Estimation of the physical properties of neurons and glial cells using dielectrophoresis crossover frequency

On-chip dielectrophoretic single-cell manipulation

Bioanalysis at a single-cell level has yielded unparalleled insight into the heterogeneity of complex biological samples. Combined with Lab-on-a-Chip concepts, various simultaneous and high-frequency techniques and microfluidic platforms have led to the development of high-throughput platforms for single-cell analysis. Dielectrophoresis (DEP), an electrical approach based on the dielectric property of target cells, makes it possible to efficiently manipulate individual cells without labeling. This review focusses on the engineering designs of recent advanced microfluidic designs that utilize DEP techniques for multiple single-cell analyses. On-chip DEP is primarily effectuated by the induced dipole of dielectric particles, (i.e., cells) in a non-uniform electric field. In addition to simply capturing and releasing particles, DEP can also aid in more complex manipulations, such as rotation and moving along arbitrary predefined routes for numerous applications. Correspondingly, DEP electrodes can be designed with different patterns to achieve different geometric boundaries of the electric fields. Since many single-cell analyses require isolation and compartmentalization of individual cells, specific microstructures can also be incorporated into DEP devices. This article discusses common electrical and physical designs of single-cell DEP microfluidic devices as well as different categories of electrodes and microstructures. In addition, an up-to-date summary of achievements and challenges in current designs, together with prospects for future design direction, is provided.

A boundary element method of bidomain modeling for predicting cellular responses to electromagnetic fields

Objective.Commonly used cable equation approaches for simulating the effects of electromagnetic fields on excitable cells make several simplifying assumptions that could limit their predictive power. Bidomain or 'whole' finite element methods have been developed to fully couple cells and electric fields for more realistic neuron modeling. Here, we introduce a novel bidomain integral equation designed for determining the full electromagnetic coupling between stimulation devices and the intracellular, membrane, and extracellular regions of neurons.Approach.Our proposed boundary element formulation offers a solution to an integral equation that connects the device, tissue inhomogeneity, and cell membrane-induced E-fields. We solve this integral equation using first-order nodal elements and an unconditionally stable Crank-Nicholson time-stepping scheme. To validate and demonstrate our approach, we simulated cylindrical Hodgkin-Huxley axons and spherical cells in multiple brain stimulation scenarios.Main Results.Comparison studies show that a boundary element approach produces accurate results for both electric and magnetic stimulation. Unlike bidomain finite element methods, the bidomain boundary element method does not require volume meshes containing features at multiple scales. As a result, modeling cells, or tightly packed populations of cells, with microscale features embedded in a macroscale head model, is simplified, and the relative placement of devices and cells can be varied without the need to generate a new mesh.Significance.Device-induced electromagnetic fields are commonly used to modulate brain activity for research and therapeutic applications. Bidomain solvers allow for the full incorporation of realistic cell geometries, device E-fields, and neuron populations. Thus, multi-cell studies of advanced neuronal mechanisms would greatly benefit from the development of fast-bidomain solvers to ensure scalability and the practical execution of neural network simulations with realistic neuron morphologies.

A Boundary Element Method of Bidomain Modeling for Predicting Cellular Responses to Electromagnetic Fields

Objective

Commonly used cable equation-based approaches for determining the effects of electromagnetic fields on excitable cells make several simplifying assumptions that could limit their predictive power. Bidomain or "whole" finite element methods have been developed to fully couple cells and electric fields for more realistic neuron modeling. Here, we introduce a novel bidomain integral equation designed for determining the full electromagnetic coupling between stimulation devices and the intracellular, membrane, and extracellular regions of neurons.

Methods

Our proposed boundary element formulation offers a solution to an integral equation that connects the device, tissue inhomogeneity, and cell membrane-induced E-fields. We solve this integral equation using first-order nodal elements and an unconditionally stable Crank-Nicholson time-stepping scheme. To validate and demonstrate our approach, we simulated cylindrical Hodgkin-Huxley axons and spherical cells in multiple brain stimulation scenarios.

