Abstract 175: Pro-survival Function of Mef2 in Cardiomyocytes is Enhanced by β-blockers
Bibliographic record
Abstract
β1-adrenergic receptor (β1-AR) stimulation increases apoptosis in cardiomyocytes via activation of cAMP/ protein kinase A (PKA) signaling. β-adrenergic receptor antagonists, or β-blockers, oppose the action of PKA signaling by blocking the β1-receptor and effectively inhibit apoptosis and heart failure. The Myocyte Enhancer Factor 2 (MEF2) proteins have been implicated as nuclear targets for signaling cascades involved in muscle-gene expression and have important roles in proliferation, apoptosis and survival in multiple cell types. We previously reported that PKA signaling represses MEF2 activity. Here, we assessed whether β-blockers can inhibit neonatal cardiac myocyte apoptosis by interfering with PKA dependent MEF2 repression. We show that siRNA mediated MEF2 loss of function induced cardiomyocyte apoptosis. β1AR activation by isoproterenol treatment represses MEF2 transcriptional activity and promotes apoptosis in neonatal cardiomyocytes and, importantly, this effect was reversed in cells expressing a PKA resistant form of MEF2D (S121/190A), as indicated by FACS analysis. We also report that a β-blocker, Atenolol, antagonizes isoproterenol induced apoptosis and also acutely enhanced MEF2 transcriptional activity. We observed that β-adrenergic stimulation modulated MEF2 cellular localization in neonatal cardiomyocytes and this was reversed by atenolol treatment. In addition, we also document that Kru[[Unable to Display Character: ̈]]ppel-like factor 6 (KLF6) is an important MEF2 target gene and loss of function analysis using siRNA-mediated knockdown of KLF6 expression resulted in cardiomyocyte apoptosis. Collectively, these observations, establish that MEF2 plays an important pro-survival role in cardiomyocytes which can be modulated by β-adrenergic signaling. These observations have important clinical implications and may contribute to novel strategies for preventing cardiomyocyte apoptosis associated with heart pathology.
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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 | 0.000 | 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) | 0.019 | 0.004 |
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".