Acute Insulin Signaling in Pancreatic Beta-Cells Is Mediated by Multiple Raf-1 Dependent Pathways
Bibliographic record
Abstract
Insulin enhances the proliferation and survival of pancreatic beta-cells, but its mechanisms remain unclear. We hypothesized that Raf-1, a kinase upstream of both ERK and Bad, might be a critical target of insulin in beta-cells. To test this hypothesis, we treated human and mouse islets as well as MIN6 beta-cells with multiple insulin concentrations and examined putative downstream targets using immunoblotting, immunoprecipitation, quantitative fluorescent imaging, and cell death assays. Low doses of insulin rapidly activated Raf-1 by dephosphorylating serine 259 and phosphorylating serine 338 in human islets, mouse islets, and MIN6 cells. The phosphorylation of ERK by insulin was eliminated by exposure to a Raf inhibitor (GW5074) or transfection with a dominant-negative Raf-1 mutant. Insulin also enhanced the interaction between mitochondrial Raf-1 and Bcl-2 agonist of cell death (Bad), promoting Bad inactivation via its phosphorylation on serine 112. Insulin-stimulated ERK phosphorylation was abrogated by calcium chelation, calcineurin and calmodulin-dependent protein kinase II inhibitors, and Ned-19, a nicotinic acid adenine dinucleotide phosphate receptor (NAADPR) antagonist. Blocking Raf-1 and Ca(2+) signaling resulted in nonadditive beta-cell death. Autocrine insulin signaling partly accounted for the effects of glucose on ERK phosphorylation. Our results demonstrate that Raf-1 is a critical target of insulin in primary beta-cells. Activation of Raf-1 leads to both an ERK-dependent pathway that involves nicotinic acid adenine dinucleotide phosphate-sensitive Ca(2+) stores and Ca(2+)-dependent phosphorylation events, and an ERK-independent pathway that involves Bad inactivation at the mitochondria. Together our findings identify a novel insulin signaling pathway in beta-cells and shed light on insulin's antiapoptotic and mitogenic mechanisms.
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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) | 0.002 | 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".