Role of vascular bed compliance in vasomotor control in human skeletal muscle
Bibliographic record
Abstract
The current view of neurogenic vasomotor control in skeletal muscle is based largely on changes in vascular bed resistance. The purpose of this study was to determine to what extent vascular bed compliance may also play a role in this regulation. For this purpose, pressure waveforms (Millar and Finometer) and flow waveforms (Doppler ultrasound) were measured simultaneously in the brachial artery of seven healthy individuals during physiological manoeuvres which were expected to produce non-neurogenic changes in resistance (wrist-cuff occlusion; n = 5) or compliance (arm elevation; n = 6) of the forearm vascular bed. Vascular resistance (R) was calculated from the average flow and pressure values. A lumped Windkessel model was used to obtain vascular bed compliance (C) from these concurrently measured waveforms. Compared with baseline (3.81 +/- 1.59 ml min(-1) mmHg(-1)), wrist occlusion increased R (65 +/- 75%; P < 0.05) with minimal change in C (-15 +/- 16%; n.s.). Compared with the arm in neutral position (0.0075 +/- 0.003 ml mmHg(-1)), elevation of the arm above heart level produced a 86 +/- 41% increase in C (P < 0.05) with little change in R (-5 +/- 11%). In addition, neurogenic changes were assessed during lower body negative pressure (LBNP) and a cold pressor test (CPT; n = 7). Lower body negative pressure induced a 29 +/- 24% increase in R and a 26 +/- 12% decrease in C (both P < 0.05). The CPT induced no consistent change in R but a 22 +/- 7% reduction in C (P < 0.05). It was concluded that vascular bed compliance is an independent variable which should be considered along with vascular bed resistance in the mechanics of vasomotor regulation in skeletal muscle.
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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 | 0.002 |
| 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 | 0.000 |
| 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".