Definition of a Skp2-c-Myc Pathway to Expand Human Beta-cells
Bibliographic record
Abstract
Type 2 diabetes (T2D) is characterized by insulin resistance and reduced functional β-cell mass. Developmental differences, failure of adaptive expansion and loss of β-cells via β-cell death or de-differentiation have emerged as the possible causes of this reduced β-cell mass. We hypothesized that the proliferative response to mitogens of human β-cells from T2D donors is reduced, and that this might contribute to the development and progression of T2D. Here, we demonstrate that the proliferative response of human β-cells from T2D donors in response to cdk6 and cyclin D3 is indeed dramatically impaired. We show that this is accompanied by increased nuclear abundance of the cell cycle inhibitor, p27(kip1). Increasing nuclear abundance of p27(kip1) by adenoviral delivery decreases the proliferative response of β-cells from non-diabetic donors, mimicking T2D β-cells. However, while both p27(kip1) gene silencing and downregulation by Skp2 overexpression increased similarly the proliferative response of human β-cells, only Skp2 was capable of inducing a significant human β-cell expansion. Skp2 was also able to double the proliferative response of T2D β-cells. These studies define c-Myc as a central Skp2 target for the induction of cell cycle entry, expansion and regeneration of human T2D β-cells.
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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) | 0.002 | 0.001 |
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".