Erythropoietin Inhibits Anoxia/Reoxygenation‐Induced Cardiomyocyte Apoptosis via Heme Oxygenase‐1
Bibliographic record
Abstract
Recent studies have shown that erythropoietin (EPO), a 165 amino acid cytokine best known for its ability to increase red blood cell production, can decrease apoptosis in the heart. As of yet, the mechanisms by which this occurs are not fully understood. Heme oxygenase 1 (HO‐1) has been shown to protect cardiomyocytes from apoptosis during myocardial ischemia and reperfusion. The present study sought to determine if increased HO‐1 expression is involved in the anti‐apoptotic effects of EPO during anoxia and reoxygenation (A/R), an in vitro counterpart of myocardial ischemia and reperfusion. Neonatal mouse ventricular cardiomyocytes were isolated from the hearts of C57BL6 mice and cultured in M199. Cells were subjected to 1 hour of anoxia, followed by 30 minutes of reoxygenation. Apoptosis was measured using a caspase‐3 activity assay. Pre‐treatment with EPO (20 U/mL 24 hours prior to anoxia) significantly reduced apoptosis following anoxia and reoxygenation (P<0.05). The reduction in apoptosis was coupled with increases in HO‐1 mRNA and protein expression. Furthermore, inhibition of HO‐1 activity using tin protoporphyrin‐IX resulted in significant attenuation of the anti‐apoptotic effects of EPO. Co‐treatment of EPO with SB203885, an inhibitor of p38 activity, blocked the EPO‐mediated increases in HO‐1 expression, however inhibition of Akt‐1 activity with LY294002 had no significant effect. Taken together, our data suggest that EPO upregulates HO‐1 in cardiomyocytes via p38 activation and that HO‐1 upregulation is partially responsible for the anti‐apoptotic effects of EPO during anoxia and reoxygenation. Supported by HSFO.
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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".