A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

Objective quantification of nanoscale protein distributions

Nanoscale distribution of molecules within small subcellular compartments of neurons critically influences their functional roles. Although, numerous ways of analyzing the spatial arrangement of proteins have been described, a thorough comparison of their effectiveness is missing. Here we present an open source software, GoldExt, with a plethora of measures for quantification of the nanoscale distribution of proteins in subcellular compartments (e.g. synapses) of nerve cells. First, we compared the ability of five different measures to distinguish artificial uniform and clustered patterns from random point patterns. Then, the performance of a set of clustering algorithms was evaluated on simulated datasets with predefined number of clusters. Finally, we applied the best performing methods to experimental data, and analyzed the nanoscale distribution of different pre- and postsynaptic proteins, revealing random, uniform and clustered sub-synaptic distribution patterns. Our results reveal that application of a single measure is sufficient to distinguish between different distributions

Immunological predictors of CD4+ T cell decline in antiretroviral treatment interruptions

<p>Abstract</p> <p>Background</p> <p>The common response to stopping anti-HIV treatment is an increase of HIV-RNA load and decrease in CD4⁺, but not all the patients have similar responses to this therapeutic strategy. The aim was to identify predictive markers of CD4⁺cell count declines to < 350/μL in CD4-guided antiretroviral treatment interruptions.</p> <p>Methods</p> <p>27 HIV-infected patients participated in a prospective multicenter study in with a 24 month follow-up. Patients on stable highly active antiretroviral therapy (HAART), with CD4⁺count > 600/μL, and HIV-RNA < 50 copies/ml for at least 6 months were offered the option to discontinue antiretroviral therapy. The main outcome was a decline in CD4⁺cell count to < 350/μL.</p> <p>Results</p> <p>After 24 months of follow-up, 16 of 27 (59%) patients (who discontinued therapy) experienced declines in CD4⁺cell count to < 350/μL. Patients with a CD4⁺nadir of < 200 cells/μL had a greater risk of restarting therapy during the follow-up (RR (CI95%): 3.37 (1.07; 10.36)). Interestingly, lymphoproliferative responses to <it>Mycobacterium tuberculosis </it>purified protein derivative (PPD) below 10000 c.p.m. at baseline (4.77 (1.07; 21.12)), IL-4 production above 100 pg/mL at baseline (5.95 (1.76; 20.07)) in PBMC cultured with PPD, and increased IL-4 production of PBMC with p24 antigen at baseline (1.25 (1.01; 1.55)) were associated to declines in CD4⁺cell count to < 350/μL.</p> <p>Conclusion</p> <p>Both the number (CD4⁺nadir) and the functional activity of CD4⁺(lymphoproliferative response to PPD) predict the CD4⁺decrease associated with discontinuation of ART in patients with controlled viremia.</p

Modeling the evolution of a classic genetic switch

Abstract Background The regulatory network underlying the yeast galactose-use pathway has emerged as a model system for the study of regulatory network evolution. Evidence has recently been provided for adaptive evolution in this network following a whole genome duplication event. An ancestral gene encoding a bi-functional galactokinase and co-inducer protein molecule has become subfunctionalized as paralogous genes (GAL1 and GAL3) in Saccharomyces cerevisiae, with most fitness gains being attributable to changes in cis- regulatory elements. However, the quantitative functional implications of the evolutionary changes in this regulatory network remain unexplored. Results We develop a modeling framework to examine the evolution of the GAL regulatory network. This enables us to translate molecular changes in the regulatory network to changes in quantitative network function. We computationally reconstruct an inferred ancestral version of the network and trace the evolutionary paths in the lineage leading to S. cerevisiae. We explore the evolutionary landscape of possible regulatory networks and find that the operation of intermediate networks leading to S. cerevisiae differs substantially depending on the order in which evolutionary changes accumulate; in particular, we systematically explore evolutionary paths and find that some network features cannot be optimized simultaneously. Conclusions We find that a computational modeling approach can be used to analyze the evolution of a well-studied regulatory network. Our results are consistent with several experimental studies of the evolutionary of the GAL regulatory network, including increased fitness in Saccharomyces due to duplication and adaptive regulatory divergence. The conceptual and computational tools that we have developed may be applicable in further studies of regulatory network evolution

Association Analysis of the Extended MHC Region in Celiac Disease Implicates Multiple Independent Susceptibility Loci

