Maladaptive Changes Associated With Cardiac Aging Are Sex-Specific and Graded by Frailty and Inflammation in C57BL/6 Mice
Bibliographic record
Abstract
We investigated whether late-life changes in cardiac structure and function were related to high levels of frailty and inflammation in male and female mice. Frailty (frailty index), ventricular structure/function (echocardiography), and serum cytokines (multiplex immunoassay) were measured in 16- and 23-month-old mice. Left ventricular (LV) mass and septal wall thickness increased with age in both sexes. Ejection fraction increased with age in males (60.4 ± 1.4 vs 68.9 ± 1.8%; p < .05) but not females (58.8 ± 2.5 vs 62.6 ± 2.4%). E/A ratios declined with age in males (1.6 ± 0.1 vs 1.3 ± 0.1; p < .05) but not females (1.4 ± 0.1 vs 1.3 ± 0.1) and this was accompanied by increased ventricular collagen levels in males. These changes in ejection fraction (r = 0.52; p = .01), septal wall thickness (r = 0.59; p = .002), E/A ratios (r = -0.49; p = .04), and fibrosis (r = 0.82; p = .002) were closely graded by frailty scores in males. Only septal wall thickness and LV mass increased with frailty in females. Serum cytokines changed modestly with age in both sexes. Nonetheless, in males, E/A ratios, LV mass, LV posterior wall thickness, and septal wall thickness increased as serum cytokines increased (eg, IL-6, IL-3, IL-1α, IL-1β, tumor necrosis factor-α, eotaxin, and macrophage inflammatory protein-1α), while ejection fraction declined with increasing IL-3 and granulocyte-macrophage colony stimulating factor. Cardiac outcomes were not correlated with inflammatory cytokines in females. Thus, changes in cardiac structure and function in late life are closely graded by both frailty and markers of inflammation, but this occurs primarily in males. This suggests poor overall health and inflammation drive maladaptive changes in older male hearts, while older females may be resistant to these adverse effects of frailty.
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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 | 0.001 |
| 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) | 0.002 | 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".