p27 Protein Protects Metabolically Stressed Cardiomyocytes from Apoptosis by Promoting Autophagy
Bibliographic record
Abstract
p27(Kip1) (p27), a key regulator of cell division, has been implicated in autophagy of cancer cells. However, its role in autophagy, the evolutionarily conserved catabolic process that enables cells to remove unwanted proteins and damaged organelles, had not been examined in the heart. Here we report that ectopic delivery of a p27 fusion protein (TAT-p27) was sufficient to induce autophagy in neonatal rat ventricular cardiomyocytes in vitro, under basal conditions and after glucose deprivation. Conversely, lentivirus-delivered shRNA against p27 successfully reduced p27 levels and suppressed basal and glucose-deprived levels of autophagy in cardiomyocytes in vitro. Glucose deprivation mimics myocardial ischemia and induces apoptosis in cardiomyocytes. During glucose deprivation, TAT-p27 inhibited apoptosis, whereas down-regulation of p27 decreased survival of cardiomyocytes. However, inhibition of autophagy by pharmacological (3-methyladenine, chloroquine, or bafilomycin A1) or genetic approaches (siRNA-mediated knockdown of Atg5) sensitized cardiomyocytes to glucose deprivation-induced apoptosis, even in the presence of TAT-p27. TAT-p27 was also able to provoke greater levels of autophagy in resting and fasting cardiomyocytes in vivo. Further, TAT-p27 enhanced autophagy and repressed cardiomyocytes apoptosis, improved cardiac function, and reduced infarct size following myocardial infarction. Again, these effects were lost when cardiac autophagy in vivo was blocked by chloroquine. Taken together, these data show that p27 positively regulates cardiac autophagy in vitro and in vivo, at rest and after metabolic stress, and that TAT-p27 inhibits apoptosis by promoting autophagy in glucose-deprived cardiomyocytes in vitro and in post-myocardial infarction hearts in vivo.
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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".