Do vasoregulatory mechanisms in exercising human muscle compensate for changes in arterial perfusion pressure?
Bibliographic record
Abstract
We tested the hypothesis that vasoregulatory mechanisms completely counteract the effects of sudden changes in arterial perfusion pressure on exercising muscle blood flow. Twelve healthy young subjects (7 female, 5 male) lay supine and performed rhythmic isometric handgrip contractions (2 s contraction/ 2 s relaxation 30% maximal voluntary contraction). Forearm blood flow (FBF; echo and Doppler ultrasound), mean arterial blood pressure (arterial tonometry), and heart rate (ECG) were measured. Moving the arm between above the heart (AH) and below the heart (BH) level during contraction in steady-state exercise achieved sudden approximately 30 mmHg changes in forearm arterial perfusion pressure (FAPP). We analyzed cardiac cycles during relaxation (FBF(relax)). In an AH-to-BH transition, FBF(relax) increased immediately, in excess of the increase in FAPP (approximately 69% vs. approximately 41%). This was accounted for by pressure-related distension of forearm resistance vasculature [forearm vascular conductance (FVC(relax)) increased by approximately 19%]. FVC(relax) was restored by the second relaxation. Continued slow decreases in FVC(relax) stabilized by 2 min without restoring FBF(relax). In a BH-to-AH transition, FBF(relax) decreased immediately, in excess of the decrease in FAPP (approximately 37% vs. approximately 29%). FVC(relax) decreased by approximately 14%, suggesting pressure-related passive recoil of resistance vessels. The pattern of FVC(relax) was similar to that in the AH-to-BH transition, and FBF(relax) was not restored. These data support rapid myogenic regulation of vascular conductance in exercising human muscle but incomplete flow restoration via slower-acting mechanisms. Local arterial perfusion pressure is an important determinant of steady-state blood flow in the exercising human forearm.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".