The functional role of brown adipose tissue in whole‐body lipid metabolism in humans (1160.3)
Bibliographic record
Abstract
Despite intense scientific interest regarding the role of human brown adipose tissue (BAT) in substrate metabolism, its role in whole‐body lipid metabolism remains unclear. To address this issue, we studied otherwise matched men with high (HBAT, n=7) and low (LBAT: n=5) BAT volume (69±18 mL vs. 4±2 mL, p<0.05) under cold exposure (CE) and thermoneutral (TN) conditions using positron emission tomography‐computed tomography, stable isotope infusions, and indirect calorimetry. For HBAT, but not LBAT participants, plasma free fatty acid concentrations (TN: 0.36±0.01mmol/L vs. CE: 0.63±0.01mmol/L, p<0.05), plasma glycerol concentrations (TN: 0.05±0.01 mmol/L vs. CE: 0.09±0.01 mmol/L, p<0.05), lipolysis (TN: 2.2±0.3 μmol/kg/min vs. CE: 5.9±0.6μmol/kg/min, p<0.05), and plasma free fatty acid oxidation (TN: 2.7±0.6 μmol/kg/min vs. CE: 5.9±1.0 μmol/kg/min, p<0.05) were higher under CE conditions than TN conditions. Moreover, during CE, plasma small LDL and large HDL particles increased more in the HBAT group than in the LBAT group (p<0.05). Finally, the HBAT group tended to have decreased plasma triglyceride concentrations the day after CE (‐33.4±11.4 mg/dl, p=0.06), whereas LBAT subjects showed no significant change. These novel findings demonstrate a functional role of BAT in human lipid metabolism. Grant Funding Source : : CTSA UL1TR000071, Pepper Center Pilot Grant, Sealy Center on Aging, Shriners Hospitals
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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 | 0.001 | 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".