Time course of vasodilation at the onset of repetitive skeletal muscle contractions
Bibliographic record
Abstract
To characterize the vasodilatory response in the transition from a single skeletal contraction to a series of contractions, we measured the response of hamster cremaster muscle arterioles associated with four to five skeletal muscle fibers stimulated to contract for one, two, three, or four contractions (250-ms train duration) at 4-s intervals [15 contractions per minute (CPM)] for up to 12 s, at stimulus frequencies of 4, 10, 20, 30, 40, 60, and 80 Hz. To investigate the contribution of contraction frequency, we stimulated muscle fiber bundles at 30 or 60 CPM for 12 s at stimulus frequencies of 4, 20, and 60 Hz. Arteriolar diameters at the site of overlap with the stimulated muscle fibers were measured before and after each contraction. At 15 CPM at 4, 20, and 60 Hz, we observed a peak change in diameter following the first contraction of 1.1 +/- 0.1, 1.6 +/- 0.2, and 2.1 +/- 0.2 mum that almost doubled in response to the second contraction (2.0 +/- 0.1, 3.0 +/- 0.1, and 3.8 +/- 0.1 mum, respectively), but there was no further dilation following the third or fourth contraction. A similar response occurred at all stimulus and contraction frequencies tested. At 30 and 60 CPM at 60 Hz, the plateau after two contractions was followed by a further increase in diameter to a second plateau at 7-8 s. Therefore, the vasodilatory response in the transition from single to multiple contractions had components that were stimulation parameter dependent and independent and showed a plateauing behavior indicative of rapid changes in either the nature and/or concentration of vasodilators released or changes in vascular reactivity.
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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 | 0.001 |
| 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) | 0.002 | 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".