Reg2 Expression Is Required for Pancreatic Islet Compensation in Response to Aging and High-Fat Diet–Induced Obesity
Bibliographic record
Abstract
Maintaining pancreatic β-cell mass and function is essential for normal insulin production and glucose homeostasis. Regenerating islet-derived 2 (Reg2, Reg II, human ortholog Reg1B) gene is normally expressed in pancreatic acinar cells and is significantly induced in response to diabetes, pancreatitis, and high-fat diet (HFD) and during pancreatic regeneration. To evaluate the role of endogenous Reg2 production in normal β-cell function, we characterized Reg2 gene-deficient (Reg2-/-) mice under normal conditions and when subjected to several pathological challenges. At a young age, Reg2 gene deficiency caused no obvious change in normal islet morphology or glucose tolerance. There was no change in the severity of streptozotocin-induced diabetes or caerulein-induced acute pancreatitis in the Reg2-/- mice, indicating that the increased Reg2 expression under those conditions was not essential to protect the islet or acinar cells. However, 13- to 14-month-old Reg2-/- mice developed glucose intolerance associated with significantly decreased islet β-cell ratio and serum insulin level. Similarly, after young mice were fed an HFD for 19 weeks, diminished islet mass expansion and serum insulin level were observed in Reg2-/- vs wild-type mice. This was associated with a decline in the rate of individual β-cell proliferation measured by Ki67 labeling. In both conditions, the β-cells were smaller in gene-deficient vs wild-type mice. Our results indicate that normal expression of Reg2 gene is required for appropriate compensations in pancreatic islet proliferation and expansion in response to obesity and aging.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".