Acute changes in forearm vascular compliance during transient sympatho‐excitation
Bibliographic record
Abstract
The study of vascular regulation often omits important information about the elastic properties of arteries under conditions of pulsatile flow. The purpose of this study was to examine the relationship between muscle sympathetic nerve activity (MSNA), vascular bed compliance, and peripheral blood flow responses in humans. We hypothesized that increases in MSNA would correlate with reductions in vascular compliance, and that changes in compliance would correspond with changes in peripheral blood flow during sympatho-excitation. MSNA (microneurography), blood pressure (Finopres), and brachial artery blood flow (Doppler ultrasound), were monitored in six healthy males at baseline and during the last 15 s of voluntary end-inspiratory, expiratory apneas and 5 min of static handgrip exercise (SHG; 20% maximum voluntary contraction) and 3 min of post-exercise circulatory occlusion (SHG + PECO; measured in the non-exercising arm). A lumped Windkessel model was employed to examine vascular bed compliance. During apnea, indices of MSNA were inversely related with vascular compliance, and reductions in compliance correlated with decreased brachial blood flow rate. During SHG, despite increased MSNA, compliance also increased, but was unrelated to increases in blood flow. Neither during SHG nor PECO did indices of MSNA correlate with forearm vascular compliance nor did vascular compliance correlate with brachial flow. However, during PECO, a linear combination of blood pressure and total MSNA was correlated with vascular compliance. These data indicate the elastic components of the forearm vasculature are regulated by adrenergic and myogenic mechanisms during sympatho-excitation, but in a reflex-dependent manner.
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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 | 0.000 |
| 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".