated protein 1; BRCA: breast cancer antigen; CCA, cholangiocarcinoma; CDH1: cadherin-1; eCCA: extrahepatic CCA; ERBB: erythroblastic leukemia viral oncogene homolog; FGFR: fibroblast growth factor receptor; iCCA: intrahepatic CCA; IDH: isocitrate dehydrogenase; KRAS: Kirsten rat sarxoma viral oncogene homolog; MSH, microsatellite instability; MSI: molecular microsatellite instability; PIK3: phosphoinositide-3-kinase; SMAD4: mothers against decapentaplegic homolog 4; TMB, tumor mutational burden.; TP53: tumor protein 53. cancers-15-01578-t002_Table 2 Table 2 Examples of targeted therapy trials. Target (Gene) % in CCA FDA-Approved Drug Date of Approval Trials Total ORR OS PFS Disease-Free Survival Duration of Response Major Adverse Events (Grade >= 3) No. of CCA/ BTCs (%) NTRK gene fusion-positive 3-9% Entrectinib 15 August 2019 Drilon et al., 2017 55 (100%) 100% (95% CI: 44 to 100) NR NR NR For the three patients, the DoR was 2.6 months, 4.6 months, and 15.1 months Fatigue/asthenia: 5 (4%) Weight increase: 2 (2%) Diarrhea: 1 (1%) Arthralgia: 1 (1%) NR NR NR NR NR NR Doebele et al., 2020 54 (100%) 57% (95% CI: 43.2 to 70.8) 21 months (95% CI 14.9 to NE) 11.2 months (95% CI 8.0 to 14.9) NR 10.4 months (95% CI: 7.1 to NE) Anemia: 8 (12%) Increased weight: 7 (10%) Fatigue: 5 (7%) 1 (2%) NR NR NR NR NR Larotrectinib 26 November 2018 Drilon et al., 2018 55 (100%) 80% (95% CI: 67 to 90) NR Not reached NR Not reached Anemia: 114 (11%) Increased weight: 73 (7%) Decreased neutrophil count: 73 (7%) Increased ALT and AST: 73 (7%) 2 (4%) 50% objective tumor shrinkage NR NR NR NR BRAF-V600E 1.5 Trametinib plus dabrafenib 22 June 2022 Subbiah et al., 2020 43 (100%) * 51% (95% CI: 36 to 67) 14 months (95% CI: 10 to 33) 9 months (95% CI: 5 to 10) NR 9 months (95% CI: 6 to 14) g-glutamyltransferase increased: 5 (12%) Decreased WBC count: 3 (7%) Pyrexia: 3 (7%) Salama et al., 2020 29 (100%) 38% (95% CI: 22.9% to 54.9%) 28.6 months 11.4 months (90% CI: 8.4 to 16.3) NR 25.1 months (90% CI: 12.8 to NE) Fatigue: 4 (11.4%) Decreased neutrophil count: 3 (8.6%) Decreased WBC count: 3 (8.6%) 4 (13.8%) 75% (3/4 pts), one is ongoing for 29 months NR NR NR NR FGFR2 fusion or rearrangements 10-16% Pemigatinib 17 April 2020 Abou-Alfa et al., 2020 107 (100%) * 35.5% (95% CI: 26.5 to 45.4%) 21.1 months (95% CI: 14.8 to NE) 6.93 months (95% CI: 6.18 to 9.59) NR 7.5 months (95% CI: 5.7 to 14.5) Hypophosphataemia: 10 (7%) Stomatitis: 8 (5%) Arthralgia: 6 (4%) Palmar-plantar erythrodysesthesia: 6 (4%) Infigratinib 28 May 2021 Javle et al., 2021 108 (100%) * 23.1 (95% CI 15.6 to 32.3%) 12.5 (95% CI: 9.9 to 16.6) 6.8 (95% CI: 5.3 to 7.6) NR 5.4 (95% CI: 3.7 to 7.4) Hypophosphatemia: 10 (14.1%) Hyperphosphatemia: 9 (12.7%) Hyponatremia: 8 (11.3%) Futibatinib 30 September 2022 Goyal et al. 103 (100%) * 41.7% 20.0 8.9 NR 9.5 NR MSI-H/dMMR tumors 4.7-18.2% Pembrolizumab 16 June 2020 Le et al., 2017 86 (100%) 53% (95% CI: 42% to 64%) Not reached 2-year OS: 64% (95% CI: 53% to 78%) Not reached 2-year PFS: 53% (95% CI: 42% to 68%) NR NR Diarrhea/colitis: 5 (6%) Pancreatitis/Hyperamylasemia: 5 (6%) Fatigue: 2 (2%) Anemia: 2 (2%) 4 (4.7%) NR NR NR NR NR Marabelle et al., 2019 233 (100%) 34.3% (95% CI: 28.3 to 40.8) 23.5 months (95% CI: 13.5 to NR) 4.1 months (95% CI: 2.4 to 4.9) NR Not reached (range, 2.9 to 31.3+ months) Fatigue: 2 (0.9%) Asthenia: 1 (0.4%) 22 (9.4%) 40.9% (95% CI: 20.7 to 63.6) in CCA pts 24.3 months (95% CI: 6.5 to NE) in CCA pts 4.2 months (2.1 to NE) in CCA pts NR NR Dostarlimab 17 August 2021 Andre et al., 2021 (Abstract) 106 (100%) 38.7% (95% CI: 29.4 to 48.6) NR NR NR Not reached Lipase increased: 2 (1.4%) 2 (1.9%) 100% CR NR NR NR NR IDH1 13% Ivosidenib 25 August 2021 Lowery et al., 2019 73 (100%) * 5% (95% CI: 1.5 to 13.4) 13.8 months (95% CI: 11.1 to 29.3) 3.8 months (95% CI: 3.6 to 7.3) NR NR Ascites: 4 (5%) Anemia: 3 (4%) Fatigue: 2 (3%) Abou-Alfa et al., 2020 185 (100%) * 2% (95% CI: 0.5 to 6.9) 10.8 months (95% CI: 7.7 to 17.6) 2.7 months (95% CI: 1.6 to 4.2) NR NR Ascites: 9 (7%) Aspartate aminotransferase increased: 6 (5%) Anemia: 4 (3%) Fatigue: 4 (3%) HER2-positive tumor 5.8% of iCCA and 13-20% of eCCA Pertuzumab plus trastuzumab Not yet approved in CCA Javle et al., 2021 39 (100%) * 23% (95% CI: 11 to 39) 10.9 months (95% CI: 5.2 to 15.6) 4.0 months (95% CI: 1.8 to 5.7) NR 10.8 months (95% CI: 0.7 to 25.4) Increased alanine aminotransferase: 5 (13%) Increased aspartate aminotransferase: 5 (13%) Blood alkaline phosphatase increased: 4 (10%) RET fusion-positive NR Pralsetinib Not yet approved in CCA Subbiah et al., 2022 23 (100%) 57% (95% CI: 35%-77%) 13.6 months (95% CI: 7.5 to NE) 7.4 months (95% CI: 5.1 to 13.6) NR 11.7 months (95% CI: 5.5 to 19.0) Neutropenia: 9 (31%) Anemia: 4 (14%) Increased AST: 3 (10%) 3 (13%) 66.7% NR NR NR NR Selpercatinib 21 September 2022 Subbiah et al., 2022 45 (41 evaluated for efficacy) 43.9% (95% CI 28.5-60.3) 18.0 months (95% CI: 10. estimated) *** 13.2 months (95% CI: 7.4-26.2) NR 24.5 (95% CI: 9.2-Not estimated) Hypertension (22%) Increased alanine aminotransferase (16%) Increased aspartate aminotransferase (13%). 2 (1 evaluated for efficacy) 100% 5.6 months * All patients were CCA/BTCs; *** investigator assessed. Abbreviations: BTCs: biliary tract cancers; CCA: cholangiocarcinoma; CI: confidence interval; DoR: duration of response; eCCA: extrahepatic cholangiocarcinoma; iCCA; intrahepatic cholangiocarcinoma; NE: not estimated; NR: not reported; OS: overall survival; ORR: objective response rate; PFS: progression-free survival; WBCs: white blood cells. cancers-15-01578-t003_Table 3 Table 3 Examples of ongoing trials in CCA. Target Phase Clinical Trial Identifier Treated Cancer Group Experimental Arm Control Arm Primary Outcome Secondary Outcome (Main) First Line FGFR2 fusion/rearrangement III NCT03656536 CCA Pemigatinib Gemcitabine/Cisplatin PFS OS, OR, DOR, DCR III NCT03773302 CCA Infigratinib Gemcitabine/Cisplatin PFS OS, DCR, DOR, BOR III NCT04093362 iCCA Futibatinib Gemcitabine/Cisplatin PFS OS, safety, ORR, DCR II NCT03230318 iCCA Derazantinib None ORR, PFS OS, safety, DCR I/II NCT04526106 iCCA and other advanced tumors RLY-4008 None ORR, MTD, safety DOR, DCR, pharmacokinetics HER 2 mutations II NCT03613168 BTCs Trastuzumab plus gemcitabine/cisplatin None BOR, safety PFS, OS I/II NCT02992340 BTCs Varlitinib plus gemcitabine/cisplatin None MTD, safety, PFS, ORR OS, DOR, DCR, PK Subsequent lines NTRK gene NCT04879121 Advanced solid tumors Larotrectinib None ORR PFS, OS, safety, DOR, GMI, CBR II NCT03213704 Advanced solid tumors Larotrectinib None ORR PFS, safety, PK, changes in tumor genomics Non-V600E BRAF mutations II NCT03839342 Advanced solid tumors Bimimetinib + Encorafenib None ORR PFS, safety, DCR I NCT04190628 Advanced solid tumors ABM-1310 None MTD PFS, OS, safety, PK, ORR, DCR, DOR I NCT04249843 Advanced solid tumors BGB-3245 None Safety, MTD PFS, OS, PK, ORR, DCR, DORf I NCT04418167 Advanced solid tumors JSI-1187 monotherapy or in combination with dabrafenib None Safety PFS, OS, ORR, DOR, time to response, DCR, PK IDH1/2 mutations II NCT02428855 iCCA Dasatinib None ORR PFS, OS, safety II NCT03212274 CCA Olaparib None ORR PFS, OS, safety II NCT03878095 CCA Ceralasertib + Olaparib None ORR PFS, OS, safety, DOR I/II NCT02273739 Advanced solid tumors Enasidenib None DLT, ECOG Plasma concentration metrics I NCT04521686 CCA LY3410738 LY3410738 + Gemcitabine/Cisplatin MTD ORR, safety and tolerability, efficacy, PK dMMR/MSI-H I/II NCT04800627 Advanced solid tumors Pevonedistat in combination with Pembrolizumab None Recommended phase 2 dose, ORR PFS, OS, safety, changes in protein misfolding HER 2 mutations II/III NCT03093870 BTCs Varlitinib with Capecitabine Capecitabine ORR, PFS OS, safety, DOR, DCR, tumor size, ECOG II NCT03185988 Metastatic carcinoma of digestive system including BTCs Trastuzumab plus 5-FU or IRI or Capecitabine None RR OS, PFS, DCR, DOR, time of response, ECOG II jRCT2031180150 Advanced solid tumors Trastuzumab and Pertuzumab None ORR PFS, OS, safety, DOR II NCT02999672 CCA Trastuzumab emtansine None BOR PFS, OS, safety, PK II NCT02675829 Advanced solid tumors Ado-Trastuzumab emtansine None ORR None II NCT04482309 Advanced solid tumors Trastuzumab Deruxtecan None ORR OS, PFS, safety, DOR, DCR, PK, immunogenicity I/II NCT03410927 Advanced solid tumors TAS0728 None Safety, ORR OS, DOR, PK, DCR I NCT04764084 CCA Niraparib + Anlotinib None DLT, MTD PFS, ORR I NCT02892123 Advanced solid tumors Zanidatamab plus chemotherapy None MTD, Safety PFS, ORR, PK, antidrug antibodies I NCT02564900 Non-breast/non-gastric solid tumors Trastuzumab Deruxtecan None ORR DCR, BOR, DOR, PFS, OS, pharmacokinetics, safety BAP1 and other DDR genes II NCT03207347 CCA Niraparib None ORR PFS, OS, safety DNA repair gene mutation II NCT03207347 CCA Niraparib None ORR PFS, OS, safety Matched molecular therapy Matched molecular therapy N/A NCT04504604 Rare tumors FoundationOne CDx and FoundationOne Liquid CDx None % who receive a molecularly targeted matched, PFS Tumor molecular profiles correlation to treatment outcome. Abbreviations: BOR: best overall response; BTCs: biliary tract cancers; CBR: clinical benefit rate; CCA: cholangiocarcinoma; DCR: disease control rate; DLT: dose-limiting toxicity; DOR: duration of response; ECOG: Eastern Cooperative Oncology Group; GMI: growth modulation index; iCCA: intrahepatic cholangiocarcinoma; MTD: maximum tolerated dose; N/A: not applicable; ORR: overall response rate; OS: overall survival; PFS: progression-free survival; PK: pharmacokinetics. 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. |
PMC10000384 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050779 cells-12-00779 Editorial Rho GTPases in Model Systems Filic Vedrana * Weber Igor * Division of Molecular Biology, Ruder Boskovic Institute, Bijenicka 54, HR-10000 Zagreb, Croatia * Correspondence: [email protected] (V.F.); [email protected] (I.W.) 01 3 2023 3 2023 12 5 77922 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 ). pmcSince the discovery of their role in the regulation of actin cytoskeleton 30 years ago, Rho GTPases have taken center stage in cell motility research. Over time, it has become clear that these "molecular switches" are also involved in the regulation of other cellular processes, such as cell polarization, cell differentiation and growth, membrane trafficking, and transcriptional regulation. The biological importance of Rho GTPases is exemplified by the fact that mammalian cells invest more than 150 genes that encode their direct regulators. Rho GTPases are essential signaling molecules in mammals and across the whole eukaryotic domain. This Special Issue of Cells represents a collection of review articles and original research papers covering Rho GTPases in model organisms and cell culture systems. It can be roughly divided into sections devoted to evolutionary aspects, screening and mechanistic approaches, and the roles of Rho GTPases in mammalian physiology and pathology. Evolutionary insight into the functional roles of Rho GTPases in simple model organisms can provide an invaluable perspective on their universal biological importance. Current knowledge and recent advances on how the fission yeasts Rho family GTPases regulate essential physiological processes, such as morphogenesis and polarity, cellular integrity, cytokinesis, and cellular differentiation, are presented by Vicente-Soler et al. . Although the genetic tools available in yeast are still unrivaled, the physiology of the actin cytoskeleton in these organisms is quite specific and distinct from metazoan cells. A much closer match is provided by the highly motile cells of amoebozoan protists, which share the composition and dynamics of the transient actin-based structures, in particular with mammalian cells of the hematopoietic lineage. Filic et al. provide an overview of the Rho signaling pathways that regulate the actin dynamics in Dictyostelium and compare them with similar signaling networks in mammals . Interestingly, although phylogenic algorithms do not identify strict homologies between Rho GTPases in the two groups, comprehensive functional studies established that canonical mammalian representatives, Rho, Rac and Cdc42, obviously have their functional analogues in Dictyostelium. Moving on into the realm of multicellularity, a review by Beljan et al. represents a compilation of the current knowledge concerning Rho-family GTPases in non-bilaterian animals, the available experimental data regarding their biochemical characteristics and functions, and an original bioinformatics analysis of their relationship with metazoan counterparts . Their findings provide a general insight into the evolutionary history of Rho-family GTPases in simple animals and support the notion that the ancestor of all animals probably contained Rho, Rac and Cdc42 homologs. Rho proteins of plants (ROPs) form a specific clade of Rho GTPases, which are involved in plant immunity and their susceptibility to diseases. In their review, Engelhard et al. summarize central concepts of Rho signaling in disease and immunity of plants and briefly compare them to important findings in the mammalian research field . Interesting similarities emerge, as follows: while invasive fungal pathogens may co-opt the function of ROPs for manipulation of the cytoskeleton that promotes pathogenic colonization, mammalian bacterial pathogens also initiate effector-triggered susceptibility for cell invasion via Rho GTPases. Zebrafish, as model vertebrates, offer a unique opportunity to explore the spatial and temporal dynamics of Rho GTPases within a complex environment at a level of detail unachievable in any other organism. Boueid et al. present a compilation of examples where the roles of Rho, Rac and Cdc42 in cell motility, developmental processes, angiogenesis, neural system and pathological processes in zebrafish were investigated using a set of powerful tools to follow and locally modulate Rho GTPases signaling and their function in real time, combined with rapidly evolving imaging and genetic techniques . Given the large complexity involved in the signaling networks centered on Rho GTPases, system-level research is required to fully grasp the extent of their biological roles and regulation. In their review article, Dahmene et al. highlight the recent large-scale studies, including proteomic approaches to map the full repertoire of Rho GTPases and Rho regulators protein interactions and high throughput screening strategies that unraveled new roles for understudied family members by using cell culture models and mouse embryos . An example of the high throughput screening approach is provided by Long et al., who developed and applied an image-based high-content screen using RNA interference to systematically perturb each of the 21 Rho family members and assess their importance to the overall organization of the Golgi complex . Their analysis revealed previously unreported roles for two atypical Rho family members, RhoBTB1 and RhoBTB3, in the endomembrane traffic events. In addition to their localization at the plasma membrane and endomembranes, recent research demonstrates that active pools of different Rho GTPases also localize to the nucleus. Navarro-Lerida et al. discuss how the modulation of Rho GTPases driven by post-translation modifications provides a versatile mechanism for their compartmentalization and functional regulation . They stress that understanding how the subcellular sorting of active small GTPase pools occurs and what its functional significance is will contribute to the exploration of Rho GTPases as important therapeutic targets in cancer and other disorders. Indeed, it is becoming increasingly clear that small Rho GTPases play essential roles in human physiology and pathology. In their review article, Sarowar and Grabrucker discuss the role of three archetypical Rho GTPases in the modulation of dendritic spine morphogenesis in the amygdala, the core brain region associated with fear learning and conditioning . Dendritic spines are tiny, dynamic, and heterogeneous actin-rich protrusions on the surface of neuronal dendrites that receive input from an axon at the synapse. RhoA inhibits dendritic growth and dynamics, while Cdc42 and Rac1 promote them. By doing so, Rho GTPases and some of their modulators expressed in the amygdala play an important role in fear-related processes. Another example of the influence of Rho signaling on synaptic plasticity is provided by Figiel and colleagues . Synaptic remodeling mediated by matrix metalloproteinase 9 (MMP-9) is essential for long-term memory formation. MMP-9 may contribute to the dynamic remodeling of structural and functional plasticity by cleaving ECM components and cell adhesion molecules. Rho GTPases seem to be downstream effectors of MMP-9, and the authors review current knowledge on their roles in MMP-9-dependent signaling pathways in the brain, with emphasis on the influence of their post-translational modifications. Mao et al. explored the function of Rho GTPases during phagocytosis of spent photoreceptor outer segment fragments by retinal pigment epithelial (RPE) cells, which is essential for visual function . This process is mediated by Mer tyrosine kinase (MerTK) receptor signaling, and MerTK mutations cause complete blindness in early adulthood, for which widely applicable therapy is still unavailable. In their research, the authors show that efficient RPE phagocytosis requires the activation of Rac1 and the simultaneous suppression of RhoA activity downstream from MerTK. In MerTK-deficient RPE cells, elevated RhoA activity blocks phagocytic cup formation. However, inhibition of RhoA downstream effector ROCK is sufficient to restore the phagocytic capacity of MerTK-deficient RPE. Since ROCK inhibitors are already approved for common, long-term use for ocular disease, this study supports future efforts toward their use in simple therapy, possibly as eye drops. Veluthakal and Thurmond systematically summarize the role of different Ras superfamily GTPases in the normal functioning of pancreatic islet b-cells . Pancreatic islet b-cells take up glucose and initiate glucose metabolism that, via a plethora of signaling events, induces insulin granule exocytosis. The authors review the roles of Rho, Arf and Rab family members in the islet insulin secretory process and describe how the altered activity of GTPases can lead to b-cell dysfunction. Considering the important roles that Rho GTPases play in the regulation of physiological processes, it is no surprise that their altered activities significantly contribute to numerous pathological conditions. Humphries et al. provide an overview of the current understanding of the regulation and functions of Rho GTPases specifically in breast cancer . They show that, similarly to findings in other tumors, there are conflicting data concerning the role of Rho GTPases in breast cancer. However, the prevalent notion is that increased activation of Rho GTPases has tumor-promoting roles in breast cancer initiation, metastatic progression, chemoresistance, and radioresistance. Furthermore, Rho GTPases have important roles in diseases whose major contributor is chronic inflammation. Kilian et al. summarize the role of RhoA in stress-induced signaling from damaged cardiomyocytes to immune cells, which leads to immune cell activation, chronic inflammation and cardiac disease progression . They discuss the possible roles of RhoA signaling in cardiomyocytes, macrophages, neutrophils, and dendritic cells, which are important in the pathogenesis and progression of cardiac dysfunction. Atherosclerosis is another example of a chronic inflammatory immune-mediated condition implicated in the pathogenesis of coronary artery disease, a major cause of mortality worldwide. Lee et al. highlight the role of Rac-mediated inflammatory signaling in the mechanisms driving atherosclerotic calcification . They also discuss the off-target effects of statins, the most widely used therapy for hypercholesterolemia, on Rac immune signaling. Inflammation also has a crucial role in the development of gastrointestinal diseases, such as inflammatory bowel disease (IBD) and colorectal cancer. IBD is marked by the uncontrolled activation of immune cells and alterations to intestinal epithelial cells (IECs), characterized by increased tight junction permeability and altered cytoskeletal rearrangements. Pradhan et al. summarize the current knowledge on the roles of classical Rho GTPases in the context of intestinal homeostasis and disease, focusing on IECs and T cells . Finally, Hahmeyer and da Silva-Santos provide a comprehensive overview of the current knowledge about the role of Rho signaling pathways in sepsis, a life-threatening organ dysfunction caused by a dysregulated response to infection . They describe how Rho proteins, mainly Rac1 and RhoA, are involved in the development of sepsis-specific symptoms in different systems and cells, including the endothelium, vessels, and the heart. Author Contributions Conceptualization, V.F. and I.W.; writing--original draft preparation, V.F. and I.W.; writing--review and editing, V.F. and I.W. All authors have read and agreed to the published version of the manuscript. 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. Vicente-Soler J. Soto T. Franco A. Cansado J. Madrid M. The Multiple Functions of Rho GTPases in Fission Yeasts Cells 2021 10 1422 10.3390/cells10061422 34200466 2. Filic V. Mijanovic L. Putar D. Talajic A. Cetkovic H. Weber I. Regulation of the Actin Cytoskeleton via Rho GTPase Signalling in Dictyostelium and Mammalian Cells: A Parallel Slalom Cells 2021 10 1592 10.3390/cells10071592 34202767 3. Beljan S. Herak Bosnar M. Cetkovic H. Rho Family of Ras-Like GTPases in Early-Branching Animals Cells 2020 9 2279 10.3390/cells9102279 33066017 4. Engelhardt S. Trutzenberg A. Huckelhoven R. Regulation and Functions of ROP GTPases in Plant-Microbe Interactions Cells 2020 9 2016 10.3390/cells9092016 32887298 5. Boueid M. Mikdache A. Lesport E. Degerny C. Tawk M. Rho GTPases Signaling in Zebrafish Development and Disease Cells 2020 9 2634 10.3390/cells9122634 33302361 6. Dahmene M. Quirion L. Laurin M. High Throughput strategies Aimed at Closing the GAP in Our Knowledge of Rho GTPase Signaling Cells 2020 9 1430 10.3390/cells9061430 32526908 7. Long M. Kranjc T. Mysior M. Simpson J. RNA Interference Screening Identifies Novel Roles for RhoBTB1 and RhoBTB3 in Membrane Trafficking Events in Mammalian Cells Cells 2020 9 1089 10.3390/cells9051089 32354068 8. Navarro-Lerida I. Sanchez-Alvarez M. del Pozo M. Post-Translational Modification and Subcellular Compartmentalization: Emerging Concepts on the Regulation and Physiopathological Relevance of RhoGTPases Cells 2021 10 1990 10.3390/cells10081990 34440759 9. Sarowar T. Grabrucker A. Rho GTPases in the Amygdala--A Switch for Fears? Cells 2020 9 1972 10.3390/cells9091972 32858950 10. Figiel I. Kruk P. Zareba-Koziol M. Rybak P. Bijata M. Wlodarczyk J. Dzwonek J. 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PMC10000385 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050996 diagnostics-13-00996 Article Super-Resolution of Dental Panoramic Radiographs Using Deep Learning: A Pilot Study Mohammad-Rahimi Hossein Conceptualization Software Formal analysis Writing - original draft 1*+ Vinayahalingam Shankeeth Conceptualization Formal analysis Writing - review & editing 2+ Mahmoudinia Erfan Software Formal analysis Investigation 3 Soltani Parisa Data curation Writing - original draft 4 Berge Stefaan J. Formal analysis Writing - original draft 2 Krois Joachim Conceptualization Methodology Writing - review & editing 1 Schwendicke Falk Conceptualization Writing - review & editing Supervision 15 Kamburoglu Kivanc Academic Editor 1 Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health, 10117 Berlin, Germany 2 Department of Oral and Maxillofacial Surgery, Radboud University Nijmegen Medical Centre, 6525 GA Nijmegen, The Netherlands 3 Department of Computer Engineering, Sharif University of Technology, Tehran 11155, Iran 4 Department of Oral and Maxillofacial Radiology, Dental Implants Research Center, Dental Research Institute, School of Dentistry, Isfahan University of Medical Sciences, Isfahan 81746, Iran 5 Department of Oral Diagnostics, Digital Health and Health Services Research, Charite--Universitatsmedizin Berlin, 10117 Berlin, Germany * Correspondence: [email protected] + These authors contributed equally to this work. 06 3 2023 3 2023 13 5 99630 12 2022 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 ). Using super-resolution (SR) algorithms, an image with a low resolution can be converted into a high-quality image. Our objective was to compare deep learning-based SR models to a conventional approach for improving the resolution of dental panoramic radiographs. A total of 888 dental panoramic radiographs were obtained. Our study involved five state-of-the-art deep learning-based SR approaches, including SR convolutional neural networks (SRCNN), SR generative adversarial network (SRGAN), U-Net, Swin for image restoration (SwinIr), and local texture estimator (LTE). Their results were compared with one another and with conventional bicubic interpolation. The performance of each model was evaluated using the metrics of mean squared error (MSE), peak signal-to-noise ratio (PNSR), structural similarity index (SSIM), and mean opinion score by four experts (MOS). Among all the models evaluated, the LTE model presented the highest performance, with MSE, SSIM, PSNR, and MOS results of 7.42 +- 0.44, 39.74 +- 0.17, 0.919 +- 0.003, and 3.59 +- 0.54, respectively. Additionally, compared with low-resolution images, the output of all the used approaches showed significant improvements in MOS evaluation. A significant enhancement in the quality of panoramic radiographs can be achieved by SR. The LTE model outperformed the other models. super-resolution neural networks deep learning image enhancement panoramic radiographs This research received no external funding. pmc1. Introduction Panoramic radiography is one of the most common imaging techniques for dental purposes, with both maxillary and mandibular structures, including teeth, being visible . One of the main issues that can significantly influence dental diagnosis and treatment planning is the resolution of panoramic radiographs, which varies among manufacturers and machine types and the regions of each image . Since panoramic radiography combines scanning and tomography, the objects in the curved focal trough or image layer are typically visualized with the highest resolution. Image resolution gradually decreases as objects move further from the center (inward or outward) of the image layer. In general, the resolution of panoramic radiographs varies from 2.58 to 3.19 lp/mm horizontally and <1.88 to 3.19 lp/mm vertically in different panoramic machines and image areas . Notably, clinically relevant objects are not always located in the ideal image layer due to patient positioning errors, anatomical constraints, and geometric properties. Hence, inadequate resolution remains a shortcoming in panoramic radiographs compared to intraoral projections, where resolutions >20 lp/mm can be achieved . Most of the available commercial softwares for viewing and processing radiographic images are equipped with built-in zoom tools as an alternative for increasing the resolution. Zoom features generally work using interpolation techniques. Several studies have shown the applicability of zooming for diagnostic tasks, such as caries detection, linear measurements, and fracture detection . However, an upper limit exists for magnification performance, above which the boundaries of anatomical structures and lesions are not detected correctly. Therefore, zooming only limitedly addresses the resolution limitations of panoramic radiographs. Super-resolution (SR) is a classic problem in computer vision in which an image with a high resolution (HR) is recovered from an image with a low resolution (LR). Due to the growing popularity of deep learning, the number of SR approaches based on deep learning has increased significantly . SR methods based on deep learning can enhance the radiographic resolution without the limitations of conventional zooming features while diagnostically acceptable LR images (with reduced complexity of image acquisition and lower radiation doses) . In dentistry, a recent study successfully employed deep learning-based methods to achieve SR of periapical radiographs . For panoramic radiographs, where SR seems even more warranted, evidence on deep learning for SR is not available. Consequently, we aimed to assess deep learning for the SR of dental panoramic radiographs and to compare it against a conventional approach to improving resolution. 2. Materials and Methods 2.1. Study Design In the present study, five state-of-the-art deep learning-based SR approaches and one conventional SR approach were applied to dental panoramic radiographs to improve image resolution. Note that, in this pilot study, we did not focus on SR to support the detection of specific conditions, but on the generic (disease-agnostic) improvement of image assessability by deep learning-based SR. Reporting follows the Checklists for Artificial Intelligence in Medical Imaging and Artificial Intelligence in Dental Research . For readers unfamiliar with deep learning and the associated terminology, a number of definitions employed in the present methods section are presented in Table 1. 2.2. Dataset and Data Preparation In total, 888 dental panoramic radiographs were collected for this study from a private oral and maxillofacial radiology center in Tehran, Iran. A comprehensive sample from patients who visited the radiology center in June 2021 was used in this study, assuming that the number of images was sufficient to demonstrate the effects of SR in this exploratory study. Low-quality images (e.g., blurry or noisy images) were excluded (n = 31). All the images were taken using Planmeca ProMax (Planmeca, Helsinki, Finland). The device settings were 64-72 kVp, 6.3-12.5 mA, and 13.8-16 s exposure time. The images were exported to .jpg format with a size of 2943 x 1435. All the samples were anonymized before use in the study. To assess whether deep learning and other conventional approaches were suitable for improving resolution, we downscaled all HR images by a factor of 4x to create LR images. Such generic downsampling has been previously employed to simulate LR images and allows high standardization and replicability . The original HR images were considered as ground truth. Seventy percent of the images (n = 622) were selected as the training set. Of the remaining images, 50% were selected as a test set (n = 133), and the other 50% were selected as a validation set (n = 133). 2.3. Model Architectures We applied five deep learning SR approaches, yielding SR images, and compared them against each other and conventional bicubic interpolation. 2.3.1. Super-Resolution Convolutional Neural Networks (SRCNN) Dong et al. first introduced SCRNN in 2014. This network learns end-to-end LR-image-to-HR-image mapping using deep convolutional neural networks. The loss function of this model is mean squared error (MSE). 2.3.2. Super-Resolution Generative Adversarial Network (SRGAN) Ledig et al. applied generative adversarial networks for SR tasks. In their approach, there is an adversarial loss and a content loss. A discriminator network is trained to distinguish between the SR and HR images through adversarial loss, pushing the solution into the HR image manifold. They also proposed a content loss based on perceptual rather than pixel similarity. 2.3.3. U-Net U-Net is a convolutional neural network (CNN) initially developed for medical image segmentation . The main idea was to use a CNN (downsampling path) in conjunction with an upsampling component (upsampling path) to increase the resolution of the output image. The authors also proposed connecting opposing convolutional layers using skip connections. These connections would provide high-resolution features to the upsampling path. In this paper, we fed U-Net with LR images for the SR task without modifying its structure. However, we changed the loss function to MSE. 2.3.4. Swin for Image Restoration (SwinIR) SwinIR is a relatively new SR approach based on Swin transformers . The SwinIR algorithm comprises three steps: shallow feature extraction, deep feature extraction, and high-quality image reconstruction. The deep feature extraction module consists of several residual Swin transformer blocks, each containing several layers of the Swin transformer with a residual connection. 2.3.5. Local Texture Estimator (LTE) LTE is the most recent approach to report favorable results with a shorter running time compared to current state-of-the-art models . LTE is a dominant frequency estimator for natural images, which allows a continuous reconstruction of images with delicate details derived from an implicit function. It can accurately characterize image textures in 2D Fourier space when jointly trained with a deep SR architecture. 2.4. Training Details The training was conducted on a Tesla K80 graphic processor unit (Nvidia Corporation, Santa Clara, CA, USA) using the Google Collaboratory platform. The Python programming language and PyTorch library were used for the model implementation. After the initial assessments of each model, the number of epochs was set from 30 to 120 on the basis of the model's performance on the validation set. To prevent overfitting, we used early stopping, where we saved the best model weights according to their performance on the validation dataset based on the structural similarity index (SSIM). Except for U-Net, all hyperparameters of the implemented approaches were set in their original implementation. Grid search was used for the hyperparameter tuning of U-Net for batch size, learning rate, and the optimizer . 2.5. Evaluation Our models were run five times using different random seeds to reduce the possibility of randomness in the results. The mean and standard deviation of each metric are reported as a result . For this study, four metrics were used to assess the performance of each SR approach, defined as follows : 2.5.1. Mean Squared Error (MSE) MSE is defined as the mean of the squares of differences between the pixel values of HR and SR images. In other words, MSE calculates the difference between each pixel of the HR image and its corresponding pixel in the SR image. It is defined as follows:(1) MSE=1MNi=1Mj=1N(f-f')2, where f is the given HR image and f' is the reconstructed SR image of size M x N. 2.5.2. Peak Signal-to-Noise Ratio (PSNR) PSNR is calculated by dividing the highest value of an image by the power of distorting noise, here MSE, which determines the quality of the image representation. It is defined as follows:(2) PSNR=10log10(255)2MSE, 2.5.3. Structural Similarity Index (SSIM) SSIM is concerned with the perception of quality by the human visual system. Here, three factors are considered: loss of correlation, luminance distortion, and contrast distortion. Each of them is calculated as follows:(3) SSIM(f,f')=l(f,f').c(f,f').s(f,f'), where f is the given HR image and f' is the reconstructed SR image. Moreover, I, c, and f are loss of correlation coefficient, luminance distortion, and contrast distortion, respectively, which are calculated on the basis of a comparison of HR and SR images. 2.5.4. Mean Objective Scale (MOS) Unlike the other three metrics, MOS is a subjective evaluation of the model's performance. Here, we asked four experienced dentists to independently score a random subset (15 images per model) of SR images selected from the test set. Dentists rated each image on a scale of 1 (bad quality) to 5 (optimal quality). To reduce bias, the images were presented randomly to the raters. The mean and standard deviation were reported. HR images were provided as control samples and rated similarly. 2.6. Statistical Analysis The Python programming language and SciPy open-source scientific computing library were used for statistical analysis. Using an unpaired two-tail t-test, we compared the models' MSE, PSNR, and SSIM values. To compare the models' outcome regarding MSE, PSNR, and SSIM values with the conventional bicubic approach, we used a one-sample t-test. Moreover, we used the Wilcoxon signed-rank test to evaluate differences in the MOS of the models compared to the conventional bicubic approach. Any p-values less than 0.05 were considered statistically significant. We also calculated the Pearson correlation coefficient (R-value) of the MSE, PSNR, and SSIM means against the MOS to assess which objective metric most closely reflects the subjective assessment of the clinicians. For interpretation, R-values of 0-0.10 are considered negligible, of 0.1-0.39 are considered weak, of 0.40-0.69 are considered moderate, of 0.70-0.89 are considered strong, and of 0.9-1 are considered very strong . 3. Results The sample output of the trained models is presented in Figure 1. Table 2 provides an overview of the performance of different models on the test set. Moreover, Table 3 presents the results of the statistical analysis of the models' comparison. Regarding the MSE metric, SRCNN and LTE showed better performances with MSEs of 7.48 +- 0.30 and 7.42 +- 0.44, respectively (p < 0.001). Similarly, these two models outperformed others when assessing the PSNR (39.57 +- 0.16 and 39.74 +- 0.17, respectively) (p < 0.001). For SSIM, all models were found to have similar performance (0.916-0.919) except for SRGAN, which showed a poorer outcome with SSIM of 0.901 +- 0.005 (p < 0.001). All deep learning models outperformed the bicubic baseline when assessing MSE, PSNR, and SSIM (with all p < 0.001, except for SRGAN in PSNR, which was 0.046). The results of the MOS evaluation are presented in Table 4. MOS was significantly higher for all SR compared with conventionally restored images. In bicubic images , it was impossible to see the root canals of the second molar, while, in HR and most SR approaches (except U-Net and, to some degree, SwinIR), these were visible. The R-values for MSE, PSNR, and SSIM against MOS were -0.794 (strong negative correlation), 0.773 (strong positive correlation), and 0.763 (strong positive correlation), respectively, i.e., all three metrics closely reflected the subjective assessments of the clinicians. 4. Discussion In the present study, on a dataset of 888 dental panoramic radiographs, SRCNN, U-Net, and LTE performed better than other SR approaches when assessing MSE and PSNR. When considering SSIM as the metric, the difference between models was less clear. Subjective evaluation using MOS found that only SRGAN and LTE yielded significant resolution improvements. Recently, SR approaches based on deep learning have been proposed to overcome the disadvantages of conventional interpolation-based methods for increasing image resolution. In the present study, we evaluated five deep learning-based SR approaches, some of which have been used before for medial image super-resolution . Dong et al., proposed the SRCNN algorithm based on deep convolutional neural networks and reported its successful application in digital photographs . Umehara et al., in a series of studies, successfully used SRCNN to increase the resolution of chest radiographs . As discussed, Moran et al., employed SRCNN to enhance the quality of periapical radiographs . Notably, for this purpose, they found that, while SRCNN improved the visual quality of radiographic images, its application was ineffective in enhancing the detection of periodontal bone loss in periapical radiographs. We confirmed this finding for SRCNN, which increased objective metrics, while clinicians did not find the resulting SR images to yield significantly better quality than LR. SRGAN is another SR model developed by Ledig et al. They reported that SRGAN could recover photo-realistic textures from down-sampled images, leading to significant gains in MOS values of image quality . This is in line with our findings, where SRGAN improved MOS (something which has previously been found for periapical radiographs ), while objective metrics were not necessarily improved. Other state-of-the-art SR models were evaluated. For instance, SwinIR, which uses Swin transformers as the backbone, has shown promising results for different SR tasks , especially for grayscale images (e.g., radiographs). Puttaguntaa et al. reported that SwinIr outperformed SRGAN, BSRGAN, and RealESRGAN on chest radiographs. On the other hand, for reconstruction, U-Net is capable of leveraging hierarchical features from multiple convolutional layers and has been applied in the SR and denoising of computed tomographic images and magnetic resonance images . Lastly, LTE is a dominant-frequency estimator for images capable of characterizing textures in 2D Fourier space. Lee et al., showed that LTE achieved a more favorable performance than other deep learning-based SR models . This approach is relatively new and has not been applied to medical imaging before. It emphasizes learning high-frequency details, such as the edges, in order to improve clinicians' diagnostic confidence in detecting lesions and structures. No previous study has compared the performance of these recent models for SR of panoramic radiographs. In the present study, while all of the selected models showed promising outcomes, LTE showed the highest MSE, PSNR, SSIM, and MOS, respectively. However, our findings show that LTE is more computationally expensive, which is a drawback. In this study, we evaluated the correlation between clinician perception of image quality through MOS and objective measurements (MSE, PSNR, and SSIM). While all of them showed strong correlations, these were not all in the same direction. It has previously been reported that MOS and other metrics may not necessarily agree , by large as the objective metrics reflect different image properties. This is why a more comprehensive set of objective metrics has been suggested . Moreover, a variety of factors, including emotion, professional background, and personal experience have been shown to affect the results of subjective evaluations , which is why we employed different examiners to mitigate this variance to some degree. Overall, the main messages of the different employed metrics remain similar across metrics in the present study, strengthening the case to employ both subjective and objective measures . Moreover, the most inconsistency was observed in SRGAN output. Such discrepancies have previously been shown for SRGAN. It is generally determined that SR models trained with adversarial loss and content loss achieve lower PSNR than those trained with pixel loss, while significantly improving perceived quality . The application of SR models for enhancing image quality has several advantages. SR allows zooming into radiographs with appropriate quality. Radiographic images with higher quality can facilitate diagnosis and better treatment planning in different clinical settings. Additionally, employing SR may decrease the radiation dose by eliminating the need for radiographic retakes and additional imaging due to poor resolution. Moreover, radiographic quality is often positively correlated with radiation dose . Lastly, the combined or specific application of different SR approaches may allow targeted SR for particular tasks (e.g., caries detection, measurement of periodontal bone loss, and detection of periapical lesions), partially because many of these tasks also require assessment of different anatomic regions. Software manufacturers may want to explore the option of condition-specific SR. The findings of this study showed that objective assessments by evaluation metrics and subjective analysis by expert opinion do not necessarily agree. This can be attributed to the small sample size or interference of image characteristics other than resolution in the viewers' scoring. One of the main limitations of this study was the limited number of training images. Larger datasets may improve model performance and generalizability. For further research, the effects of SR models on the quality of cone beam computed tomography (CBCT) images should be explored. Since radiation dose is a major concern in three-dimensional images in dentistry, applying SR models to enhance the quality of low-dose and low-resolution CBCT scans is promising. 5. Conclusions It is possible to improve the visual quality of images by applying SR methods via deep learning models. However, for enhancing the quality of panoramic radiographs, the LTE and SRCNN models were the models that showed the most desirable improvement in both subjective and objective measures of quality. Nevertheless, future research should evaluate whether these improvements lead to better diagnostic capabilities as a result of these models. Furthermore, future studies should take into account the possibility that different SR approaches may be appropriate for different conditions. Author Contributions H.M.-R., conceptualization, design, interpretation, deep learning model development, and drafting the manuscript; S.V., conceptualization, quantitative analysis, and critical revision of the manuscript; E.M., data acquisition and interpretation, quantitative analysis, and deep learning model development; P.S., conceptualization, data acquisition, and drafting the manuscript; S.J.B., conceptualization, quantitative analysis, and critical revision of the manuscript; J.K., conceptualization and critical revision of the manuscript; F.S., conceptualization, design, critical revision of the manuscript, and general supervision of the project. 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 because we only used raw anonymized images. Under local regulations, no formal ethics approval is needed in this case. 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 Super-resolution with different approaches. diagnostics-13-00996-t001_Table 1 Table 1 The definition of technical terms. Term Definition Batch size The number of image samples in each batch of the dataset used for training model Early stopping Assessing the performance of the model during training and stopping training at some criterion to reduce overfitting Epoch One training cycle Hyperparameter Non-learnable parameters that affect the training Hyperparameter tuning A strategy to find optimal hyperparameters Learning rate A hyperparameter that is used to adjust learning speed Optimizer A hyperparameter that is used to adjust learnable parameters Overfitting A model overfits when it begins to memorize training data instead of developing generalizable patterns diagnostics-13-00996-t002_Table 2 Table 2 Objective outcomes of super-resolution using different approaches on the test set. We provide the mean values for MSE, PSNR, and SSIM. Approach MSE PSNR SSIM Bicubic 25.74 34.02 0.890 SRCNN 7.48 +- 0.30 39.57 +- 0.16 0.917 +- 0.004 SRGAN 22.31 +- 0.37 34.43 +- 0.32 0.901 +- 0.005 U-Net 8.55 +- 0.23 38.76 +- 0.28 0.917 +- 0.003 SwinIR 17.31 +- 0.21 36.53 +- 0.35 0.916 +- 0.001 LTE 7.42 +- 0.44 39.74 +- 0.17 0.919 +- 0.003 MSE, mean squared error; PSNR, peak signal-to-noise ratio; SSIM, structural similarity index. diagnostics-13-00996-t003_Table 3 Table 3 p-Values for the comparison of outcomes using different approaches. Approach MSE PSNR SSIM SRCNN SRGAN U-Net SwinIR LTE SRCNN SRGAN U-Net SwinIR LTE SRCNN SRGAN U-Net SwinIR LTE Bicubic <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.046 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 SRCNN - <0.001 <0.001 <0.001 0.801 - <0.001 <0.001 <0.001 0.206 - <0.001 1 0.588 0.742 SRGAN - - <0.001 <0.001 <0.001 - - <0.001 <0.001 <0.001 - - <0.001 <0.001 <0.001 U-Net - - - <0.001 <0.001 - - - <0.001 <0.001 - - - 0.959 0.584 SwinIR - - - - <0.001 - - - - <0.001 - - - - 0.068 MSE, mean squared error; PSNR, peak signal-to-noise ratio; SSIM, structural similarity index. diagnostics-13-00996-t004_Table 4 Table 4 The subjective outcome of super-resolution approaches, measured via MOS. The p-value indicates differences compared with LR images. Approach Rater 1 Rater 2 Rater 3 Rater 4 Total MOS (Mean +- sd) p Value SRCNN 2.87 3.81 3.27 3.84 3.45 +- 0.75 <0.001 SRGAN 3.03 3.39 3.19 3.45 3.27 +- 0.65 <0.001 U-Net 2.93 3.39 2.97 3.56 3.21 +- 0.86 0.002 SwinIR 2.94 3.23 2.81 3.31 3.07 +- 0.77 0.017 LTE 3.43 3.73 3.43 3.77 3.59 +- 0.54 <0.001 HR image 3.78 4.13 3.77 4.20 3.97 +- 0.53 <0.001 Bicubic 2.1 2.91 2.67 3.03 2.68 +- 0.77 - MOS, mean opinion score; HR, high resolution; LR, low resolution. 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. Tsiklakis K. Mitsea A. Tsichlaki A. Pandis N. 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PMC10000386 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050800 cells-12-00800 Article Study of the Bcl-2 Interactome by BiFC Reveals Differences in the Activation Mechanism of Bax and Bak Gonzalo Oscar Benedi Andrea Methodology Formal analysis Investigation Writing - review & editing Vela Laura Conceptualization Methodology Formal analysis Investigation Writing - review & editing Anel Alberto Writing - review & editing Supervision Project administration Funding acquisition Naval Javier Writing - review & editing Supervision Marzo Isabel Formal analysis Writing - original draft Supervision Project administration Funding acquisition * Michaelidis Theologos Academic Editor Department Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain * Correspondence: [email protected] 03 3 2023 3 2023 12 5 80002 12 2022 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 ). Evasion of apoptosis is one of the hallmarks of cancer cells. Proteins of the Bcl-2 family are key regulators of the intrinsic pathway of apoptosis, and alterations in some of these proteins are frequently found in cancer cells. Permeabilization of the outer mitochondrial membrane, regulated by antiapoptotic members of the Bcl-2 family of proteins, is essential for the release of apoptogenic factors leading to caspase activation, cell dismantlement, and death. Mitochondrial permeabilization depends on the formation of oligomers of the effector proteins Bax and Bak after an activation event mediated by BH3-only proteins and regulated by antiapoptotic members of the Bcl-2 family. In the present work, we have studied interactions between different members of the Bcl-2 family in living cells via the BiFC technique. Despite the limitations of this technique, present data suggest that native proteins of the Bcl-2 family acting inside living cells establish a complex network of interactions, which would fit nicely into "mixed" models recently proposed by others. Furthermore, our results point to differences in the regulation of Bax and Bak activation by proteins of the antiapoptotic and BH3-only subfamilies. We have also applied the BiFC technique to explore the different molecular models proposed for Bax and Bak oligomerization. Bax and Bak's mutants lacking the BH3 domain were still able to associate and give BiFC signals, suggesting the existence of alternative surfaces of interaction between two Bax or Bak molecules. These results agree with the widely accepted symmetric model for the dimerization of these proteins and also suggest that other regions, different from the a6 helix, could be involved in the oligomerization of BH3-in groove dimers. Bcl-2 family protein-protein interactions apoptosis BH3-mimetics Bimolecular Fluorescence Complementation MCIN/AEI/10.13039/501100011033 and "ERDF A way of making Europe"SAF2016-76338-R Gobierno de AragonB31_17R This research was funded by grants SAF2016-76338-R (MCIN/AEI/10.13039/501100011033 and "ERDF A way of making Europe") and B31_17R (Gobierno de Aragon). pmc1. Introduction The key event in the intrinsic pathway of apoptosis is mitochondrial outer membrane permeabilization and the release of apoptogenic proteins. The effectors of this critical process are Bax and Bak, two proapoptotic proteins belonging to the Bcl-2 family. Thus, the presence of at least one of these two proteins is required for cell death through the intrinsic pathway initiated by many apoptotic stimuli . The Bcl-2 family also comprises a group of antiapoptotic proteins that keep proapoptotic members in check to avoid accidental activation of Bax and Bak. Finally, the family includes a subset of proapoptotic proteins, containing only the BH3 homology domain (the BH3-only group), which act as cell damage sensors and trigger Bax and Bak activation. The way BH3-only proteins activate multidomain proapoptotic proteins has been a matter of controversy in the field. The recent approval by the FDA of Venetoclax, a BH3-mimetic Bcl-2 inhibitor, for the treatment of Chronic Lymphocytic Leukemia has fueled interest in understanding the mechanisms that regulate the interactions between these proteins. Initially, two opposed models were proposed, the "displacement" (or "indirect") and the "direct" model . One of the discrepancies between both models was how BH3-only proteins triggered Bax and Bak oligomerization. The "displacement or indirect" model postulated that active Bax and Bak are blocked by antiapoptotic members of the Bcl-2 family until they are bound and neutralized by BH3-only proteins in response to proapoptotic signals . By contrast, in the "direct model", BH3-only proteins were proposed to bind and activate Bax and Bak. Initially, only tBid and Bim were included in this group of "activators", but later, also Puma and Noxa were also suggested to belong to this category. In this model, antiapoptotic proteins inhibit mitochondrial permeabilization by blocking activator BH3-only proteins. A second group of BH3-only proteins, the "sensitizers", free the activators by releasing them from the restraint of antiapoptotic proteins. Free BH3-only activators can then bind to and activate Bax and Bak through a conformational change that leads to oligomerization and pore formation. Some genetic studies in mice and immunoprecipitation data seemed to exclude a direct interaction between BH3-only and multidomain proapoptotic proteins , while other reports suggested that these interactions could be necessary for the proapoptotic function of some BH3-only proteins . The controversy was also fed by the fact that direct activation of Bax and Bak by BH3-only proteins remained difficult to detect in living cells. Immunoprecipitation analysis of the interactions between Bcl-2 family members has habitually failed to detect an association of BH3-only proteins with Bax or Bak. By contrast, in vitro studies with purified proteins and peptides have provided evidence that some BH3-only proteins can bind to Bax and Bak . It is important to note that experimental conditions in some of these studies may not truly reproduce the interactions that could occur between full-length proteins in a cellular context. Recently, we were able to visualize the interactions of Bim, Puma, or Noxa with Bax and Bak in living cells via the BiFC (Bimolecular Fluorescence Complementation) technique . Additionally, the results of this previous work outlined the complexity of the Bcl-2 family interactome, supporting more recent models, such as the "embedded together" and the "unified" models, that include features of both the direct and indirect models . An important, unsolved question concerning BH3-only activators is how these proteins would bind to Bax and Bak. Transient binding of activator BH3-only proteins to the hydrophobic groove of Bax and Bak has been proposed to provoke the activation of Bax and Bak by causing the exposure of their BH3 domain followed by dimerization. Alternatively, other authors have reported that activator BH3-only proteins interact with Bax in a "rear pocket" formed by a1 and a6 helices triggering the release of the C-terminal helix . These apparent discrepancies could reflect variations in the mechanism of activation of Bak and Bax. Although both proteins function as effectors of mitochondrial outer membrane permeabilization, differences in structure and localization could indicate that they are not completely equivalent. In healthy cells, Bax is usually a cytosolic protein that translocates to mitochondria in the early steps of apoptosis. In contrast, Bak is constitutively located at mitochondria, where its a9 helix acts as an anchor to the outer membrane. This helix could be occluded in a hydrophobic pocket in an inactive cytosolic Bax . Many models for mitochondrial permeabilization postulate that activated Bax and Bak oligomerize to form pores in the outer mitochondrial membrane. The disposition of monomers in these pores is also a matter of controversy . According to the asymmetric model, the BH3 domain of an activated molecule inserts itself into the rear pocket of another one, triggering exposure of the BH3 domain of the second monomer and expansion of the oligomer. Alternatively, a symmetric model proposes that dimers are formed by the insertion of the BH3 domain of one molecule into the hydrophobic pocket, "BH3-in-groove", of other molecules and dimers associate in high-order oligomers by interacting through the "rear" surface. Identification of this second interface, involved in the oligomerization of BH3-in-groove dimers, remains an open question in the field, and different regions of Bax and Bak have been proposed to participate in this process. Contact between the a6 helices of two dimers has been demonstrated by the use of cysteine mutants and a disulfide bridging . However, the a3/a5 surface and the a9 helix have been proposed to mediate the association of symmetric dimers in high-order oligomers. More recently, a new model of disordered dimer clusters has been described to explain Bak oligomerization . Despite some limitations, Bimolecular Fluorescence Complementation (BiFC) is a useful tool for the detection of protein interactions in a cellular context, especially for transient and weak interactions, which are difficult to detect via other methods . Using this technique, we have been able to detect interactions between some members of the Bcl-2 family, including interactions of BH3-only proteins with Bax and Bak . We have now extended our studies to interactions with Bcl-2 antiapoptotic proteins and to the study of Bax and Bak dimerization. Our present results seem to confirm that the BH3-only proteins, Bim, Puma, and Noxa, can bind to Bax and Bak, although with different affinities. According to our present results, Bim is a better activator of Bax than Puma or Noxa. However, Noxa displayed the strongest association with Bak. Furthermore, our results indicate that both the BH3-only and multidomain proapoptotic subset can be blocked by antiapoptotic proteins, pointing to a mixed or "unified" model for the activation of Bax and Bak, proposed by some authors. Finally, using different mutant forms of Bax and Bak, we have explored the roles of BH3, H6a, and H1a regions in the interactions with other proteins of the family and in the dimerization processes. Our results would suggest that several interfaces are involved in the oligomerization of both Bak and Bax proteins. 2. Materials and Methods 2.1. Construction of pBiFC and pBabe Vectors The coding sequences for human Bcl-2, Bcl-XL, Mcl-1, Bim, Puma, Noxa, Bax, Bak, and TOM20 were subcloned by standard PCR strategies into pBiFC plasmids modified to contain the sequences coding for VN (amino acids 1-173) or VC (amino acids 155-238) fragments of Venus protein and the appropriate linker sequence fused to each protein at the N-terminus. VN fusions contain the sequence of HA tag and VC fusions that of Flag tag . For multicolor BiFC experiments, the cDNA of selected proteins of the Bcl-2 family was subcloned into pBiFC vectors containing the carboxy-fragment of cerulean protein (CN and CC, respectively). Deletions of either the BH3 domain or the a1 helix of Bax and Bak were generated by PCR overlap, as previously described . Standard site-directed mutagenesis was performed to generate BaxK21E/D33A/W139A/D146A/R147A and BakH164A mutants. Enzymes used for mutagenesis included AccuPrime Pfx SuperMix (Invitrogen) and DpnI (Fisher BioReagents) digestion. Human Bax and Bak cDNAs (and the corresponding mutated forms) were also subcloned into pBabe plasmid within the appropriated restriction sites (EcoRI/SalI for pBabe-Bax and EcoRI/BamHI for pBabe-Bak). Sequences of constructs are provided in the Supplementary materials. 2.2. Cell Lines Human HeLa cervix adenocarcinoma and HCT116 Bax-/- colon carcinoma (gently provided by Dr. Julian Pardo, IIS-Aragon) and MiaPaca2 pancreatic carcinoma cells were routinely cultured at 37 degC in DMEM medium supplemented with 10% FBS, L-glutamine, and penicillin/streptomycin. 2.3. BiFC Assays Cells were seeded in 48-, 24-, or 12-well plates and grown to at least 50% confluence before being transfected with the appropriate amount of each vector using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). A ratio of 1 mg DNA:3 mL Lipofectamine was used for all the experiments. Efficiency was assessed by co-transfection with a pmRFP-TMD (a gift from Dr. Jose Alberto Carrodeguas, University of Zaragoza) or pAL2-Myc-mRFP vector. Transfections were carried out in the presence of 30 mM Z-VAD-fmk (Bachem) to maintain cell integrity. Transfected cells were cultured at 37 degC for 24 h, and then, Venus (BiFC) and mRFP signals in cells were quantified in a FACSCalibur flow cytometer. A gating analysis based on mRFP fluorescence was performed to exclude non-transfected cells. The mean fluorescence intensities of the BiFC complexes were normalized to the mean fluorescence intensity of mRFP . At least 10,000 cells were analyzed in each experiment. In some experiments, ABT-199 (Selleckchem, Houston, TX, USA), A-1155463 (MedChemExpress, Sollentuna, Sweden), or S63845 (Selleckchem) were added 1 h after transfection. For multicolor experiments, cells were simultaneously transfected with three pBiFC vectors coding for CN-, VN-, and CC-fusions and a vector expressing mRFP. Appropriate controls were performed by transfecting cells with two vectors expressing CC-fusions or CC-fusions together with the vector containing mRFP cDNA. Cerulean and Venus fluorescences in mRFP-positive cells were determined 24 h after transfection in a FACSAria cytometer equipped with 405 nm, 488 nm, and 635 nm lasers. 2.4. Cell Death Analysis Cell death was analyzed by determining phosphatidylserine (PS) exposure. Cells were incubated for 15 min at room temperature in 100 mL of annexin-binding buffer (2.5 mM NaCl, 140 mM CaCl2, 10 mM Hepes/NaOH, pH 7.4) containing 2 mL of annexin V-DY634, prepared as previously described . Cells were diluted to 1 mL with annexin-binding buffer prior to flow cytometry analysis. 2.5. CRISPR/Cas9 A MiaPaca2 Bak KO cell line was generated through CRISPR-Cas9 editing. DNA oligos for the sgRNA targeting site (up: CACCGGTCCTCCCAGGCAGGAGTG; down: AAACCACTCCTGGCCTGGGGAGGACC) were annealed and ligated into BbsI digested pSpCas9(BB)-2A-Puro (PX459) V2.0 plasmid (Addgene). Cells were transfected with Lipofectamine 2000 (Invitrogen) and selected with puromycin. Knock-down of Bak protein was verified by Western Blot. 2.6. Western Blot Analysis To determine the expression level of the fusion proteins, SDS-PAGE and Western Blot analysis of cytoplasmic cell lysates was performed. Cell extracts were prepared in lysis buffer (50 mM Tris/HCl pH 7.6, 150 mM NaCl, 10% (v/v) glycerol, 1 mM Na3VO4, 10 mM Na4P2O7, 10 mM NaF, 1 mM EDTA, 10 mg/mL leupeptin, 1 mM PMSF, and 1% (v/v) Triton X-100) and protein content was determined by BCA assay (Thermo Scientific, Carlsbad, CA, USA). After SDS-PAGE electrophoresis, proteins were transferred to nitrocellulose membranes. Proteins were immunodetected by using appropriate primary antibodies and peroxidase-labeled secondary antibodies (Sigma-Aldrich, St Louis, MO, USA). Bands were visualized with Pierce ECL or ECL Plus Western Blotting Substrate (Thermo Scientific). Specific antibodies against the following proteins were used as follows: Bcl-XL (Cell Signaling Technology, Danvers, MA, USA); Bcl-2 (Abcam, Cambridge, UK); Mcl-1 (Santa Cruz Biotechnology, Dallas, TX, USA); Bim (Merck Millipore, Darmstadt, Germany); Puma (Abcam); Noxa (Santa Cruz Biotechnology); Bax (BD Biosciences); and Bak (Santa Cruz Biotechnology and Millipore, Darmstadt, Germany). The protein-loading control was achieved by membrane reprobing with an anti-b-actin or anti-a-tubulin antibody (Sigma-Aldrich). 2.7. Fluorescence Microscopy Mitochondrial localization of complexes formed by VC-fusions was analyzed by confocal microscopy. HeLa cells were seeded in coverslips and co-transfected, as previously indicated, with pBiFC vectors expressing fusions of the indicated proteins with VN and VC fragments and pmRFP-TMD, a vector expressing a mitochondrial-targeted mRFP. Following 24 h after transfection, nuclei were stained with Hoechst 33342 (2 mg/mL), cells fixed with 4% paraformaldehyde (PFA) for 15 min at 4 degC and mounted on Fluoromount-G. Images were collected in a sequential mode in a FluoView FV10i (Olympus) confocal microscope with a 60x oil immersion lens, a line average of 4, and a format of 1024 x 1024 pixels. The confocal pinhole was 1 Airy unit. Images were exported without image manipulation from FV10-ASW viewer software (V2.0, Olympus NDT Inc., Waltham, MA, USA) to generate the figures. For fluorescence microscopy, cells were grown on coverslips and transfected as previously described. Transfected cells were stained with 100 nM MitoTracker Red (CMXRos, Invitrogen) 24 h after transfection, washed with PBS, and fixed in 4% PFA at room temperature for 20 min. Finally, coverslips containing fixed cells were washed and mounted in Fluoromount-G (Southern Biotechnology, Birmingham, AL, USA). Images were collected using an Olympus IX81 fluorescence microscope. Images were exported without image manipulation to generate the figures. 2.8. Statistical Analysis All statistical analyses were performed via GraphPad Prism (version 9, GraphPad Software, LLC, San Diego, CA, USA). 3. Results 3.1. The Interactome of the Bcl-2 Family in Living Cells Control of cell fate upon cell damage depends on the interaction network among proteins of the Bcl-2 family. The balance between antiapoptotic members and the interactions that these proteins establish determine whether mitochondrial outer membrane permeabilization, the point of no return in the intrinsic pathway, will occur. Bimolecular Fluorescence Complementation can be advantageous compared to other techniques, such as immunoprecipitation, for revealing labile or transient interactions that could be essential in the mode of action of Bcl-2 proteins . Although the fusion of Venus halves to the C-terminus of some proteins of the Bcl-2 family does not preclude correct mitochondrial localization , we have generated N-terminal fusions for all the proteins and verified the correct expressions of all the constructs . Furthermore, the topology of the protein fusions must be optimized for BiFC assays to avoid false negative results that could be caused by interference of the Venus fragments with the interaction surface or by steric hindrance preventing the fluorescent fragment from approaching the right orientation. Thus, to exclude any interference of the Venus fragments in the interaction between proteins or spatial limitations in the complementation of Venus fragments, we generated fusions of both VN and VC fragments of Venus at the N-terminus of all the proteins analyzed, and appropriate pairs were co-transfected in HeLa cells. Equivalent expression of the fusions was confirmed through Western Blot , excluding the possibility of reduced Venus fluorescence, which was due to low expression of the fusions. For each protein pair, the most favorable configuration of BiFC fusions was used in further experiments. Punctate distribution of BiFC complexes and colocalization with a mitochondria-targeted mRFP confirmed mitochondrial localization . For weak interactions, the intensity of detected fluorescence has been proposed to be proportional to the strength of the interaction . On this premise, we analyzed the interactions between various pairs of Bcl-2 proteins in order to delineate a "Bcl-2 interactome" in living cells. HeLa cells were transfected with VN/VC-fusion pairs, and the fluorescence intensity was quantified by means of flow cytometry . Cells were co-transfected with a vector containing the cDNA of mRFP to allow for the gating of transfected cells (which ranged from 30% to 50% in every experiment), and Venus/mRFP fluorescence was calculated . We first compared the interactions of the multidomain proteins Bak and Bax with antiapoptotic proteins or BH3-only proteins . Mitochondrial Tom20 protein was used as a negative control, as previously reported . Our results showed that both Bax and Bak interacted with Bcl-2, Bcl-XL, and Mcl-1, although the Mcl-1/Bax interaction seemed to be weaker, according to a lower Venus intensity detected for the Mcl-1/Bax pair . To exclude that the differences observed in Venus complementation could be due to differential expression of the constructs, we performed WB analysis using anti-Flag and anti-HA antibodies, which allowed the detection of different constructs in the same membrane . On the other hand, we observed differences in the ability of Bax and Bak to bind BH3-only proteins. Venus complementation intensities suggested that Bak binds more easily to BH3-only proteins than Bax . Among BH3-only proteins analyzed, Bim and Puma seemed to be the most probable activators of Bax. In contrast, Bak/Noxa complexes gave the highest fluorescence intensity for Bak. Fluorescence microscopy showed that complexes between Bax, Bak, and BH3-only proteins displayed a punctate pattern , according to the mitochondrial localization detected by confocal microscopy . Moreover, Venus-positive cells displayed reduced MitoTracker Red staining, suggesting loss of mitochondrial transmembrane potential. Interactions of Bim, Puma, and Noxa with antiapoptotic proteins were also evaluated. As shown in Figure 2e, Bim associates with Bcl-2 and, to a lesser extent, with Bcl-XL and Mcl-1. The intensity of Venus fluorescence for the Bim/Bcl-2 pair was similar to that of the Bim/Bak pair. Puma is strongly associated with the three antiapoptotic proteins , yielding greater intensities than the Puma/Bax and Puma/Bak complexes . Finally, we observed that Noxa could bind to Bcl-2 and Mcl-1, but it showed a very low affinity for Bcl-XL. We also analyzed the effect of specific BH3-mimetic compounds in the interaction of antiapoptotic proteins with Bim, Puma and Noxa. As shown in Figure 2f, ABT-199 significantly reduced the formation of BiFC complexes of Bcl-2 with Bim, Puma, or Noxa, especially Bim and Noxa. In the same way, A-1155463 and S63845 reduced the interaction of Bim, Puma, and Noxa with Bcl-XL or Mcl-1, respectively. To gain further insight into the complex interactions network that regulates the activity of Bcl-2 proteins, we performed multicolor bimolecular fluorescence complementation assays . This technique is based on the fusion of fragments of spectrally distinct fluorescent proteins, allowing us to analyze the competition between interaction partners . Similar levels of expression of the fusions with Venus and Cerulean fragments were verified by Western Blot . We analyzed the relative affinity of Bim, Puma, and Noxa to the antiapoptotic Bcl-XL and Mcl-1 proteins versus the multidomain proapoptotic members of the family . Dot-plot diagrams recording Venus and Cerulean intensities were converted into density graphics, and linear adjustment was performed . Cerulean and Venus fluorescence signals were analyzed in mRFP-positive cells by flow cytometry. FL-9 (cerulean)/FL-1 (Venus) histograms were divided into 15 sections in the FL-1 dimension. Mean Venus and Cerulean fluorescences in each section were recorded, represented as an XY graphic, and adjusted to a linear function using GraphPad Prism software. Cells that were positive for mRFP only were excluded from the analysis. Each point represents the Venus (X-axis) and Cerulean fluorescence (Y-axis) in these regions. The number of events in each section was represented by the diameter of the circles. These competition assays suggested that Bax/Bim interaction was favored versus Mcl-1/Bim or Bcl-XL/Bim. Furthermore, Bcl-XL was relatively inefficient in avoiding the Bim/Bak association, while Mcl-1 was able to displace an important fraction of Bim, preventing its binding to Bak, as indicated by the slopes of cell populations in dot-plot diagrams corresponding to triple transfection with CC-, CN-, and VN-fusions . In contrast, Puma seemed to associate preferentially with antiapoptotic proteins when competing with Bak . The Puma/Bax association was also partially reduced by both antiapoptotic proteins. Finally, Venus/Cerulean fluorescence representation indicated that Mcl-1 could compete with Bax and Bak for Noxa . However, Venus fluorescence was predominant in the Bcl-XL/Noxa/Bax and Bcl-XL/Noxa/Bak combinations, according to the low binding of Bcl-XL to Noxa observed in single-color BiFC assays compared to Mcl-1/Noxa and Bcl-2/Noxa. Although Bcl-XL/Noxa and Bax/Noxa complexes displayed similar fluorescence ratios in cells transfected only with two fusions , multicolor experiments suggested that Noxa bound preferentially to Bax when both Bcl-XL and Bax fusions were expressed simultaneously. Considering both the single-color BiFC experiments and the multicolor competition assays, an interactome map for the Bcl-2 family can be outlined . 3.2. Involvement of the a1 Helix and the BH3 Domain in the Interaction of Bax and Bak with BH3-Only and Antiapoptotic Proteins The rear region of Bax and Bak has been proposed to be the binding site for activator BH3-only proteins . Thus, we studied the interaction of BH3-only and antiapoptotic proteins with Bax and Bak mutants in the a1 helix and BH3 regions . Expressions of the fusions containing mutant Bax or Bak were verified by Western Blot analysis . As shown in Figure 5b, Bax D33A mutants displayed a decreased affinity for the three BH3-only proteins analyzed, suggesting that negative charges in this region of Bax could be involved in the binding of activator BH3-only proteins. On the contrary, the K21E mutation did not alter the interaction of Bax with Bim, Puma, or Noxa. However, BH3 deletion mutants of Bax even increased their association with Puma and Noxa. These results point to the a1 helix as the binding site for BH3-only proteins, as previously proposed , and confirm the critical involvement of D33 in the activation of Bax. We also explored the involvement of the a1 helix and the BH3 domain in the interaction of Bax with antiapoptotic proteins. As shown in Figure 5c, both the D33A mutation and deletion of the BH3 domain significantly reduced the interaction between Bax and antiapoptotic proteins. These results suggest that both interfaces could be binding sites for antiapoptotic proteins. However, both the K21E and the D33A mutants induced apoptosis at the same level as the wild-type protein , and fluorescence microscopy also suggested that mitochondrial transmembrane potential was dissipated after transfection with Bcl-XL combined with Bax K21E or Bax D33A fusions . In contrast, the DBH3 mutant displayed reduced proapoptotic activity . Furthermore, Venus-positive cells, after transfection with the Bcl-XL/DBH3 pair mutant, seemingly kept high mitochondrial transmembrane potential , indicating that the BH3 domain is essential for mitochondrial permeabilization. Deletion of the a1 helix of Bak did not affect the interaction with Bim and Puma . However, the DH1a mutant of Bak exhibited a reduced ability to bind Noxa. On the other hand, our results show that the BH3 domain of Bak is involved in the binding of Bim, Puma, and Noxa. The affinity between Bak and Bim or Puma was decreased when the BH3 domain of the former was deleted, but complexes were still detected and the Venus/mRFP ratio was only slightly reduced, suggesting this mutation affected the affinity of Bak for these BH3-only proteins, probably due to alterations of the canonical groove which includes the BH3 domain. According to accepted models, we observed that DBH3 Bak mutants almost lost the ability to interact with antiapoptotic proteins. However, DH1a mutants yielded higher Venus intensities when combined with Bcl-2 or Bcl-XL fusions . This finding could be explained by the constitutive activation of the truncated protein, as reported for Bax isoforms lacking the N-terminus . Surprisingly, the DH1a Bak mutant also showed a reduced interaction with Mcl-1. This could indicate that the interaction between Mcl-1 and Bak could occur through different surfaces other than the BH3 domain. In agreement with these observations, DH1a Bak, but not DBH3 Bak, induced apoptosis in Bak KO cells generated by CRISPR-Cas9 . 3.3. Involvement of the BH3 Domain and the a1-a6 Interface in Dimerization of Bax and Bak We next explored the dimerization process using fusions of Venus fragments with wild-type or mutants of both Bax and Bak proteins. In dimerization experiments, the Venus/mRFP ratios were lower than that measured for most of the heterodimers , probably due to the dimerization of fusions with non-complementary Venus fragments . Nevertheless, we observed some significant changes when mutants in the a1 helix, the a6 helix, and the DBH3 variants were used to explore the interfaces involved in the homodimerization of both proteins. Deletion of the BH3 domain from one of the Bax fusions reduced dimerization leading to Venus complementation . In this case, the reduction in Venus complementation could be caused by destabilization of the BH3-in-groove interaction when the BH3 domain of one of the Bax fusions is deleted. Alternatively, this reduction of fluorescence could probably be due to the dimerization of the wild-type proteins fused to the same Venus fragment that can associate in a BH3-in-groove configuration without yielding Venus complementation . Further studies would be required to clarify this point. However, when both fusions were constructed with DBH3 mutants, Venus fluorescence intensity was similar to that of wild-type Bax dimers , indicating that dimerization can occur by the interaction of other domains, such as the rear interface , but would not be compatible with an asymmetric model. In this case, the association of non-fluorescent dimers of fusions with the same Venus fragment would not be favored since both fusions lack the BH3 domain. Importantly, although DBH3 mutants could dimerize, these fusions were unable to induce mitochondrial dysfunction, as suggested by the detection of transmembrane potential with MitoTracker Red . Deletion of the BH3 domain only caused a decrease in dimer formation when both fusions contained truncated Bak . The fact that the WT/DBH3 pair yielded Venus complementation at the same level as WT/WT transfection could indicate that the BH3 domain of the WT fusion can still bind to the partial hydrophobic groove in the DBH3 fusion . On the other hand, when cells were transfected with BakDBH3 fusions, we did not observe a loss of mitochondrial transmembrane potential , confirming that the BakDBH3 fusion has lost proapoptotic functionality. These results suggest that a second interface, apart from the BH3-in-groove, must be involved in Bax and Bak dimerization. Data obtained in studies with recombinant proteins point to the a1:a6 as the second interface involved in Bax and Bak oligomerization . Thus, we analyzed the dimerization of Bax and Bak mutants in the a1 or the a6 helix . The K21E Bax mutant was able to associate with wild-type Bax at the same level that the non-mutated protein, but mutation of D33 to alanine slightly reduced the dimerization with wild-type Bax, both in HeLa and in HCT116 Bax-/- cells . Two different Bax mutants in the a6 helix, W139A, and E146A, significantly reduced dimerization with the wild-type fusion . In the same way, we analyzed the involvement of a1 and a6 helices in the dimerization of Bak. Deletion of the a1 helix or mutation of H164 in the a6 helix did not preclude Bak homodimerization, and we even detected higher levels of fluorescence, suggesting a favored association between wild-type and mutated Bak fusions . In order to gain further insight into the dimerization of Bax and Bak, we also analyzed the interactions between mutants in the helices a1 or a6 with the DBH3 fusions . Deletion of the BH3 domain of Bax reduced the complexes formed with the K21E and D33A mutants in HeLa and HCT116 Bax-/- cells . Taken together, these results suggest that the a1 helix could act as a binding region for Bax-BH3 domains but would not be critically involved in the assembly of dimers through the rear surface. In contrast, combining a6 helix and DBH3 mutants did not suppose a further reduction in the association of fusions , apart from that caused by a6 mutations in one of the fusions . Interestingly, we did not observe the reduction in fluorescence that occurred in the WT/DBH3 pairs . This could indicate that some of the possible non-fluorescent pairs that could assemble in these experiments would not be favored when the a6 helix is mutated. These findings would fit with a model in which the Bax a6 helix takes part in the second interface in oligomerization, but it is not a receptor domain for the BH3 region of a pre-activated Bax molecule. In contrast, deletion of the BH3 domain of Bak reduced dimerization when combined with a1 or a6 mutants . Considering that deletion of the helix a1 had no effect on the self-association of Bak monomers, the decrease observed in Figure 8f could reflect a decrease in the formation of symmetric dimers due to the lack of one BH3 domain. Since some degree of Venus fluorescence was still detected in all cases, it is possible that these mutations only partially affected the interaction between monomers or that Bax and Bak could dimerize through alternative surfaces, as proposed by some authors . 4. Discussion Interactions among proteins of the Bcl-2 family can regulate the susceptibility of cells to apoptotic death. Unraveling the Bcl-2 interactome could contribute to the improvement of therapy in pathologies in which the deregulation of cell death occurs. Based on this hypothesis, small compounds targeting the antiapoptotic members of the family by mimicking the BH3 domains have been developed. The first-in-class BH3-mimetic reaching the clinic has been ABT-199 (Venetoclax), a Bcl-2-specific inhibitor recently approved for B-CLL, SLL, and AML. Additionally, S63845, a specific and potent Mcl-1 inhibitor, has been described , and a related compound is being evaluated in clinical trials in hematological neoplasia . Since cells of different origins can vary in their dependence on antiapoptotic proteins, precise knowledge of the Bcl-2 interactome could help to predict the response of tumor cells to BH3-mimetics or to design new compounds to activate the intrinsic pathway of apoptosis in cancer cells. Data obtained with recombinant proteins or through immunoprecipitation clearly suggest that interactions among Bcl-2 proteins are more promiscuous than initially thought and probably include features of both the "direct" and the "displacement" models. Recent models, such as the "unified model", include the notion that some BH3-only proteins can directly activate the multidomain effector proteins and also propose that antiapoptotic proteins can act in two different modes, either blocking activator BH3-only proteins (Mode 1) or effector proteins (Mode 2) . These new models delineate a complex network of interactions that must be finely tuned to control cell fate in response to apoptotic stimuli. On the other hand, these interactions can also be modulated by the membranes in which these proteins are located or translocated during apoptosis, such as proposed by the "embedded together" model. In order to study interactions among proteins of the Bcl-2 family in a cellular context, we have implemented the BiFC assay to a network of proteins in the Bcl-2 family, including antiapoptotic members (Bcl-2, Bcl-XL, and Mcl-1), BH3-only (Bim, Puma, and Noxa), and the two effector multidomain proteins (Bax and Bak). First, we have compared the interactions between pairs of full-length proapoptotic proteins, which allowed us to delineate an interaction map of them . The interactions of Bax and Bak with Bcl-2, Bcl-XL, Mcl-1, Bim, Puma, and Noxa were studied simultaneously, and cells were co-transfected with an mRFP protein to allow for the normalization of Venus fluorescence intensities. We observed some differences in the ability of Bax and Bak to interact with all the proteins analyzed, suggesting differential affinities among its partners. Our results suggest that Bak can be preferentially activated by direct interaction with BH3-only proteins, but Bax may present a mixed mechanism since it displays a similar affinity for antiapoptotic and BH3-only proteins. Regarding the role of BH3-only proteins as activators, our observations confirm that Bim, but also Puma and Noxa, can bind to Bax and especially to Bak, supporting previous reports . A possible explanation of why these interactions remained elusive in many previous studies could lie in their expected transient nature . This difficulty is circumvented by the BiFC technique since the complementation of the Venus fragments is irreversible, which is an advantage for the detection of transient or weak interactions. Classification of Puma as a BH3-only activator protein has been controversial. Although Puma co-immunoprecipitates with Bax, the fact that a DC mutant, able to bind Bcl-2 but not Bax, still induces apoptosis has been interpreted as evidence that Puma mainly acts as a sensitizer . The study of interactions by BiFC also suggests that Puma can act in both modes but displays a preferential affinity for antiapoptotic proteins. First of all, single-color BiFC experiments showed that Puma associated better with Bcl-2, Bcl-XL, and Mcl-1, as reflected by the high Venus intensities observed. Likewise, using a multicolor BiFC assay, we have verified that Bcl-XL and Mcl-1 could efficiently compete with Bak and Bax to bind Puma, suggesting again that this BH3-only protein can contribute to apoptosis mainly through blocking antiapoptotic members, according to previous results . In contrast, interactions between Bim or Noxa and Bax/Bak prevailed when competing with Mcl-1 and Bcl-XL. These results would also agree with previous works showing that Puma BH3 peptides were less efficient MOMP inducers than Bim, tBid, or even Noxa BH3 peptides . Of note, they observed that Bak induces cytochrome c release only after BH3 triggering, suggesting that it depends on direct activation to induce mitochondrial permeabilization. Interestingly, our present results suggest that full-length Bak in cells is better activated by BH3-only proteins than Bax. On the other hand, the relative binding of BH3-only proteins to antiapoptotic members of the Bcl-2 family can vary among cell types, as recently reported for Bim in myeloma cell lines . This binding preference could determine the sensitivity of cancer cells to BH3-mimetics. Our present results indicate that Bcl-2 has a high affinity for Bim, Puma, and Noxa. In the case of Noxa, this result is inconsistent with the accepted assumption that Noxa is mainly kept in check by Mcl-1. This apparent discrepancy could be explained if the Bcl-2/Noxa interaction were short-lived, as observed by using a Noxa BH3 peptide in vitro . Importantly, the specificity of the interactions detected via the BiFC technique was demonstrated by inhibition with BH3-mimetic compounds. The association of Bim, Puma, and Noxa with each antiapoptotic protein was significantly reduced in the presence of the corresponding BH3-mimetic. BH3-mimetics only partially reduced the interaction between Puma and the three antiapoptotic proteins, suggesting that Puma could bind to antiapoptotic proteins through regions other than the hydrophobic canonical groove targeted by these compounds. Analysis of the interaction between Bax and Bak with the antiapoptotic proteins revealed no significant differences in the interactions of Bcl-2, Bcl-XL, and Mcl-1 with Bak, despite previous reports suggesting that Bcl-2 is unable to interact with this protein . Conversely, Bak and Bcl-2 have been reported to co-immunoprecipitate in protein extracts from lymphoid cells , according to our present results. Another important question in the direct model of Bax and Bak activation concerns the putative binding site for BH3-only proteins. Two different possibilities have been proposed, the a1/a6 rear pocket and the canonical hydrophobic groove formed by helices a2-a5. We have addressed this question using the BiFC assay with mutants affecting both interfaces. Interestingly, we found that the a1 helix seems to be involved in the association of Bim, Puma, and Noxa to Bax, as suggested by the significant decrease in the formation of complexes when cells were transfected with the D33A Bax fusion protein. However, deletion of the BH3 domain of Bax did not hinder its association with Bim and Puma and even increased binding to Noxa, probably due to conformational changes that favored the insertion of the BH3 domain of Noxa in the rear surface of Bax. Altogether, these results point to the rear surface of Bax as the activation site for BH3-only proteins, according to previous reports . Regarding the residues that could be involved in the BH3-Bax rear pocket interaction, the K21E Bax mutant interacted with Bim, Puma, and Noxa and induced mitochondrial depolarization at the same level as the wild-type protein, while mutation of D33 to alanine, partially reduced the interaction of Bax with BH3-only proteins. These results disagree with a previous work in which K21E Bax mutant partially lost the capacity to interact with a Bim SAHB peptide or induce apoptosis in reconstituted Bax/Bak KO cells and would support the involvement of D33, also proposed to be critical for Puma-mediated activation of Bax . Since the effect of the D33A mutation was only partial, we cannot exclude that other residues or other domains could also contribute to Bax activation by binding of full-length Bim. Although Bax and Bak are considered to fulfill an equivalent function in the intrinsic pathway, they present some structural differences that could reflect different mechanisms of activation. Leshchiner et al. have reported that photoreactive BH3 helices bind to the hydrophobic groove of liposome-reconstituted full-length Bak and to the a1/a6 pocket of Bax . This difference could be explained by the fact that the a9 helix of inactive cytosolic Bax is buried in the canonical hydrophobic groove, probably hindering the binding of BH3-only activator proteins. However, Bak is constitutively inserted in the outer mitochondrial membrane through its a9 helix, and the hydrophobic groove is probably more accessible for BH3-only proteins. Furthermore, Dai et al. found that mutation of R36 in the a1 helix of Bak did not affect its interaction with either Bim or Noxa, while they could detect the binding of these proteins to the hydrophobic groove . Our results with full-length Bim and Puma in a cellular context recapitulate these previous findings since deletion of the BH3 domain, which is part of the hydrophobic groove, reduces the affinity of Bim and Puma for Bak, while deletion of the H1a does not affect these interactions. However, deletion of either the H1a or the BH3 domain of Bak greatly diminishes its association with Noxa, suggesting that both surfaces could act as binding sites for this protein. The DH1a Bak mutant was expressed in cells, and it was able to induce apoptosis at the same level as the wild-type protein, excluding a disruptive effect on the stability or functionality of Bak. Our present results could be reconciled with the report of Dai et al. if residues in the a1 other than the R36 were involved in the interaction with Noxa. Alternatively, we cannot disregard that Noxa could bind to a region in Bak altered in both mutants. The fact that some hydrophobic and aromatic residues in the a1 helix can establish contacts with other amino acids in helices a2, a5, and a6 , would support this hypothesis. In this case, the alteration caused by a1 deletion might selectively affect the binding of Noxa to the hydrophobic groove without affecting activation by Bim and Puma. On the other hand, activated Bax and Bak can be neutralized by the antiapoptotic proteins of the family. The most accepted model for the association of Bax and Bak with antiapoptotic proteins is the "BH3-in-groove", but also the rear surface of Bax and Bak has been proposed to act as a binding domain for the BH4 domain of antiapoptotic proteins . The existence of two different sites for Bcl-2/Bax interaction would agree with our findings in living cells since the D33 could be part of the region, which includes the C-terminus of a1, where the BH4 Bcl-2 domain binds to Bax . In this sense, our results with the D33A and DBH3 mutants confirm that the interaction of full-length Bcl-2 with Bax could occur at two different sites and further extend this model to Bcl-XL and Mcl-1. Our results also indicate that Bcl-2 and Bcl-XL seem to block Bak exclusively through the canonical BH3-in-groove interaction, in contrast with Bax. Nevertheless, Mcl-1/Bak interaction was also reduced in the H1a mutant, indicating that this protein can block Bak through both interfaces, as observed with Bax . Available data on the binding of antiapoptotic proteins to Bax and Bak have been mainly obtained with truncated forms of these proteins. In the case of Mcl-1, both the the C-terminus were eliminated in two studies aimed at identifying critical residues in the BH3 Bax and Bak domains involved in its interaction with Mcl-1. A possible interaction through the H1a of Bax and the N-terminus of Mcl-1 was not explored, but our results with the full-length protein in living cells suggest this possibility. Taken together, these results suggest that the rear pocket of Bax is a binding site for both antiapoptotic and BH3-only proteins, suggesting that antiapoptotic proteins could prevent in this way direct activation triggered by BH3-only proteins. In the case of Bak, only Mcl-1 and Noxa seem to bind to the rear surface . We have also applied the BiFC technique to the study of Bax and Bak dimerization. Once again, we have found differences in the way these two proteins self-associate to induce mitochondrial permeabilization. Many reports indicate that once activated, both Bax and Bak form symmetric dimers through the BH3-in-groove association . Evidence of the existence of at least two independent surfaces in Bax oligomers in micelles also points to a symmetric model . As an alternative, an asymmetric model was initially proposed by some authors , and recent computational work supports that Bak oligomerization proceeds through BH3-rear pocket association to form doughnut-shaped oligomers . Our results in living cells indicate that Bax and Bak monomers can interact, at least, through three interfaces: BH3-in-groove; BH3-rear pocket; and rear pocket-rear pocket. The fact that interaction between two DBH3 mutants can be detected by BiFC suggests the existence of at least one interface other than the BH3-in-groove and does not support an asymmetric model of oligomerization. Nonetheless, our results also indicate that the BH3 domain of a Bax molecule can bind to the rear face of another molecule, and the residue D33 participates in this interaction. An alternative explanation would be that this interaction reflects an autoactivation mechanism, previously proposed for Bax and also for Bak , rather than an asymmetric oligomerization . Our results with H1a mutants suggest that maybe this autoactivation mechanism could be more important in the case of Bax since deletion of the H1a did not affect the self-association of Bak. Regarding the involvement of a6 helices in dimerization, our results also reveal some differences between Bax and Bak. Mutation of either W139 or E146 in Bax reduced the association of monomers, suggesting that these residues participate in the second dimerization interface, as previously proposed , while mutation of H164 in Bak did not reduce the level of association. We cannot exclude the involvement of other residues in the helix a6 of Bak in the rear-rear interface, but our results are more compatible with recent reports that propose alternative surfaces for dimer association. In this sense, since some level of dimerization was still detected with all the mutants herein analyzed, it is possible that several interfaces could mediate Bax and Bak oligomerization. Recent reports have described a probable additional interface in Bak oligomers, formed by the C-terminus of a3 and a5 helices . Furthermore, an a9:a9 interaction has been reported for Bax and Bak . Finally, our present results in living cells would also accommodate a new model in which heterogeneous complexes would assemble through several interaction interfaces . 5. Conclusions Present results using the BiFC technique indicate that interactions between members of the Bcl-2 family could be more promiscuous than usually accepted. Furthermore, our results suggest that Bax and Bak could be activated by BH3 proteins in a different way: BH3-only proteins bind to the H1a of Bax, while the canonic hydrophobic groove of Bak seems to be the site of binding for Bim and Puma. Concerning Bax and Bak oligomerization, our data would fit with models of symmetric BH3-in-groove dimers. Several interfaces could then be involved in the assembly of high-order oligomers. The findings of this study have to be seen in the light of some limitations. As with other techniques for this study of protein-protein interactions, BiFC has some drawbacks that have to be borne in mind. First, as this technique is based on the exogenous expression of protein fusions, it cannot be excluded that endogenous proteins do not behave in the same way. Another limitation concerns the possible effect of the fused fluorescent fragments on the function of the proteins. Finally, complementation could occur when the fusions are placed together in small subcellular compartments, even if there is no direct interaction. Although we have tried to minimize these limitations, and many of our results agree with previous findings using different methods, further studies would be necessary to fully understand the complex network of interactions among proteins of the Bcl-2 family in a cellular context. Acknowledgments We thank Mar Orzaez (CIPF, Valencia) for kindly providing the TOM20 plasmids. We also thank Jose Alberto Carrodeguas (University of Zaragoza) for plasmid pmRFP-TMD and Seamus J. Martin for plasmid pProEx.Htb.annexin V. Authors would like to acknowledge the use of Servicios Cientifico Tecnicos del CIBA (IACS-Universidad de Zaragoza). We thank Maria Royo and Cesar Vallejo (Microscopy and Image Service, IIS-Aragon), Javier Godino (Flow Cytometry Service, IIS-Aragon) for excellent technical assistance, and Julian Pardo (IIS-Aragon) for helpful discussions. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Two examples of the analysis of BiFC by flow cytometry; Figure S2: HeLa cells were cotransfected with the indicated BiFC fusions and expression was analyzed by Western Blot with anti-HA and anti-Flag tags; Figure S3: Multicolor data analysis example; Figure S4: Possible dimerization pairs through the BH3-in Groove and a1:a6 interfaces; Supplementary data: Nucleotide sequences of the fusions used in BiFC experiments. Click here for additional data file. Author Contributions Conceptualization, O.G., L.V. and I.M.; methodology, O.G., A.B. and L.V.; investigation, O.G., A.B. and L.V.; formal analysis, O.G., L.V., A.B. and I.M.; writing--original draft preparation, I.M.; writing--review and editing, O.G., A.B., L.V., A.A. and J.N.; supervision, I.M., J.N. and A.A.; project administration, A.A. and I.M.; funding acquisition, A.A. and I.M. 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. The funders had no role in the design of this 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 (a) Protein fusions used to study interactions between proteins of the Bcl-2 family. Each protein was fused to the VN or VC fragment of Venus protein. After transfection, interaction of VN-A and VC-B allows for complementation of Venus fragments, and fluorescence can be detected. Expression of the BiFC fusions in HeLa cells (VN or VC fragments fused to Bcl-2, Bcl-XL, Mcl-1, Bim, Puma, Noxa, Bax and Bak) was analyzed by Western Blot. Arrows indicate the bands of fusions, being the MW of VN-linker 17.5 kDa and VC-linker 10.5 kDa. Small arrows indicate bands corresponding to endogenous proteins. The asterisk denotes a non-specific band. (b-f) Complexes detected by BiFC show mitochondrial localization. HeLa cells were seeded in coverslips and co-transfected with vectors expressing fusions of the indicated proteins with VN and VC fragments and a vector expressing a mitochondrial-targeted mRFP. Following 24 h after transfection, nuclei were stained with Hoechst 33342 (2 mg/mL), cells fixed with 4% PFA for 15 min at 4 degC, and mounted on Fluoromount-G. Images were collected in sequential mode in a FluoView FV10i (Olympus) confocal microscope, as detailed in the Materials and Methods section. Figure 2 Analysis of Bax and Bak interactions in living cells. (a,b) Quantification of the interactions of Bax (a) and Bak (b) with antiapoptotic and BH3-only proteins. HeLa cells were transfected with appropriate pairs of BiFC vectors expressing protein fusions with the VC or VN fragments of Venus: VC-Bax and VC-Bak were co-transfected with VN-Bcl-2, VN-Bcl-XL, VN-Bim, VN-Puma, and VN-Noxa; VN-Bax and VN-Bak were co-transfected with VC-Mcl-1. Corresponding TOM20 fusions were used as control. The pmRFP-TMD vector was included in the transfections to allow for gating of transfected cells and normalization of fluorescence intensities. Venus and mRFP fluorescence were analyzed by flow cytometry 24 h after transfection. The Venus/mRFP MFI ratios are represented for each pair of proteins. Results are mean +- SEM of 9 (Mcl-1, Bcl-2, and Bim), 9 (Bcl-XL), 11 (Puma and Noxa), and 4 (TOM20) independent experiments. (c,d) Visualization of BiFC complexes and mitochondria stained with MitoTracker Red. Cells were seeded in coverslips and transfected 24 h later with corresponding BiFC vectors, as indicated in A and B. Following 24 h after transfection, cells were stained with 100 nM MitoTracker Red for 15 min at 37 degC. Then, cells were washed and fixed with 4% PFA. Coverslips were mounted with Fluoromount-G and observed in a fluorescence microscope. (e) Association of Bim, Puma and Noxa with antiapoptotic proteins was quantified as indicated in (a,b). Cells were transfected with pBiFC vectors for expression of appropriate VC-fusions (VN-Bcl-2 was co-transfected with VC-Bim, VC-Puma or VC-Noxa; VC-Bcl-XL and VC-Mcl-1 were combined with VN-Bim, VN-Puma, or VN-Noxa) together with the pmRFP-TMD. The Venus/mRFP ratio in mRFP-positive cells was determined by flow cytometry. Results are mean +- SEM of 8 independent experiments. (f) BH3-mimetics specifically disrupt interactions between antiapoptotic and BH3-only proteins. Cells were transfected as indicated in (e), and 1 h after transfection, each ABT-199, A-1155463, or S63483 was added at the indicated concentrations. Venus and mRFP fluorescence were analyzed by flow cytometry 24 h after transfection. Changes in the Venus/mRFP ratios for each inhibitor are represented. Results are mean +- SEM of 3 independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.005, **** p < 0.001 (one-way ANOVA followed by Tukey's multiple comparison test). Figure 3 Multicolor BiFC analysis of interactions between BH3-only and antiapoptotic or Bax/Bak proteins. (a) Experimental basis of the multicolor assays. Fusions of proteins in each subset with the amino or carboxy fragments of Cerulean (CN and CC, respectively) and Venus (VN) proteins were constructed, as described in the Materials and Methods section. The VN and CN fragments can complement the CC fragment, yielding complete proteins with distinct spectral properties. (b) Expression of the CC-, VN-, and CN-fusions was verified through Western Blot. Arrows indicate the bands of fusions, being the MW of VN-linker 17.5 kDa and CC-linker 10.5 kDa. Small arrows indicate bands corresponding to endogenous proteins. The asterisk denotes a non-specific band. (c) HeLa cells were transfected with vectors expressing the fusions indicated in boxes, together with the pAL2-Myc-mRFP vector. Cerulean and Venus fluorescence signals were analyzed in mRFP-positive cells by flow cytometry. FL-9 (cerulean)/FL-1 (Venus) histograms were analyzed using Weasel software. Each histogram was divided into 15 sections in the FL-1 dimension. Mean Venus and Cerulean fluorescences in each section were recorded, represented as an XY graphic, and adjusted to a linear function using GraphPad Prism software. Circle diameter is proportional to cell density in the corresponding section of the histogram. A representative graphic of two independent experiments for each assay is represented. Figure 4 Interactome of Bax/Bak, antiapoptotic, and BH3-only proteins, according to BiFC, results in living cells. Figure 5 Role of a1 helix and BH3 domain in the interactions of Bax protein with BH3-only and antiapoptotic members of the Bcl-2 family. (a) Wild-type and mutated VN/VC-Bax fusions were used for BiFC. Expression of the mutants was confirmed by means of Western Blot. Theoretical MW of the fusions is indicated on the right side of each gel (VN fragment 17.5 KDa; VC fragment 10.5 KDa). (b) HeLa cells were transfected with vectors expressing Bim, Puma, or Noxa fused to the VN Venus fragment together with vectors expressing the corresponding Bax wild-type or mutated fusions with the VC Venus fragment and the pmRFP-TMD vector. Mean Venus/mRFP fluorescence intensity ratios for each pair are indicated. Results are the mean +- SEM of 4 (Bim, Puma) or 6 (Noxa) independent experiments. (c) HeLa cells were transfected with vectors expressing Bcl-2, Bcl-XL, or Mcl-1 fusions with the VN (Bcl-2 and Bcl-XL) or the VC (Mcl-1) Venus fragment together with vectors expressing the corresponding Bax wild-type or mutated fusions and the pmRFP-TMD vector for mRFP expression. Mean Venus/mRFP fluorescence intensity ratios for each pair are indicated. Results are the mean +- SEM of 4 (Bcl-2 and Bcl-XL) or 6 (Mcl-1) independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.005. One-way ANOVA followed by Tukey's multiple comparison test. (d) HCT116 Bax-/- cells were transfected with pBabe vectors expressing WT or mutated Bax protein. A vector expressing GFP was used as a control for unspecific cell death. The percentage of apoptotic cells was analyzed 48 h after transfection by Annexin V-DY634 binding and flow cytometry. Results are mean +- SEM of 3 independent experiments. * p < 0.05, ** p < 0.01. One-way ANOVA followed by Tukey's multiple comparison test. (e) Cells were seeded in coverslips and transfected 24 h later with corresponding BiFC vectors for expression of VN-Bcl-XL and the indicated VC fusions. Following 24 h after transfection, cells were stained with 100 nM MitoTracker Red for 15 min at 37 degC. Then, cells were washed and fixed with 4% PFA. Coverslips were mounted with Fluoromount-G and observed in a fluorescence microscope. Figure 6 Role of a1 helix and BH3 domain in the interactions of Bak protein with BH3-only and antiapoptotic members of the Bcl-2 family. (a) Wild-type and mutated VN/VC-Bak fusions were used for BiFC. Expression of mutants was confirmed by Western Blot. For detection of the DBH3 mutant, the anti-Bak (NT) antibody from Upstate was used, while an anti-Bak (G-23) antibody from Santa Cruz Biotechnology allowed for detection of WT, DH1a, or H164A Bak variants. * Non-specific band. (b) HeLa cells were transfected with vectors expressing Bim, Puma, or Noxa fused to the VN Venus fragment together with vectors expressing the corresponding Bak wild-type or mutated fusions with the VC Venus fragment and the pmRFP-TMD vector. Mean Venus/mRFP fluorescence intensity ratios for each pair are indicated. Results are the mean +- SEM of 4 independent experiments. (c) Hela cells were transfected with vectors expressing Bcl-2, Bcl-XL (VN), or Mcl-1 (VC) fusions with a Venus fragment together with vectors expressing the corresponding Bak wild-type or mutated fusions and the pmRFP-TMD vector. Mean Venus/mRFP fluorescence intensity ratios for each pair are indicated. Results are the mean +- SEM of 5 independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.005. One-way ANOVA followed by Tukey's multiple comparison test. (d) MiaPaca2 Bak-/- cells were transfected with pBabe vectors expressing wild-type or mutated Bak protein. A vector expressing GFP was used as a control for unspecific cell death. The percentage of apoptotic cells was analyzed 48 h after transfection by Annexin V-DY634 binding and flow cytometry. Results are mean +- SEM of 3 independent experiments. * p < 0.05, ** p < 0.01. One-way ANOVA followed by Tukey's multiple comparison test. Figure 7 Analysis of the dimerization between Bax and Bak WT and DBH3 mutants. Cells were transfected with vectors expressing wild-type and DBH3 Bax (a) or Bak (b) fused to VC or VN fragments, as indicated, together with pmRFP-TMD vector. Venus/mRFP ratios were analyzed by flow cytometry. Results are mean +- SEM of 10 (Bax) or 6 (Bak) independent experiments. * p < 0.05, ** p < 0.01. One-way ANOVA followed by Tukey's multiple comparison test. (c,d) DBH3 Bax and Bak mutants show reduced proapoptotic activity. Hela cells were transfected with vectors expressing VN-Bax/VC-Bax and VN-BaxDBH3/VC-BaxDBH3 (c) or VN-Bak/VC-Bak and VN-BakDBH3/VC-BakDBH3 (d) and 24 h later cells were stained with 100 nM MitoTracker Red. Venus fluorescence and MitoTracker Red were visualized in a fluorescence microscope. Arrowheads point to Venus-positive cells (e) Dimerization between WT and DBH3 mutants according to the symmetric and asymmetric models. Possible dimerization interfaces for each model are depicted. Crosses denote protein interactions not allowed due to mutations. Interrogation marks indicate possible interactions that could still occur depending on the surfaces involved in dimerization and oligomerization of Bax and Bak. Figure 8 Involvement of a1 and a6 helices in Bax and Bak oligomerization. pBiFC vectors with Bax (a) or Bak (b) mutants in the helix a1 or a6 were constructed, and their expression was verified by Western Blot. * Non-specific band. (c) Cells were transfected with vectors for the expression of wild-type Bax a1 or a6 mutants indicated, fused to VC or VN fragments and the pmRFP-TMD vector. Venus/mRFP ratio for each pair of fusions is represented. Results are mean +- SEM of 6 (W139A, E146A, and R147A) or 8 (WT and K21E and D33A) * p < 0.05, ** p < 0.01 One-way ANOVA followed by Tukey's multiple comparison test. (d) Cells were transfected with vectors for the expression of wild-type Bak, and a1 or a6 helix mutants indicated, fused to VC or VN fragments. The pmRFP-TMD vector was included in the transfection. Venus/mRFP ratio for each pair of fusions is represented. Results are mean +- SEM of 6 (H164A) or 8 (WT and DH1a) independent experiments. * p < 0.05, One-way ANOVA followed by Tukey's multiple comparison test. (e) Possible interaction interfaces between WT and a1/a6 mutants or DBH3 and a1/a6 mutants. (f,g) Cells were transfected with the indicated pairs of fusions for BiFC, together with the pmRFP-TMD vector. Venus/mRFP mean fluorescence ratio was determined by flow cytometry. Results are mean +- SEM of 6 (f) or 3 (g) independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.005. Student two-tailed unpaired t-test. (h) Bax dimerization analysis by BiFC in HCT116 Bax-/- cells. Cells were transfected with vectors for BiFC containing the cDNA of the indicated wild-type or mutant Bax proteins fused to VN/VC Venus fragments, and the pmRFP-TMD vector for expression of mRFP was included for selection of transfected cells and fluorescence normalization. Venus/mRFP ratios were determined by flow cytometry 24 h after transfection. Results are mean +- SEM of 4 independent experiments with two replicates. * p < 0.05, ** p < 0.01 One-way ANOVA followed by Tukey's multiple comparison test. Figure 9 Activation steps for Bax and Bak. Activator BH3-only proteins trigger conformational changes in Bax and Bak, leading to BH3 domain exposure. The trigger site is the a1 helix (H1a) in Bax and the canonical hydrophobic groove (Bim, Puma, Noxa) and the a1 helix (Noxa) in Bak. Preactivated Bax can also activate other Bax molecule by binding to the H1a. Antiapoptotic proteins can block the H1a activation site in Bax and Bak (only Mcl-1). The exposed BH3 domains of activated Bax and Bak can be blocked by antiapoptotic proteins or dimerized through BH3-in-groove interaction. Oligomerization proceeds by BH3-in-groove dimerization, followed by the assembly of dimers in high-order oligomers. The H6a could be involved in the association of Bax dimers, but other interfaces could also mediate its oligomerization. In the case of Bak, interfaces other than the H6a seem to participate in oligomerization. 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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PMC10000387 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050860 diagnostics-13-00860 Article Implementation of Exome Sequencing in Prenatal Diagnostics: Chances and Challenges Janicki Ewa Conceptualization Methodology Data curation Writing - original draft Writing - review & editing Visualization 1 De Rademaeker Marjan Conceptualization Methodology Data curation Writing - original draft Writing - review & editing 2 Meunier Colombine Data curation 3 Boeckx Nele 2 Blaumeiser Bettina Conceptualization Methodology Data curation Writing - original draft Writing - review & editing 2* Janssens Katrien Conceptualization Methodology Data curation Writing - original draft Writing - review & editing 2 Cha Dong Hyun Academic Editor 1 Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, 2000 Antwerp, Belgium 2 Center for Medical Genetics, University of Antwerp and University Hospital of Antwerp, 2650 Antwerp, Belgium 3 Center for Medical Genetics, Institut de Pathologie et de Genetique Gosselies, 6041 Charleroi, Belgium * Correspondence: [email protected] 23 2 2023 3 2023 13 5 86011 1 2023 13 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 ). Whole exome sequencing (WES) has become part of the postnatal diagnostic work-up of both pediatric and adult patients with a range of disorders. In the last years, WES is slowly being implemented in the prenatal setting as well, although some hurdles remain, such as quantity and quality of input material, minimizing turn-around times, and ensuring consistent interpretation and reporting of variants. We present the results of 1 year of prenatal WES in a single genetic center. Twenty-eight fetus-parent trios were analyzed, of which seven (25%) showed a pathogenic or likely pathogenic variant that explained the fetal phenotype. Autosomal recessive (4), de novo (2) and dominantly inherited (1) mutations were detected. Prenatal rapid WES allows for a timely decision-making in the current pregnancy, adequate counseling with the possibility of preimplantation or prenatal genetic testing in future pregnancies and screening of the extended family. With a diagnostic yield in selected cases of 25% and a turn-around time under 4 weeks, rapid WES shows promise for becoming part of pregnancy care in fetuses with ultrasound anomalies in whom chromosomal microarray did not uncover the cause. prenatal diagnosis whole exome sequencing chromosomal microarray diagnostic yield congenital anomalies This research received no external funding. pmc1. Introduction Major congenital anomalies (MCA) have a prevalence of 2-3% and are responsible for a significant percentage of perinatal demise and neonatal morbidity . The etiology is heterogeneous, ranging from prenatal infections over teratologic agents to genetic causes. Chromosomal microarray analysis (CMA) has been widely implemented in the analysis of invasively obtained prenatal samples (amniotic fluid or chorion villi) for the genome-wide detection of both aneuploidies and microdeletions/microduplications (copy number variants or CNVs). In up to 40% of pregnancies with a fetal structural anomaly, CMA is able to diagnose an aneuploidy or CNV , still leaving more than half of the cases undiagnosed. Several recent metaanalyses have demonstrated an added diagnostic yield of 1.8-68% for prenatal whole exome sequencing (WES), with the yield largely depending on the inclusion criteria and organ system affected . With increasing evidence of the relevance of WES in the prenatal context, revision of the guidelines of the International Society for Prenatal Diagnosis (ISPD) offers directions on how to implement it . This paper describes the experiences of a single Belgian genetic center with the implementation of WES in the prenatal diagnostic workflow. In Belgium, the molecular analysis of publicly funded invasive prenatal diagnosis can only be executed at one of the eight Centers for Medical Genetics. For all indications, a genome-wide microarray is performed with national consensus guidelines in place steering the interpretation and reporting of the results . Recently, a national framework has been formulated guiding the indication, analysis and reporting of prenatal WES. Here we discuss the opportunities and challenges for the use of WES in the diagnosis of fetuses with ultrasound abnormalities and provide suggestions for implementation of this valuable technique in other labs. 2. Methods Genomic DNA was extracted from either amniotic fluid, chorion villi or cultured amniocytes using the Maxwell RSC Blood DNA kit on a Maxwell RSC 48 Instrument (Promega, Madison, MI, USA). Library prep on 50ng of genomic DNA was performed using the Twist Human Core Exome kit (Twist Bioscience, South San Francisco, CA, USA) according to the manufacturer's instructions on a Hamilton STAR robot (Hamilton, Bonaduz, Switzerland). Twenty-four libraries were pooled equimolarly for sequencing on a NextSeq500 or NextSeq550 instrument with a 2 x 75 bp or 2 x 150 bp flow cell (Illumina, San Diego, CA, USA). WES data were analyzed using an in-house developed pipeline which considers only de novo, X-linked and recessive variants, either in a predefined panel (e.g., in case of a skeletal dysplasia) or exome-wide . Additionally, the AI-driven decision-support software Moon was applied to complement our pipeline with an independent phenotype-driven analysis (Invitae, San Francisco, CA, USA), allowing the identification of variants outside the panel (if applied) and of inherited variants. An independent analysis was performed to detect sample swaps and to verify the family relations within each trio. The guidelines for prenatal WES were developed at a national level and can be found at the website of the Belgian College of Genetics (www.college-genetics.be (accessed on 1 December 2022)). The following criteria must be met: (1) The fetus shows ultrasound anomalies, but CMA is negative; a diagnosis is essential to guide the pregnancy/neonatal management; (2) All cases should be reviewed in a multidisciplinary team including a clinical geneticist; (3) Expert fetal ultrasound examinations are required to provide the best possible phenotypic evaluation. When beneficial, fetal MRI may be performed; (4) Pretest counseling by a clinical geneticist is mandatory, with signed informed consent by both parents; (5) Trio analysis (simultaneous analysis of the fetus and both parents) is strongly recommended to speed up the process. Variant classification is performed based on the ACMG guidelines . Only pathogenic (class V) and likely pathogenic (class IV) variants with known effect on gene function and which fit with the fetal phenotype and the inheritance mode are communicated. Variants of uncertain significance (class III) are in principle not communicated, but exceptions can be made for variants in known disease genes that (a) fit the fetal phenotype, (b) are expected to show the same pathomechanism as known pathogenic variants and (c) arose as de novo events or are detected in trans with a pathogenic or likely pathogenic variant and for which further clinical exams (ultrasound, MRI, etc.) are recommended to refine variant classification, possibly leading to a genetic diagnosis (upgrade of the variant to class IV/V). By national agreement, no systematic search for secondary findings, unrelated to the fetal phenotype, is performed, in line with the framework proposed by Vears et al. The identification of incidental findings is minimized by optimizing the filter settings without jeopardizing the detection of primary results. In this category, de novo fetal highly penetrant class IV/V variants known to cause moderate or severe childhood-onset disorders are reported, as well as inherited class IV/V variants causing late-onset disorders for which reporting can be expected to cause an undeniable health benefit, such as those listed in the ACMG SF v3.0 list . Fetal (and maternal) carriership for X-linked recessive disorders will be reported as well, as it can be of relevance for future pregnancies of both mother and child. On the other hand, variants causing late onset disease without actionability and carriership for autosomal recessive disorders will not be communicated. The turn-around-time (TAT) was nationally set at eight weeks for ongoing pregnancies. 3. Results The Center of Medical Genetics Antwerp, which is one of the eight genetic centers in Belgium, processes about 400 invasive prenatal samples on a yearly basis. In our center, the routine approach to determine the genetic etiology in case of fetal ultrasound anomalies, regardless of the gestational age, follows a sequential approach: first, we perform a quantitative fluorescent PCR (QF-PCR) for exclusion of the common aneuploidies (trisomy 13, 18, 21, sex chromosomal aneuploidies) and triploidy as well as for determination of maternal cell contamination and fetal identity through comparison to the maternal profile. Next, CNV detection by CMA is performed, more precisely a SNP (single nucleotide polymorphism) array with a 400 kb resolution. However, this combined approach yields a diagnosis in less than 25% of cases: on 3453 analyses that were performed over the past nine years, QF-PCR and SNP array were positive in 786 cases (22.8%), among which 557 with a trisomy (70.9% of positive and 16.1% of total cases), 30 with a triploidy (respectively 3.8% and 0.87% of cases), 62 with monosomy X (respectively 7.9% and 1.8% of cases) and 134 with a subchromosomal pathogenic anomaly (respectively 17% and 3.9% of cases) . Since January 2021, our center offers the subsequent option of whole exome sequencing (WES). In 2021, WES was performed in our center on 28 prenatal cases showing structural anomalies on ultrasound . Twenty WES analyses were performed on DNA extracted from uncultured amniotic cells, six from cultured amniotic cells and two from chorion villi. In all but two cases, an 'open' WES was performed, as the ultrasound anomalies did not allow the selection of a predefined gene panel; for the two remaining cases, the analysis was restricted to our skeletal dysplasia gene panel of 436 genes (see Supplementary Table S2 for the composition of the panel). All cases passed our quality score (capture of more than 95% of the exome with at least 20x coverage). Pathogenic or likely pathogenic variants were identified in seven out of 28 (25%) cases: two de novo variants, four autosomal recessive and one paternally inherited (from an affected parent) (see Table 1). In three fetuses with skeletal anomalies, WES detected respectively a dominantly inherited COL2A1 variant , a homozygous FANCG variant and a de novo KMT2D variant. The fetus with the COL2A1 variant displayed rhizomelic shortening and bowing of the long bones, microretrognathia and clenched hands-on prenatal ultrasound. The fetus with the FANCG variant came to attention through intrauterine growth restriction (IUGR), thumb hypoplasia on the left hand and absent thumb on the right hand. The fetus with the KMT2D variant had talipes equinovarus as well as abnormal placing of the ears. Three fetuses with multisystem anomalies, defined as the presence of at least two major anomalies in different anatomical systems, carried respectively a homozygous MUSK variant , a homozygous CHRNA1 variant and compound heterozygous THOC6 variants. The pregnancy with the MUSK variant was suspicious since it was the second pregnancy of this couple with fetal hydrops. The first was terminated and no genetic analyses had been performed; in the current, the evolution towards a more severe phenotype with fetal akineseia and abnormal position of the lower limbs justified exome sequencing. The fetus with the CHRNA1 variant came to attention because of multiple congenital malformations, namely retrognathia, diffuse subcutaneous edema, increased nuchal fold, clenched fingers, bell-shaped thorax and bilateral rocker bottom feet. The fetus with the THOC6 variants displayed Tetralogy of Fallot, cerebellar hypoplasia, mild ventriculomegaly and hypospadias. The last positive case was a de novo RIT1 variant in a fetus with bilateral hydrothorax, ascites, generalized subcutaneous edema and polyhydramnion. All but one variant was classified as pathogenic; the missense variant in CHRNA1 was classified as likely pathogenic as it had not been described in the literature, but was deemed pathogenic by prediction scores and fit the phenotype. Additionally, a pathogenic incidental finding in STXBP1 was reported in one case that also carried a pathogenic variant which explained the phenotype (RIT1). In all but one case, the parents opted for a termination of the pregnancy (see Table 1). The exception was the fetus with the paternally inherited COL2A1 variant. At birth, the baby showed--in addition to the prenatally observed anomalies--cleft palate, atrial septal defect, pathological auditory evoked potentials and ophtalmological abnormalities compatible with Stickler syndrome. At 4 months, her length is at P10 and some additional facial dysmorphisms, such as narrow palpebral fissures, long philtrum, thin upper lip and full cheeks, become apparent. When grouped based on the organ system(s) involved (see also Mellis et al. 2022 ), the highest diagnostic yield was obtained in case of skeletal anomalies (three out of six cases or 50%) or multisystem anomalies (three out of eight cases or 37.5%). No diagnosis was found in seven cases with heart disease and five with a central nervous system anomaly . 4. Discussion In Belgium, prenatal WES in a diagnostic setting is publicly funded and fully reimbursed. National guidelines describing the inclusion criteria, posttest counseling and the filtering and reporting strategy have been developed by a committee of laboratory and clinical geneticists and are publicly available on the website of the Belgian College for Human Genetics and Rare Diseases (www.college-genetics.be (accessed on 1 December 2022)). However, prenatal WES has not been implemented widely, as many hurdles still remain. Issues involve (1) the quality and quantity of the starting material; (2) the short TAT; (3) the interpretation of variants; (4) the ethical perspective. In our center, no problems with DNA quality were encountered--for all samples, DNA was extracted in-house according to an accredited protocol that yields high quality DNA. For some of the samples, insufficient DNA was obtained upon extraction from uncultured amniocytes and a second DNA extraction from cultured amniocytes was required. As a precaution, we always culture part of the amniocytes. First, this provides a back-up source of DNA, although we need as little as 2 ng of starting material for QF-PCR, 20 ng for SNP array and 50 ng for WES. Second, during the culturing process, growth of amniocytes is enhanced, but that of peripheral blood cells is not, which is an advantage in case the QF-PCR on the DNA extracted from the uncultured amniocytes shows maternal cell contamination . Although the TAT for prenatal WES has been set nationally at eight weeks, we lowered it to 4 weeks, allowing timely decision-making for the ongoing pregnancy; couples might either consider termination of pregnancy when a genetic diagnosis is established or the etiology could guide the obstetric and neonatal management. Both the library prep and the sequencing run are performed biweekly; analysis and interpretation take maximally 1 additional week, including multidisciplinary discussions on variant interpretation or reporting. All cases were analyzed as trio (index and both parents), which allows filtering of de novo, autosomal recessive and X linked variants. Additionally, we use a phenotype-driven software package for variant prioritization (Moon, Invitae) to detect inherited variants that fit the phenotype (e.g., in imprinted genes or with a mosaic or presumably unaffected carrier parent) and, in case of panel-based analysis, variants in genes outside the panel. Apart from trio analysis, other steps to limit the number of variants that require classification are minor allele frequency in the GnomAD database and our own database, location (only exonic variants and variants in the splice regions are considered) and allelic ratio of the mutant versus wild-type allele. Extensive phenotyping is key to interpretation of the remaining variants. In our center, we developed a database where clinicians can enter the phenotype as HPO (Human Phenotype Ontology) terms, allowing for structured phenotyping. Correlating the genotype with the prenatal phenotype was challenging. In general, the fetal phenotype of many conditions has not been well described and may deviate quite substantially from the known postnatal phenotype. Cataloguing the phenotype of prenatal-onset syndromes is of utmost importance to guide healthcare providers in recognizing these syndromes at an early stage and know their evolution throughout the pregnancy . The correlation was the most obvious in the fetus with the RIT1 mutation (case 23), associated with Noonan type 8 (OMIM# 615355): hydrops, ascites and hydrothorax, which were all present in this fetus, are frequent ultrasound markers in RASopathies. Given the genotypic heterogeneity of Noonan syndrome and by extension non-immune hydrops fetalis , WES or whole-genome sequencing are powerful diagnostic tools for these diseases . This fetus also carried a de novo pathogenic variant in STXBP1, that was reported as incidental finding because of its association with developmental and epileptic encephalopathy 4 (OMIM# 612164). Given the severe phenotype of seizures, profoundly impaired psychomotor development, limited or absent ability to walk, spastic quadriplegia and poor or absent speech, prenatal testing in a future pregancy is warranted as parental gonadal mosaicism cannot be ruled out. In case of a suspicion of a fetal skeletal dysplasia, the value of adding WES to the prenatal diagnostic tools has been demonstrated before ; this was confirmed in our cohort, with three out of six cases (50%) being solved by WES. The fetus with Stickler syndrome type I (OMIM# 108300) caused by a heterozygous COL2A1 missense mutation (case 10) displayed rhizomelic shortening and bowing of the long bones as well as microretrognathia and clenched hands on ultrasound . The mutation was paternally inherited, manifesting in the to that point undiagnosed father with severe myopia, hearing disorder, short stature, retrognathia, a nasal voice, tibia bowing, platyspondyly, coxofemoral dysplasia, hyperlordosis and rhizomelic shortening of the long bones . Analysis of the paternal grandparents demonstrated that the mutation arose de novo in the father. The second fetus with skeletal anomalies (case 1) was diagnosed with Kabuki syndrome as a result of a de novo stop mutation in KMT2D (OMIM# 147920). Kabuki syndrome shows prenatal phenotypic heterogeneity, with ultrasound abnormalities that are non-specific. The most frequent ultrasound features include cardiac anomalies (49.4%), followed by polyhydramnios (28.9%), genitourinary anomalies (26.5%), single umbilical artery (15.7%), intrauterine growth restriction (14.5%) and hydrops fetalis/pleural effusion/ascites (12.0%) . The fetus in our cohort showed only bilateral talipes equinovarus and abnormal ears, illustrating the broad fetal phenotypic heterogeneity. The third fetus (case 8) presented with intrauterine growth restriction, oligodactyly of the left hand and a hypoplastic ray of the right hand and was diagnosed with Fanconi anemia (FA) due to a homozygous FANCG nonsense variant (OMIM# 614082). FA is an autosomal recessive disorder with both phenotypic and genotypic heterogeneity, but major birth defects such as skeletal malformations (mainly bilateral radial ray anomalies), microcephaly, genitourinary malformations and intrauterine growth restriction are present in 75% of the cases. Consequently, these findings in the prenatal setting are suggestive of FA, although absence of skeletal anomalies does not exclude FA . Radial ray defects, as present in this fetus, can be associated with various disorders, but in combination with IUGR or other MCA, it is indicative of FA . Rapid WES in case of skeletal anomalies allows differentiating between isolated and syndromic forms, which is key to counseling the parents. Of eight fetuses with multisystem aberrations in our series, three (37.5%) were positive. The first (case 26) was compound heterozygous for four known missense variants (of which three on the maternal allele that have been described as a pathogenic haplotype) in THOC6, causing Beaulieu-Boycott-Innes syndrome (OMIM# 613680). There are seven reports of prenatally diagnosed Beaulieu-Boycott-Innes syndrome with variable clinical findings, such as IUGR, cerebral malformations, genito-renal abnormalities, cystic hygroma, retrognathia and suspicion of ventricular septal defect . Our case showed olivopontocerebellar hypoplasia, tetralogy of Fallot and hypospadias on ultrasound. The second fetus (case 28) was diagnosed with a homozygous missense variant in a receptor tyrosine kinase (MUSK). For fetal akinesia deformation sequence 1 (FADS1), caused by homozygous MUSK mutations (OMIM# 208150), prenatal diagnosis is based on multiple contractures, reduced motility, flattening of facial profile and--with increasing gestational age--IUGR, reduced cardiothoracic ratio and polyhydramnios . The ultrasound features present in our case fit the described prenatal phenotype. The third fetus (case 12) presented with nuchal translucency, edema, rocker-bottom feet, aberrant chest and ribs and retrognathia and was diagnosed with a homozygous CHRNA1 missense variant. Recessive mutations in the CHRNA1 gene result in lethal multiple pterygium syndrome (LMPS; OMIM# 253290). LMPS displays a heterogeneous range of prenatal manifestations that generally include cystic hygroma, pulmonary hypoplasia, cleft palate, cryptorchidism, joint contractures, fetal akinesia, heart defects, growth restriction and intestinal malrotation . In retrospect, the phenotype of this fetus fits the LMPS syndrome, but a clinical diagnosis remains challenging in the prenatal stage. In total, WES was able to pinpoint the cause of the fetal anomalies in 25% of cases (7 out of 28). Among the seven positive cases, two were de novo, four recessive and one paternally inherited (from an affected parent). Multidisciplinary genetic counseling of the prenatal results was performed and except for the parents with the fetus diagnosed with paternally inherited Stickler syndrome, all chose to terminate the pregnancy after approval by the ethical committee of the University Hospital Antwerp. For all cases, the decision to terminate was based on the WES result, effectively demonstrating its use in the prenatal setting. For five out of seven families (71.4%), the recurrence risk is high and preimplantation or prenatal invasive genetic testing can be offered in future pregnancies. For the family with the dominantly inherited variant, testing in first-degree relatives of the father can be considered as well. In the families with a de novo variant, genetic testing in future pregnancies should be discussed because of the possibility of parental gonadal mosaicism. Ethically, the most demanding issue is the possibility of incidental findings in both fetus and parents. Although rigorous filtering can reduce the number of incidental findings, they can never be fully excluded as this would jeopardize the identification of the primary variant(s) explaining the phenotype. Therefore, a genetic pretest counseling as well as informed consent by both parents are mandatory, so that they are well aware of the possible outcomes. The only incidental finding we encountered was a de novo mutation in STXBP1, associated with developmental and epileptic encephalopathy type 4, in the fetus carrying the RIT1 mutation. In case of future prenatal invasive testing, presence of both the RIT1 and the STXBP1 mutation can be evaluated. The recent update of the ISPD position statement on prenatal WES states that although the available data is insufficient to recommend which categories of abnormalities warrant sequencing, there are 'sufficient data to begin differentiating diagnostic yields by specific organ system or number of organ systems affected' . Our results confirm their findings that prenatal WES holds great promise for pregnancies with skeletal or multisystem anomalies. In our hands, prenatal WES was less successful in foetuses with cardiac and CNS abnormalities, but the number of cases in this study is too low to draw any definitive conclusions. It can be expected that, based on the contribution of this and other manuscripts describing the results of WES in the prenatal context, uniform guidelines on the indications for which to consider WES will follow in the near future. 5. Conclusions Our data set, although limited, clearly shows the added value of WES in the prenatal setting in case of MCA. The diagnostic yield of 25% demonstrates that the rigorous selection of prenatal cases according to our national guidelines is effective; yield is highest in cases with skeletal or multisystem anomalies. Furthermore, our findings demonstrate that WES can be implemented in a medium-throughput diagnostic lab with little failures and an acceptable TAT, effectively expanding the diagnostic portfolio that can be offered to future parents. Acknowledgments The authors wish to thank the patients for their willingness to participate in this study. Supplementary Materials The following supporting information can be downloaded at Table S1: Fetal phenotype and genotype; Table S2: Composition of the skeletal dysplasia gene panel. Legend to Supplementary Table S1; This table contains the 28 fetal cases on whom WES was performed. For each case, the fetal phenotype and the organ system involved are described, as well as the sample type from which the DNA was extracted, the applied gene panel and the result. For the positive cases, the gestational age at ultrasound, the affected gene and variant, the inheritance mode, the associated syndrome, the fetal phenotype as described in the literature and the outcome of the pregnancy are listed as well. AC: amniocytes: AD: autosomal dominant; AR: autosomal recessive; CNS: central nervous system; CV: chorionic villi; hom: homozygous; IF: incidental finding; IUGR: intrauterine growth restriction; LB: live birth; mat: maternal; NT: nuchal translucency; pat: paternal; path: pathogenic; TOP: termination of pregnancy; US: ultrasound; VSD: ventricular septal defect; WES: whole exome sequencing; WESSD: WES with skeletal dysplasia panel; Legend to Supplementary Table S2. This table lists the genes included in the skeletal dysplasias gene panel, that was used for analysis of cases 6 and 10. Click here for additional data file. Author Contributions Lab work and interpretation of WES data, N.B. and K.J.; conceptualization, methodology, writing--original draft preparation, writing--review and editing, E.J., M.D.R., B.B. and K.J.; data curation, E.J., M.D.R., C.M., B.B. and K.J.; visualization, E.J. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical approval for retrospective studies is not required by the responsible ERC. Informed Consent Statement Written and signed informed consent was obtained from the participating patients/their legal guardian and are stored in their medical files. Data Availability Statement All data are archived in the patient files. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Diagnostic yield of QF-PCR/CMA in the prenatal context. QF-PCR: quantitative fluorescent polymerase chain reaction; CMA: chromosomal microarray. Figure 2 Distribution of fetal WES cases according to organ system. CNS: central nervous system. Figure 3 Phenotype of fetus and father with Stickler syndrome due to a COL2A1 variant. (a) 3rd trimester ultrasound showing femoral shortening and bowing; (b) 3rd trimester ultrasound showing pathological lower facial angle at 44deg corresponding to microretrognathia; (c) Affected father: short and stocky appearance; (d) Feet of affected father; (d) Feet of affected father: right 4th toe and left 4th and 5th toes are proximally implanted and the lower limbs show bowing at the ankles; (e) Left hand of affected father: short hand and brachydactyly. Figure 4 Fetus with a homozygous MUSK variant causing Fetal akinesia deformation sequence 1. (a) Ultrasound at 20 weeks, showing subcutaneous edema; (b) Clinical picture: rocker-bottom feet and hydrops fetalis. diagnostics-13-00860-t001_Table 1 Table 1 Prenatal cases for which WES demonstrated a likely pathogenic or pathogenic variant. For each case, the fetal phenotype and the organ system involved are described and the affected gene and variant, the inheritance mode, the associated syndrome and the outcome of the pregnancy are listed. AD: autosomal dominant; AR: autosomal recessive; hom: homozygous; IF: incidental finding; IUGR: intrauterine growth restriction; LB: live birth; mat: maternal; NT: nuchal translucency; pat: paternal; path: pathogenic; TOP: termination of pregnancy. Case No. Phenotype Phenotypic Group Gene Variant Inheritance Classification Associated Syndrome Outcome 1 Abnormal ears, bilateral talipes equinovarus skeletal KMT2D c.450G > A p.(Trp150*) AD-de novo path Kabuki syndrome 1 (OMIM# 147920) TOP 8 IUGR, oligodactyly left hand, hypoplastic ray right hand skeletal FANCG c.115C > T p.(Arg39*) AR-hom path Fanconi anemia, complementation group G (OMIM# 614082) TOP 10 Rhizomelic shortening and bowing of the long bones, microretrognathia and clenched hands skeletal COL2A1 c.2710C > T p.(Arg904Cys) AD-pat path Stickler syndrome type I (OMIM# 108300) LB 12 Edema, rocker bottom foot, retrognathia, abnormal thorax and ribs, increased NT multisystem CHRNA1 c.548A > G p.(Asp183Gly) AR-hom likely path Multiple pterygium syndrome, lethal type (OMIM# 253290) TOP 23 Hydrops, acites, hydrothorax hydrops RIT1 c.297T > A p.(Phe99Leu) AD-de novo path Noonan syndroom 8 (OMIM# 615355) TOP STXBP1 c.875G > A p.(Arg292His) AD-de novo path (IF) Developmental and epileptic encephalopathy type 4 (OMIM# 612164) 26 Olivopontocerebellar hypoplasia, tetralogy of Fallot, hypospadias multisystem THOC6 c.298T > A p.(Trp100Arg) AR-het (mat) path Beaulieu-Boycott-Innes syndrome (OMIM# 613680) TOP THOC6 c.700G > C p.(Val234Leu) AR-het (mat) path THOC6 c.824G > A p.(Gly275Asp) AR-het(mat) path THOC6 c.569G > A p.(Gly190Glu) AR-het (pat) path 28 Fetal akinesia, hypotonia, rocker-bottom feet, hydrops, hydrothorax, ascites multisystem MUSK c.2201G > T p.(Gly734Val) AR-hom likely path Fetal akinesia deformation sequence 1 (OMIM# 208150) TOP 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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PMC10000388 | Studying the relatively underexplored atypical MAP Kinase MAPK15 on cancer progression/patient outcomes and its potential transcriptional regulation of downstream genes would be highly valuable for the diagnosis, prognosis, and potential oncotherapy of malignant tumors such as lung adenocarcinoma (LUAD). Here, the expression of MAPK15 in LUAD was detected by immunohistochemistry and its correlation with clinical parameters such as lymph node metastasis and clinical stage was analyzed. The correlation between the prostaglandin E2 receptor EP3 subtype (EP3) and MAPK15 expression in LUAD tissues was examined, and the transcriptional regulation of EP3 and cell migration by MAPK15 in LUAD cell lines were studied using the luciferase reporter assay, immunoblot analysis, qRT-PCR, and transwell assay. We found that MAPK15 is highly expressed in LUAD with lymph node metastasis. In addition, EP3 is positively correlated with the expression of MAPK15 in LUAD tissues, and we confirmed that MAPK15 transcriptionally regulates the expression of EP3. Upon the knockdown of MAPK15, the expression of EP3 was down-regulated and the cell migration ability was decreased in vitro; similarly, the mesenteric metastasis ability of the MAPK15 knockdown cells was inhibited in in vivo animal experiments. Mechanistically, we demonstrate for the first time that MAPK15 interacts with NF-kB p50 and enters the nucleus, and NF-kB p50 binds to the EP3 promoter and transcriptionally regulates the expression of EP3. Taken together, we show that a novel atypical MAPK and NF-kB subunit interaction promotes LUAD cell migration through transcriptional regulation of EP3, and higher MAPK15 level is associated with lymph node metastasis in patients with LUAD. MAPK15 EP3 p50 LUAD metastasis National Natural Science Foundation of China31771582 31271445 31900468 Guangdong Natural Science Foundation of China2017A030313131 2019A1515011193 "Thousand, Hundred, and Ten" Project of the Department of Education of Guangdong Province of ChinaBasic and Applied Research Major Projects of Guangdong Province of China2017KZDXM035 2018KZDXM036 "Yang Fan" Project of Guangdong Province of ChinaShantou Medical Health Science and Technology Plan200624165260857 This work was supported by the grants from the National Natural Science Foundation of China (31271445, 31771582, and 31900468), the Guangdong Natural Science Foundation of China (2017A030313131 and 2019A1515011193), the "Thousand, Hundred, and Ten" Project of the Department of Education of Guangdong Province of China, the Basic and Applied Research Major Projects of Guangdong Province of China (2017KZDXM035 and 2018KZDXM036), the "Yang Fan" Project of Guangdong Province of China (Andy T. Y. Lau-2016 and Yan-Ming Xu-2015), and the Shantou Medical Health Science and Technology Plan (200624165260857). pmc1. Introduction The incidence of lung cancer is high among malignant tumors, which seriously affects human health. The mortality rate of lung cancer patients is high because lung cancer is usually in an advanced stage when diagnosed, with lymph node metastasis or even distant metastasis. Radiotherapy and chemotherapy have very limited therapeutic effects on advanced lung cancer. Targeted therapies, such as the use of targeted drugs EGFR tyrosine kinase inhibitors , can improve the survival of lung cancer patients to a certain extent, but they still face the problem of chemotherapy resistance, recurrence of targeted therapy, etc. Therefore, it is still not possible to effectively control the malignant development of lung cancer . The study of molecular markers related to lung cancer metastasis and their corresponding molecular mechanisms still needs to be further explored. The classical mitogen-activated protein kinases (MAPKs, e.g., ERK1/2, p38, and JNK/SAPK) play important roles in regulating gene expression, cell growth, proliferation, etc. Atypical MAPKs such as ERK3, ERK4, and NLK (nemo-like kinase) also play critical roles in many cellular responses . MAPK15, alias extracellular signal-regulated kinase 7/8 (ERK7/8), is the most recently discovered atypical MAPK. Current research indicates that MAPK15 can promote the transformation of colon cancer by mediating the activation of the transcription factor c-Jun or promoting the growth of gastric cancer cells . MAPK15 has also been found to interact with autophagy-related proteins such as GABARAP and LC3 to control tumor development . In addition, MAPK15 can be activated by carcinogenic factors such as RET/PTC3 or involved in the regulation of telomerase activity to participate in the development of tumors. Recently, our group has reported that MAPK15 can promote arsenic trioxide-induced apoptosis, as well as boosting the efficacy of combination therapy with cisplatin and TNF-a, in lung cancer cells . At present, research about the function of MAPK15 is still limited, and its role in lung cancer metastasis remains unclear. EP3 is one of the four G protein-coupled receptors of prostaglandin E2 (PGE2), which plays an important role in cell proliferation, differentiation, apoptosis, cardiovascular system regulation, and inflammation. It has been reported that tumor angiogenesis and tumor cell growth were significantly inhibited in a mouse lung cancer model with EP3 knocked out . Yamaki et al. found that PGE2 promotes the growth of lung adenocarcinoma (LUAD) cell line A549 via the EP3 receptor-activated Src signaling pathway . However, the molecular mechanism of EP3 in regulating lung cancer progression is still not fully clarified. In this study, we detected the expression of MAPK15 in lung cancer tissues, and found that the expression of MAPK15 is positively correlated with lymph node metastasis in LUAD patients; remarkably, our results showed that the expression of EP3 was transcriptionally regulated by MAPK15, and the expression of EP3 was positively correlated with the expression of MAPK15 in LUAD tissues. Furthermore, we revealed the first time that MAPK15 promotes the expression of EP3 by interacting with p50, thereby enhancing the migration of lung cancer cells. 2. Materials and Methods 2.1. Immunohistochemistry Lung cancer tissue microarray (BC041115c, US Biomax, Rockville, MD, USA) was purchased and all human tissues were collected according to HIPPA-approved protocols as described by US Biomax accessed on 14 June 2022). Immunohistochemistry was performed to detect the expression of MAPK15 and EP3. Briefly, tissue microarray was deparaffinized thrice in xylene (10 min for each) and rehydrated in gradient series ethanol (100%, 95%, 90%, 90%, 5 min for each), respectively. After being rinsed with water, tissue slides were incubated with 3% hydrogen peroxide for 40 min to block endogenous peroxidase. Tissue slides were then rinsed with PBS and immersed in 0.01 M citrate acid antigen retrieval solution and heated at 98 degC for 20 min using a water bath. After natural cooling, tissue slides were washed with PBS and incubated with 5% BSA for 30 min. Tissue slides were then incubated with MAPK15 or EP3 (Cat. 101760, Cayman Chemical, Ann Arbor, USA) antibody at 4 degC overnight. After being rinsed with PBS, tissue slides were incubated with secondary antibody for 45 min at RT. Subsequently, tissue slides were washed with PBS and reacted with 3,3'-diaminobenzidine (DAB, Zhongshan Golden Bridge Inc. Beijing, China) and counterstained with hematoxylin. Then, tissue slides were mounted with glycerogelatin and photographed with a light microscope. Immunostaining of tissue microarray were scored according to immunoreactive score (IRS) . Each tissue in the microarray was semiquantitatively scored for intensity (0, absent; 1, weak; 2, moderate; 3, strong) and extent of staining (percentage of the positive tumor cells: 0, <=5%; 1, 6-25%; 2, 26-50%; 3, 51-75%; 4, >75%). Intensity and extent of each tissue were multiplied to give a composite score: 0-3, deemed as low expression, "-"); 4-12, deemed as high expression (4-6, "+"; 7-9, "++"; 10-12, "+++"). 2.2. Cell Culture and Transfection All cells were grown at 37 degC in a 5% CO2 incubator. HEK293T, H1299, and A549 cells were purchased from ATCC Cell Bank of the Chinese Academy of Sciences (Shanghai, China) and maintained in MEM, RPMI-1640, or F12-K medium supplemented with 10% FBS and 1% PS, respectively. MAPK15 stable knockdown LUAD H1299 cells (H1299-shMAPK15) and control cells (H1299-shCtrl) were established previously . For transfection, cells were mixed with siRNA/plasmids-polyethylenimine mixture and cultured for the indicated time point. Negative control siRNA (siN05815122147) and siRNA duplexes against EP3 were purchased from IGE Biotechnology LTD (Guangzhou, China) and listed in Supplementary Table S1. 2.3. RNA Extraction, cDNA Synthesis, and Real-Time PCR RNA was extracted using RNAiso Plus (Takara, Dalian, China) from cells. Then, cDNA was synthesized using GoScriptTM Reverse Transcription Mix (Promega, Madison, WI, USA) by following the manufacturer's instructions. Specific primers were used, and real-time PCR was performed using GoTaq qPCR Master Mix (Promega, Madison, WI, USA) on Applied Biosystems 7500 Real-Time PCR System. The 2DDCT method was used to calculate the relative expression of target genes compared to internal control (b-Actin) as described previously . Primers were synthesized by IGE Biotechnology LTD (Guangzhou, China) and listed in supplementary Table S1. 2.4. Immunoblot Analysis Equivalent amounts of extracted protein were resolved by 10% SDS-PAGE and transferred onto polyvinylidene fluoride membranes. The membranes were blocked with 5% nonfat milk in PBS containing 0.05% Tween 20 followed by incubation with primary antibody overnight at 4 degC. After reacting with primary antibody, membranes were incubated with secondary antibody and proteins were visualized with ECL reagent using Tanon 5200 system (Tanon, Shanghai, China). The optical density of each protein band was quantified by Gel-Pro Analyzer 4 (Toyobo, Osaka, Japan) software. Original blots and blot quantification are shown in Figures S3-S5, S7 and S8. 2.5. Transwell Assay Transwell assay was performed as described previously . Briefly, 3.0 x 104 cells were seeded in the upper compartment of transwell inserts with 8 mm microporous membrane (cat no. 3422, Corning Inc., Corning, NY, USA). After being incubated for 24 h, unmigrated cells on the upper surface of the microporous membrane were wiped using a cotton swab. Cells on the lower surface of the microporous membrane were fixed with 4% PFA for 20 min and subsequently stained with 0.1% crystal violet for 15 min. The transwell chamber was rinsed with PBS to remove excess crystal violet, and images of migrated cells were captured using an Axiovert 40 CFL microscope (Carl Zeiss AG, Oberkochen, Germany) with CCD camera (magnified 100x). Finally, the crystal violet in the migrated cells was dissolved with 33% acetic acid, and absorbance was measured at OD595. 2.6. Immunofluorescence and Confocal Microscopy Cells seeded on coverslip in 6-well plate were incubated for the indicated time point and fixed with 4% PFA for 15 min. After being rinsed with PBS, cells were permeabilized for 10 min with PBS containing 0.25% Triton X-100. Subsequently, cells were incubated with 5% BSA for 30 min to block unspecific binding of antibodies. Then, cells were incubated with primary antibody in a humidified chamber at 4 degC overnight. After decanting of primary antibody solution, cells were washed with PBS and incubated with secondary antibody for 1.5 h at room temperature in the dark. Coverslips were counterstained with 1 mg/mL Hoechst 33342 and mounted with mounting medium. Images were captured with Axiovert 40 CFL Microscope (Carl Zeiss AG, Germany) or Zeiss lsm 800 confocal microscope (Carl Zeiss AG, Germany). 2.7. In Vivo Peritoneal Metastasis Assay In vivo peritoneal metastasis assay was performed as described previously . Briefly, 5 x 106 MAPK15 stable knockdown H1299 or control cells in 200 mL of phosphate-buffered saline were injected intraperitoneally into BALB/c nude mice (Beijing Vital River Animal Technology Co., Ltd., Beijing, China, licensed by Charles River). After 7 weeks, the mice were sacrificed, and tumor nodules were quantified. 2.8. Co-Immunoprecipitation HEK293T cells cultured in 10 cm dish were transfected with pcDNA4/Xpress-MAPK15 plasmids and incubated for 24 h. Prior to immunoprecipitation, 1 mg of Xpress antibody or normal IgG was pre-adsorbed with 20 mL Protein A/G Sepharose slurry for 2 h at 4 degC with rotation. After transfection, cells were harvested and lysed with NP-40 lysis buffer using repetitive freeze-thawing method. An amount of 300 mg of lysates to be used for immunoprecipitation was precleared with 20 mL Protein A/G Sepharose at 4 degC for 1 h with rotation. The supernatant was then incubated with the Xpress antibody-Protein A/G Sepharose complexes overnight at 4 degC with rotation (anti-mouse IgG was used as negative control). In total, 10% of the supernatant was used as input. The Sepharose beads were collected by centrifugation and washed extensively in 500 mL of lysis buffer, and eluted in 20 mL of SDS sample buffer by heating to 98 degC for 5 min. After centrifugation at 10,000x g, the supernatant was collected for immunoblot analysis. 2.9. Chromatin Immunoprecipitation Assay Chromatin immunoprecipitation assay was performed using SimpleChIP(r) Enzymatic Chromatin IP Kit (Cell Signaling Technology, Danvers, MA, USA). Briefly, formaldehyde cross-linked H1299 cells were lysed, and chromatin was digested with micrococcal nuclease into DNA/protein fragments. Then, p50 antibody (Santa Cruz Biotechnology, Dallas, TX, USA) was added and the complex is captured by protein G magnetic beads. Seven p50 binding sites (site1-site7) in the EP3 promoter region (-2000 bp) were predicted by JASPAR databases and PCR was used to detect p50 binding. 2.10. Vector Construction and Luciferase Reporter Assay Five repeats of p50 binding sequence (site5, sequence: GGGGCTTCCC) and 12 bp linker sequences with AflII and NsiI sites were synthesized by IGE Biotechnology LTD (Guangzhou, China) and ligated to a modified pJC6-GL3 plasmid to construct luciferase reporter plasmid (5 x p50-Luc). Then, the 5 x p50-Luc plasmid was co-transfected with/without pCMV-p50 plasmid into equal amount of H1299 cells in 12-well plate. Afterward, cells were lysed for luciferase assay following manufacturer's instructions (dual-luciferase reporter assay system, Promega, Madison, WI, USA). 2.11. Statistical Analysis Mean comparisons were performed using the GraphPad Prism 8 for unpaired t-test. Fisher's exact test was used to study the correlation between MAPK15 expression and clinical parameters. Spearman rank correlation analysis was used to compare the correlation between the expression of MAPK15 and EP3 in lung cancer tissues using SPSS 19 software. The above statistical analysis was two-tailed; p < 0.05 suggested that the difference was statistically significant. 3. Results 3.1. MAPK15 Is Correlated with Lymph Node Metastasis in LUAD Patients To study the role of MAPK15 in lung cancer, we analyzed the relationship between MAPK15 and clinical-pathological parameters such as age, gender, depth of tumor invasion, lymph node metastasis, distant metastasis, tumor differentiation, clinical stage, etc. We found that there was a positive correlation between MAPK15 expression and lymph node metastasis (p = 0.012) as well as clinical stage (p = 0.033) (Supplementary Table S2). The expression of MAPK15 is higher in patients with lymph node metastasis (N1 + N2) as compared to patients without lymph node metastasis (N0) (Supplementary Table S2). Other clinical-pathological parameters such as age, gender, depth of tumor invasion, distant metastasis, and tumor differentiation were not significantly correlated with the expression of MAPK15 (Supplementary Table S2). Adenocarcinoma and squamous cell carcinoma are major types of non-small-cell lung cancer (NSCLC). As compared to squamous cell carcinoma, we revealed that the expression of MAPK15 is relatively higher in adenocarcinoma and is associated with lymph node metastasis (p = 0.013) . 3.2. Knockdown of MAPK15 Inhibits H1299 Cell Migration In Vitro and Metastasis In Vivo The above results indicate that MAPK15 is expressed more highly in lymphatic metastatic LUAD. In MAPK15 stable knockdown LUAD H1299 cells , cell migration was significantly inhibited . The expression of Snail1 was decreased in MAPK15 knockdown cells , which can down-regulate the expression of E-cadherin by post-translational modifications such as deacetylation and methylation during EMT . Consequently, the expression of epithelial marker E-cadherin was increased, while mesenchymal marker integrin b1 is decreased after MAPK15 knockdown . Then, we performed an in vivo peritoneal metastasis assay using H1299-shMAPK15 cells and found that loss of MAPK15 significantly reduces metastasis to mesentery in vivo . The above results indicate that H1299 cells undergo mesenchymal-epithelial transition after MAPK15 knockdown, thereby decreasing migration and metastasis. 3.3. MAPK15 Regulates the Expression of Migration-Related Gene EP3 It has been reported that the expression of MMP2 was depressed in EP3 knock-out mice under hypoxic stress , which indicates a correlation between the expression of MMP2 and EP3. Our results showed that MMP2 was down-regulated in MAPK15 knockdown H1299 cells . To investigate whether EP3 is involved, we detect the expression of EP3 in H1299-shCtrl and H1299-shMAPK15 cells. We found that the mRNA and protein level of EP3 was significantly decreased in MAPK15-deficient cells and the protein level of EP3 was not affected by proteasome inhibitor MG132 , suggesting that the decreased EP3 in H1299-shMAPK15 cells was transcriptionally regulated. Moreover, the migration of H1299 cells was inhibited after EP3 was knocked down . The decreased EP3 in MAPK15 knockdown cells suggested that there might be a correlation between the expression patterns of these two molecules. Then, we detected the expression of EP3 in a serial section from the same tissue that we stained with MAPK15 antibody and found that the expression of EP3 is positively correlated with MAPK15 . Taken together, the above results show that MAPK15 affects cell migration through the regulation of EP3. 3.4. MAPK15 Interacts with NF-kB p50 Subunit and NF-kB p50 Transcriptionally Regulates EP3 Expression by Binding to EP3 Promoter The molecular mechanism of how EP3 is transcriptionally regulated by MAPK15 is unknown. It has been reported that the expression of MAPK15, NF-kB1 (p50), and NF-kB2 (p52) were obviously decreased in ovarian cancer cell lines , which indicate there are correlations between MAPK15 and the NF-kB family. To investigate the relationship between MAPK15 and NF-kB family members, we transfected the pcDNA4/Xpress-MAPK15 plasmid into 293T cells and the immunoprecipitation assay revealed that MAPK15 interacts with p50 but not p65 and c-rel . We also detected the localization of MAPK15 and p50 in H1299 cells by confocal microscopy and found that MAPK15 is distributed both in the cytoplasm and nucleus, and colocalizes with p50 , indicating that there is an interaction between these two proteins in LUAD cells which might contribute to the expression of EP3. To study the relationship between MAPK15/p50 and EP3, we overexpressed MAPK15 and p50 in H1299 cells and found that the expression of EP3 was increased , which indicates that MAPK15 and p50 positively regulate the transcription of EP3. The chromatin immunoprecipitation assay found that p50 binds to two p50 binding motifs in the EP3 promoter . Subsequently, we chose site 5 to construct the luciferase reporter plasmid and co-transfect with/without pCMV-p50 in H1299 cells for the luciferase reporter assay. Our results indicate that the luciferase activity is significantly increased in cells overexpressed with p50 , which revealed that p50 can transcriptionally regulate EP3 by binding to the EP3 promoter. 3.5. TNF-a Promotes H1299 Cell Migration through Induction of MAPK15-NF-kB p50 Nuclear Localization and EP3 Expression MAPK15 interacts with p50 intracellularly, indicating potential gene regulation and cellular phenotypic change. Beinke et al. reported that the p105 pathway can positively regulate gene transcription under TNF-a stimulation . We hypothesize that TNF-a might promote the expression of EP3 through the p50 pathway, thereby contributing to cell migration. In TNF-a-treated H1299 cells, we found that TNF-a promoted EP3 expression in a dose- and time-dependent manner . Furthermore, TNF-a promoted the migration of H1299 cells but had no significant effect on the migration of MAPK15 knockdown cells . This result suggests that TNF-a promotes cell migration through MAPK15. In TNF-a-treated A549 cells, we found that TNF-a promotes nuclear localization of MAPK15 and p50 . In H1299 cells, we found that p50 is distributed in both cytoplasm and nucleus, whereas in MAPK15 knockdown cells, p50 is mainly located in the cytoplasm , indicating that nuclear localization of p50 is dependent on MAPK15. At the same time, we treated H1299 cells with TNF-a and found that p50 is mainly located in the nucleus, whereas in MAPK15 knockdown cells, p50 is distributed in both the cytoplasm (white arrows) and the nucleus . The above results indicate that TNF-a-induced nuclear translocation of p50 is dependent on MAPK15. In addition, we found that the expression of EP3 in TNF-a-treated H1299 cells was increased, while the expression changes of EP3 in MAPK15 knockdown H1299 cells were not significant , and TNF-a could not promote H1299 cell migration while EP3 was knocked down . Taken together, these results reveal that TNF-a promotes H1299 cell migration through induction of MAPK15-p50 nuclear localization and EP3 expression in cells with MAPK15 expression. 3.6. JSH-23 Inhibits MAPK15-Induced EP3 Expression and Cell Migration JSH-23 is an NF-kB inhibitor. When using JSH-23 to treat H1299 cells, we found that JSH-23 inhibited the expression of EP3 in a dose- and time-dependent manner . Furthermore, JSH-23 inhibited the migration of H1299 cells but had no significant effect on the migration of knockdown MAPK15 cells . This result suggests that JSH-23 inhibits cell migration through MAPK15. In addition, we found that the expression of EP3 in H1299 cells treated with JSH-23 was decreased, while the expression of EP3 in MAPK15 knockdown H1299 cells did not change significantly , and JSH-23 could not inhibit H1299 cell migration when EP3 was knocked down . The above results indicate that JSH-23 inhibits cell migration by inhibiting MAPK15-induced EP3 expression. 4. Discussion Lung cancer is usually at an advanced stage with lymph node or distant metastasis when diagnosed, which leads to high mortality. Medical knowledge still lacks effective diagnostic molecular markers for metastatic lung cancer. In the present study, we revealed that MAPK15 is more highly expressed in the tissues of LUAD patients with lymph node metastasis , and MAPK15 interacts with p50 to promote EP3 expression at the transcriptional level , thereby enhancing cancer cell migration and metastasis. MAPK15 is a member of the ERK subfamily, which is involved in the regulation of cell growth and differentiation like other well-known ERKs. Previous research indicates that MAPK15 is involved in the transformation of colon cancer , promotes gastric cancer cell proliferation , and is associated with autophagy . However, its clinical pathological role has, until now, not been examined in lung cancer. The correlation between MAPK15 and lymph node metastasis in LUAD described here suggests that MAPK15 plays an important role in lung cancer development, which may lead to poor clinical outcomes. Since we used a commercialized lung cancer tissue array in this study, there is a lack of relevant information on disease progression, so it is impossible to conduct a longitudinal assessment of the relationship between MAPK15 expression and patients' disease-free survival/overall survival, recurrence, metastasis, etc. However, with the in-depth study of MAPK15, we gradually realized its important role in LUAD. In future studies, multicenter, larger-sample-size studies should be conducted through longitudinal assessment of the patients' critical long-term clinical outcome to further clarify MAPK15 expression and the significance of clinical parameters. Due to the significant correlation between MAPK15 and the clinical features of the LUAD patients we observed, MAPK15 and its signaling pathway in LUAD may be a potential therapeutic target for metastatic LUAD. As a kinase, MAPK15 carries out different functions in various cancers, indicating the deregulation of key pathways. Studies have indicated a pivotal role of MAPK15 in mediating the effect of gene transcription. We have previously shown that MAPK15 promotes the transformation of colon cancer by mediating the activation of c-Jun . Here, the identification of MAPK15 as an upstream regulator for EP3 unveiled a previously unknown mechanism for the MAPK15 or EP3 signaling pathway and their roles in the regulation of cell migration in LUAD. The role of EP3 in tumor progression is still controversial. It has been reported that EP3 coupled with G proteins can effectively inhibit tumor growth. Shoji et al. found that EP3 can significantly inhibit the proliferation of tumor cells in advanced-stage colon cancer . Sanchez et al. found that EP3 can promote the expression of p21 by reducing cAMP, thereby arresting the cell cycle in the S phase, and ultimately inhibiting the proliferation of 3T6 fibroblasts . On the other hand, there are more and more studies showing that EP3 can promote the development of tumors. Finetti et al. found that EP3 is involved in regulating the formation of tumor blood vessels . Amano et al. found that in an EP3-deficient mouse tumor model, tumor angiogenesis and tumor cell growth were effectively inhibited . Yamaki et al. found that EP3 participates in the Src signaling pathway to promote the growth of LUAD A549 cells . In this study, we reveal that knocking down EP3 can inhibit the migration of LUAD cells and that the expression of EP3 was positively regulated by MAPK15, which expands our understanding of EP3 and its regulation in lung cancer. NF-kB is a type of transcription factor that plays an important role in the occurrence and development of tumors. The ERK family was linked to the NF-kB pathway . As the most recently discovered MAPK family member, the relation between MAPK15 and NF-kB is mainly uncharacterized. Previous studies on the NF-kB protein family mainly focused on the activity of IkB or p65 in the p50/p65 complex to promote gene transcription. However, more and more studies have shown that p50 can bind to the promoter of the gene and activate gene transcription. The study of Hong et al. showed that overexpression of p50 in BAR-T cells significantly enhanced the activity of the DNMT1 gene promoter . Karst et al. showed that overexpression of NF-kB p50 in melanoma cells MMRU can promote angiogenesis and up-regulate IL6 expression. They confirmed by Chip assay that p50 can bind to the promoter region of IL6 gene and activate its transcription . Similarly, Southern et al. found that the BAG-1 protein can interact with the p50-p50 homodimer and bind to the promoter region of downstream genes to play a positive role in regulating gene transcription . Beinke et al. reviewed that TNF-a/IL-1/LPS can activate the classic p50/p65 dimer NF-kB signaling pathway and the p100/RelB non-canonical signaling pathway, as well as the p105/p50 signaling pathway . In this study, we found that MAPK15 interacts with p50 in LUAD cells, and the nuclear translocation of p50 may require the assistance of MAPK15. In addition, we also found that the mRNA expression level of EP3 increased when p50 was overexpressed in H1299 cells, indicating that p50 can regulate the expression of EP3 at the transcriptional level, and CHIP assay and luciferase reporter assay confirmed that p50 can bind to the promoter region of EP3 and promote the transcription of EP3. Our results revealed that MAPK15 interacts with p50 to promote the transcription of EP3, thereby affecting biological functions such as the migration of LUAD cells. 5. Conclusions In conclusion, this study demonstrates the role of MAPK15 in the metastasis of LUAD. We revealed that MAPK15 promotes LUAD cell migration via p50 and EP3 signaling and is associated with lymph node metastasis in LUAD patients, which indicates that MAPK15 might be a potential prognostic biomarker for LUAD and a therapeutic target to inhibit metastasis in metastatic LUAD patients. The insights provided by this study could facilitate understanding the role of MAPK15 in lung cancer progression and its potential modulatory role in cancer metastasis. Acknowledgments We would like to thank members of the Lau And Xu laboratory for critical reading of this manuscript. Supplementary Materials The following supporting information can be downloaded at: Table S1: Primer and siRNA used in this study; Table S2: Correlation between MAPK15 expression and clinicopathological parameters in patients with lung cancer; Table S3: Correlation between MAPK15 expression and tissue types; Figure S1: Matrix metalloproteinase-2 (MMP2) was significantly decreased in MAPK15 knockdown H1299 cells; Figure S2: Localization of MAPK15 and p50 in TNF-a treated A549 cells; Figure S3: Original blots and blot quantification of Figure 1; Figure S4: Original blots and blot quantification of Figure 2; Figure S5: Original blots and blot quantification of Figure 3; Figure S6: Original gels and gel quantification of Figure 3; Figure S7: Original blots and blot quantification of Figure 4; Figure S8: Original blots and blot quantification of Figure 5. Click here for additional data file. Author Contributions F.-Y.Y.: conceptualization, methodology, validation, formal analysis, investigation, data curation, writing--original draft preparation, funding acquisition. Q.X.: validation, investigation, data curation. X.-Y.Z.: validation, investigation, data curation. H.-Y.M.: validation, investigation, data curation. Q.-H.Z.: validation, investigation, data curation. L.L.: validation, data curation. A.T.Y.L.: conceptualization, methodology, formal analysis, investigation, resources, writing--original draft preparation, writing--review and editing, supervision, project administration, funding acquisition. Y.-M.X.: conceptualization, methodology, formal analysis, investigation, resources, writing--original draft preparation, writing--review and editing, supervision, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The animal experiment in this study was approved by the Animal Ethics Committee of Shantou University Medical College (No. SUMC2021-042). The lung cancer tissue microarray was purchased from US Biomax Inc, Rockville, MD, USA. 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 Knockdown of MAPK15 inhibits H1299 cell migration in vitro and in vivo. (A) MAPK15 staining in lung squamous cell lung carcinoma and adenocarcinoma tissues. (B) MAPK15 staining in LUAD tissues without lymph node involvement (N0) was compared with tissue with lymph node involvement (N1). Scale bar represents 60 mm. (C,D), real-time PCR and immunoblot analysis were used to detect the mRNA level (C) and protein level (D) of MAPK15 in H1299 cells. (E,F), transwell assay was used to detect the migration ability of H1299-shCtrl and H1299-shMAPK15 cells, migrated cells were stained with crystal violet (E) and absorbance of solubilized crystal violet was shown as bar chart graph (F). (G) The expression of Snail1/E-cadherin/Integrin-b1 was detected in H1299-shCtrl and H1299-shMAPK15 cells. (H) Metastatic nodules (red arrows) on intestinal mesentery of BALB/c nude mice. (I) Number of mesenteric metastasis nodules per mouse. * p < 0.05, ** p < 0.01, *** p < 0.001, Student's t-test. Figure 2 MAPK15 regulates the expression of migration-related gene EP3. (A) The expression of EP3 mRNA was detected in H1299-shctrl and H1299-shMAPK15 cells by real-time PCR. (B) H1299-shCtrl and H1299-shMAPK15 cells were treated with/without 10 mmol/L MG132 for 4 h, then the expression of EP3 was detected by immunoblot analysis. (C-E) An amount of 40 mmol/L of negative control siRNA and EP3 siRNA were transfected into H1299 cells, respectively, for 36 h and the expression of MAPK15/EP3 were detected. (F,G) H1299 cells transfected with negative control siRNA and EP3 siRNA for 36 h were seeded in transwell chamber for 24 h, then migrated cells were stained with crystal violet (F) and absorbance of solubilized crystal violet are shown as bar chart graph (G). (H) Serial section of the same LUAD tissue shows the similar expression pattern of MAPK15 and EP3. Scale bar represents 60 mm. * p < 0.05, *** p < 0.001, Student t test. Figure 3 MAPK15 interacts with NF-kB p50 and p50 promotes EP3 expression by binding to EP3 promoter. (A) Immunoprecipitated proteins were resolved and the presence of MAPK15 and p50/c-rel/p65 were detected by anti-Xpress or anti-p50/c-rel/p65 antibodies. (B) The localization of MAPK15 and p50 in 4% paraformaldehyde-fixed H1299 cells were detected. (C-E) H1299 cells transfected with 2 mg pcDNA4, pcDNA4/Xpress-MAPK15, pCMV, and pCMV-p50 and the expression of MAPK15 (C)/p50 (D)/EP3 (E) was detected by real-time PCR. (F) Chromatin immunoprecipitation assay was used to detect the binding of p50 to EP3 promoter region; the asterisk indicates the immunoprecipitated EP3 promoter region. Original gels and gel quantification are shown in Figure S6. (G) In this study, 5 x p50-Luc plasmid was transfected with/without pCMV-p50 in H1299 cells and luciferase reporter assay was performed to detect the luciferase activity. * p < 0.05, ** p < 0.01, *** p < 0.001, Student's t-test. Figure 4 TNF-a promotes H1299 cell migration through induction of EP3 expression. (A) EP3 was detected in H1299 cells treated with different concentrations of TNF-a. (B) EP3 was detected in H1299 cells treated with 20 ng/mL TNF-a for different time points. (C,D) Transwell assay was used to detect migration effect of H1299-shCtrl and H1299-shMAPK15 cells with/without TNF-a treatment (20 ng/mL, 24 h), crystal violet in the migrated cells (C) was dissolved and absorbance was measured at OD595 (D). (E) H1299 cells cultured in serum-reduced medium (1% FBS) were stimulated with 20 ng/mL TNF-a for 1 h and p50 localization was detected in H1299 cells; scale bar represents 80 mm. (F) H1299-shCtrl and H1299-shMAPK15 cells cultured in serum-reduced medium (1% FBS) were treated with/without 20 ng/mL TNF-a for 12 h and the expression of EP3 was detected. (G,H) H1299 cells transfected with control siRNA or EP3 siRNA were resuspended in serum-reduced medium (1% FBS) and seeded to transwell chamber with/without 20 ng/mL TNF-a. Crystal violet in the migrated cells (G) was dissolved and absorbance was measured at OD595 (H). NS, non-significant; * p < 0.05, Student's t-test. Figure 5 JSH-23 inhibits MAPK15-induced EP3 expression and cell migration. (A,B) H1299 cells were treated with/without different doses of JSH-23 for 12 h (A) or with 30 mM JSH-23 for different time points (B). The expression of EP3 was detected by immunoblot analysis. (C,D) H1299-shCtrl and H1299-shMAPK15 cells were resuspended in serum-reduced medium (1% FBS) and seeded to transwell chamber with/without 30 mM JSH-23, crystal violet in the migrated cells (C) was dissolved and absorbance was measured at OD595 (D). (E) H1299-shCtrl and H1299-shMAPK15 cells cultured in serum-reduced medium (1% FBS) were treated with/without 30 mM JSH-23 for 12 h and the expression of EP3 was detected. (F,G) H1299 cells transfected with control siRNA or EP3 siRNA were resuspended in serum-reduced medium (1% FBS) and seeded to transwell chamber with/without 30 mM JSH-23 for 24 h, crystal violet in the migrated cells (F) was dissolved and absorbance was measured at OD595 (G). NS, non-significant; * p < 0.05, ** p < 0.01, Student's t-test. Figure 6 Schematic diagram of MAPK15 transcriptionally regulating EP3 by interacting with NF-kB p50 subunit and promoting LUAD metastasis. Question mark (?) indicates that how TNF-a affects MAPK15 in the cytosol is still unclear. cancers-15-01398-t001_Table 1 Table 1 Correlation between MAPK15 expression and clinical parameters in patients with LUAD and LUSC. Adenocarcinoma Squamous Cell Carcinoma Clinicopathological Parameters MAPK15 Expression Total p Value MAPK15 Expression Total p Value Low High Low High Regional lymph nodes 0.013 * 0.486 N0 10 13 23 13 8 21 N1 2 18 20 5 7 12 N2 3 2 5 3 4 7 Fisher's exact test. Statistically significant, * p < 0.05. cancers-15-01398-t002_Table 2 Table 2 Correlation between EP3 expression and MAPK15 in LUAD tissues. EP3 Total - + ++ +++ MAPK15 - 10 5 0 0 15 + 3 12 1 0 16 ++ 0 5 1 1 7 +++ 2 2 3 3 10 Total 15 24 5 4 48 Spearman correlation, r = 0.589, p < 0.001. 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PMC10000389 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050814 cells-12-00814 Editorial Large-Scale Multi-Omic Approaches and Atlas-Based Profiling for Cellular, Molecular, and Functional Specificity, Heterogeneity, and Diversity in the Endocannabinoid System Aoki Jun 12 Isokawa Masako 3* 1 Graduate School of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan 2 Laboratory for Cell Signaling Dynamics, Center for Biosystems Dynamics Research, RIKEN, Kobe 650-0047, Japan 3 Forefront Research Center, Graduate School of Science, Osaka University, Osaka 560-0043, Japan * Correspondence: [email protected] 06 3 2023 3 2023 12 5 81428 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 ). pmcThe endocannabinoid system (ECS) is a widely-recognized lipid messenger system involved in many aspects of our our lives in health and diseases. The system consists of cannabinoid receptors, their endogenous ligands, and the enzymes that mediate their synthesis and metabolic processes. Research progress was recently reviewed regarding (i) the pharmacology of the ECS, (ii) the roles of ECSs in development and synaptic function, (iii) cannabinoid signaling in pathological conditions, and (iv) cell-type-specific and localization-dependent operations of cannabinoid receptors . Of particular interest may be the conceptual framework where biomedical consequences influenced by ECS are not necessarily monotheistic; instead, there exists cellular, molecular, and functional specificity, heterogeneity, and diversity in (endo)cannabinoid action. This Special Issue aims to discuss the multiplexity of endocannabinoid signaling mechanisms and functions considering large-scale multi-omic approaches and the way data are visualized for presentation. It is well accepted that lipidomic , transcriptomic , proteomic , or any combination of these data mining strategies and atlas-based data profiling methods helped identify the involvement of critical molecules throughout our lives. Methodological orientation provided typical standards for non-parametric dimensionality reduction, data visualization, and cluster analysis that ranged from traditional principal component analysis (PCA) to the currently popular uniform manifold approximation and projection (UMAP) method. Some researchers may feel that these approaches are still young and relatively underexplored in endocannabinoid research; however, fruitful applications have already emerged in the investigation of ligands, receptors, and related enzymes. The first example concerns the role of ECSs in the transition of retinal Muller glia (MG) into proliferating progenitor-like cells in health and diseases . Using single-cell RNA sequencing (scRNA-seq) libraries, the patterns and levels of eCB-related gene expressions across different retinal cells were presented with two-dimensional profiling methods, such as UMAP and violin plots. UMAP-ordered cells formed distinct clusters of neuronal cells, resting MG, and activated MG. The expression levels in Cnr1, MGLl, DAGLa, DAGLb, and FAAH were demonstrated using heatmaps, and the cell-type specificity was shown by violin plots. Furthermore, the involvement of fatty-acid-binding proteins and fatty acid synthase was shown in the formation of Muller-glia-derived progenitor cells (MGPCs) after NMDA-induced damage. UMAP analysis illustrated aggregates of damages and the formation of distinct MGPC clusters according to the expression of GLUL, RLBP1, and SLC1A3, or NESTIN, CDK1, and TOP2A. Heatmaps and violin plots showed patterns and levels of FABP5, FABP7, and PMP2. These reports strived for a fuller understanding of the contribution of ECSs and fatty acid signaling in the reactivity and dedifferentiation of Muller glia, as well as the proliferation of microglia and MGPCs. The second example is about the involvement of cannabinoid receptor type 1 (CB1R/Cnr1) and type 2 (CB2R/Cnr2) in nonalcoholic fatty liver disease (NAFLD) and melanoma , respectively. scRNA-seq and UMAP highlighted six clusters of transcriptomic data in main liver cells, and violin plots depicted the hepatocyte-zone-specific gene expression. In melanoma, UMAP dimensionality reduction processed 6381 B-cells and mapped the top 10 upregulated genes (highest-fold change). Although the deletion of Cnr1 (CB1R KO mice) was expected to prevent the development of NAFLD, scRNA-seq and UMAP analysis did not support the hypothesis, showing that Cnr1-/- mice failed to protect the liver from fibrosis. In melanoma, UMAP analysis portrayed a positive correlation between the upregulation of intra-tumoral CB2R gene expression and improved overall survival, as well as a reduction in the metabolic activity of tumor-infiltrating B cells in Cnr2-/- mice. Anandamide synthesis was targeted by global transcriptomic analysis in the partial hepatectomy (PHX) model . The result illuminated the up-regulation of cell-cycle proteins, such as cyclin-dependent kinase 1 (Cdk1), cyclin B2, and their transcriptional regulator forkhead box protein M1 (FoxM1), and provided molecular and genetic support to the pathophysiological observation that PHX increased biosynthesis of anandamide in the liver via conjugation of arachidonic acid and ethanolamine by fatty acid amide hydrolase. Last but not least, it may be worth mentioning that in pharmaceutical sciences, dimensionality reduction and cluster analyses, such as t-distributed stochastic neighbor embedding (t-SNE) and UMAP, have been frequently used on large-scale samples of cannabis sativa chemotypes for the purpose of modeling cannabinoids . Here, a dataset of 17,600 commercial cultivars was screened for unknown gene regulation and pharmacokinetics of dozens of cannabinoids. The concentration of tetrahydrocannabinol (THC) scattered against the concentration of cannabidiol (CBD) was plotted to segregate low-CBD and -THC cultivars. These approaches not only helped reveal complex interactions in cannabinoid biosynthesis but also advanced the phenotypical classification of cannabis cultivars. We introduced scRNA-seq, t-SNE, UMAP, heatmaps, and violin plots as examples among the popular methodological tools for data generation and analysis. scRNA-seq provides a way of comprehensively defining gene expression and identifying molecular trajectories by connecting transcriptomes. However, the reconstruction of molecular lineages from gene-expression cascades to cell-type-specific markers and regulators is still a major challenge. t-SNE, UMAP, heatmaps, dendrograms, and violin plots are the techniques in data science that reduce the dimensionality of raw data and visualize the outcomes in a pictorial format. They are routinely applied in a broad range of fields, including life sciences, where datasets of increasing sizes are handled. While these techniques have been used liberally in combination with transcriptomics and proteomics, less usage has been acknowledged in the detection of molecules that cannot be labeled with antibodies and/or genetic manipulation. Further applications are encouraged with all-inclusive measurement technologies such as imaging mass spectrometry in cells and organisms, as it can directly detect and visualize the identified and unidentified lipids and metabolites that often play key roles in the eCB system. We hope you will find the collection of papers in this Special Issue interesting and helpful for expanding methodological choices in the event of mining, summarizing, and presenting new ideas and perspectives for future eCB research. 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. Busquets-Garcia A. Melis M. 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PMC10000390 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050677 cells-12-00677 Review Modelling Cancer Metastasis in Drosophila melanogaster Sharpe Joanne L. 1 Morgan Jason 1+ Nisbet Nicholas 1+ Campbell Kyra 1* Casali Andreu 2* Gonzalez Cayetano Academic Editor 1 School of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK 2 Departament de Ciencies Mediques Basiques, Universitat de Lleida and IRBLleida, Av. Alcalde Rovira Roure, 80, 25198 Lleida, Spain * Correspondence: [email protected] (K.C.); [email protected] (A.C.) + These authors contributed equally to this work. 21 2 2023 3 2023 12 5 67727 1 2023 14 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 ). Cancer metastasis, the process by which tumour cells spread throughout the body and form secondary tumours at distant sites, is the leading cause of cancer-related deaths. The metastatic cascade is a highly complex process encompassing initial dissemination from the primary tumour, travel through the blood stream or lymphatic system, and the colonisation of distant organs. However, the factors enabling cells to survive this stressful process and adapt to new microenvironments are not fully characterised. Drosophila have proven a powerful system in which to study this process, despite important caveats such as their open circulatory system and lack of adaptive immune system. Historically, larvae have been used to model cancer due to the presence of pools of proliferating cells in which tumours can be induced, and transplanting these larval tumours into adult hosts has enabled tumour growth to be monitored over longer periods. More recently, thanks largely to the discovery that there are stem cells in the adult midgut, adult models have been developed. We focus this review on the development of different Drosophila models of metastasis and how they have contributed to our understanding of important factors determining metastatic potential, including signalling pathways, the immune system and the microenvironment. Drosophila cancer metastasis larva adult Wellcome Trust204615/Z/16/Z National Centre for the Replacement, Refinement and Reduction of Animals in ResearchNC/W001136/1 Spanish Ministry of Science and InnovationPID2019-1946GB-100 This work was funded by the Wellcome Trust (K.C., Grant number 204615/Z/16/Z), the National Centre for the Replacement, Refinement and Reduction of Animals in Research (J.L.S. and J.M., Grant number NC/W001136/1) and the Spanish Ministry of Science and Innovation (A.C., Grant number PID2019-1946GB-100). AC is a Serra Hunter fellow. pmc1. Introduction Drosophila melanogaster (Drosophila) have been widely used to study the molecular and genetic underpinnings of human cancer . Historically, Drosophila research has helped to identify the mechanisms of action of many pathways that play a key role in cancer, including BMP, Hedgehog, Hippo, JAK/STAT, Notch, Ras, TGFb and Wnt. The development of new techniques such as MARCM , which makes it possible to generate homozygous clones of mutations in an animal that is otherwise heterozygous for the same mutation , enabled the generation of new models that mimic the loss of heterozygosity observed in the somatic cells of cancer patients. Since then, many multi-hit models of cancer have been described and used to study different aspects of the disease, for instance, the association between cancer and obesity , tumour-host interactions , genomic instability , inflammation and immunity and cancer cachexia . Since many aspects of Drosophila as a model for cancer and human diseases have been extensively and nicely reviewed elsewhere , we will focus this review on the use of Drosophila as a model for cancer metastasis. 2. Cancer Metastasis Tumour metastasis is a complex multistage process during which malignant cells spread from a primary tumour and proliferate, forming secondary tumours at distant sites . From the cells that are released from a tumour, only a small proportion form a distant secondary tumour. This is because very few cells are able to accumulate the phenotypic traits, akin to stem cells or regenerative stem cells, that are required to survive the stress related to the processes of cell dissemination, adaptation to a distant niche and grow . Metastasis starts when tumour cells are able to leave the primary tumour and disseminate to distant organs . A key event in promoting this initial step is the transition of epithelial tumour cells towards a more mesenchymal cell state through an epithelial-to-mesenchymal transition (EMT), with the consequent disruption of cellular adhesions, loss of apical-basal polarity and drastic remodelling of the cytoskeleton. The acquisition of mesenchymal characteristics increases migratory capacity, invasiveness and resistance to apoptosis . These changes allow tumour cells to migrate through the extracellular matrix and enter blood vessels, becoming circulating tumour cells (CTCs). CTCs may travel alone or in clusters before becoming trapped in the capillaries of distant organs seconds to minutes after leaving the primary tumour. From there, they pass through the capillary endothelium to the parenchyma of organs . Alternatively, metastatic cells may disseminate through lymphatic vessels and, in some tumours, through routes that do not require entry into the circulation . Once tumour cells have infiltrated distant organs, many are eliminated by lack of an appropriate microenvironment, together with the defensive activities of resident immune cells. However, a few malignant cells may enter a proliferative quiescence, known as the dormancy phase, that protects them from being eliminated. These cells may remain dormant for years, likely controlled by a balance between mitogenic and anti-mitogenic signals; when this balance is broken, the cells enter into the colonisation phase, outgrowing and forming an overt metastatic secondary tumour . Each phase of metastasis reflects the capacity of metastatic cells to evade immunity and to dynamically adapt to new microenvironments through a high phenotypic plasticity. However, the factors driving the dynamic cellular transitions of tumour cells that allow them progress through the different stages of metastasis are largely unknown. Moreover, genomic and transcriptomic studies have led to new insights into the intratumour heterogeneity of primary tumours and how this increases as metastatic cells evolve under the pressure of somatic mutations and clonal selection . To better understand the complex processes driving metastasis, which currently is the leading cause of cancer-related deaths, research heavily relies on in vivo experimental models. The most widely used organism to model metastasis is mice, in which transplantation experiments and genetically engineered mouse models have provided very useful insights . However, despite important caveats such as an open circulatory system and the lack of adaptative immunity, non-mammalian model organisms such as Drosophila have also proven very useful to understand the complex choreography of gene expression driving cell plasticity of tumour cells and their adaptation to new microenvironments, thanks to their amenability to complex genetic manipulations and experimental tractability. Here we will discuss the different ways Drosophila have been used to either study distinct stages of metastasis, or the entire process from primary tumour initiation to growth of secondary metastasis. 3. Modelling Metastasis in Drosophila Larvae Generally, tumour cells arise from mutations in cells that undergo mitosis. Therefore, the capacity for neoplastic transformation depends primarily on the ability of the cells to divide. This makes the larval stages of Drosophila development fruitful ground for modelling cancer, as a number of cells and tissues undergo large bursts of proliferation: the imaginal disc cells; the adult optic neuroblasts and ganglion cells in the larval brain; the blood cells; the cells in the gonads; and other smaller cell nests within different organs . It is, therefore, not so surprising that the first invasive tumours were discovered arising from the larval imaginal discs--these resulted from mutagenesis screens in the 1930s--which led to the discovery of the first Drosophila cancer genes . The epithelial imaginal discs subsequently spawned a wealth of studies on the genetic control of epithelial organisation and its relation to invasive outgrowth. Around 80% of cancers are derived from epithelial tissues, and loss of tissue integrity features prominently in the progression of an epithelial tumour from benign to metastatic . Owing to their accessibility and genetic tractability, the imaginal discs have become popular models for studying how changes to epithelial architecture link to the initiation of metastatic dissemination. The first cancer genes discovered in Drosophila were found to organise epithelial polarity and differentiation . Notably, larvae with recessive mutations in Lethal Giant Larvae (lgl)--a polarity regulator--develop sizeable neuroblastomas in the optic centre of the midbrain with evident invasion into the neuropile and an observed two-fold enlargement of the brain hemispheres . lgl mutant neuroblasts of the eye disc fail to differentiate into ganglion mother cells (GMCs) and therefore do not enter a post-mitotic state, resulting in excess proliferation. Similar outcomes can be observed following recessive mutations to the polarity regulator Discs Large (dlg), as well as Brain Tumour (brat), and Malignant Brain Tumour (mbt), which are both GMC differentiation determinants . These models recapitulate the loss of polarity, cell adhesion and resultant failure to segregate differentiation determinants that strongly correlate with metastatic progression in human epithelial tumours. Although lgl, dlg, brat and mbt mutations can invoke invasion from the eye disc into surrounding neural tissue, none have been observed to drive colonisation of distant organs within larvae . Their metastatic capacity was later demonstrated by transplant assays--which we will discuss later. Focusing more specifically on metastatic dissemination, Pagliarini et al. designed a genetic screen in larvae to identify mutations in genes that enable tumour cells of the eye imaginal disc to colonise distant sites . Upregulation of RasV12 under the eye-disc-specific promoter Eyeless causes the formation of non-invasive tumours. RasV12 was overexpressed in clones of eye imaginal disc cells in combination with recessive mutations in candidate genes to identify mutations that cooperate with constitutively activated Ras to drive colonisation to distant tissues. Using this approach, they found that the cooperation of RasV12 with the loss of the polarity factor scribble (scrib) (RasV12; scrib) was sufficient to cause degradation of the basement membrane, transcriptional downregulation of the E-Cadherin gene shotgun and invasion into the ventral nerve chord (VNC) and haemolymph, as well as the formation of secondary foci at distant tissues . The combination of RasV12 with mutations in the polarity regulators lgl, dlg, stardust (sdt), bazooka (baz) and cdc42 also produced similar metastatic behaviours. Importantly, although combining RasV12 with mutations in genes required for apicobasal polarity led to metastasis, mutations in genes required for apicobasal polarity alone resulted in loss of polarity and tumour outgrowth but no metastasis, as cells underwent apoptosis . Collectively, these findings support a mechanism whereby loss of tissue architecture--particularly as it relates to a loss of epithelial polarity and differentiation-- is a core attribute acquired by cancer cells in realising their metastatic potential. Nonetheless, it is insufficient to drive the process as epithelia appear to recognise that their integrity is compromised and undergo programmed cell death, potentially as an inbuilt tumour suppressor mechanism to prevent the outgrowth of malignant cells. The fact that the addition of RasV12 can overcome this has set the stage for a series of subsequent investigations into how oncogenes and tumour suppressor genes conspire together to enable metastatic behaviours that they otherwise would not be capable of executing alone. It was later discovered that loss of polarity in scrib clones of the eye disc results in apoptosis through c-Jun N-terminal kinase (JNK)-mediated stress signalling . Suppressing JNK-mediated apoptosis by expressing the anti-apoptotic baculovirus protein P35 was capable of enabling the metastasis of eye disc tumours . Paradoxically, JNK signalling has also been found to be responsible for the invasive features in scrib clones. Indeed, the expression of a dominant negative, non-activatable form of JNK is capable of preventing metastases in RasV12; scrib mutant imaginal discs . A later study discovered that JNK acts mechanistically by upregulating Matrix Metalloproteinase 1 (MMP1) through the transcriptional action of Drosophila Fos (dFos or Kayak). When Mmp1 is silenced by RNAi or antagonised with Tissue Inhibitor of Metalloproteases (TIMP), no basement membrane degradation or subsequent metastasis is observed . These findings suggest that RasV12 contributes to metastasis by defusing the apoptotic circuitry of JNK, while leaving its invasive programming untampered. The same metastatic phenotype can also be produced by substituting RasV12 with the oncogene Notch . Together, these findings suggest that metastasis from larval imaginal discs depends on the delicate collaboration of a tumour suppressor gene-- which enables the overhaul of tissue integrity-- as well as the input of an oncogene, which disarms apoptotic suppression by JNK. Besides the intraclonal cooperation of cancer genes, similar metastatic outcomes can be produced when those genes are distributed among separate clones in the same tissue . The ability to generate multiple genetic mosaics in the imaginal discs enabled investigation of the interclonal cooperation of clones carrying separate cancer genes. In one study, RasV12 clones were generated in the eye imaginal disc alongside adjacent clones with scrib mutations (RasV12/scrib). These clones showed the same mechanisms of growth as RasV12; scrib and result in similar metastatic outcomes, with visible invasion observed in the VNC . Later studies demonstrated that such cooperation can enable invasion in a way that is not possible by a single clone sharing both genes. For example, Enomoto et al. demonstrated that single eye disc clones harbouring mutations in the oncogenes Src and Ras do not undergo invasion. However, by inducing separate clones expressing Src and Ras, it was found that both populations of clones invade into the VNC . Src clones were seen to express the Notch receptor, whereas RasV12 clones were observed to express its ligand, Delta. The interaction of Notch with its cognate ligand triggered the downregulation of E-Cadherin expression in both clones, as well the additional downregulation of the pro-apoptotic factor head involution defective (hid) in Src+ cells. Interestingly, RNAi interference against E-Cadherin was insufficient to phenocopy invasion of Src clones into the VNC. This only occurred following the transcriptional silencing of both E-Cadherin and hid. This, again, suggests that larval tumours rely on the combined loss of tissue architecture and resistance to apoptosis. Ohshawa et al. have shown that simultaneous intraclonal and interclonal cooperation can be required for invasive behaviours . Following genetic screening, a number of genes encoding mitochondrial respiration complexes were found to collaborate intraclonally with RasV12 to induce the non-cell autonomous growth of surrounding RasV12 clones. The intraclonal combination of RasV12 and mitochondrial mutations (RasV12; mito -/-) collaborating interclonally with RasV12 clones was found to drive invasion into the VNC and brain hemispheres. Mechanistically, increased superoxide levels resulted in the JNK-dependent secretion of Unpaired (Upd) and Wg cytokines. These cytokines were necessary for invasion, as abrogating Upd signalling prevented invasion from occurring. This collaboration of diverse populations of cancer clones is relevant as cancers host highly heterogenous populations of cells carrying variable mutations; such polyclonal modelling is likely to more accurately reflect how metastasis actually occurs. Besides cancer cells collaborating with one another, there is also evidence that cancer cells actively compete with cells that are not one of their own . The genetic tractability of Drosophila make them particularly amenable to modelling this phenomenon of "cell competition", which refers to how cells within a heterogenous population will work against each other to attain a growth advantage, typically by securing a monopoly on growth factors in their niche . In a recent study, Eichenlaub et al. overexpressed EGFR and mIR-8 in the cells of the wing imaginal disc. This resulted in development of aggressive neoplasms that colonized distant tissues, including the hindgut . A subset of these cells developed into "giant cells", which had a considerable increase in overall cell size, enlarged polyploid nuclei and delocalisation of E-Cadherin and Dlg. Peculiarly, the subset of giant cells was flanked by differentiated wild-type cells with apoptotic signifiers such as pyknotic nuclei and cleaved-caspase 3 expression. The smaller wild-type cells were observed to be engulfed by the giant cells in a process that is dependent on the induction of apoptosis, as treatment with the apoptosis inhibitors P35 and DIAP1 prevented the formation of giant cells. Importantly, this same treatment also inhibited colonisation, suggesting that, in this context, metastasis proceeds by cell competition involving apoptosis of neighbouring wild-type cells . 4. Using Drosophila Larvae to Study Interactions with the Microenvironment Since the first Drosophila cancer genes were identified in larvae in 1930, many have capitalised on the genetic tractability and suitability of this system to unravel key pathways implicated in tumorigenesis and metastasis. More recently, this system has been utilised to examine the effect of manipulating the microenvironment on tumour growth and malignancy. It was famously proposed that tumours resemble wounds that do not heal . Indeed, many of the cellular and molecular alterations recurrent in wound healing become reactivated in cancer, often to the benefit of metastasis. This response is largely due to the microenvironment, consisting of stromal cells, signalling molecules, blood vessels and the extracellular matrix (ECM) . Although cancers harbour highly heterogenous populations of clones, which both cooperate and conspire to eliminate their neighbours, stromal cells can account for as much as 90% of a tumour mass . In addition, immune cells contribute to metastasis through the secretion of cytokines, which heavily influence metastatic spread via chemotaxis . Furthermore, systemic inflammation is one of the central means by which metastasis is so characteristically lethal . Although Drosophila lack adaptive immunity and possess an open circulatory system, studies on larvae have nonetheless demonstrated a remarkable degree of conservation as regards to the interplay between metastasis and the microenvironment . In Drosophila larval epithelia, a wound will activate the JNK and the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway stress signalling circuitry, which represents a strong component of Drosophila innate immunity . JNK activation leads to degradation of the basement membrane in a MMP1-dependent manner. This results in the delamination of old and injured cells, which are quickly cleared through JNK's apoptotic machinery response . Moreover, JNK will drive the secretion of inflammatory cytokines through JAK/STAT signalling, which in turn acts to recruit haemocytes to the wound, as well as coaxing the fat body and remote haemocytes to secrete their own ligands in a systemic inflammatory response . Benign imaginal disc tumours driven by mutations in the polarity factors dlg, lgl and scrib appear to activate a similar inflammatory response, with recruited haemocytes secreting Eiger (Drosophila TNFa), which triggers tumour cell apoptosis through JNK signalling . When eiger (egr) is experimentally downregulated, these tumours grow significantly . By contrast, when egr is equivalently downregulated in the metastatic RasV12; scrib model, invasion is prevented and tumour growth is reduced . This is likely to relate to the apoptotic insensitivity conferred by RasV12, which leaves the cells unscathed and still capable of harnessing the invasive capabilities afforded to them by JNK signalling. In another study, Mishra-Gorur et al. demonstrated that RasV12; scrib tumours exhibit preferential colonisation--that is, organotropic metastasis--of the VNC and the mouth hooks but not other sites such as the wing disc. A genome-wide RNAi screen established that silencing the Toll-6 receptor or its ligand Spatzle, not only abolishes organotropic metastasis but inhibits invasion entirely . Mechanistically, Spatzle was found to be secreted by the metastasis-receptive sites and is evidenced to engage JNK signalling by binding Toll-6 receptors on the imaginal disc cells. As it has already been demonstrated that scrib clones are subject to immune surveillance ; the presentation of Toll-6 likely represents a second means by which these cells make themselves amenable to immune destruction, with apoptotic resistance through RasV12 representing an avenue by which they evade surveillance. Together, these findings suggest that, as in vertebrate systems, larval tumours resemble wounding environments that, at the expense of benign tumours, become reprogrammed to their advantage as they assume malignancy. Tumour cells must migrate considerable distances to metastasise to distant sites. Blood vessel remodelling has been the subject of intense research, partially by virtue of its capacity to disseminate cancer cells to remote organs . Although flies lack blood vessels, a number of studies have identified a synonymous phenomenon in the form of neo-tracheogenesis. RasV12; scrib eye disc tumours have been observed to recruit and invade tracheal tubules . In other studies, cancer cells have been documented to crawl along the surface of tubules, even over considerable distances . Indeed, these findings extend beyond local invasion. Calleja et al. found that lgl mutant wing, leg and haltere disc tumours depend on tracheal tubule remodelling to colonise the CNS . These lgl cells were found to suffer hypoxia, as indicated by the hypoxia-specific lactate dehydrogenase reporter, and subsequently recruit tracheal tubules through the secretion of Branchless (Bnl), a fly homolog of the common angiogenesis factor Fibroblast Growth Factor (FGF) . Moreover, some lgl cells were noted to transdifferentiate into pseudo-tracheal cells expressing MMP1, which colocalised with basement membrane breaks. This may represent a means by which imaginal disc tumours undergo invasion. It also resembles human cancers, where some tumour cells are documented to transdifferentiate to endothelial precursors giving rise to blood vessels . Grifoni et al. have provided some insights into the mechanisms underlying neo-tracheogenesis in cancer models: in RasV12; lgl wing disc hypoxia is sensed by the Hypoxia-inducible factor 1-alpha (HIF1A) orthologue Similar (Sima), which upregulates Bnl to attract tracheal tubules through their FGF receptor, Breathless (Btl) . Moreover, cancer cells exhibit directional movement, with extended filopodia in the direction of recruited tracheal tubules, indicating that they are invading out in a coordinated fashion under chemotactic cues. Further examination will be needed to unpack how strongly tracheal remodelling contributes to the invasion and transport of disseminating tumour cells. A surge in pro-inflammatory cytokines driving systemic inflammation is associated with an increase in metastasis . Notably, a number of cytokines such as Tumour necrosis factor (TNFa), Transforming growth factor b (TGFb), and Interleukin 6 (IL-6) have been tied to the progressive wasting of muscle and adipose tissue through a process termed cachexia . Emerging evidence suggests that cytokines activate autophagy in these tissues to recycle nutrients for the growing metabolic demands of invasive tumours . Cachexia is estimated to be responsible for around 20-40% of cancer deaths and is a central underlier of metastasis-associated mortality . Cachexia has been observed in larval tumour models, allowing investigation into links with tumour invasion and metastasis. One study on the transformed eye disc found that metabolically stressed cells in the metastatic RasV12; scrib model, but not the RasV12 benign model, secrete Upd1-3 cytokines that cause systemic autophagy in the muscle, fat body and midgut . Pharmacological or genetic ablation of autophagy using chloroquine or Autophagy-related protein 13 (Atg13) knockout, respectively, resulted in significantly reduced invasion into the VNC . In a later study, evaluating muscle and adipose tissue volume using Computed-Tomography (CT), it was found that RasV12; scrib tumours grow 10-fold when invading into the VNC, while seeing a 50% reduction in muscle volume compared with the benign RasV12 control . Moreover, liquid chromatography/mass spectrometry detected an increase in circulating sugars and amino acids as autophagy proceeds, with carbon-13 tracing showing that the tumours become progressively more reliant on deteriorating tissues for nutrition as they grow . These findings draw attention to the potential of autophagy as a target for pharmacological intervention in the prevention of metastasis-associated mortality and morbidity. Figure 3 Modelling the influence of the tumour microenvironment in Drosophila larvae. (A) Key aspects of the tumour microenvironment in humans vs. Drosophila. The microenvironment includes fibroblasts, which secrete ECM and other factors to drive tumour growth and metastasis; immune cells, which can secrete cytokines and create an inflammatory environment; and blood vessels, which are recruited by the tumour and provide oxygen and nutrients to promote growth. Drosophila lack a closed circulatory system; their tissues are bathed in haemolymph and trachea supply oxygen. In the absence of an adaptive immune response and a vast array of immune cells, Drosophila rely on innate immune responses. In epithelia, wounds activate JAK/STAT and JNK signalling pathways which drives the recruitment of haemocytes. Haemocytes engulf and encapsulate foreign particles and initiate an inflammatory response. (B) Cachexia, where tumours cause wasting of healthy tissue, is a driving force of tumour growth. A reduction in autophagy protein Atg13 in surrounding tissue prevents the recycling of nutrients for the growing metabolic demands of tumours and reduces invasion . (C) Hypoxia is a common feature of tumours, where their intense metabolic demands result in an inadequate oxygen supply to the tissue. Increased hypoxia in the tumour microenvironment results in recruitment of trachea via increased Branchless (Bnl) expression and promotes invasion . (D) In a benign scrib -/- tumour, JNK signalling induces apoptosis and reduces tumour growth. When Drosophila TNFa (egr) is knocked down, loss of apoptosis drives tumour growth. In metastatic tumours, RasV12 confers an insensitivity to apoptosis and harnesses invasive capabilities of JNK signalling. Therefore, knockdown of egr in a RasV12; scrib -/- model inhibits invasion . (E) Spatzle, a Toll-6 receptor ligand, is secreted at metastasis-receptive sites and engages JNK signalling by binding Toll-6 receptors on tumour cells, thus resulting in preferential colonisation of these sites. Preventing this interaction, either by knockdown of Toll-6 or Spatzle, results in reduced invasion into the VNC . It is becoming increasingly apparent that the tumour microenvironment plays a key role in tumour growth, invasion and metastasis. This is in part thanks to work modelling cancer in Drosophila larvae. The accessibility and ease with which we can manipulate the microenvironment in this system has enabled phenomena such as neo-tracheogenesis, cachexia and immune cell reprogramming to be studied. However, despite the high number of mitotic cells in larvae making them amenable for modelling cancer, they remain as larvae for only 4-5 days, limiting the time that the tumours can be left to grow. This means that any changes in expression patterns or cell behaviour that occur after 5 days may be missed. One way to circumvent this problem is by using transplantation experiments. 5. Transplantation Experiments Tumour allograft assays, or transplantation assays, involve the transplantation of tumour cells or tissue into another individual. The earliest reports of transplantation in Drosophila were at the start of the 20th century. In 1918, Mary Stark described "dark bodies" that resembled tumours in Drosophila larvae. In this pioneering work, Stark surgically removed these dark bodies and transferred them to healthy larvae in an attempt to examine the potential for these tumours to spread and cause host death . Although inconclusive due to lethality associated with the surgery itself, this work laid the foundation for the next century of research using this technique. In 1936, a simple microinjection apparatus was developed, enabling successful transplantation between larvae without lethality . At this time, cancer research in flies was in its infancy, and it was not until the 1960s that transplantation experiments were used again to investigate cancer in Drosophila . After discovering that mutations in the tumour suppressor lgl led to the growth of invasive and lethal tumours in the larval brain and imaginal discs, Gateff and Schneiderman used a serial transplantation technique to demonstrate that lgl tumour cells can survive multiple transplantations and metastasise in the adult host . Early transplantation experiments also assisted in distinguishing between malignant and benign neoplasms in Drosophila. Malignant neoplasms are categorised by rapid growth, invasion into adjacent tissue, metastasis, loss of structure and function and lethal autonomous growth after transplantations. In contrast, benign neoplasms (also known as hyperplasia) retain structure and function, are non-invasive and do not grow after transplantation into a new wild-type host. Therefore, mutant lines were checked for the presence of malignant tumours against these criteria, including by serially transplanting tumours into adult hosts and examining their growth and histological characteristics in situ and after transplantation . However, the technique fell into disuse and practically disappeared towards the end of the 20th century, only a few groups were aware of its potential and used it during this time. One such study by Woodhouse et al. demonstrated that imaginal disc tissue from larvae carrying tumorigenic mutations were in fact metastatic when transplanted into adult hosts, in contrast to in situ where they do not metastasise . More recently, transplant experiments have become a standard method to analyse metastatic potential in adult flies. The revival and growth of the transplant technique in Drosophila cancer research was aided by the development of a standardised protocol specifically for studying tumour growth in Drosophila using the tissue allograft method . A key advantage of the technique is enabling tumour growth to be monitored beyond the relatively short lifespan of a single larva. Researchers have made use of this to study the potential for metastasis of tumours generated in mitotic cells within the larvae in an adult host. The first study interrogating mutations sufficient to stimulate invasion and metastasis used transplantation experiments to confirm metastatic ability in the adult after observing metastasis in larvae . For example, transplantation of the RasV12; scrib-/- imaginal tumours discussed in the previous section resulted in rare metastasis and invasion of adult host tissues, including the ovaries and gut . Serial transplants, where tumours are repeatedly harvested and retransplanted into new adult hosts, have allowed the study of primary tumour growth and metastasis over an even longer period . Caussinus and Gonzalez (2005) demonstrated that tumours generated from larval neuroblasts carrying mutations in genes that control asymmetric cell division could grow to 100 times their initial size, invade other tissues and kill adult hosts within two weeks. These tumours have been serially transplanted for over two years and continue to grow, indicating that these cells could proliferate without end, unlike wild-type imaginal disc cells that could survive for years but do not proliferate . Furthermore, small tumour colonies were found distal to the transplant site, suggesting that these tumours with perturbations to asymmetric cell division could metastasise in the adult host . Whilst the presence of secondary tumours far from the transplant sites in adult hosts is highly suggestive of metastatic behaviour, it is possible that it is an artefact from injection into an open circulatory system. As the dissected tissue and fluid in the syringe is forced into the abdomen, the tumour may break up and travel passively, carried by the flow of injected fluid and haemolymph, to distant sites. This could result in tumour fragments appearing as metastases having not undergone the complex cellular transitions required to disseminate from the primary tumour and subsequently arrest and recolonise a secondary site. To address this problem in an existing transplant model, Beaucher et al. developed an in vivo assay for the metastatic potential of tumour cells by quantifying micrometastasis formation by immunofluorescence within the ovarioles of adult hosts after transplantation into the abdomen. In order to be found within the ovarioles, the tumour cells must actively pass through basement membranes and multiple cell layers . This study built on prior work demonstrating that mutations in the tumour suppressor genes lgl and brat were sufficient to drive metastasis in the adult host . Briefly, loss-of-function mutations in these genes trigger neoplastic overgrowth in brains and imaginal discs . When transplanted into the abdomen of adult hosts, brain tumour fragments from lgl, dlg or brat mutant larvae were subsequently found in distant sites such as the leg, wing and head . By examining the ovarioles for the presence of tumour cells, Beaucher et al. were able to confirm whether cancer cells were able to actively disseminate and colonise new sites . This critical evaluation of the metastatic ability of lgl and brat tumours revealed that both were capable of the complex set of cell behaviours required for spread to the ovarioles. Previously, Beaucher et al. demonstrated that whereas lgl and brat tumours had a similar rate of metastasis in the first instance, continuous passaging of the tumour cells into new hosts increased the rate of metastasis in lgl but not brat mutants . Furthermore, non-invasive primary brat and lgl tumours contained cells expressing either neuronal (ELAV) or glial (REPO) markers but never both. In contrast, almost all lgl micrometastases expressed both markers. In brat secondary tumours, it was more variable, with less than half of the micrometastases expressing either marker. Using their newly developed assay for metastasis in the ovaries, Beaucher et al. were able to explore the mechanisms underlying these differences. They found that the matrix metalloproteinase MMP1 was required for colonisation of the ovarioles in both tumours, but the source of MMP1 was different. lgl tumours express MMP1 themselves, whereas brat tumours rely on increased Mmp1 expression in the ovaries for metastasis . This highlights the importance of tumour-microenvironment interactions in determining metastatic potential and is an example of how Drosophila transplant models can be utilised to investigate this. In recent years, several studies have used tumour allograft assays to link metastasis to mutations in Notch signalling, inflammation and TGF-b signalling, among other pathways . There is no doubt that transplant experiments have been instrumental in our understanding of tumour growth and invasion. However, the contribution of tumour microenvironment is relatively unexplored using this technique, despite its potential. One study harnessed the amenability of the transplant technique to confirm findings from larvae showed that autophagy in cells surrounding the RasV12; scrib tumours is necessary for invasion from the eye disc into the VNC . The RasV12; scrib, Atg13 tumours, which had limited growth due to ablation of autophagy, remained small when transplanted into autophagy-deficient hosts but proliferated when transplanted into wild-type hosts, thus demonstrating the importance of autophagy and the microenvironment in tumour growth . Manipulating the microenvironment through the host genotype is an easily accessible but relatively under-utilised method to explore the relationship between specific tumour mutations and environmental conditions and the effect this has on metastatic potential. Overall, transplantation experiments have advantages over studying metastasis in situ in larvae. The main advantage of this approach is the ability to overcome the limitation of the short larval lifespan, enabling tumour growth to be monitored for longer and the effect on adult lifespan to be examined. Tumours can be aged far beyond the lifespan of a single fly using serial transplantations, allowing changes in metastatic potential to be measured over a longer period, more relevant to the human tumour lifespan. Additionally, serial transplantations overcome an inherent technical challenge with Drosophila when aiming to collect large amounts tissue for omics and sequencing approaches, in that flies are very small. By continually harvesting and transplanting the tumours, sufficient tissue can be generated for these experiments. Despite these advantages, there are drawbacks to this technique which should be considered. Firstly, one could argue that it is quite divorced from how cancer actually occurs, and it is important to consider this when using it for modelling purposes. Although the transplant technique has been made more accessible since the publication of a standard protocol , and more recently an automated method for injection , it is still time consuming and challenging. The labour-intensive nature of the approach prevents its use for medium-scale genetic and drug screens. Additionally, it is important to properly define metastases by looking for them inside tissues that are surrounded by basement membrane, such as the ovaries , or by fluorescently labelling the basement membrane , otherwise secondary tumours could be an artefact from injection. Another major limitation of this technique is that it misses the first stages of tumour development. Transplant experiments focus on the later stages of metastases once the primary tumour is well developed, so we may be missing key events in initiation that happen early in primary tumour formation. Furthermore, serially transplanting tumours into new hosts allows the tumours to evolve, whereas the microenvironment is continually replaced. This is different to in human cancer where the tumour and microenvironment are adapting and responding to each other simultaneously. In summary, although transplant experiments have proved instrumental in developing our understanding of factors driving metastasis, there are practical disadvantages and inherent limitations associated with the technique. 6. Inducing Metastatic Tumours in Adult Drosophila The requirement for a cell to divide for neoplastic transformations to be generated has limited the use of adult Drosophila for studies of cancer progression and metastasis. For a long time, the blood cells and the gonads were thought to be the only cells in adult Drosophila which undergo cell divisions. However, the discovery that the adult midgut is under constant renewal, with intestinal stem cells constantly dividing to replenish the tissue, opened a whole new system for cancer modelling in adult flies . This discovery allowed for new models of tumorigenesis based on stem cells in an adult organ that is remarkably similar to its vertebrate equivalent . Furthermore, mutations in genes commonly found mutated in human colorectal cancer (CRC) were demonstrated to also lead to the formation of tumours in the adult fly intestine . Ras is one example of a gene frequently mutated in human cancers . Following a similar pattern to the development of human cancers, mutations in Ras alone are not sufficient to cause tumours in the Drosophila adult gut or larval imaginal tissues but instead lead to an over-proliferation phenotype (hyperplasia) . However, as discussed in detail earlier, Ras mutations can act cooperatively with mutations in other tumour suppressors or oncogenes, for example the tumour suppressors scrib or Adenomatous polyposis coli (APC) , to induce the growth of benign tumours. The APC gene is found mutated in 60% to 75% of human CRCs. APC encodes a protein that inhibits Wnt pathway activation and is named for the thousands of adenomatous polyps found in the gut of patients with familial APC mutations, at least one of which has an almost 100% chance of becoming cancerous . In Drosophila, loss-of-function mutations in both the Apc genes in combination with oncogenic Ras mutations leads to the formation of large tumours that grow aggressively, either inwards towards the lumen of the gut or outwards towards the surrounding musculature . Although these models recapitulate various aspects of human cancers, the resulting tumours are constrained by the ECM and do not metastasise. It is important to remember that the process of metastasis involves invasion and detachment of tumour cells into the circulatory system, transport around the organism, arrest at a suitable location, extravasation into the surrounding tissue and proliferation into a viable metastasis . As previously mentioned, flies have an open circulatory system and no adaptive immune response, thus the process of metastasis in mammals cannot be perfectly replicated in Drosophila. However, a number of models where one or more steps of metastasis are recapitulated in adult flies have now been developed. The first model showing dissemination of mutant cells in adult flies used overexpression of the oncogenic allele RasV12 to induce normally quiescent stem cells in the Drosophila hindgut to proliferate . These cells can disrupt the basal lamina to invade out of the hindgut and can be found individually or in clusters at distant sites within the fly . This process can be enhanced by causing a sustained immune response in the gut through bacterial infection . Lee et al. demonstrated a similar pattern of dissemination in the midgut by overexpressing RasV12 in all ISCs . This dissemination requires the metalloprotease MMP1 to break the basement membrane, downstream of the mechano-sensor Piezo . These models provide important insights into the factors involved in dissemination of tumour cells; however, as overexpression of oncogenic RasV12 alone does not cause the development of primary tumours in the first instance, they are missing key aspects of the metastatic cascade. Tumours can also be induced in the developing pupal eye by disrupting the Notch signalling pathway. Notch signalling is required for normal cell proliferation and differentiation in the Drosophila midgut. It has also been found to be disrupted in a number of human tumours . Disruption of Notch signalling, through either suppression of Notch in daughter cells or reduced levels of Notch ligand Delta in the ISCs , leads to the growth of tumours enriched in ISCs and secretory enteroendocrine (EE) cells. In this study, overexpression of Delta leads to a large eye phenotype; however, if Delta is overexpressed alongside loss-of-function mutations of the axon guidance regulator lola and psq, a gene involved in retinal cell fate determination, large tumours develop in the eye . These tumours form large secondary metastases in 30% of adult flies. In this model, tumour growth can be prevented by restoring expression of Retinoblastoma-family protein (Rbf), a Drosophila homologue of the retinoblastoma family of tumour suppressors, which was found to be hypermethylated. This gives an opportunity to study the effects of the interaction between genetics and epigenetics in the generation of primary and secondary tumours. A more complete model of the metastatic cascade in adult Drosophila was generated in 2019, building on the aforementioned work by Martorell et al. in which a model carrying null mutations in endogenous Apc genes and overexpressing oncogenic RasV12 exhibited growth of tumours in the fly midgut . Constrained by the ECM, these tumours did not invade surrounding tissue or metastasise. However, driving tumour cells to undergo an EMT through overexpression of the EMT transcription factor Snail in Apc, RasV12 flies, led to the formation of tumours capable of breaking through the basal lamina, migrating collectively and forming large metastases in the abdomen, thorax and head . Activation of EMT has been implicated in several human cancers , and this work in Drosophila also mirrors research in mice, where a reduction in levels of EMT transcription factors have been shown to reduce the number of metastases , whereas increased levels of EMT transcription factors correlate with the number of metastases . Understanding more about the role of EMT in metastasis and how we could target this therapeutically is an important focus for future research. The development of a high-throughput screening technique measuring circulating tumour cells and whole tumour burden using luciferase activity makes this model amenable to both genetic and drug screening . As with transplant assays, adult models of metastasis allow the development of a tumour to be studied over a longer period, better recapitulating human disease. In contrast to transplant experiments, generating clones in situ using MARCM in adult flies circumvents practical issues with microinjection, making such models far more amenable to high-throughput screening. In addition, a secondary tumour forming in the adult tumour model cannot be an artefact of the injection and importantly, it allows many stages of metastasis, including the very first and last, to be followed in a single adult fly. 7. Conclusions and Future Directions Since the earliest discoveries of cancer-related genes in larvae, the development of rudimentary transplantation experiments demonstrating the differences between benign and malignant neoplasms and, more recently, the development of adult tumour models, research using fruit flies has been instrumental in enhancing our understanding of factors underlying cancer. An important focus of future cancer research is the metastatic cascade. Metastasis is the biggest cause of cancer-related death, but the mechanisms remain unclear. Drosophila models are ideally placed to address this, and they have already yielded significant findings implicating EMT, dysregulated cell signalling and different aspects of the microenvironment in metastasis. Each type of Drosophila metastasis model has advantages and disadvantages, and each is ideally suited to investigating distinct aspects of metastasis using different techniques. Although larvae have large populations of mitotic cells amenable to induction of tumour growth, they are limited in the time the tumours can grow and are thus unsuitable for long term studies of tumour behaviour. This can be overcome by transplanting larval tumours into adult hosts and monitoring their growth. The main disadvantage of this method is that the primary tumour did not grow in the adult host, meaning you are missing the initial key steps in the metastatic cascade, as well as inducing possible artefacts through injection. More recently, adult models have been developed based on the finding of mitotic intestinal stem cells in the adult gut. These models are advantageous because you can model the entire metastatic cascade and monitor growth and behaviour over long periods. However, all Drosophila models are based on the expression of markers such as GFP, RFP and luciferase. It is possible that some of these markers may affect cell behaviour, survival and response to the immune system. Therefore, it may be an important future endeavour to establish endogenous markers of tumorigenesis to study how tumours behave in the absence of these ectopic factors. In summary, as a model for metastasis Drosophila has limitations but offers also important advantages that can be exploited. There are now a great variety of metastasis models, from the genetically induced to transplantation experiments, that are continuing to contribute to our understanding of how cells become metastatic. Moreover, the great amenability to genetic manipulation that Drosophila offers will help to dissect how gene expression is able to modulate the extraordinary cell plasticity shown by tumour cells and how it is required for their adaptation to new microenvironments. Author Contributions J.L.S., J.M., N.N., K.C. and A.C. conceived the idea behind the review, and drafted, revised and wrote the review together. J.L.S. designed the figures. 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 The metastatic cascade. Following local invasion of the basement membrane at the primary tumour site, cells can enter the blood vessel or lymphatic system and disseminate. Circulating tumour cells (CTCs) travel alone or in clusters and eventually pass through the endothelium and infiltrate distant organs. Cells may remain dormant as micrometastases (typically 2-100 cells) or proliferate and form a secondary tumour. Figure 2 Modelling metastasis in Drosophila larvae. (A) Drosophila larva, showing tissues that undergo mitosis: neuroblasts, imaginal disc cells and gonads. NB = neuroblast; VNC = ventral nerve cord. (B) RasV12 and scrib-/- tumours in the eye imaginal disc form non-invasive tumours. Intraclonal (both mutations within the same clone) and interclonal (mutations in adjacent clones) cooperation between of loss of a tumour suppressor gene such as scrib and expression of an oncogene such as RasV12 results in invasion of the VNC that is reminiscent of the initial stages of metastasis . Intraclonal cooperation has also been observed between RasV12 and mutant mitochondrial respiration complexes . (C) Tumours over expressing EGFR and mIR-8 in the wing imaginal disc grow into neoplasms that can disseminate throughout the larva. A subset of these cells develops into "giant cells" flanked by differentiated wild-type cells. The smaller wild-type cells are engulfed by the giant cells in an apoptosis-dependent manner . Figure 4 Transplantation experiments to model metastasis. (A) Transplantation of larval tissue into adult hosts. Tumours are induced in larvae, usually in the imaginal discs or the brain, and dissected into PBS. This is microinjected into the abdomen of adult host. (B) Serial transplants--tumour dissected from adult host and re-transplanted into a new host, allowing tumours to be incubated for several months. (C) Critical evaluation of active cell spread and colonisation of distant sites. Tumour masses could travel passively, carried by the flow of injected fluid and haemolymph, and be found distant to the transplant site. To be found in the ovary, tumour cells must pass through cell layers and basement membrane. This ensures that secondary tumours are not an artefact from injection into an open circulatory system . Figure 5 Modelling metastasis in adult flies. (A) The adult midgut contains pools of intestinal stem cells (ISCs) under constant renewal, which has enabled the development of adult cancer models. EC = enterocyte; EE = enteroendocrine cell. (B) Cells expressing RasV12 in enterocytes and their progenitors in the hindgut can disrupt the basal lamina to invade out of the hindgut and can be found individually or in clusters in the midgut and associated with trachea . (C) Overexpression of the EMT transcription factor Snail in Apc-RasV12 flies enables tumour cells to break through the basement membrane, disseminate and form secondary tumours. These can be seen in the thorax and the head . 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PMC10000391 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051006 foods-12-01006 Article Curcumin Alleviates Aflatoxin B1-Induced Liver Pyroptosis and Fibrosis by Regulating the JAK2/NLRP3 Signaling Pathway in Ducks Cui Yilong 1 Wang Qi 2 Zhang Xuliang 2 Yang Xu 3 Shi Yun 4 Li Yanfei 2 Song Miao 2* Buchanan Robert L. Academic Editor 1 College of Animal Science and Technology, Inner Mongolia Minzu University, Tongliao 028000, China 2 Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China 3 College of Veterinary Medicine, Henan Agricultural University, Zhengzhou 450002, China 4 Tongliao City Animal Quarantine Technical Service Center, Tongliao 028000, China * Correspondence: [email protected] 27 2 2023 3 2023 12 5 100622 12 2022 09 2 2023 12 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 ). Aflatoxin B1 (AFB1) is a serious pollutant in feed and food which causes liver inflammation, fibrosis, and even cirrhosis. The Janus kinase 2 (JAK2)/signal transducers and activators of the transcription 3 (STAT3) signaling pathway is widely involved in inflammatory response and promotes the activation of nod-like receptor protein 3 (NLRP3) inflammasome, thus leading to pyroptosis and fibrosis. Curcumin is a natural compound with anti-inflammatory and anti-cancer properties. However, whether AFB1 exposure leads to the activation of the JAK2/NLRP3 signaling pathway in the liver and whether curcumin can regulate this pathway to influence pyroptosis and fibrosis in the liver remains unclear. In order to clarify these problems, we first treated ducklings with 0, 30, or 60 mg/kg AFB1 for 21 days. We found that AFB1 exposure caused growth inhibition, liver structural and functional damage, and activated JAK2/NLRP3-mediated liver pyroptosis and fibrosis in ducks. Secondly, ducklings were divided into a control group, 60 mg/kg AFB1 group, and 60 mg/kg AFB1 + 500 mg/kg curcumin group. We found that curcumin significantly inhibited the activation of the JAK2/STAT3 pathway and NLRP3 inflammasome, as well as the occurrence of pyroptosis and fibrosis in AFB1-exposed duck livers. These results suggested that curcumin alleviated AFB1-induced liver pyroptosis and fibrosis by regulating the JAK2/NLRP3 signaling pathway in ducks. Curcumin is a potential agent for preventing and treating liver toxicity of AFB1. dietary curcumin AFB1 exposure hepatocyte pyroptosis liver fibrosis Jinding duck Doctoral Funding of Inner Mongolia Minzu UniversityBS660 Outstanding Talents of Henan Agricultural University30500996 Key Scientific Research Projects of Colleges and Universities in Henan Province23A230008 National Natural Science Foundation of China32202877 Science and Technology Innovation Fund of Henan Agricultural UniversityKJCX2021A06 This work was supported by the Doctoral Funding of Inner Mongolia Minzu University (BS660), Outstanding Talents of Henan Agricultural University (30500996), Key Scientific Research Projects of Colleges and Universities in Henan Province (23A230008), National Natural Science Foundation of China (32202877), and the Science and Technology Innovation Fund of Henan Agricultural University (KJCX2021A06). pmc1. Introduction Aflatoxin B1 (AFB1) is one of the most harmful mycotoxins in feed and food . In 1996, the World Health Organization set the upper limit of AFB1 in cereals entering the market at 20 mg/kg . However, many parts of the world have remained heavily contaminated with AFB1 for many years, posing a threat to animal and human health. In 2014, Iram et al. found that the average content of AFB1 in 487 poultry feeds and raw materials in Pakistan was 37.62 mg/kg and 23.75 mg/kg, respectively . In 2019, Akinmusire et al. found that 101 poultry feeds and raw materials in Nigeria contained an average of 74 mg/kg AFB1 . In 2019, Mahuku et al. found that the average AFB1 content in maize samples from eastern and southwestern Kenya was 67.8 mg/kg and 22.3 mg/kg, respectively . Long-term ingestion of food or feed contaminated with AFB1 can lead to chronic poisoning in humans and animals, with symptoms such as dizziness, anorexia, convulsions, and loss of memory function . Chronic AFB1 poisoning can cause damage to the liver, kidney, spleen, testis, and other parenchymal organs, resulting in growth disorder, immunosuppression, hematopoietic damage, and reduced reproductive performance . Therefore, the question of how to alleviate the harm caused by AFB1 has become a hot issue in today's research. The liver is the main organ of metabolism and detoxification and is also the main target organ for AFB1 to exert toxicity . AFB1 accumulation in the liver can cause inflammation and fibrosis, and the progression of fibrosis may lead to cirrhosis . Recently, some studies have reported that the nod-like receptor protein 3 (NLRP3) inflammasome is associated with liver fibrosis . Once the toxin enters the liver, NLRP3 molecules collect apoptosis-associated speck-like protein (ASC) and pro-caspase-1 molecules to assemble into the NLRP3 inflammasome, which catalyzes pro-caspase-1 to become mature cysteinyl aspartate-specific proteinase 1 (Caspase-1) . Subsequently, mature Caspase-1 catalyzes the hydrolysis of interleukin-1b (IL-1b) precursor protein and interleukin-18 (IL-18) precursor protein into mature IL-1b and IL-18, which are released into the extracellular matrix, triggering an inflammatory response and promoting fibrosis progression . In addition, Caspase-1 can cleat the Gasdermin D (GSDMD) protein into GSDMD-N, which can cause pyroptosis through oligomerization on the cell membrane and further promote fibrosis . The Janus kinase 2 (JAK2)/signal transducers and activators of the transcription 3 (STAT3) pathway is a newly discovered pathway widely involved in inflammation, pyroptosis, and fibrosis, which has been proved to activate the NLRP3 inflammasome . However, it is unclear whether AFB1-induced liver pyroptosis and fibrosis is related to the JAK2/NLRP3 signaling pathway. AFB1 poisoning is more common in chickens, ducks, pigs, and other economic animals, among which ducks are the most susceptible, with young and male animals being more susceptible than adult and female animals . In 1977-1978, AFB1 poisoning caused sudden concentrated deaths of waterfowl in two areas of Texas . In addition, after livestock and poultry eat feed contaminated with AFB1, the toxin can still remain in meat, eggs, milk, and other animal-derived food, and bring great safety risks to human health through the food chain . Some scholars estimate that AFB1 pollution costs the United States between USD 52.1 million and USD 1.68 billion annually . Curcumin, a diketone compound, is a plant polyphenol extracted from the rhizome of Curcuma longa . This natural compound, which is widely found in Sichuan and Guizhou provinces of China, has been shown to have antiviral, antifungal, and anti-cancer pharmacological effects . Although curcumin is rapidly metabolized in the body, and ways to improve its bioavailability are still being sought, its effective effects on neurological diseases, cardiovascular disease, and diabetes have been widely reported . In animal studies, curcumin can improve the antioxidant and anti-inflammatory ability of ducks, reduce the liver and intestinal damage caused by AFB1 and ochratoxin A, and thus improve the performance of ducks, and it has been confirmed that it is safe and harmless for ducks to feed on curcumin alone . However, whether curcumin can alleviate liver pyroptosis and fibrosis caused by AFB1 has not been reported. Therefore, the purpose of this study was to explore whether curcumin could alleviate AFB1-induced liver pyroptosis and fibrosis by regulating the JAK2/NLRP3 signaling pathway in ducks, so as to provide an experimental basis for alleviating the liver toxicity of AFB1 in clinic. 2. Materials and Methods 2.1. Schematic Overview of Experimental Program Figure 1 describes the design idea of this study. 2.2. Animals and Treatment In the first part of the experiment, one-day-old healthy male Jinding ducks (Anas platyrhyncha) were randomly divided into three groups (n = 6). The dose of AFB1 was determined according to previous studies and the median lethal dose in ducks (LD50 = 300 mg/kg body weight) . AFB1 (>=99.8%, Qingdao Pribolab Pte. Ltd., Qingdao, China) was dissolved in corn oil. The low-dose group (LG) and high-dose group (HG) were given 30 mg/kg (1/10 LD50) and 60 mg/kg (1/5 LD50) body weight of AFB1 by intragastric administration daily, respectively. The control group (CG) was given the same volume of solvent. The experiment lasted three weeks. We found that 60 mg/kg AFB1 caused more significant fibrotic lesions in the duck liver, so this dose was selected for the second part of the experiment. One-day-old healthy male ducks were divided into three groups (n = 6): control group (CG), AFB1 exposure group (AG, 60 mg/kg AFB1), and AFB1 + curcumin group (ACG, 60 mg/kg AFB1 and 500 mg/kg curcumin). Curcumin (>=99.8%, Nanjing NutriHerb BioTech Co., Ltd., Nanjing, China) was added to the base diet at doses determined by previous studies . The experiment lasted three weeks. All experimental routines and protocols have been approved by the Animal Ethics Committee of the Northeast Agricultural University (NEAUEC20230332). The ducks were kept in the Biomedical Research Center of Northeast Agricultural University and had free access to water and pellet feed formulated according to the National Research Council. The temperature in the room was 32 degC for the first week, 30 degC for the second week, and 28 degC for the third week, guaranteeing 18 h of incandescent light a day. No animals died during the experiment. 2.3. Sample Collection After stopping feeding overnight (12 h) on the 21st day, the ducks were weighed; then, the blood was collected through the wing vein and serum was collected after centrifugation at 1500x g for 10 min. The ducks were anesthetized by intravenous injection of sodium pentobarbital (50 mg/kg body weight). Livers were quickly collected, one part was fixed with 4% formaldehyde for histopathological examination, and the rest was stored at -80 degC for other studies. 2.4. Measurement of Serum ALT and AST Activities Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities were measured using an automatic hematology analyzer. 2.5. Histopathological Observation The liver was fixed in 4% paraformaldehyde for 24 h, then embedded in paraffin and sliced. Hematoxylin eosin (HE) staining and sirius red staining were performed, respectively, according to previous studies . The sections were scanned and then observed with CaseViewer software (3Dhistech, Budapest, Hungary) to evaluate the degree of histopathological damage and fibrosis. 2.6. TUNEL Analysis According to the instruction of the biochemical kit (Beyotime, Shanghai, China), the above liver sections were stained using terminal deoxynucleoside transferase (TdT) dUTP nick end labeling (TUNEL). The sections were scanned and then observed with CaseViewer software (3Dhistech, Budapest, Hungary) to evaluate the liver pyroptosis level. 2.7. Detection of IL-1b and IL-18 Levels in the Liver and Serum The 50 mg liver sample was added to 1 mL phosphate-buffered saline, fully ground with homogenizer, and then centrifuged at 12,000x g for 10 min to collect the supernatant. The contents of IL-1b and IL-18 in the supernatant and serum were determined using the ELISA kits (Nanjing Jiancheng, Nanjing, China). 2.8. RT-qPCR Analysis The total RNA of duck liver was extracted according to the instruction of Trizol reagent (Invitrogen, Carlsbad, CA, USA), and then the cDNA was synthesized using the reverse transcription kit (Roche, Basel, Switzerland). The mRNA expression was detected with an ABI PCR system (Thermo Fisher, Waltham, MA, USA). b-actin was selected as the internal reference gene, and the relative mRNA expression was calculated using the 2-DDCt method. All the information on primers is shown in Table S1. 2.9. Western Blot Analysis The 100 mg liver sample was added to 1 mL RIPA lysate (Beyotime, Shanghai, China) with 10 mL PMSF (Beyotime, Shanghai, China), fully ground with homogenizer, then centrifuged at 12,000x g for 10 min at 4 degC to collect the supernatant. A BCA kit (Solarbio, Beijing, China) was used to detect the protein concentration, and 30 mg protein samples were selected for 5-12% SDS-PAGE gel electrophoresis. The gel was then transferred to the PVDF membrane, incubated overnight with the required primary antibody at 4 degC, and then incubated with the corresponding secondary antibody for 1 h at 37 degC. Images were collected in a gel imaging system (General Electric, Fairfield, CT, USA) using an ECL luminescence solution and analyzed using Image J software (National Institutes of Health, Bethesda, MD, USA). All the information on antibodies is shown in Table S2. 2.10. Statistical Analysis Data were analyzed using SPSS 25.0 software (SPSS Incorporated, Chicago, IL, USA) and expressed as mean +- standard deviation (mean +- SD). * and ** represent p < 0.05 and p < 0.01 vs. the CG, respectively; # and ## represent p < 0.05 and p < 0.01 vs. the AG, respectively. 3. Results 3.1. AFB1 Exposure Caused Liver Damage in Ducks Compared with the CG, the body weight decreased significantly by 11% and 24.5%, the serum ALT activities increased significantly by 41% and 87%, and the serum AST activities increased significantly by 39% and 76% in the LG and HG, respectively . HE staining showed that the CG liver had normal microscopic structure, while the LG and HG livers showed hepatic cord disorders, inflammatory cell infiltration, and even hepatic cell disintegration . 3.2. AFB1 Exposure Activated JAK2/NLRP3-Mediated Pyroptosis in Duck Livers The mRNA expressions of JAK2 and STAT3 in the LG were 1.74 and 2 times that in the CG, respectively, and the mRNA expressions of JAK2 and STAT3 in the HG were 2.74 and 3.04 times that in the CG, respectively . The protein expressions of pJAK2/JAK2 and pSTAT3/STAT3 in the LG were 1.76 and 2.41 times that in the CG, respectively, and the protein expressions of pJAK2/JAK2 and pSTAT3/STAT3 in the HG were 3.06 and 4.59 times that in the CG, respectively . Compared with the CG, TUNEL staining showed that the positive rate of the LG and HG increased from 1.43% to 10.6% and 20%, respectively . The mRNA expressions of NLRP3, ASC, and Caspase-1 in the LG were 2.87, 2.56, and 1.95 times that in the CG, respectively, and the mRNA expressions of NLRP3, ASC, and Caspase-1 in the HG were 4.37, 4.23, and 4.43 times that in the CG, respectively . The protein expressions of NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N in the LG were 1.36, 2.19, 1.59, 1.89, and 2.58 times that in the CG, respectively, and the protein expressions of NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N in the HG were 2.56, 3.86, 2.5, 4.15, and 8.32 times that in the CG, respectively . 3.3. AFB1 Exposure Caused Liver Fibrosis in Ducks Compared with the CG, the liver IL-1b levels increased significantly by 22% and 62%, the liver IL-18 levels increased significantly by 14% and 38%, the serum IL-1b levels increased significantly by 22% and 61%, and the serum IL-18 levels increased significantly by 15% and 34% in the LG and HG, respectively . The mRNA expressions of IL-1b and IL-18 in the LG were 2.82 and 1.85 times that in the CG, and the mRNA expressions of IL-1b and IL-18 in the HG were 4.4 and 2.67 times that in the CG, respectively . Sirius red staining showed that the liver fibrosis of ducks became more and more obvious with the gradual increase in AFB1 exposure dose . The mRNA expressions of a-SMA, Col-I;, and TGF-b in the LG were 2.39, 2.22, and 1.79 times that in the CG, and the mRNA expressions of a-SMA, Col-I;, and TGF-b in the HG were 4.08, 4.33, and 3.33 times that in the CG, respectively . The protein expressions of a-SMA, Col-I;, and TGF-b in the LG were 2.5, 2.12, and 1.53 times that in the CG, and the protein expressions of a-SMA, Col-I;, and TGF-b in the HG were 4.15, 3.6, and 2.33 times that in the CG, respectively . 3.4. Curcumin Alleviated Liver Damage in Ducks Caused by AFB1 Exposure Compared with the AG, the body weight increased significantly by 19%, the serum ALT activity decreased significantly by 24%, and the serum AST activity decreased significantly by 21% in the ACG, respectively . Compared with the AG, HE staining showed significant remission of liver lesions in the ACG . 3.5. Curcumin Alleviated JAK2/NLRP3-Mediated Pyroptosis in the Liver of Ducks Exposed to AFB1 The mRNA expressions of JAK2 and STAT3 in the ACG were 0.61 and 0.58 times that in the AG, respectively . The protein expressions of pJAK2/JAK2 and pSTAT3/STAT3 in the ACG were 0.74 and 0.71 times that in the AG, respectively . Compared with the AG, TUNEL staining showed that the positive rate of ACG decreased from 18% to 9.4% . The mRNA expressions of NLRP3, ASC, and Caspase-1 in the ACG were 0.71, 0.53, and 0.6 times that in the AG, respectively . The protein expressions of NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N in the ACG were 0.79, 0.68, 0.63, 0.65, and 0.65 times that in the AG, respectively . 3.6. Curcumin Alleviated Liver Fibrosis in Ducks Caused by AFB1 Exposure Compared with the AG, the liver IL-1b and IL-18 levels decreased significantly by 24% and 17%, respectively, and the serum IL-1b and IL-18 levels decreased significantly by 27% and 13% in the ACG, respectively . The mRNA expressions of IL-1b and IL-18 in the ACG were 0.63 and 0.62 times that in the AG, respectively . Compared with the AG, sirius red staining showed significant remission of liver fibrosis in the ACG . The mRNA expressions of a-SMA, Col-I;, and TGF-b in the ACG were 0.76, 0.54, and 0.67 times that in the AG, respectively . The protein expressions of a-SMA, Col-I;, and TGF-b in the ACG were 0.85, 0.73, and 0.67 times that in the AG, respectively . 4. Discussion In this study, we first found that AFB1 exposure resulted in slow growth, liver structural and functional impairment, and caused the JAK2/NLRP3-mediated liver pyroptosis and fibrosis in ducks. Secondly, we found that curcumin alleviated AFB1-induced liver pyroptosis and fibrosis by regulating the JAK2/NLRP3 signaling pathway in ducks. These results provide a new understanding for exploring the mechanism of hepatotoxicity of AFB1 and provide an experimental basis for curcumin to alleviate the toxicity of AFB1. AFB1 has the highest accumulation in liver after entering the body . Meissonnier et al. found that AFB1 exposure resulted in decreased weight gain and dysfunction of liver structure and function in pigs . Gao et al. found that AFB1 exposure resulted in liver damage in chickens, including hepatocyte destruction, swelling, and inflammatory cell infiltration, as well as increased ALT and AST activities . Consistent with these results, we also demonstrated that AFB1 exposure caused slow growth and liver histopathological damage and dysfunction in ducks . These studies indicate that AFB1 is harmful to a variety of species, but the specific mechanism of liver toxicity of AFB1 still needs to be further explored. Liver fibrosis is a repair reaction after liver injury which can lead to cirrhosis or even liver cancer if it continues to develop excessively . During liver inflammation, hepatic stellate cells are activated and converted into myofibroblasts, which produced large amounts of extracellular matrix leading to fibrosis . The increased expression of a-SMA and Col-I is the main characteristic of hepatic stellate cell activation, and TGF-b can promote myofibroblast proliferation . In this study, we first found that AFB1 exposure caused significant fibrosis in duck livers through sirius red staining . RT-qPCR and Western blot detection revealed that the expression levels of a-SMA, Col-I, and TGF-b were significantly increased, which further confirmed the occurrence of fibrosis . AFB1 exposure has been shown to cause liver fibrosis in Oncorhynchus mykiss and rats in previous studies . However, there are few studies on the specific mechanism of liver fibrosis induced by AFB1. Inflammation is undoubtedly a key factor leading to fibrosis. As an intracellular protein complex, the NLRP3 inflammasome is a major inflammatory factor . The activation of the NLRP3 inflammasome, on the one hand, produces IL-1b and IL-18, leading to liver fibrosis. On the other hand, it activates Caspase-1-mediated pyroptosis to promote fibrosis development . In this study, we found that AFB1 exposure led to increased expressions of NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N in duck livers, and combined with TUNEL staining analysis, this confirmed the occurrence of pyroptosis . In addition, the JAK2/STAT3 signaling pathway has been reported to not only activate the NLRP3 inflammasome and lead to pyroptosis, but also to promote the proliferation of hepatic stellate cells and promote fibrosis . Therefore, we continued to detect the JAK2/STAT3 signaling pathway, and the results showed that this pathway was activated in the liver of AFB1-exposed ducks . In conclusion, AFB1 exposure leads to JAK2/NLRP3-mediated pyroptosis and fibrosis in duck livers and may have a critical effect on liver damage. The activation of the NLRP3 inflammasome directly promotes the progression of liver pyroptosis and fibrosis . Therefore, reducing the activation of the NLRP3 inflammasome is a reliable method to reverse the development of liver pyroptosis and fibrosis and effectively alleviates liver injury. Curcumin, a naturally occurring polyphenol in turmeric, has been shown to be effective in inhibiting inflammation and pyroptosis. Yu et al. found that curcumin alleviated doxorubicin-induced cardiac injury by inhibiting NLRP3 inflammasome activation and myocardial pyroptosis . In a recent study, Gan et al. found that curcumin mitigated arsenic trioxidation-induced hypothalamic damage in ducks by inhibiting neuronal pyroptosis mediated by the NF-kB/NLRP3 signaling pathway . In addition, curcumin has been shown to alleviate inflammation by inhibiting the JAK/STAT signaling pathway . Therefore, we hypothesized that curcumin could alleviate AFB1-induced pyroptosis and fibrosis by regulating the JAK2/NLRP3 signaling pathway in duck livers. AFB1-exposed ducklings were fed a diet supplemented with curcumin for 21 days. These ducks showed improved growth rates compared to ducks exposed only to AFB1 . HE staining showed that the damage of the liver microstructure was significantly alleviated, and the activities of ALT and AST were also decreased . Similarly, Jin et al. demonstrated that dietary curcumin could improve the growth performance, brisket quality, and antioxidant capacity of multiple organs, as well as the damage of liver structure and function in ducks . Moreover, we found that curcumin alleviated AFB1-induced duck liver fibrosis by sirius red staining and detection of a-SMA, Col-I, and TGF-b expression . The alleviative effect of curcumin on duck liver fibrosis induced by AFB1 may be the key factor for curcumin to protect the liver, and we further explored the molecular mechanism. We first detected factors related to the JAK2/STAT3 pathway and found that curcumin inhibited the activation of this pathway in the liver of AFB1-exposed ducks . We then found that curcumin inhibited the increased expressions of NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N in the liver of AFB1-exposed ducks . Combined with TUNEL staining analysis , these results demonstrated that curcumin inhibited AFB1-induced JAK2/NLRP3-mediated pyroptosis in duck livers. It should be noted that there was no significant difference between AG in the curcumin treatment experiment and HG in the toxicity experiment in this study. These reflect the stability of the test method and the effectiveness of curcumin therapy in this study. On the whole, JAK2/NLRP3-mediated pyroptosis and fibrosis may be a key target for the prevention and treatment of liver damage induced by AFB1 exposure, and curcumin can regulate this pathway and alleviate the liver toxicity of AFB1. 5. Conclusions Curcumin can alleviate AFB1-induced liver pyroptosis and fibrosis by regulating the JAK2/NLRP3 signaling pathway in ducks. Therefore, curcumin as a natural plant extract shows potential in preventing AFB1-induced liver fibrosis. Supplementary Materials The following supporting information can be downloaded at: Table S1: Primer sequences and amplification lengths of destination fragments; Table S2: The sources of the antibodies. Click here for additional data file. Author Contributions Y.C. designed the experiment and wrote the first draft of the paper. Q.W. carried out the feeding, sample collection and main experiments of ducks. X.Z. directed some of the experiments. X.Y. provided financial support. Y.S. and Y.L. checked and verified the data. M.S. reviewed and revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The experimental protocol was conducted in compliance with the Guide for the Care and Use of Agricultural Animals in Agriculture Research and Teaching of Northeast Agricultural University (Protocol number: NEAUEC20230332). Data Availability Statement The data used and analyzed in this study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic overview of experimental program. Firstly, ducks were exposed to a gradient dose of AFB1 for 21 days. The effects of AFB1 on fibrosis, JAK2/NLRP3 signaling pathway, and pyroptosis of duck livers were analyzed. Then, the dose of AFB1, which can cause significant liver fibrosis in ducks, was selected and treated with curcumin for 21 days. The effects of curcumin on fibrosis, JAK2/NLRP3 signaling pathway, and pyroptosis of duck livers caused by AFB1 were analyzed. Figure 2 AFB1 exposure caused liver damage in ducks. (A) Body weight (n = 6). (B) Serum ALT activity (n = 6). (C) Serum AST activity (n = 6). (D) Representative images of liver HE staining (red arrow: disordered hepatic cords; yellow arrow: infiltrated inflammatory cells; blue arrow: hepatocyte disintegration). Scale bar: 50 mm. ** p < 0.01 vs. the CG. Figure 3 AFB1 exposure activated JAK2/NLRP3-mediated pyroptosis in duck livers. (A) mRNA expressions of JAK2 and STAT3 (n = 6). (B) Western blot of the JAK2, p-JAK2, STAT3, and p-STAT3 protein (n = 3). (C) Representative images of liver TUNEL staining. Scale bar: 50 mm. (D) TUNEL analysis of livers (n = 3). (E) mRNA expressions of IL-1b and IL-18 (n = 6). (F) Western blot analysis of the NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N protein levels (n = 3). * p < 0.05 and ** p < 0.01 vs. the CG. Figure 4 AFB1 exposure caused liver fibrosis in ducks. (A) Liver IL-1b and IL-18 levels (n = 6). (B) Serum IL-1b and IL-18 levels (n = 6). (C) mRNA expressions of IL-1b and IL-18 (n = 6). (D) Representative images of sirius red staining of duck livers (black arrow: fibrotic lesions). (E) mRNA expressions of a-SMA, Col-I;, and TGF-b (n = 6). (F) Western blot analysis of the a-SMA, Col-I;, and TGF-b protein levels (n = 3). ** p < 0.01 vs. the CG. Figure 5 Curcumin alleviated liver damage caused by AFB1 in ducks. (A) Body weight (n = 6). (B) Serum ALT activity (n = 6). (C) Serum AST activity (n = 6). (D) Representative images of liver HE staining (red arrow: disordered hepatic cords; yellow arrow: infiltrated inflammatory cells; blue arrow: hepatocyte disintegration). Scale bar: 50 mm. * p < 0.05 and ** p < 0.01 vs. the CG. ## p < 0.01 vs. the AG. Figure 6 Curcumin inhibited JAK2/NLRP3-mediated pyroptosis of duck livers caused by AFB1. (A) mRNA expressions of JAK2 and STAT3 (n = 6). (B) Western blot of the JAK2, p-JAK2, STAT3, and p-STAT3 protein (n = 3). (C) Representative images of liver TUNEL staining. Scale bar: 50 mm. (D) TUNEL analysis of livers (n = 3). (E) mRNA expressions of IL-1b and IL-18 (n = 6). (F) Western blot analysis of the NLRP3, ASC, Caspase-1, GSDMD, and GSDMD-N protein levels (n = 3). ** p < 0.01 vs. the CG. # p < 0.05 and ## p < 0.01 vs. the AG. Figure 7 Curcumin alleviated liver fibrosis in ducks caused by AFB1. (A) Liver IL-1b and IL-18 levels (n = 6). (B) Serum IL-1b and IL-18 levels (n = 6). (C) mRNA expressions of IL-1b and IL-18 (n = 6). (D) Representative images of sirius red staining of duck livers (black arrow: fibrotic lesions). (E) mRNA expressions of a-SMA, Col-I, and TGF-b (n = 6). (F) Western blot analysis of the a-SMA, Col-I;, and TGF-b protein levels (n = 3). ** p < 0.01 vs. the CG. # p < 0.05 and ## p < 0.01 vs. the AG. 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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PMC10000392 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050856 diagnostics-13-00856 Case Report Surgical Atrial Septal Patch Endocarditis in a Patient with a Complete Corrected Atrioventricular Canal Defect: A Case Report and Review of the Literature Serban Adela 12 Achim Alexandru 1* Gavan Dana Elena 1 Tomoaia Raluca 23* Molnar Adrian 45+ Suceveanu Mihai 1 Axente Dan Damian 6+ Mot Stefan 12+ Dadarlat-Pop Alexandra 12 Henein Michael Academic Editor 1 Cardiology Department, Heart Institute Niculae Stancioiu, 19-21 Motilor Street, 400001 Cluj-Napoca, Romania 2 5th Department of Internal Medicine, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania 3 Clinical Rehabilitation Hospital, 46-50 Viilor Street, 400347 Cluj-Napoca, Romania 4 Cardiovascular Surgery Department, Heart Institute Niculae Stancioiu, 19-21 Motilor Street, 400001 Cluj-Napoca, Romania 5 7th Department of Surgery, Faculty of Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania 6 Cluj-Napoca Municipal Clinical Hospital, 400139 Cluj-Napoca, Romania * Correspondence: [email protected] (A.A.); [email protected] (R.T.) + These authors contributed equally to this work. 23 2 2023 3 2023 13 5 85609 2 2023 20 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 ). Infective endocarditis (IE) is common in patients with corrected congenital heart disease (CHD) with a residual lesion, but is rarely found on surgical patches used to close atrial septal defects (ASDs). This is also reflected in the current guidelines that do not recommend antibiotic therapy for patients with a repaired ASD with no residual shunt six months after closure (percutaneous or surgical). However, the situation could be different in the case of mitral valve endocarditis, which causes leaflet disruption with severe mitral insufficiency and could seed the surgical patch. We present herein a 40-year-old male patient with a past medical history of a complete surgically corrected atrioventricular canal defect performed in childhood who presented with fever, dyspnea and severe abdominal pain. Transthoracic and transesophageal echocardiography (TTE and TEE) revealed vegetation at the level of the mitral valve and the interatrial septum. The CT scan confirmed ASD patch endocarditis and multiple septic emboli, guiding the therapeutic management. An accurate evaluation of cardiac structures should be mandatory when a systemic infection is detected in CHD patients, even if the defects were surgically corrected, because the detection and eradication of such infectious foci as well as a surgical reintervention are particularly difficult to achieve in this subpopulation. congenital heart disease atrioventricular canal defect surgical atrial patch infectious endocarditis PDI-PFE-CDI 202140PFE/30.12.2021 This work was granted by project PDI-PFE-CDI 2021, entitled Increasing the Performance of Scientific Research, Supporting Excellence in Medical Research and Innovation, PROGRES, no. 40PFE/30.12.2021. pmc1. Introduction The overall incidence of infective endocarditis (IE) in patients with congenital heart disease (CHD) is significantly higher than in the general population . IE incidence is strongly correlated with age also among patients with CHD, as the majority of IE cases are seen in older patients with CHD . However, IE mainly occurs in unrepaired cyanotic congenital heart defects and in repaired defects with residual shunt or valvular regurgitation. Even if not repaired, due to the slow velocity of shunt flow, an atrial septal defect (ASD) has a very low risk of IE and therefore antimicrobial prophylaxis is recommended (according to the guidelines) only in patients with an ASD who have a prior history of IE or a residual shunt adjacent to a prosthetic patch or prosthetic device or during the six months after closure . Infections of the surgical atrial septal patch are rarely seen and late IE (after 6 months) at this level is even rarer. Early IE on prosthetic patches or prosthetic devices is associated with incomplete endothelization , while in late IE cases, underlying mitral valvulopathy with subsequent severe mitral valve destruction has been noted, perhaps explaining a two-step mechanism of bacterial colonization from the mitral valve to the nearby interatrial septum . Atrial septal defects larger than 1 cm require percutaneous or surgical closure. Previously, surgical closure was the standard of care for ASD, but over the last 30 years, transcatheter devices have rapidly emerged as the gold standard for ostium secundum ASD . Infectious complications of atrial septal occluder devices represents about 0.1% of cases . The risk of infectious endocarditis on the surgical patch is usually related to the time of surgery; the risk is higher in the first 3 months. Infection of a percutaneous closing device can occur either in association with the procedure, involving microorganism inoculation, or by later hematogenous spread . We present a case of a 40-year-old male patient with a past medical history of a complete atrioventricular canal defect surgically corrected in his childhood who presented with late IE of the mitral valve and the surgical patch. Multimodal imaging led to the diagnosis and the discovery of multi-organ septic embolizations. We reviewed the literature to find similar reports in order to understand the evolution and the therapeutic management of these patients. 2. Case Report A 40-year-old male was admitted to the emergency department for chills, a fever of 39 degC, dyspnea, severe abdominal pain and fatigue lasting 9 days. The fever started insidiously, the abdominal pain appeared suddenly 3 days prior to admission and the dyspnea got progressively worse, forcing the patient to seek medical help. He denied any history of travel or exposure to animals. His COVID-19 test was negative on admission. The family and social histories were noncontributory. In the patient's medical history, he had undergone surgery for a complete atrioventricular canal defect at 7 years old. The ostium primum septal defect was closed by a Dacron patch and the anterior mitral valve cleft was corrected by a cleft suture. After surgery, moderate residual mitral regurgitation was detected on several echocardiographic assessments, with no prior evidence of a leak over the atrial septum. On physical examination, he was tachycardic and tachypneic, with a systolic murmur, bilateral fine rales, peripheral oedema, jaundice and also Osler nodules on his hands. A laboratory analysis demonstrated severe inflammatory syndrome (WBC = 21 x 103/mL, CRP = 213 mg/L and Feritine = 3444 mg/L), elevated NTproBNP (=1874 pg/mL) and hepatic dysfunction (GPT = 215 UI/L and GOT = 142 UI/L). The blood cultures were positive for methicillin-sensitive Staphylococcus aureus (MSSA). Two cultures at an interval of 12 h were found positive with the same germ. He presented no risk factors for community Staphylococcus aureus infection (skin abrasions, wounds, etc.) other than acne. The ECG showed sinus tachycardia with left axis deviation and a RSR pattern in V1, which is characteristic of the ostium primum defect. Transthoracic and transesophageal echocardiography (TTE and TEE) revealed a thickened anterior mitral valve in the cleft area, with a highly mobile echogenic structure about 10 mm prolapsing in the left atrium (LA) , suggestive of vegetation with high embolic risk. Severe mitral regurgitation was detected on color Doppler evaluation with the jet origin in A2-A3 mitral segments . The TEE findings revealed that the atrial septum was infiltrated, particularly on the right side, and thickened, with mobile structures of about 5 mm in diameter . There were also some round ecolucent spaces with a color Doppler signal, indicative of an abscess . For a better description of the atrial septum, a cardiac CT was performed. This confirmed the presence of the vegetation at the level of the anterior mitral valve and revealed diffused hypocaptant thickening at the interatrial septum with a fistulous path . Thus, the diagnosis of infective endocarditis was confirmed by two major criteria: blood cultures and an echocardiography positive for mitral valve vegetation and patch fistula. Considering the high embolic risk of the mitral vegetation, we proceeded with a full-body CT scan that showed multiple septic emboli interpreted as abscesses at the cerebral, splenic, hepatic, renal and pelvic muscle level . The size of the mitral valve vegetation could represent only a remnant of the initial vegetation because of several embolizations. The endocarditis team emphasized the need for cardiac surgery, i.e., repair or replacement of the mitral valve and a patch replacement for the atrial septum, and an urgent need to start antibiotic treatment with oxacillin, rifampicin and gentamicin. Brain abscesses were clinically silent and did not require surgical treatment, only neurological and CT monitoring. After two weeks of antibiotic treatment, the clinical course was unfavorable, with a persistent infection, fever and inflammatory syndrome; therefore, we repeated the CT scan, which showed the extension of the splenic abscess. Consequently, we proceeded to a splenectomy, which was without complications. The hepatic abscesses, which explained the initial symptomatology with severe abdominal pain, developed favorably and decreased in number and extent. After 56 days of hospitalization and antibiotic treatment, the CT scan revealed resorption of the cerebral, renal, hepatic and muscle abscesses. The patient was discharged in good clinical and biological condition. The triple antibiotic therapy lasted for 6 weeks and the blood cultures became negative after 1 week. Although the mitral valve had severe regurgitation and the atrial patch had an abscess and a fistula, the patient refused cardiac reintervention. Although the entire multidisciplinary team advocated surgical treatment, the patient categorically refused it. Abscess sterilization remains an open issue, the outcome of which is difficult to predict or control. The patient decided to check their evolution with CT and to initiate any additional antibiotic therapy depending on their clinical condition. At the 4-month follow-up, he had no further hospitalizations or cardio-embolic events. The latest imagistic follow-up was at this time, showing no organ abscesses but with persistent vegetation at the level of the surgical patch. 3. Discussion 3.1. Current Reports and Actual Evidence It is well known that the risk of infective endocarditis is 15-140 times higher for patients with congenital heart defects than in the rest of the population . Moreover, it has recently been shown that there is clear delay in establishing IE diagnosis amongst CHD patients in Central and South-Eastern European countries . However, relative to other congenital diseases, the association between ASD and IE is very rare, at only around 0.4% . From a surgical point of view, there are two main sources of traditional patches for repairing intracardiac defects. One is the auto pericardial patch, with a good histocompatibility and tissue activity, but it is inaccessible and weak. The other one is the Dacron patch, which has a thin texture and a strong tension and elasticity, and is prone to anastomotic deformation, thrombosis, embolism, hemolysis and infection after repair . In the CONCOR registry, the incidence rate of IE in ASD was increased by the presence of other lesions that rendered them vulnerable to IE, for example, either valvular, particularly on the mitral valve, or small ventricular septal defects . Removal of all infected tissue is the major objective of early surgery in IE. The published European recommendations on surgical indications for IE do not strictly apply to the population of children and adults with CHD . To date, there has been no explicit recommendation for these patients. The timing of IE surgery has shifted to early intervention. In a randomized study, Kang et al. found that surgery as soon as 2 days after diagnosis resulted in a lower rate of death, embolic events or recurrence of IE after 6 months . Surgery during the first 7 days has been linked to a lower rate of mortality . As in our case, the residual mitral regurgitation after cleft repair was in the initial lesion where the vegetation was attached, and from here the infection spread to the interatrial septum patch. The fact that the patient remained with residual mitral insufficiency after the operation argues in favor of the cleft area being only partially sutured and it being the most likely initial area of bacterial seeding. Indeed, a population-based study following up patients with CHD for IE for up to 30 years reported that the incidence of endocarditis after repair of primum ASD with a mitral cleft was 1.8/1000 patient-years, carrying a moderate to low risk, while the incidence of endocarditis after repair of secundum ASD was zero . However, in a study by Morris et al., a significant proportion of patients were lost at follow-up . Contrastingly, Snygg-Martin et al. reported an 8.5% cumulative incidence of CHD IE at 87 years of age compared with 0.7% in matched controls, but with the lowest IE incidence was in patients with ASD (27.8 per 100,000 person-years) . These findings reflect the rarity of these cases. The particularity of our case consists of the consecutive seeding of the atrial patch many years apart, when the patch was completely endothelialized and, regardless, all of the interatrial septum was a poorly vascularized structure. In a study focusing on 13 autopsy cases of Dacron patch IE, the occurrence of IE on the surgical patch of the interatrial septal defect was detected in only one patient; the rest suffered from IE of the patch covering the interventricular septum . The IE was more often found early than late, at approximately 30 days postoperatively, and was associated with a sternal site infection in 8 of the 10 patients . Their latest case of IE occurred about 4 months after operation , and practically all cases were considered as periprocedural IE--a fact that gives our case a peculiarity. Interestingly, in 77% of cases, IE was not isolated on the Dacron patch but involved a neighboring cardiac structure (aortic valve, mitral valve, tricuspid valve, etc.) . In 55% of cases, the incriminating bacteria was Staphylococcus aureus , in accordance with a parallel review of 21 cases of IE of percutaneous ASD closure devices, where 57% of patients had the same bacteria in their blood cultures . In any case, correction of a congenital defect (especially with residual lesions), either simple or complex, carries an inevitable risk of bacterial colonization of the new structures, which is difficult to treat and diagnose and occasionally leads to IE . In some cases (such as our report), medical treatment is unlikely to be able to eradicate infection without surgery. We found a similar case of tardive IE on the surgical patch on the ASD in the literature. This was associated with a cerebral abscess which, unlike our case, required surgical drainage. TEE showed a shunt at atrial level suggestive of atrial septal patch dehiscence without vegetation. In this case, the diagnosis was completed with 18 -PET/CT, which detected the existence of a metabolic hyperactivity compatible with interatrial septal endocarditis . Regarding the brain abscesses, surprisingly, the neurological evolution in this case was completely asymptomatic, with the brain abscess resorbed under antibiotic treatment. Brain examinations, either CT or IRM, are crucial for the diagnosis of brain abscesses, as they are often clinically silent but can significantly worsen the prognosis . In case of brain abscesses, surgery is often delayed and based on serial imaging and clinical progression, as the treatment for brain abscess is first and foremost with antibiotics to include MRSA coverage if the organism is not known . The etiology with MSSA is positively correlated with the formation of emboli, most frequently cerebral, and mortality due to specific virulence factors and also its ability to elicit extensive myocardial tissue destruction . The case of our patient has shown that antibiotic therapy can eliminate multiple septic metastases, and that in patients in whom surgery is associated with high-risk or is refused, a "conservative" treatment actually addresses the etiopathogenetic cause of this particular germ. This of course comes with a significant and extremely unpredictable trade-off; namely, the risk of relapse and irreversible destruction of some cardiac structures. Finally, regarding the potential portals of entry of MSSA, skin infection represents the most possible cause. It is well known that in approximately one-half of patients with MSSA, no portal of entry can be documented. In this case, acne represented the only possible entry that could be detected . "Hidden" entry portals for IE could be discrete skin lesions in patients with diabetes mellitus and peripheral artery disease or micro-organisms of gastrointestinal origin (gastrointestinal polyps, tumors, etc.) . We presented this rare case of surgical atrial patch endocarditis, which we diagnosed based on the TEE exam, actually starting from the TTE that showed vegetation at the level of the mitral valve. As a result of the multiple septic emboli, the size of the vegetation at the time of presentation could represent only a remnant of the original vegetation. During the TEE examination, there was an insignificant hemodynamic shunt at the atrial level, which appeared to be as a result of endocarditis, in contrast to previous TEEs, where the appearance of the septum/patch was linear, thin, and uniform, without a residual shunt. In the current TEE, the septum was thickened with echo-lucent spaces and mobile formations which, in the clinical context of IE, we interpreted as vegetations, abscesses and fistulous tracts. Although the CT examination does not provide additional information regarding the valvular damage in endocarditis, it was essential in this case for the diagnosis of atrial septal patch infection in addition to the description of the multiple septic emboli. Indeed, after the 6-week-course of antibiotics, a cardiac MRI could have evaluated more precisely the size of the fistula and the level of inflammation around the affected structures, or a PET/CT at follow-up could have evaluated any hyperactivity. In this case, with infection at the atrioventricular level and extension into the ostium primum area of the atrial septum, a surgical approach was considered extremely difficult due to the need to replace the mitral valve and the patch in conditions of swollen, friable and infected tissue and the particular anatomy of the atrioventricular canal defect. We focused mainly on the imaging diagnosis, precisely because of the rarity of this type of endocarditis and also because of the role of multimodality imaging in the complete evaluation and deciding the therapeutic management of this complex case. 3.2. Future Outlooks The authors acknowledge that mitral valve and early corrected ASD IE are not new pathologies, and indeed, similar cases have been reported. The interplay between the two structures has been demonstrated, but very late IE of a healed septal patch (decades apart) involves a different bacterial seeding mechanism, and the cases are extremely rare with surgical corrections and slightly more common with occluded devices , probably due to partial endothelization of the metal frame. The novelty of our case comes from the interval of more than 30 years between the operation and the infective episode and that, until the present time, it was known that surgical patch closure of atrial defects does not pose a risk for IE. Undoubtedly, residual valvulopathies play an important role , but the seeding risk and mechanism of the atrial patch remains unknown. In patients with partial or complete atrioventricular canal defects and mitral clefts, residual mitral insufficiency can occur immediately after surgery or at a distance due to the degeneration of the sutures at the level of the malformed valve, which automatically increases the risk of IE. In the present case, during the follow-up, a re-intervention was recommended to the patient to correct or replace the mitral valve. There are no guidelines for the prevention, diagnosis or management of this complication. Re-intervention is particularly demanding and complete medical sterilization is almost impossible to achieve. Injecting a radiolabeled analog of glucose during PET/CT may be indicated in all corrected CHD patients with suspected IE to detect any inflammatory leukocytes on the corrected cardiac structures early. Considering the late infectious episode (33 years after the intervention), we recommend the implementation of IE prophylaxis even in the absence of residual atrial shunt and residual mitral insufficiency in this category of patients. The deficit in the embryonic development of the heart skeleton (endocardial cushion defect) can favor the propagation of the mitral valve-atrial septum infection, making curative surgical re-intervention of the extensive infection extremely difficult. 4. Conclusions IE should always be suspected in patients with fever and corrected CHD. In our patient, the complete corrected atrioventricular canal defect with residual mitral regurgitation represented the initial infected tissue lesion. Multimodality imaging (TTE, TEE and cardiac CT) is essential in the diagnosis and management of surgical atrial patch endocarditis. Author Contributions Conceptualization, A.S., A.A., A.D.-P. and D.E.G.; methodology, R.T.; software, A.D.-P.; validation, A.S., D.D.A. and M.S.; formal analysis, S.M.; investigation, D.D.A. and A.M. resources, A.S.; data curation, A.S. and D.E.G.; writing--original draft preparation, A.S.; writing--review and editing, A.A. and A.D.-P.; visualization, A.M. and R.T.; supervision, S.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Informed consent was obtained from the subject involved in the study. Written informed consent has been obtained from the patient to publish this paper. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 TTE: vegetation on the mitral valve prolapsing in LA (arrow). Figure 2 TEE: vegetation on the anterior mitral valve in the cleft area (arrow). Figure 3 TEE: color Doppler revealing severe mitral regurgitation. Figure 4 (A,B) TEE: abscess on the right side of the atrial surgical patch with ecolucent spaces (arrows). Figure 5 (A,B) Cardiac CT: interatrial septal patch abscess with a fistulous path (inside circles). Figure 6 Full-body CT scan showing multiple septic emboli. Upper left panel: the arrow shows abscesses at the cerebral level (brain abscesses: ring enhancing lesions with slightly perilesional oedema); upper right panel: large splenic abscess (arrow); lower left panel: liver structure with multiple subcapsular peripheral areas, imprecisely delimited with low contrast uptake (budding abscesses) (arrows), plus a right renal abscess (arrow); right lower panel: pelvic muscle abscess (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). 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PMC10000393 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051117 foods-12-01117 Article Phyto-Assisted Synthesis of Nanoselenium-Surface Modification and Stabilization by Polyphenols and Pectins Derived from Agricultural Wastes Golub Nikolina Methodology Formal analysis Data curation Writing - original draft 1 Galic Emerik Methodology Formal analysis Data curation 2 Radic Kristina Methodology Data curation 1 Jagodic Ana-Maria Formal analysis 1 Predovic Nela Formal analysis 1 Katelan Kristina Formal analysis 1 Tesla Lucija Formal analysis 1 Pedisic Sandra Writing - review & editing 3 Vinkovic Tomislav Conceptualization Resources Writing - review & editing Project administration Funding acquisition 2 Vitali Cepo Dubravka Conceptualization Resources Writing - original draft Writing - review & editing Supervision 1* Benito Jose M. Academic Editor 1 Faculty of Pharmacy and Biochemistry, University of Zagreb, 10000 Zagreb, Croatia 2 Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia 3 Faculty of Food Technology and Biotechnology, University of Zagreb, 10000 Zagreb, Croatia * Correspondence: [email protected] 06 3 2023 3 2023 12 5 111727 1 2023 26 2 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 ). Raw and purified mandarin peel-derived pectins were characterized and combined with olive pomace extract (OPE) in the green synthesis of selenium nanoparticles (SeNPs). SeNPs were characterized in terms of size distribution and zeta potential, and their stability was monitored during 30 days of storage. HepG2 and Caco-2 cell models were used for the assessment of biocompatibility, while antioxidant activity was investigated by the combination of chemical and cellular-based assays. SeNP average diameters ranged from 171.3 nm up to 216.9 nm; smaller SeNPs were obtained by the utilization of purified pectins, and functionalization with OPE slightly increased the average. At concentrations of 15 mg/L SeNPs were found to be biocompatible, and their toxicity was significantly lower in comparison to inorganic selenium forms. Functionalization of SeNPs with OPE increased their antioxidant activity in chemical models. The effect was not clear in cell-based models, even though all investigated SeNPs improved cell viability and protected intracellular reduced GSH under induced oxidative stress conditions in both investigated cell lines. Exposure of cell lines to SeNPs did not prevent ROS formation after exposure to prooxidant, probably due to low transepithelial permeability. Future studies should focus on further improving the bioavailability/permeability of SeNPs and enhancing the utilization of easily available secondary raw materials in the process of phyto-mediated SeNP synthesis. selenium nanoparticles pectin olive pomace extract green synthesis antioxidant activity Croatian Science FoundationHRZZ-IP-2018-01-8119 European Regional Development FundKK.01.1.1.02.0021 Croatian Science FoundationHRZZ-DOK-2018-09-1298 HRZZ-DOK-2021-02-6801 This work was supported by the Croatian Science Foundation [grant number HRZZ-IP-2018-01-8119] and the FarmInova project [grant number KK.01.1.1.02.0021], funded by the European Regional Development Fund. The work of doctoral students Emerik Galic and Nikolina Golub was fully supported by the "Young researchers' career development project--training of doctoral students" of the Croatian Science Foundation [grant numbers HRZZ-DOK-2018-09-1298, HRZZ-DOK-2021-02-6801]. pmc1. Introduction Selenium (Se) is an essential metalloid involved in different physiological functions that have been attributed largely to its presence in selenoproteins in the form of the 21st amino acid, selenocysteine. Se modulates a wide spectrum of biological processes: redox signaling, cellular differentiation, immune response, cellular response to oxidative stress and protein folding . Its intake is extremely variable across the world due to significant differences in the content and availability of the soil and can result in both Se deficiency and excessive intake. Se deficiency affects approximately 1 billion people worldwide. Usually, it occurs in areas where soil selenium content is poor as well as in certain pathological conditions (patients receiving parenteral nutrition, cirrhosis patients due to ineffective selenomethionine metabolism, low-birth-weight infants etc.). It has been implicated in the pathogenesis of cardiovascular disease, infertility, myodegenerative diseases and cognitive decline . In food and dietary supplements, Se exists in several forms, including selenide (Se2-), selenite (SeO32-), selenate (SeO42-), selenocysteine (Se-Cys), selenometheonine (Se-Met) and elemental nanoselenium . Elemental nanoselenium has gained a lot of attention recently since Se nanoparticles (SeNPs) have been reported to exert higher bioavailability, higher biological activity and lower toxicity compared to organic and inorganic Se forms . Therefore, they are considered a promising material for many applications, particularly in the field of nutraceuticals and biomedicine . SeNPs can be synthesized from inorganic precursors using physical, chemical, or biological synthesis approaches (green synthesis). Physical and chemical processes are often energy-demanding and require the use of toxic chemicals that produce environmental hazards resulting in several application-based limitations in the field of pharmaceuticals/nutraceuticals. Therefore, green syntheses that use natural reducing agents (plants, microorganisms, enzymes, etc.) to change the redox potentials of metals/metalloid-oxyanions and convert them into their nano form are being increasingly investigated. An innovative, quick, simple and cheap approach is using the plant extracts as the source of bioactive compounds for reduction of selenium salts to nanoforms and their subsequent stabilization/surface modifications . Given the increasing demand and numerous areas of possible application of SeNPs, it is necessary to focus on identification and utilization of universally available and sustainable sources of reducing/stabilizing compounds to be used in the novel synthesis processes. Organic agricultural wastes (OAW) represent an underutilized but universally available rich source of various bioactive compounds (phenolic compounds, terpenes, glucosinolates, dietary fiber, saponins, pigments, etc.) that exert a wide range of biological activities and have established biomedical applications. Considering the current acute climate, ecological crises and constant growth of population, global imperatives are becoming the adoption and successful application of different principles of circular economy (including the reuse and revalorization of OAW) . In the last decade, the applicability of utilizing OAW in the phytofabrication of nanoparticles has been investigated for the synthesis of Fe-, Ag-, Au-, Pd-nanoparticles . The main goal of this work was to investigate the possibilities of utilization of OAW-derived compounds for obtaining SeNPs with satisfactory physicochemical characteristics. purified pectin fractions extracted from mandarin peel were used as stabilizing agents, and polyphenol-rich olive pomace extract (OPE) was used for selenite reduction and SeNP surface modification. Raw materials were chosen primarily based on the availability of mandarin peel and olive pomace in Croatia as part of general attempts to improve OAW reuse and management. Besides, commercially available pectin has already been successfully applied as stabilizing agent in the formulation of metal nanoparticles, including one work that focused on SeNP . Recent application of OPE in the synthesis of polysorbate-stabilized SeNPs resulted in improved physicochemical characteristics and higher gastrointestinal bioaccessibility . Results obtained within this research will contribute to the current emerging field of green approaches in nanoparticle synthesis, particularly in terms of the reuse of OAW as the source of bioactive components to be utilized in innovative nutraceutical formulation. 2. Materials and Methods 2.1. Preparation and Chemical Characterization of OPE and Pectin Fractions from OAW The production and chemical composition of OPE has been described in detail in previous publications . Briefly, dried, milled and defatted olive pomace (8 g) was extracted with 60% (v/v) ethanol-water mixture (400 mL) in a shaking water bath at 70 degC for 2 h. The obtained extract was freeze-dried, ground into a fine powder and stored at -20 degC. For pectin extraction, a mixture of local Satsuma mandarin peel (Citrus unshiu Marc.) and peel from store-bought mandarins was dried at 50 degC for 48 h in an oven dryer (Inko, Zagreb, Croatia), milled and sieved to a particle size of 0.8 mm. The commercial pectin used as the reference was Pectin E440 (Esarom, Austria). Extraction of pectin from mandarin peel was conducted as described by Casas-Orozco and co-workers with some modifications. Ten g of defatted mandarin peel was extracted with 200 mL of 1% citric acid monohydrate (pH 1.5) for 2 h at a temperature of 85 degC, and the reaction mixture was filtered while hot through cotton gauze and filter paper. To precipitate interferents that could affect the purity of the pectin extract, the filtered samples were placed in a refrigerator at +4 degC for 24 h and filtered once again. Pectin precipitation was done by adding twice the amount of 96% ethanol relative to the amount of citric acid. The filtrate and ethanol solution was mixed for 2 h on a magnetic stirrer and placed in the refrigerator overnight to allow complete pectin precipitation. Raw pectin fractions were obtained by simple filtration, followed by drying at room temperature, grinding and storing at 4 degC. Part of raw pectin fractions was additionally washed with 63% (v/v) ethanol four times to remove the remaining soluble impurities and to obtain purified pectin fraction. Obtained pectin fractions were characterized regarding their equivalent mass (EM), methoxyl content (MC), degree of esterification (DE) and galacturonic acid content (GLA) according to standard analytical procedures . 2.2. Synthesis of SeNPs Prior to SeNP synthesis, lyophilized OPE was dissolved in ultrapure water to give a 10 mg/mL solution and filtered through a 0.45 mm polyethersulfone (PES) syringe filters (Macherey-Nagel, Duren, Germany). To synthesize SeNPs, 15 mg of raw or purified mandarin peel pectin was weighed directly into a 50 mL Erlenmeyer flask, 28 mL ultrapure water (23 mL for functionalized samples) was added under magnetic stirring (350 rpm), followed by the addition of 1 mL of ascorbic acid (1 M)--acting as a reducing agent and 5 mL of OPE (1%) to the functionalized samples. Finally, 1 mL of Na2SeO3 (0.1 M) was added dropwise, changing the color of the reaction mixture to red. When the reaction was completed (after 20 min), the reaction mixture was purified from the remaining reactants by dialysis. The end of cellulose dialysis tubing (D9527-100FT, Sigma-Aldrich, St. Luis, MO, USA) was folded twice, closed with a sealing clip (Bevara 6 cm, IKEA, Delft, Netherlands), filled with the reaction mixture, closed and submerged in a beaker filled with 950 mL ultrapure water. The dialysis was performed according to a previously described procedure . The composition of non-functionalized SeNPs stabilized with raw pectin (M) and purified pectin (Mpr) in comparison to OPE-functionalized samples stabilized with raw pectin (Mf) and purified pectin (Mprf) are presented in Table 1. 2.3. Physicochemical Characterization and Stability of SeNPs The measurements of hydrodynamic diameter (dH) and zeta potential (z) of the SeNPs were conducted at 25 degC by dynamic light scattering (DLS) and electrophoretic light scattering (ELS) respectively, by using a Zetasizer Ultra (Malvern Instruments, Malvern, UK). Data analysis was carried out using Zetasizer software 2.2 (Malvern Instruments, Malvern, UK). The size distributions and z of the samples were measured in a standard disposable cuvette (DTS0012) and disposable folded capillary cell (DTS1070), respectively, after diluting the samples in ultrapure water if needed, and are reported as an average value of 3 measurements. For the stability measurement, SeNP suspensions were stored at 4 degC in the dark for 30 days. Measurements of hydrodynamic diameter and zeta potential were conducted on the 2nd, 5th, 9th, 20th and 30th days of storage. For measuring the pH value of the samples, a pH meter (SevenMulti, Mettler Toledo, Schwerzenbach, Switzerland) was used. 2.4. Measurement of SeNP Antioxidant Activity by Chemical Methods Antioxidant activity was assessed by the measurement of total reducing capacity (TRC) by the Folin-Ciocalteu method (FC) and Trolox radical scavenging activity (TEAC) by the colorimetric assay originally described by Re and co-authors (1999) . For the TRC measurement, 20 mL of SeNPs (or ultrapure water as blank) was mixed with 50 mL 10% water solution of FC reagent (Sigma-Aldrich, St. Louis, MO, USA) in a 96-well plate. After 5 min of incubation, 160 mL of 0.7 M sodium carbonate was added to each well, and the plate was incubated for 30 min at 37 degC. The absorbance was measured at 750 nm using a Victor X3 plate reader (Perkin Elmer, Waltham, MA, USA). A range of concentrations of gallic acid was prepared to obtain a gallic acid standard curve (3-100 mg/L), and the results are expressed as gallic acid equivalents per mmol of selenium (mg GAE/mmol Se). For the measurement of TEAC against the 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic) acid radical cation (ABTS+), a radical solution was prepared by mixing equal volumes of 7 mmol/L of ABTS and 2.45 mmol/L of potassium persulfate solution. After the 12-h incubation in the dark, the ABTS+* solution was diluted to give an absorbance of 0.70 +- 0.02 at 750 nm. The reaction was conducted in a 96-well plate by mixing 20 mL of the sample/Trolox(r) standard/blank and 200 mL of adequately diluted ABTS+*. The absorbance was measured at 750 nm after 90 s of incubation at 30 degC. The percentage of quenching the absorbance was calculated according to Equation (1): A = (A0min - A3min)/A0min x 100 (1) A calibration curve was generated by plotting different Trolox(r) concentrations against their respective absorbance-quenching percentages. The antiradical efficiency was expressed as mg of Trolox(r) equivalents per mmol of selenium (mg TE/mmol Se). 2.5. Cell Cultures Human colorectal adenocarcinoma (Caco-2) and human hepatocellular carcinoma (HepG2) cells were used for SeNP biocompatibility/antioxidant activity investigation. Caco-2 cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM; Sigma-Aldrich, St. Louis, MO, USA) supplemented with 20% fetal bovine serum (FBS; Capricorn Scientific, Ebsdorfergrund, Germany), 1% antibiotic/antimycotic (A/A; Sigma-Aldrich, St. Louis, MO, USA), 1% non-essential amino acid (NEAA; Capricorn Scientific, Ebsdorfergrund, Germany) and 4 mM L-glutamine (Sigma-Aldrich, St. Louis, MO, USA). The cells were detached from the flask surface using 1x trypsin (2.5% in HBSS w/o Ca, Mg; Lonza, Basel, Switzerland) diluted in ethylenediaminetetraacetic acid (EDTA; E8008 Sigma-Aldrich, St. Louis, MO, USA) solution and seeded in 96 well plates in a concentration of 20,000 cells per well. The number of cells was estimated using a hemocytometer (Neubauer, Germany). After the seeding, the cells were incubated for 48 h in a CO2 incubator (37 degC, 5% CO2). The HepG2 cells were cultured in Eagle's Minimum Essential Medium (EMEM; Sigma-Aldrich, St. Louis, MO, USA) supplemented with 10% FBS, 1% 1% A/ and 4 mM L-glutamine. 2.5.1. Measurement of SeNP Biocompatibility The toxicity of SeNPs in cell lines was investigated by calculating the respective IC50 values in the MTT test, and the obtained results were used for the identification of non-toxic concentrations to be used in further investigation of antioxidant efficiency in cell culture models. Fresh medium was added to the wells, followed by the addition of SeNPs. The cells were incubated with SeNPs for 24 h. After that, SeNPs were removed, and cells were washed once with PBS. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) reagent (Carbosynth Limited, Compton, UK) was added in a concentration of 0.5 mg/mL (diluted in PBS), and cells were incubated for 3 h at 37 degC, 5% CO2. Dimethyl sulfoxide (DMSO) was used to dissolve formazan crystals, and the plates were shaken for 45 min. The absorbance was measured at 530 nm using a Victor X3 plate reader. Additionally, the potential of SeNPs to initiate reactive oxygen species (ROS) formation was assessed by 2',7'-dichlorofluorescin diacetate (DCFH-DA) assay and compared to the effects of known prooxidant tert-butyl hydroperoxide (100 mM) (tBOOH; Sigma-Aldrich, St. Louis, MO, USA) . For that purpose, cells were incubated with 25 mM DCFH-DA (Sigma-Aldrich, St. Louis, MO, USA) for 45 min. The excess dye was then removed, and cells were washed with PBS and treated with SeNPs for an additional 3 h. The fluorescence was measured at 485/535 nm. For the relative quantification of GSH, a monochlorobimane (mBCl) assay was conducted. The assay is based on a measurement of fluorescence that results from a redox reaction between GSH and mBCL reagent . The culture medium was removed, followed by the addition of the fresh medium. Afterward, the cells were incubated with SeNPs/sodium selenite. Negative controls were incubated with an equivalent volume of ultrapure water that was used for SeNPs' dilution, and positive controls were incubated with 100 mM of tBOOH in the wells. The treatment solutions were removed after 3 h; cells were washed with PBS and incubated with 40 mM mBCl reagent (Sigma-Aldrich, St. Louis, MO, USA) in PBS for 30 min. The fluorescence intensity was measured at 355/460 nm using a Victor X3 plate reader. 2.5.2. Measurement of SeNP Antioxidant Activity in Cell Models The efficiency of SeNPs against chemically induced oxidative stress was investigated by measuring the viability of the cells previously incubated with SeNPs for 24 h and after exposure to tBOOH (acting as a prooxidant). Protective effects of SeNPs were measured in terms of cell viability, which was assessed by the MTT test, intracellular ROS formation by the DCHF-DA method and intracellular GSH depletion by the mBCl method, as described previously. For the DCHF-DA method, SeNPs were removed from the wells prior to the addition of tBOOH. 2.6. Measurement of Se Content Selenium content was determined by flame atomic absorption spectrometry (FAAS) on Analyst 800 atomic absorption spectrometer (Perkin Elmer Instruments, Norwalk, CT, USA) with deuterium background correction under optimized measurement conditions with hollow cathode lamp (Perkin Elmer Lumina Single Element Hollow Cathode Lamp) and at optimum flame height (air-acetylene). SeNP samples were wet digested in the microwave digestion unit (Ethos Easy, Milestone Systems, Brondby, Denmark) using HNO3 and H2O2 according to the previously described procedure . 2.7. Data Analysis Investigations were conducted in duplicates (characterization of pectin) and quadruplicates (other analyses), and the obtained results were expressed as average +- standard deviations. Obtained results were compared by one-way analysis of variance (ANOVA), and in the case of significant differences, a post hoc Tukey's multiple comparison test was conducted. The differences between group averages were considered statistically significant if p < 0.05. Data were processed using GraphPad(r)Prism 6 Software (San Diego, CA, USA) and Microsoft Office Excel (Redmond, Washington, DC, United States). 3. Results and Discussion The main goal of the conducted research was to investigate the possibilities of utilizing added-value products obtained from OAW (OPE and pectins extracted from mandarin peel) in the green synthesis of SeNPs that would be characterized by satisfactory physicochemical characteristics, biocompatibility and improved antioxidant activity achieved through nanoparticle (NP) surface functionalization. Additionally, the investigation will provide novel and original insight into the physicochemical characteristics of mandarin-derived pectins, which have been very scarcely investigated. The organization of conducted experiments is schematically presented in Figure 1. 3.1. Physicochemical Characterization of Mandarin Peel-Derived Pectins For the plant-assisted green synthesis of SeNPs, mandarin peel-derived pectins were used as stabilization agents, while OPE-derived polyphenols were used for achieving SeNP surface modification that might additionally improve the functionality of obtained formulations. OPE was obtained by solvent extraction, according to the previously described procedure . OPE s composition is characterized by a high content of polyphenols that varies depending on the chemical composition of the olive pomace, the applied method of extraction and the drying process. In our laboratory, the obtained yields were usually in the following range: total phenols: 4-10 g/100 g dry extract; hydroxytyrosol: 60-100 mg/100 g dry extract; tyrosol: 15-50 mg/100 g; and oleuropein: 2-30 mg/100 g dry extract . The chemical characteristics of raw and purified mandarin pectins are presented in Table 2. It is obvious from the presented yield data (12.8%) that dried mandarin peel can be considered a valuable source of pectin, as compared to other citrus sources; notable, classic solvent extraction was applied in this work; the yields could probably be additionally improved by further optimization of extraction method/process . Originally, low EM pectins were obtained (780 g/mol); however, polymerization (that could be visualized as gel formation) occurred during the purification process, resulting in a significant EM increase (2018.8 g/mol). Obtained data are generally consistent with literature indicating low EM values for raw pectin from different citrus sources (orange and grapefruit) ranging from 381-749 g/mol , where lower values obtained by other authors can be explained by species-differences, lower pH or higher temperatures applied in the extraction process. Both raw and purified pectins can be considered highly methoxylated and, as such, suitable for sugar-containing and acidic products but with limited gelling properties. Obtained pectins were highly esterified, and the degree of esterification was significantly positively affected by the purification process (69.1% in raw pectin and 86.6% in purified pectin). This value is significantly higher compared to DE obtained for orange grapefruit-derived pectins . The content of galacturonic acid in analyzed samples was satisfactory (74.8% in 69.2% in purified pectins). It reflects the purity of pectin and should be at least 65% if pectins are to be used as food additives or pharmaceutical excipients. This is significantly higher compared to the values obtained for grapefruit peel-extracted pectins (60.95%) . 3.2. Physicochemical Characterization of SeNPs The green synthesis approach for obtaining NPs is a promising area in nanotechnology because it is focused on the development of eco-friendly processes that result in minimizing or even eliminating the use of toxic and hazardous chemicals. In this work, the focus has also been set on using naturally occurring biodegradable materials obtained from secondary and easily available raw materials (mandarin peel). To be utilized for biomedical or food applications, NPs need to possess particular functional and structural properties that distinguish them from discrete molecules or bulk materials. Depending on the raw materials used in the synthesis process and the applied preparation method, a large variety of NP types exist that differ significantly according to their characteristics . The major parameters that determine the basic characteristics of NPs are the particle size and zeta potential. Particle size is one of the main determinants of their bioavailability and biodistribution. Surface charge expressed as the zeta potential is a marker of long-term stability and an indicator of surface characteristics and the related adsorption phenomena . The average size of obtained SeNPs (expressed as hydrodynamic diameter) and zeta potential is presented in Table 3. Obtained diameter values ranged from 171.3 nm (Mpr) up to 216.9 nm (Mf)--values were significantly higher in samples obtained with raw pectins and were slightly increased by functionalization with OPE. The size distribution of the nanoparticles is often the key to their specific, desired physical and chemical properties. Smaller NPs have a relatively large surface area as compared to larger ones; this increases the interaction with biological elements and consequently trigger more toxic and adverse effect, particularly those < 100 nm . Therefore, for food application, NPs with diameters > 100 nm would be desirable. On the other hand, the NP size significantly influences the transmembrane permeability and its interaction with mucus, consequently affecting bioavailability. According to available data, NPs with diameters <= 200 nm have satisfactory bioavailability; with further diameter increase, bioavailability is significantly decreased. Investigations show that smaller-size NPs (< 200 nm) are easily reaching the firm part of the mucus layer that is resistant to removal by shear. Also, the cellular uptake and uptake pathway of particles are better for NPs < 200 nm . Considering all of the above, the target size of NPs for food/dietary supplement application would be 100-200 nm which makes purified mandarin peel-derived pectins more suitable for the formulation of SeNPs. The polydispersity indexes of the obtained SeNPs ranged from 0.19-0.25, pointing to narrow, uniform particle-size distribution. Functionalization with OPE significantly decreased the polydispersity index of SeNPs stabilized with raw pectin, but it didn't affect SeNPs stabilized with purified pectin fraction. As presented in Figure 2A, the average hydrodynamic diameter decreased during storage. The most notable decrease occurred in non-functionalized SeNPs stabilized with raw pectin (M: 84.73 nm decrease in size), and functionalization with OPE contributed to achieving greater stability (Mf: 38.57 nm decrease in size), while the application of purified pectin resulted in the formation of more stable formulations regardless of functionalization (36.03 nm and 38.13 nm decrease in size in Mpr and Mprf respectively). Zeta-potential values have long served as indicators of stability against aggregation or deposition, where values above +-30 mV were customarily considered moderately stable against aggregation due to the existence of electrostatic repulsive forces sufficient to prevent aggregation. Zeta-potential values of analyzed samples ranged from -22.3 to -23.1 mV and were not significantly affected by the type of pectin utilized in the synthesis process or OPE functionalization. With absolute values lower than 30 mV, they could be considered potentially unstable; however, it is important to understand that stabilization is also to be achieved by steric stabilization . Zeta potential remained relatively unchanged during 30 days of storage . With changes in the values of zeta potential and hydrodynamic diameter, a visual assessment on the 30th day of the analysis also showed that all the samples became cloudy. 3.3. Biocompatibility of SeNPs The increasing use of SeNPs will inevitably increase environmental exposure in the future. This highlights the importance of biocompatibility assessments that are nowadays mostly conducted by the spectrophotometric quantification of different dyes commonly used in cytotoxicity assays, such as MTT. Additionally, determining the IC50 of SeNP is important in the view of determining non-toxic concentrations of NPs to be used in the investigation of biological activity and mechanisms of action in cell-based models . As presented in Figure 3A,B, all investigated nanoparticles had lower toxicity compared to inorganic selenium, which showed significantly lower IC50 values, consistent with available literature data . Obtained results need to be interpreted with some caution since it has been shown that redox-active metals can catalyze the reduction of tetrazolium salts, so formazan can be generated either in the presence of cellular NAD(P)H or perhaps in the presence of sodium selenite . The possible interfering effect of remaining inorganic selenium in SeNP suspensions has been reduced to a minimum by applying previously validated purification of SeNPs by dialysis . Additionally, the size and coating of particular NPs can alter the magnitude of the reaction kinetics, as has been proven recently for silver nanoparticles and has not been investigated in detail in this work . The positive effect of the utilization of purified pectins as stabilization agents was visible in both cell lines-protective effects of OPE functionalization were also visible (except for the case of the Mprf investigated in Caco-2 cells). Bearing in mind the mentioned limitations of the MTT test, the cytotoxicity of SeNPs was additionally investigated in terms of their ability to induce cellular oxidative stress by measuring their impact on ROS formation and intracellular GSH depletion. As presented in Figure 3, the prooxidant activity of SeNPs at a concentration of 15 mg/L was significantly lower in comparison to tBOOH as a known prooxidant and, in the case of GSH depletion, also in comparison to inorganic selenium form. The inability of inorganic selenium to induce intracellular ROS formation at applied concentrations is probably the result of the activity of intracellular defensive mechanisms against oxidative stress occurrence . Considering ROS formation, all investigated SeNPs showed a similar effect that was not affected by the type of pectin used for stabilization nor OPE functionalization in both cell lines. However, as shown in the HepG2 cell line, the negative impact on intracellular GSH depletion, even though low for all investigated SeNPs, was less pronounced in SeNPs stabilized with purified pectins (Mpr and Mprf, respectively), with no observed effects of OPE-functionalization. Such differences could not be detected in Caco-2 cell lines which are in line with literature data indicating that liver cells are particularly sensitive to the toxicity of pharmacological doses of SeNPs, and generally more sensitive to redox-induced stress in comparison to Caco-2 . 3.4. Antioxidant Activity of SeNPs The use of SeNPs in the fields of biomedicine and nutrition is in great part based on their antioxidant activity. Therefore, we were primarily focused on the investigation of this aspect of their biological activity, with special emphasis set on the investigation of the type of stabilization agent used and OPE-functionalization. The first methodological approach used was the measuring of SeNPs direct reducing/antiradical quenching properties, which has already been used and proved useful by other authors . Figure 4 clearly shows the advantages of OPE-functionalization. Non-functionalized SeNPs (M and Mpr) showed significantly lower reducing activity in comparison to OPE-functionalized samples (Mf and Mprf) (13.4 and 10.7 g GAE/mol Se vs. 28.8 and 26.7 g GAE/mol Se, respectively). Similarly, ABTS radical scavenging activity was significantly increased by OPE-functionalization (11.4 and 8.6 g TE/mol Se in M and Mpr vs. 19.3 and 22.1 g TE/mol Se in Mf and Mprf). Our previous investigation showed that chemically synthesized polyvinylpyrrolidone stabilized SeNPs when properly purified, didn't possess significant reducing or radical scavenging capacity . Therefore, the antioxidant activity observed in this work has been mediated by pectins and/or OPE used in the SeNP synthesis process. Namely, recent research showed that citrus peel-derived pectins, particularly those of lower molecular weight, possess significant antioxidant activity and may be useful as a potential natural antioxidant in pharmaceutical and cosmetic industries . As shown in Figure 4, the application of purified pectin in the synthesis process resulted in a slightly decreased reducing potential of SeNPs, but it didn't affect their TEAC radical scavenging capacity. This might be the consequence of the removal of the residues of reductive sugars that might interfere with the determination of the total reductive potential of the samples . Functionalization of SeNP with OPE increased both types of antioxidative activity--FC reducing potential by 115% (M-Mf) and 149.5% (Mpr-Mprf) and TEAC radical scavenging capacity by 67.8% (M-Mf) and 156.9% (Mpr-Mprf). Observed effects can be explained by the surface modification of functionalized SeNPs with OPE-derived polyphenols, whose significant antioxidant potential has been proven previously . Even though fast, simple, cheap and reproducible, chemical-based assays for the determination of antioxidant activity are characterized by numerous limitations and should thus be used only as screening tests and for comparative purposes. Methods used in this work are indirect methods based on the reduction of persistent radical (TEAC) or of inorganic oxidizing species (FC) and therefore measure only one (of many) aspects of antioxidant activity and not even under physiological conditions. It is because of that that they shouldn't be used for predicting antioxidant activity in biological systems. Cell-based methods for measuring antioxidant activity are conducted under simulated physiological conditions and consider additional parameters such as biocompatibility, transepithelial permeability (bioavailability) and interaction with other cell components (enabling the measure of indirect antioxidant activity). Therefore, they provide better insight into the biological relevance of the particular antioxidant and present optimal compromise as being significantly simpler and cheaper and with no ethical issues in comparison to animal-based studies. In this work, the antioxidant activity of SeNPs was investigated in HepG2 and Caco-2 cell lines. The advantage of HepG2 cells is that they express many differentiated hepatic functions and are, as such, most often utilized for biocompatibility, toxicity or metabolism studies . Caco-2 cells were chosen considering the limited bioavailability of SeNPs and the possibility of SeNPs exerting local protective effects on enterocytes. For all experiments, cell lines were incubated with SeNPs for 24 h and then treated with the prooxidant (tBOOH) in a concentration sufficient to produce measurable oxidative stress in the untreated cells. Preincubation of cells with SeNPs protected both, HepG2 and Caco-2 cells from the negative effects of tBOOH, as indicated by viability values presented in Figure 5A,B, regardless of the type of SeNP tested. The most pronounced protective effects were noticed for Mpr (Caco-2) and Mprf (HepG2). On the other hand, none of investigated SeNPs prevented intracellular ROS formation caused by exposure to tBOOH in either of the tested cell lines . It is important to emphasize that the methodological approach of this assay requires the complete removal of the culture medium with SeNPs, prior to tBOOH addition. Therefore, the potential effects are to be completely dependent on the intracellular concentrations of SeNPs, and their absence indicates low transepithelial permeability of investigated SeNPs. A small but statistically significant protective effect of Mf was observed in the Caco-2 cell line, and this might be due to the increased pinocytosis capacity of Caco-2 cells compared to HepG2 cells and, consequently, more significant intracellular SeNP accumulation. Effects on preventing GSH depletion were more pronounced ; the most significant protective effects were obtained with OPE-functionalized SeNPs (Mprf), which is consistent with the results obtained from chemical antioxidant assays. Obtained data justify the utilization of waste-derived bioactive compounds in the synthesis of SeNPs since it contributes significantly to stability, lower toxicity and improved antioxidative activity of SeNPs. Even though literature data on this particular topic is generally scarce, there are several similar investigations available that also prove the usefulness of the phytomediated SeNP synthesis approach for obtaining improved antioxidant activity . However, most available studies are limited to chemical-based assays and are not assessing the problem of limited bioavailability/permeability of SeNPs. Additionally, future studies should primarily focus on the utilization of easily available secondary raw materials that might serve as the sources of bioactive components to be used in the process of phytomediated synthesis as reducing agents, stabilizers and/or surface modifiers. 4. Conclusions Mandarin peel pectins can be combined with OPE in the green synthesis of highly biocompatible SeNPs, less toxic than inorganic selenium form. Utilization of purified pectin fractions in the synthesis process resulted in smaller average diameters and improved stability. Functionalization with OPE significantly increased the direct radical scavenging antioxidant activity of SeNPs, while the effect of functionalization on cell-based mechanisms of antioxidant defense was not clear. All investigated NPs improved Caco-2 cell viability and protected their intracellular GSH concentrations under induced oxidative stress conditions. Acknowledgments The authors would like to thank Gordana Blazinic for providing technical and administrative support. Author Contributions Conceptualization, D.V.C. and T.V.; methodology N.G., K.R. and E.G.; formal analysis, N.G., E.G., A.-M.J., N.P., K.K., S.P. and L.T.; resources, T.V. and D.V.C.; data curation, N.G., E.G. and K.R.; writing--original draft preparation, N.G. and D.V.C.; writing--review and editing, D.V.C., S.P. and T.V.; supervision, D.V.C.; project administration, T.V.; funding acquisition, T.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 Data is contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic presentation of the organization of conducted experiments. Figure 2 Stability of SeNPs during 30 days of storage regarding average diameter (A) and zeta potential (B). Data are means of four parallel investigations. M-SeNPs stabilized with raw pectin; Mpr-SeNPs stabilized with purified pectin; Mf-SeNP stabilized with raw pectin and functionalized with OPE; Mprf-SeNPs stabilized with purified pectin and functionalized with OPE. Figure 3 Cytotoxic activity of SeNPs (15 mg/L) in HepG2 (A,C,E) and Caco-2 cells (B,D,F) as assessed by MTT (A,B), DCFH-DA assay (C,D) and mBCl assay (E,F). Data are presented as mean +- standard deviation of four parallel investigations. Differences among investigated samples were analyzed by one-way ANOVA and post hoc Tukey test. Data in the same column, marked with different letters, indicate significant differences (p <= 0.05). M-SeNPs stabilized with raw pectin; Mpr-SeNPs stabilized with purified pectin; stabilized with raw pectin and functionalized with OPE; Mprf-SeNPs stabilized with purified pectin and functionalized with OPE; control-non treated cells; tBOOH-cells treated with 100 mM tBOOH (500 mM tBOOH for MTT test). Figure 4 Total reducing potential (expressed as GAE) and radical scavenging activity (expressed as TE) of SeNPs. Data are presented as mean +- standard deviation of four parallel investigations. Differences among investigated samples were analyzed by one-way ANOVA and post hoc Tukey test. Data in the same column, marked with different letters, indicate significant differences (p <= 0.05). M-SeNPs stabilized with raw pectin; Mpr-SeNPs stabilized with purified pectin; Mf-SeNPs stabilized with raw pectin and functionalized with OPE; Mprf-SeNPs stabilized with purified pectin and functionalized with OPE. Figure 5 Antioxidant activity of SeNPs (0.1 mg/L) in HepG2 (A,C,E) and Caco-2 cells (B,D,F) as assessed by MTT (A,B), DCFH-DA assay (C,D) and mBCl assay (E,F). Data are presented as mean +- standard deviation of four parallel investigations. Differences among investigated samples were analyzed by one-way ANOVA and post hoc Tukey test. Data in the same column, marked with different letters, indicate significant differences (p <= 0.05). M-SeNPs stabilized with raw pectin; Mpr-SeNPs stabilized with purified pectin; Mf-SeNPs stabilized with raw pectin and functionalized with OPE; Mprf-SeNPs stabilized with purified pectin and functionalized with OPE; control-non treated cells; tBOOH-cells treated with 100 mM tBOOH. foods-12-01117-t001_Table 1 Table 1 Composition of reaction mixtures used for the synthesis of SeNPs. Sample Na2SeO3 (0.1 M) (mL) L-Ascorbic Acid (1 M) (mL) OPE (1%) (mL) Raw Pectin (0.05%) (mg) Purified Pectin (0.05%) (mg) Ultrapure Water (mL) M 1 1 0 15 0 28 Mpr 1 1 0 0 15 28 Mf 1 1 5 15 0 23 Mprf 1 1 5 0 15 23 OPE--olive pomace extract; M-SeNPs stabilized with raw pectin; Mpr-SeNPs stabilized with purified pectin; Mf-SeNP stabilized with raw pectin and functionalized with OPE; Mprf-SeNPs stabilized with purified pectin and functionalized with OPE. foods-12-01117-t002_Table 2 Table 2 Characterization of raw and purified pectin isolated from mandarin peel. Yield (%) EM (g/mol) MC (%) DE (%) GLA (%) Raw pectin 12.8 +- 0.6 a 780.0 +- 4.1 a 9.1 +- 0.1 ab 69.1 +- 2.4 a 74.8 +- 0.8 a Purified pectin 7.9 +- 0.5 b 2018.8 +- 10.2 b 10.6 +- 0.6 b 86.6 +- 3.5 b 69.2 +- 0.7 b Commercial pectin (reference) / 1954.6 +- 52.6 b 8.7 +- 0.2 b 72.5 +- 1.3 a 59.0 +- 1.2 c Data are presented as mean +- standard deviation of two parallel investigations. Differences among investigated samples were analyzed by one-way ANOVA and post hoc Tukey test. Data in the same column, marked with different letters, indicate significant differences (p <= 0.05). EM--equivalent mass; MC--methoxyl content; DE--degree of esterification; GLA--galacturonic acid content. foods-12-01117-t003_Table 3 Table 3 Average diameter, zeta potential and polydispersity index of SeNPs. Sample Average Diameter (nm) Zeta Potential (mV) Polydispersity Index pH M 211.83 +- 2.47 a -22.58 +- 0.91 a 0.25 +- 0.00 a 4.02 Mpr 171.33 +- 2.29 b -22.47 +- 0.90 a 0.20 +- 0.02 a 3.87 Mf 216.87 +- 1.20 c -23.09 +- 0.83 a 0.19 +- 0.03 b 4.11 Mprf 178.93 +- 1.03 d -22.27 +- 0.70 a 0.20 +- 0.02 a 3.98 Data are presented as mean +- standard deviation of four parallel investigations. Differences among investigated samples were analyzed by one-way ANOVA and post hoc Tukey test. Data in the same column, marked with different letters, indicate significant differences (p <= 0.05). 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PMC10000394 | Immune complexity status in the TME has been linked to clinical outcomes in pancreatic ductal adenocarcinoma (PDAC) patients. TME assessments with current cell marker and cell density-based analyses do not identify the original phenotypes of single cells with multilineage selectivity, the functional status of the cells, or cellular spatial information in the tissues. Here, we describe a method that circumvents these problems. The combined strategy of multiplexed IHC with computational image cytometry and multiparameter cytometric quantification allows us to assess multiple lineage-selective and functional phenotypic biomarkers in the TME. Our study revealed that the percentage of CD8+ T lymphoid cells expressing the T cell exhaustion marker PD-1 and the high expression of the checkpoint PD-L1 in CD68+ cells are associated with a poor prognosis. The prognostic value of this combined approach is more significant than that of lymphoid and myeloid cell density analyses. In addition, a spatial analysis revealed a correlation between the abundance of PD-L1+CD68+ tumor-associated macrophages and PD-1+CD8+T cell infiltration, indicating pro-tumor immunity associated with a poor prognosis. These data highlight the implications of practical monitoring for understanding the complexity of immune cells in situ. Digital imaging and multiparameter cytometric processing of cell phenotypes in the TME and tissue architecture can reveal biomarkers and assessment parameters for patient stratification. multiplexed IHC image cytometry spatial analysis PD-1+CD8+T cells PD-L1+CD68+ TAMs pancreatic ductal adenocarcinoma National Natural Science Foundation of China82071811 81871274 81871715 31670905 This research was funded by National Natural Science Foundation of China (82071811, 81871274, 81871715, and 31670905). pmc1. Introduction The PDAC TME is highly heterogeneous and composed of stromal cells and immune cells, including T cells, macrophages, and natural killer (NK) cells. Immunosuppression is supported by preventing T cell infiltration into tumor tissues or inhibiting T cell killing functions . In turn, immunosuppressive macrophages are recruited or the expression of the immune checkpoint (IC) molecules programmed cell death 1 (PD-1) and PD-ligand 1 (PD-L1) is upregulated, which are both common immune mechanisms in PDAC . IC molecules promote tumor evasion by modifying immune cells, e.g., by inactivating immune cells and suppressing the immune response to tumors . Therefore, the phenotype of immune cells in tumors, including cell subtypes, functional polarization, and spatial distribution, influences cancer patients' prognoses and responses to PD-1/PD-L1-targeted immunotherapy. The potential role of PD-1 in the maintenance of peripheral tolerance by negatively regulating T cell responses to antigenic stimulation and suppressing antitumor immunity has been reported in previous studies . PD-L1 expression is a potential biomarker of immunotherapy response, and blocking the PD-1/PD-L1 interaction is important for reactivating T cell antitumor activities . The PD-1/PD-L1 interaction is key in regulating T cell activation and expansion by suppressing T cell responses . Since PD- PD-L1-expressing cells and immune cells are proximal to and interact with tumor cells, the immunosuppressive and immunostimulatory mechanisms controlling antitumor immunity demonstrate a delicate and dynamic balance . Characterizing the PD-1/PD-L1 axis to understand the mechanism of PD-L1+ macrophages and PD-1+CD8+ T cells migrating to the tumor site or the effect of the increasing immunosuppressive cellular components can provide insight into the complex interplay of immune and heterogeneous tumor cells in the TME . Here, we aimed to investigate the involvement of PD-1/PD-L1-expressing immune cells in the TME to assess PDAC patients' prognosis. The immune cell heterogeneity in the TME has been intensively studied using the multiplex immunohistochemistry (mIHC) technique, which can characterize immune infiltration in tumor tissues with multiple biomarkers simultaneously stained on a single formalin-fixed paraffin-embedded (FFPE) slide. However, the current evaluation of the TME using single-cell markers and cell density-based assays cannot assess single-cell-based phenotypes with multiple lineage selectivity, functional status, or spatial relationship among individual cell types . Thus, we combined mIHC with computational imaging and multiparametric flow cytometry quantification, which allowed us to assess multiple lineage-selective and functional phenotypic biomarkers in the TME. Image cytometry is a multiparameter cytometric approach that uses the quantification of fluorescence intensities based on single-cell segmentation. The single-cell data includes cell size, compactness, location, and fluorescence intensity per cell per marker. This quantification analysis was applied to multiple biomarkers in mIHC images, and the lymphoid or myeloid cells were assessed based on hierarchical gating strategies. Importantly, image cytometry enables the assessment of multiple lineage-selective and functional phenotypic biomarkers and in-depth analysis of spatial characteristics based on cell location and tissue context information in the TME. Combining mIHC with computational imaging and multiparametric flow cytometry quantification allowed us to assess multiple lineage-selective and functional phenotypic biomarkers in the TME. We applied mIHC and image-based flow cytometry, a novel and powerful technique that provides subcellular parameter information, to investigate the percentage of CD8+ T lymphoid cells expressing the T cell exhaustion marker PD-1 and the percentage of CD68+ tumor-associated macrophages (TAMs) expressing the checkpoint PD-L1 in PDAC. We also assessed the spatial distribution, prognostic value, and correlation between the proximity of PD-1+CD8+ T cells and PD-L1+CD68+ macrophages in the TME. We found that PD-1+CD8+ T cells and PD-L1+CD68+ TAMs coexisted in the PDAC TME. Evaluating the percentage of lymphoid CD8+ T cells expressing the T cell exhaustion marker PD-1 or the percentage of CD68+ cells expressing a high level of PD-L1 may serve as a better independent prognostic indicator for PDAC than assessing the density of tumor-infiltrating cells, which involves using a single marker to indicate an immune cell. Furthermore, the infiltration of a proportion of PD-1+ CD8+ T cells increased with the proportion of PD-L1+ CD68+ TAMs. These findings may provide new strategies and indications for developing optimal immunotherapy regimens for PDAC patients. 2. Materials and Methods 2.1. Patient Cohort and Tissue Microarray Construction The human PDAC specimens were obtained from Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (Shanghai, China), and a written informed consent was obtained from all participants. The study was approved by the human ethics committees of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (ID: 2021-207). The human tissue specimens were processed using FFPE. Based on the H&E staining results, which were examined by a pathologist, 170 cancer or adjacent normal FFPE tissue samples were punched and arranged in tissue microarray (TMA) blocks. A total of 80 tumor and adjacent normal tissue samples were paired, and an additional 10 tumor tissues were included. After discarding the incomplete tissues, the final tumor and adjacent normal dataset comprised 84 tumor and 73 adjacent normal samples. The clinical sample information of every patient is detailed in Supplementary Table S1, and Supplementary Table S2 shows the patients' basic characteristics. Standard H&E staining was performed on the TMA sections using standard methods to further validate the tissue histology . The diameter of each block core used in this TMA assessment was 1.5 mm. 2.2. Multiplex IHC Staining and Image Acquisition We used the Ultivue UltiMapper Immuno 8 kit to conduct the mIHC staining according to the manufacturer's instructions (#ULT30801, Ultivue, Cambridge, MA, USA) . Paraffin-embedded sections were heated in an oven at 60 degC for 1 h, after which they were deparaffinized with xylene and rehydrated using a gradient of ethanol solutions. An antigen retrieval was performed in an EDTA (pH 9) buffer (Akoya Biosciences, Menlo Park, CA, USA), and the antibody diluent contained in the kit was used to block the binding of nonspecific antibodies. The commercialized primary antibodies used were pre-designed panels for identifying specific cells in the TME and included anti-CD3 (clone BC33), anti-CD8a (clone C8/144B), anti-FOXP3 (clone 236A/E7), anti-CD68 (clone KP-1), anti-PD-1 (clone CAL20), anti-PD-L1 (clone 73-10), and anti-PanCK/SOX10 (clone AE1/AE3 and BC34) antibodies. All antibodies were diluted at a ratio of 1:100 in antibody diluent and combined. The sections were then incubated in the antibody mixture for 1 h. After applying a pre-amplification mix and an amplification enzyme solution to detect antibody staining, the tissues were incubated with a nuclear counterstain solution, and the first-round fluorescent probe solution was used to detect CD8, PD-1, PD-L1, and CD68. A coverslip was then mounted over the tissue chip using the ProLong Gold Antifade Mountant (Thermo Fisher, Carlsbad, CA, USA). The sample was loaded onto the Vectra Polaris automated quantitative pathology imaging system (Akoya Biosciences), and whole-slide scanning captured the first-round images at a magnification of 20x. After acquiring the first round of images, an exchange solution was used to remove the fluorescent probes. A second round of staining was then conducted (CD3, FOXP3, and pan-keratin (PanCK)/SOX10), and the images were captured as described above. 2.3. Image Analysis The HALO image analysis platform (Indica Labs, v3.3.2541.345) was used for image overlay, tissue segmentation, and cell phenotype analysis. The positive thresholds for each marker were set based on the nuclear (DAPI and FOXP3) or cytoplasmic (CD3, CD8, CD68, PD-1, PD-L1, and PanCK/SOX10) staining intensities and were examined across all tissue samples. The combined results for cell counts, densities, and percentages were exported for further analyses and for the generation of graphic images using a previously described method . 2.4. Flow Cytometry-like Workflow The data were exported from the HALO software into a flow cytometry file (.fcs) format for the flow cytometry-like workflow. The single-cell data, including cell location and fluorescence intensity per cell per marker, were exported to the FCS Express 7 software (De Novo Software, Glendale, CA, USA) for this analysis. For each specimen, the marker expression was gated based on the fluorescence intensity of the corresponding negative control slide. The R software was used to construct scatter plots, which provided intuitive visual results of the cells gated by the FCS Express 7 software. 2.5. Spatial Analysis The data collected on all of the evaluated markers in each cell and the (x, y) locations of the cells within the tissue specimens were stored in the HALO software for further spatial analyses. The proximity of the PD-1+ or PD-+ T cells to the PD-L1+ or PD-+ macrophages was analyzed using the HALO Spatial Analysis module. In this module, the cells were defined by phenotype, and a spatial plot was generated for each sample. The proximity analysis tool was used to assess the distance between the cells and the percentage of PD-1+/PD-1-CD8+ T cells within 0-100 mm (number of bands = 10) of the PD-L1+CD68+ or PD-L1-CD68+ cells. 2.6. Survival Analysis The median was used as a cutoff value to classify the patients into low-expression groups. The patient survival analysis was performed in GraphPad Prism 9 (GraphPad, Inc., San Diego, CA, USA). The 1-year receiver operating curves (ROCs) for age, sex, stage, and cluster were plotted, and the areas under the curves (AUCs) of the ROC curves were calculated. A multivariate regression analysis was applied to evaluate the correlation between the overall survival (OS) outcomes and the age, sex, stage, and cluster information using the survival package in the R software. The HR was calculated and expressed as a forest plot. 2.7. Statistical Analysis Statistical analyses were performed using GraphPad Prism 9. An unpaired, two-tailed Student's t-test was used to determine statistically significant differences in the unpaired data. The correlations between the cell densities obtained using the flow cytometry-like workflow and HALO platforms or between the cell populations were evaluated using simple linear regression analyses. Multivariate Cox regression models were used to analyze the independent prognostic factors and immune markers. The overall survival outcomes among the subgroups were estimated by the Kaplan-Meier method, and the significant differences were assessed using log-rank tests. A p value of < 0.05 was considered to indicate significance (*: p < 0.05; **: p < 0.01; ***: p < 0.001). 3. Results 3.1. PDAC Cell Phenotyping with High-Multiplex InSituPlex DNA Barcoding and Antibody Staining An FFPE tissue microarray comprising 80 paired tumors and adjacent normal tissue samples and 10 additional PDAC tumor tissue samples (a total of 170 tissue samples) was created to sufficiently and appropriately audit the complex and dynamic microenvironments that influenced the phenotypes of resident and infiltrating leukocytes in tumors with preserved geographic distribution. We established a two-round assay with each panel containing 3-4 biomarkers, including seven distinct epitopes of lymphoid and myeloid lineage cells and tumor epitopes . The lymphoid biomarker panel depicts CD3+ T cells, CD3+CD8+ cytotoxic T cells, and CD3+FOXP3+ regulatory T cells (Tregs), while the myeloid biomarker panel shows CD68+ macrophages; the tumor cells were stained for PanCK/SOX10. Multispectral imaging followed by spectral separation and image overlay allow for the simultaneous assessment of all markers in the same slide tissue sample . In addition, we performed the flow cytometry-like workflow described above. In this approach, an image analysis was conducted by transferring the resultant unmixed multilayer TIFF images into the HALO software for tissue and cell segmentation. The resultant single-cell data, which comprised cell location and fluorescence intensity per cell per marker, were exported to the FCS Express software for further analysis. The lineage assignment implicated the functional status of PD-1 or PD-L1 in immune cells . Therefore, distinct cell phenotypes based on the markers described above were identified, and we quantitatively assessed six immune cell populations and two tumor cell populations . 3.2. Lymphoid or Myeloid Density Alone Was Not Clearly Associated with Differences in Overall Survival Outcomes Initially, we comprehensively reviewed the densities of CD3+ T cells, CD8+ T cells, FOXP3+ Tregs, and CD68+ macrophages between the paired adjacent normal tissues and the tumor tissues. The CD3+ T and CD8+ T cells were significantly reduced in the tumor tissues compared to the adjacent normal tissues , and there were no significant differences in the densities of the FOXP3+ Tregs or the CD68+ macrophages between the adjacent normal and tumor tissues . The larger population of total CD3+ T cells and CD8+ cytotoxic T cells in adjacent normal tissues may reflect an active immune response against a large number of tumor cells, representing the initial stage of cancer cell transformation. Large numbers of cytotoxic T cells in adjacent normal tissues may represent a response to the tumor. We further evaluated the CD68+ macrophages to CD3+ T cells ratio and the FOXP3+ Tregs to CD8+ cytotoxic T cells ratio. Compared with the adjacent normal tissues, the tumor tissues showed significantly higher CD68/CD3 and FOXP3/CD8 ratios , representing a more immunosuppressive phenotype in PDAC. Next, we determined whether the infiltration of specific T cells or macrophages in PDAC was an independent factor associated with patient survival outcomes. We calculated the densities of multiple lineage-selective biomarkers, such as CD3+, CD3+CD8+, CD3+FOXP3+, and CD68+, as well as the functional phenotypic CD8+PD-1+ and CD68+PD-L1+, in the TME of each patient. We then stratified the patients into low or high immune cell infiltration groups based on the median densities of each cell subset. We observed that high T cell or high macrophage infiltrations do not significantly associate with survival outcomes . This result could be attributed to a lack of analysis of differential infiltration functional subpopulations and their spatial patterns, which may correlate with the predictive survival values. Overall, these results suggest that the functional subpopulations of cytotoxic T cells and myeloid subsets need to be re-defined to find the determinants of PDAC patient survival outcomes. 3.3. Multiplexed IHC Images Established Quantitative Assessment by Image Cytometry Analysis with Preserved TME Context Information Similar to the flow cytometry (fluorescence-activated cell sorting [FACS]) data analyses, single-cell-based measurements, including shape, size, and pixel intensity, were performed. This approach allowed the visualization of qualitative assessments of signal intensity. The threshold for qualitative identification was determined based on the map distribution of each marker in the negative control. We developed a qualitative gating strategy for the panel to obtain quantitative data similar to the multiparameter, eight-color FACS. All cores corresponding to a single tumor sample were grouped using gates . We validated these data after manual gating. The gated cells were visualized in a dot plot and correlated with the fluorescence distribution of the cells in the original image of the tissue environment . For comparative analyses between the image cytometry and slice-based images, we used flow cytometry software to compare the densities of the CD3, CD8, CD68, FOXP3, PD-1, PD-L1, and tumor cells to those obtained by the phenotyping software (HALO), which is associated with the microscope platform and is the current gold standard. Both approaches showed strong positive correlations for all markers . Furthermore, associations between the densities of CD8+ and PD-1+ and CD68+ and PD-L1+ were discovered . 3.4. In Situ Leukocyte Analysis Identified the Proportion of PD-1 Expression in CD8+ TILs as a Risk Factor in PDAC Subsequently, we used multispectral staining to delineate CD8+ TILs in and around the tumors in the PDAC patients. The PD-1 positivity threshold was determined based on the negative control gated on the CD3+CD8+ T cells. When we looked at the entire tumor and the adjacent normal core, the proportion of CD8+ T cells in the CD3+ T cells was 54.71% on average (median = 54.5%) in the adjacent normal core and 46.08% on average (median = 39.2%; p < 0.001) in the tumor . We further found more CD8+ T cells expressing PD-1 in the tumor than in the adjacent normal core . Next, we further evaluated the differential infiltrating functional subpopulations of the T cells. The high proportion of PD-1+ CD8+ T cells among the total cells was not associated with patient survival outcomes (p = 0.6532) . However, patients with a high percentage of PD-1+CD8+ T cells among the CD8+ T cell population had significantly poorer OS outcomes (p < 0.001) . 3.5. Spatial Analysis Revealed That PD-1+CD8+ T Cells Proximal to PD-L1+CD68+ Macrophages Are Associated with Poor Prognosis We observed a large number of PD-L1+ cells within the CD68+ macrophage population and further evaluated the functional subpopulation in the CD68+ macrophages. A high proportion of the PD-L1+CD68+ T cells among the total cell population demonstrated a trend of poorer patient survival outcomes (p = 0.0585) . However, the patients with a high percentage of CD68+PD-L1+ among the CD68+ macrophages had significantly poorer OS outcomes (p < 0.001) . Strikingly, we found that the proportion of PD-1+CD8+ among the CD8+ TILs was positively correlated with the proportion of PD-L1+CD68+ among the CD68+ TAMs (r = 0.74; p < 0.0001) . In addition, the proportion of PD-L1+ tumor cells (PD-L1+ PanCK/SOX10+) was unrelated to the PD-1+CD8+ subset cells . Therefore, we speculate that the PD-L1+CD68+ TAMs, but not the PD-L1+ tumor cells, are located near the specific CD8+ T cell subsets that exert suppressive effects. We then performed a spatial analysis and calculated the percentage of PD-1+CD8+ TILs or PD-1-CD8+ TILs per PD-L1+ TAMs over a range of distances from 0 to 100 mm (number of bands = 10) . We found that at all of the distances studied, compared with PD-1-CD8+ TILs, the percentage of PD-1+CD8+ TILs increased significantly (0-10, 10-20, 20-30, 30-40, 40-50, and 70-80 mm; p < 0.05-0.01) or showed a tendency to increase around the PD-L1+CD68+ TAMs. However, more CD8+PD- are distributed at the distances of 50-60, 60-70, and 90-100 mm from the PD-L1+ than the CD8+PD-1+ cells, and the PD-1+CD8+ cells showed no tendency to associate with the PD-L1-CD68+ cells . Our data suggest that PD-1+ CD8+ TILs may interact closely with PD-L1+CD68+ TAMs in situ to jointly suppress potent antitumor immune responses . 3.6. Prognostic Value Evaluation of Risk Prediction Factors The correlations between the immune markers and the OS outcomes were assessed separately in the adjacent normal and tumor tissues. No significant correlations were found between the single immune markers and the OS outcomes, while the percentages of CD8+ T lymphoid cells expressing the T cell exhaustion marker PD-1 or the percentages of CD68+ myeloid lineages with high expression of the checkpoint PD-L1 were significantly associated with a poor outcome (p < 0.001). In particular, we compared the change in status (decrease or increase) of the quantitative immune markers. We considered both the PD-L1+CD68+ TAMs and the PD-1+CD8+ T cell infiltration and divided the patients into four groups based on the proportion of PD-1+CD8+ cells in the CD8+ T cells (high/low) and PD-L1+CD68+ cells in the CD68+ cells (high/low). The survival curves revealed that the patients with high CD68+PD-L1+ TAM and PD-1+CD8+ T cell proportions in the respective cell subsets had poor survival rates . We further investigated different clusters associated with different cancer stages, and the results indicated that the clusters had prognostic values only in early-stage (1-2) patients and not in advanced-stage (3-4) patients . In addition, compared with the traditional age, sex, and tumor-stage classification method, this new classification method was more accurate in predicting the one-year survival rate of PDAC patients . Multivariate analyses incorporating clinical parameters revealed that a high level of infiltrating PD-L1+CD68+ within the CD68+ macrophage subset combined with the proportion of PD-1+CD8+ cells in the CD8+ T cell subset was an independent factor associated with a high risk of cancer-related death in PDAC patients (p = 0.037; hazard risk (HR): 2.06; 95% CI [1.04-4.0]) . In conclusion, our results suggest that PD-L1+CD68+ TAMs in the TME can attract immunosuppressive PD-1+CD8+ T cells, exhibit prognostic values, and are more accurate than the results from traditional classification methods in PDAC. 4. Discussion Multiplex IHC techniques have emerged as an effective approach for studying cancer, allowing the simultaneous detection of multiple markers in a single tissue section and the comprehensive study of cell phenotypes, cellular functions, and cell-cell interactions . The evaluation of the TME using current cell markers and cell density-based assays cannot assess single-cell-based phenotypes with multiple lineage selectivity, functional status, or tissue contextual information. The strategy of multiplex IHC combined with computational imaging and multiparametric flow cytometry quantification allowed us to assess multiple lineage-selective and functional phenotypic biomarkers in the TME. Here, we defined the expression and distribution of PD-L1 and PD-1 in non-malignant cells in the PDAC microenvironment. We developed and employed analytical methods to quantify the relative proportions and locations of cells expressing PD-L1 and PD-1 and the spatial relationships between specific cell populations. We found that the percentage of lymphoid CD8+ T cells expressing the T cell depletion marker PD-1 or the percentage of myeloid lineage CD68+ macrophages with high expression of the checkpoint PD-L1 were associated with a poor prognosis. Furthermore, PD-1+CD8+ T cells proximal to PD-L1+CD68+ macrophages were associated with a poor prognosis in PDAC patients. We demonstrated the function of PD-1 cells proximal to PD-L1 cells and characterized the PD-1/PD-L1 axis, which increases the impact of immunosuppressive cellular components and affects the survival of patients with PDAC. Despite intensive immune cell heterogeneity studies in the TME, the in situ distribution of different populations in PDAC remains unclear . There is growing evidence that using marker combinations would be a more reliable method of distinguishing cell populations or activation states. Advanced techniques for studying immune cell populations exist, including IHC, CyTOF, flow cytometry, and single-cell sequencing . However, in situ distribution information is lacking, and the multiplex IHC used in this study allows for the study of marker co-expression and spatial parameters at single-cell resolution . In addition, these tissue-sectioning techniques can be analyzed similarly to flow cytometry to assess the intensity of the signal, usually using image analysis software to evaluate the output parameters of the mean intensity of fluorescence (mIF) assays. The results can be processed in a machine-readable format based on each cell and exported to the software for further analysis. In this study, we determined beforehand whether the mIHC data could be analyzed using previously defined flow cytometry workflows while maintaining the spatial information provided by this emerging technology through image cytometry. We quantified specific cell subpopulations in slides stained with mIHC using flow cytometry dot plots and associated gating strategies, as reported in previous studies , and found that the multispectral mIHC technique is better suited for image cytometry analysis than some other techniques for imaging cells. Based on this qualitative gating strategy, previous researchers observed that image cytometry and flow cytometry data performed similarly in terms of lymphocyte quantification ; thus, this imaging method can serve as a platform for multiparametric assessments of various cell lineages and realize tumor localization information. While this approach enables lineage identification based on multiple lineage selectable markers , its diversity is limited due to the availability of limited lineage biomarkers in specific cell types. Having achieved this image cytometry analysis, we turned our attention to the parameters provided by mIHC and related slide-imaging systems, which are superior to the capabilities of traditional IHC methods, in which the density is assessed using multiple labels on a single slide. We also determined spatial information at the single-cell level and performed a quantitative assessment of marker co-expression in individual cells. Nonetheless, a growing number of published reports show that the density and location of specific cellular phenotypes within the TME are correlated with the proximity of PD-L1-expressing TAM or tumor-expressing PD-L1 cells . Our study shows that the percentage of lymphoid CD8+ T cells expressing the T cell exhaustion marker PD-1 or the percentage of myeloid lineage CD68+ cells expressing the checkpoint PD-L1 are associated with a poor prognosis. The prognostic value of these methods is more important than lymphoid and myeloid cell density analyses. We believe this is because the % positive rate calculation is a ratio (the number of positive cells/total cells or a subset of cells with a positive marker function) instead of an absolute number (the number of positive cells). Therefore, this value is unlikely to change due to TME heterogeneity between different sections and/or potential sectioning artifacts or challenges in macrophage membrane segmentation. Another contributory factor may be that PD-L1+ macrophages can be identified through machine learning algorithms for higher reproducibility, as PD-L1 expression on the membrane may contribute to improved membrane segmentation and associated macrophages. Some of the possible strategies for improving macrophage membrane segmentation in follow-up studies include adding a stain to highlight the cell membrane to help the machine learning algorithms segment and/or segment macrophages from other immune cells in the TME. In this study, tumor cells were also present in a local microenvironment enriched with PD-L1. This polarization may increase the local reservoir of PD-L1 available to bind PD-1 and enforce T cell suppression in the vicinity of tumor cells. However, the density of PD-L1+ TAMs and PD-1+ T cells was consistently higher. We used cell proximity analyses to determine that the spatial organization of T cells and TAMs is associated with PD-1/PD-L1 expression. To the best of our knowledge, this is the first demonstration of an unbiased classification in which closely related outcomes were observed based on quantifiably distinct cellular components and spatial organization. These results raise the possibility of characterizing additional subtype classification methods and defining spatially resolved immune signatures. Such quantifiable features may prove useful both for diagnosis and for patient stratification within diagnostic categories for therapeutic purposes. In most of the tumors in our study, the majority of PD-L1-expressing immune cells are TAMs. This result is consistent with the observation that TAMs highly express PD-L1 in tumor tissues. Furthermore, we found that TAMs are not randomly distributed. In contrast, PD-1+CD8+ T cells were closer to PD-L1+ TAMs than PD-1-CD8+ T cells. Overall, our findings suggest a representation model in which the tumor's inflammatory microenvironment is highly organized with PD-1+ T cells close to PD-L1+ TAMs and enhances immunosuppression . This effect may be induced by the local cytokine environment, but whether the expression on TAMs is directly dependent on the presence of tumor cells is unknown . Macrophages exhibit a phenotype that is markedly plastic to their environment, and the induction of PD-L1 can include the mediation of interferon-g and granulocyte-macrophage colony-stimulating factors (GM-CSFs), which tumors regulate alongside other pro-inflammatory cytokines . Producer cells, including T cells, natural killer cells, and myeloid cells within the TME, will be analyzed in future studies. In this regard, the inflammatory TME of tumors, in which PD-L1 is expressed by non-malignant cells, including macrophages, is prominently regulated by the local microenvironment. We examined the PD-1 expression of T cells and found high or moderate levels in CD8+ cells. Previous studies have determined that T cells with moderate or low levels of PD-1 expression are antigen-experienced, while those with the highest levels of PD-1 in the periphery have an irreversible "depleted" phenotype and are poised for reactivation . Our data suggest that many PD-1 T cells within the tumor TME have a PD-1 phenotype ready for reactivation. While PD-1 primarily recognizes distinct T cell populations, CD68 and PD-L1 appear to identify a common TAM population. Similar to the examination of PD-L1 in the TME, we found that TAMs, but not tumor cells, promote the total microenvironmental pool of CD68 to a greater extent, which can be used to engage PD-1-positive T cells in the vicinity of tumor cells. Overall, these data provide further evidence that tumor cells reside in a specialized, microenvironmental, and immune-privileged niche in which they can exploit the coexisting escape pathways of the CD68/CD8 and PD-L1/PD-1 axes. 5. Conclusions In summary, we revealed that the high PD-1+ expression among CD8+ T cells and the high PD-L1+ expression among TAMs are associated with each other and correlate with a poor prognosis in PDAC patients. Thus, we identified an immune "neighborhood" in which PD-L1-expressing TAMs are surrounded by high numbers of exhausted, cytotoxic T cells, playing a crucial role in immune escape. These findings also indicate that the PD-1/PD-L1 axis affects the survival of patients with PDAC. Supplementary Materials The following supporting information can be downloaded at: Figure S1: H&E results of the 170 core TMA. Figure S2: Significant associations between the CD8 and PD-1 and the CD68 and PD-L1 densities. Figure S3: The proportion of PD-L1+ tumor cells (PD-L1+ PanCK/SOX10+) was unrelated to the proportion of PD-1+CD8+ cells in the CD8+ subset. Table S1: Clinical sample information. Table S2: The patients' basic characteristics. Click here for additional data file. Author Contributions Conceptualization, D.X., Y.H. and X.Y.; methodology, X.Y., G.W. and Y.S.; software, Y.L. and Y.X.; validation, X.Y., X.F. and Y.Z.; formal analysis, X.Y., G.W., Y.S. and T.Z.; resources, Y.H. and D.X.; data curation, X.Y. and D.X.; writing--original draft preparation, D.X. and X.Y.; writing--review and editing, Y.H., G.W., Y.S., T.Z., Y.L., Y.X., X.F. and Y.Z.; visualization, X.Y., G.W. and Y.S.; supervision, D.X.; project administration, Y.H.; funding acquisition, D.X. and Y.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 of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (protocol code: 2021-207; date of approval: 3 August 2022). Informed Consent Statement Written informed consent was obtained from the patients to publish this paper. Data Availability Statement The authors declare that the main data supporting the findings of this study are available within the article and Supplementary Information. The data presented in this study are available upon request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Characterization of cell phenotypes in PDAC tissues by InSituPlex multiplex staining technology. (A) A two-round multiplex staining assay and whole-slide digital scanning were performed in PDAC TMA, and the representative multispectral images (MSIs) of one TMA core are shown. (B) Simultaneous assessment of all markers using the "registration configure" functional module of the HALO software. The representative images show multiple staining patterns in the PDAC tissues. PanCK/SOX10 (a tumor cell marker) is shown in cyan; CD3+ T cells are shown in yellow; CD8+ cells are shown in green; FOXP3+ cells are shown in rose red; CD68+ cells are shown in white. The orange color indicates PD-1+ cells, and the red color indicates PD-L1+ cells. (C) The initial analysis was conducted using the HALO software. The tissues were segmented into tumor (red), stromal (green), and background (blue) regions based on DAPI+ and PanCK/SOX10+ cells. The cells were then distinguished into different types according to the identified markers. For the image cytometry analysis, the data were exported to the FCS Express 7 software to gate specific cell populations, and R and Prism were implemented for further analysis and data visualization. (D) Cell phenotypes identified by hierarchical gating of lineage-selective and functional biomarkers during image cytometry analysis of mIHC staining. Figure 2 The analyzed phenotypes demonstrated an immunosuppressive microenvironment in PDAC with no prognostic value identified as an independent factor. (A,B) Compared with those in the adjacent normal samples, the densities of CD3+ T cells and CD8+ cytotoxic T cells in the tumor samples were significantly reduced (p < 0.01). (C,D) There were no differences in the densities of FOXP3+ Tregs and CD68+ macrophages between the adjacent normal and tumor samples. (E,F) Compared with the adjacent normal tissues, the ratio of CD68/CD3 or FOXP3/CD8 in the tumor tissues was significantly increased (p < 0.05). (G-L) Survival data on 84 PDAC patients were collected, including the following: different T cell (CD3+) densities; cytotoxic T cell (CD3+CD8+) densities; FOXP3+ T cell (CD3+FOXP3+) densities; exhausted, cytotoxic T cells (CD3+CD8+PD-1+) densities; macrophage (CD68+) densities; immunosuppressive macrophages (CD68+PD-L1+). There were no significant differences in the OS outcomes (p > 0.05) of the patients with low-cell populations among the analyzed phenotypes. The median was used as a cutoff value to classify the patients into low-expression groups. The error bars represent SEMs. The statistical analyses between the adjacent normal and tumor samples were conducted using Student's t-tests. A log-rank test was used to determine the significance of the survival outcomes. Figure 3 Quantitative evaluation of all parameters by image cytometry. (A) Image cytometry gating strategy to define the cell phenotypes. (B) The data were visualized after manual gating and validating the image cytometry quantification. Representative image of a TMA from a FFPE PDAC core stained by mIHC (left), with corresponding image cytometry gates (middle), and a color-coded dot plot map of the gated populations (right). (C) The cell densities were identified by our image cytometry gating strategies; those image cytometry methods showed robust correlation with previous ones using the HALO platform (the current standard procedure). The linear regression and the 95% confidence interval for the slope are displayed. Figure 4 Proportion of CD3+CD8+PD-1+ cells among the CD3+CD8+ cells showing prognostic values in 84 PDAC patients. (A) Compared with the tumor tissues, the proportion of CD3+CD8+ cytotoxic T cells among the CD3+ T cells was significantly increased in the adjacent normal samples (p < 0.05). (B) Compared with the adjacent normal samples, the proportion of CD3+CD8+PD-1+ cells among the CD3+CD8+ T cells was significantly increased in the tumor tissues (p < 0.05). (C) A Kaplan-Meier curve showing no prognostic effect on the overall survival (OS) rates associated with the proportion of CD3+CD8+PD-1+ positive cells among all of the cells (p > 0.05). (D) A Kaplan-Meier curve illustrating a prognostic effect on the OS outcomes based on the proportion of CD3+CD8+PD-1+ cells among the CD3+CD8+ cells (p < 0.001). The median was used as a cutoff value to classify patients into low-expression groups. The error bars represent SEMs. The statistical analyses between the adjacent normal and tumor samples were conducted by Student's t-tests. A log-rank test was used to compare the survival distributions between the groups to determine significance. Figure 5 The spatial analysis revealed that the PD-1+CD8+ cells were close to the PD-L1+CD68+ cells within the TME. (A) A Kaplan-Meier curve showing that a low proportion of CD68+PD-L1+ among all cells tended to predict longer overall survival (OS) times (p = 0.0585). (B) A Kaplan-Meier curve illustrating the significant prognostic effect on OS based on the proportion of CD68+PD-L1+ cells among the CD68+ cells (p < 0.001). (C) A scatter plot showing the significant positive correlation between the proportion of PD-1+CD8+ among the CD8+ TILs and PD-L1+CD68+ among the CD68+ TAMs with the best-fit line shown. The Pearson's correlation coefficient (r value) and the p value are provided at the top. (D) A spatial plot showing the distribution of PD-1+CD8+ cells and PD-1-CD8+ cells from the PD-L1+CD68+ cells. (E) A spatial plot showing the distribution of PD-1+CD8+ cells and PD-1-CD8+ cells from the PD-L1-CD68+ cells. (F) A diagram depicting the interaction between the PD-L1+CD68+ macrophage and the PD-1+CD8+ T cell. The median was used as a cutoff value to classify patients into low-expression groups. The error bars represent SEMs. A log-rank test was used to compare the survival significance. The statistical analyses between the two groups were conducted using Student's t-tests. *: p < 0.05; **: p < 0.01; ***: p < 0.001. Figure 6 Establishment of a multivariate Cox model and assessment of its prognostic significance. (A) Kaplan-Meier curves were calculated to compare the overall survival (OS) outcomes and the prognostic effect in patients stratified based on the proportion of PD-1+CD8+ T cells among CD8+ T cells and PD-L1+CD68+ cells among CD68+ cells. (B) A Kaplan-Meier curve illustrating the significant prognostic effect in stage 1 and stage 2 patients based on patients' stratifications. (C) A Kaplan-Meier curve showing no prognostic effect in stage 3 and stage 4 patients based on clusters. (D) Receiver operating curve analysis shows AUC values for group, age, sex, and stage in a one-year survival prediction. (E) An HR forest plot of the multivariate Cox model of the cluster and clinicopathological variables, including sex, age, and tumor stage. *: p < 0.05; ***: p < 0.001. 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. |
