841 resultados para Medical research personnel
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El trabajo ha sido realizado dentro del marco de los proyectos EURECA (Enabling information re-Use by linking clinical REsearch and Care) e INTEGRATE (Integrative Cancer Research Through Innovative Biomedical Infrastructures), en los que colabora el Grupo de Informática Biomédica de la UPM junto a otras universidades e instituciones sanitarias europeas. En ambos proyectos se desarrollan servicios e infraestructuras con el objetivo principal de almacenar información clínica, procedente de fuentes diversas (como por ejemplo de historiales clínicos electrónicos de hospitales, de ensayos clínicos o artículos de investigación biomédica), de una forma común y fácilmente accesible y consultable para facilitar al máximo la investigación de estos ámbitos, de manera colaborativa entre instituciones. Esta es la idea principal de la interoperabilidad semántica en la que se concentran ambos proyectos, siendo clave para el correcto funcionamiento del software del que se componen. El intercambio de datos con un modelo de representación compartido, común y sin ambigüedades, en el que cada concepto, término o dato clínico tendrá una única forma de representación. Lo cual permite la inferencia de conocimiento, y encaja perfectamente en el contexto de la investigación médica. En concreto, la herramienta a desarrollar en este trabajo también está orientada a la idea de maximizar la interoperabilidad semántica, pues se ocupa de la carga de información clínica con un formato estandarizado en un modelo común de almacenamiento de datos, implementado en bases de datos relacionales. El trabajo ha sido desarrollado en el periodo comprendido entre el 3 de Febrero y el 6 de Junio de 2014. Se ha seguido un ciclo de vida en cascada para la organización del trabajo realizado en las tareas de las que se compone el proyecto, de modo que una fase no puede iniciarse sin que se haya terminado, revisado y aceptado la fase anterior. Exceptuando la tarea de documentación del trabajo (para la elaboración de esta memoria), que se ha desarrollado paralelamente a todas las demás. ----ABSTRACT--- The project has been developed during the second semester of the 2013/2014 academic year. This Project has been done inside EURECA and INTEGRATE European biomedical research projects, where the GIB (Biomedical Informatics Group) of the UPM works as a partner. Both projects aim is to develop platforms and services with the main goal of storing clinical information (e.g. information from hospital electronic health records (EHRs), clinical trials or research articles) in a common way and easy to access and query, in order to support medical research. The whole software environment of these projects is based on the idea of semantic interoperability, which means the ability of computer systems to exchange data with unambiguous and shared meaning. This idea allows knowledge inference, which fits perfectly in medical research context. The tool to develop in this project is also "semantic operability-oriented". Its purpose is to store standardized clinical information in a common data model, implemented in relational databases. The project has been performed during the period between February 3rd and June 6th, of 2014. It has followed a "Waterfall model" of software development, in which progress is seen as flowing steadily downwards through its phases. Each phase starts when its previous phase has been completed and reviewed. The task of documenting the project‟s work is an exception; it has been performed in a parallel way to the rest of the tasks.
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Los tratamientos biopelícula fueron unos de los primeros tratamientos biológicos que se aplicaron en las aguas residuales. Los tratamientos biopelícula presentan importantes ventajas frente a los cultivos en suspensión, sin embargo, el control de los tratamientos biopelícula es complicado y su modelización también. Las bases teóricas del comportamiento de las biopelículas empezaron a desarrollarse fundamentalmente a partir de los años 80. Dado que el proceso es complejo con ecuaciones de difícil resolución, estas conceptualizaciones han sido consideradas durante años como ejercicios matemáticos más que como herramientas de diseño y simulación. Los diseños de los reactores estaban basados en experiencias de plantas piloto o en comportamientos empíricos de determinadas plantas. Las ecuaciones de diseño eran regresiones de los datos empíricos. La aplicabilidad de las ecuaciones se reducía a las condiciones particulares de la planta de la que provenían los datos empíricos. De tal forma que existía una gran variedad y diversidad de ecuaciones empíricas para cada tipo de reactor. La investigación médica durante los años 90 centró su atención en la formación y eliminación de las biopelículas. Gracias al desarrollo de nuevas prácticas de laboratorio que permitían estudiar el interior de las biopelículas y gracias también al aumento de la capacidad de los ordenadores, la simulación del comportamiento de las biopelículas tomó un nuevo impulso en esta década. El desarrollo de un tipo de biopelículas, fangos granulares, en condiciones aerobias realizando simultaneamente procesos de eliminación de nutrientes ha sido recientemente patentado. Esta patente ha recibido numerosos premios y reconocimientos internacionales tales como la Eurpean Invention Award (2012). En 1995 se descubrió que determinadas bacterias podían realizar un nuevo proceso de eliminación de nitrógeno denominado Anammox. Este nuevo tipo de proceso de eliminación de nitrógeno tiene el potencial de ofrecer importantes mejoras en el rendimiento de eliminación y en el consumo de energía. En los últimos 10 años, se han desarrollado una serie de tratamientos denominados “innovadores” de eliminación de nutrientes. Dado que no resulta posible el establecimiento de estas bacterias Anammox en fangos activos convencionales, normalmente se recurre al uso de cultivos biopelícula. La investigación se