88 research outputs found

    4-(4-{[(2-Phenyl­quinazolin-4-yl)­oxy]methyl}-1H-1,2,3-triazol-1-yl)butan-1-ol hemihydrate

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    The title compound, C21H21N5O2·0.5H2O, has two fused six-membered rings linked to a benzene ring and to a triazole ring, which is connected to a butanol group. The quinazoline ring forms a dihedral angle of 7.88 (8)° with the benzene ring, while the triazole ring is approximately perpendicular to the benzene ring and to the quinazoline system, making dihedral angles of 84.38 (10) and 76.55 (8)°, respectively. The stereochemical arrangement of the butanol chain, with a C—C—C—C torsion angle of 178.34 (19)°, corresponds to an anti­periplanar conformation. However the position of the –OH group is split into two very close [O—O = 0.810(3) Å] positions of equal occupancy. The crystal structure features O—H⋯N and O—H⋯O hydrogen bonds, building an infinite three-dimensional network. The water molecule is located on a half-filled general position

    INHIBITIVE ACTION OF IMIDAZOLES FOR COPPER CORROSION IN SULFURIC ACID MEDIUM

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    The corrosion inhibition of copper in the presence of 10-3 M of imidazole derivatives; Imidazole (IM), 2-Methyle imidazole (MIM), Benzimidazole (BIM) has been investigated in 1.0 M H2SO4 solution using  potentiodynamic  polarization and electrochemical impedance spectroscopy (EIS). Relationship between molecular structure and their inhibition efficiency was elucidated by quantum chemical calculations using the density functional theory (DFT) at the B3LYP/6-31+G(d,p) level. Inhibition efficiency of these compounds which has been evaluated via experimental methods was accorded with reported theoretical ones, and following the same order as BIM Ă‹Æ’ MIM Ă‹Æ’ IM

    Ethnobotany Study of Medicinal Plants Used in the Treatment of Respiratory Diseases in the Middle Region of Oum Rbai

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    The ethnobotanical study carried out in the region of Oum Rbia (Morocco) made it possible to identify the medicinal plants used by the local population and to collect the maximum information on this use. A survey of 1360 people from the region's population noted that 170 people use medicinal plants against respiratory diseases. Women accounted for 55.3% of the workforce versus 44.7% for men; Married people 70% against 28% for singles. The illiteracy rate is high (34.1%). The leaves are the most widely used part of the plant. Infusion and decoction are the most commonly used methods for preparing traditional remedies. The most widely used species in the treatment of respiratory diseases are: Origanun glandulosum, Eucalyptus globulus, Nigella sativa, Mentha pulegium, Lavandula stoechas, Zingiber officinale, Ammodaucus leucotrichus, Ficus carica. In addition, some species have toxicity either because of the ignorance of the necessary dose or because the people treated are affected by other diseases. Thus, the survey made it possible to inventory 66 medicinal species which are divided into 36 plant families; Lamiaceae (21.2%), Myrtaceae (10.6%), Apiaceae (8.8%), Amaryllydaceae (7.7%) and Zingiberaceae (7.1%). These results resulted in a catalog of medicinal plants used in the study area to treat respiratory diseases. It is a local know-how that must be considered as a heritage to be preserved and developed

    4-{4-[(4-Oxoquinazolin-3-yl)meth­yl]-1H-1,2,3-triazol-1-yl}butyl acetate

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    In the heterocyclic title compound, C17H19N5O3, the quinazolinone ring system forms a dihedral angle of 67.22 (7)° with the triazole ring. The butyl acetate group has a non-linear conformation, with an alternation of synclinal and anti­periplanar torsion angles [N—C—C—C = 58.5 (2)°, C—C—C—C = 170.72 (19)° and C—C—C—O = −65.9 (3)°]. The crystal structure features inter­molecular C—H⋯N and C—H⋯O non-classical hydrogen bonds, building an infinite one-dimensional network along the [100] direction

    How Does Circadian Rhythm Impact Salt Sensitivity of Blood Pressure in Mice? A Study in Two Close C57Bl/6 Substrains

