66 research outputs found

    Cosmological growth and feedback from supermassive black holes

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    We develop a simple evolutionary scenario for the growth of supermassive black holes (BHs), assuming growth due to accretion only, to learn about the evolution of the BH mass function from z=3z=3 to 0 and from it calculate the energy budgets of different modes of feedback. We tune the parameters of the model by matching the derived X-ray luminosity function (XLF) with the observed XLF of active galactic nuclei. We then calculate the amount of comoving kinetic and bolometric feedback as a function of redshift, derive a kinetic luminosity function and estimate the amount of kinetic feedback and PdVPdV work done by classical double Fanaroff-Riley II (FR II) radio sources. We also derive the radio luminosity function for FR IIs from our synthesized population and set constraints on jet duty cycles. Around 1/6 of the jet power from FR II sources goes into PdVPdV work done in the expanding lobes during the time the jet is on. Anti hierarchical growth of BHs is seen in our model due to addition of an amount of mass being accreted on to all BHs independent of the BH mass. The contribution to the total kinetic feedback by active galaxies in a low accretion, kinetically efficient mode is found to be the most significant at z<1.5z<1.5. FR II feedback is found to be a significant mode of feedback above redshifts z∌1.5z\sim 1.5, which has not been highlighted by previous studies.Comment: 11 pages, 10 figure

    The inverse-Compton ghost HDF 130 and the giant radio galaxy 6C 0905+3955: matching an analytic model for double radio source evolution

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    We present new GMRT observations of HDF 130, an inverse-Compton (IC) ghost of a giant radio source that is no longer being powered by jets. We compare the properties of HDF 130 with the new and important constraint of the upper limit of the radio flux density at 240 MHz to an analytic model. We learn what values of physical parameters in the model for the dynamics and evolution of the radio luminosity and X-ray luminosity (due to IC scattering of the cosmic microwave background (CMB)) of a Fanaroff-Riley II (FR II) source are able to describe a source with features (lobe length, axial ratio, X-ray luminosity, photon index and upper limit of radio luminosity) similar to the observations. HDF 130 is found to agree with the interpretation that it is an IC ghost of a powerful double-lobed radio source, and we are observing it at least a few Myr after jet activity (which lasted 5--100 Myr) has ceased. The minimum Lorentz factor of injected particles into the lobes from the hotspot is preferred to be ÎłâˆŒ103\gamma\sim10^3 for the model to describe the observed quantities well, assuming that the magnetic energy density, electron energy density, and lobe pressure at time of injection into the lobe are linked by constant factors according to a minimum energy argument, so that the minimum Lorentz factor is constrained by the lobe pressure. We also apply the model to match the features of 6C 0905+3955, a classical double FR II galaxy thought to have a low-energy cutoff of ÎłâˆŒ104\gamma\sim10^4 in the hotspot due to a lack of hotspot inverse-Compton X-ray emission. The models suggest that the low-energy cutoff in the hotspots of 6C 0905+3955 is γ≳103\gamma\gtrsim 10^3, just slightly above the particles required for X-ray emission.Comment: 9 pages, 3 figure

    Effect of sulfasalazine on human neuroblastoma: Analysis of sepiapterin reductase (SPR) as a new therapeutic target

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    Background: Neuroblastoma (NB) is an aggressive childhood malignancy in children up to 5 years of age. High-stage tumors frequently relapse even after aggressive multimodal treatment, and then show therapy resistance, typically resulting in patient death. New molecular-targeted compounds that effectively suppress tumor growth and prevent relapse with more efficacy are urgently needed. We and others previously showed that polyamines (PA) like spermidine and spermine are essential for NB tumorigenesis and that DFMO, an inhibitor of the key PA synthesis gene product ODC, is effective both in vitro and in vivo, securing its evaluation in NB clinical trials. To find additional compounds interfering with PA biosynthesis, we tested sulfasalazine (SSZ), an FDA-approved salicylate-based anti-inflammatory and immune-modulatory drug, recently identified to inhibit sepiapterin reductase (SPR). We earlier presented evidence for a physical interaction between ODC and SPR and we showed that RNAi-mediated knockdown of SPR expression significantly reduced native ODC enzyme activity and impeded NB cell proliferation. Methods: Human NB mRNA expression datasets in the public domain were analyzed using the R2 platform. Cell viability, isobologram, and combination index analyses as a result of SSZ treatment with our without DFMO were carried out in NB cell cultures. Molecular protein-ligand docking was achieved using the GRAMM algorithm. Statistical analyses were performed with the Kruskal-Wallis test, 2log Pearson test, and Student's t test. Results: In this study, we show the clinical relevance of SPR in human NB tumors. We found that high SPR expression is significantly correlated to unfavorable NB characteristics like high age at diagnosis, MYCN amplification, and high INSS stage. SSZ inhibits the growth of NB cells in vitro, presumably due to the inhibition of SPR as predicted by computational docking of SSZ into SPR. Importantly, the combination of SSZ with DFMO produces synergistic antiproliferative effects in vitro. Conclusions: The results suggest the use of SSZ in combination with DFMO for further experiments, and possible prioritization as a novel therapy for the treatment of NB patients

