Cold acclimation increases the contribution of brown adipose tissue‐derived thermogenesis in adult humans
Bibliographic record
Abstract
Recent studies examining brown adipose tissue (BAT) metabolism in adult humans have provided convincing evidence that it can significantly contribute to cold‐induced thermogenesis under acute mild‐cold exposure. Although, many mammalian models have demonstrated the adaptability of this tissue through chronic cold exposure, little is known about its plasticity in humans. Using electromyography combined with positron emission tomography with 11 C‐acetate and 18 F‐fluorodeoxyglucose, shivering intensity and BAT oxidative metabolism and glucose uptake prior to and following four weeks of cold acclimation were examined. Non‐acclimated men were exposed to 10°C, two hours daily for four weeks (5 days/week), using a liquid‐conditioned suit (LCS). Preliminary data suggests a 5‐fold increase in BAT oxidative metabolism (from 0.005±0.004to 0.025±0.007 sec −1 , n=3) resulting in a ~40% decrease in shivering intensity (from 3.2±1.4 to 2.0±1.3 %MVC, n=3), through four weeks of cold‐acclimation, despite similar 1.8‐fold increases in cold‐induced energy expenditure (10.6±1.4 and 10.3±1.3 kJ·min −1 , pre‐and postacclimation, respectively, n=3). Fractional and net glucose uptake in BAT increased 2.2‐fold (from 0.017±0.007 to 0.037±0.015 min −1 and from 81±35 to 183±82 nmol·g −1 ·min −1 ) following cold‐acclimation. Our preliminary results demonstrate an increased capacity of BAT‐derived thermogenesis during acute cold exposure after a 4‐week cold acclimation period in healthy men. This research was supported by the Natural Sciences and Engineering Research Council of Canada and the Canadian Diabetes Association (grant OG 3–10‐2970‐AC).
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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) | 0.002 | 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".