Origin Identification and Quantitative Analysis of Honeys by Nuclear Magnetic Resonance and Chemometric Techniques

The combination of H-1 NMR spectroscopy and multivariate statistical analysis has become a promising method for the discrimination of food origins. In this paper, this method has been successfully employed to analyze 70 Chinese honey samples from eight botanic origins, three geographical origins, and five production dates. Thirty-three components in honey samples were detected and identified from their H-1 NMR spectra, and 20 of them were accurately quantified by comparing their integral area with that of internal standards with relaxation time correction. Nontargeted principal component analysis (PCA) has been applied to distinguish the honeys from different botanical and geographical origins. The variations of components in the honeys, including saccharides and all kind of amino and organic carboxylic acids, confirmed their clustering according to their origins in PCA scores plots. Orthogonal partial least squares discriminant analysis (OPLS-DA) based on the NMR data for the different pairwise honey samples allows to identify the compositional variations contributed to geographical discrimination and storage time. Hence, NMR spectroscopy coupled with chemometric techniques offers an efficient tool for quality control of honey, and it could further serve to the classification, qualitative and quantitative control of other foods

The relations between metabolic variations and genetic evolution of different species

Metabonomics has been applied in many bio-related scientific fields. Nevertheless, some animal research works are shown to fail when they are extended to humans. Therefore, it is essential to figure out suitable animal modeling to mimic human metabolism so that animal findings can serve humans. In this study, two kinds of commonly selected body fluids, serum and urine, from humans and various experimental animals were characterized by integration of nuclear magnetic resonance (NMR) spectroscopy with multivariate statistical analysis to identify the interspecies metabolic differences and similarities at a baseline physiological status. Our results highlight that the dairy cow and pig may be an optimal choice for transportation and biodistribution studies of drugs and that the Kunming (KM) mouse model may be the most effective for excretion studies of drugs, whereas the Sprague-Dawley (SD) rat could be the most suitable candidate for animal modeling under overall considerations. The biochemical pathways analyses further provide an interconnection between genetic evolution and metabolic variations, where species evolution most strongly affects microbial biodiversity and, consequently, has effects on the species-specific biological substances of biosynthesis and corresponding biological activities. Knowledge of the metabolic effects from species difference will enable the construction of better models for disease diagnosis, drug metabolism, and toxicology research. (C) 2015 Elsevier Inc. All rights reserved.Metabonomics has been applied in many bio-related scientific fields. Nevertheless, some animal research works are shown to fail when they are extended to humans. Therefore, it is essential to figure out suitable animal modeling to mimic human metabolism so that animal findings can serve humans. In this study, two kinds of commonly selected body fluids, serum and urine, from humans and various experimental animals were characterized by integration of nuclear magnetic resonance (NMR) spectroscopy with multivariate statistical analysis to identify the interspecies metabolic differences and similarities at a baseline physiological status. Our results highlight that the dairy cow and pig may be an optimal choice for transportation and biodistribution studies of drugs and that the Kunming (KM) mouse model may be the most effective for excretion studies of drugs, whereas the Sprague-Dawley (SD) rat could be the most suitable candidate for animal modeling under overall considerations. The biochemical pathways analyses further provide an interconnection between genetic evolution and metabolic variations, where species evolution most strongly affects microbial biodiversity and, consequently, has effects on the species-specific biological substances of biosynthesis and corresponding biological activities. Knowledge of the metabolic effects from species difference will enable the construction of better models for disease diagnosis, drug metabolism, and toxicology research. (C) 2015 Elsevier Inc. All rights reserved

H-1 NMR-based metabolomics study on the physiological variations during the rat pregnancy process

In this study, NMR-based metabolomics in combination with multivariate pattern recognition technologies were employed to evaluate the physiological variations in the Wistar rats' plasma that are induced by pregnancy on the gestational days (GDs) 11, 14, 17 and 20. Untargeted metabolomics analysis revealed some possible mechanism of physiological effects for healthy pregnancies and showed a metabolic trajectory during pregnancy process. The levels of 24 metabolites were found to change significantly throughout pregnancy in maternal plasma. These metabolite changes involved in varied kinds of metabolic pathways including synthesis of biological substances, microbial metabolism in diverse environments, protein digestion and absorption, carbohydrate metabolism, digestion and absorption, mineral absorption, and ATP (Adenosine Triphosphate)-binding cassette transporters (ABC transporters). The substantial cores of all the metabolic pathways are promoting fetal growth and development and regulating maternal physiological state. This work showed relevant metabolic pathways perturbation in the maternal plasma due to normal pregnancy and provided the physical basis of time-dependent metabolic trajectory against which disease-related maternal physiological responses may be better understood in future studies. (C) 2016 Elsevier Ireland Ltd. All rights reserved

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen