Background Sleep duration and snoring are correlated with tumorigenesis while their associations with esophageal squamous cell carcinoma (ESCC) are unclear. The purpose of this study is to investigate the impacts of night sleep duration and snoring on ESCC risk. Methods This study included a total of 527 esophageal squamous cell carcinoma patients and 505 gender- and age- matched healthy controls from five hospitals in China. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by conditional logistic regression models. Results Subjects with sleep duration <7 h (adjusted OR 3.18, 95%CI 1.55-6.53) and regular snoring (adjusted OR 2.56, 95%CI 1.82-3.59) were exposed to high esophageal squamous cell carcinoma risk. After the multivariate models adjusted for body mass index (BMI), the results changed slightly. In the stratified analysis regarding gender, the similar trends occurred in both men and women, and BMI ≥25.0 kg/m 2 (adjusted OR 0.68, 95%CI 0.48-0.96) was associated with decreased esophageal squamous cell carcinoma risk in men. Additionally, the esophageal squamous cell carcinoma risk attributable to sleep duration <7 h and regular snoring could be completely or partially diminished in subjects with BMI ≥25.0 kg/m 2 . Conclusion In both genders, short sleep duration (<7h) and regular snoring were significantly related to increased risk of esophageal squamous cell carcinoma independently.

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The unique structures of polynuclear MoxSy clusters make them maximize the number of active sites, being good candidates as HER catalysts. An appropriate support is highly necessary not only to...

Ubiquinone is an important cofactor that plays vital and diverse roles in many biological processes. Ubiquinone-binding proteins (UBPs) are receptor proteins that dock with ubiquinones. Analyzing and identifying UBPs via a computational approach will provide insights into the pathways associated with ubiquinones. In this work, we were the first to propose a UBPs predictor (UBPs-Pred). The optimal feature subset selected from three categories of sequence-derived features was fed into the extreme gradient boosting (XGBoost) classifier, and the parameters of XGBoost were tuned by multi-objective particle swarm optimization (MOPSO). The experimental results over the independent validation demonstrated considerable prediction performance with a Matthews correlation coefficient (MCC) of 0.517. After that, we analyzed the UBPs using bioinformatics methods, including the statistics of the binding domain motifs and protein distribution, as well as an enrichment analysis of the gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway.

In this research, we applied the physical and chemical characteristics of porous polysilicon to field emission. Porous polysilicon field emitter was fabricated by anodized, oxide, et al technology. Au film about lOnm thickness as grid was used in device. Electrons emission property of device was measured in ultrahigh vacuum chamber. Also, the oxide time as effect factor to emission property was studied.