MEK/ERK Signaling in β-Cells Bifunctionally Regulates β-Cell Mass and Glucose-Stimulated Insulin Secretion Response to Maintain Glucose Homeostasis
Bibliographic record
Abstract
In diabetic pathology, insufficiency in β-cell mass, unable to meet peripheral insulin demand, and functional defects of individual β-cells in production of insulin are often concurrently observed, collectively causing hyperglycemia. Here we show that the phosphorylation of ERK1/2 is significantly decreased in the islets of db/db mice as well as in those of a cohort of subjects with type 2 diabetes. In mice with abrogation of ERK signaling in pancreatic β-cells through deletion of Mek1 and Mek2, glucose intolerance aggravates under high-fat diet–feeding conditions due to insufficient insulin production with lower β-cell proliferation and reduced β-cell mass, while in individual β-cells dampening of the number of insulin exocytosis events is observed, with the molecules involved in insulin exocytosis being less phosphorylated. These data reveal bifunctional roles for MEK/ERK signaling in β-cells for glucose homeostasis, i.e., in regulating β-cell mass as well as in controlling insulin exocytosis in individual β-cells, thus providing not only a novel perspective for the understanding of diabetes pathophysiology but also a potential clue for new drug development for diabetes treatment.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".