683 research outputs found

    Metabolism of ticagrelor in patients with acute coronary syndromes.

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    © The Author(s) 2018Ticagrelor is a state-of-the-art antiplatelet agent used for the treatment of patients with acute coronary syndromes (ACS). Unlike remaining oral P2Y12 receptor inhibitors ticagrelor does not require metabolic activation to exert its antiplatelet action. Still, ticagrelor is extensively metabolized by hepatic CYP3A enzymes, and AR-C124910XX is its only active metabolite. A post hoc analysis of patient-level (n = 117) pharmacokinetic data pooled from two prospective studies was performed to identify clinical characteristics affecting the degree of AR-C124910XX formation during the first six hours after 180 mg ticagrelor loading dose in the setting of ACS. Both linear and multiple regression analyses indicated that ACS patients presenting with ST-elevation myocardial infarction or suffering from diabetes mellitus are more likely to have decreased rate of ticagrelor metabolism during the acute phase of ACS. Administration of morphine during ACS was found to negatively influence transformation of ticagrelor into AR-C124910XX when assessed with linear regression analysis, but not with multiple regression analysis. On the other hand, smoking appears to increase the degree of ticagrelor transformation in ACS patients. Mechanisms underlying our findings and their clinical significance warrant further research.Peer reviewedFinal Published versio

    An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies

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    The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup

    Symptoms, Distribution and Abundance of the Stem-Boring Caterpillar, Blastobasis repartella (Dietz), in Switchgrass

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    A potential pest of switchgrass, Panicum virgatum L., was first detected in South Dakota in 2004, where death of partially emerged leaves was noted in a small proportion of tillers. Similar “dead heart” symptoms were observed in switchgrass in Illinois during 2008 and adults of a stem-boring caterpillar were collected and identified as Blastobasis repartella (Dietz). In 2009, a survey of the central United States was used to estimate the distribution and abundance of this insect. In eight northern states, B. repartella was consistently found in both cultivated plots and natural stands of switchgrass. In four southern states, B. repartella was not detected. However, because symptoms are conspicuous for a short period of time, failure to collect stem-borers on one survey date for each southern location does not necessarily define the limit of distribution for B. repartella. Sampling in four northern states showed the proportion of tillers damaged by B. repartella ranged from 1.0–7.2%. Unlike some caterpillars that feed on native grasses, it appears that the egg-laying behavior of adult moths may preclude the use of prescribed burns as an effective method to suppress this stem-boring caterpillar. As a potential pest of switchgrass planted for biomass production, near-term research needs include refining the geographic distribution of B. repartella, quantifying potential losses of switchgrass biomass, and determining whether switchgrass may be bred for resistance this and other stem-boring insects

    FLT3-regulated antigens as targets for leukemia-reactive cytotoxic T lymphocytes

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    The FMS-like tyrosine kinase 3 (FLT3) is highly expressed in acute myeloid leukemia (AML). Internal tandem duplications (ITD) of the juxtamembrane domain lead to the constitutive activation of the FLT3 kinase inducing the activation of multiple genes, which may result in the expression of leukemia-associated antigens (LAAs). We analyzed the regulation of LAA in FLT3-wild-type (WT)- and FLT3-ITD+ myeloid cells to identify potential targets for antigen-specific immunotherapy for AML patients. Antigens, such as PR-3, RHAMM, Survivin, WT-1 and PRAME, were upregulated by constitutively active FLT3-ITD as well as FLT3-WT activated by FLT3 ligand (FL). Cytotoxic T-cell (CTL) clones against PR-3, RHAMM, Survivin and an AML-directed CTL clone recognized AML cell lines and primary AML blasts expressing FLT3-ITD, as well as FLT3-WT+ myeloid dendritic cells in the presence of FL. Downregulation of FLT3 led to the abolishment of CTL recognition. Comparing our findings concerning LAA upregulation by the FLT3 kinase with those already made for the Bcr-Abl kinase, we found analogies in the LAA expression pattern. Antigens upregulated by both FLT3 and Bcr-Abl may be promising targets for the development of immunotherapeutical approaches against myeloid leukemia of different origin

    Increased amino acids levels and the risk of developing of hypertriglyceridemia in a 7-year follow-up

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    BACKGROUND: Recently, five branched-chain and aromatic amino acids were shown to be associated with the risk of developing type 2 diabetes (T2D). AIM: We set out to examine whether amino acids are also associated with the development of hypertriglyceridemia. MATERIALS AND METHODS: We determined the serum amino acids concentrations of 1,125 individuals of the KORA S4 baseline study, for which follow-up data were available also at the KORA F4 7 years later. After exclusion for hypertriglyceridemia (defined as having a fasting triglyceride level above 1.70 mmol/L) and diabetes at baseline, 755 subjects remained for analyses. RESULTS: Increased levels of leucine, arginine, valine, proline, phenylalanine, isoleucine and lysine were significantly associated with an increased risk of hypertriglyceridemia. These associations remained significant when restricting to those individuals who did not develop T2D in the 7-year follow-up. The increase per standard deviation of amino acid level was between 26 and 40 %. CONCLUSIONS: Seven amino acids were associated with an increased risk of developing hypertriglyceridemia after 7 years. Further studies are necessary to elucidate the complex role of these amino acids in the pathogenesis of metabolic disorders

    Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies.

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    BACKGROUND: Untargeted mass spectrometry (MS)-based metabolomics data often contain missing values that reduce statistical power and can introduce bias in biomedical studies. However, a systematic assessment of the various sources of missing values and strategies to handle these data has received little attention. Missing data can occur systematically, e.g. from run day-dependent effects due to limits of detection (LOD); or it can be random as, for instance, a consequence of sample preparation. METHODS: We investigated patterns of missing data in an MS-based metabolomics experiment of serum samples from the German KORA F4 cohort (n = 1750). We then evaluated 31 imputation methods in a simulation framework and biologically validated the results by applying all imputation approaches to real metabolomics data. We examined the ability of each method to reconstruct biochemical pathways from data-driven correlation networks, and the ability of the method to increase statistical power while preserving the strength of established metabolic quantitative trait loci. RESULTS: Run day-dependent LOD-based missing data accounts for most missing values in the metabolomics dataset. Although multiple imputation by chained equations performed well in many scenarios, it is computationally and statistically challenging. K-nearest neighbors (KNN) imputation on observations with variable pre-selection showed robust performance across all evaluation schemes and is computationally more tractable. CONCLUSION: Missing data in untargeted MS-based metabolomics data occur for various reasons. Based on our results, we recommend that KNN-based imputation is performed on observations with variable pre-selection since it showed robust results in all evaluation schemes.This work was supported by grants from the German Federal Ministry of Education and Research (BMBF), by BMBF Grant No. 01ZX1313C (project e:Athero-MED) and Grant No. 03IS2061B (project Gani_Med). Moreover, the research leading to these results has received funding from the European Union’s Seventh Framework Programme [FP7-Health-F5-2012] under grant agreement No. 305280 (MIMOmics) and from the European Research Council (starting grant “LatentCauses”). KS is supported by Biomedical Research Program funds at Weill Cornell Medical College in Qatar, a program funded by the Qatar Foundation. The KORA Augsburg studies were financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany and supported by grants from the German Federal Ministry of Education and Research (BMBF). Analyses in the EPIC-Norfolk study were supported by funding from the Medical Research Council (MC_PC_13048 and MC_UU_12015/1)

    Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

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    Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation
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