β-cell dedifferentiation is associated with epithelial-mesenchymal transition triggered by miR-7-mediated repression of mSwi/Snf complex
Bibliographic record
Abstract
Abstract β-cell dedifferentiation has been revealed as a pathological mechanism underlying pancreatic dysfunction in diabetes. However, little is known on the genetic and epigenetic changes linked with the dedifferentiation of β-cells. We now report that β-cell dedifferentiation is associated with epithelial to mesenchymal transition (EMT) triggered by miR-7-mediated repression of Smarca4/Brg1 expression, a catalytic subunit of the mSwi/Snf chromatin remodeling complexes essential for β-cell transcription factors (β-TFs) activity. miR-7-mediated repression of Brg1 expression in diabetes causes an overall compaction of chromatin structure preventing β-TFs from accessing and transactivating genes maintaining the functional and epithelial identity of β-cells. Concomitantly, loss of β-cell identity impairs the ability of β-TFs Pdx1, Nkx6-1, Neurod1 to repress non-β-cell genes enriched selectively in mesenchymal cells leading to EMT, change in islet microenvironment, and fibrosis. Remarkably, anti-EMT agents normalized glucose tolerance of diabetic mice, thus revealing mesenchymal reprogramming of β-cells as a novel therapeutic target in diabetes. This study sheds light on the genetic signature of dedifferentiated β-cells and highlights how loss of mSwi/Snf activity in diabetes initiating a step-wise remodeling of epigenetic landscapes of β-cells leading to the induction of an EMT process reminiscent of a response to tissue injury.
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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".