Internal states adjust the Brp compartmental heterogeneity through octopamine. by Hongyang Wu (8856740)

“…*<i>P</i> < 0.05 and ns = not significant. The data underlying this Figure can be found in S1 Data.…”

Data Sheet 2_Comparison of percutaneous vs. cutdown access for endovascular aortic repair in the treatment of type B aortic dissection: a meta-analysis.pdf by Zhongyou Liang (22617608)

“…No statistically significant differences were observed between the two groups concerning estimated blood loss, ICU admissions, hematoma, acute kidney injury, lower extremity revascularization, ischemic colitis, and deep venous thrombosis.…”

Evolutionarily conserved and functionally important amino acids in Artemis. by Ziwen Huang (17562948)

“…<i>P</i> values were analyzed with Student <i>t</i> test. ns, not significant.</p>…”

SEAwise Report on the impacts of fisheries on stocks and landings under SEAwise EBFM by Dorleta Garcia (12315201)

“…The ecosystem model generally showed less optimistic outcomes under climate change, with significant decreases in biomass and catches in both the Celtic and North Seas. …”

FLEXI interactions with RNA-binding proteins. by Jun Yao (9646)

“…RNA-binding sites: I, within introns corresponding to FLEXIs; SS-I and SS-E, bimodally enriched across the 5’- and 3’ splice sites in unspliced pre-mRNAs with the midpoints in the intron or flanking exon (SS-I and SS-E, respectively; Figs <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.g004" target="_blank">4A</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.s011" target="_blank">S11</a>). mRNA levels, RBPs whose knockdown resulted in significant difference in mRNA levels (increased or decreased, DESeq2 |LFC|≥1, adjusted p≤0.05) from host gene of FLEXIs with a binding site for that RBP compared to those genes whose transcripts lacked a binding site for the same RBPs based on ENCODE RBP-knockdown datasets (p≤0.05 calculated by Fisher’s exact test; <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1011416#pgen.1011416.s013" target="_blank">S13 Fig</a>). …”

Ybx1 regulation of its target mRNAs is m⁵C-depdendent (Related to Fig 5). by Jian Zhang (1682)

“…<p><b>(A)</b> RT-qPCR confirmed the decreased expression levels of Ybx1 target mRNAs in neural stem cells with Ybx1 knockdown using siRNA. …”

Table 1_COVID-19 pandemic increased ESKAPEEc bloodstream infections and amplified carbapenem resistance in Chinese children: a multicenter surveillance study (2016–2023).xls by Xiaoqiang Li (612879)

“…Between 2016–2019 and 2020–2023, resistance to ceftazidime and gentamicin decreased in Escherichia coli and Klebsiella pneumoniae while resistance to imipenem and meropenem increased. …”

Supplementary file 1_An expert patient program for people living with multiple sclerosis improves knowledge and empowerment: a pre-test, post-test multicenter implementation study.... by Miguel Ángel Robles-Sánchez (21211703)

“…Lifestyle habits remained mostly unchanged, except for medication self-management and diet, whereas visits to nurses and other professionals in MS units significantly decreased. Physical health composite scores in the MS quality of life-54 questionnaire decreased, while the mental health composite scores remained unchanged. …”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

Minimal test data set by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Data Sheet 1_Perceived benefits and barriers to the use of long-acting injectable antiretroviral treatment among adolescents and young people living with HIV in Western Kenya: qual... by Shukri A. Hassan (14245301)

“…Introduction<p>Adolescents and young people living with HIV (AYPLHIV) face significant hurdles in adhering to daily oral antiretroviral therapy (ART). …”

Table 2_Kidney sparing surgery versus radical nephroureterectomy in upper tract urothelial carcinoma: a meta-analysis and systematic review.docx by Leqing Zhou (20981021)

“…In the comparison between the endoscopic management (EM) and RNU groups, EM was associated with worse overall survival outcomes (HR,1.40; 95%CI,1.08-1.82; P=0.01) based on multivariable Cox regression analysis, and the upper tract recurrence rate (OR,39.06; 95%CI, 14.55-104.85; P<0.00001) was significantly higher in the EM group. On the other hand, in patients treated with KSS, postoperative renal function as measured by eGFR increased by 0.4ml/min/1.73 m², while it decreased by 11.4ml/min/1.73 m² in the RNU group (WMD, 11.81 ml/min/1.73 m²; 95%CI,9.06-14.56; P<0.0001).…”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

OSNet network structure. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Data Sheet 2_Perceived benefits and barriers to the use of long-acting injectable antiretroviral treatment among adolescents and young people living with HIV in Western Kenya: qual... by Shukri A. Hassan (14245301)

“…Introduction<p>Adolescents and young people living with HIV (AYPLHIV) face significant hurdles in adhering to daily oral antiretroviral therapy (ART). …”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

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. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”