197 research outputs found

    Pharmacogenetics of ophthalmic topical ÎČ-blockers

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    Glaucoma is the second leading cause of blindness worldwide. The primary glaucoma risk factor is elevated intraocular pressure. Topical ÎČ-blockers are affordable and widely used to lower intraocular pressure. Genetic variability has been postulated to contribute to interpersonal differences in efficacy and safety of topical ÎČ-blockers. This review summarizes clinically significant polymorphisms that have been identified in the ÎČ-adrenergic receptors (ADRB1, ADRB2 and ADRB3). The implications of polymorphisms in CYP2D6 are also discussed. Although the candidate-gene approach has facilitated significant progress in our understanding of the genetic basis of glaucoma treatment response, most drug responses involve a large number of genes, each containing multiple polymorphisms. Genome-wide association studies may yield a more comprehensive set of polymorphisms associated with glaucoma outcomes. An understanding of the genetic mechanisms associated with variability in individual responses to topical ÎČ-blockers may advance individualized treatment at a lower cost

    The comet 17P/Holmes 2007 outburst: the early motion of the outburst material

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    Context. On October 24, 2007 the periodic comet 17P/Holmes underwent an astonishing outburst that increased its apparent total brightness from magnitude V\sim17 up to V\sim2.5 in roughly two days. We report on Wendelstein 0.8 m telescope (WST) photometric observations of the early evolution stages of the outburst. Aims. We studied the evolution of the structure morphology, its kinematic, and estimated the ejected dust mass. Methods. We analized 126 images in the BVRI photometric bands spread between 26/10/2007 and 20/11/2007. The bright comet core appeared well separated from that one of a quickly expanding dust cloud in all the data, and the bulk of the latter was contained in the field of view of our instrument. The ejected dust mass was derived on the base of differential photometry on background stars occulted by the moving cloud. Results. The two cores were moving apart from each other at a relative projected constant velocity of (9.87 +/- 0.07) arcsec/day (0.135 +/-0.001 km/sec). In the inner regions of the dust cloud we observed a linear increase in size at a mean constant velocity of (14.6+/-0.3) arcsec/day (0.200+/-0.004 km/sec). Evidence of a radial velocity gradient in the expanding cloud was also found. Our estimate for the expanding coma's mass was of the order of 10^{-2}-1 comet's mass implying a significant disintegration event. Conclusions. We interpreted our observations in the context of an explosive scenario which was more probably originated by some internal instability processes, rather than an impact with an asteroidal body. Due to the peculiar characteristics of this event, further observations and investigations are necessary in order to enlight the nature of the physical processes that determined it.Comment: 5 pages, 3 figures, A&A accepte

    Viral factors in influenza pandemic risk assessment

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    The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk

    Statistics of Certain Models of Evolution

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    In a recent paper, Newman surveys the literature on power law spectra in evolution, self-organised criticality and presents a model of his own to arrive at a conclusion that self-organised criticality is not necessary for evolution. Not only did he miss a key model (Ecolab) that has a clear self-organised critical mechanism, but also Newman's model exhibits the same mechanism that gives rise to power law behaviour as does Ecolab. Newman's model is, in fact, a ``mean field'' approximation of a self-organised critical system. In this paper, I have also implemented Newman's model using the Ecolab software, removing the restriction that the number of species remains constant. It turns out that the requirement of constant species number is non-trivial, leading to a global coupling between species that is similar in effect to the species interactions seen in Ecolab. In fact, the model must self-organise to a state where the long time average of speciations balances that of the extinctions, otherwise the system either collapses or explodes. In view of this, Newman's model does not provide the hoped-for counter example to the presence of self-organised criticality in evolution, but does provide a simple, almost analytic model that can used to understand more intricate models such as Ecolab.Comment: accepted in Phys Rev E.; RevTeX; See http://parallel.hpc.unsw.edu.au/rks/ecolab.html for more informatio

    Clinical and pharmacogenetic predictors of circulating atorvastatin and rosuvastatin concentrations in routine clinical care

