Jointly with Professor Tomoji Kawai, Associate Professor Makusu Tsutsui, Specially Appointed Assistant Professor Akihide Arima (full-time), Professor Takashi Washio, and Professor Mina Okouchi of the Faculty of Materials Science and Engineering, Tokyo Institute of Technology The research group has succeeded in identifying the types of influenza virus (type A, type B, subtype A) with high accuracy by combining a nanopore sensor that can detect a single particle with AI technology.
Conventionally, the type of influenza has been determined by a skilled person visually determining the presence or absence of a marker appearing in an immunochromatographic test kit.In addition to being difficult to determine in the early stages of infection when the number of viruses is small, there is the problem that the accuracy of the determination depends on the individual's ability.
Therefore, this time, the research group succeeded in detecting influenza virus at the level of one by using the nanopore method that measures the ion current passing through the nanopores opened in the ultrathin silicon nitride film.Furthermore, by applying pattern recognition technology by machine learning to the analysis of ion current signals, it has become possible to discriminate slight differences in current waveforms that cannot be discerned by the human eye.As a result, highly accurate influenza virus type determination has become possible, and it has become possible to obtain 1% accuracy with one influenza virus particle and 1% or more accuracy with detection of 72 or more particles.
This result is expected to realize influenza virus type determination in the early stage of infection, which is quick and simple and does not depend on the ability of the inspector.
Paper information:[Scientific Reports] Selective detections of single-viruses using solid-state nanopores
