Pancreatic β‐cell Raf‐1 is required for glucose tolerance, insulin secretion, and <i>insulin 2</i> transcription
Bibliographic record
Abstract
Regulation of glucose homeostasis by insulin depends on pancreatic β-cell growth, survival, and function. Raf-1 kinase is a major downstream target of several growth factors that promote proliferation and survival of many cell types, including the pancreatic β cells. We have previously reported that insulin protects β cells from apoptosis and promotes proliferation by activating Raf-1 signaling in cultured human islets, mouse islets, and MIN6 cells. As Raf-1 activity is critical for basal apoptosis and insulin secretion in vitro, we hypothesized that Raf-1 may play an important role in glucose homeostasis in vivo. To test this hypothesis, we utilized the Cre-loxP recombination system to obtain a pancreatic β-cell-specific ablation of Raf-1 kinase gene (RIPCre(+/+):Raf-1(flox/flox)) and a complete set of littermate controls (RIPCre(+/+):Raf-1(wt/wt)). RIPCre(+/+):Raf-1(flox/flox) mice were viable, and no effects on weight gain were observed. RIPCre(+/+):Raf-1(flox/flox) mice had increased fasting blood glucose levels and impaired glucose tolerance but normal insulin tolerance compared to littermate controls. Insulin secretion in vivo and in isolated islets was markedly impaired, but there was no apparent effect on the exocytosis machinery. However, islet insulin protein and insulin 2 mRNA, but not insulin 1 mRNA, were dramatically reduced in Raf-1-knockout mice. Analysis of insulin 2 knockout mice demonstrated that this reduction in mRNA was sufficient to impair in vivo insulin secretion. Our data further indicate that Raf-1 specifically and acutely regulates insulin 2 mRNA via negative action on Foxo1, which has been shown to selectively control the insulin 2 gene. This work provides the first direct evidence that Raf-1 signaling is essential for the regulation of basal insulin transcription and the supply of releasable insulin in vivo.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".