RETRACTED ARTICLE: Role of dopamine D2 receptors in ischemia/reperfusion induced apoptosis of cultured neonatal rat cardiomyocytes
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
BACKGROUND: Myocardial ischemia/reperfusion injury is the major cause of morbidity and mortality for cardiovascular diseases. Dopamine D2 receptors are expressed in cardiac tissues. However, the roles of dopamine D2 receptors in myocardial ischemia/reperfusion injury and cardiomyocyte apoptosis are unclear. Here we investigated the effects of both dopamine D2 receptors agonist (bromocriptine) and antagonist (haloperidol) on apoptosis of cultured neonatal rat ventricular myocytes induced by ischemia/reperfusion injury. METHODS: Myocardial ischemia/reperfusion injury was simulated by incubating primarily cultured neonatal rat cardiomyocytes in ischemic (hypoxic) buffer solution for 2 h. Thereafter, these cells were incubated for 24 h in normal culture medium. RESULTS: Treatment of the cardiomyocytes with 10 μM bromocriptine significantly decreased lactate dehydrogenase activity, increased superoxide dismutase activity, and decreased malondialdehyde content in the culture medium. Bromocriptine significantly inhibited the release of cytochrome c, accumulation of [Ca2+]i, and apoptosis induced by ischemia/reperfusion injury. Bromocriptine also down-regulated the expression of caspase-3 and -9, Fas and Fas ligand, and up-regulated Bcl-2 expression. In contrast, haloperidol (10 μM) had no significant effects on the apoptosis of cultured cardiomyocytes under the aforementioned conditions. CONCLUSIONS: These data suggest that activation of dopamine D2 receptors can inhibit apoptosis of cardiomyocytes encountered during ischemia/reperfusion damage through various pathways.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.012 |
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".