Quercetin-Supplemented Diets Lower Blood Pressure and Attenuate Cardiac Hypertrophy in Rats With Aortic Constriction
Bibliographic record
Abstract
Quercetin (Q), a flavonoid found in berries and onions, can reduce blood pressure in hypertensive animals and inhibit signal transduction pathways in vitro that regulate cardiac hypertrophy. We hypothesized that quercetin could prevent cardiovascular complications in rats with abdominal aortic constriction (AAC). Rats consumed standard or Q-supplemented chow (1.5 g Q/kg chow) for 7 days before AAC or sham surgery (SHAM, n = 15; AAC, n = 15; SHAMQ, n = 15; AACQ, n = 14). Fourteen days after surgery, plasma and liver Q concentrations were elevated (P < 0.05) and hepatic lipid oxidation was reduced (P < 0.05) in Q-treated versus untreated rats. Carotid arterial blood pressure and cardiac hypertrophy were attenuated (P < 0.05), and cardiac protein kinase C betaII translocation was normalized (P < 0.05) in AACQ versus AAC. Expression of cardiac beta-myosin heavy-chain mRNA was also reduced in AACQ versus AAC (P < 0.05). However, extracellular regulated kinase 1/2 phosphorylation was similar in AAC versus AACQ. The level of aortic endothelial dysfunction (wire myography) was also similar between AAC and AACQ, in spite of reduced aortic thickening in AACQ. Importantly, Q-treated rats did not show any deleterious changes in myocardial function (echocardiography). Our data supports an antihypertensive and antihypertrophic effect of Q in vivo in the absence of changes concerning vascular and myocardial function.
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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 | 0.000 | 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".