Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/151486
Title: | Plasmonic sensors for extracellular vesicle analysis : from scientific development to translational research | Authors: | Chin, Lip Ket Son, Taehwang Hong, Jae-Sang Liu, Ai Qun Skog, Johan Castro, Cesar M. Weissleder, Ralph Lee, Hakho Im, Hyungsoon |
Keywords: | Engineering | Issue Date: | 2020 | Source: | Chin, L. K., Son, T., Hong, J., Liu, A. Q., Skog, J., Castro, C. M., Weissleder, R., Lee, H. & Im, H. (2020). Plasmonic sensors for extracellular vesicle analysis : from scientific development to translational research. ACS Nano, 14(11), 14528-14548. https://dx.doi.org/10.1021/acsnano.0c07581 | Journal: | ACS Nano | Abstract: | Extracellular vesicles (EVs), actively shed from a variety of neoplastic and host cells, are abundant in blood and carry molecular markers from parental cells. For these reasons, EVs have gained much interest as biomarkers of disease. Among a number of different analytical methods that have been developed, surface plasmon resonance (SPR) stands out as one of the ideal techniques given its sensitivity, robustness, and ability to miniaturize. In this Review, we compare different SPR platforms for EV analysis, including conventional SPR, nanoplasmonic sensors, surface-enhanced Raman spectroscopy, and plasmonic-enhanced fluorescence. We discuss different surface chemistries used to capture targeted EVs and molecularly profile their proteins and RNAs. We also highlight these plasmonic platforms' clinical applications, including cancers, neurodegenerative diseases, and cardiovascular diseases. Finally, we discuss the future perspective of plasmonic sensing for EVs and their potentials for commercialization and clinical translation. | URI: | https://hdl.handle.net/10356/151486 | ISSN: | 1936-086X | DOI: | 10.1021/acsnano.0c07581 | Rights: | This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Nano, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsnano.0c07581 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles |
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Manuscript_Final.pdf | 5.9 MB | Adobe PDF | ![]() View/Open |
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