Classification of cell types using a microfluidic device for mechanical and electrical measurement on single cells

Acoustic Streaming Tunnel Enables Particle Velocity Stretching in Multiplex Flow Cytometry

Multiplexed flow cytometry, known for its powerful high-throughput identification capability, is widely applied across various biomedical and clinical fields. However, classical flow cytometry relies on multichannel lasers and detectors, which are significant in cost and size, limiting their application in miniaturized assays. Herein, we developed an acoustic streaming-based flow cytometry technique that focuses on multisized microbeads flowing sheathlessly. This method enables the discrimination of particle types and the quantification of target protein concentrations using only a single detector. Microbeads of different sizes exhibit distinct behaviors in the continuous acoustic streaming tunnel, leading to an increased velocity difference during their transition under the laser spot. Consequently, a size detection method based on "velocity stretching" has been established. A multiplex assay of three proteins: cardiac troponin I, creatine kinase-MB and myoglobin, in acute myocardial infarction is performed to validate the feasibility and evaluate the performance of the system. This new multiplexed flow cytometry strategy is expected to enable low-cost and onsite detection of multiple biomarkers.

Design and optimization of microchannel for enhancement of the intensity of induced signal in particle/cell impedance measurement

The measured impedance signal of a single particle or cell in a microchannel is of the μA level, which is a challenge for measuring such weak signals. Therefore, it is necessary to improve the intensity for expanding the applications of impedance measurement. In this paper, we analyzed the impact of geometric parameters of microchannel on output signal intensity by using the three-dimensional finite element method. In comparison to conventional microchannels, which are distributed at a uniform height, the microchannels in this design use the height difference to enhance the signal intensity. By analyzing the effects of the geometric dimensions of the constriction channel, main channel height, radius of particles, types of cells, shapes of particles with different ellipticities, and particles spacing on the current signal, we concluded the optimal dimensions of these parameters to improve the intensity of the induced current signal. Through the fabrication of the optimized size of device and experimental demonstration, it is verified that the current signal intensity caused by the particle with a diameter of 10 µm is nearly twice that of the conventional structure with a height of 20 µm, which proves the correctness of the optimization results and the feasibility of this work. In addition, the performance of the device was verified by measuring the mixtures of different size particles as well as non-viable and viable yeast cells.

Photocell-Based Optofluidic Device for Clogging-Free Cell Transit Time Measurements

Measuring the transit time of a cell forced through a bottleneck is one of the most widely used techniques for the study of cell deformability in flow. It in turn provides an accessible and rapid way of obtaining crucial information regarding cell physiology. Many techniques are currently being investigated to reliably retrieve this time, but their translation to diagnostic-oriented devices is often hampered by their complexity, lack of robustness, and the bulky external equipment required. Herein, we demonstrate the benefits of coupling microfluidics with an optical method, like photocells, to measure the transit time. We exploit the femtosecond laser irradiation followed by chemical etching (FLICE) fabrication technique to build a monolithic 3D device capable of detecting cells flowing through a 3D non-deformable constriction which is fully buried in a fused silica substrate. We validated our chip by measuring the transit times of pristine breast cancer cells (MCF-7) and MCF-7 cells treated with Latrunculin A, a drug typically used to increase their deformability. A difference in transit times can be assessed without the need for complex external instrumentation and/or demanding computational efforts. The high throughput (4000-10,000 cells/min), ease of use, and clogging-free operation of our device bring this approach much closer to real scenarios.

Metal-pad-enhanced resistive pulse sensor reveals complex-valued Braess paradox

A resistive pulse sensor measures the electrical impedance of an electrolyte-filled channel as particles flow through it. Ordinarily, the presence of a nonconductive particle increases the impedance of the channel. Here we report a surprising experimental result in which a microfluidic resistive pulse sensor experiences the opposite effect: The presence of a nonconductive particle decreases the channel impedance. We explain the counterintuitive phenomenon by relating to the Braess paradox from traffic network theory, and we call it the complex-valued Braess paradox (CVBP). We develop theoretical models to study the CVBP and corroborate the experimental data using finite element simulations and lumped-element circuit modeling. We then discuss implications and potential applications of the CVBP in resistive pulse sensing and beyond.

Performance-enhanced clogging-free viscous sheath constriction impedance flow cytometry

As a label-free and high-throughput single cell analysis platform, impedance flow cytometry (IFC) suffers from clogging caused by a narrow microchannel as mechanical constriction (MC). Current sheath constriction (SC) solutions lack systematic evaluation of the performance and proper guidelines for the sheath fluid. Herein, we hypothesize that the viscosity of the non-conductive liquid is the key to the performance of SC, and propose to employ non-conductive viscous sheath flow in SC to unlock the tradeoff between sensitivity and throughput, while ensuring measurement accuracy. By placing MC and SC in series in the same microfluidic chip, we established an evaluation platform to prove the hypothesis. Through modeling analysis and experiments, we confirmed the accuracy (error < 1.60% ± 4.71%) of SC w.r.t. MC, and demonstrated that viscous non-conductive PEG solution achieved an improved sensitivity (7.92×) and signal-to-noise ratio (1.42×) in impedance measurement, with the accuracy maintained and free of clogging. Viscous SC IFC also shows satisfactory ability to distinguish different types of cancer cells and different subtypes of human breast cancer cells. It is envisioned that viscous SC IFC paves the way for IFC to be really usable in practice with clogging-free, accurate, and sensitive performance.

