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Autoinflammatory syndromes cause sterile inflammation in the absence of any signs of autoimmune responses. Familial cold autoinflammatory syndrome (FCAS) is characterized by intermittent episodes of rash, arthralgia, and fever after exposure to cold stimuli. We have identified a missense mutation in the NLRC4 gene in patients with FCAS. NLRC4 has been known as a crucial sensor for several Gram-negative intracellular bacteria. The mutation in NLRC4 in FCAS patients promoted the formation of NLRC4-containing inflammasomes that cleave procaspase-1 and increase production of IL-1β. Transgenic mice that expressed mutant Nlrc4 under the invariant chain promoter developed dermatitis and arthritis. Inflammation within tissues depended on IL-1β-mediated production of IL-17A from neutrophils but not from T cells. Our findings reveal a previously unrecognized link between NLRC4 and a hereditary autoinflammatory disease and highlight the importance of NLRC4 not only in the innate immune response to bacterial infections but also in the genesis of inflammatory diseases.
Pubmed ID: 25385754
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Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
View all literature mentionsCommercial antibody supplier and developer for biomedical research. These products are compatible with use in flow cytometry and mass cytometry, immunoprecipitation and chip, western blotting, immunofluorescence microscopy, and quantitative multiplexing.
View all literature mentionsA dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.
View all literature mentionsSoftware application that carries out single-point and multipoint analyses of pedigree data, including IBD and kinship calculations, nonparametric and variance component linkage analyses, error detection and information content mapping. For multipoint analyses in dense maps, Merlin allows the user to impose constraints on the number of recombinants between consecutive markers. Merlin estimates haplotypes by finding the most likely path of gene flow or by sampling paths of gene flow at all markers jointly. It can also list all possible nonrecombinant haplotypes within short regions. Finally, Merlin provides swap-file support for handling very large numbers of markers as well as gene-dropping simulations for estimating empirical significance levels. (entry from Genetic Analysis Software)
View all literature mentionsCell line HEK293T is a Transformed cell line with a species of origin Homo sapiens (Human)
View all literature mentionsMus musculus with name C57BL/6J from IMSR.
View all literature mentionslaboratory mouse with name C57BL/6N from MGI.
View all literature mentionsCell line HEK293T is a Transformed cell line with a species of origin Homo sapiens (Human)
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
