Adherencia al tratamiento con fármacos moduladores de la enfermedad sintéticos en la artritis reumatoide. Resultados del estudio OBSERVAR

[Abstract] Background: Treatment compliance with disease-modifying antirheumatic drugs (DMARD) is essential to achieve the therapeutic goals in rheumatoid arthritis (RA). However, despite the need for good compliance, there is evidence that patients with RA frequently fail to use DMARD for the control of RA. Thus, the main objective of the OBSERVAR study is to evaluate the reasons for the lack of therapeutic adherence to synthetic DMARD in these patients. Patients and methods: A Delphi process involving 18 randomly selected Spanish rheumatologists determined the level of agreement with 66 causes of noncompliance selected from the literature in relation to synthetic DMARD in RA. Results: The reasons for noncompliance were consistent in 75.7%, although 3 reasons (4.5%) were highly consistent: 1) not knowing what to do in the case of an adverse event with DMARD; 2) not having undergone adherence screening by health personnel for early detection of "noncompliant patients"; and 3) not having undergone interventions or strategies that improve adherence. Conclusion: In order to improve adherence to RA treatment with synthetic DMARD, the patient should be adequately informed of each new treatment introduced, the patient's compliance profile should be incorporated into the clinical routine and the patient's motivation for therapeutic compliance be reinforced through the methods available to us.[Resumen] Introducción. La cumplimentación del tratamiento modificador de la enfermedad es esencial para alcanzar los objetivos terapéuticos en la artritis reumatoide (AR). Sin embargo, y a pesar de la necesidad de una buena adherencia, existe evidencia de que muchos pacientes con AR no cumplen adecuadamente con la prescripción del tratamiento indicado con fármacos moduladores de la enfermedad de acción lenta (FAME) sintéticos o convencionales. Conscientes de la importancia de este hecho, el estudio sobre observancia terapéutica en AR (estudio OBSERVAR) tiene como objetivo principal valorar los motivos de la falta de adherencia terapéutica a los FAME sintéticos en estos pacientes. Pacientes y métodos. Mediante un proceso Delphi entre 18 reumatólogos españoles seleccionados aleatoriamente se determinó el grado de acuerdo con 66 causas de incumplimiento seleccionadas de la bibliografía, en relación con los FAME sintéticos en la AR. Resultados. Los motivos de incumplimiento fueron consistentes en el 75,7%, si bien 3 razones (4,5%) destacaron como muy consistentes: 1) desconocer qué hacer cuando se sufre un acontecimiento adverso con el FAME; 2) no llevar a cabo métodos de cribado de la adherencia por el personal sanitario para detectar a los «pacientes incumplidores» de forma temprana y 3) no aplicar intervenciones o estrategias que mejoren la adherencia terapéutica. Conclusión. Para mejorar la adherencia al tratamiento de la AR con FAME sintéticos se debe informar al paciente de cada tratamiento nuevo introducido, incorporar el perfil de cumplimiento del paciente en la rutina clínica, y reforzar la motivación del paciente al cumplimiento terapéutico mediante los métodos a nuestro alcance

Optimizing morphology through blood cell image analysis

Introduction Morphological review of the peripheral blood smear is still a crucial diagnostic aid as it provides relevant information related to the diagnosis and is important for selection of additional techniques. Nevertheless, the distinctive cytological characteristics of the blood cells are subjective and influenced by the reviewer's interpretation and, because of that, translating subjective morphological examination into objective parameters is a challenge. Methods The use of digital microscopy systems has been extended in the clinical laboratories. As automatic analyzers have some limitations for abnormal or neoplastic cell detection, it is interesting to identify quantitative features through digital image analysis for morphological characteristics of different cells. Result Three main classes of features are used as follows: geometric, color, and texture. Geometric parameters (nucleus/cytoplasmic ratio, cellular area, nucleus perimeter, cytoplasmic profile, RBC proximity, and others) are familiar to pathologists, as they are related to the visual cell patterns. Different color spaces can be used to investigate the rich amount of information that color may offer to describe abnormal lymphoid or blast cells. Texture is related to spatial patterns of color or intensities, which can be visually detected and quantitatively represented using statistical tools. Conclusion This study reviews current and new quantitative features, which can contribute to optimize morphology through blood cell digital image processing techniques.Peer ReviewedPostprint (published version

Mutation rate is reduced by increased dosage ofmutL gene in Escherichia coli K-12

This work was supported by the grants BIO2005-04278, LSHM-CT-2005-018705 and LSHM-CT-2005-518152.Peer reviewe

Mutation rate is reduced by increased dosage ofmutL gene in Escherichia coli K-12

This work was supported by the grants BIO2005-04278, LSHM-CT-2005-018705 and LSHM-CT-2005-518152.Peer reviewe

