33 research outputs found

    Distribution function approach to redshift space distortions. Part II: N-body simulations

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    Measurement of redshift-space distortions (RSD) offers an attractive method to directly probe the cosmic growth history of density perturbations. A distribution function approach where RSD can be written as a sum over density weighted velocity moment correlators has recently been developed. We use Nbody simulations to investigate the individual contributions and convergence of this expansion for dark matter. If the series is expanded as a function of powers of mu, cosine of the angle between the Fourier mode and line of sight, there are a finite number of terms contributing at each order. We present these terms and investigate their contribution to the total as a function of wavevector k. For mu^2 the correlation between density and momentum dominates on large scales. Higher order corrections, which act as a Finger-of-God (FoG) term, contribute 1% at k~0.015h/Mpc, 10% at k~0.05h/Mpc at z=0, while for k>0.15h/Mpc they dominate and make the total negative. These higher order terms are dominated by density-energy density correlations which contribute negatively to the power, while the contribution from vorticity part of momentum density auto-correlation is an order of magnitude lower. For mu^4 term the dominant term on large scales is the scalar part of momentum density auto-correlation, while higher order terms dominate for k>0.15h/Mpc. For mu^6 and mu^8 we find it has very little power for k<0.15h/Mpc. We also compare the expansion to the full 2D P^ss(k,mu) as well as to their multipoles. For these statistics an infinite number of terms contribute and we find that the expansion achieves percent level accuracy for kmu<0.15h/Mpc at 6th order, but breaks down on smaller scales because the series is no longer perturbative. We explore resummation of the terms into FoG kernels, which extend the convergence up to a factor of 2 in scale. We find that the FoG kernels are approximately Lorentzian.Comment: 21 pages, 9 figures, published in JCA

    Large Scale Structures in Kinetic Gravity Braiding Model That Can Be Unbraided

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    We study cosmological consequences of a kinetic gravity braiding model, which is proposed as an alternative to the dark energy model. The kinetic braiding model we study is characterized by a parameter n, which corresponds to the original galileon cosmological model for n=1. We find that the background expansion of the universe of the kinetic braiding model is the same as the Dvali-Turner's model, which reduces to that of the standard cold dark matter model with a cosmological constant (LCDM model) for n equal to infinity. We also find that the evolution of the linear cosmological perturbation in the kinetic braiding model reduces to that of the LCDM model for n=\infty. Then, we focus our study on the growth history of the linear density perturbation as well as the spherical collapse in the nonlinear regime of the density perturbations, which might be important in order to distinguish between the kinetic braiding model and the LCDM model when n is finite. The theoretical prediction for the large scale structure is confronted with the multipole power spectrum of the luminous red galaxy sample of the Sloan Digital Sky survey. We also discuss future prospects of constraining the kinetic braiding model using a future redshift survey like the WFMOS/SuMIRe PFS survey as well as the cluster redshift distribution in the South Pole Telescope survey.Comment: 41 pages, 20 figures; This version was accepted for publication in JCA

    Measuring the neutrino mass from future wide galaxy cluster catalogues

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    We present forecast errors on a wide range of cosmological parameters obtained from a photometric cluster catalogue of a future wide-field Euclid-like survey. We focus in particular on the total neutrino mass as constrained by a combination of the galaxy cluster number counts and correlation function. For the latter we consider only the shape information and the Baryon Acoustic Oscillations (BAO), while marginalising over the spectral amplitude and the redshift space distortions. In addition to the cosmological parameters of the standard LCDM+nu model we also consider a non-vanishing curvature, and two parameters describing a redshift evolution for the dark energy equation of state. For completeness, we also marginalise over a set of "nuisance" parameters, representing the uncertainties on the cluster mass determination. We find that combining cluster counts with power spectrum information greatly improves the constraining power of each probe taken individually, with errors on cosmological parameters being reduced by up to an order of magnitude. In particular, the best improvements are for the parameters defining the dynamical evolution of dark energy, where cluster counts break degeneracies. Moreover, the resulting error on neutrino mass is at the level of \sigma(M_\nu)\sim 0.9 eV, comparable with that derived from present Ly-alpha forest measurements and Cosmic Microwave background (CMB) data in the framework of a non-flat Universe. Further adopting Planck priors and reducing the number of free parameters to a LCDM+nu cosmology allows to place constraints on the total neutrino mass of \sigma(M_\nu) \sim 0.08 eV, close to the lower bound enforced by neutrino oscillation experiments. [abridged]Comment: 25 pages, 2 figures, 2 tables, matches the JCAP accepted versio

    Oxidative stress causes ERK phosphorylation and cell death in cultured retinal pigment epithelium: Prevention of cell death by AG126 and 15-deoxy-delta 12, 14-PGJ(2)

