Brown adipose tissue oxidative metabolism contributes to energy expenditure during acute cold exposure in humans
Bibliographic record
Abstract
Brown adipose tissue (BAT) is vital for proper thermogenesis during cold exposure in rodents, but until recently its presence in adult humans and its contribution to human metabolism were thought to be minimal or insignificant. Recent studies using PET with 18F-fluorodeoxyglucose (18FDG) have shown the presence of BAT in adult humans. However, whether BAT contributes to cold-induced nonshivering thermogenesis in humans has not been proven. Using PET with 11C-acetate, 18FDG, and 18F-fluoro-thiaheptadecanoic acid (18FTHA), a fatty acid tracer, we have quantified BAT oxidative metabolism and glucose and nonesterified fatty acid (NEFA) turnover in 6 healthy men under controlled cold exposure conditions. All subjects displayed substantial NEFA and glucose uptake upon cold exposure. Furthermore, we demonstrated cold-induced activation of oxidative metabolism in BAT, but not in adjoining skeletal muscles and subcutaneous adipose tissue. This activation was associated with an increase in total energy expenditure. We found an inverse relationship between BAT activity and shivering. We also observed an increase in BAT radio density upon cold exposure, indicating reduced BAT triglyceride content. In sum, our study provides evidence that BAT acts as a nonshivering thermogenesis effector in humans.
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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".