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. …”

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.…”

Image 3_Kidney sparing surgery versus radical nephroureterectomy in upper tract urothelial carcinoma: a meta-analysis and systematic review.tif 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).…”

YOLOv8 overall framework. 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. …”

The performance of YOFGD model on MOT16. 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. …”

Table 1_Targeting nail psoriasis: IL-17A inhibitors demonstrate site-specific superiority over IL-23 inhibitor in a 24-week dermoscopy-guided real-world cohort.docx by Xiamei Yan (21014921)

“…</p>Results<p>(1) By week 24, PASI, BSA, DLQI and NAPSI scores had significantly decreased from baseline in all groups (P<0.001). (2) By week 24: SEC, IXE, and GUS groups saw nail matrix NAPSI score improvements of 65.9%, 60.5%, and 51.5%, with 68%, 55%, and 30% achieving NAPSI 60; Nail bed NAPSI score improvements were 58.8%, 68.6%, and 65.8%, with 28%, 65%, and 40% achieving NAPSI 60; Total NAPSI score improvements were 62.7%, 64.6%, and 53.7%, with 44%, 70%, and 30% achieving NAPSI 60. (3) All patients in the SEC and IXE groups achieved PASI 75, compared to 85% in the GUS group. …”

Table1_Adverse event signal mining and severe adverse event influencing factor analysis of Lumateperone based on FAERS database.docx by Yanjing Zhang (401134)

“…Conversely, concomitant use of CYP3A4 inhibitors or drugs metabolized by CYP3A4 was associated with a decreased risk of severe AEs (OR = 0.524 [0.434, 0.633], P = 0.000).…”

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.…”

Table 1_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).…”

Network structure of OSA. 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_Metformin upregulates circadian gene PER2 to inhibit growth and enhance the sensitivity of glioblastoma cell lines to radiotherapy via SIRT2/G6PD pathway.docx by Hailiang Li (740080)

“…Meanwhile, NADPH+ production and G6PDH enzyme activity significantly decreased. Further study validated that metformin inhibited the cell growth of GBM cell lines through up-regulating PER2 and inhibited SIRT2/G6PD signaling pathway, enhancing radiotherapy(RT) sensitivity. …”

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.…”

The performance of S-YOFEO model on MOT17. 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. …”

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.…”

DataSheet1_Probiotics combined with prebiotics alleviated seasonal allergic rhinitis by altering the composition and metabolic function of intestinal microbiota: a prospective, ran... by Yangfan Hou (8043884)

“…From baseline to day 91, mean difference between groups (MDBG) in the reduction of TNSS was -1.1 (-2.2, -0.1) (P = 0.04); MDBG in the increment of TNF-α was 7.1 pg/ml (95% CI: 0.8, 13.4, P = 0.03); the INF-γ level was significantly increased (P = 0.01), whereas that of IL-17 (P = 0.005) was significantly decreased in the test group, whilst mean difference within groups was not statistically significant in the placebo group; MDBG in the increment of acetate was 12.4% (95% CI: 7.1%, 17.6%, P <0.001). …”