Label-free light scattering imaging of nanoscale small extracellular vesicles

被引:0
作者
Eltigani, Faihaa Mohammed [1 ,2 ]
Wang, Zhuo [1 ,2 ]
Liu, Qiao [3 ]
Wang, Shuanglian [4 ]
Su, Xuantao [1 ]
机构
[1] Shandong Univ, Sch Integrated Circuits, 1500 Shunhua Rd, Jinan 250101, Shandong, Peoples R China
[2] Shandong Univ, Sch Control Sci & Engn, Inst Biomed Engn, 17923 Jingshi Rd, Jinan 250061, Shandong, Peoples R China
[3] Shandong Univ, Sch Basic Med Sci, Dept Mol Med & Genet, 44 Wenhua West Rd, Jinan 250102, Shandong, Peoples R China
[4] Shandong Univ, Sch Med, Dept Physiol, 44 Wenhua West Rd, Jinan 250102, Shandong, Peoples R China
来源
IMAGING, MANIPULATION, AND ANALYSIS OF BIOMOLECULES, CELLS, AND TISSUES XXII | 2024年 / 12846卷
基金
中国国家自然科学基金;
关键词
Light scattering imaging; small extracellular vesicles; deep learning; inverse scattering problem; nanoparticle;
D O I
10.1117/12.3001048
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Small extracellular vesicles (sEVs), which are nanoparticles around 100 nm, have been widely studied in recent years in many interesting areas, such as cancer detection and drug delivery. Bulk analysis of extracellular vesicles provides average information about the EV population. However, single EV characterization enables a profound understanding of the biophysical properties of EV subpopulations, establishing an insightful view of the EVs function and composition. It is worth to explore light scattering imaging method for the analysis of single sEVs. We introduce here the deep learningbased light scattering imaging method for analyzing label-free sEVs (DeepEVAnalyzer), which has been applied to measure the size of single sEVs. We also report our recent development of a light scattering imaging method to address the inverse problem, which is demonstrated to differentiate the label-free sEVs from healthy mice and those injected with malignant cells. Light scattering imaging together with machine learning for sEVs analysis may have potential diagnostic and therapeutic applications.
引用
收藏
页数:6
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