Synthesis, secretion and biological actions of the glucagon-like peptides
Bibliographic record
Abstract
Glucagon-like peptides-1 and -2 (GLP-1 and GLP-2) are co-encoded along with glucagon in a single mammalian proglucagon gene that is expressed in islets and enteroendocrine L cells of the small and large intestine. Both peptides are liberated following cleavage by prohormone convertase 1/3 and secreted from the intestine following nutrient ingestion. A key determinant of GLP-1 and GLP-2 bioactivity is the enzyme dipeptidyl peptidase-IV, which inactivates both peptides by cleavage at the position-2 alanine. GLP-1 regulates blood glucose via actions on gastric emptying and islet hormones, including the regulation of insulin, glucagon, and somatostatin secretion. GLP-1 action is essential for beta-cell function, because the disruption of GLP-1 signaling results in reduced insulin secretion, decreased islet cyclic adenosine monophosphate, and abnormal intracellular calcium oscillations. GLP-1 also decreases appetite and induces satiety in human subjects, and inhibits food intake in rodents following intracerebroventricular administration. GLP-2 does not appear to directly regulate blood glucose, but contributes to nutrient assimilation via trophic effects on the intestinal mucosa. GLP-2 also decreases apoptosis in the crypts and villi, reduces intestinal epithelial permeability, and promotes intestinal glucose transport. The actions of GLP-1 and GLP-2 in experimental models of diabetes or intestinal injury, respectively, suggest that GLP-1 may be useful for the treatment of human diabetes, whereas GLP-2 may be of therapeutic benefit in patients with intestinal injury and compromised nutrient assimilation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".