Metformin Reduces Oxidative Stress Status and Improves Plasma Insulin Level in Streptozotocin-Induced Diabetic Rats
Bibliographic record
Abstract
Background: Oxidative stress induced by hyperglycaemia plays a crucial role in the development of diabetic complications and metformin is commonly used in treating diabetes mellitus (DM). The aim of this study was to investigate whether metformin at the dose of 100 mg/kg/day could ameliorate oxidative stress and improve plasma insulin level in streptozotocin-induced diabetic rats.Methods: Twenty one rats (8-10 week old; weighing 190-220 g) were assigned into three groups (n=7 rats per group) i.e. non-DM, DM and DM+metformin (100 mg/kg/day metformin) groups. DM was induced using streptozotocin (60 mg/kg) intraperitoneally and treatments were given daily by oral gavage for four weeks. The levels of plasma biomarkers such as fasting blood glucose, oxidant-antioxidant markers and insulin levels were analysed.Results: Fasting blood glucose, malonyldehyde and protein carbonyls levels were significantly higher while insulin, total antioxidant capacity, catalase and glutathione peroxidase levels were significantly lower in DM group compared to non-DM group. The levels of fasting blood glucose, malonyldehyde and protein carbonyls were significantly lower while levels of total antioxidant capacity, catalase and insulin were significantly higher in DM+metformin group compared to DM group.Conclusion: This study may suggest that metformin at the dose of 100 mg/kg/day for 4 weeks reduces oxidative stress status and improves plasma insulin level in streptozotocin-induced diabetic rats possibly through its antihyperglycaemic action.
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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 | 0.001 |
| 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".