Smart MoleculesBioengineeringPeer-reviewed journal article
A COVID-19 Rapid Antigen Test Employing Upconversion Nanoparticles
Le ZhangiD, Jiajia ZhouiD, Olga ShimoniiD, Shihui WeniD, Amani AlghalayiniiD, Yuan LiuiD, Meysam Rezaeishahmirzadi, Jiayan LiaoiD, Mahnaz MaddahfariD, Roger Hunt, Murdo Black, Matt D. JohanseniD, Philip M. HansbroiD, Lin ZhangiD, Martina H. StenzeliD, Majid Ebrahimi WarkianiiD, Stella M. ValenzuelaiD, Dayong JiniD
Abstract
The COVID-19 pandemic has underscored the critical need for rapid and accurate diagnostic tools. Current methods, including PCR and rapid antigen tests (RAT), have limitations in speed, sensitivity, and the requirement for specialized equipment and trained personnel. Nanotechnology, particularly upconversion nanoparticles (UCNPs), offer a promising alternative due to their unique optical properties. UCNPs can convert low-energy near-infrared (NIR) light into higher-energy visible light, making them ideal for use as optical probes in single molecule detection and point of care applications. This study, initiated in early 2020, explores the opportunity of using highly doped UCNPs (40%Yb3+/4%Er3+) in lateral flow assay (LFA) for the early diagnosis of COVID-19. The UCNPs-based LFA testing demonstrated a minimum detection concentration of 100 pg/mL for SARS-CoV-2 antigen and 105 CCID50/mL for inactivated virus. Clinical trials, conducted in Malaysia and Western Australia independently, showed that the technique was at least 100 times more sensitive than commercial RAT kits, with a sensitivity of 100% and specificity of 91.34%. The development process involved multidisciplinary collaborations, resulting in the Virulizer device, an automated strip reader for point-of-care testing. This work sets a reference for future development of highly sensitive and quantitative rapid antigen tests, aiming for the Limits of Detection (LoD) in the range of sub-ng/mL.
- research focus: host-pathogen & immune response
- research focus: dimensionality reduction
- approach: experimental assay
- Citations
- 8
- FWCI
- 4.47
- Field percentile
- top 6%
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