Altered physical phenotypes of leukemia cells that survive chemotherapy treatment

The recurrence of cancer following chemotherapy treatment is a major cause of death across solid and hematologic cancers. In B-cell acute lymphoblastic leukemia (B-ALL), relapse after initial chemotherapy treatment leads to poor patient outcomes. Here we test the hypothesis that chemotherapy-treated versus control B-ALL cells can be characterized based on cellular physical phenotypes. To quantify physical phenotypes of chemotherapy-treated leukemia cells, we use cells derived from B-ALL patients that are treated for 7 days with a standard multidrug chemotherapy regimen of vincristine, dexamethasone, and L-asparaginase (VDL). We conduct physical phenotyping of VDL-treated versus control cells by tracking the sequential deformations of single cells as they flow through a series of micron-scale constrictions in a microfluidic device; we call this method Quantitative Cyclical Deformability Cytometry. Using automated image analysis, we extract time-dependent features of deforming cells including cell size and transit time (TT) with single-cell resolution. Our findings show that VDL-treated B-ALL cells have faster TTs and transit velocity than control cells, indicating that VDL-treated cells are more deformable. We then test how effectively physical phenotypes can predict the presence of VDL-treated cells in mixed populations of VDL-treated and control cells using machine learning approaches. We find that TT measurements across a series of sequential constrictions can enhance the classification accuracy of VDL-treated cells in mixed populations using a variety of classifiers. Our findings suggest the predictive power of cell physical phenotyping as a complementary prognostic tool to detect the presence of cells that survive chemotherapy treatment. Ultimately such complementary physical phenotyping approaches could guide treatment strategies and therapeutic interventions. Insight box Cancer cells that survive chemotherapy treatment are major contributors to patient relapse, but the ability to predict recurrence remains a challenge. Here we investigate the physical properties of leukemia cells that survive treatment with chemotherapy drugs by deforming individual cells through a series of micron-scale constrictions in a microfluidic channel. Our findings reveal that leukemia cells that survive chemotherapy treatment are more deformable than control cells. We further show that machine learning algorithms applied to physical phenotyping data can predict the presence of cells that survive chemotherapy treatment in a mixed population. Such an integrated approach using physical phenotyping and machine learning could be valuable to guide patient treatments.

Microsystem Advances through Integration with Artificial Intelligence

Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier-Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.

Viscoelastic Properties of Zona Pellucida of Oocytes Characterized by Transient Electrical Impedance Spectroscopy

The success rate in vitro fertilization is significantly linked to the quality of the oocytes. The oocyte's membrane is encapsulated by a shell of gelatinous extracellular matrix, called zona pellucida, which undergoes dynamic changes throughout the reproduction cycle. During the window of highest fertility, the zona pellucida exhibits a softening phase, while it remains rigid during oocyte maturation and again after fertilization. These variations in mechanical properties facilitate or inhibit sperm penetration. Since successful fertilization considerably depends on the state of the zona pellucida, monitoring of the hardening process of the zona pellucida is vital. In this study, we scrutinized two distinct genetic mouse models, namely, fetuin-B wild-type and fetuin-B/ovastacin double deficient with normal and super-soft zona pellucida, respectively. We evaluated the hardening with the help of a microfluidic aspiration-assisted electrical impedance spectroscopy system. An oocyte was trapped by a microhole connected to a microfluidic channel by applying suction pressure. Transient electrical impedance spectra were taken by microelectrodes surrounding the microhole. The time-depending recovery of zona pellucida deflections to equilibrium was used to calculate the Young's modulus and, for the first time, absolute viscosity values. The values were obtained by fitting the curves with an equivalent mechanical circuit consisting of a network of dashpots and springs. The observer-independent electrical readout in combination with a fitting algorithm for the calculation of the viscoelastic properties demonstrates a step toward a more user-friendly and easy-to-use tool for the characterizing and better understanding of the rheological properties of oocytes.

Concepts, electrode configuration, characterization, and data analytics of electric and electrochemical microfluidic platforms: a review

Microfluidic cytometry (MC) and electrical impedance spectroscopy (EIS) are two important techniques in biomedical engineering. Microfluidic cytometry has been utilized in various fields such as stem cell differentiation and cancer metastasis studies, and provides a simple, label-free, real-time method for characterizing and monitoring cellular fates. The impedance microdevice, including impedance flow cytometry (IFC) and electrical impedance spectroscopy (EIS), is integrated into MC systems. IFC measures the impedance of individual cells as they flow through a microfluidic device, while EIS measures impedance changes during binding events on electrode regions. There have been significant efforts to improve and optimize these devices for both basic research and clinical applications, based on the concepts, electrode configurations, and cell fates. This review outlines the theoretical concepts, electrode engineering, and data analytics of these devices, and highlights future directions for development.

A review of bio-impedance devices

Bio-impedance measurement analysis primarily refers to a safe and a non-invasive technique to analyze the electrical changes in living tissues on the application of low-value alternating current. It finds applications both in the biomedical and the agricultural fields. This paper concisely reviews the origin and measurement approaches for concepts and fundamentals of bio-impedance followed by a critical review on bio-impedance portable devices with main emphasis on the embedded system approach which is in demand due to its miniature size and present lifestyle preference of monitoring health in real time. The paper also provides a comprehensive review of various bio-impedance circuits with emphasis on the measurement and calibration techniques.

Advanced density-based methods for the characterization of materials, binding events, and kinetics

Investigations of the densities of chemicals and materials bring valuable insights into the fundamental understanding of matter and processes. Recently, advanced density-based methods have been developed with wide measurement ranges (i.e. 0-23 g cm^-3), high resolutions (i.e. 10^-6 g cm^-3), compatibility with different types of samples and the requirement of extremely low volumes of sample (as low as a single cell). Certain methods, such as magnetic levitation, are inexpensive, portable and user-friendly. Advanced density-based methods are, therefore, beneficially used to obtain absolute density values, composition of mixtures, characteristics of binding events, and kinetics of chemical and biological processes. Herein, the principles and applications of magnetic levitation, acoustic levitation, electrodynamic balance, aqueous multiphase systems, and suspended microchannel resonators for materials science are discussed.

Biosensors and machine learning for enhanced detection, stratification, and classification of cells: a review

Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another, therefore, is of paramount importance for disease diagnostics as well as therapeutics. Sensors focusing on the detection and stratification of cells have gained popularity as technological advancements have allowed for the miniaturization of various components inching us closer to Point-of-Care (POC) solutions with each passing day. Furthermore, Machine Learning has allowed for enhancement in the analytical capabilities of these various biosensing modalities, especially the challenging task of classification of cells into various categories using a data-driven approach rather than physics-driven. In this review, we provide an account of how Machine Learning has been applied explicitly to sensors that detect and classify cells. We also provide a comparison of how different sensing modalities and algorithms affect the classifier accuracy and the dataset size required.

