Authors: Shpacovitch, Victoria
Sidorenko, Irina
Lenssen, Jan Eric
Temchura, Vladimir
Weichert, Frank
Müller, Heinrich
Überla, Klaus
Zybin, Alexander
Schramm, Alexander
Hergenröder, Roland
Title: Application of the PAMONO-sensor for quantification of microvesicles and determination of nano-particle size distribution
Language (ISO): en
Abstract: The PAMONO-sensor (plasmon assisted microscopy of nano-objects) demonstrated an ability to detect and quantify individual viruses and virus-like particles. However, another group of biological vesicles—microvesicles (100–1000 nm)—also attracts growing interest as biomarkers of different pathologies and needs development of novel techniques for characterization. This work shows the applicability of a PAMONO-sensor for selective detection of microvesicles in aquatic samples. The sensor permits comparison of relative concentrations of microvesicles between samples. We also study a possibility of repeated use of a sensor chip after elution of the microvesicle capturing layer. Moreover, we improve the detection features of the PAMONO-sensor. The detection process utilizes novel machine learning techniques on the sensor image data to estimate particle size distributions of nano-particles in polydisperse samples. Altogether, our findings expand analytical features and the application field of the PAMONO-sensor. They can also serve for a maturation of diagnostic tools based on the PAMONO-sensor platform.
Subject Headings: Plasmonic sensors
Surface plasmon resonance
Extracellular vesicles
Microvesicles
Machine learning
Deep learning
URI: http://hdl.handle.net/2003/38482
http://dx.doi.org/10.17877/DE290R-20401
Issue Date: 2017-01-27
Rights link: https://creativecommons.org/licenses/by/4.0/
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