Cellular Carbonyl Stress Enhances the Expression of Plasminogen Activator Inhibitor-1 in Rat White Adipocytes via Reactive Oxygen Species-dependent Pathway
Bibliographic record
Abstract
Carbonyl stress is one of the important mechanisms of tissue damage in vascular complications of diabetes. In the present study, we observed that the plasminogen activator inhibitor-1 (PAI-1) levels in serum and its gene expression in adipose tissue were up-regulated in aged OLETF rats, model animals of obese type 2 diabetes. To study the mechanism of PAI-1 up-regulation, we examined the effect of advanced glycation end products (AGEs) and the product of lipid peroxidation (4-hydroxy-2-nonenal (HNE)), both of which are endogenously generated under carbonyl stress. Stimulation of primary white adipocytes by either AGE or HNE resulted in the elevation of PAI-1 in culture medium and at mRNA levels. The up-regulation of PAI-1 was also observed by incubating the cells in high glucose medium (30 mm, 48 h). The stimulatory effects by AGE or high glucose were inhibited by antioxidant, pyrrolidine dithiocarbamate, and reactive oxygen scavenger, probucol, suggesting a pivotal role of oxidative stress in white adipocytes. We also found that the effect by HNE was inhibited by antioxidant, N-acetylcysteine and that a specific inhibitor of glutathione biosynthesis, l-buthionine-S,R-sulfoximine, augmented the effect of subthreshold effect of HNE. Bioimaging of reactive oxygen species (ROS) by a fluorescent indicator, 6-carboxy-2',7'-dichlorodihydrofluorescein diacetate, revealed ROS production in white adipocytes treated with AGE or HNE. These results suggest that cellular carbonyl stress induced by AGEs or HNE may stimulate PAI-1 synthesis in and release from adipose tissues through ROS formation.
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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".