Differential developmental trajectories of magnetic susceptibility in human brain gray and white matter over the lifespan

As indicated by several recent studies, magnetic susceptibility of the brain is influenced mainly by myelin in the white matter and by iron deposits in the deep nuclei. Myelination and iron deposition in the brain evolve both spatially and temporally. This evolution reflects an important characteristic of normal brain development and ageing. In this study, we assessed the changes of regional susceptibility in the human brain in vivo by examining the developmental and ageing process from 1 to 83 years of age. The evolution of magnetic susceptibility over this lifespan was found to display differential trajectories between the gray and the white matter. In both cortical and subcortical white matter, an initial decrease followed by a subsequent increase in magnetic susceptibility was observed, which could be fitted by a Poisson curve. In the gray matter, including the cortical gray matter and the iron-rich deep nuclei, magnetic susceptibility displayed a monotonic increase that can be described by an exponential growth. The rate of change varied according to functional and anatomical regions of the brain. For the brain nuclei, the age-related changes of susceptibility were in good agreement with the findings from R2* measurement. Our results suggest that magnetic susceptibility may provide valuable information regarding the spatial and temporal patterns of brain myelination and iron deposition during brain maturation and ageing. © 2013 Wiley Periodicals, Inc.

Modelling the nano-scale phenomena in condensed matter physics via computer-based numerical simulations

A review of the atomistic modelling of the behaviour of nano-scale structures and processes via molecular dynamics (MD) simulation method of a canonical ensemble is presented. Three areas of application in condensed matter physics are considered. We focus on the adhesive and indentation properties of the solid surfaces in nano-contacts, the nucleation and growth of nano-phase metallic and semi-conducting atomic and molecular films on supporting substrates, and the nano- and multi-scale crack propagation properties of metallic lattices. A set of simulations selected from these fields are discussed, together with a brief introduction to the methodology of the MD simulation. The pertinent inter-atomic potentials that model the energetics of the metallic and semi-conducting systems are also given.

Modelling high particulate matter and ozone episodes in the Trans-Manche region

There is concern in the Cross-Channel region of Nord-Pas-de-Calais (France) and Kent (Great Britain), regarding the extent of atmospheric pollution detected in the area from emitted gaseous (VOC, NOx, S02)and particulate substances. In particular, the air quality of the Cross-Channel or "Trans-Manche" region is highly affected by the heavily industrial area of Dunkerque, in addition to transportation sources linked to cross-channel traffic in Kent and Calais, posing threats to the environment and human health. In the framework of the cross-border EU Interreg IIIA activity, the joint Anglo-French project, ATTMA, has been commissioned to study Aerosol Transport in the Trans-Manche Atmosphere. Using ground monitoring data from UK and French networks and with the assistance of satellite images the project aims to determine dispersion patterns. and identify sources responsible for the pollutants. The findings of this study will increase awareness and have a bearing on future air quality policy in the region. Public interest is evident by the presence of local authorities on both sides of the English Channel as collaborators. The research is based on pollution transport simulations using (a) Lagrangian Particle Dispersion (LPD) models, (b) an Eulerian Receptor Based model. This paper is concerned with part (a), the LPD Models. Lagrangian Particle Dispersion (LPD) models are often used to numerically simulate the dispersion of a passive tracer in the planetary boundary layer by calculating the Lagrangian trajectories of thousands of notional particles. In this contribution, the project investigated the use of two widely used particle dispersion models: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the model FLEXPART. In both models forward tracking and inverse (or·. receptor-based) modes are possible. Certain distinct pollution episodes have been selected from the monitor database EXPER/PF and from UK monitoring stations, and their likely trajectory predicted using prevailing weather data. Global meteorological datasets were downloaded from the ECMWF MARS archive. Part of the difficulty in identifying pollution sources arises from the fact that much of the pollution outside the monitoring area. For example heightened particulate concentrations are to originate from sand storms in the Sahara, or volcanic activity in Iceland or the Caribbean work identifies such long range influences. The output of the simulations shows that there are notable differences between the formulations of and Hysplit, although both models used the same meteorological data and source input, suggesting that the identification of the primary emissions during air pollution episodes may be rather uncertain.