PMC10000395 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051088 foods-12-01088 Article Effect of Ferulic Acid and Its Derivatives on Cold-Pressed Flaxseed Oil Oxidative Stability and Bioactive Compounds Retention during Oxidation Mikolajczak Natalia Conceptualization Methodology Software Validation Formal analysis Investigation Resources Data curation Writing - original draft Writing - review & editing Visualization Project administration Funding acquisition 1 Pilarski Wojciech Resources Writing - original draft Writing - review & editing Visualization 2 Gesinski Krzysztof Resources Writing - original draft Writing - review & editing Visualization 2 Tanska Malgorzata Conceptualization Methodology Software Validation Resources Writing - original draft Writing - review & editing Visualization Supervision 1* Ratusz Katarzyna Academic Editor Scibisz Iwona Academic Editor Wroniak Malgorzata Academic Editor 1 Department of Food Plant Chemistry and Processing, Faculty of Food Sciences, University of Warmia and Mazury in Olsztyn, 10-718 Olsztyn, Poland 2 Department of Biology and Plant Protection, Faculty of Agriculture and Biotechnology, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland * Correspondence: [email protected]; Tel.: +48-89-523-4113 03 3 2023 3 2023 12 5 108801 2 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 ). Ferulic acid (FA) is a naturally occurring phenolic antioxidant that is widely used in the food, pharmaceutical, and cosmetic industries due to its low toxicity. Its derivatives also find numerous industrial applications and may have even higher biological activity than ferulic acid. In this study, the effect of the addition of FA and its derivatives--including vanillic acid (VA), dihydroferulic acid (DHFA), and 4-vinylguaiacol (4-VG)--on the oxidative stability of cold-pressed flaxseed oil and the degradation of bioactive compounds during oxidation was investigated. The results showed that FA and its derivatives affected the oxidative stability of flaxseed oil, but their antioxidant activity depended on the concentration (25-200 mg/100 g oil) and temperature of treatment (60-110 degC). Based on Rancimat test results, flaxseed oil oxidative stability predicted at 20 degC increased linearly with ferulic acid concentration, while its derivatives effectively prolonged the induction time at lower concentrations (50-100 mg/100 g oil). The addition of phenolic antioxidants (80 mg/100 g) generally showed a protective effect against polyunsaturated fatty acids (DHFA and 4-VG), sterols (4-VG), tocols (DHFA), squalene, and carotenoids (FA). The exception was VA, which increased the degradation of most bioactive compounds. It is believed that adding properly composed mixtures of FA and its derivatives (DHFA and 4-VG) can extend the shelf life of flaxseed oil and provide nutritional benefits. vanillic acid dihydroferulic acid 4-vinylguaiacol Rancimat test fatty acids quality indices bioactive compounds National Science Centre, Poland2018/31/N/NZ9/01273 This research was funded by the National Science Centre, Poland, grant number 2018/31/N/NZ9/01273. pmc1. Introduction Flaxseed (linseed) oil is one of the most important vegetable oils in the world and is commonly produced by mechanical pressing or solvent extraction. The cold-pressing technique has attracted considerable interest in the last decade due to its capability of producing a high-quality product as well as its lower energy requirements, ease of operation, and environmentally friendly approach. The maximum temperature of cold-pressed oil should not exceed 50 degC, and only its physical purification through filtration, sedimentation, or centrifugation processes is allowed . Flaxseed oil is characterized by a high content of unsaturated fatty acids (UFA). It has been reported in the literature that their contribution to total fatty acids can be as high as 92% , with the majority (49-66%) consisting of a-linolenic acid (ALA) . The high content of ALA makes flaxseed oil a valuable preventive and medicinal product, e.g., for cardiovascular and nervous system diseases and cancers . Unfortunately, the presence of three double bonds in the ALA structure makes the oil very susceptible to the oxidation process . It is estimated that its shelf life ranges from 5 weeks to 3 months when stored refrigerated . The protection of vegetable oils, in particular oils with a high content of UFA, is achieved through the addition of antioxidants that can interact with oxidation products (free radicals) through their ability to scavenge or decompose them . In recent years, phenolic compounds have attracted considerable attention due to their beneficial antioxidant activity . For example, Michotte et al. investigated the possibility of using flavonols (myricetin, catechin) and hydroxycinnamic acid (caffeic acid) as additives to increase the stability of flaxseed oil, and in studies by Suja et al. , the addition of lignans was used to reduce the negative effects of oxidation of soybean, sunflower, and safflower oils, while Mikolajczak et al. showed that vinyl phenolic acid derivatives have protective effects on the fatty acids and bioactive compounds in flaxseed and rapeseed oils. A new approach to potentially increase the oxidative stability of edible oils is the use of antioxidants naturally occurring in foods, which may provide additional health benefits to consumers . One such antioxidant could be ferulic acid (FA), which has low toxicity, is more easily absorbed by the body, and stays in the blood for longer periods than other phenolic acids . FA (4-hydroxy-3-methoxycinnamic acid) is an important phenolic acid commonly found in the leaves, fruits, and seeds of plants . One of the best documented biological activities of FA is its antioxidant properties, which are mainly due to the presence in the molecule of the phenol nucleus and an extended side chain . This helps FA easily form a stable phenoxy radical and provides high protection against adverse oxidation processes in DNA, lipids , and proteins . FA may also have beneficial effects in the prevention or treatment of oxidative stress disorders, i.e., cardiovascular diseases, cancers, and diabetes . The shikimic pathway produces FA in plants starting from aromatic amino acids such as L-phenylalanine and L-tyrosine , which are initially converted to p-coumaric acid and cinnamic acid using phenylalanine ammonium lyase and tyrosine ammonium lyase, respectively. p-Coumaric acid is converted to FA through hydroxylation and methylation reactions . Metabolic studies have shown that FA can also be metabolized in vivo, resulting in several metabolites such as FA-glucuronide, FA-sulfoglucuronide, ferulic acid sulfate (major metabolites in rat plasma and urine), FA-diglucuronide, m-hydroxyphenylpropionic acid, feruloylglycine, dihydroferulic acid (DHFA), vanillic acid (VA), and vanillylglycine . These data suggest that the main FA metabolic pathway is glucuronidation and/or sulfate conjugation . FA conjugation occurs in the liver using sulfur transferases and glucuronosyl transferases of uridine diphosphate (UDP); the conjugation reaction may also occur partly in the intestinal mucosa and kidney . Most likely, free FA is metabolized in the liver via b-oxidation . The literature also reports that FA is transformed by numerous fungi, actinomycetes, and yeasts into various useful organic compounds . As a result of the bioconversion process (non-oxidative decarboxylation), FA is transformed into 4-vinylguaiacol (4-VG) due to the decarboxylase enzyme . It can also be degraded to vanillin, among others, via the protocatechuate 4,5-cleavage pathway . Both vanillin and 4-VG are considered value-added bioproducts and are widely used in food and cosmetics production . Furthermore, it has been proven that FA is a powerful food preservative because of its antimicrobial and antioxidant activities . Although more studies are being conducted to determine the effects of phenolic compounds on oil oxidative stability, few researchers have used FA and its derivatives to stabilize ALA-rich oils . It is emphasized that natural FA is easily available and its cost is relatively low, but the applications of FA in food are limited by its low hydrophobicity, hydrophilicity, and stability in various solvent systems . However, FA is a highly reactive compound that shows high potential for the preparation of its derivatives with higher solubility in water and/or higher biological activity . In this study, the antioxidant actions of different concentrations of FA and its derivatives (VA, DHFA, and 4-VG) in cold-pressed flaxseed oil were compared at different temperatures using the Rancimat test. Additionally, the effect of added phenolic additives on the degradation of bioactive compounds (unsaturated fatty acids, sterols, tocols, squalene, and carotenoids) under oxidation at 60 degC was evaluated. 2. Materials and Methods 2.1. Reagents Analytical-grade reagents and solvents, i.e., Folin-Ciocalteu reagent from Sigma-Aldrich (Saint Louis, MO, USA), anhydrous sodium sulfate (Na2SO4), chloroform, diethyl ether, ethanol (99.9% purity), formic acid, methanol, potassium hydroxide (KOH), sodium carbonate (Na2CO3), sulfuric acid (H2SO4), and zinc purchased from Chempur (Piekary Slaskie, Poland) were used. Chromatography-grade solvents, i.e., dichloromethane, ethanol, methanol, n-hexane, heptane, methyl tert-butyl ether, iso-propanol, pyridine, and N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) with 1% trimethylchlorosilane (TMCS) were purchased from Sigma-Aldrich (Saint Louis, MO, USA). Analytical standards such as 5a-cholestane, margaric acid, b-apo-8'-carotenal, D-catechin, phenolic acids (p-coumaric acid (p-CA), dihydroferulic acid (DHFA), sinapic acid (SA), vanillic acid (VA)), and 4-vinylguaiacol (4-VG) were purchased from Sigma-Aldrich (Saint Louis, MO, USA), while tocopherols (a-, g-, and d-tocopherol) were purchased from Calbiochem (Nottingham, UK). Deionized water was obtained from HLP 5 deionizer (Hydrolab, Gdansk, Poland). 2.2. Materials FA and its derivatives (VA, DHFA, and 4-VG) used in the study were bought as analytical standards with a declared purity > 95%. The research material was commercial cold-pressed flaxseed oil purchased from "Olejarnia Swiecie" (Swiecie, Poland) and obtained immediately after its production. The oil was analyzed after opening the package and stored at -20 degC between analyses. Water content in fresh oil was 0.06% (determined by the Karl Fischer method using a 917 Coulometer set equipped with a diaphragm (Methrom, Herisau, Switzerland)). 2.3. Accelerated Oxidation Test Mixtures of cold-pressed flaxseed oil with FA and its derivatives were prepared as follows: FA and its derivatives (VA, DHFA, and 4-VG) were dissolved in ethanol and added to oil samples (100 g) to obtain a final concentration of 25, 50, 75, 100, 150, and 200 mg per 100 g of oil. An accelerated oxidation test was evaluated on a Rancimat apparatus 743 (Metrohm, Herisau, Switzerland) at 60, 80, and 110 degC with an air flow rate of 20 L/h according to AOCS Official Method Cd 12b-92 . The time that elapsed until these oxidation products appeared was saved as the induction time (IT). Oxidized oil and oxidized oils with phenolic additives were obtained using an accelerated oxidation test at 60 degC for 10 days in a thermal research chamber (KBC-100 W type; WAMED, Warsaw, Poland) according to AOCS Official Method Cg 5-97 . The oil mixtures were prepared as before, but FA and its derivatives were added to the oil sample (200 g) to obtain a final concentration of 80 mg per 100 g of oil. In the thermostatic test, the oils were stored in closed bottles made of dark glass (with a volume of 250 mL). 2.4. Determination of Quality Indices and Fatty Acid Composition The quality indices of oils included acid (AV), peroxide (PV), and anisidine (AnV) values, and the contents of conjugated dienes and trienes were determined on the basis of the following AOCS Official Methods: Te 1a-64 , Cd 8b-90 , Cd 18-90 , and Ch 5-91 , respectively. The fatty acid composition of oils was determined according to the procedure described by Mikolajczak et al. . Methyl-esters of fatty acids were prepared as follows: the oil sample with an internal standard (margaric acid) was methylated at 70 degC for 2 h in a methylating mixture (methanol:chloroform:sulphuric acid 100:100:1, v/v/v). After neutralizing the H2SO4 through the addition of zinc, the solvent was evaporated under a stream of nitrogen. The residue was dissolved in n-hexane and analyzed using a GC-MS QP2010 PLUS gas chromatograph (Shimadzu, Tokyo, Japan) with an SGE BPX-70 capillary column (25 m x 22 mm x 0.25 mm, SGE Analytical Science, Ringwood, Australia) against helium (carrier gas) applied with a flow rate of 1.3 mL/min. The GC-MS conditions were as follows: the interface temperature was set at 240 degC, the ion source temperature was set at 240 degC, and the column temperature was programmed in the range of 150-250 degC. The electron energy was set at 70 eV. Fatty acids were identified based on mass spectra, and their contents were calculated with reference to the internal standard. The repeatability for determining margaric acid was 2.5% (expressed as a coefficient of variation), and the limit of quantification (LOQ) was 0.05 mg/g of oil. 2.5. Determination of Squalene and Sterol Contents The content of sterols and squalene was determined according to the procedure described by Mikolajczak et al. . The compounds were extracted from the oils as follows: a-cholestane (internal standard) solution in ethanol and 2 M KOH solution in ethanol were added to the sample. The mixture was heated at 70 degC for 30 min. The non-saponifying fraction was extracted three times with diethyl ether, and the collected extracts were rinsed with deionized water. The solvent was evaporated on a Buchi R-210 rotary evaporator (BUCHI Labortechnik AG, Flawil, Switzerland) at 45 degC. Derivatization was carried out as follows: pyridine and BSTFA with 1% TMCS were added to the dry extract, and then the mixture was heated at 60 degC for 1 h. Next, the solution was diluted in heptane and analyzed using the GC-MS QP2010 PLUS chromatograph (Shimadzu, Tokyo, Japan) coupled with a mass spectrometer and equipped with a ZB-5MSi capillary column (30 m x 0.25 mm x 0.25 mm, Phenomenex, Torrance, CA, USA). Helium was applied as a carrier gas with a flow rate of 0.9 mL/min. The GC-MS conditions were as follows: injector temperature was set at 230 degC, column temperature was set at 70 degC for 2 min, increased to 230 degC at the rate of 15 degC/min, and to 310 degC at the rate of 3 degC/min, and maintained for 10 min, GC-MS interface temperature was set at 240 degC, ion source temperature was set at 220 degC, and electron energy was set at 70 eV. The total ion current (TIC) mode was used for quantification (100-600 m/z range). Sterols and squalene were identified based on retention times and mass spectra, and their contents were calculated with reference to the internal standard. The repeatability for determining a-cholestane was 2.5% (expressed as a coefficient of variation), and the LOQ was 0.05 mg/g of oil. 2.6. Determination of Tocol Contents The content of tocols was determined according to the procedure described by Mikolajczak et al. . The oil sample was diluted in n-hexane and centrifuged on an Eppendorf Centrifuge 5417R type (Eppendorf AG, Hamburg, Germany) for 10 min (16,000 rpm). The resultant solution was analyzed using an HPLC Agilent Technologies 1200 chromatograph (Santa Clara, CA, USA) equipped with a fluorescence detector of the same company and a LiChrospher Si 60 column (250 mm x 4 mm x 5 mm, Merck, Darmstadt, Germany). A 0.7% solution of iso-propanol in n-hexane was used as the mobile phase at a flow rate of 1 mL/min. The fluorescence detector was set at excitation and emission wavelengths of 296 nm and 330 nm, respectively. The content of tocols was determined from calibration curves prepared for tocopherol standards. The repeatability for determining tocopherol contents was 2.5% (coefficient of variation). The LOQs were 0.45, 0.4, and 0.2 mg/g of the sample for a-, g-, and d-tocopherol, respectively. The linearity of the calibration curves was confirmed in the range of 0.02-16 mg/L. 2.7. Determination of Carotenoid Content The content of carotenoids was prepared and analyzed according to the methodology given by Mikolajczak et al. . After being diluted in n-hexane with b-apo-8'-carotenal (internal standard), the oil sample was saponified by adding a 40% KOH solution in methanol. The solution was shaken in the Multi Rotator RS-60 (Biosan, Riga, Latvia) in the dark at room temperature for 16 h. After saponification, 10% Na2SO4 was added to the sample, and the extraction of carotenoids was carried out four times with n-hexane. The collected extract was evaporated on a Buchi R-210 rotary evaporator at 225 mbar and 45 degC, and the dry extract was dissolved in a methanol:dichloromethane mixture (45:55, v/v). The resultant solution was analyzed by RP-HPLC technique using an Agilent Technologies 1200 chromatograph, equipped with a diode array detector (DAD), a YMC-C30 chromatography column (150 mm x 4.6 mm x 5 mm) and a YMC-C30 precolumn (10 mm x 4.6 mm x 3 mm) (YMC-Europe GmbH, Dinslaken, Germany). The column temperature was 30 degC and a methanol (A) and methyl tert-butyl ether (B) gradient was used for elution. The gradient was programmed as follows: 0-5 min 95% of A, until 25 min decreases to 72% of A, and keeps decreasing until 33 min to 5% of A. Next, it increases to 95% of A and is stable until 60 min. Absorbance was measured at 450 nm. Carotenoids were identified based on the retention times and absorption spectra of the individual carotenoids, and their contents were calculated with reference to the internal standard. The repeatability for determining b-apo-8'-carotenal content was 2.5% (coefficient of variation). The LOQ was 0.05 mg/g of the sample, while the linearity of the calibration curve was confirmed in the range of 1-150 mg/L. 2.8. Determination of Phenolic Compounds The total content of phenolic compounds was determined spectrophotometrically by color reaction according to the procedure described by Mikolajczak and Tanska . Phenolic compounds from the oil sample were extracted three times with 80% methanol (1:10, w/v). The collected extracts were evaporated under a vacuum using a Buchi R-210 rotary evaporator. A solution of Folin-Ciocalteu reagent in water (1:2, v/v), 14% Na2CO3 solution, and deionized water was added to the dry residue. The mixture was incubated in a dark place at room temperature for 1 h. The absorbance of the solution was measured using a microplate reader (FLUOstar OMEGA; BMG Labtech GmbH, Ortenberg, Germany). The phenolic compound content was calculated on the basis of the calibration curve prepared for D-catechin. The extraction of phenolic acids was performed using a vacuum equalizer (Witko, Lodz, Poland) and SPE Supelco columns filled with the diol (500 mg) (Sigma-Aldrich, Saint Louis, MO, USA), as described by Mikolajczak et al. . The phenolic acids were analyzed by RP-HPLC technique using an Agilent Technologies 1200 chromatograph, equipped with a photodiode detector and Eclipse XDB-C18 chromatography column (150 mm x 4.6 mm x 5 mm, Agilent Technologies, Santa Clara, CA, USA). The column temperature was 30 degC, and the mobile phase consisted of water:acetonitrile:formic acid (88:10:2, v/v/v). The isocratic flow rate was equal to 0.8 mL/min. The detection was performed at the wavelengths of 260 and 320 nm. Phenolic acids were identified based on the retention times and absorption spectra of the individual phenolic acids. The content of phenolic acids was determined from calibration curves prepared for phenolic acid standards (FA, p-CA, DHFA, SA, VA, and 4-VG). The repeatability for determining phenolic acid contents was at least 2.1% (coefficient of variation). The LOQ was at least 0.05 mg/g of the sample, while the linearity of calibration curves was confirmed in the range of 1-150 mg/L. 2.9. Statistical Analysis All analyses were performed in triplicate, and the obtained results were analyzed using Statistica 13.1 PL software (StatSoft, Cracow, Poland). The differences between the samples were determined using a one-way analysis of variance (ANOVA), followed by a Tukey test at a p <= 0.05 significance level. 3. Results and Discussion 3.1. Effect of Different Concentrations of Ferulic Acid and Its Derivatives on Oxidative Stability of Cold-Pressed Flaxseed at Different Temperatures In Figure 1, the changes are shown in the IT of cold-pressed flaxseed oil mixtures with FA and its derivatives, i.e., VA, DHFA, and 4-VG. The phenolic additives were added in amounts of 25-200 mg per 100 g of oil, and their antioxidative effect was evaluated in the Rancimat test at 110 degC , 80 degC , and 60 degC . The use of an increasing amount of FA in the Rancimat test at 110 degC resulted in a linear increase in the IT of cold-pressed flaxseed oil . It was determined that the parameter reached up to 2.83 h for 200 mg of FA per 100 g of oil. VA addition at a concentration of 25 mg/100 g showed the most beneficial effects (2.65 h), and its higher concentration in oil (50-200 mg/100 g) resulted in a gradual decrease in IT. In turn, the antioxidant activities of both DHFA and 4-VG were the best at a concentration of 75 mg/100 g. The most noticeable changes in IT of cold-pressed flaxseed oil were after the addition of 4-VG in an amount of 75 mg/100 g, where IT was 3.52 h (increased by 40.8% compared to the control sample). Lowering the temperature in the Rancimat test to 80 degC resulted in an almost 10-fold increase in the IT of cold-pressed flaxseed oil . IT elongated proportionally (as concentration increased) when FA was added. The FA addition at a concentration of 200 mg/100 g increased IT up to 30.62 h (over a 19% increase compared to the control sample). In turn, with the addition of VA, the IT of the oil gradually decreased. It was noted that the control oil had an IT of about 26 h, while after the addition of VA at 200 mg/100 g, it was more than 8% lower. DHFA addition improved IT the most at a concentration of 75 mg/100 g; at the higher concentrations, the elongation of IT was still observed but at a lower rate. The addition of 4-VG at a concentration of 25-100 mg/100 g resulted in a reduction of oil IT by 2-9% (depending on the concentration). Results of the IT in the Rancimat test at 60 degC showed that the phenolic additives generally improved the oxidative stability of cold-pressed flaxseed oil, but their effectiveness varied . A linear relationship was observed between IT values and FA concentration. The highest amount of this phenolic additive resulted in an increase in IT of up to 60% compared to the control sample. DHFA exhibited lower antioxidant effectiveness and caused a noticeable elongation of IT (an increase of 14-42%) at a concentration of 25-100 mg/100 g, but a reverse relationship was discovered. The addition of 4-VG increased IT up to 124 h at a concentration of 75 mg/100 g, but its additions up to 150 mg per 100 g of oil showed comparable antioxidant activity at 60 degC. The effect of VA on the antioxidant stability of flaxseed oil was independent of its concentration in the oil. The phenolic additive application increased IT by 10-18% compared to the control sample. Based on the Rancimat tests at different temperatures, the shelf life of the cold-pressed flaxseed oil at ambient conditions (20 degC) was predicted, and the results are presented in Table 1. The values of this parameter were calculated by plotting the logarithms of ITs versus elevated temperatures and extrapolating them to room temperature . It was evaluated that flaxseed oil with the lowest FA addition (25 mg/100 g) can be stored at 20 degC for 3.71 months, while the control oil (without additives) can be stored for 2.47 months. The higher concentrations of FA in the flaxseed oil extended its shelf life up to 5.31 months (200 mg/100 g). The addition of VA increased the shelf life of flaxseed oil by 23-34% when compared to the control sample, but the observed changes were independent of the additive concentration in the oil. The beneficial effects of DHFA addition were noticeable only at its lower concentrations in oil, ranging from 25 to 75 mg/100 g. In the case of 4-VG, the flaxseed oil shelf life was improved when 100 g of the oil was combined with 75-150 mg of this ferulic acid derivative. It is worth mentioning that cold-pressed flaxseed oil is a widely studied edible oil, and available results of its oxidative stability are varied. In the work of Bozan and Tamelli , IT of flaxseed oil at 110 degC was 1.57 h. In contrast, the IT of flaxseed oils analyzed by Tanska et al. was in the range of 2.00-4.33 h. The oxidative stability of cold-pressed flaxseed oils was also evaluated in the Rancimat test at 100 degC. For example, Raczyk et al. showed that the IT of cold-pressed flaxseed oil was from 3.47 to 5.63 h. Similar results were presented by El-Waseif et al. and Symoniuk et al. with the same measured parameters (ca. 4.90 h). Symoniuk et al. analyzed the stability of cold-pressed flaxseed oils in the Rancimat test at various temperatures (70-140 degC). The authors showed that the IT of the tested oils decreased with increasing temperature and was, on average, 36.81 h at 70 degC and 0.26 h at 130 degC. Furthermore, the oxidative stability of flaxseed oil was improved by adding different antioxidants, including various phenolic compounds. Tanska et al. analyzed the effect of phenolic acid derivatives (4-vinylsyringol (4-VS) and 4-VG) on the stability of three commercially available oils, including cold-pressed flaxseed oil. Phenolic additives were added at concentrations of 20, 40, and 80 mg per 100 g oil and oxidized in the Rancimat test at 110 degC. In general, 4-VG was more effective; the increase in IT after its addition was 5 to 25-fold greater than that of 4-VS. The highest increase was recorded in the case of cold-pressed flaxseed oil, for which the addition of 80 mg 4-VG per 100 g of oil resulted in a 50% increase in IT. The authors suggest that antioxidant activities depend not only on the total phenol content, but also on the type of phenolics present . Cinnamic acid derivatives have high antioxidant activity, which results from the presence of vinyl fragments. However, the reactive center (vinyl fragment) is significantly influenced by the substituent present in various positions of the benzene nucleus . Karamac et al. determined that the activity of phenolic compounds depends on the hydroxyl number of the moieties attached to the aromatic phenol ring, which indicates dihydroxyphenolic acids are more active than their monohydroxy counterparts. In addition, the presence of an ethylene side chain containing an unsaturated bond increases the ability to transfer electrons, stabilizes the resulting phenoxy radical, or offers an additional place to react with reactive oxygen species (ROS) . The temperature factor also seems to affect the antioxidant properties of phenolic compounds. Temperature fluctuations can change the mechanism of action of some antioxidants and affect them in different ways or affect certain reactions in which antioxidants are involved (mainly reactions with lipid radicals) . Antioxidants can also evaporate from the matrix at much higher temperatures . The literature indicates that there is a linear relationship between temperature and the antioxidant activity of phenolic compounds, mainly phenolic acids. For example, Reblova discovered a decrease in antioxidant activity with increasing temperature for VA, similar to our study. Marinova and Yanishlieva showed that an increase in temperature does not change the antioxidant activity of benzoic acid derivatives, while the activity of cinnamic acid derivatives increases. The literature also suggests that the antioxidant activity of FA is dependent on its solubility in oil. This is particularly noticeable in the pharmaceutical industry, where FA is used in skincare and cosmetic applications, making it difficult to formulate oil-based formulations. Therefore, various methods are sought to increase its solubility. An interesting approach is the development of lipophilic feruloylated derivatives through transesterification with different solvents, i.e., ionic liquids, and supercritical carbon dioxide . 3.2. Changes in Quality of Cold-Pressed Flaxseed Oil with the Addition of Ferulic Acid and Its Derivatives in an Oxidation Test Table 2 presents quality indices of fresh and oxidized flaxseed oil samples. AV of fresh cold-pressed flaxseed oil was 1.39 mg KOH/100 g, while PV and AnV values were at a low level (0.39 mEq O2/kg and 0.61, respectively). In the flaxseed oil, no trienes were found, while the content of dienes reached 0.18%. Heating cold-pressed flaxseed oil at 60 degC accelerated the hydrolysis and oxidation processes (Table 2). The AV increased by almost 10% compared to fresh oil. The use of FA and VA additives resulted in an increased amount of free fatty acids in cold-pressed flaxseed oil (AV = 1.67 mg KOH/g). Only the addition of 4-VG resulted in a reduction of AV by more than 40%. The PV in heated oil samples ranged from 6.30 to 9.88 mEq O2/kg, while oxidized control oil and oxidized oil with the addition of FA were characterized by the lowest values of the quality parameter. The 4-VG showed an unfavorable effect because the oil with its addition was characterized by an even higher content of primary oxidation products than the oil without additives (PV was almost 1.5 times higher). Oil with the addition of VA had the lowest content of secondary oxidation products (AnV = 2.60). The AnV in the other oils was comparable to each other and to the oil without any additives (AnV = 14.33). The oxidation process caused an almost 2-fold increase in the share of dienes (0.26-0.30%), while the share of trienes remained unchanged (0.00% in all analyzed oil samples). Although the hydrolysis and oxidation rates in flaxseed oil after its heating at 60 degC varied in terms of the type of phenolic additive, the AV and PV in all samples did not exceed the values indicated in the acceptable standards for cold-pressed oils , i.e., 4.0 mg KOH/g and 15.0 mEq O2/kg, respectively. Hasiewicz-Derkacz et al. confirmed a more pronounced effect for FA compared to our study. They added 0.5 mM FA to cold-pressed flaxseed oil from transgenic seeds (ALA accounted for 2-20% of the total fatty acids) and reported an 85% decrease in the formation of oxidation products at 140 degC. 3.3. Changes in Fatty Acid Composition of Cold-Pressed Flaxseed Oil with the Addition of Ferulic Acid and Its Derivatives in an Oxidation Test The total fatty acid content of fresh cold-pressed flaxseed oil was 97.88 g/100 g; more than 60% were polyunsaturated fatty acids (PUFA) (Table 3). Among them, a-linolenic acid (C18:3) predominated, and the content of linoleic acid (C18:2) was almost 5-fold lower. The analyzed cold-pressed flaxseed oil was also characterized by a low content of saturated fatty acids (SFA), in which the content of palmitic acid (C16:0) did not exceed 5 g/100 g and the content of stearic acid (C18:0) was more than 2-fold lower. The oxidation process caused changes in the fatty acid composition of cold-pressed flaxseed oil (Table 3). The highest degree of their degradation was recorded in oil with the addition of VA (86.37 g/100 g), while the other phenolic additives contributed to the preservation of 94-97% of all fatty acids. The oxidation process itself also caused significant changes in the content of individual groups of fatty acids; their final contents in oil without phenolic additives were 5.45 g/100 g for SFA, 17.30 g/100 g for monounsaturated fatty acids (MUFA), and 68.65 g/100 g for PUFA. It was also noted that 4-VG significantly reduced SFA content by almost 15%. The most noticeable changes in the unsaturated fatty acids (MUFA and PUFA) were recorded in oil with the addition of VA (a decrease of 15.8% and 14.0% compared to fresh oil, respectively). In turn, the addition of DHFA revealed a protective effect on the unsaturated fatty acids (not statistically significant differences compared to fresh oil). VA addition caused the largest changes in the content of individual fatty acids (Table 3). In oil with its addition, the content of oleic acid (C18:1) decreased by over 5%, the content of C18:2 acid by over 10%, and the content of C18:3 acid by almost 15%. It should be noted that the use of phenolic additives meant that most of the content of individual acids was preserved or their losses were small. However, phenolic additives in particular protected unsaturated fatty acids, e.g., DHFA and 4-VG reduced C18:3 acid oxidation (losses to 4%). Additionally, the C18:2 acid content was fully preserved by DHFA and 4-VG, while the C18:1 acid loss in oil with DHFA added was less than 2%. Analysis of the composition of fatty acids indicates that the oil was pressed from flaxseeds, which are characterized by a high-fat content and a high percentage of a-linolenic acid from the omega-3 family . A similar composition of fatty acids in cold-pressed flaxseed oil was found by Tanska et al. , Mikolajczak et al. , Lewinska et al. , and Zhang et al. . 3.4. Changes in the Content of Lipophilic Bioactive Compounds in Cold-Pressed Flaxseed Oils with the Addition of Ferulic Acid and Its Derivatives in an Oxidation Test The fresh cold-pressed flaxseed oil used in the study was characterized by a squalene content of 4.43 mg/100 g (Table 4). The total sterol content was 630 mg/100 g, with b-sitosterol accounting for nearly 35% of the total sterols. The contents of cycloartenol and campesterol were predominant; there were more than 150 mg/100 g of each. Other sterols (stigmasterol and 25-hydroxy-24-methylcholesterol) together accounted for no more than 14% of total sterols. g-Tocopherol predominated among tocols in cold-pressed flaxseed oil (68.18 mg/100 g). An equally high content was found for plastochromanol-8. The content of total tocols in flaxseed oil was 106.52 mg/100 g, with a-tocopherol accounting for only 5.76% of the total tocols in oil. Carotenoids were present in a low concentration (only 0.69 mg/100 g) in the studied flaxseed oil. The contents of b-carotene and lutein were dominant, and trace amounts of a-carotene and zeaxanthin were also found (up to 0.07 mg/100 g). The greatest changes in squalene and total sterol contents were recorded in oil with the addition of VA (decreases of more than 50% and more than 8%, respectively) (Table 4). Furthermore, high losses of squalene were observed in oils with the addition of DHFA (over 46%) and 4-VG (over 43%). In these oils, losses were even higher than in oxidized oil without additives (the squalene content was 3.07 mg/100 g). Only the addition of FA resulted in the retention of almost 80% of the squalene content compared to the fresh oil. The total sterol contents in oils with additives such as FA and DHFA were 592.42 and 594.79 mg/100 g, respectively, and were similar to oxidized oil (586.81 mg/100 g). Individual sterols losses, such as campesterol, stigmasterol, b-sitosterol, 25-hydroxy-24-methylcholesterol, and cycloartenol, were comparable and did not exceed 10% in oils with FA and DHFA additions; they were also comparable to oxidized oil. The addition of VA to oil caused the greatest changes in the content of campesterol, stigmasterol, and b-sitosterol. The final contents of these compounds were 103.93, 29.45, and 197.62 mg/100 g, respectively. Moreover, the addition of VA significantly increased cycloartenol losses (which reached over 12%), even when compared to oxidized oil (153.38 mg/100 g). The content of cycloartenol in other oils ranged from 156.16 to 161.42 mg/100 g. The 4-VG addition showed protective properties for all sterol fractions; losses for their contents ranged from 1.43 to 3.31%. There were no significant differences in the content of unidentified sterol-like compounds in the oils with additives (46.41-47.00 mg/100 g), but they were higher than in oxidized oil without additives (46.23 mg/100 g). Total tocol contents in oils with additives ranged from 63.35 to 75.81 mg/100 g; the lowest content was observed in oil with 4-VG addition and the highest content in oil with DHFA addition (Table 4). The total tocol contents in oxidized oil and oils with the addition of FA and VA were over 70 mg per 100 g. a-Tocopherol has been completely degraded in oils, except for oil with the addition of DHFA, where over 50% of its content has been retained (compared to fresh oil). g-Tocopherol losses were similar to each other and ranged from 24.01% (oil with VA) to 27.63% (oxidized oil). A significant decrease in its content was noted only in the oil with the addition of 4-VG, and the value was 44.83 mg/100 g. Furthermore, the content of plastochromanol-8 was significantly reduced (a decrease of over 42% compared to fresh oil) in oil with the addition of 4-VG. The content of plastochromanol-8 in oxidized oils with the addition of other phenolic additives was 21-22 mg/100 g. The total content of carotenoids in cold-pressed flaxseed oil significantly decreased after the addition of 4-VG (a decrease of almost 74% compared to fresh oil) (Table 4). A high decrease in the content of carotenoids was also noted in oil with DHFA (a decrease of almost 50% compared to fresh oil). Carotenoid content changed similarly in oxidized oil and oil with VA (a decrease of almost 30% compared to fresh oil), whereas FA addition preserved nearly 80% of the total carotenoids present in fresh oil. The content of a-carotene in oxidized oil without additives and oil with DHFA was 0.02 mg/100 g; in oils with 4-VG, it decreased to 0.01 mg/100 g; and in oils with FA and VA, it was the highest (0.03 mg/100 g). The oxidation process significantly reduced the b-carotene content (by more than 50% compared to fresh oil) but adding 4-VG accelerated this process (by more than 80% compared to fresh oil). Only FA prevented oxidation of b-carotene; more than 95% was preserved. The used additions significantly reduced the lutein content in cold-pressed flaxseed oil (losses from 33.95 to 67.70%) compared to oxidized oil, but they did not affect the content of zeaxanthin. Literature data indicate that the squalene and total sterol contents of cold-pressed flaxseed oils are varied. Mikolajczak et al. stated that the squalene content is 2.39 mg/100 g, and the total sterol content reaches almost 285 mg/100 g. Tanska et al. determined that the squalene content in commercial cold-pressed flaxseed oils is in the range of 1.01-4.29 mg/100 g and the total sterol content ranges from 409.40 to 538.83 mg/100 g. Many authors reported that the main sterol fractions in cold-pressed flaxseed oil are also b-sitosterol, cycloartenol, and campesterol. According to research conducted by Tanska et al. , the total tocol content in cold-pressed flaxseed oil ranges from 48.88 to 85.93 mg/100 g. The authors discovered that the dominant tocol fraction is g-tocopherol, but the content of plastochromanol-8 is also high. Choo et al. and Shim et al. also determined the trace content of a-tocopherol in flaxseed oil. According to Obranovic et al. , the carotenoid content of cold-pressed flaxseed oil ranges from 0.18 to 0.30 mg/100 g, but the results vary depending on the harvest year and variety. 3.5. Changes in the Content of Phenolic Compounds in Cold-Pressed Flaxseed Oils with the Addition of Ferulic Acid and Its Derivatives in an Oxidation Test The content of phenolic compounds in cold-pressed flaxseed oil was 1.67 mg/100 g, with phenolic acids accounting for approximately 1% of the total phenolic compounds (Table 5). Among phenolic acids, we found SA (9.87 mg/100 g), FA (3.27 mg/100 g), and p-CA (0.83 mg/100 g). It was found that there were noticeable losses in the content of naturally occurring phenolic acids during the oxidation process (Table 5). Losses of FA exceed 10% in oils with the addition of VA and DHFA, losses of SA ranged from more than 50% to nearly 80%, and p-CA was completely degraded in the analyzed oils. Cold-pressed flaxseed oil without additives lost approximately 27% of its total phenolic acid content due to the oxidation process. It was stated that the total phenolic compound content in other oils increased due to the addition of phenolic antioxidants. Despite the addition of individual phenolic antioxidants in an amount of 80 mg/100 g, most of them decayed during the oxidation process. Only about 29% of FA, VA, and DHFA was in the oil samples after the oxidation process, whereas 4-VG losses were even more than 95%. Siger et al. reported that the total content of phenolic compounds in cold-pressed flaxseed oil ranges from 0.40 to 0.48 mg/100 g. Tanska et al. discovered that the total phenolic compound content can reach as high as 2.19 mg D-catechin/100 g. According to the research of Siger et al. , cold-pressed flaxseed oil contains phenolic acids such as p-hydroxybenzoic, VA, and FA, while Hasiewicz-Derkacz et al. found that vanillin is the most abundant phenolic compound in cold-pressed flaxseed oil. 4. Conclusions Research results indicate that ferulic acid and its derivatives differentially affect oxidative stability and the retention of bioactive compounds in cold-pressed flaxseed oil. It seems that not only the type of additive but also the concentration and temperature of the oil treatment are important. The Rancimat tests performed at different temperatures showed that the optimum concentration of the derivatives used was 75 mg/100 g. However, an increasing tendency was observed for ferulic acid. Furthermore, the low-temperature treatment seems to be more favorable for ferulic acid derivatives. In particular, the addition of vanillic acid is not a good antioxidant for oil matrices at accelerated temperatures (>60 degC) because it reduces the induction time of cold-pressed flaxseed oil. The results of the shelf life prediction at 20 degC showed that all tested phenolic additives could be considered effective antioxidants in cold-pressed flaxseed oil for typical culinary applications, but their concentration seems to be important in the development of new oils with increased oxidative stability. During thermostatic testing, dihydroferulic acid and 4-vinylguaiacol were found to have protective properties for unsaturated fatty acids. A similar tendency was also observed for the content of sterols, while carotenoids and squalene were better protected by ferulic acid (retention of 80%). In contrast, vanillic acid mainly intensified the losses of fatty acids and bioactive compounds, except for carotenoid fractions. The dihydroferulic acid appears to be the most protective against the oil's main antioxidants, tocopherols (a and g homologues). In the future, studies on cold-pressed flaxseed oils stored under natural conditions can be carried out to evaluate the potential antioxidant properties of ferulic acid used in combination with dihydroferulic or/and 4-vinylguaiacol. Author Contributions Conceptualization, N.M. and M.T.; methodology, N.M. and M.T.; software, N.M. and M.T.; validation, N.M. and M.T.; formal analysis, N.M.; investigation, N.M.; resources, N.M., W.P., K.G. and M.T.; data curation, N.M.; writing--original draft preparation, N.M., W.P., K.G. and M.T.; writing--review and editing, N.M., W.P., K.G. and M.T.; visualization, N.M., W.P., K.G. and M.T.; supervision, M.T.; project administration, N.M.; funding acquisition, N.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. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Induction time of cold-pressed flaxseed oil with the addition of phenolic additives (FA--ferulic acid, VA--vanillic acid, DHF--dihydroferulic acid, and 4-VG--4-vinylguaiacol) determined at 110 degC (a), 80 degC (b), and 60 degC (c). foods-12-01088-t001_Table 1 Table 1 Predicted shelf life (x +- SD) at 20 degC (months) of cold-pressed flaxseed oil with addition of phenolic additives. Concentration (mg/100 g) Phenolic Additive FA % * VA % * DHFA % * 4-VG % * 0 2.47 e +- 0.11 - 2.47 c +- 0.11 - 2.47 d +- 0.11 - 2.47 e +- 0.11 - 25 3.71 d +- 0.06 50.2 3.31 a +- 0.06 34.0 4.62 a +- 0.09 87.0 2.53 de +- 0.10 2.4 50 3.84 c +- 0.10 55.5 3.20 a +- 0.08 29.5 4.11 b +- 0.02 66.4 2.69 d +- 0.08 8.9 75 3.89 c +- 0.07 57.5 3.13 b +- 0.06 26.7 3.99 c +- 0.07 61.5 3.61 a +- 0.05 46.1 100 3.98 c +- 0.08 61.1 3.09 b +- 0.08 25.1 2.55 d +- 0.08 3.2 3.29 b +- 0.09 33.2 150 4.39 b +- 0.05 77.7 3.05 b +- 0.05 23.5 1.76 e +- 0.05 -28.7 3.15 c +- 0.08 27.5 200 5.31 a +- 0.12 115.0 3.04 b +- 0.09 23.1 1.63 f +- 0.04 -34.0 2.06 f +- 0.05 -16.6 *--percentage change compared to control sample (oil without phenolic additive); FA--ferulic acid; VA--vanillic acid; DHFA--dihydroferulic acid; 4-VG--4-vinylguaiacol; n = 3; x +- SD-- mean value +- standard deviation; a-f--mean values in the same column followed by different superscript letters are significantly different (one-way ANOVA and Tukey's test, p <= 0.05). foods-12-01088-t002_Table 2 Table 2 Quality indices (x +- SD) of fresh cold-pressed flaxseed oil and oil oxidized at 60 degC without and with phenolic additives. Quality Indices Fresh Oil Oxidized Flaxseed Oil with 80 mg/100 g of - FA VA DHFA 4-VG AV (mg KOH/g) 1.39 +- 0.00 b 1.52 a +- 0.00 1.67 a +- 0.00 1.67 a +- 0.01 1.25 b +- 0.19 0.83 c +- 0.00 PV (mEq O2/kg) 0.39 +- 0.00 e 6.67 d +- 0.09 6.30 d +- 0.33 7.53 c +- 0.22 8.55 b +- 0.29 9.88 a +- 0.08 AnV (-) 0.61 +- 0.00 f 14.33 b +- 0.06 16.28 a +- 0.00 2.60 e +- 0.08 6.91 d +- 0.02 11.41 c +- 0.18 Content of Dienes (%) 0.18 +- 0.00 e 0.26 d +- 0.00 0.30 a +- 0.00 0.27 c +- 0.00 0.26 d +- 0.00 0.29 b +- 0.00 Content of Trienes (%) 0.00 +- 0.00 a 0.00 a +- 0.00 0.00 a +- 0.00 0.00 a +- 0.00 0.00 a +- 0.00 0.00 a +- 0.00 FA--ferulic acid; VA--vanillic acid; DHFA--dihydroferulic acid; 4-VG--4-vinylguaiacol; AV--acid value; PV--peroxide value; AnV--anisidine value; n = 3; x +- SD--mean value +- standard deviation; a-f--mean values in the same line followed by different superscript letters are significantly different (one-way ANOVA and Tukey's test, p <= 0.05). foods-12-01088-t003_Table 3 Table 3 Fatty acid composition (x +- SD) of fresh cold-pressed flaxseed oil and oxidized at 60 degC without and with phenolic additives. Fatty Acids Fresh Oil Oxidized Flaxseed Oil with 80 mg/100 g of - FA VA DHFA 4-VG Palmitic Acid (C16:0) (g/100 g) 4.08 b +- 0.12 4.08 b +- 0.06 4.12 b +- 0.00 3.92 b +- 0.03 4.28 a +- 0.09 3.94 b +- 0.11 Stearic Acid (C18:0) (g/100 g) 1.92 a +- 0.06 1.37 c +- 0.28 1.60 bc +- 0.01 1.93 a +- 0.10 1.81 ab +- 0.18 1.92 a +- 0.07 Oleic Acid (C18:1) (g/100 g) 18.78 a +- 0.81 17.30 a +- 0.18 17.90 a +- 0.38 17.81 b +- 0.60 18.45 a +- 0.78 17.57 a +- 1.27 Linoleic Acid (C18:2) (g/100 g) 12.92 a +- 0.16 12.75 a +- 0.01 12.78 a +- 0.48 11.59 b +- 0.12 12.90 a +- 0.20 12.92 a +- 0.42 a-Linolenic Acid (C18:3) (g/100 g) 60.00 a +- 1.52 55.90 d +- 0.13 56.81 cd +- 1.71 51.13 e +- 0.24 57.73 bc +- 0.45 58.36 b +- 0.08 Total (g/100 g) 97.88 a +- 0.48 91.40 c +- 0.38 93.21 bc +- 2.57 86.37 d +- 0.90 95.55 b +- 1.70 94.82 bc +- 1.75 SSFA (g/100 g) 6.18 a +- 0.06 5.45 d +- 0.34 5.72 cd +- 0.01 5.86 bc +- 0.06 6.09 ab +- 0.27 5.96 b +- 0.03 SMUFA (g/100 g) 18.78 a +- 0.81 17.30 b +- 0.18 17.90 ab +- 0.38 17.81 ab +- 0.60 18.45 a +- 0.78 17.57 b +- 1.27 SPUFA (g/100 g) 72.92 a +- 1.36 68.65 b +- 0.14 69.58 ab +- 2.20 62.71 c +- 0.36 70.63 ab +- 0.64 71.28 a +- 0.51 n-3:n-6 4.64:1 4.38:1 4.44:1 4.41:1 4.47:1 4.52:1 FA--ferulic acid; VA--vanillic acid; DHFA--dihydroferulic acid; 4-VG--4-vinylguaiacol; SSFA--sum of saturated fatty acids; SMUFA--sum of monosaturated fatty acids; SPUFA--sum of polyunsaturated fatty acids; n-3:n-6--ratio of omega 3 to omega 6 fatty acids; n = 3; x +- SD--mean value standard deviation; a-d--mean values in the same line followed by different superscript letters are significantly different (one-way ANOVA and Tukey's test, p <= 0.05). foods-12-01088-t004_Table 4 Table 4 Content of lipophilic bioactive compounds (+- SD) in fresh cold-pressed flaxseed oil and oxidized at 60 degC without and with phenolic additives. Bioactive Compounds Fresh Oil Oxidized Flaxseed Oil with 80 mg/100 g of - FA VA DHFA 4-VG Sterols (mg/100 g) Campesterol 112.12 a +- 1.16 105.40 c +- 0.18 105.75 c +- 0.95 103.93 d +- 1.11 107.50 b +- 0.34 110.52 a +- 0.18 Stigmasterol 32.05 a +- 0.99 29.62 c +- 0.24 30.12 bc +- 0.55 29.45 c +- 0.62 30.68 ab +- 0.15 31.15 a +- 0.05 b-Sitosterol 216.64 a +- 1.59 202.41 bc +- 2.52 204.46 b +- 5.33 197.62 c +- 0.24 203.91 b +- 1.25 210.33 a +- 1.99 25-Hydroxy-24-Methylcholesterol 53.17 a +- 0.95 49.78 b +- 0.51 48.68 c +- 0.17 48.66 c +- 0.47 49.53 b +- 0.43 52.32 a +- 0.45 Cycloartenol 166.65 a +- 1.63 153.38 b +- 1.96 156.75 b +- 3.86 146.63 c +- 5.22 156.16 bc +- 1.21 161.42 b +- 1.98 Unidentified Sterol-Like Compounds 47.02 a +- 1.14 46.23 a +- 0.42 46.67 a +- 1.95 46.41 a +- 0.18 47.00 a +- 0.23 47.02 a +- 0.02 Total 629.98 a +- 1.70 586.81 c +- 4.50 592.42 c +- 7.47 572.71 d +- 4.39 594.79 c +- 3.61 612.75 b +- 4.63 Tocols (mg/100 g) a-Tocopherol 6.14 a +- 0.24 tr tr tr 3.18 b +- 0.38 tr g-Tocopherol 68.18 a +- 0.67 49.34 c +- 0.24 50.15 c +- 1.07 51.81 b +- 0.68 50.58 bc +- 0.62 44.83 d +- 0.08 Plastochromanol-8 32.20 a +- 0.22 20.87 c +- 0.15 21.19 c +- 0.58 22.06 b +- 0.23 22.05 b +- 0.09 18.52 d +- 0.26 Total 106.52 a +- 1.14 70.21 d +- 0.39 71.34 d +- 1.65 73.87 c +- 0.44 75.81 b +- 0.91 63.35 e +- 0.19 Squalene (mg/100 g) Total 4.43 a +- 0.21 3.07 c +- 0.61 3.52 b +- 0.63 1.97 e +- 0.49 2.39 d +- 0.15 2.50 d +- 0.05 Carotenoids (mg/100 g) a-Carotene 0.07 a +- 0.02 0.02 bc +- 0.01 0.03 b +- 0.01 0.03 b +- 0.00 0.02 bc +- 0.00 0.01 c +- 0.00 b-Carotene 0.32 a +- 0.05 0.15 c +- 0.09 0.27 ab +- 0.10 0.25 b +- 0.02 0.17 c +- 0.02 0.06 d +- 0.01 Lutein 0.32 a +- 0.00 0.29 a +- 0.01 0.21 b +- 0.03 0.21 b +- 0.06 0.16 bc +- 0.00 0.10 c +- 0.01 Zeaxanthin 0.01 a +- 0.00 0.01 a +- 0.00 0.01 a +- 0.00 0.01 a +- 0.00 0.01 a +- 0.00 0.01 a +- 0.00 Total 0.69 a +- 0.07 0.48 b +- 0.09 0.55 ab +- 0.08 0.49 b +- 0.08 0.35 c +- 0.02 0.18 d +- 0.02 FA--ferulic acid; VA--vanillic acid; DHFA--dihydroferulic acid; 4-VG--4-vinylguaiacol; tr--trace amounts; n = 3; x +- SD--mean value +- standard deviation; a-e--mean values in the same line followed by different superscript letters are significantly different (one-way ANOVA and Tukey's test, p <= 0.05). foods-12-01088-t005_Table 5 Table 5 Content of phenolic compounds (x +- SD) in fresh cold-pressed flaxseed oil and oxidized oil at 60 degC without and with phenolic additives. Phenolic Compounds Fresh Oil Oxidized Flaxseed Oil with 80 mg/100 g of - FA VA DHFA 4-VG p-CA (mg/100 g) 0.83 a +- 0.00 0.63 b +- 0.00 0.00 c +- 0.00 0.00 c +- 0.00 0.00 c +- 0.00 0.00 c +- 0.00 FA (mg/100 g) 3.27 b +- 0.03 3.17 b +- 0.12 9909.25 a +- 86.24 2.96 b +- 0.17 2.92 b +- 0.31 3.17 b +- 0.02 SA (mg/100 g) 9.87 a +- 0.10 6.33 b +- 0.21 2.45 e +- 0.24 3.90 d +- 0.00 4.43 cd +- 0.40 4.91 c +- 0.34 VA (mg/100 g) 0.00 b +- 0.00 0.00 b +- 0.00 0.00 b +- 0.00 19,877.08 a +- 31.75 0.00 b +- 0.00 0.00 b +- 0.00 DHFA (mg/100 g) 0.00 b +- 0.00 0.00 b +- 0.00 0.00 b +- 0.00 0.00 b +- 0.00 1579.82 a +- 20.44 0.00 b +- 0.00 4-VG (mg/100g) 0.00 b +- 0.00 0.00 b +- 0.00 0.00 b +- 0.00 0.00 b +- 0.00 0.00 b +- 0.00 90.20 a +- 1.56 Total Phenolic Compounds (mg/100 g) 1.67 d +- 0.02 1.15 e +- 0.02 23.42 a +- 0.58 22.17 b +- 0.02 23.49 a +- 0.08 3.19 c +- 0.13 p-CA--p-Coumaric acid; FA--ferulic acid; SA--sinapic acid; VA--vanillic acid; DHFA--dihydroferulic acid; 4-VG--4-vinylguaiacol; n = 3; x +-SD --mean value +- standard deviation; a-e--mean values in the same line followed by different superscript letters are significantly different (one-way ANOVA and Tukey's test, 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. Krulj J. Pezo L. KoJic J. Solarov M.B. Teslic M. Quality evaluation of cold-pressed oils and semi-defatted cake flours obtained on semi-industrial scale J. Food Nutr. Res. 2021 60 217 228 2. Popa V.-M. Gruia A. Raba D. Dumbrava D. Moldovan C. Bordean D. Mateescu C. Fatty acids composition and oil characteristics of linseed (Linum usitatissimum L.) from Romania J. Agroaliment. Proc. Technol. 2012 18 136 140 3. Mikolajczak N. Tanska M. 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PMC10000396 | Background: Sodium new houttuyfonate (SNH) has been reported to have anti-inflammatory, anti-fungal, and anti-cancer effects. However, few studies have investigated the effect of SNH on breast cancer. The aim of this study was to investigate whether SNH has therapeutic potential for targeting breast cancer. Methods: Immunohistochemistry and Western blot analysis were used to examine the expression of proteins, flow cytometry was used to detect cell apoptosis and ROS levels, and transmission electron microscopy was used to observe mitochondria. Results: Differentially expressed genes (DEGs) between breast cancer-related gene expression profiles (GSE139038 and GSE109169) from GEO DataSets were mainly involved in the immune signaling pathway and the apoptotic signaling pathway. According to in vitro experiments, SNH significantly inhibited the proliferation, migration, and invasiveness of MCF-7 (human cells) and CMT-1211 (canine cells) and promoted apoptosis. To explore the reason for the above cellular changes, it was found that SNH induced the excessive production of ROS, resulting in mitochondrial impairment, and then promoted apoptosis by inhibiting the activation of the PDK1-AKT-GSK3b pathway. Tumor growth, as well as lung and liver metastases, were suppressed under SNH treatment in a mouse breast tumor model. Conclusions: SNH significantly inhibited the proliferation and invasiveness of breast cancer cells and may have significant therapeutic potential in breast cancer. breast cancer sodium new houttuyfonate ROS apoptosis National Natural Science Foundation of China32172925 This study was supported by a research grant from the National Natural Science Foundation of China (NO.32172925). pmc1. Introduction Breast cancer is a focus of global attention because of its high incidence and high mortality rates. According to the 2020 report from the International Agency for Research on Cancer (IRAC), breast cancer has surpassed lung cancer as the most common cancer worldwide, with an incidence rate of 11.7% . Breast cancer has great clinical heterogeneity, and patients with different subtypes of the disease have varying clinical prognoses. Canine mammary tumors are frequently regarded as models for the study of human breast cancer because of their similarities in pathology, histology, and shape . Additionally, phosphatidylinositol-4,5-bisphosphate 3-kinase (PIK3CA) mutations, abnormalities in the PI3K-AKT pathway, and a crucial gene implicated in cancer initiation and development are shared between human breast cancer and canine mammary tumors . Currently, many medications used to treat breast cancer in clinical treatment have varying degrees of severe side effects . Recently, bioactive compounds extracted from traditional Chinese medicine have shown potential anti-cancer abilities. Sodium new houttuyfonate (SNH) is the chemical synthesis of houttuynia, and it has anti-inflammatory , anti-fungal and anti-cancer properties . Studies have suggested that SNH can exert anti-inflammatory effects by promoting the generation of reactive oxygen species (ROS) , which are considered as a product of oxygen consumption and cell metabolism. Endogenous ROS include superoxide anions, hydrogen peroxide, and hydroxyl radicals . Excessive ROS may disrupt mitochondrial functions, mainly manifesting as mitochondrial membrane potential decrease, mitochondrial transcription factor A decrease, mitochondrial mass increase, and mitochondrial DNA fragmentation increase . In general, endogenous ROS are maintained within a normal range. ROS levels outside the normal range will lead to the occurrence of disease . Therefore, ROS can be considered as a potential target for cancer therapy. Studies have shown that abnormal activation of the PI3K-AKT pathway plays a critical role in the occurrence, metastasis, and drug resistance of breast cancer, and it is closely related to the prognosis of breast cancer, all of which make it a potential therapeutic target for breast cancer . The biological function of the PI3K-AKT pathway can be modulated by ROS. The combination of polydatin and 2-deoxy-d-glucose promotes apoptosis in breast cancer by eliminating endogenous ROS production , as does hyperoside . Moreover, total secondary saponin from the rhizome of Anemone raddeana showed anti-proliferation and pro-apoptotic activities on MCF-7 cells through the ROS-mediated mitochondrial apoptosis pathway . Genistein can lead to mitochondrial dysfunction through ROS accumulation, induce the inactivation of PI3K-AKT, and synergistically promote the anti-tumor effect of Centchroman . GSK3b is a downstream target of AKT. The serine 9 phosphorylation of GSK3b is negatively correlated with the activity of GSK3b, which is adversely associated with the viability of breast cancer cells . Thus, this study investigated whether SNH could induce mitochondrial dysfunction through ROS overgeneration and inactive the PDK1-AKT pathway to induce apoptosis of breast cancer cells in vitro and in vivo. 2. Materials and Methods 2.1. Bioinformatics Analysis Two expression profiles related to breast cancer (GSE139038 and GSE109169) were screened from GEO DateSets accessed on 15 August 2022. The differentially expressed genes (DEGs) and the common DEGs shared between the two datasets were shown using a Venn diagram accessed on 15 August 2022). The Gene Ontology resource (GO, accessed on 16 September 2022) and the Kyoto Encyclopedia of Genes and Genomes (KEGG, accessed on 16 September 2022) were used to analyze the enrichment of GO and KEGG involved in these common DEGs, and bubble charts of GO and KEGG enrichment analysis were plotted using bioinformatics accessed on 16 September 2022), an online platform for data analysis and visualization. An interaction network of these common DEGs was constructed, and the protein interaction network of some important genes was emphatically analyzed using Cytoscape software. The molecular structure of SNH was assessed using PubChem accessed on 16 August 2022). The potential target genes of SNH were predicted through SwissTargetPrediction accessed on 16 August 2022). The expression analysis and prognosis analysis of target genes were conducted individually using GEPIA accessed on 17 September 2022) and Kaplan-Meier Plotter accessed on 17 September 2022). 2.2. Reagents and Antibodies The reagents used were as follows: sodium new houttuyfonate (Yuanye, Shanghai, China, CAS: 112714-99-5); docetaxel (Yuanye, Shanghai, China); hydroxypropyl-b-cyclodextrin (HP-b-CD; Solarbio, Beijing, China); N-acetyl-cysteine (NAC; Macklin, Shanghai, China); matrix adhesive (Biozellen, Frontier, NE, USA); Opti-MEM I medium (Gibco, Billings, MA, USA); and crystal violet (BioSharp, Hefei, China). The kits used were as follows: Cell Counting Kit-8 (Hycezmbio, Wuhan, China), ROS Detection Kit (Hycezmbio, Wuhan, China), BCA Protein Quantification Kit (Hycezmbio, Wuhan, China), Apoptosis Detection Kit (Hycezmbio, Wuhan, China); and Transwell chamber (Corning, NY, USA). According to the protocol recommended by the manufacturer, the following antibodies were used for Western blot or immunofluorescence: Anti-BAX (Wanleibio, WL01637), Anti-p-GSK3b (Wanleibio, WL03683), Anti-b-actin (ABclonal, AC038), Anti-Bcl-2 (ABclonal, A19693), Anti-cleaved PARP p25 (ABclonal, A19612), Anti-caspase-9 (ABclonal, A0281), Anti-PDK1 (ABclonal, A0834), Anti-p-PDK1 (ABclonal, AP0426), Anti-AKT (ABclonal, A20799), Anti-p-AKT (ABclonal, WLP001), Anti-GSK3b (ABclonal, A11731), Anti-MMP1 (ABclonal, A22080), HRP Goat Anti-Rabbit IgG (ABclonal, AS014), Alexa Flour 594-Goat Anti-Rabbit IgG (ABbox, AD9279), and Cy3 Goat Anti-Rabbit IgG (H + L) (ABclonal, AS007). 2.3. Cell Culture Human breast cancer cell line MCF-7 (kindly donated by Zhiqiang Dong Laboratory at Huazhong Agricultural University) and canine mammary cancer cell line CMT-1211 (kindly provided by the Degui Lin Laboratory at the China Agricultural University) were used in this study. Both cell lines were cultured in DMEM (Gibco) medium containing 10% fetal bovine serum (Hycezmbio, Wuhan, China) and 2% penicillin-streptomycin solution (Gibco) at 37 degC with 5% CO2. 2.4. Cell Viability Assay Cells at a density of 1 x 104 cells/well were seeded into 96-well plates. When the density reached 50-60%, different concentrations of SNH were added. After treatment for 24 h, 10 mL (5 mg/mL)/well of Cell Counting Kit-8 (CCK-8, Hycezmbio, Wuhan, China) was added and incubated with cells at 37 degC for 30 min. Cell viability was measured through absorbance (optical density) with a microplate reader (Bio-Rad Instruments, Hercules, CA, USA) at 450 nm. Another set of experiments was also conducted. The cells were cultured in 96-well plates with different concentrations of SNH for different time (0, 12, 24, 36, 48, and 60 h). The cell culture medium containing the drugs was changed once every 12 h. Other operations remained unchanged unless otherwise indicated. 2.5. Cell Migration Assay Cell migration was detected using a wound-healing migration assay. The cells were inoculated into 6-well plates with 1 x 105 cells/well. When the cells reached 80-85% confluence, a 200 mL plastic sucker scraped the cell layer once, and the exfoliated cells were washed with sterile phosphate buffered saline (PBS). The cells were cultured with serum-reduced Opti-MEM I medium (Gibco, Billings, MA, USA). The wounds were photographed when the scrape wound was introduced (0 h) and at a designated time (24 h) using an inverted microscope. 2.6. Cell Invasion Assay This step was conducted according to the reagent instructions (Biozellen, Frontier, NE, USA). Matrigel A (2x) at a concentration of 1/15 was added into 8 mm transwell chambers. Then, the matrigel in chambers was refrigerated at 4 degC for 3 h, and 7.5 x 104 cells/well which have been treated with SNH for 24 h were suspended in 100 mL culture solution and added to the upper compartment of the chamber. DMEM medium containing 10% fetal bovine serum was added to the lower compartment of the chamber. The cells were cultured in an incubator at 37 degC for 24 h. Next, the cells in the chambers were fixed with methanol and stained with crystal violet. The images were photographed using an optical microscope (Olympus, Tokyo, Japan). 2.7. Apoptosis Assay Apoptosis was detected using Annexin V-FITC (fluorescein isothiocyanate) and PI (propidium iodide) double staining. The staining procedures and detection method were conducted according to the Apoptosis Detection Kit's instructions (Hycezmbio, Wuhan, China). The cell density was adjusted to 1 x 106/mL and suspended at 250 mL binding buffer. The cells were gently vortexed and incubated with 5 mL of Annexin V-FITC and 10 mL of PI at room temperature for 10 min against exposure to light. The apoptosis rates were detected using flow cytometry (CytoFLEX, Beckman, State Key Laboratory of Agricultural Microbiology at Huazhong Agricultural University). 2.8. Intracellular ROS Assay ROS generation was detected using the fluorescent probe DCFH-DA. The cells were collected after being treated with drugs. The staining procedures and detection method for the cells were conducted according to the ROS Detection Kit's instructions (Hycezmbio, Wuhan, China). The cell density was adjusted to 1 x 106/mL. The cells were stained with 1:1000 diluted probe at 37 degC for 30 min against exposure to light and washed twice with PBS. The reactive oxygen positive control reagent was Rosup, provided by the ROS Detection Kit, with a concentration of 50 mg/mL. Rosup was diluted in serum-free DMEM medium at 1:1000 and incubated cells at room temperature for 30 min. The DCFH-DA probe was loaded in accordance with the above procedures. The ROS levels were detected using flow cytometry (CytoFLEX, Beckman, State Key Laboratory of Agricultural Microbiology at Huazhong Agricultural University). 2.9. Transmission Electron Microscopy Cells were seeded into 6-well plates at a density of 1 x 105 cells/well. When the confluence rate of the cells reached 60-70%, the cells were treated with varying concentrations of SNH for 24 h. Samples were processed successively: fixed, dehydrated, and permeated. Resin blocks containing samples were cut into ultrathin sections (80 nm thick) with a Leica UC6 ultrathin microtome. Ultrathin sections were observed using a transmission electron microscope (TEM) (H7650, Hitachi, Japan) at 100 kV after being stained with uranium acetate. 2.10. Western Blot Analysis Protein immunoblotting was performed according to previous methods . The total cellar proteins were harvested with RIPA containing 1% PMSF and 1% phosphatase inhibitors. The proteins' concentrations for each treatment group were determined using a BCA Kit. Proteins were separated with electrophoresis using 10% sodium dodecyl sulfate (SDS)-polyacrylamide gel and then transferred to polyvinylidene fluoride (PVDF). The embranees were successively incubated with antibodies and secondary antibodies. Anti-b-actin was considered an internal reference protein. Protein expression was detected with the French Vilber Lourmat FX7 detection system. 2.11. Cellular Immunofluorescence Staining Cells were seeded into 24-well plates at a density of 1 x 104 cells/well. SNH at different concentrations or other drugs were added and remained for 24 h. After treatment, the cells were fixed with 4% (v/v) paraformaldehyde for 30 min and permeated with 0.5% (v/v) Triton X-100 in PBS for 20 min. Subsequently, the cells were blocked with 5% (v/v) goat serum for 2 h and incubated with primary antibodies overnight at 4 degC. The cells were incubated with Alexa Flour 594-Goat Anti-Rabbit IgG or Cy3 Goat Anti-Rabbit IgG (H + L) in the dark for 1 h and stained with 4,6-diamidino-2-phenylindole (DAPI, Beyotime, Shanghai, China) for 10 min. In this experiment, the cells were washed three times with PBS between each treatment. Images were observed using a fluorescence microscope (Olympus, Tokyo, Japan). 2.12. In Vivo Experiment Five week-old Balb/C female mice were purchased from the Experimental Animal Center of Huazhong Agricultural University (Wuhan, China) one week prior to the experiment. When the mice were six weeks old, 1 x 106 cells/mouse were inoculated at the 4th accessory mammary pad. After 10 days of injection, they were randomly divided into 5 groups: blank control group, negative control group (HP-b-CD, 0.1 mL (30% w/v)/mouse, i.p.), docetaxel group (8 mg/kg, i.p.), low-dose SNH group (20 mg/kg, i.p.), high-dose SNH group (40 mg/kg, i.p.),and mock group, which were administered by intraperitoneal injection once every 2 days for 22 days. During the treatment, the mice were weighed, and the tumor volume was measured every 2 days. After that, the mice were euthanized according to the ethical requirements of experimental animals of Huazhong Agricultural University (HZAUMO-2022-0125) and the United States National Institutes of Health. Tumor tissues and lung, heart, liver, spleen, kidney, and other tissues of the mice were harvested and fixed in 4% paraformaldehyde. Tumor volume (V) = 0.5 x length x width2. 2.13. Mouse Tissue Section Staining Subsequently, the tumor and organs were dehydrated after being fixed in formaldehyde for 48 h and embedded in paraffin, which were cut into 5 mm thick sections for hematoxylin and eosin (H&E) staining. An optical microscope (Olympus, Tokyo, Japan) was used for image acquisition. Tumor sections were also used for immunofluorescence staining. After being dewaxed to water with xylene and gradient ethanol, tumor sections were soaked in citric acid antigen repair buffer (pH 6.0) and heated in a microwave oven for antigen repair. The following procedures were similar to those of cellar immunofluorescence staining. Finally, the glass sheet needed to be sealed with an anti-fluorescent quenching agent. A fluorescence microscope (Olympus, Tokyo, Japan) was used for image collection. 2.14. Statistical Analysis The dates were obtained as mean +- SD of at least three independent experiments. Differences between groups were calculated using one-way ANOVA or nonlinear regression (GraphPad Prism 8). A level of * p < 0.05 was considered significant, ** p < 0.01, *** p < 0.001, or **** p < 0.0001 were considered extremely significant, and p > 0.05 (ns) was considered not significant. 3. Results 3.1. DEGs' Analysis of Breast Cancer Based on the GEO Database Given that the occurrence and development of breast cancer involves expression changes of multiple genes, we analyzed the expression profiles related to breast cancer in the GEO database (GSE139038 and GSE109169). In these two GEO datasets, GEO2R was applied to analyze these DEGs . The intersection of the two datasets was calculated by drawing Venn diagrams on the online tool, as shown in Figure 1a. The results show that there are 137 DEGs. These DEGs were further analyzed based on Gene Ontology (GO) annotations and KEGG pathways. We found that the 137 DEGs were involved in biological processes, including the regulation of PI3K signaling, cell proliferation, etc. . The cellular components involved included the extracellular region, the extracellular matrix, etc. . The molecular functions of these DEGs were heparin binding, integrin binding, CXCR3 chemokine receptor binding, etc. . KEGG analysis showed that these DEGs were mainly involved in the PPAR signaling pathway, the PI3K-AKT signaling pathway, etc. . To further study the interactions of these DEGs, we constructed an interaction network diagram of these DEGs using Cytoscape, highlighting the interaction relationships of some important DEGs, as shown in Figure 1f,g. 3.2. Network Pharmacological Analysis of SNH First, we recognized the molecular structure of SNH in PubChem and predicted the potential target genes of SNH using SwissTargetPrediction . After further analysis, we found that two potential target genes of SNH were consistent with 137 DEGs, namely MMP13 and MMP1 . The expression of MMP1 between breast cancer tissues and normal tissues was significantly different. The invasiveness of breast cancer is tightly linked to MMP1, and high expression of MMP1 usually predicts a poor prognosis in breast cancer . 3.3. SNH Inhibited the Proliferation and Invasiveness of Breast Cancer Cells Studies have shown that SNH exhibits a marked anti-proliferation effect on tumors. In order to explore the effect of SNH on breast cancer proliferation, MCF-7 and CMT-1211 cells were selected and treated with different concentrations of SNH. We found that SNH significantly decreased the cell viability of breast cancer cells, with a concentration-dependent decline. The IC50s of MCF-7 and CMT-1211 were 91.38 mM and 84.48 mM, respectively . Compared to the control group, the MCF-7 mortality rate reached approximately 90 percent at a concentration of 180 mM, and the CMT-1211 mortality rate reached approximately 80 percent at a concentration of 140 mM . In addition, compared with the control group, SNH had a more significant inhibitory effect on the proliferation of tumor cells as medication time increased . The medicinal effects of administration over time were more recognizable. Scratch assay and transwell assay were used to evaluate the migration and invasiveness ability of MCF-7 and CMT-1211 cells after treatment with SNH. The results showed that SNH could inhibit cell migration and invasiveness . In addition, the Western blot results showed that the protein expression of MMP1 decreased as the concentration of SNH increased . Additionally, apoptosis is an important process in maintaining the homeostasis of the cellular environment. The flow cytometry results showed that the apoptosis rate of SNH group was significantly higher than that of the control group through Annexin V/PI staining . The Western blot results showed that the expression of cleaved caspase-9 and cleaved PARP and the ratio of BAX/Bcl-2 increased after SNH treatment , which indicated apoptosis occurred in MCF-7 and CMT-1211. Combining the above results, we found that SNH could inhibit the migration capacity and invasiveness of breast cancer cells, promote cell apoptosis, and have conspicuous anti-tumor activity in vitro. 3.4. SNH Induced Cell Apoptosis by Increasing Intracellular ROS Level An appropriate amount of ROS can promote the occurrence and development of cancer, but excessive production of ROS will show an anti-tumor effect. DCFH-DA probe was applied to detect the content of ROS in the cells. The flow cytometry results showed that, compared with the control group, the level of intracellular ROS in the SNH group was significantly higher . Additionally, transmission electron microscopy images of MCF-7 and CMT-1211 revealed extensive damage to mitochondria after treatment with SNH, as follows: mitochondrial swelling, disrupted mitochondrial cristae (most disappeared), partial mitochondrial lysis, and heterogeneous mitochondrial matrix . NAC is an ROS scavenger that can effectively reduce the generation of ROS. Compared with the SNH group, the ROS level of the combined NAC and SNH group was significantly lower . At the same time, the Western blot results showed that the expression levels of MMP1 and Bcl-2 in the combined NAC and SNH group were partially restored, while the expression levels of BAX, cleaved caspase-9, and cleaved PARP decreased . These results suggest that the overgeneration of ROS induced by SNH may be an important factor for apoptosis in MCF-7 and CMT-1211. 3.5. SNH Induced Apoptosis by Suppressing the Activation of the PDK1-AKT-GSK3b Pathway via ROS At present, it is unclear whether SNH inhibits the activation of PI3K-AKT in MCF-7 and CMT-1211 cells through excessive production of ROS. The Western blot results showed that, compared with the control group, the phosphorylation levels of PDK1 and AKT were lower in the SNH group, as shown in Figure 5a,b. However, compared with SNH group, the expression levels of p-PDK1 and p-AKT were partially restored in the NAC and SNH combined group , and immunofluorescence tests showed consistent results . In addition, we detected the activity of GSK3b, a downstream target of AKT. GSK3b is a negative regulator in breast cancer. The results showed that as the SNH concentration increased, the expression level of GSK3b did not change significantly, but the phosphorylation level of GSK3b (ser9) showed a downward trend . Correspondingly, the expression of p-GSK3b (ser9) was partially restored in the NAC and SNH combined group . These results suggest that SNH could promote increased activity of the GSK3b protein. In conclusion, SNH inhibited the activation of PDK1-AKT-GSK3b by promoting the overgeneration of intracellular ROS. 3.6. SNH Inhibited the Growth of Breast Tumor To further evaluate the effect of SNH on tumor growth in vivo, a subcutaneous homotransplant mouse model was established using CMT-1211 . In order to better evaluate the effect of SNH, docetaxel (DOC) was added as a positive control group in the treatment of Balb/C mice. There was no significant difference in the changes in body weight among all treatment groups . As shown in Figure 6c, treatment with DOC was the most effective among all the experimental groups, while the HP-b-CD group (control group, a solvent for SNH) had the fastest rate of tumor growth. Compared with the control group, both low-dose and high-dose SNH had significant inhibitory effects on breast tumors, and the therapeutic effect became more significant as the concentration increased . The heart, spleen, and kidney pathological test results of each treatment group showed that there were no distinct abnormalities in the pathological sections. At the same time, histological testing showed that, in the control group, there were apparent tumor metastases in the liver (black line boxes) and lung, and the boundary between red pulp and white pulp in the spleen was obscure. In the treatment group, SNH resulted in elevated nuclear fragmentation of tumor tissue and reduced tumor metastases in the liver and lung as the SNH concentration increased . In addition, the phosphorylation levels of p-AKT and BAX in tumor tissues were detected using an immunofluorescence assay. The results showed that, compared with the control group, the expression level of p-AKT was significantly lower in the SNH treatment group, while the expression level of BAX was significantly higher . The expression levels of MMP1 and cleaved PARP were measured using Western blot. Similar to the in vitro results, SNH significantly inhibited the expression of MMP1 compared with the control group . Cleaved PARP is one of the main indicators of apoptosis, and the expression level of cleaved PARP in the SNH treatment group was significantly higher than that in the control group . Collectively, these results indicated that SNH has a significant anti-tumor effect in vivo. 4. Discussion It has been reported that gene mutations (breast cancer genes BRCA 1 and BRCA 2, etc. ) can result in the emergence of breast cancer and promote the survival and metastasis of cancer cells . Through statistical analysis of the GEO database, we found certain breast cancer-related DEGs that had a strong relationship with the invasiveness and apoptosis of breast cancer and cancer-related pathways. Breast cancer is one of the tumors with a high mortality rate, and its heterogeneity and drug resistance make the clinical treatment of breast cancer very challenging . However, the active ingredients in traditional Chinese medicines and their derivatives have attracted people's attention because of their great therapeutic potential. Therefore, it is meaningful to find active ingredients of traditional Chinese medicine that can treat breast cancer effectively. SNH, a derivative of houttuynium, has been used in the clinical treatment of pelvic inflammatory disease. SNH has also been found to have anti-tumor activity . Nevertheless, few studies have investigated the influence of SNH on breast cancer. In this study, a mouse mammary tumor model was successfully established, and SNH was found to exhibit significant anti-breast cancer activity both in vivo and in vitro. We found that SNH could induce the overgeneration of ROS and result in mitochondrial dysfunction in MCF-7 and CMT-1211 cells. The overgeneration of ROS inactivated the PI3K-AKT pathway, thereby increasing GSK3b activity, increasing the expression level of BAX, cleaved caspase-9, and cleaved PARP, and finally causing DNA damage in MCF-7 and CMT-1211 cells. Previous studies have shown that SNH has an important effect on the proliferation and invasiveness of non-small cell lung cancer . In light of the similarity between canine breast cancer and human breast cancer and the tumor-forming ability of canine mammary tumor cell CMT-1211 in Balb/C mice , two cell lines (CMT-1211 and MCF-7) were selected. The results showed that SNH could significantly inhibit the growth of breast tumors in vivo. Meanwhile, we also found that SNH inhibited the proliferation and migration of breast cancer cells in vitro, as evidenced by the wound healing rates. In addition, the flow cytometry results showed that the apoptosis rates of MCF-7 and CMT-1211 increased, which was also demonstrated using Western blot analysis. All the results aligned with previous reports . When cells receive apoptotic signals, BAX and Bcl-2 are recruited to the outer mitochondrial membrane to interact and activate, which will induce mitochondrial damage . In this research, it was found that the ratio of BAX/Bcl-2 increased. This suggests that the pro-apoptotic effect of SNH may be relevant to mitochondrial function. As a commonly used anti-inflammatory drug in clinical practice, SNH has been proven to exert anti-inflammatory effects by increasing the level of ROS . Studies have shown that ROS has a close relationship with cancer and that the excessive accumulation of ROS can cause mitochondrial membrane potential reduction, thereby inducing mitochondrial dysfunction, bioenergy failure, and apoptosis . In our study, we found that SNH could promote intracellular ROS overgeneration using flow cytometry, which enhanced along with the increase in SNH concentration, and this phenomenon was partially inhibited by NAC. In addition, the Western blot results showed that compared with the SNH group, the expressions of BAX, cleaved caspase-9, and cleaved PARP in MCF-7 and CMT-1211 cells were lower in the combined NAC and SNH group, and the expression of Bcl-2 was higher than that in SNH group. These results suggest that SNH may cause mitochondrial dysfunction and initiate cell apoptosis by promoting the production of ROS. As a by-product of cell metabolism, ROS participates in the regulation of the PI3K-AKT pathway . Low or moderate levels of ROS can activate the PI3K-AKT pathway and inhibit apoptosis , while excessive ROS can be a negative regulator of this pathway . As a direct downstream target of AKT, GSK3b acts as a tumor suppressor in breast cancer, mediating the expression of cyclin D1 to regulate the cell cycle and increase chemosensitivity . Phosphorylation of serine 9 of GSK3b reduces the activity of GSK3b, while phosphorylation of tyrosine 216 of GSK3b enhances the activity of GSK3b . GSK3b can be present in the cytoplasm and nucleus, but the activity of nuclear GSK3b is higher than that of cytosolic GSK3b. In the process of apoptosis signaling, nuclear GSK3b regulates a large number of transcription factors and encodes apoptotic regulatory proteins that target mitochondria. For example, GSK3b can form a complex with p53 to induce the expression of BAX . The polymerized BAX outside of mitochondria facilitates the release of apoptotic proteins from mitochondria into the cytoplasm, where these proteins (such as cytochrome c, apoptotic protease activating factor-1, ATP/dATP, and caspase-9) assemble apoptotic bodies, triggering the caspase cascade . In this study, the Western blot results showed that the expressions of p-PDK1, p-AKT1, and p-GSK3b (ser9) decreased, which represented a concentration gradient-dependent pattern, suggesting that SNH could inactivate the PI3K-AKT pathway, increase the activity of the GSK3b protein, and inhibit the cell viability of MCF-7 and CMT-1211. Abnormal activation of the PI3K pathway is one of the most common phenomena in the development of breast cancer. Therefore, inhibitors targeting the PI3K signaling pathway are promising drugs for treating breast cancer. Currently, there are several drugs that target the PI3K pathway: pan-PI3K inhibitor, PI3K isoform-specific inhibitors, AKT inhibitor, rapamycin analogue or mTOR inhibitors, etc. . Studies have shown that PI3K-AKT signaling activates estrogen receptor a in an estrogen-independent manner, and AKT overexpression protects breast cancer cells from tamoxifen-induced apoptosis . This indicates that inhibition of PI3K can enhance the therapeutic effect on ER+ breast cancer cells. In addition, some drugs developed according to the molecular structure and function of natural products have been shown to be able to treat breast cancer by inhibiting the overactivation of the PI3K pathway. For example, it has been proven that quercetin suppressed the activation of PI3K and AKT, which increased the ratio of BAX/Bcl-2 to induce apoptosis of breast cancer cells, as well as significantly inhibiting the growth and metastasis of CD44+/CD24 breast cancer stem cells in vivo . In a study of ginsenoside treating MDA-MB-231 cells and HUVEC cells, it was found that ginsenoside could reduce intracellular AKT/mTOR/p70S6K and hypoxia inducible factor-1-a. The activation of vascular endothelial growth factor receptor 2 in HUVECs induced by vascular endothelial growth factor was eliminated . In this study, it was found that SNH induced mitochondrial dysfunction by promoting excessive generation of ROS and inactivated the PDK1-AKT signaling pathway, which activated GSK3b activity. Activated GSK3b entered the nucleus, and regulated the expression of BAX in the nucleus and polymerization of BAX in the mitochondrial outer membrane, triggering the mitochondrial apoptotic pathway, including an increased BAX/Bcl-2 ratio and caspase cascade. On the basis of the above-mentioned results, it is suggested that SNH potentially has a therapeutic effect on breast cancer. 5. Conclusions In conclusion, the occurrence of breast cancer is involved in a large number of DEGs that participate in cancer-related pathways. SNH can promote the excessive accumulation of ROS in MCF-7 and CMT-1211 cells, target the PI3K-AKT-GSK3b pathway to induce cell apoptosis in vitro, and significantly inhibit the growth of breast tumors in vivo. Thus, SNH may be a potential drug for breast cancer treatment. Acknowledgments The authors thank Degui Lin (China Agricultural University, Beijing, China) for providing the CMT-1211 cell line and Zhiqiang Dong (Huazhong Agricultural University, Wuhan, China) for providing the MCF-7 cell line. The authors thank all members of the Laboratory of Veterinary Clinical Diagnosis for their helpful discussions and suggestions. Supplementary Materials The following supporting information can be downloaded at: Figure S1: The western blot original images. Click here for additional data file. Author Contributions Conceptualization: L.H.; methodology: L.H. and H.F.; project administration: L.H., H.F., B.Y., W.L., X.W., T.U., H.G., N.Z. and C.Q.; writing--original draft: L.H., H.F. and C.Q.; writing--review and editing: L.H., B.Y. and C.Q. 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 followed the norms of the Institutional Ethical Committee for Animal Care and Use of Huazhong Agricultural University (HZAUMO-2022-0125) and the United States National Institutes of Health. Informed Consent Statement Not applicable. Data Availability Statement The datasets generated and analyzed during this study are available from the corresponding author on reasonable request. All data and materials, as well as software applications, support their published claims and comply with field standards. Conflicts of Interest The authors declare no conflict of interest. Abbreviations AKT Protein kinase B BAX Bcl2-Associated X Bcl-2 B-cell lymphoma-2 Casp9 Caspase 9 CCK-8 Cell Counting Kit-8 DCFH-DA 2',7'-Dichlorodihydrofluorescein diacetate GO Gene Ontology GSK3b Glycogensynthasekinase-3b KEGG Kyoto Encyclopedia of Genes and Genomes NAC N-Acetyl-L-cysteine PARP Poly ADP-ribose polymerase PDK1 3-phosphoinositide-dependent protein kinase-1 PI3K Phosphatidylinositol3-kinase PMSF Phenylmethanesulfonyl fluoride RIPA Radio Immunoprecipitation Assay ROS Reactive oxygen species SNH Sodium new houttuyfonate Figure 1 DEGs' analysis associated with breast cancer in the GEO database. (a) The common DEGs between GSE139038 and GSE109169 are shown with a Venn diagram. (b-e) Bubble charts were used to show the GO and KEGG enrichment analyses for these DEGs. (f) Interaction network analysis of the common DEGs was performed using Cytoscape software. (g) Emphasizing the interaction network analysis of DEGs related to MMP1. All results are expressed as mean +- SD of three independent experiments. Figure 2 Network pharmacology analysis of SNH. (a) The chemical structural formula of SNH. (b) Category statistics of potential targets of SNH. (c) The potential targets of SNH were predicted using SwissTargetPrediction. (d) The common target genes of SNH and these two profiles (GSE139038 and GSE109169). (e) Differential expression of MMP1 in breast cancer. (f) Relationship between MMP1 and prognosis in breast cancer. All results are expressed as mean +- SD of three independent experiments. * p < 0.05. Figure 3 SNH inhibited the invasive and proliferative abilities of MCF-7 and CMT-1211 and promoted apoptosis. (a) Cell Counting Kit-8 kits were used to detect the activity of MCF-7 and CMT-1211 after treatment with different concentrations of SNH for 24 h. (b) Cell Counting Kit-8 kits were used to assess the cell activity of MCF-7 and CMT-1211 cells treated with different concentrations of SNH at 0, 12, 24, 36, 48, and 60 h. (c,d) Wound-healing assays were used to measure the cell migration capacity after SNH treatment for 24 h. Scale bar: 1000 mm. (e,f) Transwell chambers precoated with matrigel were used to examine the cell invasion ability of MCF-7 and CMT-1211 cells after SNH treatment for 24 h. Scale bar: 200 mm. (g,h) Western blot was used to detect the expression levels of MMP1 in MCF-7 and CMT-1211 cells treated with SNH for 24 h. (i,j) Flow cytometry was used to examine the effect of SNH on apoptosis. (k,l) Western blot was used to detect the expression levels of apoptosis-related proteins BAX, Bcl-2, cleaved caspase-9, and cleaved PARP in MCF-7 and CMT-1211 after being treated with SNH for 24 h. The western blot original images in the Figure S1. All results are expressed as mean +- SD of three independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, ns = not significant. Figure 4 SNH induced apoptosis of MCF-7 and CMT-12111 by promoting the excessive accumulation of ROS. (a,b) Flow cytometry was used to detect the level of ROS in MCF-7 and CMT-1211 after treatment with different concentrations of SNH. (c,d) TEM was used to observe the mitochondria of MCF-7 and CMT-1211 after treatment with different concentrations of SNH. Red boxes and red arrows pointed to mitochondria. 6000x Bar: 2 mM; 60,000x Bar: 200 nm. (e,f) After treatment with 0 mM, NAC (10 mM), SNH (60 mM in MCF-7, 50 mM in CMT-1211), and NAC combined with SNH, flow cytometry was used to detect the level of ROS in MCF-7 and CMT-1211. (g,h) After treatment with 0 mM, NAC (10 mM), SNH (60 mM in MCF-7, 50 mM in CMT-1211), and NAC combined with SNH, the expression levels of MMP1 were analyzed using Western blot. The western blot original images in the Figure S1. (i,j) After treatment with 0 mM, NAC (10 mM), SNH (60 mM in MCF-7, 50 mM in CMT-1211), and NAC combined with SNH, Western blot was applied to analyze the expression levels of apoptosis-related proteins BAX, Bcl-2, cleaved caspase-9, and cleaved PARP in MCF-7 and CMT-1211. All results are expressed as mean +- SD of three independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, ns = not significant. Figure 5 SNH acted by inhibiting the activation of the PDK1-AKT-GSK3b pathway. (a,b) After treatment with the different concentrations of SNH for 24 h, the expression levels of PDK1, p-PDK1, AKT, p-AKT (ser473), GSK3b, and p-GSK3b (ser9) were analyzed using Western blot. (c,d) After treatment with 0 mM, NAC (10 mM), SNH (60 mM in MCF-7, 50 mM in CMT-1211), and NAC combined with SNH, the expression levels of PDK1, p-PDK1, AKT, p-AKT (ser473), GSK3b, and p-GSK3b (ser9) were analyzed using Western blot. The western blot original images in the Figure S1. (e,f) After treatment with the different concentrations of SNH for 24 h, the expression level of p-AKT (ser473) was assessed using immunofluorescence staining. Scale bar: 200 mm. (g,h) After treatment with 0 mM, NAC (10 mM), SNH (60 mM in MCF-7, 50 mM in CMT-1211), and NAC combined with SNH, the expression level of p-AKT (ser473) was assessed using immunofluorescence staining. Scale bar: 200 mm. All results are expressed as mean +- SD of three independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, ns = not significant. Figure 6 SNH was previously able to inhibit tumor growth in vivo. (a) Schematic diagram of establishing the mouse model of tumor and treatment regimen. (b) Changes in the body weight of mice in each group during treatment. (c) Changes in tumor volume during treatment in each group of mice. (d,e) The tumors of the mice were collected and weighed after the mice were euthanized. (f) H&E staining of mouse organs (lung, liver, spleen, heart, and kidney) and tumor tissues. (g,h) Immunofluorescence staining of p-AKT in tumors. Scale bar: 200 mm. (i,j) The expression of MMP1 in tumor tissues was analyzed using Western blot. (k,l) The expression of cleaved PARP in tumor tissues was analyzed using Western blot. The western blot original images in the Figure S1. All results are expressed as mean +- SD of three independent experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, ns = not significant. 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. |
PMC10000398 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050924 diagnostics-13-00924 Review Sarcoma Botryoides: Optimal Therapeutic Management and Prognosis of an Unfavorable Malignant Neoplasm of Female Children Margioula-Siarkou Chrysoula 1 Petousis Stamatios 1* Almperis Aristarchos 1 Margioula-Siarkou Georgia 1 Lagana Antonio Simone 2 Kourti Maria 3 Papanikolaou Alexios 1 Dinas Konstantinos 1 Pavlik Edward J. Academic Editor 1 Gynaecologic Oncology Unit, 2nd Department of Obstetrics and Gynaecology, Aristotle University of Thessaloniki, Hippokration General Hospital, 54642 Thessaloniki, Greece 2 Unit of Gynecologic Oncology, ARNAS "Civico-Di Cristina-Benfratelli", Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, 90127 Palermo, Italy 3 3rd Department of Pediatrics, Aristotle University of Thessaloniki, Hippokration General Hospital, 54642 Thessaloniki, Greece * Correspondence: [email protected] 01 3 2023 3 2023 13 5 92422 12 2022 05 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 ). Embryonal rhabdomyosarcoma (ERMS) is a rare malignancy and occurs primarily in the first two decades of life. Botryoid rhabdomyosarcoma is an aggressive subtype of ERMS that often manifests in the genital tract of female infants and children. Due to its rarity, the optimal treatment approach has been a matter of debate. We conducted a search in the PubMed database and supplemented it with a manual search to retrieve additional papers eligible for inclusion. We retrieved 13 case reports and case series, from which we summarized that the current trend is to approach each patient with a personalized treatment plan. This consists of a combination of local debulking surgery and adjuvant or neoadjuvant chemotherapy (NACT). Effort is made in every approach to avoid radiation for the sake of preserving fertility. Radical surgeries and radiation still have a role to play in extensive disease and in cases of relapse. Despite the rarity and aggressiveness of this tumor, disease-free survival and overall prognosis is excellent, especially when it is diagnosed early, compared with other subtypes of rhabdomyosarcoma (RMS). We conclude that the practice of a multidisciplinary approach is appropriate, with favorable outcomes; however, larger-scale studies need to be organized to have a definite consensus on optimal management. sarcoma botryoides fertility-sparing surgery embryonal rhabdomyosarcoma genital tract prognosis treatment local debulking neoadjuvant chemotherapy radiation This research received no external funding. pmc1. Introduction Rhabdomyosarcoma (RMS) is the most common soft tissue tumor of early childhood and young adulthood, accounting for 4 to 6% of all malignancies in this age group, with boys being affected 1.5 times more frequently than girls. The primary sites of origin are in the region of the head and neck (35-40%), followed by the genitourinary tract (25%) . There are three major histologic subtypes of RMS described in the literature: embryonal, alveolar, and pleomorphic/undifferentiated, with embryonal rhabdomyosarcoma (ERMS) being the most common subtype (2/3 of genitourinary cases) . This last one can be further classified into the classic subtype, the spindle cell subtype, and the botryoid subtype . The botryoid subtype of ERMS is suggested to be the most common according to the literature. This specific rare type of tumor has an embryologic origin in the skeletal muscle cells and arises from the mucosal surfaces on the walls of hollow organs, such as the vagina, bladder, biliary tract, and nasopharynx of infants, or, more rarely, the uterine cervix . Sarcoma botryoides most usually affects young people; however, it can also present in some rare cases in the elderly. It also seems that botryoid sarcoma arising from the vagina tends to develop in very young girls during infancy and early childhood . Cervical and uterine tumors, on the other hand, primarily develop in older females with a peak incidence in the second decade . The name botryoides originates from the ancient Greek root borty(s), which indicates the appearance of "a bunch of grapes". The typical presentation of the tumor is a nodular, grape-like mass protruding from the vagina, which should alarm every doctor since an early diagnosis is paramount to preventing death and preserving fertility in this delicate age. In the last decades, there has been a paradigm shift in the treatment of patients, including a multidisciplinary approach consisting of a variety of surgical procedures, radiation therapy, and systemic chemotherapy . The main purpose of the present manuscript is to provide a comprehensive narrative review of the literature and summarize the main outcomes regarding the optimal therapeutic management and prognosis of this rare neoplasm of female childhood. 2. Methods A literature search was performed in September 2022 through the PubMed, Scopus, and Web of Science databases. The main objective of the present study was to identify any type of research article reporting outcomes about therapeutic management and/or prognosis of cases diagnosed with botryoid sarcoma. The literature search was focused on the period 1990-2022. An electronic search was conducted by using the terms "botryoid sarcoma" [tiab] or botryoid rhabdomyosarcoma [tiab]. Observational cohort studies, both prospective and retrospective; case series; case reports; and narrative and systematic reviews that reported on the management and the prognosis of botryoid sarcoma were included in the present review. Studies were included irrespective of stage of disease at initial diagnosis and use of adjuvant therapy. The exclusion criteria concerned studies with incomplete data that did not permit definitive conclusions, non-English studies, and published abstracts without available full text. The main outcomes of interest to identify in the included studies were age at diagnosis, primary location of the tumor, main symptom, size, stage, presence of metastases, treatment, status after treatment, diagnosis of relapse, treatment of relapse, follow up in months, and outcome as well as the main immunohistochemistry biomarkers used for final diagnosis. Systematic search initially identified 221 papers potentially eligible for inclusion in the present analysis. After adjusting for inclusion and exclusion criteria, there were finally 13 case series or case reports included in the present review. 3. Results 3.1. Management According to the literature search, female patients with a diagnosis of botryoides sarcoma are most commonly admitted to the hospital due to abnormal vaginal bleeding or a "grape-like" polypoid or prolapsing mass protruding from the vaginal introitus. In some cases, additional symptoms have also been described such as leukorrhea and malodorous discharge . In addition, clinicians must be aware of characteristics of this unusual disease, especially the common sites of origin (vagina, bladder, etc.), the aggressiveness of the tumor, and the clinical manifestations, to avoid misdiagnosis and mismanagement, since benign polyps in the vagina or cervix are relatively uncommon in children. Furthermore, some authors also suggest that any polypoidal mass spotted in a child should be considered as botryoid RMS unless proven otherwise, given the fact that this kind of tumor can rightly be suspected in the majority of cases, and, thus, contributing to a more favorable management of the patient . The initial workup usually includes imaging procedures, with first being ultrasound, followed by MRI of the primary site and regional lymph nodes, which is the best imaging method for RMS, given its superior ability to depict soft tissue changes. A computerized tomography (CT) scan and bone marrow biopsy can also provide assistance in assessing any metastatic manifestation from RMS , since the primary sites of metastasis in genitourinary RMSs are the lungs and the bone marrow . According to the literature, a risk-specific approach to staging is recommended, based on the Intergroup Rhabdomyosarcoma Study Group (IRSG) clinical categorization method and the TNM staging approach for rhabdomyosarcoma in order to determine the patient's clinical risk group; this will consequently stratify the treatment. Additionally, Borinstein et al. , in a recently published consensus article, included the tumor's PAX/FOXO1 fusion status (positive/negative) in the risk stratification of patients, since the expression of this fusion gene is associated with dismal outcomes. Molecular testing (e.g., FISH, reverse transcription PCR, or next-generation sequencing) can readily identify PAX/FOXO1 fusions, and because results may impact treatment decisions, it was recommended by these sarcoma experts to test for FOXO1 fusions on all patients with alveolar or embryonal histology. For the diagnosis of botryoid-variant RMS, three crucial criteria have been proposed that must be fulfilled: a polypoid appearance of the lesion, an origin below a mucous membrane-covered surface, and the presence of a cambium layer . However, the gold standard for the diagnosis is histopathology and post-surgery immunohistochemistry, although, in some cases, the diagnosis is achieved by preoperative histopathology or intraoperative frozen section . The optimal management of botryoid RMS is a debatable matter for gynecologists. Until the 1970s, radical surgery with pelvic exenteration was regarded as the treatment of choice. Over the years, the Intergroup Rhabdomyosarcoma Study Group (IRSG) had an important impact on changing that practice, so that the frequency of radical surgery was progressively reduced from 100% in the first IRSG study to 13% in the fourth IRSG study . Surgical treatment has evolved from radical exenterations to local surgical resection in appropriate candidates along with other treatment modalities that are offered such as multi-agent adjuvant or neoadjuvant chemotherapy with or without radiotherapy. Exenterative surgery still plays a role in treating persistent or recurrent tumors . In recent years, the effective treatment for sarcoma botryoides has been considered local control of vaginal and cervical tumor with fertility-sparing methods such as polypectomy, conization, local excisions, and robot-assisted radical trachelectomy . Cases were found in the literature in which vaginectomy and buccal mucosa vaginoplasty was implemented as local therapy for pediatric vaginal rhabdomyosarcoma in the spirit of local control for genitourinary RMS with the purpose of avoiding radiation. Due to the fact that about half of the cases of botryoid sarcoma affect the vagina, adequate local control is paramount in the treatment of these patients, as suggested by the high recurrence rates observed in these patients when treated with chemotherapy alone . Given the high incidence of micrometastatic disease that leads to relapse in patients treated only with local therapy, all RMS patients (where possible) were treated with adjuvant chemotherapy. The current trend, as seen in the majority of cases presented in Table 1, is to begin with multi-agent NACT as the first step to downstage the tumor and then proceed with excision with a safe margin of 1 cm to 2 cm, followed by 6-12 cycles of adjuvant chemotherapy to limit the chance of recurrence. Standardized schemes of chemotherapy are based on protocols created by the IRSG. The most widely used regimen of chemotherapy for children and young adults is the combination of vincristine, actinomycin D, and cyclophosphamide (VAC), usually given in 6 to 12 cycles . The recommendations of Borinstein et al. , who proposed a treatment algorithm based on the risk group and the gene fusion status of the patient with RMS, are consistent with this practice. The management of this tumor poses a great challenge since it mostly occurs at a young age, when the preservation of hormonal, sexual, and reproductive function is fundamental. This makes fertility-sparing procedures more enticing while radiation and radical excision are not routinely preferred. Nevertheless, they still play an important role and should be reserved for cases of relapse and for the treatment of gross residual disease following surgery or chemotherapy. This approach is further encouraged by the results of the studies performed by the IRSG, which stated that the 5-year survival among patients with nonmetastatic disease was not statistically different among those who underwent versus among those who did not undergo postoperative radiation therapy. These conclusions omitted the irrefutably negative effects of radiation on maintaining the fertility of the young . While surgery can be considered for lesions that can be resected with minimal morbidity, radiotherapy is often used to treat the primary tumor site, if not initially treated, and to treat metastatic sites when such therapy is feasible. Furthermore, it can be observed that there are patients who complete therapy for RMS and frequently are not able to achieve complete radiographic response by cross-sectional imaging, although their PET scans are often normal. This finding is likely due to tumor scarring or differentiation. At this point, it is suggested that resection or biopsy of a residual tumor is not recommended except for the cases in which they are enlarging or causing pain, because the extent of the tumor response does not predict survival. These cases that remain PET avid are challenging to manage, and the decision whether to biopsy or resect a residual PET-avid tumor must be made on a case-by-case basis, weighing the risks of morbidity versus the benefit. 3.2. Prognosis As with most malignancies, the key prognostic factor for the prognosis of botryoid RMS is the extent of disease and early disease stage at diagnosis. Overall, soft tissue sarcomas tend to have a dismal prognosis with a high recurrence risk for all stages, ranging from 45 to 73% (40% recurrence in the lung, 13% in the pelvic area). Furthermore, a great number of patients present with recurrence within the first 2 years after primary therapy . However, despite its malignancy and rarity, botryoid sarcoma is associated with a very favorable prognosis (95% survival at 5 years), which has seen a dramatic improvement in recent years through the utilization of multidisciplinary treatment . As indicated by the included studies, the majority of cases do not present distal metastases, which also attributes to the favorable outcomes. Several studies over the years indicated the dramatically improved prognosis, with Raney RB Jr et al. highlighting the 5-year overall survival rates of 87% in patients with early-stage disease and Raney RB et al. reporting overall survival rates up to 97%. Hawkins DS et al. demonstrated that lesions arising from the cervix, which are more common among children than among adult patients, appear to have a better prognosis than the ones arising from other parts of the female genital tract. Nonetheless, although patients with recurrent RMS tend to have poor long-term prognosis, the 5-year survival rate after recurrence for botryoid ERMS versus other embryonal tumors is more favorable, reaching 64% vs. 26%, respectively . It is obvious that long-term follow up is necessary to guarantee adequate oncological and functional results. 4. Discussion RMS is a rare tumor in childhood and adolescence, accounting for 4-6% of pediatric cancers. The female genital tract is considered the prognostically favorable site, given the improved outcomes during the last several decades. Botryoid sarcoma accounts for the majority of cases of the most common RMS histologic subtype: embryonal RMS. It is found under the mucosal surface of body orifices such as the vagina, bladder, and cervix and accounts for around 10% of all RMS cases. Until today, no clear risk factor for botryoid sarcoma could be identified with certainty due to the low number of published cases. The vast majority of cases occur sporadically. Data from a number of literature reports mention the following risk factors: aging, a certain race (African-American women have double the incidence of White Americans), 5 or more years of tamoxifen prescription, and history of radiation exposure. However, the parity, age of menarche, and menopause were not identified to affect the occurrence of RMS . Chemical exposure, maternal age greater than 30 years, low socioeconomic position, and environmental factors all led to the development of RMS, according to one study . 4.1. Molecular Pathways Involved in Botryoid Sarcoma The pathophysiology behind the formation of sarcoma botryoides remains unknown until today. The greater percentage of children who present with this malignancy have no antecedent risk factors. However, it is more likely to develop in individuals with familial diseases that induce mutations in genes responsible for cell proliferation and death (such as Li-Fraumeni syndrome). Despite the mainly sporadic character of the malignancy, a small portion of cases have been associated with genetic diseases such Li-Fraumeni cancer susceptibility syndrome, familial pleuropulmonary tumor, neurofibromatosis Type I, and Beckwith-Wiedemann syndrome. However, the incidence may be higher in patients diagnosed with RMS before the age of 3 . Specific gene alterations such as KRAS activation and p53 inactivation have been linked to the presentation of RMS. Most embryonal rhabdomyosarcomas, in particular, have a point mutation in exon 6 of the p53 gene on chromosome 17. In a family, the heterozygous p53 germline mutation was reported as the source of the Li-Fraumeni cancer susceptibility syndrome, which presents as a cluster of soft tissue cancers (including sarcomas). Dehner et al. also reported a connection between the blastoma family and pleuropulmonary tumors, as well as confirming DICER1 autosuggest, implying that RMS in children must be treated in a broader context to account for the possibility of pleuropulmonary blastoma familial tumor predisposition syndrome . The identification of DICER1 mutation is notable since it is found in 60% of Sertoli-Leydig cancers, and germline mutations found in Dicer1 increase the possibility of developing rare cancers. Mousavi and Akhavan revealed the occurrence of cervical sarcoma botryoides in two sisters, suggesting that hereditary factors may play a role in the development of sarcoma botryoides . Malignant mixed Mullerian tumor, widely known as carcinosarcoma, can develop exophytically from the uterine wall or cervix and have a sarcomatous gross and microscopic appearance. Nevertheless, malignant mixed Mullerian tumors usually tend to affect older people, in contrast with ERMS . For the time being, it seems reasonable at a minimum to strongly consider referral to genetic counseling for patients who are younger at diagnosis, whose tumors have anaplastic features, or who have a significant family history of malignancy. 4.2. Diagnostic Approach According to the literature, the diagnosis of this tumor is difficult to make, but as far as the management of this tumor is concerned, there are a variety of approaches in the treatment armamentarium, ranging from extreme, radical procedures to more conservative ones. Nuclear MRI is the gold standard for determining where the tumor originates from (whether it is in the endometrium, myometrium, or cervix) as well as the spread and involvement of neighboring structures. Because of its rarity and high-risk, malignant nature originating in the embryonic mesenchyme, botryoid sarcoma should be suspected in young-age females with vaginal bleeding or a prolapsed mass, since typically the tumor develops behind the mucosal membrane of the organs, forcing the growth to take on a characteristic grape-like form. The importance of histology in RMS prognosis cannot be overstated. Although there are three types of RMS (embryonal, alveolar, and undifferentiated), the embryonal type is the more prevalent and has a better prognosis than the alveolar type, which is rare and has a worse prognosis . The Intergroup Rhabdomyosarcoma Studies (IRS) classifies RMS based on (i) the main site, (ii) tumor size, (iii) lymph node involvement, (iv) surrounding tissue infiltration, and (v) the occurrence of metastases . The stage is established using two systems: the Intergroup Rhabdomyosarcoma Study Group clinical categorization method (Table 2) and the TNM staging approach for rhabdomyosarcoma (Table 3) . Table 2 reports the Intergroup Rhabdomyosarcoma Study Group clinical classification system for rhabdomyosarcoma. It is actually a classification of rhabdomyosarcoma cases into four clinical groups, based on the extent of disease, resectability, and margin status. 4.3. Therapeutic Modalities It is of paramount importance to organize a personalized treatment plan, considering the extent of the disease and the fertility preservation. The management of botryoid rhabdomyosarcoma poses a great challenge for gynecologists. In the past, the traditional treatment for these types of tumors involved exenterative procedures, but today, modalities such as fertility-sparing methods, e.g., polypectomy, conization, local excisions, and robot-assisted radical trachelectomy, are offered and are the ones mostly implemented for the preservation of the reproductive ability. In the last decades, a variety of procedures have been added to the options of pediatric genitourinary and anorectal reconstruction. Buccal mucosa grafts are now widely employed in both adult and pediatric urology for urethral reconstruction with acceptable results. Recent reports have established that buccal mucosa vaginoplasty leads to good outcomes in patients with Mayer-Rokitansky-Kuster-Hauser syndrome (MRKH--agenesis of the Mullerian structures and vagina), complete androgen insensitivity syndrome, and repair of urogenital sinus, as far as cosmetic and functionality results are concerned. Evidence suggests that the grafts retain favorable characteristics over time and adapt well to rapid growth demands such as those imposed by puberty. Harvesting the graft is straightforward and associated with minimal morbidity. In addition, buccal grafts greatly resemble the vaginal tissue that they are to replace. Nevertheless, as with every newly introduced procedure, long-term follow up is necessary to assess the oncological outcomes since it does not represent a standard of care but rather an intervention that holds promise as a viable option with minimal esthetic impact. It was the first IRGS trial (1972 and 1978) that recommended systematic chemotherapy following extensive surgery such as radical hysterectomy or pelvic exenteration for ERMS of the genital tract . The second IRGS trial (1978-1984) suggested NACT for the first time to minimize the extent of the tumor, allowing for a less radical surgery . Multi-agent adjuvant chemotherapy with or without the addition of radiotherapy plays a substantial role in the effective management of sarcoma botryoides, apart from the surgical resection of the tumor. In clinical practice, there are standardized schemes of chemotherapy that can be used preoperatively to minimize the volume of the tumor or after surgical resection to limit the chances of recurrence. The most frequently used regimen of chemotherapy for children and young adults with nonmetastatic disease is the triplet of vincristine, actinomycin D, and cyclophosphamide (VAC), and it is based on the protocols of IRSG . Unfortunately, there are several toxic effects that are associated with chemotherapy, and sometimes it is not well tolerated by the patients who undergo it. The most usual side effects of cyclophosphamide that are well documented are bone marrow suppression and subsequently susceptibility to infections, hemorrhage cystitis, cardiotoxicity, and gastrointestinal disturbances. Vincristine on the other hand promotes the production of severe neurotoxicity in patients and less commonly myelosuppression, alopecia, and SIADH. Other regimens consist of VAC plus VAI (vincristine, actinomycin D, and ifosfamide or VIE (vincristine, ifosfamide, and etoposide) plus VAC for 12 months. A randomized controlled trial by Amdt et al. compared the VAC regimen and the combination of vincristine, topotecan, and cyclophosphamide for the treatment of moderated-risk rhabdomyosarcoma. The results suggest that topotecan was not indicated to be more efficient than actinomycin D, with 68% and 73% 4-year survival rates, respectively. Irinotecan is another drug that is currently under examination for its efficacy in the treatment of pediatric rhabdomyosarcoma when combined with the VAC regimen . Surgery and/or radiation still play an important role in the management of high-risk RMS with oligometastatic disease to minimize treatment failures. Aggressive surgical local control most of the time offers the advantage of sparing these young patients radiation-associated complications. However, it should be kept in mind that surgical resection is not without its own possible complications, including wound infections, fistulas, and stenosis . In case of widespread metastases at presentation, local control is often postponed until later in treatment and may be customized to focus on the most symptomatic or critical sites. In almost all of these advanced cases, palliative treatment remains the only option. Although the outcome is not always favorable for the patients, the prognosis of botryoid sarcomas has dramatically improved in recent years through the combination of chemotherapy, radiotherapy, and/or surgery. Similar to the case for most other cancers, the prognosis depends on the tumor size, the histological variant, and the depth to which the disease has spread to adjacent structures at the time of diagnosis. It appears that there is a more favorable prognosis for tumors arising from the cervix compared with the ones arising from other parts of the female genital tract. Generally, the 5-year survival rate for sarcoma botryoides is 83%, 70%, 52%, and 25% for clinical stages I-IV, respectively. Unfortunately, despite the advances in therapeutic modalities, there are several reports of tumor recurrences, with the pelvis being the most common region for primary recurrence. Surprisingly, the 5-year overall survival was equally excellent, reaching 87% in nonmetastatic tumors . Consistent with these results was the publication of Brand et al. , in which the patients' survival rate was 80% at 68 months with the use of multimodality therapy (conservative surgery combined with chemotherapy). The identification of nodal metastases through imaging is critically important in the treatment of RMS, and tissue sampling must be performed for all patients with clinically or radiographically suspicious lymphadenopathy. In conclusion, we believe that a combination of debulking surgery, chemotherapy, and in cases of treatment-resistant tumor or remaining disease, radiation therapy demonstrates an appropriate approach in well-selected patients with botryoid sarcoma. This approach provides excellent oncologic outcomes and a low complication rate, taking into account the tumor's location, stage, and the patient's overall characteristics. Nevertheless, since most of the data come from case reports, larger studies with longer follow-up must be conducted in order to determine the most effective treatment guidelines. 4.4. Limitations and Advantages The present summative review is, to the best of our knowledge, the first one trying to summarize the main literature outcomes about therapeutic management and prognosis. The main limitation of the present manuscript is the fact that it is a narrative review only summarizing results of relatively low-level evidence, such as retrospective series and case reports, as no prospective RCTs or large prospective cohorts were identified through the literature search. However, despite the fact that the level of evidence is low, this is relatively reasonable because the rarity of the disease poses reasonable difficulties in the conduct of level-I evidence studies. Furthermore, as our review finally summarized the main conclusions about the therapeutic modalities and prognostic outcomes, this might be the initial step to organize prospective observational cohorts, rather than multicenter ones, in an attempt to globalize the standards of practice and, thereafter, improve the outcomes of such a demanding clinical entity. Author Contributions C.M.-S. was a major contributor in writing the manuscript. C.M.-S., S.P., A.A. and G.M.-S. were responsible for the collection of the relevant literature. A.S.L., M.K., A.P. and K.D. revised the manuscript critically for important intellectual content. 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 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. diagnostics-13-00924-t001_Table 1 Table 1 Characteristics and treatment of female patients with botryoid sarcoma . Paper Age (Months/Years) Entry Year Site Symptom Size Stage CG/TNM Metastases Treatment STATUS after Treatment Relapse Treatment of Relapse Follow Up Immunohistochemistry Panczak K et al., 2017 4 months 2017 Vagina Vaginal bleeding and a mass protruding from the vagina, clitoromegaly 2.5 cm x 2.3 cm x 4.3 cm Chemotherapy (VAI x7) + vaginoscopic resection R0 + VAI x2 + (adriamycin, cyclophosphamide, carboplatin, topotecan, trofosfamide, idarubicin, vincristine, and etoposide) x 3 Recurrence of vaginal RMS, qualified for radical surgery (vaginal resection) Yes, after 14 months Radical surgery (vaginal resection) Desmin, myogenin (myogenic factor 4), myogenic differentiation 1, Wilms' tumor gene expression, and protein in about 90% of cells van Sambeeck S J et al., 2014 17 months 2014 Vagina Abnormal vaginal bleeding and vaginal tissue loss with a "grape bunch" appearance 6.9 x 3.7 x 4.1 cm No distant metastases Chemotherapy VAI x9, radical surgery or radiotherapy was omitted Yes, 6 months Chemotherapy and brachytherapy Complete remission for almost 1 year Focal positivity for desmin and myogenin Rodrigo L. P. Romao et al., 2017 30 months 2017 Vagina Stage I/group III VAC + subtotal vaginectomy (24 weeks) with vaginal reconstruction with buccal mucosa grafts 34 months Fusion negative ALSaleh N et al., 2017 18 months 2017 Uterus, cervix, and vagina Vaginal bleeding (8 mo) and a mass protruding through the introitus (12 mo) + difficult 10 x 6 cm Without abdominal or lymphadenopathy Chemo VAC x10; after remission: total abdominal hysterectomy, bilateral salpingectomy with upper vaginectomy, ureterolysis, and bilateral ovarian transposition (oopexy) + VAC x5 No 12 months disease free on remission with no complaints Imawan D K Et al., 2019 36 months 2019 Cervix Protruding mass in vagina, with a tendency to bleed 10 cm x 10 cm Tumor excision Yes, after 3 months Wide excision with a 2 cm margin of healthy tissue without intraoperative biopsy + VAC x6 18 months post chemotherapy - still in remission, alive and well 44 months after (+) and antibody May T et al., 2018 24 months 2018 Cervix Mass protruding through the vaginal introitus 10 x 4.0 x 4.5 cm Stage I, group III rhabdomyosarcoma Vaginal portion of the mass was resected + chemo (alternating vincristine, dactinomycin, and cyclophosphamide/vincristine and irinotecan) x 2 + radical trachelectomy + chemo x 12 No 12 months disease free on remission with no complaints Neha B et al., 2015 14 years old 2007 Cervix Mass protruding from the introitus and white discharge that was occasionally blood-stained Radical hysterectomy + VAC x6 8 months after surgery, acquired a varicella zoster virus, died due to septic shock and multiple organ failure Yasmin F et al., 2015 7 months Cervix Protruding mass in the vaginal area for 7 days 9.5 x 7.4 x 10 cm3 Surgery (subtotal hysterectomy) and chemotherapy (5 cycles, no explanation about the regimen) Yes (2 months after chemotherapy) Total hysterectomy and chemotherapy x 5 (no further explanation, advised for x 14) Bouchard-Fortier G et al., 2016 14 years old 2016 Cervix Mass protruding through the vagina accompanied by uterine bleeding 5.3 x 2.9 x 6.7 cm Robotic-assisted radical trachelectomy + 35 of 43 weeks of VAC alternating with vincristine and irinotecan No evidence of disease 10 months following diagnosis ERMS with diffuse anaplastic features and (cartilage) differentiation Bouchard-Fortier G et al., 2016 20 years old 2016 Cervix Heavy vaginal and a mass protruding through the vaginal introitus 5.9 x 3.9 x 2.9 cm Hysteroscopy + cervical conization (after the mass had detached) + 4 cycles of VAC followed by 4 cycles of VA No evidence of disease 25 months from diagnosis Bouchard-Fortier G et al., 2016 21 years old 2016 Cervix One-year history of abnormal uterine bleeding 3.3 x 1.7 x 2.8 cm 6 cycles of VAC + LEEP + robotic-assisted radical trachelectomy and placement of an abdominal cerclage No evidence of disease 21 months after diagnosis Bell S G et al., 2021 17 years old 2021 Cervix One-year history of an enlarging mass protruding from the introitus associated with vaginal bleeding Underwent polypectomy of the mass using electrocautery, and margins were negative. + 6x cycles of vincristine, actinomycin-D, and cyclophosphamide Melo A et al., 2012 20 years old 2012 Cervix Postcoital vaginal bleeding over 1 year No distant metastases radical surgery, excision of the upper third of the vagina + adjuvant chemotherapy, consisting of 4 cycles of IVA pattern+ Mesna and further 5 cycles of vincristine and actinomycin. No At 3 years after diagnosis, patient remains in complete remission and without clinical signs of ovarian failure Cell positiveness for actin, vimentin, Myo D1 and desmin Michlitsch J G et al., 2017 11 months 2017 Vagina Tumor fragments were passed per vagina Stage 1, group IIa No distant metastases Partial vaginectomy, converted to a total vaginectomy + VAC therapy 38 months of follow up, patient remains disease free with no evidence of local or distant recurrence Michlitsch J G et al., 2017 30 months 2017 Vagina Exophytic vaginal mass Stage 2, group III tumor No distant metastases VAC therapy + surgical resection and reconstruction (at 24 weeks) Disease-free at 41 months following diagnosis, with no evidence of recurrence Michlitsch J G et al., 2017 24 months 2017 Vagina Vaginal bleeding No distant metastases VAC therapy + total vaginectomy with reconstruction (at week 20) Disease-free at 43 months with no evidence of recurrence Michlitsch J G et al., 2017 25 months 2017 Vagina Protruding vaginal mass No distant metastases VAC therapy + anterior vaginal resection of roughly 180-degree circumference and vaginal reconstruction Disease-free at 16 months with no evidence of recurrence VAC--vincristine, actinomycin D, cyclophosphamide; VAI--vincristine, actinomycin D, ifosfamide; LEEP--loop electrosurgical excision procedure. diagnostics-13-00924-t002_Table 2 Table 2 Intergroup Rhabdomyosarcoma Study Group Clinical Classification System for Rhabdomyosarcoma. Clinical Group Extent of Disease, Resectability, and Margin Status I A: localized tumor, confined to site of origin, completely resected. B: localized tumor, infiltrating beyond site of origin, completely resected. II A: localized tumor, gross total resection, but with microscopic residual disease. B: locally extensive tumor (spread to regional lymph nodes), completely resected. III A: localized or locally extensive tumor, gross residual disease after biopsy only. B: localized or locally extensive tumor, gross residual disease after major resection (>=50% debulking). IV Any size primary tumor, with or without regional lymph node involvement, with distant metastases, irrespective of surgical approach to primary tumor. diagnostics-13-00924-t003_Table 3 Table 3 TNM Staging System for Rhabdomyosarcoma. Stage Sites T Tumor Size Designation N M I Orbit Head and neck * Genitourinary + Biliary tract T1 or T2 a or b Any N M0 II Bladder or prostate Extremity Cranial parameningeal Other ++ T1 or T2 a N0 or Nx M0 III Bladder or prostate Extremity Cranial parameningeal Other ++ T1 or T2 a N1 M0 IV All T1 or T2 a or b N0 or N1 M1 T1, tumor confined to the anatomic site; T2, tumor extension; a, <=5 cm in diameter; b, >5 cm in diameter; N0, nodes not clinically involved; N1, nodes clinically involved; Nx, clinical status of nodes unknown; M0, no distant metastases; M1, distant metastases present. * Excluding parameningeal sites. + Nonbladder and nonprostate. ++ Includes trunk, retroperitoneum, etc., excluding biliary tract. 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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PMC10000399 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050946 diagnostics-13-00946 Interesting Images Interpreting Discordant Monosomy 3 FISH and Chromosomal Microarray Analysis Results in Uveal Melanoma Long Christopher P. 1* Coley Nicholas 2 Thorson John 3 Lin Jonathan H. 456 Ferguson Cole Academic Editor 1 Department of Ophthalmology, Roski Eye Institute, University of Southern California, 1450 San Pablo St #4400, Los Angeles, CA 90033, USA 2 Diagnostic Pathology Medical Group, 3301 C St, Suite 200E, Sacramento, CA 95816, USA 3 Department of Pathology, University of California, 9444 Medical Center Drive 1-200, La Jolla, CA 92037, USA 4 Department of Pathology, Stanford University, 300 Pasteur Dr., Palo Alto, CA 94304, USA 5 Department of Ophthalmology, Stanford University, 2452 Watson Ct, Palo Alto, CA 94303, USA 6 VA Palo Alto Healthcare System, 3801 Miranda Avenue, Palo Alto, CA 94304, USA * Correspondence: [email protected]; Tel.: +1-323-442-6335 02 3 2023 3 2023 13 5 94624 11 2022 21 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 ). Uveal melanoma is the most common primary ocular tumor in adults and causes morbidity through lymphovascular metastasis. The presence of monosomy 3 in uveal melanomas is one of the most important prognostic indicators for metastasis. Two major molecular pathology testing modalities used to assess monosomy 3 are fluorescence in situ hybridization (FISH) and chromosomal microarray analysis (CMA). Here, we report two cases of discordant monosomy 3 test results in uveal melanoma enucleation specimens, performed using these molecular pathology tests. The first case is of uveal melanoma from a 51-year-old male that showed no evidence of monosomy 3 when assessed by CMA, but where it was subsequently detected by FISH. The second case is of uveal melanoma from a 49-year-old male that showed monosomy 3 at the limit of detection when assessed by CMA, but where it was not detected by subsequent FISH analysis. These two cases underscore the potential benefits of each testing modality for monosomy 3. Mainly, while CMA may be more sensitive to low levels of monosomy 3, FISH may be best method for small tumors with high levels of adjacent normal ocular tissue. Our cases suggest that both testing methods should be pursued for uveal melanoma, with a single positive result for either test interpreted as indicating the presence of monosomy 3. uveal melanoma monosomy 3 microarray FISH Stanford Vision Research CoreNIH P30EY026877 This research was funded by Stanford Vision Research Core (NIH P30EY026877). pmc1. Materials and Methods An oncoscan microarray was performed at the University of California San Diego (UCSD) Center for Advanced Laboratory Medicine (CALM), using the Affymetrix/Thermofisher OncoScan platform (catalog number: 902695), on DNA extracted from sections of formalin-fixed, paraffin-embedded (FFPE) tissue. Monosomy 3 FISH was performed at Mayo Clinic Laboratories (test ID: UMM3F), utilizing the D3Z1 centromeric probe (Abbot Molecular) and the BCL6 long-arm probe (Mayo Laboratories). Greater than 28% of 200 cells lacking two chromosome 3 signatures is requisite for a positive monosomy 3 result when using this assay. Next-generation sequencing (NGS) was performed at the UCSD CALM on DNA extracted from FFPE tissue using a laboratory-developed 397 gene hybrid capture-based assay, with analysis conducted on an Illumina HiSeq 2500 instrument (Illumina, San Diego, CA, USA). The images of FFPE, eosin (H&E)-stained whole-eye cross sections were taken using the Aperio AT2 whole-slide scanner. The remaining images were captured using the Olympus SC30 camera with cellSens software, attached to an Olympus BX43 microscope. The UCSD institutional review board approved the use of the collected tissue samples and associated clinical information for this study. The research was Health Insurance Portability and Accountability Act (HIPAA)-compliant and adhered to the principles of the Declaration of Helsinki. 2. Figure and Table Legends Patient #1 is a 51-year-old male who was referred to ophthalmology for progressive left-sided vision loss. Ophthalmoscopic examination revealed a mushroom-shaped pigmented lesion, emanating from the posterior uvea overlying the optic nerve, which was proven to be melanoma by the performance of a fine-needle aspiration (FNA) biopsy. He underwent a 7-day surgical placement of radioiodine plaque overlying the tumor 1 month after initial pathologic diagnosis. A clinically detected local recurrence at the periphery of the plaque site, detected 60 months after pathologic diagnosis, underwent multiple rounds of laser ablation. The patient ultimately underwent enucleation 79 months after pathologic diagnosis. His most recent imaging, taken 92 months after initial pathologic diagnosis, demonstrates numerous liver metastases and local left orbital tumor extensions, tracking along the optic nerve to involve the optic chiasm. As seen in Figure 1, the melanoma from patient #1 arises from the posterior uvea overlying the optic nerve. A focus on scleral invasion adjacent to the optic nerve is present, but no extrascleral extension is noted (A). The tumor assumes a primarily epithelioid morphology (B), with the expression of HMB45 in malignant melanocytes (insert). Patient #2 is a 49-year-old male who visited ophthalmology for an enlarging pigmented mass present on his right iris. He underwent surgical radioiodine plaque placement (removed after 7 days) at the time of an FNA biopsy that demonstrated uveal melanoma. He underwent a 7-month trial of sunitinib shortly after initial pathologic diagnosis. Fifteen months after pathologic diagnosis, magnetic resonance imaging (MRI) of the abdomen demonstrated two biopsy-proven metastatic liver lesions. These were subsequently treated with radioablation. He underwent enucleation 36 months after pathologic diagnosis and a right apical lung lesion, biopsied at 38 months, demonstrated metastatic melanoma. An enlarging right apical lung lesion was the only metastatic disease detected by computed tomography (CT) of the chest in the patient's most recent imaging scan, performed 48 months after pathologic diagnosis. As demonstrated in Figure 2, the melanoma from patient #2 (A) arises from the ciliary body (Insert). The tumor assumes a primarily spindle-cell morphology (B), characterized by extensive necrosis, and the presence of melanophages, secondary to radioiodine plaque treatment (Insert). Figure 3 demonstrates the raw CMA microarray relative fluorescence data for the uveal melanoma from patient #1 (A) and patient #2 (B). For each patient, chromosome position/array probe location is located on the x axis of each panel. Relative copy number is denoted on the y axis of the top panel of data for both patients (A and B), while B-allele frequency is depicted in the lower panel of data for each patient. The uveal melanoma from patient #1 shows segmental gain of chromosome 9q, as evidenced by (1) the slight spike in the relative copy number plot (circled) and (2) the same region of the B-allele frequency plot showing an allele frequency of approximately 0.4 or 0.6 (also circled). Whereas the normal genotypes of AA, AB, or BB produce the expected B-allele frequencies of 0, 0.5, or 1.0, segmental gains result in an AAB genotype (i.e., gain of a A allele copy), leading to a b-allele frequency of >0 but <0.5 or an ABB genotype (i.e., gain of a B allele copy), producing a B-allele frequency of >0.5 but <1.0. The uveal melanoma from patient #2 shows low frequency loss of chromosome 3, 4, 12, and 16q with gains of 7, 8, 18, 19, and 22. These changes can best be appreciated by inspection of the copy number plot for patient #2 where slight shifts of the average copy number above or below the 0 line indicate a loss (movement below the 0 line) or a gain (movement above the 0 line) of chromosomal material. As summarized in Table 1, no clinically significant sequence variants were detected by NGS for either tumor. The uveal melanoma from patient #1 showed focal gain of chromosome 9 and no detectable chromosomal losses. However, this tumor demonstrated monosomy 3 when examined by FISH analysis. The uveal melanoma from patient #2 showed several chromosomal gains in addition to monosomy 3 at the limit of detection. FISH analysis did not detect monosomy 3 for this tumor. These two cases highlight the diagnostic strengths and pitfalls of CMA and FISH for assessing monosomy 3 status in uveal melanoma . CMA utilizes DNA extracted from an entire tumor sample and inevitably includes some background or interspersed normal tissues . Consequently, CMA may fail to detect monosomy 3 in a small subclone or the DNA from normal tissue may obfuscate low-level loss of chromosome 3 within a tumor . The detection of monosomy 3 by FISH, while it was not detected by CMA in patient #1, may reflect this phenomenon. FISH, however, samples a narrow plane of tissue and requires a relatively high proportion of cells with a single probe signal to minimize false positive results . Thus, FISH may miss monosomy 3 at a low level that CMA can routinely detect . The detection of monosomy 3 by CMA, a substance not detected by FISH in patient #2, may reflect this phenomenon. Overall, these two cases highlight the strengths and weaknesses of FISH and CMA as assays to detect monosomy 3 in uveal melanoma. We suggest that both FISH and CMA should be performed for uveal melanoma, with a positive result for either test interpreted as indicating the presence of monosomy 3. Acknowledgments We thank the staff at the UC San Diego Center for Advanced Laboratory Medicine (CALM) for performing all microarray testing. We thank Mayo Laboratories in Rochester MN for performing all FISH testing. Author Contributions C.P.L. and N.C. authored the majority of the manuscript. N.C. interpreted the initial molecular tests and took all images. C.P.L. wrote the majority of the background sections with additional contributions by SS. J.H.L. and J.T. reviewed the finished manuscript and served as final editors/mentors. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Tissue derived from both patients in this retrospective study was consented for potential research use under the UC San Diego Health System consent for treatment forms. Informed Consent Statement No personal identification from either patient is presented in this manuscript per HIPAA regulations. Data Availability Statement FFPE tissue from either case can be obtained for additional studies following approval of a material transfer agreement. Microarray data from each case can be provided de-identified of HIPAA sensitive information upon request as well as the original FISH reports from Mayo laboratories. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Melanoma from patient #1 without extrascleral extension (A). The tumor assumes a primarily epithelioid morphology (B), with the expression of HMB45 in malignant melanocytes (insert). Figure 2 Melanoma from patient #2 (A) originating from ciliary body (insert). Tumor sample with spindle-cell morphology (B), necrosis, melanophages, secondary to previous treatment (insert). Figure 3 Raw CGH microarray relative fluorescence data for the uveal melanoma from patient #1 (A) and patient #2 (B). diagnostics-13-00946-t001_Table 1 Table 1 Clinical Summary of CMA and FISH results of patient #1 and patient #2. Patient #1 Patient #2 Mutations No clinically significant variance detected. No clinically significant variance detected. Chromosomal Gains 2.27 Mb gain in 9q33.1 encompassing 6 genes (ASTN2, SNORA70C, LOC101928797, TLR4, LINC02578, BRINP1). Gain of chromosomes 7, 8, 18, 19, and 22. Chromosomal Losses No chromosomal losses detected. Monosomy 3 at limit of detection with additional losses of chromosomes 4, 12, and 16q. Monosomy 3 FISH Status Positive, 63.5% of 200 cells counted (28% cutoff). Negative. 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. Aronow M.E. Topham A.K. Singh A.D. Uveal Melanoma: 5-Year Update on Incidence, Treatment, and Survival (SEER 1973-2013) Ocul. Oncol. Pathol. 2018 4 145 151 10.1159/000480640 29765944 2. Damato B. Duke C. Coupland S.E. Hiscott P. Smith P.A. Campbell I. Douglas A. Howard P. Cytogenetics of uveal melanoma: A 7-year clinical experience Ophthalmology 2007 114 1925 1931 10.1016/j.ophtha.2007.06.012 17719643 3. Prescher G. Bornfeld N. Becher R. Nonrandom Chromosomal Abnormalities in Primary Uveal Melanoma JNCI J. Natl. 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PMC10000400 | Breast cancer (BC) is the world's second most frequent malignancy and the leading cause of mortality among women. All in situ or invasive breast cancer derives from terminal tubulobular units; when the tumor is present only in the ducts or lobules in situ, it is called ductal carcinoma in situ (DCIS)/lobular carcinoma in situ (LCIS). The biggest risk factors are age, mutations in breast cancer genes 1 or 2 (BRCA1 or BRCA2), and dense breast tissue. Current treatments are associated with various side effects, recurrence, and poor quality of life. The critical role of the immune system in breast cancer progression/regression should always be considered. Several immunotherapy techniques for BC have been studied, including tumor-targeted antibodies (bispecific antibodies), adoptive T cell therapy, vaccinations, and immune checkpoint inhibition with anti-PD-1 antibodies. In the last decade, significant breakthroughs have been made in breast cancer immunotherapy. This advancement was principally prompted by cancer cells' escape of immune regulation and the tumor's subsequent resistance to traditional therapy. Photodynamic therapy (PDT) has shown potential as a cancer treatment. It is less intrusive, more focused, and less damaging to normal cells and tissues. It entails the employment of a photosensitizer (PS) and a specific wavelength of light to create reactive oxygen species. Recently, an increasing number of studies have shown that PDT combined with immunotherapy improves the effect of tumor drugs and reduces tumor immune escape, improving the prognosis of breast cancer patients. Therefore, we objectively evaluate strategies for their limitations and benefits, which are critical to improving outcomes for breast cancer patients. In conclusion, we offer many avenues for further study on tailored immunotherapy, such as oxygen-enhanced PDT and nanoparticles. breast cancer T cell macrophage photodynamic therapy ROS National Natural Science Foundation of China81700567 National Natural Science Foundation of Hubei2022CFB122 Natural Science Independent Research Project of Wuhan University2042021kf0135 This study was supported by grants from the National Natural Science Foundation of China (81700567), National Natural Science Foundation of Hubei (2022CFB122), and Natural Science Independent Research Project of Wuhan University (2042021kf0135). pmc1. Introduction Breast cancer (BC), the second most common malignancy, accounts for 16.1% of all new cancer cases in women . Survival rates for BC vary widely around the world. In developed countries, the estimated 5-year survival rate is 80%; in developing countries, it is less than 40%. According to the WHO classification 2019, breast cancer is classified into four types based on molecular and histologic findings: luminal A-like, luminal B-like, HER2-positive, and basal-like (triple negative) . Although advances in early detection and therapy have led to a 38% decrease in BC mortality, cancer metastasis and resistance to therapy are significant barriers to the successful treatment of BC. Immunotherapy, which stimulates the host immune system to induce anticancer immune responses, has opened a new chapter in the treatment of malignant tumors in recent years . In BC, increasing scientific evidence supports that cancers cause local immune dysregulation by suppressing the innate immune system, tumor-induced inflammation, and suppressing the adaptive T and B cell immune response in situ . Despite the positive outlook, immunotherapy helps only some cancer patients, and the lack of tumor specificity results in particular immunotoxicity in a significant number of treated individuals. An increasing number of researchers are investigating new nanomedicines for PDT-assisted BC immunotherapy. Photodynamic therapy (PDT) is a cutting-edge, noninvasive therapy with intriguing therapeutic applications in cancer treatment. It consists of three major parts: PS, visible light with a particular wavelength, and molecular oxygen . PS molecules absorb appropriate wavelength light and begin activation mechanisms that result in the selective death of inappropriate cells. PS act as catalysts when they absorb visible light and then convert molecular oxygen into a series of highly reactive oxygen species (ROS). The ROS produced by PDT are well-established to destroy tumors via multifactorial mechanisms. PDT has an immediate effect on cancer cells, producing necrosis and/or apoptosis. PDT also affects the tumor vasculature, with illumination and ROS generation leading to vascular blockage, depriving the tumor of oxygen and nutrition. PDT reportedly not only kills tumor cells directly but can also induce immunogenic cell death (ICD), which causes antitumor immunity . As the disruption of tumor immune homeostasis progresses, tumor cells exhibit sequential changes. Cancer immunotherapy has achieved significant clinical advances in advanced cancers. However, due to a highly immunosuppressive tumor microenvironment (TME) and limited tumor immunogenicity, response rates to immunotherapy in patients with different cancers are poor. Smart nanomedicine-based techniques have recently been developed that can slightly adjust the pharmacokinetics and TME of therapeutic drugs to optimize PDT and immunotherapy for better anticancer activity. In this paper, we provide new nanomedicines for PDT-assisted cancer immunotherapy, such as hypoxia-reversing nanomedicines, nanometallic organic scaffolds, and subcellular targeted nanoparticles (NPs). In addition, we describe synergistic nanotherapeutics that boost immune responses when combined with tumor-targeted immunotherapies. Finally, the challenges and future prospects in the field of PDT-assisted cancer immunotherapy are also discussed. 2. Breast Cancer Biology The breast has 15-25 milk ducts that begin at the nipple, branch into smaller ducts, and finally reach the lobular unit of the terminal duct (lobule), which consists of a terminal duct and several smaller ducts (or tubules). The inner cuboidal to columnar epithelial cells and the outer myoepithelial cells delineate the ducts and tubules. The connective tissue within the lobules consists of fibroblasts on a background of collagen and acid mucin, joined by histiocytes and lymphocytes. The interlobular stroma consists of fibrous adipose tissue and is hypocellular . Each of these segments consists of tiny sacs called lobules (glands). In lactating mothers, these lobules produce milk. The lobules and auricles are connected to the nipple by the milk ducts, which carry milk to the nipple. The nipple is located in the center of the areola, the dark area of skin surrounding the nipple. The lymph nodes in the breast and armpit are part of the lymphatic system, a network of nodes and ducts that drain fluid (lymph) and carry white blood cells (immune cells involved in fighting infection). The rest of the breast consists of fat and connective tissue (or fibers) . Breast cancer is usually caused by a variety of factors, most of which are genetic changes that can be inherited or lifestyle or environmental factors causing mutations in a particular gene or group of genes. Some studies have reported that breast cancer gene mutations (BRCA1 and 2) can be detected in approximately 5-10% of cases, with 25% of cases occurring in women under the age of 30 . Reproductive variables, such as menopause before age 12, delayed childbearing, and childbearing after age 30, also exist . The use of exogenous hormones in the form of birth control pills or hormone replacement products, menopause, and exposure to radiation to the chest are also known susceptibility factors for breast cancer . 2.1. Stages and Grade of Breast Cancer Patients with newly diagnosed breast cancer often present with a lump or induration in the breast or armpit, a change in the size or shape of the breast, fluid from the nipple or an inwardly directed nipple, redness or scaling of the skin or nipple, and grooves or dimpling in the breast (an orange peel-like appearance). However, in the early stages of breast cancer, no signs may be evident. Diagnostic mammography, ultrasound, and a tissue sample (called a biopsy) examined under a microscope can provide additional clinical staging. At diagnosis, the five stages of breast cancer are based on tumor size, tumor location, lymph node status, and metastasis . Stage 0 is noninvasive breast cancer, including ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS). Stage I is early-stage breast cancer where the tumor is smaller than 2 cm and has not spread to lymph nodes or other parts of the body. Stage II is early-stage breast cancer where the tumor is either smaller than 2 cm and has spread to one to three lymph nodes under the arm, is between 2 and 5 cm (with or without spread to the lymph nodes under the arm), or is larger than 5 cm and has not spread outside the breast. Stage III is locally advanced breast cancer where the tumor is larger than 5 cm and has spread to the lymph nodes under the arm; alternatively, the cancer is found in more than three underarm lymph nodes or has spread to lymph nodes near the breastbone or to other tissues near the breast. Stage IV is metastatic breast cancer. Moreover, the stage of breast cancer is divided into three groups: stage I and II are early invasion; stage III is locally advanced; and stage IV is metastatic cancer. Staging provides a common method to classify cancer, allowing physicians to collaborate to arrange the best treatment for a patient . Recent breast cancer profiling studies have highlighted the importance of tumor biology in breast cancer behavior and, thus, the importance of histologic grade. The Nottingham histologic score (also known as histologic grading) is a method for determining the "grade" of breast cancer . Grading is a method for determining the aggressiveness of breast cancer tumors. The Nottingham system consists of three different scores. Under a microscope, the pathologist examines breast cancer cells and assigns a score to three characteristics: 1. tube formation--how much the tumor resembles normal cell structure; 2. nuclear pleomorphism--how much the tumor cells appear to differ from normal cells; 3. mitotic activity--how quickly the cells divide or multiply. Grade I, also known as highly differentiated disease, is assigned a score of 3 to 5. Fairly differentiated grade II is assigned a total score of 6 to 7, whereas poorly differentiated disease grade III is assigned a score of 8 to 9. Grade I tumors are less aggressive. They are also more likely to have an estrogen receptor (ER+). Grade III tumors are more aggressive and more often "triple negative", meaning they are negative for both the hormone receptor (ER and PR) and the HER2 receptor. The Nottingham score and histologic grade are used to determine whether radiation is required after surgery (lumpectomy or mastectomy) . A high-grade tumor (III) is believed to have a higher risk of recurrence, and radiation treatment is thought to reduce this risk. Grade allows the radiation oncologist to determine whether the patient would benefit from additional radiation (an extra dose to a specific area at the end of radiation), whether she is eligible for accelerated partial breast irradiation (APBI), and whether the lymph nodes should be irradiated. Grade is less commonly used to determine the need for pharmacologic therapies, such as chemotherapy and hormone therapy. The only exception is for young female patients with triple-negative malignancy in whom the lymph nodes are unaffected. In these patients, high-grade tumors indicate that they should consider chemotherapy as part of their treatment. 2.2. Breast Cancer Therapies The primary cancer treatments accessible to patients include surgery, chemotherapy, hormonotherapy, and radiation therapy. Breast cancer treatment choices are determined by stage (TNM), grade, hormonal status, and Ki67 status. The treatment of nonmetastatic breast cancer is primarily aimed at removing the tumor from the breast, removing regional lymph nodes, and preventing the recurrence of metastases. Local treatment of nonmetastatic breast cancer consists of surgically removing the tumor and removing or excising the axillary lymph nodes; postoperative radiation therapy may be considered. Systemic treatment may be given before surgery (neoadjuvant), after surgery (adjuvant), or both. The breast cancer subtype determines standard systemic therapy, which includes hormonotherapy for the majority of hormone-receptor-positive (HR+) breast cancer (with some patients also requiring chemotherapy), trastuzumab-based ERBB2 antibody therapy plus chemotherapy for all ERBB2+ breast cancer (with additional endocrine therapy if concurrent HR-positive), and chemotherapy alone for triple-negative breast cancer . The treatment aims for metastatic breast cancer include life extension and symptom relief. Almost all individuals with metastatic breast cancer are currently incurable. In metastatic breast cancer, the same broad categories of systemic treatment are employed as in neoadjuvant/adjuvant therapies. Only in the case of metastatic illness are local therapeutic techniques (surgery and radiation) employed for palliation. Depending on the size of the tumor and whether it has metastasized to other organs, surgery is the preferred treatment option . Surgical intervention remains the primary means of treatment for local and regional breast cancer. Surgery includes mastectomy, lumpectomy, lymph node removal, and reconstruction. Conservative surgery is contraindicated in the following cases: (1) presence of diffuse suspicious microcalcifications on breast imaging; (2) positive pathologic margins after lumpectomy; (3) disease that cannot be treated by excision of a single breast tissue region with satisfactory cosmetic results, except in a small number of patients; (4) certain collagenous vascular diseases such as scleroderma; and (5) prior radiation therapy to the affected breast . The surgical procedure is undoubtedly invasive and often has negative consequences for the patient, such as inflammation, induration, tenderness, disfigured appearance of the breast, asexuality, depression, and loss of self-image . Women who have undergone mastectomy may wish to undergo breast reconstruction, either immediately or later, to improve breast appearance after tumor surgery. The option of reconstructive surgery must be offered to all women who undergo mastectomy . Mastectomy is a reasonably easy surgery that normally requires 1-2 days in the hospital. External prostheses used to treat these issues can be painful and scratchy, particularly for women with large breasts. The most serious issue after mastectomy, however, is the mental impact of physical and cosmetic damage, which can include stress, depression, and negative impacts on stature and sexual activity . Breast reconstruction is frequently necessary in women with breast cancer who are unable to undergo breast-conserving treatment and have a hereditary predisposition to breast cancer. Several breast reconstruction treatments involve prosthetic implants, autologous tissue flaps, or both . For breast cancer, radiation treatment may involve the entire breast or part of the breast (after lumpectomy), the chest wall (after mastectomy), and the regional lymph nodes. Whole-breast radiation after lumpectomy is a routine part of breast-conserving treatment. The past decade has seen considerable advances in the delivery of postoperative radiation that aim to optimize the treatment for each person's anatomy and reduce acute or long-term toxicity. A meta-analysis of 10,801 patients found that radiation after lumpectomy was associated with a reduction in breast cancer recurrence (locoregional or distant) by approximately half (from 35.0% to 19.3%) and a reduction in breast cancer deaths by one-sixth (from 25.2% to 21.4%) at 10 and 15 years, respectively . Moujhuri Nandi et al. reported that no local recurrence occurred, and only four patients developed metastases after hypofractionated radiotherapy; they selected 135 women, most of whom had undergone mastectomy . Moreover, breast conservation surgery plus radiation treatment is also associated with very high local control rates (90-95%) in the preserved breast within 10 years of treatment; these rates are comparable to those obtained with mastectomy, with most women having a good or excellent cosmetic result. The process of killing cancer cells with the help of certain drugs is called chemotherapy . Depending on the patient's condition, it can be used both before and after surgery. Chemotherapy medications include docetaxel, paclitaxel, platinum drugs (cisplatin, carboplatin), vinorelbine (Navelbine), capecitabine (Xeloda), liposomal doxorubicin (Doxil), cyclophosphamide (Cytoxan), carboplatin (Paraplatin), and others, according to the American Cancer Society . However, these drugs have various side effects . Metastatic or secondary breast cancer is difficult to treat but can sometimes be managed for years . Chemotherapy may be prescribed to treat metastatic breast cancer to minimize or slow the progression of the disease. It may also be performed to make patients eligible for surgery. Other treatment options may be started before or at the same time as chemotherapy. Immunotherapy improves survival in other solid tumors and is a possible treatment option for breast cancer . Immune checkpoint inhibitors (ICIs), which target immunosuppressive receptors such as CTLA-4 and PD-1 to improve the cytotoxicity and proliferative potential of tumor-infiltrating lymphocytes (TILs), are among the most effective immunotherapeutics . ICIs, such as monoclonal antibodies targeting PD-1 (pembrolizumab, nivolumab), PD-L1 (atezolizumab, durvalumab, avelumab), and CTLA-4 (ipilimumab), have resulted in long-term responses in numerous tumor types (Table 1) . 3. The Immune System in Breast Cancer 3.1. Role of the Immune System in Normal Breast Development In the different stages of mammary gland development, there exist diverse immune cell populations within the mammary gland stroma. Thus, it is suggested that the immune system plays an important role in normal mammary gland growth and maturation. Moreover, Plaks et al. reported that CD11c+-antigen-presenting cells and CD4+ T helper 1 (Th1) cells can interact with each other in mammary gland cells and that this interaction contributes to epithelial remodeling, mammary gland organ formation, and ductal differentiation . Inhibiting CD4+ T cell responses mediated by MHC-II abolished negative regulation and accelerated alveolar branching, indicating that CD4+ immunological responses play a protective function during normal mammary gland development. However, inhibiting MHC-I-mediated CD8+ T cell activation had no effect on mouse mammary gland growth . By secreting cytokines and chemokines, macrophages and eosinophils have been demonstrated to substantially influence mammary duct dilatation during puberty . Breast development continues throughout pregnancy, with regression of alveolar branching, milk secretion, and regression . Macrophage invasion causes extensive apoptosis in milk-producing epithelial cells during postlactational regression, reducing milk output and residual milk content . During mammary gland involution, both innate and adaptive immune responses are considered to be triggered. Gene expression analysis indicated that genes associated with neutrophil and macrophage infiltration and activation were upregulated from the first day of involution and thereafter . After activation by STAT3 and NF during involution, macrophages, eosinophilic granulocytes, plasma cells, and B lymphocytes move into the lumen of the mammary duct and activate proinflammatory signals . Arginase-1, a hallmark of the M2 macrophage phenotype known to be elevated during normal tissue remodeling, has been found to be expressed by macrophages in growing lobules. CD45, a general leukocyte marker, has been demonstrated to be elevated during human mammary gland lobule formation and to rise over the first 12 months of life. IHC labeling revealed an increase in CD4+, CD8+, and CD19+ cells in the growing mammary gland lobule, indicating that T and B cell immune responses are important in mammary gland involution . The coordination of cell death and immunological responses is crucial during breast involution, and aberrant signaling in any of these processes may result in a tumor-friendly environment. 3.2. Role of the Immune System in Breast Cancer Oncodrivers increase malignancy by promoting tumor cell proliferation and survival, making them a potential target for current breast cancer treatment. Currently known oncodrivers in breast cancer are EGFR, HER2, HER3, MET, and mucin-1 (MUC1). The levels of ERBB family receptors (EGFR, HER2, HER3, and HER4) are elevated during puberty, pregnancy, lactation, and normal breast development and play important regulatory roles. The ligand-mediated activation of EGFR is highest during puberty and maturation, stimulating breast epithelial development and ductal cell differentiation. In addition, increased HER2 expression is essential for ductal expansion and acinar cell formation during puberty and maturation. erbb3/HER3 is produced only during pregnancy, whereas ERBB4/HER4 is present during both pregnancy and lactation and is required for the formation and maintenance of goblet vesicles during lactation . MET expression was found to promote ductal branching and luminal cell formation during breast maturation . The activation of the HER2 pathway promotes cell proliferation and survival of HER2+ breast cancer, ultimately leading to treatment resistance, invasiveness, and metastasis . HER3 has been shown to be the most potent HER2/HER3 activator of the downstream PI3K/AKT pathway, and HER3 overexpression has been associated with trastuzumab resistance, suggesting that HER3 plays an oncogenic driver role in breast cancer . In TNBC without targeted therapy, the overexpression of HER3 is a prognostic factor for poor 5-year DFS and 10-year DFS OS . The overexpression of EGFR occurs in all breast cancer subtypes but is more pronounced in invasive TNBC and IBC and is associated with tumor malignancy and poor prognosis . Hepatocyte growth factor receptor/receptor tyrosine kinase MET (HGFR/MET, commonly known as MET) has been shown to be overexpressed in TNBC. MET is an independent risk factor for tumor recurrence, and high expression of MET is usually an important risk factor for lower 5-year survival . In addition, molecular interactions between MET and ERBB receptor family signaling pathways may lead to resistance of breast cancer to EGFR-targeted therapies , implying that MET is promising for the development of oncodriver-targeted therapies. Since TNBC has many tumor drivers, the combination of immunotherapy and oncodriver-targeted therapy could be beneficial, but a viable treatment option is currently lacking. Although the "classical" genetic and epigenetic aspects of tumorigenesis (activation of oncogenes, inactivation of tumor suppressor genes, abnormal cell transformation, aneuploidy, etc.) are closely associated with the development of breast cancer, the immune system likely plays an important role in tumorigenesis. Breast cancer caused by carcinogens is associated with significant impairments in tumor formation, proliferation, and the immune response. The use of dimethylbenzene(a)anthrazine (DMBA) in rats causes thymic atrophy, leading to decreased IL-2 expression and eventually impaired T cell activation . In addition, aberrant cytokine expression can lead to altered cell proliferation and differentiation in malignancies. TGF-b is an anti-inflammatory cytokine released by various immune cell morphologies, and TGF-b signaling is regulated by type I and type II TGF-b receptors. Loss or mutation of TGF-b receptors is associated with increased aggressiveness and poor prognosis in breast cancer . TGF-b is a cytokine released by monocytes and lymphocytes that modulates the expression of MHC-I on the surface of tumor cells, ultimately leading to NK-cell-induced cell lysis. In breast cancer, decreased IL-10 levels are associated with increased immune evasion and cell proliferation by circumventing anticancer activity . The proinflammatory cytokine IL-6 plays an important role in the immune response to invading pathogens. However, in neoplastic diseases, IL-6 may promote tumor growth by supporting the survival of altered cells in a hostile environment . Therefore, higher IL-6 levels may serve as biomarkers to distinguish advanced cancers. In addition, IL-6 has been identified as a regulator of epithelial-mesenchymal transition (EMT) in normal breast cells, resulting in cancer cells with stem-like characteristics. In this capacity, IL-6 can form a pool of highly tumorigenic cells capable of generating multiple cell types in a given tumor . Immune cell infiltration and tumor microenvironment (TME) characteristics may promote oncogenic transformation in addition to protumor effects mediated by cytokine-induced inflammatory responses. In breast cancer patients, increased infiltration of CD4+ helper T lymphocytes, CD8+ cytotoxic T lymphocytes, B lymphocytes, M1 macrophages, and NK cells is associated with improved progression-free survival (PFS) and overall survival (OS) . Immune cell infiltration provides cytokine-specific cytotoxicity in the immune response against tumors. Conversely, regulatory T cell infiltration promotes a tumor-friendly immune response in the tumor microenvironment by inhibiting T cell activation and inactivating effector T cells, which is associated with greater cell transformation and poorer prognosis. M2 macrophages, also known as tumor-associated macrophages (TAMs), are abundant in the tumor microenvironment. The shift in macrophage polarization from M1 (tumor suppressor) to M2 (tumor promoter) has been shown to be a driving force in tumor development and metastasis. TAMs promote premetastatic tumor metastasis by increasing angiogenesis, tumor motility, and overall cell survival. TAMs also regulate IL-10 and TGF-b production, induce immunosuppression, and promote tumor cell proliferation in the tumor microenvironment . Several studies have identified inhibition of macrophage recruitment or polarization of the macrophage phenotype (M2 to M1) as potential therapeutic targets . Little is known about the B lymphocytes that infiltrate tumors. Approximately 70% of nonbreast tumor tissues test positive for infiltrating B lymphocytes. B cells are the most common infiltrating lymphocytes in nonmalignant breast lesions and ductal cell carcinoma in situ (DCIS). This infiltration into noncancerous tissues and the early stages of disease demonstrate that B cell responses play a role in the early stages of oncogenic transformation . Certain breast cancer subtypes appear to be more sensitive to B-cell-infiltrating antitumor responses, which are linked to extended patient life. This link might be due to the surface presentation of antigens recognized by B cells, resulting in an antitumor response . Although instances of B lymphocyte infiltration causing a tumor-promoting phenotype in breast cancer have not been reported, this phenomenon has been observed in other solid tumors. Ou et al. identified more B cell infiltration in neoplastic bladder tissue than in controls, and this B cell population amplified the IL-8/androgen receptor signaling pathway, leading to activation of numerous metastasis-associated matrix metalloproteinases (MMPs) . 3.3. Immunosurveillance and Immunoediting in Breast Cancer Since Paul Ehrlich established the notion of possible immune suppression of carcinoma more than a century ago, the role of the immune system in cancer has been a continually developing area of study . Burnett and Thomas first presented the formal notion of "cancer immune surveillance" : the immune system's function in protecting against neoplastic illness and maintaining tissue homeostasis . The absence of an appropriate animal model hampered experimental support for the theory, finally leading to the rejection of the immunosurveillance concept. Following the discovery of the role of IFN-g in protecting mice against transplanted, chemically induced, or spontaneous fibrosarcoma tumor growth, interest in the concept of immune surveillance has been reignited, and several studies have been conducted in various mouse models with immune dysfunction . Tumor development in four mouse models lacking IFN-g and/or STAT1 function was threefold higher than that in syngeneic wild-type mice, indicating that IFN-g and lymphocytes mediate the tumor suppressor pathway in immune surveillance . Further research in mouse models will be conducted to investigate how the intact immune system influences tumor immunogenicity and growth and to better understand the immune system's role in regulating tumor antigenicity, antigen processing, and components of the IFN-g pathway known as immune-sculpting tumors. In addition to the role of immune landscapes in cancer development and destiny modeling beyond host protection, Schreiber et al. proposed the notion of "cancer immunoediting" . 3.4. Immune Escape Mechanisms in Breast Cancer The strategies by which tumor cells evade recognition and elimination by the immune system can be classified into three categories . These main mechanisms include (1) decreased activation of immune cells and recognition by the immune system such as the loss of tumor antigens, the absence of antigens in the tumor itself, and decreased expression of MHC class I proteins, resulting in decreased antigen presentation by T cells and stimulation of dendritic cells (DCs) with tumor cells. The next mechanism is (2) increased cytotoxic resistance due to the amplification of proto-oncogenic signals (e.g., constitutive activation of STAT3). Proto-oncogenic signals primarily include tumor drivers HER2, EGFR, and the anti-apoptotic effector BCL-2. The last mechanism is (3) tumor cells generating adaptive immune resistance by secreting immunosuppressive cytokines (TGF-, VEGF), thereby inducing activation of Tregs and MDSCs and inhibiting immunosuppressive receptors (CTLA-4, PD-1, and Tim-3). The best-defined mechanisms of immune evasion in breast cancer include the production of suppressive immunostimulatory molecules (PD-L1, CTLA4, and LAG-3), abnormal maturation of DCs, and invasion of immunosuppressive cell populations (MDSCs, Tregs, and TAMs). The presence of immunosuppressive cytokines (e.g., IL-10, TGF-, and IDO) in the TME prevents tumor cell clearance by NK cells . After neoadjuvant chemotherapy for TNBC, there is a strong correlation between Ras-MAPK, PD-L1, and TILs, which can be detected in the remaining tumor cells, with higher Ras/MAPK activation and lower numbers of tumor-invading lymphocytes (TILs) . TILs and tumor immunogenicity have been proposed as markers of therapeutic success in breast cancer. Low tumor immunogenicity in breast cancer, on the other hand, leads to the maintenance of immunosuppression in the TME. 3.5. Challenges of Breast Cancer Immunotherapy Combining immunotherapy with existing conventional therapies for breast cancer, such as chemotherapy, radiation therapy, and targeted therapy, may be a beneficial treatment. Conventional cancer therapy has been proven to trigger tumor cell death, which increases antigen absorption and presentation by DCs and increases TIL recruitment. Thus, the nonoverlapping modes of action of standard medicines can turn "cool" breast cancers into immunogenic "hot" tumors , followed by immunotherapy to activate immunity and inhibit immunosuppression . Despite the efficacy of immunotherapy in a wide range of breast cancers, only a small percentage of patients with otherwise incurable malignancies obtain life-changing long-term survival with these treatments. These findings most likely reflect the immune system's complex and highly controlled structure. A sequence of biological procedures must be completed sequentially before efficient immune elimination of cancer cells is achievable, similar to other difficult and well-designed systems. Furthermore, the system is equipped with a number of protections, negative feedback loops, and checkpoints that allow for precise management as well as the capacity to halt and shut down an immune response. Furthermore, cancer is a complex, adaptable, and diverse disease caused by a number of genetic changes that can affect normal cellular function and activity. However, the genetic changes that are crucial to the oncogenic process might lead cancer cells to seem increasingly alien to the immune system, opening the door to immunotherapy. Breast cancer manifests differently in various people, and tumors may differ within a patient due to changes in the clonality of cancer cells and/or the surrounding microenvironment. Furthermore, BC may be linked to chronic inflammatory disorders, while others may subvert and/or share an immune response as part of the development and metastatic process. The resulting interaction between evolving human immune system units and an emerging cancer can result in a variety of outcomes, including complete immunological eradication of the cancer, a chronic tug-of-war between the two, or uncontrolled cancer growth that has evaded an immune response, which can lead to immunotherapy resistance . Through evolutionary processes, these pathways may be responsible for tumor-acquired drug resistance by selectively lowering the production of tumor-specific antigens . In addition, tumor cells may contribute to escape from immunotherapy by altering enzyme activity and metabolism in the TME . Tumor cells can adapt to hypoxia or vascular circulation by changing their energy metabolism, which is known as tumor metabolic reprogramming or the "Warburg effect" . The lactate generated by tumor cells as a result of metabolic reprogramming acidifies the TME, affecting IFN-g production, NK cell activation, and the number of MDSCs, resulting in a reduced immune response and increased tumor development . Furthermore, tumor-induced acidosis stimulates TAM production and increases CTLA-4 expression on T cells. A similar study found the Warburg effect in TNBC, which leads to immunological escape of the tumor during spread . One of the mechanisms that causes primary resistance to immunotherapy is the expression of a specific group of regulatory genes for various processes, such as mesenchymal transition, angiogenesis, and extracellular matrix remodeling, that are unresponsive to anti-PD-1 treatment, i.e., the innate anti-PD-1 resistance signature (IPRES) . Other mechanisms that may contribute to immunotherapy resistance include alterations in the tumor antigen presentation pathway, which may inhibit tumor antigen presentation and may be caused by epigenetic changes related to the downregulation of antigen transporters and transcriptional inactivation of MHC class I genes . Several strategies must be investigated to overcome immunotherapy resistance. One hypothesis is that by combining BC with medications targeting PD-1 and CTLA-4 antibodies, patient survival in other malignancies, including melanoma, might be enhanced. This approach "restores" the function and effectiveness of deactivated or depleted T lymphocytes. Conversely, blocking CTLA-4 increased the number of T effector cells in the tumor microenvironment of BCs. As a result, we recommend that the primary focus for overcoming radiation-induced immunotherapy resistance in breast cancer should be a mix of distinct signaling pathways. 4. Photodynamic Therapy (PDT) for Breast Cancer 4.1. Mechanisms of PDT Photodynamic therapy (PDT) is a novel method to treat a wide range of disorders that require the elimination of abnormal cells. It has received much attention recently because of its specificity, minimally invasive nature, and selective cytotoxicity for malignant cells, which implies that normal cells are maintained during therapy compared to traditional treatments . An advantage of PDT is that the photosensitizer can be administered in a variety of ways, such as intravenous injection or topical application to the skin. However, this delivery has implications for biodistribution. PDT works by using a specific wavelength of light to excite the photosensitizer (PS), which is selectively absorbed by the tumor tissue, causing a photochemical effect and stimulating the surrounding matrix, including molecular oxygen, to produce highly active reactive oxygen species, including singlet oxygen. These reactive oxygen species react with biological macromolecules in adjacent cells, such as carbohydrates, lipids, DNA, proteins, and enzymes, resulting in cytotoxicity, tumor cell death, and tumor blood vessel damage, which leads to tumor necrosis and detachment . In addition, it is important to mention that high doses of PSs increase the risk of side effects (e.g., pain, erythema, non-scarring skin lesions, and death of non-tumor cells in the vicinity of the light-exposed area). Therefore, it is important to select an optimal PS dose at which PDT induces tumor cell damage with minimal damage to normal cells. When a photon of light is absorbed by a PS, it can take one of three paths: 1. PS is activated from the ground state to a short-lived excited singlet state, and the excited PS may then emit fluorescence back to the ground state. 2. The abovementioned short-lived stimulated singlet state of PS can undergo an intersystem crossing event to create a comparatively long-lived triplet state. 3. The excited triplet state PS can react with some endogenous chemicals to create a free radical (e.g., H2O2 and O2-). Alternatively, the more long-lived triplet state can create 1O2 by directly interacting with molecular oxygen. Most of the time, the ROS produced by PSs in PDT is mostly related to the latter phase . Early preparations of photosensitizers for PDT were based on a complex mixture of porphyrins called hematoporphyrin derivatives. Extensive chemical and biological research has been carried out over the past 20 years to identify new photosensitizers that belong to different classes of compounds, including porphyrins, chlorins, phthalocyanines, texafrins, and phenothiaziniums . Methylene blue (MB), first extracted by the German chemist Heinrich Caro, has been recognized not only as a dye but also as a medicine that has been used in the treatment of malaria . MB readily penetrates the cell membrane due to the ability of its benzene ring to concentrate in the mitochondria, lysosomes, and double-stranded DNA. Because of the phenothiazinium chromophore of MB, it absorbs light near 630-680 nm, resulting in the formation of reactive oxygen species (ROS), including singlet oxygen . Hence, MB is a photosensitizer essential for PDT. In a recent study, Jesus et al. reported that MB can generate cytotoxic reactive oxygen species (ROS) from molecular oxygen and achieve specific cancer cell death or tumor tissue damage. 4.2. PDT-Mediated Cell Death Mechanisms PDT mediates tumor destruction through three main mechanisms, including direct tumor cell killing, vascular damage, and immune response. Therefore, tumor localization of the photosensitizer is an important factor determining the efficacy of PDT. In recent years, a number of more selective photosensitizers have been developed. For example, MV6401 has been shown to localize selectively in tumor vessels . Drug localization is well known to be determined by vascular permeability and interstitial diffusion, which depend on the molecular size, configuration, charge, and hydrophilic or lipophilic properties of the compound, as well as the physiological properties of blood vessels. The binding of the drug to various components of the tissue may also affect transport and retention in tumors. PDT can cause three primary types of cell death: autophagy, apoptosis, and necrosis-induced cell death. Autophagy, a lysosomal mechanism that degrades and recycles intracellular proteins and organelles, can be activated by a variety of stress signals, including oxidative stress . This mechanism, which includes ROS as one of the key pollutants, may have both cytoprotective and death-promoting effects after cancer treatment . Recent research has discovered autophagy as a method for preserving cell viability following photodynamic damage . Photodamage to the PS in the lysosomal compartment may impair autophagic process completion, resulting in inadequate removal of autophagic cargo. ROS-damaged cytoplasmic components may increase phototoxicity in apoptosis-competent cells. Apoptosis is characterized by chromatin condensation, the breakage of chromosomal DNA into internucleosomal fragments, cell shrinkage, membrane vesicles, and the production of apoptotic bodies without plasma membrane rupture. Furthermore, in cells reacting to PDT, apoptosis is the most common type of cell death. After photodynamic damage, Bcl-2 family members govern mitochondrial outer membrane permeabilization (MOMP), which is assumed to be mostly independent of p53. Photodamage to membrane-bound Bcl-2 in mitochondria-associated PS may be a favorable signal for MOMP and subsequent release of caspase activators such as cytochrome c and Smac/DIABLO or other proapoptotic molecules, such as apoptosis-inducing factor (AIF). Cleavage of Bid and MOMP is induced by lysosomal membrane rupture and the release of cathepsins from photo-oxidized lysosomes. Phototoxicity is not only induced by caspases but can also be caused by other proteases, such as caspases and nonapoptotic pathways. The inhibition of caspase protein or gene expression often only delays phototoxicity or converts cell death to cell necrosis. Recent studies have suggested that some types of necrosis may be mediated by specific signaling pathways . Although the molecular mechanisms by which phototoxicity mediates cell necrosis are not known, several events, such as receptor-interacting protein 1 (RIP1) kinase activation, mitochondrial ROS overproduction, lysosomal damage, and intracellular Ca2+ overload, are known to play roles. Severe photodestruction of the inner mitochondrial membrane or intracellular Ca2+ overload increase mitochondrial permeability, which may promote cell necrosis and apoptosis triggered by phototoxicity. Therefore, therapeutic PDT techniques need to be developed and improved to better understand the interactions between PDT and autophagy, apoptosis, and necrosis and how these processes can contribute to better therapeutic outcomes for tumor patients. 4.3. PDT in Current Breast Cancer Treatment PSs activated by local laser irradiation have recently been associated with PDT and shown to selectively damage tumor tissue rather than normal organs. PDT is a less invasive alternative to surgery. In addition, several studies have shown that PDT can enhance the immune response against tumors through a variety of approaches. Several breast cancer studies have recently shown that the combination of targeted PDT and photothermal therapy (PTT) has the potential to successfully treat HER2-positive breast cancer as a new therapeutic tool. Xu et al. found that the uptake of anti-HER2 and anti-CD44 (Cluster of Differentiation 44) antibodies was increased in tumor cells when PS 5-aminolevulinic acid was mixed with functionalized gold nanorods using the fluorescent dye cyanine 7.5 (Cy7.5) . They also observed that the combination of PDT and PTT significantly increased ROS and thermogenesis in MCF-7 breast cancer cells compared with treatment alone. They found that HER2 and CD44 receptors represented a dual target that strongly promoted the uptake of PS by tumor cells. This result suggests that the combination of PDT and PTT has potent anticancer effects in breast cancer models in vitro and in vivo . Gabrielle et al. demonstrated higher binding capacity and the selective uptake of MCF-7 breast cancer cells when using Pluronic(r) 123 (P123) micelle-loaded chrysin (HYP) photosensitizers compared with normal breast cells (MCF-10A). They also found that the HYP/P123 combination induced MCF-7 breast-cancer-cell-mediated PDT cell necrosis in mitochondria and the endoplasmic reticulum . Wang and colleagues found that PDT treatment improved survival and decreased tumor size in BC mice, suggesting that PDT inhibits proliferation and metastasis . Hoi et al. reported that PDT significantly inhibited breast tumor growth in an in vivo mouse cancer model . Duanmu et al. found that they could safely and effectively destroy multidrug-resistant MCF-7 cells in a mouse model of chemoresistant breast cancer with PDT, targeting tumor vessels and breast cancer cells (Table 2) . Tumor metastasis is considered a key factor in the high risk of death during cancer development and after treatment. During metastasis, cancer cells called circulating tumor cells (CTCs) leave the primary cancer site and enter the blood or lymphatic system. CTCs spread and accumulate in adjacent tissues and distant organs, where they become malignant and worsen tumor progression. Conventional treatments, including radiation and chemotherapy, can activate the development of cancer stem cells from CTCs and worsen metastasis . In contrast, PDT has little effect on physical invasion or off-target damage. Bhuvaneswari and colleagues found tumor vascular responses to bleaching or vasoconstriction by PDT, including platelet aggregation and tumor angiogenesis . Light irradiation and reactive oxygen species production during PDT may block blood vessels by exerting oxidative stress on the blood. In addition, Weng et al. reported that PDT can effectively reduce metastasis by minimizing CTCs after treatment . They observed the real-time and long-term dynamics of CTCs after a single PDT treatment and after surgical resection in an animal model of breast cancer and found that CTC levels were low after PDT treatment and that primary tumor recurrence was delayed in the PDT group compared with the resection group . 5. PDT-Driven Breast Cancer Immunotherapy Conventional breast cancer therapies include surgical resection, chemotherapeutic resection, radiation therapy, and molecular targeted therapy, all of which help to treat early-stage tumors but are ineffective in treating advanced-stage patients . Cancer immunotherapy, by engaging the host immune system, can prevent cancer recurrence and prolong survival in end-stage cancer patients . Many immune-based treatments, such as checkpoint blockade immunotherapy, adoptive cell therapy (ACT), and cancer vaccines, have been licensed for cancer treatment thus far. Despite the numerous benefits of immune checkpoint treatment and its application in clinical oncology, a considerable percentage of patients with breast cancer remain insensitive to immune checkpoint inhibitors due to poor tumor immunogenicity . As a result, combination immunotherapy and other therapeutic methods are receiving more attention. PDT is less intrusive than surgery. Furthermore, multiple studies have proven that PDT boosts the immune response against tumors via a variety of methods . 5.1. PDT-Stimulated Antitumor Immune Response As PDT's direct cytotoxic effects create oxidative stress in the endoplasmic reticulum and photo-oxidative damage to tumor cells, calreticulin (CRT) migrates to the cell membrane during PDT and transmits an "eat me" signal, which prompts an immune response or directly leads to tumor necrosis. Necrotic tumor cells then release intracellular proteins called damage-associated molecular patterns (DAMPs), which occur 1-4 h after PDT . These DAMPs stimulate immune cell activation and migration to sites of cell damage, as well as phagocytosis of wounded cells, resulting in antigen presentation and T cell activation. PDT initiates an inflammatory response fueled by neutrophils, macrophages, and other cellular components that migrate to the treated tumor . The number of neutrophils increases first, and this increase is promoted by TNF-a, a byproduct of PDT . Although macrophages proliferate and move as an initial response to PDT, they also play an important role in enhancing immune-mediated effects and are sensitive to dosage changes of PDT. Low-dose PDT appears to selectively activate macrophages. In addition, an increase in the populations of myeloid cells, monocytes, macrophages, and mast cells has been observed shortly after PDT . Macrophages release lysophosphatidylcholine after PDT. This protein is a substrate in T and B cell enzymatic pathways that eventually leads to the formation of macrophage-activating factor (MAF), which induces tumor-specific cytotoxic effects in activated macrophages . In addition, PDT appears to enhance the phagocytic activity of macrophages and promote their involvement in the clearance of dead and dying cells at the treatment site . The end result of this process is the activation of CD8+ T cells . The efficacy of PDT in both innate and adaptive responses depends on T-cell-mediated anticancer activity. Presentation of antigen to T cell receptors by neutrophils, macrophages, and dendritic cells via MHC class I proteins leads to CD8+ (cytotoxic) T cell activation and tumor-specific cytotoxicity . Alternatively, MHC class II antigen presentation by APCs leads to activation of CD4+ T cells (helper cells) . Another difference in T cell activity is seen in CD4+ T helper 1 cells, which are responsible for the activation of cytotoxic CD8+ T cells, whereas CD4+ T helper 2 cells promote B cell proliferation and antibody class switching, which activates macrophages. 5.2. PDT-Induced Immunogenic Cell Death One of the most important prerequisites for successful cancer therapy is the ability of an anticancer drug to effectively induce immunogenic cell death in tumor cells. Although numerous cellular stressors can induce immunogenic cell death in tumor cells, the specific pattern of molecular players and the nature of death depend on the treatment technique and possibly the cancer cell type . Stress-induced ROS have been shown to be a prerequisite for PDT-induced ICD in tumor cells, followed by exposure to one of the major DAMPs, CRT, and the activation of the host anticancer immune system . Therefore, it is reasonable to assume that the direct injection of PS-targeting agents into the endoplasmic reticulum is a successful technique for cancer eradication in PDT combined with breast cancer immunotherapy. For example, some studies have shown that hypericin accumulates directly in the ER, leading to substantial ROS formation and triggering severe immunological responses during PDT . PDT can stimulate CTL-mediated antitumor immunity while also altering the immunosuppressive microenvironment in the tumor, encouraging tumor cell death. However, adaptive immune system resistance or tumor cell invasion dramatically reduces the efficiency of this immune response. Tumor cells use adaptive immune resistance or evasion to shield themselves from host immunological responses. Programmed cell death receptor 1 (PD-1) and its ligand programmed death ligand 1 are important immunological checkpoint molecules (PD-L1). Because most malignant tumor cells express PD-L1, binding to PD-1 expressed on the surface of T cells drastically reduces cytokine production as well as T cell proliferation and activity, eventually leading to immunological resistance/evasion. 5.3. PDT Combined with Immune Modulatory Agents PDT-mediated immune responses that disseminate to distant areas following local therapy appear to depend on a variety of unknown characteristics; they do not occur in all individuals. However, both local and distant immunologic responses have been routinely documented in investigations combining PDT with an immunostimulatory medication. PDT coupled with immunomodulatory medications has been found in a variety of cancer animal models to produce a sustained immune response and boost effectiveness in killing tumor cells and reducing tumor growth (including breast cancer models). Combination treatment improved tumor antigen presentation, increased T cell activation, reduced Treg expression, and successfully resisted tumor rechallenge. This phenomenon was observed under some conditions, irrespective of the photosensitizer utilized. Xia et al. recently showed that combining PDT with the immunomodulatory drug CpG oligodeoxynucleotide resulted in delayed metastatic spread, longer life, and enhanced CD8+ T cell activation . Shams et al. employed a two-stage therapy approach combined with immune boosting, in which a low dosage of PDT (immunogenic) is provided followed by a high dose; antitumor effectiveness in different tumor cell lines was inconsistent . This treatment prolonged survival and delayed metastatic spread. To date, these findings have yet to be translated into the clinical setting. A unique combination treatment strategy based on two HPs and the capacity of PDT to operate directly on tumor cells and induce antitumor immunity was proposed. In two-step PDT therapy, HPPH and Photofrin were used. Following an immune-boosting low-dose PDT therapy, a tumor-controlling high-dose PDT treatment was administered. This combination PDT therapy enhanced the number of activated tumor-specific CD8+ T lymphocytes in tumor-draining lymph nodes, which was associated with a reduction in tumor spread potential (e.g., in and 4T1 breast carcinomas). It was also linked to better long-term tumor growth control and resistance to tumor recurrence in treated mice. Some startling results support the use of radicicin (also known as fontanelle) in PDT treatment in conjunction with immunotherapy. Tumor formation was significantly reduced after vaccination with the radiciclovine-based PDT cell lysate TC-1 that expresses human papillomavirus E7 and the immunoadjuvant CpG oligonucleotide at both prophylactic and therapeutic doses (ODN). When PDT cell lysates were combined with ODN injections, IFN production and cytotoxic T lymphocyte (CD8+ T cell) responses were greater than when ODN or PDT was administered alone. Similar results were obtained in a rat tumor model using radiation-based PDT of TC-1 cells in combination with adenoviral injections of interleukin-12 (AdmIL-12) . In this study, the combination treatment significantly increased IFN and TNF production and the expansion of CD8+ T-cell-driven CTL subpopulations, resulting in complete tumor regression in mice with 9 mm tumors. In another study, fontanin-based PDT in combination with synthetic long peptides carrying antigenic tumor epitopes was used to treat RMA cells (an aggressive T cell lymphoma cell line generated by Rauscher murine leukemia virus) in a mouse model of therapeutic immunization . This strategy resulted in a significant antitumor CD8+ T cell response. These results all suggest that current cancer therapy should be based on a combination of multiple anticancer approaches, with activation of the immune system playing a key role. Checkpoint inhibitors, such as antibodies blocking programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1), are another treatment option to induce ICD in PDT patients. He et al. used nanoscale coordination polymer core-shell nanoparticles containing oxaliplatin in the core part and PS pyrophospholipid conjugates (pyrolipid) in the shell part to provide combined anti-PD-L1 therapy (NCP-pyrolipid) of treated tumor cells and showed tumor cell exposure to CRT, anticancer immunity, increased tumor cell apoptosis, and an aspirin effect . In another study, similar effects were reported when zinc pyrophosphate (ZnP) nanoparticles were loaded with pyrolipids (ZnP-pyro) and used in combination with anti-PD-L1 therapies . 5.4. Disadvantage of PDT and Immunotherapy in Breast Cancer PDT combined with immunotherapy has many advantages: it does not induce resistance and it is minimally invasive. Thus, it has become an effective method for treating cancer and improving clinical outcomes. In particular, nanotechnology-derived PSs or photothermal converters can significantly improve patient survival by combining phototherapy and immunotherapy. However, several variables severely limit the efficacy of PDTs and reduce their potential to elicit immunologic responses. First, tumor hypoxia can reduce the efficacy of oxygen-dependent PDTs, and oxygen consumption by PDTs can exacerbate tumor hypoxia, creating a vicious cycle . Rapid tumor growth leads to inadequate blood supply, and local oxygen depletion from PDTs exacerbates tumor hypoxia, which severely impairs PDT efficacy . Therefore, alleviating hypoxia at the tumor is an important approach to improve the efficacy of PDT-assisted cancer immunotherapy. Recently, researchers have developed various biomaterials and therapeutic agents to reduce tumor hypoxia, including hemoglobin, catalase (CAT), manganese dioxide NPs, oxygen shuttle nanoperfluorinated compounds (nanoPFCs), hyaluronidase (HAase), and metformin (Met). Second, most of the PSs used for PDT are activated by short wavelengths (e.g., visible light 400-700 nm), resulting in limited penetration depth into living tissue . In addition, tissue hemoglobin can strongly absorb visible light, which greatly hinders the conversion of PS into light . Recent studies have reported that UCNs are nanoscale materials that convert low-energy light into high-energy light through an anti-Stokes emission process with sequential excitation of multiple photons. Compared with downconverted NPs, UCNs can absorb near-infrared (NIR) light and have a relatively high penetration depth into tissues, while the light can be converted into strong UV or visible light . Because of this property, UCN-based PDTs have been extensively studied for tumor therapy to improve tissue penetration depth. Third, high PS concentrations usually cause aggregation-induced quenching (ACQ), which severely weakens the optical properties of PS . During PDT, high PS concentrations in the compact core of NPs tend to induce ACQ effects, resulting in decreased ROS production and fluorescence self-quenching . To further enhance the immune response, Zhang et al. developed a cell-membrane-fused nMOF (FM) for photoactivated cancer immunotherapy using FM derived from DCs and tumor cells. Fourth, systemic administration of PSs can cause phototoxicity due to off-target effects and accumulation in normal tissues . As compared to normal tissue, solid tumors display various TME characteristics, such as low pH, severe hypoxia, and elevated glutathione (GSH) levels. As a result, smart stimuli-responsive nanomedicines including TME-sensitive chemical linkers or components may be able to adjust the release of their carriers. TME-sensitive NPs have the ability to intelligently design the placement and pharmacokinetics of PSs and immunomodulators to improve tumor targeting and increase PDT-guided cancer immunotherapy without causing major side effects. 5.5. Challenges and Future Trends in PDT-Induced ICD Hypoxia, which is common in the tumor microenvironment, may impair the effectiveness of PDT-based ICD induction. The hypoxic process is fueled by cancer cell growth, resulting in a major imbalance between oxygen supply and demand and severe metabolic abnormalities. Pathophysiological alterations, such as tumor blood vessel distortion due to an imbalance of antiangiogenic signals, physical compression, and lymphatic system disruption, all contribute to the development of oxygen deficits in the tumor microenvironment . As PDT relies on oxygen transport to generate the deadly production of ROS, hypoxia significantly lowers the effectiveness of PDT in solid tumors. As a result, finding strategies to overcome the hypoxia-related limitations of PDT is vital. The use of medicines that boost the oxygen content in the tumor microenvironment can improve the efficacy of PDT in producing ICD, an approach termed oxygen-enhanced PDT. One approach is to develop adaptive oxygen carriers or generators, such as perfluorocarbon nanoparticles utilized in clinical artificial blood applications. Because of its high oxygen capacity, perfluorocarbon has a long 1O2 lifetime, resulting in long-lasting photodynamic effects . Other procedures are linked with the creation of manganese dioxide nanoparticles (MnO2). The breakdown of MnO2 in the acidic and H2O2-rich tumor microenvironment provides sufficient oxygen and enhances ROS generation, which increases PDT effectiveness. Furthermore, Mn(I) ion reduction from Mn(V) in response to highly acidic H2O2 allows for in vivo selective MRI . Interestingly, MnO2-encapsulated core-shell gold nanocages (AuNC@MnO2) changed the hypoxic and immunosuppressive tumor microenvironment and demonstrated consistent PDT and ICD effects. The emission of DAMPs such as CRT, ATP, and HMGB1 is characterized by oxygen-enhanced PDT with such nanoparticles, followed by DC maturation and subsequent activation of effector cells such as CD8+ and CD4+ T cells and NK cells. In two different tumor models (CT26 colorectal and 4T1 breast cancer mice), this was found to trigger an anticancer immune response and successfully suppress tumor development and recurrence. 6. Conclusions In recent years, PDT has become increasingly recognized as a viable method for generating ICD in experimental cancer treatment. However, most research has employed mouse models, and this method must be validated in a clinical environment. Furthermore, new insights into the interaction between PDT and oxygen-assisted treatment may open up new avenues for the creation of a novel cancer immunotherapy. PDT and ICD are difficult areas of study with numerous potentially interesting future uses in cancer therapy. Author Contributions Conceptualization, H.J.; methodology, H.J.; software, H.J.; validation, S.L. and S.S.; formal analysis, S.S.; investigation, Z.X.; resources, J.L.; data curation, H.J.; writing--original draft preparation, H.J.; writing--review and editing, F.Y.; visualization, X.X.; supervision, F.Y.; project administration, X.X.; funding acquisition, K.Z. 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 The potential role of T cells and macrophages in the TME. Normal breast tissue can become cancerous after stimulation by radiation, chronic inflammation, or viral infection. A variety of immune cells (B cells, T cells, macrophages, and DCs) elicit the body's antitumor immune response through different mechanisms. Tumor debris generated by tumor cell death is phagocytosed and processed by DCs to present antigens to T cells, activate CD4+ Th1 cells via IFN-g, and finally activate CD8+ CTL cells. In the tumor immune microenvironment, CD103 binds to tumor cells expressing E-cadherin, reinforcing the establishment of the link between immune cells and tumor cells. T cells highly express immune checkpoint proteins such as PD-1, CTLA-4, TIM-3, and LAG-3, which prevent tumor immune escape upon binding to the corresponding ligands on tumor cells. Additionally, increased presentation of tumor-associated antigens (TAAs) promoted the activity of M1 macrophages and upregulated the antitumor immune response. Reprinted/adapted with permission from Created with BioRender.com. Figure 2 Induction of antitumor immunity by PDT. The photosensitizer (PS) is excited by light of an appropriate wavelength, and the excited PS directly transfers energy to oxygen to generate reactive oxygen species (ROS) such as singlet oxygen (1O2), superoxide anions (O2-), and hydroxyl radicals (OH) in tumor cells. Highly reactive ROS destroy tumor cells directly or indirectly through apoptotic, necrotic, and autophagy-associated cell death. In addition, PDT also induces acute inflammation and triggers the release of cytokines and stress response proteins. Initially, neutrophils are activated in the bloodstream and migrate through blood vessels to infectious or injured sites to kill cancer cells and release damage-associated molecular patterns (DAMPs). Meanwhile, blood vessel injury and tumor cells also attract macrophage infiltration, which regulates macrophage polarization and enhances macrophage phagocytosis of tumor cells. Natural killer cells (NK cells) and dendritic cells (DCs) activate adaptive immune cells such as monocytes, cytotoxic T lymphocytes (CTLs), and B cells to enhance the overall immune response by releasing cytokines. Reprinted/adapted with permission from Created with BioRender.com. cancers-15-01532-t001_Table 1 Table 1 Breast cancer immunotherapeutic drugs in clinical use or trial. Category Agent Cancer Types Phase Clinical Trial Reference Number Reference Tumor vaccine Personalized peptide vaccine MUC1 Vaccine TNBC Early Phase I NCT00986609 Folate Receptor Alpha Peptide Vaccine TNBC Phase II NCT02593227 RNA vaccines IVAC_W_bre1_uID and IVAC_M_uID TNBC Phase I NCT02316457 N/A Adoptive cell DC-CIK cells TNBC Phase II NCT02539017 gdT cells TNBC Phase II NCT02418481 HER2 vaccine E75 peptide + GM-CSF T1-T3 HER2 + BC Phase III NCT01479244 E75 peptide (KIFGSLAFL) vaccine + GM-CSF HER2 1+/2 + BC Phase II NCT01570036 AE37 + GM-CSF HER2 + BC Phase II NCT00524277 N/A Immune checkpoint inhibitors PD-1 Pembrolizumab ER+/HER2-PD-L1 + aBC Phase Ib NCT02054806 Pembrolizumab + chemotherapy High-risk, stage II/III BC Phase II NCT01042379 PD-L1 Atezolizumab + paclitaxel Locally advanced inoperable TNBC/mTNBC 1st line Phase III NCT03125902 Avelumab mBC Phase Ib NCT01772004 Atezolizumab + chemotherapy TNBC Phase III NCT03197935 Adoptive cell therapies TIL Therapy LN-145 TNBC Phase II NCT04111510 N/A Tumor infiltrating lymphocytes + IL-2 Breast Carcinoma Phase I NCT01462903 N/A CD8+ Enriched TIL vs. unselected TIL vs. unselected TIL + pembrolizumab Metastatic BC Phase II NCT01174121 N/A Costimulated tumor-derived T cells mBC Phase I NCT00301730 N/A Dendritic cell Therapy Neo-antigen pulsed DC BC Phase I NCT04105582 N/A Autologous dendritic cells + chemotherapy TNBC Phase I/II NCT03450044 Celecoxib + Pembrolizumab Brain metastases from TNBC or HER2 + BC Phase IIa NCT04348747 N/A CAR-T huMNC2-CAR44 CAR T cells Metastatic BC Phase I NCT04020575 N/A CART-TnMUC1 TNBC Phase I NCT04025216 N/A CAR-T cells recognizing EpCAM EpCAM + BC Phase I NCT02915445 N/A CAdVEC HER2 + BC Phase I NCT03740256 Oncolytic viruses Oncolytic virus Pelareorep + paclitaxel Advanced BC/mBC Phase II NCT01656538 TBio-6517 + Pembrolizumab metastatic BC Phase I/IIa NCT04301011 N/A talimogene ER + HER2-BC Phase I NCT04185311 N/A cancers-15-01532-t002_Table 2 Table 2 Clinical trials on PDT of breast cancer and related conditions. Photosensitizer(s) Wave Length (nm) Study Details Phase Zinc phthalo-cyannine 675 In vitro study on murine breast cancer cell lines Phase I SnEt2-Purlytin 660 Clinical use for treatment of skin metastases including breast cancer Phase I Motexafin lutetium (Lutex) 720 Clinical use for treatment of skin metastases including breast cancer Phase II Photofrin 630 Clinical trial for the treatment of breast cancer skin metastases Phase II mono-L-aspartyl chlorin 664-667 Clinical trial for the treatment of breast cancer skin metastases Phase II meta-tetra (hydroxyphenyl) chlorin (m-THPC) (Foscan) 652 Patient series treatment of breast cancer metastases Phase II Verteporfin (Visudyne) 690 Clinical trial for treatment in primary breast cancer used in murine breast cancer models Phase II Porphyrins 630 Confirmed stage IIIb and IV breast cancer treatment with continuous low-irradiance PDT using verteporfin Phase II Chlorins 650-700 PDT study on patients with chest wall progression of breast cancer. Phase I Transition metal compounds N/A PDT for the treatment of chest wall progression of breast cancer. N/A Hypericin 470-570 PDT treatment of primary breast cancer diagnosed patients and patients who received mastectomy or local wide excisions of the breast. Phase I/IIa 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. |
PMC10000401 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050688 healthcare-11-00688 Article COVID-19 Vaccine Acceptance Behavior among Hispanics/Latinxs in Nevada: A Theory-Based Analysis Nerida Tara Marie Conceptualization Methodology Software Validation Formal analysis Investigation Resources Data curation Writing - original draft Writing - review & editing Visualization 1* Sharma Manoj Conceptualization Methodology Validation Writing - review & editing Supervision 12* Labus Brian Validation Writing - review & editing 3 Marquez Erika Validation Writing - review & editing 4 Dai Chia-Liang Validation Writing - review & editing 5 Kern Margaret L. Academic Editor 1 Department of Social and Behavioral Health, University of Nevada, Las Vegas, NV 89119, USA 2 Department of Internal Medicine, Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas, NV 89102, USA 3 Department of Epidemiology and Biostatistics, University of Nevada, Las Vegas, NV 89119, USA 4 Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89119, USA 5 Department of Teaching and Learning, University of Nevada, Las Vegas, NV 89119, USA * Correspondence: [email protected] (T.M.N.); [email protected] (M.S.) 26 2 2023 3 2023 11 5 68830 12 2022 23 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 ). Hesitancy toward the COVID-19 vaccine has hindered its rapid uptake among the Hispanic and Latinx populations. The study aimed to use the Multi-Theory Model (MTM) for health behavior change to explain the intention of initiating and sustaining the behavior of COVID-19 vaccination among the Hispanic and Latinx populations that expressed and did not express hesitancy towards the vaccine in Nevada. Using a quantitative cross-sectional and survey-based research study design, data were collected using a 50-item questionnaire and analyzed using multiple linear regression modeling. Of 231 respondents, participatory dialogue (b = 0.113, p < 0.001; b = 0.072, p < 0.001) and behavioral confidence (b = 0.358, p < 0.001; b = 0.206, p < 0.001) displayed significant associations with the initiation of COVID-19 vaccine acceptance among vaccine-hesitant and non-vaccine-hesitant individuals. Emotional transformation (b = 0.087, p < 0.001; b = 0.177, p < 0.001) displayed a significant association with the sustenance of COVID-19 vaccine acceptance among vaccine-hesitant and non-vaccine-hesitant individuals. Results from this study provide evidence that the MTM is a useful tool in predicting COVID-19 vaccine acceptance behavior among Hispanics and Latinxs in Nevada, and it should be used in intervention designs and messaging to promote vaccine uptake. COVID-19 vaccine acceptance initiation sustenance multi-theory model of health behavior change Hispanic/Latinx This research received no external funding. pmc1. Introduction In 2020, the COVID-19 pandemic quickly became a global public health issue that has drastically impacted many lives, including individuals' and communities' health, economic shifts, and social and physical restrictions. The repercussions that the COVID-19 virus inflicted on the world have left many populations trying to get back to a "normal" life to this day. The drastic impact COVID-19 had on the United States left over ninety million cases and over one million deaths as of 4 August 2022 . Additionally, the COVID-19 pandemic exposed the disproportionate health impacts on vulnerable populations, including the inequalities affected by income, age, race, sex, and geographic location . This was particularly evident among the Hispanic and Latinx populations across the United States. Compared to White non-Hispanic people, Hispanic or Latinx people are 1.5 times more likely to be diagnosed with COVID-19, 2.3 times more likely to be hospitalized because of COVID-19, and 1.1 times more likely to die from COVID-19 . Due to having the highest uninsured rates, the majority of these populations being unauthorized or undocumented immigrants and ineligible for Medicaid or other government benefits, and having significant language barriers, the Hispanic and Latinx populations have faced many challenges that make them vulnerable to COVID-19 and the drastic effects that have impacted them . As of June 2021, three COVID-19 vaccines had been approved for Emergency Use Authorization (EUA) by the U.S. Food and Drug Administration (FDA): Pfizer-BioNTech (BNT161b2), Moderna (mRNA-1273), and Janssen (Ad26.COV2.S) . According to studies, the Pfizer, Moderna, and Janssen vaccines showed 95%, 94.1%, and 66% efficacy, respectively, at preventing illness in clinical lab settings, including severe disease leading to hospitalization and death . The Food and Drug Administration [FDA] fully approved the Pfizer-BioNTech COVID-19 vaccine on 23 August 2021 (FDA, 2021) and the Moderna COVID-19 vaccine on 31 January 2022 . However, hesitancy toward the COVID-19 vaccine has hindered its rapid uptake. Vaccine hesitancy is defined as a "delay in acceptance or refusal of vaccines despite availability of vaccine services" and has emerged as a public health issue threatening the end of the COVID-19 pandemic. Many are hesitant to receive the COVID-19 vaccine for various reasons, including the fear of vaccine side effects, the safety of the vaccine, and its effectiveness given how new the vaccine was . Another threat to vaccine acceptance is the "infodemic", which the World Health Organization defines as "an overabundance of information and the rapid spread of misleading or fabricated news, images, and videos" . This infodemic has amplified the amount of misinformation being spread about the COVID-19 vaccine, which results in increased hesitancy among vulnerable populations who have utilized social media as a major form of receiving information about the vaccine . Addressing these hesitancies and building vaccine confidence is key to increasing vaccine uptake. When the first COVID-19 vaccines were introduced and just about to be released in the United States, the December 2020 Kaiser Family Foundation COVID-19 Vaccine Monitor found that among Hispanic adults, 61% trusted the safety and effectiveness of the vaccine, 61% believed that the vaccine would be distributed equally, and 60% were confident that the development of the vaccines had considered the needs of the Hispanic and Latinx people . This finding showed that the Hispanic and Latinx populations may have been interested in receiving the vaccine early on. However, after the release of the plans for vaccine distribution across the United States, because many of the Hispanic and Latinx populations were not eligible for the vaccine right away, the long wait to get vaccinated may have allowed for more time to increase vaccine hesitancy. This may have also been influenced by several factors, such as misinformation, myths, citizenship status, language barriers, work schedules, lack of understanding of virtual technologies to schedule vaccine appointments, etc., which are responsible for this disparity . Although many members of the Hispanic and Latinx population are accepting of getting the COVID-19 vaccine, others are still hesitant due to historical and pre-existing experiences that have previously affected the hesitancy of getting vaccinated, including lower access to adequate healthcare providers for minority populations, historical mistrust, cost-related concerns, and lower awareness and education about the importance of the vaccine . While not a comprehensive list, these are some of the factors that have affected the uptake of routine immunizations that have been available for years. The acceptance of the COVID-19 vaccines has also been linked with historical reluctance to accept other routine immunizations, especially seasonal influenza (flu) vaccines . The Hispanic and Black communities in the United States have traditionally had lower rates of flu vaccine coverage compared to Whites . Survey results of one study show that those who did not intend to get the COVID-19 vaccine when it became available had 79% lower odds (aOR = 0.21) of receiving a flu vaccine in the previous year . The intent to get vaccinated is ultimately determined by values, cultures, and experiences, which include how Hispanics and Latinxs rely heavily on trusted voices within the communities to provide their expertise about vaccinations . Many cultures have various views on vaccination, including the COVID-19 vaccine, which has affected vaccine uptake . Similarly, trust and mistrust in influential individuals within specific cultures has been shown to affect the uptake of the COVID-19 vaccine. Lower levels of trust toward science and state-sponsored health programs among ethnic minorities, including the Hispanic and Latinx populations, African Americans, Native Americans, Native Hawaiians, and Alaskan Natives, are a direct result of previous or negative experiences with unethical healthcare research and an unethical healthcare system, as well as an under-representation of ethnic minorities in research . This may include colonization, eugenics, and medical experiments that inhibit the trust of Hispanics and Latinxs, among other minorities, towards the healthcare system . In addition, Hispanic and Latinx people have also demonstrated vaccine hesitancy influenced by cultural factors, such as moral concerns related to the belief that vaccine manufacturers used abortion-derived fetal cell lines or the belief that religious prayers should be preferred over the use of medicine . Because the Hispanic and Latinx populations around the United States are significantly vulnerable to COVID-19 complications, hospitalizations, and deaths , further investigation is needed to understand their perceptions and intentions of receiving the COVID-19 vaccine and completing the vaccine series compared to other racial and ethnic groups. Based on this information, four problems were identified to be addressed by public health professionals: (1) there are high rates of COVID-19 in Hispanics and Latinxs in the United States and Nevada; (2) there are low rates of vaccination in Hispanics and Latinxs in the United States and Nevada; (3) there is little literature, especially theory-based literature, focusing on the determinants of COVID-19 vaccination in Hispanics and Latinxs; and (4) there is a problem of Hispanics and Latinxs not being interested in or following through with taking the second dose or booster vaccines. The purpose of this study was to use a fourth-generation theory-based approach of the Multi-Theory Model (MTM) of health behavior change to explain the intention of initiating COVID-19 vaccination among the Hispanic and Latinx populations that expressed and did not express hesitancy toward the vaccine in Nevada. The covariates that were controlled for because of their possible effects on COVID-19 vaccination uptake status were age, race, gender, education level, religion, income, and employment status . 2. Materials and Methods 2.1. Population The study was conducted out of the University of Nevada, Las Vegas between May and August 2022. The population being sampled was Hispanic and Latinx individuals residing in Nevada from the years 2021 to 2022. In order to determine the required sample size for the multiple regression, an a priori sample size was calculated using the G*Power, Version 3.1.9.6 for Mac . The parameters set for this calculator for regression were an alpha level of 0.05, power at 0.80, an estimated effect size of 0.15 (medium), and three predictors (for the three constructs in each of the initiation and sustenance components of the MTM). This yielded a required sample size of 77. To account for any covariates that may be found as significant, the sample size was inflated by approximately 20%, which is around 92 for each of the hesitant and non-hesitant groups. Thus, the total sample size proposed was at least 184, which was also considered sufficient for confirmatory factor analysis . Inclusion criteria for participation in the study were: (1) of Hispanic or Latinx descent; (2) age 18 years or older; (3) currently residing in Nevada; and (4) providing informed consent to participate if the study was exempt. Participants who did not meet the above inclusion criteria and those who were mandated to receive the COVID-19 vaccine for employment or school requirements were excluded from the study. 2.2. Theoretical Framework The present study uses the Multi-Theory Model (MTM) of health behavior change as the theoretical framework to explore vaccine acceptance behaviors among Hispanics and Latinxs in Nevada due to its unique ability to explain the intention and sustenance of behavior change . There are two components of the MTM that facilitate health behavior change: (1) initiation of the behavior change, and (2) sustenance or continuation of the health behavior change . Initiation of the behavior change refers to a one-time or short-term change that progresses a person from one behavior to another . Sustenance or continuation of the health behavior change is the long-term change that continues after initiation is enacted . The constructs of participatory dialogue (i.e., the advantages and disadvantages of health behavior change and the dialogue facilitated by a health educator to create change), behavioral confidence (i.e., the culturally-specific term that refers to the confidence or belief that the person is capable of initiating and achieving the desired behavior change), and changes in the physical environment (i.e., the physical surroundings that provide resources for the person to initiate the behavior change) will contribute to the initiation of intended behavior . Figure 1 shows how the constructs of initiation interact and were operationalized in this study. The constructs of emotional transformation (i.e., when a person transforms or converts their emotions towards the health behavior change they are trying to sustain), practice for change (i.e., when the person continuously evaluates and adjusts the strategies, overcomes the barriers, and remains focused on maintaining that behavior change), and changes in the social environment (i.e., the social support, either natural or artificial, from the environment that creates a positive relationship with sustained behavior change) will lead to the sustenance of the intended behavior . Figure 2 shows how the constructs of sustenance interact and were operationalized in this study. 2.3. Instrumentation The survey instrument consisted of 50 total items and was developed based on the MTM theoretical framework to assess vaccine acceptance behavior. One item assessed the current state of vaccine hesitancy (i.e., do you currently have any hesitancy in taking the COVID-19 vaccine?), and two items assessed if the person had already completed at least one dose or the full series of the COVID-19 vaccine dosage. Fourteen items assessed socioeconomic characteristics (i.e., age, zip code of residence, gender, ethnicity and Hispanic/Latinx subgroup, education level, etc.), two of which were optional questions at the end of the survey, as they asked about political affiliation and citizenship status. Religion is an important aspect of the lives of the Hispanic/Latinx population; therefore, it was important that the item addressing religion included the most common religious affiliations among this population . Similarly, when addressing the Hispanic/Latinx subgroup, it was important for the item to include most, if not all, of the Hispanic and Latinx origins, as each group differs in many ways . One question assessed if the person was mandated to take the COVID-19 vaccine, and two additional questions assessed the person's trust in a medical professional for COVID-19 vaccine information and encouragement. Thirty items assessed the constructs of MTM, of which fifteen items assessed the initiation construct and fifteen items assessed the sustenance construct. 2.4. Survey Translation The survey was written in English and translated into Spanish to ensure there was access to the predominant languages of the Hispanic and Latinx populations. The survey was then retranslated back to English to ensure proper translation of survey content. 2.5. Face and Content Validity The instrument was validated by six experts in public health and the Hispanic and Latinx populations to ensure content validity. The experts included professors with doctorate degrees in public health and/or the MTM theoretical framework, community partners that focused on and worked with the Hispanic and Latinx populations, and individuals who were knowledgeable about COVID-19 vaccination based on their involvement with vaccine distribution. After validation by experts, the instrument had a Flesch Reading Ease score of 52.3 and a Flesch-Kincaid Grade Level of 9.9 overall. The instrument was thoroughly reviewed by experts and community members to ensure that face and content validity were being measured appropriately. 2.6. Data Collection The survey instrument was administered via three routes: (1) a web-based survey tool via Qualtrics, (2) in-person outreach via paper surveys and flyers with QR codes to the web-based survey tool, and (3) calls via Qualtrics Sample Services. To administer the survey via the web-based survey tool, participants were recruited through community contacts that had an established connection with the Hispanic and Latinx populations to ensure participants had trust and confidence in the individuals recruiting for and/or administering the survey. A recruitment email and flyer were provided in both English and Spanish. Participants were also recruited at in-person events with a local nonprofit organization. At in-person events, such as pop-up vaccination clinics, education sessions, and outreach events throughout Nevada, the recruitment flyer was displayed for participation, and paper surveys were available. The researcher and/or other volunteers recruited participants by distributing paper surveys and flyers. For the completed paper surveys, the researcher inputted all answers reported on paper directly onto the Qualtrics survey. The researcher also employed Qualtrics Sample Services to perform the data collection to reach the ideal sample size. The Qualtrics Sample Services delivery team managed the data collection process and invited respondents that met the geographic and demographic restrictions to complete the online survey. 2.7. Construct Validity Confirmatory factor analysis was used to assess the construct validity by using the maximum likelihood estimation of all MTM subscales being studied, including advantages, disadvantages, behavioral confidence, changes in the physical environment, emotional transformation, practice for change, and changes in the social environment. This was determined if each construct yielded a single-factor solution, factor loading values greater than 0.384, and an Eigenvalue that was greater than or equal to 1 . 2.8. Reliability Cronbach's alphas were used to determine the internal consistency reliability for each MTM construct. These values were compared to a value of 0.70 or higher to be considered acceptable . 2.9. Data Analysis The survey data from Qualtrics were further analyzed in SPSS (Version 27.0, IBM, Armonk, NY, USA). Descriptive statistical analysis was conducted for all study variables. Counts and frequencies were reported for all demographic characteristics and categorical study variables. Continuous study variables reported means and standard deviations. The demographic characteristics of age, race, gender, education level, religion, income, and employment status served as covariates in the multivariate data analysis plan. A zero-order correlation matrix was conducted among the construct variables to identify if there were any significant, simple bivariate relationships between the theoretical constructs and both the initiation and sustenance for the hesitant and non-hesitant groups. Hierarchical multiple regression was used to "control" for certain variables among different groups to see if adding variables improved the model's capacity to predict the likelihood of getting the COVID-19 vaccine and/or the second dose/booster dose ; this was used to study the hesitant and non-hesitant groups and their relationship with the two outcome variables of initiation and sustenance, which formed four models. The significance level was set at 0.05 for all data analyses, and 95% confidence intervals were reported as applicable. 2.10. Ethical Approval This study was submitted for approval to the University of Nevada, Las Vegas Institutional Review Board (IRB). The study was first approved as exempt on 3 May 2022 (UNLV-2022-192). It was then approved for its first modification to the protocol, informed consent form, and recruitment materials on 17 June 2022. The final modification was approved on 20 July 2022, for an addition to the recruitment and data collection strategy. Participants were required to provide consent to participation in the survey by clicking on the next button in the electronic version and by continuing the survey in the paper version. Participants were allowed to choose to withdraw from the survey at any time. For Spanish-speaking participants, the consent form and survey were presented "in [a] language understandable to the subject" . All procedures to conduct the research involving human subjects followed the IRB ethical standards. 3. Results 3.1. Confirmatory Factor Analysis for Construct Validity Confirmatory factor analysis was used to assess the construct validity by using the maximum likelihood estimation of all MTM subscales being studied, including advantages, disadvantages, behavioral confidence, changes in the physical environment, emotional transformation, practice for change, and changes in the social environment. Confirmatory factor analysis revealed that each MTM subscale generated a single-factor solution, with most having factor loadings greater than 0.326 and an Eigenvalue greater than or equal to 1 . All but one item met the critical value of 0.326 for factor loadings . Of those that met the critical value, the minimum factor loading was 0.615 and the maximum factor loading was 0.999. The majority of factor loadings were over double the critical value, indicating that these were high factor loadings. The item that did not meet the critical value was the question "Do you believe the COVID-19 vaccine is accessible for you to get it if you wanted it?" under the behavioral confidence construct, with a factor loading of 0.308. 3.2. Descriptive Statistics of Demographic Variables The final sample size included 231 participants. Results from the descriptive statistical analysis are displayed in Table 1. The mean age of participants was 37.83 +- 14.14 years. The majority of participants identified as female (n = 160, 69.3%). Because all participants identified as being of Hispanic or Latinx descent, the Hispanic/Latinx identity that was most associated with participants was Mexican (n = 146, 63.2%). The highest level of education achieved by most participants was "some college" (n = 94, 40.7%) and high school (n = 75, 32.5%). Of all religions presented, approximately a third of participants identified as believing in Catholicism (n = 79, 34.2%); unaffiliated with any religion (n = 69, 29.9%) had the second highest number of participants. More than half of the participants were employed (n = 138, 59.7%), where the highest reported individual incomes were USD 25,000 to USD 49,999 (n = 85, 36.8%) and USD 50,000 to USD 74,999 (n = 53, 22.9%). The mean average number of people living in one household was 3.22 +- 1.57 people. In addition, most participants reported their marital status as single (n = 84, 36.4%) or married (n = 74, 32.0%). Most participants reported possessing health insurance (n = 182, 78.8%). Of the participants who had responded to the optional questions, participants reported their political affiliation as either Republican (n = 46, 19.9%), Democratic (n = 82, 35.5%), Independent (n = 59, 25.5%), other (n = 17, 7.4%), or prefer not to answer (n = 21, 9.1%). The second optional question asked about current citizenship status, in which the vast majority of respondents reported being a citizen of the United States (n = 206, 89.2%). Most importantly for further data analysis, 36.4% of participants expressed hesitancy to take the COVID-19 vaccine (n = 84) and 63.6% of participants did not express hesitancy to take the COVID-19 vaccine (n = 147). A little over half of the participants had received at least one dose of the COVID-19 vaccine (n = 136, 58.9%), which slightly decreased the number of participants who had completed the series of the COVID-19 vaccine (n = 127, 55.0%), meaning they received at least two doses of the Pfizer or Moderna vaccine or one dose of the Janssen vaccine. While 69.7% of participants reported having a trusted medical provider to provide COVID-19 vaccine information (n = 161), more than half of participants reported not having been encouraged by their medical provider to take the COVID-19 vaccine (n = 133, 57.6%). 3.3. Descriptive Statistics of Construct Variables Table 2 displays the descriptive statistics of the MTM constructs as the independent variables and the dependent variables of initiation and sustenance. Their significance was assessed among the participants who expressed hesitancy and did not express hesitancy toward taking the COVID-19 vaccine. Mean scores are reported in Table 2. When comparing mean scores of all variables between the vaccine-hesitant and non-vaccine-hesitant groups, mean values for all constructs measured significantly higher among the non-hesitant group for each variable, except for the participatory dialogue: disadvantages. Only with the participatory dialogue: disadvantages construct variable did results indicate a mean score that was higher among vaccine-hesitant individuals compared to non-vaccine individuals, indicating vaccine-hesitant individuals agree with more of the disadvantages of the COVID-19 vaccine over the advantages. Cronbach's alpha was reported for all independent variables, or the MTM constructs, among all participants to determine internal consistency reliability for each MTM construct. These values are reported in Table 2. Cronbach's alpha values that were 0.70 or higher were considered acceptable . All Cronbach's alpha values for each MTM construct variable were above 0.70, where values ranged from the lowest value of 0.773 for behavioral confidence to the highest value of 0.992 for emotional transformation. Because all Cronbach's alpha values were above 0.70, these values were deemed acceptable. Behavioral confidence had the lowest Cronbach's alpha value of 0.773, which is still deemed acceptable, but is a lower value compared to the other MTM constructs. 3.4. Zero-Order Correlation Matrix of Construct Variables The results of the zero-order correlation matrix to describe the bivariate associations between the MTM construct variables among vaccine-hesitant and non-vaccine-hesitant individuals are described in Table 3 for initiation and in Table 4 for sustenance. Based on Table 3 results, initiation was only statistically related to participatory dialogue: advantages-disadvantages (r = 0.691, p < 0.001) and behavioral confidence (r = 0.636, p < 0.001) for vaccine-hesitant individuals. The magnitude of associations between initiation, participatory dialogue, and behavioral confidence constructs were nearly similar. Among non-vaccine-hesitant individuals, initiation was statistically related to participatory dialogue: advantages-disadvantages (r = 0.606, p < 0.001), behavioral confidence (r = 0.762, p < 0.001), and changes in the physical environment (r = 0.587, p < 0.001). Initiation and behavioral confidence had the highest magnitude of association compared to the other MTM relationships among non-vaccine-hesitant individuals. Based on Table 4 results, sustenance was statistically related to emotional transformation (r = 0.530, p < 0.001), practice for change (r = 0.382, p < 0.001), and changes in the social environment (r = 0.248, p = 0.025) for vaccine-hesitant individuals. Similarly, among non-vaccine-hesitant individuals, sustenance was statistically related to emotional transformation (r = 0.816, p < 0.001), practice for change (r = 0.632, p < 0.001), and changes in the social environment (r = 0.658, p < 0.001). Among both vaccine-hesitant and non-vaccine-hesitant individuals, sustenance and emotional transformation had the highest magnitude of association compared to the other MTM relationships. 3.5. Hierarchical Multiple Regression among Construct Variables and Covariates The hierarchical multiple regression modeling results among both groups are displayed in Table 5 for the initiation of the COVID-19 vaccine and Table 6 for the sustenance of the COVID-19 vaccine. Individual characteristics of age, race, gender, education level, religion, income, and employment status were also included as covariates in the models due to their historical identification of having an effect on COVID-19 vaccination uptake. Among vaccine-hesitant individuals, participatory dialogue and behavioral confidence explained 63.0% of the variability in the initiation of COVID-19 vaccine acceptance behavior (adjusted R2 = 0.630, F(9,73) = 16.520, p < 0.001) (Table 5). After controlling for covariates, participatory dialogue (b = 0.113, p < 0.001) and behavioral confidence (b = 0.358, p < 0.001) displayed statistically significant associations with the initiation of COVID-19 vaccine acceptance. Additionally, one individual characteristic of income, specifically an income range of USD 25,000 to USD 49,999, displayed significant results as a predictor of initiation. This income range is associated with a 0.486 increase in initiation score (b = 0.486, p = 0.007) among vaccine-hesitant individuals when compared to other income ranges lower than USD 25,000 and higher than USD 49,999. Similar to vaccine-hesitant individuals, among non-vaccine-hesitant individuals, a hierarchical multiple regression model including all covariates, participatory dialogue, and behavioral confidence explained 63.2% of the variability in the initiation of COVID-19 vaccine acceptance behavior (adjusted R2 = 0.632, F(9,132) = 27.959, p < 0.001) (Table 5). After controlling for covariates, similar to the model of vaccine-hesitant individuals, participatory dialogue (b = 0.072, p < 0.001) and behavioral confidence (b = 0.206, p < 0.001) displayed significant associations with the initiation of COVID-19 vaccine acceptance. Another individual characteristic of age displayed statistically significant results as a predictor of initiation, whereas age was associated with a 0.017 increase in initiation score (b = 0.017, p = 0.003) among non-vaccine-hesitant individuals. In the examination of the sustenance component, a hierarchical multiple regression model including all covariates and emotional transformation explained 37.4% of the variability in the sustenance of COVID-19 vaccine acceptance behavior (adjusted R2 = 0.374, F(8,73) = 7.045, p < 0.001) (Table 6). After controlling for covariates, emotional transformation (b = 0.087, p < 0.001) displayed a statistically significant association with the sustenance of COVID-19 vaccine acceptance. Only the individual characteristic of age among the vaccine-hesitant individuals displayed significant results as a predictor of sustenance, whereas age was associated with a 0.019 decrease in sustenance score (b = -0.019, p = 0.004). Similar to vaccine-hesitant individuals, among non-vaccine-hesitant individuals, a hierarchical multiple regression model including all covariates and emotional transformation explained 66.4% of the variability in the sustenance of COVID-19 vaccine acceptance behavior (adjusted R2 = 0.664, F(8,133) = 35.801, p < 0.001) (Table 6). After controlling for covariates, emotional transformation (b = 0.177, p < 0.001) displayed a statistically significant association with the sustenance of COVID-19 vaccine acceptance. No other individual characteristic showed significant associations for sustenance among non-vaccine-hesitant individuals. 4. Discussion 4.1. Interpretation of Findings The COVID-19 vaccine was identified by participants as an effective public health tool to slow the spread of disease throughout the community. However, of the 231 respondents, 36.4% (n = 84) of individuals expressed hesitancy to take the COVID-19 vaccine. This finding was similar to that of various studies that found approximately a third of the Hispanic population is very hesitant to get vaccinated . A response rate of 36.4% of our sample population expressing vaccine hesitancy indicates that there is a strong need for public health professionals to encourage COVID-19 vaccine uptake among vaccine-hesitant Hispanics and Latinxs to ensure we are able to reach a herd immunity threshold that will slow the spread of disease and put an end to the pandemic. Our study results provide further support that two of the three MTM initiation constructs, specifically participatory dialogue and behavioral confidence, were shown to be significant in explaining the intent of initiating the COVID-19 vaccine for both vaccine-hesitant and non-vaccine-hesitant individuals. As presented by the results in Table 2, the mean score for participatory dialogue among vaccine-hesitant individuals was -6.071 +- 4.834. On the contrary, the mean score for participatory dialogue among non-vaccine-hesitant individuals was +2.421 +- 4.785, indicating that these participants believed more in the advantages of the COVID-19 vaccine and less in the disadvantages. These lower mean scores are also supported by previous survey results presented by Wanin that only 34% of Latinx participants trusted the COVID-19 vaccine's safety and nearly 40% trusted the COVID-19 vaccine's effectiveness . With the introduction of a novel COVID-19 vaccine, these mean scores show that there are still some hesitancies about the advantages among both vaccine-hesitant and non-vaccine-hesitant individuals; however, these mean scores highlight that there are more hesitancies among the vaccine-hesitant individuals. They further highlight a need to focus on the advantages of the COVID-19 vaccine when addressing this particular construct among the Hispanic and Latinx populations. Since the COVID-19 vaccine was available free to all, the third MTM construct of changes in the physical environment may not have played a significant role in our study. Perhaps in the future, when COVID-19 boosters are not available for free, this construct may play a greater role. Among both the vaccine-hesitant and non-vaccine-hesitant groups, behavioral confidence was highlighted as an important construct in predicting the initiation of COVID-19 vaccine acceptance. According to Reverby, there is a lack of confidence and trust in vaccine availability, side effects, and studies performed on the COVID-19 vaccine because there are myths and misconceptions that the vaccine is used to harm or track people, which can cause more fear than confidence . Behavioral confidence then highlights the need to build trust within the Hispanic and Latinx communities when encouraging vaccine acceptance behaviors. Ensuring Hispanic and Latinx populations receive more proper education and information from credible sources to build confidence in receiving the vaccine will help to increase vaccination uptake. Only one of the three MTM sustenance constructs, specifically emotional transformation, was shown to be significant in explaining the intent of sustaining the COVID-19 vaccine for both vaccine-hesitant and non-vaccine-hesitant individuals. Similar to the study by Salgado de Snyder et al., the construct of emotional transformation could easily affect the sustenance of receiving COVID-19 vaccines and/or a routine vaccine due to fear or lack of ability to overcome these challenges . Among the Mexican men who were surveyed, a fear of needles or side effects, being lazy and irresponsible, not caring or needing to get vaccinated, and inconvenience or a lack of time to get vaccinated due to conflicting work schedules were described . Additionally, Hamel et al. and Dawson et al. also highlighted challenges to not receiving a second dose of the COVID-19 vaccine that also included the cost of the vaccine and immigration status . This further supports a need to address solutions to overcoming these challenges to getting vaccinated, which may include setting up vaccination clinics at various locations convenient to the individual or advocating for policy changes that will allow for employees to take paid time out of their work schedule to get vaccinated and recover if side effects do take a toll on their ability to continue working. Right now, long-term behavior change regarding the COVID-19 vaccine is not apparent. While the two constructs of sustenance, namely practice for change and change in the social environment, were not found to be significant in the present study, in the future, more regular boosters may be required, thus necessitating the importance of these two sustenance constructs. The time period in which this study was conducted was rather limited, and the other two constructs of MTM (practice for change and changes in the social environment) may play a greater role if regular boosters are necessary for protection against COVID-19. Nonetheless, these findings can be used for future research when planning MTM-based implementation strategies to increase COVID-19 vaccine acceptance behavior specifically for Hispanic and Latinx populations. Similar to various studies, the covariate of age was shown as a significant predictor of COVID-19 vaccine acceptance behavior, particularly for the initiation of the vaccine among non-vaccine-hesitant individuals and the sustenance of the vaccine among vaccine-hesitant individuals. This finding is further supported by results from the December 2020 Kaiser Family Foundation COVID-19 Vaccine Monitor that found Hispanic adults that were older than 50 years had more trust in the vaccine and were more likely to take the vaccine compared to their younger counterparts, who reported more vaccine hesitancy and lack of trust in government officials . Younger adults may not continue with follow-up of the second dose or booster dose. It may be that younger age groups believe they are healthy and do not need the vaccine. Income was also shown as a significant predictor of initiation of the COVID-19 vaccine among vaccine-hesitant participants. This displayed that as one gets employed and income increases, there is more of an increase in individuals initiating the COVID-19 vaccine series. One explanation for this is that working individuals do not want to get sick and be forced to take the day off, losing out on pay. Getting the COVID-19 vaccine lowers one's chance of getting seriously ill and hospitalized from COVID-19, allowing one to keep working to make their income. 4.2. Implications for Practice Based on study results, it is evident there is a need for theory-based interventions and messaging to address vaccine hesitancy and barriers that affect COVID-19 vaccine acceptance among the Hispanic and Latinx populations. As described by Salmon et al., trusted voices within their communities provide a heavy influence on decision-making among Hispanic and Latinx communities . Therefore, hosting group interventions that are led by trusted community members and/or leaders in public health in trusted locations such as a school or community center will encourage participation in the study. It may also be beneficial to employ non-U.S. citizens to conduct research or lead intervention strategies to gain trust among the non-U.S. citizen communities. Many of the Hispanic and Latinx communities have had negative historical experiences with racism and medical exclusions, therefore emphasizing the need for a trusted resource to lead the intervention. To influence the MTM constructs of participatory dialogue, behavioral confidence, and emotional transformation, small group and one-on-one discussions may be beneficial to addressing concerns, providing demonstrations for researching credible sources of knowledge, and motivating participants to overcome challenges to getting vaccinated. These interventions should also be available in the Spanish language, whether it be a Spanish speaker or with Spanish-translated resources to ensure that communication is continuous and in the participant's native language. Additionally, using a multimodal approach, such as using technology and social media, would help to continue the discussions started in the intervention and to address additional concerns participants may have. Based on our results, the use of a theory-based intervention is critical to ensure the study uses a structured model that has been extensively studied and proven to be predictive of the health behavior we are trying to change. By using a theory-based approach, we have proof that these constructs are predictive of a health behavior change. 4.3. Strengths of the Study To our knowledge, this is the first study that utilized a theory-based survey instrument to assess COVID-19 vaccine acceptance behavior among the Hispanic and Latinx populations. This study design was also very beneficial in providing relatively quick results, was particularly low cost, and provided the ability to easily evaluate this particular population in a short amount of time. The survey was written in English, then translated into Spanish and retranslated back to English to ensure the translation was an accurate reflection of the same verbiage of questions. 4.4. Limitations This study had some limitations. The study utilized a cross-sectional study which may not determine if an association equals causation or the directionality of the outcome. Additionally, as with any self-reported survey study design, one limitation was response bias. Recruitment bias may have occurred due to the difficulty of obtaining participants early in the recruitment stages. Another limitation was that the survey instrument had a Flesch Reading Ease score of 52.3 and a Flesch-Kincaid Grade Level of 9.9, which made the survey fairly difficult to read. One recommendation for future research would be to change the survey instrument by editing the survey for a lower readability score and lower grade level score to ensure more people are able to understand and take the survey, especially if participants are not native English speakers. Upon editing, the survey instrument can also be further edited to assess the prediction of other routine immunizations, such as influenza; measles, mumps, and rubella (MMR); and human papillomavirus (HPV). The sample collected contained responses from predominantly females (69%) and people of Mexican identity (63.2%), all of whom resided in Nevada. This limits the generalizability of the study findings to all genders and other Hispanic/Latinx identities outside of Nevada. Another quantitative study design that would help to generalize the study's findings could be conducted using a larger population sample; however, a qualitative study design utilizing interviews and focus groups may help to gain a deeper understanding of the participatory dialogue and behavioral confidence that would affect the initiation of the vaccine, as well as the emotional transformation of the sustenance of the vaccine. Despite the limitations, this study provided a foundation for theory-based research among the Hispanic and Latinx communities to understand what factors predict COVID-19 vaccine acceptance behaviors, and it can be tailored in future research and interventions. 5. Conclusions The COVID-19 pandemic has had a significantly disproportionate negative impact on the Hispanic and Latinx populations. Vaccine hesitancy and access to vaccines have prevented the rapid uptake of the COVID-19 vaccine. One of the MTM constructs, emotional transformation for sustenance, must be influenced by solutions to overcoming the challenges in getting vaccinated, as this plays a large factor in why people who may be accepting of the vaccine ultimately choose not to receive the vaccine. Addressing solutions that include advocating for policy change may be the most effective, including policy changes that will allow for employees to take paid time out of their work schedule to get vaccinated and recover if side effects take a toll on their ability to continue working. This may be particularly challenging, especially for ethnic minorities who may feel like their voices are not heard; however, these policies may help to provide more equitable access to vaccines and overall increase trust in policy makers. This study aimed to assess the MTM's ability to predict COVID-19 vaccine acceptance behavior among the Hispanic and Latinx populations in Nevada. Results from this study provide evidence that the MTM is a useful tool in predicting COVID-19 vaccine acceptance behavior among Hispanics and Latinxs in Nevada and can be used to influence vaccine uptake behaviors. Interventions and messaging to encourage vaccine uptake are crucial to address COVID-19 vaccine hesitancy to promote its rapid uptake, and the use of MTM can be effective in this development to ensure Hispanics and Latinxs are protected against the spread of COVID-19. Author Contributions Conceptualization, T.M.N. and M.S.; methodology, T.M.N. and M.S.; software, T.M.N.; validation, M.S., B.L., E.M. and C.-L.D.; formal analysis, T.M.N.; investigation, T.M.N.; resources, T.M.N.; data curation, T.M.N.; writing--original draft preparation, T.M.N.; writing--review and editing, M.S., B.L., E.M. and C.-L.D.; visualization, T.M.N.; supervision, M.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study protocol was approved by the Institutional Review Board (or Ethics Committee) of the University of Nevada, Las Vegas (protocol code UNLV-2022-192 approved on 3 May 2022 and modification approved on 17 June 2022). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data are available on request with the permission of T.N. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Constructs in the initiation of health behavior change in the Multi-Theory Model of health behavior change. Figure 2 Constructs in the sustenance of health behavior change in the Multi-Theory Model of health behavior change. healthcare-11-00688-t001_Table 1 Table 1 Descriptive characteristics of the study sample (n = 231). Characteristic M (SD) n (%) Age (in years) 37.83 (14.141) Gender Male 69 (29.9) Female 160 (69.3) Other 0 (0.0) Hispanic/Latinx Identity Argentinian 5 (2.2) Bolivian 0 (0.0) Chilean 2 (0.9) Colombian 4 (1.7) Costa Rican 2 (0.9) Cuban 7 (3.0) Dominican 2 (0.9) Ecuadorian 1 (0.4) Guatemalan 4 (1.7) Honduran 4 (1.7) Mexican 146 (63.2) Nicaraguan 2 (0.9) Panamanian 1 (0.4) Paraguayan 0 (0.0) Peruvian 1 (0.4) Puerto Rican 18 (7.8) Salvadoran 4 (1.7) Uruguayan 0 (0.0) Venezuelan 0 (0.0) Other Central American 0 (0.0) Other South American 3 (1.3) All other Hispanic or Latino 19 (8.2) Prefer not to answer 4 (1.7) Highest level of education Less than high school 5 (2.2) High school 75 (32.5) Some college 94 (40.7) Bachelor's degree or higher 53 (22.9) Religion Buddhism 2 (0.9) Catholicism 79 (34.2) Judaism 4 (1.7) Mormonism 3 (1.3) Orthodox Christian 7 (3.0) Other Christianity 40 (16.9) Protestant 8 (3.5) Unaffiliated with any religion 69 (29.9) Other 17 (7.4) Annual individual income USD 0 to USD 9999 15 (6.5) USD 10,000 to USD 24,999 33 (14.3) USD 25,000 to USD 49,999 85 (36.8) USD 50,000 to USD 74,999 53 (22.9) USD 75,000 to USD 99,999 28 (12.1) USD 100,000 to USD 149,999 14 (6.1) Over USD 150,000 1 (0.4) Current employment status Employed 138 (59.7) Self-employed 26 (11.3) Laid-off/Furloughed 0 (0.0) Retired 12 (5.2) Homemaker 20 (8.7) Unreported employment 2 (0.9) Unemployed 27 (11.7) Other 4 (1.7) Number of people living in household 3.22 (1.567) Marital status Single 84 (36.4) Married 74 (32.0) Divorced 31 (13.4) Widowed 1 (0.4) Separate 5 (2.2) Never married 6 (2.6) In a civil union or registered domestic partnership 11 (4.8) A member of an unmarried couple 17 (7.4) Possesses health insurance Yes 182 (78.8) No 47 (20.3) Political affiliation (optional to answer) Republican 46 (19.9) Democratic 82 (35.5) Independent 59 (25.5) Other 17 (7.4) Prefer not to answer 21 (9.1) Current citizenship status (optional to answer) Is a citizen of the United States 206 (89.2) Not a citizen of the United States 12 (5.2) Prefer not to answer 6 (2.6) Expresses hesitancy to taking COVID-19 vaccine Yes 84 (36.4) No 147 (63.6) Received at least one dose of the COVID-19 vaccine Yes 136 (58.9) No 95 (41.1) Completed series of COVID-19 vaccine Yes 127 (55.0) No 104 (45.0) Has a trusted provider provided COVID-19 vaccine information infmation Yes 161 (69.7) No 68 (29.4) Has been encouraged by a medical provider to take the COVID-19 vaccine Yes 96 (41.6) No 133 (57.6) healthcare-11-00688-t002_Table 2 Table 2 Descriptive characteristics of study variables (n = 231). Variable Vaccine-Hesitant Individuals (n = 84) Vaccine Non-Hesitant Individuals (n = 147) All Participants (n = 231) Possible Range Observed Range Mean (SD) Possible Range Observed Range Mean (SD) Cronbach's Alpha p-Value Initiation 0-4 0-4 0.843 (1.1841) 0-4 0-4 3.056 (1.378) <0.001 Participatory dialogue: advantages 0-12 0-9 3.083 (2.617) 0-12 0-12 7.545 (3.440) 0.960 <0.001 Participatory dialogue: disadvantages 0-12 2-12 9.155 (2.659) 0-12 0-12 5.124 (2.850) 0.841 0.002 Participatory dialogue: advantages-disadvantages -12-+12 -12-+7 -6.071 (4.834) -12-+12 -12-+12 2.421 (4.785) <0.001 Behavioral confidence 0-12 0-9 4.361 (1.664) 0-12 0-12 8.570 (3.351) 0.773 <0.001 Changes in the physical environment 0-20 0-20 12.928 (5.055) 0-20 0-20 14.278 (5.117) 0.870 <0.001 Sustenance 0-4 0-4 0.634 (0.988) 0-4 0-4 2.722 (1.465) <0.001 Emotional transformation 0-24 0-23 7.277 (5.315) 0-24 0-24 16.133 (7.0653) 0.992 <0.001 Practice for change 0-20 0-20 7.634 (6.093) 0-20 0-20 13.090 (5.390) 0.901 <0.001 Changes in the social environment 0-12 0-12 5.061 (3.923) 0-12 0-12 8.069 (3.363) 0.907 <0.001 Estimates attained for significance testing are based on independent t-tests. healthcare-11-00688-t003_Table 3 Table 3 Zero-order correlation matrix of study variables for initiation of COVID-19 vaccination behavior. Vaccine-Hesitant Individuals (n = 84) Construct Initiation Participatory Dialogue Behavioral Confidence Changes in the Physical Environment 1. Initiation - 0.691 ** (p < 0.001) 0.636 ** (p < 0.001) -0.165 (p = 0.136) 2. Participatory dialogue: advantages-disadvantages - 0.411 ** (p < 0.001) -0.320 ** (p = 0.003) 3. Behavioral confidence - 0.202 (p = 0.067) 4. Changes in the physical environment - Vaccine Non-Hesitant Individuals (n = 147) Construct Initiation Participatory Dialogue Behavioral Confidence Changes in the Physical Environment 1. Initiation - 0.606 ** (p < 0.001) 0.762 ** (p < 0.001) 0.587 ** (p < 0.001) 2. Participatory dialogue advantages-disadvantages - 0.568 ** (p < 0.001) 0.361 ** (p < 0.001) 3. Behavioral confidence - 0.696 ** (p < 0.001) 4. Changes in the physical environment - ** Correlation is significant at the 0.01 level (2-tailed). healthcare-11-00688-t004_Table 4 Table 4 Zero-order correlation matrix of study variables for the sustenance of COVID-19 vaccination behavior. Vaccine-Hesitant Individuals (n = 84) Construct Sustenance Emotional Transformation Practice for Change Changes in the Social Environment 1. Sustenance - 0.530 ** (p < 0.001) 0.382 ** (p < 0.001) 0.248 * (p = 0.025) 2. Emotional transformation - 0.541 ** (p < 0.001) 0.327 ** (p = 0.003) 3. Practice for change - 0.687 ** (p < 0.001) 4. Changes in the social environment - Vaccine Non-Hesitant Individuals (n = 147) Construct Sustenance Emotional Transformation Practice for Change Changes in the Social Environment 1. Sustenance - 0.816 ** (p < 0.001) 0.632 ** (p < 0.001) 0.658 ** (p < 0.001) 2. Emotional transformation - 0.789 ** (p < 0.001) 0.807 ** (p < 0.001) 3. Practice for change - 0.859 ** (p < 0.001) 4. Changes in the social environment - ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). healthcare-11-00688-t005_Table 5 Table 5 Multiple regression models for initiation of COVID-19 vaccination among hesitant and non-hesitant participants. Hesitant Participants b S.E. b p LBCI UBCI Age 0.003 0.006 0.035 0.623 -0.009 0.015 Mexican (reference: non-Mexican) -0.040 0.164 -0.017 0.807 -0.367 0.287 Female (reference: male) 0.129 0.184 0.051 0.485 -0.238 0.496 Some college (reference: high school education or less, or bachelor's degree and higher) -0.042 0.172 -0.018 0.809 -0.385 0.302 Catholicism (reference: non-Catholicism) -0.004 0.192 -0.001 0.985 -0.387 0.379 USD 25,000 to USD 49,999 (reference: lower and higher income than USD 25,000 to USD 49,999) 0.486 0.175 0.193 0.007 0.136 0.835 Employed (reference: other employment or non-employed) 0.099 0.165 0.042 0.550 -0.230 0.428 Participatory dialogue advantages-disadvantages 0.113 0.021 0.461 <0.001 0.071 0.155 Behavioral confidence 0.358 0.059 0.503 <0.001 0.241 0.475 Changes in the physical environment -0.032 0.019 -0.135 0.099 -0.069 0.006 Model statistics including predictors of covariates, participatory dialogue, and behavioral confidence: R2 = 0.671, adjusted R2 = 0.630, F(9,73) = 16.520, p < 0.001 Non-Hesitant Participants b S.E. B p LBCI UBCI Age 0.017 0.006 0.172 0.003 0.006 0.028 Mexican (reference: non-Mexican) -0.003 0.159 -0.001 0.983 -0.318 0.311 Female (reference: male) 0.093 0.159 0.031 0.557 -0.220 0.407 Some college (reference: high school education or less, or bachelor's degree and higher) -0.017 0.159 -0.006 0.915 -0.330 0.297 Catholicism (reference: non-Catholicism) -0.057 0.152 -0.020 0.707 -0.357 0.243 USD 25,000 to USD 49,999 (reference: lower and higher income than USD 25,000 to USD 49,999) 0.124 0.149 0.044 0.408 -0.171 0.419 Employed (reference: other employment or non-employed) 0.175 0.156 0.062 0.263 -0.133 0.483 Participatory dialogue advantages-disadvantages 0.072 0.018 0.249 <0.001 0.035 0.108 Behavioral confidence 0.206 0.034 0.502 <0.001 0.139 0.274 Changes in the physical environment 0.031 0.019 0.116 0.109 -0.007 0.069 Model statistics including predictors of covariates, participatory dialogue, and behavioral confidence: R2 = 0.656, adjusted R2 = 0.632, F(9,132) = 27.959, p < 0.001 S.E. = standard error of the estimate; LBCI = lower bound of the 95% confidence interval; UBCI = upper bound of the 95% confidence interval. healthcare-11-00688-t006_Table 6 Table 6 Multiple regression models for the sustenance of COVID-19 vaccination among hesitant and non-hesitant participants. Hesitant Participants b S.E. b p LBCI UBCI Age -0.019 0.006 -0.275 0.004 -0.032 -0.006 Mexican (reference: non-Mexican) 0.129 0.185 0.066 0.487 -0.239 0.497 Female (reference: male) -0.212 0.209 -0.100 0.314 -0.628 0.205 Some college (reference: high school education or less, or bachelor's degree and higher) -0.269 0.181 -0.137 0.140 -0.630 0.091 Catholicism (reference: non-Catholicism) 0.097 0.211 0.045 0.646 -0.323 0.518 USD 25,000 to USD 49,999 (reference: lower and higher income than USD 25,000 to USD 49,999) -0.115 0.194 -0.055 0.554 -0.501 0.271 Employed (reference: other employment or non-employed) 0.079 0.189 0.040 0.679 -0.299 0.456 Emotional transformation 0.087 0.020 0.470 <0.001 0.046 0.127 Practice for change 0.018 0.023 0.114 0.416 -0.027 0.063 Changes in the social environment -0.004 0.032 -0.017 0.890 -0.067 0.058 Model statistics including predictors of covariates and emotional transformation: R2 = 0.436, adjusted R2 = 0.374, F(8,73) = 7.045, p < 0.001 Non-Hesitant Participants b S.E. b p LBCI UBCI Age 0.006 0.006 0.061 0.294 -0.006 0.018 Mexican (reference: non-Mexican) -0.157 0.164 -0.048 0.341 -0.481 0.167 Female (reference: male) -0.111 0.162 -0.035 0.492 -0.432 0.209 Some college (reference: high school education or less, or bachelor's degree and higher) 0.089 0.167 0.030 0.594 -0.241 0.419 Catholicism (reference: non-Catholicism) 0.146 0.157 0.048 0.356 -0.166 0.457 USD 25,000 to USD 49,999 (reference: lower and higher income than USD 25,000 to USD 49,999) 0.212 0.153 0.071 0.166 -0.090 0.515 Employed (reference: other employment or non-employed) 0.129 0.160 0.043 0.421 -0.187 0.446 Emotional transformation 0.177 0.019 0.850 <0.001 0.139 0.215 Practice for change -0.015 0.028 -0.054 0.606 -0.070 0.041 Changes in the social environment 0.000 0.048 -0.001 0.994 -0.096 0.095 Model statistics including predictors of covariates and emotional transformation: R2 = 0.683, adjusted R2 = 0.664, F(8,133) = 35.801, p =< 0.001 S.E. = standard error of the estimate; LBCI = lower bound of the 95% confidence interval; UBCI = upper bound of the 95% confidence interval. 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PMC10000402 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050690 healthcare-11-00690 Article Effects of Meteo-Climatic Factors on Hospital Admissions for Cardiovascular Diseases in the City of Bari, Southern Italy Telesca Vito 1* Castronuovo Gianfranco 1 Favia Gianfranco 2 Marranchelli Cristina 3 Pizzulli Vito Alberto 1 Ragosta Maria 1 Dettori Marco Academic Editor 1 School of Engineering, University of Basilicata, Viale dell'Ateneo Lucano 10, 85100 Potenza, Italy 2 Interdisciplinary of Medicine, School of Medicine, University of Bari, Piazza Giulio Cesare 11, 70124 Bari, Italy 3 Freelance Engineer, Via Mazzini 54, 75025 Policoro, Italy * Correspondence: [email protected] 26 2 2023 3 2023 11 5 69019 12 2022 20 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 objective of this study was to determine the relationship between weather conditions and hospital admissions for cardiovascular diseases (CVD). The analysed data of CVD hospital admissions were part of the database of the Policlinico Giovanni XXIII of Bari (southern Italy) within a reference period of 4 years (2013-2016). CVD hospital admissions have been aggregated with daily meteorological recordings for the reference time interval. The decomposition of the time series allowed us to filter trend components; consequently, the non-linear exposure-response relationship between hospitalizations and meteo-climatic parameters was modelled with the application of a Distributed Lag Non-linear model (DLNM) without smoothing functions. The relevance of each meteorological variable in the simulation process was determined by means of machine learning feature importance technique. The study employed a Random Forest algorithm to identify the most representative features and their respective importance in predicting the phenomenon. As a result of the process, the mean temperature, maximum temperature, apparent temperature, and relative humidity have been determined to be the most suitable meteorological variables as the best variables for the process simulation. The study examined daily admissions to emergency rooms for cardiovascular diseases. Using a predictive analysis of the time series, an increase in the relative risk associated with colder temperatures was found between 8.3 degC and 10.3 degC. This increase occurred instantly and significantly 0-1 days after the event. The increase in hospitalizations for CVD has been shown to be correlated to high temperatures above 28.6 degC for lag day 5. hospital admission cardiovascular diseases temperature distributed lag non-linear model time series decomposition feature importance random forest MUR-Italian Ministry of Education, University, and ResearchARS01_000405 This research was funded in the framework of the project 'OT4CLIMA', Funder: MUR-Italian Ministry of Education, University, and Research (D.D. 2261 6.9.2018, PON R&I 2014-2020 and FSC). ARS01_000405. pmc1. Introduction Climate changes and climate seasonal variability affect human health. Meteorological factors, such as temperature, relative humidity, and atmospheric pressure, determine several negative health outcomes. Exploring relations between health and weather conditions at a local scale may allow us to measure climate change impacts on the population. Several studies show the correlation existing between ambient temperature and mortality or morbidity . Since the last century, high temperatures and heat waves have been associated with excess deaths in many US cities and were recognized as important factors determining deaths, chronic bronchitis, pneumonia, ischemic heart disease, and cerebrovascular disease in England and Wales . Increased mortality associated with high average temperatures was found in Seoul, Beijing, Tokyo, and Taipei in Asia . Temperature and mortality have a complex relationship, influenced by geographic, climatic, and demographic factors . The vulnerability of populations to temperatures can be influenced by social, economic, demographic, and infrastructural variables and, for this reason, developing countries are more sensitive to climate change . For the African continent, a significant correlation between temperature increase and an increase in mortality and morbidity for cardiovascular diseases was shown . Even on the European continent, the implications of climate change on human healthcare were addressed . The project "Assessment and prevention of acute health effects of weather conditions in Europe" (PHEWE project) was an attempt to examine the influence of temperature on various mortality and morbidity outcomes utilising a standardised approach . The project analysed acute health impacts of highly variable climatic conditions, both during hot and cold seasons in numerous European countries. It was shown that, in the short term, temperature and relative humidity were strongly correlated with hospital admissions and mortality . Although the correlation between high temperatures and mortality is clear, there is less evidence of the impact of high temperatures on hospitalisation around the world . Several studies have shown that high temperatures are associated with increased hospitalisation rates for both cardiovascular and respiratory diseases in several cities in the United States of America . The short-term effect of temperature on respiratory diseases was evident also for children . The potential influence of the environment on the infarct is underlined, analogous to considerations regarding the increase in stroke risk. At lowering temperatures, the percentage of attacks would increase by 195% in winter and 10% in spring. In this case the cold would favour the formation of blood clots with a consequent increase in risk in patients suffering from fibrillation. Investigation into the relationships between environment and pathologies could help in implementing preventive measures such as anticoagulant therapies and a reduction of exposure to cold. The possibility of predicting events linked to cardiovascular diseases, combined with greater attention to lifestyles and the living environment, suggests a benefit to deeply investigating the effects of the environment and climate on the risk of cardiovascular diseases through ad hoc therapeutic strategies. Moreover, it is possible to reduce the economic costs related to these events. Rising temperatures and the concentration of pollutants in the atmosphere also have repercussions on respiratory diseases. Climate change acts by leading to an increase in ozone and fine particulate levels, generating an increase in terms of morbidity and mortality. Heat mainly may affect a pool of fragile individuals in which death or the onset of the disease is anticipated by a short period of time . The mortality rate or morbidity is influenced not only by the current day's temperature but also by the temperature of previous days . Distributed lag models have been applied to explore the delayed effect of temperature on mortality . To overcome the strong correlation among daily temperatures on short periods, constrained distributed lag structures are used in time series regressions . Estimates are constrained by the use of smoothing methods, such as natural cubic splines or polynomials, but both unbound and constrained distributed lag models presume a linear relationship between temperature and mortality, making them weak for well characterising the influence of temperature on mortality. Distributed lag non-linear model (DLNM) has been developed to simultaneously estimate the non-linear and delayed effects of temperature (or air pollution) on mortality (or morbidity). Using this model, a three-dimensional plot allows us to show the relative risks both for temperature and for delays . Cardiovascular disease (CVD) is the leading cause of mortality, morbidity, and disability in Europe and specifically in Italy, requiring greater attention to cardiovascular risk factors in health planning and resource allocation . For this reason, we have focused our attention on these specific pathologies in order to identify meteo-climatic parameters strongly correlated to the incidence of daily hospitalizations. In this context we apply a methodological procedure for analysing and modelling the relationship between meteo-climatic factors and the daily hospitalizations for CVD in the city of Bari, southern Italy. The purpose is to identify the meteorological parameters that drive admissions to the emergency room for cardiovascular diseases. Furthermore, the relative risk of the onset of this type of pathology, concerning all the selected meteorological variables, will be analysed. In this way, it will be possible also to improve the management of access flows to the emergency room. 2. Materials and Methods 2.1. Study Area and Data Collection--Hospitalisation Data and Preliminary Statistical Analysis Hospitalisation data analysis involves daily accesses to the emergency room in the Bari Policlinico "Giovanni XXIII" for the 2013-2016 reference four-year period. Bari is the ninth Italian municipality in terms of population size, the third most populous municipality in southern Italy after Naples and Palermo with almost 300,000 inhabitants. The database of daily admissions in the emergency room was formatted according to the compilation scheme: first name; surname; sex; date of birth; birthplace; place of residence; citizenship; day, month, year of acceptance; acceptance time; main problem; day, month, year of discharge; discharge procedure; observation methods; hospitalisation department. Particularly, pathology and/or symptomatology was classified on the basis of 33 codes (Table 1). In Table 2 and in Figure 1, for each year, the number of admissions, divided for genders, is summarised. In particular, for the year 2013, 75,927 entries into the emergency room were counted, of which, 40,265 were male patients, 35,032 were female patients, and 630 data cases were missing inherent in sex. For the year 2014, a total of 80,690 admissions were counted, of which, there were 42,554 referring to the male gender, 37,127 female, and 1009 cases of missing data. For the year 2015, the total number of admissions to the emergency room amounts to 75,334, of which, 40,091 were men, 34,327 were women, and 916 were cases of missing data. For the year 2016, 71,550 visits to the emergency room were registered, of which, 38,007 were male patients, 32,914 were female patients, and 629 were cases of missing data. For this study, only the data associated with cardiovascular pathologies were selected and examined. According to the ESC (European Society of Cardiology), the high rate of deaths (in Europe there are about 4 million a year) caused by cardiovascular diseases and the correlation of these with decreasing temperatures are strongly evident. The ESC stresses that cardiovascular disorders are the leading cause of death in all European countries, especially for women; moreover, congenital heart disease alone is the leading cause of death below 65 years. Canadian and Taiwanese studies have shown that each 10 degC reduction in atmospheric temperature corresponds to an increase of 7% in the myocardial infarction (sudden rupture of a coronary artery plate) and that a reduction of 5 degC corresponds to an increase equal to 13% in the risk of thrombo-embolic fibrillation stroke. In the case of the heart attack, the study was able to identify the possibility of preceding the event 2 days in advance by observing the temperature trend, which, if they remain below 0 degC in the daytime hours, the risk of heart attack increases. Therefore, considering cardiovascular diseases, we select only the admissions with the codes shown in Table 3. For each year, the distribution of cardio-vascular admissions in the emergency room is shown in Table 4 and in Figure 2. In Figure 3 the frequencies of different codes in CVD are shown. Furthermore, for epidemiological purposes, it is important to separate data admission on the basis of age of the patient . As shown in Figure 4, the 40-54 age group has the highest number of hospital admissions. Typically, the over-60-years and the over-70-years are the categories most affected by cardiovascular diseases, both for the severity of the disease and for the greater risk of complications caused by the presence of other diseases. In this case, instead, the highest incidence is observed in more young people. 2.2. Meteo-Climatic Parameters and Preliminary Statistical Analysis The meteo-climatic data for the investigated period were collected by ARPA of the Apulia region. For the monitoring activities, ARPA manages a Telemetric Network, with five automatic stations. Each automatic meteorological station includes the following: an "ECO2" series acquisition unit with 8 analogue inputs, which controls the system and provides for the acquisition, pre-processing, and storage of data; a software package (Ecodata32) dedicated to the management of the survey stations and able to dialogue with the stations and to manage and process the data; sensors consisting of electronic or mechanical devices that measure a specific meteorological parameter. The data are recorded with a half-hourly frequency and are always expressed in solar time. In this study, the meteo-climatic parameters taken into account are as follows: average daily minimum temperature (Tmin); average maximum daily temperature (Tmax); average temperature (Tmean); temperature at the dew point (Tdewp); apparent or perceived temperature (Tapp); atmospheric pressure (P_atm); average relative humidity (RH); and average absolute humidity (AH). In Table 6, the descriptive statistics for each variable are summarised. 2.3. Methodology In order to determine the meteorological variables that most influence admissions to the emergency room for cardiovascular disease and to calculate the related relative risk, the methodology illustrated in Figure 5 was adopted. It is composed of two phases: Phase 1: correlation analysis and Phase 2: application of Machine Learning feature importance and DLNM model. In Phase 1, the pair dependence between meteorological variables and admissions to the emergency room for cardiovascular diseases is analysed with means of correlation analysis (see Section 3.1). If the Pearson coefficient r is higher or equal than a prefixed threshold (0.45 in this case) and the p-value is lower than 0.01, Phase 2 will be carried out. Conversely, the trend components are extracted using the Seasonal and Trend decomposition via Loess (STL) (see Section 3.2), and Phase 2 will be carried out using trend components data. In Phase 2, a feature importance procedure is applied (with artificial intelligence techniques, see Section 3.3) to determine the most significant meteorological variables, and then the DLNM model is applied to estimate the related relative risk (see Section 3.4). 3. Results 3.1. Correlation Analysis Correlation analysis shows how the features are related to each other or with the target variable. Positive correlation indicates that an increase in one feature's value increases the value of the target variable, whereas negative correlation means that an increase in one feature's value reduces the value of the target variable. A correlation matrix was used calculating the Pearson Correlation Coefficient r, for each pair of quantitative features. The Pearson's correlation between any two variables x,y is:rxy=i=1n(xi-x_)(yi-y_)i=1n(xi-x_)2i=1n(yi-y_)2 where:n is the sample size; xi, yi are the individual sample points and x_, y_ are the sample means. Each cell of the matrix receives a single number from -1 to +1; therefore, the table shows the strength of the (linear) relationship between any two features. The correlation analysis is also based on the p-value. In null hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the results actually observed, under the assumption that the null hypothesis is correct. A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis. This statistical measure defines the reliability of the values obtained from the correlation, as it helps to understand if the results of an experiment fall within the normal range of values for the event under observation. Only the p-value values less than 0,01 and r greater than or equal to 0.45 were considered for the hypothesis of acceptability for the set of input features. In Table 7, the correlation matrix among meteorological parameters and CVD admissions is shown. We note that (last column of the Table 7), for CVD, all the r-values satisfy the p-test. Moreover, we note that for all the pairs, CVD admission and meteorological parameters r-values are lower than 0.45, the fixed threshold. 3.2. Decomposition Model The Seasonal and Trend decomposition using Loess (STL) is a filtering procedure for decomposing a time series into seasonal, trend, and remainder components . The trend component is the low frequency variation in the data together with the nonstationary, long-term changes level. The seasonal component is the variation in the data at or near the seasonal frequency. The remainder component is the remaining variation in the data beyond that in the seasonal and trend components. Suppose the data, the trend component, the seasonal component, and the remainder component are denoted by Yv, Tv, Sv, and Rv, respectively, for v = 1 to N; then:Yv=Tv+Sv+Rv The STL model uses robust local-weighted regression as a smoothing method for time series decomposition. When estimating the value of a response variable, a subset of data is selected from the vicinity of the predicted variable, and then linear or quadratic regression is performed on the subset by using the weighted least squares method to reduce the weight of the value far from the estimated point. Finally, the value of the response variable can be estimated by the local regression model. This point-by-point method is generally used to fit the whole curve to decompose the time series accurately. The aim was to identify a simple method to verify that signal decomposition would lead to a noticeable improvement in results and allow the use of ML techniques for simulating these processes. This was accomplished by verifying the validity of STL and evaluating the stationarity of the data series using the Dickey-Fuller method. In Table 8, we compare the absolute values of r calculated among CVD admissions and meteorological parameters before and after the application of the decomposition model. As you can note, the variables Tmean, Tmax, Tapp, and RH show r-values greater than the threshold value 0.45, and only for atmospheric pressure (P_atm) is the p-value test not verified; therefore, it will be removed from the following analysis. 3.3. Application of Feature Importance Building a ranking of features is useful for better understanding the data and better understanding a model. Given an external estimator that assigns weights to features, Feature Importance calculates relative importance of the variables, enabling the identification of the features that have the most impact on the simulation of the phenomenon. A Random Forest was used here as an external estimator to determine the relative importance of all features. The aim is to quantify the strength of the relationship between the predictors and the outcome. The higher the score, the more important or relevant is the feature towards the output variable. The Figure 6 shows the Relative Importance (RI) of the meteo-climatic features obtained with a Random Forest model in our case. The graph shows that the variable Tmax alone explains over 40 percent of the model's values, RH is over 20%, Tapp is about 20%, and Tmean is about 10%. 3.4. Application of Distributed Lag Non-Linear Model (DLNM) DLNMs are statistical methods developed for time series data and used to describe the additional time dimension of the exposure-response relationship determining the distribution of next effects after the occurrence of events (in lag times). Several studies have shown how DLNM simultaneously estimates the nonlinear and delayed effects of temperature on mortality or morbidity . This statistical framework rests on the definition of a "cross-base" function, a two-dimensional functional space expressed by the combination of two sets of basic functions, which specify the relationships in the dimensions of predictor and delays . In order to model the shape of the non-linear relationship in each of the two spaces we are considering, that of the predictor and the lags, we must simultaneously apply two transformations:Choose a basis for x (vector of the exposures) such as to define the dependence in the space of the predictor, specifying the basis matrix Z obtained by applying the basis functions to x; Create the additional delay dimension for each of the derived base variables of x stored in Z. This operation produces an array representing the lagged occurrences of each base variable x. Despite its complicated parameterization, estimating and inferring the parameters of a DLNM is no more difficult compared to any other generalised linear model and can be performed using standard statistical software after cross-base variables have been provided . This application preserves the hypothesis of non-linearity of the exposure-response relationship and the hypothesis that the exposure is variable over time while maintaining the algebra of the DLNM unchanged except for the use of smoothing functions for time series. Decomposition of the time series into trend components allows for modelling the non-linear relationship of exposure-response with the DLNM. A generalised linear regression model with quasi-Poisson distribution, combined with the DLNM, was used to fit the relationship between the trend components of daily CVD hospital admissions and meteo-climatic factors. The fits of models with different response variable specifications were compared using AIC and BIC, identifying the most suitable model and evaluating the evidence for a non-linear exposure response as well as the consistent risk along the lag. The results obtained show that the response variables best correlated to the phenomenology are the trend components of Tmax, Tapp, and RH. The DLNM model becomes the following:Y=Poisson (mt)Log(mt)=a+bTmaxt,l + Tapp+RH+time+Dow where mt is the trend component of daily CVD hospital admissions at calendar day t (t = 1, 2, 3, ..., 1447); a is the intercept; Tmaxt,l is the cross-basis matrix produced by DLNM (Gasparrini et al., 2010). This matrix is obtained by the combination of the exposure-response function with three internal knots placed at the 10th, 75th, and 90th percentiles of the maximum temperature distributions and the lag-response function modelled with three internal knots placed at equally spaced values in the log scale. According to previous studies, the maximum lag was set up to 21 days for effects of cold temperature which appeared only after some delay and lasted for several days; the trend components of relative humidity (RH) and apparent temperature (Tapp) were used as response variables; Day of the week (Dow) was also included in the model as indicator variables . The median value of temperature (20 degC) was defined as the baseline temperature (centring value) for calculating the RR . All the analyses were performed with the software R, version 4.0.4, using the "dlnm package", available on the R comprehensive archive network (CRAN). The package contains functions for building basic matrices for specifying DLNM and then for predicting and tracking results for a fitted model. The expected effect was explained according to the Relative Risk parameter (RR). RR represents the probability that a subject, belonging to a group exposed to certain factors, develops the disease, with respect to the probability that a subject belonging to an unexposed group develops the same disease. This index is used in cohort studies where exposure is measured over time. If the RR is equal to 1, the risk factor is irrelevant to the appearance of the disease; if the RR is greater than 1, the risk factor is implicated in the onset of the disease; if the RR is less than 1, the risk factor defends against the disease (defence factor). The results were expressed in terms of percentage increase and respective 95% confidence intervals. The two-dimensional relationship of exposure-response estimated with DLNM can be graphically summarised in 3D and contour plot . The distributed nonlinear lag surface revealed a non-linear relationship between temperature and hospital admissions for cardiovascular diseases. In general, the lag patterns for hot and cold effects showed statistically positive but not significant cold effects occurred, while hot effects were strong and not correlated significantly. The cold effects followed a pattern of increasing RR on the current day or on lag day 0-1. In order to provide a specific assessment of the dose-response curve, the cumulative effects of temperatures at lag 0, 5, 15, and 20 days and by lag at specific temperatures 8.3 degC, 10.3 degC, 10.9 degC, and 30.9 degC corresponding to 0.1th, 5th, 95th, and 99.9th percentiles of temperature distribution are reported in Figure 9. 4. Conclusions and Remarks This study examines the correlations between the meteo-climatic factors and hospitalizations for cardiovascular diseases in the city of Bari. Correlations previously identified in epidemiological studies regarding the exposure-response relationship between daily visits to the emergency room and the variation of some meteo-climatic parameters suggest that morbidity in the case of cardiovascular diseases was related to the lowering of the average seasonal temperature. Our results confirm this relationship by evaluating a forecast scenario that shows an increase in the relative risk of hospitalizations as a function of the delayed effects of time. The correlation analysis carried out after the time series data decomposition highlights that the number of daily admissions to the emergency room for cardiovascular diseases and the daily parameters of maximum temperature, apparent temperature, and relative humidity are strongly related. A machine learning methodology, including Feature Importance, has mathematically validated the selection of the more relevant meteo-climatic variables to be used in the statistical model for the definition of a possible risk scenario, reducing the overfitting and, consequently, reducing the variance of the data. The non-linearity of the exposure-response relationship was, therefore, addressed through the application of the DLNM, using the trend components as input data. The prediction analysis carried out on decomposed time series shows an evident but not significant increase in the relative risk associated with colder temperatures between 8.3 degC and 10.3 degC. The effect, as highlighted in Figure 7, Figure 8 and Figure 9, occurs instantly and significantly between 0-1 days after the event and subsequently 4-10 days later. In agreement with other studies, the sample size may have contributed to underestimating the cold effect in the percentage increase in relative risk. The effect of temperature on cardiovascular diseases has been shown to be evident with the lowering of the seasonal temperature averages; however, most of these studies were conducted on at least a ten-year timeframe of observations. The increase in hospitalizations for CVD has been shown to be correlated to temperatures above 28.6 degC for lag day 5. This correlation does not appear to be significant; the increase in percentage terms of the relative risk associated with high temperatures is 0.73 (95% CIs), and this value is very low compared to the forecasted statistical scenario. Previous results suggest that the scenario produced by the application of the DLNM has identified an increased relative risk of hospitalisation due to lower temperatures. The sensitivity of the phenomenon to hot days has been shown to be very low. The study highlighted the delayed effects in terms of lag days. The results obtained do not show very high-risk percentages due to the numerosity of the input data. The small number of observations may have contributed to underestimating the risk percentages obtained. This study provides encouraging results that validate the extent of the influence of weather-climatic parameters on human health. Although the forecast scenario shows a lower percentage increase in RR compared to the reference scenarios of other studies, our methodological procedure for selecting the predictors and the evaluation of their influence on daily access to the emergency room appears to be reliable and in line with epidemiological studies. Furthermore, the results confirm the applicability of the DLNM method. Our findings align with those of many other studies who utilised the DLNM to study the relationship between PM2.5 exposure, temperature, and health outcomes in five cities in Poland. Their findings showed the effectiveness of the DLNM approach, with PM2.5 being identified as the most significant pollutant. Additionally, several other studies in China have leveraged the DLNM method to investigate the connection between PM2.5 exposure, temperature, and human health outcomes, further demonstrating the capabilities of the DLNM approach in these types of analyses. Furthermore, confirmed that this procedure is able to characterise the complex pattern existing among environmental variables and human health. In conclusion, our findings confirm that there is a noticeable correlation between the variation in meteorological parameters and the daily hospitalizations for cardiovascular diseases. Longer time series would allow further confirmation of the results and to identify specific variation ranges of other meteorological parameters, not only of temperature in which the relative risk increases. Moreover, more advanced signal decomposition techniques, such as the Ensemble Empirical Mode Decomposition (EEMD) , will be applied, for improving our analysis and for uncovering further insights into the relationship between the environmental features and cardiovascular diseases or other negative impacts on human health. Acknowledgments The authors thank Vito Procacci, director of the Internal Medicine department at Bari Polyclinic, who provided data and expertise that greatly assisted the research. Author Contributions V.T. and G.F. conceived of the presented idea. V.T. encouraged G.C. to investigate the relationship between weather factors and cardiovascular emergency admissions. V.A.P. collected the data. V.T., G.C. and C.M. investigated the models and the computational framework. V.T., G.F., G.C. and M.R. analysed the data and discussed the results. All authors contributed to the final manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The Emergency Department visit database is fully anonymized according to the privacy code. It is a completely de-identified data set that, assuch was not subject to the approval of the ethics committee.No patient contact was made, and patients could not be traced. Informed Consent Statement The data provided not contains any personal information about patients. Data Availability Statement The data used in this study can be requested from the corresponding author: Prof. Vito Telesca at [email protected]. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Annual hospital admissions in ER by gender. Figure 2 Boxplot of CVD admissions. Figure 3 Annual admissions for CVD. Figure 4 CVD admissions classified by age class. Figure 5 Experimental design of methodological procedure. Figure 6 Relative importance of selected features by correlation analysis. Figure 7 3D plot of RR of CVD hospital admissions along temperature and lags with references of 20 degC. Figure 8 Contour plot of RR of CVD hospital admissions along temperature and lags with references of 20 degC. Figure 9 Dose-response curve cumulative effects of temperatures at different time-lags. healthcare-11-00690-t001_Table 1 Table 1 Main symptoms entering the emergency room and identification code. CODE Main Problem/Symptomatology CODE Main Problem/Symptomatology 1 Coma 18 Oto rhino laryngeal symptoms or disorders 2 Acute neurological syndrome 19 Obstetric-gynaecological symptoms or disorders 3 Other nervous system symptoms 20 Dermatological symptoms or disorders 4 Abdominal pain 21 Odontostomatological symptoms or disorders 5 Chest pain 22 Urological symptoms or disorders 6 Dyspnea 23 Other symptoms or disorders 7 Precordial pain 24 Legal-medical investigations 8 Shock 25 Social problem 9 Non-traumatic haemorrhage 26 Fall from high 10 Trauma 27 Scalding 11 Intoxication 28 Psychiatric 12 Fever 29 Pneumology-Respiratory pathology 13 Allergic reaction 30 Violence from other 14 Changes in Rhythm 31 Self-harm 15 Hypertension 98 Dehydration 16 Psychomotor agitation 99 Animal bite 17 Eye symptoms or disorders healthcare-11-00690-t002_Table 2 Table 2 Number of admissions in the Emergency Room (ER) divided for gender. Gender 2013 2014 2015 2016 Total Men 40,265 42,554 40,091 38,007 160,917 Women 35,032 37,127 34,327 32,914 139,400 No data 630 1,009 916 629 3184 Total 75,927 80,690 75,334 71,550 303,501 healthcare-11-00690-t003_Table 3 Table 3 Selected codes for cardiovascular diseases. Code Specific Problem Classification 5 Chest pain Cardiovascular diseases 7 Precordial pain 14 Changes in Rhythm 15 Hypertension healthcare-11-00690-t004_Table 4 Table 4 Number of admissions in ER for CVD diseases. Cardiovascular. 2013 2014 2015 2016 No. of admissions 6854 6252 5728 5319 CVD admissions (%) 9.0 7.7 7.6 7.4 healthcare-11-00690-t005_Table 5 Table 5 Admissions for CVD classified by age class. Age Class 2013 2014 2015 2016 under 20 92 95 71 88 20-29 447 401 348 338 30-39 688 597 545 464 40-54 1617 1532 1456 1320 55-64 1236 1122 1035 1020 65-75 1440 1251 1218 1073 over 75 1326 1250 1053 1016 No Data 8 4 2 0 Total 6854 6252 5728 5319 healthcare-11-00690-t006_Table 6 Table 6 Descriptive data statistics. Legend: avg = average; std = standard deviation; 25%, 50%, and 75% = 25th, 50th, and 75th percentiles, respectively; min-max = range. Tmin Tmean Tmax Tdewp Tapp P_atm RH AH (degC) (degC) (degC) (degC) (degC) (mbar) (%) (%) avg 16.1 17.7 19.1 12.4 23.3 1008.2 72.2 11.3 std 6.4 6.1 6.3 5.4 8.7 8.6 10.9 3.6 min 0.0 3.5 3.7 -4.2 3.0 976.6 37.0 3.5 25% 11.0 12.2 14.0 8.2 15.8 1003.0 65.0 8.3 50% 16.0 17.3 19.0 12.5 22.2 1007.3 73.0 10.8 75% 20.8 22.8 24.1 16.9 30.2 1014.0 80.0 14.0 max 30.8 32.0 37.0 26.0 52.8 1042.0 99.0 24.1 healthcare-11-00690-t007_Table 7 Table 7 Correlation matrix; the asterisks indicate the cases in which the hypothesis null on p-value is not satisfied. r Tmean Tdewp Tapp Tmin Tmax P_atm RH AH CVD Tmean 1 0.91 0.99 0.94 0.95 -0.13 -0.38 0.90 -0.25 Tdewp 0.91 1 0.91 0.88 0.84 -0.14 0.03 * 0.99 -0.21 Tapp 0.99 0.91 1 0.91 0.95 -0.12 * -0.35 0.90 -0.25 Tmin 0.94 0.88 0.91 1 0.80 -0.27 -0.30 0.87 -0.18 Tmax 0.95 0.84 0.95 0.80 1 0.02 * -0.40 0.82 -0.28 P_atm -0.13 -0.14 -0.12 * -0.27 0.02 * 1 0.01 * -0.14 -0.14 RH -0.38 0.03 * -0.35 -0.30 -0.40 0.01 * 1 0.03 * 0.15 AH 0.90 0.99 0.90 0.87 0.82 -0.14 0.03 * 1 -0.22 CVD -0.25 -0.21 -0.25 -0.18 -0.28 -0.14 0.15 -0.22 1 healthcare-11-00690-t008_Table 8 Table 8 Correlation between meteorological parameters and CVD admissions, with absolute value of Pearson's coefficient (|r|) before (CVD1) and after (CVD2) decomposition model application. 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PMC10000403 | Background: Thyroid hormone anomalies during childhood might affect neurological development, school performance and quality of life, as well as daily energy, growth, body mass index and bone development. Thyroid dysfunction ( hyperthyroidism) may occur during childhood cancer treatment, although its prevalence is unknown. The thyroid profile may also change as a form of adaptation during illness, which is called euthyroid sick syndrome (ESS). In children with central hypothyroidism, a decline in FT4 of >20% has been shown to be clinically relevant. We aimed to quantify the percentage, severity and risk factors of a changing thyroid profile in the first three months of childhood cancer treatment. Methods: In 284 children with newly diagnosed cancer, a prospective evaluation of the thyroid profile was performed at diagnosis and three months after starting treatment. Results: Subclinical hypothyroidism was found in 8.2% and 2.9% of children and subclinical hyperthyroidism in 3.6% and in 0.7% of children at diagnosis and after three months, respectively. ESS was present in 1.5% of children after three months. In 28% of children, FT4 concentration decreased by >=20%. Conclusions: Children with cancer are at low risk of developing hyperthyroidism in the first three months after starting treatment but may develop a significant decline in FT4 concentrations. Future studies are needed to investigate the clinical consequences thereof. thyroid dysfunction childhood cancer treatment pediatrics Stichting Kinderen Kankervrij (KiKa)340 This research was supported by Stichting Kinderen Kankervrij (KiKa) (project 340). pmc1. Introduction Thyroid hormones are essential during childhood for adequate mental development, linear growth, bone development and metabolic regulation . Signs and symptoms of thyroid dysfunction can be overweight, declining linear growth, mental retardation in the young, constipation (hypothyroidism), tachycardia and growth acceleration (hyperthyroidism), or fatigue and emotional imbalances (both). In children with cancer, thyroid dysfunction may present with symptoms that are regularly observed during childhood cancer treatment and thus may be overlooked. The thyroid gland can be damaged in children with any type of cancer by the tumor itself, chemotherapy (e.g., busulphan), radiation exposure or immunotherapy, resulting in thyroidal hyperthyroidism . In several small studies, the prevalence of primary hypothyroidism during cancer treatment varied between 0 and 18% . Next to damage of the thyroid gland, thyroid hormone metabolism in children with cancer may also be distorted due to damage of the hypothalamic-pituitary region as a consequence of a brain tumor or cranial irradiation (central hypothyroidism). Moreover, specific drugs may influence the thyroid profile without actual thyroid or pituitary gland damage, as is seen, for example, after the administration of asparaginase with a decrease in thyroxine binding globulin (TBG) concentration or after the administration of corticosteroids with lowered thyroid stimulating hormone (TSH), triiodothyronine (T3) and TBG concentrations and increased reverse T3 (rT3) concentrations . Lastly, thyroid hormone metabolism may change during childhood cancer treatment as a consequence of an adaptive mechanism during illness called "euthyroid sick syndrome" (ESS) . In this case, concentrations of thyroxine (T4) and T3 decrease due to two mechanisms, (1) downregulation of hypothalamic thyrotropin-releasing hormone (TRH) secretion and (2) changed activity of the liver deiodinases, resulting in decreased conversion of T4 into T3 and increased conversion of T4 into rT3 . In children, EES has been described during severe illness and anorexia and is thus not associated with the underlying disease per se, but with its severity . For the presence of ESS, different definitions are used, and in the few small studies that have been conducted, the prevalence of ESS during childhood cancer treatment, depending on its definition, varied between 0 and 100% . When children with cancer have hyperthyroidism due to pituitary or thyroidal damage, this is considered a pathophysiological state and needs treatment. However, in case of acute illness, changes in the thyroid profile (ESS) are considered "physiological" and may even be protective. Therefore, it is not recommended to treat children who develop low thyroid hormone concentration during acute illness with thyroid hormone . In children who develop mild central hypothyroidism after treatment for a brain tumor, a decline in FT4 of >20%, even within reference ranges, was shown to be clinically relevant . Although mild central hypothyroidism may not be comparable with ESS, it may be hypothesized that a prolonged decline in the FT4 concentration of >20% in children who are not acutely but "chronically" ill (such as during a two-year treatment period for childhood leukemia) does impact bone, muscle and body mass index (BMI) development or daily energy . This has not been studied thus far. Because there is lack of studies reporting on thyroid hormone metabolism in large cohorts of children treated with cancer, we aimed to evaluate the percentage, severity and risk factors of a changed thyroid profile in children during treatment for cancer. 2. Methods and Patients 2.1. Patients We performed a prospective observational cohort during a two-year period (January 2020 to December 2021). The thyroid profile was measured at diagnosis and three months after starting chemotherapy or radiotherapy in newly diagnosed children (<21 years) with leukemia, lymphoma, sarcoma or a non-pituitary brain tumor at Princess Maxima Center for Pediatric Oncology. Children with known previous thyroid disease, Down syndrome, a thyroid cancer predisposition syndrome, a history of neck irradiation or meta-iodobenzylguanidine (MIBG) treatment, or a brain tumor in the hypothalamic-pituitary region were excluded. 2.2. Data Collection The thyroid profile, using TSH, FT4 and rT3, was measured at the time of diagnosis (range of +-35 days from diagnosis) and three months later (range of 60-160 days after diagnosis). Anti-thyreoperoxidase (anti-TPO) concentrations were measured at diagnosis. Blood results were interpreted by the treating physician. In case of aberrant thyroid function tests (FT4 < or > reference range or TSH <0.30 or >10 mU/L) children were referred to the pediatric endocrinologist and treated if needed. Clinical data on anthropometrics (height, weight and BMI), general well-being (body temperature, vomiting and nutritional status) and overall physical condition were extracted from patients' electronic medical records on the day of blood sampling. Physical condition was scored as "good" (no complaints), "medium" (moderate complaints, "not feeling well" or "feeling tired") or "poor" (severe complaints or "feeling ill") as reported by the health care provider in the electronic patient chart. 2.3. Laboratory Assays A description of the laboratory assays is shown in Supplementary File S1. 2.4. Definitions Thyroidal hypothyroidism was defined as present if the plasma TSH concentration was above the reference range (5.0 mU/L), combined with a plasma FT4 concentration below the reference range. Thyroidal subclinical hypothyroidism was defined as present if the plasma TSH concentration was above the reference range (5.0 mU/L), combined with a plasma FT4 concentration within the reference range. Subclinical hyperthyroidism was defined as present if the plasma TSH concentration was below the reference range (5.0 mU/L), combined with a plasma FT4 concentration within the reference range. Central hypothyroidism was defined as present if the plasma FT4 concentration was below the reference range, combined with non-elevated TSH concentration in combination with non-elevated rT3 concentration. ESS was defined as present if the plasma FT4 concentration was below the reference range, combined with a non-elevated TSH concentration in combination with an elevated rT3 concentration. 2.5. Statistics Data are presented as means +-SDs or medians (ranges) for continuous data variables, depending on the distribution. Data are presented as percentages for categorical variables. Differences between groups were examined using unpaired Student's t-tests for normally distributed continuous data and Mann-Whitney U tests for continuous data with a skewed distribution. For categorical data, kh2 tests or Fisher's exact tests (if the assumptions for chi-square were violated) were used. Between-time-point differences were evaluated using paired Student's t-test for continuous data with a normal distribution and Wilcoxon matched-pair signed rank test for continuous data with a skewed distribution. To assess the violation of normality distribution, QQ plots of the residuals and the Shapiro-Wilk test were used. For statistical analysis of changes in thyroid hormone concentrations, only paired blood samples per patient were used. The Pearson correlation coefficient was estimated to study the strength of linear associations between two continuous variables. Multivariable logistic regression analyses were used to estimate the association between covariates and two outcomes: elevated rT3 concentrations and >=20% decline in FT4 concentrations. Independent variables included in the multivariable logistic regression were selected by estimating the univariate model and by considering the clinical relevance of each variable. Therefore, in the final regression model, not only variables that were significant in the univariate analysis were included, but also factors that were clinically relevant. Odds ratios (ORs) along with 95% CIs are reported. Analyses were performed using SPSS, version 27.0. p-values of <0.05 were considered statistically significant. 2.6. Ethics The research protocol was approved by the medical ethical committee of Princess Maxima Center (NedMec NL69960.041.19). For ethical reasons, blood samples for the study were only taken if sampling for clinical reasons was simultaneously performed. Informed consent was given by all children and/or their parents/legal representatives depending on age. 3. Results 3.1. General Patient Characteristics Of 519 children assessed for eligibility, 284 were included . Of the included children, 141 (50%) were diagnosed with leukemia, 74 (26%) with lymphoma, 38 (13%) with sarcoma and 31 (11%) with a brain tumor (Table 1). The median age at diagnosis was 9.4 years (range of 0.0-19 years), and 127/284 (45%) children were female. 3.2. Thyroid Profile At diagnosis, TSH and FT4 were both measured in 220 children, in 81% (179/220) of which, both were within reference ranges (Table 2). Three months after diagnosis, in 91% (252/276) of children, both TSH and FT4 concentrations were found to be within reference ranges. In two children (1.2%), elevated anti-TPO antibodies were detected, and both were euthyroid. 3.2.1. (Subclinical) Hyperthyroidism At diagnosis, 8.2% (18/220) of children had subclinical hypothyroidism with a median TSH concentration of 6.30 mIU/L (range of 5.00-11.00). In 3.6% (8/220) of children, subclinical hyperthyroidism was found (median TSH of 0.21 mIU/L (range of 0.07-0.34)). Three months after diagnosis, 2.9% (8/276) of children had subclinical hypothyroidism (median TSH of 6.75 mIU/L (range of 5.30-11.00)). None of these children required treatment with thyroxine. In total, 2 of 276 children (0.7%) had subclinical hyperthyroidism (TSH, 0.31-0.33 mIU/L) after three months. 3.2.2. ESS At diagnosis, none of the children had ESS. After three months, 1.5% (4/265) of children had developed ESS. In 33% (49/148) of children, an isolated rT3 elevation was found at diagnosis (median rT3 concentration of 0.25 ng/mL (range of 0.22-0.58)) which increased to 50% (133/265) after three months (median of 0.27 ng/mL (range of 0.22-2.36)). A significant, weak, positive correlation was found between the FT4 and rT3 concentrations three months after diagnosis (r = 0.18, 95% CI 0.06-0.29). Children with an isolated elevated rT3 concentration after three months were slightly younger (7.7 compared with 9.6 years), more frequently had a brain tumor (74% versus 48%; p = 0.009) and were less often treated with anthracyclines (65% versus 80%; p = 0.006) than those without. No associations were found between corticosteroid use <48 h earlier or physical condition and having elevated rT3. In multivariable analysis, brain tumor diagnosis was the only significant risk factor for developing an elevated rT3 concentration three months after diagnosis (OR 3.17, 95% CI 1.19 to 8.41) (Table 3). 3.2.3. Central Hypothyroidism After three months, 1.9% (5/265) of children were suspected of having central hypothyroidism with lowered FT4 (median FT4 of 8 pmol/L (range of 8-9)), non-elevated TSH (median TSH of 2.80 mIU/L (range of 1.80-4.00)) and non-elevated rT3 concentrations (median of 0.17 ng/mL (range of 0.11-0.20)). All five had been diagnosed with leukemia at a median age of 5.4 years (range of 4.4-13.4). None was started on thyroxine treatment, but the thyroid profile was followed over time. 3.3. Decline in FT4 over Time Overall, the median FT4 concentration declined significantly in three months' time from a median of 16 to 14 pmol/l (p < 0.001), with no change in TSH (p = 0.334). Median rT3 concentrations significantly increased (0.18 versus 0.22 ng/ml; p < 0.001) . At time of diagnosis, 29% (82/284) of children had received corticosteroids <48 h earlier or chemotherapy before the first measurement. In this group, at diagnosis, lower median TSH and a higher median FT4 concentration were found when compared with those who had not (TSH, 1.20 (range of 0.07-11.00) versus 2.30 mIU/L (range of 0.34-9.40); p < 0.001; FT4, 17 (range of 11-28) versus 16 pmol/L (range of 10-29); p = 0.017). In the 22 children who had received corticosteroids <48 h before the blood withdrawal after three months, no differences were found in either TSH or FT4 concentration. (Supplementary File S2). Due to the differences found in median plasma TSH and FT4 concentrations in the children who had already received corticosteroids <48 h earlier or chemotherapy before their first thyroid hormone measurement at diagnosis, these children were excluded from the analysis of the changes in thyroid function over time. TSH and FT4 concentrations were found to significantly decline in three months' time (median TSH from 2.35 to 1.90 mIU/L; p < 0.001; median FT4 from 16 to 14 pmol/L; p < 0.001). The median rT3 concentrations increased significantly (0.16 to 0.22 ng/ml; p < 0.001) (Table 2). The median overall change in FT4 concentration in children who had not received corticosteroids <48 h earlier or chemotherapy before the first measurement was -11% (range of -47% to +100%). FT4 declines of >=10%, >=20% and >=30% were found in 41% (69/136), 28% (38/136) and 7.4% (10/136) of children, respectively. In children with a FT4 decline of >=20%, the median FT4 concentration declined from 17 (range of 10-29) to 12 pmol/L (range of 8-16), with no changes in median TSH and rT3 concentrations. Of these children, 36.1% had an elevated rT3 concentration after three months. The univariate analysis showed that children with a >=20% FT4 decline were of similar age (7.7 +- 5.1 years versus 10.0 +- 5.7; p = 0.200), more often received antimetabolites (84% versus 67%; p = 0.049)) and showed a trend towards more frequent treatment with vinca-alkaloids (92% versus 80%; p = 0.081) compared with those with no decline or a decline of <20%. The multivariable analysis, however, did not show risk factors for a >=20% FT4 decline (Table 3). No clinically significant effect of a >=20% FT4 decline from baseline on BMI SDS or linear growth was found. 3.4. Radiotherapy Radiotherapy was given to 21 (7.4%) children in the three months, in seven children possibly including the thyroid gland, and in 20 children, possibly including the hypothalamic-pituitary region in the radiation field. In total, 18 of the 21 children were irradiated for a brain tumor, of which 7 were craniospinal tumors (medulloblastoma, n = 5 (total dose of 54.0 Gray), and ependymoma, n = 2 (total dose of 59.4 Gray)) and 11 were cranial tumors (high-grade glioma, n = 10 (total dose 13-60 Gy), and germ-cell tumor, n = 1 (total dose 40.0 Gray)). Three children were irradiated for a sarcoma (2/3 orbit, total dose of 45-50 Gray). Median FT4 in children with radiotherapy changed from 15 (range of 13-24) to 14 pmol/L (range of 8-23) (p = 0.034), while median TSH remained unchanged. Reverse T3 concentrations after three months were significantly higher in children who had received radiotherapy than those in children who had not (0.28 (range of 0.14-0.62) and 0.21 ng/mL (range of 0.10-2.36); p = 0.015). 4. Discussion In this large prospective study investigating the percentage and severity of thyroid dysfunction in children treated for newly diagnosed cancer, we found a low percentage of (subclinical) hyperthyroidism in the first three months after starting treatment, which may be considered reassuring. In addition, the percentage of children that developed ESS, in this study defined as having lowered FT4, normal TSH and increased rT3, was low. However, in a considerable percentage of children, the thyroid profile was found to have changed, with an individual decline in FT4 concentration of >=20% in 28% of children after three months. We did not detect clinical consequences of this change in FT4 in this relative short period of time, and future studies are needed with prolonged follow-ups. Based on these results, we suggest that with the current treatment protocols, surveillance for hyperthyroidism is unnecessary at this stage of treatment. However, our results do illustrate that the thyroid profile can severely change during cancer treatment in children, which may reflect adaptation to an altered metabolic state during illness or may be iatrogenic . In ESS, the adaptive downregulation of TRH secretion may result in low-to-normal TSH concentrations with lowered thyroid hormone concentrations. Apart from this, in ESS, the alteration of liver deiodinases decreases the conversion of T4 into T3 and increases the conversion of T4 into rT3. In case of doubt between central hypothyroidism or ESS, the determination of rT3 may be used to differentiate them, as in true central hypothyroidism, rT3 is low, while in ESS, this is increased. The high percentage of isolated elevated rT3 concentration in our cohort may thus illustrate the presence of (mild) ESS, which may not be surprising, as these children undergo intensive treatment . We could not correlate the rT3 increase to corticosteroid use, although 90% of children had received different kinds of corticosteroids within the three months. Brain tumor diagnosis was found to be a risk factor for elevated rT3. Although no associations were found among poor physical state, corticosteroids and elevated rT3, it must be considered that brain tumor patients may have been in worse physical state compared with others, amongst others caused by cranial radiotherapy. No central hypothyroidism was found, as expected, because radiotherapy is unlikely to cause pituitary dysfunction after such a short period of time . Van Iersel et al. showed that an FT4 decline of >20% during prolonged follow-up, although within reference ranges, was associated with weight gain, reduced linear growth and less improvement of intelligence scores over time in childhood brain tumor survivors . This FT4 decline was regarded as a reflection of mild central hypothyroidism. Even though the etiology of declining FT4 as result of mild central hypothyroidism and (mild) ESS may not be comparable, we hypothesize that prolonged lowered thyroid hormone concentrations in (non-acutely ill) children with cancer may contribute to adverse late effects, such as short stature, weight gain, dyslipidemia, fatigue or the pathogenesis of early frailty, on childhood cancer survivors . Therefore, we aim to follow thyroid hormone parameters in relation to these possible adverse late effects until the end of cancer treatment in this large prospective cohort. It is not recommended to treat children with thyroid hormone for ESS during acute illness . When FT4 declines in time and remains lowered for a prolonged period in "chronically" ill children, this disease state may, however, be compared to adaptation of the hypothalamic-pituitary axes, which is also encountered in children with other chronic diseases. Examples of such diseases are cystic fibrosis or chronic kidney disease, whereby affected children develop low insulin-like growth factor-1 concentrations or delayed puberty due chronical illness . In these situations, treatment with sex steroids or growth hormone to improve bone development and final height are considered . With this in mind, thyroid hormone treatment might be beneficial in the situation of prolonged lowered thyroid hormones in children with chronic illness or prolonged disease. This question needs to be addressed in future studies. Our study also has several limitations. Firstly, the results might not be applicable to all children with cancer, because for this study, we only included children treated for leukemia, lymphoma, sarcoma or a non-pituitary brain tumor. Future studies may be performed to investigate changes in the thyroid profile in children with other types of childhood cancer. Secondly, although we aimed to measure the thyroid profile before any drugs had been administered, 29% of the children had already received corticosteroids <48 h earlier or chemotherapy before the first thyroid hormone measurement. For optimal analysis, we, therefore, excluded these children from analysis on changes in TSH and FT4 concentrations. Moreover, data on physical condition were scored by the researchers in three categories, based on the notes of the health care provider in the electronic patient chart, which may be considered a subjective way of physical condition scoring and thus a limitation. 5. Conclusions Children with cancer, treated within current treatment protocols, do not seem to be at risk of hyperthyroidism in the first three months of cancer treatment. In 28% of children, however, the median FT4 concentration significantly decreased during cancer treatment. The long-term clinical consequences thereof have to be investigated in future studies. Supplementary Materials The following supporting information can be downloaded at: File S1: Laboratory assays; File S2: Chemotherapeutic Agents and Corticosteroids. Click here for additional data file. Author Contributions Conceptualization, C.A.L., W.J.E.T. and H.M.v.S.; Methodology, C.A.L., M.F., W.J.E.T. and H.M.v.S.; Software, C.A.L., W.J.E.T. and H.M.v.S.; Validation, C.A.L., W.J.E.T. and H.M.v.S.; Formal analysis, C.A.L., M.F., W.J.E.T. and H.M.v.S.; Investigation, C.A.L., W.J.E.T. and H.M.v.S.; Resources, C.A.L., C.v.d.B., M.P.D., A.A.V.S., E.G.W.M.L., S.L.A.P., W.J.E.T. and H.M.v.S.; Data curation, C.A.L., W.J.E.T. and H.M.v.S.; Writing--original draft, C.A.L., W.J.E.T. and H.M.v.S.; Writing--review and editing, C.A.L., C.v.d.B., M.P.D., M.F., A.A.V.S., E.G.W.M.L., S.L.A.P., W.J.E.T. and H.M.v.S.; Visualization, C.A.L., C.v.d.B., M.P.D., M.F., A.A.V.S., E.G.W.M.L., S.L.A.P., W.J.E.T. and H.M.v.S.; Supervision, W.J.E.T. and H.M.v.S.; Project administration, C.A.L., W.J.E.T. and H.M.v.S.; Funding acquisition, W.J.E.T. and H.M.v.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The research protocol was approved by the medical ethical committee of Princess Maxima Center (NedMec NL69960.041.19). Informed Consent Statement Informed consent was given by all children and/or their parents/legal representatives depending on age. Data Availability Statement The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Inclusion flowchart of THYRO-Dynamics study. Figure 2 Median concentrations and interquartile ranges of TSH, FT4 and rT3 in children at diagnosis and three months after diagnosis (n = 284). * The boxes show the IQR divided by the median, dots denote outliers. cancers-15-01500-t001_Table 1 Table 1 Baseline patient characteristics (n = 284). Characteristic Age at diagnosis (yrs) (median, range) 9.4 (0.0-19.7) No. of females (%) 127/284 (45%) Diagnosis (number (% of entire cohort)) Leukemia 141 (50%) ALL 118 (42%) AML 20 (7.0%) CML 2 (0.7%) Other 1 (0.4%) Lymphoma 74 (26%) Hodgkin lymphoma 35 (12%) B-NHL/B-ALL 25 (8.8%) Non-B NHL 12 (4.2%) ALCL 2 (0.7%) Sarcoma 38 (13%) Bone tumor (osteosarcoma/Ewing sarcoma) 22 (7.7%) Rhabdomyosarcoma 11 (3.9%) Non-rhabdomyosarcoma 4 (1.4%) Other 1 (0.4%) Brain tumor 31 (11%) ATRT 1 (0.4%) Ependymoma 5 (1.8%) Low-grade glioma 3 (1.0%) High-grade glioma 10 (3.5%) Germ-cell tumor 2 (0.7%) Medulloblastoma 9 (3.2%) Optic glioma 1 (0.4%) Physical condition * At diagnosis Good 76 (38%) Medium 112 (57%) Poor 10 (5.1%) Unknown 22 After three months Good 186 (69%) Medium 74 (28%) Poor 8 (3.0%) Unknown 8 Abbreviations: ALL, acute lymphoblastic leukemia; AML, acute myelogenous leukemia; CML, chronic myelogenous leukemia; B-NHL, B-cell non-Hodgkin lymphoma; B-ALL, B-cell acute lymphoblastic leukemia; non-B-cell non-Hodgkin lymphoma; ALCL, anaplastic large-cell lymphoma; ATRT, atypical teratoid rhabdoid tumor. * Physical condition was scored as "good" (no complaints), "medium" (moderate complaints, "not feeling well" or "feeling tired") or "poor" (severe complaints or "feeling ill") as reported by the health care provider in the electronic patient chart. cancers-15-01500-t002_Table 2 Table 2 Median plasma concentration of thyroid determinants in children with cancer measured at diagnosis and three months after diagnosis. All Children (n = 284) Analysis of Children Who Had Not Received Corticosteroids or Chemotherapy before First Measurement Only (n = 202) Thyroid Hormone Determinant Median Concentration at Diagnosis, mIU/L (Range) (No. of Samples) Median Concentration Three Months after Diagnosis, mIU/L (Range) (No. of Samples) p-Value Median Concentration at Diagnosis before Start of Chemotherapy or Corticosteroids, mIU/L (Range) (No. of Samples) Median Concentration Three Months after Diagnosis, mIU/L (Range) (No. of Samples) p-Value TSH (0.30-5.00 mIU/L) 2.00 (0.07-11.0) (n = 222) 1.90 (0.31-8.00) (n = 276) 0.334 2.30 (0.34-9.40) (n = 141) 1.90 (0.31-11.00) (n = 199) <0.001 FT4 (10-22 pmol/L) * 16 (10-29) (n = 220) 14 (8-23) (n = 276) <0.001 16 (10-29) (n = 139) 14 (8-24) (n = 199) <0.001 rT3 (0.098-0.218 ng/mL) 0.18 (0.09-0.58) (n = 148) 0.22 (0.10-2.36) (n = 265) <0.001 0.16 (0.09-0.58) (n = 90) 0.22 (0.10-2.26) (n = 191) <0.001 Abbreviations: TSH, thyroid stimulating hormone; FT4, free thyroid hormone; rT3, reverse T3. * Dependent on age: 20 days-3 years, 12-21 pmol/L; 3-5 years, 10-19 pmol/L; 5-19 years, 11-20 pmol/L; >19 years, 10-22 pmol/L. p-Value: for analysis of changes in thyroid hormone concentrations, only paired blood samples (diagnosis and three months after diagnosis) were used. cancers-15-01500-t003_Table 3 Table 3 Risk factor analysis results. A. Risk Factors Associated with >=20% FT4 Decline Covariate/Category >=20% FT4 Decline Univariable OR (95% CI) Multivariable OR (95% CI) Age at diagnosis, years 0.95 (0.89 to 1.02) 0.97 (0.90 to 1.04) Administration of antimetabolites 2.59 (0.98 to 6.81) 2.37 (0.78 to 7.18) Use of corticosteroids <48 h before thyroid hormone measurement after three months 1.11 (0.27 to 4.55) 1.55 (0.35 to 6.97) Radiotherapy before thyroid hormone measurement after three months 0.54 (0.11 to 2.67) 0.93 (0.15 to 5.65) B. Risk factors associated with elevated rT3 concentration Covariate/Category Elevated rT3 Concentration Univariable OR (95% CI) Multivariable OR (95% CI) Age at diagnosis, years 0.96 (0.92 to 1.00) 0.97 (0.92 to 1.01) Brain tumor vs. others a 3.16 (1.29 to 7.76) 3.17 (1.19 to 8.41) b Physical condition three months after diagnosis Medium/poor vs. good 1.54 (0.90 to 2.64) 1.42 (0.80 to 2.53) Use of corticosteroids <48 h before thyroid hormone measurement 1.68 (0.67 to 4.20) 1.72 (0.67 to 4.43) Underweight (<-2 SDS) 0.51 (0.12 to 2.08) 0.57 (0.13 to 2.45) NOTE. 3A. Multivariable logistic regression for risk factors of children with a >=20% FT4 decline from diagnosis to three months after diagnosis (n = 38) compared with children without >=20% FT4 decline from diagnosis to three months after diagnosis (n = 98). NOTE. 3B. Multivariable logistic regression for risk factors of children with elevated rT3 concentrations three months after diagnosis (n = 133) compared with children without elevated rT3 concentrations three months after diagnosis (n = 132). Abbreviations: FT4, free thyroxine; OR, odds ratio; CI, confidence interval; SDS, standard deviation score. a Brain tumor diagnosis versus other diagnoses. b Statistically significant. 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. |
