INFLUENCE OF ACE INHIBITORS ON FRAILTY AND CARDIAC FUNCTION IN MIDDLE-AGED FEMALE C57BL/6 MICE
Bibliographic record
Abstract
ACE inhibitors improve exercise capacity in older adults without cardiovascular disease and in aged rodents. We hypothesised that chronic ACE inhibitor treatment may attenuate frailty through changes in cardiac function. Female C57BL/6 mice (12 months) were given enalapril (40 mg/kg/day; n=10) or control (n=10) for 3 months. Frailty was quantified with the mouse clinical frailty index (FI). Blood pressure (BP) was measured with a tail-cuff and in vivo cardiac function was measured using echocardiography. Cardiomyocytes were isolated for field-stimulation and voltage clamp experiments (2 Hz). FI scores were significantly lower in the enalapril group when compared to control mice (0.14 ± 0.01 vs 0.21 ± 0.03, p<0.05) after 3 months. BP, heart structure and contractile function were not significantly different between the enalapril and control groups. Field stimulation experiments showed that enalapril treatment increased cell shortening (1.6 ± 0.2 vs 3.0 ± 0.5 %, p<0.001), velocity-to-peak contraction (0.068 ± 0.005 vs 0.133 ± 0.016 µm/ms, p<0.001) and ½ relaxation (0.044 ± 0.005 vs 0.100 ± 0.016 µm/ms, p<0.001), with no change in underlying calcium transients. Under voltage clamp conditions both calcium transients (37.6 ± 3.2 vs 49.0 ± 3.9 nM, p<0.05) and contractions (5.7 ± 0.7 vs 8.9 ± 0.9 %, p<0.05) were increased by enalapril treatment. Calcium current and sarcoplasmic reticulum (SR) calcium content were unchanged. These results show that enalapril attenuates frailty in middle-aged animals, even in the absence of cardiovascular disease, and suggest that ACE inhibitor treatment may increase calcium release from the SR.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".