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.
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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 com...
»