Effect of Oxidative Stress on the Status of Adhesion Molecules, Nuclear Receptors and Cholesterol Flux in Endothelial Cells: Priming of Monocytes
Bibliographic record
Abstract
Circumstantial evidence suggests that oxidative stress plays a crucial role in the initiation and progression of atherosclerosis, but little is known about the relationship between oxidative stress per se, cholesterol transport and endothelial cell integrity. The aim of the present work is to tackle this issue by treating human umbilical vein endothelial cells (HUVEC) with iron/ascorbate for 4 and 8 hours and by subsequently evaluating the cholesterol flux, the gene expression status of cholesterol transporters, nuclear receptors and adhesion molecules, as well as the cellular adhesion of THP-1 monocytes to HUVEC. The incubation of HUVEC with iron/ascorbate resulted in marked lipid peroxidation as reflected by high malondialdehyde levels, which were reduced by pre-treatment with the antioxidant Trolox. Our experiments could not reveal any modifications in the protein and gene expression of the transporters (ABCA1, SR-BI, LOX-1), the adhesion molecules (VCAM-1, ICAM-1 and E-selectin) and the nuclear receptors (PPARs and LXRs) under the influence of iron/ascorbate. However, oxidative stress enhanced monocyte adhesion to HUVEC, induced the gene expression of ICAM-1, E-selectin and MCP-1, whereas it downregulated eNOS mRNA in the presence of monocytes. Overall, our data suggest that oxidative stress is more harmful in the presence of heterocellular communication between endothelial cells and monocytes.
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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) | 0.002 | 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".