Nature of excitons in PPDT2FBT: PCBM solar cell: Role played by PCBM

In organic semiconductor based bulk heterojunction solar cells, the presence of acceptor increases the formation of charge transfer (CT) excitons, thereby leading to higher exciton dissociation probabilities. In this work we used steady state EA measurements to probe the change in the nature of excitons as the blend composition of the solar cell active layer material is varied. We investigated blends of poly[(2,5-bis(2-hexyldecyloxy)phenylene)-alt-(5,6-difluoro-4,7-di(thiophen-2-yl)benzo[c]-[1,2,5]thiadiazole)] (PPDT2FBT) and (6,6)-Phenyl C71 butyric acid methyl ester (PCBM). Analysis of the EA spectra showed that in presence of fullerene based acceptor, like PCBM, CT characteristics of the excitons were modified, though, no new CT signature was observed in the blend. Enhancement in the CT characteristic in the blend was reflected in the photoluminescence (PL) measurements of the blends, where, PL quenching of $\sim$ 63\% was observed for 1\% PCBM. The quenching reaches saturation at about 20\% PCBM. However, the maximum efficiency of the devices was obtained for the blend having 50\% PCBM. Comparing experimental results with simulations, the variation of the device efficiency with PCBM percentage was shown to be arising from multiple factors like increase in polarizability and dipole moment of excitons, and the efficiency of the carrier collection from the bulk of the active layer

Linear variation analysis of intracardiac atrial impedance during internal cardioversion using rectilinear waveforms and energy step up protocol

Abstract The major determinants of success during internal cardioversion of atrial fibrillation (AF

Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences.

Microbial community metabolomics, particularly in the human gut, are beginning to provide a new route to identify functions and ecology disrupted in disease. However, these data can be costly and difficult to obtain at scale, while amplicon or shotgun metagenomic sequencing data are readily available for populations of many thousands. Here, we describe a computational approach to predict potentially unobserved metabolites in new microbial communities, given a model trained on paired metabolomes and metagenomes from the environment of interest. Focusing on two independent human gut microbiome datasets, we demonstrate that our framework successfully recovers community metabolic trends for more than 50% of associated metabolites. Similar accuracy is maintained using amplicon profiles of coral-associated, murine gut, and human vaginal microbiomes. We also provide an expected performance score to guide application of the model in new samples. Our results thus demonstrate that this 'predictive metabolomic' approach can aid in experimental design and provide useful insights into the thousands of community profiles for which only metagenomes are currently available

Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

Paradoxical Role of Prion Protein Aggregates in Redox-Iron Induced Toxicity

Imbalance of iron homeostasis has been reported in sporadic Creutzfeldt-Jakob-disease (sCJD) affected human and scrapie infected animal brains, but the contribution of this phenotype to disease associated neurotoxicity is unclear.Using cell models of familial prion disorders, we demonstrate that exposure of cells expressing normal prion protein (PrP(C)) or mutant PrP forms to a source of redox-iron induces aggregation of PrP(C) and specific mutant PrP forms. Initially this response is cytoprotective, but becomes increasingly toxic with time due to accumulation of PrP-ferritin aggregates. Mutant PrP forms that do not aggregate are not cytoprotective, and cells show signs of acute toxicity. Intracellular PrP-ferritin aggregates induce the expression of LC3-II, indicating stimulation of autophagy in these cells. Similar observations are noted in sCJD and scrapie infected hamster brains, lending credence to these results. Furthermore, phagocytosis of PrP-ferritin aggregates by astrocytes is cytoprotective, while culture in astrocyte conditioned medium (CM) shows no measurable effect. Exposure to H(2)O(2), on the other hand, does not cause aggregation of PrP, and cells show acute toxicity that is alleviated by CM.These observations suggest that aggregation of PrP in response to redox-iron is cytoprotective. However, subsequent co-aggregation of PrP with ferritin induces intracellular toxicity unless the aggregates are degraded by autophagosomes or phagocytosed by adjacent scavenger cells. H(2)O(2), on the other hand, does not cause aggregation of PrP, and induces toxicity through extra-cellular free radicals. Together with previous observations demonstrating imbalance of iron homeostasis in prion disease affected brains, these observations provide insight into the mechanism of neurotoxicity by redox-iron, and the role of PrP in this process

Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology

Genome-wide association studies have uncovered hundreds of DNA changes associated with complex disease. The ultimate promise of these studies is the understanding of disease biology; this goal, however, is not easily achieved because each disease has yielded numerous associations, each one pointing to a region of the genome, rather than a specific causal mutation. Presumably, the causal variants affect components of common molecular processes, and a first step in understanding the disease biology perturbed in patients is to identify connections among regions associated to disease. Since it has been reported in numerous Mendelian diseases that protein products of causal genes tend to physically bind each other, we chose to approach this problem using known protein–protein interactions to test whether any of the products of genes in five complex trait-associated loci bind each other. We applied several permutation methods and find robustly significant connectivity within four of the traits. In Crohn's disease and rheumatoid arthritis, we are able to show that these genes are co-expressed and that other proteins emerging in the network are enriched for association to disease. These findings suggest that, for the complex traits studied here, associated loci contain variants that affect common molecular processes, rather than distinct mechanisms specific to each association.Massachusetts Institute of Technology (MIT IDEA2 Program)Harvard University. Biological and Biomedical Sciences ProgramEunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (NICHD RO1 grant HD055150-03)National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (K08 NIH-NIAMS career development award (AR055688))National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (DK083756)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (DK086502)Denmark. Forskningsradet for Sundhed og SygdomCenter for the Study of Inflammatory Bowel Diseas

Integration of sequence data from a consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene

Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.2263G>C (p.G755R) mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009). We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2×10-6). Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry), and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT). Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted. © 2014 Plenge et al

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here, we performed a genome-wide association study (GWAS) meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single nucleotide polymorphisms (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 1012–4. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci (cis-eQTL)6, and pathway analyses7–9 – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out mouse phenotypes – to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery

Association of response to TNF inhibitors in rheumatoid arthritis with quantitative trait loci for CD40 and CD39

This study was supported by Medical Research Council (MRC) MR/K015346/1 MATURA study. ARUK 20670 MATURA study. Publisher Copyright: © Author(s) (or their employer(s)) 2019.Objectives We sought to investigate whether genetic effects on response to TNF inhibitors (TNFi) in rheumatoid arthritis (RA) could be localised by considering known genetic susceptibility loci for relevant traits and to evaluate the usefulness of these genetic loci for stratifying drug response. Methods We studied the relation of TNFi response, quantified by change in swollen joint counts (ΔSJC) and erythrocyte sedimentation rate (ΔESR) with locus-specific scores constructed from genome-wide assocation study summary statistics in 2938 genotyped individuals: 37 scores for RA; scores for 19 immune cell traits; scores for expression or methylation of 93 genes with previously reported associations between transcript level and drug response. Multivariate associations were evaluated in penalised regression models by cross-validation. Results We detected a statistically significant association between ΔSJC and the RA score at the CD40 locus (p=0.0004) and an inverse association between ΔSJC and the score for expression of CD39 on CD4 T cells (p=0.00005). A previously reported association between CD39 expression on regulatory T cells and response to methotrexate was in the opposite direction. In stratified analysis by concomitant methotrexate treatment, the inverse association was stronger in the combination therapy group and dissipated in the TNFi monotherapy group. Overall, ability to predict TNFi response from genotypic scores was limited, with models explaining less than 1% of phenotypic variance. Conclusions The association with the CD39 trait is difficult to interpret because patients with RA are often prescribed TNFi after failing to respond to methotrexate. The CD39 and CD40 pathways could be relevant for targeting drug therapy.Peer reviewe