Lee Keondo, Kim Seong-Eun, Nam Seokho, Doh Junsang, Chung Wan Kyun
Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang 37673, Republic of Korea.
Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea.
Micromachines (Basel). 2022 Nov 29;13(12):2105. doi: 10.3390/mi13122105.
Image-based cell sorting is essential in biological and biomedical research. The sorted cells can be used for downstream analysis to expand our knowledge of cell-to-cell differences. We previously demonstrated a user-friendly image-activated microfluidic cell sorting technique using an optimized and fast deep learning algorithm. Real-time isolation of cells was carried out using this technique with an inverted microscope. In this study, we devised a recently upgraded sorting system. The cell sorting techniques shown on the microscope were implemented as a real system. Several new features were added to make it easier for the users to conduct the real-time sorting of cells or particles. The newly added features are as follows: (1) a high-resolution linear piezo-stage is used to obtain in-focus images of the fast-flowing cells; (2) an LED strobe light was incorporated to minimize the motion blur of fast-flowing cells; and (3) a vertical syringe pump setup was used to prevent the cell sedimentation. The sorting performance of the upgraded system was demonstrated through the real-time sorting of fluorescent polystyrene beads. The sorter achieved a 99.4% sorting purity for 15 μm and 10 μm beads with an average throughput of 22.1 events per second (eps).
基于图像的细胞分选在生物学和生物医学研究中至关重要。分选后的细胞可用于下游分析，以扩展我们对细胞间差异的认识。我们之前展示了一种使用优化的快速深度学习算法的用户友好型图像激活微流控细胞分选技术。使用该技术通过倒置显微镜对细胞进行实时分离。在本研究中，我们设计了一种最近升级的分选系统。显微镜上展示的细胞分选技术被实现为一个实际系统。添加了几个新功能，以便用户更轻松地对细胞或颗粒进行实时分选。新添加的功能如下：（1）使用高分辨率线性压电平台获取快速流动细胞的对焦图像；（2）加入LED频闪灯以最小化快速流动细胞的运动模糊；（3）使用垂直注射泵设置以防止细胞沉降。通过对荧光聚苯乙烯微珠的实时分选展示了升级后系统的分选性能。该分选仪对15μm和10μm微珠的分选纯度达到99.4%，平均通量为每秒22.1个事件（eps）。
