84 research outputs found

    Summer and Winter Spatial Habitat Use by the Lake Erie Watersnake

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    In an effort to provide information to guide habitat management for the Lake Erie watersnake Nerodia sipedon insularum, a federally threatened and Ohio state endangered species, we used radiotelemetry to obtain spatial habitat data for adult snakes during the summer active season and during winter hibernation. During the summer active season, terrestrial habitat use was limited to a narrow band of shoreline. Among individuals, maximum distance inland from shore ranged from 1 to 50 m (mean = 8 m) and linear extent of shoreline ranged from 30 to 1,360 m (mean = 261 m). Winter hibernation occurred at varying distances inland with individual hibernation sites ranging from 1 to 580 m (mean = 29 m) from shore. Habitat use did not differ between males and females. Existing U.S. Fish and Wildlife Service habitat management guidelines suggest that ground-disturbing activities within potential hibernation areas (defined as terrestrial habitat within 161 m of shore) should be avoided in winter to prevent harm to hibernating snakes. They suggest further that excavation and removal of shrubs, standing or downed trees, root masses, animal burrows, piled rocks, cliffs, or bedrock within 21 m of shore should be avoided in summer to prevent harm to active snakes. Given that Lake Erie watersnakes have recovered to the point where delisting is being proposed, these habitat guidelines appear to be sufficient. However, maintaining voluntary compliance with habitat guidelines and meeting the need for continued public outreach will be vital to ensure long-term persistence

    Mid-infrared Selection of Active Galactic Nuclei with the Wide-Field Infrared Survey Explorer. I. Characterizing WISE-selected Active Galactic Nuclei in COSMOS

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    The Wide-field Infrared Survey Explorer (WISE) is an extremely capable and efficient black hole finder. We present a simple mid-infrared color criterion, W1 – W2 ≥ 0.8 (i.e., [3.4]–[4.6] ≥0.8, Vega), which identifies 61.9 ± 5.4 active galactic nucleus (AGN) candidates per deg^2 to a depth of W2 ~ 15.0. This implies a much larger census of luminous AGNs than found by typical wide-area surveys, attributable to the fact that mid-infrared selection identifies both unobscured (type 1) and obscured (type 2) AGNs. Optical and soft X-ray surveys alone are highly biased toward only unobscured AGNs, while this simple WISE selection likely identifies even heavily obscured, Compton-thick AGNs. Using deep, public data in the COSMOS field, we explore the properties of WISE-selected AGN candidates. At the mid-infrared depth considered, 160 μJy at 4.6 μm, this simple criterion identifies 78% of Spitzer mid-infrared AGN candidates according to the criteria of Stern et al. and the reliability is 95%. We explore the demographics, multiwavelength properties and redshift distribution of WISE-selected AGN candidates in the COSMOS field

    WISE Discovery of Low Metallicity Blue Compact Dwarf Galaxies

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    We report two new low metallicity blue compact dwarf galaxies (BCDs), WISEP J080103.93+264053.9 (hereafter W0801+26) and WISEP J170233.53+180306.4 (hereafter W1702+18), discovered using the Wide-field Infrared Survey Explorer (WISE). We identified these two BCDs from their extremely red colors at mid-infrared wavelengths, and obtained follow-up optical spectroscopy using the Low Resolution Imaging Spectrometer on Keck I. The mid-infrared properties of these two sources are similar to the well studied, extremely low metallicity galaxy SBS 0335-052E. We determine metallicities of 12 + log(O/H) = 7.75 and 7.63 for W0801+26 and W1702+18, respectively, placing them amongst a very small group of very metal deficient galaxies (Z 300 Angstrom Hbeta equivalent widths, similar to SBS 0335-052E, imply the existence of young (< 5 Myr) star forming regions. We measure star formation rates of 2.6 and 10.9 Msun/yr for W0801+26 and W1702+18, respectively. These BCDs, showing recent star formation activity in extremely low metallicity environments, provide new laboratories for studying star formation in extreme conditions and are low-redshift analogs of the first generation of galaxies to form in the universe. Using the all-sky WISE survey, we discuss a new method to identify similar star forming, low metallicity BCDs.Comment: Accepted for publication in ApJ

    Exercise training induces depot-specific adaptations to white and brown adipose tissue

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    Exercise affects whole-body metabolism through adaptations to various tissues, including adipose tissue (AT). Recent studies investigated exercise-induced adaptations to AT, focusing on inguinal white adipose tissue (WAT), perigonadal WAT, and interscapular brown adipose tissue (iBAT). Although these AT depots play important roles in metabolism, they account for only ∼50% of the AT mass in a mouse. Here, we investigated the effects of 3 weeks of exercise training on all 14 AT depots. Exercise induced depot-specific effects in genes involved in mitochondrial activity, glucose metabolism, and fatty acid uptake and oxidation in each adipose tissue (AT) depot. These data demonstrate that exercise training results in unique responses in each AT depot; identifying the depot-specific adaptations to AT in response to exercise is essential to determine how AT contributes to the overall beneficial effect of exercise11425439This work was supported by National Institutes of Health grants R01-HL138738 and K01-DK105109 (to K.I.S.), R01-DK099511 (to L.J.G.), and 5P30 DK36836 (Joslin Diabetes Center DRC). The authors thank Nathan Makarewicz for editorial contribution

    Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium

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    Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations

    A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci

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    Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM)

    Shared heritability and functional enrichment across six solid cancers

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    Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

    Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.

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    UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.The Breast Cancer Association Consortium (BCAC), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL), and the Ovarian Cancer Association Consortium (OCAC) that contributed breast, prostate, and ovarian cancer data analyzed in this study were in part funded by Cancer Research UK [C1287/A10118 and C1287/A12014 for BCAC; C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, and C16913/A6135 for PRACTICAL; and C490/A6187, C490/A10119, C490/A10124, C536/A13086, and C536/A6689 for OCAC]. Funding for the Collaborative Oncological Gene-environment Study (COGS) infrastructure came from: the European Community's Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the US National Institutes of Health (CA128978) and the Post-Cancer GWAS Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112), the US Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund [with donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07)]. Additional financial support for contributing studies is documented under Supplementary Financial Support.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/2159-8290.CD-15-122

    Shared heritability and functional enrichment across six solid cancers

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    Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis
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