Evaluation of antidiabetic, antioxidant and antilipidemic potential of natural dietary product prepared from Cyphostemma digitatum in rats’ model of diabetes
Bibliographic record
Abstract
Introduction: Cyphostemma digitatum has a high content of antioxidant constituents and has been employed by the traditional healers and local people of Yemen for diabetes treatment. However, scientific evidence regarding its antidiabetic efficacy is largely unknown. Accordingly, the present study aimed to confirm the treatment effects of a dietary natural product prepared from Cyphostemma digitatum (PCD) in diabetic rats.Methods: Diabetes was induced by a high-fat diet and streptozotocin (HF-STZ). PCD (1 g/kg) was given by gavage administration once a day continuously for 30 days. At the end of treatment, blood and skeletal muscle samples were collected for further analysis.Results: The antidiabetic effects of PCD were demonstrated by significant reduction (P ≤ 0.05) in the levels of serum glucose (40%), triglyceride (32%), cholesterol (53%), low-density lipoprotein (LDL) (44%), malondialdehyde (MDA) (61%) in PCD treated groups compared to the diabetic control group. Additionally, PCD treatment significantly (P ≤ 0.05) restored the decreased levels of insulin (70%) and the activities of superoxide dismutase (SOD) (57%) and reduced glutathione (GSH) (544%) when compared to that of diabetic control rats. We found that treatment with PCD for 30 days fully restored the plasmalemmal glucose transporter type 4 (GLUT4) contents, as well as the phosphorylation of phosphatidylinositol 3-kinase (PI3K) (P ≤ 0.05).Conclusion: Thus, PCD treatment can be considered a potential drug candidate for 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".