74 research outputs found

    Low CD4+ T Cell Counts among African HIV-1 Infected Subjects with Group B KIR Haplotypes in the Absence of Specific Inhibitory KIR Ligands

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    Natural killer (NK) cells are regulated by interactions between polymorphic killer immunoglobulin-like receptors (KIR) and human leukocyte antigens (HLA). Genotypic combinations of KIR3DS1/L1 and HLA Bw4-80I were previously shown to influence HIV-1 disease progression, however other KIR genes have not been well studied. In this study, we analyzed the influence of all activating and inhibitory KIR, in association with the known HLA inhibitory KIR ligands, on markers of disease progression in a West African population of therapy-naïve HIV-1 infected subjects. We observed a significant association between carriage of a group B KIR haplotype and lower CD4+ T cell counts, with an additional effect for KIR3DS1 within the frame of this haplotype. In contrast, we found that individuals carrying genes for the inhibitory KIR ligands HLA-Bw4 as well as HLA-C1 showed significantly higher CD4+ T cell counts. These associations were independent from the viral load and from individual HIV-1 protective HLA alleles. Our data suggest that group B KIR haplotypes and lack of specific inhibitory KIR ligand genes, genotypes considered to favor NK cell activation, are predictive of HIV-1 disease progression

    Integrating methods for ecosystem service assessment: Experiences from real world situations

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    The Ecosystem Services (ES) concept highlights the varied contributions the environment provides to humans and there are a wide range of methods/tools available to assess ES. However, in real-world decision contexts a single tool is rarely sufficient and methods must be combined to meet practitioner needs. Here, results from the OpenNESS project are presented to illustrate the methods selected to meet the needs of 24 real-world case studies and better understand why and how methods are combined to meet practical needs. Results showed that within the cases methods were combined to: i) address a range of ES; ii) assess both supply and demand of ES; iii) assess a range of value types; iv) reach different stake-holder groups v) cover weaknesses in other methods used and vi) to meet specific decision context needs. Methods were linked in a variety of ways: i) as input-output chains of methods; ii) through learning; iii) through method development and iv) through comparison/triangulation of results. The paper synthesises these case study-based experiences to provide insight to others working in practical contexts as to where, and in what contexts, different methods can be combined and how this can add value to case study analyses. (C) 2017 Published by Elsevier B.V.Peer reviewe

    Stakeholders' perspectives on the operationalisation of the ecosystem service concept : Results from 27 case studies

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    The ecosystem service (ES) concept is becoming mainstream in policy and planning, but operational influence on practice is seldom reported. Here, we report the practitioners' perspectives on the practical implementation of the ES concept in 27 case studies. A standardised anonymous survey (n = 246), was used, focusing on the science-practice interaction process, perceived impact and expected use of the case study assessments. Operationalisation of the concept was shown to achieve a gradual change in practices: 13% of the case studies reported a change in action (e.g. management or policy change), and a further 40% anticipated that a change would result from the work. To a large extent the impact was attributed to a well conducted science-practice interaction process (>70%). The main reported advantages of the concept included: increased concept awareness and communication; enhanced participation and collaboration; production of comprehensive science-based knowledge; and production of spatially referenced knowledge for input to planning (91% indicated they had acquired new knowledge). The limitations were mostly case-specific and centred on methodology, data, and challenges with result implementation. The survey highlighted the crucial role of communication, participation and collaboration across different stakeholders, to implement the ES concept and enhance the democratisation of nature and landscape planning. (C) 2017 Published by Elsevier B.V.Peer reviewe

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

    Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

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    INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

    Serum biomarkers identify critically ill traumatic brain injury patients for MRI

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