Bile acid receptors and nonalcoholic fatty liver disease

With the high prevalence of obesity, diabetes, and otherfeatures of the metabolic syndrome in United States, nonalcoholic fatty liver disease(NAFLD) has inevitably become a very prevalent chronic liver disease and is now emerging as one of the leading indications for liver transplantation. Insulin resistance and derangement of lipid metabolism, accompanied by activation of the pro-inflammatory response and fibrogenesis, are essential pathways in the development of the more clinically significant form of NAFLD, known as nonalcoholic steatohepatitis(NASH). Recent advances in the functional characterization of bile acid receptors, such as farnesoid X receptor(FXR) and transmembrane G protein-coupled receptor(TGR) 5, have provided further insight in the pathophysiology of NASH and have led to the development of potential therapeutic targets for NAFLD and NASH. Beyond maintaining bile acid metabolism, FXR and TGR5 also regulate lipid metabolism, maintain glucose homeostasis, increase energy expenditure, and ameliorate hepatic inflammation. These intriguing features have been exploited to develop bile acid analogues to target pathways in NAFLD and NASH pathogenesis. This review provides a brief overview of the pathogenesis of NAFLD and NASH, and then delves into the biological functions of bile acid receptors, particularly with respect to NASH pathogenesis, with a description of the associated experimental data, and, finally, we discuss the prospects of bile acid analogues in the treatment of NAFLD and NASH.

A cell marker-based clustering strategy(cmCluster)for precise cell type identification of scRNA-seq data

Background:The precise and efficient analysis of single-cell transcriptome data provides powerful support for studying the diversity of cell functions at the single-cell level.The most important and challenging steps are cell clustering and recognition of cell populations.While the precision of clustering and annotation are considered separately in most current studies,it is worth attempting to develop an extensive and flexible strategy to balance clustering accuracy and biological explanation comprehensively.Methods:The cell marker-based clustering strategy(cmCluster),which is a modified Louvain clustering method,aims to search the optimal clusters through genetic algorithm(GA)and grid search based on the cell type annotation results.Results:By applying cmCluster on a set of single-cell transcriptome data,the results showed that it was beneficial for the recognition of cell populations and explanation of biological function even on the occasion of incomplete cell type information or multiple data resources.In addition,cmCluster also produced clear boundaries and appropriate subtypes with potential marker genes.The relevant code is available in GitHub website(huangyuwei301/cmCluster).Conclusions:We speculate that cmCluster provides researchers effective screening strategies to improve the accuracy of subsequent biological analysis,reduce artificial bias,and facilitate the comparison and analysis of multiple studies.

VENAS:新冠病毒大规模基因组进化网络的快速分析方法

The comprehensive analyses of the SARS-CoV-2 genomes could provide a global picture of how the virus was transmitted among different populations,which may help predict the oncoming trends of the pandemic.The main approach for the molecular tracing of viral transmission is to thoroughly compare the genomes of different viral strains.

PNPLA3 and nonalcoholic fatty liver disease:towards personalized medicine for fatty liver

Nonalcoholic fatty liver disease(NAFLD)affects approximately 25%of the global population and the future clinical and economic consequences are enormous.