Resveratrol Suppresses PAI-1 Gene Expression in a Human<i>In Vitro</i>Model of Inflamed Adipose Tissue
Bibliographic record
Abstract
Increased plasminogen activator inhibitor-1 (PAI-1) levels are associated with a number of pathophysiological complications; among them is obesity. Resveratrol was proposed to improve obesity-related health problems, but the effect of resveratrol on PAI-1 gene expression in obesity is not completely understood. In this study, we used SGBS adipocytes and a model of human adipose tissue inflammation to examine the effects of resveratrol on the production of PAI-1. Treatment of SGBS adipocytes with resveratrol reduced PAI-1 mRNA and protein in a time- and concentration-dependent manner. Further experiments showed that obesity-associated inflammatory conditions lead to the upregulation of PAI-1 gene expression which was antagonized by resveratrol. Although signaling via PI3K, Sirt1, AMPK, ROS, and Nrf2 appeared to play a significant role in the modulation of PAI-1 gene expression under noninflammatory conditions, those signaling components were not involved in mediating the resveratrol effects on PAI-1 production under inflammatory conditions. Instead, we demonstrate that the resveratrol effects on PAI-1 induction under inflammatory conditions were mediated via inhibition of the NF κ B pathway. Together, resveratrol can act as NF κ B inhibitor in adipocytes and thus the subsequently reduced PAI-1 expression in inflamed adipose tissue might provide a new insight towards novel treatment options of obesity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".