Cholesterol‐lowering effects of Northern wild rice in LDL receptor knockout mice
Bibliographic record
Abstract
We have recently reported that Northern wild rice produced in Manitoba, Canada possesses higher antioxidant properties as compared to conventional white rice. This observation plus other data from available literature suggest that Northern wild rice may have anti‐atherogenic properties. The objective of the current study was to investigate potential lipid‐modifying and anti‐atherogenic properties of Northern wild rice in LDL receptor knockout mice. Sixteen 4‐week male LDL receptor knockout mice were divided into two groups of 8 each. These experimental groups received a semi‐synthetic diet containing 0.06% (w/w) cholesterol; carbohydrates in this diet were replaced with Northern wild rice and used for the “treated group.” The experiment will be carried out for 24 weeks. Plasma total cholesterol and triglyceride levels were estimated at baseline and every four weeks using standard enzymatic kits. Body weight and estimated 24‐hour food consumption were recorded. These data are summarized in the following Table. Data suggest strong cholesterol‐lowering activities for Northern wild rice in this animal model. It is most likely that such reductions in total cholesterol levels will lead to significant reductions in atherogenesis by the end of the study. This study was supported by Agriculture Research and Development Initiative (ARDI), Winnipeg, Manitoba, Canada.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".