Musashi expression in β-cells coordinates insulin expression, apoptosis and proliferation in response to endoplasmic reticulum stress in diabetes
Bibliographic record
Abstract
Diabetes is associated with the death and dysfunction of insulin-producing pancreatic β-cells. In other systems, Musashi genes regulate cell fate via Notch signaling, which we recently showed regulates β-cell survival. Here we show for the first time that human and mouse adult islet cells express mRNA and protein of both Musashi isoforms, as well Numb/Notch/Hes/neurogenin-3 pathway components. Musashi expression was observed in insulin/glucagon double-positive cells during human fetal development and increased during directed differentiation of human embryonic stem cells (hESCs) to the pancreatic lineage. De-differentiation of β-cells with activin A increased Msi1 expression. Endoplasmic reticulum (ER) stress increased Msi2 and Hes1, while it decreased Ins1 and Ins2 expression, revealing a molecular link between ER stress and β-cell dedifferentiation in type 2 diabetes. These effects were independent of changes in Numb protein levels and Notch activation. Overexpression of MSI1 was sufficient to increase Hes1, stimulate proliferation, inhibit apoptosis and reduce insulin expression, whereas Msi1 knockdown had the converse effects on proliferation and insulin expression. Overexpression of MSI2 resulted in a decrease in MSI1 expression. Taken together, these results demonstrate overlapping, but distinct roles for Musashi-1 and Musashi-2 in the control of insulin expression and β-cell proliferation. Our data also suggest that Musashi is a novel link between ER stress and the compensatory β-cell proliferation and the loss of β-cell gene expression seen in specific phases of the progression to type 2 diabetes.
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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".