Role of the estrogen/estrogen-receptor-beta axis in the genomic response to pressure overload-induced hypertrophy
Bibliographic record
Abstract
Cardiac hypertrophy, the adaptive response of the heart to overload, is a major risk factor for heart failure and sudden death. Estrogen (E2) and estrogen receptor beta (ERbeta) offer protection against hypertrophy and in the transition to heart failure. However, the underlying pathways remain incompletely defined. We employed a publicly available microarray dataset of female wild-type (WT) and ERbeta knockout (BERKO) mice subjected to pressure overload-induced hypertrophy to perform a systematic investigation of the mechanisms involved in the protection conferred by the E2/ERbeta axis. We show that considerably more genes were modulated in response to pressure overload in BERKO mice than in WT mice. The majority of the identified candidates in BERKO mice were induced, while those in WT mice were repressed. Pathway analysis revealed a similar pattern. This study is the first to demonstrate that the lack of ERbeta led to a significant increase of inflammatory pathways. Mitochondrial bioenergetics- and oxidative stress-related pathways were also modulated. In conclusion, ERbeta acquires the role of gatekeeper of the genomic response of the heart to pressure overload-induced hypertrophy. This may offer the molecular explanation for its cardioprotective role. We consider the present study to be a useful resource and that it will contribute to downstream functional analysis and to the characterization of pathways with previously unknown role in hypertrophy.
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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 | 0.000 |
| 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".