High Fat Diet Triggers a Reduction in Body Fat Mass in Female Mice Deficient for Utx demethylase
Bibliographic record
Abstract
Obesity increases the risk of metabolic disorders like diabetes mellitus and dyslipidemia. However, how metabolic status is sensed and regulates cellular behavior is unclear. Utx is an H3K27 demethylase that influences adipocyte function in vitro. To examine its role in vivo, we generated mice lacking Utx in adipocytes (UtxAKO). Although all UtxAKO mice grew normally on a normal chow diet (NCD), female UtxAKO mice on a high fat diet (HFD) showed striking reductions in body fat compared to control mice (Ctrl). Gene expression profiling of adipose tissues of HFD-fed UtxAKO female mice revealed decreased expression of rate-limiting enzymes of triacylglycerol synthesis but increased expression of those of cholesterol/steroid hormone synthesis. Moreover, these animals resisted adiposity induced by ovariectomy and exhibited increased estrogen in visceral adipose tissues. Thus, upon HFD feeding, Utx regulates lipid metabolism in adipose tissues by influencing the local hormonal microenvironment. Conversely, Utx deficiency skews lipid catabolism to enhance cholesterol/steroid hormone production and repress obesity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".