Epoxycholesterol Impairs Cholesteryl Ester Hydrolysis in Macrophage Foam Cells, Resulting in Decreased Cholesterol Efflux
Bibliographic record
Abstract
OBJECTIVE: Strategies to inhibit or reverse cholesterol accumulation in macrophages have been shown to be atheroprotective. Notably, the administration of LXR agonists upregulates key players in the reverse cholesterol transport pathway, including the ABCA1 and ABCG1 transporters. However, the effects of natural LXR activators, oxysterols, on lipid-laden macrophages remains elusive. METHODS AND RESULTS: We assessed the ability of 2 oxysterols, 22(R)-hydroxycholesterol (22-OH) and 24(S),25-epoxycholesterol (epoxycholesterol), to promote cholesterol efflux to apoA-I from LDL- and modified LDL-labeled and loaded macrophages and thus rescue the phenotype associated with the accumulation of cellular cholesterol in these cells. In macrophages labeled with LDL-derived cholesterol, epoxycholesterol treatment enhances ABCA1-mediated cholesterol efflux. In contrast, in AcLDL-loaded macrophages, epoxycholesterol treatment decreases cholesterol efflux to apoA-I, despite a dramatic increase in the expression of ABCA1 in response to epoxycholesterol treatment. We show that the decreased efflux is attributable to impaired cholesterol mobilization from lipid droplets, resulting from decreased cholesteryl ester hydrolase activity. CONCLUSIONS: Epoxycholesterol impairs cholesteryl ester hydrolysis activity in macrophage foam cells, thus reducing the availability of cholesterol for efflux to cholesterol acceptors.
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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".