Factores de riesgo y enfermedades cardiometabólicas en Risaralda 2017 proyectados a 2050

Objetivo: Proyectar el comportamiento de factores de riesgo y de la incidencia de dos enfermedades cardiometabólicas, en una población colombiana entre 2017 y 2050. Metodología: Diseño de cohorte abierta basado en un modelo de microsimulación dinámica para la población adulta de Risaralda, Colombia. Los factores de riesgo analizados son tabaquismo, obesidad global, obesidad central y colesterol total. Se creó una población sintética que replica las características demográficas y de salud de Risaralda en 2010, utilizando algoritmos de emparejamiento e imputación estadística. La evolución a lo largo del curso de vida se simuló basada en reglas derivadas de la literatura, con ecuaciones estocásticas y modelos econométricos. Se calcula la incidencia de diabetes tipo II y de eventos cerebrovasculares isquémicos de 2017 a 2050. Resultados: En 2050, 16.7 % serán fumadores, la tercera parte de ellos presentarán obesidad global y más de la mitad presentarán obesidad central. El promedio de colesterol total aumentará 5 mg/dL. Adicionalmente, se espera que entre 2017 y 2050 se presenten 204.966 casos nuevos de diabetes y 65.758 eventos cerebrovasculares isquémicos. Conclusiones: Los estilos de vida y el envejecimiento poblacional, llevarán a mayor exposición a riesgo y aumentarán la velocidad a la que los risaraldenses se enfermarán de Diabetes y experimentarán eventos cerebrovasculares. La obesidad global y central son factores que explicarían esta tendencia. Se requieren intervenciones intersectoriales que protejan a la población y reduzcan cargas fiscales por condiciones evitables

Factores de riesgo y enfermedades cardiometabólicas en Risaralda 2017 proyectados a 2050

Objetivo: Proyectar el comportamiento de factores de riesgo y de la incidencia de dos enfermedades cardiometabólicas, en una población colombiana entre 2017 y 2050. Metodología: Diseño de cohorte abierta basado en un modelo de microsimulación dinámica para la población adulta de Risaralda, Colombia. Los factores de riesgo analizados son tabaquismo, obesidad global, obesidad central y colesterol total. Se creó una población sintética que replica las características demográficas y de salud de Risaralda en 2010, utilizando algoritmos de emparejamiento e imputación estadística. La evolución a lo largo del curso de vida se simuló basada en reglas derivadas de la literatura, con ecuaciones estocásticas y modelos econométricos. Se calcula la incidencia de diabetes tipo II y de eventos cerebrovasculares isquémicos de 2017 a 2050. Resultados: En 2050, 16.7 % serán fumadores, la tercera parte de ellos presentarán obesidad global y más de la mitad presentarán obesidad central. El promedio de colesterol total aumentará 5 mg/dL. Adicionalmente, se espera que entre 2017 y 2050 se presenten 204.966 casos nuevos de diabetes y 65.758 eventos cerebrovasculares isquémicos. Conclusiones: Los estilos de vida y el envejecimiento poblacional, llevarán a mayor exposición a riesgo y aumentarán la velocidad a la que los risaraldenses se enfermarán de Diabetes y experimentarán eventos cerebrovasculares. La obesidad global y central son factores que explicarían esta tendencia. Se requieren intervenciones intersectoriales que protejan a la población y reduzcan cargas fiscales por condiciones evitables

Factores de riesgo y enfermedades cardiometabólicas en Risaralda 2017 proyectados a 2050

