UBC Theses and Dissertations
Development of smartphone-based flow cytometry for selective cell counting Xiao, Zhujun
Quantum dots (QDs) are promising bioanalytical tools because of their outstanding optical properties, especially their bright and narrow photoluminescence, which offers capacity for multiplexed imaging. Along with flow cytometry, QDs of various colours allow for the detection and enumeration of multiple cell types simultaneously, which is critical for early and efficient screening for diseases, including cancers. Flow cytometry is widely recognized as the “gold-standard” technique for cell classification; however, the cost, size, and sophistication of the method make it unsuitable for use outside of specialized laboratories. A flow cytometry format amenable to point-of-care (POC) application thus has the potential to greatly increase its utility for diagnostics and health care. This thesis developed a smartphone-based flow cytometer by integrating a laser diode, a PDMS microfluidic chip, and a magnification system into a compact 3D-printed box that interfaced with a smartphone and its camera. Silica-quantum dot (SiO₂@QD) supra-nanoparticles were coated with either dextran or carboxymethyl dextran (CM-Dex), then conjugated to antibodies targeting different cell-surface antigens via tetrameric antibody complexes (TACs) or carbodiimide chemistry. Selective enumeration of multiple cancer cell lines was achieved by immunolabeling with a combination of red, orange, yellow, or green SiO₂@(QD-CM-Dex)-antibody conjugates. Smartphone videos of labeled cells under flow were analyzed with an algorithm in MATLAB that extracted PL colour features, classified the cells with a support vector machine model, and counted the cells. Future work with this prototype smartphone-based flow cytometer will aim to improve sensitivity, expand the classification and enumeration capabilities, and test its application with clinical samples.
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