16 research outputs found
One-Step Detection of the 2009 Pandemic Influenza A(H1N1) Virus by the RT-SmartAmp Assay and Its Clinical Validation
<div><h3>Background</h3><p>In 2009, a pandemic (pdm) influenza A(H1N1) virus infection quickly circulated globally resulting in about 18,000 deaths around the world. In Japan, infected patients accounted for 16% of the total population. The possibility of human-to-human transmission of highly pathogenic novel influenza viruses is becoming a fear for human health and society.</p> <h3>Methodology</h3><p>To address the clinical need for rapid diagnosis, we have developed a new method, the âRT-SmartAmp assayâ, to rapidly detect the 2009 pandemic influenza A(H1N1) virus from patient swab samples. The RT-SmartAmp assay comprises both reverse transcriptase (RT) and isothermal DNA amplification reactions in one step, where RNA extraction and PCR reaction are not required. We used an exciton-controlled hybridization-sensitive fluorescent primer to specifically detect the HA segment of the 2009 pdm influenza A(H1N1) virus within 40 minutes without cross-reacting with the seasonal A(H1N1), A(H3N2), or B-type (Victoria) viruses.</p> <h3>Results and Conclusions</h3><p>We evaluated the RT-SmartAmp method in clinical research carried out in Japan during a pandemic period of October 2009 to January 2010. A total of 255 swab samples were collected from outpatients with influenza-like illness at three hospitals and eleven clinics located in the Tokyo and Chiba areas in Japan. The 2009 pdm influenza A(H1N1) virus was detected by the RT-SmartAmp assay, and the detection results were subsequently compared with data of current influenza diagnostic tests (lateral flow immuno-chromatographic tests) and viral genome sequence analysis. In conclusion, by the RT-SmartAmp assay we could detect the 2009 pdm influenza A(H1N1) virus in patients' swab samples even in early stages after the initial onset of influenza symptoms. Thus, the RT-SmartAmp assay is considered to provide a simple and practical tool to rapidly detect the 2009 pdm influenza A(H1N1) virus.</p> </div
Exposure assessment of process-related contaminants in food by biomarker monitoring
Exposure assessment is a fundamental part of the risk assessment paradigm, but can often present a number of challenges and uncertainties. This is especially the case for process contaminants formed during the processing, e.g. heating of food, since they are in part highly reactive and/or volatile, thus making exposure assessment by analysing contents in food unreliable. New approaches are therefore required to accurately assess consumer exposure and thus better inform the risk assessment. Such novel approaches may include the use of biomarkers, physiologically based kinetic (PBK) modelling-facilitated reverse dosimetry, and/or duplicate diet studies. This review focuses on the state of the art with respect to the use of biomarkers of exposure for the process contaminants acrylamide, 3-MCPD esters, glycidyl esters, furan and acrolein. From the overview presented, it becomes clear that the field of assessing human exposure to process-related contaminants in food by biomarker monitoring is promising and strongly developing. The current state of the art as well as the existing data gaps and challenges for the future were defined. They include (1) using PBK modelling and duplicate diet studies to establish, preferably in humans, correlations between external exposure and biomarkers; (2) elucidation of the possible endogenous formation of the process-related contaminants and the resulting biomarker levels; (3) the influence of inter-individual variations and how to include that in the biomarker-based exposure predictions; (4) the correction for confounding factors; (5) the value of the different biomarkers in relation to exposure scenarioâs and risk assessment, and (6) the possibilities of novel methodologies. In spite of these challenges it can be concluded that biomarker-based exposure assessment provides a unique opportunity to more accurately assess consumer exposure to process-related contaminants in food and thus to better inform risk assessment