Adenosine receptor activation influences postexercise skin blood flow (1106.20)
Bibliographic record
Abstract
Adenosine receptor activation influences postexercise skin blood flow R. N. McGinn, N. Fujii, G. P. Kenny Human and Environmental Physiology Research Unit, School of Human Kinetics, University of Ottawa, Ottawa, ON, K1N 6N5 Studies show that postexercise skin blood flow (SkBF) is reduced despite persistent hyperthermia. We have ascribed this to altered active vasodilation rather than adrenergic vasoconstriction (Kenny, Front Bio 15:259 2010). However, recent work shows that adenosine receptors mediates the decrease in SkBF following passive heat stress (Swift et al, Exp Phys, Epub 2013), thus it is plausible that adenosine receptors may also modulate postexercise SkBF. Eight males cycled for 15 min (85% VO2max) and then rested for 60 min at 25°C. Four microdialysis probes were inserted in the forearm and infused with: a ) Ringer’s Lactate (CON); b ) L‐NAME (nitric oxide synthase inhibitor); c ) bretylium tosylate (BT; sympathetic nerve transmission inhibitor) or d ) theophylline (THEO; adenosine receptor inhibitor). Cutaneous vascular conductance (CVC) was calculated as SkBF divided by mean arterial pressure. End‐exercise CVC was similar at all sites except L‐NAME (18% lower, P<0.01). CVC returned to resting levels after 20 min of recovery in CON (P=0.11). Compared with CON, CVC was reduced at L‐NAME at 10 min of recovery (P=0.03) and was increased at BT for the first 30 min of recovery (P<0.05). However, THEO was elevated throughout recovery (P蠄0.01) compared to CON. We show recovery SkBF to be modulated by nitric oxide (10 min) and adrenergic vasoconstriction (30 min), but adenosine receptors exerts a more prolonged effect (60 min). Abstract body: 1216/1220 characters Total: 1464/1720 characters Grant Funding Source : Supported by: Natural Sciences and Engineering Research Council of Canada
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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 | 0.000 |
| 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) | 0.004 | 0.001 |
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.
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".