Development of Glucagon-Like Peptide-1-Based Pharmaceuticals as Therapeutic Agents for the Treatment of Diabetes
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) is released from gut endocrine cells following nutrient ingestion and acts to regulate nutrient assimilation via effects on gastrointestinal motility, islet hormone secretion, and islet cell proliferation. Exogenous administration of GLP-1 lowers blood glucose in normal rodents and in multiple experimental models of diabetes mellitus. Similarly, GLP-1 lowers blood glucose in normal subjects and in patients with type 2 diabetes. The therapeutic utility of the native GLP-1 molecule is limited by its rapid enzymatic degradation by the serine protease dipeptidyl peptidase IV. This review highlights recent advances in our understanding of GLP-1 physiology and GLP-1 receptor signaling, and summarizes current pharmaceutical strategies directed at sustained activation of GLP-1 receptor-dependent actions for glucoregulation in vivo. Given the nutrient-dependent control of GLP-1 release, neutraceuticals or modified diets that enhance GLP-1 release from the enteroendocrine cell may exhibit glucose-lowering properties in human subjects. The utility of GLP-1 derivatives engineered for sustained action and/or DP IV-resistance, and the biological activity of naturally occurring GLP-1-related molecules such as exendin-4 is reviewed. Circumventing DP IV-mediated incretin degradation via inhibitors that target the DP IV enzyme represents a complementary strategy for enhancing GLP-1-mediated actions in vivo. Finally, the current status of alternative GLP-1-delivery systems via the buccal and enteral mucosa is briefly summarized. The findings that the potent glucose-lowering properties of GLP-1 are preserved in diabetic subjects, taken together with the potential for GLP-1 therapy to preserve or augment beta cell mass, provides a powerful impetus for development of GLP-1-based human pharmaceuticals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".