Incretin-Based Therapy and the Quest for Sustained Improvements in β-Cell Health
Bibliographic record
Abstract
Incretin-based therapies, principally glucagon-like peptide-1 receptor (GLP-1R) agonists and dipeptidyl peptidase-4 (DPP-4) inhibitors, have slowly gained traction in the therapy of type 2 diabetes. DPP-4 inhibitors, which exert their activities through potentiation of endogenous GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) action (1), are well tolerated and may be combined with multiple oral agents, making them well suited for use at multiple stages in the treatment of type 2 diabetes. GLP-1R agonists require injection, and are less well tolerated due principally to gastrointestinal adverse events (nausea, and less commonly diarrhea and vomiting). Hence, like insulin, they are frequently considered for use in patients who have failed to achieve adequate glycemic control on one or more oral agents alone. However, long-acting GLP-1R agonists are more potent glucose-lowering agents compared with DPP-4 inhibitors (2), and they may produce weight loss, two major points of differentiation with meaningful clinical impact. As the field of incretin biology gained prominence after clinical observations describing the importance of gut-derived factors in the potentiation of glucose-dependent insulin secretion, it is not surprising that the β-cell continues to be viewed as the predominant target of incretin action. Indeed, both GLP-1 and GIP robustly potentiate glucose-dependent insulin secretion in nondiabetic human subjects, and GLP-1 restores or enhances β-cell glucose sensing and insulin secretion even in diabetic patients with considerable loss of β-cell responsivity to glucose or sulfonylureas. Both GLP-1 and GIP also exhibit robust proliferative and antiapoptotic actions on rodent β-cells in experimental models of type 2 diabetes (3), and GLP-1 exerts salutary effects on the molecular mechanisms underlying β-cell function and enhances β-cell survival in studies with human islets cultured ex vivo (4,5). Hence, there has been considerable anticipation that incretin-based therapies may exert “disease-modifying” effects in type 2 diabetes through a combination of mechanisms including enhancing …
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".