Entity

Time filter

Source Type


Cochez C.,Research Laboratory and Reference Laboratory for Vector borne Diseases | Ducoffre G.,Scientific Institute of Public Health IPH | Vandenvelde C.,Research Laboratory and Reference Laboratory for Vector borne Diseases | Luyasu V.,Catholic University of Louvain | Heyman P.,Research Laboratory and Reference Laboratory for Vector borne Diseases
Ticks and Tick-borne Diseases | Year: 2011

Human granulocytic anaplasmosis (HGA) is a tick-borne rickettsial infection of neutrophils caused by Anaplasma phagocytophilum. Although the pathogen was known as a veterinary agent as early as 1932, the link with human disease was first established in 1990. In the past decennium, the involvement of HGA as an important and frequent cause of fever with a history of tick bite was increasingly recognized in many regions of Europe.This paper presents a 10-year A. phagocytophilum serosurveillance (2000-2009), wherein 1672 serum samples were tested and 418 were found positive. A total of 111 patients had a history of tick bite, fever, and at least a 4-fold rise in titre and are thus considered to be confirmed cases. These findings suggest that Belgium is a hot spot for HGA infections. © 2011 Elsevier GmbH. Source


Querci M.,European Commission - Joint Research Center Ispra | Van Den Bulcke M.,Scientific Institute of Public Health IPH | Zel J.,Slovenian National Institute of Biology | Van Den Eede G.,European Commission - Joint Research Center Ispra | Broll H.,Federal Institute for Risk Assessment BfR
Analytical and Bioanalytical Chemistry | Year: 2010

The steady rate of development and diffusion of genetically modified plants and their increasing diversification of characteristics, genes and genetic control elements poses a challenge in analysis of genetically modified organisms (GMOs). It is expected that in the near future the picture will be even more complex. Traditional approaches, mostly based on the sequential detection of one target at a time, or on a limited multiplexing, allowing only a few targets to be analysed at once, no longer meet the testing requirements. Along with new analytical technologies, new approaches for the detection of GMOs authorized for commercial purposes in various countries have been developed that rely on (1) a smart and accurate strategy for target selection, (2) the use of high-throughput systems or platforms for the detection of multiple targets and (3) algorithms that allow the conversion of analytical results into an indication of the presence of individual GMOs potentially present in an unknown sample. This paper reviews the latest progress made in GMO analysis, taking examples from the most recently developed strategies and tools, and addresses some of the critical aspects related to these approaches. © 2009 Springer-Verlag. Source


Depoorter P.,Federal Agency for the Safety of the Food Chain FASFC | Persoons D.,Ghent University | Uyttendaele M.,Ghent University | Butaye P.,Coda Research | And 6 more authors.
International Journal of Food Microbiology | Year: 2012

Acquired resistance of Escherichia coli to 3rd generation cephalosporin antimicrobials is a relevant issue in intensive broiler farming. In Belgium, about 35% of the E. coli strains isolated from live broilers are resistant to 3rd generation cephalosporins while over 60% of the broilers are found to be carrier of these 3rd generation cephalosporin resistant E. coli (CREC) after selective isolation. A model aimed at estimating the exposure of the consumer to CREC by consumption of broiler meat was elaborated. This model consists of different modules that simulate the farm to fork chain starting from primary production, over slaughter, processing and distribution to storage, preparation and consumption of broiler meat. Input data were obtained from the Belgian Food Safety agencies' annual monitoring plan and results from dedicated research programs or surveys. The outcome of the model using the available baseline data estimates that the probability of exposure to 1000 colony forming units (cfu) of CREC or more during consumption of a meal containing chicken meat is ca. 1.5%, the majority of exposure being caused by cross contamination in the kitchen. The proportion of CREC (within the total number of E. coli) at primary production and the overall contamination of broiler carcasses or broiler parts with E. coli are dominant factors in the consumer exposure to CREC. The risk of this exposure for human health cannot be estimated at this stage given a lack of understanding of the factors influencing the transfer of cephalosporin antimicrobial resistance genes from these E. coli to the human intestinal bacteria and data on the further consequences of the presence of CREC on human health. © 2012 Elsevier B.V. Source


Vlieghe E.R.,Institute of Tropical Medicine | de Smet B.,Institute of Tropical Medicine | Bertrand S.,Scientific Institute of Public Health IPH | Vanhoof R.,Scientific Institute of Public Health IPH | And 3 more authors.
PLoS Neglected Tropical Diseases | Year: 2012

Background: Salmonella enterica is a frequent cause of bloodstream infection (BSI) in Asia but few data are available from Cambodia. We describe Salmonella BSI isolates recovered from patients presenting at Sihanouk Hospital Centre of Hope, Phnom Penh, Cambodia (July 2007-December 2010). Methodology: Blood was cultured as part of a microbiological prospective surveillance study. Identification of Salmonella isolates was performed by conventional methods and serotyping. Antibiotic susceptibilities were assessed using disk diffusion, MicroScan and E-test macromethod. Clonal relationships were assessed by Pulsed Field Gel Electrophoresis; PCR and sequencing for detection of mutations in Gyrase and Topoisomerase IV and presence of qnr genes. Principal Findings: Seventy-two Salmonella isolates grew from 58 patients (mean age 34.2 years, range 8-71). Twenty isolates were identified as Salmonella Typhi, 2 as Salmonella Paratyphi A, 37 as Salmonella Choleraesuis and 13 as other non-typhoid Salmonella spp. Infection with human immunodeficiency virus (HIV) was present in 21 of 24 (87.5%) patients with S. Choleraesuis BSI. Five patients (8.7%) had at least one recurrent infection, all with S. Choleraesuis; five patients died. Overall, multi drug resistance (i.e., co-resistance to ampicillin, sulphamethoxazole-trimethoprim and chloramphenicol) was high (42/59 isolates, 71.2%). S. Typhi displayed high rates of decreased ciprofloxacin susceptibility (18/20 isolates, 90.0%), while azithromycin resistance was very common in S. Choleraesuis (17/24 isolates, 70.8%). Two S. Choleraesuis isolates were extended spectrum beta-lactamase producer. Conclusions and Significance: Resistance rates in Salmonella spp. in Cambodia are alarming, in particular for azithromycin and ciprofloxacin. This warrants nationwide surveillance and revision of treatment guidelines. © 2012 Vlieghe et al. Source


Deconinck E.,Scientific Institute of Public Health IPH | Sacre P.Y.,Scientific Institute of Public Health IPH | Sacre P.Y.,University of Liege | Coomans D.,Vrije Universiteit Brussel | De Beer J.,Scientific Institute of Public Health IPH
Journal of Pharmaceutical and Biomedical Analysis | Year: 2012

Classification trees built with the Classification And Regression Tree algorithm were evaluated for modelling infrared spectroscopic data in order to discriminate between genuine and counterfeit drug samples and to classify counterfeit samples in different classes following the RIVM classification system.Models were built for two data sets consisting of the Fourier Transformed Infrared spectra, the near infrared spectra and the Raman spectra for genuine and counterfeit samples of respectively Viagra ® and Cialis ®.Easy interpretable models were obtained for both models. The models were validated for their descriptive and predictive properties. The predictive properties were evaluated using both cross validation as an external validation set. The obtained models for both data sets showed a 100% correct classification for the discrimination between genuine and counterfeit samples and 83.3% and 100% correct classification for the counterfeit samples for the Viagra ® and the Cialis ® data set respectively. © 2011 Elsevier B.V. Source

Discover hidden collaborations