Objetivo: Proyectar el comportamiento de factores de riesgo y de la incidencia de dos enfermedades cardiometabólicas, en una población colombiana entre 2017 y 2050. Metodología: Diseño de cohorte abierta basado en un modelo de microsimulación dinámica para la población adulta de Risaralda, Colombia. Los factores de riesgo analizados son tabaquismo, obesidad global, obesidad central y colesterol total. Se creó una población sintética que replica las características demográficas y de salud de Risaralda en 2010, utilizando algoritmos de emparejamiento e imputación estadística. La evolución a lo largo del curso de vida se simuló basada en reglas derivadas de la literatura, con ecuaciones estocásticas y modelos econométricos. Se calcula la incidencia de diabetes tipo II y de eventos cerebrovasculares isquémicos de 2017 a 2050. Resultados: En 2050, 16.7 % serán fumadores, la tercera parte de ellos presentarán obesidad global y más de la mitad presentarán obesidad central. El promedio de colesterol total aumentará 5 mg/dL. Adicionalmente, se espera que entre 2017 y 2050 se presenten 204.966 casos nuevos de diabetes y 65.758 eventos cerebrovasculares isquémicos. Conclusiones: Los estilos de vida y el envejecimiento poblacional, llevarán a mayor exposición a riesgo y aumentarán la velocidad a la que los risaraldenses se enfermarán de Diabetes y experimentarán eventos cerebrovasculares. La obesidad global y central son factores que explicarían esta tendencia. Se requieren intervenciones intersectoriales que protejan a la población y reduzcan cargas fiscales por condiciones evitables

Brucella neotomae Infection in Humans, Costa Rica

Several species of Brucella are known to be zoonotic, but B. neotomae infection has been thought to be limited to wood rats. In 2008 and 2011, however, B. neotomae was isolated from cerebrospinal fluid of 2 men with neurobrucellosis. The nonzoonotic status of B. neotomae should be reassessed

Predictive Power of the "Trigger Tool" for the detection of adverse events in general surgery: a multicenter observational validation study

Background In spite of the global implementation of standardized surgical safety checklists and evidence-based practices, general surgery remains associated with a high residual risk of preventable perioperative complications and adverse events. This study was designed to validate the hypothesis that a new “Trigger Tool” represents a sensitive predictor of adverse events in general surgery. Methods An observational multicenter validation study was performed among 31 hospitals in Spain. The previously described “Trigger Tool” based on 40 specific triggers was applied to validate the predictive power of predicting adverse events in the perioperative care of surgical patients. A prediction model was used by means of a binary logistic regression analysis. Results The prevalence of adverse events among a total of 1,132 surgical cases included in this study was 31.53%. The “Trigger Tool” had a sensitivity and specificity of 86.27% and 79.55% respectively for predicting these adverse events. A total of 12 selected triggers of overall 40 triggers were identified for optimizing the predictive power of the “Trigger Tool”. Conclusions The “Trigger Tool” has a high predictive capacity for predicting adverse events in surgical procedures. We recommend a revision of the original 40 triggers to 12 selected triggers to optimize the predictive power of this tool, which will have to be validated in future studies

TRY plant trait database - enhanced coverage and open access

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

TRY plant trait database – enhanced coverage and open access

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 Kjøller, Tamir Klein, Michael Kleyer, Jitka Klimešová, 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 Kühn, 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 Llusià, Madelon Lohbeck, Álvaro López-García, Gabriela Lopez-Gonzalez, Zdeňka Lososová, Frédérique Louault, Balázs A. Lukács, Petr Lukeš, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki Mäkelä, Harri Mäkinen, 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 Martínez-Garza, Jordi Martínez-Vilalta, Tereza Mašková, 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, Céline Meredieu, Julie Messier, Ilona Mészáros, 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 Molnár V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka Moravcová, Alvaro Moreno-Martínez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina Müller, 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 Pärtel, 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, Valério 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 Pyšek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime Réjou-Méchain, 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 Rüger, 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-García, 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 Siebenkäs, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, Grégory Sonnier, Mia Vedel Sørensen, 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 Svitková, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, Rubén Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, Lubomír Tichý, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, Péter Török, Tonantzin Tarin, José M. Torres-Ruiz, Béla Tóthmérész, 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 André Vanselow, Angelica Vårhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime Villacís, 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, Kátia Janaina Zanini, Amy E. Zanne, David Zelený, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia Ziemińska, Chad R. Zirbel, Georg Zizka, Irié 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 Société'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

Factores de riesgo y enfermedades cardiometabólicas en Risaralda 2017 proyectados a 2050

