Using rank data to estimate health state utility models

In this paper we report the estimation of conditional logistic regression models for the Health Utilities Index Mark 2 and the SF-6D, using ordinal preference data. The results are compared to the conventional regression models estimated from standard gamble data, and to the observed mean standard gamble health state valuations. For both the HUI2 and the SF-6D, the models estimated using ordinal data are broadly comparable to the models estimated on standard gamble data and the predictive performance of these models is close to that of the standard gamble models. Our research indicates that ordinal data have the potential to provide useful insights into community health state preferences. However, important questions remain

Establishment and operation of a Good Manufacturing Practice-compliant allogeneic Epstein-Barr virus (EBV)-specific cytotoxic cell bank for the treatment of EBV-associated lymphoproliferative disease

Funded by Wellcome Trust Translational Award SNBTSPeer reviewedPublisher PD

Pleasure and meaningful discourse: an overview of research issues

The concept of pleasure has emerged as a multi-faceted social and cultural phenomenon in studies of media audiences since the 1980s. In these studies different forms of pleasure have been identified as explaining audience activity and commitment. In the diverse studies pleasure has emerged as a multi-faceted social and cultural concept that needs to be contextualized carefully. Genre and genre variations, class, gender, (sub-)cultural identity and generation all seem to be instrumental in determining the kind and variety of pleasures experienced in the act of viewing. This body of research has undoubtedly contributed to a better understanding of the complexity of audience activities, but it is exactly the diversity of the concept that is puzzling and poses a challenge to its further use. If pleasure is maintained as a key concept in audience analysis that holds much explanatory power, it needs a stronger theoretical foundation. The article maps the ways in which the concept of pleasure has been used by cultural theorists, who have paved the way for its application in reception analysis, and it goes on to explore the ways in which the concept has been used in empirical studies. Central to our discussion is the division between the ‘public knowledge’ and the ‘popular culture’ projects in reception analysis which, we argue, have major implications for the way in which pleasure has come to be understood as divorced from politics, power and ideology. Finally, we suggest ways of bridging the gap between these two projects in an effort to link pleasure to the concepts of hegemony and ideology

Association of CD4 Cell Depletion and Elevated Blood and Seminal Plasma Human Immunodeficiency Virus Type 1 (HIV-1) RNA Concentrations with Genital Ulcer Disease in HIV-1-Infected Men in Malawi

CD4 cell counts and blood plasma and seminal plasma human immunodeficiency virus type 1 (HIV-1) concentrations were compared in HIV-1 RNA-seropositive men with urethritis and with or without genital ulcer disease (GUD). GUD was associated with lower CD4 cell counts (median, 258 vs. 348/μL) and increased blood plasma HIV-1 RNA (median, 240 × 103 vs. 79.4 × 103 copies/ mL). Men with nongonococcal urethritis and GUD shed significantly greater quantities of HIV-1 in semen (median, 195 × 103 vs. 4.0 × 103 copies/mL) than men with nongonococcal urethritis without GUD. These levels decreased ∽4-fold following antibiotic therapy. The results indicate an association between GUD and increased blood HIV-1 RNA levels. Increased HIV-1 in semen was demonstrated in some men with GUD; such an increase could lead to increased transmission, thus complicating interpretation of the role of the genital ulcer itself in the infectiousness of HIV. Reasons for increased HIV RNA in semen in men with GUD remain to be determine

Common genetic variants influence human subcortical brain structures

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA\u27s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way

High Levels of Human Immunodeficiency Virus Type 1 in Blood and Semen of Seropositive Men in Sub-Saharan Africa

High levels of human immunodeficiency virus type 1 (HIV-1) replication, as reflected in HIV-1 RNA concentrations in blood and semen, probably contribute to both rapid disease progression and enhanced sexual transmission. Semen and blood were collected from 49 Malawian and 61 US and Swiss (US/Swiss) HIV-1.seropositive men with similar CD4 cell counts and no urethritis or exposure to antiretroviral drugs. Median seminal plasma and blood plasma HIV-1 RNA concentrations were > 3-fold (P = .034) and 5-fold (P = .0003) higher, respectively, in the Malawian men. Similar differences were observed in subsets of the Malawian and US/Swiss study groups matched individually for CD4 cell count (P = .035 and P <.002, respectively). These observations may help explain the high rates of HIV-1 sexual transmission and accelerated HIV-1 disease progression in sub-Saharan Afric

Genetic correlation of the plasma lipidome with type 2 diabetes, prediabetes and insulin resistance in Mexican American families

Background Differential plasma concentrations of circulating lipid species are associated with pathogenesis of type 2 diabetes (T2D). Whether the wide inter-individual variability in the plasma lipidome contributes to the genetic basis of T2D is unknown. Here, we investigated the potential overlap in the genetic basis of the plasma lipidome and T2D-related traits. Results We used plasma lipidomic data (1202 pedigreed individuals, 319 lipid species representing 23 lipid classes) from San Antonio Family Heart Study in Mexican Americans. Bivariate trait analyses were used to estimate the genetic and environmental correlation of all lipid species with three T2D-related traits: risk of T2D, presence of prediabetes and homeostatic model of assessment – insulin resistance. We found that 44 lipid species were significantly genetically correlated with one or more of the three T2D-related traits. Majority of these lipid species belonged to the diacylglycerol (DAG, 17 species) and triacylglycerol (TAG, 17 species) classes. Six lipid species (all belonging to the triacylglycerol class and containing palmitate at the first position) were significantly genetically correlated with all the T2D-related traits. Conclusions Our results imply that: a) not all plasma lipid species are genetically informative for T2D pathogenesis; b) the DAG and TAG lipid classes partially share genetic basis of T2D; and c) 1-palmitate containing TAGs may provide additional insights into the genetic basis of T2D

Prediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural network

Triplet amino acids have successfully been included in feature selection to predict human-HPV protein-protein interactions (PPI). The utility of supervised learning methods is curtailed due to experimental data not being available in sufficient quantities. Improvements in machine learning techniques and features selection will enhance the study of PPI between host and pathogen.We present a comparison of a neural network model versus SVM for prediction of hostpathogen PPI based on a combination of features including: amino acid quadruplets, pairwise sequence similarity, and human interactome properties. The neural network and SVM were implemented using Python Sklearn library. The neural network model using quadruplet features and other network features outperformance the SVM model. The models are tested against published predictors and then applied to the human-B.anthracis case. Gene ontology term enrichment analysis identifies immunology response and regulation as functions of interacting proteins. For prediction of Human-viral PPI, our model (neural network) is a significant improvement in overall performance compared to a predictor using the triplets feature and achieves a good accuracy in predicting human-B.anthracis PPI