J Fluorescence

The scope of this paper is to illustrate the need for an improved quality assurance in fluorometry. For this purpose, instrumental sources of error and their influences on the reliability and comparability of fluorescence data are highlighted for frequently used photoluminescence techniques ranging from conventional macro- and microfluorometry over fluorescence microscopy and flow cytometry to microarray technology as well as in vivo fluorescence imaging. Particularly, the need for and requirements on fluorescence standards for the characterization and performance validation of fluorescence instruments, to enhance the comparability of fluorescence data, and to enable quantitative fluorescence analysis are discussed. Special emphasis is dedicated to spectral fluorescence standards and fluorescence intensity standards

Phylogenetic Dependency Networks: Inferring Patterns of CTL Escape and Codon Covariation in HIV-1 Gag

HIV avoids elimination by cytotoxic T-lymphocytes (CTLs) through the evolution of escape mutations. Although there is mounting evidence that these escape pathways are broadly consistent among individuals with similar human leukocyte antigen (HLA) class I alleles, previous population-based studies have been limited by the inability to simultaneously account for HIV codon covariation, linkage disequilibrium among HLA alleles, and the confounding effects of HIV phylogeny when attempting to identify HLA-associated viral evolution. We have developed a statistical model of evolution, called a phylogenetic dependency network, that accounts for these three sources of confounding and identifies the primary sources of selection pressure acting on each HIV codon. Using synthetic data, we demonstrate the utility of this approach for identifying sites of HLA-mediated selection pressure and codon evolution as well as the deleterious effects of failing to account for all three sources of confounding. We then apply our approach to a large, clinically-derived dataset of Gag p17 and p24 sequences from a multicenter cohort of 1144 HIV-infected individuals from British Columbia, Canada (predominantly HIV-1 clade B) and Durban, South Africa (predominantly HIV-1 clade C). The resulting phylogenetic dependency network is dense, containing 149 associations between HLA alleles and HIV codons and 1386 associations among HIV codons. These associations include the complete reconstruction of several recently defined escape and compensatory mutation pathways and agree with emerging data on patterns of epitope targeting. The phylogenetic dependency network adds to the growing body of literature suggesting that sites of escape, order of escape, and compensatory mutations are largely consistent even across different clades, although we also identify several differences between clades. As recent case studies have demonstrated, understanding both the complexity and the consistency of immune escape has important implications for CTL-based vaccine design. Phylogenetic dependency networks represent a major step toward systematically expanding our understanding of CTL escape to diverse populations and whole viral genes

Using hippocampal microRNA expression differences between mouse inbred strains to characterise miRNA function

Micro-RNAs (miRNAs) are short, single-stranded, noncoding RNAs that are involved in the regulation of protein-coding genes at the level of messenger RNA (mRNA). They are involved in the regulation of numerous traits, including developmental timing, apoptosis, immune function, and neuronal development. To better understand how the expression of the miRNAs themselves is regulated, we looked for miRNA expression differences among four mouse inbred strains, A/J, BALB/cJ, C57BL/6J, and DBA/2J, in one tissue, the hippocampus. A total of 166 miRNA RT-PCR assays were used to screen RNA pools for each strain. Twenty miRNA species that were markedly different between strains were further investigated using eight individual samples per strain, and 11 miRNAs showed significant differences across strains (p < 0.05). This is the first observation of miRNA expression differences across inbred mice strains. We conducted an in silico correlation analysis of the expression of these differentially expressed miRNAs with phenotype data and mRNA expression to better characterise the effects of these miRNAs on both phenotype and the regulation of mRNA expression. This approach has allowed us to nominate miRNAs that have potential roles in anxiety, exploration, and learning and memory

DataSHIELD: taking the analysis to the data, not the data to the analysis

Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis