Endothelium‐dependent Vasodilation in Myogenically Active Mouse Skeletal Muscle Arterioles: Role of EDH and K<sup>+</sup> Channels
Bibliographic record
Abstract
As smooth muscle cell (SMC) membrane potential (E(m)) is critical for vascular responsiveness, and arteriolar SMCs are depolarized at physiological intraluminal pressures, we hypothesized that myogenic tone impacts on dilation mediated by endothelium-derived hyperpolarization (EDH). Studies were performed on cannulated mouse cremaster arterioles [diameter, 33+/-2 microm (n=23) at 60 mmHg; SMC Em -34.6+/-1.2 mV (n=7)]. Myogenic activity was assessed as tone developed in response to intraluminal pressure. Functional observations were related to mRNA, protein expression, and anatomy. Acetylcholine concentration-response curves showed a modest shift following indomethacin (10 microM) and L-NAME (100 microM), although maximal vasodilation was achieved. Residual dilation was removed by apamin (1 microM) in combination with TRAM-34 (1 microM) or charybotoxin (0.1 microM), indicating the requirement of small (S) and intermediate (I) calcium-activated potassium channels (K(Ca)). Charybdotoxin, but not TRAM-34, caused vasoconstriction, presumably through the inhibition of SMC BK(Ca). Expression of SK3 and IK1 was confirmed by immunohistochemistry and polymerase chain reaction, while myoendothelial junctions were common, suggesting a high degree of cell coupling. Also consistent with a role for endothelial K(Ca) channels, acetylcholine increased endothelium [Ca(2 +)](i). Apamin and TRAM-34 similarly blocked EDH-mediated dilation at intraluminal pressures of 30 and 90 mmHg, suggesting that in mouse arterioles, SK(Ca -) and IK(Ca -) mediated mechanisms predominate and operate independently of physiological levels of myogenic activation.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".