Skeletal muscle contraction-induced vasodilator complement production is dependent on stimulus and contraction frequency
Bibliographic record
Abstract
To test the hypothesis that the vasodilator complement that produces arteriolar vasodilation during muscle contraction depends on both stimulus and contraction frequency, we stimulated four to five skeletal muscle fibers in the anesthetized hamster cremaster preparation in situ and measured the change in diameter of arterioles at a site of overlap with the stimulated muscle fibers. Diameter was measured before, during, and after 2 min of skeletal muscle contraction stimulated over a range of stimulus frequencies [4, 20, and 40 Hz; 15 contractions/min (cpm), 250 ms train duration] and a range of contraction frequencies (6, 15, and 60 cpm; 20 Hz stimulus frequency, 250 ms train duration). Muscle fibers were stimulated in the absence and presence of an inhibitor of adenosine receptors [10(-6) M xanthine amine congener (XAC)], an ATP-dependent potassium (K(+)) channel inhibitor (10(-5) M glibenclamide), an inhibitor of a source of K(+) by inhibition of voltage-dependent K(+) channels [3 x 10(-4) M 3,4-diaminopyridine (DAP)], and an inhibitor of nitric oxide synthase [10(-6) M N(G)-nitro-l-arginine methyl ester (l-NAME) + 10(-7) S-nitroso-N-acetylpenicillamine (a nitric oxide donor)]. L-NAME inhibited the dilations at all stimulus frequencies and contraction frequencies except 60 cpm. XAC inhibited the dilations at all contraction frequencies and stimulus frequencies except 40 Hz. Glibenclamide inhibited all dilations at all stimulus and contraction frequencies, and DAP did not inhibit dilations at any stimulus frequencies while attenuating dilation at a contraction frequency of 60 cpm only. Our data show that the complement of dilators responsible for the vasodilations induced by skeletal muscle contraction differed depending on the stimulus and contraction frequency; therefore, both are important determinants of the dilators involved in the processes of arteriolar vasodilation associated with active hyperemia.
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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 | 0.001 | 0.001 |
| 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".