Main Results

Comparison studies show that a boundary element approach produces accurate results for both electric and magnetic stimulation. Unlike bidomain finite element methods, the bidomain boundary element method does not require volume meshes containing features at multiple scales. As a result, modeling cells, or tightly packed populations of cells, with microscale features embedded in a macroscale head model, is made computationally tractable, and the relative placement of devices and cells can be varied without the need to generate a new mesh.

Significance

Device-induced electromagnetic fields are commonly used to modulate brain activity for research and therapeutic applications. Bidomain solvers allow for the full incorporation of realistic cell geometries, device E-fields, and neuron populations. Thus, multi-cell studies of advanced neuronal mechanisms would greatly benefit from the development of fast-bidomain solvers to ensure scalability and the practical execution of neural network simulations with realistic neuron morphologies.

Dielectrophoretic profiling of erythrocytes to study the impacts of metabolic stress, temperature, and storage duration utilizing a point-and-planar microdevice

Dielectrophoresis (DEP) is widely utilized for trapping and sorting various types of cells, including live and dead cells and healthy and infected cells. This article focuses on the dielectric characterization of erythrocytes (red blood cells or RBCs) by quantifying DEP crossover frequency using a novel point-and-planar microwell device platform. Numerical simulations using COMSOL Multiphysics software demonstrate that the distribution of the DEP force is influenced by factors such as the shape of the point electrode, spacing between the point and planar electrodes, and the type of bioparticle being investigated. The dependency on electrode spacing is experimentally evaluated by analyzing the DEP crossover response of erythrocytes. Furthermore, the results are validated against the traditional electrical characterization technique called electrorotation, which typically requires laborious fabrication and operation using quadrupole electrodes. Other significant factors, including erythrocyte storage age and the changes in cell properties over time since collection, osmolarity, and temperature, are also assessed to determine the optimal conditions for erythrocyte characterization. The findings indicate a significant difference between fresh and stored erythrocyte samples (up to 4 days), highlighting the importance of maintaining an isotonic medium for cell storage.

Blue-Light-Blocking Lenses Ameliorate Structural Alterations in the Rodent Hippocampus

Evidence suggests that prolonged blue-light exposure can impact vision; however, less is known about its impact on non-visual higher-order functions in the brain, such as learning and memory. Blue-light-blocking lenses (BBLs) claim to reduce these potential impacts. Hence, we assessed structural and functional hippocampal alterations following blue-light exposure and the protective efficacy of BBLs. Male Wistar rats were divided into (n = 6 in each group) normal control (NC), blue-light exposure (LE), and blue-light with BBLs (Crizal Prevencia, CP and DuraVision Blue, DB) groups. After 28 days of light exposure (12:12 light: dark cycle), rats were trained for the Morris water maze memory retention test, and brain tissues were sectioned for hippocampal neuronal analysis using Golgi and Cresyl violet stains. The memory retention test was significantly delayed (p < 0.05) in LE compared with DB groups on day 1 of training. Comparison of Golgi-stained neurons showed significant structural alterations, particularly in the basal dendrites of hippocampal neurons in the LE group, with BBLs significantly mitigating these structural changes (p < 0.05). Comparison of Cresyl-violet-stained neurons revealed significantly (p < 0.001) increased degenerated hippocampal neurons in LE rats, with fewer degenerated neurons in the CP lens group for CA1 neurons (p < 0.05), and for both CP and DB groups (p < 0.05) for CA3 neurons. Thus, in addition to documented effects on visual centers, high-level blue-light exposure also results in degeneration in hippocampal neurons with associated behavioral deficits. These changes can be partially ameliorated with blue-light-blocking lenses.

