Effect of the Mediterranean Diet on the Lipid-Lipoprotein Profile: Is It Influenced by the Family History of Dyslipidemia?
Bibliographic record
Abstract
BACKGROUND/AIMS: To examine whether a family history of dyslipidemia influences the lipid-lipoprotein response to the Mediterranean diet (MedDiet). METHODS: We recruited 36 individuals with a positive family history of dyslipidemia (i.e. having at least one first-degree relative with a diagnosis of dyslipidemia) and 28 individuals with a negative family history of dyslipidemia, aged between 24 and 53 years, who had slightly elevated low-density lipoprotein cholesterol (LDL-C) concentrations (3.4-4.9 mmol/l) or a total cholesterol to high-density lipoprotein cholesterol (HDL-C) ratio≥5.0. Variables related to the lipid-lipoprotein profile were measured before and after a 4-week isocaloric MedDiet during which all foods and drinks were provided to participants. RESULTS: A group by time interaction was noted for plasma total cholesterol concentrations (p=0.03), subjects with a negative family history of dyslipidemia having greater decreases than those with a positive family history of dyslipidemia (-11.3 vs. -5.1%, respectively). Decreases in LDL-C, HDL-C, total cholesterol to HDL-C ratio, LDL-C to HDL-C ratio, apo B, apo A-1, apo A-2 and apo B to apo A-1 ratio were noted, with no difference between groups (p for group by time interaction≥0.11). CONCLUSIONS: Results highlight that inherited susceptibilities to dyslipidemia may explain at least in part the heterogeneity in the cholesterol-lowering effects of the MedDiet.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| 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".