Study On Rapid Detection Method And Device Of Nucleic Acid Based On Microfluidics

Since the end of 2019,coronavirus disease 2019(COVID-19)has spread all over the world,posing a serious threat to global public health security.Therefore,it is significant and valuable to study various nucleic acid rapid detection technologies and devices.As rapid nucleic acid detection technology,isothermal amplification technology has the advantages of short detection time and simple temperature control.Convection polymerase chain reaction(CPCR)technology can significantly shorten the reaction time of PCR amplification by the thermal circulation generated by constant temperature heating.Based on isothermal amplification and CPCR,the paper studied two types of rapid nucleic acid detection method and device by microfluidic technology:A paper-based microfluidic chip based on RPA isothermal amplification technology was studied and implemented.Combining paper-based microfluidic technology and isothermal amplification technology,the chip can simplify fluid control and shorten reaction time.Reagent mixing is achieved by microbeads and Z-microchannels,ensuring amplification efficiency.The chip can achieve two-step isothermal amplification detection,significantly improving detection sensitivity;in the second amplification reaction,multiple paper-based amplification chambers are constructed,and multiple detection is achieved.The performance of isothermal paper-based chip was preliminarily verified by two-step multiple amplification detection on multiple target samples.A hand-held,low-cost CPCR detection system was studied and implemented.Based on the principle of CPCR,the system constructs stable thermal convection in the reaction tube with the simplified constant heating,thereby achieving PCR amplification.In order to improve the detection performance,fluorescence detection methods were improved,and the differences between bottom collection and side-wall collection have been compared and analyzed.The fluorescence signal is transmitted to the camera through optical fibers,and the camera collects fluorescence images in real time.After image processing,the fluorescence data is obtained,which is transmitted to the smartphone through Bluetooth.The smartphone is adopted to run the classification algorithm which combines traditional method and artificial intelligence algorithm,improving the detection specificity to 97.5%.Up to 8 ASFV samples with the concentration down to 500 copies/m L can be successfully detected in 30 min with the hand-held CPCR system.In order to improve the accuracy of negative/positive results interpretation in multimodal amplification of CPCR,slope classification algorithm and machine learning based classification algorithms were studied based on the traditional Ct methods.The slope classification algorithm improves classification sensitivity and specificity to 95.3% and 91% by analyzing multiple specific slopes of the amplification curve.Machine learning based classification algorithms improve classification sensitivity and specificity to 99.46% and 99.11% through data dimensionality reduction,parameter optimization,and artificial intelligence modeling.In addition,taking for example that fluorescence crosstalk of multiple isothermal amplification in single tube,a simplified fluorescence crosstalk correction method was studied.With the least square algorithm,the effective correction of fluorescence detection crosstalk in a single reaction system was achieved.