PMC10000404 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050957 foods-12-00957 Review Protein-Based Fat Replacers: A Focus on Fabrication Methods and Fat-Mimic Mechanisms Nourmohammadi Niloufar 1 Austin Luke 2 Chen Da 1* Raak Norbert Academic Editor Li Ruifen Academic Editor Roman Laura Academic Editor 1 Department of Animals, Veterinary and Food Sciences, University of Idaho, Moscow, ID 83844, USA 2 Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA * Correspondence: [email protected] 23 2 2023 3 2023 12 5 95701 1 2023 09 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 increasing occurrence of obesity and other non-communicable diseases has shifted the human diet towards reduced calorie intake. This drives the market to develop low-fat/non-fat food products with limited deterioration of textural properties. Thus, developing high-quality fat replacers which can replicate the role of fat in the food matrix is essential. Among all the established types of fat replacers, protein-based ones have shown a higher compatibility with a wide range of foods with limited contribution to the total calories, including protein isolate/concentrate, microparticles, and microgels. The approach to fabricating fat replacers varies with their types, such as thermal-mechanical treatment, anti-solvent precipitation, enzymatic hydrolysis, complexation, and emulsification. Their detailed process is summarized in the present review with a focus on the latest findings. The fat-mimic mechanisms of fat replacers have received little attention compared to the fabricating methods; attempts are also made to explain the underlying principles of fat replacers from the physicochemical prospect. Finally, a future direction on the development of desirable fat replacers in a more sustainable way was also pointed out. protein fat replacer fat mimic microparticulation microgels thermomechanical treatment This research received no external funding. pmc1. Introduction With the prevalence of obesity and obesity-associated chronic diseases, customers become increasingly aware of the calorie intake of their diet. According to the National Health and Nutrition Examination Survey (2017-2020), ~42% of U.S. adults aged >=20 have obesity . The Dietary Guideline for Americans, 2020-2025, encourages the public to consume non-fat foods for healthier diets . Reducing calorie intake by decreasing the amount of fat in food, especially saturated ones, has been considered one of the strategies to reduce the occurrence of obesity . Nevertheless, the commitment to consuming low-fat foods or maintaining a low-fat diet remains challenging because of their deteriorated texture and sensorial properties compared to those of full-fat ones. Hence, the development of fat replacers that imitate not only the functional role of fat but also its sensory features is essential to improve the quality attributes of low-fat foods. Depending on the properties and manufacturing approaches, fat replacers fall into two categories: (1) fat substitute: typically, biomolecules or their degraded products with little or no calories, functioning similarly to fat. They fall into three main groups based on their sources, which are carbohydrate-based, which can hold water and impart a creamy texture close to fat (such as starches and gums), protein-based (such as egg white, milk, and whey), and fat-based fat replacers, which are too large to be digested with little contribution to calories (such as Caprenin as cocoa butter fat substitute and Olestra) . As a well-known fat substitute example, Olestra is a product composed of sucrose, and hexa-, hepta-, and octa-esters of saturated and unsaturated fatty acids , but its application has been limited due to the risks of causing gastrointestinal side effects, such as abdominal cramping ; (2) fat mimetic (FM): ingredients that partially mimic the organoleptic properties of animal fat, includes mainly food hydrocolloids (gums, cellulose microfibrils, pectins), proteins, protein aggregates, protein-polysaccharides composites, and emulsion gels. Protein-based fat replacers have received increasing attention. They boost the protein nutrition of food products with a low-calorie contribution. According to the dietary reference, adequate intakes of at least 0.8 g/kg body weight of high-quality protein for sedentary adults, the optimum amount of 1.2-1.8 g/kg body weight for adults with moderate activity, and 1.8-2.2 g g/kg body weight for adults with hypertrophy and strength training per day would be an ideal goal for health enhancement. When it comes to the health-related impact of a high-protein diet, protein intakes above the recommended amount within a certain range could limit the appearance of sarcopenia, and reduce the loss of muscle mass . Due to their highly reactive features towards pH, temperature, ions, and enzymes, protein-based fat replacers can be tuned with distinct physiochemical properties for expanded food applications, such as in yogurt, cream cheese, salad dressings, and frozen desserts. Common sources of proteins to develop fat replacers include egg white protein, whey protein, gelatin, soy, pea, and zein . Animal proteins are considered as higher quality because of the well-balanced amino acid profiles and high digestibility and bioavailability. For plant proteins, they commonly lack cysteine and methionine; however, this nutritional deficiency could be overcome by mixing different types of plant proteins . In addition, due to the presence of anti-nutritional factors, such as trypsin inhibitors, phenolic compounds, phytates, cyanogenic compounds, lectins, and saponins, the digestibility of plant proteins can be reduced unless properly processed . Furthermore, the incorporation of protein-based fat replacers levels up the protein content in foods, which enhances protein nutrition. The protein-based fat replacements have advantages over carbohydrate-based ones in terms of flavor interactions and the amount of fat that could be replaced . However, protein-based fat replacers may not be suitable to be incorporated into overprocessed food products because of protein denaturation and interaction with other components (e.g., Maillard reaction), resulting in a loss of functionality and fat-like mouthful feelings . The types of fat replacers, and their characterization and food applications have been reviewed systematically . However, the approaches to develop protein-based fat replacers and the mechanism of their fat-mimic effects, which varies significantly with the source of proteins, their molecular weight, solubility, and surface chemistry, remain rarely summarized. This information is essential to design fat replacers with desirable functionality using the most appropriate approach. We attempt to cover the latest findings on those within the last five years. Future perspectives on the production of protein-based fat replacers with improved sustainability are also provided. 2. Types of Protein-Based Fat Replacers 2.1. Protein Concentrates and Isolates Protein concentrates or isolates can be used directly as fat replacers . They may be slightly denatured during the manufacturing process . The former contains ~30-80% protein, whereas the latter reaches 90-92% . Extensive research has been conducted on developing low-fat dairy products including yogurt , ice cream , and cheese using protein concentrates/isolates, especially whey protein due to its high compatibility with other dairy ingredients and a matching flavor profile . A higher level (up to 6.8%) addition of whey protein could improve syneresis, yield stress, storage modulus (G'), viscosity, and creaminess of the low-fat yogurt with reduced serum separation compared to the control . In low-fat cheese, the partial (3-8%) replacement of fat with whey proteins has been found to improve its hardness because of the formation of more compact structures . 2.2. Microparticulated Proteins Protein microparticulation is a process of aggregation. The size of the particles commonly ranges within 0.1-10 mm, but larger ones >10 mm have also been reported . Protein particles with a size larger than 5 mm can be detected by oral mucosa ; thus, a smaller size is preferable to provide the smoothening mouthful feelings. The most widely used microparticulated proteins is from whey proteins, which was patented in 1988 and later commercialized with the brand name Simplesse(r) . Some other proteins, such as soy protein, bovine serum albumin , egg white protein , gelatin , zein , wheat protein , pea protein, and potato protein , have also been used to produce fat replacers, as summarized in Table 1. Due to their spherical shape and size, they were claimed to mimic fat droplets and create a smooth and creamy mouthfeel through a "ball-bearing" mechanism, which will be discussed later. 2.3. Protein-Polysaccharides Hydrogel Either proteins or polysaccharides have the capacity to form hydrogels. Protein-based hydrogels are mainly particle type, whereas those from polysaccharides are "thread or linear" type. When mixing the two, complexation could occur , which tailors protein functionality in foods by altering its surface chemistry and aggregating behavior . Many studies have confirmed that the addition of polysaccharides prevented the coalescence and interaction between microparticulated proteins, either by shielding charged groups or by decreasing the collision rate between molecules through an increase in the viscosity of the system. The presence of polysaccharides can also bind a large amount of water to provide a creaminess sensation through the oral process . Thus, a protein-based fat mimetic in combination with polysaccharides is usually formulated to replace fat to develop low-fat products . The polysaccharides used in complexation with protein are gum arabic , pectin , alginate , and xanthan . Nowadays, there is a growing trend to develop plant protein-polysaccharide hydrogel from peas , lentils , and soybeans to increase their sustainability. 2.4. Microgel Particles Protein-based microgel particles are novel types of fat replacers, with a size at micro-meter level . They can be categorized into different types: fragments of protein hydrogels, protein assembles, emulsified gel droplets , and protein-polysaccharides coacervates . The particles have the dual properties of particles and polymers, which endows ideal lubricating effects. Proteins can be used as the sole component of the microgel particles, and their elasticity depends on the types of proteins used and the interactions among protein molecules. In general, plant protein-based microgel particles have smaller elastic moduli compared to those of animal proteins due to the formation of less covalent bonds . By changing environmental conditions, such as pH and ionic strength, the surface charge of protein molecules alters, which further affects their electrostatic interactions, resulting in distinct elasticity. For example, a 15-fold increment of elasticity of whey protein microgel particles was found at pH 3 and pH 5.5 compared to those at neutral pH . Besides protein itself, other components could also be incorporated into microgel particles, such as polysaccharides and/or plant oils. Either of them contributes to the increased deformability of the particles. When plant oil was used, the system turns into an emulsion type, with Pickering emulsion being the typical example . The emulsion-type protein-based microgels commonly have a more regular shape and better lubricating capacity than those of protein-only particles due to the formation of a lubrication film from the protein nanoparticles and base oils . However, they are vulnerable to environmental change and long-term stability remains a challenge. Synthetic polymers or organic solvents might be used to decrease the surface tension or increase the stability of emulsion-type microgel particles, but they are not suitable for food applications. 3. Production of Protein-Based Fat Replacers The way to fabricate fat replacers associates closely with their physicochemical properties and functionalities, such as particle size and shape, viscosity, gelling, emulsifying, foaming, and water-holding capacity. This further affects the color, texture, and other sensory characteristics of the final products. For proteins with high water solubility, such as whey proteins, thermal treatment to trigger protein aggregation under the controlled shear is commonly used. For those with limited water solubility, microparticulation could be achieved by breaking down large aggregates into smaller ones or improving their solubility/dispersibility first followed by precipitation. In the following sections, the common approaches used to produce fat replacers are discussed with a focus on protein microparticles and microgels. 3.1. Protein Concentrate or Isolate The production of a protein concentrate or isolate has been well summarized and will not be detailed here. Animal proteins, especially dairy proteins, are concentrated by ultrafiltration or diafiltration followed by optional evaporation of the retentate prior to spray drying . The temperature of spray drying associates closely with the denaturation of the proteins, and their aggregation and particle morphology. The mean diameter of whey protein powders has been reported to increase from ~15 mm to ~20 mm when the outlet temperature was increased from 60 degC to 100 degC . The morphology of whey protein concentrate particles was changed from spherical at a lower inlet air temperature to a deflated shape at high temperatures . How the morphology and size of particles in a milk protein isolate or concentrate affect their fat-mimic capacity remains poorly studied. It has to be noted that the size and morphology of the particles in powders may change after they are incorporated into the food matrix due to the presence of water, salt, or other food components. For plant proteins, wet and dry fractionation has been widely used . Wet methods include mainly alkaline-isoelectric point precipitation, or water, salt, or acid extraction. By using acid or alkaline, the protein recovery efficiency is high due to the increased solubility of proteins at the pH values far away from its isoelectric point . Alkaline-isoelectric precipitation is more commonly used than other methods in food industries to extract proteins followed by spray drying to produce a protein isolate , but it uses a large amount of water and generates excessive salt in wastewater, which potentially threatens the freshwater ecosystem. In addition, high pH used during extraction may cause denaturation, racemization, and lysinoalanine formation of plant proteins, resulting in deteriorated quality . Dry fractionation is more environmentally friendly and specific to produce a protein concentrate (40-50% protein content). It takes advantage of the size and charge of proteins that differed from those of starch and dietary fiber and achieves the separation by sieving or electrostatic interactions forces . Since no high pH and extensive heat are involved during isolation, the proteins tend to have better functionality than those from the alkaline method. 3.2. Microparticulated Proteins 3.2.1. Thermal-Mechanical Treatments Thermomechanical treatment is the most common approach to develop microparticulated proteins as fat replacers. In general, a heating source is needed to unfold proteins by heating above their denaturation temperature . Unfolded proteins are then aggregated via covalent (S-S bonds) and non-covalent interactions (mainly hydrophobic interactions). Animal proteins are commonly heated at 75-95 degC for 20-40 min for microparticulation to occur . More extensive heating (80-95 degC, ~30 min) is required for plant proteins due to their higher thermal stability . The duration of heating shortens with the increase of temperature. For instance, pea protein particles were formed within a minute at 135 degC . The morphology and size of the protein particle changes with the heating conditions. At lower temperatures, particles commonly have a smaller size with higher compactness . Besides temperature, the shear force also applies to the system during heating unless at a low protein concentration (<=5%), otherwise, gelation could occur. The size of the particles negatively correlates with the shear force. High shear force results in more rigorous breaking of the aggregates and produces particles with smaller sizes , as demonstrated in whey proteins . Multiple strategies have been adopted to provide heat and shear simultaneously . The simplest setup is to stir the sample on a temperature-controlled water bath. The strength of the shear can be fulfilled through adjusting the stirring speed, but the heating and cooling rate may be beyond control unless a sophisticated heating/cooling system is used. The other shortcoming of the method is it fails to provide ideal mixing of the concentrated protein suspension because of the high viscosity. These can be overcome by using a concentric cylinder accessory (bob-cup) equipped on a rheometer. The shear rate of the bob can be adjusted to the required value while the temperature is controlled by the cup. Such a method has been used to design microparticulated structures from whey, potato, and pea proteins (Table 1). Within a certain range, the increase of the shear rate reduces the size of the formed particles as it disrupts the accumulated aggregation of proteins. The concentric cylinder is also able to monitor the microparticulation progress and explore the effects of shear force and temperature on the viscoelasticity, but the large-scale production of microparticles using a concentric cylinder remains a challenge as the volume of the cup is limited (e.g., 25 mL or less). The extrusion process, another thermomechanical treatment, is widely applied in food industries with the features of large-scale and continuous production. Proteins are unfolded and aggregated under the control of heating and screw rotation. Compared to the water bath and concentric cylinder, the temperature inside the extruder can achieve above 100 degC due to the high-sealed environment . This facilitates protein microparticulation within a short duration. In addition, the protein content in the fed materials can be adjusted to higher values (>=20%), which significantly increases the yield of protein microparticles . Whey protein particles produced through extrusion have been found to enhance the creaminess of low-fat, plain, stirred yogurt while maintaining its consumer acceptance with a less than 0.5% addition . Similarly, the incorporation of pea protein microparticles derived from the same method into fat-reduced milk desserts resulted in approximately the same creamy perception as the full-fat milk dessert . The conventional extrusion method consumes a large amount of energy to unfold proteins for subsequent aggregation. A hybrid technology, which takes advantage of the expanding properties of supercritical carbon dioxide (SC-CO2) to induce aggregation at lower temperatures (<100 degC), is more energy efficient . In supercritical fluid extrusion, proteins tend to expose the hydrophobic regions and aggregates driven by the surrounding non-polar environment, resulting in distinct properties of microparticles, such as the protein-protein interactions, surface hydrophobicity, and rheological properties . High-pressure homogenization combined with heat treatment is another technique capable of applying a strong shear force and a sudden pressure modulation to tune protein aggregation (Table 1). Liu et al. used such a method (10,000 rpm for 60 s, 75 degC for 13 min) to produce microparticulated egg white proteins as a fat replacer in salad dressings, which are comparable to the commercial salad dressings' features . Ultrasound-assisted heating could also induce protein microparticulation. The ultrasonication could be conducted simultaneously with the heating or after. A recent study found large whey protein aggregates (60-600 mm) were formed by heating, whose size was reduced to 0.01-2 mm upon sonication . The treatment also resulted in higher surface hydrophobicity of the particles, which is possibly due to the exposure of more interior regions of protein aggregates. 3.2.2. Enzymatic Hydrolysis Protein aggregation and microparticulation could also be triggered by enzymatic treatment with or without additional heating. Transglutaminase catalyzes acyl transfer between e-amino groups of lysine residues and the g-carboxyamide groups to form covalent cross-links, but the reaction is slow and requires hours to complete, which hinders large-scale production . The breaking down of proteins to expose hydrophobic regions or reactive amino acid residues also induces aggregation , which can be fulfilled through limited enzymatic hydrolysis. Compared to heat-induced aggregation, proteolysis is a greener approach, which consumes less energy. Depending on the types of proteases and the proteins, the conditions to promote aggregation vary. For instance, small aggregates were formed in Bacillus licheniforms (BLP) hydrolyzed whey proteins when 70% of the proteins were intact . Using the same enzyme, whey proteins were found to form soft and turbid aggregate gels at 50 degC for 1 h . For pea proteins, when the degree of hydrolysis was controlled to around 6-7% by a short time (2-3 min) hydrolysis with alcalase at 50 degC, the obtained hydrolysates were aggregated rapidly in response to heat. Analysis of the aggregates found that non-covalent interactions were the dominant forces that drive aggregation . This suggests the aggregates might be deformed easily to provide lubricating effects. Zang et al. studied the influence of limited enzymatic hydrolysis of rice bran proteins by trypsin, at the ratio of 1:100 (Enzyme:Substrate)(v/w), on the emulsifying properties. They found a significant enhancement of the emulsifiying properties of hydrolysates with a 3% degree of hydrolysis. This was due to the release and exposure of soluble peptides from insoluble aggregates resulting in the exposure of more ionizable amino groups . 3.2.3. Anti-Solvent Precipitation Anti-solvent precipitation has been used to produce fine particles at the nano-scale level. The size and morphology of the particles could be well controlled by adjusting the protein concentration and polarity of the solvent . The method is mainly applied to fabricate prolamin-based composites, such as zein and wheat gluten. Zein is the dominating protein found in maize, which can be extracted from dry-milled corn (DMC) or distillers-dried grains by using aqueous ethanol, acetic acid, or alkaline . The hydrophobic nature of zein and its incomplete amino acid profile limit the food applications. Nevertheless, the inherent hydrophobicity and the heat-softening capacity of zein make it an ideal candidate for fat analog . To achieve this, zein or its aggregates are suggested to micronize to a level similar to those of oil droplets by anti-solvent precipitation. Firstly, hydrophobic proteins are solubilized in an organic solvent, such as aqueous ethanol (70 to 90% v/v) or acetic acid/ethanol solution (e.g., at 55/45 ratio, v/v, pH 3.0) under agitation . Then, the concentration of the organic solvents is lowered down by adding water, resulting in increased polarity of the environment . This triggers the aggregation of zein or wheat gluten mediated by hydrophobic interactions and precipitates out from the system when gravity overcomes electrostatic repulsions. Cui et al. have used zein nanoparticles prepared from anti-solvent precipitation as a stabilizer in low-fat emulsions. They solubilized zein in an 85% (v/v) aqueous ethanol at room temperature followed by the addition of phytic acid (PA) solutions to improve its stability. By stirring the mixture continuously for 30 min at 600 rpm, zein protein nanoparticles with a mean size of ~160 nm were formed . The concentration of the organic solvent and the drying temperature directly links to the size and stiffness of the formed nanoparticles. Bisharat et al. (2018) found that the size of zein particles was increased from an average of 200-500 nm to 1 mm as the ethanol concentration was decreased from 90% to 70%. When the drying temperature was decreased from 55 degC to 40 degC and then to room temperature, the Young's modulus of the particles was dropped continuously, corresponding to a higher flexibility and less resistance to stretching . Zein could also form particles containing polysaccharides using anti-solvent precipitation. The particles have been shown to stabilize oil droplets as a potential fat replacer in sausages . 3.2.4. Protein-Polysaccharides Hydrogel When proteins and polysaccharides co-exist, depending on the environmental conditions and the concentration of each component, they behave distinctly. Thermodynamic incompatibility occurs mainly at high protein and polysaccharide concentrations due to their differed chemical nature and affinity towards solvent. Nevertheless, phase separation may not occur because of the high viscosity of the system. When gelation occurs fast, for instance, heating under a high temperature, the extent of phase separation or inhomogeneity of the gel would become less . This results in higher consistency of the gel texture. Even though heating is not the sole condition to form a protein-polysaccharides hydrogel, it is the most common approach. Depending on the types of proteins and polysaccharides, they can both gel under heat, but not always. Most of the proteins are heat-sensitive and tend to unfold and aggregate to form a gel under heat, whereas polysaccharides could remained unchanged . The proportion of the polysaccharides affects the rheological and fat-mimic capacity of the mixed gel and can be tuned accordingly. For instance, when mixing soy protein isolate and cellulose nanofibrils (CF), with the increasing of CF, the creaminess was increased . If strong electrostatic interactions occur during the initial heating of proteins and polysaccharides, they can be gelled without extra heating. Since the complexation occurs rapidly, the protein or polysaccharides solution needs to be prepared separately before mixing. A high-pressure homogenization might be required to facilitate a homogenous distribution of polysaccharides and proteins . Using this approach, Fan et al. (2020) developed oat b-glucan/marine collagen peptides mixed gels to replace the fat in sausage products . Adjusting the environmental pH or ionic strength enables us to modify the surface charge of proteins, which further tunes the interactions between proteins and polysaccharides , and the textural properties of the gel. As non-covalent interaction are weak forces, the formed gels commonly possess high deformability against force and heat as desirable fat mimics. 3.3. Microgel Particles For protein-only microgel particles, a hydrogel needs to be prepared followed by size reduction via homogenization or microfluidization to form nano-particles. Gelation could be conducted by using either the hot or cold method. Heat gelation occurs normally at 80-95 degC at a relatively high protein concentration (>=10%) for 20-30 min to induce protein aggregation and cross-linking . Cold gelation also requires heat to denature the protein first, followed by aggregating using calcium , salt , polysaccharides , or acid at room temperature (Table 1). By changing the concentration of the reactants, the microgel particles display distinct physicochemical properties. For instance, when the concentration of CaCl2 was increased from 0.02 to 0.1 M, the size of whey protein microgel particles was decreased with the increment of their viscoelasticity . When using salt, the concentration should be high enough to screen the surface charge of proteins to promote coacervation , but not cause the "salt in" effects. Similar to salt, the charged polysaccharides could also mediate the aggregation of proteins by reducing their surface charge. The hydrogen bonding between proteins and polysaccharides may also contribute and possibly play more significant roles than the electrostatic interaction on large-scale aggregation . Besides protein-only or protein-polysaccharides microgel particles, there is increasing interest to fabricate emulsion-based ones . Proteins could be gelled or denatured via heating (e.g., 90 degC for 20 min) followed by emulsification with plant oil using homogenization. Heating enables the exposure of the buried hydrophobic regions of proteins for increased non-polarity favoring the stabilization of oil droplets. When the concentration of denatured proteins is too low to form gels, additional gelling steps are required, such as acidification and complexation with polysaccharides . In some other cases, proteins are mixed with oil in their native states to form emulsions with or without the assistance of an emulsifier, then heated or acidified to trigger the gelation of proteins . Thermal gelation has been shown to deliver aggregates or heterogeneous microgels, whereas gelation by acidification resulted in spherical and more homogenous particles with a better fat-mimic capacity . To facilitate industrial applications, the microgel particles can be harvested by centrifugation or membrane filtration followed by spray drying to form powders. 4. The Fat-Mimicking Mechanisms An ideal fat replacer should possess lubrication, flow properties, and heat melting capacity analog to fat. Unfortunately, protein-based fat replacers can hardly mimic all of them. Providing lubrication for the reduced friction of food products is the main function of a fat replacer. One of the theories to explain the changes in textures is the "ball-bearing" effect. It refers to the protein microparticles or microgels employing a rolling mechanism similar to "ball bearings" . When force is applied, the balls rotate and/or slide to decrease frictions of the surrounding matrix . The surrounding matrix could be the neighboring protein networks or the boundary regime between proteins and non-protein components . The shape and size of the protein microparticles allow them to entrain in the narrow space between the tongue and palate in the mouth and provide creaminess and the perception of smoothness. The spherical shape and size of microparticulated fat replacers ranging from 0.2 to 9 mm are the key factors in providing the ball-bearing effect. This mechanism has been claimed to be dominant for microparticulated whey proteins in liquid and semi-liquid model foods . Besides size and shape, the interior compactness of the protein particles is also highly desirable for the ball-bearing effect to occur. Sarkar et al. (2017) found negligible changes in the microstructure and size of whey protein microgel particles after the tribology test, implying their resistance towards friction force . For the particles with irregular shapes and larger sizes, such as aggregates from plant protein or protein hydrolysates, their deformation or even disintegration would contribute to a soft and/or smooth texture . Mechanical deformation of food through chewing and a biting motion in the oral cavity helps facilitate organoleptic perception, such as flavor release or the textural attributes of food. These movements, alongside the forces that the tongue makes by bouncing and excreting against the palate, could deform or even break the protein aggregates through disrupting non-covalent interactions . Klost et al. (2020) have changed the proportion of soluble and insoluble pea protein aggregates in the fermented gels to mimic the texture of yogurt. They found the gels with higher insoluble aggregates showed higher flexibility and were easier to deform, showing smaller elastic moduli. After reducing the size of the aggregates by applying a larger intercycle strain, the system was converted from predominantly elastic to plastic behavior . In a recent study, Chen and Campanella (2022) observed a substantial reduction of viscosity of pea protein hydrolysate gels under shear. Such shear-thinning behavior was partially due to the breaking down of the formed aggregates in addition to the realignment of the aggregates toward the shear flow direction . Another assumption for the fat-mimic mechanism is the emulsification effects where the fat replacers may form an emulsifier layer or oil layer on the respective surfaces for lubrication, depending on the stability of emulsion gel microparticles . For those with high stability , the oil droplets are entrapped by interacting with the inner surface of protein particles during mastication. The outer surface of protein particles contacts with other macromolecules (e.g., starch, proteins) in the food matrix. Since the oil droplet inside the emulsion gel microparticles has a low glass transition and high flexibility, the outer layer that made up of protein particles can act as a filler. When experiencing force such as chewing, the particles slide to each other and deform to reduce the friction and increase the creaminess. For emulsion-type particles with limited stability, during mastication, they can be broken down into small fragments at a small deformation with the release of entrapped oil. The released oil lubricates the foods and provides a smooth mouth perception . For a certain type of fat replacers, a set of fat-mimic mechanisms may occur which requires a comprehensive assessment . 5. Conclusions and Future Trends In summary, designing protein-based fat replacers is essential to improve the quality attributes of low-fat and fat-free food products; although, they are more costly compared to those of carbohydrate-based ones. Microparticulated proteins, as the dominant fat replacers, are produced mainly by thermal-mechanical treatment. Other fabrication methods, such as anti-solvent precipitation and enzymatic hydrolysis, have also been used with less heat requirement. Microgel particles as a novel type of fat replacement receives increasing attention. With the incorporation of plant oil, it could provide a better lubrication effect and creaminess. The mechanisms of protein-based fat replacers remain unambiguous. The ball-bearing effect, protein aggregates/particle deformation and disassembly, and their emulsification contribute significantly to the lubrication and flow properties of fat-replacer incorporated food products for desirable texture and mouthful feeling. Although much progress has been made in the production, modification, and/or application of fat replacers, the development of novel protein-based fat replacers in a greener way is still in its infancy. The thermal-mechanical treatment requires a large amount of energy input to trigger protein unfolding and aggregation, which, in turn, levels up the cost of the final products and is not environmentally friendly. The modification of the protein structure using processing or bioprocessing to promote their aggregating capacity under heat requires further investigation. Most of the protein-based fat replacers do not have the heat melting property except the prolamin-based ones. The incorporation of zein particles to those of others with high compatibility and ideal fat-mimic effects is worthwhile to explore. There is a growing trend of using plant proteins as fat replacers and each of them has its own structural, physiochemical, and mechanical properties. Yet, the maximum amount of fat that can be replaced with plant-based protein is ambiguous. The evaluation of different protein sources, as well as combining plant-based with other animal-based proteins, such as whey, or other non-protein ingredients, such as carbohydrates , to test their fat-mimicking potential, needs further attention. In addition, tribology combined with rheological textural analysis is dominant to assess the lubrication of fat replacer-incorporated low-fat products . The difference between instrumental analysis and human mouth sensing implies a combination of the two is more accurate to reflect the true fat-mimic capacity of protein-based fat replacers and needs focused attention. Acknowledgments The authors would like to acknowledge the support from the Department of Animal, Veterinary and Food Sciences in the University of Idaho. Author Contributions N.N. and D.C. designed and wrote the manuscript. L.A. edited the manuscript. 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 A schematic showing the types of protein-based fat replacers. Figure 2 A schematic showing the production of protein isolates and concentrates. Figure 3 A schematic illustrating the production of microparticulated proteins using thermal-mechanical treatments. Figure 4 A schematic showing the formation of protein-based microgels. Figure 5 A schematic showing the mechanisms of fat-mimic effects. foods-12-00957-t001_Table 1 Table 1 A summary of different types of protein-based fat replacers, their fabrication methods, and applications. Type Protein Source Fabrication Method Particle Size (mm) Application References Protein concentrate/isolate Whey concentrates Ultrafiltration at 40-45 degC, membrane cut-off 10 kDa - Reduced fat cheese Soy protein fractions Protein solubilization at pH 8 and 9 for 1 h, separate oil-rich cream by centrifuge, protein precipitation in pH 4.5 and 5 by adding 1 M HCl hold for 1 h 10-250 Meat analog Protein microparticles Microparticulated soy protein/egg white protein Heated 95 degC for 5-15 min with continuous stirring 2-20 Drinkable or semi-solidprotein-rich foods Microparticulated whey, potato, and pea proteins Heating to 10 degC above denature temperature of proteins, held for 10 min, and cooling in a concentric cylinder with 100-150 s-1 shear rate 20-250 - Microparticulated whey proteins Extrusion at 90 degC with a screw speed of 200-1000 rpm 2-7 Reduced-fat yogurt Potato protein Extrusion at 80 degC and 800 rpm screw speed, pH 6.9 9-110 Fat-reduced dessert Pea protein Extrusion cooking at 100 degC with 600 rpm screw speed 10-75 Milk dessert Egg white protein Heated at 75 degC for 13 min, followed by high-shear homogenization at 10,000 rpm for 60 s 9.4 Salad dressing Microparticulated whey protein Heated at 85 degC for 15 min and sonicated at 20 kHz for 1 min 0.01-2 Reduced-fat cheese emulsion Soy protein hydrolysate Alcalase 2.4 L hydrolysate followed by heating at 90 degC for 20 min and homogenized at 8000 rpm for 6 min 7.1-9.3 Ice cream Pea protein hydrolysate Hydrolysis by Alcalase 2.4 L for 3 min, followed by heating at 85 degC for 10 min - - Zein/ carboxymethyl dextrin Zein was dissolved in 80% ethanol and then added to a dextrin solution, followed by the removal of ethanol 0.1-0.6 Sausage Protein-polysaccharide complex Oat b-glucan/marine collagen peptide Oat b-glucan was dissolved in buffer solution at pH 3 (glycine-HCl buffer) at 12% concentration and mixed with marine collagen peptide solution at different ratios. The samples were stirred at 25 degC for 4 h, then subjected to high pressure at 400-500 MPa for 30 min - Sausage Pea protein/pectin Pea protein powder was added to solutions containing different ratios of pectin to reach 15% (w/v) of protein concentrate. The dispersion was stirred at 1500 rpm for 1 h at room temperature followed by adjusting the pH to 6.5 using 2 N NaOH - - Protein microgels Canola protein microgels Heated at 90 degC under stirring for 1 h, stored at 4 degC to form a gel followed by homogenization and complexation with polysaccharides 1-100 Pickering emulsion stabilization as a potential fat replacer Whey protein emulsion gel microparticles Heated at 90 degC for 20 min, followed by the addition of oil, homogenization, and addition of glucono-delta-lactone 0.3-300 Low-fat yogurt Whey protein/alginate microgels Whey protein was heated at 80 degC for 30 min followed by alginate addition - - Soy protein microgels Salt-induced coacervation followed by heating at 80 degC for 30 min under stirring 1-3 - Note: The "-" means "it is not reported". 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PMC10000405 | Allogeneic hematopoietic stem cell transplantation (HSCT) represents the best therapeutic option for many patients with acute myeloid leukemia (AML). However, relapse remains the main cause of mortality after transplantation. The detection of measurable residual disease (MRD) by multiparameter flow cytometry (MFC) in AML, before and after HSCT, has been described as a powerful predictor of outcome. Nevertheless, multicenter and standardized studies are lacking. A retrospective analysis was performed, including 295 AML patients undergoing HSCT in 4 centers that worked according to recommendations from the Euroflow consortium. Among patients in complete remission (CR), MRD levels prior to transplantation significantly influenced outcomes, with overall (OS) and leukemia free survival (LFS) at 2 years of 76.7% and 67.6% for MRD-negative patients, 68.5% and 49.7% for MRD-low patients (MRD < 0.1), and 50.5% and 36.6% for MRD-high patients (MRD >= 0.1) (p < 0.001), respectively. MRD level did influence the outcome, irrespective of the conditioning regimen. In our patient cohort, positive MRD on day +100 after transplantation was associated with an extremely poor prognosis, with a cumulative incidence of relapse of 93.3%. In conclusion, our multicenter study confirms the prognostic value of MRD performed in accordance with standardized recommendations. acute myeloid leukemia AML measurable residual disease MRD flow cytometry stem cell transplantation Instituto de Salud Carlos III/Subdireccion General de Investigacion Sanitaria Fondo de Investigacion en SaludPI17/02283 Red de terapia celularTERCEL RD16/0011/0035 RICORSRD21/0017/0016 This work was supported by Instituto de Salud Carlos III/Subdireccion General de Investigacion Sanitaria Fondo de Investigacion en Salud (proyect PI17/02283), Red de terapia celular (TERCEL RD16/0011/0035), and RICORS (RD21/0017/0016). pmc1. Introduction Acute myeloid leukemia (AML) is a heterogeneous disease with different molecular and prognostic characteristics . Allogeneic hematopoietic stem cell transplantation (HSCT) represents the best therapeutic option for many patients with high-risk AML . However, relapse remains the main cause of mortality after transplantation. The prognostic value of measurable residual disease (MRD) in AML patients is well recognized. Accordingly, 2017 European LeukemiaNet (ELN2017) introduced the new response category, complete remission (CR) without minimal residual disease . The techniques used for MRD monitoring must be applicable, sensitive, specific, and reproducible. In this regard, quantitative polymerase chain reaction (PCR), and more recently, next generation sequencing and digital PCR, have a high sensitivity and applicability. However, they are limited to patients with certain genetic alterations, therefore, their applicability in routine clinical practice can be reduced. Multiparametric flow cytometry (MFC) is almost universally applicable, but display a lower sensitivity; the development of new generation flow (NGF) allows to achieve a similar sensitivity compared to molecular techniques . Nevertheless, NGF is only validated in multiple myeloma and B acute lymphoblastic leukemia . An elevated level of expertise is needed to perform MFC-MRD, and the harmonization of the technical issues for the measurement of MRD is necessary. According to ELN consensus, MRD by MFC must integrate the "leukemia-associated phenotype (LAP)" assessment, plus the "different from normal (DfN)" approach . Other recommendations include considering the cut-off point of 0.1% to define MRD as positive, the use of prospectively validated panels, such as the Euroflow consortium , and the use of standardized flow cytometers . However, there are no studies reporting routine clinical practice based on these standards. In 2022, the update of the ELN classification emphasized the relevance of the early MRD evaluation that can modify the individual risk classification . In addition, ELN 2017 and 2022 imply a broad genetic characterization, which is not considered in this study, since it includes patients transplanted from 2012 to 2020, who are therefore classified according to ELN 2011. The detection of MRD by MFC in AML patients undergoing HSCT is a powerful predictor of outcome, and might allow individualized therapeutic strategies, as shown in different studies . However, multicenter and standardized studies are lacking. We performed a retrospective multicenter study to evaluate the prognostic value of MRD by second generation of MFC among patients undergoing HSCT, using recommendations from the Euroflow consortium. 2. Methods 2.1. Patients A retrospective analysis was performed, including 295 AML patients treated according to PETHEMA protocols, undergoing HSCT from 2012 to 2020 in 4 transplant centers. CR was defined, based on ELN2011, as less than 5% of blasts in bone marrow (BM), and no evidence of extramedullary leukemia . All patients who had flow cytometric evaluation prior to transplantation were included in the analysis. All patients provided written informed consent in accordance with the Declaration of Helsinki. This study has been approved by a formally constituted review board: C.P. S2200072, C.I. 0466-N-22, CEI de los Hospitales Universitarios Virgen Macarena y Virgen del Rocio (Protocolo V.1-21 February 2022). 2.2. Detection of Measurable Residual Disease by Second Generation Flow Cytometry BM aspirate was obtained before starting the conditioning regimen, and at day one hundred after HSCT. The MRD was carried out using 8-color panels based on Euroflow protocols . The Euroflow consortium periodically organizes an Internal Quality Assurance (QA) program to verify that the laboratories work in a standardized way, and according to the published recommendations. Two centers included in the study participate in the QA program organized since 2015, and another one from 2016. Supplementary Table S1 shows the information from the QA program. All the centers carry out calibration and stability controls of the cytometers daily, with CS&T (Becton Dickinson, San Jose, CA, USA) and SPHEROTM Rainbow Calibration Particles, EuroFlowTM. If it fails, and failure is not due to a fluid problem, the technical service is notified. Normal cells were used for internal control, case by case. Fifty mL of BM per tube were stained with monoclonal antibodies. After 30 min of incubation at room temperature in the dark, erythrocytes were lysed, and the sample was washed. The samples were acquired in 8-color digital cytometers FACSCanto II (Becton Dickinson, San Jose, CA, USA). Cytometers were calibrated and compensated according to Euroflow protocols using the Diva software (Becton Dickinson) . More than five hundred thousand viable cells per tube were acquired. For the design of the MRD, the different laboratories used panels from the myelodysplastic syndrome (MDS) panel of Euroflow (T1, T2, and T3 in more than 80% +- T4 when lymphoid markers were expressed, or when the phenotype at diagnosis was not available), along with additional tubes, depending on the patient's specific "leukemia-associated phenotype" (LAP). The tubes that include the LAP had to include the 4 backbones, HLADR, CD45, CD34, and CD117, together with another 4 antibodies at the discretion of each laboratory, in accordance with the recommendations by ELN for MRD . In 240 cases, tubes were added to the maturation tubes of the Euroflow MDS diagnostic panel. The combinations for LAP analysis are shown in Supplementary Table S2. When the phenotype of the blasts at diagnosis corresponded to monocytes, more than 1 tube associated with LAP was designated. Analysis was performed with Infinicyt software 1.6 to 2.0 (Cytognos). Both LAP assessment plus the "different from normal (DfN)" approach were used to analyze MRD according to the criteria of each laboratory. Any measurable MRD level was considered as positive. A representative MRD image is shown in Supplementary Figure S1. The abnormal population was quantified as a percentage of the total viable cells (including the erythroblast population). There was no reference laboratory, but each laboratory independently carried out the analysis of its samples. All centers carried out the same initial strategy of population selection analysis based on the 4 common markers. The 4 centers confirmed the MRD in more than 1 tube. MRD was considered assessable when the peripheral blood cell counts were recovered. Maturation patterns were analyzed. MRD assays were performed by 2 experts, and most included the lead analyst. A comparative study of 6 MRD samples was carried out between the 4 centers (Supplementary Table S3). MRD included in this study achieved a sensitivity of 0.1%, and more than 90% was 0.01%. The level of sensitivity was considered based on the following conditions: number of acquired events, viable cells, patient's LAP if available, and bone marrow status (representation of bone marrow cells: mast cells, plasma cells, B precursors...). We considered the marrow evaluable for analysis if mast cells, red series, and less than 80% mature neutrophils were found. A cluster of 20 cells with phenotypic abnormalities was needed for the detection of MRD. 2.3. Statistical Analysis The objective of our study was to evaluate the impact of MRD on the outcome of patients with AML undergoing HSCT. The following endpoints were analyzed: cumulative incidence of relapse (CIR), acute and chronic graft versus host disease (GvHD), non-relapse mortality (NRM), overall survival (OS), and leukemia free survival (LFS). Probabilities of OS and LFS were calculated using the Kaplan-Meier method. Cumulative incidence functions were used to estimate CIR, NRM, aGvHD, and cGvHD rates in the setting of competing risks. OS was calculated from the time of transplantation to death from any cause, and those who survived were censored at last follow-up. LFS was calculated from the time of transplantation to relapse or death, and those patients who did not obtain a CR were considered events. Neutrophil recovery was considered as more than 0.5 x 109/L for at least 2 consecutive days, and platelet engraftment was more than 20 x 109/L platelets for at least 2 consecutive days. Comparisons were performed using the log-rank test for LFS and OS, and Gray's test for RI and NRM. The impact of age, type of conditioning, GvHD prophylaxis, ELN classification, and MRD (according to ELN criteria) was evaluated both in univariate and multivariate analysis. Cox proportional hazards regression models were constructed for OS and LFS. GvHD was diagnosed according to NIH criteria. The occurrence of chronic GvHD was treated as a time-dependent covariate. Patients who lived more than 100 days after transplantation were evaluated for chronic GvHD. Cumulative incidences were calculated with the cmprsk package for R version 2.14.0, and other analyses were performed using SPSS 20.0 and Stata 14.2. 3. Results 3.1. Patient Characteristics A total of 295 patients were included into the analysis; Table 1 shows the characteristics of the patients. Of them, 285 (96.7%) were in CR at the time of HSCT, 207 had negative MRD (MRD neg), in 21 patients MRD was positive but below 0.1% (namely MRD-low), and in 57 patients MRD was positive and greater than or equal to 0.1% (MRD-high or MRD >= 0.1). Ten patients had active disease. A total of 47.1% received HSCT from a matched sibling donor, while 39.7% had unrelated donors. A total of 59.7% of patients received myeloablative conditioning. Considering only patients who were in CR at the time of transplant, no significant differences were observed between patients with MRD positive (MRD pos) or negative, except for age, the prior being slightly older (54.5 vs. 51 years, p = 0.02), and GvHD prophylaxis, with MRD pos patients receiving more T-cell depletion-based approaches (Table 1). 3.2. Transplant Toxicities and GvHD Regarding the toxicity of the procedure, no patient in the MRD pos, and three in the MRD neg group, had neutrophil graft failure. Regarding neutrophil engraftment, no differences were observed between MRD neg and MRD pos patients: median of 16 days (range 8-385) among MRD pos patients, versus 16 days (range 9-181) for MRD neg patients. Regarding platelet engraftment, two patients in both MRD pos and MRD neg groups did not engraft. There were no differences in the speed of platelet engraftment between MRD pos (15, range 5-171) versus MRD neg patients (12, range 3-1096) (Table 2). One hundred and eighty-four (62.4%) patients developed acute GvHD: 56 presented grade one, 100 grade two, 15 grade three, and 12 grade four. Chronic GvHD was observed in 121 patients (41%); in 60 (20%) of them it was mild, and in 61 (20.7%) it was moderate/severe. There were no differences in the incidence of acute or chronic GvHD between MRD pos and MRD neg groups (Table 2). On the other hand, 76 MRD positive patients with were evaluable for acute GvHD, and 32 of them relapsed. Of the patients, 63.5% (28 of 44) who did not relapse developed acute GvHD, versus 40.6% (13 of 32) of patients who relapsed (p = 0.063). In other words, we observed a trend towards a higher risk of aGvHD in MRD positive patients who did not relapse, as compared to those who did. No significant differences in chronic GvHD were observed: 61.3% (27 of 44) of patients who did not relapse developed chronic GvHD, versus 71.9% (23 of 32) of patients who did (p = 0.5). 3.3. Impact of MRD Prior to Transplantation on Outcomes after HSCT Overall survival at 2 and 5 years was 69% [95% CI 63.18-74.18] and 58.4% [95% CI 52.4-63.9], respectively, and the LFS at 2 and 5 years was 57.8% [95% CI 50.8-64.7%] and 50.4% [95% CI 44-57], respectively. Among patients in CR, MRD levels significantly influenced outcomes, with OS and LFS at 2 years of 76.7% [95% CI 70.1-82] and 67.6% [95% CI 60.6-73.6] for MRD neg patients, 68.5% [95% CI 42.1-84.7] and 49.7% [95% CI 26.4-69.3] for MRD-low patients, and 50.5% [95% CI 36-63.2] and 36.6% [95% CI 23.7-49.5] for MRD-high patients, respectively (MRD >= 0.1) (p < 0.001) . Next, we attempted to confirm the prognostic value of the ELN17 proposed cut-off (0.1%) to identify patients at a higher risk of relapse and, therefore, we combined the MRD neg and MRD-low groups into MRD < 0.1: at 2 and 5 years, the respective values for these MRD < 0.1 patients were 76% [95% CI 69.7-81.1] and 66.7% [95% CI 59.1-73.1] for OS (p < 0.001 as compared to those with MRD >= 0.1), and 66% [95% CI 59.3-71.8] and 58.1% [95% CI 50.6-64.8] for LFS (p < 0.001 as compared to MRD >= 0.1), respectively. In Figure 1, the OS and LFS of the three groups MRD < 1, MRD >= 0.1, and active disease are shown (p < 0.001). In univariate analysis, age (HR = 1.03 [95% CI 1.01-1.04], p = 0.002 and HR = 1.02 [95% CI 1.01-1.03], p = 0.008), conditioning (HR = 1.73 [95% CI 1.18-2.53], p = 0.005 and HR = 1.43 [95% CI 1.01-2.01], p = 0.041), adverse risk of ELN2011 (HR = 3.26 [95% CI 1.62-6.55], p = 0.001 and HR = 3.75 [95% CI 1.98-7.09], p < 0.001), and MRD >= 0.1 (HR = 2.51 [95% CI 1.64-3.83], p < 0.001 and HR = 2.29 [95% CI 1.55-3.38], p < 0.001) significantly influenced OS and LFS, respectively (Supplementary Table S4). In multivariate analysis, adverse risk of ELN2011 (HR = 2.42 [95% CI 1.18-5.00], p = 0.016 for OS and HR = 3.16 [95% CI 1.64-6.07], p = 0.001 for LFS) and MRD >= 0.1 (HR = 2.07 [95% CI 1.26-3.39], p = 0.004 for OS and HR 2.1 [95% CI 1.36-3.29], p = 0.001 for LFS) significantly influenced OS and LFS (Table 3). In multivariate time-dependent analysis (time-dependent variable GvHD), the adverse risk group, according to ELN2011 (for OS HR= 2.8 95% [CI 1.33-5.89], p = 0.006 and for LFS HR = 3.43 [95% CI 1.76-6.7], p < 0.001), and MRD >= 0.1 before transplant (for OS HR = 1.98 [95% CI 1.26-3.11], p < 0.001 and for LFS HR = 1.89 [95% CI 1.25-2.86], p < 0.001) significantly influenced the outcome (Supplementary Table S5). Next, we attempted to identify whether these differences, in terms of OS and LFS between MRD >= 0.1 and MRD < 0.1, were due to a higher RI and/or NRM. Considering only patients in CR, CIR at 2 and 5 years were significantly lower among MRD < 0.1 patients: 22% [95% CI 17-28.1%] and 27% [95% CI 21-33.5%], versus 46.5% [95% CI 32.4-59.5%] and 50% [95% CI 34.8-63.2%] among MRD >= 0.1 patients, respectively, p = 0.0005. By contrast, no differences were observed in terms of NRM (11.7% [95% CI 7.9-16.3%] and 14.8% [95% CI 10.1-20.4%] for MRD < 0.1, and 16.9% [95% CI 8.2-28.3%] and 23.7% [95% CI 11.9-37.8%] for MRD >= 0.1 p = 0.2), . In univariate analysis, age (HR = 1.02 [95% CI 1-1.04], p = 0.037), adverse risk of ELN2011 (HR = 4.88 [95% CI 1.99-11.99], p = 0.01), and MRD >= 0.1 (HR = 2.29 [95% CI 1.43-3.65], p = 0.001) significantly influenced CIR. As far as NRM is concerned, only the type of donor had a statistically significant influence in univariate analysis: unrelated donor (HR = 2.04 [95% CI 1.06-3.95], p = 0.033) and haplo-identical donor (HR = 2.73 [95% CI 1.16-6.42], p = 0.021) (Supplementary Table S4). Finally, in multivariate analysis, haplo-identical donor (HR = -0.27 [95% CI 0.11-0.67], p = 0.005), T-cell depletion (HR 1.78 [95% CI 1.01-3.14], p = 0.045), adverse risk ELN2011 (HR = 4.37 [95% CI 1.67-11.4], p = 0.003), and MRD >= 0.1 (HR = 2.47 [95% CI 1.4-4.33], p = 0.002) significantly influenced CIR. On the other hand, the use of haplo-identical donor (HR = -2.63 [95% CI 1.04-6.65], p = 0.042) significantly influenced NRM (Table 3). In Supplementary Table S6, we describe 43 patients who had MRD pos and did not relapse. Of these 43 patients, 30 (70%) developed acute GvHD (70%): 15 grade two, 4 grade four, and the rest grade one. Nineteen developed chronic GvHD (44.2%). Fourteen patients had MRD < 0.1, and three of them died because of an infection within one year after transplantation. The remaining 30 had MRD >= 0.1 and 11 (37%) of them have died, 8 before one year post-transplant because of infections (2 bilateral pneumonia), 2 due to GVHD, 1 due to veno-occlusive disease, 1 due to ureteral carcinoma, and another of unknown cause. Four of these thirty patients are still alive with a follow-up of less than 1 year. 3.4. Impact of MRD before Transplantation on OS and LFS among the Different ELN2011 Subgroups and Conditioning Regimens MRD before transplantation also identified patients with different outcomes within the ELN2011 subgroups: OS and LFS at 2 years among high-risk ELN2011 patients were 58% and 41.1% in MRD < 0.1 vs. 39.3% and 20% for MRD >= 0.1 patients, p = 0.16 and p = 0.216, respectively; for intermediate risk: 77.6% and 70.2% for MRD < 0.1 vs. 60.6% and 43.5% among MRD >= 0.1 patients, p = 0.0.018 and p = 0.0037, respectively; and for favorable ELN2011 risk: 88.6% and 82.9% among MRD < 0.1 vs. 48.5% and 49.1% for patients with MRD >= 0.1, p= 0.0098 and p= 0.0315, respectively . Finally, MRD level did influence the outcome, irrespective of the conditioning regimen: patients with MRD < 0.1 before transplantation had a better OS and LFS at 2 years (82% and 71.4% among those who received myeloablative conditioning, and 65% and 57.6% among those who received reduced intensity conditioning, respectively) than those who had MRD >= 0.1 prior to transplantation (56% and 44.4% for myeloablative, and 43% and 25.5% for those who received reduced intensity conditioning) (p < 0.001) . 3.5. Impact of MRD on 100 Days after HSCT Next, we analyzed the prognostic value of MRD at 100 days post transplantation; at 2 years, OS and LFS were significantly higher in patients with MRD < 0.1 on day +100 (83% and 76% in MRD < 0.1 vs. 76% and 7% in MRD >= 0.1, respectively, p < 0.001) . Similarly, CIR at 2 years was significantly lower in patients with MRD < 0.1 (12.8% [95% CI 8.4-18%] as compared to 93.3% [95% CI 41.4%-99.5%]) among those with MRD >= 0.1, p < 0.001. By contrast, no differences were observed in terms of NRM (10.6% [95% CI 6.7-15.6] in MRD < 0.1 vs. 0% in in MRD >= 0.1, p = 0.19). However, the main limitation for the analysis of the MRD at 100 days after transplantation is that only 16 patients with positive MRD remained in CR at this time-point. 4. Discussion Numerous studies have described the prognostic value of measurable residual disease after induction and/or consolidation and, based on these results, it is currently used to tailor the intensification strategy in patients with AML . Terwijn et al. showed the independent prognostic value of MRD >= 0.1% by MCF after induction and consolidation therapy, identifying a subgroup of patients with higher risk of relapse . Similarly, a second multicenter prospective study identified that patients with positive MRD had a poor outcome . On the other hand, Balsat et al. showed the prognostic value of the detection of mutated NPM1 in peripheral blood after induction, thus identifying a subgroup of patients who would be candidates for transplantation . Likewise, RUNX1-RUNX1T1 MRD monitoring also identifies a subgroup of patients at high risk of relapse . Moreover, Jongen-Lavrencic et al. showed that the combination of detection of MRD by next-generation sequencing and flow cytometry has additional prognostic value in terms of relapse and overall survival . Based on these findings, Cornelissen et al. proposed an algorithm, considering not only the risk subgroup at diagnosis and the performance status of the patients, but also the levels of MRD . Unfortunately, although HSCT is considered the best option for patients with persistent MRD after first line treatment, tumor load, even at the MRD level, is one of the variables with the highest impact on outcome, after allogeneic stem cell transplantation, as described in different studies using either molecular or flow cytometry techniques. Regarding the latter, available studies have not used international standardized protocols; different cut-off values have been used, and the number of combinations of the fluorochrome-conjugated antibodies used, or the analysis strategy, have also greatly varied. Likewise, the need to maintain calibration and compensation protocols is not considered. Araki et al. showed that patients in CR with positive MRD at the time of transplantation had a similar outcome compared to patients with active disease with OS at 3 years, of 26% and 23%, respectively . In this study, 1 million events were acquired, and a panel of 10 colors with three combinations of antibodies is carried out, considering any level of detection to determine positive MRD. However, it is a single center study conducted by the same group of hematopathologists. Additionally, a different from normal approach is used, considering a population showing a deviation from antigen expression patterns on reactive or regeneration hematopoietic cells. However, this approach might not display a uniform sensitivity in all cases. Moreover, it is not considered an international standardization of cytometers, allowing an adequate reproducibility within different laboratories. Likewise, in the same group in the context of myeloablative transplantation, the presence of MRD before or after transplantation identified patients with poor outcome As in our study, they observed that 16 patients with MRD pos after transplantation had shorter OS and RFS. However, the MRD measurement is performed at an earlier post-transplant period, between days +28 and +35. Other studies that show the prognostic value of positive MRD use numbers of fluorescence less than six , or combine the detection of disease with low-sensitivity techniques, such as karyotype or fluorescence in situ hybridization (FISH) . In a recent retrospective study, patients with monosomal karyotype had a higher likelihood of MRD positivity by MFC prior to transplant, with worse OS and higher relapse risk than those without it . However, in multivariate analysis, only MRD positivity was associated with a shorter survival. The current study has been conducted in routine clinical practice, in real life, outside of a specific trial, in four centers that had to meet certain requirements. Three laboratories participated in the quality control organized within the Euroflow QA program. Two different approaches were used to determinate MRD: "leukemia-associated phenotype (LAP)" and "different from normal (DfN)". The latter allowed us to identify MRD even if the diagnostic phenotype was not available, or in case of changes in the phenotype during the disease . Both strategies have been used, as recommended by ELN . All laboratories work with the same quality criteria, and each one carried out its own analyses by experts in clinical cytometry. In the current study, we confirmed the prognostic value of MRD monitoring, both post-allogeneic stem cell transplantation. In fact, cumulative incidence of relapse was significantly higher, both if we consider patients with MRD pos as compared to MRD neg, and by using the cut-off value suggested by ELN, and this difference in relapse incidence significantly influenced OS and LFS. Considering ELN2011 subgroups, MRD also allowed the identification of subgroups of patients with different prognoses among favorable and intermediate ELN2011, while in the adverse risk group, no clear difference was observed. The number of patients included in each subgroup, when the analysis is separately performed, might explain the lack of statistically significant differences in this subgroup, in terms of overall survival. Alternatively, the poor outcome of these patients might not be influenced by the MRD levels. Further studies would be required to elucidate this point. An area of current interest, in the context of allogeneic transplantation, is whether the therapeutic strategy should be modified in those patients with positive MRD, before transplantation. In fact, several studies have suggested that patients with positive MRD prior to transplant might benefit from receiving myeloablative conditionings . However, in a recent retrospective study of 746 patients, Morsink et al. observed that in all patients, regardless of the type of conditioning, the risk of relapse, relapse free survival, and OS were higher in patients with positive, as compared to those with negative, MRD . Similarly, no effect of the conditioning regimen intensity on OS was observed in NPM1 mutated AML patients who remained MRD positive . In the same way, in the current analysis, regardless of the type of conditioning, the presence of MRD by flow cytometry implied a poor prognosis. Recently, Paras et al. conducted a retrospective study of 810 patients, showing that the conditioning regimen can influence the ability to eliminate MRD; however, the elimination of MRD in non-myeloablative regimens had a greater impact on the outcome . With these contradictory results, it remains unclear whether MRD should determine the choice of conditioning regimen. An alternative approach would be to identify these patients for alternative therapy after HSCT, such as withdraw of immunosuppression, hypomethylating agents , infusion of donor lymphocytes , or venetoclax , among other approaches. For example, the RELAZA2 prospective study demonstrated that treatment with azacytidine in patients with MRD pos could avoid or delay hematology relapse of AML or high-risk myelodysplastic syndromes (MDS). In this regard, MRD monitoring after transplantation would further allow the identification of patients at a high risk of relapse, and establish therapeutic maneuvers. In our patient's cohort, positive MRD on day +100 after transplantation was associates with an extremely poor prognosis, with a CIR of 93.3%. It is possible that the identification of MRD should be conducted in an earlier post-transplant period, to assess any preventive strategy to avoid relapse. Moreover, in our study, those patients who reach day +100 post-transplant and persist, or have a new positive MRD, have an unfavorable short-term prognosis, regardless of the status of the pre-transplant MRD. In this way, a recent study of Paras et al. showed that the dynamics of MRD before, and early after transplantation (+20 or 40 days after transplantation), improve the accuracy of risk assessment; in that study, patients with MRDpos/MRDpos and MRDneg/MRDpos had high relapse rates and poor survival estimates . In relation to the type of donor, is relevant to point out that Yu et al. have shown that a haplo-identical donor might increase the graft versus leukemia effect . Therefore, the positivity of MRD before transplant could modify the selection of the donor. Other authors have identified the CD34+/ stem cell (LSC) phenotype, and have shown its prognostic value, both at diagnosis and during follow-up . Furthermore, this phenotype might be used in combination with the MRD assessment in a single tube combining six markers . Therefore, future studies might allow the further improvement of MRD analysis, for example, by incorporating the LSC phenotype into the standardized MRD strategy currently used. The main limitation of this study is its retrospective nature over a long period of time, in which changes have been incorporated to the treatment according to the molecular results. Likewise, GvHD conditioning and prophylaxis vary during this period. On the other hand, each center carried out its analysis independently. However, this further reinforces the fact that a positive MRD performed with standardized technical conditions has prognostic value in real life. 5. Conclusions Our multicenter study confirms the prognostic value of MRD performed in accordance with standardized recommendations. Regardless of the conditioning regimen, positive MRD maintains its poor prognostic value, and might allow the identification of patients who are candidates to receive early post-transplant therapeutic procedures. Acknowledgments This work was supported by Instituto de Salud Carlos III/Subdireccion General de Investigacion Sanitaria Fondo de Investigacion en Salud (proyect PI17/02283), Red de terapia celular (TERCEL RD16/0011/0035), and RICORS (RD21/0017/0016). The authors TCV, OPL, AYB, ECV, AST, MBV, and CPM belong to Grupo Espanol de Citometria de Flujo Hematologica. The authors declare that they have no conflict of interest. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Representative image of MRD analysis by flow cytometry. Figure S2: Impact of MRD levels in OS and LFS. Table S1. The information per fluorchrome from QA program, Table S2. Designed panels to LAIP analysis, Table S3. Comparative analysis of MRD samples in the 4 laboratories: The table represents the MRD value determined by each laboratory, Table S4. Univariate analysis of CIR, NRM, OS and LFS, Table S5. OS and LFS according to multivariate time-dependent analysis (time-dependent variable GvHD, Table S6. Evolution of patients who did not relapse with positive MRD prior to transplantation. Click here for additional data file. Author Contributions T.C.-V. and J.A.P.-S. conceived the idea and designed the study. T.C.-V., O.P.-L., A.Y.B., E.C.V., A.S.T., M.B.V., M.R.S., C.Q.C., E.P.L., M.S.-R., C.P.-M., P.M. and J.A.P.-S. supplied study material or patients. T.C.-V., O.P.-L., A.Y.B., E.C.V., A.S.T., M.B.V., C.Q.C. and C.P.-M. analyzed flow cy-tometry data. T.C.-V. and O.P.-L. performed statistical analysis. T.C.-V., O.P.-L., E.R.A. and J.A.P.-S. analyzed and interpreted data. T.C.-V. and J.A.P.-S. wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement C.P. S2200072, C.I. 0466-N-22, CEI de los Hospitales Universitarios Virgen Macarena y Virgen del Rocio (Protocolo V.1-21 February 2022). Informed Consent Statement All patients provided written informed consent in accordance with the Declaration of Helsinki. This study has been approved by a formally constituted review board: C.P. S2200072, C.I. 0466-N-22, CEI de los Hospitales Universitarios Virgen Macarena y Virgen del Rocio (Protocolo V.1-21 February 2022). Data Availability Statement The original data will be available by request to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Impact of MRD levels in OS and LFS, considering MRD < 0.1%, MRD >= 0.1%, and group of active disease. Figure 2 Impact of MRD in CIR and NRM: (A) CIR at 2 and 5 years were significantly lower among those with MRD >= 0.1. (B) However, no differences were observed in terms of non-relapse mortality. Figure 3 Impact of MRD in OS and LFS according to risk group ELN2011: survival was significantly worse in patients with MRD >= 0.1 in favorable (A,D) and intermediate groups (B,E). However, no differences were observed in the adverse risk group (C,F). Figure 4 Impact of MRD in OS and LFS, according to conditioning regimen. Patients with MRD < 0.1 before transplantation had a better OS (A) and LFS (B) at 2 years, with both types of conditioning. Figure 5 Impact of MRD on day +100 after transplantation. At 2 years, OS and LFS were significantly higher in patients with MRD >= 0.1 on day +100. cancers-15-01609-t001_Table 1 Table 1 Characteristics of the patients according to MRD before transplantation. All Group (n = 295) MRD Negative (n = 207) MRD Positive (n = 78) p-Value AGE mean (range) 51 (2-71) 51 (2-71) 54.5 (18-69) 0.02 Recipient Gender, n (%) Male 148(50.2) 102(49.3) 40(51.3) 0.63 ELN2011, n (%) favorable intermediate I intermediate II adverse 47 (15.9) 57 (19.3) 111 (37.6) 70 (23.7) 31 (15) 48 (23.2) 79 (38.2) 44 (21.3) 15 (19.2) 8 (10.3) 30 (38.5) 21 (28.2) 0.217 Disease Status at transplant, n (%) 1st CR 2nd CR Others CR Active disease Aplasia 235 (79.7) 28 (9.5) 19 (6.4) 10 (3.4) 3 (1) 176 (85) 17 (8.2) 13 (6.3) 1 (0.5) 0 59 (77.6) 11 (14.5) 6 (7.9) 0 2 0.271 Donor, n (%) Matched sibling Unrelated donor Haplo-identical donor 139 (47.1) 117 (39.7) 38 (12.9) 103 (49.8) 82 (39.6) 22 (10.6) 31 (39.7) 30 (38.5) 16 (20.5) 0.092 Conditioning, n (%) Myeloablative No myeloablative 176 (59.7) 117 (40.4) 119 (57.5) 88 (42.5) 50 (64.1) 28 (35.9) 0.781 Conditioning Therapy, n (%) BUCy BUCy + Thiothepa FLUBU FLUBU + Cy FLUBU + THIOTHEPA FLUBU + THIOTHEPA + ATG FLUBU + ATG Cy TBI +- ATG FLUMEL +- Thiothepa Others 56 (19) 3 (1) 162 (54.9%) 8 (2.7%) 42 (14.2) 2 (0.7) 2 (0.7) 5 (1.3) 7 (2.3) 8 (2.7) 44 (21.3) 1 (0.5) 113 (54.6) 5 (2.4) 33 (15.9) 2 (1) 1 (0.5) 2 (1) 2 (1) 4 (1.9) 10 (12.8) 0 (0) 44 (56.4) 3 (3.8) 9 (11.5) 0 (0) 1 (1.3) 2 (2.6) 5 (6.4) 4 (5.2) 0.385 Donor gender, n (%) Male 192 (65.1) 135 (65.2) 51 (65.4) 0.945 Donor/Recipient gender, n (%) Female/male 52 (17.6) 38 (18.4) 12 (15.4) 0.807 GvHD Prophylaxis, n (%) Tacrolimus/CsA + MTX Tacrolimus + Sirolimus +- MMF Tacrolimus/CsA + MTX + ATG Tacrolimus/CsA + MMF Tacrolimus/CsA + MMF + Cy Sirolimus + MMF + Cy CsA + Pred 121 (41) 82 (27.8) 28 (9.5) 25 (8.5) 24 (8.1) 10 (3.4) 2 (0.7) 87 (42) 64 (30.9) 14 (6.7) 18 (8.7) 13 (6.2) 8 (3.9) 2 (1) 28 (35.9) 16 (21) 13 (16.6) 7 (9) 11 (14.1) 2 (2.6) 0 (0) 0.001 ELN: European LeukemiaNet; CR: complete remission; BUCy: busulfan + cyclophosphamide; FLUBU: fludarabine + busulfan; Cy: cyclophosphamide; ATG: thymoglobulin; TBI: total body irradiation; MTX: methotrexate; MMF: mycophenolate mofetil; CsA: cyclosporine A; GvHD: graft versus host disease. cancers-15-01609-t002_Table 2 Table 2 Toxicities: engraftment and GvHD. All Group (n = 295) MRD Negative before Transplantation (n = 207) MRD Positive before Transplantation (n = 78) p-Value Engraftment (YES/patients) Neutrophil Platelets 286/289 287/293 204/207 205/207 78/7 876/78 Engraftment day mean (range) Neutrophil Platelets 16 (8-385) 13 (3-1096) 16 (9-181) 12 (3-1096) 16 (8-385) 15 (5-171) 0.889 0.317 Acute GvHD, n(%) Grade 1 Grade 2 Grade 3 Grade 4 184 (62.4) 56 (19) 100 (33.9) 15 (5.1) 12 (4.1) 137 (55.6) 45 (21.7) 71 (34.3) 12 (5.8) 8 (3.9) 43 (55.1) 11 (14.1) 28 (36.8) 0 (0) 3 (3.9) 0.137 Chronic GvHD, n (%) Mild Moderate/severe 121 (59) 60 (20) 61 (20.7) 92 (44.4) 47 (22.7) 41 (19.8) 28 (35.9) 13 (16.7) 14 (17.9) 0.356 MRD: measurable residual disease; GvHD: graft versus host disease. cancers-15-01609-t003_Table 3 Table 3 Multivariate analysis considering MRD before transplantation. Variable CIR HR (95% CI) NRM HR (95% CI) OS HR (95% CI) LFS HR (95% CI) Sex male 0.93 (0.59-1.48), p = 0.785 1.0 (0.53-1.92), p = 0.980 1.05 (0.68-1.60), p = 0.837 1.01 (0.7-1.47), p = 0.852 Age 1.01 (0.98-1.04), p = 0.456 1.02 (0.99-1.05), p = 0.231 1.02 (1.00-1.04), p = 0.077 1.02 (0.99-1.04), p = 0.065 Conditioning RIC 1.17 (0.65-2.10), p = 0.595 1.32 (0.62-2.84), p = 0.467 1.65 (0.95-2.88), p = 0.077 1.32 (0.82-2.12), p = 0.248 Donor Unrelated Haploidentical 1.04 (0.64-1.69), p = 0.886 0.27 (0.11-0.67), p = 0.005 2.05 (0.94-4.50), p = 0.073 2.63 (1.04-6.65), p = 0.042 1.25 (0.79-1.99), p = 0.333 0.86 (0.43-1.69), p = 0.655 1.29 (0.87-1.94), p = 0.206 0.69 (0.37-1.29), p = 0.248 Depletion T Yes 1.78 (1.01-3.14), p = 0.045 0.56 (0.26-1.21), p = 0.138 0.94 (0.56-1.57), p = 0.812 1.13(0.73-1.76), p = 0.583 ELN_2011 Intermediate Adverse 2.51 (0.99-6.34), p = 0.052 4.37 (1.67-11.4), p = 0.003 1.09 (0.43-2.82), p = 0.851 1.45 (0.53-4.00), p = 0.470 1.51 (0.75-3.04), p = 0.243 2.42 (1.18-5.00), p = 0.016 1.88 (1.00-3.54), p = 0.05 3.16 (1.64-6.07), p = 0.001 MRD >= 0.1 before transplantation 2.47 (1.4-4.33), p = 0.002 1.10 (0.47-2.59), p = 0.821 2.07 (1.26-3.39), p = 0.004 2.1 (1.36-3.29), p = 0.001 CIR: cumulative incidence of relapse; NRM: non-relapse mortality; OS: overall survival; LFS: leukemia free survival; HR: hazard ratio; CI: confidence interval; Mielo: myeloablative; RIC: reduced intensity conditioning; ELN: European LeukemiaNet; MRD: measurable residual disease. 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PMC10000406 | Indeterminate thyroid nodules (ITN) are commonly encountered among the general population, with a malignancy rate of 10 to 40%. However, many patients may be overtreated with futile surgery for benign ITN. To avoid unnecessary surgery, PET/CT scan is a possible alternative to help differentiate between benign and malignant ITN. In this narrative review, the major results and limitations of the most recent studies on PET/CT efficacy (from PET/CT visual assessment to quantitative PET parameters and recent radiomic features analysis) and on cost-effectiveness (compared to other alternatives (such as surgery)) are presented. PET/CT can reduce futile surgery with visual assessment (around 40%; if ITN >= 10 mm). Moreover, PET/CT conventional parameters and radiomic features extracted from PET/CT imaging can be associated together in a predictive model to rule out malignancy in ITN, with a high NPV (96%) when certain criteria are met. Even though promising results were obtained in these recent PET/CT studies, further studies are needed to enable PET/CT to become the definitive diagnostic tool once a thyroid nodule is identified as indeterminate. indeterminate thyroid nodule 18F-FDG PET/CT 18F-FCH PET/CT PET metrics radiomics cost-effectiveness This research received no external funding. pmc1. Introduction Thyroid nodule prevalence depends on the evaluation tool used. In the general population, 4 to 7% and 20 to 70% have a thyroid nodule detected on palpation and on ultrasound assessment, respectively . Following thyroid nodule detection by palpation, or incidentally on imaging, guidelines recommend evaluating thyroid nodules for possible malignancy status. The first step in the evaluation process should be measuring TSH and visualizing the thyroid nodule on ultrasound (US). If the TSH level and US features are consistent with a suspicious thyroid nodule (for example, if they include microcalcifications, hypoechogenicity, irregular borders, taller-than-wide shape, the absence of a simple cyst and spongiform nodule, or extension to adjacent tissues and organs), then the next best step should be a fine-needle aspiration biopsy (FNAB) to assess the cytological characteristics of the thyroid nodule and rule out malignancy . On average, approximately 10 to 30% of thyroid nodules undergoing FNAB are classified as indeterminate on cytological examination . Some pathologists consider indeterminate thyroid nodules (ITN) to be thyroid nodules with either Bethesda category III, IV or V , while others believe that ITN should only include Bethesda III and IV due to the high rate of malignancy of Bethesda V (50-75%) . Bethesda III includes thyroid nodules classified as atypia of undetermined significance or follicular lesions of undetermined significance (AUS/FLUS), while Bethesda IV includes thyroid nodules indicative of a follicular neoplasm (FN/SFN) or a Hurthle cell neoplasm (HCN/SHCN). Bethesda V is composed of thyroid nodules suspicious of malignancy, such as papillary carcinoma, medullary carcinoma, metastatic carcinoma and lymphoma . The reported malignancy rate of ITN ranges from 10-40%, with an approximated risk of 10 to 30% for Bethesda III and 25 to 40% for Bethesda IV . In this study, ITN is defined only as thyroid nodules with a Bethesda category of III or IV. Once FNAB is repeated for Bethesda III only, then the next step in ITN management would be to either actively monitor or surgically remove the nodule. In fact, the treatment plan will depend on the nodule's clinical and imaging characteristics and patient preference . Nonetheless, an important number of patients still undergo futile surgery. Recently, to reduce unnecessary surgery, other tools have been suggested, such as molecular testing or PET/CT scan. In some cases, molecular testing was able to prevent futile surgery, but it has limitations (e.g., lack of long-term studies, accessibility, high cost) that have led researchers to review other more affordable and widely available alternatives, such as PET/CT scan. Currently, in contrast to US and FNAB, PET-CT is not recommended in the initial diagnostic work-up of ITN due to the findings of past studies that analyzed the impact and importance of PET/CT in the diagnosis process of thyroid nodules . However, with the promising development of radiomics, the use of PET/CT in the diagnostic process for thyroid nodules could increase. In this review, we present a summary of the recent literature evaluating PET/CT, including PET/CT visual assessment efficacy and utility in the initial management of ITN relative to other imaging techniques. We review the efficacy of using PET quantitative metrics to differentiate ITN histopathological status. The cost-effectiveness of PET/CT compared to alternative diagnostic tools is also reviewed. Evidence of the ability of radiomics analysis based on PET/CT imaging and its consequent model to discriminate between benign and malignant ITN is summarized. Finally, we review relevant PET/CT radiomic features (RFs) and models used to assess thyroid incidentaloma that might be extrapolated to contribute to ITN status identification. 2. Visual 18F-Fluorodeoxyglucose PET/CT Assessment Efficacy A recent double-blinded randomized controlled multicenter trial demonstrated that 18F-fluorodeoxyglucose (FDG) PET/CT scan can decrease by half unnecessary surgery for ITN (with a size >= 10 mm). This study included 132 patients who were divided randomly into two groups. The first group was the 18F-FDG PET/CT group. It included 91 patients with ITN (69%), all of whom initially had a 18F-FDG PET/CT scan. Then patients with a positive FDG uptake were recommended to have surgery, while those with a negative FDG uptake were recommended to have active medical follow-up for their ITN. A second group was composed of 41 patients with ITN (31%) who had undergone surgery. The study results showed, with a p-value <0.001, that 42% of patients in the first group compared to 83% in the second group had undergone futile surgery. Moreover, this study demonstrated that 18F-FDG PET/CT scan led to a 48% reduction (23/48) in surgery for non-Hurthle cell nodules compared to a 13% (2/15) reduction in Hurthle cell nodules. These results are explained by the fact that Hurthle cell nodules readily take up FDG regardless of their histopathological nature (benign or malignant) . This study also showed that 18F-FDG PET/CT had a high sensitivity 94.1%, a high negative predictive value (NPV) 95.1%, and a benign call rate of 31.1%, with low specificity and a positive predictive value (PPV) (Table 1). The findings of this recent study are consistent with those of previous studies that also demonstrated high sensitivity and high NPV of 18F-FDG PET/CT when evaluating ITN (with a size >= 10 mm). In other words, 18F-FDG PET/CT can rule out malignancy of ITN (>=10 mm) with a reasonable degree of certainty when FDG uptake is negative . cancers-15-01547-t001_Table 1 Table 1 Studies reporting PET/CT scan performance in identifying thyroid nodule histopathological characteristics. Radiotracer Study Study Design TN Size (mm) Number of Patients Bethesda Classification Time of Imaging after Radiotracer Injection Sensitivity (%) Specificity (%) PPV (%) NPV (%) Accuracy (%) Malignant Rate (% (ratio)) 18F-FDG De Koster et al. Prospective >=10 91 Bethesda III-IV 60 min 94.1 39.8 35.2 95.1 N/A 31 (28/91) Piccardo et al. Prospective >10 87 TIR3A, TIR3B * 50 min 94 58 37 98 66 21 (18/87) 18F-FCH Ciappuccini et al. Prospective >=15 107 Bethesda III-IV-V 20 min 90 50 29 96 55 19 (20/107) ** 60 min 85 49 28 94 67 94 Bethesda III-IV 20 min 100 47 17 100 N/A 11 (10/94) ** FDG: fluorodeoxyglucose; FCH: fluorocholine, N/A: not applicable, NPV: negative predictive value, PPV: positive predictive value, TN: thyroid nodule. * TIR3A and TIR3B are equivalent to Bethesda III and IV, respectively. ** Represent the pre-malignant and malignant rate. 3. Visual Assessment from PET/CT Compared to Other Imaging Techniques Piccardo et al. compared the ability of three different imaging techniques to detect malignancy of ITN. This prospective study included 87 patients with ITN (nodules with TIR3A and TIR3B were included, which are the equivalent of Bethesda III and IV, respectively) who had 99mTc-methoxyisobutylisonitrile scintigraphy (99mTc-MIBI-scan), multiparametric neck ultrasonography (MPUS) and 18F-FDG PET/CT scan within one day of each other before thyroidectomy for ITN. They showed that 18F-FDG PET/CT had significantly better sensitivity, accuracy, and NPV than MPUS and 99mTC-MIBI scan. Moreover, in line with previous studies, the absence of FDG uptake on PET/CT correlated with benign ITN, with a high NPV of 98% . In addition, the study found a specificity of 94% (p-value = 0.0001) for detecting thyroid malignancy when an ITN had a positive FDG uptake associated with a negative MIBI. Moreover, in a multivariate analysis (adjusted by age, thyroglobulin levels and nodule dimensions), the association of a positive 18F-FDG on PET/CT scan and a negative 99Tc-MIBI scan supported malignancy. In a univariate analysis, positive FDG PET/CT associated with a positive MPUS was associated with a higher specificity for differentiating thyroid carcinoma than the specificity observed for FDG PET/CT on its own. 4. 18F-Fluorocholine an Alternative to 18F-FDG Radiotracer 18F-FDG is the radiotracer for PET/CT scan that is routinely used to identify or rule out malignant thyroid nodules, while 18F-fluorocholine (FCH) or 11C-choline is typically used in prostate cancer. Some patients with prostate cancer who had had a 18F-FCH PET/CT scan incidentally showed positive 18F-FCH uptake within their thyroid gland that later turned out to be secondary to either a benign or malignant thyroid nodule . These reported cases led Ciappuccini et al. to study the performance of 18F-fluorocholine in identifying premalignant (non-invasive follicular thyroid neoplasm (NIFTP)) and malignant ITN. This prospective study included 107 patients with an ITN >= 15mm. In this study, Bethesda V nodules were considered as ITN and the population studied included 13, 81 and 13 patients with Bethesda III, IV and V, respectively. The participants underwent 18F-fluorocholine PET/CT scan at 20 and 60 min after injection of the radiotracer (1.5 MBq/Kg). Most of the PET/CT test characteristics were slightly better at 20 min than at 60 min with a higher sensitivity and NPV at 20 min with only the accuracy value better at 60 min (Table 1). This study demonstrated a possible reduction of 48% (p < 0.001) in futile surgery by relying on 18F-FCH PET/CT to identify benign thyroid nodules among Bethesda III-IV nodules. This reduction was possible because of a high NPV (96% at 20 min). However, this study had two major limitations. First, Bethesda category V was considered as an ITN, and the authors included 13 patients with a Bethesda V nodule (with 10 malignant nodules). If these patients are removed from the cohort, both the sensitivity and NPV increase to 100% while the specificity remains practically unchanged at 47% and the PPV decreases to 17% at 20 min. The second issue is the possible overestimation of the NPV due to a low premalignancy/malignancy rate of 11% (one NIFTP and nine malignant nodules among the 94 patients with Bethesda III-IV nodules), and 19% (20/107) when Bethesda III-IV-V nodules were included. Based on the Ciappucini et al. study, it seems that the 18F-FCH radiotracer performance is better, or at least similar to, the 18F-FDG radiotracer performance when used on patients to detect ITN. Nevertheless, it may be too early to draw this conclusion because more studies are needed to validate these results. Additionally, 18F-FCH has two advantages compared to 18F-FDG. Firstly, a lower irradiation dose is needed when the PET/CT radiotracer is 18F-FCH (1.5MBq/kg) compared to 18F-FDG (usually around 3.7 MBq/kg) . Secondly, a lower latency time is needed between radiotracer injection and image acquisition for 18F-FCH (only 20 min compared to +/- 60 min for 18F-FDG) (Table 1). Another consideration when comparing the two radiotracers is their cost. In Europe, both radiotracers have practically the same price according to Ciappucini et al. study, but in other countries their costs might differ. 5. PET Quantitative Parameters A study undertaken by De Koster et al. assessed the ability of quantitative measurements obtained from 18F-FDG PET/CT imaging to differentiate preoperative ITN properties. It included 123 patients (55 were Bethesda III nodules, while 68 were Bethesda IV nodules (39 FN/SFN and 29 HCN/SHCN). In this study, PET conventional parameters were measured (mainly SUVmax, SUVpeak, SUVmax-ratio, and SUVpeak-ratio). A higher median value for conventional parameters was present in malignant/borderline nodules compared to benign nodules, with p <0.001 (Table 2). Moreover, similar cut-off values for the conventional parameters were found in non-Hurthle cell nodule groups and all the 123 nodule groups, while a higher cut-off value was measured in the HCN/SHCN group. These cut-off values were associated with high sensitivity in each group (Table 2). Other studies have also focused on traditional quantitative 18F-FDGPET parameters (especially SUVmax) to determinate ITN histological characteristics. Some have reported a significant correlation between the SUVmax value and ITN benign/malignant status. In fact, it was reported that malignant ITN had a higher SUVmax compared to benign ITN . Similar results were reported when an 18F-FCH radiotracer was used instead of 18F-FDG . Some reports have suggested a cut-off value to differentiate between benign and malignant ITN . Tumoral tissue usually has higher metabolic activity (which leads to a higher SUVmax) than benign tissue. Nonetheless, SUVmax was not always reported as a discriminative tool able to differentiate between them. For example, Nguyen et al. prospectively followed 108 patients with follicular neoplasm or atypia and reported a difference in the median SUVmax between malignant ITN (7.2 g/mL) and benign ITN (4.9 g/mL), but this was not statistically significant, with a p value = 0.10. Even though some studies have suggested relying on SUVmax as a diagnostic tool to detect malignant ITN, currently, SUVmax and other SUV parameters should not be used alone to differentiate between benign/malignant ITN due to the presence of overlapping values between benign and malignant ITN and the inclusion of Hurthle cell nodules within the ITN categories. It is well-known that Hurthle cell nodules have a higher FDG avidity (secondary to the abundance of mitochondria within Hurthle cells) leading to a higher SUV value even if they are benign nodules . Similarly, when an 18F-FCH radiotracer was used, a higher SUVmax was found in Hurthle cell adenoma and carcinoma compared to other benign and malignant subtypes, respectively . 6. Cost-Effectiveness of PET/CT Scan Different pathways exist once an ITN is identified. The classical pathway recommended by current guidelines is diagnostic surgery. However, recently, many patients before undergoing surgery have decided, with the assistance of their physician, to undergo a molecular test (different tests exist) to rule in or out malignant ITN nodules to avoid futile surgery (molecular tests are especially frequent in the United States). Another alternative to molecular testing is 18F-FDG PET/CT, which is also not currently recommended as a matter of course before diagnostic surgery for ITN, even though some studies suggest a considerable reduction in futile surgery . A study by Vriens et al. compared the cost-effectiveness of these different pathways and their respective impacts on patient quality of life. They created a Markov decision model based on probabilistic analysis of a 5-year follow-up to compare the cost and effectiveness of the four different pathways (i.e., surgery, gene expression classifier (GEC), mutation marker panel (MMP), 18F-FDG PET/CT scan) once a thyroid nodule is characterized as indeterminate on cytology. After a 5-year follow-up, the mean cost of the FDG PET/CT pathway was the lowest compared to the other pathways. Furthermore, only the genetic pathway had a minimally better health-related quality of life outcome than FDG PET/CT due to a higher percentage of futile surgery undergone in the 18F-FDG PET/CT group (40%) compared to the GEC group (38%). Moreover, according to the Vriens study, if an 18F-FDG PET/CT scan was required in the United State for ITN before surgery, it could theoretically reduce the annual cost by EUR 164 million (which corresponds to approximately USD 177 million (if the current euro-dollar exchange rate is used (15 January 2023: EUR 1.0000 = USD 1.0823) )). This study was conducted within the Dutch health system. Nevertheless, the use of an 18F-FDG PET/CT scan could play a major role in regions outside the United States where genetic testing might not be available or, if available, is very expensive. De Koster et al. , in a prospective multicentered study, analyzed the cost-effectiveness of using an 18F-FDG PET/CT scan compared to surgery in patients with ITN at one year of follow-up. The study included 132 patients with ITN divided into an 18F-FDG PET/CT group and surgery group which were followed for 1 year. A total of 106 patients underwent diagnostic surgery during the 1 year of observation with inclusion of crossover between the management pathways in the analysis. At 1 year of follow-up, a mean healthcare cost difference of EUR 1300/patient (p = 0.01) was found between the two management strategies in favor of the 18F-FDG PET/CT strategy (but this difference became statistically non-significant and decreased to EUR 1000/patient (p = 0.06) in favor of 18F-FDG PET/CT when healthcare costs related to incidental FDG PET/CT findings were added). A Markov decision model was built to predict the difference in total societal cost (which included all medical costs (not only those limited to thyroid-nodule-related care), costs secondary to productivity losses, and patient costs (such as travel expenses)) between both management strategies over a lifelong period. Even though a mean lifelong societal cost difference of EUR 9900/patient was found, it was not statistically significant, with a p-value = 0.14. Regarding the quality of life, no statistically significant difference between both management strategies was found at 1 year follow-up and over the lifelong interval. The previously mentioned study of De Koster et al. found a decrease of approximately 40% in futile surgery when 18F-FDG PET/CT was used in ITN before surgery. This decrease in unnecessary surgery, added to the absence of significative differences in cost and quality of life between both management strategies, tends to favor 18F-FDG PET/CT over surgery (from a cost-effectiveness point of view). 7. Radiomics Based on 18F-FDG PET/CT Imaging in Indeterminate Thyroid Nodules Radiomics has the potential to significantly improve cancer diagnosis and management. It extracts numerous quantitative features from medical imaging. Some of the RFs extracted can serve as biomarkers in models aimed at identifying malignant tumors, predicting oncological patient clinical prognosis, or identifying genomic mutation status . The radiomics extracted from PET/CT imaging provides information on the anatomical location and metabolic activity of the tumoral and surrounding tissue, which represents a potentially powerful tool . Kim et al. , in a retrospective study, enrolled 200 patients with 18F-FDG incidentaloma who underwent an FNAB. Among the PET/CT parameters studied (SUVmax, SUVmean, MTV, TLG, heterogeneity factor) only the intratumoral metabolic heterogeneity measured by the heterogeneity factor (a derivate of a volume-threshold function; HF = dV/dT) could predict malignancy within the inconclusive FNAB group (31 patients), which included 12, 6 and 13 patients with Bethesda III, IV and V, respectively. They found a cut-off value for the heterogeneity factor (HF) (HF > 2.751 in favor of malignancy), with a sensitivity of 100%, specificity of 60% and AUC of 0.826 with a p-value < 0.0001. Even though this pilot study had some limitations (a small cohort of patients with inconclusive FNAB results, which included Bethesda category V in the analysis group), the results suggest that, by measuring tumor metabolic heterogeneity, it is possible to differentiate between benign and malignant thyroid nodules with better efficacy than using conventional PET/CT parameters. These results should lead to further research to closely evaluate tumor heterogeneity, which can be measured at a global and local level by relying on first-order histogram-based features and on second-order grey-level co-occurrence matrix (GLCM) features, respectively. De Koster et al. assessed the ability of quantitative measurements and radiomics based on 18F-FDG PET/CT imaging to differentiate preoperative ITN characteristics in a multicenter study. The study included 123 patients (55 were Bethesda III, while 68 were Bethesda IV (39 FN/SFN; 29 HCN/SHCN). A total of 100 patients had surgery, while the other 23 patients had active monitoring. Only 84 patients (28 Hurthle cell nodules and 56 non-Hurthle cell nodules) had a positive 18F-FDG uptake. These 84 patients were included in the radiomics analysis and had PET conventional parameters measured (SUVmax, SUVpeak, SUVmax -ratio, SUVpeak -ratio, TLG). These patients were divided into a training set with 68 patients and a testing set with 16 patients. Additionally, other subgroups for Hurthle cell nodules (with a training and testing set) and non-Hurthle cell nodules (with a training and testing set) were created. A total of 107 RFs were retrieved using the PyRadiomics software package (version 2.1.2). An SUVmax threshold of 50% was applied when the volume of interest was extracted. The 107 RFs were divided into 18 intensity features, 14 shape features and 75 texture features (5 neighboring grey tone difference matrix (NGTDM), 14 grey-level dependence matrix (GLDM), 16 grey-level size zone matrix (GLSZM), 16 grey-level run length matrix (GLRLM) and 24 GLCM). Only six parameters (i.e., entropy of the intensity histogram, nodule size, high intensity on PET, variance in area size, total lesions glycolysis (TLG), and small areas with low grey levels) were retained in the training set after RF dimensional reduction (the Kaiser-Meyer-Olkin tests were excellent in all folds (>=0.927)). The PET/CT model created from these features had a low mean area under the curve (AUC) in the test sets that included all ITN nodules (0.461), only the non-Hurthle cell nodules (0.466) and the Hurthle cell nodule (0.537). In addition, similar results were found in the PET model with an AUC of 0.421 when all patients with ITN of less than 64 voxels/volume of interest (VOI) were excluded from the analysis (18 patients excluded). The radiomic analysis in this study did not improve the discriminating power of 18F-FDGPET/CT in ruling out malignancy among ITN compared to 18F-FDGPET/CT visual evaluation or its quantitative analysis. In fact, in this study, even quantitative parameters of 18F-FDG PET/CT helped to differentiate between malignant and benign Hurthle cell nodules in a better way (with an AUC > 0.7 in all, non-Hurthle and Hurthle cell nodules) than the testing group in the radiomic analysis. The failure of this predictive model was not secondary to the size of the ITN because no improvement in AUC was found when ITNs less than 64 voxels/VOI were excluded. A retrospective study undertaken by Giovanella et al. assessed the possibility of relying on PET conventional features and RFs to determinate the final pathological status of the ITN with a positive FDG uptake. The study included 78 patients with FDG positive ITN (35 and 45 patients with Bethesda III and IV, respectively) that were later resected for definite histological diagnosis. First, 107 RFs were retrieved, which included 18 first-order features, 14 shape-based features and 75 matrix-based features (5 NGTDM, 14 GLDM, 16 GLRLM, 16 GLSZM and 24 GLCM). These features were extracted using the PyRadiomics software package (version 2.2.0). Only two features (GLCM_Autocorrelation and shape_Sphericity) were found to be non-redundant and capable of predicting ITN malignancy (with an AUC = 0.733). They were obtained after ruling out 65 RFs highly correlated to MTV and/or SUVmax, then, on the remaining 42 RFs, TLG and TSH, a LASSO (least absolute shrinkage and selection operator) logistic regression was applied. These two features with the ITN cytology (Bethesda category) were integrated into the multiparametric model capable of predicting malignancy in ITN with FDG uptake. This model had three outputs (a score of 0, 1 or 2) depending on the number of positive features. It was better in predicting the malignancy status of ITN when the population studied included only non-Hurthle cell nodules (65 patients) compared to when all types of ITN were included (65 non-Hurthle cell + 13 Hurthle cell nodules). In fact, when only non-Hurthle cell nodules (vs. all types of ITN) were included, a score of 0 represented benign nodules with an NPV of 95% (vs. 96%), and a score of 2 represented a possible malignant nodule with a PPV of 79% (vs. 58%, respectively). Unfortunately, the PET/CT model in the De Koster et al. study produced inconclusive results (i.e., low AUC in all groups). Nevertheless, future studies should apply the same approach by creating a training and a testing set for non-Hurtle cell nodules and Hurthle cell nodules separately to be able to integrate quantitative parameters in the predictive model. In addition, by segmenting the population studied in this manner, a larger number of participants per study are needed to reach enough patients in each group to obtain statistically significant results. 8. Radiomics Analysis Based on 18F-FDG PET/CT Imaging in Thyroid Incidentaloma and the Potential Application of the Results on ITN Studies examining the ability of PET/CT radiomics to determine the malignancy status of thyroid incidentalomas were included in this review because there are currently only two studies that have investigated PET/CT radiomics capacity to discriminate ITN characteristics (Table 3). Sollini et al. retrospectively included in their study 50 patients with a thyroid incidentaloma detected by 18F-FDG PET/CT. In this study, all the patients had seven PET conventional parameters and four histogram-based features extracted from PET/CT imaging, but only 28 patients with a large enough region of interest (>=64 voxels) had additional matrices-based features retrieved (11 GLRLM, 11 grey-level zone length matrix (GLZLM), 6 GLCM, 2 neighboring grey-level different matrix (NGLDM)) and 2 shape and size features). A 40% SUVmax threshold was applied to extract the region of interest and the RFs were retrieved using the Life Image Features Extraction (LIFEx) program package. Among these 43 features only seven features extracted were defined as potential predictors of thyroid incidentaloma (TI) benign/malignant status. The seven features were SUVmax, SUVstd, TLG, MTV, kurtosis, skewness and GLCM_Correlation. Among the seven features, only skewness had possible predictive power to identify pathological thyroid nodule characteristics with a sensitivity of 69%, specificity of 69%, PPV of 57% and NPV of 81%. In addition, a reciprocal correlation was found between skewness and kurtosis, MTV and TLG, and SUVmax and SUVstd, with AUC values of 0.830, 0.970 and 0967, respectively. GLCM_Correlation might be helpful in rejecting the possibility of having a malignant nodule due to its high NPV (100%). Furthermore, only compacity (a shape and size-based feature) was able to discriminate between TIR categories, with a p-value = 0.03. This study lacked a validation group to verify the results and it did not present a predictive model to differentiate between benign and malignant incidentaloma. A study by Aksu et al. used the texture analysis obtained by 18F-FDG PET/CT to differentiate thyroid incidentaloma pathological characteristics. The study included 60 patients, the majority being oncological patients (non-thyroid cancer), except for three patients. They were divided into two sets. The first set was the training group, with 42 patients, while the second set was the testing group, with 18 patients. The LIFEx software package was used to retrieve RFs and a threshold of 40% SUVmax was applied when the region of interest was drawn. Six conventional PET metrics (SUVmax, SUVmean, SUVstd, SUVmin, SUVpeak, TLG) were measured from PET/CT imaging and 40 RFs were extracted. The RFs were divided into 5 first-order features, 3 shape-based features and 32 matrix-based features (including 11 GLRLM, 11 GLZLM, 7 GLCM and 3 NGLDM features). The training set univariate analysis demonstrated a significant difference in all traditional PET metrics, 5 first-order and 16 second-order features (GLCM, NGLDM, GLRLM, GLZLM) between benign and malignant thyroid nodules. Among these features, the grey-level run length matrix--run length non-uniformity feature (GLRLM_RLNU) was the most powerful feature to differentiate between benign and malignant nodules with an NPV of 100%. The median values of GLRLM_RLNU (range value) were 43.2 (20-84.5), 105.2 (24.7-645.7) and 60.7 (20.0-645.7) in the benign group, malignant group and both groups, respectively, with a p-value <0.001. Finally, to create a predictive model of ITN malignancy, a correlation analysis was first performed among 18 features, with an AUC superior to 0.7 to avoid overfitting of these features. We found that only two of these features (GLRLM_RLNU and SUVmax) had a correlation coefficient inferior to 0.6. Then these two features were used in five machine learning algorithms. Among them, the random forest algorithm had the best model accuracy (78.6%) with the highest AUC at 0.849. When this algorithm was applied to the testing set, it had a good accuracy of 77.8%, with an AUC of 0.731. Unlike the Giovanella et al. study, shape_Sphericity RF was not a determinant factor in discriminating between benign/malignant thyroid nodules. The median value in shape_Sphericity (value range) was 1.055 (0.990-1.160) and 1.025 (0.910-1.160) in the benign and malignant groups, respectively (p-value = 0.036). The small number of participants, and the fact that this study was not limited to ITN, could be reasons for the lack of association between shape_Sphericity and thyroid nodule benign/malignant characteristics. GLCM_autocorrelation RF was not extracted in this study. Ceriani et al. extracted traditional PET parameters and RFs from 104 patients with 107 FDG positive nodules. This study involved the creation of a multiparametric predictive model based on three parameters (SUVmax, TLG and shape_Sphericity) that could identify thyroid incidentaloma malignancy status, with a PPV that could reach 100% when these three parameters were positive. The shape_Sphericity parameter was the only predictor of malignancy among six uncorrelated and non-redundant RFs (Shape_Maximum, 2DDiameterSlice, Firstorder_Energy, GLCM_InverseDifferenceMoment, GLCM_Constrast and GLCM_SumSquares) that were identified within the 107 RFs as potential malignancy predictors. The RFs were divided into 18 first-order features, 14 shape-based features, and 75 matrix-based features (including 24 GLCM, 16 GLRLM, 16 GLSZM, 14 GLDM and 5 NGTDM features). The RFs were extracted using the PyRadiomics software package (version 2.2.0). Five PET conventional parameters (SUVmax, SUVmean, SUVpeak, MTV, TLG) and six RFs were identified as potential predictors of malignancy, so they were included in a multivariate stepwise logistic regression analysis. This analysis showed that only three features (SUVmax, TLG and shape_Sphericity) were statistically significant, with a p-value < 0.0001. In this study, the mean shape_Sphericity of the benign and malignant lesion was 0.67 (0.53-0.78) and 0.79 (0.72-0.82), respectively, with a p-value < 0.0004. Regarding shape_Sphericity, it is an RF that represents the circularity of a nodule in comparison with a sphere. It seems to be an important malignancy predictor factor because tumoral tissue expands in an unorganized way. This anarchic expansion can be measured by shape_Sphericity. Moreover, two different studies with two different types of population (one with TI , the other with only ITN ) had shape_Sphericity as one of their predictive factors used in their respective malignancy predictive models. GLCM_Autocorrelation is another RF that measures how fine or coarse a texture is. It was considered to be a predictor factor of ITN histopathological status in the Giovanella et al. study. However, the Ceriani et al. study was the only one to measure this feature among the three radiomic studies on TI and the authors did not find the GLCM_Autocorrelation feature to be a predictive feature of TI histopathological status. Since TI includes more histological-type nodules this can lead to a more significant variation in texture within each category (i.e., more different histological types of benign and malignant nodules). In a study conducted by Sollini et al. , the inclusion of four PET metrics as potential predictors of TI histopathological status highlighted the importance and the need to include quantitative PET metrics in future models that can predict the histopathological diagnosis of ITN. For this reason, any future PET/CT radiomic study on ITN should divide the cohort into two groups (Hurthle cell nodules and non-Hurthle cell nodules) due to higher radiotracer uptake and quantitative parameters of Hurthle cell compared to non-Hurthle cell nodules. Moreover, the inclusion of PET quantitative parameters in both the predictive models of Aksu et al. (only SUVmax ) and Ceriani et al. (SUVmax and TLG) highlights the importance of separating Hurthle cell and non-Hurthle cell nodules. 9. Conclusions Although the current guideline only recommends diagnostic surgery for ITN, more patients are choosing to have a PET/CT or a molecular test to avoid surgery. In this review, we presented the results of recent studies on ITN and the different ways PET/CT scan can assess the benign/malignant status of an ITN to reduce unnecessary surgery. Visual assessment by PET/CT can prevent around 40% of futile surgeries in patients with ITN (Bethesda III-IV) of at least 10 mm. In addition, PET/CT quantitative metrics may be valuable as possible predictors of malignancy in ITN. However, they should not be used on their own to determine the histopathological status of ITN. Instead, they should be integrated into a predictive model. This predictive model should also select specific RFs extracted from PET/CT imaging that are predictors of benign or malignant nodules (especially: shape_Sphericity or GLCM_Autocorrelation as used in the Giovanella et al. study model). Another important aspect of a diagnostic tool is its cost-effectiveness. Based on current studies, PET/CT may be a more cost-effective tool compared to diagnostic surgery (with a preserved quality of life in patients who chose a PET/CT active follow-up). Finally, these promising results are paving the way for new studies that could potentially make PET/CT the definitive diagnostic tool once a thyroid nodule is identified as indeterminate. 10. Future Directions To the best of our knowledge, only two studies have used radiomics extracted from 18F-FDG PET/CT to create a predictive model able to identify ITN histopathological characteristics. Future studies should divide cohorts into two groups (Hurthle cell nodules and non-Hurthle cell nodules). Each of these groups should have a training and a testing group. Future predictive models should not be limited to radiomic features only (especially shape_Sphericity) but should also include PET quantitative parameters and other clinical factors, such as cytology features, TSH, thyroglobulin, age, and sex. In addition, there may be value in adding RFs extracted from another imaging technique, such as ultrasound imaging. Finally, regarding the PET/CT radiotracer, 18F-FCH seems to be a valid (if not a better) alternative to an 18F-FDG radiotracer in PET/CT. Nevertheless, prospective studies on the 18F-FCH radiotracer that includes only Bethesda III-IV nodules are needed to confirm the results reported in the Ciappuccini et al. study. Author Contributions Conceptualization, G.A.K. and A.M.; methodology, G.A.K. and A.M.; resources, G.A.K. and A.M.; writing--original draft preparation, G.A.K. and A.M.; writing--review and editing, G.A.K. and A.M.; supervision, A.M. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. cancers-15-01547-t002_Table 2 Table 2 Quantitative parameter cut-off values and their respective sensitivity in discriminating between malignant and benign thyroid nodules in three different groups (all nodule types, non-Hurthle and Hurthle cell nodules). SUVmax (g/mL) SUVpeak (g/mL) SUVmax-ratio (g/mL) SUVpeak (g/mL) Sensitivity (%) All nodule types (n = 123) 2.1 1.6 1.2 0.9 97 Non-Hurthle cell nodules group (n = 94) 2.1 1.6 1.2 0.9 95.8 Hurthle cell nodules group (n = 29) 5.2 4.7 3.4 2.8 100 (c) 2023 De Koster et al. This table information comes from Table 2 (Threshold analysis and diagnostic accuracy) (only column one, two and seven were used) found in de Koster et al. study ) and is licensed under CC BY 4.0 ). cancers-15-01547-t003_Table 3 Table 3 Studies that relied on radiomics to determine thyroid nodule histopathological characteristics. Type of Thyroid Nodules Study Study Design Number of Patients Software RF Extracted Features Included in the Predictive Model AUC ITN studies De Koster et al. Prospective 84 (68 train set, 16 test set) PyRadiomics (version 2.2.1). 107 RF: 18 IF, 14 SF and 75 TF (5 NGTDM, 14 GLDM, 16 GLSZM, 16 GLRLM and 24 GLCM) Entropy of the intensity histogram, nodule size, high intensity on PET, variance in area size, TLG, small areas with low grey levels 0.461 (all FDG-positive nodules) 0.466 (NHCN) 0.537 (HCN) 0.421 (only ITN >= 64 voxel/VOI) Giovanella et al. Retrospective 78 PyRadiomics (version 2.2.0). GLCM_Autocorrelation and Shape_Sphericity 0.733 Thyroid incidentaloma studies Sollini et al. Retrospective 50 LifeX 4 RF for 22 patients (4 IF); 36 RF for 28 patients: 2 shape and size features, 4 IF and 30 TF (2 NGLDM, 11 GLZLM, 11 GLRLM and 6 GLCM) N/A (only skewness had possible predictive power to identify histopathological thyroid nodule characteristics) N/A Aksu et al. Retrospective 60 (42 train set, 18 test set) LifeX 40 RF: 5 IF, 3 SF and 32 TF (3 NGLDM, 11 GLZLM, 11 GLRLM and 7 GLCM) SUVmax and GLRLM_RLNU 0.849 (train set) 0.731 (test set) Ceriani et al. Retrospective 104 (with 107 nodules) PyRadiomics (version 2.2.0). 107 RF: 18 IF, 14 SF, and 75 TF (5 NGTDM, 14 GLDM, 16 GLSZM, 16 GLRLM and 24 GLCM) TLG, SUVmax, and Shape_Sphericity 0.830 AUC: area under the curve, FDG: fluorodeoxyglucose, GLCM: grey-level co-occurrence matrix, GLDM: grey-level dependence matrix, GLRLM: grey-level run length matrix, GLRLM_RLNU: grey-level run length matrix--run length non-uniformity, GLSZM: grey-level size zone matrix, GLZLM: grey-level zone length matrix, HCN: Hurthle cell nodules, IF: intensity features, ITN: indeterminate thyroid nodules, LifeX: life image features extraction, N/A: not applicable, NGLDM: neighboring grey-level different matrix, NGTDM: neighboring grey tone difference matrix, NHCN: non-Hurthle cell nodules, RF: radiomic features, SF: shape features, TF: texture features, TLG: total lesion glycolysis, VOI: volume of interest. 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PMC10000407 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051046 foods-12-01046 Review Advances in Postharvest Storage and Preservation Strategies for Pleurotus eryngii Guo Yuxi Chen Xuefeng Gong Pin * Wang Ruotong Qi Zhuoya Deng Zhenfang Han Aoyang Long Hui Wang Jiating Yao Wenbo Yang Wenjuan Wang Jing Li Nan Cefola Maria Academic Editor Pace Bernardo Academic Editor School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China * Correspondence: [email protected]; Tel.: +86-13772196479 01 3 2023 3 2023 12 5 104623 12 2022 22 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 king oyster mushroom (Pleurotus eryngii) is a delicious edible mushroom that is highly prized for its unique flavor and excellent medicinal properties. Its enzymes, phenolic compounds and reactive oxygen species are the keys to its browning and aging and result in its loss of nutrition and flavor. However, there is a lack of reviews on the preservation of Pl. eryngii to summarize and compare different storage and preservation methods. This paper reviews postharvest preservation techniques, including physical and chemical methods, to better understand the mechanisms of browning and the storage effects of different preservation methods, extend the storage life of mushrooms and present future perspectives on technical aspects in the storage and preservation of Pl. eryngii. This will provide important research directions for the processing and product development of this mushroom. Pleurotus eryngii king oyster mushroom quality influential factors preservation National Key Research and Development Program2021YFD1600400 General Plan of Shaanxi Province2020GY-236 2022NY-035 Key Industrial Chain Projects of the Shaanxi Province-Agricultural Field2021ZDLNY04-01 2022ZDLNY04-05 Industrialization projects of the Education Department of Shaanxi Province22JC021 Project from Weiyang Technology Bureau202131 Project from the Xi'an City Innovation Plan-Agricultural Field21NYYF0022 project from Qinchuang Yuan "Scientist& Engineers" TeamS2022-ZC-QCYK-0011 Project from the Ningxia Zhong Ning Goji Industry Innovation Research InstituteZNGQCX-A-2020003 This work was supported in part by grants from the National Key Research and Development Program [No. 2021YFD1600400], the General Plan of Shaanxi Province [No. 2020GY-236, 2022NY-035], the Key Industrial Chain Projects of the Shaanxi Province-Agricultural Field [2021ZDLNY04-01, 2022ZDLNY04-05], Industrialization projects of the Education Department of Shaanxi Province [22JC021], the Project from Weiyang Technology Bureau (202131), the Project from the Xi'an City Innovation Plan-Agricultural Field (21NYYF0022), the project from Qinchuang Yuan "Scientist& Engineers" Team (S2022-ZC-QCYK-0011) and the Project from the Ningxia Zhong Ning Goji Industry Innovation Research Institute (ZNGQCX-A-2020003). pmc1. Introduction The king oyster mushroom (Pleurotus eryngii) is a high-quality, large, fleshy umbrella mushroom that is widely grown in many parts of the world . It is grown in Europe, the Middle East and China . Pl. eryngii has been intensively studied as a medicinal mushroom, a part of traditional diet and medicine, for its unique flavor, nutrition and biological functions . In addition, Pl. eryngii has a wide market for its easily cultivated, high-yielding, and delicious product that can be cooked directly . Simultaneously, Pl. eryngii is rich in protein, carbohydrates, unsaturated fatty acids, vitamins and other nutrients. It is also low in fat with high nutritional and medicinal value, which results in its high economic value. Its dried product contains 14.85% protein, 4.46% fat, 15.51% crude fiber, 43.15% carbohydrates and 18 amino acids. It is also rich in polysaccharides and has good therapeutic effects, such as its activities against viruses and hypoglycemia and its ability to lower cholesterol, promote intestinal digestion, prevent cardiovascular disease and improve immunity . Postharvest quality is a major concern for mushroom growers. Pl. eryngii is a highly perishable commodity and is not suitable for prolonged storage or transport over long distances . In recent years, Pl. eryngii has become popular with consumers owing to its crunchy texture and nutritious nature; it meets the demand for a healthy lifestyle . However, unexpected softening in texture and browning caused by polyphenol oxidase always occurs during storage, which significantly increases the challenges of postharvest storage and preservation and significantly increases the cost of transporting the king oyster mushroom . From the relevant postharvest preservation studies that have been conducted on Pl. eryngii, drying not only has a positive impact on physical properties, such as shrinkage, dehydration capacity and color, but also on the components that exert antioxidant and health-promoting properties. These include preservation technologies, such as modified atmosphere packaging (MAP) , g-radiation , 1-methylcyclopropene (1-MCP) nanopackaging and polysaccharide nanoparticle preservation , that can maintain their texture and nutrient content and extend the storage period. In addition, physical methods, such as microwave hot-air drying, vacuum freeze drying, solar drying and steam bleaching, can effectively reduce the loss of nutrients and reduce the intensity of respiration during storage and preservation. However, the current preservation techniques only have a small effect on the primary nutrients, and it is not known whether other nutrients are affected. Chemical methods, such as essential oils (EOs) and coating preservation , can delay the water loss and softening of Pl. eryngii to some extent and inhibit their respiration rate, thus resulting in successful storage and preservation (Table 1). To fully preserve the nutrient contents of Pl. eryngii, increase its shelf life and better promote the interests of the whole king oyster mushroom industry, this paper reviews the primary manifestations of quality deterioration of these mushrooms, the quality changes of Pl. eryngii in postharvest storage, the mechanism of browning and the storage effects of different preservation methods, and provides a reference for the development of green preservation processes for Pl. eryngii. 2. Deterioration of the Quality of Pl. eryngii The deterioration of the quality of Pl. eryngii after harvesting severely limits its commercial value and hinders the development of the mushroom industry. The deterioration in mushroom quality is characterized by the reduction in sensory and nutritional quality, which is owing to a combination of internal and external factors. Currently, research on the deterioration of the quality of the mushroom has focused on water loss, weight loss, postharvest morphological changes, changes in textural characteristics, color-specific changes, loss of nutrition and flavor and microbial infection. 2.1. Loss of Water and Weight Fresh Pl. eryngii has a moisture content of up to 90% (wet basis), but its loss of moisture during storage can easily lead to weight loss, which is an important factor in the quality of fresh mushrooms . A study showed that the weight loss of Pl. eryngii stored at 4 degC and 25 degC increased to 0.69% and 3.41%, respectively, (p < 0.01) compared with that of Pl. eryngii on day 0 throughout the storage period . This is primarily owing to the exudation of cell contents, the sudden increase in the content of malondialdehyde (MDA) and the effect of related enzymes, such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). When the weight loss reaches 3.41% of its fresh mass, Pl. eryngii is considered decayed and unusable as food . 2.2. Altered Textural Properties King oyster mushrooms are subject to aging during storage, which results in a rapid loss of hardness and contamination by microorganisms, thus explaining their short shelf life . Studies have demonstrated that after 12 days of storage at 4 degC, the hardness of the mushroom decreases from 9.024 N to approximately 3.132 N. After 6 days of storage at 25 degC, the hardness of the mushroom decreases sharply to 3.11 N. Studies have shown that when the hardness of stored mushrooms decreases to less than 3.11 N, microorganisms appear on their surface, which causes them to deteriorate . During storage at low temperatures, the fresh appearance of the Pl. eryngii is always accompanied by deterioration owing to lignification . Lignification not only leads to a toughening of the Pl. eryngii texture and a significant reduction in nutrients but also promotes lipid peroxidation and deterioration of the king oyster mushroom substrate . 2.3. Change in Color Characteristics Of all the quality properties that drive consumer purchasing behavior, color is the most evident dimension of quality. Among the parameters of mushroom browning, the L* value is often used to reflect the color change of the mushroom; a higher L* value indicates less browning and higher quality . A study showed that the L* of Pl. eryngii stored at 4 degC during the first 6 days did not change significantly. The L* value of Pl. eryngii stored at 25 degC decreased from 94.15 to 75.33 from day 0 to day 6, respectively, indicating severe deterioration of Pl. eryngii . When L* <= 82, the mushroom is of poor quality and not acceptable to the consumer. In addition to the L* value, the browning index (BI) can also be used to measure the degree of browning on the surface of king oyster mushrooms. Studies have shown that the degree of browning of the mushroom continues to increase with storage time. After 9 days of storage at 4 degC, there was slight browning on the surface of the mushroom. On day 12 of storage at 4 degC, the BI value on the surface of the mushroom reached 5.33-flod, which was no longer acceptable to the consumer compared to day 0. Compared with storage at 4 degC, the surface of the mushrooms stored at 25 degC reached a severe degree of browning after 6 days . 2.4. Loss of Nutrition Sugars and soluble proteins in the king oyster mushroom are the primary nutrients that support ongoing metabolic activity during the postharvest phase. A reduction in protein or sugar is an important indicator of deterioration . Li et al. demonstrated that the cellular oxidation of Pl. eryngii increased with storage time, resulting in more reactive oxygen species (ROS), which caused a decrease in reducing sugars owing to oxidation. In addition, the total free amino acid content is consumed during the pre-storage period to maintain the metabolic functions of the mushrooms. The contents of amino acids generally continue to decrease during the first 3 days of storage and do not start to increase until after 3 days. In addition to this, the fat content decreases as the storage time increases because the fat stored in the fat cells is gradually hydrolyzed by lipase into fatty acids and glycerol, which are then oxidized in other tissues . 3. Factors That Affect the Storage Quality of Pl. eryngii 3.1. Moisture The tissue concentration of active polyphenol oxidase (PPO) and phenolic compounds, pH, temperature, water activity and oxygen accessibility are the most important factors that influence the rate of enzymatic browning in freshly harvested Pl. eryngii , which are highly susceptible to mechanical damage and microbial infection owing to their high contents of water (approximately 89%), lack of cuticle and presence of microorganisms on them . Secondly, water loss or transpiration is an important physiological process that affects the primary quality characteristics of fresh mushrooms, such as marketable weight, appearance and texture, depending on the ambient and relative temperature and humidity . Fresh Pl. eryngii has a very limited shelf life of 1-3 days at ambient temperature and 4-7 days at 4 degC . With the increase in storage time, the apparent degradation of Pl. eryngii after harvesting gradually decreases in moisture, changes in internal enzymatic activity and bacterial enzymatic activity, which manifests as browning, texture softening and loss of flavor, which seriously affects its nutritional and commercial value . 3.2. Respiratory Rate The respiration rate and energy status of Pl. eryngii are key factors that influence postharvest senescence . During storage at 25 degC, the respiratory intensity of freshly cut mushrooms increased rapidly with time, reaching 1382 CO2 mg/(kg*h) at 12 h and 3526 CO2 mg/(kg*h) at 72 h when more than 50% of the surface of the mushroom became brown and basically lost its edible value . First, in terms of respiration rate, postharvest storage is an abiotic stress on Pl. eryngii since storage conditions are very different from those of growth. This storage leads to an inhibition of electron transfer in the mitochondria and an increase in the production of ROS . As the levels of ROS surpass the cell's antioxidant capacity, oxidative stress develops and mediates structural damage to lipids, membranes, proteins and DNA . These results demonstrate that mitochondrial membrane enzymes implicated in mitochondrial respiratory metabolism, such as cytochrome C oxidase (CCO), will be destroyed and their function severely diminished . To better preserve the mushrooms, the relationship between ROS and respiratory metabolism in Pl. eryngii is currently a hot topic in postharvest preservation research . Secondly, in terms of energy metabolism, it has been shown that an inadequate supply of ATP is closely associated with a variety of postharvest symptoms, such as chilling injury, browning, yellowing and decay . An adequate supply of ATP inhibits the accumulation of ROS and maintains membrane integrity, thereby delaying the aging and deterioration of Pl. eryngii . Under postharvest abiotic stress, the energy status plays an important role in mitigating oxidative damage and maintaining organoleptic properties . Therefore, the energy maintenance of Pl. eryngii during postharvest storage needs to be given high priority . 3.3. Microbial Infection Freshly harvested Pl. eryngii is highly susceptible to mechanical damage and microbial infection owing to its high content of water (approximately 89%), the absence of cuticle protection and the presence of many microorganisms on its surface . Decay in Pl. eryngii is usually induced by the tolaasin toxin in Pseudomonas tolaasii, which results in brown spots and yellow to dark brown lesions on the cap of the fungus . In addition, other bacteria, such as Pseudomonas azotoformans, Pseudomonas brenneri and Ewingella americana, have been reported to be able to cause decay in Pl. eryngii . Listeria monocytogenes has also been isolated from Pl. eryngii farm environments, which highlights the importance of monitoring the production chain from substrate production to harvesting, processing and packaging . 3.4. Temperature and Relative Humidity The various nutrients, such as polysaccharides, aldehydes and phenolic compounds, quality characteristics and microbial reproduction in the king oyster mushroom are influenced by temperature and relative humidity. Temperature fluctuations during storage can activate a variety of oxidative enzymes, enhance physiological activity, affect respiration and transpiration and increase the post-ripening period of stored Pl. eryngii , while temperature is also an important factor in determining the rate of enzymatic browning . Therefore, in general, when storing Pl. eryngii, the shelf life is usually extended by reducing the storage temperature and increasing the ambient humidity. A storage temperature of 4-6 degC and relative humidity (RH) of approximately 95% is generally used . 4. Methods for Storing and Preserving Pl. eryngii 4.1. Physical Methods and Mechanism 4.1.1. Modified Atmosphere Packaging (MAP) MAP is used to control the proportion of nitrogen, oxygen, carbon dioxide and ethylene in the gas, humidity, temperature (above the freezing threshold) and air pressure of the gas in the gas conditioning warehouse, thereby inhibiting the amount of cellular respiration and reducing the metabolic rate, so that the mushrooms are nearly dormant, thus preserving them over a long-term period . As a complement to storage temperature control, MAP has been found to be a simple, economical and effective postharvest preservation technique for commodities . Four core parameters need to be considered when designing MAP, including the product characteristics, the permeability of the packaging material, gas concentration (carbon dioxide and oxygen) and temperature dependence . The quality of the MAP of Pl. eryngii is related to texture, microbial count, whiteness, color variation and organoleptic characteristics, which are essential for the analysis of spoilage rates and thus influence consumer acceptance . Figure 2 summarizes the mechanism of action of MAP preservation and the changes in Pl. eryngii morphology from existing MAP studies. To investigate the total quality index of king oyster mushrooms treated with different gas mixtures of MAP after harvesting, Wan-Mohtar et al. investigated this and showed that high CO2 packaging (HCP) (20% CO2 and 15% O2) retained the best qualities of king oyster mushrooms. HCP recorded the highest total phenolic content (TPC) and showed the highest effectiveness in maintaining the color and odor of Pl. eryngii compared with the control and low CO2 packaging (LCP: 2% CO2 and 30% O2). Briones et al. suggested that the use of 2.5-5% CO2 and 5-10% O2 would result in optimal storage conditions for mushrooms. For safety reasons, it is recommended that O2 should not be less than 2% under MAP conditions . Research by Jafri et al. that utilized 10% O2 + 5% CO2 for the MAP treatment of king oyster mushrooms showed that this model was more effective at retaining quality characteristics and higher organoleptic ratings compared with other samples, which could be maintained for a storage period of 25 days. The treated mushrooms showed minimal changes in weight loss, pH and total soluble solids. Free radical scavenging activity and the total polyphenol contents were maintained at 85% and 91%, respectively . The effect of MAP on the enzymatic activity and shelf life of king oyster mushrooms stored at 20-25 degC and 90-95% RH for 5 days was investigated by Li et al. The results indicated that 2% O2 + 30% CO2 significantly prolonged the shelf life of the mushrooms compared with the control. A total of 2% O2 + 30% CO2 mixture was more suitable for maintaining the organoleptic properties of the mushrooms and delaying the increase in MDA and O2 production during storage. In addition, the activities of SOD, POD and CAT were significantly higher than those of the control. Treatment with 2% O2 + 30% CO2 reduced lipid peroxidation and enhanced the activity of antioxidant enzymes but had little effect on the CCO activity of the mushrooms . The molecular mechanisms of postharvest senescence also merit attention. Zhang et al. showed that the shelf-life of the mushrooms was prolonged after 2% O2 + 30% CO2 treatment and that the cell morphology was normal with no obvious aberrations, and the cytoplasmic distribution was as uniform as that of freshly harvested mushrooms, which significantly inhibited cell abnormalities, serine protease activity and PeSpr1 expression. However, there is a lack of research on the flavor and nutrient changes caused by metabolic substances during the gas conditioning process of king oyster mushrooms, which is crucial for acceptability by consumers. Further studies on the transcriptome, proteome, metabolome and multi-omics of this mushroom after gas conditioning treatment should be strengthened to provide a theoretical basis for the gas conditioning preservation mechanism . 4.1.2. Special Packaging Phase change materials (PCMs) are substances that absorb latent heat through phase changes and play an important role in short-duration cold chain transport . Li et al. developed a new water-based PCM and showed that king oyster mushrooms treated with the new PCM accumulated the most phenolics and flavonoids in all three groups, which mitigated the deterioration of its appearance during storage . The measurements of free amino acids demonstrated that the new PCM treatment increased the levels of phenylalanine, glutamic acid (Glu) and proline (Pro) by creating low-temperature conditions, thus improving the nutritional quality and flavor attributes and delaying the postharvest aging of king oyster mushrooms. In addition, the new PCM treatment maintained an adequate energy supply to the mushroom by activating the activities of succinate dehydrogenase, CCO and ATPases, thus reducing the catabolism of Pro and Glu. The application of nano-packaging can extend the life of postharvest edible mushrooms and maintain their original color and taste . 1-MCP, a type of cyclopropene, has been widely used and shown to inhibit the action of ethylene in respiratory senescent fruit by competitively binding to ethylene receptors . Xu et al. indicated that 1-MCP combined with nanopackaging treatment was effective at suppressing the increase in respiratory intensity, weight loss, MDA content and PPO activity of Pl. eryngii at 4 degC, delaying the decrease in soluble protein content, maintaining soluble sugar and soluble solid content and increasing the activities of SOD and POD, thereby maintaining the postharvest quality of king oyster mushrooms and extending the storage time . The efficiency of the combined treatment was superior to that of the sole packaging with 1-MCP or nano compared with the untreated samples . Currently, nanopackaging studies on Enoki mushrooms (Flammulina velutipe) are relatively thorough and complete in terms of basic physicochemical indicators, reactive oxygen metabolism, energy metabolism, proteomics and metabolomics to elaborate the storage quality, primarily browning and softening, of Enoki mushrooms extreme mechanisms of action. The study on king oyster mushrooms can also be studied in-depth in this respect in terms of a single packaging technique, which expands its intrinsic preservation mechanisms in terms of energy and multi-omics expression. 4.1.3. Low-Temperature Storage Low-temperature storage is a common way to store and preserve edible mushrooms. Low temperatures can inhibit enzyme activity, reduce physiological metabolic activity, reduce the respiratory intensity and inhibit the growth and reproduction of microorganisms . Li et al. conducted a related study on this in 2015 and showed that the optimal treatment was 2 degC and that toughening occurred twice throughout the storage process. This treatment maintained high textural properties for 18 days, with higher contents of chitin and higher activities of phenylalanine ammonia lyase (PAL), CAT and POD, and maintained a high content of total phenolics and lower membrane lipid peroxidation. This also suggests that toughening may be primarily caused by oxidation and can affect the quality of the mushrooms after harvesting . A further complementary study on the same preservation method by Li et al. in 2021 compared quality parameters, chemical composition, MDA concentration and metabolic enzyme activity during storage at 4 degC for 12 days and at 25 degC for 6 days. The best treatment measure was found to be the treatment group stored at 4 degC for 12 days, which maintained high quality, high nutritional characteristics, a high content of total phenolics, progressively higher enzyme activity and low membrane lipid peroxidation. Simultaneously, increased activities of laccase, lipoxygenase and PAL and the accumulation of MDA, as well as polysaccharide degradation, were the primary factors that contributed to the deterioration of the king oyster mushrooms during storage . Freezing prevents the growth of microorganisms and preserves the texture of tissues and the nutritional value of food . Long-term freezing (fast or slow) is the appropriate way to preserve mushrooms for the long term . It involves the extensive exposure of cells to low temperatures and dehydration. Jiang et al. evaluated the metabolite content of substrates to improve the understanding of changes in the nutritional composition of king oyster mushrooms during short-term slow frozen storage. The study showed that the optimal treatment was a storage temperature of -30 degC for the caps, which maintained a high nutritional value. The content of polysaccharides, proteins and amino acids in the cap increased and then decreased, while the content of all measured substances in the stalk slowly decreased. The activity of a-amylase decreased; that of POD increased, and the contents of reducing sugars and vitamin C continuously decreased with the extension of the freezing time . 4.1.4. Irradiation The application of improved postharvest techniques, such as food irradiation, can improve marketability and extend storage life, and the technology is now widely commercialized . The technical suitability and nutritional safety of irradiated foods have been well studied . Low doses of irradiation of fresh produce can provide hygienic safety and affect different physiological processes, such as enzyme activity and respiration, thus significantly improving postharvest storage . Akram et al. investigated the quality attributes of irradiated king oyster mushrooms. The study showed that the best treatment measure was irradiation at 1 kGy and that the L-value (brightness) of this group increased after irradiation and remained high throughout storage, maintaining a good appearance as indicated by homogeneous color and the absence of fungal decay and blemishes, good hardness and microstructure and low weight loss . Irradiation at 1 kGy was the most effective for extended postharvest storage and had additional advantages . However, irradiation treatment requires a high level of skill on the part of the operator and still requires significant consideration of its cost. 4.1.5. Drying Drying is a typical approach to food preservation based on the principle that the water activity of the product should be minimized to a defined level to ensure microbiological and physicochemical stabilization; it has been used for many years to improve the shelf life of food commodities . Hot blanching is receiving increasing attention as a pretreatment method to improve drying quality . The current scalding process, which is conducted by direct interaction between the sample and a medium, such as hot water and steam , can significantly (p < 0.05) reduce the total number of bacteria, improve drying efficiency and reduce the level of browning of the sample during drying . However, shortcomings of water and steam blanching have been reported, including the loss of nutrients, such as vitamins, proteins and polysaccharides, and uneven blanching . The results of Tolera et al. showed that the optimal treatment was a solar drying method with an infiltration concentration of 5%, which reduced the moisture by 7.74% and maintained the following proximal component contents: crude protein content 25.13% db, crude fat 2.27% db, total ash 10.17% db, crude fiber 10.26% db and carbohydrates 44.42% db. The purpose of microwave hot-air flow rolling dry-blanching (MARDB) pretreatment is to improve the drying efficiency and quality of the king oyster mushroom . Microwaving can alter the microstructure during the drying-hot blanching process, which could affect the drying characteristics, water state and migration . Su et al. revealed that optimal pretreatment (9 min) with MARDB significantly improved the quality indicators, such as color, water content and polysaccharide content of Pl. eryngii, shortened the drying time and completely deactivated PPO and POD. T2 relaxation spectra and microstructural analysis indicated that the primary reason for the improved drying efficiency at the optimal MARDB time was the resistance to free water migration and reduction in the pore structure. Excessive hot blanching (12 min) prolongs the drying time and leads to a reduction in whiteness and the contents of polysaccharides and phenolics . Ucar et al. freeze-dried Pl. eryngii at -20 degC, which maintained a better color and preserved the textural properties to prevent softening. However, the cost is relatively high when it comes to industrial production . 4.2. Chemical Methods and Mechanism 4.2.1. Essential Oil Treatment EOs are natural volatiles obtained by distillation and have the characteristic aroma of the plants from which they are extracted . An EO acts on the biochemical processes of the mushroom and inhibits or increases the concentration of enzymes and secondary metabolites associated with the preservation of quality . Manjari et al. conducted an experiment to study the effect of different essential oils on the enzymatic activity of stored Pl. eryngii. The results showed that the best treatment was peppermint oil (10 mL), which maintained high contents of total phenolics, TPC (0.286 mg/g), PAL (0.038 mM/g), PPO (0.042 U/mg) and POD (0.38 U/mg). The higher levels of TPC and PAL in the Pl. eryngii treated with EO and the lower levels of PPO and POD in the treated samples compared with those of the control indicated that the EO treatment had a positive effect on the quality of the harvested mushrooms . This preservative technique will help to extend the shelf life of the harvested substrates. Studies have reported that EOs have a significant antibacterial effect , but there is a lack of available research on the antibacterial effect and mechanism of action of EOs on Pl. eryngii during storage. 4.2.2. Coating In recent years, many different types of edible coatings have been successfully explored and further developed for the postharvest storage of mushrooms . Chitosan is a biodegradable polymer that occurs naturally and can be applied as an edible coating to suppress changes in the quality of mushrooms during storage . Liu et al. investigated a solution of protocatechuic acid grafted chitosan (PA-g-CS) with an antioxidant potential as a possible new edible coating material for the postharvest storage of king oyster mushrooms . The results showed that the best treatment was the PA-g-CS III (high grafting rate) coating group, which was able to maintain good textural properties, low membrane lipid peroxidation, high activities of SOD, ascorbate peroxidase (APX), glutathione reductase (GR) and CAT and low activity of PPO . There is good current acceptance of edible coating films in mushroom preservation, but there is still a need to expand the use of edible coating solutions of natural plant origin in king oyster mushrooms. Moreover, the mechanism of action of coated film preservation in Pl. eryngii merits further study, such as the use of a multi-omics approach to elucidate the expression of relevant browning and softening genes, protein up-/downregulation and flavor changes during storage caused by differential metabolites. In addition to this, changes in energy owing to respiration after film coating for preservation need to be considered to elucidate the mechanisms of preservation . 4.3. Others 4.3.1. Different Freeze-Thaw Treatments In contrast to slow block freezing, the single-piece quick freezing method uses cryogenic gases to rapidly reduce the temperature of mushrooms to the freezing point, which maintains cellular integrity with little change in nutritional quality and organoleptic properties . In general, frozen foods need to be thawed before processing and consumption, and thawing has a direct or indirect effect on the quality of the product. Therefore, freezing and defrosting are equally important to consumers. There are several methods of defrosting that are frequently used by consumers, such as natural air convection defrosting (NT), flow-through defrosting (FT) or microwave defrosting (MT) . Li et al. used the natural freezing (NF, -20 degC) or single freezing (-62.5 degC, speed 8.23 m/s) methods to freeze cut king oyster mushrooms, and three thawing methods, including flowing water (FT, 4 degC), microwaving (MT, 620 W) and natural air convection (NT, 20 +- 5 degC), to thaw the mushrooms . The results of the study showed that the best treatment measure was individual quick freezing and thawing with NT at room temperature, which was able to maintain cell integrity, preserve the texture of king oyster mushrooms and maintain high water holding capacity, low thawing losses, good color and good flavor. As a result, the method minimizes changes in the quality of frozen king oyster mushrooms . 4.3.2. Fermentation As one of the oldest processing techniques, lactic acid fermentation is recognized as a highly valuable processing approach to retain and improve the safety, nutritional and sensory characteristics of vegetables . In addition, varieties of lacto-fermented vegetables are often classified by their composition and method of preparation. For example, sauerkraut, kimchi, such as that made from cucumber and olive, and kimchi are the most investigated lacto-fermented vegetables, predominantly for their commercial importance . Today, pure fermentations of lactic acid bacteria (LAB) are widely used on a commercial scale for these commodities. As a result, this technique offers advantages over traditional methods, including shortened fermentation cycles, the elimination of non-lactic acid contaminants, and rapid fermentation at higher temperatures. It also ensures hygienic conditions and maintains consistency for better quality and flavor. Lactobacillus plantarum is an important member of the LAB family and is commonly used to ferment vegetables . Zheng et al. studied the preservation of king oyster mushrooms using three typical lactic acid fermentation processes, including sauerkraut, pickling and kimchi, with L. plantarum as the fermentation agent. This study showed that controlling the heavy salt pickling process inhibited microbial growth and reproduction and rendered most microorganisms inactive. These LAB rapidly colonize the mushroom substrate and quickly control spoilage and pathogenic microorganisms . The final fermentation product contained high levels of LAB (>7 Log CFU/g). In addition, the nitrite concentration in the final fermentation product was below the current maximum level permitted in China (<20 mg/kg). The results indicate that the lactic acid fermentation method is effective and safe for the preservation of king oyster mushrooms . 4.3.3. Polysaccharide Nanoparticle Preservation Chitosan nanoparticles are used to encapsulate bioactive substances owing to their good biocompatibility, high efficiency of encapsulation, safety and non-toxic properties . Therefore, if chitosan-based nanoparticles are used in combination with antimicrobial agents, such nanoparticles may induce synergistic effects between chitosan and antimicrobial agents . Microbial contamination usually occurs on the surface of food products. When nanoparticles are sprayed directly onto the food surface, vesicles and uneven distribution can occur, thus weakening the antimicrobial effect. The morphological transformation from nanoparticles to nanofibers is considered a feasible approach because nanofibers have a larger specific surface area and disperse more effectively. Pomegranate peel polyphenol (PPP), a natural, safe and green antimicrobial agent, was introduced and embedded in chitosan to form stable nanoparticles. PPP chitosan nanoparticles (PPP-CNPs) were further electrospun into king oyster mushroom polysaccharide (PEP)-based nanofibers. The optimal treatment measure of PPP 3 mg/mL was obtained by Cai et al. . This group was able to maintain small nanoparticle size and uniform nanoparticle dispersion, maintain optimum stability, produce tighter nanofibers, improve the thermal stability of PEP nanofibers, inhibit the activity of E. coli O157: H7 on the food surface, maintain good color quality and obtain the highest encapsulation rate of 23.71 +- 0.51% . However, the safety of this type of preservation technology in industrial applications that produce king oyster mushrooms still requires additional evaluation. 5. Challenges and Future Trends There are currently relatively few effective means to commercially preserve Pl. eryngii. They primarily include low-temperature storage, gas preservation and vacuum drying, and their ability to preserve the mushrooms is highly inadequate for the needs of industrialization. Therefore, it is important to study the mechanisms that cause the quality of Pl. eryngii to deteriorate and implement new preservation techniques to extend the shelf life of these mushrooms. Based on the mechanism of the deterioration in the quality of king oyster mushrooms, future research should focus on the following aspects. (1) To further investigate the mechanisms of quality fission during storage and preservation, such as browning, softening and lignification, and to use multi-omics techniques to study the potential molecular mechanisms of gene regulation in different preservation methods. This approach should help to address the problem of postharvest quality deterioration of king oyster mushroom strains at the molecular level. (2) Research on the mechanisms of nutrient retention and flavor transfer during storage and the effects of different preservation methods on the biological activity and quality characteristics of king oyster mushrooms should be strengthened to improve the quality characteristics of king oyster mushrooms after preservation while extending its shelf life and greatly enhancing its commercial value. (3) Among the methods of preserving Pl. eryngii, relatively little research has been conducted on the use of radiation, ozone and film coatings to preserve these mushrooms. There is still a need to explore the effects of these traditional methods of preserving edible mushrooms on Pl. eryngii and the mechanism of preservation, as well as the development of new green preservatives, based on natural types of bioactive substances. (4) In the future, a combination of new and traditional technologies can be used to improve the postharvest quality of Pl. eryngii, such as combining radiation treatment with 1-MCP in concert with nanopackaging treatment, developing cold sterilization equipment, creating safe and efficient sterilization processes, such as irradiation, microwave, low-pressure electrostatic field and low-temperature plasma sterilization equipment and processes, and decreasing the deterioration of the quality of Pl. eryngii during storage and distribution. Acknowledgments Thanks to the College of Food and Biological Engineering, School of Biology and Medicine, Shaanxi University of Science and Technology for their support. Author Contributions Y.G.: Writing--original draft, Conceptualization. X.C.: Visualization, Investigation, Writing--review and editing. P.G.: Supervision. Z.D., Z.Q., R.W. and A.H.: Investigation and Formal analysis. H.L. and J.W. (Jiating Wang): Data curation, Formal analysis, Investigation. W.Y. (Wenbo Yao), W.Y. (Wenjuan Yang), J.W. (Jing Wang) and N.L.: Formal analysis, Investigation. 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 Relationship between post-harvest quality degradation, influencing factors and preservation processes of Pl. eryngii. Created with BioRender.com. Figure 2 Mechanism of action of MAP preservation of Pl. eryngii (A) and changes in Pl. eryngii morphology from existing MAP research (B). (A) Created with BioRender.com. (B) cited from The arrow in the figure points to the destruction of the cell structure. (c)Copyright 2012, Elsevier. (c)Copyright 2015, Elsevier. Figure 3 Mechanism of action of special packaging preservation of Pl. eryngii. Created with BioRender.com. Figure 4 Mechanism of action of Pl. eryngii for low-temperature storage and preservation. Created with BioRender.com. Figure 5 Mechanism of action of irradiation preservation of Pl. eryngii (A) and changes in Pl. eryngii morphology and SEM images from existing irradiation research (B). (A) Created with BioRender.com. (B) Cited from (c)Copyright 2012, Elsevier. Figure 6 Mechanism of action of Pl. eryngii for coating. Created with BioRender.com. foods-12-01046-t001_Table 1 Table 1 Methods of Pl. eryngii storage and preservation. Treatments Process Parameters Storage Days Preservation Effect Ref. Modified atmosphere packaging Storage temperature: 4 degC Storage relative humidity: 95% Grouping processing: -high carbon dioxide packaging (HCP: 20% CO2 + 15% O2) -low carbon dioxide packaging (LCP: 30% O2 + 2% CO2) -high nitrogen packaging (HNP: 85% N2, 15% O2) 10 d Optimal processing: HCP: 20% CO2 + 15% O2 -High total phenolic content -Darkening delaying effect High carbon dioxide and low oxygen storage Storage temperature: 4 degC Storage relative humidity: 95% Grouping processing: -2% O2 + 30% CO2 -Air 5 d Optimal processing: 2% O2 + 30% CO2 -Inhibition of serine protease activity Storage temperature:4 degC Storage relative humidity:95% Grouping processing: -2% O2 -2% O2 + 10% CO2 -2% O2 + 30% CO2 -1% O2 + 50% CO2 -Air 5 d Optimal processing: 2% O2 + 30% CO2 - rate: 50.7% -Improve enzyme activity (SOD) 1-MCP treatment combined with nano-packaging Storage temperature:4 +- 1 degC Storage relative humidity: 90-95% Grouping processing: -Untreated -1-MCP (0.3 mL L-1, 24 h) -Nano-packaging -1-MCP (0.3 mL L-1, 24 h) + nano-packaging. 12 d Optimal processing: 1-MCP + nanopackaging -Texture enhancement -Delay respiration rate -Soluble protein improved -Avoid the accumulation of activated oxygen and enhance antioxidant activity (PPO, SOD and CAT) A novel phase change material Storage temperature: 22 degC +- 2 degC Preparation of PCM: 0.01% nano-TiO2, 2.09% K2SO4, 1.72% maltitol, and 0.50% superabsorbent polymer Grouping processing: -Novel PCM (-2 degC) -Ice (-2 degC) -Equal mass of water 5 d Optimal processing: the novel PCM (-2 degC) -Total flavonoid contents: 37.31% higher than control -Free amino acids: the contents of Glu, Phe and Pro were 1.95-fold, 1.34-fold and 2.07-fold higher than those in control, respectively; electrolyte leakage: 17.94% lower than that in control -Antioxidant activity enhancement (GDH, POD, SOD and CCO) Gamma irradiation Storage temperature: 5 +- 1 degC Group: 0, 1, 2, 3 kGy 28 d Optimal processing: 1 kGy -Uniform color with no fungus spoilage and blemishes -Scanning electron microscopy: comparable micro-structure to that of the control MARDB (microwave hot-air flow rolling dry-blanching) Storage temperature: 4 degC MARDB pretreatment: constant microwave power: 3 W/g, the speed of the rolling bed: 5 rpm Hot-air drying treatment: speed of rolling bed: 5 rpm, drying temperature of the material: 60 degC Group processing: -After pretreatment, cooled to 60 degC in the air and dried. -After pretreatment, packed in plastic bags, sealed and placed in the refrigerator of 4 degC 12 d Optimal processing: microwave hot-air flow rolling dry-blanching for 9 min -Maintaining quality parameters -Maintain moisture ratio -Reducing water holding capacity and water binding capacity Temperature-controlled cold rooms Relative humidity: 87 +- 5% Packing material: PE Group: 2 degC low temperature 4 degC low temperature 8 degC low temperature 18 d Optimal processing: 2 degC low temperature -High total phenolic content -Darkening delaying effect -Membrane lipid peroxidation is low Distilled water coating, CS coating, PA-g-CS I (low grafting 125degree) coating, PA-g-CS II (medium grafting degree) coating, PA-g-CS III (high grafting degree) coating Treatment Time: 30 s Storage temperature: 4 +- 1 degC Relative humidity: 95% Group: -Control (distilled water coating) group -CS coating group -PA-g-CS I (low grafting degree) coating group -PA-g-CS II (medium grafting degree) coating group -PA-g-CS III (high grafting degree) coating group 15 d Optimal processing: PA-g-CS III (high grafting rate) coating group -Maintain high quality -Lower membrane lipid peroxidation -Antioxidant activity enhancement (SOD, APX, GR, CAT) -Microstructure: PA-g-CS coating group has a less entangled fiber structure and smaller pores. Lactic acid fermentation Group: -Storage temperature: 20 degC Sauerkraut process: 2% salt, 1% crystal sugar, and 0.1% Lactic Acid Bacteria Powder Starter -Storage temperature: 4 degC Kimchi process: 4% solar salt, 2% sugar and 0.1% Lactic Acid Bacteria Powder Starter -Storage temperature: 30 degC Pickle process: 50 mM acetic acid, 2.06 M NaCl and 2% sugar and 0.1% Lactic Acid Bacteria Powder Starter -Storage temperature: 20-25 degC Control heavy salting process: Saturated brine (450 mL, 25%, approximately) 30 d Optimal processing: Control heavy salting process -Microbial counts changes: no count of lactic acid bacteria and Enterobacterial was detected; yeasts and molds were able to survive at 30 days -Inhibit the action of microorganisms: pH and titratable acidity: nearly unchanged -Nitrite concentration: relatively low and stable Natural freezing (NF, -20 degC) or individually quick-frozen (IQF) (-62.5 degC and speed 8.23 m/s) methods Storage temperature: -20 degC Group: -NF, thawed by NT at room temperature -NF, thawed by FT at 4 degC -NF, thawed by MT at 620 W. -IQF, thawed by NT at room temperature -IQF, thawed by FT at 4 degC -IQF, thawed by MT at 620 W -- Optimal processing: IQF, thawed by NT at room temperature -Thawing curve: takes less time to reach 4 degC -Water holding capacity: significantly higher than that of NF; thawing loss: significantly lower than that of NF -Cutting force analysis: high hardness -Sensory evaluation of thawed mushroom: superior to NF samples in all aspects; IQF least affected the quality after thawing freezing or canning Group: Storage temperature: -25 degC Freezing and Canning -- Optimal processing: Boletus edulis, Freezing Preservation effect: -The coefficients for converting total nitrogen to protein: 4.18 PPP@chitosan nanoparticles Storage temperature: 37 degC Group: -PPP 1.5 mg/mL -PPP 3 mg/mL -PPP 4.5 mg/mL -PPP 6 mg/mL 5 d Optimal processing: PPP 3 mg/mL -Inhibit the activity of E. coli O157:H7 on food surfaces. 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PMC10000408 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050713 healthcare-11-00713 Article Knowledge, Attitudes and Practices of Pregnant Women and Healthcare Providers in Bangladesh regarding Multivitamin Supplements during Pregnancy Kraemer Klaus Supervision 1 Beesabathuni Kalpana Conceptualization Formal analysis 1 Askari Sufia Writing - review & editing 1 Khondker Rudaba Supervision 2 Khan Toslim Uddin Writing - review & editing 3 Rahman Moshiur Writing - review & editing 3 Gibson Sarah Writing - review & editing 4 Merritt Rowena Investigation Writing - review & editing 5 Bajoria Madhavika Formal analysis 6 Lingala Srujith Formal analysis 1 Bipul Moniruzzaman Writing - review & editing 2 Tshering Puja Peyden Conceptualization Investigation Writing - original draft 1* Mirzakhani Hooman Academic Editor Koshiyama Masafumi Academic Editor 1 Sight and Life, P.O. Box 2116, 4002 Basel, Switzerland 2 Global Alliance for Improved Nutrition (GAIN), P.O. Box 55, 1211 Geneva, Switzerland 3 Social Marketing Company, Dhaka 1213, Bangladesh 4 Child Investment Fund Foundation, London W1S 2FT, UK 5 Center for Health Services Studies, University of Kent, Canterbury CT2 7NZ, UK 6 AVPN, Singapore 079025, Singapore * Correspondence: [email protected] 28 2 2023 3 2023 11 5 71310 1 2023 10 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 ). Micronutrient deficiencies are widespread among pregnant women in middle-income countries (LMIC) and lead to potentially adverse effects for mother and baby. In Bangladesh, maternal malnutrition remains a severe problem, with high rates of anemia (49.6% of pregnant women and 47.8% of lactating women are anemic) and other nutritional deficiencies. A Knowledge, Attitudes, and Practices (KAP) study was conducted to assess Bangladeshi pregnant women's perceptions and related behaviors, as well as awareness and knowledge among pharmacists and healthcare professionals concerning prenatal multivitamin supplements. This was done in both rural and urban areas across Bangladesh. A total of 732 quantitative interviews were conducted (330 with providers and 402 with pregnant women, with an equal split between urban and rural areas for both sets of audiences; 200 women were users of prenatal multivitamin supplements, while 202 women were aware non-users). The study identified a few findings that can guide further research or market-based interventions to reduce micronutrient deficiencies. These include most pregnant women not knowing the right time to start multivitamin supplements (56.0%, [n = 225], stating that a woman should start taking supplements 'after the first trimester'), not knowing their benefits, and how they help both the mother and baby-only 29.5% [n = 59] stated that they believed the supplements helped their baby to grow well). Further, barriers to taking the supplements include women believing a nutritious diet is a substitute (88.7% [n = 293]), and a perceived lack of support from other family members (21.8%, [n = 72]). This suggests that there is a need for further awareness-raising among all pregnant women, their family members, and providers. pregnancy micronutrient deficiencies prenatal multivitamin supplements multiple micronutrient supplements (MMS) consumer research Social Marketing Company Sight and Life Global Alliance for Improved Nutrition (GAIN)This research was funded by a consortium of three stakeholders--Social Marketing Company (a not-for-profit organization), Sight and Life (a Humanitarian Think Tank) and Global Alliance for Improved Nutrition (GAIN) (a Swiss-based foundation). pmc1. Introduction In middle-income countries (LMIC), micronutrient deficiencies are common in pregnancy, and inadequate maternal nutrition before and during pregnancy leads to adverse outcomes for the mother and baby, causing major impediments to economic development . Addressing malnutrition saves lives, reduces inequalities, and builds strong and resilient individuals, families, communities, and populations . Along with other nutrition and health interventions at the population level, since 1989 the World Health Organization (WHO) has recommended enhancing the diets of pregnant women with iron and folic acid supplements to prevent and treat gestational anemia . However, despite the growing evidence highlighting their positive effect in improving birth outcomes , supplementation programs in pregnancy have had less than optimal results in many countries, including low intervention coverage and poor adherence . Multiple micronutrient supplements (MMS) containing 15 essential vitamins and minerals can help address the high micronutrient demands of pregnancy and can help address dietary deficiencies more generally. The International Multiple Micronutrient Antenatal Preparation (UNIMMAP) MMS formulation, developed by the United Nations Children's Fund (UNICEF), the United Nations University, and WHO, is considered the benchmark for ingredients. It provides the recommended intakes of vitamins A (800 mg), B1 (1.4 mg), B2 (1.4 mg), B6 (1.9 mg), B12 (2.6 mg), C (70 mg), D (200 IU) and E (10 mg), as well as niacin (18 mg), folic acid (400 mg), copper (2 mg), selenium (65 mg), and iodine (150 mg), with 30 mg of iron and 15 mg of zinc for pregnant women . The 2015 Cochrane review, which included 17 trials involving 137,791 women, acted as the primary source of summary evidence on the effects of MMS, showing that MMS reduced the risk of low birth weight, being born small for gestational age, and stillbirth . In Bangladesh, although several strategies-such as National Strategy on Prevention and Control of Micronutrient Deficiencies, Bangladesh (2015-2024) -have been implemented over the past decades to address the high rates of malnutrition, the prevalence of micronutrient deficiencies remains high and is considered a significant public health problem . Further, while the government of Bangladesh does distribute free iron-folic acid and vitamin A supplementation nationwide, targeting women of reproductive age (WRA), these target-specific supplementations are highly resource-intensive and expensive, and are effectively unsustainable . A large majority of Bangladeshi people follow a diet consisting predominantly of plant-based foods and featuring minimal amounts of animal food, including eggs, milk and other dairy products. Thus, a poor-quality diet with low bioavailability is potentially the major contributor to micronutrient deficiencies in the country . In addition to a poor-quality diet, the major underlying causes of micronutrient deficiency in the country have been reported to be limited dietary diversity due to low socio-economic status and household food insecurity, and low levels of understanding in relation to an optimal diet and hygiene practices, along with infection and parasitic infestation . It is noteworthy that infectious diseases and micronutrient deficiencies exacerbate one another in a vicious cycle. Infections deplete micronutrients, and with limited stores to draw upon, the immune system weakens further and becomes less capable of fighting the infection . In 2011, the Bangladesh Demographic and Health Survey (BDHS) found that 49.6% of pregnant women and 47.8% of lactating women are anemic . In an older study from 2002, 55% of pregnant women in Bangladesh were found to be zinc-deficient, 46% were vitamin B12-deficient and 18% were folate-deficient. Infestation with Ascaris (an intestinal parasite) was highly prevalent (67%) and was associated with both folate and vitamin B12 deficiency in the pregnant women. Anemia and micronutrient deficiencies all varied significantly with the season; anemia was most common in the cool and dry season and least common in the mild temperature season . There are several prenatal multivitamin supplements available to purchase in Bangladesh, but currently only one MMS that is adherent to UNIMMAP's formulation. Called FullCare, it was introduced by Social Marketing Company (SMC; a Bangladeshi non-profit organization that offers education and products for family planning, maternal, and child health) and is the first and only MMS product produced with the recommended composition or ingredients of the UNIMMAP formulation available in Bangladesh. FullCare is currently being distributed across SMC's widespread pharmacy network, completing more than 6 months of being in the market without much marketing support. This brand is available through community-level private medical practitioners and pharmacists. These channels cater predominantly to lower-income and lower-middle-income groups. This study details the findings of two Knowledge, Attitudes and Practices (KAP) surveys. The first KAP survey was conducted with pregnant women across different socio-economic classes and regions in Bangladesh, and the second was conducted with pharmacists and healthcare professionals (referred to henceforth as 'providers') across the country in relation to prenatal multivitamin supplements. The survey also explored barriers to uptake, potential gaps in the market, and how MMS can be better positioned to increase usage. To our knowledge, there is no published KAP survey aimed at understanding the feasibility of MMS in Bangladesh. This research study seeks to address this knowledge gap. 2. Materials and Methods This study employed a KAP model , i.e., a structured, standardized questionnaire completed by a target population that can quantify and analyze what is known (knowledge), believed (attitudes) and done (practices) regarding a topic of interest . It originated from Albert Bandura's learning theory and Everett Rogers' diffusion of innovation theory , was developed for family planning and population studies in the 1950s , and is commonly employed in pharmacy practice research. At its core, it reveals misconceptions or misunderstandings that may represent obstacles to the activities that an actor, such as a brand or business, would like to implement, as well as potential barriers to behavior change . More specifically, it can help inform and devise market-based intervention strategies . This study was conducted across six divisions (12 sub-districts) in Bangladesh. It spanned six of the eight divisions of the country, covering both rural and urban areas. The locations were:1. Dhaka--Dhaka City Corporation (urban) & Keraniganj (rural) 2. Chittagong--Chattogram City Corporation (urban) & Hathazari (rural) 3. Rajshahi--Sador (urban) & Godagari (rural) 4. Khulna--KCC (urban) & Fultola (rural) 5. Rangpur--Sador (urban) & Gangachara (rural) 6. Mymensingh--Sador (urban) & Phulpur (rural) This study involved a convenience sampling design. A total of 732 quantitative interviews were conducted (330 with providers and 402 with consumers, with an equal split between urban and rural areas for both sets of audiences). Table 1 shows the split across urban and rural for consumers: As it relates to pregnant women, a survey was administered face to face in February 2021. A mix of pregnant women were recruited, including women currently consuming prenatal multivitamin supplements and/or other supplements during pregnancy, and pregnant women who are aware of prenatal multivitamin supplements/other pregnancy supplements but are not using prenatal multivitamin supplements/other supplements. This study explored two main questions: (i) what are pregnant women's current attitudes toward prenatal multivitamin supplements in Bangladesh?, and (ii) what is the current usage of prenatal multivitamin supplement products among pregnant women? As it relates to providers, a survey was administered face to face with pharmacists and healthcare providers in February 2021. Two surveys were developed, one for the mothers and another for the providers. The questionnaires were pre-tested with 20 pregnant women and 15 providers. Two days of training were also conducted to ensure that the data collectors knew how to administer the survey. After this pre-testing and training, the questionnaires were tested with some preliminary respondents as well in order to check for ease of comprehension and time taken. Minor modifications were recommended to improve the quality of data and of the changes made. Each questionnaire included a screener questionnaire at the beginning. The pregnant women questionnaire was made up of 43 questions spread across four sections:Knowledge and Awareness section--9 questions Attitudes section--11 questions Practices section--12 questions Demographics--11 questions The provider questionnaire was made up of 36 questions spread across three sections:Knowledge and Awareness section--25 questions Attitudes section--5 questions Practices section--6 questions The surveys were developed in several stages. First, a review of the literature was conducted, and stakeholders were engaged to help understand some of the possible social and cultural barriers, as well as some of the physical barriers. Based on this, the surveys were drafted and then pre-tested for cultural and contextual relevance. A mix of providers were recruited including: (1) practicing obstetricians/gynecologists (from SMC's Pink Star Network), and (2) pharmacists (from SMC's Blue and Green Star networks). In total, 330 providers from six areas from across the country, with each division represented by one urban and one rural district, were interviewed. It was important to gain the professionals' perspective in order to understand how a UNIMMAP MMS product could be introduced into the Bangladesh market. The survey aimed to understand the professionals' knowledge, attitudes and practices in relation to prenatal multivitamin supplements (which was the closest segment to what MMS could offer); all the professionals surveyed regularly interacted with pregnant women and their families. To administer the survey, we utilized the SMC network of pharmacies and retailers. SMC started operations in 1974, and currently implements several programs across Bangladesh, with networks of private-sector retailers, health care professionals (mostly obstetricians and gynecologists) and pharmacists. SMC produces MMS with the exact composition or ingredients of the UNIMMAP formulation. This formulation will be rolled out countrywide through SMC's existing pharmacy networks in Bangladesh, known as the Star Network Providers. This networks includes Blue Star (BSP) and Green Star (GSP) pharmacies, Gold Star members (GSM) and Pink Star providers (PSP). The providers worked at a mixture of facilities, including pharmacists', non-government organization healthcare centers and hospitals, public hospitals, and private clinics, and came from the three existing networks of SMC, including: Blue Star Network, comprising community-level non-graduate health providers who are trained in family planning, reproductive and child health and nutrition, along with other public health priority areas, to offer quality services to the community people, operating as attachments to pharmacies Green Star Network, comprising non-graduate health care providers with at least 2 years of professional experience plus pharmacists and drug-sellers who own their own store. These are the primary point of contact at the community level for minor ailments, such as diarrhea, cough, fever and weakness. They also advise on family planning and nutrition. Pink Star Network: comprising the SMC's internal network of obstetricians and gynecologists who are serving in medical colleges and hospitals. All surveys were translated into Bangla (the local language). Each survey (with pregnant women and providers) took an average of 25 min to administer. For pregnant women, the survey included questions on demographics, knowledge around prenatal multivitamin supplements, attitudes toward prenatal multivitamin supplements-including the perception of risk and need, barriers to consumption and perceived motivations for, and benefits of, taking prenatal multivitamin supplements. The survey also covered current uptake and consumption of prenatal multivitamin supplements. For providers, the survey included questions on demographics, knowledge around prenatal multivitamin supplements, providers' perceptions of what consumers know about prenatal multivitamin supplements, attitudes toward prenatal multivitamin supplements, and the healthcare professionals' opinions regarding consumer practices and behaviors around prenatal multivitamin supplements. Informed consent (written) was obtained from all participants. Voluntary participation and confidentiality were ensured. The participants were given a choice as to whether they would want to have the entire informed consent form read out to them, or if they would prefer reading it on their own. This was done to accommodate participants who were unable to read. Participants who were unable to sign their own names were asked to give their thumbprint. Consent was taken before the survey questions were asked. Ethics approval for the analysis of the data was obtained from the University of Kent, Research Ethics Committee, Ref 0464. Descriptive results are presented as total numbers and percentages and mean with standard deviation (SD), or median (range) if not normally distributed. Groups were compared using the Mann-Whitney U test. The significance level was set at 5%. All analyses were conducted using SPSS. 3. Results 3.1. Pregnant Women (Consumers) A total of 402 pregnant women participated in the survey: Two hundred pregnant women were currently taking prenatal multivitamin supplements/other supplements during pregnancy (100 from rural areas and 100 from urban areas)--referred to as 'Segment 1'. Two hundred-and-two pregnant women who were aware of prenatal multivitamin supplements but were not taking prenatal multivitamin supplements/other supplements during pregnancy (101 from rural areas and 101 from urban areas)--referred to as 'Segment 2'. The mixed sample was selected to explore differences among the segments based on their current awareness and usage of pregnancy supplements. Participant characteristics are given in Table 2. Most of the respondents (65.7%, n = 264) were between 18 to 25 years of age, with most being in their second or third trimester at the time of the interview (38.3% and 42.8%, respectively). Most of the respondents (93%, n = 374) classified themselves as homemakers and were not in other employment. 3.2. Knowledge and Attitudes toward Pregnancy Supplements Of the 402 respondents who were either currently taking (Segment 1) or else aware of, but not taking prenatal multivitamin supplements/other supplements (Segment 2), over half of the respondents (56.0%, n = 225) stated that a woman should start taking supplements 'after the first trimester', while 27% (n = 109) believed they should take supplements as soon as they conceive . When asked what the benefits of taking supplements are, the most frequently given response was 'to fulfill nutritional requirements of expectant mothers' (80.9%, n = 325). There were no significant differences in responses between Segments 1 and 2, or differences between rural and urban respondents. The sources of awareness to buy pregnancy supplements were high, with most of the respondents (94.3%, n = 379) having reported 'pharmacy' as the source, while 95% (n = 383) of respondents believed it was safe to take supplements during pregnancy. When asked about the benefits of taking supplements, over half of the respondents from both segments (54.5%, n = 220) stated, 'not falling sick', and 47.0 % (n = 94) mentioned being 'able to do regular work'. Only 29.5% (n = 59) stated that they believed the supplements helped their baby to grow well. There was one significant difference between respondents in rural and urban areas. Having enough nutrition was mentioned as a benefit significantly more by respondents living in urban areas than by those respondents living in rural areas (36.0%, n = 36). 3.3. Current Practices Of the 200 respondents who were currently taking prenatal multivitamin supplements (Segment 1), only 42 respondents were taking just one supplement. Most of the respondents (79%, n = 158) were taking more than one. The most frequently taken supplement was calcium tablets, with 34.4 % (n = 146) of the respondents reporting taking this supplement. Table 3 details the number and type of supplements taken. 3.4. Barriers to Uptake Respondents in both segments were asked what the barriers are to taking supplements during pregnancy. Among Segment 1, most of the respondents (68%, n = 136) stated that there were no barriers. However, there were significant differences between the Segments, with Segment 2 identifying barriers (Table 4) including 'in-laws/husband doesn't allow', 'husband is reluctant to bring/buy it', 'people are not aware of its benefit', and 'it is expensive'. It is interesting to note that this reluctance exists despite the women being told by the doctor or pharmacist about the need to start taking prenatal multivitamin supplements. Out of the 202 respondents in Segment 2, nearly two-thirds (64%, n = 129) said they were not using pregnancy supplements because they did not currently have any health issues. Another 14% (n = 28) of the respondents stated that they were not using supplements as they had not been advised to do so by their doctor. More than half the respondents in Segment 1 (59%, n = 118) stated that their own health was the most important thing during pregnancy, while 32.5% (n = 65) said that the most important thing was their baby's health. Only 2.5% (n = 5) stated that it was both their own and their baby's health. When Segment 2 was asked what the benefits are of taking prenatal multivitamin supplements/other pregnancy supplements, the most frequent response was 'to fulfil nutritional requirements of expectant mothers', with 81% (n = 325) of the respondents stating this benefit, followed by 'to prevent anemia during pregnancy' (42.0%, n = 169). Other benefits detailed are shown in Table 5. In line with this finding, when asked about the potential side-effects of taking supplements, most respondents (85%, n = 170) said there were no side-effects among Segment 1 and 63.3% (n = 128) among Segment 2. The only significant finding was in relation to the side-effect 'dizziness'. This side-effect was mentioned significantly more by Segment 2 (17.3%, n =35). 3.5. Providers A total of 330 providers were interviewed from the different networks including 60.6% (n = 200) from the Blue Star Network, 30.3% (n = 100) from the Green Star Network and 9% (n = 30) from the Pink Star Network. The sample size was based on the size of each network: BSPs are currently 9000 in number, GSPs are 4500 in number and PSPs are 350 in number (Table 6). Most of the providers (98.5%, n = 325) believed that consuming supplements during pregnancy posed no risk to users, and over half of providers (60.9%, n = 201) stated that there were no side-effects. Of the providers who mentioned side-effects, the side-effects most frequently mentioned included dizziness (18.8%, n = 62), nausea/vomiting (21.2%, n = 70), and indigestion/gas problems (17.8%, n = 59). Most of the providers (78.8%, n = 260) recommended or prescribed to pregnant women one supplement a day. The remaining respondents (21.2%, n = 70) stated two supplements per day. Again 62.4% (n = 206) of the providers stated that pregnant women should start consuming pregnancy supplements after completion of the first trimester, while 33% (n = 109) recommended as soon as the woman conceives. Further details are presented in Table 7. Most of the providers (83%, n = 274) mentioned that prenatal multivitamin supplements are essential, but 61.5% (n = 203) stated that there were substitutes for prenatal multivitamin supplements. Of the respondents who believed there were substitutes available, 'nutritious foods' was the most frequently given response 88.7% (n = 293). Providers were asked what were the barriers that prevented pregnant women from using prenatal multivitamin supplements. Over half of the respondents (56.1%, n = 185) stated that there were no barriers. However, the immediate family circle, the elderly, and the husband of the pregnant woman were identified by other respondents as the main barriers (Table 8). 4. Discussion KAP studies, as mentioned earlier, can inform market-based approaches with the aim of behavior change aimed at encouraging increased and regular usage of MMS. Given that current interventions have so far been far from satisfactory and unsustainable , market-based interventions can potentially fill this vacuum and grow in relevance in the future. The study found six things that both governmental and private actors may consider in developing or refining any interventions. First, rectifying incorrect knowledge among pregnant women as to when MMS should be introduced to pregnant women. The study found that most of the respondents did not see prenatal multivitamin supplements as something they needed to take before falling pregnant or during their first trimester. This is an interesting finding, as other studies have highlighted the benefits of taking certain supplements while trying to conceive and during early pregnancy . One of the reasons why this might be the case is the existing belief about when to first attend antenatal care and preferences for disclosing pregnancy status . However, receiving MMS early in pregnancy is important, as there are multiple maternal micronutrient deficiencies present during early pregnancy in Bangladesh . These findings suggest the need for the MMS to be promoted as a product that should be used throughout pregnancy (evidence suggests that benefits are seen when MMS is provided for at least 180 days) , and possibly when trying to conceive, while also tackling the myths and beliefs around when an expectant mother should attend antenatal care. Interestingly, the providers also mirror the women's views in this regard. For instance, most of them believed that MMS should be taken after the first trimester, whereas it is recommended that they should be taken earlier--starting from as early as when trying to conceive. One of the reasons could be that pregnancy in Bangladesh (in rural areas especially) is usually detected in the first 2-3 months, requiring no additional medical intervention unless significant complications arise . However, there is still merit in trying to further understand why providers have this attitude and in promoting the benefits of taking supplements while trying to conceive or as soon as conception has occurred. Second, educating as to the benefits of MMS among pregnant women in a more targeted and specific way. Users and non-users of MMS conveyed similar and generic responses to the benefits of MMS, indicating that there is not strong conviction associated with it. Further, most women see MMS linked with the absence of a general negative such as 'not falling sick' or a presence of a general positive such as 'being able to do regular work' rather than anything specific to their own and their baby's health. Studies evaluating the absolute and relative relevance of benefits such as reduced risk of low birth weight can be conducted to create more targeted and robust educational and awareness programs toward pregnant women. Third, overcoming a lack of awareness among pregnant women, of not just the content of the benefits of MMS but also their intended target. For instance, the study found the need to promote the wellbeing of both mother and child, as the respondents often focused on either their health or that of their babies. Very few of the respondents considered the health of both the mother and the baby. This might suggest that mothers lack an understanding of how their health and their baby's health are interlinked. Fourth, highlighting how MMS and a nutritious diet can work together to improve maternal health. Currently, even if any benefits around MMS are registered, pregnant women consider that a nutritious diet, which they incorrectly think they are following, circumvents a need for MMS. MMS in this case does not intrinsically generate a strong pull. While eating a healthy and varied diet during pregnancy is important for the health of mother and baby, globally, pregnant women are challenged to achieve a dietary intake sufficient to improve maternal and neonatal outcomes . These challenges are often amplified in traditional communities where cultural and gender dynamics and practices may hinder the mother's ability to eat enough of the right foods. MMS is a way to overcome this issue and boost vitamin intake during pregnancy. Among pregnant women, this study found that many respondents understood the importance of healthy eating during pregnancy. While this is a positive finding, it could also potentially be a barrier to the uptake and usage of MMS, as pregnant women may not see the need to take the supplements if they believe they are already consuming a healthy diet. However, other studies have shown that pregnant women in Bangladesh often do not eat enough healthy foods during pregnancy , which highlights a potential gap between people's understanding of dietary needs and actual consumption patterns. For instance, one study showed that in Bangladesh, the largest knowledge-to-practice gaps were related to foods containing essential micronutrients such as eggs, milk and milk products . Providers echo consumer sentiment in this regard. This study also found that most of the providers agreed that pregnancy supplements are essential to a healthy pregnancy and a healthy baby; however, the belief that supplements can be substituted by a nutritious diet (involving more fruits and vegetables) shows that there is a need to also sensitize providers to prenatal supplementation and its importance, and to promote the added value of taking pregnancy supplements, including MMS. This is due to the ongoing high rates of food insecurity within Bangladesh, with poverty and hunger remaining widespread . This could explain why, despite the providers' belief that pregnant women would benefit from taking supplements, the uptake rates are still low, leading to micronutrient deficiencies in pregnancy. This highlights a need to further promote their use among pregnant women. Fifth, MMS can be seen as one core component among a full spectrum of vitamins and minerals which are critical for healthy pregnancy development. The study found that calcium was the main supplement being taken during pregnancy, followed by iron tablets, while in other countries folic acid and vitamin D are often the main vitamins promoted to take during pregnancy. WHO recommends that pregnant women living in regions of low calcium intake should consume an additional 1.5g to 2.0g of elemental calcium per day from 20 weeks of gestation until the end of pregnancy to reduce their risk of pre-eclampsia . While Bangladesh has widespread deficiencies of calcium , there are also other micronutrient deficiencies such as poor vitamin D status and high rates of anemia . Sixth, different family members, including the husband and in-laws, can be looked at as a secondary audience to create the demand for MMS, as these family members play a core role in the adoption/non-adoption process. Among the several barriers mentioned earlier, a key one was the perceived lack of support from other family members. This is especially a handicap for the pregnant women, as the opposite has definite benefits. For instance, a study on maternal nutrition practices in the context of a large-scale maternal, newborn, and child health (MNCH) program in Bangladesh shows that women with high support from their husbands (25 out of a recommended 180) were likely to consume more IFA than those with low support. Women who received reminders from other family members to take the supplements also consumed more IFA (six tablets) . These figures highlight the need to engage with other family members in order to increase the acceptability of MMS and communicate the need for mothers to take them. These conversations should be had with the extended family, and not only the husbands, as mothers-in-law have substantial influence within the family units . 5. Conclusions This research described findings from a KAP survey conducted with pregnant women and providers on current prenatal multivitamin supplements and pregnancy supplement practices in rural and urban Bangladesh. The pregnant women surveyed highlighted some key barriers to the uptake of prenatal multivitamin supplements, as well as potential motivators for change. The study findings may contribute to improving the nutritional status of pregnant women by providing knowledge of current attitudes and practices related to pregnancy nutrition. From the research findings, gender inequality and intra-household dynamics were identified as potential barriers, and inform future potential research direction. Locally, this research may inform program changes by working with local professionals and other family members to more effectively promote the benefits of taking supplements during pregnancy and the best time to take the supplements. By promoting to all family members a greater understanding of the benefits to both mother and baby, current practices may change and reduce the micronutrient deficiencies during pregnancy commonly reported in Bangladesh. The study also points out knowledge gaps and inconsistencies among providers of prenatal micronutrient supplements, such as information regarding the benefits and use of prenatal multivitamin supplements, and when to start prescribing prenatal multivitamin supplements. Knowledge of prenatal multivitamin supplements is critical, and it is important that providers should understand and learn about MMS fully through proper training and sensitization and that they should see it as essential to pregnant women in Bangladesh. Making a distinction between prenatal multivitamin supplements and MMS is important in such training. It is important to address these gaps around the critical importance of prenatal multivitamin supplements in order to be able to convey why MMS is a viable option for pregnant women, so the providers can become advocates of MMS, thereby contributing to reductions in maternal malnutrition. 5.1. Limitations This study has several limitations. First, the study only involved respondents from specific areas in Bangladesh. Although the areas were selected as a representative national sample, the data might not be representative of Bangladeshi women in other parts of the country, or across Bangladesh's other ethnic groups. Next, the data for prenatal multivitamin supplement intake in the survey were self-reported, and the survey questions did not include all the available or recommended supplements to be taken during pregnancy. For example, vitamin D was not explicitly asked about, despite the evidence showing that it is an important vitamin to take during pregnancy and that it is an issue in Bangladesh . Future studies investigating MMS and pregnancy supplements in Bangladesh should also consider additional categories, such as vitamin D. The survey also did not ask if pregnant women were taking these supplements before pregnancy; therefore, it is unclear what additional supplements were being taken during pre-conception. The study collected self-reported data, and the providers may have been inclined to give the answer which they thought was correct as opposed to the one they believed in. The study did not extensively explore other attitudinal factors associated with prescribing supplement behaviors, such as other communication factors that may have influenced the public's knowledge, including seeking information, using the media, or processing information. Convenience sampling, used in the study, is a reason for the limitations mentioned above. On the one hand, convenience sampling can be linked with a selection bias as well as with difficulty in generalizing the results across a larger audience. On the other, in conjunction with and corroborated by other secondary research, it is useful in terms of time and affordability to collect data quickly and to inform existing or create new intervention strategies related to maternal supplementation, accelerating efforts to make a positive impact on the health of pregnant women in Bangladesh. Lastly, there are a few other limitations. The findings outline the knowledge, attitudes and practices around prenatal supplements in the study area rather than deeply examining one or more specific factors (e.g., lack of family support as a barrier to MMS) underpinning or contributing to the KAP areas of inquiry. Conversely, this increases the scope for any future studies. 5.2. Implications for Further Research The findings have implications for future research conceived to understand the reasons why pregnant women do not take prenatal multivitamin supplements or other pregnancy supplements during the first trimester. It also has implications regarding what can be done to motivate this behavior change, as well as the knowledge of, and attitude toward, prenatal multivitamin supplements on the part of the fathers and other key family members who influence the mothers. Future research should also explore the social, cultural and gender dynamics within a household and the local community, and how these can influence women's uptake of MMS, including ensuring that uptake happens during the first trimester. Furthermore, additional information on how providers may be familiarized with the promotion and use of MMS, given their current predisposition toward prenatal multivitamin supplements, is needed. It remains to be seen what level of influence the provider has on the purchase decisions of the consumer in the case of prenatal multivitamin supplements and, eventually, MMS. Author Contributions Conceptualization: K.B., P.P.T.; formal analysis, K.B., S.L., M.B. (Madhavika Bajoria); Investigation, R.M., P.P.T.; writing--original draft preparation, R.M., P.P.T.; writing--review and editing, S.A., S.G., T.U.K., M.R., R.M., M.B. (Moniruzzaman Bipul); supervision, K.K., R.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 (or Ethics Committee) of the University of Kent (Ref 0464, 4 August 2021). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Knowledge, Attitudes and Practices Model. Figure 2 Knowledge on starting-time of consuming pregnancy supplements. healthcare-11-00713-t001_Table 1 Table 1 Split between urban and rural for the consumer segments. Quantitative Sample Split Consumers Rural Urban Pregnant women who are current users of prenatal supplements 100 100 Pregnant women who are aware non-users of prenatal supplements 101 101 TOTAL CONSUMERS (B) 201 201 healthcare-11-00713-t002_Table 2 Table 2 Pregnant women participant details. Characteristic n (%) Stage of pregnancy 1st trimester 76 (18.9) 2nd trimester 154 (38.3) 3rd trimester 172 (42.8) Age range (in years) 18-20 119 (29.6) 21-25 145 (36.1) 26-30 99 (24.6) 31-35 31 (7.7) 36-40 8 (2.9) Highest level of education Below primary 36 (9.0) Primary 126 (31.3) Secondary 100 (24.9) Secondary School Certificate (SSC) 60 (14.9) Higher Secondary Certificate (HSC) 50 (12.4) Graduation 16 (4.0) Post-Graduation 4 (1.0) No education 7 (1.7) Madrasa Education 3 (0.7) Household monthly income Below BDT 5000 (approximately USD 58) 9 (2.2) BDT 5000-10,000 (approximately USD 58-116) 141 (35.1) BDT 10,000-20,000 (approximately USD 116-232) 172 (42.8) BDT 20,000-30,000 (approximately USD 232-350) 56 (13.9) BDT 30,000-50,000 (approximately USD 350-580) 22 (5.5) BDT 50,000-100,000 (approximately USD 580-1150) 2 (0.5) Work status Homemaker 374 (93.0) Entrepreneur/small business owner 5 (1.2) Garments worker 3 (0.7) Teacher 7 (1.7) Service 5 (1.5) Student 3 (0.7) Handicraft (working from home/odd jobs) 3 (0.7) Farming 2 (0.5) healthcare-11-00713-t003_Table 3 Table 3 Supplements that were currently taken during pregnancy by the users. Issues Frequency (n) Percentage (%) Number of supplements taken during pregnancy 1 supplement 42 21 2 supplements 100 50 3 supplements 49 24.5 4 supplements 9 4.5 Type of supplement Calcium tablets 146 34.4 Folic acid 46 10.8 Iron and folic acid 13 3.1 Iron tablets 129 30.4 Multivitamin 91 21.3 healthcare-11-00713-t004_Table 4 Table 4 Reported barriers to uptake of supplements. Responses Segment 1 Segment 2 Mann Whitney U Test N % N % Significance In-laws/husband doesn't allow 16 8 36 17.8 -2.930 ** Husband is reluctant to bring/buy it 3 1.5 20 10 -3.622 ** People are not aware of its benefit 10 5 26 12.8 -2.760 ** It is expensive 13 6.5 31 15.3 -2.837 ** ** Significant at 5-percent level (p = 0.05). healthcare-11-00713-t005_Table 5 Table 5 Awareness about the benefits of taking pregnancy supplements. Responses N % Not falling sick 109 54.5 Able to do regular work 94 47.0 Able to eat regular foods 78 39.0 Baby is growing well inside 42 21.0 Having enough nutrition 59 29.5 None 3 1.5 Stays healthy 5 2.5 Reduce vomiting 3 1.5 Other 3 1.5 Do not know 1 0.5 N healthcare-11-00713-t006_Table 6 Table 6 Sample details. Providers Sample Split Rural Urban Blue Star Network 100 100 Green Star Network 50 50 Pink Star Network 15 15 healthcare-11-00713-t007_Table 7 Table 7 Awareness of timing to start consuming pregnancy supplements by pregnant women. Responses [This Was a Multiple Response Question] N % As soon as they conceive 109 32.9 Immediately after first trimester 206 62.2 When trying for a baby 13 3.9 Immediately after 2nd trimester 33 10.0 During the end of the pregnancy/around 9 months 1 0.30 According to doctor's advice or if experiencing specific health issues, such as weakness 2 0.60 Before conceiving 1 0.30 healthcare-11-00713-t008_Table 8 Table 8 Perceptions about the barriers to women consuming pregnancy supplements. Barriers [This Was a Multiple Response Question] N % Doctors do not prescribe it 14 4.2 Elderly people discourage 46 13.9 Feels risky 3 0.9 In-laws do not allow / husband does not allow 26 7.9 It is expensive 8 2.4 Not available all the time 12 3.6 No barrier 186 56.2 Other 8 2.4 Does not know 2 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. References 1. Arlappa N. Laxmaiah A. Balakrishna N. Harikumar R. Kodavanti M.R. Gal Reddy C.H. Saradkumar S. Ravindranath M. Brahmam G.N.V. Micronutrient deficiency disorders among the rural children of West Bengal, India Ann. Hum. Biol. 2011 38 281 289 10.3109/03014460.2010.536572 21155655 2. Sankar R. Beesabathuni K. A New Look at Take Home Rations 2020 Available online: (accessed on 15 May 2022) 3. De Maeyer E.M. Preventing and Controlling Iron Deficiency through Primary Care World Health Organization Geneva, Switzerland 1989 4. Haider B.A. Bhutta Z.A. Multiple-micronutrient supplementation for women during pregnancy Cochrane Database Syst. Rev. 2015 2015 CD004905 10.1002/14651858.CD004905.pub4 26522344 5. 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PMC10000409 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050773 cells-12-00773 Article Zinc Supplementation Induced Transcriptional Changes in Primary Human Retinal Pigment Epithelium: A Single-Cell RNA Sequencing Study to Understand Age-Related Macular Degeneration Emri Eszter Conceptualization Methodology Formal analysis Investigation Writing - original draft Writing - review & editing Visualization 12+ Cappa Oisin Conceptualization Methodology Formal analysis Investigation Writing - review & editing Visualization 1+ Kelly Caoimhe Formal analysis Visualization 1 Kortvely Elod Conceptualization Writing - review & editing 3 SanGiovanni John Paul Formal analysis Writing - review & editing Visualization 4 McKay Brian S. 5 Bergen Arthur A. Writing - review & editing Supervision Funding acquisition 26 Simpson David A. 1 Lengyel Imre Conceptualization Formal analysis Investigation Writing - original draft Writing - review & editing Visualization Supervision Project administration Funding acquisition 1* Koch Karl-Wilhelm Academic Editor 1 Wellcome-Wolfson Institute for Experimental Medicine, Queen's University of Belfast, Belfast BT97BL, UK 2 Section Ophthalmogenetics, Department of Human Genetics, Queen Emma Centre for Precision Medicine, Amsterdam UMC, Location AMC, 1105AZ Amsterdam, The Netherlands 3 Immunology, Infectious Diseases and Ophthalmology (I2O) Discovery and Translational Area, Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland 4 Biosciences Research Laboratories, BIO5 Institute, University of Arizona, 1230 North Cherry Avenue, Tucson, AZ 85724, USA 5 Department of Ophthalmology and Vision Science, University of Arizona, 1656 E. Mabel Street, Tucson, AZ 85724, USA 6 The Netherlands Institute for Neuroscience (NIN-KNAW), 1105AZ Amsterdam, The Netherlands * Correspondence: [email protected] + These authors contributed equally to the work. 28 2 2023 3 2023 12 5 77305 2 2023 23 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 ). Zinc supplementation has been shown to be beneficial to slow the progression of age-related macular degeneration (AMD). However, the molecular mechanism underpinning this benefit is not well understood. This study used single-cell RNA sequencing to identify transcriptomic changes induced by zinc supplementation. Human primary retinal pigment epithelial (RPE) cells could mature for up to 19 weeks. After 1 or 18 weeks in culture, we supplemented the culture medium with 125 mM added zinc for one week. RPE cells developed high transepithelial electrical resistance, extensive, but variable pigmentation, and deposited sub-RPE material similar to the hallmark lesions of AMD. Unsupervised cluster analysis of the combined transcriptome of the cells isolated after 2, 9, and 19 weeks in culture showed considerable heterogeneity. Clustering based on 234 pre-selected RPE-specific genes divided the cells into two distinct clusters, we defined as more and less differentiated cells. The proportion of more differentiated cells increased with time in culture, but appreciable numbers of cells remained less differentiated even at 19 weeks. Pseudotemporal ordering identified 537 genes that could be implicated in the dynamics of RPE cell differentiation (FDR < 0.05). Zinc treatment resulted in the differential expression of 281 of these genes (FDR < 0.05). These genes were associated with several biological pathways with modulation of ID1/ID3 transcriptional regulation. Overall, zinc had a multitude of effects on the RPE transcriptome, including several genes involved in pigmentation, complement regulation, mineralization, and cholesterol metabolism processes associated with AMD. zinc retinal pigment epithelium single-cell RNA sequencing age-related macular degeneration maturation F. Hoffmann La Roche LtdBelfast Association of BlindEuropean Union's Horizon 2020 research and innovation program634479 Netherlands Neuroscience Institute (NIN-KNAW)This research was funded by unrestricted grants from F. Hoffmann La Roche Ltd., Belfast Association of Blind, the EYE-RISK project funded by the European Union's Horizon 2020 research and innovation program under grant agreement no. 634479 (Oogfonds, Rotterdamse Stichting Blindenbelangen, Landelijke Stichting voor Blinden en Slechtzienden, Algemene Nederlandse Vereniging ter voorkoming van Blindheid), contributed through UitZicht, The Foundation Friends of the Netherlands Neuroscience Institute (NIN-KNAW), fund H-I. pmc1. Introduction The retinal pigment epithelium (RPE) is a highly polarized monolayer of cells lining the back of the eye which provides critical support for the functioning of the adjacent photoreceptors. It is part of the outer blood-retina barrier that regulates the transport of metabolites between the bloodstream and the neural retina. The RPE undergoes structural and functional transitions during maturation, which are essential to fulfill its biological functions . Because of its critical function, the RPE has been directly implicated in several retinal diseases, most notably age-related macular degeneration (AMD). A hallmark feature of AMD is the accumulation of protein-, lipid-, and mineral-rich deposits between the RPE and the choroidal microcapillary network . The size and number of these sub-RPE deposits increase with disease progression . Another hallmark is pigmentary changes associated with the RPE . Both of these are linked to the progression to end-stage AMD manifested as geographic atrophy (GA), characterized by progressive degeneration and loss of the RPE layer, or as neovascular (NV) AMD, which is characterized by abnormal leaky blood vessels that grow from the choroid into the sub-RPE space (Type 1), sub-retinal space (Type 2), or the retina (Type 3) , causing fluid accumulation and scarring . Zinc is part of a nutritional supplement endorsed by the National Eye Institute (NEI) to slow the progression from mild/moderate to advanced AMD . The biochemical pathways involved in these beneficial effects are not fully understood. Recent studies showed that human primary RPE cells in long-term culture model the hallmark features of AMD. RPE cell-based models develop as monolayers with tight junctions and high transepithelial resistance (TEER), extensive pigmentation, specific gene expression profiles, and also sub-RPE deposits , many of which can be affected by zinc supplementation directly . This in vitro model system can be manipulated experimentally and interrogated longitudinally under conditions resembling health and disease. In this study, we identified dynamic changes in gene expression and the effects of acute (1 week) zinc supplementation using single-cell RNA sequencing (scRNA-Seq). Our results elucidate several specific pathways involved in the maturation of RPE to a stage that develops hallmark changes of AMD (sub-RPE deposition and pigmentary changes) and how these are modified by zinc supplementation. 2. Materials and Methods 2.1. Retinal Pigment Epithelial (RPE) Cell Culture Primary human fetal RPE cells (ScienCell, Carlsbad, CA, USA) from one donor were purchased and used at passage three (P3) for the complete study in duplicates/triplicates with unknown clinical or genetic background. Cells were seeded onto Corning 6-well transwell inserts (10 mm thick polyester inserts with 0.4 mm pore size, 4 x 106/cm2 pore density, Corning, Wiesbaden, Germany) in 125.000/cm2 of epithelial cell medium (EpiCM, ScienCell, Carlsbad, CA, USA). After one week in culture, cell culture media were replaced with Miller medium with 1% FBS and cells were cultured for two, nine, and nineteen weeks in duplicates. Two types of short-term zinc treatment were also conducted, where one-one extra replicates of untreated controls were taken for the two types of zinc treatment experimental setup. After one week or eighteen weeks in culture, cell culture media were replaced with Miller medium with 1% FBS for an additional one week in the absence or presence of 125 mM externally added zinc (as zinc sulphate; Thermo Fisher Scientific, Waltham, MA, USA) both in the apical and basal chambers, resulting in ~10 nM bio-available or free zinc . The resulting replicates were the following: duplicates of zinc-treated samples, triplicates of untreated controls at the nineteen-week time point, and duplicates of untreated controls at the nine-week time point. Cellular differentiation was monitored through the development of cobblestone cell morphology and increase in pigmentation using light microscopy. The increase in transepithelial resistance (TEER) was measured using the EVOM2 Epithelial Voltohmmeter and STX2 electrodes (World Precision Instruments, Sarasota, FL, USA). At the sample collection time, as detailed above, cells were washed with PBS (Thermo Fisher Scientific, Waltham, MA, USA) two times for one minute. Cells were detached by incubation with 0.15 % Trypsin-EDTA for thirty minutes at 37 degC. The trypsinization was stopped using 100% FBS and trypsin neutralization solution (ScienCell, Carlsbad, CA, USA). The obtained single-cell suspensions were washed in PBS with 1% BSA (Thermo Fisher Scientific, Waltham, MA, USA) 2 times for 5 min at 1000 rpm. After automatic cell counting (EVE, Thermo Fisher Scientific, Waltham, MA, USA), 7 x 105 cells/mL were prepared, and the cells were kept on ice for a maximum of ten minutes before proceeding with single-cell RNA sequencing. In parallel to single-cell sequencing, adjacent samples were fixed for fifteen minutes in 4% PFA (Merck, Darmstadt, Germany) diluted in PBS (Thermo Fisher Scientific, Waltham, MA, USA) for immunofluorescence. 2.2. Experiment Overview Our previous study showed individual differences in assaying primary hfRPE from different donors . To overcome the variations introduced by variability in donor samples and to generate a reproducible zinc effect, in this manuscript, experiments were performed on primary hfRPE cells from a single donor. In the initial scRNA-Seq run, samples were obtained from RPE cells cultured for two weeks (2W), nine weeks (9W), and nineteen weeks (19W) in duplicates. Cells were collected from two wells at these time points. A total of 7000 cells from each sample were loaded on 10x Genomics Chromium v1.3 with a target recovery of 4000. Libraries made from each sample were pooled and sequenced. In the second run, samples originated from RPE cultures were treated with a zinc-supplemented medium for one week either after: (1) one week in culture or (2) eighteen weeks in culture in duplicates. We also included one-one sample from untreated RPE culture in this run and the transcriptomic profiles were generated in a pooled fashion as described above. The actual cell recovery of both runs ranged from 3000 to 4000 in each well, resulting in a total recovery of ~30,000 cells for the first run and ~15,000 for the second run. The raw scRNA-Seq data were processed using CellRanger v3.0.0. and then Seurat v3.1 to determine the heterogeneity of our specimens using unsupervised clustering, followed by annotation based on hierarchical clustering of a pre-defined set of canonical RPE marker genes (Supplementary Table S3). For further analysis, we initially analyzed our samples of untreated control RPE cultures from the two runs (triplicates for 2W and 19W and duplicates for 9W cultures). We then separately analyzed the duplicate samples of our zinc-treated RPE cultures compared to the triplicate samples of untreated control RPE cultures of 2W and 19W. 2.3. scRNA-Seq Approximately 7000 single cells per sample were processed with the Chromium system using the v3 single-cell reagent kit (10x Genomics, San Francisco, CA, USA). Barcoded libraries were pooled and sequenced on the NovaSeq platform (Illumina, San Diego, CA, USA), generating 150 bp paired-end reads as per 10x Genomics recommendations, with >30,000 reads per cell. 2.4. Bioinformatics The raw scRNA-Seq data were processed using CellRanger version 3.0.0 (10x Genomics). The resulting filtered expression matrices were then imported into R for analyses using scRNA-Seq packages, Seurat (Version 3.1) (Stuart et al. 2019) and Monocle (Version 3.0) (Trapnell et al. 2014; Cao et al. 2019). Cells were filtered to exclude those with <1000 or >8000 genes, or with >20% of counts aligned to mitochondrial genes, or >40% counts aligned to ribosomal genes. Cells passing QC were downsampled randomly to 1000 cells per sample to prevent under-representation of any sample. Each sample was log-normalized using default Seurat parameters, with the top 3000 highly variable genes used for Seurat iterative pairwise integration. The integrated dataset was scaled to regress variance arising from read depth and mitochondrial and ribosomal expression. Principal Component Analysis was then performed on the integrated dataset, and Seurat's JackStraw function was applied to determine the components used in UMAP and SNN clustering. Unsupervised clustering was run iteratively at resolutions ranging from 0.25 to 1, at increments of 0.25. At the highest resolution, a total of 13 clusters were detected. These clusters were observed in UMAP to form two overall, as-yet unannotated cell populations. Using untreated cells only, the average expression for the clusters was determined for a set of 213 canonical RPE marker genes (Supplementary Table S3) to which hierarchical clustering was applied. The clusters were segregated into two distinct branches, exhibiting characteristics of more and less differentiated RPE, which matched the distinction observed in UMAP. As such, the 13 unsupervised clusters were annotated to reflect these two overall cellular populations for downstream differential expression analysis. Seurat's Wilcoxon rank sum test was used for differential expression testing, using default FindMarkers parameters, with genes below 0.05 adjusted p-value considered significantly differentially expressed. Monocle 3 was used for pseudotime analysis, for which downsampled count data were imported from Seurat and independently processed and batch-corrected in Monocle using default parameters. For continuity, a pseudotime trajectory graph was calculated and projected on the UMAP coordinates preserved from Seurat analysis. The data were filtered to focus on the main less differentiated to more differentiated pseudotemporal trajectory, by excluding small branches not contributing to the main trajectory. This was followed by graph autocorrelation analysis to detect gene expression changes correlating with progress along the trajectory, filtered for significance at p-value and Q-value <0.05. Genes with expression significantly correlated with the trajectory were grouped into 'modules' of co-regulated genes and the average expression of each gene module calculated across pseudotime. 2.5. Functional Classification Pathway and Network Analysis For pathway and network analysis, we used the GeneAnalytics accessed on 14 March 2021) and STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) 11.0 accessed on 14 March 2021) in combination with Cytoscape . GeneAnalytics uses binomial distribution to test the null hypothesis that the queried genes are not over-represented within any superpath, GO term, or compound in the GeneAnalytics data sources. The presented score in each section is a transformation of the resulting p-value, corrected for multiple comparisons using the false discovery rate (FDR) method, with higher scores indicating a better match. The bar color, indicating the matching quality--high (dark green), medium (light green), low (beige)--is common for all sections. STRING in combination with Cytoscape implements classification systems such as Gene Ontology, KEGG, and systems based on high-throughput text mining and the used reference dataset was the human genome. The identified functional protein association network was validated via text mining, database information, co-expression, and experimental evidence. 2.6. Immunofluorescence For immunofluorescence analysis, the cells on the transwell membrane were permeabilized in 0.5% Triton-X (Merck, Darmstadt, Germany) in PBS for ten minutes at 4 degC and then washed in 0.1% Tween20 in PBS (PBST) (Merck, Darmstadt, Germany) and blocked with 5% goat sera (Merck, Darmstadt, Germany) in PBST for one hour at room temperature. Samples were then incubated with primary antibodies overnight: COL1A1 (Abcam plc, Cambridge, UK, dilution 1:200) and RPE65 (Merck Millipore, Darmstadt, Germany, 1:50), diluted in PBST containing 1% goat sera. Following washing with PBST, the samples were incubated with secondary antibodies in 1:200 in PBST with 1% goat sera for one hour in the dark at room temperature. Samples were washed with PBST for five minutes, then with PBS. Cell nuclei were then labelled with DAPI (Thermo Fisher Scientific, Waltham, MA, USA) diluted 1:1000 in PBS. Finally, samples were mounted onto Menzel-Glaser slides (Thermo Fisher Scientific, Waltham, MA, USA) in Vectashield (Vector Laboratories, Burlingame, CA, USA). For negative control, the primary antibody labelling was omitted. Cells were visualized using a Leica SP8 confocal microscope (Leica, Wetzlar, Germany). Images were obtained and analyzed with Leica Application Suite X Image software (Leica, Wetzlar, Germany). 3. Results 3.1. Maturation of RPE Cells in Culture Primary human fetal RPE cells from a single donor were cultured for 2 weeks (2W = short term), 9 weeks (9W = medium term), and 19 weeks (19W = long term) . We used culture conditions that, in our hands, reproducibly recapitulated key aspects of RPE cells as described in previous studies . As time in culture increased, RPE cells were observed to develop pigmentation, hexagonal morphology , and a progressively increasing epithelial barrier function (112.9 +- 3.9 Ohm x cm2 at 2W, 195.2 +- 16.6 Ohm x cm2 at 9W, and 201.36 +-49 Ohm x cm2 in 19W in culture). The cell cultures also began accumulating sub-RPE deposits containing lipids and hydroxyapatite that we have shown earlier . To identify the transcriptomic profiles of RPE cells at the three time points, we collected cells from three wells at 2W and 19W and two wells at 9W in culture (see Section 2 for detail). Approximately 3000-4000 cells were captured from each well and processed on the 10x Genomics Chromium v1.3 platform, with transcriptomes generated for a total of 30,000 cells. 3.2. Cluster Analysis of the scRNA-Seq Data Identifies Significant Heterogeneity of RPE Cells 3.2.1. Unsupervised Clustering Analysis To ensure equal representation from all conditions, all samples were downsampled to include an equal number (1000) of randomly selected cells in Seurat 3.1 . Based on 3417 differentially expressed transcripts (Supplementary Table S1), the cells were automatically allocated into thirteen clusters and visualized on a Uniform Manifold Approximation and Projection (UMAP) plot . The lists of cluster-specific 'marker' genes were input into GeneAnalytics. The gene set analysis tool identified significant cluster-specific canonical pathways , labelled as superpathways for the functional analysis of the cell populations. Supplementary Table S2 contains information on the 'marker' genes, numbers of enriched pathways, and matched number of genes to the total number of genes in a pathway for each cluster. The software assigned the 312 genes in Cluster 0 to 18 superpathways, with respiratory electron transport and heat production of uncoupling proteins, metabolism, and visual cycle among the top five hits. The 205 genes in Cluster 1 were assigned to 44 superpathways, with degradation of extracellular matrix, ERK signalling, and phospholipase C pathway amongst the top five hits. The 270 genes in Cluster 2 were associated with 19 superpathways with metabolism, respiratory electron transport, heat production of uncoupling proteins, and visual cycle amongst the top five hits. In Cluster 3, the 210 differentially expressed genes were associated with 76 superpathways with cytoskeletal signalling, ERK signalling, and focal adhesion among the top five hits. The 87 differentially expressed genes in Cluster 4 were associated with 29 superpathways with cytoskeletal signalling, ERK signalling, and integrin signalling among the top five hits. The 30 differentially expressed genes in Cluster 5 were associated with two superpathways: melanin biosynthesis and tyrosine metabolism. The 270 differentially expressed genes in Cluster 6 were associated with 50 superpathways, degradation of extracellular matrix, metabolism of proteins, and cell adhesion and ECM remodelling amongst the top five hits. In Cluster 7, 313 differentially expressed genes were associated with 110 superpathways with cytoskeletal signalling, ERK signalling, and degradation of extracellular matrix among the top five hits. The 303 differentially expressed genes in Cluster 8 were associated with 61 superpathways, degradation of extracellular matrix, ERK signalling, and phospholipase C pathway among the top five hits. In Cluster 9, we identified 302 differentially expressed genes associated with 21 superpathways with metabolism, visual cycle, and copper homeostasis among the top five hits. In Cluster 10, 198 differentially expressed genes were associated with 24 superpathways with metabolism, visual cycle, and oxidative stress among the top five hits. The 807 differentially expressed genes in Cluster 11 were associated with 86 superpathways, degradation of extracellular matrix, protein processing in the endoplasmic reticulum, and cytoskeletal signalling amongst the top five hits. Finally, in Cluster 12, 164 differentially expressed genes were associated with 11 superpathways with organelle biogenesis and maintenance, intraflagellar transport, and mitotic cell cycle among the top five hits. The identification of thirteen clusters shows that cells in culture are not homogenous. 3.2.2. Hierarchical Clustering Analysis Using Markers of Mature RPE Cells We aimed to identify which of the unsupervised clusters most resemble mature RPE. We separated cells that were deemed to be more differentiated based on the expression of 213 RPE-specific genes we identified from several publications (Supplementary Table S3). Hierarchical clustering based on the gene list divided the 13 clusters into two distinct groups . We annotated clusters 0, 2, 5, 9, 10, and 12 as 'more differentiated' RPE cells and the remaining clusters (1, 3, 4, 6, 7, 8, and 11) 'less differentiated' cells . We use the terms 'more differentiated' and 'less differentiated' from this point forward. The more and less differentiated cells are separated on the original UMAP ). We calculated the proportion of more and less differentiated cells at the 2W, 9W, and 19W. Interestingly, nearly half of the cells were more differentiated even as early as 2W or 9W in culture (2W = 41%, 9W = 41%). By 19W, the proportion of the more differentiated cells increased to 73% ), with 27% remaining less differentiated. Supplementary Table S4 lists the genes that define the more and less differentiated groups. The expression levels of three highly expressed representative genes from each group are presented as violin plots and UMAP plots in Supplementary Figure S2, highlighting the enrichment but not the exclusive presence of these genes in one or the other group. Next, we tested whether the protein products of the genes that distinguish more and less differentiated cells show differential expression. One of the highly expressed mRNAs in the less differentiated cells was Collagen Type I alpha 1 chain (COL1A1), fibril-forming collagen. The RPE secretes the protein encoded by this gene and it is found in the sub-RPE space . We found that the expression of COL1A1 gradually increased in the less differentiated group and decreased in the more differentiated group . In contrast, Retinoid Isomerohydrolase (RPE65), a visual cycle component marker for differentiated RPE, was mainly expressed in the more differentiated group . Both genes were expressed in the other group but at a low level in the opposing groups . Next, we determined the immunolocalization of the COL1A1 and RPE65 proteins in the 19W RPE monolayer. In line with the gene expression results, the cells with a strong RPE65 immunolabelling also had weak intracellular immunoreactivity for COL1A1 proteins, and cells with strong immunolabelling for COL1A1 showed weak labelling for RPE65 . Immunolabeling of COL1A1 is also present in the sub-RPE space. This extracellular immunoreactivity gradually increased with time in culture , suggesting that the secreted COL1A1 accumulates as part of the developing extracellular sub-RPE material . As we identified more and less differentiated RPE cells in our hfRPE, we investigated whether more and less differentiated cells are also present in RPE cells directly isolated from human eyes. We used two independent previously published datasets: the scRNA-Seq data obtained from human embryos or adult human eyes . We applied our cell grouping strategy based on 213 RPE-specific signature genes (Supplementary Table S2). Indeed, our analysis showed that both the embryonic RPE ) and adult RPE ) could be classified into more and less differentiated cell populations. Of note, the number of cells analyzed in the publication using adult RPE was relatively low. Hence, clusters were less well separated. 3.3. Pseudotemporal Ordering of the Expressed RPE Genes To identify the genes associated with transitioning from the less to the more differentiated cells, we performed a pseudotemporal ordering of our scRNA-Seq transcriptome profile using Monocle3 . This unsupervised analysis identified a main trajectory with 11 nodes ). Based on the original cluster analysis depicted in Figure 1, node 1 corresponded to the less and node 10 to the more differentiated cells ). The main trajectory was correlated with 537 variably expressed genes. Based on their pseudotemporal expression profile, these clustered into seven modules ; Supplementary Table S5). Modules 2 and 5 contained 175 genes with high expression at the early stages of the trajectory that gradually declined towards the end of the trajectory. GeneAnalytics identified 62 potential significant superpathways associated with these genes (Supplementary Table S6). Degradation of extracellular matrix, focal adhesion, and cell adhesion-endothelial cell contacts were amongst the top five ranked pathways. Modules 3, 4, and 6 contained 172 genes. These gradually increased towards the late stages of the trajectory. GeneAnalytics identified nine potential superpathways defined by these genes, including the transport of glucose, metabolism, and visual cycle among the top five hits (Supplementary Table S6). Modules 1 and 7 contained 190 genes. The expression of these genes transiently increased to a maximum at the middle of the trajectory followed by a decrease over pseudotime. These identified sixteen superpathways with degradation of extracellular matrix, ERK signalling, and cytoskeleton remodelling among the top five hits (Supplementary Table S6). To identify potential transcriptional regulators of the pseudotemporal trajectory, GO term analysis was carried out in GeneAnalytics. This identified transcriptional regulator activity in two genes, ID1 and ID3, belonging to the combined Module 1 and 7, representing the transitional phase on the pseudotemporal trajectory. Next, we examined the potential relationships between the most highly significantly correlated in the main trajectory using a cut-off value of Moran I = 0.5 (see Section 2). We identify 44 genes strongly influencing the main trajectory. Using GeneAnalytics in combination with STRING database and Cytoscape, we found that these genes do not appear to be randomly distributed. A total of 31 out of 44 genes showed a significant biological connection, validated via text mining, database information, co-expression, or experimental evidence ). The 44 genes were associated with six potential superpathways, including visual cycle, extracellular matrix degradation, and cell adhesion-extracellular matrix remodelling as the top hits (Supplementary Table S6). 3.4. Acute Zinc Supplementation Has a Multitude of Effects on Transcription in RPE Cells 3.4.1. Transcriptional Changes in Response to Acute Zinc Supplementation Previous studies have shown that chronic zinc supplementation has clinical benefit associated with molecular and cellular changes , but the effects of acute or short-term zinc supplementation had not been studied in detail. To identify the effects of short-term zinc supplementation, we treated our RPE cultures for one week with a zinc-supplemented medium, using the same approach as we described earlier . This acute zinc supplementation was carried out on less differentiated cells starting at the end of the first week in culture. Then, cells were harvested at the end of 2W or more differentiated cells at the end of the 18th week, and cells were harvested at the end of 19W. Gene expression changes with zinc supplementation were compared to cells in culture without zinc supplementation for either 2W or 19W. Cells with and without zinc supplementation were clustered using the process used in Figure 1(C1). While acute zinc supplementation did not noticeably change the proportion of the more and the less differentiated cells , it significantly changed the expression of 472 genes in the more differentiated cells ) and 149 genes in the less differentiated cells ) at the two-week time point (Supplementary Table S7). At 19W, zinc altered the gene expression of 487 genes in the more differentiated cells ) and 417 genes in the less differentiated cells ) (Supplementary Table S7) (logFC > 0.25, adjusted p-value < 0.05). We displayed the four datasets in a four-way Venn diagram to further analyze specific temporal zinc-induced gene expression changes . We found 81 overlapping genes differentially expressed under all four conditions. Two-thirds of these 81 genes were identified as housekeeping genes by GeneAnalytics, confirming previous studies showing that zinc plays a role in regulating cellular homeostatic processes . Relevant proteins include metallothioneins (MT1E, MT1F, and MT1X) that act as essential stress proteins to regulate immune homeostasis. In the more differentiated cells, 222 uniquely affected genes were at 2W and 163 at 19W . In the less differentiated cells, only four genes were specifically affected by zinc supplementation at 2W and 94 genes at 19W . At 2W, we identified superpathways only in the more differentiated cells; these were cytoskeleton remodelling, focal adhesion, and degradation of extracellular matrix among the top five superpathways (Supplementary Table S8). At 19W, in the less differentiated cells, we identified presenilin signalling, SMAD signalling, and antigen-presenting cross-presentation amongst the top five superpathways (Supplementary Table S8). In contrast, in the more differentiated cells, we identified metabolism, ferroptosis, and protein processing in the endoplasmic reticulum amongst the top five superpathways (Supplementary Table S8). Information on the magnitude and direction of zinc-associated change in transcript abundance of these gene lists is provided in Supplementary Table S7. The analysis of these five gene lists by GeneAnalytics to identify superpathways is listed in Supplementary Table S8. 3.4.2. Influence of Zinc on Transcription Dynamics We next determined the overlap between the 537 genes identified in the main trajectory in the pseudotemporal analysis ; Supplementary Table S5) and the list of the differentially expressed genes following the acute zinc supplementation ; Supplementary Table S7). This comparison identified 16 common genes (Supplementary Table S9). Using GeneAnalytics in combination with STRING database and Cytoscape, we found that these 16 genes show significantly (p-value < 1.0 x 10-16) more interactions than expected, validated by text mining, database information, co-expression, and experimental evidence ) that relates to the respiratory electron transport and response to metal ions as biological function (Supplementary Table S9). 3.5. Sub-RPE Deposition-Related Gene Expression Pattern Depends on Maturation State and Zinc Supplementation Our hfRPE culture developed sub-RPE deposits even without photoreceptors and the supporting choriocapillaris . This allowed us to analyze the expression of genes potentially involved in the sub-RPE deposit formation process. We compiled lists of genes associated with various aspects of sub-RPE deposit formation and analyzed the changes in expression throughout cell maturation and zinc supplementation (Supplementary Table S11). Some genes belong to more than one gene list . 3.5.1. Genelist 01 This contains 55 genes previously genetically associated with AMD . We found that 52 out of the 55 genes in AMD-risk-associated risk loci were expressed in our RPE model (Supplementary Table S11). Some genes were expressed higher at 2W, like CFHR3, LIPC, SYN3, and VTN, while others were expressed higher at 19W, like ARHGAP21, RDH5, SKIV2L, SRPK2, TGFBR1, and TRPM3. Among the genes expressed higher in less differentiated cells were CFHR3, LIPC, TGFBR1, and VTN. In more differentiated cells, we found higher expression of PRLR, RDH5, RORB, SLC16A8, SPEF2, and VEGFA. From these 52 genes, CFH, COL8A1, CD63, TSPAN10, APOE, TIMP3, and SLC16A8 were significantly upregulated, while CFHR1, VEGFA, TRPM3, and RDH5 were significantly downregulated in response to acute zinc supplementation (Supplementary Table S7). 3.5.2. Genelist 02 This contains 66 complement-regulation-related genes. Several complement proteins have been implicated in AMD and are found in sub-RPE deposits . A total of 41 out of the 66 identified complement genes were expressed in our hfRPE cultures, most showing low expression levels (Supplementary Table S11). The genes that were expressed higher in 2W cultures were C4B, C4BPB, C8B, C8G, CFHR3, CFP, CSMD1, CSMD3, TPSG1, and VTN, while the genes expressed higher in 19W cultures were C1S, CD55, CD59, and PTX3. Among the genes expressed higher in less differentiated cells were C4BPA, C4BPB, `C8G, CFHR3, CFP, CR2, CSMD1, FHL-1, ITGB2, PTX3, and VTN. The expressions of C2, C4A, C5, CR1, and SERPING1 were higher in the more differentiated cells. CFH and C1R were significantly upregulated, while CFHR1 and CLU were significantly downregulated in response to zinc supplementation (Supplementary Table S7). 3.5.3. Genelist 03 This contains cholesterol-metabolism-related genes . A total of 42 out of the 51 identified genes were expressed in hfRPE (Supplementary Table S11). The genes that were expressed higher at 2W were ABCG5, ANGPTL8, APOA1, CD36, LIPC, and STAR, while the genes expressed higher at 19W were APOC1, LDLRAP1, and NPC1. Among the genes expressed higher in less differentiated cells were CD36, LIPC, PCSK9, and STAR. In the more differentiated cells, the expressions of CYP27A1, LIPG, LPL, and PLTP were higher. PLTP, ANGPTL4, APOE, LRPAP1, VDAC2, and TSPO were significantly upregulated, and NPC2 was significantly downregulated in response to zinc supplementation. Interestingly, CYP27A1 showed significant upregulation at 2W and significant downregulation at 19W in response to zinc supplementation (Supplementary Table S7). 3.5.4. Genelist 04 This contains mineralization-related genes that could be associated with the inorganic hydroxyapatite component of sub-RPE deposits. A total of 80 out of the identified 99 calcification-related genes were expressed in the RPE (Supplementary Table S11). The genes that were expressed higher at 2W were COL10A1, NKX3-2, PHEX, SPP1, TNFRSF11B, and WNT7B, while others were expressed higher at 19W, including AP1S2, BMP2, CLCN3, LAMP1, POSTN, SMAD1, and SOX9. Among the genes expressed higher in less differentiated cells were AP1S1, COL10A1, COL1A1, DLX5, IBSP, JAM2, LAMP1, MGP, MYORG, NKX3-2, PDGFB, PHEX, POSTN, and RUNX2. The expressions of ABCC6, BMP2, BMP7, CNMD, SOX6, and WNT6 were higher in the more differentiated cells. COL1A1, POSTN, CD63, LAMP1, and BMP4 were significantly upregulated and SLC20A1, SOX9, and BMP7 were significantly downregulated in response to zinc supplementation (Supplementary Table S7). 3.5.5. Genelist 05 This contains genes that are related to pigmentation . Pigmentary abnormalities show strong correlation with sub-RPE deposit formation and the development of AMD, and we found that 19 out of the identified 21 genes were expressed in hpRPE (Supplementary Table S11). At 2W, we found no differentially expressed genes. At 19W, however, we found that AP3B1, AP3D1, BLOC1S6, HPS5, HPS6, and SLC24A5 were expressed higher. There were no highly expressed genes in less differentiated cells. In the more differentiated cells, the expression of OCA2 and SLC24A5 was higher. TYR, TYRP1, and DCT were significantly downregulated in response to zinc supplementation in our acute treatment (Supplementary Table S7). 4. Discussion The RPE plays a pivotal role in maintaining the health of the retina, and changes in RPE function have been linked to the development and progression of AMD . Optimal zinc balance is key for RPE function , and zinc deficiency contributes to AMD pathogenesis . Based on these findings, it has been suggested that zinc supplementation can slow the progression of AMD , although the mechanism of this beneficial effect is not fully understood . In this study, we used primary human fetal RPE cells and scRNA-Seq analysis to identify the transcriptomic changes and biologically plausible molecular pathways involved in the maturation of the RPE and the changes associated with zinc supplementation. The specific transcriptional changes and molecular pathways identified provide an improved understanding of RPE cell maturation and insight into how the function of RPE might be affected by acute zinc supplementation, which has relevance for the progression of AMD. 4.1. Study Rationale Maturation of RPE cells is key to developing appropriate morphology, pigmentation , and production of key signature proteins that determine the function of these cells . Different studies use a variety of sources to study RPE maturation and function, ranging from the immortalized ARPE-19 cells to induced pluripotent stem-cell-derived RPE and primary porcine or human RPE . As with all model systems, cellular models for RPE must replicate the in vivo situation as closely as possible. Recently we have shown that primary human fetal RPE cells develop the most critical features of native RPE, including the formation of pigmentation, tight junctions with high TEER values, and the expression of RPE signature genes and proteins . Most importantly, the cells in culture can lay down sub-RPE deposits, a hallmark feature of AMD . Despite demonstrating these in vivo-like features, the molecular signature for RPE maturation has not yet been fully explored. Previous studies have reported a variety of approaches to map molecular maturation. Earlier studies used microarrays or bulk RNA sequencing. Most recently, a powerful tool capable of sequencing individual cells has been introduced. Single-cell RNA sequencing provides an unparalleled opportunity to identify cell heterogeneity . Lidgerwood et al. used pluripotent stem-cell-derived RPE to analyze transcriptomic changes after 1 month or 12 months in culture and analyzed these separately, then combined the data. In a subsequent study, the same group combined scRNA-Seq and proteomics in iPSC cells obtained from individuals with or without AMD to identify regulations in geographic atrophy . Exciting opportunities are presented by scRNA-Seq studies using freshly isolated RPE from human eyes. RPE cells from both fetal and adult human eyes were analyzed in previous studies and , respectively). Although both studies used a limited number of cells, they provide invaluable insight for cell-culture-based observations. In our study, we used primary fetal RPE cells that recapitulated features of RPE cells in vivo . Despite their fetal origin, these cells developed sub-RPE deposits and varied pigmentation, suggesting that they recapitulate the hallmarks of AMD despite the relatively short time in culture (19W). 4.2. Heterogeneity of RPE Cells The generation of scRNA-Seq data from a large number of cells allowed us to confidently determine that there is a significant degree of heterogeneity between the cells. A key observation was that some RPE cells could develop into more differentiated cells even after 2 weeks in culture, but even after 19 weeks, we still observed less differentiated cells . Heterogeneity of RPE had been reported after multiple passages and over the years in culture , reflecting what had been reported for RPE in vivo and in situ . Despite the long-lasting heterogeneity, the melanosome precursor PMEL17 was expressed in both less and more differentiated cells. In fact, from the 19 pigmentation-related genes expressed in our cells, the only transcripts that showed elevated expression in the more differentiated RPE cells were OCA2 and SLC24A2 and Supplementary Table S11, Figure 5E), suggesting that all cells could become pigmented . COL1A1 was amongst the top transcripts in the less differentiated cells, and immunoreactivity of COL1A1 protein was able to distinguish the less differentiated cells from the more differentiated cells that express the RPE65 gene highly and are immunopositive for the RPE65 protein . Immunoreactivity to the COL1A1 protein gradually increased in the sub-RPE space with time in culture , suggesting that the half-life of this extracellular matrix protein is long in our culture system. This increase in sub-RPE COL1A1 may correspond to the role this protein plays in forming the extracellular matrix of Bruch's membrane . Other collagens were also expressed highly in the less differentiated cell population (Supplementary Table S4), reflecting their reported involvement in increased attachment and spread of RPE cells . The only highly expressed transcript for collagen in the more differentiated cells was COL8A1 (Supplementary Table S4). The COL8A1 protein is a component of basement membranes in the eye and contributes to the formation of the basement membrane of RPE and a genetic risk variant of AMD . The findings on COL1A1 and RPE65 might be mechanistically important: the mature RPE cells (RPE65 expressing) could enable the performance of the visual cycle, while the less differentiated cells (COL1A1 expressing) can support the formation of ECM throughout life. 4.3. Transition from Less to More Differentiated RPE As more and less differentiated cells are present at all three time points, we combined the scRNA-Seq data from the three time points and analyzed these datasets together, an approach different from a previous study . This integrated approach helped us to identify a pseudotemporal trajectory of gene expression from less to more differentiated cells ). This approach identified a well-defined main trajectory ). The top genes with the highest score in the main trajectory were associated with regulating the visual cycle (RPE65, LRAT, TTR, RDH5) (Supplementary Table S6). Transcriptomic analysis of the bulk RNA isolated from RPE cells from aging human donor eyes recently reported a positive feedback mechanism between the upregulation of visual cycle genes and the accumulation of retinoid by-products . As visual cycle-related bisretinoids are constituents of the accumulating lipofuscin in RPE , this upregulation could eventually lead to AMD-like pathogenesis in this cell culture model. Indeed, there are ongoing clinical trials for visual cycle modulators as therapeutic options for AMD , and our cell culture model has the potential to serve as a preclinical tool for testing novel compounds. 4.4. Genes Involved in Transitioning RPE from Less to More Differentiated Cells The genes associated with the main trajectory could be clustered into seven modules based on their transcriptional change along the pseudotemporal trajectory (Supplementary Table S5). The transcripts whose expression is transiently upregulated on the pseudotemporal trajectory likely represent the genes mediating the transition from the less to the more differentiated cells (Supplementary Table S5). These genes were associated with cellular and extracellular remodelling and metabolic pathways (Supplementary Table S6). Therefore, our data support the hypothesis that extracellular matrix remodelling of the Bruch's membrane could become a therapeutic target to combat RPE loss due to topographic changes in the RPE-Bruch's membrane interface . Alterations of the extracellular matrix may impact immune response as well as the secretion of pro-inflammatory cytokines, such as MCP-1 and IL-8 , and promote sub-RPE deposit formation . Our data highlights potential molecular targets to achieve a regulation of this process. Among the transiently expressed genes, we identified ID1 and ID3 (Supplementary Table S6). The corresponding helix-loop-helix (HLH) proteins form heterodimers with members of the basic HLH family of transcription factors, inhibiting DNA binding and preventing the formation of active transcriptional complexes . ID proteins promote cell cycle progression and cell migration and restrict cellular senescence and the differentiation of a number of progenitor cell types . Recent results indicate that the expression of ID family proteins may play an important role in regulating retinal progenitor cell proliferation and differentiation . ID genes and proteins showed increased expression levels in the retina at embryonic and early postnatal stages and declined in the adult . ID protein expression is silenced in many adult tissues but is re-activated in diverse disease processes . ID proteins appear to play a crucial role in the angiogenic processes. It was proposed that inhibition of expression and/or function of ID1 and ID3 may be of therapeutic value for conditions associated with pathological angiogenesis . In fact, the deletion of Id1/Id3 reduced ocular neovascularization in a mouse model of neovascular AMD . In conclusion, drugs targeting ID1/ID3 could modulate RPE maturation and pathological changes in AMD. 4.5. Response to Acute Zinc Supplementation Treatment with zinc has been reported to prevent progression to advanced AMD (for review, see ), at least partly due to a direct effect of zinc on the RPE . In previous in vitro studies, we investigated long-term supplementation with zinc and found altered selective gene expression, protein secretion, and increased pigmentation and barrier function . We identified several molecular pathways, such as cell adhesion/polarity, extracellular matrix organization, protein processing/transport, and oxidative stress response, involved in the beneficial effects of chronic zinc supplementation on the RPE. However, these studies could not address the complexity associated with cell heterogeneity and detailed temporal changes. We were particularly interested in exploring how zinc supplementation could affect the less and more differentiated cells in the short term to understand the potential to develop a more targeted intervention through supplementation. To decipher the effects of acute zinc supplementation, RPE cells were treated with elevated zinc for 1 week following the protocols we used previously . We found that acute zinc supplementation induced significant changes in gene expression in both long-term cultures ) regardless of the temporal stage of the cells. We also identified 81 zinc-responsive transcripts that were common amongst all groups. These transcripts were enriched in housekeeping genes and contained transcripts for metallothioneins, ribosomal protein, and ATP synthases (Supplementary Table S8), indicating that zinc affects the cellular homeostasis of the RPE, similar to that of other systems . Apart from the shared genes, specific changes were associated with the more or the less differentiated cell groups at both 2W and 19W in culture . The four specific genes affected by short-term zinc supplementation in the less differentiated cell group (Supplementary Table S8) are genes linked to the integrity of Bruch's membrane (COL8A1) , epithelial-mesenchymal transition (KRT17) , phagocytic activity and the rescue of the RPE (MFGE8) , and activity of heparan sulfate (SULF1) , suggesting that zinc might influence interaction with the local extracellular environment. In the more differentiated cell group in the 2W cultures, zinc affected biological processes including extracellular matrix organization, cellular polarity, and visual processes (Supplementary Table S8) that are critical for supporting the photoreceptors . At 19W in culture, zinc affected the less differentiated cells via modulating proteolysis, DNA replication and RNA transcription, and amino acid metabolisms (Supplementary Table S8), probably to mitigate oxidative stress, one of the AMD-associated biological functions . In the more differentiated cells at 19W in culture, zinc supplementation affected several metabolic pathways (Supplementary Table S8). Dysregulation of metabolic pathways is an important contributor to AMD pathophysiology . This may directly explain the benefit of zinc supplementation in patients in the AREDS study . Therefore, zinc supplementation has a multitude of effects on RPE, with some specific effects depending on cell differentiation and maturity. Identifying the specific molecular changes may help redefine treatment strategies based on zinc supplementation or nutritional interventions. 4.6. The Effects of Zinc on the Genes in the Pseudotemporal Trajectory Earlier we identified 537 genes (Supplementary Table S5) in the main pseudotemporal trajectory ). Zinc supplementation did not affect 240 genes ). Of the remaining 297 genes, 16 were housekeeping genes associated with the mitochondrion, the activation of cytochrome-c oxidase and ubiquinone, and response to metal ions (Supplementary Table S9). This is in line with a previous observation that zinc supplementation can protect the RPE from oxidative-stress-induced cell death by improving mitochondrial function , and this could be behind the positive effect of zinc supplementation in the AREDS studies or increased zinc intake through diet . Metallothioneins (MT1F and MT1E) that belong to this group , Supplementary Tables S7 and S9) are well-recognized mediators of zinc supplementation in the RPE via mediating oxidative-stress-induced RPE damage and differentiation of RPE . The remaining 281 genes in the main trajectory ) were associated with various biological processes including extracellular matrix organization, angiogenesis, collagen fibril organization, and visual perception (Supplementary Table S10). The composition of extracellular matrix has a profound effect on how the RPE attaches to the Bruch's membrane . Thus, gene expression modification by zinc could directly affect sub-RPE deposit formation . We also found that acute zinc supplementation upregulated the expression of transcriptional regulators ID1 and ID3, a finding that had not been reported before. In addition, in a previous study, we identified TGFB1 as a potential upstream regulator effect of chronic zinc supplementation . In our current study, we found that TGFB1 expression was also upregulated by acute zinc supplementation. Therefore, we carried out an Upstream Analysis in Ingenuity Pathway Analysis (QIAGEN, Redwood City) for the 190 transiently expressed genes in the combined pseudotime-correlated groups 1 and 7 (Supplementary Table S5). We identified a strong relationship for TGFB1 (p < 6.98 x 10-19) and also for ID1 (p < 3.59 x 10-5) and ID3 (p < 1.23 x 10-3) as potential upstream regulators for a group of genes among the transiently expressed group. In fact, TGFB1 was an upstream regulatory element for ID1 and ID3 (Supplementary Table S12). A direct molecular link between ID1 and TGFB1 had already been suggested . Therefore, the positive effects of zinc supplementation could be directly through TGFB1 signalling, which involves ID1 and ID3. The receptor of TGFB1, TGFBR1, is an AMD genetic risk variant , suggesting that these findings are directly relevant to further studies on AMD. 4.7. AMD-Specific Gene Expression Changes Based on literature searches, we generated gene lists that have been shown to contribute to the pathological changes associated with AMD and we examined the effects of cell maturation and zinc supplementation on these genes . Specific attention was paid to the activation complement system and lipid-metabolism-related genes, as these were the genetically most significantly associated pathways with AMD . We also scrutinized genes associated with pigmentary changes and mineralization-associated genes due to their potential link with RPE function and/or sub-RPE deposit formation in AMD . Not all genes involved in complement regulation were expressed in RPE cells . This is perhaps not surprising, as the local activity of the complement cascade is influenced by a complicated mix of local and systemic regulatory factors, which is altered in AMD retina . However, some complement genes that were expressed in the RPE were affected by acute zinc supplementation, including CFH, C1R, CFHR1, and CLU . These transcriptomic changes are in line with our previous reports that zinc supplementation has a functional effect on CFH secretion as well as oligomerization and activity , and zinc levels can regulate interferon gamma systematically, which, in turn, regulates expression of complement genes . Apart from CFH, several complement proteins can bind zinc, and this binding alters their activity . In addition, network analysis has highlighted elements of the complement regulation as potential targets for nutrient-affected pathways . Finally, there is also clinical evidence that zinc supplementation can directly inhibit complement activation in AMD patients , suggesting that modulation of the complement system could be one of the ways that zinc supplementation affects the progression to AMD. Of the 42 genes expressed in our RPE culture associated with cholesterol metabolism , ANGPTL4, LRPAP1, VDAC2, APOE, PLTP, NPC2, TSPO, and CYP27A1 were altered in response to acute zinc supplementation . These findings corroborate our previously reported effect of long-term zinc supplementation on lipid metabolism . ANGPTL4 is a lipid-inducible feedback regulator of LPL-mediated lipid uptake. However it is also a multifunctional cytokine, regulating vascular permeability, angiogenesis, and inflammation . The systemic level of ANGPTL4 is associated with NV AMD . Reportedly, this protein indirectly induces RPE barrier breakdown . LRPAP1 is a chaperon protein, generally controlling the folding and ligand-receptor interaction expression of the LRP receptors . Its role in RPE and AMD remains elusive. VDAC2 is a ceramide sensor integrated into the mitochondrial membrane and its function relates to regulation of mitochondrial apoptosis . Increased ceramide levels affect non-polarized RPE cells found in late stages of AMD . APOE, a lipophilic glycoprotein with a major role in lipid transport, is one of the many constituents of the sub-RPE deposits and has been associated with increased AMD risk . PLTP is a phospholipid transfer protein and is one of the main players in lipid homeostasis in ApoB-containing particles and high-density lipoprotein metabolism. PLTP plasma levels are associated with AMD , but their potential role in drusen formation remains elusive. NPC2 is a cholesterol transporter, effluxing cholesterol out of late endosomes in RPE. The lack of this protein is associated with age-related maculopathies . TSPO is a translocator protein that transfers cholesterol from the mitochondrial outer membrane to the mitochondrial inner membrane and also plays role in oxidative stress and inflammation. It was recently implicated as a highly relevant drug target for immunomodulatory and antioxidant therapies of AMD . CYP27A1 is involved in the elimination of 7-ketocholesterol from RPE, a toxic product of cholesterol auto-oxidation, which accumulates in drusen . In summary, the aforementioned affected gene expressions in response to zinc suggest that zinc has an impact on sub-RPE cholesterol accumulation, oxidative stress, inflammation, and angiogenesis via the regulation of lipid-membrane interaction, lipid transport, and the elimination of toxic lipid byproducts. In our cultures, we found 80 RPE-expressed genes associated with mineralization . Out of these, we found that COL1A1, POSTN, CD63, LAMP1, BMP4, SLC20A1, SOX9, and BMP7 were altered in response to acute zinc supplementation . The POSTN gene encodes a secreted extracellular matrix protein that functions in tissue development and regeneration and a potential anti-fibrotic therapeutic target for NV AMD . CD63 is involved in the regulation of cell development, activation, growth, and motility , and together with LAMP1, it plays a role in autophagy, exosome secretion, and drusen formation . BMP4 has been implicated in the disruption of RPE cell migration and barrier disruption in NV AMD . The protein encoded by SLC20A1 is a sodium-phosphate symporter involved in vascular calcification but not reported in association with RPE function or AMD . SOX9 plays a key role in regulating visual cycle gene expression in RPE but also plays a role in the prevention of calcification . BMP7 is hypothesized to be critical for the differentiation of the retinal pigmented epithelium during development . It also has been implicated in prevention of vascular calcification . Zinc supplementation is reported to inhibit phosphate-induced vascular calcification , but, as our results indicate, it may also have a (indirect) role in the prevention of drusen calcification. In our cultures, most pigmentation-related genes were detected and their expression level either remained constant or increased throughout the culture time . Only TYR, TYRP1, and DCT were altered in response to acute zinc supplementation . TYR, TYRP1, and DCT are key to the production of melanin and pigmentary abnormalities show a strong correlation with sub-RPE deposit formation and development of AMD . TYR catalyzes the production of melanin from tyrosine, in which L-DOPA is produced as an intermediate . The function of TYRP1 is in the biosynthesis of melanin from tyrosine, whilst TYRP1 catalyzes the oxidation of 5-6-dihydroxyindole-2-carboxylic acid to an indole, whilst DCT catalyzes the conversion of L-dopachrome into 5-6-dihydroxyindole-2-carboxylic acid . These events lead to the activation of GPR143 signaling and may initiate several downstream effects, such PEDF, VEGF secretion, and/or exosome release . Since we found an influence of zinc on the expression of these pigmentation-related genes, and given the data from literature above, zinc might also have an influence on GPR143 signaling. Surprisingly, acute zinc treatment resulted in downregulation of the aforementioned genes, despite long-term zinc supplementation enhancing RPE pigmentation . At the transcriptional level, long-term zinc supplementation significantly altered the expression of 18 out of the 21 pigmentation-related genes (Supplementary Table S11, ), of which the majority were also downregulated, except for HPS5, HPS6, and LYST. These three upregulated genes are all related to intracellular trafficking, such as lysosomes and melanosomes .The negative effect of acute zinc supplementation on the gene expression of other pigmentation-related genes needs to be further investigated. 5. Conclusions Primary hfRPE cultures that recapitulate the main phenotypes of aged RPE in vivo can help to dissect the molecular changes associated with RPE maturation and experimental manipulation, such as zinc supplementation. This cellular model provides an excellent platform for further preclinical studies to identify new treatment strategies for AMD. As reported in vivo, these cells retain a high degree of heterogeneity even after extended time in culture, which may help to understand the role of this heterogeneity in the human eyes. Identifying the transcriptional machinery, including transcriptional regulators ID1 and ID3, may help us to target pathways previously not considered for AMD. The data also show that the differentiation of RPE into cells that resemble those in vivo requires an extended time in culture, and experimental manipulation will need to consider this. The wide-ranging effects of zinc supplementation, from the regulation of housekeeping genes to very specific AMD-associated transcripts, build confidence that this intervention could indeed be a suitable intervention strategy to slow the progression to advanced-stage AMD, as suggested by the AREDS studies. Acknowledgments The authors gratefully acknowledge the QUB Genomics Core Facility for their expertise and assistance in this work. Supplementary Materials The following supporting information can be downloaded at: Figure S1: In vitro primary fetal RPE culture; Figure S2: Comparing gene expression patterns of more and less differentiated groups; Figure S3: Basal immunolabeling of COL1A1 protein increased in the RPE culture experiments; Figure S4: Gene expressional patterns of single-cell populations in the developmental and adult RPE ex vivo; Table S1: Unsupervised clusters marker genes; Table S2: Unsupervised clusters Gene Analytics; Table S3: RPE specific genes; Table S4: Supplementary Table S4 More and Less differentiated cells marker genes; Table S5: Pseudotime main trajectory genes; Table S6: Pseudotime main trajectory Gene Analytics; Table S7: Acute zinc differentially expressed genes list; Table S8: Acute zinc differentially expressed Gene Analytics; Table S9: Acute zinc pseudotime overlap Gene Analytics 01; Table S10: Acute zinc pseudotime overlap Gene Analytics 02; Table S11: AMD Genelists; Table S12: Overlapping genes for TGFB1 Upstream regulator table run from the 190 transiently expressed genes in the combined group of Pseudotime module 1 and 7. Click here for additional data file. Author Contributions Conceptualization, E.E., O.C., E.K., D.A.S. and I.L.; Methodology, E.E. and O.C.; Investigation, E.E., O.C., D.A.S. and I.L.; Formal Analysis and Visualization, E.E., O.C., C.K., J.P.S., D.A.S. and I.L.; Writing--Original Draft, E.E. and I.L.; Writing--Review and Editing, E.E., O.C., E.K., B.S.M., J.P.S., A.A.B., D.A.S. and I.L.; Supervision and Funding Acquisition, I.L., D.A.S. and A.A.B.; Project Administration, I.L. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data that support the findings of this study will be openly available in the GEO database public repository upon publication, which does not issue DOIs. Conflicts of Interest Imre Lengyel was supported by unrestricted grants from F. Hoffmann-La Roche Ltd. E. Kortvely is an employee of F. Hoffmann-La Roche Ltd. The other authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. Figure 1 Heterogeneity of cultured human primary fetal RPE cells revealed by single-cell transcriptome analysis. (A) UMAP reduced dimensionality plot labelled with the thirteen clusters identified within the RPE cells. (B) Hierarchical clustering based on RPE-specific genes showed that the thirteen clusters partitioned into two distinct branches. (C1) UMAP replotted to indicate more (green) and less (red) differentiated RPE cells. (C2) The proportion of more differentiated cells increased after 19 weeks in culture (blue represents more differentiated cells, orange less differentiated cells). 2W-2 weeks; 9W-9 weeks; 19W-19 weeks in culture. Figure 2 Gene expression pattern of more and less differentiated cell populations of in vitro RPE over time. Top markers of the more and less differentiated single-cell populations. Gene expressional change of COL1A1 (A) and RPE65 (B) over time at more (green) or less (red) differentiated cell population level; representative image of their protein expression pattern in RPE flatmounts (green: RPE65, red: COL1A1) (C). The scale bar is 10 um. 2W-two weeks; 9W-nine weeks; 19W-19 weeks in culture. Figure 3 Dynamic changes of RPE over time in vitro. Identified trajectories (A1) and the highlighted main trajectory (A2) of in vitro RPE transcriptome over pseudotime (A, 0-20 represents pseudotime, node 1 corresponded to the less and node 10 to the more differentiated cells), heatmap visualization of the expression patterns the genes correlated with the main trajectory grouped into modules (B1, -1.5-1.5 represents pseudotemporal expression), and network representation of the genes showing highest correlation with main trajectory of RPE culture pseudotime above the cut-off value of Moran I using Gene Analytics ((B2), grey lines represent validated connection via text mining, database information, and co-expression, pink lines represent experimentally validated network connection; the thickness of lines indicates the strength of data support). Figure 4 Impact of acute zinc supplementation on in vitro RPE at single-cell level. Relative proportion of less and more differentiated cells over time following acute zinc treatment (A); volcano plot visualization of the differentially expressed genes in less (B1) and more (B2) differentiated cells in two-week culture and in less (B3) and more (B4) differentiated cells in 19-week culture; number of differentially expressed genes overlapped amongst the different cell types and culture times (C); overlap between pseudotime-correlated genes and differentially expressed genes following acute zinc supplementation (D1) and a network representation of the 16 overlapping genes using Gene Analytics in combination with String and Cytoscape (D2), in which grey lines represent validated connections via text mining, database information, and co-expression, pink lines represent experimentally validated network connection, and the thickness of lines indicates the strength of supporting data. Figure 5 Distribution of age-related gene expression in RPE over time in vitro. 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PMC10000410 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050986 diagnostics-13-00986 Article A High-Efficiency Consultation Improves Urological Diagnosis in Patients with Complex LUTS--A Pilot Study Ciudin Alexandru Conceptualization Methodology Validation Investigation Data curation Writing - original draft Supervision Project administration 1* Padulles Bernat Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing - original draft 1 Manasia Pasqualino Conceptualization Software Validation Formal analysis Investigation Data curation Writing - original draft 1 Alcoberro Josep Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing - original draft 1 Ounia Sanae Investigation Data curation Writing - original draft 1 Lopez Maria Investigation Data curation Writing - original draft 1 Allue Natalia Methodology Writing - review & editing Supervision Project administration 2 Ferrer Joan Maria Conceptualization Writing - original draft Supervision Project administration 2 Duran Jaume Conceptualization Writing - review & editing Supervision Project administration 2 Aguilar Antonio Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing - review & editing Supervision Project administration 1 Neuhaus Jochen Academic Editor Longo Nicola Academic Editor 1 Urology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain 2 Hospital Management, Hospital Universitari de Mollet, 08100 Barcelona, Spain * Correspondence: [email protected] 04 3 2023 3 2023 13 5 98608 2 2023 24 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 ). (1) Background: The diagnosis of moderate-severe lower urinary tract symptoms (LUTS) is not easy due to the complexity of the micturition act. Sequential diagnostic tests can be time consuming due to waiting lists. Thus, we developed a diagnostic model combining all the tests in a single one-stop consultation. (2) Methods: In a prospective pilot study in patients with complex LUTS, they received all diagnostic tests (ultrasound, uroflowmetry, cystoscopy, pressure-flow study) in a single consultation and by the same doctor. Patients' results were compared with those from a 2021 paired cohort that underwent the classical sequential diagnostic pathway. (3) Results: Per patient, the high-efficiency consultation saved: 175 days of waiting, 60 min doctor time and 120 nursing assistant time and over 300 euros on average. The intervention also saved 120 patient journeys to the hospital, lowering the total carbon footprint by 145.86 kg CO2. In one-third of the patients, performing all the tests within the same consultation contributed to reaching a more appropriate diagnosis and thus more effective treatment. Patients' satisfaction was high, with good tolerability. (4) Conclusions: The high-efficiency urology consultation improves waiting times, therapeutic decisions and the degree of patient satisfaction while optimizing the use of resources and generating savings for the health system. LUTS diagnostics uroflowmetry ultrasound cystoscopy pressure-flow study waiting list time to diagnosis This research received no external funding. pmc1. Introduction Lower urinary tract symptoms (LUTS) are one of the main reasons for urological consultation. The prevalence of LUTS in patients attending a urology clinic was 41%, increasing with age: 14.1%, 41.5% and 60.8% of patients aged 18-49, 50-64 and >=65 years, respectively. Of the 1015 selected patients, only 2.6% exclusively presented filling symptoms . Lower urinary tract symptoms (LUTS) associated with benign prostatic hyperplasia are present in 20-30% of the Spanish male population aged 50 or over . The prevalence of moderate/severe LUTS is 16.6% in men over 40 years of age (95% CI: 14.8-18.3) . LUTS are common in women and can create a great deal of anguish and embarrassment, as well as considerable financial expenses for both individuals and society . Prevalence estimates vary depending on the definition and the population under study. However, it is commonly agreed that the issue is crucial given the human suffering and financial costs involved. LUTS greatly modify a person's quality of life, affecting their daily activities, modifying the things that one can do, limiting their ability to perform things, worsening night rest, modifying their mood and relationships with other people and obviously their ability to work and integrate into the world of work . Not only can LUTS comprise filling symptoms (overactive bladder syndromes), voiding symptoms (bladder outlet obstructions such as BPH, urethral strictures or bladder-sphincter dyssynergia), urge incontinence, stress incontinence or even pelvic pain , but LUTS are also usually associated with a marked decrease in the quality of life, affecting the patient's state of mind, which may affect their working productivity and integration or even impair their performance of daily activities . Patients with complex moderate-severe LUTS tend to find it has a more marked impact on their quality of life than patients with mild LUTS. Therefore, the sooner a correct diagnosis is made and the optimal treatment is offered, the less time the patient will spend with a diminished quality of life . The diagnosis is not easy, however, due to the complexity of the micturition act. The filling phase depends on bladder accommodation and detrusor relaxation and can cause irritative symptoms, usually classified as overactive bladder syndromes with increased urination frequency, urgency and even urgency urinary incontinence, sometimes associated with pain caused by the filling of the bladder. The emptying phase depends on bladder contractility (modified in hypocontractile detrusor), anatomical bladder outlet obstruction (BPH, urethral stenosis) or functional outlet obstruction (bladder-sphincter dyssynergia caused by suboptimal coordination of bladder contractility and sphincter relaxation) . Given the simultaneous involvement of several organs and systems (bladder, prostate, pelvic floor muscles, nervous system) in complex voiding syndromes, several diagnostic tests are often needed to determine the reason for the appearance of symptoms . The most common tests recommended in the EAU guidelines are an ultrasound, uroflowmetry, cystoscopy and urodynamic pressure-flow study . Currently, the diagnosis process implies the performance of these tests separately in time and space, each one with its corresponding waiting time; the total waiting time for patients to have a complete final diagnosis can exceed 6 months. To address the high prevalence of LUTS and the lengthy waiting time until a final complete diagnosis is available, we strongly believe that a high-efficiency urological consultation could offer an excellent solution. On these bases, our hypothesis is that performing the recommended diagnostic tests in the course of one day, as part of one unique process, will have a positive impact on the quality of life, quality of diagnosis and treatment, and the health system. With those goals, the aim of this project was to develop a specific consultation for patients with complex LUTS who require various diagnostic tests. The objective of this consultation was to combine all the diagnostic tests in a single one-stop consultation, with the corresponding waiting time reduced. Our secondary objective was to demonstrate that performing all the tests at the same time provides a better approach, improving the diagnosis and treatment. 2. Materials and Methods A prospective pilot study was conducted at our center between October and December 2022, implementing a high-efficiency consultation, with all diagnostic tests performed in a single consultation and by the same person for patients with complex LUTS. Inclusion criteria (a + b/c/d + e): (a) age >18 years; (b) patients with two or more of the following symptoms in a moderate or severe manner: voiding symptoms, filling symptoms, urge urinary incontinence, stress urinary incontinence, pelvic pain; (c) operated patients with permanence of symptoms after surgery; (d) patients who did not respond to previous medical treatment; (e) signed informed consent form. Exclusion criteria: patients who refused to participate in the study. To assess the benefits that this type of consultation could provide, a second cohort was created with the same number of patients and with similar characteristics, who visited the center in 2021 and following the standard of care clinical diagnostic protocol. The patients were selected based on the CIM 10 diagnostic codes, then they were matched by sex, age and initial symptoms with the patients evaluated using the high-efficiency consultation. In this cohort, we evaluated the waiting time of the patients (from the moment the need to carry out diagnostics was indicated in the urology office to the final complete diagnosis). 2.1. The Standard Clinical Protocol The EAU guidelines recommend identifying differential diagnoses during urological diagnosis, since the origin of LUTS is multifactorial, and defining the clinical profile (including the risk of disease progression) of patients with LUTS in order to provide adequate care. To do so, the guidelines recommend using flowmetry, ultrasound, cystoscopy and/or urodynamics as complementary tests, without specifying a preestablished order or the need to use all or only some of the tests. So, based just on the evaluation in the urology office, the decision is made to expand the diagnostics by requesting one or more of the tests . 2.2. Ultrasound The BK Ultrasound Flex Focus 400 ultrasound machine was used with a 5 Mhz abdominal probe. A standard kidney-bladder-prostate ultrasound was performed, evaluating the size and morphological and anatomical characteristics of the kidneys, urinary tract, bladder and prostate, along with the postvoid bladder volume. 2.3. Flowmetry The MMS Solar System urodynamics machine was used. Free uroflowmetry was performed in a standing or sitting position according to the patient's preference. We evaluated the maximum flow rate, voiding volume, voiding time and postvoid residue, as were assessed by ultrasound. 