Glucagon and Glucagon-Like Peptide Receptors as Drug Targets
Bibliographic record
Abstract
Glucagon and the glucagon-like peptides are derived from a common proglucagon precursor, and regulate energy homeostasis through interaction with a family of distinct G protein coupled receptors. Three proglucagon-derived peptides, glucagon, GLP-1, and GLP-2, play important roles in energy intake, absorption, and disposal, as elucidated through studies utilizing peptide antagonists and receptor knockout mice. The essential role of glucagon in the control of hepatic glucose production, taken together with data from studies employing glucagon antagonists, glucagon receptor antisense oligonucleotides, and glucagon receptor knockout mice, suggest that reducing glucagon action may be a useful strategy for the treatment of type 2 diabetes. GLP-1 secreted from gut endocrine cells controls glucose homeostasis through glucose-dependent enhancement of beta-cell function and reduction of glucagon secretion and gastric emptying. GLP-1 administration is also associated with reduction of food intake, prevention of weight gain, and expansion of beta-cell mass through stimulation of beta-cell proliferation, and prevention of apoptosis. GLP-1R agonists, as well as enzyme inhibitors that prevent GLP-1 degradation, are in late stage clinical trials for the treatment of type 2 diabetes. Exenatide (Exendin-4) has been approved for the treatment of type 2 diabetes in the United States in April 2005. GLP-2 promotes energy absorption, inhibits gastric acid secretion and gut motility, and preserves mucosal epithelial integrity through enhancement of crypt cell proliferation and reduction of epithelial apoptosis. A GLP-2R agonist is being evaluated in clinical trials for the treatment of inflammatory bowel disease and short bowel syndrome. Taken together, the separate receptors for glucagon, GLP-1, and GLP-2 represent important targets for developing novel therapeutic agents for the treatment of disorders of energy homeostasis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.006 | 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".