A Bayesian model predicts the response of axons to molecular gradients

Axon guidance by molecular gradients plays a crucial role in wiring up the nervous system. However, the mechanisms axons use to detect gradients are largely unknown. We first develop a Bayesian “ideal observer” analysis of gradient detection by axons, based on the hypothesis that a principal constraint on gradient detection is intrinsic receptor binding noise. Second, from this model, we derive an equation predicting how the degree of response of an axon to a gradient should vary with gradient steepness and absolute concentration. Third, we confirm this prediction quantitatively by performing the first systematic experimental analysis of how axonal response varies with both these quantities. These experiments demonstrate a degree of sensitivity much higher than previously reported for any chemotacting system. Together, these results reveal both the quantitative constraints that must be satisfied for effective axonal guidance and the computational principles that may be used by the underlying signal transduction pathways, and allow predictions for the degree of response of axons to gradients in a wide variety of in vivo and in vitro settings.

Numerical exploration of plastic deformation mechanisms of copper nanowires with surface defects

Based on the molecular dynamics simulation, plastic deformation mechanisms associated with the zigzag stress curves in perfect and surface defected copper nanowires under uniaxial tension are studied. In our previous study, it has found that the surface defect exerts larger influence than the centro-plane defect, and the 45o surface defect appears as the most influential surface defect. Hence, in this paper, the nanowire with a 45o surface defect is chosen to investigate the defect’s effect to the plastic deformation mechanism of nanowires. We find that during the plastic deformation of both perfect and defected nanowires, decrease regions of the stress curve are accompanied with stacking faults generation and migration activities, but during stress increase, the structure of the nanowire appears almost unchanged. We also observe that surface defects have obvious influence on the nanowire’s plastic deformation mechanisms. In particular, only two sets of slip planes are found to be active and twins are also observed in the defected nanowire.

Advanced numerical characterization of mono-crystalline copper with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the mono-crystalline copper with different defects is investigated through tension and nanoindentation simulation. The single-crystal copper nanowire with surface defects is firstly studied through tension. For validation, the tension simulations for nanowire without defect are carried out under different temperatures and strain rates. The defects on nanowires are then systematically studied in considering different defects orientation distribution. It is found that the Young’s modulus is insensitive of surface defects and centro-plane defects. However, the yield strength and yield point show a significant decrease due to the different defects. Specially, the 〖45〗^° defect in surface and in (200) plane exerts the biggest influence to the yield strength, about 34.20% and 51.45% decrease are observed, respectively. Different defects are observed to serve as a dislocation source and different necking positions of the nanowires during tension are found. During nanoindentation simulation, dislocation is found nucleating below the contact area, but no obvious dislocation is generated around the nano-cavity. Comparing with the perfect substrate during nanoindentation, the substrate with nano-cavities emerged less dislocations, it is supposed that the nano-cavity absorbed part of the indent energy, and less plastic deformation happened in the defected substrate.