Computer-Vision-Based Dielectrophoresis Mobility Tracking for Characterization of Single-Cell Biophysical Properties

Fast and precise measurements of live single-cell biophysical properties is significant in disease diagnosis, cytopathologic analysis, etc. Existing methods still suffer from unsatisfied measurement accuracy and low efficiency. We propose a computer vision method to track cell dielectrophoretic movements on a microchip, enabling efficient and accurate measurement of biophysical parameters of live single cells, including cell radius, cytoplasm conductivity, and cell-specific membrane capacitance, and in situ extraction of cell texture features. We propose a prediction-iteration method to optimize the cell parameter measurement, achieving high accuracy (less than 0.79% error) and high efficiency (less than 30 s). We further propose a hierarchical classifier based on a support vector machine and implement cell classification using acquired cell physical parameters and texture features, achieving high classification accuracies for identifying cell lines from different tissues, tumor and normal cells, different tumor cells, different leukemia cells, and tumor cells with different malignancies. The method is label-free and biocompatible, allowing further live cell studies on a chip, e.g., cell therapy, cell differentiation, etc.

Modelling neuron fiber interaction and coupling in non-myelinated bundled fiber

Understanding the local dynamics of a neural network relies heavily on local field potential and cell-field interaction. But it is still unclear how local the local potential is and what kinds of consequences the trans-membrane current flow and produced electric field have on the local neural fiber. Mimicking signal transmission in neighboring nerve fiber, a simulation model is built to analyze local behavior due to trans-membrane current, cell-field interactions, and their repercussions on the bundled fiber system. Simulation studies reveal that depending on the coupling parameters, activity in one fiber can depolarize or hyper-polarize adjacent fibers. The suggested cell-field interaction model was tested using an orientation-selective coupled retinal ganglion cell network, which was compared to its uncoupled counterpart. The proposed work has been used to model and simulate local signal dynamics in a bundled fiber system of an orientation-selective RGC network due to cell-field interaction, as well as to gain insight into the possible significance of dendritic fiber coupling in orientation selectivity bandwidth adjustment.

Advance of microfluidic constriction channel system of measuring single-cell cortical tension/specific capacitance of membrane and conductivity of cytoplasm

This paper reported a microfluidic platform which realized the characterization of inherent single-cell biomechanical and bioelectrical parameters simultaneously. Individual cells traveled through a constriction channel with deformation images and impedance variations captured and processed into cortical tension T_c , specific membrane capacitance C_sm , and cytoplasmic conductivity σ_cy based on an equivalent biophysical model. These properties of thousands of individual cells of K562, Jurkat, HL-60, HL-60 treated with paraformaldehyde (PA)/cytochalasin D (CD)/concanavalin A (ConA), granulocytes of Donor 1, Donor 2, and Donor 3 were quantified for the first time. Leveraging T_c , C_sm , and σ_cy , (1) high accuracies of classifying wild-type and processed HL-60 cells (e.g., 93.5% of PA treated vs. CD treated HL-60 cells) were realized, revealing the effectiveness of using these three biophysical parameters in cell-type classification; (2) low accuracies of classifying normal granulocytes from three donors (e.g., 56.4% of Donor 1 vs. 2), indicating comparable parameters for normal granulocytes. In conclusion, this platform can characterize single-cell T_c , C_sm , and σ_cy concurrently and quantify multiple parameters in single-cell analysis.

Dielectrophoresis applications in biomedical field and future perspectives in biomedical technology

Dielectrophoresis (DEP) is a technique to manipulate trajectories of polarisable particles in non-uniform electric fields by utilising unique dielectric properties. The manipulation of a cell using DEP has been demonstrated in various modes, thereby indicating potential applications in the biomedical field. In this review, recent DEP applications in the biomedical field are discussed. This review is intended to highlight research work that shows significant approach related to dielectrophoresis application in biomedical field reported between 2016 and 2020. Firstly, single-shell model and multiple-shell model of cells are introduced. Current device structures and recently introduced electrode patterns for DEP applications are discussed. Secondly, the biomedical uses of DEP in liquid biopsies, stem cell therapies, and diagnosis of infectious diseases due to bacteria and viruses are presented. Finally, the challenges in DEP research are discussed, and the reported solutions are explained. DEP's potential research directions are mentioned. This article is protected by copyright. All rights reserved.

Dielectrophoresis as a tool for electrophysiological characterization of stem cells

Dielectrophoresis (DEP), a nonlinear electrokinetic technique caused by Maxwell-Wagner interfacial polarization of neutral particles in an electrolyte solution, is a powerful cell manipulation method used widely for various applications such as enrichment, trapping, and sorting of heterogeneous cell populations. While conventional cell characterization and sorting methods require tagging or labeling of cells, DEP has the potential to manipulate cells in a label-free way. Due to its unique ability to characterize and sort cells without the need of labeling, there is renewed interest in using DEP for stem cell research and regenerative medicine. Stem cells have the potential to differentiate into various lineages, but achieving homogeneous cell phenotypes from an initially heterogeneous cell population is a challenge. Using DEP to efficiently and affordably identify, sort, and enrich either undifferentiated or differentiated stem cell populations in a label-free way would advance their potential uses for applications in tissue engineering and regenerative medicine. This review summarizes recent, significant research findings regarding the electrophysiological characterization of stem cells, with a focus on cellular dielectric properties, i.e., permittivity and conductivity, and on studies that have obtained these measurements using techniques that preserve cell viability, such as crossover frequency. Potential applications for DEP in regenerative medicine are also discussed. Overall, DEP is a promising technique and, when used to characterize, sort, and enrich stem cells, will advance stem cell-based regenerative therapies.

Electrodiffusion models of synaptic potentials in dendritic spines

The biophysical properties of dendritic spines play a critical role in neuronal integration but are still poorly understood, due to experimental difficulties in accessing them. Spine biophysics has been traditionally explored using theoretical models based on cable theory. However, cable theory generally assumes that concentration changes associated with ionic currents are negligible and, therefore, ignores electrodiffusion, i.e. the interaction between electric fields and ionic diffusion. This assumption, while true for large neuronal compartments, could be incorrect when applied to femto-liter size structures such as dendritic spines. To extend cable theory and explore electrodiffusion effects, we use here the Poisson (P) and Nernst-Planck (NP) equations, which relate electric field to charge and Fick's law of diffusion, to model ion concentration dynamics in spines receiving excitatory synaptic potentials (EPSPs). We use experimentally measured voltage transients from spines with nanoelectrodes to explore these dynamics with realistic parameters. We find that (i) passive diffusion and electrodiffusion jointly affect the dynamics of spine EPSPs; (ii) spine geometry plays a key role in shaping EPSPs; and, (iii) the spine-neck resistance dynamically decreases during EPSPs, leading to short-term synaptic facilitation. Our formulation, which complements and extends cable theory, can be easily adapted to model ionic biophysics in other nanoscale bio-compartments.

Crossing constriction channel-based microfluidic cytometry capable of electrically phenotyping large populations of single cells

This paper presents a crossing constriction channel-based microfluidic system for high-throughput characterization of specific membrane capacitance (Csm) and cytoplasm conductivity (σcy) of single cells. In operations, cells in suspension were forced through the major constriction channel and instead of invading the side constriction channel, they effectively sealed the side constriction channel, which led to variations in impedance data. Based on an equivalent circuit model, these raw impedance data were translated into Csm and σcy. As a demonstration, the developed microfluidic system quantified Csm (3.01 ± 0.92 μF cm-2) and σcy (0.36 ± 0.08 S m-1) of 100 000 A549 cells, which could generate reliable results by properly controlling cell positions during their traveling in the crossing constriction channels. Furthermore, the developed microfluidic impedance cytometry was used to distinguish paired low- and high-metastatic carcinoma cell types of SACC-83 (ncell = ∼100 000) and SACC-LM cells (ncell = ∼100 000), distinguishing significant differences in both Csm (3.16 ± 0.90 vs. 2.79 ± 0.67 μF cm-2) and σcy (0.36 ± 0.06 vs.0.41 ± 0.08 S m-1). As high-throughput microfluidic impedance cytometry, this technique may add a new marker-free dimension to flow cytometry in single-cell analysis.

Three-Dimensional Conductive Scaffolds as Neural Prostheses Based on Carbon Nanotubes and Polypyrrole

Three-dimensional scaffolds for cellular organization need to enjoy a series of specific properties. On the one hand, the morphology, shape and porosity are critical parameters and eventually related with the mechanical properties. On the other hand, electrical conductivity is an important asset when dealing with electroactive cells, so it is a desirable property even if the conductivity values are not particularly high. Here, we construct three-dimensional (3D) porous and conductive composites, where C8-D1A astrocytic cells were incubated to study their biocompatibility. The manufactured scaffolds are composed exclusively of carbon nanotubes (CNTs), a most promising material to interface with neuronal tissue, and polypyrrole (PPy), a conjugated polymer demonstrated to reduce gliosis, improve adaptability, and increase charge-transfer efficiency in brain-machine interfaces. We developed a new and easy strategy, based on the vapor phase polymerization (VPP) technique, where the monomer vapor is polymerized inside a sucrose sacrificial template containing CNT and an oxidizing agent. After removing the sucrose template, a 3D porous scaffold was obtained and its physical, chemical, and electrical properties were evaluated. The obtained scaffold showed very low density, high and homogeneous porosity, electrical conductivity, and Young's Modulus similar to the in vivo tissue. Its high biocompatibility was demonstrated even after 6 days of incubation, thus paving the way for the development of new conductive 3D scaffolds potentially useful in the field of electroactive tissues.

Expanding the flexibility of dynamics simulation on different size particle-particle interactions by dielectrophoresis

In this paper, we perform flexible and reliable dynamics simulations on different sizes of two or more particles' interactive motions, where they encounter positive or negative dielectrophoresis (DEP) forces. The particles with identical or non-identical size are in close proximity suspended freely in a solution under a homogeneous electric field. According to the description of classic dipole moment, DEP forces make the particles form a straight chain. Therefore, dynamics simulation based on Newton's laws is utilized to understand AC DEP phenomena among multiple particles. To solve the relevant governing equations, Stokes drag and repulsive forces (including wall and particles) are combined with DEP forces to obtain the trajectories of particles. Results show that particles with the same sign of the Clausius-Mossotti (CM) factor revolve clockwise or counterclockwise to attract each other parallel to the electric field direction. Conversely, the particle chain is perpendicular to the field. This programmable advantage is of great benefit to the study of three or four particle motions. Meanwhile, the pearl chain consisting of three or four particles is related not only to an individual CM factor but also to initial spatial configuration. Both the cluster and short chain are dependent on symmetry between the geometric distribution and electric field, while it implies different size particles easily cause the chain structure with less time.

Frequency-Modulated Wave Dielectrophoresis of Vesicles And Cells: Periodic U-Turns at the Crossover Frequency

