Abstract
Methods for the detection, enumeration, and typing of cells are important in many areas of research and healthcare. In this context, flow cytometers are a widely used research and clinical tool but are also an example of a large and expensive instrument that is limited to specialized laboratories. Smartphones have been shown to have excellent potential to serve as portable and lower-cost platforms for analyses that would normally be done in a laboratory. Here, we developed a prototype smartphone-based flow cytometer (FC). This compact 3D-printed device incorporated a laser diode and a microfluidic flow cell and used the built-in camera of a smartphone to track immunofluorescently labeled cells in suspension and measure their color. This capability was enabled by high-brightness supra-nanoparticle assemblies of colloidal semiconductor quantum dots (SiO2@QDs) as well as a support vector machine (SVM) classification algorithm. The smartphone-based FC device detected and enumerated target cells against a background of other cells, simultaneously and selectively counted two different cell types in a mixture, and used multiple colors of SiO2@QD-antibody conjugates to screen for and identify a particular cell type. The potential limits of multicolor detection are discussed alongside ideas for further development. Our results suggest that innovations in materials and engineering should enable eventual smartphone-based FC assays for clinical applications.