Improvement of Glucose Tolerance and Hepatic Insulin Sensitivity by Oligofructose Requires a Functional Glucagon-Like Peptide 1 Receptor
Bibliographic record
Abstract
Nondigestible fermentable dietary fibers such as oligofructose (OFS) exert an antidiabetic effect and increase the secretion of glucagon-like peptide 1 (GLP-1). To determine the importance of GLP-1 receptor-dependent mechanisms for the actions of OFS, we studied high-fat-fed diabetic mice treated with OFS for 4 weeks in the presence or absence of the GLP-1 receptor antagonist exendin 9-39 (Ex-9). OFS improved glucose tolerance, fasting blood glucose, glucose-stimulated insulin secretion, and insulin-sensitive hepatic glucose production and reduced body weight gain. Ex-9 totally prevented the beneficial effects of OFS. Furthermore, GLP-1 receptor knockout mice (GLP-1R(-/-)) were completely insensitive to the antidiabetic actions of OFS. At the molecular level, the effects of OFS on endogenous glucose production correlated with changes of hepatic IRS (insulin receptor substrate)-2 and Akt phosphorylation in an Ex-9-dependent manner. As inflammation is associated with diabetes and obesity, we quantified nuclear factor-kappaB and inhibitor of kappaB kinase beta in the liver. The activity of both intracellular inflammatory effectors was reduced by OFS but, importantly, this effect could not be reverted by Ex-9. In summary, our data show that the antidiabetic actions of OFS require a functional GLP-1 receptor. These findings highlight the therapeutic potential of enhancing endogenous GLP-1 secretion 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) | 0.001 | 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".