Influence of Core Temperature Changes During Whole-Body Warming and Cooling on Cutaneous Vascular Reactivity
Bibliographic record
Abstract
Objective: Endothelial function, the ability of cells of the vascular endothelial wall to secrete compounds, is linked with metabolic and cardiovascular disease risks. One of the most well-known noninvasive tests used to assess skin vascular reactivity as a measure of endothelial function is the reactive hyperemic response test (RHRT). However, there is lack of consensus regarding the impact of thermoregulation on endothelial (dys)function and the results from the RHRT. Thus, the aim of the present study was to investigate the impact of core temperature on cutaneous vascular reactivity, as assessed via the finger RHRT. Approach: Following a 15-minute baseline period, seven adults entered a water tank maintained at 42°C and passively rested in a semi-supine position. Thereafter, they entered a water tank maintained at 12°C. They were immersed until their rectal temperature (Tre) increased or decreased about 0.5°C above and below the baseline Tre respectively. This procedure was repeated twice and an occlusion was conducted during the baseline period and at the second repetition of water immersions. Main results: During the post-occlusion phase, skin blood flow (SkBF) was greater, comparing to pre- and occlusion phases, across all Tre levels (five levels: baseline, mild hyperthermia 1, mild hypothermia 1, mild hyperthermia 2, mild hypothermia 2). Also, SkBF throughout pre-occlusion, occlusion, and post-occlusion was greater during mild hyperthermia 2. Significance: We found a significant impact of core temperature on SkBF and cutaneous vascular reactivity which affects the diagnostic indicators obtained from the RHRT and can impact the final outcome.
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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) | 0.002 | 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".