Figure 4 from Functional Profiling of p53 and RB Cell Cycle Regulatory Proficiency Suggests Mechanism-Driven Molecular Stratification in Endometrial Carcinoma by Zelei Yang (18491142)

“…<b>A,</b> A cartoon demonstrating the experimental setup is shown. …”

CARE-checklist JOSPT[1].docx by Sanjivani Bangde (19749151)

“…The patient’s pain levels decreased, and functional status improved as indicated by a reduction in score.…”

Lomie district map. by Arnauld Efon-Ekangouo (15295634)

“…</p><p>Conclusions/significance</p><p>The persistent high prevalence and intensity of STH infection despite 16 years of mebendazole-based PCT and expected collateral impact of ivermectin mass distribution, points to plausible implementation gaps, poor compliance to WASH or sub-optimal efficacy of the anthelminthics used. …”

DataSheet1_Pressure-tolerant survival mechanism of Schizophyllum commune 20R-7-F01 isolated from deep sediments 2 kilometers below the seafloor.csv by Mengshi Zhao (20157978)

“…In this study, we investigated Schizophyllum commune 20R-7-F01 isolated from coal-bearing sediments at a depth of 2 km below the seafloor. By assessing the cell viability, biomass, and cell wall thickness changes of strain 20-7-1 under different HHP conditions, we observed that, compared to 0.1 MPa, strain 20-7-1 exhibited slower growth rates and decreased cell viability at 15 MPa and 35 MPa, yet demonstrated significant pressure tolerance. …”

Flow chart. by Aysenur Karakus (21192337)

“…Both TTH and migraine groups received PRT twice a week for six weeks,</p><p>Results</p><p>Within-group comparisons showed significant decreases in attack frequency, VAS, HIT-6, PCS, and WHODAS-II scores in both groups post-intervention (p<0.001). …”

Presentation1_Pressure-tolerant survival mechanism of Schizophyllum commune 20R-7-F01 isolated from deep sediments 2 kilometers below the seafloor.pdf by Mengshi Zhao (20157978)

“…In this study, we investigated Schizophyllum commune 20R-7-F01 isolated from coal-bearing sediments at a depth of 2 km below the seafloor. By assessing the cell viability, biomass, and cell wall thickness changes of strain 20-7-1 under different HHP conditions, we observed that, compared to 0.1 MPa, strain 20-7-1 exhibited slower growth rates and decreased cell viability at 15 MPa and 35 MPa, yet demonstrated significant pressure tolerance. …”

Figure 5 from Functional Profiling of p53 and RB Cell Cycle Regulatory Proficiency Suggests Mechanism-Driven Molecular Stratification in Endometrial Carcinoma by Zelei Yang (18491142)

“…<b>A,</b> A cartoon demonstrating the experimental setup is shown. …”

Data Sheet 1_Balancing conservation and community needs: challenges, threats, and socioeconomic disparities in Kakamega Forest, Kenya.docx by Ibrahim Osewe (21460079)

“…Illegal logging emerged as the most significant threat to KFE, regardless of wealth category, followed by a lack of awareness of conservation efforts, with significant differences in perception across wealth categories. …”

AI KRegression by CHIN-CHENG CHU (20718575)

“…<p dir="ltr">The single-axis Sample Entropy (X-axis) only slightly decreased from 0.095 ± 0.054 to 0.080 ± 0.048 (p = 0.025*), and the Y-axis also only decreased from 0.106 ± 0.046 to 0.090 ± 0.043 (p = 0.025*), indicating that the complexity changes in a single direction are limited. …”

Table2_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table13_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table12_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table3_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table9_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Image1_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.tif by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table7_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table6_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table11_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table8_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”

Table5_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. …”