Glucagon receptor antagonist upregulates circulating GLP-1 level by promoting intestinal L-cell proliferation and GLP-1 production in type 2 diabetes
Bibliographic record
Abstract
OBJECTIVE: Glucagon receptor (GCGR) blockage improves glycemic control and increases circulating glucagon-like peptide-1 (GLP-1) level in diabetic animals and humans. The elevated GLP-1 has been reported to be involved in the hypoglycemic effect of GCGR blockage. However, the source of this elevation remains to be clarified. RESEARCH DESIGN AND METHODS: mice and high-fat diet+streptozotocin (HFD/STZ)-induced type 2 diabetic (T2D) mice. Blood glucose, glucose tolerance and plasma GLP-1 were evaluated during the treatment. The gut length, epithelial area, and L-cell number and proliferation were detected after the mice were sacrificed. Cell proliferation and GLP-1 production were measured in mouse L-cell line GLUTag cells, and primary mouse and human enterocytes. Moreover, GLP-1 receptor (GLP-1R) antagonist or protein kinase A (PKA) inhibitor was used in GLUTag cells to determine the involved signaling pathways. RESULTS: and HFD/STZ-induced T2D mice. Besides, the treatment promoted L-cell proliferation and LK-cell expansion, and increased the gut length, epithelial area and L-cell number in these two T2D mice. Similarly, our in vitro study showed that the GCGR mAb promoted L-cell proliferation and increased GLP-1 production in GLUTag cells, and primary mouse and human enterocytes. Furthermore, either GLP-1R antagonist or PKA inhibitor diminished the effects of GCGR mAb on L-cell proliferation and GLP-1 production. CONCLUSIONS: The elevated circulating GLP-1 level by GCGR mAb is mainly due to intestinal L-cell proliferation and GLP-1 production, which may be mediated via GLP-1R/PKA signaling pathways. Therefore, GCGR mAb represents a promising strategy to improve glycemic control and restore the impaired GLP-1 production in T2D.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".