Hypoglycaemic effect of catalpol in a mouse model of high-fat diet-induced prediabetes
Bibliographic record
Abstract
Type 2 diabetes mellitus is a major health problem and a societal burden. Individuals with prediabetes are at increased risk of type 2 diabetes mellitus. Catalpol, an iridoid glycoside, has been reported to exert a hypoglycaemic effect in db/db mice, but its effect on the progression of prediabetes is unclear. In this study, we established a mouse model of prediabetes and examined the hypoglycaemic effect, and the mechanism of any such effect, of catalpol. Catalpol (200 mg/(kg·day)) had no effect on glucose tolerance or the serum lipid level in a mouse model of impaired glucose tolerance-stage prediabetes. However, catalpol (200 mg/(kg·day)) increased insulin sensitivity and decreased the fasting glucose level in a mouse model of impaired fasting glucose/impaired glucose tolerance-stage prediabetes. Moreover, catalpol increased the mitochondrial membrane potential (1.52-fold) and adenosine triphosphate content (1.87-fold) in skeletal muscle and improved skeletal muscle function. These effects were mediated by activation of the insulin receptor-1/glucose transporter type 4 (IRS-1/GLUT4) signalling pathway in skeletal muscle. Our findings will facilitate the development of a novel approach to suppressing the progression of diabetes at an early stage. Novelty Catalpol prevents the progression of prediabetes in a mouse model of prediabetes. Catalpol improves insulin sensitivity in skeletal muscle. The effects of catalpol are mediated by activation of the IRS-1/GLUT4 signalling pathway.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| 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".