Role of beetroots in oxidative stress and vascular relaxation in ovariectomized rats
Bibliographic record
Abstract
The onset of hypertension in women is known to peak dramatically after menopause, partly due to decreased estrogen levels. It is well known that postmenopausal estrogen therapy can cause many adverse effects, and there is growing interest in using dietary products as potential treatment options. Dietary nitrates in beetroot may raise blood nitric oxide levels. We tested the hypothesis that beetroot can improve the oxidative stress and vascular relaxation responses in a model of an ovariectomized rodent. Female ovariectomized Sprague‐Dawley rats were divided into four treatment groups: beetroot juice (nitrate content 18.75mg), nitroglycerin (0.2 mg/kg), estradiol replacement (1.5mg) or no treatment for 12 weeks (n=4 per group). The isometric contractile activities were measured in isolated aortic rings mounted in tissue baths. Phenylephrine (10 ‐6 M) was used to precontract the aortic rings. The contractile activities to various concentrations of acetylcholine and sodium nitroprusside were evaluated. The superoxide concentration was measured using chemiluminescence. The beetroot treatment significantly reduced superoxide production (P<0.05). However, it did not affect acetylcholine or sodium nitroprusside‐induced vascular relaxation at any of the concentrations used in the experiments (P>0.05). There were no significant differences in acetylcholine‐induced vascular relaxation curves among the different treatment groups (P>0.05). In conclusion, these experiments indicate that dietary beetroot does not improve acetylcholine‐mediated vascular relaxation while decreasing oxidative stress, contrary to expectations.
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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 | 0.001 | 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".