University of Portsmouth

About: University of Portsmouth is a education organization based out in Portsmouth, Portsmouth, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 5452 authors who have published 14256 publications receiving 424346 citations. The organization is also known as: Portsmouth and Gosport School of Science and Art & Portsmouth and Gosport School of Science and the Arts.

Histone H3 lysine 4 methylation patterns in higher eukaryotic genes.

Abstract: Lysine residues within histones can be mono-, di - or tri-methylated. In Saccharomyces cerevisiae tri-methylation of Lys 4 of histone H3 (K4/H3) correlates with transcriptional activity, but little is known about this methylation state in higher eukaryotes. Here, we examine the K4/H3 methylation pattern at the promoter and transcribed region of metazoan genes. We analysed chicken genes that are developmentally regulated, constitutively active or inactive. We found that the pattern of K4/H3 methylation shows similarities to S. cerevisiae. Tri-methyl K4/H3 peaks in the 5' transcribed region and active genes can be discriminated by high levels of tri-methyl K4/H3 compared with inactive genes. However, our results also identify clear differences compared to yeast, as significant levels of K4/H3 methylation are present on inactive genes within the beta-globin locus, implicating this modification in maintaining a 'poised' chromatin state. In addition, K4/H3 di-methylation is not genome-wide and di-methylation is not uniformly distributed throughout the transcribed region. These results indicate that in metazoa, di- and tri-methylation of K4/H3 is linked to active transcription and that significant differences exist in the genome-wide methylation pattern as compared with S. cerevisiae.

Passive sampling techniques for monitoring pollutants in water

Abstract: We review the state of the art in using passive sampling technology for environmental monitoring of waterborne organic and inorganic pollutants. We discuss strategies for sampler design, calibration, in situ sampling and quality-control issues, and advantages and challenges associated with passive sampling in aqueous environments. We then review typical applications of passive samplers in assessing the aquatic environment.

European Association for Neuro-Oncology (EANO) guideline on the diagnosis and treatment of adult astrocytic and oligodendroglial gliomas

Abstract: The European Association for Neuro-Oncology guideline provides recommendations for the clinical care of adult patients with astrocytic and oligodendroglial gliomas, including glioblastomas. The guideline is based on the 2016 WHO classification of tumours of the central nervous system and on scientific developments since the 2014 guideline. The recommendations focus on pathological and radiological diagnostics, and the main treatment modalities of surgery, radiotherapy, and pharmacotherapy. In this guideline we have also integrated the results from contemporary clinical trials that have changed clinical practice. The guideline aims to provide guidance for diagnostic and management decisions, while limiting unnecessary treatments and costs. The recommendations are a resource for professionals involved in the management of patients with glioma, for patients and caregivers, and for health-care providers in Europe. The implementation of this guideline requires multidisciplinary structures of care, and defined processes of diagnosis and treatment.

A 6% measurement of the Hubble parameter at z∼0.45: direct evidence of the epoch of cosmic re-acceleration

Abstract: Deriving the expansion history of the Universe is a major goal of modern cosmology. To date, the most accurate measurements have been obtained with Type Ia Supernovae (SNe) and Baryon Acoustic Oscillations (BAO), providing evidence for the existence of a transition epoch at which the expansion rate changes from decelerated to accelerated. However, these results have been obtained within the framework of specific cosmological models that must be implicitly or explicitly assumed in the measurement. It is therefore crucial to obtain measurements of the accelerated expansion of the Universe independently of assumptions on cosmological models. Here we exploit the unprecedented statistics provided by the Baryon Oscillation Spectroscopic Survey (BOSS, [1-3]) Data Release 9 to provide new constraints on the Hubble parameter H(z) using the cosmic chronometers approach. We extract a sample of more than 130000 of the most massive and passively evolving galaxies, obtaining five new cosmology-independent H(z) measurements in the redshift range 0.3 < z < 0.5, with an accuracy of ~11–16% incorporating both statistical and systematic errors. Once combined, these measurements yield a 6% accuracy constraint of H(z = 0.4293) = 91.8 ± 5.3 km/s/Mpc. The new data are crucial to provide the first cosmology-independent determination of the transition redshift at high statistical significance, measuring zt = 0.4 ± 0.1, and to significantly disfavor the null hypothesis of no transition between decelerated and accelerated expansion at 99.9% confidence level. This analysis highlights the wide potential of the cosmic chronometers approach: it permits to derive constraints on the expansion history of the Universe with results competitive with standard probes, and most importantly, being the estimates independent of the cosmological model, it can constrain cosmologies beyond—and including—the ΛCDM model.

First-Year Sloan Digital Sky Survey-II Supernova Results: Hubble Diagram and Cosmological Parameters

Abstract: We present measurements of the Hubble diagram for 103 Type Ia supernovae (SNe) with redshifts 0.04 < z < 0.42, discovered during the first season (Fall 2005) of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. These data fill in the redshift "desert" between low- and high-redshift SN Ia surveys. Within the framework of the MLCS2K2 light-curve fitting method, we use the SDSS-II SN sample to infer the mean reddening parameter for host galaxies, RV = 2.18 ± 0.14stat ± 0.48syst, and find that the intrinsic distribution of host-galaxy extinction is well fitted by an exponential function, P(AV ) = exp(–AV /τV), with τV = 0.334 ± 0.088 mag. We combine the SDSS-II measurements with new distance estimates for published SN data from the ESSENCE survey, the Supernova Legacy Survey (SNLS), the Hubble Space Telescope (HST), and a compilation of Nearby SN Ia measurements. A new feature in our analysis is the use of detailed Monte Carlo simulations of all surveys to account for selection biases, including those from spectroscopic targeting. Combining the SN Hubble diagram with measurements of baryon acoustic oscillations from the SDSS Luminous Red Galaxy sample and with cosmic microwave background temperature anisotropy measurements from the Wilkinson Microwave Anisotropy Probe, we estimate the cosmological parameters w and ΩM, assuming a spatially flat cosmological model (FwCDM) with constant dark energy equation of state parameter, w. We also consider constraints upon ΩM and ΩΛ for a cosmological constant model (ΛCDM) with w = –1 and non-zero spatial curvature. For the FwCDM model and the combined sample of 288 SNe Ia, we find w = –0.76 ± 0.07(stat) ± 0.11(syst), ΩM = 0.307 ± 0.019(stat) ± 0.023(syst) using MLCS2K2 and w = –0.96 ± 0.06(stat) ± 0.12(syst), ΩM = 0.265 ± 0.016(stat) ± 0.025(syst) using the SALT-II fitter. We trace the discrepancy between these results to a difference in the rest-frame UV model combined with a different luminosity correction from color variations; these differences mostly affect the distance estimates for the SNLS and HST SNe. We present detailed discussions of systematic errors for both light-curve methods and find that they both show data-model discrepancies in rest-frame U band. For the SALT-II approach, we also see strong evidence for redshift-dependence of the color-luminosity parameter (β). Restricting the analysis to the 136 SNe Ia in the Nearby+SDSS-II samples, we find much better agreement between the two analysis methods but with larger uncertainties: w = –0.92 ± 0.13(stat)+0.10 –0.33(syst) for MLCS2K2 and w = –0.92 ± 0.11(stat)+0.07 –0.15 (syst) for SALT-II.