Detrimental effects of nicotine on the acute gastric mucosal injury induced by ethanol: role of asymmetric dimethylarginine
Bibliographic record
Abstract
The aim of this study was to determine whether asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase (NOS), is responsible for the detrimental effects of nicotine on ethanol-induced gastric mucosal injury and its underlying mechanisms. Gastric mucosal injury was induced by an injection of ethanol in the stomach in rats. Animals were pretreated with nicotine for 28 days before ethanol injection. The gastric mucosal ulcer index (UI) and the levels of ADMA and NO in gastric juice were determined. In vitro, the cultured mucosal epithelial cells were treated with nicotine in the presence or absence of ethanol. The concentration of ADMA in the culture medium and the ratio of cell apoptosis were measured, and the effect of nicotine or ADMA alone on cell apoptosis was also examined. In rats treated with ethanol, the UI and ADMA levels were increased and the NO level was decreased, and these effects of ethanol were augmented by pretreatment with nicotine. Administration of nicotine alone did not show significant impact on UI, ADMA level, or NO level. In vitro, incubation of human epithelial cells with ethanol induced cell injury accompanied by increased ADMA levels in the culture medium, an effect which was amplified in the presence of nicotine. Similarly, ethanol was able to induce epithelial cell apoptosis that was exacerbated by nicotine. Incubation of epithelial cells with nicotine alone did not induce cell apoptosis, but administration of ADMA alone did induce cell apoptosis. The results suggest that the gastric mucosal injury induced by ethanol is augmented by nicotine, which is related to the increased ADMA level.
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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 | 0.001 |
| 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".