A comparison of microfluidic methods for high-throughput cell deformability measurements

Deformability of Heterogeneous Red Blood Cells in Aging and Related Pathologies

Aging is interrelated with changes in red blood cell parameters and functionality. In this article, we focus on red blood cells (RBCs) and provide a review of the known changes associated with the characterization of RBC deformability in aging and related pathologies. The biophysical parameters complement the commonly used biochemical parameters and may contribute to a better understanding of the aging process. The power of the deformability measurement approach is well established in clinical settings. Measuring RBCs' deformability has the advantage of relative simplicity, and it reflects the complex effects developing in erythrocytes during aging. However, aging and related pathological conditions also promote heterogeneity of RBC features and have a certain impact on the variance in erythrocyte cell properties. The possible applications of deformability as an early biophysical biomarker of pathological states are discussed, and modulating PIEZO1 as a therapeutic target is suggested. The changes in RBCs' shape can serve as a proxy for deformability evaluation, leveraging single-cell analysis with imaging flow cytometry and artificial intelligence algorithms. The characterization of biophysical parameters of RBCs is in progress in humans and will provide a better understanding of the complex dynamics of aging.

The F-actin bundler SWAP-70 promotes tumor metastasis

Dynamic rearrangements of the F-actin cytoskeleton are a hallmark of tumor metastasis. Thus, proteins that govern F-actin rearrangements are of major interest for understanding metastasis and potential therapies. We hypothesized that the unique F-actin binding and bundling protein SWAP-70 contributes importantly to metastasis. Orthotopic, ectopic, and short-term tail vein injection mouse breast and lung cancer models revealed a strong positive dependence of lung and bone metastasis on SWAP-70. Breast cancer cell growth, migration, adhesion, and invasion assays revealed SWAP-70's key role in these metastasis-related cell features and the requirement for SWAP-70 to bind F-actin. Biophysical experiments showed that tumor cell stiffness and deformability are negatively modulated by SWAP-70. Together, we present a hitherto undescribed, unique F-actin modulator as an important contributor to tumor metastasis.

An in-silico study on the mechanical behavior of colorectal cancer cell lines in the micropipette aspiration process

Cancer alters the structural integrity and morphology of cells. Consequently, the cell function is overshadowed. In this study, the micropipette aspiration process is computationally modeled to predict the mechanical behavior of the colorectal cancer cells. The intended cancer cells are modeled as an incompressible Neo-Hookean visco-hyperelastic material. Also, the micropipette is assumed to be rigid with no deformation. The proposed model is validated with an in-vitro study. To capture the equilibrium and time-dependent behaviors of cells, ramp, and creep tests are respectively performed using the finite element method. Through the simulations, the effects of the micropipette geometry and the aspiration pressure on the colorectal cancer cell lines are investigated. Our findings indicate that, as the inner radius of the micropipette increases, despite the increase in deformation rate and aspirated length, the time to reach the equilibrium state increases. Nevertheless, it is obvious that increasing the tip curvature radius has a small effect on the change of the aspirated length. But, due to the decrease in the stress concentration, it drastically reduces the equilibrium time and increases the deformation rate significantly. Interestingly, our results demonstrate that increasing the aspiration pressure somehow causes the cell stiffening, thereby reducing the upward trend of deformation rate, equilibrium time, and aspirated length. Our findings provide valuable insights for researchers in cell therapy and cancer treatment and can aid in developing more precise microfluidic.

Liquid Biopsy Instrument for Ultra-Fast and Label-Free Detection of Circulating Tumor Cells

Rapid diagnosis and real-time monitoring are of great important in the fight against cancer. However, most available diagnostic technologies are time-consuming and labor-intensive and are commonly invasive. Here, we describe CytoExam, an automatic liquid biopsy instrument designed based on inertial microfluidics and impedance cytometry, which uses a deep learning algorithm for the analysis of circulating tumor cells (CTCs). In silico and in vitro experiments demonstrated that CytoExam could achieve label-free detection of CTCs in the peripheral blood of cancer patients within 15 min. The clinical applicability of CytoExam was also verified using peripheral blood samples from 10 healthy donors and >50 patients with breast, colorectal, or lung cancer. Significant differences in the number of collected cells and predicted CTCs were observed between the 2 groups, with variations in the dielectric properties of the collected cells from cancer patients also being observed. The ultra-fast and minimally invasive features of CytoExam may pave the way for new paths for cancer diagnosis and scientific research.

Deformation under flow and morphological recovery of cancer cells

The metastatic cascade includes a blood circulation step for cells detached from the primary tumor. This stage involves significant shear stress as well as large and fast deformation as the cells circulate through the microvasculature. These mechanical stimuli are well reproduced in microfluidic devices. However, the recovery dynamics after deformation is also pivotal to understand how a cell can pass through the multiple capillary constrictions encountered during a single hemodynamic cycle. The microfluidic system developed in this work allows single cell recovery to be studied under flow-free conditions following pressure-actuated cell deformation inside constricted microchannels. We used three breast cancer cell lines - namely MCF-7, SK-BR3 and MDA-MB231 - as cellular models representative of different cancer phenotypes. Changing the size of the constriction allows exploration of moderate to strong deformation regimes, the latter being associated with the formation of plasma membrane blebs. In the regime of moderate deformation, all cell types display a fast elastic recovery behavior followed by a slower viscoelastic regime, well described by a double exponential decay. Among the three cell types, cells of the mesenchymal phenotype, i.e. the MDA-MB231 cells, are softer and the most fluid-like, in agreement with previous studies. Our main finding here is that the fast elastic recovery regime revealed by our novel microfluidic system is under the control of cell contractility ensured by the integrity of the cell cortex. Our results suggest that the cell cortex plays a major role in the transit of circulating tumor cells by allowing their fast morphological recovery after deformation in blood capillaries.

Viscoelasticity in 3D Cell Culture and Regenerative Medicine: Measurement Techniques and Biological Relevance

The field of mechanobiology is gaining prominence due to recent findings that show cells sense and respond to the mechanical properties of their environment through a process called mechanotransduction. The mechanical properties of cells, cell organelles, and the extracellular matrix are understood to be viscoelastic. Various technologies have been researched and developed for measuring the viscoelasticity of biological materials, which may provide insight into both the cellular mechanisms and the biological functions of mechanotransduction. Here, we explain the concept of viscoelasticity and introduce the major techniques that have been used to measure the viscoelasticity of various soft materials in different length- and timescale frames. The topology of the material undergoing testing, the geometry of the probe, the magnitude of the exerted stress, and the resulting deformation should be carefully considered to choose a proper technique for each application. Lastly, we discuss several applications of viscoelasticity in 3D cell culture and tissue models for regenerative medicine, including organoids, organ-on-a-chip systems, engineered tissue constructs, and tunable viscoelastic hydrogels for 3D bioprinting and cell-based therapies.

