Insulin Stimulates Primary β-Cell Proliferation via Raf-1 Kinase
Bibliographic record
Abstract
A relative decrease in beta-cell mass is key in the pathogenesis of type 1 diabetes, type 2 diabetes, and in the failure of transplanted islet grafts. It is now clear that beta-cell duplication plays a dominant role in the regulation of adult beta-cell mass. Therefore, knowledge of the endogenous regulators of beta-cell replication is critical for understanding the physiological control of beta-cell mass and for harnessing this process therapeutically. We have shown that concentrations of insulin known to exist in vivo act directly on beta-cells to promote survival. Whether insulin stimulates adult beta-cell proliferation remains unclear. We tested this hypothesis using dispersed primary mouse islet cells double labeled with 5-bromo-2-deoxyuridine and insulin antisera. Treating cells with 200-pm insulin significantly increased proliferation from a baseline rate of 0.15% per day. Elevating glucose from 5-15 mm did not significantly increase beta-cell replication. beta-Cell proliferation was inhibited by somatostatin as well as inhibitors of insulin signaling. Interestingly, inhibiting Raf-1 kinase blocked proliferation stimulated by low, but not high (superphysiological), insulin doses. Insulin-stimulated mouse insulinoma cell proliferation was dependent on both phosphatidylinositol 3-kinase/Akt and Raf-1/MAPK kinase pathways. Overexpression of Raf-1 was sufficient to increase proliferation in the absence of insulin, whereas a dominant-negative Raf-1 reduced proliferation in the presence of 200-pm insulin. Together, these results demonstrate for the first time that insulin, at levels that have been measured in vivo, can directly stimulate beta-cell proliferation and that Raf-1 kinase is involved in this process. These findings have significant implications for the understanding of the regulation of beta-cell mass in both the hyperinsulinemic and insulin-deficient states that occur in the various forms of diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 teacher head, 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".