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Register a new userActively stressed marginal networks
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We study the effects of motor-generated stresses in disordered three dimensional fiber networks using a combination of a mean-field, effective medium theory, scaling analysis and a computational model. We find that motor activity controls the elasticity in an anomalous fashion close to the point of marginal stability by coupling to critical network fluctuations. We also show that motor stresses can stabilize initially floppy networks, extending the range of critical behavior to a broad regime of network connectivities below the marginal point. Away from this regime, or at high stress, motors give rise to a linear increase in stiffness with stress. Finally, we demonstrate that our results are captured by a simple, constitutive scaling relation highlighting the important role of non-affine strain fluctuations as a susceptibility to motor stress.
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A biomimetic model of cell-cell communication was developed to probe the passive molecular transport across ion channels inserted in synthetic lipid bilayers formed between contacting droplets arranged in a linear array. Diffusion of a fluorescent probe across the array was measured for different pore concentrations. The diffusion characteristic time scale is found to vary non-linearly with the pore concentration. Our measurements are successfully modeled by a continuous time random walk description, whose waiting time is the first exit time from a droplet through a cluster of pores. The size of the cluster of pores is found to increase with their concentration. Our results provide a direct link between the mesoscopic permeation properties and the microscopic characteristics of the pores such as their number, size and spatial arrangement.
Respiration in bacteria involves a sequence of energetically-coupled electron and proton transfers creating an electrochemical gradient of protons (a proton-motive force) across the inner bacterial membrane. With a simple kinetic model we analyze a redox loop mechanism of proton-motive force generation mediated by a molecular shuttle diffusing inside the membrane. This model, which includes six electron-binding and two proton-binding sites, reflects the main features of nitrate respiration in E. coli bacteria. We describe the time evolution of the proton translocation process. We find that the electron-proton electrostatic coupling on the shuttle plays a significant role in the process of energy conversion between electron and proton components. We determine the conditions where the redox loop mechanism is able to translocate protons against the transmembrane voltage gradient above 200 mV with a thermodynamic efficiency of about 37%, in the physiologically important range of temperatures from 250 to 350 K.
A simple flashing ratchet model in two dimensions is proposed to simulate the hand-over-hand motion of two head molecular motors like kinesin. Extensive Langevin simulations of the model are performed. Good qualitative agreement with the expected behavior is observed. We discuss different regimes of motion and efficiency depending of model parameters.
We present a multi-scale model to study the attachment of spherical particles with a rigid core, coated with binding ligands and in equilibrium with the surrounding, quiescent fluid medium. This class of fluid-immersed adhesion is widespread in many natural and engineering settings. Our theory highlights how the micro-scale binding kinetics of these ligands, as well as the attractive / repulsive surface potential in an ionic medium effects the eventual macro-scale size distribution of the particle aggregates (flocs). The results suggest that the presence of elastic ligands on the particle surface allow large floc aggregates by inducing efficient inter-floc collisions (i.e., a large, non-zero collision factor). Strong electrolytic composition of the surrounding fluid favors large floc formation as well.
In bacteria, regulatory proteins search for a specific DNA binding target via facilitated diffusion: a series of rounds of 3D diffusion in the cytoplasm, and 1D linear diffusion along the DNA contour. Using large scale Brownian dynamics simulations we find that each of these steps is affected differently by crowding proteins, which can either be bound to the DNA acting as a road block to the 1D diffusion, or freely diffusing in the cytoplasm. Macromolecular crowding can strongly affect mechanistic features such as the balance between 3D and 1D diffusion, but leads to surprising robustness of the total search time.
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