245 research outputs found

    Cryptic genetic subdivision in the San Benito evening primrose (Camissonia benitensis)

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    When rare plants are distributed across a range of habitats, ecotypic differentiation may arise requiring customized conservation measures. The rate of local adaptation may be accelerated in complex landscapes with numerous physical barriers to gene flow. In such cases, examining the distribution of genetic diversity is essential in determining conservation management units. We investigated the distribution of genetic diversity in the federally threatened Camissonia benitensis (Onagraceae), which grows in two distinct serpentine habitats across several watersheds in San Benito, Fresno, and Monterey Cos., CA, USA. We compared genetic diversity with that of its two widespread relatives, C. contorta and C. strigulosa, and examined the potential for hybridization with the latter species. Genotyping results using seven heterospecific microsatellite markers indicate that differentiation between habitat types was weak (F ST = 0.0433) and in an AMOVA analysis, there was no significant partitioning of molecular variation between habitats. Watersheds accounted for 11.6 % of the molecular variation (pairwise F ST = 0.1823–0.4275). Three cryptic genetic clusters were identified by InStruct and STRUCTURE that do not correlate with habitat or watershed. C. benitensis exhibits 5–11× higher inbreeding levels and 0.54× lower genetic diversity in comparison to its close relatives. We found no evidence of hybridization between C. benitensis and C. strigulosa. To maximize conservation of the limited amount of genetic diversity in C. benitensis, we recommend mixing seed representing the three cryptic genetic clusters across the species’ geographic range when establishing new populations

    Energy Efficient Scheduling Methods for Computational Grids and Clouds, Journal of Telecommunications and Information Technology, 2017, nr 1

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    This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage proles are presented together with energy efficiency measuring methods. Modeling of computing dynamics is discussed from the viewpoint of system identication theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimization are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally, energy-aware control mechanisms are presented. In addition, this paper introduces the example of batch scheduler based on ETC matrix approach

    Quantification of macrophage-driven inflammation during myocardial infarction with 18F-LW223, a novel TSPO radiotracer with binding independent of the rs6971 human polymorphism

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    Myocardial infarction (MI) is one of the leading causes of death worldwide, and inflammation is central to tissue response and patient outcomes. The 18-kDa translocator protein (TSPO) has been used in PET as an inflammatory biomarker. The aims of this study were to screen novel, fluorinated, TSPO radiotracers for susceptibility to the rs6971 genetic polymorphism using in vitro competition binding assays in human brain and heart; assess whether the in vivo characteristics of our lead radiotracer, 18F-LW223, are suitable for clinical translation; and validate whether 18F-LW223 can detect macrophage-driven inflammation in a rat MI model. Methods: Fifty-one human brain and 29 human heart tissue samples were screened for the rs6971 polymorphism. Competition binding assays were conducted with 3H-PK11195 and the following ligands: PK11195, PBR28, and our novel compounds (AB5186 and LW223). NaĂŻve rats and mice were used for in vivo PET kinetic studies, radiometabolite studies, and dosimetry experiments. Rats underwent permanent coronary artery ligation and were scanned using PET/CT with an invasive input function at 7 d after MI. For quantification of PET signal in the hypoperfused myocardium, K1 (rate constant for transfer from arterial plasma to tissues) was used as a surrogate marker of perfusion to correct the binding potential for impaired radiotracer transfer from plasma to tissue (BPTC). Results: LW223 binding to TSPO was not susceptible to the rs6971 genetic polymorphism in human brain and heart samples. In rodents, 18F-LW223 displayed a specific uptake consistent with TSPO expression, a slow metabolism in blood (69% of parent at 120 min), a high plasma free fraction of 38.5%, and a suitable dosimetry profile (effective dose of 20.5–24.5 ÎŒSv/MBq). 18F-LW223 BPTC was significantly higher in the MI cohort within the infarct territory of the anterior wall relative to the anterior wall of naĂŻve animals (32.7 ± 5.0 vs. 10.0 ± 2.4 cm3/mL/min, P ≀ 0.001). Ex vivo immunofluorescent staining for TSPO and CD68 (macrophage marker) resulted in the same pattern seen with in vivo BPTC analysis. Conclusion: 18F-LW223 is not susceptible to the rs6971 genetic polymorphism in in vitro assays, has favorable in vivo characteristics, and is able to accurately map macrophage-driven inflammation after MI

