Antagonistic interaction between Nodal and insulin modulates pancreatic β-cell proliferation and survival
Bibliographic record
Abstract
BACKGROUND: Insulin signaling pathway in β-cell is essential to promote β-cells proliferation and survival, while Nodal-ALK7-Smad3 signaling involves β-cells apoptosis. We attempted to address inter-relationship between Nodal and insulin in modulating β-cell proliferation and apoptosis. METHODS: Using INS-1 β-cells and isolated rat islets, we examined the effects of Nodal, insulin, or the two combined on β-cell proliferation and/or apoptosis. RESULTS: The β-cells under high-glucose or palmitate conditions showed significant up-regulation of Nodal expression and activation of its downstream signaling pathway resulted in increased cleaved caspase-3. Insulin treatment led to significantly attenuated Nodal-induced cell apoptotic pathway. Similar results were found in directly Nodal-treated β-cell that insulin could partially block Nodal-induced up-regulation of ALK7-Smad3-caspase-3 signaling pathways with significantly attenuated β-cell apoptosis. Interestingly, we found that insulin-induced Akt activation and downstream molecules including GSK-3β, β-catenin and ERK1/2 was significantly attenuated by the co-treatment with Nodal, resulted in decreased cell proliferation. Furthermore, Nodal decreased glucose-evoked calcium influx and played a negative role during glucose-stimulated insulin secretion in the β-cells. Immunocytochemistry studies showed that Nodal treatment translocated Smad3 from cytosol mostly to the nucleus; however, co-treatment with insulin significantly decreased Smad3 nuclear localization. Co-immunoprecipitation experiments showed a directly interaction between Smad3 and Akt, and this interaction was enhanced by co-treatment with insulin. CONCLUSIONS: Our data suggest that the antagonistic interaction between Nodal and insulin has a role in the regulation of β-cell mass and secretion.
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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 | 0.000 |
| 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".