Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.

The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits

Open defecation and childhood stunting in India: an ecological analysis of new data from 112 districts.

Poor sanitation remains a major public health concern linked to several important health outcomes; emerging evidence indicates a link to childhood stunting. In India over half of the population defecates in the open; the prevalence of stunting remains very high. Recently published data on levels of stunting in 112 districts of India provide an opportunity to explore the relationship between levels of open defecation and stunting within this population. We conducted an ecological regression analysis to assess the association between the prevalence of open defecation and stunting after adjustment for potential confounding factors. Data from the 2011 HUNGaMA survey was used for the outcome of interest, stunting; data from the 2011 Indian Census for the same districts was used for the exposure of interest, open defecation. After adjustment for various potential confounding factors--including socio-economic status, maternal education and calorie availability--a 10 percent increase in open defecation was associated with a 0.7 percentage point increase in both stunting and severe stunting. Differences in open defecation can statistically account for 35 to 55 percent of the average difference in stunting between districts identified as low-performing and high-performing in the HUNGaMA data. In addition, using a Monte Carlo simulation, we explored the effect on statistical power of the common practice of dichotomizing continuous height data into binary stunting indicators. Our simulation showed that dichotomization of height sacrifices statistical power, suggesting that our estimate of the association between open defecation and stunting may be a lower bound. Whilst our analysis is ecological and therefore vulnerable to residual confounding, these findings use the most recently collected large-scale data from India to add to a growing body of suggestive evidence for an effect of poor sanitation on human growth. New intervention studies, currently underway, may shed more light on this important issue

A Fluorescent Probe for Diacetyl Detection

A water-soluble fluorescent probe, rhodamine B hydrazide (RBH), was prepared and its properties for recognition of diacetyl were studied. The method employs the reaction of diacetyl with RBH, a colorless and non-fluorescent rhodamine B spiro form derivative to give a pink-colored fluorescent substance. In weakly acidic media, RBH reacts more selectively with diacetyl than with other carbonyls, causing a large increase in fluorescence intensity and thereby providing an easy assay for the determination of diacetyl

MAGIC observations of MWC 656, the only known Be/BH system

Context: MWC 656 has recently been established as the first observationally detected high-mass X-ray binary system containing a Be star and a black hole (BH). The system has been associated with a gamma-ray flaring event detected by the AGILE satellite in July 2010. Aims: Our aim is to evaluate if the MWC 656 gamma-ray emission extends to very high energy (VHE > 100 GeV) gamma rays. Methods. We have observed MWC 656 with the MAGIC telescopes for $\sim$23 hours during two observation periods: between May and June 2012 and June 2013. During the last period, observations were performed contemporaneously with X-ray (XMM-Newton) and optical (STELLA) instruments. Results: We have not detected the MWC 656 binary system at TeV energies with the MAGIC Telescopes in either of the two campaigns carried out. Upper limits (ULs) to the integral flux above 300 GeV have been set, as well as differential ULs at a level of $\sim$5% of the Crab Nebula flux. The results obtained from the MAGIC observations do not support persistent emission of very high energy gamma rays from this system at a level of 2.4% the Crab flux.Comment: Accepted for publication in A&A. 5 pages, 2 figures, 2 table

Breakfast Staple Types Affect Brain Gray Matter Volume and Cognitive Function in Healthy Children

Childhood diet is important for brain development. Furthermore, the quality of breakfast is thought to affect the cognitive functioning of well-nourished children. To analyze the relationship among breakfast staple type, gray matter volume, and intelligence quotient (IQ) in 290 healthy children, we used magnetic resonance images and applied voxel-based morphometry. We divided subjects into rice, bread, and both groups according to their breakfast staple. We showed that the rice group had a significantly larger gray matter ratio (gray matter volume percentage divided by intracranial volume) and significantly larger regional gray matter volumes of several regions, including the left superior temporal gyrus. The bread group had significantly larger regional gray and white matter volumes of several regions, including the right frontoparietal region. The perceptual organization index (POI; IQ subcomponent) of the rice group was significantly higher than that of the bread group. All analyses were adjusted for age, gender, intracranial volume, socioeconomic status, average weekly frequency of having breakfast, and number of side dishes eaten for breakfast. Although several factors may have affected the results, one possible mechanism underlying the difference between the bread and the rice groups may be the difference in the glycemic index (GI) of these two substances; foods with a low GI are associated with less blood-glucose fluctuation than are those with a high GI. Our study suggests that breakfast staple type affects brain gray and white matter volumes and cognitive function in healthy children; therefore, a diet of optimal nutrition is important for brain maturation during childhood and adolescence

Configuring Balanced Scorecards for Measuring Health System Performance: Evidence from 5 Years' Evaluation in Afghanistan

Anbrasi Edward and colleagues report the results of a balanced scorecard performance system used to examine 29 key performance indicators over a 5-year period in Afghanistan, between 2004 and 2008

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Targeted sequencing of lung function loci in chronic obstructive pulmonary disease cases and controls

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide; smoking is the main risk factor for COPD, but genetic factors are also relevant contributors. Genome-wide association studies (GWAS) of the lung function measures used in the diagnosis of COPD have identified a number of loci, however association signals are often broad and collectively these loci only explain a small proportion of the heritability. In order to examine the association with COPD risk of genetic variants down to low allele frequencies, to aid fine-mapping of association signals and to explain more of the missing heritability, we undertook a targeted sequencing study in 300 COPD cases and 300 smoking controls for 26 loci previously reported to be associated with lung function. We used a pooled sequencing approach, with 12 pools of 25 individuals each, enabling high depth (30x) coverage per sample to be achieved. This pooled design maximised sample size and therefore power, but led to challenges during variant-calling since sequencing error rates and minor allele frequencies for rare variants can be very similar. For this reason we employed a rigorous quality control pipeline for variant detection which included the use of 3 independent calling algorithms. In order to avoid false positive associations we also developed tests to detect variants with potential batch effects and removed them before undertaking association testing. We tested for the effects of single variants and the combined effect of rare variants within a locus. We followed up the top signals with data available (only 67% of collapsing methods signals) in 4,249 COPD cases and 11,916 smoking controls from UK Biobank. We provide suggestive evidence for the combined effect of rare variants on COPD risk in TNXB and in sliding windows within MECOM and upstream of HHIP. These findings can lead to an improved understanding of the molecular pathways involved in the development of COPD