Extra-virgin olive oil consumption improves the capacity of HDL to mediate cholesterol efflux and increases ABCA1 and ABCG1 expression in human macrophages
Bibliographic record
Abstract
The present study was aimed to investigate the effect of 12 weeks of extra-virgin olive oil (EVOO) consumption on the capacity of HDL to promote cholesterol efflux (CE) and to determine which CE pathways are modulated by EVOO consumption. Whole HDL and HDL₂/HDL₃ subclasses were isolated from the plasma of twenty-six healthy volunteers before and after 12 weeks of EVOO consumption (25 ml/d). EVOO consumption increased the capacity of serum and HDL to mediate CE from THP-1, J774 macrophages and Fu5AH cells by 9·8-24·57 %, depending on the cell type. The increase in CE was independent of both HDL concentration and subclass distribution. The three HDL-mediated CE pathways (ATP-binding cassette (ABC) A1, ABCG1 and scavenger receptor class B type I (SR-BI)) were modulated by EVOO consumption. The fluidity of the phospholipidic layer of HDL increased by 13 % (P< 0·001) following EVOO consumption compared with baseline. EVOO consumption also increased the release of excess cholesterol from human monocyte-derived macrophages (HMDM) by 44 % (P< 0·001), and ABCA1 and ABCG1 mRNA transcription by 16·08 % (P< 0·001) and 35·79 % (P< 0·01), respectively. The protein expression of these two cholesterol transporters also increased after EVOO consumption. In contrast, SR-BI mRNA and protein expression in HMDM were significantly lower after 12 weeks of EVOO consumption. Incubating J774 macrophages with EVOO polyphenol extracts induced a concentration-dependent up-regulation of ABCA1 and ABCG1 expression in macrophages. After 12 weeks of EVOO consumption, the capacity of HDL to mediate CE was improved and the ability of HMDM to release excess cholesterol was enhanced by increasing the expression of ABCA1 and ABCG1 transporters.
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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".