2.4. Cystoscopy The CYF-VH cystoscope with the CV-170 image processing unit was used to perform a flexible cystoscopy according to the standard technique using water-based lubricant and continuous saline irrigation. The anatomy of the penile, membranous, bulbar, prostatic urethra, bladder neck and bladder was evaluated, providing information on the anatomical modifications, the length of the prostatic urethra, the degree of obstruction of the prostatic urethra, the trilobular growth of the prostate, the appearance of the bladder mucosa, the trabeculation of the bladder wall and the appearance of the trigone and the anatomical position of the meatus. Any pathological image was reported and diagnosed according to current protocols . 2.5. Pressure-Flow Study The MMS Solar System urodynamics machine was used. A pressure-flow study was carried out in a standing or sitting position according to the patient's tolerability, performing two fillings. Water pressure lines were used, performing atmospheric zero. The following variables were also noted: the demographic data of the patients, the indication for a diagnostic study, the final diagnosis and the proposed treatment, the total time of the consultation, the average time until the final therapeutic decision, the influence on the therapeutic decision made at the end of the consultation, the savings for the hospital and health system, systemic savings obtained by reducing the number of visits and the degree of patient satisfaction. The total time of the consultation was evaluated in order to define whether it is feasible to conduct all the indicated tests in one hour, which would be the time assigned to carry out the consultation and prepare the next one. This was compared with the average time assigned to each test and query separately, to assess whether there is a difference in favor of the high-efficiency consultation. The average time until the final therapeutic decision was calculated from the visit when the need to expand the diagnostic study was indicated, either by performing a high-resolution consultation or following the classic sequential diagnostic algorithm. The savings for the hospital and the health system were calculated by evaluating the costs of the extra tests or consultations that were saved by condensing them all into a single consultation and comparing this cost with the cost of the high-efficiency consultation. The cost of the material for the high-resolution consultation was considered to be similar to the other consultations since the material is the same, with differences only arising from the necessary personnel time. We evaluated and compared the number of visits made by patients who underwent the classical successive diagnostic algorithm and patients who attended the one-stop high-efficiency visit. Furthermore, we evaluated if these patients came accompanied and the reduction in the number of visits that the high-efficiency consultation can produce for the family members that usually accompany patients. The influence on the therapeutic decision was evaluated by comparing the therapeutic decision made after the high-resolution consultation with the decision that could have been made by performing the same tests sequentially. For this, the cases were presented to other urologists from the urology department who neither carried out the high-efficiency consultation nor indicated the diagnosis tests, in order to avoid bias. The tests were presented anonymously, in sequential order according to the diagnostic algorithm applied by the urologist who was evaluating the tests. It was not considered essential that the urologist requested all the tests be performed during the high-efficiency consultation, and the order of the tests was merely requested by the evaluating urologist. The diagnostic and therapeutic decision made by the evaluating urologists and the therapeutic decision made after the high-efficiency consultation were then compared. The degree of satisfaction of the patients with having all the tests performed in the same consultation and the degree of pain caused by the tests were evaluated using Likert scales . 3. Results A total of 30 patients attended the high-efficiency urology consultation at our hospital. Of those, 83.3% of the patients were male and 16.7% female. The average age of the patients was 66.5 (+/-15) years. Patients' demographics can be found in Table 1. A total of 93% of the patients came accompanied by a family member, 53% by a retired one and 40% by a family member that needed to ask for a leave of absence from work. Flowmetry, ultrasound, cystoscopy and urodynamics were performed for all patients. In 26 cases, the indication was complex LUTS, whereas the remaining 4 patients were referred for a high-resolution consultation due to persistence of voiding symptoms after surgery (TURP). As for the diagnoses after consultation, there were 3 urethral strictures, 3 pelvic floor myofascial syndromes, 12 BPH, 6 patients with hypocontractile detrusor, 2 bladder tumors and 3 idiopathic detrusor hyperactivities. The indicated treatments were: 3 internal optical urethrotomy surgeries, 9 TURP, 4 medical treatments for bladder outlet obstruction, 5 patients maintained their current treatment, 2 TURB and 1 botulinum toxin injection. The average time for the high-efficiency consultation was 51 min (+/-7 min) versus 150 min for the classic sequential diagnostic algorithm. When evaluating the 2021 cohort who were diagnosed according to the standard protocol, the four tests were performed in four different diagnostic consultations and one medical consultation. The personnel times required for each consultation are reflected in Table 2. When comparing the times of the sequential consultation with those of the high-efficiency consultation, it is shown that the high-efficiency consultation requires 60 fewer minutes for the doctor and 120 fewer minutes for the nursing assistant. Since the materials used are the same, the differences between consultations are due to the staff time needed, creating an average saving of more than 300 euros per patient. The average waiting time for the high-efficiency consultation of the patients was 22 days (+-6 days), while the average time that the 2021 cohort needed to undergo all the diagnostic tests was 197 days (+-31 days), with a mean difference of 175 days . The number of visits to the hospital was reduced from five to one in favor of the high-efficiency consultation. From an overall point of view, the patients in the high-efficiency consultation made 30 trips to the hospital and the ones form the classical sequential diagnostic algorithm group made up to 150 trips, resulting in 120 less visits to the hospital. Furthermore, in 90% of the visits by patients in the sequential diagnostic algorithm group, they came accompanied by a family member, 46% by a retired one and 43% by a family member who required leave from work. In comparison, of the patients in the high-efficiency consultation, 93% came accompanied by a family member, 53% by a retired one and 40% by a family member who had to request a leave of absence from work. Family member visits were reduced from 135 to 28, and for family members who had to miss work, from 65 to 12 (Table 3). In 33% of the patients, there were diagnostic and thus treatment differences between the urologists who evaluated the tests sequentially or in a high-efficiency consultation. There were six patients with obstructive syndrome due to a hypocontractile detrusor and an apparently obstructive image of the prostatic urethra, but with a non-obstructive urodynamic study; in these patients, TURP was proposed by the evaluating urologist but the fact that the pressure flow study ruled out bladder outlet obstruction changed the treatment decision. In addition, two patients were diagnosed with bladder-sphincter dyssynergia, and the urethral profile gained during the high-efficiency consultation changing the treatment from TURP to an initial medical and physiotherapeutic approach. Furthermore, there were two patients with irritative syndrome due to a bladder tumor, where cystoscopy changing the treatment from anticholinergic drugs indicated based on the pressure flow study to a TURB resection. All patients reported being satisfied with the consultation (9/10 +/-0.6), with low pain levels caused by the four tests (3.7/10 +/-1.1). No complications were recorded after the consultation and no patient attended the emergency department or was diagnosed with UTI or hematuria. 4. Discussion To our knowledge, ours is the first study to prove that optimizing the urological diagnostic process of patients with complex LUTS through a one-stop diagnostic consultation that includes all the necessary tests is an excellent way to reach an optimal diagnosis in the shortest possible time. To date, there have been few attempts to optimize urological diagnosis through a one -stop consultation. The attempts were focused on patients received from primary care, not patients with complex LUTS . We point out that not all patients referred to the urology office will need all the tests that can be performed in a high-efficiency consultation. The diagnosis of moderate-severe LUTS is usually complex due to the mixture of voiding and filling symptoms, stress or urge incontinence and even pelvic pain. The complexity of the voiding act requires several tests for diagnosis, which may necessitate a long waiting time while the patient lives with a greatly diminished quality of life. The few studies that tried to demonstrate the feasibility of a one-stop consultation did not focus exclusively on patients with complex LUTS, but on all patients sent from primary care to the urology office. Since moderate-severe LUTS represents only 16% of these patients, not all patients underwent all the diagnostic tests; in many cases, an ultrasound and uroflowmetry were sufficient. One of the questions raised in our study was whether it is feasible to carry out a high-resolution consultation focused only on patients with complex LUTS, knowing that all the tests must be performed in all patients. In our study, the average time for this consultation, including anamnesis, the four tests, explaining the test results to the patient, agreeing on the therapeutic decision and preparing the consultation for the next patient was 51 min, demonstrating that it is feasible to schedule the patients hourly. The key goal of treating patients with LUTS is for them to regain quality of life and the ability to carry out activities of daily living, recover self-esteem and return to work. Therefore, the time between the start of the diagnosis study and the treatment is essential since patients live during this time with a low quality of life. In addition, patients with moderate-severe complex LUTS are the ones whose quality of life is most greatly impacted . Our study shows that by carrying out a high-efficiency consultation, we can advance the diagnosis and the definitive therapeutic decision by up to 175 days--almost 6 months--in the case of complex patients. Combining all the tests in a single consultation clearly saves time. A comparison between the consultation time for the 2021 cohort and the patients in the high-efficiency consultation showed that by implementing the high-efficiency consultation, up to 60 min of doctor time and up to 120 min of nursing assistant time can be saved. This can be translated either into savings of more than 300 euros per patient or into the possibility of specialists being able to see more patients due to time optimization. Our study demonstrates that the high-efficiency consultation can reduce the number of trips to the hospital, not only for the patients but also for their family members. The number of visits needed for each patient was reduced from five to one. Therefore, 120 trips to the hospital were avoided. The mean age of our patients was 65 years, and most of them came accompanied by a family member. The reduction in trips to the hospital was also seen in case of family members from 135 to 28, and even more importantly, the number of family members that had to miss work was reduced from 65 to 12. From an environmental point of view, reducing the number of visits and trips to the hospital lowers the carbon footprint that these patients generate. Our study avoided 120 visits to the hospital, and considering that the average distance our patients live from the hospital is 7.15 km, a total of 858 km were saved. A study carried out in a similar setting quantified the amount of CO2 saved by avoiding a kilometer of travel to the hospital as 0.17 kg CO2/km; therefore, in our case, the carbon footprint was lowered by a total of up to 145.86 kg CO2 . There are many treatment alternatives for LUTS, and in some cases, they have opposite effects and results . For this reason, a precise diagnosis must always be made before deciding on treatment, sometimes even balancing the resolution of one type of symptom with that of another, especially in patients with severe filling and voiding symptoms. Our study shows that performing all the tests jointly can improve the integration of diagnostic data by the health professional and, therefore, optimize the diagnosis and the proposed treatment. In one-third of the patients, performing all the tests within the same consultation contributed to reaching a more appropriate diagnosis and, therefore, offering more effective treatment to the patient. One of the initial obstacles when developing the concept of high-efficiency consultation was the space where it could be carried out. Due to the high number of tests that needed to be performed in a limited time, there were concerns about whether the consultation could be carried out in the space of a standard diagnostic and examination office. However, through an ergonomic arrangement of the elements involved (examination table, ultrasound, additional table for cystoscope, urodynamic machine), a space was arranged where all tests could be performed effortlessly. A key element in achieving a smooth consultation was having expert, trained personnel with solid knowledge of all the issues involved, which made carrying out the consultation efficient. One of the limitations of our study was the small number of patients. However, this study was designed from the beginning as a pilot test to support the subsequent performance of a larger study or to modify the usual clinical practice. The relatively small number of patients does not prevent us from underlining the advantages that a high-efficiency consultation could provide both for patients and the healthcare system. Last but not least, there was concern as to whether carrying out all the tests in the same consultation would be poorly tolerated by the patients. The results of the questions on tolerability in our study showed that the consultation was well tolerated by the patients, without complications and with high degrees of satisfaction. 5. Conclusions A high-efficiency urology consultation is a feasible alternative to traditional successive consultations, improving waiting times, the therapeutic decision and the degree of patient satisfaction while optimizing the use of resources and generating savings for the health system. The results obtained since its implementation have been excellent, paving the way for an evolution toward a more efficient health system in all aspects, as well as patient-centered care that allows greater satisfaction. Author Contributions Conceptualization, A.C., B.P., P.M., J.A., A.A. and J.D.; methodology, A.C., B.P., P.M., J.A., A.A., N.A., J.M.F. and J.D.; validation, A.C., B.P., J.A., P.M. and A.A.; formal analysis, A.C., B.P., P.M., J.A. and A.A.; investigation, A.C., S.O., M.L., B.P., P.M., J.A. and A.A.; data curation, A.C., S.O., M.L., B.P., P.M., J.A. and A.A.; writing--original draft preparation, A.C., S.O., M.L., B.P., P.M., J.A. and A.A.; writing--review and editing, B.P., P.M., J.A., N.A., J.M.F., J.D. and A.A.; supervision, N.A., J.M.F., J.D., A.A. and A.C.; project administration, A.C., N.A., J.M.F., J.D. and A.A. 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. Ethical review and approval were waived by the ethical committee for this study considering that the study was only a variation of the official diagnostic protocol and since it did not change the tests, nor the way of performing them, nor their order, but only the time between tests. Patient data were processed in accordance with the Spanish Organic Law on Data Protection. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data is not available due to the Spanish Organic Law on Data Protection. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Comparative flowchart of the waiting times of the sequential diagnostic algorithm (above) and the high-efficiency consultation. Figure 2 The high-efficiency consultation setting. diagnostics-13-00986-t001_Table 1 Table 1 Patients' demographics. Study Cohort 2021 Cohort Number of patients 30 30 Male % 83.3% 83.3% Average age 66.5 years 67.2 years Number of diagnostic visits per patient 1 5 Time required for diagnosis 51 min 150 min Mean waiting time 22 +- 6 days 197 +- 31 days diagnostics-13-00986-t002_Table 2 Table 2 Staff time required for sequential query versus high-efficiency consultation. Sequential Diagnostic Algorithm High-Efficiency Consultation Medical Time Nursing Assistant Time Medical Time Nursing Assistant Time Ultrasound 20 min 20 min 60 min 60 min Flowmetry - 30 min Cystoscopy 30 min 30 + 30 min Urodynamics 60 min 60 min Medical consultation 10 min 10 min Total 120 min 180 min 60 min 60 min diagnostics-13-00986-t003_Table 3 Table 3 Reduction in number of visits to the hospital. 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PMC10000411 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050857 diagnostics-13-00857 Systematic Review MRI Radiomics and Predictive Models in Assessing Ischemic Stroke Outcome--A Systematic Review Dragos Hanna Maria 123 Stan Adina 123* Pintican Roxana 4 Feier Diana 4 Lebovici Andrei 4 Panaitescu Paul-Stefan 5 Dina Constantin 6 Strilciuc Stefan 12 Muresanu Dafin F. 123 Jianu Dragos Catalin Academic Editor Sadik Jean Claude Academic Editor Ilic Tihomir V. Academic Editor 1 Department of Neurosciences, Iuliu Hatieganu University of Medicine and Pharmacy, No. 8 Victor Babes Street, 400012 Cluj-Napoca, Romania 2 RoNeuro Institute for Neurological Research and Diagnostic, No. 37 Mircea Eliade Street, 400364 Cluj-Napoca, Romania 3 Neurology Department, Emergency County Hospital, No. 43 Victor Babes Street, 400347 Cluj-Napoca, Romania 4 Department of Radiology, Iuliu Hatieganu University of Medicine and Pharmacy, No. 3-5, Clinicilor Street, 400006 Cluj-Napoca, Romania 5 Department of Microbiology, Iuliu Hatieganu University of Medicine and Pharmacy, No. 8 Victor Babes Street, 400012 Cluj-Napoca, Romania 6 Department of Radiology, Faculty of Medicine, Ovidius University, 900527 Constanta, Romania * Correspondence: [email protected] 23 2 2023 3 2023 13 5 85731 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 ). Stroke is a leading cause of disability and mortality, resulting in substantial socio-economic burden for healthcare systems. With advances in artificial intelligence, visual image information can be processed into numerous quantitative features in an objective, repeatable and high-throughput fashion, in a process known as radiomics analysis (RA). Recently, investigators have attempted to apply RA to stroke neuroimaging in the hope of promoting personalized precision medicine. This review aimed to evaluate the role of RA as an adjuvant tool in the prognosis of disability after stroke. We conducted a systematic review following the PRISMA guidelines, searching PubMed and Embase using the keywords: 'magnetic resonance imaging (MRI)', 'radiomics', and 'stroke'. The PROBAST tool was used to assess the risk of bias. Radiomics quality score (RQS) was also applied to evaluate the methodological quality of radiomics studies. Of the 150 abstracts returned by electronic literature research, 6 studies fulfilled the inclusion criteria. Five studies evaluated predictive value for different predictive models (PMs). In all studies, the combined PMs consisting of clinical and radiomics features have achieved the best predictive performance compared to PMs based only on clinical or radiomics features, the results varying from an area under the ROC curve (AUC) of 0.80 (95% CI, 0.75-0.86) to an AUC of 0.92 (95% CI, 0.87-0.97). The median RQS of the included studies was 15, reflecting a moderate methodological quality. Assessing the risk of bias using PROBAST, potential high risk of bias in participants selection was identified. Our findings suggest that combined models integrating both clinical and advanced imaging variables seem to better predict the patients' disability outcome group (favorable outcome: modified Rankin scale (mRS) <= 2 and unfavorable outcome: mRS > 2) at three and six months after stroke. Although radiomics studies' findings are significant in research field, these results should be validated in multiple clinical settings in order to help clinicians to provide individual patients with optimal tailor-made treatment. radiomics ischemic stroke predictive model This research received no external funding. pmc1. Introduction Stroke is a leading cause of mortality and disability, resulting in substantial socio-economic costs for post-stroke care . Although the mortality rates have declined over the past two decades, the absolute number of incident stroke, disability-adjusted life-years lost due to stroke, and stroke-related deaths is increasing . Predictive models (PMs), which integrate patient characteristics and care process to estimate the probability of developing a particular event or future outcome have been proven valuable in the primary prevention of cerebrovascular diseases . PMs such as Framingham Score , QRISK , Reynolds and Euro-Score have been used in cardiovascular and cerebrovascular diseases to help health service planning and to support clinical decision making, diagnostic and therapeutic management in risk groups. A systematic review of 109 studies on clinical PMs for functional outcome in ischemic stroke concluded that, in the thirty-five years of literature, the following clinical factors are consistently identified as the most suitable predictor variables of functional outcome and mortality: age, gender, stroke severity, stroke subtypes and comorbidities such as diabetes and atrial fibrillation. Ntaios et al. demonstrated that recently introduced prognostic scores such as ASTRAL , DRAGON and SEDAN predict outcome of AIS patients with higher accuracy compared to clinical predictions made by physicians, providing evidence that PMs may positively impact patient outcome. All three scores incorporate age, admission National Institute of Health Stroke Scale (NIHSS) and blood glucose level as predicting variables, whereas DRAGON and SEDAN contain as predictive feature hyperdense middle cerebral artery (MCA) sign or early infarct signs on computer tomography (CT). During the past decade, advances in computational technologies, especially in machine learning, have placed medical imaging in an increasingly central role in patient-specific management . This progress makes it possible to convert subjective visual interpretation into an objective assessment that is driven by image data . Radiomics analysis (RA) has emerged in this context, being a method that extracts undiscovered imaging features by converting routinely acquired images into higher dimensional data . This process is motivated by the concept that digitally encrypted images contain information related to the pathophysiology of certain diseases, and this information can be exploited via quantitative image analysis . Currently, in the ischemic stroke field, the role of RA was explored in three domains: diagnosis of stroke lesion, prediction of early outcome and long-term prognosis assessment . The diagnostic role of radiomics in stroke lesions was investigated using CT or magnetic resonance imaging (MRI). Oliviera et al. performed texture analysis (TA) on non-contrast CT images of acute ischemic stroke (AIS) patients to distinguish healthy tissue from regions affected by AIS and found that TA parameters were significantly different between patients and controls, with the most discriminative feature being angular second moment. By using MRI, Sikio et al. assessed 30 patients with chronic right hemisphere stroke and found that the ischemic region had lower homogeneity compared with non-affected side and relatively high values of complexity and randomness. Ortiz-Ramon et al. used multimodal MRI data of different brain regions from 100 patients to investigate if RA could distinguish between patients who had prior ischemic stroke and the stroke-free health population. They showed that TA and wavelet transformation could identify the presence of previous stroke lesions with favorable discrimination (area under the ROC curve (AUC) > 0.7) independently on what MRI sequence has been used or what brain region has been affected . Regarding early outcomes after AIS, Kassner et al. investigated if RA could predict hemorrhagic transformation in AIS patients treated with intravenous thrombolysis and suggested that radiomics features could be a better predictor compared to visual enhancement score in post-contrast T1-weighted MRI (AUC > 0.75 compared to AUC < 0.6). Qiu et al. conducted RA to predict early recanalization after proximal occlusion in large vessels in 67 AIS patients treated with intravenous thrombolysis and suggested that the combination of RA features from non-contrast CT and CT angiography was more predictive of early recanalization with an AUC of 0.85 compared with conventional thrombus imaging features such as length, volume or permeability. Regarding post-stroke cognitive impairment, Betrouni et al. showed that texture features of hippocampus and entorhinal cortex at 72 h after AIS onset can predict the occurrence of cognitive impairment. Their results were further confirmed in a rat model of middle cerebral artery occlusion, with significant correlation being demonstrated between texture features and hippocampal neural density . The increasing number of studies investigating RA and machine learning algorithms applications in ischemic stroke with variable protocols and design allows for data pooling. This review aims to systematically evaluate the role of RA in acute ischemic stroke neuroimaging and the potential applications in clinical practice. The primary objective is to compare the results of AIS studies using RA for clinical outcome prediction. The secondary objective is to assess the methodological quality of studies using radiomics quality score (RQS). 2. Materials and Methods The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement was used for this systematic review (Supplementary Materials Table S1). The protocol for this review is available in the OSF registry, accessed on 31 January 2023. Before a formal search was conducted, we used the keywords to perform preliminary search stage in several preprint and peer-reviewed databases. The selection of databases depends on the availability of data and the degree of overlap between databases. Publications in English assessing MRI radiomics features in AIS patients published from the earliest date available until our last search date of 31 December 2022 were searched on two electronic databases (PubMed and Embase). The search terms consisted of MRI, radiomics and stroke. The detailed search string is displayed in the Supplementary Materials (Table S2). Two researchers assessed the eligibility of the articles through title and abstract screening using the inclusion and exclusion criteria (Table 1). Any disagreements were resolved by consensus. The full text of articles in which RA was applied on MRI images of AIS patients for predictive purposes were obtained for further evaluation. Although CT seems to be the most commonly used technique for RA modeling , several studies have recently suggested that the majorities of radiomics features are highly affected by image acquisition and reconstruction parameters and thus their reproducibility could be affected. Moreover, a phantom study showed that diverse CT scanners made by different manufactures could cause variability in RA values. Thus, we selected the studies which performed RA on MRI images. Lohman et al. proposed a list of recommendations that should be considered in study investigating the value of radiomics in research or clinical practice, from preferred methods for quality evaluation to radiomics workflow steps that should be reported. Thus, we created a specific standardized data extraction form consisting of the following categories: image acquisition, image pre-processing, segmentation, feature extraction, feature selection, model generation and validation, model testing, results, and clinical translation. All of these categories are addressed within the radiomics quality score (RQS) , which is a tool developed to assess the methodological quality of studies using radiomics . Thus, we chose to use RQS to analyze the main radiomics steps among studies and to present the extensive RA process for each study only in Supplementary Materials-Table S3. The detailed RQS score is described in the Supplementary Materials-Table S4. Two readers with previous experience in radiomics independently assigned an RQS score to each article included in this systematic review. The reviewers extracted the data using a predefined RQS form used in other systematic reviews on RA according to RQS six domains : protocol quality and reproducibility, feature reduction and validation, clinical validation and utility, the performance index, high level of evidence, and open science with open availability of source code and data. Any disagreement was resolved by consensus. The total RQS score was calculated for each article and for each component (score range, -8 to 36) and expressed as a median and interquartile range. For the six domains in the RQS score, basic adherence was assigned. The main goal of radiomics is to establish a practical and accurate model for predicting clinical outcomes . A prediction model is defined as any combination of 2 or more predictors (demographic, clinical, imaging or biological variables) for estimating for an individual the probability of developing a particular outcome . Therefore, we extracted the studies' data regarding the predictive models employed using the following categories: model objective, clinical features, conventional imaging features, biological features, radiomics features, validation methods, main results, and limits. PROBAST was designed for use in systematic review or prediction model studies and consists of four domains (participants, predictors, outcome and analysis) containing twenty signaling questions to facilitate risk of bias assessment. A graphical summary presenting the percentage of studies rated by level of concern (low risk of bias, high risk of bias, unclear risk of bias) was displayed. The data were reported in a qualitative narrative synthesis based on the identified categories. The results' risk of bias and applicability were compared with existing literature. Unfortunately, the studies were methodologically heterogeneous, and meta-analysis was not possible. 3. Results In total, 150 articles were obtained, out of which 36 were duplicates. Of the remaining 114, 87 were rejected during title and abstract screening. Twenty-one articles were eligible for full-text evaluation. Six articles fulfilled the pre-established eligibility criteria. The study selection process is displayed in the PRISMA flow diagram , whereas Table 2 contains details on study design, characteristics of study population, clinical and imaging variables integrated in PMs and the performance of PMs for each study. All studies investigated the predictive value of radiomics features in assessing AIS clinical outcome. Clinical outcome was evaluated at ninety days in five studies , respectively, at six months in one study using the modified Rankin scale (mRS) and the patients were dichotomized into good outcome (mRS = 0, 1, or 2) and poor outcome (mRS = 3, 4, or 5) groups. Additionally, one study assessed the role of radiomics-based models for predicting one-year ischemic stroke recurrence confirmed on diffusion-weighted imaging (DWI). Five studies integrated separately clinical and radiomics features and then combined these variables within PMs, tested its performance and validated into another datasets. Additionally, two studies used conventional MRI features such as infarct volume, orthogonal diameters of ischemic lesion, DWI-Alberta Stroke Program Early CT Score (ASPECTS) or Fazekas score together with clinical and RA parameters. Among the clinical factors known to be independent predictors for AIS outcome, the most used in the PMs were age, gender, admission NIHSS, 24-h NIHSS, prior documented stroke, atrial fibrillation, hypertension or diabetes . These studies also conducted preliminary univariate and multivariate analysis to select the clinical features that were significantly associated with unfavorable outcome. Additionally, an interclass-correlation coefficient with a cut-off of 0.75 was used to evaluate the consistency between the researchers for estimating infarct volume and admission NIHSS and to assess the reliability of extracted RA features . The most used MRI sequences for feature extraction were apparent diffusion coefficient (ADC) and DWI . In all studies, the region of interest was the ischemic lesion which underwent manually segmentation performed by at least two experienced neuroradiologists . Only one study applied automatic segmentation. The number of radiomics features extracted varied from 15 to 1310 features , but after applying feature reduction methods, the number decreased at 6 to 100 , respectively. Most of the studies used first-order statistics and second-order statistics (texture analysis), but three studies applied high-order statistics, such as wavelet or Laplacian of Gaussian transformation, respectively. Three studies were from single center and built validation cohorts from the same institute, whereas only one study applied the PM to datasets from two different institutes. The description of radiomics workflow for each study is depicted in Supplementary Materials-Table S3. Five studies evaluated predictive performance for different PMs. Three studies initially investigated models based only on clinical factors and the most performant PM consisted of clinical variables such as age, gender, stroke history, diabetes, baseline mRS and NIHSS, achieving an AUC of 0.82 (95% CI, 0.77-0.87). Additionally, one study built a PM based on clinical and conventional MRI features such as age, gender, admission NIHSS, DWI-ASPECT score and orthogonal diameters of infarct lesion and obtained an AUC of 0.78 (95% CI, 0.68-0.88). One study compared radiomics-based PMs depending on the MRI sequence used for feature extraction and showed that ADC radiomics-based PM seems to achieve a better predictive performance compared to FLAIR radiomics-based PM (AUC = 0.77, 95% CI 0.62-0.83 versus AUC = 0.73. 0.62-0.83). Moreover, when ADC and FLAIR radiomics features were added in the same PM, the predictive value was higher (0.81, 95% CI 0.73-0.89) . In all studies , the combined PMs consisting of clinical and imaging features have achieved the best predictive performance compared to PMs based only on clinical or only on radiomics features, with the results varying from an AUC of 0.80 (95% CI, 0.75-0.86) to an AUC of 0.92 (95% CI, 0.87-0.97) . The best PM was validated in external datasets from two different institutes, obtaining an AUC of 0.864 (95% CI, 0.773-0.954) in the validation cohort. Two studies developed a clinical-based nomogram, which is an easy-to-use scoring model with the ability to assess the risk of unfavorable outcome in individual patients . Wang et al. included in their nomogram clinical variables such as age, 24-h NIHSS or the presence of hemorrhagic transformation and 11 radiomics features, reaching an AUC of 0.80 (95% CI 0.75-0.86) in the training cohort and an AUC of 0.73 (95% CI 0.64-0.82) in the validation set. On the other hand, Zhou et al. created a nomogram with higher performance (AUC = 0.868, 95% CI 0.825-0.910 in the training set and AUC = 0.890, 95% CI 0.844-0.936 in the validation set), including the following features: age, gender, prior stroke, baseline NIHSS, baseline mRS, diabetes and 7 radiomics features. The previous study of Wang et al. did not find a predictive value of texture features in assessing the stroke outcome but demonstrated that ADC-entropy and T2-FLAIR 0.75 quantile have predicted AIS severity with an AUC = 0.7 (p = 0.01). Regarding the methodological quality of the six radiomics studies, the median RQS score was 15 (interquartile range, 4), which represented 36.11% of the ideal score of 36 . The adherence rate of the RQS of all included studies is depicted in Figure 2. The RQS assessment for each study is described in Supplementary Materials-Table S5. The lowest score was 6 and the highest score was 16. The RQS of selected studies was lowest in the following domains: high level of evidence, open science, and model performance index , meaning that the most of studies did not validate the results in further prospective cohorts, did not perform a cost-effectiveness analysis of the model, did not make the code or radiomics data publicly available and did not use calibration and cut-off analysis in order to promote model reproducibility. Meanwhile, studies with higher RQS earned additional points by using multiple segmentations or external validation based on datasets from distinct institutes. Regarding the risk of bias assessment, the PROBAST tool was used. The overall risk of bias based on the four domains of PROBAST depending on three levels of concern (low, high or unclear risk of bias) is depicted in Figure 3. The PROBAST assessment for each study is described in Supplementary Materials-Table S6. Both overall risk of bias and applicability of concerns were low. Two studies presented high risk of bias regarding participant selection, excluding a large number of patients from the initial cohorts due to comorbid diseases that may affect their long-term stroke outcome. Unclear risk of bias due to unavailable information regarding the predictors and outcome analysis was established in the case of one study. 4. Discussion Prognostic scores may not fit to all cohorts due to patients' differences regarding racial or ethnic identity, background or comorbidities, hospital type or healthcare system, and acute stroke management . Poststroke functional outcome is affected by a variety of factors, such as age, gender, comorbid diseases, stroke severity, stroke subtypes, and treatments before and after discharge . Age and stroke severity are considered significant factors , which is consistent across the majority of studies assessing predictive scores or PMs, even those based on automatic algorithms . The external validity of initial stroke prognostic scores is limited . A recent study on 10,777 patients investigating eight stroke prognostic clinical scales confirmed differences in the prognostic accuracy when they are applied to external datasets, suggesting that even the best performing scale had a prognostic accuracy that may not be sufficient as a basis for clinical decision-making. In the era of large amounts of data and artificial intelligence (AI), automated systems may be helpful in predicting outcomes in patients with stroke and providing individual patients with optimal tailor-made treatment . The current applications of AI in AIS field seem to be efficient in numerous parts of the diagnostic and management pathways, including detection, triage, and outcome prediction . Computer-aided detection schemes based on texture features from areas known to show early AIS signs such as insula ribbon and lentiform nucleus were suggested to be a promising algorithm for lacunar AIS diagnosis . As lacunar AIS is relatively difficult to diagnose on CT within the first hours after onset , early detection is crucial for establishing the best treatment, and there is a need for a more efficient method to improve CT detection rate. Automated color maps (e.g., ColorViz) have proved to be rapid and accurate post-processing tools that permit maintenance of the temporal resolution of CT angiography, summing in a single image the three different cerebral vascular phases using a time variant color map . As the definition of the collateral circulation status is essential in selecting patients for mechanical thrombectomy, the possibility of using an immediate scoring scale for CT angiography could make the diagnostic assessment faster and easier. A recent systematic review showed that AI-based comprehensive platforms (e.g., Brainomix, iSchemaView, Viz.ai) could automatically detect the presence of large vessel occlusion (LVO), being a catalyst for timely LVO detection and an aid to acute management decision-making. Moreover, automated clot composition analysis systems using machine learning seem to provide information on the cause of cerebral artery occlusion and may further guide acute revascularization and secondary prevention. For example, a recent study assessed the accuracy of a such algorithm based on blooming effect on pre-treatment gradient echo images (GRE) from 67 patients with middle cerebral artery stroke and identified atrial fibrillation with high accuracy (AUC > 0.87). Blooming artifacts caused by paramagnetic materials in GRE images have been associated with cardioembolic stroke , cardioembolic clots having significant higher proportion of red blood cells compared with noncardiac clots and, oxyhemoglobin in erythrocytes goes through sequential stages of degradation into deoxyhemoglobin and hemosiderin, which are paramagnetic materials . Conventional MRI parameters extracted from DWI and fluid-attenuated-inversion recovery (FLAIR) sequences had been proven to be significant predictor of stroke outcome . Recent evidence suggest that DWI lesion may not be entirely composed of irreversibly damaged core. A systematic review on tissue outcome of DWI hyperintense stroke lesions suggested that hyperintense DWI lesions are rather heterogenous regions comprising various biochemical and metabolic environments, which may be variably amenable to salvage rather than as homogenous regions of ischemic core tissue. Guadagno et al. investigated oxygen metabolism in DWI lesions and revealed spatial variability in the cerebral metabolic rate of oxygen with individual DWI lesions. Additionally, significant variability of oxygen extraction fraction was demonstrated within single DWI lesions, ranging from areas with decreased flow relative to oxygen demand ('misery perfusion') to areas with increased flow relative to demand ('absolute luxury perfusion') . In this context, RA captures subtle variation within medical images and could be used to analyze the heterogeneity of lesions for a better diagnostic or predictive purposes. Regarding the heterogeneity of AIS lesions, radiomics seems to be superior to conventional imaging visual analysis . Texture features allow quantification of the heterogeneity within a lesion by considering both pixel intensity and statistical interrelationship in space (distance or orientation) . Due to their objective and quantitative values, recently, radiomics features were integrated in stroke outcome PMs and compared to clinical based PMs or prognostic scores. The findings of our systematic review confirmed the superiority of a combined model, suggesting that clinical and imaging factors may have an intercrossing and synergistic effect on each other, resulting in a more satisfactory outcome PM. After combining clinical and radiomics features in their PMs, five of the six included studies demonstrated better predictive values compared to models based only on clinical or imaging variables. Therefore, two studies performed nomograms, integrating the clinical and radiomics features that have achieved the best results in PMs. Interestingly, the most efficient nomogram resulted after combing more clinical factors such as age, gender, stroke history, diabetes, baseline mRS and NIHSS and less radiomics variables (7 texture features in Zhou et al. study versus 11 texture features in Wang et al. study ). This could be explained by the fact that Zhou et al. used multiple feature reduction methods, beginning with 1310 extracted features of different types and applying variable statistics tools (from Spearmen's correlation to minimum redundancy maximum relevance and least absolute shrinkage and selection operator) to reduce the redundancy of features and to select the best predictive ones. Moreover, among the radiomics features selected, exponential gray level non-uniformity and wavelet feature cluster prominence were the best predictors . Both features quantify the similarity of gray-level intensity values in the image and describe the heterogeneity of the infarcts. Thus, higher values indicate higher signal heterogeneity of the infarcted lesion, the possibility of lesion progression and worse outcomes . These findings are incongruent with data from Boss et al. study which suggested that visually assessed DWI lesion homogeneity could be associated with significantly higher mRS at three months. Thus, quantitative image analysis via radiomics may offer a better description of lesions' subtle abnormalities or heterogeneity, adding valuable information to conventional imaging markers. Wang et al. investigated a clinical and radiomics-based model to predict one-year stroke recurrence and obtained an AUC of 0.84 (95% CI, 0.82-0.87) and the mean interval time between the first stroke and stroke recurrence was 167.11 +- 100.08 days. The stroke subtypes were significantly different between recurrence and non-recurrence groups (p = 0.003) . Of the 544 large artery atherosclerosis patients, 10.3% of patients repeated the stroke within the first year, and these patients were older than the non-occurrence stroke group (p = 0.016). These findings are inconsistent with previous studies that showed a higher risk of recurrent stroke in large artery atherosclerosis despite aggressive medical treatment. In contrast, 11.3% of atrial fibrillation patients had a stroke recurrence within a year, and these patients were younger than those who did not repeat stroke (p = 0.036) . The lowest recurrence rate was in the group of patients with small vessel disease, which is consistent with previous data . Incongruent with the other five studies , the Wang et al. study failed to achieve predictive values for texture features derived from T2-FLAIR and ADC images. This could be explained by the fact that the other studies built extensive PMs based on multiple clinical factors, conventional imaging markers and numerous radiomics features, whereas Wang et al. investigated in this study few radiomics features. However, Wang et al. found that ADC-entropy and T2-FLAIR 0.75 quantile were associated with baseline NIHSS (AUC = 0.7, p = 0.01). Entropy measures the randomness in the gray level intensities of an image and, visually, an image with higher entropy will appear heterogeneous . Assessing the risk of bias using the PROBAST tool, potential high risk of bias in participants selectin in two studies was identified. Wang et al. excluded a large number of patients (577) from the initial sample due to cerebral hemorrhage and previous neurological or psychiatric disorders. Quan et al. also excluded 154 patients due to bilateral cerebral infarction, multiple territories strokes and neurological dysfunction left by previous AIS or other neurological diseases. All of these factors are associated with unfavorable prognosis in AIS patients , thus, participants selection could influence the findings of the studies. Moreover, only patients with MCA stroke were included in Quan et al. study, thus, their findings cannot be generalized to strokes in other territories. Moreover, the findings of Quan et al. and Wang et al. should be interpreted with caution because the datasets from these studies were imbalanced (number of cases with favorable outcome was much higher compared to number of cases with unfavorable outcome), and oversampling methods were applied such as Synthetic Minority Oversampling Technique (SMOTE) to increase the number of cases in the unfavorable outcome group from both training and validation cohorts. Regarding the participant selection process, it is important to notice that in the population from three studies prevailed the male participants with at least 60% proportion. Previous research suggested that women are more likely to develop a poor long-term outcome after AIS, having a two-to-three-fold risk of poor outcome compared to men, as women develop AIS at an older age when they have multiple comorbid diseases . The RQS is a recently introduced score whose aim is to assess the methodological quality of radiomics-based studies and does not consider differences in study objectives. It could help identifying high-quality results among the large number of publications in this field, as well as issues limiting their value and applicability . The median RQS of the studies included in our systematic review is 15, reflecting a moderate methodological quality. This finding is consistent with previous systematic reviews performing quality assessment with RQS tool in other fields of neuroradiology . However, the RQS score was relatively recently introduced and has been applied in a limited number of occasions . In our review, all studies collected 0 points on the following items: imaging at multiple time points, performing a prospective study to apply the model and cost-effectiveness analysis. Therefore, temporal variability was never tested, also due to the retrospective design of studies. Our study has some limitations that should be acknowledged. The number of included studies was low, probably due to strict inclusion criteria and pre-established study objectives to assess the role of radiomics in ischemic stroke outcome prediction. Study heterogeneity was moderate and meta-analysis was not possible, but this is in line with other systematic reviews investigating RA in the field of neuroradiology . However, to our knowledge, this is the first systematic review evaluating the role of radiomics in stroke outcome assessment and applying the quality radiomics score in stroke studies. AI technologies will herald fundamental changes in healthcare delivery , providing patients with optimal tailor-made treatment. Radiomics may prove to be one of the most impactful AI applications by bridging the gap between medical imaging and personalized medicine . Radiomics-based tools have the potential to change clinical practice in AIS management by exploring digitally encrypted imaging information related to cerebrovascular pathophysiology. Radiomics integrated in AI algorithms could improve stroke diagnosis in acute phase (e.g., diagnosis of acute lacunar stroke on CT, prediction of hemorrhagic transformation) or in chronic phase (e.g., MRI radiomics features may identify prior or undocumented stroke lesions) , guiding the secondary prevention strategies. Machine learning algorithms based on radiomics features also seem to be promising tools for assessing collateral circulation status or clot composition , providing important data that could affect the decision for mechanical recanalization techniques. Developing stroke outcome predictive scores based on clinical and quantitative imaging information and improving them in clinical settings, long-term post-stroke disability could be more accurately assessed, helping physicians to create personalized rehabilitation strategies. However, to create tools with clinical utility, prospective trials that validate radiomics signatures on external datasets are required . There is also a need for standardization of RA in line with recent recommendations . Moreover, identification of radiomics features that remain robust, especially against differences in image acquisition and reconstruction from different scanners, needs further research. 5. Conclusions Our findings suggest that combined models integrating both clinical and advanced imaging variables seem to better predict the patients' disability outcome group (favorable outcome: mRS <= 2 and unfavorable outcome: mRS > 2) at three and six months after stroke onset. Radiomics may be successfully used in AIS assessment, treatment selection and long-term prognosis, providing patients with optimal tailor-made management. In our review, moderate methodological quality of AIS radiomics studies was identified. External validity, prospective studies, cost-effectiveness analysis and publicly available RA protocols are needed to increase methodological quality in stroke radiomics studies. Although their predictive values are significant in the research field, radiomics-based PMs should be validated in multiple clinical settings to become relevant prognosis tools in daily clinical practice and to promote personalized precision medicine. Supplementary Materials The following supporting information can be downloaded at: Table S1: PRISMA checklist; Table S2: Search strategies; Table S3: Radiomics workflow main steps of included studies; Table S4: RQS domains and items; Table S5: RQS scores for all included studies; Table S6: PROBAST scores for all included studies. Click here for additional data file. Author Contributions Conceptualization, H.M.D., A.S., A.L. and D.F.M.; methodology, R.P., D.F., A.L. and C.D.; software, R.P., D.F., A.L. and C.D.; validation, A.S., D.F., S.S. and D.F.M.; formal analysis, H.M.D., A.S., R.P., D.F. and A.L.; investigation, H.M.D., P.-S.P. and R.P.; data curation, A.S., S.S. and P.-S.P.; writing--original draft preparation, H.M.D., R.P., C.D., P.-S.P. and S.S.; writing--review and editing, A.S., D.F., A.L. and D.F.M.; visualization, C.D., P.-S.P. and S.S.; supervision, A.L., A.S. and D.F.M. 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 or Supplementary Material. The data presented in this study are available in [insert article or Supplementary Material here]. Conflicts of Interest The authors declare no conflict of interest. Figure 1 PRISMA diagram of the study selection process. Figure 2 Adherence rate of the RQS of the included studies according to RQS key domains. Figure 3 Methodological quality of the studies included according to PROBAST tool for risk of bias and applicability concerns. diagnostics-13-00857-t001_Table 1 Table 1 Inclusion and exclusion criteria. Inclusion Criteria Exclusion Criteria Studies that investigated MRI radiomics features in patients with AIS Studies that assessed the clinical outcome based on RA features in AIS patients Unavailable data on RA and predictive model performance CT-, US-based RA studies Non-original investigations (reviews, editorials, letters or opinions) CT = computer tomograph, CTA = CT angiography, US = ultrasound. diagnostics-13-00857-t002_Table 2 Table 2 Characteristics of studies included in systematic review. Study, Year Sample, Age, Sex AIS Type Tx Onset-to-MRI Time Outcome Criteria Clinical Factors MRI Markers MRI Seq RA Features Predictive Models AUC, 95% CI Quan et al. , 2021 110, 62, 70.9% male first AIS in MCA territory, onset <=72 h ivT, MT: 12 p 26.5 +- 15.7 90 days unfavorable outcome mRS > 2 Age, gender, admission NIHSS DWI-ASPECT score, ODs FLAIR ADC 6, TA, wavelet Clinical 0.79, 0.68-0.89 Clinical + MRI 0.78, 0.68-0.88 ADC radiomics 0.77, 0.62-0.83 FLAIR radiomics 0.73. 0.62-0.83 ADC + FLAIR radiomics 0.81, 0.73-0.89 RA + Clinical + MRI 0.92, 0.87-0.97 Wang et al. , 2021 399, 67, 63.9% male NR NR within 24 h after AIS onset 90 days outcome mRS > 2 Age, 24-h NIHSS Hemorrhage DWI 11, TA Clinical model 0.77, 0.71-0.84 Radiomics model 0.70, 0.64-0.77 Clinical + radiomics 0.80, 0.75-0.86 Zhou et al. , 2022 311, 58, 72.7% male Pen artery: 43.1%, cMCA: 28.6%, cACA: 5.5%, cPCA = 8.4%, >=2 territories: 14.5% NR <24 h: 6.1%24-72 h: 93.9% 6-month good outcome (mRS <= 2), poor outcome (mRS > 2) Age, gender, stroke history, DM, b-mRS, b-NIHSS - DWI, ADC 7, first-order statistics, TA Clinical model 0.82, 0.77-0.87 Radiomics model 0.76, 0.70-0.82 Clinical + radiomics 0.86, 0.82-0.91 Zhang et al. , 2022 103, 65, 64% male Unilateral anterior circulation NR NR 90 days outcome mRS > 2 Atrial fibrillation - ADC 7, TA, wavelet, LGT ADC 0.60, 049-0.71 tADC 0.83, 075-0.91 tADC + clinical 0.86, 079-0.93 Wang et al. , 2022 1003, 67, 67.9% m Ant-circ: 68.5%, Post-circ: 28.5%, Both: 3% NR 72 h of AIS onset 90 d outcome 1y AIS recurrence NR - DWI 100, TA, wavelet Radiomics model 0.77, 0.75-0.80 Clinical + radiomics 0.84, 0.82-0.87 Wang et al. , 2020 116, 64, 72% male NR NR NR 90 days outcome mRS > 2, stroke severity - - FLAIR, ADC 15, first-order statistics, TA RA features were not predictive of mRS. ADC-entropy and T2-FLAIR 0.75 quantile predicted AIS severity (AUC = 0.7, p = 0.01). Tx = treatment, MRI Seq = MRI sequences for feature selection, MCA = middle cerebral artery, ivT = intravenous thrombolysis, MT = mechanical thrombectomy, OD = orthogonal diameters, TA = texture analysis, FLAIR = fluid-attenuated-inversion recovery, ADC = apparent diffusion coefficient, TA = texture analysis, tADC = texture analysis from ADC, Pen artery = penetrating artery, cor-MCA = cortical branches of middle cerebral artery, cor-ACA = cortical branches of anterior cerebral artery, cor-PCA = cortical branches of posterior cerebral artery, DM = diabetes mellitus, b-mRS = baseline mRS, b-NIHSS = baseline NIHSS, LGT = Laplacian of Gaussian transformation, NR = not reported. 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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PMC10000412 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050932 foods-12-00932 Article Changes in the Sensory Odor Profile during Chorizo Maturation and Their Relationship with Volatile Compound Patterns by Partial Least Square Regression (PLS) Carmona-Escutia Rosa Pilar Conceptualization Methodology Formal analysis Data curation Writing - original draft 12* Ponce-Alquicira Edith Methodology Supervision 2 Garcia-Parra Maria Dolores Methodology Supervision 3 Villanueva-Rodriguez Socorro Josefina Methodology Writing - review & editing Supervision 4 Escalona-Buendia Hector B. Conceptualization Formal analysis Writing - review & editing 2* Hamid Nazimah Academic Editor 1 ESDAI, Universidad Panamericana, Alvaro del Portillo 49, Zapopan 45010, Mexico 2 Departamento de Biotecnologia, Universidad Autonoma Metropolitana, Av. Ferrocarril San Rafael Atlixco 186, Mexico City 09310, Mexico 3 Unidad de Tecnologia Alimentaria, Centro de Investigacion y Asistencia en Tecnologia y Diseno del Estado de Jalisco, Camino al Arenero No. 1227, El Bajio, Zapopan 45019, Mexico 4 Unidad de Tecnologia Alimentaria, Centro de Investigacion y Asistencia en Tecnologia y Diseno del Estado de Jalisco, Normalista No. 800, La Normal, Guadalajara 44270, Mexico * Correspondence: [email protected] (R.P.C.-E.); [email protected] (H.B.E.-B.) 22 2 2023 3 2023 12 5 93212 1 2023 08 2 2023 15 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 ). Odor is one of the most important attributes to determine the overall acceptance of a product. The aim of this investigation is to evaluate the changes in the odor profile and the volatile compounds during thirty-three days of ripening to obtain the pattern of volatile compounds necessary to integrate the odor profile of chorizo (fermented sausage), using Partial Least Squares (PLS). The chili and pork meat odors were predominant during the first five days, vinegar and fermented odors at days twelve and nineteen days, and finally a rancid odor predominated at the end. Only the vinegar, rancid, and fermented odors could be predicted with a good fit model, with the R2 coefficient above 0.5, using linear PLS, and the pork meat odor using logarithmic PLS. Each group of volatile compounds interacted in different ways; esters had a positive influence on the vinegar and rancid odors, but a negative on the fermented odor. Some volatile compounds contributed to more than one odor, such as hexanal, ethanol, and ethyl octanoate. This work allowed us to understand the pattern of volatile compounds required to generate some of the specific odors of chorizo; further studies are required to explore the effect of other food components on these patterns of odors. SPME sensory evaluation generalized procrustes analysis multifactor analysis This research received no external funding. pmc1. Introduction Fermented meat products, such as chorizo sausage, have diverse odors due to volatile compounds derived from the presence of spices, and those generated during fermentation and ripening. The role of food odors is highly relevant to the overall acceptance of a product and it is a key attribute influencing the amount of food that is ingested, because we perceive the smell (orthonasal) before consumption . Dewik et al. showed that odor and visual texture were the key attributes in deciding the amount of food that is ingested. The properties of chorizo have been widely studied, such as its sensory properties , its volatile compound profile during ripening , and an evaluation of different brands of Pamplona chorizo . Other investigations using chorizo have focused on the effect of ripening time and/or different amounts of some ingredients (fat, starter culture, antioxidants) on volatile compounds, as well as their relationship to the acceptance of the product or the effect on the sensory properties , although sensory tests were only carried out on the final product. Similar studies have been undertaken with other dry-fermented sausages . In some cases, the studies omitted spices to avoid interference in the volatile analysis . However, the flavor of these types of products is the result of a complex equilibrium between spices and the variability of volatile compounds derived from different reactions . All of these studies had some limitations, focusing on only a few odors or the global intensity of flavor and/or odor, or the sensory information was focused on preferences and overall acceptability at the end of ripening. Therefore, changes in the odor profile during the whole process of development have been poorly studied in fermented sausages such as chorizo. Gas Chromatography-Olfactometry (GC-O) has also been used to study fermented sausage aromas . The technique consists of the elution of a compound mixture through a column in GC coupled with the human olfactory system as a detector. It allows the active odor compounds that are in suprathreshold odor concentrations to be detected, although GC-O detects these active compounds in isolation . It is important to note that the odors we perceive are not due to a single compound; the perception of an odor is the interaction of volatile compound mixtures, with the odorant receptors in a combinatory strategy where one molecule is recognized by more than one receptor, and one receptor recognizes several molecules . Consequently, the odor/aroma we perceive depends on which receptors are activated, so it is also important to understand the pattern of volatile active compounds that activate the receptors that generate the signals for specific odors. To achieve this, multivariate statistics can be used as tools to explore relationships between volatile composition and odor/aroma perception in foods. Principal Component Analysis (PCA) is the most common multivariate statistical technique used to evaluate the relationship between volatile and sensory information, but it is only an exploratory method, providing an overview of the data. Other modeling techniques must also be explored . Partial least squares (PLS) modeling combines features from PCA and multiple regression to predict a set of dependent variables, the sensory data, from a large set of independent variables, the predictors, which are the volatile compounds . PLS has been applied in other studies on meat products , Salami Milano sausage , pac choi , roasted peanuts , and wines . To our knowledge, there is no other study that describes the volatile compound pattern which generates the odors in chorizo during the ripening process using this statistical method. Our aim was to evaluate the changes in the odor profile of chorizo during the maturing process over thirty-three days, and relate this to the changes of volatile compounds, in order to obtain the pattern of compounds that generate each specific odor involved in the odor profile of chorizo, using Partial Least Squares as the multivariate statistical technique. 2. Materials and Methods 2.1. Sausage Manufacture Chorizo samples were manufactured in the pilot plant of the Centro de Investigacion y Asistencia en Tecnologia y Diseno del Estado de Jalisco (CIATEJ). A batch of 12 kg was prepared with 20% pork back fat and 80% lean pork, obtained from a local market in Guadalajara, Jalisco. Lean and back fat were ground through a 5 mm diameter mincing plate (Torrey CI-22-1 L9N2E, Nuevo Leon, Mexico) in the grinder (Torrey Mod. M-22RW, Nuevo Leon, Mexico). Then, they were mixed with the rest of the ingredients in g/kg of mixture: 22 of paprika, 20 of salt, 10 of glucose, 3 of garlic, 1.5 of pepper, 0.5 of sodium ascorbate (all spices were obtained in a local market in Guadalajara, Mexico), and 0.15 of sodium nitrate (Fabpsa(r), CDMX, Mexico), with 40 mL of water. Starter cultures were not added. The meat mixture was maintained at 4 degC for 24 h and then was stuffed into a synthetic casing with a diameter of 35-38 mm and tied in small pieces of approximately 15 cm, which were then transferred to a dry-ripening chamber where they were kept for 5 days at 6-8 degC and at the relative humidity of the environment (50-80%). Finally, the temperature was increased to 10-12 degC and maintained for 28 days for ripening. A sample of 200-250 g (four pieces of chorizo) was taken for volatile analysis and 500-600 g (eight pieces) for sensory analysis, per day of ripening, at 0, 5, 12, 19, 26, and 33 days (D0, D5, D12, D19, D26, and D33, respectively), and all samples were randomly taken and vacuum-packaged and stored at -20 degC for not more than three months until the respective analyses. Physico-chemical and microbiological analyses of these samples have been previously reported . 2.2. Sensory Evaluation The sensory evaluation was carried out by conventional descriptive analysis, focusing only on the odor profile. The panel consisted of seven people (one man and six women between 24 and 45 years old), selected according to their ability to detect and recognize basic tastes and a series of odor compounds (listed in Table 1) selected from previous chorizo, salami, and other sausage studies, and their discrimination ability. For this purpose, a triangle test with two volatile compounds (carvacrol and eugenol) and a duo-trio test with two commercial brands of chorizo were performed. Commercial and homemade chorizo samples were used to generate the first list of descriptors, then a preliminary list was obtained in two consensus sessions, and the intensity of the preliminary terms in the chorizo samples was evaluated. The final list of descriptors consisted of eight terms: vinegar, fermented, chili, garlic, pepper, greasy, rancid, and pork meat (Table 2). These terms were relevant to describe the chorizo, not redundant or hedonic, and able to discriminate between samples . The training phase consisted of three steps. The first step was recognition and familiarization with different types of spices: onion, garlic, oregano, pepper, cumin, clove, vinegar (acetic acid), and fermented (lactic acid) through a matching test, in which four samples per session were used. The second step aimed at familiarization with simple pork meat mixtures. The first mixtures consisted of minced pork meat and one spice, and then more complex mixtures of minced meat with more than one spice were used. Three mixtures per session were presented to the panelists, and each one was evaluated in duplicate. The third step was evaluating the intensity of the odor terms in various chorizo samples at different times of ripening. The sensory tests were conducted in a sensory laboratory with individual cabinets kept free from odors. The six samples of chorizo (D0, D5, D12, D19, D26, and D33) were placed in an odorless amber glass bottle (75 mL) covered with aluminum and coded with three digits, presented simultaneously in a randomized order, to be evaluated in duplicate by each judge. The eight odors were included for each replicate (session), but there was a break for each judge after the first four odors. The intensity of each odor was evaluated on a 15 cm non-structured line scale from 0 (not perceived) to 15 (maximum). 2.3. Analysis of Volatile Compounds The volatile extraction was carried out using solid-phase micro-extraction (SPME) in triplicate. Each sample (3 g) was placed inside a 40 mL amber vial, screw-capped with a PTFE/silicone (Supelco, Bellefonte, PA, USA) septum, in a metallic block thermostat at 35 degC for 60 min, based on the methodology reported by Flores & Olivares . After this period of time, a DVB/CAR/PDMS (divinylbenzene/carboxen/polydimethylsiloxane) fiber, film thickness 50/30 mm (Supelco), was placed in the headspace for 120 min at the same temperature. The fiber was conditioned for 60 min at 240 degC prior to extraction. The methodology for quantification of volatile compounds was adapted from Flores & Olivares and carried out on a Gas Chromatography system GC-2010 (Shimadzu Corporation, Kyoto, Japan) equipped with a flame ionization detector (FID). A split-splitless injection port held at 240 degC was used to thermally desorb the volatile compounds from the SPME fiber onto the front of a DB-624 UI capillary column of 30 m x 0.25 mm, i.d., 1.4 mm film thickness (Agilent J&W, Palo Alto, CA, USA), and nitrogen was used as a carrier gas at a linear velocity of 37 mL/min flow rate. The temperature was 37 degC, isothermal for 13 min, then raised to 110 degC at a rate of 3 degC/min and maintained for 10 min, then raised to 150 at a rate of 3 degC/min, and then 210 degC at a rate of 5 degC/min and held for 10 min. The total run time was 82.67 min. Injector and detector temperatures were both set at 240 degC. The content of each volatile compound was calculated from the FID area and was multiplied by 10-5 for easier data management. Volatile compounds were identified with three complementary approaches. These included mass spectrometry using a GC 6890N (Agilent Technologies, Palo Alto, CA, USA) equipped with a mass selective detector 5975N (Agilent Technologies), using the same column and conditions by quantification section. The mass spectra were obtained by electron impact at 70 eV, acquired over the range m/z 40-500, and compared with the database of the NIST MS library (National Institute of Standards and Technology, Gaithersburg, MD, USA). Additionally, the linear retention indices (LRI) for the compounds were obtained by using the series C5-C18 (Supelco) of alkanes in the CG-FID with the same column and conditions, and compared with the LRI available in the references, which used the same column . Finally, some compounds (these are indicated in Table S2, Supplementary Material) were also compared with the retention time of the authentic standards in CG-FID. 2.4. Statistical Analysis Three-way ANOVA was carried out on the sensory data for each attribute, considering the sample, sessions, and assessor as fixed factors at a 95% significance level in the analysis. Generalized Procrustes Analysis (GPA) was used to evaluate the repeatability, discrimination ability, and panel agreement; parameters were considered to establish that the panel was training. The GPA is widely applied in sensory profiling data and uses translation, rotation/reflection, and isotropic scaling to minimize the effects of the different average scoring positions on a line scale, the interpretation of the attributes, and the different ranges of scoring that assessors use . Means and standard deviations were calculated for the data of volatile compounds. One-way analysis of variance (ANOVA) was carried out to analyze the effect of ripening time. The Tukey multiple range test was applied to compare the significance of means. Multifactor Factor Analysis (MFA), using ten groups of variables that correspond to nine groups of volatile compounds and sensory data, was applied to explore their evolution during chorizo ripening. Partial Least Square regression (PLS-R) was carried out to predict the model of the pattern of volatile compounds to generate each odor. The fit model to predict each odor by the volatile compounds (R2 Y), the capacity of the model to predict the odor (R2 X), and the index of quality (Q2) were considered to evaluate the quality of each model . The optimum number of the factor was determined by leave-one-out cross-validation (Jackknife-LOO). The volatile compounds with Variable Importance for the Projection (VIP) >1, and standardized coefficients of >0.025, were selected as the most important variables to predict each odor, applying the PLS model. All statistical analyses were performed in XLSTAT (version 2019.2, Addinsoft, Boston, MA, USA). 3. Results and Discussion 3.1. Sensory Evaluation In general, the ANOVA results of the sensory data (Table S1) showed that factor ripening time (day) had a significant effect (p < 0.05) on the eight odors; vinegar, fermented, rancid, greasy, chili pepper, garlic, and pork meat; these results showed that the odor profile changed during ripening. Additionally, the judging factor had a significant effect (p < 0.05) on all odors. Even though the judges were trained, differences between them were common, as they used different parts of the scale, but the session factor did not have a significant effect (p > 0.05) in any odor, indicating that the judges were consistently able to detect the odor differences at the diverse times of ripening in different sessions . When we analyzed the panel data through GPA, Figure 1, we observed that all judges had the ability to differentiate. Results for the repeatability were similar, as the sample evaluations of sessions one and two were close to each other. Figure 1 shows the evolution of the odor profile during the ripening of chorizo samples. In general, the GPA explained 65.44% of the variability, and the first GPA dimension (F1) explained 43.16% of the variability. The chorizo at zero and five days of ripening (D0 and D5, respectively) was on the negative side, while the chorizo samples at twelve, nineteen, twenty-six, and thirty-three days of ripening (D12, D19, D26, and D33, respectively) were on the positive side. The beginning of ripening, D0, was characterized by the pork meat odor and chili odor, then these odors decreased during ripening, although the first odor had a slight increase on the final day of ripening, showing similar results to those reported previously . Vinegar, fermented, and rancid odors were detected; these odors were not expected until the final ripening. Nevertheless, some ingredients of chorizo, such as paprika, contain a diversity of organic acids, such as acetic acid, which could be related to the first two odors . The intensity of the garlic odor increased from five days of ripening, but the judges found significant differences (p < 0.05) only between D0, with the least intensity, and the chorizo samples at the end of ripening, D26 and D33, with the highest intensity values. This result contrasted with Fernandez-Fernandez et al. and Stahnke et al. , who found that the garlic odor did not change over time. The garlic odor is mainly associated with sulfur compounds, and previous research has found that the amount of some sulfur compounds, such as allyl methyl sulfide, increased during ripening , so this likely explains the increase in the garlic odor. The second GPA dimension (F2), explaining 22.29% of variability, formed a group with D0, D12, and D19 on the positive side, while the negative side grouped the D5, D26, and D33 samples. The chorizo samples in the middle of ripening, D12 and D19, showed the highest intensity of vinegar and fermented odors that were significantly different (p < 0.05), Table S1, from the rest of the ripening days. At the same time, as the vinegar odor increased, we observed an increase in lactic acid bacteria (LAB) growth, data not shown, as reported by Carmona-Escutia et al. . This bacteria group is mainly responsible for carbohydrate fermentation, which generates a diversity of organic acids, such as acetic, propionic, and lactic acid; compounds associated with vinegar and fermented odors . Lactobacillus sakei was considered potentially responsible for these sensory characteristics, together with other microorganisms . The odor profile in the chorizo samples at the end of the process, D26, showed that the rancid odor had the highest score, with a significant difference (p > 0.05), in accordance with other studies on Galician chorizo and salami . Additionally, in those studies, the global odor intensity was evaluated and shown to decrease during ripening. We observed that although at day thirty-three, D33, fermented and rancid were the predominant odors, both had decreased in intensity compared with D26. Additionally, the intensity of vinegar and chili odors decreased at the end of ripening when compared with D19. According to our results, the global odor is probably integrated vinegar, fermented, rancid, and chili. 3.2. Relationship between Volatile Compounds and the Odor Sensory Profile A total of 120 volatile compounds were extracted by SPME and identified (Table S2). The groups of compounds were twenty-three aldehydes, twenty alcohols, sixteen terpenes, thirteen esters, twelve ketones, eleven alkanes, ten aromatic compounds, eight acids, and seven sulfur compounds. The MFA, including volatile and sensory data, explained 65.02% of the variability of the data, and this analysis was applied in order to explore the change of different groups of volatile compounds during chorizo ripening, Figure 2. The first MFA dimension (F1) explained 39.30% of the variability, allowing the first days of ripening, D0 and D5, to be differentiated; these were located on the positive side of F1, with the remaining days of ripening, D12, D19, D26, and D33, on the negative side of F1. Terpenes were the principal groups of volatile compounds related to the pepper, greasy, and pork meat odors at days D0 and D5, Figure 2B. The terpenes were the compounds occurring at the highest amounts at this time of the process, including a-thujene (T1), a-caryophyllene (T16), a-terpinene (T4), thujene (T7), 3-carene (T11), and b-caryophyllene (T15), Table S2. The main sources of these compounds were spices, pepper, and paprika , which probably explains their relationship with the pepper odor. In general, the major terpenes decreased during ripening (Table S2). Lorenzo, Bedia et al. found similar results and suggested that the volatile compounds from spices, such as pepper and garlic, were lost and/or degraded during ripening. Nevertheless, only T11 and T15 were significant (p < 0.05), probably because the amount of spice was not the same in each sample of chorizo analyzed, which generated a large data variation, as is common in flavor analysis in meat products . Sulfur compounds such as allyl mercaptan (S1) and allyl sulfide (S4) showed a slight increase (not significant p > 0.5), Table S2, but allyl methyl sulfide (S2) and dimethyl disulfide (S3) decreased significantly (p > 0.05). In general, sulfur compounds decreased during ripening, and Gorraiz et al. reported a similar finding for this group of compounds. Some sulfur compounds came from the meat, and these were formed from the degradation of amino acids with sulfur content, such as methionine, cysteine, and cysteine, via Strecker degradation to thiols , as well terpenes, like styrene, which came from the meat as a consequence of their presence in animal feedstuff , so the relationship between sulfur and terpene compounds with pork meat odor was expected. Another group of compounds detected at days D0 and D5 were alkanes, such as pentane (A1), hexane (A2), and isobutene (A3), and some alcohols, such as octan-1-ol (L19), butan-1-ol (L5), and hexan-1-ol (L12). Many of these were derived from fatty acids; the source of the fat was the back fat used to make the chorizo, and this possibly explains their relationship with the greasy odor. Alcohols, aldehydes, and acids were the main groups of volatile compounds present in the middle of the ripening time, D12 and D19, and were related to vinegar, fermented, and chili odors. These were located on the negative side of the second MFA dimension (F2) that explained 25.73% of the variability; Figure 2. During these days, ethanol (L1) was the major alcohol (significant at p < 0.05), Table S2; this came from the catabolism of amino acids and carbohydrate fermentation, and was close to the fermented odor, meaning a strong relationship with alcohol existed. Gorraiz et al. found that alcohol also contributes to beef flavor. Other alcohols, such as 2-methylbutan-1-ol (L8) and 2-phenylethanol (L20), were derived from amino acid degradation; these were products of Strecker reactions, associated with the Maillard reaction or caused by bacterial enzymes . Additionally, phenol (L18) occurred in the highest amount at D12 and D19 (p < 0.05), then decreased at the end of ripening, probably due to alcohol's participation in ester formation. Acetic acid (C1) was also related to the fermented and vinegar odors. C1 was the most abundant acid during the process and came from carbohydrate fermentation, paprika, or compounds from Maillard reactions . It occurred in the highest amount at D19 (p < 0.05), then had a slight decrease. Similar results were obtained previously . Other important acids in these days were propanoic (C2), pentanoic (C4), and heptanoic acids (C6). The linear saturated aldehydes propanal (AD1), butanal (AD3), and heptanal (AD9) increased significantly (p < 0.05) at days D12 and D19, then decreased by the end, D33, and were related to the vinegar and chili odors, Figure 2B. In addition, 2-methylpropanal (AD2) also increased on these days, but not significantly. The branched aldehyde AD2 originated from valine degradation ; AD1, AD3, and AD9 were probably formed by an oxidation reaction of their respective alcohols, while AD9 could also have come from autoxidation of fatty acids . The last days of ripening, D26, located on the negative side of F1, and D33, on the positive side of F2, Figure 2A, were related mainly to the rancid odor and various groups of volatile compounds generated by the increase of degradation of amino acids, and oxidation of fatty acids by bacterial enzymes, which related to an increase of molds and LAB at days D26 and D33 . The compounds derived from proteolysis or degradation of amino acids, such as 3-methlbutan-1-ol (L7), 2-methylbutan-1-ol (L8), ethyl-3-methyl-butanoate (E6), and benzaldehyde (AD12), showed significant differences (p < 0.05), except for the last one; similar findings for these aldehydes were reported previously . At D33 of ripening, hexanal (AD7) was the major aldehyde (significant p < 0.05); this came from the oxidation of n-6 fatty acids and linoleic and arachidonic acids , so has been used as a marker of both lipid oxidation and flavor deterioration . Therefore, the relationship with the rancid odor was expected. The unbranched alcohols, pentan-1-ol (L9), hexan-1-ol (L12), and octen-1-en-3-ol (L15), increased significantly (p < 0.05) at the end of ripening; these came from lipid autooxidation reactions or incomplete b-oxidation . Due to their origin, Resconi et al. proposed L12 and other volatile compounds be used as a shelf-life marker in raw beef. The ketones, pentan-2-one (K3), pentane-2,3-dione (K4), and heptan-2-one (K6), occurred in the highest amounts (significant p < 0.05) at D33. These can be produced by lipid oxidation, oxidation of free fatty acids, alkane degradation, or bacterial dehydrogenation of secondary alcohols . Esters were the least abundant group but had an important impact on chorizo odor, probably due to their low threshold, and commonly generate fruit notes . However, in this study, esters were related to the rancid and fermented odors. Esters were formed through the esterification of alcohols and carboxylic acids following microbial esterase activity, mainly attributed to staphylococci, LAB, yeast, and molds . Ethyl butanoate (E3), ethyl pentanoate (E8), methyl octanoate (E10), ethyl octanoate (E11), and ethyl decanoate (E12) significantly (p < 0.05) increased their concentrations during ripening, Table S2. The most abundant was ethyl (2E,4E)-hexa-2,4-dienoate, which came from the mixture of sorbic acid and natamycin applied to the sausage casing to prevent surface molds, as previously reported . 3.3. Pattern of Volatile Compounds of the Specific Odors Using PLS In order to determine the patterns of volatile compounds, we created two PLS models for each odor, evaluated by sensory analysis: a linear PLS using the raw areas of the volatile data and a log PLS, where a logarithmic transformation of the areas was made. Using the linear PLS model, the results showed the eight odors had a good fit model (R2Y), above 0.85, but only vinegar, rancid, fermented, and pork meat models had a good capacity to predict these, because their parameter R2 X was above 0.5 , and they had a positive fraction of the sensory variable, which can be predicted by components using cross-validation, Q2 Table 3. However, in the linear PLS model, only the volatile compounds with large quantities or with the highest area had a significant weight in the model. According to Chambers & Koppel , the logarithmic transformation increases the weight of the volatile compounds found at a lower concentration, which is an important factor to consider, since odor perception not only depends on the concentration of the volatile compound but also on their odor threshold, as well as the interactions that they have with other volatile compounds and other foods components . Therefore, we decided to apply the logarithmic transformation to our data and obtained the logarithmic PLS model. The results showed that vinegar, fermented, and pork meat odors increased their fitness predictive model using a logarithmic PLS. Lykomitros et al. reported a similar increase in R2 X coefficients when they applied logarithmic PLS to predict four flavors of roasted peanuts, suggesting logarithmic transformation was a good choice. Rancid odor had the best model prediction using a linear PLS in terms of the difference in the prediction model of each odor. This can probably be explained as the odor detection or recognition of the major volatile compounds related to fermented, vinegar, and pork meat, which have a logarithmic function, while the compounds related to a rancid odor have a linear function . Then, we determined the volatile compounds that predicted each one of the four odors using the best predictive PLS model. Vinegar odor was positively related to propanal (solvent), butanal, (pungent), heptanal (fat, rancid), 2-methyl propanal (sour, green), ethanol (sweet), some esters such as ethyl butyrate (apple) and ethyl octanoate (fruit, fat), propanoic acid (pungent, rancid), pentanoic acid (sweet, rancid), heptanoic acid (rancid), and acetic acid (sour) . Often, vinegar odor was only associated with one compound, acetic acid , but the process by which we perceive one odor, in this case, vinegar, is complex; when we smell food, all volatile compounds reach the nose at the same time, not just one compound, so the vinegar odor was generated by more than one volatile compound. At present, we have no knowledge of another study focused on the vinegar odor in sausages; the closest one was the sour-sock odor investigated by Stahnke et al. , which was related to some ketones (butan-2-one, hexan-2-one, heptan-2-one), propanol, sulfur compounds, acetoin, and others. The branched aldehyde, 2-methyl propanal, was the only volatile compound found in common with this study. Compounds negatively related to this odor were styrene (balsamic, gasoline), 3-carene (lemon, resin), hexen-2-enal (apple, green), 2-methylfuran (chocolate), and some alkanes such as octane and pentane (alkene odor, both). These compounds belong to the alkanes and terpenes, and some authors have noted that these groups of volatile compounds are unlikely to contribute to flavor, due to the fact that they have a high threshold . Nevertheless, these negatively related compounds also had an impact on vinegar odor, so their presence is probably only the result of creating a synergism, suppression, or increase in other important volatile compounds that are part of the pattern of compounds . Rancid odor was positively related to butanal (pungent), non-2-enal (toast), oct-2-enal (glue), 2-methyl-butan-1-ol (wine, onion), ethanol (sweet), hexanal (grass, fat), propanoic acid (pungent, rancid), acetic acid (sour), 2-phenylacetaldehyde (sweet, green), and some esters, such as ethyl octanoate (fruit, fat) and ethyl decanoate (grape). This odor was negatively related to 2-ethylhexan-1-ol (green), butan-1-ol (medicine), pentan-2-ol (green, plastic), allylmercaptan (garlic), and a-terpinene (woody) Figure 3. Other authors have reported the relationship of rancid flavor with non-2-enal, octanol , organic acids such as pentanoic and hexanoic acids, 2-pentyl furan, ethyl octanoate , and hexanal , which is the main volatile compound associated with rancid odor and is strongly related to aroma quality and consumer acceptability . Fermented odor was positively related to non-2-enal (toast), 2-methylbutan-1-ol (wine), ethanol (sweet), propanal (solvent), hexanal (grass, fat), and undecane (alkane), and negatively related to ethyl octanoate (fruit, fat), methyl octanoate (orange), 2-methylfuran (chocolate), allyl mercaptan (garlic), and dodecane (alkane), Figure 3. Some compounds, like 2-methylbutan-1-ol, butanoic acid, pentanoic acid, and ethyl hexanoate, create a fermented odor in cheese . In meat products, Hu et al. found the volatile compounds nonanal, octanal, hexanal, 1-octen-3-ol, heptanol, ethyl hexanoate, ethyl butyrate, ethyl acetate ethyl heptanoate, ethyl octanoate, and methyl hexanoate had an impact on the overall flavor profile of the fermented sausage. Furthermore, Corral et al. found that the esters ethyl 2-methylpropanoate, ethyl-3-methylbutanoate, ethyl butanoate, ethyl pentanoate, and ethyl hexanoate contribute to fermented sausage aroma. Our results also showed that some esters contribute to generating this odor, but indirectly, due to the fact that these had a negative correlation; the presence of esters probably overpowers the fermented odor . Another study found a relationship with 3-methlbutanal, 2-methylbutanal, diacetyl, and 3-methyl butanoic acid . Pork meat odor was positively related to pentane (alkane), 2-methyl furan (chocolate), ethyl propanoate (fruit), heptan-2-one (cheese), and heptan-2-ol (mushroom), and negatively related to 2-methylbuthyl acetate (fruit), ethanol (sweet), ethyl butyrate (apple), heptanoic acid (unpleasant), heptanal (fat, rancid), nonanal (fat, citrus), limonene (citrus), terpinen-4-ol (wood), and undecane (alkane), Figure 3. Furan is the main group of volatile compounds related to meaty flavor, but other authors have found 3-methyl furan, 2-ethyl furan, 2-acetyl furan, and 2-pentyl furan are related to meat odor . These are derived from linolenic acid and other n-6-fatty acids . Pavlidis et al. reported that aldehydes such as pentanal, hexanal, decanal, nonanal, and benzaldehyde are characteristic volatile compounds in minced pork meat, explaining why we found the contribution of heptanal and nonanal to the pork meat odor, although these were negatively related. Bueno et al. obtained a negative relationship between meaty odor and aldehyde, saturated and unsaturated. Previous studies have found that ethanol, ethyl octanoate , and limonene are associated with this odor. Even though the groups of sulfur compounds are important to meaty flavor, in our results, the sulfur compounds did not show an important contribution to pork meat odor, probably due to the methodology that we used to detect the volatile compounds. When we used a linear PLS allyl sulfide we found they did become important to this odor, which was probably because the sulfur compounds are associated mainly with beef flavor . 4. Conclusions The odor profile of chorizo changed during ripening; pork meat, pepper, and greasy odors predominated at the beginning of the process, while vinegar and fermented odors predominated in the middle of the ripening period, on days twelve and nineteen, and while rancid was the predominant odor at day thirty-three. However, to determine the best time for ripening, a consumer test should be carried out to relate this odor profile to levels of taste and preference. This is a possible aim of future work. The use of PLS allowed us to obtain a pattern of volatile compounds to generate the vinegar, fermented, rancid, and pork meat odors. Only these four odors had a good fit model, probably due to the fact that the number of days of chorizo samples ripening used in the study was insufficient since more data is necessary to get better results with this tool. Vinegar, pork meat, and fermented odors improved their fit model when we used a logarithmic transformation in PLS, and rancid odor improved with linear PLS. Odor perception is a complex interaction between diverse groups of volatile compounds; one group of volatile compounds interacts in different ways depending on each odor. For vinegar and rancid odors, the esters had a positive influence, while they had a negative influence on fermented odor. Moreover, some volatile compounds contributed to more than one odor, such as hexanal, ethanol, and ethyl octanoate. In general, this work contributed to the understanding of the pattern of volatile compounds that generate some specific odors of chorizo, but we have not considered how other ingredients could affect the perception of these odors. Therefore, further studies are required where the contribution of some other components, like nonvolatile compounds, are considered. Acknowledgments The authors are grateful to the Mexican National Council of Science and Technology (Consejo Nacional de Ciencia y Tecnologia-CONACYT) for the PhD scholarship of R.P. Carmona-Escutia, received at Universidad Autonoma Metropolitana in the Biotechnology Postgraduate Program (REF 001466). RP. Carmona-Escutia also wants to thank Jacobo Rodriguez for his support with the instrumental equipment and all the people who participated in the sensory panel. Supplementary Materials The following supporting information can be downloaded at: Table S1. Means of the eight odors evaluated by a trained panel during ripening; Table S2. Means and standard deviations of volatile compounds, grouped according to their chemical class, were expressed in UA (1.0 x 10-5) on days 0, 5, 12, 19, 26, and 33 of ripening. Click here for additional data file. Author Contributions R.P.C.-E.: Conceptualization, methodology, formal analysis, data curation, writing--original draft, E.P.-A.: Supervision, methodology, M.D.G.-P.: Supervision, methodology, S.J.V.-R.: Methodology, supervision, writing--review and editing, H.B.E.-B.: Conceptualization, formal analysis, writing--review and editing. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study is part of the divisional project "techno-biofunctional and sensory properties of biomolecules and their application in food" and it has the approval of the Ethics Committee of Universidad Autonoma Metropolitana-Iztapalapa under the number 1913 on 31 October 2019. 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 Biplot of Generalized Procrustes Analysis for the six days of ripening of chorizo samples (D0, D5, D12, D19, D26, and D33), and each session (S1 and S2), and the loadings of sensory descriptors. Figure 2 (A) Map of days of ripening, D0, D5, D12, D19, D26, and D33. (B) Evolution of the groups of volatile compounds and eight odors in chorizo samples using a Multifactor Analysis (MFA). Figure 3 Standardized coefficients of volatile compounds used to predict odors: rancid (A), fermented (B), vinegar (C), and pork meat (D). foods-12-00932-t001_Table 1 Table 1 List of fourteen odor compounds used during panel selection. Odor Compound Brand a Concentration b (ppm) Odor Descriptor Furfural SF 90 bread, almond, sweet 8 Linalool SA 3 citrus-like, bergamot-like 6 Isoamyl acetate SA 10 fruity, banana, pear odor 7 Eugenol SA 10 spicy, smoky, clove-like 7 Dimethyl sulfide FK 0.1 Cauliflowers 1, cabbage, sulfur 8 1-Octen-3-ol SA 10 earthy, dust, mushroom 1,2,3,4,5 Limonene SA 12 citric, fresh 1,2,3 Benzaldehyde SA 10 bitter almonds 1 2,3-Butanedione FK 0.03 Buttery 1,4, cheese 2,3 Myrcene SA 15 hop-like, geranium-like 6 Carvacrol SA 25 medicinal, origanum, herbaceous 7 Ethyl butanoate SF 2 Fruity 6 Acetic acid SF 30000 Vinegar 4, pungent, sour 5 Hexanal FK 6 rancid, fresh cut grass 2,3,4,5 SF: SAFC, Missouri, USA; SA: Sigma-Aldrich; FK: Fluka, Missouri, USA. a: All Kosher grade; b: Threshold reported by Czerny et al. . 1 ; 2 ; 3 ; 4 ; 5 ; 6 ; 7 Flavor-base " (accessed on 10 April 2020; 8 Flavornet " "(accessed on 10 April 2020). foods-12-00932-t002_Table 2 Table 2 Definition and references used to evaluate the odor intensity. Odor Definition Reference Samples Greasy Odor associated with the pork back fat 5 g of pork back fat Fermented Odor associated with the lactic acid or cheese 25 mL of 2% (v/v) lactic acid Garlic Odor associated with the garlic powder 5 g of garlic mixture (0.5 g garlic powder/100 g pork meat minced + 50 mL of water) Vinegar Odor associated with the acetic acid 25 mL of 0.4% (v/v) acetic acid Rancid Odor associated with the old oil 1 soup spoon rancid olive oil Chili Odor associated with the paprika 5 g of chili mixture (1.5 g paprika + 50 mL water/100 g pork meat minced) Pork meat Odor associated with the minced pork meat 5 g pork meat minced Pepper Odor associated with the pepper powder 5 g of pepper mixture (1 g/100 mL pork meat minced + 50 mL of water) foods-12-00932-t003_Table 3 Table 3 Results of quality parameters of the predicted model for the chorizo odors, obtained by linear and logarithmic Partial Least Squares. 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PMC10000413 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050637 healthcare-11-00637 Article Effectiveness of Dengue Awareness Calendar on Indigenous Population: Impact on Knowledge, Belief and Practice Wong Li Ping Conceptualization Methodology Validation Formal analysis Data curation Writing - original draft Writing - review & editing Supervision 12+ Rajandra Arulvani Methodology Formal analysis Data curation Writing - original draft 1+ Abd Jamil Juraina Conceptualization Validation 3 AbuBakar Sazaly Conceptualization Writing - review & editing Funding acquisition 3 Lin Yulan Conceptualization Funding acquisition 2* Lee Hai Yen Conceptualization Methodology Validation Writing - review & editing Supervision 3* Tung Tao-Hsin Academic Editor 1 Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia 2 Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China 3 Tropical Infectious Disease Research and Education Centre (TIDREC), Higher Institution Centre of Excellence (HiCOE), Universiti Malaya, Kuala Lumpur 50603, Malaysia * Correspondence: [email protected] (Y.L.); [email protected] (H.Y.L.); Tel.: +603-79676670 (H.Y.L.) + These authors contributed equally to this work. 21 2 2023 3 2023 11 5 63714 1 2023 17 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 ). Background: Dengue is prevalent among the indigenous community due to impoverished living conditions near the forest fringe areas and lack of health awareness. The study aims to determine the effect of a dengue awareness calendar on knowledge, belief, and practices (KBP) among the indigenous population. Method: A cross-sectional study was conducted in nine selected indigenous villages in Selangor, Malaysia. A dengue awareness calendar was distributed to the indigenous communities after pre-intervention. The KBP scores were compared between the pre-and post-intervention. Result: A total of 609 paired responses were obtained. Knowledge, perceived severity, cues to action, self-efficacy, and prevention practices were significantly improved after the intervention (p > 0.00). Participants with primary (Odds Ratio (OR) 2.627; 95% CI 1.338-5.160) and secondary level education (OR 2.263; 95% Cl 1.126-4.550) reported a high increment in practices score. High increments in dengue knowledge scores (OR 2.190; 95% CI 1.521-3.757, p < 0.00) were significantly more likely to report a high increment in practices score. Housewives (OR 0.535; 95% Cl 0.289-0.950), perceived severity (OR 0.349; 95% CI 0.184-0.662), and perceived susceptibility (OR 0.474; 95% CI 0.286-0.785) were significantly less likely to report an increment in prevention practices score. Conclusion: Findings inferred that the dengue awareness calendar significantly improved knowledge and practices. Our findings revealed the effectiveness of the dengue awareness calendar in dengue prevention among indigenous communities. dengue fever indigenous community knowledge belief prevention practices Ministry of Higher Education, Malaysia Higher Institution Centre of Excellence (HICoE) programMO002-2019 Skim Dana Program Flagship DSTINFP0514D0025-2 Ministry of Higher Education, Malaysia Higher Institution Centre of Excellence (HICoE) program (Project MO002-2019) and Skim Dana Program Flagship DSTIN (Project number: FP0514D0025-2) Development, Evaluation and Integration Of Innovative Tools To Reduce Dengue Morbidity And Mortality In The Community by the Ministry of Science, Technology and Innovation Malaysia (MOSTI Malaysia). pmc1. Introduction Dengue fever is an alarming epidemic worldwide, and 3.6 billion people are at high risk of being infected with dengue fever . Malaysia was ranked third in the number of cases due to the hyper-endemic outbreak of dengue . The incidence and death of dengue in Malaysia have grown dramatically over the years. The highest number of dengue cases was reported in 2019, with 130,101 cases, and the highest dengue mortality cases were recorded in 2015, with 336 deaths. (Department of Statistics Malaysia, 2020). The increasing world population, unplanned rapid expansion of urbanization, global warming, ineffective mosquito control methods, inadequate health care facilities, migration, globalization travel and trade, and an uneven climate are some of the key factors contributing to the increase in disease transmission, spreading to new territories and rural areas . Past studies in Malaysia showed that dengue has spread from urban to rural areas, including forest fringe areas where most of the indigenous community resides . Indeed, in 2014, a study revealed that seroprevalence cases were reported significantly higher in rural areas compared to urban areas . The indigenous population, also known as Orang Asli (in the Malaysian language), is the minority in Malaysia and accounts for less than 1% of the total population in Malaysia. Indigenous people are classified into three main ethnolinguistic groups, namely Senoi, Proto-Malays, and the Negritos, each consisting of different dialectic subgroups and geographical locations . The control of mosquito-borne viral infections is very challenging, especially in rural and forest fringe areas . Primary prevention, such as vector control, is the key to overcoming dengue phenomena but is often inhibited due to low community support and involvement . Early detection and prompt access to medical care are the prime factors in reducing fatalities in the absence of any specific treatment . Community participation is vital for successful prevention and relies heavily on awareness, knowledge, and attitude about the disease, mode of transmission, and breeding sites . Knowledge, attitude, and practices (KAP) research is often used in assessing the level of awareness and disease prevention practices . Studies involving dengue and its prevention among the indigenous community are lacking in Malaysia. To date, only one study has been performed to assess the KAP of this community in Malaysia . Health education plays an important role in providing adequate knowledge of the disease and its vector, as well as promoting behavioral changes such as following proper prevention practices to reduce the severity of cases . Intervention targeting environmental cleanliness, vector control, and changing human behavior is important. This dengue awareness calendar was designed to assist the user in improving their dengue knowledge and health beliefs and subsequently performing the correct dengue prevention practices as their daily routine through vibrant infographic design and daily visual contact with the calendar. Our main objective is to evaluate the effectiveness of the dengue awareness calendar in enhancing dengue knowledge, health beliefs, and prevention practices among indigenous communities in Selangor, Malaysia. Moreover, this study aims to identify the factors that influence the increase in dengue prevention practices. 2. Materials and Methods 2.1. Sampling Frame We conducted a cross-sectional study among the indigenous community in Selangor state in Peninsular Malaysia. The sample for this study was indigenous people originating and living in the selected village. According to the Department of Orang Asli Development (JAKOA), there are seven out of nine districts in Selangor where indigenous people are found. From these seven districts, two villages from each district where JAKOA was able to assist in accessing the indigenous community of the respective districts were selected using purposive sampling. In total, nine indigenous villages were selected based on (1) the accessibility of these villages by land transport, (2) permission granted by the head of the villages, and (3) a large number of populations in each village. Each household in the selected villages was approached, and only one person was surveyed. If there was more than one eligible person available in a household, one participant was selected randomly. If participants refused to be interviewed or if the resident of the house was not present, it was regarded as a non-response. Inclusion criteria for the study were (1) residents aged 18 and above, (2) willing to provide verbal informed consent, (3) able to understand and comprehend Bahasa Malaysia, and (4) willing to provide a telephone number. The sample size was calculated using the Daniel (1999) sampling method equation: n = Z2* [p(1 - p)/d2]. Using a margin of error (d) of 0.05 (5%), with a 95% CI, chi-square value (Z) of 1.96, and 50% expected rate of dengue (p), the calculated sample size was 384. An extra 10% was added to the estimated sample size to account for potential missing values and invalid responses, and the minimum survey sample size was set to 422 participants. 2.2. Dengue Awareness Calendar The dengue awareness calendar was provided in the local language (Malaysian language or Bahasa Malaysia) for the convenience of the indigenous community. The content of the dengue prevention education in the calendar was developed and validated by a panel of experts consisting of physicians and academicians who specialized in epidemiology, infectious disease, and microbiology. The calendar was designed with five important key messages (1) the knowledge of dengue vectors, (2) Aedes mosquitoes characteristics, (3) dengue transmission, (4) correct measures to eliminate the mosquito breeding sites, and (5) proper prevention of mosquito bites . The calendar was made in a form that could be hung anywhere inside the house so that the participants could continuously see the messages displayed on the calendar. 2.3. Research Instrument The survey questionnaire of post-intervention consisted of five sections accessing (1) socio-demographic characteristics, (2) symptomatic dengue experience and environmental surroundings, (3) dengue-related knowledge, (4) health beliefs, and (5) self-reported prevention practices (File S1). Questions on knowledge about dengue transmission, symptoms, control, and treatment consisted of 6 sections (40 items), i. general information on dengue and the Aedes spp. mosquito (10 items), ii. transmission of dengue (9 items), iii. proper prevention of dengue (5 items), iv. signs and symptoms of dengue (14 items), and v. treatment and preventive measure (2 items). For each statement, the answer options were "yes", "no", or "don't know". The correct response was given a score of one, and incorrect or "don't know" scored zero. The six items where the correct response is false were reverse coded. The knowledge score was categorized based on the median split; therefore, in the pre-intervention, the knowledge score was categorized into two groups, low score (11-26) and high score (27-36); post-intervention, the low score (13-32) and high score (33-40). The differences between pre-intervention dengue knowledge scores were also calculated. The increment was categorized into 0-6 and 7-17, with a higher range implying a higher increment. The health belief model (HBM) has been applied extensively to study health beliefs that explain, predict, and influence behaviors . In this study, belief questions based on several constructs of the HBM were used to evaluate the participants' intentions and actions in dengue prevention, each ranging on a scale of 0-10. (i) Perceived severity refers to the seriousness of dengue; (ii) perceived susceptibility explains the vulnerability of being infected with dengue fever; (iii) perceived barriers assess the obstacles faced to prevent dengue (lack of community participation, lack of self-efficacy, and lack of preventive measures; (iv) cues to action evaluates the motivation to perform the dengue prevention practices (e.g., death, encouragement from a non-governmental organization (NGO), neighborhood infected with dengue, enlightenment from mass media, sudden fogging by authorities); (v) self-efficacy measures the confidence level of an individual engaging in protective practices. All items in the attitude question were summed to create a score with a higher score range indicating a higher level of positive attitude. post-differences were categorized into (1) post-intervention score is the same or less than the pre-intervention score (Post <= pre) is regarded as no increment and (2) post-intervention score is more than the pre-intervention (Post > pre) is regarded as having increment in positive attitude. Self-reported prevention practices of dengue consisted of 19 questions, i. prevention of mosquito breeding sites (9 items), ii. prevention of mosquito bites (7 items), and iii. prevention of dengue transmission (3 items). For each question, the response options were "never", "rarely", "sometimes", and "often", scored as 0, 1, 2, and 3, respectively. The possible total prevention scores ranged from 0 to 57 points, where higher scores implied a greater level of self-reported dengue prevention practices. The prevention score was categorized based on the median split; therefore, in the pre-intervention, the prevention score was categorized into two groups, (1) low prevention practices (score 10-25) and (2) high prevention practices (score 26-40); post-intervention, (1) the lower prevention practices (score 21-43) and (2) high prevention practices (score 44-57). The differences between pre-intervention dengue prevention practices scores were also calculated. The increment was categorized into a lower increment of prevention practices (score 0-17) and a higher increment of prevention practices (score 17-34). The items for knowledge, perceived severity, perceived susceptibility, perceived barriers, cues to action, self-efficacy, and self-reported practice questions had reliability (Cronbach's a) of 0.904, 0.817, 0.802, 0.885, 0.840, and 0.869, respectively. All the questions were developed in reference to previous literature by the research team and validated by a panel of experts that consisted of physicians and academicians. The questionnaire was developed in English and translated into Bahasa Malaysia. The translated questionnaires were reviewed by an independent translator, and back translation was conducted on the primary translated version. The questionnaire was pilot tested for clarity on a total of 52 indigenous people randomly selected from the study population. The pre-intervention was performed face-to-face by a team of trained enumerators. The enumerators were trained to reduce interviewer-related errors by ensuring that all respondents were asked identically worded questions without unscripted commentary that could bias responses. Participation was voluntary, and the participants provided written informed consent before the start of the interview. Upon completion of the pre-intervention, enumerators explained, distributed, and encouraged the study participants to hang the dengue calendar. The study participants were also informed on the post-intervention questionnaire survey after six months using telephone interviews. 2.4. Statistical Analysis Descriptive statistics were used to describe the proportion of knowledge, belief, and dengue prevention practices. The normality of total knowledge and self-reported prevention practices scores were checked using the Kolmogorov-Smirnov test. The comparison of scores post-intervention was performed using the Wilcoxon signed-rank test. Multivariable logistic regression for the outcome variable of self-reported dengue prevention practices score included demographic characteristics, experience, and environmental factors, increment in knowledge score, and differences in health belief. In the multivariable logistic regression analyses, all variables found to have a statistically significant association (two-tailed, p-value < 0.05) in the univariate analyses were entered into the model via the forced-entry method. The increase in prevention practices score was not normally distributed; therefore, multivariate logistic regression was used in the analysis. The dependent variable in multivariable logistic regression analysis was the increment in prevention practices scores that were categorized as a score of 17-34, representing 1, vs. a score of 0-16, representing 0. The independent variables were socio-demographic characteristics, increment in knowledge, and health beliefs scores. Odds ratios (OR), 95% confidence intervals (95%CI), and p-values were calculated for each independent variable. The model fit was assessed using the Hosmer-Lemeshow goodness of fit test. A p-value of less than 0.05 was considered statistically significant. All statistical analyses were performed with the Statistical Package for the Social Sciences Version 23.0 (SPSS; Chicago, IL, USA). 3. Results 3.1. Socio-Demographic Characteristics, Symptomatic Dengue Experience, and Surrounding Environment The demographic characteristics of the 609 participants are shown in Table 1. A majority of the participants were aged between 31 to 50 years old (44.7%). The study had a slightly higher representation of female participants (59.1%, n = 360), participants with secondary level education attainment (47.8%, n = 291), and with an average monthly household income of less than Malaysian Ringgit (MYR) 1000 (60.8%, n = 289). Less than half (n = 291, 47.8%) of the participants attained secondary-level education and were housewives (39.7%). By tribe, the majority were Temuan (58.9%, n = 359). In the self-reported survey among 609 indigenous participants, only 4.8% (n = 29) had dengue fever. 3.2. Dengue Knowledge Figure S2 shows the correct responses to knowledge items. In general, the proportion of correct responses increased from post-intervention. The majority had a good knowledge of the mosquitoes, and over 90% of participants provided correct responses. Other increases in the knowledge dimension included protective measures against dengue infection and increased percent scores of dengue transmissions through blood (38.4%), dengue hemorrhagic symptoms (27.1%), and blood in urine (26.0%), Aedes mosquito do not live in places with lots of plants (24.6%), and Aedes mosquito egg contains dengue virus (24.5%). The least increased knowledge score in post-intervention was pain in the eyes (3.3%) as one of the symptoms of dengue. 3.3. Health Beliefs In the health beliefs section, analysis of the perception of severity, susceptibility, barriers, cues to action, and self-efficacy are shown in Table 2. The pre-intervention revealed that the majority of the participants had a higher agreement score (6-10) for perceived severity (77.0%), perceived susceptibility (57.3%), perceived barriers (52.1%), and self-efficacy (85.9%). The proportion of the participants who had a higher agreement score (6-10) for all health belief items increased in the post-intervention assessment. The highest increment was observed for 'cues to action' (49.6% pre-intervention vs. 81.5% post-intervention). 3.4. Prevention Practices Figure S3 shows the self-reported dengue prevention practices by the participants in the study. Overall, increases in practice scores were observed for all items. The highest increment in the proportion of "often" practicing post-intervention was reported for preventing mosquitoes from biting a dengue patient (15.9% pre-intervention vs. 52.7% post-intervention), and the lowest was avoiding sexual intercourse with a spouse infected with dengue (5.4% pre-intervention vs. 15.3% post-intervention). 3.5. Overall Comparision of the Variables Table 3 summarizes the median and interquartile range (IQR) of dengue knowledge score, health beliefs towards dengue agreement score, and dengue prevention practices scores post-intervention. Overall, all variable scores showed an increase from post-intervention. The median score of dengue knowledge increased significantly (p < 0.001) from pre-intervention (26.0) to post-intervention (32.0). The median score of dengue prevention practices increased significantly (p < 0.001) from pre-intervention (24.0) to post-intervention (43.0). 3.6. Factors Associated with the Increment of Dengue Prevention Practices Score The multivariate logistic regression analysis (Table 1) indicates that the tribe 'Temuan' were significantly less likely to have a high increment in practice score (OR 0.444, 95%CI 0.254-0.777) compared to "other" tribes. Participants who are housewives were less likely (OR 0.535, 95%CI 0.289-0.950) to have a high increment in practices score compared to the "other" occupation category. Compared to participants with non-formal education, those with primary education level and secondary or above level education showed a high increment in practices score ((OR 2.627, 95%CI 1.338-5.160); OR 2.263, 95%CI 1.126-4.550, respectively). Participants with a higher dengue knowledge score (7-17) were more likely (OR 2.390, 95%CI 1.521-3.757) to have a high increment in practices score. Participants with no increment in perceived severity (OR 0.349 95%CI 1.521-3.757) and no increment in perceived susceptibility (OR 0.474 95%CI 0.286-0.785) were less likely to have a higher increment in practices score. 4. Discussion This study shows an overall increase in all knowledge, belief, and practices dimensions studied after awareness intervention using a calendar among the indigenous participants. For the indigenous community, multiple efforts have been in place to advance the lifestyle and well-being of the community ; however, there are still many efforts to be made to achieve better literacy about dengue prevention in the community. A previous study reported that skilled workers in the indigenous community who have higher educational levels reported higher knowledge scores compared to those who were unemployed, including housewives; this is in concordance with our current findings. A study in Yogyakarta, Indonesia, reported that housewives are an important target group for dengue prevention practices . In the indigenous communities, most housewives were less likely to receive high education; therefore, our findings suggest that awareness campaigns should place a higher emphasis on housewives. Furthermore, housewives spend most of their time at home, and they are also the prime person that carries out household control of mosquito breeding sites. In this study, the awareness of dengue among this indigenous community is considerably high in the knowledge of the dengue virus and the role of mosquitoes in the transmission of dengue, as similarly found in previous studies in Malaysia . However, a lower increment in the knowledge scores was observed in areas of preventive measures and signs of dengue hemorrhagic fever (DHF), suggesting a gap in the knowledge, findings which provide insights into areas of improvement for future community-based intervention programs. On a positive note, this study found an overall improvement in identifying DHF signs, perception of the severity of dengue, and prevention practices. Perception of severity played an important role in behavioral prevention, as it was evident that increased perception of severity may promote mosquito control practices in Zika virus prevention . Findings about the perception of severity and perception of susceptibility to dengue showed that, although many were concerned about the likelihood of dengue infection, less than half of the participants viewed themselves as at low risk of becoming infected with dengue. This was also reported in another study , where the study participants expressed fear about dengue; however, the perception of vulnerability was low. A study by Becker (1974) quoted that "one's intention to self-care is influenced by his or her perception of vulnerability and the severity of disease outcomes". This indicates the importance of dengue awareness to enhance the risk perception among the indigenous community, as high-risk perception translates into protective behaviors. People with a high perception of self-efficacy in taking measures to prevent dengue reported greater commitment to engaging in activities . A similar observation was reported among the rural population in Kuala Kangsar, where respondents believed that the responsibility of Aedes control lies within the community, and they would support the health authorities in any campaigns or activities that aimed to eradicate dengue . This indicates that dengue awareness is useful in enhancing dengue prevention practices. With regard to dengue practices, over half reported an increment in score from -intervention, which shows the dengue prevention education message in the calendar may have positively encouraged the study participants to enhance their engagement in mosquito prevention practices. The high level of prevention practices found in this study was related to daily practices for controlling mosquito nuisance, which was similarly reported in other studies . The majority of participants took action by clearing mosquito breeding sites, as reported in post-intervention, which was also similarly reported in Saudi Arabia . The improvement in prevention practices, such as proper disposal of household garbage, covering all water containers, and changing stored water to eliminate the mosquito-breeding site, was observed in this study. This shows that the message displayed on the dengue awareness measures to avoid mosquito breeding grounds in the calendar shows a positive influence on the community. It is also worth noting that in various studies, the prevention of mosquito bites usually involves the use of mosquito coils to repel the mosquitoes from biting, as also reported in India, Malaysia, the Philippines, and Pakistan . The reason for the common use of mosquito coils could be due to advertising in the media. Our study found an increase in the use of aerosol insecticides post-intervention. This is similar to a study conducted in Puerto Rico, where exposure to posters increased the indoor use of aerosol insecticides . However, it is important to note that preventive practices are subject to affordability; people in the Philippines and the rural and slum communities in India reportedly did not use any insecticidal sprays as they considered this prevention an expensive practice considering most of them have limited financial capabilities . Fewer respondents use mosquito repellent and wear bright-colored clothing to avoid mosquito bites in post-intervention, similar to a community-based study in Brazil . A simple practice such as a change in the color of the clothes can potentially help in reducing the risk of mosquito bites, as mosquitoes are attracted to darker areas and colors, which should be made known to the community. The present study also highlights the importance of educational interventions in many forms, including daily broadcasts, dengue campaigns, and group education, as reported in . A noteworthy finding from the multivariate analysis shows the importance of HBM constructs in dengue prevention. It was found that higher perceived severity and susceptibility to dengue were associated with higher dengue prevention practices. Thus, low severity and perceptions of risk may reduce motivation to take action against mosquito prevention. Therefore, interventions should enhance the perception of the serious threat of dengue, and adding testimonials from people with previous dengue exposure or lost family member due to dengue would be useful. Lastly, there is a significant positive association between an increment in knowledge score and an increase in mosquito prevention practices, which aligned with previous studies . This indicates that low knowledge of dengue transmission, prevention, and treatment leads to poorer prevention practices against dengue. There are a few limitations seen in this study. Firstly, the selection of indigenous villages was based on JAKOA approval that relied on accessibility by land transport and approval by the Head of the village; therefore, the findings may not be representative of all indigenous people in general. Secondly, the cross-sectional design used could not infer a causal relationship. Furthermore, other barriers in prevention practices are not able to be captured in qualitative study design. A future study using qualitative methods, such as focus group discussion, would be advantageous to gauge an in-depth understanding of prevention barriers in this community. Thirdly, the self-reporting data may be subjected to reporting bias towards socially desirable responses. 5. Conclusions The novelty of the study was shown by the improved knowledge, belief, and practices of the indigenous community after the distribution of the dengue awareness calendar, which is a new mode of awareness intervention delivery. The calendar's content encouraged indigenous communities to perform better prevention activities. The dengue awareness calendar is a good substitute for other promotional materials as people may likely display the calendar at home; hence, it may act as a constant reminder for them to perform mosquito prevention practices. Moreover, it is a relatively low cost, and the infographics in the calendar highlight steps of dengue prevention practices in an easy-to-understand way. The demographic disparities in prevention practices found in this study provide insights for intervention tailored to specific demographic groups in the indigenous communities. Future intervention programs should consider literacy-related barriers in their implementation. The findings provide important insights for policymakers to consider using this approach in future dengue prevention programs. Acknowledgments We acknowledge the funds provided by the Ministry of Higher Education, Malaysia for niche area research under the Higher Institution Centre of Excellence (HICoE) program (Project MO002-2019) and Skim Dana Program Flagship DSTIN (Project number: FP0514D0025-2) Development, Evaluation and Integration of innovative tools to reduce Dengue morbidity and mortality in the community by the Ministry of Science, Technology and Innovation Malaysia (MOSTI Malaysia). Supplementary Materials The following supporting information can be downloaded at: Figure S1: The Dengue Awareness Calendar (PDF); Figure S2: The percentage of correct responses of dengue knowledge items post-intervention (N = 609). (PDF); Figure S3: Proportion of 'Often practiced' for dengue prevention practices post-intervention (PDF); File S1: The post-survey questionnaire (PDF). Click here for additional data file. Author Contributions Conceptualization, L.P.W., S.A., H.Y.L., J.A.J., Y.L.; Methodology, L.P.W., H.Y.L., and A.R.; Validation, L.P.W., H.Y.L., J.A.J.; Formal analysis, L.P.W., H.Y.L., A.R.; Data curation, L.P.W., A.R.; Writing--original draft preparation, A.R.; Writing--review and editing: all authors; Funding acquisition, S.A., Y.L. 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 Medical Ethics Committee) of University Malaya Medical Centre (MEC Ref. No: 20161115-4602). Informed Consent Statement Written informed consent was obtained from all subjects involved in the study. Data Availability Statement Data sharing is not applicable to this article, as no data sets were generated or analyzed during the current study. All data given are available in the original articles. Conflicts of Interest The authors declare no conflict of interest. healthcare-11-00637-t001_Table 1 Table 1 Association between socio-demographic characteristics, increment in knowledge score, and differences in health beliefs with increment in prevention practices score (N = 609). Details n (%) Increment in Prevention Practices Score Multivariate Logistics Regression for 17-34 vs. 0-16 Socio-Demographic Data 0-16 (n = 311) 17-34 (n = 298) p-Value Age group (years old) 18-30 215 (35.3) 112 (52.1) 103 (47.9) 31-50 272 (44.7) 138 (50.7) 134 (49.3) 0.924 >50 122 (20.0) 61 (50.0) 61 (50.0) Gender Male 249 (40.9) 108 (43.4) 141 (56.6) 1.357 (0.790-2.329) Female 360 (59.1) 203 (56.4) 157 (43.6) 0.002 Reference Tribe (N = 615) Temuan 359 (58.9) 202 (56.3) 157 (43.7) 0.444 (0.254-0.777) * Mahmeri 127 (20.9) 53 (41.7) 74 (58.3) 0.007 0.608 (0.312-1.184) Others 123 (20.2) 56 (45.5) 67 (54.5) Reference Education No formal 82 (13.5) 58 (70.7) 24 (29.3) Reference Primary level 236 (38.8) 108 (45.8) 128 (54.2) 0.00 2.627 (1.338-5.160) * Secondary and above level 291 (47.8) 145 (49.8) 146 (50.2) 2.263 (1.126-4.550) * Occupation Manual worker 203 (33.3) 88 (43.3) 116 (56.7) 1.113 (0.663-1.870) Housewife 242 (39.7) 144 (59.5) 98 (40.5) 0.002 0.535 (0.289-0.950) * Others 164 (26.9) 79 (48.2) 85 (51.8) Reference Monthly income (MYR) [N = 475] <=1000 289 (60.8) 161 (55.7) 126 (44.3) 0.019 Reference >1000 186 (39.2) 83 (44.6) 103 (55.4) 1.142 (0.706-1.851) Symptomatic Dengue Experiences Yes 29 (4.8) 18 (62.1) 11 (37.9) 0.257 No 580 (95.2) 293 (50.5) 287 (49.5) Environmental Factors Density of plants or vegetation None/Low 162 (26.6) 89 (54.9) 73 (45.1) Moderate 231 (37.9) 118 (51.1) 113 (48.9) 0.426 A lot 216 (35.6) 104 (48.1) 112 (51.9) Abundance of mosquitoes in neighborhood None/Low 224 (36.8) 117 (52.2) 107 (47.8) Moderate 254 (41.7) 127 (50.0) 127 (50.0) 0.888 Severe 131 (21.5) 67 (51.1) 64 (48.9) Frequency of mosquito fogging None/Rarely 448 (73.6) 225 (50.2) 223 (49.8) Occasionally /Often 161 (26.4) 86 (53.4) 75 (46.6) 0.520 Increment in Knowledge Score 0-6 367 (60.1) 220 (59.9) 147 (40.1) 0.00 Reference 7-17 242 (39.9) 91 (37.6) 151 (62.4) 2.390 (1.521-3.757) *** Differences in Health Beliefs Perceived Severity Have increment 91 (14.9) 29 (31.9) 62 (68.1) 0.00 Reference No increment 518 (85.1) 282 (54.4) 236 (45.6) 0.349 (0.184-0.662) ** Perceived Susceptibility Have increment 114 (18.7) 44 (38.6) 70 (61.4) 0.004 Reference No increment 495 (81.3) 267 (53.9) 228 (46.1) 0.474 (0.286-0.785) * Perceived Barriers Have increment 119 (19.5) 53 (44.5) 66 (55.5) 0.125 No increment 490 (80.5) 258 (52.7) 232 (47.3) Cues to Action Have increment 205 (33.7) 88 (42.9) 117 (57.1) 0.005 Reference No increment 404 (66.3) 223 (55.2) 181 (44.8) 0.694 (0.448-1.076) Self-Efficacy Have increment 63 (10.3) 27 (42.9) 36 (57.1) 0.185 No increment 546 (89.7) 284 (52.0) 262 (48.0) * p < 0.05, ** p < 0.01, *** p < 0.001. Hosmer and Lemeshow test, c2(8) = 10.584, p = 0.226; Cox and Snell R2 = 0.153; Nagelkerke R2 = 0.205. OR, odds ratio; CI, confidence interval; -, not applicable in the multivariate analysis. healthcare-11-00637-t002_Table 2 Table 2 The frequency and percentage of agreement score responses on the health beliefs in post-intervention [N = 609]. Details Frequency, n (%) (D) Health Belief Model Pre-intervention Post-intervention Perceived Severity Seriousness of dengue 0-5 140 (23.0) 61 (10.0) 6-10 469 (77.0) 548 (90.0) Perceived Susceptibility Worried about the likelihood of getting infected with dengue 0-5 260 (42.7) 249 (40.9) 6-10 349 (57.3) 360 (59.1) Perceived Barriers Concern about the lack of community participation, lack of self-efficacy, and lack of preventive measure 0-5 292 (47.9) 243 (39.9) 6-10 317 (52.1) 366 (60.1) Cues to Action Motivation to prevent dengue, e.g., death, encouragement from NGO, neighborhood infected with dengue, enlightenment from mass media, sudden fogging by authorities 0-5 307 (50.4) 112 (18.4) 6-10 302 (49.6) 497 (81.5) Self-Efficacy Confidence level to prevent dengue 0-5 86 (14.1) 61 (10.0) 6-10 523 (85.9) 548 (90.0) healthcare-11-00637-t003_Table 3 Table 3 Wilcoxon Signed Rank test for dengue knowledge score, level of health beliefs, and prevention score in the post-intervention. Variable Pre-Test Median (IQR) Post-Test Median (IQR) Z-Value p-Value Knowledge score 26.0 [19.0-30.0] 32.0 [26.0-36.0] 21.20 p < 0.001 Health Beliefs Perceived severity 10.0 [8.0-10.0] 10.0 [9.0-0.0] 4.45 p < 0.001 Perceived susceptibility 6.0 [4.0-8.0] 6.0 [4.0-8.0] 0.28 0.779 Perceived barriers 6.0 [3.0-8.0] 6.0 [4.0-8.0] 1.29 0.199 Cues to action 5.0 [4.0-9.0] 6.0 [4.0-8.0] 3.48 p < 0.001 Self-efficacy 8.0 [6.0-10.0] 8.0 [7.0-10.0] 3.54 p < 0.001 Practices score 24.0 [21.0-29.0] 43.0 [36.0-48.0] 21.22 p < 0.001 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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PMC10000414 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050735 healthcare-11-00735 Article Quantitative Evaluation of Dental Students' Perceptions of the Roleplay-Video Teaching Modality in Clinical Courses of Dentistry: A Pilot Study Ganji Kiran Kumar 1*+ Nagarajappa Anil Kumar 2+ Sghaireen Mohammed G 3 Srivastava Kumar Chandan 2 Alam Mohammad Khursheed 1 Nashwan Shadi 4 Al-Qerem Ahmad 5 Khader Yousef 6 Leal-Costa Cesar Academic Editor Diaz Agea Jose Luis Academic Editor 1 Department of Preventive Dentistry, College of Dentistry, Jouf University, Sakaka 72388, Saudi Arabia 2 Department of Oral & Maxillofacial Surgery & Diagnostic Sciences, College of Dentistry, Jouf University, Sakaka 72388, Saudi Arabia 3 Department of Prosthetic Dentistry, Jouf University, Sakaka 72388, Saudi Arabia 4 Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72388, Saudi Arabia 5 Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa 13110, Jordan 6 Department of Public Health, Jordan University of Science & Technology, Irbid 22110, Jordan * Correspondence: [email protected] + These authors contributed equally to this work and both are the 1st authors. 02 3 2023 3 2023 11 5 73516 1 2023 25 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 the modern era of dentistry, role modeling/roleplaying is one of the most prevalent and recommended methods of dental education. Working on video production projects and using student-centred learning also help students create feelings of ownership and self-esteem. This study aimed to compare students' perceptions of roleplay videos among genders, different disciplines of dentistry, and different levels of dental students. This study included 180 fourth-year dental students registered in courses such as 'Introduction to Dental Practice' and 'Surgical management of oral and maxillofacial diseases', respectively, at the College of Dentistry at Jouf University. Four groups of recruited participants were pre-tested using a questionnaire about their clinical and communication skills. The students were tested again using the same questionnaire at the end of the workshop to evaluate improvements in their skills. The students were then assigned to create roleplay videos with respect to demonstrated skills related to all three disciplines (Periodontics, Oral Surgery, and Oral Radiology) in a week's time. Students' perceptions of the roleplay video assignments were collected through a questionnaire survey. The Kruskal-Wallis test was used to compare responses for each section of the questionnaire (p < 0.05). Improvements in problem-solving and project management skills during video production were reported by 90% of the participants. No significant difference (p > 0.05) in the mean scores of the responses was found with respect to the type of discipline involved in the process. There was a significant difference in the mean scores of the responses between male and female students (p < 0.05). The fourth year participants demonstrated increased mean scores and significantly higher (p < 0.05) mean scores than third-year participants. Students' perceptions of roleplay videos differed by gender and the level of the students, but not by the type of discipline. dental perception role play teaching strategies Deanship of Scientific Research at Jouf UniversityDSR2022-RG-0157 This work was funded by the Deanship of Scientific Research at Jouf University under Grant Number (DSR2022-RG-0157). pmc1. Introduction Skills are the capacity to apply information quickly and effectively . To be skilled in one's craft, one must have the ability to discern. Soft skills (SS) are beneficial in both personal and professional situations. Soft skills aid in the organisation, planning, and management of changes in growing dental practise . Personal values and interpersonal skills that define a person's ability to integrate within a certain framework, such as a project team or firm, are known as soft or social skills. Individual soft skill characteristics such as communication skills , critical thinking , teamwork , leadership , professionalism , life-long learning , and entrepreneurship have been emphasised in dental training programs and in the literature . Communication, critical thinking and problem-solving, teamwork, lifelong learning and information management, entrepreneurship, professional ethics and morals, and leadership are among the different soft skills identified by extensive research and expert consultation . Perreault described soft skills as an individual's personal traits, attributes, or level of commitment that distinguishes him from others with similar talent and expertise . The implementation of soft skills by active learning tools helps not only students, by encouraging them to practise abilities and ask questions, but also professors, by enabling them to ascertain students' comprehension and remediate critical points in near 'real time' . In dental education, role modeling/roleplaying is one of the most prevalent and recommended means of dental education . Students' prior role-playing experience may have an impact on how they approach this strategy . In medical education, role-play is extensively utilised as an educational tool for learning about communication because it allows for observation, rehearsal, and debate, as well as realistic roles and alignment of roles with other aspects of the curriculum. Yardley-Matwiejczuk defined it as activities in which individuals engage in 'as if' scenarios through simulated actions and conditions . Role-playing exercises assist children in becoming acquainted with 'real-world' events while fostering good attitudes and sentiments . It gives a secure space for students to express their own and sometimes unpopular views and beliefs, and the majority of students love these activities and become more motivated learners as a result. Khalifa et al. reported that student-generated videos were successful in teaching soft skills. Working on video production projects and using student-centred learning also helps students create feelings of ownership and self-esteem . Omar et al. studied undergraduate dentistry students' reactions to the use of student-generated videos to teach professionalism in Malaysia. According to the authors, the majority of students thought that the movies improved their collaboration and communication skills as well as their comprehension of the dentist's role in providing dental care. However, there is a lack of data on students' responses to the development of soft skills using roleplay in integrated dentistry courses. Therefore, this study aimed to evaluate students' perceptions of roleplay videos in integrated dental courses conducted over different levels of the Bachelor of Dental and Oral Surgery program. The study hypothesised that students' perception of roleplay videos does not differ among genders, different disciplines of dentistry, and different levels of dental students. 2. Materials and Methods 2.1. Study Design and Setting This cross-sectional study was conducted at the College of Dentistry affiliated with Jouf University, Sakaka, Kingdom of Saudi Arabia. This study was approved by the Local Committee for Bio-ethics (reference number 14-15-9/40). A trained researcher recruited the participants and provided information about the objectives of the study. The Bachelor of Oral and Dental Surgery (BDS) degree at Jouf University is a 5-year program in which the first and second years are preclinical and the third to fifth years are clinical. 2.2. Participants This study was carried out among the fourth-year undergraduate dental students registered for courses such as 'Introduction to Dental Practice' and 'Surgical Management of Oral and Maxillofacial Diseases' under the integrated Bachelor of Oral and Dental Surgery program. These courses were introductory undergraduate courses of the Bachelor of Dental and Oral Surgery program at their respective levels. Both courses focused on the basic foundations of knowledge, intellectual skills, and practical skills related to various disciplines. The sample size was estimated using the G power computing tool with a margin of error of 0.05 and a critical value of 1.96. Therefore, the sample size was set at 180, assuming a response rate of 60%. This study included data from two cohorts of the study population who were enrolled for the academic years 2020-2021 and 2021-2022, and the students were informed that participation was voluntary and anonymous. A Google form was used to distribute the questionnaires to 180 undergraduate students. Cover letters explaining the study design, consent form, and importance of the study were provided to reduce nonresponse bias. 2.3. Procedure In this study, students were assigned to create roleplay videos in both courses . Miller's pattern was employed with an emphasis on clinical competencies for the creation of roleplay video assignments: (1) knowledge, (2) observation, (3) simulation, and (4) experience (KOSE) . The 'knowledge' required for the assignment creation was imparted through didactic lectures, lab sessions, and workshops. A few roleplay videos were shown to the students to familiarise them with patient communication skills as well as ethical and professional issues of the dental team. This equipped them with the convenience of learning through 'observation'. Roleplay videos enabled learning through 'simulation'. Learning 'experience' was gathered during the creation of roleplay videos as a unit in the course environment. Following the brief orientation, students were assigned to create roleplay videos with their clinical skills involving models and patients in both courses: Introduction to Dental Practice and Surgical Management of Oral and Maxillofacial Diseases. Group dynamics were followed to create a total of four groups (two groups in the third year and two groups in the fourth year). Four video assignments were given to each of these groups of students enrolled in the Introduction to Dental Practice course. Before the students were given the video assignments, they were pre-tested using a questionnaire about their clinical skills and communication skills in the classrooms by the subject experts. Workshops were conducted for participating male and female students at the college premises. Later, they were briefed about the entire procedure through a workshop model with a demonstration of the skilled procedure that was accomplished at the student clinics by multiple faculties in groups. The students were tested again using the same questionnaire at the end of the workshop to evaluate improvements in their skills. The students were assigned to create roleplay videos with respect to all three disciplines (Periodontics, Oral Surgery, and Oral Radiology) about the demonstrated skill procedure in a week's time. Similar procedures were practised in all three courses for the creation of roleplay videos. These video assignments were aimed at instilling basic lifelong clinical and communication skills in various disciplines. The students were given common clinical scenarios and a stipulated time for the completion of the video assignments. The students shoot/created video assignments at the College of Dentistry's student clinics. Furthermore, the students worked collectively and processed the videos themselves to ensure originality, quality, and timeline. Following the submission of the roleplay videos by the students, the same were graded by experienced faculties of respective disciplines for the content, and feedback was given to each group using predetermined rubrics. 2.4. Study Instrument The students' responses on the creation of the roleplay video assignments were collected through a questionnaire survey shared via Google Forms . The study instrument consisted of six sections: (1) effectiveness of instructional videos, (2) general satisfaction with instructional videos, (3) open-ended questions, and (4) how satisfied were you with the introduction of educational videos in the course? A five-point Likert-Scale was used for the first two items (strongly agree, agree, neutral, disagree, strongly disagree). Similarly, a five-point Likert scale was used to score the items (poor to excellent). The questionnaire distributed to the participants was developed, discussed, and reviewed with co-investigators for its relevance to the course and regional cultural adaptation, as described by Artino et al. . The questionnaire was pre-tested for its validity and reliability by expert evaluation before distribution to the study participants. 2.5. Study Variables Participants' responses to the questionnaire were used as the outcome data. Gender, year of study, and subject discipline were selected as associated factors in the present study. Data on the sex, year of study, and subject discipline of participants were collected using a self-report survey. 2.6. Statistical Analysis For each study variable, the mean, standard deviation, frequency, and percentage were calculated. The mean score was calculated by averaging the options agree (3), neutral (2), and disagree (1) for each item. The Brunner Munzel test was administered to compare male and female responses and students with different courses. We used the Kruskal-Wallis test to compare the responses for each section of the questionnaire. p-values of 0.05 were considered statistically significant for statistical analysis using SPSS version 22 (IBM, Armonk, NY, USA). 3. Results In total, the survey involved 180 students over two cohorts ( fourth-years) of a Bachelor of Oral and Dental Surgery program. In general, most students perceived the advantages of role-playing as an effective teaching method for improving their dentistry skills. As part of the 'student preparation for roleplay production' project, most students reported that preparing the scripts helped them grasp the written material in the lesson (90%) and gain confidence in demonstrating the skill (89%). Ninety percent of the participants reported an improvement in their problem-solving and project-management skills during video production . A comparison of participant feedback responses across the three disciplines revealed no significant difference (p > 0.05) in responses to all items, indicating no differences in the rating response between disciplines. Roleplay, as a teaching tool for video production and soft skill development, was unaffected by the type of discipline, as all three disciplines were rated highly by the participants (Table 1). Table 2 compares the responses of participants by gender. The mean scores for all questionnaire items were higher for female students than for male students, indicating a more positive outlook. There was a significant difference in the mean scores for these seven items between the male and female students (p < 0.05). Table 3 presents comparisons of the participants' responses regarding the course level ( fourth-year). The participants at the fourth-year level demonstrated increased mean scores and significantly higher (p < 0.05) mean scores than participants at the third-year level for all seven items (p < 0.05). 4. Discussion Simulations such as roleplaying are used to teach knowledge, attitudes, and skills in a variety of fields. Involving students in the learning process makes this teaching method enjoyable and active . Roleplay has also been found to improve students' critical thinking and attention span compared to lectures, demonstrations, tutorials, and field studies . Medical educators utilise roleplays to teach students communication skills. Through roleplaying, students become familiar with roles/characters, discuss them with others, and practise them, aligning the topics with the course learning outcomes. Introducing students to 'real world' scenarios through role play helps them gain positive attitudes and feelings. Furthermore, it provides students with an opportunity to express themselves and learn unpopular attitudes and opinions, and the majority of students find these activities stimulating and inspiring. The guidelines mentioned in Mogra et al. are based on Pendleton's rules, which are considered ways to ensure that feedback is constructive rather than destructive . In addition to improving cognitive abilities and psychomotor skills, roleplay assignments also have positive effects on the learning outcomes of dental programs. Research has shown that student-generated videos have positive effects on learning . The present study compared students' perceptions of roleplay videos implemented in three different courses across two levels of BDS students. Throughout the study period, the team of instructors, methods of delivery for classroom instruction, themes of roleplay assignments, and measuring instruments remained the same. The conditions needed for appropriate comparisons among the three disciplines in the study, namely periodontology, Oral Surgery, and Oral Radiology. Al-Khalifa et al. showed that video assignments should be a part of professional courses in dentistry to improve students' communication skills with their colleagues and patients . However, no studies have evaluated the efficacy of roleplay teaching methodologies in the clinical course of dentistry. Therefore, the current study was the first to evaluate participants' perceptions of roleplay teaching strategies for individual disciplines in an integrated dental curriculum course. The findings of the study showed that most students recognised the importance of roleplay videos by the end of the study. Students' perceptions of roleplay video teaching modes were found to vary by gender and student level, with female students expressing highly favourable views of this teaching modality. The students' perceptions of roleplay videos in dentistry did not differ across disciplines. The findings of the study showed that participants' perception of roleplay was very high with respect to Periodontics, Oral Surgery, and Oral Radiology. The sole purpose of choosing these three disciplines was based on the concept that they are horizontally integrated within an introductory course for third-year and fourth-year BDS programs at the College of Dentistry, Jouf University. Upon evaluation, there was no significant difference in the participants' questionnaire response scores for these three disciplines, indicating that the roleplay teaching methodology was beneficial in all respects. Nestel and Tierney reported that students learned communication skills through roleplay . Manzoor et al. found that 88.9% of medical students were satisfied with the communication skills acquired through roleplaying. These findings are in agreement with a recent report by Manzoor et al. . As a result, students who were exposed to a new course viewed roleplaying video assignments as a powerful learning tool because roleplaying can enrich learning experiences through emotional engagement, movements, and variations. The current study found that female students preferred roleplay as a teaching method for allied clinical courses, which was confirmed by a higher rating than by male participants. Such gender differences are due to different preferences for learning styles among dental students. Numerous studies have indicated that female students learn better through kinaesthetic approaches . Similarly, a greater proportion of students with high academic performance reflected through gross point average (GPA) scores demonstrated a preference for a kinaesthetic learning style than those with low academic performance . Surprisingly, in our study, females with kinaesthetic learning style preferences also had higher GPA scores. Kinaesthetic learners learn through practise, experimentation, and experience and prefer learning via roleplays, field trips, and case studies . With respect to participants' perception level ( fourth-year) towards roleplay, it was estimated that fourth-year students had a more positive view of the importance of roleplay in understanding textbook information more deeply. This is in contrast to a study conducted by Al-Khalifa et al. , which demonstrated that significantly higher proportions of third-year students than fourth-year students thought that roleplay improved the clarity of communication, provoked critical thinking, increased their attention span, and was a feasible method of learning. Such variation in perception is related to the type of course in which the roleplay was implemented. As noted in the current study, the fourth-year students understand the importance of roleplay in clinical courses, and they also realised the key aspects of roleplay through learning experiences after getting involved in them. In the current study, the students' ability to apply their content knowledge to new clinical situations was improved by modelling application skills, as shown in the videos prepared by the students. These findings are in accordance with the reports of Miller et al. and Kavadella et al. . The proceedings of the study could illuminate the need for advanced care planning to enhance the learning experience of dental students in an integrated dental curriculum, as suggested by Blomberg et al. . Role-play is indeed a highly effective method of teaching communication skills, but given time limitations on the part of the faculty, it sometimes becomes difficult to practise many practical scenarios. We targeted and addressed a major lapse of such situations in our undergraduate training and strongly agree with the fact that it is the need of the hour to train dental undergraduates to encourage imagination, creativity, and a sense of active learning strategies among peers. We also believe that good communication skills with problem-solving skills employed through role play need to be taught to dental undergraduates to inculcate in them greater clinical competence and that these skills can never be taught through didactic lectures. Our belief is that video-assisted learning would overcome these limitations and would enable students to be exposed to a variety of scenarios via roleplay with limited faculty and fewer time constraints. The current study encountered some limitations while teaching through roleplay methods, such as the topic of roleplay varying for different levels of participants and time management. With roleplay activities, students deviate towards directed self-learning instead of self-directed learning, which would lead the students to become involved in information that is scientifically not evident. Hence, peer involvement is mandatory for the successful completion of roleplay activities. 5. Conclusions Clinical courses in dentistry should include video assignments as part of the curriculum to improve students' communication skills and professional behaviours with their colleagues and patients. With the aid of technology, dental students can develop problem-solving skills whenever they roleplay together as a group. Author Contributions Conceptualization, K.K.G. and A.K.N.; methodology, M.G.S., M.K.A., K.C.S. and S.N.; formal analysis, Y.K. and A.A.-Q.; investigation, K.K.G. and M.G.S.; writing--original draft preparation, A.K.N., K.K.G. and K.C.S.; writing--review and editing, A.A.-Q., S.N. and Y.K.; funding acquisition, M.G.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 local committee for bioethics, Jouf University-wide reference number 14-15-9/40, dated 20 May 2019. Informed Consent Statement Informed consent was obtained from all the subjects involved in the study. Data Availability Statement Data will be made available upon request to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Responses of the participants towards roleplay soft skills in Oral Surgery discipline. Figure 2 Responses of the participants towards roleplay soft skills in Periodontics discipline. Figure 3 Responses of the participants towards roleplay soft skills in Radiology discipline. healthcare-11-00735-t001_Table 1 Table 1 Comparison of feedback responses for roleplay videos implemented in various disciplines of the BDS course. Questionnaire Periodontics Discipline Oral Surgery Discipline Oral Radiology Discipline p Value Sections Sub-Section Mean +- SD Mean +-SD Mean +- SD Preparation of students for video production a. This roleplay video gave me new understanding that I didn't have after reading the XYZ written material for this lesson. 2.75 +- 0.60 2.73 +- 0.48 2.68 +- 0.63 0.094 b. This roleplay video helped me to better understand the textbook information. 2.86 +- 0.66 2.76 +- 0.51 2.84 +- 0.66 0.084 c. This roleplay gave me more confidence in my ability to XYZ. 2.83 +- 0.74 2.76 +- 0.72 2.79 +- 0.71 0.076 Skill development achieved from roleplay videos a. My language and communication skills improved as a result of participation in video production 2.84 +- 0.48 2.81 +- 0.51 2.79 +- 0.43 0.083 b. My problem-solving skills were improved by participating in video generation 2.76 +- 0.60 2.84 +- 0.63 2.82 +- 0.66 0.072 Overall learning experience from roleplay videos a. Overall I was satisfied with these roleplay videos. 2.86 +- 0.72 2.83 +- 0.66 2.89 +- 0.69 0.085 b. Overall I feel I was able to learn the information from this roleplay videos as well as I would have in a face-to-face class presentation. 2.81 +- 0.77 2.78 +- 0.74 2.80 +- 0.72 0.094 healthcare-11-00735-t002_Table 2 Table 2 Comparison of feedback responses for roleplay videos in relation to gender of the participants. Questionnaire Male Female p Value Sections Sub-Sections Mean +- SD Mean +- SD Preparation of students for video production a. This roleplay video gave me new understanding that I didn't have after reading the XYZ written material for this lesson. 2.79 +- 0.40 2.95 +- 0.58 0.038 * b. This roleplay video helped me to better understand the textbook information. 2.76 +- 0.46 2.85 +- 0.71 0.005 * c. This roleplay gave me more confidence in my ability to XYZ. 2.77 +- 0.61 2.94 +- 0.63 0.021 * Skill development achieved from roleplay videos a. My language and communication skills improved as a result of participation in video production 2.83 +- 0.63 2.91 +- 0.71 0.015 * b. My problem-solving skills were improved by participating in video generation 2.64 +- 0.83 2.85 +- 0.74 0.005 * Overall learning experience from roleplay videos a. Overall I was satisfied with these roleplay videos. 2.85 +- 0.68 2.90 +- 0.74 0.003 * b. Overall I feel I was able to learn the information from this roleplay videos as well as I would have in a face-to-face class presentation. 2.84 +- 0.69 2.92 +- 0.59 0.000 * * statistically significant (p < 0.05). healthcare-11-00735-t003_Table 3 Table 3 Comparison of feedback responses for roleplay videos in relation to third-year and fourth-year levels of BDS students. Questionnaire 3rd-Year 4th-Year p Value Sections Sub-Sections Mean +- SD Mean +- SD Preparation of students for video production a. This roleplay video gave me new understanding that I didn't have after reading the XYZ written material for this lesson. 2.72 +- 0.50 2.89 +- 0.68 0.016 * b. This roleplay video helped me to better understand the textbook information. 2.83 +- 0.86 2.95 +- 0.71 0.019 * c. This roleplay gave me more confidence in my ability to XYZ. 2.71 +- 0.44 2.86 +- 0.56 0.008 * Skill development achieved from roleplay videos a. My language and communication skills improved as a result of participation in video production 2.82 +- 0.61 2.90 +- 0.39 0.015 * b. My problem-solving skills were improved by participating in video generation 2.66 +- 0.70 2.84 +- 0.59 0.005 * Overall learning experience from roleplay videos a. Overall I was satisfied with these roleplay videos. 2.81 +- 0.52 2.93 +- 0.80 0.002 * b. Overall I feel I was able to learn the information from this roleplay videos as well as I would have in a face-to-face class presentation. 2.79 +- 0.69 2.89 +- 0.59 0.000 * * statistically significant (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. Subramanian R. 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PMC10000415 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050880 diagnostics-13-00880 Communication Clinical Evaluation of an Antigen Home Test Using Surface-Enhanced Raman Spectroscopy and Stacking Pad for SARS-CoV-2 Screening with Nasal and Salivary Swab Samples Ryu Hyejin 1 Oh Eunha 2 Cha Kyungjae 3 Kim Kina 1 Kim Soohyun 1 Minn Dohsik 12* Baraniak Anna Academic Editor 1 Department of Diagnostic Immunology, Seegene Medical Foundation, Seoul 04805, Republic of Korea 2 Immune Research Institute, Seegene Medical Foundation, Seoul 04805, Republic of Korea 3 SG Medical, Inc., Seoul 05548, Republic of Korea * Correspondence: [email protected]; Tel.: +82-2-2218-9111 24 2 2023 3 2023 13 5 88004 1 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 ). This prospective study aimed to evaluate the performance of the InstaView COVID-19 (coronavirus diseases 2019) Antigen Home Test (InstaView AHT) which detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens. In this test kit, surface-enhanced Raman spectroscopy was used, a stacking pad was inserted, and nasal swab and salivary swab samples were used simultaneously to improve performance. The clinical performance of the InstaView AHT was compared to that of RT-PCR using nasopharyngeal samples. The participants without any prior training were recruited and performed the sample collection, testing, and interpretation of the results by themselves. Of the 91 PCR-positive patients, 85 had positive InstaView AHT results. The sensitivity and specificity of the InstaView AHT were 93.4% (95% confidence interval [CI]: 86.2-97.5) and 99.4% (95% CI: 98.2-99.9). The sensitivity of the InstaView AHT was above 90% for all samples obtained from patients with Ct <= 20, 20 < Ct <= 25, and 25 < Ct <= 30 (100%, 95.1%, and 92.0%, respectively). The InstaView AHT can be used as an alternative to RT-PCR testing because of its relatively high sensitivity and specificity, especially when SARS-CoV-2 prevalence is high, and the availability of RT-PCR testing is limited. SARS-CoV-2 antigen test rapid test COVID-19 diagnostics self-testing surface-enhanced Raman spectroscopy This research received no external funding. pmc1. Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in 2019 , and its spread has continued despite ongoing efforts to prevent transmission . The standard method for diagnosing coronavirus disease 2019 (COVID-19) is to detect the presence of viral RNA by reverse transcription polymerase chain reaction (RT-PCR) using nasopharyngeal swabs (NPS) . However, there are disadvantages to this testing method, such as restrictions on sample collection, technical complexity, long testing time, and high cost . In contrast to the RT-PCR method, the rapid antigen test (RAT) is widely used because it does not require complicated techniques or large equipment and is convenient, rapid, and inexpensive . In particular, the rapid antigen home test (RAHT) can be performed anywhere a sample can be collected for testing and reading; moreover, it does not require visits to hospitals or clinics and is convenient to use. However, RAT for SARS-CoV-2 diagnosis is generally known to be less sensitive than RT-PCR . In addition, RAHT has the potential for inaccurate performance during self-sampling . NPS, nasal swabs, oropharyngeal swabs, saliva, and sputum samples can be used to test for SARS-CoV-2 . NPS samples can cause pain and nasal congestion owing to the invasive specimen collection method, which causes difficulties in specimen collection, particularly in patients with coagulopathy or children . In comparison, nasal swab, saliva, and sputum samples are less invasive and convenient to collect because the expertise of professional medical staff is not required . In addition, in a study comparing test results, NPS, nasal swabs from the front of the nasal cavity, and saliva samples showed similar sensitivities . It has also been reported that sensitivity and specificity were high in samples collected from the nasal cavity and saliva at the same time, rather than in samples collected from the nasal cavity alone at the onset of the disease . The InstaView COVID-19 Antigen Home Test (InstaView AHT; SG Medical, Seoul, Republic of Korea) used in this study was designed to increase sensitivity and specificity. First, nasal and salivary swab samples were used simultaneously during the sampling step. Then, gold nanoparticle complexes, using surface-enhanced Raman spectroscopy (SERS) technology, were used for the conjugate pad and a stacking pad section was inserted, which was different from existing products. This prospective study aimed to compare the results of the InstaView AHT, which detects SARS-CoV-2 antigens using nasal and salivary swab samples self-collected, with the RT-PCR results of NPS samples collected by experts at the same time. 2. Materials and Methods 2.1. Patients and Specimens Participants without any prior training were prospectively recruited to proceed on their own, from sample collection to testing, and interpretation of their results under minimal supervision by medical professionals. As for the positive patients, 99 volunteers were recruited from among those admitted to the Taereung Residential Treatment Center in Seoul. In the PCR retest before admission, five were negative and excluded; thus, 94 individuals were tested. The negative control group was comprised of 485 individuals who visited the Seegene Medical Foundation for a pre-departure examination. A case report was prepared for all samples and included their sex, age, date of symptom onset, date of sample collection, date of confirmation, and control reagent results. 2.2. Antigen Tests InstaView AHT is an in vitro diagnostic medical device that tests for the presence of the coronavirus nucleocapsid protein (NP) antigen in nasal and salivary swab samples by immunochromatographic assay (ICA). 40 nm gold nanospheres were prepared according to the seed-growth nanoparticle synthesis method developed by Neus . The synthesized gold nanoparticles were characterized by UV-visible spectroscopy and transmission electron microscopy (TEM), and the maximum absorption wavelength was 527 nm. It consists of a nitrocellulose membrane coated with a control line (C) and test line (T), a conjugate pad that can bind to the SARS-CoV-2 antigen in the sample, and a stacking pad. The control line is coated with goat anti-mouse antibodies, and the test line is coated with antibodies specific to the SARS-CoV-2 antigen. The conjugate pad contains gold nanoparticles coated with antibodies specific to the SARS-CoV-2 antigen. The sample is placed in the extraction solution, sufficiently mixed, and dropped into the sample inlet of the test device. If the sample contains the SARS-CoV-2 antigens, the antigens react with the gold nanoparticles to form nanoparticle complexes by SERS . It is designed to extend the antigen-antibody reaction time by adding a stacking pad between the conjugation pad and membrane . The antigen-antibody complexes react with the antibodies coated on the test line to form sandwich immune complexes, resulting in a red line. All participants conducted the test according to the instructions after fully familiarizing themselves with the user manual and quick guide provided by the InstaView AHT product and the quick guide video provided in QR format. Participants first collected a nasal swab specimen. A sterile cotton swab was inserted up to about 1.5 cm into one nostril and turned along the wall of the nostril more than 5 times, and samples were also collected from the opposite nose with the same sterile swab. Saliva samples were collected by placing another sterile swab under the tongue in the mouth and rolling it at least 5 times to allow sufficient saliva to be absorbed into the sterile swab. The swabs collected from the nasal cavity and saliva were placed in the sample extraction solution for elution, and the results were visually confirmed 15 min after instillation into the sample inlet of the test device. If both the control line (C) and test line (T) appeared, the COVID-19 virus antigens were found in the sample, and the sample was judged to be positive for possible infection with COVID-19. If only the control line (C) appeared, no COVID-19 virus antigen was found in the sample, and it was judged as negative. If control line (C) did not appear, it was judged to be an invalid result . The LOD of InstaView AHT provided by the manufacturer was 5.938 x 104 TCID50/mL, and the Ct value of the RdRP gene was 27.16. 2.3. Standard Reference RT-PCR All participants underwent RT-PCR testing to detect the presence of the SARS-CoV-2 RNA-dependent RNA polymerase gene (RdRp) at the same time as the InstaView AHT. All specimens were collected using nasopharyngeal swabs, transported to the laboratory in a virus transport medium (VTM), and stored at 4 degC before and after testing, according to the guidelines reported by Hong et al. . The AllplexTM 2019-nCoV Assay (Seegene, Seoul, Republic of Korea) was used according to the manufacturer's instructions and the expert response from the Korea Centers for Disease Control and Prevention (COVID-19 Diagnosis Test Management Committee) . The result was considered positive when the Ct (cycle threshold) value of genes was <33.5. The laboratory medicine specialist judged the results near the reference value with low viral titers. 2.4. Statistical Analysis Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were evaluated based on the positive and negative results of the InstaView AHT and RT-PCR test methods and the statistical analysis was used by the chi-squared test. The differences in InstaView AHT sensitivity according to the period of the symptom onset date were evaluated using Fisher's exact test. MedCalc(r) Statistical Software version 20.2 (MedCalc Software Ltd., Ostend, Belgium) was used for all statistical analyses. Statistical significance was set at p < 0.001. 3. Results 3.1. Participants From February to April 2022, 576 people were enrolled in the study at the Taereung Residential Treatment Center and Seegene Medical Foundation Departure Test Center. The RT-PCR results were 91 positive and 485 negative. The average age was 36.9 years (standard deviation 12.5), and 52.6% of the patients were women. The mean symptom onset in all RT-PCR-positive patients was 3.0 days, and the standard deviation was 1.5 days. 3.2. Comparison between InstaView AHT and RT-PCR Of the 91 RT-PCR-positive patients, 85 had positive InstaView AHT results, and 482 of the 485 RT-PCR negative controls had negative InstaView AHT results (Table 1). The measured sensitivity, specificity, PPV, and NPV of InstaView AHT were 93.4% (95% confidence interval [CI]: 86.2-97.5), 99.4% (95% CI: 98.2-99.9), 96.6% (95% CI: 90.2-98.8), and 98.8% (95% CI: 97.4-99.3), respectively. The true negative and false positive rates of the InstaView AHT test measured in PCR-negative participants were 99.4% and 0.6%, respectively. 3.3. Comparison of Ct Values and Days of Symptoms of InstaView AHT Results The sensitivity of the InstaView AHT was evaluated by dividing the Ct values of RT-PCR positive results into four groups: <=20, 20 < Ct <= 25, 25 < Ct <= 30, and 30 < Ct. The sensitivity of InstaView AHT was >90% for all samples obtained from patients with Ct <= 20, 20 < Ct <= 25, and 25 < Ct <= 30, however, for patients with a Ct > 30, the sensitivity of InstaView AHT decreased to 75.0% (6/8) (Table 2). The days of symptom onset in all RT-PCR-positive patients were within 5 days. There was no difference in the sensitivity of the InstaView AHT test according to the period from symptom onset to diagnosis (93.6% on days 1-2 and 93.2% on days 3-5, respectively). This suggests that 5 days of symptom onset is the optimal time to perform antigen testing (Table 2). 4. Discussion In this study, 91 RT-PCR-positive and 485 RT-PCR-negative participants were prospectively collected from nasal and salivary samples to interpret the results. We evaluated the clinical performance of the InstaView AHT with the RT-PCR tests of NPS samples collected by experts. The clinical sensitivity and specificity of the InstaView AHT based on the RT-PCR test results were 93.4% (95% CI: 86.2-97.5) and 99.4% (95% CI: 98.2-99.9). These results met both the WHO criteria , which required a sensitivity of >80% and a specificity of 97-100%, and the Korean Ministry of Food and Drug Safety (MFDS) approval review criteria , which recommended a clinical sensitivity of >=80% (with a lower limit of confidence interval of >=70%), and a clinical specificity of >=95% (with a lower limit of confidence interval of >=90%). Comparing the performance of RAHT and RT-PCR in previously reported studies , the sensitivity of RAHT ranged from 49-96%, and the specificity ranged from 82-100%. There was no significant difference in the diagnostic performance between the collected samples, and our study showed similar results. When the results were further subdivided according to the Ct value, they were found to be highly reliable for high viral loads, however, they were less sensitive when the viral load was low (Ct > 30). Shin et al. reported a sensitivity of 73.33% at Ct > 25, and Kim et al. reported a sensitivity of 63.6% at Ct > 30. In other previous studies, the sensitivity reached 98.4% when the viral load was high (<20 Ct or >=107 RNA copies/mL). However, as the viral load decreased, it was reported that the sensitivity decreased steadily to 36.7% at 104 to <105 RNA copies/mL and 7.5% at <104 RNA copies/mL . This can be considered a limitation of the RAT. In this study, a sensitivity of 87.9% at Ct > 25 and 75.0% at Ct > 30 was achieved with better performance than that in previous studies using the following tools: first, the InstaView AHT used two samples, nasal swab, and salivary swab samples at the same time, and it is considered a test method that could increase the detection rate more than existing tests using a single sample. In a previous study comparing sensitivity between samples, Lindner et al. reported positive and negative agreement rates of 90.6% and 99.2%, respectively, between antigen tests of self-collected nasal samples and NPS samples. Hanson et al. reported positive and negative concordance rates of 93.8% and 97.8%, respectively, in tests using NPS and saliva samples, suggesting that using samples taken simultaneously from multiple anatomical sites could slightly increase the detection rate of SARS-CoV-2. Second, in order to improve the low sensitivity, the InstaView AHT has the function of forming a nanoparticle complex when inserting a stacking pad. Gold nanoparticles are the most commonly used detection tool in lateral flow assays. The nanoparticles used in this device are gold nanoparticle complexes. The complex was formed by malachite green isothiocyanate (MGITC). These particles produce a colored readout that requires no development process for visualization and improves the sensitivity owing to the large number of nanoparticles per unit area . This kit was attached in the following order: sample pad, conjugate pad, stacking pad, nitrocellulose membrane, and absorbent pad. Unlike other products, a stacking pad is designed to improve sensitivity by increasing the reaction time between the SARS-CoV-2 antigens present on the conjugate pad and SARS-CoV-2 antibodies conjugated with gold nanoparticle complexes . The stacking pad increases the reaction efficiency by increasing the reaction time between nanoparticles and samples. Clustered nanoparticles can increase sensitivity by giving the same effect as multiple nanoparticles reacting to one antigen. In addition, Raman signals are greatly amplified by "hot spots" generated between nanoparticles. Thus, it shows better performance than the other products by using two samples, SERS, and a stacking pad. This study has some limitations. First, the average age of the participants was low, and it did not reflect the entire population distribution. Second, the detection targets of the InstaView AHT and RT-PCR are not the same as nucleocapsid and RdRp, respectively. Third, the samples of InstaView AHT and RT-PCR test were different. Fourth, as we could not find individuals 5 days after symptom onset, we could not obtain sensitivity in patients with long-term symptoms, as this was a prospective study that included patients who were hospitalized immediately after RT-PCR positivity. However, while most previous studies were retrospective studies using archived samples, this study was a prospective study, therefore, the data reflected are believed to be more realistic. 5. Conclusions In conclusion, the InstaView AHT showed excellent performance as a kit for detecting SARS-CoV-2 antigens. Therefore, when RT-PCR testing is limited, COVID-19 results can be easily and quickly confirmed through self-collection. Author Contributions Conceptualization, D.M.; methodology, D.M.; validation, K.K. and S.K.; formal analysis, K.C.; investigation, E.O.; data curation, E.O., K.K. and S.K.; writing--original draft preparation, H.R.; writing--review and editing, D.M.; visualization, K.C.; supervision, D.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was conducted in compliance with ethical regulations of the Declaration of Helsinki. The study has the approval of the Institutional Review Board (IRB) of Seoul Medical Center (2022-02-005) for the inclusion of COVID-19 positive patients admitted to the Taereung Residential Treatment Center (Seoul, Republic of Korea). The negative control group was approved by the IRB of Seegene Medical Foundation (SMF) (SMF-IRB-2021-025). Informed Consent Statement 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 (A). Schematic representation of gold nanoparticle and detection antibodies. (B). Gold nanoparticle complex using surface-enhanced Raman spectroscopy. These particles form clusters, allowing more sensitive detection even in the presence of fewer antigens. Figure 2 The InstaView COVID-19 Antigen Home Test device is attached in order of sample pad, conjugate pad, stacking pad, nitrocellulose membrane, and absorbent pad. The stacking pad exists between the conjugate pad and the membrane, and the sensitivity can be improved by increasing the reaction time between anti-SARS-CoV-2 antibodies conjugated gold nanoparticles present in the conjugate pad and the SARS-CoV-2 antigens. Figure 3 Interpretation of the test results of the InstaView COVID-19 Antigen Home Test. diagnostics-13-00880-t001_Table 1 Table 1 Comparison of InstaView COVID-19 Antigen Home Test and RT-PCR results. RT-PCR Total p-Value * Positive Negative InstaView COVID-19 Home Test Positive 85 3 88 <0.0001 Negative 6 482 488 Total 91 485 576 * Chi-squared test. diagnostics-13-00880-t002_Table 2 Table 2 Clinical performance analysis of InstaView COVID-19 Antigen Home Test according to Ct values and days of symptom onset. Ct Values InstaView COVID-19 Antigen Home Test Sensitivity (%) (95% CI) Positive Negative Overall 85 6 93.4 (86.2-97.5) RT-PCR Ct values Ct <= 20 17 0 100 (80.5-100) 20 < Ct <= 25 39 2 95.1 (83.5-99.4) 25 < Ct <= 30 23 2 92.0 (74.0-99.0) 30 < Ct 6 2 75.0 (34.9-96.8) Days after symptom onset 1-2 44 3 93.6 (82.5-98.7) 3-5 41 3 93.2 (81.3-98.6) Abbreviations: Ct, cycle threshold; CI, confidence interval. 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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PMC10000416 | Clinically relevant bone metastases are a major cause of morbidity and mortality for prostate cancer patients. Distinct phenotypes are described: osteoblastic, the more common osteolytic and mixed. A molecular classification has been also proposed. Bone metastases start with the tropism of cancer cells to the bone through different multi-step tumor-host interactions, as described by the "metastatic cascade" model. Understanding these mechanisms, although far from being fully elucidated, could offer several potential targets for prevention and therapy. Moreover, the prognosis of patients is markedly influenced by skeletal-related events. They can be correlated not only with bone metastases, but also with "bad" bone health. There is a close correlation between osteoporosis--a skeletal disorder with decreased bone mass and qualitative alterations--and prostate cancer, in particular when treated with androgen deprivation therapy, a milestone in its treatment. Systemic treatments for prostate cancer, especially with the newest options, have improved the survival and quality of life of patients with respect to skeletal-related events; however, all patients should be evaluated for "bone health" and osteoporotic risk, both in the presence and in the absence of bone metastases. Treatment with bone-targeted therapies should be evaluated even in the absence of bone metastases, as described in special guidelines and according to a multidisciplinary evaluation. bone metastasis bone health prostate cancer bone health specialist bone-targeted therapies This research received no external funding. pmc1. Introduction Prostate cancer (PC) is the second most common cancer in men worldwide and more than half of PC occurs in men over the age of 70 years . The propensity of PC cells to seed in the skeleton and then to progress into clinically relevant metastatic tumors is widely studied, and is a major cause of morbidity and mortality in PC patients . Bone metastases most frequently affect the axial skeleton and often cause skeletal complications known as skeletal-related events (SREs), such as: pathological fracture, radiotherapy (RT), surgery, spinal cord compression (SCC) and hypercalcemia . Despite the osteosclerotic nature of bone metastases, SREs in PC are still very common, reducing quality of life and worsening survival . Bone metastases start with the tropism of cancer cells to the bone through specific migratory and invasive processes . The complex molecular pathogenetic mechanism of bone metastases offers several potential targets for prevention and therapy . Although the mechanisms underlying bone metastases are far from being fully elucidated, several translational models of PC bone metastases have been studied, including the application of molecular profiling techniques, animal model systems and engineered cell lines: all of these models could help to improve our treatment capacity. Nowadays, several therapeutic options are available for PC patients. The milestone was androgen-deprivation therapy. Other possibilities now include chemotherapeutic agents, new-generation hormone therapies, radium 223 and, more recently, radioligand therapies. However, for these patients, special attention should be also placed on the management of bone health and the prevention of treatment-induced bone loss . Bone-targeted agents, bisphosphonates and denosumab are active in bone metastases ; however, these drugs should still be evaluated even in the absence of bone metastases and under multidisciplinary evaluation, according to dedicated guidelines. Our review aimed to attract attention to both the biological and clinical implications of bone metastases and to the risk of "bad" bone health in PC patients. 2. Bone Metastases in Prostate Cancer PC cells show a preference for tropism to the bone. An autopsy study revealed that approximately 90.1% of men who had died with metastases of PC were diagnosed with bone metastases . In PC patients with bone metastases, the 5-year survival rate was 33% . In cases of spinal metastases of PC, the median overall survival (OS) appears to be 24 months with an estimated 1-year OS of 73% . The extent of skeletal metastatic involvement correlates with survival in patients with advanced PC. The "bone scan index" allows us to quantify the extent of tumor skeletal involvement. Patients with low, intermediate and extensive skeletal involvement had a median overall survival of 18.3, 15.8, and 8.1 months, respectively, in a study of 191 patients with androgen-independent PC . Distinct phenotypes of bone metastases have been described in patients with PC: osteolytic, osteoblastic and mixed. The existence of mixed lesions suggests that the processes that regulate tumor-associated osteolysis and bone formation may occur together in bone metastases and are not mutually exclusive. Furthermore, the relative activity of these two coexisting processes defines the bone metastases' phenotype. Osteolytic metastases, defined as a "punched-out" area of severe bone loss, are a consequence of tumor-induced activation of bone-matrix resorption. Resorption of mineralized bone matrix is the natural function of the osteoclast, a multinucleated cell of hematopoietic origin residing in the bone, in cooperation with multiple other actors and with several stimuli (as reported below). Osteoblastic metastases, characterized by bone forming, are prevalent in advanced PC patients and induced by cancer cell interactions with osteoblasts and their progenitors through several interactions . PC cells also demonstrate osteomimicry by responding to growth factor stimulation . This would suggest that bone-forming tumors may also occur through differentiation of the cancer cells towards an osteoblastic bone-forming phenotype, which is a phenomenon that has been observed in the bone metastatic PC cell line, C42b . A category of cancer and bone interactions likely to contribute to the metastatic tumor phenotype are those driven by sex steroid hormones. Prostate and breast cancers, both sex steroid-sensitive diseases, show a predilection to form bone metastases. In addition, it has been shown that hormone-sensitive PC cells can respond to sex steroid deprivation by activating de novo synthesis , which implies that bone cells interacting with metastatic cancer may be stimulated by androgen produced locally by tumor cells. Osteoblatic metastases are more common in PC, representing 68% of all bone metastases . Despite this, the osteolytic factor parathyroid hormone-related protein (PTHrP) is also highly expressed in PC. A proposed explanation is that PTHrP can also stimulate bone formation by activating the ETAR with NH2-terminal fragments of PTHrP, which share strong sequence homology with ET-1 . The prognosis of patients is markedly influenced by SREs, such as pathological fractures, hypercalcemia and pain, which occur in 49% of osteoblastic metastases . To predict the risk of SREs, bone resorption markers may be useful, such as N-telopeptide of type I collagen (NTX) and bone alkaline phosphatase (BALP), which are associated with higher rates of death and SREs in PC bone metastases . Further studies would be useful to stratify the risk of SREs in different types of bone metastases. The field exploring potential biomarkers of bone metastases deserves special attention, and researchers have investigated new strategies and approaches with different biomarkers. Yu and colleagues retrospectively analyzed data from 150 PC patients and found that patients with bone metastases had significantly elevated serum levels of carcinoembyonic antigen 125 (CA125), total prostate-specific antigen (T-PSA), free PSA (F-PSA), cytokeratin-19 fragment (CYFRA 21-1) and pro-gastrin-releasing peptide (ProGRP). The ROC curves indicated that T-PSA, F-PSA and ProGRP could effectively aid in discriminating between patients with bone metastases and those without. The area under the curves for the combination of these parameters was 0.941 with 90% sensitivity and gave better results than with each biomarker alone or with two biomarkers combined . Instead, Aufderklamm and colleagues investigated the utility of serum c-terminal telopeptide of type I collagen (1CTP) and n-terminal propeptide of type I procollagen (P1NP) in the diagnosis of bone metastases and in the prognosis of patients. These peptides are markers of bone formation which are increased in PC patients and bone metastases. They analyzed serum samples of 186 patients with prostatic hyperplasia or PC, with or without metastases. Increased levels of 1CTP were found in PC patients compared with others, while no significant difference was shown for P1NP levels. Instead, both markers were altered in metastatic patients compared with non-metastatic ones. Cancer prognosis was significantly worse in metastatic PC patients with higher 1CTP concentration . Moreover, to improve the capability of detecting for the risk of bone metastases, Windrichova and colleagues compared the performance of 16 biomarkers and suggested a mathematical model, the Bone Risk Score (BRS), by combining three of the biomarkers. They compared serum biomarkers levels in patients with different primary tumors, using scintigraphy to detect those with bone metastases (56 patients) or those without (75 patients). The best performance was obtained with the BRS combining P1NP, growth differentiation factor-15 (GDF15) and osteonectin . In addition, Ku et al. carried out comprehensive expression profiling of tissue samples of bone metastasis from different types of cancer, revealing their proteome landscape and four significant proteins with the potential capability to differentiate tumor primaries . Further studies are required to confirm these findings with a larger number of patients, and the clinical relevance of these markers. 3. Biology of Bone Metastases in Prostate Cancer Two historical hypotheses to explain mechanisms of tumor dissemination are the "seed-and-soil" hypothesis proposed by Paget in 1889 and the "mechanical entrapment theory" postulated by Ewing in 1928 . After about a century, both of these hypotheses have been integrated and collected, according to the 'metastatic cascade' model , with different multi-step tumor-host interactions . Its major steps are summarized in the following paragraphs and schematized in Figure 1 and Table 1. Table 1, Step 1A describes tumor cells escaping from the primary tumor and preparing the metastatic niche by epithelial-to-mesenchymal transition (EMT) and exosome release. Step 1B describes invasion of the surrounding tissue, intravasation and survival into circulation (with platelet coat formation). Step 2 in Figure 1 and Table 1 describes implantation into the soil, in this case in the bone marrow. Tumor cells undergo arrest, extravasation and invasion, with settlement in the new tissue. In the bone marrow niche, as shown in the Figure 1 (step 2), tumor cells form relationships with multiple resident and attracted cells and several molecules (see text and Table 1). Step 3 in Figure 1 and Table 1 is the representation of dormancy. It is a particular phase of balance between tumor cells and normal cells; players and factors involved are multiple. Step 4 is growth, in which the results of multiple interactions may differ and the two extreme possibilities range from the predomination of the 'osteoclastic vicious cycle' (Step 4A) or the 'osteoblastic vicious cycle' (Step 4B), see Figure 1. 3.1. Prepare and Reach the Soil: The First, General Mechanisms A. Escape from primary tumor and prepare the metastatic niche Some tumor cells at the primary site undergo epithelial-to-mesenchymal transition (EMT) and release exosomes, small vesicles involved in cell-to-cell communication and expression of integrins capable of conditioning their target to create the pre-metastatic niche . The suitable pre-metastatic niche must evolve to allow tumor cell engraftment (metastatic niche) and proliferation ( macrometastatic transition) . Fibroblasts, through fibronectin, attract hematopoietic cells from the bone marrow expressing vascular endothelial growth factor receptor-1 (VEGFR-1), and establish a metastasis-supporting microenvironment . The primary tumor also releases VEGF-A, TGF-b and TNF-a, which, via expression of S100, mediate the migration of myeloid cells into the metastatic niche . Matrix metalloproteinase (MMP) MMP-9 and lysyl oxidase (LOX) are also important for metastatic niche's formation. B-C. Invasion of surrounding tissue and intravasation MMP-1, -2, -7, -9 and -14 are involved in tumor angiogenesis and MMP-14 may remodel the extracellular matrix (ECM) to facilitate cancer cell migration and invasion . Tumor-associated macrophages (TAM) and PHD2 expressed in the tumor vasculature are important in these steps . Cancer cells can access the bloodstream directly through compromised tumor-associated blood vessels; or with active intravasation , dysregulation of angiogenesis ; or through inflammatory signaling . D-E. Survival in circulation and "attraction" to new locations Cancer cells may be isolated from the blood stream as circulating tumor cells (CTCs), either as single cells or as clusters . To reach their goal, CTCs have to survive into the circulation and act in cooperation with platelets, which adhere to their surface, increasing their metastatic potential, preventing their recognition by the immune system and decreasing their shear stress . Stromal cells secrete several chemokines such as CXCL12 and RANKL to "attract" cancer cells to the bone marrow. 3.2. Implant in the Soil: Prostate Cancer Cell Homing in the Bone Marrow F. Arrest The mechanical entrapment of CTCs in capillaries preludes their arrest in the tissue . Platelets help in the initial adherence and facilitate the initial interaction of cancer cells through E-selectin, which is expressed in the endothelium and in the primary cancer . Platelets have been implicated in the specific development of bone metastases through the release of lysophosphatidic acid and the production of IL-6 and IL-8, stimulating osteoclast activity . Integrins, CD44 and MUC1 are then important, for a more stable interaction of CTCs with the endothelium . PC cells bind preferentially to the bone marrow endothelium . Jung and colleagues, using an in vivo murine model of human PC cell metastasis, noted that growth arrest specific-6 (GAS-6) levels were significantly greater in the forelimb versus hindlimb bone marrow, and spinal lesions or lesions in the bones of the hindlimb were more frequent than those of the forelimb . GAS-6 is a ligand for the tyrosine kinase receptor Axl, and its role in prostate cancer is controversial but the therapeutic manipulation of its levels may prove useful for treatment of metastatic disease. G. Extravasation Once bound to the endothelium, cancer cells begin opening the endothelial junctions in response to multiple factors--including TGF-b and VEGF --traverse the basement membrane and enter into the stroma. The endothelial cells of the bone perivascular niche modulate cell trafficking. H. Settlement Once they arrive in the bone marrow, cancer cells require phenotypical changes to stabilize and survive. They acquire the capability to respond to physical and chemical microenvironmental stimuli and adhere to the special niches previously prepared. The CXCL12/CXCR4 axis facilitates the bone invasion processes by inducing MMP-9 and downregulating the expression of tissue inhibitors of MMP-2 in PC cells . Moreover, MMPs lead to cancer cell colonization in the bone marrow, through integrin avb3 and integrin avb5, which interact with osteopontin and integrin-binding sialoprotein (IBSP), respectively . Galectin-3/Thomsen-Friedenreich antigen is one other adhesion molecule important for the interaction of PC cells with bone marrow endothelium . The protein CCL5, a member of the chemokine superfamily produced by cells in the bone microenvironment, with its receptor CCR5, increases PC cell migration to the bone via androgen receptor signaling . Other molecules are also involved . Furthermore, the transcription factors Twist-1 and lysophosphatidic acid (LPA) are reported to be important for bone invasion due to their expression of two microRNAs, miR-10b and miR-21, respectively. Knocking out these two microRNAs inhibits bone marrow invasion in in vivo experiments . 3.3. Dormancy: The Prelude of Detectable Bone Metastases In the bone niche, cancer cells have to engage in several interactions with stromal and resident cells, resulting in different outcomes: a "silent balance" called "dormancy" or an "activation state" that lead to an "osteoclastic" or an "osteoblast vicious cycle" . In 1998, Luzzi et al. provided one of the first descriptions of these interactions, underlining the multistep nature of metastatic inefficiency and two critical points: failure of solitary cells to initiate growth and failure of early micrometastases to continue growth . Among others, GAS-6, bone morphogenetic protein 7 (BMP7) and transforming growth factor beta 2 (TGF-b2) have been associated with dormancy. GAS-6 acts by binding to receptors Axl, Sky and Mer . Shiozawa et al., demonstrated that the activation of Axl by GAS-6 on PC cells in a bone marrow niche environment plays a critical role as a molecular switch to establish dormancy of PC cells . BMP7 and TGF-b2 act via inhibitions of the ERK signaling pathway . Cancer-associated fibroblasts (CAFs) and the immune system are important for cancer cell survival in bone marrow and the immune system is a key player in tumor cell dormancy . NK cells, via production of interferon g (INFg) and TRAIL/FASL-induced apoptosis, collaborate to maintain balance . 3.4. Growth: The "Clinical Phase" of Bone Metastasis In triggering cancer cell reactivation after dormancy, the important players are: endothelial cells from neovasculature that produce TGF-b1 and periostin ; adipocytes via FABP4 ; macrophages with cathepsin K ; and protein in the microenvironment, such as type 1 collagen and fibronectin . Furthermore, immature myeloid cells (iMCs) in the presence of tumor cells differentiate into myeloid-derived suppressor cells (MDSCs) and TAM . Dendritic cells (DCs) play a critical link between innate and adaptive immunity and the inhibition of a special population such as plasmacytoid DCs is associated with a greater Th1 response, INFg production and restoration of CD8+ T cell function against cancer cells . In the bone, neutrophils (TAN) enhance bone resorption . In this scenario, cancer cells mimic bone cells in a manner called osteomimicry. They have been shown to have an osteoblast-like phenotype, owing to their expression of cathepsin K, osteonectin, cadherin-11, connexin-43 and RUNX2 . However, cancer cells may also acquire osteoclast properties due to fusion with macrophages, or induce multinucleated giant cells due to fusion with osteoclast precursors . Moreover, cancer cells may shift their behavior more towards growth by their expression of VCAM1 and the release of signals related to the NFkB pathway . Further research will allow us to specify even more detail about the role and relationships between resident and circulating cells, both in cancer and non-cancer cells, and factors used to communicate. Some important growth factors are reported below. IGF is the most abundant growth factor stored in bone, and metastatic PC cells are positive for IGF type I receptor (IGF-IR). Their interaction increases proliferation and cancer cell survival through AKT and NF-kB signaling . TGF-b, the second most abundant growth factor stored, promotes the production of osteolytic factors that induce RANKL expression and inhibit osteoprotegerin expression in BMSCs and osteoblasts. The latter promote osteoclastic bone destruction; progression of bone metastases; and also secrete several proteins that positively regulate tumor growth, including IL-6, SPARC and periostin. SPARC induces cancer migration and homing through the aVb5 integrin, whereas periostin and IL-6 promote prostate tumor survival . Moreover, high levels of extracellular calcium facilitate bone metastases of PC via the CaSR and the Akt signaling pathway . PC cells, on their side, produce several cytokines and growth factors, including IL-6, BMP, TGFR, VEGFR and Wnt. These factors activate osteoblasts, which secrete RANKL. RANKL binds to receptor activator of NF-kB (RANK) expressed on osteoclasts, resulting in osteoclast activation. Osteoclasts reabsorb bone and release growth factors supporting tumor growth, such as TGF-b. Osteoprotegerin (OPG), an inhibitor of RANKL, is consequently overwhelmed by TGF-b and unable to oppose RANKL production, continuing the vicious cycle of bone metastases . PTHrP was shown to potently stimulate osteoclastogenesis by increasing the production of RANKL by osteoblasts. However, PTHrP also facilitates osteoblastic alterations . Recently, the role of the Wnt pathway in the progression of prostate bone disease has been investigated. The Wnt gene family is a big family of cysteine-rich glycoproteins. In this context, Wnt induces osteoblastic activity through upregulation of OPG expression and downregulation of RANKL, which together increases the osteoblastic phenotype of bone metastases . Hall et al. demonstrated that elevated glycoprotein Dickkopf-1 (DKK-1) is an early event in prostate cancer, and a decline is a later event in advanced bone disease. The decline of DKK-1 levels in bone metastases is interlinked with the osteoblastic activity of Wnt and supports a model in which DKK-1 is a molecular switch that transitions the phenotype of PC bone lesions from osteolytic to osteoblastic. DKK-1 has proved to be oncogenic and an inhibitor of Wnt signaling and, thus, of bone formation (osteoinduction) . Sclerostin is another protein secreted by osteocytes and was recently shown to both upregulate the expression of RANKL by osteocyte-like cells and promote osteoclastogenesis . Last but not least, the role of androgen receptor (AR) should be underlined. During the castration-resistant phase of prostate cancer, AR is reactivated through several mechanisms, including AR amplification and mutation, as well as activation of ARs through other signaling pathways. Bone metastases usually occur in the castration-resistant phase and androgen receptor variants (AR-Vs), active even in the absence of ligand-binding domain (including AR-V1, AR-V7, and AR-V567es), are highly expressed in bone metastases of patients with castration-resistant PC (CRPC). Cellular-myelocytomatosis viral oncogene (c-Myc) has a positive role in regulating ARs and AR-Vs in prostate cancer as reported by Bai et al., in cell models and in a patient-derived xenograft model . Importantly, their study highlights the role of c-Myc in CRPC and suggests the utility of its target as an adjuvant to AR-directed therapy. They demonstrated that the inhibition of c-Myc sensitizes enzalutamide-resistant cells to growth inhibition by enzalutamide, one of the second-generation anti-androgen therapies used for PC treatment . The close relationship between c-Myc and ARs was recently underlined also by Qiu and colleagues. They demonstrated that c-Myc overexpression significantly diminishes the AR transcriptional program and contributes to PC initiation and progression . 3.4.1. Osteolytic Lesions: The 'Osteoclastic Vicious Cycle' Reactivated cancer cells express VCAM-1 with the recruitment of osteoclastic precursors and the release of several factors, such as PTHrP. This process increase the expression of RANKL, responsible of the formation of new osteoclasts . Myeloid bone marrow cells and lymphocytes produce cytokines that stimulate osteoclast activity . Osteoblast activity is inhibited by cancer cells through the release of soluble proteins, such as DKK-1 . Bone tissue may contribute to osteolysis by the production of growth factors, such as TGF-b and IGFs I and II . 3.4.2. Sclerotic Lesions: The "Osteoblast Vicious Cycle" In their paper, Logothetis et al. reported the role of BMP-2, Wnt, adrenomedullin, FGF9, endothelin-1 and OPG in osteoblast activity in PC with bone metastasis . 3.4.3. Mixed Lesions The division between the two previously mentioned types of bone lesions is not well defined. In a single patient, and even in a single lesion, they may co-exist and produce mixed lesions. 4. Molecular Subtypes of Prostate Cancer Bone Metastases: Beyond "Classical" Characteristics of Bone Metastases The important role of ARs in PC has already been emphasized, and CRPC bone metastases can be divided into two subgroups, according to AR activity: high and low AR activity subgroups. These two groups of bone metastases have different immune cell profiles . Moreover, following analysis of genome-wide expression (GWAS) within PC bone metastases from patients who were untreated or who underwent androgen-deprivation therapy (ADT), Thysell and colleagues identified three distinct molecular subtypes within bone lesions: Met A, B and C. The subtypes have different gene expression, morphology and clinical features (Table 2). MetA is the most frequent, has a high expression of androgen receptor-regulated genes, including Prostate-Specific Antigen (PSA) and seems to be of luminal cell origin. MetB shows poor prognosis after ADT, has a dedifferentiated luminal phenotype and some characteristics similar to neuroendocrine tumors. It exhibits profiles related to DNA damage and cell cycle activity, androgen-stimulated gene expression is generally low and cell proliferation is high. MetC shows high transcription activity involved in stroma-epithelial cell interactions and inflammation. This latter group is the least common and most poorly defined . Using PSA and Ki67 analysis, the same group was able to differentiate MetA-like from MetB-like tumors, with different prognoses (Table 2) . Recently, the same group verified the clinical relevance of the MetA-C subtype classification, and in particular its usefulness to identify MetB patients in need of complementary therapy . They retrospectively analysed a total of 103 metastasis samples from 67 clinically different PC patients and from the sequencing data of 573 other metastasis samples previously published. Their results confirmed that MetA was the most common subtype and had a high androgen response, while MetB was associated with poor prognosis; was enriched in CRPC and in liver metastases; was characterized by high cell cycle activity and DNA repair; and demonstrated specific gene alterations. MetC was characterized by epithelial-to-mesenchymal transition and inflammation, and showed diverse biology, organ tropism and prognoses . Moreover, researchers examined whether bone metastatic subtypes and prognosis after ADT could be predicted by immunohistochemical analysis of epithelial and stromal cell markers in primary tumor biopsies made at diagnosis . They analysed samples from primary tumors and metastases from 98 PC patients and found that International Society of Urological Pathology (ISUP) grade was not associated with outcome or metastasis subtypes, whereas high expression on tumor epithelial cells of Ki67 in combination with low PSA expression and a low fraction of AR positive stroma cells, correlated with poor prognosis after ADT and with developing of MetB subtypes. The opposite pattern predicted the development of the MetA subtype with better ADT response. Thanks to these results, a subtype-specific metastasis treatment could be initiated at diagnosis, for example, complementary therapies for patients with a primary tumor with high proliferation and/or low PSA expression. It is noteworthy that the analysis was restricted to microscopic evaluation and that the correlation coefficient for individual factors measured in primary tumors and paired metastases samples were all relatively low. The quantification of "hot spot" regions in primary tumors could have higher correlation; there is also the consideration of other aspects, such as the bone microenvironment. Furthermore, it remains to be explored how this conclusion applies to different patients, such as those diagnosed at an earlier disease stage . Further studies are needed to clarify whether patients with different metastasis types would benefit from different therapies or new subtype-specific treatments. 5. Systemic Treatments in Prostate Cancer and Skeletal Related Events ADT with surgical bilateral orchiectomy, administration of non-steroidal anti-androgens or analogs of luteinizing hormone releasing hormone (LHRH) are the possible therapeutic options administered in PC in different settings . The goal of ADT is to reduce testosterone by up to 95% and to lower estrogens, but it also results in increased bone resorption in order to alter the balance between osteoblastic and osteoclastic cells, and a rapid decline of bone mineral density (BMD). The duration of ADT is proportional to the risk of osteoporotic fracture . In contrast, treatment with peripheral anti-androgens does not cause bone adverse events . ADT is also related to modification of body composition: loss of muscle mass (sarcopenia) and an increase in fat mass . Management of bone health and prevention of cancer treatment-induced bone loss (CTIBL) in an important part of the treatment of PC patients undergoing hormonal treatment , and prevention of CTIBL is covered by already-cited ESMO guidelines . When PC becomes resistant to androgen deprivation (CRPC), the disease is more aggressive and often metastatic. Optimal management of PC patients with bone metastases requires a multidisciplinary team composed of a medical oncologist, radiotherapist, orthopedic specialist, interventional radiologist, nuclear medicine physician and bone specialist. In CRPC patients, LHRH therapy is combined with second-generation hormonal therapies, such as abiraterone , enzalutamide , apalutamide or darolutamide , or with chemotherapeutic drugs such as docetaxel or cabazitaxel . Metabolic radiotherapy can also be used in patients with metastatic prostate cancer and symptomatic bone metastases . There are no data about the role of taxane-based chemotherapy in the control of SRE, but it induces myelosuppression , and, in animal models, the administration of drugs with medullar toxicity were responsible for persistent loss of trabecular components of bone and increased bone resorption . Moreover, the use of over-physiological glucocorticoids in patients undergoing taxane chemotherapy could adversely affect bone health. Glucocorticoids inhibit osteoblastic differentiation and increase osteoclastic survival, promoting bone resorption . Oral abiraterone acetate plus prednisone compared with placebo and prednisone improved OS (15.8 mo vs. 11.2 mo; p < 0.0001), delayed time to first SRE (9.9 mo vs. 4.9 mo, p = 0.0001), median time to occurrence of first SRE (25 vs. 20.3 mo, p = 0.0001), enhanced pain relief and improved quality of life (QoL) in metastatic CRPC (mCRPC) previously treated with docetaxel in the COU-AA-301 trial . In the COU-AA-302 trial, where treatment with abiraterone acetate plus prednisone compared with placebo and prednisone was evaluated in mCRPC patients who had not previously received chemotherapy, the time to first SRE was not among the endpoints; however, the drug improved radiographic progression-free survival (PFS) and significantly delayed clinical decline . The STAMPEDE trial analyzed the role of abiraterone acetate plus prednisolone and ADT compared with ADT alone in patients with locally advanced or metastatic PC. After 3 years of treatment, the combination arms showed an elevated survival rate (83% vs. 76%, HR 0.63; p < 0.001) and a reduced risk of SRE (12% vs. 22%, HR 0.46, p < 0.001) . Enzalutamide, an oral non-steroidal antiandrogen evaluated in the AFFIRM trial, improved OS in comparison with placebo (18.4 mo vs. 13.6 mo) and showed a reduction in the risk of a first SRE (16.7 mo vs. 13.3 mo) in metastatic prostate patients after docetaxel-based chemotherapy . The PREVAIL trial showed an improved time to first SRE (32% vs. 37%, HR, 0.72; p < 0.001) in metastatic chemotherapy-naive patients treated with enzalutamide compared with placebo (median 31.1 mo vs. 31.3 mo) . In men with nonmetastatic CRPC with rapidly rising PSA levels at high risk for metastases, enzalutamide (in comparison with placebo) significantly lowered the risk of metastases and death in the PROSPER trial . Apalutamide in men with nonmetastatic CRPC at high risk for the development of metastases had significantly improved metastasis-free survival and time to symptomatic progression compared with placebo in the SPARTAN trial . Darolutamide is an antagonist of the androgen receptor. Its role has been evaluated in the ARAMIS trial in men with non-metastatic CRPC. It delayed the time to first appearance of a symptomatic skeletal event versus placebo (16 events vs. 18 events, HR 0.43, p: 0.01) . Radium-223-dichloride is a bone-targeting agent approved for patients with symptomatic bone metastases from PC without visceral disease. Radium-223-dichloride binds with high-affinity hydroxyapatite in sites with elevated bone turnover, and has a local cytotoxic effect via double-strand DNA breaks . In the ALSYMPCA trial, patients with symptomatic bone metastases of PC after docetaxel or not suitable for docetaxel were treated with six cycles of intravenous radium-223-dichloride. Compared with placebo, the experimental group showed better OS (14.9 months vs. 11.3 months; HR, 0.70 p < 0.001) and a longer time to first SRE . Patients receiving antiresorptive treatments in addition to radium-223-dichloride showed a delayed time to first symptomatic SRE and a prolonged symptomatic SRE-free survival time (HR 0.69, p < 0,0001) . However, the results of the ERA 223 trial should be emphasized: radium-223-dichloride plus abitaterone acetate and prednisone did not reduce the risk of SKE or improve survival in mCRPC, but they did increase the risk of fracture. After a median of 21.2 months, at least 1 SKE was reported in 49% of patients in the experimental group vs. 47% of controls, and the median symptomatic skeletal event-free survival was 22.3 vs. 26.0 months. Moreover, 29% of patients followed for safety in the experimental group experienced bone fracture, especially osteoporotic fractures, compared with 11% of controls . This evidence led the US Food and Drug and the European Medicines Agency to revise the prescribing recommendations for radium-223-dichloride, but it should be stressed that patients in both treatments arms who used bone health agents had a reduced risk of fracture compared with non-users. The results of studies of the beta-emitting lutetium (Lu)-177-labeled prostate-specific membrane antigen (PSMA) radioligand therapy (RLT) for mCRPC were presented in 2021 with the phase 3 randomized trial VISION. 177Lu-PSMA-617 plus standard care compared with standard care alone significantly prolonged imaging-based PFS and OS (primary end points). The time to first SRE was also longer: 11.5 vs. 6.8 months with an HR of 0.50 (95% CI, 0.40-0.62) p < 0.001. The incidence of high-grade adverse events was also higher with 177Lu-PSMA-617 than without, but quality of life was not adversely affected . In mCRPC that progressed after Lu-177-PSMA treatment, measurable antitumor effects were seen also with alpha-emitting actinium (Ac)-225-PSMA-617 RLT . For metastatic hormone-sensitive PC (mHSPC) several studies demonstrated that the addition of abiraterone (LATITUDE and STAMPEDE ), apalutamide (TITAN ), enzalutamide (ARCHES and ENZAMET ) or docetaxel (CHAARTED and STAMPEDE ) to ADT improves OS, but also in this setting the attention to bone health and SRE should not be underestimated. Table 3 reports phase II/III trials on prostate cancer and outcomes in terms of OS and time to first SRE. 6. Bone Health in Prostate Cancer 6.1. Bone Loss Osteoporosis is a skeletal disorder characterized by decreased bone mass and qualitative alterations associated with increased fracture. Bone Mineral Density (BMD), evaluated by dual-energy x-ray absorptiometry (DXA), represents an accurate and precise measurement of bone mass. Fracture risk exponentially increases at a T score < -2.5 SD, which has been established by the WHO as the cut-off for densitometric diagnosis of osteoporosis . There is a close correlation between osteoporosis and PC. From 3.9% to 37.8% of hormone-naive PC patients show osteoporosis before the start of any oncological treatment, suggesting that PC could itself be a risk factor for loss of BMD, due to the promotion of bone resorption . Osteoporosis in patients treated with LHRH analogs involving any site varies from 10% to 40% and worsens with age and ADT duration , reaching 80% of patients after 10 years of treatment . The annual rate of bone loss in all men is between 0.5% and 1%. Bone loss during the first year of ADT in patients with metastatic disease is 2-8% in the lumbar spine and 1.5-6.5% in the hip . In subsequent years, the reduction in BMD continues, at approximately 1-4% each year . After bilateral orchiectomy, BMD at the femoral neck diminishes by 2.4% after the first year and by 10% after two years . At the end of ADT, BMD may increase in the lumbar spine, while remaining low in other sites , no increase is observed at the hip. Risk factors for bone loss are older age and lower body mass index (BMI) . Bone loss is associated with an increased risk of incident fractures . 6.2. Fracture Risk PC is not an independent risk factor for bone fractures . After bilateral orchiectomy, BMD diminishes and the fracture rate is 38% at 5 years . All patients treated with ADT should be evaluated for osteoporotic risk during treatment. The main risk factors are age >= 75 years, history of low-energy fracture after the age of 50 years, osteoporosis defined as a T-score <= -2.5 at one or both measurement sites (spine and femur), BMI < 19 kg/m2, at least three comorbidities (e.g., cardiovascular disease, depression, Parkinson's disease, dementia) and current or past glucocorticoid therapy . Several trials showed that treatment with an LHRH analog for longer than 6 months is associated with an increased fracture risk. In men older than 50 years old without PC, osteoporotic fracture risk was 13% versus 21-37% in patients with PC . Patients who received LHRH treatment suffered bone fractures in 19.4% of cases from 1 to 5 years after diagnosis, versus 12.6% without LHRH analog therapy (p < 0.001) . The relative risk (RR) of fracture in each bone was 1.21 (p < 0.001), 1.45 for vertebral fractures (p < 0.001) and 1.30 for hip fractures (p = 0.002) . Fracture risk was associated with mortality risk . The risk of fall was increased by loss of muscle mass secondary to decrease in testosterone levels . The FRAX score can be used to estimate the absolute 10-year risk of osteoporotic hip fracture and major osteoporotic fracture (clinical spine, forearm, hip or shoulder fracture) in men older than 40 years old. This tool could drive physicians to start treatment for osteoporosis. In men on ADT, Adler et al. underline that DXA and FRAX identify ADT-treated men differently for treatment for osteoporosis . The Italian Association of Clinical Endocrinologists (AME) position statement for the treatment of osteoporosis recommends considering for treatment all subjects with a BMD assessment T-score <= -2.5 SD with prior fragility fracture, regardless of BMD measurement, or with a DXA-based T-score between -2.5 and -1 SD and with an increased 10-year fracture risk evaluated with a fracture risk algorithm . In contrast, Dawson-Hughes and colleagues in the practice guidelines published in the USA in 2008, suggested a cost-effective cut-off for the treatment of osteoporosis when the 10-year probability of hip fracture reached 3% . 6.3. Treatment for Bone Health in PC Patients SRE-like pathological fractures, spinal compression, bone pain and increased levels of calcium are involved in around 40% of patients with metastatic PC, and influence QoL . In every man before starting ADT and during antineoplastic treatment, for maintaining bone health, Body Mass Index (BMI), medical history (for example, diabetes, smoking history, alcohol abuse, use of medications such as steroids), history of fractures, dietary calcium intake, physical activity, vitamin D, and calcium and phosphorous levels are topics to investigate . The NCCN guidelines for PC version 2.2021 for screening and treatment of osteoporosis in patients on ADT refer to the National Osteoporosis Foundation guidelines recommending calcium and vitamin D3 supplementation and additional treatment (denosumab, zoledronic acid, alendronate) for men aged >=50 years with low bone mass (T-score between -1.0 and -2.5) at the femoral neck, total hip or lumbar spine by DEXA and a 10-year probability of hip fracture >=3% or a 10-year probability of a major osteoporosis-related fracture >=20% (fracture risk assessed using FRAX algorithm) . The European Academy of Andrology (EAA) clinical guideline on management of bone health published in 2018 as regards PC patients receiving ADT recommends starting antiresorptive treatment in patients with moderate-to-high fracture risk (with FRAX score) . The already-cited position paper of AME for the treatment of osteoporosis suggests that men on ADT perform mild endurance exercise consistent with their overall clinical state; consume 1000-2000 mg daily calcium, possibly from their diet; receive vitamin D supplementation if they have low plasma levels; and alendronate or zoledronate if they have a high risk of fracture; denosumab is also recommended . The same experts recommend against the use of selective estrogen receptor modulators (SERMs) for treating men with ADT, as these drugs are not registered for this indication . Most trials evaluated the role of biphosphonates in preventing BMD decline, but they were not powered to evaluate fracture risk reduction . On the other hand, denosumab, a human monoclonal antibody associated with RANKL inhibition that suppresses bone resorption caused by osteoclasts , is associated with increased BMD and also demonstrated a significant reduction in the incidence of new vertebral fractures at 36 months in men on ADT and one additional risk factor for fracture (age > 70, T-score < 1.0 or history of osteoporotic fracture) . In their study, Smith et al. found a BMD increase of 5.6% in the lumbar spine, 4.8% at the total hip and 3.9% in femoral neck (p < 0.001) and a reduced risk of incident vertebral fracture over 36 months with denosumab (1.5% vs. 3.6% in placebo arms; RR 0.38, 95% CI 0.17-0.78) . For patients with SRE, treatment with antiresorptive drugs should be evaluated. Bisphosphonates and denosumab are active in bone metastases for their suppression of bone resorption and they improve bony tenderness and pain. Intravenous bisphosphonates showed a longer duration of action than the oral formulation . Bisphosphonates cause osteoclast death during bone resorption . In locally advanced or recurrent castration-sensitive PC, the upfront use of bisphosphonates did not show a survival benefit . In patients with CRPC with bone metastases, treatment with intravenous zoledronic acid every 21 days showed a reduction in SRE and improved BMD in lumbar spine (8.09%, 95% CI 5.89-10.29; p < 0.00001), in total hip (4.45%, 95% 0.84-8.06%, p = 0.02) and in femoral neck . Denosumab 120 mg monthly showed superior results when compared with zoledronic acid (4 mg monthly) for prevention of SRE in men with bone metastatic CRPC (HR 0.82; CI 0.71-0.95; p = 0.0002) . Antiresorptive drugs are well tolerated and adverse events, such as fever, myalgias and atypical femoral fractures, are rare. Jaw osteonecrosis (ONJ) is a possible adverse event when bisphosphonates and denosumab are administered for long time in patients with low oral hygiene, prior tooth surgery or who use a dental device. The risk is very low at the dosages used for osteoporosis, and slightly greater when used for bone metastases, but it remains infrequent and its management is mostly conservative . In patients with risk factors for ONJ, preventive dental treatments are indicated before bone-target therapy and education of clinicians and patients about oral health before and during antiresorptive therapy may help reduce the incidence of ONJ and improve its outcomes . Before every intravenous infusion, tests for serum creatinine clearance, calcium and phosphorus levels must be completed and adequate vitamin D supplementation should be ensured. If creatinine clearance level is between 30 and 60 ml/min then bisphosphonates can be administered with caution. The optimal duration of antiresorptive treatments is still unclear and must be evaluated for each patient, both to prevent bone loss and to treat bone metastases. In clinical trials evaluating the prevention of bone loss, bisphosphonates were administered for different durations . In cancer patients with bone metastases continuing treatment beyond 2 years there may be some benefit, in addition to an individualized approach and a switching strategy after skeletal disease progression . In patients with different cancers with bone metastases, the administration of i.v. zoledronic acid every 12 weeks is non-inferior to 4-week schedules, with a similar incidence of SRE >=1 within 2 years of randomization . Nevertheless, for each case, a multidisciplinary team evaluation is desirable. Additionally, for example, in patients with oligometastatic disease, low risk of SRE and good response to systemic treatment, antiresorptive drugs may have a limited duration of effect; therefore, in cases of multiple bone metastases, bisphosphonates or denosumab may instead be administered for longer if well tolerated. Palliative radiation therapy is indicated for patients with metastatic disease with bone pain. Steroid treatment can be administered in case of an initial flare in bone pain. Radiotherapy demonstrates rapid resolution of pain and an overall response rate (ORR) of 70-80%. It improves QoL and it is related to a low rate of adverse events . 7. Conclusions Several therapeutic options are available for PC patients, but bone metastases are still a relevant problem both for morbidity and mortality. Researchers on biological mechanisms for their formation and growth and on their molecular landscape could offer several potential targets for prevention and therapy. However, it is also important to raise awareness in the oncology and medical community of the maintenance of bone health before and during oncological treatments. Every man with PC should be evaluated for osteoporosis risk before starting ADT. Patients with an elevated risk of osteoporosis and "bad" bone health should be referred to a multidisciplinary panel that includes a bone health specialist. For these patients, treatment with bone-targeted therapies should be evaluated, even in the absence of bone metastases. In this way, we can try to ensure the best care for PC patients, with significant improvement both in quality of life and in overall survival. Bone health plays a central role in PC. It may be influenced by cancer treatments and several other conditions and may be divided in two aspects: bone metastasis and osteoporosis. An appreciation of the biology of bone and bone metastases is important for understanding and choosing treatment strategies. 'Bad' bone health conditions can lead to major skeletal events. Their prompt recognition and treatment, with the help of a multidisciplinary team with a bone health specialist, can improve the quality of life and survival of patients. Acknowledgments The authors would like to thank all the specialists who have committed themselves to set up a multidisciplinary collaboration for prostate cancer in our reality. In addition, special thanks to all the patients and their families for their trust and relationships. Author Contributions Conceptualization, C.B., R.S. and M.G.V.; methodology C.B., R.S. and M.G.V.; software, C.B., E.M., R.S. and M.G.V.; validation, B.M., M.D. and R.S.; formal analysis, C.B. and G.P.; investigation, C.B., S.P., K.C., M.F., C.N., M.O., M.P., E.D. and S.C.; resources, C.B., S.P., K.C., M.F., C.N., M.O., M.P., E.D. and S.C.; data curation, C.B. and G.P.; writing and original preparation, C.B., S.P., K.C., M.F., C.N., M.O., M.P., E.D. and S.P.; writing--review and editing C.B., S.P. and E.M.; visualization, C.B., S.P. and E.M.; supervision, B.M., M.D. and R.S.; project administration, C.B. and E.M.; funding acquisition, not applicable. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest C.B., R.S., M.G.V. and S.P. declare conflicts of interest for advisory board/clinical trials/conference speaking/travel grant with Astellas, AstraZeneca, Bayer, BMS, Clovis, Exelixis, GSK, Ipsen, Janssen, Merck, MSD, Novartis, Pfizer, Roche, Sanofi. The other authors declare no conflict of interest. Abbreviations SRE Skeletal-related event OS overall survival NTX N-telopeptide of type I collagen EMT epithelial-to-mesenchymal transition ADT androgen deprivation therapy AME The Italian Association of Clinical Endocrinologists AR Androgen receptor AR-Vs androgen receptor variants BALP bone alkaline phosphatase BMD bone mineral density BMI body mass index BMP7 bone morphogenetic protein CAF Cancer-associated fibroblast c-Myc Cellular-myelocytomatosis viral oncogene CRPC castration resistant PC CTC circulating tumor cell CTIBL cancer treatment-induced bone loss DC dentritic cell DKK Dickkopf DXA dual-energy x-ray absorptiometry EAA The European Academy of Andrology ECM extracellular matrix EMT epithelial-to-mesenchymal transition GAS growth arrest-specific GWAS genome-wide expression IBSP integrin-binding sialoprotein IGF-IR IGF type I receptor iMCs immature myeloid cells INFg interferon g LHRH Hormone-releasing hormone LOX Lysyl oxidase LPA lysophosphatidic acid Lu Lutetium mCRPC metastatic CRPC MDSC Myeloid-derived suppressor cells MPP Matrix metalloproteinase NTX N-telopeptide of type I collagen ONJ osteonecrosis of the jaw OPG Osteoprotegerin ORR Overall response rate OS overall survival PC Prostate cancer PSA Prostate-Specific Antigen PSMA prostate-specific membrane antigen PTHrP parathyroid hormone-related protein QoL quality of life RLT radioligant therapy RR relative risk RT radiotherapy SCC spinal cord compression SERM selective estrogen receptor modulators SRE Skeletal-related event TAM Tumor-associated macrophage TAN neutrophil TGF-b2 transforming growth factor beta VEGFR-1 vascular endothelial growth factor receptor-1 Figure 1 Steps of metastatic cascade. Figure 2 Possibilities and strategies for bone health in PC. The green ovals indicate interventions or factors that improve bone health, while the red ovals indicate factors that make it worse. cancers-15-01518-t001_Table 1 Table 1 The metastatic cascade's major steps. Process Cells Other than Cancer Cells Molecules From Tumor From Other Cells 1 Prepare and Reach the Soil A Escape from primary tumor and prepare metastatic niche Fibroblasts; Hematopoietic stem cells Exosomes with integrins; VEGF-A, TGF-b and TNF-a; MMP-9, LOX Fibronectin VEGFR-1 B Invasion of surrounding tissue TAM MMP-1,2,7,9,14 MMP C Intravasation TAM; vasculature PHD2 D Survival in circulation Platelets E "Attraction" to new locations Stromal cells CXCR4 RANK CXCL12 RANKL 2 Implant into the Soil F Arrest Platelets; Endothelial cells Lysophosphatidic acid, IL-6, IL-8; E-selectin, integrins, CD44, MUC1 G Extravasation Endothelial cells TGF-b, VEGF Adhesion molecules H Settlement Stromal cells CXCR4, MMP-2, MMP-9, Integrin avb3, avb5 CCR5 CXCL12 Galectin-3/Thomsen-Fr Ag CCL5 3 Dormancy CAF, NK cells Osteomimicry GAS6, BMP7, TGF-b2; INFg, TRAIL-FASL 4 Growth Endothelial cells; Adipocites; Macrophages; MDSC and DC; TAN Osteomimicry with osteoblast-like phenotype or osteoclast properties; VCAM1, NFkB TGF-b1; periostin; FABP4; Cathepsin K; Collagen t.1, fibronectin I Osteoclastic lesion Pro-osteoclasts and osteoclasts; Myeloid cells and lymphocytes VCAM1, PTHrP, DKK-1 TGF-b, IGF-1 II Slerotic lesions Osteoblasts OPG, BMP-2, Wnt, adrenomedullin, FGF9, PDGF, ET-1 IL-6, MCP-1, VEGF, MIP-2 III Mixed lesions cancers-15-01518-t002_Table 2 Table 2 Molecular subtypes of prostate cancer bone metastases . Subtypes N of Cases Cellular Differentiation Gene Expression Ki-67 PSA Level Prognosis MetA 71% Moderate cellular atypia, glandular differentiation KLK3, FOXA1, KRT18, CDH1 Low High Good MetB 17% Prominent cellular atypia, lack of glandular differentiation FOXM1, CCNB1-2, CDC25B, CDK1, PLK1, PKMYT1, LMB1, KNSL1, NCL, KRT18 and others High Low Poor MetC 12% Prominent cellular atypia, glandular differentiation detectable in some cases, relatively high stroma/epithelial ratio ECM remodelling, regulation of EMT (Wnt, Notch, TGF-b, PDGF, immunological synapse formation, C/EBP, GSTP1 Low Low Poor cancers-15-01518-t003_Table 3 Table 3 Systemic treatments in prostate cancer, overall survival (OS) and time to the first skeletal-related event (SRE). Author Trial Drug Setting Ndeg of Patients OS p-Value Time to First SRE * p-Value Tannock et al., 2004 TAX 327 Docetaxel (3 weekly and w) + prednisone vs. Mitoxantrone (m) + prednisone mCRPC 1006 (335 vs. 334 vs. 337) 18.9 vs. 17.4 vs. 16.5 0.009 (3 w vs. m); 0.36 (w vs. m) No data - Sweeney et al., 2015 CHAARTED Docetaxel + ADT vs. ADT mHSPC 790 (397 vs. 393) 57.6 mo vs. 44.0 mo <0.001 No data - De Bono et al., 2010 TROPIC Cabazitaxel + prednisone vs. Mitoxantrone (m) + prednisone mCRPC 755 (378 vs. 377) 15.1 mo vs. 12.7 mo <0.0001 No data (bone pain 5% vs. 5%) - Logothetis et al., 2012 COU-AA-301 Abiraterone + prednisone vs. placebo + prednisone mCRPC 1195 (797 vs. 398) 15.8 mo vs. 11.2 mo <0.0001 9.9 mo vs. 4.9 mo 0.0001 James et al., 2017 STAMPEDE Abiraterone + prednisone + ADT vs. ADT mHSPC and mCRPC 1917 (960 vs. 957) 83% vs 76% (3-year OS rate) <0.001 12% of events vs. 22% of events <0.001 Fizazi et al., 2017 LATITUDE Abiraterone + prednisone + ADT vs. placebo + ADT mHSPC 1199 (597 vs. 602) not reached (NR) vs. 34.7 mo <0.001 NR vs NR 0.009 Scher et al., 2012 AFFIRM Enzalutamide vs. placebo mCRPC 1199 (800 vs. 399) 18.4 mo vs. 13.6 mo <0.001 16.7 mo vs. 13.3 mo <0.001 Beer et al., 2014 PREVAIL Enzalutamide vs. placebo mCRPC 1717 (872 vs. 845) 32.4. mo vs. 30.2 mo <0.001 32% events vs. 37% events <0.001 Armstrong et al., 2019 ARCHES Ezalutamide + ADT vs. placebo + ADT mHSPC 1150 (574 vs. 576) NR (HR 0.81) 0.3361 NR (HR 0.52) 0.0026 Davis et al., 2019 ENZAMET Ezalutamide + standard care vs. standard care mHSPC 1125 (563 vs. 562) NR (at 36 mo: 80% vs. 72%) 0.002 No data - Chi et al., 2019 TITAN Apalutamide + ADT vs. placebo + ADT mHSPC 1052 (525 vs. 527) NR (at 24 mo: 82.4% vs. 73.5%) 0.005 NR (HR 0.80) - Fizazi et al., 2019 ARAMIS Darolutamide vs. placebo non mCRPC 1509 (955 vs. 554) NR vs. NR 0.045 16 events vs. 18 events 0.01 Parker et al., 2013 ALSYMPCA Radium-223-dichloride vs. placebo mCRPC 921 (614 vs. 307) 14.9 mo vs. 11.3 mo <0.001 15.6 mo vs. 9.8 mo <0.001 Smith et al., 2019 ERA 223 Radium-223-dichloride vs. placebo in addition to Abiraterone + prednisone mCRPC and bone met 806 (401 vs. 405) 30.7 mo vs. 33.3 mo 0.128 22.3 mo vs. 26.0 mo 0.2636 Sartor et al., 2021 VISION 177Lu-PSMA-617 plus standard care vs. standard care mCRPC 831 (551 vs. 280) 15.3 mo vs. 11.3 mo <0.001 11.5 mo 6.8 mo <0.001 * Or similar, e.g., median time to next symptomatic skeletal event, median symptomatic skeletal event-free survival. 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PMC10000417 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050652 healthcare-11-00652 Review Non-Surgical Therapy and Oral Microbiota Features in Peri-Implant Complications: A Brief Narrative Review Corsalini Massimo 1 Montagnani Monica 2 Charitos Ioannis Alexandros 3 Bottalico Lucrezia 4 Barile Giuseppe 1* Santacroce Luigi 1 Kanno Takahiro Academic Editor Giudice Amerigo Academic Editor 1 Interdisciplinary Department of Medicine, University of Bari "Aldo Moro", Policlinico University Hospital of Bari, p.zza G. Cesare 11, 70124 Bari, Italy 2 Department of Precision and Regenerative Medicine and Ionian Area, Section of Pharmacology, School of Medicine, University of Bari "Aldo Moro", Policlinico University Hospital of Bari, p.zza G. Cesare 11, 70124 Bari, Italy 3 Emergency/Urgent Department, National Poisoning Center, Riuniti University Hospital of Foggia, 71122 Foggia, Italy 4 Interdepartmental Research Center for Pre-Latin, Latin and Oriental Rights and Culture Studies (CEDICLO), University of Bari "A. Moro", 70124 Bari, Italy * Correspondence: [email protected] 23 2 2023 3 2023 11 5 65229 12 2022 18 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 therapeutic discretion in cases of peri-implantitis should take into account the limits and advantages of specific therapeutic itineraries tailored according to each clinical case and each individual patient. This type of oral pathology emphasizes the complex classification and diagnostic issues coupled with the need for targeted treatments, in light of the oral peri-implant microbiota changes. This review highlights the current indications for the non-surgical treatment of peri-implantitis, describing the specific therapeutic efficacy of different approaches and discussing the more appropriate application of single non-invasive therapies The non-surgical treatment choice with antiseptics or antibiotics (single or combined, local, or systemic) for short courses should be considered on a case-by-case basis to minimize the incidence of side effects and concomitantly avoid disease progression. infection immune response periodontitis peri-implantitis antibiotics oral microbiota This research received no external funding. pmc1. Introduction The term "peri-implant diseases" refers to the inflammatory reactions affecting the peri-implant soft and hard tissues, including two distinct nosologically entities, peri-implant mucositis and peri-implantitis. In 2008, mucositis was defined as inflammation of the peri-implant mucosa without loss of supporting bone tissue, and peri-implantitis as a condition characterized by inflammation of the peri-implant mucosa associated with loss of supporting bone tissue. Definitions were confirmed in the consensus reports of the Sixth and of the Seventh European Workshop of Periodontology . The reversible inflammatory reaction of the soft tissue surrounding an implant has been termed peri-implant mucositis. Instead, the term peri-implantitis refers to inflammatory processes accompanied by loss of supporting bone . Detection of peri-implant mucositis is carried out with a periodontal bur in the peri-implant fissure to detect bleeding or pyorrhea. Peri-implantitis defines an inflammation of the peri-implant tissues, such as mucositis, complicated by a radiographically detectable loss of the supporting bone. Its detection is performed by measuring the drilling depth of the peri-implant fissure and attachment loss . During the measurement, the existence of bleeding or pyorrhea is also evaluated. Infectious complications are one of the main causes of failure in implantology . Peri-implantitis in the last two decades seems to have become a major disease. The prevalence of this disease is unclear in the literature, and a recent systematic review and meta-analysis found that, on average, 19.5% of patients and 12.5% of implants had peri-implantitis. This evidence suggests that there is a high frequency of patients and implants that may be affected by this clinical condition. Hence, it suggests that booster and hygiene regimens need to be strengthened (particularly for patients with a clinical history of this disease) . Infections may originate from the local bacterial biofilm and then spread in tissues surrounding osseointegration implants, causing a reversible inflammatory reaction of the peri-implant soft tissues . During implant insertion procedures, mucositis manifests with a prevalence of 50%, and peri-implantitis of up to 40%. It should be considered that the implant does not behave like a totally bioinert material but triggers an immune reaction from the host . In fact, at the bone-implant interface, the presence of multinucleated giant cells and macrophages, which are pathognomonic of a foreign body reaction, is a common histological observation. Therefore, osseointegration would be based on the principle of foreign body equilibrium, making it essential in the treatment of peri-implantitis to eliminate the bacterial infection in order to arrest the progression of the lesion and, to whichever possible extent, to regenerate/re-osseointegrate the peri-implant bone lost . Indeed, antimicrobial therapies are often used in dentistry, both in therapeutic and in preventative regimens. Their therapeutic use focuses on the treatment of foci of inflammation in the hard or soft tissues of the oral cavity and most often are of endodontic/periodontal ethology . The preventative use of antimicrobics is to protect against the effects of dental procedures and subsequent triggered infections. Indeed, microbial infections are the main cause of peri-implantitis , and the topical preventative antiseptic and antibiotic therapy of preference should consist of formulations allowing a slow release and longer protection. This is of particular importance when considering that microbial infection in patients with dental implants may not only initiate local peri-implantitis but also spread to distant tissues where they can induce pathological conditions (such as endocarditis) and, potentially, evolve to a systemic clinical sepsis status . Special attention should be devoted to patients with immune-compromising conditions or neoplastic diseases such as leukemias and lymphoma, as well as in subjects undergoing radiotherapy to the head and neck. Early targeted antibiotic treatment can help to avoid peri-implant bone surgery, either of the resective, conservative, or regenerative type, with the latter becoming unavoidable when the bone loss is mainly horizontal and the lost tissue cannot regenerate. The following paragraphs deal with the main non-surgical treatments to date, with particular attention to the antibiotic use and efficacy for this oral pathology . 2. Pathogenesis of Peri-Implant Diseases Retrograde peri-implantitis occurs when the implant can fail due to overload, trauma, or occlusal factors. This overload occurs for four reasons, i.e., when (i) the bone in which it is located is of poor quality or of inadequate quantity, (ii) the implant is in a position such that the load is directed off axis (imbalanced distribution of occlusal forces) on the surface of the implant itself, (iii) the total number of implants is insufficient compared to the masticatory surface offered by the prosthetic superstructure, and (iv) the superstructure itself does not fit perfectly with the implants themselves . These reasons will lead to periapical bone resorption without the appearance of inflammation of the peri-implant soft tissues, and therefore it will lead to a clinical picture of retrograde peri-implantitis. It differs from infectious peri-implantitis due to its association with intrasulcular microbiota more consistently with gingival health status (which may be predominantly Streptococcus spp.). Infectious peri-implantitis is a manifestation of periodontitis at the implant level . These, in fact, are two diseases linked by the same clinical characteristics and the same etiological factor: the bacterial plaque. Implants have a less effective natural tissue barrier than natural teeth and are therefore less resistant to infection. This occurs for two reasons on the implant: (i) there is no cement and therefore there are also no collagen fiber insertions that run parallel and not perpendicular to the implant, and thus the only barrier that prevents the dissemination of microbes in the peri-implant sulcus is made up of circular fibers, and (ii) no biological seal (i.e., adhesion of epithelial cells via basement membrane and hemidesmosomes) develops between the soft tissues and the metallic implant surface so that the adaptation of the soft tissues to the implant surfaces would be more linked to the tone and proximity of the gingiva than to the presence of junctional epithelium attachment . Therefore, for these two reasons, microorganisms find an easier way to reach the implant surface directly. Subsequently, on its implant surface, the bacteria produce endotoxins capable of initiating an acute inflammatory response, which tends to progress more apically, involving the peri-implant alveolar bone more rapidly in the destructive process. Therefore, the reduced quantitative fibroblasts/collagen ratio and the scarce blood supply of this tissue causes a lower resistance of the peri-implant supraveolar connective tissue to progressive tissue destruction. Thus, it becomes obvious that before starting implant therapy, a patient with periodontitis must be treated until its remission . Thus, bacterial colonization of oral prosthetic and implant surfaces occurs through the formation of biofilms. Then, a stable aggregation of several microorganisms organized in a polysaccharide matrix develops to form a film adhering to a solid substrate. The biofilm represents an advantage for microorganisms (bacteria, etc.), making them more resistant to host defense mechanisms (such as phagocytes) but also to chemotherapy . The presence of biofilm at the level of the peri-implant sulcus is to be considered a physiological phenomenon, such as the biofilm present in the gingival sulcus of the teeth. For this reason, it is important to consider the differences between the microbiota residing in the peri-implant sulcus of a healthy implant and one affected by peri-implantitis as well as the factors responsible for the transformation of a physiological biofilm into a pathogenic biofilm . The oral microbiota (the largest composition of microorganisms, second only to the gut microbiota) is composed of over 700 different species of microbes, only half of which can be cultured by existing methods . Potentially pathogenic bacteria found in the oral cavity include Staphylococcus aureus, Streptococcus pyogenes, Streptococcus pneumoniae, Neisseria meningitidis, Haemophilus influenzae, Enterococcus faecalis, Enterobacteriaceae, and Actinomycetota phylum . The advancement of microbiological analysis techniques (following the introduction of next-generation sequencing (NGS)) has allowed more accurate analysis, overcoming the limits related to microbial culturing of species under investigation. These techniques have made it possible to identify specific periodontal pathogenic bacteria, mainly non-saccharolytic Gram-negative bacteria, associated with peri-implantitis. The NGS techniques demonstrated that microbiota in the peri-implant is different and less complex than the periodontal one, both in terms of health and disease . Anaerobic Gram-negative bacteria have been identified in the peri-implant fissures of healthy implants, thus suggesting that the periodontal and peri-implant fissure/pocket constitute different niches and ecosystems. However, even a simple microbiological test can have diagnostic importance, being functional to clinical observation and radiological examination. Thus, laboratory microbial analysis of the saliva (easy to collect) and peri-implant fluid may provide useful information on the levels of different inflammatory mediators secreted in the peri-implant fluid, especially when combined with clinical signs on the state of health or pathology of the peri-implant tissue and associated oral microbiota dysbiosis . The most sensitive biochemical markers include pro-inflammatory mediators such as interleukins-1b and -6, prostaglandin E2, aspartate aminotransferase, b-glucuronidase, elastase, myeloperoxidase, collagenase, and other metalloproteinases; glycosaminoglycans; and growth factors (such as TGF-b, PDGF, and TNF-a), among others . Contamination of a transgingival implant and/or prosthetic components occurs early in what has been defined as a "race to the surface" and is influenced by the presence or absence of teeth and periodontal pockets. Interaction between microorganisms and the surface does not in fact occur through direct contact but is always mediated by salivary glycoproteins. Thus, the first stage of biofilm formation is the adsorption of salivary glycoproteins on the implant surface . Protein adsorption is mainly influenced by various protein-surface interaction forces (such as Van der Waals, electrostatic, and hydrophobic forces). These proteins form a glycoprotein film on the surface that is capable of mediating the colonization of microorganisms. It contains lysozyme, histatin, staterin, amylase a, cystatin, secretory IgA, lactoferrin, and proline-rich proteins . Film proteins contain various amino acid sequences capable of binding adhesion molecules expressed by early colonizers (such as bacteria). The interactions between microorganisms and acquired film are initially due to weak interaction forces (Van der Waals forces), which are subsequently replaced by irreversible chemical bonds between bacterial adhesions and receptors of the acquired film. It has been demonstrated that the acquired pellicle proteins also play a role in the metabolism of the first bacteria that colonize the implant surface (such as Streptococcus oralis and Streptococcus mitis) . The metabolism of the first colonizing bacteria creates nutritional and environmental conditions more suitable for the subsequent colonizers, i.e., the late ones. Oxygen is gradually consumed by facultative aerobes and anaerobes favoring the development of late colonizers belonging to obligate anaerobic species such as Fusobacterium nucleatum, Tannerella forsythensis, Porphiromonas gingivalis, and Aggregatibacter actinomycete comitans . Therefore, the late colonizing microorganisms bind to the polysaccharide chains of the biofilm or to receptors present on the capsule of the pioneer bacteria. Subsequently, thanks to coaggregation mechanisms, the formation of horizontal and vertical stratifications begins, which are suitable for the growth and multiplication of different bacterial species . The result is the formation of a mature polymicrobial biofilm in which different species cohabit synergistically or antagonistically in a nutrient-rich polysaccharide matrix. The peri-implant bacteria most detected in a non-pathological condition are Gram-positive Cocci belonging to the group of Streptococci and Actinomyces, with a small presence of periodontopathogenic bacteria such as P. gingivalis, T. forsythia, P. intermedia, Aggregatibacter, and F. nucleatum . Under healthy conditions, the resident bacteria coexist with the host, and the onset of a pathology occurs only when exogenous or endogenous factors alter this equilibrium. Some studies have shown that contamination of the surface of the implant body can occur through direct contact of the fixture with soft tissues and/or oral fluids . Early implant contamination is particularly favored by contact with saliva, containing numerous adhesion proteins that favor the formation of an adhesion biofilm for bacteria (acquired biofilm) on the implant surface. However, it is unclear as to whether such initial contamination could be responsible for the early failure of an implant. Thus, a few hours after surgical placement, a layer of glycoproteins develops on the implant surface, subsequently colonized by microorganisms. During the 3-week period of plaque accumulation, the periodontal and peri-implant soft tissues develop an inflammatory infiltrate similar in composition, volume, and distance from the bone tissue. If the period of plaque accumulation is longer (3 months), the peri-implant inflammatory infiltrate, composed by plasma cells, lymphocytes, and other immune cells, is greater than the periodontal one both apically and laterally to the junctional epithelium . Numerous surveys underline a great similarity between the microorganisms found in peri-implant and in periodontal lesions . However, the local oral microbiota of peri-implantitis differs from that of periodontitis, whose composition may also depend on the patient's systemic diseases . Among the microorganisms found are Peptostreptococcus micros, Fusobacterium Nucleatum, Prevotella intermedia, and Wolinella recta. Changes in the oral microbiota around the implant shift the composition of local microorganisms leading to the predominance of Gram-anaerobic microbes . Aggregatibacter actinomycetemcomitans, Tannerela Forsythia, Treponema Denticola, and also Staphylococcus aureus and Enterococci spp. are frequently isolated from peri-implant lesions , together with Campylobacter rectus, Eikenella corrodens, strains of the genus Capnocytophaga, and fungi of the genus Candida, all detectable in peri-implant pockets . Interestingly, trains of the genus Staphylococcus and Pseudomonas are found not only around dental implants but also on the surfaces of other implant materials, such as those used in hip arthroplasty. In a prospective study, implants were placed and monitored weekly for four months with microbiological investigation control from the peri-implant fissure to identify the developmental diversity of the local oral microbial population . The results showed an increased number of anaerobic microbes as early as the second week. At third week, an increase in the number of rod-shaped bacteria was observed with a corresponding decrease in Cocci bacteria. After six weeks, microbes of the Fusobacterium genus were detected, while at four months, Spirochetes spp. were also present in the peri-implant gap, with clinical signs of a 6 mm cyst and purulent exudate . In another study, comparing healthy and successful implants with respect to failed implants (with pocket depths > 6 mm and bone reduction), it was found that healthy implants had a small concentration of microbes and a minor presence of rod-shaped microbes, while implants that led to failure were characterized by a high percentage of Gram-microbes, with a strong presence of Spirochaetes spp. and rod-shaped bacteria . Since microbial infection is a primary cause of peri-implantitis, oral hygiene is an absolute requirement. When oral hygiene is interrupted for a few days, the undisturbed accumulation of microbial plaque around implants leads to inflammation of the surrounding soft tissue. This process can be facilitated by certain risk factors and comorbidities . It has been observed that the association of periodontitis with other risk factors, such as diabetes mellitus and smoking, increases the risk of peri-implantitis and implant loss . Moreover, the genetic polymorphism linked to allele 2 of the IL1-RN gene, resulting in a greater production of IL1 during the inflammatory response of the subject (IL1 positive genotype), has been proposed as a susceptibility condition for the development of peri-implantitis. In retrospective studies, a greater loss of peri-implant bone has been observed in subjects with IL1-positive genotype and associated smoking . With the removal of the microorganisms (bacteria, fungi), inflammation subsides, and tissue health is restored to the area. In the presence of ligatures maintained for 6 weeks, and even after ligature removal, soft tissue inflammation and bone destruction are more marked at the implant sites. With respect to periodontal sites, where infiltrates are never in contact with the alveolar bone, the peri-implant infiltrate extends to the bone tissue (osteitis), and the osteoclasts--an expression of greater bone resorption--are more represented. Maintaining bone-level stability around an implant is a necessary requirement for successful post-implant repair . 3. Diagnostic Evidence of Peri-Implantitis As briefly anticipated, the synergy between microbiological results and early detection of clinical signs can be of fundamental importance for the diagnosis and the prognostic outcome of peri-implantitis . At present, a unifying criterion for the diagnosis of peri-implantitis based on the calculation of the loss on the peri-implant bone support is not considered feasible, since the bone remodeling that leads to the resorption of the cervical bone of the implant in the most apical area is a pathophysiological event naturally occurring after an implant placement. For this reason, each proposed diagnostic method is based on specific criteria . Vertical bone loss of less than 1.5 mm in the first year after implant placement and less than 0.2 mm in each subsequent year was one of the first criteria used to characterize an implant as successful . More recently, an attempt has been made to classify peri-implantitis in the context of epidemiological studies investigating risk factors and causes of implant failure . The way in which to measure the depth of the peri-implant fissure or pocket is also determinant in the diagnosis of peri-implant disease mucositis or peri-implantitis. In peri-implantitis, the severity of the disease and its classification as an initial or advanced form leads to different prognostic conclusions . As an example, during measurement within follicles with peri-implant disease, the tip of the molar ends very closely to the bone edge (less than 0.5 mm away), while in healthy peri-implant spaces, the distance measured from the bone is in between 0.5 and 1.5 mm . In several studies, the presence of peri-implantitis was considered only in cases with radiographically detected vertical loss of peri-implant bone, measured from the fixed points of the implants. The more correct diagnosis, however, would come from radiographical comparison of the implant at two subsequent time intervals in which the loss of the peri-implant bone is evident, bearing in mind that a certain absorption of the tissue bone should be considered normal . Clinically, it is possible to detect soft tissue subsidence around an implant, whose presence in the anterior area can create an aesthetic problem . In a study conducted on the correlation of the depth of the peri-implant pocket with the peri-implant bone loss, measurements were performed with and without prosthetic restoration. The level of bone around the implants can be significantly correlated with the existence of keratinized mucosa and with the appearance of pyorrhea from the peri-implant fissure. The absence of bleeding on palpation with a periodontal probe has significant prognostic value on the healthy state of periodontal tissues . Conversely, the presence of bleeding, especially if combined with positive microbiological assessment, can be an indication of disease progression. Finally, in another study, a more detailed evaluation, according to bone morphology damage around the implant, was added to the assessment of vertical loss tissues. This additional categorization describes the damage at two levels, horizontal (category I) and vertical (category II). The horizontal category I can have three further sub-categories when the buccal bone wall (a) is absent without a circular peri-implant bone loss (class Ib), (b) is absent with a circular peri-implant bone loss (class Ic), and (c) when loss occurs around the implant (class Ie) . Similar to this, another categorization of peri-implantitis classifies the type of bone damage surrounding implants as follows: (a) circular crater bone lesion with four bony walls; (b) circular crater bone lesion with three bony walls; (c) circular crater bone lesion with two bony walls; (d) circular lesion resembling a bone crater with a bony wall; (e) bone damage with cleft defect on an implant surface; and (f) in case there is no bone wall around the implant, bone loss is characterized as horizontal . 4. The Non-Surgical Peri-Implantitis Treatment In general, on the basis of the evaluation of the fundamental diagnostic parameters for peri-implantitis, it is possible to proceed with the adoption of the CIST (Cumulative Interceptive Supportive Therapy) therapeutic protocol to prevent and/or block the development of peri-implant lesions. It is a cumulative protocol because it consists of five specific pathways associated in sequence with an increasing antibacterial potential proportional to the severity and extent of the lesion: mechanical detoxification (A), antiseptic therapy (B), antibiotic therapy (C), surgical therapy (D), and explant (E) . 4.1. Mechanical Debridement The treatment of peri-implantitis (the same as periodontitis) is divided into two main categories (non-surgical and surgical treatment), which further include various therapeutic techniques. The non-surgical approach to peri-implantitis consists of a synergy of procedures summarized in Figure 5 . Mechanical debridement aims to remove microbes, soft and hard chemical deposits from the implant surfaces, and smooth/polish these surfaces mechanically. The removal of the microorganisms favors the inflammation subsiding, allowing tissue health restoration and ameliorating the eradicating effects of local or systemic antibiotic treatment . Curettes are the basic treatment for the removal of tartar and plaque deposits from the implant surface, being performed manually with instruments made of different materials. Titanium-coated curettes have similar hardness to the implant surface and therefore are not dangerous for the implant itself. Carbon fiber curettes are used to remove bacterial deposits without damaging the implant surface. Teflon curettes share the same characteristics and are often proposed in combination with air/polishing systems. Plastic curettes have the most limited debriding capacity . Alternative methods employ equipment based on concepts of vibrational frequencies in which the working part oscillates at sonic or ultrasonic frequencies. The sonic ones are instruments provided with a compressed air handpiece, wherein the air pressure mechanically creates vibrations (2500-6300 cycles/s, 6-8 kHz) or oscillation (50-200). The ultrasonic instruments are characterized by different vibration parameters (25,000-42,000 cycles/s, 25-42 kHz). At these frequencies, heat is produced, and therefore cooling is required. They may have a direct or indirect (cavitation) action and a cleansing effect . 4.2. Non-Ionizing Radiation Sources The laser is a device emitting a coherent, monochromatic, and concentrated straight beam of light that is extremely collimated. In a bactericidal modality, CO2, diode, erbium-doped yttrium aluminum garnet laser (Er: YAG), and erbium chromium-doped yttrium scandium gallium garnet (Er, Cr: YSGG) lasers are used in the treatment of peri-implant diseases with increasing frequency. Compared to mechanical debridement with the plastic curettes, the use of Er: Yag has led to significantly better results in terms of bleeding index. Although there are some data in contrast, laser therapy should be considered as an adjuvant rather than a treatment option. Further studies are needed to evaluate the clinical efficacy of laser therapy as a treatment for peri-implantitis . Photodynamic therapy (PDT) generates reactive oxygen species with the aid of high-energy single frequency light, for example, a laser diode (wave 580-1400 nm), in combination with photosensitizers (such as toluidine blue concentration between 10 and 50 mg/mL). This type of treatment generates bactericidal effects against aerobic and anaerobic bacteria (such as Aggregatibacter Actinomycetemcomitans, P. gingivalis, P. intermedia, S. mutans, and Enterococcus Faecalis) . 4.3. Antiseptics Slow-release antibacterial agents include chlorhexidine, indicated for the adjunctive topical and antimicrobial treatment of both moderate-to-severe adult periodontitis and peri-implantitis . Chlorhexidine can be used as a mouthwash at 0.12% as a bacteriostatic and at 0.2% as a bactericide. Chlorhexidine gel xanthan is a product indicated for the topical treatment of periodontitis and peri-implantitis. The gel may have 1.5% or 0.5% chlorhexidine in the rapid-release digluclonate form (high concentration in the first 24 h and continuous release for approximately fifteen more days), and 1% in the slow-release dichlorhydric form. The use of this antiseptic agent (0.1-0.2% chlorhexidine digluconate) is indicated for a period of 3-4 weeks, with additional local lavage with 0.1-0.5% chlorhexidine solution or local application of 1% chlorhexidine gel, and should be accompanied by the simultaneous repetition of the oral hygiene instructions . While for shallow peri-implant pockets (<4 mm), the sole use of mechanical techniques might be sufficient, the combined application of a 0.2% chlorhexidine solution may provide advantages in the treatment of deep (>5 mm) peri-implant pockets. Thus, chlorhexidine can be useful in all peri-implant pockets and also when the patient presents an epi-implant plaque, bleeding on detection, possible effusion (unnecessary), deep peri-implant pockets (>5 mm), and radiographically visible peri-implant bone loss. The final step required, after cleaning the implant surface area with mechanical debridement and the use of antiseptics, should be the use of antibiotics (with local application or systemic administration). 4.4. Antibiotics Antibiotics are mostly derived from living organisms such as bacteria and fungi, while only a few are of synthetic or semi-synthetic origin. These drugs are used to enhance the antibacterial effect of mechanical debridement and to prevent bacterial recolonization of the implant surface . Antibiotics can be administered topically (gel or microspheres with slow release) or systemically (oral or injective routes). Topical antibiotic administration allows for the selection of the sites to be treated by prolonging contact with the pathogen and to maintain a concentration adequate and constant over time, whereas systemic administration should be performed to reach sites that would normally be inaccessible . As emerged from the systematic reviews to date, no randomized controlled clinical trials have been carried out reporting the systemic administration of antibiotics as adjunctive therapeutic agents to the use of mechanical or antiseptic/local antibiotics for the non-surgical treatment of peri-implantitis . As for the topical antiseptic therapy, the antibiotic treatment indicated more in peri-implantitis should be characterized by a slow-release formulation to maintain the efficacy in the pocket . Metronidazole is a derivative of 5-nitroimidazole. When the nitro group is reduced to reactive radical species, these radicals react with cellular components such as DNA or protein. On the basis of metronidazole's mechanism of action, the metronidazole-based film products are especially active on Gram-negative anaerobic bacteria. These products consist of an absorbable gel containing 25% metronidazole benzoate in a matrix made of a mixture of glyceryl-mono-oleate and oil of sesame . The decay of the antibiotic (release is effective over a time frame ranging from 24 to 36 h) and the concentration in the peri-implant pocket follow an exponential trend. The application can be repeated once a week. Several studies have reported additional benefits from combination with topical slow-release doxycycline or the placement of tetracycline fibers within peri-implant pockets. Tetracyclines' antimicrobial activity results from drug binding to the 30S subunit of the ribosome in susceptible bacteria, with subsequent interference with bacterial protein synthesis. Tetracycline preparations contain broad-spectrum antibiotics effective against anaerobic organisms and facultative anaerobes with a high capacity to bind to the dentin, favoring maintenance of the antibacterial action over time . Generally, the active principle tetracycline is contained in cellulose acetate fibers, polyacrylic acid strips, collagen preparations, and hydroxypropyl cellulose films with poly(methacrylic acid). The most used system is based on cellulose fibers loaded with tetracycline hydrochloride, to be inserted into the pocket. One topical application of tetracyclines consists of fibers of ethylene-vinyl-acetate containing 25% (weight/volume) of tetracycline hydrochloride. The fibers are wrapped around the implant in several concentric layers until the peri-implant space is totally filled; once the placement is completed, an isobutyl-cyanoacrylate adhesive is applied to the mucosal margin to fix the fibers. In case of fiber loss during the seven days following placement, other fibers can be applied. The fibers are usually removed after 10 days . Doxycycline, another tetracycline, is applied directly in the form of gel to infected sites. This formulation provides very high antibiotic concentrations with a duration of up to seven days. Typically, the application kit consists of two syringes, one containing the polymer liquid, the other the antibiotic powder. Treatment with chlorhexidine gel or mechanical therapy and subsequent slow-release doxycycline polymer improves healing more significantly than mechanical therapy alone . Products based on minocycline, a broad-spectrum antibiotic of the tetracycline class, are active against Gram-negative and Gram-positive bacteria . The topical application of minocycline microspheres improves the therapeutic effect more than the topical application of chlorhexidine gel in incipient or intermediate peri-implant cysts, while the additional efficacy of topical application of minocycline in deep (>5 mm) peri-implant pockets is not clear . This formulation consists of granules of different sizes of polymer with active principle microencapsulated and is administered subgingivally after scaling; the release takes place in the crevicular fluid, and detectable drug levels persist for at least fourteen days and they are completely bioabsorbable. Another topical aid for the treatment of peri-implantitis is based on the treatment with minocycline in biodegradable microspheres combined with mechanical debridement, being able to improve clinical parameters at 12 months follow-up . Penicillines inhibit the biosynthesis of the mucoproteins constituting the cell wall of susceptible bacteria by interacting with the so-called penicillin-binding proteins (PBP). Slow-release, piperacillin-based antibacterials are available as fluid-alcohol-based solutions containing 12% acrylic resins and 10% piperacillin sodium. Piperacillin has a spectrum of activity that includes Gram-positive and Gram-negative bacteria. The product solidifies rapidly after application, creating a protective film (made up of the two polymers) by evaporation of the organic solvent (ethyl alcohol). The distinctive feature of this film is to release the antibiotic in a controlled way (piperacillin sodium), with it remaining inside the resins after evaporation of the organic solvent . These resins are permeable and insoluble to water, and this feature allows for the formation and permanence of the film in the oral cavity where it is maintained for 7-10 days with the release of piperacillin sodium. The beneficial effects of systemic antibiotic administration (such as metronidazole 250 mg twice a day or clavulanic acid 500 mg twice a day/10 days) in peri-implantitis, with the exception of possible abscess episodes, still remains uncertain. The most used with beneficial effects of systemic antibiotic administration are those based on metronidazole (3 x 350 mg or 2 x 250 mg per day) or a combination of metronidazole (500 mg per day) and amoxicillin (375 mg per day) during the last 10 days of therapy. Another antibiotic that can be administered is ornidazole (2 x 500 mg per day) or clavulanic acid (500 mg twice a day/10 days). Therefore, when peri-implantitis is localized and is not accompanied by a widespread periodontal problem with the presence of other infected sites, the use of local antibiotics takes place. These must remain in situ (at least 7-10 days) in concentrations in order to penetrate the biofilm of the submucosa so they have good antimicrobial efficacy as, for example, occurs with tetracycline fibers . Although topical application of antibiotics may offer hypothetical additional benefits, in the non-surgical treatment of peri-implantitis, some points still need to be clarified: for example, the depth of the peri-implant pockets that should indicate whether or not topical antibiotic treatment should be used is still an unresolved question. Consequently, the synergy of microbiological and clinical signs can be useful for the diagnosis and prognosis of peri-implantitis. Therefore, before deciding to treat peri-implantitis with adjunctive antibiotic therapy, the microbiological research and analysis may provide valuable information to guide on the selection of the appropriate antibiotic drug, route of administration, and antibiotic regimen. However, the continuous emergence of antibiotic-resistant bacterial species makes it necessary to limit the use of antibiotics in periodontal therapy . However, microbiological examination alone can be considered a diagnostic method because it serves clinical observation and radiological examination. Thus, laboratory microbial research analysis of the saliva (is easier to collect) and peri-implant fluid can investigate the possible correlation between the levels of different of biochemical markers of inflammation (inflammatory mediators) secreted in the peri-implant fluid with clinical signs that indicate the state of health of the peri-implant tissue and its pathological changes, together with the oral microbiota dysbiosis . The biochemical markers are pro-inflammatory mediators (interleukins-1b and -6, prostaglandin E2), aspartate aminotransferase, b-glucuronidase, elastase, myeloperoxidase, collagenase, various other metalloproteinases, glycosaminoglycans, and growth factors (i.e., TGF-b, PDGF, TNF-a), among others . 5. Conclusions For correct management of the prosthetic implant, the most important tool to apply is prevention. This starts right from the beginning of the drafting of the prosthetic implant rehabilitation plan. The correct design of the prosthesis must avoid occlusal overloads that can alter the bone-implant interface. Another factor would be the elimination or reduction of the various risk factors (for example smoking) with effective and regular professional and home oral hygiene interventions. In non-surgical therapy, the combination of mechanical cleaning techniques and air polishing systems may be recommended together in the short term with the aid of antiseptics or antibiotics (systemic or local). These procedures are effective for bacterial load reduction in combination with the other techniques. However, long-term benefit results of these techniques are still scarce. Moreover, on the basis of available data, non-surgical therapy of peri-implantitis may be not effective in resolving the disease, as only limited improvements have been reported in the main clinical parameters and there is a clear tendency towards recurrence. In part, this may depend on the stage of the disease at the time of diagnosis, or insufficient care on prevention procedures (including oral hygiene). For all these cases, it is recommended to consider advanced therapies, including surgical procedures, when non-surgical peri-implant therapy is unable to achieve significant improvements in clinical parameters. In cases where the use of antibiotics is considered necessary, local application is the first option when the pathological condition is localized, as the systemic administration in these cases may lead to exposure to unnecessary side effects. On the other hand, more complicated and recurrent conditions may require systemic administration on the basis of the more appropriate antibiotic choice in light of the mechanism of action and individual patient's characteristics. In this context, development of reliable biochemical assays would greatly enhance the diagnosis and follow-up of periodontitis or peri-implantitis progression. Finally, since local oral microbiota dysbiosis has been indicated as an important contributor to peri-implant inflammation, further studies should consider this additional aspect. Author Contributions Conceptualization, M.C. and L.S.; methodology, M.M.; validation, L.S.; formal analysis, M.M.; investigation, M.M., L.B. and I.A.C.; resources, G.B. and I.A.C.; data curation, G.B. and L.B.; writing--original draft preparation, M.M. and I.A.C.; writing--review and editing, L.B. and G.B.; visualization, M.C.; supervision, L.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement As a review, this study did not require ethical approval. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The clinical signs among peri-implantitis and peri-implant mucositis (in red are the common clinical features). Figure 2 According to the most widespread and thus far most documented theory, bacterial colonization of the implant surface represents the primary etiological factor of peri-implantitis. Different microbial species, in particular, Gram-negative anaerobes, would be at the basis of the development and progression of peri-implantitis . Figure 3 The main microorganisms found in peri-implant lesions . Figure 4 Implant failure risk can be early or late. Early implant failure, due to lack of osseointegration, may be attributable to factors not related to susceptibility to periodontitis, such as overheating of the bone > 47deg during the preparation of the implant site, with consequent peri-implant bone necrosis, an early infection, a lack of primary stability, or early mechanical overload. Late implant failure, once osseointegration has taken place, can be of a biomechanical, aesthetic, or biological nature. The major contraindications relating to the implant may be insulin-dependent diabetes, osteoporosis, heart disease, pregnancy and breastfeeding, acute articular rheumatism, trigeminal neuralgia, or bruxism . Figure 5 Summary of the non-surgical peri-implantitis treatments. Figure 6 The types of antibiotics most commonly used in the case of an oral implant infection. 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. Lin G.H. Kapila Y. Wang H.L. Parameters to Define Peri-Implantitis: A Review and a Proposed Multi-Domain Scale J. Oral Implantol. 2017 43 491 496 10.1563/aaid-joi-D-17-00035 28873021 2. Kwon T. Wang C.W. Salem D.M. Levin L. 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PMC10000418 | Tumor hypoxia can seriously impede the effectiveness of photodynamic therapy (PDT). To address this issue, two approaches, termed in situ oxygen generation and oxygen delivery, were developed. The in situ oxygen generation method uses catalysts such as catalase to decompose excess H2O2 produced by tumors. It offers specificity for tumors, but its effectiveness is limited by the low H2O2 concentration often present in tumors. The oxygen delivery strategy relies on the high oxygen solubility of perfluorocarbon, etc., to transport oxygen. It is effective, but lacks tumor specificity. In an effort to integrate the merits of the two approaches, we designed a multifunctional nanoemulsion system named CCIPN and prepared it using a sonication-phase inversion composition-sonication method with orthogonal optimization. CCIPN included catalase, the methyl ester of 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO-Me), photosensitizer IR780, and perfluoropolyether. Perfluoropolyether may reserve the oxygen generated by catalase within the same nanoformulation for PDT. CCIPN contained spherical droplets below 100 nm and showed reasonable cytocompatibility. It presented a stronger ability to generate cytotoxic reactive oxygen species and consequently destroy tumor cells upon light irradiation, in comparison with its counterpart without catalase or perfluoropolyether. This study contributes to the design and preparation of oxygen-supplementing PDT nanomaterials. hypoxia nanoemulsion photodynamic therapy tumor National Natural Science Foundation of China32160224 12132006 Guizhou Provincial Science and Technology ProjectsZK 349 2021-5637 ZK2021-029 ZK2022-397 Youth Science and Technology Talents Growth Project of Guizhou Ordinary Colleges and UniversitiesKY 220 Science and Technology Fund Project of Guizhou Provincial Health Commissiongzwkj2022-228 gzwkj2022-444 Excellent Young Talents Plan of Guizhou Medical University2021-101 Cultivation Project for National Natural Science Foundation of China21NSFCP38 High-Level Talent Initiation Project of Guizhou Medical UniversityJ 029 This research was funded by the National Natural Science Foundation of China (32160224, 12132006), the Guizhou Provincial Science and Technology Projects (ZK 349, 2021-5637, ZK2021-029, ZK2022-397), the Youth Science and Technology Talents Growth Project of Guizhou Ordinary Colleges and Universities (KY 220), the Science and Technology Fund Project of Guizhou Provincial Health Commission (gzwkj2022-228, gzwkj2022-444), the Excellent Young Talents Plan of Guizhou Medical University (2021-101), the Cultivation Project for National Natural Science Foundation of China (21NSFCP38), the High-Level Talent Initiation Project of Guizhou Medical University (J 029). pmc1. Introduction Photodynamic therapy (PDT) has been recognized as a promising modality to treat tumors. Typically, PDT utilizes the toxic reactive oxygen species (ROS) converted from the oxygen molecules surrounding the photosensitizers under light irradiation to kill cancer cells . Owing to the unique characteristics of light, PDT has a high tumor-targeting ability, low side effects, and low invasiveness, which are favorable properties for tumor treatments . Photosensitizers can be innovated to obtain functions, such as targeting oncogenic mutations , targeting epigenetic alterations , and targeting tumors with molecules that are required for cancer growth , which can improve the anti-cancer effect. Despite their valuable properties, the efficiency of photosensitizers in converting oxygen to cytotoxic ROS is seriously limited by the hypoxic state during the PDT treatment process. On the one hand, the tumor microenvironment is innately hypoxic due to the rapid tumor cell proliferation and abnormal tumor blood vessels . On the other hand, the PDT reaction consumes oxygen, which exacerbates hypoxia . Therefore, it is critical to overcome hypoxia for the purpose of improving PDT efficiency. Moreover, it has also been recognized that hypoxia promotes tumor metastasis and resistance to treatment methods including chemotherapy, radiotherapy, and immunotherapy . Therefore, alleviation of the hypoxic state might also improve the therapeutic effect of these therapies if they are combined with PDT . To address hypoxia in PDT, many strategies based on innovative material preparation have been developed. The oxygen-supplementing strategy has attracted wide attention owing to its ability to alter the hypoxic tumor microenvironment and, thereby, its potential to inhibit tumor metastasis. The oxygen-supplementing strategy can be categorized briefly into two methods: in situ oxygen generation and oxygen delivery. The in situ oxygen generation method uses catalase or metal-based catalysts to accelerate the decomposition of tumor-overproduced hydrogen peroxide (H2O2) into oxygen . The other strategy, oxygen delivery, relies on materials having high oxygen solubility, such as perfluorocarbon and hemoglobin, to transport oxygen and gather oxygen around photosensitizer molecules . Perfluorocarbons have intrinsically higher oxygen loading efficiency than hemoglobin-based formulations. Under 1 atm at 25 degC, 40-50 mL oxygen can be loaded by 100 mL of perfluorocarbon, while only ~20 mL oxygen could be solubilized by 100 mL of blood (hemoglobin concentration 150 g L-1, pO2 ~159 mmHg) . The in situ oxygen generation strategy and oxygen delivery strategy have their own strengths and shortcomings. The in situ oxygen generation strategy offers high tumor specificity because the level of H2O2 in the tumor site is higher than that in normal tissue. However, the tumor H2O2 level (<100 mM) is still too low to generate adequate oxygen for PDT . In contrast, the oxygen delivery strategy possesses no intrinsic tumor specificity, but can supply plenty of oxygen molecules and be used as an efficient oxygen reservoir. In this context, herein we designed and prepared a multifunctional nanoemulsion system, aiming at integrating the merits of the in situ oxygen generation strategy and oxygen delivery strategy. This multifunctional nanoemulsion system contains catalase, a synthetic triterpenoid the methyl ester of 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO-Me), photosensitizer IR780, and perfluoropolyether. It is named the catalase-CDDO-Me-IR780-perfluoropolyether nanoemulsion, and abbreviated as CCIPN. When delivered to tumor cells via an enhanced permeability and retention (EPR) effect and/or nanomaterial-induced endothelial leakiness (NanoEL) effect , CCIPN could achieve a cascade effect. The catalase decomposes the tumor-overproduced H2O2 into oxygen, and the oxygen is then reserved in the perfluoropolyether for PDT. CCIPN combines the tumor specificity of the in situ oxygen generation strategy and the high efficiency of the oxygen delivery strategy. Moreover, CDDO-Me has been reported to remodel the immunosuppressive tumor microenvironment and enhance the therapeutic efficacy of immunotherapy . Therefore, the CDDO-Me loaded within CCIPN might boost the antitumor immune response of the body, and provides CCIPN with the potential to be synergized with immunotherapy. To prepare CCIPN, we used a sonication-phase inversion composition-sonication (S-PIC-S) method that we developed by advancing our previous sonication and phase-inversion composition (SPIC) method . The S-PIC-S method could further reduce the production droplet size while retaining the advantage of environment-sensitive substance (herein, IR780) protection . The preparation process of the S-PIC-S method was optimized by orthogonal tests in terms of system compositions and operation parameters. Afterwards, the properties of CCIPN were investigated. In addition, the cytocompatibility and the ability of CCIPN to generate ROS and kill cancer cells were evaluated in vitro. This research provides insights into the rational design and convenient preparation of oxygen-supplementing nanoemulsion systems for PDT and possible combined PDT and immunotherapy. 2. Materials and Methods 2.1. Materials IR780 iodide (purity >= 95.0%) was purchased from Bellingway Technology Co., Ltd. (Beijing, China). Bardoxolone methyl (CDDO-Me) and perfluoropolyether with molecular weight 6000 (PFPE MW 6000) were purchased from Maclean Biochemical Technology Co., Ltd. (Shanghai, China). Catalase (CAT, 2000-5000 units/mg protein) from bovine liver was obtained from Sigma-Aldrich(r) (Shanghai, China). Minimum essential medium (MEM), Ham's F-12K medium, Dulbecco's Modified Eagle Medium (DMEM), fetal bovine serum (FBS), and Tween 20 and acetonitrile (purity >= 99.9%) were purchased from Chaoyuan Zhicheng Biotechnologies Co., Ltd. (Guiyang, China). Fomblin(r) Y (MW 1800), 1H-tridecafluorohexane (MW 320.05), perfluorooctane (MW 438.06), and 1-bromoheptadecafluorooctane (MW 498.96) were purchased from Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). Syringe filters with a pore size of 0.22 mm and 0.45 mm (PTFE hydrophilic) were purchased from Navigator Lab Instrument Co., Ltd. (Tianjin, China). Deionized water was produced by ELGA VEOLIA (Veolia Water Solutions & Technologies, Shanghai, China). 2.2. Selection of Perfluorocarbon Type for CCIPN To investigate the influence of the perfluorocarbon type on the droplet diameter and IR780 EE, five diverse perfluorocarbons (Fomblin(r) Y, 1H-tridecafluorohexane, perfluorooctane, 1-bromoheptadecafluorooctane, and PFPE MW 6000) were used to produce nanoemulsions with similar total compositions (3.6 mL PBS containing 16 mg CAT, 0.28 g surfactant [Tween 20], 0.12 g perfluorocarbon, 4 mg IR780, and 2 mg CDDO-Me) using the SPIC method. Primarily, a multipoint magnetic stirrer (CJB-S-10D, Yuming Instrument equipment Co., Ltd., Shanghai, China) was used to stir the aforementioned mixture for 10 min (750 r min-1). The bottle containing the mixture was then partly submerged in water and bath-sonicated for 20 min utilizing ultrasonic cleaning equipment (SB-4200D, Xinzhi Biotechnology Co., Ltd., Ningbo, China). Afterwards, a multipoint magnetic stirrer was employed to stir the mixture in the bottle for 20 min (750 r min-1). The water phase (3.6 mL PBS, pH 7.4 containing 16 mg CAT) was then titrated into the mixture with a peristaltic pump (BT100J-1A, Huiyu Weiye Fluid Equipment Co., Ltd., Beijing, China) when the mixture was continuously agitated at 750 r min-1. The rotation speed of the peristaltic pump was set as 22.0 rpm, and the titration rate was approximately one drop every 3 s. When the process of adding the water phase was finished, agitation proceeded for 30 min. The product was then centrifuged for 3 min (3000 r min-1) using a centrifuge (H1650-W, Xiangyi Centrifuge Instrument Co., Ltd., Changsha, China). Finally, 3 mL supernatant was taken and filtered with firstly 0.45 mm and then 0.22 mm syringe filters. A UV-visible spectrophotometer (A360, Aoyi Instruments Co., Ltd., Shanghai, China) was utilized to measure the absorbance at 793 nm (i.e., absorption peak value of IR780 emulsions). A Brookhaven 90 Plus PALS dynamic light scattering (DLS) machine (Brookhaven Instruments Corporation, Holtsville, NY, USA) was used to detect the mean droplet size at room temperature. A standard curve for the relationship between the IR780 concentration and absorbance at 793 nm was established and used to calculate the IR780 concentration and subsequently the IR780 EE. An acetonitrile solution of 2 mg mL-1 IR780 was diluted for the standard curve by preparing a gradient of IR780 concentration with 0.0013, 0.002, 0.0027, 0.0033, and 0.004 mg mL-1. The IR780 EE of CCIPN can be calculated from Equation (1):(1) EE(%)=100%xCtV/m where Ct is the tested IR780 concentration, V is the volume of the system (in Section 2.2, 4 mL and in other sections, 10 mL), and m is the weight of initially used IR780. 2.3. Determination of Added CDDO-Me Amount and CAT Distribution Ratio for CCIPN Unless otherwise stated, the emulsion was prepared in the following way using the SPIC method. First, a multipoint magnetic stirrer was used to stir the organic phase consisting of Fomblin(r) Y (0.3 g), Tween 20 (0.7 g), IR780 (10 mg), and CDDO-Me (5 mg) for 10 min (750 r min-1). The bottle containing the organic phase was then partly submerged in water and sonicated for 20 min utilizing ultrasonic cleaning equipment (SB-4200D, Xinzhi Biotechnology Co., Ltd., Ningbo, China). Afterwards, the multipoint magnetic stirrer was used to stir the organic phase for 20 min (750 r min-1). After this, the water phase (9 mL PBS, pH 7.4 containing 40 mg CAT) was titrated into the organic phase at ~1 drop every 3 s (pump rotation speed 22.0 rpm) with a ristaltic pump (BT100J-1A, Huiyu Weiye Fluid Equipment Co., Ltd., Beijing, China) while the organic phase was under continual agitation (750 r min-1). When the process of adding the water phase was finished, agitation was continued for 30 min. Then, the emulsion was centrifuged for 3 min (3000 r min-1) using a centrifuge (H1650-W, Xiangyi Centrifuge Instrument Co., Ltd., Changsha, China). Finally, 3 mL supernatant was taken and filtered using firstly 0.45 mm and then 0.22 mm syringe filters. The production process was conducted at 25 degC. In some assays, certain parameters were changed to explore their influence on the size of the droplet and IR780 EE prepared by the abovementioned method. 2.3.1. Effect of Added CDDO-Me Amount on Droplet Size and IR780 EE The influence of the added CDDO-Me amount on the droplet diameter and IR780 EE of CCIPN was explored by varying the amount (0, 1, 2, or 5 mg) of CDDO-Me added to the 10 mL system. 2.3.2. Effect of CAT Distribution on Droplet Size and IR780 EE The effect of CAT distribution on the droplet diameter and IR780 EE was examined by altering the organic-phase-to-aqueous-phase ratio of CAT (0, 1:3 or 1:1) when the total CAT amount was set as 40 mg. The diverse organic-phase-to-aqueous-phase ratios were achieved by adding a certain amount of CAT to the organic phase in the beginning of the preparation process. 2.4. Orthogonal Optimization for Preparation of CCIPN Using S-PIC-S Method During all the orthogonal assays, the weight of CDDO-Me added was 1 mg, and the organic-phase-to-aqueous-phase ratio of CAT was 1:3. The CCIPNs were prepared using the S-PIC-S method as follows. First, a multipoint magnetic stirrer was used to agitate the organic phase consisting of Fomblin(r) Y (0.3 g), Tween 20 (0.7 g), IR780 (10 mg), CDDO-Me (1 mg) and CAT (certain amount) for 10 min (750 r min-1) at 25 degC. The bottle containing the organic phase was then partly submerged in water and bath-sonicated for 20 min utilizing ultrasonic cleaning equipment (SB-4200D, Xinzhi Biotechnology Co., Ltd., Ningbo, China). Afterwards, the multipoint magnetic stirrer was used to stir the organic phase for 20 min (750 r min-1). Then, the water phase (9 mL PBS, pH 7.4 containing a certain amount of CAT) was added into the organic phase at ~1 drop every 3 seconds (pump rotation speed 22.0 rpm) with a peristaltic pump (BT100J-1A, Huiyu Weiye Fluid Equipment Co., Ltd., Beijing, China) when the organic phase was under continuous agitation (750 r min-1). After the water phase's addition, agitation was continued for 30 min. Then, the system was probe sonicated using an Ultrasonic Homogenizer (JY92-IIN, Xinzhi Biotechnology Co., Ltd., Ningbo, China). Subsequently, the system was centrifuged for 3 min (3000 r min-1) using a centrifuge (H1650-W, Xiangyi Centrifuge Instrument Co., Ltd., Hunan, China). Finally, 4 mL supernatant was taken and filtered using the 0.45 mm syringe filter. The influences of the total CAT concentration (including the CAT in both the aqueous phase and organic phase, 2, 4 and 6 mg mL-1), ultrasonic power (50%, 60% and 70%), ultrasonic time (30, 60 and 90 s), and stirring temperature during the first 10 min (25, 30 and 35 degC) on the droplet size and IR780 EE were examined. The levels and factors of the orthogonal experiment are shown in Table 1. In this research, because there were three levels and four factors, the L9(34) orthogonal experiment was used. The mean droplet diameters of the CCIPNs were measured using the Brookhaven 90 Plus PALS equipment at 25 degC. The IR780 EE was calculated from the aforementioned Equation (1). 2.5. The Optimized CCIPN Preparation First, a multipoint magnetic stirrer was used to stir a bottle of organic phase consisting of Fomblin(r) Y (0.3 g), Tween 20 (0.7 g), IR780 (10 mg), CDDO-Me (1 mg) and CAT (5 mg) for 10 min (750 r min-1) at 25 degC. The bottle was then partly submerged in water and bath-sonicated for 20 min utilizing ultrasonic cleaning equipment (SB-4200D, Xinzhi Biotechnology Co., Ltd., Ningbo, China). After, the multipoint magnetic stirrer was used to agitate the organic phase for 20 min (750 r min-1). The water phase (9 mL PBS, pH 7.4 containing 15 mg CAT) was then added into the organic phase at ~1 drop every 3 seconds (pump rotation speed 22.0 rpm) with a peristaltic pump (BT100J-1A, Huiyu Weiye Fluid Equipment Co., Ltd., Beijing, China) when the organic phase was under continual agitation (750 r min-1). After the process of adding the water phase was finished, agitation was continued for 30 min. The system was then probe sonicated using an Ultrasonic Homogenizer (JY92-IIN, Xinzhi Biotechnology Co., Ltd., Ningbo, China). Afterwards, the emulsion was centrifuged for 3 min (3000 r min-1) using a centrifuge (H1650-W, Xiangyi Centrifuge Instrument Co., Ltd., Changsha, China). Finally, 4 mL supernatant was taken and filtered using the 0.45 mm syringe filter. The production process was conducted at 25 degC. 2.6. Droplet Size Measurements, UV-Visible Light Absorption Spectrum and Fluorescence Spectrum A Brookhaven 90 Plus PALS instrument was employed to detect the mean droplet diameters and polydispersity index (PDI) of the optimized CCIPNs at 25 degC. Here, 1.33 was set as the refractive index. All samples were diluted 60 times with deionized water prior to measurements. When the preparation of CCIPNs was finished, the mean droplet diameter and PDIs were determined directly. The blank nanoemulsions utilized in the UV-visible light absorption spectra detection were produced similarly to the CCIPNs, except that no IR780 was added. A UV-visible spectrophotometer was employed to record the absorption spectra at 25 degC. Fluorescence spectra were measured using cuvettes with a 1 cm path length and a slit width of 10 nm at 298 K on a Fluorescence-4600 spectrometer (Hitachi High-Technologies Corporation, Tokyo, Japan). 2.7. Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM) TEM and SEM were used to record the morphology of the CCIPN droplets. To accomplish this, 10 mL CCIPN was dropped onto a carbon-coated copper grid, dried naturally, and photographed using TEM (JEOL-2100F, JEOL Ltd., Tokyo, Japan). 10 mL CCIPN was diluted 100 times and 10 mL samples of the diluted emulsions were dropped onto a carbon-coated copper grid, and photographed using SEM (Phenom XL etc., FEI Electron Optics BV, Eindhoven, The Netherlands) after the sample had dried naturally. 2.8. Physical and Chemical Stability of CCIPN The physical and chemical stability of CCIPN in the physiological environment and during storage at 4 degC were investigated. The alteration of the droplet size measured by DLS was used to evaluate the physical stability, and the variations in the UV-visible light absorption were applied to examine the chemical stability. To study their stability in the physiological condition, the CCIPNs were diluted at a ratio of 1:60 with PBS (pH 7.4) and stored in incubators at 37 degC (GNP-9080BS-III, Xinmiao Medical Device Manufacturing Co., Ltd., Shanghai, China). The droplet size and absorbance at 793 nm were recorded after storage for 0, 12, 24, 36, or 48 h. For the storage stability of CCIPN at 4 degC, droplet size and UV-visible light absorption spectrum detections were conducted every 3 days during the 15-day storage period. All of the emulsions were diluted 50 times with deionized water and then determined. 2.9. Cell Culture Human PC-3 prostate cancer cells and DU145 prostate cancer cells were obtained from Procell Life Science & Technology Co., Ltd. (Wuhan, China). Human Umbilical Vein Endothelial Cells (HUVECs) were obtained from Shunran Biotechnology Company (Shanghai, China). The PC-3 cells, DU145 cells and HUVECs were cultured in Ham's F-12K medium, MEM and DMEM, respectively. Each type of medium contained 10% FBS and 1% penicillin-streptomycin solution. The cells were cultivated at 37 degC in a humidified incubator with 5% CO2 and ~21% O2. 2.10. Cytocompatibility Assays For cytocompatibility assays, 1.0 x 104 HUVECs or DU145 cells were placed into each well of the 96-well plates. The plates were incubated for 24 h in a 37 degC incubator with 5% CO2. The complete medium was then substituted by DMEM (for HUVECs) or MEM (for DU145 cells) containing diverse concentrations of CCIPNs (0, 0.025, 0.05 and 0.075 mg mL-1, IR780 concentrations). After incubation at 37 degC with 5% CO2 for 24 h, the medium was replaced with 100 mL of PBS containing 10 mL CCK-8. Afterwards, the cells were incubated for 1.5 h at 37 degC. Lastly, a Microplate Reader (ELX800, Bio Tek instruments, Inc., Highland Park, USA) was employed to measure the absorbance at 450 nm. In addition, the morphologies of cells incubated for 24 h with the CCIPNs were recorded utilizing a CYTATION/5 imaging reader (Bio Tek instruments, Inc., Winooski, VT, USA). 2.11. Phototoxicity Assays The phototoxicity assays were conducted on a cancerous cell line (DU145 prostate cancer cells) and a normal cell line (HUVECs) under hyperoxic condition (~21% O2), and on a cancerous cell line (PC-3 prostate cancer cells) under hypoxic condition (1% O2). For comparison, CINs were prepared similarly to the CCIPNs but without CAT and perfluoropolyether involvement. The phototoxicity assays on DU145 cells under hyperoxic condition (~21% O2) were performed as follows: DU145 cells were placed into two separate 96-well plates at 1.2 x 104 cells well-1 and incubated for 24 h in a 37 degC incubator with 5% CO2. The complete medium was then displaced by CCIPNs or CINs, which were diluted with MEM to 0.075 mg mL-1 (IR780 concentration). In addition, MEM was used to treat the cells and served as a control. After incubation at 37 degC and 5% CO2 for 3 h, the medium was replaced with 100 mL MEM. Subsequently, the cells in one plate were irradiated with a laser device (MDL-III-785 nm-2.5 W-CJ11170, New Industries Optoelectronics Tech. Co., Ltd., Changchun, China) for 5 min, and the cells in the other plate received no irradiation. The distance between the laser device and the plate, the optical power density and the wavelength of the laser were 20 cm, 0.579 W/cm2 and 785 nm, respectively. The cells were then incubated at 37 degC and 5% CO2 for 12 h. Afterwards, the liquids were substituted by PBS containing 10% CCK-8. After incubation at 37 *C and 5% CO2 for 3 h, a Microplate Reader (ELX800, Bio Tek instruments, Inc., Highland Park, IL, USA) was used to measure the absorbance at 450 nm. The cell morphologies were recorded utilizing a CYTATION/5 imaging reader (Bio Tek instruments, Inc., Winooski, VT, USA). The phototoxicity tests on HUVECs under hyperoxic condition (~21% O2) were conducted as follows: HUVECs were planted into a 96-well plate at 1.2 x 104 cells well-1 and incubated for 24 h at 37 degC and 5% CO2. Afterwards, the complete medium was substituted with CCIPNs or CINs, which were diluted with DMEM to 0.075 mg mL-1 (IR780 concentration). Meanwhile, DMEM was used to treat cells and served as a control. After incubation at 37 degC and 5% CO2 for 3 h, the liquids were substituted with DMEM. Then, the cells were treated with or without laser irradiation. The laser was generated by a laser device (MDL-III-785 nm-2.5 W-CJ11170, New Industries Optoelectronics Tech. Co., Ltd., Changchun, China). The distance between the laser device and the plate, the optical power density, the wavelength of the laser, and the irradiation time were 20 cm, 0.579 W/cm2, 785 nm, and 5 min, respectively. Afterwards, the cells were incubated at 37 degC and 5% CO2 for 12 h. The medium was then replaced with PBS containing 10% CCK-8. Lastly, the cells were incubated at 37 degC for 3 h and the absorbance at 450 nm was measured by a Microplate Reader (ELX800, Bio Tek instruments, Inc., Highland Park, IL, USA). The cell morphologies were photographed using a CYTATION/5 imaging reader (Bio Tek instruments, Inc., Winooski, VT, USA). The phototoxicity tests on PC-3 cells under hypoxic condition (1% O2) were performed as follows: PC-3 cells were placed into 96-well plates at 1.2 x 104 cells well-1 and incubated for 12 h in a 37 degC incubator with 5% CO2. The complete medium was then displaced by CCIPNs or CINs, which were diluted with MEM to 0.075 mg mL-1 (IR780 concentration). In addition, Ham's F-12K medium was used to treat the cells and served as a control. The hypoxic condition was created by setting the gas composition to 1% O2 on an incubator [HF100 (Tri-Gas), Lishen Scientific Instrument Co., Ltd., Shanghai, China]. After incubation at 37 degC, 1% O2 and 5% CO2 for 1 h, the liquid was replaced by Ham's F-12K medium, and the incubation continued for 30 min at 37 degC, 1% O2 and 5% CO2. Subsequently, the cells were irradiated with a laser device (MDL-III-785 nm-2.5 W-CJ11170, New Industries Optoelectronics Tech. Co., Ltd., Changchun, China) for 6 min, or received no irradiation. The distance between the laser device and the plate, optical power density, and wavelength of the laser were 20 cm, 0.579 W/cm2, and 785 nm, respectively. The liquid was then substituted by PBS containing 10% CCK-8. After incubation at 37 degC, 1% O2, and 5% CO2 for 2 h, a Microplate Reader (ELX800, Bio Tek instruments, Inc., Highland Park, IL, USA) was used to measure the absorbance at 450 nm. The cell morphologies were recorded utilizing an CYTATION/5 imaging reader (Bio Tek instruments, Inc., Winooski, VT, USA). 2.12. Intracellular ROS Detection DU145 prostate cancer cells or PC-3 prostate cancer cells were seeded into each well of the 96-well plates at a density of 1.2 x 104 cells well-1 and incubated at 37 degC and 5% CO2 for 24 h. Afterwards, the complete medium that was used to incubate the DU145 cells was displaced by CCIPNs or CINs that were diluted with MEM to 0.075 mg mL-1 (IR780 concentration), and the complete medium that was used to incubate PC-3 cells was displaced by CCIPNs or CINs that were diluted with DMEM to 0.15 mg mL-1 (IR780 concentration). In addition, MEM or DMEM was used to treat the cells and served as a control. After incubation at 37 degC and 5% CO2 for 3 h, the liquids were replaced with MEM (for DU145 cells) or DMEM (for PC-3 cells). Subsequently, the cells were treated with or without laser irradiation. The laser was generated by a laser device (MDL-III-785 nm-2.5 W-CJ11170, New Industries Optoelectronics Tech. Co., Ltd., Changchun, China). The distance between the laser device and the plate, the optical power density, the wavelength of the laser, and the irradiation time were 20 cm, 0.579 W/cm2, 785 nm, and 5 min, respectively. Afterwards, the cells were incubated at 37 degC for 3 h. The medium was then replaced with 10 mmol L-1 DCFH-DA (ROS probe), and the cells were incubated at 37 degC for 20 min. After this, serum-free medium was used to wash the cells three times, and a CYTATION/5 imaging reader was used to determine the intensities of fluorescence generated by DCF (Ex/Em = 488/525 nm). 2.13. Statistical Analysis All the data are reported as the mean value +- standard deviation (SD). Statistical analysis was conducted using the SPSS software (edition 16.0, SPSS, Inc., Chicago, IL, USA). After Levene's test for equality of variances, one-way analysis of variance (ANOVA) analysis was performed. Afterwards, Bonferroni's multiple comparison test was utilized to compare the mean values. A value of p < 0.05 was considered significant. 3. Results and Discussion 3.1. Selection of Perfluorocarbon Type for CCIPN The mean droplet diameters of emulsions prepared by employing various types of perfluorocarbons are shown in Figure 1a. Among the perfluorocarbon types tested, Fomblin(r) Y (MW 1800) generated the smallest droplets (290.34 +- 21.93 nm), while other types of perfluorocarbons such as perfluorooctane (MW 438.06) and 1-bromoheptadecafluorooctane (MW 498.96) produced large droplets. Meanwhile, the IR780 EE of the droplets produced by Fomblin(r) Y was acceptable . In this context, Fomblin(r) Y was chosen as the optimal perfluorocarbon for CCIPN preparation and used in the following experiments. 3.2. Determination of Added CDDO-Me Amount and CAT Distribution Ratio for CCIPN 3.2.1. Effect of Added CDDO-Me Amount on Droplet Size and IR780 EE As seen from Figure 2a, the droplet size of the emulsion was strongly affected by the amount of CDDO-Me added in the beginning of the preparation process. Small droplets (d < 100 nm) were acquired in the emulsion prepared by adding 1 mg CDDO-Me, while larger droplets were acquired at higher CDDO-Me amounts. In our research, changing the added CDDO-Me amount from 1 mg to 2 mg caused a sharp increase in droplet size. The reason for this phenomenon might be as follows. Usually, a nanoemulsion system has a limited capacity to encapsulate the specific drug. Herein, our nanoemulsion system should have a maximum capacity for loading CDDO-Me. When the fed CDDO-Me amount was 1 mg, our nanoemulsion system might had approached its maximum encapsulating capability. Beyond the maximum capacity, emulsion system ingredients could no longer self-assemble into fine structures below 1000 nm , which was the case in the 2 mg CDDO-Me group. A sharp increase in droplet diameter was also observed in another research work using a nanoemulsion system to deliver vitamin E, as the hydrophobic small molecule payload (vitamin E) feeding amount increased . In this article, the 1 mg added CDDO-Me amount did not induce a significant increase in the droplet size. Meanwhile, the 1 mg added CDDO-Me amount presented an acceptable IR780 EE . Accordingly, 1 mg CDDO-Me was selected as the optimal input amount and utilized in the succeeding experiments. 3.2.2. Effect of CAT Distribution on Droplet Size and IR780 EE To evaluate the influence of the CAT distribution among the organic phase and aqueous phase on the droplet size and IR780 EE, the organic-phase-to-aqueous-phase ratio of CAT was set as 0, 1:3, or 1:1. As seen from Figure 3a, the emulsion prepared at a ratio of 1:3 (i.e., 1/4 CAT was blended with other ingredients of the organic phase at the start of the preparation process, and 3/4 CAT was dispersed in the aqueous phase) had the smallest droplet diameter. Meanwhile, the emulsion produced at a ratio of 1:3 presented a satisfactory IR780 EE . Therefore, the ratio of 1:3 (i.e., 1/4 catalase in organic phase) was considered optimal for CCIPN preparation and was used in subsequent experiments. 3.3. Orthogonal Optimization for Preparation of CCIPN Using S-PIC-S Method The orthogonal experimental design, also known as the factorial design or full factorial design, is a statistical design approach that allows researchers to study the combined effects of multiple variables on an outcome of interest. In an orthogonal design, all possible combinations of the levels of the variables being studied are included in the design, and the effects of the variables are examined independently of one another. This allows researchers to identify the specific contributions of each variable to the outcome and to determine how the variables interact with each other . 3.3.1. Orthogonal Experiment and Calculation Results In order to acquire nanoemulsion droplets with satisfactory indexes (i.e., small diameter and high IR780 EE), the orthogonal experiment was applied. We aimed to search for the optimal level combination of four factors, including the total CAT concentration, ultrasonic power, ultrasonic time, and stirring temperature during the first 10 min (Table 1). According to the characteristic of the orthogonal design, the highest or lowest K value indicates the optimal level of a factor. Therefore, the optimal level of each factor can be determined from calculations based on the orthogonal experiment results. The combination of optimal levels constitutes the soundest plan that we aimed to obtain. In addition, the extent of influence that each factor has on the index (mean droplet diameter or IR780 EE) can be judged according to the R value. The larger R is, the greater influence the factor has on the index. When the mean droplet diameter was used as an index, the orthogonal experiment and calculation results were as presented in Table 2. The K values indicate that the smallest droplets can be acquired when the preparation condition is A1B2C3D1 (Scheme a). The content of Scheme a is as follows: the total CAT concentration is 2 mg mL-1, the ultrasonic power is 60%, the ultrasonic time is 90 s, and the stirring temperature during the first 10 min is 25 degC. Based on the R values, the order of the extent of influence is as follows: ultrasonic time > total CAT concentration > ultrasonic power > stirring temperature during the first 10 min. When IR780 EE was used as an index, the experimental and calculational results were as shown in Table 3. The K values indicate that when the preparation condition is A1B3C3D1 (Scheme b), the highest IR780 EE can be obtained. Scheme b has the following characteristics: the CAT concentration is 2 mg mL-1, the ultrasonic power is 70%, the ultrasonic time is 90 s, and the stirring temperature during the first 10 min is 25 degC. The R values imply that the order of the extent of influence is as follows: ultrasonic time > ultrasonic power > total CAT concentration > stirring temperature during the first 10 min. 3.3.2. Validation of Orthogonal Calculation The preparation was performed according to Scheme b (A1B3C3D1) or Scheme a (A1B2C3D1). As can be seen from Table 4 and Table 5, the emulsion prepared as per Scheme b had a smaller droplet diameter and higher encapsulation efficiency in comparison with that prepared as per Scheme a. Therefore, Scheme b was determined as the optimal experimental condition. Scheme b has the following characteristics: the total CAT concentration is 2 mg mL-1, the ultrasonic power is 70%, the ultrasonic time is 90 s, and the stirring temperature during the first 10 min is 25 degC. 3.4. Physicochemical Properties of the Optimized CCIPN The biomedical application of the near-infrared (NIR) photosensitizer IR780 is impeded by its low aqueous solubility and poor chemical stability . CCIPN enhanced its aqueous solubility through nanoencapsulation. IR780 is innately water-immiscible. However, CCIPN showed a clear and homogeneous appearance, indicating the satisfactory enhancement of the aqueous solubility of IR780 . Meanwhile, the transparent nature of the appearance suggested that the droplet size was below 100 nm. As seen from Figure 4b, the DLS measurement results indicated that the mean droplet diameter of CCIPN was 65.23 +- 7.39 nm, which was consistent with the visual appearance. The CCIPN droplet diameter is notably smaller than the mean droplet diameters recently published for IR780-P/W NE (205.81 +- 2.25 nm) and FA-IR780 (291.20 +- 82.70 nm) . The small droplet size may facilitate the accumulation of CCIPN at the tumor location and improve the therapeutic effects. PDI values describe the narrowness of the droplet size distribution, with a small value indicating a narrow distribution. The PDI value of the optimized CCIPN was 0.355 +- 0.034 , demonstrating a narrow distribution, which was vital in avoiding droplet growth induced by Ostwald ripening . The SEM and TEM results revealed the spherical morphology of CCIPN droplets . The droplet diameters acquired by the SEM and TEM images agreed with the DLS results. Figure 4e,f display the UV-visible light absorption spectrum and fluorescence emission spectrum of CCIPN, respectively. As shown in Figure 4e, the blank nanoemulsion (including no IR780) showed no absorption throughout the 400-1000 nm range, whereas CCIPN displayed a prominent absorption peak similar to the peak of IR780 in the acetonitrile solution. This demonstrated that IR780 was effectively encapsulated by the nanoemulsion carrier. The fluorescence emission spectra shown in Figure 4f confirm the conclusion obtained from the UV-visible light absorption spectra. CCIPN showed an identical characteristic peak to IR780 in acetonitrile, demonstrating effective IR780 encapsulation. 3.5. Physical and Chemical Stability of CCIPN in Physiological Conditions To investigate the stability of CCIPN in the physiological environment, CCIPN in pH 7.4 PBS was stored for 48 h at 37 degC. During the storage period, the mean droplet diameter was measured by DLS equipment, and the UV-visible spectrophotometer was utilized to determine the absorbance. The absorbance was recorded to detect possible sediments that could not be monitored by appearance observation or DLS measurements. During the 48 h storage period, although slightly increased , the mean droplet diameter was still less than 100 nm , which might help to maintain the strength on account of the nano size of CCIPN in biomedical applications. Moreover, the results of absorbance showed that the IR780 remained up to 81.7% after 48 h. The small decrease in IR780 content was likely caused by the IR780's degradation rather than sedimentation after storage for 48 h at 37 degC, because IR780 is easily degraded when the temperature is increased. In brief, the results of the absorbance tests demonstrated that the location of IR780 was within the emulsion system rather than sedimentation, which suggested the reliability of the DLS results. In conclusion, the results above indicate that the nanoemulsion's encapsulation might promote the biomedical application of IR780 by extending the circulation time of IR780. 3.6. Physical and Chemical Stability of CCIPN during Storage at 4 degC The DLS equipment was used to investigate the physical stability of CCIPN during storage at 4 degC. Although it rose to 138.30 +- 3.13 nm (the 15th day), the mean droplet diameter was still below 150 nm . Meanwhile, no creaming or precipitation was detected, and the CCIPN maintained a transparent and homogeneous appearance over the 15-day duration . This is beneficial for the transport and application of CCIPN. It is possible that as a type of protein, the catalase in the CCIPN underwent a conformational change as time passed in the aqueous environment, leading to the elevation of the droplet size. The changes in the absorbance at 793 nm and the UV-visible light absorption spectrum were recorded to evaluate the chemical stability of CCIPN during 15-day storage at 4 degC. As seen from Figure 7a, after storage at 4 degC for 15 days, the IR780 retention rate was above 86%. The absorption spectrum of CCIPN presented a trivial alteration before and after 15-day storage at 4 degC . This indicated that the packing of IR780 in nanoemulsion formulations resulted in high chemical stability. The chemical stability could be ascribed to the interfacial protective layer created by the emulsifier molecules. 3.7. Cytocompatibility Assays To evaluate the CCIPN's compatibility with normal cells, we detected the viability and morphologies of HUVEC (a non-cancerous cell line) cells incubated with various concentrations of CCIPNs for 24 h in the dark at 37 degC and 5% CO2. As is shown in Figure 8a, no significant change in cell viability was observed within our concentration range (0-0.075 mg mL-1). As presented in Figure 8b, consistent with the cell viability results, the cells at every concentration presented no detectable morphological alteration in comparison with the culture medium group. The cells retained their normal elongated or fusiform shapes similar to the morphologies of the cells incubated with only the culture medium. These results concerning cell viability and morphology indicate the satisfactory cytocompatibility of CCIPN. PDT uses light as a switch to control the cytotoxicity of a photosensitizer, killing cancer cells selectively. In this context, excellent cytocompatibility in the absence of light is essential for a PDT agent . Therefore, the cytocompatibility of CCIPN with DU145 prostate cancer cells under dark conditions was studied. After the cells were incubated with CCIPNs at diverse concentrations (0-0.075 mg mL-1) in the dark for 24 h at 37 degC and 5% CO2, almost no cell viability variation could be detected . Moreover, in agreement with the cell viability results, the cells at each concentration presented no detectable morphological change in comparison with the control group . The cells retained their normal elongated or fusiform shapes, similar to the morphologies of the control group cells. These results demonstrate the satisfactory cytocompatibility of CCIPN in darkness, i.e., negligible "dark toxicity" . 3.8. Phototoxicity Assays In order to examine the anticancer effect in vitro, cell viability measurements were performed using the CCK-8 method, and cell morphology inspection was conducted utilizing a CYTATION/5 imaging reader. Under hyperoxic condition (~21% O2), DU145 prostate cancer cells were incubated with CCIPN or CIN having the same IR780 concentration as the CCIPN, or serum-free medium, and then treated with or without 785 nm laser irradiation. As seen from Figure 10a, in the absence of light, the cells incubated with culture medium, CIN, or CCIPN presented no variation in cell viability. This indicated that no tumor cell killing could be achieved without light illumination. As seen from Figure 10b, a slightly (non-significantly) greater reduction in cell viability was observed in the CCIPN + NIR group than in the CIN + NIR group, demonstrating the higher efficiency of the CCIPN in destroying tumor cells upon light stimulation. Furthermore, the cell morphologies of the treatment groups are shown in Figure 11. In agreement with the cell viability results, the cells in the CCIPN group or CIN group without illumination showed little morphological variation in comparison with the control group. The DU145 cells maintained their normal elongated or fusiform shapes . In the CIN + NIR group, the majority of cells maintained their normal fusiform or elongated shapes similar to the control group. In sharp contrast, nearly all the cells in the CCIPN + NIR group contracted to spherical shapes, indicating severe damage to the tumor cells . The high solubility of Fomblin(r) Y compounds for oxygen and the generation of oxygen by catalase should be critical reasons for the high DU145 cell-killing efficiency. In summary, these results suggest that CCIPN could enhance the phototherapeutic influence on tumor cells under NIR light activation because of the increased oxygen supply. For prostate cancer, severe hypoxia has been reported to be closely related to disease aggressiveness , and it constitutes an important obstacle for immunotherapy . The superior cytotoxicity to DU145 prostate cancer cells promoted by oxygen supplementation makes CCIPN a candidate to enhance prostate cancer immunotherapy via combating hypoxia. Meanwhile, CDDO-Me has been reported to vigorously inhibit the proliferation and promote the apoptosis of diverse types of cancer cell lines . It was also stated that CDDO-Me could regulate the immunosuppressive tumor microenvironment and coordinate with vaccine therapy . Therefore, if CCIPN is combined with immunotherapies, it might improve the therapeutic effect by relieving hypoxia through catalase & perfluoropolyether and remodeling the immunosuppressive tumor microenvironment through CDDO-Me. We further studied the phototoxicity of CCIPN on a non-cancerous cell line, HUVEC cells under hyperoxic condition (~21% O2). To examine the influence of CCIPN on HUVECs, the CCK-8 method was used to measure cell viability, and a CYTATION/5 imaging reader was applied to record the cells' morphologies. HUVECs were incubated with CCIPN, CIN having the same IR780 concentration as the CCIPN, or serum-free medium, and then treated with or without 785 nm laser irradiation. As presented in Figure 12, without light irradiation, the cells incubated with the culture medium, CIN or CCIPN, showed little alteration in cell viability. This is in agreement with the abovementioned cytocompatibility assay results and indicates that no cell damage could occur without light stimulation. In addition, the cell viability of the Medium + NIR group was similar to that in the Medium--NIR group, indicating that the light irradiation condition (optical power density, irradiation time, etc.) itself could not elicit cytotoxicity. Upon light irradiation, the cells cultured with CCIPN showed a greater decrease in cell viability compared with the cells incubated with CIN. Furthermore, the cell morphology results agree with the cell viability data . The cellular shapes of the - NIR groups and Medium + NIR group were similar, being elongated, suggesting that the cells were in a normal state. The CCIPN + NIR group presented a greater number of round cells in comparison with the CIN + NIR group, which indicated more severe damage to cells. The light-responsive property of CCIPN here is consistent with the abovementioned phototoxicity assay results on the DU145 prostate cancer cells. The results here suggest that the CCIPN could enter both cancerous and normal cells, and cause side effects if the normal cells were irradiated accidentally or due to other reasons. However, this side effect may be avoided by strictly confining the irradiation area to only tumor sites. Future modification to CCIPN, such as conjugating tumor-targeting moieties (e.g., folic acid, or ligands targeting CD44), might realize a "double targeting" (tumor-targeting moiety and light) effect, and benefit antitumor treatment outcomes . We further studied the phototoxicity of CCIPN in comparison with CIN under hypoxic condition. The experimental O2 concentration was set as 1% in order to simulate the hypoxic tumor microenvironment . As presented in Figure 14, the CCIPN + NIR treatment induced a lower cell viability compared with CIN + NIR treatment, suggesting the superior ability of CCIPN to destruct cells under light irradiation in hypoxic condition. It is noteworthy that neither Medium + NIR group nor - NIR groups (CCIPN - NIR group and CIN - NIR group) presented significant cell viability change in comparison with the Medium - NIR group, indicating that neither irradiation alone nor drug incubation alone could cause cell death. This demonstrated that the cell viability reductions seen in the CCIPN + NIR group and CIN + NIR group were caused by the combinatory effect of light and drug. In other words, the results here suggest that CCIPN could induce stronger photodynamic effect than CIN. This might be ascribed to the oxygen-supplying ability of catalase and Fomblin(r) Y in the CCIPN. As shown in Figure 15, the cell morphology detection results agree with the cell viability data. The CIN + NIR group presented elongated morphology similar to the Culture medium group, while the CCIPN + NIR group exhibited a contracted spherical shape. Neither drug alone nor irradiation alone elicited obvious cell morphology change. In this article, most of the in vitro cellular experiments were performed in hyperoxic condition, and this is a strong limitation of the present study. More in vitro experiments under hypoxic condition and in vivo tests remain to be performed to provide information on the potential of CCIPN to work in the hypoxic tumor microenvironment. 3.9. Intracellular ROS Production by CCIPN After determining the ability of CCIPN to kill cells in response to light stimulation, we further explored the mechanism underlying the phototoxicity in terms of intracellular ROS production. The intracellular ROS generated by CCIPN and CIN at the same IR780 concentration with or without NIR irradiation was quantified utilizing a fluorogenic probe DCFH-DA, with serum-free medium serving as a control. After 785 nm laser irradiation, the DU145 prostate cancer cells incubated with CCIPN showed clearly higher fluorescence intensity compared with those incubated with CIN . This demonstrated that more ROS was generated by the CCIPN under laser irradiation. Consistently, tests on another prostate cancer cell line, PC-3, showed that the fluorescence intensity of the CCIPN + NIR group was clearly higher than that of the CIN + NIR group , which indicated the higher efficiency of CCIPN in generating cytotoxic ROS upon light stimulation in comparison with CIN. The results here are in agreement with other research using catalase or perfluorocarbon to increase the PDT efficacy. In summary, the results here imply that CCIPN may boost the cytotoxic ROS production through oxygen supplementation, leading to enhanced phototoxicity. 4. Conclusions In this research, a hydrogen peroxide-responsive and oxygen-gathering nanoemulsion system, CCIPN, was rationally designed to address hypoxia in PDT. With perfluoropolyether and catalase converged in one nanoplatform CCIPN, the oxygen generated by the decomposition of tumor-overproduced hydrogen peroxide via catalase could be reserved by perfluoropolyether for PDT. CCIPN represents a hypoxic tumor PDT strategy integrating the high tumor specificity of the oxygen generation approach and the high efficiency of the oxygen delivery tactic. CCIPN was produced using the S-PIC-S method, which we developed from our previous SPIC method, and the preparation process was optimized using orthogonal tests. The prepared CCIPN contained spherical droplets below 100 nm in size, with a considerable amount of catalase loaded. It showed high cytocompatibility in the dark and enhanced ROS generation and cytotoxicity under light irradiation, which indicated its feasibility in supplementing oxygen and boosting PDT efficiency. Moreover, with the ability to combat hypoxia (which is also an obstacle in tumor immunotherapy) and the potential to regulate the immunosuppressive tumor microenvironment (endowed by the loaded CDDO-Me), CCIPN may be a promising agent to activate the immune system and be synergized with immunotherapy in the future. Author Contributions Conceptualization, L.H. and J.W.; methodology, L.H., J.W. and X.Z.; validation, J.W., Y.Z., J.L., T.G., G.S., H.T. and Y.L.; formal analysis, L.H. and J.W.; investigation, L.H., J.W. and Y.Z.; resources, L.H.; data curation, J.W.; writing--original draft preparation, J.W.; writing--review and editing, J.W. and L.H.; visualization, J.W.; supervision, L.H., Z.Z. and Z.H.; project administration, L.H.; funding acquisition, L.H., Z.Z. and Z.H. 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 in this article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The influence of perfluorocarbon type on the (a) mean droplet diameter and (b) IR780 EE of emulsions. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. Figure 2 The impact of added CDDO-Me amount on the (a) droplet size and (b) IR780 EE of emulsions. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. Figure 3 The effect of CAT distribution on the (a) droplet size and (b) IR780 EE of emulsions. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. Figure 4 Physicochemical properties of CCIPN. (a) The appearance of CCIPN; (b) The droplet size distribution of CCIPN; (c) Transmission electron microscopy image of CCIPN. Water was used as the aqueous phase to avoid the influence of PBS on the photograph; (d) Scanning electron microscopy image of CCIPN. Water was used as the aqueous phase to avoid the influence of PBS on the photograph; (e) Absorption spectra of CCIPN, IR780 in acetonitrile, and blank nanoemulsion; (f) Fluorescence spectra of CCIPN and IR780 in acetonitrile. Figure 5 (a) Change in CCIPN droplet diameter in pH 7.4 PBS during storage for 48 h at 37 +- 0.5 degC. (b) Change in CCIPN absorbance in pH 7.4 PBS during storage for 48 h at 37 +- 0.5 degC. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. Figure 6 (a) The change in droplet diameter of CCIPNs during storage at 4 degC for 15 days. (b) The appearance of CCIPNs preserved at 4 *C and stored for 0 or 15 days. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. Figure 7 (a) The change in absorbance of CCIPNs during storage at 4 degC for 15 days. (b) The change in ultraviolet-visible light absorption spectrum of CCIPNs during storage at 4 degC for 15 days. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. Figure 8 (a) Viability of HUVECs after incubation with various concentrations of CCIPNs (IR780 concentration 0, 0.025, 0.05 and 0.075 mg mL-1) for 24 h in the dark. (b) Morphologies of HUVECs after incubation with various concentrations of CCIPNs (IR780 concentration 0, 0.025, 0.05 and 0.075 mg mL-1) for 24 h in the dark. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. Figure 9 (a) Viability of DU145 prostate cancer cells after incubation with various concentrations of CCIPNs (IR780 concentration 0, 0.025, 0.05, and 0.075 mg mL-1) for 24 h in the dark. (b) Morphologies of DU145 prostate cancer cells after incubation with various concentrations of CCIPNs (IR780 concentration 0, 0.025, 0.05 and 0.075 mg mL-1) for 24 h in the dark. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. Figure 10 Investigation of the phototoxicity of CCIPN. (a) Viability of DU145 cells treated with culture medium, CCIPN at 0.075 mg mL-1, or CIN at 0.075 mg mL-1 under no irradiation. (b) Viability of DU145 cells treated with culture medium, CCIPN at 0.075 mg mL-1, or CIN at 0.075 mg mL-1 under irradiation. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p value vs. indicated group is presented. Figure 11 DU145 cell morphologies under different treatment conditions. Figure 12 Investigation of the phototoxicity of CCIPN. Viability of HUVECs treated with culture medium, CCIPN at 0.075 mg mL-1 or CIN at 0.075 mg mL-1 under irradiation or no irradiation. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p value vs. indicated group is presented. Figure 13 HUVECs morphologies under different treatment conditions. Figure 14 Investigation of the phototoxicity of CCIPN under hypoxic condition. Viability of PC-3 cells treated with culture medium, CCIPN at 0.075 mg mL-1, or CIN at 0.075 mg mL-1 under irradiation or no irradiation. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. Figure 15 PC-3 cell morphologies after receiving different treatments in hypoxic condition. Figure 16 (a) Generation of intracellular reactive oxygen species indicated by DCF in DU145 cells treated with culture medium, CCIPN at 0.075 mg mL-1 or CIN at 0.075 mg mL-1 with/without NIR light irradiation. (b) Generation of intracellular reactive oxygen species indicated by DCF in PC3 cells treated with culture medium, CCIPN at 0.15 mg mL-1 or CIN at 0.15 mg mL-1 with/without NIR light irradiation. Values are expressed as mean +- SD (n = 3). Each dot represents an independent experiment. The p values vs. indicated groups are presented. cancers-15-01576-t001_Table 1 Table 1 Factors and levels in the design of the orthogonal experiment. Level Factor A B C D 1 2 50 30 25 2 4 60 60 30 3 6 70 90 35 A (Total CAT concentration, mg mL-1), B (Ultrasonic power, %), C (Ultrasonic time, s), D (Stirring temperature during the first 10 min, degC). cancers-15-01576-t002_Table 2 Table 2 Orthogonal experiment design and results concerning mean droplet diameter. Experiment Number Factor Mean Droplet Diameter (nm) A B C D 1 2 50 30 25 428.57 2 2 60 60 30 433.00 3 2 70 90 35 312.76 4 4 50 60 35 825.13 5 4 60 90 25 326.12 6 4 70 30 30 501.58 7 6 50 90 30 449.51 8 6 60 30 35 546.12 9 6 70 60 25 570.00 K1 1174.33 1703.21 1476.27 1324.69 K2 1652.83 1305.24 1828.13 1384.09 K3 1565.63 1384.34 1088.39 1684.01 R 159.50 132.66 246.58 119.77 A (Total CAT concentration, mg mL-1), B (Ultrasonic power, %), C (Ultrasonic time, s), D (Stirring temperature during the first 10 min, degC). Ki represents the sum of the test results with level number i within any column. R stands for range, i.e., the averaged result of maximum Ki average minus minimum Ki. The smallest K value indicates the optimal level of the factor. The larger the R-value is, the greater influence the factor has on the index. cancers-15-01576-t003_Table 3 Table 3 Orthogonal experiment design and results concerning encapsulation efficiency. Experiment Number Factor Encapsulation Efficiency (%) A B C D 1 2 50 30 25 20.95 2 2 60 60 30 22.51 3 2 70 90 35 32.14 4 4 50 60 35 22.13 5 4 60 90 25 25.57 6 4 70 30 30 20.77 7 6 50 90 30 23.44 8 6 60 30 35 18.61 9 6 70 60 25 26.75 K1 75.60 66.52 60.33 73.27 K2 68.47 66.69 71.39 66.72 K3 68.80 79.66 81.15 72.88 R 2.38 4.38 6.94 2.18 A (Total CAT concentration, mg mL-1), B (Ultrasonic power, %), C (Ultrasonic time, s), D (Stirring temperature during the first 10 min, degC). Ki represents the sum of the test results with level number i within any column. R stands for range, i.e., the averaged result of maximum Ki average minus minimum Ki. The highest K value indicates the optimal level of the factor. The larger the R-value is, the greater influence the factor has on the index. cancers-15-01576-t004_Table 4 Table 4 Experimental results on mean droplet diameters of Scheme a and Scheme b. Scheme Factor Mean Droplet Diameter (nm, +- SD) a A1 B2 C3 D1 73.80 +- 12.74 b A1 B3 C3 D1 57.14 +- 9.49 A1 (Total CAT concentration is 2 mg mL-1), B2 (Ultrasonic power is 60%), B3 (Ultrasonic power is 70%), C3 (Ultrasonic time is 90 s), D1 (Stirring temperature during the first 10 min is 25 degC). cancers-15-01576-t005_Table 5 Table 5 Experimental results on IR780 encapsulation efficiencies of Scheme a and Scheme b. Scheme Factor Encapsulation Efficiency (%) a A1 B2 C3 D1 22.84 b A1 B3 C3 D1 32.36 A1 (Total CAT concentration is 2 mg mL-1), B2 (Ultrasonic power is 60%), B3 (Ultrasonic power is 70%), C3 (Ultrasonic time is 90 s), D1 (Stirring temperature during the first 10 min is 25 degC). 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. |