Microfluidic Impedance-Deformability Cytometry for Label-Free Single Neutrophil Mechanophenotyping

The intrinsic biophysical states of neutrophils are associated with immune dysfunctions in diseases. While advanced image-based biophysical flow cytometers can probe cell deformability at high throughput, it is nontrivial to couple different sensing modalities (e.g., electrical) to measure other critical cell attributes including cell viability and membrane integrity. Herein, an "optics-free" impedance-deformability cytometer for multiparametric single cell mechanophenotyping is reported. The microfluidic platform integrates hydrodynamic cell pinching, and multifrequency impedance quantification of cell size, deformability, and membrane impedance (indicative of cell viability and activation). A newly-defined "electrical deformability index" is validated by numerical simulations, and shows strong correlations with the optical cell deformability index of HL-60 experimentally. Human neutrophils treated with various biochemical stimul are further profiled, and distinct differences in multimodal impedance signatures and UMAP analysis are observed. Overall, the integrated cytometer enables label-free cell profiling at throughput of >1000 cells min^-1 without any antibodies labeling to facilitate clinical diagnostics.

Recent Advances in Electrical Impedance Sensing Technology for Single-Cell Analysis

Cellular heterogeneity is of significance in cell-based assays for life science, biomedicine and clinical diagnostics. Electrical impedance sensing technology has become a powerful tool, allowing for rapid, non-invasive, and label-free acquisition of electrical parameters of single cells. These electrical parameters, i.e., equivalent cell resistance, membrane capacitance and cytoplasm conductivity, are closely related to cellular biophysical properties and dynamic activities, such as size, morphology, membrane intactness, growth state, and proliferation. This review summarizes basic principles, analytical models and design concepts of single-cell impedance sensing devices, including impedance flow cytometry (IFC) to detect flow-through single cells and electrical impedance spectroscopy (EIS) to monitor immobilized single cells. Then, recent advances of both electrical impedance sensing systems applied in cell recognition, cell counting, viability detection, phenotypic assay, cell screening, and other cell detection are presented. Finally, prospects of impedance sensing technology in single-cell analysis are discussed.

High-Throughput Characterization of Cell Adhesion Strength Using Long-Channel Constriction-Based Microfluidics

The adhesion strength of a cancer cell is a valuable biophysical marker of its metastatic potential, tightly associated with various metastatic processes; for example, cancer cells escape from a primary tumor, and circulating tumor cells (CTCs) are anchored to the vessel wall. Although constriction-based microfluidics can realize the high-throughput characterization of single-cell deformability, due to the influence of cell size heterogeneity, accurately evaluating the adhesion strength of a cancer cell at high throughputs in constriction remains difficult. In this paper, we first proposed an approach for the assessment of adhesion strength of BGC-823 and SGC-7901 cell lines at high throughputs based on a friction coefficient using the constant velocity stage of cell transit in a long-channel constriction. Cell size was proven to be independent of adhesion strength by cell detachment assay; however, it has large effects on cell transit velocity in constriction. Therefore, the linear elasticity of a completely deformed cell in constriction is simplified as a compressed spring model, effectively reducing the influence of cell size heterogeneity. Theoretically, our proposed model can well offset the influence of cell size by cell transit velocity, while our experimental results indicate that the friction coefficient has a good linear relationship with the logarithm of the adhesion strength too. Therefore, our proposed approach can realize accurate characterization of cell adhesion strength at high throughputs using long-channel constriction-based microfluidics. Hence, this work might enrich the functions of constriction-based microfluidics and bring new insights into the characterization of mechanical phenotypes.

Submicron-precision particle characterization in microfluidic impedance cytometry with double differential electrodes

Submicron-precision particle characterization is crucial for counting, sizing and identifying a variety of biological particles, such as bacteria and apoptotic bodies. Microfluidic impedance cytometry has been attractive in current research for microparticle characterization due to its advantages of label-free detection, ease of miniaturization and affordability. However, conventional electrode configurations of three electrodes and floating electrodes have not yet demonstrated the capability of probing submicron particles or microparticles with a submicron size difference. In this study, we present a label-free high-throughput (∼800 particles per second) impedance-based microfluidic flow cytometry system integrated with a novel design of a double differential electrode configuration, enabling submicron particle detection (down to 0.4 μm) with a minimum size resolution of 200 nm. The signal-to-noise ratio has been boosted from 13.98 dB to 32.64 dB compared to a typical three-electrode configuration. With the proposed microfluidic impedance cytometry, we have shown results of sizing microparticles that accurately correlate with manufacturers' datasheets (R² = 0.99938). It also shows that population ratios of differently sized beads in mixture samples are consistent with the results given by commercial fluorescence-based flow cytometry (within ∼1% difference). This work provides a label-free approach with submicron precision for sizing and counting microscale and submicron particles, and a new avenue of designing electrode configurations with a feature of suppressing the electrical noise for accomplishing a high signal-to-noise ratio in a wide range of frequencies. This novel double differential impedance sensing system paves a new pathway for real-time analysis and accurate particle screening in pathological and pharmacological research.

Engineering mechanobiology through organoids-on-chip: A strategy to boost therapeutics

The mechanical environment of living cells is as critical as chemical signaling. Mechanical stimuli play a pivotal role in organogenesis and tissue homeostasis. Unbalances in mechanotransduction pathways often lead to diseases, such as cancer, cystic fibrosis, and neurodevelopmental disorders. Despite its inherent relevance, there is a lack of proper mechanoresponsive in vitro study systems. In this context, there is an urge to engineer innovative, robust, dynamic, and reliable organotypic technologies to better connect cellular processes to organ-level function and multi-tissue cross-talk. Mechanically active organoid-on-chip has the potential to surpass this challenge. These systems converge microfabrication, microfluidics, biophysics, and tissue engineering fields to emulate key features of living organisms, hence, reducing costs, time, and animal testing. In this review, we intended to present cutting-edge organ-on-chip platforms that integrate biomechanical stimuli as well as novel multicellular culture, such as organoids. We focused on its application in two main fields: precision medicine and drug development. Moreover, we also discussed the state of the art for the development of an engineered model to assess patient-derived tumor organoid metastatic potential. Finally, we highlighted the current drawbacks and emerging opportunities to match the industry needs. We envision the use of mechanoresponsive organotypic-on-chip microdevices as an indispensable tool for precision medicine, drug development, disease modeling, tissue engineering, and developmental biology.

