MECHANISMS FOR CHOLESTEROL ACCUMULATION IN ARTERY CELLS: IMPACT ON ATHEROGENESIS
Bibliographic record
Abstract
Growing evidence suggests that oxidative stress is widely involved in the physiopathology of cardiovascular diseases. The accumulation of lipids in the arterial wall is important in this process and implicates several cellular types, including macrophages and vascular endothelial cells. Many cholesterol transporters and signalling pathways are related to cholesterol transport in these cells, including ABCA1, SR‐B1, PPARs and LXRs. The aims of this study are to determine, in macrophages and in vascular endothelial cells, the effect of oxidative stress on cholesterol flux and on its transporters ABCA1 and SR‐B1, along with the mechanisms responsible for their regulation. To this end, THP‐1 macrophages and HUVEC endothelial cells were treated with iron/ascorbate (100/1000μM) for a period of 4 and 8 hours in order to induce oxidative stress. Iron/ascorbate led to strong lipid peroxidation as documented by the elevation of MDA levels measured by HPLC, which had been reduced by the antioxidants Trolox and BHT (0.5mM). In macrophages, cholesterol efflux has been found reduced by oxidative stress consequently to the reduction of ABCA1 gene and protein expression, a transporter involved in cellular cholesterol efflux. This regulation involves the nuclear receptors PPAR(α,γ) and LXR(α,β). Our results show that oxidative stress also reduces ABCA1 expression in endothelial cells, without altering cholesterol transport and SR‐B1. Overall, our results demonstrated that oxidative stress can modulate cholesterol transport and receptors in THP‐1 and HUVEC cells, which could stimulate endothelial dysfunction, 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".