Day 2 :
National University of Singapore, Singapore
Time : 09:00-09:30
Choon Nam ONG is the Director of the NUS Environmental Research Institute (NERI) and a professor at the Saw Swee Hock School of Public Health, National University of Singapore. He has published more than 300 papers in international peer-reviewed journals with an h-index of 75, and over 17,000 citations. His main research interest is Environmental Health Sciences and teaches in Toxicology and Environment Health, and nursing a lifelong passion of all matters related to environment on health. Since 1985, he has served as a consultant to the World Health Organization (WHO) on many occasions and was involved in 12 of its Health Criteria publications.He is an editorial board member of several international journals on environment and sustainability. He is a visiting professor to several overseas universities and serves as a Scientific Advisor to the China Center of Disease Control and Prevention (CDC). He was the recipient of Astra-Zeneca American Toxicology Society Award, 2002. Dr Ong also served as an advisor to the OECD, US National Water Research Institute, and has been consulted often by international health agencies on issues related to environmental health. He has been a member of the WHO Guidelines for Drinking Water Quality Expert Panel since 2003. His research group currently focuses on the use of metabolomics as a technology platform for biomedical and environmental research.
Dietary factors play important roles in human metabolism and influence the status of health. So far, few human studies have been focused on how diet affects the palsma metabolome. In this study, we investigated the differences in plasma metabolic profiles between habitual high meat and seafood (HMS) eaters and low meat and seafood (LMS) eaters using mass spectrometry-based metabolomics methods, aimed to reveal the link between plasma metabolic profiles and habitual dietary intake. Plasma metabolites were profiled and compared between 83 HMS eaters and 82 LMS eaters from a healthy cohort in Singapore. A total of 49 differential metabolites were found between the two dietary groups. The difference was mainly reflected by higher concentrations of arachidonic acid (AA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and AA/EPA/DHA-content phospholipids in HMS eaters than in LMS eaters, although there were also differences in levels of other metabolites, such as D-glucose, glycine, and urea. We observed strong correlations across a wide range of plasma metabolites and food variables. The strongest association was found for DHA levels with fish consumption (r = 0.535). Our study demonstrates that mass spectrometry-based metabonomics is a valid technique to dietary pattern analysis, and the findings illustrates that plasma metabolic profiles were associated with habitual diets.
Pacific Northwest National Laboratory, USA
Time : 09:31-10:00
Jian Zhi Hu received his Ph.D in 1994 and is currently a senior staff scientist and principal investigator of Pacific Norwest National Laboratory. He has published more than 170 papers in peer reviewed journals, delivered a large number of presentations, received two US R&D 100 awards and 10 US patents.
Ionizing radiation can be fatal to a living system and is a growing concern in the fields of medicine where diagnostic imaging techniques using X-rays are frequently used on patients, the space exploration where astronauts have a great chance of exposing to high energy space particle radiation and nuclear energy generation where an unfortunate accident may happen. In this work, NMR based metabolomics combined with multivariate data analysis are used to evaluate the metabolic changes in the C57BL/6 mice 4 and 11 days post whole body 3.0 Gy and 7.8 Gy gamma radiations, including proton irradiation, using various organs (liver, spleen, lung and heart) and blood. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification of potential metabolite markers associated with gamma irradiation. Two different strategies for NMR spectral data reduction, i.e., spectral binning and spectral deconvolution are compared with normalization to constant sum and unit weight before multivariate data analysis. It is found that the combination of spectral deconvolution and normalization to unit weight is the best way for identifying discriminatory metabolites between the irradiation and control groups. Using this method, metabolite markers responsible for gamma radiation are identified on each organ and blood, separately. The possibility of accessingindividual organ injury due to ionizing radiation via minimally invasive blood will be discussed.