Microfluidic impedance cytometry for single-cell sensing: Review on electrode configurations

Single-cell analysis has gained considerable attention for disease diagnosis, drug screening, and differentiation monitoring. Compared to the well-established flow cytometry, which uses fluorescent-labeled antibodies, microfluidic impedance cytometry (MIC) offers a simple, label-free, and noninvasive method for counting, classifying, and monitoring cells. Superior features including a small footprint, low reagent consumption, and ease of use have also been reported. The MIC device detects changes in the impedance signal caused by cells passing through the sensing/electric field zone, which can extract information regarding the size, shape, and dielectric properties of these cells. According to recent studies, electrode configuration has a remarkable effect on detection accuracy, sensitivity, and throughput. With the improvement in microfabrication technology, various electrode configurations have been reported for improving detection accuracy and throughput. However, the various electrode configurations of MIC devices have not been reviewed. In this review, the theoretical background of the impedance technique for single-cell analysis is introduced. Then, two-dimensional, three-dimensional, and liquid electrode configurations are discussed separately; their sensing mechanisms, fabrication processes, advantages, disadvantages, and applications are also described in detail. Finally, the current limitations and future perspectives of these electrode configurations are summarized. The main aim of this review is to offer a guide for researchers on the ongoing advancement in electrode configuration designs.

Autoregressive parametric modeling combined ANOVA approach for label-free-based cancerous and normal cells discrimination

Label free based methods received huge interest in the field of bio cell characterizations because they do not cause any cell damage nor contribute any change in its compositions. This work takes a close outlook of cancerous cells discrimination from normal cells utilizing parametric modeling approach. Autoregressive (AR) modeling technique is used to fit the measured optical transmittance profiles of both cancer and normal cells. The transmitted light intensity, when passes through the cells, gets affected by their intercellular compositions and membrane properties. In this study, four types of cells: lung-cancerous and normal, liver-cancerous and normal, were suspended in their corresponding medium and their transmission characteristics were collected and processed. The AR coefficients of each type of the cell were analyzed with the statistical technique called Analysis of variance (ANOVA), which provided the significant coefficients. The poles extracted from the significant coefficients resulted in an improved demarcation for normal and cancer cells. These outcomes can be further utilized for cell classification using statistical tools.

Non-invasive acquisition of mechanical properties of cells via passive microfluidic mechanisms: A review

The demand to understand the mechanical properties of cells from biomedical, bioengineering, and clinical diagnostic fields has given rise to a variety of research studies. In this context, how to use lab-on-a-chip devices to achieve accurate, high-throughput, and non-invasive acquisition of the mechanical properties of cells has become the focus of many studies. Accordingly, we present a comprehensive review of the development of the measurement of mechanical properties of cells using passive microfluidic mechanisms, including constriction channel-based, fluid-induced, and micropipette aspiration-based mechanisms. This review discusses how these mechanisms work to determine the mechanical properties of the cell as well as their advantages and disadvantages. A detailed discussion is also presented on a series of typical applications of these three mechanisms to measure the mechanical properties of cells. At the end of this article, the current challenges and future prospects of these mechanisms are demonstrated, which will help guide researchers who are interested to get into this area of research. Our conclusion is that these passive microfluidic mechanisms will offer more preferences for the development of lab-on-a-chip technologies and hold great potential for advancing biomedical and bioengineering research studies.

A constriction channel analysis of astrocytoma stiffness and disease progression

Studies have demonstrated that cancer cells tend to have reduced stiffness (Young's modulus) compared to their healthy counterparts. The mechanical properties of primary brain cancer cells, however, have remained largely unstudied. To investigate whether the stiffness of primary brain cancer cells decreases as malignancy increases, we used a microfluidic constriction channel device to deform healthy astrocytes and astrocytoma cells of grade II, III, and IV and measured the entry time, transit time, and elongation. Calculating cell stiffness directly from the experimental measurements is not possible. To overcome this challenge, finite element simulations of the cell entry into the constriction channel were used to train a neural network to calculate the stiffness of the analyzed cells based on their experimentally measured diameter, entry time, and elongation in the channel. Our study provides the first calculation of stiffness for grades II and III astrocytoma and is the first to apply a neural network analysis to determine cell mechanical properties from a constriction channel device. Our results suggest that the stiffness of astrocytoma cells is not well-correlated with the cell grade. Furthermore, while other non-central-nervous-system cell types typically show reduced stiffness of malignant cells, we found that most astrocytoma cell lines had increased stiffness compared to healthy astrocytes, with lower-grade astrocytoma having higher stiffness values than grade IV glioblastoma. Differences in nucleus-to-cytoplasm ratio only partly explain differences in stiffness values. Although our study does have limitations, our results do not show a strong correlation of stiffness with cell grade, suggesting that other factors may play important roles in determining the invasive capability of astrocytoma. Future studies are warranted to further elucidate the mechanical properties of astrocytoma across various pathological grades.

Monitoring Single S. cerevisiae Cells with Multifrequency Electrical Impedance Spectroscopy in an Electrode-Integrated Microfluidic Device

This chapter describes an electrode-integrated microfluidic system with multiple functions of manipulating and monitoring single S. cerevisiae cells. In this system, hydrodynamic trapping and negative dielectrophoretic (nDEP) releasing of S. cerevisiae cells are implemented, providing a flexible method for single-cell manipulation. The multiplexing microelectrodes also enable sensitive electrical impedance spectroscopy (EIS) to discern the number of immobilized cells, classify different orientations of captured cells, as well as detect potential movements of immobilized single yeast cells during the overall recording duration by using principal component analysis (PCA) in data mining. The multifrequency EIS measurements can, therefore, obtain sufficient information of S. cerevisiae cells at single-cell level.

Differences in the dielectric properties of various benign and malignant thyroid nodules

PURPOSE

This experiment was conducted to investigate the dielectric properties of different types of thyroid nodules. Our goal was to find a simple and fast method to detect thyroid diseases at different stages from the dielectric properties of thyroid nodules.

METHODS

We used the open-ended coaxial line method to measure the dielectric permittivities of thyroid tissues from 155 patients at frequencies ranging from 1 to 4000 MHz. Tissues that were investigated included normal thyroid tissue and benign and malignant thyroid nodules (nodular goiter, follicular adenoma, papillary carcinoma, and follicular carcinoma), as determined from pathological reports. Differences in dielectric properties were measured between each nodule and the surrounding 1 cm of tissue.

