Genetically controlled environmental variance for sternopleural bristles in Drosophila melanogaster - an experimental test of a heterogeneous variance model

This is an Accepted Manuscript of an article published by Taylor & Francis in Acta Agriculturae Scandinavica Section A - Animal Science on2007, available online: http://doi.org/10.1080/09064700801959403[EN] objective of this study was to test the hypothesis that the environmental variance of sternopleural bristle number in Drosophila melanogaster is partly under genetic control. We used data from 20 inbred lines and 10 control lines to test this hypothesis. Two models were used: a standard quantitative genetics model based on the infinitesimal model, and an extension of this model. In the extended model it is assumed that each individual has its own environmental variance and that this heterogeneity of variance has a genetic component. The heterogeneous variance model was favoured by the data, indicating that the environmental variance is partly under genetic control. If this heterogeneous variance model also applies to livestock, it would be possible to select for animals with a higher uniformity of products across environmental regimes. Also for evolutionary biology the results are of interest as genes affecting the environmental variance may be important for adaptation to changing environmental conditions.Sørensen, AC.; Kristensen, TN.; Loeschcke, V.; Ibañez Escriche, N.; Sorensen, D. (2007). Genetically controlled environmental variance for sternopleural bristles in Drosophila melanogaster - an experimental test of a heterogeneous variance model. Acta Agriculturae Scandinavica Section A - Animal Science. 57(4):196-201. https://doi.org/10.1080/09064700801959403S19620157

Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1

Genome-wide approaches for identification of nuclear receptor target genes

Large-scale genomics analyses have grown by leaps and bounds with the rapid advances in high throughput DNA sequencing and synthesis techniques. Nuclear receptor signaling is ideally suited to genomics studies because receptors function as ligand-regulated gene switches. This review will survey the strengths and limitations of three major classes of high throughput techniques widely used in the nuclear receptor field to characterize ligand-dependent gene regulation: expression profiling studies (microarrays, SAGE and related techniques), chromatin immunoprecipitation followed by microarray (ChIP-on-chip), and genome-wide in silico hormone response element screens. We will discuss each technique, and how each has contributed to our understanding of nuclear receptor signaling

Origins and composition of fine atmospheric carbonaceous aerosol in the Sierra Nevada Mountains, California

In this paper we report chemically resolved measurements of organic aerosol (OA) and related tracers during the Biosphere Effects on Aerosols and Photochemistry Experiment (BEARPEX) at the Blodgett Forest Research Station, California from 15 August–10 October 2007. OA contributed the majority of the mass to the fine atmospheric particles and was predominately oxygenated (OOA). The highest concentrations of OA were during sporadic wildfire influence when aged plumes were impacting the site. In situ measurements of particle phase molecular markers were dominated by secondary compounds and along with gas phase compounds could be categorized into six factors or sources: (1) aged biomass burning emissions and oxidized urban emissions, (2) oxidized urban emissions (3) oxidation products of monoterpene emissions, (4) monoterpene emissions, (5) anthropogenic emissions and (6) local methyl chavicol emissions and oxidation products. There were multiple biogenic components that contributed to OA at this site whose contributions varied diurnally, seasonally and in response to changing meteorological conditions, e.g. temperature and precipitation events. Concentrations of isoprene oxidation products were larger when temperatures were higher during the first half of the campaign (15 August–12 September) due to more substantial emissions of isoprene and enhanced photochemistry. The oxidation of methyl chavicol, an oxygenated terpene emitted by ponderosa pine trees, contributed similarly to OA throughout the campaign. In contrast, the abundances of monoterpene oxidation products in the particle phase were greater during the cooler conditions in the latter half of the campaign (13 September–10 October), even though emissions of the precursors were lower, although the mechanism is not known. OA was correlated with the anthropogenic tracers 2-propyl nitrate and carbon monoxide (CO), consistent with previous observations, while being comprised of mostly non-fossil carbon (>75%). The correlation between OA and an anthropogenic tracer does not necessarily identify the source of the carbon as being anthropogenic but instead suggests a coupling between the anthropogenic and biogenic components in the air mass that might be related to the source of the oxidant and/or the aerosol sulfate. Observations of organosulfates of isoprene and α-pinene provided evidence for the likely importance of aerosol sulfate in spite of neutralized aerosol although acidic plumes might have played a role upwind of the site. This is in contrast to laboratory studies where strongly acidic seed aerosols were needed in order to form these compounds. These compounds together represented only a minor fraction (<1%) of the total OA mass, which may be the result of the neutralized aerosol at the site or because only a small number of organosulfates were quantified. The low contribution of organosulfates to total OA suggests that other mechanisms, e.g. NO_x enhancement of oxidant levels, are likely responsible for the majority of the anthropogenic enhancement of biogenic secondary organic aerosol observed at this site