Robust Gradient Hydrogel-Loaded Nanofiber Fleshy Artificial Skin Via A Coupled Microfluidic Electrospinning-Reactive Coating Strategy

Skin regeneration attracts tremendous interest due to the important role of skin for human protection and beauty. Thus, methods allowing artificial skin to be carried out in a controllable fashion are potentially important for wound healing, which involves an intersection of materials, medicine, biology, and other disciplines. Herein, aiming at a new general methodology for fleshy materials, a new hydrogel-loaded hydrophobic-hydrophilic nanofiber fleshy artificial skin is designed and fabricated. The gradient hydrogel-loaded nanofiber artificial skin integrates both advantages of nanofiber and hydrogel, exhibiting fleshy feature (comparability to real skin in terms of appearance, texture, and function), excellent air permeability, compatibility, and good mechanical and antibacterial property. Interestingly, the efficient transport channels are formed throughout the hydrogel-loaded nanofiber structure, which is beneficial for water absorption and transfer. These advantages enable the establishment of a moist and favorable microenvironment; thus, greatly accelerating wound healing process. This work couples microfluidic electrospinning with reactive coating technique, which is in favor of material design and fabrication with controllable and uniform structures. The hydrogel-loaded nanofiber fleshy artificial skin shows comparability to real skin in terms of beauty, texture, and function, which would definitely provide new opportunities for the further optimization and upgrading of artificial skin.

Boosting antitumor efficacy of nanoparticles by modulating tumor mechanical microenvironment

Nanoparticles have shown great potential for tumor targeting delivery via enhanced permeability and retention effect. However, the tumor mechanical microenvironment, characterized by dense extracellular matrix (ECM), high tumor stiffness and solid stress, leads to only 0.7% of administered dose accumulating in solid tumors and even fewer (∼0.0014%) reaching tumor cells, limiting the therapeutic efficacy of nanoparticles. Furthermore, the tumor mechanical microenvironment can regulate tumor cell stemness, promote tumor invasion, metastasis and reduce treatment efficacy. In this review, methods detecting the mechanical are introduced. Strategies for modulating the mechanical microenvironment including elimination of dense ECM by physical, chemical and biological methods, disruption of ECM formation, depletion or inhibition of cancer-associated fibroblasts, are then summarized. Finally, prospects and challenges for further clinical applications of mechano-modulating strategies to enhance the therapeutic efficacy of nanomedicines are discussed. This review may provide guidance for the rational design and application of nanoparticles in clinical settings.

Microfluidic characterization of single-cell biophysical properties and the applications in cancer diagnosis

Single-cell biophysical properties play a crucial role in regulating cellular physiological states and functions, demonstrating significant potential in the fields of life sciences and clinical diagnostics. Therefore, over the last few decades, researchers have developed various detection tools to explore the relationship between the biophysical changes of biological cells and human diseases. With the rapid advancement of modern microfabrication technology, microfluidic devices have quickly emerged as a promising platform for single-cell analysis offering advantages including high-throughput, exceptional precision, and ease of manipulation. Consequently, this paper provides an overview of the recent advances in microfluidic analysis and detection systems for single-cell biophysical properties and their applications in the field of cancer. The working principles and latest research progress of single-cell biophysical property detection are first analyzed, highlighting the significance of electrical and mechanical properties. The development of data acquisition and processing methods for real-time, high-throughput, and practical applications are then discussed. Furthermore, the differences in biophysical properties between tumor and normal cells are outlined, illustrating the potential for utilizing single-cell biophysical properties for tumor cell identification, classification, and drug response assessment. Lastly, we summarize the limitations of existing microfluidic analysis and detection systems in single-cell biophysical properties, while also pointing out the prospects and future directions of their applications in cancer diagnosis and treatment.

Single-Cell Mechanics: Structural Determinants and Functional Relevance

The mechanical phenotype of a cell determines its ability to deform under force and is therefore relevant to cellular functions that require changes in cell shape, such as migration or circulation through the microvasculature. On the practical level, the mechanical phenotype can be used as a global readout of the cell's functional state, a marker for disease diagnostics, or an input for tissue modeling. We focus our review on the current knowledge of structural components that contribute to the determination of the cellular mechanical properties and highlight the physiological processes in which the mechanical phenotype of the cells is of critical relevance. The ongoing efforts to understand how to efficiently measure and control the mechanical properties of cells will define the progress in the field and drive mechanical phenotyping toward clinical applications.

High-Throughput Sorting and Single-Cell Mechanotyping by Hydrodynamic Sorting-Mechanotyping Cytometry

The existence of many background blood cells hinders the accurate identification of circulating tumor cells (CTCs) in the blood of cancer patients. To unlock this limitation, a hydrodynamic sorting-mechanotyping cytometry (HSMC) integrated with a sorting-concentration chip and a detection chip is proposed for simultaneously achieving the high-throughput cell sorting and the multi-parameter mechanotyping of the sorted tumor cells. The HSMC adopts the spiral inertial microfluidics for label-free sorting of cells in a high-throughput manner, allowing the efficient enrichment of tumor cells from the large background blood cells. Then, the sorted cells are concentrated by the concentration unit and finally passed through the detection unit for hydrodynamic deformation. The HSMC has a high throughput for sorting and detection and can successfully reveal the differences in the cellular mechanical properties. After characterizing and optimizing the single chips, the identification of white blood cells (WBCs) and three types of tumor cells (A549, MCF-7, and MDA-MB-231 cells) is successfully achieved. The identification accuracies for WBCs and different tumor cells are all larger than 94%, while the highest identification accuracy is up to 99.2%. This study envisions that the HSMC will offer an avenue for the analysis of single cell intrinsic mechanics in clinical medicine.

Elasticity of Carrier Fluid: A Key Factor Affecting Mechanical Phenotyping in Deformability Cytometry

Recently, microfluidics deformability cytometry has emerged as a powerful tool for high-throughput mechanical phenotyping of large populations of cells. These methods characterize cells by their mechanical fingerprints by exerting hydrodynamic forces and monitoring the resulting deformation. These devices have shown great promise for label-free cytometry, yet there is a critical need to improve their accuracy and reconcile any discrepancies with other methods, such as atomic force microscopy. In this study, we employ computational fluid dynamics simulations and uncover how the elasticity of frequently used carrier fluids, such as methylcellulose dissolved in phosphate-buffered saline, is significantly influential to the resulting cellular deformation. We conducted CFD simulations conventionally used within the deformability cytometry field, which neglect fluid elasticity. Subsequently, we incorporated a more comprehensive model that simulates the viscoelastic nature of the carrier fluid. A comparison of the predicted stresses between these two approaches underscores the significance of the emerging elastic stresses in addition to the well-recognized viscous stresses along the channel. Furthermore, we utilize a two-phase flow model to predict the deformation of a promyelocyte (i.e., HL-60 cell type) within a hydrodynamic constriction channel. The obtained results highlight a substantial impact of the elasticity of carrier fluid on cellular deformation and raise questions about the accuracy of mechanical property estimates derived by neglecting elastic stresses.

