The effects of passive heating and subsequent exercise in the heat on lipid metabolism
Bibliographic record
Abstract
The goal of this study was to examine the effects of heat exposure on lipid metabolism during passive heating and subsequent exercise in the heat by focusing on changes in whole‐body lipid utilization and plasma lipids. Male participants (n=8) were passively heated for 120 min at 42°C, then exercised on a treadmill in the heat at 50% VO2peak for 30 min (HEAT), and on a separate occasion followed the same procedure at 23°C (CON). Results showed that whole‐body lipid utilization rates were not different between HEAT and CON during passive heating and during exercise. At rest, non‐esterified fatty acid (NEFA) concentrations were significantly higher following passive heating (618 ± 59 μmol/l) compared to CON (391 ± 51 μmol/l). The same trend was observed following exercise (2036 ± 183 μmol/l and 1350 ± 147 μmol/l for HEAT and CON respectively). Triglyceride, phospholipid and cholesterol levels were not different between HEAT and CON following passive heating or exercise. We conclude that heat exposure results in higher circulating NEFAs both at rest and during exercise without significant changes in whole‐body lipid utilization. CIHR graduate student scholarship and NSERC to F. Haman
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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) | 0.001 | 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".