A cross-verified database of notable people, 3500BC-2018AD
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ABSTRACT:
SUBMITTER: Laouenan M
PROVIDER: S-EPMC9184645 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:UnlabelledMany cell lines can be reprogrammed to other cell lines by forced expression of a few transcription factors or by specifically designed culture methods, which have attracted a great interest in the field of regenerative medicine and stem cell research. Plenty of cell lines have been used to generate induced pluripotent stem cells (IPSCs) by expressing a group of genes and microRNAs. These IPSCs can differentiate into somatic cells to promote tissue regeneration. Similarly, many somatic cells can be directly reprogrammed to other cells without a stem cell state. All these findings are helpful in searching for new reprogramming methods and understanding the biological mechanism inside. However, to the best of our knowledge, there is still no database dedicated to integrating the reprogramming records. We built RPdb (cellular reprogramming database) to collect cellular reprogramming information and make it easy to access. All entries in RPdb are manually extracted from more than 2000 published articles, which is helpful for researchers in regenerative medicine and cell biology.Availability and implementationRPdb is freely available on the web at http://bioinformatics.ustc.edu.cn/rpdb with all major browsers supported.Contactaoli@ustc.edu.cnSupplementary informationSupplementary data are available at Bioinformatics online.
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Project description:MotivationPost-translational modification (PTM) is an important biochemical process. which includes six most well-studied types: phosphorylation, acetylation, methylation, sumoylation, ubiquitylation and glycosylation. PTM is involved in various cell signaling pathways and biological processes. Abnormal PTM status is closely associated with severe diseases (such as cancer and neurologic diseases) by regulating protein functions, such as protein-protein interactions (PPIs). A set of databases was constructed separately for PTM sites and PPI; however, the resource of regulation for PTM on PPI is still unsolved.ResultsHere, we firstly constructed a public accessible database of PTMint (PTMs that are associated with PPIs) (https://ptmint.sjtu.edu.cn/) that contains manually curated complete experimental evidence of the PTM regulation on PPIs in multiple organisms, including Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Currently, the first version of PTMint encompassed 2477 non-redundant PTM sites in 1169 proteins affecting 2371 protein-protein pairs involving 357 diseases. Various annotations were systematically integrated, such as protein sequence, structure properties and protein complex analysis. PTMint database can help to insight into disease mechanism, disease diagnosis and drug discovery associated with PTM and PPI.Availability and implementationPTMint is freely available at: https://ptmint.sjtu.edu.cn/.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Autoimmune diseases emerge due to several reasons, of which molecular mimicry i.e., similarity between the host's and pathogen's interacting peptides is an important reason. In the present study we have reported a database of only experimentally verified peptide sequences, which exhibit molecular mimicry. The database is named as miPepBase (Mimicry Peptide Database) and contains comprehensive information about mimicry proteins and peptides of both host (and model organism) and pathogen. It also provides information about physicochemical properties of protein and mimicry peptides, which might be helpful in predicting the nature of protein and optimization of protein expression. The miPepBase can be searched using a keyword or, by autoimmune disease(s) or by a combination of host and pathogen taxonomic group or their name. To facilitate the search of proteins and/or epitope in miPepBase, which is similar to the user's interest, BLAST search tool is also incorporated. miPepBase is an open access database and available at http://proteininformatics.org/mkumar/mipepbase.
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Project description:BackgroundThe modeling of interactions among transcription factors (TFs) and their respective target genes (TGs) into transcriptional regulatory networks is important for the complete understanding of regulation of biological processes. In the case of experimentally verified human TF-TG interactions, there is no database at present that explicitly provides such information even though many databases containing human TF-TG interaction data have been available. In an effort to provide researchers with a repository of experimentally verified human TF-TG interactions from which such interactions can be directly extracted, we present here the Human Transcriptional Regulation Interactions database (HTRIdb).DescriptionThe HTRIdb is an open-access database that can be searched via a user-friendly web interface and the retrieved TF-TG interactions data and the associated protein-protein interactions can be downloaded or interactively visualized as a network through the web version of the popular Cytoscape visualization tool, the Cytoscape Web. Moreover, users can improve the database quality by uploading their own interactions and indicating inconsistencies in the data. So far, HTRIdb has been populated with 284 TFs that regulate 18302 genes, totaling 51871 TF-TG interactions. HTRIdb is freely available at http://www.lbbc.ibb.unesp.br/htri.ConclusionsHTRIdb is a powerful user-friendly tool from which human experimentally validated TF-TG interactions can be easily extracted and used to construct transcriptional regulation interaction networks enabling researchers to decipher the regulation of biological processes.
