Therapeutic effects of the endothelin receptor antagonist Ro 48-5695 in the TNBS/DNBS rat model of colitis
Bibliographic record
Abstract
OBJECTIVE: Endothelins can act as polyfunctional cytokines. It is therefore possible that endothelins could play an active role in gut inflammation. Elevated levels of endothelin-1 have been reported in ulcerative colitis and Crohn's disease. The aim of this study was to establish the therapeutic effect of a 'new' endothelin receptor antagonist Ro 48-5695 in an animal model of inflammatory bowel disease. This study compares the effect of Ro 48-5695 on colonic damage induced by two haptens: trinitrobenzenesulphonic (TNBS) or dinitrobenzenesulphonic acid (DNBS). METHODS: Colitis was induced by intra-rectal administration of TNBS or DNBS. After TNBS/DNBS injury, rats were treated with 10.0, 3.0, 1.0 or 0.3 mg/kg of Ro 48-5695 orally, daily for 5 days. On day 6 post-hapten treatment, colonic tissues were removed and examined in a blinded fashion for macroscopic damage (damage score) and myeloperoxidase (MPO) activity. Stool consistency and adhesions were also measured. RESULTS: Oral administration of Ro 48-5695 almost completely prevented TNBS-induced damage at a dose of 10 mg/kg. The same dose in this model also had a therapeutic effect as measured by MPO and incidence of diarrhoea and adhesions. In DNBS-induced colonic damage, Ro 48-5695 was more potent and at 1.0 and 3.0 mg/kg decreased the damage score by 50 and 60% respectively; also the incidence of adhesions and diarrhoea was significantly reduced. However, MPO activity in this model was affected only by the highest dose of Ro 48-5695 tested (3.0 mg/kg) where it was reduced by 48%. CONCLUSIONS: These data provide evidence for the involvement of endothelins in the pathophysiology of inflammatory bowel disease and support the possibility of exploring a new therapeutic approach.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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".