Antihypertensive effect of aqueous polyphenol extracts of <i>Amaranthusviridis</i> and <i>Telfairiaoccidentalis</i> leaves in spontaneously hypertensive rats
Bibliographic record
Abstract
The antihypertensive effects of aqueous polyphenol-rich extracts of Amaranthusviridis (AV) and Telfairiaoccidentalis (TO) leaves in spontaneously hypertensive rats (SHR) were investigated. The dried vegetable leaves were extracted using 1:20 (leaves:water, w/v) ratio for 4 h at 60 °C. Results showed significantly (P < 0.05) higher polyphenol contents in TO extracts (80–88 mg gallic acid equivalents, GAE/100 mg) when compared with the AV (62–67 mg GAE/100 mg). Caffeic acid, rutin and myricetin were the main polyphenols found in the extracts. The TO extracts had significantly (P < 0.05) higher in vitro inhibition of angiotensin I-converting enzyme (ACE) activity while AV extracts had better renin inhibition. Oral administration (100 mg/kg body weight) to SHR led to significant (P < 0.05) reductions in systolic blood pressure for the AV (−39 mmHg after 8 h)and TO (−24 mmHg after 4 and 8 h).The vegetable extracts also produced significant (P < 0.05) reductions in diastolic blood pressure, mean arterial blood pressure and heart rate when compared to the untreated rats. Thus both the AV and TO leaf extracts have the potential to be used as antihypertensive agents, especially the AV, which produced persistent long-lasting effect over a 24 h period.
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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) | 0.000 | 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 | 0.000 |
| 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".