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0.406655 | 8389732c203c4c7c8bde2c63c3186d1d | Human biological media assayed for chemical biomarkers in CTD Exposure are now integrated with CTD Anatomy. An exposure study reports that the environmental chemical 2,4-dichlorophenol is measured in a variety of human media (here, bile, blood, serum, stomach, and urine). These terms are now linked to their corresponding pages in CTD Anatomy, allowing users to seamlessly traverse and find additional chemicals detected in the same media reported by other exposure studies, as well as peruse the chemical-induced phenotypes associated with them. This integration helps tie mechanistic toxicology to the exposome concept. | PMC9825590 | gkac833fig2.jpg |
0.5238 | 0079d1fd9f1b4b0b918460d130f90eea | ATP-binding cassete activity according to the most relevant flow cytometry markers. Violin plots showing the median and the interquartile range of ATP-binding cassette (ABC) activity. For each cytometry marker patient data is represented with low ABC activity on the left and high ABC activity on the right. *P<0.05; **P≤0.01; ***P≤0.001; ****P≤0.0001. | PMC9827156 | 10861.fig1.jpg |
0.447147 | ba9e43aa44a842b5a40d1cf91f3161e8 | ATP-binding cassete activity is associated with acute myeloid leukemia ontogeny. (A) Frequency of cytogenetic or molecular lesions in the ATP-binding cassette low (ABClow) group (left-hand bars) and the ABChigh group (right-hand bars). Mutated genes and KMT2A and core-binding factor (CBF) rearrangements were grouped according to the ontogenic classification from Lindsley et al.27 Colors reflect ontogenic specificity of mutated genes and cytogenetic abnormalities: de novo acute myeloid leukemia (AML) specific (red), TP53-mutated AML (green), secondary AML specific (blue), pan-AML (yellow), and other genes not included in the Lindsley study, (burgundy). *P<0.05; **P≤0.01; ***P≤0.001; ****P≤0.0001. (B) Box-plot of D JC-1 values distribution between de novo AML, TP53-mutated and secondary AML specific groups. ****P≤0.0001 | PMC9827156 | 10861.fig2.jpg |
0.368785 | 5f78a74cc86f4ec38bb87bd7222abad8 | Forest plot of significant parameters for event-free survival in multivariate analysis. Hazard ratio with 95% confidence interval, P values <0.05 are in bold. | PMC9827156 | 10861.fig3.jpg |
0.455416 | 9e407afda3fb435cae1ebda3ffd3547a | Plots of Kaplan-Meier overall survival (OS) curves comparison. (A) OS and relative survival (RS). (B) OS by categories of age. (C) OS by grade. (D) OS by Mortality-Related Morbidity Index. (E) OS by neurofibromatosis type 2 (NF2). (F) OS by surgical technique and location. | PMC9827205 | asj-2021-0213f1.jpg |
0.473492 | baff486245bf4b18b681772900a628a0 | (A) Analysis of HP1/Target hybridization and lambda exonuclease digestion by 8% PAGE. M, 20 bp DNA lander, lane 1, HP1, lane 2, Target, lane 3, HP1 + Target, lane 4, HP1 + Target + lambda exonuclease. (B) Fluorescence emission spectra of solution containing only MB (a), genome DNA of healthy tobacco plant (b), and in the absence of lambda exonuclease (c), total DNA of tobacco plant infected by A. alternata (d), and genome DNA of A. alternata (e). The concentrations of HP1, P1, MB, and lambda exonuclease are 1.0 μM, 1.2 μM, 1 μM, and 1 U, respectively. | PMC9827279 | d2ra05616j-f1.jpg |
0.573884 | 78e9fb4ba3c24d7baf99f18a071a2ea9 | Optimization of digestion time of lambda exonuclease (A), concentration of P1 (B), hybridization time of HP1 and genome of A. alternata (C), and formation time of intact Mg2+-dependent DNAzyme (D). Concentration of A. alternata genome was 0.1 ng L−1 in the above experiments. Error bars in the figures represent the standard deviations of three experiments, and the same below. | PMC9827279 | d2ra05616j-f2.jpg |
0.412648 | 9e12693bfbfd460ab57d8950a39ba3f4 | (A) Fluorescence intensity of the solutions at different genome concentrations of A. alternata. Arrow from a to h represents the genome concentrations of 0 pg L−1, 10 pg L−1, 15 pg L−1, 20 pg L−1, 30 pg L−1, 50 pg L−1, 0.1 ng L−1, and 0.2 ng L−1. (B) Linear correlation between fluorescence intensity and logarithm of A. alternata genome concentration from 10 pg L−1 to 0.1 ng L−1. Pg means picogram, and ng means nanogram. | PMC9827279 | d2ra05616j-f3.jpg |
0.481393 | b1f065fc793245118e3070e477ab7053 | Selectivity of the proposed method. Total genome of tobacco plant infected by TMV (1), CMV (2), A. alternata (7). Genome of Rastonia solanacearum (3), genome of Phytophthora nicotianae (4), genome of healthy tobacco plant (5), and genome of A. alternata (6). Concentration of A. alternata genome was 0.1 ng L−1 in the experiments. | PMC9827279 | d2ra05616j-f4.jpg |
0.479025 | 420e995e4abc4ffb86c9360ff1922b11 | Characterization of further alkylpyrones produced by E. coli expressing dquA. Compounds 1–8 were produced by E. coli‐dquA. | PMC9827899 | CBIC-23-0-g001.jpg |
0.449149 | 0d212b8c06024596b79b15f5b17e68f8 | Phylogenetic analysis of selected Firmicutes. Spore‐forming strains are depicted in orange. The dquA‐dquB‐like BGC is highly conserved in spore forming Gram‐positive (monoderm) Bacillaceae and Gram‐negative (diderm) Sporomusaceae but not in non‐sporulating Gram‐negative diderms. Phylogenetic tree based on 16S rDNA genes. Heterologous expression of dquA orthologs from highlighted strains in E. coli led to production of alkylpyrones. Strains to encode orthologs of DquA and DquB are labeled with green (type III PKS) and purple (putative ICMT) dots. | PMC9827899 | CBIC-23-0-g002.jpg |
0.464018 | 6fcf20812d274f44babd6c4a5328de66 | Heterologous production of DquA in vivo and purification of compounds 1 and 2. A) New hydrophobic compounds are produced by E. coli expressing dquA. B) Compounds 1 and 2 were elucidated as alkylpyrones by NMR. C) Determination of the double‐bond position in 2 by chemical modification and MS/MS analysis. | PMC9827899 | CBIC-23-0-g003.jpg |
0.439468 | 4238753c4cd14537a0965cda27032739 | Bioinformatic analysis of the dquA‐B gene locus. A) A two‐gene locus encoding a BpsA/BpsB‐like type III PKS/ICMT‐like methyltransferase is highly conserved in members of the diderm family Sporomusaceae. B) Phylogenetic tree based on type III PKSs shows branching in accordance with strain‐level phylogeny. Type III PKSs from Sporomusaceae branch together and share the BpsA containing Bacillaceae branch as closest group. | PMC9827899 | CBIC-23-0-g005.jpg |
0.426355 | c6386f0b22084d38b08bba20e9969af7 |
Figure1
KLF1 triggers metabolic reprogramming to induce cardiomyocyte proliferation and myocardial regenerationKLF1, as a transcription factor, regulates the proliferation, differentiation and energy metabolism reprogramming of cardiomyocytes by regulating different factors. KLF1 can upregulate myocyte enhancer factor 2-positive proliferating cell nuclear antigen-positive (Mef2
+PCNA
+, cyclin D1/2a) and dedifferentiation factors (Alcam and Sm22) to promote cardiomyocyte proliferation. In addition, KLF1 downregulates the PGC1α/PPARGC1A gene to impair mitochondrial function and further triggers glycolytic shunt, so as to provide energy for cardiomyocyte proliferation and myocardial regeneration. Mef2
+PCNA
+: myocyte enhancer factor 2-positive proliferating cell nuclear antigen-positive; Sm22: smooth muscle protein 22a; PPP: pentose phosphate pathway; SSP: serine synthesis pathway.
