Rapid vasoregulatory mechanisms in exercising human skeletal muscle: dynamic response to repeated changes in contraction intensity
Bibliographic record
Abstract
We tested the hypothesis that vasoregulatory mechanisms exist in humans that can rapidly adjust muscle blood flow to repeated increases and decreases in exercise intensity. Six men and seven women (age, 24.4+/-1.3 yr) performed continuous dynamic forearm handgrip contractions (1- to 2-s contraction-to-relaxation duty cycle) during repeated step increases and decreases in contraction intensity. Three step change oscillation protocols were examined: Slow (7 contractions per contraction intensityx10 steps); Fast (2 contractions per contraction intensityx15 steps); and Very Fast (1 contraction per contraction intensityx15 steps). Forearm blood flow (FBF; Doppler and echo ultrasonography), heart rate (ECG), and mean arterial pressure (arterial tonometry) were examined for the equivalent of a cardiac cycle during each relaxation phase (FBFrelax). Mean arterial pressure and heart rate did not change during repeated step changes (P=0.352 and P=0.190). For both Slow and Fast conditions, relaxation phase FBFrelax adjusted immediately and repeatedly to both increases and decreases in contraction intensity, and the magnitude and time course of FBFrelax changes were virtually identical. For the Very Fast condition, FBFrelax increased with the first contraction and thereafter slowly increased over the course of repeated contraction intensity oscillations. We conclude that vasoregulatory mechanisms exist in human skeletal muscle that are capable of rapidly and repeatedly adjusting muscle blood flow with ongoing step changes in contraction intensity. Importantly, they demonstrate symmetry in response magnitude and time course with increasing versus decreasing contraction intensity but cannot adjust to very fast exercise intensity oscillations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".