Monomeric ephrinB2 binding induces allosteric changes in Nipah virus G that precede its full activation.

Nipah virus is an emergent paramyxovirus that causes deadly encephalitis and respiratory infections in humans. Two glycoproteins coordinate the infection of host cells, an attachment protein (G), which binds to cell surface receptors, and a fusion (F) protein, which carries out the process of virus-cell membrane fusion. The G protein binds to ephrin B2/3 receptors, inducing G conformational changes that trigger F protein refolding. Using an optical approach based on second harmonic generation, we show that monomeric and dimeric receptors activate distinct conformational changes in G. The monomeric receptor-induced changes are not detected by conformation-sensitive monoclonal antibodies or through electron microscopy analysis of G:ephrinB2 complexes. However, hydrogen/deuterium exchange experiments confirm the second harmonic generation observations and reveal allosteric changes in the G receptor binding and F-activating stalk domains, providing insights into the pathway of receptor-activated virus entry.Nipah virus causes encephalitis in humans. Here the authors use a multidisciplinary approach to study the binding of the viral attachment protein G to its host receptor ephrinB2 and show that monomeric and dimeric receptors activate distinct conformational changes in G and discuss implications for receptor-activated virus entry

Pre-transplant CDKN2A expression in kidney biopsies predicts renal function and is a future component of donor scoring criteria

CDKN2A is a proven and validated biomarker of ageing which acts as an off switch for cell proliferation. We have demonstrated previously that CDKN2A is the most robust and the strongest pre-transplant predictor of post- transplant serum creatinine when compared to “Gold Standard” clinical factors, such as cold ischaemic time and donor chronological age. This report shows that CDKN2A is better than telomere length, the most celebrated biomarker of ageing, as a predictor of post-transplant renal function. It also shows that CDKN2A is as strong a determinant of post-transplant organ function when compared to extended criteria (ECD) kidneys. A multivariate analysis model was able to predict up to 27.1% of eGFR at one year post-transplant (p = 0.008). Significantly, CDKN2A was also able to strongly predict delayed graft function. A pre-transplant donor risk classification system based on CDKN2A and ECD criteria is shown to be feasible and commendable for implementation in the near future

Signatures of malaria-associated pathology revealed by high-resolution whole-blood transcriptomics in a rodent model of malaria.

The influence of parasite genetic factors on immune responses and development of severe pathology of malaria is largely unknown. In this study, we performed genome-wide transcriptomic profiling of mouse whole blood during blood-stage infections of two strains of the rodent malaria parasite Plasmodium chabaudi that differ in virulence. We identified several transcriptomic signatures associated with the virulent infection, including signatures for platelet aggregation, stronger and prolonged anemia and lung inflammation. The first two signatures were detected prior to pathology. The anemia signature indicated deregulation of host erythropoiesis, and the lung inflammation signature was linked to increased neutrophil infiltration, more cell death and greater parasite sequestration in the lungs. This comparative whole-blood transcriptomics profiling of virulent and avirulent malaria shows the validity of this approach to inform severity of the infection and provide insight into pathogenic mechanisms

Can spacetime curvature induced corrections to Lamb shift be observable?

The Lamb shift results from the coupling of an atom to vacuum fluctuations of quantum fields, so corrections are expected to arise when the spacetime is curved since the vacuum fluctuations are modified by the presence of spacetime curvature. Here, we calculate the curvature-induced correction to the Lamb shift outside a spherically symmetric object and demonstrate that this correction can be remarkably significant outside a compact massive astrophysical body. For instance, for a neutron star or a stellar mass black hole, the correction is $\sim$ 25% at a radial distance of $4GM/c^2$, $\sim$ 16% at $10GM/c^2$ and as large as $\sim$ 1.6% even at $100GM/c^2$, where $M$ is the mass of the object, $G$ the Newtonian constant, and $c$ the speed of light. In principle, we can look at the spectra from a distant compact super-massive body to find such corrections. Therefore, our results suggest a possible way of detecting fundamental quantum effects in astronomical observations.Comment: 13 pages, 3 figures, slight title change, clarifications and more discussions added, version to be published in JHE

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

Putting it into perspective: Mathematics in the undergraduate science curriculum

Mathematics and science are tightly interwoven, yet they are often treated as distinct disciplines in the educational context. This study details the development, implementation and outcomes of a teaching intervention that highlights the links between mathematics and science, in the form of a first-year interdisciplinary course. A mixed method study using surveys and focus groups was employed to investigate undergraduate science students' perceptions of their experiences. Findings reveal that students bring strong beliefs about the nature of mathematics and science from secondary school, which can impact significanly on the success of interdisciplinary science-mathematics courese at the teritary level. Despite this, a range of beneficial outcomes can arise from such courses when they are delivered within a framework of analysing real-world issues. However, students with weak mathematical skills derived little benefit from an interdisciplinary approach and are likely to disengage from learning, in comparision with students who enter university with a solid foundation in mathematics

Protocol for: Sheffield Obesity Trial (SHOT): A randomised controlled trial of exercise therapy and mental health outcomes in obese adolescents [ISRCNT83888112]