RESULTS

The analysis results revealed that the dielectric permittivity and conductivity values were positively correlated with the degree of malignancy of the nodule (normal < benign < malignant; all differences P < 0.05). This was more obvious at frequencies within 20~70 MHz, following the order normal tissue < nodular goiter < follicular adenoma < papillary carcinoma < follicular carcinoma. A significant difference (P < 0.05) in dielectric permittivity and conductivity was found when comparing these nodules with the surrounding 1 cm of tissue.

CONCLUSIONS

Normal, benign, and malignant nodules were successfully distinguished from one another, and dielectric permittivity was found to be a more sensitive parameter than conductivity. In particular, different disease types can be distinguished at a stimulation frequency of 20~70 MHz, which shows that dielectric properties have application prospects for the detection and diagnosis of cancer. At the same time, the dielectric parameter differences between the surrounding 1 cm of tissue and the diseased nodule can distinguish the tumor and its surrounding tissues in real time during surgery to determine the tumor boundary.

Biological Living Cell in-Flow Detection Based on Microfluidic Chip and Compact Signal Processing Circuit

Detection and counting of biological living cells in continuous fluidic flows play an essential role in many applications for early diagnosis and treatment of diseases. In this regard, this study highlighted the proposal of a biochip system for detecting and enumerating human lung carcinoma cell flow in the microfluidic channel. The principle of detection was based on the change of impedance between sensing electrodes integrated in the fluidic channel, due to the presence of a biological cell in the sensing region. A compact electronic module was built to sense the unbalanced impedance between the sensing microelectrodes. It consisted of an instrumentation amplifier stage to obtain the difference between the acquired signals, and a lock-in amplifier stage to demodulate the signals at the stimulating frequency as well as to reject noise at other frequencies. The performance of the proposed system was validated through experiments of A549 cells detection as they passed over the microfluidic channel. The experimental results indicated the occurrence of large spikes (up to approximately 180 mV) over the background signal according to the passage of a single A549 cell in the continuous flow. The proposed device is simple-to-operate, inexpensive, portable, and exhibits high sensitivity, which are suitable considerations for developing point-of-care applications.

Comparative Study of Prostate Cancer Biophysical and Migratory Characteristics via Iterative Mechanoelectrical Properties (iMEP) and Standard Migration Assays

This study reveals a new microfluidic biosensor consisting of a multi-constriction microfluidic device with embedded electrodes for measuring the biophysical attributes of single cells. The biosensing platform called the iterative mechano-electrical properties (iMEP) analyzer captures electronic records of biomechanical and bioelectrical properties of cells. The iMEP assay is used in conjunction with standard migration assays, such as chemotaxis-based Boyden chamber and scratch wound healing assays, to evaluate the migratory behavior and biophysical properties of prostate cancer cells. The three cell lines evaluated in the study each represent a stage in the standard progression of prostate cancer, while the fourth cell line serves as a normal/healthy counterpart. Neither the scratch assay nor the chemotaxis assay could fully differentiate the four cell lines. Furthermore, there was not a direct correlation between wound healing rate or the migratory rate with the cells' metastatic potential. However, the iMEP assay, through its multiparametric dataset, could distinguish between all four cell line populations with p-value < 0.05. Further studies are needed to determine if iMEP signatures can be used for a wider range of human cells to assess the tumorigenicity of a cell population or the metastatic potential of cancer cells.

An Easy Method for Pressure Measurement in Microchannels Using Trapped Air Compression in a One-End-Sealed Capillary

Pressure is one basic parameter involved in microfluidic systems. In this study, we developed an easy capillary-based method for measuring fluid pressure at one or multiple locations in a microchannel. The principal component is a commonly used capillary (inner diameter of 400 μm and 95 mm in length), with one end sealed and calibrated scales on it. By reading the height (h) of an air-liquid interface, the pressure can be measured directly from a table, which is calculated using the ideal gas law. Many factors that affect the relationship between the trapped air volume and applied pressure (p_applied) have been investigated in detail, including the surface tension, liquid gravity, air solubility in water, temperature variation, and capillary diameters. Based on the evaluation of the experimental and simulation results of the pressure, combined with theoretical analysis, a resolution of about 1 kPa within a full-scale range of 101.6–178 kPa was obtained. A pressure drop (Δp) as low as 0.25 kPa was obtained in an operating range from 0.5 kPa to 12 kPa. Compared with other novel, microstructure-based methods, this method does not require microfabrication and additional equipment. Finally, we use this method to reasonably analyze the nonlinearity of the flow-pressure drop relationship caused by channel deformation. In the future, this one-end-sealed capillary could be used for pressure measurement as easily as a clinical thermometer in various microfluidic applications.

Single ascospore detection for the forecasting of Sclerotinia stem rot of canola

Smart-agriculture technologies comprise a set of management systems designed to sustainably increase the efficiency and productivity of farming. In this paper, we present a lab-on-a-chip device that can be employed as a plant disease forecasting tool for canola crop. Our device can be employed as a platform to forecast potential outbreaks of one of the most devastating diseases of canola and other crops, Sclerotinia stem rot. The system consists of a microfluidic chip capable of detecting single airborne Sclerotinia sclerotiorum ascospores. Target ascospores are injected into the chip and selectively captured by dielectrophoresis, while other spores in the sample are flushed away. Afterward, captured ascospores are released into the flow stream of the channel and are detected employing electrochemical impedance spectroscopy and coplanar microelectrodes. Our device provides a design for a low-cost, miniaturized, and automated platform technology for airborne spore detection and disease prevention.

Post-enrichment circulating tumor cell detection and enumeration via deformability impedance cytometry

Circulating tumor cells (CTCs) in blood can provide valuable information when detecting, diagnosing, and monitoring cancer. This paper describes a system that consists of a constriction-based microfluidic sensor with embedded electrodes that can detect and enumerate cancer cells in blood. The biosensor measures impedance in terms of magnitude and phase at multiple frequencies as cells transit through the constriction channel. Cancer cells deform as they move through while blood cells remain intact, thus generating differential impedance profiles that can be used for detecting and counting CTCs. Two versions of this device are reported, one where the electrodes are embedded into the disposable microfluidic channel, and the other in which the disposable chip is externally fixed to a reusable substrate housing the electrodes. Both configurations were tested by spiking breast or prostate cancer cells into murine blood, and both detected all tumor cells passing through the narrow channels while being able to differentiate between the two cell lines. The chip in its current format has a throughput of 1 μL/min. While the throughput is scalable by integrating more constriction channels in parallel, the presented assay is intended for post-enrichment label-free enumeration and characterization of CTCs.

