7,695 research outputs found

    sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

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    Background: Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. Results: This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. Conclusions: The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMapComment: 3 pages, 1 table, 1 eps figur

    A simple and robust method for connecting small-molecule drugs using gene-expression signatures

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    Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties. The Connectivity Map was a novel concept and innovative tool first introduced by Lamb et al to connect small molecules, genes, and diseases using genomic signatures [Lamb et al (2006), Science 313, 1929-1935]. However, the Connectivity Map had some limitations, particularly there was no effective safeguard against false connections if the observed connections were considered on an individual-by-individual basis. Further when several connections to the same small-molecule compound were viewed as a set, the implicit null hypothesis tested was not the most relevant one for the discovery of real connections. Here we propose a simple and robust method for constructing the reference gene-expression profiles and a new connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with the two example gene-signatures (HDAC inhibitors and Estrogens) used by Lamb et al and also a new gene signature of immunosuppressive drugs. Our testing with this new method shows that it achieves a higher level of specificity and sensitivity than the original method. For example, our method successfully identified raloxifene and tamoxifen as having significant anti-estrogen effects, while Lamb et al's Connectivity Map failed to identify these. With these properties our new method has potential use in drug development for the recognition of pharmacological and toxicological properties in new drug candidates.Comment: 8 pages, 2 figures, and 2 tables; supplementary data supplied as a ZIP fil

    AtPAP2 modulates the import of the small subunit of Rubisco into chloroplasts

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    Sign-reversal of the in-plane resistivity anisotropy in hole-doped iron pnictides

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    The in-plane anisotropy of the electrical resistivity across the coupled orthorhombic and magnetic transitions of the iron pnictides has been extensively studied in the parent and electron-doped compounds. All these studies universally show that the resistivity ρa\rho_{a} across the long orthorhombic axis aOa_{O} - along which the spins couple antiferromagnetically below the magnetic transition temperature - is smaller than the resistivity ρb\rho_{b} of the short orthorhombic axis bOb_{O}, i. e. ρa<ρb\rho_{a}<\rho_{b}. Here we report that in the hole-doped compounds Ba1x_{1-x}Kx_{x}Fe2_{2}As2_{2}, as the doping level increases, the resistivity anisotropy initially becomes vanishingly small, and eventually changes sign for sufficiently large doping, i. e. ρb<ρa\rho_{b}<\rho_{a}. This observation is in agreement with a recent theoretical prediction that considers the anisotropic scattering of electrons by spin-fluctuations in the orthorhombic/nematic state.Comment: This paper has been replaced by the new version offering new explanation of the experimental results first reported her

    A geometric network model of intrinsic grey-matter connectivity of the human brain

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    Network science provides a general framework for analysing the large-scale brain networks that naturally arise from modern neuroimaging studies, and a key goal in theoretical neuro- science is to understand the extent to which these neural architectures influence the dynamical processes they sustain. To date, brain network modelling has largely been conducted at the macroscale level (i.e. white-matter tracts), despite growing evidence of the role that local grey matter architecture plays in a variety of brain disorders. Here, we present a new model of intrinsic grey matter connectivity of the human connectome. Importantly, the new model incorporates detailed information on cortical geometry to construct ‘shortcuts’ through the thickness of the cortex, thus enabling spatially distant brain regions, as measured along the cortical surface, to communicate. Our study indicates that structures based on human brain surface information differ significantly, both in terms of their topological network characteristics and activity propagation properties, when compared against a variety of alternative geometries and generative algorithms. In particular, this might help explain histological patterns of grey matter connectivity, highlighting that observed connection distances may have arisen to maximise information processing ability, and that such gains are consistent with (and enhanced by) the presence of short-cut connections

    Predictability of evolutionary trajectories in fitness landscapes

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    Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.Comment: 14 pages, 7 figure

    An epidemiologic study of early biologic effects of benzene in Chinese workers.

