Phytosterols as functional food ingredients: linkages to cardiovascular disease and cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it