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    Background-A barrier to statin therapy is myopathy associated with elevated systemic drug exposure. Our objective was to examine the association between clinical and pharmacogenetic variables and statin concentrations in patients. Methods and Results-In total, 299 patients taking atorvastatin or rosuvastatin were prospectively recruited at an outpatient referral center. The contribution of clinical variables and transporter gene polymorphisms to statin concentration was assessed using multiple linear regression. We observed 45-fold variation in statin concentration among patients taking the same dose. After adjustment for sex, age, body mass index, ethnicity, dose, and time from last dose, SLCO1B1 c.521T\u3eC (P\u3c0.001) and ABCG2 c.421C\u3eA (P\u3c0.01) were important to rosuvastatin concentration (adjusted R2=0.56 for the final model). Atorvastatin concentration was associated with SLCO1B1 c.388A\u3eG (P\u3c0.01) and c.521T\u3eC (P\u3c0.05) and 4ÎČ-hydroxycholesterol, a CYP3A activity marker (adjusted R2=0.47). A second cohort of 579 patients from primary and specialty care databases were retrospectively genotyped. In this cohort, genotypes associated with statin concentration were not differently distributed among dosing groups, implying providers had not yet optimized each patient\u27s risk-benefit ratio. Nearly 50% of patients in routine practice taking the highest doses were predicted to have statin concentrations greater than the 90th percentile. Conclusions-Interindividual variability in statin exposure in patients is associated with uptake and efflux transporter polymorphisms. An algorithm incorporating genomic and clinical variables to avoid high atorvastatin and rosuvastatin levels is described; further study will determine whether this approach reduces incidence of statin myopathy. © 2013 American Heart Association, Inc

    Genome-wide Association of Lipid-lowering Response to Statins in Combined Study Populations

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    Background: Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy. Methods and Principal Findings: Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks). Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P = 1.8×10−8^{−8}). This SNP was less significantly associated with change in LDL-cholesterol (posterior probability = 0.16, P = 4.0×10−6^{−6}). Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol. Conclusions and Significance: Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we have identified SNPs that may be associated with variation in the magnitude of statin-mediated reduction in total and LDL-cholesterol, including one in the CLMN gene for which statistical evidence for association exceeds conventional levels of genome-wide significance.Trial Registration PRINCE and TNT are not registered. CAP is registered at Clinicaltrials.gov NCT0045182

    An interesting candidate for isolated massive star formation in the Small Magellanic Cloud

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    The region of the Small Magellanic Cloud (SMC) with which this paper is concerned contains the highest concentration of IRAS/Spitzer sources, H I emission, and molecular clouds in this neighboring galaxy. However very few studies have been devoted to it, despite these signs of star formation. We present the first detailed study of the compact H II region N33 in the SMC by placing it in a wider context of massive star formation. Moreover, we show that N33 is a particularly interesting candidate for isolated massive star formation. This analysis is based mainly on optical ESO NTT observations, both imaging and spectroscopy, coupled with other archive data, notably Spitzer images (IRAC 3.6, 4.5, 5.8, and 8.0 mic) and 2MASS observations. We derive a number of physical characteristics of the compact H II region N33 for the first time. This gas and dust formation of 7".4 (2.2 pc) in diameter is powered by a massive star of spectral type O6.5-O7 V. The compact H II region belongs to a rare class of H II regions in the Magellanic Clouds, called high-excitation blobs (HEBs). We show that this H II region is not related to any star cluster. Specifically, we do not find any traces of clustering around N33 on scales larger than 10" (~ 3 pc). On smaller scales, there is a marginal stellar concentration, the low density of which, below the 3 sigma level, does not classify it as a real cluster. We also verify that N33 is not a member of any large stellar association. Under these circumstances, N33 is also therefore attractive because it represents a remarkable case of isolated massive-star formation in the SMC. Various aspects of the relevance of N33 to the topic of massive-star formation in isolation are discussed.Comment: 17 pages, 9 figures, 5 tables; Accepted for publication in A&

    Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

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    In addition to lowering low density lipoprotein-cholesterol (LDL-C), statin therapy also raises high density lipoprotein-cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation
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