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    BACKGROUND: The retina, which is exposed to both sunlight and very high levels of oxygen, is exceptionally rich in polyunsaturated fatty acids, which makes it a favorable environment for the generation of reactive oxygen species. The cytotoxic effects of hydrogen peroxide (H(2)O(2)) induced oxidative stress on retinal pigment epithelium were characterized in this study. METHODS: The MTT cell viability assay, Texas-Red phalloidin staining, immunohistochemistry and Western blot analysis were used to assess the effects of oxidative stress on primary human retinal pigment epithelial cell cultures and the ARPE-19 cell line. RESULTS: The treatment of retinal pigment epithelial cells with H(2)O(2 )caused a dose-dependent decrease of cellular viability, which was preceded by a significant cytoskeletal rearrangement, activation of the Extracellular signal-Regulated Kinase, lipid peroxidation and nuclear condensation. This cell death was prevented partially by the prostaglandin derivative, 15d-PGJ(2 )and by the protein kinase inhibitor, AG126. CONCLUSION: 15d-PGJ(2 )and AG126 may be useful pharmacological tools in the future capable of preventing oxidative stress induced RPE cell death in human ocular diseases

    A connectome of the adult drosophila central brain

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    The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions. Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain

    A connectome and analysis of the adult Drosophila central brain

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    The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain

    A connectome and analysis of the adult Drosophila central brain

    Get PDF
    The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain

    Comparing Presenting Clinical Features in 48 Children With Microscopic Polyangiitis to 183 Children Who Have Granulomatosis With Polyangiitis (Wegener&apos;s) : an ARChiVe Cohort Study

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    OBJECTIVE: To uniquely classify children with microscopic polyangiitis (MPA), to describe their demographic characteristics, presenting clinical features, and initial treatments in comparison to patients with granulomatosis with polyangiitis (Wegener's) (GPA). METHODS: The European Medicines Agency (EMA) classification algorithm was applied by computation to categorical data from patients recruited to the ARChiVe (A Registry for Childhood Vasculitis: e-entry) cohort, with the data censored to November 2015. The EMA algorithm was used to uniquely distinguish children with MPA from children with GPA, whose diagnoses had been classified according to both adult- and pediatric-specific criteria. Descriptive statistics were used for comparisons. RESULTS: In total, 231 of 440 patients (64% female) fulfilled the classification criteria for either MPA (n\u2009=\u200948) or GPA (n\u2009=\u2009183). The median time to diagnosis was 1.6 months in the MPA group and 2.1 months in the GPA group (ranging to 39 and 73 months, respectively). Patients with MPA were significantly younger than those with GPA (median age 11 years versus 14 years). Constitutional features were equally common between the groups. In patients with MPA compared to those with GPA, pulmonary manifestations were less frequent (44% versus 74%) and less severe (primarily, hemorrhage, requirement for supplemental oxygen, and pulmonary failure). Renal pathologic features were frequently found in both groups (75% of patients with MPA versus 83% of patients with GPA) but tended toward greater severity in those with MPA (primarily, nephrotic-range proteinuria, requirement for dialysis, and end-stage renal disease). Airway/eye involvement was absent among patients with MPA, because these GPA-defining features preclude a diagnosis of MPA within the EMA algorithm. Similar proportions of patients with MPA and those with GPA received combination therapy with corticosteroids plus cyclophosphamide (69% and 78%, respectively) or both drugs in combination with plasmapheresis (19% and 22%, respectively). Other treatments administered, ranging in decreasing frequency from 13% to 3%, were rituximab, methotrexate, azathioprine, and mycophenolate mofetil. CONCLUSION: Younger age at disease onset and, perhaps, both gastrointestinal manifestations and more severe kidney disease seem to characterize the clinical profile in children with MPA compared to those with GPA. Delay in diagnosis suggests that recognition of these systemic vasculitides is suboptimal. Compared with adults, initial treatment regimens in children were comparable, but the complete reversal of female-to-male disease prevalence ratios is a provocative finding

    Identification of novel sarcoma risk genes using a two-stage genome wide DNA sequencing strategy in cancer cluster families and population case and control cohorts

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    Background Although familial clustering of cancers is relatively common, only a small proportion of familial cancer risk can be explained by known cancer predisposition genes. Methods In this study we employed a two-stage approach to identify candidate sarcoma risk genes. First, we conducted whole exome sequencing in three multigenerational cancer families ascertained through a sarcoma proband (n = 19) in order to prioritize candidate genes for validation in an independent case-control cohort of sarcoma patients using family-based association and segregation analysis. The second stage employed a burden analysis of rare variants within prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, for which whole genome sequence was available. Results Variants from eight genes were identified in stage one. Following gene-based burden testing and after correction for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significant association with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, p-value = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to have a significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared to sarcoma cases. Conclusions Based on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate risk genes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has been shown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatory elements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Future genetic studies in other family and population cohorts will be required for further validation of these novel findings
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