Plasma Concentrations of Plant Sterols: Physiology and Relationship with Coronary Heart Disease
Bibliographic record
Abstract
Recently, it has been questioned whether elevated levels of circulating plant sterols increase the risk of coronary heart disease (CHD). To date, no definitive conclusions regarding such a relationship have been reached, nor have there been any studies summarizing the factors that contribute to the observed elevations in plant sterol concentrations in plasma. Thus, the purpose of this review is to systematically compare the plant sterol levels of subjects from the general population and to describe factors that contribute to the variations observed. The question of whether elevated plasma concentrations of plant sterols are associated with an increased risk of CHD was also assessed. Results indicate that the key factors accounting for variations in circulating plant sterol concentrations include: apolipoprotein E phenotypes, ATP-binding cassette transporter polymorphisms, use of statin drugs, presence of metabolic syndrome, dietary intake of plant sterols, gender, and analytical techniques used in the measurement of plant sterols in the plasma. An analysis of the studies examining the relationship between circulating levels of plant sterols and CHD risk in non-sitosterolemic populations revealed no clear associations. Furthermore, it was shown that the above-mentioned factors play an important role in determining the levels of plant sterols in plasma. Since these factors may act as potential confounders, they must be controlled for before more solid conclusions can be reached.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".