We have formulated the dielectrophoretic force exerted on micro/nanoparticles upon the application of frequency-modulated (FM) electric fields. By adjusting the frequency range of an FM wave to cover the crossover frequency f _X in the real part of the Clausius-Mossotti factor, our theory predicts the reversal of the dielectrophoretic force each time the instantaneous frequency periodically traverses f _X . In fact, we observed periodic U-turns of vesicles, leukemia cells, and red blood cells that undergo FM wave dielectrophoresis (FM-DEP). It is also suggested by our theory that the video tracking of the U-turns due to FM-DEP is available for the agile and accurate measurement of f _X . The FM-DEP method requires a short duration, less than 30 s, while applying the FM wave to observe several U-turns, and the agility in measuring f _X is of much use for not only salty cell suspensions but also nanoparticles because the electric-field-induced solvent flow is suppressed as much as possible. The accuracy of f _X has been verified using two types of experiment. First, we measured the attractive force exerted on a single vesicle experiencing alternating-current dielectrophoresis (AC-DEP) at various frequencies of sinusoidal electric fields. The frequency dependence of the dielectrophoretic force yields f _X as a characteristic frequency at which the force vanishes. Comparing the AC-DEP result of f _X with that obtained from the FM-DEP method, both results of f _X were found to coincide with each other. Second, we investigated the conductivity dependencies of f _X for three kinds of cell by changing the surrounding electrolytes. From the experimental results, we evaluated simultaneously both of the cytoplasmic conductivities and the membrane capacitances using an elaborate theory on the single-shell model of biological cells. While the cytoplasmic conductivities, similar for these cells, were slightly lower than the range of previous reports, the membrane capacitances obtained were in good agreement with those previously reported in the literature.

Development of microfluidic impedance cytometry enabling the quantification of specific membrane capacitance and cytoplasm conductivity from 100,000 single cells

This paper presents a new microfluidic impedance cytometry with crossing constriction microchannels, enabling the characterization of cellular electrical markers (e.g., specific membrane capacitance (C_sm) and cytoplasm conductivity (σ_cy)) in large cell populations (~ 100,000 cells) at a rate greater than 100 cells/s. Single cells were aspirated continuously through the major constriction channel with a proper sealing of the side constriction channel. An equivalent circuit model was developed and the measured impedance values were translated to C_sm and σ_cy. Neural network was used to classify different cell populations where classification success rates were calculated. To evaluate the developed technique, different tumour cell lines, and the effects of epithelial-mesenchymal transitions on tumour cells were examined. Significant differences in both C_sm and σ_cy were found for H1299 and HeLa cell lines with a classification success rate of 90.9% in combination of the two parameters. Meanwhile, tumour cells A549 showed significant decreases in both C_sm and σ_cy after epithelial-mesenchymal transitions with a classification success rate of 76.5%. As a high-throughput microfluidic impedance cytometry, this technique can add a new marker-free dimension to flow cytometry in single-cell analysis.

Determination of Cell Membrane Capacitance and Conductance via Optically Induced Electrokinetics

Cell membrane capacitance and conductance are key pieces of intrinsic information correlated with the cellular dielectric parameters and morphology of the plasma membrane; these parameters have been used as electrophysiological biomarkers to characterize cellular phenotype and state, and they have many associated clinical applications. Here, we present our work on the non-invasive determination of cell membrane capacitance and conductance by an optically activated microfluidics chip. The model for determining the cell membrane capacitance and conductance was established by a single layer of the shell-core polarization model. Three-dimensional finite-element analyses of the positive and negative optically induced dielectrophoresis forces generated by the projected light arrays of spots were performed, thus providing a theoretical validation of the feasibility of this approach. Then, the crossover frequency spectra for four typical types of cells (Raji cells, MCF-7 cells, HEK293 cells, and K562 cells) were experimentally investigated by using a micro-vision based motion-tracking technique. The different responses of these cells to the positive and negative ODEP forces were studied under four different liquid conductivities by automatic observation and tracking of the cellular trajectory and texture during the cells' translation. The cell membrane capacitance and conductance were determined from the curve-fitted spectra, which were 11.1 ± 0.9 mF/m² and 782 ± 32 S/m², respectively, for Raji cells, 11.5 ± 0.8 mF/m² and 114 ± 28 S/m² for MCF-7 cells, 9.0 ± 0.9 mF/m² and 187 ± 22 S/m² for HEK293 cells, and 10.2 ± 0.7 mF/m² and 879 ± 24 S/m² for K562 cells. Furthermore, as an application of this technique, the membrane capacitances of MCF-7 cells treated with four different concentrations of drugs were acquired. This technique introduces a determination of cell membrane capacitance and conductance that yields statistically significant data while allowing information from individual cells to be obtained in a non-invasive manner.