The Loss of Gonadal Hormones Has a Different Impact on Aging Female and Male Mice Submitted to Heart Failure-Inducing Metabolic Hypertensive Stress
Bibliographic record
Abstract
BACKGROUND: Aging and the female sex are considered risk factors for the development of heart failure with preserved ejection fraction (HFpEF). Unlike other risk factors, such as hypertension, obesity, or diabetes, they do not represent therapeutic targets. METHODS: In a recently developed two-hit murine HFpEF model (angiotensin II + high-fat diet; MHS), we studied the relative contributions of the biological sex, aging, and gonadal hormones to cardiac remodeling and function. We aimed to reproduce a frequent HFpEF phenotype in mice characterized by aging, hypertension, the female sex, menopause, and metabolic alterations. Using the MHS mouse model, we studied cardiac remodeling and function in C57Bl6/J mice of both sexes, young (12 weeks) and old (20 months), that were gonadectomized (Gx) or not. RESULTS: We observed that in mice, aging was associated with body weight gain, cardiac hypertrophy (CH), left ventricle (LV) concentric remodeling, and left atrial (LA) enlargement. Diastolic parameters such as E and A wave velocities were modulated by aging but only in females. Submitting young and old mice to MHS for 28 days induced the expected HFpEF phenotype consisting of CH, LV wall thickening, LA enlargement, and diastolic dysfunction with a preserved EF except for old males, in which it was significantly reduced. Young mice were Gx at five weeks, and old mice at six months (over a year before MHS). Gx increased myocardial fibrosis in MHS females and helped preserve the EF in males. CONCLUSIONS: Our results suggest that MHS has sex-specific effects on old mice, and the loss of gonadal hormones significantly impacts the observed heart failure phenotype.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".