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-learning-based 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.
Liver cancer is one of the most common digestive system malignancies with an average five-year survival rate of less than 20%, while traditional methods are often unautomated, labeling required, and limited for early liver cancer detection. Exosomes are a type of extracellular vesicles with a diameter of 40-150 nm, which play important role in disease diagnosis and treatment. It is of interest to develop a label-free optical system for the analysis of nanoscale exosomes. Here, we developed a label-free two-dimensional (2D) light scattering acquisition system for the measurements of microparticles and the exosomes derived from the normal liver cells. By adjusting the thickness of the light sheet for illumination in our system, nanoparticles down to 41 nm are detected. The visualization and accurate particle size analysis of liver cell exosomes are then performed by our 2D light scattering technology. Our method is expected to have important applications in the quantitative analysis field of cellular and extracellular structures that may find potential applications in clinics such as for early cancer diagnosis.
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