MRI Reveals Human Brown Adipose Tissue Is Rapidly Activated in Response to Cold
Bibliographic record
Abstract
Abstract Context In rodents, cold exposure induces the activation of brown adipose tissue (BAT) and the induction of intracellular triacylglycerol (TAG) lipolysis. However, in humans, the kinetics of supraclavicular (SCV) BAT activation and the potential importance of TAG stores remain poorly defined. Objective To determine the time course of BAT activation and changes in intracellular TAG using MRI assessment of the SCV (i.e., BAT depot) and fat in the posterior neck region (i.e., non-BAT). Design Cross-sectional. Setting Clinical research center. Patients or Other Participants Twelve healthy male volunteers aged 18 to 29 years [body mass index = 24.7 ± 2.8 kg/m2 and body fat percentage = 25.0% ± 7.4% (both, mean ± SD)]. Intervention(s) Standardized whole-body cold exposure (180 minutes at 18°C) and immediate rewarming (30 minutes at 32°C). Main Outcome Measure(s) Proton density fat fraction (PDFF) and T2* of the SCV and posterior neck fat pads. Acquisitions occurred at 5- to 15-minute intervals during cooling and subsequent warming. Results SCV PDFF declined significantly after only 10 minutes of cold exposure [−1.6% (SE: 0.44%; P = 0.007)] and continued to decline until 35 minutes, after which time it remained stable until 180 minutes. A similar time course was also observed for SCV T2*. In the posterior neck fat (non-BAT), there were no cold-induced changes in PDFF or T2*. Rewarming did not result in a change in SCV PDFF or T2*. Conclusions The rapid cold-induced decline in SCV PDFF suggests that in humans BAT is activated quickly in response to cold and that TAG is a primary substrate.
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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".