Do Life Style Factors And Socioeconomic Variables Explain Why Black Women Have A Remarkably Higher Body Mass Index (BMI) Than White Women In The United States? Findings From The 2010 National Health Interview Survey

Objective: There are marked inequalities in body mass index (BMI), overweight, and obesity across ethnic groups. We sought to examine the extent to which lifestyle factors and socioeconomic variables explain the higher BMI in Black women compared to White women in the United States. Methods: We used data from the 2010 National Health Interview Survey (NHIS) and limited the sample to non-Hispanic Black and non-Hispanic White women (n = 9,491). We employed normal regression and compared the association of race with BMI before and after adjusting for lifestyle factors (diet, physical activity, smoking, and drinking) and socioeconomic variables (education, ratio of income to poverty threshold, occupation, and home ownership). Data analysis was performed in 2012. Results: The difference between the BMI of Black and White women decreased from 2.91 to 2.17 Kg/m2 (i.e. a decrease of 27.2%) after adjusting for lifestyle factors and socioeconomic variables. Multivariate results also showed that higher consumption of fruit/vegetables and beans, lower consumption of red meat and sugar sweetened beverages, physical activity, smoking, regular drinking, and higher socioeconomic status were associated with lower BMI. Conclusions: Lifestyle factors and socioeconomic variables explain about a quarter of the BMI inequality between Black and White women. Thus, interventions that promote healthy eating and physical activity among Blacks as well as social policies that ameliorate socioeconomic inequalities between races might be able to reduce the current BMI inequality between Black and White women

Overview of the BlockNormal Event Trigger Generator

In the search for unmodeled gravitational wave bursts, there are a variety of methods that have been proposed to generate candidate events from time series data. Block Normal is a method of identifying candidate events by searching for places in the data stream where the characteristic statistics of the data change. These change-points divide the data into blocks in which the characteristics of the block are stationary. Blocks in which these characteristics are inconsistent with the long term characteristic statistics are marked as Event-Triggers which can then be investigated by a more computationally demanding multi-detector analysis.Comment: GWDAW-8 proceedings, 6 pages, 2 figure

Hybridisation-based target enrichment of phenology genes to dissect the genetic basis of yield and adaptation in barley

Barley (Hordeum vulgare L.) is a major cereal grain widely used for livestock feed, brewing malts and human food. Grain yield is the most important breeding target for genetic improvement and largely depends on optimal timing of flowering. Little is known about the allelic diversity of genes that underlie flowering time in domesticated barley, the genetic changes that have occurred during breeding, and their impact on yield and adaptation. Here we report a comprehensive genomic assessment of a worldwide collection of 895 barley accessions based on the targeted resequencing of phenology genes. A versatile target‐capture method was used to detect genome‐wide polymorphisms in a panel of 174 flowering time‐related genes, chosen based on prior knowledge from barley, rice, and Arabidopsis thaliana. Association studies identified novel polymorphisms that accounted for observed phenotypic variation in phenology and grain yield, and explained improvements in adaptation as a result of historical breeding of Australian barley cultivars. We found that 50% of genetic variants associated with grain yield, and 67% of the plant height variation was also associated with phenology. The precise identification of favourable alleles provides a genomic basis to improve barley yield traits and to enhance adaptation for specific production areas

Organ printing as an information technology

Funding Information: This work has been sponsored by the São Paulo Research Foundation (FAPESP), The Brazilian Institute of Biofabrication (INCT-BIOFABRIS) and National Council for Scientific and Technological Development (CNPq). Publisher Copyright: © 2015 Published by Elsevier Ltd.Organ printing is defined as a layer by layer additive robotic computer-aided biofabrication of functional 3D organ constructs with using self-assembling tissue spheroids according to digital model. Information technology and computer-aided design softwares are instrumental in the transformation of virtual 3D bioimaging information about human tissue and organs into living biological reality during 3D bioprinting. Information technology enables design blueprints for bioprinting of human organs as well as predictive computer simulation both printing and post-printing processes. 3D bioprinting is now considered as an emerging information technology and the effective application of existing information technology tools and development of new technological platforms such as human tissue and organ informatics, design automation, virtual human organs, virtual organ biofabrication line, mathematical modeling and predictive computer simulations of bioprinted tissue fusion and maturation is an important technological imperative for advancing organ bioprinting.publishersversionPeer reviewe

Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL

BACKGROUND: Next-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL. RESULTS: We use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino acid alterations between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy. CONCLUSIONS: The efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat.Jose M. Barrero, Colin Cavanagh, Klara L. Verbyla, Josquin F.G. Tibbits, Arunas P. Verbyla, B. Emma Huang, Garry M. Rosewarne, Stuart Stephen, Penghao Wang, Alex Whan, Philippe Rigault, Matthew J. Hayden, and Frank Guble

Searching for gravitational waves from known pulsars

We present upper limits on the amplitude of gravitational waves from 28 isolated pulsars using data from the second science run of LIGO. The results are also expressed as a constraint on the pulsars' equatorial ellipticities. We discuss a new way of presenting such ellipticity upper limits that takes account of the uncertainties of the pulsar moment of inertia. We also extend our previous method to search for known pulsars in binary systems, of which there are about 80 in the sensitive frequency range of LIGO and GEO 600.Comment: Accepted by CQG for the proceeding of GWDAW9, 7 pages, 2 figure

Drug Screening Platform Using Human Induced Pluripotent Stem Cell-Derived Atrial Cardiomyocytes and Optical Mapping

Current drug development efforts for the treatment of atrial fibrillation are hampered by the fact that many preclinical models have been unsuccessful in reproducing human cardiac physiology and its response to medications. In this study, we demonstrated an approach using human induced pluripotent stem cell‐derived atrial and ventricular cardiomyocytes (hiPSC‐aCMs and hiPSC‐vCMs, respectively) coupled with a sophisticated optical mapping system for drug screening of atrial‐selective compounds in vitro. We optimized differentiation of hiPSC‐aCMs by modulating the WNT and retinoid signaling pathways. Characterization of the transcriptome and proteome revealed that retinoic acid pushes the differentiation process into the atrial lineage and generated hiPSC‐aCMs. Functional characterization using optical mapping showed that hiPSC‐aCMs have shorter action potential durations and faster Ca2+ handling dynamics compared with hiPSC‐vCMs. Furthermore, pharmacological investigation of hiPSC‐aCMs captured atrial‐selective effects by displaying greater sensitivity to atrial‐selective compounds 4‐aminopyridine, AVE0118, UCL1684, and vernakalant when compared with hiPSC‐vCMs. These results established that a model system incorporating hiPSC‐aCMs combined with optical mapping is well‐suited for preclinical drug screening of novel and targeted atrial selective compounds

Analysis of LIGO data for gravitational waves from binary neutron stars

We report on a search for gravitational waves from coalescing compact binary systems in the Milky Way and the Magellanic Clouds. The analysis uses data taken by two of the three LIGO interferometers during the first LIGO science run and illustrates a method of setting upper limits on inspiral event rates using interferometer data. The analysis pipeline is described with particular attention to data selection and coincidence between the two interferometers. We establish an observational upper limit of $\mathcal{R}<$1.7 \times 10^{2}$per year per Milky Way Equivalent Galaxy (MWEG), with 90coalescence rate of binary systems in which each component has a mass in the range 1--3$M_\odot$.Comment: 17 pages, 9 figure