Wild rice (<i>Zizania latifolia</i>(Griseb) Turcz) improves the serum lipid profile and antioxidant status of rats fed with a high fat/cholesterol diet
Bibliographic record
Abstract
The diet consumed by urban residents in modern China has become rich in saturated fats and cholesterol. In addition, the diet is high in carbohydrates from white rice and processed wheat starch. The aim of the present study was to determine the effects of replacing white rice and processed wheat starch with wild rice (WR) as the chief source of dietary carbohydrates. Rats fed with the diet patterned after the diet consumed by city residents of modern China showed elevated serum lipid levels comparable with rats consuming a high fat/cholesterol diet known to induce hyperlipidaemia in this species. Meanwhile, rats consuming the city diet with WR as the carbohydrate source suppressed the increase in serum TAG and total cholesterol, and the decrease in HDL cholesterol level. In addition, the rats fed the WR diet suppressed the build-up of oxidative stress by improving antioxidant capacity, increasing superoxide dismutase activity and reducing malondialdehyde concentration, both in the serum and liver. These findings illustrate that WR is effective in suppressing hyperlipidaemia and oxidative stress in rats even when the diet consumed is high in fat and cholesterol.
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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) | 0.000 | 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".