Angelica dahurica Extracts Improve Glucose Tolerance through the Activation of GPR119
Bibliographic record
Abstract
G protein-coupled receptor (GPR) 119 is expressed in pancreatic β-cells and intestinal L cells, and is involved in glucose-stimulated insulin secretion and glucagon-like peptide-1 (GLP-1) release, respectively. Therefore, the development of GPR119 agonists is a potential treatment for type 2 diabetes. We screened 1500 natural plant extracts for GPR119 agonistic actions and investigated the most promising extract, that from Angelica dahurica (AD), for hypoglycemic actions in vitro and in vivo. Human GPR119 activation was measured in GeneBLAzer T-Rex GPR119-CRE-bla CHO-K1 cells; intracellular cAMP levels and insulin secretion were measured in INS-1 cells; and GLP-1 release was measured in GLUTag cells. Glucose tolerance tests and serum plasma insulin levels were measured in normal C57BL6 mice and diabetic db/db mice. AD extract-treated cells showed significant increases in GPR119 activation, intracellular cAMP levels, GLP-1 levels and glucose-stimulated insulin secretion as compared with controls. In normal mice, a single treatment with AD extract improved glucose tolerance and increased insulin secretion. Treatment with multiple doses of AD extract or n-hexane fraction improved glucose tolerance in diabetic db/db mice. Imperatorin, phellopterin and isoimperatorin were identified in the active fraction of AD extract. Among these, phellopterin activated GPR119 and increased active GLP-1 and insulin secretion in vitro and enhanced glucose tolerance in normal and db/db mice. We suggest that phellopterin might have a therapeutic potential for the treatment of type 2 diabetes.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".