13,397 research outputs found

    Structure of l,l-Diphenylarsenanium Bromide Monohydrate

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    The estrogenic activity of phthalate esters in vitro

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    A large number of phthalate esters were screened for estrogenic activity using a recombinant yeast screen. a selection of these was also tested for mitogenic effect on estrogen-responsive human breast cancer cells. A small number of the commercially available phthalates tested showed extremely weak estrogenic activity. The relative potencies of these descended in the order butyl benzyl phthalate (BBP) > dibutyl phthalate (DBP) > diisobutyl phthalate (DIBP) > diethyl phthalate (DEP) > diisiononyl phthalate (DINP). Potencies ranged from approximately 1 x 10(6) to 5 x 10(7) times less than 17beta-estradiol. The phthalates that were estrogenic in the yeast screen were also mitogenic on the human breast cancer cells. Di(2-ethylhexyl) phthalate (DEHP) showed no estrogenic activity in these in vitro assays. A number of metabolites were tested, including mono-butyl phthalate, mono-benzyl phthalate, mono-ethylhexyl phthalate, mon-n-octyl phthalate; all were wound to be inactive. One of the phthalates, ditridecyl phthalate (DTDP), produced inconsistent results; one sample was weakly estrogenic, whereas another, obtained from a different source, was inactive. analysis by gel chromatography-mass spectometry showed that the preparation exhibiting estrogenic activity contained 0.5% of the ortho-isomer of bisphenol A. It is likely that the presence of this antioxidant in the phthalate standard was responsible for the generation of a dose-response curve--which was not observed with an alternative sample that had not been supplemented with o,p'-bisphenol A--in the yeast screen; hence, DTDP is probably not weakly estrogenic. The activities of simple mixtures of BBP, DBP, and 17beta-estradiol were assessed in the yeast screen. No synergism was observed, although the activities of the mixtures were approximately additive. In summary, a small number of phthalates are weakly estrogenic in vitro. No data has yet been published on whether these are also estrogenic in vitro. No data has yet been published on whether these are also estrogenic in vivo; this will require tests using different classes of vertebrates and different routes of exposure

    Challenging the geographic bias in recognising large-scale patterns of diversity change

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    Aim: Geographic structure is a fundamental organising principle in ecological and Earth sciences, and our planet is conceptually divided into distinct geographic clusters (e.g. ecoregions and biomes) demarcating unique diversity patterns. Given recent advances in technology and data availability, however, we ask whether geographically clustering diversity time-series should be the default framework to identify meaningful patterns of diversity change. Location: North America. Taxon: Aves. Methods: We first propose a framework that recognises patterns of diversity change based on similarities in the behaviour of diversity time-series, independent of their specific or relative spatial locations. Specifically, we applied an artificial neural network approach, the self-organising map (SOM), to group time-series of over 0.9 million observations from the North American Breeding Birds Survey (BBS) data from 1973 to 2016. We then test whether time-series identified as having similar behaviour are geographically structured. Results: We find little evidence of strong geographic structure in patterns of diversity change for North American breeding birds. The majority of the recognised diversity time-series patterns tend to be indistinguishable from being independently distributed in space. Main Conclusions: Our results suggest that geographic proximity may not correspond to shared temporal trends in diversity; assuming that geographic clustering is the basis for analysis may bias diversity trend estimation. We suggest that approaches that consider variability independently of geographic structure can serve as a useful addition to existing organising rules of biodiversity time-series

    The influence of nonrandom extra-pair paternity on heritability estimates derived from wild pedigrees

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    Quantitative genetic analysis is often fundamental for understanding evolutionary processes in wild populations. Avian populations provide a model system due to the relative ease of inferring relatedness among individuals through observation. However, extra-pair paternity (EPP) creates erroneous links within the social pedigree. Previous work has suggested this causes minor underestimation of heritability if paternal misassignment is random and hence not influenced by the trait being studied. Nevertheless, much literature suggests numerous traits are associated with EPP and the accuracy of heritability estimates for such traits remains unexplored. We show analytically how nonrandom pedigree errors can influence heritability estimates. Then, combining empirical data from a large great tit (Parus major) pedigree with simulations, we assess how heritability estimates derived from social pedigrees change depending on the mode of the relationship between EPP and the focal trait. We show that the magnitude of the underestimation is typically small (<15%). Hence, our analyses suggest that quantitative genetic inference from pedigrees derived from observations of social relationships is relatively robust; our approach also provides a widely applicable method for assessing the consequences of nonrandom EPP

    Trajectories and Particle Creation and Annihilation in Quantum Field Theory

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    We develop a theory based on Bohmian mechanics in which particle world lines can begin and end. Such a theory provides a realist description of creation and annihilation events and thus a further step towards a "beable-based" formulation of quantum field theory, as opposed to the usual "observable-based" formulation which is plagued by the conceptual difficulties--like the measurement problem--of quantum mechanics.Comment: 11 pages LaTeX, no figures; v2: references added and update

    SDSS-RASS: Next Generation of Cluster-Finding Algorithms

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    We outline here the next generation of cluster-finding algorithms. We show how advances in Computer Science and Statistics have helped develop robust, fast algorithms for finding clusters of galaxies in large multi-dimensional astronomical databases like the Sloan Digital Sky Survey (SDSS). Specifically, this paper presents four new advances: (1) A new semi-parametric algorithm - nicknamed ``C4'' - for jointly finding clusters of galaxies in the SDSS and ROSAT All-Sky Survey databases; (2) The introduction of the False Discovery Rate into Astronomy; (3) The role of kernel shape in optimizing cluster detection; (4) A new determination of the X-ray Cluster Luminosity Function which has bearing on the existence of a ``deficit'' of high redshift, high luminosity clusters. This research is part of our ``Computational AstroStatistics'' collaboration (see Nichol et al. 2000) and the algorithms and techniques discussed herein will form part of the ``Virtual Observatory'' analysis toolkit.Comment: To appear in Proceedings of MPA/MPE/ESO Conference "Mining the Sky", July 31 - August 4, 2000, Garching, German

    The Mean and Scatter of the Velocity Dispersion-Optical Richness Relation for maxBCG Galaxy Clusters

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    The distribution of galaxies in position and velocity around the centers of galaxy clusters encodes important information about cluster mass and structure. Using the maxBCG galaxy cluster catalog identified from imaging data obtained in the Sloan Digital Sky Survey, we study the BCG-galaxy velocity correlation function. By modeling its non-Gaussianity, we measure the mean and scatter in velocity dispersion at fixed richness. The mean velocity dispersion increases from 202+/-10 km/s for small groups to more than 854+/-102 km/s for large clusters. We show the scatter to be at most 40.5+/-3.5%, declining to 14.9+/-9.4% in the richest bins. We test our methods in the C4 cluster catalog, a spectroscopic cluster catalog produced from the Sloan Digital Sky Survey DR2 spectroscopic sample, and in mock galaxy catalogs constructed from N-body simulations. Our methods are robust, measuring the scatter to well within one-sigma of the true value, and the mean to within 10%, in the mock catalogs. By convolving the scatter in velocity dispersion at fixed richness with the observed richness space density function, we measure the velocity dispersion function of the maxBCG galaxy clusters. Although velocity dispersion and richness do not form a true mass-observable relation, the relationship between velocity dispersion and mass is theoretically well characterized and has low scatter. Thus our results provide a key link between theory and observations up to the velocity bias between dark matter and galaxies.Comment: 25 pages, 15 figures, 2 tables, published in Ap
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