Tag Archive for: Love-SAW sensors

Publication on AWSensors technology

Surface Acoustic Wave Immunosensor for Detection of Botulinum Neurotoxin

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Authors: Michał Grabka, Krzysztof Jasek and Zygfryd Witkiewicz

Journal: Sensors (2023)

 

Abstract

A Love-type acoustic wave sensor (AT-cut quartz substrate, SiO2 guiding layer) with a center frequency of approximately 120 MHz was used to detect a simulant of pathogenic botulinum neurotoxin type A—recombinant of BoNT-A light chain—in liquid samples. The sensor was prepared by immobilizing monoclonal antibodies specific for botulinum neurotoxin via a thiol monolayer deposited on a gold substrate. Studies have shown that the sensor enables selective analyte detection within a few minutes. In addition, the sensor can be used several times (regeneration of the sensor is possible using a low pH buffer). Nevertheless, the detectability of the analyte is relatively low compared to other analytical techniques that can be used for rapid detection of botulinum neurotoxin. The obtained results confirm the operation of the proposed sensor and give hope for further development of this label-free technique for detecting botulinum neurotoxin.

Surface Acoustic Wave (Love-SAW) immunosensor for detection of botulinum neurotoxin. Source: Sensors 2023, 23(18), 7688

You may read the full paper here.

QCMD workshop training

Hands-on Training Workshop on QCMD at IMBB-FORTH, Greece

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AWSensors ran a successful hands-on training workshop at the Gizeli group at IMBB FORTH in Crete, Greece. Undergraduate students, graduate students, and postdocs were invited to attend the session and learned how to use our X1 QCMD instrument and Love-SAW devices. During the workshop, participants had the opportunity to understand how to effectively utilize these acoustic sensing technologies for their research. Building on their core expertise in molecular biology and biophysics, the Gizeli group is exploring biosensing applications in human, animal, and plant disease diagnostics as well as pathogen and environmental pollutant detection. The training helped researchers in the group exploit the unique advantages of AWSensors’ equipment, such as sensitivity, time resolution, flexibility, integrated flow control, and ease of use, for biosensor development.