ha centrado en el desarrollo de estos procesos innovadores en cultivos biopelícula, en particular en los fangos granulares y MBBR e IFAs, con el objeto de establecer las condiciones bajo las cuales estos procesos se pueden desarrollar de forma estable. Muchas empresas y organizaciones buscan una segunda patente. Una cuestión principal en el desarrollo de estos procesos se encuentra la correcta selección de las condiciones ambientales y de operación para que unas bacterias desplacen a otras en el interior de las biopelículas. El diseño de plantas basado en cultivos biopelícula con procesos convencionales se ha realizado normalmente mediante el uso de métodos empíricos y semi-empíricos. Sin embargo, los criterios de selección avanzados aplicados en los Tratamientos Innovadores de Eliminación de Nitrógeno unido a la complejidad de los mecanismos de transporte de sustratos y crecimiento de la biomasa en las biopelículas, hace necesario el uso de herramientas de modelización para poder conclusiones no evidentes. Biofilms were one of the first biological treatments used in the wastewater treatment. Biofilms exhibit important advantages over suspended growth activated sludge. However, controlling biofilms growth is complicated and likewise its simulation. The theoretical underpinnings of biofilms performance began to be developed during 80s. As the equations that govern the growth of biofilms are complex and its resolution is challenging, these conceptualisations have been considered for years as mathematical exercises instead of practical design and simulation tools. The design of biofilm reactors has been based on performance information of pilot plants and specific plants. Most of the times, the designing equations were simple regressions of empirical data. The applicability of these equations were confined to the particular conditions of the plant from where the data came from. Consequently, there were a wide range of design equations for each type of reactor During 90s medical research focused its efforts on how biofilm´s growth with the ultimate goal of avoiding it. Thanks to the development of new laboratory techniques that allowed the study the interior of the biofilms and thanks as well to the development of the computers, simulation of biofilms’ performance had a considerable evolution during this decade. In 1995 it was discovered that certain bacteria can carry out a new sort of nutrient removal process named Anammox. This new type of nutrient removal process potentially can enhance considerably the removal performance and the energy consumption. In the last decade, it has been developed a range of treatments based on the Anammox generally named “Innovative Nutrient Removal Treatments”. As it is not possible to cultivate Anammox bacteria in activated sludge, normally scientists and designers resort to the use of biofilms. A critical issue in the development of these innovative processes is the correct selection of environment and operation conditions so as to certain bacterial population displace to others bacteria within the biofilm. The design of biofilm technology plants is normally based on the use of empirical and semi-empirical methods. However, the advanced control strategies used in the Innovative Nutrient Removal Processes together with the complexity of the mass transfer and biomass growth in biofilms, require the use of modeling tools to be able to set non evident conclusions.
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This work was funded by the Medical ResearchCouncil (G1100357).We are grateful to Anne Saunderson, Joan Creiger and the staff of the Bruntsfield Suite, Royal Infirmary of Edinburgh, for their considerable assistance in patient recruitment. Funding to pay the Open Access publication charges for this article was provided by MRC grant G1100357.
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Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved. Acknowledgements The author's studies in this field are supported by MRC grants G1002118 (NS and RAA) and G110357 (RAA), MR/L010011/1 (PAF), the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 212885 (PAF) and the Wellcome Trust (080388 to PAF). AS was funded by a BBSRC CASE Studentship co-funded by AstraZeneca.
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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Acknowledgements: We thank Ms Margaret Fraser, Ms Samantha Flannigan, and Dr Wing Yee Kwong for their expert assistance. The staff at Grampian NHS Pregnancy Counselling Service were essential for collecting fetuses. We thank Professor Geoffrey Hammond and Dr Marc Simard, University of British Colombia for helpful comments on the manuscript. Supported by grants as follows: Scottish Senior Clinical Fellowship (AJD); Chief Scientist Office (Scottish Executive, CZG/1/109 to PAF, & CZG/4/742 (PAF & PJOS); NHS Grampian Endowments 08/02 (PAF, SB & PJOS); the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no 212885 (PAF & SMR); the Medical Research Council grants MR/L010011/1 (PAF & PJOS) and MR/K018310/1 (AJD). None of the funding bodies played any role in the design, collection, analysis, and interpretation of data, in the writing of the manuscript, nor in the decision to submit the manuscript for publication
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Acknowledgements The work was in part funded by UK Medical Research Council project grant G0601253 to G.S.B. and R.W.B.
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Funding: This study is supported by the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London (FM and HZ), the Medical Research Council grant (grant reference MR/L013142/1, FM), SMA-Europe grant (FM and HZ) and Great Ormond Street Hospital Children’s Charity grants (FM and JM). JEM is supported by Great Ormond Street Hospital Children’s Charity. PS is supported by Bill Marshall Fellowship and The CP Charitable Trust at Great Ormond Street Hospital and UCL. SHP is supported by SMA Trust and Euan MacDonald Centre for Motor Neurone Disease Research.
