Individual vasodilatory response heterogeneity during progressive forearm exercise: evidence for vasodilator phenotypes
Bibliographic record
Abstract
PURPOSE To determine whether vasodilator and/or pressor response phenotypes are present during a perfusion pressure induced perturbation to exercising muscle oxygen delivery (O 2 D). METHODS 10 healthy male subjects (19.5±0.4 yrs) completed two trials of progressive handgrip exercise to exhaustion (2.5kg increments every 3.5 mins) in each forearm above and below heart level (forearm arterial perfusion pressure (FAPP) Δ 29.5±0.97mmHg). Forearm blood flow ((FBF (ml/min); brachial artery Doppler and echo ultrasound), mean arterial blood pressure (MAP (mmHg); finger photoplethysmography) and O 2 D (ml/O 2 /min; venous effluents) were measured at the end of each work rate (WR). RESULTS Group level, Δ FBF was compromised beyond the 5kg WR in above vs. below. There was no vasodilatory (P=0.21) or exercise pressor (P=0.63) response, and submax O 2 D, submax and peak VO 2 and peak WR were compromised by reduced FAPP (all P<0.05). In contrast, individual responses revealed compensatory vasodilators (n=6) and those who did not (n=4). Vasodilators blunted the FAPP‐evoked reduction in submax O 2 D and VO 2 compared to non‐vasodilators (P<0.05), and experienced less of a compromise to peak WR (P<0.05). CONCLUSIONS In the current model, vasodilatory response phenotypes exist, which determine hypoperfusion susceptibility and the degree to which aerobic metabolism and exercise performance are compromised. NSERC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".