Changes in anatomical brain connectivity between ages 12 and 30: A HARDI study of 467 adolescents and adults

Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but only one study - in just 30 subjects - has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age 2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.

Heritability of white matter fiber tract shapes: A HARDI study of 198 twins

Genetic analysis of diffusion tensor images (DTI) shows great promise in revealing specific genetic variants that affect brain integrity and connectivity. Most genetic studies of DTI analyze voxel-based diffusivity indices in the image space (such as 3D maps of fractional anisotropy) and overlook tract geometry. Here we propose an automated workflow to cluster fibers using a white matter probabilistic atlas and perform genetic analysis on the shape characteristics of fiber tracts. We apply our approach to large study of 4-Tesla high angular resolution diffusion imaging (HARDI) data from 198 healthy, young adult twins (age: 20-30). Illustrative results show heritability for the shapes of several major tracts, as color-coded maps.

The multivariate A/C/E model and the genetics of fiber architecture

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.

White matter integrity measured by fractional anisotropy correlates poorly with actual individual fiber anisotropy

Fractional anisotropy (FA), a very widely used measure of fiber integrity based on diffusion tensor imaging (DTI), is a problematic concept as it is influenced by several quantities including the number of dominant fiber directions within each voxel, each fiber's anisotropy, and partial volume effects from neighboring gray matter. High-angular resolution diffusion imaging (HARDI) can resolve more complex diffusion geometries than standard DTI, including fibers crossing or mixing. The tensor distribution function (TDF) can be used to reconstruct multiple underlying fibers per voxel, representing the diffusion profile as a probabilistic mixture of tensors. Here we found that DTIderived mean diffusivity (MD) correlates well with actual individual fiber MD, but DTI-derived FA correlates poorly with actual individual fiber anisotropy, and may be suboptimal when used to detect disease processes that affect myelination. Analysis of the TDFs revealed that almost 40% of voxels in the white matter had more than one dominant fiber present. To more accurately assess fiber integrity in these cases, we here propose the differential diffusivity (DD), which measures the average anisotropy based on all dominant directions in each voxel.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Translation and psychometric properties of the Chinese version of the Leeds Attitudes to Concordance II scale

Background Concordance is characterised as a negotiation-like health communication approach based on an equal and collaborative partnership between patients and health professionals. The Leeds Attitudes to Concordance II (LATCon II) scale was developed to measure the attitudes towards concordance. The purpose of this study was to translate the LATCon II into Chinese and psychometrically test the Chinese version of LATCon II (C-LATCon II). Methods The study involved three phases: i) translation and cross-cultural adaptation; ii) pilot study, and; iii) a cross-sectional survey (n = 366). Systematic random sampling was used to recruit hypertensive patients from nine communities covering around 78,000 residents in China. Tests of psychometric properties included content validity, construct validity, criteria-related validity (correlation between the C-LATCon II and the Therapeutic Adherence Scale for Hypertensive Patients (TASHP)), internal reliability, and test-retest reliability (n = 30). Results The study found that the C-LATCon II had a satisfactory content validity (item-level Content Validity Index (CVI) = 0.83-1, scale-level CVI/universal agreement = 0.89, and scale-level CVI/averaging calculation = 0.98), construct validity (four components extracted explained 56.66% of the total variance), internal reliability (Cronbach’s alpha of overall scale and four components was 0.78 and 0.66-0.84, respectively), and test-retest reliability (Pearson’s correlation coefficient = 0.82, p < 0.001; interclass correlation coefficient = 0.82, p < 0.001; linear weighted kappa3 statistic for each item = 0.40-0.65, p < 0.05). Criteria-related validity showed a weak association (Pearson’s correlation coefficient = 0.11, p < 0.05) between patients’ attitudes towards concordance during health communication and their health behaviours for hypertension management. Conclusions The C-LATCon II is a validated and reliable instrument which can be used to evaluate the attitudes to concordance in Chinese populations. Four components (health professionals’ attitudes, partnership between two parties, therapeutic decision making, and patients’ involvement) describe the attitudes towards concordance during health communication.

Tuning the resonance properties of 2D carbon nanotube networks towards a mechanical resonator

The capabilities of the mechanical resonator-based nanosensors in detecting ultra-small mass or force shifts have driven a continuing exploration of the palette of nanomaterials for such application purposes. Based on large-scale molecular dynamics simulations, we have assessed the applicability of a new class of carbon nanomaterials for nanoresonator usage, i.e. the single-wall carbon nanotube (SWNT) network. It is found that SWNT networks inherit excellent mechanical properties from the constituent SWNTs, possessing a high natural frequency. However, although a high quality factor is suggested from the simulation results, it is hard to obtain an unambiguous Q-factor due to the existence of vibration modes in addition to the dominant mode. The nonlinearities resulting from these extra vibration modes are found to exist uniformly under various testing conditions including different initial actuations and temperatures. Further testing shows that these modes can be effectively suppressed through the introduction of axial strain, leading to an extremely high quality factor in the order of 109 estimated from the SWNT network with 2% tensile strain. Additional studies indicate that the carbon rings connecting the SWNTs can also be used to alter the vibrational properties of the resulting network. This study suggests that the SWNT network can be a good candidate for applications as nanoresonators.

