Vulgarin, a Sesquiterpene Lactone from Artemisia judaica, Improves the Antidiabetic Effectiveness of Glibenclamide in Streptozotocin-Induced Diabetic Rats via Modulation of PEPCK and G6Pase Genes Expression
Bibliographic record
Abstract
), on the antidiabetic potential of glibenclamide (GLB) using streptozotocin (STZ) to induce diabetes. Seven groups of rats were used in the study; the first group received the vehicle and served as normal control. The diabetic rats of the second to the fifth groups were treated with the vehicle (negative control), GLB at 5 mg/kg (positive control), VGN at 10 mg/kg (VGN-10) and VGN at 20 mg/kg (VGN-20), respectively. The diabetic rats of the sixth and seventh groups were administered combinations of GLB plus VGN-10 and GLB plus VGN-20, respectively. The diabetic rats treated with GLB plus VGN-20 combination showed marked improvement in the fasting blood glucose (FBG), insulin and glycated hemoglobin (HbA1c), as well as the lipid profile, compared with those treated with GLB alone. Further, the pancreatic tissues of the diabetic rats that received the GLB+VGN-20 combination showed superior improvements in lipid peroxidation and antioxidant parameters than those of GLB monotherapy. The insulin content of the β-cells was restored in all treatments, while the levels of glucagon and somatostatin of the α- and δ-endocrine cells were reduced in the pancreatic islets. In addition, the concurrent administration of GLB+VGN-20 was the most effective in restoring PEPCK and G6Pase mRNA expression in the liver. In conclusion, the results demonstrated that the GLB+VGN-20 combination led to greater glycemic improvement in diabetic rats compared with GLB monotherapy through its antioxidant effect and capability to modulate PEPCK and G6Pase gene expression in their livers.
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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 | 0.001 | 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) | 0.000 | 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".