The influence of Metabo‐ and Baroreceptors on Postexercise Heat Loss
Bibliographic record
Abstract
We studied the relative and separate contribution of metabo‐ and baroreflex activity to heat loss during postexercise recovery. Seven males (21 ± 2 years) performed 15 min of running (90% heart rate max) in the heat (35°C). During the 60 min postexercise period, four 1‐min bouts of isometric handgrip exercise (IHG) were followed by 2 min of forearm ischemia (toactivate metaboreceptors, OCC), each separated by 15 min. This was repeated on separate days during a normal seated recovery (CON) and during the application of lower body positive (LBPP, +40 mmHg) or negative (LBNP, ‐20 mmHg) pressure starting at 13 min of recovery. Forearm sweat rate and cutaneous vascular conductance (CVC) were measured continuously. For all conditions CVC returned to pre‐dynamic exercise resting levels at 45 min of recovery ( P > 0.05) whereas sweating remained elevated for the duration of recovery ( P < 0.05). Relative to pre‐IHG resting CVC was reduced during IHG at 15 min of recovery and subsequently returned to pre‐IHG levels during OCC in CON only. No effect of IHG on CVC was observed for LBPP or LBNP. However LBNP caused an OCC‐induced decrease in CVC from pre‐IHG levels at 15 min of recovery only ( P < 0.05). Sweating increased during IHG and remained elevated at similar levels during OCC for all conditions in the final 30 min of recovery ( P < 0.05). We show that metaboreceptors influence CVC during the early stages of recovery which is modulated to a certain extent by baroreceptor activity. In contrast, sweating is influenced by metaboreceptor activation in the mid‐to‐late stages of recovery independent of changes in baroreceptor activity. Support: Natural Sciences and Engineering Research 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 | 0.001 |
| 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".