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    Background Mouse transgenesis has provided the unique opportunity to investigate mechanisms underlying sodium kidney reabsorption as well as end organ damage. However, understanding mouse background and the experimental conditions effects on phenotypic readouts of engineered mouse lines such as blood pressure presents a challenge. Despite the ability to generate high sodium and chloride plasma levels during high-salt diet, observed changes in blood pressure are not consistent between wild-type background strains and studies. Methods The present work was designed in an attempt to determine guidelines in the field of saltinduced hypertension by recording continuously blood pressure by telemetry in mice submitted to different sodium and potassium loaded diets and changing experimental conditions in both C57BL/6N and C57BL/6J mice strain (Normal salt vs. Low salt vs. High-salt/normal potassium vs. High salt/low potassium, standard vs. modified light cycle, Non-invasive tail cuff blood pressure vs. telemetry). Results In this study, we have shown that, despite a strong blood pressure (BP) basal difference between C57BL/6N and C57BL/6J mice, High salt/normal potassium diet increases BP and heart rate during the active phase only (dark period) in the same extent in both strains. On the other hand, while potassium level has no effect on salt-induced hypertension in C57BL/6N mice, high-salt/low potassium diet amplifies the effect of the high-salt challenge only in C57BL/6J mice. Indeed, in this condition, salt-induced hypertension can also be detected during light period even though this BP increase is lower compared to the one occurring during the dark period. Finally, from a methodological perspective, light cycle inversion has no effect on this circadian BP phenotype and tail-cuff method is less sensitive than telemetry to detect BP phenotypes due to salt challenges. Conclusions Therefore, to carry investigations on salt-induced hypertension in mice, chronic telemetry and studies in the active phase are essential prerequisites

    Predictive model of biliocystic communication in liver hydatid cysts using classification and regression tree analysis

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    <p>Abstract</p> <p>Background</p> <p>Incidence of liver hydatid cyst (LHC) rupture ranged 15%-40% of all cases and most of them concern the bile duct tree. Patients with biliocystic communication (BCC) had specific clinic and therapeutic aspect. The purpose of this study was to determine witch patients with LHC may develop BCC using classification and regression tree (CART) analysis</p> <p>Methods</p> <p>A retrospective study of 672 patients with liver hydatid cyst treated at the surgery department "A" at Ibn Sina University Hospital, Rabat Morocco. Four-teen risk factors for BCC occurrence were entered into CART analysis to build an algorithm that can predict at the best way the occurrence of BCC.</p> <p>Results</p> <p><b>I</b>ncidence of BCC was 24.5%. Subgroups with high risk were patients with jaundice and thick pericyst risk at 73.2% and patients with thick pericyst, with no jaundice 36.5 years and younger with no past history of LHC risk at 40.5%. Our developed CART model has sensitivity at 39.6%, specificity at 93.3%, positive predictive value at 65.6%, a negative predictive value at 82.6% and accuracy of good classification at 80.1%. Discriminating ability of the model was good 82%.</p> <p>Conclusion</p> <p>we developed a simple classification tool to identify LHC patients with high risk BCC during a routine clinic visit (only on clinical history and examination followed by an ultrasonography). Predictive factors were based on pericyst aspect, jaundice, age, past history of liver hydatidosis and morphological Gharbi cyst aspect. We think that this classification can be useful with efficacy to direct patients at appropriated medical struct's.</p

    TRY plant trait database – enhanced coverage and open access

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    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center

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    The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports &gt;500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate &gt;1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial &amp; Viral BRC

    A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa.

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    The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants

    TRY plant trait database – enhanced coverage and open access

    Get PDF
    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus KjĂžller, Tamir Klein, Michael Kleyer, Jitka KlimeĆĄovĂĄ, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf KĂŒhn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan LlusiĂ , Madelon Lohbeck, Álvaro LĂłpez-GarcĂ­a, Gabriela Lopez-Gonzalez, Zdeƈka LososovĂĄ, FrĂ©dĂ©rique Louault, BalĂĄzs A. LukĂĄcs, Petr LukeĆĄ, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki MĂ€kelĂ€, Harri MĂ€kinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina MartĂ­nez-Garza, Jordi MartĂ­nez-Vilalta, Tereza MaĆĄkovĂĄ, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, CĂ©line Meredieu, Julie Messier, Ilona MĂ©szĂĄros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila MolnĂĄr V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka MoravcovĂĄ, Alvaro Moreno-MartĂ­nez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina MĂŒller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis PĂ€rtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, ValĂ©rio D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr PyĆĄek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime RĂ©jou-MĂ©chain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja RĂŒger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-GarcĂ­a, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun SiebenkĂ€s, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, GrĂ©gory Sonnier, Mia Vedel SĂžrensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana SvitkovĂĄ, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, RubĂ©n Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, LubomĂ­r TichĂœ, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, PĂ©ter Török, Tonantzin Tarin, JosĂ© M. Torres-Ruiz, BĂ©la TĂłthmĂ©rĂ©sz, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim AndrĂ© Vanselow, Angelica VĂ„rhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime VillacĂ­s, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, KĂĄtia Janaina Zanini, Amy E. Zanne, David ZelenĂœ, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia ZiemiƄska, Chad R. Zirbel, Georg Zizka, IriĂ© Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et SociĂ©tĂ©'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc
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