Leptin Deficiency Unmasks the Deleterious Effects of Impaired Peroxisome Proliferator–Activated Receptor γ Function (P465L PPARγ) in Mice
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor (PPAR)gamma is a key transcription factor facilitating fat deposition in adipose tissue through its proadipogenic and lipogenic actions. Human patients with dominant-negative mutations in PPARgamma display lipodystrophy and extreme insulin resistance. For this reason it was completely unexpected that mice harboring an equivalent mutation (P465L) in PPARgamma developed normal amounts of adipose tissue and were insulin sensitive. This finding raised important doubts about the interspecies translatability of PPARgamma-related findings, bringing into question the relevance of other PPARgamma murine models. Here, we demonstrate that when expressed on a hyperphagic ob/ob background, the P465L PPARgamma mutant grossly exacerbates the insulin resistance and metabolic disturbances associated with leptin deficiency, yet reduces whole-body adiposity and adipocyte size. In mouse, coexistence of the P465L PPARgamma mutation and the leptin-deficient state creates a mismatch between insufficient adipose tissue expandability and excessive energy availability, unmasking the deleterious effects of PPARgamma mutations on carbohydrate metabolism and replicating the characteristic clinical symptoms observed in human patients with dominant-negative PPARgamma mutations. Thus, adipose tissue expandability is identified as an important factor for the development of insulin resistance in the context of positive energy balance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".