AsianScientist (Dec. 3, 2018) – Researchers in Japan have combined sensor technology and artificial intelligence to rapidly diagnose influenza. They published their findings in Scientific Reports.
Influenza is a highly contagious respiratory disease which causes millions of infections annually. Passive vaccination is the only method available for partial control of the virus. Although scientists have been exploring ways to diagnose influenza quickly so as to prevent outbreaks, the diagnostic sensitivity of existing technologies needs to be improved.
To develop a better diagnostic tool for influenza, researchers led by Associate Professor Makusu Tsutsui of Osaka University, Japan, designed a sensor that could assess distinct nanoscale properties of influenza virus particles in patient samples.
Made of silicon nitride, the sensor consists of pores through which virus particles can pass. The research team found that liquid motion induced by an electric current across the nanopore—otherwise known as electroosmotic flow—could block the passage of non-virus particles in a sample, thereby increasing the sensitivity of their system.
Furthermore, as different subtypes of the influenza virus passed through the nanopore, the electrical signals produced varied.
“We used machine-learning analysis of the electrical signatures of the virions,” said Tsutsui. “Using this artificial intelligence approach to signal analysis, we were able to recognize a slight current waveform difference, which cannot be discerned by human eyes. This enables high-precision identification of viruses.”
In addition to enabling early detection of influenza, this nanosensor could be modified to enable early detection of other viral particles, said the researchers, making it useful for detecting and tracking a variety of local epidemics and potential pandemics.
“Importantly, the use of this sensor does not require specialized human expertise, so it can readily be applied as a point-of-care screening approach by a wide variety of healthcare personnel,” said lead author Dr. Akihide Arima of Osaka University.
The article can be found at: Arima et al. (2018) Selective Detections of Single-viruses Using Solid-state Nanopores.
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Source: Osaka University; Photo: Shutterstock.
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