662 research outputs found

    Cito y genotoxicidad en eritrocitos de tortugas Trachemys sp sometidas a diferentes concentraciones de metil-mercurio

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    El metil mercurio (MeHg) es un contaminante ambiental tóxico y nocivo que se bioacumula y biomagnifica en la cadena trófica. La tortuga Trachemys scripta elegans (Tse), considerada centinela de contaminación ambiental debido a su longevidad, posee eritrocitos (RBCs) nucleados con afinidad del 90% por MeHg. Este estudio determinó la citotoxicidad y genotoxicidad in vitro del MeHg sobre RBCs de Tse a concentraciones de 0, 0,5, 0,7, 1, 10, 20, 50 y 100 mg/L-1 a las 24 y 96 h de exposición. Los RBCs se aislaron por centrifugación y se emplearon 1,69 x 106 RBCs por tratamiento. Se determinó el porcentaje de viabilidad, concentración letal media (CL50) y se verificaron cambios citológicos a las 24 y 96 h. El ADN fue extraído a las 96 h y se evaluó la genotoxicidad por marcadores RAPDs calculando el porcentaje de polimorfismo, índice de estabilidad genética (GST) y coeficiente de disimilaridad de Jaccard (dJSC). A las 96 h la viabilidad a 0,5, 0,7 y 1 mgL-1 de MeHg fue del 99% y 10, 20, 50 y 100 mgL-1 de MeHg fue de 94%, 20% y 0%. La CL50 determinada en 22,55 mgL-1 de MeHg. El análisis celular mostró en las diferentes concentraciones de MeHg, inclusiones citoplasmáticas, desvanecimiento o ruptura de membrana, núcleos excéntricos y lisis celular. El polimorfismo identificado fue del 85% y 50% y dJSC de 0,5 y 0,63 en 50 a 100 mgL-1 de MeHg comparado con el grupo control. La GST disminuyó hasta 42% a 100 mgL-1 de MeHg. Se concluye que el MeHg es citotóxico y genotóxico a concentraciones mayores de 10 mgL-1 en RBCs de Tse. Este estudio representa una línea base para estudios en toxicología por Hg en RBCs de Tse

    A Hydrophobic Gate in an Ion Channel: The Closed State of the Nicotinic Acetylcholine Receptor

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    The nicotinic acetylcholine receptor (nAChR) is the prototypic member of the `Cys-loop' superfamily of ligand-gated ion channels which mediate synaptic neurotransmission, and whose other members include receptors for glycine, gamma-aminobutyric acid, and serotonin. Cryo-electron microscopy has yielded a three dimensional structure of the nAChR in its closed state. However, the exact nature and location of the channel gate remains uncertain. Although the transmembrane pore is constricted close to its center, it is not completely occluded. Rather, the pore has a central hydrophobic zone of radius about 3 A. Model calculations suggest that such a constriction may form a hydrophobic gate, preventing movement of ions through a channel. We present a detailed and quantitative simulation study of the hydrophobic gating model of the nicotinic receptor, in order to fully evaluate this hypothesis. We demonstrate that the hydrophobic constriction of the nAChR pore indeed forms a closed gate. Potential of mean force (PMF) calculations reveal that the constriction presents a barrier of height ca. 10 kT to the permeation of sodium ions, placing an upper bound on the closed channel conductance of 0.3 pS. Thus, a 3 A radius hydrophobic pore can form a functional barrier to the permeation of a 1 A radius Na+ ion. Using a united atom force field for the protein instead of an all atom one retains the qualitative features but results in differing conductances, showing that the PMF is sensitive to the detailed molecular interactions.Comment: Accepted by Physical Biology; includes a supplement and a supplementary mpeg movie can be found at http://sbcb.bioch.ox.ac.uk/oliver/download/Movies/watergate.mp

    Transfer learning for galaxy morphology from one survey to another

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    © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of \sim5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy (\sim 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies (\sim500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

    COSMOGRAIL XVI: Time delays for the quadruply imaged quasar DES J0408-5354 with high-cadence photometric monitoring

