Weight Loss and the Renin-Angiotensin-Aldosterone System
Bibliographic record
Abstract
The renin-angiotensin-aldosterone system has been causally implicated in obesity-associated hypertension. We studied the influence of obesity and weight reduction on the circulating and adipose tissue renin-angiotensin-aldosterone system in menopausal women. Blood samples were analyzed for angiotensinogen, renin, aldosterone, angiotensin-converting enzyme activity, and angiotensin II. In adipose tissue biopsy samples, we analyzed angiotensinogen, renin, renin-receptor, angiotensin-converting enzyme, and angiotensin II type-1 receptor gene expression. Obese women (n=19) had higher circulating angiotensinogen, renin, aldosterone, and angiotensin-converting enzyme than lean women (n=19), and lower angiotensinogen gene expression in adipose tissue. Seventeen women successfully participated in a weight reduction protocol over 13 weeks to reduce daily caloric intake by 600 kcal. Body weight was reduced by -5%, as were angiotensinogen levels by -27%, renin by -43%, aldosterone by -31%, angiotensin-converting enzyme activity by -12%, and angiotensinogen expression by -20% in adipose tissue (all P<0.05). The plasma angiotensinogen decrease was highly correlated with the waist circumference decline (r=0.74; P<0.001). Weight and renin-angiotensin-aldosterone system reductions were accompanied by a -7-mm Hg reduced systolic ambulatory blood pressure. These data suggest that a 5% reduction in body weight can lead to a meaningfully reduced renin-angiotensin-aldosterone system in plasma and adipose tissue, which may contribute to the reduced blood pressure.
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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".