Influence of mulberry leaf extract on serum adiponectin, visfatin and lipid profile levels in type 2 diabetic rats
Bibliographic record
Abstract
The effect of ethanolic mulberry leaf extract (MLE) and mulberry leaf powder (MLP) on glycemic control, serum adiponectin, visfatin and lipid profile in type2 diabetic rats have been investigated. 30 male wistar rats randomly divided into 5 groups. One group was randomly assigned as control (I) and diabetes was induced in others by administration of streptozotocin (STZ) (55 mg/kg body weight) 15 minutes after the administration of nicotinamide (110 mg/kg body weight) intraperitoneally. Finally, fasting blood glucose (FBG), lipid profile, adiponectin and visfatin were assessed after 6 weeks. Lipid profiles including serum FBG, total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL) and visfatin significantly decreased and high-density lipoprotein cholesterol (HDL-c) and adiponectin increased in the two groups of treated diabetic rats in comparison to the diabetic control (p<0.05). For all the investigated factors, there was no significant difference between two treatment methods. However, MLP was more effective than MLE in improving visfatin. Results showed that MLE and MLP possess hypoglycemic and hypolipidemic activities and play an important role in regulating the secretion of adipokines such as adiponectin and visfatin.
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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 | 0.000 |
| 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 | 0.001 |
| 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".