Phytosterols as functional food ingredients: linkages to cardiovascular disease and cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: To examine experimental evidence that has examined association of phytosterols and the reduction of the risk of cardiovascular disease and cancer. RECENT FINDINGS: Phytosterols exist as naturally occurring plant sterols that are present in the nonsaponifiable fraction of plant oils. Phytosterols are plant components that have a chemical structure similar to cholesterol except for the addition of an extra methyl or ethyl group; however, phytosterol absorption in humans is considerably less than that of cholesterol. In fact, phytosterols reduce cholesterol absorption, although the exact mechanism is not known, and thus reduce circulating levels of cholesterol. The efficacy of phytosterols as cholesterol-lowering agents have been shown when incorporated into fat spreads as well as other food matrices. In addition, phytosterols have been combined with other beneficial dietary components including fish and olive oils, psyllium and beta-glucan to enhance their effect on risk factors of cardiovascular disease. Phytosterols appear not only to play an important role in the regulation of cardiovascular disease but also to exhibit anticancer properties. A side effect associated with the consumption of phytosterols is that they reduce the blood levels of carotenoid. Nevertheless, it has been suggested that compensation for this impact on serum carotenoid levels can occur either by increasing the intake of carotenoid-rich foods or by taking supplements containing these carotenoids. SUMMARY: Dietary phytosterols appear to play an important role in the regulation of serum cholesterol and to exhibit anticancer properties.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".