Endothelial calcium-activated potassium channels as therapeutic targets to enhance availability of nitric oxide
Bibliographic record
Abstract
The vascular endothelium plays a critical role in vascular health by controlling arterial diameter, regulating local cell growth, and protecting blood vessels from the deleterious consequences of platelet aggregation and activation of inflammatory responses. Circulating chemical mediators and physical forces act directly on the endothelium to release diffusible relaxing factors, such as nitric oxide (NO), and to elicit hyperpolarization of the endothelial cell membrane potential, which can spread to the surrounding smooth muscle cells via gap junctions. Endothelial hyperpolarization, mediated by activation of calcium-activated potassium (K(Ca)) channels, has generally been regarded as a distinct pathway for smooth muscle relaxation. However, recent evidence supports a role for endothelial K(Ca) channels in production of endothelium-derived NO, and indicates that pharmacological activation of these channels can enhance NO-mediated responses. In this review we summarize the current data on the functional role of endothelial K(Ca) channels in regulating NO-mediated changes in arterial diameter and NO production, and explore the tempting possibility that these channels may represent a novel avenue for therapeutic intervention in conditions associated with reduced NO availability such as hypertension, hypercholesterolemia, smoking, and diabetes mellitus.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".