The effects of local versus systemic passive heating on the acute inflammatory, vascular and glycaemic response
Bibliographic record
Abstract
The aim of this study was to compare the acute cardiometabolic and perceptual responses between local and whole-body passive heating. Using a water-perfused suit, 10 recreationally active males underwent three 90 min conditions: heating of the legs with upper-body cooling (LBH), whole-body heating (WBH) and exposure to a thermoneutral temperature (CON). Blood samples were collected before and up to 3 h post-session to assess inflammatory markers, while a 2 h oral glucose tolerance test was initiated 1 h post-session. Femoral artery blood flow and perceptual responses were recorded at regular intervals. The interleukin (IL)-6 incremental area under the curve (iAUC) was higher for LBH (1096 ± 851 pg/mL × 270 min) and WBH (833 ± 476 pg/mL × 270 min) compared with CON (565 ± 325 pg/mL × 270 min; p < 0.047). Glucose concentrations were higher after WBH compared with LBH and CON (p < 0.046). Femoral artery blood flow was higher at the end of WBH (1713 ± 409 mL/min) compared with LBH (943 ± 349 mL/min; p < 0.001), and higher in LBH than CON (661 ± 222 mL/min; p = 0.002). Affect and thermal comfort were more negative during WBH compared with LBH and CON (p < 0.010). In conclusion, local passive heating elevated blood flow and the IL-6 iAUC. However, while resulting in more positive perceptual responses, the majority of the included cardiometabolic markers were attenuated compared with WBH. Novelty: The increase in the IL-6 iAUC in response to passive heating is not reduced by upper-body cooling. Upper-body cooling attenuates the plasma nitrite, IL-1ra and femoral artery blood flow response to passive heating. Upper-body cooling leads to more positive perceptual responses to passive heating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".