Characterising encapsulated nuclear waste using cosmic-ray muon tomography

Tomographic imaging techniques using the Coulomb scattering of cosmic-ray muons have been shown previously to successfully identify and characterise low- and high-Z materials within an air matrix using a prototype scintillating-fibre tracker system. Those studies were performed as the first in a series to assess the feasibility of this technology and image reconstruction techniques in characterising the potential high-Z contents of legacy nuclear waste containers for the UK Nuclear Industry. The present work continues the feasibility study and presents the first images reconstructed from experimental data collected using this small-scale prototype system of low- and high-Z materials encapsulated within a concrete-filled stainless-steel container. Clear discrimination is observed between the thick steel casing, the concrete matrix and the sample materials assayed. These reconstructed objects are presented and discussed in detail alongside the implications for future industrial scenarios.Comment: 6 pages, 4 figure

CO I Barcoding Reveals New Clades and Radiation Patterns of Indo-Pacific Sponges of the Family Irciniidae (Demospongiae: Dictyoceratida)

DNA barcoding is a promising tool to facilitate a rapid and unambiguous identification of sponge species. Demosponges of the order Dictyoceratida are particularly challenging to identify, but are of ecological as well as biochemical importance.Here we apply DNA barcoding with the standard CO1-barcoding marker on selected Indo-Pacific specimens of two genera, Ircinia and Psammocinia of the family Irciniidae. We show that the CO1 marker identifies several species new to science, reveals separate radiation patterns of deep-sea Ircinia sponges and indicates dispersal patterns of Psammocinia species. However, some species cannot be unambiguously barcoded by solely this marker due to low evolutionary rates.We support previous suggestions for a combination of the standard CO1 fragment with an additional fragment for sponge DNA barcoding

Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015-16: a modelling study.

BACKGROUND: Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. METHODS: We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. FINDINGS: The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34-0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52-0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13-0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92-0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. INTERPRETATION: Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. FUNDING: Wellcome Trust

Red Blood Cell Fatty Acid Patterns and Acute Coronary Syndrome

BACKGROUND:Assessment of coronary heart disease (CHD) risk is typically based on a weighted combination of standard risk factors. We sought to determine the extent to which a lipidomic approach based on red blood cell fatty acid (RBC-FA) profiles could discriminate acute coronary syndrome (ACS) cases from controls, and to compare RBC-FA discrimination with that based on standard risk factors. METHODOLOGY/PRINCIPAL FINDINGS:RBC-FA profiles were measured in 668 ACS cases and 680 age-, race- and gender-matched controls. Multivariable logistic regression models based on FA profiles (FA) and standard risk factors (SRF) were developed on a random 2/3(rds) derivation set and validated on the remaining 1/3(rd). The area under receiver operating characteristic (ROC) curves (c-statistics), misclassification rates, and model calibrations were used to evaluate the individual and combined models. The FA discriminated cases from controls better than the SRF (c = 0.85 vs. 0.77, p = 0.003) and the FA profile added significantly to the standard model (c = 0.88 vs. 0.77, p<0.0001). Hosmer-Lemeshow calibration was poor for the FA model alone (p = 0.01), but acceptable for both the SRF (p = 0.30) and combined models (p = 0.22). Misclassification rates were 23%, 29% and 20% for FA, the SRF, and the combined models, respectively. CONCLUSIONS/SIGNIFICANCE:RBC-FA profiles contribute significantly to the discrimination of ACS cases, especially when combined with standard risk factors. The utility of FA patterns in risk prediction warrants further investigation

HIV-1 co-receptor usage:influence on mother-to-child transmission and pediatric infection

Viral CCR5 usage is not a predictive marker of mother to child transmission (MTCT) of HIV-1. CXCR4-using viral variants are little represented in pregnant women, have an increased although not significant risk of transmission and can be eventually also detected in the neonates. Genetic polymorphisms are more frequently of relevance in the child than in the mother. However, specific tissues as the placenta or the intestine, which are involved in the prevalent routes of infection in MTCT, may play an important role of selective barriers

Pathogenic variants in SLF2 and SMC5 cause segmented chromosomes and mosaic variegated hyperploidy

Embryonic development is dictated by tight regulation of DNA replication, cell division and differentiation. Mutations in DNA repair and replication genes disrupt this equilibrium, giving rise to neurodevelopmental disease characterized by microcephaly, short stature and chromosomal breakage. Here, we identify biallelic variants in two components of the RAD18-SLF1/2-SMC5/6 genome stability pathway, SLF2 and SMC5, in 11 patients with microcephaly, short stature, cardiac abnormalities and anemia. Patient-derived cells exhibit a unique chromosomal instability phenotype consisting of segmented and dicentric chromosomes with mosaic variegated hyperploidy. To signify the importance of these segmented chromosomes, we have named this disorder Atelís (meaning - incomplete) Syndrome. Analysis of Atelís Syndrome cells reveals elevated levels of replication stress, partly due to a reduced ability to replicate through G-quadruplex DNA structures, and also loss of sister chromatid cohesion. Together, these data strengthen the functional link between SLF2 and the SMC5/6 complex, highlighting a distinct role for this pathway in maintaining genome stability

The Human Serum Metabolome

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca