4.7 Article

A low-cost, label-free microfluidic scanning flow cytometer for high-accuracy quantification of size and refractive index of particles

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LAB ON A CHIP
卷 23, 期 8, 页码 2039-2047

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ROYAL SOC CHEMISTRY
DOI: 10.1039/d2lc01179d

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This article introduces a microfluidic scanning flow cytometer (mu SFC) that can achieve accurate angle-resolved scattering measurements within a standard polydimethylsiloxane microfluidic chip. In contrast to conventional flow cytometers and fluorescence activated cell sorters, the mu SFC yields linearly correlated size estimates and quantitative refractive index estimates for particles, making it suitable for characterizing biological samples and potentially applicable in diagnostic settings.
Flow cytometers and fluorescence activated cells sorters (FCM/FACS) represent the gold standard for high-throughput single-cell analysis, but their usefulness for label-free applications is limited by the unreliability of forward and side scatter measurements. Scanning flow cytometers represent an appealing alternative, as they exploit measurements of the angle-resolved scattered light to provide accurate and quantitative estimates of cellular properties, but the requirements of current setups are unsuitable for integration with other lab-on-chip technologies or for point-of-care applications. Here we present the first microfluidic scanning flow cytometer (mu SFC), able to achieve accurate angle-resolved scattering measurements within a standard polydimethylsiloxane microfluidic chip. The system exploits a low cost linearly variable optical density (OD) filter to reduce the dynamic range of the signal and to increase its signal-to-noise ratio. We present a performance comparison between the mu SFC and commercial machines for the label free characterization of polymeric beads with different diameters and refractive indices. In contrast to FCM and FACS, the mu SFC yields size estimates linearly correlated with nominal particle sizes (R-2 = 0.99) and quantitative estimates of particle refractive indices. The feasibility of using the mu SFC for the characterization of biological samples is demonstrated by analyzing a population of monocytes identified based on the morphology of a peripheral blood mononuclear cells sample, which yields values in agreement with the literature. The proposed mu SFC combines low setup requirements with high performance, and has great potential for integration within other lab-on-chip systems for multi-parametric cell analysis and for next-generation point-of-care diagnostic applications.

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