The Glucagon-Like Peptide-1 Receptor Agonist Oxyntomodulin Enhances β-Cell Function but Does Not Inhibit Gastric Emptying in Mice
Bibliographic record
Abstract
The proglucagon gene gives rise to multiple peptides that play diverse roles in the control of energy intake, gut motility, and nutrient disposal. Glucagon-like peptide-1 (GLP-1), a 30-amino-acid peptide regulates glucose homeostasis via control of insulin and glucagon secretion and by inhibition of gastric emptying and food intake. Oxyntomodulin (OXM) a 37-amino-acid peptide also derived from the proglucagon gene, binds to both the glucagon and GLP-1 receptor (GLP-1R); however, a separate OXM receptor has not yet been identified. Here we show that OXM, like other GLP-1R agonists, stimulates cAMP formation and lowers blood glucose after both oral and ip glucose administration, actions that require a functional GLP-1R. OXM also directly stimulates insulin secretion from murine islets and INS-1 cells in a glucose- and GLP-1R-dependent manner. Moreover, OXM ameliorates hyperglycemia and significantly reduces apoptosis in murine beta-cells after streptozotocin administration and directly reduces apoptosis in thapsigargin-treated INS-1 cells. Unexpectedly, OXM, but not the GLP-1R agonist exendin-4, increased plasma levels of insulin after oral glucose administration. Moreover, OXM administered at doses that potently lower blood glucose had no effect on inhibition of gastric emptying but reduced food intake in WT mice. Taken together, these findings illustrate that although structurally distinct proglucagon-derived peptides such as GLP-1 and OXM engage the GLP-1R, OXM mimics some but not all of the actions of GLP-1R agonists in vivo. These findings may have implications for therapeutic efforts using OXM as a long-acting GLP-1R agonist for the treatment of metabolic disorders.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".