A Systematic Study on Transit Time and Its Impact on Accuracy of Concentration Measured by Microfluidic Devices

Gating or threshold selection is very important in analyzing data from a microflow cytometer, which is especially critical in analyzing weak signals from particles/cells with small sizes. It has been reported that using the amplitude gating alone may result in false positive events in analyzing data with a poor signal-to-noise ratio. Transit time (τ) can be set as a gating threshold along with side-scattered light or fluorescent light signals in the detection of particles/cells using a microflow cytometer. In this study, transit time of microspheres was studied systematically when the microspheres passed through a laser beam in a microflow cytometer and side-scattered light was detected. A clear linear relationship between the inverse of the average transit time and total flow rate was found. Transit time was used as another gate (other than the amplitude of side-scattering signals) to distinguish real scattering signals from noise. It was shown that the relative difference of the measured microsphere concentration can be reduced significantly from the range of 3.43%-8.77% to the range of 8.42%-111.76% by employing both amplitude and transit time as gates in analysis of collected scattering data. By using optimized transit time and amplitude gate thresholds, a good correlation with the traditional hemocytometer-based particle counting was achieved (R² > 0.94). The obtained results suggest that the transit time could be used as another gate together with the amplitude gate to improve measurement accuracy of particle/cell concentration for microfluidic devices.

Microfluidic impedance cytometry device with N-shaped electrodes for lateral position measurement of single cells/particles

Tracking the lateral position of single cells and particles plays an important role in evaluating the efficiency of microfluidic cell focusing, separation and sorting. In this work, we present an N-shaped electrode-based microfluidic impedance cytometry device for the measurement of the lateral position of single cells and particles in continuous flows. Specifically, a simple analytical expression for determining the particle lateral position is derived from the measured electrical signal and geometry relationship among the positions of the flowing particles, electrodes and microchannel. This microfluidic system is experimentally validated by measuring the lateral positions of 5, 7 and 10 μm diameter beads and human red blood cells (RBCs) flowing in a 200 μm wide channel at varying flow rates up to 59.3 μl min^-1. Statistical analyses show a good correlation (R² = 0.99) and agreement (Bland-Altman analysis) between our results and those obtained by a microscopy imaging method. The resolution of our system reflected by the root-mean-square deviation (RMSD) is 10.3 μm (5.15% of the channel width) for 5 and 10 μm beads, and 11.4 μm (5.7% of the channel width) for RBCs at a flow rate of 42.4 μl min^-1. Compared to the existing impedance-based methods for measuring the particle lateral position, we achieve the highest resolution, highest flow rate and smallest measured particle size (3.6 μm beads). The experimental results of the mixture with 5 and 10 μm beads demonstrate that our device does not merely measure the lateral position of single particles or cells, but also can characterize their physical properties (e.g., size) simultaneously. Furthermore, we demonstrate the position monitoring of sheath flow-induced particle focusing, which is in quantitative agreement with the results by imaging quantification. With the advantages of rapid and accurate processing of electrical signal and high throughput of the impedance flow cytometry, this novel N-shaped electrode-based system can be easily integrated with other microfluidic platforms as a downstream approach for the real-time measurement of the lateral position and physical properties of single cells and particles.

Biophysical phenotyping of cells via impedance spectroscopy in parallel cyclic deformability channels

This paper describes a new microfluidic biosensor with capabilities of studying single cell biophysical properties. The chip contains four parallel sensing channels, where each channel includes two constriction regions separated by a relaxation region. All channels share a pair of electrodes to record the electrical impedance. Single cell impedance magnitudes and phases at different frequencies were obtained. The deformation and transition time information of cells passing through two sequential constriction regions were gained from the time points on impedance magnitude variations. Constriction channels separated by relaxation regions have been proven to improve the sensitivity of distinguishing single cells. The relaxation region between two sequential constriction channels provides extra time stamps that can be identified in the impedance plots. The new chip allows simultaneous measurement of the biophysical attributes of multiple cells in different channels, thereby increasing the overall throughput of the chip. Using the biomechanical parameters represented by the time stamps in the impedance results, breast cancer cells (MDA-MB-231) and the normal epithelial cells (MCF-10A) could be distinguished by 85%. The prediction accuracy at the single-cell level reached 97% when both biomechanical and bioelectrical parameters were utilized. While the new label-free assay has been tested to distinguish between normal and cancer cells, its application can be extended to include cell-drug interactions and circulating tumor cell detection in blood.

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.

Biophysical phenotyping of single cells using a differential multiconstriction microfluidic device with self-aligned 3D electrodes

Precise measurement of mechanical and electrical properties of single cells can yield useful information on the physiological and pathological state of cells. In this work, we develop a differential multiconstriction microfluidic device with self-aligned 3D electrodes to simultaneously characterize the deformability, electrical impedance and relaxation index of single cells at a high throughput manner (>430 cell/min). Cells are pressure-driven to flow through a series of sequential microfluidic constrictions, during which deformability, electrical impedance and relaxation index of single cells are extracted simultaneously from impedance spectroscopy measurements. Mechanical and electrical phenotyping of untreated, Cytochalasin B treated and N-Ethylmaleimide treated MCF-7 breast cancer cells demonstrate the ability of our system to distinguish different cell populations purely based on these biophysical properties. In addition, we quantify the classification of different cell types using a back propagation neural network. The trained neural network yields the classification accuracy of 87.8% (electrical impedance), 70.1% (deformability), 42.7% (relaxation index) and 93.3% (combination of electrical impedance, deformability and relaxation index) with high sensitivity (93.3%) and specificity (93.3%) for the test group. Furthermore, we have demonstrated the cell classification of a cell mixture using the presented biophysical phenotyping technique with the trained neural network, which is in quantitative agreement with the flow cytometric analysis using fluorescent labels. The developed concurrent electrical and mechanical phenotyping provide great potential for high-throughput and label-free single cell analysis.

