A role for Campylobacter jejuni-induced enteritis in inflammatory bowel disease?
Bibliographic record
Abstract
The inflammatory bowel diseases (IBD), Crohn's disease and ulcerative colitis, are T cell-mediated diseases that are characterized by chronic, relapsing inflammation of the intestinal tract. The pathogenesis of IBD involves the complex interaction between the intestinal microflora, host genetic and immune factors, and environmental stimuli. Epidemiological analyses have implicated acute bacterial enteritis as one of the factors that may incite or exacerbate IBD in susceptible individuals. In this review, we examine how interactions between the common enteric pathogen Campylobacter jejuni (C. jejuni), the host intestinal epithelium, and resident intestinal microflora may contribute to the pathogenesis of IBD. Recent experimental evidence indicates that C. jejuni may permit the translocation of normal, noninvasive microflora via novel processes that implicate epithelial lipid rafts. This breach in intestinal barrier function may, in turn, prime the intestine for chronic inflammatory responses in susceptible individuals. Insights into the interactions between enteric pathogens, the host epithelia, and intestinal microflora will improve our understanding of disease processes that may initiate and/or exacerbate intestinal inflammation in patients with IBD and provide impetus for the development of new therapeutic approaches for the treatment of IBD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".