Secreted apolipoprotein E reduces macrophage‐mediated LDL oxidation in an isoform‐dependent way
Bibliographic record
Abstract
As an inflammatory cell, the macrophage produces various oxidizing agents, such as free radical species. These can modify LDL as a secondary effect and doing so may favor atherogenic processes. Any molecule able to counteract these reactions would be of much benefit, especially if secreted by the macrophage itself at the lesion site. Such is the case for apolipoprotein E (apoE), which has been shown to exert antioxidant properties in some studies, mostly in relation to Alzheimer's disease. In this study, we assessed the antioxidant potential of the various isoforms of apoE (E2, E3, and E4) using a metal-induced LDL oxidation system with exogenous recombinant apoE and an in vitro model of macrophage-mediated LDL oxidation. We found that all three isoforms had an antioxidant capacity. However, whereas apoE2 was the most protective isoform in the cell-free system, the opposite was observed in apoE-transfected J774 macrophages. In the latter model, cellular cholesterol efflux was found to be more important with apoE2, possibly explaining the larger quantity of oxidative indices observed in the medium. It is proposed that the antioxidant property of apoE results from a balance between direct apoE antioxidant capacities, such as the ability to trap free radicals, and potentially pro-oxidative indirect events associated with cholesterol efflux from cells. Our observations add to the therapeutic potential of apoE. However, they also suggest the need for more experiments in order to achieve careful selection of the apoE isoform to be targeted, especially in the perspective of apoE transgene use.
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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".