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    Benzene is a recognized hematotoxin and leukemogen, but its mechanisms of action in humans are still uncertain. To provide insight into these processes, we carried out a cross-sectional study of 44 healthy workers currently exposed to benzene (median 8-hr time-weighted average; 31 ppm), and unexposed controls in Shanghai, China. Here we provide an overview of the study results on peripheral blood cells levels and somatic cell mutation frequency measured by the glycophorin A (GPA) gene loss assay and report on peripheral cytokine levels. All peripheral blood cells levels (i.e., total white blood cells, absolute lymphocyte count, platelets, red blood cells, and hemoglobin) were decreased among exposed workers compared to controls, with the exception of the red blood cell mean corpuscular volume, which was higher among exposed subjects. In contrast, peripheral cytokine levels (interleukin-3, interleukin-6, erythropoietin, granulocyte colony-stimulating factor, tissue necrosis factor-alpha) in a subset of the most highly exposed workers (n = 11) were similar to values in controls (n = 11), suggesting that benzene does not affect these growth factor levels in peripheral blood. The GPA assay measures stem cell or precursor erythroid cell mutations expressed in peripheral red blood cells of MN heterozygous subjects, identifying NN variants, which result from loss of the GPA M allele and duplication of the N allele, and N phi variants, which arise from gene inactivation. The NN (but not N phi) GPA variant cell frequency was elevated in the exposed workers compared with controls (mean +/- SD, 13.9 +/- 8.4 mutants per million cells versus 7.4 +/- 5.2 per million cells, (respectively; p = 0.0002), suggesting that benzene produces gene-duplicating but not gene-inactivating mutations at the GPA locus in bone marrow cells of exposed humans. These findings, combined with ongoing analyses of benzene macromolecular adducts and chromosomal aberrations, will provide an opportunity to comprehensively evaluate a wide range of early biologic effects associated with benzene exposure in humans

    Blow-up profile of rotating 2D focusing Bose gases

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    We consider the Gross-Pitaevskii equation describing an attractive Bose gas trapped to a quasi 2D layer by means of a purely harmonic potential, and which rotates at a fixed speed of rotation Ω\Omega. First we study the behavior of the ground state when the coupling constant approaches a_a\_* , the critical strength of the cubic nonlinearity for the focusing nonlinear Schr{\"o}dinger equation. We prove that blow-up always happens at the center of the trap, with the blow-up profile given by the Gagliardo-Nirenberg solution. In particular, the blow-up scenario is independent of Ω\Omega, to leading order. This generalizes results obtained by Guo and Seiringer (Lett. Math. Phys., 2014, vol. 104, p. 141--156) in the non-rotating case. In a second part we consider the many-particle Hamiltonian for NN bosons, interacting with a potential rescaled in the mean-field manner a_NN2β1w(Nβx),with--a\_N N^{2\beta--1} w(N^{\beta} x), with wapositivefunctionsuchthat a positive function such that \int\_{\mathbb{R}^2} w(x) dx = 1.Assumingthat. Assuming that \beta < 1/2andthat and that a\_N \to a\_*sufficientlyslowly,weprovethatthemanybodysystemisfullycondensedontheGrossPitaevskiigroundstateinthelimit sufficiently slowly, we prove that the many-body system is fully condensed on the Gross-Pitaevskii ground state in the limit N \to \infty$

    Exoplanet phase curves: observations and theory

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    Phase curves are the best technique to probe the three dimensional structure of exoplanets' atmospheres. In this chapter we first review current exoplanets phase curve observations and the particular challenges they face. We then describe the different physical mechanisms shaping the atmospheric phase curves of highly irradiated tidally locked exoplanets. Finally, we discuss the potential for future missions to further advance our understanding of these new worlds.Comment: Fig.5 has been updated. Table 1 and corresponding figures have been updated with new values for WASP-103b and WASP-18b. Contains a table sumarizing phase curve observation

    Ductile Metallic Glasses in Supercooled Martensitic Alloys

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    We report ductile bulk metallic glasses based on martensitic alloys. The slowly cooled specimens contain a mixture of parent 'austenite' and martensite phase. The slightly faster cooled bulk metallic glasses with 2-5 nm sized 'austenite'-like crystalline cluster reveal high strength and large ductility (16%). Shear bands propagate in a slither mode in this spatially inhomogeneous glassy structure and undergo considerable 'thickening' from 5-25 nm. A 'stress induced displacive transformation' is proposed to be responsible for both plasticity and work-hardening-like behavior of these 'M-Glasses'
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