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Sensors 2017, 17(2), 244; doi:10.3390/s17020244

Application of the PAMONO-Sensor for Quantification of Microvesicles and Determination of Nano-Particle Size Distribution

1
Leibniz Institute für Analytische Wissenschaften, ISAS e.V., Bunsen-Kirchhoff-Straße 11, 44139 Dortmund, Germany
2
MIVITEC GmbH, Wamslerstraße.4, 81829 Munich, Germany
3
Department of Computer Science VII, TU Dortmund University, Otto-Hahn-Straße. 16, 44227Dortmund,Germany
4
Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany
5
Children’s Hospital, Oncology Laboratory, University Clinic Essen, Hufelandstraße. 55, 45122 Essen, Germany
*
Author to whom correspondence should be addressed.
Received: 31 October 2016 / Accepted: 16 January 2017 / Published: 27 January 2017
(This article belongs to the Special Issue Last Advances in Nanoplasmonics Biosensors)
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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. View Full-Text
Keywords: plasmonic sensors; surface plasmon resonance; extracellular vesicles; microvesicles; machine learning; deep learning plasmonic sensors; surface plasmon resonance; extracellular vesicles; microvesicles; machine learning; deep learning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Shpacovitch, V.; Sidorenko, I.; Lenssen, J.E.; Temchura, V.; Weichert, F.; Müller, H.; Überla, K.; Zybin, A.; Schramm, A.; Hergenröder, R. Application of the PAMONO-Sensor for Quantification of Microvesicles and Determination of Nano-Particle Size Distribution. Sensors 2017, 17, 244.

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