Analytical approximations for spatial stochastic gene expression in single cells and tissues

Gene expression occurs in an environment in which both stochastic and diffusive effects are significant. Spatial stochastic simulations are computationally expensive compared with their deterministic counterparts, and hence little is currently known of the significance of intrinsic noise in a spatial setting. Starting from the reaction–diffusion master equation (RDME) describing stochastic reaction–diffusion processes, we here derive expressions for the approximate steady-state mean concentrations which are explicit functions of the dimensionality of space, rate constants and diffusion coefficients. The expressions have a simple closed form when the system consists of one effective species. These formulae show that, even for spatially homogeneous systems, mean concentrations can depend on diffusion coefficients: this contradicts the predictions of deterministic reaction–diffusion processes, thus highlighting the importance of intrinsic noise. We confirm our theory by comparison with stochastic simulations, using the RDME and Brownian dynamics, of two models of stochastic and spatial gene expression in single cells and tissues

Influence of structure of iron nanoparticles in aggregates on their magnetic properties

Zero-valent iron nanoparticles rapidly aggregate. One of the reasons is magnetic forces among the nanoparticles. Magnetic field around particles is caused by composition of the particles. Their core is formed from zero-valent iron, and shell is a layer of magnetite. The magnetic forces contribute to attractive forces among the nanoparticles and that leads to increasing of aggregation of the nanoparticles. This effect is undesirable for decreasing of remediation properties of iron particles and limited transport possibilities. The aggregation of iron nanoparticles was established for consequent processes: Brownian motion, sedimentation, velocity gradient of fluid around particles and electrostatic forces. In our previous work, an introduction of influence of magnetic forces among particles on the aggregation was presented. These forces have significant impact on the rate of aggregation. In this article, a numerical computation of magnetic forces between an aggregate and a nanoparticle and between two aggregates is shown. It is done for random position of nanoparticles in an aggregate and random or arranged directions of magnetic polarizations and for structured aggregates with arranged vectors of polarizations. Statistical computation by Monte Carlo is done, and range of dominant area of magnetic forces around particles is assessed

Oxygen reduction reaction features in neutral media on glassy carbon electrode functionalized by chemically prepared gold nanoparticles

Gold nanoparticles (AuNPs) were prepared by chemical route using 4 different protocols by varying reducer, stabilizing agent and solvent mixture. The obtained AuNPs were characterized by transmission electronic microscopy (TEM), UV-Visible and zeta potential measurements. From these latter surface charge densities were calculated to evidence the effect of the solvent mixture on AuNPs stability. The AuNPs were then deposited onto glassy carbon (GC) electrodes by drop-casting and the resulting deposits were characterized by cyclic voltammetry (CV) in H2SO4 and field emission gun scanning electron microscopy (FEG-SEM). The electrochemical kinetic parameters of the 4 different modified electrodes towards oxygen reduction reaction (ORR) in neutral NaCl-NaHCO3 media (0.15 M / 0.028 M, pH 7.4) were evaluated by rotating disk electrode voltammetry and subsequent Koutecky-Levich treatment. Contrary to what we previously obtained with electrodeposited AuNPs [Gotti et al., Electrochim. Acta 2014], the highest cathodic transfer coefficients were not obtained on the smallest particles, highlighting the influence of the stabilizing ligand together with the deposits morphology on the ORR kinetics

Migration and agglomeration of adhesive microparticle suspensions in a pressure‐driven duct flow

Transport of suspensions consisting of monodisperse adhesive micro-particles in a pressure-driven duct flow with the Reynolds number in the range of 5.4-108 is analysed by means of a coupled lattice Boltzmann method with the discrete element method. The influence of the adhesion on migration and agglomeration of particles is investigated. The results show that the suspensions undergo a transition from purely lateral focusing to completely agglomeration as the surface energy is increased. A dimensionless adhesion number, defined as the ratio of the adhesive force to the drag force, is employed to characterise the degree of agglomeration. It is found that all the particles come into agglomerates as the adhesion number reaches a critical value. Moreover, a detailed examination of size evolution and velocity illustrates that the agglomerates mainly grow spherically, and their velocities depend on the lateral positions rather than their sizes, as the Stokes number is far below one