Global gene expression profiling in human lung cells exposed to cobalt.

International audienceBACKGROUND: It has been estimated that more than 1 million workers in the United States are exposed to cobalt. Occupational exposure to 59 Co occurs mainly via inhalation and leads to various lung diseases. Cobalt is classified by the IARC as a possible human carcinogen (group 2B). Although there is evidence for in vivo and in vitro toxicity, the mechanisms of cobalt-induced lung toxicity are not fully known. The purpose of this work was to identify potential signatures of acute cobalt exposure using a toxicogenomic approach. Data analysis focused on some cellular processes and protein targets that are thought to be relevant for carcinogenesis, transport and biomarker research. RESULTS: A time course transcriptome analysis was performed on A549 human pulmonary cells, leading to the identification of 85 genes which are repressed or induced in response to soluble 59 Co. A group of 29 of these genes, representing the main biological functions, was assessed by quantitative RT-PCR. The expression profiles of six of them were then tested by quantitative RT-PCR in a time-dependent manner and three modulations were confirmed by Western blotting. The 85 modulated genes include potential cobalt carriers (FBXL2, ZNT1, SLC12A5), tumor suppressors or transcription factors (MAZ, DLG1, MYC, AXL) and genes linked to the stress response (UBC, HSPCB, BNIP3L). We also identified nine genes coding for secreted proteins as candidates for biomarker research. Of those, TIMP2 was found to be down-regulated and this modulation was confirmed, in a dose-dependent manner, at protein level in the supernatant of exposed cells. CONCLUSION: Most of these genes have never been described as related to cobalt stress and provide original hypotheses for further study of the effects of this metal ion on human lung epithelial cells. A putative biomarker of cobalt toxicity was identified

Chemical gradients in the Milky Way from the RAVE data: II. Giant stars

Aims. We provide new constraints on the chemo-dynamical models of the Milky Way by measuring the radial and vertical chemical gradients for the elements Mg, Al, Si, Ti, and Fe in the Galactic disc and the gradient variations as a function of the distanc

Improved distances and ages for stars common to TGAS and RAVE

ABSTRACT We combine parallaxes from the first Gaia data release with the spectrophotometric distance estimation framework for stars in the fifth RAVE survey data release. The combined distance estimates are more accurate than either determination in isolation – uncertainties are on average two times smaller than for RAVE-only distances (three times smaller for dwarfs), and 1.4 times smaller than TGAS parallax uncertainties (two times smaller for giants). We are also able to compare the estimates from spectrophotometry to those from Gaia, and use this to assess the reliability of both catalogues and improve our distance estimates.We find that the distances to the lowest log g stars are, on average, overestimated and caution that they may not be reliable. We also find that it is likely that the Gaia random uncertainties are smaller than the reported values. As a byproduct we derive ages for the RAVE stars, many with relative uncertainties less than 20 percent. These results for 219 566 RAVE sources have been made publicly available, and we encourage their use for studies that combine the radial velocities provided by RAVE with the proper motions provided by Gaia. A sample that we believe to be reliable can be found by taking only the stars with the flag notification ‘flag_any=0’. Key words: Galaxy: fundamental parameters – methods: statistical –Funding for the research in this study came from the Swedish National Space Board, the Royal Physiographic Society in Lund, and some of the computations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at Lunarc under project SNIC 2016/4-17. Funding for RAVE has been provided by: the Australian Astronomical Observatory; the Leibniz-Institut fuer Astrophysik Potsdam (AIP); the Australian National University; the Australian Research Council; the French National Research Agency; the German Research Foundation (SPP 1177 and SFB 881); the European Research Council (ERC-StG 240271 Galactica); the Istituto Nazionale di Astrofisica at Padova; The Johns Hopkins University; the National Science Foundation of the USA (AST-0908326); the W. M. Keck foundation; the Macquarie University; the Netherlands Research School for Astronomy; the Natural Sciences and Engineering Research Council of Canada; the Slovenian Research Agency (research core funding No. P1-0188); the Swiss National Science Foundation; the Science & Technology Facilities Council of the UK; Opticon; Strasbourg Observatory; and the Universities of Groningen, Heidelberg and Sydney. The RAVE web site is https://www.rave-survey.org. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC; https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement

From dwarf spheroidals to cDs: Simulating the galaxy population in a LCDM cosmology

We apply updated semi-analytic galaxy formation models simultaneously to the stored halo/subhalo merger trees of the Millennium and Millennium-II simulations. These differ by a factor of 125 in mass resolution, allowing explicit testing of resolution effects on predicted galaxy properties. We have revised the treatments of the transition between the rapid infall and cooling flow regimes of gas accretion, of the sizes of bulges and of gaseous and stellar disks, of supernova feedback, of the transition between central and satellite status as galaxies fall into larger systems, and of gas and star stripping once they become satellites. Plausible values of efficiency and scaling parameters yield an excellent fit not only to the observed abundance of low-redshift galaxies over 5 orders of magnitude in stellar mass and 9 magnitudes in luminosity, but also to the observed abundance of Milky Way satellites. This suggests that reionisation effects may not be needed to solve the "missing satellite" problem except, perhaps, for the faintest objects. The same model matches the observed large-scale clustering of galaxies as a function of stellar mass and colour. The fit remains excellent down to ~30kpc for massive galaxies. For M* < 6 x 10^10Msun, however, the model overpredicts clustering at scales below 1 Mpc, suggesting that the sigma_8 adopted in the simulations (0.9) is too high. Galaxy distributions within rich clusters agree between the simulations and match those observed, but only if galaxies without dark matter subhalos (so-called orphans) are included. Our model predicts a larger passive fraction among low-mass galaxies than is observed, as well as an overabundance of ~10^10Msun galaxies beyond z~0.6, reflecting deficiencies in the way star-formation rates are modelled.Comment: Accepted for publication in MNRAS. SQL databases containing the full galaxy data at all redshifts and for both the Millennium and Millennium-II simulations are publicly released at http://www.mpa-garching.mpg.de/millenniu

Evidence for association between the HLA-DQA locus and abdominal aortic aneurysms in the Belgian population: a case control study

BACKGROUND: Chronic inflammation and autoimmunity likely contribute to the pathogenesis of abdominal aortic aneurysms (AAAs). The aim of this study was to investigate the role of autoimmunity in the etiology of AAAs using a genetic association study approach with HLA polymorphisms. METHODS: HLA-DQA1, -DQB1, -DRB1 and -DRB3-5 alleles were determined in 387 AAA cases (180 Belgian and 207 Canadian) and 426 controls (269 Belgian and 157 Canadian) by a PCR and single-strand oligonucleotide probe hybridization assay. RESULTS: We observed a potential association with the HLA-DQA1 locus among Belgian males (empirical p = 0.027, asymptotic p = 0.071). Specifically, there was a significant difference in the HLA-DQA1*0102 allele frequencies between AAA cases (67/322 alleles, 20.8%) and controls (44/356 alleles, 12.4%) in Belgian males (empirical p = 0.019, asymptotic p = 0.003). In haplotype analyses, marginally significant association was found between AAA and haplotype HLA-DQA1-DRB1 (p = 0.049 with global score statistics and p = 0.002 with haplotype-specific score statistics). CONCLUSION: This study showed potential evidence that the HLA-DQA1 locus harbors a genetic risk factor for AAAs suggesting that autoimmunity plays a role in the pathogenesis of AAAs

The sixth data release of the Radial Velocity Experiment (RAVE). I. Survey description, spectra and radial velocities