Biomechanics of circulating cellular and subcellular bioparticles: beyond separation

Biomechanical attributes have emerged as novel markers, providing a reliable means to characterize cellular and subcellular fractions. Numerous studies have identified correlations between these factors and patients' medical status. However, the absence of a thorough overview impedes their applicability in contemporary state-of-the-art therapeutic strategies. In this context, we provide a comprehensive analysis of the dimensions, configuration, rigidity, density, and electrical characteristics of normal and abnormal circulating cells. Subsequently, the discussion broadens to encompass subcellular bioparticles, such as extracellular vesicles (EVs) enriched either from blood cells or other tissues. Notably, cell sizes vary significantly, from 2 μm for platelets to 25 μm for circulating tumor cells (CTCs), enabling the development of size-based separation techniques, such as microfiltration, for specific diagnostic and therapeutic applications. Although cellular density is relatively constant among different circulating bioparticles, it allows for reliable density gradient centrifugation to isolate cells without altering their native state. Additionally, variations in EV surface charges (-6.3 to -45 mV) offer opportunities for electrophoretic and electrostatic separation methods. The distinctive mechanical properties of abnormal cells, compared to their normal counterparts, present an exceptional opportunity for diverse medical and biotechnological approaches. This review also aims to provide a holistic view of the current understanding of popular techniques in this domain that transcend conventional boundaries, focusing on early harvesting of malignant cells from body fluids, designing effective therapeutic options, cell targeting, and resonating with tissue and genetic engineering principles.

Parallel on-chip micropipettes enabling quantitative multiplexed characterization of vesicle mechanics and cell aggregates rheology

Micropipette aspiration (MPA) is one of the gold standards for quantifying biological samples' mechanical properties, which are crucial from the cell membrane scale to the multicellular tissue. However, relying on the manipulation of individual home-made glass pipettes, MPA suffers from low throughput and no automation. Here, we introduce the sliding insert micropipette aspiration method, which permits parallelization and automation, thanks to the insertion of tubular pipettes, obtained by photolithography, within microfluidic channels. We show its application both at the lipid bilayer level, by probing vesicles to measure membrane bending and stretching moduli, and at the tissue level by quantifying the viscoelasticity of 3D cell aggregates. This approach opens the way to high-throughput, quantitative mechanical testing of many types of biological samples, from vesicles and individual cells to cell aggregates and explants, under dynamic physico-chemical stimuli.

Mechanical complexity of living cells can be mapped onto simple homogeneous equivalents

Biological cells are built up from different constituents of varying size and stiffness which all contribute to the cell's mechanical properties. Despite this heterogeneity, in the analysis of experimental measurements one often assumes a strongly simplified homogeneous cell and thus a single elastic modulus is assigned to the entire cell. This ad-hoc simplification has so far mostly been used without proper justification. Here, we use computer simulations to show that indeed a mechanically heterogeneous cell can effectively be replaced by a homogeneous equivalent cell with a volume averaged elastic modulus. To demonstrate the validity of this approach, we investigate a hyperelastic cell with a heterogeneous interior under compression and in shear/channel flow mimicking atomic force and microfluidic measurements, respectively. We find that the homogeneous equivalent cell reproduces quantitatively the behavior of its heterogeneous counterpart, and that this equality is largely independent of the stiffness or spatial distribution of the heterogeneity.

How cytoskeletal crosstalk makes cells move: Bridging cell-free and cell studies

Cell migration is a fundamental process for life and is highly dependent on the dynamical and mechanical properties of the cytoskeleton. Intensive physical and biochemical crosstalk among actin, microtubules, and intermediate filaments ensures their coordination to facilitate and enable migration. In this review, we discuss the different mechanical aspects that govern cell migration and provide, for each mechanical aspect, a novel perspective by juxtaposing two complementary approaches to the biophysical study of cytoskeletal crosstalk: live-cell studies (often referred to as top-down studies) and cell-free studies (often referred to as bottom-up studies). We summarize the main findings from both experimental approaches, and we provide our perspective on bridging the two perspectives to address the open questions of how cytoskeletal crosstalk governs cell migration and makes cells move.

The Plasma Membrane and Mechanoregulation in Cells

Cells inhabit a mechanical microenvironment that they continuously sense and adapt to. The plasma membrane (PM), serving as the boundary of the cell, plays a pivotal role in this process of adaptation. In this Review, we begin by examining well-studied processes where mechanoregulation proves significant. Specifically, we highlight examples from the immune system and stem cells, besides discussing processes involving fibroblasts and other cell types. Subsequently, we discuss the common molecular players that facilitate the sensing of the mechanical signal and transform it into a chemical response covering integrins YAP/TAZ and Piezo. We then review how this understanding of molecular elements is leveraged in drug discovery and tissue engineering alongside a discussion of the methodologies used to measure mechanical properties. Focusing on the processes of endocytosis, we discuss how cells may respond to altered membrane mechanics using endo- and exocytosis. Through the process of depleting/adding the membrane area, these could also impact membrane mechanics. We compare pathways from studies illustrating the involvement of endocytosis in mechanoregulation, including clathrin-mediated endocytosis (CME) and the CLIC/GEEC (CG) pathway as central examples. Lastly, we review studies on cell-cell fusion during myogenesis, the mechanical integrity of muscle fibers, and the reported and anticipated roles of various molecular players and processes like endocytosis, thereby emphasizing the significance of mechanoregulation at the PM.

A microfluidic microalgae detection system for cellular physiological response based on an object detection algorithm

The composition of species and the physiological status of microalgal cells serve as significant indicators for monitoring marine environments. Symbiotic with corals, Symbiodiniaceae are more sensitive to the environmental response. However, current methods for evaluating microalgae tend to be population-based indicators that cannot be focused on single-cell level, ignoring potentially heterogeneous cells as well as cell state transitions. In this study, we proposed a microalgal cell detection method based on computer vision and microfluidics, which combined microscopic image processing, microfluidic chip and convolutional neural network to achieve label-free, sheathless, automated and high-throughput microalgae identification and cell state assessment. By optimizing the data import, training process and model architecture, we solved the problem of identifying tiny objects at the micron scale, and the optimized model was able to perform the tasks of cell multi-classification and physiological state assessment with more than 95% mean average precision. We discovered a novel transition state and explored the thermal sensitivity of three clades of Symbiodiniaceae, and discovered the phenomenon of cellular heat shock at high temperatures. The evolution of the physiological state of Symbiodiniaceae cells is very important for directional cell evolution and early warning of coral ecosystem health.

