Background
Rupture of atherosclerotic plaque can cause acute malignant heart and cerebrovascular events, such as acute coronary heart disease, stroke and so on, which seriously threaten the safety of human life and property. Therefore, the early diagnosis and inhibition of atherosclerotic plaque progress still be a vital task.
Results
In this study, we presented the development of composite mesoporous silica nanoparticle (Ru(bpy)3@SiO2-mSiO2, CMSN)-based nanomedicines (NMs) (Ru(bpy)3@SiO2-mSiO2@SRT1720@AntiCD36, CMSN@SRT@Anti) for accurate diagnosis and treatment of atherosclerosis (AS). In vitro cell experiments showed that both RAW264.7 and oxidized low density lipoprotein (ox-LDL)-stimulated RAW264.7 cells could significantly uptake CMSN@SRT@Anti. Conversely, little fluorescence signal could be observed in CMSN@SRT group, showing the excellent targeting ability of CMSN@SRT@Anti to Class II scavenger receptor, CD36 on macrophage. Additionally, such fluorescence signal was significantly stronger in ox-LDL-stimulated RAW264.7 cells, which might benefit from the upregulated expression of CD36 on macrophages after ox-LDL treatment. For another, compared with free SRT1720, CMSN@SRT@Anti had a better and more significant effect on the inhibition of macrophage foaming process, which indicated that drug-carrying mesoporous silicon with targeting ability could enhance the efficacy of SRT1720. Animal experimental results showed that after the abdominal injection of CMSN@SRT@Anti, the aortic lesions of ApoE-/-mice could be observed with obvious and persistent fluorescence signals. After 4 weeks post-treatment, the serum total cholesterol, aortic plaque status and area were significantly improved in the mouse, and the effect was better than that in the free SRT1720 group or the CMSN@SRT group.
Conclusions
The designed CMSN@SRT@Anti with excellent biocompatibility, high-performance and superior atherosclerosis-targeting ability has great potential for accurate identification and targeted therapy of atherosclerotic diseases.
Graphic abstract