44 research outputs found

    Missed opportunities in health care education evidence synthesis

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    We read with excitement the systematic review on how to teach evidence-based medicine (EBM) to medical trainees.1 The conclusions of the paper1 represent a concise and accurate reflection of this large synthesis of evidence. Unfortunately, we were left reflecting not on the evidence base illuminated by this review, but on the missed opportunities we will highlight herein. These examples are not in any way meant to represent a specific set of criticisms of this work,1 but, rather, are intended as exemplars of wider methodological issues that currently exist within much published material on the synthesis of evidence in health care educatio

    Usando Redes Aleatorias na Analise de Mobilidade

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    National audienceThe constant advancement of information systems has allowed more data to be generated and stored from the most diverse situations. It is fascinating that, behind these records, we see the reflection of the environment itself, since every record represents a decision made by some entity. In this work, we modeled real-world scenarios of mobility from using temporal complex networks. The analysis assumes that these systems are composed of entities able to interact in a rational manner, reflecting their interests and activity dynamic. In this direction, we propose a technique for analyzing mobility scenarios from random graphs. This technique examines how the real system would evolve if the agents' decisions were random, and from there, you can check, for example, which edges are random and which are derived from social relationships, such as friendship or professional.O avanco constante de sistemas de informacao tempermitido que mais dados sejam gerados e armazenados a partir das mais diversas situacoes. E fascinante que, por tras de cada registro, seja possıvel ver o reflexo do ambiente em si, ou seja, alguma decisao tomada por alguma entidade. Neste trabalho, sao estudados cenarios reais de mobilidade a partir de uma modelagem usando redes complexas temporais. A analise parte do pressuposto que esses sistemas sao compostos de entidades capazes de interagir entre si de uma maneira racional, refletindo seus interesses e dinamica de atividade. Nessa direcao, e proposta uma tecnica para analisar cenarios de mobilidade a partir de grafos aleatorios. Essa tecnica verifica como o sistema real evoluiria caso as decisoes dos seus agentes fossem aleat'orias e, a partir dela, pode-se verificar, por exemplo, quais arestas s˜ao aleat'orias e quais s˜ao provenientes de relac¸ ˜oes sociais, tais como relac¸ ˜oes de amizade ou profissionais

    RECAST: Telling Apart Social and Random Relationships in Dynamic Networks

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    International audienceIn this paper, we argue that the ability to accurately spot random and social relationships in dynamic networks is essential to net- work applications that rely on human routines, such as, e.g., op- portunistic routing. We thus propose a strategy to analyze users' interactions in mobile networks where users act according to their interests and activity dynamics. Our strategy, named Random rElationship ClASsifier sTrategy (RECAST), allows classifying users' wireless interactions, separating random interactions from differ- ent kinds of social ties. To that end, RECAST observes how the real system differs from an equivalent one where entities' decisions are completely random. We evaluate the effectiveness of the RECAST classification on real-world user contact datasets collected in diverse networking contexts. Our analysis unveils significant dif- ferences among the dynamics of users' wireless interactions in the datasets, which we leverage to unveil the impact of social ties on opportunistic routing

    Participatory Sensor Networks as Sensing Layers

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    International audienceParticipatory sensor networks (PSNs) regards smartphone users as consumers as well as active producers of data. A sensing layer represents a type of data, coming from a given source of data, such as web services, traditional wireless sensor networks, and PSNs. In this work, we show the usefulness and potential of having sensing layers in PSNs. We also show how we can formalize the concept of sensing layers in participatory sensor networks. Furthermore, we demonstrate how to derive and create new applications and services that are not promptly available from different sensing layers, opening up very interesting research opportunities

    Traffic Condition Is More Than Colored Lines on a Map: Characterization of Waze Alerts

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    International audienceParticipatory sensor network (PSN) enables the understanding of city dynamics and the urban behavioral patterns of their inhabitants. In this work, we focus our analysis on a specific PSN, derived from Waze, for sensing traffic con-ditions. Our objective is to characterize the properties of this PSN, its broad and global spatial coverage as well as its limitations. We also bring discussions on dif-ferent opportunities for application design using this network. We claim that the PSN derived from Waze has the potential to help us in the better understanding of traffic problem reasons. Besides that, it could be useful for improving algorithms used in navigation services: (1) by exploiting the provided real-time traffic in-formation or (2) by helping in the identification of valuable pieces of information that are hard to detect with traditional sensors, such as car accidents and potholes

    Molecular fragmentation of wheat-germ agglutinin induced by food irradiation reduces its allergenicity in sensitised mice

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    WGA, an agglutinin from wheat germ which is largely responsible for many of wheat's allergies, was used as a model to investigate the action of ionising radiation on WGA's anti-nutritive effects in sensitised mice. Based on the molecular structure, the present study also examined the structural modification of WGA in relation to the range of dose. Structural integrity was monitored using HPLC, fluorescence spectrometry and circular dichroism. Results showed a loss of intrinsic activity and the formation of insoluble amorphous aggregates with a lack of native conformational structures after irradiation. Current findings suggest that the allergenic epitopes of WGA became less active and antigenic after high-dose radiation. the reduction of cytokines typical of allergic reactions, with decreased lymphocytic infiltrate, was observed in the gut of mice given irradiated versus native WGA. Food irradiation proved effective and safe in combating immunological and allergic effects of WGA. (C) 2011 Elsevier B.V. All rights reserved.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Ministerio da Ciencia e Tecnologia (Brazilian)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundacao de Amparo a Ciencia e Tecnologia do Estado de Pernambuco (FACEPE)Univ Fed Pernambuco, Dept Bioquim, Recife, PE, BrazilUniv Fed Pernambuco, Dept Histol & Embriol, Recife, PE, BrazilUniv Fed Pernambuco, Dept Biofis & Radiobiol, Recife, PE, BrazilUniv Fed Pernambuco, Dept Antibiot, Recife, PE, BrazilUniv Estadual Oeste Parana, Ctr Engn & Ciencias Exatas, Toledo, BrazilUniversidade Federal de São Paulo, Dept Bioquim, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Bioquim, São Paulo, BrazilWeb of Scienc

    RWE in Europe Paper III: A Roadmap for RWE

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    Real world evidence (RWE) has been touted as a remedy for current market access issues, facilitating quicker approvals and increased odds of reimbursement at a good price. It is therefore an attractive avenue for pursuit for manufacturers today. This paper, the third in a series looking at the use of RWE in Europe, outlines the discussions held between key opinion leaders in pricing and reimbursement across a number of European countries at a roundtable-style meeting. The aim of the meeting was to develop a 3-year roadmap, and resulting action plan, of initiatives for the enhanced use of RWE in decision-making in the pharmaceutical industry. Following a series of brainstorming sessions across the areas of commissioning and access, clinical evidence and patients and outcomes, contributors were asked to prioritise the importance of a refined set of initiatives identified in these brainstorming sessions to develop the three-year road map. Finally, four key points from the roadmap were identified for initial action: actively engage in early dialogue with payers on RWE needs; consensus exercise on RWD/E in clinical decisions, develop a definition of patient reported/relevant outcomes and develop a model approach for the collection of patient reported/relevant outcomes data. These action points are seen as the most imperative steps for enhancing the role of RWE. If its use is to become more common addressing these steps, as quickly and efficiently as possible, will be vital for all stakeholders in the pharmaceutical arena

    2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC) Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC)

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    ARIA digital anamorphosis : Digital transformation of health and care in airway diseases from research to practice

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    Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.Peer reviewe

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
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