Efficacy of flavonoids in the management of high blood pressure
Bibliographic record
Abstract
Plant compounds such as flavonoids have been reported to exert beneficial effects in cardiovascular disease, including hypertension. Information on the effects of isolated individual flavonoids for management of high blood pressure, however, is more limited. This review is focused on the flavonoids, as isolated outside of the food matrix, from the 5 main subgroups consumed in the Western diet (flavones, flavonols, flavanones, flavan-3-ols, and anthocyanins), along with their effects on hypertension, including the potential mechanisms for regulating blood pressure. Flavonoids from all 5 subgroups have been shown to attenuate a rise in or to reduce blood pressure during several pathological conditions (hypertension, metabolic syndrome, and diabetes mellitus). Flavones, flavonols, flavanones, and flavanols were able to modulate blood pressure by restoring endothelial function, either directly, by affecting nitric oxide levels, or indirectly, through other pathways. Quercetin had the most consistent blood pressure-lowering effect in animal and human studies, irrespective of dose, duration, or disease status. However, further research on the safety and efficacy of the flavonoids is required before any of them can be used by humans, presumably in supplement form, at the doses required for therapeutic benefit.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".