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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 (μSFC), 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 μSFC and commercial machines for the label free characterization of polymeric beads with different diameters and refractive indices. In contrast to FCM and FACS, the μSFC 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 μSFC 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 μSFC 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.

A multichannel microfluidic platform for real-time monitoring of epithelial barrier integrity by electrical impedance has been developed. Growth and polarization of human epithelial cells from the airway or gastrointestinal tract was continuously monitored over 5 days in 8 parallel, individually perfused microfluidic chips. Electrical impedance data were continuously recorded to monitor cell barrier formation using a low-cost bespoke impedance analyser. Data was analysed using an electric circuit model to extract the equivalent transepithelial electrical resistance and epithelial cell layer capacitance. The cell barrier integrity steadily increased overtime, achieving an average resistance of 418 ± 121 Ω cm 2 (airway cells) or 207 ± 59 Ω cm 2 (gastrointestinal cells) by day 5. The utility of the polarized airway epithelial barrier was demonstrated using a 24 hour challenge with double stranded RNA to mimic viral infection. This caused a rapid decrease in barrier integrity in association with disruption of tight junctions, whereas simultaneous treatment with a corticosteroid reduced this effect. The platform is able to measure barrier integrity in real-time and is scalable, thus has the potential to be used for drug development and testing.

Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell analysis. Multi-frequency impedance measurements provide data that allows full characterisation of cells, linking electrical phenotype to individual biophysical properties. To efficiently extract the information embedded in the electrical signals, potentially in real-time, tailored signal processing is needed. Artificial intelligence approaches provide a promising new direction. Here we demonstrate the ability of neural networks to decipher impedance cytometry signals in two challenging scenarios: (i) to determine the intrinsic dielectric properties of single cells directly from raw impedance data streams, (ii) to capture single-cell signals that are hidden in the measured signals of coincident cells. The accuracy of the results and the high processing speed (fractions of ms per cell) demonstrate that neural networks can have an important role in impedance-based single-cell analysis.

We present an innovative impedance cytometer for the measurement of the cross-sectional position of single particles or cells flowing in a microchannel. As predicted by numerical simulations and experimentally validated, the proposed approach is applicable to particles/cells with either spherical or non-spherical shape. In particular, the optics-free high-throughput position detection of individual flowing red blood cells (RBCs) is demonstrated and applied to monitor RBCs hydrodynamic focusing under different sheath flow conditions. Moreover, the device provides multiparametric information useful for lab-on-a-chip applications, including particle inter-arrival times and velocity profile, as well as RBCs mean corpuscular volume, distribution width and electrical opacity.