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Home / Archives for Van Wijngaerden E

Predictors of non adherence to antiretroviral therapy at an urban HIV care and treatment center in Tanzania

  • Autores: Aboud S, Chalamilla G, Kamuhabwa A, Lyamuya EF, Mosha F, Sangeda RZ, Van Wijngaerden E, Vandamme AM, Vercauteren J
  • Ano de Publicação: 2018
  • Journal: Drug Healthcare and Patient Safety
  • Link: https://www.ncbi.nlm.nih.gov/pubmed/30174460

BACKGROUND: Measurement of adherence to antiretroviral therapy (ART) can serve as a proxy for virologic failure in resource-limited settings. The aim of this study was to determine the factors underlying nonadherence measured by three methods. PATIENTS AND METHODS: This is a prospective longitudinal cohort of 220 patients on ART at Amana Hospital in Dar es […]
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Phylogenetic evidence for underreporting of male-to-male sex among human immunodeficiency virus–infected donors in the Netherlands and Flanders

  • Autores: Bezemer D, Claas EC, Compernolle V, de Smet A, van de Laar TJ, Van Laethem K, van Sighem AI, Van Wijngaerden E, Vandamme AM, Vandewalle G, Zaaijer HL
  • Ano de Publicação: 2017
  • Journal: Transfusion
  • Link: https://onlinelibrary.wiley.com/doi/abs/10.1111/trf.14097

Separate transmission networks for human immunodeficiency virus (HIV) coexist. Molecular typing of viral genomes can provide insight in HIV transmission routes in donors for whom risk behavior-based donor selection failed. This study includes all HIV-infected Dutch and Flemish donors in the period 2005 to 2014 (n = 55). Part of the HIV polymerase (pol) gene was amplified, […]
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Quantifying next generation sequencing sample pre-processing bias in HIV-1 complete genome sequencing

  • Autores: Baele G, Lemey P, Trovão NS, Van Laethem K, Van Wijngaerden E, Vandamme AM, Vrancken B
  • Ano de Publicação: 2016
  • Journal: Viruses
  • Link: http://www.mdpi.com/1999-4915/8/1/12%20

Genetic analyses play a central role in infectious disease research. Massively parallelized “mechanical cloning” and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome […]
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HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure

  • Autores: Beheydt G, Bruzzone B, Camacho RJ, De Luca A, Deforche K, Grossman Z, Imbrechts S, Incardona F, Libin P, Pironti A, Rhee SY, Ruiz L, Sangeda RZ, Shafer RW, Sönnerborg A, Theys K, Torti C, Van de Vijver DA, Van Laethem K, Van Wijngaerden E, Vandamme AM, Vercauteren J, Zazzi M
  • Journal: Infection Genetics and Evolution
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/23523594

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment.
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RegaDB: Community-driven data management and analysis for infectious diseases

  • Autores: Alcantara LC, Assel M, Ayouba A, Beheydt G, Boucher C, Camacho RJ, Carvalho AP, Cavaco-Silva J, De Bel A, De Munter P, De Oliveira T, Deforche K, Ferreira F, Grossman Z, Imbrechts S, Kaiser R, Lacor P, Lapadula G, Libin P, Otelea D, Paraschiv S, Peeters M, Ruelle J, Sloot P, Snoeck J, Theys K, Torti C, Van Laethem K, Van Wijngaerden E, Vandamme AM, Wesner S, Zazzi M
  • Journal: Bioinformatics
  • Link: http://www.ncbi.nlm.nih.gov/pubmed/23645815

RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface.
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About GHTM

GHTM is a R&D Center that brings together researchers from IHMT with a track record in Tropical Medicine and International/Global Health. It aims at strengthening Portugal's role as a leading partner in the development and implementation of a global health research agenda. Our evidence-based interventions contribute to the promotion of equity in health and to improve the health of populations.

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