    Schrödinger-Poisson-Vlasov-Poisson correspondence

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    The Schr\"odinger-Poisson equations describe the behavior of a superfluid Bose-Einstein condensate under self-gravity with a 3D wave function. As ℏ/m→0\hbar/m\to 0, mm being the boson mass, the equations have been postulated to approximate the collisionless Vlasov-Poisson equations also known as the collisionless Boltzmann-Poisson equations. The latter describe collisionless matter with a 6D classical distribution function. We investigate the nature of this correspondence with a suite of numerical test problems in 1D, 2D, and 3D along with analytic treatments when possible. We demonstrate that, while the density field of the superfluid always shows order unity oscillations as ℏ/m→0\hbar/m\to 0 due to interference and the uncertainty principle, the potential field converges to the classical answer as (ℏ/m)2(\hbar/m)^{2}. Thus, any dynamics coupled to the superfluid potential is expected to recover the classical collisionless limit as ℏ/m→0\hbar/m\to 0. The quantum superfluid is able to capture rich phenomena such as multiple phase-sheets, shell-crossings, and warm distributions. Additionally, the quantum pressure tensor acts as a regularizer of caustics and singularities in classical solutions. This suggests the exciting prospect of using the Schr\"odinger-Poisson equations as a low-memory method for approximating the high-dimensional evolution of the Vlasov-Poisson equations. As a particular example we consider dark matter composed of ultra-light axions, which in the classical limit (ℏ/m→0\hbar/m\to 0) is expected to manifest itself as collisionless cold dark matter

    Simulating Turbulence Using the Astrophysical Discontinuous Galerkin Code TENET

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    In astrophysics, the two main methods traditionally in use for solving the Euler equations of ideal fluid dynamics are smoothed particle hydrodynamics and finite volume discretization on a stationary mesh. However, the goal to efficiently make use of future exascale machines with their ever higher degree of parallel concurrency motivates the search for more efficient and more accurate techniques for computing hydrodynamics. Discontinuous Galerkin (DG) methods represent a promising class of methods in this regard, as they can be straightforwardly extended to arbitrarily high order while requiring only small stencils. Especially for applications involving comparatively smooth problems, higher-order approaches promise significant gains in computational speed for reaching a desired target accuracy. Here, we introduce our new astrophysical DG code TENET designed for applications in cosmology, and discuss our first results for 3D simulations of subsonic turbulence. We show that our new DG implementation provides accurate results for subsonic turbulence, at considerably reduced computational cost compared with traditional finite volume methods. In particular, we find that DG needs about 1.8 times fewer degrees of freedom to achieve the same accuracy and at the same time is more than 1.5 times faster, confirming its substantial promise for astrophysical applications.Comment: 21 pages, 7 figures, to appear in Proceedings of the SPPEXA symposium, Lecture Notes in Computational Science and Engineering (LNCSE), Springe

    The Tully-Fisher Relation for 25,000 SDSS Galaxies as Function of Environment

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    We construct Tully-Fisher relationships (TFRs) in the uu, gg, rr, ii and zz bands and stellar mass TFRs (smTFRs) for a sample of 25,69825,698 late spiral type galaxies (with 0.045<z<0.0850.045<z<0.085) from the Sloan Digital Sky Survey (SDSS) and study the effects of environment on the relation. We use SDSS-measured Balmer emission line widths, vFWHMv_{\rm FWHM}, as a proxy for disc circular velocity, vcircv_{\rm circ}. A priori it is not clear whether we can construct accurate TFRs given the small 3"3" diameter of the fibres used for SDSS spectroscopic measurements. However, we show by modelling the Hα\alpha emission profile as observed through a 3"3" aperture that for galaxies at appropriate redshifts (z>0.045z>0.045) the fibres sample enough of the disc to obtain a linear relationship between vFWHMv_{\rm FWHM} and vcircv_{\rm circ}, allowing us to obtain a TFR and to investigate dependence on other variables. We also develop a methodology for distinguishing between astrophysical and sample bias in the fibre TFR trends. We observe the well-known steepening of the TFR in redder bands in our sample. We divide the sample of galaxies into four equal groups using projected neighbour density (Σ\Sigma) quartiles and find no significant dependence on environment, extending previous work to a wider range of environments and a much larger sample. Having demonstrated that we can construct SDSS-based TFRs is very useful for future applications because of the large sample size available.Comment: accepted for publication in MNRAS. 15 pages, 12 figure

    Direct observation shows superposition and large scale flexibility within cytoplasmic dynein motors moving along microtubules

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    Cytoplasmic dynein is a dimeric AAA+ motor protein that performs critical roles in eukaryotic cells by moving along microtubules using ATP. Here using cryo-electron microscopy we directly observe the structure of Dictyostelium discoideum dynein dimers on microtubules at near-physiological ATP concentrations. They display remarkable flexibility at a hinge close to the microtubule binding domain (the stalkhead) producing a wide range of head positions. About half the molecules have the two heads separated from one another, with both leading and trailing motors attached to the microtubule. The other half have the two heads and stalks closely superposed in a front-to-back arrangement of the AAA+ rings, suggesting specific contact between the heads. All stalks point towards the microtubule minus end. Mean stalk angles depend on the separation between their stalkheads, which allows estimation of inter-head tension. These findings provide a structural framework for understanding dynein’s directionality and unusual stepping behaviour

    Measuring the predictability of life outcomes with a scientific mass collaboration.

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    How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences
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