Lentil-based diets attenuate hypertension and large-artery remodelling in spontaneously hypertensive rats
Bibliographic record
Abstract
Hypertension is a major risk factor for CVD, the leading cause of mortality worldwide. The prevalence of hypertension is expected to continue increasing, and current pharmacological treatments cannot alleviate all the associated problems. Pulse crops have been touted as a general health food and are now being studied for their possible effects on several disease states including hypertension, obesity and diabetes. In the present study, 15-week-old spontaneously hypertensive rats (SHR) were fed diets containing 30% w/w beans, peas, lentils, chickpeas, or mixed pulses or a pulse-free control diet for 4 weeks. Normotensive Wistar-Kyoto (WKY) rats were placed on a control diet. Pulse wave velocity (PWV) was measured weekly, while blood pressure (BP) was measured at baseline and week 4. Fasting serum obtained in week 4 of the study was analysed for circulating lipids. A histological analysis was carried out on aortic sections to determine vascular geometry. Of all the pulse varieties studied, lentils were found to be able to attenuate the rise in BP in the SHR model (P< 0·05). Lentils were able to decrease the media:lumen ratio and media width of the aorta. The total cholesterol (TC), LDL-cholesterol (LDL-C) and HDL-cholesterol levels of rats fed the pulse-based diets were found to be lower when compared with those of the WKY rat and SHR controls (P< 0·05). Although all pulses reduced circulating TC and LDL-C levels in the SHR, only lentils significantly reduced the rise in BP and large-artery remodelling in the SHR, but had no effect on PWV. These results indicate that the effects of lentils on arterial remodelling and BP in the SHR are independent of circulating LDL-C levels.
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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".