Involvement of NADPH oxidase in oxidized LDL-induced upregulation of heat shock factor-1 and plasminogen activator inhibitor-1 in vascular endothelial cells
Bibliographic record
Abstract
Plasminogen activator inhibitor-1 (PAI-1) is implicated in thrombogenesis, inflammation, and extracellular matrix remodeling. Previous studies indicated that oxidized low-density lipoprotein (LDL) stimulated the generation of PAI-1 in vascular endothelial cells (EC). The present study demonstrated that LDL oxidized by copper, iron, or 3-morpholinosydnonimine increased the expression of NADPH oxidase (NOX) 2, PAI-1, and heat shock factor-1 (HSF1) in human umbilical vein EC or coronary artery EC compared with LDL or vehicle. Diphenyleneiodonium, a NOX inhibitor, prevented the increases of the expression of HSF1 and PAI-1 in EC induced by oxidized LDLs. Small-interference RNA (siRNA) for p22(phox), an essential subunit of NOX, prevented oxidized LDL-induced expression of NOX2, HSF1, and PAI-1 in EC. HSF1 siRNA inhibited oxidized LDL-induced expression of PAI-1 and HSF1, but not NOX2, in EC. The binding of HSF1 to PAI-1 promoter and the activity of PAI-1 promoter in EC were enhanced by oxidized LDL. Butylated hydroxytulene, a potent antioxidant, inhibited oxidized LDL-induced release of hydrogen peroxide (H(2)O(2)) and the expression of NOX2, HSF1, and PAI-1 in EC. Treatment with H(2)O(2) increased the abundance of NOX2, HSF1, and PAI-1 in EC. The results of the present study indicate that oxidized LDL-induced expression of NOX may lead to the elevated release of reactive oxygen species, the activation of HSF1, and the enhancement of the transcription of PAI-1 gene in cultured vascular EC.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".