Female sex and estrogen receptor-β attenuate cardiac remodeling and apoptosis in pressure overload
Bibliographic record
Abstract
We investigated sex differences and the role of estrogen receptor-beta (ERbeta) on myocardial hypertrophy in a mouse model of pressure overload. We performed transverse aortic constriction (TAC) or sham surgery in male and female wild-type (WT) and ERbeta knockout (ERbeta(-/-)) mice. All mice were characterized by echocardiography and hemodynamic measurements and were killed 9 wk after surgery. Left ventricular (LV) samples were analyzed by microarray profiling, real-time RT-PCR, and histology. After 9 wk, WT males showed more hypertrophy and heart failure signs than WT females. Notably, WT females developed a concentric form of hypertrophy, while males developed eccentric hypertrophy. ERbeta deletion augmented the TAC-induced increase in cardiomyocyte diameter in both sexes. Gene expression profiling revealed that WT male hearts had a stronger induction of matrix-related genes and a stronger repression of mitochondrial genes than WT female hearts. ERbeta(-/-) mice exhibited a different transcriptional response. ERbeta(-/-)/TAC mice of both sexes exhibited induction of proapoptotic genes with a stronger expression in ERbeta(-/-) males. Cardiac fibrosis was more pronounced in male WT/TAC than in female mice. This difference was abolished in ERbeta(-/-) mice. The number of apoptotic nuclei was increased in both sexes of ERbeta(-/-)/TAC mice, most prominent in males. Female sex offers protection against ventricular chamber dilation in the TAC model. Both female sex and ERbeta attenuate the development of fibrosis and apoptosis, thus slowing the progression to heart failure.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".