Logic training through algorithmic problem solving

Available for individual study only.Although much of mathematics is algorithmic in nature, the skills needed to formulate and solve algorithmic problems do not form an integral part of mathematics education. In particular, logic, which is central to algorithm development, is rarely taught explicitly at preuniversity level, under the justification that it is implicit in mathematics and therefore does not need to be taught as an independent topic. This paper argues in the opposite direction, describing a one-week workshop done at the University of Minho, in Portugal, whose goal was to introduce to high-school students calculational principles and techniques of algorithmic problem solving supported by calculational logic. The workshop resorted to recreational problems to convey the principles and to software tools, the Alloy Analyzer and Netlogo, to animate models.On- going collaboration with Roland Backhouse is deeply acknowledged. This research was supported by the MathIS project under contract PTDC/ EIA/ 73252/ 2006. The first two authors were further supported by FCT grants SFRH/ BD/ 24269/ 2005 and SFRH/ BD/ 29553/ 2006, respectively

Valoración de las condiciones actuales de los suelos dedicados a cultivos intensivos y ajuste de recomendaciones de manejo sostenible en la región inundable del municipio de Arauca : informe final

Los suelos dedicados al cultivo de arroz, en el municipio de Arauca cuyo sistema es conocido también como de secano favorecido o de inundación natural, se localiza en los valles aluviales recientes denominados vegas o vegones de fertilidad moderada a alta con baja o nula presencia de aluminio intercambiable. También incluye aquellas áreas en donde puede establecerse oportunamente antes del proceso de inundación natural.‎‎Corporación colombiana de investigación agropecuaria - AGROSAVIAArroz-Oryza sativ

A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES)

