Uptake of home-based voluntary HIV testing in sub-Saharan Africa: a systematic review and meta-analysis

Improving access to HIV testing is a key priority in scaling up HIV treatment and prevention services. Home-based voluntary counselling and testing (HBT) as an approach to delivering wide-scale HIV testing is explored here

A bovine lymphosarcoma cell line infected with theileria annulata exhibits an irreversible reconfiguration of host cell gene expression

Theileria annulata, an intracellular parasite of bovine lymphoid cells, induces substantial phenotypic alterations to its host cell including continuous proliferation, cytoskeletal changes and resistance to apoptosis. While parasite induced modulation of host cell signal transduction pathways and NFκB activation are established, there remains considerable speculation on the complexities of the parasite directed control mechanisms that govern these radical changes to the host cell. Our objectives in this study were to provide a comprehensive analysis of the global changes to host cell gene expression with emphasis on those that result from direct intervention by the parasite. By using comparative microarray analysis of an uninfected bovine cell line and its Theileria infected counterpart, in conjunction with use of the specific parasitacidal agent, buparvaquone, we have identified a large number of host cell gene expression changes that result from parasite infection. Our results indicate that the viable parasite can irreversibly modify the transformed phenotype of a bovine cell line. Fifty percent of genes with altered expression failed to show a reversible response to parasite death, a possible contributing factor to initiation of host cell apoptosis. The genes that did show an early predicted response to loss of parasite viability highlighted a sub-group of genes that are likely to be under direct control by parasite infection. Network and pathway analysis demonstrated that this sub-group is significantly enriched for genes involved in regulation of chromatin modification and gene expression. The results provide evidence that the Theileria parasite has the regulatory capacity to generate widespread change to host cell gene expression in a complex and largely irreversible manner

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system

Emission of volatile halogenated compounds, speciation and localization of bromine and iodine in the brown algal genome model Ectocarpus siliculosus

This study explores key features of bromine and iodine metabolism in the filamentous brown alga and genomics model Ectocarpus siliculosus. Both elements are accumulated in Ectocarpus, albeit at much lower concentration factors (2-3 orders of magnitude for iodine, and < 1 order of magnitude for bromine) than e.g. in the kelp Laminaria digitata. Iodide competitively reduces the accumulation of bromide. Both iodide and bromide are accumulated in the cell wall (apoplast) of Ectocarpus, with minor amounts of bromine also detectable in the cytosol. Ectocarpus emits a range of volatile halogenated compounds, the most prominent of which by far is methyl iodide. Interestingly, biosynthesis of this compound cannot be accounted for by vanadium haloperoxidase since the latter have not been found to catalyze direct halogenation of an unactivated methyl group or hydrocarbon so a methyl halide transferase-type production mechanism is proposed

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells

Outer membrane protein folding from an energy landscape perspective

The cell envelope is essential for the survival of Gram-negative bacteria. This specialised membrane is densely packed with outer membrane proteins (OMPs), which perform a variety of functions. How OMPs fold into this crowded environment remains an open question. Here, we review current knowledge about OFMP folding mechanisms in vitro and discuss how the need to fold to a stable native state has shaped their folding energy landscapes. We also highlight the role of chaperones and the β-barrel assembly machinery (BAM) in assisting OMP folding in vivo and discuss proposed mechanisms by which this fascinating machinery may catalyse OMP folding

Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance.

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies

Control of bovine mastitis: old and recent therapeutic approaches

Mastitis is defined as the inflammatory response resulting of the infection of the udder tissue and it is reported in numerous species, namely in domestic dairy animals. This pathology is the most frequent disease of dairy cattle and can be potentially fatal. Mastitis is an economically important pathology associated with reduced milk production, changes in milk composition and quality, being considered one of the most costly to dairy industry. Therefore, the majority of research in the field has focused on control of bovine mastitis and many efforts are being made for the development of new and effective anti-mastitis drugs. Antibiotic treatment is an established component of mastitis control programs; however, the continuous search for new therapeutic alternatives, effective in the control and treatment of bovine mastitis, is urgent. This review will provide an overview of some conventional and emerging approaches in the management of bovine mastitis infections.F. Gomes acknowledge the financial support of the Portuguese Foundation for Science and Technology through the Grant SFRH/BPD/84488/2012 and for financial support to the CEB research center

The Generation R Study Biobank: a resource for epidemiological studies in children and their parents

The Generation R Study is a population-based prospective cohort study from fetal life until young adulthood. The study is designed to identify early environmental and genetic causes of normal and abnormal growth, development and health from fetal life until young adulthood. In total, 9,778 mothers were enrolled in the study. Prenatal and postnatal data collection is conducted by physical examinations, questionnaires, interviews, ultrasound examinations and biological samples. Major efforts have been conducted for collecting biological specimens including DNA, blood for phenotypes and urine samples. In this paper, the collection, processing and storage of these biological specimens are described. Together with detailed phenotype measurements, these biological specimens form a unique resource for epidemiological studies focused on environmental exposures, genetic determinants and their interactions in relation to growth, health and development from fetal life onwards