Visco-Node-Pore Sensing: A Microfluidic Rheology Platform to Characterize Viscoelastic Properties of Epithelial Cells.

Viscoelastic properties of cells provide valuable information regarding biological or clinically relevant cellular characteristics. Here, we introduce a new, electronic-based, microfluidic platform-visco-node-pore sensing (visco-NPS)-which quantifies cellular viscoelastic properties under periodic deformation. We measure the storage (G) and loss (G″) moduli (i.e., elasticity and viscosity, respectively) of cells. By applying a wide range of deformation frequencies, our platform quantifies the frequency dependence of viscoelastic properties. G and G″ measurements show that the viscoelastic properties of malignant breast epithelial cells (MCF-7) are distinctly different from those of non-malignant breast epithelial cells (MCF-10A). With its sensitivity, visco-NPS can dissect the individual contributions of different cytoskeletal components to whole-cell mechanical properties. Moreover, visco-NPS can quantify the mechanical transitions of cells as they traverse the cell cycle or are initiated into an epithelial-mesenchymal transition. Visco-NPS identifies viscoelastic characteristics of cell populations, providing a biophysical understanding of cellular behavior and a potential for clinical applications

On-Chip Detection of Gel Transition Temperature using a Novel Micro-Thermomechanical Method

We present a new thermomechanical method and a platform to measure the phase transition temperature at microscale. A thin film metal sensor on a membrane simultaneously measures both temperature and mechanical strain of the sample during heating and cooling cycles. This thermomechanical principle of operation is described in detail. Physical hydrogel samples are prepared as a disc-shaped gels (200 μm thick and 1 mm diameter) and placed between an on-chip heater and sensor devices. The sol-gel transition temperature of gelatin solution at various concentrations, used as a model physical hydrogel, shows less than 3% deviation from in-depth rheological results. The developed thermomechanical methodology is promising for precise characterization of phase transition temperature of thermogels at microscale

Classification of analytics, sensorics, and bioanalytics with polyelectrolyte multilayer capsules

Polyelectrolyte multilayer (PEM) capsules, constructed by LbL (layer-by-layer)-adsorbing polymers on sacrificial templates, have become important carriers due to multifunctionality of materials adsorbed on their surface or encapsulated into their interior. They have been also been used broadly used as analytical tools. Chronologically and traditionally, chemical analytics has been developed first, which has long been synonymous with all analytics. But it is not the only development. To the best of our knowledge, a summary of all advances including their classification is not available to date. Here, we classify analytics, sensorics, and biosensorics functionalities implemented with polyelectrolyte multilayer capsules and coated particles according to the respective stimuli and application areas. In this classification, three distinct categories are identified: (I) chemical analytics (pH; K+, Na+, and Pb2+ ion; oxygen; and hydrogen peroxide sensors and chemical sensing with surface-enhanced Raman scattering (SERS)); (II) physical sensorics (temperature, mechanical properties and forces, and osmotic pressure); and (III) biosensorics and bioanalytics (fluorescence, glucose, urea, and protease biosensing and theranostics). In addition to this classification, we discuss also principles of detection using the above-mentioned stimuli. These application areas are expected to grow further, but the classification provided here should help (a) to realize the wealth of already available analytical and bioanalytical tools developed with capsules using inputs of chemical, physical, and biological stimuli and (b) to position future developments in their respective fields according to employed stimuli and application areas

Cell viscoelasticity is linked to fluctuations in cell biomass distributions.

The viscoelastic properties of mammalian cells can vary with biological state, such as during the epithelial-to-mesenchymal (EMT) transition in cancer, and therefore may serve as a useful physical biomarker. To characterize stiffness, conventional techniques use cell contact or invasive probes and as a result are low throughput, labor intensive, and limited by probe placement. Here, we show that measurements of biomass fluctuations in cells using quantitative phase imaging (QPI) provides a probe-free, contact-free method for quantifying changes in cell viscoelasticity. In particular, QPI measurements reveal a characteristic underdamped response of changes in cell biomass distributions versus time. The effective stiffness and viscosity values extracted from these oscillations in cell biomass distributions correlate with effective cell stiffness and viscosity measured by atomic force microscopy (AFM). This result is consistent for multiple cell lines with varying degrees of cytoskeleton disruption and during the EMT. Overall, our study demonstrates that QPI can reproducibly quantify cell viscoelasticity

Mechanical fluidity of fully suspended biological cells

Mechanical characteristics of single biological cells are used to identify and possibly leverage interesting differences among cells or cell populations. Fluidity---hysteresivity normalized to the extremes of an elastic solid or a viscous liquid---can be extracted from, and compared among, multiple rheological measurements of cells: creep compliance vs. time, complex modulus vs. frequency, and phase lag vs. frequency. With multiple strategies available for acquisition of this nondimensional property, fluidity may serve as a useful and robust parameter for distinguishing cell populations, and for understanding the physical origins of deformability in soft matter. Here, for three disparate eukaryotic cell types deformed in the suspended state via optical stretching, we examine the dependence of fluidity on chemical and environmental influences around a time scale of 1 s. We find that fluidity estimates are consistent in the time and the frequency domains under a structural damping (power-law or fractional derivative)model, but not under an equivalent-complexity lumpedcomponent (spring-dashpot) model; the latter predicts spurious time constants. Although fluidity is suppressed by chemical crosslinking, we find that adenosine triphosphate (ATP) depletion in the cell does not measurably alter the parameter, and thus conclude that active ATP-driven events are not a crucial enabler of fluidity during linear viscoelastic deformation of a suspended cell. Finally, by using the capacity of optical stretching to produce near-instantaneous increases in cell temperature, we establish that fluidity increases with temperature---now measured in a fully suspended, sortable cell without the complicating factor of cell-substratum adhesion

