Hyperhomocysteinemia Activates Nuclear Factor-κB in Endothelial Cells via Oxidative Stress
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Bibliographic record
Abstract
Hyperhomocysteinemia is an independent risk factor for cardiovascular diseases. Our previous studies demonstrated an important interaction between nuclear factor-kappaB (NF-kappaB) activation and homocysteine (Hcy)-induced chemokine expression in vascular smooth muscle cells and macrophages. The objective of the present study was to investigate the in vivo effect of hyperhomocysteinemia on NF-kappaB activation and the underlying mechanism of Hcy-induced NF-kappaB activation in endothelial cells. Hyperhomocysteinemia was induced in Sprague-Dawley rats after 4 weeks of a high-methionine diet. The activated form of NF-kappaB and increased level of superoxide anions were detected in the endothelium of aortas isolated from hyperhomocysteinemic rats. The underlying mechanism of Hcy-induced NF-kappaB activation was investigated in human umbilical cord vein endothelial cells and in human aortic endothelial cells. Incubation of cells with Hcy (100 micromol/L) activated IkappaB kinases (IKKalpha and IKKbeta), leading to phosphorylation and subsequent degradation of IkappaBalpha. As a consequence, NF-kappaB nuclear translocation, enhanced NF-kappaB/DNA binding activity, and increased transcriptional activity occurred. Additional analysis revealed a marked elevation of superoxide anion levels in Hcy-treated cells. Treatment of cells with a superoxide anion scavenger (polyethylene glycol-superoxide dismutase) or IkappaB kinase inhibitor (prostaglandin A(1)) could prevent Hcy-induced activation of IKK kinases and NF-kappaB in endothelial cells. In conclusion, these results suggest that Hcy-induced superoxide anion production may play a potential role for NF-kappaB activation in the early stages of atherosclerosis in the vascular wall via activation of IkappaB kinases.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 it