On-chip refractive index cytometry for whole-cell deformability discrimination

On-chip high-throughput phenotyping of single cells has gained a lot of interest recently due to the discrimination capability of label-free biomarkers such as whole-cell deformability and refractive index. Here we present on-chip refractive index cytometry (RIC) for whole-cell deformability at a high measurement rate. We have further exploited a previously published on-chip optical characterization method which enhances cellular discrimination through the refractive index measurement of single cells. The proposed on-chip RIC can simultaneously probe the cellular refractive index, effective volume and whole-cell deformability while reaching a measurement rate up to 5000 cells per second. Additionally, the relative position of the nucleus inside the cell is reflected by the asymmetry of the measured curve. This particular finding is confirmed by our numerical simulation model and emphasized by a modified cytoskeleton HL-60 cells model. Furthermore, the proposed device discriminated HL-60 derived myeloid cells such as neutrophils, basophils and promyelocytes, which are indistinguishable using flow cytometry. To our knowledge, this is the first integrated device to simultaneously characterize the cellular refractive index and whole-cell deformability, yielding enhanced discrimination of large myeloid cell populations.

Label-free detection of live cancer cells and DNA hybridization using 3D multilayered plasmonic biosensor

Three-dimensional (3D) multilayered plasmonic nanostructures consisting of Au nanosquares on top of SU-8 nanopillars, Au asymmetrical nanostructures in the middle, and Au asymmetrical nanoholes at the bottom were fabricated through reversal nanoimprint technology. Compared with two-dimensional and quasi-3D plasmonic nanostructures, the 3D multilayered plasmonic nanostructures showed higher electromagnetic field intensity, longer plasmon decay length and larger plasmon sensing area, which are desirable for highly sensitive localized surface plasmonic resonance biosensors. The sensitivity and resonance peak wavelength of the 3D multilayered plasmonic nanostructures could be adjusted by varying the offset between the top and bottom SU-8 nanopillars from 31% to 56%, and the highest sensitivity of 382 and 442 nm/refractive index unit were observed for resonance peaks at 581 and 805 nm, respectively. Live lung cancer A549 cells with a low concentration of 5 × 10³ cells ml^-1 and a low sample volume of 2 μl could be detected by the 3D multilayered plasmonic nanostructures integrated in a microfluidic system. The 3D plasmonic biosensors also had the advantages of detecting DNA hybridization by capturing the complementary target DNA in the low concentration range of 10^-14-10^-7 M, and providing a large peak shift of 82 nm for capturing 10^-7 M complementary target DNA without additional signal amplification.

Kernel-Based Microfluidic Constriction Assay for Tumor Sample Identification

A high-throughput multiconstriction microfluidic channels device can distinguish human breast cancer cell lines (MDA-MB-231, HCC-1806, MCF-7) from immortalized breast cells (MCF-10A) with a confidence level of ∼81-85% at a rate of 50-70 cells/min based on velocity increment differences through multiconstriction channels aligned in series. The results are likely related to the deformability differences between nonmalignant and malignant breast cells. The data were analyzed by the methods/algorithms of Ridge, nonnegative garrote on kernel machine (NGK), and Lasso using high-dimensional variables, including the cell sizes, velocities, and velocity increments. In kernel learning based methods, the prediction values of 10-fold cross-validations are used to represent the difference between two groups of data, where a value of 100% indicates the two groups are completely distinct and identifiable. The prediction value is used to represent the difference between two groups using the established algorithm classifier from high-dimensional variables. These methods were applied to heterogeneous cell populations prepared using primary tumor and adjacent normal tissue obtained from two patients. Primary breast cancer cells were distinguished from patient-matched adjacent normal cells with a prediction ratio of 70.07%-75.96% by the NGK method. Thus, this high-throughput multiconstriction microfluidic device together with the kernel learning method can be used to perturb and analyze the biomechanical status of cells obtained from small primary tumor biopsy samples. The resultant biomechanical velocity signatures identify malignancy and provide a new marker for evaluation in risk assessment.

Geometric screening of core/shell hydrogel microcapsules using a tapered microchannel with interdigitated electrodes

Core/shell hydrogel microcapsules attract increasing research attention due to their potentials in tissue engineering, food engineering, and drug delivery. Current approaches for generating core/shell hydrogel microcapsules suffer from large geometric variations. Geometrically defective core/shell microcapsules need to be removed before further use. High-throughput geometric characterization of such core/shell microcapsules is therefore necessary. In this work, a continuous-flow device was developed to measure the geometric properties of microcapsules with a hydrogel shell and an aqueous core. The microcapsules were pumped through a tapered microchannel patterned with an array of interdigitated microelectrodes. The geometric parameters (the shell thickness and the diameter) were derived from the displacement profiles of the microcapsules. The results show that this approach can successfully distinguish all unencapsulated microparticles. The geometric properties of core/shell microcapsules can be determined with high accuracy. The efficacy of this method was demonstrated through a drug releasing experiment where the optimization of the electrospray process based on geometric screening can lead to controlled and extended drug releasing profiles. This method does not require high-speed optical systems, simplifying the system configuration and making it an indeed miniaturized device. The throughput of up to 584 microcapsules per minute was achieved. This study provides a powerful tool for screening core/shell hydrogel microcapsules and is expected to facilitate the applications of these microcapsules in various fields.

Smart Cell Culture Systems: Integration of Sensors and Actuators into Microphysiological Systems

Technological advances in microfabrication techniques in combination with organotypic cell and tissue models have enabled the realization of microphysiological systems capable of recapitulating aspects of human physiology in vitro with great fidelity. Concurrently, a number of analysis techniques has been developed to probe and characterize these model systems. However, many assays are still performed off-line, which severely compromises the possibility of obtaining real-time information from the samples under examination, and which also limits the use of these platforms in high-throughput analysis. In this review, we focus on sensing and actuation schemes that have already been established or offer great potential to provide in situ detection or manipulation of relevant cell or tissue samples in microphysiological platforms. We will first describe methods that can be integrated in a straightforward way and that offer potential multiplexing and/or parallelization of sensing and actuation functions. These methods include electrical impedance spectroscopy, electrochemical biosensors, and the use of surface acoustic waves for manipulation and analysis of cells, tissue, and multicellular organisms. In the second part, we will describe two sensor approaches based on surface-plasmon resonance and mechanical resonators that have recently provided new characterization features for biological samples, although technological limitations for use in high-throughput applications still exist.

