Flavonoids targeting of IκB phosphorylation abrogates carcinogen-induced MMP-9 and COX-2 expression in human brain endothelial cells
Bibliographic record
Abstract
Brain endothelial cells play an essential role as structural and functional components of the blood-brain barrier (BBB). Increased BBB breakdown and brain injury are associated with neuroinflammation and are thought to trigger mechanisms involving matrix metalloproteinase upregulation. Emerging evidence also indicates that cyclooxygenase (COX) inhibition limits BBB disruption, but the mechanisms linking metalloproteinase to COX remain unknown. In this study, we sought to investigate the nuclear factor-kappa B (NF-κB) signaling pathway, a common pathway in both the regulation of matrix metalloproteinase-9 (MMP-9) and COX-2 expression, and the inhibitory properties of several chemopreventive flavonoids. Human brain microvascular endothelial cells were treated with a combination of phorbol 12-myristate 13-acetate (PMA), a carcinogen documented to increase MMP-9 and COX-2 through NF-κB, and several naturally occurring flavonoids. Among the molecules tested, we found that fisetin, apigenin, and luteolin specifically and dose-dependently antagonized PMA-induced COX-2 and MMP-9 gene and protein expressions as assessed by qRT-PCR, immunoblotting, and zymography respectively. We further demonstrate that flavonoids impact on IκK-mediated phosphorylation activity as demonstrated by the inhibition of PMA-induced IκB phosphorylation levels. Our results suggest that BBB disruption during neuroinflammation could be pharmacologically reduced by a specific class of flavonoids acting as NF-κB signal transduction inhibitors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".