Phenotypic targeting using magnetic nanoparticles for rapid characterization of cellular proliferation regulators

Genome-wide CRISPR screens have provided a systematic way to identify essential genetic regulators of a phenotype of interest with single-cell resolution. However, most screens use live/dead readout of viability to identify factors of interest. Here, we describe an approach that converts cell proliferation into the degree of magnetization, enabling downstream microfluidic magnetic sorting to be performed. We performed a head-to-head comparison and verified that the magnetic workflow can identify the same hits from a traditional screen while reducing the screening period from 4 weeks to 1 week. Taking advantage of parallelization and performance, we screened multiple mesenchymal cancer cell lines for their dependency on cell proliferation. We found and validated pan- and cell-specific potential therapeutic targets. The method presented provides a nanoparticle-enabled approach means to increase the breadth of data collected in CRISPR screens, enabling the rapid discovery of drug targets for treatment.

High-throughput viscoelastic characterization of cells in hyperbolic microchannels

Extensive research has demonstrated the potential of cell viscoelastic properties as intrinsic indicators of cell state, functionality, and disease. For this, several microfluidic techniques have been developed to measure cell viscoelasticity with high-throughput. However, current microchannel designs introduce complex stress distributions on cells, leading to inaccuracies in determining the stress-strain relationship and, consequently, the viscoelastic properties. Here, we introduce a novel approach using hyperbolic microchannels that enable precise measurements under a constant extensional stress and offer a straightforward stress-strain relationship, while operating at a measurement rate of up to 100 cells per second. We quantified the stresses acting in the channels using mechanical calibration particles made from polyacrylamide (PAAm) and found that the measurement buffer, a solution of methyl cellulose and phosphate buffered saline, shows strain-thickening following a power law up to 200 s-1. By measuring oil droplets with varying viscosities, we successfully detected changes in the relaxation times of the droplets and our approach could be used to get the interfacial tension and viscosity of liquid-liquid droplet systems from the same measurement. We further applied this methodology to PAAm microgel beads, demonstrating the accurate recovery of Young's moduli and the near-ideal elastic behavior of the beads. To explore the influence of altered cell viscoelasticity, we treated HL60 human leukemia cells with latrunculin B and nocodazole, resulting in clear changes in cell stiffness while relaxation times were only minimally affected. In conclusion, our approach offers a streamlined and time-efficient solution for assessing the viscoelastic properties of large cell populations and other microscale soft particles.

Using a micro-device with a deformable ceiling to probe stiffness heterogeneities within 3D cell aggregates

Recent advances in the field of mechanobiology have led to the development of methods to characterise single-cell or monolayer mechanical properties and link them to their functional behaviour. However, there remains a strong need to establish this link for three-dimensional (3D) multicellular aggregates, which better mimic tissue function. Here we present a platform to actuate and observe many such aggregates within one deformable micro-device. The platform consists of a single polydimethylsiloxane piece cast on a 3D-printed mould and bonded to a glass slide or coverslip. It consists of a chamber containing cell spheroids, which is adjacent to air cavities that are fluidically independent. Controlling the air pressure in these air cavities leads to a vertical displacement of the chamber's ceiling. The device can be used in static or dynamic modes over time scales of seconds to hours, with displacement amplitudes from a fewµm to several tens of microns. Further, we show how the compression protocols can be used to obtain measurements of stiffness heterogeneities within individual co-culture spheroids, by comparing image correlations of spheroids at different levels of compression with finite element simulations. The labelling of the cells and their cytoskeleton is combined with image correlation methods to relate the structure of the co-culture spheroid with its mechanical properties at different locations. The device is compatible with various microscopy techniques, including confocal microscopy, which can be used to observe the displacements and rearrangements of single cells and neighbourhoods within the aggregate. The complete experimental and imaging platform can now be used to provide multi-scale measurements that link single-cell behaviour with the global mechanical response of the aggregates.

Enhancing micropipette aspiration with artificial-intelligence analysis

The micropipette-aspiration technique is commonly used in the field of mechanobiology, offering a variety of measurement types. To extract biophysical parameters from the experiments, numerical analysis is required. Although previous works have developed techniques for the partial automation of these analyses, these approaches are relatively time consuming for the researchers. In this article, we describe the development and application of an artificial-intelligence tool for the completely automatic analysis of micropipette-aspiration experiments. The use of this tool is compared with previous methods and the impressive reduction in the time required for these analyses is discussed. The new tool opens new possibilities for the micropipette-aspiration technique by enabling dealing with large numbers of experiments and real-time measurements.

Towards a biomimetic cellular structure and physical morphology with liposome-encapsulated agarose sol systems

The cytoplasm, serving as the primary hub of cellular metabolism, stands as a pivotal cornerstone for the harmonious progression of life. The ideal artificial cell should not only have a biomembrane structure system similar to that of a cell and the function of carrying genetic information, but also should have an intracellular environment. In this pursuit, we employed a method involving the incorporation of glycerol into agarose, resulting in the formation of agarose-glycerol mixed sol (AGs). This dynamic sol exhibited fluidic properties at ambient temperature, closely mimicking the viscosity of authentic cytoplasm. Harnessing the electroformation technique, AGs was encapsulated within liposomes, enabling the efficient creation of artificial cells that closely resembled native cellular dimensions through meticulous parameter adjustments of the alternating current (AC) field. Subsequently, artificial cells harboring AGs were subjected to diverse electrolyte and non-electrolyte solutions, enabling a comprehensive exploration of their deformation phenomena, encompassing both inward and outward budding. This study represents a significant stride forward in addressing one of the most fundamental challenges in the construction of artificial cytoplasm. It is our fervent aspiration that this work shall offer invaluable insights and guidance for future endeavors in the realm of artificial cell construction.

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.

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation

Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC technology remains a challenge owing to the insignificant differences in data. Here, we developed a convolutional neural networks (ConvNet) deep learning approach to enhance the accuracy and efficiency of the IFC toward distinguishing various species of bacteria. First, more than 1 million sets of impedance data (comprising 42 characteristic features for each set) of various groups of bacteria were trained by the ConvNet model. To improve the efficiency for data analysis, the Spearman correlation coefficient and the mean decrease accuracy of the random forest algorithm were introduced to eliminate feature interaction and extract the opacity of impedance related to the bacterial wall and membrane structure as the predominant features in bacterial differentiation. Moreover, the 25 optimized features were selected with differentiation accuracies of >96% for three groups of bacteria (bacilli, cocci, and vibrio) and >95% for two species of bacilli (Escherichia coli and Salmonella enteritidis), compared to machine learning algorithms (complex tree, linear discriminant, and K-nearest neighbor algorithms) with a maximum accuracy of 76.4%. Furthermore, bacterial differentiation was achieved on spiked samples of different species with different mixing ratios. The proposed ConvNet deep learning-assisted data analysis method of IFC exhibits advantages in analyzing a huge number of data sets with capacity for extracting predominant features within multicomponent information and will bring about progress and advances in the fields of both biosensing and data analysis.

