570 research outputs found

    Static platelet adhesion, flow cytometry and serum TXB2 levels for monitoring platelet inhibiting treatment with ASA and clopidogrel in coronary artery disease: a randomised cross-over study

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    <p>Abstract</p> <p>Background</p> <p>Despite the use of anti-platelet agents such as acetylsalicylic acid (ASA) and clopidogrel in coronary heart disease, some patients continue to suffer from atherothrombosis. This has stimulated development of platelet function assays to monitor treatment effects. However, it is still not recommended to change treatment based on results from platelet function assays. This study aimed to evaluate the capacity of a static platelet adhesion assay to detect platelet inhibiting effects of ASA and clopidogrel. The adhesion assay measures several aspects of platelet adhesion simultaneously, which increases the probability of finding conditions sensitive for anti-platelet treatment.</p> <p>Methods</p> <p>With a randomised cross-over design we evaluated the anti-platelet effects of ASA combined with clopidogrel as well as monotherapy with either drug alone in 29 patients with a recent acute coronary syndrome. Also, 29 matched healthy controls were included to evaluate intra-individual variability over time. Platelet function was measured by flow cytometry, serum thromboxane B<sub>2 </sub>(TXB<sub>2</sub>)-levels and by static platelet adhesion to different protein surfaces. The results were subjected to Principal Component Analysis followed by ANOVA, t-tests and linear regression analysis.</p> <p>Results</p> <p>The majority of platelet adhesion measures were reproducible in controls over time denoting that the assay can monitor platelet activity. Adenosine 5'-diphosphate (ADP)-induced platelet adhesion decreased significantly upon treatment with clopidogrel compared to ASA. Flow cytometric measurements showed the same pattern (r<sup>2 </sup>= 0.49). In opposite, TXB<sub>2</sub>-levels decreased with ASA compared to clopidogrel. Serum TXB<sub>2 </sub>and ADP-induced platelet activation could both be regarded as direct measures of the pharmacodynamic effects of ASA and clopidogrel respectively. Indirect pharmacodynamic measures such as adhesion to albumin induced by various soluble activators as well as SFLLRN-induced activation measured by flow cytometry were lower for clopidogrel compared to ASA. Furthermore, adhesion to collagen was lower for ASA and clopidogrel combined compared with either drug alone.</p> <p>Conclusion</p> <p>The indirect pharmacodynamic measures of the effects of ASA and clopidogrel might be used together with ADP-induced activation and serum TXB<sub>2 </sub>for evaluation of anti-platelet treatment. This should be further evaluated in future clinical studies where screening opportunities with the adhesion assay will be optimised towards increased sensitivity to anti-platelet treatment.</p

    Optical Magnetometry

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    Some of the most sensitive methods of measuring magnetic fields utilize interactions of resonant light with atomic vapor. Recent developments in this vibrant field are improving magnetometers in many traditional areas such as measurement of geomagnetic anomalies and magnetic fields in space, and are opening the door to new ones, including, dynamical measurements of bio-magnetic fields, detection of nuclear magnetic resonance (NMR), magnetic-resonance imaging (MRI), inertial-rotation sensing, magnetic microscopy with cold atoms, and tests of fundamental symmetries of Nature.Comment: 11 pages; 4 figures; submitted to Nature Physic

    Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

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    One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort

    The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

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    Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma

    MultiMSOAR 2.0: An Accurate Tool to Identify Ortholog Groups among Multiple Genomes

