Modulation of apolipoprotein A1 and B, adiponectin, ghrelin, and growth hormone concentrations by plant sterols and exercise in previously sedentary humansThis article is one of a selection of papers published in this special issue (part 1 of 2) on the Safety and Efficacy of Natural Health Products.
Bibliographic record
Abstract
Plant sterols combined with exercise beneficially alter lipid levels in hypercholesterolemic adults. The effect of this combination therapy on other indicators of coronary heart disease risk, however, has yet to be determined. The objective of this trial was to investigate the effect of plant sterols and exercise, alone and in combination, on levels of apolipoprotein (apo) A1 and B, adiponectin, ghrelin, and growth hormone in previously sedentary hypercholesterolemic adults. In an 8 week, parallel-arm trial, 84 subjects were randomized to 1 of 4 groups: combination, exercise, plant sterols, or control. Body mass decreased by 1.1% (p < 0.01) and 0.9% (p < 0.05) in the combination and exercise group, respectively. Low-density lipoprotein cholesterol levels decreased (p < 0.01) by 0.30 mmol/L in the combination group and by 0.49 mmol/L in the plant sterol group. High-density lipoprotein cholesterol levels increased by 7.5% and 9.5% (p < 0.01) in the combination and exercise groups, respectively. Plant sterols increased (p < 0.05) adiponectin levels by 16%. No change in apoA1, apoB, ghrelin, or growth hormone levels were noted in any intervention group. ApoA1 was correlated with high-density lipoprotein cholesterol (r = 0.33, p = 0.01), whereas apoB was weakly related to low-density lipoprotein cholesterol levels (r = 0.13, p = 0.002). Adiponectin was associated with body mass index (r = -0.10, p = 0.006) and high-density lipoprotein cholesterol (r = 0.17, p = 0.0003). These findings suggest that plant sterols can increase adiponectin levels, thereby possibly reducing the risk of future coronary heart disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".