Hydrodynamic shear stress' impact on mammalian cell properties and its applications in 3D bioprinting

As an effective cell assembly method, three-dimensional bioprinting has been widely used in building organ models and tissue repair over the past decade. However, different shear stresses induced throughout the entire printing process can cause complex impacts on cell integrity, including reducing cell viability, provoking morphological changes and altering cellular functionalities. The potential effects that may occur and the conditions under which these effects manifest are not clearly understood. Here, we review systematically how different mammalian cells respond under shear stress. We enumerate available experimental apparatus, and we categorise properties that can be affected under disparate stress patterns. We also summarise cell damaging mathematical models as a predicting reference for the design of bioprinting systems. We concluded that it is essential to quantify specific cell resistance to shear stress for the optimisation of bioprinting systems. Besides, as substantial positive impacts, including inducing cell alignment and promoting cell motility, can be generated by shear stress, we suggest that we find the proper range of shear stress and actively utilise its positive influences in the development of future systems.

Inertial Multi-Force Deformability Cytometry for High-Throughput, High-Accuracy, and High-Applicability Tumor Cell Mechanotyping

Previous on-chip technologies for characterizing the cellular mechanical properties often suffer from a low throughput and limited sensitivity. Herein, an inertial multi-force deformability cytometry (IMFDC) is developed for high-throughput, high-accuracy, and high-applicability tumor cell mechanotyping. Three different deformations, including shear deformations and stretch deformations under different forces, are integrated with the IMFDC. The 3D inertial focusing of cells enables the cells to deform by an identical fluid flow, and 10 parameters, such as cell area, perimeter, deformability, roundness, and rectangle deformability, are obtained in three deformations. The IMFDC is able to evaluate the deformability of different cells that are sensitive to different forces on a single chip, demonstrating the high applicability of the IMFDC in analyzing different cell lines. In identifying cell types, the three deformations exhibit different mechanical responses to cells with different sizes and deformability. A discrimination accuracy of ≈93% for both MDA-MB-231 and MCF-10A cells and a throughput of ≈500 cells s-1 can be achieved using the multiple-parameters-based machine learning model. Finally, the mechanical properties of metastatic tumor cells in pleural and peritoneal effusions are characterized, enabling the practical application of the IMFDC in clinical cancer diagnosis.

Microfluidic Platforms for Real-Time In Situ Monitoring of Biomarkers for Cellular Processes

Cellular processes are mechanisms carried out at the cellular level that are aimed at guaranteeing the stability of the organism they comprise. The investigation of cellular processes is key to understanding cell fate, understanding pathogenic mechanisms, and developing new therapeutic technologies. Microfluidic platforms are thought to be the most powerful tools among all methodologies for investigating cellular processes because they can integrate almost all types of the existing intracellular and extracellular biomarker-sensing methods and observation approaches for cell behavior, combined with precisely controlled cell culture, manipulation, stimulation, and analysis. Most importantly, microfluidic platforms can realize real-time in situ detection of secreted proteins, exosomes, and other biomarkers produced during cell physiological processes, thereby providing the possibility to draw the whole picture for a cellular process. Owing to their advantages of high throughput, low sample consumption, and precise cell control, microfluidic platforms with real-time in situ monitoring characteristics are widely being used in cell analysis, disease diagnosis, pharmaceutical research, and biological production. This review focuses on the basic concepts, recent progress, and application prospects of microfluidic platforms for real-time in situ monitoring of biomarkers in cellular processes.

High-throughput single-cell assay for precise measurement of the intrinsic mechanical properties and shape characteristics of red blood cells

The intrinsic physical and mechanical properties of red blood cells (RBCs), including their geometric and rheological characteristics, can undergo changes in various circulatory and metabolic diseases. However, clinical diagnosis using RBC biophysical phenotypes remains impractical due to the unique biconcave shape, remarkable deformability, and high heterogeneity within different subpopulations. Here, we combine the hydrodynamic mechanisms of fluid-cell interactions in micro circular tubes with a machine learning method to develop a relatively high-throughput microfluidic technology that can accurately measure the shear modulus of the membrane, viscosity, surface area, and volume of individual RBCs. The present method can detect the subtle changes of mechanical properties in various RBC components at continuum scales in response to different doses of cytoskeletal drugs. We also investigate the correlation between glycosylated hemoglobin and RBC mechanical properties. Our study develops a methodology that combines microfluidic technology and machine learning to explore the material properties of cells based on fluid-cell interactions. This approach holds promise in offering novel label-free single-cell-assay-based biophysical markers for RBCs, thereby enhancing the potential for more robust disease diagnosis.

Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels

During the multistep process of metastasis, cancer cells encounter various mechanical forces which make them deform drastically. Developing accurate in-silico models, capable of simulating the interactions between the mechanical forces and highly deformable cancer cells, can pave the way for the development of novel diagnostic and predictive methods for metastatic progression. Spring-network models of cancer cell, empowered by our recently proposed identification approach, promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular scale. Using this numerical tool, we presented spring-network models of breast cancer cells that can accurately replicate the experimental data of deformation behavior of the cells flowing in a fluidic domain and passing narrow constrictions comparable to microcapillary. First, using high-speed imaging, we experimentally studied the deformability of breast cancer cell lines with varying metastatic potential (MCF-7 (less invasive), SKBR-3 (medium-high invasive), and MDA-MB-231 (highly invasive)) in terms of their entry time to a constricted microfluidic channel. We observed that MDA-MB-231, that has the highest metastatic potential, is the most deformable cell among the three. Then, by focusing on this cell line, experimental measurements were expanded to two more constricted microchannel dimensions. The experimental deformability data in three constricted microchannel sizes for various cell sizes, enabled accurate identification of the unknown parameters of the spring-network model of the breast cancer cell line (MDA-MB-231). Our results show that the identified parameters depend on the cell size, suggesting the need for a systematic procedure for identifying the size-dependent parameters of spring-network models of cells. As the numerical results show, the presented cell models can simulate the entry process of the cell into constricted channels with very good agreements with the measured experimental data.

Characterization of Cancer Cell Mechanics by Measuring Active Deformation Behavior

Active deformation behavior reflects cell structural dynamics adapting to varying environmental constraints during malignancy progression. In most cases, cell mechanics is characterized by modeling using static equilibrium systems, which fails to comprehend cell deformation behavior leading to inaccuracies in distinguishing cancer cells from normal cells. Here, a method is introduced to measure the active deformation behavior of cancer cells using atomic force microscopy (AFM) and the newly developed deformation behavior cytometry (DBC). During the measurement, cells are deformed and allows a long timescale relaxation (≈5 s). Two parameters are derived to represent deformation behavior: apparent Poisson's ratio for adherent cells, which is measured with AFM and refers to the ratio of the lateral strain to the longitudinal strain of the cell, and shape recovery for suspended cells, which is measured with DBC. Active deformation behavior defines cancer cell mechanics better than traditional mechanical parameters (e.g., stiffness, diffusion, and viscosity). Additionally, aquaporins are essential for promoting the deformation behavior, while the actin cytoskeleton acts as a downstream effector. Therefore, the potential application of the cancer cell active deformation behavior as a biomechanical marker or therapeutic target in cancer treatment should be evaluated.

