The smart grid international research facility network - SIRFN

SIRFN's vision is to accelerate progress and pave the way for the global deployment of renewable energy and smart grids, in conjunction with joint global activities of research facilities, application & standardization

Chemical informatics uncovers a new role for moexipril as a novel inhibitor of cAMP phosphodiesterase-4 (PDE4)

PDE4 is one of eleven known cyclic nucleotide phosphodiesterase families and plays a pivotal role in mediating hydrolytic degradation of the important cyclic nucleotide second messenger, cyclic 3′5′ adenosine monophosphate (cAMP). PDE4 inhibitors are known to have anti-inflammatory properties, but their use in the clinic has been hampered by mechanism-associated side effects that limit maximally tolerated doses. In an attempt to initiate the development of better-tolerated PDE4 inhibitors we have surveyed existing approved drugs for PDE4-inhibitory activity. With this objective, we utilised a high-throughput computational approach that identified moexipril, a well tolerated and safe angiotensin-converting enzyme (ACE) inhibitor, as a PDE4 inhibitor. Experimentally we showed that moexipril and two structurally related analogues acted in the micro molar range to inhibit PDE4 activity. Employing a FRET-based biosensor constructed from the nucleotide binding domain of the type 1 exchange protein activated by cAMP, EPAC1, we demonstrated that moexipril markedly potentiated the ability of forskolin to increase intracellular cAMP levels. Finally, we demonstrated that the PDE4 inhibitory effect of moexipril is functionally able to induce phosphorylation of the Hsp20 by cAMP dependent protein kinase A. Our data suggest that moexipril is a bona fide PDE4 inhibitor that may provide the starting point for development of novel PDE4 inhibitors with an improved therapeutic window

The role of income inequality and social policies on income-related health inequalities in Europe

INTRODUCTION: The aim of the paper is to examine the role of income inequality and redistribution for income-related health inequalities in Europe. This paper contributes in two ways to the literature on macro determinants of socio-economic inequalities in health. First, it widens the distinctive focus of the research field on welfare state regimes to quantifiable measures such as social policy indicators. Second, looking at income differences completes studies on socio-economic health inequalities, which often analyse health inequalities based on educational differences. METHODS: Using data from the European Values Study (2008/2009), 42 European countries are available for analysis. Country characteristics are derived from SWIID, Eurostat, and ILO and include indicators for income inequality, social policies, and economic performance. The data is analysed by using a two-step hierarchical estimation approach: At the first step—the individual level—the effect of household income on self-assessed health is extracted and introduced as an indicator measuring income-related health inequalities at the second step, the country-level. RESULTS: Individual-level analyses reveal that income-related health inequalities exist all across Europe. Results from country-level analyses show that higher income inequality is significantly positively related to higher health inequalities while social policies do not show significant relations. Nevertheless, the results show the expected negative association between social policies and health inequalities. Economic performance also has a reducing influence on health inequalities. In all models, income inequality was the dominating explanatory effect for health inequalities. CONCLUSIONS: The analyses indicate that income inequality has more impact on health inequalities than social policies. On the contrary, social policies seemed to matter to all individuals regardless of socio-economic position since it is significantly positively linked to overall population health. Even though social policies are not significantly related to health inequalities, the power of public redistribution to impact health inequalities should not be downplayed. Social policies as a way of public redistribution are a possible instrument to reduce income inequalities which would in turn lead to a reduction in health inequalities

LDL-C reductions and goal attainment among naive statin users in the Netherlands: real life results.

Item does not contain fulltextOBJECTIVE: The effectiveness of statin therapy in a real life setting may differ from that in clinical trials, as physicians make non-randomised treatment decisions for patients with less uniform and possibly different characteristics. We therefore performed a study to compare the effectiveness of different statins and doses in routine clinical practice with respect to total serum cholesterol and LDL-cholesterol (LDL-C) reduction and goal attainment according to European guidelines on the prevention of cardiovascular disease (CVD). RESEARCH DESIGN AND METHODS: Naive statin users starting treatment in 2003 and 2004 with LDL-C measurements at baseline and between 30 and 365 days after start of treatment were extracted from the PHARMO database. During treatment with their initial statin dose LDL-C reduction and attainment of cholesterol goals were compared between different statins and doses. RESULTS: Of 2303 identified naive patients, approximately 30% were allocated to the high CVD-risk group. Average LDL-C reductions were 48%, 42%, 39%, and 32% at mean doses of 11 mg rosuvastatin, 17 mg atorvastatin, 22 mg simvastatin and 35 mg pravastatin, respectively. The proportion of patients attaining cholesterol goals was 75% for rosuvastatin, 68% for atorvastatin, 56% for simvastatin, and 42% for pravastatin. Dose comparisons showed greater LDL-C reduction and increased goal attainment for rosuvastatin 10 mg compared to other statins at most doses (adjusted p < 0.05). CONCLUSIONS: In a real life setting, both LDL-C reduction and the proportion of patients attaining cholesterol goals appear to be significantly increased among users of rosuvastatin compared to other statins. These results confirm and extend reported clinical trial results to a real world setting

Experimental and Mathematical Analysis of Hepatic Uptake

Introduction: To investigate the nonlinear kinetics of in vitro hepatic uptake the OATP substrate, Pitivastatin, was used as a probe. Experiments were conducted using freshly isolated rat hepatocytes, utilising the ‘oil spin’ methodology described by Hassen et al [1]. [...

A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease

BACKGROUND: Transcriptomic studies in clinical research are essential tools for deciphering the functional elements of the genome and unraveling underlying disease mechanisms. Various technologies have been developed to deduce and quantify the transcriptome including hybridization and sequencing-based approaches. Recently, high density exon microarrays have been successfully employed for detecting differentially expressed genes and alternative splicing events for biomarker discovery and disease diagnostics. The field of transcriptomics is currently being revolutionized by high throughput DNA sequencing methodologies to map, characterize, and quantify the transcriptome. METHODS: In an effort to understand the merits and limitations of each of these tools, we undertook a study of the transcriptome in sickle cell disease, a monogenic disease comparing the Affymetrix Human Exon 1.0 ST microarray (Exon array) and Illumina’s deep sequencing technology (RNA-seq) on whole blood clinical specimens. RESULTS: Analysis indicated a strong concordance (R = 0.64) between Exon array and RNA-seq data at both gene level and exon level transcript expression. The magnitude of differential expression was found to be generally higher in RNA-seq than in the Exon microarrays. We also demonstrate for the first time the ability of RNA-seq technology to discover novel transcript variants and differential expression in previously unannotated genomic regions in sickle cell disease. In addition to detecting expression level changes, RNA-seq technology was also able to identify sequence variation in the expressed transcripts. CONCLUSIONS: Our findings suggest that microarrays remain useful and accurate for transcriptomic analysis of clinical samples with low input requirements, while RNA-seq technology complements and extends microarray measurements for novel discoveries