Label-free light scattering imaging of nanoscale small extracellular vesicles

This is the authors' abstract. We don't add key points for this paper.

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.