Associations between socioeconomic status and environmental toxicant concentrations in adults in the USA: NHANES 2001-2010

This is the final version, also available from Elsevier via the DOI in this record.Low level chronic exposure to toxicants is associated with a range of adverse health effects. Understanding the various factors that influence the chemical burden of an individual is of critical importance to public health strategies. We investigated the relationships between socioeconomic status (SES) and bio-monitored chemical concentration in five cross-sectional waves of the U.S. National Health and Nutrition Examination Survey (NHANES).We utilised adjusted linear regression models to investigate the association between 179 toxicants and the poverty income ratio (PIR) for five NHANES waves. We then selected a subset of chemicals associated with PIR in 3 or more NHANES waves and investigated potential mediating factors using structural equation modelling.PIR was associated with 18 chemicals in 3 or more NHANES waves. Higher SES individuals had higher burdens of serum and urinary mercury, arsenic, caesium, thallium, perfluorooctanoic acid, perfluorononanoic acid, mono(carboxyoctyl) phthalate and benzophenone-3. Inverse associations were noted between PIR and serum and urinary lead and cadmium, antimony, bisphenol A and three phthalates (mono-benzyl, mono-isobutyl, mono-n-butyl). Key mediators included fish and shellfish consumption for the PIR, mercury, arsenic, thallium and perfluorononanoic acid associations. Sunscreen use was an important mediator in the benzophenone-3/PIR relationship. The association between PIR and cadmium or lead was partially mediated by smoking, occupation and diet.These results provide a comprehensive analysis of exposure patterns as a function of socioeconomic status in US adults, providing important information to guide future public health remediation measures to decrease toxicant and disease burdens within society. © 2013 Elsevier Ltd.University of ExeterEuropean Social Fund Convergence Programme for Cornwall and the Isles of ScillyEuropean Regional Development Fund Programme 2007 to 201

High urinary tungsten concentration is associated with stroke in the National Health and Nutrition Examination Survey 1999-2010.

Published onlineClinical TrialMulticenter StudyResearch Support, Non-U.S. Gov'tBACKGROUND: In recent years there has been an exponential increase in tungsten demand, potentially increasing human exposure to the metal. Currently, the toxicology of tungsten is poorly understood, but mounting evidence suggests that both the elemental metal and its alloys have cytotoxic effects. Here, we investigate the association between tungsten and cardiovascular disease (CVD) or stroke using six waves of the National Health and Nutrition Examination Survey (NHANES). METHODS: We investigated associations using crude and adjusted logistic regression models in a cohort of 8614 adults (18-74 years) with 193 reported stroke diagnoses and 428 reported diagnoses of CVD. We also stratified our data to characterize associations in a subset of younger individuals (18-50 years). RESULTS: Elevated tungsten concentrations were strongly associated with an increase in the prevalence of stroke, independent of typical risk factors (Odds Ratio (OR): 1.66, 95% Confidence Interval (95% CI): 1.17, 2.34). The association between tungsten and stroke in the young age category was still evident (OR: 2.17, 95% CI: 1.33, 3.53). CONCLUSION: This study represents the most comprehensive analysis of the human health effects of tungsten to date. Individuals with higher urinary tungsten concentrations have double the odds of reported stroke. We hypothesize that the pathological pathway resulting from tungsten exposure may involve oxidative stress.This work was supported by funding from University of Exeter Medical School. No funding organization or sponsor played any part in the design or conduct of the study, in the analysis or interpretation of the data, or preparation, review, or approval of the manuscript. The European Centre for the Environment and Human Health (part of the University of Exeter Medical School) is supported by investment from the ERDF (European Regional Development Fund) and ESF (European Social Fund) Convergence Programmed for Cornwall and the Isles of Scilly. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Urinary bisphenol a concentration and angiography-defined coronary artery stenosis.

