Sildenafil prevents indomethacin‐induced gastropathy in rats: role of leukocyte adherence and gastric blood flow
Bibliographic record
Abstract
Nitric oxide (NO) is an important mediator of gastric mucosal defense. Sildenafil (SILD), a cyclic GMP-specific phosphodiesterase inhibitor, promotes an increase in cGMP concentrations in the gastrointestinal tract. cGMP mediates many of the biological actions of NO. We tested the hypothesis that SILD could increase mucosal defense against indomethacin-induced gastropathy in rats. SILD (1, 4 or 10 mg kg(-1), p.o.) pretreatment significantly reduced (P < 0.01) the gastric damage and the increase in gastric myeloperoxidase (MPO) activity elicited by indomethacin (20 mg kg(-1) p.o.), with the maximal effect at the dose of 10 mg kg(-1). L-NAME (3, 10 or 20 mg kg(-1), i.p.) dose dependently reversed the protective effects of SILD, an effect not seen when L-arginine (L-ARG) (200 mg kg(-1), i.p.) was co-administered with L-NAME. Indomethacin-induced leukocyte adhesion, assessed by intravital microscopy, was decreased (P < 0.01) by SILD, and this effect was reversed by L-NAME cotreatment. Indomethacin elicited a decrease in gastric blood flow and in gastric PGE2 levels. SILD was able to prevent the decrease in gastric blood flow (P < 0.01), without diminishing the inhibitory effect of indomethacin on prostaglandin synthesis. These results indicate that SILD, acting via NO-dependent mechanisms, prevents indomethacin-induced gastropathy, possibly through a reduction of leukocyte adhesion and maintenance of gastric blood flow.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".