2,438 research outputs found

    The Impact of Stellar Migration on Disk Outskirts

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    Stellar migration, whether due to trapping by transient spirals (churning), or to scattering by non-axisymmetric perturbations, has been proposed to explain the presence of stars in outer disks. After a review of the basic theory, we present compelling, but not yet conclusive, evidence that churning has been important in the outer disks of galaxies with type II (down-bending) profiles, while scattering has produced the outer disks of type III (up-bending) galaxies. In contrast, field galaxies with type I (pure exponential) profiles appear to not have experienced substantial migration. We conclude by suggesting work that would improve our understanding of the origin of outer disks.Comment: Invited review, Book chapter in "Outskirts of Galaxies", Eds. J. H. Knapen, J. C. Lee and A. Gil de Paz, Astrophysics and Space Science Library, Springer, in press 39 pages, 15 figure

    Analysis of surfactant-associated bacteria in the sea surface microlayer using deoxyribonucleic acid sequencing and synthetic aperture radar

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    The sea surface microlayer (SML) is the upper 1 mm of the ocean, where Earth’s biogeochemical processes occur between the ocean and atmosphere. It is physicochemically distinct from the water below and highly variable in space and time due to changing physical conditions. Some microorganisms influence the composition of the SML by producing surfactants for biological functions that accumulate on the surface, decrease surface tension, and create slicks. Slicks can be visible to the eye and in synthetic aperture radar (SAR) satellite imagery. This study focuses on surfactant-associated bacteria in the near-surface layer and their role in slick formation where oil is present

    The identification of informative genes from multiple datasets with increasing complexity

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    Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

    Simple Metals at High Pressure

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    In this lecture we review high-pressure phase transition sequences exhibited by simple elements, looking at the examples of the main group I, II, IV, V, and VI elements. General trends are established by analyzing the changes in coordination number on compression. Experimentally found phase transitions and crystal structures are discussed with a brief description of the present theoretical picture.Comment: 22 pages, 4 figures, lecture notes for the lecture given at the Erice course on High-Pressure Crystallography in June 2009, Sicily, Ital

    A dietary carbohydrate–gut Parasutterella–human fatty acid biosynthesis metabolic axis in obesity and type 2 diabetes

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    Recent rodent microbiome experiments suggest that besides Akkermansia, Parasutterella sp. are important in type 2 diabetes and obesity development. In the present translational human study, we aimed to characterize Parasutterella in our European cross-sectional FoCus cohort (n = 1,544) followed by validation of the major results in an independent Canadian cohort (n = 438). In addition, we examined Parasutterella abundance in response to a weight loss intervention (n = 55). Parasutterella was positively associated with BMI and type 2 diabetes independently of the reduced microbiome α/β diversity and low-grade inflammation commonly found in obesity. Nutritional analysis revealed a positive association with the dietary intake of carbohydrates but not with fat or protein consumption. Out of 126 serum metabolites differentially detectable by untargeted HPLC-based MS-metabolomics, L-cysteine showed the strongest reduction in subjects with high Parasutterella abundance. This is of interest, since Parasutterella is a known high L-cysteine consumer and L-cysteine is known to improve blood glucose levels in rodents. Furthermore, metabolic network enrichment analysis identified an association of high Parasutterella abundance with the activation of the human fatty acid biosynthesis pathway suggesting a mechanism for body weight gain. This is supported by a significant reduction of the Parasutterella abundance during our weight loss intervention. Together, these data indicate a role for Parasutterella in human type 2 diabetes and obesity, whereby the link to L-cysteine might be relevant in type 2 diabetes development and the link to the fatty acid biosynthesis pathway for body weight gain in response to a carbohydrate-rich diet in obesity development

    The Fueling and Evolution of AGN: Internal and External Triggers

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    In this chapter, I review the fueling and evolution of active galactic nuclei (AGN) under the influence of internal and external triggers, namely intrinsic properties of host galaxies (morphological or Hubble type, color, presence of bars and other non-axisymmetric features, etc) and external factors such as environment and interactions. The most daunting challenge in fueling AGN is arguably the angular momentum problem as even matter located at a radius of a few hundred pc must lose more than 99.99 % of its specific angular momentum before it is fit for consumption by a BH. I review mass accretion rates, angular momentum requirements, the effectiveness of different fueling mechanisms, and the growth and mass density of black BHs at different epochs. I discuss connections between the nuclear and larger-scale properties of AGN, both locally and at intermediate redshifts, outlining some recent results from the GEMS and GOODS HST surveys.Comment: Invited Review Chapter to appear in LNP Volume on "AGN Physics on All Scales", Chapter 6, in press. 40 pages, 12 figures. Typo in Eq 5 correcte

    Skin and soft tissue infections in hospitalized and critically ill patients: a nationwide population-based study

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    <p>Abstract</p> <p>Background</p> <p>The proportional distributions of various skin and soft tissue infections (SSTIs) with/without intensive care are unclear. Among SSTI patients, the prevalence and significance of complicating factors, such as comorbidities and infections other than skin/soft tissue (non-SST infections), remain poorly understood. We conducted this population-based study to characterize hospitalized SSTI patients with/without intensive care and to identify factors associated with patient outcome.</p> <p>Methods</p> <p>We analyzed first-episode SSTIs between January 1, 2005 and December 31, 2007 from the hospitalized claims data of a nationally representative sample of 1,000,000 people, about 5% of the population, enrolled in the Taiwan National Health Insurance program. We classified 18 groups of SSTIs into three major categories: 1) superficial; 2) deeper or healthcare-associated; and 3) gangrenous or necrotizing infections. Multivariate logistic regression models were applied to identify factors associated with intensive care unit (ICU) admission and hospital mortality.</p> <p>Results</p> <p>Of 146,686 patients ever hospitalized during the 3-year study period, we identified 11,390 (7.7%) patients having 12,030 SSTIs. Among these SSTI patients, 1,033 (9.1%) had ICU admission and 306 (2.7%) died at hospital discharge. The most common categories of SSTIs in ICU and non-ICU patients were "deeper or healthcare-associated" (62%) and "superficial" (60%) infections, respectively. Of all SSTI patients, 45.3% had comorbidities and 31.3% had non-SST infections. In the multivariate analyses adjusting for demographics and hospital levels, the presence of several comorbid conditions was associated with ICU admission or hospital mortality, but the results were inconsistent across most common SSTIs. In the same analyses, the presence of non-SST infections was consistently associated with increased risk of ICU admission (adjusted odds ratios [OR] 3.34, 95% confidence interval [CI] 2.91-3.83) and hospital mortality (adjusted OR 5.93, 95% CI 4.57-7.71).</p> <p>Conclusions</p> <p>The proportional distributions of various SSTIs differed between ICU and non-ICU patients. Nearly one-third of hospitalized SSTI patients had non-SST infections, and the presence of which predicted ICU admission and hospital mortality.</p

    Feasibility studies of time-like proton electromagnetic form factors at PANDA at FAIR

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    Simulation results for future measurements of electromagnetic proton form factors at \PANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is estimated. The signal channel pˉpe+e\bar p p \to e^+ e^- is studied on the basis of two different but consistent procedures. The suppression of the main background channel, i.e.\textit{i.e.} pˉpπ+π\bar p p \to \pi^+ \pi^-, is studied. Furthermore, the background versus signal efficiency, statistical and systematical uncertainties on the extracted proton form factors are evaluated using two different procedures. The results are consistent with those of a previous simulation study using an older, simplified framework. However, a slightly better precision is achieved in the PandaRoot study in a large range of momentum transfer, assuming the nominal beam conditions and detector performance
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