Involvement of Heat Shock Factor-1 in Glycated LDL–Induced Upregulation of Plasminogen Activator Inhibitor-1 in Vascular Endothelial Cells
Bibliographic record
Abstract
Coronary artery disease is the predominant cause of death in diabetic patients. Plasminogen activator inhibitor-1 (PAI-1) is the major physiological inhibitor of plasminogen activators. Heat shock protein (Hsp) was upregulated in uncontrolled diabetic patients. Our previous studies demonstrated that glycated LDL stimulated the generation of PAI-1 from vascular endothelial cells. The present study examined the effect of glycated LDL on the expression of heat shock factor-1 (HSF1), a physiological transcription factor of Hsp, and the involvement of HSF-1 in glycated LDL-induced production of PAI-1 in cultured human umbilical vein endothelial cells (HUVECs) and coronary artery endothelial cells (HCAECs). Treatment with glycated LDL increased the expression of HSF1 and Hsp-70 compared with LDL in subconfluent HCAECs or HUVECs, and that was associated with an increase of PAI-1 expression. The transfection of HSF1 gene enhanced the expression of PAI-1 in endothelial cells. Small interference RNA against HSF1 prevented glycated LDL-induced upregulation of PAI-1 in HCAECs or HUVECs. Glycated LDL increased the binding of a nuclear protein to the PAI-1 promoter. The nuclear protein-DNA complex was supershifted by HSF1 antibody. The presence of an antioxidant, butylated hydroxytulene, during the glycation of LDL prevented glycated LDL-induced increases of the expression of HSF1 or PAI-1 in endothelial cells. The results suggest that HSF-1 is involved in glycated LDL-induced upregulation of PAI-1 in subconfluent vascular endothelial cells through the binding of HSF1 to PAI-1 promoter. Glyco-oxidation may contribute to glycated LDL-induced expression of HSF1 and PAI-1 in endothelial cells.
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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) | 0.001 | 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".