4E-BP2/SH2B1/IRS2 Are Part of a Novel Feedback Loop That Controls β-Cell Mass
Bibliographic record
Abstract
The mammalian target of rapamycin complex 1 (mTORC1) regulates several biological processes, although the key downstream mechanisms responsible for these effects are poorly defined. Using mice with deletion of eukaryotic translation initiation factor 4E-binding protein 2 (4E-BP2), we determine that this downstream target is a major regulator of glucose homeostasis and β-cell mass, proliferation, and survival by increasing insulin receptor substrate 2 (IRS2) levels and identify a novel feedback mechanism by which mTORC1 signaling increases IRS2 levels. In this feedback loop, we show that 4E-BP2 deletion induces translation of the adaptor protein SH2B1 and promotes the formation of a complex with IRS2 and Janus kinase 2, preventing IRS2 ubiquitination. The changes in IRS2 levels result in increases in cell cycle progression, cell survival, and β-cell mass by increasing Akt signaling and reducing p27 levels. Importantly, 4E-BP2 deletion confers resistance to cytokine treatment in vitro. Our data identify SH2B1 as a major regulator of IRS2 stability, demonstrate a novel feedback mechanism linking mTORC1 signaling with IRS2, and identify 4E-BP2 as a major regulator of proliferation and survival of 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) | 0.001 | 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".