Celiac disease is a common autoimmune disease caused by sensitivity to the dietary protein gluten. Forty loci have been implicated in the disease. All disease loci have been characterized as low-penetrance, with the exception of the high-risk genotypes in the HLA-DQA1 and HLA-DQB1 genes, which are necessary but not sufficient to cause the disease. The very strong effects from the known HLA loci and the genetically complex nature of the major histocompatibility complex (MHC) have precluded a thorough investigation of the region. The purpose of this study was to test the hypothesis that additional celiac disease loci exist within the extended MHC (xMHC). A set of 1898 SNPs was analyzed for association across the 7.6 Mb xMHC region in 1668 confirmed celiac disease cases and 517 unaffected controls. Conditional recursive partitioning was used to create an informative indicator of the known HLA-DQA1 and HLA-DQB1 high-risk genotypes that was included in the association analysis to account for their effects. A linkage disequilibrium-based grouping procedure was utilized to estimate the number of independent celiac disease loci present in the xMHC after accounting for the known effects. There was significant statistical evidence for four new independent celiac disease loci within the classic MHC region. This study is the first comprehensive association analysis of the xMHC in celiac disease that specifically accounts for the known HLA disease genotypes and the genetic complexity of the region

Deficits in Inhibitory Control in Smokers During a Go/NoGo Task: An Investigation Using Event-Related Brain Potentials

Contains fulltext : 119553.pdf (publisher's version ) (Open Access)Introduction: The role of inhibitory control in addictive behaviors is highlighted in several models of addictive behaviors. Although reduced inhibitory control has been observed in addictive behaviors, it is inconclusive whether this is evident in smokers. Furthermore, it has been proposed that drug abuse individuals with poor response inhibition may experience greater difficulties not consuming substances in the presence of drug cues. The major aim of the current study was to provide electrophysiological evidence for reduced inhibitory control in smokers and to investigate whether this is more pronounced during smoking cue exposure. Methods: Participants (19 smokers and 20 non-smoking controls) performed a smoking Go/NoGo task. Behavioral accuracy and amplitudes of the N2 and P3 event-related potential (ERP), both reflecting aspects of response inhibition, were the main variables of interest. Results: Reduced NoGo N2 amplitudes in smokers relative to controls were accompanied by decreased task performance, whereas no differences between groups were found in P3 amplitudes. This was found to represent a general lack of inhibition in smokers, and not dependent on the presence of smoking cues. Conclusions: The current results suggest that smokers have difficulties with response inhibition, which is an important finding that eventually can be implemented in smoking cessation programs. More research is needed to clarify the exact role of cue exposure on response inhibition.7 p

Advances in exosome therapies in ophthalmology–From bench to clinical trial

During the last decade, the fields of advanced and personalized therapeutics have been constantly evolving, utilizing novel techniques such as gene editing and RNA therapeutic approaches. However, the method of delivery and tissue specificity remain the main hurdles of these approaches. Exosomes are natural carriers of functional small RNAs and proteins, representing an area of increasing interest in the field of drug delivery. It has been demonstrated that the exosome cargo, especially miRNAs, is at least partially responsible for the therapeutic effects of exosomes. Exosomes deliver their luminal content to the recipient cells and can be used as vesicles for the therapeutic delivery of RNAs and proteins. Synthetic therapeutic drugs can also be encapsulated into exosomes as they have a hydrophilic core, which makes them suitable to carry water-soluble drugs. In addition, engineered exosomes can display a variety of surface molecules, such as peptides, to target specific cells in tissues. The exosome properties present an added advantage to the targeted delivery of therapeutics, leading to increased efficacy and minimizing the adverse side effects. Furthermore, exosomes are natural nanoparticles found in all cell types and as a result, they do not elicit an immune response when administered. Exosomes have also demonstrated decreased long-term accumulation in tissues and organs and thus carry a low risk of systemic toxicity. This review aims to discuss all the advances in exosome therapies in ophthalmology and to give insight into the challenges that would need to be overcome before exosome therapies can be translated into clinical practice

Molecular mechanisms of severe acute respiratory syndrome (SARS)

Severe acute respiratory syndrome (SARS) is a new infectious disease caused by a novel coronavirus that leads to deleterious pulmonary pathological features. Due to its high morbidity and mortality and widespread occurrence, SARS has evolved as an important respiratory disease which may be encountered everywhere in the world. The virus was identified as the causative agent of SARS due to the efforts of a WHO-led laboratory network. The potential mutability of the SARS-CoV genome may lead to new SARS outbreaks and several regions of the viral genomes open reading frames have been identified which may contribute to the severe virulence of the virus. With regard to the pathogenesis of SARS, several mechanisms involving both direct effects on target cells and indirect effects via the immune system may exist. Vaccination would offer the most attractive approach to prevent new epidemics of SARS, but the development of vaccines is difficult due to missing data on the role of immune system-virus interactions and the potential mutability of the virus. Even in a situation of no new infections, SARS remains a major health hazard, as new epidemics may arise. Therefore, further experimental and clinical research is required to control the disease