Erythropoietin protects cardiomyocytes from apoptosis via up-regulation of endothelial nitric oxide synthase
Bibliographic record
Abstract
OBJECTIVE: Erythropoietin (EPO), a cytokine best known for its ability to increase red blood cell mass, has recently been shown to protect cardiomyocytes from apoptotic cell death. The objective of the present study was to investigate the role of endothelial nitric oxide synthase (eNOS) in the anti-apoptotic effects of EPO in cardiomyocytes. METHODS AND RESULTS: Neonatal mouse ventricular cardiomyocytes were isolated and cultured from wild-type and eNOS(-/-) mice. Treatment with EPO significantly reduced apoptosis induced by norepinephrine (NE) in the wild-type cardiomyocytes. The reduction of apoptosis was associated with significant increases in eNOS expression, phosphorylation and NO production. However, the anti-apoptotic effects of EPO were significantly decreased in wild-type cardiomyocytes treated with L-NAME, which inhibits nitric oxide synthase activity. The results were further confirmed using eNOS(-/-) cardiomyocytes. To investigate the in vivo significance of eNOS in mediating the anti-apoptotic effects of EPO, wild-type and eNOS(-/-) mice were subjected to myocardial ischemia and reperfusion. EPO decreased myocardial apoptosis and infarct size in wild-type mice. However, the protective effects of EPO were significantly diminished in eNOS(-/-) mice. CONCLUSIONS: EPO increases eNOS expression and NO production in cardiomyocytes. The anti-apoptotic effects of EPO in cardiomyocytes are mediated by eNOS-derived NO production.
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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".