Effect of buttermilk consumption on blood pressure in moderately hypercholesterolemic men and women
Bibliographic record
Abstract
OBJECTIVES: Milk fat globule membrane (MFGM) found in buttermilk is rich in unique bioactive proteins. Several studies suggest that MFGM proteins possess biological activities such as cholesterol-lowering, antiviral, antibacterial, and anticancer properties, but data in humans are lacking. Furthermore, to our knowledge, no study has yet investigated the antihypertensive potential of MFGM proteins from buttermilk. The aim of this study was to investigate the effects of buttermilk consumption on blood pressure and on markers of the renin-angiotensin-aldosterone (RAS) system in humans. METHODS: Men and women (N = 34) with plasma low-density lipoprotein cholesterol < 5 mmol/L and normal blood pressure (< 140 mm Hg) were recruited in this randomized, double-blind, placebo-controlled, crossover study. Their diets were supplemented with 45 g/d of buttermilk and with 45 g/d of a macro-/micronutrient-matched placebo in random order (4 wk for each diet). RESULTS: Buttermilk consumption significantly reduced systolic blood pressure (-2.6 mm Hg; P = 0.009), mean arterial blood pressure (-1.7 mm Hg; P = 0.015), and plasma levels of the angiotensin I-converting enzyme (-10.9%; P = 0.003) compared with the placebo, but had no effect on plasma concentrations of angiotensin II and aldosterone. CONCLUSION: Short-term buttermilk consumption reduces blood pressure in normotensive individuals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| 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".