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    The identification of orthologous genes shared by multiple genomes plays an important role in evolutionary studies and gene functional analyses. Based on a recently developed accurate tool, called MSOAR 2.0, for ortholog assignment between a pair of closely related genomes based on genome rearrangement, we present a new system MultiMSOAR 2.0, to identify ortholog groups among multiple genomes in this paper. In the system, we construct gene families for all the genomes using sequence similarity search and clustering, run MSOAR 2.0 for all pairs of genomes to obtain the pairwise orthology relationship, and partition each gene family into a set of disjoint sets of orthologous genes (called super ortholog groups or SOGs) such that each SOG contains at most one gene from each genome. For each such SOG, we label the leaves of the species tree using 1 or 0 to indicate if the SOG contains a gene from the corresponding species or not. The resulting tree is called a tree of ortholog groups (or TOGs). We then label the internal nodes of each TOG based on the parsimony principle and some biological constraints. Ortholog groups are finally identified from each fully labeled TOG. In comparison with a popular tool MultiParanoid on simulated data, MultiMSOAR 2.0 shows significantly higher prediction accuracy. It also outperforms MultiParanoid, the Roundup multi-ortholog repository and the Ensembl ortholog database in real data experiments using gene symbols as a validation tool. In addition to ortholog group identification, MultiMSOAR 2.0 also provides information about gene births, duplications and losses in evolution, which may be of independent biological interest. Our experiments on simulated data demonstrate that MultiMSOAR 2.0 is able to infer these evolutionary events much more accurately than a well-known software tool Notung. The software MultiMSOAR 2.0 is available to the public for free

    Computing Brane and Flux Superpotentials in F-theory Compactifications

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    In four-dimensional F-theory compactifications with N=1 supersymmetry the fields describing the dynamics of space-time filling 7-branes are part of the complex structure moduli space of the internal Calabi-Yau fourfold. We explicitly compute the flux superpotential in F-theory depending on all complex structure moduli, including the 7-brane deformations and the field corresponding to the dilaton-axion. Since fluxes on the 7-branes induce 5-brane charge, a local limit allows to effectively match the F-theory results to a D5-brane in a non-compact Calabi-Yau threefold with threeform fluxes. We analyze the classical and instanton contributions to the F-theory superpotential using mirror symmetry for Calabi-Yau fourfolds. The F-theory compactifications under consideration also admit heterotic dual descriptions and we discuss the identification of the moduli in this non-perturbative duality.Comment: 75 pages, 1 figure; typos corrected, references adde

    A Common KIF6 Polymorphism Increases Vulnerability to Low-Density Lipoprotein Cholesterol: Two Meta-Analyses and a Meta-Regression Analysis

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    Background: We sought to determine if a common polymorphism can influence vulnerability to LDL cholesterol, and thereby influence the clinical benefit derived from therapies that reduce LDL cholesterol. Methods: We conducted a meta-analysis of the association between a common Trp719Arg polymorphism in the kinesin-like protein 6 (KIF6) gene and the risk of cardiovascular disease (CVD), and a meta-regression analysis to measure the effect modification of this polymorphism on the association between LDL cholesterol and the risk of CVD. We used this measure of genetic effect modification to predict the expected difference in clinical benefit among KIF6 719Arg allele carriers and non-carriers in response to therapies that reduce LDL cholesterol. We then conducted a meta-analysis of statin trials to compare the expected difference in clinical benefit with the observed difference during treatment with a statin. Results: In a meta-analysis involving 144,931 participants, the KIF6 719Arg allele was not associated with the relative risk (RR) of CVD (RR: 1.02, 95%CI: 0.98-1.07, p = 0.288). Meta-regression analysis involving 88,535 participants, however, showed that the 719Arg allele appears to influence the effect of LDL cholesterol on the risk of CVD. KIF6 carriers experienced a 13% greater reduction in the risk of CVD per mmol/L decrease in LDL cholesterol than non-carriers. We interpreted this difference as the expected difference in clinical benefit among KIF6 carriers and non-carriers in response to therapies that lower LDL cholesterol. The difference in clinical benefit predicted by the increased vulnerability to LDL cholesterol among KIF6 carriers (ratio of RR: 0.87, 95%CI: 0.80-0.94, p = 0.001) agreed very closely with the observed difference among 50,060 KIF6 carriers and non-carriers enrolled in 8 randomized trials of statin therapy (ratio of RR: 0.87, 95%CI: 0.77-0.99, p = 0.038). Conclusion: The KIF6 719Arg allele increases vulnerability to LDL cholesterol and thereby influences the expected clinical benefit of therapies that reduce LDL cholesterol. Š 2011 Ference et al
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