A simple approach to improve the electrocatalytic properties of commercial Pt/C

Here we demonstrate that commercial carbon supported Pt nanoparticles react with [AuCl4]- ions at room temperature to produce a highly active Au/Pt/C material with an ultralow coverage of elemental Au on the Pt nanoparticles that exhibits significantly enhanced activity for ethanol oxidation when compared to Pt/C.

Sodium and lithium storage properties of spray-dried molybdenum disulfide-graphene hierarchical microspheres

Developing nano/micro-structures which can effectively upgrade the intriguing properties of electrode materials for energy storage devices is always a key research topic. Ultrathin nanosheets were proved to be one of the potential nanostructures due to their high specific surface area, good active contact areas and porous channels. Herein, we report a unique hierarchical micro-spherical morphology of well-stacked and completely miscible molybdenum disulfide (MoS2) nanosheets and graphene sheets, were successfully synthesized via a simple and industrial scale spray-drying technique to take the advantages of both MoS2 and graphene in terms of their high practical capacity values and high electronic conductivity, respectively. Computational studies were performed to understand the interfacial behaviour of MoS2 and graphene, which proves high stability of the composite with high interfacial binding energy (−2.02 eV) among them. Further, the lithium and sodium storage properties have been tested and reveal excellent cyclic stability over 250 and 500 cycles, respectively, with the highest initial capacity values of 1300 mAh g−1 and 640 mAh g−1 at 0.1 A g−1.

Effects of biodiesel chemical composition on the chemical and physical properties of the primary and secondary diesel particulate matter

This thesis improves our insight towards the effects of using biodiesels on the particulate matter emission of diesel engines and contributes to our understanding of their potential adverse health effects. The novelty of this project is the use of biodiesel fuel with controlled chemical composition that enables us to relate changes of physiochemical properties of particles to specific properties of the biodiesel. For the first time, the possibility of a correlation of the volatility and the Reactive Oxygen Species concentration of the particles is investigated versus the saturation, oxygen content and carbon chain length of the fuel.

Single layer lead iodide: Computational exploration of structural, electronic and optical properties, strain induced band modulation and the role of spin-orbital-coupling

Graphitic like layered materials exhibit intriguing electronic structures and thus the search for new types of two-dimensional (2D) monolayer materials is of great interest for developing novel nano-devices. By using density functional theory (DFT) method, here we for the first time investigate the structure, stability, electronic and optical properties of monolayer lead iodide (PbI2). The stability of PbI2 monolayer is first confirmed by phonon dispersion calculation. Compared to the calculation using generalized gradient approximation, screened hybrid functional and spin–orbit coupling effects can not only predicts an accurate bandgap (2.63 eV), but also the correct position of valence and conduction band edges. The biaxial strain can tune its bandgap size in a wide range from 1 eV to 3 eV, which can be understood by the strain induced uniformly change of electric field between Pb and I atomic layer. The calculated imaginary part of the dielectric function of 2D graphene/PbI2 van der Waals type hetero-structure shows significant red shift of absorption edge compared to that of a pure monolayer PbI2. Our findings highlight a new interesting 2D material with potential applications in nanoelectronics and optoelectronics.

Enhanced earth grid performance by improved conductor properties

Encroaching built environment with increased fault current levels is demanding a robust design approach and prolonged improved performance of the earth grid. With this in mind, the aim of the project was to perform a sensitivity analysis of the earth grid and an earthing performance evaluation with graphene coated conductors. Subsequent to these, a conceptual design to continuously monitor the performance of the earth grid was developed. In this study, earth grid design standards were compared to evaluate their appropriate use in determining the safety condition. A process to grow a thin film of graphene on the surface of cylindrical copper rods was developed to evaluate earthing performance in terms of conductivity and corrosion susceptibility.

Influence of interlayer properties on the blast performance of laminated glass panels

This paper investigates the influence of interlayer properties on the blast performance of laminated glass (LG) panels. A parametric study is carried out by varying the thickness and Young’s modulus (E) of the interlayer under two different blast loads. Results indicate the existence of a critical interlayer thickness (or E) that causes the onset of interlayer failure. This should be achieved in the design to enhance energy absorption, reduce support reactions and initiate a safer failure mode. Present findings provide information to achieve such design targets and enable safe and efficient performance of LGs under credible blast loads.