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Is the Response Capacity of Rapid Vasodilation Mechanism(s) at Exercise Onset Sensitive to Exercise Training?

2010· article· en· W2072885577 on OpenAlexaff
Kristine Matusiak, Robert F. Bentley, Trevor J. King, Michael E. Tschakovsky

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsQueen's University
Fundersnot available
KeywordsIsometric exerciseMedicineForearmSupine positionCardiologyVasodilationHeart rateInternal medicineContraction (grammar)Brachial arteryBlood pressurePhysical therapySurgery

Abstract

fetched live from OpenAlex

Resistance vessels in skeletal muscle dilate with the first contraction of exercise. This dilation is proportional to contraction intensity. Whether the mechanism(s) responsible for this immediate, rapid vasodilation can be modified with exercise training is unknown. PURPOSE: We tested the hypothesis that the immediate and peak forearm vasodilatory response to a single, brief forearm contraction would be higher in arm + leg trained athletes vs. leg trained athletes. METHODS: 8 male distance runners and 9 male rowers were recruited from the Queen's University varsity teams. Varsity runners served as a control for whole body training status. Subjects lay supine with the arm extended laterally at heart level and performed single, 1 s isometric handgrip contractions at each of 5 kg, 15 kg, 25 kg and 35 kg contraction force. 3 trials per contraction force were averaged for each subject. Order of contraction force was counterbalanced across subjects. Beat by beat measures of brachial artery forearm blood flow (FBF; Doppler and Echo ultrasound) mean arterial blood pressure (MAP; finger photoplethysmography) and heart rate (HR; ECG) were made at baseline and for 1 min following each contraction. RESULTS: Data are mean ±SE. MAP was not different between groups. Therefore, increases in FBF (DFBF) from rest were representative of the vasodilatory response to contractions. DFBF (ml/min) in the first cardiac cycle post-contraction was not different between groups at 5 kg (P=0.275) or 35 kg (P=0.332), but was significantly elevated in rowers at 15 kg (118 ±19 vs. 84 ±9, P=0.013) and 25 kg (176 ±17 vs. 130 ±13, P=0.038). Peak DFBF (∼3rd - 4th cardiac cycle following contraction) was not different at 5 kg (P=0.967). It was elevated in rowers at 15 kg (183 ±18 vs. 112 ±11, P=0.015), 25 kg (266 ±23 vs. 193 ±21, P=0.005) and 35 kg (333 ±32 vs. 256 ±27, P<0.001). The slope of the peak FBF response vs. contraction force was significantly steeper in rowers than runners (8.6 ±0.9 vs. 5.5 ±0.8 ml/min/kg, P=0.02) CONCLUSIONS: These data support the hypothesis that rapid vasodilatory mechanisms responsible for the onset of exercise hyperemia can be improved with exercise training. This effect can be achieved in young, healthy males and is independent of whole body training status. The stimulus for this adaptation appears to be local to the trained muscle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.024
GPT teacher head0.279
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2010
Admission routes1
Has abstractyes

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