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Record W3134661075 · doi:10.1093/jcag/gwab002.039

A41 LINKING THE APPENDIX MICROBIOME WITH INFLAMMATORY BOWEL DISEASES

2021· article· en· W3134661075 on OpenAlexaff
N Arjomand Fard, Heather Armstrong, Matthew Carroll, Hien Q. Huynh, Eytan Wine

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMetagenomicsInflammatory bowel diseaseBiologyCecumAppendixUlcerative colitisPathogenesisMicrobiomeMicrobiologyCrohn's diseaseShotgun sequencingVirulenceDiseaseImmunologyBioinformaticsMedicinePathologyGeneticsGeneDNA sequencingEcology

Abstract

fetched live from OpenAlex

Abstract Background The appendix has been shown to be associated with the pathogenesis and health outcomes in inflammatory bowel diseases (IBD). Specifically, post appendectomy patients are found to be protective for development of ulcerative colitis (UC); however, mechanisms of appendix involvement remain unclear. Aims Our aim is to examine the microbes associated with the appendix of IBD patients by identifying changes in microbe abundance and interactions with the host in patient cecum luminal washes, collected from close to the neck of the appendix during colonoscopy. We hypothesize that microbes originating in the appendix of IBD patients, through interactions with host-cells in a disrupted microenvironment in the appendix, could contribute to the pathogenesis of UC. Methods Shotgun metagenomics was performed on cecum luminal washes of IBD patients and non-IBD controls. Guided by the metagenomic results, we performed gentamicin protection assays to determine virulence of microbes of interest using Caco2 intestinal epithelial cells. Co-culturing them with human host cells in vitro will identify relevant disease-related factors secreted by microbes and/or host cells using disease models and multiomic approaches. Results Shotgun metagenomics results showed that among numerous microbes, several bacterial taxa demonstrated differences in abundance between IBD and non-IBD patients: Flavonifractor, Bacteroide fragilis, and Alistipes represented 8%, 10%, and 21% abundance respectively in non-IBD patients, while in IBD patients they were present below 0.1%. In contrast, Bacteroide vulgatus and Escherichia coli were about 9% and 69% respectively, in IBD patients, whilst they were present at 1.7% and 1.2% in non-IBD patients, respectively. Following our recent method for validating pathobionts (Armstrong, 2019), we used the gentamicin protection assays to assess the ability of these bacteria to invade Caco2 cells, demonstrating a correlation between invasive potential of these microbes and cecal abundance. Mechanistic experiments, aimed at identifying factors impacting invasion, are in progress. Conclusions These results provide preliminary, but promising findings suggesting mechanisms by which microbiota possibly originating in the appendix may show altered virulence, which may be related to changes in the appendix microenvironment in IBD. With plans in place to increase our patient cohort we will validate these findings. Identifying and profiling these microbes in IBD patients can help improve the understanding of mechanisms underlying microenvironment changes within the appendix and the gut, which could shed light on the role of the appendix in IBD pathogenesis and clarify how microbes drive inflammation in IBD. Funding Agencies CIHR

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.186
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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