High-throughput quantification of red blood cell deformability and oxygen saturation to probe mechanisms of sickle cell disease

The complex, systemic pathology of sickle cell disease is driven by multiple mechanisms including red blood cells (RBCs) stiffened by polymerized fibers of deoxygenated sickle hemoglobin. A critical step toward understanding the pathologic role of polymer-containing RBCs is quantifying the biophysical changes in these cells in physiologically relevant oxygen environments. We have developed a microfluidic platform capable of simultaneously measuring single RBC deformability and oxygen saturation under controlled oxygen and shear stress. We found that RBCs with detectable amounts of polymer have decreased oxygen affinity and decreased deformability. Surprisingly, the deformability of the polymer-containing cells is oxygen-independent, while the fraction of these cells increases as oxygen decreases. We also find that some fraction of these cells is present at most physiologic oxygen tensions, suggesting a role for these cells in the systemic pathologies. Additionally, the ability to measure these pathological cells should provide clearer targets for evaluating therapies.

Deformability-Based Microfluidic Microdroplet Screening to Obtain Agarolytic Bacterial Cells

Environmental microorganisms possess enzymes that can digest macromolecules such as agarose into smaller molecules that can be utilized for growth. These enzymes could be valuable for the effective utilization of global resources. However, since most of the microorganisms on Earth remain uncultured, there is significant untapped enzymatic potential in nature. Therefore, it is necessary to develop innovative tools and strategies for exploring these enzymatic resources. To address this, we developed a method for screening microbial cells that secrete hydrogel-degrading enzymes using deformability-based microfluidic microdroplet sorting. In this method, microbial cells are encapsulated as single cells in water-in-oil (W/O) microdroplets with a hydrogel whose shape becomes deformable as the hydrogel is progressively degraded into smaller molecules. Screening is achieved using a microfluidic device that passively sorts the deformed W/O microdroplets. Using this method, we successfully sorted agarose-containing microdroplets, encapsulating single bacterial cells that hydrolyzed agarose. This method can be used to screen various hydrogel-degrading microbial cells.

IL-3 receptor signalling suppresses chronic intestinal inflammation by controlling mechanobiology and tissue egress of regulatory T cells

IL-3 has been reported to be involved in various inflammatory disorders, but its role in inflammatory bowel disease (IBD) has not been addressed so far. Here, we determined IL-3 expression in samples from patients with IBD and studied the impact of Il3 or Il3r deficiency on T cell-dependent experimental colitis. We explored the mechanical, cytoskeletal and migratory properties of Il3r -/- and Il3r +/+ T cells using real-time deformability cytometry, atomic force microscopy, scanning electron microscopy, fluorescence recovery after photobleaching and in vitro and in vivo cell trafficking assays. We observed that, in patients with IBD, the levels of IL-3 in the inflamed mucosa were increased. In vivo, experimental chronic colitis on T cell transfer was exacerbated in the absence of Il-3 or Il-3r signalling. This was attributable to Il-3r signalling-induced changes in kinase phosphorylation and actin cytoskeleton structure, resulting in increased mechanical deformability and enhanced egress of Tregs from the inflamed colon mucosa. Similarly, IL-3 controlled mechanobiology in human Tregs and was associated with increased mucosal Treg abundance in patients with IBD. Collectively, our data reveal that IL-3 signaling exerts an important regulatory role at the interface of biophysical and migratory T cell features in intestinal inflammation and suggest that this might be an interesting target for future intervention.

Impedance-Based Multimodal Electrical-Mechanical Intrinsic Flow Cytometry

Reflecting various physiological states and phenotypes of single cells, intrinsic biophysical characteristics (e.g., mechanical and electrical properties) are reliable and important, label-free biomarkers for characterizing single cells. However, single-modal mechanical or electrical properties alone are not specific enough to characterize single cells accurately, and it has been long and challenging to couple the conventionally image-based mechanical characterization and impedance-based electrical characterization. In this work, the spatial-temporal characteristics of impedance sensing signal are leveraged, and an impedance-based multimodal electrical-mechanical flow cytometry framework for on-the-fly high-dimensional intrinsic measurement is proposed, that is, Young's modulus E, fluidity β, radius r, cytoplasm conductivity σi , and specific membrane capacitance Csm , of single cells. With multimodal high-dimensional characterization, the electrical-mechanical flow cytometry can better reveal the difference in cell types, demonstrated by the experimental results with three types of cancer cells (HepG2, MCF-7, and MDA-MB-468) with 93.4% classification accuracy and pharmacological perturbations of the cytoskeleton (fixed and Cytochalasin B treated cells) with 95.1% classification accuracy. It is envisioned that multimodal electrical-mechanical flow cytometry provides a new perspective for accurate label-free single-cell intrinsic characterization.

Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies

During surgery, rapid and accurate histopathological diagnosis is essential for clinical decision making. Yet the prevalent method of intra-operative consultation pathology is intensive in time, labour and costs, and requires the expertise of trained pathologists. Here we show that biopsy samples can be analysed within 30 min by sequentially assessing the physical phenotypes of singularized suspended cells dissociated from the tissues. The diagnostic method combines the enzyme-free mechanical dissociation of tissues, real-time deformability cytometry at rates of 100-1,000 cells s-1 and data analysis by unsupervised dimensionality reduction and logistic regression. Physical phenotype parameters extracted from brightfield images of single cells distinguished cell subpopulations in various tissues, enhancing or even substituting measurements of molecular markers. We used the method to quantify the degree of colon inflammation and to accurately discriminate healthy and tumorous tissue in biopsy samples of mouse and human colons. This fast and label-free approach may aid the intra-operative detection of pathological changes in solid biopsies.

Reliable, standardized measurements for cell mechanical properties

Atomic force microscopy (AFM) has become indispensable for studying biological and medical samples. More than two decades of experiments have revealed that cancer cells are softer than healthy cells (for measured cells cultured on stiff substrates). The softness or, more precisely, the larger deformability of cancer cells, primarily independent of cancer types, could be used as a sensitive marker of pathological changes. The wide application of biomechanics in clinics would require designing instruments with specific calibration, data collection, and analysis procedures. For these reasons, such development is, at present, still very limited, hampering the clinical exploitation of mechanical measurements. Here, we propose a standardized operational protocol (SOP), developed within the EU ITN network Phys2BioMed, which allows the detection of the biomechanical properties of living cancer cells regardless of the nanoindentation instruments used (AFMs and other indenters) and the laboratory involved in the research. We standardized the cell cultures, AFM calibration, measurements, and data analysis. This effort resulted in a step-by-step SOP for cell cultures, instrument calibration, measurements, and data analysis, leading to the concordance of the results (Young's modulus) measured among the six EU laboratories involved. Our results highlight the importance of the SOP in obtaining a reproducible mechanical characterization of cancer cells and paving the way toward exploiting biomechanics for diagnostic purposes in clinics.

