We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
Radcal IBA  Group

Download Mobile App





Machine Learning Algorithm for Identifying Single Virus Particles Could Lead to More Accurate, Fast COVID-19 Test

By HospiMedica International staff writers
Posted on 30 Nov 2020
A new system for single-virion identification of common respiratory pathogens that uses a machine learning algorithm trained on changes in current across silicon nanopores may lead to fast and accurate screening tests for diseases like COVID-19 and influenza.

Scientists at Osaka University (Suita, Japan) have introduced a new system using silicon nanopores sensitive enough to detect even a single virus particle when coupled with a machine learning algorithm. More...
In this method, a silicon nitride layer just 50 nm thick suspended on a silicon wafer has tiny nanopores added, which are themselves only 300 nm in diameter. When a voltage difference is applied to the solution on either side of the wafer, ions travel through the nanopores in a process called electrophoresis. The motion of the ions can be monitored by the current they generate, and when a viral particle enters a nanopore, it blocks some of the ions from passing through, leading to a transient dip in current. Each dip reflects the physical properties of the particle, such as volume, surface charge, and shape, so they can be used to identify the kind of virus.

The natural variation in the physical properties of virus particles had previously hindered implementation of this approach. However, using machine learning, the team built a classification algorithm trained with signals from known viruses to determine the identity of new samples. The computer can discriminate the differences in electrical current waveforms that cannot be identified by human eyes, which enables highly accurate virus classification. In addition to coronavirus, the system was tested with similar pathogens - respiratory syncytial virus, adenovirus, influenza A, and influenza B. The team believes that coronaviruses are especially well-suited for this technique since their spiky outer proteins may even allow different strains to be classified separately. Compared with other rapid viral tests like polymerase chain reaction or antibody-based screens, the new method is much faster and does not require costly reagents, which may lead to improved diagnostic tests for emerging viral particles that cause infectious diseases such as COVID-19.

“By combining single-particle nanopore sensing with artificial intelligence, we were able to achieve highly accurate identification of multiple viral species,” said senior author Makusu Tsutsui.

“This work will help with the development of a virus test kit that outperforms conventional viral inspection methods,” added last author Tomoji Kawai.

Related Links:
Osaka University


Gold Member
POC Blood Gas Analyzer
Stat Profile Prime Plus
Gold Member
12-Channel ECG
CM1200B
New
Medical Cart
Medical Carts
New
Multifunctional Patient Floor Lift
Maxi Move 5
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to HospiMedica.com and get access to news and events that shape the world of Hospital Medicine.
  • Free digital version edition of HospiMedica International sent by email on regular basis
  • Free print version of HospiMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of HospiMedica International in digital format
  • Free HospiMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Critical Care

view channel
Image: the deep tissue in vivo sound printing (DISP) platform, which combines ultrasound with low-temperature–sensitive liposomes loaded with crosslinking agents (Photo courtesy of Elham Davoodi and Wei Gao/Caltech)

New Ultrasound-Guided 3D Printing Technique to Help Fabricate Medical Implants

3D bioprinting technologies hold considerable promise for advancing modern medicine by enabling the production of customized implants, intricate medical devices, and engineered tissues designed to meet... Read more

Surgical Techniques

view channel
Image: The engine-free, nonlinear, flexible, micro-robotic platform leverages AI to optimize GBM treatment (Photo courtesy of Symphony Robotics)

First-Ever MRI-Steerable Micro-Robotics to Revolutionize Glioblastoma Treatment

Glioblastoma Multiforme (GBM) is one of the most aggressive and difficult-to-treat brain cancers. Traditional surgical procedures, such as craniotomies, involve significant invasiveness, requiring large... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.