Genome-wide scans of three independent sets of 90 Irish multiplex schizophrenia families and follow-up of selected regions in all families provides evidence for multiple susceptibility genes

From our linkage study of Irish families with a high density of schizophrenia, we have previously reported evidence for susceptibility genes in regions 5q21-31, 6p24-21, 8p22-21, and 10p15-p11. In this report, we describe the cumulative results from independent genome scans of three a priori random subsets of 90 families each, and from multipoint analysis of all 270 families in ten regions. Of these ten regions, three (13q32, 18p11-q11, and 18q22-23) did not generate scores above the empirical baseline pairwise scan results, and one (6q13-26) generated a weak signal. Six other regions produced more positive pairwise and multipoint results. They showed the following maximum multipoint H-LOD (heterogeneity LOD) and NPL scores: 2p14-13: 0.89 (P = 0.06) and 2.08 (P = 0.02), 4q24-32: 1.84 (P = 0.007) and 1.67 (P = 0.03), 5q21-31: 2.88 (P= 0.0007), and 2.65 (P = 0.002), 6p25-24: 2.13 (P = 0.005) and 3.59 (P = 0.0005), 6p23: 2.42 (P = 0.001) and 3.07 (P = 0.001), 8p22-21: 1.57 (P = 0.01) and 2.56 (P = 0.005), 10p15-11: 2.04 (P = 0.005) and 1.78 (P = 0.03). The degree of 'internal replication' across subsets differed, with 5q, 6p, and 8p being most consistent and 2p and 10p being least consistent. On 6p, the data suggested the presence of two susceptibility genes, in 6p25-24 and 6p23-22. Very few families were positive on more than one region, and little correlation between regions was evident, suggesting substantial locus heterogeneity. The levels of statistical significance were modest, as expected from loci contributing to complex traits. However, our internal replications, when considered along with the positive results obtained in multiple other samples, suggests that most of these six regions are likely to contain genes that influence liability to schizophrenia.

Thermolyzable polymer networks and star polymers containing a novel, compact, degradable acylal-based dimethacrylate cross-linker: Synthesis, characterization, and thermolysis

A compact, cleavable acylal dimethacrylate cross-linker, 1,1-ethylenediol dimethacrylate (EDDMA), was synthesized from the anhydrous iron(III) chloride-catalyzed reaction between methacrylic anhydride and acetaldehyde. The ability of EDDMA to act as cross-linker was demonstrated by using it for the preparation of one neat cross-linker network, four star polymers of methyl methacrylate (MMA), and four randomly cross-linked MMA polymer networks using group transfer polymerization (GTP). For comparison, the corresponding polymer structures based on the commercially available ethylene glycol dimethacrylate (EGDMA) cross-linker (isomer of EDDMA) were also prepared via GTR The number of arms of the EDDMA-based star polymers was lower than that of the corresponding EGDMA polymers, whereas the degrees of swelling in tetrahydrofuran of the EDDMA-based MMA networks were higher than those of their EGDMA-based counterparts. Although none of the EDDMA-containing polymers could be cleanly hydrolyzed under basic or acidic conditions, they could be thermolyzed at 200 degrees C within 1 day giving lower molecular weight products.

Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets

Motivation: To date, Gene Set Analysis (GSA) approaches primarily focus on identifying differentially expressed gene sets (pathways). Methods for identifying differentially coexpressed pathways also exist but are mostly based on aggregated pairwise correlations, or other pairwise measures of coexpression. Instead, we propose Gene Sets Net Correlations Analysis (GSNCA), a multivariate differential coexpression test that accounts for the complete correlation structure between genes.

Results: In GSNCA, weight factors are assigned to genes in proportion to the genes' cross-correlations (intergene correlations). The problem of finding the weight vectors is formulated as an eigenvector problem with a unique solution. GSNCA tests the null hypothesis that for a gene set there is no difference in the weight vectors of the genes between two conditions. In simulation studies and the analyses of experimental data, we demonstrate that GSNCA, indeed, captures changes in the structure of genes' cross-correlations rather than differences in the averaged pairwise correlations. Thus, GSNCA infers differences in coexpression networks, however, bypassing method-dependent steps of network inference. As an additional result from GSNCA, we define hub genes as genes with the largest weights and show that these genes correspond frequently to major and specific pathway regulators, as well as to genes that are most affected by the biological difference between two conditions. In summary, GSNCA is a new approach for the analysis of differentially coexpressed pathways that also evaluates the importance of the genes in the pathways, thus providing unique information that may result in the generation of novel biological hypotheses.

