p53 and Mdm2 act synergistically to maintain cardiac homeostasis and mediate cardiomyocyte cell cycle arrest through a network of microRNAs
Bibliographic record
Abstract
Defining the roadblocks responsible for cell cycle arrest in adult cardiomyocytes lies at the core of developing cardiac regenerative therapies. p53 and Mdm2 are crucial mediators of cell cycle arrest in proliferative cell types, however, little is known about their function in regulating homeostasis and proliferation in terminally differentiated cell types, like cardiomyocytes. To explore this, we generated a cardiac-specific conditional deletion of p53 and Mdm2 (DKO) in adult mice. Herein we describe the development of a dilated cardiomyopathy, in the absence of cardiac hypertrophy. In addition, DKO hearts exhibited a significant increase in cardiomyocyte proliferation. Further evaluation showed that proliferation was mediated by a significant increase in Cdk2 and cyclin E with downregulation of p21Cip1 and p27Kip1. Comparison of miRNA expression profiles from DKO mouse hearts and controls revealed 11 miRNAs that were downregulated in the DKO hearts and enriched for mRNA targets involved in cell cycle regulation. Knockdown of these miRNAs in neonatal rat cardiomyocytes significantly increased cytokinesis with an upregulation in the expression of crucial cell cycle regulators. These results illustrate the importance of the cooperative activities of p53 and Mdm2 in a network of miRNAs that function to impose a barrier against aberrant cardiomyocyte cell cycle re-entry to maintain cardiac homeostasis.
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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".