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.

E-Band Transformer-Based Differential 4-Way Power-Combining Amplifier

This paper presents the design and implementation of a differential 4-way power-combining amplifier operating at E-band. The proposed 4-way power combiner (4WPC) facilitates short interconnects to the PA cells, thereby resulting in reduced loss. Simple C-L-C and L-C networks are deployed in order to compensate inductive loading due to the routing lines that would otherwise introduce mismatch and subsequently increase overall loss. Realized in SiGe technology, the PA prototype delivered 13.2 dBm output-referred 1-dB compression point and 14.3 dBm saturated output power when operated from a single 3.3 V DC supply at 75 GHz.

Epitaxial BiFeO3 nanostructures fabricated by differential etching of BiFeO3 films

We report on differential etching behavior of the different orientations of the polarization in BiFeO3 (BFO), similar to other ferroelectrics, such as LiNbO3. We show how this effect can be used to fabricate epitaxial BiFeO3 nanostructures. By means of piezoresponse force microscopy (PFM) domains of arbitrary shape and size can be poled in an epitaxial BiFeO3 film, which are then reproduced in the film morphology by differential etching. Structures with a lateral size smaller than 200 nm were fabricated and very good retention properties as well as a highly increased piezoelectric response were detected by PFM. (C) 2011 American Institute of Physics. [doi:10.1063/1.3630027]

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21 856) and multiple sclerosis (MS) (n=43 879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16 731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.Molecular Psychiatry advance online publication, 28 January 2014; doi:10.1038/mp.2013.195.

Roche tomography of cataclysmic variables - VI. Differential rotation of AE Aqr - not tidally locked!

We present Roche tomograms of the K4V secondary star in the cataclysmic variable AE Aqr, reconstructed from two data sets taken 9 d apart, and measure the differential rotation of the stellar surface. The tomograms show many large, cool starspots, including a large high-latitude spot and a prominent appendage down the trailing hemisphere. We find two distinct bands of spots around 22° and 43° latitude, and estimate a spot coverage of 15.4-17 per cent on the Northern hemisphere. Assuming a solar-like differential rotation law, the differential rotation of AE Aqr was measured using two different techniques. The first method yields an equator-pole lap time of 269 d and the second yields a lap time of 262 d. This shows that the star is not fully tidally locked, as was previously assumed for CVs, but has a co-rotation latitude of ˜40°. We discuss the implications that these observations have on stellar dynamo theory, as well as the impact that spot traversal across the L1 point may have on accretion rates in CVs as well as some of their other observed properties. The entropy landscape technique was applied to determine the system parameters of AE Aqr. For the two independent data sets, we find M1 = 1.20 and 1.17 M⊙, M2 = 0.81 and 0.78 M⊙, and orbital inclinations of 50° to 51° at optimal systemic velocities of γ = -64.7 and -62.9 km s-1.

Differential affinity of FLIP and procaspase 8 for FADD's DED binding surfaces regulates DISC assembly

Death receptor activation triggers recruitment of FADD, which via its death effector domain (DED) engages the DEDs of procaspase 8 and its inhibitor FLIP to form death-inducing signalling complexes (DISCs). The DEDs of FADD, FLIP and procaspase 8 interact with one another using two binding surfaces defined by α1/α4 and α2/α5 helices, respectively. Here we report that FLIP has preferential affinity for the α1/α4 surface of FADD, whereas procaspase 8 has preferential affinity for FADD's α2/α5 surface. These relative affinities contribute to FLIP being recruited to the DISC at comparable levels to procaspase 8 despite lower cellular expression. Additional studies, including assessment of DISC stoichiometry and functional assays, suggest that following death receptor recruitment, the FADD DED preferentially engages FLIP using its α1/α4 surface and procaspase 8 using its α2/α5 surface; these tripartite intermediates then interact via the α1/α4 surface of FLIP DED1 and the α2/α5 surface of procaspase 8 DED2.

GPU Acceleration of Partial Differential Equation Solvers

Differential equations are often directly solvable by analytical means only in their one dimensional version. Partial differential equations are generally not solvable by analytical means in two and three dimensions, with the exception of few special cases. In all other cases, numerical approximation methods need to be utilized. One of the most popular methods is the finite element method. The main areas of focus, here, are the Poisson heat equation and the plate bending equation. The purpose of this paper is to provide a quick walkthrough of the various approaches that the authors followed in pursuit of creating optimal solvers, accelerated with the use of graphical processing units, and comparing them in terms of accuracy and time efficiency with existing or self-made non-accelerated solvers.

Mutagenesis of RpoE-like sigma factor genes in Bdellovibrio reveals differential control of groEL and two groES genes

BACKGROUND: Bdellovibrio bacteriovorus HD100 must regulate genes in response to a variety of environmental conditions as it enters, preys upon and leaves other bacteria, or grows axenically without prey. In addition to "housekeeping" sigma factors, its genome encodes several alternate sigma factors, including 2 Group IV-RpoE-like proteins, which may be involved in the complex regulation of its predatory lifestyle.

RESULTS: We find that one sigma factor gene, bd3314, cannot be deleted from Bdellovibrio in either predatory or prey-independent growth states, and is therefore possibly essential, likely being an alternate sigma 70. Deletion of one of two Group IV-like sigma factor genes, bd0881, affects flagellar gene regulation and results in less efficient predation, although not due to motility changes; deletion of the second, bd0743, showed that it normally represses chaperone gene expression and intriguingly we find an alternative groES gene is expressed at timepoints in the predatory cycle where intensive protein synthesis at Bdellovibrio septation, prior to prey lysis, will be occurring.

CONCLUSIONS: We have taken the first step in understanding how alternate sigma factors regulate different processes in the predatory lifecycle of Bdellovibrio and discovered that alternate chaperones regulated by one of them are expressed at different stages of the lifecycle.

Differential evolution combined with clonal selection for dynamic economic dispatch

Dynamic economic load dispatch (DELD) is one of the most important steps in power system operation. Various optimisation algorithms for solving the problem have been developed; however, due to the non-convex characteristics and large dimensionality of the problem, it is necessary to explore new methods to further improve the dispatch results and minimise the costs. This article proposes a hybrid differential evolution (DE) algorithm, namely clonal selection-based differential evolution (CSDE), to solve the problem. CSDE is an artificial intelligence technique that can be applied to complex optimisation problems which are for example nonlinear, large scale, non-convex and discontinuous. This hybrid algorithm combines the clonal selection algorithm (CSA) as the local search technique to update the best individual in the population, which enhances the diversity of the solutions and prevents premature convergence in DE. Furthermore, we investigate four mutation operations which are used in CSA as the hyper-mutation operations. Finally, an efficient solution repair method is designed for DELD to satisfy the complicated equality and inequality constraints of the power system to guarantee the feasibility of the solutions. Two benchmark power systems are used to evaluate the performance of the proposed method. The experimental results show that the proposed CSDE/best/1 approach significantly outperforms nine other variants of CSDE and DE, as well as most other published methods, in terms of the quality of the solution and the convergence characteristics.