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Proceedings 2017, 1(8), 744; doi:10.3390/proceedings1080744

The PAMONO-Sensor Enables Quantification of Individual Microvesicles and Estimation of Nanoparticle Size Distribution

1
Leibniz Institute für Analytische Wissenschaften, ISAS, e.V., 44139 Dortmund, Germany
2
Mathematical Faculty, Technical University of Munich, 85748 Garching, Germany
3
Department of Computer Science VII, TU Dortmund University, 44227 Dortmund, Germany
4
Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany
5
Department of Medical Oncology, West German Cancer Center, University Hospital Essen, 45122 Essen, Germany
Presented at the 5th International Symposium on Sensor Science (I3S 2017), Barcelona, Spain, 27–29 September 2017.
*
Author to whom correspondence should be addressed.
Published: 24 November 2017
(This article belongs to the Proceedings of the 5th International Symposium on Sensor Science (I3S 2017))
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Abstract

In our recent work, the plasmon assisted microscopy of nano-objects (PAMONO) was successfully employed for the detection and quantification of individual viruses and virus-like particles in aquatic samples (Shpacovitch et al., 2015). Further, we adapted the PAMONO-sensor for the specific detection of individual microvesicles (MVs), which have gained growing interest as potential biomarkers of various physiological and pathological processes. Using MVs derived from human neuroblastoma cell line cells, we demonstrated the ability of the PAMONO-sensor to specifically detect individual MVs. Moreover, we proved the trait of the PAMONO-sensor to perform a swift comparison of relative MV concentrations in two or more samples without a prior sensor calibration. The detection software developed by the authors utilizes novel machine learning techniques for the processing of the sensor image data. Using this software, we demonstrated that nanoparticle size information is evident in the sensor signals and can be extracted from them. These experiments were performed with polystyrene nanoparticles of different sizes. We also suggested a theoretical model explaining the nature of observed signals. Taken together, our findings can serve as a basis for the development of diagnostic tools built on the principles of the PAMONO-sensor.
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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MDPI and ACS Style

Shpacovitch, V.; Sidorenko, I.; Lenssen, J.E.; Temchura, V.; Weichert, F.; Müller, H.; Überla, K.; Zybin, A.; Schramm, A.; Hergenröder, R. The PAMONO-Sensor Enables Quantification of Individual Microvesicles and Estimation of Nanoparticle Size Distribution. Proceedings 2017, 1, 744.

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