Coarse-grained Soft-Clusters Remain non-Diffusing in the Melt State

Melts of 3-dimensional dendritic beads-springs, namely coarse-grained soft-clusters, are studied by molecular dynamics simulations. The goal is to elucidate the unique dynamics of giant molecules, or generally speaking, 3-dimensional architectured polymers. When constituted by more than the critical number around 200 beads, soft-clusters cannot diffuse or relax far above their glass transition temperature, although relaxation can happen on the level of beads. Each soft-cluster can only rotate in the cage formed by neighboring soft-clusters. Such a non-diffusing state would transform to the liquid state at exceptionally high temperature, e.g. 10 times the glass transition temperature. Agreeing with experiments, 3D hierarchies lead to unique dynamics, especially their divergent relaxation times with the number of beads. These unique dynamics are in sharp contrast with 1-dimensional chain-like polymers. We name such a special state as 'cooperative glass', because of the 'cooperation' of the 3D-connected beads. The design of soft-clusters may also resemble cooperative rearranging regions where cooperativeness is contributed by low temperature, thus offer further insights into the glass problem

Low-intensity continuous ultrasound to inhibit cancer cell migration

In recent years, it has been verified that collective cell migration is a fundamental step in tumor spreading and metastatic processes. In this paper, we demonstrate for the first time how low-intensity ultrasound produces long-term inhibition of collective migration of epithelial cancer cells in wound healing processes. In particular, we show how pancreatic tumor cells, PANC-1, grown as monolayers in vitro respond to these waves at frequencies close to 1 MHz and low intensities (< 100 mW cm(-2)) for 48-72 h of culture after some minutes of a single ultrasound irradiation. This new strategy opens a new line of action to block the spread of malignant cells in cancer processes. Despite relevant spatial variations of the acoustic pressure amplitude induced in the assay, the cells behave as a whole, showing a collective dynamic response to acoustic performance. Experiments carried out with samples without previous starving showed remarkable effects of the LICUs from the first hours of culture, more prominent than those with experiments with monolayers subjected to fasting prior to the experiments. This new strategy to control cell migration demonstrating the effectiveness of LICUS on not starved cells opens a new line of action to study effects of in vivo ultrasonic actuation on tumor tissues with malignant cells. This is a proof-of-concept study to demonstrate the physical effects of ultrasound stimulation on tumor cell migration. An in-depth biological study of the effects of ultrasounds and underlying biological mechanisms is on-going but out of the scope of this article.This work is financed by the Spanish National Plan projects PID 2021-128985OB-I00: "New Non-invasive technology to inhibit growth of solid tumors by low intensity ultrasounds", DPI 2017-90147-R and intramural research project IRYCIS (2018/0240)

New Tools for Viscoelastic Spectral Analysis, with Application to the Mechanics of Cells and Collagen across Hierarchies

Viscoelastic relaxation spectra are essential for predicting and interpreting the mechanical responses of materials and structures. For biological tissues, these spectra must usually be estimated from viscoelastic relaxation tests. Interpreting viscoelastic relaxation tests is challenging because the inverse problem is expensive computationally. We present here (1) an efficient algorithm and (2) a quasi-linear model that enable rapid identification of the viscoelastic relaxation spectra of both linear and nonlinear materials. We then apply these methods to develop fundamental insight into the mechanics of collagenous and fibrotic tissues. The first algorithm, which we term the discrete spectral approach, is fast enough to yield a discrete spectrum of time constants that is sufficient to fit a measured relaxation spectrum with an accuracy insensitive to further refinement. The algorithm fits a discrete spectral generalized Maxwell (Maxwell-Wiechert) model, which is a linear viscoelastic model, to results from a stress-relaxation test. The discrete spectral approach was tested against trial data to characterize its robustness and identify its limitations and strengths. The algorithm was then applied to identify the viscoelastic response of reconstituted collagen and engineered fibrosis tissues, revealing that cells actively adapted the ECM, and that cells relax at multiple timescales, including one that is fast compared to those of the ECM. The second algorithm, which we term the discrete quasi-linear viscoelastic (DQLV) approach, is a spectral extension of the Fung quasi-linear viscoelastic (QLV) model, a standard tool for characterizing biological materials. The Fung QLV model provides excellent fits to most stress-relaxation data by imposing a simple form upon a material\u27s temporal relaxation spectrum. However, model identification is challenging because the Fung QLV model\u27s “box” shaped relaxation spectrum, predominant in biomechanics applications, because it can provide an excellent fit even when it is not a reasonable representation of a material\u27s relaxation spectrum. The DQLV model is robust, simple, and unbiased. It is able to identify ranges of time constants over which the Fung QLV model\u27s typical box spectrum provides an accurate representation of a particular material\u27s temporal relaxation spectrum, and is effective at providing a fit to this model. The DQLV spectrum also reveals when other forms or discrete time constants are more suitable than a box spectrum. After validating the approach against idealized and noisy data, we applied the methods to analyze medial collateral ligament stress-relaxation and sinusoidal excitation data and identify the strengths and weaknesses of an optimal Fung QLV fit. Taken together, the tools in this dissertation form a comprehensive approach to characterizing the mechanics of viscoelastic biological tissues, and to dissecting the micromechanical mechanisms that underlie a tissue\u27s viscoelastic responses

Synthetic Elastography using B-mode Ultrasound through a Deep Fully-Convolutional Neural Network