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Project description: Not available
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Project description:With the advent of precision and genomic medicine, a critical issue is whether a disease gene variant is pathogenic or benign. Such is the case for the three autosomal dominant acute hepatic porphyrias (AHPs), including acute intermittent porphyria, hereditary coproporphyria, and variegate porphyria, each resulting from the half-normal enzymatic activities of hydroxymethylbilane synthase, coproporphyrinogen oxidase, and protoporphyrinogen oxidase, respectively. To date, there is no public database that documents the likely pathogenicity of variants causing the porphyrias, and more specifically, the AHPs with biochemically and clinically verified information. Therefore, an international collaborative with the European Porphyria Network and the National Institutes of Health/National Center for Advancing Translational Sciences/National Institute of Diabetes and Digestive and Kidney Diseases (NIH/NCATS/NIDDK)-sponsored Porphyrias Consortium of porphyria diagnostic experts is establishing an online database that will collate biochemical and clinical evidence verifying the pathogenicity of the published and newly identified variants in the AHP-causing genes. The overall goal of the International Porphyria Molecular Diagnostic Collaborative is to determine the pathogenic and benign variants for all eight porphyrias. Here we describe the overall objectives and the initial efforts to validate pathogenic and benign variants in the respective heme biosynthetic genes causing the AHPs.
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Project description:AimThis study's objective was to assess the risk of severe in-hospital complications of patients admitted for COVID-19 and diabetes mellitus (DM).DesignThis was a cross-sectional study.SettingsWe used pseudonymised medical record data provided by six general hospitals from the HM Hospitales group in Spain.Outcome measuresMultiple logistic regression analyses were used to identify variables associated with mortality and the composite of mortality or invasive mechanical ventilation (IMV) in the overall population, and stratified for the presence or absence of DM. Spline analysis was conducted on the entire population to investigate the relationship between glucose levels at admission and outcomes.ResultsOverall, 1621 individuals without DM and 448 with DM were identified in the database. Patients with DM were on average 5.1 years older than those without. The overall in-hospital mortality was 18.6% (N=301), and was higher among patients with DM than those without (26.3% vs 11.3%; p<0.001). DM was independently associated with death, and death or IMV (OR=2.33, 95% CI: 1.7 to 3.1 and OR=2.11, 95% CI: 1.6 to 2.8, respectively; p<0.001). In subjects with DM, the only variables independently associated with both outcomes were age >65 years, male sex and pre-existing chronic kidney disease. We observed a non-linear relationship between blood glucose levels at admission and risk of in-hospital mortality and death or IMV. The highest probability for each outcome (around 50%) was at random glucose of around 550 mg/dL (30.6 mmol/L), and the risks flattened above this value.ConclusionThe results confirm the high burden associated with DM in patients hospitalised with COVID-19 infection, particularly among men, the elderly and those with impaired kidney function. Moreover, hyperglycaemia on admission was strongly associated with poor outcomes, suggesting that personalised optimisation could help to improve outcome during the hospital stay.
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Project description:Interferon lambda proteins activate the JAK-STAT signalling pathway, resulting in upregulation of genes with antiviral effects. The interferon lambda family was initially thought to be redundant to the interferon alpha family, which signals through the same pathway, except for the more limited expression of the IFNLR1 receptor. However, recent studies show that interferon lambdas uniquely protect tissue barriers against a wide range of important viral infections. The interferon lambda 4 gene (IFNL4) was discovered in 2013. The IFNL4 protein is determined by the IFNL4-ΔG/TT (rs368234815) variant. The ancestral IFNL4-ΔG allele generates IFNL4, whereas IFNL4-TT causes pre-mature termination of the protein. Surprisingly, although interferons are generally antiviral proteins, the genotypes that generate the IFNL4 protein are strongly linked to impaired clearance of hepatitis C virus (HCV). IFNL4 genotype has also been linked to variation within the HCV genome, as well as risk of hepatic fibrosis, certain cancers and some infectious diseases. There has been very strong evolutionary selection against the ancestral IFNL4-ΔG allele, which is the major form in African populations, but the minor allele in Europeans and Asians. The reason for this selection and the biological mechanisms underlying observed phenotypic associations remain to be explained.
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