Overexpression of peroxisome proliferator‐activated receptor α in pancreatic β‐cells improves glucose tolerance in diet‐induced obese mice
Bibliographic record
Abstract
New findings What is the central question of this study? Does overexpression of peroxisome proliferator‐activated receptor α (PPARα) specifically in pancreatic β‐cells of diet‐induced obese mice preserve pancreatic β‐cell function and delay the onset of obesity‐induced diabetes? What is the main finding and its importance? This study reports the phenotype of the first in vivo model of β‐cell‐specific PPARα overexpression in a murine model of diet‐induced obesity. We show that pancreatic β‐cell‐specific overexpression of PPARα significantly improves glucose tolerance in diet‐induced obese mice. These results suggest that activation of β‐cell PPARα may be an appropriate target to preserve β‐cell function in obesity‐induced diabetes. Lipotoxicity is implicated in pancreatic β‐cell dysfunction in obesity‐induced type 2 diabetes. In vitro , activation of peroxisome proliferator‐activated receptor α (PPARα) has been shown to protect pancreatic β‐cells from the lipotoxic effects of palmitate, thereby preserving insulin secretion. Utilizing an adeno‐associated virus (dsAAV8), overexpression of PPARα was induced specifically in pancreatic β‐cells of adult, C57Bl/6 mice fed a high‐fat diet for 20 weeks and carbohydrate metabolism and β‐cell mass assessed. We show that overexpression of PPARα in pancreatic β‐cells in vivo preserves β‐cell function in obesity, and this improves glucose tolerance by preserving insulin secretion in comparison to control mice with diet‐induced obesity. No changes in β‐cell mass were observed in PPARα‐overexpressing mice compared with diet‐induced obese control animals. This model of β‐cell‐specific PPARα overexpression provides a useful in vivo model for elucidating the mechanisms underlying β‐cell lipotoxicity in obesity‐induced type 2 diabetes.
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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) | 0.001 | 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".