Fluid-driven deformation of a soft granular material

Compressing a porous, fluid-filled material will drive the interstitial fluid out of the pore space, as when squeezing water out of a kitchen sponge. Inversely, injecting fluid into a porous material can deform the solid structure, as when fracturing a shale for natural gas recovery. These poromechanical interactions play an important role in geological and biological systems across a wide range of scales, from the propagation of magma through the Earth's mantle to the transport of fluid through living cells and tissues. The theory of poroelasticity has been largely successful in modeling poromechanical behavior in relatively simple systems, but this continuum theory is fundamentally limited by our understanding of the pore-scale interactions between the fluid and the solid, and these problems are notoriously difficult to study in a laboratory setting. Here, we present a high-resolution measurement of injection-driven poromechanical deformation in a system with granular microsctructure: We inject fluid into a dense, confined monolayer of soft particles and use particle tracking to reveal the dynamics of the multi-scale deformation field. We find that a continuum model based on poroelasticity theory captures certain macroscopic features of the deformation, but the particle-scale deformation field exhibits dramatic departures from smooth, continuum behavior. We observe particle-scale rearrangement and hysteresis, as well as petal-like mesoscale structures that are connected to material failure through spiral shear banding

Visualization of Minute Mechanical-Excitation/Relaxation Wave-front Propagation in Myocardial Tissue

Unlike the case of skeletal muscle, the direction of myocardial contraction does not coincide with the direction of work necessary to eject the intraventricular blood, contributing to great complexity of the wall deformation sequence of cardiac contraction. The advent of advanced techniques (CT^1^, MRI^2,3^, SPECT^4^, echocardiology^5-9^, electrocardiography^10^, and magnetocardiography^11,12^) has enabled to the evaluation of cardiac function and disorders by the measurement of blood flow, pressure, electrical reaction process, and other factors. However, complexity of the contraction sequence is still not fully understood because the dynamic mechanical excitation process, which directly correlates with contraction, cannot be accurately measured based on these electro-magnetic phenomena. Here, developing and using a noninvasive novel imaging modality with high temporal and spatial resolutions^13-17^, we show that the propagation of the mechanical wave-front occurs at the beginning of each cardiac contraction and relaxation sequence for the first time. The former occurs about 60 ms prior to the ordinarily accepted onset time of the contraction (R-wave of the electrocardiogram). From the apical side of the interventricular septum, close to the terminal of the Purkinje fibers (specialized to carry contraction impulses), a minute velocity component with an amplitude of several tenth micrometers is generated and propagates sequentially to the entire left ventricle, that is, it propagates from the apex to the base of the posterior wall, and then from the base to the apex of the septum, with a propagation speed of 3-9 m/s. The latter occurs at the end of the first heart sound at the apical side and propagates to the base side with a speed of 0.6 m/s. These physiological findings, unlike the widely accepted myocardial excitation process, have potential for accurate assessment of myocardial tissue damage in coronary disease and cardiomyopathy. This dynamic measurement modality is also applicable to various tissues in biology

Fluid-structure interaction simulation of prosthetic aortic valves : comparison between immersed boundary and arbitrary Lagrangian-Eulerian techniques for the mesh representation

In recent years the role of FSI (fluid-structure interaction) simulations in the analysis of the fluid-mechanics of heart valves is becoming more and more important, being able to capture the interaction between the blood and both the surrounding biological tissues and the valve itself. When setting up an FSI simulation, several choices have to be made to select the most suitable approach for the case of interest: in particular, to simulate flexible leaflet cardiac valves, the type of discretization of the fluid domain is crucial, which can be described with an ALE (Arbitrary Lagrangian-Eulerian) or an Eulerian formulation. The majority of the reported 3D heart valve FSI simulations are performed with the Eulerian formulation, allowing for large deformations of the domains without compromising the quality of the fluid grid. Nevertheless, it is known that the ALE-FSI approach guarantees more accurate results at the interface between the solid and the fluid. The goal of this paper is to describe the same aortic valve model in the two cases, comparing the performances of an ALE-based FSI solution and an Eulerian-based FSI approach. After a first simplified 2D case, the aortic geometry was considered in a full 3D set-up. The model was kept as similar as possible in the two settings, to better compare the simulations' outcomes. Although for the 2D case the differences were unsubstantial, in our experience the performance of a full 3D ALE-FSI simulation was significantly limited by the technical problems and requirements inherent to the ALE formulation, mainly related to the mesh motion and deformation of the fluid domain. As a secondary outcome of this work, it is important to point out that the choice of the solver also influenced the reliability of the final results