Control of pancreatic β-cell fate by insulin signaling: The sweet spot hypothesis
Bibliographic record
Abstract
Diabetes results from an absolute or relative deficiency in functional pancreatic beta-cell mass. Over the past few years, there has been renewed interest in the role of insulin itself in the regulation of beta-cell fate. Numerous animal models point to a critical role for beta-cell insulin signaling in the survival and proliferation of pancreatic beta-cells. In the present article, we review new studies that elucidate the mechanism by which insulin exerts anti-apoptotic and pro-mitogenic effects on beta-cells. In particular, we highlight the emerging role for Raf-1 kinase in autocrine insulin signaling and beta-cell fate decisions. We also discuss provocative evidence that the relationship between the dose of insulin and the birth and death of beta-cells is not linear. We propose a new hypothesis based on these findings, called the 'sweet spot' hypothesis, that can explain how both upward and downward deviations from normal levels of autocrine/paracrine insulin signaling might play an important role in the pathogenesis of type 1 diabetes and type 2 diabetes. We also highlight the key experiments that are required to further test this hypothesis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".