The first-line treatment of hyperuricemia, which causes gout, is allopurinol. The allopurinol response is highly variable, with many users failing to achieve target serum uric acid (SUA) levels. No genome-wide association study (GWAS) has examined the genetic factors affecting allopurinol effectiveness. Using 2,027 subjects in Kaiser Permanente's Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort, we conducted a GWAS of allopurinol-related SUA reduction, first in the largest ethnic group, non-Hispanic white (NHW) subjects, and then in a stratified transethnic meta-analysis. ABCG2, encoding the efflux pump BCRP, was associated with SUA reduction in NHW subjects (P = 2 × 10(-8) ), and a missense allele (rs2231142) was associated with a reduced response (P = 3 × 10(-7) ) in the meta-analysis. Isotopic uptake studies in cells demonstrated that BCRP transports allopurinol and genetic variants in ABCG2 affect this transport. Collectively, this first GWAS of allopurinol response demonstrates that ABCG2 is a key determinant of response to the drug.

This paper presents a computational vascular fluid-structure interaction (FSI) methodology and its application to patient-specific aneurysm models of the middle cerebral artery bifurcation. A fully coupled fluid-structural simulation approach is reviewed, and main aspects of mesh generation in support of patient-specific vascular FSI analyses are presented. Quantities of hemodynamic interest such as wall shear stress and wall tension are studied to examine the relevance of FSI modeling as compared to the rigid arterial wall assumption. We demonstrate the importance of including the flexible wall modeling in vascular blood flow simulations by performing a comparison study that involves four patient-specific models of cerebral aneurysms varying in shape and size.

Four new hydroxycinnamic acid amides, scotanamines A-D (1-4), and seven known alkaloids, including N ¹,N ¹⁰-di-dihydrocaffeoylspermidine (5), scopolamine (6), anisodamine (7), hyoscyamine (8), anisodine (9), caffeoylputrescine (10), and N ¹-caffeoyl-N ³-dihydrocaffeoylspermidine (11), were obtained from the roots of Scopolia tangutica. The present study represents the first recognition of hydroxycinnamic acid amides containing putrescine or spermidine in S. tangutica. Compound 1, in particular, contains a moiety resulting from the condensation of nortropinone and putrescine. Compound 2 exhibited moderate agonist activity at the μ-opioid receptor (EC50=7.3μM). Compound 2 was tested in vivo and induced analgesia in mice. The analgesic effect was recorded using the tail-flick assay and was reversed by naloxone.

BARREL observed electron precipitation over wide range of energy and timescalesPrecipitating electron distribution is determined using spectroscopy for 19 January 2013 eventBARREL timing data has accuracy within sampling interval of 0.05 s.

Transporter-mediated drug-drug interactions (DDIs) are a major cause of drug toxicities. Using published genome-wide association studies (GWAS) of the human metabolome, we identified 20 metabolites associated with genetic variants in organic anion transporter, OATP1B1 (P < 5 × 10^-8 ). Of these, 12 metabolites were significantly higher in plasma samples from volunteers dosed with the OATP1B1 inhibitor, cyclosporine (CSA) vs. placebo (q-value < 0.2). Conjugated bile acids and fatty acid dicarboxylates were among the metabolites discovered using both GWAS and CSA administration. In vitro studies confirmed tetradecanedioate (TDA) and hexadecanedioate (HDA) were novel substrates of OATP1B1 as well as OAT1 and OAT3. This study highlights the use of multiple datasets for the discovery of endogenous metabolites that represent potential in vivo biomarkers for transporter-mediated DDIs. Future studies are needed to determine whether these metabolites can serve as qualified biomarkers for organic anion transporters. Quantitative relationships between metabolite levels and modulation of transporters should be established.

One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the effect of genetic variants in transcription factors on metformin pharmacokinetics (PK) and response. Overall, 546 patients and healthy volunteers contributed their genome-wide, pharmacokinetic (235 subjects), and HbA1c data (440 patients) for this analysis. Five variants in specificity protein 1 (SP1), a transcription factor that modulates the expression of metformin transporters, were associated with changes in treatment HbA1c (P < 0.01) and metformin secretory clearance (P < 0.05). Population pharmacokinetic modeling further confirmed a 24% reduction in apparent clearance in homozygous carriers of one such variant, rs784888. Genetic variants in other transcription factors, peroxisome proliferator-activated receptor-α and hepatocyte nuclear factor 4-α, were significantly associated with HbA1c change only. Overall, our study highlights the importance of genetic variants in transcription factors as modulators of metformin PK and response.

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques. This paper describes the results from the second and third MOPEX workshops. The specific objective of these workshops is to examine the state of a priori parameter estimation techniques and how they can be potentially improved with observations from well-monitored hydrologic basins. Participants of the second and third MOPEX workshops were provided with data from 12 basins in the southeastern US and were asked to carry out a series of numerical experiments using a priori parameters as well as calibrated parameters developed for their respective hydrologic models. Different modeling groups carried out all the required experiments independently using eight different models, and the results from these models have been assembled for analysis in this paper. This paper presents an overview of the MOPEX experiment and its design. The main experimental results are analyzed. A key finding is that existing a priori parameter estimation procedures are problematic and need improvement. Significant improvement of these procedures may be achieved through model calibration of well-monitored hydrologic basins. This paper concludes with a discussion of the lessons learned, and points out further work and future strategy. © 2005 Elsevier Ltd. All rights reserved.

Using atmospheric forcing data generated from a general circulation climate model, sixteen land surface schemes participating in the Project for the Intercomparison of Land-surface Parametrization Schemes (PILPS) were run off-line to equilibrium using forcing data from a GCM representative of a tropical forest and a mid-latitude grassland grid point. The values for each land surface parameter (roughness length, minimum stomatal resistance, soil depth etc.) were provided. Results were quality controlled and analyzed, focusing on the scatter simulated amongst the models. There were large differences in how the models' partitioned available energy between sensible and latent heat. Annually averaged, simulations for the tropical forest ranged by 79 W m-2 for the sensible heat flux and 80 W m-2 for the latent heat flux. For the grassland, simulations ranged by 34 W m-2 for the sensible heat flux and 27 W m-2 for the latent heat flux. Similarly large differences were found for simulated runoff and soil moisture and at the monthly time scale. The models' simulation of annually averaged effective radiative temperature varied with a range, between all the models, of 1.4 K for tropical forest and 2.2 K for the grassland. The simulation of latent and sensible heat fluxes by a standard 'bucket' models was anomalous although this could be corrected by an additional resistance term. These results imply that the current land surface models do not agree on the land surface climate when the atmospheric forcing and surface parameters are prescribed. The nature of the experimental design, it being offline and with artificial forcing, generally precludes judgements concerning the relative quality of any specific model. Although these results were produced de-coupled from a host model, they do cast doubt on the reliability of land surface schemes. It is therefore a priority to resolve the disparity in the simulations, understand the reasons behind the scatter and to determine whether this lack of agreement in decoupled tests is reproduced in coupled experiments.

A preliminary investigation was carried out by the US Environmental Protection Agency (EPA) on the impact of regional ozone concentrations on climate change in the country. The main objective of the investigation was to enhance the ability of air quality managers to consider global change in their decisions through improved characterization of the potential effects of global change on air quality, including O3, PM, and Hg. An integrated assessment framework was designed that supported the research and development efforts within the EPA and the academic research professionals. This design recognized the challenges of bridging spatial scales, temporal scales, and disciplines that characterize the global change and regional air quality problem. A major component of the assessment approach involved the development and application of global to regional climate and air quality modeling systems.