Signs of diastolic dysfunction are graded by serum testosterone levels in aging C57BL/6 male mice
Bibliographic record
Abstract
We investigated whether maladaptive, age-associated changes in heart structure and function were linked to circulating testosterone levels. Male C57BL/6 mice had a gonadectomy (GDX) or sham surgery at 4 weeks and effects of GDX on the heart were examined with echocardiography. Serum testosterone was measured with ELISA. Left ventricular (LV) mass increased with age but was smaller in GDX mice than sham at 18 months (144.0 ± 8.7 vs 118.2 ± 11.9 mg; p = 0.009). The isovolumic relaxation time (IVRT) declined with age but was prolonged in GDX mice at 18 months (10.5 ± 0.8 vs 12.5 ± 0.5 msec, p = 0.008). Ejection fraction did not change with age or GDX, but E/A ratios were lower in GDX mice than controls at 18 months (1.6 ± 0.2 vs 1.3 ± 0.1, p = 0.021). When links between serum testosterone and cardiac parameters were examined longitudinally in 18-24-month-old mice, LV mass declined with decreasing testosterone (β = 37.70, p = 0.016), however IVRT increased as testosterone decreased (β=-2.69, p = 0.036). Since longer IVRT and lower E/A ratios are signs of diastolic dysfunction, low circulating testosterone may promote or exacerbate diastolic dysfunction in older males. These findings suggest that lower testosterone directly modifies heart structure and function to promote maladaptive remodeling and diastolic dysfunction in the aging heart.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".