Vitamin C prevents the endothelial dysfunction induced by acute ethanol intake
Bibliographic record
Abstract
AIMS: Investigate the effect of ascorbic acid (vitamin C) on the endothelial dysfunction induced by acute ethanol intake. MAIN METHODS: Ethanol (1g/kg; p.o. gavage) effects were assessed within 30min in male Wistar rats. KEY FINDINGS: Ethanol intake decreased the endothelium-dependent relaxation induced by acetylcholine in the rat aorta and treatment with vitamin C (250mg/kg; p.o. gavage, 5days) prevented this response. Ethanol increased superoxide anion (O2(-)) generation and decreased aortic nitrate/nitrite levels and these responses were not prevented by vitamin C. Superoxide dismutase (SOD) and catalase (CAT) activities as well as hydrogen peroxide (H2O2) and reduced glutathione (GSH) levels were not affected by ethanol. RhoA translocation as well as the phosphorylation levels of protein kinase B (Akt), eNOS (Ser(1177) or Thr(495) residues), p38MAPK, SAPK/JNK and ERK1/2 was not affected by ethanol intake. Vitamin C increased SOD activity and phosphorylation of Akt, eNOS (Ser(1177) residue) and p38MAPK in aortas from both control and ethanol-treated rats. Incubation of aortas with tempol prevented ethanol-induced decrease in the relaxation induced by acetylcholine. Ethanol (50mM/1min) increased O2(-) generation in cultured aortic vascular smooth muscle cells (VSMC) and vitamin C did not prevent this response. In endothelial cells, vitamin C prevented the increase on ROS generation and the decrease in the cytosolic NO content induced by ethanol. SIGNIFICANCE: Our study provides novel evidence that vitamin C prevents the endothelial dysfunction induced by acute ethanol intake by a mechanism that involves reduced ROS generation and increased NO availability in endothelial cells.
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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) | 0.002 | 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".