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

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 (R2 = 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.

Extensional-Flow Impedance Cytometer for Contactless and Optics-Free Erythrocyte Deformability Analysis.

OBJECTIVE: Deformability is an essential feature of red blood cells (RBCs), enabling them to undergo significant shape change in response to external forces. Impaired erythrocyte deformability is associated with several pathologic conditions, and quantitative measurement of RBC deformability is critical to understanding and diagnosing RBC related diseases. Whereas traditional approaches to cell mechanical characterization generally have limited throughput, emerging microscale technologies are opening new opportunities for high-throughput deformability cytometry at the single-cell level. METHODS: In this work, we propose an innovative microfluidic system based on (i) a hyperbolic microchannel to induce erythrocyte deformation by extensional flow, and (ii) an electrical sensing zone with coplanar electrodes to evaluate the deformed cell shape. RESULTS: RBC deformation under extensional flow is achieved, and the deformed cell shape is quantified by means of an electrical anisotropy index, at a throughput of 300 cell/s. Measurements of healthy and chemically stiffened RBCs demonstrate that the anisotropy index can be used to characterize RBC deformability, as an alternative to deformation indices based on high-speed image processing. CONCLUSION: A contactless and optics-free approach for RBC deformability analysis has been presented. SIGNIFICANCE: Due to its simplicity and potential for integration, the proposed approach holds promises for fast and low-cost erythrocyte deformability assays, especially in point-of-care and resource-limited settings.

Real-time monitoring of epithelial barrier function by impedance spectroscopy in a microfluidic platform.

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 cm2 (airway cells) or 207 ± 59 Ω cm2 (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.

Deciphering impedance cytometry signals with neural networks.

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.

Electro-Optical Classification of Pollen Grains via Microfluidics and Machine Learning.

OBJECTIVE: In aerobiological monitoring and agriculture there is a pressing need for accurate, label-free and automated analysis of pollen grains, in order to reduce the cost, workload and possible errors associated to traditional approaches. METHODS: We propose a new multimodal approach that combines electrical sensing and optical imaging to classify pollen grains flowing in a microfluidic chip at a throughput of 150 grains per second. Electrical signals and synchronized optical images are processed by two independent machine learning-based classifiers, whose predictions are then combined to provide the final classification outcome. RESULTS: The applicability of the method is demonstrated in a proof-of-concept classification experiment involving eight pollen classes from different taxa. The average balanced accuracy is 78.7% for the electrical classifier, 76.7% for the optical classifier and 84.2% for the multimodal classifier. The accuracy is 82.8% for the electrical classifier, 84.1% for the optical classifier and 88.3% for the multimodal classifier. CONCLUSION: The multimodal approach provides better classification results with respect to the analysis based on electrical or optical features alone. SIGNIFICANCE: The proposed methodology paves the way for automated multimodal palynology. Moreover, it can be extended to other fields, such as diagnostics and cell therapy, where it could be used for label-free identification of cell populations in heterogeneous samples.

A Bayesian Approach for Coincidence Resolution in Microfluidic Impedance Cytometry.

OBJECTIVE: Cell counting and characterization is fundamental for medicine, science and technology. Coulter-type microfluidic devices are effective and automated systems for cell/particle analysis, based on the electrical sensing zone principle. However, their throughput and accuracy are limited by coincidences (i.e., two or more particles passing through the sensing zone nearly simultaneously), which reduce the observed number of particles and may lead to errors in the measured particle properties. In this work, a novel approach for coincidence resolution in microfluidic impedance cytometry is proposed. METHODS: The approach relies on: (i) a microchannel comprising two electrical sensing zones and (ii) a model of the signals generated by coinciding particles. Maximum a posteriori probability (MAP) estimation is used to identify the model parameters and therefore characterize individual particle properties. RESULTS: Quantitative performance assessment on synthetic data streams shows a counting sensitivity of 97% and a positive predictive value of 99% at concentrations of 2×106 particles/ml. An application to red blood cell analysis shows accurate particle characterization up to a throughput of about 2500 particles/s. An original formula providing the expected number of coinciding particles is derived, and good agreement is found between experimental results and theoretical predictions. CONCLUSION: The proposed cytometer enables the decomposition of signals generated by coinciding particles into individual particle contributions, by using a Bayesian approach. SIGNIFICANCE: This system can be profitably used in applications where accurate counting and characterization of cell/particle suspensions over a broad range of concentrations is required.

A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry.

Microfluidic applications such as active particle sorting or selective enrichment require particle classification techniques that are capable of working in real time. In this paper, we explore the use of neural networks for fast label-free particle characterization during microfluidic impedance cytometry. A recurrent neural network is designed to process data from a novel impedance chip layout for enabling real-time multiparametric analysis of the measured impedance data streams. As demonstrated with both synthetic and experimental datasets, the trained network is able to characterize with good accuracy size, velocity, and cross-sectional position of beads, red blood cells, and yeasts, with a unitary prediction time of 0.4 ms. The proposed approach can be extended to other device designs and cell types for electrical parameter extraction. This combination of microfluidic impedance cytometry and machine learning can serve as a stepping stone to real-time single-cell analysis and sorting. Graphical Abstract.

High-throughput label-free characterization of viable, necrotic and apoptotic human lymphoma cells in a coplanar-electrode microfluidic impedance chip.

The study and the characterization of cell death mechanisms are fundamental in cell biology research. Traditional death/viability assays usually involve laborious sample preparation and expensive equipment or reagents. In this work, we use electrical impedance spectroscopy as a label-free methodology to characterize viable, necrotic and apoptotic human lymphoma U937 cells. A simple three-electrode coplanar layout is used in a differential measurement scheme and thousands of cells are measured at high-throughput (≈200 cell/s). Tailored signal processing enables accurate and robust cell characterization without the need for cell focusing systems. The results suggest that, at low frequency (0.5 MHz), signal magnitude enables the discrimination between viable/necrotic cells and cell fragments, whereas phase information allows discriminating between viable cells and necrotic cells. At higher frequency (10 MHz) two subpopulations of cell fragments are distinguished. This work substantiates the prominent role of electrical impedance spectroscopy for the development of next-generation cell viability assays.

High-throughput electrical position detection of single flowing particles/cells with non-spherical shape.

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.

A simple electrical approach to monitor dielectrophoretic focusing of particles flowing in a microchannel.

This paper reports an impedance-based system for the quantitative assessment of dielectrophoretic (DEP) focusing of single particles flowing in a microchannel. Particle lateral positions are detected in two electrical sensing zones placed before and after a DEP-focusing region, respectively. In each sensing zone, particle lateral positions are estimated using the unbalance between the opposite pulses of a differential current signal obtained with a straightforward coplanar electrode configuration. The system is used to monitor the focusing of polystyrene beads of 7 or 10 µm diameter, under various conditions of DEP field intensities and flow rates that produce different degrees of focusing. This electrical approach represents a simple and valuable alternative to optical methods for monitoring of particle focusing systems.

Cellular crosstalk between airway epithelial and endothelial cells regulates barrier functions during exposure to double-stranded RNA.

INTRODUCTION: The epithelial and endothelial barriers of the airway mucosa are critical for regulation of tissue homeostasis and protection against pathogens or other tissue damaging agents. In response to a viral infection, epithelial cells must signal to the endothelium to initiate immune cell recruitment. This is a highly temporal regulated process; however, the mechanisms of this cross-talk are not fully understood. METHODS: In a close-contact co-culture model of human airway epithelial and endothelial cells, cellular crosstalk was analyzed using transepithelial electrical resistance (TER) measurements, immunofluorescence, electron microscopy, and ELISA. Viral infections were simulated by exposing airway epithelial cells apically to double-stranded RNA (Poly(I:C)). Using a microfluidic culture system, the temporal release of mediators was analyzed in the co-culture model. RESULTS: Within 4 h of challenge, double-stranded RNA induced the release of TNF-α by epithelial cells. This activated endothelial cells by triggering the release of the chemoattractant CX3CL1 (fractalkine) by 8 h post-challenge and expression of adhesion molecules E-selectin and ICAM-1. These responses were significantly reduced by neutralising TNF-α. CONCLUSION: By facilitating kinetic profiling, the microfluidic co-culture system has enabled identification of a key signaling mechanism between the epithelial and endothelial barriers. Better understanding of cell-cell cross-talk and its regulatory mechanisms has the potential to identify new therapeutic strategies to control airway inflammation.

Numerical Investigation of a Novel Wiring Scheme Enabling Simple and Accurate Impedance Cytometry.

Microfluidic impedance cytometry is a label-free approach for high-throughput analysis of particles and cells. It is based on the characterization of the dielectric properties of single particles as they flow through a microchannel with integrated electrodes. However, the measured signal depends not only on the intrinsic particle properties, but also on the particle trajectory through the measuring region, thus challenging the resolution and accuracy of the technique. In this work we show via simulation that this issue can be overcome without resorting to particle focusing, by means of a straightforward modification of the wiring scheme for the most typical and widely used microfluidic impedance chip.

Temporal Monitoring of Differentiated Human Airway Epithelial Cells Using Microfluidics.

The airway epithelium is exposed to a variety of harmful agents during breathing and appropriate cellular responses are essential to maintain tissue homeostasis. Recent evidence has highlighted the contribution of epithelial barrier dysfunction in the development of many chronic respiratory diseases. Despite intense research efforts, the responses of the airway barrier to environmental agents are not fully understood, mainly due to lack of suitable in vitro models that recapitulate the complex in vivo situation accurately. Using an interdisciplinary approach, we describe a novel dynamic 3D in vitro model of the airway epithelium, incorporating fully differentiated primary human airway epithelial cells at the air-liquid interface and a basolateral microfluidic supply of nutrients simulating the interstitial flow observed in vivo. Through combination of the microfluidic culture system with an automated fraction collector the kinetics of cellular responses by the airway epithelium to environmental agents can be analysed at the early phases for the first time and with much higher sensitivity compared to common static in vitro models. Following exposure of primary differentiated epithelial cells to pollen we show that CXCL8/IL-8 release is detectable within the first 2h and peaks at 4-6h under microfluidic conditions, a response which was not observed in conventional static culture conditions. Such a microfluidic culture model is likely to have utility for high resolution temporal profiling of toxicological and pharmacological responses of the airway epithelial barrier, as well as for studies of disease mechanisms.

Human aquaporin 4 gating dynamics under and after nanosecond-scale static and alternating electric-field impulses: a molecular dynamics study of field effects and relaxation.

Water self-diffusion and the dipolar response of the selectivity filter within human aquaporin 4 have been studied using molecular dynamics (MD) simulations in the absence and presence of pulses of external static and alternating electric fields. The pulses were approximately 50 and 100 ns in duration and 0.0065 V/Å in (r.m.s.) intensity and were either static or else 2.45 or 100 GHz in frequency and applied both along and perpendicular to the channels. In addition, the relaxation of the aquaporin, water self-diffusion and gating dynamics following cessation of the impulses was studied. In previous work it was determined that switches in the dihedral angle of the selectivity filter led to boosting of water permeation events within the channels, in the presence of identical external static and alternating electric fields, although applied continuously. Here the application of field impulses (and subsequently, upon removal) has shown that it is the dipolar orientation of the histidine-201 residue in the selectivity filter which governs the dihedral angle, and hence influences water self-diffusion; this constitutes an appropriate order parameter. The dipolar response of this residue to the applied field leads to the adoption of four distinct states, which we modelled as time-homogeneous Markov jump processes, and may be distinguished in the potential of mean force (PMF) as a function of the dipolar orientation of histidine-201. The observations of enhanced "dipolar flipping" of H201 serve to explain increased levels of water self-diffusion within aquaporin channels during, and immediately following, field impulses, although the level of statistical certainty here is lower. Given the appreciable size of the energy barriers evident in PMFs computed directly from deterministic MD (whether in the absence or presence of external fields), metadynamics calculations were undertaken to explore the free-energy landscape of histidine-201 orientation with greater accuracy and precision. These indicate that electric fields do alter the free-energy profile of the H201 side-chain orientation, wherein a perturbation of the symmetric bimodal state evident in the zero-field case is observed. These effects are dependent on the field intensities.