p53 regulates the cardiac transcriptome
Bibliographic record
Abstract
The tumor suppressor Trp53 (p53) inhibits cell growth after acute stress by regulating gene transcription. The mammalian genome contains hundreds of p53-binding sites. However, whether p53 participates in the regulation of cardiac tissue homeostasis under normal conditions is not known. To examine the physiologic role of p53 in adult cardiomyocytes in vivo, Cre-loxP-mediated conditional gene targeting in adult mice was used. Genome-wide transcriptome analyses of conditional heart-specific p53 knockout mice were performed. Genome-wide annotation and pathway analyses of >5,000 differentially expressed transcripts identified many p53-regulated gene clusters. Correlative analyses identified >20 gene sets containing more than 1,000 genes relevant to cardiac architecture and function. These transcriptomic changes orchestrate cardiac architecture, excitation-contraction coupling, mitochondrial biogenesis, and oxidative phosphorylation capacity. Interestingly, the gene expression signature in p53-deficient hearts confers resistance to acute biomechanical stress. The data presented here demonstrate a role for p53, a previously unrecognized master regulator of the cardiac transcriptome. The complex contributions of p53 define a biological paradigm for the p53 regulator network in the heart under physiological conditions.
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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".