| PMC9828331 | 21378-t1.jpg |
0.421752 | bba97f79d5d8499c879bdebbaf9df43f | Time series of COVID-19 vaccine acceptance from July 2020 to March 2021 by country.Shown are the 23 countries with repeated data collection over time. “Yes” also includes respondents indicating they already received a vaccine. Within each country, there are 19 points representing a time-series across the 19 waves of the survey. (inset) Pooling data from all 23 countries, people who believe a larger fraction of their community will accept a vaccine are on average more likely to say they will accept a vaccine; this is also true within each included country (Supplementary Fig. S15). Source data are provided as a Source Data file. | PMC9828376 | 41467_2022_35052_Fig1_HTML.jpg |
0.4334 | a1baca011a474dd1a3468e3474ad850c | Within-country distributions of beliefs about descriptive norms.Plot of within-country distributions of beliefs about descriptive norms (“Out of 100 people in your community, how many do you think would take a COVID-19 vaccine if it were made available?”) during the experimental period (October 2020 to March 2021). To enable comparison with actual country-wide potential vaccine acceptance, these histograms are colored by whether they are below (red) the narrow (“Yes” only) definition of vaccine acceptance, between (yellow) the narrow and broad (“Yes” and “Don't know”) definitions, or above (teal) the broad definition. Source data are provided as a Source Data file. | PMC9828376 | 41467_2022_35052_Fig2_HTML.jpg |
0.419273 | 383664e20e5d452fb4ad398a4b2a0b06 | Treatment effects on beliefs and intentions.(left) Effect on beliefs about descriptive norms. Coefficients on treatment from a regression of beliefs about norms on treatment status, including centered covariates and interactions. In this analysis, treated respondents are those who receive the treatment before the question eliciting beliefs about norms. This will not agree, in general, with the treatment status for the main analysis given the randomized question order in the survey. There are n = 304,840 responses in the masking analysis, n = 70,078 in the physical distancing analysis, and n = 356,004 in the vaccination analysis. (right) Effect on intentions. Coefficients from regression of intentions on treatment, centered covariates, and their interactions. There are n = 323,085 responses in the masking analysis, n = 85,619 in the physical distancing analysis, and n = 365,593 in the vaccination analysis. Error bars are 95% confidence intervals centered around mean estimates. Source data are provided as a Source Data file. | PMC9828376 | 41467_2022_35052_Fig3_HTML.jpg |
0.394972 | 78c47a9e2fb44351a02bfb7bec6c4040 | Effect of intervention on vaccination intentions.a The normative information treatments shift people to higher levels of vaccine acceptance, whether compared with receiving no information (control) or information about other, non-vaccine-acceptance norms (other behavior). The figure shows estimated distribution of vaccine acceptance responses for n = 464,533 respondents. b These estimated effects are largest for respondents who are uncertain about accepting a vaccine at baseline and respondents with baseline beliefs about descriptive norms that are under (rather than above or between) both of the levels of normative information provided in the treatments. There are n = 365,593 responses in the average analysis, n = 362,438 responses in the baseline vaccine acceptance analysis, and n = 113,438 responses in the beliefs about vaccine norms analysis. c While there is some country-level heterogeneity in these effects, point estimates of the effect of the broad normative information treatment are positive in all but one country (n = 365,593 responses). Error bars are 95% confidence intervals centered around mean estimates. Source data are provided as a Source Data file. | PMC9828376 | 41467_2022_35052_Fig4_HTML.jpg |
0.458084 | ff38560f1d314e5488f135888cbf2226 | Rosettes of asci from crosses between Neurospora metzenbergii 8881 and (a) the Sk‐2 backcross strains or (b) the Sk‐3 backcross strain. For crosses to Sk‐2, nearly all asci are aborted without producing spores of any kind, but occasionally will produce an ascus with small aborted spores (*). For Sk‐3 crosses, asci contain only small aborted spores most of the time, but occasionally viable spores are found (*). | PMC9828778 | EVO-76-2687-g001.jpg |
0.411384 | 32aa8f8d05304a23a69944a51852d931 | Proportion of black spores produced by crosses between four Neurospora metzenbergii strains (10395 [Mexico], 5119 [New Zealand], 7830 [New Zealand], and 8881 [Madagascar]) and four N. intermedia strains (3193 [Sk‐3], 7426 [Sk‐2], 7427 [Sk‐2], and 8761 [sensitive]). Horizontal lines represent half the value of the cross to 8761 to the given N. metzenbergii strain as an expectation for a decrease in germination due to spore killing alone. Asterisks represent significant deviations from this expectation according to a chi square test (* <0.05, ** <0.01, *** <0.001); whiskers denote one standard error. | PMC9828778 | EVO-76-2687-g002.jpg |
0.453985 | 3804f59e8c224800a4200cac44884644 | Global distribution of Neurospora intermedia and Neurospora metzenbergii. All strains from the Perkins collection at FGSC (http://www.fgsc.net) that were determined to be N. intermedia through crossing to reference strains are plotted. The geographic origins of those which were confirmed as N. intermedia through molecular evidence are shown in green, and those which were revealed to be N. metzenbergii are shown in purple. The “unknown” strains refer to isolates of N. intermedia with no molecular data. The inset is a magnified view of Mexico and surrounding regions. Note that strains with no precise locale data are visualized as midpoints in their country of origin, including three in Mexico. | PMC9828778 | EVO-76-2687-g003.jpg |
0.456235 | 97c726ea161040e0ba25175ad59354cc | Schedule of enrollment, interventions, and assessments from SPIRIT Guidelines. DASS-21 = Depression, anxiety and Stress Scale, BMQ = Brief medication questionnaire. | PMC9829266 | medi-102-e32295-g001.jpg |
0.461675 | 5ab5a38fc714489ab808220b2cf69536 | CONSORT 2010 flow diagram for the study. | PMC9829266 | medi-102-e32295-g002.jpg |
0.487767 | 5de2ce82d2364c2fbd1da4ae448ca95f | Data collection timeline at the lab scheduled before allocation and repeated upon intervention completion. BP= blood pressure, v = variability, RCBA = resting carotid body activity, CPET = cardiopulmonary exercise testing. | PMC9829266 | medi-102-e32295-g003.jpg |
