Secoisolariciresinol Diglucoside (SDG) from flaxseed in the prevention and treatment of diabetes mellitus
Bibliographic record
Abstract
This review focuses on the role of reactive oxygen species (ROS) on the development of type 1 and type 2 diabetes and its treatment with secoisolariciresinol diglucoside (SDG) isolated from flaxseed which is an antioxidant and suppresses phosphoenolpyruvate carboxykinase (PEPCK) gene expression, a ratelimiting enzyme in the gluconeogenesis in the liver. Role of ROS in the development of type 1 diabetes [diabetic prone Bio Breeding (BBdp) rats and streptozotocin-induced diabetic (STZ) rats and type 2 diabetes (Zucker diabetic fatty female rats, ZDF rats)] has been discussed. Oxidative stress has been assessed by measuring serum and pancreatic malondialdehyde (MDA), pancreatic chemiluminescence (pancreatic-CL) and oxygen radical producing activity of white blood cells (WBCCL). Diagnosis of diabetes was made by hyperglycaemia and glucosuria. Incidence of diabetes was 100 % in SDZ rats, 72 % in BBdp rats and 100 % in ZDF rats by the age of 72 days. Development of diabetes was associated with increases in the serum and pancreatic MDA, WBC-CL and pancreatic-CL and glycated haemoglobin (HbA1 c). SDG prevented the development of diabetes by 75 % in STZ rats, by 71 % in BBdp rats and by 20 % at 72 days of age in ZDF rats. However, 80 % of the rats which did not develop diabetes by 72 days of age, developed diabetes later on, suggesting that SDG treatment delays the development of diabetes in ZDF rats. Treatment with SDG decreased the levels of serum and pancreatic MDA, WBC-CL and pancreatic-CL. In conclusion, development of type 1 and type 2 diabetes is mediated through oxidative stress and the prevention or delay in the development of diabetes with SDG could be due to its antioxidant activity and its suppressant effect on PEPCK enzyme. Lignan complex which contains 34 % to 38 % of SDG is effective in lowering serum glucose and HbA1 c in type 2 diabetes in humans.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".