    The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

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    The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

    Seagrass restoration is possible: insights and lessons from Australia and New Zealand

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    Seagrasses are important marine ecosystems situated throughout the world's coastlines. They are facing declines around the world due to global and local threats such as rising ocean temperatures, coastal development and pollution from sewage outfalls and agriculture. Efforts have been made to reduce seagrass loss through reducing local and regional stressors, and through active restoration. Seagrass restoration is a rapidly maturing discipline, but improved restoration practices are needed to enhance the success of future programs. Major gaps in knowledge remain, however, prior research efforts have provided valuable insights into factors influencing the outcomes of restoration and there are now several examples of successful large-scale restoration programs. A variety of tools and techniques have recently been developed that will improve the efficiency, cost effectiveness, and scalability of restoration programs. This review describes several restoration successes in Australia and New Zealand, with a focus on emerging techniques for restoration, key considerations for future programs, and highlights the benefits of increased collaboration, Traditional Owner (First Nation) and stakeholder engagement. Combined, these lessons and emerging approaches show that seagrass restoration is possible, and efforts should be directed at upscaling seagrass restoration into the future. This is critical for the future conservation of this important ecosystem and the ecological and coastal communities they support

    A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples

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    The synthesis of this dataset was enabled by funding from the Canada Foundation for Innovation, from Genome Canada through Ontario Genomics, from NSERC, and from the Ontario Ministry of Research, Innovation and Science in support of the International Barcode of Life project. It was also enabled by philanthropic support from the Gordon and Betty Moore Foundation and from Ann McCain Evans and Chris Evans. The release of the data on GGBN was supported by a GGBN – Global Genome Initiative Award and we thank G. Droege, L. Loo, K. Barker, and J. Coddington for their support. Our work depended heavily on the analytical capabilities of the Barcode of Life Data Systems (BOLD, www.boldsystems.org). We also thank colleagues at the CBG for their support, including S. Adamowicz, S. Bateson, E. Berzitis, V. Breton, V. Campbell, A. Castillo, C. Christopoulos, J. Cossey, C. Gallant, J. Gleason, R. Gwiazdowski, M. Hajibabaei, R. Hanner, K. Hough, P. Janetta, A. Pawlowski, S. Pedersen, J. Robertson, D. Roes, K. Seidle, M. A. Smith, B. St. Jacques, A. Stoneham, J. Stahlhut, R. Tabone, J.Topan, S. Walker, and C. Wei. For bioblitz-related assistance, we are grateful to D. Ireland, D. Metsger, A. Guidotti, J. Quinn and other members of Bioblitz Canada and Ontario Bioblitz. For our work in Canada’s national parks, we thank S. Woodley and J. Waithaka for their lead role in organizing permits and for the many Parks Canada staff who facilitated specimen collections, including M. Allen, D. Amirault-Langlais, J. Bastick, C. Belanger, C. Bergman, J.-F. Bisaillon, S. Boyle, J. Bridgland, S. Butland, L. Cabrera, R. Chapman, J. Chisholm, B. Chruszcz, D. Crossland, H. Dempsey, N. Denommee, T. Dobbie, C. Drake, J. Feltham, A. Forshner, K. Forster, S. Frey, L. Gardiner, P. Giroux, T. Golumbia, D. Guedo, N. Guujaaw, S. Hairsine, E. Hansen, C. Harpur, S. Hayes, J. Hofman, S. Irwin, B. Johnston, V. Kafa, N. Kang, P. Langan, P. Lawn, M. Mahy, D. Masse, D. Mazerolle, C. McCarthy, I. McDonald, J. McIntosh, C. McKillop, V. Minelga, C. Ouimet, S. Parker, N. Perry, J. Piccin, A. Promaine, P. Roy, M. Savoie, D. Sigouin, P. Sinkins, R. Sissons, C. Smith, R. Smith, H. Stewart, G. Sundbo, D. Tate, R. Tompson, E. Tremblay, Y. Troutet, K. Tulk, J. Van