PMC10000419 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050993 diagnostics-13-00993 Article Assessment of the Carotid Bodies in Magnetic Resonance--A Head-to-Head Comparison with Computed Tomography Budynko Lukasz Conceptualization Methodology Validation Investigation Resources Writing - original draft 1+ Nowicki Tomasz K. Conceptualization Methodology Investigation Resources Writing - original draft Writing - review & editing 2+ Kaszubowski Mariusz F. Formal analysis 3 Swieton Dominik Conceptualization 2 Piskunowicz Maciej Conceptualization Methodology 1* Ginat Daniel Thomas Academic Editor 1 Department of Radiology, Faculty of Medicine, Medical University of Gdansk, Smoluchowskiego 17, 80-214 Gdansk, Poland 2 2nd Department of Radiology, Faculty of Health Sciences with the Institute of Maritime and Tropical Medicine, Medical University of Gdansk, Smoluchowskiego 17, 80-214 Gdansk, Poland 3 Department of Statistics and Econometrics, Faculty of Management and Economics, Gdansk University of Technology, Traugutta 79, 80-233 Gdansk, Poland * Correspondence: [email protected]; Tel.: +48-58-349-3680; Fax: +48-58-349-3690 + These authors contributed equally to this work. 05 3 2023 3 2023 13 5 99330 1 2023 28 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 ). Objectives: To evaluate carotid body visibility in contrast-enhanced magnetic resonance (MR) studies and to compare the results to contrast-enhanced computed tomography (CT). Methods: Two observers separately evaluated MR and CT examinations of 58 patients. MR scans were acquired with contrast-enhanced isometric T1-weighted water-only Dixon sequence. CT examinations were performed 90 s after contrast agent administration. Carotid bodies' dimensions were noted and their volumes calculated. To quantify the agreement between both methods, Bland-Altman plots were computed. Receiver operating characteristic (ROC) and its localization-oriented variant (LROC) curves were plotted. Results: Of the 116 expected carotid bodies, 105 were found on CT and 103 on MR at least by a single observer. Significantly more findings were concordant in CT (92.2%) than in MR (83.6%). The mean carotid body volume was smaller in CT (19.4 mm3) than in MR (20.8 mm3). The inter-observer agreement on volumes was moderately good (ICC (2,k) 0.42, p < 0.001), but with significant systematic error. The diagnostic performance of the MR method added up to 88.4% of the ROC's area under the curve and 78.0% in the LROC algorithm. Conclusions: Carotid bodies can be visualized on contrast-enhanced MR with good accuracy and inter-observer agreement. Carotid bodies assessed on MR had similar morphology as described in anatomical studies. carotid body magnetic resonance imaging computed tomography Dixon sequence This research received no external funding. pmc1. Introduction The carotid body (CB) lies in the common carotid artery adventitia, measuring 5-7 mm in height and 2.5-4 mm in width . CBs constitute a cluster of specialized non-neuronal chemoreceptor tissue , detecting changes in arterial blood gases concentration and stimulating the respiratory centre in the brain stem . Currently, there is considerable interest in the adverse effects of chronic overactivity of CBs, which has been linked to several sympathetically mediated diseases: chronic heart failure (CHF), arterial hypertension (HT), and diabetes mellitus (DM) . Autopsy studies indicated CB volume increases in the settings of CHF and HT, an effect related to cell hyperplasia driven by an oxygen-depleted state . Early attempts to reduce CB activity in respiratory diseases by surgical excision did not bring the desired results. However, a reduction in blood pressure was observed, which stimulated further efforts to decrease their sympathetic activation in CHF and HT . At present, CB visualization relies on computed tomography angiography (CTA) , exposing a patient to high radiation doses and the possible adverse effects of intravenous iodine-based contrast agent (CA) administration. There are also two reports in the literature concerning the detection of CBs by ultrasound . Meanwhile, magnetic resonance (MR) has become an essential imaging modality in the head and neck region due to its excellent tissue contrast and comprehensive tissue characterization. Considering the enhanced signal-to-noise ratio and resolution capabilities of modern high-field scanners, it should be possible to distinguish unaltered CBs in head and neck examinations. This retrospective cohort study was aimed to evaluate CB visibility in MR head and neck studies and compare results to contrast-enhanced CT of the same patients. 2. Materials and Methods 2.1. Patients We browsed our hospital information system database for contrast-enhanced head and neck MR and CT examinations with the following inclusion criteria: (1) patients at least 18 years of age, (2) the time period between MR and CT studies not longer than 5 years, (3) MR study protocol containing contrast-enhanced isometric sequence in T1-weighted images with Dixon technique and diffusion-weighted imaging (DWI), (4) CT slice thickness equal to or less than 1.5 mm, (5) arterial or arteriovenous phase included in CT examination, (6) coverage of the carotid bifurcation in both examinations. We excluded studies with considerable motion artefacts in the region of interest and with neck masses infiltrating carotid arteries. Necessary images were downloaded from the hospital PACS server. 2.2. Magnetic Resonance Examination Protocol MR images were acquired on a 1.5 T scanner (Magnetom Aera, Siemens, Erlangen, Germany). We assessed the CBs in the contrast-enhanced 3D acquired gradient-echo, volumetric interpolated breath-hold examination (VIBE) sequence in T1-weighted images with the Dixon technique. Echo time (TE) was 2.4 ms, and repetition time (TR) 7.6 ms. Images were acquired with a parallel imaging technique (GRAPPA, acceleration factor of two) and the number of averages of two. The acquisition voxel size was 1.18 x 1.0 x 1.27 mm, and the reconstructed voxel was isometric and measured 1.0 x 1.0 x 1.0 mm. An automatic pressure injector was used for the administration of CA. The total volume of administrated CA was 0.5 or 1.0 mL/kg of the patient's body weight, depending on the manufacturer's recommendation. CA administration with a flow rate of 3 mL/s was followed by a flush of 30 mL of normal saline at the same rate. The readout-segmented echo-planar diffusion-weighted sequence with b values of 0, 500 and 1000 s/mm2, slice thickness of 5.0 mm, gap of 1.0 mm, and pixel size of 1.5 x 1.5 mm was acquired with parallel imaging technique (GRAPPA, acceleration factor of two). The sequence was used only to differentiate CBs from potentially adjacent lymph nodes . Only a diffusion-weighted image allows a lymph node to be easily distinguished from a carotid body as the first one has a high signal (yellow) and the second has a low signal . In the rest of the presented magnetic resonance images, a lymph node and a carotid body have a similar appearance. 2.3. Computed Tomography Protocol Protocols for contrast-enhanced head and neck CT varied moderately between studies. Images were obtained on either a 128-row CT scanner (Somatom Definition Flash, Siemens) or a 64-row CT scanner (Lightspeed VCT XT, GE Healthcare, Chicago, IL, USA) available at our institution. Patients received 80 mL of CA, and the iodine concentration was either 350 or 400 mg/mL. The bolus of CA (1.0 mL/s) was followed by a flush of 30 mL of normal saline (3.0 mL/s). The acquisition started 90 s after the initiation of the CA bolus. Images were acquired in the arteriovenous phase. The helical acquisition of 0.6 or 0.625 mm collimated images with a pitch of 0.53-0.8 was used. The kilovoltage was within a range of 100 to 140 kV with a standard reference output of 110 mAs up to 280 mAs. The automated dose reduction programs were performed on both scanners. The reconstruction field of view ranged from 240 to 280 mm, and the reconstruction matrix was 512 x 512, resulting in pixel size from 0.47 to 0.55 mm. Reconstruction slice thickness was from 0.6 to 1.5 mm, depending on the reconstruction algorithm. Images were reconstructed with soft tissue algorithms provided by manufacturers. 2.4. Carotid Bodies Identification Anonymized studies were evaluated independently with a one-week interval between MR and CT reading sessions. Two researchers (a fourth-year radiology resident and a radiology specialist with five years of expertise in head and neck imaging) read scans separately on dedicated workstation software (Syngo.via VB20A, Siemens). MR studies were viewed in a standard window. Consistent window level settings (width 190, centre 90) were used in the case of CT images. As in previous studies , CB was defined as a reproducible, ovoid, avidly enhancing structure at the inferomedial aspect of the carotid bifurcation . In the case of MR readings, each researcher used a semi-quantitative confidence scale from 1 to 6 points, representing the number of typical features displayed by the assessed CB and, therefore, the probability that the detected focus represents a CB. The typical features were: location adjacent to the carotid bifurcation, clearly separated oval or flame-shaped structures, transverse axis from 2 to 4 mm and longitudinal axis up to 8 mm, marked enhancement after CA, but lesser than arterial lumen. One point was assigned if no CB was visible, and six points if a single structure with all typical features of CB was detected (Table 1). A detailed assessment protocol is available in Supplementary Materials File S1. After annotating CBs on all datasets, researchers first compared their CT findings to establish a reliable reference. Each difference deemed significant (CB location mismatch, size discrepancy more than 50%) was thoroughly discussed. After correcting obvious mistakes, a consensus was reached on the most probable CB location. MR findings were later evaluated against our mutual CT agreement. If a finding in MR was not visible in CT (the reference method), then it was not considered a CB. We reported the findings in the form of binary variables under the following conditions: (1) if a particular CB was visible in either diagnostic modality, (2) if both readers marked the CB in the same location, (3) if there was a consensus about CB localization between both methods. 2.5. Carotid Bodies Measurements Orthogonal measurements of CBs were performed bilaterally on multiplanar reconstructed MR and CT images, thereby designating their locations. For the measurements in MR, solely isometric contrast-enhanced VIBE sequence in T1-weighted, water-only images was used. CB volume was calculated based on the standard formula for ellipsoids (1):(1) V=16p*x*y*z where x, y, and z are transverse, sagittal, and longitudinal dimensions, respectively. Additionally, on CT images, region of interest markers were inserted in common carotid arteries 2 cm below bifurcation to calculate CT enhancement differences. 2.6. Statistical Analysis The results were analyzed with dedicated statistical software (STATISTICA 13, StatSoft, and PQStat 1.6.4.120, PQStat Software). ROC and LROC curves were computed with free web-based tools . All calculated p values (with a priori significance level a set to 0.05) were two-tailed for random variables with a symmetric distribution. Normality was verified by the Shapiro-Wilk W test. Arithmetic means with 95% confidence intervals and standard deviations were calculated for quantitative variables. The reproducibility of quantitative measurements was assessed with the intraclass correlation coefficient (ICC) for concordant CBs. To quantify the agreement between both methods and evaluate distribution error, Bland-Altman plots were constructed with +-1.96 SD agreement limits. To examine the significance of measurement differences between methods, Student's t-test and Cochrane Q test were used, depending on variable properties. 2.7. Receiver Operating Characteristic To delineate the MR ability to detect CB within set discrimination thresholds, we plotted two receiver operating characteristic (ROC) curves: conventional--as first described by Egan , and localization ROC (LROC)--its extension developed among others by Swensson . LROC is optimized for detection tasks for multiple readers on the premise that there is only one lesion per assessed area. To fulfil the algorithm requirements, we treated each side of the neck as a separate location. Having ascertained that there was no statistical significance between the diagnostic efficiency of both readers, we collated our readings. Because CT has been assigned as the method of reference, CT studies with non-discernible CBs were removed. All the MR readings with CT references were included in the analysis. The study was approved by the Independent Bioethics Committee for Scientific Research at Medical University of Gdansk, Gdansk, Poland (NKBBN/183/2018). 3. Results We found 58 patients with adequate head and neck MR studies and recent CT scans. The mean period between acquisitions of the CT and MR scans was 481 days (median 187 days). The group consisted of 32 men and 26 women (mean age: 58 years, median 59 years, range: 21-88 years). 3.1. Carotid Bodies Recognition Of the expected 116 CBs, 105 were found on CT scans at least by one reader. In one instance, an anatomical variant of the carotid bifurcation precluded identification, one CB was covered by a nearby pathologic lesion, and nine were evaluated as truly imperceptible. Associated CT sensitivity, considering all reported findings as true positives, was 90.52% (95% CI 83.67-95.17%). In MR studies, after validation with CT results, 103 CBs were identified, yielding a sensitivity of 88.79% (95% CI 81.60-93.90%). There was no significant difference between the sensitivity of both modalities. No significant difference was observed in the visibility of CBs between both methods (Cochrane Q test, p = 0.64). Concordance between observers was achieved in 107 CT readings (92.2% of the total): 97 visible instances and 10 imperceptible instances. Seven discordant CBs were not initially recognized by one of the observers, and, in two cases, each attributed CB to other structures. In comparison, there was agreement in 97 cases in MR (83.6% of the total), with 13 CBs imperceptible for one observer and six structures mismatched. There was a higher rate (Cochrane Q, p = 0.04) of concordant descriptions in computed tomography (agreement in 92% of cases) than in magnetic resonance (84%). 3.2. Carotid Bodies Dimensions The average CB dimensions acquired from CT readings were consistently smaller in comparison with MR (Table 2). Average CB volume was estimated respectively 19.4 mm3 and 20.8 mm3 with a moderate degree of correlation between both modalities (ICC (2,k) 0.46, p < 0.003). Systematic bias for CB volume measurement, estimated on the base of Bland-Altman analysis, added up to 1.4 mm3. Although CB volumes in MR were typically reported as larger, the measurement variation seems constant and, for larger structures, contributed less to the overall result. Volume differences followed the normal distribution. However, established agreement limits were broad (20.4 mm3 for +-1.96 SD). There was a very good correlation between CBs volumes on both sides of the neck in both techniques (Spearman's ranks, p < 0.001). Inter-observer agreement on CBs volumes was moderately good (ICC (2,k) 0.42, p < 0.001), but with significant systematic error (bias of 10.9 mm3), even after adopting rigorous measurement criteria. None of the observed CBs was enlarged. 3.3. Receiver Operating Characteristics There were 228 readings eligible for analysis . Excluding 25 cases where the CB could not be found on CT images, 203 entries were used to generate an analogous ROC curve with the maximum likelihood of fit a binormal model . Using the ROC cut-off value of two points in our semi-quantitative confidence scale (meaning all discernible structures counted as positives), we achieved specificity of the MR method as 64.3% with 100% sensitivity. The diagnostic performance of the MR method added up to 88.4% of the area under the ROC curve and 78.0% AUC in the LROC algorithm. Details of ROC and LROC processing can be viewed in Supplementary Materials File S2. 4. Discussion In this study, we demonstrated for the first time that CBs could be visualized and assessed with an appropriately designed MR study protocol. Although MR revealed fewer CBs than CT, the diagnostic accuracy was satisfactory, even in LROC analysis. CBs assessed in MR had similar dimensions as described in published anatomical studies . CB morphology in MR approximated the CT examinations. The CB dimensions and volume were significantly larger in MR, probably due to lower spatial resolution and avid enhancement of CBs, causing a partial volume artefact. If the differences in the volume of CBs between CT and MR have a clinical impact should be established in the future. Importantly, there was no significant difference between volumes of CBs of the left and right side in MR, which may be used for comparative assessment. Instead of CTA, as suggested in some previous papers, we utilized CT examinations in the arteriovenous phase as a reference, more suitable for the assessment of parenchymal structures such as CBs and fully diagnostic . In our study, the arteriovenous phase in CT facilitated visualization of 90% of CBs. In comparison, Jazwiec et al. exposed in CTA only up to 62% of CBs , and Nguyen et al. up to 86% of CBs . Cramer et al. managed to detect 91% of expected CBs in CTA , comparable with our result. The above data support the usefulness of the arteriovenous phase in CT in the detection of CBs. There is some bias related to the expected location and number of CBs. We did not observe any developmental anomalies described in the literature, such as duplication or atypical shape . A relatively small study group and a very low incidence of such anomalies probably did not allow us to note these. The study has some limitations. The first and most important is the lack of anatomical confirmation. However, a study with histopathological verification would be difficult to design from an ethical point of view. Thus, we used the most widely available, non-invasive reference method of visualization, i.e., CT . Secondly, the study group is small in the context of anatomical investigation. However, the main aim of this study was merely to demonstrate the feasibility of CB visualization with MR. Thirdly, the spatial resolution in MR studies is lower than in CT; however, the size of the applied acquisitional voxel of the VIBE sequence complies with the Nyquist theorem. A higher spatial resolution could be achieved by a 3T scanner and allow for improved detectability and size assessment of CBs. Additionally, some factors might have impacted CT examinations used as the referral method. CT images were calculated with different kernel algorithms. According to previous studies on lung nodules, the kernel algorithm has little effect on volume measurement . Lastly, taking into the assumption that all the patients have CBs on both sides of the neck, both modalities in our study failed to recognize all the CBs. Nevertheless, the results are comparable with CTA . We see the need for further studies, not only similar to this one but also to evaluate correlations between MR and other modalities. The MR imaging of CB enlargement caused by various conditions (DM, HT, and CHF) is an exciting challenge. It needs to be emphasized that MR imaging has unquestionable advantages over CT and CTA: a lack of radiation, high soft-tissue contrast resolution, and fewer adverse reactions to macrocyclic CA. The usefulness of MR in the planning of treatment of CBs' enlargement and employing MR for imaging other chemoreceptors is also worth assessing. Modern MR scanners can offer a relatively short protocol time, and the Dixon sequence provides excellent fatty tissue saturation. 5. Conclusions CBs can be visualized in contrast-enhanced MR studies with good accuracy and inter-observer agreement. CBs assessed in MR had a similar morphology to that described in anatomical studies. Supplementary Materials The following supporting information can be downloaded at: File S1: Detailed assessment protocol of carotid bodies in CT and MRI; File S2: Details of ROC and LROC processing. Click here for additional data file. Author Contributions Conceptualization, L.B., T.K.N., D.S. and M.P.; methodology, L.B., T.K.N. and M.P.; formal analysis, M.F.K.; investigation, L.B. and T.K.N.; resources, L.B. and T.K.N.; writing--original draft preparation, L.B. and T.K.N.; writing--review and editing, T.K.N.; visualization, L.B. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Independent Bioethics Committee for Scientific Research at Medical University of Gdansk, Gdansk, Poland (NKBBN/183/2018). Informed Consent Statement Patient consent was waived by IRB due to the retrospective study design and the absence of traceable images and clinical information of the patients in the text. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Signal characteristics of the carotid body and lymphatic node. Arrows mark the carotid body (-) and lymph node (|). Axial contrast-enhanced computed tomography image of the patient with marked carotid body and lymph node (A); VIBE sequence in T1-weighted image with Dixon technique in the water-only image with (B) and without (C) contrast agent enhancement; diffusion-weighted image with b value of 1000 s/mm2 automatically fused with contrasted-enhanced VIBE sequence in T1-weighted image with Dixon technique in the water-only image (D); turbo spin-echo sequence in T2-weighted image with (E) and without (F) fat saturation. Figure 2 Comparison of the appearance of the carotid body (arrows) in contrast-enhanced computed tomography (upper row) with the appearance in contrasted-enhanced VIBE sequence in T1-weighted image with Dixon technique in the water-only images (lower row). Computed tomography (images (A-C)) and magnetic resonance (images (D-E)) examinations show the carotid body in three orthogonal planes: oblique coronal (A,D), oblique sagittal (B,E) and axial (C,F). Figure 3 Flow chart. Flow chart depicting patient selection process for the ROC/LROC analysis. Figure 4 ROC and LROC curves. Calculated ROC and LROC curves were plotted from fit-distribution parameters. diagnostics-13-00993-t001_Table 1 Table 1 The semi-quantitative confidence scale for assessment of the carotid bodies. Score ROC Threshold Criteria (Both Lists Are Equivalent) 6 Single structure with four typical features 5 Single structure with three typical features 4 Single structure with two typical features OR two structures, one of them with more typical features 3 Single structure with one typical feature OR two structures, both comparable 2 Single structure with no typical features OR three or more comparable structures 1 None structure visible The features that were taken into consideration: (1) well-defined oval or flame-like shape, (2) typical dimensions, (3) marked enhancement after contrast agent, (4) proximity to the carotid bifurcation (see also Supplementary Materials File S1). diagnostics-13-00993-t002_Table 2 Table 2 Comparison of mean carotid body dimensions (in mm) and volume (in mm3) in magnetic resonance and computed tomography, with 95% CI in brackets. MR CT ICC (2,k) p Level long transverse dimension (mm) 2.7 (2.6-2.8) 2.6 (2.5-2.7) 0.40 (0.10-0.61) <0.01 short transverse dimension (mm) 2.3 (2.2-2.4) 2.1 (2.0-2.2) -0.08 (-0.56-0.26) 0.65 longitudinal dimension (mm) 5.8 (5.6-6.1) 5.6 (5.4-5.9) 0.72 (0.57-0.82) <0.001 volume (mm3) 20.8 (19.0-22.7) 19.4 (17.5-21.4) 0.46 (0.17-0.65) <0.003 The mean degree of enhancement in carotid arteries equalled 191 HU, with a standard deviation of 42 HU. There was no significant correlation between carotid arteries enhancement and reported CB visibility (Spearman's ranks, p = 0.68). diagnostics-13-00993-t003_Table 3 Table 3 Frequency summary table of the carotid bodies eligible for ROC analysis. Method CT Total Confidence Score Invisible Visible Not Matching Matching MR Invisible 10 (4.39%) 18 (7.89%) - 28 (12.28%) 1 Visible 3 (1.32%) 0 (0.0%) 2 (0.88%) 5 (2.19%) 2 0 (0.0%) 0 (0.0%) 11 (4.82%) 11 (4.82%) 3 6 (2.63%) 6 (2.63%) 25 (10.96%) 37 (16.23%) 4 4 (1.75%) 2 (0.88%) 56 (24.56%) 62 (27.19%) 5 2 (0.88%) 2 (0.88%) 81 (35.53%) 85 (37.28%) 6 Total 25 (10.96%) 28 (12.28%) 175 (76.75%) 228 (100%) 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. Standring S. Neck Gray's Anatomy: The Anatomical Basis of Clinical Practice 41st ed. Elsevier Limited New York, NY, USA 2016 455 2. Sarrat-Torres M. Torres A. Whyte J. Baena S. Cisneros A. Sarrat R. 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PMC10000420 | Prostate cancer (PCa) is the second-most commonly diagnosed cancer in men around the world. It is treated using a risk stratification approach in accordance with the National Comprehensive Cancer Network (NCCN) in the United States. The main treatment options for early PCa include external beam radiation therapy (EBRT), brachytherapy, radical prostatectomy, active surveillance, or a combination approach. In those with advanced disease, androgen deprivation therapy (ADT) is considered as a first-line therapy. However, the majority of cases eventually progress while receiving ADT, leading to castration-resistant prostate cancer (CRPC). The near inevitable progression to CRPC has spurred the recent development of many novel medical treatments using targeted therapies. In this review, we outline the current landscape of stem-cell-targeted therapies for PCa, summarize their mechanisms of action, and discuss avenues of future development. prostate cancer therapy resistance cancer stem cells targeted therapy This research received no external funding. pmc1. Introduction 1.1. Epidemiology Prostate cancer (PCa) is the second-most common cancer in men around the world, with 288,300 estimated new cases and 34,700 estimated deaths in the United States in 2023 . In the United States alone, 13 out of every 100 men will be diagnosed with PCa in their lifetime . Surveillance, epidemiology, and end results (SEER) data concluded that between 2010 and 2015, the overall incidence of PCa in men decreased for low-risk disease. However, the incidence of high-risk disease, including metastasis, increased from 6.2 to 7.1 in men aged 50 to 74 years and from 16.8 to 22.6 in men greater than the age of 75 years . The decreased incidence in low-risk disease can at least partly be due to the 2012 change from the United States Preventive Services Task Force (USPSTF) , which concluded that PCa screening using prostate-specific antigen (PSA) should not be recommended . In 2018, the USPSTF recommendation changed again, recommending a personalized approach for PCa screening in men aged 55 to 69, which may again be associated with a change in both screening practices and the apparent incidence of disease . 1.2. Screening and Diagnosis Without proper screening, many cases of PCa may remain clinically silent . Carcinogenesis often occurs so slowly that most men with PCa die from other unrelated causes before the disease becomes advanced enough to be detected . This fact underscores the ongoing debate concerning the usefulness of PCa screening and likely accounts for the continuously changing USPSTF guidelines. For disease screening to be useful, it must be effective at reducing disease-specific morbidity and mortality by detecting the disease at an early stage. In prostate cancer, early-stage detection does not necessarily correlate with a decrease in morbidity and mortality nor a clinically beneficial outcome for the patient. Screening increases the detection of PCa among men and thus increases the apparent incidence. For example, the development of prostate-specific antigen (PSA) testing was followed by a sharp increase in the reported incidence of PCa, but has since returned closer to original levels as PSA testing has declined . According to a recent meta-analysis, PSA testing was found to effectively aid in diagnosing more men with PCa than in those who were not screened at all . This screening was also shown to reduce the risk for late-stage PCa, with the absolute risk reduction of high-grade metastatic disease being 3.1 per 1000 men as found by the European Randomized Study of Screening for Prostate Cancer (ERSPC) . PCa mortality rates have significantly decreased since the development of PSA testing; however, it is unclear if this decrease is due solely to PSA testing specifically or there are other contributing factors . Another important consideration with more screening is the increased risk of false-positive results . A prostate biopsy is the next diagnostic step following a sufficiently elevated PSA, meaning that a greater number of men may be subjected to the stress of unnecessary testing and treatment with its potential related morbidities . For example, for every 1000 men screened for PCa using PSA, 1 will need hospitalization for sepsis, 3 will need pads for urinary incontinence, and 25 will develop erectile dysfunction . As such, it is imperative to continue collecting data and adjust recommendations as needed. 1.3. Grading of Prostate Cancer The most common type of carcinoma arising in the prostate is adenocarcinoma. Upon diagnosis, the tumor is graded using the Gleason scoring system, which correlates with the patient's overall prognosis and, on biopsy specimens, helps guide treatment and management protocols. Gleason grading relies on the identification of architectural growth patterns of the tumor . It is divided into five patterns with Gleason grade 1 being the most (well) differentiated and Gleason grade 5 being the least (poorly) differentiated . A known caveat of the Gleason scoring system is that grades 1 and 2 are unable to be reliably identified in histology and therefore are not diagnosed in practice or applied in the Gleason scoring system. The Gleason score represents a composite of the two most prevalent Gleason grade patterns identified . The most predominant (primary) Gleason grade is numerically added to the next most predominant (secondary) Gleason grade, and the sum is known as the Gleason score, which ranges from 6 to 10 . The higher the Gleason score, the greater the risk of having metastatic disease as well as a worse clinical outcome following treatment of localized disease . Recently, the International Society of Urologic Pathology (ISUP) introduced a newly devised a Grade Group designation, which correlates each Gleason score with one of five distinct successive categories known as the Grade Group . This has been shown to provide more accurate stratification than the Gleason core alone. The Gleason Score and Grade Group are reported in tandem . 1.4. Treatment of Prostate Cancer PCa is treated using a risk-stratification approach in accordance with the National Comprehensive Cancer Network (NCCN) . The main treatment options for early PCa include external beam radiation therapy (EBRT), brachytherapy, radical prostatectomy, active surveillance, or a combination of these. In those with advanced disease, androgen deprivation therapy (ADT) is considered first-line therapy. ADT is used in patients with advanced metastatic disease and can be used alone or in combination with chemotherapy . The approach to this therapy is through bilateral orchiectomy or medical castration using a gonadotropin-releasing hormone (GnRH) agonist, which may be used alone or along with androgen blockade . 1.5. Mechanisms of Progression into Castration-Resistant Prostate Cancer ADT is used in patients with advanced PCa . During androgen-dependent progression, PCa cells largely rely on the androgen receptor (AR) for both growth and survival . Testosterone enters the cell by simple diffusion and is converted to dihydrotestosterone (DHT) using the cytoplasmic enzyme 5-alpha-reductase . DHT has a five-to-ten-fold increased affinity for the AR compared to testosterone . When DHT binds to the receptors in the cytoplasm, the AR undergoes phosphorylation, dimerization, and translocation into the nucleus, thus binding to the androgen-response elements within the host DNA and triggering transcription of genes involved in growth and survival . Despite ADT, the vast majority of PCa will eventually progress to a disease state called castration-resistant prostate cancer (CRPC) . The transition from androgen dependent to androgen independent tumors is still not well-understood, although continuous AR signaling in the absence of circulating androgens and AR blockage appear to be central factors . Additional hypothesized mechanisms include AR gene amplification, AR gene mutations, ligand-independent activation of the AR, involvement of coregulators, and recruitment of tumor stem cells . 1.6. Need for Targeted Therapies The near inevitable progression to CRPC and lack of effective treatment options has illustrated the significant need for novel therapies. While many pathways involved in the development of CRPC are still unknown, continued investigation into developmental and potentially oncogenic pathways have elicited the discovery of new and promising targeted therapies . These novel therapies are being approached by either specifically targeting the critical pathways or targets or through multi-targeted therapies that affect both the cancer cell and the surrounding microenvironment of the tumor . While progress is being made toward elucidating the critical components of CRPC progression, significant work is still needed in identifying and testing potential new treatments . 2. Cancer Stem Cells in Prostate Cancer A very small proportion of cells that are CD44+/a2b1/CD133+ and do not express AR, comprising less than 0.1 percent of the tumor volume, have been identified as prostate cancer stem cells (PCSC) ; the hierarchy stem cell model of PCa states that only this small subset of cells is responsible for the androgen-independent cell growth seen in PCa . Since these cells are androgen-independent in nature, they are free to continue to grow in an androgen-depleted environment and continue to multiply despite receiving ADT . These cancer stem cells (CSC) differentiate into both androgen-dependent and androgen-independent cells, accounting for the heterogenous androgen phenotype that is often observed in CRPC patients . This mechanism of tumor growth indicates the need for specific stem cell therapies . Conventional therapies eradicate the majority of cells within the tumor, but they offer only a temporary solution to a growing problem if the residual PCSCs are able to continue proliferating . 3. Targeting Prostate CSC-Related Signaling Pathways 3.1. Hedgehog (Hh) Pathway The hedgehog (Hh) signaling pathway is an important orchestrator of development in the embryonic prostate and epithelial regeneration in the adult prostate . The pathway begins with a secretory Hh ligand binding to the transmembrane Patched (Ptc) receptor, which removes the inhibitory action of the Smoothened (Smo) receptor and allows Gli transcription factors to translocate to the nucleus and promote cell differentiation . Increased activity of this pathway has been implicated in metastatic progression of PCa, opening several potential avenues for targeted therapies . Initial efforts have primarily focused on blocking the pathway intermediate Smo due to its membrane accessibility, but therapy resistance has prompted additional work on downstream effector targeting. The Smo-antagonists CDC-0449 (Vismodegib) and Sonidegib showed early promise with treating basal cell carcinoma but less robust results when utilized for PCa . It has been postulated that both downstream oncogenic activation pathways and an absence of primary cilium, the site of Gli activation by Smo, in PCa cells has thus far blunted results with direct Smo targeting . However, the downstream Gli-antagonist GANT-61 has demonstrated a more robust impact on suppressing PCa stem cell survival and self-renewal . Of note, Gonnissen et al. observed an increased radiosensitivity in GANT-61-treated PCa xenografts . In vitro, cell-intrinsic sensitivity was mediated by GANT-61 inhibition of Gli1 resulting in downstream activation of p53 signaling and cell cycle arrest with apoptosis . In vivo, additional radiosensitization was hypothesized to come from inhibition of Hh signaling in the surrounding tumor stroma, a known contributor to tumorigenesis . Several subsequent studies have shown promise with GANT-61 promoting increased sensitization to other molecular pathway targeting drugs, further emphasizing the need for additional research into relevant pathway interactions and therapeutic applicability . 3.2. Wnt Signaling Pathway The Wnt signal cascade plays a critical role in cell fate determination, embryonic patterning, cell proliferation, survival, and differentiation . The pathway begins with a specific Wnt ligand binding its specific Frizzled (Frz) transmembrane receptor, leading to activation of the Dishevelled (Dvl) protein that frees b-catenin, a protein that mediates cell proliferation and differentiation . Wnt signaling is often activated in PCa and has been correlated with progression to CRPC, higher Gleason scores, elevated PSA levels, earlier disease onset, and higher rates of recurrence . As such, a number of inhibitor molecules have been developed to exploit this important pathway through Wnt inhibitory factors, Wnt antagonists, or conditional knockout of b-catenin . Compound 3289-8625 inhibits signaling at the level of Dvl and has been shown to inhibit the growth of PC3 Pca cells in vitro . LGK974 is an inhibitor of the Porcupine (Porcn) enzyme responsible for the palmitoylation of Wnt prior to Frz binding, which is a crucial step in the process of Wnt ligand secretion . Foxy-5 is a WNT5A-mimicking peptide that specifically impairs prostate cancer invasion by inhibiting endothelial tumor cell migration through activation of Wnt-5a-mediated signaling . Pafricept (OMP-54F28) is a WNT receptor decoy and fusion protein of FZD8 ligand-binding domain that binds to all Wnt ligands . 3.3. Notch Pathway Notch glycoproteins are a family of transmembrane cell surface receptors that participate in the transmission of growth and proliferation signals . Upon ligand activation, a series of cleavage reactions leads to activation of the gamma secretase complex, which ultimately releases a Notch intracellular domain . This activated Notch translocates to the nucleus to act as a transcriptional co-activator of genes for progenitor cell differentiation and pluripotent stem cell self-renewal . As such, an increase in Notch signaling promotes tumor cell proliferation by maintaining tumor cells in a stem-cell-like proliferative fate . It has previously been demonstrated that an upregulation of Notch signaling plays a role in PCa epithelial-to-mesenchymal transition, metastasis, and progression to CRPC . Similarly, multiple inhibitory strategies targeting the Notch pathway have produced growth suppression, apoptosis, and increased sensitivity to cytotoxic chemotherapy . Gamma-secretase inhibitors (GSI) have produced some promising results in various cancers; however, RO4929097 is the only GSI trialed in Pca to date . RO4929097 demonstrated an initial preclinical and Phase 1 ability to produce slower-growing tumor phenotypes with good tolerance . A Phase 2 clinical trial sought to exploit this propensity to delay re-growth following anti-androgen therapy, but the trial was ended early due to a lack of available drug . Of note, recent studies with the GSI PF-03084014 have shown promising preclinical results in decreasing tumor growth with or without docetaxel in both Pca and CRPC, warranting further investigation . 3.4. NF-kB Signaling Pathway Nuclear factor kB (NF-kB) plays a major role in apoptosis by regulating the transcription of Bcl-2 . Activation of the NF-kB pathway in PCa cells leads to Pca progression, metastasis, recurrence, and resistance . This implies that inhibiting signaling can combat antitumor responses while increasing the vulnerability of tumor cells to anticancer medications . Bortezomib is a current anti-tumor medication on the market that utilizes proteasome inhibitors to inhibit IKB-alpha degradation through inhibition of the ER-associated protein degradation (ERAD) mechanism, which involves the retrograde translocation or dislocation of misfolded proteins out of the ER and subsequent degradation by cytosolic 26S proteasomes . It has an overall inhibitory effect on NF-kB signaling and is able to inhibit cell growth and cause apoptosis in many different cancer cell lines . It can also help in overcoming drug resistance when combined with conventional therapeutic agents or radiation and has shown anti-tumor activity when used alone in those with advanced CRPC . One method of tumor proliferation is through the independent activation of inhibitor of kB kinase (IKK) . BMS-345541 and PS1145 are novel compounds that are highly selective for IKK-beta, leading to inhibitory activity, thus triggering cell apoptosis in androgen receptor-expressing Pca cell lines . BKM120 acts downstream of the NF-kB pathway as a strong and highly selective pan-class I PI3K inhibitor . 17-(allylamino)-17-demethoxygeldanamycin is a heat-shock protein 90 (HSP90) inhibitor . Aspirin is being evaluated as a mechanism for targeting this pathway, since inflammation may have a key role in the progression of prostate cancer through unknown mechanisms, and aspirin has been shown to prevent several inflammation-related tumors . 3.5. PI3K/AKT/mTOR Pathway Alterations in the PI3K/AKT/mTOR pathway have been associated with a variety of malignancies due to its well-documented involvement with development, cell growth, proliferation, malignant transformation, metastasis, tumor progression, apoptosis, and resistance . It has been found that the signaling of this pathway is up-regulated in 30 to 50 percent of PCa subjects with phosphatase and tensin homolog (PTEN) suppression or inappropriate activation of both AKT and S6 . In prostate epithelial cells, suppression of PTEN or increased expression of AKT resulted in PI3K/AKT/mTOR activation sufficient for development of in vivo PCa . BEZ235 is a dual inhibitor of PI3K and mTOR that has been shown to reduce the tumor volume in PCa, which was mediated by the loss of PTEN . 4. Targeting Prostate CSC Microenvironment The prostate CSC niche is a microenvironment for stem cells that maintains a stem-like state . CSCs rely on a similar niche, which is able to control the differentiation and self-renewal of these cells . The CSC niche provides a microenvironment that regulates the balance between quiescence and self-renewal, actively responding to any requirements of homeostasis . This has been supported through the finding that loss of the CSC niche results in the loss of CSCs . The CSC microenvironment has been shown to protect CSCs from drug-induced apoptosis and leads to resistance . Furthermore, it has been implicated with abnormal induction of Hh, Wnt, NF-kB, Notch, PI3K/AKT/mTOR, and TGF-beta pathways and is directly involved in the development of metastasis . Bevacizumab is a monoclonal antibody that can be used to target vascular endothelial growth factor (VEGF) to disrupt the CSC microenvironment through the reduction of neovasculature at the level of the stromal epithelium . However, it was found that many PCSCs themselves are resistant to bevacizumab through Rac1-mediated ERK activation, with subsequent studies showing that inhibition of Rac1 and downregulation of P-Rex1 increased the sensitivity of these cells to bevacizumab . 5. Immunotherapies Targeting Prostate CSCs 5.1. (CAR)-Modified T-Cell Therapy Targeting CSC-Associated Tumor Antigens PCSCs have been shown to have increased expression of various cell surface markers with potential for immunotherapeutic targeting . Chimeric antigen receptor T-cell (CAR-T) therapy is a relatively recent treatment approach that exploits this differential expression and has shown great promise with both hematologic malignancies and solid tumors . By engineering T cells with artificial receptors specific for pre-selected tumor associated antigens (TAA), CAR-T has the potential for highly precise and efficacious targeting of CSCs . 5.2. Anti-CD133 CAR-T Therapy CD133 (prominin-1) is a well-documented CSC biomarker in a number of solid tumors and represents an interesting potential target for PCSC prognostication and therapeutic intervention . Collins et al. originally described the isolation of CD44+/a2b1high/CD133+ PCSCs and their ability to reconstitute cancer bulk on xenograft inoculation . Subsequently, a gene profiling analysis of CD133+ cells performed by Kanwal et al. identified an array of upregulated stem cell markers consistent with enhanced clonogenic and tumorigenic capacity . Initial efforts at CAR-T targeting of CD133 have shown promising results in a number of solid tumors. Zhu et al. derived AC133-CAR-T cells for glioblastoma multiforme that demonstrated good CSC recognition and inhibition of orthotopic xenograft growth . Additionally, a phase 1 clinical trial of CD133-CAR-T cells from Wang et al. further supported the feasibility, controllable toxicities, and effectiveness of CD133-targeted therapy for a number of highly metastatic malignancies . Studies investigating CD133-CAR-T therapy specifically for PCSCs remain outstanding, but the growing body of evidence linking CD133 activity to PCSC stemness supports further investigation into this immunotherapeutic approach. 5.3. CAR T Cells Targeting the CSC Marker EpCAM Epithelial cell adhesion molecule (EpCAM) is another well-known biomarker commonly overexpressed in PCSCs . Multiple studies have demonstrated a positive association between the degree of overexpression and the progression of PCa metastasis and resistance . An early preclinical investigation by Deng et al. showed early promise with significant tumor-killing ability of EpCAM-CAR-transduced human peripheral blood lymphocytes both in vitro and in vivo . However, the distribution of EpCAM in normal epithelia has raised some concerns for off-tumor immunopathology, particularly regarding adverse pulmonary effects . Only a single clinical trial with an unknown recruitment status has been initiated to investigate EpCAM-CAR-T therapy against PCSCs. As such, additional studies are needed to further determine the efficacy and toxicity of EpCAM-targeted interventions in PC. 6. Targeted Nanoparticles The use of nanoparticles as chemotherapeutic delivery vehicles is a developing avenue of targeted tumor therapy. Originally, nanomedicine relied on the increased penetrability of tumor vasculature; however, more recently developed nanoparticles exploit tumor surface moieties for more precise targeting . PCSC, commonly identified by their CD44, a2b1, and CD133 surface markers, appear to be ideal candidates for this treatment modality. Traditional drugs developed for PCa, including abiraterone acetate, cabozantinib, and docetaxel, have inherent drawbacks in PCSC populations with relatively poor targeting, tumor resistance, and a variety of adverse effects . Nanomedicine therapies offer the potential to avoid these pitfalls through the highly specific targeting of PCSC populations. Thus, with their enhanced utilization efficiency and reduced toxicity profile, nanoparticle interventions represent an enticing direction for future therapeutic innovation . 6.1. CD44-Targeting Therapies CD-44 is a transmembrane glycoprotein commonly used in the identification of PCSC, with the overexpression of CD44 being associated with increased PCa tumorigenicity and metastasis . To date, a variety of nanotherapeutic approaches have been developed that tend to either utilize hyaluronic acid (HA), the primary ligand of CD44, or CD44 antibodies for drug targeting. Huang et al. developed a HA-based nanoparticle to deliver bioactive epigallocatechin-3-gallate to CD44-positive PCa cells . In vitro results demonstrated efficient nanoparticle internalization via ligand-receptor recognition with inducible G2/M phase cell cycle arrest and inhibition of PCa cell growth . Subsequent in vivo results confirmed the specificity of CD44 binding, as well as the nanoparticle's ability to promote PCa cell apoptosis and significantly decrease tumor activity and tissue inflammation . In a different approach, Wei et al. generated nanoparticles with CD44 antibodies (SM-LPN-CD44) to deliver the potent therapeutic agent salinomycin to CD44-positive PCSC . In vivo assays demonstrated an enhanced ability for the SM-LPN-CD44 nanoparticles to deliver salinomycin to PCSC compared to non-targeted nanoparticles, with the SM-LPN-CD44 nanoparticles also showing a significant decrease in CD44-positive cells and drug concentration needed to inhibit 50% of tumor growth (IC50) . Mahira et al. opted to develop a variant of the HA-targeted method by producing cationic liposomes coated with HA to deliver the chemotherapeutic agents cabazitaxel and silibinin directly to CD44-positive PCSC . Their results demonstrated that the HA-coated liposomes had significantly increased cytotoxicity in the target cells, with a lower IC50 and improved colony formation inhibition, G2/M phase arrest, and induction of apoptosis . Sanfilippo et al. sought to employ another variant of the HA-targeting model by utilizing synthesized spherical gold nanoparticles capped with low and high molecular weight HA . The results showed a higher rate of CD44-positive PCa cellular uptake for nanoparticles functionalized with HA compared to those without HA, supporting this approach as another possible targeting system for therapeutic delivery . In a more recent study, Pramanik et al. explored yet another variant of the HA-targeting method by creating HA-functionalized liquid crystalline lipid nanoparticles, termed cubosomes, to deliver chemotherapeutic copper acetylacetonate to CD44-expressing tumors . Their results showed increased selective uptake of the targeted-cubosomes by CD44-positive cells compared to non-targeted-cubosomes, as well as significantly elevated rates of apoptotic cell death induced by the targeted cubosomes . While this study only utilized breast and colon cancer cell lines, the selective CD44-targeting of the nanoparticle shows potential for use in other solid tumors, such as PCa, and warrants further investigation. 6.2. CD133-Targeted Therapy CD133 is a transmembrane glycoprotein thought to help organize cell membrane topography and is the most frequently used cell surface marker to detect and isolate cancer stem cells from a variety of solid tumors, including PCa . There are a number of studies that have shown promising early results in targeting CD133 with antibodies or oligonucleotides known as aptamers. Tan et al. utilized a CD133-antibody approach by functionalizing a gold nanoprobe (GNS@IR820/DTX-CD133) to deliver IR820 and docetaxel to PCa cells for synergistic photothermal therapy, photodynamic therapy, and chemotherapy . In vivo results demonstrated a significantly higher cellular uptake efficiency and number of dead PCa cells with the targeted nanoprobe compared to non-targeted interventions, supporting the importance of CD133-targeting in therapeutic efficacy . In the realm of aptamer targeting, Ma et al. developed curcumin-containing lysosomes embedded with the aptamer A15, which has shown promise in specifically targeting CD133-positive cancer stem cells . Their results showed significantly higher rates of PCa-specific drug internalization, inhibition of cell growth, and decreased tumor volume in the A15-targeted group compared to the non-targeted groups . As a whole, each of these preclinical studies highlight the potential for CD133-mediated PCSC therapeutic targeting and support the need for additional investigation. 7. Anti-CSC Targeted Therapies: Clinical Trials More than 50 clinical trials were identified on www.clinicaltrials.gov (accessed on 15 January 2023) to involve PCa and one of the previously discussed targeted therapies. Several of these were excluded from further review due to their only being indirectly involved with PCSCs. For example, study NCT03103152 involving aspirin measured the rate of patient recruitment to a randomized chemoprevention study with a secondary outcome of measuring response to treatment in those receiving aspirin and/or D3 via MRI. Study NCT00349557 is working to determine the acute toxicities from IMRT with other therapies including bevacizumab. Study NCT03878524 is looking at the feasibility of implementing an individualized treatment strategy in those receiving SMMART-PRIME therapy including bevacizumab. Study NCT03878524 is investigating the feasibility of implementing individualized therapy with GDC-0449. Study NCT03878524 is looking at the feasibility of implementing an individualized treatment strategy with bortezomib. Because of these exclusions, 52 of these clinical trials were investigated further. The status of each trial is listed as recruiting, completed, terminated, or unknown based on its latest update. The overall profile of each targeted therapy is summarized below with a full listing of included clinical trials available in Table 1. 7.1. Hedgehog (Hh) Pathway One completed clinical trial (NCT02111187) involving Soniedegib found that six of seven participants had at least a twofold reduction in GLI1 expression following treatment when comparing one group that received Sonidegib prior to prostatectomy and another that underwent prostatectomy alone. 7.2. WNT Signaling Pathway Awaiting the results for two clinical trials (NCT0202029, NCT02655952) investigating the safety profiles of Foxy-5. 7.3. Notch Pathway A clinical trial (NCT01200810) for RO4929097 was terminated due to a lack of available drug. 7.4. NF-kB Pathway Following treatment with a combination of weekly docetaxel and bortezomib, there was no improved efficacy when compared to prior studies which used docetaxel alone. It was also found that bortezomib has minimal activity in patients with CRPC and is unlikely to make an impact on treatment efficacy (NCT00059631). Another trial focusing on the safety of bortezomib as pre-treatment in those about to undergo prostatectomy found that none of the subjects were affected by poor wound healing or excessive bleeding (NCT00425503). 7.5. PI3K/AKT/mTOR Pathway One clinical trial (NCT01717898) for BEZ235 was terminated due to high toxicity. Another clinical trial (NCT01634061) for BEZ235 was completed and is pending results. 7.6. Microenvironment (VEGF) In a clinical trial evaluating the efficacy of bevacizumab and erlotinib, it was found that 7 of 19 subjects had tumor recurrence after an average of 285 days (NCT00203424). Another study found that the average time to tumor progression was seven months in those taking satraplatin and bevacizumab in mPca patients previously treated with docetaxel (NCT00499694). One study found that in those receiving ADT alone the average relapse free survival rate was 13 months compared to those receiving ADT and bevacizumab, who had an average relapse free survival of 10 months (NCT00776594). Another trial found that, for every one patient, 0.22 patients experienced an endorectal MRI response after completion of six cycles of neoadjuvant therapy of bevacizumab plus docetaxel (NCT00321646). One trial evaluating the PSA and immune response to docetaxel, thalidomide, prednisone, and bevacizumab found that 52 of 60 subjects had a PSA response (NCT00089609). Another trial focused on determining the maximum tolerated dose of temsirolimus with a fixed dose of bevacizumab found that 5 of 16 subjects had a change from baseline PSA at a MTD of 25 mg (NCT01083368). In those with non-metastatic CRPC receiving bevacizumab, it was found that 5 of 15 subjects had a PSA decline of >/=50 percent, 14 of 15 experienced drug toxicities, and the average time to PSA progression was 2.8 months (NCT-1656304). It was also found that 98 percent of subjects had PSA progression at one year in those receiving bevacizumab one year following treatment with ADT (NCT00658697). Those taking docetaxel and placebo survived an average of 21.5 months while those receiving docetaxel plus bevacizumab survived an average of 22.6 months in those who did not respond to ADT (NCT00110214). Those taking gemcitabine hydrochloride, cisplatin, and bevacizumab survived an average of 14.5 months, while those taking the same regimen but without bevacizumab survived 14.3 months (NCT00942331). 7.7. CAR-T A clinical trial (NCT03013712) for EpCAM currently has unknown status. 7.8. Nanoparticles Two clinical trials (NCT01300533 and NCT02646319) have been completed and are pending results. One clinical trial (NCT02769962) is currently recruiting with projected completion in 2023. Two clinical trials (NCT03531827 and NCT04221828) were terminated due to toxicity and lack of enrollment, respectively. One clinical trial (NCT00499291) was withdrawn for unknown reasons. There are currently 52 clinical trials of interest available on the targeted therapies mentioned. Only 13 have been completed with available results as of 8 January 2023. Furthermore, 16 of the studies mentioned in Table 1 describe only safety and maximum tolerated dose of certain therapies rather than the overall effectiveness of treatment. These studies were included in this review, since the safety of the therapy is as important as the efficacy in most cases. The aforementioned 13 completed trials involve only three of the different targeted pathways. For the Hh pathway, trials involving GDC-0449 are incomplete, and there are currently no trials involving GD-61. For the Wnt pathway, there are no studies involving 3289-8625, LGK974, or OMP-54F28, and the trials involving Foxy-5 do not have results. The trial involving RO4929097 of the Notch pathway was terminated. Regarding NF-kB, there are no trials with PS1145, BMS345541, or 17-(allylamino)-17-demethoxygeldanamycin, and there are no results for the trials using bortezomib, aspirin, or BKM120. Both of the PI3K/AKT/mTOR pathway trials targeting BEZ235 do not have results. There is one clinical trial looking at EpCAM for CAR-T that has had unknown status since 2017, and no trials involving anti-CD133. The highest number of trials with completed results involved VEGF-targeting bevacizumab therapy, comprising 10 of the 13 completed clinical trials with available results. It should be noted that no clinical trials involving nanoparticle therapy specifically targeting PCSC were able to be found. However, several trials involving more generalized nanoparticle therapy for advanced PCa were included to highlight the current state of investigation. At this time, 15 clinical trials have been marked as complete but have not posted results, with 9 of these investigating the safety of treatment only. These findings will hopefully provide further insight into the effectiveness of the Wnt-targeting Foxy-5, NF-kB-targeting bortezomib/aspirin/BKM120, and PI3K/AKT/mTOR-targeting BEZ235. Furthermore, the results of the seven currently active trials are also highly anticipated and will provide additional information on the Hh-targeting GDC-0449, NF-kB-targeting bortezomib, and VEGF-targeting bevacizumab therapies. 8. Conclusions and Future Directions In conclusion, based on this review of potential clinical targets and available clinical trials, it is clear that a significant need exists for further research and testing into these targeted therapies. The intricacies and interactions among the developmental pathways identified here still require a great deal of investigation to better understand their targeting effects. Most of the developed therapies still require extensive testing with regard to their feasibility, safety, efficacy, and dosing. Yet, even with the limited results published to date, it remains clear that targeted anti-CSC therapies have the potential for significant clinical impact on the treatment of CRPC and remain an important avenue for future treatment. In agreement with Wolf et. al., future characterization of PCSCs using genomics and proteomics would increase our knowledge of PCSC targets of interest, increase treatment possibilities, and provide more individualized therapy for those diagnosed with prostate cancer even in advanced stages . Acknowledgments Figures were created with BioRender.com. All rights and ownership of BioRender content are reserved by BioRender (Agreement numbers WU2508652Z, ET25169DTN, OI2516BX7K, GU2516D4GT, EN2516EZUP, and KM2516HHGQ). BioRender content included in the completed graphic is not licensed for any commercial uses beyond publication in a journal. For any commercial use of this figure, users may, if allowed, recreate it in BioRender under an Industry BioRender Plan. Author Contributions Conceptualization, H.F.B.; methodology, S.G. and M.R.; validation, H.F.B.; data curation, S.G., M.R. and H.F.B.; writing--original draft preparation, S.G. and M.R.; writing--review and editing, H.F.B., F.A., Y.O. and R.P.; visualization, H.F.B.; supervision, R.P.; project administration, H.F.B.; funding acquisition, H.F.B. 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. Figure 1 PCa tumor grading using the Gleason and ISUP grading system. Created with BioRender.com (2023). Figure 2 Hedgehog signaling pathway featuring the SMO antagonists Vismodegib and Sonidegib and Gli antagonist GANT-61. Created with BioRender.com (2023). Figure 3 Wnt signaling pathway featuring Porcn inhibitor LGK974, WNT receptor decoy Pafricept, and Dvl signaling inhibitor compound 3289-8625. Created with BioRender.com (2023). Figure 4 Notch signaling pathway featuring GSIs RO4929097 and PF-03084014. Created with BioRender.com (2023). Figure 5 NF-kB signaling pathway featuring IkB degradation inhibitor bortezomib and IKK-beta inhibitors BMS-345541 and PS1145. Created with BioRender.com (2023). Figure 6 PI3K/AKT/mTOR signaling pathway featuring the PI3K/mTOR inhibitor BEZ235. Created with BioRender.com (2023). cancers-15-01621-t001_Table 1 Table 1 A summary of all clinical trials via clinicaltrials.gov (accessed on 15 January 2023) available on the targeted therapies discussed including Hedgehog (Hh) pathway and targeting with inhibitors (sonidegib, GANT-61, and GDC-0449), Wnt signaling pathway and targeting with inhibitors (3289-8625, LGK974, Foxy-5, and OMP-54F28), Notch pathway and targeting with inhibitors (RO4929097), NF-kB pathways and targeting with inhibitors (bortezomib, PS1145, BMS345541, aspirin, 17-(allylamino)-17-demethoxygeldanamycin, and BKM120), PI3K/AKT/mTOR pathway and targeting it with inhibitors (BEZ235), prostate CSC microenvironment (Bevacizumab), and immunotherapies (anti-C133 CAR-T therapy and CAR T cells targeting the CSC marker EpCAM). Pathway Target NCT Number Phase Status Notes Hh Sonidegib NCT02111187 1 Completed Primary outcome: change from baseline in tissue GLi1 expression levels in those receiving LDE225, compared to those receiving no treatment prior to prostatectomy. Results: 6/7 participants had at least a 2-fold reduction in GLi1 expression in post treatment vs. pretreatment tumor tissue. NCT02182622 1 Withdrawn Primary outcome: maximum tolerated dose of LDE225 plus docetaxel/prednisone. Withdrawn: no reason reported. GDC-0449 NCT01163084 1,2 Terminated Primary outcome: proportion of patients with </=5% tumor involvement in those receiving leuprolide acetate or goserelin acetate with or without vismodegib. Terminated: no reason reported. NCT 00607724 1 Completed Primary outcome: percentage of participants with dose-limiting toxicities (DLTs) Results: 0/68 subjects affected. NCT02465060 2 Recruiting Primary outcome: objective response rate in those receiving targeted therapy directed by genetic testing. Recruiting: projected completion 2025. Wnt Foxy-5 NCT02020291 1 Completed Primary outcome: safety and tolerability of Foxy-5. No results posted. NCT02655952 1 Completed Primary outcome: presence of dose limiting toxicities of Foxy-5. No results posted. Notch RO4929097 NCT01200810 2 Terminated Primary outcome: time to PSA progression in those receiving bicalutamide and RO4929097. Terminated: lack of study drugs. NF-kB Bortezomib NCT00103376 2 Terminated Primary outcome: PSA response in those receiving bortezomib with or without hormone therapy. Terminated: low accrual. NCT00183937 2 Completed Primary outcome: number of patients with improved serum PSA response rate in those receiving bortezomib and docetaxel. No results posted. NCT00059631 1 Completed Primary outcome: maximum tolerated dose of mitoxantrone combined with bortezomib. No results posted. NCT00193232 2 Completed Primary outcome: objective response rate. Results: treatment with combination of weekly docetaxel and bortezomib showed no improved efficacy vs. previous results with docetaxel alone, bortezomib has minimal activity in pts with HRPC and is unlikely to make any impact on treatment efficacy. NCT00425503 2 Completed Primary outcome: assess the safety of PS-341 as a pretreatment in patients who are to undergo a radical prostatectomy measured with poor wound healing and excessive bleeding. Results: 0/37 subjects affected. NCT00064610 1,2 Completed Primary outcome: determine the maximum tolerated dose and preliminary activity of PS-341 plus docetaxel. No results posted. NCT00667641 1 Completed Primary outcome: maximum tolerated dose of paclitaxel in combination with bortezomib. No results posted. NCT00620295 1 Completed Primary outcome: maximum tolerated dose of bortezomib and gemcitabine. No results posted. Aspirin NCT03819101 3 Recruiting Primary outcome: overall survival in those taking aspirin and atorvastatin. Recruiting: projected completion 2034. NCT02757365 4 Unknown Primary outcome: aspirin PSA response, digital rectal exam, US of prostate, biopsy, fPSA level. Unknown: last status verification in 2016 NCT02420652 2 Terminated Primary outcome: change in stable PSA rates after 6 months of metformin hydrochloride and aspirin or placebo. Terminated: slow accrual. NCT01428869 Unknown Completed Primary outcome: diagnosis of prostate cancer in REDUCE study participants treated with statins, aspirin, and dutasteride. No results posted. NCT00234299 NA Completed Primary outcome: assess the effect of oral aspirin on in vivo prostate epithelial cells. No results posted. NCT02804815 3 Recruiting Primary outcome: survival and disease recurrence in those receiving aspirin after primary therapy. Recruiting: projected completion 2026. BKM120 NCT01695473 2 Terminated Primary outcome: percent of patients with decrease in phosphorylated S6 ICH from baseline, percent with downstream target inhibition of PI3K in prostate tumor tissue measured by ICH when treated with BKM120. Terminated: lack of accrual. NCT01634061 1 Completed Primary outcome: incidence of dose limiting toxicities and PSA decline >/= 30% in those getting abiraterone acetate and BEZ235 or BKM120. No results posted. NCT01385293 2 Terminated Primary outcome: progression free survival prostate cancer working group 2 criteria or based on the onset of a skeletal related event in those getting BKM120. Terminated: 1st stage due to futility NCT02035124 2 Withdrawn Primary outcome: number of subjects with serious and non-serious adverse events and progression free survival in those receiving cabazitaxel and BKM120. Withdrawn: slow accrual, no subjects enrolled. NCT02487823 1 Terminated Primary outcome: determine MTD of BKM120 when given orally in combination with daily bicalutamide and LH-RH agonists. Terminated: defect of recruitment. NCT01741753 1 Terminated Primary outcome: safety profile and mTD for BKM120/abiraterone/prednisone. Terminated: slow accrual, supplier of BKM120 asked to cease further enrollment. PI3K/AKT/mTOR BEZ235 NCT01717898 1,2 Terminated Primary outcome: number of reported DLT and MTD when combining BEZ235 and abiraterone acetate, decline in PSA > 50%. Terminated: DLT on lowest dose level. NCT01634061 1 Completed Primary outcome: incidence of DLT and PSA decline >/= 30% in those getting abiraterone acetate and BEZ235 or BKM120. No results posted. VEGF Bevacizumab NCT00203424 2 Completed Primary outcome: evaluate efficacy of bevacizumab and erlotinib, time to tumor recurrence. Results: 7/19 subjects had tumor recurrence, average 285 days. NCT00499694 NA Completed Primary outcome: time to progression in those taking satraplatin and bevacizumab in mPCa patients previously treated with docetaxel. Results: average time to progression 7 months. NCT00574769 1,2 Completed Primary outcome: MTD of RAD001 with docetaxel/bevacizumab. No results posted. NCT00776594 2 Completed Primary outcome: relapse-free survival in those treated with ADT vs. ADT plus bevacizumab. Results: average relapse free survival of 13 months vs. 10 months respectively. NCT00321646 2 Completed Primary outcome: endorectal MRI response after completion of 6 cycles of neoadjuvant therapy in subjects receiving bevacizumab plus docetaxel. Results: 22% of participants had a response. NCT00027599 2,3 Completed Primary outcome: efficacy of APC8015 and bevacizumab in terms of decline in PSA and effect on PSA doubling time. No results posted. NCT00348998 2 Unknown Primary outcome: determine the safety and efficacy of bevacizumab with hormonal therapy and radiotherapy. Unknown: last status update in 2008 stated active, not recruiting. NCT00089609 2 Completed Primary outcome: number of participants with PSA response and immune response to docetaxel, thalidomide, prednisone, and bevacizumab. Results: 52/60 subjects had PSA response, immune response not measured. NCT01083368 1,2 Completed Primary outcome: MTD of temsirolimus with fixed dose bevacizumab and objective response via PSA level. Results: MTD of temsirolimus was 25 mg, 5/16 subjects had a change from baseline PSA. NCT01656304 2 Completed Primary outcome: PSA response rate with bevacizumab in non-metastatic CRPC, toxicities of bevacizumab, and time to PSA progression. Results: 5/15 subjects had a PSA decline >/=50%, 14/15 subjects had toxicities, time to PSA progression = average 2.8 months. NCT00016107 2 Completed Primary outcome: time to objective progression, objective and PSA response rates, and toxicity in those receiving chemo plus bevacizumab. No results posted. NCT00658697 2 Completed Primary outcome: PSA progression at 1 year after completing ADT. Results: 98% had PSA progression at 1 year. NCT00110214 3 Completed Primary outcome: overall survival in those receiving docetaxel and prednisone with or without bevacizumab who did not respond to hormone therapy. Results: those taking docetaxel plus placebo survived average 21.5 months, docetaxel plus bevacizumab survived average 22.6 months. NCT00942331 3 Completed Primary outcome: overall survival in those receiving gemcitabine hydrochloride and cisplatin with or without bevacizumab. Results: those taking gemcitabine hydrochloride, cisplatin, and bevacizumab survived average 14.5 months, gemcitabine hydrochloride, cisplatin, and placebo survived average 14.3 months. NCT05489211 2 Recruiting Primary outcome: objective response rate, number of subjects with adverse events in those receiving dato-dxd monotherapy and in combination with anti-cancer drugs including bevacizumab. Recruiting: projected completion 2025. CAR-T EpCAM NCT03013712 1,2 Unknown Primary outcome: toxicity profile of EpCAM targeted CAR T cells with CTCAE. Unknown: last status update 2017 stated recruiting. Nanoparticles Nanoparticle-Based Drug Delivery System NCT00499291 NA Withdrawn Primary outcome: develop a population pharmacokinetic model in those receiving paclitaxel albumin-stabilized nanoparticle formulation. Withdrawn: no reason reported NCT04221828 2 Terminated Primary outcome: number of adverse events in those receiving NanoPac (sterile nanoparticle paclitaxel). Terminated: lack of enrollment NCT03531827 2 Terminated Primary outcome: percentage of participants with anti-tumor activity with combined CRLX101 and enzalutamide in those who previously failed enzalutamide therapy. Terminated: closed due to toxicity NCT02769962 2 Recruiting Primary outcome: determine overall response rate of EP005 plus Olaparib in mCRPC. Results: projected completion 2023 NCT02646319 1 Completed Primary outcome: clinical benefit rate, incidence of adverse events, survival time, and time to disease progression in those receiving nanoparticle albumin-bound rapamycin. No results posted. NCT01300533 1 Completed Primary outcome: determine DLT of BIND-014. No results posted. 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. |
PMC10000421 | The assessment of PD-L1 expression in TNBC is a prerequisite for selecting patients for immunotherapy. The accurate assessment of PD-L1 is pivotal, but the data suggest poor reproducibility. A total of 100 core biopsies were stained using the VENTANA Roche SP142 assay, scanned and scored by 12 pathologists. Absolute agreement, consensus scoring, Cohen's Kappa and intraclass correlation coefficient (ICC) were assessed. A second scoring round after a washout period to assess intra-observer agreement was carried out. Absolute agreement occurred in 52% and 60% of cases in the first and second round, respectively. Overall agreement was substantial (Kappa 0.654-0.655) and higher for expert pathologists, particularly on scoring TNBC (6.00 vs. 0.568 in the second round). The intra-observer agreement was substantial to almost perfect (Kappa: 0.667-0.956), regardless of PD-L1 scoring experience. The expert scorers were more concordant in evaluating staining percentage compared with the non-experienced scorers (R2 = 0.920 vs. 0.890). Discordance predominantly occurred in low-expressing cases around the 1% value. Some technical reasons contributed to the discordance. The study shows reassuringly strong intra-observer concordance among pathologists in PD-L1 scoring. A proportion of low-expressors remain challenging to assess, and these would benefit from addressing the technical issues, testing a different sample and/or referring for expert opinions. PD-L1 breast cancer VENTANA SP142 triple-negative Egyptian Cultural and Educational BureauMinistry of Higher Education and Scientific Research, General Mission SectorBirmingham CR-UK CentreCA17422/A25154 M.Z. was funded by a grant from the Egyptian Cultural and Educational Bureau and sponsored by the Ministry of Higher Education and Scientific Research, General Mission Sector (Egypt). A.M.S. is supported by a Birmingham CR-UK Centre Grant, CA17422/A25154. pmc1. Introduction Advances in biomarker assessment, companion diagnostics and genomics have revolutionised the way breast cancer is currently classified and managed . The immune microenvironment of solid tumours, including in breast cancer, plays a pivotal role in tumour development and progression . Cancer cells can evade the regulatory pathways of Programmed death-1 (PD-1) and its ligand (PD-L1), thus overcoming the cytotoxic effect of T cells. Immune checkpoint blockades using anti-PD-L1 inhibitors have been investigated in various trials in lung, melanoma and, more recently, breast cancer, with confirmed efficacy . This has led to the approval of immune modulators for the treatment of PD-L1-positive breast cancer, and this is currently being incorporated in various guidelines . The first-approved and most established immune checkpoint inhibitor in breast cancer is atezolizumab, for which a companion diagnostic assay (the VENTANA SP142) is required for selecting patients eligible for this drug. The limited data available in the literature on non-breast cancer suggest the poor reproducibility of PD-L1 SP142 scoring . Some studies compared the performance of various PD-L1 assays , and only few analysed pathologist concordance in the scoring of breast cancer . Those latter studies were small and heterogeneous, with some including training sets . Furthermore, the nature of discordant cases was not analysed, nor was there an assessment of the intra-observer agreement or the effect of the pathologist's experience. In addition, all previous studies focused on TNBC, and, therefore, information on pathologist concordance in the scoring of in HER2-positive and/or luminal breast cancer does not exist. Emerging data suggest cross-talk between HER2 and PD-L1 and potentially support the use of immunotherapy in HER2-positive breast cancer . PD-L1 expression is correlated with the response to neoadjuvant chemotherapy in HER2-positive breast cancer . We therefore aimed to assess the intra-observer concordance of breast pathologists of various expertise and geographical locations in reporting a large cohort of PD-L1 SP142-stained invasive breast carcinomas of various molecular subtypes to assess if particular molecular subtypes would be more or less prone to poor inter-observer concordance. We also sought to analyse discordant cases in detail to gain insight into the reasons for discrepancies in PD-L1 results, allowing for a subsequent search for strategies on how to tackle them. 2. Materials and Methods Core biopsies from a total of 100 cases of primary breast cancers were included in the study. Cases were selected retrospectively from the files of a single large UK institution (Queen Elizabeth Hospital Birmingham) to include all molecular subtypes with enrichment for the TNBC group. First, 4 mm sections of formalin-fixed, paraffin-embedded tumour blocks were cut and stained using the VENTANA SP142 anti-PD-L1 rabbit monoclonal primary antibody and a VENTANA Benchmark ULTRA automated staining platform, according to the manufacturer's protocol. A section from a cell block containing three cell lines with various staining intensities and a section of normal tonsil were included as on-slide controls. Paired H&E sections and PD-L1-stained immunohistochemistry slides were digitally scanned using a Leica Aperio AT2 slide scanner at x40 and uploaded to the University of Birmingham digital platform via a secure link: Last accessed 23 February 2023. Each participant was provided with a unique username and password to allow for access to the digital platform for whole slide scoring. Twelve pathologists from eight institutions representing three European countries (United Kingdom, Republic of Ireland, Belgium) evaluated all cases in round one, of whom 10 re-scored the same cases in round two, separated by at least 3 months of a washout period designed to assess intra-observer variability. All pathologists had previously received Roche training for SP142 PD-L1 scoring in TNBC and passed a proficiency test. PD-L1 SP142 Immune cell (IC) scoring was conducted according to the recommended scoring algorithm , using a cut-off value of >=1% to indicate positivity. In addition, the pathologists were asked to provide their percentage of immune cells with positive staining for each case, including those cases scored as negative. All scorers completed a survey assessing their experience in breast pathology reporting as well as their training and real-life reporting of PD-L1. Statistical Analysis The data were tabulated and statistically analysed using the SPSS (IBMS) software version 28. We used standard statistical analyses for assessing intra/inter-rater concordance/agreement, which have been previously described . Intraclass correlation coefficient (ICC), which is a measure of the reliability of ratings (using median percentage scores), was used to determine if subjects/items can be rated reliably by different raters. ICC is a descriptive statistic used to assess the consistency or reproducibility of quantitative measurements made by different observers measuring the same quantity. The value of an ICC can range from 0 to 1, with 0 indicating no reliability among raters and 1 indicating perfect reliability among raters. The ICC results are interpreted as follows: values < 0.5 indicate poor reliability, values from 0.5 to 0.75 indicate moderate reliability, values from 0.75 to 0.9 indicate good reliability and values greater than 0.9 indicate excellent reliability . In our study, we used a Two-Way Random model, testing both the consistency and the absolute agreement relationships and the mean of ratings as the unit of measurement. Fleiss multiple-rater Kappa statistics of inter-observer and intra-observer agreement for designating cases as PD-L1-positive versus -negative using a cut-off value of 1% were calculated. Fleiss' Kappa k is a measure of inter-rater agreement used to determine the level of agreement between two or more raters when the method of assessment, known as the response variable, is measured on a categorical scale. The Kappa results are interpreted as follows: values <= 0 indicate no agreement, values from 0.01 to 0.20 indicate none to slight agreement, values from 0.21 to 0.40 indicate fair agreement, values from 0.41 to 0.60 indicate moderate agreement, values from 0.61 to 0.80 indicate substantial agreement and values from 0.81 to 1.00 indicate almost perfect agreement. A case was regarded as PD-L1 positive or -negative if more than 50% of the participants designated it as positive or negative, respectively. The consensus score was considered a majority score if 67% or more of the participants agreed on the categorisation. If all participants agreed (100%), this was regarded as absolute agreement (AA). The cases with agreement less than 67% and above 50% were considered challenging. In cases of no agreement (50% or less), a case was considered as PD-L1-positive or -negative based on the consensus of the experienced pathologists only. Scatter plots were used to visualise percentage PD-L1 scores, and the strength of the relationship between scores was expressed as a squared correlation coefficient (R2). All analyses were supervised by an expert in pathology informatics (PL). An outline of the study methodology is shown in Figure 1. 3. Results 3.1. Cohort Characteristics A total of 100 breast cancers were assessed, comprising 29/93 (33.3%) grade 2 and 62/93 (66%) grade 3 cases, while 7 cases had missing grades. The patient ages ranged from 42 to 59 years, with a median of 49 years. Fifty-eight carcinomas were triple-negative, 28 were luminal and 14 were Her2-positive. All cases were evaluated independently by twelve pathologists, including nine specialist consultant breast pathologists, of whom six had 1-3 years' experience in PD-L1 scoring, as per the survey responses. All scorers had significant experience in breast pathology reporting, and six had experience in scoring PD-L1 SP142 in TNBC in routine practice. A consultant Biomedical Scientist and two trainee pathologists were among the scorers. Ten pathologists scored round two, following a washout period. The overall percentage of PD-L1 positivity for all of the breast cancer molecular subtypes was 36-38%, and the highest was for TNBC (55%) (Table 1). 3.2. Inter-Observer Agreement and Pathologist Experience The Kappa of the inter-observer agreement between the participants in classifying cases as PD-L1-positive vs. -negative and the number of cases with absolute agreement (AA) for rounds one and two were calculated. The overall agreement was substantial (Kappa 0.654 and 0.655 for the first and second rounds, respectively) (Table 2). There was absolute agreement on scoring cases as either positive or negative in 52 cases in the first round . This increased to 60 cases in the second round (Table 3). A further 42 and 32 cases achieved majority agreement in the first and second rounds, respectively. Overall, the Kappa value, for all cases, was similar between experienced pathologists and those without considerable experience in PD-L1 reporting. However, it was higher for expert pathologists scoring PD-L1 in the TNBC group (0.6 vs. 0.568 in the second round) (Table 4). 3.3. Concordance of PD-L1 Percentage Expression When the median percentage of PD-L1 expression was considered, the expert pathologists had a higher and tighter concordance compared with the non-experts (R2 = 0.920 vs. 0.89). The overall concordance was excellent (R2 = 0.935). The distribution of the percentage scoring among all raters (those with and without experience in PD-L1 routine reporting) in both rounds is shown in Figure 3A-E. 3.4. Reasons for Discordance Ten cases were regarded as challenging, with low (<67->50%) or no agreement (<50%), most of which (8/10) were of the TNBC phenotype (Table 5). All ten cases had a low PD-L1 score, with a median range of 0.5-1%, highlighting the difficulties in classifying cases close to the cut-off value of 1%. Four cases were challenging in both rounds, indicating of the innate difficulty of the cases, regardless of the pathologists' expertise in PD-L1 scoring. We analysed the reasons for the difficulties in scoring those cases by reviewing the digital images and referring to pathologists' comments on scoring. Those cases were reassuringly recognised as difficult by most scorers due to the nature of the tumour and/or technical issues. Reasons for discordance included uncertainty as to the presence/extent of the in situ carcinoma, a small amount of invasive carcinoma, positive staining around the normal mammary epithelium, very focal staining, background staining and staining within areas of necrosis . It is of note that the consensus in scoring those challenging cases among the expert pathologists ranged from no agreement (50%) to absolute agreement (100%), with a higher percentage of the former in the first round (3/10; 30%) compared to the second (1/10; 10%). For the experts, concordance improved in the second round, with all but one case showing absolute agreement. Strong to almost perfect agreement among the experts was seen in 6/10 of those challenging cases, in both rounds. For the non-experts, the proportion of cases with low or no agreement was higher than that for the experts and increased from 30% in the first round to 50% in the second round (Table 5). 3.5. Intra-Observer Agreement Cohen's Kappa was calculated to assess the inter-observer agreement between each of the scoring pathologists and the intra-observer agreement for each scorer across the two rounds. Inter-observer agreement was, overall, moderate (0.5) to substantial (0.75) (Table 6). The highest Kappa values for inter-observer agreement were 0.871 (in the first round) and 0.88 (in the second round), while the lowest values were moderate: 0.475 (in the first round) and 0.498 (in the second round). The intra-observer agreement was substantial to almost perfect, ranging from 0.667 to 0.956 (Table 6). 3.6. Intraclass Correlation Coefficient (ICC) ICC was used to assess the reliability of scoring between different groups of raters using the median percentage expression. The ICC for different groups (all scorers, experienced scorers and non-experienced scorers) ranged from moderate (0.5-0.75) to excellent (>0.9), with the predominance of the latter (Table 7). The highest ICC was 0.974 (between all scorers in first round and experienced ones in the second round), while the lowest value was 0.619 (between the non-experienced in the first round and the experienced in the second round). 3.7. Intra-Observer Agreement and Scoring Reliability in Relation to Pathologists' Experience All scorers had significant experience in breast pathology reporting, but only six scored PD-L1 SP142 in breast cancer in routine practice. The experience in PD-L1 reporting did not appear to affect the intra-observer agreement, with all scorers showing substantial or almost perfect agreement. On the other hand, the intra-observer reliability in the percentage assessment of PD-L1 expression was higher for experienced pathologists compared with non-experienced pathologists (Table 8). 4. Discussion We present comprehensive data of a large PD-L1 concordance cohort, scored twice by pathologists from eight institutions, representing three countries. Our data show reassuring intra-observer agreements, which were the highest among experts, and highlight cancers with low levels of PD-L1 expression as the most challenging in classifying as either PD-L1-positive or -negative. Unlike standard diagnostic and prognostic markers for breast cancer, SP142 PD-L1 immunohistochemistry is assessed in the immune micro-environment of breast cancer and not in the neoplastic cells themselves. PD-L1 expression in foci of ductal carcinoma in situ (DCIS), necrotic debris, normal mammary tissue and normal nodal tissue is excluded. Therefore, experience in both tumour morphology and PD-L1 assessment is required and may affect the reproducibility of scoring. Few studies, summarised in Table 9, have addressed the consistency of PD-L1 reporting among pathologists. A prospective multi-institutional study showed the poor reproducibility of PD-L1 scoring, with pathologists disagreeing on the classification of cases as PD-L1-positive or -negative in over half of the scored cases, and the with complete agreement of SP-142 scoring in only 38% of cases . In a cohort of 426 tumours of Chinese women, the concordance between two pathologists in PDL-1 scoring was 78.2%, with a Kappa value of 0.567, and 61.4% in primary tumours and nodal metastasis, respectively, indicating moderate agreement . Using "Observers Needed to Evaluate Subjective Tests" (ONEST), Reisenbichler et al. reported a decreased overall percentage agreement with the increase in the number of pathologists assessing each case, with the lowest concordance at eight pathologists or more. Another study of 79 PD-L1 SP142-stained breast cancers scored by experienced breast pathologists at the Memorial Sloan-Kettering Cancer Centre revealed strong agreement . Our data, based on a larger cohort of TNBC cases, confirm the substantial agreement and show that concordance was higher among experts than among those with no experience in reporting PD-L1. More importantly, the agreement among experts was observed as substantial to perfect in those challenging cases, and those experts showed a much higher consistency in reporting challenging, low-expressing TNBC, a finding that is relevant to clinical practice. This is in accordance with findings in other biomarkers and reflects the importance of testing at regional institutions with quality-assured protocols and experienced scorers and the value of discussing/referring difficult/equivocal cases to expert pathologists for their opinions. While several antibodies/assays for PD-L1 assessment are available (e.g., 22C3, 28-8, SP142, SP263 and 73-10), the VENTANA Roche SP142 assay is the only companion CE-IVD (European Commission in vitro diagnostics)-approved test for atezolizumab therapy. An expert round table in 2019 recommended the assay as the only approved companion diagnostic for selecting patients for immunotherapy and recommended using the primary tumour samples, where available, over metastases for assessment. In the UK, atezolizumab plus chemotherapy, and its companion diagnostic assay, were granted approval by the National Institute of Health and Care Excellence (NICE) for the treatment of locally advanced/metastatic PD-L1-positive TNBC. More recently, pembrolizumab plus chemotherapy has been approved for the same indication for PD-L1-positive TNBC using the companion diagnostic Agilent 22C3 assay. In this study, we assessed both the intra-observer concordance among the participating pathologists. It is notable that the intra-observer concordance was high (0.667 to 0.956) among both expert and non-expert pathologists in PD-L1 scoring, indicating that pathologists are likely to stick to their parameters on scoring. When the median percentage of PD-1 expression was compared among the raters, the highest ICC (0.974) was achieved among experienced raters in the second round. We observed the lowest concordance value of 0.619 when comparing non-experienced to experienced scorers. Similarly, a higher concordance among those experienced in PD-L1 scoring (93.3%) compared with non-experts (81.5%) was previously reported by Pang et al. . While, overall, there was a high concordance among pathologists in PD-L1 SP142 scoring, some cases were challenging to score. Those cases comprised 6-8% of all cases and generally showed very low levels of expression spanning the threshold for positivity. These may represent a so called "borderline category" where expression cannot readily be designated into a clear-cut positive or negative status. Ideally, information on the tumour response to immunotherapy should determine how those cases should be classified. It is of interest that expert pathologists, who routinely reported PD-L1 in breast cancer, showed substantial concordance in scoring those difficult cases. We therefore recommend that those cases of very low expression (i.e., close to the 1% cut-off value) are scored by an expert pathologist either via double-reporting or via a second opinion referral. cancers-15-01511-t009_Table 9 Table 9 Summary of studies evaluating the SP142 PD-L1 concordance of scoring. Reference Number of Cases (Type) Clone(s) SP142 Scoring Method Scorers Inter-Observer Agreement Intra-Observer Agreement Downes et al. 2020 30 surgical excisions TMAs 22C3, SP142, E1L3N IC >= 1% 3 pathologists Kappa for IC1%: 0.668 1 month washout period. Kappa = 0.798 Noske et al. 30 (resections) SP263, SP142, 22C3, 28-8 IC >= 1% 7 trained + one Ventana SP142 expert for SP142 only ICC for SP142: 0.805 (0.710-0.887) Not tested Dennis et al. (abstract) 28 test sets through the Roche International Training Programme SP142 IC >= 1% 432 (trained multiple institutions), from several countries OPA: was 98.2%, with PPA of 99.4% and NPA of 96.6%. Not tested Hoda et al. 75 (cores and excision), primary and metastases SP142 IC >= 1% 8 experienced (single institution) Kappa 0.727 Not tested Reisenbichler et al. 2021 68 cases for SP142 and 67 cases for SP263 SP142, SP263 IC >= 1% & % expression for cases scored as positive only 19 randomly selected pathologists from 14 US institutions; breast pathologists, with few non-breast pathologists. Experience in reporting PD-L1 not stated Complete agreement for SP142 categorisation into positive vs. negative in 38%. Agreement decreased with the increasing number of scorers, reaching a low plateau of 0.41 at eight scorers or more Not tested Pang et al. 60 TNBC TMAs VENTANA SP142, DAKO 22C3 IC >= 1% 10 pathologists including 5 PD-L1 who were naive and 5 who passed a proficiency test 93.3% for experts; 81.5% for non-experts. Tested after a 1 h training video and an overnight washout period. OPA increased from 81.5% to 85.7% for non-experts after video training. OPA was 96.3% for experts. Van Bockstal et al. 2021 49 metastatic TNBC (biopsies and resections) VENTANA SP142 IC >= 1% 10 pathologists; all passed a proficiency test Substantial variability at the individual patient level. In 20% of cases, chance of allocation to treatment was random, with a 50-50 split among pathologists in designating as PD-L1-positive or -negative Not tested Ahn et al. 2021 30 surgical excisions SP142, SP263, 22C3 and E1L3N ICs and TCs were scored in both continuous scores (0-100%) and five categorical scores (<1%, 1-4%, 5-9%, 10-49% and >=50%). 10 pathologists with no special training, of whom 6 underwent Ventana Roche training 80.7% inter-observer agreement at a 1% cut-off value Proportion of cases with identical scoring at a 1% IC cut-off value increased from 40% to 70.0% after training Abreu et al. 2022 (Conference abstract) 168 in tissue microarrays 22C3 and SP142 Not stated 4 pathologists including 2 breast pathologists and 2 surgical pathologists with no specific PD-L1 training Overall concordance for SP142 was 64.8%; overall k = 0.331, with k = 0.420 for breast pathologists and k = 0.285 for general pathologists Not tested Chen et al. 2022 426 primary and metastatic surgical excisions SP142 IC >= 1% Two experienced pathologists 78.2% concordance; k = 0.567 Not tested Current study 100 (cores), primary breast cancer SP142 IC >= 1% & % expression for all cases; two rounds of scoring separated by a 3-month washout period 12 experienced breast pathologists from 8 institutions in the UK, Ireland and Belgium. All passed a proficiency test. Absolute agreement was substantial in 52% and 60% of cases in the first and second rounds, with Kappa values of 0.654 and 0.655 for the first and second rounds, respectively. Higher concordance among experts, particularly in TNBC and challenging cases. Tested after 3 months of a washout period. Almost perfect agreement regardless of pathologists' PD-L1 experience Similar challenges in PD-1 scoring have been highlighted in carcinomas in other tissues. For example, the concordance between the assays used for PD-L1 assessment in head and neck squamous cell carcinoma (HNSCC) was fair to moderate, with a tendency for the SP142 assay to better stain the immune cells . Furthermore, using 3 PD-L1 tests for HNSCC tissue microarrays (standard SP263, standard 22C3 and in-house-developed 22C3), significant differences were found among the three tests using clinically relevant cut-off values, i.e., >=20 and >=50%, for the combined positive score (CPS) and Tumour positive score (TPS). Intra-tumour heterogeneity was generally higher when CPS was used . On the other hand, Cerbelli et al. showed a high concordance between the 22C3 PharmDx assay and the SP263 assay on 43 whole sections of HNSCC . The data collectively highlight the challenges in PD-L1 assessment in various cancers, including the differences in the results between the available antibody clones and staining platforms. Our data also confirm previous studies showing the highest proportion of PD-L1 positivity in TNBC . PD-L1 was previously shown to be associated with higher tumour grades and higher pCR rates. Low levels of expression were associated with shorter recurrence-free survival (RFS), including following subtype adjustment . The current study and previous lessons from the IMpassion trial shed some light on issues related to the immunohistochemical assessment of PD-L1 in breast cancer tissue. The strengths of the study include the large cohort of cases, the inclusion of 12 pathologists from three countries, the inclusion of both expert and non-expert assessors, the robust design, with the assessment of intra-observer concordance in two rounds, and the detailed statistical analysis. The digital analysis of whole slide images, rather than scoring glass slides, may be a weakness for pathologists who are not used to digital reporting. More recently, the use of digital image analysis algorithms and/or artificial intelligence (AI) has been proposed for PD-L1 scoring in various solid tumours . Going forward, this is an exciting and promising endeavour that requires thorough validation in comparison to the gold-standard pathologist scoring before implementation and the determination of whether those algorithms are superior to manual scoring in identifying responders to immune therapy. Currently, PD-L1 Artificial Intelligence (AI) scoring in breast cancer is limited to research studies and has not been validated for routine clinical use. 5. Conclusions In summary, we present a detailed analysis of 12 pathologists who scored 100 digitally scanned breast cancer slides for PD-L using the Ventana SP142 assay in two rounds separated by a washout period. Absolute (100%) agreement was substantial in 52% and 60% of cases in the first and second rounds, with Kappa values of 0.654 and 0.655 for rounds one and two, respectively. We provide reassuring evidence of a high concordance of PD-L1 reporting among pathologists, the highest being among experts and in reporting challenging, low-expressing TNBC. The intra-observer agreement was substantial for all raters. Despite experience and the adherence to current reporting guidelines, there remains a minority of tumours (6-8%) that are challenging to assign to either a positive or negative category. Those are PD-L1 low-expressing and/or heterogeneous tumours that suffer from the least concordance among pathologists. Consensus scoring and referrals for expert opinions should be considered in those cases. If uncertainly persists, this should be recognised and well communicated to clinicians in the context of a multidisciplinary approach. For inconclusive cases, testing on another tumour sample and/or using another assay (e.g., the DAKO 22C3 assay for selecting patients for pembrolizumab therapy) could be performed. Pathologists' training and experience are paramount in evaluating PD-L1 expression and selecting patients for immune checkpoint anti-PD-L1 inhibitors. Further work on refining the criteria for scoring, pathologists' training and assessing pathologist concordance is needed. This will ensure the accurate classification of tumours into a positive or negative category and, hence, the accurate selection of patients for atezolizumab therapy. This study also shows that digital pathology is a useful tool that allows for the instantaneous sharing of high-quality whole slide scans with colleagues. This is particularly helpful for consensus scoring and/or seeking expert opinions. Author Contributions M.Z.: Virtual slide scoring, data curation, statistical analysis, results interpretation, designing tables and figures, writing; M.V.B., C.G., G.C., E.P., R.H., C.D., N.M.B., J.S., B.T. and Y.M.: Virtual slide scoring, editing the manuscript; B.O.: Slide staining; P.L.: Statistical analysis, statistical writeup, results interpretation; A.M.S.: Conceptualisation, methodology, virtual slide scoring, statistical analysis, writing, overall project overview. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study did not require ethical approval, as it was conducted as an audit of the consistency of scoring of anonymous breast cancer images. Informed Consent Statement Not applicable. Data Availability Statement Full data are available from the corresponding author upon reasonable request. Digital slides are password-protected and available at the University of Birmingham platform: Last accessed 23 February 2023. Conflicts of Interest The authors declare no conflict of interest. Figure 1 A flowchart showing the outline of the study. Figure 2 Examples of breast cancer PD-L1 scores using the Ventana SP142 assay and challenging cases: (A) H&E staining of three cores of invasive no-special-type carcinoma (x50); (B) Only focal PD-L1 staining is noted (<1%), and the case was classified as PD- (x100); (C) H&E staining of one core of invasive no-special-type carcinoma (x100); (D) Higher magnification of PD-L1 immunohistochemistry shows strong positivity with absolute agreement among all scorers in both rounds (x100); (E) Challenging case due to uncertainty as to whether the PD-L1 staining observed is associated with in situ or invasive carcinoma (x100); (F) Challenging cases showing low levels of expression. Experts' consensus was to designate the case as PD-L1-negative (x100); (G) A case with no consensus in either round. Low-power view showing areas of tumour necrosis and background staining (x15); (H) Higher magnification showing focal expression in tumour stroma and adjacent to an area of necrosis (x50). This case was also challenging for experts; in the first round, it showed low agreement (60% as negative), and in the second round, it showed no agreement (50%). Figure 3 Scatter plot showing the distribution of the median percentage of PD-L1 in the four groups; experienced consultants (Exp; red line), non-experienced consultants (Con; green line) and all (All; blue line) participants. (A) The distribution of percentage scores among all scorers in both rounds; (B) All pathologists' (including non-experts and trainees) percentage scores in both rounds (R2 = 0.935); (C) All consultants' (including experts and non-experts) percentage scores in both rounds (R2 = 0.902); (D) Experienced consultants' percentage scores in both rounds (R2 = 0.920); (E) Non-experienced pathologists' (including trainees) percentage scores in both rounds (R2 = 0.89). cancers-15-01511-t001_Table 1 Table 1 Frequency of PD-L1 positivity in breast cancer in both rounds, stratified by the molecular type. No. First Round Second Round Positive (%) Negative (%) Positive (%) Negative (%) TNBC 58 32 (55%) 26 (45%) 32 (55%) 26 (45%) Median (range) 4 (0.75-30) 0 (0-1) 5 (0.5-30) 0 (0-1) Luminal 28 4 (14%) 24 (86%) 4 (14%) 24 (86%) Median (range) 2 (1-4) 0 (0-0.75) 3.5 (1.5-5) 0 (0-0.5) Her2-positive 14 2 (14%) 12 (86%) 1 (7%) 13 (93%) Median (range) 5.5 (1-10) 0 (0-0.5) 10 0 (0-0.5) Total 100 38 (38%) 62 (62%) 36 (36%) 64 (64%) Median (range) 2 (0.75-30) 0 (0-1) 5 (0.5-30) 0 (0-1) cancers-15-01511-t002_Table 2 Table 2 Absolute agreement in scoring among raters in the two rounds. Raters P1 P2 P3 P4 c P5 c P6 c P7 e P8 e P9 e P10 e P11 e P12 e First Round Neg 62 64 61 58 63 68 75 51 64 67 63 63 Pos 38 35 31 41 37 32 25 49 36 33 37 34 Total 100 99 92 99 100 100 100 100 100 100 100 97 Kappa 0.654 AA 52/100 cases; 36 scored negative and 16 scored positive Second Round Neg 60 64 64 46 62 52 72 69 69 66 Pos 40 35 35 54 37 48 28 31 31 30 Total 100 99 99 100 100 100 100 100 100 97 Kappa 0.655 AA 60/100 cases; 40 scored negative and 20 scored positive e Experienced consultant, c Consultant, (AA) Absolute agreement. P3 and P7 did not score the second round. cancers-15-01511-t003_Table 3 Table 3 Agreement categories in the first and second scoring rounds. Round Consensus (Agreement) No Agreement Majority Challenging/Low Agreement <=50% 100% (AA) 67-99% <67->50% First Negative 36 24 2 0 Positive 16 18 4 0 Total 52 42 6 0 94 6 0 100 0 Second Negative 40 20 2 2 Positive 20 12 4 0 Total 60 32 6 2 92 6 2 98 2 cancers-15-01511-t004_Table 4 Table 4 Fleiss Kappa of agreement between the pathologists in both rounds. Fleiss Kappa First Round Fleiss Kappa Second Round Scoring Categories Scoring Categories Overall (TNBC) NEG POS Overall (TNBC) NEG POS All 0.654 (0.61) 0.660 0.678 0.655 (0.602) 0.656 0.669 Consultants 0.663 (0.616) 0.664 0.673 0.633 (0.568) 0.636 0.650 Experienced 0.659 (0.642) 0.661 0.672 0.674 (0.600) 0.677 0.695 cancers-15-01511-t005_Table 5 Table 5 Distribution of ten challenging (low concordance and no agreement) cases in both rounds. FIRST ROUND SECOND ROUND Type ALL (12) PD-L1 Status M NON (6) PD-L1 Status M EXP (6) PD-L1 Status M All (10) PD-L1 Status M Non (5) PD-L1 Status M EXP (5) PD-L1 Status M TNBC 6/11 (55%) - 0.5 3/6 (50%) 0.75 3/5 (60%) - 0.5 6/9 (67%) - 0.5 4/5 (80%) - 0 2/4 (50%) 1 Her2 7/12 (58%) - 1 4/6 (67%) - 1 3/6 (50%) 0.75 7/10 (70%) - 0.5 3/5 (60%) + 1 5/5 (100%) - 0.5 TNBC 7/12 (58%) - 0.5 4/6 (67%) - 0.25 3/6 (50%) 0.75 6/10 (60%) + 1 4/5 (80%) + 1 3/5 (60%) - 0.5 TNBC 7/12 (58%) - 1 3/6 (50%) 1 4/6 (67%) - 1 6/10 (60%) - 1 3/5 (60%) + 1 4/5 (80%) - 0.75 TNBC 7/12 (58%) + 1 4/6 (67%) + 1 3/6 (50%) 0.75 5/9 (56%) + 1 2/4 (50%) 2 3/5 (60%) + 0.75 TNBC 7/12 (58%) - 1 4/6 (67%) + 1 5/6 (83%) - 0.5 5/10 (50%) 1 4/5 (80%) + 1.5 4/5 (80%) - 0.75 TNBC 9/12 (75%) + 1 4/6 (67%) + 1 5/6 (83%) + 1 6/10 (60%) + 2 4/5 (80%) + 2.5 3/5 (60%) - 0.5 TNBC 8/12 (67%) + 1 3/6 (50%) 0.5 5/6 (83%) + 1 6/10 (60%) - 1 3/5 (60%) - 0.5 4/5 (80%) + 1.5 TNBC 11/12 (83%) - 0.5 6/6 (100%) - 0.5 5/6 (83%) - 0.5 6/10 (60%) - 0.5 3/5 (60%) + 1 4/5 (80%) - 0.5 Lum 8/12 (75%) + 1 4/6 (67%) + 1 4/6 (67%) + 1 5/10 (50%) 1.5 4/5 (80%) + 3.5 4/5 (80%) - 0.5 AGREEMENT No 0 3/10; 30% 3/10; 30% 2/10; 20% 1/10; 10% 1/10; 10% Low 6/10; 60% 0 1/10; 10% 6/10; 60% 4/10; 40% 3/10; 30% High 4/10; 40% 7/10; 10% 6/10; 60% 2/10; 20% 5/10; 50% 6/10; 60% PD-L1 status: negative (-) or positive (+); (M) Median percentage score; (ALL) refers to all scorers, which were then divided into (NON) Non-expert participants in PD-L1 scoring and (EXP) Expert pathologists. Cases in green represent challenging cases in the first round, those in orange represent challenging ones in both rounds and those in grey represent challenging and no-agreement cases in the second round only. The yellow cases represent contradictory agreement of non-experts in relation to the experts' agreement, and the blue cases represent cases with no agreement (50%). Agreement levels are categorised into no-agreement (50%), low-agreement (>50%-<67%) and high-agreement (>67%). cancers-15-01511-t006_Table 6 Table 6 intra-observer agreement for all scoring pathologists. Consensus 1 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 Consensus 2 0.912 0.851 0.78 0.823 0.629 0.715 0.737 0.747 0.819 0.865 0.884 P1 0.892 0.832 0.766 0.679 0.724 0.787 0.758 0.649 0.719 0.762 0.733 P2 0.765 0.747 0.722 0.735 0.551 0.695 0.575 0.562 0.729 0.774 0.745 P3 0.786 0.768 0.607 P4 0.823 0.762 0.654 0.641 0.956 0.587 0.669 0.631 0.606 0.637 0.728 0.699 P5 0.74 0.723 0.64 0.696 0.607 0.667 0.682 0.801 0.498 0.554 0.515 0.539 P6 0.798 0.737 0.741 0.632 0.617 0.713 0.732 0.632 0.635 0.688 0.643 0.656 P7 0.718 0.659 0.579 0.717 0.669 0.54 0.634 P8 0.678 0.658 0.533 0.543 0.613 0.678 0.577 0.475 0.94 0.552 0.574 0.614 0.661 P9 0.891 0.871 0.745 0.764 0.715 0.72 0.733 0.744 0.658 0.772 0.784 0.64 0.826 P10 0.822 0.76 0.634 0.831 0.687 0.649 0.704 0.711 0.597 0.801 0.862 0.762 0.88 P11 0.87 0.808 0.724 0.649 0.738 0.743 0.801 0.586 0.638 0.763 0.737 0.778 0.784 P12 0.843 0.735 0.646 0.758 0.708 0.643 0.7 0.687 0.563 0.732 0.749 0.732 0.906 Figures in italics below the equatorial bordered cells represent the values of the first round, while those in bold represent the second round. The equatorial bordered cells (in bold red font) represent the intra-observer agreement for each participant, as scored in both rounds. Cell shading colours reflect the level of agreement as follows; light green for almost perfect agreement (0.81-1), orange for substantial agreement (0.61-0.8) and light red for moderate agreement (0.41-0.6). cancers-15-01511-t007_Table 7 Table 7 Intraclass correlation coefficient for all groups of pathologists. ALL-1 EXP-1 NON-1 ALL-2 EXP-2 NON-2 ALL-1 0.907 0.931 0.906 0.768 0.932 EXP-1 0.915 0.772 0.974 0.913 0.919 NON-1 0.933 0.788 0.781 0.619 0.876 ALL-2 0.919 0.974 0.804 0.911 0.946 EXP-2 0.798 0.923 0.655 0.919 0.792 NON-2 0.936 0.920 0.891 0.949 0.808 Figures in bold/italics below the equatorial grey cells represent values of ICC calculated according to the consistency of assessment, while values below equatorial cells represent ICC calculated according to absolute agreement. (ALL): All scorers' median percentage; (EXP): Experienced scorers' median percentage; (NON): Non-experienced scorers' median percentage. Cells' shading colours reflect the level of reliability as follows: Red for moderate reliability (0.5-0.75); Orange for good reliability (0.75-0.9); Green for excellent reliability (greater than 0.9). cancers-15-01511-t008_Table 8 Table 8 Intra-observer concordance based on pathologists' experience in scoring PD-L1. Rater Position Experience as a Breast Reporting Pathologist (years) Experience in SP142 PD-L1 Reporting (years) Previous Training in SP142 PD-L1 Reporting (Provider) Intra-Observer Agreement (Cohen's Kappa/Level of Agreement) Intra-Observer Reliability (ICC/Level of Reliability) P1 Trainee Pathologist 12 0 Roche 0.832/Almost perfect 0.826/Good P2 12 0 Roche 0.722/Substantial 0.525/Moderate P3 Consultant Scientist N/A 0 Roche N/A/N/A N/A/N/A P4 Consultant Pathologist 20 0 N/S 0.956/Almost perfect 0.852/Good P5 21 0 Roche 0.667/Substantial N/A/N/A P6 25 0 None 0.732/Substantial 0.770/Good P7 25 3 Roche N/A/N/A N/A/N/A P8 29 1 Roche 0.94/Almost perfect 0.935/Excellent P9 10 2 Roche 0.772/Substantial 0.933/Excellent P10 25 2 Roche 0.862/Almost perfect 0.920/Excellent P11 30 3 Local 0.778/Substantial 0.756/Good P12 22 2 Roche 0.906/Almost perfect 0.929/Excellent (N/S) Not stated; (N/A) Not applicable. 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PMC10000422 | Locoregionally advanced and metastatic melanoma are complex diagnoses with a variety of available treatment options. Intralesional therapy for melanoma has been under investigation for decades; however, it has advanced precipitously in recent years. In 2015, the Food and Drug Administration (FDA) approved talimogene laherparepvec (T-VEC), the only FDA-approved intralesional therapy for advanced melanoma. There has been significant progress since that time with other oncolytic viruses, toll-like receptor agonists, cytokines, xanthene dyes, and immune checkpoint inhibitors all under investigation as intralesional agents. Further to this, there has been exploration of numerous combinations of intralesional therapies and systemic therapies as various lines of therapy. Several of these combinations have been abandoned due to their lack of efficacy or safety concerns. This manuscript presents the various types of intralesional therapies that have reached phase 2 or later clinical trials in the past 5 years, including their mechanism of action, therapeutic combinations under investigation, and published results. The intention is to provide an overview of the progress that has been made, discuss ongoing trials worth following, and share our opinions on opportunities for further advancement. advanced melanoma in transit metastases intralesional therapy intratumoral therapy local therapy locoregional therapy melanoma metastatic melanoma regional therapy regional chemotherapy This research received no external funding. pmc1. Introduction While early-stage localized melanoma disease has a 5-year survival of greater than 90%, regional and distant disease have 5-year survival rates of 66% and 27%, respectively . Therefore, there remains significant room for improvement in the treatment of advanced melanoma. Many of the major advancements in the treatment of advanced disease have been with systemic immune checkpoint inhibitors (ICIs) and targeted therapies . These therapies have revolutionized the treatment of advanced disease, which previously had an even poorer prognosis; however, they can have permanent, life-altering side effects in some and responses are limited . In patients with locoregionally advanced and metastatic melanoma that is unresectable but amenable to injection, intralesional therapy provides a promising alternative or adjunct to systemic therapy. Intratumoral therapy has been explored for the treatment of melanoma since the 1970s. Early investigations included the injection of bacillus Calmette-Guerin (BCG), a live, attenuated strain of Mycobacterium bovis developed as a tuberculosis vaccine, as an intralesional therapy for melanoma in 1974 . More recent randomized trials have not supported the efficacy of BCG , and it has fallen further out of favor due to significant systemic toxicity . However, since that time, innumerable other intralesional therapies have been and continue to be investigated for the treatment of advanced melanoma. To limit the scope of this discussion to the most current and clinically relevant therapies, the focus of this review is on intralesional therapies that have reached phase 2 or later clinical trials within the past 5 years. To identify clinical trials, the clinicaltrials.gov Advanced Search feature was used. The condition or disease was specified as melanoma and phase 2, phase 3, and phase 4 were selected. Key terms searched were: intralesional, intratumoral, inject, xanthene, PV-10, Rose Bengal, intratumoral interleukin, intratumoral interferon, Aldesleukin, tavokinogene telseplasmid, tavo, electroporation, Darleukin, L19IL2, Daromun, L19TNF, stimulator of interferon genes, STING, DMXAA, MIW815, MK1454,, oncolytic virus, talimogene laherparepvec, T-VEC, GM-CSF, vusolimogene oderparepvec, RP1, OrienX010, Oncos-102, BT-001, canerpaturev, C-REV, TBI-1401, HF-10, coxsackievirus A21, CA21, CAVATAK, V937, gebasaxturev, lerapolturev, PVSRIPO, Telomelysin, OBP-301, Voyager-V1, VV1, VSV-IFNb-NIS, VSV-IFNbTYRP1, Ad-p53, RheoSwitch, Ad-RTS-hIL-12, IXN-2001, veledimex, IXN-1001, oca511, Toca FC toll-like receptor, TLR, tilsotolimod, IMO-2125, SD-101, vidutolimod, CMP-001, cavrotolimod, AST-008, Lefitolimod, MGN1703, NKTR-262, G100, CV8102, LHC165, intratumoral ipilimumab, LL37, MAGE-A3, Hiltonol, poly-ICLC, APX005M, ABBV-927, dendritic cell, INT230-6, and TTI-621 polidocanol. Trials were included if they had published results in 2018 or later or were ongoing as of December 2022. Trials were excluded if at least one agent was not delivered intralesionally. 2. Xanthene Dyes 2.1. PV-10 PV-10 is a formulation of 10% Rose Bengal xanthene dye in saline. The dye was first found to have antitumor effects when it was observed to have a dose-dependent survival benefit in a strain of mice with a propensity for spontaneous tumor development that were used to test its safety as a food dye . PV-10 is theorized to cause photolytic release of lysosomal enzymes resulting in tumor cell lysis and has been found in vitro to cause cell lysis in melanoma cell lines, but not in normal fibroblasts . Bystander lesion response has also been observed with intralesional PV-10 injection and is theorized to result from High Mobility Group Box 1 activation and the maturation of dendritic cells and tumor-specific CD-8+ T cells . In 2015, a phase 2 clinical trial of single-agent intratumoral PV-10 in 80 patients with treatment-refractory American Joint Committee of Cancer 8th Edition stage III-IV melanoma found an overall response rate (ORR) of 51% with an ORR of 33% in uninjected lesions . AEs were observed in all patients, mostly grade 1 to 2, while 15% experienced possibly related grade 3 adverse event (AE); the most common AEs were injection site pain (80%), edema (41%), and vesicles (39%). This was continued in two single-institution studies that reported ORRs of 53-87% with a 50% response in non-injected lesions and consistent AE profiles . The dosing schedule examined, intralesional injections on Day 0 then repeated on Weeks 8, 12, and 16 for additional or incomplete responding lesions, makes this therapy particularly appealing. The addition of external beam radiotherapy (XRT) to intralesional PV-10 was examined in stage IIB-IV melanoma in a phase 2 trial at a single institution . A total of 98 target lesions in 15 patients were treated, the ORR was 87%, and all patients experienced at least one grade 1 or 2 AE, including injection site pain (87%), swelling (60%), and blistering (20%) with one patient experiencing a grade 3 AE of injection site pain. A phase 3, randomized controlled trial (NCT02288897) sought to compare PV-10 to investigator choice chemotherapy (dacarbazine or temozolomide) or T-VEC, but was terminated early due to an inadequate rate of enrollment and the changing landscape of therapy for advanced melanoma. Since PV-10 exerts its antitumor effects through T cell activation , the addition of immune checkpoint inhibitors provides a potential pathway for overcoming resistance or potentiating PV-10's effects. The efficacy of intralesional PV-10 with systemic pembrolizumab, anti-programmed cell death protein 1 (PD-1) antibody, in stage IIIB-IVM1c unresectable melanoma is undergoing evaluation in a phase 1b/2 trial (NCT02557321) in which intralesional PV-10 is dosed every 3 weeks with intravenous pembrolizumab for up to 5 weeks followed by intravenous pembrolizumab alone (Table 1). In phase 1b, 21 ICI-naive patients experienced a 67% ORR with primarily grade 1 and 2 injection-site-related AEs and one grade 3 AE related to PV-10 of injection site pain as well as AEs consistent with pembrolizumab's known toxicity profile . An expansion phase 1b cohort in 14 evaluable ICI-refractory patients had an ORR of 29% and AEs were consistent with known drug profiles, primarily grade 1 or 2 injection site events related to PV-10 and grade 1-3 immune-related events related to pembrolizumab . Phase 2 with arm 1, PV-10 with pembrolizumab, and arm 2, pembrolizumab alone, is ongoing. 2.2. Cytokines 2.2.1. Interleukin-2 (IL-2, Aldesleukin) IL-2 acts to activate numerous pathways modulating lymphocyte proliferation, activity, and survival by binding the IL-2 receptor . It received Food and Drug Administration (FDA) approval in 1998 for the treatment of advanced melanoma; however, its systemic application has been limited by significant side effects at efficacious doses . Intralesional injection of IL-2 is an appealing way to minimize systemic effects while locally delivering high doses of the drug. This premise was first investigated in 1994 , and in 2010 a phase 2 trial in 48 evaluable patients reported a complete response (CR) of 69%, though the response was not observed in any uninjected lesions . Only grade 1/2 AEs were reported, including injection site reaction and pain in most patients as well as fever (58%), fatigue (36%), and nausea (34%). The addition of ICIs to cytokine therapy should theoretically potentiate cytokine effects by antagonizing immune regulatory pathways . In 2017, a phase 2 trial (NCT01480323) sought to investigate the combination of intratumoral IL-2 plus systemic ipilimumab, an anti-CTLA-4 antibody, in 15 patients with treatment-refractory stage IV melanoma, but found a disappointing ORR of 0%, a disease control rate (DCR) of 20%, and grade 3/4 AEs in 40%, most commonly fatigue and pain (excluding injection pain) The combination of systemic ICI with intratumoral IL-2 is under further investigation in a phase 1/2 trial (NCT03474497) evaluating intralesional IL-2 in combination with systemic pembrolizumab and hypofractionated radiotherapy in patients with metastatic melanoma and other solid tumors who failed to respond or progressed on previous anti-PD-1/PD-L1 therapy (Table 1). One limitation to the use of IL-2 in the above-mentioned trials is the frequent dosing schedule of injections, two times per week. Every-2-week dosing is under investigation in a phase 2/3, randomized controlled trial (NCT03928275), a 2-stage study of intralesional IL-2 versus combination intralesional IL-2 and BCG in stage IIIC-IVM1a melanoma. 2.2.2. Tavokinogene Telseplasmid (Tavo) Interleukin-12 (IL-12) bridges the innate and adaptive immune systems, stimulates Interferon-gamma (IFN-g), regulates natural killer (NK) and T cell production, and promotes T helper type 1 (Th-1) differentiation . Systemic administration of IL-12 has been found to have high toxicity with limited efficacy . Tavokinogene telseplasmid (tavo) is a plasmid that encodes IL-12 that is delivered intratumorally and is typically combined with electroporation (EP) to improve plasmid cell uptake by increasing cell permeability . Simply, this results in increased local IL-12 and IFN-g expression, which activates the innate and adaptive immune systems . Intratumoral tavo-EP alone in stage III-IV melanoma was investigated in a phase 2 trial (NCT01502293) . The results published in 2020 included a CR rate of 18% and ORR of 36% in the 28 patients in the standard dosing cohort, with a median PFS of 3.72 months . The most common AEs reported were procedural pain in 80% and various injection site reactions. Since cytokines increase tumor-specific T cells, the addition of ICIs should potentiate their effects by inhibiting immune regulatory pathways . This combination is under investigation with intratumoral tavo-EP and intravenous pembrolizumab in a phase 2 trial (NCT03132675) in 54 ICI-refractory patients with stage III/IV melanoma (Table 1). On interim analysis, ORR was 30% with a reduction in non-injected tumor burden seen in all 12 patients with non-injected disease and the most common AEs were low-grade fatigue, procedural pain, and diarrhea . Though tavo-EP injection occurs on Days 1, 5, and 8 of each cycle, cycles span for 6 weeks, making overall dosing frequency more manageable. 2.3. Antibody-Cytokine Fusion Proteins 2.3.1. Darleukin (L19IL2) As previously discussed, IL-2 acts to increase tumor immunogenicity but is not well tolerated when delivered systemically at efficacious doses . A fusion protein of IL-2 to L19, a monoclonal antibody targeted to an angiogenesis marker, L19IL2, enables preferential delivery and activation of the cytokine within the tumor cells . It has been investigated as a single agent in a phase 2 trial (NCT01253096) in 24 evaluable patients with unresectable stage IIIB/C melanoma and found to generate a CR in 25% at lower doses than non-targeted IL-2 with the most common toxicity being injection site reaction, seen in 76%, with few grade 3 cases . Other AEs were seen in 25% or less and included fatigue, edema, and fever. The addition of intratumoral L19IL2 to systemic dacarbazine vs. systemic dacarbazine alone is now under investigation for the treatment of stage IVM1a-b melanoma in a phase 1/2 trial (NCT02076646) (Table 1). 2.3.2. Daromun (L19IL2 and L19TNF) Daromun is the combination of the previously mentioned, L19IL2 and L19TNF, a fusion protein of L19 and human recombinant tumor necrosis factor-alpha (TNFa). The addition of L19TNF acts synergistically in murine models to enhance the antiangiogenic and, therefore, antitumor effects . A phase 2 trial (NCT02076633) of intratumoral daromun injection weekly for 4 weeks in stage III-IVM1a melanoma in 2015 found that of 20 evaluable patients, 50% had PR, 25% had SD, and 20% had PD for an ORR of 55% and DCR of 80%. Additionally, in 13 lesions not amenable to injection, 54% demonstrated CR . Injection site reaction was the most common AE, seen in 73%, and was the only grade 3 AE reported. Other common grade 1 and 2 AEs were fever, headache, edema, and erythema. The efficacy of intralesional daromun in the neoadjuvant setting with systemic investigator's discretion ICI compared to neoadjuvant systemic ICI alone is now under investigation in a phase 3 trial (NCT03567889) in resectable stage IIIB/C melanoma in the United States and Europe (Table 1) . A similar trial (NCT02938299) is ongoing at European centers with neoadjuvant intratumoral daromun versus surgery alone. 2.4. Oncolytic Viral Therapies 2.4.1. Talimogene Laherparepvec Talimogene laherparepvec (T-VEC) is a live-attenuated herpes simplex virus type-1 (HSV1) that has been engineered to express the gene for granulocyte-macrophage colony-stimulating factor (GM-CSF) . Two mutations in the engineered HSV1, g34.5 and a47 gene deletions, enable the virus to selectively replicate in tumor cells and enhance the immune response, respectively . T-VEC enters tumor cells through herpes virus glycoproteins and ultimately results in cell lysis. Lysis of injected cells releases viral particles, tumor-derived antigens, and GM-CSF, promoting both cell-mediated and humoral immune responses and linking innate and acquired immune systems through T cell proliferation and activation and DC growth and maturation . While the results of intralesional injection of GM-CSF have been underwhelming , intralesional T-VEC has received FDA approval. This is based on the results of the OPTiM phase III trial in stage IIB-IV melanoma, in which 47% of injected lesions, 22% of uninjected non-visceral lesions, and 9% of uninjected visceral lesions had CR . The most common adverse events seen in those treated with T-VEC were fatigue (50%), chills (49%), and pyrexia (43%), with an 11% incidence of grade 3 or 4 treatment-related AEs including cellulitis (2%), fatigue (2%), and vomiting (2%) . Single-agent T-VEC neoadjuvant therapy with surgery (arm 1, n = 76) versus surgery alone (arm 2, n = 74) in resectable Stage IIIB-IVM1a melanoma was compared in a phase 2 randomized controlled trial, NCT02211131, which demonstrated that 2-year recurrence-free survival (RFS), the primary endpoint, was improved with the addition of neoadjuvant T-VEC, 29.5% vs. 16.5% (overall hazard ratio 0.75, 80% confidence interval 0.58-0.96) for a 25% recurrence risk reduction with the addition of neoadjuvant T-VEC . Side effects included flu-like illness and pyrexia and were consistent with the known T-VEC safety profile established by the OPTiM trial . The application of T-VEC monotherapy as a neoadjuvant therapy in surgically resectable, high-risk melanoma is also being evaluated in a phase 2 trial, NCT04427306 (Table 1). Theoretically, oncolytic viral therapies and ICIs should have synergistic effects since the viral infection increases susceptibility to immune surveillance and facilitates antigen-presenting cell (APC) processing . A phase 2 trial in which CD8+ T cell levels were monitored in response to intralesional T-VEC demonstrated that, while CD8+ T cell levels were not associated with response, a 2.4-fold increase in CD8+ T cells was observed in non-injected lesions and the CD8+ T cells identified in non-injected lesions had increased expression of PD-1, programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) checkpoints . In a 2018 phase 2 trial (NCT01740297) of 98 patients who received intratumoral T-VEC with intravenous ipilimumab versus 100 who received systemic ipilimumab alone, ORR was significantly improved with the combination, 39% vs. 18%, respectively, without a significant increase in toxicity, the most common AEs in the combination arm being fatigue (59%), chills (53%), and diarrhea (42%) . However, in 2022, a phase 3 (NCT02263508) randomized controlled, double-blinded trial evaluating intralesional T-VEC with systemic pembrolizumab versus an intralesional placebo with systemic pembrolizumab in 692 patients with Stage IIIB-IVM1c unresectable, anti-PD-1-naive melanoma found no significant difference in overall survival (OS) or progression-free survival (PFS) and similar rates of grade 3 or greater treatment-related AEs between the two groups . However, it is important to note that the lack of statistical significance in survival may in part be due to the inclusion of stage IVM1b and IVM1c patients in this trial when the most benefit from T-VEC has been demonstrated in stage IIIB-IVM1a in the past . An ongoing phase 2 trial (NCT04068181) is evaluating the combination of intralesional T-VEC with systemic pembrolizumab in patients who have previously progressed on anti-PD-1 therapy (Table 1). Preliminary results have shown limited efficacy in those who previously progressed on anti-PD-1 in a locally recurrent or metastatic setting, 0% ORR in Cohort 1 (primary resistance, n = 26) and 7% ORR in Cohort 2 (acquired resistance, n = 15), but more promising results in those who progressed after receiving anti-PD-1 only in the adjuvant setting, 40% ORR in Cohort 3 (disease free < 6 months, n = 15) and 47% ORR in Cohort 4 (disease free >= 6 months, n = 15) . The most common treatment-related AEs in all cohorts combined were pyrexia (30%), fatigue (16%), and flu-like illness (16%) with 13% experiencing grade 3 or higher treatment-related AEs. The combination of intratumoral T-VEC with systemic ICI is also being examined in the neoadjuvant setting. A phase 2 trial, NCT04330430, is evaluating neoadjuvant T-VEC with nivolumab for resectable Stage IIIB-IVM1a melanoma (Table 1). In patients with clinically node-positive disease, neoadjuvant intranodal T-VEC injection with pembrolizumab is being evaluated in a phase 2 trial, NCT03842943. The addition of T-VEC to other treatment modalities also provides an avenue for therapeutic benefit. Intralesional T-VEC with and without radiotherapy is under investigation in a phase 2 trial in Stage IIIB or higher melanoma and other solid malignancies (NCT02819843) (Table 1). Additionally, a phase 1/2 trial (NCT03555032) examining the efficacy of intralesional T-VEC with isolated limb perfusion in stage IIIB-IVM1b melanoma as well as sarcoma is ongoing. 2.4.2. RP1 (Vusolimogene Oderparepvec) RP1 is a genetically modified HSV1 encoding GM-CSF and the gibbon ape leukemia virus fusogenic membrane glycoprotein with R sequence deletion (GALV-GP R-) that has been demonstrated to have potent antitumor activity in vitro, abscopal effects in murine models, as well as potentiated effects when administered with anti-mouse PD-1 antibody in murine models . In humans, a phase 1/2 trial (NCT03767348) of intratumoral RP1 alone and in combination with intravenous nivolumab in advanced solid tumors, including Stage IIIB-IVM1c melanoma, is underway (Table 1). Interim results in cutaneous melanoma reported an ORR of 63% in eight anti-PD-1-naive patients who received combination therapy and 38% in 16 patients who previously failed anti-PD-1 therapy . More recent interim results of 75 patients who failed anti-PD-1/L1 therapy reported an ORR of 36% and DCR of 53% at a median follow-up of 10 months . An additional phase 1b/2 trial of RP1 (NCT04349436) is ongoing for cutaneous malignancies, including locally advanced or metastatic melanoma, in solid organ transplant patients. 2.4.3. OrienX010 OrienX010 is an oncolytic HSV engineered to express GM-CSF like T-VEC does; however, it uses a strain isolated in China, HSV1 CL1 . It is undergoing phase 2 investigation (NCT04200040) as a single, intratumoral agent compared to systemic dacarbazine in treatment-naive, unresectable Stage IIIB-IVM1b melanoma in China (Table 1). 2.4.4. ONCOS-102 (Ad5/3-D24-GM-CSF) Oncos-102 is an adenovirus that is genetically modified to express GM-CSF that has preferential tumor cell binding through desmoglein 2 receptors . As with T-VEC, the intratumoral GM-CSF increases the antitumor response by increasing NK and CD8+ T cells. Furthermore, combination with pembrolizumab in murine models has increased antitumor activity, thought to be related to increased immune surveillance against tumor-antigens exposed by viral cell lysis. A phase 2 trial (NCT05561491) of intratumoral ONCOS-102 alone or in combination with intravenous anti-PD-1 inhibitor, balstilimab, in anti-PD-1-refractory unresectable or metastatic melanoma is not yet accruing (Table 1). 2.4.5. BT-001 BT-001 is an oncolytic vaccinia virus containing genes encoding human GM-CSF and the human recombinant anti-CTLA-4 antibody . This allows for T-VEC-like effects of local GM-CSF delivery as well as local immune checkpoint blockade from delivery of the anti-CTLA-4 antibody. In murine models, it has also been demonstrated to have abscopal effects despite low systemic levels of the anti-CTLA4 antibody. An ongoing, phase 1/2a, multipart clinical trial, NCT04725331, is evaluating intratumoral BT-001 alone and in combination with systemic pembrolizumab in multiple solid tumors, including locally advanced or metastatic melanoma (Table 1). 2.4.6. Canerpaturev (C-REV, TBI-1401, HF10) C-REV is a strain of HSV1, HF10, with naturally occurring genomic alterations that result in preferential infection of and replication in tumor cells . This causes cytolysis and intratumoral penetration of CD4+, CD8+, and NK cells. As previously discussed, oncolytic viruses are theorized to synergize with ICIs by increasing immune surveillance . Therefore, intratumoral C-REV in combination with intravenous ipilimumab was investigated in a phase 2 trial (NCT02272855) in 44 evaluable patients with ipilimumab-naive, stage IIIB-IV melanoma . The results presented in 2018 included an ORR of 41% and DCR of 68% . Grade 3 or higher AEs were reported in 37%, though only 7% were attributed to C-REV and were classified as gastrointestinal, musculoskeletal, metabolism/nutrition, and vascular disorders. In 2019, the results of a similar phase 2 trial (NCT03153085) in 27 evaluable Japanese patients who had failed prior therapies were presented and included an 11% ORR and 56% DCR . Unspecified severe AEs were seen in 36% of patients. Further investigation of the combination of intralesional C-REV with systemic ICI was undertaken in a phase 2 trial (NCT03259425) examining C-REV in combination with nivolumab in the neoadjuvant setting for resectable stage IIIB-IVM1a melanoma, but it was terminated in 2022 at the recommendation of the Data Safety Monitoring Committee. 2.4.7. Coxsackievirus A21 (CVA21, CAVATAK, V937, Gebasaxturev) CVA21 is an enterovirus that preferentially infects melanoma cells since it binds to receptors that are overexpressed on melanoma cells, decay-accelerating factor (DAF) and intracellular adhesion molecule-1 (ICAM-1) . A phase 2 trial (NCT01227551) of intratumoral CVA21 in 57 patients with stage IIIC-IV melanoma published in 2021 reported an ORR of 39% (unconfirmed per irRECIST) and 28% (confirmed) as well as 12-month PFS and OS of 33% and 75%, respectively . All treatment-related AEs reported were grade 1 or 2 with the most common being injection site pain, fatigue, and chills. Patients with stable or responding disease could continue on NCT01636882, the extension study. The synergistic potential of CVA21 delivered both intratumorally and intravenously in combination with systemic pembrolizumab versus pembrolizumab alone in anti-PD-1-naive stage III-IV melanoma is under phase 2 investigation (NCT04152863) (Table 1). The same combination is under investigation in the neoadjuvant setting in one arm of a multi-arm, phase 1/2 study (NCT04303169) comparing systemic pembrolizumab in combination with five different investigational agents in stage III melanoma. 2.4.8. PVSRIPO (Lerapolturev) PVSRIPO is a recombinant, live-attenuated poliovirus Sabin type 1 with human reovirus type 2 in the internal ribosomal entry site . It preferentially enters melanoma cells, which have a high rate of CD155 poliovirus receptor expression, and stimulates the host antiviral immune response against the tumor cells. It is currently under investigation in a phase 2 randomized clinical trial (NCT04577807) as a single, intralesional agent or in combination with systemic anti-PD-1 therapy in unresectable, anti-PD-1/L1 refractory stage III-IVM1b (Table 1). 2.4.9. OBP-301 (Telomelysin) OBP-301 is a telomerase-specific replication-competent oncolytic adenovirus 5 in which human telomerase reverse transcriptase enables selective replication in tumor cells . Preclinically, it has been shown to increase local infiltration of CD8+ T cells and APCs and decrease regulatory T cells in both injected and uninjected tumor sites. A phase 2a trial, NCT03190824, examining this drug as an intralesional therapy in unresectable Stage III-IV melanoma is ongoing (Table 1). 2.4.10. Voyager-V1 (VV1, VSV-IFNb-NIS) VV1 is a vesicular stomatitis virus engineered to express interferon-beta (IFN-b), potentiating the immune response to viral cell lysis, as well as a sodium/iodide symporter (NIS) gene for tracking through single-photon emission computerized tomography (SPECT) or positron emission tomography (PET) imaging . It has been shown to increase inflammation and T cell infiltration in injected and non-injected lesions in phase 1 trials, and clinical benefit was observed as a monotherapy and in combination with systemic ICI in ICI-refractory disease. A phase 2 trial (NCT04291105) is underway in anti-PD-1/L1-refractory solid tumors, including advanced or metastatic melanoma; one study arm includes intratumoral and intravenous VV1 with intravenous cemiplimab in melanoma (Table 1). 2.4.11. Ad-p53 Ad-p53 is a recombinant human adenovirus with wild-type p53. It functions as a gene therapy, delivering the wild-type p53 gene to tumor cells, which otherwise often suppress p53 function as a part of regulatory evasion . It has been applied to other malignancies without any reported serious adverse events, the most common AEs being transient fever, flu-like symptoms, muscle aches, and injection site pain, and is approved in China for the treatment of head and neck squamous cell carcinoma. It is now under phase 2 investigation (NCT03544723) in combination with ICI in recurrent or metastatic solid tumors including melanoma (Table 1). 2.4.12. RheoSwitch Therapeutic System RheoSwitch is comprised of a replication-incompetent adenoviral vector (Ad-RTS-hIL-12, IXN-2001) administered via intratumoral injection in combination with an oral activator ligand (veledimex, IXN-1001) . Preclinical models demonstrated increased intratumoral IL-12 and CD8+ T cells with a corresponding dose-dependent decrease in tumor volume. Preliminary results of a phase 1/2 trial (NCT01397708) of this therapeutic combination in unresectable Stage III-IV melanoma reported a similar increase in tumor IL-12 mRNA and tumor-infiltrating lymphocytes and well-tolerated dose escalation (Table 1) . 2.5. Toll-like Receptor 9 (TLR9) Agonists TLR 9 agonists act to induce DC maturation; cytokine secretion; APC uptake, processing and presentation; NK cell activation; and T cell response, thereby improving tumor immunogenicity . Additionally, this improves tumor cell susceptibility to ICIs as the antitumor response is dependent upon tumor immunogenicity . 2.5.1. Tilsotolimod (IMO-2125) TLR9 agonist, tilsotolimod, activates the Th-1-type immune response, which increases expression of ICIs by promoting the maturation of local APCs . The results from 49 evaluable patients with Stage IIIC-IV, anti-PD-1 refractory melanoma treated with tilsotolimod and ipilimumab in a phase 2 trial (NCT02644967) published in 2020 included an ORR of 22% and median OS of 21 months . The most common AEs seen related to this combination were fatigue, nausea, and anemia with 48% experiencing grade 3 or 4 treatment-emergent AEs and 32% experiencing at least one serious AE. This combination was compared to systemic ipilimumab alone in anti-PD-1-refractory, stage III-IVM1c melanoma in a phase 3, randomized trial (NCT03445533); however, it was terminated in 2022 for a lack of improvement in the ORR and OS. 2.5.2. SD-101 SD-101, a TLR9 agonist, is a synthetic cytosine-phosphate-guanine (CpG) oligonucleotide that exerts its effects by inducing the production of CD8+ T cells and T cell infiltration . A phase 1/2 trial (NCT02521870) of SD-101 in combination with pembrolizumab in metastatic melanoma or head and neck squamous cell carcinoma was terminated by the sponsor in 2021 with no plans for additional investment in SD-101 development. 2.5.3. Vidutolimod (CMP-001) Vidutolimod is comprised of CpG-A DNA, a TLR9 agonist, packaged in a virus-like particle, which ultimately induces IFN-a production by DCs and creates a Th-1-type immune response . The combination of intralesional vidutolimod with systemic nivolumab is under phase 2 investigation (NCT04698187) in anti-PD-1-refractory and phase 2/3 investigation (NCT04695977) compared to systemic nivolumab alone in treatment-naive, unresectable or metastatic melanoma (Table 1). The role of vidutolimod in the neoadjuvant setting is also being explored. Neoadjuvant intralesional vidutolimod in combination with intravenous nivolumab was evaluated in a phase 2 clinical trial (NCT03618641) in 30 patients with Stage IIIB-D, clinically node-positive melanoma . On surgical pathology, CR was seen in 50% with 70% having a >50% reduction in tumor volume. There were no dose-limiting toxicities, three patients experienced an unspecified grade 3 or 4 immune-related AE and two discontinued vidutolimod as a result. A similar trial of neoadjuvant intratumoral vidutolimod with systemic nivolumab versus nivolumab alone is being evaluated in an ongoing phase 2 study, NCT04401995, in stage IIIB-D melanoma, but with palpable nodal disease or nodal recurrence (Table 1). Neoadjuvant intralesional vidutolimod is also being investigated in combination with systemic pembrolizumab versus pembrolizumab alone in stage III, N1b-N3c, resectable melanoma in a phase 2 trial (NCT04708418). 2.5.4. Cavrotolimod (AST-008) Cavrotolimod (AST-008) is a spherical nucleic acid configuration, with densely and radially arranged oligonucleotides on liposomal nanoparticles, of a TLR9 agonist that has been shown, preclinically, to elicit a Th-1-type immune response similar to other TLR9 agonists . Clinical investigation of intratumoral cavrotolimod in combination with systemic pembrolizumab is ongoing in a phase 1b/2 trial (NCT03684785) in solid tumors including anti-PD-1/L1-refractory, locally advanced or metastatic melanoma (Table 1). Interim phase 1b data reported that in 19 evaluable patients, the ORR was 21% and two of the four responders had anti-PD-1 refractory melanoma . There were no dose-limiting toxicities and the most common treatment-related AEs were grade 1 or 2 injection site reactions. 2.6. Toll-like Receptor 7/8 (TLR 7/8) Agonists NKTR-262 NKTR-262, a TLR7/8 agonist, has similar effects to TLR9 agonists; it increases CD8+ T cell and NK cells, resulting in amplified tumor antigen release and presentation . In combination with bempegaldesleukin, it has been shown to increase innate immune signaling and antigen presentation . Therefore, the combination of intralesional NKTR-262 with systemic bempegaldesleukin with or without systemic nivolumab was under investigation in unresectable or metastatic solid tumors including melanoma in a phase 1/2 trial (NCT03435640); however, it was recently terminated by the sponsor based on phase 1 findings. 2.7. Immune Checkpoint Inhibitors Ipilimumab is an anti-CTLA-4 antibody that acts to disinhibit the antitumor T cell response and is FDA-approved for metastatic melanoma . However, its efficacy as an intravenous therapy is often limited by significant systemic adverse effects . Intratumoral delivery offers the potential to avoid systemic dosing and, in early clinical investigation, was well tolerated and elicited responses in combination with intratumoral IL-2 . Specifically, of the 12 patients, none experienced dose-limiting toxicities, there were no grade 4 or 5 treatment-related AEs, and the most common were injection site reaction, pain, and ulceration as well as fatigue and chills. Intratumoral ipilimumab is now under investigation in combination with systemic nivolumab compared to intravenous administration of both drugs in a phase 1/2 trial (NCT02857569) in stage III-IV melanoma (Table 1). This concept is being expanded to include localized delivery of various ICIs in a phase 2/3 trial (NCT03755739) assessing the efficacy of intralesional and trans-arterial delivery of investigator's choice ICIs compared to standard venous administration in advanced sold tumors, including melanoma. 2.8. Other Therapeutics 2.8.1. LL37 LL37 is an endogenous antimicrobial peptide that can increase DC and B cell recognition and binding of CpG oligonucleotides . A phase 1/2 trial (NCT02225366) investigating intratumoral LL37 in Stage IIIB-IVA melanoma is awaiting publication (Table 1). 2.8.2. Hiltonol (Polyinosinic-Polycytidylic Acid-Poly-I-Lysine Carboxymethylcellulose, Poly-ICLC) Hiltonol is a toll-like receptor 3 and melanoma differentiation-associated protein 5 ligand, a synthetic double-stranded RNA mimic of a pathogen-associated molecular pattern . In early clinical investigation with intratumoral and intramuscular injection, it was shown to increase intratumoral levels of CD4+ and CD8+ T cells, PD-1, and PD-L1. A phase 2 trial (NCT02423863) of intratumoral and intramuscular hiltonol alone or in combination with anti-PD-1/L1 in advanced, unresectable solid tumors, including melanoma, is now underway (Table 1). 2.8.3. APX005M APX005M is a monoclonal antibody agonist of CD40. CD40 is present on APCs and macrophages and the CD40 ligand is on T cells; therefore, APX005M has the potential to activate CD8+ T cells and increase major histocompatibility complex (MHC) class I expression on tumor cells . It is now under investigation as an intralesional agent in a phase 1/2 trial (NCT02706353) in combination with systemic pembrolizumab in ICI-naive, unresectable stage III-IVM1c melanoma (Table 1). 2.8.4. Dendritic Cell Therapy DCs are APCs, which, in their mature state, express MHC-antigen complexes and costimulatory molecules, and elicit a T cell response . Since DC activation is an important part of the antitumor immune response, autologous DCs have been a therapeutic avenue under investigation for many malignancies. A phase 1b/2 trial (NCT03325101) examining the efficacy of intratumoral autologous mature DCs in combination with cryosurgery and systemic pembrolizumab for anti-PD-1/L1-refractory unresectable stage III-IV melanoma is ongoing (Table 1). 2.8.5. INT230-6 INT230-6 is a combination of cisplatin and vinblastine with an amphiphilic penetration enhancer for targeted tumor cell delivery . It has been shown to result in CD4+ and CD8+ T cell activation and DC recruitment with abscopal effects in preclinical models as well as synergistic effects when combined with ICIs. It is under phase 1/2 investigation (NCT03058289) in solid tumors, including treatment-refractory metastatic melanoma, alone and in combination with ICIs, and interim results show it is well-tolerated without dose-limiting toxicity or grade 4 or 5 treatment-emergent adverse events (Table 1) . The most common treatment-related AEs reported were localized pain, nausea, fatigue, and vomiting. 2.8.6. Polidocanol Polidocanol, an intralesional sclerosant that has long been used in the treatment of varicose veins , was under investigation as an intralesional therapy in Stage IIIB-IV melanoma (NCT03754140); however, the phase 2 study was recently withdrawn due to poor accrual. 3. Conclusions There remains significant room for advancement in the treatment of advanced melanoma. In patients with lesions amenable to injection, intralesional therapy provides a promising option. Though intralesional therapies for melanoma were under investigation nearly 50 years ago, the field has seen the most growth within the past decade. Following the FDA approval of T-VEC in 2015, the field has continued to grow and evolve. In the past 5 years, we have seen numerous therapies under investigation, with most modulating or activating the host immune response in some way. This has followed the trend of systemic immunotherapy for advanced melanoma. While systemic ICIs have revolutionized the treatment of advanced disease, response and durability is limited and there can be significant treatment-limiting immune-related adverse events. Local delivery of therapeutics that have the potential to modulate the immune response at the site(s) of disease provide promise as a way to enhance efficacy, circumvent resistance, and limit systemic adverse effects, as we have seen in some of the trials discussed above. Unfortunately, not every intralesional regimen investigated has been successful. Perhaps the most notable and surprising were the recent results of NCT02288897, the phase 3, randomized controlled trial of intralesional T-VEC with systemic pembrolizumab versus an intralesional placebo with systemic pembrolizumab in which no survival benefit was seen . Since this study was conducted in anti-PD-1-naive advanced melanoma, it highlights the importance of identifying the appropriate timing of therapeutic regimens. Additionally the inclusion of stage IVM1b-IVM1c melanoma despite past trials demonstrating greater efficacy in less advanced (stage III-IVM1a) disease , emphasizes the importance of patient selection for future trials. Further to this, the trial outcome suggests that optimal benefit of T-VEC in combination with ICI may either be in the neoadjuvant, or second-line or later setting, as is currently under investigation. Additionally, multiple trials evaluating intralesional toll-like receptor agonists in combination with systemic immunotherapies in metastatic melanoma (NCT03445533, NCT02521870, NCT03435640) have recently been terminated due to their lack of efficacy or concern from the sponsor. Other TLR-9 agonists, vidutolimod and cavrotolimod, remain in phase 2 trials with systemic ICIs and bear watching. Ultimately, the major limitation of intralesional therapy is administration. Injection should be performed by an experienced provider and drug delivery is dependent on provider technique. T-VEC and other intralesional therapies have attempted to account for variability by providing specific dosing instructions based on lesion size and number; however, the nature of intralesional therapy makes it impossible to completely standardize dosing. For many patients, a significant barrier to receiving intralesional therapies is access to healthcare facilities in which they are offered. This is further exacerbated by frequent dosing schedules. In general, it seems that the cytokine-based therapies (IL-2) and TLR-9 agonists have the most intensive dosing regimens, while other therapies have less frequent dosing, but even the less intensive schedules are every 3-4 weeks. Lastly, the intratumoral delivery of these therapies is advantageous in generating a response to specific disease sites and limiting systemic side effects; however, it also appears to limit efficacy in uninjected sites of disease. The abscopal effects of intralesional therapies are of great interest since in many cases of advanced disease, it is not possible to inject every tumor and microscopic disease may not be identified. While intralesional therapies have demonstrated a response in some sites of uninjected disease, to our knowledge, no studies of intratumoral agents alone have demonstrated an equivocal response in injected and uninjected lesions. Future Directions In discussing the limitations and shortcomings of current intralesional therapies, we highlight areas for improvement and future directions. One of the greatest areas for advancement is sorting out the appropriate drug regimens and timing. There are numerous possible combinations of intratumoral and systemic therapies, even if only using the drugs that have been discussed here. We have already seen instances of regimens that appear promising in other settings or earlier phase trials that have not delivered expected results. Therefore, we should expect more clarity regarding effective timing and combinations in the coming years. Accessibility of intratumoral therapy is another avenue for future improvement. As more intratumoral therapies and combination regimens become FDA-approved or widely available, we can expect to see more providers administering intralesional therapies. Additionally, once more efficacious intratumoral therapies and combination regimens have been identified, accessibility can be further improved with optimization of the dosing schedules to make them more patient friendly where possible. Finally, the application of precision medicine to intratumoral therapy is largely unexplored. The use of autologous mature DCs as intralesional therapy is one of the few personalized therapies currently under investigation. With more widespread tumor genome sequencing, identification of targetable mutations, and development of targeted therapies, we can hope for a more individualized approach to intralesional therapy in the future. Author Contributions D.K.D. and J.S.Z. made substantial contributions to the conception and design of the work and the acquisition, analysis, and interpretation of data for the work. D.K.D. contributed to the drafting of the work, and J.S.Z. contributed to the critical revision for important intellectual content. D.K.D. and J.S.Z. provided final approval of the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest D.K.D. declares no conflict of interest. J.S.Z. has advisory board relationships and has received fees from with Merck, Novartis, Philogen, Castle Biosciences, Pfizer, and Sun Pharma. He also received research funding from Amgen, Delcath Systems, Philogen, Provectus, and Novartis. He serves on the medical advisory board for Delcath Systems. Figure 1 Timeline of Phase 2 or later clinical trials of intralesional therapy for advanced melanoma published in the last 5 years. Abbreviations: IT, intratumoral; IV, intravenous; T-VEC, talimogene laherparepvec; ipi, ipilimumab; pts, patients; ORR, overall response rate; C-REV, canerpaturev; DCR, disease control rate; AE, adverse event; tavo-EP, tavokinogene telseplasmid electroporation; CR, complete response; PFS, progression-free survival; PD-1, programmed cell death protein 1; OS, overall survival; nivo, nivolumab; RFS, recurrence-free survival; CVA21, coxsackievirus A21; irRECIST, immune-related response evaluation criteria in solid tumors; pembro, pembrolizumab. cancers-15-01404-t001_Table 1 Table 1 Ongoing Phase 2 or Later Clinical Trials of Intralesional Therapy for Locoregionally Advanced and Metastatic Melanoma. Clinical Trial Number Phase Regimen Melanoma Population Intralesional Dosing Schedule Preliminary Results NCT02557321 1b/2 IT PV-10 + IV pembro vs. IV pembro alone ICI-Naive and ICI-refractory, unresectable, stage III-IV Q3W x 5C - 21 ICI-naive, 67% ORR - 19 ICI-refractory, 26% ORR NCT03474497 1/2 IT IL-2 + IV ICI + hypofractionated XRT PD-1/L1-refractory, stage IV 2x/W x 4C - NCT03928275 2/3 IT IL-2 vs. IT IL-2 + IT BCG Stage IIIC-IVM1a Q2W x 4C - NCT03132675 2 IT Tavo-EP + IV pembro Anti-PD-1-refractory, unresectable, stage III-IV Days 1, 5, 8, Q6W, up to 18C - 54 evaluable, 30% ORR - 5.4% grade 3 treatment-related AEs NCT02076646 1/2 IT L19IL2 + IV DTIC vs. IV DTIC alone Stage IV (M1a-b in phase 2) Days 1, 8, 15 Q3W - NCT03567889 3 IT Daromun + surgery + IV ID adjuvant vs. surgery + IV ID adjuvant Neoadjuvant, resectable stage IIIB-C Q1W, up to 4C - NCT02938299 3 IT Daromun + surgery vs. surgery Neoadjuvant, resectable stage IIIB-C Q1W, up to 4C - NCT04427306 2 IT T-VEC + surgery Neoadjuvant, resectable, high-risk Not specified - NCT04068181 2 IT T-VEC + IV pembro Anti-PD-1-refractory, unresectable, stage IIIB-IV Q3W, up to 35C - 26 primary resistance in recurrent/metastatic setting, 0% ORR - 15 acquired resistance in recurrent/metastatic setting, 7% ORR - 15 resistance in adjuvant setting with <6 mos. disease free, 40% ORR - 15 resistance in adjuvant setting with >=6 mos. disease free, 47% ORR NCT04330430 2 IT T-VEC + IV nivo Neoadjuvant, resectable stage IIIB-IVM1a Q3W x 1C then Q2W x 3C - NCT03842943 2 IN T-VEC + IV pembro Neoadjuvant, clinically node-positive, resectable, stage III Q3W up to 6 mos. - NCT02819843 2 IT T-VEC +- XRT Unresectable, stage IIIB-IV Q3W x 1C then Q2W x 7C - NCT03555032 1/2 IT T-VEC + ILP Amenable to ILP, stage IIIB-IVM1b Q2-3 Weeks x 3 doses - NCT03767348 1/2 IT RP1 +- IV nivo Stage IIIB-IVM1c Not specified - 8 anti-PD-1-naive, 63% ORR. - 16 anti-PD-1-refractory, 38% ORR - 75 anti-PD-1/L1-refractory, 36% ORR, 53% DCR NCT04349436 1b/2 IT RP1 Treatment-refractory, locally advanced or metastatic, solid organ transplant recipients Q2W - NCT04200040 2 IT OrienX010 vs. IV DTIC Treatment-naive, unresectable, stage IIIB-IVM1b Q2W - NCT05561491 2 IT Oncos-102 +- IV balstilimab Anti-PD-1-refractory, unresectable or metastatic Not specified - NCT04725331 1/2a IT BT-001 +- IV pembro Locally advanced or metastatic Not specified - NCT04152863 2 IT & IV CVA21 + IV pembro vs. IV pembro ICI-naive, stage III-IV Day 1, 3, 5, 8 Q4W x 1C, then Q3W x up to 7C - NCT04303169 1/2 IT CVA21 + IV pembro + surgery vs. other investigational drugs + IV pembro + surgery Neoadjuvant, treatment-naive, resectable, stage IIIB-D Not specified - NCT04577807 2 IT PVSRIPO +- IV anti-PD-1 therapy Anti-PD-1/L1-refractory, unresectable, stage III-IVM1b Q1W x 7C then Q3-4W - NCT03190824 2a IT OBP-301 Unresectable, stage IIIB-IV Q2W up to 13C - NCT04291105 2 IT and IV VV1 + IV cemiplimab +- ipi Anti-PD-1/L1-refractory, advanced or metastatic Q4W x 1C, then Q3W - NCT03544723 2 IT Ad-p53 + IV ID ICI Recurrent or metastatic Not specified - NCT01397708 1/2 IT RheoSwitch Unresectable, stage III-IV Q3W up to 6 C - Dose-escalation well tolerated, most common AEs were chills, pyrexia NCT04698187 2 IT vidutolimod + IV nivo Anti-PD-1-refractory, unresectable or metastatic Q1W x 7C then Q3W - NCT04695977 2/3 IT vidutolimod + IV nivo vs. IV nivo Treatment-naive, unresectable or metastatic Q1W x 7C then Q3W - NCT04401995 2 IT vidutolimod + IV nivo vs. IV nivo Neoadjuvant, palpable nodal disease or nodal recurrence, stage IIIB-D Q1W x 7C - NCT04708418 2 IT vidutolimod + IV pembro + surgery vs. IV pembro + surgery Neoadjuvant, resectable, stage III N1b-N3c Day 1, 8, 15 Q3W x 2C then Q3W x 4C - NCT03684785 1b/2 IT cavrotolimod + IV pembro Anti-PD-1/L1-refractory, locally advanced or metastatic Not specified - 19 evaluable phase 1b, 21% ORR (2 of 4 responders had anti-PD-1-refractory melanoma) NCT02857569 1/2 IT ipi + IV nivo vs. IV ipi + IV nivo Unresectable, stage III-IV Q3W up to 4C - NCT03755739 2/3 IT ID ICIs vs. trans-arterial ID ICIs vs. IV ID ICIs Advanced Q3W - NCT02225366 1/2 LL37 Unresectable, stage IIIB-IVA Q1W up to 8C - NCT02423863 2 IT hiltonol + IM hiltonol +- IV anti-PD-1/L1 Unresectable, advanced IT Day 1, 3, 5 x 1W then IM 2x/W - NCT02706353 1/2 IT APX005M + IV pembro ICI-naive, unresectable, stage III-IVM1c Q3W up to 4C - NCT03325101 1b/2 IT DCs + cryosurgery + IV pembro Anti-PD-1/L1-refractory, unresectable, stage III-IV Apheresis then Q3W x 2C - NCT03058289 1/2 IT INT230-6 +- IV ICI Treatment-refractory, metastatic Q4W x 5C - No dose-limiting toxicity, grade 1-2 injection site pain most common Table 1 abbreviations: IT, intratumoral; IV, intravenous, pembro, pembrolizumab; ICI, immune checkpoint inhibitor; Q, every; W, week; x, times; C, cycle; ORR, overall response rate; IL-2, interleukin-2; XRT, external beam radiation therapy; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1; BCG, bacillus Calmette-Guerin; Tavo-EP, tavokinogene telseplasmid electroporation; AE, adverse event; DTIC, dacarbazine; ID, investigator's discretion; T-VEC, talimogene laherparepvec; IN, intranodal, ILP, isolated limb perfusion; RP1, vusolimogene oderparepvec; CVA21, coxsackievirus A21; VV1, voyager V1; ipi, ipilimumab; Ad-p53, adenoviral p53; nivo, nivolumab; IM, intramuscular; DC, dendritic cell. 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PMC10000423 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050947 foods-12-00947 Article Phytochemical Composition and Bioactive Potential of Melissa officinalis L., Salvia officinalis L. and Mentha spicata L. Extracts Silva Beatriz Nunes 1234 Cadavez Vasco 12 Caleja Cristina 12 Pereira Eliana 12 Calhelha Ricardo C. 12 Anibarro-Ortega Mikel 12 Finimundy Tiane 12 Kostic Marina 5 Sokovic Marina 5 Teixeira Jose Antonio 34 Barros Lillian 12 Gonzales-Barron Ursula 12* Rutkowska Jaroslawa Academic Editor Pasqualone Antonella Academic Editor 1 Centro de Investigacao de Montanha (CIMO), Instituto Politecnico de Braganca, Campus de Santa Apolonia, 5300-253 Braganca, Portugal 2 Laboratorio Associado para a Sustentabilidade e Tecnologia em Regioes de Montanha (SusTEC), Instituto Politecnico de Braganca, Campus de Santa Apolonia, 5300-253 Braganca, Portugal 3 CEB--Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal 4 LABBELS--Associate Laboratory, 4710-057 Braga, Portugal 5 Institute for Biological Research "Sinisa Stankovic"--National Institute of Republic of Serbia, University of Belgrade, Bulevar Despota Stefana 142, 11000 Belgrade, Serbia * Correspondence: [email protected]; Tel.: +35-12-7330-3325 23 2 2023 3 2023 12 5 94719 1 2023 13 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 ). Plants are rich in bioactive phytochemicals that often display medicinal properties. These can play an important role in the production of health-promoting food additives and the replacement of artificial ones. In this sense, this study aimed to characterise the polyphenolic profile and bioactive properties of the decoctions, infusions and hydroethanolic extracts of three plants: lemon balm (Melissa officinalis L.), sage (Salvia officinalis L.) and spearmint (Mentha spicata L.). Total phenolic content ranged from 38.79 mg/g extract to 84.51 mg/g extract, depending on the extract. The main phenolic compound detected in all cases was rosmarinic acid. The results highlighted that some of these extracts may have the ability to prevent food spoilage (due to antibacterial and antifungal effects) and promote health benefits (due to anti-inflammatory and antioxidant capacities) while not displaying toxicity against healthy cells. Furthermore, although no anti-inflammatory capacity was observed from sage extracts, these stood out for often displaying the best outcomes in terms of other bioactivities. Overall, the results of our research provide insight into the potential of plant extracts as a source of active phytochemicals and as natural food additives. They also support the current trends in the food industry of replacing synthetic additives and developing foods with added beneficial health effects beyond basic nutrition. Lamiaceae polyphenols antimicrobials antifungals antioxidants anti-inflammatory effect antiproliferative effect alternative preservatives biopreservation EU PRIMAPRIMA/0001/2018 FCT/MCTESUIDB/00690/2020 LA/P/0007/2021 UIDB/04469/2020 European Regional Development FundNORTE-01-0145-FEDER-000004 Ministry of Science, Technological Development and Innovation of the Republic of Serbia451-03-47/2023-01/200007 The authors are grateful to the EU PRIMA program and the Portuguese Foundation for Science and Technology (FCT) for funding the ArtiSaneFood project (PRIMA/0001/2018) and for financial support through national funds FCT/MCTES to CIMO (UIDB/00690/2020) and SusTEC (LA/P/0007/2021). This study was supported by FCT under the scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020--Programa Operacional Regional do Norte. This work has been supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (451-03-47/2023-01/200007). B.N. Silva and M. Anibarro-Ortega acknowledge the financial support provided by FCT through the Ph.D. grants SFRH/BD/137801/2018 and 2020.06297.BD, respectively. E. Pereira (2021.03908.CEECIND), R.C. Calhelha, L. Barros and U. Gonzales-Barron acknowledge the national funding by FCT, P.I., through the Individual and Institutional Scientific Employment Program contract. C. Caleja is grateful for her contract through the project Healthy-PETFOOD (POCI-01-0247-FEDER-047073). pmc1. Introduction Over recent years, with the increasingly negative perception of consumers towards artificial food additives and the higher demand for nutritious foods with additional health benefits, two major trends in the food industry have been to replace synthetic additives, which may be harmful to human health , and to develop nutraceuticals/functional foods . In line with these trends, modern science has shown that plant matrices are sources of valuable molecules (for example, phenolic compounds) with promising biological value (e.g., antioxidant, anti-inflammatory, antibacterial and antifungal), thus encouraging their use for the development of functional foods and nutraceuticals, and as possible substitutes for artificial additives in foods or their packaging . However, it is necessary to guarantee that the herbal extracts are safe for human consumption, and, among other considerations, it is crucial that they are obtained: (i) using nontoxic solvents authorised for the industrial production of foodstuffs and food ingredients, which do not leave residues or derivatives in the product after removal (or leave them in technically unavoidable quantities that pose negligible risk to human health) ; and (ii) from herbs with documented traditional use, commonly used in cooking as aroma and/or flavour enhancers . To this, lemon balm (Melissa officinalis L., Lamiaceae), sage (Salvia officinalis L., Lamiaceae) and spearmint (Mentha spicata L., Lamiaceae) are among the various plants widely used in traditional Mediterranean cuisine and medicine, and for which several researchers have reported health-promoting capacities and potential as natural food additives . Lemon balm has many beneficial capacities, such as spasmolytic, sedative, antitumoral, antimicrobial and antioxidant effects . Furthermore, this plant has shown therapeutic effects for the treatment of the cognitive disturbance of Alzheimer's disease, and has been traditionally used to reduce anxiety, sleep disturbance, depression and gastrointestinal disorders . In relation to sage, this herb has been used as a gargle for throat inflammations, to reduce perspiration, improve regularity of menstrual cycle, decrease hot flashes in menopause, battle gastrointestinal problems, prevent neurodegenerative diseases and improve mental capacity . Furthermore, sage has shown anti-inflammatory, antimicrobial, hypoglycemic, antidiabetic, antioxidant and antitumor activities . As for spearmint, it is frequently used in folk medicine against gastrointestinal and respiratory complications, haemorrhoids, stomach ache, memory dysfunction, and can be used as a carminative, antispasmodic, diuretic, antibacterial, antifungal and antioxidant agent . Considering the recognised beneficial effects for human health of lemon balm, sage and spearmint, the goal of this research was to chemically characterise and appraise the bioactivities of extracts from such plants, produced through different environmentally friendly extraction methods (decoction, infusion and maceration), using water and 80% ethanol (v/v) as solvents. More specifically, the extracts' cytotoxicity, antibacterial, antifungal, anti-inflammatory and antioxidant capacities were evaluated to assess their safety and preservative effects. 2. Materials and Methods 2.1. Plant Material and Extraction Procedures Sage, lemon balm and spearmint dry aerial parts were supplied by Pragmatico Aroma, Lda. ("Mais Ervas", Tras-os-Montes, Portugal), mechanically milled and submitted to the following extraction methods: infusion, decoction and dynamic maceration. For the infusions, 2 g of plant material was mixed with 200 mL of boiling distilled water and left to rest for 5 min without additional heating. For the decoctions, 2 g of plant material was mixed with 200 mL of distilled water, heated to boiling and boiled for 5 min. Infusions and decoctions were then filtrated (7-10 mm), frozen and lyophilised (FreeZone 4.5, Labconco, Kansas City, MO, USA). To obtain hydroethanolic extracts, dynamic macerations were conducted by incorporating 1 g of plant material in 30 mL of ethanol at 80% (v/v) and stirring at room temperature for 1 h. The supernatants were filtrated (7-10 mm), another 30 mL of ethanol 80% (v/v) was added to the extraction residues, and the maceration was repeated for 1 h. Finally, the ethanolic portion was evaporated (Buchi R-210, Flawil, Switzerland) and the resulting extracts were frozen and lyophilised. The extractions were carried out in triplicate (n = 3). 2.2. Identification and Quantification of Individual Phenolic Compounds Individual phenolic compounds were investigated using a previously validated method, as described by Restivo et al. . First, the samples were dissolved in ethanol 20% (v/v) up to a final concentration of 10 mg/mL and filtered through disposable 0.22 mm filters. The phenolic profiles were then determined by a liquid chromatography system (Dionex Ultimate 3000 UPLC, Thermo Scientific, San Jose, CA, USA) equipped with a quaternary pump, an automatic injector at 5 degC, a degasser and a column compartment with an automated thermostat. Compound detection was carried out with a diode-array detector (at wavelengths of 280 nm, 330 nm and 370 nm), coupled to a mass spectrometry (MS) detector. Separation was performed on a reverse phase Waters Spherisorb S3 ODS-2 C18 column (4.6 mm x 150 mm, 3 mm) at 35 degC. The flow rate was 0.5 mL/min. The mobile phase used was water/formic acid 0.1% (A) and acetonitrile (B). The elution gradient for solvent B was as follows: 10-15% eluent B up to 5 min, 15-20% B up to 5 min, 20-25% B 10 min, 25-35% B 10 min, 35-50% B 10 min and column re-equilibration for 10 min. For MS detection, a Linear Ion Trap LTQ XL spectrophotometer equipped with an electrospray ionization source was used. Nitrogen (50 psi) was used as a carrier gas, and the system worked with an initial temperature of 325 degC, a spray voltage of 5 kV and a capillary voltage of -20 V. The tube lens offset voltage remained at -66 V. Spectra were recorded in negative ion mode 100-1500 m/z. The phenolic compounds were identified through their chromatographic characteristics by comparison to the obtained standard compounds (4-hydroxybenzoic acid, apigenin-6-C-glucoside, apigenin-7-O-glucoside, caffeic acid, chlorogenic acid, naringenin and rosmarinic acid) and with the literature . For quantitative analysis, calibration curves prepared with appropriate standards (between 100 and 2.5 mg/L) were used. Limits of detection and quantification were also calculated, and, in all cases, the coefficient of linear correlation was R2 > 0.99 (supplementary materials, Table S1). All analyses were made in triplicate (n = 3). The results were expressed in mg per g of dry extract (mg/g). 2.3. Biological Evaluation 2.3.1. Antibacterial and Antifungal Activity For the antibacterial and antifungal activity screening, six bacterial strains were used: Escherichia coli (ATCC 25922), Salmonella enterica serovar Typhimurium (ATCC 13311), Enterobacter cloacae (clinical isolate), Staphylococcus aureus (ATCC 11632), Bacillus cereus (food isolate) and Listeria monocytogenes (NCTC 7973), and six micromycetes: Aspergillus fumigatus (human isolate), Aspergillus niger (ATCC 6275), Aspergillus versicolor (ATCC 11730), Penicillium funiculosum (ATCC 36839), Penicillium verrucosum var. cyclopium (food isolate) and Trichoderma viride (IAM 5061). Minimum inhibitory (MIC), minimum bactericidal (MBC) and minimum fungicidal (MFC) concentrations were determined using a broth microdilution method and 96-well microplates . The streak plate culture method, conducted on tryptic soy agar (Torlak, Belgrade, Serbia) incubated at 37 degC for 24 h, was used to obtain bacterial cells in the exponential growth phase. Then, an adequate number of individual colonies were placed in tubes with sterile water to achieve bacterial suspensions with a concentration of approximately 1.0 x 105 CFU/well in the microplates. For the antifungal activity essay, fungal spores were washed from the surface of malt agar plates (Neogen, Heywood, UK) with sterile 0.85% saline added with 0.1% Tween 80 (v/v) (Zorka pharma, Sabac, Belgrade). Sterile saline was then used to adjust the spore suspension to a concentration of approximately 1.0 x 105 in a final volume of 100 mL per well. For the antibacterial and antifungal essay, resuspended extracts were obtained by dissolving them in ethanol 30% (v/v) to obtain a final concentration of 10 mg/mL. The liquid media (90 mL) used in the microplate wells was tryptic soy broth (Torlak, Belgrade, Serbia) for the antibacterial essay, or malt extract broth (Neogen, Heywood, UK) in the case of the antifungal essay. After placing the inoculum, resuspended extract and liquid media in the microplate wells as appropriate, the microdilution plates were incubated at 37 degC for 24 h for the determination of the antibacterial activity, or 28 degC for 72 h for the determination of the antifungal activity. After that, 40 mL of iodonitrotetrazolium (Sigma-Aldrich, St. Louis, MO, USA), at a concentration of 0.2 mg/mL, was added to each well, and the microplate incubated again at 37 degC for 1 h. Afterwards, the microplates were evaluated, and the lowest concentrations without visible growth were determined as the MICs. The MBCs were determined as the lowest concentration with no visible growth after serial sub-cultivation of 10 mL into microdilution plates containing 100 mL of tryptic soy broth per well and further incubated for 24 h at 37 degC. For the antifungal essay, MICs were determined under binocular microscope using the same procedure as described above. After that, the MFC was determined by serial sub-cultivation of 2 mL of the content of the wells and further incubation at 28 degC for 72 h. The lowest concentration of this sub-culture with no visible growth was defined as the MFC. Two commonly used artificial food preservatives, sodium benzoate (E211) and potassium metabisulfite (E224), were also tested to evaluate the sensitivity of the microorganisms to such additives. The MIC, MBC and MFC were expressed in mg/mL of the resuspended lyophilised extracts. 2.3.2. Antioxidant Activity The antioxidant activity was evaluated through two in vitro essays, using previously described methodologies : inhibition of lipid peroxidation by decrease in the formation of thiobarbituric acid reactive substances (TBARS), and the oxidative haemolysis inhibition essay (OxHLIA). The extracts were initially diluted in distilled water (for TBARS) or phosphate-buffered saline (PBS, pH 7.4) (for OxHLIA) to different concentrations. Trolox was used as a positive control in both essays. For TBARS essay: the extracts were examined for their power to inhibit the ferrous sulphate-induced lipid peroxidation, using porcine brain cell homogenates, through monitorisation of the colour strength (at 532 nm) provided by malondialdehyde-thiobarbituric acid complexes. The results were expressed as the extract concentration (mg/mL) required to inhibit 50% of the TBARS formation (half-maximal inhibitory concentration, IC50). For OxHLIA essay: 200 mL of an erythrocyte solution at 2.8% prepared in PBS was added to 400 mL of either: extract solution (13-800 mg/mL in PBS), PBS solution (negative control), distilled water (baseline), or Trolox (7.81-250 mg/mL). After incubation for 10 min at 37 degC with agitation, 200 mL of 2,2'-azobis(2-methylpropionamidine) dihydrochloride (AAPH, 160 mM in PBS) was added, and the optical density (at 690 nm) was measured in a microplate reader (Bio-Tek Instruments, ELx800, Winooski, VT, USA) every 10 min until complete haemolysis. The percentage of the erythrocyte population that remained undamaged (P) was calculated using Equation (1), where St and S0 are the optical density of the sample at t and 0 min, respectively, and CH0 is the optical density of the complete haemolysis at 0 min. (1) P%=100x(St-CH0S0-CH0) The delayed time of haemolysis (Dt) was calculated using Equation (2), where the 50% haemolytic time (min) graphically obtained from the haemolysis curve of each sample concentration is represented by Ht50: Dt (min) = Ht50 (sample) - Ht50 (control) (2) Lastly, the Dt values were correlated to the various sample concentrations. From that correlation, the concentrations able to promote Dt haemolysis delays of 60 min and 120 min were calculated. The results were expressed as IC50 values (mg/mL) at Dt = 60 min and Dt = 120 min, i.e., the sample concentration required to protect 50% of the erythrocyte population from the haemolytic action of AAPH for 60 min and 120 min, respectively. 2.3.3. Anti-Inflammatory Activity The anti-inflammatory activity was evaluated using a previously described essay, with modifications . First, cells from the mouse macrophage-like cell line RAW264.7 were seeded in plates of 96-wells, and their attachment was allowed overnight. Subsequently, cells were subjected to different extract concentrations (6.25-400 mg/mL) for 1 h, and then stimulated with lipopolysaccharides (1 mg/mL) for 18 h. This procedure enabled observation of the occurrence of induced changes in nitric oxide basal levels, using a Griess Reagent System kit (Promega, Madison, WI, USA). The nitrite level produced was determined in a microplate reader (Bio-Tek Instruments, ELx800, Winooski, VT, USA) by assessing the optical density at 540 nm and comparing it with the standard calibration curve. The positive control used was dexamethasone (50 mM). The results are stated as the sample concentration (mg/mL) necessary to inhibit 50% of the nitric oxide production (IC50). 2.3.4. Cytotoxic Activity The lyophilised extracts were dissolved in water and successively diluted to obtain the stock solutions. The cytotoxic activity was then assessed against six human tumour cell lines, namely AGS (gastric adenocarcinoma), CaCo-2 (colorectal adenocarcinoma), HeLa (cervical carcinoma), MCF-7 (breast adenocarcinoma), NCI-H460 (large cell lung carcinoma) and non-tumour hFOB (human foetal osteoblasts), using the previously described sulforhodamine B essay . For this, each of the cell lines (190 mL, 104 cells/mL) was incubated with the plant extracts at various concentrations (6.25-400 mg/mL). Ellipticine was used as a positive control. The results were expressed as the extract concentration required to inhibit 50% of the net cell growth (half-maximal cell growth inhibitory concentration, GI50). 2.4. Statistical Analysis Data were presented as mean +- standard deviation (SD) values. One-way analysis of variance (ANOVA, a = 0.05) was used to assess statistical differences between the means. Clustered heatmaps were generated using the pheatmap function from the pheatmap package . Statistical analysis was conducted in R software (version 4.1.0, R Foundation for Statistical Computing, Vienna, Austria). 3. Results and Discussion 3.1. Phenolic Profile The peak characteristics (retention time, wavelength of maximum absorption and mass spectral data), tentative identification and quantification of the phenolic compounds detected in the extracts produced are reported in Tables S2-S4 of the Supplementary Materials (sage, lemon balm and spearmint, respectively). Heatmaps for a fast visualisation of the phenolic compounds identified and their concentrations were produced and are shown in Figure 1, Figure 2 and Figure 3 (sage, lemon balm and spearmint, respectively). The dendrograms of each clustered heatmap arrange the information on phenolic composition in terms of similarities, where the lower the height at which any two objects are joined, the greater the similarity. In this sense, one dendrogram (left) offers insight regarding compounds detected in similar concentrations across extracts obtained through different methodologies (infusion, decoction and hydroethanolic maceration), whereas the other dendrogram (upper) informs about similar total phenolic compound content across the extracts produced, for each plant. Twenty-four phenolic compounds were identified in all sage extracts. From Figure 1 and Table S2, sage decoction and infusion contained higher and similar total phenolic compounds content (84.07 and 77.67 mg/g extract, respectively), compared to the hydroethanolic extract (63.17 mg/g extract). In the case of lemon balm, a maximum of fourteen compounds were identified, depending on the extract type. Figure 2 and Table S3 indicate that its infusion and hydroethanolic extract showed comparable total phenolic compounds content (61.00 and 58.35 mg/g extract, respectively); however, lower than that of the decoction (84.51 mg/g extract). As for the spearmint extracts, a maximum of fourteen compounds were identified. Figure 3 and Table S4 reveal that spearmint infusion and hydroethanolic extract had closer total phenolic compounds concentration (38.79 and 57.92 mg/g extract, respectively) than spearmint decoction (77.20 mg/g extract). Considering these results, decoctions revealed the highest amount of total phenolic compounds when compared to infusions and hydroethanolic extracts, regardless of the plant (Tables S2-S4). Overall, sage and lemon balm decoctions stood out for their higher total phenolic content (84.07 and 84.51 mg/mL, respectively). Oppositely, spearmint infusion yielded the lowest total phenolic content among the nine extracts (38.79 mg/g extract, Table S4). In all cases, the plant extracts revealed a higher content of total phenolic acids compared with total flavonoids (Tables S2-S4). This was particularly noticeable in lemon balm extracts, which presented total flavonoid concentrations lower than 0.7 mg/g extract, in comparison with the total phenolic acids content, which ranged between 57.74 and 83.90 mg/g extract. In terms of qualitative profile, sage showed the highest variety of phenolic acids, with a total of fifteen different acids regardless of the type of extract. In comparison, in lemon balm, twelve or thirteen distinct phenolic acids were identified, depending on the extract type, whereas nine or ten acids were identified in spearmint extracts. Some phenolic acids were found across all the evaluated extracts, namely, rosmarinic and salvianolic acids, as well as lithospermic acid A. Among these, the major compound in all the sage extracts was cis-rosmarinic acid , followed by a derivative of luteolin, luteolin-7-O-glucuronide . In lemon balm, rosmarinic acid was found in the greatest amount, irrespective of the type of extract, with concentrations between 34.40 and 41.71 mg/g extract . Similarly, the major phenolic compound in spearmint extracts was rosmarinic acid . Rosmarinic acid is known to possess extraordinary therapeutic potential, which includes antiviral, antibacterial, anticarcinogenic, antioxidant, anti-aging, antidiabetic, cardioprotective, hepatoprotective, nephroprotective, antidepressant, antiallergic and anti-inflammatory activities . Sage extracts presented the highest number of different flavonoids (nine in total). These were derivates of apigenin and luteolin, with the most abundant compound being luteolin-7-O-glucuronide. Flavonoids were also detected in lemon balm and spearmint extracts, although in lesser variety (one and four in total, respectively), and these were also luteolin derivatives. Given these results, sage, lemon balm and spearmint extracts appear to be valuable sources of valuable bioactive compounds, particularly of phenolic acids. Previous studies also investigated the phenolic profile of the plant materials used in this work. In sage and lemon balm hydroethanolic extracts, Sprea et al. identified twenty-one and twelve phenolic compounds, respectively, several of which were also detected in the present study. Maliki et al. studied the polyphenolic profile of a sage aqueous extract, identifying eighteen compounds, most of which belonged to hydroxycinnamic acid, rosmarinic acid and luteolin derivatives. Both the studies of Sprea et al. and Maliki et al. found rosmarinic acid (51.00 mg/g and 2.192 mg/g, respectively) and luteolin-7-O-glucuronide (27.00 and 1.877 mg/g, respectively) to be the compounds of the highest concentrations in sage extracts, thus supporting the findings of our study. Also, in agreement with our results, Cirlini et al. identified rosmarinic acid and its derivatives as the most prevalent polyphenolic compounds in an aqueous spearmint extract (230.5 mg/g), followed by salvianolic acids (14.70 mg/g) and caffeoylquinic acids (3.06 mg/g). Silva et al. identified rosmarinic acid as the main compound in aqueous (204 mg/L) and hydroethanolic (333 mg/L) spearmint extracts; however, in lemon balm hydroethanolic extract, naringin was the principal compound (116 mg/L), and in sage aqueous and hydroethanolic extracts, hesperidin was present in the greatest amount (279 and 805 mg/L, respectively). This and other studies may have reported different phytochemical compositions , which however does not conflict with our results, since variations can be caused by different environmental factors during plant development, including soil type, change in season, salinity, light, altitude and humidity, as well as plant growth stage and extraction procedure . Since the health-promoting properties of plants have been largely attributed to their phenolic compounds (among other secondary metabolites) , it is intuitive that differences in phenolic profile among extracts produced from the same plant matrix will also originate variations in their bioactivities (antimicrobial, antioxidant and anti-inflammatory, for example). 3.2. Antibacterial and Antifungal Activity The results of the antibacterial and fungicidal activity are shown in Table 1 and Table 2, respectively. Overall, the extracts revealed antimicrobial activity against all foodborne pathogens tested, namely S. aureus, B. cereus, L. monocytogenes, E. coli, S. Typhimurium and E. cloacae (MIC <= 2 mg/mL; MBC <= 4 mg/mL). Sage infusion presented the lowest MIC and MBC values of all extracts (i.e., the greatest antimicrobial potential), particularly against S. aureus and B. cereus (MIC = 0.25 and MBC = 0.5 mg/mL in both cases). On the other hand, lemon balm decoction displayed the highest MIC and MBC values, specifically against L. monocytogenes (MIC = 2 and MBC = 4 mg/mL). With a few exceptions, hydroethanolic extracts showed uniform activity (MIC = 0.5 and 1 mg/mL) for all tested bacteria. In terms of antifungal capacity, all the infusions and hydroethanolic extracts were effective in inhibiting the six fungi tested, A. fumigatus, A. niger, A. versicolor, P. funiculosum, P. verrucosum and T. viride (MIC <= 1 mg/mL; MFC <= 2 mg/mL). Infusions demonstrated inhibition activity against the tested fungi with MIC values between 0.125 and 0.5 mg/mL, except for spearmint infusion against P. verrucosum var. cyclopium (MIC = 1 mg/mL). Hydroethanolic extracts stood out for inhibiting T. viride at a low concentration (MIC = 0.125 mg/mL for spearmint and sage extracts; MIC = 0.25 mg/mL for lemon balm extract), which demonstrates the susceptibility of this microorganism to such extracts. The three decoctions were also effective against all fungi (MIC <= 0.5 mg/mL; MFC <= 1 mg/mL) except A. niger (MIC > 4 mg/mL for lemon balm and spearmint). In general, the infusions, decoctions and hydroethanolic extracts showed comparable or higher antimicrobial and fungicidal activities than those of the artificial food preservatives E211 and E224. In particular, the results of E211 against S. aureus (MIC and MBC = 4 mg/mL) and P. verrucosum (MIC = 2 and MFC = 4 mg/mL), and those of E224 against B. cereus (MIC = 2 and MBC = 4 mg/mL) differ noticeably from the lower concentration of plant extracts needed to prevent the growth of such microorganisms. These findings point out the potential of the extracts tested in this study as good candidates for applications in food and possible alternatives for replacing synthetic preservatives, aiming to delay the proliferation of food spoilage and pathogenic bacteria and fungi. In line with our research, some previous studies have also reported on the antimicrobial and antifungal effects of these plants. The sage infusions of Abdel-Wahab et al. showed MIC values of 50 mg/mL for E. coli, and 75 mg/mL for Salmonella spp., S. aureus and B. cereus. Hydroethanolic sage extracts produced by Hemeg et al. revealed MIC values of 5 mg/mL for S. aureus, 0.625 mg/mL for B. cereus and 2.5 mg/mL for E. coli and S. Enteritidis. Silva et al. hydroethanolic sage extracts revealed MIC values of 2.5-5 mg/mL for L. monocytogenes, 0.625 mg/mL for S. aureus, 10 mg/mL for S. Typhimurium and 1.25 mg/mL for E. coli. In turn, Ueda et al. investigated hydroethanolic sage extracts obtained through ultrasound-assisted extraction, and MIC values were 1 mg/mL for S. aureus, B. cereus, L. monocytogenes, E. coli, S. Typhimurium and E. cloacae, 0.25 mg/mL for A. fumigatus, A. versicolor, P. funiculosum and P. verrucosum and 0.5 mg/mL for A. niger and T. viride. Silva et al. also tested the hydroethanolic extracts of spearmint and lemon balm, which revealed MIC values of 2.5 mg/mL for L. monocytogenes, 1.25 mg/mL for S. aureus, 20 mg/mL for S. Typhimurium and 1.25 mg/mL for E. coli for spearmint, and 5 mg/mL for L. monocytogenes, 2.5 mg/mL for S. aureus, 20 mg/mL for S. Typhimurium and 2.5 mg/mL for E. coli for lemon balm. Caleja et al. analysed the antimicrobial activity of spearmint infusions, reporting MIC values of 0.5 mg/mL for L. monocytogenes, B. cereus and E. coli and 0.25 mg/mL for S. Typhimurium. The same study also determined the MIC of lemon balm infusions, which revealed values of 1 mg/mL for all bacteria mentioned before . Furthermore, Caleja et al. evaluated the MIC of said infusions against A. niger, A. versicolor, P. funiculosum and P. verrucosum, and the values ranged between 0.25 and 1 mg/mL. 3.3. Antioxidant Activity The results of the TBARS and OxHLIA essays, which assess the ability of the plant extracts to inhibit lipid peroxidation and oxidative haemolysis in vitro, are presented in Table 3. The results are expressed as IC50 values, meaning that lower values correspond to greater antioxidant potential. In both TBARS and OxHLIA essays, the antioxidant capacity of each plant infusion was significantly different from that of the other two (p < 0.05). Differences were also found among the decoctions, in both essays, depending on the plant species (p < 0.05). The antioxidant power of the hydroethanolic extracts also displayed differences depending on the plant used (p < 0.05), although not all of them were significant in the case of the OxHLIA essay. Moreover, in both essays, for each plant, different extraction methods yielded distinct antioxidant activities (p < 0.05). The exception was the decoction and hydroethanolic extract of lemon balm, which presented similar antioxidant potential in the TBARS essay (p > 0.05). Overall, according to the statistical analysis, lemon balm infusion and sage hydroethanolic extract (125 mg/mL and 132 mg/mL, respectively) showed the best capacities to inhibit the formation of malondialdehyde and other reactive substances that are the result of the ex vivo decomposition of lipid peroxidation products (in the TBARS essay). The results of the OxHLIA essay showed that the sage decoction (8.93 mg/mL and 23.5 mg/mL, for Dt = 60 min and 120 min) and the hydroethanolic extracts of spearmint (12.5 mg/mL and 27.6 mg/mL, for Dt = 60 min and 120 min) and of lemon balm (13.5 mg/mL and 27.4 mg/mL, for Dt = 60 min and 120 min) exhibited the greatest antioxidant protection for the erythrocyte membrane, even compared to the pure antioxidant compound used as a positive control, Trolox (21.8 mg/mL and 43.5 mg/mL, for Dt = 60 min and 120 min). These results suggest the potential of such extracts to be used against free radical-induced oxidative damage of biological membranes. Furthermore, the OxHLIA essays allows us to distinguish between short-term and long-term antioxidant protection, as the antioxidant behaviour is monitored over time and the oxidative haemolysis assessed at two Dt. It was observed that all the infusions had anti-haemolytic activity for longer exposure times, as the concentration necessary to protect 50% of the red blood cells for 120 min was less than double the concentration necessary for this protection for 60 min. This also occurred in the case of spearmint and lemon balm decoctions, but not for the remaining extracts. Our findings agree with other researchers that have also reported on the antioxidant capacities of lemon balm, spearmint and sage. Groupwise summary statistics calculated by Silva et al. showed the high antioxidant power of these three plants, determined by the free radical scavenging (DPPH), radical cation decolorization (ABTS) and ferric reducing antioxidant power (FRAP) essays: the results were between 259 and 507 mmol Trolox Equivalent/g dry plant, for the DPPH and ABTS essays, and between 722 and 1013 mmol Fe2+/g dry plant for the FRAP essay. Abdel-Wahab et al. also evaluated a sage extract, using the DPPH method, and reported an IC50 of 13.34 mg/mL. Ueda et al. reported an IC50 of 2.6 mg/g of sage extract, determined by the OxHLIA method, for the time period of 120 min. Caleja et al. used two methods to assess the antioxidant power, reporting IC50 values of 6.6 mg/mL and 4.2 mg/mL for lemon balm and spearmint extracts, respectively (using the TBARS essay), and IC50 values of 24.8 mg/mL and 38.3 mg/mL for lemon balm and spearmint extracts, respectively (using the OxHLIA method for Dt = 60 min). 3.4. Anti-Inflammatory Activity Table 4 presents the anti-inflammatory activity essay results. These are expressed as IC50 values, so lower values correspond to greater anti-inflammatory potential. The outcomes shown in Table 4 indicate that most extracts did not reveal anti-inflammatory action at the tested concentrations (IC50 > 400 mg/mL). Only those of spearmint showed this capability, regardless of the extraction method. Spearmint hydroethanolic extract showed the greatest anti-inflammatory capacity, considering its IC50 of 26.6 mg/mL. In agreement with our results, the spearmint infusions of Caleja et al. also displayed anti-inflammatory activity against the RAW 246.7 cell line (IC50 = 324 mg/mL), whereas those of lemon balm did not (IC50 > 400 mg/mL). Nonetheless, and despite our results, some researchers have reported anti-inflammatory effects of sage and lemon balm extracts, meaning that these plants may be capable of offering such beneficial capacity under different circumstances . It could be expected that extracts with high rosmarinic acid concentrations and promising antioxidant activity (low IC50 values in Table 3), such as sage or lemon balm infusions, for example, would also show anti-inflammatory potential, as antioxidants can reduce the inflammatory process caused by the overproduction of free radicals . However, from the results in Table 4, it is noticeable that extracts presenting anti-inflammatory activity were not always the ones with the highest antioxidant capacity (except for spearmint hydroethanolic extract, which presented the lowest IC50 = 12.5 mg/mL in the OxHLIA essay among that type of extract). In this sense, it is important, when conducting analyses, to evaluate all bioactivities, and not to infer the results of one essay from the outcomes of another, to avoid arriving at wrongful conclusions, or even discarding plant extracts with substantial potential in terms of one particular bioactivity. 3.5. Cytotoxic Activity The cytotoxicity essay results are shown in Table 5. These are expressed as GI50, meaning that lower outcomes correspond to greater cytotoxic capacity. All nine extracts produced revealed inhibitory potential (GI50 < 400 mg/mL) against at least one tumour cell line. Overall, the extracts were more active in tumour cells AGS, CaCo-2, HeLa and MCF-7 than NCI-H460. In fact, the cytotoxic capacity of the infusions and decoctions in the NCI-H460 tumour line was non-existent (GI50 > 400 mg/mL); however, some hydroethanolic extracts revealed activity. The absence of toxicity (GI50 > 400 mg/mL) against non-tumour human foetal osteoblast cells, hFOB, was evident in the case of infusions and two decoctions (the exception was that of sage), which is a desirable outcome as extracts to be used in food products must be safe for consumption and cannot display toxicity against healthy cells. In contrast, the majority of hydroethanolic extracts (except that of sage, curiously) showed a cytotoxic effect towards hFOB cells, suggesting that this methodology may induce toxicity to the extracts, thus compromising their applicability as food additives. From all the extracts, those that are non-toxic against hFOB and simultaneously present inhibitory potential against AGS, CaCo-2, HeLa and MCF-7 cells are: sage hydroethanolic extract and the infusions of lemon balm, spearmint and sage. These results point out the cytotoxic potential of the infusions produced in comparison to other extraction methods. The infusion of spearmint, specifically, showed overall greater antiproliferative capacity, with GI50 values of 196 mg/mL for the AGS cell line, 304 mg/mL for the CaCo-2 cell line, 229 mg/mL for the HeLa cell line and 203 mg/mL for the MCF-7 cell line. The results obtained in this study agree, to some extent, with those of other researchers. Sage hydroethanolic extracts produced by Ueda et al. did not show hepatotoxicity in PLP2 cells (non-tumour) at the maximum tested concentration of 400 mg/mL. Lemon balm and spearmint infusions of Caleja et al. did not show toxicity for non-tumour cells PLP2 (GI50 > 400 mg/mL) and inhibited the growth of the HeLa cell line (GI50 = 241 mg/mL and GI50 = 251 mg/mL, respectively), in agreement with our results. Their spearmint infusion also inhibited MCF-7 growth (GI50 = 283 mg/mL), as found in our study. However, in contrast to our findings, lemon balm and spearmint infusions were able to inhibit NCI-H460 (GI50 = 290 mg/mL and GI50 = 322 mg/mL, respectively), and lemon balm infusion was incapable of affecting MCF-7 viability (GI50 > 400 mg/mL) . Overall, these results indicate that extracts originating from any of the plants examined are potentially valuable for their cytotoxic impact on various tumour cell lines. However, it is crucial to further evaluate potential undesired effects against healthy cell lines, as even reduced concentrations may result in dangerous consequences for human health. 4. Conclusions This work revealed the biological capacities of sage, spearmint and lemon balm extracts. Although only spearmint extracts showed anti-inflammatory potential, all infusions, decoctions and hydroethanolic extracts presented encouraging results in terms of antibacterial, antifungal and antioxidant capacities. Infusions revealed the most promising results, compared to decoctions and hydroethanolic extracts, as they yielded the best outcomes in each of the essays conducted (antimicrobial, antioxidant, anti-inflammatory and antiproliferative tests), while displaying an absence of toxicity against non-tumour cells, and even though infusions did not contain the highest total phenolic contents. Extracts from sage stood out from the remainder as they were often among those presenting the best capacities, both in terms of inhibiting the oxidation and growth of pathogenic bacteria and fungi, as well as impairing the viability of tumour cells. Nonetheless, no anti-inflammatory action was detected. Overall, the results of this study emphasise the potential value of sage, spearmint and lemon balm extracts as natural food ingredients to prevent spoilage, provide beneficial health effects and potentially replace artificial additives, hence aligning with current trends in the food industry. However, further in vitro and in vivo studies must be conducted to verify the functionality of these extracts: for example, evaluating their pharmacokinetic parameters (bioavailability and bioaccessibility). It is also expected that the food matrix has some impact on the bioactivities of plant extracts, causing differences between the results observed in vitro and in vivo, which may limit the bio-functionalities of such extracts in food products. Another obstacle that must be investigated and that herbal extracts may face is related to their effect on the sensory characteristics of foods, since the concentrations necessary to provide the desired biological capacities can be very high and, therefore, negatively affect the aroma and taste of the products. In this sense, further research must be conducted to complement in vitro studies and address these and other limitations. Supplementary Materials The following supporting information can be downloaded at: Table S1: Limit of detection (LOD), limit of quantification (LOQ) and coefficient of linear correlation (R2) of the different standards used to obtain the calibration curves required for phenolic compound quantification; Table S2. Phenolic compound content (mg/g dry extract) of sage (Salvia officinalis L.) extracts; Table S3. Phenolic compound content (mg/g dry extract) of lemon balm (Melissa officinalis L.) extracts; Table S4. Phenolic compound content (mg/g dry extract) of spearmint (Mentha spicata L.) extracts. Click here for additional data file. Author Contributions Conceptualization, V.C., J.A.T. and U.G.-B.; Data curation, B.N.S., C.C., E.P. and U.G.-B.; Formal analysis, B.N.S. and U.G.-B.; Funding acquisition, V.C., J.A.T. and U.G.-B.; Investigation, B.N.S., C.C., E.P., R.C.C., M.A.-O., T.F., M.K. and M.S.; Methodology, C.C., E.P., M.K., M.S., L.B. and U.G.-B.; Project administration, V.C., J.A.T. and U.G.-B.; Resources, V.C., L.B., J.A.T. and U.G.-B.; Software, B.N.S., V.C. and U.G.-B.; Supervision, V.C., L.B., J.A.T. and U.G.-B.; Validation, B.N.S., V.C., C.C., E.P. and U.G.-B.; Visualization, B.N.S., C.C., E.P. and U.G.-B.; Writing--original draft, B.N.S.; Writing--review and editing, C.C., E.P. and U.G.-B. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Summary data available upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Clustered heatmap visualisation of phenolic compounds detected in sage infusion, decoction and hydroethanolic extract (units: mg/g). Figure 2 Clustered heatmap visualisation of phenolic compounds detected in lemon balm infusion, decoction and hydroethanolic extract (units: mg/g). Figure 3 Clustered heatmap visualisation of phenolic compounds detected in spearmint infusion, decoction and hydroethanolic extract (units: mg/g). foods-12-00947-t001_Table 1 Table 1 Antibacterial activity of plant extracts expressed as minimum inhibitory concentration and minimum bactericidal concentration, MIC/MBC, respectively (mg/mL; mean +- SD, n = 3). Extraction Plant SA 1 BC 2 LM 3 EC 4 ST 5 EntC 6 Infusion Lemon balm 0.5/1 1/2 0.5/1 0.5/1 0.5/1 1/2 Spearmint 0.5/1 0.5/1 0.5/1 0.5/1 0.5/1 1/2 Sage 0.25/0.5 0.25/0.5 1/2 1/2 0.5/1 1/2 Decoction Lemon balm 0.5/1 0.5/1 2/4 1/2 0.5/1 1/2 Spearmint 0.5/1 0.5/1 1/2 0.5/1 0.5/1 1/2 Sage 0.5/1 0.5/1 1/2 0.5/1 0.5/1 1/2 Hydroethanolic extraction Lemon balm 0.5/1 0.5/1 1/2 0.5/1 0.5/1 0.5/1 Spearmint 0.5/1 1/2 0.5/1 0.5/1 0.5/1 0.5/1 Sage 0.5/1 1/2 0.5/1 0.5/1 0.5/1 0.5/1 E211 7 4/4 0.5/0.5 1/2 1/2 1/2 2/4 E224 8 1/1 2/4 0.5/1 0.5/1 1/1 0.5/0.5 Legend: 1 S. aureus, 2 B. cereus, 3 L. monocytogenes, 4 E. coli, 5 Salmonella enterica ser. Typhimurium, 6 E. cloacae, 7 Sodium benzoate, 8 Potassium metabisulfite. foods-12-00947-t002_Table 2 Table 2 Antifungal activity of plant extracts expressed as minimum inhibitory and minimum fungicidal concentration, MIC/MFC, respectively (mg/mL; mean +- SD, n = 3). Extraction Plant AF 1 AN 2 AV 3 PF 4 PVC 5 TV 6 Infusion Lemon balm 0.125/0.25 0.125/0.25 0.25/0.5 0.5/1 0.5/1 0.25/0.5 Spearmint 0.125/0.25 0.25/0.5 0.25/0.5 0.5/1 1/2 0.25/0.5 Sage 0.25/0.5 0.25/0.5 0.25/0.5 0.25/0.5 0.25/0.5 0.125/0.25 Decoction Lemon balm 0.25/0.5 >4/>4 0.25/0.5 0.5/1 0.25/0.5 0.125/0.25 Spearmint 0.25/0.5 >4/>4 0.25/0.5 0.5/1 0.25/0.5 0.25/0.5 Sage 0.25/0.5 0.5/1 0.5/1 0.5/1 0.5/1 0.25/0.5 Hydroethanolic extraction Lemon balm 0.5/1 0.5/1 0.25/0.5 0.25/0.5 0.25/0.5 0.25/0.5 Spearmint 0.25/0.5 0.25/0.5 0.25/0.5 0.25/0.5 0.25/0.5 0.125/0.25 Sage 0.5/1 0.5/1 0.25/0.5 0.25/0.5 0.125/0.25 0.125/0.25 E211 7 1/2 1/2 2/2 1/2 2/4 1/2 E224 8 1/1 1/1 1/1 0.5/0.5 1/1 0.5/0.5 Legend: 1 A. fumigatus, 2 A. niger, 3 A. versicolor, 4 P. funiculosum, 5 P. verrucosum var. cyclopium, 6 T. viride, 7 Sodium benzoate, 8 Potassium metabisulfite. foods-12-00947-t003_Table 3 Table 3 Antioxidant activity of plant extracts expressed as half-maximal inhibitory concentration (IC50, mg/mL) measured by the TBARS (mean +- SD, n = 9) and OxHLIA (mean +- SD, n = 3) essays. Essay Plant Infusion Decoction Hydroethanolic Extract TBARS 1 Lemon balm 125 +- 2.08 a 204 +- 2.66 b 206 +- 8.99 b Spearmint 255 +- 11.0 c 197 +- 5.68 a 295 +- 9.77 c Sage 235 +- 6.43 b 196 +- 5.04 a 132 +- 5.07 a OxHLIA 2 Dt = 60 min Lemon balm 61.4 +- 1.31 b 27.0 +- 0.43 b 13.5 +- 0.38 a Spearmint 83.5 +- 1.84 c 42.2 +- 0.62 c 12.5 +- 0.17 a Sage 21.9 +- 0.77 a 8.93 +- 0.44 a 23.9 +- 0.94 b OxHLIA 2 Dt = 120 min Lemon balm 95.5 +- 2.16 b 41.6 +- 0.63 b 27.4 +- 0.85 a Spearmint 120 +- 1.84 c 66.8 +- 0.92 c 27.6 +- 1.28 a Sage 38.4 +- 0.89 a 23.5 +- 0.67 a 56.4 +- 1.51 b Legend: 1 Thiobarbituric acid reactive substances, 2 Oxidative haemolysis inhibition essay. Trolox IC50 value: 5.4 +- 0.3 mg/mL (TBARS), 21.8 +- 0.25 mg/mL (OxHLIA Dt = 60 min), 43.5 +- 1.00 mg/mL (OxHLIA Dt = 120 min). For each essay, values with different superscript letters in a column mean significant differences (ANOVA, p < 0.05). foods-12-00947-t004_Table 4 Table 4 Anti-inflammatory activity of plant extracts expressed as half-maximal inhibitory concentration (IC50, mg/mL) measured by nitric oxide production inhibitory capacity (mean +- SD, n = 2). Plant Infusion Decoction Hydroethanolic Extract Lemon balm >400 b >400 b >400 b Spearmint 44.4 +- 0.66 a 43.9 +- 4.26 a 26.6 +- 1.65 a Sage >400 b >400 b >400 b Dexamethasone IC50 value: 6 +- 1 mg/mL. Values with different superscript letters in a column mean significant differences (ANOVA, p < 0.05). foods-12-00947-t005_Table 5 Table 5 Cytotoxic activity of plant extracts expressed as half-maximal cell growth inhibitory concentration (GI50, mg/mL) measured by the sulforhodamine B essay (mean +- SD, n = 3). Extraction Plant AGS 1 CaCo-2 2 HeLa 3 MCF-7 4 NCI-H460 5 hFOB 6 Infusion Lemon balm 215 +- 6.22 a 290 +- 0.19 b 249 +- 11.5 a 239 +- 0.99 b >400 >400 Spearmint 196 +- 7.44 a 304 +- 0.55 c 229 +- 21.2 a 203 +- 1.50 a >400 >400 Sage 249 +- 8.68 b 242 +- 0.40 a 248 +- 25.6 a 198 +- 0.97 a >400 >400 Decoction Lemon balm 255 +- 7.45 b >400 c 301 +- 10.9 b >400 >400 >400 Spearmint 258 +- 5.49 b 396 +- 0.05 b 289 +- 1.49 b >400 >400 >400 Sage 215 +- 6.25 a 269 +- 0.31 a 111 +- 2.14 a 320 +- 1.05 a >400 350 +- 4.25 a Hydroethanolic extract Lemon balm 231 +- 2.75 b 351 +- 3.30 c 266 +- 11.5 b 180 +- 4.43 a 369 +- 3.37 a 271 +- 2.52 a Spearmint 162 +- 8.05 a 285 +- 0.43 b 215 +- 2.21 a 210 +- 2.20 b 381 +- 0.63 b 264 +- 2.29 a Sage 361 +- 3.74 c 272 +- 0.06 a 257 +- 1.17 b 206 +- 2.34 b >400 c >400 b Legend: 1 Gastric adenocarcinoma, 2 Colorectal adenocarcinoma, 3 Cervical carcinoma, 4 Breast adenocarcinoma, 5 Large cell lung carcinoma, 6 non-tumour hFOB (human foetal osteoblasts). Ellipticine GI50 values: 1.23 +- 0.03 mg/mL (AGS), 1.21 +- 0.02 mg/mL (CaCo-2), 1.91 +- 0.12 mg/mL (HeLa), 1.02 +-0.02 mg/mL (MCF-7), 1.01 +- 0.01 mg/mL (NCI-H460) and 1.21 +- 0.08 mg/mL (hFOB). Values with different superscript letters in a column mean significant differences (ANOVA, 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. Mesias F.J. Martin A. Hernandez A. Consumers' growing appetite for natural foods: Perceptions towards the use of natural preservatives in fresh fruit Food Res. Int. 2021 150 110749 10.1016/j.foodres.2021.110749 34865767 2. Abiega-Franyutti P. Freyre-Fonseca V. 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PMC10000424 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050796 cells-12-00796 Review No Time to Die--How Islets Meet Their Demise in Transplantation Kale Atharva 12 Rogers Natasha M. 123* Perego Carla Academic Editor 1 Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Westmead, NSW 2145, Australia 2 Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia 3 Renal and Transplant Unit, Westmead Hospital, Westmead, NSW 2145, Australia * Correspondence: [email protected] 03 3 2023 3 2023 12 5 79603 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 ). Islet transplantation represents an effective treatment for patients with type 1 diabetes mellitus (T1DM) and severe hypoglycaemia unawareness, capable of circumventing impaired counterregulatory pathways that no longer provide protection against low blood glucose levels. The additional beneficial effect of normalizing metabolic glycaemic control is the minimisation of further complications related to T1DM and insulin administration. However, patients require allogeneic islets from up to three donors, and the long-term insulin independence is inferior to that achieved with solid organ (whole pancreas) transplantation. This is likely due to the fragility of islets caused by the isolation process, innate immune responses following portal infusion, allo-immune-mediated destruction and b-cell exhaustion following transplantation. This review covers the specific challenges related to islet vulnerability and dysfunction that affect long-term cell survival following transplantation. islet transplantation beta cells rejection IBMIR ER stress University of Sydney and Juvenile Diabetes Research FoundationNational Health and Medical Research CouncilDiabetes AustraliaGNT2007991 A.K. is supported by awards from the University of Sydney and Juvenile Diabetes Research Foundation. N.M.R. is supported by funding from the National Health and Medical Research Council (GNT2007991) and Diabetes Australia. pmc1. Introduction Diabetes mellitus (DM) is a developing global health emergency. Current estimates suggest that >500 million people worldwide are affected, with an increasing prevalence in middle-income countries. DM, regardless of aetiology, has a unique capacity to affect multiple organ systems that predispose to a substantially increased risk of cardiovascular disease, chronic kidney and liver diseases, malignancy and neurological impairment. The long-term economic burden that accompanies a diagnosis of DM and the development of complications create concerns about the cost and utilisation of healthcare resources over the duration of the disease. Type 1 DM (T1DM) is characterised by the autoimmune destruction of b-cells, although the notion of b-cell complicity in their own destruction due to limited responses to survive an inflammatory insult is touted as a competing hypothesis for disease development. Type 2 DM (T2DM) is caused by a combination of b-cell dysfunction and insulin resistance . The failure of insulin-sensitive tissues to respond appropriately to insulin leads to compensatory hyperinsulinemia, which facilitates b-cell dysfunction and death through exhaustion. Islet transplantation is an accepted treatment option for patients with T1DM --and not yet for patients with T2DM primarily due to a lack of sufficient donors--but despite the initial success in reducing hypoglycaemia unawareness, long-term allograft survival and insulin independence are limited due to an inexorable decline in b-cell number and function. The loss of critical islet mass is common in both type 1 and type 2 DM, as well as in islet transplantation. Our understanding of islet biology, particularly how these cells die in response to exogenous stressors, remains key to developing novel treatments that protect the endocrine pancreas and facilitate the survival of transplanted b-cells. 2. Mechanisms of Islet Cell Death in Islet Transplantation Insulin replacement has remained the standard management for patients with T1DM and for patients with late-stage T2DM. However, it is not able to provide complete physiological metabolic control. Allogeneic islet cell transplantation remains an effective treatment for patients with T1DM who have concurrent hypoglycaemia unawareness and metabolic instability . Hypoglycaemia can pass as unrecognised in a subset of patients with diabetes--this condition is known as hypoglycaemic unawareness--where the development of neuroglycopenia is not preceded by autonomic warning symptoms (e.g., tremors and sweating) due to a loss of sympathetic and adreno-medullary counterregulatory mechanisms, as well as a lack of a-cell responsiveness . The development of hypoglycaemia unawareness is associated with the duration of diabetes in the context of tight metabolic control. It is most commonly observed in patients with T1DM, affecting 30-40% of patients, compared to patients with insulin-dependent T2DM . Hypoglycaemic unawareness is associated with the development of severe hypoglycaemia leading to increased morbidity and mortality . Islet transplantation provides the replacement of b-cell (and potentially a-cell) function, and it has been shown to effectively reduce hypoglycaemia unawareness, improve quality of life and provide durable insulin independence . Islet transplantation also slows the macro-vascular complications that impact morbidity and mortality , as well as healthcare resource use, although the procedure is not necessarily cost-effective . The ability to apply this therapy to a broader range of patients with diabetes is also limited by donor pancreas availability. Patients typically require three separate transplantation procedures to maximise the efficacy and stability of islet cell mass. The majority of islets are thought to be lost in the immediate peri-transplant period following infusion and engraftment. This is typically followed by a second phase of cellular loss, where an inexorable decline in b-cell function can be mediated by auto-immune destruction, as well as by non-immunological functional impairment and destruction that resembles the failure of islets in T2DM . This results in long-term insulin independence rates of <30% . 3. Instant Blood Inflammatory Reaction (IBMIR) and Early Islet Demise Inflammation during the early stages of islet transplantation has been identified as one of the major reasons for poor long-term graft survival. Approximately 25% of transplanted islets are lost immediately as they come into contact with intraportal ABO-compatible whole blood, triggered by exposed tissue factor on the surface of the islets . Tissue factor interacts with factor VIIa to activate the extrinsic coagulation pathway. IBMIR is therefore characterised by coagulation, complement activation, the recruitment and infiltration of leukocytes and the production of proinflammatory cytokines/chemokines, all of which lead to the regulated necrosis of b-cells. Concurrent increases in thrombin-antithrombin levels and c-peptide are indicative of islet damage and cell lysis, although this can be mitigated by the use of heparin . Extra-hepatic transplantation sites have been considered alternative locations for islet deposition, as they eliminate the potential for IBMIR, and while they have been effective in small animal models, these have typically produced poorer clinical outcomes . The use of encapsulation technology as a cytoprotective mechanism has been extensively explored (well-reviewed in ) but has not been robustly translated to clinical practice. The study of IBMIR in vivo is difficult to recapitulate due to multiple interacting components; however, whole blood models of human allo-islet transplantation have been developed, and the early (<6 h) innate immune response has been well characterised. A recent study investigated IBMIR for up to 48 h , demonstrating ongoing thrombin-antithrombin complexes and platelet activation at 12 h post-transplantation. This was accompanied by increased expressions of chemokines, including interferon-inducible T-cell chemoattractant (the CXCR3 ligand), soluble CD40 ligand and monocyte chemoattractant protein-1 (the CCR2 ligand), and a massive infiltration of neutrophils and monocytes. Natural killer (NK) cells and macrophages also contribute to IBMIR. The liver--a typical site of b-cell deposition following intraportal infusion--and its substantial mononuclear cell population contain a large proportion of NK cells, which are highly cytotoxic compared to peripheral blood NK cells. NK cells are part of the innate immunity and mediate their cytotoxicity by secreting cytokines and via direct cell-to-cell contact. One of the dominant apoptotic pathways utilised by NK cells is the TNF-a-related apoptosis-inducing ligand (TRAIL) to TRAIL receptor pathway. It has been discovered that pancreatic b-cells express the TRAIL receptor. TRAIL-mediated islet destruction by NK cells was partially but significantly inhibited following the administration of anti-TRAIL mAb in mice. The inhibitory effect was more profound following the co-administration of anti-TRAIL mAb and concanamycin A, an inhibitor of perforin-mediated cytotoxicity . NK cells are traditionally believed to not differentiate into memory cells (cells that have the ability to remember a past encounter with a foreign antigen and stimulate an efficient and enhanced response when re-encountering the same antigen). This is a pathognomonic feature of both T cells and B cells in the adaptive immune system. There is now accumulating evidence that NK cells may possess memory-cell-like properties. NK cells specific to the liver in particular exhibit memory-like properties and responses and lack a classical NK marker DX5, the a2 integral chain CD49b. TNF-a induces the activation of cells through interactions with both TNF-a 1 and 2 receptors on cells. The blocking of TNF-a 1 and 2 receptors on cells with anti-TNF-a antibody treatment prior to transplantation protects islets from NK cell attack during IBMIR. The memory-like liver-resident cells significantly expand in number after primary syngeneic islet transplantation in mice and may target both the originally engrafted primary and secondary transplanted islets. Anti-TNF-a antibody treatment also significantly inhibited the expansion of cells and the prolonged CD69/TRAIL expression on liver NK cells after sequential islet transplantations . NF-kB inhibitors can mitigate the effects of IBMIR on human islets in vitro , partly due to their regulation of tissue factor expression. The overexpression of the integral membrane ectonucleotidase CD39 on islets enhances ATP degradation, and it has been shown to limit platelet activation and coagulation without effecting glucose metabolism . The use of complement inhibitors--a C5a inhibitory peptide in a rodent model and a complement inhibitor in a xenotransplant model --showed improved graft survival. Islets are particularly susceptible to damage mediated by the pro-inflammatory cytokines interleukin (IL)-1, interferon-g and tumour necrosis factor (TNF)a through NK-kB signalling, the activation of mitogen-activated protein kinases (MAPKs) and Fas-triggered apoptosis. Macrophage-mediated IL-1b secretion may represent the final common pathway for functional islet impairment and destruction through pro-inflammatory cytokine stimulation by enhancing inducible nitric oxide synthase activity and impairing glucose-stimulated insulin secretion . IL-1b gene expression was significantly upregulated in in vitro cultures of islets , which was exacerbated by serum deprivation and mitigated following incubation with an IL-1 receptor antagonist . Post-transplantation, IL-1b is detectable even in syngeneic grafts . The TNF decoy receptor etanercept has been shown to reduce inflammation and oxidative stress in islets . However, its incorporation into clinical practice proceeded with limited clinical data after being trialled in eight patients . The attractiveness of anti-inflammatory therapeutics to limit IBMIR has persisted, and drug repurposing studies using the IL-1 receptor antagonist anakinra demonstrated improved marginal mass islet engraftment by limiting apoptosis . The combined use of etanercept and anakinra (an IL-1 inhibitor) in allogeneic and autologous islet transplantation demonstrated both safety and tolerability , although larger clinical trials are required to show definitively improved clinical outcomes. CD47 is a universally expressed cell membrane receptor that ligates signal regulatory protein (SIRP), particularly the alpha domain, to monitor self (versus non-self) and oversee the don't-eat-me signal. The interaction of parenchymal cell CD47 with myeloid-based SIRPa places it as a checkpoint of innate, allogeneic and xenogeneic immunity. Enhanced CD47 expression correlates with improved solid organ engraftment. The generation of a chimeric CD47-SIRPa protein (containing binding and signal transduction domains) linked to streptavidin was able to limit the macrophage-based phagocytosis of biotinylated cells . Mouse islets engineered to express this protein were protected from the development of an IBMIR-type reaction in vitro and in vivo, facilitating engraftment and long-term syngeneic graft function. These findings were associated with decreased inflammatory cell infiltrates, particularly CD11b+Ly6Chi/CD11b+/Ly6Cint inflammatory monocytes and CD11bhiGr1hi neutrophils. 4. Alloimmunity and the Risk of Islet Transplant Failure Allogeneic islet transplantation requires immunosuppression to limit the rejection of islets, with the potential added benefit of suppressing autoimmunity. Patients with T1DM and a concurrent burden of autoimmune antibodies have a lower rate of islet transplant success due to the presence of memory CD4+ and CD8+ T cells that are rapidly reactivated to target islet antigens (IA-2, GAD-54 and ZnT8) and destroy b-cells . Despite their clear prognostic role in the development of T1DM , the association between autoantibodies and long-term islet allograft function has been difficult to demonstrate robustly due to small patient numbers. Indeed, patients with T1DM receiving adequate (calcineurin inhibitor and mammalian target of rapamycin inhibitor-based) immunosuppression following islet transplantation demonstrated lymphopenia and a concurrent chronic elevation of IL-7 and IL-15 that promoted T-cell turnover and the expansion of auto-antigen-specific T cells . Human islets bind complement proteins, particularly IgG, IgM, C1q and C3b/iC3b (18431241), leading to lysis and the release of c-peptide. This may be crucial in bridging innate (IBMIR-based) and allogeneic (HLA-based) immune responses in islet transplantation, as C3 can trigger rejection in pre-clinical models of solid organ transplantation and humans . The presence or the development of alloimmunity (to human leukocyte antigens, HLAs) and its effect on allograft survival is well-defined in the solid organ transplantation literature. Donor-specific antibodies (DSAs), pre-formed or de novo, are a leading cause of graft failure due to the development of antibody-mediated rejection in the kidney , heart and lung , which is associated with graft dysfunction and poorer long-term graft survival. The introduction of molecular typing and Luminex technology has facilitated our ability to precisely define HLAs, the presence (or absence) of antibodies and their (relative) abundance. The risk factors for developing de novo DSAs encompass inadequate immunosuppression (including nonadherence) and inflammation within the graft (rejection) or systemically (infection), which can incite graft immunogenicity and/or heterologous immunity . As many islet transplant patients receive grafts from two-three HLA mismatched donors, the presumed risk of allosensitisation is higher. DSAs binding to endothelial cells or islets (that constitutively express class I and aberrantly upregulate class II HLAs ) can activate the classic complement pathway. Even in the absence of complement, some DSAs can promote antibody-dependent cytotoxicity, and innate immune cells bind Fc fragments that trigger degranulation and the release of lytic enzymes from neutrophils and NK cells. C4d, the degradation product of the classical complement pathway, binds covalently to the endothelium and can be used as an immunological marker of antibody-mediated rejection. However, the breadth of islet dispersal throughout the liver parenchyma increases the risk-benefit ratio of a liver biopsy to provide histological assistance for the diagnosis of rejection. The association of DSAs with islet transplant failure is not as well characterised. It is not known whether the hepatic location of islets is relatively protective given the tolerogenic environment provided by the liver . The prevalence of pre-formed DSAs in islet transplant recipients has been shown to be similar to that of other solid organ transplant cohorts , with the suggestion that pre-existing IgM antibodies against HLA class II are associated with improved outcomes. De novo DSAs have been shown to be predictive of islet graft failure , particularly the development of class I HLAs , although this has been disputed . Indeed, allogeneic islets may be resistant to DSA-mediated rejection despite the susceptibility with direct binding in vitro, and this is directly due to the endothelial sequestration of DSAs in neo-vascularised islets. 5. Non-Immunological Causes of Islet Death The chronic attrition of islet allograft function over time, despite initial engraftment success, is multifactorial and contributed to by rejection, chronic fibrosis within a non-physiological environment and the drug-induced toxicity of immunosuppression. Both tacrolimus and sirolimus, which are part of standard immunosuppression protocols , have diabetogenic properties. Calcineurin inhibitors (tacrolimus and ciclosporin) act by limiting the dephosphorylation and translocation of the nuclear factor of activated T cells (NFATs). Calcineurin signalling is required for insulin secretion and b-cell proliferation , and the specific inactivation of calcineurin in b-cells is associated with hyperglycaemia with increasing age . Tacrolimus has been shown to increase blood glucose and reduce the homeostasis model assessment of b-cell function (HOMA-b) and the insulin sensitivity index in animals with intact native endocrine pancreatic function , following transplantation with human islets and following solid organ transplantation . The effects of short-term tacrolimus exposure promoting hyperglycaemia and compensatory hyperinsulinemia transition to the pseudo-normalisation of insulin, indicative of the loss of insulin secretory capacity, with evidence of b-cell death . Islet apoptosis associated with calcineurin inhibition is also thought to occur by limiting the cAMP response element binding protein (CREB) , which decreases IRS-2 expression, limits the phosphorylation of Akt and impacts insulin secretion . CNIs also reduce the cell surface expression of GLUT4 and decrease insulin-stimulated glucose uptake in adipocytes , which potentially contributes to peripheral insulin resistance. Tacrolimus promotes a decrease in mitochondrial Ca2+ uptake, which has been shown to impair respiration and ATP production, leading to compromised glucose-stimulated insulin secretion (GSIS) . CNIs, tacrolimus in particular, potentiate the deleterious effect of glucolipotoxicity on b-cells, inducing nuclear FoxO1 expression (which, in turn, limits proliferation ) and reducing insulin content and secretion . The incidence of post-transplant diabetes mellitus in solid organ transplantation is the highest in tacrolimus-treated recipients . However, mTOR inhibitors are not innocuous in terms of diabetogenic capacity, although much of the literature derives from clinical studies in solid organ (kidney transplant) recipients. An analysis of >20,000 patients in USRDS revealed that kidney transplant recipients without DM receiving sirolimus as part of their immunosuppression regimen were most likely to have Medicare billing for post-transplant DM , and the highest HR associated with post-transplant DM was sirolimus and calcineurin inhibitors combined. Tacrolimus and sirolimus both induce reversible graft dysfunction, characterised by amyloid deposition and macrophage infiltration in transplanted islets , but without evidence of frank b-cell death. An ultrastructural examination of grafts demonstrated decreased insulin granules, and an accompanying genomic analysis revealed transcripts associated with extracellular matrix deposition and inflammation. Insulin signalling and b-cell proliferation/survival require intact mammalian target of rapamycin (mTOR), particularly mTORC1 function, which occurs via the insulin receptor substrate 1-Akt-mTOR pathway, where the final step is the phosphorylation of p70 ribosomal protein S6 kinase. In rodent studies, the administration of sirolimus worsened hyperglycaemia, abolished the hyperinsulinemic response and decreased muscle insulin sensitivity in diabetic animals . The latter effect is mediated by glycogen synthase 3b activity , and further work has demonstrated that the sirolimus-based dephosphorylation of Yin Yang 1 in skeletal muscle limits insulin signalling . Sirolimus has been shown to cause islet death and impair proliferative cell recovery . mTORC2 is required for the insulin-mediated suppression of hepatic gluconeogenesis , which is disrupted by sirolimus at higher doses. Not all studies concur with sirolimus impacting insulin action and glucose homeostasis, and this may be related to overall drug exposure at concentrations that affect both mTORC1 and 2. Immune cell infiltration and amyloid deposition have both been described in liver biopsy results following intraportal transplantation, but these correlate poorly with clinical phenotype. The transplantation of islets from islet amyloid polypeptide (IAPP)-expressing transgenic mice demonstrated early amyloid deposition post-transplantation, reduced b-cell volume and graft failure. This was thought to be due to apoptosis and a concurrent reduction in b-cell replication , and both phenomena have been observed in vitro in response to amyloid fibrils. Although IAPP is secreted by b-cells, the human form can aggregate to form cytotoxic fibrils . Interestingly, heparin, which is used to reduce the cyto-destructive effect of IBMIR on islets, promotes the fibrillogenesis of human IAPP, and it has been shown to simultaneously promote amyloid deposition and decrease b-cell apoptosis. Heparinase treatment significantly reduced amyloid deposition and subsequent b-cell cytotoxicity . 6. The Importance of Islet-Endothelial Crosstalk Islets are three-dimensional structures, occupying only 2% of the total pancreatic volume but intrinsically linked to abundant vasculature. The islet vascular network comprises 7-8% of the total islet volume and, overall, receives approximately 10x more blood than the surrounding exocrine pancreas . Intact, this capillary system is critical for islet survival and function, and it is central to the secretion of insulin into the circulation for subsequent systemic distribution. Intra-islet endothelial cells (EC) are highly fenestrated. Islet-EC crosstalk provides a number of paracrine effects that promote angiogenesis and b-cell survival, including vascular endothelial growth factor , angiopoietins , ephrins and insulin . The basement membrane also provides a barrier function, structural support and signalling moieties for cellular integrity. The process of islet isolation for transplantation strips b-cells of their vascular infrastructure, and islets are therefore devoid of endothelial cells to support neoangiogenesis, an absolute requirement for engraftment. The basement membrane is also lost during isolation, particularly laminin and collagen , and matrix detachment promotes apoptosis . The recovery of structure and function is seen in syngeneic mouse models of islet transplantation, and this is incomplete in allotransplantation . Islets make little matrix and are dependent on endothelial cell recruitment (donor and recipient) for basement membrane repair. Islets are clusters of approximately 2000 b-cells. Due to the loss of blood flow, the availability of oxygen and nutrients becomes diffusion-dependent, and isolated islets are hypothesised to become hypoxic typically at the central core; however, formal quantitation is difficult. Previous studies have suggested that smaller islets produce superior outcomes as a surrogate marker of islet survival. Studies have shown that approximately 70% of transplanted islets remain hypoxic 1 month post-transplantation . However, the exposure of isolated islets to hyperoxic conditions paradoxically worsens the damage of cells residing on the periphery, despite a reduction in central necrosis . The liver is currently considered to be the most suitable site for islet transplantation because, compared to other vascularised beds, such as the spleen and kidney, it is easily accessible with minimal invasion and is (potentially) the least immunogenic. The liver provides a significantly lower oxygen tension (5-10 mmHg) than native pancreatic tissue (30-40 mmHg); however, it allows for a better dispersal of oxygen and nutrients from hepatic sinusoids to transplanted islets. The root of the cause of low revascularisation and oxygen deficiencies in transplanted islets may be intrinsic, as transplanted islets have been reported to have low nitric oxide production, which is essential for regulating vascular tone and blood flow, as well as mitochondrial oxygen consumption. Furthermore, the physiological route of secreted insulin from the pancreas is first directed to the liver via the hepatic portal vein, where it is first consumed before being dispersed to adipose tissue and skeletal muscles . b-cells require large amounts of oxygen to meet mitochondrial respiration demands and to facilitate efficient insulin secretion. Hypoxic stress is a contributing factor to cellular dysfunction, islet death during isolation and low islet survival post-transplantation. High numbers of islets are therefore required at transplantation to compensate for cell death and loss. Hypoxia activates the HIF-1a cascade in islets following initial procurement and isolation. HIF-1a accumulates in islet grafts , which presumably drives an adaptive response to hypoxia, inducing the expression of pro-angiogenic factors, such as VEGF, AngptI4, Pgf and Anxa2, as well as downstream effectors that initiate angiogenesis . The protective effect of HIF-1a was shown by a poorer survival of transplanted null islets; iron chelation using desferrioxamine increased HIF-1a expression (as well as concurrent ATP content and glucose oxidation) leading to improved islet transplant outcomes . HIF-1a also drives impaired glucose-stimulated insulin secretion and apoptosis , an effect mediated by metabolic switching to glycolysis and reduced ATP generation . This has been confirmed in microarray analyses of human isolated islets, where a range of upregulated hypoxia-response genes were identified . The transplantation of hypoxic islets demonstrated a defect in (but not the absence of) b-cell function, which was a consequence of stabilised HIF-1a. HIF-1a activation also initiates apoptosis and mitochondrial caspase-mediated cell death pathways , a loss of glucose-stimulated insulin secretion and pro-inflammatory cytokine activation and release, followed by the structural defragmentation of islets. This is exacerbated by significant delays in revascularisation post-transplantation. The mechanisms of hypoxia-induced b-cell death and dysfunction have been widely investigated, and they are key to facilitating post-transplantation survival. Pancreatic b-cells exposed to acute hypoxia induce caspase-3-mediated apoptosis and endoplasmic reticulum (ER) stress . Recent studies have alluded to ER stress as a causal factor in b-cell dysfunction and islet transplant failure . b-cells are highly metabolic and have a highly developed ER involved in post-translational modification and the assembly and folding of newly synthesised proteins (e.g., insulin in b-cells). An overload of protein production in cells can lead to ER stress. A clinical feature of islet allograft failure (as well as T2DM) is the overproduction of insulin to meet high demands in the context of significant b-cell loss. Insulin overproduction results in protein misfolding and the induction of ER stress through the activation of the C/EBP homologous protein (CHOP), X-box binding protein 1 (XBP-1) and immunoglobulin heavy chain (BIP). To re-establish cellular homeostasis, the adaptive unfolded protein response (UPR) is triggered via three main sensors: activating transcription factor (ATF) 6, double-stranded RNA-dependent protein kinase (PKR)-like ER kinase (PERK) and inositol requiring kinase 1 (IRE1). The UPR responds to ER stress by inducing the upregulation of genes encoding ER chaperone proteins to mitigate protein aggregation and accumulation and to initiate the proteasomal degradation of misfolded proteins. However, in the context of chronic ER stress, the cytoprotective role of the UPR fails, and apoptotic pathways are initiated to induce cell death. The ER stress marker CHOP is also a pro-apoptotic transcription factor. In response to acute hypoxia, CHOP is upregulated in b-cells. Upon the silencing of CHOP, hypoxia-induced apoptosis is prevented . In addition to environmental hypoxia, intracellular hypoxia is also present in isolated islets. Despite culturing islets in normoxic conditions following isolation, intracellular hypoxia remains. Studies have found that HIF-1a remains overexpressed in isolated islets and that CHOP is upregulated within 4 h of isolation, suggesting early apoptosis. Hypoxia-mediated apoptosis is also implicated in the pathogenesis of T2DM, as pancreatic islets obtained from various murine models (including db/db, ob/ob and kky mice) were discovered to be significantly hypoxic and overexpressed ER stress markers compared to non-diabetic counterparts . Chronic hyperglycaemia, which is a clinical feature of both DM and islet allograft failure, damages islets further by triggering b-cell de-differentiation, ER-stress and a loss of function. This phenomenon is known as glucotoxicity. The hyperglycaemic environment in diabetic islet transplant recipients has been implicated in the early loss of transplanted islets. The elimination of glucocorticoids from the immunosuppressive regimen was a significant contributing factor to the success of the Edmonton protocol . One study recently investigated the effects of in vivo chronic hyperglycaemia on ER stress and UPR gene expression in transplanted mouse islets . Diabetic recipients receiving a suboptimal islet transplant that failed to restore euglycemia demonstrated a significant reduction in UPR gene expression, including PERK and IRE1/ATF6, in transplanted islets compared to non-diabetic mice receiving the same b-cell mass. The recovery of adaptive UPR gene expression was observed in diabetic mice transplanted with a sufficient islet mass that established normoglycaemia. Glucotoxicity is also known to exacerbate other stressors within the graft environment, including inflammation, oxidative stress, hypoxia and impaired vascularisation. Hypoxia decreases ER-to-Golgi protein trafficking and induces cell death by inhibiting the adaptive UPR . Hypoxia mediates these responses independent of HIF-1a activation via several effectors of ER stress, including CHOP, DNA-damage inducible transcript 3 (DDIT3) and c-Jun N-terminal kinase (JNK). Islets isolated from diabetic mice have decreased expressions of adaptive UPR genes, such as Hspa5, spliced Xbp1 and Fkbp11. The overexpression of Hspa5 was found to protect islet b-cells from hypoxia-induced cell death. The silencing of CHOP or JNK also restored UPR gene expression and protein trafficking, providing protection against apoptosis induced by hypoxia . 7. Future Directions in Islet Transplantation Emerging strategies to overcome the current limitations of islet transplantation and to improve their success include the encapsulation of islets, the co-transplantation of islets with endothelial cells, stem cell sources for islet transplantation, genetic manipulation and immunosuppression strategies. To mitigate the effects of IBMIR, extrahepatic locations, including the kidney capsule, the spleen, the omental pouch and subcutaneous sites, have been explored in pre-clinical and human studies. The subcutaneous site is minimally invasive and easily accessible; however, the main limitation is poor vascularisation . Multiple strategies have been developed to counteract this problem and improve the outcomes of transplanted islet survival, including the bioengineering of functional cell sheets using bone-marrow-derived mesenchymal stem cells (MSCs) . MSCs are a source of pro-angiogenic and anti-apoptotic cytokines, including VEGF, HGF, IL-6 and TGFb1. TGFb1 triggers the production of heat shock protein 32 (HSP32) and X-linked inhibitor of apoptosis protein (XIAP), which protect islets by supressing oxidative stress , inflammation and b-cell apoptosis . MSCs can also differentiate into endothelial cells to facilitate peri-islet vascularisation. When engineered into cell sheets, they provided an ideal substrate for human islets and the extracellular matrix that improved islet function and survival . The co-transplantation of islets with adipose-derived mesenchymal stem cell sheets into the subcutaneous site normalised blood glucose levels in diabetic pig recipients . Human dermal fibroblasts have also been studied in vitro as an alternative source to bone-marrow-derived MSCs, as they can be easily harvested from the skin and are highly proliferative. Fibroblasts are also a source of pro-angiogenic factors, such as VEGF and fibroblast growth factor, both of which can improve vascularisation and islet viability post-transplantation. Furthermore, when engineered into cell sheets, fibroblasts maintain the natural structural integrity of islets while also improving their function and survival in vitro . Overcoming insufficient revascularisation to facilitate islet engraftment has been a substantial challenge clinically. The increasing evidence of molecular crosstalk between intra-islet endothelial cells and b-cells suggests that the co-transplantation of these cells may be advantageous. In addition to their contribution to angiogenesis, intra-islet endothelial cells produce various endocrine factors, including thrombospondins, hepatocyte growth factors, collagen and laminins, which promote b-cell survival and improve insulin secretion. Similarly, intra-islet endothelial cells benefit from proliferative factors secreted by b-cells, including ephrins, VEGF, angiopoietins and insulin. Bone-marrow-derived endothelial progenitor cells co-transplanted with islets in diabetic mice have shown promising results in restoring euglycemia through rapid revascularisation . This was also associated with a strong downregulation of PECAM-1, which is involved in mediating inflammatory responses by promoting the trans-endothelial migration of monocytes, NK cells and neutrophils . Alternative vascularisation units, such as adipose-tissue-derived microvascular fragments (MVFs), may be more efficient at reassembling into microvessels in the initial post-islet-transplantation phase . MVFs are also composed of substantial numbers of mesenchymal stem cells, which are known to secrete angiogenic factors and reduce inflammation, thereby protecting islets from hypoxia-induced death. In pre-clinical studies, MVFs co-transplanted with islets under the kidney capsule, as well as the subcutaneous space, were found to improve islet engraftment and restore normoglycaemia in recipients with diabetes . Plasma insulin levels post-transplantation were similar to non-diabetic healthy controls, which was accompanied by enhanced angiogenesis in the grafts. Engineered vascularised organoids have also been shown to re-assemble into larger interconnected channels for perfusion , which has been applied to islet transplantation for integration with recipient vasculature . To bypass immune attack following islet transplantation, transplanted islets can be encapsulated in biomaterials (well-reviewed in ), including alginate, a polysaccharide derived from seaweed with hydrophilic and biocompatible properties. However, foreign-body responses and fibrotic overgrowth have limited long-term islet viability and graft function . Chemical modifications or the addition of anti-TNFa to capsules can improve viability. Cell subsets of myeloid, mesenchymal and T cell lineage have the capacity to regulate immune responses and show po-tential as adjuvant immunosuppressive agents in pre-clinical and clinical studies . The intrahepatic infusion of autologous bone-marrow-derived mesenchymal stem cells co-transplanted with islets improved glycaemic control, islet engraftment and quality of life in patients with total pancreatectomy . However, there are no current clinical trials investigating cell therapy in allogeneic islet transplantation. 8. Conclusions Islet transplantation is an effective treatment that reduces severe hypoglycaemia, re-establishes hypoglycaemia awareness, stabilises glycaemic control and can provide insulin independence. Its long-term benefits also include reduced morbidity from microvascular complications, particularly retinopathy and nephrotoxicity . The benefits of islet transplantation are balanced by the need for immunosuppression--and the concordant risks of malignancy, infection and cardiovascular disease that manifest with long-term exposure to immunomodulatory agents--and the relatively ephemeral duration of successful islet transplantation (only 40% of patients achieve long-term insulin independence). The failure to meet graft survival outcomes similar to those of solid organ transplantation may be due to the susceptibility of b-cells to demise. This effect is multifactorial, but the development of strategies to improve b-cell durability or to reverse the adverse changes that are initiated by the islet isolation process will improve the success and duration of islet transplantation. The use of alternative sources of islets--xenotransplantation or stem-cell-derived sources--may help to reverse the current imbalance between supply and demand, but much remains unknown regarding their immunogenicity and physiological function. Further refinements in immunosuppressive drug regimens are also required to limit the harmful effects on both b-cells and remote organs. Author Contributions A.K. and N.M.R. wrote the original and revised manuscript. A.K. designed the figure. 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 Mechanisms of beta cell destruction following islet transplantation. 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. Roep B.O. Thomaidou S. van Tienhoven R. Zaldumbide A. Type 1 diabetes mellitus as a disease of the beta-cell (do not blame the immune system?) Nat. Rev. Endocrinol. 2021 17 150 161 10.1038/s41574-020-00443-4 33293704 2. Galicia-Garcia U. Benito-Vicente A. Jebari S. Larrea-Sebal A. Siddiqi H. Uribe K.B. Ostolaza H. Martin C. Pathophysiology of Type 2 Diabetes Mellitus Int. J. Mol. Sci. 2020 21 6275 10.3390/ijms21176275 32872570 3. O'Connell P.J. Holmes-Walker D.J. 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PMC10000425 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051073 foods-12-01073 Article Blackcurrant Alleviates Dextran Sulfate Sodium (DSS)-Induced Colitis in Mice Moon Hye-Jung Methodology Validation Formal analysis Investigation Data curation Writing - original draft Writing - review & editing Visualization 1 Cha Youn-Soo Methodology Validation Formal analysis Resources Writing - review & editing Supervision 12 Kim Kyung-Ah Conceptualization Methodology Validation Formal analysis Investigation Resources Data curation Writing - review & editing Supervision Project administration Funding acquisition 3* Tocmo Restituto Academic Editor Huang Dejian Academic Editor 1 Department of Food Science and Human Nutrition, Jeonbuk National University, Jeonju 54896, Republic of Korea 2 K-Food Research Center, Jeonbuk National University, Jeonju 54896, Republic of Korea 3 Department of Food and Nutrition, Chungnam National University, Daejeon 34134, Republic of Korea * Correspondence: [email protected]; Tel.: +82-42-821-6832 02 3 2023 3 2023 12 5 107302 2 2023 24 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 ). Previous studies have reported that anthocyanin (ACN)-rich materials have beneficial effects on ulcerative colitis (UC). Blackcurrant (BC) has been known as one of the foods rich in ACN, while studies demonstrating its effect on UC are rare. This study attempted to investigate the protective effects of whole BC in mice with colitis using dextran sulfate sodium (DSS). Mice were orally given whole BC powder at a dose of 150 mg daily for four weeks, and colitis was induced by drinking 3% DSS for six days. Whole BC relieved symptoms of colitis and pathological changes in the colon. The overproduction of pro-inflammatory cytokines such as IL-1b, TNF-a, and IL-6 in serum and colon tissues was also reduced by whole BC. In addition, whole BC significantly lowered the levels of mRNA and protein of downstream targets in the NF-kB signaling pathway. Furthermore, BC administration increased the expression of genes related to barrier function: ZO-1, occludin, and mucin. Moreover, the whole BC modulated the relative abundance of gut microbiota altered with DSS. Therefore, the whole BC has demonstrated the potential to prevent colitis through attenuation of the inflammatory response and regulation of the gut microbial composition. blackcurrant whole foods ulcerative colitis anti-inflammation tight junction proteins gut microbiota National Research Foundation of Korea (NRF)2020R1F1A1058098 This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Education) (NRF-2020R1F1A1058098). pmc1. Introduction Inflammatory bowel disease (IBD) refers to a chronic inflammatory condition of the intestinal tract that increases health and economic burdens due to an increase in global prevalence and lowers the quality of life . Ulcerative colitis (UC), one of the typical IBDs, appears only in the colon and is marked by supercritical mucosal inflammation . A cross-sectional study of 15 countries in Asia and the Middle East reported that UC is twice as prevalent as Crohn's disease and occurs more frequently in men in their 30s . In addition, it is essential to treat UC because it can develop into colorectal cancer if it persists for a long time . UC is characterized by diarrhea, bloody stools, urgency, increased frequency of defecation, and, in severe cases, fever and weight loss . It is estimated that UC is caused by the disruption of intestinal homeostasis due to genetic, microbiological, immunological, and environmental factors including diet, smoking, and stress . Drugs such as 5-aminosalicylic acid (5-ASA), biological drugs (anti-tumor necrosis factor-a (anti-TNF-a) and anti-adhesion molecule inhibitors), immunosuppressants, and corticosteroids have been used to treat UC . However, it has been reported that the remission rate of UC is only 15% to 44.9%, and adverse events such as infection, UC flare, nasopharyngitis, myelosuppression, liver toxicity, and malignancy occur . Therefore, to develop other safe and effective treatments, natural products using polyphenols such as apigenin and curcumin, and polysaccharides such as Scutellaria baicalensis Georgi, are being studied . Anthocyanins (ACN), belonging to the flavonoid subgroup of polyphenols, are found in flowers, vegetables, and fruits and are water-soluble pigments in red, blue, and purple . Various health benefits of ACNs have been discovered, in particular, ACN supplements have been shown to improve gut health by modifying the gut microflora and enhancing the intestinal barrier, thereby reducing the potential risk of inflammation . ACN-rich foods include berries (blackcurrants, blueberries, and raspberries) and dark red vegetables (red cabbage, eggplant, and purple wheat), among which blackcurrants have been reported to have a higher total ACN content than blueberries . Blackcurrant (BC) has been suggested to possess various health effects, including prevention of obesity, improvement of cognitive impairment due to aging, and reduction of diabetes-related cardiovascular dysfunction . Recently, ACN dietary supplements consisting of BC and bilberry extracts have shown anti-inflammatory effects in intestinal epithelial cells . Additionally, silver nanoparticles based on BC extracts were observed to restore inflammation of induced colitis in mice . However, these studies are insufficient to confirm the effect of BC on improving intestinal inflammation. Furthermore, most of these studies have verified the physiological activity of BC extracts, and studies on BC in its whole form are rare. Therefore, the aim of this study was to investigate whether the intake of whole BC in mice alleviates dextran sulfate sodium (DSS)-induced colitis. 2. Materials and Methods 2.1. Materials and Reagents The commercial freeze-dried powder of whole BC was obtained from Sujon Berries (Nelson, New Zealand). According to Willems et al. (2017), 1 g of Sujon's BC powder contained 23.1 mg of anthocyanin, 0.9 g of carbohydrates, and 8.2 mg of vitamin C . DSS was bought from MP Biochemical (MW: 36-50 kDa; Solon, OH, USA). A TNF-a enzyme-linked immunosorbent assay (ELISA) kit was bought from Invitrogen (Vienna, Austria), and interleukin (IL)-1b and IL-6 ELISA kits were purchased from R&D Systems (Minneapolis, MN, USA). The RNAiso Plus kit, PrimeScript RT Master Mix, and bicinchoninic acid (BCA) protein assay kits were purchased from Takara Bio, Inc. (Shiga, Japan). RIPA buffer was procured from Thermo Scientific Inc. (Rockford, IL, USA). Primary antibodies including phosphorylated-p65 (p-p65), p65, inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and b-actin were purchased from Cell Signaling Technology (Danvers, MA, USA). 2.2. Animals The animal experiment was approved by the Animal Ethics Committee of Chungnam National University (IACUC approval number: 202112-CNU-214). Five-week-old male C57BL/6J mice were acquired from Central Lab Animal, Inc. (Seoul, Republic of Korea). The experimental design is illustrated in Figure S1. The mice were housed under the same conditions (temperature of 22 +- 2 degC, relative humidity of 50 +- 5%, and 12 h/12 h light/dark cycles) and acclimatized for six days. After the adaptation period, 24 mice were separated into three groups (n = 8 per group): Vehicle group, normal control group not treated with DSS; DSS group, DSS-treated control group; DSS + BC group, DSS and blackcurrant treatment group. In the DSS + BC group, BC powder diluted in phosphate-buffered saline (PBS) was orally administered at a dose of 150 mg/mice per day throughout the experimental period. The PBS dosage given to the Vehicle and DSS groups was the same as that given to the DSS + BC group. To induce colitis in the DSS group and the DSS + BC groups, 3% DSS (w/v) in drinking water was given for six days from the 21st day of the experiment. One day before the experiment's termination, DSS was replaced with normal water. Symptoms of colitis were monitored daily using the DAI (disease activity index) while DSS was administered. The DAI, which was slightly modified from what Peng et al. (2019) described, was measured as scores for body weight loss (0, none; 1, 1-5%; 2, 5-10%; 3, >10%), stool consistency (0, normal; 1, slightly loose feces; 2, loose feces; 3, watery diarrhea), and bloody stools (0, none; 1, slightly bloody; 2, bloody; 3, gross bleeding) . Feces were collected the day before the sacrifice. Mice were euthanized after fasting for 12 h. The blood and colon tissues were obtained after the experiment was completed. Blood was centrifuged at 1100 g for 15 min to obtain the serum. After measuring the length and weight of colonic tissue samples, some were fixed in 4% formalin for histological assessment. The remaining colon tissues were immediately frozen in liquid nitrogen and kept at -80 degC until the experiment. 2.3. Histologic Analysis Hematoxylin and eosin (H&E) staining was accomplished on 4 mm thick sections of colon tissues fixed in 4% formalin. Colon slides were examined using a light microscope (DM2500, Leica Microsystems, Wetzlar, Germany) installed at the Center for University-wide Research Facilities (CURF) at Jeonbuk National University (Jeonju, Republic of Korea). Histological damage to the colon tissue was evaluated by the scores of epithelium loss (0-3), crypt damage (0-3), depletion of goblet cells (0-3), and infiltration of inflammatory cells (0-3) . 2.4. Measurement of Inflammatory Cytokine Levels Colon tissue was homogenized with lysis buffer, and the supernatant was separated. ELISA kits were used to quantify inflammatory cytokines (TNF-a, IL-1b, and IL-6) contained in the separated supernatant and serum, according to the manufacturer's procedure. 2.5. Quantitative Real-Time PCR (qRT-PCR) Analysis qRT-PCR analysis was performed with reference to Song et al. (2021) and the instructions of the manufacturer of the reagent . Following the manufacturer's directions for the RNAiso Plus kit (Takara Bio, Inc.), total RNA was extracted from the colon tissue. cDNA was synthesized from total RNA using PrimeScript RT Master Mix (Takara Bio, Inc.). The TOPrealTM SYBR green qPCR Premix (Enzynomics, Daejeon, Republic of Korea) and a 7500 real-time PCR system (Applied Biosystems, Foster City, CA, USA) were used to carry out the qRT-PCR. The relative expression of the target gene was determined using the 2 -DDCt method and normalized to that of the internal reference GAPDH. 2.6. Western Blotting Western blotting was carried out by referring to the experimental method of Jang et al. (2019) . Total protein lysates were extracted by homogenizing the colon tissue in a radioimmunoprecipitation assay (RIPA) buffer containing protease and phosphatase inhibitors. The protein content of the supernatant obtained by centrifugation of the extract was quantified using a BCA assay kit. Loading buffer was added to the supernatant and inactivated at 95 degC for 10 min. Protein samples were electrophoresed on SDS-polyacrylamide gels and then transferred to polyvinylidene difluoride (PVDF) membranes. After blocking the membrane with 5% skim milk, the antibody diluted to an appropriate concentration was applied for 24 h at 4 degC. After washing the membrane with tris-buffered saline with 0.1% tween 20 (TBST), the secondary antibody was added, and the protein was identified using enhanced chemiluminescence (ECL) solution and the ChemiDoc system (ATTO LuminoGraph II, ATTO, Tokyo, Japan). The bands of the target proteins were quantified using Image J software (US National Institutes of Health, Bethesda, MD, USA) and normalized to b-actin. 2.7. Gut Microbial Community Analysis Song et al. (2021) and Jang et al. (2019) were referred to for fecal collection and gut microbiota analysis . The day after the DSS drinking was completed, feces were collected and stored at -80 degC in order to analyze the gut microbial community. The microbial community of the collected feces was analyzed by Macrogen Inc. (Seoul, Republic of Korea). In summary, a library for 16S metagenomic sequencing was prepared by amplifying the V3-V4 region of 16S rRNA using the Hercules kit on the Illumina platform to construct a library of DNA extracted from fecal samples. The sequencing results were analyzed using the QIIME2 program, and taxonomic information classification was confirmed using the BLAST program of the NCBI 16S database. 2.8. Statistical Analysis Data were shown as the mean +- standard deviation (SD). Statistical analysis was performed using SPSS 18.0 software (SPSS Inc., Chicago, IL, USA). The significance of differences among groups was assessed using a one-way analysis of variance (ANOVA) by Duncan's post hoc tests at p < 0.05. 3. Results 3.1. Effects of Blackcurrant on Clinical Symptoms and Colon Damage in DSS-Induced Colitis UC symptoms of colitis were identified as changes in body weight, disease activity index (DAI), colon length, and weight per length of the colon . There was no significant difference in the change in body weight before DSS administration, but from the 6th day after DSS administration, both the DSS and DSS + BC groups were significantly reduced compared with the Vehicle control group . Changes in DAI were checked daily during the DSS drinking period . The DSS group showed a significantly higher DAI than the Vehicle group from the 22nd day. In contrast, the DSS + BC group showed significantly lower values than the DSS group until the 25th day. The DSS + BC group also showed an improved DAI on the final day of the experiment. The colon length was 4.73 +- 0.66 cm in the UC-induced DSS group, which was significantly shorter by about 29.9% compared with 6.75 +- 0.33 cm in the Vehicle group . In the DSS + BC group, colon length was 5.70 +- 0.42 cm, and a DSS-related decrease in colon length was significantly restored. In addition, the DSS + BC group showed a significantly reduced colon weight-to-length ratio. 3.2. Effects of Blackcurrant on Histological Changes in the Colon Tissue in DSS-Induced Colitis Sections of the colonic tissue were stained with H&E and histopathological scores were given to confirm the extent of damage . The Vehicle group had no damage or inflammatory response to the mucosa, submucosa, crypt structure, or goblet cells in the colon. However, severe epithelial erosion, deficiency of goblet cells, destruction of the crypt structure, and infiltration of many inflammatory cells into the mucosa and submucosa were observed in DSS-treated mice. Supplementation with blackcurrant alleviated damage to the mucosal layer of colonic tissue and infiltration of inflammatory cells caused by DSS, and significantly reduced the histological damage score. 3.3. Effects of Blackcurrant on the Levels of Pro-inflammatory Cytokines in the Serum and Colon Tissue in DSS-Induced Colitis The levels of proinflammatory cytokines in the serum and colon are shown in Table 1. The DSS group showed significantly higher levels of serum TNF-a and interleukin (IL)-6 than the Vehicle group. The DSS + BC group showed significantly attenuated levels of serum TNF-a, which were elevated by DSS. In colon tissue, the levels of TNF-a and IL-1b in the DSS group were increased significantly compared with the Vehicle group. However, the levels of TNF-a and IL-1b increased by DSS treatment were significantly reduced in the DSS + BC. 3.4. Effects of Blackcurrant on the Nuclear Factor-Kappa-Light-Chain-Enhancer of Activated B cells (NF-kB) Signaling Pathway, Tight Junction (TJ) Proteins, and Mucin in DSS-Induced Colitis We investigated whether BC affects the expression of genes and proteins related to the NF-kB signaling pathway, mucin, and TJ proteins . The DSS group upregulated the genes of toll-like receptor-4 (TLR-4) and nuclear factor-kappa-light-chain-enhancer of activated B cells (NF-kB) related to the NF-kB signaling pathway compared with the Vehicle group . Furthermore, an increase in the expression of iNOS, COX-2, pro-inflammatory cytokines (TNF-a, IL-1b, IL-6), and monocyte chemoattractant protein-1 (MCP-1), which are downstream genes of NF-kB, was observed in the DSS group. However, the expression levels of these excessive mRNAs were inhibited in the DSS + BC group, with a value similar to those of the Vehicle group. Next, the effects of BC on the expression of genes encoding TJ proteins and mucin involved in barrier function were evaluated . The DSS group significantly downregulated expression of all genes associated with TJ proteins and mucin compared with the Vehicle group. In contrast, the DSS + BC group showed higher expression of all such genes than the DSS group. The expression of proteins related to the NF-kB signaling pathway, an inflammatory response pathway, was also examined . As a result, it was found that the phosphorylation of NF-kB p65 (p-p65) and the protein expression of its downstream enzymes, iNOS and COX-2, were significantly increased in the DSS group compared with the Vehicle group. However, the DSS + BC group was revealed to inhibit the overexpression of p-p65, iNOS, and COX-2 increased by DSS. That is, it was shown that the administration of BC decreased the inflammatory response by inhibiting the NF-kB signaling pathway activated by DSS in the colon. 3.5. Effects of Blackcurrant on Modulation of the Gut Microbiome in DSS-Induced Colitis The influence of BC on the diversity and relative abundance of the gut microbiome was analyzed . To confirm the a-diversity of the gut microbiota, the observed amplicon sequence variant (ASV), an index of evenness, and Chao1, an index of richness, were evaluated. There was no significant difference between all groups, but the a-diversity of the DSS + BC group tended to increase slightly compared with the DSS group (ASV; Vehicle, 116.00 +- 32.33; DSS, 106.80 +- 9.36; DSS + BC, 125.20 +- 36.53, Chao1; Vehicle, 117.61 +- 32.30; DSS, 108.66 +- 11.33; DSS + BC, 127.79 +- 37.95). Regarding the composition of gut microbiota, the DSS group showed a distinct alteration from that of the Vehicle group . In taxonomic community analysis at the phylum level, Firmicutes and Actinobacteria were reduced in the DSS group compared with the Vehicle group, whereas Bacteroidetes and Verrucomicrobia were increased . Meanwhile, the DSS + BC group was found to modulate the changes in the phylum caused by DSS. The abundance of Ligilactobacillus, Enterococcus, and Bifidobacterium at the genus level was high in the Vehicle group . However, DSS treatment diminished these genera and elevated the levels of Bacteroides, Escherichia, and Akkermansia. BC decreased Bacteroides levels and increased Ligilactobacillus compared with the DSS group. Moreover, at the species level, the administration of BC was shown to regulate the change in microbial composition due to DSS . As a result of analyzing b-diversity with a principal coordinate analysis (PCoA) plot to confirm the relative similarity in the gut microflora between each group, it was distinguished by the first principal component (PC1) between the Vehicle and DSS-treated groups . Moreover, the DSS and DSS + BC groups were distinguished by the second principal component (PC2), and supplementation with BC tended to modulate the gut microbial community. 4. Discussion The cause of colitis is considered to be an imbalance in intestinal homeostasis due to the influence of genetic, microbiological, immunological, and environmental factors . Natural products are being developed to treat UC, and ACNs are known to have positive effects on gut health . Thus, the current study aimed to analyze how the beneficial effects of ACN-rich BC caused immunological and microbiological changes in the colon in mice with DSS-induced colitis. Indeed, a previous study reported that nonalcoholic steatohepatitis was prevented in mice fed a high-fat/high-sucrose diet containing 6% whole BC powder, which was equivalent to consuming two cups of fresh BC per day in humans, for 24 weeks . Based on a previous study, we explored the effect of oral administration of 150 mg/day (7.5 g/kg body weight (BW), total ACN content; 165 mg/kg BW) of whole BC powder to mice, which was less than the dose administered in the previous study. In addition, the anti-inflammatory effects in colitis mice induced by DSS when administered BC at this dose were confirmed as a result of this study. Chemical induction of colitis using DSS in mice is the most widely used method because it reflects clinical symptoms and histological changes observed in humans . DSS, which has a highly negative charge, acts directly on colonic epithelial cells as a chemical toxin and damages them, resulting in the depletion of mucin and goblet cells, epithelial erosion, and ulcers . Destruction of the intestinal epithelial layer also increases colonic epithelial permeability, allowing commensal bacteria and related antigens to infiltrate the mucosa, followed by infiltration of immune cells such as neutrophils . Immune cells infiltrating the lamina propria and submucosa reportedly secrete pro-inflammatory cytokines and disseminate inflammatory responses to underlying tissues . The results of this work revealed that, when colitis was induced with DSS, clinical symptoms such as a decrease in body weight and colon length, as well as an increase in DAI and colon weight, were observed. Furthermore, histological changes were observed after inducing colitis with DSS, including epithelial loss, crypt damage, depletion of goblet cells, and infiltration of inflammatory cells. In contrast, the administration of BC had no effect on weight loss but showed beneficial effects on other clinical symptoms and histological changes following colitis induction. In another study, the intake of 200 mg/kg BW of crude ACN isolated from the fruits of Lycium ruthenicum Murray had no effect on weight loss induced by DSS, similar to our results . Previous studies also demonstrated that giving mice ACN-containing materials such as the water extract of maqui berry, ACN extracted from mulberry fruit and black rice relieved the pathological changes in the colon caused by DSS, like inflammatory cell infiltration and mucosal damage . Additionally, when silver nanoparticles with a diameter of 213 nm based on blackcurrant extract were supplied to the DSS colitis mice model at a concentration of 2 mg/kg, only the macroscopic score and colon shortening were significantly improved . Similar to the previous study, our study in which whole BC powder was administered also showed an improvement effect in these indicators, as well as a relieving effect in the colonic weight-to-length ratio. This difference is likely due to the difference in dose concentration. Damage to intestinal epithelial cells caused by DSS was reported to worsen the inflammatory response by increasing the generation of pro-inflammatory cytokines . It was also reported that the levels of TNF-a and IL-6 were altered in the serum of mice with early-stage colitis induced by one week of DSS administration . Elevated levels of pro-inflammatory cytokines due to colitis can be reduced by various polyphenols, including ACNs . In this study, except for IL-1b in the serum and IL-6 in the colon tissue, DSS treatment increased the levels of other pro-inflammatory cytokines, whereas BC administration decreased these levels. It was reported that treatment with petunidin 3-O-[rhamnopyranosyl]-(trans-p-coumaroyl)-5-O-[b-D-glucopyranoside] (P3G), isolated from the fruits of Lycium ruthenicum Murray, reduced all pro-inflammatory cytokines in the serum, but there was no difference in IL-1b levels in the crude ACN-administered group compared with the DSS-treated group, as in our study . When mulberry ACN was administered, the inhibitory effect on pro-inflammatory cytokines in the colon decreased all indicators at a high concentration (200 mg/kg BW), but there was no change, except for IL-1b, at a low concentration (100 mg/kg BW) . The major ACNs in BC are delphinidin-3-rutinoside, cyanidin-3-rutinoside, delphinidin-3-glucoside, and cyanidin-3-glucoside, and each food item contains different types of ACNs . Therefore, the difference in effects on weight loss and pro-inflammatory cytokines was presumed to be due to differences in the types and intake of different ACNs in food, and differences in UC mouse models and disease stages. Moreover, previous studies have shown that BC extract decreases inflammation-related cytokines in bone-marrow-derived macrophages and vascular tissue in mice with type 2 diabetes mellitus . Similarly, in the present study, BC was observed to reduce the production of pro-inflammatory cytokines, even when consumed in the form of whole BC powder. Intestinal homeostasis is maintained by a barrier consisting of mucus, epithelial, and immune cells that prevent the penetration of bacteria and other antigens into the colon tissue . DSS-induced loss of TJ proteins (ZO-1 and occludin) in mucus and mucin in the intestinal epithelial layers . NF-kB is an inducible transcription factor that regulates the expression of genes encoding cytokines associated with immune and inflammatory responses and is involved in maintaining intestinal homeostasis . When cells are stimulated externally through gut microbes, pro-inflammatory cytokines and toll-like receptors activate NF-kB (p-p65), which is known to be involved in the onset of inflammatory diseases by upregulating the expression of inflammation-related cytokines (TNF-a, IL-1b, and IL-6), chemokines (MCP-1), and inducible enzymes (COX-2, iNOS) . In previous studies, the administration of ACN in mice with DSS-induced colitis and mice fed a high-fat diet increased the expression of factors related to mucin and TJ proteins in the colon, while downregulating the expression of target genes in the NF-kB signaling pathway . In vitro, ACN-rich bilberry and BC extracts, as well as the 3-O-glucosides of cyanidin and delphinidin, have been shown to inhibit the activity of TNF-a-induced NF-kB in intestinal epithelial cells . The results of this study demonstrated that BC intake enhanced the expression of genes related to mucin and TJ proteins in colitis-induced mice. Additionally, BC decreased the phosphorylation of the NF-kB subunit and downregulated the expression of NF-kB target genes and proteins, such as COX-2 and iNOS, which were shown to improve DSS-induced colitis. Many studies have reported that changes in the community structure of gut microflora are associated with the development of colitis . In the DSS-induced colitis model, maqui berry extract and ACNs of mulberry and Lycium ruthenicum Murray changed the a-diversity of gut microflora , but BC did not change it significantly. However, it was confirmed that the treatment with BC had an effect on the b-diversity and gut microbial composition, which was distinct from that of the DSS group. Several studies using DSS-induced colitis mouse models revealed a reduction in Firmicutes and an increase in Bacteroidetes at the phylum level, and the intake of ACNs and flavonoids modulated their composition . The genera Lactobacillus (some of the reclassified genera, Ligilactobacillus ) and Bifidobacterium in the colon, known to have beneficial effects on health in several studies, are reduced by DSS , and our results were similar. Similar to another chronic DSS animal study, this study observed that treatment with DSS increased the genus Akkermansia, and this increase was a positive correlation with IL-1b, a pro-inflammatory cytokine . Although the genus Akkermansia is known to have anti-inflammatory effects, it is still controversial and more studies are required because its exact role in IBD is not known . As a change in relative abundance at the species level, BC decreased Bacteroides acidifaciens, known colitis-associated bacteria, after DSS treatment, and increased Bacteroides caecimuris, which rose in the recovery phase after stopping DSS treatment . In addition, BC administration tended to increase the abundance of Mucispirillum schaedleri, which has been reported to have a preventive effect against colitis caused by Salmonella and Alistipes putredinis, which decreases in IBD . As such, BC modulated the composition of gut microbiota that was altered by DSS. However, further studies are required to investigate the precise mechanism for the role of gut microbiota in each in the alleviation of colitis by BC. 5. Conclusions The intake of whole BC powder has been shown to prevent clinical symptoms and histological destruction caused by colitis. BC was observed to attenuate the levels of pro-inflammatory cytokines in serum and colon tissues and enhance the gene expression of mucin and tight junction proteins. Additionally, it downregulated the expression of target proteins and genes involved in the NF-kB signaling pathway. Furthermore, BC showed the potential to alleviate the intestinal inflammatory response by modulating the composition of gut microbiota altered by DSS. Therefore, in this study, whole BC powder showed a protective effect against DSS-induced colitis by regulating the inflammation-related NF-kB signaling pathway and gut microflora, confirming its potential as a natural dietary material to improve UC. Acknowledgments We would like to thank Sujon Berries for providing blackcurrant powder. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Experimental design. Click here for additional data file. Author Contributions Conceptualization, K.-A.K.; methodology, H.-J.M., Y.-S.C. and K.-A.K.; validation, H.-J.M., Y.-S.C. and K.-A.K.; formal analysis, H.-J.M., Y.-S.C. and K.-A.K.; investigation, H.-J.M. and K.-A.K.; resources, Y.-S.C. and K.-A.K.; data curation, H.-J.M. and K.-A.K.; writing--original draft preparation, H.-J.M.; writing--review and editing, H.-J.M., Y.-S.C. and K.-A.K.; visualization, H.-J.M.; supervision, Y.-S.C. and K.-A.K.; project administration, K.-A.K.; funding acquisition, K.-A.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The animal experiment was approved by the Animal Ethics Committee of Chungnam National University (IACUC approval number: 202112-CNU-214). Informed Consent Statement Not applicable. Data Availability Statement Data are contained within the article or Supplementary Materials. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Effects of blackcurrant on the clinical symptoms of DSS-induced colitis. (A) Changes in body weight during the experiment period; (B) disease activity index (DAI); (C) representative images, and measurement of colon length and colon weight/length. The values are shown as mean +- SD (n = 8 per group). Distinct lowercase letters indicate significant differences between groups through one-way ANOVA and Duncan's post hoc tests (p < 0.05). Vehicle, normal control group not treated with DSS; DSS, DSS control group; DSS + BC; DSS + blackcurrant group. Figure 2 Effects of blackcurrant on the colon damage of DSS-induced colitis. (A) Representative images of microscopic colon tissue stained with hematoxylin and eosin (magnification 50x and 100x); (B) histology scores of each group. The values are shown as mean +- SD (five sections each within n = 3 per group). Distinct lowercase letters indicate significant differences between groups through one-way ANOVA and Duncan's post hoc tests (p < 0.05). Vehicle, normal control group not treated with DSS; DSS, DSS control group; DSS + BC; DSS + blackcurrant group. Figure 3 Effects of blackcurrant on the mRNA expression related to inflammatory factors, mucin, and tight junction protein, and the activation of the NF-kB signaling pathway in DSS-induced colitis. (A) The relative levels of mRNA expression related to inflammatory factors (Tlr-4, Nf-kb, iNOS, Cox-2, Tnf-a, Il-1b, Il-6, Mcp-1) in colon tissues; (B) the relative levels of mRNA expression related to tight junction protein (Zo-1, Occludin) and mucin (Muc-1, Muc-2, Muc-3) in colon tissues; (C) representative images and (D) quantitative results showing the expression levels of proteins (p-p65, p65, iNOS, COX-2) related to NF-kB signaling pathway in colon tissue. The values are shown as mean +- SD (n = 8 per group). Distinct lowercase letters indicate significant differences between groups through one-way ANOVA and Duncan's post hoc tests (p < 0.05). Vehicle, normal control group not treated with DSS; DSS, DSS control group; DSS + BC; DSS + blackcurrant group. Figure 4 Effects of blackcurrant on gut microbiota on microbiota in DSS-induced colitis. (A) Taxonomy community analysis at the phylum levels; (B) taxonomy community analysis at the genus levels (>=0.03%); (C) heatmap analysis showing normalized abundance at the species levels; (D) principal coordinate analysis (PCoA) plots of gut microbiota of each group. The values are shown as mean +- SD (n = 5 per group). Vehicle, normal control group not treated with DSS; DSS, DSS control group; BC; DSS + blackcurrant group. foods-12-01073-t001_Table 1 Table 1 Effects of blackcurrant on the levels of pro-inflammatory cytokines in serum and colon tissues. Vehicle DSS DSS + BC Serum (pg/mL) TNF-a 1.93 +- 0.58 c 7.88 +- 1.28 a 5.70 +- 1.07 b IL-1b 0.10 +- 0.00 0.12 +- 0.04 0.12 +- 0.04 IL-6 0.54 +- 0.05 b 2.92 +- 1.13 a 3.02 +- 0.51 a Colon tissue (pg/mg protein) TNF-a 28.75 +- 25.70 b 65.05 +- 22.26a 37.30 +- 17.13 b IL-1b 2.85 +- 0.71 c 37.58 +- 3.64 a 25.30 +- 4.97 b IL-6 6.92 +- 0.57 7.12 +- 1.17 8.33 +- 1.45 The values are shown as mean +- SD (n = 8 per group). Distinct lowercase letters indicate significant differences between groups through one-way ANOVA and Duncan's post hoc tests (p < 0.05). Values with no significant difference among the groups were indicated by blanks. Vehicle, normal control group not treated with DSS; DSS, DSS control group; DSS + BC; DSS + blackcurrant 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). 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PMC10000426 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050699 healthcare-11-00699 Article Convergent Validity of the Edinburgh Postnatal Depression Scale and the Patient Health Questionnaire (PHQ-9) in Pregnant and Postpartum Women: Their Construct Correlations with Functional Disability Srisurapanont Manit Conceptualization Methodology Software Validation Formal analysis Writing - original draft Writing - review & editing Funding acquisition 1* Oon-arom Awirut Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing - original draft Writing - review & editing 1 Suradom Chawisa Conceptualization Methodology Writing - original draft Writing - review & editing 1 Luewan Suchaya Investigation Data curation 2 Kawilapat Suttipong Validation Formal analysis 3 Rigourd Virginie Academic Editor Billeaud Claude Academic Editor 1 Department of Psychiatry, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand 2 Department of Obstetrics and Gynecology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand 3 Research Administration Section, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand * Correspondence: [email protected]; Tel.: +66-53-945422; Fax: +66-53-945426 27 2 2023 3 2023 11 5 69909 2 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 ). This study aimed to evaluate the convergent validity of the Edinburgh Postnatal Depression Scale (EPDS) and the Patient Health Questionnaire (PHQ-9) in Thai pregnant and postpartum women, using the 12-item WHO Disability Assessment Schedule (WHODAS) as the reference standard. Participants completed the EPDS, PHQ-9, and WHODAS during the third trimester of pregnancy (over 28 weeks in gestational age) and six weeks postpartum. The sample included 186 and 136 participants for the antenatal and postpartum data analyses, respectively. The antenatal and postpartum data showed moderate correlations between both the EPDS and the PHQ-9 scores and the WHODAS scores (Spearman's correlation coefficients = 0.53-0.66, p < 0.001). The EPDS and PHQ-9 were moderately accurate in distinguishing disability (WHODAS score >= 10) from non-disability (WHODAS score < 10) in pregnant and postpartum participants, but the area under the curve of the PHQ-9 receiver operating characteristic curves in postpartum participants was significantly larger than that of the EPDS, with a difference (95% CI; p-value) of 0.08 (0.16, 0.01; p = 0.044). In conclusion, the EPDS and PHQ-9 are valid for assessing PND-related disability in pregnant and postpartum women. The PHQ-9 may perform better than the EPDS in distinguishing disability from non-disability in postpartum women. data accuracy depressive disorder prenatal diagnosis postpartum depression psychosocial functioning psychometrics Chiang Mai University16/2563 Chiang Mai University Faculty of Medicine34/2563 This study was supported by Chiang Mai University Faculty of Medicine (grant no. 34/2563) and Chiang Mai University (grant no.16/2563). However, the funding source was not involved in the study design, data collection, data analysis, data interpretation, manuscript preparation, or the decision to submit this article for publication. pmc1. Introduction Perinatal depression (PND) is clinically significant depression that occurs during pregnancy or the first postpartum year. It is a common complication that often goes unrecognized and has devasting effects on mothers and infants. Studies estimate that 10-15% of pregnant and postpartum women may experience PND , with higher prevalence in middle-income countries compared to high-income countries . Without treatment, PND can have significant adverse long-term effects on both mothers and infants. A standardized, validated tool for PND screening should be used in obstetric and postpartum care. While other screening tools have 20 items or more and need more than 5 min to complete, the 10-item EPDS and the 9-item PHQ-9 can be completed in less than 5 min . Studies show that using either the EPDS or PHQ-9 to screen for depression in postpartum women is effective . These questionnaires are both helpful in assessing PND depression in different clinical settings . Both are reliable and accurate for postpartum depression assessment, but they seem to identify different behavioral symptoms of antenatal depression . The PHQ-9 covers many physical symptoms, while the EPDS is better at detecting anxiety during the perinatal period. The Edinburgh Postnatal Depression Scale (EPDS) is the most commonly used tool for PND case finding. In postpartum women, the EPDS has a sensitivity range of 0.60 (specificity 0.97) to 0.96 (specificity 0.45) for major depression only and from 0.31 (specificity 0.99) to 0.91 (specificity 0.67) for major or minor depression . A meta-analysis of individual participant data collected from pregnant and postpartum women found that the combined sensitivity and specificity were highest, at a cut-off point of 11 or higher. However, to identify higher symptom levels of PND, a cut-off point of 13 or higher should be used . Although the EPDS was primarily developed for screening postpartum depression, it also has high accuracy in detecting antenatal depression, with an optimal cut-off score of 11/12 and above, both in terms of sensitivity and specificity . Previous findings suggested that the EPDS is a valid self-report for detecting postpartum depression in Thai women . The Patient Health Questionnaire-9 (PHQ-9) is another commonly used tool for PND case finding. Wang and colleagues (2021) compared the PHQ-9 to a criterion standard psychiatric interview and reported that the standard PHQ-9 cut-off point >=10 had high accuracy in detecting both antenatal and postpartum depression with a pooled sensitivity, specificity, and AUC of 0.84, 0.81, and 0.89, respectively . Furthermore, they found that the receiver operating characteristics (ROC) curves of the PHQ-9 and EPDS were nearly identical, with a median correlation between the two of 0.59 and moderate categorical agreement. A study of Thai women living with HIV also found that PHQ-9 depressive symptoms in pregnant and postpartum women were associated with low quality of life . These findings suggest that the PHQ-9 may be used as an alternative to the EPDS for PND case findings. The PHQ-9 appears to have two major strengths and some drawbacks in use as a case-finding tool for PND. First, the PHQ-9 was developed from the diagnostic criteria for major depressive episode (MDE), defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM). Therefore, its detection of PND would be very similar to the MDE, peripartum onset, which is a widely accepted diagnosis in clinical practice. Second, while the EPDS has several cut-off points for detecting PND, the PHQ-9 seems to have a consistent cut-off point of 10 for detecting clinically significant depression, which is also applicable for PND. Therefore, the PHQ-9 is relatively easy to use across healthcare settings, including the obstetric and postpartum care settings. Although there are some critics that the PHQ-9 items mainly focus on physical symptoms , most women can distinguish somatic symptoms related to their pregnancy (e.g., nausea in the first trimester, sleep difficulties related to caring for a newborn) from those related to depression . Distinguishing (functional) disability from non-disability refers to the ability to identify whether individuals are experiencing a significant impairment in their ability to perform daily activities and tasks, or if they are functioning normally. For a broader concept, disability includes the areas as follows: (1) understanding and communication, (2) self-care, (3) mobility, (4) interpersonal relationships, (5) work and household roles, and (6) community and civic roles or participation . In clinical practice, this distinguishing has two-fold benefits. First, disability is a crucial characteristic for diagnosing mental disorders, including PND . Furthermore, individuals who are experiencing a high level of disability should be given priority for intervention or support. Convergent validity is a method to evaluate the accuracy of a case-finding tool (for diagnosis) by examining the correlation between their scores and the scores from other instruments that measure the same construct . This is done through "hypothesis testing", which involves determining whether the correlation between the scores is what would be expected. If the correlation is as expected, the case-finding tool is considered to have good convergent validity. Based on the hypotheses mentioned above, pregnant and postpartum women with more severe depression should also have more severe disability. The EPDS and PHQ-9 scores, commonly used to measure the severity of PND, should be correlated with disability. So far, two studies have used the WHO Disability Assessment Schedule (WHODAS) as a reference standard for testing the convergent validity of EPDS and PHQ-9 against disability. The EPDS and PHQ-9 scores collected from Ghana postpartum women were weakly correlated with the WHODAS scores (r = 0.19 and r = 0.22, respectively) . The antenatal PHQ-9 scores were weakly to moderately correlated with the WHODAS scores (r = 0.38 in Ghana and r = 0.41 in Cote d'Ivoire) . These findings suggest that the EPDS and PHQ-9 scores may not effectively measure disability in PND, raising questions about their use as diagnostic tools for PND, which usually needs a crucial characteristic of disability. Recently, we conducted a study to investigate the use of biological markers in predicting antenatal and postpartum depression in Thai pregnant women . In the current study, we used the EPDS, PHQ-9, and 12-item WHODAS scores from that previous study to perform a secondary data analysis to determine the convergent validity of EPDS and PHQ-9 in Thai pregnant and postpartum women by using the WHODAS as a reference standard. Additionally, we aimed to evaluate the overall performance of both questionnaires in distinguishing disability from non-disability in these populations. 2. Materials and Methods 2.1. Participants and Study Design This study was approved by the Ethics Committee for Human Research, Faculty of Medicine, Chiang Mai University (Approval Number 367/2518) and adhered to the Declaration of Helsinki (1964) and its subsequent revisions. It was a single-center, prospective, observational study conducted at Maharaj Nakorn Chiang Mai Hospital, a public hospital at the tertiary level in Chiang Mai, Thailand. We approached adult participants during their first visits in the third trimester of pregnancy. Participants provided informed consent after the study details were fully explained. The study took place between December 2018 and November 2019. Because the materials and methods were fully described in our previous publication , we present only the highlights here. The participants were a convenient sample of pregnant women aged 18-55 years who attended antenatal clinics for high-risk pregnancies. They were screened for exclusion of psychotic disorders, current major depressive disorder, and dysthymia in the third trimester using the Mini International Neuropsychiatric Interview (M.I.N.I.) Thai version 5.0.0 . We also excluded participants currently taking antipsychotics or antidepressants. 2.2. Assessing Depression, Anxiety, and Disability Participants completed the EPDS, the PHQ-9, and the 12-item WHODAS questionnaire (version 2.0) in their Thai versions during the third trimester of pregnancy (more than 28 weeks in gestational age) and six weeks postpartum, . The EPDS is a ten-symptom questionnaire that assesses depression over the week before the assessment. The PHQ-9 questionnaire uses nine symptoms to diagnose DSM-IV major depressive disorder. Each item on the EPDS or PHQ-9 is scored from 0 to 3 based on the severity of the symptom. The EPDS and PHQ-9 item scores are then summed to derive full scales of 0-30 and 0-27, respectively. The EPDS and PHQ-9 are reliable and valid measures for PND. However, they seem to assess different behavioral symptoms of depression . While the PHQ-9 covers a broader range of physical symptoms, the EPDS tends to identify anxiety symptoms specifically during the perinatal period. The WHODAS questionnaire assesses six dimensions of disability: (1) understanding and communication, (2) self-care, (3) mobility, (4) interpersonal relationships, (5) work and household roles, and (6) community and civic roles or participation. Each domain includes two questions, each using a five-level scale from 0, denoting "no difficulty", to 4, denoting "extreme difficulty or cannot do". The severity of each item is rated from 0 (none) to 4 (extreme or cannot do), and the scores of all items are summed to produce a total score from 0 to 48. Based on previous findings , a 12-item WHODAS score of 10 or more is considered clinically significant disability. The 21-item Depression Anxiety Stress Scale (DASS-21), in its Thai version, was administered once during the third trimester of pregnancy . The DASS-21 total score ranges from 0 to 63. Additionally, the DASS-21 includes three subscale scores that reflect the severity of depression, anxiety, and stress. 2.3. Statistical Analysis The data collected from pregnant and postpartum participants were analyzed separately. We presented continuous and categorical data as mean (standard deviation, SD) and n (%). The internal consistencies of the EPDS, PHQ-9, and WHODAS were evaluated using Cronbach's alphas, with a value of 0.8 and above considered good internal consistency . The EPDS, PHQ-9, and WHODAS scores were considered ordinal data. Therefore, the Wilcoxon Signed-Rank test was applied to determine the score changes from the third trimester to the postpartum period, and the Spearman's test was used for assessing the correlations among these scores. We conducted convergent analysis using two methods. First, we reportedthe correlation between the severity of PND assessed using the EPDS or PHQ-9 and the disability measured using the WHODAS as Spearman's correlation coefficients (rs) (95% confidence intervals, 95% CIs). The 95% CI of rs was calculated based on the R distribution 95% confidence limits, which took into account the skewness and kurtosis of the sample data and provided a more accurate result. For the interpretation, the rs values were categorized as follows: very strong (0.90-1.00), strong (0.70-0.89), moderate (0.40-0.69), weak (0.10-0.39), and negligible (0.00-0.10) . Second, we plotted receiver operating characteristic (ROC) curves to determine the overall performance of EPDS and PHQ-9 scores in discriminating disability (WHODAS score >= 10) from non-disability (WHODAS score < 10). The area under the curve (AUC) of each ROC was calculated, and its accuracy was classified as poor (0.5-0.7), moderate (0.7-0.9), and high (>0.9) . The AUCs EPDS and PHQ-9 ROC curves were compared using a paired design. A p-value less than 0.05 was considered statistically significant. All analyses were conducted using NCSS 21.0 . 3. Results 3.1. Antenatal Data Analysis Out of 200 participants, 186 completed the EPDS, PHQ-9, and WHODAS in their third trimester of pregnancy and were included in the antenatal data analysis. The mean years of age and education were 29.46 (SD = 5.16) and 14.06 (SD = 3.37) years, respectively (see Table 1). Table 1 presents other characteristics of 186 pregnant participants included in the antenatal data analysis. For the antenatal data (N = 186), the mean scores (SDs) of the EPDS, PHQ-9, and WHODAS were 6.35 (3.86), 4.38 (3.31), and 6.79 (5.88), respectively. Forty-eight participants (25.81%) had a clinically significant disability (WHODAS >= 10). The EPDS, PHQ-9, and WHODAS had good internal consistency, with Cronbach's alphas of 0.80, 0.83, and 0.88, respectively. Figure 1 illustrates the correlation plots among the EPDS, PHQ-9, and WHODAS scores. The EPDS and the PHQ-9 scores were significantly and strongly correlated, with an rs (95% CI; p-value) of 0.73 (0.63, 0.78; p < 0.001). The WHODAS score was significantly and moderately correlated with the EPDS score, with an rs (95% CI; p-value) of 0.60 (0.50, 0.68; p < 0.001). The WHODAS score was significantly and moderately correlated with the PHQ-9 score, with an rs (95% CI; p-value) of 0.56 (0.45, 0.65; p < 0.001). The ROC curves for the EPDS and PHQ-9 scores showed that both questionnaires had moderate accuracy in distinguishing disability from non-disability, with AUCs (95% CIs; p values) of 0.82 (0.73, 0.88; p < 0.001) and 0.79 (0.71, 0.86, p < 0.001), respectively . The AUCs of both questionnaires were not significantly different, with a difference of 0.03 (95% CI -0.05, 0.10; p = 0.513). 3.2. Postpartum Data Analysis Out of 200 participants, 136 completed the EPDS, PHQ-9, and WHODAS at the six-week postpartum visit and were included in the analysis of postpartum data. The mean years of age and education were 29.77 (SD = 5.34) and 14.02 (SD = 3.34) years, respectively (see Table 1). The mean scores (SDs) of the EPDS, PHQ-9, and WHODAS during the third trimester of pregnancy were 6.20 (3.61), 4.13 (2.82), and 6.83 (5.89), respectively. Maternal and newborn complications occurred in 51 (38.64%) and 15 (11.36%) of the participants. Table 1 presents other characteristics of the 136 postpartum participants included in the analysis of postpartum data. For the postpartum data (N = 136), the mean scores (SDs) of the EPDS, PHQ-9, and WHODAS were 5.83 (3.99), 3.62 (3.50), and 5.27 (5.37), respectively. Twenty-five participants (18.38%) had a clinically significant disability (WHODAS >= 10). The EPDS, PHQ-9, and WHODAS had good internal consistency, with the Cronbach's alphas of 0.82, 0.85, and 0.86, respectively. Figure 3 illustrates the correlation plots among the EPDS, PHQ-9, and WHODAS scores. These questionnaires were significantly and moderately correlated, with an rs (95% CIs; p-values) as follows: (i) the EPDS and PHQ-9 scores = 0.66 (0.55, 0.74; p < 0.001), (ii) the EPDS and WHODAS scores = 0.53 (0.39, 0.64, p < 0.001), and (iii) the PHQ-9 and WHODAS scores = 0.57 (0.45, 0.68; p < 0.001). The ROC curves for the EPDS and PHQ-9 scores showed that both questionnaires had moderate accuracy in distinguishing disability from non-disability, with AUCs (95% CIs; p values) of 0.82 (0.70, 0.89; p < 0.001) and 0.90 (0.81, 0.94, p < 0.001), respectively . The AUC of PHQ-9 was significantly larger than that of EPDS, with a difference of 0.08 (95% CI 0.16, 0.01; p = 0.044). 4. Discussion The present findings add another dimension of evidence to the widely accepted questionnaires for screening PND. Their correlations with functional disability during perinatal periods suggest that the EPDS and PHQ-9 are valid for assessing PND in Thai pregnant and postpartum women. As disability is another dimension for diagnosing mental illnesses, these good correlations with disability indicate that a high EPDS or PHQ-9 score can be used to support the diagnosis of PND. Both questionnaires also have good internal consistency and are strongly correlated with each other. The scores of both questionnaires show moderate correlation with functional disability and moderate accuracy in distinguishing disability from non-disability. However, the PHQ-9 may be more effective than the EPDS in distinguishing disability from non-disability in postpartum women. Our findings should not be interpreted as the PHQ-9 being superior to the EPDS in screening for postpartum depression, due to limitations of the study. However, the PHQ-9 may still be considered as a viable alternative to the EPDS for this purpose in pregnant and postpartum women. The antenatal data of this study showed more positive results on the correlations between the EPDS or the PHQ-9 scores and the WHODAS score compared to those reported in previous studies. Barthel et al. (2015) reported that the PHQ-9 score was weakly correlated with the WHODAS score in South African pregnant women (r = 0.38-0.41) , but our findings suggested that they were moderately correlated in Thai pregnant women (rs = 0.56). Although it might be difficult to explain the differences between the previous and the present findings, it should be noted that the participants in the study of Bartherl et al. (2015) seemed to be more depressed, with mean PHQ-9 scores of 7.53 and 7.85, compared to our participants (mean PHQ-9 score of 4.38). The moderate correlation between the EPDS and the WHODAS scores found in this study (rs = 0.60) has never been reported. The postpartum data of this study showed that the EPDS and the PHQ-9 scores were moderately correlated with the WHODAS score in this population. In postpartum women, we found stronger correlations between the EPDS and WHODAS scores (rs = 0.50) and between the PHQ-9 and WHODAS scores (rs = 0.60) compared to only weak correlations in previous research (r = 0.19 and r = 0.22, respectively) . While our study had a lower mean EPDS score (5.8) compared to the previous study (7.7), the mean PHQ-9 scores were similar in both studies (3.6). The difference in EPDS scores may explain the different correlations between the EPDS and WHODAS scores reported in previous and current studies. The discrepancy in findings may suggest that African and Asian postpartum women have different symptom profiles of postpartum depression and/or different perceptions of disability due to the fact that the PHQ-9 includes more somatic questions than EPDS. To our knowledge, this study is the first to compare the overall performance of the EPDS and PHQ-9 in distinguishing disability from non-disability. The scores of both questionnaires show moderate accuracy in such differentiation. Our findings suggest that both questionnaires can be used to determine if a pregnant or postpartum woman is experiencing a level of disability. The larger AUC of PHQ-9 in postpartum women indicates that the PHQ-9 may be superior to the EPDS in distinguishing disability from non-disability in this population. Future studies are needed to identify the appropriate cut-off point of the PHQ-9 that reflects perinatal depression with clinically significant disability. This study had some limitations. First, the small sample caused a low prevalence of participants with high symptom levels and/or clinically significant disability. The AUC difference between the EPDS and the PHQ-9 found in this study should be viewed only as preliminary findings and applied in clinical decisions with caution. The statistically nonsignificant associations or differences might be caused by type-II errors. Second, this is a single-site study in Thai women living in Chiang Mai and nearby regions. The effects of national circumstances, geography, and economic development should be considered. Therefore, these findings should be generalized to other populations with caution. Third, the clinically significant disability indicated by the WHODAS cut-off point of >=10 was based on a population sample of Australian adults. Whether this cut-off point is appropriate for Thai adults, including pregnant and postpartum women, is unknown. Fourth, several factors that might affect the PND and the disability in this study population were not collected and taken into account, e.g., socioeconomic status, the severity of morning sickness, and the burden of newborn care. Last, as a study conducted during the COVID-19 pandemic, COVID-19 worries might affect the participants' mood assessed using the EPDS and the PHQ-9. However, COVID-19 infection affecting mood symptoms would be low because the prevalence of COVID-19 infection was relatively low in Thai pregnant women . Another issue of concern is the changes in living, socioeconomic, and environmental conditions after the COVID-19 epidemic. These problems may affect maternal mood differently and have to be considered in generalizing the present findings. Our findings further support the use of EPDS and PHQ-9 as case-finding tools for PND, for both antenatal and postpartum depression. Previous studies suggested that both tools have high sensitivity and specificity. By using the convergent validity analysis, the present findings support that EPDS and PHQ-9 scores are correlated with disability, a dimension needed for making a diagnosis of mental disorders. In addition, pregnant and postpartum women with high EPDS or PHQ-9 scores should be a priority group for treatment initiation because they are likely to have PND-related disability. Both questionnaires display strong internal consistency and a high degree of correlation with each other, which suggests that they are relatively comparable in measuring the severity of PND. Due to several limitations, the present findings cannot be taken as evidence that the PHQ-9 is better than the EPDS in screening for PND. Nonetheless, the results suggest that the PHQ-9 may not be inferior to the EPDS and may provide support for using it as an alternative tool to the EPDS in evaluating PND in pregnant and postpartum women. Our findings on the convergent validity further support the use of EPDS or PHQ-9 in clinical settings, because these questionnaires not only can identify women with PND but also can identify those with disability, who desperately need treatment. 5. Conclusions The EPDS and PHQ-9 are valid for assessing PND-related disability in Thai pregnant and postpartum women. The scores of these questionnaires reflect not only the severity of PND but also the disability levels. Although the PHQ-9 may perform better than the EPDS in distinguishing disability from non-disability in postpartum women, these findings should be interpreted with caution due to several limitations of this study. The PHQ-9 may be an alternative to EPDS for assessing depression in pregnant and postpartum women. Our findings further support the use of EPDS or PHQ-9 in clinical settings. Future studies are needed to compare other psychometric properties of the PHQ-9 with those of the EPDS. Acknowledgments The authors would like to thank the participants in this study and all healthcare workers at the Antenatal Care Clinic and Postpartum Care Clinic, Chiang Mai University Hospital, for facilitating the clinical collection. Author Contributions Conceptualization, M.S., A.O.-a. and C.S.; methodology, M.S., A.O.-a. and C.S.; software, M.S.; validation, M.S., A.O.-a. and S.K.; formal analysis, M.S., A.O.-a. and S.K.; investigation, A.O.-a. and S.L.; data curation, A.O.-a. and S.L.; writing--original draft preparation, M.S., A.O.-a. and C.S.; writing--review and editing, M.S., A.O.-a. and C.S.; visualization, M.S.; supervision, M.S.; project administration, A.O.-a. and S.K.; funding acquisition, M.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 Ethics Committee for Human Research, Faculty of Medicine, Chiang Mai University (Approval Number 367/2518). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data is available upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Correlations among EPDS, PHQ-9, and WHODAS scores and regression lines in 186 pregnant participants (antenatal data only): (a) Correlation between antenatal EPDS and PHQ-9 scores: Spearman's rho (95% CI; p-value) = 0.73 (0.63, 0.78; p < 0.001; (b) Correlation between antenatal EPDS and WHODAS scores: Spearman's rho (95% CI; p-value) = 0.60 (0.50, 0.68; p < 0.001); and (c) Correlation between antenatal PHQ-9 and WHODAS scores: Spearman's rho (95% CI; p-value) = 0.56 (0.45, 0.65; p < 0.001). EPDS, Edinburgh Postnatal Depression Scale; PHQ9, 9-item Patient Health Questionnaire; WHODAS, 12-item World Health Organization Disability Assessment Schedule. Figure 2 The receiver operating characteristic (ROC) curves of EPDS and PHQ-9 scores to differentiate disability (WHODAS score >= 10) from non-disability in 186 pregnant women (antenatal data only). AUC (95% CI; p-value): EPDS score = 0.82 (0.73, 0.88; p < 0.001), PHQ-9 score = 0.79 (0.71, 0.86; p < 0.01). AUC difference (95% CI; p-value): 0.03 (-0.05, 0.10; p = 0.513). AUC, area under the (receiver operating) curve (empirical estimate); EPDS, Edinburgh Postnatal Depression Scale; PHQ9, 9-item Patient Health Questionnaire; WHODAS, 12-item World Health Organization Disability Assessment Schedule. Figure 3 Correlations among EPDS, PHQ-9, and WHODAS scores and regression lines in 136 postpartum participants (postpartum data only): (a) Correlation between postpartum EPDS and PHQ-9 scores: Spearman's rho (95% CI; p-value) = 0.66 (0.55, 0.74; p < 0.001); (b) Correlation between postpartum EPDS and WHODAS scores: Spearman's rho (95% CI; p-value) = 0.53 (0.39, 0.64, p < 0.001); and (c) Correlation between postpartum PHQ-9 and WHODAS scores: Spearman's rho (95% CI; p-value) = 0.57 (0.45, 0.68; p < 0.001). EPDS, Edinburgh Postnatal Depression Scale; PHQ9, 9-item Patient Health Questionnaire; WHODAS, 12-item World Health Organization Disability Assessment Schedule. Figure 4 The receiver operating characteristic (ROC) curves of EPDS and PHQ-9 scores to differentiate disability (WHODAS score >= 10) from non-disability in 136 postpartum participants (postpartum data only). AUC (95% CI; p-value): EPDS = 0.82 (0.70, 0.89; p < 0.001), PHQ-9 = 0.90 (0.81, 0.94; p < 0.001). AUC difference (95% CI; p-value): 0.08 (0.16, 0.01; p = 0.044). AUC, area under the (receiver operating) curve (empirical estimate); EPDS, Edinburgh Postnatal Depression Scale; PHQ9, 9-item Patient Health Questionnaire; WHODAS, 12-item World Health Organization Disability Assessment Schedule. healthcare-11-00699-t001_Table 1 Table 1 Characteristics and psychopathology of 186 pregnant and 136 postpartum participants. Characteristics Pregnant Participants (N = 186) Postpartum Participants (N = 136) At the third-trimester visit during pregnancy Mean (SD) Mean (SD) Age (years) 29.46 (5.16) 29.77 (5.34) Education (years) 14.06 (3.37) 14.02 (3.34) Body mass index (kg/m2) 23.03 (4.46) 23.23 (4.73) DAS-depression score 4.76 (5.20) 4.23 (4.41) DAS-anxiety score 5.29 (5.08) 4.94 (4.67) DAS-stress score 6.89 (6.97) 6.76 (6.48) Gestational number 1.75 (0.88) 1.75 (0.80) Antenatal EPDS score 6.35 (3.86) 6.20 (3.61) Antenatal PHQ-9 score 4.38 (3.31) 4.13 (2.82) Antenatal WHODAS score 6.79 (5.88) 6.83 (5.89) At the third-trimester visit during pregnancy n (%) n (%) History of psychiatric disorders 6 (3.23) 5 (3.79) Family history of psychiatric disorders 12 (6.45) 10 (7.58) History of abortion 40 (21.51) 28 (21.21) Labor characteristics n (%) Assisted delivery/Cesarian section 33 (25.00) Maternal complications 51 (38.64) Newborn complications 15 (11.36) 6 weeks postpartum Mean (SD) Postpartum EPDS score 5.83 (3.99) Postpartum PHQ-9 score 3.62 (3.50) Postpartum WHODAS score 5.27 (5.37) DASS, 21-item Depression Anxiety Stress Scale; EPDS, Edinburgh Postnatal Depression Scale; PHQ9, 9-item Patient Health Questionnaire; WHODAS, 12-item World Health Organization Disability Assessment Schedule. 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PMC10000427 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051090 foods-12-01090 Article Correlation between Water Characteristics and Gel Strength in the Gel Formation of Golden Pompano Surimi Induced by Dense Phase Carbon Dioxide Duan Weiwen Conceptualization Methodology Software Writing - original draft Writing - review & editing 1 Qiu Hui Software Formal analysis Investigation 1 Htwe Kyi Kyi Investigation 1 Wang Zefu Validation 1 Liu Yang Supervision 1 Wei Shuai Data curation 1 Xia Qiuyu Validation 1 Sun Qinxiu Resources 1 Han Zongyuan Visualization 1 Liu Shucheng Conceptualization Project administration Funding acquisition 123* Shand Phyllis Academic Editor 1 Guangdong Provincial Key Laboratory of Aquatic Product Processing and Safety, Guangdong Province Engineering Laboratory for Marine Biological Products, Guangdong Provincial Engineering Technology Research Center of Seafood, Key Laboratory of Advanced Processing of Aquatic Product of Guangdong Higher Education Institution, College of Food Science and Technology, Guangdong Ocean University, Zhanjiang 524088, China 2 Guangdong Laboratory of Southern Marine Science and Engineering (Zhanjiang), Zhanjiang 524088, China 3 Collaborative Innovation Center for Key Technology of Marine Food Deep Processing, Dalian University of Technology, Dalian 116034, China * Correspondence: [email protected] 03 3 2023 3 2023 12 5 109008 2 2023 28 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 ). The relationship between the gel quality of golden pompano surimi treated with dense phase carbon dioxide (DPCD) and changes in water characteristics was evaluated. Low-field nuclear magnetic resonance (LF-NMR) and nuclear magnetic resonance imaging were used to monitor changes in the water status of surimi gel under different treatment conditions. Whiteness, water-holding capacity and gel strength were used as the quality indicators of the surimi gel. The results showed that DPCD treatment could significantly increase the whiteness of surimi and the strength of the gel, while the water-holding capacity decreased significantly. LF-NMR analysis showed that, as the DPCD treatment intensity increased, the relaxation component T22 shifted to the right, T23 shifted to the left, the proportion of A22 decreased significantly (p < 0.05) and the proportion of A23 increased significantly (p < 0.05). A correlation analysis of water characteristics and gel strength showed that the water-holding capacity of surimi induced by DPCD was strongly positively correlated with gel strength, while A22 and T23 were strongly negatively correlated with gel strength. This study provides helpful insights into the quality control of DPCD in surimi processing and also provides an approach for the quality evaluation and detection of surimi products. golden pompano surimi processing dense phase carbon dioxide gel strength water characteristics Guangdong Innovation Team of Seafood Green Processing Technology2019KCXTD011 Modern Agro-industry Technology Research System of ChinaCARS-48 National Natural Science Foundation of China (Youth Program)32202086 Scientific and Technological Innovation Strategy of Guangdong Province2022A05036 Guangdong General Universities Young Innovative Talents Project2020KQNCX028 General transfer payment fund project of fishery development support policy in Guangdong Province2022-440000-45060100-9680 Guangdong Innovation Team of Seafood Green Processing Technology (2019KCXTD011); Modern Agro-industry Technology Research System of China [CARS-48]; National Natural Science Foundation of China (Youth Program) (32202086), Scientific and Technological Innovation Strategy of Guangdong Province (2022A05036), Guangdong General Universities Young Innovative Talents Project (2020KQNCX028), General transfer payment fund project of fishery development support policy in Guangdong Province in 2022 (2022-440000-45060100-9680). pmc1. Introduction Golden pompano (Trachinotus ovatus) is one of the marine fishes with important economic value in the southern coastal region of China. It is popular with consumers for its tender flesh, delicious taste and high content of polyunsaturated fatty acids . China is one of the world's largest producers of golden pompano, with a total domestic mariculture production of 243,900 tonnes in 2021; this ranked second among all marine economic fish and was an increase of 139.85% compared to 2020 . Currently, golden pompano is mainly sold as fresh and frozen fish. Surimi is an important processed aquatic product, which is mainly formed by heat induction. However, surimi processed by heat induction is prone to the loss of heat-sensitive nutrients due to excessive temperatures. Additionally, in the process of heat-induced surimi formation, the surimi remains at 50-70 degC for long periods due to the slow heating rate and heat transfer rate of heat induction. This is the optimum temperature for the enzymatic activity of the alkaline protease in the surimi gel, resulting in the degradation of myofibrillar protein and leading to gel deterioration, which in turn results in the deterioration of surimi quality . High-density CO2 (dense phase carbon dioxide, DPCD) is a new non-thermal processing technology that generally operates at temperatures (<60 degC) and pressures (<50 MPa). A high-pressure acidic environment is created by the pressure of the carbon dioxide and its molecular action. Unlike conventional heat treatment, DPCD technology can be used at mild processing conditions, which can be applied in sterilisation, enzyme inactivation and promotion of food quality attributes such as textural and nutritional properties . In addition, CO2 has a low viscosity and high diffusivity, which enables it to penetrate the bacterial cell membranes. The advantage of this method can avoid thermal damage and maintain food quality . It has been shown that DPCD treatment can denature proteins to form gels with significantly better gel characteristics than those of traditional heat-induced gels while preserving the nutritional value and flavour of the food to the greatest extent possible; thus, DPCD can be used as an alternative to traditional thermal processing methods . Gel strength and water-holding capacity are important quality characteristics of surimi. During processing, surimi proteins stretch and denature to form a three-dimensional network structure that holds more water . Generally, surimi gel has a high water content. The distribution of water in surimi gel and the relative proportions of water in different states will directly affect the quality of surimi gel . In this study, the effects of different DPCD treatment conditions on the water characteristics of golden pompano surimi gel were compared. The water distribution and relative proportions in surimi gel under different treatment conditions were investigated by low-field nuclear magnetic resonance (NMR) spectroscopy. The relationships between the gel strength, water-holding capacity and whiteness of the surimi gel were investigated in relation to its water characteristics. This work aimed to reveal the quality changes relating to DPCD-induced gel formation in golden pompano surimi from the perspective of water characteristics and gel strength. This work also provides a theoretical basis for evaluating and improving the quality of DPCD-induced gel formation in golden pompano surimi. 2. Materials and Methods 2.1. Chemicals Pure Carbon dioxide (99.99%) was obtained from the Zhanjiang Oxygen Plant. Sucrose and sodium chloride were purchased from Guangdong Guanghua Sci-Tech Co., Ltd. (Guangzhou, China). All reagents were analytical grade. 2.2. Surimi Sample Preparation Golden pompano fish of average weight (750 +- 50 g) were purchased from Dongfeng Seafood Market (Zhanjiang, China). The fish was kept in oxygenated water and immediately transported to the laboratory within 1 h. Then, the fish were rapidly immersed in ice water and the surimi was prepared according to the method proposed by Liu et al. . The fish were rinsed, scaled, headed, gutted and cleaned to remove any remaining offal from the abdominal cavity, keeping the water temperature below 10 degC during the cleaning process. The fish flesh was then placed in a roller-type flesh separator (SZC-180, Jinan, China) to separate the flesh. The resulting minced fish was rinsed in five batches of ice water three times (10 min/each). Next, the minced fish was squeezed and dewatered in three layers of gauze and then dehydrated in a minced fish spiral dehydrator (ZTZY-120, Xinxiang, China) at 30 rpm for 3 min. The minced fish was supplemented with 1% sucrose by mass and chopped with a blender (MQ785, Germany Braun Co. Ltd., Cluj-Napoca, Romania) at 14,200 rpm for 5 min. Next, the minced fish was placed in a custom-made cylindrical mold and used for DPCD or heat treatment. 2.3. Experimental Design Based on our previously reported research method , a schematic diagram of the DPCD treatment equipment is shown in Figure 1A. The temperature of the DPCD treatment kettle was set prior to the experiment and the sample was not inserted until the kettle had been heated to the set temperature. The surimi was formed into a cylinder (thickness 20 mm, diameter 40 mm) using a mold , placed in the DPCD treatment kettle and sealed. The CO2 inlet and outlet valves were opened for 30 s to evacuate the air from the kettle and then the outlet valve was closed. Next, the pressure was kept constant when the CO2 pressure reached the target condition in the sample-treated kettle. After the treatment was completed, the exhaust valve was opened to slowly depressurise the kettle. Then, the surimi gel was removed and packaged in a sealed bag. The test indices were measured after 12 h at 4 degC. The DPCD treatment group was carried out using a single-factor design. (1) different pressure conditions (5, 10, 15, 20, 25, 30 and 35 MPa) and constant temperature and time (50 degC and 60 min); (2) different temperature conditions (30, 35, 40, 45, 50, 55 and 60 degC) and constant pressure and time (20 MPa and 60 min); and (3) different treatment time (10, 20, 30, 40, 50, 60 and 70 min) and constant pressure and temperature (20 MPa and 50 degC) were applied. The surimi gel quality was tested in each individual factor treatment. Two control groups were also set up, one for the raw surimi group (Control), which was not treated, and the other for the heat treatment group (WB), which applied two-stage water bath heating (40 degC for 30 min, 90 degC for 30 min). 2.4. Determination of Whiteness The surimi colour parameters were determined using a colourimeter (CR-20, Konica Minolta Inc., Tokyo, Japan). The CIE Lab coordinates were reported as lightness (L*), redness (a*) and yellowness (b*). Whiteness (W) was calculated according to Equation (1). (1) W=100-(100-L*)2+(a*)2+(b*)2 2.5. Determination of Water-Holding Capacity The water-holding capacity (WHC) was determined according to the method of Yang et al. . A 5.0 +- 0.1 g gel sample (m1) was wrapped with filter paper and centrifuged at 4 degC and 5000 rpm for 10 min. Then, the sample was weighed (m2) after removing the filter paper. The WHC was calculated according to Equation (2). (2) WHC (%)=m2m1x100 2.6. Low-Field Nuclear Magnetic Resonance and Magnetic Resonance Imaging The water distribution was determined using an NMI 20-060H-I NMR analyser (Newmark Analytical Instruments Co., Ltd., Suzhou, China) with a stable frequency of 21.12 MHz at 32 degC. The instrument was calibrated as described by Zhou et al. , with a slight modification. TE (echo time) = 0.35 ms; TW (wait time) = 3000 ms; NECH (number of echoes) = 4000 were set. The greyscale image was converted into a colour image using Niumag NMR V3.0 image processing software to visualise the water distribution. 2.7. Determination of Gel Strength The gel strength of the surimi was determined using a TMS-Pro analyser (FTC Co., Ltd., Vienna, Virginia, USA). According to the method described by Zheng et al. , a probe = P/0.5 s, trigger force = -5 g; pre-test speed = 5 mm*s-1; test speed = 1 mm*s-1; compression deformation, 75% were set. The gel strength (g x mm). was obtained by multiplying the breaking strength (g) and the breaking distance (mm). 2.8. Statistical Analysis Experimental data are expressed as the mean +- standard deviation. A variance and Tukey's HSD multiple comparisons (with a 95% confidence interval) were analysed using JMP 16.0 software. The correlation between water characteristics and gel strength during DPCD-induced gel formation in surimi was analysed via Pearson's correlation analysis using Origin 2022 software (Origin Lab, Hampton, NH, USA). Three batches of experiments were performed and each batch had three parallel samples. 3. Results and Discussion 3.1. Effect of Different DPCD Treatments on Surimi Whiteness The whiteness (W) of surimi gel is one of the most important indicators for evaluating its quality. The greater the whiteness, the more favoured the surimi is by consumers. The brightness of an object is related to the light reflectance of its surface, and the intensity of light scattered by the surface of food is closely related to the moisture content of food. In general, the higher the moisture content of the food, the higher the intensity of light scattered from its surface and the greater the whiteness . The whiteness of surimi gel is also related to protein denaturation, aggregation and gel networks . Generally, the denser the protein gel network structure, the better the water retention and the greater the intensity of light scattering, resulting in greater whiteness. As shown in Figure 2A-C, both the heat treatment and the DPCD treatment significantly increased the surimi gel whiteness compared to the control group (p < 0.05). When the DPCD treatment conditions were 50 degC and 60 min , the surimi gel whiteness increased with increasing pressure in the range of 5-20 MPa (p < 0.05). This was because CO2 under pressure caused moderate denaturation and aggregation of proteins, resulting in a dense three-dimensional network structure of the surimi gel to trap moisture. Meanwhile, the whiteness of the surimi gel increased due to increased light scattering. However, the whiteness of the surimi gel decreased when the treatment pressure was higher than 20 MPa (p < 0.05). This was because the excessive pressure enhanced the molecular action of CO2, resulting in the loss of water from the surimi gel and a decrease in the whiteness of the surimi gel due to the weakening of its light scattering intensity . When the DPCD treatment conditions were 20 MPa and 60 min , the whiteness of the surimi gel increased as the temperature increased from 30-50 degC (p < 0.05). This was because the increase in temperature contributed to the rapid gelation of the surimi. However, when the temperature was 50-60 degC, the surimi gel whiteness decreased as the temperature increased (p < 0.05). This was because the high temperature accelerated the evaporation of water, resulting in the loss of water from the surimi gel. The weakening of the light scattering intensity of the surimi gel decreased its whiteness. The whiteness of the surimi gel increased with time when the DPCD treatment conditions were 20 MPa and 50 degC in the range of 10-60 min (p < 0.05). This was because increasing the treatment time intensified the surimi gelation. However, when the time was in the range of 60-70 min, there was no significant change in the whiteness of the surimi gel, indicating that surimi gelation was largely complete at 60 min . 3.2. Effect of Different DPCD Treatments on the Water-Holding Capacity of Surimi Moisture content is a key factor affecting the quality of surimi, accounting for 73-80% of its weight. The amount of moisture will directly affect gel formation . The water-holding capacity (WHC) is an important indicator of the moisture content of surimi and the formation of a gel structure . As shown in Figure 3, the WHC of the surimi gel decreased significantly (p < 0.05) in both the heat treatment group and the DPCD treatment group compared to the control group. This was due to the gradual formation of the surimi gel network during the treatment process, which had a binding effect on the water within it . The WHC of the surimi peaked at a treatment pressure of 20 MPa when the DPCD treatment conditions were 50 degC and 60 min , which was significantly higher than that of the heat-treated samples. When the treatment pressure exceeded 30 MPa, the WHC of the surimi decreased significantly (p < 0.05). This could be due to two reasons. First, at 20 MPa the surimi gel formed a dense network structure and thus the WHC was optimal. However, as the treatment pressure continued to increase, the network structure of the surimi gel was destroyed and the WHC decreased. Second, CO2 has an extraction effect and during the treatment process, it removed a large amount of water from the surimi. When the DPCD treatment conditions were 20 MPa and 60 min and the temperature was in the range of 30-50 degC, the WHC of the surimi gel increased as the temperature increased (p < 0.05). This was because the increase in temperature was conducive to surimi gelation, forming a dense three-dimensional network structure to trap the water. Simultaneously, the increase in temperature enhanced the thermal motion of the CO2 molecules, facilitating their penetration and diffusion into the surimi. This also stabilised the gel structure induced by DPCD and was conducive to maintaining the WHC of the surimi gel. In the temperature range of 50-60 degC, there was no significant difference in the WHC of the surimi gel as the temperature increased, indicating that the dense three-dimensional network structure of surimi had essentially formed at 50 degC . When the DPCD treatment conditions were 20 MPa and 50 degC , and the treatment time was in the range of 10-60 min, the WHC of the surimi gel increased as the treatment time increased (p < 0.05). This indicated that there was a cumulative effect of DPCD treatment on the WHC of the surimi gel, with increasing treatment time intensifying the surimi gelation and increasing its WHC. However, when the treatment time reached 60-70 min, there was no significant change in the WHC of the surimi gel, showing that the gelation of surimi was complete by 60 min. 3.3. Effect of Different DPCD Treatments on the Water Characteristics of Surimi 3.3.1. Effect of Different DPCD Treatments on the T2 Relaxation Times of Surimi The T2 relaxation time reflects the chemical environment of the hydrogen proton, which is related to its degree of freedom and binding force . The shorter the T2 relaxation time, the greater the binding force or the smaller the degree of freedom of the hydrogen proton in the sample, and the more to the left the peak position on the T2 inversion spectrum . As shown in Figure 4, there were four peaks in the T2 inversion spectrum, with the relaxation times represented by T21a, T21b, T22 and T23. These correspond to the different states of water molecules in the surimi gel: bound water (T21a, T21b; 0.01-10 ms), immobilised water (T22; 30-100 ms) and free water (T23; >1000 ms) . There was a tendency for T21a and T21b to shift to the right as the intensity of the DPCD treatment increased, compared to the control group, and their relaxation time range increased. This could be one reason for the significant decrease in the WHC for each group of DPCD treatment samples compared to the control group . Conversely, as the DPCD intensity increased, the protein conformation of the surimi changed and the exposure of hydrophobic groups affected the hydration of the protein, resulting in an increase in the degree of freedom (T21a and T21b) . However, as the DPCD intensity increased, T22 tended to shift to the right, indicating an increase in the relaxation times of this part of the water, which reflected the macromolecular water retained in the gel. During the treatment process, the myofibrillar protein was denatured with the penetration and diffusion of CO2, which changed the state of the macromolecular water that was retained in the three-dimensional network of the gel. Thus, the degree of freedom of T22 increased significantly during the treatment process, which may be a major reason for the significant decrease in the WHC of the samples in each treatment group shown in Figure 3 . In contrast, T23 tended to move to the left as the DPCD treatment intensity increased. This indicated that the degree of freedom of free water in the surimi gradually decreased under the effect of DPCD treatment. This was due to the gradual contraction of the myofibrillar protein after denaturation to form a network structure, resulting in changes in the environment of this part of the water with the highest degree of freedom. At the same time, the gel network structure formed a certain binding capacity for free water during the treatment . 3.3.2. Effect of Different DPCD Treatments on the Different States of Water Content in Surimi The signal intensity of the T2 inversion spectrum is positively correlated with the moisture content of the sample components. Accordingly, the areas of the four peaks were calculated for each group of samples in Figure 4. The area of each peak was then expressed as a percentage of the total area, representing the percentage of moisture content in each of the different states (A21a, A21b, A22 and A23) . As shown in Figure 5, the highest moisture content in the surimi gel was A22. Compared with the control group, A22 decreased significantly (p < 0.05) and A23 increased significantly (p < 0.05) after DPCD treatment. During the DPCD treatment, the myofibrillar proteins in the surimi were denatured by the combined effects of CO2, pressure and temperature. The advanced structure was loosened, the peptide chains stretched and the water binding force was weakened. Then, the molecules aggregated and cross-linked to form a gel network with hydrogen bonds, hydrophobic interactions, non-disulphide covalent bonds, disulphide bonds, etc. This resulted in the conversion of immobile water into free water, leading to a significant decrease in A22 and a significant increase in A23 (p < 0.05) . There was no significant change in A23 as the intensity of the DPCD treatment increased (>30 MPa, >50 degC, >60 min). This was because A23 was extruded by DPCD while immobile water became free water, and the formation of a gel network bound a certain content of water so that the migration of the two water fractions reached equilibrium . Additionally, the proportion of A21a and A21b also increased significantly (p < 0.05), which may have been because DPCD treatment mainly caused the loss of free water and immobile water, while the content of bound water did not change; thus, the proportion of bound water increased. 3.3.3. Effect of Different DPCD Treatments on Magnetic Resonance Imaging of Surimi Magnetic resonance imaging (MRI) can be used to visualise the moisture distribution and migration of food. Figure 6 shows the changes in the MRI images of surimi under the different DPCD treatments; red indicates a higher hydrogen proton density and higher moisture content, while blue indicates a lower hydrogen proton density and lower water content . The MRI images of the surimi show that the red parts gradually decreased as the DPCD processing intensity increased, corresponding to a weakening of the relaxation signal. This indicated that the hydrogen proton density in surimi gradually decreased and water was continuously lost as the treatment intensity increased. This further confirmed the results of the change in moisture content shown in Figure 5. 3.4. Effect of Different DPCD Treatments on the Surimi Gel Strength Gel strength refers to the force per unit area of a gel when it disintegrates or breaks; it corresponds to the tightness of the internal structure of the gel, which is related to the denaturation of the protein . Our previous study found that surimi could be induced to form a gel by DPCD treatment through two main effects. First, the CO2 in DPCD dissolved in water to form carbonic acid, which in turn dissociated to form H+, , decreasing the pH of the system. Then, interactions with proteins occurred through hydrogen bonding and protonation. Protein molecules interacted with each other through hydrogen bonding and electrostatic repulsion, inducing the denaturation and aggregation of surimi proteins to form gels. Second, CO2 is a hydrophobic solvent that interacted with the hydrophobic groups in the surimi to induce protein denaturation and aggregation to form gels . The effect of DPCD treatment on the surimi gel strength is shown in Figure 7. Both DPCD treatment and heat treatment significantly increased the surimi gel strength compared to the control group (p < 0.05). The gel strength also increased as the intensity of DPCD treatment increased. At DPCD treatment conditions of 50 degC and 60 min and treatment pressures in the range of 5-25 MPa, the surimi gel strength increased with increasing pressure (p < 0.05). Furthermore, at DPCD treatment pressures of up to 20 MPa, the surimi gel strength was significantly better than that of the samples in the heat treatment group (p < 0.05). The increase in pressure increased the CO2 density, which in turn increased its permeation. At treatment pressures in the range of 5-15 MPa, protein depolymerisation was low and the internal polar and hydrophobic groups were not fully exposed, preventing the surimi from forming a good gel network structure. However, the surimi gel strength did not change significantly when the treatment pressure reached 25-35 MPa. This showed that when the DPCD treatment conditions were 50 degC, 60 min and 20 MPa, the surimi had formed a good gel structure. Therefore, under these conditions, increasing the treatment pressure had no significant effect on the surimi gel strength. When the DPCD treatment conditions were 20 MPa and 60 min and the treatment temperature was in the range of 30-50 degC, the surimi gel strength increased with increasing temperature (p < 0.05). Additionally, the surimi gel strength at DPCD treatment temperatures up to 50 degC was significantly better than that of the samples from the heat treatment group (p < 0.05). This was mainly due to the heat-resistant alkaline protease in the surimi, which has an optimum enzymatic activity at 50-70 degC. During heat treatment, proteases degrade myofibrillar proteins, reducing gel elasticity and strength . However, gel degradation was inhibited by DPCD-induced gel formation of the surimi at temperatures below 55 degC and by the passivating effect of DPCD on some heat-tolerant alkaline proteases. However, there was no significant change in the surimi gel strength at DPCD treatment temperatures in the range of 55-60 degC. Furthermore, when the DPCD treatment temperature reached 50 degC, the surimi gel strength was significantly better than that of the heat-treated samples (p < 0.05). This showed that a DPCD treatment temperature of 50 degC induced gel network formation at 20 MPa and 60 min; further increasing the treatment temperature did not significantly change the gel strength. The surimi gel strength increased with time when the DPCD treatment conditions were 20 MPa and 50 degC and the treatment times were in the range of 10-60 min. This was due to the cumulative effect of the DPCD treatment on the surimi gel. With increased treatment time, more CO2 molecules penetrated the surimi gels and more CO2 molecules interacted with the myofibrillar proteins, contributing to the acceleration of the gel network formation. The strength of the surimi gel was significantly better than that of the heat-treated samples (p < 0.05) when the DPCD treatment time reached 60 min, indicating that the surimi gel network had formed under these conditions and that there was no significant change in gel strength as the treatment time was further increased. 3.5. Correlation between Water Characteristics and Gel Strength during DPCD-Induced Gel Formation in Surimi To investigate the correlation between the moisture properties and gel strength during DPCD-induced gel formation in golden pompano surimi, a correlation analysis was performed between the above moisture property indicators and gel strength. The correlation heat map was colour-coded with different intensities of blue and red, with blue indicating a negative correlation, red indicating a positive correlation and the intensity of the colour expressed by the Pearson correlation coefficient (P). Depending on the magnitude of P, the correlation was classified as weak (0.0-0.19), medium (0.2-0.6), or strong (0.6-0.1) . As shown in Figure 8, water-holding capacity, A21a, A21b, A23, T21a, T21b and T22 were strongly positively correlated with gel strength, while A22 and T23 were strongly negatively correlated with gel strength. As the major component of water in surimi, A22 corresponds to a degree of water mobility that is second only to free water as a layer of immobile water. The decrease in its proportion was to some extent indicative of the overall decrease in water in the surimi gel. Meanwhile, the denaturation of the proteins during gel formation resulted in changes to their hydration, so the increased gel strength inevitably also led to a loss of this water . As the component with the longest relaxation time, T23 corresponds to water molecules with a high degree of freedom. As an increase in gel strength means the formation of a three-dimensional gel network, the gel network has a certain binding effect on this part of the water, decreasing the relaxation time. 4. Conclusions This study showed that DPCD treatment induced gel formation in pompano surimi. Compared to the control group, DPCD treatment had a significant effect on the quality of the surimi gel, yielding a superior product compared to the samples in the conventional heat treatment group. LF-NMR showed that, after DPCD treatment, the relaxation component T22 of surimi shifted to the right, T23 shifted to the left, A22 decreased significantly (p < 0.05) and A23 increased significantly (p < 0.05). Correlation analysis showed that the water-holding capacity of surimi was strongly positively correlated with gel strength, while A22 and T23 were strongly negatively correlated with gel strength for all DPCD treatment conditions. Therefore, water-holding capacity, A22 and T23 can be used as useful indicators to evaluate the changes in gel strength associated with DPCD-induced gel formation in pompano surimi. In future research, a new and rapid gel quality evaluation technique could be developed by modelling based on these moisture characteristics. On this basis, the correlation between gel strength and other microscopic or molecular properties could also be investigated, thereby achieving the rapid and efficient evaluation of surimi gel quality. Author Contributions Conceptualization, W.D. and S.L.; methodology, W.D.; software, W.D. and H.Q.; validation, Z.W. and Q.X.; formal analysis, H.Q.; investigation, K.K.H. and H.Q.; resources, Q.S.; data curation, S.W.; writing--original draft preparation, W.D.; writing--review and editing, W.D.; visualization, Z.H.; supervision, Y.L.; project administration, S.L.; funding acquisition, S.L. 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 datasets generated for this study are available upon request to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 DPCD processing unit diagram (A) and mold drawing (B): colorful balls is dense phase carbon dioxide. Figure 2 Effect of different DPCD treatments on surimi whiteness (A): Pressure, (B): Temperature, (C): Time. Different letters indicate statistically significant differences (p < 0.05). Figure 3 Effect of different DPCD treatments on the water holding capacity of surimi (A): Pressure, (B): Temperature, (C): Time. Different letters indicate statistically significant differences (p < 0.05). Figure 4 Effect of different DPCD treatments on the T2 relaxation time of surimi (A): Pressure, (B): Temperature, (C): Time. Figure 5 Effect of different DPCD treatments on the different states of the water content in surimi (A): Pressure, (B): Temperature, (C): Time. Different letters indicate statistically significant differences (p < 0.05). Figure 6 Effect of different DPCD treatments on MRI of surimi (A): Pressure, (B): Temperature, (C): Time. Figure 7 Effect of different DPCD treatments on the surimi gel strength (A): Pressure, (B): Temperature, (C): Time. Different letters indicate statistically significant differences (p < 0.05). Figure 8 Correlation between water characteristics and gel strength during DPCD-induced gel formation in surimi (WHC: water-holding capacity, A2b1, A2b2, A21, and A22 represent the contents of strongly bound water, weakly bound water, immobilised water, and free water, respectively, T21a, T21b, T22 and T23 represent strongly bound water, weakly bound water, immobilised water, and free water, respectively). 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PMC10000428 | Cancer-induced bone pain (CIBP) is a common and devastating symptom with limited treatment options in patients, significantly affecting their quality of life. The use of rodent models is the most common approach to uncovering the mechanisms underlying CIBP; however, the translation of results to the clinic may be hindered because the assessment of pain-related behavior is often based exclusively on reflexive-based methods, which are only partially indicative of relevant pain in patients. To improve the accuracy and strength of the preclinical, experimental model of CIBP in rodents, we used a battery of multimodal behavioral tests that were also aimed at identifying rodent-specific behavioral components by using a home-cage monitoring assay (HCM). Rats of all sexes received an injection with either heat-deactivated (sham-group) or potent mammary gland carcinoma Walker 256 cells into the tibia. By integrating multimodal datasets, we assessed pain-related behavioral trajectories of the CIBP-phenotype, including evoked and non-evoked based assays and HCM. Using principal component analysis (PCA), we discovered sex-specific differences in establishing the CIBP-phenotype, which occurred earlier (and differently) in males. Additionally, HCM phenotyping revealed the occurrence of sensory-affective states manifested by mechanical hypersensitivity in sham when housed with a tumor-bearing cagemate (CIBP) of the same sex. This multimodal battery allows for an in-depth characterization of the CIBP-phenotype under social aspects in rats. The detailed, sex-specific, and rat-specific social phenotyping of CIBP enabled by PCA provides the basis for mechanism-driven studies to ensure robustness and generalizability of results and provide information for targeted drug development in the future. bone cancer pain home cage rodent-specific behavior EU GrantELAC2015/T07-0713 Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq, Brazil)#ELAC2015/T07-0713 443180/2016-4 309633/2021-4 This research was funded by the EU Grant to EPZ and NB: ELAC2015/T07-0713. WAVJ: Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq, Brazil) (#ELAC2015/T07-0713, #443180/2016-4 and #309633/2021-4). pmc1. Introduction Bone metastases are one of the most common complications in patients with advanced cancer, and pain is the main and most devastating symptom . Cancer-induced bone pain (CIBP) is usually high, can occur at rest, increases under certain conditions and is associated with a significant impairment of patients' quality of life . Interestingly, common analgesics are only partly able to reduce pain and pain-related symptoms and side effects are common; radiation therapy might help but is also limited in efficacy. More specific analgesics targeting the specific mechanisms of CIBP are currently missing. Consequently, the mechanisms underlying CIBP are increasingly studied in preclinical animal pain models . Based on pathophysiological findings, CIBP appears to have unique features and must be distinguished from other cancer-induced and chronic pain states , which are embedded in disease and treatment classification . However, how these cancer-related features and mechanisms relate to pain and pain-related symptoms relevant for the QoL in patients is currently unclear. Although preclinical pain research is improving, widely used animal models and the currently applied phenotyping approaches have been criticized . Behavioral phenotyping of different pain entities, including CIBP, is based mainly on evoked, reflexive withdrawal methods . Although well-established and standardized, they have endpoints based only on sensory perception and may reduce the complex clinical reality to one feature, limiting their clinical value. . Additionally, factors that have been shown to influence the outcome of these behavioral tests, such as testing rodents in light periods, the presence of an experimenter, or the experimenter's gender, may limit the internal and external validity of findings . Recent clinical interventions use multidimensional therapeutic approaches and aim to restore daily life activities without decreasing physiological sensory perception to external stimuli. Furthermore, pain states always have a social dimension , not reflected by evoked pain assessments. This mismatch between preclinical research and clinical application critically contributes to a lack of efficient translational pain research and therefore needs to be bridged . Novel behavioral assays that detect clinically relevant symptoms of different pain entities are vastly underrepresented, and only a few studies show a multimodal approach to examining pain-associated behaviors . This problem is also present in CIBP research . In the past two decades, novel, video-based assays have been developed to address (1) functional aspects, such as pain-related changes in gait patterns , (2) non-evoked pain- (NEP) related behavior , or (3) changes in rodent-specific complex behavior (e.g., resting, ambulatory, social, and pain-related behaviors) . In this context, monitoring behavior in home-cage settings seems promising to broaden behavioral studies and investigate the animals within their familiar environments. In this way, the physical contact between the animals and human experimenters is reduced, thereby minimizing any direct experimenter effects . At the same time, it might become possible to detect more subtle behavioral changes that indicate pain-related behavior in more detail and/or with more reliability . To bridge the translational gap in CIBP, we combined traditionally used, reflex-based withdrawal assays with mechanical and heat stimuli with video-based approaches for non-evoked pain-related behavior in both sexes. Additionally, we analyzed the complex rat-specific behavior of chronic CIBP in a video-based home-cage setting to identify pain phenotypes for the first time in unprecedented detail. We used a highly efficient and well-described CIBP model in rats by using Walker 256 mammary carcinoma cells inoculated into the tibia. We hypothesized that in addition to the known changes in reflex-based pain-related behavior in both sexes, an antalgic gait, non-evoked pain, and changes in complex rat-specific behavior develop time-dependently due to the induction of a bone tumor and its progression. By integrating multimodal datasets, including home-cage observation, we detected previously unknown sex differences in the CIBP phenotype and behavioral changes in cancer and sham animals relative to the bystander. This will help to improve future mechanism-driven research that can ensure imprinted robustness and generalizability of results and ultimately inform target-specific drug development. 2. Materials and Methods The experiments in this study were reviewed and approved by the Animal Ethics Committee of the State Agency for Nature, Environment, and Consumer Protection North Rhine Westphalia (LANUV, Recklinghausen, Germany; 84-02.04.2017.A055). We reported on the study details according to the ARRIVE guidelines 2.0 and were in accordance with the ethical guidelines for investigating experimental pain in conscious animals . 2.1. General Male and female Sprague-Dawley (SD) rats (total n = 114 rats, age: 6-7 weeks, weight males: 280.1 +- 7.8 g (Mean +- SD), weight females: 192.3 +- 5.3) were kept in a 12/12 h day/night cycle with ad libitum access to food and water under conventional conditions (FELASA guidelines) . According to their experimental group, the rats were housed in pairs. The experimental group allocation was random, and a blinded analysis of video-based behavior assessments was performed. Blinding to the withdrawal/reflex-based behavioral assays and pain model was not possible due to the testing conditions and visible signs, such as a visible tumor or a guarding behavior of the cancer-bearing limb of CIBP. Finally, the animals were euthanized by decapitation under deep isoflurane anesthesia at the end of the observation period of 18 days. 2.2. Culture of Walker 256 Cells Walker 256 mammary gland carcinoma cells (Cell Resource Centre for Medical Research at Tohoku University (CRCTU), Sendai, Japan) were cultured in a 20 mL medium containing RPMI 1640 (Sigma-Aldrich, Steinheim am Albuch, Germany), antibiotic antimycotic solution (100x) (Sigma-Aldrich, St. Louis, MI, USA), glutamine (Merck, Rahway, NJ, USA), and fetal bovine serum (FBS, Capricon Scientific, Ebsdorfergrund, Germany). For the preparation of the medium, a standard bottle (500 mL) RPMI and 5 mL antibiotic antimycotic solution (100x), 5 mL glutamine solution, and 50 mL FBS solution were mixed and dispensed to the culture bottles. When 80% confluence was achieved, the cells were transferred to a new culture flask. This was done twice a week under the above conditions. To generate a sham group, those cells dedicated for inoculation in sham animals were separated and heat deactivated (10 min/95 degC). To ensure that heat deactivation was successful, a sample of heat-deactivated cells was re-cultured and checked for (the absence of) cell proliferation over two days after deactivation. Heat deactivation functioned in every case, eliminating the need to exclude any sham animals due to methodological deficiencies. Cells of passage 15-20, starting from the supplied cells from the cell bank, were used for inoculation. 2.3. Pain Model: Cancer-Induced Bone Pain (CIBP) Any surgery was performed on the right hindlimb of rats. Rats were initially anesthetized with 5% isoflurane in 100% oxygen; anesthesia was maintained with 1.5-2.0% isoflurane delivered through a nose cone during the whole procedure. To minimize the wound pain caused by skin incision, Metamizole (Vetalgin(r) 500 mg/mL, MSD Tiergesundheit, Friesoythe, Germany) was administered subcutaneously (100 mg/kg BW) 30 min in advance of the surgical procedure. After anesthesia and analgesia were established, the surgical area was shaved and disinfected by the use of Betadine(r) (Aviro Health, Cape Town, South Africa). For inoculation with Walker 256 cells , a skin incision of 1 cm above the right knee joint was made with a scalpel (No. 11, 0.5 cm), and the proximal tibial bone was displayed. Using a 23 G needle, a hole was drilled into the right tibial epiphysis to access the intramedullary space. Afterward, the needle was removed and replaced by a Hamilton syringe that contained the cell suspension (4 x 105 Walker 256 cells in 10 mL Hank's solution). Next, the cell suspension was injected into the intramedullary space of the right proximal tibia. The syringe remained inside the bone for two minutes after each cell injection to ensure that the cell suspension would not leak out of the intramedullary space right after inoculation . After removing the syringe, the hole was closed with bone wax (SMI, St. Vith, Belgium). The skin incision was sutured with a mattress suture of 7-0 Prolene(r) (Ethicon, Raritan, NJ, USA). Finally, the skin wound was disinfected with Betadine(r) again. Sham (inoculation of heat-deactivated cancer cells) and Naive rats (received Hank's solution only) were used to control the cancer cell inoculation . 2.4. Multidimensional Assessment of Pain-Related Behaviors Reflex-based withdrawal behaviors for hypersensitivity assessment of the ipsilateral hind paw 2.4.1. Paw Withdrawal to Von Frey Filaments (PWT) The ascending stimulus method determined the punctate paw withdrawal threshold (PWT) by application of calibrated Semmes-Weinstein von Frey filaments (Bioseb, Vitrolles, France; 14, 20, 39, 59, 78, 98, 147, 255, 588 mN bending force) to the plantar side of the right hind paw . Rats were placed on a mesh grid, and covered by a transparent plastic box (dimensions 15 x 20 x 10 cm, H x W x H). After a habituation period of 15 min, the filaments were applied in ascending order until the occurrence of withdrawal responses or reaching of the cutoff limit of 588 mN. If so, 588 mN was regarded as PWT. The median force of three trials leading to a response was considered as the PWT to mechanical stimuli. 2.4.2. Paw Withdrawal Latency to Heat (PWL) The paw withdrawal latency (PWL) to heat was explored using a Hargreaves box (IITC Life Science Inc., Woodland Hills, CA, USA) . Here, rats were placed on a pre-warmed glass plate (30 degC), covered by transparent plastic boxes (dimensions 15 x 20 x 10 cm, H x W x H) . After 15 min of habituation, a radiant heat source was applied to the plantar aspect of the right hind paw. The intensity of the halogen lamp was adjusted to 17%. The latency to hind paw withdrawal was measured with a cutoff time set to 20 s. Five trials with 5-10 min intervals were performed to calculate the mean PWL to heat stimuli. 2.5. Voluntary Pain-Related Behaviors 2.5.1. Non-Evoked Pain Assessment (NEP) Non-evoked pain was determined by comparing the weight-bearing (print area) of the affected (ipsilateral) and non-affected (contralateral) paw at rest . For this purpose, we adapted the NEP for mice to rats. Briefly, rats were separately placed in transparent boxes (dimensions 15 x 20 x 10 cm, H x W x H) on a 1-cm-thick and green light-illuminated glass plate. The boxes were covered by a slim LED panel (illuminated in red) to enhance contrast. Without prior habituation, images of the footprints of rats were captured at intervals of 30 s for a total period of 10 min. The areas of illuminated footprints of both hind paws were blindly determined on 10 different pictures for each rat using ImageJ . The ratios of ipsilateral to contralateral illuminated hind paw areas were calculated for each time point and averaged for every animal. The image selection was based on predefined exclusion criteria, such as visible grooming, rearing, or an unsharp hind paw due to movement. The reduction in area ratios represents the degree of guarding behavior of the affected limb at rest. 2.5.2. Movement-Evoked Pain Assessment (MEP) Movement-evoked pain was assessed using the commercial CatWalk XT System (Noldus Information Technology, Wageningen, The Netherlands) . Only completed runs within the defined velocity range between 10 and 20 cm/s with a speed variance <60% were accepted as passed runs and included in the analysis. These inclusion criteria ensured comparability across all trials. The individual footprints were visualized by green light emitted into the glass plate on which the rats were running. Runs were recorded by a high-speed camera (100 fps) underneath the plate. Subsequently, three passed runs for each rat and time point were semiautomatically analyzed for two selected static (print area and stand duration) and dynamic (swing speed and stride length) gait parameters, which changed in different unilateral pain models by use of the CatWalk XT software:Print area: area of the whole paw Stand duration (s): duration of ground contact for a single paw Swing duration (s): duration of any swing cycle of a single paw Swing speed (cm/s): rate at which a paw is not in contact with the glass plate 2.5.3. Home-Cage Monitoring (HCM) Pairs of rats were kept in custom-made cages for HCM over the whole observation period. HCM cages have been designed in cooperation with the technical workshop of the faculty of medicine of the WWU (Munster, Germany). They were designed according to the dimensions of the "SEALSAFE PLUS Rat-GR1800 DOPPELDECKER" (Tecniplast, Hohenpeissenberg, Germany) (2 levels, 3D enrichment, internal height of 38 cm, 1800 cm2 volume). As they were built of entirely transparent material, video recording via two cameras for night observations (the first two hours in the dark phase) was possible both from the top and in front of each cage . Videos were collected in an automated fashion and randomized to experimenters. Two blinded experimenters observed and rated videos using a specific ethogram and INTERACT software (Mangold International GmbH, Arnstorf, Germany) and finally statistically analyzed them. The specific ethogram depicts a wide range of individual (e.g., food/water intake, bipedal stance (BS)) and social (e.g., social resting (SR)) behaviors of rats kept under home-cage conditions. 2.6. microCT Visualization The contralateral tibiae from each animal were scanned by micro-computer tomography (mCT) using a SkyScan 1176 (Bruker, Kontich, Belgium) after euthanization. Scans were performed at an isotropic resolution of 8.9 mm with a source voltage of 65 kV and a source current of 385 mA. Images were obtained at an angle shift of 0.5deg with a 1.065 s exposure time using a 1 mm aluminum filter. To reduce artifacts, three pictures per angle were averaged. Pictures underwent axial reconstruction using the NRecon software (Bruker, Kontich, Belgium) for further evaluation. For scoring, shadow projections of each reconstruction were created using the CTVox software (Version number: 3.2.0 r1294, Bruker, Kontich, Belgium). Each tibia was orientated in the same manner, and the same transfer function for the opacity of the projection was used to visualize equal bone densities. Tibial projections were scored by two independent experimenters in a blinded manner to determine bone destruction. An ordinal scale has been defined in advance to represent the status of bone destruction: no morphological changes compared to the non-treated control: 1; Slight lysis of the bone without loss of integrity: 2; Moderate bone lysis with loss of the overall shape but bone fragments still connected to the main body: 3; Severe fracture of the bone with visible free bone fragments: 4. 2.7. Data Analyses The prior sample size calculation was based on the reporting effect size (2.74 standard deviations (SD), 95% confidence interval (CI)) from a systematic review and current narrative review with CIBP as a topic. PWT raw data was analyzed by nonparametric analysis, such as the Friedman test for within-group comparisons and the Kruskal-Wallis test for between-group comparisons. For PWL, NEP, MEP, and HCM behavior parameters, two-way ANOVA was used to analyze groups (to pre-value) and for between-group analysis. Multivariate behavioral data were analyzed by principal component analysis (PCA) with prior standardizations. PC selection was based on the largest eigenvalues. The first two principal components were plotted as biplots. Groups were added to the biplots for illustration but were not used during the PCA. The significance of group segregation was determined by multivariate analysis of PC loadings regarding the group with Tukey post hoc tests. Multivariate ANOVA (MANOVA) was performed to provide regression analysis and analysis of variance for multiple dependent variables by one or more factor variables or covariates. A significance level of p < 0.05 indicates significant effects. Data were analyzed by Prism software, version 8 (GraphPad, San Diego, CA, USA) and SPSS (IBM, Armonk, NY, USA). 2.8. Study Design 2.8.1. Cohort 1 Cohort 1 (n = 25 , n = 25 ) contained three different experimental groups (Naive, sham, CIBP). For all animals of Cohort 1, behavioral assessments, including PWT, PWL, NEP, and MEP were performed before (pre) and on 3, 6, 8, 14, and 17 d after surgery. After euthanization, mCT visualization was performed for all animals . 2.8.2. Cohort 2: Home-Cage Monitoring Cohort 2 (n = 32 , n = 32 ) also contained animals from every experimental group and received behavioral testing before (pre) and 17 d after surgery. Additionally, the rats of Cohort 2 received home-cage monitoring, as they were kept in pairs in HCM cages for the entire observation period. Behavior was recorded during the first two hours of the night before (pre) and on day 3, 8, and 17 after surgery. Various combinations of the experimental groups (Naive-Naive, 4 Cages; sham-sham, 4 Cages; CIBP-CIBP, 4 Cages; shamBY-CIBP, 4 Cages) were used to assess social implementations of pain states. After euthanization, mCT visualization was performed for all animals of Cohort 2 as well . 3. Results 3.1. Bone Cancer Causes Distinct Pain-Related Behavioral Trajectories in Rats of Both Sexes Unilateral inoculation of Walker 256 mammary gland carcinoma cells into the right proximal tibia was used to induce bone cancer and investigate concomitant time-related behavioral changes assessed by multiple behavioral assays in Sprague Dawley(r) (SD) rats of both sexes . Our multimodal behavioral battery included traditional, reflex-based withdrawal assays on the hind paw, and approaches to assess voluntary pain-related and complex social and voluntary behavioral measures . Reflex-based assays determined paw withdrawal thresholds (PWT) to mechanical stimulation with von Frey filaments and the paw withdrawal latencies (PWL) to heat stimuli. Voluntary pain-related behavior was assessed by a specific non-evoked pain (NEP), and movement-evoked pain (MEP) approach. Finally, rodent-specific complex behavior was determined by a home-cage monitoring (HCM) approach depicting a wide range of individual (e.g., food/water intake, bipedal stance (BS)), and social (e.g., social resting (SR)) behaviors of rats kept under home-cage conditions. Additionally, the body weight of the animals was determined to identify a possible influence of bone cancer progression on the animals' fundamental survival functions. In the end, the cancer-induced bone destruction was evaluated using a micro-computed tomography imaging (mCT) approach . To keep the interference between behavioral assays as small as possible, two separate cohorts were used: PWT, PWL, NEP, and MEP were assessed in cohort 1, while rodent-specific complex behavior in the home cage was assessed in cohort 2. Both cohorts included two control groups (naive, sham) and the cancer-induced bone pain (CIBP) group, which were examined for pain-related behavior before (pre) and at multiple time points after cell innoculation. Body weight in both sexes was unaffected by the devitalizing bone cancer in the CIBP group compared to both control groups . In CIBP rats of both sexes, PWT was significantly decreased from 6 d until up to 17 d after cell inoculation compared to the pre-value. Exclusively in females, PWT at 6 d was reduced to the pre-value in the sham group . PWL was unaffected in males but significantly decreased to the pre-value at 14 d and naive group at 14 d and 17 d in CIBP females . A withdrawal response to lower mechanical force and shorter latency in withdrawal to heat stimuli on the hind paw surface indicates a state of hypersensitivity. NEP, represented by a reduction in the ipsilateral hind paw's footprint (surface contact area) compared with the contralateral side at rest, was significantly reduced compared to the pre-value, and naive and sham control groups from 6 d in males and 8 d in females until the end of the observation period (17 d) . These reductions in the footprint area are typical signs of guarding injured limbs, also called pain avoidance behavior to mechanical weight-bearing . MEP was assessed by gait analysis of static (print area, stand time) and dynamic (swing speed, swing time) parameters. A reduced print area, stand time, swing speed, and prolonged swing time, starting from 8 d in CIBP rats of both sexes, are characteristics of an antalgic gait pattern observed in unilateral rodent pain models . However, significant print area reduction was observed in both sexes as early as 6 d. The progressive nature of bone tumor growth caused a manifestation of a bone cancer-induced pain phenotype via distinct pain modalities, including mechanical hypersensitivity, heat hypersensitivity (in females only), pain avoidance behavior, and an antalgic gait in the CIBP groups of both sexes. Next, we asked which behavioral components of this pain phenotype are most relevant to group segregation over time and whether this behavioral signature changes as bone cancer develops. First, we performed correlation analyses of longitudinal trajectories for each pain-related behavioral outcome to determine which of the eight parameters assessed exhibited coherence concerning the underlying mechanisms . The correlation analysis was applied separately for sex and experimental groups, including the modality-specific time profiles. Significant correlations were determined for PWT and NEP with all MEP parameters in females, and PWT with NEP and the static parameters of MEP together with swing time in male CIBP animals . Interestingly, PWL only showed a positive correlation with NEP and stand time in CIBP females. In sham rats, a significant positive correlation was determined for PWT and print area in males and a negative correlation for swing speed and swing time in females. Second, we performed two-dimensional principal-component analyses (PCA) to determine distinct factors that are primarily responsible for group segregation for each time point . Principal-component (PC) scores and loadings revealed that no significant group segregation occurred in either sex before and 3 d post cell inoculation, as represented by unidirectional loadings and evenly distributed variance across both components . In 6 d post-cell inoculation, CIBP males showed significant segregation from sham and naive groups, mainly along with the first principle component (PC1), as determined by a positive correlation between PWT, NEP, and print area (static gait parameter), associated with a negative direction for PWL. Progressive group segregation, driven by a positive correlation between PWT, NEP, and static and dynamic gait parameters (print area, stand time, swing speed), was established from 8 d for CIBP animals of both sexes. Except for PWL, swing time was negatively correlated to all parameters. The (negative and positive) correlations between gait parameters were representative of an antalgic gait pattern. PCA revealed a male phenotype characterized by mechanical hypersensitivity and an associated antalgic gait and guarding behavior beginning on 6 d. A similar phenotype, with additional PWL amounting to significant group segregation, could be identified in CIBP females from 8 d on. 3.2. Cancer-Induced Bone Destruction Is Associated with Pain-Related Behavior Next, we wondered to which extent bone destruction, as a morphological outcome of bone cancer, is associated with the pain phenotype and whether sex-specific differences are present. Bone morphology was assessed 17 d post-cell inoculation by post-mortem mCT images with a double-independent and blinded scoring . We chose post-mortem imaging since recurrent anesthesia for longitudinal mCT scans represents a potential confounding factor for behavioral outcomes because of the potential for alteration of neuronal activity . As a degree of agreement among independent raters, the inter-rater reliability (ICC) score was k = 0.972 for bone destruction (k was calculated according to guidelines from Cicchetti and Sparrow , 0.0 = poor to 1.0 = excellent). Significant bone destruction and positive correlation with all parameters, except PWL and body weight, were identified in both sexes 17 d post inoculation . PCA analysis revealed that the bone score significantly segregated controls from the CIBP group and is negatively correlated with pain-related behavior outcomes, except for swing time and body weight in both sexes and PWL in males . Comparing both sexes revealed two main clusters in the direction of PC1, which were segregated by pain phenotype and bone destruction . On the PC2 axis, these clusters were sex-specifically segregated by the presence of PWL in females and the higher body weight in males. The correlation between radiologically determined bone destruction, as a sign of progenerated bone cancer, and pain phenotype (e.g., PWT, PWL, NEP) underpinned a causality for the CIBP phenotype and bone destruction in both sexes at 17 d post-cell inoculation. 3.3. Bone Cancer Alters Rodent-Specific Complex Behavior in Rats of Both Sexes in a Home-Cage Setting The rats showed an ipsilateral pain phenotype, characterized by mechanical hypersensitivity, hind paw guarding, and an antalgic gait pattern in both sexes, induced by a tibial bone tumor. This raises the question of to what extent CIBP alters complex rat-specific behaviors and whether other measurable behavioral parameters, e.g., social interaction, might be sensitive to pain states as well. Therefore, we assessed rat-specific behavior in the second cohort of animals in a home-cage environment. Chronic pain states alter human activity profiles. Therefore, it is reasonable to examine the effects of CIBP on the specific complex behavior of rats under home-cage conditions without external influences during two hours at the beginning of the dark phase of the light cycle . In our video-based home-cage monitoring setup, two independent investigators rated resting behavior (i.e., individual and social resting behavior), ambulatory behaviors (bipedal stance, jump to 1st floor), aspects of social (allogrooming), and pain-related behavior (e.g., ipsilateral grooming) in a blinded manner (Table S2). Two rats of the same sex and various combinations of the three experimental groups were housed in a home cage. Our approach included housing equally treated animals (naive-naive, sham-sham, CIBP-CIBP) but also combined sham-treated with CIBP animals to investigate the social transfer of CIBP (see below). As with the assessment of mCT images, the inter-rater reliability of the two independent and blinded raters and thus the ICC for the respective behavioral categories was determined. The ICC for the different parameters is in the excellent range (0.75-1.00) (Table S3). Individual resting was not affected by the housing combinations in sham-sham and CIBP-CIBP animals of both sexes compared with the pre-value . Male rats in the naive-naive group showed significantly decreased individual resting at 8 d and 17 d compared with the pre-value. The duration of social rest was higher for females in the control groups than for males but was significantly different from males in the sham-sham combination at 3 d only . In the CIBP-CIBP group, social resting increased with time in both sexes, reaching the significance level of the pre-value at 8 d only in males. Total resting time in the observed two-hour interval varied around 50%, except for a significant increase in the CIBP-CIBP group in both sexes, compared with the pre-value (8 d in males, 8 d and 17 d in females) . The bipedal stance was significantly decreased in CIBP-CIBP at 8 d and 17 d for males and 17 d for females . Jumping to the 1st floor was unaffected for the most part but significantly reduced in sham-sham at 3 d and CIBP-CIBP at 8 d . Self-grooming activity was unaffected by either bone cancer or housing conditions . A sex-specific significant difference in food intake was detected in the naive-naive group (pre, 3 d, 8 d) and the sham-sham group (pre) . Social playing behavior is one of the earliest forms of non-mother-directed social behavior observed in mammals and has been observed to contain behavioral patterns related to social, sexual, and aggressive behavior with a high reward value . Playing behavior was unaffected over the whole observation period in the sham-sham group in both sexes . In males, playing behavior was significantly decreased in the naive-naive group at 3 d, CIBP-CIBP group at 8 d and 17 d, and mixed housing group at 17 d, compared with the pre-value. A similar trend was observed in the corresponding female groups. Allogrooming (i.e., grooming of the partner rat) was only significantly reduced in the CIBP-CIBP group at 17 d compared with the pre-value. Grooming, or licking the affected side, is discussed as a surrogate behavior of spontaneous (non-evoked) pain in different rodent pain models , but was not observed under our experimental conditions . Again, the question arose as to which parameters from the home-cage observation drove possible group segregation and which were redundant. Therefore, PCA was performed for each time point to detect a linear correlation in both sexes . CIBP-CIBP males were characterized by increased individual and total resting time (and ipsi-grooming), reduced bipedal stance, jumping, and allogrooming. 3.4. Social Transfer of Pain-Related Behavior from CIBP Rats to Sham Bystanders and Alterations in Complex Behavior Caused in Both Sexes Recently, a phenomenon called "social transfer of pain" in male rodents has been characterized. This term describes the emergence of pain-related behaviors in sham-treated bystander rats (shamBY) following social interaction with a cage mate experiencing pain . We hypothesize that such transfer of pain-related behavior also occurs when one rat bears a bone tumor (CIBP) and the other is shamBY. Furthermore, the transfer should also be detectable in females and reflected by changes in complex behavior in shamBY rats. Therefore, we investigated whether there was a transfer of behavior from CIBP rats of both sexes to shamBY-animals and which behaviors were affected. Mixed housing resulted in significant hypersensitivity to mechanical stimuli , but not to heat , in both paws of shamBY rats of either sex, compared to equal sham-sham housed animals . In contrast to shamBY rats, no significant mechanical hypersensitivity of the ipsilateral limb could be detected in sham or naive rats. Equal housing of CIBP rats (CIBP-CIBP) caused ipsilateral but not contralateral mechanical hypersensitivity in both sexes. NEP was observed in CIBP rats of both sexes but not in shamBY rats at the ipsilateral site . Individual resting was significantly increased compared to the pre-value at 17 d post-cell inoculation in CIBP males housed with a shamBY and vice versa . Mixed female cage mates showed a similar, but non-significant trend in individual resting compared with the pre-value. Social resting was significantly reduced at 8 d and 17 d in males and for shamBY-CIBP combinations at 17 d in females, compared with the pre-value . Total resting was decreased in the female shamBY-CIBP group to the pre-value and to that in males . As with the CIBP-CIBP rats, the CIBP-shamBY group shows a reduction in bipedal standing of tumor-bearing rats in both sexes . In contrast to the sham-sham group, jumping was significantly increased in shamBY at 3 d in males. Ipsilateral grooming of the tumor-bearing site was significantly increased at 8 d in CIBP-shamBY females. In the mixed housing groups, the question emerged as to which of the two animals initiated social vs. individual rest phases. Therefore, we investigated how often CIBP rats approached shamBY rats over time and vice versa . No significant changes were observed in this behavior for both sexes. Although multidirectional loadings in PCA analysis were present, significant group segregation of tumor-bearing animals (CIBP) and shamBY from sham was detected in females at 8 d and 17 d, and in males at 3 d, 8 d, and 17 d . Strikingly, the shamBY rats significantly differed from the sham-sham husbandry in males from 3 d and significantly in females from 8 d . PCA analysis of combined pain-related (which can be measured separately on both hind paws) and complex behaviors revealed that shamBY males are characterized by a mechanical hypersensitivity of both paws and reduced playing behavior along the PC1 axis, combined with increased individual resting (PC2) . In contrast, the shamBY females were determined by increased playing behavior and decreased social and total resting . The CIBP males, regardless of the housing combinations (CIBP-CIBP, CIBP-shamBY), were significantly distinguished from the controls by a higher ipsilateral bone score (PC1) and a reduction in playing behavior, bipedal stance, jumping to the 1st floor, and PWT of the ipsilateral paw. CIBP females differed significantly from controls by pronounced bone destruction, increased playing behavior, and individual resting. Just like in CIBP-CIBP males, mechanical hypersensitivity (PC1) and decreased ambulatory behavior along the PC2 axis were observed. 4. Discussion In this study, we combined traditional reflex-based assays with rodent-specific complex behavior assessments to comprehensively phenotype a clinically relevant pain model for cancer-induced bone pain (CIBP) in rats of both sexes. CIBP in rats leads to a distinct CIBP-related phenotype, including (1) mechanical hypersensitivity of the ipsilateral hind paw, (2) non-evoked CIBP-related behavior (3), and antalgic gait pattern in both sexes. Heat hypersensitivity was associated only with female tumor-bearing rats. Progression of tumor growth causes CIBP phenotype clustering beginning at 6 d after cell innoculation in males and 8 d in females. Furthermore, intra-tibia tumor development generates bone destruction, correlating with the pain-related phenotype but not with the alterations in body weight of both sexes. Rodent-specific complex behavior analyses revealed both sexes' social and ambulatory cancer-induced behavior alterations. In mixed housing conditions (shamBY-CIBP), the prevalence of social-resting behavior shifted towards individual resting. Furthermore, mechanical hypersensitivity of both hind paws of shamBY rats occurred in both sexes without a radiological diagnosis of bone cancer. This hypersensitivity is indicative of a social transfer of CIBP-related behavior from tumor-bearing rats to the shamBY. 4.1. Bone Cancer Causes a Sex-Specific Pain Phenotype Associated with Bone Destruction Studies of CIBP using different rodent models are increasingly performed . However, preclinical pain research, in general, has been criticized because many models and methods used for phenotyping appear to be artificial and only partially representative of the clinical situation, leading to a translational gap . Assessing multimodal pain-related behaviors is a topic of ongoing debate in pain research, with the prevailing view that multiple modalities must be analyzed to address pain as a multidimensional phenomenon and bridge the translational gap of rodent pain research . Furthermore, preclinical pain phenotypes in rodents are determined by a limited number of modalities using traditional stimulus-evoked assays with withdrawal responses of hind limbs based as endpoints, mainly in male animals . In contrast, a multimodal approach to treat CIBP is crucial in the clinical setting . To mimic the clinical situation for CIBP, we inoculated Walker 256 rat breast gland carcinoma cells intratibially in rats of both sexes. For the generation of this CIBP model, to create a distinct pain phenotype, we considered, firstly, to minimize the severity for the animals as far as possible and; secondly, to use a donor cell bank to reduce in vitro cell phenotypic changes during passage and avoid extensive cell culture amplification ; and, finally, to use a well-defined cell number for inoculation. These are essential parameters for the generation of the CIBP model . This CIBP model is characterized by less interlaboratory variability, absence of metastases to other bones, CIBP-related behavior in rats of both sexes, and tumor progression independent of age, weight, and the estrous cycle. The typical observation time in this model ranges from 8-to-18 days post-cell innoculation to minimize the severity and address ethical trade-offs . Multimodal pain-related behavioral approaches in both sexes using this CIBP model are scarce but urgently needed. In particular, the further development of novel behavioral methodologies using video assessments to, for example, reduce experimenter bias and acknowledge that pain states might lead to changes in complex rodent behaviors, is needed . Recent findings regarding the social transfer of pain states in this and other pain entities represent essential cornerstones for study planning and performance in the future. Multimodal assessment and multivariate analysis of extensive complex behavioral data sets allow detailed insight into the underlying mechanisms and define pain entity-dependent phenotypes. Additionally, identifying redundant and, therefore, replaceable pain-related behavior assays, especially for evoked assays (direct interaction with the animal by the experimenter), is essential for the refinement of future study designs to avoid unnecessary animal stress and maximize clinical evidence . A detailed and, especially, multidimensional pain phenotyping allows for the classification of the model in terms of its clinical relevance and, thus, its "value" for translational research. On the other hand, both desired effects through, e.g., pharmacological interventions, such as the reduction of non-evoked pain, and undesired ones (side effects) can be identified in the pain-related phenotype context. We observed stable development of ipsilateral mechanical hypersensitivity, guarding behavior (non-evoked), and antalgic gait pattern, but no body weight reduction in rats of both sexes. These results are consistent with other studies, although there are contradictory results on body weight, depending on methodological aspects such as cell concentration, species, strain, sex, housing conditions, and observation duration . Additionally, there are sex-dependent contradictory results for heat hypersensitivity . We did not detect heat hypersensitivity in male rats; however, detection was evident during the late tumor progression phase in females. Reasons for this may be found at different experimental levels indicating that the detection of heat hypersensitivity does not represent a meaningful behavioral outcome in this CIBP model . Tumor progression is also associated with sensory nerve sprouting , and the extent to which this is related to the development of heat hypersensitivity remains unclear. Sex differences also exist in the onset of pain phenotype expression in tumor-bearing rats. A CIBP-related phenotype can be observed in males from 6 d and females from 8 d, which may be caused by a sex-dependent release of lipoxins and endogenous lipoxygenase-derived eicosanoids . Direct evidence to explain this difference in the development of CIBP-related phenotypes is not yet available, but it provides support to the hypothesis that pain phenotypes are sex-dependent . Osteolysis caused by bone cancer is one of the essential macroscopic findings in animal studies of CIBP . Here, we were able to identify a direct relationship between bone destruction and the CIBP-related phenotype, but not for body weight in both sexes. Despite the clear findings of radiological bone destruction and behavioral changes due to pain states, no effects on physical development were detected, calling the impact of CIBP on food intake into question; which rodent-specific complex behavior is modulated by CIBP in the first place and are cagemates and sex possible variables influencing the outcome? 4.2. Social Interaction with a Cage Mate Suffering from CIBP Alters Rodent-Specific Behavior We developed a housing environment with additional structures and vertical spaces to assess the complex behaviors of rats within their familiar home cage. The home cage was built to serve basic physiological and behavioral rodent needs, including resting, grooming, exploring, or engaging in a range of social activities (play or allogrooming) . Dependent on housing conditions, rat behavioral patterns were altered by bone tumor progression. Thus, we showed that social resting was increased, but ambulatory behaviors (e.g., bipedal stance) were reduced in both sexes. Furthermore, a significant decrease in social behaviors associated with physical activity, such as playing or allogrooming, was observed in males. In all behavioral categories, the trajectories of females are comparable to those of males, except for allogrooming. The reasons may be manifold: the tumor-related behavioral changes occur later in females, indicating different mechanisms for developing the tumor itself and, consequently, the CIBP-related phenotype. Sex-specific fundamental differences in neuro-immune pathways play a role in acute and chronic pain states but have not been studied in depth for CIBP in both sexes . Pain-related behaviors, such as excessive grooming or licking of the tumor-bearing leg, are only occasionally observed here. Reasons for this may be that there is no acute nociceptive pain or acute skin injury, and extensive licking of the skin in this chronic CIBP model is not beneficial or necessary for the animal . Furthermore, chronic pain conditions are very energy-consuming, so reducing or altering behavior, especially play, exploration, courtship, and mating, prevent re-injury and ensures that resources are initially reserved for defense, which seems reasonable from an evolutionary perspective . Social interaction is characterized by the exchange of signals and adaptation of sensory and emotional states of the object. These conserved evolutionary behaviors have also been identified in rodents . Rodent studies demonstrated that a rapidly adopting sensory-affective mechanism exists in an animal housed with a diseased cagemate of the experimental group, regardless of the valence of the information (pain, fear, or pain relief) . Furthermore, this effect is independent of whether the pain is acute, nociceptive, or chronic. There is evidence that rodents show empathy-like behavior, which might deliver an evolutionary advantage since, among other effects, empathic behavior in social contexts seems to reduce pain perception . For the first time, we demonstrated a social transfer of pain-related behavior (here, mechanical hypersensitivity) caused by CIBP in rats of both sexes. Presentation of CIBP-related behavior to an unaffected conspecific cagemate of the same sex, here a shamBY rat, leads to their adoption of sensory-affective states expressed by bilateral mechanical hypersensitivity in the absence of radiological signs of bone destruction. Speculatively, the ultimate reason for this hypervigilance state could be that an increased willingness to adopt fight-or-flight behavior is necessary to protect one's own and group-relevant resources by activating the defense cascade . How the transfer of sensory and affective states to conspecific unaffected cagemates occurs in CIBP can only be speculated. In other acute and chronic rodent pain models, the transfer was triggered by social signals such as ultrasound vocalization or pheromone release . Therefore, it can be assumed that similar dissemination in CIBP might exist. 4.3. Limitations of the Study In this study, we use an established animal model in rats to identify a sex-specific pain-related phenotype of bone cancer. The limitations here are the small group size of shamBY rats in home-cage analyses, which shows an altered phenotype. However, these results provide a first indication of social pain transfer in this bone cancer model, the mechanisms of which should be the subject of further investigation. 4.4. Implications for Study Planning and Severity Assessment in CIBP The study findings can be discussed in light of two additional aspects: (1) the study design of animal experiments and (2) the question of how to assess the severity of experimental procedures. With respect to the former, our video observations showed that the composition of cagemate pairs could directly influence sensory-affective parameters. Additionally, social transmission of pain was observed, which needs to be addressed systematically in the study design to avoid any biases on the experimental and analysis level. More specifically, this could either mean separating pain groups from control groups or systematically including these mixed groups in the study design . Besides this, using video approaches offers several additional advantages: (1) Video observations are carried out within the familiar home-cage environment of the experimental subjects, and, hence, the recordings can cover species-relevant times (e.g., night-time for rodents). (2) The direct influence of the experimenter and handling-related stress is reduced. (3) Video observations allow tracking the animals' complex behavior without subjecting them to an external and, hence, unfamiliar test apparatus. (4) They increase the chance of detecting even subtle effects that might otherwise be overlooked . (5) Lastly, such novel approaches enable a thorough understanding of species-typical behaviors that are not achieved by more traditional approaches. With respect to the latter, the data presented here can also be used to discuss the question of how to assess the severity of experimental procedures imposed on animals objectively. Our results show that this chronic pain model could only detect behavioral changes with significant personal and technical effort. This not only demonstrates how difficult it is to assess and classify the severity of procedures according to the national and European guidelines , it also underlines the need for the development and validation of tools and methods to adequately, objectively, and reliably assess the animals' welfare under varying experimental conditions . This way, animal suffering can be minimized, and ethical and scientific considerations can be addressed. 5. Conclusions In summary, we demonstrated the impact of CIBP evoked-, non-evoked behavior and complex rat-specific behaviors in animals of both sexes. Thus, we have provided the behavioral groundwork for mechanism-triggered (pharmacological) studies on CIBP and indicated which effect modifiers exist for animal pain studies in CIBP and in general, and how these can be considered in the future. Furthermore, we demonstrated social pain transfer in a bone cancer model for the first time in rats of both sexes, resulting in mechanical and, in females, also heat hypervigilance in non-tumor bearing shamBY. Acknowledgments We are grateful to Mirjam Augustin and Dagmar Evers for their support in the video evaluation for the home-cage monitoring, and Joanna Sherwood for proofreading. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Correlation matrix between pain-related behavior features; Figure S2: Bone cancer causes group segregation based on pain-related behavior trajectories in both sexes of rats; Figure S3: Bone cancer does not affect the feed intake of rats and approximation of both sexes.; Figure S4: Bone cancer alters daily behavior in rats of both sexes; Figure S5: Social transfer of mechanically evoked pain-related behavior to sham bystander (BY) rats caused by cancer-induced bone pain in both sexes; Table S1: Cluster analysis of PCA results by multivariate analysis of variance (MANOVA); Table S2: Ethogram of rat behavior in the home-cage system; Table S3: Cohen's k values of home-cage observation analysis; Table S4: Cluster analysis of PCA results by multivariate analysis of variance (MANOVA). Click here for additional data file. Author Contributions Conceptualization, D.S. and E.M.P.-Z.; methodology, D.S., J.L., B.P., D.K., R.S., S.H.R., D.G. and E.M.P.-Z.; investigation, D.S., J.L., B.P., D.K., S.H.R., D.G. and E.M.P.-Z.; data curation, D.G.; writing--original draft preparation, D.S., J.L., B.P. and E.M.P.-Z.; writing--review and editing, D.S., J.L., B.P., D.K., R.S., S.H.R., D.G., N.B., G.D.P., W.A.V.J., S.A. and E.M.P.-Z.; visualization, D.S., J.L., B.P., and E.M.P.-Z.; supervision, E.M.P.-Z.; funding acquisition, E.M.P.-Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The experiments in this study were reviewed and approved by the Animal Ethics Committee of the State Agency for Nature, Environment, and Consumer Protection North Rhine Westphalia (LANUV, Recklinghausen, Germany; 84-02.04.2017.A055). Informed Consent Statement Not applicable. Data Availability Statement Data is contained within the article or Supplementary Materials. Conflicts of Interest During the last 5 years, EPZ received financial support from Mundipharma GmbH and Grunenthal for research activities and from Grunenthal, MSD Sharp & DOHME GmbH, Mundipharma GmbH, Mundipharma International, Novartis, Janssen-Cilag GmbH, Fresenius Kabi, and AcelRx for advisory board activities and/or lecture fees. None of this research support/funds was used for or influenced this manuscript, and EPZ declares no conflict of interest. All authors have no competing interests. Figure 1 Study design. (A) Female and male Sprague Dawley rats (age 6-7 weeks, weight 192.3 +- 5.3 g (mean +- SD), 280.1 +- 7.8 g) were used. This study employed intratibial inoculation of Walker 256 cells as a surrogate for cancer-induced bone pain (CIBP). To assess the multimodal CIBP-related behaviors, rats were treated with Walker 256 cells (4 x 105) or heat-deactivated cells (sham). Naive animals, without any manipulation (anesthesia or cell inoculation), were used to test the effect of intratibial cell injection. (B) Multidimensional pain-related behaviors were subgrouped into reflexive-based withdrawal, including punctate mechanical paw withdrawal threshold (PWT) to mechanical stimuli and paw withdrawal latency (PWL) to heat stimuli; voluntary pain-related behavior, including non-evoked pain (NEP) and movement-evoked pain (MEP) behavior; and rodent-specific behavior assessed by home-cage monitoring (HCM) of the first two night hours. (C) Ipsilateral and contralateral tibiae of all rats were examined for bone destruction by X-ray microtomography (mCT), post-mortem 17 days after cell inoculation. (D) Characterizing multidimensional pain behavior trajectories were assessed in a time-dependent manner with cohort 1 in both sexes. HCM was performed with cohort 2 in both sexes and different cagemate combinations. Figure 2 Bone cancer causes distinct pain-related behavior trajectories in both sexes of rats. (A,B) Trajectories of body weight and reflex-based withdrawal behavior, including paw withdrawal threshold to punctate mechanical stimuli (PWT), latency times to radiant heat stimuli (PWL), non-evoked pain-related behavior (NEP), and two static (print area, stand time) and two dynamic (swing speed, swing time) parameters of gait pattern analysis were determined in naive, sham, and CIBP female (A) and male (B) rats. PWT was significantly decreased 6 d after cell inoculation in both sexes, and up to 17 d in CIBP rats. PWL was unaffected in CIBP males but significantly decreased in CIBP female rats at 14 d (to pre-value) and 17 d (to naive). Assessment of the contralateral and ipsilateral hind-paw print area at rest revealed a non-evoked pain-related behavior (NEP) from 6 d in males and 8 d in females until 17 d, which was expressed by guarding behavior of the tumor-bearing hindlimb. Significant reduction to pre-value and naive rats of print area, stand time, and swing speed combined with increased swing time, starting from 8 d in CIBP rats of both sexes, indicated an antalgic gait pattern. (C) Principal component analysis (PCA) of multimodal behavioral data was applied to identify a CIBP-induced phenotype in a time-dependent manner. Significant group segregation was determined at 6 d for CIBP males and 8 d for CIBP females. The results are expressed as mean +- SEM. Two-way ANOVA (repeated measures based on GLM) followed by Dunnett's multiple comparison test. * for comparison to Pre; p-values: * <=0.05, ** <=0.01, *** <=0.001. + for comparison to sham; p-values: + <=0.05, ++ <=0.01, +++ <=0.001. The PC components were selected to determine the eigenvalues. MANOVA was used for cluster analysis in PCA (see Supplementary Table S1). Black = Naive rats, Light magenta = Female sham rats, Magenta = Female CIBP rats, Light cyan = Male cham rats, Cyan = Male CIBP rats. Figure 3 Cancer-induced bone destruction is associated with pain-related behavior. (A) Bone morphology was determined by post-mortem scoring of micro-computed tomography imaging (mCT) images from the contralateral tibiae. Scale bar = 5 mm (B) Scoring of the bone destruction of the ipsilateral side. In both female and male CIBP rats, a significantly increased bone score was detected, indicating increased bone destruction of the ipsilateral tibia. (C,D) PCA-assisted phenotyping showed significant group segregation of CIBP from control groups in both sexes, which was significantly triggered by the increased bone score and gait analysis parameters (see PCA loadings). (E) Including sex as a biological variable, the CIBP and sham control groups were segregated in both sexes based on PC1 axes (as in (C,D)). Sex segregation was determined by the significant PC2 loadings, body weight, and heat hypersensitivity (PWT), independent of the experimental group. Results in (B) are expressed as median +- 95%CI. Holm-Sidak's multiple comparison tests followed two-way ANOVA. * for comparison to sham; p-values: *** <=0.001. # for comparison to naive. p-values: ### <=0.001. The PC components were selected to determine the eigenvalues. MANOVA was used for cluster analysis in PCA. Figure 4 Bone cancer alters specific complex behavior in rats of both sexes. (A-C) Resting behavior was divided into individual (A), social (B), and total (C) resting. Significant differences to the pre-value are observed in the housing groups containing CIBP (CIBP-CIBP, shamBY-CIBP). (D-F) Ambulatory behaviors were divided into a bipedal stance (D), jumping to 1st floor (E), and self-grooming (F). The bipedal stance was significantly reduced in tumor-bearing rats (CIBP). (G,H) Social behaviors were analyzed by assessing playing behavior (G) and allogrooming (H). Playing behavior was significantly decreased in male housing combinations, including CIBP rats. Allogrooming was significantly reduced in the CIBP-CIBP male housing combination. (I) Grooming of the tumor-bearing (ipsilateral) hindleg is a proxy for pain-related behavior. A significant increase in ipsilateral grooming was determined on 8 d in CIBP females housed together with shamBY. Four different housing combinations are shown here. Each housing combination was repeated 4 times with other animals (n= 8, naive; n = 8 sham; n = 8 CIBP; n = 4 CIBP-shamBY; n = 4 shamBY-CIBP). Boxes represent the data shown. Results are expressed as mean+- SEM. Two-way ANOVA (repeated measures based on GLM) followed by Dunnett's multiple comparison test * for comparison to sham; p-Values: * <=0.05, ** <=0.01, *** <=0.001. + for comparison to male; p-values: + <=0.05, ++ <=0.01, +++ <=0.001. Figure 5 Social transfer of pain-related behavior to sham bystander (BY) rats caused by cancer-induced bone pain in both sexes (A) Mechanical (PWT) and heat (PWL) (B) thresholds of the ipsilateral versus contralateral hind paws in rats of both sexes in four different housing conditions 17 d after cell innoculation. (C,D) Representative visualization of the principal component analysis of female (C) and male (D) rats, including home-cage parameter, bone score, and mechanical threshold (PWT) of both hind paws at 17 d. The bubble size represents the PWT. Four different housing combinations are shown here. Each housing combination was repeated four times with other animals (n = 8, Naive; n = 8 sham; n = 8 CIBP; n = 4 CIBP-shamBY; n = 4 shamBY-CIBP). Boxes represent the data shown. Results are expressed as mean+- SEM. Two-way ANOVA (repeated measures based on GLM) followed by Dunnett's multiple comparison test * for comparison to the contralateral site; p-Values: * <=0.05, # for comparison to sham-sham; p-values: # <=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. |
PMC10000429 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050979 foods-12-00979 Article The Effect and Mechanism of Corilagin from Euryale Ferox Salisb Shell on LPS-Induced Inflammation in Raw264.7 Cells Wu Minrui Writing - original draft 1 Jiang Yuhan Methodology Validation 1 Wang Junnan Methodology Software 1 Luo Ting Software Supervision 1 Yi Yang Supervision Funding acquisition 2 Wang Hongxun Funding acquisition 1 Wang Limei Validation Project administration 1* Gentile Carla Academic Editor 1 College of Life Science and Technology, Wuhan Polytechnic University, Wuhan 430023, China 2 College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China * Correspondence: [email protected] 25 2 2023 3 2023 12 5 97904 1 2023 09 2 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 ). (1) Background: Euryale ferox Salisb is a large aquatic plant of the water lily family and an edible economic crop with medicinal value. The annual output of Euryale ferox Salisb shell in China is higher than 1000 tons, often as waste or used as fuel, resulting in waste of resources and environmental pollution. We isolated and identified the corilagin monomer from Euryale ferox Salisb shell and discovered its potential anti-inflammatory effects. This study aimed to investigate the anti-inflammatory effect of corilagin isolated from Euryale ferox Salisb shell. (2) Methods: We predict the anti-inflammatory mechanism by pharmacology. LPS was added to 264.7 cell medium to induce an inflammatory state, and the safe action range of corilagin was screened using CCK-8. The Griess method was used to determine NO content. The presence of TNF-a, IL-6, IL-1b, and IL-10 was determined by ELISA to evaluate the effect of corilagin on the secretion of inflammatory factors, while that of reactive oxygen species was detected by flow cytometry. The gene expression levels of TNF-a, IL-6, COX-2, and iNOS were determined using qRT-PCR. qRT-PCR and Western blot were used to detect the mRNA and expression of target genes in the network pharmacologic prediction pathway. (3) Results: Network pharmacology analysis revealed that the anti-inflammatory effect of corilagin may be related to MAPK and TOLL-like receptor signaling pathways. The results demonstrated the presence of an anti-inflammatory effect, as indicated by the reduction in the level of NO, TNF-a, IL-6, IL-1b, IL-10, and ROS in Raw264.7 cells induced by LPS. The results suggest that corilagin reduced the expression of TNF-a, IL-6, COX-2, and iNOS genes in Raw264.7 cells induced by LPS. The downregulation of the phosphorylation of IkB-a protein related to the toll-like receptor signaling pathway and upregulation of the phosphorylation of key proteins in the MAPK signaling pathway, P65 and JNK, resulted in reduced tolerance toward lipopolysaccharide, allowing for the exertion of the immune response. (4) Conclusions: The results demonstrate the significant anti-inflammatory effect of corilagin from Euryale ferox Salisb shell. This compound regulates the tolerance state of macrophages toward lipopolysaccharide through the NF-kB signaling pathway and plays an immunoregulatory role. The compound also regulates the expression of iNOS through the MAPK signaling pathway, thereby alleviating the cell damage caused by excessive NO release. inflammatory reaction Raw264.7 macrophage corilagin from Euryale ferox Salisb shell cell pathway Hubei Province Natural Science Foundation of China2022CFB429 Primary Research and Development Plan of Hubei Province2022BBA0023 This work was supported by Hubei Province Natural Science Foundation of China (2022CFB429) and the Primary Research and Development Plan of Hubei Province (2022BBA0023). pmc1. Introduction The immune stimulator, LPS, can activate multiple signaling pathways in macrophages, leading to a series of pathophysiological responses , and is often used in in vitro inflammation studies. Inhibition of excessive activation of macrophages and its mediated inflammation has been demonstrated to be beneficial in many disease models , suggesting that targeting macrophage activation is a promising strategy for preventing inflammatory diseases. Euryale ferox Salisb is a large aquatic plant belonging to the water lily family, which has been frequently reported for its use in lowering blood sugar and blood lipid , in addition to its antioxidation properties . Shuliang He et al. characterized the constituents of the volatile oil of Euryale ferox Salisb and identified its biological activity, particularly its antioxidant activity . Additionally, Wen-Na Zhang et al. characterized the polysaccharide in Euryale ferox Salisb and investigated its hypoglycemic effect . The biosynthesis mechanism of flavonoids in Euryale ferox Salisb was analyzed by Peng Wu et al. through metabolomic and transcriptomic analyses, which revealed the key factors involved in the biosynthesis of flavonoids in Euryale ferox Salisb, its main functional substances . Transcriptomic analysis of Euryale ferox Salisb at different developmental stages was performed by Xian Liu et al. , knowledge of which is particularly useful for the development and utilization of Euryale ferox Salisb. With an annual output of more than 1000 tons, the Euryale ferox Salisb shell accounts for around 40% of the seed. It is often used as fuel or transported for disposal, resulting in waste of resources and environmental pollution . Cheng Ying Wu et al. studied the antioxidant and anti-fatigue properties of phenolic extracts of the Euryale ferox Salisb shell, which led to the discovery of potential antioxidant agents . Corilagin has been reported to exhibit various pharmacological activities, including inhibition of inflammatory development , antiviral , liver protection , and antitumor effects . Li et al. found that corilagin significantly reduced the levels of IL-6 and IL-1b in the serum of cells and mice and exhibited an anti-inflammatory role by downregulating the TLR4 signaling molecules, improving the extreme inflammatory state in patients with sepsis. Additionally, Tong et al. found that corilagin may inhibit the activation of the nuclear factor-kB pathway in a STAT3-related manner and reduce the secretion of IL-1b and TNF-a, thereby reducing radiation-induced brain injury in mice. Previous studies have demonstrated that corilagin mainly improves cellular inflammation through the TLR signaling pathway, but there is no report of its activity in the LPS-induced RAW264. Previously, we isolated and identified the corilagin monomer from Euryale ferox Salisb shell; however, the anti-inflammatory effect was not evaluated. We applied a network pharmacology approach to predicting the anti-inflammatory mechanism of corilagin, using the LPS-stimulated Raw264.7 cells as an in vitro inflammatory model to determine the effect of corilagin from Euryale ferox Salisb on the expression of inflammatory and anti-inflammatory factors in macrophages and the possible molecular mechanisms at three levels, i.e., biochemical factors, transcription, and protein levels. The theoretical groundwork is provided by developing and utilizing the Euryale ferox Salisb shell. 2. Materials and Methods 2.1. Materials and Chemicals Raw264.7 cells were purchased from Shanghai Cell Bank, Chinese Academy of Sciences. The cell viability detection kit was purchased from Japan Tongren Reagent Company, and lipopolysaccharide for inducing inflammation was purchased from Sigma Company. The ELISA kit was purchased from Beijing Sizheng Bo Bio Co., Ltd. (Beijing, China), the ROS kit was purchased from Beijing Prilai Gene Technology Co., Ltd. (Beijing, China), and the reverse transcription kit was provided by Bao Bioengineering Co., Ltd. (Dalian, China). Primers were provided by Shanghai Sangon Biology Co., Ltd. (Shanghai, China). The primary and secondary antibodies used for Western blotting were provided by CST (Pi3K and p-Pi3K, Bioss; AKT and JNK, Wuhan Miting). 2.2. Separation and Identification of Corilagin from Euryale ferox Salisb Shell Euryale ferox Salisb shells were dried and crushed, filtered with a 200-mesh sieve, ultrasonically extracted with 70% ethanol, concentrated under reduced pressure, and freeze-dried to obtain Euryale ferox Salisb shell polyphenol alcohol extracts. The chitosan polyphenol extract was added with water and ultrasonicated before being fractionally extracted with petroleum ether, ethyl acetate, and n-butanol (v/v = 1:1). The extract phase of the Euryale ferox Salisb shell was collected and packed on a silica gel column (60 mesh) by the wet method for separation. Elution was carried out with a mixture of ethyl acetate and petroleum ether (2:1), and the elution fractions were collected. The fraction with the highest activity was concentrated and lyophilized. The eluent was petroleum ether:ethyl acetate (100:15), and the eluent was collected. The samples were separated on a Sephadex LH-20 (Hydroxypropyl Sephadex) chromatographic column with 50% methanol and water, and the monomer compound was obtained by semi-preparative liquid phase, which was identified as corilagin . 2.3. Corilagin and Inflammation Target Prediction and Screening Application The 2D structure of corilagin was obtained from the PubChem database, and the sdf file of the drug structure was imported into PharmMapper and Swiss Target Prediction, the TCMSP database, to obtain drug-related targets by merging and de-weighting. The disease-related targets were obtained from the GeneCards database by setting the search keyword "inflammation" as the genus "human origin". 2.4. Construction of PPI Network and Acquisition of Crossover Genes The species was set as the human species, and the minimum relationship score was 0.4. The key proteins with the cross-repetition of corilagin and inflammation were input into the protein interaction database (STRING), and the proteins without an interaction relationship were removed to obtain the protein interaction map. 2.5. HUB Genes' Acquisition and KEGG and GO Enrichment Analysis Cytoscape 3.9.1 was supplied with the protein-protein interaction diagram obtained from the STRING database to obtain the top 30 central target genes for interactions with other proteins in the network diagram. GO and KEGG analysis of central target genes were performed using the R-package clusterProfiler and enrichment plot. The data with p-value < 0.05 were screened, and the relevant legends were plotted using the R package ggplot2. 2.6. Docking Analysis The top five degrees in the PPI network were used as the receptor proteins, the top nodes in the "active ingredient-target-disease" network were used as the ligands, and the structures of the receptor proteins were downloaded from the PDB database. The proteins and ligands were pre-processed using PyMOL-2.3.4. Subsequently, AutoDockTools software was used to pre-process the protein and ligands, and Vina was used for predicting the binding energy of the ligands of small size to the proteins, with the lowest binding energy indicating the optimal conformation. The receptor-ligand docking files were processed by PyMOL and uploaded to the online website called Plip to visualize the validation results. 2.7. Cell Culture and Model Establishment Raw264.7 cells, the mouse monocytic leukemia cells, were cultured in a DMEM medium containing 10% FBS and 1% penicillin and streptomycin dual-antibodies at 37 degC in an incubator containing 5% CO2. The culture was passaged when grown to more than 90% in cell culture flasks, and selected experiments were performed on counted cells. The experiments were conducted by comparing different groups of experimental subjects: the control group (without LPS and corilagin intervention), the LPS stimulation group (with the addition of 1 mg/mL of LPS for intervention), the experimental group (different concentrations of corilagin were pretreated for 2 h and the final concentration of 1 mg/mL was added and LPS co-treated for 24 h), and the positive drug group (50 mmol/L of dexamethasone pretreatment for 2 h, LPS with a final concentration of 1 mg/mL added for 24 h). 2.8. Cell Morphology Observation and CCK-8 Assay to Detect the Proliferation Toxicity of Corilagin on Raw264.7 Cells Cells were seeded into 6-well plates (at a density of 5 x 105 cells per well). The cells were divided into a normal control group, an LPS stimulation group, and a corilagin treatment group, and the experiments were conducted in replicates (2 wells for each group). The cellular morphology was observed by an inverted microscope. To screen for the safe concentration of corilagin from the Gorgon husk source, the CCK-8 method was used to analyze the effect of corilagin on the survival rate of Raw264.7 cells. Cells in the logarithmic growth phase were sampled for cell counting, and 100 mL of cell suspension was added to each well of a 96-well plate (density of 3000 cells per well). The surrounding wells were sealed with PBS and grown for 24 h. The experiment was divided into the blank group (without cells and drugs), the control group (without drugs), and the experimental group. The drugs were prepared by diluting with complete medium to 2-fold gradient dilution, followed by filtration with a membrane of 0.22 mm pore size, and used immediately. The cultures were grown for 24 h before the analysis. When testing, the medium in the 96-well plate was aspirated, washed twice with PBS, and patted dry on thick paper. CCK-8 was prepared in the dark to avoid errors caused by residual CCK-8 in the pipette tip left when adding samples. A complete medium was used to dilute CCK-8, and the diluted solution was mixed well for later use. The cultures were incubated for 3 h in an incubator, and the OD value at a wavelength of 450 nm was determined. 2.9. Determination of NO Content by Griess Method Raw264.7 cells were seeded into a 24-well plate (at a density of 2 x 105 cells per well) and placed in a cell incubator for 12 h. Different groups were cultured for 24 h according to the corresponding treatment, and the cell supernatant was collected. The NO content in the supernatant was detected by the Griess reagent method, and the amount of released NO of each group was calculated using the standard curve. 2.10. ELISA Method to Determine the Effect of Corilagin on the Secretion of Inflammatory Factors Cell treatment was kept consistent with the pretreatment method used for cell morphology observation, and the cell supernatant was collected. The contents of TNF-a, IL-6, IL-1b, and IL-10 were determined according to the instructions of the ELISA kit. 2.11. Detection of Intracellular Reactive Oxygen Species by Flow Cytometry The cells in the logarithmic growth phase were inoculated into 6-well plates and cultured for 12 h. Different groups were cultured for 24 h according to the corresponding treatment. The liquid in the 6-well plate was discarded and washed twice with PBS. The control group was added with 2 mL of complete medium. The base, lipopolysaccharide, and experimental groups were added with 2 mL of 20 mmol DCFH-DA diluted in a complete medium and incubated in an incubator for 2 h. After incubation, PBS was used for rinsing twice, i.e., 1 mL of PBS was added to each well and the cells were detached by pipetting, collected into a centrifuge tube, and centrifuged at 1000 r/min for 3 min, the supernatant was discarded, and 1 mL of PBS was added to each tube. The mixtures were mixed by pipetting, the cell suspension was transferred to a 1.5 mL flow centrifuge tube, and the intensity of the intracellular ROS fluorescence was measured by flow cytometry. 2.12. qRT-PCR Detection of TNF-a, IL-6, COX-2, and iNOS Gene Expression Levels The six-well plate was taken out, and the medium discarded and rinsed twice with PBS. Then, 1 mL of RNA iso plus was added and left to stand for 1 min before pipetting. The cell suspension was collected by pipetting, transferred into a sterile tube, and added with 200 mL of chloroform, and the mixture was mixed well. Next, extraction was carried out on the ice for 15 min with inversion every 5 min. The EP tube with three layers of supernatant was carefully removed, and the supernatant was pipetted into another 1.5 mL EP tube using a 100 mL pipette. Then, 500 mL of isopropanol was added and mixed well, and the tube was placed on ice for 15 min. The mixture was then centrifuged at 12,000 rpm and at 4 degC for 15 min to recover a white precipitate. The supernatant was carefully removed to avoid disturbing the pellet. Next, 1 mL of 75% ethanol was added, and the pellet was gently lifted. The wall of the tube was washed by inversion, at 7500 rpm. The supernatant was discarded, and the pellet was air-dried with the lid opened at room temperature for 5 min before the addition of an appropriate amount of DEPC water to dissolve the pellet. The RNA concentration was measured using a UV micropipette and adjusted to obtain the RNA concentration of 1000 ng/mL per tube. The RNA was reverse-transcribed into cDNA according to the protocols for reverse transcription, and the real-time fluorescence quantitative PCR reaction system using 10 mL of SYBR Premix Ex Taq TM, 8 mL of primers, and 2 mL of cDNA was conducted. Primer sequences (Table 1): The cDNA sequences of each gene were retrieved from NCBI, and specific primer sequences were designed and synthesized by Shanghai Sangon Bioengineering Co., Ltd. 2.13. Western Blot Analysis of Key Proteins' Expression in NF-kB, MAPK, and PI3K-AKT Signaling Pathways After preconditioning cells, the excess medium in the well plate was aspirated, and 1 mL of PBS was used for washing twice. Cells were digested with 1 mL of trypsin, transferred to a 1.5 mL EP tube, and centrifuged at 3000 rpm for 1 min. The resulting supernatant was discarded. Next, 100 mL of lysis buffer (prepared by RIPA lysis buffer and protease inhibitor 1:100) was added to each tube and evenly pipetted. The cells were lysed on ice for 30 min to ensure complete cell lysis. The cells were then centrifuged at 12,000 rpm for 10 min at 4 degC, and the supernatant was collected to obtain the total protein. A 5x protein loading buffer 4:1 was added to the protein sample, mixed by vortexing, and incubated in a water bath at 95 degC for 10 min. The treated samples were stored in a -20 degC refrigerator for later use. The treated protein samples were transferred to 10% SDS-polyacrylamide gel for electrophoretic separation. The PVDF membrane was placed on the glue and covered with wet filter paper and a sponge. The mounted membrane transfer system was secured with the membrane transfer clip, and the transfer was conducted at 200 mA for 1 h. The membrane was then blocked with 5% skimmed milk at room temperature for 1 h with gentle shaking, followed by overnight incubation with a primary antibody at 4 degC. The blocked membrane was then washed thrice on a decolorizing shaker for 5 min at room temperature. Two hours later, the membrane was then washed thrice on a decolorizing shaker for 5 min. The membrane was then exposed to ECL, and the signal was analyzed using gel imaging software. 2.14. Data Statistics and Analysis GraphPad Prism 8 was used for statistical analysis. All data are expressed as the mean +- standard deviation unless otherwise stated. The p-value of <0.05 was considered significant. 3. Results 3.1. Acquisition of Corilagin and Inflammatory Targets and the "Corilagin-Target-Inflammation" Interaction Network The 3D structure of corilagin from Euryale ferox Salisb shell was obtained from the PubChem database . A total of 307 corilagin genes were obtained from the PharmMapper website and the Swiss Target Prediction database. Among human species, the GeneCard database showed that there were 111,109 genes related to inflammation. Then, 268 cross-repeating genes that appear in both drug targets and inflammatory targets were selected, suggesting that these genes may be the key genes in regulating inflammation of corilagin. To further investigate the relationship between corilagin and inflammation, a "Corilagin-Target-Inflammation" network has been constructed in Cytoscape 3.9.1 . 3.2. Construction of PPI Network and Acquisition of HUB Genes The crossover genes were imported into the STRING website for protein interactions, and a protein interaction map containing 268 nodes and 3724 edges was obtained. Cytoscape software visualized the protein interaction map, and the top 30 target proteins of the protein interaction network were calculated using the MCC calculation method in the CytoHubba plugin . The results predicted that the above genes and related proteins play an important role in treating hepatocellular carcinoma. 3.3. GO and KEGG Pathway Analysis The GO analysis revealed the expression of genes localized in the nucleus, while the KEGG analysis revealed the MAPK and TOLL-like receptor signaling pathways. Based on findings from the GO and KEGG analyses, it was concluded that corilagin may validate protein expression by regulating the MAPK signaling pathway, which is related to the secretion of inflammatory factors by macrophages, as well as in the NF-B and PI3K signaling pathways, which are closely related to toll-like receptors that attenuate the tolerance level of macrophages. 3.4. Validation of Molecular Docking The binding energy (kcal/mol) between the target and corilagin was predicted based on molecular docking , whereby the negative binding energy of the ligand and receptor usually indicates the binding affinity between them. The docking revealed that the binding energy was less than -5 kcal/mol between all hub gene targets and keratine, from which only three models with good binding energy were selected for visualization . 3.5. The Effect of Corilagin on the Viability of Raw264.7 Cells and Changes in Cellular Morphology The investigation of the effect of corilagin on the viability of Raw264.7 cells demonstrated that cell viability was significantly decreased after incubation for 24 h at concentrations exceeding 100 mm/L, i.e., 25, 50, and 100 mmol/L were selected as the low, medium, and high doses of corilagin from the Gorgon shell source in the experiment. Raw264.7 is a mononuclear macrophage derived from the leukemia virus in Balb/c mice . The health of the cells can be impacted by the state of the cells, and since Raw264.7 cells are small and bright in appearance, they are not in a good shape. After the LPS stimulation, the cells formed a long shuttle with elongated false feet . Additionally, pseudopodia were reduced in cells treated with corilagin, with most of the cells being round in shape . The results indicated that corilagin from Euryale ferox Salisb could mitigate inflammation by inhibiting the differentiation of Raw264.7 cells. 3.6. Effects of Corilagin on LPS-Induced NO Secretion by Raw264.7 Macrophages NO is an endogenous synthetic gas signal molecule, synthesized in the cytoplasm, which quickly diffuses through the cell membrane. The molecule rapidly reacts with other free radicals, producing high levels of active peroxidase (oxidant) and other active nitrogen derivatives. These molecules can reflect inflammation and diseases such as atherosclerosis . The effects of NO secretion on the volume of Raw264.7 cells induced by LPS via the Griess method were investigated. The results depict that at the concentration of higher than 25, 50, and 100 mmol/L, the corilagin intervention resulted in a significant reduction in the volume of LPS-induced Raw264.7 cells' supernatant, indicating the potential inflammation-relieving activity of corilagin, which concerns its ability to suppress the release of NO. 3.7. The Effect of Corilagin on the Expression of Inflammatory Factors in LPS-Induced Raw264.7 Macrophages When macrophages are activated, inflammatory cytokines such as inflammatory enzymes and TNF-a, IL-6, IL-1b, and IL-10 are secreted. Following anti-inflammatory drug intervention, macrophages secrete anti-inflammatory factors, which are responsible for anti-inflammatory effects. The investigation of the effect of corilagin on the secretion of TNF-a, IL-6, IL-1b, and IL-10 in Raw264.7 cells revealed that treatment with corilagin at 25, 50, and 100 mmol/ L significantly reduced the secretion of TNF-a and IL-6 in LPS-induced Raw264.7 cells. At 50 and 100 mmol/L, corilagin significantly reduced the secretion of IL-1b and IL-10 in LPS-induced Raw264.7 cells. 3.8. The Effect of Corilagin on the Content of Reactive Oxygen Species in Raw264.7 Cells Activated oxygen is an active oxygen family, which includes superoxide and hydroxyl radicals that stimulate macrophages and neutrophils. This reactive oxygen species is produced by many biologically active media. Reactive oxygen species and other pro-inflammatory factors activate nuclear transcription factors (NF-kB) and cell nuclear binding, thereby promoting inflammatory factor transcription, sometimes resulting in inflammatory allergic reactions. These factors play a key role in the inflammation and wound healing processes, which lack specificity in bacteria. Excessive active oxygen can destroy the integrity of the mitochondrial membrane, resulting in changes in mitochondrial permeability; thus, eliminating tissue and damaging active oxygen is highly important. The effects of corilagin on the content of reactive oxygen species in Raw264.7 cells at 25, 50, 100, and 50 mmol/L of dexamethasone are presented in Figure 10. Following the intervention with corilagin at 25, 50, 100, and 50 mmol/L of dexamethasone, the intracellular ROS was reduced by 9.49%, 10.91%, 15.43%, and 8.73%, respectively. The results demonstrate that the corilagin from Euryale ferox Salisb shell can prevent the inflammatory reaction by reducing reactive oxygen species. 3.9. Effects of Corilagin on the Gene Expression of TNF-a, IL-6, iNOS, and COX-2 in LPS-Induced Raw264.7 Macrophages The results demonstrate that after the intervention of 25, 50, and 100 mmol/L derived from the Gorgon shell, the levels of gene expression of TNF-a, iNOS, and COX-2 were significantly reduced in a dose-dependent manner. Additionally, intervention by 100 mmol/L of corilagin significantly reduced the level of gene expression of IL-6. The nitric oxide synthase (NOS) can convert left-transverse arginine to left-transverse citrulline, thereby causing NO production, which can be classified into constitutive and inducible. Many studies have suggested that continuous and excessive NO production is primarily associated with the high expression level of inducible nitric oxide synthase (iNOS) . The results indicate that the corilagin could reduce the secretion of NO by lowering the expression of iNOS, thereby exerting its anti-inflammatory effect. In addition, the level of COX-2 is increased in the inflammatory process, causing excessive production of PGE2, resulting in an excessive inflammatory response. The results also display that the corilagin could downregulate the expression of COX-2 to alleviate inflammation. TNF-a and IL-6 are the most common inflammatory cytokines, which play a vital role in inflammation. The results demonstrate that corilagin could reduce the gene expression of TNF-a and IL-6, thereby reducing the secretion of TNF-a and IL-6 and achieving an anti-inflammatory effect. 3.10. The Effect of Corilagin on the Expression of Key Proteins in the NF-kB Signaling Pathway in Raw264.7 Cells The effect of corilagin from the Gorgon shell on the expression of NF-kB pathway-related proteins in Raw264.7 cells is presented in Figure 12. The protein assay of IkB-a revealed that LPS stimulation and intervention by Gorgon shell-derived corilagin produced no significant effect on phosphorylation of IkB-a. Additionally, the phosphorylation of P65 was significantly downregulated following LPS stimulation, whereas the treatment with 50 mmol/L of corilagin resulted in upregulation of the phosphorylation of P65. 3.11. The Effect of Corilagin on the Expression of Key Proteins in the MAPK Signaling Pathway in Raw264.7 Cells The effect of corilagin from the Gorgon shell on the expression of MAPK pathway-related proteins in Raw264.7 cells is presented in Figure 13. The ERK protein assay revealed that LPS stimulation produced no significant effect on the phosphorylation of ERK, whereas the phosphorylation of ERK was significantly upregulated after the intervention of corilagin at 50 mmol/L. It was also found that the phosphorylation of JNK was significantly downregulated following LPS stimulation, while the intervention by 50 mmol/L of corilagin resulted in upregulation of phosphorylation of JNK. Additionally, both LPS stimulation and treatment with 50 mmol/L of corilagin produced no significant effect on the phosphorylation of P38. 3.12. The Effect of Corilagin on the Expression of Key Proteins in the PI3K-AKT Signaling Pathway in Raw264.7 Cells The effect of corilagin from the Gorgon shell on the expression of PI3K-AKT pathway-related proteins in Raw264.7 cells is depicted in Figure 14. The PI3K protein assay revealed that both stimulations by LPS and intervention with 50 mmol/L of corilagin produced no significant effect on the phosphorylation of PI3K. Compared with the blank group, the phosphorylation of AKT protein was significantly downregulated following LPS stimulation, whereas the intervention with 50 mmol/L of corilagin produced no significant effect on the phosphorylation of AKT protein. The investigation of the effect of the corilagin intervention revealed that no significant effect was produced on the expression of key proteins in the NF-kB signaling pathway in Raw264.7 cells. Similarly, stimulation by LPS produced no significant effect on the phosphorylation of IkB-a but significantly downregulated the phosphorylation of P65. In the MAPK signaling pathway, LPS stimulation had no significant effect on the phosphorylation of ERK and P38 but significantly inhibited the phosphorylation of JNK. In addition, in the PI3K-AKT signaling pathway, LPS stimulation had no significant effect on the phosphorylation of PI3K but significantly downregulated the phosphorylation of AKT. Previous studies have demonstrated that when macrophages develop lipopolysaccharide tolerance, LPS stimulation results in reduced P65 phosphorylation in the NF-kB signaling pathway, as well as that of ERK, JNK, and P38 in the MAPK signaling pathway . The results from Western blot analysis demonstrate that the macrophages were lipopolysaccharide-tolerant and that LPS at 50 mmol/L was tolerated in this study. Additionally, the intervention of corilagin originated from the Gorgon husk significantly upregulated the phosphorylation of P65 and JNK proteins and relieved the lipopolysaccharide tolerance state of Raw264.7 cells, indicating its potential immunoregulatory role . 4. Discussion Corilagin is a polyphenolic tannin compound , which is widely found in geranium, bead, white clover, longan, Phyllanthi fructus, and other plants . Structurally, ellagic acid is a dilactone of hexahydroxy biphenyl acid (HHDP). Corilagin, a kind of ellagitannin which is a condensation of ellagic acid, has good antioxidant potential. After optimizing the extraction process of ellagitannin, Anindita Paul et al. obtained the result that ellagitannin could combine well with catalase through calculation and analysis . Studies have demonstrated that corilagin exhibits antitumor, antiviral, and antibacterial activities in addition to anti-inflammatory and antioxidant effects, suggesting its potential use as an agent in the preventive treatments of cardiovascular diseases . Corilagin sourced from Gorgon husk was extracted and identified during the early stages of a study on Gorilla husk by our research team, but its anti-inflammatory properties have not yet been revealed. Cyber-pharmacology efficiently integrates research content, utilizing high-throughput computing methods and software. By setting different screening conditions, proteins interacting with small molecules can be accurately predicted, to predict protein-related metabolic pathways . In this study, we identified 307 targets of corilagin using PharmMapper. The subsequent GO and KEGG enrichment analyses revealed that the anti-inflammatory effects of corilagin are primarily associated with MAPK and TOLL-like receptor signaling pathways. Additionally, LPS and other pro-inflammatory factors can induce the phosphorylation of MAPK signaling pathway-associated proteins and trigger the expression of iNOS genes in the nucleus. Findings from this study demonstrate that corilagin, a Gorgon fruit source, could significantly inhibit the production of reactive oxygen species induced by LPS in macrophages, as well as the related oxidative stress responses in cells. These results further confirm the findings reported in previous studies regarding the positive correlation between the degree of oxidative stress and the degree of inflammation and that inhibiting excessive production of reactive oxygen species can suppress the inflammatory response. Analysis of NO secretion revealed that the intervention of corilagin from Gorgon shell significantly reduced NO content in the supernatant of LPS-induced Raw264.7 cells. Analysis of the gene expression of inflammatory factors demonstrated that the corilagin intervention significantly reduced the expression of IL-6 and TNF-a genes compared with LPS-induced macrophage inflammation. Corilagin also significantly downregulated the expression of iNOScox-2, and nitric oxide synthase (NOS) could convert L-arginine to L-citrulline, thereby causing the release of NO. Numerous studies have suggested that persistent and excessive NO production is mainly attributed to the overexpression of inducible nitric oxide synthase (iNOS) . In addition, the expression of COX-2 is elevated during the inflammation process, causing the overproduction of PGE2, which results in an excessive response to inflammation . This proves that corilagin, a source of a gorgonian shell, could reduce the secretion of NO by downregulating the expression of iNOS, thereby exerting its anti-inflammatory effect. Many physiological and pathological responses in mammalian cells and tissues are mediated by MAPK signaling, including stress responses, inflammation, and apoptosis. Phosphorylation of ERK1/2 and p38 promotes the production of inflammatory factors, including TNFa, IL-6, and IL-8 . In addition, TNF-a also stimulates the MAPK cascade and promotes IL-8 secretion . The analysis conducted in this study revealed that phosphorylation levels of ERK and JNK proteins increased following treatment with corilagin. Related studies have reported that p38 of MAPK and PI3K-Akt can regulate LPS-induced gene expression by controlling the hyperphosphorylation and nuclear translocation of p65 of NF-kB . Corilagin could also significantly upregulate the phosphorylation of P65 protein. This study also examined the expression of related proteins in the PI3K-Akt signaling pathway, which revealed that LPS induction significantly reduced the phosphorylation level of AKT. Previous studies have demonstrated that when macrophages develop lipopolysaccharide tolerance, LPS stimulation can reduce the phosphorylation of P65 protein in the NF-kB signaling pathway, as well as that of ERK, JNK, and P38 in the MAPK signaling pathway . Western blot analysis demonstrated that the intervention of 50 mmol/L of gorgonian shell-derived corilagin could significantly upregulate the phosphorylation of P65 and JNK, relieving the lipopolysaccharide tolerance state of Raw264.7 cells, thereby exerting an immune-regulating effect. The results indicate that macrophages developed lipopolysaccharide tolerance and that corilagin interfered with the phosphorylation of P65 and JNK proteins and relieved the macrophages of their tolerance. Notably, lipopolysaccharide tolerance plays an immunomodulatory role . Supplementary Materials The following are available online at Figure S1. Mass spectra of corilagin; Figure S2. Claritin extraction process. Click here for additional data file. Author Contributions Methodology, Y.J. and J.W.; Software, J.W. and T.L.; Validation, Y.J. and L.W.; Writing--original draft, M.W.; Supervision, T.L. and Y.Y.; Project administration, L.W.; Funding acquisition, Y.Y. and H.W. 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 to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Corilagin and inflammation intersection targets: (A) structural formula of corilagin and (B) intersection Venn diagram. Figure 2 "Corilagin-Target-Inflammation" network. Figure 3 PPI network map and screening of HUB genes. Figure 4 GO and KEGG pathway analyses of HUB genes: (A) GO analysis and (B) KEGG analysis. Figure 5 Validation of molecular docking: (A) molecular binding energy heatmap and (B-D) visualization of molecular docking results. Figure 6 Effect of LPS on Raw264.7 cell viability. (Compared with control group, *** p < 0.001). Figure 7 Morphology of Raw264.7 cells under different treatment conditions: (A) control cells, (B) lipopolysaccharide-stimulated cells, and (C) cells treated with corilagin from Euryale ferox Salisb shell. Figure 8 The effect of corilagin from Euryale ferox Salisb shell on NO secretion of Raw264.7 cells. (Compared with the control group, ### p < 0.001; Compared with LPS group, *** p < 0.001). Figure 9 Effect of corilagin on TNF-a, IL-6, IL-1b, and IL-10 secretion of Raw264.7 cells: the amount of (A) TNF-a, (B) IL-6, (C) IL-1b, and (D) IL-10 secreted in the cell supernatant. (Compared with the control group, ### p < 0.001; Compared with LPS group, * p < 0.05, ** p < 0.01 and *** p < 0.001). Figure 10 Effect of corilagin on ROS content of Raw264.7 cells. Pictures 1-6 correspond to the control group, LPS treatment group, 25, 50, 100 mmol/L of corilagin treatment group, and the 50 mmol/L dexamethasone treatment group, in which P3 represents intracellular reactive oxygen species content. Figure 11 Effect of corilagin on TNF-a, IL-6, COX-2, and iNOS expression of Raw264.7 cells: expressions of (A) TNF-a, (B) IL-6, (C) iNOS, and (D) expression of COX-2. (Compared with the control group, ### p < 0.001; Compared with LPS group, * p < 0.05, ** p < 0.01 and *** p < 0.001). Figure 12 Effect of corilagin on the expression of NF-kB pathway-related proteins in Raw264.7 cells. (A) Western Blot results, (B) Relative protein expression (Compared with the control group, # p < 0.05; Compared with LPS group, * p < 0.05). Figure 13 Effect of corilagin on the expression of MAPK pathway-related proteins in Raw264.7 cells. (A) Western Blot results, (B) Relative protein expression (Compared with the control group, # p < 0.05; Compared with LPS group, * p < 0.05 and ** p < 0.01). Figure 14 Effect of corilagin on the expression of PI3K-AKT pathway-related proteins in Raw264.7 cells. (A) Western Blot results, (B) Relative protein expression (Compared with the control group, ## p < 0.01). foods-12-00979-t001_Table 1 Table 1 Primer sequences. Gene Name Forward Primer (5-3) Reverse Primer (3-5) b-actin CTACCTCATGAAGATCCTGACC CACAGCTTCTCTTTGATGTCAC TNF-a ATGTCTCAGCCTCTTCTCATTC GCTTGTCACTCGAATTTTGAGA IL-6 CTCCCAACAGACCTGTCTATAC CCATTGCACAACTCTTTTCTCA COX-2 ATTCCAAACCAGCAGACTCATA ATTCCAAACCAGCAGACTCATA iNOS CGGACGAGACGGATAGGCAGAG GGAAGGCAGCGGGCACATG 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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PMC10000430 | Hereditary myeloid malignancy syndromes (HMMSs) are rare but are becoming increasingly significant in clinical practice. One of the most well-known syndromes within this group is GATA2 deficiency. The GATA2 gene encodes a zinc finger transcription factor essential for normal hematopoiesis. Insufficient expression and function of this gene as a result of germinal mutations underlie distinct clinical presentations, including childhood myelodysplastic syndrome and acute myeloid leukemia, in which the acquisition of additional molecular somatic abnormalities can lead to variable outcomes. The only curative treatment for this syndrome is allogeneic hematopoietic stem cell transplantation, which should be performed before irreversible organ damage happens. In this review, we will examine the structural characteristics of the GATA2 gene, its physiological and pathological functions, how GATA2 genetic mutations contribute to myeloid neoplasms, and other potential clinical manifestations. Finally, we will provide an overview of current therapeutic options, including recent transplantation strategies. GATA2 deficiency GATA2 haploinsufficiency germline mutation predisposition to myeloid neoplasms FEDERCB16/12/00284 Instituto de Salud Carlos III (ISCIII)PI18/1472 PI19/00812 PI22/01633 Fundacio La Marato de TV3228/C/2020 Conselleria de Educacion, Cultura y DeporteCIGE/2021/015 Asociacion Espanola contra el CancerCLJUN19005SANT Rio HortegaCM22/00191 Generalitat ValencianaAPOSTD/2021/212 This study was supported by research funding from FEDER funds (CIBERONC [CB16/12/00284]), Instituto de Salud Carlos III (ISCIII) grants PI18/1472, PI19/00812, and PI22/01633, Fundacio La Marato de TV3 grant 228/C/2020, as well as from the Conselleria de Educacion, Cultura y Deporte CIGE/2021/015. M.S. is the recipient of the "Clinico Junior 2019" (CLJUN19005SANT) and Rio Hortega (CM22/00191) fellowships granted by the Asociacion Espanola contra el Cancer (AECC) and the ISCIII, respectively. A.L. is the recipient of the APOSTD/2021/212 Generalitat Valenciana post-doctoral fellowship. pmc1. Background Familial myelodysplastic syndromes (MDSs) and acute myeloid leukemia (AML), also known as hereditary myeloid malignancy syndromes (HMMSs), have been recognized phenotypically for more than a century, with the first molecular basis discovered in 1999 through the identification of germline RUNX1 mutations . Since then, and recently accelerated by the advent of next-generation sequencing (NGS), a growing number of genes have been associated with germline predisposition to myeloid malignancies, including the ANKRD26 , ETV6 , CEBPA , DDX41 , GATA2 , RBBP6 , TERT, TERC , and, most recently the SAMD9 and SAMD9L genes . Although they are traditionally considered very rare entities, it is now known that 4-13% of pediatric and 5-15% of adult MDS/AML cases are caused by germline predisposition . Although most of these entities have only recently been described, the World Health Organization (WHO) incorporated some of them as provisional categories in its fourth revised classification . In recognition of the robustness of data, HMMSs have also been integrated into other guidelines and expert recommendations, such as the Nordic Guidelines and the European Leukemia Network , highlighting the need to identify, diagnose, and correctly manage patients with hereditary syndromes. Finally, the growing recognition and molecular identification of this subset of myeloid malignancies have led to their being formalized in the most recent revisions by the WHO and the International Consensus Classification (ICC) of myeloid neoplasms . The WHO 2022 update reinforces this category and includes it within the group of secondary myeloid neoplasms . On the other hand, the 2022 ICC proposes to place these entities within the category of pediatric and/or germline mutation-associated disorders due to their overlap with other childhood disorders . This review focuses on one of these entities, specifically the phenotypic spectrum of patients diagnosed with GATA2 deficiency, recognized as a major myeloid neoplasia predisposition syndrome with pleiotropic manifestations. We discuss the structural characteristics of the GATA2 gene and describe how its genetic alterations might contribute to the onset of myeloid neoplasms as a result of aberrant induced hematopoiesis . In addition, we will summarize diagnostic clues for proper identification and management of this syndrome. 2. GATA2 Molecular Insights The GATA binding protein 2 (GATA2) gene is located on the long arm of human chromosome 3 at cytoband 21.3 (i.e., 3q21.3) and encodes two main isoforms (NM_032638 and NM_001145661) identical in their coding regions, but differing in the 5' untranslated region . The GATA2 protein belongs to the GATA binding factors family, which modulates the expression of several genes by binding to the DNA motif GATA and other transcription factors . This is managed by two highly conserved zinc finger domains (ZF1 and ZF2), which are responsible for the DNA-binding ability of GATA2. In addition, the GATA2 protein contains two transactivation domains, a nuclear localization signal, and a negative regulatory domain . The precise role of GATA2 in hematopoiesis is still not entirely understood. Hematopoietic stem cells (HSCs) found in the bone marrow of GATA2+/- mice were found to be impaired in terms of both number and functionality, as evidenced by serial transplantation assays . GATA2 heterozygosity is associated with decreased proliferation ability and increased quiescence and apoptosis in HSCs . Moreover, GATA2 haploinsufficiency impairs the function of granulocyte-macrophage progenitors but not that of other committed myeloid progenitors . Despite this, GATA2+/- mice do not develop MDS/AML, which makes it challenging to study the impact of GATA2 haploinsufficiency on leukemic progression in these models. On the other hand, the overexpression of GATA2 results in the self-renewal of myeloid progenitors and hampers lymphoid differentiation in mouse bone marrow . Additionally, the overexpression of GATA2 promotes proliferation in human embryonic stem cells (hESCs) but quiescence in hESC-derived HSCs . Elevated levels of GATA2 have been observed in AML patients, both adults and children, who have poor prognoses . These findings indicate that, in addition to its function as a tumor suppressor, GATA2 may also act as an oncogene when overexpressed. In line with these data, and focusing on adult hematopoiesis, the GATA2 protein, together with several transcription factors (e.g., FLI1, LMO2, and RUNX1), is involved in HSC survival and self-renewal, thus participating in early lineage commitment. Meanwhile, during hematopoietic differentiation, GATA2 modulates downstream fate decisions by interacting with CEBPA, GATA1, and SPI1 . To date, roughly 500 GATA2-deficient patients have been reported, and the syndrome was confirmed to be inherited according to an autosomal dominant pattern in 50% of cases, de novo in 5% of cases, and uncertain in the rest of the cases . This is unexpectedly different from previous studies, in which de novo occurrence was estimated in two thirds of all cases . However, there is a lack of a well-characterized series in which segregation studies have been carried out systematically or in which penetrance or expressivity were considered. Therefore, these data should be viewed with caution. In addition, almost 200 unique (likely) pathogenic variants have been described that can be classified into four groups: truncating mutations (splice site, nonsense, frameshift, and whole-gene deletions) proximal to or within the ZF2 domain; missense mutations within the ZF2 domain; mutations resulting in aberrant mRNA splicing (e.g., synonymous changes) ; and other regulatory variants, such as those located in the GATA2 intronic +9.5 kb enhancer site (e.g., c.1017+572C>T, the c.1017+532A>T, and the c.1017+513_1017+540del [c.1017+512del28]), which is essential for hematopoiesis . Overall, germline GATA2 (likely) pathogenic variants are hypothesized to result in haploinsufficiency because truncated alleles lead to clinical phenotypes similar to missense variants . Strikingly, some variants have been associated with only partial loss-of-function (p.T354M) or even gain-of-function (p.L359V) mechanisms, suggesting more complex pathways . Although most deleterious changes are private, it is possible to recognize some mutational hotspots. Recurrent variants in the extended ZF2 domain have been identified, including p.T354M and p.R396W/Q/W, found in roughly one fifth of the reported cases, as well as the c.1017+572C>T intronic variant, found in 20 patients . Germline GATA2 mutations are usually necessary but not sufficient for myeloid disease development. It has been proposed that different environmental stressors may modify the expression of these germline variants during embryogenesis or after birth, inducing disorder in tissues where limited GATA2 expression is inadequate for their normal cellular function . Particularly in bone marrow (BM), such stressors can lead to certain cytogenetic and molecular alterations that accumulate over time, selecting clonality and triggering myeloid transformation. Indeed, the germline variant can also modify the BM microenvironment, contributing to clonal selection . In patients with progression to a malignant neoplasm, certain cytogenetic and molecular alterations appear recurrently. The most frequent cytogenetic alterations in patients with germline GATA2-mutated myeloid neoplasms involve chromosome 7, including its monosomy, partial deletion of 7q and der(1;7)(q10;p10), and trisomy of chromosome 8 . These neoplasms tend to show fewer somatic mutations and a different molecular landscape compared to non-GATA2 MDS/AML. The most frequent recurrent somatic mutations identified in GATA2-MDS/AML patients are in the SETBP1, ASXL1, and STAG2 genes, and the RAS pathway. By contrast, deleterious SF3B1, U2AF1, NPM1, and FLT3 changes are infrequent in GATA2-mutated myeloid neoplasms . Interestingly, GATA2 can also be mutated in somatic cells of sporadic MDS/AML. Different from germline GATA2 mutations, which mainly include truncated and ZF2 missense changes, somatic GATA2 mutations are usually missense variants located in the ZF1 domain (e.g., p.N317-L321 hotspot) or in-frame indels in the C-terminus . This suggests a likely difference in GATA2 function during the leukemogenic process between germline and somatic cases . Of note, somatic GATA2 mutations are often associated with both monoallelic and biallelic CEBPA somatic mutations . Additionally, somatic mutations in GATA2, although rare, have also been linked to milder forms of the immunodeficiency phenotype observed in patients with germline mutant GATA2 . 3. GATA2 Phenotypic Spectrum Heterozygous pathogenic variants in the GATA2 gene cause a highly heterogeneous disorder with incomplete penetrance . This may present with immunodeficiency (including monocytopenia with Mycobacterium avium complex (MonoMAC) infection and dendritic cell (DC), monocyte, B, and natural killer (NK) lymphoid (DCML) deficiency syndromes); syndromic features, such as congenital deafness and lymphedema (originally defining Emberger syndrome), or pulmonary and vascular involvement , and there is a high probability of evolving to MDS and/or AML. In 2011, these diverse clinical syndromes were linked to define a common genetic diagnosis of the GATA2 deficiency syndrome . Except for a few cases, the relationship between genotype and phenotype in these patients is poorly understood due to significant variations in clinical presentation, even among individuals within the same family . Therefore, determining the true clinical penetrance of this disorder would require a comprehensive examination of the genotypes of a large number of first-degree relatives of patients. It is worth noting some of the reported phenotype/genotype correlations: (1) patients with noncoding variants (which can account for up to 10% of cases) have been observed to exhibit reduced disease penetrance ; (2) the p.T354M variant seemed to be associated with a predominance of myeloid malignancies (83% of cases; 44/53), while p.R398W/Q variants were more commonly associated with immunodeficiency (88% of cases; 23/26) in a relatively large series ; (3) there have been indications that complete haploinsufficiency or loss of GATA2 function, rather than missense mutations, may be required for the development of lymphedema . These complex and variable presentations pose a significant challenge for clinicians when diagnosing and managing patients with GATA2 mutations. 4. Hematological Presentation The first hematoimmunologic manifestation typically occurs between the second and third decade of life, with a median age that varies in different studies (ranging from 12 to 19 years) . While some patients present with cytopenias, immunodeficiency, or BM failure during childhood, others can develop MDS without preexisting clinical features during young adulthood . 4.1. Bone Marrow Failure Unlike other germline alterations predisposing to HMMSs that preferentially lead to thrombocytopenia (e.g., ANKRD26, RUNX1, ETV6) , neutropenia may be the first and leading form of cytopenia in these patients. Although a decreased white blood cells (WBC) count can lead to a complex differential diagnosis, neutropenia with profound monocytopenia should prompt consideration of GATA2 deficiency . Paradoxically, monocytosis can be the initial presenting sign in patients who develop GATA2-related MDS . Bone marrow morphology can reveal altered cellularity ( normal or hypercellular marrow in patients with cytopenia or MDS, respectively), pronounced erythropoiesis, multilineage dysplasia, and fibrosis . 4.2. Myeloid Neoplasms GATA2 haploinsufficiency is a major contributor to MDS/AML in adolescents and young adults. While some patients who develop MDS have a high risk of progressing to AML or chronic myelomonocytic leukemia (CMML), a small subset presents directly with AML . Other reported hematological disorders include acute lymphoblastic leukemia (ALL), juvenile myelomonocytic leukemia (JMML), and myelofibrosis . The prevalence of GATA2 deficiency is currently unknown, but given the significant disease penetrance and low tolerance to pathogenic mutations in the GATA2 gene, it is likely that most carriers of the mutation will develop hematologic or immunologic complications over the course of their lifetime. In one study that reviewed 18 published series (>350 individuals), the penetrance of myeloid neoplasms was estimated to reach 75% in GATA2-mutated carriers , with an increased risk of developing MDS/AML as they aged. The risk of developing MDS/AML was calculated to be 6% at 10 years, 39% at 20 years, and 81% at 40 years in a series of 79 patients . While MDS/AML is the most common neoplasm in GATA2 deficiency, the EWOG-MDS study , which included 426 patients, found that GATA2 germline mutations were present in up to 7% of all pediatric cases with primary MDS and 15% of advanced MDS in examined series . Monosomy 7 is the most frequent cytogenetic alteration, being present in 37-57% of all patients with GATA2 MDS and 48-72% of adolescents (>12 years old) with GATA2 MDS . Since MDS is very uncommon during childhood, it would seem mandatory to screen all children with this diagnosis for GATA2 germline mutations . 5. Immunodeficiency Disorder GATA2 deficiency is a unique primary immune deficiency that is also known as immunodeficiency 21, DCML, or MonoMAC (OMIM #614172). The immune defect may appear in adult life, as the number of hematopoietic stem and progenitor cells (HSPCs) decreases with age, which makes GATA2 deficiency a unique primary immune deficiency . It is characterized by immunophenotype features resembling those seen in chronic infection or age-related immunosenescence. The spectrum of alterations can include dendritic cell deficiency, monocytopenia, loss of transitional B cells, the absence of CD56 bright NK cells (which presents an altered CXCL12/CXCR4-dependent chemotaxis ), reversed CD4:CD8 ratio, an excess of CD45RA+ CD8+ T cells, and poor-quality humoral response despite normal levels of immunoglobulins and an adequate presence of bone marrow plasma cells in most patients . As a result of immune deficiency, GATA2 carriers have an increased frequency of infections, with significant differences in the severity between patients . Due to the deficit and dysfunction of dendritic cells, NK cells, and monocytes/macrophages, the identification of viruses and intracellular pathogens is compromised, leading to the severe spread of viral infections and mycobacterial susceptibility . Donadieu and colleagues described severe bacterial infections as the most frequent pathogenic occurrences in GATA2 carriers, with a cumulative rate of 33% at 20 years and 64% at 40 years . On the other hand, Spinner et al. reported that severe viral infections were the most common ones in their series (70%), in particular those related to the human papilloma virus (HPV), which occurred in about two thirds of carriers . The most important complication derived from underlying HPV infection is the development of recurrent warts or condyloma that can lead to dysplasia and/or squamous carcinoma . Infections with other disseminated pathogens are frequently observed in GATA2-deficient patients, including non-tuberculous mycobacteria, herpes virus (varicella zoster virus, Epstein-Barr virus, and cytomegalovirus), and fungi (invasive aspergillosis, disseminated histoplasmosis, and candidiasis) . Therefore, various immunological factors are highly suggestive of GATA2 deficiency and should make the clinician think of this disorder. These include prior immunodeficiency in a patient with MDS, atypical mycobacterial infections in patients with monocytopenia, persistent warts or severe herpes virus infections in cytopenic patients, and loss of B cells and their precursors, especially in patients who develop MDS . Eventually, as in other immunodeficiencies, these patients can also present with autoimmune manifestations, described in 11-30% of cases , which may overshadow typical features of GATA2 deficiency and delay the diagnosis. Amarnani et al. reported rheumatological findings in 18% of their GATA2 deficiency cohort, with notable manifestations, including early onset osteoarthritis, piezogenic pedal papules, ankylosing spondylitis, and seronegative erosive rheumatoid arthritis . 6. Non-Hemato-/Immunologic Manifestations 6.1. Pulmonary Involvement Pulmonary dysfunction is a common finding in up to 50% of patients with GATA2 deficiency , even in the absence of hematopoietic disease, leading to progressive compromised pulmonary function with diffusion defects, ventilatory defects, or a mixed pattern, along with significant clinical and radiographic disease . In addition to recurrent infections, pulmonary alveolar proteinosis (PAP) is one of the most distinctive lung features. This rare disorder is characterized by the lack of anti-GM-CSF autoantibodies and the accumulation of surfactant proteins and subsequent impaired gas exchange . It results from impaired function of the alveolar macrophages in GATA2-deficiency patients, which are responsible for inadequate clearance, and is associated with increased restrictive ventilatory defects and pulmonary arterial hypertension (PAH) . Depending on the studied cohort, PAP and PAH may be present in 4-20% of patients . Therefore, it is recommended to screen patients with PAP and/or immunodeficiency and/or myeloid malignancies without anti-GM-CSF antibodies for GATA2 alterations. It is important to note that clinical variability within families, including asymptomatic relatives identified through family screening, has also been reported in the case of pulmonary dysfunction . Radiographic findings might be unspecific and will depend on the underlying disorder. Several structural abnormalities have been identified on chest computed tomography, including nodular and reticular opacities, ground-glass opacities, consolidations, a "crazy-paving" pattern, subpleural blebbing, and paraseptal emphysema . Although some of the lung manifestations, including PAP, PAH, and underlying infections, can be reversed as a result of an allogeneic hematopoietic stem cell transplantation (allo-HSCT) , it should be noted that HSCT toxicity related to the conditioning regimen and pulmonary graft-versus-host disease (GvHD) can also harm lung function . Therefore, individuals with GATA2 deficiency should undergo regular, ongoing monitoring of their lung function throughout their lifetime. Although there are no guidelines for the pulmonary follow-up of these patients, it should be individualized and tailored to each patient's needs. This may involve regular visits to a pulmonologist for symptom monitoring and pulmonary function testing to assess respiratory capacity. Imaging tests, such as chest X-rays or computerized tomography (CT) scans, may also be used to evaluate lung changes. Additionally, if there is suspicion of alveolar proteinosis, a diagnosis confirmation can be made through bronchoscopy with bronchoalveolar lavage (BAL) and/or parenchymal biopsy. 6.2. Emberger Syndrome: Dysmorphic Features Emberger syndrome (OMIM #614038) is characterized by the association of primary lymphedema (a common feature found in 11-20% of GATA2 carriers, typically affecting one or both lower limbs, frequently involving the genitals in the form of a hydrocele), with AML (often preceded by pancytopenia or MDS), with or without congenital sensorineural hearing loss . 6.3. Other Dysmorphic Features Additional dysmorphic features that have been described, include hypothyroidism, bilateral syndactyly of the toes, hypotelorism, and epicanthal folds, behavioral disorder, and urogenital malformations, among others . 7. Management and Surveillance 7.1. Allogeneic-HSCT Although allo-HSCT is the only curative therapy for the impaired hematopoietic and lymphoid systems of patients with GATA2 deficiency , it represents a therapeutic challenge due to disease-associated comorbidities and clinical heterogeneity. Meanwhile, determining who should be candidates for allo-HSCT and when it should be performed (so that the benefits outweigh the risks) are questions that remain under debate . Moreover, due to the low prevalence and relatively recent description of GATA2 deficiency syndrome, most outcomes and complications following allo-HSCT have been described in case reports or small series . While some studies have reported an overall survival (OS) rate in 5-year posttransplant patients with clonal events at a rate of 55-60% , other reports have shown superior outcomes after the procedure . Notably, Nichol-Vinueza et al. showed a 4-year posttransplant OS rate of 85.1% . However, these cohorts are not necessarily comparable due to the heterogeneity of conditioning regimens and GvHD prophylaxis, donor type source, HSCT-related risk factors, duration of follow-up, and the clinical status or comorbidities of the GATA2 patient population . 7.1.1. Indications for and Timing of allo-HSCT While hematologic malignancy development may be the most dangerous complication and a primary indication for transplant, it is not the only one. Restoring normal immunity and lung function is also important in the decision to proceed with SCT . The lack of a genotype-phenotype correlation makes the natural history of GATA2 deficiency unpredictable, to the point that there are patients who become symptomatic after many decades. However, once symptoms appear, survival declines, with a probability of survival by 40 years of 60-80% according to different series . In this regard, the ideal time for allo-HSCT should be after the onset of symptoms but before irreversible organ damage occurs , although more specific criteria for the timing need to be defined . While some authors report better outcomes when HSCT is performed earlier after diagnosis and when there are fewer comorbidities , the EWOG-MDS 2017 guidelines on childhood MDS recommend watchful waiting if blood cells are stable and high-risk genetic aberrations are absent . By contrast, other authors go as far as to propose that preemptive allo-HSCT could improve overall outcomes before malignancy develops . More specific treatment strategies have yet to be fully elucidated. There are three major indications for HSCT. Firstly, diagnosis of MDS/AML, however, it is not clear if better timing for HSCT is during the hypocellular MDS phase or when the patients develop cytogenetics abnormalities/excess of blasts . Secondly, history of severe, recurrent, or treatment-refractory infections, particularly aggressive HPV infection. Relapsed/refractory precancerous or malignant disease due to HPV should be an indication for allo-HSCT. In this sense, considering the iatrogenic immunosuppression after HSCT, rigorous evaluation for HPV must take place before and after transplantation so that surgical and other therapeutic measures can be undertaken in cases with new or persistent disease . Thirdly, progressive lung injury from infection and PAP, which leads to deteriorated lung function . 7.1.2. Conditioning, Graft Source, and Donors Transplanting GATA2-deficient patients is a controversial topic due to the variable disease progression and the timing of HSCT . Although nonmyeloablative HSCT can reverse clinical manifestations and was the strategy used in the earlier years, relapse rates, engraftment failure, and late graft rejections led to the consideration of more intensive conditioning regimens . In this regard, several reports have demonstrated similar outcomes when using myeloablative regimens in patients with mutated and wild-type (wt) GATA2 . However, in patients with low-stage and hypocellular MDS, myeloablation may not be necessary due to low rates of relapse , and the intensity can be reduced by using a controlled approach . Therefore, some authors propose that the choice of conditioning scheme choice for GATA2-deficient patients should be based on the patient's MDS phenotype and cytogenetics . The donor source constitutes a critical variable in the outcome of HSCT. Although it is still unclear which donor source will yield better outcomes for GATA2-deficient patients , it has been suggested that bone marrow should be preferred over peripheral blood, while umbilical cord blood should be avoided . Matched related donors remain the best choice, although haploidentical HSCT could be an appropriate alternative . 7.1.3. HSCT-Derived Complications Bortnick et al. conducted a study of 65 cases and found that pediatric patients with GATA2 deficiency had a similar risk of transplant-related toxicity (TRT) or transplant-related mortality (TRM) as compared to those with wt GATA2 . However, they also reported that three patients developed transplant-associated microangiopathy, which might indicate a distinct endothelial vulnerability in GATA2 patients, consistent with the known role of GATA2 in the perturbation of normal vascular development . Simonis et al. conducted a systematic review of 183 patients (median age 23 years) from January 2010 until March 2018 and reported that the risk of TRT was not higher in patients with GATA2 deficiency compared to those without it . Similarly, Hofmann et al. reported no differences in TRM and overall organ toxicity between a pediatric cohort with GATA2 deficiency and controls . However, they did observe a small number of serious and unusual infectious/immunologic complications and neurologic toxicities in the GATA2 population, as well as a higher rate of thrombotic events in GATA2 patients, with complete resolution after transplantation . Although information about GvHD is often not available in these series, it seems that the proportion of patients with acute or chronic GvHD is similar to that of other transplant cohorts . Reducing the severity of both acute and chronic GvHD is being evaluated in GATA2 deficiency patients with promising outcomes by administering post-cyclophosphamide (PTCy) after HSCT, as seen in wt GATA2 patients . However, when HSCT is indicated but no preexisting malignancies are present, strategies to prevent GvHD are of the greatest importance, as there is no advantage to this complication . In summary, considering that there are no formal recommendations on the indications for allo-HSCT, conditioning regimen, GvHD prophylaxis, donor source, and antibiotic prophylaxis in GATA2-deficiency patients, the decision to perform an allo-HSCT requires careful and individualized management . Although treatment-related morbidity is manageable in these patients, an individualized approach should be taken into consideration for optimal outcomes. 7.2. Antibiotic Prophylaxis, Immunoglobulins, and Vaccination Prior to performing allo-HSCT, it is crucial to effectively treat any severe infections to create a favorable environment for the transplanted donor stem cells to thrive . Although opportunistic infections that manifest before transplantation do not seem to pose a major issue in terms of overall outcomes, patients are typically kept on antibiotic prophylaxis to prevent such infections. While most case reports of allo-HSCT do not provide details on the antibiotic prophylaxis regimen, in a study by Simonis et al., patients treated for non-tuberculous mycobacterium before HSCT took prophylactic azithromycin until the time of transplant and for about one year afterward . For patients still receiving treatment for active infection at the time of HSCT, antimycobacterial drugs were administered for 6-12 months after the transplant . Spinner et al. also recommend azithromycin for all patients with GATA2 deficiency even before HSCT is indicated . Although rare, GATA2 patients may experience humoral deficiency . In such cases, immunoglobulin replacement may be necessary . Due to the high susceptibility of patients to HPV and the potential for recurrent and life-threatening oncogenic HPV lesions, early vaccination is likely to be beneficial . 7.3. Surveillance Given the complexity of information available on GATA2 deficiency syndrome and other HMMSs, patients should be referred to multidisciplinary teams that include physicians who are well-versed in these conditions. This would facilitate the assessment of potential organ-system manifestations that could impact the patient's treatment, and promote consultation with appropriate subspecialists. Since most patients with symptomatic GATA2 deficiency will eventually require an allo-HSCT, close monitoring is crucial in order to perform the procedure before organ damage occurs . Therefore, a donor search should be conducted as soon as the deficiency is diagnosed, with systematic testing of potential relatives considered for donation . Allo-HSCT can eradicate clonal malignancy, restore normal hematopoiesis, clear underlying infections, and improve pulmonary symptoms and function in patients with PAP . However, it cannot reverse extra-hematopoietic manifestations of GATA2 deficiency, so patients remain at risk for non-hematopoietic issues and will require lifelong follow-up . It is worth mentioning that HPV can persist after allo-HSCT, so gynecologists play an important role in guiding the management and surveillance of these patients , especially during the period of immunosuppression following the procedure. 7.4. Family Monitoring Genetic testing should be offered to first-degree relatives, particularly to potential donors of HSC progenitors, to identify asymptomatic carriers with GATA2 deficiency. According to some authors, hematological surveillance of carriers should include annual bone marrow analysis with morphological, cytogenetic, and molecular evaluation to prevent the appearance of new driver acquisitions . Moreover, some researchers recommend avoiding exposure to corticosteroids and immunosuppressive drugs and monitoring pulmonary function regularly to prevent complications . 7.5. Genetic Counseling It is important to note that genetic counseling should be offered to family members who test positive for GATA2 mutations to help them understand the implications of the diagnosis and the potential risks of passing the condition on to their own children, and they should receive proper information about the different reproductive or prenatal diagnostic options. 8. Conclusions Recognizing GATA2 deficiency in clinical care is crucial for several reasons . Firstly, an accurate diagnosis can help patients understand their specific disorder and avoid inappropriate treatments. Secondly, a genetic diagnosis can aid in selecting the most suitable HSCs donor for an allo-HSCT. TShirdly, identifying GATA2 syndrome can impact treatment recommendations and disease management for patients and their families. As patients with this condition face various complications affecting many systems, HSCT is often an attractive therapeutic option. The choice of therapy largely depends on the patient s age, the availability of a compatible donor, and any co-existing medical conditions. Thus, early and accurate diagnosis of these patients allows for tailored therapy. 9. Future Directions As awareness of GATA2 deficiency grows within the scientific community, early diagnosis will help in avoiding unnecessary diagnostic procedures and enable tailored strategies, for both treatment and surveillance . Moreover, we may be able to identify patients who are at high risk of transforming to myeloid malignancies based on factors such as molecular alterations, cytogenetic evolution, or severity of cytopenias. By managing these patients early, we can aim for better outcomes before organ dysfunction occurs. Author Contributions M.S.; writing--original draft preparation, M.S., A.L., E.S., A.Z. and J.C.; writing--review and editing, J.C.; supervision. 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 Germline and somatic GATA2 (likely) pathogenic variants obtained from ClinVar and COSMIC databases, respectively. Somatic variants are restricted to those found in hematopoietic malignancies. Variants were visualized using the ProteinPaint web application accessed on 27 January 2023) and colored based on their functional type (e.g., frameshift and missense). Since the effect of splice variants is often undetermined, these were annotated on the position of the closest amino acid that would be involved (e.g., the NM_001145661:c.1018-1G>T variant is annotated as X339_splice). Numbers in circles indicate the number of entries and/or reported cases. All variants are annotated to NM_001145661. Figure 2 GATA2 deficiency clinical spectrum. HPV, human papilloma virus; MDS, myelodysplastic syndromes; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia. Figure made using accessed on 27 January 2023. 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PMC10000431 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050704 cells-12-00704 Article Quanty-cFOS, a Novel ImageJ/Fiji Algorithm for Automated Counting of Immunoreactive Cells in Tissue Sections Beretta Carlo Antonio 12* Liu Sheng 1 Stegemann Alina 1 Gan Zheng 1 Wang Lirong 1 Tan Linette Liqi 1 Kuner Rohini 1* Smet Frederik De Academic Editor 1 Pharmacology Institute, Heidelberg University, Im Neuenheimer Feld 366, 69120 Heidelberg, Germany 2 Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Im Neuenheimer Feld 307, 69120 Heidelberg, Germany * Correspondence: [email protected] (C.A.B.); [email protected] (R.K.) 23 2 2023 3 2023 12 5 70418 11 2022 17 1 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 ). Analysis of neural encoding and plasticity processes frequently relies on studying spatial patterns of activity-induced immediate early genes' expression, such as c-fos. Quantitatively analyzing the numbers of cells expressing the Fos protein or c-fos mRNA is a major challenge owing to large human bias, subjectivity and variability in baseline and activity-induced expression. Here, we describe a novel open-source ImageJ/Fiji tool, called 'Quanty-cFOS', with an easy-to-use, streamlined pipeline for the automated or semi-automated counting of cells positive for the Fos protein and/or c-fos mRNA on images derived from tissue sections. The algorithms compute the intensity cutoff for positive cells on a user-specified number of images and apply this on all the images to process. This allows for the overcoming of variations in the data and the deriving of cell counts registered to specific brain areas in a highly time-efficient and reliable manner. We validated the tool using data from brain sections in response to somatosensory stimuli in a user-interactive manner. Here, we demonstrate the application of the tool in a step-by-step manner, with video tutorials, making it easy for novice users to implement. Quanty-cFOS facilitates a rapid, accurate and unbiased spatial mapping of neural activity and can also be easily extended to count other types of labelled cells. quantitative analysis immunohistochemistry in situ hybridization Fos protein c-fos mRNA 2D automated cell counts open-source ImageJ/Fiji tool Deutsche Forschungsgemeinschaftprojects B01, B06 and Z01 Affiliated Hospital of Zunyi Medical UniversityChina scholarship councilUnion Hospital, Tongji Medical college, Huazhong University of Science and TechnologyThis research was funded by the Deutsche Forschungsgemeinschaft in form of a CRC1158 grant to R.K. (projects B01, B06 and Z01). The authors gratefully acknowledge scholarship support for S.L. from the Affiliated Hospital of Zunyi Medical University, China and China scholarship council, Z.G. from Union Hospital, Tongji Medical college, Huazhong University of Science and Technology and L.W. from China scholarship council. pmc1. Introduction Analysis of neural circuits frequently relies on the use of immunohistochemistry assays to identify specific cell types using neurochemical marker proteins or mRNAs target genes. Similarly, quantitative analyses of cell counts expressing plasticity markers, such as the activity-induced immediate early gene, c-fos, represent a cornerstone of studying neural plasticity processes over large cellular networks in histological specimens. However, reliably counting cells immunohistochemically positive for protein markers or for mRNAs visualized in in situ hybridization experiments in large histological specimens, such as brain sections, remains a major challenge. Manual counting is extremely time-consuming, cumbersome and prone to subjective variations. Recently, several automated digital image analysis tools have been developed. A major part of this development has focused on an automated analysis of the expression levels of proteins over regions of interest in histological specimens, such as tumor or immune markers, as clinical diagnostic or prognostic tools . Despite this progress, availability of automated tools that enable easy-to-use, reproducible and reliable identification and quantitative counting of positive cells in immunohistochemical or mRNA in situ hybridization experiments on thick slices of tissue remains limited . Often, user is required to have image analysis skills and experience, in-depth coding knowledge or access to expensive commercial software. Furthermore, automated tools for the identification of positive cells need high signal-to-noise levels, thus favoring highly expressed proteins. Signals representing nuanced differences in expression levels, high background and difficult antibodies, in contrast, are not suitable for conventional automated tools. This is particularly relevant to the protooncogene c-fos, the immediate early gene that is directly induced in expression upon neuronal activation, leading to a rapid and transient build-up of c-fos mRNA and consequently of the Fos protein, which decays shortly after cessation of neuronal activity. Over the recent years, mapping Fos expression has emerged as a technically simple and reliable global marker for analyzing neurons that are activated by diverse external inputs, such as sensory stimuli . Moreover, because Fos expression is well-correlated with behavioral readouts in animals, Fos-based mapping enables spatial analysis of regions and cells recruited during particular behaviors . Finally, Fos expression is frequently used to characterize the effects of diverse therapeutic regimens on the central nervous system . The recent development of Fos-based transgenic tools for labelling ensembles, i.e., cells that are co-active during particular functional tasks, as well as approaches that enable the consecutive labelling of two distinct cell populations with c-fos mRNA and the Fos protein, provide tremendous scope for studying functional encoding in the nervous system . Thus, although they lack the spatial resolution of direct electrophysiological measurements, Fos-based mapping approaches represent attractive, highly useful and popular tools that are delivering unprecedented insights into neural function. Quantifying Fos-expressing neurons, however, still represents a major problem owing to high background levels and non-linear expression with different levels of signal-to-noise within and across samples preparations. Batch-to-batch variability of both antibody-based signals as well as c-fos mRNA in situ probes leads to several confounding effects. This has led to the necessary use of experimenter-based manual counting in studies employing Fos-based mapping in a quantitative manner, which is highly laborious, time-consuming, not entirely objective and highly subject to experimenter bias. Here, we report the development of an open-source tool for ImageJ/Fiji , called 'Quanty-cFOS', with an easy-to-use, streamlined pipeline for automated or semi-automated quantitative analysis of cells positive for the Fos protein and/or c-fos mRNA on two-dimensional images (2D) or confocal maximum intensity projections (MIP) derived from tissue sections. Using example data sets of brain tissue from mice subjected to somatosensory stimuli, we demonstrate the entire process in a step-by-step manner and with the use of video tutorials, making it easy for novice users to apply on their images. Using manual counting to establish ground truth, we demonstrate both the fidelity of Quanty-cFOS and its ability to overcome user-to-user subjective variability. The tool also takes into account day-to-day and sample-to-sample variations in staining efficiency and enables for the deriving of cell counts registered to specific brain areas in a highly time-efficient and reliable manner. Thus, by delivering reliable and fast automated cell quantification across complex, technically non-optimal data sets, Quanty-cFOS accelerates the use of Fos mapping for analyses of neural circuits and thus provides an impetus to a wide range of research fields, including memory, chronic pain, addiction and psychiatric disorders. Importantly, although this tool was optimized and validated for quantitating Fos-expressing cells, it is just as readily applicable to any antibody, and is particularly suitable for proteins that show a variable baseline and induced expression within and across samples. 2. Materials and Methods 2.1. Animals All experiments were conducted in C57BL/6J male mice (20-30 g) at 8 weeks of age that were obtained from Janvier Labs. In total 12 animals were used. Mice were housed individually in separated cages and kept under a 12 h light/dark cycle at a controlled temperature (22 +- 2 degC), humidity (40-50%), with food and water provided ad libitum according to ARRIVE guidelines. All experimental procedures were approved by the local governing body (Regierungsprasidium Karlsruhe, Germany, Ref. 35-9185.81/G-184/18), and abided to German Law (TierSchG, TierSchVersV) that regulates animal welfare and the protection of animals used for scientific purpose. 2.2. Application of Sensory Stimuli and Fos/c-fos Induction A heat stimulus was presented to mice on a hot plate at 50 degC for 30 s (Ugo Basile Inc., Gemonio, Italy). Mice were exposed only once. To allow sufficient expression of Fos and to validate the Quanty-cFOS ImageJ/Fiji tool, C57BL/6J mice were kept in a home cage after stimuli for 20 min, 1 h or 3 h after the application of the stimulus prior to perfusion. 2.3. Tissue Fixation and Immunofluorescence Antibody Staining Mice were sacrificed with an overdose of carbon dioxide, transcardially perfused with pre chilled phosphate-buffered saline (PBS) followed by 10% formalin fixative solution (Merck, Darmstadt, Germany). The brains were extracted and fixed in 10% formalin for 24 h at 4 degC. Coronal brain sections were collected at 50 mm with a vibratome (Leica VT100S, Wetzlar, Germany). Free-floating sections were incubated in antigen retrieval solution (2.94% Tri-sodium citrate in dH2O, pH 8.5) for 25 min at 85 degC, and after cooling down, washed at room temperature with 50 mM Glycine (AppliChem, Darmstadt, Germany) for 10 min, followed by PBS for 5 min and 0.2% Triton X-100 (Carl Roth, Karlsruhe, Germany) in PBS (PBST) for 15 min. Lastly, sections were treated with 5% horse serum in PBST for 1 h, before incubating with the rabbit anti-Fos primary antibody (Ab190289, 1:1000 in 5% horse serum in PBST, Abcam, Cambridge, UK) at 4 degC overnight. The next day, sections were washed with 5% horse serum in PBST 3 times for 10 min and incubated with the donkey anti-rabbit Alexa 594 secondary antibody (Ab21206, dilution 1:700 in 10% NHS in PBS, Thermo Fischer Scientific, Waltham, MA, USA) for 2 h. After washing again with 5% horse serum in PBST 3 times for 10 min and in PBS for 10 min, Hoechst (#H367, 1:10,000 in PBS, Thermo Fischer Scientific, Waltham, MA, USA) was added for 10 min, followed by washing 3 times in PBST for 10 min each and in 10 mM TRIS-HCl for 10 min before mounting on glass slides with Mowiol. 2.4. c-fos mRNA In Situ Hybridization and Fos Immunofluorescence Co-Staining For brain tissue preparation, mice were killed with CO2 at a defined time interval after the application of the external sensory stimulus and perfused with chilled PBS, followed by chilled 4% PFA. Brains were removed and held in 4% PFA for 3 h and transferred to 30% sucrose-PBS at 4 degC for 18-24 h. Brains were coronally sectioned with a cryotome (Leica CM1950, Wetzlar, Germany) at 50 mm and slices collected into 24-well plates with chilled PBS. All equipment was precleaned with RNaseZAP (Sigma RNaseZAP, Darmstadt, Germany), and all reagents were prepared using diethyl pyrocarbonate (DEPC)-treated PBS to avoid RNase contamination. For mRNA in situ hybridization, the c-fos mRNA in situ probe was constructed according to the information on the Allen Brain Atlas website accessed on 15 February 2023). The RNA probe was generated via an in vitro transcription and labeled using the DIG-RNA-Labeling Mix kit and T7 RNA polymerase (Merck, Darmstadt, Germany), dissolved as a 1 mg/mL concentration in the hybridization solution (50% formamide (v/v), 5x SSC, 0.3 mg/mL Yeast tRNA and 0.5 mg/mL Salmon Sperm DNA). For c-fos tyramide-amplified in situ hybridization, slides were firstly washed 3-times with ice-cold PBS for 3 min and treated with acetylation buffer (0.25% acetic anhydride (v/v) in 0.1 M triethanolamine) for 10 min at room temperature. After rinsing once with cold PBS, cells were permeabilized with 0.3% TX100-PBS for 20 min at 4 degC. For in situ hybridization, tissues were pre-hybridized in hybridization buffer for 30 min. For hybridization, a c-fos anti-sense probe (diluted 1:200 in hybridization buffer) was applied and incubated overnight at 65 degC. The sense probe was applied to control slides. Post-hybridization, the tissue was washed twice with 2 x SSC/0.1% N-Lauroylsarcosine/50% formamide at 60 degC, rinsed in RNAse buffer (10 mM Tris, pH 8.0, 500 mM NaCl, 1 mM EDTA) and then digested with 20 mg/mL RNaseA in the RNase buffer for 30 min at 37 degC. This was followed by washing with 2 x SSC/0.1% N-Lauroylsarcosine and 0.2 x SSC/0.1% N-Lauroylsarcosine twice for 20 min at 37 degC and then rinsed once again with MABT (Maleic acid buffer with 1% of Tween 20). Tissue was then blocked with MABT++ (MABT with 10% heat-inactivated goat serum and 1% Blocking reagent) for 1 h at room temperature. Next, the tissue was incubated in MABT++ solution with the anti-digoxygenin antibody (anti-DIG-POD, 1:1000, Roche, Basel, Switzerland) at 4 degC for 16 h. For signal amplification, the slides were washed with MABT for 30 min at least 6 times, then rinsed with TSA buffer (10 mM imidazole) and incubated with TSA staining solution (Dilute Rhodamine tyramide 1:75 in TSA buffer, add in 0.001% H2O2) for 20 min at room temperature in the dark, followed by washing with PBST (PBS with 0.1% Tween 20) for 10 min, 5 times at room temperature in the dark. Tissues were mounted on slides with Mowiol after washing with PBS for single mRNA staining, or further used for immunofluorescence co-staining. For immunofluorescence co-staining, the tissue was first washed with T-BST (0.05% Tween 20 and 0.05 M Tris-HCl in PBS) for 10 min, 5 times at room temperature in the dark and afterwards incubated with the anti-Fos primary antibody (1:1000, abcam, ab190289) in T-BST at 4 degC overnight. On the second day, the tissue was washed 3 times for 5 min in T-BST and then incubated with species-specific fluorescent secondary antibodies in T-BST for 1 h at room temperature. Finally, slides were washed 3 times for 15 min with 0.3% T-BST, then again with T-BST 3 times for 10 min and finally rinsed with 10 mM Tris-HCl for 10 min before mounting the coverslips with Mowiol. 2.5. Confocal Laser Scanning Microscopy Acquisition Settings As examples of the region showing robust Fos expression upon somatosensory (cold) stimulation as well as reasonable baseline activity, coronal sections from the prelimbic and insula cortex (from 2.4 mm to 0.37 mm anterior to the bregma) were used for analysis. A confocal microscope (Leica TCS SP8, Wetzlar, Germany) was used to acquire immunofluorescence image stacks with 2 mm-thick planes using the 20x objective (N.A.: 0.75, oil immersion). Laser diode wavelengths of 405, 488, 552 and 638 nm in combination, respectively, with filters sets for DAPI (ex BP360/403 em LP425), FITC (ex 470/40, em LP515) and TRITC (ex 540/45, em LP590) were used. This resulted in an average z-optical section of 20 mm. The Fos protein signal showed nuclear staining pattern, whereas the c-fos mRNA appeared mostly in the cytoplasm. 2.6. Manual Counting of Cells Positive for Fos Protein or c-fos mRNA For manual counting, the experimenter was blind to the different test groups, and images from groups were assigned a random number prior to analysis that was decoded after analysis. All confocal images were overlaid with the corresponding atlas section to anatomically define the regions of interest. All labeled cells within the boundaries of the defined sites were marked using a self-developed tool accessed on 15 February 2023) for ImageJ/Fiji and manually counted on MIP obtained from confocal stacks . Brightness and contrast were optimized for each image. Background subtraction was performed by subtracting the mean intensity value estimated from a single background ROI placed within an unlabeled region in the same image. The Fos protein and c-fos mRNA signals were analyzed as separate images taken from the same slice using their respective excitation wavelengths. Positive cells on the XY boundary were excluded, and Fos protein signals were typically 6-8 mm in diameter and located in or near the nucleus. Nuclei were identified via DAPI staining. The c-fos mRNA signals were located in the cytoplasm as regions of 8-16 mm diameter surrounding the nucleus. In order to be counted positive, a cell had to display an intensity value above the intensity threshold of the background. 2.7. Quantification of Fos Protein and c-fos mRNA Intensity Features for Development of Quanty-cFOS Image intensity features were extracted from 60 images acquired by 4 experimenters for the anti-Fos antibody staining and from 63 images acquired by 2 experimenters for the c-fos mRNA in situ using a customized ImageJ/Fiji script accessed on 15 February 2023). The script extracts intensity features to measure Fos staining variability between different preparations and image acquisition settings. The following features were computed for each image: mean intensity, standard deviation intensity, minimum intensity, maximum intensity, mode intensity and mean background intensity. 2.8. Development of Quanty-cFOS, an ImageJ/Fiji Tool to Count Fos/c-fos Positive Cells in an Unbiased Meter Here, we developed Quanty-cFOS.ijm as an ImageJ/Fiji tool to semi-automatically or automatically count in an unbiased manner cells expressing the Fos protein or c-fos mRNA in fixed stained brain slices. It can be extended to generally count cell markers in 2D fluorescent images or on MIP. For flexibility reasons, this tool is developed as a macro-set (IJ1) for ImageJ/Fiji (tested on ImageJ version 1.53s and later) . The proposed workflow consists of two major steps:- Automated cell segmentation, - Cell counting using the automated or the manual optimization method. The Quanty-cFOS tool can be downloaded from (accessed on 15 February 2023) and we provide a detailed step-by-step documentation of how to use it, including supplementary videos and several scripts to validate the cell counting (the GitHub validation folder). 2.9. Automated Cell Detection with Quanty-cFOS Quanty-cFOS cell detection is implemented using two different state-of-the-art segmentation strategies, based on deep learning and machine learning. The first uses the StarDist 2D Versatile (Fluorescent-Nuclei) inference available in the StarDist ImageJ/Fiji plugin and applies it on the raw images to segment convex shape structures . The second uses the ilastik software pixel classification machine learning workflow to generate a probability map image using manual user annotations for different classes of pixels in an image . In this case, the corresponding probability map image is loaded in addition to the raw input image in the Quanty-cFOS and intensity-thresholded to segment the cells. The user can decide which method is more suitable to process the images depending on the signal-to-noise ratio and on the shape of the cells that need to be segmented. The ilastik pixel classification workflow needs to be trained in ilastik software before to run the Quanty-cFOS tool accessed on 15 February 2023). 2.10. Automated Intensity Optimization Method in Quanty-cFOS A key feature defining the novelty of the Quanty-cFOS counting method is the z-score intensity cutoff used for the Automated Optimization. The proposed algorithm computes the mean intensity value and the intensity standard deviation of each single segmented cell in the images, averages these two values and computes the z-score (Zi):Zi=xi-ms xi: single cell intensity m: mean cell intensity s: mean cell intensity standard deviation The intensity values in the significant z-score range (sigma) are averaged and used to set the intensity thresholds cutoff to count Fos/c-fos-positive (above) or negative (below) cells. The user can specify the range of standard deviations (sigma) to optimize the cutoff value for the Fos/c-fos cell counts. The larger the sigma value, the less restricted is the intensity cutoff value, and vice-versa. IcS Zi-S=i=1nixin IcS: intensity cutoff computed on an image Zi: z-score S: significant range of standard deviations (sigma) xi: single cell intensity n: number of positive cells in an image The cutoff optimization is critical to gain an accurate and robust estimation of cell numbers. To consistently calculate the mean and standard deviation intensity, an arbitrary number of images can be used as input to compute the intensity cutoff (see Batch Analysis with Optimization Steps). In this case, the average intensity values of the images used for the optimization are accounted to calculate the intensity cutoff. IcA=i=1fiIcSf IcA: intensity cutoff with the optimization steps IcS: intensity cutoff x image f: optimization steps The results of the automated intensity method can be validated by manually counting cells in fewer images and by running the MATLAB correlation analysis provided together with the Quanty-cFOS (CorrelationAnalysis.mlx, see also the ValidationTable.xlsx file as an example). Manual counting can be performed using any favorite tool or by using the following ImageJ/Fiji IJ1 script that we developed for this purpose accessed on 15 February 2023). 2.11. Manual Intensity Optimization Method in Quanty-cFOS The intensity threshold value used for Fos/c-fos cell counting is the key parameter to decide the cutoff for positive or negative counts. This is rather important if images have been acquired with different settings or high staining variability occurs between samples. To optimize this process and to help test different threshold values in a semiautomated unbiased way, we implemented the Manual Optimization function. By using this method, images can be previewed, and different intensity values can be tested for Fos/c-fos-positive cell counting. The Manual Optimization default intensity value displayed in the user setting dialog box is computed via the Automated Optimization function to help in choosing the appropriate intensity cutoff value. Moreover, different size filters for the cell area can be applied to remove small and large detected objects in the images. The number of images previewed is specified using the Optimization Steps. Indeed, only these images are used for testing different thresholds and the average intensity value of these thresholds is applied as an intensity cutoff on all the subsequently listed raw images. 2.12. Cell Batch Analysis without Intensity Optimization in Quanty-cFOS (Optional) Counting all cells without intensity optimization is also possible as an option and can be achieved by unchecking the Automated Optimization and the Manual Optimization. In this way, all the cells in the image are counted without an intensity cutoff. Only a size cutoff filter (based on the cell area) is applied to exclude cells below the cutoff value and 5 times above the specified cutoff value. This option is supported only with Batch Analysis and the number of Optimization Steps is ignored. 2.13. Additional Quanty-cFOS Functionalities Select Multiple Sub-Brain Region was added to select specific regions of interest in the input images and to count positive cells only inside the selected regions. This option works only without batch analysis. Select Allow Preview User Setting was added to preview the intensity threshold and area cutoff used for the ilastik probability map segmentation (simple method). The intensity threshold method and cell size filter (area) can be modified to gain the best segmentation results. Currently, we support simple ImageJ/Fiji thresholding methods to segment cells in the ilastik probability map. 2.14. Additional Software Matlab (R2019a) was used for the correlation analysis and statistics. Figures were prepared using Adobe Photoshop CS6 (Adobe) and Adobe Illustrator CS6 (Adobe). DaVinci Resolve was used to edit the supplementary movies. 2.15. Statistical Analyses All statistical analyses were performed in Matlab (R2019a). Box plots were created using the Matlab box plot function and show the mean intensity value +/- and the standard deviation (S.D.) of each plotted feature. The black horizontal line in each box represents the median value z-score. Analysis was computed in Matlab, and a positive correlation was considered in the range of two standard deviations. Box plots were generated for each time point for c-fos mRNA and Fos protein counts. Each box shows the mean intensity counts, the vertical lines show the S.D. (+/-). 3. Results 3.1. Fos/c-fos Staining Can Lead to Biased Results Depending on Sample Preparation and Microscopy Acquisition Settings Our past experience has shown that quantifying Fos-expressing cells is challenging, not only because major differences exist in expression levels across cells as well as across samples, but also owing to technical aspects of sample preparation and imaging parameters. This was again observed when we acquired Confocal Laser Scanning Microscopy (CLSM) z-stacks after Fos protein immunostaining and c-fos mRNA in situ hybridization, as described under methods. To address differences in the image acquisition, four different experimenters prepared the samples, optimized the confocal settings and acquired the images . We quantified Fos protein expression by extracting intensity features along the different staining and acquisition settings (ImageJ/Fiji Set Measurement plugin) . Our analysis revealed major differences between the different extracted features across samples and experimenters. Indeed, we observed a high variability for the mean image intensity, mode intensity and mean background intensity features . Intriguingly, the maximum intensity feature also showed a large dynamic range, suggesting fluctuation in the signal-to-noise ratio between acquired images. Moreover, for the minimum and the mode intensity, several data points were detected outside the whiskers in box-and-whisker plots, highlighting the differences between stained images . The c-fos mRNA was evaluated in the same way on two different sets of samples prepared by two experimenters. The analysis revealed an even larger variability in terms of the mean image intensity, mode intensity and mean background intensity features . Differently from the Fos protein, the maximum intensity value is set to 255 for an 8-bit dynamic range (0-255), indicating that all the images have been saturated while being acquired. This is indicative of a low signal-to-noise ratio for the c-fos mRNA that required a high confocal gain or/and laser power during image acquisition. Considering the extracted intensity variability between the tested images, fewer data points were detected outside the whiskers . Intensity fluctuations between different staining rounds, acquisition settings and in between images acquired to investigate a specific physiological problem can lead to bias, especially if cell counting is the main readout. These experiments thus demonstrate the need to reduce bias in manual counts, which served as the starting point of our efforts toward developing the Quanty-cFOS ImageJ/Fiji tool for the automated/semiautomated counting of cells positive for the Fos protein and c-fos mRNA. 3.2. Fos/c-fos Cell Counting Workflow with Quanty-cFOS The Quanty-cFOS was developed to be a user-friendly, unbiased ImageJ/Fiji tool for Fos protein and c-fos mRNA counts. The workflow consists of four major steps: input, detection, quantification and results . An input directory containing all the Fos protein images to process can be chosen. For the Fos protein detection, we used the StarDist 2D versatile fluorescent nuclei model in the Quanty-cFOS . This method generated labeled images and it was optimized to segment convex objects in two dimensions (2D). The cell detection can be easily improved in the Quanty-cFOS tool by training a custom StarDist 2D model . For the c-fos mRNA counts, we used two input directories. The detection method uses pre-processed images obtained from ilastik pixel classification workflow in combination with the raw images . We implemented this method to detect any cell shape, from convex to more elongated shapes. Moreover, this option allows us to choose any pre-processed method in case cell detection is inefficient and upload the pre-processed images in the tool. MIP are automatically created using the Quanty-cFOS tool or can be generated by the user prior to the cell counting. The Quanty-cFOS tool supports three methods for cell counting: 'automated optimization', 'manual optimization' and 'all cells counts'-'with batch analysis' and 'without batch analysis' . The option 'with batch analysis' has been implemented to help the user in choosing the detection parameters and the intensity cutoff to batch process all the images in the input source directory by applying the same settings. This modality allows us to apply the 'automated optimization', the 'manual optimization' and 'all cells counting' methods . Choosing the detection parameters can be difficult, in particular when the images are different from each other, or the counting method settings needs to be changed during the processing. Therefore, to simplify cell counting, we developed the option 'without batch analysis' . Optimization methods and parameters can be changed for each image to achieve the best counts. This method is recommended if the images to process are very different from each other, or different parameters need to be tested for the cell counting. Chosen parameters are thereby saved in the root output directory to document the analysis (output Log.txt file). This modality can be used only for the 'automated' and the 'manual optimization' methods. Moreover, the option 'without batch analysis' supports the multiple 'sub-brain regions selection' function to count Fos-positive cells in selected subregions of an image . The 'automated optimization' method is used to compute the intensity threshold cutoff on a predefined number of images specified via the 'optimization steps' and applies this cutoff to all the following images listed in the input directory . The cutoff intensity threshold is computed on the optimization images by calculating the z-score. Only cell intensity values in the range of the specified z-score sigma (number of standard deviations) are averaged and contribute to the final intensity cutoff. The 'manual optimization' method allows the user to choose the intensity cutoff by previewing a selected number of images specified via the 'optimization steps'. These values are averaged and used as an intensity cutoff for cell counting . For both methods, an area filter is applied. For the 'automated optimization option', the area is set two times above and below the area standard deviation. In the 'manual optimization', the area can be measured on the previewed images and the cutoff value can be specified. The option 'All cells counts' can be used to count all the positive cells in the images without any 'optimization steps' . This has been included to count in 2D all the cells in an image independently of an intensity cutoff. To simplify further analysis and statistics, the Quanty-cFOS output consists of an output root directory created outside the input path with subdirectories named as the input processed images. Each subdirectory saves the labeled image for positive and negative cells , the ImageJ/Fiji ROI Manager ROIs and a comma separator values (csv) file with the coordinates of the center of mass of each detected cell. Moreover, the output root directory contains the summary of the counts as an csv file and the Log.txt file with the analysis steps and the chosen parameters . An additional subdirectory with all the labeled images for positive and negative cells is created in the main output path for further analysis. 3.3. Quanty-cFOS Validation for Fos Protein Cell Counting After establishing the methodology, cell counting results generated using Quanty-cFOS on cells expressing the Fos protein were compared to manual counts of Fos-expressing cells using a test data set of randomly selected images from mouse brain sections . Fos-expressing cells were manually annotated in the validation images by four different experimenters and the results compared with the Quanty-cFOS output . For the manual counting, we developed an ImageJ/Fiji tool that allows the user to select positive and negative cells by clicking the left and right mouse button. Positive cells can be counted by clicking the left mouse button, negative cells with the right mouse button accessed on 15 February 2023). By comparing the manual counts from the four experimenters, we observed consistent results between the single human counts in certain ROIs but also miscounted cells in other parts of the images . Indeed, the single counts analysis of Fos protein-expressing cells over 30 images showed a discrepancy in the absolute number of positive cells counted manually . The discrepancy in counts was also seen when the absolute single counts from manual counting were compared with the Quanty-cFOS output . To evaluate the relation between the two methods, we compared the manual counts average slope with the Quanty-cFOS slope. The slope for both, the manual average and Quanty-cFOS, showed a similar distribution in the number of positive cells counted, suggesting a consistent relation between the manual and the Quanty-cFOS counts . To further verify this observation, we computed the correlation analysis between the manual and Quanty-cFOS counts using the z-score method. The analysis showed a significant correlation in two standard deviations range (sigma) between the manual and the Quanty-cFOS counts . These results support the accuracy of the automated Quanty-cFOS method. Furthermore, the large differences in the absolute manual counts between the four experimenters further revealed the need of an unbiased algorithm for cell counting. 3.4. Quanty-cFOS Validation for c-fos mRNA Cell Counting In Quanty-cFOS, we developed a similar approach for counting cells positive for c-fos mRNA in in situ hybridization experiments, as was used for the Fos protein. First, we compared the manual counting results performed by four experimenters on 30 images from the mouse brain with the output of the automated Quanty-cFOS algorithm . The manual counts were obtained as described for the Fos protein. The automated counts were achieved by using the combination of raw and ilastik pixel classification probability map as pre-processing step. Ilastik pixel classification workflow was trained using 15 raw c-fos mRNA images and all the images were batch processed in ilastik . A larger amount of training data or different pre-processing methods can be used to gain higher accuracy in the segmentation results, e.g., ilastik Autocontex , image denoising with noise2void , image restoration with CARE and a suitable deep learning model from BioImage Model Zoo . The manual counts comparison showed consistent results between the experimenters' counts in certain ROIs but also revealed miscounted cells in other parts of the images . Similar results are observed for the automated c-fos mRNA counts . Manual cell counts showed differences in the absolute number of c-fos-positive cell counts . This was also seen when comparing the c-fos manual counts with the automated counting results . However, the discrepancy within the absolute counts, within the manual counts and in between the manual and the automated counts was smaller in comparison to what we observed for Fos protein counts . We evaluated the counts relation by comparing the manual counts average slope with the mRNA Quanty-cFOS slope. Both slopes, manual and automated, showed the same distribution with many overlapping data points . We further tested the counts for significance by computing the z-scores in two S.D. ranges. Manual and automated counts showed a strong correlation. As with the Fos protein counts, these analyses demonstrate the validity and accuracy of the Quanty-cFOS automated method for counting c-fos mRNA-positive cells in complex tissues . 3.5. Hot Plate Analysis of Fos Protein and c-fos mRNA Expression Using Quanty-cFOS Having established the Quanty-cFOS automated method, we then demonstrate its utility for studying activation in neuronal networks in the rodent brain by applying it to follow changes in both c-fos mRNA and Fos protein expression after sensory stimulation. In mice subjected to a heat stimulus of 50 degC applied to the hindpaw, c-fos mRNA levels started to increase in the prefrontal cortex within 20 min, peaked at 1 h and the mRNA was degraded by 3 h after stimulation . In contrast, Fos protein increased only after 1 h and strong expression was evident 3 h after stimulation . The automated counts were compared with manual counts performed by four experimenters, as described above. Both automated and manual counts for mRNA and protein show the expected c-fos expression. Indeed, c-fos mRNA could be seen at 20 min, reached a peak after 1 h and was degraded after 3 h, while protein expression was evident at 1 h and not seen at 20 min post-stimulation . Thus, we validated the Quanty-cFOS method, showing that it can be reliably used to automate the Fos protein and c-fos mRNA cell counts. This is an important prerequisite for using Quanty-cFOS for the automated quantification of positive cell counts in methods involving dual counting of mRNA and protein within the same specimen. While this can apply to any biological marker mRNAs or proteins, the ability to reliably count cells expressing c-fos mRNA and protein within the same specimen in the context of the different time course of their expression using Quanty-cFOS will allow for the implementation of this tool in dual-epoch labelling methods, such as TAI-FISH, that involve an analysis of cells responding in an activity-dependent manner to different stimuli (e.g., two distinct sensory stimuli, such as heat and cold) applied with a temporal gap . The variability of manual cell counts can affect the final experiment outcome depending on how an experimenter visually counts cells . Instead, the Quantity-cFOS tool can be used to obtain unbiased cell counts making analysis reproducible and objective, as shown in our results. 4. Discussion This study introduces an open-source, novel and fully validated ImageJ/Fiji tool for the unbiased counting of cells expressing Fos protein or c-fos mRNA. The main advantages of this tool are its objectivity and lack of human bias in cell counting, consistence of methodology and analyses across different experiments and its ability to set thresholds objectively in experiments with intra-experiment variability. Further, Quanty-cFOS allows for higher speed and efficiency in analyzing a large number of images and applicability to antibodies or RNA probes that yield high experimental variability as well as graded nuances in expression levels which can lead to large errors when viewed subjectively. Importantly, the study provides an easy-to-use tool, including in-depth step-by-step videos for different cell counting applications that can be quickly learned and efficiently applied by non-experts in image analysis. Analysis of the activity-induced expression of the immediate early gene c-fos has rapidly established itself into a major surrogate for addressing activity in neurons . While levels of expression of the gene can be measured quantitatively in terms of quantitative PCR analyses for the mRNA transcript or Western blot analyses for the protein product, they lack spatial and cellular resolution. Therefore, immunohistochemistry and in situ hybridization of the c-fos gene expression is critical in yielding information on activity-induced changes in distinct regions, pathways and individual cells of the brain. Although it lacks the fine temporal resolution of electrophysiology, analysis of spatial profiling of Fos expression is technically much easier, faster and can be carried out simultaneously across the whole brain, making it a broadly applicable method. Cells that induce and express Fos simultaneously following a particular external stimulus, such as painful sensory stimuli, or in association with a particular internal function, such as establishment or recall of particular memories, have been considered to be part of assemblies or ensembles that subserve particular functions. A very recent study has employed simultaneous Fos monitoring and in vivo calcium imaging of the hippocampus in mice to demonstrate that neurons with high Fos induction form cellular ensembles which show highly correlated activity and play an important functional role in spatial memory, thus leading further credence to the use of Fos mapping for identifying functionally relevant cells . Thus, spatial profiling of the Fos protein is a valuable and widely employed method in the neurosciences. Unfortunately, quantitative analysis of Fos-expressing neurons has not evolved at the same rate, and most studies have relied on manual counting, which is not only highly cumbersome and time-consuming, but also prone to subjectivity, bias and variability within and across groups and experiments. While an automated algorithm was successfully developed for counting Fos-expressing cells in light sheet microscopy on cleared whole brains , analysis of thick brain slices or sections has proven to be more complex, owing to the high background from the brain parenchyma as well as difficulties in estimating cells that are cut out of the section in the z dimension. Fewer, automated solutions for cell counting on tissue sections are available as open-source standing alone software or as ImageJ/Fiji plugins. For instance, Cellpose and CellProfiler can be used to automatically count the number of cells in microscopy sections; however, these tools lacked specific thresholding optimization methods essential for mapping immunoreactive cells . Basal expression of Fos/c-fos in neurons requires the development of ad hoc optimization algorithms necessary to count only reactive cells. Therefore, to cover this gap, we developed the Quanty-cFOS tool, optimized to count cells above an automated computed intensity or manual intensity cutoff. The option to count only cells above a specific cutoff, in a step-by-step designed workflow, is the major novelty of the Quanty-cFOS tool in comparison to the tools publicly available. To the best of our knowledge, there is no other open-source tool that is easily accessible and usable by non-experts, can run in a standard image analysis program such as ImageJ/Fiji, is accompanied by detailed video tutorials and which has been validated and optimized for both the Fos protein and c-fos mRNA. Currently, Quanty-cFOS can be used to count cells only on two-dimensional images and this could limit its application if cells need to be counted in three-dimensional stacks. Indeed, extending the Quanty-cFOS to count cells in three-dimensional stacks will be part of the future development of this open-source tool. Here, we took care to include human experimenters and manual counting in an iterative process while developing and optimizing the Quanty-cFOS tool. Moreover, emphasis was placed on collecting data sets showing a high level of inter-experimenter variability to challenge and optimize Quanty-cFOS. Furthermore, an important challenge in counting Fos-positive cells in response to a given stimulus or function is given by the fact that natural, spontaneous activity yields background Fos expression and stimulus-derived Fos expression can vary in strength across cells within the sample and across samples, rendering it difficult to set a threshold. This aspect is dealt efficiently in Quanty-cFOS using the automated and manual optimization methods. Nevertheless, the experimenter can choose to either employ the automated optimization method, which represents the most unbiased option, or to use the manual optimization method, or to count all stained cells without any intensity cutoff, as required per experimental conditions, thus providing maximum flexibility. Although in situ mRNA hybridization represents a more cumbersome method of spatially testing activity-induced expression of c-fos, requiring stringent control of RNA degradation, methods such as RNAscope have led to widespread use in recent times. Counting c-fos-positive cells harbors the same difficulties as discussed above for the Fos protein while carrying the additional hindrance that mRNA is diffusely distributed in a spotty, dotted appearance across the cytoplasm in contrast to nuclear localization of the Fos protein, rendering it harder to distinguish between neighboring cells. In Quanty-cFOS, using image preprocessing with ilastik pixel classification enabled us to circumvent this problem and facilitate the segmentation and the counting of mRNA-positive cells. This will not only foster the use of the c-fos mRNA as a spatial marker of activity-induced changes in networks, but also support methodologies in which analyses of the c-fos mRNA and Fos protein are combined with the same samples to identify differentially-activated cohorts, such as TaiFISH . This method applies sequentially given stimuli and it takes advantage of the early expression and short lifespan of the c-fos mRNA in comparison with the later induction and longer expression of the Fos protein. Methods such as these are becoming increasingly prominent in yielding insights into the differential cellular encoding of distinct functions within the same region in the nervous system, e.g., aversion vs. reward processing in the prefrontal networks. Furthermore, it deserves to be noted that emphasis was placed on making Quanty-cFOS user-friendly by developing several workflow options and leaving control in the hands of the user. Additionally, with the tool we provide in-depth video tutorials to make it easily useable by scientists without expertise in image processing and image analysis. This is of critical importance since the lack of bioimage analysis and computing skills often limits stringent standards fundamental for reproducibility in image quantification. Finally, the efficiency of using Quanty-cFOS to quantitate activity-dependent changes in cellular responses deserves to be discussed. Having conducted and published a number of in-depth studies with c-fos-based activity mapping using manual counting that required several weeks to months of work , frequently leading to experimenter fatigue, we are confident that automated counting via Quanty-cFOS can achieve the same goals in the fraction of time required for manual analyses. In conclusion, making this fully validated tool freely available to the scientific community will help overcome human bias in spatial activity mapping and foster unbiased, efficient and rapid analyses. Moreover, although the tool was designed and optimized for quantitating cells expressing the Fos protein or c-fos mRNA in the nervous system, it is in principle applicable to any antibody or mRNA being investigated and to any type of tissue, thus rendering its multiple applications. Acknowledgments The authors are grateful to members of the R.K. lab for helpful discussions, to Agnieszka Plociennikowska and Dominik Kutra for comments on the manuscript and to Christl Gartner for secretarial assistance. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Step-by step workflow description and applications of Quanty-cFOS.; Figure S2: Automated Quanty-cFOS with batch analysis.; Figure S3: Semi-automated Quanty-cFOS without batch analysis; Movie S1: Quanty-cFOS all cells counting with batch processing without intensity cutoff.; Movie S2: Quanty-cFOS automated intensity cutoff workflow using StarDist segmentation method for Fos protein cell counting.; Movie S3: Quanty-cFOS manual intensity cutoff workflow using StarDist segmentation method for Fos protein cell counting.; Movie S4: Quanty-cFOS automated intensity cutoff workflow using raw images and ilastik pixel classification probability map images for c-fos mRNA cell counting.; Movie S5: Quanty-cFOS without batch analysis with multiple brain sub-regions selection. The manuscript is accompanied by three supplementary figures describing aspects of the methodology and accessory information on the results, and five videos which demonstrate the use of the Quanty-cFOS tool in a systematic manner and which can be used by readers as a basis to run their own analyses using the tool uploaded in the public repository. Click here for additional data file. Author Contributions Conceptualization, R.K., C.A.B.; methodology, C.A.B., S.L.; experimental investigation, C.A.B., S.L., A.S., Z.G., L.W., L.L.T.; analysis, C.A.B.; writing--C.A.B., R.K., S.L., A.S.; writing--review and editing, Z.G., A.S.; visualization, C.A.B., S.L.; supervision, R.K., C.A.B.; funding acquisition, R.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The animal study protocol was approved by the Institutional Review Board of Regierungsprasidium Karlsruhe, Germany (Ref. 35-9185.81/G-184/18). Informed Consent Statement Not applicable. Data Availability Statement All raw data are included in the figures in form of individual data points in dot blots. All Matlab scripts and algorithms generated during the development of Quanty-cFOS are uploaded in a publicly accessible repository: (accessed on 15 February 2023). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Intensity variability in Fos protein immunohistochemistry and mRNA in situ hybridization. (A-D) Confocal maximum intensity projections of neurons immunostained for expression of Fos protein in mouse brain sections (prefrontal cortex shown here), which were acquired by four experimenters. The representative images show staining variability and different confocal settings for image acquisition (images were acquired at different resolutions). (A'-D') Confocal maximum intensity projections of c-fos mRNA after in situ hybridization on mouse brain sections, which were acquired by two experimenters (prefrontal cortex and S1 shown here). Representative images show differences in mRNA in situ hybridization efficiency and image acquisition settings. Scale bar was added using ImageJ/Fiji on the right bottom corner of each image. (E,E') Intensity features box plot comparisons, in which intensity features were extracted using the Extract-ImageProperties_V0.ijm ImageJ/Fiji script. The extracted intensity features are shown plotted on the x-axis. Data points outside the whiskers are marked with the plus symbol. Data are represented as mean +- standard deviation (S.D.). Figure 2 Step-by-step counting of cells expressing Fos protein and c-fos mRNA using the Quanty-cFOS ImageJ/Fiji tool. Top to bottom, Quanty-cFOS workflow steps: number of input directories containing the images to process (INPUT), detection method for image segmentation (DETECTION), positive cell counting (QUANTIFICATION, automated or manual optimization method) and output results (RESULTS). (A-C) Quanty-cFOS workflow to count Fos protein-positive neurons in confocal maximum intensity projections. (A) Representative input raw image, (B) StarDist segmented labeled image and (C) image showing output of positive and negative cells counted in Quanty-cFOS. Fos-positive cells (Fos+) are labeled in blue and Fos-negative cells (Fos-) are labeled in red. (A'-C') Quanty-cFOS workflow to count c-fos mRNA-positive neurons in confocal maximum intensity projection images. (A1') raw input image, (A2') pre-processed ilastik pixel classification probability map input image. (B') Thresholded ilastik pixel classification binary image (0, 255) generated via the Quanty-cFOS tool using the ImageJ/Fiji default threshold method. (C') c-fos mRNA-positive cells (c-fos+) are labeled in blue and c-fos negative cells (c-fos-) are labeled in red. Red squares show a region of interest magnified on the right side of each image for Fos protein and c-fos mRNA. The output results folder structure is shown at the bottom (SF1, subfolder 1). (A,A1',A2') Scale bar was added using ImageJ/Fiji on the right bottom corner of each image. Figure 3 Fos protein: analysis and comparison of cells counted manually vs. Quanty-cFOS. (A-D) Representative maximum intensity projection images for Fos-positive cells manually counted by four experimenters. (A-E) Scale bar was added using ImageJ/Fiji on the right bottom corner of each image. (E) Quanty-cFOS automated Fos-positive cell counting using the 'Automated Optimization' method. (A-E) Fos-positive cells are highlighted with a green outline. (A-E,A'-E') Green rectangular ROI shows cells counted manually by the 4 experimenters to be positive for Fos or counted as positive using the Quanty-cFOS automated method. Red rectangular ROI shows Fos-positive cells counted differentially between the four experimenters and the Quanty-cFOS tool. (A'-E') Highlighted red and green rectangular ROIs; white arrowheads point to a miscounted cell in red rectangular ROIs. (F) Comparison between automated Quanty-cFOS and human manual counts over 30 images; blue line shows the automated Fos-positive cell counts; orange, yellow, purple and green lines represent the manual counts performed by the four experimenters. (G) Automated Quanty-cFOS counts and average of manually counted Fos-positive neurons; blue circular markers show the automated counts, red circular markers the average values of manual counts. Single manual Fos-positive cell counts performed by each of the four experimenters are shown by the orange, yellow, purple and green triangular markers. The dashed lines show the counting slope for the automated Quanty-cFOS (blue) and the human manual counts (red). (H) z-score analysis with a significant counting correlation in the two standard deviations (S.D.) range between the automated and human manual counts. Blue and red circles plot the individual correlation values for the automated and the manual counts. Black dashed line shows the correlation slope. Figure 4 c-fos mRNA: analysis and comparison of cells counted manually vs. Quanty-cFOS. (A-D) Representative maximum intensity projection images for c-fos-positive cells manually counted by four experimenters. Scale bar was added using ImageJ/Fiji on the right bottom corner of each image. (E) Quanty-cFOS automated c-fos-positive cell counting using the 'Automated Optimization' method. (A-E) c-fos-positive cells are highlighted with a green outline. (A-E,A'-E') Green rectangular ROI shows cells counted manually by the four experimenters to be positive for c-fos mRNA or counted as positive using the Quanty-cFOS automated method. Red rectangular ROI shows Fos-positive cells counted differentially between the four experimenters and the Quanty-cFOS tool. (A'-E') Highlighted red and green rectangular ROIs; white arrowheads point to a miscounted cell in red rectangular ROIs. (F) Comparison between automated Quanty-cFOS and human manual counts over 30 images; blue line shows the automated c-fos-positive cell counts; orange, yellow, purple and green lines represent the manual counts performed by the four experimenters. (G) Automated Quanty-cFOS counts and average of manually counted c-fos-positive neurons; blue circular markers show the automated counts, red circular markers the average values of manual counts. Single manual c-fos-positive cell counts performed by each of the four experimenters are shown by the orange, yellow, purple and green triangular markers. The dashed lines show the counting slope for the automated Quanty-cFOS (blue) and the human manual counts (red). (H) z-score analysis with a significant counting correlation in the two standard deviations (S.D.) range between the automated and human manual counts. Blue and red circles plot the individual correlation values for the automated and the manual counts. Black dashed line shows the correlation slope. Figure 5 Using Quanty-cFOS to study Fos protein and c-fos mRNA expression in the brain over time following sensory stimulation of the hindpaw. Analysis of cells expressing Fos protein (A-C) and mRNA (D-F) at three different time points after hindpaw exposure to a 50 degC heat stimulus is shown. Representative images at 20 min (A,D), 1 h (B,E) and 3 h (C,F) after heat stimulation of the paw are shown. The gamma was adjusted to 0.6 in ImageJ/Fiji for the purpose of representation. (G) Statistical analysis of mean Fos protein and c-fos mRNA expression. Red circles show the Quanty-cFOS protein automated counts on 16 images for each time point; the red rectangular boxes highlight the mean Fos-positive automated counts. The green left arrowheads indicate the protein manual counts performed at the 3 time points. Blue circles show the c-fos-positive counts using Quanty-cFOS automated counting on 16 images for each time point; the blue diamond boxes highlight the mean c-fos-positive automated counts 20 min, 1 h and 3 h after heat plate stimulation and the orange right arrowheads show the mRNA manual counts. Dash lines highlight the changes in positive cells counts over time. Data are represented as mean +- S.D. 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PMC10000432 | Colorectal cancer (CRC) is associated with mutations in APC/Wnt leading to c-myc activation and the overexpression of ODC1, the limiting step in polyamine synthesis. CRC cells also display a remodeling of intracellular Ca2+ homeostasis that contributes to cancer hallmarks. As polyamines may modulate Ca2+ homeostasis during epithelial tissue repair, we investigated whether polyamine synthesis inhibition may reverse Ca2+ remodeling in CRC cells and, if so, the molecular basis for this reversal. To this end, we used calcium imaging and transcriptomic analysis in normal and CRC cells treated with DFMO, an ODC1 suicide inhibitor. We found that polyamine synthesis inhibition partially reversed changes in Ca2+ homeostasis associated with CRC, including a decrease in resting Ca2+ and SOCE along with an increased Ca2+ store content. We also found that polyamine synthesis inhibition reversed transcriptomic changes in CRC cells without affecting normal cells. Specifically, DFMO treatment enhanced the transcription of SOCE modulators CRACR2A; ORMDL3; and SEPTINS 6, 7, 8, 9, and 11, whereas it decreased SPCA2, involved in store-independent Orai1 activation. Therefore, DFMO treatment probably decreased store-independent Ca2+ entry and enhanced SOCE control. Conversely, DFMO treatment decreased the transcription of the TRP channels TRPC1 and 5, TRPV6, and TRPP1 while increasing TRPP2, thus probably decreasing Ca2+ entry through TRP channels. Finally, DFMO treatment enhanced the transcription of the PMCA4 Ca2+ pump and mitochondrial channels MCU and VDAC3 for enhanced Ca2+ extrusion through the plasma membrane and mitochondria. Collectively, these findings suggested the critical role of polyamines in Ca2+ remodeling in colorectal cancer. colorectal cancer polyamines intracellular calcium transcriptomic analysis DFMO store-operated calcium entry mitochondria TRP channels Ministry of Science and Innovation, SpainRTI2018-099298-B-100 PID2021-125909OB-100 Excellence Program Instituto de Biologia y Genetica Molecular from the Junta de Castilla y LeonCCVC8485 Asociacion Espanola contra el Cancer (AECC)This work was supported by grants RTI2018-099298-B-100 and PID2021-125909OB-100 from the Ministry of Science and Innovation, Spain; the Excellence Program Instituto de Biologia y Genetica Molecular from the Junta de Castilla y Leon, grant CCVC8485; and Asociacion Espanola contra el Cancer (AECC), Spain. E.P.-R. was supported by Asociacion Espanola Contra el Cancer (AECC). E.H.-P. and V.F. were supported by predoctoral fellowships from Junta de Castilla y Leon, Spain. pmc1. Introduction Colorectal cancer (CRC) is one of the most common types of cancer and causes of cancer deaths worldwide, with nearly 1,250,000 new CRC cases every year and a mortality rate as high as 50% of all cases . The molecular basis of CRC involves in most cases the activation of the Wnt-b-catenin signaling pathway by the mutation of intracellular components such as APC, AXIN, and CTNNB1/b-catenin genes or the epigenetic alteration of Wnt inhibitors such as DKK-1, SFRPs, and WIF, considered the initial steps in colorectal tumorigenesis . These changes result in the activation of c-myc and K-ras, which lead to adenoma, adenocarcinoma, and colon carcinoma . Myc activation induces the overexpression of multiple genes, including ornithine decarboyxlase (ODC), the limiting step in the synthesis of the polyamines putrescine, spermine, and spermidine. ODC activation can be efficiently prevented by the suicide inhibitor Difluoromethylornithine (DFMO, also named eflornithine) . Substantial evidence links ODC overexpression, excess polyamines synthesis, and CRC. For instance, ODC is overexpressed in most CRCs, and different tumor promoters induce ODC1 and tumor formation . ODC polymorphisms have also been reported in CRC. In addition, targeting ODC and polyamines using cell lines, animal models, and even clinical trials may efficiently prevent CRC . For instance, DFMO inhibits colon carcinogenesis in ApcMin/+ mice with increased levels of ODC and polyamines in intestinal tissues and suppresses carcinogenesis in the small intestines of these mice . Interestingly, the grade of intestinal polyps is polyamine-dependent, and the anti-carcinogenic effects can be rescued by putrescine. DFMO may work in humans as well. An ongoing trial is presently evaluating the effectiveness of the combination of DFMO and sulindac in preventing colon adenomas . However, the mechanisms by which polyamines promote carcinogenesis remain to be fully established. Polyamines are physiological molecules that are produced transiently during epithelial restitution for epithelial tissue repair. This process involves the transient activation of cell migration and/or proliferation after wounding. Evidence suggests that this process could be mediated by Ca2+ signaling induced by changes in the expression of TRPC1 channels as well as an increased ratio of STIM1 to STIM2 ; molecular players involved in SOCE in epithelial cells, mediated by caveolin ; and the small guanosine-5'-triphosphate-binding protein RhoA . Interestingly, SOCE and its molecular players have recently been found to be involved in carcinogenesis in CRC and other forms of cancer . For instance, we recently reported that intracellular Ca2+ homeostasis is remodeled in CRC cells . Specifically, CRC cells display enhanced SOCE and decreased Ca2+ store content relative to normal colonic cells, and these changes contribute to cancer hallmarks, such as increased cell proliferation, cell invasion, and resistance to apoptosis . At the molecular level, enhanced SOCE was linked to the increased expression of TRPC1 and an increased ratio of STIM1 to STIM2 in CRC cells , thus mimicking changes previously reported to be induced by transient polyamine exposure during epithelial restitution . In addition, we also reported that store-operated currents (SOCs) are quite different in normal and colon cancer cells. Specifically, normal colonic cells display typical CRAC-like currents driven by Orai1 channels, which are very small, Ca2+-selective, inward-rectifying currents. In contrast, CRC cells display larger, non-selective currents with both inward and outward components that are mediated by both Orai1 and TRPC1 channels . We recently conducted a transcriptomic analysis of 77 selected gene transcripts involved in intracellular Ca2+ transport that provided the first insights into the transcriptional basis of this remodeling . In short, we found the differential expression of selected voltage-operated Ca2+ channels and SOCE players, transient receptor potential (TRP) channels, Ca2+ release channels, Ca2+ pumps, Na+/Ca2+ exchanger isoforms, and genes involved in mitochondrial Ca2+ transport . Therefore, the evidence suggests that intracellular Ca2+ homeostasis is largely remodeled in CRC, and these changes could be mediated by excess polyamine synthesis linked to CRC. To address this issue, we recently tested the effects of polyamine synthesis inhibition on Ca2+ remodeling in CRC cells . In accordance with this hypothesis, we reported that CRC cells overexpressed ODC1 relative to normal cells. In addition, polyamine synthesis inhibition in CRC cells that were resistant to cell death reversed this phenotype and sensitized CRC cells to apoptosis. Importantly, polyamine synthesis inhibition promoted changes in intracellular Ca2+ homeostasis consistent with phenotype reversal, including changes in store-operated currents and SOCE, Ca2+ store content, and the expression of a few proteins involved in SOCE . However, whether polyamine synthesis inhibition reverses the whole calcium signature linked to carcinogenesis remains to be addressed. Here, we combined calcium imaging and transcriptomic analysis using next-generation sequencing and microarray technology to determine the molecular basis of Ca2+ remodeling in CRC and the effects of polyamine synthesis inhibition on transcriptomic remodeling and changes in intracellular Ca2+ homeostasis. Our results indicated that polyamine synthesis inhibition partially reversed the remodeling of intracellular Ca2+ in CRC cells. In addition, polyamine synthesis inhibition induced expression changes in 25% of the whole transcriptome of CRC cells but had nearly negligible effects on normal cells. Finally, we found that the reversal of Ca2+ remodeling depended on the changes in a dozen genes, including SOCE modulators, several TRP channels, two Ca2+ pumps, and two channels involved in mitochondrial Ca2+ transport. 2. Materials and Methods 2.1. Materials The HT29 cell line was obtained from LONZA (Basel, Switzerland). NCM460 cells were from INCELL Corporation (San Antonio, TX, USA). SW480 cells were a kind gift from Prof. Alberto Munoz (CSIC, Madrid, Spain). Dulbecco's modified Eagle's medium (DMEM), penicillin, streptomycin, and fetal bovine serum (FBS) were sourced from Lonza (Basel, Switzerland). L-glutamine was from Gibco (Barcelona, Spain). Trypsin-EDTA was from LONZA (Verbiers, Belgium). Poly-L-Lysin was from Marlenfeld GmbH (Lauda-Konlgshofen, Germany). Six-well plates were from NUNC (Thermo Scientific, Waltham, MA, USA). Dishes 10 cm2 in diameter were from Corning (NY, USA). DFMO was from TOCRIS (Bristol, UK). Fura2/AM and qPCR primers are from Invitrogen (Eugene, OR, USA). Cyclopiazonic acid (CPA) was from Sigma-Aldrich (Steinheim, Alemania). Antibodies against MCU and b actin were from Sigma (Madrid, Spain). The RNA extraction kit was a GeneMATRIX Universal RNA Purification Kit from EURx (Gdansk, Poland). Clariom D human microarrays (Affymetrix) were supplied by CABIMER (Andalucia, Spain). RNA-seq (Illumina) was provided by Sistemas Genomicos S.L (Valencia, Spain). PolyamineRED was from Funakoshi Co., Ltd., Tokyo, Japan). All other reagents were obtained from Sigma and Merck. 2.2. Cell Models and Sample Preparation As human colon cancer models, we used the HT29 and SW480 colon cancer cell lines, and the NCM460 cell line was employed as the normal control; all of these have been widely used and validated in the colon cancer research field. Cells were cultured in a 25 cm2 flask with DMEM plus 1 g/L of glucose, 10% FBS, 1% penicillin/streptomycin, and 1% L-glutamine, which were placed into an incubator at 37 degC under a 10% CO2 atmosphere. All cells were used in passage 2. From each cell culture seeded in one flask, cells were detached with trypsin-EDTA and broken into two parts. One of these parts, which was used for the calcium imaging experiment, was seeded on four glass coverslips pretreated with poly-L-Lysin; each of them was then placed into a well in a 6-well plate with a cell density of 3000 cells per coverslip. The other part, which was used for the transcriptomic experiment (microarrays), was seeded on two dishes 10 cm2 in diameter with a cell density of 10.5 x 105 cells per dish. Notably, two flasks, one flask of HT29 and the other of NCM460 cells, were processed on the same day. Then, two flasks (one from HT29 cell cultures and the other from NCM460) were processed every day on four different days. After an entire day at 37 degC under a 10% CO2 atmosphere, of the eight coverslips and four dishes obtained from the two flasks (with one flask per cell line), two coverslips and one dish from each flask were treated with DFMO (DFMO 5 mM in DMEM 1 g/L glucose plus 10% dialyzed FBS), whereas the other two coverslips and dish from each flask were used to represent the non-treated conditions, i.e., treated without DFMO (DMEM 1 g/L glucose plus 10% dialyzed FBS). Then, the eight coverslips and four dishes were kept in an incubator at 37 degC under a 10% CO2 atmosphere for 96 h. Next, the coverslips were used for calcium imaging experiments, and the dishes were used to extract and isolate their mRNA for transcriptomic analysis . Notice that a transcriptome analysis was previously carried out for both the NCM460 and HT29 cell lines without DFMO treatment using Illumina RNA-seq for comparison. 2.3. Intracellular Polyamine Levels Intracellular polyamines were estimated using fluorescence imaging and PolyamineRED (Funakoshi Co., Ltd., Japan), an intracellular polyamine detection reagent. Treated and control cells were cultured with 30 mM of the reagent in free-serum media for 30 min according to manufacturer's procedure. Then, cells were fixed, and nuclei were stained with DAPI. Fluorescence images were obtained using a Nikon Eclipse 90i fluorescence microscope and analyzed with ImageJ software. Figure 2 shows that PolyamineRED fluorescence in cells treated with DFMO was largely reduced relative to untreated cells, in accordance with polyamine depletion. Similar results were obtained in SW480 and NCM460 cells. 2.4. Experimental Design The effect of the inhibition of the polyamine synthesis pathway through DFMO on both HT29 and NCM460 cells was assessed at both the transcriptomic and functional levels . On the one hand, the transcriptomic experiment was conducted using Clarion D human microarrays from Affymetrix and, on the other hand, the functional test was carried out using calcium imaging. Then, four experimental conditions were evaluated: NCM460 cells, both treated and non-treated with DFMO, and HT29 cells, again both treated and non-treated with DFMO. Furthermore, since we were interested in obtaining the transcriptomic expression profile through calcium imaging assays, we acquired from the same flask, at the same time, a replicate for every experimental condition (for the same cell line) and for both transcriptomic and calcium imaging assays, as shown in Figure 1c. Specifically, on the same day, a replicate for both treated and non-treated experimental conditions was extracted from the same flask, and two replicates for calcium imaging for the experimental condition "g" were obtained and processed from one replicate for the same experimental conditions in the transcriptomic experiment. Furthermore, prior to the experiments described above, both non-treated HT29 and NCM460 cells were assessed at the transcriptomic level through Illumina RNA-seq technology. Regarding the factors that needed to be considered for later data analysis, on the one hand, in the calcium imaging experiment, there were two random factors (day and coverslip) and another two fixed factors (cell line and treatment). Then, we had to use linear mixed models to control the effects of random factors. On the other hand, concerning the transcriptomic experiment, there were two fixed factors (cell line and treatment) and just one random factor. We took into account this random factor, since it was necessary to control it. The data analysis for each type of experiment is explained more in detail in the corresponding paragraph. 2.5. Single-Cell Calcium Measurements Fluorescence calcium measurements were conducted in colon cancer HT29 and SW480 cells as well as normal NCM460 cells, all treated and non-treated with DFMO. First of all, cells were washed with a standard external medium (SEM) containing (in mM) NaCl 145, KCl 5, CaCl2 1, MgCl2 1, glucose 10, and Hepes/NaOH 10 (pH 7.4). Then, cells were loaded with 4 mM of Fura2/AM, the acetoxymethyl ester form of the calcium-sensitive dye fura2, in SEM for 45 min at room temperature and in the dark. After loading, coverslips with attached cells were mounted in the perfusion chamber of a Zeiss Axiovert 100 TV inverted microscope and perfused with prewarmed (37 degC) SEM. Then, the cells in the chamber were excited alternately by light at 340 and 380 nm using a xenon lamp and a filter wheel, and the light emitted by the cells at 520 nm was filtered through a dichroic mirror and recorded every 5 s by a Hamamatsu ER camera (Hamamatsu Photonics France). Finally, the 340 nm/380 nm ratios between each pair of pixels were calculated, and all those belonging to the same region of interest (ROI), corresponding to a single cell, were averaged and interpreted as an intracellular [Ca2+] measurement from that ROI, as detailed before . For resting [Ca2+] measurements, we used the median 340 nm/380 nm ratio of the first 30 s from each cell. After that, to obtain a measure of the Ca2+ store content from each cell, cells were treated with the reversible sarcoplasmic and endoplasmic reticulum Ca2+ ATPase (SERCA) inhibitor cyclopiazonic acid (CPA) at 10 mM in a calcium-free SEM. Accordingly, the Ca2+ store content from each cell was measured as both the increment in and area under the curve (AUC) of the 340 nm/380 nm ratio for the signal corresponding to the rise in intracellular [Ca2+] induced by CPA in Ca2+-free medium. Finally, after store depletion, cells were perfused with SEM containing CPA and 1 mM Ca2+ to induce SOCE. Then, the SOCE corresponding to every single cell was measured as both the rise in and the area under the curve (AUC) of the F340 nm/F380 nm ratio for the signal corresponding to the rise in intracellular [Ca2+]. 2.6. Transcriptomic Experiments After RNA isolation (using a GeneMATRIX Universal RNA Purification Kit from EURx), microarrays were carried out in Centro Andaluz de Medicina Regenerativa (CABIMER, Seville, Spain), and RNA-seq assays were conducted by Sistemas Genomicos S.L (Valencia, Spain). Then, data analysis based on the microarrays was performed by our group using .CEL files, whereas data analysis for RNA-seq was performed using count-matrix, provided by Sistemas Genomicos S.L. (Valencia, Spain). 2.7. Western Blotting HT29 cells were treated with vehicle or DFMO (5 mM, 96 h) and used for western blotting. Total protein was extracted from cells and used to quantify the expression of MCU. Whole-cell lysate was obtained using RIPA buffer (20 mM Tris-HCl, pH 7.8, 150 mM NaCl, 1% Triton X-100, 1% deoxycholic acid, 1 mM EDTA, 0.05% SDS) supplemented with the HaltTM Protease and Phosphatase Inhibitor Cocktail (100x) from ThermoFisher Scientific (ref #1861281) (Waltham, MC, USA). Protein concentrations were determined by a Bradford protein assay. Proteins were fractionated by SDS-PAGE; electroblotted onto PVDF membranes; and probed with the antibodies at a dilution of 1/200, except for the anti-b-actin, which was used at a dilution of 1/5000. The antibody against MCU (SC-246071) had been previously characterized and was visualized by the addition of goat anti-rabbit IgG or rabbit anti-mouse IgG. Detection was performed using Pierce ECL Western Blotting substrate (Thermo Scientific) and a VersaDoc Imaging System (BioRad, Munich, Germany). The quantification of protein expression was carried out using Quantity One software (BioRad, Munich, Germany). The datasets were analyzed by adjusting a linear model to fit the data, the model assumptions were evaluated, the response variables were transformed with Box-Cox family transformations because the normality assumption was violated, and outlier detection was carried out by an analysis of the Cook's distance and the studentized residual. After transformation, the model assumptions were fulfilled as follows: residual normality with the Shapiro-Wilks test (p value = 0.1961) and homoscedasticity with the Bartlett test (p value = 0.8771). The sample size was equal to 6:3, corresponding to HT29 cells without treatment and HT29 cells treated with DFMO, respectively; p < 0.01. 2.8. RNA Isolation, RT, and Real-Time PCR Total RNA from HT29 and NCM460 cells was isolated with a GeneMatrix Universal RNA purification kit (Eurx(r), Molecular biology products) following the manufacturer's instructions. A confluent 60 mm Petri dish per condition was employed for each assay. The quality of the RNA was determined by optical density measurements at 260 and 280 nm and by electrophoresis on agarose gels. After DNAse I treatment with a RapidOut DNA removal kit (Thermo Scientific), 1000 ng of RNA was reverse-transcribed using a High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific) at 37 degC for 120 min to obtain cDNA. Quantitative PCR was carried out on equal amounts of cDNA in triplicate for each sample using a Kapa Sybr(r) Fast qPCR kit (Kapa Biosystems, Wilmington, MA, USA) in a LightCyler(r) 480 (Roche, Basel, Switzerland) thermocycler. The primers used are shown in Table 1 and were designed using OligoPerfect Primer Designer (ThermoFisher Scientific). The cycling conditions were 5 min at 95 degC, 40 cycles of 95 degC for 15 s, and 60 degC for 20 s. These amplifications were used to compare the different samples and melting curves to determine the specificity of the PCR products. The qPCR data were analyzed using the threshold cycle (Ct) relative quantification method (DDCt). The gene expression levels were normalized by the housekeeping gene RP18S. The relative abundance of the genes was calculated as 2DCt, where DCt = Ctgene-Ct18S. Differences between cancer (HT29) and control (NCM460) cells were calculated from 2DDCt, where DDCt = DCt(HT29)-DCt(NCM460), using DCt(NCM460) as the calibrator. In this analysis, a value of 0 indicated no change, negative values indicated decreased expression, and positive values indicated increased expression relative to the calibrator. The statistical analysis method used was a Student's t test with Bonferroni's correction for two independent samples (DCt(HT29) and DCt(NCM460)) obtained with RP18S as endogenous control. * p < 0.05, ** p < 0.01, *** p < 0.001 2.9. Data Analysis: Calcium Imaging For the calcium imaging experiments, we were interested in testing which experimental conditions were different from each other in terms of resting intracellular [Ca2+], Ca2+ store content, and SOCE. Thus, as response variables, at the single-cell level, we considered the median from the absolute value of the signal across the first 30 s for resting intracellular [Ca2+], and the corresponding increase in [Ca2+] levels and the area under the curve (AUC) for both Ca2+ store content and SOCE. We evaluated the effect of two factors, treatment and cellular line, on the response variable, each of them with just two levels (control and DFMO for the treatment factor, and NCM460 and HT29 for the cellular line factor), so there was a total of 4 experimental conditions: control-NCM460, DFMO-NCM460, control-HT29, and DFMO-HT29. Due to the experimental design, the dataset showed a hierarchical structure, since observations were clustered into, or organized at, different levels: the experiment was carried out on 4 different days; each day we performed 2 replicates corresponding to each of the 4 experimental conditions; and within each replicate, we measured several cells from the same experimental conditions. Furthermore, both replicates and day were random factors. Since there were random factors and there could be a correlation between observations belonging to the same cluster (i.e., they were non-independent), it became necessary to use linear mixed models, also known as multilevel models. Regarding the most adequate random structure, we followed the top-down strategy suggested by Brady and West : several models with the same full structure (i.e., with all possible variables and interactions) but with a different random structure were estimated using restricted maximum likelihood estimation (REML) and compared using the conditional Akaike criterion information (cAIC), such that the model whose cAIC was lower was selected. We fitted the linear mixed models for each variable response: both Ca2+ rise and the AUC of the calcium signal for SOCE and Ca2+ store content or the median of the first 30 s of the recording. Specifically, we evaluated the assumptions of the models, such as the normality and homoscedasticity, through both graphical and test methods, since the non-independence of the observations from the same cluster was controlled, precisely, by the linear mixed models. On the one hand, for the normality assumption of both the Pearson residuals and random effects, we used QQ plots, histograms, Pearson residuals against fitted values plots, Shapiro-Wilks tests, and Jarke Bera tests. On the other hand, we employed Pearson residuals versus fitted values plots and Breush-Pagan and Barlett tests for the homoscedasticity assumption. If any model assumption was violated, different approaches were followed depending on the assumption violated: normality violations were addressed by removing outliers and transforming the response with Box-Cox transformation; heteroscedasticity violations were solved using generalized linear mixed models and different variance-covariance matrix structures and weighting observations. Furthermore, re-sampling methods, such as parametric bootstrapping for mixed models, were performed to evaluate the models and to estimate both the coefficients and their confidence intervals. Notably, the results from the bootstrapping procedures agreed with those from the classic linear mixed models that slightly violated the assumptions. That is why, in the real world, some deviations from assumptions are expected, since, if these deviations are not too large, the inferences extracted from the analysis will be acceptable, which is known as the robustness of validity . For example, the non-normality of the residual distribution results in neither bias nor inefficiency from models; indeed, several authors claim that the violation of normality is not a serious problem as a consequence of the central limit theorem and can even be disregarded when the sample size is large (our experiment consisted of nearly 1000 observations), since the residual distribution will approximate to normality . Regarding which experimental conditions were different from each other, all possible pairwise comparisons were made based on combinations between levels for the two explanatory variables considered: treatment and cellular line. At first, the expected value for each experimental condition was estimated from a linear mixed model. Secondly, the differences between each pair of expected values for each experimental condition were estimated; p-values were corrected using the Tukey method with a significance level of 0.05; and experimental conditions were grouped according to a pairwise comparison, i.e., if there were no differences between two experimental conditions, they belonged to the same group. In the graphs, this is shown by letters, which indicate the group to which each experimental condition belonged. The last step was based on graph theory and was carried out using the Bron-Kerbosch algorithm to find all maximal cliques. All data analyses and data collection processes were performed in the R environment ; the lmer and nlme packages were used for creating linear mixed models, lmer and boot packages for performing bootstrap methods, and multcomp and igraph for pairwise comparison and experimental condition grouping. 2.10. Data Analysis: Transcriptomic Experiment Based on Microarrays First at all, the .CEL files, one per sample, were read with R software (oligo and affy packages). Then, samples were subjected to quality control through different methods, such that those samples which did not pass the quality control were removed from the posterior analysis. At first, the distribution of each sample and the possible presence of any batch effect or the need to normalize was tested through box plots and kernel estimators from non-normalized data. Then, pattern matching was conducted. To achieve this, it was necessary to normalize (quantile) and transform (log2) the datasets to make the samples comparable between them. Next, a principal component analysis (PCA) across all samples was conducted, and outlier detection was carried out by determining the robust Mahalanobis distance within each class (group of interest, e.g., observations from NCM460 cells treated with DFMO), where the input variables were the first principal components such that they explained at least 70% (PC70%) of the variability . Another pattern-matching method employed was hierarchical cluster analysis with the Ward method, PC70%, and the Euclidean distance. Finally, probe-level models were employed from which both the normalized unscaled standard error (NUSE) and the relative log expression (RLE) were extracted and evaluated . After quality control, the dataset was preprocessed, i.e., the dataset background was corrected, normalized, and finally summarized, all through the RMA method . Subsequently, data were filtered by employing a non-specific filter implemented by the gene filter R function, and we kept those genes (probes) whose interquartile ranges (across all samples) were larger than the median of all interquartile ranges. Furthermore, we removed all those genes whose ALIAS annotation was unknown. Nevertheless, since we were concerned about a near 80 calcium gene set, all of them were retained in the dataset after the filtering process. In this way, the dataset passed from 138,745 to 12,933 probes. Afterward, differential expression analysis was carried out through linear models, specifically, through linear models for the microarray data (limma) method . Regarding the variables in the model, the fixed factors were cellular line (levels: NCM460 and HT29) and treatment (levels: control and DFMO), whereas the random factor was day, i.e., the day on which the experimental units were processed, taking into account that each day a replicate corresponding to each experimental condition was processed. Then, the linear model selected was:log2Expression=Cellular Line + Treatment + Cellular line x Treatment +Day where Day is a random factor. Finally, to control I-type error rates, we had to employ the false discovery rate (FDR) . Differences were considered significant at FDR < 0.05. 3. Results 3.1. Functional Analysis Results To assess changes in intracellular Ca2+ homeostasis during tumoral transformation (i.e., HT29 vs. NCM460) and the effect of DFMO treatment on each cell line, we employed the calcium imaging technique and Fura2/AM as a fluorescence ratiometric probe. Specifically, we assessed the free resting Ca2+cyt, the Ca2+ store content, and the SOCE in vehicle and DFMO-treated NCM460 and HT29 cells. Firstly, the free basal Ca2+cyt was measured as the median of the absolute F340/F380 signal during the first 30 s of the recordings, and the perfusion medium contained 1 mM Ca2+. Secondly, the Ca2+ store content was measured as the AUC and Dmax of the signal due to calcium release induced by CPA. Finally, SOCE was assessed as the increase in the AUC and Dmax of the signal due to perfusion with medium containing 1 mM Ca2+ after calcium store depletion. In accordance with our previous results , resting Ca2+ and SOCE levels appeared higher in colon cancer HT29 cells than in normal NCM460 cells, whereas the Ca2+ store content was larger in the normal NCM460 cells than in the colon cancer HT29 cells. Furthermore, DFMO treatment decreased resting [Ca2+] and SOCE in colon cancer HT29 cells and increased the Ca2+ store content in the same cells. In contrast, DFMO treatment had little or no effect on normal NCM460 cells. These results were similar to our previous results . Figure 4 shows the statistical analysis of these data. Notably, due to the hierarchic structure of the data generated by this kind of experiment, we employed linear mixed models and Box-Cox transformation when needed. Furthermore, through pairwise comparison, the four experimental conditions (i.e., NCM460 control, NCM460 + DFMO, HT29 control, and HT29 + DFMO) were grouped into several clusters, such that the number of conditions in the each group was equal . As result, we found that basal Ca2+cyt was significantly higher in non-treated HT29 than in non-treated NCM460 cells, and DFMO treatment decreased it in both cell lines . Ca2+ store content was significantly lower in HT29 control cells than in NCM460 control cells . Furthermore, DFMO treatment affected each cell line differently, since this treatment slightly reduced the calcium store content in NCM460 cells (just in terms of Dmax) but increased it in HT29 cells (in terms of both the AUC and Dmax). Notably, HT29 cells treated with DFMO showed a Ca2+ store content equal to that of the NCM460 control in terms of the AUC . Finally, the data indicated that the SOCE was higher in HT29 cells than in NCM460 cells, and DFMO treatment reduced the SOCE in HT29 cells but not in NCM460 cells. Collectively, these data indicated that DFMO treatment was able to reverse, at least partially, the Ca2+ remodeling observed in HT29 cells relative to normal NCM460 cells. Furthermore, our previous results showed that DFMO treatment also reduced proliferation and death resistance in HT29 cells in accordance with the reversal of Ca2+ remodeling . We also investigated the effects of DFMO treatment on another colon cancer cell line, SW480. Experiments were carried out again in parallel to the Ca2+ imaging experiments in normal NCM460 cells. As expected, the Ca2+ store content in colon cancer SW480 cells was much lower than in normal NCM460 cells, whereas the SOCE was higher in SW480 cancer cells than in normal cells. Treatment with DFMO significantly increased the Ca2+ stores in SW480 cancer cells but had no effect on normal NCM460 cells. In contrast to HT29 cells, DFMO treatment had no significant effect on the SOCE in SW480 cells . 3.2. Transcriptomic Analysis The transcriptomic differential expression assays that we carried out could be separated into two parts. The first was conducted through two different technologies (RNA-seq and microarrays) to ascertain the differential expression between the HT29 and NCM460 cell lines. Thus, we established the following criteria to consider the information obtained by the two technologies and infer if a gene was differentially expressed or not: a gene was differentially expressed if it was indicated as such by at least one of the two technologies at a 0.05 significance level or by both technologies at a 0.1 significance level, as long as the logFC provided by both technologies fell in the same direction. The second part, i.e., the differential expression analysis between DFMO-treated and non-treated cells, both for HT29 and NCM460 cells, was conducted only by microarrays. Furthermore, the transcriptomic microarray-based experiments were conducted in parallel to the calcium imaging experiment, i.e., each sample assessed through microarrays was extracted from the same culture as a sample assessed by calcium imaging. In addition, both treated and non-treated samples processed on the same day were also extracted from the same culture. Finally, differential expression analyses were carried out for all genes (65,219 genes with ENSEMBL annotation for RNA-seq and more than 57,500 for Clariom D Human microarray). On the one hand, we identified 16,375 differentially expressed genes (DEGs) between HT29 and NCM460 through Illumina and 12,973 through microarrays. On the other hand, we found out that DFMO treatment was very much selective for HT29 cells, since treatment affected the expression of 3385 genes in HT29 cells against only 61 genes in NCM460 cells. Among all these genes, we focused only on 89 genes related to intracellular Ca2+ homeostasis, which we split into six clusters: voltage-operated calcium channels (VOCCs), SOCE modulators, TRP channels, Ca2+ release channels, Ca2+ pumps and exchangers, and mitochondrial Ca2+ transporters. Interestingly, none of these genes were affected in NCM460 cells, as opposed to 17 in HT29 cells. Furthermore, among these 17 genes, the change in the expression of 11 reversed the changes associated with cancer, i.e., the expression of these 11 genes was partially reverted by DFMO treatment. Regarding the effect at the transcriptomic level, DFMO treatment in NCM460 cells affected the expression of only 61 genes, whereas up to 3385 genes were differentially expressed in HT29 cells after treatment, indicating that DFMO is a treatment highly selective for colon cancer cells that is able to reverse, at least partially, the colon cancer phenotype. Regarding VOCCs, our results showed that CAV1.2 was downregulated in colon cancer HT29 cells, whereas CAV1.3 was overexpressed in colon cancer HT29 cells . Furthermore, CAV2.3 and CAV3.2 were downregulated, and CAV3.1 and CAV3.3 were overexpressed according to RNA-seq technology. Regarding the effect of DFMO, no gene belonging to the VOCCs was affected by this treatment . Regarding the 23 genes involved in SOCE, as many as 18 of them were identified as differentially expressed in cancer cells relative to normal cells by RNA-seq technology, whereas only 13 of them were differentially expressed according to microarrays . Specifically, RNA-seq showed the overexpression of ORAI1, STIM1, STIM2, MBP, and SEPTIN2,4,7-11 and the downregulation of CRACR2A, STIMATE, ORMDL3, SARAF, SEPTIN1,3, and SEPTIN6 in HT29 cells relative to NCM460 cells . Microarrays showed the overexpression of STIM1, MBP, SEPTIN9, and SEPTIN10 and the downregulation of ORAI1, CRACR2A, ORMDL3, SARAF, SEPTIN3,6-8, and SEPTIN11 . Accordingly, both technologies reported the overexpression of STIM1, MBP, SEPTIN9, and SEPTIN10 and the downregulation of CRACR2A, ORMDL3, SARAF, SEPTIN3, and SEPTIN6 in colon cancer cells. Thus, some discrepancies occurred for SEPTIN7,8 and SEPTIN11, so these genes were not considered as differentially expressed. Consequently, the data suggested that HT29 cells overexpressed ORAI2, STIM1, STIM2, MBP, SEPTIN2, SEPTIN4, SEPTIN9, and SEPTIN10 relative to NCM460 cells, and showed a lower expression of ORAI1, CRACR2A, STIMATE, ORMD3, SARAF, SEPTIN1, SEPTIN3, and SEPTIN6 relative to the normal cells. Notably, treatment with DFMO did not affect NCM460 but did affect HT29 cells . Specifically, DFMO treatment induced the overexpression of STIM1, STIM2, CRACR2A, ORMDL3, SEPTIN6-9, and SEPTIN11 in HT29 cells only . Thus, it was clear that DFMO treatment was able to partially reverse the differential expression found for CRACR2A, ORMDL3, and SEPTIN6. Furthermore, if we consider the differential expression between HT29 and NCM460 cells identified by microarrays, DFMO treatment was also able to partially reverse the differential expression of SETPIN7, SEPTIN8, and SEPTIN11. Regarding the 27 genes that coded for TRPs, the most remarkable result was that over half of them were downregulated in HT29 cells relative to NCM460 cells . Specifically, by combining the outcomes from both transcriptomic technologies, we could infer, on the one hand, that the following 13 genes were less expressed in HT29 cells: TRPC7, TRPM2, TRPM3, TRPM5, TRPM6, TRPM8, TRPML1-3, TRPV1, TRPA1, TRPP3, and TRPP5 . On the other hand, it was clear that TRPC4, TRPC5, and TRPV6 were upregulated in HT29 cells. It is important to note that three genes showed an opposite differential expression pattern according to both technologies: TRPV5, TRPP1, and TRPP2. Regarding the effects of DFMO treatment, again, the treatment affected HT29 but not NCM460 cells . Specifically, DFMO treatment decreased the expression of TRPC1, TRPC5, TRPV6, and TRPP1, whereas it increased the expression of TRPP2 . Thus, DFMO treatment was able to partially reverse the tumoral phenotype in terms of the expression of TRPC5 and TRPV6, and, by taking into account just the results from the microarrays, DFMO treatment also partially reversed the differential expression of both TRPP1 and TRPP2. Regarding the expression of genes coding for Ca2+ release channels, our results indicated that Illumina identified five out of six genes belonging to the CRC set as differentially expressed between HT29 and NCM460 cells, against only three identified by microarrays . Combining the results from both technologies, our findings suggested that IP3R1 and IP3R3 were upregulated in HT29 cells, whereas IP3R2 and RYR2 were downregulated. Nevertheless, RYR3 may also be overexpressed in HT29 cells. However, DFMO treatment had no effect on gene expression either in NCM460 or HT29 cells, suggesting that the possible differences could be mediated by excess polyamines. The calcium extrusion systems were also differentially expressed between HT29 and NCM460 cells . Indeed, among the 12 genes considered, seven were identified as DEGs by Illumina (PMCA1, SERCA2,3, and NCX2 overexpressed, and PMCA3,4 and SPCA1 less expressed in HT29) and six by microarrays (PMCA1, NCX2,3, and SPCA2 overexpressed, and PMCA4 and SPCA1 less expressed in HT29). Again, DFMO treatment only affected HT29 cells and not NCM460 cells. Interestingly, tumor cells showed an increased expression of PMCA4 and decreased expression of SPCA2, and DFMO treatment reversed both changes in HT29 cells . We also studied the differential expression of genes involved in mitochondrial Ca2+ transport. These genes showed clear differential expression between both cell lines . On the one hand, Illumina identified five overexpressed genes (MCU, MICU1, MCUR1, EMRE, and VDAC2) and five downregulated genes (MICU2, MCUb, VDAC1, VDAC3, and NCLX) in HT29 cells. On the other hand, microarrays identified just one overexpressed gene, MCU (also identified by Illumina), and the same five downregulated genes identified by Illumina. Again, DFMO treatment affected only HT29 cells . Specifically, DFMO treatment upregulated the expression of MCU and VDAC3, indeed reversing the effects of cancer in the case of VDAC3. Western blotting confirmed that MCU was upregulated by DFMO treatment in HT29 cells at the protein level . In order to validate the most important results, the differential expression of selected genes was confirmed by qPCR analysis. For this analysis, we selected those genes whose differential expression in cancer cells vs. normal cells was reversed by DFMO treatment. The selected genes included those coding for channels TRPV6, TRPP1, and TRPC5; the SOCE modulators SEPTIN6 and ORMDL3; the pumps SPCA2 and PMCA4; and the mitochondrial transporters VDAC3 and MCU. Figure 11a confirms that all selected gene transcripts were differentially expressed in HT29 colon cancer cells relative to normal NCM460 cells, except for TRPC5 and ORMDL3, which showed no significant difference. Interestingly, when we compared the expression of the same selected genes in DFMO-treated normal and tumor cells, most differential expression was largely dampened , thus also confirming the microarray data shown above. Finally, when we compared qPCR data on the expression of the selected genes before and after DFMO treatment in HT29 cells, the results confirmed that, in accordance with the microarray data shown above, DFMO treatment significantly increased the expression of the Ca2+ extrusion systems PMCA4 and VDAC3 in HT29 colon cancer cells and decreased the expression of the TRPV6 and TRPP1 channels and the Orai1 positive modulator SPCA2 . However, in contrast to the microarray data, the qPCR data did not confirm the effects of DFMO treatment on TRPC5, SEPTIN6, ORMDL3, or MCU . 4. Discussion We investigated whether polyamine synthesis inhibition using DFMO as an ODC suicide inhibitor was able to reverse Ca2+ remodeling in cancer cells. To this end, HT29 and NCM460 cells were used as well-established cell models representing CRC and normal colonic cells, respectively . CRC cells displayed significantly enhanced levels of resting intracellular [Ca2+] and SOCE relative to normal cells. Likewise, CRC cells showed decreased Ca2+ store content relative to normal cells. These findings are similar to previous results reported in . We also showed here that SW480 colon cancer cells displayed enhanced SOCE and decreased Ca2+ stores compared to NCM460 cells, thus resembling the same intracellular Ca2+ remodeling as HT29 colon cancer cells. Although these changes were observed in cell lines representative of normal and tumor cells and should be confirmed in primary normal and tumor cells, changes in intracellular [Ca2+] homeostasis, collectively referred to as Ca2+ remodeling, could be part of the phenotypic changes associated with carcinogenesis; they may contribute to the hallmarks of cancer displayed by CRC cells, including enhanced cell proliferation and resistance to cell death . We found that the incubation of cells with DFMO, a treatment that abolishes polyamine biosynthesis and decreases levels of intracellular polyamines, also significantly decreased both resting Ca2+ and SOCE, whereas it increased the Ca2+ store content in CRC cells, thus reversing the hypothetical Ca2+ remodeling associated with CRC. These results are similar to our recently reported results . In contrast, in normal cells, the effects of DFMO were less important. These data suggested that polyamine synthesis inhibition may reverse, at least partially, the hypothetical Ca2+ remodeling associated with CRC, having minor effects on normal cells, where the ODC expression is low. Conversely, our results suggested that the excess polyamine synthesis observed in c-myc-related cancers may contribute to the hypothetical Ca2+ remodeling associated with CRC. The transcriptomic analysis of normal and CRC cells treated with DFMO showed that polyamine synthesis inhibition was able to significantly modify a large fraction (nearly 25%) of all gene transcripts studied in CRC cells. In striking contrast, in normal colonic cells, the same treatment affected less than 0.5% of the transcripts. Therefore, DFMO treatment was highly specific for cancer cells and had a nearly negligible effect on normal colonic cells. Again, we could explain these results by the fact that normal cells do not express ODC or express very low ODC levels unless this gene is induced during epithelial restitution, for instance. In this scenario, DFMO treatment probably induces only off-target effects or nearly negligible effects due to polyamine synthesis inhibition. These data also suggested that polyamines may induce rather dramatic effects on the transcriptome and the differential expression of nearly 25% of all the transcripts studied. In this work, we focused on the transcriptional effects on genes directly involved in intracellular Ca2+ homeostasis. We analyzed the effects of DFMO treatment (polyamine synthesis inhibition) on the transcription of the 10 voltage-gated Ca2+ channels, the 23 genes known to be involved in SOCE, the 28 TRP channels, the 6 Ca2+ release channels of the ER, the 12 Ca2+ pumps and exchangers, and the 11 genes known to be involved in mitochondrial Ca2+ transport. Figure 12 summarizes the changes in the Ca2+ transport systems in cancer cells relative to normal cells and the effects of DFMO. We used two independent approaches for transcriptomic analysis, i.e., Illumina next-generation RNA sequencing (RNAseq) and microarrays. Illumina data include sequence data that are critical in cases where polymorphisms or mutations are the main target. Microarrays only provide data on the relative transcription level of selected sequences. We selected microarrays instead of RNAseq for our analysis of the effects of DFMO treatment for several reasons. First, because microarray sensitivity is lower than that of RNAseq, we expected that the differentially expressed genes would be those more significantly influenced by DFMO treatment, leading to less artefactual DEGs. Second, the computational and preprocessing methods of transcriptomic outcomes are simpler with microarrays, i.e., RNAseq outcomes warrant more sophisticated and more computationally powerful methods than microarray outcomes. Finally, transcriptomic microarrays are generally more affordable. Regarding voltage-gated Ca2+ channels, the data obtained using Illumina were quite similar but not identical to our previous results obtained using Ion Torrent technology . Microarray analysis showed that only two transcripts were differentially expressed in cancer cells, whereas changes in three other transcripts were only significant according to Illumina and not microarray. Specifically, we found that Cav1.2 was downregulated, whereas Cav1.3 was upregulated in CRC cells. Polyamine synthesis inhibition had no effect on the expression of any of the voltage-gated Ca2+ channels, either in the CRC cells or in the normal cells. Accordingly, these data indicated that, although the previous results suggested the differential expression of certain voltage-gated Ca2+ channels in CRC, they could not be attributed to excess polyamine synthesis in CRC. In marked contrast, a number of molecular players involved in SOCE (ORAI1,2,3 and STIM1,2) and its modulatory proteins were differentially expressed in CRC cells relative to normal cells. Moreover, the transcription levels of SOCE molecular players were deeply influenced by polyamine synthesis inhibition. However, these changes were only observed in CRC and not in normal colon cells. Specifically, we found that DFMO treatment induced the increased expression of Stim1 and Stim2 transcripts in HT29 cells. These data are similar to our previous results using qRT-PCR . However, at the protein level, DFMO treatment decreased Stim1 expression in HT29 cells without changing Stim2 expression . In addition, DFMO treatment increased the expression of a number of SOCE modulators, including CRACR2A, ORMDL3, and several septins. In nearly all these cases, except for SEPTIN9, the change induced by DFMO reversed the change associated with cancer. These data suggested that a number of SOCE modulators are downregulated in CRC, leading to a loss in SOCE modulation that might contribute to the enhanced SOCE in cancer cells. However, in contrast to the microarray data, the qPCR data did not confirm that DFMO increased either SEPTIN6 or ORMDL3. Although qPCR is considered the gold-standard for testing differential expression, the larger number of primers used for the microarrays (20 instead of just one for qPCR) may explain this difference. Further research is required, therefore, to confirm the effects of the polyamine depletion of SOCE modulators. SPCA2, a secretory pathway Ca2+ ATPase that has recently been reported to interact and modulate Orai1 channels to activate them independently of store depletion , was overexpressed in CRC cells. Interestingly, we found that SPCA2 was downregulated after DFMO treatment in HT29 colon cancer cells but not in normal cells. These data were also confirmed by qPCR analysis. Therefore, these data suggested that overexpressed SPCA2 in CRC cells might contribute to enhance resting [Ca2+] and Orai1 activation independently of store depletion in CRC, a process that is limited by polyamine synthesis inhibition. In addition, it has recently been reported that the epigenetic modulation of SPCA2 reverses the epithelial-to-mesenchymal transition in breast cancer cells . It is tempting to speculate that overexpressed SPCLA2 in CRC cells due to polyamine excess may play a similar, previously unrecognized role in CRC as well. TRP channels were also differentially expressed in CRC cells relative to normal cells. In general, both the Illumina and microarray technologies showed the decreased expression of a number of different TRP channels in CRC cells, particularly TRPML1,2,3 and TRPP2. However, CRC cells also showed the enhanced expression of a few TRP channels, including the TRPC5, TRPV6, and TRPP1 channels, that may have contributed to the appearance of non-selective store-operated currents characteristic of CRC cells . qPCR data confirmed these results for TRPV6 and TRPP1 but not for TRPC5. This finding for TRPC5 could have been due to the extremely low number of copies of TRPC5 transcripts. Again, polyamine synthesis inhibition had no effect on the transcription of TRP channels in normal cells. In contrast, in CRC cells, polyamine synthesis inhibition decreased the expression of the TRPC1 and 5, TRPV6, and TRPP1 channels, whereas it increased TRPP2 gene transcription. The pPCR data also confirmed the effects of DFMO on the expression of TRPV6 and TRPP1. We reported previously that DFMO treatment decreased the expression of TRPC1 in HT29 cells at the protein level . Further research is required to validate these additional changes in the TRP channel expression at the protein level. The data on TRP channel remodeling induced by DFMO treatment strongly suggested that polyamines may influence cancer hallmarks acting on the transcriptional level of these TRP channels. For instance, TRPV6, the epithelial Ca2+ channel modulated by the vitamin D receptor, has also been previously related to CRC and other forms of cancer . The cases of TRPP1 and TRPP2 are intriguing, as these are channel complexes involved in sensing shear stress in epithelia that are present in the ER. The results indicated an increased TRPP1/TRPP2 ratio in CRC cells, a feature that was also reversed by polyamine synthesis inhibition. Further research is required to understand the role of the TRPP1 and 2 channels in colon cancer and their relation to polyamine synthesis. The Ca2+ release channels of the ER, including IP3 and ryanodine receptors, were differentially expressed in cancer cells and may also contribute to cancer hallmarks. However, none of these Ca2+ release channels were modulated by polyamine synthesis inhibition, either in normal or CRC cells, at least at the transcriptional level, thus excluding the possibility that changes in the transcription of these channels are mediated by ODC overexpression. Interestingly, as mentioned above, the TRPP1 and TRPP2 channels can also be found at the ER membranes, where they could play a role as leak channels. Specifically, TRPP2 is a calcium-permeant transient receptor potential (TRP) cation channel expressed primarily on the ER membrane and primary cilia of all cell and tissue types . TRPP2 mutations lead to autosomal-dominant polycystic kidney disease. Recent data indicate that TRPP2 is involved in susceptibility to cell death induced by stress . Accordingly, changes in the TRPP1/TRPP2 ratio related to CRC and polyamine synthesis could be involved in Ca2+ store content, Ca2+ transfer from the ER to mitochondria, and sensitivity to stress. Again, further research is required to validate this possibility. Regarding Ca2+ extrusion systems such as Ca2+ pumps and transporters, the data showed the differential expression of several transport systems, including the enhanced expression of the pumps PMCA1 and SPCA2 and the exchanger NCX2, along with the decreased transcription of the pumps PMCA4 and SPCA1. Again, polyamine synthesis inhibition had no effect on the transcription of any of these calcium extrusion systems in normal cells. However, in CRC cells, polyamine synthesis inhibition reversed the changes in the transcription of PMCA4 and SPCA2 linked to CRC. These results were confirmed by qPCR analysis. As stated above, SPCA2 may interact and modulate Orai1 to activate Orai1 independently of both Stim1 and Ca2+ store depletion, thus leading to store-independent Ca2+ entry. PMCA4, the plasma membrane Ca2+ ATPase linked previously to CRC , was downregulated in CRC, likely contributing to enhanced resting intracellular [Ca2+]. This gene returned to normal levels after DFMO treatment, thus probably contributing to decreased resting Ca2+ levels in treated cells. Finally, mitochondrial Ca2+ transport systems were differentially expressed in CRC cells. Most changes involved the decreased expression of the molecular players involved in the control of the mitochondrial Ca2+ uniporter (MCU) and the Ca2+ channel involved in mitochondrial Ca2+ uptake. Once more, polyamine synthesis inhibition had no effect on the transcription levels of the mitochondrial Ca2+ transport systems in normal cells. However, in cancer cells, polyamine synthesis inhibition increased the expression of both MCU and VDAC3. qPCR analysis also confirmed the increased expression of VDAC3 in DFMO-treated HT29 cells. We used western blotting to confirm that MCU expression was also enhanced at the protein level in HT29 cells treated with DFMO . Therefore, the modulation of the transcription of these two particularly relevant mitochondrial channels in CRC could be mediated by ODC and polyamines. Interestingly, these changes may contribute to explaining the reversal of the cancer hallmarks related to susceptibility to apoptosis. In other words, the enhanced resistance to apoptosis characteristic of CRC cells could be mediated, at least partially, by changes in the expression of MCU and VDAC3 due to ODC activation. In summary, our results indicated that a few genes involved in Ca2+ transport appeared to be specifically modulated by polyamines in CRC cells and could be responsible for most changes in intracellular Ca2+ homeostasis in CRC cells. Thus, an excess of polyamines could induce the downregulation of SOCE modulatory genes (STIM1,2), the plasma membrane Ca2+ ATPase PMCA4 Ca2+ pump, and the mitochondrial Ca2+ channels MCU and VDAC3, contributing to dysregulated SOCE and enhanced resting Ca2+ and mitochondrial Ca2+ uptake in CRC. Conversely, polyamines could also induce the overexpression of TRPV6 channels, the Orai1 activator SPCA2, and the exchange of TRPP1 channels by TRPP2, thus likely contributing to enhanced Ca2+ entry and decreased Ca2+ store content in CRC. These findings may provide new insights into the role of polyamines in Ca2+ remodeling in cancer. Further research in animal models and/or tumor samples from patients is required to validate our findings. 5. Conclusions We conclude that polyamine synthesis inhibition may partially reverse changes in intracellular calcium homeostasis hypothetically associated with CRC, including a decrease in resting intracellular Ca2+ and store-operated Ca2+ entry, as well as an increase in Ca2+ store content. These effects were observed in CRC cells but not in normal colonic cells. Analogously, polyamine synthesis inhibition induced the differential expression of 25% of the whole transcriptome in cancer cells but only about 0.25% of the transcripts in normal colonic cells. We also conclude that polyamine synthesis inhibition reversed the changes in the differential expression of transcripts associated with cancer. Specifically, polyamine synthesis inhibition decreased the expression of the TRPV6 and TRPP1 channels, as well as the Orai1 positive modulator SPCA2, probably contributing to decreased Ca2+ influx in DFMO-treated tumor cells. In addition, polyamine depletion enhanced the transcription of the plasma membrane PMCA4 Ca2+ pump and the mitochondrial channels MCU and VDAC3, thus probably contributing to enhanced Ca2+ extrusion in DFMO-treated cells. Collectively, these results may provide a transcriptional basis for the hypothetical calcium remodeling in CRC and its reversal by DFMO. Further research in animal models and/or tumor samples from patients is required to validate our findings. Acknowledgments We appreciate the expert technical assistance provided by David del Bosque. Supplementary Materials The following supporting information can be downloaded at: Table S1. Fold changes log2Fold Change (log FC) and corresponding FDR of Figure 4. Table S2. Fold changes log2Fold Change (log FC) and corresponding FDR of Figure 5. Table S3. Fold changes log2Fold Change (log FC) and corresponding FDR of Figure 6. Table S4. Fold changes log2Fold Change (log FC) and corresponding FDR of Figure 7. Table S5. Fold changes log2Fold Change (log FC) and corresponding FDR of Figure 8. Table S6. Fold changes log2Fold Change (log FC) and corresponding FDR of Figure 9. Figure S1. Effects of DFMO treatment on resting Ca2+ levels, Ca2+ store content and store-operated Ca2+ entry (SOCE) in normal NCM460 cells and colon cancer SW480 cells. Cultures of both normal NCM460 and colon cancer SW480 cells were treated with vehicle (a,c) or DFMO (b,d) for 96 h and then loaded with fura2/AM for Ca2+ imaging experiments. Resting Ca2+ levels were measured be-fore stimulating cells with cyclopiazonic acid (CPA) in Ca2+ free media to estimate Ca2+ store content. Finally, Ca2+ containing media was perfused in the presence of CPA to record SOCE. Representative single cell recordings are shown for cells located in the same optical field. Data are representative of 3 independent experiments for each condition. Figure S2. Statistical analysis of the effects of DFMO treatment on resting Ca2+ levels (a), Ca2+ store content (b) and store-operated Ca2+ entry (SOCE) (c) in NCM460 (blue bars) and SW480 cells (red bars). NCM460 and SW480 were pre-treated with vehicle (control) or DFMO for 96 h and subjected to calcium imaging for analysis of resting Ca2+ levels, Ca2+ store content and SOCE as shown in Figure 2. Bars plots represent, in original units of response variables (i.e. absolute value, maximum increment or AUC of F340/380 curves), the expected value (bar) and the SEM (error bars). Experimental conditions are grouped into different clusters which are indicated by letters: experimental conditions with different letters mean they are different between them; equal letters mean they are equal, and those experimental conditions with 2 or more letters (e.g., cluster ab) mean they are similar to those groups with any of these letters (i.e., cluster ab is similar both to cluster a and to cluster b). For every experimental condition 8 replicates have been and the total number of cells studied is 76 for NCM460 Control, 88 for SW480 Control, 88 for NCM460 treated with DFMO and 93 for SW480 treated with DFMO. Figure S3. Differences of MCU expression at protein level between HT29 colon cancer cells (Control) colon cancer cells treated with DFMO (DFMO). Protein level expression was carried out by Western-Blot assay, where MCU Expression variable means optical density from MCU normalized to optical density from b-actin. Data set have been analyzed by adjusting a linear model to data, model assumptions have been evaluated, the response variable transformed with Bos-Cox family transformations because of normality assumption was violated, and outlier detection has been carried out by analysis of the cook distance, the residual studentized and the hat values. After transformation, model assumptions were fulfilled: residual normality with the Shapiro-Wilks test (p value = 0.1961) and homocedasticity with the Bartlett test (p value = 0.8771). The sample size is equal to 6:3 corresponding to HT29 cells without treatment and the other 3 corresponding to HT29 cells treated with DFMO. p < 0.01. Click here for additional data file. Author Contributions Conceptualization, E.P.-R. and C.V.; methodology, E.P.-R., E.H.-P., and C.V.; software, E.P.-R.; validation, E.P.-R., E.H.-P., V.F., and S.T.; formal analysis, E.P.-R., E.H.-P., and L.N.; investigation, E.P.-R. and C.V.; resources, L.N. and C.V.; data curation, E.P.-R.; writing--original draft preparation, E.P.-R. and C.V.; writing--review and editing, E.P.-R. and C.V.; visualization, E.P.-R.; supervision, L.N. and C.V.; project administration, L.N. and C.V.; funding acquisition, L.N. and C.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 All data are available 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, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 Transcriptomics and functional experimental designs. (a) For each cellular line, the mRNA was extracted, isolated, and analyzed with Illumina technology. Specifically, in a single day (up to a total of 3 days), one sample from every cellular line was processed. (b,c) For every cellular line, we seeded 4 coverslips into 6-well plates and 2 dishes of 10 cm. After 24 h, treatment was added (control or DFMO 5 mM). After 96 h, on the one hand, the mRNA from the samples seeded into dishes was extracted and isolated to carry out transcriptomic assays. On the other hand, samples seeded over coverslips into 6-well plates were used for Ca2+ imaging experiments. Figure 2 Effect of DFMO treatment on intracellular polyamine levels in HT29 cells. Intracellular polyamine levels were estimated by measuring the red fluorescence of PolyamineRED (PolyRED) reagent on non-treated (control) or DFMO-treated cells. Images are representative of experiments on HT29 cells in the same acquisition conditions. Bar plot displays values corresponding to optical density (O.D.) from each cell, and the background was removed. The sample size was equal to 4 coverslips for each set of experimental conditions. The p-value corresponding to the hypothesized contrast in polyamines levels between the control and DFMO-treated cells was lower than 0.001, so we rejected the null hypothesis and accepted that polyamines levels were reduced in cells treated with DFMO. *** p < 0.001. Figure 3 Effects of DFMO treatment on resting Ca2+ levels, Ca2+ store content, and store-operated Ca2+ entry (SOCE) in NCM460 and HT29 cells. Cultures of both normal NCM460 and colon cancer HT29 cells were treated with vehicle (a,c) or DFMO (b,d) for 96 h and then loaded with fura2/AM for Ca2+ imaging experiments. Resting Ca2+ levels (I) were measured before stimulating cells with cyclopiazonic acid (CPA) in Ca2+-free media to estimate Ca2+ store content (II). Finally, Ca2+-containing medium was perfused in the presence of CPA to record SOCE (III). Ca2+ images (F340/F380) and single-cell recordings are shown for representative cells located in the same optical field. Images are coded in pseudocolor (color scale showing ratio values between 0 (blue) and 1 (red), corresponding to cytosolic free Ca2+ concentration (I), Ca2+ store content (II), and SOCE (III)). Data are representative of 8 independent experiments for each condition including 272 NCM460 control cells, 230 HT29 control cells, 303 NCM460 DFMO-treated cells, and 222 HT29 DFMO-treated cells. Figure 4 Statistical analysis of the effects of DFMO treatment on resting Ca2+ levels (a), Ca2+ store content (b,c), and SOCE (d,e) in NCM460 (blue bars) and HT29 cells (red bars). NCM460 and HT29 cells were pretreated with vehicle (control) or DFMO and subjected to calcium imaging for analysis of resting Ca2+ levels, Ca2+ store content, and SOCE, as shown in Figure 2. Bar plots represent, in the original units of the response variables (i.e., absolute value, maximum increment, or AUC of F340/380 curves), the expected value (bar) and the SEM (error bars). Experimental conditions were grouped into different clusters according to the adjusted p values shown in Table 2, which are indicated by letters: experimental conditions with different letters presented differences; identical letters indicate that the experimental conditions were equal; and those experimental conditions with 2 or more letters (e.g., cluster ab) were similar to those groups with any of these letters (i.e., cluster ab was similar to both cluster a and cluster b). For every experimental condition, 8 replicates were generated, and the total number of cells was: 272 for vehicle-treated NCM460 cells, 230 for vehicle-treated HT29 cells, 303 for DFMO-treated NCM460 cells, and 222 for DFMO-treated HT29 cells. Figure 5 Differential expression of VOCCs between HT29 (colon cancer) and NCM460 (normal colon) cells and effects of DFMO treatment. Bars from bar plots represent log2Fold Change, where the error is the confidence interval (x-axis), and both of them were estimated by the limma method for several genes (y-axis). Grey bars are not statistically different between conditions. Blue bars toward the left indicate significantly lower expression (FDR < 0.05) for cancer cells, whereas red bars toward the right indicate significantly higher expression in cancer cells (FDR < 0.05). (a,b) Differential expression between cell lines was tested through two different transcriptomic technologies: RNA-seq/Illumina (a) and microarrays/Clariom D Human Affymetrix (b). (c,d) Differential expression between cell lines treated and non-treated with DFMO was tested through microarrays/Clariom D Human Affymetrix both for NCM460 (c) and HT29 cells (d). Fold changes and p values are shown in Supplementary Table S1. Figure 6 Differential expression between HT29 (colon cancer) and NCM460 (normal colon) cells and between DFMO-treated and non-DFMO-treated cells for those genes that code for members of the store-operated calcium entry (SOCE) mechanism. Bars from bar plots represent log2Fold Change, where the errors are the confidence interval (x-axis), and both of them were estimated by the limma method for several genes (y-axis). Grey bars are not statistically different between conditions. Blue bars toward the left indicate significantly lower expression (FDR < 0.05) for tumoral cells in relation to normal cells, whereas red bars toward the right indicate higher expression (FDR < 0.05). (a,b) Differential expression between cell lines was tested through two different transcriptomic technologies: RNA-seq/Illumina (a) and microarrays/Clariom D Human Affymetrix (b). (c,d) Differential expression between cell lines treated and non-treated with DFMO was tested through microarrays/Clariom D Human Affymetrix for both NCM460 (c) and HT29 cells (d). The letter "R" in a circle beside the name of a gene means that the differential expression of that gene due to tumoral transformation was reversed after DFMO treatment (there was significant differential expression in terms of log2Fold Change, but in the opposite direction to that observed in tumor cells with respect to normal cells). Fold changes and p values are shown in Supplementary Table S2. Figure 7 Differential expression of TRP channel genes between HT29 (colon cancer) and NCM460 (normal colon) cells and between DFMO-treated and non-DFMO-treated cells. Bars from bar plots represent log2Fold Change, where the errors are the confidence interval (x-axis), and both of them were estimated by the limma method for several genes (y-axis). Grey bars are not statistically different between conditions. Blue bars toward the left indicate significantly lower expression (FDR < 0.05) for tumoral cells in relation to normal cells, whereas red bars toward the right indicate higher expression (FDR < 0.05). (a,b) Differential expression between cell lines was tested through two different transcriptomic technologies: RNA-seq/Illumina (a) and microarrays/Clariom D Human Affymetrix (b). (c,d) Differential expression between cell lines treated and non-treated with DFMO was tested through microarrays/Clariom D Human Affymetrix for both NCM460 (c) and HT29 cells (d). The letter "R" in a circle beside the name of a gene means that the differential expression of that gene due to tumoral transformation was reversed after DFMO treatment (there was significant differential expression in terms of log2Fold Change, but in the opposite direction to that observed in tumor cells with respect to normal cells). Fold changes and p values are shown in Supplementary Table S3. Figure 8 Differential expression of Ca2+ release channel genes between HT29 (colon cancer) and NCM460 (normal colon) cells and between DFMO-treated and non-DFMO-treated cells. Bars from bar plots represent log2Fold Change, where the errors are the confidence interval (x-axis), and both of them were estimated by the limma method for several genes (y-axis). Grey bars are not statistically different between conditions. Blue bars toward the left indicate significantly lower expression (FDR < 0.05) for tumoral cells in relation to normal cells, whereas red bars toward the right indicate higher expression (FDR < 0.05). (a,b) Differential expression between cell lines was tested through two different transcriptomic technologies: RNA-seq/Illumina (a) and microarrays/Clariom D Human Affymetrix (b). (c,d) Differential expression between cell lines treated and non-treated with DFMO was tested through microarrays/Clariom D Human Affymetrix for both NCM460 (c) and HT29 cells (d). Fold changes and p values are shown in Supplementary Table S4. Figure 9 Differential expression of Ca2+ extrusion genes between HT29 (colon cancer) and NCM460 (normal colon) cells and between DFMO-treated and non-DFMO-treated cells. Bars from bar plots represent log2Fold Change, where the errors are the confidence interval (x-axis), and both of them were estimated by the limma method for several genes (y-axis). Grey bars are not statistically different between conditions. Blue bars toward the left indicate significantly lower expression (FDR < 0.05) for tumoral cells in relation to normal cells, whereas red bars toward the right indicate higher expression (FDR < 0.05). (a,b) Differential expression between cell lines was tested through two different transcriptomic technologies: RNA-seq/Illumina (a) and microarrays/Clariom D Human Affymetrix (b). (c,d) Differential expression between cell lines treated and non-treated with DFMO was tested through microarrays/Clariom D Human Affymetrix for both NCM460 (c) and HT29 cells (d). The letter "R" in a circle beside the name of a gene means that the differential expression of that gene due to tumoral transformation was reversed after DFMO treatment (there was significant differential expression in terms of log2Fold Change, but in the opposite direction to that observed in tumor cells with respect to normal cells). Fold changes and p values are shown in Supplementary Table S5. Figure 10 Differential expression of genes coding for mitochondrial Ca2+ transport between HT29 (colon cancer) and NCM460 (normal colon) cells and between DFMO-treated and non-DFMO-treated cells. Bars from bar plots represent log2Fold Change, where the errors are the confidence interval (x-axis), and both of them were estimated by the limma method for several genes (y-axis). Grey bars are not statistically different between conditions. Blue bars toward the left indicate significantly lower expression (FDR < 0.05) for tumoral cells in relation to normal cells, whereas red bars toward the right indicate higher expression (FDR < 0.05). (a,b) Differential expression between cell lines was tested through two different transcriptomic technologies: RNA-seq/Illumina (a) and microarrays/Clariom D Human Affymetrix (b). (c,d) Differential expression between cell lines treated and non-treated with DFMO was tested through microarrays/Clariom D Human Affymetrix for both NCM460 (c) and HT29 cells (d). The letter "R" in a circle beside the name of a gene means that the differential expression of that gene due to tumoral transformation was reversed after DFMO treatment (there was significant differential expression in terms of log2Fold Change, but in the opposite direction to that observed in tumor cells with respect to normal cells). Fold changes and p values are shown in Supplementary Table S6. Figure 11 qPCR analysis of differential expression of selected genes in HT29 and NCM460 cells in control and DFMO-treated cells. (a) mRNA expression levels in cancer cells (HT29) were calculated using control cell (NCM460) expression levels as calibrator, and the ribosomal RP18S gene was used as housekeeping gene. In this representation, a value of 0 indicates no change, negative values indicate decreased expression, and positive values indicate increased expression in HT29 cells relative to NCM460. (b) mRNA levels of those genes coding selected Ca2+ transport system proteins in DFMO-treated HT29 cells relative to DFMO-treated NCM460 cells. (c) Differential expression of selected genes between DFMO-treated and non-treated HT29 cancer cells. Each data point was obtained from triplicate determinations from at least three different samples. Data were analyzed using the threshold cycle (Ct) relative quantification method (DDCt), and the relative abundance of the genes was calculated from 2(-DCt). Bar plots represent log(2-Ct) +- SEM. Statistical analysis in this plot was conducted by Student's t test with Bonferroni s correction for two independent samples (DCt(HT29) and DCt(NCM460)) obtained with RP18S as endogenous control. For the sake of clarity, statistically significant changes are plotted in green. * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 12 Molecular basis for the hypothetical remodeling of intracellular Ca2+ homeostasis in cancer and its reversal by polyamine synthesis inhibition. At the top of figure is displayed the differential expression between HT29 (right) and NCM460 (left) cell lines for only those genes of interest (i.e., genes coding for Ca2+ transport systems or modulators), which showed differential expression at a 0.05 signification level. Specifically, in the HT29 cell are displayed the genes that were upregulated in HT29 cells relative to NCM460 cells. The NCM460 cell shows genes that were upregulated in normal cells. Those genes whose differential expression was equal when assessed by both microarray and RNA-seq methods are surrounded by a black frame. Genes whose differential expression differed between the methods are indicated by two up and down arrows. Boxes next to each cell indicate the expected functional changes due to remodeling and its reversal (DFMO treatment). At the bottom of figure, indicated by a green arrow to the left, are displayed the changes observed in HT29 cells after DFMO treatment. HT29 cells treated with DFMO are halfway between HT29 and NCM460 cells. Genes which were differentially expressed after DFMO treatment include upregulated genes in red and downregulated genes in blue. Genes whose differential expression was reversed by DFMO treatment are highlighted in yellow. The effects of DFMO on the expression of TRPV6, TRPP1, SPCA2, PMCA4, and VDAC3 were confirmed by qPCR analysis. cancers-15-01600-t001_Table 1 Table 1 Primers used for PCR experiments. Name Primers (5' to 3') Predicted Size (pb) VDAC3 F: TCTATGGCTGGGCTGTGTTG R: ATGTGTGTGCAGCTGGAAGT 137 TRPV6 F: CCTTTGCTGCCTGTGTGAAC R: AGGTTGTACATCTGGCAGGC 151 TRPP1 F: GAGCCTAGACGTGTGGATCG R: GAGCACAGGTCGGTGTTACA 183 TRPC5 F: CCTGGTAGTGCTGCTGAACA R: GGGCTGGGGATGATGTTGAA 165 SPCA2 F: TTCCTCTACTCCGTCCTGGG R: CTCTTGGGGCTGCAACAGTA 191 SEPTIN6 F: TTTGTGAAGCTGCGGGAGAT R: AGCCCATCTCCTCCAGCTTA 112 PMCA4 F: TGGTCAAGTCGCAACTACCC R: GGCAGTCACTAACACCACGA 106 ORMDL3 F: CATCGGTCTCCTCCACATCG R: CACGATGGGTGTGATGGTCA 238 MCU F: ACTTTGGTGCTATGGGGTGG R: AGGTCCATTTCTGCCTGAGC 296 cancers-15-01600-t002_Table 2 Table 2 Adjusted p values of comparisons of resting cytosolic [Ca2+], Ca2+ store content, and SOCE between experimental conditions shown in Figure 3. Adjusted p Value (Red Values Are p < 0.05) [Ca2+]cyt Ca2+ Store Content SOCE Comparison Median 1st min AUC Max AUC Max HT29 Control - NCM460 Control 5.9962 x 10-1 0 2.8816 x 10-4 0 0 HT29 DFMO - HT29 Control 5.7354 x 10-1 0 0 3.3232 x 10-2 7.2647 x 10-1 HT29 DFMO - NCM460 Control 9.9997 x 10-1 9.8773 x 10-1 0 0 0 HT29 DFMO - NCM460 DFMO 1.8581 x 10-1 2.4919 x 10-5 0 0 0 NCM460 DFMO - HT29 Control 5.3660 x 10-3 0 2.6411 x 10-1 0 0 NCM460 DFMO - NCM460 Control 1.6650 x 10-1 6.4158 x 10-5 6.6866 x 10-2 9.9962 x 10-1 7.7062 x 10-1 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. |
PMC10000433 | The purpose of this RNA sequencing study was to investigate the biological mechanism underlying how the transcription factors (TFs) Twist1 and Zeb1 influence the prognosis of mycosis fungoides (MF). We used laser-captured microdissection to dissect malignant T-cells obtained from 40 skin biopsies from 40 MF patients with stage I-IV disease. Immunohistochemistry (IHC) was used to determinate the protein expression levels of Twist1 and Zeb1. Based on RNA sequencing, principal component analysis (PCA), differential expression (DE) analysis, ingenuity pathway analysis (IPA), and hub gene analysis were performed between the high and low Twist1 IHC expression cases. The DNA from 28 samples was used to analyze the TWIST1 promoter methylation level. In the PCA, Twist1 IHC expression seemed to classify cases into different groups. The DE analysis yielded 321 significant genes. In the IPA, 228 significant upstream regulators and 177 significant master regulators/causal networks were identified. In the hub gene analysis, 28 hub genes were found. The methylation level of TWIST1 promoter regions did not correlate with Twist1 protein expression. Zeb1 protein expression did not show any major correlation with global RNA expression in the PCA. Many of the observed genes and pathways associated with high Twist1 expression are known to be involved in immunoregulation, lymphocyte differentiation, and aggressive tumor biology. In conclusion, Twist1 might be an important regulator in the disease progression of MF. cutaneous T-cell lymphoma mycosis fungoides Twist1 Zeb1 RNA sequencing DNA methylation laser capture microdissection Northern Finland Terttu FoundationCancer Foundation FinlandThis study was funded by Northern Finland Terttu Foundation and Cancer Foundation Finland. pmc1. Introduction Primary cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of non-Hodgkin's lymphomas with no evidence of extracutaneous spread at the time of diagnosis. Mycosis fungoides (MF) is the most common CTCL, accounting for about 60% of all CTCL cases . Usually, patients are adults, and most of the patients are males. Sezary syndrome (SS) is a leukemic variant of CTCL. The clinical course of MF is variable. The disease starts with localized or disseminated patches or plaques that can remain skin-limited for years. However, in a subset of patients (10-20%) the disease evolves into the tumor or erythroderma stages, including extracutaneous spread with poor prognosis. Although the treatment modalities for MF have developed over the years, the disease remains still incurable, indicating the need to understand the biology of this disease better. Epithelial-to-mesenchymal transition (EMT) is an essential process in embryonic development and common in cancer progression . During EMT, the epithelial cells obtain the mesenchymal phenotype and convert to a more invasive, motile phenotype and acquire resistance to apoptosis. The role of EMT in cancer progression, dissemination, and therapy resistance has been well recognized in epithelial tumors, but in the case of hematopoietic malignancies, the significance of EMT is less well studied. One basic difference is that the cells of hematological malignancies already have a mesenchymal phenotype since they arrive from blood cells derived from the embryonic mesoderm. However, some of the EMT-controlling transcription factors (EMT-TFs), including Twist1 and Zeb1, control the differentiation of hematopoietic cells and have been associated with the progression of hematological malignancies . Twist1 is a T-cell oncoprotein that belongs to the basic helix-loop-helix (bHLH) protein family. Twist1 regulates the inflammatory processes and is involved in lymphocyte function and maturation, working as a key regulator of immune cells, especially T helper (Th) cell activation . Zeb1 is a protein-coding gene that suppresses hematopoiesis and downregulates the expression of CD4 during T-cell maturation . In the study of vanDoorn et al. (2004) , Twist1 was highly overexpressed among SS patients. Goswami et al. (2012) showed that Twist1 expression was correlated with MF and SS stages. They also observed an association between increased Twist1 and c-Myc expression and abnormal p53 expression. Our earlier studies showed that IHC Twist1+ is associated with worse prognosis and Zeb1+ with better prognosis in patients with MF . In this study, our aim was to investigate both the downstream regulation of Twist1 and Zeb1 to understand the biology behind their prognostic value. Our methods included Twist1 and Zeb1 IHC and RNA sequencing from 40 MF cases. The methylation level of the Twist1 promoter was analyzed from 28 MF samples. 2. Materials and Methods 2.1. Patient Material The retrospective patient material consisted of 40 biopsies from 40 MF patients with stage I-IV disease from the Helsinki University Hospital obtained during the years 2015-2019. 21 formalin-fixed and paraffin-embedded (FFPE) samples were taken at the time of the diagnosis and 19 from patients with relapsed disease. Patient data were collected from hospital records. These clinical variables included gender, age, WHO-EORTC stage, plasma lactate dehydrogenase (LDH) level, treatments, data on follow-up or relapses, progression, and mortality. 2.2. Immunohistochemical Staining, Analysis, and Correlation with Disease Presentation and Outcome Twist1 and Zeb1 immunohistochemical staining was performed as previously described in Lemma et al. (2013) . In the IHC analysis, the cut-off point for low and high expression of Twist1 was 17.6% and that for Zeb1 was 37%, defined by using a receiver operating characteristic (ROC) curve. Morphologically assessed neoplastic cells were counted as positive in the IHC analysis. Tumor cell count was estimated from the hematoxylin-eosin-stained samples identifying the hyperchromatic small to medium-sized haloed lymphocytes with hyperconvoluted nuclei as a percentage of the surrounding reactive lymphocytic cell infiltrate. The tumor cell count was estimated by an experienced hematopathologist. Additionally, the proportion of the entire lymphocytic infiltrate was estimated from the sample area. The time from diagnosis to the initiation of systemic therapy or to the last follow-up date (TTST) was calculated and used to perform a Kaplan-Meier analysis. A chi-squared test was used as a statistical method, and statistical significance was evaluated with the log rank. p-values < 0.05 were considered statistically significant. IBM SPSS Statistics for Macintosh, Version 28.0. (Armonk, NY: IBM Corp.) was used for ROC curves and Kaplan-Meier analysis. 2.3. Microdissection and RNA Extraction In total, 8-13 sequential paraffin-embedded slide sections with a thickness of 5 mm were prepared and mounted on pet (polyethylene terephthalate) slides (Leica AS LMD; Leica Microsystems Ltd., Wetzlar, Germany). Paraffin was removed by soaking in xylene twice for 10 min, and sections were stained with hematoxylin. One section was stained with CD3 antibody (NCL-L-CD3-565), which was used as a guide to differentiate between lymphocytic and epithelial cells . Laser capture microdissection (LCM) was performed using a ZEISS PALM MicroBeam Microsdissection system (Carl Zeiss Microscopy GmbH, Oberkochen, Germany) and adhesive collection caps. After microdissection, the samples were placed into collection vessels containing appropriate volumes of Depaffinization Solution (#19093, Qiagen GmbH, Hilden, Germany), and RNA was extracted using an MiRNeasy FFPE extraction kit (#217504, Qiagen GmbH, Hilden, Germany) generally according to the manufacturer's instructions. However, after adding proteinase K solution, the samples were incubated overnight at 56 degC with gentle shaking for a better yield. 2.4. The TWIST1 Promoter Methylation Analysis After LCM, DNA was isolated using a QIAamp DNA FFPE tissue kit (Qiagen, Hilden, Germany). DNA concentrations were measured using a Qubit 4 fluorometer, and bisulfite treatment was carried out using an EpiTect Fast DNA Bisulfite kit (Cat. No. 59824, Qiagen). The promoter area of the TWIST1 gene (Entrez Gene ID: 7291) was then amplified using a PyroMark CpG Assay (GeneGlobe Cat. no: PM00030121), PyroMark PCR kit, and RotorGeneQ device (Qiagen). The specificity of biotin-labeled amplification products was confirmed on agarose gel and purified for pyrosequencing with Streptavidin Sepharose beads (Cytiva) using a PyroMark Q24 Vacuum Workstation. Single-stranded DNA on a sequencing plate was annealed with the sequencing primer at 80 oC (2 min) and cooled at room temperature (15 min). Then, the plate was processed using the PyroMark Q24 Instrument with compatible Gold Q24 reagents. Finally, the sequencing run was analyzed via the PyroMark Q24 software version 2.0.6. (Qiagen, Hilden, Germany). 2.5. RNA Sequencing Data Analysis The quality and quantity of the extracted RNA samples were analyzed with a LabChip GX Touch HT RNA Assay Reagent Kit (PerkinElmer, Waltham, MA, USA) and Qubit RNA BR kit (Thermo Fisher Scientific, Waltham, MA, USA). For genomic DNA contamination measurement, a Qubit DNA BR kit (Thermo Fisher Scientific, Waltham, MA, USA) was used. Dual-indexed mRNA libraries were prepared from 150 ng of total RNA with a QuantSeq 3' mRNA-Seq Library Prep Kit FWD (Lexogen Gmbh, Vienna, Austria) according to user guide version 015UG009V0251. During second strand synthesis, 6 bp Unique Molecular Identifiers (UMIs) were introduced with the UMI Second Strand Synthesis Module (Lexogen Gmbh, Vienna, Austria) for detection and removal of PCR duplicates. The quality of the libraries was measured with a LabChip GX Touch HT DNA High Sensitivity Reagent Kit (PerkinElmer, Waltham, MA, USA). Sequencing was performed with a NovaSeq 6000 System (Illumina, San Diego, CA, USA) with read length of 2 x 101 bp and target coverage of 10 M reads for each library. QuantSeq 3' mRNA-Seq Integrated Data Analysis Pipeline version 2.3.1 FWD UMI (Lexogen Gmbh, Vienna, Austria) on Bluebee(r) Genomics Platform was used for primary quality evaluation of the RNA sequencing data. 2.6. Read Counts and Principal Component Analysis For visual exploration of the data, the read counts were normalized using the variance stabilizing transformation (VST) method implemented in the DESeq2 (version 1.30.1) package in R (version 4.0.3) , which transforms the count data in a way that minimizes differences between samples for rows with small counts and normalizes the data with respect to library size, with large values approximating a log2 scale. Visual inspection of the samples was performed using principal component analysis (PCA) implemented in the 'prcomp' function in R, applied to the normalized read counts of the top 500 genes according to variance. Additionally, the same data were used to generate a Pearson's correlation heat map from all pairwise comparisons of samples, using the 'pheatmap' package (version 1.0.12) in R. 2.7. Differential Expression Analyses Data normalization and differential expression (DE) analysis were performed using the DESeq2 package in R. Genes with an absolute log2 fold change > 0.58 (absolute fold change of 1.5) and an adjusted p value < 0.05 (adjusted for multiple testing using the Benjamini-Hochberg procedure ) were considered to be significantly differentially expressed. Initially, two contrasts were made using only diagnostic samples: first, high-Twist1-expression (Twist+) samples against low-Twist1-expression (Twist1-) samples, followed by high-Zeb1-expression (Zeb1+) samples against low-Zeb1-expression (Zeb1-) samples. A second round of DE analysis was performed between Twist1+ and , this time including both diagnostic and follow-up samples. The results of the two sets of Twist1 expression contrasts were compared using Pearson's correlations. 2.8. Ingenuity Pathway Analysis The full results table from the DESeq2 analysis of Twist1+ versus Twist1-, using both diagnostic and follow-up samples, was read into the Ingenuity Pathway Analysis (IPA) software . Then an IPA core analysis was run with the following analysis settings: the reference was set to 'User Dataset', the confidence level was set to 'Experimentally Observed', the species was set to 'Human', the log2 fold-change filter was set to <-0.58 and >0.58, and the adjusted p value filter was set to <0.05. The significance threshold for the identified pathways and regulators was also set to an adjusted p value of 0.05. 2.9. Hub Gene Analysis To identify hub genes, a protein-protein interaction (PPI) network was constructed from the genes that were significantly differentially expressed between high and low Twist1 expression groups (all samples) using the STRING database through the StringApp within Cytoscape . The connectivity of the nodes in the network was assessed using the cytoHubba plugin and nodes with a degree of connectivity of 10 or more were said to be hub genes. 3. Results 3.1. Patients Patient demographics are presented in Table 1. The median age was 63 years (range 19-86 years), and most of the patients were male (70%). The median follow-up time was 32.2 months (range: 6.28-203 months). 3.2. Immunohistochemistry of Twist1 and Zeb1, Correlation with Histomorphology, Disease Presentation and Outcome For Twist1, there were 20 high expression and 20 low expression cases. For Zeb1, there were 4 high expression and 36 low expression cases. Twist1 expression was not associated with tumor cell percentage or lymphocyte cell proportion, or with the clinical stage. There were no significant correlations between the collected clinical variables and Twist1 protein expression. However, among the patients with diagnostic samples, there was a trend for the cases with high Twist1 protein expression to require systemic therapy sooner than the cases with low expression . 3.3. The Analysis of TWIST1 Promoter Methylation The methylation levels of four CpG islands of 28 cases were analyzed: CpG1, CpG2, CpG3, and CpG4. The means and standard deviations for GpG islands 1, 2, 3, and 4 were M1 = 3.96 (SD1 = 2.25), M2 = 3.36 (SD2 = 2.22), M3 = 12.31 (SD3 = 3.76), and M4 = 1.58 (SD4 = 0.902), respectively. For the total methylation level, the mean was 20.95 and SD was 6.88. The methylation levels did not correlate with the IHC or RNA expression of Twist1. 3.4. The Association between Twist1 and Zeb1 Protein Levels and RNA Levels To see how well the RNA expression for Twist1 and Zeb1 corresponded to high/low classification based on IHC expression, the normalized expression for each gene in each sample was plotted on a heat map . Generally, Twist1 RNA expression agreed with the high/low IHC expression classification of the samples, while Zeb1 RNA expression did not correlate well with the classification. A Pearson correlation coefficient was conducted to examine these correlations. Twist1 RNA expression correlated positively to IHC expression (r (38) = 0.46, p value < 0.01), while no correlation could be seen between Zeb1 RNA and protein expression (r (38) = -0.070, p value = 0.67). For Twist1, there were also cases that did not correlate; for example, the case of MH37 had high Twist1 protein expression but the lowest RNA expression of the whole series. 3.5. The Principal Component Analysis (PCA) To investigate whether the samples clustered according to their Twist1 and Zeb1 expression, we performed PCAs on the normalized read counts both for all samples combined and diagnostic samples individually (see Methods). The samples were observed to separate along PC1 according to their Twist1 expression category in both analyses. PC1 explained 26% of the variation for all samples and 32% of the variation for diagnostic samples . A similar pattern was not seen for Zeb1 expression categories. Furthermore, there appeared to be no separation between the diagnostic and follow-up samples . 3.6. High vs. Low Twist1 and Zeb1--Differential Expression Analysis Differential expression (DE) analysis between Twist1+ and samples only returned 11 significantly (adjusted p value <= 0.05, absolute log2 fold change > = 0.58) differentially expressed genes: OAS2, ENSG00000201329, FCER1G, LGALS9, LYZ, LITAF, HLA-DRA, HLA-A, IGHM, NDUFA4 and RPGR . The corresponding analysis for Zeb1 expression yielded no significant genes. Considering the low statistical power when analyzing only diagnostic samples and given that there seemed to be little separation between diagnostic and follow-up samples in terms of gene expression , the DE analysis between Twist1+ and was repeated for the diagnostic and follow-up samples combined. This analysis yielded 321 significant genes (adjusted p value < = 0.05, absolute log2 fold change > = 0.58). Expression of the top 100 significant genes (according to the adjusted p value) is visualized in the heatmap in Figure 5, where the samples are clustered largely by their Twist1 categories. The top genes generally have higher expression in the Twist1+ samples than in the . Furthermore, diagnostic and follow-up samples appeared to be intermixed, irrespective of the clinical staging. The results of the DE analysis with all samples combined correlated well with those from the analysis using only diagnostic samples for both the adjusted p value and the log2 fold change . Seven of the significant genes from the first analysis were also identified in the second analysis (OAS2, ENSG00000201329, LGALS9, LITAF, HLA-DRA, IGHM and NDUFA4). 3.7. High vs. Low Twist1--Ingenuity Pathway Analysis The results of the differential expression analysis were used as input for Ingenuity Pathway Analysis (IPA). This resulted in three significant pathways (adjusted p value < 0.05): the 'GP6 Signaling Pathway', 'Hepatic Fibrosis/Hepatic Stellate Cell Activation', and 'B Cell Development'. Prior to correcting for multiple testing, there were 35 significant pathways (p value < 0.05), as shown in Supplementary Figure S3. The IPA core analysis also identified 228 significant upstream regulators (adjusted p value < 0.05) and 177 significant master regulators/causal networks (adjusted p value < 0.05) (Supplementary Tables S1 and S2). 3.8. Hub Gene Analysis Analysis of the protein-protein interaction network constructed from the results of the Twist1 differential expression analysis resulted in 28 identified hub genes (connectivity degree >= 10), as shown in Figure 7. 4. Discussion In previous studies, the protein expression of the EMT TFs Twist1 and Zeb1 was shown to have prognostic relevance in MF . Here, we sought to explore the biology of these differences more deeply. Through RNA sequencing, we found that most of the regulation of Twist1 expression occurs at the translational level, while no correlations were found between Zeb1 protein and the mRNA level. In the PCA, Twist1 expression was found to classify MF cases into different clusters according to their global RNA expression. Several genes and pathways known to be associated with aggressive tumor biology were found to be overexpressed among high Twist1 cases. For Zeb1, similar associations were not observed. MF is the most frequent cutaneous T-cell lymphoma, originating from the peripheral epidermotropic T-cells. Despite the many available treatment options, MF is still considered incurable, except for allogenic stem cell transplantation. The intricate molecular mechanisms behind the MF transition from an indolent to a progressive disease are not completely understood. Currently, it is anticipated that alterations in defined signaling networks promote the proliferation, survival, and migration of malignant T-cells, as well as the suppression of their immune regulation, resulting in changes to the tumor microenvironment that enables disease progression . In our previous study , we found that the IHC detection of Twist1 and Zeb1 have prognostic value in MF: Twist1+ and patients with a worse prognosis. The results of the IHC analysis of the present study were in line with previous results, but statistical significance could not be shown, likely due to the limited sample size. Other studies have also proposed that Twist1 protein may be one of the key regulators in MF progression. Dobos et al. studied the prognostic value of the expression levels of several proteins of peripheral blood leukocytes in MF and SS using the multiomics method. The authors found T-plastin, Twist1, and KIR3DL2 to bear the highest prognostic relevance. On the other hand, Song et al. demonstrated core oncogenic processes behind large cell transformation of MF. These processes included metabolic reprogramming, cellular plasticity, upregulation of myelocytomatosis oncogene (MYC) and E2 promoter binding factor (E2F) activities, and downregulation of major histocompatibility complex 1 (MHC1). One of the key elements in cellular plasticity is the upregulation of Twist1 protein expression through gene amplification . The regulation of Twist1 expression in cancer is a complicated process including modulation at many levels and depending on the cancer type and tissue context . Transcriptionally, Twist1 can be upregulated via multiple signal transduction pathways such as the tumor necrosis factor receptor (TNFR), receptor tyrosine kinase (RTK), frizzled (FZD), tumor growth factor beta (TGFss), NOTCH, and epidermal growth factor receptor (EGFR) pathways . The most important intracellular regulators include mitogen activated protein kinase (MAPK), protein kinase B (Akt), nuclear factor-kB (NF-kB), muscle segment homeobox 2 (MSX2), ss-catenin, Fibulin 5 (FBLN5), mothers against decapentaplegic homolog 2 (Smad), high-mobility group AT-hook 2 (HMGA2), signal transducer and activator of transcription 3 (STAT3), and hypoxia inducible factor-1 (HIF-1a) . MAPK, Akt, and casein kinase (CK2) are important Twist1 phosphorylating kinases that participate in the post-translational regulation of Twist1 . We found an association between Twist1 protein and RNA expression levels. In contrast to a study by Galvan et al. , we did not detect a clear connection between promoter methylation and the RNA levels of TWIST1/Twist1, indicating that this is likely not a major reason for TWIST1 overexpression in MF. We also did not observe overexpression of other known positive TWIST1 regulators, thereby leaving TWIST1 overexpression largely unexplained. Despite a robust correlation between TWIST1 mRNA and protein levels, there were also cases with deviant results, indicating that translational/posttranslational regulation also plays a role. For example, beta-transducing repeat containing protein (b-TRCP) was shown to play a role in Twist1 degradation . For Zeb1, the protein and RNA amounts did not correlate with each other, suggesting that most regulation takes place in the posttranscriptional level. In the PCA, Twist1 expression partly explained the clustering of the MF cases along the first principal component. This result illustrates that Twist1 is an important modulator of MF biology. This implication seems reasonable considering Twist1's integral role in T-cell differentiation. However, in this study setting, we were only able to demonstrate association between these two factors, which does not always imply causality. For Zeb1, the PCA did not reveal any grouping of samples according to their Zeb1 expression. The small number of cases with high Zeb1 expression might explain why we could not detect a function of Zeb1 in MF. Differential expression analysis between Twist1+ and MF samples revealed 11 significantly differentially expressed genes; OAS2, ENSG00000201329, FCER1G, LGALS9, LYZ, LITAF, HLA-DRA, HLA-A, IGHM, NDUFA4 and RPGR. High Twist1 protein expression was associated with overexpression of RPGR and ENSG0000020132. The rest of the genes were downregulated when Twist1 protein expression was high. Most of these genes are associated with adverse biological features in different malignancies. High OAS2 expression was shown to associate with better prognosis in breast , bladder and colorectal cancer . In acute myeloid leukemia (AML), OAS2 expression was shown to induce chemoresistance . Galectin-9 was previously shown to correlate with disease severity and decreased CD8 cell infiltration in CTCL . Moreover, anti-Gal-9 therapy selectively expands intratumoral T-cell immunoglobulin and mucin-domain containing-3 positive (TIM-3+) cytotoxic CD8 T-cells, as well as immunosuppressive regulatory cells . Previous studies have confirmed the role of FCER1G in several cancers . FCER1G takes part in promoting squamous carcinogenesis (SCC) progression , and predicts poor prognosis in gliomas and clear cell renal cell carcinomas (RCC) . In multiple myeloma, FCER1G predicts better prognosis . According to the previous research, LITAF may be considered as a tumor suppressor . In AML, LITAF was shown to increase cell apoptosis and differentiation . In colorectal cancer, HLA-A is associated with a favorable prognosis . The downregulation of NDUFA4 was detected in RCC . The ingenuity pathway analysis of Twist1 overexpression resulted in 35 pathways before correcting for multiple testing. When Twist1 was overexpressed, the glycol protein VI (GP6) signaling pathway was one of the most strongly upregulated pathways. GP6 is part of the immunoglobulin superfamily and is expressed in the platelets and megakaryocytes taking part in their activation. Along with their coagulative functions, platelets have an active role in regulating immune phenomena and in tumor cells immune escape. On the other hand, platelets also induce EMT in tumor cells. It was proposed that platelets play a role in tumor progression and metastasis by reducing natural killer (NK) cell antitumor activity. Kopp et al. showed that when coating tumor cells with platelet-derived soluble factors from stimulated platelets, the functions of NK cells were impaired. Additionally, the platelet coat might protect tumor cells from immunosurveillance . In a study by Yavadav et al. , the GP6 signaling pathway was associated with endometrial cancer progression. The other upregulated pathways included "regulation of the EMT in development pathway", "actin cytoskeleton signaling", "pulmonary fibrosis idiopathic signaling pathway", and "integrin linked kinase (ILK) signaling". Since Twist1 functions as an EMT inducer, it is a logical consequence that this pathway is upregulated. Actin filament modulation has also been closely associated with EMT and the actin cytoskeleton has a vital role in completing EMT-induced alterations in the cells . The transformations in the cell cytoskeleton are significant in several cancers. For example, changes to the actin cytoskeleton can promote metastasis . Twist1 was shown to modulate the actin cytoskeleton in human glioblastoma . Upregulation of the pulmonary fibrosis pathway seems reasonable since EMT also plays a role in pulmonary fibrosis . ILK participates in many cell functions such as cell-extracellular matrix interactions, cell cycle, apoptosis, cell proliferation, and cell motility. ILK also has multiple functions in different cancers, such as inducing EMT . Twist was proven to activate ILK, while in phyllodes breast tumors, ILK was shown to transmit its effects via the Twist pathway . 'Hub genes' are genes with a high degree of connectivity in the protein-protein interaction network that are significantly enriched in transcriptional regulation. From our differential expression analysis, we were able to highlight 28 genes that share a known protein to protein interaction. In "high Twist1"- samples, the transcriptionally downregulated molecules included the B-cell lineage markers PAX5, CD19, CD22, CD20 (MS4A1) CD79a, B-cell activator cytokine TNFSF13B, and the antigen presentation marker CD40, whereas transcriptionally upregulated molecules included cell-cell interaction molecules tight junction protein 1 (TJP1) and gap junction alpha-1 protein (GJA1), cell-matrix interaction molecule integrin alpha 1 (ITGA1) with multiple extracellular matrix proteins collagen type V alpha 2 (COL5A2), decorin (DCN), fibrillin (FBN1), transgelin (TAGLN), basement membrane protein laminins (LAMA, LAMB, LAMC), and extracellular matrix cross linker lysyl oxidase (LOX). Very few studies are available about cell interaction and matrix molecules in mycosis fungoides . The observed downregulation of B-cell markers contrasts with previous papers reporting a trend towards worse prognosis in the presence of over 50% of CD20 positive cells and upregulation of the CD20 gene (MS4A1) in MF disease progression . The downregulation of B-cell markers could result from a paucity of reactive intratumoral B-lymphocytes or true gene expression downregulation in such cells. One of the most interesting, downregulated pathways was the "Th 1 pathway". During MF progression, the amount of Th1 cells decreases while the amount of Th2 cells increases . This change in the predominance between Th1 and Th2 cells also changes the cytokine milieu of the tumor. Malignant T-cells produce immunoregulatory cytokines that repress Th1 responses and activate signaling pathways related to altered immune responses in the tumor microenvironment, further enhancing disease progression . Based on hub gene analysis, one of the most strongly upregulated genes in the Twist1 high group is CD73 (NT5E), which is an integral protein in immune suppression . The expression of CD22, a molecule that prevents autoimmune reactions, was reported to be expressed in MF but our results were different. Surprisingly, the extracellular-signal-regulated kinase (ERK)/MAPK signaling pathway was downregulated when Twist1 expression was high. Hyperactivation of this signaling pathway was detected in cancer development and progression . Previously, the upregulation of MAPKs was associated with Twist1 overexpression in breast cancer and melanoma . The hub gene analysis highlighted the upregulation of gap-junction protein (GJA1), which is a limiting factor in MAPK/ERK signaling . In MF, malignant cells form gap junctions with Langerhans cells . Other downregulated pathways included "phosphoinositide 3-kinase (PI3K) signaling in B-lymphocytes", "ribosomal protein S6 kinase beta 1 (p70S6K) signaling", and "triggering receptor expressed on myeloid cells 1 (TREM1) signaling systemic lupus erythematosus in B-cell-signaling pathway". The PI3K-Akt pathway is an intracellular signal transduction pathway that promotes metabolism, proliferation, cell survival, growth, and angiogenesis in response to extracellular signals. The PI3K/Akt signaling pathway has a connection with EMT, having the ability to influence tumor aggressiveness by affecting EMT . Indeed, the hub gene analysis highlighted differentially expressed EMT related adhesion and matrix proteins, which is no surprise as the DE analysis was set against high and low expression of EMT transcription factor Twist1, and additionally, they are essential to the microdissected area. 5. Conclusions In conclusion, Twist1 overexpression seems to be associated with several proteins and pathways involved in immunoregulation and lymphocyte differentiation. Zeb1 protein expression did not show any major correlation with global RNA expression in the PCA. However, there were only four cases with strong Zeb1 protein expression, a fact that precludes drawing any firm conclusions from these data. One limitation of our study is that we used both diagnostic and follow-up samples. However, these two groups did not considerably differ in terms of their gene expression. In addition, the results of the DE analysis with all samples combined correlated well with those from the analysis using only diagnostic samples, thus indicating that this limitation likely did not have a major impact on the results. Additionally, the number of cases was limited; especially regarding the analyses of Zeb1 expression, limited number of cases may have hindered the detection of some existing biological differences. Additionally, using paraffin-embedded tissue may have interfered with the sensitivity of the method. The strength of our study is in the high standard data analyses as well as the use of laser-captured microdissected samples, which decreased the bias caused by non-malignant stromal and epithelial cells. However, we were not able to fully rule out the impact of dilution of genes of interest. Could there, with this approach, be a dilution of genes of interest in early-stage disease as the microdissected area represents a much larger percentage of stromal and non-neoplastic T-cells compared to MF in advanced-stage disease? We find this unlikely, since Twist1 expression did not correlate with MF staging or tumor cell density or percentage of reactive lymphocyte. Although we microdissected CD3-positive cells from the FFPE sections, cell populations with different backgrounds were inevitably collected during RNA extraction. Considering the present results compared to recent literature, we anticipate Twist1 to be a central transcription factor and pathway regulator in the disease progression of MF. Naturally, in this kind of experiment setting, we were not able to confirm causality, and our results still need to be validated in cell culture or animal models with Twist1 knockout. Nevertheless, these results suggest that Twist1 is an interesting object for developing targeted therapies for MF. Acknowledgments We would like to thank Anne Ojala for skillful technical assistance. RNA sequencing was performed by the Sequencing Unit of the Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. The sequencing unit was supported by Biocenter Finland. Supplementary Materials The following supporting information can be downloaded at: Figure S1: The immunohistochemical CD3 expression and microdissected region; Figure S2: Principal component analysis with diagnostic status annotated; Figure S3: Canonical pathways significant before correcting for multiple testing; Table S1: 228 significant upstream regulators according to adjusted p value in the IPA core analysis; Table S2: 177 significant master regulators/causal networks according to the adjusted p value in the IPA core analysis. Click here for additional data file. Author Contributions Conceptualization, A.R., H.K., K.-M.H., L.V., M.E.L.K. and O.K.; methodology, H.-R.T. and K.P.; software, H.-R.T. and M.J.H.; formal analysis, H.J.B., H.K., J.K., K.-M.H., M.E.L.K., M.J.H. and O.K.; investigation, H.-R.T., J.K., K.-M.H., M.J.H. and O.K.; resources, L.V. and M.J.H.; data curation, H.-R.T., J.K. and M.J.H.; writing--original draft preparation, J.K. and O.K.; writing--review and editing, A.R., H.K., H.-R.T., K.-M.H., K.P., L.V., M.E.L.K. and O.K.; visualization, H.J.B., H.-R.T., J.K. and M.J.H.; supervision, H.-R.T. and O.K.; project administration, O.K.; funding acquisition, H.K. and O.K. 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 Northern Ostrobothnia Hospital District, Oulu University Hospital, and the Finnish National Supervisory Authority for Welfare and Health, who granted permission to use patient samples for research purposes (EETTMK: 14/2018, 20 January 2020). Informed Consent Statement According to the national legislation of Finland, tissues gathered for diagnostic purposes can be used in scientific studies without informed consent from the patient; therefore, informed consent was not obtained for the current study (Valvira Dnro 6622/05.01.00.06/2010, 28 September 2010). Data Availability Statement For detailed data, please contact corresponding author. Conflicts of Interest The authors declare no conflict of interest. Abbreviations Akt Protein kinase B AML Acute myeloid leukemia bHLH Basic helix-loop-helix CCL2 C-C motif chemokine ligand2 CD Cluster of differentiation CDK5 Cyclin-dependent kinase 5 CK2 Casein kinase 2 COL5A2 Collagen type V alpha 2 chain CTCL Primary cutaneous T-cell lymphoma CXCR5 C-X-C chemokine receptor type 5 DCN Decorin DE Differential expression EGFR Epidermal growth factor receptor eIF4 Eukaryotic translation initiation factor 4E EMT Epithelia-mesenchymal transition ERK Extracellular signal-regulated kinase FBLN5 Fibulin 5 FBN1 Fibrillin 1 FCER1G Fc epsilon receptor Ig FFPE Formalin-fixed, paraffin-embedded FZD Frizzled GJA1 Gap junction alpha-1 protein GP6 Glycoprotein VI HGF Hepatocyte growth factor HIF-1 Hypoxia inducible factor-1 HLA-A Major histocompatibility complex, class I, A HLA-DRA Major histocompatibility complex, class II, DR Alpha HMGA2 High-mobility group AT-hook 2 IGHM Immunoglobulin heavy constant IHC Immunohistochemistry ILK Integrin-linked kinase IL-7 Interleukin 7 ITGA1 Integrin alpha 1 ITGAX Integrin subunit alpha X LAMA Laminin subunit alpha 1 LAMB Laminin subunit beeta LAMC Laminin subunit gamma LCM Laser capture microdissection LDH Lactate dehydrogenase LGALS9 Galectin 9 LITAF Lipopolysaccharide induced TNF factor LOX Lysyl oxidase LYZ Lysozyme MAPK Mitogen activated protein kinase MF Mycosis fungoides MSX2 Muscle segment homeobox 2 MS4A1 Membrane Spanning 4-Domains A1 NDUFA4 NDUFA4 Mitochondrial Complex Associated NF-kB Nuclear factor-kB NK cell Natural killer cell NT5E 5'-Nucleotidase Ecto OAS2 2'-5'-oligoadenylate synthetase PAX5 Paired box 5 PCA Principal component analysis Pet Polyethylene terephthalate PI3K Phosphoinositide 3-kinase p70S6K Ribosomal protein S6 kinase beta 1 RCC Clear cell renal cell carcinomas RTK Receptor tyrosine kinase RPGR Retinitis pigmentosa GTPase regulator SCC Squamous carcinogenesis SELL Selectin L Smad Mothers against decapentaplegic homolog 2 SS Sezary syndroma STAT3 Signal transducer and activator of transcription 3 SRC-1 Steroid receptor coactivator TAGLN Transgelin TF Transcription factor TGFss Tumor growth factor beta Th T helper TIM-3+ T-cell immunoglobulin and mucin-domain containing-3 TJP1 Tight junction protein 1 TNFR Tumor necrosis factor receptor TNFSF13B TNF superfamily member 13b TTNST Time to next systemic treatment TREM Triggering receptor expressed on myeloid cells 1 TSEB Total skin radiation therapy TTST Time to systemic therapy TWIST1 TWIST1 gene Twist1 Twist1 protein Twist1+ High Twist1 expression Twist1 expression Zeb1+ High Zeb1 expression Zeb1 expression ZBTB16 Zinc finger and BTB domain containing 16 B-TRCP Beta-transducing repeat containing protein Figure 1 Time to systemic therapy (TTST) based on Twist1 nuclear expression in MF patient samples. TTST was evaluated from confirmed diagnosis date to beginning of systemic therapy or last follow-up date. The cut-off value for Twist1 was 17.6% and cases were divided into two groups based on expression results: Twist1 low <17.6% (n = 10) and Twist1 high >=17.6% (n = 11). Patients with high nuclear Twist1 expression were associated with shorter TTST and required systemic treatments earlier (p value = 0.133). Figure 2 Comparison of immunohistochemical and RNA levels of Twist1 and Zeb1 in analyzed samples. First three rows indicate diagnostic and follow-up samples, Twist+ and Zeb+ and . Heat map of normalized read counts (normalized with the VST method in DESeq2) for all analyzed samples for TWIST1 and ZEB1 RNA. The rows are scaled so that blue indicates below-average expression for the gene, and red indicates above-average expression. Figure 3 First two principal components of the PCA, with Twist1 (a) and Zeb1 (b) expression categories for all samples (n = 40) and diagnostic samples only (n = 21). Blue indicates low Twist1/Zeb1 expression, and red indicates high Twist1/Zeb1 expression. Figure 4 Heatmap of normalized read counts (with the VST method in DESeq2) for the nine genes according to adjusted p value, for diagnostic samples in the DE analysis. The rows are scaled so that blue indicates below-average expression for the gene, and red indicates above-average expression. IGHM, Immunoglobulin heavy constant; Mu OAS2, 2'-5'-oligoadenylate synthetase; NDUFA4, NDUFA4 Mitochondrial complex associated; LGALS9, Galectin 9; LITAF, Lipopolysaccharide induced TNF factor; LYZ, Lysozyme; HLA-A, Major histocompatibility complex, class I; FCER1G, Fc epsilon receptor Ig; HLA-DRA, Major histocompatibility complex, class II, DR Alpha; RPGR, Retinitis pigmentosa GTPase regulator. Figure 5 Heatmap of normalized read counts (with the VST method in DESeq2) for the top 100 genes according to adjusted p value, for all samples in the differential expression analysis. The rows are scaled so that blue indicates below-average expression for the gene, and red indicates above-average expression. Figure 6 Comparison of the results of the DE analysis run on diagnostic samples and all samples combined, showing the relationship between the two models' adjusted p values (a) and predicted log2 fold changes (b). Figure 7 Interaction network of the 28 identified hub genes. The fill color corresponds to log2 fold change estimated by DESeq2, with blue indicating negative changes and red indicating positive changes in the high-Twist1-expression group relative to the low-expression group (created using the Cytoscape software). CCL2, C-C motif chemokine ligand2; CD, cluster of differentiation; COL5A2, collagen type V alpha 2 chain; CXCR5, C-X-C chemokine receptor type 5; DCN, decorin; FBN1, fibrillin 1; GJA1, gap junction alpha-1 protein; ITGAX, integrin subunit alpha X; ITGA1, integrin subunit alpha 1; LAMA2, laminin subunit alpha 2; LAMA3, laminin subunit alpha 3; LAMB1, laminin subunit beta 2; LAMC1, laminin subunit gamma 1; LOX, lysyl oxidase; MS4A1, membrane spanning 4-domains A1; NT5E, 5'-nucleotidase ecto; PAX5, paired box 5; SELL, selectin L; TAGLN, transgelin; TJP1, tight junction protein 1; TNFSF13B; TNF superfamily member 13b, NID, Nidogen 1. cancers-15-01527-t001_Table 1 Table 1 Patient demographics: The median follow-up time was 32.2 months (range: 6.28-203 months). 6 duplicated patient samples were removed. Diagnostic Samples, n (%) Follow-up Samples, n (%) All Samples, n (%) Number of cases 21 19 40 Male 16/21 (76%) 12/19 (63%) 28/40 (70%) Age 60 years or older 16/21 (76%) 11/19 (58%) 27/40 (68%) (median 63 years, range 19-86) Stage I-IIA 16/21 (76%) 13/19 (68%) 29/40 (73%) Stage IIB-IV 5/21 (24%) 6/19 (32%) 11/40 (28%) Elevated LDH 7/21 (33%) 7/19 (37%) 14/40 (35%) Presenting lesions Solitary 1/21 (5%) 0/19 (0%) 1/40 (3%) Multiple 16/21 (76%) 15/19 (79%) 31/40 (78%) Erythrodermic 4/21 (19%) 4/19 (21%) 8/40 (20%) LDH, Lactate dehydrogenase. 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. |
PMC10000434 | As a practical local therapeutic approach to destroy tumor tissue, thermal ablation can activate tumor-specific T cells via enhancing tumor antigen presentation to the immune system. In the present study, we investigated changes in infiltrating immune cells in tumor tissues from the non-radiofrequency ablation (RFA) side by analyzing single-cell RNA sequencing (scRNA-seq) data of tumor-bearing mice compared with control tumors. We showed that ablation treatment could increase the proportion of CD8+T cells and the interaction between macrophages and T cells was altered. Another thermal ablation treatment, microwave ablation (MWA), increased the enrichment of signaling pathways for chemotaxis and chemokine response and was associated with the chemokine CXCL10. In addition, the immune checkpoint PD-1 was especially up-regulated in the infiltrating T cells of tumors on the non-ablation side after thermal ablation treatment. Combination therapy of ablation and PD-1 blockade had a synergistic anti-tumor effect. Furthermore, we found that the CXCL10/CXCR3 axis contributed to the therapeutic efficacy of ablation combined with anti-PD-1 therapy, and activation of the CXCL10/CXCR3 signaling pathway might improve the synergistic effect of this combination treatment against solid tumors. thermal ablation microwave ablation CXCL10 tumor microenvironment cancer immunotherapy National Natural Science Foundation of China81972869 82172689 81902386 Key R&D Project of Jiangsu ProvinceBE2022721 BE2022719 Natural Science Foundation of Jiangsu ProvinceBK20211065 China Postdoctoral Science Foundation2021M700543 2021M700547 High-Level Talents Project of Jiangsu Commission of HealthLGY2020034 Key R&D Project of ChangzhouCE20215030 Applied Basic Research Foundation of ChangzhouCJ20210089 Changzhou International Cooperation ProjectCZ2021005 State Key laboratory of Pharmaceutical Biotechnology, Nanjing University, ChinaNo. KF202203 Funding was received from the National Natural Science Foundation of China (No. 81972869, No. 82172689 and No. 81902386), the Key R&D Project of Jiangsu Province (No. BE2022721 and No. BE2022719), the Natural Science Foundation of Jiangsu Province (No. BK20211065), the China Postdoctoral Science Foundation (No. 2021M700543, No. 2021M700547), the High-Level Talents Project of Jiangsu Commission of Health (No. LGY2020034), the Key R&D Project of Changzhou (No. CE20215030), the Applied Basic Research Foundation of Changzhou (No. CJ20210089), the Changzhou International Cooperation Project (No. CZ2021005), and the open fund of the State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, China (No. KF202203). pmc1. Introduction Thermal ablation mainly uses the heat generated by radiofrequencies, microwaves, or lasers to cause coagulative necrosis of local tumors. It has been considered a necessary minimally invasive treatment for certain solid tumors . Moreover, thermal ablation is widely accepted as an important form of tumor immunotherapy . After tumor ablation, it can cause local coagulation and necrosis, and tumor antigens are released, stimulating T-cell-mediated anti-tumor immune responses . Our previous study has demonstrated that radiofrequency ablation (RFA) synergizes with PD-1 blockade-based cancer immunotherapy, illustrating the great potential of thermal-ablation-based cancer immunotherapy . Increasing the numbers of tumor-infiltrating T lymphocytes in tumor tissues is an essential step to improve the efficacy of immunotherapy against solid tumors . RFA, as well as microwave ablation (MWA), has been confirmed as the most widely used thermal ablation modality in the treatment of solid tumors, including primary liver cancer, colorectal cancer (CRC), liver metastasis, and kidney cancer . In addition, many studies have demonstrated that thermal ablation can affect the microenvironment of solid tumors and promote the infiltration of T lymphocytes into tumor tissues . However, the immune response induced by ablation is insufficient to prevent the tumor from recurring. The intensity of the anti-tumor immune response after ablation cannot be maintained or even rapidly weakened, which may be a fundamental reason limiting the efficacy of tumor-ablation treatment . Immune checkpoint blockade (ICB) therapy destroys harmful immunomodulatory molecules and releases pre-existing anti-tumor immune effects by therapeutic antibodies . Antibodies against checkpoint molecules have been successfully applied in clinical practice, such as CTLA-4, PD-1, and PD-L1 . Contrarily, ICB-based cancer immunotherapy significantly extends the life span of patients with responsive cancers. In contrast, ICB therapy does not benefit a sizable portion of patients with non-responsive cancers . Therefore, it is necessary to explore novel strategies to improve ICB efficacy against solid tumors. Chemokines are cytokines or signal proteins secreted by immune cells, stromal cells, and epithelial cells that can regulate the homing and retention of immune cells in inflamed tissues . The CXC chemokine superfamily member CXC-chemokine ligand 10 (CXCL10), also called interferon-g-inducible protein (IP-10), interacts with the CXC-chemokine receptor 3 (CXCR3) to regulate the immune response, angiogenesis, apoptosis, and proliferation . CXCL10 can be up-regulated by IFN-a, IFN-b, IFN-g, or LPS in various cells, including endothelial cells, fibroblasts, monocytes, and neutrophils. In addition to inducing effector Th1 cells, CXCL10 can also recruit CXCR3+CD8+T cells to the tumor site and promote these cells to produce Granzyme B, which enhances the anti-tumor effect . In the present study, we investigated the role of CXCL10 in thermal-ablation-based tumor immunotherapy by analyzing scRNA-seq data of CD45+ immune cells in tumors from the non-thermal-ablation side of Panc02 tumor-bearing mice from a published database . We found that the interaction between macrophages and effector CD8+T cells through the CXCL10/CXCR3 pathway in the tumor microenvironment (TME) of the non-ablation zone was required. We then constructed the tumor model by symmetrically injecting the MC38 cells subcutaneously into the bilateral flanks of wild-type and CXCL10 knockout mice according to our previous study. Moreover, we investigated the role of CXCL10 in MWA therapy, ICB therapy, or MWA combined with ICB for liver metastasis of intestinal cancer. Our present study provided valuable insights into the mechanism of thermal-ablation-based tumor immunotherapy and demonstrated that CXCL10 promoted CTLs to migrate into tumor tissues to enhance the synergistic anti-tumor effect of thermal ablation in combination with ICB. Therefore, augmenting the intra-tumoral function of the CXCL10/CXCR3 axis could improve clinical therapeutic efficacy. 2. Materials and Methods 2.1. Cell Lines and Animals The murine colon cancer cell line MC38 was obtained from the Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. MC38 cells were maintained in DMEM (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 100 mg/mL streptomycin, 100 U/mL penicillin, and 10% (v/v) fetal bovine serum (FBS, Gibco, Thermo Fisher Scientific, Waltham, MA, USA). Cells were cultured for less than 2 weeks before injection into mice. Wild-type C57BL/6 mice and Cxcl10 knockout mice (Cxcl10-/-, C57BL/6 background, male, 6-8 weeks old) were obtained from the Model Animal Research Institute of Nanjing University (Jiangsu, China). Animals were housed at the specific pathogen-free (SPF) facility of Cavens Laboratory Animals (Changzhou, Jiangsu, China). All animal experiments were approved by the Ethics Committee of the Third Affiliated Hospital of Soochow University. 2.2. Tumor Model, MWA Treatment, and Anti-PD-1 Therapy Briefly, 2 x 106 MC38 cells were subcutaneously injected into the symmetrical bilateral back of male C57BL/6 and Cxcl10-/- mice, and MWA was performed on the right tumor when the tumor volume reached approximately 300 mm3. The operation was conducted as reported in our previous study . The ablation needle (Microwave Ablation Antennas, Canyon Medical Inc., Jiangsu Nanjing, China) was inserted percutaneously perpendicular to the center of the tumor with a 1 cm tip. The target temperature was 70 degC, the output power was 10W, and the ablation was performed for 3-5 min to completely ablate the tumor. Then the anti-PD-1 (Clone: J43, BioXcell, Lebanon, NH, USA) therapy was performed on the 2nd day after ablation by intraperitoneally (i.p.) injecting 200 mg antibodies every 3 days four times. Mouse IgG2b (BE0086, BioXcell) was used as a control. Tumor growth was monitored every 2 days after tumor inoculation or MWA treatment. The formula for calculating tumor volume was as follows: Volume = (p x long axis x short axis2)/6. 2.3. Flow Cytometry Tumors were collected from mice, cut into pieces smaller than 1 mm3, and digested with Liberase TL (0.25 mg/mL, REF 05401020001, Roche) and DNase I (0.33 mg/mL, REF 10104159001, Roche) at 37 degC for 30 min. Subsequently, digestion was terminated by the addition of a serum-containing medium, and the pieces were ground and filtered through a 200-mm filter to obtain a single-cell suspension. Anti-mouse antibodies were used to stain cells, including antibodies against CD45 (Clone 30-F11), Ghost (Cell Signaling Technology, Danvers, MA, USA), CD3 (Clone 17A2), CD4 (Clone GK1.5), CD8 (Clone 53-6.7), Foxp3 (Clone FJK-16S), and PD-1 (Clone RPM1-30). For the measurement of intracellular cytokine levels, the cells were stimulated with a cell-activation cocktail (with brefeldin A, BioLegend, San Diego, CA, USA) at 37 degC for 6 h. After stimulation, the cells were stained with antibodies against surface markers, fixed, and permeabilized according to the manufacturer's instructions provided by the Invitrogen Fixing/Permeabilization Solution kit. The fixed cells were stained using antibodies against IFN-g (Clone XMG1.2). Data were acquired using a BD FACS Aria II flow cytometer and were analyzed using FlowJo software. 2.4. Isolation of Tumor-Infiltrating CD8+T Cells Briefly, 2 x 106 MC38 cells were subcutaneously injected into the symmetrical bilateral back of male C57BL/6 mice. MWA was performed only on the right flank tumors as mentioned above. After 3 days of MWA treatment, target cells were enriched using CD8a microbeads (Miltenyi) and flow-sorted using FACS Aria II. Total RNA was prepared and subjected to RNA sequencing (Shanghai OE Biotech, Shanghai, China). 2.5. Analysis of RNA-Seq Data Magnetic-bead-enriched and flow-sorted CD8+T cells were subjected to mRNA isolation, fragmentation, reverse transcription, and cDNA amplification. These data were analyzed for differential expression by comparing cDNA libraries. Differences between the two groups of samples were assessed using GO term enrichment analysis or gene set enrichment analysis (GSEA) software. 2.6. Analysis of scRNA-Seq Data Sra files were downloaded from the NCBI website. The scRNA-seq data were derived from infiltrating CD45+ immune cells established by Fei et al. . Then fastq-dump was used to transfer all sra files into FASTQ files. Next, FASTQ files were processed with cellranger software (Version 4.0.0), which aligned samples to the mm10 genome, followed by filtration and qualification. Finally, cellranger was used to aggregate the data for each sample, and after normalization, the data were merged into one. Seurat was used to analyze the combined data. Doublets were filtered with DoubletFinder (Version 2.0.3), and cells with less than 400 or more than 5500 gene counts, more than 5% mitochondrial contamination, more than 40% ribosome contamination, or more than 25,000 RNA counts were filtered out, leaving 26,084 cells for downstream analysis. Data were normalized and scaled, principal component analysis (PCA) was performed, and neighbors were found using 50 dimensions. PCA was performed on ~3000 genes with the PCA function. The batch effect was removed with harmony (Version 0.1.0). The scaled matrix was subjected to dimensional reduction based on the first 20 PCA components, allowing the cell state to be represented in two dimensions. The main cell clusters were identified with the FindClusters function. Every cell was classified into a known biological cell type using conventional markers. 2.7. Differential Gene Expression Analysis The edgeR package (version 3.28.1) was used to select differentially expressed genes (DEGs) between samples. The raw data obtained from the Seurat object were normalized using TMM (trimmed mean of M-values) with the calcNormFactors function, and the dispersion of gene expression values was estimated with the estimateDisp function. Then, DEGs were selected for the following analysis. 2.8. Gene Set Enrichment Analysis Gene set enrichment analysis was performed using the GSEA software (Version 4.1.0). The gene sets we used were derived via MSigDB gene sets. Difference analyses of pathway activities scored per cell between clusters were performed with wilcox.test. 2.9. GO Enrichment Analysis Differentially expressed genes calculated with the edgeR package were selected for GO analysis with the clusterProfiler R package (Version 3.14.3). The Barplot function was used to visualize the data. 2.10. Statistical Analysis GraphPad Prism V.8 and R software were used in the statistical analyses. The data were presented as mean +- SEM. Two-tailed unpaired Student's t-tests were used for comparisons between two groups, and the ANOVA was used for multiple comparisons. The log-rank test was used to analyze and calculate the survival of mice. p < 0.05 was considered statistically significant. 3. Results 3.1. scRNA-Seq Identifies Tumor-Infiltrating Immune Cells We used scRNA-seq data to investigate population changes in infiltrating immune cells in the TME on the distant non-ablation side after thermal ablation treatment. Overall, scRNA-seq data from 26,084 cells were obtained after quality control , including 14,837 cells from the control group and 11,247 cells from the RFA treatment group. We essentially adopted the cell annotations used in the previous study , and all cells were assigned to five clusters, including T cells, macrophages, dendritic cells (DCs), neutrophils, and mast cells . Based on the database, we found that thermal ablation treatment increased the proportion of neutrophils and decreased the proportion of DCs and mast cells in the TME on the distant non-ablation side, while the proportion of T cells and macrophages did not change significantly . Therefore, this finding supported the notion that thermal ablation could induce the remodeling of immune cell subsets in the TME. 3.2. Ablation Therapy Affects the Interaction of Tumor-Infiltrating Immune Cell Subsets As a subpopulation of T cells, CD8+TILs exert a major anti-tumor effect. We analyzed the RNA-seq data of CD8+TILs on the non-ablation-side tumor with flow sorting. Statistical analysis of DEGs was performed for the control and MWA groups. As shown in Figure 2A, CD8+TILs in the MWA treatment group were associated with chemotaxis and response to chemokine signatures. Similarly, GO enrichment analysis revealed that cells from the MWA treatment group expressed the transcriptional profile consistent with T cell activation, including leukocyte activation, chemotaxis, and cell adhesion . Therefore, we speculated that thermal ablation therapy could enhance the anti-tumor effect by promoting lymphocyte infiltration into tumor tissue through chemotaxis. The scRNA-seq data of the Panc02 tumor-bearing mouse model were analyzed for the strength of the interactions between the immune cell subsets after thermal ablation treatment. We found that macrophages interacted most strongly with other cell type subpopulations, especially with T cells . To infer the interactions of molecules that mediate the cell-cell interactions in the chemokine system, we calculated the strength of ligand-receptor pairs using the CellphoneDB2 method, which shows the cell population specificity of interaction pairs . Since the response to the chemokine signature was enriched in cells from the ablation treatment group, we collected data on interaction pairs, including chemokine families, and identified multiple interaction pairs that were specific to cell populations. Among them, CXCL10/CXCR3 and CCL2/CCR2 were mainly present between macrophage and T cell interactions . However, RFA treatment increased the CCL2 expression and decreased the CCR2 expression, which seemed to be somewhat difficult to explain. In contrast, the expressions of CXCL10 and its receptor CXCR3 were both increased in lymphocyte subpopulations after thermal ablation treatment . Consistent with the existing literature , macrophages and neutrophils were the primary sources of CXCL10, and CXCR3 was widely expressed in T cells . These data indicate that the CXCL10/CXCR3 axis was involved in the anti-tumor immune response induced by thermal ablation. 3.3. Ablation-Induced Remodeling of TILs in the TME We found that the interaction between macrophages and T cells was the closest among tumor-infiltrating immune cells. We isolated the T cells (n = 3522) and macrophages (n = 10,013) from the other immune cells and performed unbiased cluster classification of cell types using the Seurat package. T cell subsets were divided into seven distinct cell clusters based on the ImmGen database and known cell type markers . Thermal ablation treatment decreased the proportions of ILC, Th, Treg, and cycling CD8+T cell clusters compared with the controls and increased the proportion of effector CD8+T cells . Ablation enhanced the activation of CD8+T cells, especially cytotoxic CD8+T cells, and promoted the accumulation of functional CD8+T cells to enhance anti-tumor immunity. Moreover, we analyzed the macrophage subpopulations in the tumor-infiltrating immune cells based on the cell annotations used in a published study . Tumor-associated-macrophage 1 (TAM1) cells were rich in factors that regulate angiogenesis, such as Spp1, Marco, and Vegfa, while TAM2 cells expressed genes involved in antigen presentation and phagocytosis (C1qc, Trem2, Mertk, and Cd80) . Furthermore, ablation treatment decreased the proportion of TAM2 cells, while the proportion of TAM1 cells was increased . Moreover, a higher percentage of cells in the ablation group occupied the TAM1 cluster . Therefore, these were the main interactions between the TAM1 cell subset and T cells after thermal ablation treatment. To explore the potential mechanism of increased lymphocyte enrichment in TME after thermal ablation treatment, we compared the transcriptomic differences in CD8+T cells between control and ablation-treated groups for scRNA-seq data. NicheNet was used to analyze the highly expressed genes in CD8+T cells in the ablation treatment group . We noticed that Cxcl10, which is highly expressed by TAMs, was predicted to be a potential ligand and drive the CD8+T cell effector phenotype in the ablation treatment group . In addition, among the target genes predicting the phenotype of CD8+T cells in the ablation treatment group, Cxcl10 was one of the prioritized ligands . It was further proved that CXCR3-induced migration of effector T cells into tumors and CXCL10 production by macrophages were critical for the recruitment of CXCR3-dependent T cells into tumors . 3.4. CXCL10/CXCR3 Contributes Essentially to Thermal-Ablation-Induced Anti-Tumor Effect Next, we analyzed the expressions of chemokine-family genes in T cell and macrophage subpopulations both before and after thermal ablation treatment. The expressions of Cxcl10 and Cxcr3 were increased after ablation treatment . In addition, Cxcr3 was essentially expressed in Th, Treg, and naive CD8 clusters in the control group, whereas the expression of Cxcr3 was specifically increased in cycling CD8 and effector CD8 clusters in the ablation therapy group . Therefore, ablation treatment might maintain the expression of Cxcr3 in effector CD8+ T cells. Furthermore, Cxcl10 was expressed mainly in the TAM1 cluster in the control group and in both TAM1 and TAM2 clusters in the ablation-treated group . Cxcr3 is highly expressed in activated T cells and regulates migration behavior and effector function . Therefore, we proposed a scientific hypothesis that thermal ablation treatment could induce TAM1 to express CXCL10, leading to the recruitment of CXCR3+CD8+T cells into the tumor site and enhancement of anti-tumor immunity. To investigate the function of the CD8+T cell subgroup after thermal ablation treatment, we performed GSEA enrichment analysis on the DEGs of CD8+T cells in the control and ablation groups. The result revealed that CD8+T cells from the ablation group were associated with interferon-alpha/gamma and oxidative phosphorylation, while TNFA signaling via NF-kB, the P53 pathway, and glycolysis were enriched in the control group . We speculated that thermal ablation treatment induced the expression of CXCL10, stimulated interferon secretion, and recruited CXCR3-expressing CD8+T cells to the TME, thus exerting an effector function. Next, we inoculated MC38 tumor cells bilaterally on the back of C57BL/6 and Cxcl10-/- mice and treated one side of the tumor with MWA . Tumor growth on the non-ablation side was monitored. We observed a slight delay in contralateral tumor growth after MWA treatment . In contrast, in Cxcl10-/- mice, the inhibition of tumor growth by MWA was diminished and the overall survival rate was much lower than that of wild-type mice . 3.5. CXCL10 Is Required for Effective Response to PD-1 Blockade Therapy To explore the role of CXCL10 in the efficacy of anti-PD-1 therapy, we subcutaneously inoculated MC38 cells in wild-type and Cxcl10-/- mice treated with anti-PD-1 or IgG control antibodies . The anti-PD-1 treatment could significantly inhibit MC38 tumor growth in wild-type mice, while tumor growth inhibition after anti-PD-1 treatment in Cxcl10-/- mice was not as good as in the wild-type mice . This result demonstrated that CXCL10 played an important role in the anti-PD-1 strategy against MC38 tumors. We further speculated that the reduced efficacy of anti-PD-1 treatment in Cxcl10-/- mice might be related to the reduction in CD8+T cells in tumor tissues. The multi-color flow cytometry analysis found that anti-PD-1 treatment increased the ratio of infiltrating CD45+ immune cells and CD8+T cells in tumors compared with controls from wild-type mice, and there was an increasing trend in the proportion of CD4+T cells and Treg cells . Compared with wild-type mice, the proportion of =CD8+T cells in the control and anti-PD-1 treatment groups of Cxcl10-/- mice was noticeably reduced, and the proportions of CD4+T cells and Treg cells had a decreasing trend . We next showed that the frequency of IFN-g+CD8+TILs cells was similar in wild-type and Cxcl10-/- mice in the control group. However, a significant increase in IFN-g+CD8+TILs upon anti-PD-1 treatment was found in wild-type mice compared with Cxcl10-/- mice . These data suggest that the chemokine CXCL10 was associated with promoting the CD8+T-cell-mediated anti-tumor effects upon anti-PD-1 treatment. 3.6. CXCL10 Enhances the Synergistic Anti-Tumor Effect of Thermal Ablation Combined with PD-1 Blockade Consistent with published reports , scRNA-seq data analysis showed increased immune checkpoint PD-1 expression in tumor-infiltrating T cells in distal non-ablated tumors after the ablation treatment . The MC38 tumor-bearing mouse model also confirmed that PD-1 expression was up-regulated in CD4+ and CD8+T cells in the non-ablated tumors after MWA treatment . Combination therapy of ablation and anti-PD-1 significantly enhanced T cell anti-tumor immunity and prolonged the survival of tumor-bearing mice . Next, we studied the role of CXCL10 in the combination therapy of MWA and anti-PD-1 . We found that the MWA plus anti-PD-1 treatment had a better synergistic anti-tumor effect in MC38-bearing wild-type mice compared with Cxcl10-/- mice . To better explore the synergistic anti-tumor immune responses of combined ablation and anti-PD-1 therapy, we investigated the T cell response after MWA and MWA plus anti-PD-1. On day 12 after ablation in wild-type mice, the frequency of tumor-infiltrating CD45+ and CD8+T cells was higher in the combination treatment group than in the MWA group . Moreover, the proportions of CD45+, CD4+, and CD8+T cells within tumors in Cxcl10-/- mice were reduced after combination treatment compared with wild-type mice, especially CD8+T cells . Notably, the proportion of IFN-g+CD8+TILs in the combination treatment group was increased compared with the MWA group . Meanwhile, the proportion of IFN-g+CD8+TILs was reduced in Cxcl10-/- mice compared with wild-type mice in the MWA group and the combination treatment group . The combination therapy of MWA and anti-PD-1 in Cxcl10-/- mice was less effective than in wild-type mice. These data further support that the anti-PD-1 therapy enhanced MWA-induced anti-tumor effects based on adaptive CD8+T cell immune responses, and the chemokine CXCL10 contributed to the synergistic effect of ablation plus anti-PD-1 treatment. 4. Discussion As a widely used strategy of minimally invasive treatment, thermal ablation can destroy tumor tissues, improve the immune recognition of tumor antigens, activate the effective and specific anti-tumor immunity, and especially play an essential role in the initiation of the T-cell-mediated anti-tumor response . We have previously demonstrated that in the early-stage CT26-bearing tumor model after RFA, the percentages of the total infiltrating CD8+T cells, or the percentages of IFN- TNF-a-expressing CD8+T cells in the tumor tissues, are significantly increased in contrast to the non-ablated groups . These results lead to further considerations about the potential mechanism of how these functional CD8+T cells infiltrate into the tumor tissues upon RFA treatment. In our present study, as shown in Figure 2C, based on the scRNA-seq data analysis, Cxcl10 expressed on myeloid cells and Cxcr3 expressed on T cells were markedly up-regulated after thermal ablation treatment. Therefore, the CXCL10/CXCR3 axis was indispensable in RFA-triggered anti-tumor immunity. The chemokine CXCL10 interacts with its receptor CXCR3, and the CXCL10/CXCR3 pathway is well-known to contribute to the migration, differentiation, and activation of many immune cells. It induces an immune response by recruiting immune cells, such as CTLs, natural killer (NK) cells, and macrophages . In addition, it can also regulate the polarization of Th1 cells and activate immune cells in response to IFN-g . Therefore, we assumed that the mechanism of ablation treatment enhancing anti-tumor immune response was regulated by the CXCL10/CXCR3 axis. In addition, we also found that the expression of CXCR3 in cytotoxic CD8+T cells was significantly up-regulated after RFA. It is well known that the involvement of myeloid cells is required to modulate the T-cell-mediated immune response . Based on the results from the intercellular receptor interaction study, we found that the macrophages and T cells might interact through the CXCL10/CXCR3 axis. Further analysis of macrophage subsets showed that the expression of Cxcl10 in TAM subsets was significantly up-regulated after thermal ablation. Therefore, ablation might promote the recruitment of cytotoxic CD8+T cells to infiltrate tumor tissues by up-regulating TAM1 to secrete CXCL10. However, how ablation treatment induces TAM1 to up-regulate CXCL10 in distant non-ablated tumors remains to be further investigated. Moreover, the local inflammation and tumor antigen release induced by ablation can also recruit antigen-presenting cells, including DCs and macrophages, which will prime and activate T cells . However, in the absence of CXCR3 on T cells, DCs could not effectively interact with T cells and then impair the transformation of memory T cells into effector T cells . After ablation treatment, CD8+T cells were enriched with interferon-related pathways. Chemokine CXCL10, as an interferon-inducible protein, is most likely involved in the thermal-ablation-induced expression of CXCL10 by TAM1, which stimulates interferon secretion and recruits CXCR3+CD8+T cells to infiltrate into tumor tissues, thus exerting anti-tumor effects. This is only our speculation at present, and we will follow up with this as a focus for an in-depth study. Although ICB therapy has made a great breakthrough in the treatment of advanced cancers, there still remains a low response rate in many solid tumors to maintain long-term anti-tumor immunity . Previous studies have shown that PD-1 blockade treatment can enhance the T-cell-mediated anti-tumor response and also increase the levels of IFN-g and CXCL10 in the TME . In our present study, we found that the reduction in tumor progression by anti-PD-1 treatment in MC38 tumor models was dependent on CXCL10. We also found that in the MC38 tumors from Cxcl10 knockout mice, the activation of CD8+T cells was significantly inhibited, in contrast to the wild-type mice upon anti-PD-1 treatment. Our results were consistent with the notion that the anti-tumor immune response elicited by ICB requires the involvement of macrophage-derived CXCL9 and CXCL10 . We have previously confirmed that the tumor-infiltrating T cells expressing PD-1 are significantly increased in the late stage after thermal ablation in contrast to the non-ablated group . This may be an important reason for limiting the inability to maintain the efficacy of thermal ablation treatment. When we carried out the combined treatment of MWA and anti-PD-1, both the numbers and function of the tumor-infiltrating CD8+T cells were obviously increased, in contrast to the MWA group, anti-PD-1 group, and control group . A phase I clinical trial has also confirmed that the combined strategy of RFA and anti-CTLA-4 treatments against human hepatocellular carcinoma can present a synergistic anti-tumor effect and an increasing number of CD8+TILs . MWA has been verified to induce a robust immune response, but also could up-regulate the expression of immunosuppressive molecules. We have recently reported that the IFN, CCL, and CXCL pathways were significantly enriched in the MWA plus immune checkpoint inhibitor combination therapy compared with the MWA therapy alone . The addition of TIGIT blockade to MWA resulted in the up-regulation of CXCL9 and CXCL10 expression in TAMs and their receptor CXCR3 expression in T cells, which restrain tumor growth and enhance anti-tumor immunity . The interactions among the CXCL pathway and IFN pathway were stronger after combination treatment with MWA and LAG3 blockade, and the expression of specific genes in their pathways were also up-regulated . In our current study, we further demonstrated that the chemokine CXCL10 was involved in the synergistic anti-tumor effect induced by the combination therapy of MWA and anti-PD-1. In the combination of MWA and anti-PD-1 treatment, Cxcl10 knockout mice had fewer CD8+TILs and IFN-g+CD8+T cells than wild-type mice. Therefore, CXCL10 could regulate the synergistic effect of the combination treatment of thermal ablation with anti-PD-1, and the detailed mechanism merits further investigation. 5. Conclusions Taken together, our current work revealed that thermal ablation treatment increased the proportion of CD8+T cells in the TME in distant non-thermally-ablated areas, enhanced the interaction between macrophages and T cells, and increased the expressions of chemokine CXCL10 and its receptor CXCR3. In addition, CXCL10 played an essential role in mediating the anti-tumor effect of anti-PD-1 treatment and also contributed essentially to the synergistic anti-tumor effects of thermal ablation and anti-PD-1 treatment. It could be an important intervention targeting the CXCL10/CXCR3 signaling pathway to improve the synergistic effect of this combined treatment against solid tumors. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Immune cells on the non-RFA side of the PDAC mouse model. (A,B). scRNA-seq data from 26,084 cells were obtained before (A) and after (B) batch removal. Click here for additional data file. Author Contributions Conceived the project: J.J. and L.C.; Supervised the research, performed the biological interpretation of data: J.J., L.C. and X.Z.; Performed the bioinformatics, computational analysis, and statistical analysis: H.H. and W.X.; Performed the tumor model and animal experiments: W.X., H.H., Y.C. and J.C.; Carried out the flow cytometry analysis and flow-sorting experiments: W.X., P.Z. and Y.L.; Carried out the cell culture: W.X., P.Z. and J.C.; Manuscript writing: J.J., L.C., W.X. and H.H.; Final approval of manuscript: All authors. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Institutional Ethics Committee of the Third Affiliated Hospital of Soochow University (No. 2020-208). All animal experiments conformed to the internationally accepted principles for the care and use of laboratory animals. Informed Consent Statement Not applicable. Data Availability Statement All data generated or analyzed during this study are included in the published article. Conflicts of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential competing interests. Figure 1 scRNA-seq identifies the changes in tumor-infiltrating immune cells. (A). UMAP plot showing CD45+ immune cells colored by computationally determined clusters based on scRNA-seq data in the Panc02 tumor-bearing mouse model (above). The frequencies of cell composition in the tumor-infiltrating CD45+ immune cells with the control group (not subjected to ablation, n = 14,837) and ablation group (n = 11,247) (below). (B). Dotplot showing the top 10 marker genes across five different CD45+ immune cell subgroups. (C). Percentages of cells in the control group and ablation group among the different cell subgroups of CD45+ immune cells. Figure 2 Enrichment analysis of DEGs in CD8+TILs after MWA treatment. (A). GSEA analysis showing the top enriched chemotaxis and chemokine-mediated signal transduction regulatory pathways in CD8+TILs of the MWA treatment group. (B). GO enrichment analysis of up-regulated genes in CD8+TILs of the MWA treatment group. Figure 3 CXCL10-CXCR3 plays a vital role in ablation-induced cell-cell interactions. (A). Heatmap showing the cell-cell communication among immune cell populations between subgroups of CD45+ immune cells predicted by CellphoneDB2. (B). Dotplot showing the expression intensity of selected ligand-receptor pairs among the different cell subgroups of CD45+ immune cells. Sizes of dots represent the p-value, and colors of dots represent the strength interaction between two subpopulations. (C). Dotplot showing the expression levels of chemokines and its receptors across cell types in the control and ablation treatment groups. (D). UMAP plot showing expressions of chemokine Cxcl10 and its receptor Cxcr3 in two groups. Figure 4 Ablation leads to the remodeling of tumor-infiltrating CD45+ immune cell subsets. (A). UMAP plot showing sub-clusters of T cells based on scRNA-seq data in the Panc02 tumor-bearing mouse model (left). The frequency of cell composition in the T cells of the control group (n = 2042) and ablation group (n = 1480) (right). (B). Heatmap displaying marker genes expressed in different subpopulations of TILs. (C). UMAP plot showing sub-clusters of macrophages colored by computationally determined clusters (left). The frequency of cell composition in the macrophages of the control group (n = 5860) and RFA group (n = 4153) (right). (D). Heatmaps showing potential ligands from macrophages interacting with receptors expressed on CD8+T cells on the non-ablation side in the ablation group. (E). Heatmaps showing that potential ligands from macrophages might influence the gene expression in CD8+T cells of the RFA group. Figure 5 CXCL10 contributes essentially to thermal-ablation-induced anti-tumor effects. (A). Normalized expression of the chemokine receptor Cxcr3 gene in T cell sub-clusters shown by the violin plot. (B). Normalized expression of the chemokine Cxcl10 gene in macrophage sub-clusters shown by the violin plot. (C). GSEA analysis showing top-down enriched IFN-a/g response and oxidative phosphorylation in the MWA group (left). GSEA analysis showing top-down enriched TNFA signaling via NF-kB, P53 pathway, and glycolysis in the RFA group (right). NES denotes normalized enrichment score. (D). Schematic diagram of the protocol for MWA treatment of tumor-bearing mice. C57BL/6 and Cxcl10-/- mice were bilaterally inoculated with MC38 cells on the back to construct tumor-bearing mouse models, and one side of the tumor was treated with MWA. (E). Tumor burden in C57BL/6 and Cxcl10-/- mice treated with MWA (n = 6). (F). Mouse survival after treatment with MWA in C57BL/6 and Cxcl10-/- mice (n = 8). Data are presented as the mean +- SEM. * p < 0.05, ** p < 0.01, and *** p < 0.001 according to the one-way ANOVA test and the log-rank test. Figure 6 CXCL10 deletion dampens PD-1 blockade efficacy. (A). Schematic diagram of the protocol for the anti-PD-1 treatment of tumor-bearing mice. C57BL/6 and Cxcl10-/- mice were subcutaneously inoculated with 2 x 106 MC38 tumor cells, then injected i.p. with 200 mg of anti-PD-1 antibody or isotype control antibody on days 4, 7, 10, and 13 after tumor cell inoculation. Tumor growth was monitored until the experimental endpoints. (B). Tumor growth in C57BL/6 and Cxcl10-/- mice treated with control or anti-PD-1 antibody. Six mice were in each group. (C). Flow cytometry analysis followed by quantification of CD45+ cells, CD4+TILs, CD8+TILs, and Foxp3+Treg within tumors of C57BL/6 and Cxcl10-/- mice treated with control or anti-PD-1 antibodies (n = 6). (D). Representative flow cytometry plots and quantitation of the percentages of IFN-g expression in CD8+TILs (n = 6). Data are presented as the mean +- SEM. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001 according to the one-way ANOVA test and the log-rank test. Figure 7 CXCL10 contributes to the synergy of MWA and PD-1 blockade. (A). Normalized expression of Pdcd1 gene in the lymphocyte subsets shown by the violin plot. (B). The percentage of PD-1 in CD4+TILs and CD8+TILs on day 12 of MWA in the MC38 tumor-bearing mouse model dosed with control or MWA treatment. (C). Schematic drawing of the study. C57BL/6 and Cxcl10-/- mice were bilaterally inoculated with MC38 cells on the back to construct tumor-bearing mouse models, and one side of the tumor was treated with MWA. Mice were injected i.p. with isotype control or anti-PD-1 antibody on day 1 after MWA and then every 3 days four times. (D). The size of the tumors on the non-MWA area tumor was recorded every 2 days after MWA. Five mice were in each group. (E). Flow cytometric analysis of the percentages of CD45+ tumor-infiltrating cells, CD4+TILs, and CD8+TILs of C57BL/6 and Cxcl10-/- mice treated with control or MWA treatment (n = 4). (F). Representative flow cytometry plots and quantitation of the percentage of IFN-g expression in CD8+TILs (n = 4). Data are represented as the mean +- SEM. * p < 0.05 and ** p < 0.01 according to the one-way ANOVA test and the log-rank test. 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. |
PMC10000435 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051063 foods-12-01063 Article Design of Lactococcus lactis Strains Producing Garvicin A and/or Garvicin Q, Either Alone or Together with Nisin A or Nisin Z and High Antimicrobial Activity against Lactococcus garvieae Feito Javier Methodology Validation Formal analysis Investigation Writing - original draft Project administration 1 Araujo Carlos Methodology Validation Investigation 1 Arbulu Sara Methodology Validation Investigation 1 Contente Diogo Validation 1 Gomez-Sala Beatriz Validation 23 Diaz-Formoso Lara Formal analysis 1 Munoz-Atienza Estefania Methodology Formal analysis 1 Borrero Juan Methodology Formal analysis 1 Cintas Luis M. Conceptualization Project administration Funding acquisition 1 Hernandez Pablo E. Conceptualization Project administration Funding acquisition 1* Medina Luis M. Academic Editor Perez-Rodriguez Fernando Academic Editor 1 Grupo de Seguridad y Calidad de los Alimentos por Bacterias Lacticas, Bacteriocinas y Probioticos (Grupo SEGABALBP), Seccion Departamental de Nutricion y Ciencia de los Alimentos (Higiene y Seguridad Alimentaria), Facultad de Veterinaria, Universidad Complutense de Madrid, Avda. Puerta de Hierro, s/n., 28040 Madrid, Spain 2 APC Microbiome Ireland, University College Cork, T12 K8AF Cork, Ireland 3 Teagasc Food Research Centre, Moorepark, P61 C996 Cork, Ireland * Correspondence: [email protected] 02 3 2023 3 2023 12 5 106302 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 ). Lactococcus garvieae is a main ichthyopathogen in rainbow trout (Oncorhynchus mykiss, Walbaum) farming, although bacteriocinogenic L. garvieae with antimicrobial activity against virulent strains of this species have also been identified. Some of the bacteriocins characterized, such as garvicin A (GarA) and garvicin Q (GarQ), may show potential for the control of the virulent L. garvieae in food, feed and other biotechnological applications. In this study, we report on the design of Lactococcus lactis strains that produce the bacteriocins GarA and/or GarQ, either alone or together with nisin A (NisA) or nisin Z (NisZ). Synthetic genes encoding the signal peptide of the lactococcal protein Usp45 (SPusp45), fused to mature GarA (lgnA) and/or mature GarQ (garQ) and their associated immunity genes (lgnI and garI, respectively), were cloned into the protein expression vectors pMG36c, which contains the P32 constitutive promoter, and pNZ8048c, which contains the inducible PnisA promoter. The transformation of recombinant vectors into lactococcal cells allowed for the production of GarA and/or GarQ by L. lactis subsp. cremoris NZ9000 and their co-production with NisA by Lactococcus lactis subsp. lactis DPC5598 and L. lactis subsp. lactis BB24. The strains L. lactis subsp. cremoris WA2-67 (pJFQI), a producer of GarQ and NisZ, and L. lactis subsp. cremoris WA2-67 (pJFQIAI), a producer of GarA, GarQ and NisZ, demonstrated the highest antimicrobial activity (5. 10.7-fold and 17. 68.2-fold, respectively) against virulent L. garvieae strains. bacteriocins garvicin nisin Lactococcus garvieae lactic acid bacteria (LAB) heterologous production Lactococcus lactis probiotics paraprobiotics postbiotics Ministerio de Ciencia, Innovacion y Universidades (MCIU, Madrid, Spain)RTI2018-094907-B-I00 Universidad Complutense de Madrid (UCM)FEI16/54 Santander/UCMPR75/18-21627 This work was supported by project RTI2018-094907-B-I00 from the Ministerio de Ciencia, Innovacion y Universidades (MCIU, Madrid, Spain), project FEI16/54 from the Universidad Complutense de Madrid (UCM) and project PR75/18-21627 from Santander/UCM. Javier Feito was supported by a FEI16/54 contract from UCM and held a predoctoral contract from the UCM. Carlos Araujo and Sara Arbulu held a FEI16/54 contract from the UCM. pmc1. Introduction Bacteriocins produced by lactic acid bacteria (LAB) have been largely valued as potential food preservatives, and the LAB producers of bacteriocins (bacteriocinogenic strains) have been valued as potential starter, protective, probiotic, paraprobiotic and postbiotic cultures . Moreover, concerns regarding the increase in antimicrobial resistances (AMRs) confer bacteriocins and the bacteriocinogenic LAB unlimited possibilities for applications in the food industry, human and veterinary medicine and the animal production field . Microbial-derived biotics, including bacteriocins, are recognized as functional components of natural and bioengineered probiotic, paraprobiotic and postbiotic cultures . Bacteriocins, including nisin A (NisA) and nisin Z (NisZ), drive the apoptosis of cancer cells and show low toxicity toward normal cells, making them promising anticancer candidates to replace or be combined with conventional therapeutic agents . Bacteriocinogenic LAB and the bacteriocins they produce may also have an impact in the modulation of the microbiota and immune system of their host . Most LAB bacteriocins are synthesized as biologically inactive precursors that contain an N-terminal extension, whereas the mature peptides are often cationic, amphiphilic, membrane-permeabilizing molecules. The N-terminal extensions of most bacteriocins are of the so-called double-glycine type (leader sequence) and are cleaved off concomitantly with export across the cytoplasmic membrane by dedicated, ATP-binding cassette transporters (ABC-transporters) and their accessory proteins . However, a few bacteriocins contain N-terminal extensions of the Sec-type (signal peptide), which are proteolytically cleaved concomitantly with peptide externalization by the general secretory pathway (GSP) or the Sec-dependent pathway . Several bacteriocins have been shown to be synthesized without N-terminal sequences and represent bacteriocins with a novel secretion mechanism . The mature bacteriocins are often classified into three main classes: class I, or lantibiotics, which have post-translationally modified amino acid residues, class II bacteriocins, which have unmodified amino acid residues, and class III large, heat-labile bacteriocins . However, the class I bacteriocins are currently included in the group of ribosomally synthesized and post-translationally modified peptides (RiPPS) . The class II bacteriocins can be further divided into the subclasses pediocin-like (class IIa), two-peptide (class IIb), leaderless (class IIc) and the non-pediocin single (class IId) bacteriocins . In most cases, bacteriocin production appears to be regulated and involves a quorum-sensing mode of regulation . The production of nisin is autoregulated by NisK, a sensor kinase protein, and NisR, a response regulator, which regulate transcription via signal transduction by a two-component regulatory system. The induction of NisA or NisZ is likely to be dependent on their interaction with NisK . The NisI and the ATP-binding cassette transporter NisEFG support the immunity of the producer cells to nisin . The presence of LAB in many ecological niches, including fish and their rearing environment, is well characterized, and the antimicrobial activity and the probiotic potential of the isolated strains is emphasized . However, despite the beneficial role of most LAB, the species Lactococcus garvieae has been identified as the aetiological agent of lactococcosis, a major, re-emerging and widely distributed ichthyopathology that causes a hyperacute haemorrhagic septicaemia and relevant economic losses in rainbow trout (Oncorhynchus mykiss, Walbaum) farming . The reported human cases of pathologies associated with this bacterium are increasing, and its zoonotic potential has been accepted . Bacteriocinogenic L. garvieae that demonstrate an antagonistic activity against virulent L. garvieae strains have been isolated. Their bacteriocins have been characterized, such as garvicin A , garvicin AG1 and garvicin AG2 , garvicin KS , garvicin L1-5 , garvicin ML and garvieacin Q . GarA, produced by L. garvieae 21881, is encoded in the plasmid pGL5, which holds the structural gene of GarA (lgnA), its putative immunity protein (lgnI) and the ABC-transporter and its accessory proteins (lgnC and lgnD). GarA is synthesized as a 63 amino acid precursor with a typical double-glycine leader peptide. Once processed, this peptide results in a 43-aa mature peptide with a theoretical molecular mass of 4645.5 Da. GarA has a narrow activity spectrum and is limited only to other L. garvieae strains, suggesting that its mechanism of action is based on the inhibition of cell division, most likely by inhibiting septum formation in target cells . GarQ is produced by L. garvieae BCC 43588 and is encoded as the GarQ structural gene (garQ), its putative immunity protein (garI) and the ABC-transporter (garT). GarQ shows a wide spectrum of antimicrobial activity against LAB and other potentially foodborne pathogenic strains . GarQ is synthesized as a 70-aa precursor with a double-glycine cleavage site, resulting in mature GarQ of 50-aa and a theoretical molecular mass of 5340 Da. GarQ utilizes the IID and IIC subunits of the mannose phosphotransferase system (Man-PTS) as a receptor. It kills target bacteria by disrupting the membrane integrity, mainly locking the Man-PTS into a conformation that leads to the formation of a constitutively open pore . NisZ, a 34 amino acid pentacyclic peptide naturally produced by L. lactis, exhibits antimicrobial activity against several Gram-positive and Gram-negative bacteria , and the bacteriocin exerts its antimicrobial activity by both pore formation and the inhibition of cell wall synthesis through specific binding to lipid II, which is an essential precursor of the bacterial cell wall . The cloning and heterologous expression of bacteriocins by LAB, particularly Lactococcus lactis, has proven to be a promising approach for obtaining microbial cell factories with a potent antimicrobial activity . Moreover, the simultaneous production of bacteriocins of different classes and/or subclasses and distinct modes of action may not only improve their antimicrobial activity and spectrum in a synergistic fashion but may also reduce the presence of bacteria that are resistant to their antagonistic activity . In this study, we have proceeded to the design and expression in different L. lactis strains of up to three different bacteriocins with antimicrobial activity against virulent L. garvieae. These bacteriocins, namely, GarA, GarQ and NisA/NisZ, show different modes of action and other well-described beneficial effects, such as the anticarcinogenic effect of NisA/NisZ and its ability to modulate the microbiota and regulate the immune system of its host. Thus, synthetic genes that encode the signal peptide of the lactococcal secreted protein Usp45 (SPusp45), fused to either mature GarA (lgnA) with its putative immunity gene (lgnI) and/or to mature GarQ (garQ) with its immunity gene (garI), were cloned into the protein expression vectors pMG36c which encodes the P32 constitutive promoter and in plasmid pNZ8048c, under control of the inducible PnisA promoter. Recombinant L. lactis strains were then obtained, and their antimicrobial activity against virulent L. garvieae was determined. 2. Materials and Methods 2.1. Bacterial Strains, Plasmids and Growth Conditions The bacterial strains and plasmids used in this study are listed in Table 1. The L. lactis strains were grown at 30 degC in M17 broth (Oxoid Ltd., Basingstoke, UK) supplemented with 0.5% (w/v) glucose (GM17). Pediococcus damnosus CECT4797 was grown in MRS broth (Oxoid Ltd.) at 30 degC. Escherichia coli JM109 (Promega, Madison, WI, USA) was grown in Luria-Bertani (LB) broth (Oxoid Ltd.) at 30 degC with shaking. Chloramphenicol (Sigma-Aldrich, St. Louis, MO, USA) was added at 20 mg/mL to select growth of E. coli and at 5 mg/mL for the selection of the recombinant lactococcal strains. The cell dry weights of the late exponential phase cultures were determined gravimetrically. Agar plates were made by the addition of 1.5% (w/v) agar (Oxoid) to the liquid media. 2.2. Basic Genetic Techniques and Enzymes Synthetic gene fragments were designed from the described amino acid sequence of the bacteriocin GarA (lgnA) and GarQ (garQ), as well as those from their putative immunity proteins GarAI (lgnI) and GarQI (garI), respectively. In addition, the leader peptide of the native bacteriocins was replaced by the signal peptide of the secreted protein Usp45 (SPusp45), a Sec-dependent protein produced by L. lactis MG1363 . Similarly, additional sequences containing the SacI cleavage site and the P32 ribosome binding site (RBS) as well as the SacI/HindIII or the BspHI/HindIII enzyme restriction cleavage sites were added at the 5' and 3' ends, respectively, of the designed synthetic gene fragments. Their codon usage was adapted for its expression by L. lactis. GeneArt(r) supplied the synthetic genes into the carrier plasmid pMA-T (Life Technologies S.A., Madrid, Spain). The protein expression vectors pMG36c and pNZ8048c were purified from E. coli JM109 by using the NucleoSpin Plasmid Kit (Macherey-Nagel, Duren, Germany). DNA restriction enzymes were supplied by New England Biolabs (Beverly, MA, USA). Ligations were performed with the T4 DNA ligase (Invitrogen, Walthman, MA, USA). Electrocompetent L. lactis subsp. cremoris NZ9000, L. lactis subsp. cremoris WA2-67, L. lactis subsp. lactis DPC5598 and L. lactis subsp. lactis BB24 cells were obtained after successive growth in the SGGM17 medium, which consisted of of M17 (Oxoid Ltd.) supplemented with 0.5 M sucrose, glucose (0.5%; w/v) and glycine (2%; w/v). The cultures were centrifuged and resuspended in a cold wash buffer containing glycerol (20%; v/v) and 0.5 M sucrose. Aliquots of 50 mL were stored at -80 degC until further use. 2.3. Recombinant Plasmids Derived from pMG36c and Transformation into L. lactis Hosts The primers and PCR products used for the construction of the pMG36c-derived vectors are listed in Table S1. PCR product amplifications were performed in 50 mL reaction mixtures that contained 20 ng of the synthetic gene fragments included in the carrier pMA-T vectors, 70 pmol of each primer, 1 U of Velocity DNA polymerase (Bioline Reagents, Ltd., London, UK), 10 mL of Hi-Fi buffer and 1.5 mL of 30 mM dNTP's mix in a MJ Mini Gradient Thermal Cycler (BioRad Laboratories). PCR cycling conditions were as follows: denaturation at 98 degC (2 min), 35 cycles of denaturation-annealing-extension (98 degC for 30 s, 60 degC for 30 s and 72 degC for 30 s, respectively) and a final extension step at 72 degC (5 min). The PCR-generated fragments were purified using a NucleoSpin(r) Gel and PCR clean-up kit (Macherey-Nagel) for cloning and nucleotide sequencing. When required, PCR amplifications were sequenced using the ABI PRISM(r) BigDye(r) Terminator cycle sequence reaction kit and the automatic DNA sequencer ABI PRISM, model 377 (Applied Biosystems, Foster City, CA, USA) at the Unidad de Genomica (CAI Tecnicas Biologicas, UCM, Madrid, Spain). Digestion of the amplified PCR products with SacI/HindIII permitted the ligation of the resulting restriction fragments into pMG36c, which was digested with the same enzymes. The resulting pMG36c-derived vectors were transformed into competent lactococcal hosts and electrotransformed with a Gene PulserTM and Pulse Controller apparatus (Bio-Rad Laboratories, Hercules, CA, USA), according to a previously described procedure . Transformed cells containing the pMG36c-derived vectors pJFAI, pJFQI, pJFAIQI and pJFQIAI (Table 1), were selected for their growth with chloramphenicol and evaluated for their bacteriocinogenity. The total bacterial DNA from the transformed lactococcal strains was purified using the InstaGene Matrix (BioRad Laboratories). It was then submitted to PCR using the primers MGPJ-F and MGPJ-R. The sequencing of the generated PCR products was performed at the Unidad de Genomica (CAI Tecnicas Biologicas, UCM). 2.4. Recombinant Plasmids Derived from pNZ8048c and Transformation into L. lactis Hosts The primers and PCR products used for the construction of the pNZ8048c-derived vectors are listed in Table S1. The initial PCR amplification of the designed gene fragments into carrier pMA-T vectors was performed with primers GARF-BSPHI and GARAIM-R, which were designed to provide the restriction cleavage site for BspHI/HindIII. The digestion of the amplified PCR products with BspHI/HindIII permitted the ligation of the resulting restriction fragments into pNZ8048c, which was digested with NcoI and HindIII. However, it should be highlighted that construction of the pNZ8048c-derived vectors carrying GarQ or GarQ and GarA and their respective immunity proteins was achieved using a novel, PCR-based, restriction-enzyme-free cloning, or ABC cloning, method . Briefly, the procedure implies the PCR amplification of three overlapping fragments, two from the pNZ8048c vector and one from the previously designed synthetic gene fragments, to generate a single, circular, pNZ8048c-derived vector by using a pair of overlapping primers. For the amplification of the appropriate gene fragments, 50 mL PCR reactions containing 100 ng of plasmid pNZ8048c or the synthetic gene fragments included in the carrier pMA-T vectors, 0.5 mmol of each primer and 25 mL of Phusion Hot Start II High-Fidelity PCR Master Mix (Thermo Scientific, Waltham, MA, USA) were used. PCR cycling conditions were as follows: one initial denaturation step at 98 degC (30 s), 30 cycles of denaturation-annealing-extension (98 degC for 10 s, 49.1-65.8 degC for 20 s and 72 degC for 25 s, respectively) and a final extension step at 72 degC for 5-10 min). Overlapping PCRs were carried out using the three corresponding fragments as templates. Specifically, 1.5 x 1010 copies of fragments derived from amplification of pNZ8048c and 3 x 1010 copies of fragments obtained from amplification of the designed synthetic genes were used. Agarose gel electrophoresis, visualization and sequencing of the generated PCR products were performed essentially as described for the construction of the pMG36c-derived vectors. The resulting pNZ8048c-derived vectors were transformed into competent lactococcal hosts, and the transformed cells containing the pNZ8048c-derived vectors pNJFAI, pNJQI and pNJFQIAI (Table 1) were selected for their growth with chloramphenicol and evaluated for their bacteriocinogenicity. Bacterial DNA from the lactococcal transformed cells was submitted to PCR amplification with the primers NZPJ-F and NZPJ-R. The sequencing of the generated PCR products was performed at the Unidad de Genomica (CAI Tecnicas Biologicas, UCM). 2.5. Antimicrobial Activity of the Recombinant L. lactis Strains The direct antimicrobial activity of colonies from the recombinant lactococcal strains was examined by a stab-on-agar test (SOAT) as previously described . When appropriate, cultures were induced with nisin A (Sigma-Aldrich) at a final concentration of 10 ng/mL for the production of the cloned bacteriocins. Cell-free culture supernatants (CFS) were obtained by the centrifugation of cultures at 12,000x g at 4 degC for 10 min, adjusted to pH 6.2 with 1 M NaOH, filtered through 0.22 mm pore-size syringe filters (Sartorius, Gottingen, Germany) and stored at -20 degC until further use. The antimicrobial activity of the supernatants was determined by an agar diffusion test (ADT). It was further quantified by a microtiter plate assay (MPA) as previously described . For the MPA, the growth inhibition of sensitive cultures was measured spectrophotometrically at 620 nm with a FLUOstar OPTIMA (BMGLabtech, Ortenberg, Germany) plate reader. One bacteriocin unit (BU) was defined as the reciprocal of the highest dilution of the bacteriocin that caused a growth inhibition of 50% (50% of the turbidity of the control culture without bacteriocin). 2.6. Purification of Bacteriocins Bacteriocins were purified as previously described using a multi-chromatographic procedure . Briefly, 1 L supernatants from early stationary cultures of the recombinant lactococci were precipitated with (NH4)2SO4 (50%; w/v), desalted by gel filtration (PD-10 columns) and subjected to a cation-exchange (SP Sepharose Fast Flow), followed by a hydrophobic interaction (Octyl-Sepharose CL-4B) and reverse-phase chromatography in an AKTA purifier Reverse Phase Fast Protein Liquid Chromatography system (RP-FPLC), using the PepRPC HR 5/5 column. Fractions exhibiting the highest bacteriocin activity were pooled and re-chromatographed on the same column until chromatographically pure bacteriocin peptides were obtained. All chromatographic columns and equipment were obtained from GE Healthcare Life Sciences (Barcelona, Spain). 2.7. Mass Spectrometry (MS) and Multiple Reaction Monitoring (MRM) Analysis of Purified Peptide Fractions from Supernatants of the Recombinant L. lactis Strains Purified RP-FPLC fractions from the supernatants of the recombinant lactococcal strains were subjected to matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) and multiple reaction monitoring liquid chromatography-electrospray ionization tandem mass spectrometry (MRM-LC-ESI-MS/MS) analyses at the Unidad de Proteomica (CAI Tecnicas Biologicas, UCM). Briefly, 1 mL of eluted fractions were spotted onto a MALDI target plate and allowed to air-dry at room temperature. Then, 0.8 mL of a sinapic acid matrix (Sigma-Aldrich) in 30% acetonitrile and 0.3% trifluoroacetic acid was added and allowed to air-dry at room temperature. MALDI-TOF MS analyses were performed using a 4800 Plus Proteomics Analyzer MALDI-TOF/TOF mass spectrometer (Applied Biosystems/MDS Sciex, Toronto, Canada). For the identification of bacteriocins, the MRM method evaluates a complex mixture of tryptic peptides that can be selectively detected by liquid chromatography coupled to electrospray MS. Briefly, the purified RP-FPLC fractions of interest were dried in Speed-vac and resuspended in 20 mL of 8 M urea. The samples were reduced by adding 10 mM of dithiothreitol for 45 min at 37 degC and alkylated with 55 mM of iodacetamide for 30 min in the dark. The urea was then diluted with 25 mM of ammonium bicarbonate to obtain a molarity of less than 2. When the pH was 8.5, digestion was performed by adding recombinant sequencing grade Trypsin (Roche Molecular Biochemicals, Branchburg, NJ, USA) 1:20 (w/w) and incubating at 37 degC. After 60 min, an aliquot was taken for the partial digestion of the sample. The rest was incubated overnight. The produced peptides were dried in Speed-vac and resuspended in 2% acetonitrile and 0, 1% formic acid. Skyline (64-bit), version 20.1, was used to build and optimize the MRM for the detection of the peptides of interest . All analyses were performed on a LC-MS/MS Eksigent Nanoflow LC system coupled to a hybrid triple quadrupole/ion trap mass spectrometer, 5500 QTRAP (AB Sciex, Foster City, CA, USA), equipped with a nano electrospray interface operating in the positive ion mode. The MS/MS data were analyzed using Protein Pilot 4.5 software (AB Sciex) or MASCOT 2.3 (MatrixScience, London, UK) to identify the peptides against an in-house DataBase with the fasta sequences of the targeted proteins. The searches were performed assuming a digestion with trypsin with a maximum of 2 missed cleavages, a fragment ion mass tolerance of 0.6 Da and a parent ion tolerance of 0.15 Da. Peptide identifications based on the MS/MS data were accepted if they could be established at a CI of greater than 95% (p < 0.05). Data were then processed against the MRM-library on Skyline to ensure consistency between the transitions detected and the sequences of the peptides searched. 3. Results 3.1. Genetic Design and Cloning of Synthetic Genes That Drive the Heterologous Production of GarA and/or GarQ by Recombinant L. lactis Cells In this work, synthetic genes containing the protein SPusp45, fused to mature GarA (lgnA) and its putative immunity protein GarAI (lgnI) (AI) encoded by L. garvieae 21881 , synthetic genes containing the protein SPusp45 fused to mature GarQ (garQ) and its putative immunity protein GarQI (lgnI) (QI) encoded by L. garvieae BCC43578 , and synthetic genes containing the genetic fusions SPusp45::lgnA+lgnI+garQ+garI (AIQI) and SPusp45::garQ+garI+lgnA+lgnI (QIAI), were designed for cloning into the protein expression vectors pMG36c which carries the P32constitutive promoter, and in pNZ8048c with the inducible PnisA promoter. PCR-based amplifications of the synthesized gene fragments allowed for the generation of the PCR products shown in Table S1. Cloning the PCR products A, B, C and D in pMG36c resulted in the pMG36c-derived vectors pJFAI, pJFQI, pJFAIQI and pJFQIAI, and cloning the PCR product E in pNZ8048c resulted in the pNZ8048c-derived vector pNJFAI (Table 1). Similarly, the use of a novel, PCR-based, restriction-enzyme-free cloning method for cloning fragments in plasmid pNZ8048 allowed for the construction of the pNZ8048c-derived vectors pNJFQI and pNJFQIAI (Table 1). In this study, no efforts were made to omit the presence of hypothetically redundant genes that encode putative immunity proteins in the designed synthetic gene fragments. 3.2. Antimicrobial Activity of the Recombinant L. lactis Strains as Determined by Their Direct Antagonistic Effect (SOAT) and the Antimicrobial Activity (ADT) of Their Cell-Free Supernatants The transformation of recombinant plasmids into L. lactis subsp. cremoris NZ9000 showed that while the control NZ9000 (pMG36c) and NZ9000 (pNZ8048c) cells showed no antimicrobial activity against L. garvieae CF00021 or P. damnosus CECT4797, all the recombinant NZ9000-derived strains exhibited a measurable antagonistic effect against L. garvieae CF00021 (Table 2). Interestingly, results from both the SOAT and ADT tests showed that the recombinant strains NZ9000 (pJFAI) and NZ9000 (pNJFAI), which only encode the production of GarA, showed no antimicrobial activity against P. damnosus CECT4797. However, the recombinant strains derived from the native NisZ producer (L. lactis subsp. cremoris WA2-67) and the native NisA producers (L. lactis subsp. lactis DPC5598 and L. lactis subsp. lactis BB24) showed a higher antimicrobial activity against P. damnosus CECT4797 than L. garvieae CF00021. The strains that only encoded the production of GarA and/or GarQ but not NisZ or NisA (NZ9000 derivatives) showed a weaker antimicrobial activity against P. damnosus CECT4797. A closer evaluation of the antimicrobial activity of the NisZ-producing strain L. lactis subsp. cremoris WA2-67 suggested that the strains WA2-67 (pJFQI) and WA2-67 (pJFQIAI) displayed slightly larger halos of inhibition against both indicator strains than the rest of the recombinant strains evaluated (Table 2). Furthermore, the evaluation of the diluted supernatants of L. lactis subsp. cremoris WA2-67, which were transformed with pMG36c or the pMG36c-derived vectors, showed that the antimicrobial activity of the recombinant strains WA2-67 (pJFAI), WA2-67 (pJFQI), WA2-67 (pJFAIQI) and WA2-67 (pJFQIAI) was 2-, 8-, 16-fold higher, respectively, than the antimicrobial activity of L. lactis subsp. cremoris WA2-67 (pMG36c) . The evaluation of the antimicrobial activity of the NisA-producing strain L. lactis subsp. lactis DPC5598 showed that recombinants encoding the production of either GarAI, GarQI, GarAI+GarQI or GarQI+GarAI displayed similar halos of inhibition to the control strains, DPC5598 (pMG36c) and DPC5598 (pNZ8048c), against both P. damnosus CECT4797 and L. garvieae CF00021. However, supernatants of the recombinant strains, derived from the NisA producer L. lactis subsp. lactis BB24, showed slightly larger inhibition halos against L. garvieae CF00021 than the control BB24 (pMG36c) and BB24 (pNZ8048) cells (Table 2). 3.3. Antimicrobial Activity of Recombinant L. lactis Strains against Different L. garvieae Strains The antimicrobial activity of supernatants from all lactococcal strains was quantified against different virulent L. garvieae strains by using a more sensitive microtiter plate assay (MPA). Again, L. lactis subsp. cremoris NZ9000 (pMG36c) showed no antimicrobial activity against any of the L. garvieae strains evaluated, while the recombinant NZ9000-derived strains transformed with the constitutive pMG36c-derived vectors showed a weak antimicrobial activity against the virulent L. garvieae strains (Table 3). However, the NisZ-producing L. lactis subsp. cremoris WA2-67 (pMG36c) showed a much higher antimicrobial activity against L. garvieae. Remarkably, the antimicrobial activity determined for the recombinant WA2-67-derived strains transformed with the pMG36c-derived vectors to generate the WA2-67 (pJFAI), WA2-67 (pJFQI), WA2-67 (pJFAIQI) and WA2-67 (pJFQIAI) bacteriocin producers was 1. 1.6-fold, 5. 10.7-fold, 0. 1.6-fold, and17. 68.2-fold higher, respectively, than that of the control strain WA2-67 (pMG36c) (Table 3). The antimicrobial activity of the NisA producer L. lactis subsp. lactis DPC5598 recombinants was 0. 1.2-fold higher than that of the control DPC5598 (pMG36c) strain against L. garvieae, while the antagonistic activity of the NisA producer L. lactis subsp. lactis BB24 recombinants was 1. 3.7-fold higher than that of the control BB24 (pMG36c) strain against the same L. garvieae indicator strains (Table 3). When the antimicrobial activity of the lactococcal strains that were transformed with the inducible pNZ8048c-derived vectors was determined, L. lactis subsp. cremoris NZ9000 (pNZ8048c) showed no antimicrobial activity against any of the L. garvieae strains, while the recombinant NZ9000 (pNJFAI), NZ9000 (pNJFQI), and NZ9000 (pNJQIAI) strains showed a 12. 18.9-fold, 7. 18.1-fold and 6. 14.4-fold higher antimicrobial activity, respectively, than the cells transformed with the pMG36c-derived vectors (Table 4). However, the antimicrobial activity of the L. lactis subsp. cremoris WA2-67 (pNZ8048c) cells and their recombinant WA2-67 (pNJFAI), WA2-67 (pNJFQI) and WA2-67 (pNJFQIAI) strains showed a 0. 0.9-fold, 0. 0.8-fold, 0. 0.2-fold and 0. 0.08-fold lower antimicrobial activity, respectively, against the L. garvieae strains than the cells transformed with the pMG36c-derived vectors (Table 4). The antimicrobial activity of the NisA-producing L. lactis subsp. lactis DPC5598 transformed with the pNZ8048c-derived vectors was only slightly (0. 2.0-fold) higher than the antimicrobial activity of the cells transformed with the pMG36c-derived vectors. Similarly, the antagonistic activity of the NisA producer L. lactis subsp. lactis BB24 recombinants transformed with the pNZ8048c-derived vectors was only slightly (0. 1.9-fold) higher than cells transformed with the pMG36c-derived vectors (Table 4). 3.4. Purification of Bacteriocins Produced by L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI) The results regarding the purification to homogeneity of the bacteriocins in supernatants of the selected L. lactis subsp. cremoris recombinants are summarized in Table 5. The evaluation of the most active antimicrobial fractions after the first reversed-phase chromatography step (RP-FPLC) permitted the identification of two active fractions during the purification of the bacteriocins produced by L. lactis subsp. cremoris WA2-67 (pJFQI) and three active fractions during the purification of the bacteriocins produced by L. lactis subsp. cremoris WA2-67 (pJFQIAI). Although the antimicrobial activity of the eluted fractions was low, a significant increase in their specific antimicrobial activity was observed. 3.5. Mass Spectrometry (MS) and Multiple Reaction Monitoring (MRM) Analysis of the Purified Bacteriocin Fractions MALDI-TOF MS analysis of fraction 8 and fraction 7, eluted during the RP-FPLC step of the purification of supernatants from L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI), showed major peaks of 3331.4 Da and 3331.3 Da , respectively, matching the molecular mass described for NisZ. In addition, second peaks of 3349.3 Da and 3348.8 Da, respectively, likely correspond to the oxidation of the lanthionine ring of NisZ . However, MALDI-TOF MS analysis of the eluted fraction 14 from the L. lactis subsp. cremoris WA2-67 (pJFQI), which encoded GarQ and NisZ, in addition to an analysis of fractions 9 and 12 from the L. lactis subsp. cremoris WA2-67 (pJFQIAI), which encoded GarA, GarQ and NisZ, could not identify the presence of the bacteriocins GarA and GarQ with predicted molecular masses of 4645.2 Da and 5340 Da, respectively, in the eluted fractions. Since this was a totally unexpected result, the fractions were subjected to MRM-LC-ESI-MS/MS analysis to determine the presence of the expected bacteriocins in the samples. In the MRM method, a series of target tryptic peptides and their associated transitions (fragments m/z) were predicted from the molecular masses and amino acid sequences of the bacteriocins GarA and GarQ. Each targeted peptide has a set of accompanying transitions which are then selectively detected in the second stage of the MS. A summary of the results obtained is shown in Table 6. MRM transitions were established and validated by tandem mass spectrometry (MS/MS). For each bacteriocin, two encrypted peptides were confidently detected in duplicate runs. 4. Discussion Virulent L. garvieae are the etiological agents of a hyperacute hemorrhagic septicemia in fish, known as lactococcosis. They are also responsible for human pathologies due to their zoonotic character and potential presence in foods . Bacteriophages and bacteriocins have potential as complementary strategies for combating L. garvieae in foods and fish , while bacteriocinogenic LAB could be evaluated for their potential use as probiotics, paraprobiotics and postbiotics in food, feed and other biotechnological applications . The optimization of bacteriocin gene synthesis, expression and production helps the development of LAB as cell factories for the production and delivery of multiple bacteriocins . The use of synthetic genes that match the codon usage of the producer organisms has a significant impact on gene expression levels and protein folding . In this work, the transformation of L. lactis subsp. cremoris NZ9000 with pNZ8048c-derived vectors demonstrated that the NZ9000 (pJFAI) and NZ9000 (pNJFAI) recombinant cells, which encode GarAI, showed antimicrobial activity against L. garvieae CF00021 but not against P. damnosus CECT4797 (Table 2), confirming their production of GarA and previous observations that this bacteriocin was only active against L. garvieae . However, differences in the antimicrobial activity of recombinants derived from the NisZ producer L. lactis subsp. cremoris WA2-67, which was transformed with the pMG36c-derived vectors but not pNZ8048c-derived vectors, were observed against both indicator strains. The obtained results showed that the WA2-67 (pJFQI) cells exhibited larger halos of inhibition than the WA2-67 (pJFAI) cells, and that the WA2-67 (pJFQIAI) cells displayed the largest observed halos . These results suggest that the constitutive expression of GarQI is higher than GarAI or that the specific antimicrobial activity of GarQ is higher than that of GarA. Perhaps the transcription, processing and secretion from genes encoding GarQI+GarAI are more effective than from genes encoding GarAI+GarQI. On the other hand, no remarkable differences were found in the antimicrobial activity of the recombinants derived from the NisA producers transformed with the pMG36c-derived or the pNZ8048c-derived vectors, L. lactis subsp. lactis DPC5598 and L. lactis subsp. lactis BB24 (Table 2). Due to the increasing interest that L. garvieae is attracting as not only a relevant bacterial pathogen but also as a zoonotic agent , the antimicrobial activity of the L. lactis recombinants was further evaluated and quantified against different virulent L. garvieae strains by using a more sensitive microplate assay (MPA). The obtained results showed that the L. lactis subsp. cremoris NZ9000 cells transformed with the pNZ8048c-derived vectors showed a 6. 18.9-fold higher antimicrobial activity than the recombinant cells bearing the pMG36c-derived vectors (Table 3 and Table 4). The enhanced antimicrobial activity in cells with the nisin-inducible constructs may be due to copy number differences between pNZ8048c and pMG36c, but is more likely caused by the promoters used to drive gene expression . Plasmid pNZ8048c contains the high-copy number heterogramic replicon of the lactococcal plasmid pSH71 with a unique NcoI cleavage site downstream of the nisA ribosome binding site (RBS), which is used for translational fusions inducible by NisA . To optimize protein production, inducible systems are usually considered superior to constitutive expression systems since the former allow for the achievement of a sufficient biomass before the initiation of target protein expression . The increased antimicrobial activity observed with the NisA-induced cells may also be ascribed to the short induction time for the production of GarA and/or GarQ (3 h), which most likely prevented the secreted bacteriocins from attaching to cell walls to form aggregates and/or to undergo protease degradations. Moreover and quite remarkably, the antimicrobial activity of L. lactis subsp. cremoris WA2-67 (pMG36c) and the pMG36c-derived WA2-67 (pJFAI), WA2-67 (pJFQI), WA2-67 (pJFAIQI), and WA2-67 (pJFQIAI) strains showed a 1. 1.6-fold, 5. 10.7-fold, 0. 1.6-fold and 17. 68.2-fold higher antimicrobial activity, respectively, than the control WA2-67 (pMG36c) strain (Table 3). These results also indicate that the expression of QI increases the antimicrobial activity of the producer cells; however, the expression of AI has a much lower effect. Additionally, no increase in antimicrobial activity is observed when QI is expressed as the second of the two modules (AIQI). However, when QI is expressed as the first module (QIAI), a synergistic effect of both modules seems to occur regarding the very high antimicrobial activity of the producer cells. Thus, the AI in the AIQI module appears to prevent the QI from becoming active. However, when QI is expressed first in the QIAI module, the AI appears to synergistically increase the QI activity (Table 3). The pMG36c vector is a shuttle vector. It is based on the low-copy replication origin of pWV01 and is able to replicate in Escherichia coli, Bacillus subtilis and LAB, whereas the strong P32 promoter drives the constitutive transcription of inserted genes into the multicloning site (MCS) of pUC18 . From the results obtained, it may occur that, as previously suggested, the specific antimicrobial activity of GarA against L. garvieae is lower and/or its production and stability is less than that of GarQ. Additionally, besides the choice of vector and promoters, other factors such as the activation of quality control networks involving folding factors and housekeeping proteases, the oxidation of methionine to methionine-sulfoxide, bacteriocin self-aggregation and mRNA stability may affect bacteriocin production and activity from the recombinant hosts . The coexpression of putative immunity genes may also increase the production of bacteriocins in heterologous hosts. These immunity proteins can act by either affecting bacteriocin pore formation or by perturbing the interaction between the bacteriocin and a membrane-located bacteriocin receptor, thereby preventing producer cells from being killed . The expression in AIQI of LgnI before the expression of GarI could also affect producer protection against GarQ, thereby affecting growth and bacteriocin production by the producer cells. Importantly, L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI) showed the highest antimicrobial activity against all virulent strains of L. garvieae evaluated (Table 3). However, the antimicrobial activity of L. lactis subsp. cremoris WA2-67, which was transformed with the pNZ8048c-derived vectors, produced WA2-67-derivatives that showed a 0. 0.9-fold lower antimicrobial activity, respectively, than the cells transformed with the pMG36c-derived vectors (Table 4). This was an unexpected result since, as previously described, inducible systems are often considered superior to constitutive expression systems for the optimization of protein production. Perhaps NisK and NisR, the two component signal transduction systems for the regulation of NisZ synthesis in L. lactis subsp. cremoris WA2-67, do not fully activate transcription of the PnisA present in pNZ8048c. It could be also possible that levels of phosphorylated NisR may be not enough to drive the activation of two independent Pnis promoters which, in addition, derive from two different Lactoccocus lactis subspecies: cremoris and lactis, respectively. Alternatively, NisZ may not be as efficient as NisA for an interaction with the NisK produced by L. lactis subsp. cremoris WA2-67, thus constraining the induction of transcription of PnisA in pNZ8048c by blocking NisZ with NisI and NisEFG. The antimicrobial activity of the NisA-producers L. lactis subsp. lactis DPC5598 and L. lactis subsp. lactis BB24 was slightly higher for the cells transformed with the the pMG36c-derived vectors, suggesting that NisA is a better inducer than NisZ for the activation of the transcription of PnisA in pNZ8048c (Table 3 and Table 4). However, the antimicrobial activity of the DPC5598-derived recombinants under constitutive or inducible conditions was lower during multi-bacteriocin production. This was probably due to the high energy and metabolic cost linked to plasmid maintenance and replication, to the secretion stress associated with bacteriocin overproduction and/or to the synthesis of proteinases for the elimination of misfolded proteins . Differences in the antimicrobial activity of these strains and those from the L. lactis subsp. cremoris WA2-67 transformed with the pMG36c-derived vectors may be also ascribed to yet-unknown genetic and/or metabolic differences between the strains. L. lactis subsp. lactis DPC5598 was selected as a potential multi-bacteriocin-producing host because it is a plasmid-free derivative of an industrial strain that is extensively used in fermented dairy products due to its phage insensitivity and fast acid-producing ability . L. lactis subsp. lactis BB24 is a fermented, meat-derived isolate widely used as an efficient host for the heterologous production of bacteriocins . Both multi-bacteriocin producers should be considered for their potential evaluation as probiotics, paraprobiotics and/or postbiotics reducing the increasing presence of virulent and zoonotic L. garvieae in selected milk and meat substrates, respectively . The MALDI-TOF MS analysis of purified eluted fractions from supernatants of the most active antimicrobial strains, L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI) (Table 5), allowed for the detection of NisZ in supernatants of the producer strains , suggesting that this bacteriocin is appropriately processed and transported out of the producer cells. However, the presence of GarA and GarQ could not be detected, suggesting interactions of the bacteriocins with unknown biological compounds, or a low amount and recovery of the bacteriocins during their purification to homogeneity . However, bacteriocins in the purified fractions were suitable for MRM evaluation and data analysis, which is an emerging targeted proteomics workflow and a highly selective and sensitive method for detecting peptides in the low ng/mL to sub-ng/mL range concentrations . When the purified fractions were subjected to MRM-LC-ESI-MS/MS analysis, two encrypted peptides were confidently (99%) detected. The detected peptides were confirmed by MS/MS, and at least four transitions were identified for each (Table 6). The peptide fragments covered 44% of the sequence of GarQ, while the coverage was 21% for GarA. These relatively low-coverage percentages are related to the reduced presence of lysine and arginine (trypsin cleavage sites) in GarA and GarQ, which significatively reduces the number of potentially identifiable target peptides. Previous studies by our research group identified probiotic features of the native or wild-type NisZ producer L. lactis subsp. cremoris WA2-67 such as a potent antimicrobial activity against ichthyopathogens, survival in fresh water and the gastrointestinal tract of trout, a resistance to bile and low pH, and an improved colonization ability with respect to the intestinal trout mucosa . Further in silico analyses of the whole-genome sequence (WGS) of this strain also identified other potential probiotic traits such as the production of vitamins and amino acids, adhesion/aggregation and stress resistance factors and the absence of transferable antibiotic resistance determinants and genes encoding detrimental enzymatic activities or potential virulence factors . Other studies performed by our group demonstrated the effectiveness of L. lactis subsp. cremoris WA2-67 to protect rainbow trout in vivo against infection of the virulent L. garvieae and the relevance of NisZ production as an anti-infective mechanism . The work described in this study constitutes the first report on the design of multi-bacteriocinogenic L. lactis subsp. cremoris WA2-67 strains with a high antimicrobial activity against virulent L. garvieae and a promising role as probiotics, paraprobiotics and/or postbiotics in food, feed and other biotechnological applications. The evaluation of bioengineered strains as probiotics is subjected to approval by regulatory authorities and is performed under strict biological conditions. However, the number of reports on the evaluation of bioengineered bacterial strains as probiotics (live cells), paraprobiotics (dead, non-viable cells) and postbiotics (physical-, enzymatic-lysis of probiotic cells) is increasing . Accordingly, experiments are being planned to evaluate the in vitro effect of L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI) on rainbow trout intestinal epithelial cells (RTgutGC) for a transcriptional analysis of several immune, intestinal, barrier-integrity and homeostasis genes and the induction of antimicrobial peptides (AMPs), as well as for their effect on the in vivo modulation of the intestinal microbiota and immune response of rainbow trout (Oncorhynchus mykiss, Walbaum) and turbot (Scophthalmus maximus). 5. Conclusions The design of synthetic genes and their cloning into protein expression vectors bearing constitutive or inducible promoters has allowed for the production and functional expression of GarA and/or GarQ by L. lactis subsp. lactis and L. lactis subsp. cremoris strains. Most importantly, L. lactis subsp. cremoris WA2-67, transformed with the pMG36c-derived vectors, allowed for the obtention of L. lactis subsp. cremoris WA2-67 (pJFQI), a producer of GarQ and NisZ, and L. lactis subsp. cremoris WA2-67 (pJFQIAI), a producer of GarA, GarQ and NisZ, with a much higher antimicrobial activity (5. 10.7-fold and 17. 68.2-fold, respectively) against virulent L. garvieae than the rest of the L. lactis strains evaluated. The concerted use of a sensitive microtiter plate assay (MPA) for the quantification of the antimicrobial activity of supernatants, the use of a multi-chromatographic procedure for the purification of bacteriocins to homogeneity, and the use of a MALDI-TOF MS multiple reaction monitoring (MRM-LC-ESI-MS/MS) analysis of the purified bacteriocins are unavoidable and possibly irreplaceable tools for the identification and characterization of the bacteriocins produced by L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI). Acknowledgments We thank the Proteomics Unit of the University Complutense of Madrid (UCM), integrated the ProteoRed, PRB3-ISCIII, and support from the Grant PT17/0019 of the PE I + D + I 2013-2016, funded by ISCIII and ERDF, for technical assistance in the proteomic analysis of the samples. Supplementary Materials The following supporting information can be downloaded at: Table S1: Primers and PCR products used in this study; Figure S1: MALDI-TOF MS analysis of purified NisZ from Lactococcus lactis subsp. cremoris WA2-67 (pJFQI) (A) and Lactococcus lactis subsp. cremoris WA2-67 (pJFQIAI (B). Numbers indicate the molecular mass in Daltons of major peptide fragments. Click here for additional data file. Author Contributions Conceptualization, P.E.H. and L.M.C.; methodology, J.F., C.A., S.A., E.M.-A. and J.B.; validation, J.F., C.A., S.A., D.C. and B.G.-S.; formal analysis, J.F., L.D.-F., E.M.-A. and J.B.; investigation, J.F., C.A. and S.A.; writing--original draft preparation, J.F.; project administration, P.E.H., L.M.C. and J.F.; funding acquisition, P.E.H. and L.M.C. 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 or supplementary material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Antimicrobial activity of diluted supernatants of recombinant L. lactis strains as determined by an agar diffusion test (ADT) with L. garvieae CF00021 as the indicator microorganism. Supernatants from: L. lactis subsp. cremoris WA2-67 (pMG36c) (A), L. lactis subsp. cremoris WA2-67 (pJFAI) (B), L. lactis subsp. cremoris WA2-67 (pJFQI) (C), L. lactis subsp. cremoris WA2-67 (pJFAIQI) (D) and L. lactis subsp. cremoris WA2-67 (pJFQIAI) (E). Supernatants from recombinant strains in the upper lines were diluted 1, 2, 4, 8, 16 and 32 times, and in the bottom lines were diluted 64, 128, 256, 512, 1024 and 2048 times. foods-12-01063-t001_Table 1 Table 1 Bacterial strains and plasmids used in this study. Strain or Plasmid Description a Source and/or Reference b Strains Lactococcus lactis subsp. cremoris NZ9000 Host strain; non-bacteriocin producer; pepN::nisRK. NIZO, Lactococcus lactis subsp. cremoris WA2-67 Host strain; fish origin; nisin Z producer. , Lactococcus lactis subsp. lactis DPC5598 Host strain; milk origin; nisin A producer. Plasmid-free derivative of DPC4268. DPC, Lactococcus lactis subsp. lactis BB24 Host strain; meat origin; nisin A producer. , Lactococcus garvieae CF00021 SOAT, ADT, MPA indicator CEFAS-BCC Lactococcus garvieae CF01144 MPA indicator CEFAS-BCC Lactococcus garvieae CLG4 MPA indicator LFP-UNIZAR Lactococcus garvieae CLG5 MPA indicator LFP-UNIZAR Lactococcus garvieae CLFP28/06 MPA indicator LFP-UNIZAR Lactococcus garvieae JIP29/99 MPA indicator Jouy-en-Josas SC Pediococcus damnosus CECT4797 SOAT, ADT indicator CECT Plasmids pMG36c Cmr; pMG36e derivative; constitutive expression vector carrying the P32 promoter. RUG-MG, pNZ8048c Cmr; inducible expression vector carrying the nisA promoter. NIZO, pJFAI Cmr, pMG36c derivative carrying the PCR product A (P32 ribosome binding site and the SPusp45 fused to mature lgnA and lgnI). This work pJFQI Cmr, pMG36c derivative carrying the PCR product B (P32 ribosome binding site and the SPusp45 fused to mature garQ and garI). This work pJFAIQI Cmr, pMG36c derivative carrying the PCR product C (P32 ribosome binding site and the SPusp45 fused to mature lgnA and lgnI and mature garQ and garI). This work pJFQIAI Cmr, pMG36c derivative carrying the PCR product D (P32 ribosome binding site and the SPusp45 fused to mature garQ and garI and mature lgnA and lgnI). This work pNJFAI Cmr, pNZ8048c derivative carrying the PCR product E (SPusp45 fused to mature lgnA and lgnI). This work pNJFQI Cmr, pNZ8048c derivative corresponding to the PCR product J (SPusp45 fused to mature garQ and garI). This work pNJFQIAI Cmr, pNZ8048c derivative corresponding to the PCR product K (SPusp45 fused to mature garQ and garI and mature lgnA and lgnI). This work a SOAT-- stab-on-agar test; ADT--agar diffusion test; MPA--microtiter plate assay; Cmr--chloramphenicol resistance. b NIZO--Department of Biophysical Chemistry, NIZO Food Research (Ede, The Netherlands); SD-NUTRYCIAL--Seccion Departamental de Nutricion y Ciencia de los Alimentos, Facultad de Veterinaria, Universidad Complutense de Madrid (Madrid, Spain); DPC--Teagasc Dairy Products Research Centre, Moorepark, Fermoy, Co., (Cork, Ireland); CEFAS-BCC-- Centre for Environment Fisheries and Aquaculture Science-Bacterial Culture Collection (Suffolk, United Kingdom); LFP-UNIZAR--Laboratory of Fish Pathology, Universidad de Zaragoza (Zaragoza, Spain); Jouy-en-Josas SC--Jouy-en-Josas Strain Collection, INRAE (Jouy-en-Josas, France); CECT--Spanish Type Culture Collection, Universidad de Valencia (Valencia, Spain); RUG-MG--Department of Molecular Genetics, University of Groningen (Haren, The Netherlands). foods-12-01063-t002_Table 2 Table 2 Direct antimicrobial activity and extracellular antimicrobial activity of recombinant L. lactis strains, producing garvicin A (GarA) and/or garvicin Q (GarQ), against different bacterial indicators. Strain SOAT a ADT b L. garvieae CF00021 P. damnosus CECT4797 L. garvieae CF00021 P. damnosus CECT4797 L. lactis subsp. cremoris NZ9000 (pMG36c) (-) (-) (-) (-) NZ9000 (pJFAI) 6.7 (-) 10.1 (-) NZ9000 (pJFQI) 6.4 6.0 10.3 8.6 NZ9000 (pJFAIQI) 6.6 5.8 10.4 8.9 NZ9000 (pJFQIAI) 6.8 5.9 10.2 8.8 NZ9000 (pNZ8048c) (-) (-) (-) (-) NZ9000 (pNJFAI) 8.6 (-) 11.9 (-) NZ9000 (pNJFQI) 8.3 7.1 12.2 11.2 NZ9000 (pNJFQIAI) 8.1 6.5 11.7 9.5 WA2-67 (pMG36c) 12.6 20.5 13.7 21.7 WA2-67 (pJFAI) 12.8 20.4 14.0 21.8 WA2-67 (pJFQI) 13.6 21.3 15.6 23.2 WA2-67 (pJFAIQI) 12.7 20.1 13.8 21.7 WA2-67 (pJFQIAI) 14.8 23.0 16.9 25.4 WA2-67 (pNZ8048c) 12.3 20.5 13.6 21.3 WA2-67 (pNJFAI) 12.7 20.1 13.8 21.7 WA2-67 (pNJFQI) 12.2 20.8 14.0 22.2 WA2-67 (pNJFQIAI) 12.3 20.3 13.8 22.0 L. lactis subsp. lactis DPC5598 (pMG36c) 7.2 9.0 13.7 20.0 DPC5598 (pJFAI) 7.6 8.7 13.5 19.4 DPC5598 (pJFQI) 7.5 8.9 13.6 19.7 DPC5598 (pJFAIQI) 6.8 7.6 12.8 18.0 DPC5598 (pJFQIAI) 6.2 6.5 11.9 16.7 DPC5598 (pNZ8048c) 7.6 9.5 14.0 20.6 DPC5598 (pNJFAI) 7.8 9.1 14.5 21.3 DPC5598 (pNJFQI) 7.3 9.4 14.8 22.0 DPC5598 (pNJFQIAI) 6.8 8.6 12.5 19.1 BB24 (pMG36c) 7.9 9.7 12.4 18.6 BB24 (pJFAI) 9.9 10.0 14.5 18.3 BB24 (pJFQI) 9.4 13.4 14.6 20.5 BB24 (pJFAIQI) 9.7 13.8 14.2 19.9 BB24 (pJFQIAI) 9.6 13.9 14.3 20.2 BB24 (pNZ8048c) 8.5 10.1 13.0 18.7 BB24 (pNJFAI) 10.3 13.7 15.0 19.3 BB24 (pNJFQI) 10.7 14.2 15.1 20.4 BB24 (pNJFQIAI) 10.2 14.6 15.0 20.0 a Direct antimicrobial activity as determined by a stab-on-agar test (SOAT) and b extracellular antimicrobial activity as determined by an agar diffusion test (ADT). Both are expressed as halos of growth inhibition (diameter in mm). Most of the data are means from two independent determinations in triplicate. Control strains are in bold. (-)--no activity. foods-12-01063-t003_Table 3 Table 3 Antimicrobial activity a of supernatants from recombinant L. lactis strains transformed with pMG36c-derived plasmids against virulent L. garvieae strains. Strain L. garvieae CF00021 CF01144 CLG4 CLG5 CLFP28/06 JIP29/99 L. lactis subsp. cremoris NZ9000 (pMG36c) (-) (-) (-) (-) (-) (-) NZ9000 (pJFAI) 88 90 76 69 88 85 NZ9000 (pJFQI) 98 143 112 106 97 100 NZ9000 (pJFAIQI) 121 169 151 153 149 140 NZ9000 (pJFQIAI) 126 145 101 167 107 108 WA2-67 (pMG36c) 2199 1035 1148 391 1087 521 WA2-67 (pJFAI) 2276 1469 1920 475 1566 744 WA2-67 (pJFQI) 11,798 11,082 5935 4201 8864 4821 WA2-67 (pJFAIQI) 2193 1749 1825 468 1637 847 WA2-67 (pJFQIAI) 150,033 19,571 28,362 6780 33,114 9412 L. lactis subsp. lactis DPC5598 (pMG36c) 1808 1271 1865 139 1042 855 DPC5598 (pJFAI) 1529 1326 2133 198 1318 960 DPC5598 (pJFQI) 1770 1338 1976 129 1288 1066 DPC5598 (pJFAIQI) 1096 1068 1312 92 1064 905 DPC5598 (pJFQIAI) 1033 659 1489 81 1055 815 BB24 (pMG36c) 1123 790 443 115 1479 514 BB24 (pJFAI) 2385 2480 1617 203 2036 1105 BB24 (pJFQI) 2532 2530 1725 202 3115 1243 BB24 (pJFAIQI) 2238 2756 1786 204 2615 1459 BB24 (pJFQIAI) 2535 2699 1641 196 3166 1317 a Antimicrobial activity as determined by a microtiter plate assay (MPA) and expressed in bacteriocin units per milligram cell dry weight (BU/mg cdw). Most of the data are means from two independent determinations in triplicate. Control strains are in bold. (-)--no activity. foods-12-01063-t004_Table 4 Table 4 Antimicrobial activity a of supernatants from recombinant L. lactis strains transformed with pNZ8048c-derived plasmids against virulent L. garvieae strains. Strain L. garvieae CF00021 CF01144 CLG4 CLG5 CLFP28/06 JIP29/99 L. lactis subsp. cremoris NZ9000 (pNZ8048c) (-) (-) (-) (-) (-) (-) NZ9000 (pNJFAI) 1126 997 1440 1295 1600 1263 NZ9000 (pNJFQI) 1214 1069 1395 1194 1440 1220 NZ9000 (pNJFQIAI) 1051 1188 1297 1167 1541 1255 WA2-67 (pNZ8048c) 1668 1002 897 364 987 369 WA2-67 (pNJFAI) 1853 989 1000 412 902 385 WA2-67 (pNJFQI) 2150 1351 1237 565 1163 486 WA2-67 (pNJFQIAI) 2021 1223 1149 595 1245 491 L. lactis subsp. lactis DPC5598 (pNZ8048c) 2123 1258 2317 198 1097 1096 DPC5598 (pNJFAI) 2760 2699 3443 317 1610 1770 DPC5598 (pNJFQI) 2605 1496 2334 266 1499 1492 DPC5598 (pNJFQIAI) 1150 880 1800 98 1480 920 BB24 (pNZ8048c) 1203 693 397 158 1022 685 BB24 (pNJFAI) 3398 3102 2340 339 2989 1597 BB24 (pNJFQI) 3705 3663 2732 397 4172 1603 BB24 (pNJFQIAI) 3502 3375 2541 299 5016 2001 a Antimicrobial activity as determined by a microtiter plate assay (MPA) and expressed in bacteriocin units per milligram cell dry weight (BU/mg cdw). Most of the data are means from two independent determinations in triplicate. Control strains are in bold. (-)--no activity. foods-12-01063-t005_Table 5 Table 5 Purification of NisZ and GarQ produced by L. lactis subsp. cremoris WA2-67 (pJFQI) and purification of NisZ, GarA and GarQ produced by L. lactis subsp. cremoris WA2-67 (pJFQIAI). Purification Stage Volume (mL) Total A254 a Total Antimicrobial Activity (BU) b Specific Antimicrobial Activity (BU/A254) c Increase in Specific Antimicrobial Activity (Fold) d Recovery Antimicrobial Activity (%) L. lactis subsp. cremoris WA2-67 (pJFQI) Culture supernatant 1000 30,500 10.6 x 106 347 1 100 Ammonium sulfate precipitation 100 1930 12.3 x 106 6370 18 116 Gel filtration chromatography 185 872 2.1 x 106 2410 7 20 Cation-exchange chromatography 50 75 11.3 x 106 150,670 434 107 Hydrophobic-interaction chromatography 15 8.4 1.0 x 106 119,050 343 9 Reversed-phase chromatography Fraction 8 0.300 0.325 50.0 x 103 153,850 443 0.5 Fraction 14 0.400 0.056 2.3 x 103 41,070 118 0.02 L. lactis subsp. cremoris WA2-67 (pJFQIAI) Culture supernatant 1000 28,400 1.4 x 108 4930 1 100 Ammonium sulfate precipitation 100 1510 1.5 x 109 993,380 201 1071 Gel filtration chromatography 185 832 2.3 x 108 276,440 56 164 Cation-exchange chromatography 50 119 1.8 x 109 15,130 3 1286 Hydrophobic-interaction chromatography 15 13.8 16.1 x 106 1,166,670 237 11.5 Reversed-phase chromatography Fraction 7 0.300 0.125 21,400 171,200 35 0.015 Fraction 9 0.450 0.218 2200 10,100 2 0.0016 Fraction 12 0.500 0.040 200 5000 1 0.00014 a Absorbance at 254 nm (A254) multiplied by the volume in milliliters. b Antimicrobial activity in bacteriocin units per milliliter (BU/mL), determined by an MPA against L. garvieae CF00021 and multiplied by the total volume in milliliters. c Specific antimicrobial activity expressed as the total antimicrobial activity (BU) divided by the total A254. d Specific antimicrobial activity of a fraction (BU/A254) divided by the specific antimicrobial activity of the initial culture supernatant (BU/A254). foods-12-01063-t006_Table 6 Table 6 Peptide fragments identified by MRM-LC-ESI-MS/MS (QTRAP) in eluted purified fractions from supernatants of L. lactis subsp. cremoris WA2-67 (pJFQI) and L. lactis subsp. cremoris WA2-67 (pJFQIAI). Strain Fraction Peptide Sequence Precursor MW Detected m/z Retention Time Detected Transitions MS/MS Confirmation L. lactis subsp. cremoris WA2-67 (pJFQI) 14 GarQ EYHLMNGANGYLTR 1638.76 546.92 (+3) 20.1 4 + VNGKYVYR 998.54 499.77 (+2) 8.7 4 + WA2-67 (pJFQIAI) 9 GarQ EYHLMNGANGYLTR 1638.76 546.92 (+3) 21.3 4 + VNGKYVYR 998.54 499.77 (+2) 10.4 4 + 12 GarA GKINQYRPY 1138.60 569.8 (+3) 14.7 4 + INQYRPY 953.48 477.24 (+2) 15.6 5 + Amino acid sequence of GarQ: EYHLMNGANGYLTRVNGKYVYRVTKDPVSAVFGVISNGWGSAGAGFGPQH and GarA: IGGALGNALNGLGTWANMMNGGGFVNQWQVYANKGKINQYR. PY. Lysine (K) and arginine (R) residues for hydrolysis by trypsin, in bold. +, positive confirmation. 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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PMC10000436 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050936 diagnostics-13-00936 Review Precision Medicine for Chronic Endometritis: Computer-Aided Diagnosis Using Deep Learning Model Mihara Masaya 1 Yasuo Tadahiro 2 Kitaya Kotaro 1* Carmina Enrico Academic Editor 1 Infertility Center, Kouseikai Mihara Hospital/Katsura Mihara Clinic, Kyoto 615-8227, Japan 2 Department of Obstetrics and Gynecology, Otsu City Hospital, Otsu 520-0804, Japan * Correspondence: [email protected] 01 3 2023 3 2023 13 5 93601 2 2023 15 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 ). Chronic endometritis (CE) is a localized mucosal infectious and inflammatory disorder marked by infiltration of CD138(+) endometrial stromal plasmacytes (ESPC). CE is drawing interest in the field of reproductive medicine because of its association with female infertility of unknown etiology, endometriosis, repeated implantation failure, recurrent pregnancy loss, and multiple maternal/newborn complications. The diagnosis of CE has long relied on somewhat painful endometrial biopsy and histopathologic examinations combined with immunohistochemistry for CD138 (IHC-CD138). With IHC-CD138 only, CE may be potentially over-diagnosed by misidentification of endometrial epithelial cells, which constitutively express CD138, as ESPCs. Fluid hysteroscopy is emerging as an alternative, less-invasive diagnostic tool that can visualize the whole uterine cavity in real-time and enables the detection of several unique mucosal findings associated with CE. The biases in the hysteroscopic diagnosis of CE; however, are the inter-observer and intra-observer disagreements on the interpretation of the endoscopic findings. Additionally, due to the variances in the study designs and adopted diagnostic criteria, there exists some dissociation in the histopathologic and hysteroscopic diagnosis of CE among researchers. To address these questions, novel dual immunohistochemistry for CD138 and another plasmacyte marker multiple myeloma oncogene 1 are currently being tested. Furthermore, computer-aided diagnosis using a deep learning model is being developed for more accurate detection of ESPCs. These approaches have the potential to contribute to the reduction in human errors and biases, the improvement of the diagnostic performance of CE, and the establishment of unified diagnostic criteria and standardized clinical guidelines for the disease. chronic endometritis computer-aided diagnosis convolutional neural network deep learning fluid hysteroscopy This research received no external funding. pmc1. Introduction Chronic endometritis (CE) is a localized infectious and inflammatory disorder of the uterine lining . The major cause of CE is considered to be intrauterine infections by microorganisms frequently found in the urogenital areas, such as common bacteria (Streptococcus species, Staphylococcus species, Escherichia coli, and Enterococcus faecalis), Mycobacterium tuberculosis, Mycoplasma species, and Ureaplasma species. Antibiotic treatment against these microorganisms is effective to eradicate endometrial stromal plasmacytes (ESPCs), the landmark immunocompetent cells in this pathology. CE is drawing interest because of its association with female infertility of unknown etiology, endometriosis, repeated implantation failure following in vitro fertilization-embryo transfer cycles, and recurrent pregnancy loss as well as several obstetric complications (preeclampsia and preterm labor) and neonatal diseases in premature infants (periventricular leukomalacia and cerebral palsy) . In contrast to acute endometritis, which manifests with intense symptoms such as pelvic pain, vaginal discharge, and systemic fever, CE is generally so asymptomatic or oligosymptomatic that it is often overlooked by affected patients and even by experienced gynecologists . Given that the clinical course of CE, including onset, progress, and remission remains largely unknown, there are some controversies over the term "chronic" to describe this pathologic condition . Currently, no universally accepted diagnostic criteria or clinical guidelines exist for CE. The diagnosis of CE has long relied on somewhat painful endometrial biopsy and histopathologic examinations combined with immunohistochemistry for CD138 (IHC-CD138), an ESPC marker also known as transmembrane heparan sulfate proteoglycan syndecan-1 . With IHC-CD138 only, however, CE may be potentially over-diagnosed by misidentification of endometrial epithelial cells, which constitutively express CD138, as ESPCs . Fluid hysteroscopy is emerging as an alternative, less-invasive diagnostic tool that can visualize the whole uterine cavity in real-time and enables the detection of several unique mucosal findings associated with CE. Meanwhile, the serious biases in the hysteroscopic diagnosis of CE are the inter-observer and intra-observer disagreements over the interpretation of the endoscopic findings . Thus, each of these two diagnostic methods has its strengths and weaknesses. Additionally, in past studies, examiners set the definitions of CE according to their original standards or preferences, resulting in so many variances from one study to another. Some dissociation thereby exists in the histopathologic and hysteroscopic diagnosis of CE among researchers . The optimization within individual diagnostic tools and integration between multiple diagnostic tools are craved for the establishment of standardized diagnostic criteria and/or unified clinical guidelines for CE. One promising diagnostic tool for IHC is dual immunohistochemistry for CD138 and another potential ESPC marker multiple myeloma oncogene 1 (MUM-1), which are currently being tested. Artificial intelligence is being actively introduced into the medical field . Deep learning is an artificial intelligence model that is intensively studied due to its well-fitting into medical image analysis. The advantage and value of the deep learning models in the situation of the clinical diagnosis are that the output can provide the probability of the disease, contrary to physicians being able to give only two judgments (presence or absence) . Indeed, deep learning models have been shown to reduce errors and increase the accuracy and precision in the medical image diagnosis made by physicians . Computer-aided diagnosis (CADx) using a deep learning model is being carried out for more accurate detection of ESPCs. These approaches have the potential that contributes to improving the diagnostic performance of CE and help us establish standardized diagnostic criteria and unified clinical guidelines for the disease. This article aimed to introduce some novel approaches for potential solutions to some questions on CE and give insights into precision medicine for women suffering from this disease. 2. Unsolved Questions on Histopathologic CE As a localized mucosal inflammatory disease, the combination of endometrial biopsy and histopathology, along with immunohistochemistry, have been traditionally prioritized and emphasized as the diagnostic method of CE. The histopathologic features of CE contain superficial edema, increased stromal density, unsynchronized differentiation between endometrial epithelium and stroma, and infiltration of CD138(+) ESPCs. Of them, the most specific and sensitive finding of CE is the presence of multiple ESPCs . These lymphoid cells are found in the endometrial stroma as scattered or clustered cells in CE. Antibiotic treatment is effective in the eradication of ESPCs in the affected infertile women, although it awaits further studies to determine if the histopathologic cure of CE improves the reproductive outcomes in the following infertility treatment cycles in these women . Under a light microscope, typical plasmacytes are described as large-sized lymphocytes with a high nuclear-cytoplasmic ratio, basophilic cytoplasm, and eccentric nucleus with heterochromatin rearrangement ("spoke-wheel" or "clock-face" pattern). But several types of endometrial cells, including natural killer cells, macrophages, and stromal fibroblasts, present a morphological appearance that is close to ESPCs . It is therefore very demanding and time-consuming to identify ESPCs by classical histopathologic examinations only. The introduction of IHC-CD138 significantly contributed to the development of the histopathologic diagnosis of CE with marked improvement of sensitivity (100% vs. 75%, IHC-CD138 vs. conventional tissue staining with hematoxylin/eosin or methyl green), specificity (100% vs. 65%, IHC-CD138 vs. conventional tissue staining), inter-observer variability (96% vs. 68%, IHC-CD138 vs. conventional tissue staining), and intra-observer variability (93% vs. 47%, IHC-CD138 vs. conventional tissue staining) . Despite the application of IHC-CD138 and its spread in the clinical diagnosis of CE, there are some precautions for use. First, CD138 is constitutively expressed not only in ESPCs but also in endometrial surface/glandular epithelial cells, especially on the basolateral sides. The currently available primary antibodies against CD138 also react to the epitope of CD138 both on ESPCs and endometrial epithelial cells. Although the immunoreactive intensity in endometrial epithelial cells is generally weaker than that in ESPCs, the conditions of the section preparation potentially cause the misidentification of endometrial epithelial cells as ESPCs, overestimation of ESPCs, and overdiagnosis of CE . One of the potential risks of the over-diagnosis of CE is the overtreatment of infertile women using antibiotic agents. Multi-drug resistance is a serious global medical problem in the antibiotic treatment of infectious diseases. Antibiotic resistance is unexceptionally increasing in CE. In 2008, Cicinelli et al. reported that <20% of CE was ineffective to single oral doxycycline treatment, whereas their update in 2015 demonstrated that multiple courses of antibiotic treatments failed to cure CE in 24.6% of the affected women, implicating the increment of multi-drug resistant CE . In a retrospective/prospective survey from 2010 to 2020, we investigated the prevalence of antibiotic resistance in CE in a series of infertile women with a history of repeated implantation failure in three or more failed in vitro fertilization-embryo transfer cycles . The prevalence of CE in the cohort did not change conspicuously for the ten years (30.2% from April 2010 to March 2015 vs. 31.7% from April 2015 to March 2020). The resistance (failed eradication of ESPCs) to the first-line 200 mg/day, 14-day oral doxycycline administration was observed in 21.2% of whole CE cases. Meanwhile, the prevalence of multi-drug resistant CE (regarded as the ineffectiveness of the first-line doxycycline and 14-day oral second-line metronidazole 500 mg/day and ciprofloxacin 400 mg/day treatment) in the whole CE cases was 8-fold higher in the latter five years (9.6% between April 2015 and March 2020) than in the earlier five years (1.3% between April 2010 and March 2015). In some women, we performed microbiome analysis in the vaginal and uterine cavities to seek the potential pathogens associated with multi-drug resistance in CE. However, any unique microbial genera/species and/or bacterial communities were not identified in the microbiota of their paired endometrial fluid and vaginal secretions . These findings indicate the difficulty in the antibiogram designs and the choices of the third-line antibiotic agents for infertile women with multi-drug resistant CE. Second, IHC-CD138 is not yet technically standardized for human endometrial tissue. The histopathologic diagnosis of CE may be influenced by multiple laboratory factors, such as the dilutions and incubation periods of the primary antibodies and the secondary detection systems, and the thickness, area, and number of the fields and/or sections evaluated for the detection of ESPCs. Indeed, it was shown that the choices for clones (B-B4 versus B-A38) and dilutions (1:1000 vs. 1:100 dilution of clone B-B4) of the primary antibodies brought about the differences in the diagnostic rates (more than 9% estimated difference) of histopathologic CE . Moreover, the method and device of the endometrial biopsy can affect the diagnostic performance of histopathologic CE. ESPCs tend to form focal accumulation in the endometrial stromal compartments rather than homogeneous distribution. In addition, in some women with CE, ESPCs accumulate in the endometrial basal layer (the part that is not shed during menstruation) only . Thus, ESPCs may be missed under observation within the small areas of the endometrial biopsy specimens . IHC-CD138 using the "whole-wall" endometrial curettage may elevate the chance to detect ESPCs, but this method can pose serious harm to women desiring pregnancy, causing endometrial thinning and intrauterine adhesions/Asherman's syndrome that can reduce their endometrial receptivity, along with some life-threatening gestational complications such as ectopic pregnancy and placenta accreta spectrum disorder . 3. CADx Using Deep Learning Model for Unsolved Questions on Histopathologic CE While deep learning has been long utilized for the histopathologic diagnosis of the images of the specimens with conventional tissue staining, its application to IHC images is yet under development. Using a newly constructed framework, Zhang et al. found that a deep learning model (entitled Global Scanner subnetwork) is capable of detecting CD138(+) ESPCs that are distributed sparsely in the endometrial stromal components effectively and efficiently as well as predicting the location map of CD138(+) ESPCs quickly in the whole slide images. In addition, they proposed a novel grid-oversampling strategy for the solution of the sample imbalance problems in preprocessing whole slide images. MUM1 (also known as interferon regulatory factor 4) is a transcription factor expressed at the late plasmacyte-directed stages of B cell differentiation . MUM1 is a promising ESPC marker that may be equivalent or possibly superior to CD138. Using a combination of IHC-CD138, IHC for MUM1 (IHC-MUM1), and conventional hematoxylin and eosin staining, Parks et al. evaluated the presence of ESPCs in 311 endometrial biopsy specimens. While CD138 identified ESPCs in 15%-23%, MUM1 detected ESPCs in 48% of the samples with minor background staining, resulting in MUM1 as a more sensitive ESPC marker than in CD138. Meanwhile, Cicinelli et al. showed that both the sensitivity and specificity in the detection of ESPCs were higher in IHC-CD138 than in IHC-MUM1, but IHC-MUM1 scored a higher inter-observer agreement value compared with IHC-CD138. The concomitant use of IHC-CD138 and IHC-MUM1 may thereby potentially make up for the shortcomings of each method in the histopathologic diagnosis of CE. Recently, Jiang et al. tested the feasibility of dual immunohistochemistry for these two plasmacyte markers for the detection of ESPCs. They found that CD138(+)/MUM1(+) ESPCs can be distinguished from false-positive cells that are immunoreactive to CD138 alone (14%) or MUM1 alone (24%). When the histopathologic CE was defined as 5 or more CD138(+)/MUM1(+) ESPCs per section, all of the sensitivity, specificity, and accuracy, of its diagnosis reached 100%. Interestingly, they further developed and trained an artificial intelligence system for the automatic identification of CD138(+)/MUM1(+) ESPCs and the diagnosis of histopathologic CE. To reduce the values of the false positive rates and improve the precision, they adopted the deep learning model that comprised the cascades of a high-performance anchor-free version of you-look-only-once (YOLOX), residual neural network-18 (ResNet18), and extreme gradient boosting (XGBoost) classifiers . The digitally photographed images of immunostained endometrial specimens were cropped using a sliding window. Following the discovery of the valid areas in the whole slide images using the Otsu algorithm , the images were entered into a trained YOLOX-s. A total of 2000 regions of interest in the whole slide images were chosen, and 1308 patches containing ESPCs were manually annotated with bounding boxes. After the mean precision value of 0.51 was yielded in the testing data set, the patches containing ESPCs and those not containing ESPCs were further processed for the training of the ResNet18 model as a post-processing module and XGBoost using the extracted shape, color, and texture features of ESPCs. Compared with the review results of the experienced pathologists, their deep learning model achieved sensitivity, specificity, and accuracy rates of 100%, 83.3%, and 91.4%, respectively, for the histopathologic diagnosis of CE. XGBoost is an optimized distributed gradient-boosting library with a binary decision tree (yellow and blue dots) of algorithms that implement machine learning under the Gradient Boosting Decision Tree framework . The residual from tree-1 is fed to tree-2 to decrease both the residual and onward. Distinct from Random Forest, each tree model in XGBoost minimizes the residual from its previous tree model. XGBoost performs the second-order Taylor expansion of the cost function and uses both the first and second derivatives. ResNet is a deep residual neural network that replaces convolutional layers and pooling layers in a convolutional neural network (CNN) with fully connected layers . It contains an input layer, an output layer, and in-between three sets of one dense block and two identity blocks with three hidden dense layers in both blocks. While the input is also connected to the output via another dense layer in a dense block, it is directly connected to the identity blocks. YOLOX is a real-time object detection system characterized by the adoption of the decoupled head to improve the conflict between classification and regression tasks. For each level of the feature pyramid network, one 1 x 1 convolutional layer was adopted to reduce the feature channel to 256. Two parallel branches and 3 x 3 convolutional layers were then added for classification and regression tasks, respectively. The Intersection Over Union (IOU) branch was added to the regression branch . These findings indicate the superiority of the dual IHC-CD138/MUM-1 to the single IHC-CD138 and the possibility of the clinical application of the deep learning model to the histopathologic diagnosis of CE. In addition, the development of deep learning models holds promise for the determination of the threshold/cut-off ESPC density to define histopathologic CE, which is another unsolved question in female infertility. 4. Unsolved Questions on Hysteroscopic CE Fluid hysteroscopy is a handy and versatile diagnostic modality that can be performed in office gynecologic practice. Fluid hysteroscopy has been broadly utilized for real-time detection of female infertility-associated uterine cavity lesions, such as endometrial polyps, submucosal fibroids, intrauterine adhesions/Asherman's syndrome, and uterine septum. Recent studies focus on the application of fluid hysteroscopy for endoscopic diagnosis of CE, instead of rather painful and hemorrhagic endometrial biopsy/suction and time-consuming histopathologic diagnosis/microbial analysis . Thus, fluid hysteroscopy is expected to be a promising diagnostic tool that works both for infertile couples and reproductive endocrinologists if it can visually define and accurately identify the lesions with CE. In 2019, based on the two rounds of the systematic review of the selected articles and the Delphi poll agreement, the diagnostic criteria for hysteroscopic CE were proposed by the International Working Group for Standardization of Chronic Endometritis Diagnosis as follows :(1) strawberry aspect: localized/scattered large hyperemic endometrial areas flushed with white central points , (2) focal hyperemia, (3) hemorrhagic spots: focal lurid endometrium with sharp and irregular borders possibly in continuity with capillary, (4) micropolyposis: a cluster of typically less than 1 mm-sized protrusions on the focal or entire surface with a distinct connective vascular axis , (5) stromal edema: the thick and pale appearance of the endometrium in the proliferative phase originating from the stroma (a nonpathologic finding that is observed during the secretory phase). Of these five hysteroscopic features, endometrial micropolyposis is the finding that endoscopists can easily visualize. Endometrial micropolyposis is attracting attention with the anticipation that suggesting the presence of histopathologic CE with the highest probability. In a retrospective study, Cicinelli et al. first assessed the relationship between endometrial micropolyposis and histopathologic CE. While Endometrial micropolyposis was identified in a total of 11.7% of 820 women undergoing fluid hysteroscopy, histopathologic CE was detected in 93.7% of these women with endometrial micropolyposis. By contrast, histopathologic CE was less frequently identified in women without evident endometrial micropolyposis (10.8%), resulting in a very high prevalence of histopathologic CE in women with endometrial micropolyposis (odds ratio 124.2, confidence interval 50.3-205.4). In addition, endometrial micropolyposis is unexceptionally associated with other findings suggesting the presence of hysteroscopic CE, such as stromal edema and focal hyperemia. Meanwhile, endometrial micropolyposis was observed in 53.6% of women with histopathologic CE. The sensitivity, specificity, positive predictive values, negative predictive values, and diagnostic accuracy of the endometrial micropolyposis for the presence of histopathologic CE were 54%, 99%, 94%, 89%, and 90%, respectively. In another retrospective study that enrolled 910 women with a history of abnormal uterine bleeding, the same research group further demonstrated that the positive and negative predictive values rose to 98.4% and 94.5%, respectively, if fluid hysteroscopy detected the triad of endometrial micropolyposis, stromal edema, and focal (or diffuse) hyperemia . Similarly, Zolghadri et al. also reported the association between the findings of hysteroscopic CE and those of histopathologic CE, with a higher sensitivity (98.4%) and negative predictive values (97.82%), but the specificity (56.23%) and positive predictive values (63.5%) of the combination of the two hysteroscopic CE findings (endometrial micropolyposis and hyperemia) for histopathologic CE were lower. These results implicate that the likelihood of histopathologic CE is quite high if endometrial micropolyposis is identified in fluid hysteroscopy, whereas substantial proportions of women with histopathologic CE do not present the findings of endometrial micropolyposis. The limitation and biases of these studies were that the diagnosis of histopathologic CE relied on the sole classical histomorphological findings including superficial stromal edema, increased stromal density, and pleomorphic stromal lymphocyte infiltrates, along with the detection of ESPCs based on conventional tissue staining using hematoxylin and eosin only. Using more sensitive and specific IHC-CD138 based on the detection of CD138(+) ESPCs, the estimated diagnostic accuracy of endometrial micropolyposis (alone or in combination with other hysteroscopic findings) under the fluid hysteroscopy for prediction of the presence of histopathologic CE is calculated as 60-70% , although some variances are seen between the studies. In addition, the limitation and potential biases in these studies were the retrospective design. In a prospective study that enrolled 94 women with a history of repeated implantation failure or recurrent pregnancy loss, it was demonstrated that endometrial micropolyposis, stromal edema, and hyperemia often coexist within an individual and these three hysteroscopic features are predominant as the suggestive findings of histopathologic CE . These findings were also confirmed in a meta-analysis . Recently, Wang et al. performed a unique study that included infertile women before proceeding to their first in vitro fertilization-embryo transfer treatment cycle. Both fluid hysteroscopy and endometrial biopsy/IHC-CD138 were performed in succession on the same day in the proliferative phase. The presence of one or more endoscopic findings of endometrial focal hyperemia/strawberry aspect, micropolyposis, and/or stromal edema was regarded as hysteroscopic CE, whereas the infiltration of >=5 CD138(+) ESPCs in 1 HPF (= >=50 CD138(+) ESPCs in 10 HPFs) was defined as histopathologic CE in this study. Serum concentrations were measured for pituitary hormones and ovarian steroids in the identical cycle. In infertile women with endometrial focal hyperemia/strawberry aspect, progesterone and basal follicle-stimulating hormone concentrations were significantly lower than in those with endometrial micropolyposis and/or stromal edema. On the contrary, in infertile women with endometrial focal hyperemia/strawberry aspect, body mass index and other serum markers (testosterone, anti-Mullerian hormone, and serum basal luteinizing hormone concentrations) were significantly higher than in those with endometrial micropolyposis and/or stromal edema. These findings indicate a close association between endometrial focal hyperemia/strawberry aspect and polycystic ovarian syndrome. Additionally, endometrial focal hyperemia/strawberry aspect was seen more frequently in women with primary infertility than in those with endometrial micropolyposis and/or stromal edema, which were more prevalent in women with secondary infertility. These findings implicate that infertile women with a history of previous pregnancies are more likely to have endometrial micropolyposis and/or stromal edema. Thus, the presence of the conceptus in the uterine cavity may potentially increase the risk of local microbial infection. Moreover, the prevalence of histopathologic CE was much lower in the endometrial focal hyperemia/strawberry aspect group (10.1%) than in the endometrial micropolyposis group (63.2%) and endometrial stromal edema group (74.0%), indicating that the occurrence of histopathologic CE significantly differs depending on the features of hysteroscopic CE. In addition, the lower prevalence of histopathologic CE in the focal hyperemia/strawberry aspect group than in the other two groups implicates the low positive predictive value of endometrial focal hyperemia/strawberry aspect for histopathologic CE. Furthermore, the researchers further compared the hysteroscopic CE findings before and after a 14-day, 200 mg/day oral doxycycline administration cycle. . The total cure rate of hysteroscopic CE in the second-look fluid hysteroscopy performed in the proliferative phase in the next cycle (3-5 days after the cessation of the menstrual bleeding) was 75.82% (207/273). The cure rate of endometrial micropolyposis and stromal edema were 73.6% and 83.2%, respectively, but none in the endometrial focal hyperemia/strawberry aspect group were improved despite the antibiotic treatment. Collectively, judging by these findings, the endometrial focal hyperemia/strawberry aspect, the findings that are more prevalent in women with polycystic ovarian syndrome than in those with other infertility etiologies, may not represent the definitive endoscopic signs of CE. Taken together, if endometrial micropolyposis is identified on fluid hysteroscopy, the likelihood of histopathologic CE is considerably high. Meanwhile, a substantial proportion of histopathologic CE does not present endometrial micropolyposis. If other features of hysteroscopic CE are accompanied by endometrial micropolyposis, the predictive accuracy for the histopathologic CE rises significantly . On the other hand, the predictive value of classical endometrial polyps for histopathologic CE remains controversial. Further studies are essential to draw a conclusion regarding this question. 5. CADx Using Deep Learning Model for Unsolved Questions on Hysteroscopic CE One of the clinical problems of the hysteroscopic diagnosis of CE is that the interpretation of the findings by gynecologists tends to be subjective . The accuracy of the fluid hysteroscopic CE findings to predict histopathologic CE based on IHC-CD138 is moderate (accuracy 60-70%) as aforementioned. To minimize these kinds of human biases/errors, CADx systems using deep learning models are being actively introduced into gynecologic practice in parallel with other medical fields. For example, using a convolutional neural network (CNN) and visual attention mechanisms, Sun et al. first developed a CADx system using a deep learning model, entitled HIENet, which can classify the photographic images of the hematoxylin and eosin-stained endometrial tissue preparations into four categories (normal endometrium, endometrial polyp, endometrial hyperplasia, and endometrial adenocarcinoma). Following the testing, training, and cross-validation, the model achieved an accuracy of 84.5% as well as an area under the curve value of 0.9829 with 77.97% sensitivity and 100% specificity. This deep learning model finally outperformed three expert pathologists and five existing CNN-based classifiers. Meanwhile, Zhang et al. reported the establishment of the CNN-based deep learning model that is capable of the automatic classification of the endometrial lesions presented by hysteroscopic image inputs. The accuracy of the model in the five-category classification of endometrial lesions was 80.8 with a sensitivity and specificity of 84.0% and 92.5% for endometrial hyperplasia without atypia, 68.0% and 95.5% for atypical hyperplasia, 78.0% and 96.5% for endometrial cancer, 94.0% and 95.0% for endometrial polyp, and 80.0% and 96.5% for submucosal fibroids, respectively. In the task of classifying the lesions into two categories (benign or premalignant/malignant), the model achieved 90.8% accuracy, 83.0% sensitivity, and 96.0% specificity, respectively. Again, this model outperformed multiple experienced gynecologists. Thus, they concluded that the mode is able to support gynecologists to improve the overall accuracy of the diagnosis of endometrial lesions. Furthermore, Takahashi et al. demonstrated a CNN-based automatic hysteroscopic image analysis model that distinguishes endometrial cancer lesions from normal endometrium. Compared with the standard diagnostic method (78.91-80.93%), the model employing the proposed continuity analysis (83.94-89.13%) and the combination of the three neural networks (90.29%) obtained higher accuracy, with the high scores of the corresponding sensitivity and specificity 91.66% and 89.36%, respectively. Given the recent prominent progress in hysteroscopic image analysis, the CADx systems using deep learning models have the potential enough to be utilized for hysteroscopic prediction of the presence or absence of histopathologic CE. We launched a study to construct a CNN-based deep learning model for the prediction of histopathologic CE in infertile women using archival fluid hysteroscopic images. As the first step, we trained the model with Visual Geometry Group (VGG)-16 to detect endometrial micropolyposis . A portion of archival hysteroscopic images was randomly selected for testing and validation, whereas another portion was used for data augmentation and model training. The training accuracy and validation accuracy of the model gradually increased and reached a plateau over 105 and 90 epochs, respectively. The value for the area under the curve for diagnosing endometrial micropolyposis exceeded 0.90 (as of 6 November 2022) which was at a similar level with several experienced gynecologists (according to the comparison using the DeLong test ). As our model seems to be feasible for the detection of endometrial micropolyposis in hysteroscopic image analysis, we are proceeding to the next steps to test and train the model for the prediction of the cases without endometrial micropolyposis but with histopathologic CE, those with endometrial micropolyposis but without histopathologic CE, and those with other hysteroscopic CE findings and histopathologic CE. VGG16 is developed by the Oxford Visual Geometry Group. VGG16 is composed of the convolution layers with a stride 1 and the same paddings and the max pooling layers with a stride 2, resulting in a total of 138 million parameters. One of its features is that all the convolutional kernels are of size 3 x 3 and max-pooling kernels are of size 2 x 2. This is in contrast to Alexnet, the winner of the ImageNet Large Scale Visual Recognition Challenge 2012, adopting several different sizes of kernels. The other is the implementation of the deeper sixteen layers, which doubles the eight layers of Alexnet. At the end of the stream of VGG, the data passes through the fully connected layers and rectified linear unit function [f(x) = x+ = max (0, x)], an activation function to separate specific excitation and unspecific inhibition. They were followed by the softmax function [(z)i = ezi/(ez1 + ez2 + ez3 + ... + ezK) for i (= 1, 2, 3,..., K) and z (= z1, z2, z3,..., zK)] for the normalization of the output of the CNN to a probability distribution over predicted classes based upon Luce's choice axiom . The model repeatedly iterates to reduce the cross-entropy loss to enhance accuracy. 6. Conclusions The negative impact of CE on reproductive outcomes in infertile women recently comes to light . The etiology and pathogenesis of CE are becoming clear with the expansion and development of research incorporating cellular and molecular biological approaches. Meanwhile, the cause-effect relationship between CE and female fecundity yet remains to be determined . Different studies so far adopted different definitions for CE. To get the right answers and solve the inconclusive questions on CE, the establishment of unified diagnostic criteria that integrated histopathology and hysteroscopy (along with microbiome analysis) is essential. To reach the goal, more studies with rigorous designs are indispensable to delineate the distinct boundaries between CE and non-CE cases, although the CADx systems using deep learning models are expected to help us establish the diagnostic criteria and standardize the clinical guidelines for this yet elusive disease and provide precision medicine for infertile women. Author Contributions Conceptualization, M.M., T.Y. and K.K.; formal analysis, K.K.; writing--original draft preparation, M.M. and K.K.; writing--review and editing, M.M., T.Y. and K.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 Schema of simplified architectures of XGBoost, Resnet18, and YOLOX. Figure 2 Basic architecture of VGG16 CNN model. 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. Cicinelli E. De Ziegler D. Nicoletti R. Colafiglio G. Saliani N. Resta L. Rizzi D. De Vito D. Chronic Endometritis: Correlation among Hysteroscopic, Histologic, and Bacteriologic Findings in a Prospective Trial with 2190 Consecutive Office Hysteroscopies Fertil. Steril. 2008 89 677 684 10.1016/j.fertnstert.2007.03.074 17531993 2. Moreno I. Cicinelli E. Garcia-Grau I. Gonzalez-Monfort M. Bau D. Vilella F. De Ziegler D. 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PMC10000437 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050922 foods-12-00922 Article Genetic-Phenotype Analysis of Bifidobacterium bifidum and Its Glycoside Hydrolase Gene Distribution at Different Age Groups Wei Xiaojing Writing - original draft Writing - review & editing 12 Yu Leilei Resources Visualization 123* Zhang Chuan Software 12 Ni Yongqing Writing - review & editing Funding acquisition 4 Zhang Hao Writing - review & editing Project administration Funding acquisition 123 Zhai Qixiao Resources 123 Tian Fengwei Writing - review & editing Project administration Funding acquisition 123 Cepeda Saez Alberto 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 National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China 4 School of Food Science and Technology, Shihezi University, Shihezi 832000, China * Correspondence: [email protected]; Tel./Fax: +86-510-85912155 22 2 2023 3 2023 12 5 92201 1 2023 18 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 ). Human gut microbiota interfere with host development and aging. Bifidobacterium is a microbial genus found in the human digestive tract that has probiotic activities such as improving constipation and enhancing immunity. The species and numbers present change with age, but there has been limited research on probiotic gut microbiota at specific ages. This study analyzed the distribution of 610 bifidobacteria in subjects in several age groups (0-17, 18-65, and 66-108 y) using 486 fecal samples and determined the distribution of glycoside hydrolases based on genetic analysis of strains representing 85% of the Bifidobacterium species abundance in each age group. 6'-Sialyllactose is a major component of acidic breast milk oligosaccharides, which can promote human neurogenesis and bifidobacteria growth. Using genotypic and phenotypic association analysis, we investigated the utilization of 6'-sialyllactose by six B. bifidum strains isolated from subjects 0-17 and 18-65 y. A comparative genomic analysis of the six B. bifidum strains revealed differences in genomic features across age groups. Finally, the safety of these strains was evaluated by antibiotic gene and drug resistance phenotype analysis. Our results reveal that the distribution of glycoside hydrolase genes in B. bifidum varies with age, thus affecting the phenotypic results. This provides important insights for the design and application of probiotic products for different ages. glycoside hydrolase (GH) Bifidobacterium bifidum 6'-sialyllactose comparative genomics genotype phenotype This research received no external funding. pmc1. Introduction Billions of bacteria colonize the human gut, with effects that are strongly linked to human health . Different microbial communities colonize different parts of the human body , and the most densely colonized body part is the intestinal tract . As humans age, the gut microbiota proceed through a series of phase changes. In early childhood, there is a dynamic gut microbial composition, while adults have a relatively stable flora, and the numbers of the intestinal microbiota in the elderly gradually decrease and health-promoting functions decline . There is a close association between age-related changes in immunity, dysbiosis, disease, and probiotic-based products, and utilizing this association in combating age-related disease is an attractive proposition . Some studies have proposed modifying the gut microbiome with live microbes, and clinical trials have demonstrated age-dependent beneficial effects of the consumption of LcZ . Given the importance and complexity of the gut microbiota, it is critical to gain an understanding of compositions, patterns, and the laws of intestinal microecology to better understand human health and disease. Intestinal physiological changes due to age-related factors have an inevitable impact on the structure of the gut microbiota. Bifidobacteria are dominant microorganisms colonizing the gut in early life, with a strong competitive advantage due to an ability to break down human milk oligosaccharides (HMOs) . The predominant Bifidobacterium species in the early infant gut is Bifidobacterium breve, along with B. bifidum and B. longum subsp. infantis . Macrogenomic sequencing revealed a high abundance of B. longum subsp. longum and B. pseudobulbarum in the gut of breastfed infants . With a decrease in breastfeeding and a gradual increase in solid food intake, the composition of the infant intestinal microbiota begins to shift toward that of the adult gut . The composition of Bifidobacterium species in the adult gut is more complex. Among the Bifidobacterium species present are B. longum subsp. longum, B. adolescentis, and B. catenulatum, as well as a lower-abundance B. bifidum and B. breve . The numbers of bifidobacteria in the intestinal microbiota of the elderly are generally lower than in that of non-elderly adults, and the diversity of bifidobacteria is significantly reduced primarily due to a loss of B. adolescentis, B. longum subsp. longum, and B. angulatum . Bifidobacterium uses non-digestive carbon sources and has cross-intertrophic effects on nutrients with other intestinal microbiota to maintain gut homeostasis. More than 13% of the genes in the bifidobacteria genome are involved in carbohydrate metabolism, with glycoside hydrolase being the most important component. Given the various glycoside hydrolases carried by different species, the types of carbohydrates in the gut have a significant impact on Bifidobacterium composition . Through the analysis of bacterial comparative genomics, the relationship between their genomic and phenotypic features can be determined, thus facilitating further examination of the related molecular mechanisms. The whole genome sequencing and bioinformatics analysis of B. bifidum PRL2010 published in PNAS in 2010 revealed the unique degradation and utilization mechanism of B. bifidum mucin oligosaccharides, helping people understand the unique mechanism of B. bifidum intestinal adaptation . Currently, the available bifidobacteria genome in the NCBI database allows us to conduct genomic analyses of strain evolutionary relationships, functional conservation, and variability. Arboleya et al. reported genomic data for B. longum, revealing a rich complement of glycosyl hydrolase genes leading to strong polysaccharide utilization ability. Using comparative genomics, Duranti et al. demonstrated a lack of genes for metabolism of host-derived polysaccharides (such as HMOs or mucin) in the B. adolescentis genome, explaining at a genetic level why B. adolescentis is abundant in the adult intestine. Using comparative genomic analysis, Lu et al. found that core enzymes isolated from B. bifidum strains from different ecological niches accounted at a molecular level for an ability to metabolize host-derived polysaccharides. In contrast to other Bifidobacterium species, B. bifidum has extracellular glycosidases that can degrade many host-derived glycans, including HMOs, glycan chains of high-molecular-weight glycoproteins, and glycosphingolipids . Sialic acids are constituents of HMOs and include sialyloligosaccharides such as 6'-sialyllactose (6'-SL) and 3'-SL as well as N-acetylneuraminic acid (Neu5Ac). These compounds play an important role in nerve development. The extracellular degradation of sialylated HMOs by B. bifidum JCM1254 is one example of a broader metabolic activity of bifidobacteria . B. bifidum not only utilizes polysaccharides in the gastrointestinal tract through its own GH activity but also benefits the growth of other microorganisms by breaking down polysaccharides into monosaccharides. Comparative studies of the genomes of B. bifidum strains require additional strains for validation. Existing studies on strain-age relationships are also limited. Various studies have shown that an imbalance in human intestinal bifidobacteria can have adverse effects on health. As the ability of bifidobacteria to metabolize host-derived carbon sources is the basis of their long-term colonization of the intestinal tract, it is critical to investigate the carbohydrate utilization abilities of bifidobacteria present at different stages of human life. The data obtained can be used as a reference for targeted intervention to assist the intestinal growth of Bifidobacterium and to provide new ideas for designing probiotic products for different age groups. There is a need to collect more genome-level information on Bifidobacterium and conduct in-depth comparative analyses to better understand the relationship between the intestinal microbiota, host age, and health. 2. Materials and Methods 2.1. Bacterial Screening The distribution of 610 bifidobacteria from three age groups in the strain library was counted (Table 1). Reference strains were from the food biotechnology research center of Jiangnan University. The collection of fecal samples was approved by the Ethics Committee of Jiangnan University, China (SYXK 2012-0002). Based on the occurrence of Bifidobacterium spp. in each age group, we selected strains representing a summed abundance of bifidobacteria in each age group of >85%, comprising five species each for the age 0-17 y and 18-65 y groups, and four species for the age 66-108 y group. Three bifidobacterial strains were selected at random for each species, comprising a total of 42 strains. Strains preserved at -80 degC were thawed and inoculated onto 2% mMRS culture medium and grown in an anaerobic incubator for 24-48 h. Purified single colonies were taken up in 0.1 mL medium, incubated for 48 h, then grown in mMRS liquid medium supplemented with 0.5% L-cysteine for 24-48 h. Samples (1 mL) were centrifuged (6000 rpm for 3 min). The supernatants were discarded, and pellets were washed twice with 1.5 mL sterile water. Pellets were resuspended in 1 mL sterile water, and samples were used as templates for strain identification. 16S rRNA PCR amplification was performed as previous reported . Amplified products were subjected to nucleic acid electrophoresis, and the single band on the agarose gel was excised and sent to GENEWIZ Co., Ltd. (South Plainfield, NJ, USA). for sequencing. 16S rDNA sequences were used for NCBI BLAST alignment. 2.2. Genomic DNA Extraction Strains were cultured in mMRS liquid medium at 37 degC for 24-48 h and then pelleted for genomic DNA extraction. Genomic DNA was extracted using a bacterial DNA extraction kit (Omega Bio-Tek, Norcross, GA, USA) following the manufacturer's instructions. The extracted genomic DNA was tested for quality using agarose gel electrophoresis (1% gel concentration), purity using a UV spectrophotometer, and concentration using a QubitTM 4 fluorometer and a Qubit DNA Assay Kit (Life Technologies, Carlsbad, CA, USA). 2.3. Genome Sequencing, Assembly, and Annotation The genomes of 42 Bifidobacterium strains were sequenced at Majorbio BioTech Co., Ltd. using the Hiseq X Ten platform (Illumina, San Diego, CA, USA). Qualified bacterial genomic DNA (700 ng) was used for the construction of sequencing libraries using an NEB Next Ultra DNA Library Prep Kit (New England Biolabs, Ipswich, MA, USA). After library construction, library sequences were clustered using the HiSeq 4000 PE Cluster Kit (Illumina) and sequenced using the Hiseq 4000 platform (Illumina). A paired-end read of 150 bp was selected for the sequencing library. High-quality paired-end reads were spliced using SOAPdenovo2, and internal gaps were filled using GapCloser . The open reading frame (ORF) of Glimmer 3.02 was used, and gene sequences were translated into amino acid sequences using the Transeq tool in EMBOSS6. Following the method of Pan et al. , functional gene annotation of predicted genes (COG and NR databases) was performed using Prokka or BLASTX. Pan-genome and core gene analyses were performed using PGAP-1.2.1. Glimmer 3.02 and GeneMarkS were used to obtain the GC content, the raw amino acid sequence (.faa), and the nucleotide sequence (.fna) of each genome. Results were base-annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Genes (COG), and Swiss-Prot databases. Protein sequences for all strains were obtained using the dbcan2 metagenome tool accessed on 18 March 2021). Carbohydrate-active enzyme annotations were performed using Hmmer. Annotated glycoside hydrolases were coded and classified using EC data accessed on 18 March 2021). 2.4. Determination of the Ability of Bifidobacteria to Utilize 6'-Sialyllactose Frozen bifidobacterial cultures (containing carbohydrate-active enzymes in the GH33 family) were added to 5 mL mMRS medium (2% (v/v) inoculation), placed in an anaerobic workstation, and cultured at 37 degC for 24-36 h. After 3 generations of continuous subculturing, bacteria were collected via centrifugation, washed, and resuspended in an equal volume of sterilized normal saline. The bacterial suspension was inoculated into culture medium with unique carbon sources and the resuspended cultures were added to three 96-well plates (2 mL capacity) and incubated in a fully automated enzyme labeling instrument in an anaerobic workstation at 37 degC for 40 h. OD600 values were measured at every other period. The experiment was conducted in triplicate. 6'-Sialyllactose used in the carbon source medium was purchased from Shanghai HuicH Biotechnology Co., Ltd. (Shanghai, China) and had a purity of 98% by HPLC and a degree of polymerization of 23, 6'-Sialyllactose was added to the medium at a final concentration of 0.5% (w/v) . 2.5. Comparative Analysis of the Genomes of Six B. bifidum Strains from Subjects of Different Ages Orthologs from six B. bifidum strains were defined using OrthoMCL with default parameters . The core gene sequences chosen were aligned using PGAP-1.2.1. Pairwise average nucleotide identity (ANI) values of B. bifidum genomes were calculated and visualized using R (Version 3.6.1). Orthologous proteins, carbohydrate-active enzymes, virulence factors, and antibiotic factors were annotated using the COG, CAZyme, Gene Ontology (GO), ANI Calculation, comprehensive antibiotic research (CARD), and Virulence Factor (VFDB) databases using BLAST with default parameters. Information about the six B. bifidum strains and quality data for each genome (genome size, GC content, genomic level, and gene number) . 2.6. Antibiotic Resistance Gene and Phenotype Analysis of B. bifidum Antibiotic resistance genes were predicted to be present in the B. bifidum genome by comparing the amino acid sequences of six B. bifidum strains to those registered at CARD accessed on 25 April 2021) . The antibiotic susceptibility of B. bifidum strains was determined using a disk diffusion method, as recommended by the Clinical and Laboratory Standards Institute (CLSI) (CLSI, 2012). Drugs and concentrations were taken from the experimental method by Jin et al. , and all drugs were purchased from Sangon Biotech Co., Ltd. (Shanghai, China). B. bifidum strains were categorized as resistant, susceptible, or intermediate, according to inhibition zone diameters. 2.7. Statistical Analysis Growth curve data were analyzed and visualized using GraphPad Prism 9.1. Excel 2021 was used to analyze the distribution of bifidobacteria. R (Version 3.6.1) software was used to compare genomic data. The heat map of Bifidobacterium glycoside hydrolase gene distributions was constructed using Helm V1.0.s . 3. Results 3.1. Bifidobacteria Distribution at Various Ages The identification of gut microbiota using 16S rRNA sequencing is only accurate at a genus level, while GroEL sequencing can distinguish bifidobacteria at a species or subspecies level. In this study, 610 strains of bifidobacteria were identified in 446 fecal samples using GroEL sequencing. The numbers of bacterial strains in subjects from age groups 0-17, 18-65, and 66-108 y was 260, 244, and 106, respectively. A total of nine species of Bifidobacterium was identified across all samples , of which 250 B. longum strains included two clearly identified subspecies: B. longum subsp. infantis and B. longum subsp. longum; while unidentified subspecies of B. animali and B. augulatum were not isolated from the 66-108 age group but were present in the other two age groups. B. breve was the most abundant bifidobacterium in the 0-17 y age group, accounting for 33% of all Bifidobacterium species in this group. Other species with high abundance were B. bifidum, B. longum subsp. longum, B. longum subsp. infantis, and B. pseudocatenulatum. The most abundant species in the 18-65 y age group was B. longum, accounting for 49% of the bifidobacteria in this group (including two well-identified subspecies, B. longum subsp. infantis and B. longum subsp. longum, as well as an unknown subspecies), followed by B. adolescentis (18%), B. pseudocatenulatum, and B. bifidum. The most abundant species in the 66-108 y age group was B. longum subsp. longum, accounting for 65% of the bifidobacteria isolated from subjects in this age group, which was followed by B. pseudocatenulatum (14%), B. bifidum, and B. breve . 3.2. Glycoside Hydrolase Genes of Bifidobacterium Species Was Studied at Various Ages An ability to utilize carbon sources in the gut is an important factor in determining the abundance of gut microbes. The hydrolysis of carbohydrates in the gut by GHs is a key step allowing utilization by microbes, whereby the substrate specificities and numbers of glycoside hydrolases encoded by microorganisms determine the range of available carbon sources. To evaluate the carbohydrate utilization ability of bifidobacteria from subjects in different age groups, we selected strains representing a summed abundance of bifidobacterial species in each age group of >85%, including five species from the 0-17 and 18-65 y age groups and four species from the 66-108 y age group. A total of 42 strains of Bifidobacterium were selected. We used the dbCAN server to assess the presence of genes encoding glycosyl hydrolases and annotated genes based on GH hidden Markov models (HMMs) generated from data from the CAZy database. Forty-nine families of glycoside hydrolase were found encoded in the genome. Heat maps are shown in Figure 2. The heart icon represents the 0-17 y age group, the oval icon represents the 18-65 y age group, and the firework icon represents the 66-108 y age group. Red represents B. breve, green represents B. bifidum, black represents B. pseudocatenulatum, yellow represents B. longum subsp. infantis, blue represents B. adolescentis, and purple represents B. longum subsp. longum. Statistical analysis showed that there was no significant difference in the average number of glycoside hydrolase genes among species isolated from different age groups. However, it is of interest to note that B. pseudocatenulatum has the highest average number of carbohydrase genes among species taken from all age groups, which is followed by B. longum subsp. longum. The average number of carbohydrase genes in B. bifidum was the lowest among species taken from all age groups, being 38, 34, and 36 in samples from subjects in the 0-17, 18-65, and 66-108 y age groups, respectively. The genomes of all strains encoded the GH2, GH13, GH36, GH42, and GH77 families of glycosidase hydrolases, and they were predicted to be primarily amylases as well as some b-galactosidases that are involved in degrading most of the non-digestible carbon sources in staple foods and dairy products. These glycosidases are essential for the proliferation of Bifidobacterium and can be considered core bifidobacterial glycoside hydrolases. Bifidobacterium genomes also encode glycoside hydrolases associated with the degradation of host-derived carbon sources, and these are encoded in the largest number in the genomes of B. bifidum and B. longum subsp. infantis. For example, B. bifidum and B. longum subsp. infantis encode an average of four b-hexosaminidase genes in the GH20 family, but B. adolescens does not possess genes for this enzyme. a-Fucosidases of the GH95 family are encoded in the genomes of B. bifidum, B. longum subsp. infantis, B. breve, and some strains of B. pseudocatenulatum, and they are involved in the degradation of 2'-fucosyllactose. B. longum subsp. infantis encodes an average of two sialidases from the GH33 family, which is possibly related to the degradation of sialyllactose or other sialic-acid-modified glycans in HMOs. The three strains of B. bifidum encode an average of two sialidases from the GH33 family in ages 0-17 y, but B. bifidum from subjects of age 18-65 y does not encode these enzymes, and there is only an average of one sialidase from the GH33 family in samples from the 66-108 y age group. Different glycoside hydrolases endow Bifidobacterium with specific carbon source utilization abilities, provide a unique ecological adaptation mechanism, and affect interactions with other species. 3.3. Determination of the Ability of Bifidobacteria to Utilize 6'-Sialyllactose 6'-Sialyllactose is primarily found in human milk and mammalian tissues. It has many biological functions and is an important component of glycoproteins and glycolipids with functions in cell recognition and immune responses. In this study, 6'-sialyllactose was used as a sole carbohydrate source to evaluate the utilization phenotype for 6'-SL utilization of different Bifidobacterium species containing the GH33 gene . The results of the phenotypic experiments are given in Table 2. All six strains of B. breve were able to utilize 6'-SL, although strain FBJCP1M6 was less able to use it than the other strains. The six strains of B. longum subsp. infantis were able to grow well in the medium with 6'-SL as a sole carbon source. The phenotypic utilization of 6'-SL by B. bifidum in different age groups was mainly studied. Six B. bifidum strains from the 0-17 and 65-108 y age groups were able to use this acidic oligosaccharide, but the three B. bifidum strains from subjects in the 18-65 age group showed no obvious growth consistent with the genotype of B. bifidum in terms of glycoside hydrolases from the GH33 family, as shown in Figure 3a. The corresponding growth curves of these strains are shown in Figure 3c. Therefore, further investigation was conducted to determine whether three B. bifidum strains, FJSNJ1M3, FZJHZD4M4, and FAHWH21M3, from subjects in the 0-17 y age group (encoding an average of two sialidases from the GH33 family) and three B. bifidum strains from subjects in the 18-65 age group that lacked genes for the GH33 family of sialidases, were different at a genomic level. 3.4. Comparison of Genomes between Six Strains of B. bifidum from Subjects of Different Ages Comparative genomics was used to explore differences in the genomes of six strains of B. bifidum strains from subjects in the 0-17 and 18-65 y age groups. As shown in Table 3, the average genome size for the six bifidobacteria is 2.14 MB, and the average GC content is 62.6%. GC content and genome size are considered to be closely related to bacterial genome evolution and energy metabolism. Changes in the bacterial genome size may explain changes in bacterial carbohydrate metabolism and amino acid metabolism. The genomes of six B. bifidum strains were analyzed for core genes . The results showed that the number of pan-genes increased with the number of strains, while the number of core genes tended to stabilize. When the sixth strain was added, the number of pan-genes stabilized at 2488 and the number of core genes reached 1533. The asymptotic trend of the pan-genomic curve may indicate that B. bifidum has an open pan-genome. The specific core genes and homologous core genes of B. bifidum strains were determined, and a Wayne diagram was drawn . The analysis using OrthoMCL showed that the six strains had 1533 common core genes with numbers of unique specific genes, ranging from 16 to 124. Although there are some differences in age-specific genes, the results showed that the specific genes in the three strains of B. bifidum strains from subjects in the 0-17 y age group were present in significantly lower numbers than those in B. bifidum from subjects in the 18-65 age group. Between-strain ANI values can determine the similarity of two genetic sequences at a genomic level. ANI values for the six B. bifidum strains were calculated, and it was found that the distribution of ANI values within the B. bifidum group was consistent, ranging from 99% to 100%. As shown in Figure 4c, ANI values were more similar within a single age group. The results show that B. bifidum genomes from subjects in the 0-17 y age group are more similar to each other than to those of B. bifidum strains in the 18-65 age group. To distinguish whether the distribution of functional genes in the B. bifidum genome differed among samples from the different age groups, the six B. bifidum genomes were functionally annotated using the COG database and analyzed statistically for the two age groups . By comparing the distribution of COG genes in the two age groups, it was found that gene classes J (Translation, ribosomal structure), G (Carbohydrate transport), M (Cell wall biogenesis), K (Transcription), and T (Signal transduction) were higher in the genome of B. bifidum from subjects of age 0-17 y than from subjects of age 18-65 y, while gene classes A (RNA processing), N (Cell motility), U (Intracellular trafficking), O (protein turnover), and L were lower in subjects of age 0-17 y than in those of ages 18-65 y. Carbohydrate metabolic pathway expression was significantly greater in B. bifidum from subjects aged 0-17 y than in B. bifidum from subjects aged 18-65 y. B. bifidum in the two age groups showed no significant differences in GO enrichment. Most of the differentially distributed genes had catalytic activity and metabolism-related functions . Six B. bifidum strains encoding a large number of carbohydrate-active enzymes (CAZymes), including GTs, GHs, CEs, and CBMs, of which, GHs were the most abundantly distributed . 3.5. Antibiotic Resistance Gene and Phenotype Analysis in B. bifidum Antibiotic tolerance is important in maintaining the abundance of gut symbiotic bacteria, but the horizontal transfer of resistance genes between gut microbes may lead to the generation of deleterious antibiotic-resistant pathogenic bacteria. Using antibiotic resistance testing, this study evaluated the safety of six strains of B. bifidum obtained from subjects of different ages, providing a reference for future application in the probiotics industry. The B. bifidum genomes were annotated using the CRAD database to determine whether they contained potential antibiotic resistance genes. As shown in Figure 6a, each strain carried an average of 97 antibiotic resistance genes of 73 different types, including a macrolide resistance gene (macB), which had the highest content in all strains, which was followed by the lincosamide resistance genes (lmrB and lmrD), aminoglycoside resistance genes (baeS), and glycopeptide resistance genes (vanHF and vanHM). By comparing the total numbers of resistance genes in six B. bifidum isolates from subjects of different ages, the result showed that the resistance genes in B. bifidum isolates from the 0-17 y group were higher than those from the 18-65 age group . Among these, the number of resistance genes in B. bifidum FZJHZD4M4 and B. bifidum FJSNJ1M3 was the highest (99), and that in B. bifidum FGSZY50M8 was the lowest (94). Table 4 shows the antibiotic susceptibility of the six B. bifidum strains to 18 antibiotics. In this study, the tested strains were resistant to ciprofloxacin, trimethoprim, neomycin, kanamycin, streptomycin, aztreonam, and erythromycin but were fully or moderately susceptible to penicillin, ampicillin sodium, amoxicillin, chloramphenicol, tetracycline, rifampicin, ceftizoxime, teicoplanin, vancomycin, and oxacillin. These was semi-tolerance to other antibiotics. The results indicated that B. bifidum strains had different responses to the antibiotics; however, most of them were susceptible to ten different antibiotics. The antibiotic resistance phenotypes were highly consistent with their genotypes. 4. Discussion Bifidobacterium species are among the earliest microorganisms to colonize the human intestine and play important roles in maintaining host health. Bifidobacterium species can affect various disease states, for example, by exercising anti-tumor effects. In a recent study, oral administration of Bifidobacterium to mice achieved an anti-cancer effect of similar magnitude to that of anti-PD-L1 therapy, while combined treatment almost completely inhibited tumor growth . Bifidobacterium and derived preparations have been reported to regulate inflammatory bowel disease by altering the diversity of the intestinal microbiota, regulating the intestinal immune response, and secreting anti-pathogenic substances . The establishment of Bifidobacterium in the intestine can lead to an increase in lactic acid production and reduce the pH of the intestine, inhibiting the propagation of harmful bacteria such as Escherichia coli and Clostridium spp. They can also optimize the physical and chemical environment of the intestine and inhibit the initiation and development of colon cancer induced by azomethane oxide . Bifidobacterium spp. are also capable of reducing blood lipid levels, regulating the intestinal environment, exercising anti-aging effects, and assisting defecation . Bifidobacterium is mainly passed via mother-to-child vertical transmission at birth . Common bifidobacteria in the intestinal tracts of infants include B. bifidum, B. longum subsp. infants, and B. breve , while the common Bifidobacterium species in the adult gut are B. adolescentis, B. pseudobulbarum, and B. longum subsp. longum . Common bifidobacteria species in the intestine of the elderly are B. longum subsp. longum, B. pseudobulbarum and B. bifidum. Aging, which may be accompanied by a change in carbon source intake, is one of many factors that can influence the species composition of Bifidobacterium in the human intestinal tract . According to the World Health Organization, human life can be divided into five stages: 0 to 17 years, 18 to 65 years, 66 to 79 years, 80 to 99 years and over 100 years. In this work, 610 Bifidobacterium strains were divided into three groups based on subject age. The results showed that there were 260 Bifidobacterium strains from subjects in the 0-17 y age group, with B. breve, B. bifidum, B. longum subsp. longum, B. longum subsp. infantis, and B. pseudobulbarum having the highest abundance. From subjects of age 18-65 y, we isolated 244 Bifidobacterium strains, with B. adolescentis, B. pseudobulbarum, B. longum subsp. longum, and B. longum subsp. infantis having the highest abundance. A total of 106 strains were found in fecal samples from subjects in the 66-108 y age group, of which the abundance of B. longum subsp. longum accounted for 65%, which was followed by B. pseudobulbarum and B. bifidum. These findings are consistent with previous results . More than 13% of the homologous gene family clusters in the bifidobacterial genome are associated with carbohydrate metabolism . This glycemic genotype allows Bifidobacterium to metabolize various carbohydrates that cannot be digested by host enzymes , providing a competitive advantage for Bifidobacterium in colonizing the complex intestinal environment. Glycoside hydrolases are enzymes that catalyze carbohydrate hydrolysis. In recent years, the number of GHs represented in the CAZy database has increased almost exponentially . When He et al. studied the microbial samples in the rumen of sheep using macrotranscriptional sequencing, it was found that more than half of the GHs were located in the CAZymes group. B. bifidum has many extracellular glycosidases that can degrade host-derived glycans, including human milk oligosaccharides and high-molecular-weight carbohydrate chains . Bifidobacterium enzymes can be used in the food industry, especially in the production of glycosylated products. For example, Bifidobacterium can be added in the preparation of yogurt to directly synthesize oligomeric galactose using lactose as a substrate . The present study focused on carbohydrate-active enzymes in Bifidobacterium from subjects in different age groups and the annotation and distribution of the abundance glycoside hydrolase genes. The results showed no obvious differences in the glycoside hydrolase gene distribution between samples from subjects of different ages, but there were significant differences in Bifidobacterium species distribution. Across all age groups, B. pseudobulbarum had the largest number of glycoside hydrolase genes, with an average of 58 genes, which was followed by B. longum subsp. longum (55) and B. breve (51). The B. bifidum genome coded for the smallest number of GH genes, with an average of 36. B. bifidum is one of the earliest bacteria to colonize the intestinal tracts of infants, and it has high abundance in the infant intestinal tract. Some specific mechanisms in B. bifidum may be responsible for the highly competitive nature of this taxon in the infant intestine, allowing it to persist in this special environment. Previous studies have found that the combined effects of N-acetylneuraminic lyase (nanA), N-acetylmannosamine kinase (nanK), and N-acetylmannosamine isomerase (nanE) affect the degradation of sialic acid in some Bifidobacterium species . The presence of sialidase was confirmed in the genomes of strains including B. longum subsp. infantis ATCC15697, B. breve UCC2003, and B. bifidum PRL2010 . Kiyohara et al. first reported that the B. bifidum JCM1254 exosialidase SiaBb2, an extracellular enzyme located on the membrane and belonging to the GH33 family, can act on sialylated oligosaccharides and promote release of free sialic acid. Yu et al. showed that B. longum subsp. infantis JCM7009 and JCM7011 can efficiently utilize 3'-SL and 6'-SL using neuraminidase and ultimately produce lactate and short-chain fatty acids. Other results showed that B. bifidum extracellular sialidase promotes the utilization of sialylated carbohydrates with cross-feeding of free sialic acid to other Bifidobacterium strains. Bifidobacterium can grow in media containing SL as the main carbon source as it has galactosidase-encoding genes that allow for the cleavage of the relevant glycosidic bonds . To assess this, we selected 21 Bifidobacterium strains from subjects of different ages, including B. breve (6 strains), B. longum subsp. infantis (6), and B. bifidum (9) and assessed the gene distribution of the GH33 family of glycosidases. All the strains were subjected to an in vitro 6'-SL utilization test. The results showed that all the B. longum subsp. infantis and B. breve samples grew well with 6'-SL as sole carbon source, and most of the B. bifidum strains (other than those isolated from subjects in the 18-65 age group) could also utilize 6'-SL (Table 2), which is consistent with previous reports . By correlating the presence or absence of genes and the growth or nongrowth patterns of 21 Bifidobacterium strains with 6'-SL as sole carbon source, we found that the phenotypic experiment results were consistent with the genotypic predictions. The distribution of genes in the GH33 family of sialidases varied for B. bifidum across samples from different age groups, with no GH33 genes detected in strains isolated from the 18-65 y age group, and only a few genes detected in strains from the 0-17 y (2) and 66-108 y (1) age groups. The development of genomic tools provides strong support for understanding the diversity and functional characteristics of bacterial strains. We performed comparative genomic analyses on six strains of B. bifidum from subjects in the 0-18 y and 18-65 y age groups and determined the carbohydrate metabolic capacity. The average genome size for the six B. bifidum strains was 2.17 Mb, which is consistent with previous reports . The pan-genome and core genome results suggested that the six B. bifidum strains have an open pan-genome. Average nucleotide identity is a standard method to determine whether a particular strain belongs to a reference species or whether a subspecies exists, whereby a threshold of 96% is used as a species boundary . The heatmap of ANI values showed that the average nucleotide identity was higher in strains obtained from the same age group . Furthermore, by annotating the core genes, the functions of transcription, defense mechanisms, and general function prediction of B. bifidum were revealed. We found differences between the six B. bifidum strains obtained from subjects in the 0-17 and 18-65 y age groups in terms of core and pan-genomes, ANI, carbohydrate utilization enzymes, COG, and antibiotic resistance. GO analysis, antibiotic resistance genes, and antibiotic resistance phenotypes did not show differences with age. Even so, age-related factors may be important in developing appropriate probiotics. In contrast to the other Bifidobacterium species, B. bifidum has been shown to utilize host-derived carbohydrates, especially human milk oligosaccharides and mucin . In vitro and animal studies support the proposal that various extracellular proteins produced by B. bifidum are crucial for the interaction between strain and host. In recent years, numerous studies have confirmed the influence of gut microbiota on healthy aging and shown that the ability of intestinal microbiota to assist in fighting disease gradually decreases with age. This study found a loss of the GH33 family of glycosidase genes in strains isolated from the 18-65 y age group, possibly indicating a partial loss of metabolic capacity with age. Probiotics with particular functions may be useful as supplements for populations with specific needs. At present, the knowledge of the B. bifidum genome is limited, and more strains should be studied. Species numbers, subject ages, geographic regions, and other potentially relevant factors in existing studies remain limited. It is urgent to investigate the potential of age-specific probiotics at a genetic level. This study provides a reference for future application in probiotic development, taking into account factors including glycoside hydrolase types, phenotype-genotype relationships, and subject age. 5. Conclusions In this study, whole genome sequencing was used to reveal the distribution of glycoside hydrolases in Bifidobacterium, with the results revealing differences in the distribution of the sialidase GH33 family in B. bifidum at different ages. Comparative genome and phenotypic studies were conducted, and the studies confirmed that the distribution of glycoenzyme genes in B. bifidum varied with age, affecting the phenotypic outcomes. It is critical to investigate the genomic and carbohydrate utilization properties of Bifidobacterium present in the digestive tract at various ages, as the data can be used as a reference for targeted intervention addressing intestinal Bifidobacterium composition as well as providing new ideas for probiotic products targeting various age groups. Acknowledgments This work was supported by the National Natural Science Foundation of China [U1903205, 31820103010, 32001665]; the Key Scientific and Technological Research Projects in the Key Areas of the Xinjiang Production and Construction Corps [2018AB010]; and Collaborative innovation center of food safety and quality control in Jiangsu Province. Author Contributions X.W. collected all the related materials, performed the methodology, validation and wrote the manuscript. C.Z., L.Y., F.T. and Q.Z. conceived the topic and the outline. Y.N., F.T., L.Y. and H.Z. designed the work and designed and coordinated the comparative genomics study funding acquisition. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The 610 strains used in this study were all isolated from fecal samples of healthy Chinese people. The collection of fecal samples was approved by the Ethics Committee of Jiangnan University, China (SYXK 2012-0002). Informed Consent Statement Written informed consent for the use of fecal samples was obtained from the participants or their legal guardian before sampling. All those strains were deposited at Culture Collection of Food Microorganisms (CCFM), Jiangnan University. Data Availability Statement The data shown in this study are contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The distribution of the bifidobacteria isolated. (a) Distribution of bifidobacteria by age groups. (b) Proportions of different kinds of bifidobacteria in different age groups. Figure 2 Analysis of the glycoside hydrolase genes from Bifidobacterium spp. isolated from subjects in different age groups. The heatmap shows the number of ORFs annotated as GH for each GH family (y-axis) and each genome (x-axis). The arrow marks GH33. Figure 3 6'-Sialyllactose as a key carbon source for Bifidobacterium growth. (a) Numbers of GH33 family glycoside hydrolase enzymes in B. bifidum isolated from different age groups; (b) Chemical structure of HMO 6'-SL generated; (c) Growth in 6'-SL-containing medium for Bifidobacterium strains containing the GH33 family gene encoding glycoside hydrolase. Figure 4 Comparative genomic and phylogenetic analyses of six B. bifidum strains. (a) Pan-genome and core genome; (b) Venn diagrams based on the homologous genes of six B. bifidum strains isolated from human feces from different age groups. (c) ANI value among six B. bifidum strains. Figure 5 Functional gene analysis of six strains of B. bifidum. (a) Functional assignment of the core genome based on the COG database; (b) The number of genes in four families of carbohydrate-active enzymes from different strains of B. bifidum; (c) Functional assignment of the core genome based on the GO database. Figure 6 Genotype-phenotype analysis of the antibiotic resistance of B. bifidum. (a) Clustering heat map analysis of antibiotic resistance genes in B. bifidum; (b) The total number of resistance genes in six B. bifidum strains. foods-12-00922-t001_Table 1 Table 1 Demographic characteristics of a cohorts. Demographic Data Age Group (y) Values or No. (%) 0-17 18-65 66-108 0-17 18-65 66-108 Gender Male 96 80 33 96 (51%) 80 (39%) 33 (35%) Female 69 118 61 69 (37%) 118 (58%) 61 (65%) Not specified 23 6 0 23 (12%) 6 (3%) 0 Total no. of samples 188 204 94 - Total no. of strains 260 244 106 - foods-12-00922-t002_Table 2 Table 2 Phenotypic results for 6'-sialyllactose utilization in 21 strains of Bifidobacterium. Strain Age 0-17 Age 18-65 Age 66-108 B. bifidum FJSNJ1M3 ++ FGSZY50M8 - FHNFQ34M6 + FZJHZD4M4 +++ FHNFQ25M12 - FHNFQ11M4 ++ FAHWH21M3 ++ FGSYC45M3 - FHNXY17M1 + B. longum subsp. infantis FGZ19I1M3 +++ FGZ6I2M6 +++ / HeNJZ8M1 +++ FJ12WI1M14 +++ / FGZ17I1M1 +++ FJ12WI1M1 ++ / B. breve JSWX17M1 ++ / FHNXY48M6 +++ FJSZJ1M5 ++ / FCQNA20M1 ++ FBJCP1M6 + / FHNFQ34M6 ++ Growth was classified as follows: -, negative (maximum OD600 < 0.2); +, low (OD600 from 0.2-0.5); ++, moderate (OD600 from 0.5-0.8); +++, high (OD600 > 0.8). foods-12-00922-t003_Table 3 Table 3 Genome information for six B. bifidum strains used in this study. Host Bacterial Strain Gene No. Genome Size/Mb G + C% Level Accession Number Human feces (0-17) B. bifidum FJSNJ1M3 1910 2.13 62.7 Scaffold SRR13205608 B. bifidum FZJHZD4M4 1959 2.17 62.6 Scaffold SRR13205566 B. bifidum FAHWH21M3 1899 2.12 62.7 Scaffold SRR13205659 Human feces (18-65) B. bifidum FGSZY50M8 1956 2.18 62.5 Scaffold SRR13205646 B. bifidum FHNFQ25M12 1985 2.12 62.6 Scaffold SRR13205635 B. bifidum FGSYC45M3 1932 2.13 62.7 Scaffold SRR13205647 foods-12-00922-t004_Table 4 Table 4 Antibiotic resistance and susceptibility of six B. bifidum strains. Strains PEN AMS AMO CLM RIF CEF TET TEC VAN OXA CIP GM T/S NEO KAN S ATM E FJSNJ1M3 S S S S S S S S S S R S R R R R R R FZJHZD4M4 S S S S S S S S S S R R R R R R R R FAHWH21M3 S S S S S S S S S S R R R R R R R R FHNFQ25M12 S S S S S S S S S S R R R R R R R R FGSZY50M8 S S S S S S S S S S R S R R R R R R FGSYC45M3 S S S S S S S S S S R R R R R R R R Penicillin (PEN), Ampicillin sodium (AMS), Amoxicillin (AMO), Chloramphenicol (CLM), Rifampicin (RIF), Ceftizoxime (CEF), Tetracycline (TET), Teicoplanin (TEC), Vancomycin (VAN), Oxacillin (OXA), Ciprofloxacin (CIP), Gentamicin (GM), Trimethoprim (T/S), Neomycin (NEO), Kamamycin (KAN), Streptomycin (S), Aztreonam (ATM), Erythromycin (E). R = resistant, I = intermediate, S = susceptible. 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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PMC10000438 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050680 cells-12-00680 Article Microbiological Aspects of Pharmaceutical Manufacturing of Adipose-Derived Stem Cell-Based Medicinal Products Szablowska-Gadomska Ilona Conceptualization Methodology Validation Formal analysis Investigation Writing - original draft Writing - review & editing Visualization Supervision 12* Humiecka Monika Methodology Validation Formal analysis Investigation Resources Data curation Writing - original draft Writing - review & editing Visualization 1 Brzezicka Joanna Methodology Validation Formal analysis Investigation Resources Writing - original draft Writing - review & editing Visualization 1 Chroscicka Anna Conceptualization Validation Resources Writing - original draft Visualization Project administration Funding acquisition 123 Placzkowska Joanna Validation Formal analysis Investigation Resources Data curation Writing - review & editing 4 Oldak Tomasz 4 Lewandowska-Szumiel Malgorzata Conceptualization Methodology Resources Data curation Writing - original draft Writing - review & editing Visualization Supervision Project administration Funding acquisition 13* Dani Christian Academic Editor 1 Laboratory for Cell Research and Application, Center for Preclinical Research and Technology, Medical University of Warsaw, Banacha 1b, 02-097 Warsaw, Poland 2 BBMRI.pl Consortium, 61 Zwirki i Wigury Street, 02-091 Warsaw, Poland 3 Department of Histology and Embryology, Medical University of Warsaw, Chalubinskiego 5, 02-004 Warsaw, Poland 4 Polish Stem Cell Bank (PBKM), Jana Pawla II 29, 00-867 Warsaw, Poland * Correspondence: [email protected] (I.S.-G.); [email protected] (M.L.-S.) 21 2 2023 3 2023 12 5 68009 12 2022 08 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 ). Subcutaneous adipose tissue is an excellent source of mesenchymal stem cells (ADSCs), which can be used in cell therapies as an active substance in advanced therapy medicinal products (ATMPs). Because of the short shelf-life of ATMPs and the time needed to obtain the results of microbiological analysis, the final product is often administered to the patient before sterility is confirmed. Because the tissue used for cell isolation is not sterilized to maintain cell viability, controlling and ensuring microbiological purity at all stages of production is crucial. This study presents the results of monitoring the contamination incidence during ADSC-based ATMP manufacturing over two years. It was found that more than 40% of lipoaspirates were contaminated with thirteen different microorganisms, which were identified as being physiological flora from human skin. Such contamination was successfully eliminated from the final ATMPs through the implementation of additional microbiological monitoring and decontamination steps at various stages of production. Environmental monitoring revealed incidental bacterial or fungal growth, which did not result in any product contamination and was reduced thanks to an effective quality assurance system. To conclude, the tissue used for ADSC-based ATMP manufacturing should be considered contaminated; therefore, good manufacturing practices specific to this type of product must be elaborated and implemented by the manufacturer and the clinic in order to obtain a sterile product. microbiological control mesenchymal stem cell cell therapy ATMP GMP ADSC National Center for Research and DevelopmentSTRATEGMED2/267976/13/NCBR/2015 Ministry of Science and Higher Education in PolandDIR/WK/2017/2018/01-1 This work was supported by the National Center for Research and Development (grant number STRATEGMED2/267976/13/NCBR/2015) and by the Ministry of Science and Higher Education in Poland (Grant DIR/WK/2017/2018/01-1). pmc1. Introduction After years of the successful use of bone marrow hematopoietic stem cell transplantation, the discovery of nonhematopoietic stem cells in the bone marrow by Friedenstein opened the way to completely new cell therapies . These cells were named mesenchymal stem cells (MSCs), as proposed by Caplan . Although this term is currently under discussion and many authors, including Caplan himself, generally use the term "stromal" instead of "stem" cells, the MSC abbreviation is clearly recognizable and for the purpose of this manuscript, the classic name will be used. Over the last three decades, it has been proven that it is possible to obtain MSCs from various tissues, such as the umbilical cord, dental pulp, dermis, peripheral blood, and adipose tissue . The latter is currently widely exploited as an MSC source due to its easy availability and MSC abundance, which is 100-fold higher than that of bone marrow . Although MSCs obtained from different sources are not exactly the same, they are of interest as an active substance in a wide variety of medical applications. Due to their ability to differentiate toward various phenotypes, there was initially great interest in the possibility of their use for the regeneration of various tissues . In addition, there has recently been growing evidence of their immunomodulatory properties, which suggests possible MSC applications in healing wounds in an inflammatory environment, autoimmunological diseases, and graft versus host disease (GvHD), for example . There is a rich and continuously growing index in the Clinicaltrials.gov database ) which is also reflected in a number of review papers . The road toward MSC-based products becoming available on the medical market is demanding and cost-consuming . This is because, unlike bone marrow transplants, they are considered to be medicinal products in the vast majority of cases. As such, they must fulfill not only transplantological requirements but also fall under the regulations of pharmaceutical laws, requiring centralized marketing authorization . Currently, there are 54 approved ATMPs on the global medical market, excluding genetically modified products . Currently, ten MSC-based ATMPs have achieved market approval . Among them, there is Alofisel, approved for use by the EU, and in the US there is Prochymal, renamed to Remestemcel-L, already approved for use in Canada and New Zealand, which is under FDA consideration as a GVHD treatment for children . The time gap between clinical trials and market approval is understandable in view of the regulatory pathway for ATMPs . Although the regulatory details may differ in particular countries, the general rule is similar . In the EU, there is the Regulation of the European Parliament and of the Council of 2007, which introduced the term Advanced Therapy Medicinal Products (ATMP) . Apart from the details, products containing such cells as MSCs are not considered transplants, but rather ATMPs, if they are substantially manipulated or if their intended essential role in the recipient is not the same as in the donor . In particular, cell culture or cell isolation via the enzymatic digestion of tissue are considered to constitute substantial manipulation . Therefore, all steps, from cell isolation to product preparation, must be performed following good clinical manufacturing practice (GMP) regimens in accordance with pharmaceutical law. Such rules apply not only to products with market approval, but also to advanced therapy investigational medicinal products (ATIMP), i.e., those which are prepared for clinical trials. Thus, the further development of cell-based therapies is inseparable from the distinctive manufacturing requirements of ATMPs, and the exchange of experience in this area represents an area of continued progress. This paper is focused on clinical microbiology laboratory practice in terms of MSC-based ATIMP production. Regardless of the fact that the general GMP rules for medicinal products must be respected, there are some distinctive issues relating to products containing cells collected from culture that should be considered in terms of sterility. Firstly, the starting material, i.e., the human tissue used for cell isolation, may be contaminated. Secondly, all of the manufacturing steps, including many activities typical to cell culture and characterization, are performed in a manner that keeps the cells alive. Finally, for non-cryopreserved cells from culture, the results of the sterility test of the product are not available upon release, which is accepted by the regulatory bodies ; however, this imposes the need for special attention and control during all stages of production. This study is based on original data taken from a two-year-long continuous production of ADSC-based ATIMPs (advanced therapy investigational medicinal products), i.e., ATMPs manufactured for the purpose of a clinical trial. It presents well-documented data illustrating the microbiological characteristics of the manufacturing process controlled during various stages over the whole road of the product from the clinic to the lab and back in order to share the experience, analyze the critical points, and propose steps towards improving ATIMP manufacturing. 2. Materials and Methods 2.1. Sterility Testing of the Biological Material Lipoaspirates were acquired via standard liposuction from 100 adult patients at two aesthetic clinics in Poland during a two-year clinical trial after obtaining their informed consent EudraCT Number: 2016-004110-10). Prior to digestion, the adipose tissue was washed extensively with a 1% antibiotic-antimycotic solution containing 10,000 IU penicillin, 10,000 mg/mL streptomycin and 25 mg/mL amphotericin B (Corning, Manassas, VA, USA) in phosphate-buffered saline (PBS) (Thermo Fisher Scientific, Bleiswijk, The Netherlands). The tissue was then digested with collagenase NB 6 GMP Grade (SERVA Electrophoresis GmbH, Heidelberg, Germany) and reconstituted in PBS (Thermo Fisher Scientific, Bleiswijk, The Netherlands). After digestion, the collagenase was inactivated. The stromal vascular fraction (SVF) was separated by centrifugation (350x g/10 min/22 degC) and filtration (strainer 100 mm) and washed with sodium chloratum (Fresenius Kabi, Warsaw, Poland). Depending on the type of product, the ATMPs were either prepared (SVF) or further cultured (ADSCs). To prepare the ADSC product, the cells were plated in T75 culture flasks and cultured at 37 degC and 5% CO2 in a humidified atmosphere in the complete GMP-grade culture medium: a MSC NutriStem(r) XF Basal Medium with Supplement Mix (Biological Industries, Beit Haemek, Israel) and antibiotic-antimycotic solution (Corning, Manassas, VA, USA). The latter contained 10,000 IU penicillin (class Penicillins b-lactam antibiotics, 10,000 mg/mL streptomycin (aminoglycoside antibiotics class) and 25 mg/mL amphotericin B (polyene antifungal antibiotic class), and its final concentration in the medium (either PBS, for washing, or full culture medium) was equal to 0.1% . The presence of microbial contamination was checked at five different stages during the cell harvesting process, including Stage 1: where the samples were taken during the preparation of tumescent fluid before liposuction (fresh tumescent fluid, which is routinely used to ensure a painless and relatively bloodless liposuction procedure--contains 40 mL of 1% lidocaine and 2 mg adrenaline in 1000 mL lactated Ringer's solution); Stage 2: where the material taken after liposuction (lipoaspirate); Stage 3: where the samples were collected during the intermediate stage of processing (the medium from the isolated cells); and Stage 4: the final stage of isolation (where the medium was separated from the last wash of the cells). The samples from the first and second stages were taken in the clinic, and the samples from the third and fourth stages were taken in the laboratory. Additional samples were also taken during the in vitro cell culture process (cell culture supernatant--Stage 5). The examination of the samples for the presence of microbial contamination was performed using a BACTECTM automated system. The use of the BD Bactec system has been validated according to the EU Pharmacopoeia (Polish version) following the scheme for alternative methods . For the validation of Bactec method according to the Pharmacopeia , the following strains were used: Pseudomonas aeruginosa ATCC9027; Bacillus subtilis ATCC6633; Staphylococcus aureus ATCC6538; Candida albicans ATCC 10231; Bacteroides fragilis ATCC25285; Clostridium sporogenes ATCC19404; Streptococcus pyogenes ATCC19615; Aspergillus brasiliensis (niger) ATCC16404; and Propionibacterium acnes ATCC11827. Additionally, microorganisms were inoculated in the solution in which the cells were previously suspended (e.g., culture medium, medium with 0.1% AAS). The samples prepared in this way were then tested. The applied methodology has been positively verified by the Polish Pharmaceutical Regulatory Authority. BACTECTM Plus Aerobic/F Culture Vials and BACTECTM Plus Anaerobic/F Culture Vials media are enriched soybean-casein digest broths with an antibiotic-removing resin (Becton Dickinson and Company, Sparks, NV, USA). The BACTECTM Plus Aerobic/F culture vial medium contains CO2, and the BACTECTM Plus anaerobic/F culture vial medium is dispensed with CO2 and N2 . The bottles were inoculated with the samples under a laminar air flow chamber (LabGard Class II, Type A2 Biosafety Cabinet) and incubated at 35 degC +- 2.5 for 14 days. In the case of a positive signal, the identification of the contamination was conducted and the results were collected. In the final stage of production, the endotoxin levels were determined in the supernatant sample after the last centrifugation during the process of washing cells with sodium chloratum . For this purpose, the Endosafe(r) endotoxin test system was used. The acceptable endotoxins level was <2 EU/mL (according to Polish Pharmacopeia chapter 5.1.10) . When positive microbiological test results of the starting material--lipoaspirate (e.g., after 24 h), were obtained, corrective actions were implemented, e.g., extending the culture time, changing the number of passages, or extra freezing/thawing steps. These steps were carried out until a sterile microbiology test result was obtained from at least two of the subsequent probes of the cellular material processing. The sampling points of the microbiological and endotoxin tests are indicated in Figure 1, illustrating the subsequent stages of the procedure, from the collection of the starting material to the production of ATIMP and the detailing of the manufacturing steps used in the laboratory . 2.2. Environmental Monitoring of Microbiological Quality Three methods were used to monitor the microbiological safety of the manufacturing environment: active air sampling (volumetric sampling), passive air sampling (settle plates), and surface sampling (contact plates). All of the samples were collected according to an approved microbiological monitoring program and at a frequency recorded in accordance with the quality management system that was developed according to the legal requirements of the pharmaceutical quality assurance system. This program includes the monitoring of the cleanliness of laboratory rooms and consists of checking for the presence of microorganisms as well as the content of inanimate particles in the air. The sampling sites, their number, and their frequency were also determined. The activities carried out ensured that an appropriate level of cleanliness was maintained in the production environment, minimizing the risk of the product becoming contaminated with microorganisms. For the volumetric sampling, a MICROFLOWa 90/C sampler (AQUARIA, Lacchiarella, Italy) was used. The aspirated volume was 1 m3, and the air was collected every 10 min on 90 mm Petri dishes (IRR Tryptone Soya 1.6% Agar + Neutralizer Ndeg 4, Redipor, Bicester, UK). The test was carried out every 3 months. Passive air sampling was conducted using 90 mm Petri settle plates (IRR Tryptone Soya 1.6% Agar + Neutralizer Ndeg 4, Redipor, Bicester, UK). Open plates were exposed to air (including the laminar airflow chambers) for a maximum of 4 h to prevent agar desiccation. In Grade A and B areas, the test was always carried out during all stages of manufacturing. In Grade C and lower areas, the test was carried out at least every two weeks. While conducting the experiment, the frequency of sampling in specific places and purity classes was reduced. Changes were made on the basis of a systematic analysis of the trends in the microbiological results and after conducting an appropriate risk analysis. Contact plates with tryptone soya agar (IRR Tryptone Soya 1.6% Agar + Neutralizer Ndeg 4, Redipor, Bicester, UK) were used for surface monitoring. This aspect of the environmental sampling included cleanroom windows, floors, walls, door handles, working surfaces (including laminar airflow chambers and tabletops) and devices (CO2 incubators, centrifuge, and microscope). After sampling, the surfaces were cleaned with 70% alcohol. The samples taken from the staff involved in the manufacturing process were also collected using this method. The samples taken from the garments and hands were collected at the end of each manufacturing day. For hand dabs, standard 90 mm diameter settle plates (IRR Tryptone Soya 1.6% Agar + Neutralizer Ndeg 4, Redipor, UK) were used. The test was carried out at the same time schedule as in the passive air sampling method. All of the collected samples from each of the methods were incubated for five days (with a possible extension of the incubation time by four days) at 35 degC +- 3. The results obtained from active air sampling are presented as the CFU/m3 of air. In the case of the settled plates, the results are reported as CFU/4 h, and the contact plates are reported as CFU/plate. In the case of positive samples from staff and grade A and B areas, the identification of contaminations was conducted in a specialized microbiological laboratory. The correct cleanliness classes of the manufacturing rooms were confirmed at all stages as a part of the environmental control, and the total number of airborne particles (0.5 mm and 5 mm) was also measured according to the GMP to the ISO 14644-1:2015 standard by measuring during environmental control, referring to cleanrooms and associated controlled environments--Part 1: Classification of air cleanliness by particle concentration. No irregularities were noted. 2.3. Statistical Analysis For statistical analysis, the chi-square test with Yates correction was used with the exception of the data presented in Table 4. For these results, Fisher's exact test was used. The data were considered statistically significant at the level of significance p < 0.05. 3. Results 3.1. Detection of Microbial Contamination in the Biological Material The results of the microbiological analysis of the biological material samples are shown in Table 1. During the two-year clinical trial, 498 samples were collected for microbiological tests. The materials from all stages of ATMP manufacturing were studied, starting with fresh tumescent fluid, lipoaspirate, the fluids from two stages of cell isolation, and the primary cell culture. Overall, the numbers of samples taken from these manufacturing steps in the two consecutive years were 276 and 222, respectively. The contamination of samples taken from Stage 1 (fresh tumescent fluid) was detected in two probes (one each year). In Stage 2 (lipoaspirate), 41 samples derived from the two clinics were contaminated: 25/56 samples in the first year and 16/44 samples in the second year of the clinical trial. Contamination in the probes from Stage 3 (the medium from the isolated cells) and Stage 4 (the medium from the last wash of the cells) was still detected; overall, 12% and 6% of contaminated samples were found in Stage 3 and Stage 4, respectively. No contamination was detected in any probe collected from the subsequent primary cell culture (stage 5). The cells obtained after processing 100 lipoaspirates were used to prepare 130 Advanced Therapy Investigational Medicinal Products and administered to the patients: 36 products were based on freshly isolated SVF cells, and 94 products contained expanded ADSCs (data not shown). The endotoxin results of the samples taken at the stage of the completed preparation of the medicinal product ranged between >0.05 and >0.25 EU/mL. All of the results obtained were below the accepted endotoxin level. 3.2. Identification of Microbial Contamination in Biological Material Fresh tumescent fluid was contaminated by Staphylococcus epidermidis, Staphylococcus capitis and Dermabacter hominis. More than 40% of the lipoaspirates were contaminated with thirteen different microorganisms. The most commonly isolated bacteria were Staphylococcus epidermidis (40%), Propionibacterium acnes (13%), Staphylococcus capitis (9%), and Bacillus spp. (9%) . Due to the difficulties in assigning Bacillus bacteria to individual species, all of the isolated bacteria of this genus are presented together in all figures. Figure 3 shows the data of the microorganisms identified from the contaminated lipoaspirates depending on the incubation conditions of the collected samples (aerobic and anaerobic). Only five species were identified under both aerobic and anaerobic conditions: Staphylococcus epidermidis, Propionibacterium acnes, Staphylococcus capitis, Staphylococcus hominis, and Staphylococcus lugdunensis. In both cases, the most frequently identified microorganism was Staphylococcus epidermidis, which was isolated from over 50% of the contaminated samples. Under aerobic conditions, six other microorganisms were also isolated. The bacteria identified in the samples from the subsequent stages of manufacturing (stages 2-4) are presented in Table 2. Microorganisms were detected in 40 samples of lipoaspirates (in eight samples, there was more than one bacterial species). In one case, despite a positive signal, no microbial growth was obtained. Bacterial contamination was detected in 12 samples taken from Stage 3, and these were the same bacteria as those identified in the lipoaspirate samples (Stage 2). In six cases, the contamination of the samples taken from Stage 4 was still associated with the original contamination of the probes from the lipoaspirates (Stage 2). 3.3. Environmental Monitoring of Microbiological Quality During the two-year clinical trial, a total of 27,634 samples were collected under the environmental monitoring program at our GMP certified laboratory (details in Table 3), 22,173 of which were collected from Grade A and B areas. In this paper, only the results from routine aseptic monitoring of these GMP grades are presented. The types and number of the samples collected in areas of Grades A and B are shown in Table 4. During the two years, 15,644 samples were collected using the surface sampling method, 6393 samples were collected using the passive air sampling method (settle plates), and 136 samples were collected using the volumetric method. Comparing the results of the microbiological monitoring of the manufacturing environment between the first and second years of lipoaspirate processing, a decrease in the percentage of positive samples collected from the laboratory by passive air sampling and surface sampling was observed. For the settled plates method, this percentage was 2.00% in the first and 1.04% in the second year of the clinical trial, and 1.17% and 0.54% for the contact plates, respectively. Statistically significant differences were noted in the frequency of contaminated samples collected in the first and second years using these methods (p < 0.001 for surface sampling and p < 0.01 for passive air sampling). For active air sampling, we detected one contaminated sample each year. The most commonly isolated and identified cleanroom bacteria were Bacillus spp. (44%), Micrococcus spp. (27%) and Staphylococcus spp. (19%). The remaining 10% included bacteria of other types . The analysis of the identified microorganisms from the samples collected using different methods revealed Bacillus spp. in over 60% of the positive samples obtained using surface sampling (data not shown). A decrease in the percentage of positive microbiological results for the samples taken from staff directly involved in the manufacturing process was also observed, but the differences in the frequency of contaminated probes were not statistically significant. In the first year, microbiologically positive samples constituted 1.94% of all staff samples taken from both gloves and clothing, and in the second year, this percentage was 1.68% (data not shown). Figure 5 shows the data regarding the observed contamination for individual employees. Almost all employees (except one) reported a decrease in the number of positive tests in the second year. The most commonly isolated bacteria from the staff were Bacillus spp. (in 43.4%), Staphylococcus spp. (in 28.7%), and Micrococcus spp. (in 24.6%). Other identified species occasionally occurred, i.e., Corynebacterium, Moraxella, and Kocuria . 4. Discussion MSC-based ATMPs hold great promise in relation to many unresolved medical problems . Although classified as medicinal products, their method of production is not typical, so regulatory bodies try to look for special solutions for them, and scientists share their experience in solving manufacturing problems . Our results concern the manufacturing of ADSCs, one of the most promising MSCs for cell-based therapies . The most important finding is that, surprisingly, more than 40% of lipoaspirates, i.e., forty-one out of 100 samples received from the clinic to produce ADSC-based ATMPs, were contaminated. To the best of our knowledge, this is the first study presenting such an observation. It was an unexpected result when considering that the material was harvested by experienced clinicians that understood the entire procedure as participants in a clinical trial. The clinics were controlled by regulatory authorities, and above all, they were fully aware of the importance of the sterility of the collected material in view of the safety of the final product, as it is intended to be used in their patients. The implementation of the improved procedures in very determined and cooperating clinics brought about a decrease in the number of contaminated samples (from 44.6% to 36.4%) in the second year of the trial but did not eliminate them. Since all of the identified microorganisms are part of the physiological flora of human skin, the contamination is apparently related to the tissue donor site. This leads to the conclusion that the starting material for ADSC-based ATMPs should be considered contaminated even if it is harvested under the strictest regimen. Therefore, decontamination steps must be routinely implemented. Our results document the successful implementation of the additional steps of the procedure, including the repeated rinsing of the starting material in an antibiotic and antimycotic solution. Other laboratories also use these or other antibiotics; for example, Golay et al. used gentamycin, showing a minimal amount of gentamycin in the final product after washing . Martins et al. used an antibiotic-antimycotic solution during the initial stage of mesenchymal stem cell isolation from umbilical cord tissue but not in the cell culture medium . Each cell laboratory develops its own strategy regarding the use of antibiotics-antimycotics at various stages of manufacturing based on the optimization of the type, dosage and duration of exposure, depending on the type of the source tissue, as well as the most frequent contamination type and level. The developed strategy must always be validated in terms of its influence on the quality and safety of the final products and should be based on individually adjusted risk analysis. Microbiological monitoring during every stage of the procedure until the application, including the steps following manufacturing, should also be an issue of general concern for the manufacturer and the clinician. We have not had any such cases, but Veriter et al. reported contamination with Staphylococcus aureus, Staphylococcus epidermidis and Corynebacterium spp. in three out of nineteen samples of transport medium, revealed after the delivery of the ADSC-based products manufactured in their laboratory. The medium was sterile when leaving the manufacturing laboratory, so it must have been contaminated in the operating room . Our results show the importance of sterility tests that were already performed at the stage of material acquisition in the clinic--in the case of ADSC--two extra samples, from tumescent fluid and lipoaspirate, are recommended to be controlled. As a consequence, not only the additional routine decontamination of tissue but also the individual adaptation of further steps, e.g., the duration of culture, may be applied. This is not only to extend the duration of exposure to antibiotics but to allow time for the microbiological results to be obtained. A long wait for the final microbiological results is a known limitation. For the product, this is formally resolved through a two-step procedure, i.e., initial and final batch certification . For manufacturing, we propose possibly extending the time in culture, with additional freezing if necessary, to determine need for additional decontamination depending on the results of the tests. A cost-benefit balance should be taken into account. ATMP manufacturing takes place in cleanrooms of grades A, B, C and D, as defined by the Rules Governing Medicinal Products in the European Union (Volume 4) and the EU Guidelines on Good Manufacturing Practice Medicinal Products specific to Advanced Therapy Medicinal Products . Not only the appropriate design of the manufacturing laboratory but also an environmental monitoring system is indispensable, and it should precisely define all activities related to microbiological environmental monitoring, i.e., the number of samples, the sampling technique and frequency, the acceptable limits on the number of microorganisms, and all of the actions to be performed in case of any microbiological incorrectness . In this study, 22,173 samples from GMP Grade A and B areas were collected during a two-year clinical trial. Among all of these samples, only 248 (1.12%) showed bacterial or fungal growth. Passive air sampling results were positive for 102 agar plates, while volumetric air sampling revealed bacterial growth in only two samples (1.47%) taken from GMP Grade B. Interestingly, Martin et al., who reported the absence of microorganisms in all collected passive air samples and a definitely smaller number of positive samples from surfaces, observed bacterial growth in 38 samples (21.8%) and fungal growth in two samples (3.8%) collected via active air sampling in a Grade B area . Trsan et al. also reported that most positive samples were collected with active air sampling . Another study to assess the microbiological environment showed that approximately 47% of the air samples collected using volumetric analysis were free of microorganisms . Differences in the data reported by various laboratories may be a result of the different sampling frequencies. The appropriateness of using the passive vs. active method is also currently under wider discussion; this topic is still waiting for a commonly accepted consensus . For the microbial cleanliness of the laboratory surfaces, Cobo and Concha reported a large amount of floor surface contamination, especially near critical equipment such as incubators and centrifuges, as well as a significant amount of wall contamination . In our laboratory, most cases of contamination were found in relation to cleanroom windows and door handles (Table 4). Most importantly, we achieved a significant improvement in the second year of production in both cases, where we did not find any contamination of the working surfaces. This confirms the importance of continuous staff training as well as a constant verification of staff behavior patterns in clean rooms. The predominant bacterial genus isolated in our study was Bacillus spp. (44%), Micrococcus spp. (27%), and Staphylococcus spp. (19%). Other bacterial genera accounted for 10% of all of the identified microorganisms. In previous studies, the most commonly isolated microorganism was Staphylococcus spp. or Micrococcus spp. . The authors also showed the presence of bacteria from the Bacillus spp. genus. Sandle noted that 97% of the bacteria recovered from 40 Grade A and B cleanrooms and clean zones were Gram-positive. In this study, the vast majority of identified microorganisms were also Gram-positive bacteria, which is in agreement with the results reported by Cobo and Concha and Martin et al. . Gram-positive rods (for example, Bacillus) are usually transferred to cleanrooms on equipment or dust. Gram-positive cocci (such as Staphylococcus spp. and Micrococcus spp.) are usually associated with a normal human microbiota and therefore often occur in clean rooms . The bacterial species isolated in this study are usually nonpathogenic. Nevertheless, any contamination of ATMP entails the disqualification of the final product in accordance with GMP requirements. Therefore, to eliminate any risk of contamination of the product, continuous improvement of the procedures used, including the sanitization program for the cleanroom, is required. More than half of the microorganisms that cause contamination in cleanrooms for manufacturing aseptic products originate from the normal skin flora of the staff. Microorganisms can be isolated from staff working in cleanrooms, where full-body covers with hoods and masks are worn . Therefore, sampling from staff is another important element in the assessment of microbiological quality control. In this study, samples were collected from each staff member in a cleanroom after working with the cells of each donor. The most commonly isolated microorganisms were Bacillus spp. (43.4%), Staphylococcus spp. (28.7%), and Micrococcus spp. (24.6%), coinciding with the most commonly identified microorganisms in the monitored cleanroom environment. The percentage of positive samples decreased in the second year of manufacturing (1.68% compared to 1.94%). This is undoubtedly due to the acquisition of more staff experience and training during the manufacturing period. Lastly, it should be emphasized that even if a well-designed contamination control strategy is in place with regard to ATMPs that contain cells derived directly from the culture, the batch release is performed prior to obtaining all QC results. Faster, reliable microbial tests would be highly desirable, as they would significantly improve the safety of the patients receiving ATMPs. Given the development of cell-containing products with a short shelf life, there has been an intensive development of rapid microbiological methods (RMM) accepted by regulatory bodies as so-called "alternative methods" . However, for the products with shelf lives of a few hours, currently available RMMs which shorten the test from the classical 14 days to 7 days are still too long. To conclude, for ADSC-based ATMPs, the starting material should be considered contaminated. However, that does not prevent the obtaining of a sterile final product for release from the clinic as long as appropriate actions are taken. Additional routine decontamination steps should be included at the very beginning of manufacturing. Microbiological control at the stage of material acquisition in the clinic is indispensable, and the results should be taken into account in terms of further manufacturing steps. The proficiency of personnel in the conditions of a specific manufacturing process increases the quality of the production environment. Regardless of these specific implications, the results presented support the common voice of the community for the further development of rapid microbiological tests. Acknowledgments The study was carried out with the use of the infrastructure of the Center for Preclinical Research, the Medical University of Warsaw, Warsaw, Poland, financed by the European Union through the European Regional Development Fund within the operational program Innovative Economy for 2007-2013. Author Contributions Conceptualization, I.S.-G., A.C. and M.L.-S.; methodology, I.S.-G., M.H., J.B. and M.L.-S.; validation, I.S.-G., M.H., J.B., A.C., J.P. and T.O.; formal analysis, I.S.-G., M.H., J.B. and J.P.; investigation, I.S.-G., M.H., J.B. and J.P.; resources, M.H., J.B., A.C., J.P. and M.L.-S.; data curation, M.H., J.P. and M.L.-S.; writing-original draft preparation, I.S.-G., M.H., J.B., A.C. and M.L.-S.; writing-review & editing, I.S.-G., M.H., J.B., J.P., T.O., A.C. and M.L.-S.; visualization, I.S.-G., M.H., J.B., A.C. and M.L.-S.; supervision, I.S.-G., A.C., T.O. and M.L.-S.; project administration, A.C. and M.L.-S.; funding acquisition, A.C. and M.L.-S. 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 Bioethics Committee of Regional Medical Chamber, resolution number 33/17 (KB/1097/17). Informed Consent Statement Written informed consent was obtained from all subjects involved in the study. Data Availability Statement All data generated or analyzed during this study are included in the published article. Conflicts of Interest The authors declare that they have no conflict of interest. Figure 1 Subsequent stages of the procedure, from the collection of the starting material to the production of ATIMP; (A) overall schema of the whole process; (B) detailed manufacturing steps in the laboratory. The sampling points for sterility and endotoxin tests are marked with the letters S and E, respectively. Figure 2 Microbiota identified in lipoaspirates collected throughout the clinical trial are presented as the % of each genus out of all the identified microorganisms. All isolated bacteria of the Bacillus genus are presented together. Figure 3 The frequency of individual microorganisms isolated from contaminated lipoaspirates identified after incubation under aerobic and anaerobic conditions. All isolated bacteria of the Bacillus genus are presented together. Figure 4 Cleanroom microbiota identified during the two-year clinical trial presented as % of isolated genera out of all identified microorganisms. Figure 5 Microbial contamination observed in the samples taken from the staff (including glove prints). The diagram shows the total score for each individual employee by year over the course of the entire trial. Figure 6 Microbial flora identified in the samples taken from the staff (glove prints and work clothing) during the entire trial. The circles representing individual genera are proportional to the frequency of occurrence (indicated in brackets), presented as % of each type of identification out of all identified samples. cells-12-00680-t001_Table 1 Table 1 Contamination of the processed material at subsequent stages--from harvesting of the adipose tissue to the primary cell culture--observation from a two-year clinical trial. Year of Clinical Trial Total Number of Samples Stage 1 Fresh Tumescent Fluid Stage 2 Lipoaspirate Stage 3 Medium from the Isolated Cells Stage 4 Medium from the Last Wash of Cells Stage 5 Cell Culture Supernatant Number of Samples Positive/% Contaminated Number of Samples Positive/% Contaminated Number of Samples Positive/% Contaminated Number of Samples Positive/% Contaminated Number of Samples Positive/% Contaminated Year 1 276 56 1/1.8 56 25/44.6 56 8/14.3 56 3/5.4 52 0/0 Year 2 222 44 1/2.3 44 16/36.4 44 4/9.1 44 3/6.8 46 0/0 Total 498 100 2 100 41 100 12 100 6 98 0 cells-12-00680-t002_Table 2 Table 2 The number of samples contaminated with specific microorganisms in the subsequent stages of the isolation process. The data include the results of all samples from stages 2 to 4 collected throughout the clinical trial. A single probe could be contaminated with more than one species. All isolated bacteria of the Bacillus genus are presented together. Empty fields listed in the table represent that no samples were contaminated with microorganisms for that particular stage of the isolation process. Microorganism Stage Stage 2 Lipoaspirate Stage 3 Medium from the Isolated Cells Stage 4 Medium from the Last Cell Wash Staphylococcus epidermidis 22 5 2 Propionibacterium acnes 6 4 2 Bacillus 4 Staphylococcus capitis 4 1 1 Staphylococcus hominis 4 Staphylococcus lugdunensis 3 1 Staphylococcus caprae 2 1 Propionibacterium avidum 2 1 1 Micrococcus luteus 1 Rothia mucilaginosa 1 Staphylococcus warneri 1 cells-12-00680-t003_Table 3 Table 3 The number of samples taken from cleanroom environments with different sampling methods during a two-year clinical trial. Year of Manufacturing for Clinical Trial Number of Samples Collected from All Monitored Grade Areas Surface Sampling (Contact Plates) Passive Air Sampling (Settle Plates) Active Air Sampling (Volumetric Sampling) Year 1 11,670 4731 128 Year 2 7588 3389 128 Total 19,258 8120 256 cells-12-00680-t004_Table 4 Table 4 Data of positive samples from Grade A and B areas taken with different sampling methods. Statistically significant differences in the frequency of contamination in individual years are marked with square brackets. Sampling Surface GMP Grade Two-Year Manufacturing Period Differences between Years Year One Year Two Total Number of Samples Number of Positive Samples % of Positive Samples Total Number of Samples Number of Positive Samples % of Positive Samples Statistical Significance Cleanroom windows B 307 21 6.84 417 12 2.88 p < 0.05 Floor B 2200 45 2.05 1498 18 1.20 ns Door handles B 1300 30 2.31 875 3 0.34 p < 0.001 Walls B 1277 5 0.39 563 1 0.18 ns Devices B 1438 5 0.35 1005 1 0.10 ns Working surfaces A + B 2863 5 0.17 1901 0 0.00 ns Laminar air flow chamber A 2708 3 0.11 1798 0 0.00 ns Tables B 155 2 1.29 103 0 0.00 ns 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. 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PMC10000439 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051097 foods-12-01097 Article Study on Characteristics and Lignification Mechanism of Postharvest Banana Fruit during Chilling Injury Xiao Lu Conceptualization Methodology Software Formal analysis Data curation Writing - original draft 123 Jiang Xunyuan Methodology 123 Deng Yicai Methodology 123 Xu Kaihang Methodology 123 Duan Xuewu Project administration 4 Wan Kai Supervision Funding acquisition 123 Tang Xuemei Visualization Funding acquisition 123* Wang Yun Academic Editor 1 Institute of Quality Standard and Monitoring Technology for Agro-Products of Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China 2 Key Laboratory of Testing and Evaluation for Agro-Product Safety and Quality, Ministry of Agriculture and Rural Affairs, Guangzhou 510640, China 3 Guangdong Provincial Key Laboratory of Quality & Safety Risk Assessment for Agro-Products, Guangzhou 510640, China 4 Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China * Correspondence: [email protected]; Tel.: +86-020-85160430 04 3 2023 3 2023 12 5 109715 12 2022 22 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 banana is prone to chilling injury (CI) at low temperature and showing a series of chilling symptoms, such as peel browning, etc. Lignification is a response to abiotic stress and senescence, which is an important manifestation of fruits and vegetables during chilling exposure. However, little is known about the lignification of bananas during low-temperature storage. Our study explored the characteristics and lignification mechanism of banana fruits during low-temperature storage by analyzing the changes of chilling symptoms, oxidative stress, cell wall metabolism, microstructures, and gene expression related to lignification. The results showed that CI inhibited post-ripening by effecting the degradation of the cell wall and starch and accelerated senescence by increasing H2O2 content. For lignification, Phenylalanine ammonia-lyase (PAL) might start the phenylpropanoid pathway of lignin synthesis. Cinnamoyl-CoA reductase 4 (CCR4), cinnamyl alcohol dehydrogenase 2 (CAD2), and 4-coumarate--CoA ligase like 7 (4CL7) were up-regulated to promote the lignin monomer's synthesis. Peroxidase 1 (POD1) and Laccase 3 (LAC3) were up-regulated to promote the oxidative polymerization of lignin monomers. These results suggest that changes of the cell wall structure and cell wall metabolism, as well as lignification, are involved in the senescence and quality deterioration of the banana after chilling injury. banana peel chilling symptoms cell wall metabolism lignification mechanism National Natural Science Foundation of China32102452 Joint Foundation of Basic, Applied Basic Research of Guangdong Province2020A1515110100 Special Fund for Scientific Innovation Strategy-Construction of High-Level Academy of Agriculture ScienceR2021YJ-YB-3024 R2019YJ-YB3011 Guangdong Provincial Key Laboratory of Quality & Safety Risk Assessment for Agro-products2019B121203009 This research was funded by the National Natural Science Foundation of China, (32102452), Joint Foundation of Basic, Applied Basic Research of Guangdong Province (2020A1515110100), Special Fund for Scientific Innovation Strategy-Construction of High-Level Academy of Agriculture Science (R2021YJ-YB-3024, R2019YJ-YB3011), and Guangdong Provincial Key Laboratory of Quality & Safety Risk Assessment for Agro-products (2019B121203009). pmc1. Introduction Low-temperature storage, as one of the most useful technologies, can slow down the speed of cell metabolism and delay plant senescence to extend the post-harvest life of horticultural products . However, some tropical or subtropical fruits, such as banana and mango, are highly susceptible to chilling injury (CI). Low-temperature storage would cause appearance of physiological disorders and then negatively affect the fruit's quality and, therefore, their marketing . The CI symptoms can be observed in all developmental stages of the plant, which is related to the storage time, temperature of cold treatment, plant organ, and even developmental stage . The symptoms of CI include skin depression, abnormal skin yellowing, tissue decomposition, internal or surface browning, water infiltration in intercellular spaces, the development of a woolly or dry texture in the tissue, as well as developmental or metabolic disorders, such as incomplete ripening and deficient flavor and aroma. The injured tissue or organ expressed a lower resistance to mechanical injury, fungal infection, and microbial infection . Some studies suggested that the texture changes of certain CI-sensitive fruits during low-temperature storage are due mainly to disorders of cell wall metabolism, including a decrease in the solubalization and depolymerization of pectins . Lignification, a response to abiotic stress and natural senescence, is observed in many chilling-sensitive horticultural products, such as loquat , mangosteen , bamboo shoots , and pears . Generally, lignification is caused by the accumulation of lignin in plant cell walls and the biosynthesis of lignin has been widely studied in the model plant Arabidopsis, woody tress, and some other crops . However, the process of lignification has different pathways, and the synthesis and polymerization of lignification varies among different plant species and cultivars . Banana, as an typical tropical or subtropical fruit, is sensitive to chilling and suffers physiological damage when exposed to low-temperature (<13 degC) storage, generally resulting in peel browning, pitting, discoloration, and abnormal fruit ripening and softening . Chilling injury in horticultural products has been attributed to alterations in cell membrane structure and oxidative stress . Disorders in the composition of lipids, unsaturation, and the phase transition were accepted to be the primary response to CI, which lead to the changes of cell membranes components. Although the evident differences in CI symptoms have been studied, little attention has been paid to CI-induced lignification in the banana fruit. In this study, the objective was to investigate the characteristics of CI as well as the mechanism of lignification induced in harvested banana fruits during storage at a low temperature. Some related physiological indexes, including chilling symptoms, cell wall component, enzyme activity, observation of tissue structure, and related gene expression, were tested and analyzed. This study provides a theoretical basis for the study of alleviating the symptoms of banana chilling injury by exploring its mechanism. 2. Materials and Methods 2.1. Plant Materials and Treatments Green mature banana (Musa spp., AAA group cultivar "Brazil'') fruit (approximately 110 days after anthesis) was harvested from an orchard in Shawei Village, Wanqingsha Town, Nansha District, Guangzhou city, Guangdong province, China (E 113deg35'20.93'', N 22deg39'35.68'') and transported to the laboratory within 2 h. Banana fruit fingers were cut and then dipped in 0.1% Sportak(r) (Prochloraz, Bayer, Germany) fungicide solution for 3 min and finally allowed to air-dry. Fruit with uniform shape, color, and size were selected and randomly divided into two groups, which were stored at 25 degC or 6 degC respectively with 85-90% relative humidity depending on the allocated group. During storage, samples were periodically taken to measure the related physiological indexes. Some indicators related to the appearance, senescence, cell wall metabolism were measured. Some enzymes were related to the phenylpropanoid pathway and peel browning, including the up-stream enzymes PAL, PPO, and POD, were analyzed. Banana peel tissues were collected, frozen in liquid nitrogen, and stored at -80 degC for RNA extraction and physicochemical indexes analysis. Each treatment consisted of three biological replicates, with each replicate containing 60 fruit fingers. 2.2. Physiological Parameters Firmness. Fruit firmness was measured with a penetrometer (Model FT 327, Facchini, Alfonsine, Italy) by recording the force needed to penetrate 5 mm into the middle part of whole fruit. The flat probe of penetrometer is 8 mm in diameter. The results were expressed as N. Peel color. Banana peel color was measured with a Konica Minolta CR-400 colorimeter (Konica Minolta Co. Ltd., Japan) in the CIEL*a*b mode. L* indicated the lightness ranging from black to white, C* represented the color saturation that varied from dull to vivid, and hue angle (h*) referred to a color wheel: red at an angle of 0deg, yellow at 90deg, green at 180deg, and blue at 270deg in accordance with the method by McGuire . Chlorophyll fluorescence. Chlorophyll fluorescence of the banana peel was determined using a portable chlorophyll fluorometer (PAM 2100, Walz, Germany). Minimum and maximum fluorescence yields (Fo, Fm) were measured on dark-adapted (30 min) fruit. Fo was measured with a measuring beam at a light intensity less than 0.05 mmol m-2 s-1, while Fm was obtained by measuring chlorophyll fluorescence during a 2.5 s pulse of saturating light (18,000 mmol m-2 s-1). The maximal variable fluorescence (Fv = Fm-Fo) and PSII quantum yield (Fv/Fm) were calculated from the Fo and Fm values. Protopectin content. Protopectin was extracted and determined according to the method of Lu et al. with some modifications. Frozen banana peel (5.0 g) was extracted in 100.0 mL 95% ethanol with boiling for 30 min. After cooling to room temperature, the tissue was centrifuged (5000x g) for 10 min at 25 degC and the supernatant was removed. Then, the residue was washed twice with 10.0 mL ethanol and the supernate was removed. The precipitate was hydrolyzed in H2SO4 (0.5 M) at 90 degC for 1 h. After cooling to room temperature, the sample was centrifuged (8000x g) for 15 min at 25 degC and the supernate was collected for protopectin analyzation. The following experimental operations mainly referred to corresponding assay kits (Comin biotechnology Co., Ltd., Suzhou, China) in accordance with the manufacturer's instructions. The absorbance was analyzed by Multiskan Spectrum (Multiskan Go 1510, Thermo Fisher Scientific Oy Ratastie 2, Vantaa Finland) at 530 nm. Protopectin content (mg g-1 FW) = mst * VTS * DA2/(DA1 * m * VS); 'mst'--the quality of the standard substance, mg; 'VTS'--total volume of enzyme-extracting solution, mL; 'VS'--volume of the reactive enzyme liquid added; 'm'--fresh weight of banana peel, g; DA1530nm = Astandard - Ablank, DA2530nm = Atest - Acontrol. Cellulose content. Cellulose contents were determined using the anthrone method. Frozen banana peel (3.0 g) was homogenized in 10.0 mL ethanol of 80% for 20 min at 90 degC. After cooling to room temperature, the homogenate was centrifuged (6000x g) for 10 min at 25 degC and the supernate was removed. The precipitate was added to 1.0 mL DMSO for 15 h to remove starch and then centrifuged (6000x g) at 25 degC for 10 min to remove the supernate. The precipitate was dried as cell wall materials (CWM). A total of 50.0 mg of dried CWM was homogenized in distilled water (5.0 mL) and then added 7.5 mL H2SO4 slowly and incubated in ice water for 30 min. Then, the homogenate was centrifuged at 4 degC for 10 min (8000x g) and the supernate was collected for cellulose content analysis. After adding anthrone reagent and incubating at 95 degC for 10 min, the absorbance of sample was measured against a distilled water blank at 620 nm. Cellulose content (mg-1 g-1 DW) = [(DA620nm + 0.0043) * VS/5.25]/(m * VS/Vt); 'DA620nm' = Atest - Ablank; 'VS'--volume of the extracting solution added, mL; 'VT'--total volume of extracting solution, mL; 'm'--dry weight of banana peel, g; '20'--dilution ratio of sample; '0.0043' and '5.25' were from the regression equation (y = 5.25x - 0.0043, R2 = 0.9987) under standard conditions. Lignin content. Lignin was extracted and measured by the method of Bruce and West . Three grams of frozen tissue powder was homogenized in 10.0 mL 99.5% (v/v) ethanol and centrifuged at 20,000x g for 20 min. The pellet was dried overnight at room temperature. Fifty milligrams of dried residue was suspended with 5.0 mL of 2 M HCl and 0.5 mL of thioglycolic acid. The sample was heated at 100 degC for 8 h and cooled on ice, then centrifuged at 20,000x g for 20 min (4 degC) and the supernate was remove. The pellet was washed with distilled water and re-suspended in 5.0 mL 1 M NaOH. The solution was agitated gently at 25 degC for 18 h and then centrifuged at 20,000x g for 20 min. One milliliter of concentrated HCl was added to the supernate and the lignin thioglycolic acid was allowed to precipitate at 4 degC for 4 h. After centrifugation at 20,000x g for 20 min, the pellet was dissolved in 1.0 mL of 1 M NaOH. The absorbance was measured against a NaOH blank at 280 nm, and data was expressed on a dry weight basis. Lignin content (mg g-1 DW) = [(DA-0.0068) * VTA * 10-3 * N]/(0.0347 * m); 'DA' = Atest - Abalnk; 'VTA'--total volume of the reaction system, mL; 'm'--dry weight of banana peel, g; 'N': '0.0068' and '0.0347' were from the regression equation (y = 0.0347x - 0.0068, R2 = 0.9889) under standard conditions. Superoxide anion and H2O2 content. Superoxide anion and H2O2 content were determined using corresponding assay kits (Comin biotechnology Co., Ltd., Suzhou, China) in accordance with the manufacturer's instructions. Extration and assay of PPO, POD and PAL. Peel tissues (2.0 g) from three fruit were ground in liquid nitrogen and homogenized in 20.0 mL of 0.05 M phosphate buffer (pH 7.0) and 0.5 g of polyvinylpyrrolidone (insoluble) at 4 degC. After centrifugation for 20 min at 19,000x g and 4 degC, the supernate was collected as the crude enzyme extract of the analysis of PPO and POD activity. PAL activity was extracted with 50 mM sodium phosphate buffer (pH 8.8) containing 5 mM b-mercaptoethanol. According to the method of Jiang with some modifications, PPO activity was measured with 2.9 mL reaction liquid (10 mM pyrocatechol prepared with phosphate buffer) and 0.1 mL enzyme-extracting solution. After adding enzyme-extracting solution, the change in the OD525nm value was measured. One unit of enzyme activity was defined as the amount that cause a change of 0.005 in the absorbance at 525 nm per minute. PPO activity (OD525nm g-1 min-1 FW) = DOD525nm * Vt/(Vs * m * DT * 0.005); 'Vt'--total volume of enzyme-extracting solution, mL; 'Vs'--volume of the reactive enzyme liquid added, mL; 'm'--fresh weight of banana peel, g; 'DT'--reaction time, min. POD activity was measured with 0.1 mL guaiacol (4.0%), 0.1 mL hydrogen peroxide (0.46%), 2.75 mL phosphate buffer (pH 6.8), and 0.05 mL enzyme-extracting solution. After adding enzyme fluid, the change value of the absorbance of 0.005 at 470 nm was measured. One unit of enzyme activity was defined as the amount that caused a change of 0.01 in the absorbance at 470 nm per minute. PPO activity (OD470nm g-1 min-1 FW) = DOD470nm * Vt/(Vs * m * DT * 0.005). PAL activity was assayed with the method of Assis et al. with some modifications. A total of 1 mL of the supernate was added to 2.0 mL 50 mM borate buffer (pH 8.8) and 1.0 mL 20 mM 1-phenylalanine and then incubated in a water bath at 37 degC for 2 h. The reaction was stopped by adding 1.0 mL 1 M HCl. Trans-cinnamate formed and the absorbance was assayed at 290 nm. One unit of enzyme activity was defined as the amount that caused a change of 0.05 in the absorbance at 290 nm per minute. PAL activity (OD290nm g-1 min-1 FW) = DOD290nm * Vt/(Vs * m * DT * 0.005). All absorbance values were analyzed by using Multiskan Spectrum and the results were expressed on a fresh weight basis. Cellulase activity. Cellulase activity was determined by the anthrone colorimetry method. A total of 2 g frozen tissue powder was dissolved in 20.0 mL sodium phosphate buffer (20 mM, pH 7.0) containing cysteine, HCl (20 mM), EDTA (20 mM), and TritonX-100 (0.05%). Then, the homogenate was centrifuged at 15,000x g for 30 min at 4 degC and the supernate was collected for enzyme activity analysis. The enzyme was added in sodium acetate buffer (100 mM, pH 5.0) containing carboxy methyl cellulose (1.0% w/v) in a final volume of 10.0 mL. The mixture was incubated at 37 degC with vibration for 1 h and was then incubated at 90 degC for 15 min. After cooling down, the mixture was centrifuged at 8000x g for 10 min at 25 degC. The supernate was saccharification solution added with authrone and then incubated at 90 degC for 10 min. After another cooling, the samples were analyzed at 620 nm. One unit of cellulase activity is defined as the amount of the enzyme that releases 1.0 mg glucose per milligram of fresh weight per minute. Cellulase activity (mg min-1 g-1 FW) = [1000 * (DA + 0.0462) * VTA * VT]/[2.509 * (m * Vs) * T]; '1000'--1 mg mL-1 = 1000 mg mL-1; 'VTA'--total volume of the reaction system, mL; 'Vs'--volume of sample added, mL; 'VT'--total volume of enzyme-extracting solution, mL; 'T'--reaction time, min; '0.0462' and '2.509' were from the regression equation (y = 2.509x - 0.0462, R2 = 0.9956) under standard conditions. a-amylase and b-amylase activity. a-amylase and b-amylase were determined with the 3, 5-dinitrosalicylic acid method according to the characteristics that a-amylase was not resistant to acid and b-amylase was not resistant to the heat (70 degC). Assay kits (Comin biotechnology Co., ltd., Suzhou, China) were used to analysis enzyme activity in accordance with the manufacturer's instructions. Scanning electron microscopy observation and analysis. The banana peel was cut into regular squares and then fixed with glutaraldehyde (2.5% glutaraldehyde and 2% paraformaldehyde) overnight and vacuumed. The glutaraldehyde was washed with 0.1 M phosphate buffer for 40 min, three times in total, and the samples were then dehydrated with 30%, 50%, and 70% ethanol for 20 min each time, followed by further dehydration with 80%, 90%, and 100% ethanol for 20 min each time. Finally, the samples were washed three times with tert-butanol for 20 min each time. The samples were finally freeze-dried and sprayed with gold (180 s, 20 mA) using the JFC-1600 (JEOL, Tokyo, Japan) ion sputtering instrument. The specimens were observed with a JSM-6360 LV (JEOL, Tokyo, Japan) scanning electron microscope (SEM) at 15 KV. Quantitative real-time PCR analysis. DNA-free RNA was reverse-transcribed for first-strand cDNA synthesis. The gene-specific oligonucleotide primers were used for qRT-PCR analysis (Table S1). The qRT-PCR reactions for some genes related with synthesis of lignin were carried out in the ABI 7500 Real-Time PCR System (Applied Biosystems, Carlsbad, CA, USA) with SYBR Green Real-Time PCR Master Mix (TOYOBO Co., Ltd.). The conditions were as follows: 30 s at 95 degC, 40 cycles of 5 s at 95 degC, and 34 s at 58 degC. MaActin-3 was selected as the reference gene . qRT-PCR reactions were normalized using the Ct value corresponding to that of the reference gene. The relative expression levels of target genes were calculated using the formula 2-DDCT. Three independent biological replicates were performed in the analysis. 2.3. Statistical Analysis The experiments were arranged in a completely randomized design with three replicates, and the data were expressed as the mean +- SD (standard deviation). Data were analyzed by SPSS version 19.0. Least significant differences (L.S.D.) were calculated to compare significant effects at the 5% level. 3. Results and Discussion 3.1. Chilling Symptoms Many tropical and subtropical fruits are sensitive to low temperatures and suffer different physiological disorders, known as CI. The incidence by CI limits the application of cold storage. Bananas are sensitive to chilling and suffer physiological damage when exposed to low-temperature (<13 degC) storage . As shown in Figure 1A, banana fruit began to exhibit the CI symptoms of pitting and brown patches on the skin after 3 days of storage at 6 degC and became severe as the storage days prolonged when compared with the control group. The hue angle of banana peel decreased significantly on the third day . the Fv/Fm ratio, which refers to chlorophyll content, also decreased as the CI symptoms appeared , which was consistent with the browning and discoloration symptoms shown in Figure 1A. On the sixth day of storage, the firmness of bananas stored at 25 degC steadily decreased as the storage prolonged and decreased by 11.9% compared with the firmness of bananas stored at 6 degC . Softening is an important manifestation of banana ripening. The higher firmness might be related to the lignification of peel or abnormal fruit ripening, which indicated that CI might accelerate the lignification of banana peel and affect the normal ripening of banana fruit. 3.2. Oxidative Stress, H2O2 Alterations in the biomembrane conformation and structure are considered the first events at the molecular level of CI. Different degrees of CI-induced cell membranes have been shown, including the increase in electrolyte leakage , lipid-phase transitions , and changes in lipid composition . Among them, low-temperature-induced membrane lipid-phase transition was used to explain the membrane integrity and physiological dysfunction . Apart from the direct effect of low temperatures on the molecular organization of membrane lipids, low-temperature stress boosted the damage of membrane integrity by a disproportionate increase in reactive oxygen species (ROS) production . When the CO2 fixation is limited by environment stresses, such as CI, an excess of photosystem I reduction and ROS production is observed . In addition, the activation of NADPH oxidase in cell membrane can induce a massive production of O2- . In our present study, the production rate of banana peels stored at 6 degC increased during first two days and then decrease in the later storage days , and it was higher than that of control group by 43.1% on 2nd day. As shown in Figure 2B, for the banana stored at 6 degC, the H2O2 content of banana peels was higher than that of control group during the entire storage period. It indicated that CI might induce oxidative stress by increasing the content of H2O2. 3.3. Peel Browning, PPO, POD and PAL Tissue browning is a common CI symptom in fruit and vegetables . The visual CI symptoms of banana fruit are peel browning and pitting or discoloration. However, an early or mild symptom was darkening of the peel vascular tissues. Such symptoms appear due to enzymatic and non-enzymatic browning reactions involving oxidation of phenolic substrate and pigment degradation . Polyphenol oxidase (PPO) and peroxidase (POD) are believed to be a major cause of brown discoloration by the oxidation of phenolic substrates and have synergistic effects on the formation of brown polymers . As shown in Figure 3A, the PPO activity decreased and then increased as storage days prolonged. During the first two days, the banana peel exposed to low temperature (6 degC) exhibited a decrease in the activity of PPO than that of control group. It might be due to the low temperature inhibiting PPO activity at the very onset of storage, while there was dramatically increased PPO activity to response to the cold stress. POD can oxidize phenols to quinones, then condense tannins to brown polymers in the presence of H2O2, which may contribute to enzymatic browning . Furthermore, POD plays a very important role in the growth and development of plants, such as improving the adaptability of plants to the external environment, increasing the thickness of the secondary wall of plant cells by regulating lignin synthesis, and protecting the cells . As shown in Figure 3B, the POD activity of the two groups showed similar changes that decrease in the first days of storage and then increase in the later storage days. However, the POD activity increased rapidly under low-temperature storage than that of the control group from the fourth day, which might be attributed to the accumulated reactive oxygen species under CI, triggering a rapid increase in POD activity. Phenylalaninammo-nialyase (PAL) is a vital enzyme between the shikimate pathway and secondary phenylpropanoid pathway, which can convert phenylalanine to diphenols, which are substrates of PPO . PAL activity could be induced by various stresses, including wounding, UV-B light, ozone, pathogen invasion, and plant hormones . Parkin et al. suggested that there was an elevation in PAL synthesis activity in fruits occurring at low temperatures, which likely contributed to the increase of phenol concentration in these tissues upon CI. Moreover, the PAL also plays a role in the heat pretreatment-induced chilling tolerance of banana fruit . In our study, for banana stored at 6 degC, PAL activity of banana peel tended to increase with the aggravation of CI symptoms (such as browning) and was significantly higher than that of control group by 70.2% and 92.2% on the 4th and 6th day, respectively . This was also consistent with the report by Choehom et al. that PAL was involved in the browning reaction . 3.4. Cell Wall Metabolism, Content of Lignin, Cellulose and Protopectin, Activity of Cellulase and Pectinase It had been reported that the texture changes of certain CI-sensitive fruits under low-temperature storage were due mainly to disorders of cell wall metabolism, including a decrease in the solubilization and depolymerization of pectin . Lignin is the major constituent of the secondary cell wall in plants and is involved in plant growth, development, and defense . In our study, the lignin content of banana peels stored at 6 degC was increased from 30.03 to 35.04 mg g-1 DW, while the lignin content of banana peels stored at 25 degC did not change significantly . The increase of lignin content was consistent with the increase in firmness, which indicated that the low temperature promoted the lignification of banana fruit. Cellulose is the most dominant constituent of plant cell walls . As shown in Figure 4B, the cellulose content of banana stored at 25 degC decreased as the storage days prolonged, while the bananas stored at 6 degC exhibited a non-significant change. It indicated that CI inhibited the degradation of cellulose and then affected cell wall metabolism. Pectin is a common component of the middle lamella and the primary cell walls in the fruit texture, constituting approximately one third of the structure . Pectin solubilization is a common feature of fleshy fruit ripening. As shown in Figure 4C, the protopectin content of banana peels stored at 6 degC increased rapidly and then decreased slowly, which showed a higher level than the control group. The changes of fruit texture are closely related to the degradation of cell wall components, such as the degradation of protopectin and the increase of soluble pectin content . In our study, low temperature could cause metabolic disorder of the cell wall and inhibit the degradation of cellulose and protopectin, thus inhibiting the post-ripening of banana fruit and promoting lignification of banana peels. The major textural changes resulting in the fruit softening are related to enzyme-mediated alterations in the structure and composition of the cell wall, including the changes in cell wall composition mentioned above, as well as the changes of related enzyme activity. As shown in Figure 5A, in the first two storage days, the cellulase activity increased gradually, which was consistent with the decrease in cellulose content for the two groups. As the storage period was prolonged, the cellulase activity decreased for bananas stored at 25 degC, and the cellulose content increased form the forth storage day. However, for bananas stored at 6 degC, the cellulase activity for banana peels basically remained unchanged, while cellulose content increased slightly . On the fourth and sixth day of low-temperature storage, the cellulose content was 53.79% and 25.43% higher than that stored at 25 degC, respectively , which indicated that low-temperature storage affects the cell wall component. As shown in Figure 5B, for the bananas stored at 25 degC, pectinase activity was decreased during the whole storage period, while the protopectin content was also decreased, which might due to protopectin being not the only substrate of pectinase, which needs further investigation. For the pectinase activity of banana peel at 6 degC, it rapidly decreased during the first storage days and then increased in the later storage days, and the protopectin content was increased first and then decreased . In the early storage stage, pectinase activity was inhibited by cold stress, and with the enhancement of adaptability to low temperature in the later stage, the pectinase activity was increased to degrade the content of pectin. These results indicated that chilling injury caused the disorder of metabolism of the banana peel cell wall and finally led to the change in the cell wall composition. As the results above, bananas could change the structure of their cell wall by affecting cell wall metabolism to respond to cold stress during storage at a low temperature. 3.5. Ultrastructural Changes of Banana Peel after Chilling Injury In addition to the structural alteration and rearrangements of the cell wall, the tissue structure was also significantly changed by scanning electron microscopy (SEM) observation. As shown in Figure 6A, the boundary of epidermal cells on the banana peels stored at a low temperature were blurred. Starch is the main form of carbon storage in bananas, and the unripe bananas have a large amount of starch. In our present study, the starch grains in banana peels stored at 25 degC decreased gradually as the storage time prolonged and were almost degraded on the 6th day of storage, while the starch grains in banana peels stored at 6 degC basically remained unchanged . Furthermore, the a/b amylase activity of banana peels were analyzed. During the storage period, the a-amylase content in banana peel of the two treatment groups showed a trend of rapid decrease in the first two days and then remained basically unchanged . The b-amylase in banana peels remained basically unchanged under low-temperature storage, while it increased significantly in the control group . This was consistent with the decrease of starch grains in Figure 6B. These results indicated that b-amylase might play a vital role in the degradation of starch grains in banana peels, and CI might inhibit the post-ripening of bananas by affecting the degradation of starch grains. In addition, we found that the tissue structure and cell structure (such as vascular bundle cells) of the longitudinal section of banana peels had no significant changes before and after CI . 3.6. Expression Profiles of Many Genes Involved in Lignification Caused by CI To further understand the mechanism of lignification in bananas after CI, some genes possibly involved in the lignification process were selected for gene expression analysis, as shown in Figure 7, including POD1, PAL, LAC3, CCR4, CAD2, and 4CL7. Studies have shown that POD and PAL are the key enzymes of lignification, and the enzyme activities increase significantly as lignification occurs . POD is an oxido-reductive enzyme that participates in the cell wall polysaccharide processes, such as the oxidation of phenols, suberization, and lignification . In our present study, the gene expression of POD1 for chilled banana peels was down-regulated at the early storage stage, then up-regulated from the second day, and finally higher than that of the control group at the end of the storage period . This is consistent with the change of POD activity . LAC has also been reported to be implicated in the polymerization of lignin and is required for lignification in plants . It has been reported that AtmiR397b can reduce the lignin deposition by negatively regulating LAC4 . ZmmiR528 regulates lignin biosynthesis and lignification by negatively regulating LAC3 and LAC5 . In our study, the gene expression of LAC3 increased dramatically, especially on the fourth day , which was consistent with the change in PAL activity. It indicated that PAL, POD, and LAC play important roles in the lignification of banana peels under chilling injury. Lignin is one of the important products of the phenylpropane metabolism pathway, and its biosynthesis involves many enzymes, such as CCR, CAD, and 4CL. CCR is the first rate-limiting enzyme in the lignin synthesis pathway, which has a potential regulatory effect on lignin monomer biosynthesis . CAD is the earliest studied enzyme in the lignin synthesis pathway and is the last step to catalyze the formation of the lignin monomer . CAD can convert aldehydes into alcohols and plays an important role in the proportion regulation of lignin monomer synthesis . At the terminal position is 4CL in the phenylpropanoid derivative metabolic pathway and is the last enzyme that turns the phenylpropanoid metabolic pathway to the downstream branch pathway. As the key enzyme that connects the phenylpropanoid metabolic pathway to the specific lignin synthesis pathway, 4CL plays a rate-limiting role in the lignin monomer synthesis pathway . In our study, the gene expressions of CCR4, CAD2, and 4CL7 were significantly up-regulated during the storage for chilled banana fruit, which was involved in the lignification process for bananas after chilling injury . It indicated that under cold stress, the lignin synthesis-related genes were up-regulated to promote the lignification of banana peels, which could reinforce the cell walls to alleviate the damage caused by cold stress. 4. Conclusions Low-temperature storage can improve the storage quality of fruits and vegetables but also has adverse effects on heat sensitive fruits and vegetables. The study comprehensively elucidated the involvement of chilling symptoms and the mechanism of lignification for bananas after chilling injury. In the present study, banana peel browning induced by chilling injury was promoted by the degradation of chlorophyll and the increased activity of POD and PAL. Chilling injury accelerated the senescence of banana fruit by increasing the content of hydrogen peroxide. In addition, chilling injury affected the normal post-harvest ripening process of banana fruit by inhibiting the normal degradation of starch grains and metabolism of the cell wall. We found that lignification, as a response to abiotic stress and senescence, is an important manifestation of banana fruits after chilling injury. The study showed that PAL might start the phenylpropanoid pathway of lignin synthesis, while the synthesis of lignin monomers was promoted by up-regulating the expression of the CCR4, CAD2, and 4CL7 genes. Then, the POD1 and LAC3 genes were up-regulated to promote the oxidation of lignin monomers. POD1 and LAC3 were finally up-regulated to promote the oxidative polymerization of lignin monomers. These results suggest that changes in cell wall structure and metabolism, as well as lignification, are involved in the senescence and quality deterioration of bananas after chilling injury. Studies on the characteristics and lignification mechanisms of bananas involved in chilling injury will provide a theoretical basis for heat-sensitive fruits and vegetables to alleviate CI. Acknowledgments The work and experimental material were also supported by Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou. Supplementary Materials The following supporting information can be downloaded at: Figure S1. Changes of amylase activity in banana peel during storage at 6 degC and 25 degC. a-amylase activity (A), b-amylase activity (B). Each data point represents a mean +- standard error (n = 3). '*' means a significant difference between control and experimental fruit at 5% level. Figure S2. Ultrastructural changes of banana peel during storage at 6 degC and 25 degC were observed by scanning electron microscope. Parenchyma cells (A) and vascular cells (B) of banana peel during storage. Table S1. Primers used for RT-qPCR. Click here for additional data file. Author Contributions L.X.: conceptualization, data curation, formal analysis, methodology, software, writing--original draft. X.J., Y.D. and K.X.: methodology. X.D.: project administration, K.W. and X.T.: funding acquisition, supervision. 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 or Supplementary Materials. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Chilling injury characteristics of banana fruit during storage at 6 degC. Fruit stored at 25 degC is the control. Changes in chilling injury phenotype (A), hue angle (B), Fv/Fm (C), and firmness (D) of banana fruit during storage. Each data point represents a mean +- standard error (n = 3). '*' means a significant difference between control and experimental fruit at the 5% level. Figure 2 Changes in oxidative stress of banana fruit during storage at 6 degC and 25 degC. Production rate of superoxide anion (A) and H2O2 content (B) of banana peels during storage. Each data point represents a mean +- standard error (n = 3). '*' means a significant difference between control and experimental fruit at the 5% level. Figure 3 Changes in enzyme activity associated with browning of banana fruit during storage at 6 degC and 25 degC. PPO activity (A), POD activity (B), and PAL activity (C) of banana peel during storage. Each data point represents a mean +- standard error (n = 3). '*' means a significant difference between control and experimental fruit at the 5% level. Figure 4 Changes in cell wall component of banana fruit during storage at 6 degC and 25 degC. Lignin content (A), cellulose content (B), and protopectin content (C) of banana peels during storage. Each data point represents a mean +- standard error (n = 3). '*' means a significant difference between control and experimental fruit at 5% level. Figure 5 Changes of enzyme activity related to cell wall degradation of banana fruit during storage at 6 degC and 25 degC. Cellulase activity (A) and pectinase activity (B) of banana peels during storage. Each data point represents a mean +- standard error (n = 3). '*' means a significant difference between control and experimental fruit at 5% level. Figure 6 Structural changes of banana peel were observed by scanning electron microscope during storage at 6 degC and 25 degC. Epidermis structure (A) and Starch granules (B) of banana peel during storage. Figure 7 Changes in the relative expression of genes associated with lignification in banana peels during storage at 6 degC and 25 degC. POD1 (A), PAL (B), LAC3 (C), CCR4 (D), CAD2 (E), and 4CL7 (F). Each data point represents a mean +- standard error (n = 3). The values with different letters for different storage temperature for each sampling date are significantly different (p < 0.05). 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PMC10000440 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050782 cells-12-00782 Article PGNneo: A Proteogenomics-Based Neoantigen Prediction Pipeline in Noncoding Regions Tan Xiaoxiu Conceptualization Software Formal analysis Data curation Writing - original draft 12 Xu Linfeng Software 2 Jian Xingxing Writing - review & editing 2 Ouyang Jian Software 2 Hu Bo Resources 3 Yang Xinrong Resources 3 Wang Tao Supervision 1* Xie Lu Conceptualization Writing - review & editing Supervision 2* Xue Yu Academic Editor 1 Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China 2 Shanghai-MOST Key Laboratory of Health and Disease Genomics & Institute of Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China 3 Liver Cancer Institute, Fudan University, Shanghai 200032, China * Correspondence: [email protected] (T.W.); [email protected] (L.X.) 01 3 2023 3 2023 12 5 78227 1 2023 26 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 ). The development of a neoantigen-based personalized vaccine has promise in the hunt for cancer immunotherapy. The challenge in neoantigen vaccine design is the need to rapidly and accurately identify, in patients, those neoantigens with vaccine potential. Evidence shows that neoantigens can be derived from noncoding sequences, but there are few specific tools for identifying neoantigens in noncoding regions. In this work, we describe a proteogenomics-based pipeline, namely PGNneo, for use in discovering neoantigens derived from the noncoding region of the human genome with reliability. In PGNneo, four modules are included: (1) noncoding somatic variant calling and HLA typing; (2) peptide extraction and customized database construction; (3) variant peptide identification; (4) neoantigen prediction and selection. We have demonstrated the effectiveness of PGNneo and applied and validated our methodology in two real-world hepatocellular carcinoma (HCC) cohorts. TP53, WWP1, ATM, KMT2C, and NFE2L2, which are frequently mutating genes associated with HCC, were identified in two cohorts and corresponded to 107 neoantigens from non-coding regions. In addition, we applied PGNneo to a colorectal cancer (CRC) cohort, demonstrating that the tool can be extended and verified in other tumor types. In summary, PGNneo can specifically detect neoantigens generated by noncoding regions in tumors, providing additional immune targets for cancer types with a low tumor mutational burden (TMB) in coding regions. PGNneo, together with our previous tool, can identify coding and noncoding region-derived neoantigens and, thus, will contribute to a complete understanding of the tumor immune target landscape. PGNneo source code and documentation are available at Github. To facilitate the installation and use of PGNneo, we provide a Docker container and a GUI. neoantigen noncoding regions proteogenomics prediction pipeline tumor immunotherapy National Natural Science Foundation of China31870829 Shanghai Municipal Health Commission Collaborative Innovation Cluster Project2019CXJQ02 This work was supported by the National Natural Science Foundation of China (31870829), Shanghai Municipal Health Commission Collaborative Innovation Cluster Project (2019CXJQ02). pmc1. Introduction Neoantigens are considered to be promising therapeutic targets owing to their tumor specificity, and to their neither being affected by pre-existing immune tolerance nor generating autoimmunity . Thus, neoantigens can be used as potential targets for therapeutic vaccines. A neoantigen vaccine is designed to trigger de novo T cell response and broaden the endogenous repertoire of tumor-specific T cells . A phase-I trial of a neoantigen-based peptide vaccine showed that four patients with stage III melanoma induced CD4+ T cell and CD8+ T cell responses after vaccination and remained disease-free for a median follow-up of 25 months after vaccination. This demonstrates the potent tumor-specific immunogenicity and antitumor activity of neoantigen vaccines . However, one major challenge in neoantigen vaccine design is the rapid and accurate identification of neoantigens that can induce T cell responses in patients. The advent of next-generation sequencing has provided opportunities to efficiently identify tumor-specific antigens in individual patients, leading to the exploration of clinical target therapies. In fact, several pipelines have been developed to predict neoantigens, such as pVACtools , NeoPredPipe , Neopepsee , etc. Although the development of these tools has opened the way for identifying potentially immunogenic neoantigens , limitations to these tools exist. First, most traditional prediction pipelines were developed based on genomic and transcriptomic data. Many false-positive neoantigens inevitably occur, due to the large number of mutations in individual patients and the limited performance of MHC ligand binding prediction . In addition, studies have shown that the mRNA measurements of many genes correlate poorly with protein expression . With advances in mass spectrometry (MS)-based proteomics, the combination of proteomics and genomics, i.e., proteogenomics, has been a major force in driving personalized neoantigen vaccine identification . It allows the presence verification of those peptides that are most likely to generate an immune response based on neoantigen prediction pipelines; thus, such peptides may be moved into subsequent functional selection processes. Proteogenomics has greatly reduced the number of false positives for predicted neoantigens and has eased the burden of experimental validation. Our group previously developed proteogenomics neoantigen prediction pipelines, ProGeo-neo and ProGeo-neo2.0 , and WEN B et al. developed NeoFlow . Another limitation of the currently existing neoantigen prediction pipelines is that they almost all focus on genomic coding regions. While variants in protein-coding regions have received the most attention, numerous studies have noted the importance of noncoding variants in cancers . Exomes only account for 2% of the human genome, whereas up to 75% of the genome has been shown to be transcribed and potentially translated . Therefore, many allegedly noncoding regions are actually protein-coding. For example, long noncoding RNAs (LncRNA) are a type of noncoding RNA with a length of more than 200 nt, lacking a protein-coding function due to the lack of a complete open read frame (ORF) . Intriguingly, several recent studies have noted LncRNAs as a source of new peptides . Of particular relevance to tumor neoantigen discovery, 99% of cancer mutations are located in noncoding regions . Therefore, focusing on the exome as the only source of tumor neoantigens is very restrictive. Notably, peptides derived from the noncoding regions have been shown to bind to MHC molecules, some of which were identified as the targets of T cells . Subsequently, landmark studies demonstrated that the noncoding regions are the main source of targetable tumor-specific antigens . However, an efficient and easy-to-use tool to predict and investigate the personalized neoantigens from noncoding regions is still lacking. Herein, we present PGNneo, an integrated computational pipeline to predict noncoding neoantigens from RNA-seq and MS data. We demonstrated the effectiveness of PGNneo and validated our methodology in two real-world hepatocellular carcinoma (HCC) cohorts. In addition, we applied PGNneo to a colorectal cancer (CRC) cohort, demonstrating that the tool can be extended and verified in other tumor types. PGNneo is an efficient tool to identify noncoding neoantigens and can be easily installed and deployed at To be more user-friendly, we also provide a Docker version at ) and a GUI. 2. Methods 2.1. Data Collection The paired-end sequencing data of lncRNA from 5 HCC patient-derived xenograft (PDX) samples, including tumor and normal tissues, were obtained from Hu et al. . The proteomics datasets of the HCC cell line were downloaded from the ProteomeXchange Consortium ) (accessed on 21 September 2020) with the identifier, PXD000529. This cohort is hereinafter referred to as HCC_HF. Another HCC cohort (hereinafter referred to as HCC_HT) from a previous collaboration with Jiang et al. included RNA-seq files and MS raw data from 10 patients (early stage of HCC, subtype 3) were downloaded from the Gene Expression Omnibus (GEO) (accession number GSE124535) (accessed on 15 November 2021) and iProX database accession number IPX0000937000) (accessed on 15 November 2021), respectively. Detailed sample information is provided in Table S1 in the Supplementary Materials. In addition, we collected a CRC cohort , including RNA-seq data and MS raw data from three CRC cell lines and RNA-seq data from one normal fetal small intestine cell line. This can be downloaded from the GEO (accession number GSE195985) (accessed on 2 October 2022) and the ProteomeXchange Consortium (Identifier PXD028309) (accessed on 2 October 2022), respectively. Detailed sample information of this cohort is presented in Table S12 in the Supplementary Materials. The human reference genome (hg38) and Proteome (version 101) were downloaded from UCSC ) (accessed on 1 September 2020) and the Ensembl database ) (accessed on 1 September 2020), respectively. Contaminated protein sequences were available in a FASTA format from the common repository of adventitious proteins (cRAP) ) (accessed on 1 September 2020). 2.2. RNA-Seq Data Processing RNA-seq raw data were cleaned by Trimmomatic (v0.39) (Max Planck Institute of Molecular Plant Physiology, Golm, Germany) , with the standard adapters trimmed and low-quality reads filtered. All clean reads were aligned to the human reference genome using the Burrows-Wheeler alignment tool (BWA, v0.7.17) (Wellcome Trust Sanger Institute, Cambridge, UK) with the default parameters. The resulting .sam file was converted to .bam, sorted, and indexed using samtools . The Picard tool, MarkDuplicates (Broad Institute, Cambridge, MA, USA), was used to identify duplicates. To correct as many systematic errors in the sequencing process as possible, we performed base quality score recalibration. The Picard AddorReplacereAdgroups tool (Broad Institute, Cambridge, MA, USA) was used to modify the headers of BAM files for subsequent processing. Somatic single nucleotide variants (SNVs), and insertions and deletions (Indels), were detected by GATK Mutect2 (v4.1.9) (The Broad Institute of Harvard and MIT, Cambridge, MA, USA) from the BAM files of paired tumor and normal samples. The GATK FilterMutectCalls (The Broad Institute of Harvard and MIT, Cambridge, MA, USA) tool was used to filter somatic mutations using default parameters, with true positive mutations marked with "PASS" and we selected "PASS" mutations. Since affinity predictions for the peptide-MHC interface are MHC-specific, it is critical to know the patient HLA types. HLA alleles in each sample were inferred from trimmed RNA-seq data using OptiType (University of Tubingen, Tubingen, Germany) with the default settings, which has been demonstrated to achieve HLA typing with ~97% accuracy . 2.3. Mutation Annotation and Peptide Extraction The annotation of mutations and the extraction of the peptide are shown in Figure 1. Somatic mutation data that were obtained based on RNA-seq data were annotated using Annovar to identify noncoding-region somatic mutations, including SNVs and indels. The noncoding regions that we used specifically included: "downstream", "intergenic", "intronic", "ncRNA_exonic", "ncRNA_intronic", "ncRNA_splicing", "splicing", "upstream", "UTR3", and "UTR5". After mutation filtering, nucleotide sequences with a set interval length were obtained according to the mutation sites and reference genome using Bedtools (University of Virginia School of Medicine, Charlottesville, VA, USA) . Specifically, 100 nucleotide sequences were taken from along each side of the mutation site. To generate the nucleotide sequences containing the mutation, we replaced the reference bases with mutant bases, i.e., we replaced the "REF" column with the "ALT" column in the mutation table. For the translation of nucleotide sequences in the genome, six-frame translation is the classical method. Six-frame translation has the advantage of being independent of any a priori annotation of the nucleotide sequence . Thus, according to the 64 codons, the mutant nucleotide sequences were translated into novel proteins via six-frame translation. The termination codons were replaced with "*" and the protein sequences were cleaved into short peptides according to "*". The short peptides that did not contain the mutations were then filtered out. Finally, we obtained tumor protein sequences containing mutations from noncoding regions. 2.4. Database Construction and Peptide Identification Identifying a mutant peptide expressed at the protein level is a crucial step. In this study, MaxQuant (Max-Planck Institute for Biochemistry, Martinsried, Germany) , a proteomics identification quantitative tool, was used to identify the peptides. To search the proteomics data, we first constructed a customized database for each individual tumor sample, including human reference proteins, common contaminant protein sequences in the laboratory (cRAP), and cancer-specific proteomes. Then, to filter for true peptides, all MS/MS spectra were searched using MaxQuant in the customized peptide database. A separate target-decoy search strategy was used. Decoy peptides were generated from the peptides of corresponding target databases using a reversed tryptic approach. The parameters of MaxQuant were set as follows: (1) the variable modifications included protein N-terminal acetylation with methionine oxidation; (2) strict trypsin specificity was required, allowing up to two missed cleavages; (3) the carbamidomethylation of cysteine was set as a fixed modification. In addition, false discovery rate (FDR) thresholds for protein peptides were specified at 1%. The minimum required peptide length was set to 7 amino acids. Finally, we extracted the cancer-specific mutant peptides identified by MS data and provided evidence in terms of protein expression level. 2.5. Neoantigen Prediction and Selection PGNneo uses NetMHCpan 4.1 (Department of Bio and Health Informatics, Technical University of Denmark, Kgs. Lyngby, Denmark) to calculate the binding affinity of peptides to patient-specific HLA alleles. To match the length of the peptides bound by MHC-I molecules, the peptides that were filtered by mass spectrometry were cleaved into short peptides containing mutated 8-11 mers. The percentile rank score was proven to exhibit higher sensitivity and less bias in HLA-peptide identification than the half-maximum inhibitory concentration (IC50) . Therefore, the percentile rank (%rank) value was used as the metric of HLA-peptide binding prediction, and peptides with a %rank < 2 were considered to be candidate neoantigens. Similar sequences often originate from a common ancestral sequence and they are likely to have similar spatial structure and biological function; in fact, tumor-infiltrating T cells were found to exhibit a cross-reactivity that recognizes both tumor neoantigens and homologous non-tumor microbial antigens . Therefore, to filter candidate neoantigens, sequence similarity analysis was performed using the basic local alignment search tool (BLAST) (National Center for Biotechnology Information, Bethesda, MD, USA) . In total, 746 experimentally immunogenic neoantigens, collected from an in-house database, dbPepNeo2.0 , were used to build the target sequence database, while candidate neoantigens were treated as retrieval sequences. Then, BLASTp was used to identify homologous sequences so that the degree of homology between candidate neoantigens and immunogenic neoantigens could be established. We adjusted several default options to increase the sensitivity of BLAST searches that were performed with short input sequences. The peptides were reported to have sequence identity to immunogenic neoantigens if the percentage of identical matches was above 60%. 2.6. PGNneo Pipeline Implementation PGNneo is open-source software written in Python, shell, and R. The software is divided into four toolkits, based on four modules. The user needs to configure the path and parameters of the software before applying the toolkits. After completing the configuration, the pipeline can be run by executing the command line. A more detailed tutorial on the use of PGNneo is available in the User's Manual. The PGNneo source code and documentation are available at To facilitate the installation and use of PGNneo, we provide a Docker container (Docker: ) and a GUI. 3. Results 3.1. The Workflow of the PGNneo Pipeline Here, as shown in Figure 2, a versatile and comprehensive workflow, PGNneo, is presented to identify neoantigens in the noncoding region. In PGNneo, several input datasets are required, including RNA-seq profiles and MS datasets. First, the RNA-seq profiles from the paired tumor and normal samples are used to screen for somatic mutations in the noncoding regions, and the amino acid sequences containing mutant sites in the noncoding region can thus be identified. Then, those expressed sequences can be filtered using MS datasets. Eventually, the resulting peptides are used for neoantigen prediction and selection by using MHC affinity and the database dbPepNeo2.0 . The general computational framework of PGNneo consists of the following modules. (1) Noncoding somatic variant calling and HLA typing. Identifying somatic mutations in tumor cells is a key step in the neoantigen presentation pathway. For this purpose, paired tumor and normal samples were used for somatic variant calling. Prior to annotation, we removed any low-quality somatic mutations. Eventually, the noncoding mutations were extracted. The prediction of HLA typing was performed, based on the RNA-seq data from tumor samples. (2) Peptide extraction and customized database construction. Working according to the mutation information, the nucleotide sequences were obtained and were then translated into proteins by six-frame translation. The process of extraction of the peptide is shown in Figure 1. Eventually, tumor mutant peptides were obtained. Subsequently, these mutant protein sequences and reference proteins were combined to construct a customized protein database. (3) Variant peptide identification. The resulting peptides were filtered using MS datasets. The proteomic data provided evidence not only for the presence of peptides at protein levels but also for the binding of peptides to MHC molecules. (4) Neoantigen prediction and selection. Candidate neoantigens were predicted, according to peptides and HLA types, using NetMHCpan 4.1. The candidate neoantigens were filtered using the database dbPepNeo 2.0, which is an in-house dataset using 746 experimental immunogenic peptides as a reference. The resulting datasets at different filtering stages could then be obtained and downloaded according to the user's preference. Table 1 summarizes the software used in PGNneo. 3.2. Evaluation of PGNneo Pipeline Results To evaluate the performance of PGNneo, we performed sequence similarity analysis using two independent datasets. The positive dataset comprises 746 experimentally validated immunogenic neoantigens (Positive) collected from the dbPepNeo2.0 dataset, and the background control dataset contains 6400 mutant peptides (Random) of length 8-11 residue . We performed sequence similarity analysis on the candidate neoantigens (unfiltered) that were obtained from the two cohorts of HCC_HF and HCC_HT with the positive dataset and random dataset, respectively. Two sequences exhibiting more than 60% of identical matches and an E-value of less than 0.5 are considered to be similar. Figure 3 shows that the results obtained from the positive and random datasets were significantly different in both the HCC_HF and HCC_HT cohorts, with p-values of 0.0278 (<0.05) and 0.01704 (<0.05), respectively (Wilcoxon test). The results indicate that the candidate neoantigens predicted by our method are more likely to have immunogenic potential. Therefore, filtering using the positive datasets was incorporated into the pipeline. This can be considered as an in silico verification step in the pipeline for the prediction of neoantigens. 3.3. Neoantigen Prediction, Selection, and Cross-Comparison from HCC Cohorts PGNneo was applied to two independent HCC cohorts. We statistically analyzed the number of key steps in the pipeline for each sample . In the HCC_HT cohort, one sample deviated significantly from other samples, possibly due to data quality problems, so this sample was deleted; finally, for this cohort, 9 samples were retained. The average number of key steps in the pipeline on the HCC_HF and HCC_HT cohorts are shown in Figure 4A. After filtering and annotation, an average of 3260 and 1178 noncoding mutations were obtained (Tables S2 and S3 in the Supplementary Materials). At the protein level, an average of 2339 and 610 peptides were identified by MS data analysis. HLA genotypes were predicted from the RNA-seq fastq file using the Optitype, and MHC-I binding predictions for the filtered peptides were predicted with netMHCpan4.1. As a result, an average of 3518 and 932 candidate neoantigens were obtained in the two cohorts, respectively (Tables S4 and S5 in the Supplementary Materials). After screening for HCC_HF, an average of 77 noncoding high-confidence neoantigens were eventually identified in each sample, ranging from 37 to 147 (Table S6 in the Supplementary Materials). However, in the HCC_HT cohort, an average of 13 noncoding high-confidence neoantigens were identified per sample, ranging from 4 to 23 (Table S7 in the Supplementary Materials). Upon comparing the results of the two cohorts, we found 403 overlapping non-coding mutations and 189 overlapping candidate neoantigens in the two cohorts ; however, no overlap was found in the high-confidence neoantigens. The results show that neoantigens are unique and the number of neoantigens varies greatly between different datasets. In addition, 26 and 28 unique HLA alleles were predicted for the two cohorts, respectively (Table S8 in the Supplementary Materials). We further calculated the frequency of HLA alleles in the sample population using the getHlaFrequencies function in the midasHLA package of R . Then, the mean value of neoantigens bound by each HLA allele was calculated, based on the count of HLA alleles, thus normalizing the number of neoantigens. The frequency of HLA alleles and the number of corresponding neoantigens are given in Table S9 in the Supplementary Materials. Based on the ranking of the normalized number of neoantigens, the 10 most frequent binding HLA alleles that matched with candidate neoantigens in two cohorts are shown in Figure 5A and Figure 5B, respectively. The results showed that HLA alleles exhibited a preference for the binding of neoantigens, while HLA-A33:03 and HLA-A23:01 accounted for the largest binding proportion in the HCC_HF and HCC_HT cohorts. Moreover, the same candidate neoantigen can bind to different HLA alleles; this neoantigen is more likely to be present and may be applicable to a wider range of individuals. 3.4. The Sharing of Noncoding Neoantigens and Genes in Different Samples We further analyzed the overlapping neoantigens and their corresponding genes in the two cohorts. In the HCC_HF cohort (lncRNA-seq data from 5 HCC PDX samples and MS data from the HCC cell line), 10 neoantigens were found to be in common in at least 2 patients (Table S10 in the Supplementary Materials). These overlapping neoantigens are called "shared neoantigens" and have the potential to be designed as shared neoantigen vaccines. Conversely, neoantigens across the 5 patients were mapped to 118 unique genes, and 6 of these genes were observed in at least 2 patients (Table S10 in the Supplementary Materials). These overlapping genes are "hot-spot mutations" where the corresponding neoantigens may be in common among multiple patients. Unfortunately, no overlapping neoantigens or genes were found in the HCC_HT cohort (with paired RNA-seq data and MS data from 10 human HCC samples). This may be because the HCC_HF cohort dataset comprises unpaired lncRNA-seq data and MS data; the MS data is cell line data with lower heterogeneity, so that shared neoantigens can be found, while the HCC_HT cohort is of paired RNA-seq data and MS data from patients with a higher degree of individualization. To some extent, this explains the individualization of neoantigens in real patients. Therefore, this also reinforces the necessity for more research on hot-spot mutations for building up data resources for shared neoantigens. 3.5. Function Verification Analysis of Frequently Mutated Genes and Neoantigens in HCC In order to correlate the predicted neoantigens with the clinical information garnered from patients, we explored the association between the predicted neoantigens and the pathogenesis of HCC. Rao et al. summarized the frequently mutated genes and their functions that are associated with HCC. We compared candidate neoantigen-associated genes in the HCC_HF cohort and HCC_HT cohort with the frequently mutated genes associated with HCC. The TP53, WWP1, ATM, KMT2C, and NFE2L2 mutant genes associated with HCC were identified in two cohorts and corresponded to 98 neoantigens (Table S11 in the Supplementary Materials). Table 2 only shows information about the 26 candidate neoantigens that bind most strongly to HLA. Among them, TP53 is one of the most studied tumor suppressors, with multiple functions, and is associated with DNA damage checkpoints and repair defects. WWP1 is associated with the activation of oncogenic pathways in HCC; the overexpression of WWP1 promotes tumorigenesis in HCC patients and predicts poor prognosis. The loss of ATM reduces hepatocyte apoptosis and fibrosis, suggesting that the activation of ATM in response to oxidative stress plays a role in hepatic fibrosis development. KMT2C and KMT2D are functionally similar and may be involved in chromatin localization and genomic instability. NFE2L2 deficiency may render cells susceptible to oxidative stress-mediated DNA damage. Genes that are highly mutated in HCC may be attractive potential therapeutic targets. 3.6. Extended Application of PGNneo to Other Tumor Types In addition, we applied PGNneo to another tumor type with moderate TMB, colorectal cancer (CRC) . Firstly, 4206, 3664, and 5823 non-coding mutations were obtained on COLO205, SW620, and HCT116 cell line data, respectively, and further predictions yielded 217, 330, and 291 candidate neoantigens. In addition, to evaluate the potential immunogenicity of candidate neoantigens, we obtained high-confidence neoantigens based on the filtering of an experimentally validated immunogenic neoantigen database constructed by our group. Detailed results on sample information, noncoding region mutations, HLA typing, candidate neoantigens, and high-confidence neoantigens are provided in Table S12 in the Supplementary Materials. The results demonstrate that our pipeline can be applied to multiple tumor types. The biological mechanisms of noncoding neoantigens may be cross-verified as the application of PGNneo expands. 3.7. Comparing PGNneo with Other Tools To complete the identification and comparison of neoantigens from both coding and noncoding regions, we applied four other common neoantigen prediction tools, including ProGeo-neo , pVACtools , Neopredpipe , and TSAFinder , to compare their performance with our own tool, PGNneo. pVACtools, Neopredpipe, and TSAFinder require fastq data for RNA-seq and/or VCF data for mutations as input, and ProGeo-neo requires the additional input of MS data. For two HCC cohorts, we randomly selected three patient samples, HCC42, HCC67, and HCC1076, for comparison across five neoantigen prediction tools. Since most neoantigens are composed of 9 amino acids, we only compared the prediction of 9-mer neoantigens . The number of candidate neoantigens obtained by the five tools is shown in Figure 6. It is worth noting that PGNneo introduces MS data and shows candidate neoantigens after MS filtering so that the results of PGNneo are more stringent. Although ProGeo-neo also has a module for MS data filtering, unfortunately, no neoantigens were obtained after MS data identification. This is consistent with studies on neoantigens in the coding region of HCC, which suggested that the tumor mutational burden (TMB) of HCC is relatively low and neoantigens in coding regions are scarce . In contrast, the other tools do not have an MS filtering step, and we only show their candidate neoantigens as predicted by peptide-MHC binding affinity (Table S13 in the Supplementary Materials). In addition, PGNneo sets up a module for secondary filtering by using 746 experimentally validated neoantigens, resulting in high-confidence neoantigens. Twenty, three, and one high-confidence 9-mer neoantigens were obtained in samples HCC1076, HCC42, and HCC67, respectively (Table S13 in the Supplementary Materials). Furthermore, we explored the association between these high-confidence neoantigens and the pathogenesis of HCC. The high-confidence neoantigen genes TNFSF14, GAD1, STARD1, and DHRS4-AS1 have been reported in the literature to be closely associated with HCC . Specifically, TNFSF14 and GAD1 are highly expressed in HCC ; STARD1 promotes the progression of non-alcoholic steatohepatitis to HCC via bile acids ; DHRS4-AS1 ameliorates HCC by suppressing proliferation and promoting apoptosis via the miR-522-3p/SOCS5 axis . Moreover, we analyzed the overlap of the candidate neoantigens predicted by different tools. For three samples, HCC1076, HCC42, and HCC67, the number of neoantigens identified by at least three tools was 411, 80, and 3, respectively (Table S14 in the Supplementary Materials). We recommend using multiple tools to predict neoantigens, which may yield more reliable results. Our investigation demonstrates that for cancer types with a low TMB, the source of neoantigens may be enriched when the noncoding region is taken into consideration. Therefore, PGNneo aims to expand the scope of neoantigen prediction and provide a richer neoantigen reference for some cancer types with a low TMB in the coding region. 4. Discussion Although some algorithms and tools have been developed to tackle the problem of neoantigen prediction, most are based on coding regions. However, in the human genome, 98% of the sequence involves noncoding regions, and most DNA sequence variants occur in the noncoding regions . The general properties of sequence variants are also applicable to noncoding variants, such as SNVs and Indels. What is more, noncoding variants can also generate neoantigens. However, there are few prediction tools that operate on noncoding regions; the majority of tools focus on exonic variant calling, which is based on genomic data rather than transcriptomic data. For this reason, we developed a proteogenomics-based pipeline, PGNneo, to identify those neoantigens derived from noncoding regions, based on transcriptomic data from the human genome. Furthermore, we successfully validated the effectiveness of PGNneo through its application in two HCC cohorts. A total of 386 and 113 high-confidence neoantigens were identified in the two HCC cohorts, respectively. In addition, we applied PGNneo to a CRC cohort, demonstrating that the tool can be extended to multiple tumor types. Compared with the traditional neoantigen prediction pipeline, PGNneo has several advantages. First, it focuses on neoantigens in noncoding regions, which provides a new source of neoantigens for low-TMB tumor types. Studies have shown that for cancer types with a low TMB, such as liver cancer, the source of neoantigens should be extended to noncoding regions for better applicability to immunotherapy . Second, it combines transcriptomics and proteomics data, furthering the proteogenomics neoantigen prediction pipelines for coding regions in our research group . Most of the previously developed neoantigen prediction tools are based on genomic data only, and the predicted false-positive rate of neoantigens is relatively high. Combined with proteomic data, the accuracy of neoantigen prediction can be improved. Moreover, proteogenomics holds the promise of providing deeper mechanistic insights to enable the better matching of patients to targeted therapies than when analyzing each type of omics data separately. In addition, our pipeline uses RNA-seq data from paired tumor and normal tissues to call somatic mutations. Mutations in the RNA-seq data provide a better reference for a proteomics dataset than WES, mainly because of the ability of RNA-seq to identify novel somatic variants, while for oncogenes that are highly expressed in cancer, RNA-seq provides higher sequencing coverage than WES and, therefore, has higher statistical confidence in detecting variants . Thus, in our pipeline, the customized searchable peptide database was derived from tumor RNA-seq data. Compared to the coding-region-based proteogenomic prediction pipeline established by our group, in terms of data requirements, ProGeo-neo requires data at the genomic, transcriptomic, and proteomic levels of the patients, while PGNneo only requires transcriptomic and proteomic data from patients, and not WES/WGS data. This is because the neoantigen prediction step in ProGneo-neo is performed based on the mutations detected by WES/WGS, whereas in PGNneo, the step is based on RNA-seq data. Therefore, the application scenario of the PGNneo can be further expanded. There are still some limitations to our study, so we will expand on the following aspects. To further enrich the types of neoantigens, we may later update the tool to predict those neoantigens derived from gene fusion and RNA splicing, which will provide more potential neoantigen targets for developing therapeutic cancer vaccines. In addition, considering the complementary roles of coding-region-based and noncoding-region-based pipelines in identifying neoantigens, we will integrate neoantigen prediction tools such as ProGeo-neo that have already been developed within the group to further facilitate their use by researchers. Moreover, as noncoding neoantigens have been shown to have strong tumor specificity, more relevant studies have since emerged in the field. Recently, Cai et al. developed IEAtlas, an atlas of HLA-presented immune epitopes derived from noncoding regions, which provides a valuable data resource for studying the immunogenicity of noncoding epitopes. Therefore, we will combine the data from IEAtlas to further improve the predictive power of PGNneo. Even though the subsequent experimental validation of candidate neoantigens is essential for real-world clinical application, our computational methods can narrow down the range of neoantigens to a certain extent and thereby pave the way to improved preclinical vaccine design. Therefore, PGNneo may prove to be a useful tool for cancer researchers and clinicians. 5. Conclusions In this study, we developed a proteogenomics-based pipeline to predict neoantigens in noncoding regions, namely, PGNneo. PGNneo is a pipeline that integrates state-of-the-art computational tools. It mainly includes four modules: (1) noncoding somatic variant calling and HLA typing; (2) peptide extraction and customized database construction; (3) variant peptide identification; (4) neoantigen prediction and selection. PGNneo can be easily applied to RNA-seq data and MS data drawn from patients of different cancer types. In summary, PGNneo can specifically detect the neoantigens generated by noncoding regions in tumors, providing guidance for cancer types with a low TMB in coding regions. PGNneo, together with our previous tool, can improve the identification of coding and noncoding region-derived neoantigens and will contribute to a more complete understanding of the tumor immune landscape. This capability holds promise for broadening the repertoire of candidates for therapeutic cancer vaccination and T cell-based therapy and may ultimately extend the neoantigen clinical benefits of immunotherapy. Acknowledgments The authors would like to thank Michael Liebman for his critical reading and native English editing. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Results of key steps in neoantigen prediction based on PGNneo for each sample; Table S1: Detailed sample information of the HCC_HF cohort and HCC_HT cohort; Table S2: Noncoding mutations in the HCC_HF cohort; Table S3: Noncoding mutations in the HCC_HT cohort; Table S4: Candidate neoantigens in the HCC_HF cohort; Table S5: Candidate neoantigens in the HCC_HT cohort; Table S6: High-confidence neoantigens in the HCC_HF cohort; Table S7: High-confidence neoantigens in the HCC_HT cohort; Table S8: HLA alleles of each sample in the HCC_HF cohort and HCC_HT cohort; Table S9: The frequency of HLA alleles and the number of corresponding neoantigens in the HCC_HF cohort and HCC_HT cohort; Table S10: Overlap of noncoding neoantigens and noncoding genes between samples in the HCC_HF cohort; Table S11: Frequently mutated genes associated with HCC and the corresponding neoantigens; Table S12: Detailed results on sample information, noncoding region mutations, HLA typing, candidate neoantigens, and high-confidence neoantigens in the CRC cohort; Table S13: Candidate neoantigens, as predicted by five tools; Table S14: Overlap of candidate neoantigens, as predicted by five tools; User's Manual: Detailed tutorials for using the PGNneo tool. Click here for additional data file. Author Contributions L.X. (Lu Xie) and X.T. conceived and designed this study and drafted the manuscript. L.X. (Lu Xie) and T.W. supervised this study. X.T. carried out data collection and analysis, built the pipeline, and wrote the draft manuscript. X.T., L.X. (Linfeng Xu) and J.O. wrote the software package. L.X. (Lu Xie) and X.J. revised the manuscript. X.Y. and B.H. contributed to data 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 noncoding mutation dataset for the lncRNA-seq of HCC samples is available in the Supplementary Materials. The proteomics datasets of the HCC cell line were obtained from the ProteomeXchange Consortium ) with the identifier, PXD000529. Another HCC cohort associated with Jiang et al. , including RNA-seq files and MS raw data from 10 patients, was downloaded from the Gene Expression Omnibus (GEO) (accession number GSE124535) and iProX database accession number IPX0000937000), respectively. The CRC cohort , including RNA-seq data and MS raw data from three CRC cell lines and RNA-seq data from one normal fetal small intestine cell line, were downloaded from the GEO (accession number GSE195985) and ProteomeXchange Consortium (identifier PXD028309), respectively. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Generation of the variant peptides. Figure 2 Overview of the PGNneo pipeline for proteogenomics-based noncoding neoantigen prediction. Figure 3 Evaluation of candidate neoantigens predicted by PGNneo, based on independent datasets: boxplot of the positive and random peptides in the HCC_HF cohort (A) and the HCC_HT cohort (B), with a * p-value < 0.05, ascertained by a Wilcoxon test. Figure 4 Results overview for the neoantigen discovery process. (A) The average number of key steps in the PGNneo on the HCC_HF cohort and HCC_HT cohort, respectively. (B) Overlapping non-coding mutations in the HCC_HF cohort and the HCC_HT cohort. (C) Overlapping candidate neoantigens in the HCC_HF cohort and the HCC_HT cohort. Figure 5 The number of predicted neoantigens binding with each HLA allele. (A) The top 10 HLA alleles matched with candidate neoantigens in the HCC_HF cohort. (B) The top 10 HLA alleles matched with candidate neoantigens in the HCC_HT cohort. Figure 6 The number of candidate neoantigens predicted by PGNneo, ProGeo-neo, pVACtools, NeoPredPipe, and TSAFinder. cells-12-00782-t001_Table 1 Table 1 Summary of the tools available in PGNneo. Module Software Function (1) Noncoding somatic variant calling and HLA typing Trimmomatic-0.39 Trims adapters and filters low-quality reads BWA-0.7.17 Sequence alignment SAMtools(V1.7) Converts .sam files to .bam, sort, and index files GATK4.2.0.0 Call somatic mutation Picard-2.23.9 Modifies the headers of .bam files OptiType-1.3.5 Predicts HLA typing (2) Peptide extraction and customized database construction Annovar Mutation annotation Bedtools(v2.29.2) Sources the nucleotide sequence (3) Variant peptide identification MaxQuant Peptide identification (4) Neoantigen prediction and selection NetMHCpan-4.1 Calculates the binding affinity of peptides to patient-specific HLA alleles Blast-2.11.0+ Sequence similarity analysis cells-12-00782-t002_Table 2 Table 2 Strongly bound neoantigens that are generated by frequently mutated genes in HCC. Gene Neoantigen HLA %Rank Bind Level WWP1 VSHDGATAL HLA-C*03:04 0.009 SB NFE2L2 KTDAQAISL HLA-C*04:03 0.025 SB TP53 TMAGQLLHV HLA-A*02:06 0.052 SB NFE2L2 SSRPAWPTR HLA-A*33:03 0.08 SB KMT2D QQKNPSLFL HLA-B*13:02 0.126 SB NFE2L2 GQHSETPSL HLA-B*15:01 0.154 SB NFE2L2 WPGHQFFKY HLA-B*35:01 0.155 SB KMT2C IVSSRFCTR HLA-A*31:01 0.167 SB KMT2D QQKNPSLFLI HLA-B*13:02 0.185 SB NFE2L2 GIWPGHQFF HLA-B*15:25 0.206 SB NFE2L2 LFFETRSRF HLA-A*24:02 0.226 SB ATM AEAGEPLEP HLA-B*40:06 0.232 SB WWP1 YRCVPPHPANF HLA-C*06:02 0.258 SB KMT2C KLGDNHFFM HLA-A*02:01 0.293 SB NFE2L2 ATRTGRLWWR HLA-A*31:01 0.323 SB NFE2L2 HPKSKQISCTW HLA-B*58:01 0.362 SB NFE2L2 IWPGHQFF HLA-A*24:02 0.376 SB KMT2D QKNPSLFLI HLA-B*13:02 0.379 SB NFE2L2 RMPVIQAAW HLA-A*24:20 0.385 SB NFE2L2 RMPVIQAAW HLA-B*58:01 0.396 SB WWP1 FSCLSLSGGW HLA-B*58:01 0.432 SB ATM RACQRQAVGIK HLA-A*30:01 0.433 SB NFE2L2 KTDAQAISL HLA-C*03:04 0.442 SB NFE2L2 GQHSETPSLLK HLA-A*11:01 0.46 SB TP53 ATMAGQLLHV HLA-A*02:06 0.474 SB WWP1 VSHDGATAL HLA-C*04:03 0.48 SB 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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PMC10000441 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050865 diagnostics-13-00865 Article Revealing the Boundaries of Selected Gastro-Intestinal (GI) Organs by Implementing CNNs in Endoscopic Capsule Images Athanasiou Sofia A. Formal analysis Software Validation Writing - original draft 12 Sergaki Eleftheria S. Conceptualization Investigation Methodology Project administration Supervision Writing - original draft Writing - review & editing 1* Polydorou Andreas A. Conceptualization Methodology Resources Supervision Validation 3 Polydorou Alexios A. Data curation Software Validation 4 Stavrakakis George S. Conceptualization Investigation Methodology 1 Afentakis Nikolaos M. Data curation Software Writing - original draft 2 Vardiambasis Ioannis O. Conceptualization Methodology Supervision 2* Zervakis Michail E. Conceptualization Methodology Supervision 1 Isomoto Hajime Academic Editor 1 School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Greece 2 Department of Electronic Engineering, Hellenic Mediterranean University, 73133 Chania, Greece 3 Aretaeio Hospital, 2nd University Department of Surgery, Medical School, National and Kapodistrian University of Athens, 11528 Athens, Greece 4 Medical School, National and Kapodistrian University of Athens, 11528 Athens, Greece * Correspondence: [email protected] (E.S.S.); [email protected] (I.O.V.) 23 2 2023 3 2023 13 5 86529 9 2022 03 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 ). Purpose: The detection of where an organ starts and where it ends is achievable and, since this information can be delivered in real time, it could be quite important for several reasons. For one, by having the practical knowledge of the Wireless Endoscopic Capsule (WEC) transition through an organ's domain, we are able to align and control the endoscopic operation with any other possible protocol, i.e., delivering some form of treatment on the spot. Another is having greater anatomical topography information per session, therefore treating the individual in detail (not "in general"). Even the fact that by gathering more accurate information for a patient by merely implementing clever software procedures is a task worth exploiting, since the problems we have to overcome in real-time processing of the capsule findings (i.e., wireless transfer of images to another unit that will apply the necessary real time computations) are still challenging. This study proposes a computer-aided detection (CAD) tool, a CNN algorithm deployed to run on field programmable gate array (FPGA), able to automatically track the capsule transitions through the entrance (gate) of esophagus, stomach, small intestine and colon, in real time. The input data are the wireless transmitted image shots of the capsule's camera (while the endoscopy capsule is operating). Methods: We developed and evaluated three distinct multiclass classification CNNs, trained on the same dataset of total 5520 images extracted by 99 capsule videos (total 1380 frames from each organ of interest). The proposed CNNs differ in size and number of convolution filters. The confusion matrix is obtained by training each classifier and evaluating the trained model on an independent test dataset comprising 496 images extracted by 39 capsule videos, 124 from each GI organ. The test dataset was further evaluated by one endoscopist, and his findings were compared with CNN-based results. The statistically significant of predictions between the four classes of each model and the comparison between the three distinct models is evaluated by calculating the p-values and chi-square test for multi class. The comparison between the three models is carried out by calculating the macro average F1 score and Mattheus correlation coefficient (MCC). The quality of the best CNN model is estimated by calculations of sensitivity and specificity. Results: Our experimental results of independent validation demonstrate that the best of our developed models addressed this topological problem by exhibiting an overall sensitivity (96.55%) and specificity of (94.73%) in the esophagus, (81.08% sensitivity and 96.55% specificity) in the stomach, (89.65% sensitivity and 97.89% specificity) in the small intestine and (100% sensitivity and 98.94% specificity) in the colon. The average macro accuracy is 95.56%, the average macro sensitivity is 91.82%. computer-aided detection wireless endoscopic capsule gastro-intestinal CNN artificial intelligence (AI) GI organ boundary capsule tracking This research received no external funding. pmc1. Introduction All the recent hardware and software advances incorporated in the technology of Wireless Endoscopic Capsule (WEC) robots constantly demonstrate their great potential for improvement, as research boundaries progress even further, revealing new opportunities for gastroenterologists and patients, for better diagnosis and treatment. The WEC has the potential to become a screening, diagnostic and therapeutic technique for the entire GI tract because of its low discomfort to users . Thus, the WEC has become the first choice for small bowel endoscopy in children . Moreover, the use of a robotic WEC (in the future) promises to offer some form of targeted "smart" therapy, e.g., drug delivery, clip release for bleeding control, precise biopsy sampling, etc. Nevertheless, there are some specific computer-aided techniques based on AI that are approved by the European Medicines Agency (EMA) and by the Pharmaceuticals and Medical Devices Agency (PMDA) since 2018 :- CADe by FUJIfilm, PENTAX, - GI Genious by Medtronic, - EndoBRAIN by Cybernet, - Endo-AID by Olympus (as of this time, pending approval). To the best of our knowledge, no methods or algorithms seem to have been proposed yet to automatically detect the capsule passing by selected GI organs (their extend, from start to finish), although medical reviewers can surely identify such a position through their optical review and diagnosis later on. This kind of automation can play a significant role in the near future, as technology evolves rapidly towards better, cheaper and more efficient endoscopic capsules. The present work reveals such a case, specifically the detection of WEC's transition and regional awareness while passing the boundaries of gastrointestinal (GI) organs through the GI tract. A lot of algorithms are proposed for reducing WEC's videos review time by the experts, by detecting and diagnosing of hemorrhage and GI tract lesions based on AI . The topic of localizing the capsule inside GI has gained a lot of interest among researchers. Few robotic research groups have proposed methods for the real time localization of the capsule, possibly by providing wireless endoscopic capsule control through magnetic devices and other RF localization techniques . To the best of our knowledge, the most relevant algorithms capable of classifying single frame images into GI organs, or detecting the boundaries of the GI organs are presented in references . In , a CNN algorithm with a temporal filtering detects three GI organs (the stomach, the small bowel, and the colon), but is not able to identify the boundary transitions among these organs. On the other hand, the algorithm of , employing the long-term dependencies of WEC frames, detects both transitions between stomach and small bowel and between small bowel to colon. Moreover, the CAD tool based on CNN and SVM algorithms for narrow band imaging endoscopy is implemented into the FPGA-based prototyping platform . In this study, the problem to solve is the real-time tracking of the WEC transition through the boundaries of GI's organs (esophagus to stomach, stomach to small intestine, small intestine to colon), from CNN multi-class classification of endoscopy capsule images. Moreover, the algorithms can be executed from a mobile platform that can be physically attached for the time of recording upon the patient. Another aim is to study how the difference of the kernel size and number effects the CNN's performance or how adding dropout layers will affect the possibility of overfitting and underfitting of the proposed CNN classifier. 2. Materials and Methods This prospective, noninterventional study was conducted at Aretaeio Hospital, at the Department of Surgery, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece from December 2019 to June 2020. The School of Electrical and Computer Engineering of the Technical University of Crete, Greece and the Department of Electronic Engineering, Hellenic Mediterranean University, were responsible for CAC algorithm development. 2.1. Data and Resources For this research, we have used video data out of a total of 138 PillcamTM SB endoscopic capsule videos collected from random anonymous patients hospitalized in four different Gastroenterology Departments of (a) the Medical School of the National and Kapodistrian University of Athens, (b) the Attikon University Hospital, (c) the Laikon University Hospital and (d) the Medical School of the Aristotle University of Thessaloniki. All these 138 patients have been diagnosed by their attending doctors positive to: (i) bleeding, (ii) angiodysplasias, (iii) haemangiomas, or (iv) lesions which predispose to bleeding in the small intestine. The 138 videos have been evaluated by the third coauthor, who is a very experienced endoscopist, and divided into two sets: the training set with 99 videos which are used by the proposed algorithm for feature extraction and the validation set with the rest of the 39 videos which are used for independent validation as images unseen from the algorithm. From those videos, there was an extraction of total 5520 frames, 1380 frames for each organ (ten frames for each organ boundary of each video) of interest: esophagus, stomach, small intestine, colon. In order to achieve success in regional information extraction of the endoscopy capsule, the problem to be solved is the organ's entrance (gate) classification. After extracting the images in order to use them for machine learning purposes, images were divided in different folders. First of all, they were distinguished in training data (total 5520 frames, 1380 for each organ) and in testing data (total 496 frames, 124 frames for each organ). Training data are the ones that are fed into the model in the training phase and testing are the ones used in order to verify that the model is producing comprehensive training results. Afterwards, the training data were split in four folders . Each folder represents one of the four points of interest. For example, the stomach folder contains only images that are coming from that area. Moreover, for the training process, a CSV file was created in which there is a labelling of the images based on the category they belong to and their name. In Figure 2, images samples are shown. All images are in three colour channels (RBG--Red Blue Green), with the typical pixel level , although the data are normalized during the experiment. The data of the training folder are separated so that 80% of them are used for the phase of training the model. The rest of the 20% are used as validation data during the training process. Validation data are important so that we have a quicker and better feedback on the model and we do not fall into cases of overfitting or underfitting . To conclude, before feeding the data into the training phase of the model, the following actions were performed: create validation data using 20% of the training data, in order to be used as unknown data during the training process; reduce the size of images from the 576 x 576 original image size to 256 x 256; define the batch size to be 16; use autotune data, in order to help our model to be faster, since it will decouple the time when data is produced from the time when data is consumed. It will use a background thread and an internal buffer to prefetch elements from the input dataset ahead of the time they are requested. Autotune function will prompt the tf.data to tune the value dynamically at runtime; perform data normalization, by transforming all pixel values in the interval. 2.2. Proposed CNNs 4-Class Classifiers Taking under consideration similar research that classifies images into corresponding categories, the Convolutional Neural Network (CNN) model is well known to be good at image classification. CNN stands for Convolutional Neural Network, where each image goes through a series of convolution and max pooling for features extraction. CNN takes an input image and assigns importance (weights and biases) to various features to help in distinguishing images, for example, animal classification , bleeding and non-bleeding images in endoscopy capsule , ImageNET , concluded that Convolutional Neural Networks were a great starting point. In general, CNN contains a series of connected layers, containing the convolutional layer, the pooling layer and the dense layer. For this research, three different CNN models were created and evaluated. Additionally, there was a testing of those models including data augmentation. The input of our models at all times are images in three color channels (RGB) with final dimensions [256 x 256]. Then, the pixel values were normalized. This is achieved by subtracting the mean of each pixel and then diving that result by the standard deviation. That will lead to a Gaussian curve centred to zero. In case of images, the possible values are only the positive ones so it will move the data from the value range of to the value range of . The idea around Convolutional Neural Networks is that there are the layers that will help in feature extraction, the convolutional layers in cooperation with the pooling layers, and the layers that will transform their input to a decision, which are the flatten layers. Convolutional layers will perform a linear matrix multiplication by sliding the filter windows through the image pixels. In our research, when it comes to the convolutional layers in Model 1 and 2, the filters are of the size [3 x 3], and in Model 3 are of the size [5 x 5]. From layer to layer in each model, what is changed, also, is the number of filters applied for example, in Model 1 , firstly, we apply 32 filters, later on 64 and finally 128. Between the Convolutional Layers there is a pooling function, that function helps in order to select the most powerful features, in a window of [2 x 2]; it will parse the outcome of the convolutional layer and select the maximum values. In the next connected layer, the filters will be applied to the strongest feature in order to extract the ones that are more relevant. This will provide also the advantage of downsampling the features and reducing the computational cost of the algorithm and the same time we will care for the most relevant characteristics of the images. For the code and result production, open source tools were used. All code was written in Python and run in the Google Colab platform in order to have an environment with more resources in memory and GPU than the local system. The libraries that were used for data pre-processing and model creation are Tensorflow and Keras. For image manipulation, the cv2 library was used. From Keras, in order to create the models' layers, we used the functions: Conv2D, Maxpool2D, Flatten and Dense, Sequential (in order to define that we are referring to a Convolutional Neural Network). 2.2.1. CNN-Model 1 Model 1 consists connected two dimensional convolution layers and two dimensional maxpooling layers as feature extractors, a flatten layer in order to have a vector of features after the last pooling layer that will be an input for the upcoming two dense layers that follow in order to make the final decision of the classification. In total, using that model, there were 8,412,836 trainable parameters. In Table 1 are shown the details regarding the different layers as well as the sizes of the filters and the trainable parameters. In Figure 3, there is a graphical representation of Model 1. 2.2.2. CNN-Model 2 Model 2 is a deeper neural network using, again, connected two dimensional convolution layers and two dimensional maxpooling layers as feature extractors, a flatten layer in order to create a vector of features after the last pooling layer that will be an input for the upcoming two dense layers. In total, that model leads to 13,235,756 trainable parameters. In Table 2, there are details regarding output size of the different layers as well as the sizes of the filters and the trainable parameters. In Figure 4, there is a graphical representation of Model 2. 2.2.3. CNN-Model 3 Model 3 is using convolutional layers with filters of the size (5 x 5) instead the filters of size (3 x 3) that were using the previous models. Moreover, in the previous models, there was an increase of the number of filters that were used, as the network was getting deeper. For this model, there were used in all steps filters of the same size and number; in every convolutional layer there were used 32 filters of the size (5 x 5). Another difference of this model is that there was used also a dropout layer between the last two dense layers. Other than those two key differences, the rest remain the same. In total, that model results in 6,477,508 trainable parameters. In Figure 5, there is a graphical representation of Model 3 and Table 3 presents the details. 3. Results of CNNs Training Taking under consideration the relatively small set of data (5520 frames selected from 99 videos) that we are using for training as well as the fact that the data did not undergo any pre-processing before arriving at the training process, our results stand out. There are references on the curves that refer to the loss and accuracy of training and validation data as per epoch of the training process. Those curves are provided as per model. All models used 30 epochs in order to conclude to a stable value of validation and training accuracy. This amount of epochs worked well enough to allow our training model to conclude with a good training convergence. There was used also instead of individual images, a patch of images of size 16. For the Model 1, training accuracy and validation accuracy start being stable after epoch 15; for Model 2 we see the same behavior after epoch 20 and for the Model 3, those values start being stable after epoch 25. We observed, after a relatively small amount of epochs, the results we were taking were quite sufficient. Model 1 concludes with training accuracy 1 and validation accuracy 0.9677. Model 2 provides training accuracy 1 and validation accuracy 0.9677. Moreover, Model 3 provides training accuracy 1 and validation accuracy 1. All those values refer to the results of the 30th epoch. Among the three models, the one that provides a more stable view, as many times as the experiment of training was reproduced, is Model 2. We observed that increasing the number of filters as the model becomes deeper shows that is providing a more stable result. 4. Methods of Multiclass CNNs Independent Evaluation The independent evaluation for the prediction quality of our multiclass CNNs, is the trained models test, examining data not used in the training procedure. To evaluate the quality of the performance of any multiclass classifier and compare them to each other, it is broken into multiple binary classification models. The Mattheus correlation coefficient (MCC), calculates a high score only if the prediction obtained correct results in all of the confusion matrix categories (true positives, false negatives, true negatives, and false positives), proportionally both to the size of positive elements and the size of negative elements in the dataset . (1) MCC=cxs-kKpkxtks2-kKpk2xs2-kKtk2 where K is the number of classes, - tk=iKCik is the number of times class k truly correct, - pk=iKCik is the number of times class k was predicted into class, - c=kKCkk is the total number of samples that was correctly predicted, - s=iKjKCij is the overall number of samples, and - cxs-kKpkxtk includes the elements wrongly classified by the model and covers multiplicative entities that are weaker than the product c x s. To evaluate each multi class classifier, the macro average F1 score indicates how the classifier performs for every class . The macro average involves computing one versus all confusion matrices for each class, where each individual ith class is the positive class and all the other classes are the negative class. Since our experiment refers to a 4-class classification, for each class we calculate the values of True Positive (TP), True Negative (TN), False Positive (FP), False Negative (FN). The macro average F1 score is defined by the harmonic mean of the macro average of recall (or sensitivity) and macro average precision as:(2) F1macro=2PmacroxRmacroPmacro+Rmacro where the macro average calculates a simple average of the binary classification metric values of all classes, (3) Pmacro=1Ki=1KPi=1Ki=1KTPiTPi+FPi, (4) Rmacro=1Ki=1KRi=1Ki=1KTPiTPi+FNi, where precision of the ith class, Pi, stands for the fraction of positive class predictions that were actually positive. The value of sensitivity or recall of the ith class, Ri, stands for the fraction of all positive samples that were correctly predicted as positive by the classifier. Accuracy is providing the overall accuracy of a model for a specific class, meaning the fraction of the total class objects that were correctly classified by the classifier. The accuracy of predicting the frames that refer to a class of a model is calculated by Equation (5):(5) Accuracy=TP+TNTP+TN+FP+FN Furthermore, Error Rate, which indicates the quality of the classifiers towards the wrong predictions, is calculated by Equation (6):(6) Error Rate=FP+FNTP+TN+FP+FN and Specificity, which presents the fraction of all negative samples that are correctly predicted as negative by the classifier, is calculated by Equation (7):(7) Specificity=TNTN+FP In the present testing, we evaluate the statistical significance of predictions between the three CNN models by calculating the test result for p. If the p-value is greater than 0.05 then no effect is observed, meaning that our test hypothesis is false and the outcomes are statistically independent. Our null hypothesis is that all the models are equivalent, so "Ho = there is no difference between the models". The basic format for reporting a chi-square test result is: x2 (degrees of freedom, N = sample size) = chi-square statistic value, p = p value, while our p-values are calculated by the Pearson's chi-squared test, using Equation (8):(8) x2=i=1rj=1cOi,j-Ei,j2Ei,j where r is the number of rows corresponding to the number of models, c is the number of columns corresponding to the number of classes of the contingency table, df is the degrees of freedom calculated by df = (r - 1) x (c - 1) for test of independence, Ei,j is the "theoretical frequency" for a cell, given the hypothesis of independence, and Oi,j is the observations of type j ignoring the row attribute (fraction of column totals). 