Involvement of PPAR <b>γ</b> in the protective action of tropisetron in an experimental model of ulcerative colitis
Bibliographic record
Abstract
receptor antagonist, is highly used to counteract chemotherapy-induced emesis. Previous studies revealed the anti-inflammatory properties of this drug. The aim of this study was to evaluate the role of peroxisome proliferator-activated receptor gamma (PPARγ) receptor in the protective effect of tropisetron in an animal model of ulcerative colitis. Experimental colitis was induced by a single intra-colonic instillation of 4% (V/V) acetic acid in male rats. Tropisetron (3 mg/kg) and GW9662 (PPARγ antagonist) (5 mg/kg) were given twice daily for 2 days after colitis induction. Forty-eight hours after induction of colitis, colon was removed and macroscopic and microscopic features were given. Moreover, colonic concentrations of malondialdehyde (MDA), nitric oxide (NO), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) levels, myeloperoxidase (MPO), and PPARγ activity were assessed. Both macroscopic and histopathological features of colonic injury were markedly ameliorated by tropisetron. Likewise, levels of NO, MDA, TNF-α, and IL-1β diminished significantly (p < .05). GW9662 reversed the effect of tropisetron on these markers partially or completely. In addition, tropisetron increased the PPARγ and decreased the MPO activity (p < .05). Tropisetron exerts notable anti-inflammatory effects in acetic acid-induced colitis in rats, which is probably mediated through PPARγ receptors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".