Antidiabetic Effect of Chinese yam (<i>Dioscorea opposita</i> Thunb.) in High‐Fat Diet/Streptozotocin‐Induced Diabetic Rats
Bibliographic record
Abstract
Abstract This study aims to assess the effect of different doses of Chinese yam (CY) on a high‐fat diet (HFD) and a streptozotocin‐induced diabetic rat model, using resistant starch (RS) as a positive control. Rats in the normal control and diabetes model (DM) groups are fed the standard diet and HFD, respectively. The RS and CY‐intervention groups are fed with a special HFD, in which starch, maltodextrin, and sucrose in the HFD are replaced completely with RS or CY powder in different proportions: 33.33% (1/3), 66.67% (2/3), and 100% respectively. The results show that CY powder can decrease serum levels of total triglycerides, total cholesterol, low‐density lipoprotein cholesterol, fasting blood glucose, and glycated hemoglobin, lower abdominal fat weight and abdominal fat index, increase levels of insulin and hepatic glycogen, and improve glucose tolerance and insulin sensitivity in diabetic rats. In addition, CY reduces oxidative stress and inflammation and reduces spleen weight and spleen index in diabetic rats. Notably, CY shows higher efficacy than RS in glucose tolerance and serum insulin and nitric oxide levels. This study suggests that CY powder may replace RS as a functional food in diabetic diets.
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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".