Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine.
The purpose of this study was to extend understanding of Chinese couples' enqing, a culturally specific component of marital affection that involves the expression of feelings of gratitude and admiration toward one's spouse. In this study, the authors examined family stress, spousal contributions, and sacrifices to study their possible effects on enqing in Chinese marriages. Participants were 455 married people living in northern Taiwan. Overall, the results highlighted the importance of spousal contributions and sacrifices in the development of marital enqing. Additionally, the results indicated that family stress moderated the spousal economic contribution--enqing relationship and the spousal sacrifices--enqing relationship for wives, but not for husbands.
Follicular fluid (FF) accumulates in the antrum of the ovarian follicle and provides the microenvironment for oocyte development. FF plays an important role in follicle growth and oocyte maturation. The FF provides a unique window to investigate the processes occurring during buffalo follicular development. The observed low quality of buffalo oocytes may arise from the poor follicular microenvironment. Investigating proteins found in buffalo FF (BFF) should provide insight into follicular development processes and provide further understanding of intra-follicular maturation and oocytes quality. Here, a proteomic-based approach was used to analyze the proteome of BFF. SDS-PAGE separation combined with mass spectrometry was used to generate the proteomic dataset. In total, 363 proteins were identified and classified by Gene Ontology terms. The proteins were assigned to 153 pathways, including signaling pathways. To evaluate difference in proteins expressed between BFF with different follicle size (small, <4 mm; and large, >8 mm), a quantitative proteomic analysis based on multi-dimensional liquid chromatography pre-fractionation tandem Orbitrap mass spectrometry identification was performed. Eleven differentially expressed proteins (six downregulated and five upregulated in large BFF) were identified and assigned to a variety of functional processes, including serine protease inhibition, oxidation protection and the complement cascade system. Three differentially expressed proteins, Vimentin, Peroxiredoxin-1 and SERPIND1, were verified by Western blotting, consistent with the quantitative proteomics results. Our datasets offers new information about proteins present in BFF and should facilitate the development of new biomarkers. These differentially expressed proteins illuminate the size-dependent protein changes in follicle microenvironment.
The testicular seminiferous tubules contain Sertoli cells and different types of spermatogenic cells. They provide the microenvironment for spermatogenesis, but the precise molecular mechanism of spermatogenesis is still not well known. Here, we have employed tandem mass tag coupled to LC-MS/MS with the high-throughput quantitative proteomics technology to explore the protein expression from buffalo testicular seminiferous tubules at three different developmental stages (prepuberty, puberty, and postpuberty). The results show 304 differentially expressed proteins with a ≥2-fold change, and bioinformatics analysis indicates that 27 of these may be associated with spermatogenesis. Expression patterns of seven selected proteins were verified via Western blot and quantitative RT-PCR analysis, and further cellular localizations of these proteins by immunohistochemical or immunofluorescence analysis. Taken together, the results provide potential molecular markers of spermatogenesis and provide a rich resource for further studies on male reproduction regulation.
The identification which uses biological characteristics has been a current top in the recent past. However, numerous spoofing skills occur with the rising prosperity of advance recognition technology, especially in the detection and recognition of a face. In allusion to the problem above, more robust and accurate face spoofing detection schemes have been put forward. Convolutional neural networks (CNNs) have demonstrated extraordinary success in face liveness detection recently. In this study, an effective face anti-spoofing detection method based on CNN and rotation invariant local binary patterns (RI-LBP) has been proposed. First, the authors use CNN to extract deep features and use RI-LBP to extract colour texture features. In addition, the principal component analysis approach is employed to decrease the dimensions of deep characteristic. Moreover, two different features are fused before applying to support vector machine (SVM). Finally, the SVM classifier is adopted to identify genuine faces from fake faces. They have conducted extensive experiments to obtain a scheme of better generalisation capability for face anti-spoofing detection. The analysis results indicate that the proposed approach implements great generalisation capability over other state-of-the-art approaches within the intra-databases and cross-databases.
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