GLP-1 Mediates Antiapoptotic Effect by Phosphorylating Bad through a β-Arrestin 1-mediated ERK1/2 Activation in Pancreatic β-Cells
Bibliographic record
Abstract
Strategies based on activating GLP-1 receptor (GLP-1R) are intensively developed for the treatment of type 2 diabetes. The exhaustive knowledge of the signaling pathways linked to activated GLP-1R within the beta-cells is of major importance. In beta-cells, GLP-1 activates the ERK1/2 cascade by diverse pathways dependent on either Galpha(s)/cAMP/cAMP-dependent protein kinase (PKA) or beta-arrestin 1, a scaffold protein. Using pharmacological inhibitors, beta-arrestin 1 small interfering RNA, and islets isolated from beta-arrestin 1 knock-out mice, we demonstrate that GLP-1 stimulates ERK1/2 by two temporally distinct pathways. The PKA-dependent pathway mediates rapid and transient ERK1/2 phosphorylation that leads to nuclear translocation of the activated kinases. In contrast, the beta-arrestin 1-dependent pathway produces a late ERK1/2 activity that is restricted to the beta-cell cytoplasm. We further observe that GLP-1 phosphorylates the cytoplasmic proapoptotic protein Bad at Ser-112 but not at Ser-155. We find that the beta-arrestin 1-dependent ERK1/2 activation engaged by GLP-1 mediates the Ser-112 phosphorylation of Bad, through p90RSK activation, allowing the association of Bad with the scaffold protein 14-3-3, leading to its inactivation. beta-Arrestin 1 is further found to mediate the antiapoptotic effect of GLP-1 in beta-cells through the ERK1/2-p90RSK-phosphorylation of Bad. This new regulatory mechanism engaged by activated GLP-1R involving a beta-arrestin 1-dependent spatiotemporal regulation of the ERK1/2-p90RSK activity is now suspected to participate in the protection of beta-cells against apoptosis. Such signaling mechanism may serve as a prototype to generate new therapeutic GLP-1R ligands.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".