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  Label-free discrimination of extracellular vesicles from large lipoproteins

Kashkanova, A. D., Blessing, M., Reischke, M., Baur, J.-O., Baur, A. S., Sandoghdar, V., et al. (2023). Label-free discrimination of extracellular vesicles from large lipoproteins. Journal of extracellular vesicles, 12: 12348. doi:10.1002/jev2.12348.

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 Creators:
Kashkanova, Anna D.1, 2, Author           
Blessing, Martin1, 2, 3, Author           
Reischke, Marie1, Author           
Baur, Jan-Ole4, Author
Baur, Andreas S., Author
Sandoghdar, Vahid1, 2, 3, Author           
Van Deun, Jan4, Author
Affiliations:
1Sandoghdar Division, Max Planck Institute for the Science of Light, Max Planck Society, ou_2364722              
2Max-Planck-Zentrum für Physik und Medizin, Max Planck Institute for the Science of Light, Max Planck Society, ou_3164414              
3Department of Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany, ou_persistent22              
4External Organizations, ou_persistent22              

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 Abstract: Extracellular vesicles (EVs) are increasingly gaining interest as biomarkers and therapeutics. Accurate sizing and quantification of EVs remain problematic, given their nanometre size range and small scattering cross-sections. This is compounded by the fact that common EV isolation methods result in co-isolation of particles with comparable features. Especially in blood plasma, similarly-sized lipoproteins outnumber EVs to a great extent. Recently, interferometric nanoparticle tracking analysis (iNTA) was introduced as a particle analysis method that enables determining the size and refractive index of nanoparticles with high sensitivity and precision. In this work, we apply iNTA to differentiate between EVs and lipoproteins, and compare its performance to conventional nanoparticle tracking analysis (NTA). We show that iNTA can accurately quantify EVs in artificial EV-lipoprotein mixtures and in plasma-derived EV samples of varying complexity. Conventional NTA could not report on EV numbers, as it was not able to distinguish EVs from lipoproteins. iNTA has the potential to become a new standard for label-free EV characterization in suspension.

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 Dates: 2023-07-25
 Publication Status: Published online
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 Identifiers: DOI: 10.1002/jev2.12348
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Title: Journal of extracellular vesicles
  Other : Journal of extracellular vesicles : JEV / The International Society for Extracellular Vesicles
  Abbreviation : JEV
Source Genre: Journal
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Publ. Info: Hoboken, NJ : Wiley
Pages: - Volume / Issue: 12 Sequence Number: 12348 Start / End Page: - Identifier: ISSN: 2001-3078
CoNE: https://pure.mpg.de/cone/journals/resource/2001-3078