Glucagon-Like Peptide-2 Receptor Activation in the Rat Intestinal Mucosa
Bibliographic record
Abstract
Glucagon-like peptide-2 (GLP-2) increases small intestinal growth and function in rodents and human subjects. GLP-2 exerts its effects through a seven-transmembrane domain, G protein-coupled receptor (GLP-2R), stimulating cAMP generation and activating protein kinase A signaling in heterologous cell lines transfected with the GLP-2R. As intestinal cell lines expressing the GLP-2R have not been identified, we developed methods for studying GLP-2R signaling in the rat small intestinal mucosa in vitro. Isolated rat intestinal mucosal cells expressed mRNA transcripts for the GLP-2R, as well as for chromogranin A and beta-tubulin III, markers for enteroendocrine and neural cells, respectively. cAMP production in response to [Gly2]GLP-2, a degradation-resistant analog of GLP-2, was maximal at 10-11 m (268 +/- 93% of control, P < 0.001), with reduced cAMP accumulation observed at higher doses. The cAMP response was diminished by pretreatment with 10-9 m GLP-2, and was abolished by pretreatment with 10-6 m GLP-2 (P < 0.05), indicating receptor desensitization. GLP-2 treatment of isolated mucosal cells increased 3H-thymidine incorporation (to 128 +/- 8% of controls, P < 0.05), and this was prevented by inhibition of the protein kinase A pathway with H89. In contrast, GLP-2 did not affect p44/p42 MAPK phosphorylation or the levels of cytosolic calcium in the mucosal cell preparation. These results provide the first evidence that activation of the endogenous rat mucosal GLP-2 receptor is linked to activation of a cAMP/protein kinase A-dependent, growth-promoting pathway in vitro.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".