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Ref Arxiv: 1607.01734
DOI: 10.1103/PhysRevE.96.050601
WoS: 000416028000001
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12 Citations
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Tracking experiments in dense biological tissues reveal a diversity of sources f or local energy injection at the cell scale. The effect of cell motility has been largely studied, but much less is known abo ut the effect of the observed volume fluctuations of individual cells. We devise a simple microscopic model of `actively-deforming' particles where local fluctuations of the particle size constitute a unique source of motion. We demonstrate that collective motion can emerge under the sole influence of such active volume fluctuations. We interpret the onset of diffusive motion as a nonequilibrium first-order phase transition, which arises at a well-defined amplitude of self-deformation. This behaviour contrasts with the glassy dynamics produced by self-propulsion, but resembles the mechanical response of soft solids under mechanical deformation. It thus constitutes the first example of active yielding transition.

Commentaires: 5 pages, 3 figs. Réf Journal: Phys. Rev. E 96, 050601 (2017)

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Recent theoretical advances in the mean-field theory of hard-sphere glasses predict the existence of the so-called Gardner transition, an ergodicity breaking transition that takes place deep in the glass phase. In hard-sphere glasses, this transition is crucial to make theoretical predictions for the jamming transition occurring at higher densities. Our goal is to determine if the Gardner transition is also a crucial element to understand the low temperature behaviour of soft glasses. We use two complementary theoretical approaches: a mean-field study of a soft glassy model in the limit of infinite dimensions, combined to a numerical investigation of the transition in a simple three-dimensional soft glass-former. Analytical results confirm the existence of the Gardner transition even in soft glasses. Numerical investigations of three-dimensional soft glasses are in progress, and preliminary results are surprisingly more difficult to interpret than originally expected.

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Collective behavior in a minimal model of cilia beating: synchronization, phase-locking and entrainment

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Mechanical response of amorphous solids is a fundamental research topic in glass science. Whereas amorphous solids respond elastically to a small strain (or stress), the system eventually yields at a large strain, showing plastic response. Although amorphous solids such as glasses are ubiquitous and relevant for industrial applications, understanding of mechanical response is still poor.Computer simulations play an important role in this field, since they are able to provide atomic resolution of mechanical response of glasses. However, there are huge gaps in the accessible timescales between ordinary computer simulations and experiments in terms of glass preparation (e.g. cooling rate) and timescale of deformation (e.g. strain rate). Timescale of current computer simulations are about 10 orders of magnitudes smaller, behind as compared to that of experiments, which makes possible studies of poorly annealed glasses with very large strain rate. For the strain rate, one can overcome the timescale gap by using the athermal quasi-static shear (zero strain rate limit) method which neglects thermal fluctuations [1]. However, fast cooling rate of ordinary simulations still prevents us from studying glasses in experimental condition.Recently, we have developed very efficient simulation setup using particle swap Monte-Carlo algorithm with size polydisperse particles [2]. By applying this setup for a realistic glass-forming system with a continuous potential in three dimensions, we produce very well-annealed glasses whose cooling rate is even slower than experiments, that is ultrastable glasses. We perform athermal quasi-static shear deformation on these systems. Aim of this work is to establish the first simulation study of mechanical response of glasses in and beyond experimental timescales in both cooling and strain rates [3].Our athermal quasi-static shear simulation of the ultrastable glasses show qualitatively different behaviors from ordinary computer glasses [3]. 1) Sharp yielding transition: The stress-strain curve of the ultrastable glasses show very big stress overshoot and sharp yielding, which corresponds to shear band spanning entire sample. With the help of the finite size scaling, we unambiguously determine the yielding transition point at the thermodynamic limit. 2) Burst of stress drops before yielding: We observe sudden emergence of burst of stress drops slightly before the yielding transition point, which can be regarded as a precursor of the yielding. 3) Strong persistent initial memory: After the yielding transition, the systems do not converge to a steady state until more than 1000% shear strain, which is in stark contrast to ordinary computer glasses. REFERENCES[1].Maloney, C E. and Lemaitre, A., Amorphous systems in athermal, quasistatic shear, Phys. Rev. E, 74, 016118 (2006).[2].Berthier, L., Coslovich, D., Ninarello, A., and Ozawa, M., Equilibrium Sampling of Hard Spheres up to the Jamming Density and Beyond, Phys. Rev. Lett.. 116, 238002 (2016).[3].Ozawa, M., Ninarello, A., and Berthier, L., in preparation.

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In this short talk I will focus on mRNA, one of the last step of protein synthesis often neglected. I will introduce a quantitative model based on a Totally Asymmetric Simple Exclusion Process and integrate experimental data to the model to estimate translation rates previously undetermined.

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Existing evidence such as codon usage bias suggests that protein translation of fast-growing organisms has been optimised for accuracy and better yield. One possibility for optimisation stems from the fact that different codons are translated at different rates. Common measures for optimal codon choice, which ignore the dynamics of this process, have so far had mixed success in predicting protein levels. Recent advances in experimental techniques such as ribosome profiling allow us to study dynamical details of this intricate process and theoretical modelling is required to interpret the new data. In this work we study a kinetic model for translation that takes into account stochastic movement of individual ribosomes along the mRNA molecule. Unlike previous studies of this and similar models that were limited to numerical simulations, we develop a novel mathematical method to find the steady state solution when the translation initiation is a rate-limiting step. This allows us, for the first time, to find an analytic prediction for the translation rate and ribosome density. We use these predictions to address some of the long-standing controversies surrounding the determinants of translation efficiency.