Adipocyte HDAC4 activation leads to beige adipocyte expansion and reduced adiposity
Bibliographic record
Abstract
Numerous studies have suggested that beige adipocyte abundance is correlated with improved metabolic performance, but direct evidence showing that beige adipocyte expansion protects animals from the development of obesity is missing. Previously, we have described that the liver kinase b1 (LKB1) regulates beige adipocyte renaissance in subcutaneous inguinal white adipose tissue (iWAT) through a class IIa histone deacetylase 4 (HDAC4)-dependent mechanism. This study investigates the physiological impact of persistent beige adipocyte renaissance in energy homeostasis in mice. Here we present that the transgenic mice H4-TG, overexpressing constitutively active HDAC4 in adipocytes, showed beige adipocyte expansion in iWAT at room temperature. H4-TG mice exhibited increased energy expenditure due to beige adipocyte expansion. They also exhibited reduced adiposity under both normal chow and high-fat diet (HFD) feeding conditions. Specific ablation of beige adipocytes reversed the protection against HFD-induced obesity in H4-TG mice. Taken together, our results directly demonstrate that beige adipocyte expansion regulates adiposity in mice and targeting beige adipocyte renaissance may present a novel strategy to tackle obesity 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".