Shear-wave elastography (SWE) permits local estimation of tissue elasticity, an important imaging marker in biomedicine. This recently-developed, advanced technique assesses the speed of a laterally-travelling shear wave after an acoustic radiation force "push" to estimate local Young's moduli in an operator-independent fashion. In this work, we show how synthetic SWE (sSWE) images can be generated based on conventional B-mode imaging through deep learning. Using side-by-side-view B-mode/SWE images collected in 50 patients with prostate cancer, we show that sSWE images with a pixel-wise mean absolute error of 4.5+/-0.96 kPa with regard to the original SWE can be generated. Visualization of high-level feature levels through t-Distributed Stochastic Neighbor Embedding reveals substantial overlap between data from two different scanners. Qualitatively, we examined the use of the sSWE methodology for B-mode images obtained with a scanner without SWE functionality. We also examined the use of this type of network in elasticity imaging in the thyroid. Limitations of the technique reside in the fact that networks have to be retrained for different organs, and that the method requires standardization of the imaging settings and procedure. Future research will be aimed at development of sSWE as an elasticity-related tissue typing strategy that is solely based on B-mode ultrasound acquisition, and the examination of its clinical utility.Comment: (c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Microrheology of soft matter and living cells in equilibrium and non-equilibrium systems

Myosin-generated stresses are responsible for non-equilibrium mechanical behavior of synthesized cytoskeletal networks in vitro. In particular, it is found that myosin stresses can modify the network elasticity. For living cells, it has been suggested that internally generated stress might help cells sense and mimic the stiffness of their environments. However, cellular mechanical responses to intracellular stress are not well understood. To address these questions, we studied microrheology inside living cells by comparing their mechanical properties to those expected by a statistical analysis of non-thermal fluctuations. We used an experimental method that combines optical tweezers-based active microrheology with particle-tracking passive microrheology. First, we calibrated the trapping force in the linear restoring-force regime with oscillatory optical tweezers. Then, we used optical tweezers to test the response functions against the fluctuation-dissipation theorem in equilibrium systems (i.e., polymer solutions or colloidal crystal gels) and in non-equilibrium systems (i.e., living cells). In living cells, we employed cellular microrheology using an internal probe as well as an externally attached particle. Whereas extracellular probes attached to the cytoskeleton provide a measure of global cell mechanical properties, intracellular probes provide direct measurements of intracellular mechanical properties. We used an engulfed micro-particle as a probe to study local intracellular stress and stiffness. The relationship between fluctuations in stress and in cell elasticity for living cells under different internal tensions reveals a strong non-linearity between cell elasticity and intracellular stress, which follows a master curve. Our results show that the motors induce an internal tension that forces the network into a non-equilibrium and non-linear state. These aspects provide a better understanding of the noise in a non-equilibrium system. The relationship between the different sources of noise in living cells helps reveal the inner workings of the highly dynamic cytoskeleton network. Studies of intracellular stress and mechanical properties promote our current understanding of how cells sense and respond to their mechanical environment. Such knowledge could lead to new designs in biomaterials and advance our understanding of diseases related to cellular mechanotransduction. Our studies in active systems contribute to our knowledge of fundamental non-equilibrium statistical physics in biological systems

Dynamic problems for metamaterials: Review of existing models and ideas for further research

Metamaterials are materials especially engineered to have a peculiar physical behaviour, to be exploited for some well-specified technological application. In this context we focus on the conception of general micro-structured continua, with particular attention to piezoelectromechanical structures, having a strong coupling between macroscopic motion and some internal degrees of freedom, which may be electric or, more generally, related to some micro-motion. An interesting class of problems in this context regards the design of wave-guides aimed to control wave propagation. The description of the state of the art is followed by some hints addressed to describe some possible research developments and in particular to design optimal design techniques for bone reconstruction or systems which may block wave propagation in some frequency ranges, in both linear and non-linear fields. (C) 2014 Elsevier Ltd. All rights reserved

Multiscale approach including microfibril scale to assess elastic constants of cortical bone based on neural network computation and homogenization method

The complexity and heterogeneity of bone tissue require a multiscale modelling to understand its mechanical behaviour and its remodelling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network computation and homogenisation equations was developed to link nanoscopic and macroscopic scales to estimate the elastic properties of human cortical bone. The multiscale model is divided into three main phases: (i) in step 0, the elastic constants of collagen-water and mineral-water composites are calculated by averaging the upper and lower Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril are computed using a trained neural network simulation. Finite element (FE) calculation is performed at nanoscopic levels to provide a database to train an in-house neural network program; (iii) in steps 2 to 10 from fibril to continuum cortical bone tissue, homogenisation equations are used to perform the computation at the higher scales. The neural network outputs (elastic properties of the microfibril) are used as inputs for the homogenisation computation to determine the properties of mineralised collagen fibril. The mechanical and geometrical properties of bone constituents (mineral, collagen and cross-links) as well as the porosity were taken in consideration. This paper aims to predict analytically the effective elastic constants of cortical bone by modelling its elastic response at these different scales, ranging from the nanostructural to mesostructural levels. Our findings of the lowest scale's output were well integrated with the other higher levels and serve as inputs for the next higher scale modelling. Good agreement was obtained between our predicted results and literature data.Comment: 2

Thermal convection in a Brinkman–Darcy–Kelvin–Voigt fluid with a generalized Maxwell–Cattaneo law

We investigate thoroughly a model for thermal convection of a class of viscoelastic fluids in a porous medium of Brinkman–Darcy type. The saturating fluids are of Kelvin–Voigt nature. The equations governing the temperature field arise from Maxwell–Cattaneo theory, although we include Guyer–Krumhansl terms, and we investigate the possibility of employing an objective derivative for the heat flux. The critical Rayleigh number for linear instability is calculated for both stationary and oscillatory convection. In addition a nonlinear stability analysis is carried out exactly