Hydrogen sulphide protects against <scp>NSAID</scp> ‐enteropathy through modulation of bile and the microbiota
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Hydrogen sulphide is an important mediator of gastrointestinal mucosal defence. The use of non-steroidal anti-inflammatory drugs (NSAIDs) is significantly limited by their toxicity in the gastrointestinal tract. Particularly concerning is the lack of effective preventative or curative treatments for NSAID-induced intestinal damage and bleeding. We evaluated the ability of a hydrogen sulphide donor to protect against NSAID-induced enteropathy. EXPERIMENTAL APPROACH: Intestinal ulceration and bleeding were induced in Wistar rats by oral administration of naproxen. The effects of suppression of endogenous hydrogen sulphide synthesis or administration of a hydrogen sulphide donor (diallyl disulphide) on naproxen-induced enteropathy was examined. Effects of diallyl disulphide on small intestinal inflammation and intestinal microbiota were also assessed. Bile collected after in vivo naproxen and diallyl disulphide administration was evaluated for cytotoxicity in vitro using cultured intestinal epithelial cells. KEY RESULTS: Suppression of endogenous hydrogen sulphide synthesis by β-cyano-L-alanine exacerbated naproxen-induced enteropathy. Diallyl disulphide co-administration dose-dependently reduced the severity of naproxen-induced small intestinal damage, inflammation and bleeding. Diallyl disulphide administration attenuated naproxen-induced increases in the cytotoxicity of bile on cultured enterocytes, and prevented or reversed naproxen-induced changes in the intestinal microbiota. CONCLUSIONS AND IMPLICATIONS: Hydrogen sulphide protects against NSAID-enteropathy in rats, in part reducing the cytotoxicity of bile and preventing NSAID-induced dysbiosis.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".