Endothelial Feedback and the Myoendothelial Projection
Bibliographic record
Abstract
The endothelium plays a critical role in controlling resistance artery diameter, and thus blood flow and blood pressure. Circulating chemical mediators and physical forces act directly on the endothelium to release diffusible relaxing factors, such as NO, and elicit hyperpolarization of the endothelial cell membrane potential, which spreads to the underlying smooth muscle cells via gap junctions (EDH). It has long been known that arterial vasoconstriction in response to agonists is limited by the endothelium, but the question of how contraction of smooth muscle cells leads to activation of the endothelium (myoendothelial feedback) has, until recently, received little attention. Initial studies proposed the permissive movement of Ca(2+) ions from smooth muscle to endothelial cells to elicit release of NO. However, more recent evidence supports the notion that flux of IP(3) leading to localized Ca(2+) events within spatially restricted myoendothelial projections and activation of EDH may underlie myoendothelial feedback. In this perspective, we review recent data which supports the functional role of myoendothelial projections in smooth muscle to endothelial communication. We also discuss the functional evidence supporting the notion that EDH, as opposed to NO, is the primary mediator of myoendothelial feedback in resistance arteries.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".