Background While obesity is known to have many physiological consequences, the psychopathology of this condition has not featured prominently in the literature. Cross-sectional studies have indicated that obese children have increased odds of experiencing poor quality of life and mental health. However, very limited trial evidence has examined the efficacy of exercise therapy for enhancing mental health outcomes in obese children, and the Sheffield Obesity Trial (SHOT) will provide evidence of the efficacy of supervised exercise therapy in obese young people aged 11–16 years versus usual care and an attention-control intervention. Method/design SHOT is a randomised controlled trial where obese young people are randomised to receive; (1) exercise therapy, (2) attention-control intervention (involving body-conditioning exercises and games that do not involve aerobic activity), or (3) usual care. The exercise therapy and attention-control sessions will take place three times per week for eight weeks and a six-week home programme will follow this. Ninety adolescents aged between 11–16 years referred from a children's hospital for evaluation of obesity or via community advertisements will need to complete the study. Participants will be recruited according to the following criteria: (1) clinically obese and aged 11–16 years (Body Mass Index Centile > 98th UK standard) (2) no medical condition that would restrict ability to be active three times per week for eight weeks and (3) not diagnosed with insulin dependent diabetes or receiving oral steroids. Assessments of outcomes will take place at baseline, as well as four (intervention midpoint) and eight weeks (end of intervention) from baseline. Participants will be reassessed on outcome measures five and seven months from baseline. The primary endpoint is physical self-perceptions. Secondary outcomes include physical activity, self-perceptions, depression, affect, aerobic fitness and BMI

Metabolomics profiling of visceral adipose tissue: Results From MESA and the NEO study

Background Identifying associations between serum metabolites and visceral adipose tissue ( VAT ) could provide novel biomarkers of VAT and insights into the pathogenesis of obesity-related diseases. We aimed to discover and replicate metabolites reflecting pathways related to VAT . Methods and Results Associations between fasting serum metabolites and VAT area (by computed tomography or magnetic resonance imaging) were assessed with cross-sectional linear regression of individual-level data from participants in MESA (Multi-Ethnic Study of Atherosclerosis; discovery, N=1103) and the NEO (Netherlands Epidemiology of Obesity) study (replication, N=2537). Untargeted 1H nuclear magnetic resonance metabolomics profiling of serum was performed in MESA, and metabolites were replicated in the NEO study using targeted 1H nuclear magnetic resonance spectroscopy. A total of 30 590 metabolomic spectral variables were evaluated. After adjustment for age, sex, race/ethnicity, socioeconomic status, smoking, physical activity, glucose/lipid-lowering medication, and body mass index, 2104 variables representing 24 nonlipid and 49 lipid/lipoprotein subclass metabolites remained significantly associated with VAT ( P=4.88×10-20-1.16×10-3). These included conventional metabolites, amino acids, acetylglycoproteins, intermediates of glucose and hepatic metabolism, organic acids, and subclasses of apolipoproteins, cholesterol, phospholipids, and triglycerides. Metabolites mapped to 31 biochemical pathways, including amino acid substrate use/metabolism and glycolysis/gluconeogenesis. In the replication cohort, acetylglycoproteins, branched-chain amino acids, lactate, glutamine (inversely), and atherogenic lipids remained associated with VAT ( P=1.90×10-35-8.46×10-7), with most associations remaining after additional adjustment for surrogates of VAT (glucose level, waist circumference, and serum triglycerides), reflecting novel independent associations. Conclusions We identified and replicated a metabolite panel associated with VAT in 2 community-based cohorts. These findings persisted after adjustment for body mass index and appear to define a metabolic signature of visceral adiposity

A Model-Based Analysis of GC-Biased Gene Conversion in the Human and Chimpanzee Genomes

GC-biased gene conversion (gBGC) is a recombination-associated process that favors the fixation of G/C alleles over A/T alleles. In mammals, gBGC is hypothesized to contribute to variation in GC content, rapidly evolving sequences, and the fixation of deleterious mutations, but its prevalence and general functional consequences remain poorly understood. gBGC is difficult to incorporate into models of molecular evolution and so far has primarily been studied using summary statistics from genomic comparisons. Here, we introduce a new probabilistic model that captures the joint effects of natural selection and gBGC on nucleotide substitution patterns, while allowing for correlations along the genome in these effects. We implemented our model in a computer program, called phastBias, that can accurately detect gBGC tracts about 1 kilobase or longer in simulated sequence alignments. When applied to real primate genome sequences, phastBias predicts gBGC tracts that cover roughly 0.3% of the human and chimpanzee genomes and account for 1.2% of human-chimpanzee nucleotide differences. These tracts fall in clusters, particularly in subtelomeric regions; they are enriched for recombination hotspots and fast-evolving sequences; and they display an ongoing fixation preference for G and C alleles. They are also significantly enriched for disease-associated polymorphisms, suggesting that they contribute to the fixation of deleterious alleles. The gBGC tracts provide a unique window into historical recombination processes along the human and chimpanzee lineages. They supply additional evidence of long-term conservation of megabase-scale recombination rates accompanied by rapid turnover of hotspots. Together, these findings shed new light on the evolutionary, functional, and disease implications of gBGC. The phastBias program and our predicted tracts are freely available. © 2013 Capra et al