The PAMONO-sensor enables quantification of individual microvesicles and estimation of nanoparticle size distribution
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Date
2017-09-27
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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.