Matched data. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Nomogram model. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Table 1_Plant-based diets and total and cause-specific mortality: a meta-analysis of prospective studies.docx by Qiwang Mo (9091292)

“…Participants in the highest quintile of both the PDI and hPDI had a significantly decreased risk of all-cause mortality (pooled HR_PDI = 0.85; 95% CI: 0.80–0.90; pooled HR_hPDI = 0.86; 95% CI: 0.81–0.92) compared to participants in the lowest quintile. …”

Flowchart of Study Design and Analysis. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Data Sheet 1_Changes in sST2 and NT-proBNP levels predict early cardiac arrhythmia in breast cancer patients treated with anthracycline-containing chemotherapies.pdf by Cuncun Chen (11842427)

“…</p>Results<p>sST2 levels increased significantly from baseline to C1 (P < 0.01). NT-proBNP levels decreased from baseline to C1 and C5 (P < 0.01). …”

Multivariate Binary Logistic Regression Analysis. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Table 1_Global, regional, and national esophageal cancer deaths and DALYs attributable to diet low in vegetables and fruits, 1990–2019: analysis for the global burden of disease st... by Bing Cui (179696)

“…The burden was greater in males than females, peaking in middle-aged groups. …”

ROC curve. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Image 2_Plant-based diets and total and cause-specific mortality: a meta-analysis of prospective studies.tif by Qiwang Mo (9091292)

“…Participants in the highest quintile of both the PDI and hPDI had a significantly decreased risk of all-cause mortality (pooled HR_PDI = 0.85; 95% CI: 0.80–0.90; pooled HR_hPDI = 0.86; 95% CI: 0.81–0.92) compared to participants in the lowest quintile. …”

Unmatched data. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Image 1_Plant-based diets and total and cause-specific mortality: a meta-analysis of prospective studies.tif by Qiwang Mo (9091292)

“…Participants in the highest quintile of both the PDI and hPDI had a significantly decreased risk of all-cause mortality (pooled HR_PDI = 0.85; 95% CI: 0.80–0.90; pooled HR_hPDI = 0.86; 95% CI: 0.81–0.92) compared to participants in the lowest quintile. …”

Calibration curve. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

Decision curves. by Feng Zhang (6548)

“…Decision curve analysis indicated that the net benefit of predicting false-negative IGRA results using this nomogram model was greater than 0 when the threshold probability ranged from 0.15 to 0.95.…”

The effect of IFN-β and Vit D on the IL-1β and IL-10 protein production. by Farzad Nasri (8941850)

“…IFN-β and Vit D alone or together decreased IL-1β and IL-10 protein level, significantly in comparison with the control <b>(A, B)</b>. …”

Table_1_Differential microbiome features in lake–river systems of Taihu basin in response to water flow disturbance.xlsx by Peng Xiao (172430)

“…In the ET region, where water flow disturbances were stronger, microbial richness significantly increased, and phylogenetic relationships were closer, yet variations in community structure were greater than in the ST region, which experienced milder water flow disturbances. …”

Image_1_Differential microbiome features in lake–river systems of Taihu basin in response to water flow disturbance.pdf by Peng Xiao (172430)

“…In the ET region, where water flow disturbances were stronger, microbial richness significantly increased, and phylogenetic relationships were closer, yet variations in community structure were greater than in the ST region, which experienced milder water flow disturbances. …”

Therapeutic Administration Success Rates. by Alani Mohanad Khalid Ahmed (22693496)

“…<p>Bar chart representing the Mean Therapeutic Administration Success Rates for the control group, treated groups (BM-MSC1, BM-MSC2, AD-MSC1, AD-MSC2), and untreated groups (Un-BM1, Un-BM2, Un-AD1, Un-AD2). …”

Integrated bioinformatic and experimental study links cyclin B1/B2 to poor prognosis and immune infiltration in endometrial cancer by Haikun Yang (14815742)

“…In TCGA cohort, high expression of CCNB1/CCNB2 correlated with greater disease severity and predicted poor prognosis. …”

Data Sheet 1_The impact of cell density variations on nanoparticle uptake across bioprinted A549 gradients.docx by Luigi Di Stolfo (21216599)

“…This inverse relationship correlated with greater average cell surface area in lower-density regions, while differences in the proliferation rates of the A549 cells at varying densities did not significantly impact uptake, did not significantly impact uptake.…”

Data Sheet 1_A machine learning model for predicting the risk of diabetic nephropathy in individuals with type 2 diabetes mellitus.docx by Tingting Li (10553)

“…The application of artificial intelligence holds promise for delaying renal deterioration and decreasing treatment expenses by facilitating early detection and intervention. …”