Initial plasma plant sterol concentrations do not predict changes in plasma lipids and plant sterols following intake of a plant sterol‐enriched food
Bibliographic record
Abstract
Background: Plant sterols (PS) effectively lower plasma TC and LDL‐C concentrations, while minimally elevating PS concentrations. Initial plasma PS concentrations, however, may reflect sterol absorption. Accordingly, reductions in plasma TC and LDL‐C and elevations in PS may differ between individuals with initially high (HPS) and low (LPS) plasma PS concentrations after dietary PS intake. Objective: To examine whether HPS and LPS plasma concentrations are related to subsequent changes in plasma PS and cholesterol concentrations, following dietary PS intake in otherwise healthy hypercholesterolemic men. Design: This single‐blinded, randomized, controlled study consisted of two 4‐week phases, separated by a 4‐week wash‐out, whereby a diet with a placebo or the 1.8 g/d PS‐enriched spread was consumed. Results: Following PS intake, plasma PS concentrations were elevated from 34.59 to 46.17 μmol/L and 16.45 to 20.8 μmol in HPS and LPS groups, respectively; while percent changes were not different between groups. TC and LDL‐C concentrations were decreased (p<0.0001) by 6.3 and 7.8 %, for all individuals. Changes in lipid parameters were not different between groups. Conclusions: In view of these data, a supplement of 1.8 g/d of PS should be viewed as a beneficial cholesterol‐lowering therapy that minimally elevates plasma PS concentrations to the same extent for all healthy individuals, with respect to their initial plasma PS concentrations. Acknowledgements: This research was funded by Unilever R&D, The Netherlands.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".