Pdgfrα deficiency in islet β-cells up-regulates apoptosis of beta-cells and disturbs glucose metabolism in B6 mice
Bibliographic record
Abstract
Introduction: Pancreatic β-cell dysfunction is a key contributor to the development of Type 2 Diabetes. The platelet-derived growth factor receptor α (PDGFRα) is known to play a crucial role in β-cell proliferation and expansion. However, its specific role in β-cell function and glucose metabolism remains unclear. This study aimed to investigate the effects of Pdgfrα deficiency on islet β-cell function and overall glucose metabolism. Methods: ) and assessed their metabolic function under both normal and high-fat diet conditions. Various parameters were measured, including body weight, body fat composition, glucose metabolism, insulin content, and β-cell apoptosis. Additionally, we conducted mechanistic analyses to understand the signaling pathways involved. Results: Pdgfrα-deficient mice exhibited significantly greater weight gain and increased body fat compared to controls. These mice also showed impaired glucose metabolism, reduced insulin content in β-cells, and increased β-cell apoptosis. Mechanistic studies revealed that Pdgfrα deletion led to suppression of Atf5 expression via downregulation of the PI3K pathway. This suppression resulted in enhanced β-cell apoptosis. Furthermore, Atf5 was found to regulate the expression of Gadd45b, Bcl2, and aminoacyl-tRNA synthetases, which are involved in insulin biosynthesis and glucose metabolism. Discussion: Our findings demonstrate that PDGFRα plays a critical role in maintaining β-cell function and glucose homeostasis. Loss of PDGFRα impairs β-cell survival and insulin production, likely through the PI3K-Atf5 axis. These insights suggest that targeting β-cell apoptotic pathways, particularly involving Atf5 and its downstream effectors, may offer promising avenues for the prevention and treatment of Type 2 Diabetes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".