Targeting type 2 diabetes: lessons from a knockout model of insulin receptor substrate 2
Bibliographic record
Abstract
Insulin receptor substrate 2 (IRS2) is a widely expressed protein that regulates crucial biological processes including glucose metabolism, protein synthesis, and cell survival. IRS2 is part of the insulin - insulin-like growth factor (IGF) signaling pathway and mediates the activation of the phosphotidylinositol 3-kinase (PI3K)-Akt and the Ras-mitogen-activated protein kinase (MAPK) cascades in insulin target tissues and in the pancreas. The best evidence of this is that systemic elimination of the Irs2 in mice (Irs2(-/-)) recapitulates the pathogenesis of type 2 diabetes (T2D), in that diabetes arises as a consequence of combined insulin resistance and beta-cell failure. Indeed, work using this knockout mouse has confirmed the importance of IRS2 in the control of glucose homeostasis and especially in the survival and function of pancreatic beta-cells. These studies have shown that IRS2 is critically required for beta-cell compensation in conditions of increased insulin demand. Importantly, islets isolated from T2D patients exhibit reduced IRS2 expression, which supports the likely contribution of altered IRS2-dependent signaling to beta-cell failure in human T2D. For all these reasons, the Irs2(-/-) mouse has been and will be essential for elucidating the inter-relationship between beta-cell function and insulin resistance, as well as to delineate therapeutic strategies to protect beta-cells during T2D progression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".