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.

Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

Development of non-intrusive monitoring for reactive switching of high voltage circuit breaker

High-voltage circuit breakers are among the most important equipments for ensuring the efficient and safe operation of an electric power system. On occasion, circuit breaker operators may wish to check whether equipment is performing satisfactorily and whether controlled switching systems are producing reliable and repeatable stress control. Monitoring of voltage and current waveforms during switching using established methods will provide information about the magnitude and frequency of voltage transients as a result of re-ignitions and restrikes. However, high frequency waveform measurement requires shutdown of circuit breaker and use of specialized equipment. Two utilities, Hydro-Québec in Canada and Powerlink Queensland in Australia, have been working on the development and application of a non-intrusive, cost-effective and flexible diagnostic system for monitoring high-voltage circuit breakers for reactive switching. The proposed diagnostic approach relies on the non-intrusive assessment of key parameters such as operating times, prestrike characteristics, re-ignition and restrike detection. Transient electromagnetic emissions have been identified as a promising means to evaluate the abovementioned parameters non-intrusively. This paper describes two complimentary methods developed concurrently by Powerlink and Hydro-Québec. Also, return of experiences on the application to capacitor bank and shunt reactor switching is presented.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Nutritional impact of antipseudomonas intravenous antibiotic courses in cystic fibrosis

Editor,—In their study of cystic fibrosis patients who were nutritionally assessed at the start and end of a 14 day period of home intravenous antibiotic treatment for chest disease, Vicet al concluded that increased weight was a result of increased fat storage.1 While this may in part be true, their methodology dictates caution in drawing conclusions....

The atmospheric extinction of light

An experiment is described that enables students to understand the properties of atmospheric extinction due to Rayleigh scattering. The experiment requires the use of red, green and blue lasers attached to a traveling microscope or similar device. The laser beams are passed through an artificial atmosphere, made from milky water, at varying depths, before impinging on either a light meter or a photodiode integral to a Picotech Dr. DAQ ADC. A plot of measured spectral intensity verses depth reveals the contribution Rayleigh scattering has to the extinction coefficient. For the experiment with the light meter, the extinction coefficient for red, green and blue light in the milky sample of water were 0.27, 0.36 and 0.47 cm-1 respectively and 0.032, 0.037 and 0.092 cm-1 for the Picotech Dr. DAQ ADC.

Antithrombin III associated with fibrinogen predicts the risk of cerebral ischemic stroke

Background and purpose: The purpose of this study is to examine the feasibility of developing plasma predictive value biomarkers of cerebral ischemic stroke before imaging evidence is acquired. Methods: Blood samples were obtained from 198 patients who attended our neurology department as emergencies - with symptoms of vertigo, numbness, limb weakness, etc. - within 4.5 h of symptom onset, and before imaging evidence was obtained and medical treatment. After the final diagnosis was made by MRI/DWI/MRA or CTA in the following 24-72 h, the above cases were divided into two groups: stroke group and non-stroke group according to the imaging results. The levels of baseline plasma antithrombin III (AT-III), thrombin-antithrombin III (TAT), fibrinogen, D-dimer and high-sensitivity C-reactive protein (hsCRP) in the two groups were assayed. Results: The level of the baseline AT-III in the stroke group was 118.07 ± 26.22%, which was lower than that of the non-stroke group (283.83 ± 38.39%). The levels of TAT, fibrinogen, hsCRP were 7.24 ± 2.28 μg/L, 5.49 ± 0.98 g/L, and 2.17 ± 1.07 mg/L, respectively, which were higher than those of the non-stroke group (2.53 ± 1.23 μg/L, 3.35 ± 0.50 g/L, 1.82 ± 0.67 mg/L). All the P-values were less than 0.001. The D-dimer level was 322.57 ± 60.34 μg/L, which was slightly higher than that of the non-stroke group (305.76 ± 49.52 μg/L), but the P-value was 0.667. The sensitivities of AT-III, TAT, fibrinogen, D-dimer and hsCRP for predicting ischemic stroke tendency were 97.37%, 96.05%, 3.29%, 7.89%, but the specificity was 93.62%, 82.61%, 100% and 100%, respectively, and all the P-values were less than 0.001. High levels of D-dimer and hsCRP were mainly seen in the few cases with severe large-vessel infarction. Conclusions: Clinical manifestations of acute focal neurological deficits were associated with plasma AT-III and fibrinogen. These tests might help the risk assessment of acute cerebral ischemic stroke and/or TIA with infarction tendency in the superacute stage before positive imaging evidence is obtained.

Neonatal screening for cystic fibrosis

Two groups of patients with cystic fibrosis were compared. The screened group, detected with an improved neonatal screening assay for immunoreactive trypsin, developed fewer chest infections requiring treatment and gained more weight than the unscreened group. Early diagnosis by screening seems to affect early morbidity.

Moving European research on work and ageing forward: Overview and agenda

This paper summarizes the state of affairs of European research on ageing and work. After a close inspection of the age construct, an overview is presented of research in four areas: the relationship between age and HR-policies, early retirement, age and performance/employability, age and health/well-being. The overview results in a research agenda on work and ageing and in recommendations for practice.

Dominating search: Google before the law

For many, particularly in the Anglophone world and Western Europe, it may be obvious that Google has a monopoly over online search and advertising and that this is an undesirable state of affairs, due to Google's ability to mediate information flows online. The baffling question may be why governments and regulators are doing little to nothing about this situation, given the increasingly pivotal importance of the internet and free flowing communications in our lives. However, the law concerning monopolies, namely antitrust or competition law, works in what may be seen as a less intuitive way by the general public. Monopolies themselves are not illegal. Conduct that is unlawful, i.e. abuses of that market power, is defined by a complex set of rules and revolves principally around economic harm suffered due to anticompetitive behavior. However the effect of information monopolies over search, such as Google’s, is more than just economic, yet competition law does not address this. Furthermore, Google’s collection and analysis of user data and its portfolio of related services make it difficult for others to compete. Such a situation may also explain why Google’s established search rivals, Bing and Yahoo, have not managed to provide services that are as effective or popular as Google’s own (on this issue see also the texts by Dirk Lewandowski and Astrid Mager in this reader). Users, however, are not entirely powerless. Google's business model rests, at least partially, on them – especially the data collected about them. If they stop using Google, then Google is nothing.

Designing for user engagement: The ALTC exchange for higher education

The Australasian Society for Computers in Learning in Tertiary Education (ascilite) has recently completed research to inform development of the ALTC Exchange, a new online service for learning and teaching in Australia. The research investigated resource identification and contribution, engagement with the repository and user community, and associated peer review and commentary processes. This article focuses on the data obtained and recommendations developed for engagement of potential end users. It reports a literature review and findings, including an international perspective on the ALTC Exchange, with specific focus on prospective user needs, contexts of use and policies necessary to facilitate engagement of the higher education sector with the ALTC Exchange