Protective effect of<scp>l</scp>-citrulline against acute gastric mucosal lesions induced by ischemia–reperfusion in rats
Bibliographic record
Abstract
The present study investigated the protective effect of L-citrulline on gastric mucosal injury induced by ischemia-reperfusion (IR) in rats. Under anesthesia, the celiac artery was clamped for 30 min, and then the clamp was removed for 60 min reperfusion. Sixty minutes before ischemia, L-citrulline was administered intragastrically at doses of 300, 600, and 900 mg/kg. After the experiment, the stomachs were removed for biochemical and histological examinations. Pretreatment with L-citrulline (300, 600, and 900 mg/kg) significantly ameliorated the gastric damage caused by IR. Moreover, L-citrulline prevented the production of lipid peroxidation and inhibited the increase of myeloperoxidase activity. The elevation in total nitric oxide synthase (NOS) activity, inducible NOS activity, and inducible NOS protein expression as well as the decrease in constitutive NOS activity and gastric mucus level in the gastric mucosa induced by IR were significantly prevented. However, the protective effect mediated by L-citrulline was significantly antagonized by coadministration of L-nitroarginine methyl ester (10 mg/kg, s.c.). These results suggest that part of the mechanism of gastric protection by L-citrulline might be through inhibiting neutrophil infiltration and preserving gastric mucus synthesis and secretion in rats, functions that are closely related to the maintenance of constitutive NOS activity.
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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 | 0.001 | 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".