In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysisThis work has also been supported by grants BFU2012-39816-C02-01 (co-financed by FEDER funds and the Ministry of Economy and Competitiveness, Spain) to AL and Prometeo/2009/092 (Ministry of Education, Government of Valencia, Spain) and Explora Ciencia y Explora Tecnologia/SAF2013-49788-EXP (Spanish Ministry of Economy and Competitiveness) to AM. IRF is recipient of a "Sara Borrell" postdoctoral fellowship (Ref. CD12/00492) from the Ministry of Economy and Competitiveness (Spain). We are also grateful to the Spanish Network for the Study of Plasmids and Extrachromosomal Elements (REDEEX) for encouraging and funding cooperation among Spanish microbiologists working on the biology of mobile genetic elements (Spanish Ministry of Science and Innovation, reference number BFU2011-14145-E).Campos Frances, M.; Llorens, C.; Sempere Luna, JM.; Futami, R.; Rodríguez, I.; Carrasco, P.; Capilla, R.... (2015). A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES). Biology Direct. 10(41):1-13. https://doi.org/10.1186/s13062-015-0070-9S1131041Baquero F, Coque TM, Canton R. Counteracting antibiotic resistance: breaking barriers among antibacterial strategies. Expert Opin Ther Targets. 2014;18:851–61.Baquero F, Lanza VF, Canton R, Coque TM. Public health evolutionary biology of antimicrobial resistance: priorities for intervention. Evol Appl. 2014;8:223–39.Baquero F, Coque TM, de la Cruz F. Ecology and evolution as targets: the need for novel eco-evo drugs and strategies to fight antibiotic resistance. Antimicrob Agents Chemother. 2011;55:3649–60.Carlet J, Jarlier V, Harbarth S, Voss A, Goossens H, Pittet D, et al. Ready for a world without antibiotics? The pensieres antibiotic resistance call to action. Antimicrob Resist Infect Control. 2012;1:11.Laxminarayan R, Duse A, Wattal C, Zaidi AK, Wertheim HF, Sumpradit N, et al. Antibiotic resistance-the need for global solutions. Lancet Infect Dis. 2013;13:1057–98.G8-Science-Ministers-Statement. 2013. https://www.gov.uk/government/news/g8-science-ministers-statement .Levy SB, Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med. 2004;10:S122–9.Wellington EM, Boxall AB, Cross P, Feil EJ, Gaze WH, Hawkey PM, et al. The role of the natural environment in the emergence of antibiotic resistance in gram-negative bacteria. Lancet Infect Dis. 2013;13:155–65.Marshall BM, Levy SB. Food animals and antimicrobials: impacts on human health. Clin Microbiol Rev. 2011;24:718–33.Marshall BM, Ochieng DJ, Levy SB. Commensals: underappreciated reservoir of antibiotic resistance. Microbe. 2009;4:231–8.Forsberg KJ, Reyes A, Wang B, Selleck EM, Sommer MO, Dantas G. The shared antibiotic resistome of soil bacteria and human pathogens. Science. 2012;337:1107–11.Heuer H, Schmitt H, Smalla K. Antibiotic resistance gene spread due to manure application on agricultural fields. Curr Opin Microbiol. 2011;14:236–43.Teillant A, Laxminarayan R. Economics of Antibiotic Use in U.S. Swine and Poultry Production. Choices. 2015;30:1. 1st Quarter 2015.ANTIBIOTIC RESISTANCE THREATS in the United States. http://www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013-508.pdf .Gillings MR. Evolutionary consequences of antibiotic use for the resistome, mobilome and microbial pangenome. Front Microbiol. 2013;4:4.Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev. 2010;74:417–33.Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nat Rev Genet. 2013;14:243–8.Baquero F, Tedim AP, Coque TM. Antibiotic resistance shaping multi-level population biology of bacteria. Front Microbiol. 2013;4:15.Partridge SR. Analysis of antibiotic resistance regions in Gram-negative bacteria. FEMS Microbiol Rev. 2011;35:820–55.Baquero F, Coque TM. Multilevel population genetics in antibiotic resistance. FEMS Microbiol Rev. 2011;35:705–6.Martinez JL, Baquero F, Andersson DI. Predicting antibiotic resistance. Nat Rev Microbiol. 2007;5:958–65.Martinez JL, Baquero F. Emergence and spread of antibiotic resistance: setting a parameter space. Upsala Journal of Medical Sciences. Upsala J Med Sci. 2014, Early Online: 1–10, doi: 10.3109/03009734.2014.901444 ).Baquero F, Nombela C. The microbiome as a human organ. Clin Microbiol Infect. 2012;18 Suppl 4:2–4.Kumsa B, Socolovschi C, Parola P, Rolain JM, Raoult D. Molecular detection of Acinetobacter species in lice and keds of domestic animals in Oromia Regional State. Ethiopia PLoS One. 2012;7:e52377.Ahmad A, Ghosh A, Schal C, Zurek L. Insects in confined swine operations carry a large antibiotic resistant and potentially virulent enterococcal community. BMC Microbiol. 2011;11:23.Graczyk TK, Knight R, Gilman RH, Cranfield MR. The role of non-biting flies in the epidemiology of human infectious diseases. Microbes Infect. 2001;3:231–5.Limoee M, Enayati AA, Khassi K, Salimi M, Ladonni H. Insecticide resistance and synergism of three field-collected strains of the German cockroach Blattella germanica (L.) (Dictyoptera: Blattellidae) from hospitals in Kermanshah, Iran. Trop Biomed. 2011;28:111–8.Salehzadeha A, Tavacolb P, Mahjubc H. Bacterial, fungal and parasitic contamination of cockroaches in public hospitals of Hamadan, Iran. J Vect Borne Dis. 2007;44:105–10.Akinjogunla OJ, Odeyemi AT, Udoinyang EP. Cockroaches (periplaneta americana and blattella germanica): reservoirs of multi drug resistant (MDR) bacteria in Uyo, Akwa Ibom State. Scientific J Biol Sci. 2012;1:19–30.Mideo N, Alizon S, Day T. Linking within- and between-host dynamics in the evolutionary epidemiology of infectious diseases. Trends Ecol Evol. 2008;23:511–7.Gillings MR, Stokes HW. Are humans increasing bacterial evolvability? Trends EcolEvol. 2012;27:346–52.Baquero F. Environmental stress and evolvability in microbial systems. Clin Microbiol Infect. 2009;15 Suppl 1:5–10.Paun G, Rozemberg G, Salomaa A. The Oxford Handbook of Membrane Computing. Oxford, London. Oxford University Press. 2010.Paun G. Membrane Computing. An Introduction. Berlin, Heidelberg. Springer-Verlag GmbH. 2002.Paun G. Computing with membranes. J Comput Syst Sci. 2000;61:108–43.Fontana F, Biancom L, Manca V. P systems and the modeling of biochemical oscillations. Lect Notes Comput Sci. 2006;3850:199–208.Cheruku S, Paun A, Romero-Campero FJ, Perez-Jimenez MJ, Ibarra OH. Simulating FAS-induced apoptosis by using P systems. Prog Nat Sci. 2007;4:424–31.Perez-Jimenez MJ, Romero-Campero FJ. P systems, a new computational modelling tool for systems biology. Transactions on computational systems. Lect N Bioinformat. 2006;Biology VI:176–97.Romero-Campero FJ, Perez-Jimenez MJ. Modelling gene expression control using P systems: The Lac Operon, a case study. Biosystems. 2008;91:438–57.Romero-Campero FJ, Perez-Jimenez MJ. A model of the quorum sensing system in Vibrio fischeri using P systems. Artif Life. 2008;14:95–109.Besozzi D, Cazzaniga P, Pescini D, Mauri G. Modelling metapopulations with stochastic membrane systems. Biosystems. 2008;91:499–514.Cardona M, Colomer MA, Perez-Jimenez MJ, Sanuy D, Margalida A. Modelling ecosystems using P Systems: The Bearded Vulture, a case of study. Lect Notes Comput Sci. 2009;5391:137–56.Cardona M, Colomer MA, Margalida A, Perez-Hurtado I, Perez-Jimenez MJ, Sanuy D. A P system based model of an ecosystem of some scavenger birds. Lect Notes Comput Sci. 2010;5957:182–95.Frisco P, Gheorghe M, Perez-Jimenez M. Applications of Membrane Computing in Systems and Synthetic biology. Cham. Springer International Publishing. 2014.Membrane Computing Community. http://ppage.psystems.eu .P-Lingua. http://www.p-lingua.org/wiki/index.php/Main_Page .Llorens C, Futami R, Covelli L, Dominguez-Escriba L, Viu JM, Tamarit D, et al. The Gypsy Database (GyDB) of mobile genetic elements: release 2.0. Nucleic Acids Res. 2011;39:D70–4.Baquero F. From pieces to patterns: evolutionary engineering in bacterial pathogens. Nat Rev Microbiol. 2004;2:510–8.Java. http://www.java.com .Garcia-Quismondo M, Gutierrez-Escudero R, Martinez-del-Amor MA, Orejuela-Pinedo E, Pérez-Hurtado I. P-Lingua 2.0: a software framework for cell-like P systems. Int J Comput Commun. 2009;IV:234.R programming language. http://www.r-project.org .Maciel A, Sankaranarayanan G, Halic T, Arikatla VS, Lu Z, De S. Surgical model-view-controller simulation software framework for local and collaborative applications. Int J Comput Assist Radiol Surg. 2011;6:457–71.Dethlefsen L, McFall-Ngai M, Relman DA. An ecological and evolutionary perspective on human-microbe mutualism and disease. Nature. 2007;449:811–8.Ley RE, Lozupone CA, Hamady M, Knight R, Gordon JI. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat Rev Microbiol. 2008;6:776–88.Pallen MJ, Wren BW. Bacterial pathogenomics. Nature. 2007;449:835–42.Carrasco P, Perez-Cobas AE, Van de Pol C, Baixeras J, Moya A, Latorre A. Succession of the gut microbiota in the cockroach Blattella germanica. Int Microbiol. 2014;17:99–109