0.444802 | 5df6171211f64d6b815c140606987d62 | Schematic presentation of TINF2 (a) gene and (b) protein, and localization of currently identified and previously discovered pathogenic variants for both DC and high cancer risk. TINF2 short isoform is a result of a small intron retention between exon 6 and 7 and the consequent stop codon [9]. Based on the cDNA analysis, c.936 C > A variant is stable only in this mRNA isoform. In exon 5, truncating variant c.591delG (p.Trp198fs) is associated with papillary thyroid carcinoma and melanoma [6], and a splice donor variant c.604G > C (with predicted truncations p.Glu202fs and p.Leu170fs) and c.557del (causing frameshift and a stop codon, p.Ser186fs) are proposed as high-risk alleles for multiple cancer types [7]. A majority of missense and truncating variants associated with DC localize to exon 6, specifically to a highly conserved area called DC cluster [3]. Variants associated with high cancer risk are shown under schematic gene and protein illustrations, and DC variants above (ClinVar database, https://www.ncbi.nlm.nih.gov/clinvar/). Variant c.936 C > A (p.Tyr312Ter) is pointed by a red arrow. TERF2, ACD and TERF1 interaction sites are marked with diagonal stripes | PMC9829577 | 10689_2022_295_Fig1_HTML.jpg |
0.486154 | 029ea308b95a47ffa5dbadb1dd5baea0 | Overview of the image-assisted pico-dispenser (Picodis) setup. a Workflow of microcapillary dispensing to prepare a cell pellet dispensing experiment: (1) 3T3 cells in culture flask. (2) Cell centrifugation. (3) Removal of supernatant medium to yield a cell pellet that was retrieved by a pipettor. (4) Transfer of cell pellets into an unpulled glass microcapillary. (5) Insertion of steel plunger to the unpulled microcapillary. (6) Coupling of the unpulled microcapillary with the pulled microcapillary (tip), and transfer of cells from the unpulled microcapillary to the pulled capillary tip. (7) Decoupling of unpulled microcapillary and plunger, and completing the backfilling of cells into the pulled capillary tip. (8) Insertion of plunger into Picodis and securing it to the stepper actuator for linear displacement. (9) Insertion of loaded tip into Picodis. (10) Securing the tip in the Picodis housing. (11) Spatial positioning of tip into the final position. (12) Stepping control for cell extrusion. (13) Cell deposition into phosphate buffered saline (PBS) bath for cell deposition characterisation. (14) Deposition into 96-well plate vials for offline imaging. (15) Offline imaging via inverted microscope. b Example of a pulled glass microcapillary used in this study. c A broken microcapillary caused by continuous stepping after the steel plunger reached the conical part of the microcapillary. d A steel plunger immersed in cell culture medium. e A microcapillary tip immersed in PBS in a rectangular container to obtain a sharper edge definition for accurate dimensional measurement | PMC9829649 | 42242_2022_205_Fig1_HTML.jpg |
0.469926 | d41daa490dc545ae96b339b0414409ff | Controllability for liquid dispense. a In the null-loading case, an example of the plunger movement triggered by 10,000-step actuation at a rate of 500 steps/s (Video S2 in Supplementary Information). b In the fluid-loaded case, meniscus control with the colouring ink in the microcapillary tip (ID=39 µm) in air, with images showing two consecutive 50-step actuations, as shown in Video S3 in Supplementary Information (Scale bar=100 µm). c Example of the process of droplet generation and retraction using colouring ink through a microcapillary tip (ID=49 µm), as shown in Video S4 in Supplementary Information (Scale bar=100 µm). d Droplets generated with 1000-step actuation and lateral movement of the tip, as shown in Video S5 in Supplementary Information. Consistency was observed after first ejection (Scale bar=200 µm). e Correlation between the number of steps per injection and the generated droplet diameter for tips of different inner diameter (ID) openings at 1000 steps/s | PMC9829649 | 42242_2022_205_Fig2_HTML.jpg |
0.431362 | 1cce19f2570d46beb3dc246a5a1ff55b | Sedimentation of cells in a microcapillary loaded with cell suspension. a Image showing inhomogeneous cell distribution within the microcapillary when it was left flat before fitting to the dispenser. b The relative positions of about 1×103 cells during the sedimentation process. Normalised frequency histograms of c the horizontal velocity and d the vertical velocity of cells during sedimentation. e A trapped air bubble inside a microcapillary, as shown in Video S7 in Supplementary Information. f Close-up images showing inhomogeneous cell density behind an air bubble within a microcapillary at 70 s from the start of imaging, corresponding to Video S8 in Supplementary Information (Scale bar=50 µm). g Intensity profiles along the cross-sectional lines of the microcapillary at 900, 585 and 180 µm from the meniscus. h Images showing the time-dependent accumulation of cells above the meniscus. i Intensity profiles at 23, 54 and 85 s (since the start of imaging) obtained along the horizontal dashed line, which is 180 µm from the meniscus (Scale bar=50 µm) | PMC9829649 | 42242_2022_205_Fig3_HTML.jpg |
0.434505 | 849e894b0d5a4cd9add8b81f8a56c3d8 | Visualisation of sedimented cell aggregation, compaction and microcapillary tip blockage during ejection experiment. a Inner diameter profile of the pulled microcapillary at the narrow end of the tip. The positions of cell front at different time points and the total number of input steps (N) were labelled. b Video frames captured from Video S9 in Supplementary Information showing the cell front positions during two significant jumps in the advanced cell-medium volume. c Plot of actual volume of cell-medium that advanced over the number of input steps applied | PMC9829649 | 42242_2022_205_Fig4_HTML.jpg |
0.42213 | df494d6defff4cf79791c9cfc2b19190 | Cell pellet extrusion through microcapillary. a Microcapillary filled with a high density of cell aggregate. b Image of the experimental setup used for injecting cell aggregates into a microplate prefilled with culture media. As shown, the purged cell aggregate through the microcapillary tip in air initiated the microcapillary tip for the experiment prior to immersion into vials. c Variability in the number of cells ejected when different sizes of microcapillary tip were used. The number of cells was counted within 10 min after the ejection experiments. The mean values were indicated (Scale bar=50 µm) | PMC9829649 | 42242_2022_205_Fig5_HTML.jpg |