Design of a compact spectrometer for high-flux MeV gamma-ray beams

A novel design for a compact gamma-ray spectrometer is presented. The proposed system allows for spectroscopy of high-flux multi-MeV gamma-ray beams with MeV energy resolution in a compact design. In its basic configuration, the spectrometer exploits conversion of gamma-rays into electrons via Compton scattering in a low-Z material. The scattered electron population is then spectrally resolved using a magnetic spectrometer. The detector is shown to be effective for gamma-ray energies between 3 and 20 MeV. The main properties of the spectrometer are confirmed by Monte Carlo simulations.

Compact Low-Profile Antenna for Wireless Medical Vital Sign Monitors at 868 MHz

A low-profile wearable antenna suitable for integration into low-cost, disposable medical vital signs monitors is presented. Simulated and measured antenna performance was characterized on a layered human tissue phantom, representative of the thorax region of a range of human bodies. The wearable antenna has sufficient bandwidth for the 868 MHz Industrial, Scientific and Medical frequency band. Wearable radiation efficiency of up to 30 % is reported when mounted in close proximity to the novel human tissue phantom antenna test-bed at 868 MHz.

Compact FSS absorber design using resistively loaded quadruple hexagonal loops for bandwidth enhancement

This letter presents the design of a thin microwave absorber which exhibits a -10 dB reflectivity bandwidth of 108% at normal incidence and 16% for simultaneous suppression of TE and TM polarised waves over the angular range 0-45° is presented. The structure consists of a 3 mm-thick metal backed frequency selective surface (FSS) with four resistively loaded hexagonal loop elements in each unit cell. The surface resistivity and width of the loops are carefully chosen to maximise the bandwidth by merging the reflection nulls that are generated by the multi-resonant absorber. Measurement and simulation results are in good agreement over the broad frequency range 7.8-24 GHz.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

Kuznetsov independence of variables X and Y means that, for any pair of bounded functions f(X) and g(Y), E[f(X)g(Y)]=E[f(X)] *times* E[g(Y)], where E[.] denotes interval-valued expectation and *times* denotes interval multiplication. We present properties of Kuznetsov independence for several variables, and connect it with other concepts of independence in the literature; in particular we show that strong extensions are always included in sets of probability distributions whose lower and upper expectations satisfy Kuznetsov independence. We introduce an algorithm that computes lower expectations subject to judgments of Kuznetsov independence by mixing column generation techniques with nonlinear programming. Finally, we define a concept of conditional Kuznetsov independence, and study its graphoid properties.

Inference in Credal Networks Through Integer Programming

A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks.

The use of a novel compact fluorosensor for in situ monitoring of the photocatalytic destruction of methylene blue dye effluents

The use of TiO 2 photocatalysis for the destruction of dyes such as methylene blue has been extensively reported. One of the challenges faced in both the laboratory and large scale water treatment plants is the fact that the samples have to be removed from the reactor vessel and the catalyst separated prior to analysis being undertaken. In this paper we report the development of a simple fluorimeter instrument and its use in monitoring the photocatalytic destruction of methylene blue dyes in the presence of catalyst suspensions. The results reported show that the instrument provides an effective method for in situ monitoring of the photocatalytic destruction of fluorescent dyes hence allowing more accurate measurement due to the minimisation of sample loss and cross contamination. Furthermore it also provides a method for real time monitoring of the dye pollutant destruction in large scale photocatalytic reactors.

A compact broadband ion beam focusing device based on laser-driven megagauss thermoelectric magnetic fields

Ultra-intense lasers can nowadays routinely accelerate kiloampere ion beams. These unique sources of particle beams could impact many societal (e.g., proton-therapy or fuel recycling) and fundamental (e.g., neutron probing) domains. However, this requires overcoming the beam angular divergence at the source. This has been attempted, either with large-scale conventional setups or with compact plasma techniques that however have the restriction of short (<1 mm) focusing distances or a chromatic behavior. Here, we show that exploiting laser-triggered, long-lasting (>50 ps), thermoelectric multi-megagauss surface magnetic (B)-fields, compact capturing, and focusing of a diverging laser-driven multi-MeV ion beam can be achieved over a wide range of ion energies in the limit of a 5° acceptance angle.