Chronic Resveratrol Enhances Endothelium-Dependent Relaxation but Does Not Alter eNOS Levels in Aorta of Spontaneously Hypertensive Rats
Bibliographic record
Abstract
Spontaneously hypertensive rats (SHRs) were administered the red wine polyphenol resveratrol in drinking water at 0, 0.448, or 4.48 mg/l (control, low, or high, respectively) for 28 days. The low dosage was chosen to mimic moderate red wine consumption. After the treatment period, thoracic aorta rings were excised for in vitro assessment of vasomotor function. Chronic resveratrol significantly improved endothelium-dependent relaxation to acetylcholine (Ach), increasing maximal values to 80.8% +/- 5.2% and 80.8% +/- 5.0% in low and high groups, respectively, compared with 60.7% +/- 1.4% in controls (P<0.01). This treatment effect was eliminated in the presence of the endothelial nitric oxide synthase (eNOS) blocker N(omega)-nitro-L-arginine methyl ester. Resveratrol did not affect relaxation to sodium nitroprusside or systolic blood pressure in SHRs. In contrast to the SHR results, chronic resveratrol in Sprague Dawley rats did not affect vasomotor function in aorta rings in response to Ach. Hydrogen peroxide was reduced in the SHR thoracic aorta by a high dosage of resveratrol (P<0.05), but it was not significantly altered in other tissues tested. Thoracic aorta immunoblots revealed no significant treatment effects in SHRs on eNOS, superoxide dismutases 1 and 2, gp91phox, or Hsp90. Thus, these data provide novel evidence of improved endothelium-dependent vasorelaxation in hypertensive, but not normotensive, animals as a result of chronic resveratrol consumption mimicking dosages resulting from moderate red wine consumption. This response was not dependent on increases in eNOS expression but was dependent on improved NO bioavailability.
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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 | 0.000 | 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".