Anti-Inflammatory Activity of Ezetimibe by Regulating NF-κB/MAPK Pathway in THP-1 Macrophages
Bibliographic record
Abstract
Inflammation plays a crucial role in atherosclerosis. Monocytes/macrophages are involved in the inflammatory process during atherogenesis. Here, we performed daily gavage of ezetimibe in apolipoprotein E-deficient mice fed with a high-fat diet and found that ezetimibe administration decreased the level of C-reactive protein significantly. To investigate the potential molecular mechanism, we employed microarray analysis on the cultured macrophages treated with Chol:MβCD in the presence or absence of ezetimibe. We found that ezetimibe dramatically down-regulated the expression of the tumor necrosis factor-α (TNF-α) gene. Consistent with the microarray results, TNF-α protein levels were inhibited by ezetimibe. Moreover, ezetimibe suppressed the promoter activity of TNF-α but not TNF-α lacking the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) binding domain in THP-1 cells treated with phorbol myristate acetate and Chol:MβCD. Furthermore, treatment of THP-1 macrophages with ezetimibe resulted in the degradation of IκB and subsequently inhibited nuclear translocation of NF-κB and its transcriptional activity. Inhibition of the mitogen-activated protein kinase (MAPK) pathway using PD98059 attenuated the reduction effect of ezetimibe on the expression of NF-κB. Collectively, our results demonstrated that the anti-inflammatory properties of ezetimibe in THP-1 macrophages are, at least in part, through suppression of NF-κB activation via the MAPK pathway. These data provide direct evidence for the potential application of ezetimibe in the prevention and treatment of inflammatory diseases.
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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) | 0.000 | 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) | 0.000 | 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".