0.453635 | d7c01fdd96c74778b936c4bde8a54784 | Forms of cell pellet exiting a microcapillary tip. a Images showing cell pellet extrusion experiments using different sizes of microcapillary tips. b–e Flow of ejected cells using b a 85-µm ID microcapillary tip with 100-step actuation; c the same parameters as b with 0.2 mm at 0.5-Hz side-to-side movement of the tip; d A 32-µm ID tip with 250-step actuation and e a 22-µm ID tip with 1000-step actuation. f Relative position of ejected cells in the b–e experiments. The mean speed of the cells, \documentclass[12pt]{minimal}
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0.434535 | a455d3bfa8dc4697aa251fbe656df8b1 | Summary of observed cell and microcapillary tip interactions during cell extrusion deposition | PMC9829649 | 42242_2022_205_Fig7_HTML.jpg |
0.428069 | ebffebfcd4654427a2c65302b1246f5a | Schematic diagram of the discrete event simulation model. EP, electrophysiologist; CBA, cryoballoon ablation; RFA, irrigated point-by-point radiofrequency ablation; PVI, pulmonary vein isolation. The figure represents a schematic diagram of the discrete event simulation model. On each day, patients arrive at the EP lab for the PVI procedure and experience a one-time delay prior to being available for the case (including a “no delay” time option). When the patient is available, the case will proceed with a randomly selected procedure duration according to the FREEZE Cohort procedure time distribution. Once the procedure is over, the patient leaves the EP lab | PMC9830778 | 12872_2022_3015_Fig1_HTML.jpg |
0.456499 | 364d67c8e20a47a9bf86e68f4b71824f | FREEZE Cohort procedure time details. The figure represents the box-plots for CBA and RFA procedure time distributions | PMC9830778 | 12872_2022_3015_Fig2_HTML.jpg |
0.468748 | 1c6476a0cc9c41f3bc86d4040577ef73 | FREEZE Cohort mean procedure times per center. The figure represents the average procedure time for CBA and RFA per center | PMC9830778 | 12872_2022_3015_Fig3_HTML.jpg |
0.524349 | cb3ef4dbb4f448469ccafc5ab3a8a3d7 | FREEZE Cohort mean procedure times per year. The figure represents the average procedure time for CBA and RFA per year during FREEZE Cohort study period | PMC9830778 | 12872_2022_3015_Fig4_HTML.jpg |
0.416071 | 9e85a96aace04b58b61289dc5a3c80e9 | PVI case begin and end times per day: subset simulated lab occupancy. A CBA centres and B RFA centres. The figure represents the begin and end times for a sampling of days from the simulation, with each contiguous vertical line indicating the time of lab occupancy (the bottom end indicating the case begin time and the top end indicating the case end time) for CBA (A) and RFA (B) procedures | PMC9830778 | 12872_2022_3015_Fig5_HTML.jpg |
0.427025 | 3a6f5e3655474634941d8ba21cf66564 | Discrete event simulation model results, 3 metrics after simulation of 1000 lab days. The Fig. 6 represents three DES model metrics after 1000 simulated lab days with PVI using CBA and 1000 using RFA. The metrics are the number of days with overtime, the number of days with an hour left at the end of the EP lab shift and the cumulative overtime in hours | PMC9830778 | 12872_2022_3015_Fig6_HTML.jpg |
0.426093 | 609fa365ecf8486d8d06b6fb7df70a04 | PLK1 and AURKB levels in TNBC are higher in AAs than in EAs.Bar graphs showing mitosis scores in the Emory (A) and Dekalb (B) cohorts. C Heatmap showing the expression levels of various kinases in the TCGA BC dataset. D, E Bar graphs showing the expression levels of PLK1 (D) and AURKB (E) in AA (n = 3) and EA (n = 3) TNBC cell lines. F–H Representative IHC images of PLK1 and AURKB (F) and quantification bar graphs showing PLK1 (G) and AURKB (H) levels in grade- and stage-matched AA and EA patients with TNBC (Dekalb cohort). I Immunoblot showing PLK1 and AURKB protein levels in AA and EA TNBC cell lines (n = 3 each). FPKM fragments per kilobase of transcript per million mapped reads. Bars indicate mean ± SEM. Unpaired two-tailed Student’s t-test with Welch’s correction was used to determine statistical significance (*P < 0.05, ***P < 0.0005, ns = non-significant). The scale bar represents 100 µm. | PMC9832024 | 41419_2022_5539_Fig1_HTML.jpg |
0.45058 | 95802d29c6c641eeb6fea91ffae2f95b | Survivin expression, localization, and phosphorylation in AAs and EAs with TNBC.A
BIRC5 expression level in AA and EA patients with TNBC (TCGA dataset). B Relative BIRC5 expression in AA and EA TNBC cell lines from Neve et al. (2006) (B) and our in-house TNBC cell lines (C) (n = 3 each). D Immunoblot showing survivin levels in AA (n = 3) and EA (n = 3) TNBC cell lines. E–G Representative IHC images (E) and bar graphs (F, G) showing survivin H scores in AA and EA patients with TNBC in the Dekalb (F) and Emory (G) cohorts. H IF images showing the localization of survivin (green) in AA and EA TNBC cell lines. Nuclei were stained with Hoechst (blue) and tubulin (red). I Immunoblot showing p-survivin (S20, T117) levels in AA and EA TNBC cell lines (n = 3 each). FPKM fragments per kilobase of transcript per million mapped reads, TPM transcripts per million mapped reads. Bars indicate mean ± SEM. Unpaired two-tailed Student’s t-test with Welch’s correction was used to determine statistical significance (*P < 0.05, ***P < 0.0005, ns = non-significant). Scale bars in E and H are 100 µm and 10 µm, respectively. | PMC9832024 | 41419_2022_5539_Fig2_HTML.jpg |
0.447594 | cd59a5dee867451da7624fe7fb7e15d9 | Silencing or inhibition of PLK1 and AURKB modulates survivin phosphorylation at S20 and T117 in AA TNBC cells.A, B Immunoblots showing the levels of PLK1, survivin, p-survivin (S20), and β-actin after PLK1 silencing (A, B) or inhibition (C) in AA and EA TNBC cell lines. D–F Immunoblots showing the levels of AURKB, survivin, p-survivin (T117), and β-actin after AURKB silencing (D, E), or inhibition (F) in AA and EA TNBC cell lines. | PMC9832024 | 41419_2022_5539_Fig3_HTML.jpg |
0.488782 | becc406330fd4e53a9642e36952b79fd | Survivin is crucial for cell proliferation and cell cycle progression in AA TNBC cells.A–C Representative immunofluorescence images (A, B) and quantification bar graphs (C) showing BrdU (green) incorporation in various AA (A) and EA (B) TNBC cell lines transfected with scrambled or survivin siRNAs. Nuclei were counterstained with Hoechst (blue) and tubulin (red). D–F Bar graphs showing BrdU incorporation in AA and EA TNBC cells treated with survivin siRNA (D), volasertib (E), and barasertib-HQPA (F). Absorbance was measured at 450–540 nm. G–I Flow cytometry analysis depicting various cell cycle phases in AA (G) and EA (H) TNBC cells treated with control (red), survivin siRNA (light blue), YM155 (dark green), volasertib (orange), and barasertib (bright green) and their quantification (I). Data were analyzed using FlowoJo. Bars indicate mean ± SEM. Unpaired two-tailed Student’s t-test with Welch’s correction was used to determine statistical significance (*P < 0.05, ***P < 0.0005, ns = non-significant). The scale bar represents 10 µm. | PMC9832024 | 41419_2022_5539_Fig4_HTML.jpg |
0.423868 | d1e6113cf00b4b64a422b355ac78ed46 | Inhibition of PLK1 and AURKB suppresses tumor growth and improves survival in nude mice bearing AA TNBC tumors.A Schematic diagram showing the treatment schedule for volasertib (green arrow) and barasertib (red arrow) in mice bearing AA and EA TNBC xenografts. B–F Representative tumor images (B), changes in tumor volume in AA (C) and EA (F) tumors, and tumor growth inhibition in mice with AA (n = 12) (D) and EA (n = 12) (G) TNBC xenografts. E, H Kaplan–Meier plots showing survival in mice bearing AA (n = 12) (E) and EA (n = 12) (H) xenografts. Bars indicate mean ± SEM. Unpaired two-tailed Student’s t-test with Welch’s correction was used to determine statistical significance (*P < 0.05, **P < 0.005, ****P < 0.00005, ns = non-significant). | PMC9832024 | 41419_2022_5539_Fig5_HTML.jpg |
0.43266 | 5e78dfc509b947708db6d19f8c4aa86a | Inhibition of PLK1 and AURKB decreases Ki-67 and p-survivin levels in mice bearing AA TNBC tumors.A–F Representative IHC images (A, B) and bar graphs (C–F) showing Ki-67 and survivin levels in AA (C, E) and EA (D, F) TNBC xenografts under various treatment conditions. G, H Immunoblots showing the levels of p-survivin (T117), p-survivin (S20), total survivin, AURKB, PLK1, and β-actin in AA (G) and EA (H) fresh-frozen xenograft tumor lysates from mice treated with volasertib, barasertib, or their combination (n = 12 per treatment group). Bars represent mean ± SEM. Unpaired two-tailed Student’s t-test with Welch’s correction was used to determine statistical significance (****P < 0.00005, ns = non-significant). The scale bar represents 100 µm. | PMC9832024 | 41419_2022_5539_Fig6_HTML.jpg |
0.440245 | a89cae3f3b6a4705ae1b669b9efe51ab | CPC complex formation is highest in S20-T117 double phospho-mimic survivin mutants.A Schematic representation of survivin-mutant plasmids. B–D Immunoblots (B, C) showing the levels of CPC proteins in input (B) and IP-bound (C) samples from cells expressing various survivin-WT and mutant plasmids, and their respective quantification (D). E Bar graphs showing the percentage of cell proliferation in control cells and in cells expressing survivin-WT and mutant plasmids. F Schematic illustration of YM155 treatment schedule in mice bearing tumors and surgically implanted with osmotic pumps. G–J Representative tumor images (G), changes in tumor volume (H), and changes in tumor size (I, J) in mice bearing AA (n = 12) and EA (n = 12) TNBC xenografts. Bars represent mean ± SEM. Unpaired two-tailed Student’s t-test with Welch’s correction was used to determine statistical significance (*P < 0.05, **P < 0.005, ns = non-significant). | PMC9832024 | 41419_2022_5539_Fig7_HTML.jpg |
0.447366 | 6bd8fb04e0bd4b07bbd1b4e138346b58 | Placing the implants on the gypsum model with the parallelometer. | PMC9832143 | jap-14-388-g001.jpg |
0.447465 | 16dec21e7eb541c092ffff07bde6d706 | Master model. | PMC9832143 | jap-14-388-g002.jpg |
0.46999 | e242272e51fa4fbd99b4aff217b0ecfd | Virtual reference model. | PMC9832143 | jap-14-388-g003.jpg |
0.455486 | 3fbe30148a25463a89cf15eb76074284 | Selection of implant areas on virtual model. | PMC9832143 | jap-14-388-g004.jpg |
0.442603 | 341b0e0cbd874d53a88d739b6ea7b25f | Superimposing. | PMC9832143 | jap-14-388-g005.jpg |
0.472686 | f3b81109ba54437c9016fad75d181c13 | Chart of accuracy (trueness and precision). | PMC9832143 | jap-14-388-g006.jpg |
0.411971 | ac989587cdfe423cb8862b0b023674d2 | Trueness of intraoral scanners. | PMC9832143 | jap-14-388-g007.jpg |
0.414482 | f5a61eae9c684b679930e6f0506e2de1 | Precision of all scanners. | PMC9832143 | jap-14-388-g008.jpg |
0.370783 | 9d69e596b5df451d84111c15865c057f | Quiescent Lrig1-lineage stem cells in the lateral wall of the adult mouse brain. A Control analysis of the Tg(Nr2e1-EGFP)/+ mouse brains. Orthogonal view after whole mount immunofluorescence and confocal microscopy. Scale bar, 10 μm. B An EGFP+ KI-67- ASCL1- cell filling the gap between S100+ ependymal cells, suggesting a B1 type stem cell identity. Scale bar, 10 μm. C The previously identified Lrig1-lineage stem cells largely did not incorporate EdU during one week pulse and did not contact the ventricle with an apical extension. Scale bar, 10 μm. D Analyses of additional mouse strains. E Dot plot of the distributions of the cell body locations. Black bars, mean ± standard deviation. Magenta bar, median. Student’s t test. F Histogram of the same distributions. Kolmogorov-Smirnov test. G Percentages of ventricle-contacting or non-ventricle-contacting cells. Chi-square test | PMC9832784 | 13064_2022_169_Fig1_HTML.jpg |
0.42862 | 7cc62c65e6e1407f85cb8349b3545049 | The Lrig1-lineage stem cells in the adult brain lateral wall were largely quiescent during juvenile development. A Control analysis of EdU administration in juvenile mice showed complete labeling without disrupting the KI-67+ cell or DCX+ cell numbers. Scale bar, 100 μm. B The EdU signal overlapped completely with the KI-67 signal. Scale bar, 100 μm. C EdU pulse-chase during juvenile development. Number of EdU+ nuclei per mm2. Mean ± standard deviation. D EdU then BrdU double pulse-chase during juvenile development. Mean ± standard deviation. E EdU pulse-chase during juvenile development then tamoxifen induction in adult age. Mean ± standard deviation. F A representative confocal image from one of the ventricular walls quantitated. Scale bar, 10 μm. G EdU pulse-chase during juvenile development then tamoxifen induction shortly after. A representative confocal image. Scale bar, 10 μm. H Additional time points of EdU pulses during juvenile development then tamoxifen induction in adults. Mean ± standard deviation | PMC9832784 | 13064_2022_169_Fig2_HTML.jpg |
0.4036 | 7a73298532474845b9d00b848c1f5c55 | The rare EdU label-retaining Lrig1-expressing cells. A-C The rare RFP+ EdU+ cells were identified from low magnification confocal scans then imaged again with a high magnification objective at the confocal. Scale bar, 10 μm | PMC9832784 | 13064_2022_169_Fig3_HTML.jpg |
0.399716 | 8f2c43458c104b829b57cea4fb985da9 | The Lrig1-expressing cells in the juvenile brain lateral wall. A Two morphologically distinct cells from tamoxifen induction during juvenile development. Scale bar, 10 μm. B The two distinct morphotypes remained after juvenile development. Scale bar, 10 μm. C Dot plot of the distributions of the cell body locations. Black bars, mean ± standard deviation. Magenta bar, median. Student’s t test. D Histogram of the same distribution. Kolmogorov-Smirnov test. E Percentages of ventricle-contacting or non-ventricle-contacting cells. Chi-square test. F Numbers of the cells’ branches during juvenile development. Mean ± standard deviation. Student’s t test | PMC9832784 | 13064_2022_169_Fig4_HTML.jpg |
0.380767 | a86c57e4fcf14af7921162617e1e6c29 | The Lrig1-expressing cells were largely quiescent during juvenile development. A Tamoxifen induction then EdU pulse during juvenile development. Two morphologically distinct subsets were again observed. Scale bar, 10 μm. B An RFP+ cell that was EdU-. Scale bar, 10 μm. C An RFP+ cell that was dimly EdU+. Scale bar, 10 μm. D A doublet of RFP+ EdU+ cells that did not contact the ventricle and were located in the subventricular zone. Scale bar, 10 μm | PMC9832784 | 13064_2022_169_Fig5_HTML.jpg |
0.402091 | e7686212ef0f493ba19a16cd69287621 | The Lrig1-expressing cells in the postnatal brain lateral wall. A RFP+ postnatal radial glial cells from tamoxifen induction during postnatal development. Scale bar, 10 μm. B VCAM1 expression in an RFP+ cell. Scale bar, 10 μm. C An RFP+ KI-67- cell. Scale bar, 10 μm. D Two distinct morphotypes at juvenile age after postnatal tamoxifen induction. Scale bar, 10 μm. E Two distinct morphotypes at young adult age after postnatal tamoxifen induction. Scale bar, 10 μm. F Unbranched RFP+ postnatal radial glial cells. Scale bar, 10 μm. G Branched RFP+ postnatal radial glial cells. Scale bar, 10 μm | PMC9832784 | 13064_2022_169_Fig6_HTML.jpg |
0.428738 | 440dd48ebfce48fa8923690c6c991806 | Fate of the Lrig1-expressing cells during postnatal/juvenile development. A Tamoxifen induction postnatally and EdU pulse during juvenile development. A doublet of RFP+ EdU- cells located in the subventricular zone. Scale bar, 10 μm. B A doublet of RFP+ EdU+ cells located in the subventricular zone. Scale bar, 10 μm. C Tamoxifen induction postnatally and EdU pulse-chase from juvenile development to young adult age. A singlet RFP+ EdU+ label-retaining cell. Scale bar, 10 μm | PMC9832784 | 13064_2022_169_Fig7_HTML.jpg |
0.360425 | 39d61666c45b47bd95fcf696f6d5cf3e | Lrig1 knock-out resulted in persistent hyperproliferation in the lateral wall even in old mice. A-C KI-67, ASCL1, or DCX immunoreactivity in 1 year and 3 month-old mice. Scale bar, 100 μm. D-E Graphs of KI-67+ and ASCL1+ cell counts. Mean ± standard deviation. Student’s t test. F-H KI-67, ASCL1, or DCX immunoreactivity in 2 years and 4 month-old mice. Scale bar, 100 μm. I-J Graphs of KI-67+ and ASCL1+ cell counts. Mean ± standard deviation. Student’s t test. K-N KI-67, ASCL1, DCX, or cleaved CASP3 immunoreactivity in 1 year and 8 month-old mice. Scale bar, 100 μm | PMC9832784 | 13064_2022_169_Fig8_HTML.jpg |
0.409526 | 5334244cc60d48b6acfb703ea4ebae2c | Schematic illustration of all steps of the microalgae-based biofuel production pipeline and how the developed GNT-Microfluidic chemostatic bioreactor system work. Algal cell structure serves goals of biodiesel production through the photosynthetic carbon fixation pathways the Calvin-Benson cycle | PMC9833044 | 40820_2022_993_Fig10_HTML.jpg |
0.42335 | 34d9da1459364ac9b5cc6877895dca3d | Nature-derived 2D materials fabrication and PEGylation (reprint with permission from Nature Publishing Group [263]) | PMC9833044 | 40820_2022_993_Fig11_HTML.jpg |
0.457813 | 7bb0ebdde91142248ec36dbbba6c3739 | Schematic illustration of upgradation of SP@AMF and its radioprotective mechanisms. I. Schematic illustration of the mechanism how SP protects AMF from gastric destruction. II–IV. Schematic illustration of the controlled releases AMF form the upgraded SP@AMF when traveling along the small intestine. V. Schematic illustration of the protection of SP@AMF from radiation-induced epithelial injury, inflammation, and fibrosis. VI. Schematic illustration of SP@AMF for maintaining the health of gut microbiota [267]. (Reprint with permission from Nature Publishing Group) | PMC9833044 | 40820_2022_993_Fig12_HTML.jpg |
0.421347 | 89dae037356444ef8070f8780c261909 | Schematic diagram of analogies between natural living materials (plants) and Syn-SCOBY materials for engineered living | PMC9833044 | 40820_2022_993_Fig13_HTML.jpg |
0.40722 | 31fe52214ea04a16987b856f5c69ed95 | a Examples of the delivery of cargo using solid micro/nanomotors: (a) cargo pick-up, (b) cargo delivery, and (c) cargo release, respectively. b Organic pollutants degraded by multifunctional micromotors in solutions. c Detection of nucleic acid, which alters the propulsion of the micro/nanomotors. d A catalytic nanomotor drilling into an immobilized cancer cell | PMC9833044 | 40820_2022_993_Fig14_HTML.jpg |
0.526114 | 3e166db7a3ab437eae947dc675eecac0 | Applications of the HALUB | PMC9833044 | 40820_2022_993_Fig1_HTML.jpg |
0.452445 | 746d2d93e0334056a9f437fc4ed1ea97 | Promising technologies for HALUB conversion to energy and materials | PMC9833044 | 40820_2022_993_Fig2_HTML.jpg |
0.437981 | d9671380401a4e7c812ff4da53b58912 | Basic constituents of biomass, a lignin, b cellulose, c xylans, and d glucomannan, respectively [27] | PMC9833044 | 40820_2022_993_Fig3_HTML.jpg |
0.483864 | 091245b20941482b8190d75a9dd752b4 | Schematic representation of the main processes for lignin extraction and possible chemical modifications performed in order to valorize lignin, depending on the applications [66] | PMC9833044 | 40820_2022_993_Fig4_HTML.jpg |
0.46616 | 2e6ed321ada648708a4d4010f7aaf230 | Schematic diagram of the deconstruction strategy of lignin [81] | PMC9833044 | 40820_2022_993_Fig5_HTML.jpg |
0.553359 | 863f7aff04b94c159f07cd64c76a64b5 | Overview of the chemical modifications of lignin: synthesis of new chemically active sites [82] | PMC9833044 | 40820_2022_993_Fig6_HTML.jpg |
0.469745 | 615e38bd55fb4993b5da4ebaba3614b9 | Electrochemical lignin valorization. Electro-oxidation at the anode via direct, mediated methods and via the generation of reactive oxygen species (ROS) from reduction of O2. Electroreduction via direct method. Water splitting competes with lignin electrochemical conversion at both anode (OER) and cathode (HER) | PMC9833044 | 40820_2022_993_Fig7_HTML.jpg |
0.396198 | 7699abbb37364dfc9032b250656ae96a | Application of machine learning workflow to predict new Pd(I) dimers | PMC9833044 | 40820_2022_993_Fig8_HTML.jpg |
0.419981 | ad99eda7356d485fa91059f5d3ffa815 | Application of machine learning in modeling of biomass thermochemical conversions. GPR: Gaussian process regression; SVM: support vector machine; RF: random forest (RF); ANN: artificial neural network | PMC9833044 | 40820_2022_993_Fig9_HTML.jpg |
0.398639 | 862dcdac1ee04ff8bc535a47573619dc | Sharply circumscribed depigmented patches ranging from 1 cm to 5 cm on the dorsum of both hands, forehead, cheeks, dorsum of the nose, and perioral region. | PMC9833350 | SEMB-56-572-g001.jpg |
0.44066 | 5486da17fa0f46c7be98b8ae63351923 | Surface orthokeratosis, flatness of epidermis, and loss of melanin in the basal layer. MELAN-A worked as immunohistochemical. | PMC9833350 | SEMB-56-572-g002.jpg |
0.46478 | b5e069fb3db14f5fa9e5c4793874e63f | Sixty days mortality among the groups. | PMC9833380 | NCI-9-557-g001.jpg |
0.438013 | ec77b11baae54cbbabd69212f533dce0 | The culture positivity in Group I (immunonutrients >9 days) was significantly higher than that in Groups II (immunonutrients 3–9 days) and Group III (immunonutrients <3 days). | PMC9833380 | NCI-9-557-g002.jpg |
0.523838 | a4e59d8e9cd540eab20fe5d6a1ac021e | The length of intensive care unit stay among the groups. | PMC9833380 | NCI-9-557-g003.jpg |
0.483324 | 6df92bad8ca04f20895077d1a56c5c69 | The relationship between physicochemical properties and activity of GPs. The different monosaccharide compostiton, molecular weight, glycosidic bonds and side-chains of GPs are responsible for its diverse activities; The alterations of GPs in several ginseng products depending on their processing methods also exert influence on its antitumor activities; The utilization of medicinal sites vary GPs from parts to parts, too. | PMC9834022 | gr1.jpg |
0.459043 | 5b5b596b525343c685badf8f2a1fa700 | The mechanisms of action of GPs as an immunomodulator. GPs play a fundamental role for antitumor effects in modulating the function of immunes cells such as NK cells, T cells, macrophages and neutrophils. The modes underlying are associated with the expression of CR3 in immune cells, regulation of Inflammatory pathways (NF-κB) and activation of animal lectins (galectin-3). | PMC9834022 | gr2.jpg |
0.472071 | fd752b6d3c814ff9a92d89eaa9f2e31d | Complex interplay among GPs, gut microbiota and host. By transforming the GPs in the host's digestive system, the microbiota, especially some probiotics, degrade dietary fibers and produce short-chain fatty acids, thus enhancing the immune system and curing the tumor. GPs also play a vital role in modulating the structure of gut microbiota through its prebiotic-like effects, which promotes the absorption, distribution, metabolism and excretion of other ginseng active components simultaneously. | PMC9834022 | gr3.jpg |
0.404645 | dc0e3c8fc2164f3ba23c59ad4425e97f | Other antitumor mechanisms of GPs. GPs might inhibit tumorigenesis via regulating the apotosis, modulating oxidative stress and weakening the migration and invasion of tumor cells. | PMC9834022 | gr4.jpg |
0.377755 | 9f31a6c576ab478ea1cdc3f2469b067e | RNA-Seq analysis of DEGs at 24 h after tMCAO in subcortical structures of the CH related to the corresponding brain samples from SO rats. (a) RNA-Seq results for IR-c versus SO-l. The numbers in the diagram sectors indicate the number of DEGs. (b) A volcano plot shows a comparison of the distribution of genes between the IR-c and SO-l groups. Upregulated and downregulated DEGs are represented as red and green dots, respectively (fold change > 1.50. Padj < 0.05). Not differentially expressed genes (non-DEGs) are represented as dark purple dots (fold change ≤ 1.50. Padj ≥ 0.05). (c) The top 10 genes that exhibited the greatest fold change in expression in IR-c vs. SO-l. The data are presented as the mean ± standard error (SE) of the mean. (d) RT–PCR verification of the RNA-Seq results. Data for the comparison between IR-c and SO-l are shown. Two reference mRNAs Gapdh and Rpl3 were used to normalize the PCR results. Each group included at least five rats. Six genes whose expression changed by > 1.5-fold from the baseline value and whose P-value was < 0.05 and two other genes were selected for analysis. The data are presented as the mean ± SE. | PMC9834327 | 41598_2023_27663_Fig1_HTML.jpg |
0.39073 | 815c60f303d844b6ba104bee68e1763f | Comparison of RNA-Seq results for the CH and IH relative to the SO controls. (a) Comparisons of data are presented. Blue arrows indicate comparisons of ischemic (IR) brain samples versus the respective hemisphere in SO control rats. (b–d) Schematic comparisons of the results obtained for pairwise comparisons of IR-i vs. SO-r and IR-c vs. SO-l as represented by Venn diagrams. Comparison for all (b), upregulated (c), and downregulated (d) DEGs. The cutoff for gene expression changes was 1.50-fold, and only those genes with Padj < 0.05 were selected for analysis. (e–g) The top 10 genes that exhibited the greatest fold change in expression for IR-i vs. SO-r (f) or IR-c vs. SO-l (e, g) and that were within the gene sets on the Venn diagram are presented (b–d). DEGs that overlapped in pairwise comparisons of IR-i vs. SO-r and IR-c vs. SO-l are shown (e). DEGs for IR-i vs. SO-r but non-DEGs for IR-c vs. SO-l are shown (f). DEGs for IR-c vs. SO-l but non-DEGs for IR-i vs. SO-r are shown (g). Data are presented as the mean ± SE. Genes whose fold change was > 1.50 and Padj < 0.05 relative to the comparison group are marked with an asterisk (*). (h) Hierarchical cluster analysis of all DEGs for IR-i vs. SO-r and IR-c vs. SO-l. Each column represents a comparison group, and each row represents a DEG. Green stripes represent a high relative expression level and red stripes represent a low relative expression (n = 3 per group). | PMC9834327 | 41598_2023_27663_Fig2_HTML.jpg |
0.500632 | cad1d5eb35cb448dae62a87380563f7e | Comparison of RNA-Seq results in the CH and IH relative to the SO rats showed an opposite directionality of changes in gene expression in two rat brain hemispheres at 24 after tMCAO. (a, b) Schematic comparisons of the results obtained in pairwise comparisons for IR-i vs. SO-r and IR-c vs. SO-l are represented by Venn diagrams. Comparison of only the upregulated DEGs for IR-i vs. SO-r and downregulated DEGs for IR-c vs. SO-l (a), and downregulated DEGs for IR-i vs. SO-r and upregulated DEGs for IR-c vs. SO-l (b) are shown. The cutoff for gene expression changes was 1.50-fold. Only those genes with Padj < 0.05 were selected for analysis. C. Sixteen DEGs that were downregulated for IR-i vs. SO-r and, conversely, upregulated for IR-c vs. SO-c are presented and were shown to lie within the intersection of the gene sets on the Venn diagram (b). Data are presented as the mean ± SE. | PMC9834327 | 41598_2023_27663_Fig3_HTML.jpg |
0.425359 | 2416a7a992534ebaa859323dd8329e05 | The functional networks of the DEGs with codirectionally changed mRNA levels in the two brain hemispheres after tMCAO. (a) In 69 of the 114 DEGs analyzed, significant associations with signaling pathways were observed using DAVID. (b) The DEGs associated with the MAPK signaling pathway (KP). Only those DEGs that had codirectionally changed mRNA levels (cutoff > 1.5; Padj < 0.05) in the comparisons IR-i vs. SO-r and IR-c vs. SO-l were selected for analysis. Only those pathways associated significantly (Padj < 0.05) with DEGs in the comparison IR-i vs. SO-r were selected for analysis. The networks were constructed using Cytoscape 3.8.2 software. The nodes indicate DEGs. Each line connecting the nodes indicates an involvement of the protein product of the corresponding gene in the signaling pathway functioning. | PMC9834327 | 41598_2023_27663_Fig4_HTML.jpg |
0.448208 | 2abc893336ec40dcbebaad46267b8b34 | Network showing the involvement of the DEGs that had oppositely changed mRNA levels for the signaling pathways modulated during IR in the two brain hemispheres after tMCAO. The network was constructed using Cytoscape 3.8.2 software. The nodes are designated as the DEGs or signaling pathways. Each line connecting the nodes indicates the involvement of the protein product of the corresponding gene in signaling pathway functioning. All clustered signaling pathways were annotated using KP, RP, and WP databases. The cutoff for mRNA expression changes was 1.50. Only those DEGs and annotations with Padj < 0.05 for each set of DEGs in the comparison IR-i vs. SO-r were selected for analysis. | PMC9834327 | 41598_2023_27663_Fig5_HTML.jpg |
0.441242 | a72e7cff387d4464b7497ca596785f2d | The image presents the pedigree of the family with long QT (LQT) syndromes, as well as the results of the electrocardiogram (ECG) and sequencing chromatograms of the mutated nucleotide in the KCNQ1 gene. A The pedigree of the family with LQT syndromes is presented herein. The proband is indicated with the arrow. B The Sanger sequencing results of the KCNQ1 gene in the patient and his family members are shown here. The patients carried a heterozygous nonsense variant: c.G968A. C The image demonstrates the poor region of the Kv11.1 schematic structure with the W323X variant. D This region includes amino acids conserved among humans, mice, rats, rabbits, and horses | PMC9835262 | 40001_2023_984_Fig1_HTML.jpg |
0.448181 | f9ce6d18e396480db43fd8fdf03b8730 | A The baseline 12-lead standard electrocardiogram indicates a normal sinus rhythm, a normal QRS frontal axis, and a normal corrected QT interval. B Four minutes after exercise cessation, the corrected QT interval is about 480 ms, deemed prolonged for this situation. C The image presents the leads of ambulatory monitoring. The corrected QT interval is normal in most of the leads but is prolonged in the right lower panel | PMC9835262 | 40001_2023_984_Fig2_HTML.jpg |
0.559609 | a1cb53df9e794cf395db188302ee380a | XRD patterns
of neat OMMT and PBAT/starch films with quercetin
and varying contents of OMMT. | PMC9835550 | ao2c05836_0002.jpg |
0.418604 | ce171693fb814d06a939a7d51a6d0fca | Influence of OMMT concentration on the
morphology of PBAT/TPS films.
The cross-sectional cryofractured surface recorded in the machine
direction for films: (a) PBAT/TPS, (b) PBAT/TPS/Q, (c) PBAT/TPS/Q/OMMT-0.9
vol %, (d) PBAT/TPS/Q/OMMT-1.75 vol %, (e) PBAT/TPS/Q/OMMT-2.61 vol
%, and (f) PBAT/TPS/Q/OMMT-3.34 vol %. | PMC9835550 | ao2c05836_0003.jpg |
0.442006 | 51f8b07126cd4b45a8e14e097484913e | FTIR spectra of PBAT/starch
films loaded with quercetin and different
amounts of OMMT. | PMC9835550 | ao2c05836_0004.jpg |
0.464345 | a5c83ac867944ec5a2e6585636b7a159 | (a) Complex
viscosities (η*) and (b) storage moduli (G′)
of PBAT/TPS blends loaded with quercetin and different amounts of
OMMT. | PMC9835550 | ao2c05836_0005.jpg |
0.418233 | 5f692ce5ad274fc9a0215485a443f518 | (a) Comparison between the experimental P/P0 and the data predicted using the Nielsen model
and Cussler model, (b) optimum values of OTR and WVTR for different
food packaging materials, and the comparison with the values for PBAT/TPS/Q/OMMT
films developed in this work. | PMC9835550 | ao2c05836_0006.jpg |
0.420812 | 3504ef3cfec048a6b781756cf6cccadc | (a) UV light transmittance and (b) antioxidant activity
of PBAT/starch
films modified with quercetin and OMMT. (c) Comparison of UV light
transmittance of PBAT/TPS/Q/OMMT-1.75 vol % after immersion in ethanol
for different times. | PMC9835550 | ao2c05836_0007.jpg |
0.455344 | 6c9750906f074be19650b3481cfc9f1d | Appearance
of (a) bananas and (b) blueberries during the storage
in different packaging films. | PMC9835550 | ao2c05836_0008.jpg |
0.494868 | 167ad8d0821843e29616548088e2fc26 | SEM images of (a) as-received
Class 5 RDX, (b) spray-dried RDX
using an ultrasonic nozzle, and (c) spray-dried RDX using a 0.7 mm
atomizing nozzle. | PMC9835642 | ao2c07011_0002.jpg |
0.488013 | e4ae66a445794b738dfa771fa476295e | Particle size distributions for spray-dried RDX powders
with various
nozzle sizes and types. (a) PSD for spray-dried RDX using the three
different sizes of atomizing nozzles, 0.7, 1.4, and 2.0 mm size openings.
(b) PSD for spray-dried RDX using the ultrasonic nozzle. | PMC9835642 | ao2c07011_0003.jpg |
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