Escherichia coli and Staphylococcus aureus: bad news and good news from the European Antimicrobial Resistance Surveillance Network (EARS-Net), formerly EARSS), 2002 to 2009

Based on data collected by the European Antimicrobial Resistance Surveillance Network (EARS-Net) and the former EARSS, the present study describes the trends in antimicrobial susceptibility patterns and occurrence of invasive infections caused by Escherichia coli and Staphylococcus aureus in the period from 2002 to 2009. Antimicrobial susceptibility results from 198 laboratories in 22 European countries reporting continuously on these two microorganisms during the entire study period were included in the analysis. The number of bloodstream infections caused by E. coli increased remarkably by 71% during the study period, while bloodstream infections caused by S. aureus increased by 34%. At the same time, an alarming increase of antimicrobial resistance in E. coli was observed, whereas for S. aureus the proportion of meticillin resistant isolates decreased. The observed trend suggests an increasing burden of disease caused by E. coli. The reduction in the proportion of meticillin-resistant S. aureus and the lesser increase in S. aureus infections, compared with E. coli, may reflect the success of infection control measures at hospital level in several European countries.</p

II Jornadas de la Sociedad Española para la Conservación y Estudio de Los Mamíferos (SECEM) Soria 7-9 diciembre 1995

Seguimiento de una reintroducción de corzo (Capreolus capreolus) en ambiente mediterráneo. Dispersión y área de campeoModelos de distribución de los insectívoros ern la Península IbéricaDieta anual del zorro, Vulpes vulpes, en dos hábitats del Parque Nacional de DoñanaDesarrollo juvenil del cráneo en las poblaciones ibéricas de gato montés, Felis silvestris Schreber, 1777Presencia y expansión del visón americano (Mustela vison) en las provincias de Teruel y Castellón (Este de España).Preferencias de hábitat invernal de la musaraña común (Crocidura russula) en un encinar fragmentado de la submeseta norteUso de cámaras automáticas para la recogida de información faunística.Dieta del lobo en dos zonas de Asturias (España) que difieren en carga ganadera.Consumo de frutos y dispersión de semillas de serbal (Sorbus aucuparia L.) por zorros y martas en la cordillera Cantábrica occidentalEvaluación de espermatozoides obtenidos postmorten en el ciervo.Frecuencia de aparición de diferentes restos de conejo en excrementos de lince y zorroAtlas preliminar de los mamíferos de Soria (España)Censo y distribución de la marmota alpina (Marmota marmota) en Navarra.Trampeo fotográfico del género Martes en el Parque Nacional de Aigüestortes i Estany de Sant Maurici (Lleida)Peer reviewe