Role of large-conductance Ca<sup>2+</sup>-activated K<sup>+</sup> channels in adenosine A<sub>1</sub> receptor-mediated pharmacological postconditioning in H9c2 cells
Bibliographic record
Abstract
Ischaemic postconditioning is a phenomenon whereby short periods of ischaemia applied during the start of reperfusion protect the myocardium from the damaging consequences of reperfusion. As such, pharmacological-induced postconditioning represents an attractive therapeutic strategy for reducing reperfusion injury during cardiac surgery and following myocardial infarction. The primary aim of this study was to determine the role of large-conductance Ca²(+)-activated potassium channels (BK(Ca) channels) in adenosine A₁ receptor-induced pharmacological postconditioning in the rat embryonic cardiomyoblast-derived cell line H9c2. H9c2 cells were exposed to 6 h hypoxia (0.5% O₂) followed by 18 h reoxygenation (H/R) after which cell viability was assessed by monitoring lactate dehydrogenase (LDH) release and caspase-3 activation. The adenosine A₁ receptor agonist N⁶-cyclopentyladenosine (CPA; 100 nmol/L) or the BK(Ca) channel opener NS1619 (10 µmol/L) were added for 30 min at the start of reoxygenation following 6 h hypoxic exposure. Where appropriate, cells were treated (15 min) before pharmacological postconditioning with the BK(Ca) channel blockers paxilline (1 µmol/L) or iberiotoxin (100 nmol/L). Pharmacological postconditioning with CPA or NS1619 significantly reduced H/R-induced LDH release. Treatment with paxilline or iberiotoxin attenuated adenosine A₁ receptor and NS1619-induced pharmacological postconditioning. These results have shown for the first time that BK(Ca) channels are involved in adenosine A₁ receptor-induced pharmacological postconditioning in a cell model system.
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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 | 0.001 |
| 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".