Glucagon-Like Peptide-2 Activates β-Catenin Signaling in the Mouse Intestinal Crypt: Role of Insulin-Like Growth Factor-I
Bibliographic record
Abstract
Chronic administration of glucagon-like peptide-2 (GLP-2) induces intestinal growth and crypt cell proliferation through an indirect mechanism requiring IGF-I. However, the intracellular pathways through which IGF-I mediates GLP-2-induced epithelial tropic signaling remain undefined. Because beta-catenin and Akt are important regulators of crypt cell proliferation, we hypothesized that GLP-2 activates these signaling pathways through an IGF-I-dependent mechanism. In this study, fasted mice were administered Gly(2)-GLP-2 or LR(3)-IGF-I (positive control) for 0.5-4 h. Nuclear translocation of beta-catenin in non-Paneth crypt cells was assessed by immunohistochemistry and expression of its downstream proliferative markers, c-myc and Sox9, by quantitative RT-PCR. Akt phosphorylation and activation of its targets, glycogen synthase kinase-3beta and caspase-3, were determined by Western blot. IGF-I receptor (IGF-IR) and IGF-I signaling were blocked by preadministration of NVP-AEW541 and through the use of IGF-I knockout mice, respectively. We found that GLP-2 increased beta-catenin nuclear translocation in non-Paneth crypt cells by 72 +/- 17% (P < 0.05) and increased mucosal c-myc and Sox9 mRNA expression by 90 +/- 20 and 376 +/- 170%, respectively (P < 0.05-0.01), with similar results observed with IGF-I. This effect of GLP-2 was prevented by blocking the IGF-IR as well as ablation of IGF-I signaling. GLP-2 also produced a time- and dose-dependent activation of Akt in the intestinal mucosa (P < 0.01), most notably in the epithelium. This action was reduced by IGF-IR inhibition but not IGF-I knockout. We concluded that acute administration of GLP-2 activates beta-catenin and proliferative signaling in non-Paneth murine intestinal crypt cells as well as Akt signaling in the mucosa. However, IGF-I is required only for the GLP-2-induced alterations in beta-catenin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".