Wieren, C. Vance, G. Walker, D. Whitaker, C. White, R. Wissink, C. Wong, and Y. Zharikov. For our work near Canada’s ports in Vancouver, Toronto, Montreal, and Halifax, we thank R. Worcester, A. Chreston, M. Larrivee, and T. Zemlak, respectively. Many other organizations improved coverage in the reference library by providing access to specimens – they included the Canadian National Collection of Insects, Arachnids and Nematodes, Smithsonian Institution’s National Museum of Natural History, the Canadian Museum of Nature, the University of Guelph Insect Collection, the Royal British Columbia Museum, the Royal Ontario Museum, the Pacifc Forestry Centre, the Northern Forestry Centre, the Lyman Entomological Museum, the Churchill Northern Studies Centre, and rare Charitable Research Reserve. We also thank the many taxonomic specialists who identifed specimens, including A. Borkent, B. Brown, M. Buck, C. Carr, T. Ekrem, J. Fernandez Triana, C. Guppy, K. Heller, J. Huber, L. Jacobus, J. Kjaerandsen, J. Klimaszewski, D. Lafontaine, J-F. Landry, G. Martin, A. Nicolai, D. Porco, H. Proctor, D. Quicke, J. Savage, B. C. Schmidt, M. Sharkey, A. Smith, E. Stur, A. Tomas, J. Webb, N. Woodley, and X. Zhou. We also thank K. Kerr and T. Mason for facilitating collections at Toronto Zoo and D. Iles for servicing the trap at Wapusk National Park. This paper contributes to the University of Guelph’s Food from Thought research program supported by the Canada First Research Excellence Fund. The Barcode of Life Data System (BOLD; www.boldsystems.org)8 was used as the primary workbench for creating, storing, analyzing, and validating the specimen and sequence records and the associated data resources48. The BOLD platform has a private, password-protected workbench for the steps from specimen data entry to data validation (see details in Data Records), and a public data portal for the release of data in various formats. The latter is accessible through an API (http://www.boldsystems.org/index.php/resources/api?type=webservices) that can also be controlled through R75 with the package ‘bold’76.Peer reviewedPublisher PD

    Seagrass restoration is possible:Insights and lessons from Australia and New Zealand

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    Seagrasses are important marine ecosystems situated throughout the world’s coastlines. They are facing declines around the world due to global and local threats such as rising ocean temperatures, coastal development and pollution from sewage outfalls and agriculture. Efforts have been made to reduce seagrass loss through reducing local and regional stressors, and through active restoration. Seagrass restoration is a rapidly maturing discipline, but improved restoration practices are needed to enhance the success of future programs. Major gaps in knowledge remain, however, prior research efforts have provided valuable insights into factors influencing the outcomes of restoration and there are now several examples of successful large-scale restoration programs. A variety of tools and techniques have recently been developed that will improve the efficiency, cost effectiveness, and scalability of restoration programs. This review describes several restoration successes in Australia and New Zealand, with a focus on emerging techniques for restoration, key considerations for future programs, and highlights the benefits of increased collaboration, Traditional Owner (First Nation) and stakeholder engagement. Combined, these lessons and emerging approaches show that seagrass restoration is possible, and efforts should be directed at upscaling seagrass restoration into the future. This is critical for the future conservation of this important ecosystem and the ecological and coastal communities they support

    Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition

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    A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009–2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world’s planktonic ecosystems
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