Selective cell capture and analysis using shallow antibody-coated microchannels

Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Convolutional Neural Network

Understanding the intricacies of particle-cell interactions is essential for many applications such as imaging, phototherapy, and drug/gene delivery, because it is the key to accurate control of the particle properties for the improvement of their therapeutic and diagnostic efficiency. Recently, high-throughput methods have emerged for the detailed investigation of these interactions. For example, imaging flow cytometry (IFC) collects up to 60,000 images of cells per second (in 12 optical channels) and provides information about morphology and organelle localization in combination with fluorescence and side scatter intensity data. However, analysis of IFC data is extremely difficult to perform using conventional methods that calculate integral parameters or use mask-based object recognition. Here, we show application of a convolutional neural network (CNN) for precise quantitative analysis of particle targeting of cells using IFC data. CNN provides high-throughput object detection with almost human precision but avoids the subjective choice of image processing parameters that often leads to incorrect data interpretation. The method allows accurate counting of cell-bound particles with reliable discrimination from the nonbound particles in the field of view. The proposed method expands capabilities of spot counting applications (such as organelle counting, quantification of cell-cell and cell-bacteria interactions) and is going to be useful not only for high-throughput analysis of IFC data but also for other imaging techniques. © 2019 International Society for Advancement of Cytometry.

Advances in microfluidic cell separation and manipulation

Cellular separations are required in many contexts in biochemical and biomedical applications for the identification, isolation, and analysis of phenotypes or samples of interest. Microfluidics is uniquely suited for handling biological samples, and emerging technologies have become increasingly accessible tools for researchers and clinicians. Here, we review advances in the last few years in techniques for microfluidic cell separation and manipulation. Applications such as high-throughput cell and organism phenotypic screening, purification of heterogeneous stem cell populations, separation of blood components, and isolation of rare cells in patients highlight some of the areas in which these technologies show great potential. Continued advances in separation mechanisms and understanding of cellular systems will yield further improvements in the throughput, resolution, and robustness of techniques.