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Acknowledgments The staff at Grampian National Health Service Pregnancy Counseling Service were essential for collecting fetuses. We thank the Aberdeen Proteomics Core Facility (University of Aberdeen) for their expert assistance. Support for the study was provided by the Chief Scientist Office (Scottish Executive, CZG/1/109, & CZG/4/742), National Health Service Grampian Endowments (08/02), the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement no 212885, and the Medical Research Council, UK (MR/L010011/1).
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ACKNOWLEDGEMENTS We acknowledge the data management support of Grampian Data Safe Haven (DaSH) and the associated financial support of NHS Research Scotland, through NHS Grampian investment in the Grampian DaSH. S.S. is supported by a Clinical Research Training Fellowship from the Wellcome Trust (Ref 102729/Z/13/Z). We also acknowledge the support from The Farr Institute of Health Informatics Research. The Farr Institute is supported by a 10-funder consortium: Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly Government), the Chief Scientist Office (Scottish Government Health Directorates) and the Wellcome Trust (MRC Grant Nos: Scotland MR/K007017/1).
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Funding This work was funded by Arthritis Research UK (grants 17859, 17971, 19654), INNOCHEM EU FP6 (grant LSHB-CT-2005-51867), MRC (MR/K013076/1) and the William Harvey Research Foundation
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ACKNOWLEDGMENTS G.D.B. thanks the Wellcome Trust and MRC (United Kingdom) for funding.
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Acknowledgements This paper belongs to the studies carried out by Kuopio Birth Cohort consortium (www.KuBiCo.fi). We thank Ms Pirjo Hänninen for expert laboratory assistance at University of Eastern Finland, Ms Margaret Fraser, Dr Panagiotis Filis and the Proteomics Core Facility at the University of Aberdeen for their expert assistance. We also thank the staff of the Department of Obstetrics and Gynaecology in Kuopio University Hospital for skilful collection of these specimens. This work was supported by the Academy of Finland [122859/2007], the Helena Vuorenmies Foundation, the Emil Aaltonen Foundation, the University of Eastern Finland Doctoral Programme in Drug Research and the Medical Research Council, UK [MR/L010011/1]. The funders played no roles in study design, data collection, data analysis, manuscript preparation and/or publication decisions.
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Funding: This work was supported by a grant from the Medical Research Council MR/J015277/1. The Scottish National Islet Transplant Programme is funded by the National Services Division of NHS Scotland. KRM was funded by a Fellowship from the Wellcome Trust / Scottish Translational Medicine and Therapeutics Initiative 85664. Acknowledgments This work was supported by a grant from the Medical Research Council MR/J015277/1. The Scottish National Islet Transplant Programme is funded by the National Services Division of NHS Scotland. KRM was funded by a Fellowship from the Wellcome Trust/ Scottish Translational Medicine and Therapeutics Initiative 85664. We thank Joanna Sweetman for assistance in optimisation of the immunogold staining.
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Funding: British Women’s Heart and Health Study is funded by the Department of Health grant no. 90049 and the British Heart Foundation grant no. PG/09/022. British Regional Heart Study is supported by the British Heart Foundation (grant RG/ 13/16/30528). CB (COPDBEAT) received funding from the Medical Research Council UK (grant no. G0601369), CB (COPDBEAT) and AJW (UKCOPD) were supported by the National Institute for Health Research (NIHR Leicester Biomedical Research Unit). MB (COPDBEAT) received funding from the NIHR (grant no. PDF-2013-06-052). Hertfordshire Cohort Study received support from the Medical Research Council, Arthritis Research UK, the International Osteoporosis Foundation and the British Heart Foundation; NIHR Biomedical Research Centre in Nutrition, University of Southampton; NIHR Musculoskeletal Biomedical Research Unit, University of Oxford. Generation Scotland: Scottish Family Health Study is funded by the Chief Scientist Office, Scottish Government Health Directorates, grant number CZD/16/6 and the Scottish Funding Council grant HR03006. EU COPD Gene Scan is funded by the European Union, grant no. QLG1-CT-2001-01012. English Longitudinal Study of Aging is funded by the Institute of Aging, NIH grant No. AG1764406S1. GoDARTs is funded by the Wellcome Trust grants 072960, 084726 and 104970. MDT has been supported by MRC fellowship G0902313. UK Biobank Lung Exome Variant Evaluation study was funded by a Medical Research Council strategic award to MDT, IPH, DPS and LVW (MC_PC_12010)
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Funding The research reported in this publication was supported by the Biotechnology and Biological Sciences Research Council (E007821/1 to M.S.M-G, R.L.C and E00797X/1; BB/K001418 /1 to L.K.H), the British Heart Foundation (FS/09/029/27902 to S.E.O.), the UK Medical Research Council Metabolic Diseases Unit (MC_UU_12012/4 to S.E.O and MC_UU_12012/1 to G.S.H.Y), the Wellcome Trust (WT081713 and WT098012 to L.K.H), the European Union (FP7-HEALTH-266408 Full4Health to G.S.H.Y) and the Helmholtz Alliance ICEMED to G.S.H.Y.