Multiparameter cell-tracking intrinsic cytometry for single-cell characterization

An abundance of label-free microfluidic techniques for measuring cell intrinsic markers exists, yet these techniques are seldom combined because of integration complexity such as restricted physical space and incompatible modes of operation. We introduce a multiparameter intrinsic cytometry approach for the characterization of single cells that combines ≥2 label-free measurement techniques onto the same platform and uses cell tracking to associate the measured properties to cells. Our proof-of-concept implementation can measure up to five intrinsic properties including size, deformability, and polarizability at three frequencies. Each measurement module along with the integrated platform were validated and evaluated in the context of chemically induced changes in the actin cytoskeleton of cells. viSNE and machine learning classification were used to determine the orthogonality between and the contribution of the measured intrinsic markers for cell classification.

Microfluidic flow cytometry: The role of microfabrication methodologies, performance and functional specification

Flow cytometry is an invaluable tool utilized in modern biomedical research and clinical applications requiring high throughput, high resolution particle analysis for cytometric characterization and/or sorting of cells and particles as well as for analyzing results from immunocytometric assays. In recent years, research has focused on developing microfluidic flow cytometers with the motivation of creating smaller, less expensive, simpler, and more autonomous alternatives to conventional flow cytometers. These devices could ideally be highly portable, easy to operate without extensive user training, and utilized for research purposes and/or point-of-care diagnostics especially in limited resource facilities or locations requiring on-site analyses. However, designing a device that fulfills the criteria of high throughput analysis, automation and portability, while not sacrificing performance is not a trivial matter. This review intends to present the current state of the field and provide considerations for further improvement by focusing on the key design components of microfluidic flow cytometers. The recent innovations in particle focusing and detection strategies are detailed and compared. This review outlines performance matrix parameters of flow cytometers that are interdependent with each other, suggesting trade offs in selection based on the requirements of the applications. The ongoing contribution of microfluidics demonstrates that it is a viable technology to advance the current state of flow cytometry and develop automated, easy to operate and cost-effective flow cytometers.

Recent advances in the use of microfluidic technologies for single cell analysis

The inherent heterogeneity in cell populations has become of great interest and importance as analytical techniques have improved over the past decades. With the advent of personalized medicine, understanding the impact of this heterogeneity has become an important challenge for the research community. Many different microfluidic approaches with varying levels of throughput and resolution exist to study single cell activity. In this review, we take a broad view of the recent microfluidic developments in single cell analysis based on microwell, microchamber, and droplet platforms. We cover physical, chemical, and molecular biology approaches for cellular and molecular analysis including newly emerging genome-wide analysis.

Characterizing Deformability and Electrical Impedance of Cancer Cells in a Microfluidic Device

Mechanical properties of cells, reflective of various biochemical characteristics such as gene expression and cytoskeleton, are promising label-free biomarkers for studying and characterizing cells. Electrical properties of cells, dependent on the cellular structure and content, are also label-free indicators of cell states and phenotypes. In this work, we have developed a microfluidic device that is able to simultaneously characterize the mechanical and electrical properties of individual biological cells in a high-throughput manner (>1000 cells/min). The deformability of MCF-7 breast cancer cells was characterized based on the passage time required for an individual cell to pass through a constriction smaller than the cell size. The total passage time can be divided into two components: the entry time required for a cell to deform and enter a constriction, which is dominated by the deformability of cells, and the transit time required for the fully deformed cell to travel inside the constriction, which mainly relies on the surface friction between cells and the channel wall. The two time durations for individual cells to pass through the entry region and transit region have both been investigated. In addition, undeformed cells and fully deformed cells were simultaneously characterized via electrical impedance spectroscopy technique. The combination of mechanical and electrical properties serves as a unique set of intrinsic cellular biomarkers for single-cell analysis, providing better differentiation of cellular phenotypes, which are not easily discernible via single-marker analysis.

Flow-Induced Transport of Tumor Cells in a Microfluidic Capillary Network: Role of Friction and Repeated Deformation

INTRODUCTION

Circulating tumor cells (CTCs) in microcirculation undergo significant deformation and frictional interactions within microcapillaries. To understand the physical parameters governing their flow-induced transport, we studied the pressure-driven flow of cancer cells in a microfluidic model of a capillary network.

METHODS

Our microfluidic device contains an array of parallel constrictions separated by regions where cells can repetitively deform and relax. To characterize the transport behavior, we measured the entry time, transit time, and shape deformation of tumor cells as they squeeze through the network.

RESULTS

We found that entry and transit times of cells are much lower after repetitive deformation as their elongated shape enables easy transport in subsequent constrictions. Furthermore, upon repetitive deformation, the cells were able to relieve only 25% of their 40% imposed compressional strain, suggesting that tumor cells might have undergone plastic deformation or fatigue. To investigate the influence of surface friction, we characterized the transport behavior in the absence and presence of bovine serum albumin (BSA) coating on the constriction walls. We observed that BSA coating reduces the entry and transit time significantly. Finally, using two breast tumor cell lines, we investigated the effect of metastatic potential on transport properties. We found that the cell lines could be distinguished only upon surface treatment with BSA, thus surface-induced friction is an indicator of metastatic potential.

CONCLUSIONS

Our results suggest that pre-deformation can enhance the transport of CTCs in microcirculation and that frictional interactions with capillary walls can play an important role in influencing the transport of metastatic CTCs.

Accurate Extraction of the Self-Rotational Speed for Cells in an Electrokinetics Force Field by an Image Matching Algorithm

We present an image-matching-based automated algorithm capable of accurately determining the self-rotational speed of cancer cells in an optically-induced electrokinetics-based microfluidic chip. To automatically track a specific cell in a video featuring more than one cell, a background subtraction technique was used. To determine the rotational speeds of cells, a reference frame was automatically selected and curve fitting was performed to improve the stability and accuracy. Results show that the algorithm was able to accurately calculate the self-rotational speeds of cells up to ~150 rpm. In addition, the algorithm could be used to determine the motion trajectories of the cells. Potential applications for the developed algorithm include the differentiation of cell morphology and characterization of cell electrical properties.