Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Project description:Pouchitis is a common complication for ulcerative colitis (UC) patients with ileal pouch-anal anastomosis (IPAA) surgery. Similarly to IBD, both innate host factors such as genetics, and environmental stimuli including the tissue-associated microbiome have been implicated in the pathogenesis. In this study, we make use of the IPAA model of inflammatory bowel disease (IBD) to carry out a study associating mucosal host gene expression with the microbiome and corresponding clinical outcomes. In order to determine how host gene expression might influence, or be influenced by the tissue associated microbiome, we analyzed 205 IPAA patients with biopsies collected from the pouch and afferent limb for host transcriptomics and 16S rDNA gene sequencing. Metadata included antibiotic use, inflammation score, and clinical classification. To achieve power for a genome-wide microbiome-transcriptome association study, we used principal component analysis to reduce OTUs and host transcripts to eigengenes and eigenclades explaining 50% of observed variance. These were subsequently tested for significant covariation with one another and/or outcome using multivariate linear modeling.