Recent advances in deformation-assisted microfluidic cell sorting technologies

Cell sorting is an essential prerequisite for cell research and has great value in life science and clinical studies. Among the many microfluidic cell sorting technologies, label-free methods based on the size of different cell types have been widely studied. However, the heterogeneity in size for cells of the same type and the inevitable size overlap between different types of cells would result in performance degradation in size-based sorting. To tackle such challenges, deformation-assisted technologies are receiving more attention recently. Cell deformability is an inherent biophysical marker of cells that reflects the changes in their internal structures and physiological states. It provides additional dimensional information for cell sorting besides size. Therefore, in this review, we summarize the recent advances in deformation-assisted microfluidic cell sorting technologies. According to how the deformability is characterized and the form in which the force acts, the technologies can be divided into two categories: (1) the indirect category including transit-time-based and image-based methods, and (2) the direct category including microstructure-based and hydrodynamics-based methods. Finally, the separation performance and the application scenarios of each method, the existing challenges and future outlook are discussed. Deformation-assisted microfluidic cell sorting technologies are expected to realize greater potential in the label-free analysis of cells.

A deformability-based biochip for precise label-free stratification of metastatic subtypes using deep learning

Cellular deformability is a promising biomarker for evaluating the physiological state of cells in medical applications. Microfluidics has emerged as a powerful technique for measuring cellular deformability. However, existing microfluidic-based assays for measuring cellular deformability rely heavily on image analysis, which can limit their scalability for high-throughput applications. Here, we develop a parallel constriction-based microfluidic flow cytometry device and an integrated computational framework (ATMQcD). The ATMQcD framework includes automatic training set generation, multiple object tracking, segmentation, and cellular deformability quantification. The system was validated using cancer cell lines of varying metastatic potential, achieving a classification accuracy of 92.4% for invasiveness assessment and stratifying cancer cells before and after hypoxia treatment. The ATMQcD system also demonstrated excellent performance in distinguishing cancer cells from leukocytes (accuracy = 89.5%). We developed a mechanical model based on power-law rheology to quantify stiffness, which was fitted with measured data directly. The model evaluated metastatic potentials for multiple cancer types and mixed cell populations, even under real-world clinical conditions. Our study presents a highly robust and transferable computational framework for multiobject tracking and deformation measurement tasks in microfluidics. We believe that this platform has the potential to pave the way for high-throughput analysis in clinical applications, providing a powerful tool for evaluating cellular deformability and assessing the physiological state of cells.

Computer vision meets microfluidics: a label-free method for high-throughput cell analysis

In this paper, we review the integration of microfluidic chips and computer vision, which has great potential to advance research in the life sciences and biology, particularly in the analysis of cell imaging data. Microfluidic chips enable the generation of large amounts of visual data at the single-cell level, while computer vision techniques can rapidly process and analyze these data to extract valuable information about cellular health and function. One of the key advantages of this integrative approach is that it allows for noninvasive and low-damage cellular characterization, which is important for studying delicate or fragile microbial cells. The use of microfluidic chips provides a highly controlled environment for cell growth and manipulation, minimizes experimental variability and improves the accuracy of data analysis. Computer vision can be used to recognize and analyze target species within heterogeneous microbial populations, which is important for understanding the physiological status of cells in complex biological systems. As hardware and artificial intelligence algorithms continue to improve, computer vision is expected to become an increasingly powerful tool for in situ cell analysis. The use of microelectromechanical devices in combination with microfluidic chips and computer vision could enable the development of label-free, automatic, low-cost, and fast cellular information recognition and the high-throughput analysis of cellular responses to different compounds, for broad applications in fields such as drug discovery, diagnostics, and personalized medicine.

Biomechanical Investigation of Red Cell Sedimentation Using Blood Shear Stress and Blood Flow Image in a Capillary Chip

Blood image intensity has been used to detect erythrocyte sedimentation rate (ESR). However, it does not give information on the biophysical properties of blood samples under continuous ESR. In this study, to quantify mechanical variations of blood under continuous ESR, blood shear stress and blood image intensity were obtained by analyzing blood flows in the capillary channel. A blood sample is loaded into a driving syringe to demonstrate the proposed method. The blood flow rate is set in a periodic on-off pattern. A blood sample is then supplied into a capillary chip, and microscopic blood images are captured at specific intervals. Blood shear stress is quantified from the interface of the bloodstream in the coflowing channel. τ0 is defined as the maximum shear stress obtained at the first period. Simultaneously, ESRτ is then obtained by analyzing temporal variations of blood shear stress for every on period. AII is evaluated by analyzing the temporal variation of blood image intensity for every off period. According to the experimental results, a shorter period of T = 4 min and no air cavity contributes to the high sensitivity of the two indices (ESRτ and AII). The τ0 exhibits substantial differences with respect to hematocrits (i.e., 30-50%) as well as diluents. The ESRτ and AII showed a reciprocal relationship with each other. Three suggested properties represented substantial differences for suspended blood samples (i.e., hardened red blood cells, different concentrations of dextran solution, and fibrinogen). In conclusion, the present method can detect variations in blood samples under continuous ESR effectively.

The Nanomechanical Properties of CLL Cells Are Linked to the Actin Cytoskeleton and Are a Potential Target of BTK Inhibitors

Chronic lymphocytic leukemia (CLL) is an incurable disease characterized by an intense trafficking of the leukemic cells between the peripheral blood and lymphoid tissues. It is known that the ability of lymphocytes to recirculate strongly depends on their capability to rapidly rearrange their cytoskeleton and adapt to external cues; however, little is known about the differences occurring between CLL and healthy B cells during these processes. To investigate this point, we applied a single-cell optical (super resolution microscopy) and nanomechanical approaches (atomic force microscopy, real-time deformability cytometry) to both CLL and healthy B lymphocytes and compared their behavior. We demonstrated that CLL cells have a specific actomyosin complex organization and altered mechanical properties in comparison to their healthy counterpart. To evaluate the clinical relevance of our findings, we treated the cells in vitro with the Bruton's tyrosine kinase inhibitors and we found for the first time that the drug restores the CLL cells mechanical properties to a healthy phenotype and activates the actomyosin complex. We further validated these results in vivo on CLL cells isolated from patients undergoing ibrutinib treatment. Our results suggest that CLL cells' mechanical properties are linked to their actin cytoskeleton organization and might be involved in novel mechanisms of drug resistance, thus becoming a new potential therapeutic target aiming at the normalization of the mechanical fingerprints of the leukemic cells.

