Constitutive androstane receptor regulates the intestinal mucosal response to injury
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The pathogenesis of the inflammatory bowel diseases (IBD), comprising Crohn's disease (CD) and ulcerative colitis (UC), involves aberrant interactions between a genetically susceptible individual, their microbiota and environmental factors. Alterations in xenobiotic receptor expression and function are associated with increased risk for IBD. Here, we have assessed the role of the constitutive androstane receptor (CAR), a xenobiotic receptor closely related to the pregnane X receptor, in the regulation of intestinal mucosal homeostasis. EXPERIMENTAL APPROACH: CAR expression was assessed in intestinal mucosal biopsies obtained from CD and UC patients, and in C57/Bl6 mice exposed to dextran sulphate sodium (DSS; 3.5% w/v in drinking water) to evoke intestinal inflammation and tissue damage. CAR-deficient mice were exposed to DSS and mucosal healing assessed. Modulation of wound healing by CAR was assessed in vitro. The therapeutic potential of CAR activation was evaluated, using 3,3',5,5'-tetrachloro-1,4-bis(pyridyloxy)benzene (TCPOBOP), a selective rodent CAR agonist. KEY RESULTS: CAR expression was reduced in CD and UC samples, compared with expression in healthy controls. This was reproduced in our DSS studies, where CAR expression was reduced in colitic mice. CAR-deficient mice exhibited reduced healing following DSS exposure. In vitro, CAR activation accelerated intestinal epithelial wound healing by enhancing cell migration. Lastly, treating mice with TCPOBOP, following induction of colitis, enhanced mucosal healing. CONCLUSION AND IMPLICATIONS: Our results support the notion that xenobiotic sensing is altered during intestinal inflammation, and suggest that CAR activation may prove effective in enhancing mucosal healing in patients with 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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".