DHA‐enriched high oleic canola oil diet may accelerate the cholesterol synthesis in humans.
Bibliographic record
Abstract
Circulating plant sterols are commonly used as surrogate biomarkers of cholesterol absorption, while desmosterol and lathosterol levels indicate cholesterol synthesis. To investigate the health benefits of various dietary oils varying n‐9/n‐6 fatty acid profiles on cholesterol trafficking using markers of cholesterol absorption and synthesis, a double‐blinded randomized crossover clinical trial consisting of five 30‐d periods was conducted. Diets included 60 g/d of canola oil (Canola, 59% OA, 20% LA, 10% ALA), high oleic canola oil (CanoalOleic, 72% OA, 15% LA), high oleic canola/DHA oil (CanolaDHA, 63% OA, 13% LA, 6% DHA), corn/safflower oil (CornSaff, 18% OA, 69% LA) and flax/safflower oil (FlaxSaff, 18% OA, 38% LA, 32% ALA). Total cholesterol and other sterol measures were determined using GC‐FID at endpoints. Results (n=54) showed that CanolaDHA feeding produced the highest serum total cholesterol levels (p<0.05) compared to other four treatments. No differences were observed in desmosterol levels across all diets. CanolaDHA also produced the highest lathosterol (p<0.0001) among all treatments with 27% more than the n‐6 control CornSaff. The sum of sitosterol and campesterol levels within three n‐9 rich diets, Canola, CanolaDHA, and CanolaOleic were higher (p<0.001) than two n‐6 rich diets by 27%, 34% and 20%, respectively. The data suggest that dietary DHA oil may accelerate cholesterol synthesis, resulting in high circulating cholesterol levels while n‐9 rich diets can elevate cholesterol absorption compared to n‐6 rich 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".