Source abstract
Abstract
Abstract Single‐cell encapsulation in droplet microfluidics has become a powerful tool in precision medicine, single‐cell analysis, and immunotherapy. However, droplet generation with a single‐cell encapsulation is a random process, which also results in a large number of empty and multi‐cell droplets. Current microfluidics sorting technologies suffer from drawbacks such as fluorescent labeling, inability to remove multi‐cell droplets, or low throughput. This paper presents a gray‐level guided image‐activated droplet sorter (GL‐IADS), which enables label‐free, high‐accuracy screening of single‐cell droplets by rejecting empty and multi‐cell droplets. The gray‐level based recognition method can accurately classify droplet images (empty, single‐cell, and multi‐cell droplets), especially in differentiating empty and cell‐laden droplets (accuracy of 100%). Crucially, this method reduces the image processing time to ≈300 µs, which makes the GL‐IADS possible to reach an ultra‐high sorting throughput up to hundreds or even KHz. The GL‐IADS integrates the novel recognition method with a detachable acoustofluidic system, achieving sorting purity of 97.9%, 97.4%, and >99% for single‐cell, multi‐cell, and cell‐laden droplets, respectively, with a throughput of 43 Hz. The GL‐IADS holds promise for numerous biological applications that are previously difficult with fluorescence‐based technologies.
Source: crossref · Quality: baseline
Affiliations
Department of Biomedical Engineering City University of Hong Kong Hong Kong SAR China
National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Institute of Robotics and Automatic Information System (IRAIS) Nankai University Tianjin 300350 China
Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen 518083 China
Funding
National Natural Science Foundation of China