The role of the DDAH–ADMA pathway in the protective effect of resveratrol analog BTM-0512 on gastric mucosal injury
Bibliographic record
Abstract
A recent study showed that resveratrol, a polyphenol found in many plant species, exerts dual effects on gastric mucosal injury. By using the model of ethanol-induced gastric mucosal injury in the present study, we explored the effect of trans-3,5,4'-trimethoxystilbene (BTM-0512), a novel analog of resveratrol, on gastric mucosal injury and the possible underlying mechanisms. Gastric mucosal injury in the rat was induced by oral administration of acidified ethanol. The gastric tissues were collected for determination of the gastric ulcer index, asymmetric dimethylarginine (ADMA) and nitric oxide (NO) contents, the activity of dimethylarginine dimethylaminohydrolase (DDAH) and superoxide anion (O2(-)) or hydroxyl radical (OH*) formation. The results showed that acute administration of ethanol significantly increased the gastric ulcer index concomitantly with the decrease in DDAH activity and NO content as well as the increase in ADMA content, effects that were reversed by pretreatment with BTM-0512 (100 mg/kg) or L-arginine (300 mg/kg). Administration of BTM-0512 did not show a significant effect on O2(-) or OH. formation. The results suggest that BTM-0512 could protect the gastric mucosa against ethanol-induced injury, which is mainly related to an increase in DDAH activity and subsequent decrease in ADMA content.
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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) | 0.000 | 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) | 0.001 | 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".