Image 1_No change in key HIV target cell markers following initiation of three progestin-based hormonal contraception methods: findings from the CHIME study.jpeg by Marisa R. Young (7919255)

“…There were statistically significant but moderate absolute decreases in proportion of CD45+ and CD4+ T cells in CVL, and CD4+ T cells in blood, and increased proportion of CD69+ T cells in blood post-HC. …”

Table 3_No change in key HIV target cell markers following initiation of three progestin-based hormonal contraception methods: findings from the CHIME study.docx by Marisa R. Young (7919255)

“…There were statistically significant but moderate absolute decreases in proportion of CD45+ and CD4+ T cells in CVL, and CD4+ T cells in blood, and increased proportion of CD69+ T cells in blood post-HC. …”

Image 13_No change in key HIV target cell markers following initiation of three progestin-based hormonal contraception methods: findings from the CHIME study.tiff by Marisa R. Young (7919255)

“…There were statistically significant but moderate absolute decreases in proportion of CD45+ and CD4+ T cells in CVL, and CD4+ T cells in blood, and increased proportion of CD69+ T cells in blood post-HC. …”

DataSheet1_Updated evidence of the Naoshuantong capsule against ischemic stroke: a systematic review and meta-analysis of randomized controlled trials.docx by Cuilin Que (19743256)

“…Significant disparities in the incidence of adverse events between the NSTC and control groups were not observed. …”

Table 1_No change in key HIV target cell markers following initiation of three progestin-based hormonal contraception methods: findings from the CHIME study.docx by Marisa R. Young (7919255)

“…There were statistically significant but moderate absolute decreases in proportion of CD45+ and CD4+ T cells in CVL, and CD4+ T cells in blood, and increased proportion of CD69+ T cells in blood post-HC. …”

Image 10_No change in key HIV target cell markers following initiation of three progestin-based hormonal contraception methods: findings from the CHIME study.tiff by Marisa R. Young (7919255)

“…There were statistically significant but moderate absolute decreases in proportion of CD45+ and CD4+ T cells in CVL, and CD4+ T cells in blood, and increased proportion of CD69+ T cells in blood post-HC. …”

Image 5_No change in key HIV target cell markers following initiation of three progestin-based hormonal contraception methods: findings from the CHIME study.tiff by Marisa R. Young (7919255)

“…There were statistically significant but moderate absolute decreases in proportion of CD45+ and CD4+ T cells in CVL, and CD4+ T cells in blood, and increased proportion of CD69+ T cells in blood post-HC. …”

Supplementary file 1_Effects of nitrogen addition on SOC in alpine grasslands of the Qinghai-Tibetan Plateau and adjacent mountain regions: a meta-analysis.docx by Yanhui Ye (22775894)

“…The addition of nitrogen decreased the soil pH by 0.20 units and the soil C/N ratio by 1.7%. …”

Data Sheet 1_Immunotherapy for neuromyelitis optica spectrum disorder: a comparative analysis of efficacy and safety of azathioprine, mycophenolate mofetil, tacrolimus, and rituxim... by Jing Zhou (168494)

“…The annual relapse rate (ARR) significantly decreased after treatment with all four drugs. …”

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.…”

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.…”

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.…”

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

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

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

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