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    We present time-delay measurements for the new quadruply imaged quasar DES J0408-5354, the first quadruply imaged quasar found in the Dark Energy Survey (DES). Our result is made possible by implementing a new observational strategy using almost daily observations with the MPIA 2.2m telescope at La Silla observatory and deep exposures reaching a signal-to-noise ratio of about 1000 per quasar image. This data quality allows us to catch small photometric variations (a few mmag rms) of the quasar, acting on temporal scales much shorter than microlensing, hence making the time delay measurement very robust against microlensing. In only 7 months we measure very accurately one of the time delays in DES J0408-5354: Dt(AB) = -112.1 +- 2.1 days (1.8%) using only the MPIA 2.2m data. In combination with data taken with the 1.2m Euler Swiss telescope, we also measure two delays involving the D component of the system Dt(AD) = -155.5 +- 12.8 days (8.2%) and Dt(BD) = -42.4 +- 17.6 days (41%), where all the error bars include systematics. Turning these time delays into cosmological constraints will require deep HST imaging or ground-based Adaptive Optics (AO), and information on the velocity field of the lensing galaxy.Comment: 9 pages, 5 figures, accepted for publication in Astronomy & Astrophysic

    Brown dwarf census with the Dark Energy Survey year 3 data and the thin disc scale height of early L types

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    27 pages, 18 figuresIn this paper we present a catalogue of 11 745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year 3 release matched to the Vista Hemisphere Survey (VHS) DR3 and Wide-field Infrared Survey Explorer (WISE) data, covering ≈2400 deg2 up to iAB = 22. The classification method follows the same phototype method previously applied to SDSS-UKIDSS-WISE data. The most significant difference comes from the use of DES data instead of SDSS, which allow us to classify almost an order of magnitude more brown dwarfs than any previous search and reaching distances beyond 400 pc for the earliest types. Next, we also present and validate the GalmodBD simulation, which produces brown dwarf number counts as a function of structural parameters with realistic photometric properties of a given survey. We use this simulation to estimate the completeness and purity of our photometric LT catalogue down to iAB = 22, as well as to compare to the observed number of LT types. We put constraints on the thin disc scale height for the early L (L0–L3) population to be around 450 pc, in agreement with previous findings. For completeness, we also publish in a separate table a catalogue of 20 863 M dwarfs that passed our colour cut with spectral types greater than M6. Both the LT and the late M catalogues are found at DES release page https://des.ncsa.illinois.edu/releases/other/y3-mlt.Peer reviewedFinal Published versio

    Chemical Abundance Analysis of Tucana III, the Second rr-process Enhanced Ultra-Faint Dwarf Galaxy

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    We present a chemical abundance analysis of four additional confirmed member stars of Tucana III, a Milky Way satellite galaxy candidate in the process of being tidally disrupted as it is accreted by the Galaxy. Two of these stars are centrally located in the core of the galaxy while the other two stars are located in the eastern and western tidal tails. The four stars have chemical abundance patterns consistent with the one previously studied star in Tucana III: they are moderately enhanced in rr-process elements, i.e. they have + \approx +0.4 dex. The non-neutron-capture elements generally follow trends seen in other dwarf galaxies, including a metallicity range of 0.44 dex and the expected trend in α\alpha-elements, i.e., the lower metallicity stars have higher Ca and Ti abundance. Overall, the chemical abundance patterns of these stars suggest that Tucana III was an ultra-faint dwarf galaxy, and not a globular cluster, before being tidally disturbed. As is the case for the one other galaxy dominated by rr-process enhanced stars, Reticulum II, Tucana III's stellar chemical abundances are consistent with pollution from ejecta produced by a binary neutron star merger, although a different rr-process element or dilution gas mass is required to explain the abundances in these two galaxies if a neutron star merger is the sole source of rr-process enhancement.Comment: 18 pages, 10 figures; accepted by Ap

    Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

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    Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σΔz=0.007\sigma_{\Delta z} = 0.007, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.Comment: 24 pages, 11 figures; matches version accepted to MNRA
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