Acoustophoretic Characterization and Separation of Blood Cells in Acoustic Impedance Gradients

Single-cell phenotyping based on biophysical properties is a promising tool to distinguish cell types and their response to a given condition, and charting such properties also enables optimization of cell separations. Isoacoustic focusing, where cells migrate to their points of zero acoustic contrast in an acoustic impedance gradient, added the effective acoustic impedance of cells to the directory of biophysical properties that can be utilized to categorize or separate cells. This study investigates isoacoustic focusing in a stop-flow regime and shows how cells migrate towards their isoacoustic point. We introduce a numerical model that we use to estimate the acoustic energy density in acoustic impedance gradient media by tracking particles of known properties, and we investigate the effect of acoustic streaming. From the measured trajectories of cells combined with fluorescence intensity images of the slowly diffusing gradient, we read out the effective acoustic impedance of neutrophils and K562 cancer cells. Finally, we propose suitable acoustic impedance gradients that lead to a high degree separation of neutrophils and K562 cells in a continuous-flow configuration.

Microparticles with tunable, cell-like properties for quantitative acoustic mechanophenotyping

Mechanical properties of biological cells have been shown to correlate with their biomolecular state and function, and therefore methods to measure these properties at scale are of interest. Emerging microfluidic technologies can measure the mechanical properties of cells at rates over 20,000 cells/s, which is more than four orders of magnitude faster than conventional instrumentation. However, precise and repeatable means to calibrate and test these new tools remain lacking, since cells themselves are by nature variable. Commonly, microfluidic tools use rigid polymer microspheres for calibration because they are widely available in cell-similar sizes, but conventional microspheres do not fully capture the physiological range of other mechanical properties that are equally important to device function (e.g., elastic modulus and density). Here, we present for the first time development of monodisperse polyacrylamide microparticles with both tunable elasticity and tunable density. Using these size, elasticity, and density tunable particles, we characterized a custom acoustic microfluidic device that makes single-cell measurements of mechanical properties. We then applied the approach to measure the distribution of the acoustic properties within samples of human leukocytes and showed that the system successfully discriminates lymphocytes from other leukocytes. This initial demonstration shows how the tunable microparticles with properties within the physiologically relevant range can be used in conjunction with microfluidic devices for efficient high-throughput measurements of mechanical properties at single-cell resolution.

Evolution of focused streams for viscoelastic flow in spiral microchannels

Particle migration dynamics in viscoelastic fluids in spiral channels have attracted interest in recent years due to potential applications in the 3D focusing and label-free sorting of particles and cells. Despite a number of recent studies, the underlying mechanism of Dean-coupled elasto-inertial migration in spiral microchannels is not fully understood. In this work, for the first time, we experimentally demonstrate the evolution of particle focusing behavior along a channel downstream length at a high blockage ratio. We found that flow rate, device curvature, and medium viscosity play important roles in particle lateral migration. Our results illustrate the full focusing pattern along the downstream channel length, with side-view imaging yielding observations on the vertical migration of focused streams. Ultimately, we anticipate that these results will offer a useful guide for elasto-inertial microfluidics device design to improve the efficiency of 3D focusing in cell sorting and cytometry applications.

Tunable microfluidic chip for single-cell deformation study

Microfluidic phenotyping methods have been of vital importance for cellular characterization, especially for evaluating single cells. In order to study the deformability of a single cell, we devised and tested a tunable microfluidic chip-based method. A pneumatic polymer polydimethylsiloxane (PDMS) membrane was designed and fabricated abutting a single-cell trapping structure, so the cell could be squeezed controllably in a lateral direction. Cell contour changes under increasing pressure were recorded, enabling the deformation degree of different types of single cell to be analyzed and compared using computer vision. This provides a new perspective for studying mechanical properties of cells at the single cell level.

Nanomechanical hydrodynamic force sensing using suspended microfluidic channels

Microfluidics has demonstrated high versatility in the analysis of in-flow particles and can even achieve mechanical properties measurements of biological cells by applying hydrodynamic forces. However, there is currently no available technique that enables the direct measurement and tracking of these hydrodynamic forces acting on a flowing particle. In this work, we introduce a novel method for the direct measurement of the hydrodynamic force actuating on an in-flow particle based on the analysis of the induced resonance changes of suspended microchannel resonators (SMRs). This hydrodynamic force sensitivity depends on the device used; therefore, we considered the geometry and materials to advance this dependency on the SMR resonance frequency.

Bladder Cancer Cells Interaction with Lectin-Coated Surfaces under Static and Flow Conditions

Aberrant expression of glycans, i.e., oligosaccharide moiety covalently attached to proteins or lipids, is characteristic of various cancers, including urothelial ones. The binding of lectins to glycans is classified as molecular recognition, which makes lectins a strong tool for understanding their role in developing diseases. Here, we present a quantitative approach to tracing glycan-lectin interactions in cells, from the initial to the steady phase of adhesion. The cell adhesion was measured between urothelial cell lines (non-malignant HCV29 and carcinoma HT1376 and T24 cells) and lectin-coated surfaces. Depending on the timescale, single-cell force spectroscopy, and adhesion assays conducted in static and flow conditions were applied. The obtained results reveal that the adhesion of urothelial cells to two specific lectins, i.e., phytohemagglutinin-L and wheat germ agglutinin, was specific and selective. Thus, these lectins can be applied to selectively capture, identify, and differentiate between cancer types in a label-free manner. These results open up the possibility of designing lectin-based biosensors for diagnostic or prognostic purposes and developing strategies for drug delivery that could target cancer-associated glycans.

An enhanced tilted-angle acoustic tweezer for mechanical phenotyping of cancer cells

Acoustofluidic devices becomes one of the emerging and versatile tools for many biomedical applications. Most of the previous acoustofluidic devices are used for cells manipulation, and the few devices for cell phenotyping with a limitation in throughput. In this study, an enhanced tilted-angle (ETA) acoustofluidic device is developed and applied for mechanophenotyping of live cells. The ETA Device consists of an interdigital transducer which is positioned along a microfluidic channel. An inclination angle of 5° is introduced between the interdigital transducer and the liquid flow direction. The pressure nodes formed inside the acoustofluidic field in the channel deflect the biological cells from their original course in accordance with their mechanical properties, including volume, compressibility, and density. The threshold power for fully converging the cells to the pressure node is used to calculate the acoustic contrast factor. To demonstrate the ETA device in cell mechanophenotyping, and distinguishing between different cell types, further experimentation is carried out by using A549 (lung cancer cells), MDB-MA-231 (breast cancer cells), and leukocytes. The resulting acoustic contrast factors for the lung and breast cancer cells are different from that of the leukocytes by 27.9% and 21.5%, respectively. These results suggest this methodology can successfully distinguish and phenotype different cell types based on the acoustic contrast factor.