Young Measures Generated by Ideal Incompressible Fluid Flows

In their seminal paper "Oscillations and concentrations in weak solutions of the incompressible fluid equations", R. DiPerna and A. Majda introduced the notion of measure-valued solution for the incompressible Euler equations in order to capture complex phenomena present in limits of approximate solutions, such as persistence of oscillation and development of concentrations. Furthermore, they gave several explicit examples exhibiting such phenomena. In this paper we show that any measure-valued solution can be generated by a sequence of exact weak solutions. In particular this gives rise to a very large, arguably too large, set of weak solutions of the incompressible Euler equations.Comment: 35 pages. Final revised version. To appear in Arch. Ration. Mech. Ana

Rigged Hilbert Space Approach to the Schrodinger Equation

It is shown that the natural framework for the solutions of any Schrodinger equation whose spectrum has a continuous part is the Rigged Hilbert Space rather than just the Hilbert space. The difficulties of using only the Hilbert space to handle unbounded Schrodinger Hamiltonians whose spectrum has a continuous part are disclosed. Those difficulties are overcome by using an appropriate Rigged Hilbert Space (RHS). The RHS is able to associate an eigenket to each energy in the spectrum of the Hamiltonian, regardless of whether the energy belongs to the discrete or to the continuous part of the spectrum. The collection of eigenkets corresponding to both discrete and continuous spectra forms a basis system that can be used to expand any physical wave function. Thus the RHS treats discrete energies (discrete spectrum) and scattering energies (continuous spectrum) on the same footing.Comment: 27 RevTex page

Restricted and unrestricted Hartree-Fock calculations of conductance for a quantum point contact

Very short quantum wires (quantum contacts) exhibit a conductance structure at a value of conductance close to $0.7 \times 2e^2/h$. It is believed that the structure arises due to the electron-electron interaction, and it is also related to electron spin. However details of the mechanism of the structure are not quite clear. Previously we approached the problem within the restricted Hartree-Fock approximation. This calculation demonstrated a structure similar to that observed experimentally. In the present work we perform restricted and unrestricted Hartree-Fock calculations to analyze the validity of the approximations. We also consider dependence of the effect on the electron density in leads. The unrestricted Hartree-Fock method allows us to analyze trapping of the single electron within the contact. Such trapping would result in the Kondo model for the ``0.7 structure''. The present calculation confirms the spin-dependent bound state picture and does not confirm the Kondo model scenario.Comment: 6 pages, 9 figure

Human Blood Lipoprotein Predictions from ¹H NMR Spectra:Protocol, Model Performances, and Cage of Covariance

Lipoprotein subfractions are biomarkers for the early diagnosis of cardiovascular diseases. The reference method, ultracentrifugation, for measuring lipoproteins is time-consuming, and there is a need to develop a rapid method for cohort screenings. This study presents partial least-squares regression models developed using 1H nuclear magnetic resonance (NMR) spectra and concentrations of lipoproteins as measured by ultracentrifugation on 316 healthy Danes. This study explores, for the first time, different regions of the 1H NMR spectrum representing signals of molecules in lipoprotein particles and different lipid species to develop parsimonious, reliable, and optimal prediction models. A total of 65 lipoprotein main and subfractions were predictable with high accuracy, Q2 of >0.6, using an optimal spectral region (1.4-0.6 ppm) containing methylene and methyl signals from lipids. The models were subsequently tested on an independent cohort of 290 healthy Swedes with predicted and reference values matching by up to 85-95%. In addition, an open software tool was developed to predict lipoproteins concentrations in human blood from standardized 1H NMR spectral recordings