Modulation of cholesterol transport by oxidative stress in THP‐1 macrophages
Bibliographic record
Abstract
Foam cell formation constitutes a crucial step in atherosclerosis development. Several cholesterol transporters and signalling pathways are involved in this process. It has also been shown that oxidative stress is highly implicated in atherogenic events. The aims of this study are to determine the effect of oxidative stress on cholesterol flux and on its transporters ABCA1 and SR‐B1, as well as to identify the mechanisms involved in their regulation. To this end, we treated THP‐1 macrophages with iron/ascorbate (100/1000μM) for a period of 2 and 4 hours in order to assess oxidative stress. To neutralize lipid peroxidation, we used the antioxidants Trolox (0.5mM) and BHT (0.5mM). Iron/ascorbate led to strong peroxidation as shown by the elevation of MDA levels (2200%, p<0.001) measured by HPLC, which had been reduced by the antioxidants. Oxidative stress down‐regulated mRNA and protein expression of ABCA1, a transporter involved in cellular cholesterol efflux. Peroxidation stimulated mRNA expression without alteration of protein mass of SR‐B1, a scavenger receptor that usually enhances cholesterol uptake. In parallel, experiments performed on cholesterol transport showed that peroxidation reduces cholesterol efflux without altering the influx process. Experiments using RT‐PCR showed that these modulations are orchestrated by the nuclear receptors LXRα, LXRβ, PPARα and PPARγ. Overall, our results demonstrated that oxidative stress modulates receptor and signalling pathways in THP‐1 macrophages, thus inhibiting cholesterol efflux, which could stimulate foam cell formation and atherosclerosis development.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".