Adipose ABHD6 regulates tolerance to cold and thermogenic programs
Bibliographic record
Abstract
Enhanced energy expenditure in brown (BAT) and white adipose tissues (WAT) can be therapeutic against metabolic diseases. We examined the thermogenic role of adipose α/β-hydrolase domain 6 (ABHD6), which hydrolyzes monoacylglycerol (MAG), by employing adipose-specific ABHD6-KO mice. Control and KO mice showed similar phenotypes at room temperature and thermoneutral conditions. However, KO mice were resistant to hypothermia, which can be accounted for by the simultaneously increased lipolysis and lipogenesis of the thermogenic glycerolipid/free fatty acid (GL/FFA) cycle in visceral fat, despite unaltered uncoupling protein 1 expression. Upon cold stress, nuclear 2-MAG levels increased in visceral WAT of the KO mice. Evidence is provided that 2-MAG causes activation of PPARα in white adipocytes, leading to elevated expression and activity of GL/FFA cycle enzymes. In the ABHD6-ablated BAT, glucose and oxidative metabolism were elevated upon cold induction, without changes in GL/FFA cycle and lipid turnover. Moreover, response to in vivo β3-adrenergic stimulation was comparable between KO and control mice. Our data reveal a MAG/PPARα/GL/FFA cycling metabolic signaling network in visceral adipose tissue, which contributes to cold tolerance, and that adipose ABHD6 is a negative modulator of adaptive thermogenesis.
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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".