A291 INVESTIGATING THE ROLE OF ANTIBIOTICS AND ADHERENT-INVASIVE E. COLIIN THE PATHOGENESIS OF CROHN’S DISEASE
Bibliographic record
Abstract
Crohn’s disease (CD) is an immune-mediated intestinal illness that is a significant health concern in many developed countries. CD is believed to have a complex etiology consisting of both host susceptibility factors and environmental insults. Multiple epidemiological studies have linked antibiotics with subsequent CD diagnosis. CD is also associated with increased abundance of an unusual phenotypic group of Escherichia coli known as adherent-invasive E. coli (AIEC) in many patients. AIEC are characterized by their ability to adhere and invade various cell types, to stimulate the production of inflammatory cytokines, and also tend to be resistant to multiple classes of antibiotics. Our lab has found that chronic colonisation of conventional mice with AIEC leads to intestinal inflammation and fibrosis. Our objective was to use this mouse model to investigate the impact of antibiotics on AIEC colonisation, pathology, and immune responses. Mice were treated with various antibiotics in drinking water or by oral gavage. These mice were infected with various doses of AIEC either before or after antibiotic treatment. We found that certain antibiotics administered prior to infection greatly reduced the infectious dose of bacteria required and led to greater bacterial burden. Mice administered antibiotics after infection similarly showed an expansion of AIEC in the feces and tissues. We are continuing to investigate how antibiotics alter AIEC colonisation by studying the metabolic and immune consequences of antibiotic treatment. These results show that antibiotics may create a favourable environment for AIEC colonisation in CD patients. Future work will continue investing how antibiotics impact the gut environment in the context of CD. CIHROntario Graduate Scholarship
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".