A hand-held, real-time, AI-assisted capillary convection PCR system for point-of-care diagnosis of African swine fever virus

Abstract

A hand-held, low-cost and real-time convection polymerase chain reaction (CPCR) system is developed for point-of-care diagnosis of African swine fever (ASF) virus. In CPCR amplification, the reagent is transferred to denaturation, annealing and extension stages of the reaction repeatedly due to thermal convection. Two different modes of fiber-based optical detection are compared, and it shows that the detection sensitivity, repeatability, and consistency can be significantly improved with bottom collection comparing to sidewall collection. Each capillary tube is illuminated by its own LED from the top through a common optical filter, and meanwhile, a camera equipped with another optical filter is adopted to detect the fluorescence signal from optical fibers. To handle the untypical real-time fluorescence curves of negative tests due to non-specific amplification, AI-based classification methods, for example, artificial neural network (ANN) is adopted to improve the detection specificity up to 97.50% comparing to 47.5% or 75.0% which is achieved with Ct-based method. A smartphone is adopted to run the AI algorithm and custom software, as well as to report an ASF event with the geographical information. Experimental results show that with the hand-held CPCR system, within 30 min, ASF viruses can be successfully detected with acceptable sensitivity and specificity.