The COVID-19 pandemic has dramatically changed the patterns of lifestyle and posed psychological stress on pregnant women. However, the association of sleep duration and screen time with anxiety among pregnant women under the backdrop of the COVID-19 pandemic scenario has been poorly addressed. We conducted one large-scale, multicenter cross-sectional study which recruited 1794 pregnant women across middle and west China. Self-reported demographic characteristics, lifestyle, and mental health status were collected from 6th February to 8th May 2020. We investigated the association of sleep duration and screen time with the risk of anxiety by multivariable logistic regression analysis and linear regression analysis after adjusting potential confounders. The dose-response relationship of sleep duration and screen time with anxiety was visualized using a cubic spline plot. Our data revealed that almost 35% of pregnant women suffered from anxiety during the COVID-19 pandemic. Sleep duration was dose-dependently associated with a lower risk of anxiety among pregnant women (OR = 0.41, 95% CI: 0.27–0.63), while screen time exhibited a conversed effect (OR = 2.01, 95% CI:1.00–4.39). Notably, sleep duration (≥8 h/day) synergistically combined with screen time (3–7 h/day) to diminish the risk of anxiety (OR = 0.70, 95% CI: 0.50–0.99). Taken together, sleep duration and screen time were independently and jointly associated with anxiety (P < 0.05). Therefore, promoting a more active lifestyle and maintaining higher sleep quality could improve the mental health of pregnant women, especially under public health emergency.

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Objective Accumulating evidence has shown that aberrant alternative splicing events are closely associated with the onset and development of cancer. However, whether genetic variants-associated alternative splicing is linked to risk of endometrial cancer remains largely uncertain. Methods We identified single nucleotide polymorphisms (SNPs) locates in the splicing number trait locus (sQTL) of endometrial cancer using the CancerSplicing QTL database. In parallel with bioinformatics analysis, we conducted a case-control study comprising 2,000 cases and 2,013 controls to assess the association between identified SNP which possesses mRNA splicing function and endometrial cancer susceptibility. Furthermore, we used the Kaplan-Meier Plotter, The Human Protein Atlas, SPNR, and Spliceman2 databases for sQTL and differential gene expression analyses to identify the genetic variant which most potentially influence the risk of endometrial cancer through alternative splicing to reveal the potential mechanism by which candidate SNPs regulate the risk of endometrial cancer. Results The results indicated that SNP rs7128029 A

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