Objective: predict the behavior of the risk factors and the incidence of two cardiometabolic diseases in a population from Colombia between 2017 and 2050. Methodology: Follow up of individual’s cohort of an artificial society of Risaralda, Colombia, based on a microsimulation model. The risk factors analyzed in this study are tobacco use, obesity, central obesity and total cholesterol. A synthetic population was created to replicate demographic and health characteristics of Risaralda in 2010, using pairing algorithms and statistical imputation. The evolution along the life course was simulated based on rules from scientific literature, with stochastic equations and econometric estimates. The incidence of type II diabetes and ischemic stroke is calculated for the adult population between 2017 to 2050. Results: 16.7% of the adults by 2050 is expected to be smokers, a third of them will have global obesity and more than half will have central obesity. The average level of serum total cholesterol would increase by 5 mg/dL. Additionally, is expected that between 2017 and 2050 there will be 204.966 incident cases of diabetes and 65.758 first-ever ischemic stroke events. Conclusions: Lifestyles and expected population aging will lead to greater risk of disease and will increase the rate at which local people will get diabetes and ischemic stroke. Risk factors like global and central obesity explain this trend. Effective intersectoral interventions are needed to protect the population and reduce tax burden due to preventable conditionsObjetivo: Proyectar el comportamiento de factores de riesgo y de la incidencia de dos enfermedades cardiometabólicas, en una población colombiana entre 2017 y 2050. Metodología: Diseño de cohorte abierta basado en un modelo de microsimulación dinámica para la población adulta de Risaralda, Colombia. Los factores de riesgo analizados son tabaquismo, obesidad global, obesidad central y colesterol total. Se creó una población sintética que replica las características demográficas y de salud de Risaralda en 2010, utilizando algoritmos de emparejamiento e imputación estadística. La evolución a lo largo del curso de vida se simuló basada en reglas derivadas de la literatura, con ecuaciones estocásticas y modelos econométricos. Se calcula la incidencia de diabetes tipo II y de eventos cerebrovasculares isquémicos de 2017 a 2050. Resultados: En 2050, 16.7 % serán fumadores, la tercera parte de ellos presentarán obesidad global y más de la mitad presentarán obesidad central. El promedio de colesterol total aumentará 5 mg/dL. Adicionalmente, se espera que entre 2017 y 2050 se presenten 204.966 casos nuevos de diabetes y 65.758 eventos cerebrovasculares isquémicos. Conclusiones: Los estilos de vida y el envejecimiento poblacional, llevarán a mayor exposición a riesgo y aumentarán la velocidad a la que los risaraldenses se enfermarán de Diabetes y experimentarán eventos cerebrovasculares. La obesidad global y central son factores que explicarían esta tendencia. Se requieren intervenciones intersectoriales que protejan a la población y reduzcan cargas fiscales por condiciones evitables

Insights into the genome of the De Donno strain of Xylella fastidiosa

Genetic studies showed that the genotype of the olive-infecting strain of X. fastidiosa (Xf- De Donno) belongs to the sequence type ST53 within subspecies pauca, already reported to occur in Costa Rica. The analysis of single nucleotide polymorphisms (SNPs) and the study of the pan-genome of 27 available whole genomes were performed to determine the phylogenetic placement of Xf-De Donno. Maximum-parsimony and maximum likelihood trees constructed using the SNPs and the pangenome data distinguished the subsp. fastidiosa, multiplex, pauca, sandyi, and morus and groups the Italian and three Costa Rican ST53 isolates in a compact clade that diverges from the South American pauca isolates. These findings were supported by the characterization of a conjugative plasmid shared by the four ST53 isolates and by the identification of a gene encoding a putative histidine kinase-like ATPase, which is not present in isolates from the subsp. multiplex, sandyi and pauca, but was detected in the four ST53 and ST21 isolates of the subspecies fastidiosa from Costa Rica. These data support the common and recent origin of the ST53 isolates. The complete and annotated genome sequence of the strain De Donno of X. fastidiosa was obtained by a combined Illumina and PacBio sequencing. This strain, recovered from an olive tree affected by Olive Quick Decline Syndrome (OQDS), when mechanically inoculated in different olive cultivars, caused symptoms identical to those observed in contaminated olive groves