Possible protective effect of TNF-α inhibition and triad NO/cGMP/VEGF activation on gastric ulcer in rats
Bibliographic record
Abstract
Peptic ulcers are one of the world's major gastrointestinal disorders, embracing both gastric and duodenal ulcers, and affecting 10% of the world population. The current study aimed to investigate the possible protective effect of tadalafil and pentoxifylline (PTX) on indomethacin-induced peptic ulcers. Male albino rats were divided into five groups: control group; ulcerated group; Indomethacin + Tadalafil, in which animals were pretreated with tadalafil orally before indomethacin; Indomethacin+ PTX, in which animals were pretreated with PTX orally before indomethacin; and Indomethacin + Tadafil + PTX. Indomethacin treatment revealed histopathological changes and ulcer scoring and ulcer index were markedly increased. Serum levels of prostaglandin and heme oxygenase-1 were significantly decreased. The ulcerogenic also induced marked oxidative stress as evident from the increased malondialdehyde, decreased in gastric glutathione content and superoxide dismutase activity, while the gastric myeloperoxidase was increased. Gastric nitric oxide content was decreased and the expression of vascular endothelial growth factor was downregulated while the tumor necrosis factor α (TNF-α) level was dramatically increased. Pretreatment of the ulcerative group by either tadalafil or PTX or their combination improved all these pathological changes. Tadalafil or PTX may have a role in protecting gastric mucosa damage caused by indomethacin which may be useful in the future for the treatment of gastric ulceration.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".