The Role of AEBP1 in Sex-Specific Diet-Induced Obesity
Bibliographic record
Abstract
Obesity is an important risk factor for heart disease, diabetes, and certain cancers, but the molecular basis for obesity is poorly understood. The transcriptional repressor AEBP1, which functions as a negative regulator of PTEN through a protein-protein interaction, is highly expressed in the stromal compartment of adipose tissues, including proliferative preadipocytes, and its expression is abolished in terminally differentiated, nonproliferative adipocytes. Here we show that transgenic overexpression of AEBP1 during adipogenesis coupled with a high-fat diet (HFD) resulted in massive obesity in female transgenic (AEBP1(TG)) mice via adipocyte hyperplasia. AEBP1 levels dynamically changed with aging, and HFD induced AEBP1 expression in females. Thus, HFD-fed AEBP1(TG) females display hyperinduction of AEBP1 and a marked reduction of PTEN level with concomitant hyperactivation of the survival signal in white adipose tissue. Our results suggest that AEBP1 plays a key functional role in in vivo modulation of adiposity via fat-cell proliferation and is involved in a sex-specific susceptibility to diet-induced obesity by the estrogen signaling pathway.
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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".