CONTRACTION INTENSITY DETERMINES IMMEDIATE BLOOD FLOW INCREASE AT EXERCISE ONSET
Bibliographic record
Abstract
Debate continues regarding the existence of vasodilatory mechanisms that could contribute to the “immediate” increase (first second following initial contraction release) in blood flow at the on set of exercise. PURPOSE To test the hypothesis that vasodilation proportional to muscle activation determines the immediate increase in blood flow following the first contraction of exercise. We reasoned that if such vasodilatory mechanisms do exist, we would observe an increase in blood flow during the first heart beat following a single, brief contraction that was proportional to the intensity of the contraction in conditions where the muscle pump was ineffective. METHODS 5 healthy young subjects 24.5 ± 2.5 yrs; 2 males, 3 females) lay supine with the forearm above heart level. In this position, veins are virtually empty, and we do not observe any contraction-induced venous emptying, i.e. muscle pump is ineffective (data not shown). 1-s forearm isometric handgrip contractions were performed across a range of %maximal voluntary contraction (%MVC) intensities (5–70%). Beat-by-beat measures of brachial artery diameter and mean blood velocity (BAD,MBV; Doppler ultrasound), heart rate (HR; ECG) and arterial blood pressure (ABP; tonometry) were performed.Figure: No Caption AvailableRESULTS Neither HR, BAD nor ABP changed with the first heart beat following contraction, therefore MBV represents forearm blood flow and is reported here. Figure demonstrates the tight linear relationship of %change in MBV with contraction intensity. CONCLUSIONS These data support the hypothesis that vasodilation proportional to muscle activation determines the immediate blood flow increase at the onset of exercise. Mechanisms responsible remain to be determined. Supported by NSERC; CFI New Opportunities Fund
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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) | 0.003 | 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".