Dr. Mahmut Kamil Aslan and colleagues in the deMello group have developed an innovative smartphone-based imaging flow cytometer. Imaging flow cytometry combines the high-throughput nature of a conventional flow cytometry with single-cell imaging capabilities. A small number of commercial imaging flow cytometers are available in the market, but are limited in terms of their analytical throughput and are extremely expensive. To address both these issues, Mahmut and colleagues developed a portable imaging flow cytometer that uses a mid-range smartphone as the central optical and electronic component. The cytometer is able to enumerate and image cells at rates exceeding 65,000 cells/s; a 20-fold improvement over commercial high-end imaging flow cytometers. The platform also comprises a SmartFlow app that integrates a GUI and can acquire, process and display bright-field images in real-time. Significantly, the flow cytometer can extract high-resolution bright-field images with a spatial resolution <700 nm and through the of machine learning algorithms can classify mixed-cell populations via size and morphology measurements. In the future, the team hopes to test the cytometer in resource-limited settings and will provide an open-source app customizable to different diagnostic applications.
Written by Eunhee Cho
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