Coronary arterial BK channel dysfunction exacerbates ischemia/reperfusion-induced myocardial injury in diabetic mice
Bibliographic record
Abstract
The large conductance Ca(2+)-activated K(+) (BK) channels, abundantly expressed in coronary artery smooth muscle cells (SMCs), play a pivotal role in regulating coronary circulation. A large body of evidence indicates that coronary arterial BK channel function is diminished in both type 1 and type 2 diabetes. However, the consequence of coronary BK channel dysfunction in diabetes is not clear. We hypothesized that impaired coronary BK channel function exacerbates myocardial ischemia/reperfusion (I/R) injury in streptozotocin-induced diabetic mice. Combining patch-clamp techniques and cellular biological approaches, we found that diabetes facilitated the colocalization of angiotensin II (Ang II) type 1 receptors and BK channel α-subunits (BK-α), but not BK channel β1-subunits (BK-β1), in the caveolae of coronary SMCs. This caveolar compartmentation in vascular SMCs not only enhanced Ang II-mediated inhibition of BK-α but also produced a physical disassociation between BK-α and BK-β1, leading to increased infarct size in diabetic hearts. Most importantly, genetic ablation of caveolae integrity or pharmacological activation of coronary BK channels protected the cardiac function of diabetic mice from experimental I/R injury in both in vivo and ex vivo preparations. Our results demonstrate a vascular ionic mechanism underlying the poor outcome of myocardial injury in diabetes. Hence, activation of coronary BK channels may serve as a therapeutic target for cardiovascular complications of diabetes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".