The Radial Velocity Experiment (RAVE) is a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A). The 6th and final data release (DR6 or FDR) is based on 518387 observations of 451783 unique stars. RAVE observations were taken between 12 April 2003 and 4 April 2013. Here we present the genesis, setup and data reduction of RAVE as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in RAVE DR6. Furthermore, we present derived spectral classification and radial velocities for the RAVE targets, complemented by cross matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km/s, while 95% of the objects have radial velocities better than 4.0 km/s. Stellar atmospheric parameters, abundances and distances are presented in subsequent publication. The data can be accessed via the RAVE Web (http://rave-survey.org) or the Vizier database.Comment: 32 pages, 11 figures, accepted for publication to A

Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute to the development of ovarian cancer

The Gaia-ESO Public Spectroscopic Survey: Motivation, implementation, GIRAFFE data processing, analysis, and final data products

Context. The Gaia-ESO Public Spectroscopic Survey is an ambitious project designed to obtain astrophysical parameters and elemental abundances for 100 000 stars, including large representative samples of the stellar populations in the Galaxy, and a well-defined sample of 60 (plus 20 archive) open clusters. We provide internally consistent results calibrated on benchmark stars and star clusters, extending across a very wide range of abundances and ages. This provides a legacy data set of intrinsic value, and equally a large wide-ranging dataset that is of value for the homogenisation of other and future stellar surveys and Gaia's astrophysical parameters. Aims. This article provides an overview of the survey methodology, the scientific aims, and the implementation, including a description of the data processing for the GIRAFFE spectra. A companion paper introduces the survey results. Methods. Gaia-ESO aspires to quantify both random and systematic contributions to measurement uncertainties. Thus, all available spectroscopic analysis techniques are utilised, each spectrum being analysed by up to several different analysis pipelines, with considerable effort being made to homogenise and calibrate the resulting parameters. We describe here the sequence of activities up to delivery of processed data products to the ESO Science Archive Facility for open use. Results. The Gaia-ESO Survey obtained 202 000 spectra of 115 000 stars using 340 allocated VLT nights between December 2011 and January 2018 from GIRAFFE and UVES. Conclusions. The full consistently reduced final data set of spectra was released through the ESO Science Archive Facility in late 2020, with the full astrophysical parameters sets following in 2022. A companion article reviews the survey implementation, scientific highlights, the open cluster survey, and data products

The Gaia-ESO Public Spectroscopic Survey: Implementation, data products, open cluster survey, science, and legacy

Context. In the last 15 years different ground-based spectroscopic surveys have been started (and completed) with the general aim of delivering stellar parameters and elemental abundances for large samples of Galactic stars, complementing Gaia astrometry. Among those surveys, the Gaia-ESO Public Spectroscopic Survey, the only one performed on a 8m class telescope, was designed to target 100 000 stars using FLAMES on the ESO VLT (both Giraffe and UVES spectrographs), covering all the Milky Way populations, with a special focus on open star clusters. Aims. This article provides an overview of the survey implementation (observations, data quality, analysis and its success, data products, and releases), of the open cluster survey, of the science results and potential, and of the survey legacy. A companion article reviews the overall survey motivation, strategy, Giraffe pipeline data reduction, organisation, and workflow. Methods. We made use of the information recorded and archived in the observing blocks; during the observing runs; in a number of relevant documents; in the spectra and master catalogue of spectra; in the parameters delivered by the analysis nodes and the working groups; in the final catalogue; and in the science papers. Based on these sources, we critically analyse and discuss the output and products of the Survey, including science highlights. We also determined the average metallicities of the open clusters observed as science targets and of a sample of clusters whose spectra were retrieved from the ESO archive. Results. The Gaia-ESO Survey has determined homogeneous good-quality radial velocities and stellar parameters for a large fraction of its more than 110 000 unique target stars. Elemental abundances were derived for up to 31 elements for targets observed with UVES. Lithium abundances are delivered for about 1/3 of the sample. The analysis and homogenisation strategies have proven to be successful; several science topics have been addressed by the Gaia-ESO consortium and the community, with many highlight results achieved. Conclusions. The final catalogue will be released through the ESO archive in the first half of 2022, including the complete set of advanced data products. In addition to these results, the Gaia-ESO Survey will leave a very important legacy, for several aspects and for many years to come