5. Results of CNN Models Testing After using the formulas above for each class versus all classes and for each model, the results of the metrics when it comes to each model are presented in Table 4, Table 5, Table 6 and Table 7. For Model 1, the report is in Table 4 and its performance analysis in Table 7. We can observe that the model is working well for all organs, with slightly bigger error rate when it comes to the stomach. After the examination of the error that we saw in the predictions, many times this error occurs because the presence of pituitary or of saliva is misunderstood as the pituitary of the colon which is causing confusion in the model. Next, for Model 2, the report in Table 5 and its performance analysis in Table 7 show that this model is the most accurate among the three, when it comes to predictions; since the error rate is improved for stomach frames prediction and it also provides the best metrics for esophagus frames prediction. Lastly, the Model 3 report and performance metrics appear in Table 6 and Table 7. As we can observe, Model 3 provides the biggest error rate in stomach frames prediction among the rest of the models. Although, the predictions for esophagus and small intestine frames have better metrics using that model. Our results of independent validation and cross validation, demonstrate that the best of our three distinct models is that of Model 2. For the 4 x 4 contingency table of each of our CNN1, CNN2 and CNN3 models, our chi-square test results separately in a p-value <= 0.00001, showing that the four-class classification of each model is statistically independent. Moreover, for the 3 x 4 contingency table comparing our three CNN models, the chi-square test results in a p-value <= 0.00001. It is showing that the outputs of the three four-class models are statistically independent. 6. Conclusions By using our research as a tracking and four classes classification algorithm, physicians can successfully detect the gates of the four GI organs (and, furthermore, to recognize the digestive organ) that the capsule is passing by, in real time. The algorithms can be executed from a mobile platform that can be physically attached for the time of recording upon the patient. This can be used as a passive compass while navigating through the digestive tract, to reveal better metrics concerning each capsule design potential (i.e., to overcome palindrome movements or to obtain better insight on how to cope through them), as well as an activation control tool for a number of actions. The whole procedure will provide better accuracy per individual patient (in terms of charting topological idiosyncrasies), without any added cost (same hardware, the processing power needed should be provided by an external unit linked to the capsule). With the future advancement of technology, when sufficient electrical power will be available to ensure the independence of the capsule unit, it will become possible to embed in the capsule a microprocessor to execute the algorithm. For now, the algorithm could be executed upon an external mobile unit, as the video frames are transferred wirelessly in real time. Acknowledgments The authors are grateful to the Greek Aretaeio University Hospital, Attikon University Hospital, and Laikon General Hospital, and the Aristotle University of Thessaloniki. Author Contributions Conceptualization, E.S.S., M.E.Z., A.A.P. (Andreas A. Polydorou), G.S.S. and I.O.V.; methodology, E.S.S., M.E.Z., A.A.P. (Andreas A. Polydorou), G.S.S. and I.O.V.; software, S.A.A., A.A.P. (Alexios A. Polydorou) and N.M.A.; validation, S.A.A., A.A.P. (Alexios A. Polydorou) and A.A.P. (Andreas A. Polydorou); investigation, G.S.S. and E.S.S.; resources, A.A.P. (Andreas A. Polydorou); data curation, S.A.A., N.M.A. and A.A.P. (Alexios A. Polydorou); writing--original draft preparation, N.M.A., E.S.S. and S.A.A.; writing--review and editing, E.S.S. supervision, E.S.S., A.A.P. (Andreas A. Polydorou), I.O.V. and M.E.Z.; project administration, E.S.S. 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 the explicit usage of fully anonymized data. Informed Consent Statement Patient consent was waived due to the explicit usage of fully anonymized data. Data Availability Statement The data used in this study are available on request from the corresponding authors. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Folder structure. Figure 2 Images of esophagus (a), stomach (b), small intestine (c) and colon (d). Figure 3 Model 1 architecture. Figure 4 Model 2 architecture. Figure 5 Model 3 architecture. diagnostics-13-00865-t001_Table 1 Table 1 Model 1 summary. Layer Name Layer Type Number of Filters Output Shape Number of Parameters Conv2D Conv2D 16 (256, 256, 16) 448 Max_pooling2D MaxPooling2D (128, 128, 16) 0 Conv2D_1 Conv2D 32 (128, 128, 32) 4640 Max_pooling2D_1 MaxPooling2D (64, 64, 32) 0 Conv2D_2 Conv2D 64 (64, 64, 32) 18,496 Max_pooling2D_2 MaxPooling2D (32, 32, 64) 0 Flatten Flatten 65,536 0 Dense Dense 128 8,388,736 Dense_1 Dense 4 516 diagnostics-13-00865-t002_Table 2 Table 2 Model 2 summary. Layer Name Layer Type Number of Filters Output Shape Number of Parameters Conv2D Conv2D 32 (254, 254, 32) 896 Max_pooling2D MaxPooling2D (127, 127, 32) 0 Conv2D_1 Conv2D 64 (125, 125, 64) 18,496 Max_pooling2D_1 MaxPooling2D (62, 62, 64) 0 Conv2D_2 Conv2D 128 (60, 60, 128) 73,856 Max_pooling2D_2 MaxPooling2D (30, 30, 128) 0 Conv2D_3 Conv2D 256 (28, 28, 256) 295,168 Max_pooling2D_3 MaxPooling2D (14, 14, 256) 0 Flatten Flatten 50,176 0 Dense Dense 256 12,845,312 Dense_1 Dense 4 1028 diagnostics-13-00865-t003_Table 3 Table 3 Model 3 summary. Layer Name Layer Type Number of Filters Output Shape Number of Parameters Conv2D Conv2D 32 (252, 252, 32) 2432 Max_Pooling2D MaxPooling2D (126, 126, 32) 0 Conv2D_1 Conv2D 32 (122, 122, 32) 25,632 Max_Pooling2D_1 MaxPooling2D (61, 61, 32) 0 Conv2D_2 Conv2D 32 (57, 57, 32) 25,632 Max_Pooling2D_2 MaxPooling (28, 28, 32) 0 Flatten Flatten 25,088 0 Dense Dense 256 6,422,784 Dropout Dropout 256 0 Dense_1 Dense_1 4 1028 diagnostics-13-00865-t004_Table 4 Table 4 Report from testing 496 frames (124 not seen before frames of each organ) with CNN model 1. Matrix C Predicted Values Class k TPii TN i=14FPi i=14FNi Total tk Actual values 1 Esophagus C11 = 27 87 8 2 tk=1 = 124 2 Stomach C22 = 25 83 4 12 tk=2 = 124 3 Small Intestine C33 = 26 91 4 3 tk=3 = 124 4 Colon C44 = 29 94 1 0 tk=4 = 124 Total pk c = 107 pk=2= 355 pk=3= 17 pk=4= 17 s = 992 4 x 4 contingency table Significance Level: 0.05, X2 (N = 124) = 249.92, p < 0.00001. Significant at p < 0.05. diagnostics-13-00865-t005_Table 5 Table 5 Report from testing 496 frames (124 not seen before frames of each organ) with CNN model 2. Matrix C Predicted Values Class k TPii TN i=14FPi i=14FNi Total tk Actual values 1 Esophagus C11 = 28 90 5 1 tk=1 = 124 2 Stomach C22 = 30 84 3 7 tk=2 = 124 3 Small Intestine C33 = 26 93 2 3 tk=3 = 124 4 Colon C44 = 29 94 1 0 tk=4 = 124 Total pk c = 113 pk=2 = 361 pk=3 = 11 pk=4 = 11 S = 992 4 x 4 contingency table Significance Level: 0.05, X2 (N = 124) = 219.76, p = 0.00001. Significant at p < 0.05. diagnostics-13-00865-t006_Table 6 Table 6 Report from testing 496 frames (124 not seen before frames of each organ) with CNN Model 3. Matrix C Predicted Values Class k TPii TN i=14FPi i=14FNi Total tk Actual values 1 Esophagus C11 = 27 95 0 2 tk=1 = 124 2 Stomach C22 = 25 84 3 12 tk=2 = 124 3 Small Intestine C33 = 22 95 0 7 tk=3 = 124 4 Colon C44 = 29 77 18 0 tk=4 = 124 Total pk c = 103 pk=2= 351 pk=3= 21 pk=4= 21 s = 992 4 x 4 contingency table Significance Level: 0.05, X2 (N = 124) = 223.19, p = < 0.00001. Significant at p < 0.05. diagnostics-13-00865-t007_Table 7 Table 7 Performance metrics of our CNN models 1, 2 and 3 for independent validation (data not seen before). Model/Class Accuracy Error Rate Precision Specificity Sensitivity (Recall) F1 Score MCC Model 1/Class 1 vs. rest 0.9193 0.0806 0.7714 0.9157 0.9310 Model 1/Class 2 vs. rest 0.8709 0.1290 0.8620 0.9540 0.6756 Model 1/Class 3 vs. rest 0.9435 0.0564 0.8666 0.9578 0.8965 Model 1/Class 4 vs. rest 0.9919 0.0080 0.9666 0.9894 1 Model 1/Average macro 0.9314 0.0685 0.8667 0.9542 0.8758 0.871188 62.53618 Model 2/Class 1 vs. rest 0.9516 0.0483 0.8484 0.9473 0.9655 Model 2/Class 2 vs. rest 0.9193 0.0806 0.9090 0.9655 0.8108 Model 2/Class 3 vs. rest 0.9596 0.0403 0.9285 0.9789 0.8965 Model 2/Class 4 vs. rest 0.9919 0.0080 0.9666 0.9894 1 Model 2/Average macro 0.9556 0.0443 0.9131 0.9703 0.9182 0.915655 69.9200 Model 3/Class 1 vs. rest 0.9838 0.0161 1 1 0.9310 Model 3/Class 2 vs. rest 0.8790 0.1209 0.8928 0.9655 0.6756 Model 3/Class 3 vs. rest 0.9435 0.0564 1 1 0.7586 Model 3/Class 4 vs. rest 0.8548 0.1451 0.6170 0.8105 1 Model 3/Average macro 0.9153 0.0846 0.8775 0.9440 0.8413 0.858994 57.63078 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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PMC10000442 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050921 diagnostics-13-00921 Article CBCT Images to an STL Model: Exploring the "Critical Factors" to Binarization Thresholds in STL Data Creation Kamio Takashi Methodology Software Data curation Writing - original draft Visualization * Kawai Taisuke Conceptualization Methodology Writing - review & editing Supervision Leung Yiu Yan Academic Editor Department of Oral and Maxillofacial Radiology, School of Life Dentistry at Tokyo, The Nippon Dental University, 1-9-20 Fujimi, Chiyoda-ku, Tokyo 102-8159, Japan * Correspondence: [email protected]; Tel.: +81-3-3261-6516 01 3 2023 3 2023 13 5 92113 2 2023 24 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 ). In-house fabrication of three-dimensional (3D) models for medical use has become easier in recent years. Cone beam computed tomography (CBCT) images are increasingly used as source data for fabricating osseous 3D models. The creation of a 3D CAD model begins with the segmentation of hard and soft tissues of the DICOM images and the creation of an STL model; however, it can be difficult to determine the binarization threshold in CBCT images. In this study, how the different CBCT scanning and imaging conditions of two different CBCT scanners affect the determination of the binarization threshold was evaluated. The key to efficient STL creation through voxel intensity distribution analysis was then explored. It was found that determination of the binarization threshold is easy for image datasets with a large number of voxels, sharp peak shapes, and narrow intensity distributions. Although the intensity distribution of voxels varied greatly among the image datasets, it was difficult to find correlations between different X-ray tube currents or image reconstruction filters that explained the differences. The objective observation of voxel intensity distribution may contribute to the determination of the binarization threshold for 3D model creation. cone beam computed tomography imaging radiology oral and maxillofacial surgery dentistry DICOM 3D printing computer-aided design STL data This research received no external funding. pmc1. Introduction Recently, patient-specific three-dimensional (3D) models have been widely used in clinical practice. In particular, osseous 3D models are used to simulate surgical procedures on delicate anatomical structures during maxillofacial surgery, craniofacial surgery, and otolaryngology, and they are also used for surgical training and medical education. These 3D models allow users to actually manipulate the 3D model and view it from any angle. They can also be simulated with actual surgical instruments. Such an understanding of the three-dimensional anatomy of the surgical site contributes to a better understanding on the part of the surgeon, the surgical team, and medical students. This, in turn, is expected to lead to more predictable surgeries and shorter operating times. Its use as a preoperative educational tool for patients also contributes to better communication . The generalization of 3D printing technologies has facilitated the fabrication of such 3D models from multi-detector row computed tomography (MDCT) images using desktop 3D printers; i.e., "one-stop 3D printing" . Over the last two decades, cone beam computed tomography (CBCT), which has a smaller field of view (FOV) than MDCT and a higher spatial resolution, has become remarkably widespread, especially in the field of oral and maxillofacial surgery . The design of osseous 3D models primarily requires 3D computer-aided design (CAD) data represented in stereolithography (STL) format. Although these data are used to create STL models (3D CAD models), the design of a more precise 3D model is expected to use image datasets from the CBCT scanner as the source of data. The first step, binarization of the Digital Imaging and Communications in Medicine (DICOM) image dataset, is the most important operation in the sequence of fabricating 3D models. On the basis of numerous 3D model fabrication examples and our previous studies, unlike MDCT image datasets, it is sometimes difficult to determine the value to set the binarization threshold of an STL model using CBCT image datasets . Several factors make the binarization of CBCT image datasets difficult. The biggest problem is that the threshold for binarization varies from one CBCT image dataset to another, and there is no specific value, such as a "CT value", for an MDCT image. The quality of image datasets exported as DICOM files varies from one CBCT unit to another, which is a major factor affecting the determination of the threshold value. These are also the problems that plague 3D CAD operators in determining the appropriate binarization threshold for creating STL models. To enable anyone to create 3D models that satisfy clinical demands, it is necessary to establish a method to create highly precise 3D models from CBCT images in a reasonable procedure. It is also necessary to understand the characteristics of image datasets and what factors make it easy or difficult to determine the binarization threshold for STL model creation. Therefore, to understand the factors that affect the determination of the binarization threshold, this study aimed to evaluate the quality of STL models created from image datasets acquired with a CBCT scanner and to explore the factors relating to successful STL model creation from the perspective of 3D image engineering and 3D image processing. 2. Materials and Methods 2.1. Definition In this study, DICOM image datasets exported to the STL file format (or data after segmentation) are called "STL data"; 3D surface CAD models (virtual 3D models) created from STL data are called "STL models". The model fabricated with a 3D printer from the STL data is referred to as a "3D model". The units for the intensity (brightness) values of the voxels are expressed in gray values (GV), according to a previous report by Katsumata et al. . 2.2. CBCT Scanning and Imaging to STL Model Creation A dry human skull was used as a specimen. The skull was placed in a 20 cm cubic acrylic case filled with water and scanned. A cranial specimen with bilateral missing maxillary molars, without crown restorations, was used for maxillary alveolar and periapical maxillary sinus surgery . Scanning was performed with two different CBCT units, SOLIO XZ II (Asahi Roentgen Ind., Co. Ltd., Kyoto, Japan) and 3D Accuitomo F17 (J. Morita Mfg. Corp., Kyoto, Japan). After scanning, the image processing software attached to each CBCT unit was used to export the images as a DICOM file. Details of each scanning condition and the image reconstruction filters applied are shown in Table 1. The impact of differences in the scanning X-ray tube current and image reconstruction filters on the determination of the binarization threshold in STL model creation was evaluated. The binarization threshold for each image was set so that both anterior and posterior nasal spines could be visualized and identified. Volume Extractor 3.0 (VE3, i-Plants Systems, Iwate, Japan), a 3D medical/general purpose image processing software package , was used to binarize the image datasets and create STL models. In VE3, the Marching Cube method was used as the isosurface extraction method. VE3 was used only for the conversion of image datasets to STL models, not for image linear interpolation or the noise reduction function. The removal of spatial polygonal noise (independent polygonal data not touching the surface of the STL model) was performed using the "Remove small polygons" command in the polygon data editing software package POLYGONALmeister ver7 (UEL Corp., Tokyo, Japan) . 2.3. Converting the DICOM Image Dataset to 256 Grayscale and Making a Histogram ImageJ (version 1.53k, NIH, Bethesda, MD, USA) was used to convert the DICOM image dataset to 256 grayscale, and its histogram was used to evaluate the appearance of the voxel intensity distribution. 2.4. STL Model Superimposition, Comparison, and 3D Model Fabrication To find the differences in the shape of each STL model created from the CBCT image dataset, the STL models were superimposed and the shape error (signed difference between two STL models) was observed. An STL model was created from the MDCT image dataset, which was used as the gold standard for the STL model shape. The MDCT scanner was an Aquilion 64 system (Canon Medical Systems Inc., Tochigi, Japan), with the following scanning conditions: X-ray tube voltage of 120 kV, X-ray tube current of 150 mA, slice thickness of 0.5 mm, FOV of 240 mm, a 512 x 512 matrix, and convolution kernel FC81 (bone sharp). The 3D evaluation software package spGauge 2014.1 (spG, ARMONICOS Co., Ltd., Shizuoka, Japan) was used for the superimposition of the created STL models and their color mapping. In the superimposition, one of the two STL models was moved using spG's best fit surface-based registration algorithm, and the operation was repeated until the misalignment with the other STL model was as close as possible to 0.00 mm. STL models created from CBCT image datasets were fabricated as 3D models using the same procedure as in our previous report . 3D model fabrication was performed with a desktop Fused Deposition Modeling (FDM) 3D printer (Value3D MagiX MF-800, Mutoh Industries, Tokyo, Japan). The 3D printing conditions are as follows: a PolyTerra-1.75 mm PLA filament, a laminating pitch of 0.2 mm, an infill density of 30%, a printing speed of 40 mm/s, and with support structures and rafts. 3. Results 3.1. Visibility of the Exported Images Each image in the CBCT image dataset was imported and displayed in VE3, as shown in Figure 2. These are the native images with the default display settings of VE3. The same specimen was scanned; however, different X-ray tube currents and different applied image reconstruction filters resulted in different appearances. 3.2. Differences in the Shape of Each STL Model The STL model created from each CBCT image dataset, with the binarization threshold for STL model creation set to the GV where the anterior and posterior nasal spines can be identified, is shown in Figure 3. For each image dataset, there was a difference in the shape of the STL model and the number of polygons that were mixed in as noise. 3.3. Histogram of the Voxel Intensity Distribution Figure 4A,B show the voxel intensity distribution of each CBCT image dataset, and Figure 4C shows the voxel intensity distribution of the MDCT image dataset used as the gold standard for STL model creation. In both CBCT image datasets, each voxel had a single peak; however, the maximum value and range of the peak varied. Histogram observations showed that, compared with the 3D Accuitomo F17, the SOLIO XZ II had fewer maximum voxels and tended to converge at the center of the voxel intensity value distribution. In the image dataset acquired on the Aquilion 64, the distribution of the voxel intensity values was bimodal, with apex-like peaks and narrow ranges. 3.4. Differences in Images for Each GV The image visibility also differed significantly depending on the binarization threshold. At lower threshold values, the spatial noise increased. However, a higher threshold resulted in less replicability of thin areas of bone tissue . 3.5. Shape Error of the STL Models The superimposed shape error of the STL models created from the two CBCT and MDCT image datasets, respectively, showed that both the SOLIO XZ II and 3D Accuitomo F17 had more noise in the teeth and surrounding tissue, and the error was large. Additionally, the SOLIO XZ II had a rougher surface than the 3D Accuitomo F17, with a higher percentage of green to yellow or slightly distended areas . 4. Discussion Dental implant surgeries, such as maxillary sinus floor augmentation, and maxillofacial surgery, such as a Le Fort I osteotomy, require delicate handling of the maxillary alveolar bone, maxillary sinus, and sphenoid process regions. As a result, highly precise 3D models are necessary for their simulation. In this study, we explored the optimal binarization threshold for STL model creation to fabricate osseous 3D models that faithfully replicate delicate and complicated anatomical structures. Two flagship CBCT scanners from two different suppliers were used. One is the SOLIO XZ II, a multifunctional scanner capable of CBCT scanning and panoramic imaging. This scanner is mainly used in the field of dentistry and maxillofacial surgery. The other is the 3D Accuitomo F17 scanner, which is a dedicated scanning unit for CBCT, with a range from a minimum ph40 mm x height of 40 mm to a maximum of ph170 mm to a height of 230 mm, and 11 different FOVs can be selected according to the region of interest. The Accuitomo F17 scanner is primarily used in the fields of oral and maxillofacial surgery, craniofacial surgery, and otolaryngology. Three steps are required to create a 3D model from an image dataset . The first step is to acquire the 3D volumetric data of the object as a DICOM file. The second step is to segment the anatomical structures of the 3D model fabrication object from the surrounding structures and export them to a 3D CAD model in STL file format. While segmentation of hard and soft tissues is relatively easy, the subsequent STL model creation is sometimes difficult for two reasons. Small or thin bones (such as in the maxillary sinus, nasal cavity, or orbital floor) and narrow bone cavities (such as the joint cavity of the temporomandibular joint) are not easily reflected in the STL model. Problems resulting from the scanning characteristics of CBCT/MDCT (e.g., metallic artifacts from dental materials, beam hardening, overshooting, and undershooting) reduce image visibility and make it difficult to determine the threshold for binarization. The final step is to generate data for 3D printing, called G-code, from the created STL model and run the 3D printer. Failure in any of these steps results in poor quality of the 3D model. Therefore, the creation of satisfactory STL data is the most important operation in the sequence of 3D model fabrication . CBCT images do not contain the quantitative physical quantities that are in MDCT images, such as "CT values" or "Hounsfield units" . In other words, because the GV of a CBCT image is not a linearized value, the binarization threshold is also difficult to determine using standard methodologies. Therefore, the shape of the STL model may be highly dependent on the discretion of the 3D CAD operator. The 3D model created from the STL model (A6M), which the authors created by determining the binarization threshold, is shown in Figure 7. Even with the full use of polygon data editing software packages, it was difficult to control the noisy 3D CAD model. The detail of the fabricated 3D model is somewhat less replicable, with numerous irregular structures appearing on the surface. With our approach, differences in the visibility of each X-ray tube current and image reconstruction filter--that is, differences in the scanning and imaging characteristics of each CBCT unit--could be objectively visualized as differences in the intensity distribution of voxels. This is the same as a visualization of the differences in image contrast in each image dataset. These differences in image datasets can be attributed to differences in the method of image reconstruction performed by image processing software after CBCT image data acquisition; i.e., differences in the image gamma correction applied to each filter. It was easier to determine the binarization threshold of an image dataset with high image contrast that was made in the histogram as a positive curve with more voxels, high peaks, a relatively narrow distribution, and a steep slope. Unsuitable binarization thresholds can result in poor replication of details in the STL model. 3D models from poor-quality STL models can, for example, lead to unintended defects or cavities, thus compromising the reliability of the surgical simulation. This result partly explains why it is difficult to determine the binarization threshold when the peak number of voxels is too low or the voxel intensity distribution range is too narrow or too wide. Although the binarization threshold required for STL data depends on the application of the 3D model and cannot be uniformly specified, a histogram of the voxel intensity distribution of the image dataset would help determine the binarization threshold for creating STL models that satisfy clinical demand. There are numerous reports on automatic segmentation of CBCT and MDCT images. However, even for MDCT images, for which voxel intensity values can be obtained quantitatively, automatic segmentation is difficult to perform. For CBCT images, however, there are many different scanners available, with varying scanning and imaging characteristics, making segmentation a very difficult challenge . Furthermore, to our knowledge, there are few reports evaluating MDCT images for STL data creation for 3D model fabrication, and there are no reports using the same approach as ours using CBCT images . CBCT scanners are expected to be used as 3D scanning devices for dental casts and dental prosthetics (surgical guides, dentures) . As the demand for 3D printed models increases, better STL data are needed and their importance will increase. Because the two CBCT units used in this study were not equipped with image reconstruction filters that are specialized for the 3D model, such as the "STL data creation mode", the binarization threshold for creating STL data had to be determined manually by the 3D CAD operators. Considering the rapid development of 3D technology, a CBCT unit equipped with an "Imaging filter for 3D copy" that can create optimal STL data under optimal scanning and imaging conditions will likely be available soon. A limitation of this study is that there were only 18 image datasets with each scanning X-ray tube voltage set to 85 kV and three representative image reconstruction filters. Both CBCT units had other scanning modes. In addition to the scanning conditions, such as the X-ray tube voltage and tube current, it is possible to select a larger or smaller FOV according to the object size and image reconstruction filters according to the diagnostic purpose. Another limitation is that there is no standard for determining the binarization threshold for creating STL models from CBCT images. We have used a threshold where the targeted anatomical structures are somewhat visible. However, we recognize that this binarization threshold value was determined by the experience of the authors, who are also 3D CAD/3D printing operators, and it is lacking objectivity. There is currently no methodology to prove this binarization threshold is appropriate; however, that is a topic for future research. In this study, we evaluated voxel intensity distribution histograms made from DICOM image datasets from two different CBCT scanners to determine why it is difficult to create STL data for a 3D model from CBCT images and how to address this issue. The image appearance varied greatly depending on the scanning and imaging conditions, and the binarization threshold also varied relative to each image. In conclusion, the results of this study suggest the importance of understanding the scanning and imaging characteristics of each CBCT device in advance to determine the optimal and objective binarization threshold. Our approach, which enables facile observation of the visibility of the voxel intensity distribution and is technically simple, may help find the "critical factors" to binarization threshold determination, which is essential for the fabrication of 3D models for the medical field. Acknowledgments We would like to thank Asahi Roentgen Ind., Co. Ltd., and J. Morita Mfg. Corp. for their substantial cooperation on this study. Author Contributions Conceptualization, T.K. (Taisuke Kawai); methodology, T.K. (Taisuke Kawai); software, T.K. (Takashi Kamio); validation, T.K. (Takashi Kamio); formal analysis, T.K. (Takashi Kamio); investigation, T.K. (Taisuke Kawai) and T.K. (Takashi Kamio); resources, T.K. (Taisuke Kawai); data curation, T.K. (Takashi Kamio); writing--original draft preparation, T.K. (Takashi Kamio); writing--review and editing, T.K. (Taisuke Kawai); visualization, T.K. (Takashi Kamio); supervision, T.K. (Taisuke Kawai); project administration, T.K. (Taisuke Kawai); funding acquisition, T.K. (Taisuke Kawai) 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 because they belong to an academic institution. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The specimen and CBCT units. (A) A specimen in an acrylic case filled with water, and the specimen in the (B) SOLIO XZ II (Asahi Roentgen Ind., Co. Ltd., Kyoto, Japan) scanner, and (C) 3D Accuitomo F17 (J. Morita Mfg. Corp., Kyoto, Japan) scanner. Figure 2 CBCT horizontal cross-sectional images of anterior and posterior nasal spines without window level setting displayed in Volume Extractor 3.0 using the (A) SOLIO XZ II scanner and (B) 3D Accuitomo F17 scanner. Figure 3 The STL models from the (A) SOLIO XZ II scanner and (B) 3D Accuitomo F17 scanner were created with the binarization threshold set to an arbitrary value. The abbreviation of each STL model is shown at the left shoulder of each figure, and the binarization threshold is shown at the bottom center of each figure. The GV indicates the percentile after the intensity value of each image dataset was converted to 256 grayscale. Figure 4 Histograms of voxel intensity for CBCT images from the (A) SOLIO XZ II and (B) 3D Accuitomo F17 scanners and (C) Aquilion 64 MDCT scanner images. The vertical axis represents the number of voxels and the horizontal axis represents the voxel intensity value in 256 grayscale. Figure 5 Images at different binarization threshold values (image dataset: A4C). The gray values shown at the bottom of each figure are the native voxel values of the CBCT image (in this case, from 3721 to -2359 [GV]) converted to 256 grayscale. Figure 6 Shape error of two superimposed STL models. (A) CBCT STL model (image dataset: A4C) vs. MDCT STL model. (B) CBCT STL model (image dataset: M8G) vs. MDCT STL model. The areas where shape errors compared with the MDCT STL model used as the gold standard were observed are in color. Positive errors (expansion) are shown in warm colors and negative errors (contraction) are shown in cool colors. Figure 7 (A,C) Close-up view of the specimen. (B,D) Close-up view of the 3D model fabricated from an STL model (image dataset: A4C) with a desktop FDM 3D printer. In fabricating the 3D model, the STL model was smoothed, noise-reduced, and polygon-count-reduced using POLYGONALmeister Ver 7. Observations of the 3D model show that the replication of the teeth and surrounding tissues is poor (arrows). The incisal and greater palatine foramen are also generally narrower (arrowheads). Partial defects on the surface of the 3D model because of 3D printing errors are noted (*). diagnostics-13-00921-t001_Table 1 Table 1 Overview of the scanning and image reconstruction filters for each CBCT unit and abbreviations for each DICOM image dataset. CBCT Unit X-ray Tube Voltage Scanning Mode Field of View Voxel Size Image Processing Software (Version) X-ray Tube Current Image Reconstruction Filter Abbreviation SOLIO XZ II 85 kV I-MODE ph90 x 91 mm 0.177 mm NEOPREMIUM2 (NeoExpCalc 1.0.17.0) 4.0 mA Scattered ray correction A4C Sharp A4H Smooth A4M 6.0 mA Scattered ray correction A6C Sharp A6H Smooth A6M 8.0 mA Scattered ray correction A8C Sharp A8H Smooth A8M 3D Accuitomo F17 85 kV D140 x H100 Hi-Fi ph140 x 100 mm 0.200 mm i-Dixel (3DXAPP 2.3.7.5) 4.0 mA Bone M4B Dental M4D General M4G 6.0 mA Bone M6B Dental M6D General M6G 8.0 mA Bone M8B Dental M8D General M8G 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. 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PMC10000443 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051069 foods-12-01069 Article Hyperspectral Imaging Combined with Chemometrics Analysis for Monitoring the Textural Properties of Modified Casing Sausages with Differentiated Additions of Orange Extracts Feng Chao-Hui 12* Arai Hirofumi Investigation Writing - original draft Writing - review & editing Supervision Project administration Funding acquisition 1 Rodriguez-Pulido Francisco J. Methodology Software Validation Formal analysis Investigation Data curation Writing - original draft Writing - review & editing Visualization 3 Alamprese Cristina Academic Editor 1 School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, Hokkaido, Japan 2 RIKEN Centre for Advanced Photonics, RIKEN, 519-1399 Aramaki-Aoba, Aoba-ku 980-0845, Sendai, Japan 3 Food Colour and Quality Laboratory, Facultad de Farmacia, Universidad de Sevilla, 41012 Sevilla, Spain * Correspondence: [email protected]; Tel.: +81-(0)157-26-9390 02 3 2023 3 2023 12 5 106910 2 2023 22 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 textural properties (hardness, springiness, gumminess, and adhesion) of 16-day stored sausages with different additions of orange extracts to the modified casing solution were estimated by response surface methodology (RSM) and a hyperspectral imaging system in the spectral range of 390-1100 nm. To improve the model performance, normalization, 1st derivative, 2nd derivative, standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied for spectral pre-treatments. The raw, pretreated spectral data and textural attributes were fit to the partial least squares regression model. The RSM results show that the highest R2 value achieved at adhesion (77.57%) derived from a second-order polynomial model, and the interactive effects of soy lecithin and orange extracts on adhesion were significant (p < 0.05). The adhesion of the PLSR model developed from reflectance after SNV pretreatment possessed a higher calibration coefficient of determination (0.8744) than raw data (0.8591). The selected ten important wavelengths for gumminess and adhesion can simplify the model and can be used for convenient industrial applications. hyperspectral imaging texture sausage core orange extracts modified natural casing Northern Advancement Center for Science & Technology of Hokkaido JapanThe Japan Science SocietyGovernment of Japan Ministry of Education, Culture, Sports, Science and Technology MEXT2020L0277 Japan Society for the Promotion of Science Grant-in-Aid for Early Career Scientists20K15477 Kitami Institute of TechnologyFY2021 This research was financially supported by Grants-in-Aid for Regional R&D Proposal-Based Program from Northern Advancement Center for Science & Technology of Hokkaido Japan, the Sasakawa Scientific Research Grant from The Japan Science Society, Leading Initiative for Excellent Young Researchers (LEADER) from the Government of Japan Ministry of Education, Culture, Sports, Science and Technology MEXT (2020L0277), the Japan Society for the Promotion of Science Grant-in-Aid for Early Career Scientists (20K15477), FY 2022 Mishima Kaiun Memorial Foundation, and FY 2022 & FY2021 President's Discretionary Grants, funded by the Kitami Institute of Technology. pmc1. Introduction Compared to conventional spectroscopic methods, hyperspectral imaging renders the measured reference parameters can be shown from spot to spot in samples . Combined with the chemometrics analysis, it has been proved to be a powerful and emerging non-destructive technique that has been comprehensively applied to pork , lamb , beef , chicken , ham , and processed meat . Wang and He (2019) non-invasively classified the Cantonese sausage degree using hyperspectral imaging, and the predictive accuracy can reach 100% . The physicochemical and microbial attributes of bratwurst packaged in a pouch of 60 mm polyvinylidene chloride coated with polyamide (PVDC/PA) film after 20 days of storage (4 degC) were evaluated . All of those illustrate that HSI is an emerging method to be widely applied to different types of meat products. Sausage casing is the material used to encase sausage meat. It can be made from various materials, such as natural casings, synthetic casings, or collagen casings. Natural casings are typically made from the intestines of animals (e.g., sheep, pig (named as hog casing), or beef), while synthetic casings are made from materials such as cellulose, plastic, or fibrous materials. Collagen casings are made from collagen fibers, which are derived from the skin and connective tissue of animals. Sausage casings serve several purposes in the production of sausage. They provide a barrier between the sausage meat and the environment, helping to prevent spoilage and contamination. They also help to give the sausage its characteristic shape and size and can contribute to the texture and flavor of the final product. From the sausage quality point of view, the texture is an essential parameter to evaluate sausages, where the minced meat and fat were stuffed in the natural casings. Compared to artificial casings that are uniform, strong, flexible, and of hygienic quality, and natural casings are preferable to the sausage manufactories owing to their tenderness with a special bite . Because the natural casings are susceptible to burst during production (such as handling, smoking, stuffing, cooking, and so on), there is a need to improve their properties to tolerate the high pressure generated during sausage production or post-cooking whilst maintaining the quality of the sausages. Feng et al. (2014) exploited the modified casings treated with a surfactant solution and slush salt with lactic acid and found less burst incidence occurred . This is due to the porous structure, which releases pressure during stuffing or cooking. Nevertheless, this porous structure may render microorganisms easy to invade. There is a risk where lipid oxidation may occur. Therefore, it makes sense to add some natural additives to prolong the shelf life of this type of sausage. It is well known that various bioactive compounds exist in citrus fruit peels and are useful and helpful for human beings . Currently, waste orange peels (WOP) are not fully utilized and are either left in landfills as fertilizer or utilized as animal feedstuff . Hesperidin, a common composition rich in citrus fruits, especially orange peels, showed its potential for therapeutics against COVID-19 in recent studies . The effects of the addition of orange peel flour on the texture of sausage have been investigated . The hardness of the sausages added with orange peel flour was significantly higher than the control group but showed better moisture and yield . Diaz-Vela et al. (2015) studied the effects of the addition of cactus pear flour and pineapple peel flour to cooked sausages on the texture attributes during 20-day storage . The softest samples were observed with the sausages containing cactus fruit peel flour, while the cohesiveness of samples with pineapple peel flour were different than those with cactus fruit peel, irrespective of the storage days . In those studies, peels were used as the flour or fiber, and, up until now, few relevant studies has addressed evaluating the effects of orange peel extracts on the texture of sausages stuffed in modified hog casings. The objectives of the current study are to evaluate the effects of different combinations of surfactant solution and orange extracts addition on the textural properties of sausage cores by using hyperspectral imaging coupled with algorithms. Subsequently, important wavelengths will be selected for the sausage core texture with the different treated combinations. 2. Materials and Methods 2.1. Sample Preparation Natural hog casing sections (30 cm), purchased from a local Japanese casing factory (Pakumogu.com, Niigata Prefecture, Japan), were desalted and modified in a solution composited of soy lecithin, soy oil, and orange extracts. A magnetic agitation was used to mix the solution and casing sections at 500 rpm and 25 degC. After the residence time, the casings (without rinsing) were put in salt and added with lactic acid for another residence time. Orange extracts were obtained from dried blade-milled Valencia sweet orange (Citrus sinensis) powder by Soxhlet extraction using 100% ethanol. The extracts from Soxhlet extraction were washed with a small amount of distilled water after leaving them in the fume hood overnight and transferring them to a filter paper. The crude orange extracts were obtained by drying naturally in a desiccator for three days. The detailed extraction procedures can be found in Feng et al. . The effects of variables, soy lecithin (X1, SL), soy oil (X2, SO), residence time (X3, RT), the addition of orange extracts (X4, OE), and lactic acid (X5, LA), added in the slush salt, were studied by response surface methodology (RMS). The central composite design (CCD) was performed in Minitab 21.1 software (Kozo Keikaku Engineering Inc., Tokyo, Japan). The coded values and actual values of the independent variables were shown in Table 1. The CCD can provide the same quantity of information in all directions of the fitted surface by introducing star points. The star points were used to render the central composite design rotatable. The center point was executed in sextuplicate to calculate the reproducibility of the method and a single run for each combination was conducted in Table 2 with a randomized order. In this way, the effect of unexplained variability in the observed responses owing to extraneous factors can be minimized. Hardness (Yh), springiness (Ys), gumminess (Yg), and adhesion (Ya) were the responses in this study. In order to develop the relationship between independent variables (Xi; i = 1-5) and responses (Yn, n = h, s, g, a), a second-order polynomial equation was used to fit the experimental data: (1) Y(n) = m + i=1miXi +i=1miiXi2+i=1j=i+1mijXiXj where m, mi, mii, and mij are the constant, linear, quadratic, and interaction coefficients, respectively. The accuracy of fitted models was estimated by determination coefficient (R2) and non-significant lack of fit. Sausages were made using modified hog casings and natural hog casings. The composition of the sausage batter (total weight: 6966.80 g) was shoulder lean pork (57.70%), back fat (24.69%), salt (2.87%), sugar (1.72%), Chinese white wine (10.31%, ethanol content: 52% v/v), black pepper (1.06%), spicy pepper (0.61%), and seasonings (1.03%). A stuffing machine was employed to fill the well-mixed batter (curing 2 h at 4 degC) using modified casings and control natural casings. The sausages were twisted into sections and hung in the oven to dry for 24 h at 45 degC and aged at the temperature of 20 degC for an additional 48 h. Following this, the sausages were sectioned, sterilized, cut, and vacuum packaged. The packaged sausage sections were finally stored at 4 degC for sixteen days for HSI image capture and textural analysis. 2.2. Image Acquisition and Processing The sausage cores were prepared with a diameter of 2.77 +- 0.16 cm and a height of 2.03 +- 0.16 cm. Images were captured by a laboratory visible 10-bit charged coupled device hyperspectral camera (NH-4-KIT, EBA Japan, Tokyo, Japan). The exposure time was 12.47 ms with push-broom line scanning. The flame rate was 100 fps and three halogen lamp lights were fixed beside the camera. A white sheet was employed to obtain an even light distribution and to avoid shadow. The camera spectral range was from 350-1100 nm divided into 151 bands. Samples were placed on a black sheet (to obtain a good contrast between the sample and background), perpendicular to the camera in a dark room with a room temperature controlled at 20 degC. A reflectance mode was used for imaging acquisition. Before measurement, a white reference with 100% reflectance was used to calibrate the HSI system. Dark reference was carried out by covering the camera lens with its opaque cap completely. The corrected images reference (Rcorrection) was obtained via Equation (2) (2) Rcorrection=R1-R2R3-R2 where R1, R2, and R3 are the raw, dark, and white reflectance images, respectively. A software named HSAnalyzer was employed to extract and analyze sample spectra. The version of this software is 1.2, produced by EBA Japan, Tokyo, Japan. The region of interest (ROI) of sausage core with different casing treatments was selected automatically: all pixels, which had reflectance higher than 0.06 at 735 nm, were considered for hardness, springiness, gumminess, and adhesive, respectively. 2.3. Textural Profile Analysis (TPA) After HSI imaging acquisition, each meat core without casing was immediately put onto the center of a texture testing machine (EZ Test, Shimadzu Ltd., Kyoto, Japan) at room temperature of 20 degC. Two cycles of 50% compression with a 500 N aluminum cylindrical plunger (AL D36) load cell with a deformation rate of 1.0 mm/s were employed. The hardness, springiness, gumminess, and adhesion were recorded for the overall textural assessment. The parameter setting for conducting the textural profile analysis was based on Shin and Choi (2021) , Feng et al. (2014) , Herrero et al. (2008) , and the preliminary tests. Sausage textural analysis was conducted in triplicate. 2.4. Selection of Important Wavelengths The weighted regression coefficients (BW) with large absolute values were selected as the important wavelengths. In this way, the model could be simplified and potentially improve its accuracy by eliminating the noise and redundancy information. A new simplified model was developed according to those selected wavelengths. 2.5. Model Development and Evaluation The partial least square regression models with full and important wavelengths were used to establish the relationship between textural parameters and the spectra of the sausage cores with different casing modifications. Several spectral data pre-treatments, such as normalization, the 1st and 2nd derivatives, standard normal variate (SNV), and multiplicative scatter correction (MSC), were applied to improve the model's performance. One-third of the samples (n = 11) were randomly chosen and used for the validation group, while the left two-thirds (n = 22) were used for the calibration group. The predictive ability was evaluated by the mean square error of calibration (RMSEC), validation (RMSEV), the determination coefficients of calibration (Rc2), and validation (RV2). 2.6. Statistical Analysis The simultaneous effects of SL, SO, RT, OE, and LA added in the slush salt were analyzed by Minitab 21.1 (shown in Table 3). The effects of different casing treatments on TPA were analyzed by Tukey's HSD (honestly significant difference) ANOVA, as shown in Table 4 (one-way, IBM SPSS Statistics 28, Armonk, NY, USA). 3. Results and Discussion 3.1. Effects of SL, SO, RT, OE Addition, and Salt with LA on Textural Properties of Sausage Core The simultaneous five effects on the textural properties of sausage cores were analyzed by response surface methodology. The highest R2 value of the regression model is the one developed for adhesion (77.57%), while the lowest value can only be 44.32%, developed by springiness. The lack of fits for models developed for all the textural parameters were insignificant (p > 0.05), indicating that those models were highly adequate. The predicted polynomial equations for the textural attributes, as in the uncoded units, are as follows: (3) Yh = 307.00 - 32.70 X1 - 17.60 X2 - 2.30 X3 - 290.00 X4 - 7.10 X5 + 1.44 X12 + 10.81 X22 + 0.01 X32+ 104.00 X42 + 2.56 X52 + 2.56 X1 x X2 + 0.14 X1 x X3 - 38.4 X1 x X4 + 0.90 X1 x X5 + 0.20 X2 x X3 + 27.40 X2 x X4 - 2.88 X2 x X5 - 0.08 X3 x X4 - 0.00 X3 x X5 + 16.90 X4 x X5 (4) Ys =-12.08+0.29 X1+1.07 X2+0.00 X3+4.04 X4+1.08 X5+0.03 X12-0.13 X22+0.00 X32-3.74 X42-0.02 X52-0.03 X1x X2+0.00 X1x X3-0.04 X1x X4-0.03 X1x X5-0.01 X2x X3-0.37 X2x X4-0.00 X4x X5+0.01 X3x X4-0.00 X3x X5-0.08 X4x X5 (5) Yg =-9.66-0.51 X1-1.32 X2-0.02 X3+4.67 X4+1.13 X5+0.06 X12+0.19 X22-0.00 X32+3.49 X42-0.02 X52+0.15 X1x X2+0.00 X1x X3-0.57 X1x X4-0.00 X1x X5+0.01 X2x X3+0.11 X2x X4-0.03 X2x X5+0.04 X3x X4+0.00 X3x X5-0.38 X4x X5 (6) Ya =-15.31-0.95 X1+1.26 X2-0.01 X3-8.14 X4+1.67 X5+0.07 X12+0.14 X22-0.00 X32+4.68 X42-0.04 X52+0.02 X1x X2+0.01 X1x X3-0.96 X1x X4+0.00 X1x X5+0.01 X2x X3-0.05 X2x X4-0.13 X2x X5+0.04 X3x X4-0.00 X3x X5+0.33 X4x X5 For all the textural attributes of the sausage core, orange extracts (X4) showed the most important role according to the corresponding coefficient from Equation (3). Interactive effects of X1 x X4 on adhesion can be observed at a 5% significant level (Table 3). Based on the two-dimensional contour plot and the three-dimensional surface plot displayed in Figure 1, it can be discovered that adhesion decreased if a low SL concentration was associated with higher OEs. It is well known that hardness is defined as the peak force during the initial penetration cycle, while adhesion is defined as the negative area under the force-time curve following the first withdrawal . It was reported that the increased adhesiveness may be due to the release of fat . 3.2. Spectra Overview Figure 2 illustrates the mean reflectance of sausages core with different modified casings. The reflectance of the sausage core with treatment 11 was higher (i.e., lower absorbance) than that of treatment 32. The average hardness of the sausage core with treatment, 11 (45.67 +- 5.69 N), was significantly lower than that with treatment, 32 (84.43 +- 1.01 N) (p < 0.05). The mean springiness of the treatment 11 (0.70 +- 0.38 mm) sample was higher than treatment (21 samples (0.48 +- 0.03 mm)) and control (0.46 +- 0.02 mm), although it was not significant at 5% level (Table 4, p > 0.05). Those indicate that sausage stuffed with the casing of treatment 11 possessed higher springiness with soft properties. Regarding adhesion, it represents the force required to overcome the stickiness or adhesion of a food product. The negative sign indicates that the force is acting in the opposite direction of the compression force used to deform the product. The higher the absolute value is, the stronger adhesion (i.e., sticky or slimy) will be. It can be found that control sample (-1.52 +- 0.38) and sample treated by treatment 5 (-1.51 +- 0.03) possessed significantly higher adhesion than that treated by treatment 12 (-0.44 +- 0.02, the lowest) (p < 0.05). There are several factors affect sausage's adhesion, which includes meat composition, mixing grinding during sausage filling production, cooking temperature, casing types, additives, pH level, stuffing processing, and so on. In this study, the sausage filling was prepared in the same batch and stuffing and pre-cooking in the same behavior. The only difference may be due to the casing types and the pH change during the 16-d storage under different types of the modified casing. A pH level that is too high or too low can negatively affect the protein structure of the meat and finally lead to poor adhesion. The absorbances are associated with the combinations of fundamental vibrations of C-H, N-H, O-H, and S-H functional groups . For example, the slope shape between 600-700 nm is always related to oxymyoglobin formation. The third overtone of N-H stretching is related to a transmittance absorption band at 790 nm coupled with protein . Subtle absorption at 780 nm and 980 nm may associate with the third and second overtones of O-H stretching, respectively, which may be relevant to water . Absorption at 940 nm is related to C-H third overtone and relevant to fat . 3.3. Calibration Model Using Full Wavelengths Table 5 displays the validation and calibration of textural attributes using full spectra. Only the adhesion of the PLSR model combined with 143 variables showed a comparably better-predicting capability than other textural properties. Compared with all the pre-treatments, Rc2 (0.8744) and Rv2 values (0.6837) after SNV treatment were higher than that of raw data (Rc2 = 0.8591, Rv2 = 0.5556), indicating the model improvement. The function of SNV is reported to remove variability in the reflectance spectra, resulting from light scattering . Likewise, the function of MSC is to compensate for additive and multiplicative effects . The individual discriminant factor analysis classified groups with HSI were assigned a quality deterioration index (QDI, composed of physicochemical, microbiological, and sensory analysis) to signify the quality of the packaged dry-cured sausages . The R2 of calibration and validation produced by PLSR can achieve 0.99 and 0.96, respectively. The lower sample amounts may attribute to the low R2 values. It seems that only adhesion may comparably fit the PLSR model according to the R2 and RMSE values. As the hardness and springiness showed very low Rv2 values and high RMSEV, only gumminess and adhesion were chosen for the following important wavelength selection. 3.4. Calibration Model Using Important Wavelengths The gumminess of sausage refers to its texture, specifically the degree to which it is chewy or rubbery. A total of ten different important wavelengths were chosen for gumminess (395, 405, 445, 580, 645, 795, 965, 1000, 1075 and 1095 nm) and adhesion (395, 400, 455, 465, 510, 905, 975, 1025, 1065 and 1070 nm) using regression coefficients . The gumminess of sausage is defined as the energy required to chew semi-solid food until it can be swallowed, which is also influenced by a combination of factors, including the meat composition, casing, cooking temperature, mixing and grinding, additives, and pH level. Similar to adhesion, different casing treatments, and pH level evaluations may again attribute to the different gumminess values in the current study. Table 6 shows the predictive ability of the newly created models using the selected important wavelengths. If the accuracy of the new models at selected important wavelengths can be equivalent to that with full wavelengths, it provides useful information for the multispectral imaging system for real-time monitoring of the textural attributes of sausages core with different modified casings. As depicted in Table 6, the Rc2 value (0.5301) of gumminess improved slightly at the reduced model compared to the model using full wavelengths (0.4128). The Rv2 value of gumminess cannot be performed with 2nd derivative treatment in the model with full wavelengths, while it can be performed using the reduced model. This may be due to the noise and pixel outliers' removal. As for the adhesion, the prediction ability degraded using the selected wavelengths, but the models are simplified by lessening the full wavelengths. 4. Conclusions In the current study, a hyperspectral imaging system was tested to investigate the probability of evaluating the textural properties of sausage core after 16 days of cold room storage. Sausage cores with treatment 11 modified casing were softer than that with treatment 32 modified casing sausage. Sausages with a treatment of five modified casings showed significantly higher adhesion than those treated by treatment of 12. Response surface methodology was capable to elucidate the relationship between different modification processing added with different concentrations of orange extracts and adhesion, with R2 of 77.57% and insignificant lack of fit. Ten important wavelengths were chosen for gumminess and adhesion, respectively, which provide useful information for a simple costless multispectral system development. This study shows how sausage textural properties respond to the different types of casing modification after adding the orange extracts, which could also be of practical use for future casing manufacturing. Acknowledgments The authors thank the anonymous reviewers for their constructive comments. Author Contributions C.-H.F.: Conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing--original draft preparation, writing--review and editing, visualization, project administration, and funding acquisition. H.A.: investigation, writing--original draft preparation, writing--review and editing, visualization, supervision, project administration, and funding acquisition. F.J.R.-P.: methodology, software, validation, formal analysis, investigation, data curation, writing--original draft preparation, writing--review and editing, and visualization. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Data are contained within this article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Adhesion of the sausage cores with modified casings as affected by orange extracts additions and concentration of soy lecithin. (a) two-dimensional contour plot; (b) three-dimensional surface plot. Figure 2 Mean reflectance spectral profiles of sausage cores with different casing treatments (i.e., different legend numbers) in the spectral range of 390-1100 nm. Figure 3 Selection of the important wavelengths for gumminess (a) and adhesion (b) from the PLSR model. foods-12-01069-t001_Table 1 Table 1 Coded and uncoded physical values of operational parameters used in the CCD. Point Symbol Coded (Xi) Variable Level Star Low Center High Star -2 -1 0 1 2 SL concentration 1 X1 1:90 1:45 1:30 1:22.5 1:18 SO concentration (%, w/w) X2 0.625 1.25 1.875 2.5 3.125 RT (min) X3 45 60 75 90 105 OE (%, w/w) X4 0 0.12 0.26 0.4 0.54 LA (mL/kg NaCl) X5 16.5 18 19.5 21 22.5 Note: SL: soy lecithin, SO: soy oil, RT: residence time, OE: orange extracts, LA: lactic acid. 1 SL: distilled water (w/w). foods-12-01069-t002_Table 2 Table 2 Matrix of central composite design for each combination. Samples Surfactant Solution with OE Salt with LA SL Concentration (X1, w/w) b SO Concentration (X2, %, w/w) RT (X3, min) OE (X4, %, w/w) LA (mL/kg NaCl, X5) RT (X3, min) 1 a 1:30 1.875 75 0.26 19.50 75 2 1:30 1.875 75 0.26 22.50 75 3 1:22.5 1.250 90 0.40 18.00 90 4 1:30 1.875 75 0.26 16.50 75 5 1:45 2.500 90 0.12 21.00 90 6 a 1:30 1.875 75 0.26 19.50 75 7 1:45 2.500 60 0.40 21.00 60 8 1:90 1.875 75 0.26 19.50 75 9 1:30 1.875 105 0.26 19.50 105 10 1:30 1.875 45 0.26 19.50 45 11 a 1:30 1.875 75 0.26 19.50 75 12 1:45 1.250 90 0.40 21.00 90 13 1:22.5 2.500 60 0.12 21.00 60 14 1:22.5 2.500 60 0.40 18.00 60 15 1:22.5 1.250 60 0.40 21.00 60 16 1:45 1.250 90 0.12 18.00 90 17 1:30 3.125 75 0.26 19.50 75 18 1:22.5 1.250 90 0.12 21.00 90 19 1:45 1.250 60 0.12 21.00 60 20 1:22.5 2.500 90 0.40 21.00 90 21 1:45 1.250 60 0.40 18.00 60 22 1:22.5 1.250 60 0.12 18.00 60 23 1:30 1.875 75 0.53 19.50 75 24 1:18 1.875 75 0.26 19.50 75 25 1:45 2.500 90 0.40 18.00 90 26 a 1:30 1.875 75 0.26 19.50 75 27 1:22.5 2.500 90 0.12 18.00 90 28 a 1:30 1.875 75 0.26 19.50 75 29 a 1:30 1.875 75 0.26 19.50 75 30 1:45 2.500 60 0.12 18.00 60 31 1:30 1.875 75 0.00 19.50 75 32 1:30 0.625 75 0.26 19.50 75 Note: a Central points; b SL: distilled water (w/w), SL: soy lecithin, SO: soy oil, RT: residence time, OE: orange extracts, LA: lactic acid. foods-12-01069-t003_Table 3 Table 3 Linear, quadratic, and interaction of the response variables of textural attributes. Analysis of Variance Df Response Variables Hardness (Yh) Springiness (Ys) Gumminess (Yg) Adhesion (Ya) Source Adj SS F-Value Adj SS F-Value Adj SS F-Value Adj SS F-Value Model 20 2195.12 0.87 0.52324 0.44 1.38276 1.29 2.19927 1.90 Linear 5 261.61 0.42 0.0711 0.24 0.17593 0.65 0.3688 1.28 Soy lecithin (X1) 1 10.34 0.08 0.00279 0.05 0.00831 0.15 0.10545 1.82 Soy oil (X2) 1 51.58 0.41 0.02982 0.50 0.00073 0.01 0.22761 3.94 Residence time (X3) 1 90.29 0.72 0.00156 0.03 0.01124 0.21 0.00472 0.08 Addition of orange extracts (X4) 1 54.83 0.44 0.03693 0.62 0.03286 0.61 0.0276 0.48 Lactic acid (X5) 1 54.57 0.43 0.00001 0.00 0.12279 2.28 0.00342 0.06 Square 5 759.30 1.21 0.33969 1.14 0.56663 2.11 0.74679 2.58 X12 1 92.41 0.74 0.03333 0.56 0.16329 3.04 0.21651 3.74 X22 1 523.37 4.17 0.07666 1.28 0.1684 3.13 0.08971 1.55 X32 1 175.70 1.40 0.00137 0.02 0.01316 0.24 0.00012 0.00 X42 1 113.35 0.90 0.14656 2.45 0.12764 2.37 0.22977 3.97 X52 1 3.66 0.03 0.08727 1.46 0.08375 1.56 0.18835 3.26 2-Way Interaction 10 1174.21 0.94 0.11245 0.19 0.6402 1.19 1.08368 1.87 X1 x X2 1 50.52 0.40 0.00671 0.11 0.18471 3.44 0.00277 0.05 X1 x X3 1 81.41 0.65 0.00776 0.13 0.00134 0.02 0.24642 4.26 X1 x X4 1 550.21 4.39 0.00053 0.01 0.12008 2.23 0.34024 5.88 * X1 x X5 1 36.25 0.29 0.03108 0.52 0.00096 0.02 0.00082 0.01 X2 x X3 1 56.47 0.45 0.04032 0.67 0.12035 2.24 0.06547 1.13 X2 x X4 1 89.04 0.71 0.01603 0.27 0.00143 0.03 0.00024 0.00 X2 x X5 1 116.42 0.93 0.00007 0.00 0.01488 0.28 0.23318 4.03 X3 x X4 1 0.41 0.00 0.00459 0.08 0.09796 1.82 0.088 1.52 X3 x X5 1 0.00 0.00 0.00083 0.01 0.00091 0.02 0.03097 0.54 X4 x X5 1 193.48 1.54 0.00453 0.08 0.09758 1.82 0.07558 1.31 Error 11 1380.02 0.65748 0.59121 0.63611 Lack of Fit 6 1058.46 2.74 0.31435 0.76 0.22919 0.53 0.34281 0.97 Pure Error 5 321.56 0.34313 0.36202 0.2933 R2 (%) 61.40 44.32 70.05 77.57 Note: the value marked with * means significant at p < 0.05, and values with no mark mean not significant (p > 0.05). Df: degree of freedom. Adj SS: adjust sum of squares. foods-12-01069-t004_Table 4 Table 4 Textural properties of sausage core with different modified casing treatments. Sample Hardness (N) Springiness (mm) Gumminess (N) Adhesion (N s) 1 65.25 +- 18.75 ab 0.51 +- 0.02 a 0.97 +- 0.05 a -1.14 +- 0.01 abcdefg 2 66.47 +- 7.42 ab 0.53 +- 0.05 a 0.54 +- 0.00 a -1.19 +- 0.17 abcdefg 3 47.31 +- 10.05 ab 0.96 +- 0.76 a 0.59 +- 0.59 a -0.87 +- 0.32 abcdefg 4 58.06 +- 1.67 ab 0.48 +- 0.07 a 0.98 +- 0.04 a -1.36 +- 0.06 bcdefg 5 44.00 +- 12.58 b 0.48 +- 0.03 a 0.54 +- 0.05 a -1.51 +- 0.03 fg 6 43.59 +- 11.75 b 1.19 +- 0.44 a 0.20 +- 0.04 a -0.79 +- 0.08 abcdefg 7 66.84 +- 4.37 ab 0.51 +- 0.07 a 0.68 +- 0.37 a -0.93 +- 0.16 abcdefg 8 79.66 +- 1.13 ab 1.06 +- 0.62 a 0.19 +- 0.04 a -0.51 +- 0.07 abcdefg 9 78.96 +- 5.79 ab 0.51 +- 0.06 a 0.92 +- 0.06 a -1.18 +- 0.11 abcd 10 62.32 +- 8.90 ab 0.98 +- 0.20 a 0.34 +- 0.17 a -0.75 +- 0.47 abcdefg 11 45.67 +- 5.69 b 0.70 +- 0.38 a 0.57 +- 0.26 a -0.94 +- 0.04 abcdefg 12 68.94 +- 14.13 ab 0.76 +- 0.27 a 0.17 +- 0.04 a -0.44 +- 0.02 a 13 60.46 +- 4.33 ab 0.44 +- 0.03 a 0.31 +- 0.13 a -1.36 +- 0.57 defg 14 54.05 +- 6.19 ab 0.52 +- 0.02 a 0.55 +- 0.04 a -1.50 +- 0.26 g 15 62.99 +- 2.94 ab 0.50 +- 0.02 a 0.68 +- 0.37 a -0.97 +- 0.11 abcdefg 16 57.13 +- 11.36 ab 0.49 +- 0.06 a 0.76 +- 0.03 a -1.04 +- 0.14 abcdefg 17 71.07 +- 12.90 ab 0.51 +- 0.22 a 0.17 +- 0.04 a -0.80 +- 0.31 abcdefg 18 74.55 +- 5.38 ab 0.66 +- 0.25 a 0.47 +- 0.37 a -0.74 +- 0.10 abcdefg 19 61.27 +- 13.01 ab 0.44 +- 0.02 a 0.15 +- 0.08 a -0.65 +- 0.20 abcd 20 70.65 +- 14.63 ab 0.50 +- 0.00 a 0.25 +- 0.02 a -0.99 +- 0.17 abcdefg 21 64.11 +- 10.55 ab 0.48 +- 0.03 a 0.23 +- 0.02 a -0.65 +- 0.19 abcdefg 22 67.95 +- 7.68 ab 0.47 +- 0.02 a 0.54 +- 0.33 a -0.90 +- 0.20 abcdefg 23 77.12 +- 11.28 ab 0.48 +- 0.02 a 0.22 +- 0.04 a -0.58 +- 0.04 abcd 24 56.24 +- 21.73 ab 0.66 +- 0.07 a 0.30 +- 0.08 a -0.71 +- 0.30 abcdefg 25 66.46 +- 7.29 ab 0.51 +- 0.02 a 0.19 +- 0.02 a -0.56 +- 0.06 ab 26 52.61 +- 4.10 ab 0.49 +- 0.10 a 0.40 +- 0.04 a -1.23 +- 0.15 abcdefg 27 77.62 +- 1.73 ab 0.57 +- 0.04 a 0.38 +- 0.12 a -0.55 +- 0.03 abcdefg 28 58.14 +- 10.65 ab 0.54 +- 0.10 a 0.75 +- 0.30 a -1.38 +- 0.01 abcd 29 51.25 +- 1.80 ab 0.67 +- 0.26 a 0.67 +- 0.05 a -0.80 +- 0.30 cdefg 30 55.71 +- 8.72 ab 0.42 +- 0.01 a 0.84 +- 0.11 a -0.92 +- 0.31 abcdefg 31 60.31 +- 3.82 ab 0.39 +- 0.03 a 0.34 +- 0.39 a -0.61 +- 0.13 abcd 32 84.43 +- 1.01 a 0.52 +- 0.06 a 0.31 +- 0.12 a -0.66 +- 0.25 abcdefg Control 64.47 +- 2.57 ab 0.46 +- 0.02 a 0.66 +- 0.60 a -1.52 +- 0.38 efg Note: values marked with different letters in a same column mean a significant difference (p < 0.05). foods-12-01069-t005_Table 5 Table 5 Calibration and validation statistics for predicting textural attributes of sausage core using PLSR with full wavelengths range. Parameters Raw Normalization 1st Derivative 2nd Derivative SNV MSC Hardness (N) Calibration group Rc2 0.6840 0.4760 0.4183 0.5772 0.4557 0.4552 RMSEC (%) 7.0092 9.0264 9.5102 8.1079 9.2000 9.2039 Validation group Rv2 Na Na Na Na Na Na RMSEV (%) 9.5719 6.8142 5.6889 6.4465 6.1000 6.0803 Springiness Calibration group Rc2 0.2083 0.9820 0.1485 0.2955 0.2653 0.2609 RMSEC (%) 0.1782 0.2685 0.1848 0.1681 0.1716 0.1721 Validation group Rv2 0.1785 0.2859 0.1267 Na 0.2014 0.1917 RMSEV (%) 0.1615 0.1506 0.1666 0.2060 0.1593 0.1602 Gumminess (N) Calibration group Rc2 0.4128 0.4005 0.9994 0.3245 0.6210 0.5919 RMSEC (%) 0.1679 0.1697 0.0052 0.1801 0.1349 0.1400 Validation group Rv2 0.3908 0.3462 0.1397 Na 0.5042 0.5091 RMSEV (%) 0.2359 0.2444 0.2803 0.3360 0.2128 0.2117 Adhesion (N s) Calibration group Rv2 0.8591 0.8494 0.9999 0.4825 0.8744 0.8451 RMSEC (%) 0.1189 0.1229 0.0030 0.2279 0.1123 0.1247 Validation group Rv2 0.5556 0.5742 0.3370 0.1706 0.6837 0.5949 RMSEV (%) 0.2249 0.1964 0.2451 0.2742 0.1693 0.1916 Note: SNV: standard normal variate; MSC: multiplicative scatter correction; RMSEC: the root mean square error of calibration; RMSEV: the root mean square error of validation. foods-12-01069-t006_Table 6 Table 6 Calibration and validation statistics for predicting textural attributes of sausage core using PLSR with selected important wavelengths range. Parameters Raw Normalization 1st Derivative 2nd Derivative SNV MSC Gumminess (N) Calibration group Rc2 0.5301 0.4807 0.5063 0.5450 0.4984 0.4892 RMSEC (%) 0.1502 0.1579 0.1540 0.1478 0.1552 0.1557 Validation group RV2 0.3620 0.4228 0.3862 0.3731 0.4354 0.4417 RMSEV (%) 0.2414 0.2296 0.2368 0.2393 0.2271 0.2258 Adhesion (N s) Calibration group Rc2 0.7746 0.7530 0.6877 0.7042 0.7311 0.6665 RMSEC (%) 0.1504 0.1574 0.1770 0.1723 0.1643 0.1829 Validation group RV2 0.4427 0.4748 0.5440 0.3765 0.5248 0.4877 RMSEV (%) 0.2247 0.2182 0.2033 0.2377 0.2075 0.2155 Note: SNV: standard normal variate; MSC: multiplicative scatter correction; RMSEC: the root mean square error of calibration; RMSEV: the root mean square error of validation. 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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PMC10000444 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050730 healthcare-11-00730 Article Prevalence of Malnutrition in Hospitalized Patients in Lebanon Using Nutrition Risk Screening (NRS-2002) and Global Leadership Initiative on Malnutrition (GLIM) Criteria and Its Association with Length of Stay Ouaijan Krystel 12 Hwalla Nahla 3 Kandala Ngianga-Bakwin 45 Mpinga Emmanuel Kabengele 2* Roberts Shelley Academic Editor 1 Department of Clinical Nutrition, Saint George Hospital University Medical Center, Beirut 11002807, Lebanon 2 Institute of Global Health, University of Geneva, 1211 Geneva, Switzerland 3 Department of Nutrition and Food Sciences, American University of Beirut, Beirut 11072020, Lebanon 4 Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 3K7, Canada 5 Division of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg 2000, South Africa * Correspondence: [email protected] 02 3 2023 3 2023 11 5 73028 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 ). (1) Background: Prevalence studies on hospital malnutrition are still scarce in the Middle East region despite recent global recognition of clinical malnutrition as a healthcare priority. The aim of this study is to measure the prevalence of malnutrition in adult hospitalized patients in Lebanon using the newly developed Global Leadership Initiative on Malnutrition tool (GLIM), and explore the association between malnutrition and the length of hospital stay (LOS) as a clinical outcome. (2) Methods: A representative cross-sectional sample of hospitalized patients was selected from a random sample of hospitals in the five districts in Lebanon. Malnutrition was screened and assessed using the Nutrition Risk Screening tool (NRS-2002) and GLIM criteria. Mid-upper arm muscle circumference (MUAC) and handgrip strength were used to measure and assess muscle mass. Length of stay was recorded upon discharge. (3) Results: A total of 343 adult patients were enrolled in this study. The prevalence of malnutrition risk according to NRS-2002 was 31.2%, and the prevalence of malnutrition according to the GLIM criteria was 35.6%. The most frequent malnutrition-associated criteria were weight loss and low food intake. Malnourished patients had a significantly longer LOS compared to patients with adequate nutritional status (11 days versus 4 days). Handgrip strength and MUAC measurements were negatively correlated with the length of hospital stay. (4) Conclusion and recommendations: the study documented the valid and practical use of GLIM for assessing the prevalence and magnitude of malnutrition in hospitalized patients in Lebanon, and highlighted the need for evidence-based interventions to address the underlying causes of malnutrition in Lebanese hospitals. malnutrition nutrition assessment nutrition screening Global Leadership Initiative on Malnutrition (GLIM) Nutrition Risk Screening 2002 (NRS-2002) handgrip strength mid-upper arm muscle circumference (MUAC) length of hospital stay (LOS) Dietitians in Nutrition Support--DNS--Academy of Nutrition and Dietetics104037 This research study was partially funded by Dietitians in Nutrition Support--DNS--Academy of Nutrition and Dietetics in the United States, grant number 104037. pmc1. Introduction Nutritional risk and malnutrition are highly prevalent in hospitalized patients , and have been reported to range from 20 to 50% in different European and South American countries with an average of 41.7% worldwide . There is abundant evidence that malnutrition is associated with increased morbidity, nosocomial infections and hospital readmission . Recent studies have also demonstrated that malnutrition is associated with prolonged length of stay (LOS) in patients with acute illness or even chronic non-communicable diseases . Consequently, malnutrition is identified as a major encumbrance for hospitalized patients and a driver of increased healthcare cost incurring a considerable economic burden, accounting for 2.1 and 10% of the national health expenditures in Europe . Nevertheless, malnutrition is still not addressed as a serious clinical problem due to the lack of clearly defined responsibilities and lack of unequivocally universally accepted diagnostic criteria . Global efforts are being launched as well as a call to action to implement mandatory screening, establish a diagnostic code and develop national protocols to position nutrition as a healthcare priority . Recently, the Global Leadership Initiative on Malnutrition (GLIM) has established a consensus for the diagnosis of malnutrition based on a combination of phenotypic and etiologic criteria and proposed it as a new tool to be validated in the disease-afflicted hospitalized population . In the Middle East region, initiatives to study the prevalence of malnutrition in hospitals have been modest, with Turkey recently publishing a rate of 39% . An international multicenter study published in 2008 has reported a lower rate of 22% of risk of malnutrition in two Lebanese hospitals . Other prevalence studies in Lebanon have focused only on the rate of malnutrition in the community settings, with reported rates of 61.3% malnutrition and a risk of malnutrition in older adults living in long-term care centers and lower rates of 48.3% in older adults living in their homes . Context of the Study Lebanon is a small country of the Middle East region covering an area of 10,452 km2 and having borders with both Syria and Israel, considered to be a conflict area. The country is divided into five main districts: north, Mount Lebanon, south, Bekaa Valley and the capital Beirut and its suburbs. In 2015, the population was estimated to be 6,847,712, including Lebanese people, foreign workers and refugees . The highest population density is seen in Beirut and its suburbs. The south, north and Bekaa have the highest number of rural small villages. Lebanon has one hundred and forty-four hospitals comprising 11742 beds, of which 78.3% are private and 21.7% are public. The number of beds is distributed as follows: 3806 (32.4%) in Mount Lebanon, 2452 in Beirut (20.9%), 1931 (16.4%) in the south, 1852 (15.8%) in the north and 1701 (14.5%) in Bekaa. The annual hospital admission is declared to be 698,210 cases per year, with the highest percentages in Beirut and Mount Lebanon, 22.3% and 29.6%, respectively . According to the World Bank, the gross domestic product was estimated at USD 23.1 billion in 2021 compared to USD 52 billion in 2019. The drop in GDP per capita was a drastic 36.5% in just two years and Lebanon was reclassified as a lower-middle-income country instead of an upper-middle-income country. These drastic changes have resulted in difficulties in the cost of medical treatments and health coverage, which relies both on National Social Security and private insurances . The aim of this study was to determine the prevalence of malnutrition in Lebanese hospitals by using the newly proposed GLIM tool, and to explore its different criteria and their relationship with length of stay, an easily measurable outcome parameter that is directly related to hospital costs . The findings of this study will be the first milestone to establish a national policy mandating nutritional screening and assessment in all hospitalized patients. They can also guide the authority in forming a surveillance system and evaluating strategies targeted at decreasing the rate of malnutrition in hospitals. 2. Materials and Methods 2.1. Design and Sample Size The study is a cross-sectional, observational, multicenter study. The sample size was estimated as 330 hospitalized patients to achieve a 95% confidence interval with a margin of error of 0.05 and 100% expected response rate based on using the STEPS sample size calculator of WHO and on the number of yearly hospital admissions . It was calculated considering a significance level of 5% with 80% power. The number of patients in a random sample of hospitals in the five districts of Lebanon was weighed against the number of admissions per district from the National Health Survey . The distribution of samples according to districts to have a national representation is presented in Figure 1. Private hospitals were only included due to the restricted access to the public hospitals in the period of data collection. All adult patients, males and females aged 18 years and above, admitted to the different wards of the hospital during the period of data collection were recruited within 48 h of admission. Exclusion criteria included the following wards: gynecology (including all pregnant and lactating women), intensive care unit, psychiatry and short stay of less than 48 h. 2.2. Data Collection Patient characteristics, i.e., age, gender, admission diagnosis, history of previous admissions, underlying diseases and number of home medications, were recorded. Patients were interviewed for history of weight loss, appetite and record of food intake. C-reactive protein levels (CRPs) were retrieved from the available blood tests from patients' records. The length of hospital stay was calculated from the date of admission to the date of discharge. Body weight and height were measured using the Detecto manual scale to the nearest 1 kg and 1 cm, respectively. BMI (weight kg/height m2) was calculated accordingly. Mid-upper arm muscle circumference (MUAC) was measured at the midpoint between the acromion and olecranon processes at the non-dominant arm using a non-stretchable tape measure to the nearest 0.1 cm. The MUAC was categorized into three groups: "normal", "moderately depleted" for measurements <23 cm and "severely depleted" for those <20 cm . Handgrip strength was measured with the non-dominant hand using the Saehan hydraulic hand dynamometer to the nearest 0.1 kg. The handgrip strength variable was categorized into two groups: "normal" and "low" accounting for the gender cut-off points being <27 kg and <16 kg for males and females, respectively . 2.3. Nutritional Status The Nutrition Risk Screening (NRS-2002) tool was used for nutritional screening, followed by an evaluation of malnutrition using the GLIM criteria. NRS is a two-step tool consisting of evaluating BMI, assessing recent weight loss and changes in food intake and identifying a grading of severity of disease as a reflection of increased nutritional requirements. Patients with a total score of 3 or more in the final screening were nutritionally at risk . GLIM diagnosis was performed as a two-step process by firstly identifying at least one phenotypic criterion and one etiologic criterion and secondly assessing the severity of malnutrition as being either "moderate" or "severe" based on the phenotypic criterion . Weight loss and BMI were used to evaluate the phenotypic criteria. The third phenotypic criterion evaluated was muscle mass, using MUAC as the measurement and handgrip strength as the supportive measure. MUAC was used as a surrogate technique as endorsed in recent recommendations in usual situations where body composition techniques such as bioelectrical impedance analysis and dual-energy X-ray absorptiometry are not available in the hospitals . GLIM criteria emphasize that handgrip strength should be used as an additional supportive measure when only anthropometric measurements are available . Handgrip strength is commonly employed in practice to assess muscle function qualitatively . Reduced food intake, chronic gastrointestinal condition affecting absorption and inflammatory condition assessed via CRP levels were the etiologic criteria. Cut-off points of the different etiologic and phenotypic criteria are described in Table 1. 2.4. Statistical Analysis Statistical analysis was performed using STATA V17.1. Descriptive variables were described as n (%), mean +- standard deviation (SD) and median +- interquartile range (IQR). Cohen's kappa (k) was conducted to assess the agreement between NRS 2002 and GLIM. The length of hospital stay variable was then dichotomized into two groups with the median of 5 days used as the cut-off point: group one: <=5 days and group two: >5 days. Mann-Whitney U and kh2 tests were performed to assess the differences in the length of hospital stay and history of hospital readmissions between the malnourished patients and those of normal nutritional status. Spearman's rank correlations coefficient (rho) was used to measure the association between the non-parametric variables of length of hospital stay, handgrip strength and MUAC. Multiple logistic regression analysis was used to determine whether malnutrition with the GLIM criteria was independently associated with length of stay with adjustments for gender and admission diagnosis. All reported p-values were to a significance level of 5%. 2.5. Ethics The study was completed in compliance with the guidelines of the Helsinki Declaration. The study protocol was reviewed and approved by the Institutional Review Board of the American University of Beirut (SBS-2020-0079). All participants reviewed and signed an informed consent form before participation. 3. Results 3.1. Basic Characteristic A total of 343 participants were enrolled in this study from May to October 2021. Baseline characteristics and distribution among districts are presented in Table 2. The mean age was 60 years (SD: 17 years) and the majority of the participants were less than 70 years old (65.89%). Surgical procedures (32.94%) and infectious diseases (27.7%) were the main diagnostic criteria for hospital admissions. 3.2. Prevalence of Malnutrition According to the NRS-2002 screening tool (Table 3), 31.20% of the participants had scores that were greater than or equal to 3 and thus were identified as being "at risk of malnutrition", of which 51% were males and 49% were females. Beirut (38.27%) followed by the north (38.00%) and Mount Lebanon (33.00%) were the main districts identified by NRS-2002 as having participants at risk. The south had the lowest proportion (18.97%) compared to Beirut and the result was statistically significant (p = 0.016). As for GLIM, 21.28% and 14.29% were identified as being "moderately" and "severely" malnourished, respectively, accounting for a total of 35.57% malnourished participants (Table 3). Half of the malnourished patients were male and the same proportion was female. Similarly to the NRS-2002 results identifying patients at risk of malnutrition, Beirut (43.21%), the north (42.00%) and Mount Lebanon (34.00%) were the main districts with malnourished participants . Bekaa had the lowest proportion (25.93%) compared to Beirut and the result was statistically significant (p = 0.043). The strength of the agreement between NRS 2002 and GLIM in identifying at-risk-of-malnutrition and malnourished patients as per Cohen's kappa k was 0.7580 (p < 0.001), indicative of good agreement. 3.3. Frequency of the Different GLIM Criteria The frequencies of the different GLIM criteria among malnourished patients are described in Figure 3. Among the 122 patients who were identified as "moderately" and "severely" malnourished according to GLIM, the most dominant phenotypic criterion was "weight loss", accounting for 82%. The median weight loss percentage was 8.5 kg (IQR 6.25-10). As for the etiologic criterion, the most prominent was "reduced food intake" accounting for 88% of patients, among which reduction in food intake for a period exceeding 2 weeks was the main measure (41.8%). The number of patients with low handgrip strength was 92 (75.4%). The mean handgrip strength of the males was 19.59 kg (SD = 4.28), whereas that of the females was 12.61 kg (SD= 2.44). As for the MUAC, 32 patients were identified as being moderately depleted (26.2%) and 10 patients were identified as being severely depleted (8.2%), a total of 42 patients (34.4%). The mean MUAC was 21.56 cm (SD = 0.7) and 20.2 (SD = 2.8) for males and females, respectively. More than half of the moderately malnourished patients had normal BMIs (54.9%). 3.4. Association of Malnutrition, Muscle Mass and Length of Hospital Stay The patients' median length of hospital stay was 5 days (IQR 3-10). There was a significant difference in the length of hospital stay between patients identified as malnourished according to GLIM criteria and those of normal nutritional status (11 days with IQR 9-15 versus 4 days with IQR 3-5, respectively, p < 0.001). When a median of 5 days was considered as the cut-off point, 90.9% of malnourished patients had a length of hospital stay greater than 5 days compared to 9.1% of patients of normal nutritional status, as shown in Table 4 (p < 0.001). Handgrip strength and MUAC measurements were negatively correlated with the length of hospital stay (rho/r = -0.40, p < 0.001 and rho/r = -0.25, p < 0.001), regardless of the patient's nutritional status. Patients with low handgrip strength measurements had a length of hospital stay greater than the median of 5 days (74.4% versus 25.6%, p < 0.001). As for patients with moderate and severe depletion in MUAC measurements, 84.4% had a length of hospital stay greater than the median (84.4% versus 15.6%, p < 0.001) (Table 4). 3.5. Multiple Logistic Regression of Length of Hospital Stay Having a malnutrition diagnosis was found to be an independent predictor of length of hospital stay, as shown in Table 5. Specifically, patients who were identified as malnourished according to GLIM criteria (p < 0.001) had higher odds of having a length of hospital stay that exceeded 5 days compared to those who were well-nourished. Age was excluded from the model because it was part of the malnutrition diagnosis. The Hosmer and Lemeshow goodness-of-fit test indicated that our model fit the data well with p-values of 0.2364. 3.6. Association of Malnutrition with Hospital Readmission Patients who were identified as being malnourished according to GLIM criteria (33.61%) were more likely to have been previously admitted to the hospital in the past 3 months compared to those identified as having a normal nutritional status (3.17%) (kh2 = 60.51, p < 0.001). 4. Discussion The prevalence rate of malnutrition risk among hospitalized patients was 31.2% according to NRS-2002 and the prevalence of malnutrition according to the GLIM criteria was 35.6%. These figures is different from previous data collected in 2008 in two large Lebanese hospitals of the international multicenter study, where malnutrition risk was only screened and the rate was 22% using the NRS-2002 tool . In addition to the fact that our data are larger and more hospitals were included, this difference in rate reflects the increase in the risk of malnutrition in hospitalized patients in a country where economic crisis has drastically deteriorated. This crisis is affecting the access to and availability of nutrition care in hospitals . The higher percentage of malnutrition according to GLIM was detected in the capital Beirut (43.2%), where hospitals are larger and more complicated cases are admitted. A lower prevalence of 26% was observed, on the other hand, in Bekaa where the population density is much lower . The prevalence in the five districts is very similar to the rates reported in other countries, varying from 20% to 50% with higher ranges in developing countries . One other recent study restricted to one hospital in Lebanon with a smaller sample size reported that 34.7% of their sample population was at risk of malnutrition and 9.3% were malnourished . Although the percentage of at-risk patients is high, their lower rate of malnutrition is probably due to the use of a different tool, which was the Mini Nutritional Assessment MNA, specific to older adults . The prevalence of risk of malnutrition when using NRS-2002 was slightly lower than the prevalence rate of the malnutrition diagnosis using GLIM criteria, reporting a rate of 31.2%. However, there was a good agreement statistically between the two tools. This concordance was also recently reported in a study on hospitalized patients in Turkey, where GLIM was correlated with NRS-2002 and not with other nutrition assessment tools . Other studies have found a stronger correlation between GLIM and other screening tools such as the Malnutrition Universal Screening Tool (MUST), but the sample population was of older adults and those specifically having cancer . Therefore, NRS-2002 is still considered to be a valid and more specific tool to be used for hospitalized patients during the screening process as recommended by clinical practice guidelines . GLIM is considered to be a diagnostic tool to be used after screening to confirm nutritional assessment. It is different from other assessment tools as it has many different criteria and severity levels. In our study, we have studied the frequency of each phenotypic and etiologic criterion in patients diagnosed with moderate and severe malnutrition. The most frequent criteria were weight loss and low food intake, which are quick and easy to collect. This same combination of weight loss and low food intake was observed in a study on the validation of GLIM and was considered to be the most predictive with regard to worse clinical outcomes . On the other hand, low BMI in our sample population was the least recorded criterion, with 16% compared to 88% for weight loss and 57% for low muscle mass. More than half of malnourished patients had a normal BMI, reemphasizing the importance of not relying solely on BMI in nutrition assessment, an issue always challenged by clinicians . Patients identified as malnourished by GLIM had a significantly longer length of stay (LOS) of 7 days and had significantly higher rates of previous hospital readmissions. Both LOS and the incidence of hospital readmissions are surrogate markers of a patient's clinical outcomes and economical costs . This strong correlation associates malnutrition with unexpected complications and a worsening clinical status of patients, highlighting the importance of identifying malnutrition early during hospitalization. The prediction model identifying malnutrition diagnosis as a predictor of length of stay independent of underlying diseases reinforced the association of malnutrition with worsening clinical outcomes. It demonstrates the validity of GLIM criteria to predict prolonged hospitalization as a health outcome . Interestingly, a correlation with LOS was also found in our study with low MUAC and handgrip strength, independently of nutritional status. Handgrip strength has previously been linked to longer hospitalization but MUAC has never been studied from this perspective since it is commonly more used in the pediatric population . Our findings may help in adding simple anthropometric measurements not requiring expensive tools such as MUAC in assessing muscle mass as part of GLIM criteria when body impedance analysis (BIA) or dual-energy X-ray absorptiometry DEXA are not available . Our study findings of high prevalence rates support the need for increasing awareness towards malnutrition, which many global efforts are now targeting. Consequently, the newly developed European Nutrition for Health Alliance has started the Optimal Nutritional Care for All (ONCA) campaign, which launched a global call for action in 2013 to all countries to raise public awareness, establish a nutrition assessment pathway and develop national protocols to include effective nutrition care as a fundamental right to heath . Other similar associations from different countries followed this path and launched an international call to action in a forum "Linking Nutrition Around the World" . In addition, the United Nations Decade of Action on Nutrition emphasized that national policies should prioritize aligned health systems providing universal coverage of all essential nutrition actions . Lebanon and other countries in the Middle East have not joined these global efforts yet. However, a national policy, supported by international instruments, is becoming a necessity to identify and target malnutrition, especially in the economic crisis that the country is going through. It is important to mention that initiatives and policies targeting malnutrition should recognize the crucial role of dietitians in the nutrition care of the patient . Clinical dietitians are integral members of the multidisciplinary team in the hospitals and they are uniquely qualified in the assessment and the management of malnutrition in the care pathway of the patients . They are specialized in interpreting anthropometric measurements, recommending nutrition support plans and providing informational counseling to patients . Their nutrition interventions will aim to improve the continuum of care of the hospitalized patients in enhancing clinical outcomes. Strength and Limitations To our knowledge, this is the first study to report the prevalence of malnutrition in hospitalized patients in a national representative sample of hospitals in Lebanon and is one of the very few studies in the Middle East. Nutrition screening and assessment were conducted upon admission in a heterogeneous population of different medical and surgical diagnoses, making our study different from other prevalence studies conducted retrospectively and on a specific patient population. The GLIM tool that is newly developed was also used with simple anthropometric measurements that could be easily found in settings with minimal resources. Our study nevertheless has limitations. Data were collected from private hospitals only and public hospitals were excluded due to security reasons, meaning that patients admitted to these hospitals of usually lower socioeconomic status were not represented. The cut-off values we used for MUAC and handgrip strength to assess muscle mass were taken from consensus recommendations and were not validated in different patient populations. We therefore recommend that future studies clarify their cut-off values. 5. Conclusions Our present study reports a considerable high prevalence of malnutrition in hospitalized patients upon admission that was directly associated with a longer length of stay, implicating worsening clinical outcomes. Since the identification of malnutrition remains an important first step to target its recognition and management in daily clinical practice, the use of GLIM criteria with simple, affordable and anthropometric measurements is considered to be both valid and a practical diagnosis step. Acknowledgments The authors would like to thank all of the hospitals that participated in the study: Saint George Hospital University Medical Center (Beirut), Sacre Coeur (Mount Lebanon), Monla Hospital (north), Raee Hospital (south) and Hopital Libano-Francais (Bekaa). The authors express tremendous gratitude to all clinical dietitians who facilitated the process of data collection. Author Contributions Conceptualization, E.K.M., K.O., N.H. and N.-B.K.; methodology, E.K.M. and K.O.; formal analysis, K.O.; writing--original draft preparation, K.O.; writing--review and editing, E.K.M., N.H. and N.-B.K.; supervision, E.K.M.; funding acquisition, K.O. and N.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was completed in compliance with the guidelines of the Helsinki Declaration. The study protocol was reviewed and approved by the Institutional Review Board of the American University of Beirut (SBS-2020-0079, approved on 15 February 2021) for studies involving humans. Informed Consent Statement Informed consent was obtained from all subjects or their caregivers involved in the study. Data Availability Statement Data are contained within the 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 the data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 Distribution of sample according to district representation. Figure 2 Distribution of malnutrition rates in the different districts according to Global Leadership Initiative on Malnutrition (GLIM). Figure 3 Frequencies of the phenotypic and etiologic criteria present in the malnourished patients as classified by the Global Leadership Initiative on Malnutrition (GLIM) (n = 122). healthcare-11-00730-t001_Table 1 Table 1 GLIM criteria for diagnosis of malnutrition . Phenotypic Criteria Etiologic Criteria Severity level Moderate Severe Weight loss >5-10% within past 6 months or 10-20% beyond 6 months >10% within past 6 months or >20% beyond 6 months Reduced food intake <50% of estimated needs in >1 week or any reduction for >2 weeks Low BMI <20 kg/m2 if <70 years, <22 kg/m2 if >=70 years <18.5 if <70 years, <20 if <70 years Any chronic GI condition that adversely impacts food assimilation or absorption Reduced muscle mass 2 MUAC 1 < 23 cm MUAC < 20 cm Inflammation Elevated C-reactive protein (CRP) levels 1 Mid-upper arm muscle circumference (MUAC). 2 Handgrip strength was used as the supportive measure as recommended. healthcare-11-00730-t002_Table 2 Table 2 Baseline characteristics of participants (N = 343). Characteristic N (%) Age <70 years old 226 (65.9%) >=70 years old 117 (34.11%) Gender Male 188 (54.81%) Female 155 (45.19%) District Beirut 81 (23.62%) North 50 (14.58%) South 58 (16.91%) Mount Lebanon 100 (29.15%) Bekaa Valley 54 (15.74%) Present illness Oncology 25 (7.29%) Cardiovascular disease 53 (15.45%) Infectious disease 95 (27.70%) Gastrointestinal disease 40 (11.66%) Surgical procedure 113 (32.4%) Other 17 (4.96%) Underlying disease None 87 (25.36%) Diabetes and cardiovascular diseases 192 (55.98%) Cancer 44 (12.83%) Neurological disorders 8 (2.33%) Gastrointestinal diseases 12 (3.50%) Home medications None 110 (32.07%) One medication 46 (13.41%) Two medications 46 (13.41%) Three or more medications 141 (41.11%) Previous hospital admission within 3 months Yes 48 (13.99%) No 295 (86.01%) healthcare-11-00730-t003_Table 3 Table 3 The prevalence of malnutrition according to Nutrition Risk Screening (NRS-2002) and Global Leadership Initiative on Malnutrition (GLIM) (N = 343). Prevalence Rate N (%) NRS-2002 Mild risk (<3) 236 (68.8%) At risk (>=3) 107 (31.2%) GLIM Normal nutritional status 221 (64.43%) Malnourished 122 (35.57%) Moderate malnutrition 73 (21.28%) Severe malnutrition 49 (14.29%) healthcare-11-00730-t004_Table 4 Table 4 Effect of various measurements of nutritional status on length of stay (LOS) greater than 5 days in Lebanese hospitals (n = 343). Nutritional Status Low Normal Nutritional status according to GLIM criteria 1 90.9% 9.1% Handgrip strength (HGS) 74.4% 25.6% Mid-upper arm muscle circumference (MUAC) 84.4% 15.6% 1 Global Leadership Initiative on Malnutrition. healthcare-11-00730-t005_Table 5 Table 5 Multiple logistic regression models for length of stay. Odds Ratio (OR) 95% CI for OR p-Value Underlying disease a Diabetes and cardiovascular diseases 0.97 0.31; 3.06 0.963 Cancer 1.50 0.31; 7.11 0.608 Other (neurological disorders and gastrointestinal diseases) 0.56 0.11; 2.87 0.489 Home medications b 1-2 1.67 0.56; 5.03 0.356 >=3 1.08 0.32; 3.67 0.894 Present illness c Oncology 5.00 0.86; 29.05 0.073 Cardiovascular disease 4.85 0.92; 25.68 0.063 Infectious disease 0.87 0.13; 5.78 0.889 Gastrointestinal disease 1.16 0.22; 5.97 0.854 Other 3.18 0.39; 25.58 0.276 Malnutrition diagnosis d Present 60.72 23.97; 153.78 <0.001 * a Reference group "none", b reference group "none", c reference group "none", d reference group "absent". * 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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PMC10000445 | Cancer metastasis is a main cause of failure in treating subjects with nasopharyngeal carcinoma (NPC) and is frequently linked to high death rates. EF-24, an analog of curcumin, has exhibited many anti-cancer properties and enhanced bioavailability over curcumin. Nevertheless, the effects of EF-24 on the invasiveness of NPC are poorly understood. In this study, we demonstrated that EF-24 effectively inhibited TPA-induced motility and invasion responses of human NPC cells but elicited very limited cytotoxicity. In addition, the TPA-induced activity and expression of matrix metalloproteinase-9 (MMP-9), a crucial mediator of cancer dissemination, were found to be reduced in EF-24-treated cells. Our reporter assays revealed that such a reduction in MMP-9 expression by EF-24 was transcriptionally mediated by NF-kB via impeding its nuclear translocation. Further chromatin immunoprecipitation assays displayed that the EF-24 treatment decreased the TPA-induced interaction of NF-kB with the MMP-9 promoter in NPC cells. Moreover, EF-24 inhibited the activation of JNK in TPA-treated NPC cells, and the treatment of EF-24 together with a JNK inhibitor showed a synergistic effect on suppressing TPA-induced invasion responses and MMP-9 activities in NPC cells. Taken together, our data demonstrated that EF-24 restrained the invasiveness of NPC cells through the transcriptional suppression of MMP-9 gene expression, implicating the usefulness of curcumin or its analogs in controlling the spread of NPC. nasopharyngeal carcinoma curcumin analog cancer metastasis matrix metalloproteinase-9 Chung Shan Medical University HospitalCSH-2022-E-002-Y3 This research was funded by grants from the Chung Shan Medical University Hospital (CSH-2022-E-002-Y3). pmc1. Introduction Nasopharyngeal carcinoma (NPC), a neoplasm originating in the part of the throat connecting the back of the nose to the back of the oral cavity, is particularly frequent in East and Southeast Asia . Apart from inherited factors and exposure to the Epstein-Barr virus (EBV), numerous environmental parameters related to unique ethnic practices and lifestyles (e.g., habitual use of tobacco products and preserved food) are known to be involved in the susceptibility to NPC . These predisposing factors over different geographical areas largely elucidate the high heterogeneity in the global prevalence, histologic classifications, and therapy outcomes for this cancer. At present, the main treatment for NPC is radiation therapy alone (for early-stage tumors) or combined chemo-radiotherapy (for advanced diseases). However, nearly 20% of patients receiving primary therapy still developed recurrent tumors or metastatic dissemination , which are usually resistant to the mainstay of treatment and linked to high death rates . Thus, improving our knowledge of the molecular basis of disseminated NPC is central to the development of new treatment options for ultimately alleviating this aggressive malignancy. Cancer cell invasion and metastasis are hallmarks of tumors that require malignant cells to move from the original site and propagate at a remote location . The metastatic dissemination of NPC comprises various molecular and cellular processes carried out by both malignant and non-malignant cells within the tumor microenvironment . These mechanisms involve the orchestration of signal cascades, the modulation of cell-matrix adhesion, the breakdown of the extracellular matrix (ECM) by matrix metalloproteinases (MMPs), cytoskeletal rearrangement, the induction of cell mobility and angiogenic responses, evading apoptosis, and an epithelial-mesenchymal transition (EMT). TPA (12-O-Tetradecanoylphorbol-13-acetate) is a phorbol ester commonly employed in biomedical studies to promote cancer dissemination, mainly through the activation of protein kinase C (PKC) . The impact of TPA-mediated PKC signaling on cancer metastasis has been well-documented in various cancer types [13,14,15,1613-16]. Curcumin, a polyphenol derived from the rhizome of Curcuma longa, exhibits many oncostatic properties in a myriad of tumors . However, the clinical use of this natural compound is largely restrained by its low solubility and poor bioavailability . To address these issues, efforts toward the development of curcumin derivatives and analogs were made to improve current cancer treatments . Among these synthetic analogs of curcumin, EF-24 demonstrated anti-cancer effects and displayed an enhanced bioavailability compared to curcumin . Mounting evidence has indicated that EF-24 has impeded cancer progression by employing multiple and interrelated mechanisms, such as the inhibition of NF-kB and MAPK signaling, the suppression of hypoxia-inducible factor-1a (HIF-1a) expression , glucose metabolism , and the regulation of reactive oxygen species (ROS) production . However, the impact of EF-24 on NPC metastasis remains unexplored. In the present study, we evaluated the effect of EF-24 on the invasiveness of NPC cells and investigated the molecular mechanisms associated with EF-24-regulated NPC cell migration, aiming to offer potential avenues for the use of curcumin analogs with enhanced bioavailability in combating this devastating malignancy. 2. Materials and Methods 2.1. NPC Cell Culture and Reagents HONE-1 cells were obtained from the Food Industry Research and Development Institute (Hsinchu, Taiwan). NPC-39 and NPC-BM, derived from patients with NPC , were kind gifts from Dr. MK Chen, Department of Otolaryngology, Changhua Christian Hospital, Changhua, Taiwan. The cell culture was maintained in RPMI-1640 medium at 37 degC in a humidified atmosphere of 5% CO2. EF-24 was purchased from Sigma-Aldrich (St. Louis, MO, USA) and prepared in dimethyl sulphoxide (DMSO, Sigma-Aldrich, St. Louis, MO, USA). Where indicated, the cells were pretreated with EF-24 for 1 h and then incubated with 50 ng/mL TPA (Sigma-Aldrich, St. Louis, MO, USA) for 23 h, followed by the subsequent experiments. 2.2. Cell Viability Assay The cytotoxic effects of EF-24 were evaluated by assessing the cell viability using a microculture tetrazolium test (MTT), as previously stated . After the pretreatment of various EF-24 concentrations for 1 h, the cells were incubated with TPA for 23 h, followed by an MTT assay. Cell viability was determined by the generation of formazan, which was measured spectrophotometrically at 563 nm in a spectrophotometer (DU640, Beckman Instruments, Fullerton, CA, USA). 2.3. Wound Healing Assay The cells were cultured in 6 cm plates for 24 h until full confluence. Serum starvation of the cells was performed overnight before making a scratch with a pipette tip . Then, cell debris was washed out, and the cell culture was maintained in a conditioned medium containing the indicated concentrations of EF-24 and TPA. Images of the cell cultures were taken at 0 and 12 h by using an Olympus CKX41 phase-contrast microscope (Olympus Corporation, Tokyo, Japan) at 100x magnification. 2.4. Cell Migration and Invasion Assay Cell migration and invasion were evaluated by a modified Boyden chamber system coated without and with 10 mL of Matrigel (25 mg/50 mL; BD Biosciences), respectively . Briefly, the cells were pretreated with the indicated concentrations of EF-24, in the absence or presence of TPA for 24 h, and were subsequently placed at a cell density of 104 cells per well on the membrane filters with a pore size of 8 mm in serum-free media for 24 h. Cell migration or invasion was counted with an Olympus CKX41 microscope (Olympus Corporation, Tokyo, Japan). 2.5. Gelatin Zymography A gelatin zymography protease assay was used to measure the gelatinolytic activities of MMP-9 in the culture medium, as stated previously . In brief, the conditioned medium was subjected to 0.1% gelatin (Sigma-Aldrich, St. Louis, MO, USA) and 8% SDS-PAGE. Followed by the electrophoresis, the gels were washed with 2.5% Triton X-100, soaked with a reaction buffer (10 mM CaCl2, 0.01% NaN3, and 40 mM Tris-HCl, pH 8.0) for 24 h at 37 degC, and were subsequently stained with Coomassie Brilliant Blue R-250 (Sigma-Aldrich, St. Louis, MO, USA). 2.6. Immunoblotting and Immunofluorescence Protein lysates were harvested, subjected to SDS-PAGE, and transferred to Immobilon PVDF membranes (Millipore) . The nuclear protein extraction was performed by using a Nuclear Extraction Kit (ab113474, Abcam) . Antibodies against the following proteins were used for detection: Anti-p38a (612168) from BD Biosciences (Bedford, MA, USA); Anti-NF-kB p65 (51-0500) from Invitrogen (Carlsbad, CA, USA); Anti-Lamin B2 (ab151735) from Abcam (Cambridge, UK); Anti-phospho-p38 mitogen-activated protein kinase (MAPK) (Thr180/Tyr182), Anti-p44/42 MAPK (ERK1/2), Anti-phospho-p44/42 MAPK (ERK1/2), Anti-SAPK/JNK, Anti-phospho-SAPK/JNK (Thr183/Tyr185) antibodies from Cell Signaling Technology (Danvers, MA, USA); and HRP-conjugated secondary antibodies (Dako). Densitometric analyses of immunoblots were conducted by using ImageJ software. For immunofluorescence, the fixation was conducted in 4% paraformaldehyde, and the permeabilization was performed by using PBS containing 0.5% Triton X-100. The cells were then blocked by PBS containing 1% goat serum, 1% BSA, 0.2% sodium azide, and 0.1% Triton X-100. Following hybridization with a polyclonal anti-p-65 antibody (1:100 dilution; 51-0500, Invitrogen) for 2 h and FITC-conjugated goat anti-rabbit IgG (1:50 dilution; Jackson ImmunoResearch) for 1 h, the cells were stained with DAPI and mounted on glass slides with an antifading, aqueous mounting medium (Biomeda, Foster City, CA, USA). 2.7. Quantitative PCR The total RNA was isolated by using an RNeasy Mini Kit (Qiagen), and cDNA was prepared using an AccuScript High-Fidelity 1st Strand cDNA Synthesis Kit (Stratagene). The primers were designed using Beacon Designer software, such that amplicons were 100-200 bp. Real-time PCR was carried out on a Bio-Rad iCycler iQ Multicolor Real-Time PCR Detection system using the iQ SYBR Green Supermix (Bio-Rad, Hercules, CA, USA), as described previously . Primer sequences were as follows: MMP-9: 5'-CAACATCACCTATTGGATCC-3' (forward) and 5'-CGGGTGTAGAGTCTCTCGCT-3' (reverse) and GAPDH: GAPDH: 5'-CGGAGTCAACGGATTTGGTCGTAT-3' (forward), 5'- AGCCTTCTCCATGGTGGTGAAGAC-3' (reverse). The quantification of relative expression levels was performed based on the standard curves for both MMP-9 and a constitutively expressed gene, GAPDH. 2.8. Reporter Assay A reporter assay was performed by the Luciferase Assay System (Promega, Madison, WI, USA) to analyze the activity of the luciferase. The vector encoding the MMP-9 promoter/reporter gene was a kind gift from Professor JL Ko (Chung Shan Medical University, Taichung, Taiwan). The constructs containing NF-kB-Luc, SP-1-Luc, or AP-1-Luc sequences were obtained from Stratagene (La Jolla, CA, USA). The mutant MMP-9 promoter/reporter vectors were constructed as described previously . Prior to the treatment of EF-24 and TPA, NPC cells were co-transfected with a b-galactosidase expression vector pCH110 (Pharmacia, Piscataway, NJ, USA), pGL-3-basic, and MMP-9 promoter plasmids, by using a LipofectamineTM 2000 Transfection Reagent (Invitrogen, Carlsbad, CA, USA) for 16 h. The cell lysates were collected, and luciferase activities normalized to a b-galactosidase internal control were assessed with a luciferase assay kit (Sigma). 2.9. Chromatin Immunoprecipitation (ChIP) Assay NPC cells were pretreated with EF-24 for 1 h and were subsequently incubated with TPA for 23 h. A ChIP assay was conducted using the ChIP assay kit (ab500, Abcam) . In brief, the cells were harvested, fixed with 1% paraformaldehyde and quenched with glycine at room temperature. The cells were lysed with the ChIP lysis buffer, and genomic DNA was sheared by sonication to produce DNA fragments of 200-700 bp. The sheared chromatin was immunoprecipitated with antibodies specific to the NF-kB p65 (51-0500, Invitrogen) and protein A Sepharose beads (Invitrogen). The NF-kB-bound chromatin fragments were analyzed using a PCR, using specific primers F-5'-GCCATGTCTGCTGTTTTCTAGAGG-3' and R-5'-CACACTCCAGGCTCTGTCCTCTTT-3' for the MMP-9 promotor. 2.10. Statistical Analysis Data represent averages +- standard deviation (SD) of at least three separate experiments. A p value of <0.05 was considered statistically significant by using a one-way analysis of variance with Tukey's post-hoc test. 3. Results 3.1. EF-24 Restricted Cell Motility and Invasion but Not Cell Viability in TPA-Induced NPC Cells The inhibitory roles of EF-24 in cell invasiveness have been observed in numerous tumor cell lines . Here, we first tested whether EF-24 affected the proliferation, motility, or invasion of NPC cells in response to TPA, a phorbol ester commonly used to promote cancer dissemination in cancer studies . Our result demonstrated that there was no anti-proliferative effect of NF-24 on HONE-1, NPC-39, and NPC-BM cells, as only mild cytotoxicity was detected for HONE-1 cells at a high concentration (1 mM) . Further examination of the cell motility by performing an in vitro wound healing revealed a dose-dependent inhibitory effect of EF-24 on TPA-induced NPC cell motility . Moreover, TPA-induced NPC cell migration and invasion were consistently suppressed by various concentrations of EF-24 in HONE-1, NPC-39, and NPC-BM cells . These data implicate the usefulness of EF-24 in restraining NPC invasiveness and metastasis. 3.2. EF-24 Represses the Activity and Expression of MMP-9 in NPC Since MMP-9 was shown to be a key player in mediating TPA-induced NPC cell invasion , we explored whether the levels of MMP-9 activity and expression were regulated during the inhibition of NPC invasion by EF-24. To test this, a gelatin zymography assay was used to evaluate the activity of MMP-9 in EF-24-treated NPC cell lines. We found that TPA-induced gelatin digestion in the culture media of all three NPC cell lines was decreased upon EF-24 treatment in a dose-dependent manner , suggesting that EF-24 effectively represses the activity or extracellular abundance of MMP-9 in NPC. Furthermore, the intracellular expression levels of MMP-9 were also tested. It was demonstrated that EF-24 resulted in the downregulation of MMP-9 gene expression in all three NPC cell lines. These findings indicate that EF-24 reduced both the expression and the activity of a crucial determinant of NPC cell invasion. 3.3. EF-24 Negatively Regulates the Transcription of MMP-9 Gene by Interfering with Nuclear Translocation of NF-kB To further explore the mechanisms by which EF-24 affected MMP-9 gene expression, we performed a series of reporter gene assays by using various forms of mutated MMP-9 promoter. In HONE-2 cells expressing a reporter gene driven by wild-type MMP-9 promoter, EF-24 elicited a dose-dependent downregulation of the TPA-induced luciferase gene , revealing a suppressive effect of EF-24 on MMP-9 gene transcription. While the SP-1 or AP-1 binding sequence of the MMP-9 promoter was mutated, EF-24 still contributed to a reduction in TPA-activated luciferase activities at a low (0.25 mM) or moderate (0.5 mM) concentration . However, such reductions by a low or moderate concentration of EF-24 were restored as the NF-kB binding sequence was mutated , suggesting that the regulation of MMP-9 gene transcription by EF-24 was mediated by the actions of NF-kB. Moreover, we tested whether EF-24 influenced the nuclear translocation of NF-kB. Our data from the isolated nuclear factions and immunofluorescence staining demonstrated a significant decrease in nuclear NF-kB levels under the treatment of EF-24 (0.5 and 1 mM) . Uncropped blots are available in the supplementary material. Further chromatin immunoprecipitation experiments showed that EF-24 interfered with the TPA-induced interaction between the NF-kB and MMP-9 promoter . Together, these findings indicate that EF-24 caused transcriptional suppression of MMP-9 in NPC cells by impeding the nuclear translocation of NF-kB. 3.4. EF-24 Inhibits JNK Signaling Pathway in NPC Invasion It is known that many signaling pathways, including MAPK pathways , mediate MMP-9 expression and regulate cancer invasiveness. Subsequently, we explored whether EF-24 orchestrates the activation of ERK, JNK, and p38 in NPC cells. Our data showed that EF-24 inhibited the activation of JNK, whereas it failed to alter TPA-activated ERK and p38 in NPC cells . This observation is further supported by the finding that the use of EF-24 and a pharmaceutical inhibitor of JNK, JNK-IN-8 exhibited synergistic effects on suppressing TPA-induced invasion responses and MMP-9 activities in NPC . 4. Discussion Even though standard treatment for NPC has achieved prevailing outcomes in early-stage cases, metastatic cancer remains a substantial hurdle of NPC therapies. Therefore, extra options to treat this disease are necessary to enhance patients' overall survival. A huge number of preclinical and clinical studies have revealed that curcumin, a herbal compound, increased the effectiveness of conventional cancer therapies, along with reducing their side effects and elevating the expression of anti-metastatic proteins, when given together with radio-therapeutics . In the present study, we showed that EF-24, a synthetic analog of curcumin with augmented bioavailability over its parent compound, rendered inhibitory effects on the invasiveness of NPC. Exploration of the underlying mechanisms demonstrated that the suppression of NPC invasion by EF-24 was coupled with a reduction in MMP-9 gene transcription by restraining the nuclear translocation of NF-kB and the activation of JNK signaling . Collectively, these results support the usefulness of EF-24 in controlling NPC progression. Many investigations have demonstrated an inhibitory effect of curcumin on the proteolytic activities and expression levels of the gelatinases MMP-2 and -9 in a series of cancer cell lines ; such suppressions of various MMPs by curcumin were mainly caused by interference with the transcriptional activities of AP-1 and NF-kB . Although EF-24 and its parent compound share numerous molecular mechanisms , such as the inactivation of NF-kB and the regulation of microRNAs, they likely exert bioactivities in different ways. For instance, curcumin blocked HIF-1a gene transcription, whereas EF-24 negatively regulated HIF-1a levels in a post-transcriptional manner . In breast cancer cells, curcumin inhibited TPA-induced cell invasion and MMP-9 expression by suppressing both NF-kB and AP-1 activation . However, our reporter assays showed that NF-kB, rather than AP-1, was functionally involved in the EF-24-mediated downregulation of MMP-9 in TPA-induced NPC cells. In addition to interfering with the activity of transcription factors, EF-24 was shown to resensitize renal cancer cells to TNF-related apoptosis-inducing ligand (TRAIL)-induced apoptosis via reducing intracellular ROS production and MMP-2/MMP-9 activity . The findings from our and others' studies implicate the use of EF-24 as a promising modality to restrain the anti-metastatic potential of nasopharyngeal cancers by targeting MMP-9. MAPK pathways are known as a key determinant of cancer cell invasion that show a complex interplay with NF-kB signaling . Unlike the highly consistent role of EF-24 in inhibiting NF-kB across different cancer types, the effect of EF-24 on regulating MAPK pathways is still under debate or appears to be specific to cancer/tissue types. In lung cancer cells, EF-24 induced cell apoptosis accompanied by the upregulation of three major MAPK pathways: ERK, JNK, and p38 . On the contrary, EF-24 triggered oral cancer cell apoptosis through the deactivation of the MAPK/ERK signaling pathway . However, we found that neither p38 nor ERK activation was affected by EF-24 in TPA-treated NPC cells. Notably, EF-24 inhibited JNK activation in TPA-treated NPC cells, and the co-treatment of NPC cells with EF-24 and a pharmaceutical inhibitor of JNK exhibited synergistic effects in suppressing TPA-induced invasion responses and MMP-9 activities. Our data demonstrated an anti-cancer effect of EF-24 on NPC invasion. However, additional efforts are required to address some of the limitations of this study. One concern is that ingestion into the human body might influence the bioactivity of EF-24, although we observed a suppressive effect on the invasion responses of NPC cell cultures. Further in vivo investigations are needed to ascertain its clinical applications in the management of NPC. Another issue is that the cell lines tested here were Epstein-Barr virus (EBV)-negative. Nevertheless, the main histologic subtypes of NPC (nonkeratinizing carcinoma and undifferentiated carcinoma) are mostly positive for EBV infection . Examining the efficacy of EF-24 on EBV-positive NPC cell lines will strengthen the clinical relevance. 5. Conclusions In conclusion, our results showed that through interfering with the nuclear translocation of NF-kB and the activation of JNK, EF-24 inhibited MMP-9 gene transcription, repressing NPC invasion. These findings provide potential avenues for the use of curcumin analogs with increased bioavailability in managing this devastating disease. Supplementary Materials The following supporting information can be downloaded at Click here for additional data file. Author Contributions Conceptualization: S.-C.S., C.-H.H., S.-F.Y. and C.-W.L.; Methodology: Y.-T.H. and F.-L.Y.; Writing--original draft preparation: S.-C.S., C.-H.H., Y.-T.L., C.-Y.C., S.-F.Y. and C.-W.L.; and Writing--review and editing: S.-C.S., S.-F.Y. and C.-W.L. 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 upon request, from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 EF-24 inhibited TPA-induced cell motility but did not render cytotoxicity in human NPC cells. (A) Structural formula of EF-24. (B) Prior to examining for cell viability, NPC cell lines were incubated with different concentrations of EF-24 for 1 h and then treated with TPA for an additional 23 h. Data represented the means +- SD from at least three separate experiments. (C-E) Wound closure of HONE-1 (C), NPC-39 (D), or NPC-BM cells (E) was assessed by measuring the width of the remaining wound area relative to the original wound width at 12 h post-treatment of EF-24 and TPA. Data represented the means +- SD from at least three independent experiments. a Significantly different, p < 0.05, when compared with the control group. b Significantly different, p < 0.05, when compared with the TPA treatment group. c Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.25 mM) group. Figure 2 EF-24 impedes TPA-induced migrative and invasive responses in NPC cell lines. HONE-1 (A), NPC-39 (B), or NPC-BM cells (C) were incubated with various concentrations of EF-24 and TPA for 24 h. Cell migration and invasion were assessed in a Boyden chamber system coated without and with Matrigel, respectively. Quantification of responses is shown on the right. a Significantly different, p < 0.05, when compared with the control group. b Significantly different, p < 0.05, when compared with the TPA treatment group. c Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.25 mM) group. d Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.5 mM) group. Figure 3 EF-24 suppresses the activity and expression of MMP-9 in NPC cells. HONE-1, NPC-39 and NPC-BM cells were pretreated with EF-24 for 1 h and incubated with TPA for an additional 23 h. Conditioned medium was collected for analyzing the activity of MMP-9 through gelatin zymography (A). Total RNA was extracted to assess the expression level of MMP-9 gene by using RT-PCR (B) and quantitative PCR (C). Densitometric analysis of gelatin zymography was conducted by the ImageJ software. The expression of the MMP-9 gene was normalized to the level of GAPDH gene. a Significantly different, p < 0.05, when compared with the control group. b Significantly different, p < 0.05, when compared with the TPA treatment group. c Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.25 mM) group. d Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.5 mM) group. Figure 4 EF-24 suppresses MMP-9 gene transcription by interfering with nuclear translocation of NF-kB. HONE-1 cells expressing a luciferase gene driven by wild-type (A) and various mutated forms (B-E) of MMP-9 promoter were pretreated with EF-24 for 1 h and then incubated with TPA for an additional 23 h. Luciferase assays were used to measure the transcriptional activity of MMP-9 promoter. Schematic representations of the reporter plasmids containing a mutated SP-1 (B), AP-1 (C,D), or NF-kB responsive element (E) are shown on the top. To explore the nuclear translocation of NF-kB, a nuclear extract of untransfected HONE-1 cells after the treatment of EF-24 and TPA was isolated and analyzed for the protein levels of NF-kB (F). Blots are representative of three independent experiments. Densitometric analyses were conducted by ImageJ, and quantitative results were normalized to the nuclear levels of an internal control, lamin B2. In addition, HONE-1 cells treated with EF-24 and TPA were fixed and stained with DAPI and a specific antibody against NF-kB p65 (G). The interaction of NF-kB with MMP-9 promoter was analyzed by using chromatin immunoprecipitation assay (ChIP) with an NF-kB antibody in HONE-1 cells treated with or without NF-24 and TPA (H). Densitometric analyses were conducted by ImageJ. a Significantly different, p < 0.05, when compared with the control group. b Significantly different, p < 0.05, when compared with the TPA treatment group. c Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.25 mM) group. d Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.5 mM) group. Figure 5 Regulation of EF-24 on MAPK activation. NPC cell lines were pretreated with EF-24 for 1 h and subsequently incubated with TPA for 23 h. Protein lysate was collected for a Western blot analysis to evaluate the phosphorylation of ERK (A), JNK (B), and p38 MAPK signaling (C). Densitometric data of kinase phosphorylation were obtained by ImageJ. Images shown are representative of three separate experiments. a Significantly different, p < 0.05, when compared with the control group. b Significantly different, p < 0.05, when compared with the TPA treatment group. c Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.25 mM) group. d Significantly different, p < 0.05, when compared with the TPA treatment plus EF-24 (0.5 mM) group. Figure 6 Synergistic effect of EF-24 and JNK-IN-8 on suppressing cell invasion and MMP-9 activity in NPC. HONE-1 cells were pretreated with EF-24, JNK-IN-8, or both for 1 h and then incubated with TPA for 23 h. Cell invasion responses were assessed by Boyden chamber assays (A), and MMP-9 activities were measured by gelatin zymography (B). a p < 0.05, compared with the untreated control; b p < 0.05, compared with TPA-treated cells; c p < 0.05, compared with the TPA + EF-24 treated cells. Figure 7 A schematic diagram of EF-24 in the regulation of TPA-induced NPC invasion. 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PMC10000446 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051081 foods-12-01081 Article Sub-Regional Variation and Characteristics of Cabernet Sauvignon Wines in the Eastern Foothills of the Helan Mountain: A Perspective from Phenolics, Visual Properties and Mouthfeel Zhao Bing-Yan Formal analysis Investigation Data curation Writing - original draft 12+ Zhang Xin-Ke Methodology Formal analysis Data curation Writing - review & editing 12+ Lan Yi-Bin Methodology Supervision 34 Duan Chang-Qing Conceptualization Supervision Project administration 34 Zhu Bao-Qing Methodology Supervision 5 Li De-Mei Conceptualization Resources Writing - review & editing Supervision 12* Henick-Kling Thomas Academic Editor 1 Department of Food Science and Engineering, College of Food Science and Engineering, Beijing University of Agriculture, Beijing 102206, China 2 "The Belt and Road" International Institute of Grape and Wine Industry Innovation, Beijing University of Agriculture, Beijing 102206, China 3 Center for Viticulture and Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China 4 Key Laboratory of Viticulture and Enology, Ministry of Agriculture and Rural Affairs, Beijing 100083, China 5 Beijing Key Laboratory of Food Processing and Safety in Forestry, Department of Food Science, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China * Correspondence: [email protected] + These authors contributed equally to this work. 03 3 2023 3 2023 12 5 108103 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 ). As one of the most promising wine regions in China, the eastern foothills of the Helan Mountain (EFHM) in the Ningxia Hui Autonomous Region has attracted great attention recently. Geographically, EFHM is divided into six sub-regions, namely Shizuishan, Xixia, Helan, Qingtongxia, Yongning and Hongsipu. However, there have been few reports on the character and differences between wines in the six sub-regions. In this experiment, a total of 71 commercial Cabernet Sauvignon wines from six sub-regions were collected, and their phenolic compounds, visual properties and mouthfeel were investigated. The results showed that wines from the six sub-regions of EFHM showed distinctive phenolic profiles and could be distinguished through the OPLS-DA mode using 32 potential markers. In terms of color, Shizuishan wines showed higher a* values and lower b* values. The sensory evaluation showed that Hongsipu wines had higher astringency strength and lower tannin texture. The overall results implied that the phenolic compounds of wines in different sub-regions were affected by terroir conditions. To the best of our knowledge, this is the first time that a wide coverage of phenolic compounds has been analysed for wines from the sub-regions of EFHM, which could provide valuable information in deciphering the terroir of EFHM. sub-region Cabernet Sauvignon phenolic compounds CATA QDA Key Project of R&D Program of Ningxia Hui Autonomous Region, China2021BEF02014 National Natural Science Foundation of ChinaU20A2042 This research was supported by the Key Project of R&D Program of Ningxia Hui Autonomous Region, China (grant number 2021BEF02014) and the National Natural Science Foundation of China (grant number U20A2042). pmc1. Introduction Wine is the most popular alcoholic drink across the world because of its unique culture and complex flavor. The term 'terroir' appears to have first been applied in the 14th century in France and encompasses the key natural elements of landscape features, soil characteristics, climate and human factors (socio-economics, history, genotype, variety and rootstock selection, winemaking technologies and vineyard management practices) that result in the production of unique, site-specific terroir wines . The eastern foothills of the Helan Mountain (EFHM) in the Ningxia Hui Autonomous Region, with latitude of 34deg14'-39deg23' and longitude of 104deg17'-107deg39', is located in the flood plain zone between the alluvial plain of the Yellow River and the alluvial fan of Helan Mountain . EFHM has a classic continental climate with sufficient sunlight, heat and suitable rainfall (2850-3110 h of sunshine, 3100-3500 degC of active accumulated temperature and 150-200 mm of rainfall). Helan Mountain obstructs cold air from the northwest, and the irrigation canals of the Yellow River in the east provide sufficient water, making EFHM a suitable region for wine grapes . In 2011, the General Administration of Quality Supervision, Inspection and Quarantine of China ratified the protection of place of origin (POD) of EFHM in Ningxia Hui Autonomous Region, making it the third Appellation wine region, after Changli in Hebei province and Yantai in Shandong province. High in the north and low in the south, the Helan Mountain borders the desert in the south, creating a microclimate that varies from north to south. In addition, the wine-producing region in EFHM is located along the mountain and river, and this provides different soil types due to various distances from the mountain, thus creating a variety of vineyard conditions. After 10 years of development, delicate sub-regions in EFHM have been formed and recognised officially, namely Hongsipu region, Qingtongxia region, Yongning region, Xixia region, Helan region and Shizuishan region . Although EFHM is the first appellation in China with geographical indication for sub-regions, the comprehensive understanding of the terroir in these sub-regions is far from adequate due to a short development period. Cabernet Sauvignon is the offspring of a cross between Cabernet Franc and Sauvignon Blanc , originated from the Bordeaux region in France, and is regarded as one of the most important grape varieties for making high quality red wines . It has pronounced influences on the wine making regime, given its aptitude to vinification by itself, but particularly when blended with other grape varieties . It is also one of the most popular grape varieties in China and has a sizable production in EFHM. EFHM contains 4000 hectares of Cabernet Sauvignon vine, accounting for 63% of the total wine grape cultivation area in the region. In addition, Cabernet Sauvignon is grown in all sub-regions, accounting for 50% or more of the total wine grape area in each. Cabernet Sauvignon is a late maturing variety with a very thick pericarp, resulting in abundant accumulation of phenolic compounds. Color and properties are important organoleptic aspects of wines, and phenolic compounds contribute to color , bitterness and astringency . The phenolic composition of a wine is dependent on cultivar , climate , soil type , viticulture practice and vinification techniques , all of which are factors of terroir. Different wine regions can have different terroir conditions which can lead to great differences in the quality, style and composition of wine. This difference could be reflected in the profile of secondary metabolites especially aromatic and phenolic compounds, as well as sensory characteristics. For instance, regional variation was characterized in 14 commercial Canadian Riesling wines using descriptive analysis (DA), and significant differences in the key aroma compounds of the wines were found . Similarly, regional variation was notably observed based on total polyphenols, trans and cis-resveratrol and biogenic amines in 73 wines from four Southern Italy regions . Using 18 non-flavonoid phenolic compounds, the origin of 43 Riesling wines from five regions in the Czech Republic could be successfully distinguished . Li et al. analysed the phenolic compounds in Cabernet Sauvignon wines from five distinct regions across China and found different phenolic profile in wines from hot and arid regions in northwest China and warm and humid regions in eastern China, respectively. Compared with wines from the other four regions selected for the experiment, wines from Deqin in Yunnan province (a highland valley in southwest China) contained extremely high concentrations of cyanidin derivatives and quercetin derivatives, but extremely low concentration of epicatechin, reflecting the terroir effect of the wines . However, the characteristics of phenolic compounds in Cabernet Sauvignon wines from different sub-regions in EFHM have not been reported. With the aim of studying the delicate regional variation of Cabernet Sauvignon wines, 71 wines from six sub-regions of EFHM were selected. Primary phenolic compounds, including non-anthocyanin phenolics, anthocyanins and their derivatives, were analysed by high-performance liquid chromatography-triple-quadrupole (HPLC-QqQ-MS/MS). The colors of the wines were quantified using the CIELAB method. At the same time, the mouthfeel of the wines was evaluated using Check-All-That-Apply (CATA) and Quantitative Descriptive Analysis (QDA). To the best of our knowledge, this is the first time that such a wide range of wines from six sub-regions of EFHM has been collected. The phenolic profile of these samples from such a wide coverage could provide valuable information in deciphering the terroir of EFHM, which in turn could provide an academic basis for the better development of the wine industry in China. 2. Materials and Methods 2.1. Wine Samples A total of 71 commercial wines from six different sub-regions of EFHM were collected. These wines were all Cabernet Sauvignon or Cabernet Sauvignon-dominant blends (>75%), with vintages ranging from 2015 to 2021. The basic wine compositions (residual sugar, alcohol level, pH, volatile acidity and total acidity) were measured using a WineScan (FT 120) rapid-scanning infrared Fourier-transform spectrometer with FOSS WineScan software version 2.2.1 (Foss Electric, Hillerod, Denmark). Information for all wine samples is given in Table S1A. 2.2. Chemicals and Standards Methanol, formic acid and acetonitrile (HPLC grade) were purchased from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Deionised water was purchased from Wahaha Co., Ltd. (Hangzhou, China). The standard compounds of anthocyanin and non-anthocyanin phenolics were purchased from Sigma-Aldrich (St. Louis, MO, USA), ChromaDex (Irvine, CA, USA), and Extrasynthese (Genay, France). 2.3. Analysis of Phenolic Compounds Phenolic compounds in wines were analysed according to various published methods. All wines were filtered through a 0.22 mm inorganic polyether-sulfone membrane prior to HPLC-MS analysis. An Agilent 1200 series high-performance liquid chromatographer equipped with an Agilent 6410B triple-quadrupole (QqQ) mass spectrometer (Agilent Technologies, Santa Clara, CA, USA) was used. The column was a Poroshell 120 EC-C18 column (150 mm x 2.1 mm, 2.7 mm; Agilent Technologies, Santa Clara, CA, USA). The mobile phases A were 0.1% formic acid in water; the mobile phases B were 0.1% formic acid in methanol and acetonitrile (50/50 v/v). 2.3.1. Analysis of Non-Anthocyanin Phenolic Compounds The gradient elution was: (1) from 10% to 46% B in 28 min; (2) from 46% to 10% B in 1 min. The post time was 5 min. The injection volume was 5 mL and the flow rate was 0.4 mL/min. The column was thermostatically controlled at 55 degC. An electrospray ionization source was used with 4 kV voltage and in the negative mode. The temperatures of the ion source and the drying gas (N2) were 150 degC and 350 degC, respectively. The drying gas flow rate was 12 L/min and the nebulizer pressure was 35 psi. The precursor ions and product ions of each phenolic compound were set in the multiple reaction monitoring (MRM) mode according to the published method . The quantification of each phenolic compound was achieved through a calibration curve for each commercially available phenolic standard. 2.3.2. Analysis of Anthocyanins The HPLC conditions for the analysis of anthocyanins were the same as for non-anthocyanin phenolic compounds. The ion source parameters were the same as for the non-anthocyanin phenolics, except that the positive mode was used. The MRM mode was also selected for the detection of anthocyanins according to a previous publication . The quantification of each anthocyanin compound was achieved through the malvidin-3-O-glucoside calibration curve. 2.3.3. Analysis of Anthocyanin Derivatives The mobile phase for the analysis of anthocyanin derivatives was the same as the above. The gradient elution started with the isocratic elution of 100% A for 1 min, then linearly increased B to 25% at 3 min, to 30% B at 15 min, to 100% B at 20 min, when the column was maintained by eluting with 100% B for an additional 5 min. The post time was 5 min. The injection volume was 10 mL and the flow rate was 0.3 mL/min. The ion source conditions were the same as for the analysis of anthocyanins. The MRM parameters for the anthocyanin derivatives were set according to a previous publication . The semi-quantification of each anthocyanin derivative was calculated from the basis of the calibration curve of malvidin-3-O-glucoside measured by the same method. 2.4. Color Measurement The chromatic characteristics of all wines were quantified using the CIELAB approach . All wines were first filtered through a 0.22 mm inorganic polyether-sulfone membrane and then placed in a 2-mm-optical-path glass cuvette. The absorbances at wavelengths ranging from 400 nm to 700 nm (at 1 nm intervals) were measured using a UV-visible spectrophotometer (Shimadzu UV-2450, Shimadzu Co., Kyoto, Japan). The values of lightness (L*), red-greenness (a*), and yellow-blueness (b*) were calculated accordingly. 2.5. Sensory Analysis It should be emphasized that this study complied with The Code of Ethics of the World Medical Association (Declaration of Helsinki), and all sensory evaluators provided informed consent to participate in the study. The Research Ethics Committee of China Agricultural University gave its approval for human subjects to be involved in this study, reference number CAUHR-20220901. 2.5.1. CATA CATA is a rapid descriptive analysis method for consumers to select all sensory properties from a given list of sensory descriptors. CATA chooses consumers to replace professional sensory evaluators, without the need for professional training and maintenance . Prior to the formal experiment, all 71 wine samples were evaluated by 16 experienced experts (professional sommeliers, winemakers and faculty), including 10 males and 6 females, aged between 26 and 58 years. Firstly, twelve experts were asked to participate in two sessions, each of which was divided into two rounds (approximately 50 min each). A glossary was then created. In the subsequent session, the appropriate terms were then agreed on by another four experts who had evaluated 71 wines. The final list consists of the 18 descriptors in Table S2A. Forty people were randomly recruited to participate in the CATA, 14 males and 26 females, aged between 20 and 30 years old. All sensory evaluators had experience of wine tasting and were selected on the basis of their interest. Prior to the formal CATA, each evaluator was trained to successfully describe the astringency and tannin texture of wines. For the training session, gradient solutions of skin tannin extract (0.1, 0.5, 1.0, 1.5 and 2.0 g/L) were used, and the scales for perceived astringency strength were set as weak, moderately weak, moderate, moderately strong and strong, respectively. For the descriptors describing the tannin texture sensations (satin, velvet, fine emery and abrasive), the touch of a physical standard with the fingertips could be used as a reference, as recommended by Gawel et al. , e.g., the touch of a velvet cloth to represent the mouth surface sensation labelled velvet. The detailed sensory options are shown in Table S2A. After the training, 40 sensory evaluators were instructed to taste prepared wine samples and then check the appearance, astringency strength and tannin texture options using a pre-designed questionnaire. Water and tasteless biscuits were prepared for each evaluator, and they were requested to relieve their mouths after each tasting. The entire CATA was conducted in 3 sessions, and each session consisted of 4 rounds. In each round, 6 wines were served and the evaluator was requested to complete the questionnaire within 25 min. A 10-min break was provided after the first two rounds. All wines were prepared in International Standards Organisation (ISO) wine tasting glasses (ISO 3591:1977) containing approximately 30 mL of wine and presented in a random order. All sensory evaluators worked in individual booths at a controlled temperature (20 degC). 2.5.2. QDA QDA is one of the classical descriptive sensory techniques to describe the characteristic and the intensity of sensory properties from a single evaluation of a product . It has been widely applied to vegetables , milk , wine , etc. CATA can only identify the characteristics of wines from different sub-regions, but cannot quantify these characteristics, especially when comparing the differences between wines from different sub-regions. Therefore, based on the results of CATA, wines with typical characteristics of each sub-region were selected for QDA. Seventeen experienced sensory evaluators were invited to participate in the QDA, 12 females and 5 males, aged between 25 and 32. Each sensory evaluator had passed the selection, training and periodic testing stipulated in the national standards of China (GB/T 16291.1-2012). Prior to the formal experiment, two Cabernet Sauvignon wines were used to standardize the scoring criteria and all sensory evaluators were requested to evaluate and discuss the body, finish, astringency strength and tannin texture of the wines until they reached a consensus. They were then asked to rate the selected wines on a scale of 0 to 10 for the four mouthfeel characteristics, with 0 being very weak and 10 being very strong. The wines for the QDA were divided into four rounds for scoring, lasting a total of two hours, with a 10-min break at the end of each session. The environment and supplies of QDA are the same as for CATA conditions. 2.6. Statistical Analysis The identification and quantification of all phenolic compounds in the wines were achieved using Mass Hunter workstation software (version 10.0) (Agilent Technologies, Santa Clara, CA, USA). One-way analysis of variance (ANOVA) was conducted and Duncan's post-hoc test with a significance level of 0.05 was performed in SPSS Statistics software (version 25.0) (IBM, Chicago, IL, USA). Soft Independent Modeling of Class Analogy (SIMCA, version 14.1 from Umetrics) was used for Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). Hierarchical cluster analysis was achieved through "MetaboAnalyst 5.0" (accessed on 14 October 2022)). CATA data were analysed using XLSTAT 2019 (Addinsoft, New York, NY, USA). 3. Results and Discussion 3.1. Basic Wine Compositions The basic compositions of all the wines, including ethanol level, residual sugar, pH, total acidity and volatile acidity are listed in Table S1A. The alcohol level of all the wines ranged from 13.14% to 15.74% (v/v), the residual sugar ranged from 1.7 to 10.3 (g/L), the pH ranged from 3.54 to 4.23, the total acidity ranged from 4.9 to 7.6 (g/L, tartaric acid equivalent), and the volatile acidity ranged from 0.5 to 1.0 (g/L). All the basic parameters of the wines conformed to the national standards of China (GB/T 15037-2006) and can be used for subsequent analysis. 3.2. OPLS-DA Analysis A total of 67 phenolic compounds were identified in all wines by HPLC-QqQ-MS/MS. Detailed information is shown in Table 1. The OPLS-DA model was used to differentiate and characterize six sub-regions in EFHM, as it has shown good performance in wines with subtle regional and vintage variations . In the model, R2 is a measure of fitness, i.e., how well the model fits the data. Q2 indicates the predictability of the model. As shown in Figure 2A, a separation was obtained by a reliable OPLS-DA model (R2X = 0.662, R2Y = 0.331, Q2 = 0.159) based on the concentration of phenolic compounds. The further validation of the model was tested by 7-fold internal cross-validation and 200-time permutation tests. The prediction result of the cross-validated score plot was basically consistent with the actual score plot , indicating a good predictive effect. The results of 200-time permutation tests showed that the OPLS-DA model did not overfit . According to the model, it can be clearly seen that the wines from Yongning, Qingtongxia and Hongsipu region were all well separated. Meanwhile, there was some overlap between the wines from Helan and Xixia region . We speculated that this may be due to the fact that Helan and Xixia regions are adjacent to each other , leading to more similarities in topographical features. Interestingly, wines from Shizuishan and Qingtongxia regions also overlap in the model, but the two sub-regions have nothing in common other than the same altitude (Table S3). Figure 2B shows the correlation between the explanatory variables, i.e., the concentration of phenolic compounds (in purple dots) and the dependent variables, i.e., the sub-regions (in black dots) in the first and second principal components. These compounds, located close to the sub-regions in Figure 2B, could be considered as potential features with these sub-regions. Figure 2C shows the Variable Importance for the Projection (VIP) plot of the OPLS-DA model. A higher VIP value indicates a greater contribution of the explanatory variable to the discriminative ability in OPLS-DA. Normally, a VIP value above 1 could be considered as a threshold for selecting potential markers . A total of 32 phenolic compounds with VIP above 1 were screened . Combined with Figure 2B,C, it can be seen that cyanidin-3-O-acetylglucoside (Cy-Aglu), malvidin-3-O-glucoside-(epi)catechin (A type) (Mv-(e)cat) and (epi)catechin-malvidin-3-O-glucoside (B type) ((E)cat-Mv) were the potential markers in wines from Xixia region. Delphinidin-3-O-glucoside-pyruvic acid (Dp-py), petunidin-3-O-glucoside-pyruvic acid (Pt-py) and cyanidin-3-O-glucoside (Cy-glu) were the potential markers in wines from Helan region and Hongsipu region. Delphinidin-3-O-glucoside-acetaldehyde (Dp-ace), cyanidin-3-O-glucoside-acetaldehyde (Cy-ace) and protocatechuic acid (PA) were the potential markers in wines from Yongning region. 3.3. Sub-Regional Variation of Phenolic Compounds 3.3.1. Comparison of Non-Anthocyanin Phenolic Compounds A total of 28 non-anthocyanin phenolic compounds were identified in all wines via HPLC-QqQ-MS/MS (Table S4), including six flavan-3-ols, nine phenolic acids (three hydroxycinnamic acids and six hydroxybenzoic acids) and 13 flavonols. It was found that the concentration of the total detectable flavan-3-ols in wines from six sub-regions ranged from 145.12 to 673.67 mg/L. Wines from the Yongning region had the lowest flavan-3-ol concentration, while those from the Hongsipu region had the highest. (Table S4). Previous studies had shown that the type of soil has a significant effect on phenolic compounds in grape . The soil of Hongsipu region is a sierozem soil with loose texture and good aeration, which makes the soil have strong water and fertilizer holding capacity and rich calcium concentration . Such soil provided favourable conditions for tannin accumulation . This may be one of the reasons accounting for the higher concentration of flavan-3-ols in wines from Hongsipu region. The total detectable flavonol concentrations in wines from the six sub-regions ranged from 21.74 to 118.69 mg/L. The concentrations of myricetin-glucoside (M-glu), quercetin-glucoside (Q-glu) and isorhamnetin-glucoside (I-glu) in Helan wines were significantly higher than those in other sub-regions, resulting overall in the highest total flavonol concentrations. In contrast, the Hongsipu wines had the lowest flavonol concentrations (Table S4). Both genotype (variety) and environment are critical factors in controlling the production of flavonols . Furthermore, in the case of wines, even common wine-making processes, including grape skin contact, stabilization processes and ageing, have been shown to cause significant changes in flavonols . However, the reason for the high concentration of flavonols in Helan wines is still unclear and further studies are required. The concentration of total detectable hydroxybenzoic acids ranged from 10.16 to 51.38 mg/L, with the highest concentration in Shizuishan wines and the lowest in Qingtongxia wines. Gallic acid (GLA) was the predominant hydroxybenzoic acid (6.77 to 38.12 mg/L), which was consistent with previous reports . Compared with the wines from other sub-regions, the wines from the Hongsipu region contained a significantly higher concentration of GLA but a lower concentration of vanillic acid (VA), 4-hydroxybenzoic acid (4-HBA) and PA. In contrast, more 4-HBA and PA were detected in Shizuishan wines, even up to about twice as much as in wines from other sub-regions (Table S4). In terms of hydroxycinnamic acids, concentration ranged from 4.47 to 29.19 mg/L. In addition, as the predominant hydroxycinnamic acid , caffeic acid (CFA) showed no significant difference among the six sub-regions. More generally, the remaining hydroxycinnamic acids in the six sub-regions of wines were not significantly different except for 3-hydroxycinnamic acid (3-HCA) (Table S4). 3.3.2. Comparison of Anthocyanins A total of 15 anthocyanins were identified by HPLC-QqQ-MS/MS in all wines, including non-acylated anthocyanins, acylated anthocyanins and coumaroylated anthocyanins (Table S5). In general, there were no significant differences in the total concentration of detectable anthocyanins between the six sub-regions. Nonetheless, wines from Helan and Shizuishan region showed a higher and lower concentration of total detectable anthocyanins, respectively. The biosynthesis of anthocyanins in grape was influenced by temperature, with a lower temperature promoting the expression levels of anthocyanin biosynthesis genes such as VIMYBA2, while a higher temperature may suppress them . Although climate data for recent years were not available, a higher effective accumulated temperature from July to October was observed in the Shizuishan region from historical data (Table S3). This may be one of the reasons that account for a lower anthocyanin concentration in this region. All five types of anthocyanins were detected: cyanidin, delphinidin, peonidin, petunidin and malvidin. The proportion of the five types of anthocyanins in wines from the six sub-regions was almost the same (Table S5). Cyanidin-type anthocyanins had the lowest concentration and malvidin-type anthocyanins had the highest concentration, suggesting that the anthocyanin composition was not influenced by sub-regional factor but might be inherently controlled by a genetic factor, such as cultivar . Among all the anthocyanins, malvidin-3-O-glucoside (Mv-glu) showed the highest concentration in wine, in agreement with previous results . 3.3.3. Comparison of Anthocyanin Derivatives A total of 24 anthocyanin derivatives were identified in all wines by HPLC-QqQ-MS/MS (Table S6), including three direct flavanol-anthocyanin condensation products (F-A), five direct anthocyanin-flavanol condensation products (A-F) and 16 pyrano-anthocyanins (10 vitisins, three flavanyl-pyrano-anthocyanins and three pinotins). Overall, there was no significant difference in the concentration of total detectable anthocyanin derivatives in different sub-regions, but it could be seen that the wines from Hongsipu region had the highest concentration of total detectable anthocyanin derivatives, followed by the wines from Helan region, and the wines from Shizuishan region had the lowest concentration of total detectable anthocyanin derivatives (Table S6). For most anthocyanin derivatives, such as delphinidin-3-O-glucoside-pyruvic acid (Dp-py) and petunidin-3-O-glucoside-pyruvic acid (Pt-py), their concentrations were significantly higher in wines from Hongsipu, which was largely consistent with the concentration conditions of their anthocyanin precursors. For those anthocyanin derivatives with no significant difference, a reasonable explanation was that there were also no significant differences in the concentrations of their anthocyanin precursors. In addition, anthocyanin derivatives were mostly formed during the process of alcoholic fermentation, malolactic fermentation and aging of wine . For example, the precursors of vitisins were pyruvic acid and acetaldehyde derived from yeast metabolism during alcoholic fermentation . Therefore, the accumulation of anthocyanin derivatives in wines from the six sub-regions was a complex process influenced by many factors, such as wine-making technology and grape variety. 3.4. Hierarchical Cluster Analysis The phenolic compounds of the 71 EFHM wines were analyzed using hierarchical cluster analysis to determine the similarities for these sub-regions . Yongning region, Helan region, Qingtongxia region, Shizuishan region and Xixia region were consecutively grouped into one category, which may be due to the fact that these sub-regions are all adjacent to the foothill of Helan Mountain and therefore share similar climate and soil type. As the southernmost sub-region of EFHM, Hongsipu region is far away from other sub-regions and less protected by Helan Mountain . Moreover, its high altitude makes it more susceptible to the northwesterly cold flow. It also received more rainfall than most of the sub-regions (Table S3). These factors led to large differences in terroir, so Hongsipu region was divided into a separate category, which is consistent with the clustering results of different sub-regions in EFHM by Zhang et al. . 3.5. Comparison of Color of Wines The chromatic properties of wines from different sub-regions were quantified using the CIELAB approach (Table 2). The color of wine is originally derived from anthocyanins extracted from grape skins during winemaking. Anthocyanins showed a negative correlation with L* and b* values but a positive correlation with a* values . The results of the chromatic characteristics of all wines showed no significant differences in L* values between wines from different sub-regions, indicating no significant variation in color intensity. Wines from Shizuishan had significantly higher b* values (more yellowness) and lower a* values (less redness) than those from other sub-regions. Based on the quantification of phenolic compounds, we found that this might be due to the lowest concentration of total anthocyanins in Shizuishan wines (Table S5). In addition, wines from Shizuishan region had a significantly higher pH than those from other sub-regions (Table S1B), while higher pH could result in wine losing its color intensity and redness . 3.6. Sensory Characteristics of Wines CATA was used to characterize the appearance, astringency strength and tannin texture of Cabernet Sauvignon wines from the six sub-regions of EFHM. Correspondence analysis (CA) is a multivariate statistical technique which is applicable to tables of categorical data . In the study, CA was used to explore the visual and mouthfeel characteristics of wines in descriptors of specific characteristics such as appearance, astringency strength and tannin texture. In CA, there was a significant difference in frequency for 17 of the 18 descriptors (p < 0.05) and their correlation with the wines is shown in Figure 4A. F1 and F2 explained a 56.59% of the total variance. Wines in the first quadrant were deep ruby or deep purple in appearance, with strong to moderately strong astringency strength and fine emery or abrasive tannin texture. Wines in the second quadrant were brick red, brown or garnet in appearance. In the third quadrant, the wines were mainly light ruby or ruby in appearance, with moderately weak or weak astringency strength and satin or velvet tannin texture. In the fourth quadrant, the wines were mainly light purple and purple in appearance. In addition, Table S2B shows the frequencies of the descriptors used to describe the wines, from which frequencies above 20% were selected as representative sensory characteristics. The typical visual and mouthfeel characteristics of wines from different sub-regions were obtained. The results showed that the wines from Shizuishan region were ruby, while the astringency strength was moderately weak, with velvet or fine emery tannin texture. However, moderately strong astringency strength was also selected by some sensory evaluators for Shizuishan wines. Most Helan wines were deep ruby or ruby, and their astringency strength was considered as moderately weak, with velvet or fine emery tannin texture. Wines from Xixia region were ruby or deep ruby in appearance, with moderately weak astringency strength and velvet or fine emery tannin texture. Yongning wines were light ruby or deep ruby, some wines were described as garnet, and the astringency strength was moderately weak, with velvet or fine emery tannin texture. Qingtongxia wines were mostly ruby, and the astringency strength was moderately weak or weak, felt satin or velvet, and a few were described as fine emery. Hongsipu wines were purple or ruby in appearance, with moderately weak astringency strength and fine emery tannin texture. Using the above-mentioned criteria (frequency > 0.2), 27 representative wines from different sub-regions (excluding Shizuishan region) were used for QDA. The box plot in Figure 4B shows the profile of astringency strength, tannin texture, body and finish of wines from the different sub-regions. The results shows that the astringency strength of Hongsipu wines is significantly higher (Table S2C). It has been confirmed that flavan-3-ols are the most important compounds in determining the astringency strength of wine ; in this case, however, flavan-3-ols were more pronounced in Hongsipu wines, albeit no significant difference was observed (Table S4). Hydroxybenzoic acids were also proved to contribute to astringency , and this might be one of the reasons for the stronger astringency of Hongsipu wines. Lower pH and ethanol in Hongsipu wines (Table S1B) could also accentuate the astringent sensation in month , and could lead to a higher astringency strength result. In addition, Hongsipu wines showed lower tannin texture than the others, which was basically consistent with the CATA results, possibly due to more flavan-3-ols and hydroxybenzoic acids, as well as lower pH and ethanol level, as suggested . 4. Conclusions In this study, primary phenolic compounds, visual properties and mouthfeel of 71 Cabernet Sauvignon wines from the six sub-regions of EFHM were analysed. Through the mining of the OPLS-DA model, it was found that 32 phenolic compounds could be used as characteristic compounds to distinguish wines from different sub-regions. The quantitative analysis results showed that the concentration of phenolic compounds in wines from different sub-regions had their own characteristics; especially, the Hongsipu wines showed great differences in phenolic compounds compared with others. In addition, these characteristics are also reflected in the senses, forming the unique visual properties and mouthfeel of the wines of different sub-regions. Thus, a terroir effect was observed for phenolic compounds and detailed studies on the effects of terroir on the phenolic compounds in wines from different sub-regions in EFHM should be further investigated. It should also be noted that the exploration of terroir conditions in different sub-regions of EFHM is still limited, and the typical characteristics of wines in different regions are not well understood. In the future, further probing could be carried out in this respect. Acknowledgments The authors are grateful to China Agricultural University for providing sensory evaluation conditions and the help of all sensory evaluation experts invited in this study. Supplementary Materials The following supporting information can be downloaded at: Table S1A: The information and basic composition and L*, a*, and b* values of all wine samples; Table S1B: The statistical summary of basic physical and chemical indexes of Cabernet Sauvignon wines from six sub-regions of EFHM; Table S2A: The materials and scales for training in CATA; Table S2B: The CATA frequency of 71 Cabernet Sauvignon wines from the six sub-regions of EFHM; Table S2C: The QDA result of 71 Cabernet Sauvignon wines from the six sub-regions of EFHM; Table S3: The historic terroir parameter of the six sub-regions of EFHM; Figure S1: Cross-validated score plot for the OPLS-DA model based on the concentrations of phenolic compounds in Cabernet Sauvignon wines from six sub-regions of EFHM; Figure S2: Validation plot obtained from 200-time permutation tests for the OPLS-DA model based on the concentrations of phenolic compounds in Cabernet Sauvignon wines from six sub-regions of EFHM; Table S4: Concentration of non-anthocyanin phenolic compound in Cabernet Sauvignon wines from six sub-regions of EFHM; Table S5: Concentration of anthocyanin in Cabernet Sauvignon wines from six sub-regions of EFHM; Table S6: Concentration of anthocyanin derivative in Cabernet Sauvignon wines from six sub-regions of EFHM. Click here for additional data file. Author Contributions B.-Y.Z. contributed to investigation, formal analysis, data curation and writing of the original draft. X.-K.Z. contributed to formal analysis, data curation, methodology and review & editing. Y.-B.L. contributed to methodology and supervision. C.-Q.D. contributed to conceptualization, supervision and project administration. B.-Q.Z. contributed to methodology and supervision. D.-M.L. contributed to conceptualization, resources, supervision and review & 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 The topographic map of the six sub-regions from EFHM in Ningxia Hui Autonomous Region. Figure 2 OPLS-DA model based on the concentrations of phenolic compounds in Cabernet Sauvignon wines from six sub-regions of EFHM. (A) Score plot (B) Loading plot (C) VIP plot of the OPLS-DA model. Figure 3 Hierarchical cluster analysis based on the concentrations of phenolic compounds in Cabernet Sauvignon wines in the six sub-regions of EFHM. Figure 4 Sensory characteristics of Cabernet Sauvignon wines from the six sub-regions of EFHM. (A) Correspondence analysis of wines based on CATA; (B) Box plot of wines based on QDA. Different letters in the same area indicate significant difference (p < 0.05) using Duncan's multiple range test. foods-12-01081-t001_Table 1 Table 1 Abbreviation, MRM information, and calibration curves of phenolic compounds. Phenolic Compounds Abbreviation MRM Transition Ions (m/z) Retention Time (Min) Quantitative Standards Calibration Curves (mg/L) R2 Procyanin B PC B 577-407 7.6 C y = 0.0019x - 1.5545 R2 = 0.9934 Procyanin C1 PC C 865-407 10.36 C y = 0.0019x - 1.5545 R2 = 0.9934 Epigallocatechin EGC 305-125 5.2 C y = 0.0019x - 1.5545 R2 = 0.9934 Catechin C 289-123 5.8 C y = 0.0019x - 1.5545 R2 = 0.9934 Epicatechin EC 289-123 9.3 EC y = 0.002x - 2.4286 R2 = 0.9929 Gallo-catechin GC 305-125 2.5 C y = 0.0019x - 1.5545 R2 = 0.9934 Caffeic acid CFA 179-135 7.2 CFA y = 0.00008x + 0.8751 R2 = 0.9921 3-hydroxycinnamic acid 3-HCA 163-119 10.58 3-HCA y = 0.000006x + 0.066 R2 = 0.9966 Ferulic acid FA 193-134 12.72 FA y = 0.0003x + 0.3138 R2 = 0.9991 Chlorogenic acid CA 353-191 6.3 CA y = 0.00009x + 0.3061 R2 = 0.9969 Gallic acid GLA 169-125 1.7 GLA y = 0.0002x + 0.4347 R2 = 0.9972 Protocatechuic acid PA 153-109 3.0 PA y = 0.0002x - 0.0369 R2 = 0.9996 4-hydroxybenzoic acid 4-HBA 137-93 5.02 4-HBA y = 0.0003x - 0.0372 R2 = 0.9909 Gentisic acid GTA 153-109 5.0 GTA y = 0.0002x + 0.045 R2 = 0.9996 Vanillic acid VA 167-152 6.9 GTA y = 0.0002x + 0.045 R2 = 0.9996 Myricetin-glucoside M-glu 479-316 13.3 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Dihydro-quercetin DHQ 303-125 13.5 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Dihydro-kampferol DHK 287-259 17.13 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Quercetin-glucoside Q-glu 463-300 16.3 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Quercetin-galactoside Q-gal 463-300 15.75 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Quercetin-glucuronide Q-gluc 477-301 15.9 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Quercetin Q 301-151 23.9 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Larictrin L 331-151 24.8 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Myricetin M 317-151 19.02 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Isorhamnetin-glucoside I-glu 477-314 19.77 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Kaempferol-3-O-glucoside K-glu 447-255 18.9 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Syringetin-glucoside S-glu 507-344 20.1 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Quercetin-rhamnoside Q-rha 447-300 19.0 DHQ y = 0.0002x + 0.2793 R2 = 0.9965 Cyanidin-3-O-glucoside Cy-glu 449-287 4.5 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Cyanidin-3-O-acetylglucoside Cy-Aglu 491-287 5.69 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Cyanidin-3-O-coumaroylglucoside (cis+trans) Cy-Cglu 595-287 6.43 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Delphinidin-3-O-glucoside Dp-glu 465-303 4.6 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Delphinidin-3-O-acetylglucoside Dp-Aglu 507-303 5.39 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Delphinidin-3-O-coumaroylglucoside (cis+trans) Dp-Cglu 611-303 6.16 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-glucoside Pn-glu 463-301 5.07 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-acetylglucoside Pn-Aglu 505-301 6.08 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-coumaroylglucoside (cis+trans) Pn-Cglu 609-301 6.76 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Petunidin-3-O-glucoside Pt-glu 479-317 4.7 Mv-glu y = 0.00002 x + 0.0327 R2 = 0.9954 Petunidin-3-O-acetylglucoside Pt-Aglu 521-317 5.76 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Petunidin-3-O-coumaroylglucoside (cis + trans) Pt-Cglu 625-317 6.47 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside Mv-glu 493-331 5.15 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-acetylglucoside Mv-Aglu 535-331 6.08 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-coumaroylglucoside (cis + trans) Mv-Cglu 639-331 6.74 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-(epi)catechin (A type) Mv-(e)cat 783-343 10.53 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-glucoside-(epi)catechin (A type) Pn-(e)cat 753-313 10.29 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Delphinidin-3-O-glucoside-(epi)catechin (A type) Dp-(e)cat 755-315 8.08 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Petunidin-3-O-glucoside-(epi)catechin (A type) Pt-(e)cat 769-329 9.1 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Cyanidin-3-O-glucoside-(epi)catechin (A type) Cy-(e)cat 739-299 8.9 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 (Epi)catechin-cyanidin-3-O-glucoside (B type) (E)cat-Cy 737-575 6.39 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 (Epi)catechin-malvidin-3-O-glucoside (B type) (E)cat-Mv 781-619 6.97 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 (Epi)catechin-petunidin-3-O-glucoside (B type) (E)cat-Pt 767-605 6.5 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Cyanidin-3-O-glucoside-acetaldehyde Cy-ace 473-311 8.5 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Delphinidin-3-O-glucoside-acetaldehyde Dp-ace 489-327 7.2 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-acetaldehyde Vitisin B 517-355 10.7 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Petunidin-3-O-glucoside-acetaldehyde Pt-ace 503-341 10.1 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-glucoside-acetaldehyde Pn-ace 487-325 10.14 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Cyanidin-3-O-glucoside-pyruvic acid Cy-py 517-355 8.36 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Delphinidin-3-O-glucoside-pyruvic acid Dp-py 533-371 7.6 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-pyruvic acid Vitisin A 561-399 10.415 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Petunidin-3-O-glucoside-pyruvic acid Pt-py 547-385 8.7 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-glucoside-pyruvic acid Pn-py 532-369 9.86 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-4-vinyl(epi)catechin Mv-v-Cat 805-643 20.69 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Peonidin-3-O-glucoside-4-vinyl(epi)catechin Pn-v-Cat 775-613 20.51 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Petunidin-3-O-glucoside-4-vinyl(epi)catechin Pt-v-Cat 791-629 19.34 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-4-vinylcatechol Mv-vcol 625-463 20.9 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-4-vinylphenol Mv-vpol 609-447 21.21 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 Malvidin-3-O-glucoside-4-vinylguaiacol Mv-vgol 639-477 21.31 Mv-glu y = 0.00002x + 0.0327 R2 = 0.9954 foods-12-01081-t002_Table 2 Table 2 Color parameters of Cabernet Sauvignon wines from the six sub-regions of EFHM. 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PMC10000447 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050667 healthcare-11-00667 Article To Admit or Not to Admit to the Emergency Department: The Disposition Question at a Tertiary Teaching and Referral Hospital Alahmary Khalid 12 Kadasah Sarah 12 Alsulami Abdulrahman 12 Alshehri Ali M. 12 Alsalamah Majid 23 Da'ar Omar B. 12* Sartini Marina Academic Editor 1 College of Public Health and Health Informatics, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi Arabia 2 King Abdullah International Medical Research Center (KAIMRC), King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi Arabia 3 Emergency Department, King Abdulaziz Medical City and King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi Arabia * Correspondence: [email protected] 24 2 2023 3 2023 11 5 66716 11 2022 11 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 ). Background: Disposition decision-making in the emergency department (ED) is crucial to patient safety and quality of care. It can inform better care, lower chance of infections, appropriate follow-up care, and reduced healthcare costs. The aim of this study was to examine correlates of ED disposition among adult patients at a teaching and referral hospital based on patients' demographic, socioeconomic, and clinical characteristics. Method: A cross-sectional study conducted at the ED of the King Abdulaziz Medical City hospital in Riyadh. A two-level validated questionnaire was used--a patient questionnaire and healthcare staff/facility survey. The survey employed a systematic random sampling technique to recruit subjects at a pre-specified interval as patients arrived at the registration desk. We analyzed 303 adult patients visiting the ED, who were triaged, consented to participate in the study, completed the survey, and admitted to a hospital bed or discharged home. We used descriptive and inferential statistics to summarize and determine the interdependence and relationships of variables. We used logistic multivariate regression analysis to establish relationships and the odds of admission to a hospital bed. Results: The mean age of the patients was 50.9 (SD = 21.4, Range 18 to 101). A total of 201 (66%) were discharged home while the rest were admitted to a hospital bed. Results of the unadjusted analysis suggest that older patients, males, patients with low level of education, and those with comorbidities and middle-income were more likely to be admitted to the hospital. The results of the multivariate analysis suggest that patients with comorbidities, urgent conditions, prior history of hospitalization, and higher triage levels were more likely to be admitted to a hospital bed. Conclusions: Having proper triage and timely stopgap review measures in the admission process can help new patients to locations that best support their needs and improve the quality and efficiency of the facility. The findings may be a sentinel indicator that informs overuse or inappropriate use of EDs for non-emergency care, which is a concern in the Saudi Arabian publicly funded health system. emergency department disposition decision Saudi Arabia King Abdullah Medical Research Center (KAIMRC)R15/131/R This research was supported by King Abdullah Medical Research Center (KAIMRC). Funded under protocol # R15/131/R. pmc1. Introduction An essential element of handling patients in an emergency department (ED) is the disposition decision. Disposition involves determining whether a patient is appropriate for release or needs in-patient care for additional evaluation and stabilization. As the ultimate endpoint for all ED cases, disposition may be a patient leaving without being seen, admitting patient in a hospital bed, transferring patients to other facilities, discharging patients to home, death, or patients leaving without medical advice . Proper disposition can inform what type of follow-up care patients may need. Disposition may influence not only current utilization, but also how and to what extent patients access care in the future. Disposition decisions at an ED are influenced by a complex interaction of clinical factors such as diagnosis, severity and response to treatment, as well as patients' demographic, socioeconomic, and health factors . Utilization of ED services is a common practice in Saudi Arabia with the dramatic increases in public hospitals . Available evidence suggests that despite the availability of free primary care, patients tend to bypass these facilities to seek ED services for non-urgent and avoidable conditions . Even with the universal coverage of healthcare in these facilities, there is no evidence of a balance between demand for and provision of ED health services. Despite overutilization of EDs being commonplace, there is limited evidence on comprehensive evaluation of factors affecting disposition decisions . Previous evidence partially looked at factors associated with disposition concentrating on the provider side and clinical status, examining specific patients with non-urgent needs . To bridge this gap, this study considered adult patients visiting the ED and set out to examine correlates of ED disposition among adult patients at a teaching and referral hospital based on patients' demographic, socioeconomic, and clinical characteristics. It is important to evaluate disposition decision-making in the ED because it is crucial to informing patient safety and quality of care , overutilization and overcrowding , and increased mortality and healthcare costs . Given these negative outcomes were especially exacerbated during the recent COVID-19 pandemic , it is paramount to predict the likelihood of dispositioning that sends patients to locations that best support their needs and improves quality and efficiency of the facility. 2. Methods 2.1. Study Design This is a cross-sectional study that used ED data previously collected using a validated survey tool at King Abdulaziz Medical City-King Fahad hospital in Riyadh (KAMC-KF). The data were collected from 1 December 2016 to 31 January 2017. The survey employed a systematic random sampling technique to recruit participants at a pre-specified interval as patients arrived at the registration desk for triaging. Participants consented before agreeing to participate. A total of 440 patients visiting the ED were sampled and invited, of which 381 consented to participate. Of these patients, 366 completed the questionnaires. After excluding deaths, incomplete participation, and patients who left against medical advice, 303 patients were included for analysis. Ethical approval for the study was obtained from the Institutional Review Board at King Abdullah International Medical Research Center (KAIMRC), Riyadh, Saudi Arabia. 2.2. Inclusion Criteria Inclusion criteria allowed enrollment of adult patients who visited the ED, triaged, consented to participate in the study, and were admitted to a hospital bed or discharged home and/or transferred to other facilities. The ED used the Canadian Triage and Acuity Scale (CTAS) . 2.3. Setting of the Study The study was at the ED of the King Abdulaziz Medical City (KAMC) Hospital in Riyadh. The facility is a tertiary referral and teaching hospital and a member of the Joint Commission of International Standards (JCI). With an over 690-bed capacity, the facility serves the national guard health affairs (NGHA) employees and their dependents. Attendees of the hospital are eligible for most services for free, although there are out-of-pocket patients in the business section. Proximity to the capital city and the variety of case-mix services at the out-patient, in-patient, and emergency services make the facility ideal for most patients. 2.4. The Tool Description A two-level validated questionnaire was used-a patient questionnaire and a healthcare staff/facility survey. The questionnaire was a modified version of the Queensland University of Technology (QUT) Emergency Health Services study . English and Arabic language translations and reverse translations of the patient questionnaire were conducted to check for consistency and validity. Translation of the survey was designed to facilitate in case any patient wanted to self-administer the questionnaire in the local language without the assistance of trained research assistants. The researchers who interviewed patients spoke both languages well. 2.5. Statistical Analysis The primary outcome of interest was patients' disposition decisions from ED. Disposition and covariates data were extracted and analyzed using statistical STATA statistical software version 12 (College Station, TX, USA). Descriptive statistics were summarized for all variables. We dichotomized the primary outcome of ED disposition decisions into either admission to a hospital bed or discharged home. Other disposition decisions such as transfers to other facilities, deaths and patients leaving without medical advice were excluded from the analysis. To determine the association between socioeconomic, demographic profiles, and clinical conditions of patients, we used the Chi-squared test or Fisher's exact test for categorical variables. In addition, we investigated the relationship between disposition decisions and covariates, including socioeconomic and demographic profiles, and clinical conditions of patients using multivariate logistic regression. We estimated odds ratios and their corresponding 95% confidence intervals (95% CI). 3. Results 3.1. Patients' Demographic and Socioeconomic Characteristics Of the 303 patients included for analysis, 201 (66%) were discharged home while the rest were admitted to a hospital bed. Figure 1 depicts ED disposition by demographic, socioeconomic, and clinical characteristics. More male patients were admitted to a hospital beds, while more females were discharged home; admission to a hospital bed was higher among middle-income patients, those with comorbidities, and patients with no formal schooling. Table 1 details patients' socioeconomic characteristics and association with disposition decisions. The mean age of the patients was 50.9 (SD = 21.4, Range 18 to 101). There was no statistically significant difference between patients admitted to a hospital bed and those discharged home in terms of marital status, residence, household income, employment status, and insurance eligibility. However, patients admitted to a hospital bed included more men, those aged over 50 years, and those with low levels of education. 3.2. Patients' Clinical Conditions and Characteristics Table 2 details patients' clinical conditions and their association with disposition decisions. There was no statistically significant difference between patients admitted to a hospital bed and those discharged home in terms of frequency of visits in a year and those who received help at home when needed. However, there were fewer patients with a history of hospitalization; more patients with 'excellent or very good' and 'fair/good' perceived health, and more patients initially arriving with their own car discharged home compared to those admitted to a hospital bed. In addition, more patients with non-urgent clinical conditions and those triaged with priority level III were discharged home. However, there were more patients with urgent clinical conditions (58.82%), patients with one or more comorbidities (79.41%), and patients with triage level I (16.5%) and level II who were admitted to a hospital bed compared to those discharged home. 3.3. Multivariate Analysis Results Table 3 shows multivariate analysis of ED disposition and covariates. Urgent clinical condition upon arrival at the ED was related to more than twice the chance of being admitted to a hospital bed compared to non-urgent condition (OR 2.37; 95% CI 1.18 to 4.75, p = 0.015). Prior hospitalization within the past 12 months was related to three times the chance of being admitted to a hospital bed compared to having no history of hospitalization (OR 3.02; 95% CI 1.5 to 6.05, p = 0.002). Lower-middle and middle-income households were associated with three times (OR 3.04; 95% CI 1.17 to 7.89, p = 0.02) and five times (OR 5.36; 95% CI 1.9 to 14.9, p = 0.001) higher chances of being admitted, respectively, compared to having a low income. Patients triaged with lower priority acute level were associated with a 72% lower chance of being admitted compared to be assigned a high priority level (OR 0.277; 95% CI 0.07 to 0.99, p = 0.049). 4. Discussion In an attempt fill the evidence gap, this study examined disposition decision-making and its correlates at the ED of a large teaching and referral hospital. The results suggest no statistically significant difference between patients admitted and those discharged home in terms of marital status, residence, employment status, and insurance eligibility. Bivariate analysis, however, suggests that patients admitted to a hospital bed included more men, those aged over 50 years, and those with low levels of education. Household income appeared to be a significant factor related to disposition decision in the multivariate analysis results. Consistent with our findings, there is evidence in the literature of a strong association between elevated admission rates and patients older than 50 years of age . Admission rates have been shown to rise steadily with age in a linear relationship . In addition, patients seeking care at the ED or being admitted to a hospital bed were older compared to those discharged home . Elsewhere, studies document that predisposing factors such as age and education explain, in part, why people choose to visit the ED . However, there is inconclusive evidence on whether these factors were also associated with admission. A systematic review showed that older patients accounted for up to one-quarter of all ED visits with clinical presentation of illness, a high prevalence of cognitive disorders, and the presence of multiple comorbidities, which complicate their evaluation and management . In a systematic review that discussed non-urgent cases in ED, some studies suggested that there is no difference between age groups, while other articles revealed that younger patients presented with more non-urgent conditions . However, non-urgent conditions do not necessarily mean that the patients were not admitted. Consistent with the evidence, our results suggest a mixed relationship between the gender of the patient and disposition decision at the ED. While the bivariate analysis indicates more men were admitted to a hospital bed, adjusting for other factors in the multivariate analysis washed out that association. However, evidence shows a higher admission rate among females compared to males . A systematic review showed that influence of gender was mixed as approximately half of the studies suggest that more men are presented to ED with non-urgent conditions . While visiting the ED does not mean admission to a hospital bed, there is a need for further studies in Saudi Arabia for the logical conclusion of this finding. Adjusting for other covariates, our multivariate analysis results suggest that patients from middle-income households were more likely to be admitted to a hospital bed compared to high-income patients. This finding is consistent with a previous study conducted in Saudi Arabia which showed that patients of similar income brackets were more likely to visit ED with non-urgent conditions . While the difference of categorization in the income between studies may cause confusion, in general, studies in the literature agree that patients with lower-income households are more likely to visit the ED with non-urgent conditions . A plausible reason behind this may be due to the nature of care being free. In addition, the more affluent individuals may prefer to go to a private hospital for faster care. Finally, there may be low-income groups who cannot go to the hospital due lack of transportation. Our study found that patients with urgent clinical conditions upon arrival at the ED were more likely to be admitted to a hospital bed compared to patients arriving with non-urgent conditions. This finding is intuitive given that one would expect patients who visited the ED to have more pressing urgent conditions. This finding appears to be consistent with the pattern of ED utilization, where previous research revealed that poor health status was more likely to be associated with higher utilization of ED services . That said, this may, however, be a facility-specific phenomenon and a mismatch between perceived health status and what they consider urgent. While some patients may require urgent medical attention, most of their needs or demands are non-urgent and potentially preventable with appropriate primary care or timely options elsewhere . The descriptive data in our study show two-thirds of patients visiting the ED were classified as non-urgent, which is worrisome in the sense that non-urgent cases may cause overcrowding in the ED and delay care for cases that may be considered more urgent. The possible reasons behind this issue in Saudi Arabia are primary care short working hours, scheduling, and early appointment issues, insufficient community awareness of the role of the ED, and perceived lack of access to primary healthcare services . To the best of our knowledge, there are no studies in Saudi Arabia which link recent hospitalization with the possibility of being admitted to a hospital bed. We find that compared to having no history of hospitalization, recent hospitalization within the last 12 months was associated with a greater chance of being admitted to a hospital bed. This key factor needs to be considered since multiple studies agree with our finding. Systematic review found two studies that linked immediate hospitalization with lower chance of non-urgent ED visits . We believe that those with prior hospitalization are those with high healthcare needs that require follow-ups and hence, more ED visits and admissions. Elsewhere, there is evidence that patients with comorbidities coupled with previous in-patient admission within 30 days of current ED presentation were more likely to be admitted to a hospital bed . Our results further suggest an association between comorbidities and admission to a hospital bed. Patients with comorbidities were more likely to be admitted to a hospital bed compared to patients who had no comorbidities. This finding is consistent with evidence in the literature in other countries. In Spain, a study that examined increased risk factors linked to hospital admission in a cohort of ambulatory chronic obstructive pulmonary disease (COPD) patients revealed that severity of exacerbations provoking hospital admissions is associated with the presence of significant comorbidity . In the United States, having a comorbidity, including cardiovascular, respiratory febrile illness, and other general medical presenting problems was linked to admission to a hospital bed and overall ED throughput time for patients . A cohort study in Uganda revealed that patients with anemia and compromised consciousness predicted disposition . A study of 174 EDs in France and Belgium indicated that 81.4% of deaths at ED were patients who had chronic underlying diseases, while 46% had previous functional limitations . This may imply that ailments are the ones who end up in the ED of hospitals and admitted to a hospital bed. However, beyond bivariate analysis and controlling for other covariates, we find no relationship between comorbidity and admission, consistent with previous evidence. A study in Singapore showed that chronic conditions have not been a major driver in the increasing number of emergency admissions . The multivariate results suggest that patients triaged with low to moderate priority levels were less likely to be admitted compared to patients who were assigned higher priority level. This may indicate appropriate use of the triage system by the hospital to ration health care. Previous studies indicated that while prevalence of priority level and in triage categories differed across senior and older-seniors, only triage categories contributed moderately to explaining the age-related difference in hospitalization rates after the ED visit . Data in our study were based the Canadian Triage and Acuity Scale (CTAS), but a systematic review and meta-analysis on performance of triage systems in Eds showed that while performance varies considerably when different triage systems are used, there is a reasonable validity for the triage of patients at the ED . 5. Contribution and Limitations In the context of Saudi Arabia, this study contributes to the dearth of evidence on the covariates of the likelihood of a disposition decision at the ED. Our study has limitations, however. First, as a cross-sectional study, the findings provide a snapshot of the analysis and are limited in establishing a true causality between disposition decision and the various covariates considered. Additionally, parts of the patients' information were potentially subject to recall bias, especially in revealing socioeconomic factors such as their level of household income. Moreover, the study was conducted in a single center at a major medical city. Inclusion or comparison with other facilities may present different distributions and associations between variables of interest. Finally, the outcome variable of interest was binary, analyzing admission to a hospital bed or discharged home. Patients who left without being seen, died, or left against medical advice were excluded. Although negligible, the characteristics of those excluded patients might have presented interesting dynamics. 6. Conclusions This study attempted to enhance limited evidence predicting disposition decision-making at the ED of a large teaching and referral hospital. The findings suggest that older patients, males, patients with no or less education, those with fair perceived health, and those who arrived by car with relatives were more likely to be admitted to an ED bed. In addition, patients triaged with higher priority levels, those with comorbidities, urgent conditions, and a prior history of hospitalization were more likely to be admitted. Having proper triage and timely stopgap review measures in the admission process can help scrutinize patients' characteristics and clinical conditions. This will not only better predict and improve the likelihood of dispositioning them to locations that best support their needs but is crucial for the quality and efficiency of the facility. Thus, our findings may be a sentinel indicator that informs overuse or inappropriate use of EDs for non-emergent care, which is a concern in the Saudi Arabian publicly funded health system. We acknowledge that our study was limited to a single large teaching and referral hospital. Thus, there is a need for further research that isolates facility-specific disposition operations as an experiment to assess the comparative practice styles of different ED facilities in the locality. Author Contributions K.A., M.A. and O.B.D. conceptualized study, collected, and curated the data; K.A., S.K. and O.B.D. analyzed data; S.K. and M.A. reviewed analysis; O.B.D. wrote and framed the manuscript; K.A, A.A., S.K. and A.M.A. participated in the writing and editing of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The research committee of King Abdullah Medical Research Center (KAIMRC) granted the original institutional review board (IRB) under research protocol R15/131/R. Informed Consent Statement Not applicable. Data Availability Statement This study used previously collected data. Conflicts of Interest The authors do not have any conflict of interest to report. Abbreviations ED Emergency Department SAR Saudi Arabia Riyals KAMC-KF King Abdulaziz Medical City-King Fahad hospital NGHA National Guard Health Affairs JCI Joint Commission of International Standard QUT Queensland University of Technology IRB Institutional Review Board KAIMRC King Abdullah International Medical Research Center Figure 1 ED disposition by demographic, socioeconomic, and clinical characteristics (%), n = 303. healthcare-11-00667-t001_Table 1 Table 1 Patients' demographic, socioeconomic, and clinical characteristics by disposition decision. Variable Discharged Home (n = 201) Admitted to Bed (n = 102) All Patients (n = 303) p-Value n (%) n (%) n (%) Age category <50 years 109 (54.23) 31 (30.39) 140 (46.2) 0.001 * >=50 years 92 (45.77) 71 (69.61) 163 (53.8) Gender Female 105 (52.24) 42 (41.18) 147 (48.51) 0.044 * Male 96 (47.76) 60 (58.82) 156 (51.49) Marital status Others 69 (34.33) 28 (27.45) 97 (32.01) 0.139 Married 132 (65.67) 74 (72.55) 206 (67.99) Residence Out of Riyadh 32 (16.24) 15 (14.71) 47 (15.72) 0.434 Riyadh 165 (83.76) 87 (85.29) 252 (84.28) Schooling level No schooling 52 (25.87) 48 (47.06) 100 (33) 0.003 * Elementary 23 (11.44) 11 (10.78) 34 (11.22) Primary 65 (32.34) 20 (19.61) 85 (28.05) High school 28 (13.93) 7 (6.86) 35 (11.55) Higher Education 33 (16.42) 16 (15.69) 49 (16.17) Household income (SAR) <3000 46 (24.34) 16 (16.67) 62 (21.75) 0.469 3000 to 5000 62 (32.8) 35 (36.46) 97 (34.04) 5001 to 10,000 49 (25.93) 32 (33.33) 81 (28.42) 10,001 to 15,000 17 (8.99) 7 (7.29) 24 (8.42) >=15,000 15 (7.94) 6 (6.25) 21 (7.37) Employed No 156 (77.61) 81 (79.41) 237 (78.22) 0.42 Yes 45 (22.39) 21 (20.59) -21.78 Insurance NGHA No 15 (7.46) 7 (6.86) 22 (7.26) 0.526 Yes 186 (92.54) 95 (93.14) 281 (92.74) * Implies significant at <5% level. healthcare-11-00667-t002_Table 2 Table 2 Patients' clinical conditions by disposition decision. Variable Discharged Home (n = 201) Admitted to Bed (n = 102) All Patients (n = 303) p-Value n (%) n (%) n (%) History of hospitalization No 143 (71.14) 51 (50) 194 (64.03) <0.001 * Yes 58 (28.86) 51 (50) 109 (35.97) Frequency of ED visits in a year <4 visits 123 (63.4) 58 (57.43) 181 (61.36) 0.191 >=4 or more 71 (36.6) 43 (42.57) 114 (38.64) Health status Poor 5 (2.51) 11 (11) 16 (5.35) <0.001 * V.good/Excellent 81 (40.7) 22 (22) 103 (34.45) Fair/good 113 (56.78) 67 (67) 180 (60.2) Get care when needed No 55 (27.36) 22 (21.57) 77 (25.41) 0.17 Yes 146 (72.64) 80 (78.43) 226 (74.59) Mode arrival at ED Others 5 (2.53) 3 (2.97) 8 (2.68) <0.001 * Ambulance 12 (6.06) 9 (8.91) 21 (7.02) Own car 120 (60.61) 37 (36.63) 157 (52.51) Fam/friend car 61 (30.81) 52 (51.49) 113 (37.79) Urgency of clinical condition Not urgent 148 (73.63) 42 (41.18) 190 (62.71) <0.001 * Urgent 53 (26.37) 60 (58.82) 113 (37.29) Comorbidity None 85 (42.29) 21 (20.59) 106 (34.98) <0.001 * One 96 (47.76) 57 (55.88) 153 (50.5) More than one 20 (9.95) 24 (23.53) 44 (14.52) Triage Acute Scale Priority I 10 (5.0) 16 (16.5) 26 (8.8) <0.001 * Priority II 131 (66.2) 72 (74.2) 203 (68.8) Priority III 57 (28.8) 9 (9.3) 66 (22.4) * Implies significant at <5% level. healthcare-11-00667-t003_Table 3 Table 3 Multivariate analysis of disposition and associated factors. Variable OR 95% CI p-Value Intercept 0.232 0.015 3.649 0.299 Mode of arrival at ED (Ambulance = reference) Others 0.685 0.083 5.676 0.726 Own car 0.623 0.172 2.258 0.471 Family/friend car 1.356 0.362 5.088 0.651 Clinical condition (Non-urgent = reference) Urgent 2.370 1.181 4.756 0.015 * Comorbidity (None = reference) One 0.952 0.393 2.304 0.913 Two 1.356 0.378 4.863 0.640 Gender (Female = reference) Male 1.271 0.624 2.592 0.509 Age category (<= 50 years = reference) >=50 years 1.689 0.654 4.357 0.279 Marital status (Others = reference) Married 0.787 0.354 1.750 0.558 Residence (Outside Riyadh = reference) Riyadh 1.419 0.580 3.473 0.443 Household income SAR (<3000 reference) 3000 to 5000 3.049 1.177 7.898 0.022 * 5001 to 10,000 5.367 1.922 14.989 0.001 * 10,001 to 15,000 3.434 0.725 16.269 0.120 >15,000 1.436 0.242 8.512 0.690 Schooling level (No schooling = reference) Elementary 0.541 0.164 1.784 0.313 Primary 0.657 0.204 2.116 0.481 High school 0.359 0.117 1.104 0.074 Higher Education 0.625 0.165 2.371 0.490 Employement (Otherwise = reference) Employment Employed 1.525 0.534 4.356 0.431 Insurance (Others = reference) Insurance NGHA 1.086 0.271 4.356 0.908 Hospitalization (More than 12 months = reference) Last 12 months 3.026 1.513 6.055 0.002 * Frequency of ED visits (Once = reference) Frequency of ED visits More than once 0.928 0.440 1.957 0.844 Health status (Poor = reference) Very good/Excellent 0.411 0.066 2.563 0.341 Fair/good 0.595 0.125 2.835 0.515 Social healp (No care = reference) Get care when needed 1.206 0.569 2.556 0.625 CTAS (High priority = reference) Moderate priority 0.426 0.153 1.189 0.103 Lower priority 0.277 0.077 0.996 0.049 * * Implies significant at < 5% level. 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PMC10000448 | The enzyme ataxia-telangiectasia mutated (ATM) kinase is a pluripotent signaling mediator which activates cellular responses to genotoxic and metabolic stress. It has been shown that ATM enables the growth of mammalian adenocarcinoma stem cells, and therefore the potential benefits in cancer chemotherapy of a number of ATM inhibitors, such as KU-55933 (KU), are currently being investigated. We assayed the effects of utilizing a triphenylphosphonium-functionalized nanocarrier delivery system for KU on breast cancer cells grown either as a monolayer or in three-dimensional mammospheres. We observed that the encapsulated KU was effective against chemotherapy-resistant mammospheres of breast cancer cells, while having comparably lower cytotoxicity against adherent cells grown as monolayers. We also noted that the encapsulated KU sensitized the mammospheres to the anthracycline drug doxorubicin significantly, while having only a weak effect on adherent breast cancer cells. Our results suggest that triphenylphosphonium-functionalized drug delivery systems that contain encapsulated KU, or compounds with a similar impact, are a useful addition to chemotherapeutic treatment schemes that target proliferating cancers. ataxia-telangiectasia mutated kinase cancer stem cells triphenylphosphonium cation Operational Program "Competitiveness, Entrepreneurship and Innovation"NSRF 2014-2020 GSRT Greece and the European Union (European Regional Development Fund)MIS 5002567 NCSREE11968 Regione Lazio PROGETTI DI GRUPPI DI RICERCA 2020A0375-2020-36597 Associazione Italiana per la Ricerca sul CancroD.B. and C.C.AIRC-IG2021-n.26230 Italian Ministry of HealthRF-2016-02362022 A.K. was funded by the Operational Program "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by GSRT Greece and the European Union (European Regional Development Fund), project MIS 5002567, implemented under the "Action for the Strategic Development on the Research and Technological Sector" initiative. This work was partially supported by NCSR internal project No EE11968, entitled "Synthesis and characterization of nanostructured materials for environmental applications". V.S. was supported by a research grant from Regione Lazio PROGETTI DI GRUPPI DI RICERCA 2020, project ID: A0375-2020-36597. This work has been supported by research grants from Associazione Italiana per la Ricerca sul Cancro AIRC-IG2021-n.26230, and the Italian Ministry of Health, RF-2016-02362022. The work of D.B. and C.C. was also supported by AIRC-IG2021-n.26230. pmc1. Introduction Resistance to genotoxic therapies has been associated with increased DNA damage response (DDR) signaling, and many cancer defects in certain components of the DDR are highly dependent on the remaining DDR pathways for survival . The enzyme ataxia-telangiectasia mutated (ATM) kinase is a key mediator of DDR, and its inhibition has become an attractive therapeutic concept in cancer therapy for the sensitization of cancer cells to chemotherapeutic drugs. In particular, cancer stem cells (CSCs) have been gathering increasing attention over the past decade as they play a crucial role in tumor progression, metastasis, and drug resistance . It has been well documented that ATM kinase inhibition sensitizes cells to the cytotoxic effects of DNA double-strand break-inducing chemotherapeutic agents, including the topoisomerase II inhibitors etoposide, doxorubicin, and amsacrine, the topoisomerase I inhibitor camptothecin, and PARP inhibitors . Furthermore, the ATM inhibitor KU-55933 (KU) was shown to sensitize p53-deficient cholangiocarcinoma cells to genotoxic agents, including gemcitabine, 5-fluorouracil, cisplatin, and doxorubicin. This sensitization was more potent when KU was combined with ATR (ataxia-telangiectasia mutated and Rad3-related kinase) inhibitor VE-821 . KU has also been reported to block the phosphorylation of protein kinase B (Akt) and inhibit MDA-MB-453 and PC-3 cell proliferation , as well as to attenuate the phosphorylation and activation of AMP-activated protein kinase in a rat hepatoma cell line . The inhibition of Akt was confirmed and extended when it was shown that glucose uptake, glycolysis, epithelial to mesenchymal transition, motility, and the proliferation of aggressive breast and prostate cancer cell lines with high Akt activity were blocked by KU . Interestingly, ATM kinase is also an essential signaling mediator that enables the growth of cancer stem cells. Thus, the potential benefits of a number of ATM inhibitors, such as KU-55933 (KU), in overcoming the resistance of CSCs to chemotherapeutic agents are currently being investigated . It has been found that the application of this ATM inhibitor effectively decreases the radiation resistance of the tumorspheres of cancer initiating cells, which are stem-like cells . In fact, ATM is known to sustain the mammospheres of cancerous cells and are considered model CSC systems that are also known to exhibit high resistance to genotoxic agents, such as doxorubicin (DOX) . ATM function is linked to mitochondria. It is well known that it regulates mitochondrial function and mitophagy . In this connection, studies on the action of KU on cell lines have shown that its administration reduces the mitochondrial membrane potential and perturbs the tricarboxylic acid (TCA) cycle and oxidative phosphorylation . KU has also been shown to suppress the proliferation of Hep G2 and SMMC-7721 cells by inducing mitochondrial dysfunction and by enhancing 5'-adenosine monophosphate-activated protein kinase (AMPK) phosphorylation . Nutlin-3 (an MDM2 inhibitor that leads to non-genotoxic p53 activation) and KU synergize to induce apoptosis in a number of cancer cell types, including colorectal cancer cell lines, but do not kill non-transformed cells. The mechanism of cell death activation entails the blocking of autophagy and a consequent accumulation of both mitochondria and reactive oxygen species (ROS) . It has also been reported that the inhibition of ATM with KU depleted mitochondrial DNA in wild-type fibroblasts . Therefore, ATM suppression would be advantageous in eradicating cancer cells, in particular CSCs, but disadvantageous for normal cells because its function is indispensable in DNA repair, in preserving mitochondrial functionality, and in the selective removal of damaged mitochondria . Consequently, there is a need of a delivery system for ATM inhibitors that, ideally, specifically targets cancer stem cells. The essential role of mitochondria in cell function and the fact that mitochondrial dysfunctions are associated with a number of pathologies, including cancer, had led to the growth of so-called mitochondrial medicine and, in parallel with this, to the development of systems capable of the accurate and efficient delivery of therapeutic agents and/or imaging agents to mitochondria. A number of mitochondriotropic moieties, i.e., moieties that can target mitochondria, have already been identified, from mitochondria-penetrating peptides to delocalized lipophilic cations, such as the well-studied triphenylphosphonium cation (TPP). In the latter case, mitochondrial internalization is caused by the delocalized positive charge of the TPP and the large negative membrane potential of the mitochondria (DPsm = 150-180 mV) . Mitochondrial targeting by drugs has been achieved by employing these mitochondriotropic agents, either by their direct conjugation with bioactive molecules or by their conjugation with a variety of drug-loaded delivery systems . Previous studies by our group have indicated that TPP-functionalized hyperbranched polyethylenimine nanoparticles (PTPP) can encapsulate DOX and target mitochondria, causing severe cytotoxicity at low DOX concentrations . Interestingly, this nanocarrier also showed selective cytotoxicity against mammospheres that depended on the expression of the gene encoding ATM kinase . In this context, it has been reported that the enhanced tolerance of CSCs to chemotherapeutics or radiation correlates well with the changes in membrane potential, and that cells with higher membrane potential are more prone to continue dividing and form tumors compared with cells with lower membrane potentials . Therefore, TPP-functionalized carriers may also have the ability to target cells with high membrane potential, such as CSCs . Indeed, TPP-functionalized nanoparticles have shown that cell internalization is dependent on cell membrane potential, which enables them to be internalized preferably to cancerous but not to non-cancerous cells . In this current study, we explore whether encapsulating an ATM inhibitor in a TPP-functionalized hyperbranched polyethylenimine nanocarrier can be effective against the mammospheres of drug resistant breast cancer cells--a close analogue to CSCs--without having considerable toxic effects against adherent cells. We further explore the resistance of mammospheres derived from breast cancer cell lines against DOX chemotherapy and the therapeutic benefit of ATM inhibition upon administration of the water insoluble ATM kinase inhibitor KU, encapsulated in the PTPP nanocarrier (PTPP-KU). 2. Materials and Methods 2.1. Chemicals and Reagents RPMI-1640 medium, penicillin/streptomycin, L-glutamine, phosphate buffer saline (PBS), and trypsin/EDTA were all purchased from Biochrom (Berlin, Germany), while HyClone fetal bovine serum was obtained from Invitrogen (Carlsbad, CA, USA). Dimethyl sulfoxide (DMSO) and MTS solution were purchased from Merck KGaA (Calbiochem(r), Darmstadt, Germany) and Promega Corp. (Madison, WI, USA), respectively, while 2-Morpholin-4-yl-6-thianthren-1-yl-pyran-4-one (KU-55933) was obtained from Sigma-Aldrich Ltd. (Poole, UK). Doxorubicin (D1515) was purchased from Sigma-Aldrich Corp. (St. Louis, MO, USA). 2.2. Preparation and Characterization of KU-Loaded PTPP Nanoparticles The introduction of decyltriphenylphosphonium groups to hyperbranched polyethylenimine (PTPP) has been detailed in our previous publications . Given that both PTPP and KU are practically water insoluble, a co-precipitation method was established for either the formation of PTPP nanoparticles or the encapsulation of KU in the PTPP nanoparticles, entailing the drop-wise addition of 100 mL DMSO solution of PTPP and KU (KU concentration 7 mM, PTPP concentration 7 mg/mL) in 10 mL RPMI medium under vigorous stirring. In a similar manner, empty PTPP nanoparticles were prepared by the drop-wise addition of 100 mL DMSO solution of PTPP (7 mg/mL) in 10 mL RPMI under vigorous stirring. In all cases, the obtained nanoparticles were centrifuged and redispersed in the appropriate amount of RPMI for obtaining, after bath sonication for ~20 s, typical nanoparticle dispersions of 100 mM KU and of 100 mg/mL PTPP, or empty PTPP nanoparticles of the same concentration. The PTPP concentrations in their dispersions were determined by dissolving them in ethanol and registering their absorbance at 275 nm and using the respective PTTP calibration curves in ethanol. For the determination of both the PTPP and KU concentrations in the respective nanoparticle dispersions, first order derivative spectroscopy was employed. Specifically, the spectra of both compounds separately, or of their mixtures in ethanol, were acquired and processed to obtain the first derivative spectra. The wavelengths 329 nm and 278 nm were selected for the KU and PTPP determinations, respectively, as at these wavelengths there is no interference from the other compound. Similarly, the derivative spectra of standard solutions were obtained, and the respective calibration curves for each compound at these wavelengths were also derived. The mean hydrodynamic radii of the dispersions of the PTPP and PTPP-KU nanoparticles in RPMI were determined using dynamic light scattering (DLS) (AXIOS-150/EX, Triton, Hellas, 50 mW laser source at 658 nm, Avalanche photodiode detector at an angle of 90deg). 2.3. Cell Culture and Treatments Human breast cancer cell lines MCF-7, MDA-MB-231, and SKBR3, obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA), were grown as described previously . Briefly, cells were cultured in RPMI-1640 containing 2 mM L-glutamine and 1% penicillin/streptomycin and supplemented with 10% HyClone fetal bovine serum at 37 degC in a humidified CO2 incubator (5%). The treatment concentrations in all the experiments always refer to the KU concentration in mM, while the concentration of PTPP always follows the same ratio with respect to KU (i.e., KU concentration 1 mM, PTPP concentration 1 mg/mL). 2.4. Mammosphere Cultures Single cell suspensions of breast cell lines MCF-7 and MDA-MB-231 were grown in ultralow attachment 6-well plates (Corning) at a density of 4000 cell/mL in mammosphere medium (Dulbecco's modified Eagle's medium/F-12, containing 5 mg/mL insulin (Sigma), B27 (Invitrogen), 20 ng/mL epidermal growth factor (GIBCO), 10 ng/mL basic fibroblast growth factor (GIBCO), and 0.4% bovine serum albumin (Sigma)), as described in . After 10 days, the diameters of the mammospheres were measured in phase contrast pictures (ZOE) using the ImageJ software. The mammospheres (diameter > 50 mm) were counted and the efficiency of mammosphere formation was evaluated (%SFE = number of mammospheres/number of plated cells x 100). Mammosphere pellets were collected by gentle centrifugation (900 rpm, 5 min) to further analyze for protein extraction and DOX uptake. 2.5. MTS Assay The cell viability of the MCF-7 and MDA-MB-231 and their derived mammospheres under normal and treatment conditions was measured using the MTS assay. In brief, cells were transferred into a single-cell suspension and plated into ultralow 96-well plates with a density of 400 cells/100 mL per well for the mammospheres, and, in adhesion conditions, in a TC-treated well at a density 1000 cells/100 mL medium. The cells were cultured in mammosphere medium and treated with different doses of KU, PTPP, or PTPP-KU at 37 degC for 30 min before DOX (1 mM) was added. After 24 h, the wells were washed with RPMI, and MTS solution was added to each well and incubated at 37 degC for 3 h. Finally, the optical density (OD) was measured at a wavelength of 492 nm and the survival rates were calculated. 2.6. Quantification of DOX Uptake The adherent cells and mammospheres in the 96 well plates were treated with KU (5, 10 mM), PTPP (5, 10 mg/mL), and PTPP-KU (PTPP concentrations: 5, 10 mg/mL, KU concentrations: 5, 10 mM, respectively) for 30 min, and then DOX (1 mM) was added. In addition to the control, we also had a number of wells with cells treated only with 1 mM DOX. After 3 h, the wells were washed with RPMI (without phenol red) and the DOX concentration was measured with an Infinite M200 plate reader (Tecan, Switzerland, lex = 510 nm, lem = 580 nm). Throughout the experiment, a medium without phenol red (colorless) was used to avoid any interference with the final DOX concentration measurement. 2.7. Western Blotting (WB) The cells were lysed in RIPA buffer (50 mM Tris-HCl pH 8.0, 150 mM NaCl, 1% NP40, 1 mM EGTA, 1 mM EDTA, 0.25% sodium deoxycholate) supplemented with protease and phosphatase inhibitors (Roche Diagnostic, Mannheim, Germany). Proteins were resolved by 10% SDS PAGE (about 30 mg of extract per lane was loaded) and transferred onto a nitrocellulose membrane (Protran BA83, GE Healthcare, Chicago, IL, USA) using a semi-dry system (Bio-Rad Laboratories S.r.l., Segrate, Italy). Blocking and antibody incubations were performed at room temperature in TBS containing 0.1% Tween 20 and 5% low fat milk for 1 h. The following antibodies were used: rabbit anti-PARP (Cell Signaling Technology, Danvers, MA, USA), mouse anti-ATM (Cell Signaling Technology, Danvers, MA, USA), anti-rabbit-pS15 p53 (Cell Signaling Technology, Danvers, MA, USA), and rabbit anti-Vinculin (Cell Signaling Technology, Danver, MA, USA). HRP-conjugated secondary antibodies (Bio-Rad Laboratories S.r.l., Segrate, MI, Italy) were revealed using the Clarity Western ECL Substrate (Bio-Rad Laboratories S.r.l., Segrate, Italy). 2.8. Statistical Analysis Data are presented as mean +- standard deviation. All experiments were performed independently at least three times. Statistical significance for the various treatments was assessed using a Student's t-test in GraphPad Prism (GraphPad Inc., La Jola, CA, USA). Significance was defined as * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, using a Student's t-test. 3. Results The functionalization of hyperbranched polyethylenimine with decyltriphenylphosphonium groups endows amphiphilicity to hydrophilic macromolecules, which is the basis of their self-assembly into nanoparticles in aqueous media. Due to its lipophilic character, the water-insoluble KU resides in PTTP nanoparticles whose chemical structure encompasses both hydrophilic (i.e., ethylene imine) and hydrophobic (i.e., decyltriphenylphosphonium) entities, the properties of which endow the solubilizing (or encapsulating) properties of nanoparticles. Thus, PTTP nanoparticles encapsulating KU, which is known to be insoluble in aqueous buffers, were formed in RPMI. They had a mean hydrodynamic radius of about 60 nm, as was revealed by DLS experiments . For comparison, empty PTPP nanoparticles formed under the same conditions were slightly smaller, i.e., 55 nm . The KU loading was found to be 28.3% w/w corresponding to a KU concentration 1 mM when the PTPP concentration was 1 mg/mL. To investigate the ability of these PTTP nanoparticles encapsulating KU to sensitize breast cancer cells to doxorubicin (DOX), we took advantage of the human breast adenocarcinoma cell line MCF-7 (luminal estrogen receptor-positive HER2-low), cultured either as adherent cells ("Adh") or as tumor spheres (mammospheres, "MS"), which are a more suitable cellular model compared with adherent cells in that they more closely approximate the resistance to anticancer therapy of breast cancer cells . Herein, we co-treated adherent MCF-7 cells and mammospheres with DOX at 1 mM and increasing concentrations of PTTP, PTTP-KU, and free KU . Cell viability was measured as the percentage of the control treated with PTTP, PTTP-KU, or free KU, plus DOX, normalized to the same treatment without DOX . As expected, the mammospheres were more resistant to DOX treatment compared with the adherent cells, which showed a reduction in cell viability of 30-40% compared with the non-treated (NT) cells . We have previously reported that PTTP is effective in inhibiting the growth of cancer stem-like structures such as mammospheres . It is of note that we confirmed these results, and that we also demonstrated that PTTP alone as well as PTTP-KU were slightly toxic to the adherent cells at all concentrations tested, and show considerable toxicity (ca 70%) to mammospheres (MS) only at a high concentration (10 mg/mL) . These results are consistent with those of previous studies which have indicated that the treatment of TPP-functionalized moieties increases cytotoxicity in cells grown in mammosphere conditions compared with cells grown in adherence conditions . We attribute the observed toxicity to the fact that PTPP is preferentially internalized in the mitochondria of mammospheres, leading to an increase in mitochondrial stress . Herein, we found that PTTP treatment can also effectively induce sensitization to DOX treatment in mammospheres, with a dose-dependent reduction in cell viability in DOX treated cells of about 40% at lower doses (1 mM) and 60% at higher doses (10 mM) , compared with a reduction of only 10% at higher doses (10 mM) in adherent cells treated with DOX . Interestingly, the results demonstrated that PTTP-KU is more effective in sensitizing resistant mammosphere cells to DOX, compared with adherent cells or mammospheres treated with PTTP alone . In mammospheres derived from MCF-7 cells, PTTP-KU co-treatment with DOX led to a significant reduction of 50% of cell viability at 1 mM and to a reduction of 80% at 10 mM. This reduction in cell viability was evident from our observations of the morphology of the mammospheres which showed a significant reduction in mammosphere size after five days of culture following treatment at low concentrations (PTPP-KU 1mM) and at higher concentrations (PTPP-KU 5mM) . It is of note that free KU is not able to sensitize cells to DOX treatment , which suggests that encapsulated ATM inhibitors play a specific and functional role in sensitizing resistant breast cancer cells to anticancer therapies. It is well known that DOX uptake in cells is correlated with the ability of drugs to induce cell toxicity inside the cell . Moreover, several papers have demonstrated that mammosphere resistance to anti-cancer drugs is also correlated with an impaired uptake of drugs in the cells . We consistently asked whether the PTPP-KU-dependent increased sensitivity to DOX treatment in the mammospheres could correlate with an increased DOX uptake in the cells. In Figure 3A,B, we quantified the DOX uptake in the cells treated with PTTP, PTTP-KU, and free KU at 5 mM and 10 mM, co-treated with 1 mM DOX . After washing the cells, we measured the DOX-dependent fluorescence emission . Compared with the free DOX treatment, the treatment with PTTP and PTTP-KU at 10 mM led to a 30-50% increase in DOX uptake in the adherent condition . Interestingly, co-treatment with PTTP-KU at 5 mM and 10 mM led to an increase DOX uptake of about 20-50% in the mammospheres in a dose-dependent manner, compared with mammospheres treated with free DOX. Conversely, treatment with PTTP or free KU did not increase DOX uptake. These results suggest that the encapsulation of the ATM inhibitor in this specific drug delivery system leads to an increased uptake of DOX that is correlated with an increase in the sensitivity of mammospheres to DOX treatment. To verify whether encapsulated KU efficiently inhibits ATM kinase activity, we decided to look at a well-known marker of ATM kinase activation, the autophosphorylation on serine 1981, and also at the phosphorylation of p53 at Ser 15 (phospho-S15), which is activated by DNA damage induced by DOX treatment. We performed a Western blot analysis using phospho-S1981 ATM antibodies and phosho-S15 p53-specific antibodies to investigate ATM kinase signaling activation upon DOX stimulation with or without PTTP, PTTP-KU, or free KU treatment . As expected, and as is shown in Figure 4, the ATM kinase phosphorylation on S1981 induced by the DOX treatment was inhibited in the mammospheres derived from the MCF-7 co-treated with free KU inhibitor . As expected, the PTTP-KU treatment, as well as free KU treatment, was able to reduce the ATM kinase phosphorylation on S1981 induced by the DOX treatment more efficiently than PTPP alone. It is of note that PTTP also reduced ATM phosphorylation on S1981, indicating a role of this nanoparticle in modulating ATM kinase activity (see Discussion section). Moreover, DOX stimulation induced phosphorylation on S15 of p53, a well-known ATM substrate. Unexpectedly, p53 phosphorylation on S15 induced by DOX stimulation was slightly reduced by treatment with all the compounds (PTPP, PTTP-KU, and free KU), and total p53 was stabilized after DOX induction in all samples, suggesting that the effect on cell viability of different treatments is independent of p53 status (see Discussion section). We consequently looked at the PARP protein under different conditions as a marker of the cell death process . We could not detect a reduction in PARP protein levels after DOX treatment because, as expected, mammospheres are resistant to DOX treatment . Interestingly, we observed a reduction in PARP levels in samples co-treated with DOX and PTTP-KU, suggesting that only PTTP-KU is able to sensitize mammospheres to DOX treatment, according to the results obtained in Figure 1. Since p53 has a central role in regulating the DOX sensitivity of breast cancer resistant cells , and we found that phosphorylation on S15 of p53 is also inhibited by empty PTTP nanoparticles, we wanted to clarify the role of p53 in the sensitization of mammospheres to DOX treatment. To evaluate the necessity for intact p53 function, we also utilized cell lines with mutant p53. We therefore performed viability experiments in mammospheres derived from p53 WT cells (MCF-7) or mutant p53 cells (SKBR3 and MDA-MB-231 cells). We co-treated the cells with DOX (1 mM) and with increasing doses of PTTP, PTTP-KU, or free KU . Interestingly, PTPP-KU sensitized the mammospheres derived from all the above cell lines to DOX in a dose-dependent manner, suggesting that the role of PTPP-KU in sensitizing resistant mammospheres to DOX is independent of p53 status. 4. Discussion Doxorubicin is a tetracycline antibiotic commonly used in the treatment of breast cancer, and it induces DNA damage by the inhibition of topoisomerase II and free radical generation as an anticancer mechanism . Doxorubicin has severe side effects, including acute toxicity to normal tissue and cardiotoxicity, and its therapeutic effects can be minimized by the inherent multidrug resistance (MDR) of many tumor cells, in particular of breast cancer stem cells . The MDR of breast cancer stem cells is a major challenge to successful chemotherapy, and mitochondria-targeting therapy represents a promising strategy that may enable us to overcome MDR . There are various mechanisms associated with MDR, often involving acquired and intrinsic resistance. Unlike acquired MDR, which mechanism was originated from the overexpression of P-glycoprotein (P-gp), an ATP-dependent efflux pump, intrinsic MDR is often attributed to genetic or epigenetic changes which perturb the apoptosis signaling pathway . Generally, the intrinsic pathway of apoptosis is often initiated at the mitochondria, making the mitochondria of MDR cancer cells an attractive intracellular target. Herein, we have demonstrated via viability MTS assays and by PARP level, that encapsulating an ATM inhibitor (KU) in a previously developed TPP-functionalized drug delivery system (PTPP) is an effective means of sensitizing mammospheres to doxorubicin in a dose-dependent way . Interestingly, we were also able to show that ATM inhibition using the PTPP-KU carrier increases DOX uptake in mammospheres . Drug resistance depends on mitochondria since, in general, mitochondrial function has been shown to control the susceptibility of MCF-7 and MDA-MB-231 cells to doxorubicin and paclitaxel . The targeting of the mitochondrial metabolism has been shown to suppress doxorubicin resistance by controlling the drug efflux . Therefore, the increased DOX uptake can tentatively be attributed to a reduced drug efflux. In line with this, it has been reported that an ATM inhibitor (AZ32) could influence multidrug resistance . TPP-functionalized drug carriers are known to effectively target and be internalized by cells and organelles with large negative membrane potentials (a characteristic of rapidly proliferating malignant cells such as CSCs , as well as of mammospheres that are their close analogue). Our results are, therefore, consistent with an enhanced impact of the nanocarrier PTPP on mammosphere cells, which can be attributed to the large negative membrane potential of the mammosphere cells. Furthermore, this study demonstrates that (a) ATM has an essential role in the enhanced resistance of mammospheres to anthracycline treatment, and (b) that a mitochondriotropic nanocarrier is effective in abolishing the resistance of mammospheres to anthracycline treatment. It has been demonstrated that ATM kinase is involved not only in DNA repair pathways, but also in the oxidative stress responses induced by several anti-cancer drugs , suggesting that ATM kinase plays a role in regulating mitochondrial functions. Enhanced DNA repair via efficient ATM kinase signaling is a well-known mechanism that contributes to doxorubicin resistance in cancer, but in this work, for the first time, we also described the role of mitochondria-targeting polymeric nanoparticles in sensitizing resistant cells to doxorubicin. Moreover, we hypothesize that ATM kinase activity could protect cells from DOX-induced mitochondrial damage and that directing this nanocarrier to mitochondria could reverse this function. Consequently, both increased DOX internalization and reduced DNA repair due to the inhibition of ATM kinase activity results in the observed toxicity. This protective effect of ATM on cancer tumorsphere cells can be attributed to the induction of cell stress signaling networks through a mechanism mediated by ATM. Indeed, the nature of the main components of the mammalian stress response allows malignant tumor cells, especially upon exposure to drugs and cytotoxic conditions, to activate a phenotypic switch and pass into the tumorsphere state, whereby participating neoplastic cells take up properties of stem and progenitor cell clones, permitting at least a part of a malignant tumor to survive not only drug treatment , but also some "last generation" treatment schemes, including apoptosis inducers and, notably, immunotherapy , especially therapy employing immune checkpoint inhibitors . Thus, drug-induced cell stress allows malignant tumors to escape from antineoplastic treatment. Although in normal cells doxorubicin and ATM converge on the activation of p53 , we here observed that, in the breast cancer cells used in this study, the impact of mitochondrial targeting, ATM inhibition, and the suppression of doxorubicin resistance were independent of the p53 status of the cells . This can be attributed to the multiplicity of ATM signaling networks related to the cell stress response. Even though ATM was previously shown to regulate mitophagy , which is a macromolecular degradation system that is involved in several major regulatory mechanisms, including the proteostatic stress response, and helps redistribute cellular materials to enable cells to adapt to adverse conditions, this is not the only role ATM plays in the cell stress response (although this may be a key role of ATM in the metabolic adaptation of mammospheres). There are other aspects of ATM's function that also link apparently unrelated mechanisms to one another . One example of this complexity can be illustrated by the activation of immune checkpoint function by the network of ATM interactions. On the one hand, it mediates the induction of transactivator nuclear factor-kB (NF-kB), leading to an increase in checkpoint inhibitor PD-L1 expression . On the other hand, ATM activity is mutually dependent on PD-L1 expression, making ATM a central node between immune checkpoint function and DNA repair . It must be noted that NF-kB itself can sustain breast cancer CSC, anthracycline resistance, and drug efflux, as well as the escape of cancer cells from host tissue restrictions and from several components of the immune response . Importantly, it activates chromatin epigenetic changes that sustain these mechanisms over time, far beyond one single cell division . It can therefore be expected that the inhibition of ATM impairs multiple mechanisms of survival in cancer cells, which are not limited to metabolic adaptation to cell stress, or to drug internalization, but which also include escape from the immune system and from host tissue biological surveillance. 5. Conclusions In conclusion, our results have demonstrated that the encapsulation of an ATM inhibitor in a mitochondriotropic nanocarrier has the capacity to suppress doxorubicin resistance in breast cancer mammospheres independently of the cells' p53 status. A notable effect of this combination is a substantial increase in the internalization of doxorubicin, suggesting that this strategy can potently reverse MDR in breast cancer stem cells. ATM now emerges as a pivotal regulator of breast cancer stem cell responses to stress signals, especially those signals that are induced by drugs used in antineoplastic treatment. We expect that our discovery will contribute to the development of important translational approaches to breast cancer, given the substantial therapeutic importance of breast cancer stem cells in mediating resistance to anti-cancer therapies . Overall, we strongly believe that further investigation of the role of ATM kinase-dependent functions could be useful and lead to the design of new strategies for overcoming MDR in breast cancer stem cells. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Hydrodynamic size distribution of PTPP and PTPP-KU nanoparticles in RPMI-1640 media supplemented with 10% fetal bovine serum, Figure S2: Cell viability of the MCF-7 cell line grown in adherent cells (Adh) and in mammosphere (MS)conditions, Figure S3: Mammosphere morphology after treatment with 1 mM of DOX and free KU, PTPP-KU, and PTPP, Figure S4: Raw data of Figure 3, Figure S5: Original Western blot. Click here for additional data file. Author Contributions Conceptualization, V.S., S.A.V. and D.T.; writing--original draft preparation, V.S., S.A.V., Z.S., A.K. and D.T.; writing--review and editing, V.S., S.A.V., D.B., Z.S. and D.T.; funding acquisition, Z.S. and A.K.; investigation, V.S., C.C., R.L.S., Z.S. A.K., and D.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 Data are contained within the article and supplementary material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 PTPP-KU sensitization of mammospheres to doxorubicin compared with non-treated (NT) cells. Cell viability of the MCF-7 cell line grown (A) in adherent (Adh) and (B) in mammosphere (MS) conditions. Cells were treated with 1 mM of doxorubicin (DOX) for 3 h and various doses of free KU-55933 (KU), PTPP-KU, and PTPP (administered 30 min before adding DOX), as indicated. After 24 h, cell viability was measured using an MTS assay. The results are expressed as the mean +- SD for at least three independent experiments and were analyzed using a Student's t-test (* p < 0.05, ** p < 0.01, *** p < 0.001, ns not significant). Figure 2 Reduction in mammosphere size caused by PTPP-KU after doxorubicin treatment compared with non-treated (NT) cells. (A) Optical microscopy images (20X) representative of the mammospheres' morphology after treatment with 1 mM of DOX for 3 h and free KU (1 mM), PTPP-KU (1 mM), and PTPP (1 mg/mL), administered 30 min before adding DOX. Scale bar 150 mm. (B) Graph representing the percentage of mammospheres (diameter > 50 mm with rounded morphology) obtained from 5000 cells/mL in triplicate wells, with or without treatment. The results are expressed as the mean +- SD for at least three independent experiments and were analyzed using a Student's t-test (* p < 0.05, ** p < 0.01, **** p < 0.0001; statistical analysis is not shown if it is not considered significant) (n = 4). (C) Graph representing the mammosphere diameters after the treatments described in (A). Figure 3 Doxorubicin internalization compared with non-treated (NT) cells. (A) Adherent cells (Adh) and (B) mammospheres (MS) in 96 well plates were treated with KU (5, 10 mM), PTPP (5, 10 mg/mL), and PTPP-KU (KU: 5, 10 mM; PTPP 5, 10 mg/mL) for 30 min before adding DOX, 1 mM. After 3 h, the wells were washed with RPMI without phenol red, and the DOX concentration was measured with an Infinite M200 plate reader (Tecan, Switzerland, lex = 510 nm, lem = 580 nm) and expressed as fluorescence intensity in arbitrary units (a.u.). The results are expressed as the mean +- SD for at least three independent experiments and were analyzed using a Student's t-test (** p < 0.01, *** p < 0.001, ns not significant). Statistical analysis is not shown if it is not considered significant (n = 3). Figure 4 ATM activation and apoptosis induction in mammospheres co-treated with DOX and PTPP-KU. Representative Western blot of total protein extracts, performed after 24 h, from mammospheres derived from MCF-7 cells treated with DOX (1 mM) for 3 h and immunoblotted for the indicated antibodies (n = 3). Figure 5 PTPP-KU sensitizes p53 WT and mutant p53 mammospheres to DOX. Cell viability of (A) MCF-7, (B) SKBR3 and (C) MDA-MB-231 cell lines grown in mammosphere (MS) conditions. Cells were treated with 1 mM of Doxorubicin (DOX) for 3 hours with increased concentrations of free KU-55933 (KU), PTPP-KU, and PTPP (administered 30 min before adding DOX), as indicated (the corresponding PTPP concentrations were 1 mg/mL, 5 mg/mL, and 10 mg/mL, respectively). After 24 h, cell viability was measured using an MTS assay. The results are expressed as the mean +- SD for at least three independent experiments and were analyzed using a Student's t-test (*** p < 0.001) (n = 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. |
PMC10000449 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050689 cells-12-00689 Communication Inflammatory Cell Dynamics after Murine Femoral Artery Wire Injury: A Multi-Parameter Flow Cytometry-Based Analysis Pamulapati Vivek Methodology Formal analysis Investigation Writing - original draft Writing - review & editing Visualization 1 Cuda Carla M. Methodology Formal analysis Investigation Data curation Writing - review & editing 2 Smith Tracy L. Methodology Formal analysis Investigation Data curation Writing - review & editing 1 Jung Jonathan Data curation Writing - review & editing Visualization 1 Xiong Liqun Methodology Investigation Writing - review & editing Visualization 1 Swaminathan Suchitra Methodology Formal analysis Investigation Writing - review & editing Visualization 2 Ho Karen J. Conceptualization Formal analysis Writing - original draft Writing - review & editing Supervision Project administration Funding acquisition 1* Das Anindita Academic Editor Samidurai Arun Academic Editor 1 Division of Vascular Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA 2 Division of Rheumatology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA * Correspondence: [email protected] 22 2 2023 3 2023 12 5 68911 11 2022 15 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 ). An acute inflammatory response following arterial surgery for atherosclerosis, such as balloon angioplasty, stenting, and surgical bypass, is an important driver of neointimal hyperplasia after arterial injury, which leads to recurrent ischemia. However, a comprehensive understanding of the dynamics of the inflammatory infiltrate in the remodeling artery is difficult to attain due to the shortcomings of conventional methods such as immunofluorescence. We developed a 15-parameter flow cytometry method to quantitate leukocytes and 13 leukocyte subtypes in murine arteries at 4 time points after femoral artery wire injury. Live leukocyte numbers peaked at 7 days, which preceded the peak neointimal hyperplasia lesion at 28 days. Neutrophils were the most abundant early infiltrate, followed by monocytes and macrophages. Eosinophils were elevated after 1 day, while natural killer and dendritic cells gradually infiltrated over the first 7 days; all decreased between 7 and 14 days. Lymphocytes began accumulating at 3 days and peaked at 7 days. Immunofluorescence of arterial sections demonstrated similar temporal trends of CD45+ and F4/80+ cells. This method allows for the simultaneous quantitation of multiple leukocyte subtypes from small tissue samples of injured murine arteries and identifies the CD64+Tim4+ macrophage phenotype as being potentially important in the first 7 days post-injury. mice femoral artery inflammation hyperplasia angioplasty leukocyte count flow cytometry macrophages neutrophils monocytes eosinophils dendritic cells National Heart, Lung and Blood InstituteR03HL146880 R01HL153306 T32HL094293 National Institute of Allergy and Infectious DiseasesR01AI170938 American College of Surgeons and Society for Vascular SurgeryAmerican Heart AssociationRheumatology Research FoundationNorthwestern University Robert H. Lurie Cancer Center Flow Cytometry FacilityNational Cancer InstituteP30CA060553 This work was supported by the National Heart, Lung and Blood Institute (R03HL146880 and R01HL153306 to K.J.H. and T32HL094293 to V.P.), National Institute of Allergy and Infectious Diseases (R01AI170938 to C.M.C.), American College of Surgeons and Society for Vascular Surgery (Career Development Awards to K.J.H.), American Heart Association (Postdoctoral Fellowship to T.L.S.), Rheumatology Research Foundation (Innovative Research Award to C.M.C.), the Northwestern University Robert H. Lurie Cancer Center Flow Cytometry Facility, and the National Cancer Institute (P30CA060553). pmc1. Introduction Surgical interventions for atherosclerosis, such as balloon angioplasty, bypass grafting, and stenting, are considered a form of acute arterial "injury." Transluminal endothelial disruption exposes the underlying extracellular matrix, leading to rapid deposition of platelets, coagulation proteins, and leukocytes. The ensuing thrombo-inflammatory response is characterized by leukocyte recruitment, the elaboration of cytokines, and vascular smooth muscle cell activation and phenotype switch, which can lead to the subsequent development of neointimal hyperplasia, a common cause of restenosis and recurrent ischemia requiring reoperation or other interventions . In humans, the extent of neointimal formation correlates with inflammation , and there is preclinical evidence that modulation of inflammation mitigates neointimal hyperplasia following vascular surgery . Characterizations of the post-injury cellular inflammatory response have commonly relied on the quantitation of cell markers on individual arterial sections by immunofluorescence or immunohistochemistry . While this allows for spatial localization of the cellular infiltrate in the arterial wall, it is time-consuming, labor-intensive, susceptible to bias, and does not provide global quantitation of the cellular infiltrate along the length of the injured artery. Murine models of neointimal hyperplasia after arterial injury include carotid ligation , femoral artery wire injury , carotid artery wire injury , and placement of an external cuff . Of all these models, femoral artery wire injury most closely phenocopies balloon angioplasty in humans since it utilizes transluminal endothelial denudation and enlargement of the external elastic lamina, which elicits fibrin deposition, platelet accumulation, and infiltration of inflammatory cells . By 4 weeks after injury, there is reproducible luminal narrowing due to a neointimal lesion composed of smooth muscle cells . While traditional flow cytometry panels were limited to 3-4 colors, multi-parameter instruments are capable of measuring 12 or more colors in small sample sizes. Herein, we describe a multi-parameter panel, validated by immunofluorescence studies, to obtain details and insights into the dynamics of the inflammatory cellular infiltrate after murine femoral artery wire injury. 2. Materials and Methods 2.1. Unilateral Femoral Artery Wire Injury Male C57BL/6 mice aged 18-22 weeks of age underwent left femoral artery wire injury as previously described . In brief, mice were anesthetized, and a 1.5 cm incision was made directly over the left femoral artery. The right femoral artery served as the uninjured control. The common femoral artery was dissected out along its length. Vascular control was obtained proximally and distally using suture loops. An arteriotomy was performed in a medial muscular arterial branch and a 0.014-inch guide wire was inserted through the arteriotomy into the common femoral artery, passed in and out 3 times, and then held in place for 5 min. Following arterial injury, the guide wire was removed and the muscular branch was ligated. Flow was restored in the femoral artery. At selected time points after surgery, mice were anesthetized, euthanized, and underwent in situ cardiac perfusion with PBS before collection of the injured arterial segment. The location of the injured segment, which is approximately 4 mm in length, was identified using the ligated arterial branch as a distal landmark. Samples used for immunofluorescence were perfusion-fixed with 2% paraformaldehyde prior to collection of the injured arterial segment. 2.2. Immunofluorescence and Quantification of Staining Cryopreserved femoral arteries were prepared as previously described . Five-micron arterial sections were outlined using a hydrophobic barrier pen (ImmEdge; Vector Labs; Burlingame, CA, USA), rehydrated, fixed in 2% paraformaldehyde, and incubated with primary antibodies diluted in IHC-Tek diluent pH 7.4 (IHC-World; Woodstock, MD, USA) for 1 h at room temperature, followed by the appropriate secondary antibody (donkey anti-rat IgG, Alexa Fluor 647; 0.5 mg/mL; Abcam; Cambridge, UK) for 1 h at room temperature. Sections were mounted with ProLong Gold Antifade with DAPI (ThermoFisher Scientific; Waltham, MA, USA). The following primary antibodies were used: rat anti-CD45 (IBL-3/16) (1 mg/mL; Abcam; Cambridge, UK) and rat anti-F4/80 (BM8) (1 mg/mL; Thermo-Fisher Scientific; Waltham, MA, USA). Digital images were acquired using an Axio Observer D1 Inverted Phase Contrast Fluorescence microscope (Carl Zeiss Microscopy, LLC; Oberkochen, Germany). Positively stained cells and DAPI-stained nuclei in the intimal, medial, and adventitial layers of each high-powered field were separately counted in a blinded fashion by 2 blinded investigtors. At least 4 high-powered fields were sampled per arterial segment from 3 mice. 2.3. Preparation of Single-Cell Suspensions Two femoral arteries were collected and pooled together for each single-cell suspension sample. Each artery was cut into sub-millimeter pieces using microsurgical scissors under a microscope and digested in RPMI buffer supplemented with 0.25 mg/mL of LiberaseTM TL (composed of collagenase I/II) (MilliporeSigma; St. Louis, MO, USA), and 1 mg/mL DNase (Roche; Indianapolis, IN, USA) for 1 h at 37 degC with shaking at 200 rpm. Digested samples were sheared 8-10 times using a 21.5-gauge needle attached to a 1 mL syringe and then filtered through a 40 mM nylon mesh filter. Residual tissue was macerated using a rubber syringe plunger. The filtrate was washed with MACS buffer 3 times to generate a single-cell suspension. Single-cell suspensions underwent a 1 min red blood cell lysis step using Pharm LyseTM buffer (BD Biosciences; Franklin Lakes, NJ, USA) at room temperature, which was halted using ice-cold HBSS. Following RBC lysis, concentration was measured using an automated cell counter (Nexcelom Bioscience; Lawrence, MA, USA). 2.4. Immunostaining and Flow Cytometry A 15-color flow cytometry panel was designed to identify leukocyte subtypes of interest, as shown in Table 1. Antibody concentrations were optimized using single-antibody staining of cell suspensions of murine splenocytes and bone marrow cells with serial antibody titrations to determine the concentration with optimal staining index for each antibody. During these antibody titration steps, splenocyte and bone marrow suspensions were diluted to a cell count of approximately 1.2 x 105 cells/mL to match the expected concentration for a single-cell suspension prepared from two femoral arteries. Single-cell suspensions were first stained with a fixable live/dead stain to allow for selection of live cells, followed by incubation with Fc BlockTM (BD Biosciences), and the staining cocktail for 14 antigens: CD45, MHCII, CD8, CD4, CD19, CD11b, CD11c, CD43, CD64, NK1.1, Ly6G, Ly6C, SiglecF, and Tim4. Finally, the cell suspension was fixed in 2% paraformaldehyde for 8 h at 4 degC. Flow cytometry was performed using a FACSymphonyTM A5 Cell Analyzer (BD Biosciences; Franklin Lakes, NJ, USA) and data were captured using BD FACSDivaTM software (BD Biosciences; Franklin Lakes, NJ, USA). The entirety of each sample was acquired and recorded. Cell populations were identified using a sequential gating strategy (see Results). "Fluorescence minus one" controls were used as necessary. Compensation and gating were performed using FlowJo version 10.8.1 software (BD Biosciences; Franklin Lakes, NJ, USA). 2.5. Statistical Analysis Data are shown as means +- SEM. Differences between means were assessed using Student's t-tests. All analyses were performed using GraphPad Prism, version 9.0 (GraphPad Software; San Diego, CA, USA). p < 0.05 was considered statistically significant. 3. Results 3.1. Immunofluorescence Staining of Femoral Artery Sections Arterial morphometry of uninjured and injured arteries was assessed by hematoxylin and eosin staining, as shown in Figure 1B,C. As shown in Figure 1C,D, overall leukocyte (CD45) and macrophage (F4/80) infiltration increased starting 1 day after injury, peaked 7 days after injury, and declined between days 7 and 28. Peak inflammatory infiltration occurred prior to the peak neointimal hyperplasia lesion at day 28 . 3.2. Flow Cytometry Gating Strategy for Leukocyte Sub-Populations Following routine gating to identify singlets and live cells, a staining mixture containing 14 monoclonal antibodies, each conjugated to different fluorophores, was used for differential identification of leukocyte subpopulations (Table 1) using the gating strategy shown in Figure 2. 3.3. Dynamics of Leukocyte Accumulation in Injured Femoral Arteries The accumulation of overall leukocytes and of leukocyte subpopulations was first compared between uninjured arteries and injured arteries at the 3-day timepoint, when an acute inflammatory response is known to occur . Approximately 32,200 live cells were present in the injured artery samples (each comprising two pooled arteries), of which approximately 29,000 were leukocytes , representing 58.6-fold more leukocytes per sample than the uninjured artery samples. For all leukocyte subpopulations examined at this time point (lymphocytes, natural killer [NK] cells, neutrophils, eosinophils, dendritic cells, monocytes, and macrophages), the number of cells in each injured artery sample significantly exceeded those in the uninjured artery samples . The dynamics of leukocyte accumulation from 1-14 days after femoral artery injury are shown in Figure 4. Total leukocyte accumulation was between 29,000 and 49,600 cells in the first 7 days after injury and decreased thereafter, reaching 5400 at 14 days , a trend which is qualitatively in concordance with the immunofluorescence of arterial sections described above. In uninjured arteries from the same animals, there was an average of 570 live leukocytes/sample, which represented approximately 17.9% of all live cells at each time point. Live leukocyte numbers did not vary over time in the uninjured arteries, suggesting that the trends seen in the injured artery samples do not represent a sample processing artifact . Both B and T lymphocytes (CD4+ and CD8+) were sparse and peaked in cell number at 7 days (200 and 1800 per sample, respectively) . Neutrophils were the most abundant innate cell type in the first 7 days after injury and peaked at 30,900 cells/sample at day 1 before decreasing to 10,300 cells/sample at 7 days and 730 cells/sample at 14 days. NK cells had a similarly rapid accumulation in the first 7 days before declining significantly by 14 days . Eosinophils remained steadily elevated in the first 7 days before also declining between 7 and 14 days . By day 3, monocytes and macrophages represented the largest proportion of all leukocytes, or 18,600 cells/sample, and peaked at 24,500 cells/sample on day 7 , again in concordance with immunofluorescence. Monocytes were further subdivided into fractions of classical (Ly6C+CD43-), non-classical (Ly6C-CD43+), and intermediate monocytes (Ly6CdimCD43dim) . Three distinct subpopulations of macrophages were identified using CD64 and Tim4. As shown in Figure 4C, the steady increase in CD64+Tim4+ macrophage accumulation in the first 7 days corresponds to a steady decrease in CD64+, and both subpopulations had a downward trend after day 7. CD64+ represented 97.0%, 53.4%, 31.6%, and 30.7% of all macrophages, while CD64+Tim4+ macrophages represented 0.7%, 26.9%, 37.7%, and 25.0% of all macrophages at 1, 3, 7, and 14 days, respectively. 4. Discussion We performed a 15-parameter flow cytometry study to obtain quantitative and simultaneous characterization of multiple distinct leukocyte subtypes involved in remodeling mouse femoral arteries after wire injury, a commonly used model of neointimal hyperplasia . Transluminal mechanical injury and dilation and the ensuing acute inflammatory response incurred by this model closely mimics balloon angioplasty. The major qualitative trends in the flow cytometry findings were validated by immunostaining for CD45 and F4/80, which showed that most leukocytes accumulate within the first 7 days after injury. As anticipated, we observed an early peak in the neutrophil infiltrate , followed by infiltration of monocytes/macrophages . We observed an earlier peak in the monocyte/macrophage infiltrate than previously reported (beginning at day 3 rather than day 7) , possibly due to differences in mouse age or strain or our technique, which assesses the entire injured segment in comparison to quantitation of staining on selected arterial sections, which may not be representative of the entire injured segment. We also observed a robust inflammatory infiltrate that overall lasted at least 7 days , which is also more protracted than previously reported . The finding that CD64+Tim4+ macrophages steadily increase in number over the first 7 days after arterial injury while CD64+ over the same period has not been previously described. This finding suggests that Tim4 expression was induced by the arterial microenvironment or that Tim4+ macrophages trafficked into the artery. Tim4 is a type-I cell-surface glycoprotein that is expressed by professional antigen-presenting cells and may regulate macrophage function . Specifically, Tim4 is a negative regulator of nitric oxide production by macrophages and lipopolysaccharide-induced macrophage activation , and promotes phagocytosis of apoptotic cells . Blockade of Tim4 increases atherosclerosis in mouse models by the prevention of phagocytosis of phosphatidylserine-expressing apoptotic cells and activated T cells by Tim4-expressing cells. Macrophages are the dominant myeloid cells recruited to injured arteries prior to the development of the neointima lesion . Thus, mechanistic studies aimed at understanding specifically how Tim4+ macrophages regulate the arterial remodeling process are underway. A 13-parameter flow cytometry technique was used to characterize total leukocytes, B and T lymphocytes, dendritic cells, monocytes/macrophages, NK cells, and granulocytes in a model of disturbed flow (low and oscillatory shear stress) induced by partial carotid ligation in apolipoprotein-E-deficient mice fed a high-fat diet that leads to atheroma development . This work differs from the current study in its focus on immune cell accumulation from flow disturbance in the context of atherosclerosis rather than restenosis from neointimal hyperplasia after transluminal mechanical injury. This work also did not quantify granulocyte subsets (e.g., neutrophils) or monocyte/macrophage subsets, which are specifically relevant to neointimal hyperplasia. A high-parameter flow cytometry study allows for the accurate and unbiased quantitation of multiple cell markers in an entire sample simultaneously. Drawbacks are the use of enzymatic digestion and the homogenization of tissue, which could lead to cell death or systematic artifacts in the quantitation of subpopulations. This technique also does not allow for spatial characterization of the cellular infiltrate in the layers of the arterial wall. Nevertheless, we were able to demonstrate in detail the dynamics of leukocyte accumulation that precede neointima formation after arterial injury and to use CD64+Tim4+ phenotyping to define a discrete macrophage subpopulation that may be important in regulating arterial remodeling. 5. Conclusions In conclusion, we present a multi-parameter flow cytometry method for simultaneous quantitation analysis of live leukocytes and 13 leukocyte subtypes in remodeling segments of mouse femoral arteries after injury, thus allowing for a detailed analysis of the dynamics of inflammatory cell infiltration in the arterial wall. Future studies will be aimed at determining the role of CD64+Tim4+ macrophages in early arterial remodeling and applying this methodology to studies of fate mapping and cell sorting for transcriptomic or proteomic studies. Author Contributions Conceptualization, K.J.H.; Data curation, V.P., C.M.C., T.L.S., J.J., L.X. and K.J.H.; Formal analysis, V.P., C.M.C., T.L.S., J.J., L.X. and K.J.H.; Funding acquisition, K.J.H.; Investigation, V.P., C.M.C., T.L.S., L.X. and S.S.; Methodology, V.P., C.M.C., T.L.S., J.J., L.X., S.S. and K.J.H.; Project administration, K.J.H.; Supervision, K.J.H.; Visualization, V.P., C.M.C., J.J., L.X. and S.S.; Writing--original draft, V.P. and K.J.H.; Writing--review and editing, V.P., C.M.C., T.L.S., J.J., L.X., S.S. and K.J.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The animal procedures were approved by the Institutional Animal Care and Use Committee of Northwestern University (protocol numbers IS00012938 and IS00016547, which were approved on 9 September 2019 and 27 January 2021, respectively). Data Availability Statement The data that were generated during the current study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 A. Schematic of mouse femoral artery wire injury model. (A) guidewire is inserted into the lumen of the artery through a muscular side branch and used to denude the endothelium and dilate the artery. Following removal of the wire, the branch is ligated, and the artery is reperfused. The injured segment is denoted in blue. (B) Representative hematoxylin and eosin (H + E) staining of the full cross-section of an uninjured artery. (C) Representative H + E and immunofluorescence for CD45 and F4/80 in uninjured (inset of B) and injured femoral artery cross sections 1, 3, 7, 14, and 28 days after injury. Internal and external lamellae are denoted by black arrows on H + E sections. "L" denotes arterial lumen. Red denotes CD45 or F4/80 staining. Green represents autofluorescence of the elastic lamellae. Original magnification 200x. Scale bar represents 5 mM. (D) Quantification of CD45+ (gray bars in top plot) and F4/80+ cells (gray bars in bottom plot) by immunofluorescence at 1, 3, 7, 14, and 28 days after injury and in corresponding uninjured arteries from the same animals. Total cell number (black bars) was determined by DAPI-stained nuclei on the same sections. Each bar represents mean cells +- SEM in 4 high powered fields (HPF) from at least 3 different animals. At each time point, p values were calculated using the Mann-Whitney test and represent comparisons between stained cells or nuclei in the injured group with the uninjured group. # p = 0.04. * p = 0.03. ** p = 0.02 compared to uninjured group. Figure 2 Gating strategy used to identify leukocytes and leukocyte sub-populations in a representative sample with the 15-parameter flow cytometry panel. FSC-H, forward scatter height. FSC-A, forward scatter area. NK cells, natural killer cells. DCs, dendritic cells. Figure 3 Comparison of leukocytes and leukocyte sub-populations identified using high-parameter flow cytometry in uninjured arteries and in femoral artery samples 3 days after injury. Comparisons are in numbers of live leukocytes (A), B and T lymphocytes (B), natural killer (NK) cells, neutrophils, and eosinophils (C), dendritic cells (D), monocytes and monocyte subpopulations (E), and macrophages and macrophage subpopulations (F). Each bar represents the mean cell number +- SEM of at least 3 samples, each comprising 2 arterial segments. p values calculated using Student's t-test. CM, classical monocytes. IM, intermediate monocytes. NC, non-classical monocytes. * p = 0.007, # p = 0.004. Figure 4 Leukocyte and leukocyte sub-population infiltration in uninjured arteries and at 1, 3, 7, and 14 days after injury using the high-parameter flow cytometry panel. Line graphs show all leukocytes, lymphocytes, neutrophils, natural killer (NK) cells, and eosinophils in injured and uninjured arteries (A), dendritic cells, monocytes, and monocyte sub-populations (B), and macrophages and macrophage subpopulations (C). cells-12-00689-t001_Table 1 Table 1 Antibody staining panel and optimal staining concentration for approximately 1 x 105 cells in 50 mL volume. Fluorophore Antibody Marker Clone Staining Concentration * Vendor BB700 CD8 Cytotoxic T cells 53-6.7 0.5 BD Biosciences (Franklin Lakes, NJ, USA) BB515 CD43 Monocyte subsets S7 5 BD Biosciences AF700 CD4 Helper T cells RM4-5 3 BD Biosciences A647 CD64 Monocytes and macrophages X54-5/7.1 1.25 BD Biosciences PE/Cy7 MHCII Professional antigen-presenting cells M5/114.15.2 3 Invitrogen (Waltham, MA, USA) PE/CF594 SiglecF Eosinophils E50-2440 0.6 BD Biosciences PE Tim4 Macrophage subsets RMT4-54 2.5 BD Biosciences BV786 NK1.1 Natural killer cells PK136 1 BD Biosciences BV711 Ly6G Neutrophils 1A8 1 BD Biosciences BV480 Live/Dead Viability dye v500 1 mL/2 mL eBioscience (San Diego, CA, USA) BV421 Ly6C Monocytes and macrophages HK1.4 2.5 BioLegend (San Diego, CA, USA) BUV805 CD45 Leukocytes 30-F11 0.25 BD Biosciences BUV737 CD11b Innate immune cells M1/70 3 BD Biosciences BUV563 CD19 B cells 1D3 1.25 BD Biosciences BUV395 CD11c Dendritic cells, monocytes, macrophages, granulocytes, NK cells, and subsets of B and T cells HL3 5 BD Biosciences * mg/ 50mL unless otherwise indicated. 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PMC10000450 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051039 foods-12-01039 Article Formation of Ne-Carboxymethyl-Lysine and Ne-Carboxyethyl-Lysine in Heated Fish Myofibrillar Proteins with Glucose: Relationship with Its Protein Structural Characterization Zhang Siqi Conceptualization Methodology Software Validation Formal analysis Investigation Data curation Writing - original draft Writing - review & editing + Zhou Pengcheng Conceptualization Methodology Software Validation Formal analysis Investigation Data curation Writing - original draft Writing - review & editing + Han Peng Methodology Software Formal analysis Zhang Hao Software Formal analysis Dong Shiyuan Conceptualization Validation Data curation Writing - original draft Supervision Project administration Funding acquisition * Zeng Mingyong Data curation Writing - review & editing Funding acquisition Martinez-Alvarez Oscar Academic Editor College of Food Science and Engineering, Ocean University of China, Qingdao 266003, China * Correspondence: [email protected]; Tel./Fax: +86-532-6089-2400 + These authors contributed equally to this work. 01 3 2023 3 2023 12 5 103913 1 2023 22 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 formation of advanced glycation end products (AGEs), including Ne-carboxymethyl-lysine (CML) and Ne-carboxyethyl-lysine (CEL), in a fish myofibrillar protein and glucose (MPG) model system at 80 degC and 98 degC for up to 45 min of heating were investigated. The characterization of protein structures, including their particle size, z-potential, total sulfhydryl (T-SH), surface hydrophobicity (H0), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Fourier transform infrared spectroscopy (FTIR), were also analyzed. It was found that the covalent binding of glucose and myofibrillar protein at 98 degC promoted protein aggregation when compared with the fish myofibrillar protein (MP) heated alone, and this aggregation was associated with the formation of disulfide bonds between myofibrillar proteins. Furthermore, the rapid increase of CEL level with the initial heating at 98 degC was related to the unfolding of fish myofibrillar protein caused by thermal treatment. Finally, correlation analysis indicated that the formation of CEL and CML had a significantly negative correlation with T-SH content (r = -0.68 and r = -0.86, p <= 0.011) and particle size (r = -0.87 and r = -0.67, p <= 0.012), but was weakly correlated with a-Helix, b-Sheet and H0 (r2 <= 0.28, p > 0.05) during thermal treatment. Overall, these findings provide new insights into the formation of AGEs in fish products based on changes of protein structure. advanced glycation end products thermal treatment myofibrillar proteins aggregation Ne-carboxymethyl-lysine Ne-carboxyethyl-lysine National Key R&D Program of China2018YFD0901005 This research was funded by National Key R&D Program of China (2018YFD0901005). pmc1. Introduction The Maillard reaction is one of the common reactions during food thermal processing, which plays a vital role in the formation of food flavor and color . Advanced glycation end products (AGEs) are chemicals formed at the advanced stage of the Maillard reaction and regarded as harmful substances . It is worth noting that long-term exposure to a high AGEs diet could cause accumulation in the body and promote inflammation, which may cause some chronic diseases such as diabetes and atherosclerosis . Some AGEs, especially lysine-derived Ne-carboxymethyl-lysine (CML) and Ne-carboxyethyl-lysine (CEL), are most abundant and stable in protein and fat-rich foods, such as meat and meat products , and widely studied in foods . The formation of CEL and CML in cooked fish products depends on the food composition and the type of thermal treatment, heating temperature and time. Niu et al. (2017) reported that boiling at 100 degC for 30 min resulted in a significant increase in protein-bound CML (2.1-10.8-fold increase) and CEL (27-242% increase) from grass carp muscle. Liu et al. (2022) showed that production of fluorescent AGEs in sturgeon fillets was greatly increased by frying time, and both frying temperature and time had an extremely significant effect on CML and CEL levels (p < 0.001). Our previous study showed that CML levels in fried hairtail fillets were higher than in boiled and baked ones, regardless of the cooking time . Notably, since proteins are macromolecules with complex advanced structures, the glycation of protein during thermal treatments can also be regulated by changing the structure of the protein . Recently, the interaction between the changes of protein structure and its glycation extent during thermal processing treatments has attracted extensive attention. By analyzing proteomics, Xu et al. (2020) showed that ultrasonic pretreatment (UP) at 20 kHz induced in protein unfolding and aggregation behavior in a bovine serum albumin (BSA) or b-lactoglobulin (b-Lg) model system, which changed the glycation extent of the Lys and Arg. In addition, Huang et al. (2013) monitored the number of glycation sites of ovalbumin by Fourier transform ion cyclotron mass spectrometry (FTICR-MS) before and after reducing the pair of the intrachain disulfide bond, and found that when the ovalbumin tertiary structure was disrupted after reducing the disulfide bond, the number of glycated sites of the protein increased. It is worth noting that mild oxidation led to the unfolding of pork myofibrillar protein and exposed more free amino acids, which facilitated the formation of CML by the Maillard reaction . However, few studies have examined the relationship between the structure changes of fish protein and the formation of CML and CEL via glycation reaction. In recent years, sturgeon aquaculture has developed rapidly in China, with an estimated annual harvest of 121,875 metric tons in 2021 (China Fishery Statistical Yearbook, 2022). Sturgeon is a precious food source with many active components that are beneficial for human's health, and has high nutritional and economic value worldwide . Thermal processing methods, such as steaming, boiling, baking or frying have been applied to treat sturgeon meat products . Myofibrillar protein, accounting for 55-65% of muscle proteins, is the predominant component of proteins in fish muscle . Our hypothesis is that the structural changes of myofibrillar protein (MP) during thermal treatments may affect the formation process of AGEs. Therefore, the structure properties of myofibrillar protein and glucose during the heating process were determined by total sulfhydryl, surface hydrophobicity, free amino content, particle size, z-potential, Fourier transform infrared spectroscopy, sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and the formation of corresponding furosine, Ne-carboxymethyl-lysine (CML) and Ne-carboxyethyl-lysine (CEL) were analyzed. The correlations between these parameters and AGEs were also analyzed. These findings provide a theoretical basis for revealing the mechanism of AGEs formation in fish products during cooking or processing treatments. 2. Materials and Methods 2.1. Chemicals Ne-carboxymethyl-lysine (CML), Ne-carboxyethyl-lysine (CEL), Ne-carboxymethyl-lysine-d4 (CML-d4), and Ne-carboxyethyl-lysine-d4 (CEL-d4) were bought from Toronto Research Chemicals Inc. (Toronto, Canada). Acetonitrile of HPLC grade was purchased from Merck (Darmstadt, Germany). All the other chemicals and reagents used in this study were of analytical grade. 2.2. Sample Preparation Fresh hybrid sturgeons (Acipenser baerii x Acipenser schrenckii), weighing 1.8 +- 0.2 kg and 65 +- 5 cm in length, were purchased from a local sturgeon farm in Qingdao (Shandong province, China) and transported to the laboratory within an hour. The head, bones, and skin of the fish were manually removed and the fresh flesh was used for myofibrillar protein (MP) extraction. The MP was extracted according to the method of Han et al., (2017) with some modifications. The protein concentration was evaluated by the Biuret method . For myofibrillar protein and glucose (MPG) heated samples, MP (10 mg mL-1) and glucose at the ratio of 10:1 (w/w) were dissolved in 50 mM phosphate buffer solution (pH 7.0). The solution was kept in 25 mL screw-cap tubes and heated in a water bath at 80 degC and 98 degC for 2.5, 5, 10, 15, 30 and 45 min, respectively. The choice of heating condition is according to light (80 degC) or strong (98 degC) cooking or processing of some fish foods . Control experiments with MP suspensions (10 mg mL-1) heated without glucose were also conducted. The MP and MPG samples were stored at -60 degC for further analysis. 2.3. Analysis of CML and CEL The levels of CML and CEL were assessed by the method of Sun et al. (2015) with minor modifications. Briefly, two milliliters of sample suspension (5 mg mL-1) were incubated with 0.4 mL borate buffer (0.2 M, pH 9.2) and 0.08 mL sodium borohydride (2 M, dissolved with 0.1 M NaOH) at 4 degC for 8 h and then hydrolyzed by 1.6 mL 6 M HCl at 110 degC for 24 h. Next, the protein hydrolysate was dried in a vacuum oven (DZF-6050; Shanghai Jinghong Laboratory instrument Co., Ltd., Shanghai, China) at 60 degC and diluted with water to 4 mL, from which 1 mL was withdrawn and spiked with 20 mL internal standard (CML-d4, CEL-d4). After activating and balancing a Sep-Pak MCX column, the sample was purified by this column and eluted with 2 mL methanol containing 5% ammonia water. Finally, the eluent was dried in nitrogen with a nitrogen evaporator (DC12H; Shanghai ANPEL Scientific Instrument Co., Ltd., Shanghai, China), reconstituted with 2 mL deionized water, and filtered through a 0.22 mm filter before LC-MS/MS analysis. 2.4. Analysis of Furosine Furosine was determined according to the method described by Semedo Tavares et al. (2018) with a slight modification. The analyses were performed using a HPLC system (Agilent 1100, San Leandro, CA, USA) equipped with an Alltima C8 column (250 mm x 4.6 mm, 5 mm, Grace Davison, Columbia, MD, USA). The column (250 x 4.6 mm Alltech, Nicholasville, KY, USA) temperature was set at 30 degC and the UV/VIS detector set at 280 nm. The mobile phase was performed at a flow rate of 1 mL/min with (A) water containing 0.4% acetic acid, and (B) 0.3% potassium chloride (KCl) in (A). The mobile phase consists of 98% liquid A and 2% liquid B. 2.5. Total Sulfhydryl (T-SH) The T-SH content of samples was determined according to the method of Ellman (1959) . The results were calculated by using a molar extinction coefficient of 1.36 x 104 M/cm and expressed in micromoles of T-SH per gram of protein. 2.6. Protein Surface Hydrophobicity (H0) Bromophenol blue (BPB) can adhere the surface hydrophobic region of soluble proteins and insoluble proteins and is therefore used to estimate protein surface hydrophobicity . The H0 content of samples was measured by the method of Zhang et al. (2020) with some modifications. A total of 40 mL 1 mg mL-1 BPB (in deionized water) was added to 2 mL samples and the solution was stirred at 200 rpm for 10 min at room temperature. The mixtures were centrifuged for 10 min at 2000x g, and then the absorbance of the supernatant was measured at 595 nm. The results were expressed as the content of bound BPB. 2.7. Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) The SDS-PAGE was performed using the method of Zhou et al. (2021) with an 10% separating gel and a 5% stacking gel. Coomassie Brilliant Blue R was used for protein staining. 2.8. Fourier Transform Infrared Spectroscopy (FTIR) The FTIR was determined according to the method described by Ren et al. (2022) with some modifications. A Fourier transform spectrophotometer (Nicolet iS10, Thermo Scientific Corp., Madison, WI, USA) was used to obtain the infrared absorption value of samples. The dried powder samples were diluted with spectral grade potassium bromide (KBr) and the absorbance spectrum of KBr as background was used to eliminate interference for samples. The scanning range was 4000-400 cm-1 with a resolution of 4 cm-1 and 64 scans for each sample. 2.9. Particle Size and z-Potential The average particle size and z-potential of samples were determined by using a laser particle size analyzer (Malvern Nano ZS, Malvern Instruments Ltd., Malvern, Worcestershire, UK) at 25 degC. Samples were diluted approximately 4-fold with the same buffer, mixed, and immediately transferred into plastic cuvettes for determination. 2.10. Free Amino Content The free amino content of samples was quantified by the OPA (o-phthalaldehyde) spectrophotometric assay, as described by Church et al., (1983) . The OPA reagent was prepared daily by combining the following reagents and diluting to a final volume of 50 mL with distilled water: 40 mg of OPA (dissolved in 1 mL of methanol), 25 mL of 100 mM sodium tetraborate, 2.5 mL of 20% (w/w) SDS and 100 mL of b-mercaptoethanol. One hundred microliters of the solution of samples (5 mg mL-1) was added directly to 2 mL of OPA reagent and left at 35 degC in the dark for 2 min. The absorbance was measured at 340 nm. The standard curve was prepared with lysine at the range of 0-3 mmol L-1. 2.11. Statistical Analysis All experiments were performed with three repeats (n = 3) and data expressed as mean +- standard deviation (SD). The statistical analysis was performed using SPSS 25 software. Significant differences between samples were identified at p < 0.05 by multi-way analysis of variance (ANOVA). Pearson's correlation test evaluated the correlation between AGEs formation and structure changes of protein, and p < 0.05, p < 0.01 and p < 0.001, respectively, represented different levels of statistical significance. 3. Results and Discussion 3.1. CML and CEL Levels The CEL and CML levels of MPG under different heating conditions are shown in Figure 1A,B, respectively. At both temperatures, the CML level of MPG significantly increased with heating time. Interestingly, the CEL level of MPG within the first 2.5 min of heating at 98 degC dramatically increased by 56.94% when compared with the unheated samples, but then slightly increased by 10.88% from 2.5 min to 30 min. At 80 degC, the CEL level in MPG sharply increased by approximately 33% within the first 2.5 min of heating when compared with the unheated samples, but only increased by 3.43% from 2.5 min to 10 min, and then significantly increased by 24.51% from 10 min to 30 min. Moreover, within the first 10 min of heating, the CEL level of MPG at 98 degC was much higher than that at 80 degC, but there was no significant difference of CEL level between these two temperatures for 15 min to 45 min of heating. On the other hand, the CEL level of MPG during the whole heating process was much higher than that of CML, suggesting that myofibrillar protein and glucose were more likely to produce CEL under such thermal treatment conditions. Our previous study also found that the CEL level in fried sturgeon fillets was much higher than that of the CML . To the best of our knowledge, the reason for the sharp increase of the CEL level during the initial heating stage is not clear. Yu et al. (2018) found that, when the myofibrillar protein-glucose-linoleic acid system was mildly oxidized during heating, the myofibrillar protein began to unfold, and the exposed free amino groups could facilitate AGEs generation by the Maillard reaction pathway. Xu et al. (2020) reported that five cycles of ultrasonic pretreatment (UP) up-regulated the glycation degree of BSA and b-Lg, possibly due to the unfolding behavior of protein induced by UP, which exposed additional glycation. Thus, we speculated that, during the initial heating, the rapid increase of CEL might be related to the unfolding of fish myofibrillar protein caused by thermal treatment. However, our results demonstrated that the formation of CEL was not obviously affected by further heating at higher temperatures, which might be attributed to the aggregation of fish myofibrillar protein caused by deeper thermal treatments to hide some glycation sites . 3.2. Furosine Furosine is an important indirect indicator of Amadori products and often related to early stage Mailard reaction products . Regardless of temperatures, the furosine content in MPG during the first 2.5 min of heating was markedly increased, but there were no significant changes during 5 min to 15 min of heating . A reasonable explanation might be that, in the later stage of heating, even though the Maillard reaction of fish myofibrillar protein and glucose produced a lot of furosine, some of these compounds could become degraded as Maillard progressed, generating intermediate and end products . Furthermore, when MPG was heated at 80 degC and 98 degC for 45 min, the furosine increases were 30.09% and 64.55%, respectively, more than those after 15 min. This was a similar trend to that observed by Mitra et al., (2018) , who reported that no significant changes in furosine content from pork samples heated at 58 degC for 72 min were found, but a longer heating time (17 h) significantly increased furosine content. 3.3. Total Sulfhydryl Content The total sulfhydryl (T-SH) content of MP and MPG greatly varied with heating time and temperature . The T-SH content of MPG within the first 2.5 min of heating rapidly increased, and then significantly decreased with further heating. During the whole heating process, the T-SH content of MPG heated at 98 degC was much lower than that at 80 degC. A decrease in T-SH content was reported to be due to the fact that the sulfhydryl groups of protein intra-molecules formed disulfide bonds during heating . Jimenez-Castano et al. (2005) documented that dry heating b-Lg with dextran enhanced polymerization of protein, and this polymerization occurred due to disulfide bonds. In this study, when heated at the same temperature for 10 min to 45 min, the T-SH content of MPG was much lower than that of MP. We surmised that this phenomenon was due to the fact that fish myofibrillar protein heated in the presence of glucose promoted protein aggregation to some degree, which caused the sulfhydryl groups of myofibrillar protein to form disulfide bonds. 3.4. Surface Hydrophobicity Content Analysis of the surface hydrophobicity (H0) of molecules can be used to reflect the change of protein conformation . The H0 of MPG and MP under different heating conditions is shown in Figure 4. Compared with the unheated samples, the H0 content of MPG and MP after heating greatly increased. Moreover, the H0 of MPG during the whole process was much higher than that of MP except after 2.5 min of heating. To the best of our knowledge, reasons for the changes of surface hydrophobicity in heated food protein and carbohydrates remain controversial. Jiang et al. (2021) observed that the decrease of surface hydrophobicity of a-lactalbumin heated with xylose was possibly due to the protection of the surface hydrophobic groups by the attached xylose molecules when compared with a-lactalbumin heated alone. However, our results are similar to those of Bian et al. (2018) , who reported that the chicken myofibrillar protein heated with glucosamine resulted in higher surface hydrophobicity than myofibrillar protein heated alone, which might be related to protein unfolding. In our present study, the surface hydrophobicity of fish myofibrillar proteins in the presence of glucose was higher than that of fish myofibrillar proteins alone during heating, probably due to aggregation dissociation or protein unfolding . 3.5. SDS-PAGE The electrophoretic pattern of MP and MPG under different heating conditions was monitored by SDS-PAGE. The myosin heavy chain (MHC), actin chain (AC) and tropomyosin chain (TM) bands intensity of MPG and MP heated at 80 degC did not decrease with heating time (channels 1 to 6). When MP was heated at 98 degC for 15 min to 45 min, the MHC, AC and TM bands intensity markedly decreased with heating time and. after 45 min of heating, the MHC band almost disappeared (channels 10 to 12), indicating self-aggregation of MP . However, no obvious decrease in MHC, AC and TM bands intensity of MPG were observed at 98 degC for 10 min to 45 min, which could be attributed to the fact that steric hindrance due to glucose conjugated on the MP contributed to the decrease of MP self-aggregation propensity during heating . In addition, the band above 180 KDa of MPG at 98 degC during the whole heating treatment was much denser than that at 80 degC. It is worth noting that, regardless of heating temperature, the band above 180 KDa of MPG was denser than that of MP during the whole heating process, suggesting that heating caused the covalent link of fish myofibrillar protein with glucose to form larger molecular mass polymers than myofibrillar proteins heated alone . The protein polymers in this large molecular mass could be from myosin heavy chain, actin and tropomyosin, as the bands intensity of these proteins were reduced or missing during heating. This finding was consistent with that reported by Bian et al. (2018) , who revealed that myosin heavy chain, actin chain, tropomyosin chain or myosin light chain were the main protein reactants in the glycation of chicken myofibrillar protein heated with glucosamine. The present results further confirmed that fish myofibrillar protein and glucose heated at a higher temperature and for a longer heating time promoted protein aggregation, when compared with fish myofibrillar protein heated alone. 3.6. FTIR Analysis The bands at 1600-1700 cm-1 and 1450-1550 cm-1 from amide I and II groups referred to C=O and C-N stretching, respectively . As reported by Gu et al. (2010) , changes in the bands at 1180-953 cm-1 could correspond to the stretching of C-C and C-O and the bending mode of C-H bonds. Figure 6A,B show that, in our present study, the absorption intensities of MPG at wavenumbers of 1660 cm-1 (amide I), 1536 cm-1 (amide II), and 1158 cm-1 were much lower than those of MP at the same heating temperature. Qu et al. (2018) indicated that functional groups such as -NH2 in proteins, especially lysine, were reduced and the absorption intensity at the wavenumbers of 1650-1600 cm-1, 1600-1500 cm-1, and 1200-1300 cm-1 decreased with the Maillard reaction of rapeseed protein isolate and dextran. Our previous study also found that decreased absorption intensity around the wavenumbers of 1680 cm-1, 1540 cm-1, and 1153 cm-1 were associated with covalent binding of silver carp myofibrillar protein to glucose during heating . Further information about secondary structure contents of MP and MPG under different heating conditions was calculated by PeakFit 4.12 software and are shown in Figure 7. The a-helix content of MPG heated at 80 degC for 10 min to 45 min was markedly lower than that of MP, and the corresponding b-sheet content was significantly higher than that of MP; at 98 degC, the opposite trend was observed. Typically, a-helix structures are buried in the interior sites of polypeptide chains and related to stability of protein . In this sense, evaluation of the secondary structure showed that the binding of glucose and fish myofibrillar protein during heating at 80 degC caused fish myofibrillar protein to become more flexible and disordered . However, heating with a higher temperature (98 degC) might cause more glucose to bind to myofibrillar proteins, and the introduction of more hydroxyl groups from glucose causes an intermolecular interaction among the neighboring proteins, thereby increasing the a-helix content . From the present results, the covalent binding of glucose and fish myofibrillar protein at a higher heating temperature could affect the secondary structure of myofibrillar protein. 3.7. Particle Size and z-Potential The particle size of MP and MPG under different heating conditions is shown in Figure 8A. During the whole heating process, the particle size of MPG and MP heated at 98 degC was much smaller than that at 80 degC. The particle size of MPG heated at these two heating temperatures rapidly decreased with heating time. For MP, at these two temperatures, except for at 30 min, the particle size decreased significantly with heating time, and the decrease of particle size in MP might be attributed to the reduction of MP clusters and more uniform dispersion of MP in solution after heat treatment . In addition, the increase of particle size in MP at 30 min might be related to protein aggregation ; the mechanisms behind this phenomenon still need to be further investigated. It is noteworthy that, when heated at 80 degC for 15 min to 45 min and 98 degC for 2.5 min to 30 min, the particle size of MPG was significantly smaller than MP. Generally, glycation modification of protein resulted in the increase of its particle size . However, the conclusions of the present study were inconsistent with empirical results. This was most likely due to the fact that, during heating, the glucose unbound to myofibrillar protein underwent auto-oxidation and generated free radicals , that caused the aggregation formed by glucose and myofibrillar protein to shrink in size . The z-potential can reflect the surface charge state of particles in a dispersion system which affects the surface electrical charge . As shown in Figure 8B, the changes of negative charge in MPG did not have an obvious trend with heating time. However, it was noted that the negative charge of MPG during the whole heating process at 80 degC was much less than that of MP, except at 30 min of heating. At 98 degC, the negative charge of MPG within 10 min of heating was less than that of MP, but no significant differences between them were observed with further heating. Vate & Benjakul (2016) reported that protein aggregation induced by oxidized tannic acid plausibly masked the charged amino acids present in natural actomyosin, resulting in a less negative charge on the protein surface. Thus, we hypothesize that fish myofibrillar protein heated in the presence of glucose promoted protein aggregation to some degree, masking the charged amino acids in myofibrillar proteins. 3.8. Free Amino Content In a glycation reaction, the free amino content of protein and the reducing end of the sugar can form a Schiff base, and this causes the depletion of the available amino groups of proteins . At the same heating temperature, the loss of free amino content from 5 min to 45 min of heating was greater in MPG when compared to MP . At both temperatures, the free amino content of MP and MPG rapidly increased within the first 2.5 min, and then decreased with further heating. Interestingly, the free amino content of MPG at 98 degC for 2.5 min of heating was 18.13% higher than that at 80 degC. The higher free amino content of fish myofibrillar proteins and glucose with higher temperatures during the initial heating stage could be a consequence of the intensity of heating treatments, which enhanced the denaturation of protein and caused an increase in free amino content . Moreover, regardless of heating temperature, the increase of free amino content of fish myofibrillar protein heated with glucose during the initial heating stage might be due to the expansion of protein caused by the thermal treatment, thus exposing more free amino acid . 3.9. Correlation Analysis In order to further explore the effects of protein structural changes on formation of AGEs from fish myofibrillar proteins and heated with glucose, correlations between specific AGEs (CEL, CML), and the corresponding structural properties of myofibrillar proteins were analyzed by Pearson's correlation analysis . The formation of CEL and CML were markedly negatively correlated with total sulfhydryl content (r = -0.68, p < 0.05 and r = -0.86, p < 0.001, respectively), but positively correlated with surface hydrophobicity content (p > 0.05); Furosine content was significantly correlated with CEL and CML levels (r = 0.78, p < 0.01 and r = 0.92, p < 0.001, respectively); however, there was a weak correlation between CEL and CML levels and a-Helix, b-Sheet, random coil and b-Turn. In addition, free amino content was significantly negatively correlated with CML level (r = -0.74, p < 0.01), but weakly negatively correlated with CEL level (r = -0.49, p > 0.05). Interestingly, particle size was significantly negatively correlated with CEL and CML levels (r = -0.87, p < 0.001 and r = -0.67, p < 0.05, respectively), suggesting that the formation of CML and CEL were greatly affected by the decrease of particle size during thermal treatments. The reason for this result is still not clear. Zhu et al. (2021) found that, when myofibrillar proteins and glucosamine were exposed to protein peroxyl radicals (ROO) derived from linoleic acid during heating, CML and CEL levels were significantly negatively correlated with particle size, which was related to the decomposition of myofibrillar proteins aggregation. Currently, there are few studies about the obvious correlation between the total sulfhydryl content of heated food proteins and the formation of CEL and CML. However, our results showed that high CEL and CML levels were closely related to low total sulfhydryl content. Zhu et al. (2020) reported that formation of a strong covalent bond between the disulfide bonds of myosin could promote the formation of CEL and CML. We hypothesized that the heating of fish myofibrillar proteins with glucose led to the aggregation of proteins via disulfide bonds, which could promote the formation of CEL and CML. Furthermore, the formation of CEL and CML levels was related to the increase of surface hydrophobicity content, but the mechanism behind this phenomenon is not clear. We speculate that the fish myofibrillar protein conformations disrupted and exposed more surface hydrophobicity groups during thermal treatments , which was related to the formation of AGEs. The findings of the present study could mean that the formation of AGEs in fish myofibrillar protein might be affected by the protein structure changes during heat treatment, including the decrease of protein size and total sulfhydryl content and the increase of surface hydrophobicity content, which could be related to protein unfolding and aggregation. Some previous studies have also shown that the protein unfolding and aggregation induced by heat treatment might regulate the glycation process of food protein, such as bovine serum albumin, b-lactoglobulin and pork myofibrillar protein . Based on the results and correlation analysis presented above, a possible mechanism of CEL and CML formation in a heated fish myofibrillar protein and glucose model system was proposed . This formation mechanism includes the following two possible mechanisms: During the initial heating stage, fish myofibrils heated with glucose were unfolded and exposed free amino, sulfhydryl groups and surface hydrophobicity groups , which were related to the up-regulation of glycation sites , resulting in the rapid increase of CEL and CML levels. As the extent of thermal treatments increased, fish myofibrillar proteins in the presence of glucose formed polymerization through disulfide bonds, which buried the free amino and sulfhydryl groups . At this point, the aggregation of fish myofibrillar proteins caused some glycation sites to be hidden, which slowed down the formation of CEL and CML . Based on the results presented above, it was summarized that with the increase of the extent of thermal treatments, the predominant influence factor of heating on the fish myofibrillar protein and glucose system gradually transferred from unfolding, which promoted the formation of CEL and CML, to aggregation, which slowed down the formation of CEL and CML. 4. Conclusions In this study, the effects of changes in protein structure of a fish myofibrillar protein and glucose model system during thermal treatment on the formation of corresponding AGEs were investigated. It was found that the decrease of particle size, free amino content and total sulfhydryl content and the increase of hydrophobicity in myofibrillar protein and glucose during thermal treatment had a positive influence on the formation of CEL and CML. Furthermore, the correlation analysis showed that the CEL and CML levels were less affected by the protein secondary structure based on FTIR analysis. The underlying mechanism behind these results indicates that the formation of CEL and CML in fish myofibrillar protein heated with glucose was affected by its unfolding and aggregation, depending on the extent of thermal treatments. These findings help to enhance understanding of the relationship between the formation of AGEs and structure changes of fish protein during thermal processing methods, and provide some valuable references and guidelines for revealing the mechanism of AGEs formation in fish products. Author Contributions Conceptualization, S.D., S.Z. and P.Z.; methodology, S.Z., P.Z. and P.H.; software, S.Z., P.Z., P.H. and H.Z.; validation, S.D., S.Z. and P.Z.; formal analysis, S.Z., P.Z., P.H. and H.Z.; investigation, S.Z. and P.Z.; data curation, S.D., S.Z., P.Z. and M.Z.; writing--original draft, S.Z. and P.Z.; writing--review and editing, S.D., S.Z., P.Z. and M.Z.; visualization, S.Z.; supervision, S.D.; project administration, S.D.; funding acquisition, S.D. and M.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 Date are contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Changes in Ne-carboxyethyl-lysine (CEL) (A) and Ne-carboxymethyl-lysine (CML) (B) content of myofibrillar protein and glucose (MPG) under different heating conditions (80 degC and 98 degC, 0-45 min). Error bars indicate standard deviation (n = 3). Samples with * p < 0.05 indicate significant differences at different heating times (compared with 0 min). Samples with # p < 0.05 indicate significant differences between 80 degC and 98 degC. Figure 2 Changes in furosine content of myofibrillar protein and glucose (MPG) under different heating conditions (80 degC and 98 degC, 0-45 min). Error bars indicate standard deviation (n = 3). Samples with * p < 0.05 indicate significant differences at different heating times (compared with 0 min). Samples with # p < 0.05 indicate significant differences between 80 degC and 98 degC. Figure 3 Changes in total sulfhydryl content of myofibrillar protein and glucose (MPG) and myofibrillar protein (MP) under different heating conditions (80 degC and 98 degC, 0-45 min). Error bars indicate standard deviation (n = 3). Samples with * p < 0.05 indicate significant differences at different heating times (compared with 0 min). Samples with # p < 0.05 indicate significant differences between 80 degC and 98 degC. Samples with & p < 0.05 indicate significant differences between MPG and MP. Figure 4 Changes in surface hydrophobicity of myofibrillar protein and glucose (MPG) and myofibrillar protein (MP) under different heating conditions (80 degC and 98 degC, 0-45 min). Error bars indicate standard deviation (n = 3). Samples with * p < 0.05 indicate significant differences at different heating times (compared with 0 min). Samples with & p < 0.05 indicate significant differences between MPG and MP. Figure 5 Sodium dodecyl sulfate-polyacrylamide gel electrophoresis profiles of myofibrillar protein (MP) (A) and myofibrillar protein and glucose (MPG) (B) under different heating conditions (80 degC and 98 degC, 0-45 min). Lanes: c = 0 min; 1 = 80 degC, 2.5 min; 2 = 80 degC, 5 min; 3 = 80 degC, 10 min; 4 = 80 degC, 15 min; 5 = 80 degC, 30 min; 6 = 80 degC, 45 min; 7 = 98 degC, 2.5 min; 8 = 98 degC, 5 min; 9 = 98 degC, 10 min; 10 = 98 degC, 15 min; 11 = 98 degC, 30 min; 12 = 98 degC, 45 min; MHC: myosin heavy chain; AC: actin chain; TM: tropomyosin chain. Figure 6 Changes in Fourier transform infrared spectroscopy of myofibrillar protein and glucose (MPG) and myofibrillar protein (MP) heated at 80 degC (A) and 98 degC (B) for 0-45 min. Figure 7 Changes in relative contents of secondary structures of myofibrillar protein and glucose (MPG) and myofibrillar protein (MP) heated at 80 degC (A) and 98 degC (B) for 0-45 min. c = 0 min; 1 = MP, 2.5 min; 2 = MP, 5 min; 3 = MP, 10 min; 4 = MP, 15 min; 5 = MP, 30 min; 6 = MP, 45 min; 7 = MPG, 2.5 min; 8 = MPG, 5 min; 9 = MPG, 10 min; 10 = MPG, 15 min; 11 = MPG, 30 min; 12 = MPG, 45 min. Figure 8 Changes in particle size (A) and z-potential (B) of myofibrillar protein and glucose (MPG) and myofibrillar protein (MP) under different heating conditions (80 degC and 98 degC, 0-45 min). Error bars indicate standard deviation (n = 3). Samples with * p < 0.05 indicate significant differences at different heating times (compared with 0 min). Samples with # p < 0.05 indicate significant differences between 80 degC and 98 degC. Samples with & p < 0.05 indicate significant differences between MPG and MP. Figure 9 Changes in free amino content of myofibrillar protein and glucose (MPG) and myofibrillar protein (MP) under different heating conditions (80 degC and 98 degC, 0-45 min). Error bars indicate standard deviation (n = 3). Samples with * p < 0.05 indicate significant differences at different heating times (compared with 0 min). Samples with # p < 0.05 indicate significant differences between 80 degC and 98 degC. Samples with & p < 0.05 indicate significant differences between MPG and MP. Figure 10 Correlation analysis of all parameters measured in this research of myofibrillar protein and glucose (MPG) under different heating conditions (80 degC and 98 degC, 0-45 min). The asterisk (*) denotes significant difference. *: p < 0.05; **: p < 0.01; ***: p < 0.001. Figure 11 Possible mechanism for the effect of protein structure changes induced by the extent of thermal treatments on the formation of AGEs. (A) Initial heating. (B) Further heating. 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PMC10000451 | s were reviewed by two reviewers to select final articles. Subsequently, the articles found were critically evaluated by two reviewers according to the CEBM method. Finally, article data were extracted. Of the 1812 articles found, 54 were included in the final evaluation. Of these, 47 articles were related to the diagnosis of whole body mizaj (WBM). WBM was diagnosed in 37 studies using questionnaires and 10 using expert panels. In addition, six articles examined the mizaj of organs. Only four of these questionnaires were found with reported reliability and validity. There were two questionnaires for assessing WBM, but neither had sufficient reliability and validity. Questionnaires that assess organs had weak designs and lacked sufficient reliability and validity. Persian medicine temperament traditional medicine questionnaire diagnosis This research received no external funding. pmc1. Introduction Traditional and complementary medicine paradigms are used increasingly worldwide. In recent years, many studies in the field of complementary medicine have been published in Medline . In addition, there has recently been a trend toward person-centered medicine . Personalized medicine means that people are evaluated based on individual characteristics that can influence disease manifestations and treatment patterns . Although this paradigm is a new approach in current medicine, it has been the basis of diagnosis and treatment in traditional Chinese medicine, Ayurveda, and Persian medicine (PM) for centuries . PM is one of the traditional schools of medicine where the diagnosis and treatment are based on the concept of mizaj (also known as temperament). Mizaj is determined based on the physical, physiological, and psychological characteristics of individuals . Based on this concept, according to 10 criteria, each person belongs to one of four simple groups (hot, cold, dry, wet), four complexes (cold and wet, hot and wet, cold and dry, hot and dry), or moderate mizaj . From the point of view of PM, each person and also each organ of the body has its own mizaj. Consequently, the resultant mizaj of the organs (including the brain, heart, and liver) makes the whole body mizaj (WBM) . It is believed that when the WBM and the mizaj of all the organs are in balance, there is health in the individual's body. Any imbalance in WBM or the mizaj of organs can lead to illness (called sue-mizaj or dystemperament in PM) . PM references provide qualitative and descriptive criteria for determining the WBM and its main organs . Several studies have recently used different methods to identify mizaj. Some studies used expert panels, while others used questionnaires as the basis for diagnosis. Some studies have investigated the relationship between some diseases and WBM and organ mizaj. These studies evaluated the correlations of mizaj with some objective indicators . However, it seems that different invalid and unreliable methods were used in these studies. Based on our searches, no study has been conducted to investigate the diagnostic tools in PM. This study aims to investigate the diagnostic tools for determining mizaj in PM. 2. Materials and Methods This systematic review was conducted in 2022 in Babol, Iran. Articles in Persian and English were selected for review. 2.1. Information Sources English electronic databases including the Web of Science, PubMed, Scopus, Google Scholar (the first 20 pages), and SID databases (in Persian) and gray literature up to 2022 September were searched. 2.2. Eligibility Criteria Our review includes all types of studies (cross-section, case-control, cohort, RCT) using standard tools for mizaj assessment, mizaj expert opinion, and human studies on mizaj evaluation for all participants in any age group, sex, race, etc. Animals, paraclinical articles, and low-quality articles based on critical appraisal tools were excluded from our study. 2.3. Search Strategy In the absence of a specific word suitable for the concept of mizaj in MeSH terms, the words used in the title and keywords were extracted in the initial search. Then, the final words were selected for the search based on the opinion of PM experts. A search strategy was developed based on the keywords found, and the search was conducted by abstract and title. The databases query syntaxes are shown in the Supplementary Data. 2.4. Selection and Data Collection Process Researchers screened the titles of the found articles, and selected related articles to review their summary. Articles' abstracts were reviewed by two reviewers and the final articles were selected. References of final articles were also searched for relevant articles or gray literature. Articles on Unani medicine not related to PM, systematic reviews, animal studies, phytotherapy articles without mizaj diagnosis, PM studies using methods other than mizaj diagnosis, book chapters, letters, and case report articles were excluded from the study. 2.5. Risk of Bias Assessment Then, the found articles were critically reviewed by two reviewers using the Oxford Centre for Evidence-Based Medicine critical appraisal tools (CEBM) . If the two reviewers disagreed, a consensus was reached in the presence of a third reviewer. The articles that were not of sufficient quality to be included in the study were excluded, with the agreement of the reviewers. 2.6. Data Items Data including author names, date and location of study, year of publication, type of the study, sample size, age range or mean age, type of mizaj (WBM or organ mizaj), mizaj assessment tools' reliability and reliability values, and the number of questions of the tool were extracted from the articles. 2.7. Data Synthesis Data synthesis was performed by examining the text in the results section line by line, discussing it, and then identifying the proper items. Finally, data from the articles were extracted and summarized in the tables. 3. Results 3.1. Characteristics of the Included Studies In this study, by searching the electronic databases, 1812 articles were found, out of which 148 articles were removed due to similarity. After excluding the articles according to the exclusion criteria, 57 studies remained. . Then, the articles were subjected to critical appraisal to evaluate their quality . According to the consensus of two reviewers, three articles by Dashty, Yazdanifaro, and Zarghami were excluded from the review. Dashti and Yazdanifar's articles did not receive a score for the most important feature, which is related to the random selection of the sample and the appropriate selection of the sample, and also did not provide a proper explanation of the characteristics of the test. The method of performing the test in patients is not fully explained. Zarghami's article did not provide specifications that determine the sensitivity and specificity of the test. On the other hand, the test was not performed in a suitable range of society and the sampling method was not random . Thus, 54 articles were included in the final review of the study. As most of the studies used some limited questionnaires (Mojahedi, Salmannejad, etc.), critical appraisal using the CEBM tool was performed for articles using the new method of mizaj assessment. Due to the lack of a standard mizaj questionnaire, most of the second and third columns after the assessment are red. 3.2. Mizaj Determination Out of the 54 articles included in the study, 47 articles were related to the diagnosis of WBM. The diagnosis of WBM in 37 studies was made using a questionnaire, of which 30 studies used the Mojahedi questionnaire and 7 used the Salmannejad questionnaire . In addition, in 10 studies, an expert panel was used to determine the mizaj. Meanwhile, there is a study that used both the Mojahedi questionnaire and an expert panel to assess WBM . Out of the 54 articles found, six articles investigated the organ mizaj. Four articles involved uterine mizaj, one study used a scientifically developed questionnaire to assess the uterine mizaj , and the other two studies used a researcher-developed questionnaire to assess uterine mizaj. One of the studies to assess organ mizaj was related to the mizaj of the brain and another to the dystemperament of the digestive system . Except for one study conducted in India using the Mojahedi questionnaire , all other studies were conducted in Iran (Table 1). After reviewing the articles found, only four questionnaires were found with reported reliability and validity (Table 2). Figure 2 Critical appraisal of primarily included studies. Q1 = Was the diagnostic test evaluated in a representative spectrum of patients (like those on whom it would be used in practice)? Q2 = Was the reference standard applied regardless of the index test result? Q3 = Was there an independent blind comparison between the index test and an appropriate reference ('gold') standard of diagnosis? Q4 = Are test characteristics presented? Q5 = Were the methods for performing the test described in sufficient detail to permit replication? Each row of the figure corresponds to a critical evaluation of the articles: Shahabi , Yazdanifar , Sohrabvand , Mojahedi , Mirtaheri , Roshandel , Mozaffarpur , Zarghami , Mojahedi , Salmannezhad , Hoseinzadeh , Moradi , Dashty , Tansaz , Asghari , Mojahedi , Mozaffarpur . = Yes, = NO, = Unclear. Figure 3 Critical appraisal chart. 3.3. Mizaj Assessment Tools Novel questionnaires were introduced in four studies and were used in other studies. They include: 3.3.1. Mojahedi Questionnaire Developed by a group of 10 PM experts, it is a self-report questionnaire containing 10 items (8 in hotness/coldness and 2 in dryness/wetness). It was designed in 2012 to 2013 in Tehran, Iran, to assess WBM in 20-40 healthy volunteers. The researchers had a good design to develop the scale and assessed the reliability and validity of the questionnaire. It is the most widely used WBM assessment tool in mizaj studies (28 out of 49 studies including review studies). Its internal consistency is 0.7, but the average consistency of the fields of the questionnaire is 55.5% (hotness: 65%, coldness: 52%, dryness: 53%, wetness: 53%). 3.3.2. Salmannejad Questionnaire A well-designed self-report questionnaire with 20 items (15 in hotness/coldness and 5 in dryness/wetness) was developed by a group of 15 PM experts in 2015-2017 in Babol, northern Iran. It can assess WBM in 20-60-year-old individuals. It was used in 4 out of the 49 included studies in this review. More items of the 10 criteria of the mizaj assessment (based on PM references) were used in this study. 3.3.3. Hoseinzadeh Questionnaire It is a quantitative tool for the diagnosis of gastrointestinal dystemperaments. The items were generated through an expert panel and literature review, and then given weight after the item reduction process. The researchers then designed software to calculate them. Its reliability is stated to be evaluated, but only internal consistency (standardized Cronbach's alpha) is reported. This means that the usual method of assessing reliability (test-retest) was not performed. The interpretation of the total score is also not explained. Furthermore, no cut-off point for the questionnaire is calculated, and the sensitivity and specificity of this tool are not reported. More importantly, the items of hotness/coldness and dryness/wetness of mizaj of gastrointestinal dystemperaments are not addressed in this study. 3.3.4. Tansaz Questionnaire It is a 12-item questionnaire to evaluate the uterine temperaments (mizaj) of infertile women in Iran. Nine of the items assess the hotness/coldness of the uterine mizaj and three of them assess the dryness/wetness. Item generation was performed using PM references. The rest of the method seems logical. Acceptable internal consistency, reliability, and validity are reported. However, the process of calculating cut-off points is ambiguous when interpreting the scores. Furthermore, no sensitivity and specificity as important indices are reported. 3.4. Expert Panel Method in Mizaj Assessment Some studies evaluated the mizaj using expert panels. Most of them made criteria based on PM references and then 1 to 15 experts evaluated the mizaj. Novel methods of expert panels were used in only two studies: 3.4.1. Asghari Method In this study, three PM experts (MD. Ph.D.) with at least 5 years of clinical practice experience with a break of at least 2 weeks visited 30 volunteers in two different sessions. Mizaj assessments were performed separately by experts for each participant and recorded on a sheet; then to finalize the diagnosis, an expert panel discussion was held. 3.4.2. Mizaj Assessment Methods in Amirkola Health and Aging Project (AHAP Cohort) This process was carried out on 2135 elderly people in two phases. In the first phase, 5 to 10 elderly people were examined daily by one PM expert for 20 min, and videos and audio files were recorded. At this phase, a researcher-made 74-question checklist was fulfilled and then the WBM and main organ mizaj were determined. Finally, the elderly people with a typical diagnosis of WBM (based on PM professional sentiment and expertise) were noted. The diagnosis was determined based on the clinical experience of the PM experts. At the end of this phase, 268 elderly people were identified as typical. Their files were evaluated in the second phase (expert panel sessions). In the second phase, the files of the elderly people with typical diagnoses were evaluated in an expert panel with the presence of five PM experts for an average of 30 to 45 min. At first, the expert who visited the elderly person introduced the person without revealing the diagnosis. The audio and video files recorded by the examiner were then played on a TV set. Finally, all five present experts, without any discussion, recorded their diagnoses secretly and individually. Complete agreement was considered if at least four of the five experts made the same diagnosis (206 people). Otherwise, relative agreement or disagreement was considered. 4. Discussion According to the research strategy, a total of 1812 articles were found in the search in the electronic databases. After the process of the systematic review, 54 articles were finally included in the study. Among 45 articles in the field of WBM, 37 articles were conducted using the Mojahedi or Salmannejad mizaj assessment tools, which reported reliability and validity. The Mojahedi questionnaire is widely used in WBM assessment studies. Its internal consistency is acceptable (0.7), but the average consistency of the fields of the questionnaire is 55.5% (hotness: 65%, coldness: 52%, dryness: 53%, wetness: 53%). As an explanation, if the sensitivity is 50%, there are as many true positives as false negatives, indicating that the test is not useful in determining the true diagnosis . Additionally, as the minimum acceptable sensitivity + specificity value is 1.5 , it can only reach the minimum acceptable score in hotness, and cannot make a true diagnosis in coldness, dryness, and wetness. This may be because the final questionnaire does not use some indices that are important for mizaj assessment based on PM references. Therefore, the experts used these indices (as the gold standard in this study) to assess mizaj, but they were not used in the questionnaire. In this questionnaire, the moderate is so narrow that most of the population will be categorized as hot or cold mizaj or as dry or wet mizaj, which is not matched with the real diagnosis based on experts and references. Additionally, in dryness/wetness, only two items out of 10 indices of PM references are used and the other eight types of indices are dismissed. The sensitivities of moderate mizaj have not been reported, neither in hotness/coldness nor in dryness/wetness. This questionnaire is developed to identify the mizaj of healthy individuals. However, it has been used in some studies at younger or older ages or in diagnosing the mizaj of unhealthy people . This means that in these studies, it was used in areas for which it was not developed. Compared with the Mojahedi questionnaire, the Salmannejad questionnaire has a wider age range (20-60 years old). In this study, sensitivities of moderates in hotness/coldness and dryness/wetness were evaluated. Since this questionnaire has more items than the Mojahedi questionnaire, the ranges of moderates are wider. Although the questionnaire has acceptable internal consistency, in subgroups other than dryness, which has an acceptable minimum sensitivity + sensitivity score (>1.5), other factors (hotness, coldness, wetness, and moderates) did not reach the minimum expectable values. Compared with the Mojahedi questionnaire, the Salmannejad questionnaire has higher sensitivity and lower specificity generally. This means that the Salmannejad questionnaire is better for screening mizaj in research. Out of six documents found on the diagnosis of organ mizaj, one article was on the diagnosis of digestive mizaj, four articles were on the diagnosis of uterine mizaj, and one article was on the diagnosis of brain mizaj. None of these studies took scientific steps to develop valid and reliable questionnaires. In most of them, items were generated and used to determine mizaj based on the opinion of the researchers and using the PM references. Two of them introduced a questionnaire. The Hoseinzaheh questionnaire that was developed for the diagnosis of gastrointestinal dystemperaments is interpreted as weak because, except for internal consistency, the usual methods of assessing reliability (test-retest) and validity are not reported. Additionally, in Tansaz's questionnaire on uterine mizaj, its sensitivity and specificity are not reported. Therefore, this questionnaire is also interpreted as weak. In studies that assessed mizaj based on an expert panel model, only the Asghari method and AHAP method introduced a clear method. None of these studies can provide a standard model for mizaj assessment. Our review found some other types of studies that are related to the concept of the mizaj but did not meet our inclusion criteria. Most of them are preliminary studies to develop new valid and reliable diagnostic tools. The first category is articles that help conceptualizations. As the goal of our study was the practical method of evaluating mizaj, these articles were removed during the study . The second type of these studies are the articles that evaluated the current situation of mizaj assessment, in the absence of valid and reliable diagnostic tools . These articles can help to monitor the validity and reliability of the mizaj assessment over time. The third type of the studies aimed to give weight to each proposed index of mizaj assessment (based on PM references) to develop a final diagnostic tool. Some of these studies evaluated the unconscious effect of indices on the mizaj assessment . In some other studies, PM experts were asked to give weight to each index (10 criteria of mizaj assessment based on PM references) . In some other studies of this type, each proposed criterion was evaluated in correlation with the final diagnosis of mizaj . Our study had some limitations. Although all the articles that used the PM-based mizaj assessment methods were reviewed, the details of the methods of mizaj assessment were not given in most of the articles. The limitation of language was another limitation of our search strategy. Based on our prediction, the entire articles should be published in Persian or English, but it may be helpful to be able to search in other languages. The lack of definite words related to the concept of mizaj in the MeSH database was another limitation of our study. Therefore, in the preliminary primary search stage, we tried to extract related keywords from related articles. Based on our systematic review, there is still no valid and reliable tool or questionnaire as the gold standard in PM. Designing and developing new diagnostic tools to identify mizaj in both WBM and organs is strongly suggested. We also propose that future studies use new statistical methods that are used in the field of personalized medicine to assess the relationship between paraclinical criteria and mizaj. We also propose assessing all physiological parameters in healthy individuals and defining the companionship or interrelationships of these parameters. This pathway can be used as a parallel model to establish a gold standard for categorizing people. This means that all clinical and paraclinical parameters can be used in this way, rather than limiting ourselves to PM reference criteria for determining the mizaj. Additionally, the mizaj assessment may require evaluation of the correlation between a set of indicators and the final diagnosis, and it is not sufficient to check each criterion individually with the final diagnosis. 5. Conclusions In this systematic review, we found two questionnaires for evaluating WBM, neither of which is sufficiently reliable and valid. Two other questionnaires for organ mizaj assessment are poorly designed and lack sufficient reliability and validity. Developing a new valid tool to assess mizaj requires preliminary studies on conceptualization, weighting the indices (described in PM references), consensus building in history taking and physical examination, and using new approaches in personalized medicine. Acknowledgments The authers thanks student research committee of Babol university of medical Sciences. Supplementary Materials The following supporting information can be downloaded at: Click here for additional data file. Author Contributions M.A., H.S. and S.A.M. contributed to the conceptualization and supervision of the article. M.A., H.S. and S.A.M. contributed to the establishment of the methodology and the literature research. All authors (M.A., H.S. and S.A.M.) contributed to writing, critically revising and editing the content of the article, and approved the final article for submission to Diagnostics. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The protocol of the study was approved by the ethics committee of Babol University of Medical Sciences (code: IR.MUBABOL.HRI.REC.1401.176) and the Persian version of the protocol is visible at (accessed on 7 November 2022). The English version of the protocol is not registered anywhere. Informed Consent Statement Not applicable. Data Availability Statement The data presented in the present systematic review are available upon request from the corresponding author. Conflicts of Interest The 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 PRISMA 2020 flow diagram of included studies. diagnostics-13-00818-t001_Table 1 Table 1 Final included studies. Authors Date and Location of Study Study Type Population Sample Size Sample Age Way of Mizaj Diagnosis Type of Mizaj Reliability and Validity of the Questionnaire Number of Questions Shahabi et al., 2007 * - Iran Cross-sectional Healthy person 37 20-40 Expert panel Whole body mizaj Not reported - Mojahedi et al., 2014 - Iran Instrument design Healthy person 52 20-40 Expert panel Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Sohrabvand et al., 2014 * 2012 Iran Cross-sectional Infertile women 54 20-40 Self-designed questionnaire for uterine Uterine and whole body mizaj Cronbach's alpha > 0.7 12 Mirtaheri et al., 2015 2013 Iran Cross-sectional Overweight women 135 18-30 Expert panel Whole body mizaj - - Parvizi et al., 2016 - Iran Cross-sectional Healthy person 86 20-40 Expert panel and Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Safari et al., 2016 * 2014 Iran Cross-sectional Healthy person 109 healthy people 20-27 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Dehnavi et al., 2016 * 2014-2015 Iran Cross-sectional People with premenstrual problems 65 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Jafarnejad et al., 2016 2015 Iran RCT Women with premenstrual syndrome Case = 35, control = 30 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Roshandel et al., 2016 - Iran Instrument design Healthy person 197 18-70 Expert panel Innate and acquired mizaj Cronbach's alpha = 0.912 for innate and 0.825 for acquired mizaj First = 26, second = 56 Mohebbi et al., 2017 * 2016 Iran Cross-sectional Healthy women 200 <20 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Shakeri et al., 2017 * 2014 Iran Clinical trial Healthy person 70 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Zendehboodi et al., 2017 - Iran - Healthy male 247 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Safari et al., 2017 * 2014-2015 Iran Cross-sectional Healthy person 119 22.29 +- 2.02 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Salmannezhad et al., 2017 2016 Iran Cross-sectional Healthy person 610 20-30 Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Zar et al., 2017 * 2014 Iran Cross-sectional Healthy person 60 - Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Mozaffarpur et al., 2017 - Iran Cross-sectional Healthy volunteers 150 18-40 Expert panel Whole body mizaj - - Tokaman nezhad et al., 2018 * 2017 Iran Cross-sectional Pregnant women 169 Mean age = 27.7 +- 5.3 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Salmannezhad et al., 2018 - Iran Instrument design Healthy person 221 20-60 Expert panel Whole body mizaj Cronbach's alpha coefficient equal to 0.77-0.80 20 Hoseinzadeh et al., 2018 - Iran Instrument design Healthy person 10 - Expert panel Gastrointestinal dystemperament Cronbach's alpha = 0.795 validity equal to 0.8 49 Tavoosi et al., 2018 * 2015-2017 Iran Cross-sectional Healthy person 293 22-24 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Nematollahi et al., 2018 2016 Iran Cross-sectional Healthy volunteers 199 - Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Parvizi et al., 2018 2016 Iran Cross-sectional Healthy person 112 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Mojahedi et al., 2018 2016 Iran Cross-sectional Healthy person 74 19-40 Expert panel Whole body mizaj - - Bahman et al., 2018 2013-2015 Iran Case study Healthy women 150 18-45 Sohrabvand uterine questionnaire Uterine temperament Cronbach's alpha > 0.7 12 Ilkhani et al., 2019 2015 Iran Case-control Type 1 diabetes mellitus patients and healthy controls Case = 68, control = 80 Mean age = 10.0 +- 6.2 Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Moradi et al., 2019 2009-2010 Iran Cross-sectional PatientS with abnormal uterine bleeding 70 15-45 Questionnaire according to PM textbook Uterine dystemperaments Not reported 19 Banaei et al., 2019 * 2017-2018 Iran Cross-sectional Healthy person 300 23 +- 4.48 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Safari et al., 2019 * - Cross-sectional Healthy men 100 18< Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Safari et al., 2019 * 2013-2014 Iran Cross-sectional Healthy person 40 22.48 +- 5.4 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Farhadinezhad et al., 2019 * - Iran Cross-sectional Healthy person 196 - Salmannejad Mizaj questionnaire Whole body mizaj Cronbach's alpha coefficient equal to 0.77-0.80 20 Rostami et al., 2019 * 2016 Iran Cross-sectional 113 prisoners, 113 non-prisonerS 226 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Rajabzadeh et al., 2019 2017 Iran Cross-sectional Healthy men 105 18-35 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Vahedi et al., 2020 * - Cross-sectional Diabetic patients 100 patients 18< Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Tansaz et al., 2020 2013 Iran Instrument design Infertile females 54 20-40 Uterine mizaj questionnaire Uterine mizaj Cronbach's alpha of 0.73 to 0.69 12 Farsani et al., 2020 - Iran Cross-sectional Healthy volunteers 45 18-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Asghari et al., 2020 2016 Iran Case-control Healthy volunteers 30 20-40 Expert panel Whole body mizaj - - Kaviani et al., 2020 2018 Iran Cross-sectional Patients with abnormal uterine bleeding 112 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Zareivash et al., 2020 * 2019 Iran Cross-sectional Healthy person 165 20-60 Salmannejad Mizaj questionnaire Whole body mizaj Cronbach's alpha coefficient equal to 0.77-0.80 20 Banaei et al., 2020 * 2017-2018 Iran Cross-sectional Healthy person 296 23 +- 4.48 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Mehr 2020 * 2017 Iran Cross-sectional Healthy housewife 144 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Aliabadi et al., 2021 2019 Iran Cross-sectional Healthy females 340 20-32 Salmannejad Mizaj questionnaire Whole body mizaj Cronbach's alpha coefficient equal to 0.77-0.80 20 Aliabadi et al., 2021 - Iran - Healthy men 135 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Mojahedi et al., 2021 * 2015-2017 Iran Instrument design Diabetic children - - Expert panel Mizaj of diabetic child - 11 Zendehboodi et al., 2021 2018 Iran Case-control Healthy person Case = 110 Control = 181 >20 Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82,Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Khosrojerdi et al., 2021 * 2017 Iran Cross-sectional 60 healthy, 60 addictS) 120 25-32 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Parvizi et al., 2022 - Iran - Healthy males 217 20-40 Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Noori et al., 2022 2020 Iran Cross-sectional Healthy person 145 26-60 Salmannejad Mizaj questionnaire Whole body mizaj Cronbach's alpha coefficient equal to 0.77-0.80 20 Abbasian et al., 2022 2015-2017 Iran Case-control multiple sclerosis patients and healthy person Case = 42, Control = 54 18-50 Expert panel and Mojahedi's Mizaj questionnaire Whole body and brain mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Ghods et al., 2022 2020 Iran Cross-sectional Healthy person 34 Mean age = 37.11 +- 7 Mojahedi's Mizaj questionnaire Whole body mizaj kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Nasiri et al., 2022 * 2021 Iran Descriptive study COVID-19 patient 168 patientS 18-60 Salmannejad Mizaj questionnaire Whole body mizaj Cronbach's alpha coeffcient equal to 0.77-0.80 20 Sultana et al., 2022 2019 India Cross-sectional People with amenorrhoea 80 14-50 Mojahedi's Mizaj questionnaire Whole body mizaj Cronbach's alpha = 0.71 10 Mozaffarpur et al., 2022 2020 Iran Cross-sectional Healthy volunteers 324 20-40 Expert panel Whole body mizaj - - Mojahedi et al., 2022 2016-2017 Iran Cohort Elderly person 1541 >60 Expert panel Whole body mizaj - - Razavi et al., 2022 2020 Iran Cross-sectional CTS patients 170 20< Salmannejad Mizaj questionnaire Whole body mizaj Cronbach's alpha coeffcient equal to 0.77-0.80 20 * These articles are in Persian. diagnostics-13-00818-t002_Table 2 Table 2 Details of articles with questionnaires. Questionnaire Type of Mizaj Assessment Number of Items Validity and Reliability Number of Experts Mojahedi et al., 2014 * WBM 10 kappa coefficient: 0.4-0.82, Cronbach's a coefficient: 0.71, content validity index of each item: 0.70-1.00 10 Salmannezhad et al., 2018 * WBM 20 Cronbach's alpha coefficient equal to 0.77-0.80 15 Hoseinzadeh et al., 2018 Dystemperament of gastrointestinal system 49 Cronbach's alpha = 0.795 validity equalto 0.8 14 Tansaz et al., 2020 Uterine mizaj 12 Cronbach's alpha of 0.73 to 0.69 1 * WBM = whole body mizaj. 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. |
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