Heart Failure and MEF2 Transcriptome Dynamics in Response to β-Blockers
Bibliographic record
Abstract
Myocyte Enhancer Factor 2 (MEF2) mediates cardiac remodelling in heart failure (HF) and is also a target of β-adrenergic signalling, a front-line treatment for HF. We identified global gene transcription networks involved in HF with and without β-blocker treatment. Experimental HF by transverse aortic constriction (TAC) in a MEF2 "sensor" mouse model (6 weeks) was followed by four weeks of β-blockade with Atenolol (AT) or Solvent (Sol) treatment. Transcriptome analysis (RNA-seq) from left ventricular RNA samples and MEF2A depleted cardiomyocytes was performed. AT treatment resulted in an overall improvement in cardiac function of TAC mice and repression of MEF2 activity. RNA-seq identified 65 differentially expressed genes (DEGs) due to TAC treatment with enriched GO clusters including the inflammatory system, cell migration and apoptosis. These genes were mapped against DEGs in cardiomyocytes in which MEF2A expression was suppressed. Of the 65 TAC mediated DEGs, AT reversed the expression of 28 mRNAs. Rarres2 was identified as a novel MEF2 target gene that is upregulated with TAC in vivo and isoproterenol treatment in vitro which may have implications in cardiomyocyte apoptosis and hypertrophy. These studies identify a cohort of genes with vast potential for disease diagnosis and therapeutic intervention in 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 | 0.000 |
| 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".