Extra-virgin olive oil consumption reduces the age-related decrease in HDL and paraoxonase 1 anti-inflammatory activities
Bibliographic record
Abstract
Paraoxonase 1 (PON1) is associated with HDL and modulates the antioxidant and anti-inflammatory role of HDL. The goals of the present study were to investigate the effect of ageing and the role of PON1 on the anti-inflammatory activity of HDL, and to determine whether extra-virgin olive oil (EVOO) consumption could improve the atheroprotective activity of HDL. HDL and PON1 were isolated from the plasma of ten young (Y-HDL and Y-PON1) and ten elderly (E-HDL and E-PON1) healthy volunteers before and after 12 weeks of EVOO consumption. Inflammation was assessed by measuring intracellular adhesion molecule 1 (ICAM-1) expression. THP-1 (human acute monocytic leukaemia cell line) monocyte chemotaxis was measured using a Boyden chamber. Oxidative damage to HDL was assessed by measuring conjugated diene formation and changes in electrophoretic migration. Y-HDL had more anti-inflammatory activity than E-HDL. The conjugated diene content and the electrophoretic mobility of E-HDL were higher than those of Y-HDL. Y-PON1 had significant anti-inflammatory activity, reducing ICAM-1 expression by 32·64 (SD 2·63)%, while E-PON1 had no significant effect. THP-1 chemotaxis measurements confirmed the ICAM-1 expression results. The 12 weeks of EVOO consumption significantly increased the anti-inflammatory activities of both HDL and PON1. The anti-inflammatory activity of HDL was modulated by PON1 and was lower in the elderly volunteers. EVOO consumption increased the anti-inflammatory effect of HDL and reduced the age-related decrease in anti-atherogenic activity.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".