Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99


Any time

2018 ( 1 )

2017 ( 2 )

2015 ( 36 )

2014 ( 57 )

Custom range...

Search Results: 1 - 10 of 524 matches for " Miles Trupp "
All listed articles are free for downloading (OA Articles)
Page 1 /524
Display every page Item
Editorial: Tourismus im Fokus / Tourism in Focus
Alexander Trupp
ASEAS : ?sterreichische Zeitschrift für Südostasienwissenschaften , 2011,
Exhibiting the ‘Other’ Then and Now: 'Human Zoos' in Southern China and Thailand
Alexander Trupp
ASEAS : ?sterreichische Zeitschrift für Südostasienwissenschaften , 2011,
Metabolomics Reveals Amino Acids Contribute to Variation in Response to Simvastatin Treatment
Miles Trupp, Hongjie Zhu, William R. Wikoff, Rebecca A. Baillie, Zhao-Bang Zeng, Peter D. Karp, Oliver Fiehn, Ronald M. Krauss, Rima Kaddurah-Daouk
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0038386
Abstract: Statins are widely prescribed for reducing LDL-cholesterol (C) and risk for cardiovascular disease (CVD), but there is considerable variation in therapeutic response. We used a gas chromatography-time-of-flight mass-spectrometry-based metabolomics platform to evaluate global effects of simvastatin on intermediary metabolism. Analyses were conducted in 148 participants in the Cholesterol and Pharmacogenetics study who were profiled pre and six weeks post treatment with 40 mg/day simvastatin: 100 randomly selected from the full range of the LDL-C response distribution and 24 each from the top and bottom 10% of this distribution (“good” and “poor” responders, respectively). The metabolic signature of drug exposure in the full range of responders included essential amino acids, lauric acid (p<0.0055, q<0.055), and alpha-tocopherol (p<0.0003, q<0.017). Using the HumanCyc database and pathway enrichment analysis, we observed that the metabolites of drug exposure were enriched for the pathway class amino acid degradation (p<0.0032). Metabolites whose change correlated with LDL-C lowering response to simvastatin in the full range responders included cystine, urea cycle intermediates, and the dibasic amino acids ornithine, citrulline and lysine. These dibasic amino acids share plasma membrane transporters with arginine, the rate-limiting substrate for nitric oxide synthase (NOS), a critical mediator of cardiovascular health. Baseline metabolic profiles of the good and poor responders were analyzed by orthogonal partial least square discriminant analysis so as to determine the metabolites that best separated the two response groups and could be predictive of LDL-C response. Among these were xanthine, 2-hydroxyvaleric acid, succinic acid, stearic acid, and fructose. Together, the findings from this study indicate that clusters of metabolites involved in multiple pathways not directly connected with cholesterol metabolism may play a role in modulating the response to simvastatin treatment. Trial Registration ClinicalTrials.gov NCT00451828
Research on South-East Asia in Austria: Department of Geography and Regional Research, University of Vienna
Karl Husa,Alexander Trupp
ASEAS : ?sterreichische Zeitschrift für Südostasienwissenschaften , 2010,
Images of Hans Manndorff's Anthropological Research on the 'Hill Tribes' of Northern Thailand (1961-1965)
Alexander Trupp,Kosita Butratana
ASEAS : ?sterreichische Zeitschrift für Südostasienwissenschaften , 2009,
Thai Communities in Vienna
Kosita Butratana,Alexander Trupp
ASEAS : ?sterreichische Zeitschrift für Südostasienwissenschaften , 2011,
Enteric Microbiome Metabolites Correlate with Response to Simvastatin Treatment
Rima Kaddurah-Daouk, Rebecca A. Baillie, Hongjie Zhu, Zhao-Bang Zeng, Michelle M. Wiest, Uyen Thao Nguyen, Katie Wojnoonski, Steven M. Watkins, Miles Trupp, Ronald M. Krauss
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0025482
Abstract: Although statins are widely prescribed medications, there remains considerable variability in therapeutic response. Genetics can explain only part of this variability. Metabolomics is a global biochemical approach that provides powerful tools for mapping pathways implicated in disease and in response to treatment. Metabolomics captures net interactions between genome, microbiome and the environment. In this study, we used a targeted GC-MS metabolomics platform to measure a panel of metabolites within cholesterol synthesis, dietary sterol absorption, and bile acid formation to determine metabolite signatures that may predict variation in statin LDL-C lowering efficacy. Measurements were performed in two subsets of the total study population in the Cholesterol and Pharmacogenetics (CAP) study: Full Range of Response (FR), and Good and Poor Responders (GPR) were 100 individuals randomly selected from across the entire range of LDL-C responses in CAP. GPR were 48 individuals, 24 each from the top and bottom 10% of the LDL-C response distribution matched for body mass index, race, and gender. We identified three secondary, bacterial-derived bile acids that contribute to predicting the magnitude of statin-induced LDL-C lowering in good responders. Bile acids and statins share transporters in the liver and intestine; we observed that increased plasma concentration of simvastatin positively correlates with higher levels of several secondary bile acids. Genetic analysis of these subjects identified associations between levels of seven bile acids and a single nucleotide polymorphism (SNP), rs4149056, in the gene encoding the organic anion transporter SLCO1B1. These findings, along with recently published results that the gut microbiome plays an important role in cardiovascular disease, indicate that interactions between genome, gut microbiome and environmental influences should be considered in the study and management of cardiovascular disease. Metabolic profiles could provide valuable information about treatment outcomes and could contribute to a more personalized approach to therapy.
Induced voltage in an open wire
K. Morawetz,M. Gilbert,A. Trupp
Physics , 2015,
Abstract: A puzzle arising from Faraday's law is considered and solved concerning the question which voltage is induced in an open wire feeling a time-varying homogeneous magnetic field. The longitudinal electric field contributes 1/3 and the transverse field 2/3 to the induced voltage. The representation of a homogeneous and time-varying magnetic field implies unavoidably a certain symmetry point or line dependent on the geometry of the source. As a consequence the induced voltage of an open wire is found to be the area covered with respect to the symmetry line or point perpendicular to the magnetic field. This in turn allows to find the symmetry points of a magnetic field source by measuring the voltage of an open wire. We present two exactly solvable models for a symmetry point and for a symmetry line. The results are applicable to open circuit problems and for astrophysical applications.
A framework for power analysis using a structural equation modelling procedure
Jeremy Miles
BMC Medical Research Methodology , 2003, DOI: 10.1186/1471-2288-3-27
Abstract: Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used.The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis.The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres.Structural equation modelling (SEM) was developed from work in econometrics (simultaneous equation models; see for example Wansbeek and Meijer [2]) and latent variable models from factor analysis [3,4]. Structural equation modelling is an enormously flexible technique – it is possible to use a structural equation modelling approach to carry out direct equivalents of many analyses, including (but not limited to): ANOVA, correlation, ANCOVA, multiple regression, multivariate analysis of variance, and multivariate regression. This flexibility will be exploited in the approach set out in this article.A necessarily very brief introduction to the logic of structural equation modelling is presented here – for a more thorough introduction to the basics of structural equation modelling the reader is directed towards one of the many good introductory texts, (Steiger has recently reviewed several such texts [5]). For more details on the statistical and mathematical aspects of struc
Yao bride-exchange, matrifiliation and adoption
Douglas Miles
Bijdragen tot de Taal-, Land- en Volkenkunde , 1972,
Page 1 /524
Display every page Item

Copyright © 2008-2017 Open Access Library. All rights reserved.