Chronic Treatment With the ACE Inhibitor Enalapril Attenuates the Development of Frailty and Differentially Modifies Pro- and Anti-inflammatory Cytokines in Aging Male and Female C57BL/6 Mice
Bibliographic record
Abstract
Studies on interventions that can delay or treat frailty in humans are limited. There is evidence of beneficial effects of angiotensin converting enzyme (ACE) inhibitors on aspects related to frailty, such as physical function, even in those without cardiovascular disease. This study aimed to longitudinally investigate the effect of an ACE inhibitor on frailty in aging male and female mice. Frailty was assessed with a clinical frailty index (FI) which quantifies health-related deficits in middle-aged (9-13 months) and older (16-25 months) mice. Chronic treatment with enalapril (30 mg/kg/day in feed) attenuated frailty in middle-aged and older female mice, and older male mice, without a long-term effect on blood pressure. Enalapril treatment resulted in a reduction in the proinflammatory cytokines interleukin (IL)-1α, monocyte chemoattractant protein-1 and macrophage inflammatory protein-1a in older female mice, and an increase in the anti-inflammatory cytokine IL-10 in older male mice compared with control animals. These sex-specific effects on inflammation may contribute to the protective effects of enalapril against frailty. This is the first study to examine the longitudinal effect of an intervention on the FI in mice, and provides preclinical evidence that enalapril may delay the onset of frailty, even when started later in life.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".