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We further acknowledged that GWAS implemented in individuals of Asian ancestries have not only validated the potential role of previously specified obesity susceptibility loci but also exposed novel ones, which have been missed in the initial genetic studies in individuals of European ancestries. Thus, multi-ethnic studies have a great potential not only to contribute to a better understanding of the complex etiology of human obesity but also potentially of ethnic differences in the prevalence of obesity, which may ultimately pave new avenues in more targeted and personalized obesity treatments.Recently, a few animals have been frequently reported to have been diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Whether they are SARS-CoV-2 intermediate hosts is worthy of great attention. The interaction of SARS-CoV-2 spike protein and its acceptor protein ACE2 is an important issue in determining viral host range and cross-species infection, while the binding capacity of Spike protein to ACE2 of different species is unknown. Here, we used the atomic structure model of SARS-CoV-2 and human ACE2 to assess the receptor utilization capacity of ACE2s from 10 kinds of animals. Results show that chimpanzees, domestic cats and cattles are more susceptible to infection by SARS-CoV-2. Cats in particular, such as pet cats and stray cats, interact very closely with humans, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic. Furthermore, based on ACE2(cats)-SARS-CoV-2-RBD model, through high-throughput screening methods using a pool of 30,000 small molecules, eight compounds were selected for binding free energy calculations. All the eight compounds can effectively interfere with the binding of ACE2 and Spike protein, especially Nelfinavir, providing drug candidates for the treatment and prevention of SARS-CoV-2, suggesting further assessment of the anti-SARS-CoV-2 activity of these compounds in cell culture. Although we only reported the results of the simulation, and more laboratory and epidemiological investigation are required. FKBP inhibitor Like cats are a risk factor, we can further detect SARS-CoV-2 according to the susceptibility of different animals, find the potential host of infection, and completely cut off the living space of the virus. Especially, cats could be a choice of animal model for screening antiviral drugs or vaccine candidates against SARS-CoV-2.Salvia species have been widely used as medicinal plants and have played an important role in the treatment and recovery of individuals with COVID-19. In this study, we reported two newly identified whole chloroplast genome sequences of Salvia medicinal plants (Salvia yangii and Salvia miltiorrhiza f. alba) and compared them with those of seven other reported Salvia chloroplast genomes. These were proven to be highly similar in terms of overall size, genome structure, gene content, and gene order. We identified 10 mutation hot spots (trnK-rps16, atpH-atpI, psaA-ycf3, ndhC-trnV, ndhF, rpl32-trnL, ndhG-ndhI, rps15-ycf1, ycf1a, and ycf1b) as candidate DNA barcodes for Salvia. Additionally, we observed the transfer of nine large-sized chloroplast genome fragments, with a total size of 49,895 bp (accounting for 32.97% of the chloroplast genome), into the mitochondrial genome as they shared >97% sequence similarity. Phylogenetic analyses of the whole chloroplast genome provided a high resolution of Salvia. This study will pave the way for the identification and breeding of Salvia medicinal plants and further phylogenetic evolutionary research on them as well.The unprecedented proliferation of recent large-scale and multi-omics databases of cancers has given us many new insights into genomic and epigenomic deregulation in cancer discovery in general. However, we wonder whether or not there exists a systematic connection between copy number aberrations (CNA) and methylation (MET)? If so, what is the role of this connection in breast cancer (BRCA) tumorigenesis and progression? At the same time, the PAM50 intrinsic subtypes of BRCA have gained the most attention from BRCA experts. However, this classification system manifests its weaknesses including low accuracy as well as a possible lack of association with biological phenotypes, and even further investigations on their clinical utility were still needed. In this study, we performed an integrative analysis of three-omics profiles, CNA, MET, and mRNA expression, in two BRCA patient cohorts (one for discovery and another for validation) - to elucidate those complicated relationships. To this purpose, we first established a set of CNAcor and METcor genes, which had CNA and MET levels significantly correlated (and anti-correlated) with their corresponding expression levels, respectively. Next, to revisit the current classification of BRCA, we performed single and integrated clustering analyses using our clustering method PINSPlus. We then discovered two biologically distinct subgroups that could be an improved and refined classification system for breast cancer patients, which can be validated by a third-party data. Further studies were then performed and realized each-subgroup-specific genes and different interactions between each of the two identified subgroups with the age factor. These findings can show promise as diagnostic and prognostic values in BRCA, and a potential alternative to the PAM50 intrinsic subtypes in the future.RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data.