PublishedResearch Support, Non-U.S. Gov'tThis is the final version of the article. Available from PLoS via the DOI in this record.BACKGROUND: Bisphenol A is widely used in food and drinks packaging. There is evidence of associations between raised urinary bisphenol A (uBPA) and increased incidence of reported cardiovascular diagnoses. METHODOLOGY/PRINCIPAL FINDINGS: To estimate associations between BPA exposure and angiographically graded coronary atherosclerosis. 591 patients participating in The Metabonomics and Genomics in Coronary Artery Disease (MaGiCAD) study in Cambridgeshire UK, comparing urinary BPA (uBPA) with grades of severity of coronary artery disease (CAD) on angiography. Linear models were adjusted for BMI, occupational social class and diabetes status. Severe (one to three vessel) CAD was present in 385 patients, 86 had intermediate disease (n=86) and 120 had normal coronary arteries. The (unadjusted) median uBPA concentration was 1.28 ng/mL with normal coronary arteries, and 1.53 ng/mL with severe CAD. Compared to those with normal coronary arteries, uBPA concentration was significantly higher in those with severe CAD (OR per uBPA SD=5.96 ng/ml OR=1.43, CI 1.03 to 1.98, p=0.033), and near significant for intermediate disease (OR=1.69, CI 0.98 to 2.94, p=0.061). There was no significant uBPA difference between patients with severe CAD (needing surgery) and the remaining groups combined. CONCLUSIONS/SIGNIFICANCE: BPA exposure was higher in those with severe coronary artery stenoses compared to those with no vessel disease. Larger studies are needed to estimate true dose response relationships. The mechanisms underlying the association remain to be established.David Melzer and Tamara Galloway’s work on BPA has been supported by unrestricted funds from the University of Exeter (www.exeter.ac.uk), the Peninsula Clinical Research facility (www.peninsulacrf.org) and by grant funding from the British Heart Foundation (www.bhf.org.uk - grant reference PG/09/097). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Protein content prediction in single wheat kernels using hyperspectral imaging

Hyperspectral imaging (HSI) combines Near-infrared (NIR) spectroscopy and digital imaging to give information about the chemical properties of objects and their spatial distribution. Protein content is one of the most important quality factors in wheat. It is known to vary widely depending on the cultivar, agronomic and climatic conditions. However, little information is known about single kernel protein variation within batches. The aim of the present work was to measure the distribution of protein content in whole wheat kernels on a single kernel basis, and to apply HSI to predict this distribution. Wheat samples from 2013 and 2014 harvests were sourced from UK millers and wheat breeders, and individual kernels were analysed by HSI and by the Dumas combustion method for total protein content. HSI was applied in the spectral region 980-2500 nm in reflectance mode using the push-broom approach. Single kernel spectra were used to develop partial least squares (PLS) regression models for protein prediction of intact single grains. The protein content ranged from 6.2 to 19.8% (“as-is” basis), with significantly higher values for hard wheats. The performance of the calibration model was evaluated using the coefficient of determination (R2) and the root mean square error (RMSE) from 3250 samples used for calibration and 868 used for external validation. The calibration performance for single kernel protein content was R2 of 0.82 and 0.79, and RMSE of 0.86 and 0.94% for the calibration and validation dataset, enabling quantification of the protein distribution between kernels and even visualisation within the same kernel. The performance of the single kernel measurement was poorer than that typically obtained for bulk samples, but is acceptable for some specific applications. The use of separate calibrations built by separating hard and soft wheat, or on kernels placed on similar orientation did not greatly improve the prediction ability. We simulated the use of the lower cost InGaAs detector (1000-1700 nm), and reported that the use of proposed HgCdTe detectors over a restricted spectral range gave a lower prediction error (RMSEC=0.86% vs 1.06%, for HgCdTe and InGaAs, respectively), and 26 increased R2 value (Rc2=0.82 vs 0.73)

The ontogeny of bumblebee flight trajectories: From naïve explorers to experienced foragers

Understanding strategies used by animals to explore their landscape is essential to predict how they exploit patchy resources, and consequently how they are likely to respond to changes in resource distribution. Social bees provide a good model for this and, whilst there are published descriptions of their behaviour on initial learning flights close to the colony, it is still unclear how bees find floral resources over hundreds of metres and how these flights become directed foraging trips. We investigated the spatial ecology of exploration by radar tracking bumblebees, and comparing the flight trajectories of bees with differing experience. The bees left the colony within a day or two of eclosion and flew in complex loops of ever-increasing size around the colony, exhibiting Lévy-flight characteristics constituting an optimal searching strategy. This mathematical pattern can be used to predict how animals exploring individually might exploit a patchy landscape. The bees’ groundspeed, maximum displacement from the nest and total distance travelled on a trip increased significantly with experience. More experienced bees flew direct paths, predominantly flying upwind on their outward trips although forage was available in all directions. The flights differed from those of naïve honeybees: they occurred at an earlier age, showed more complex looping, and resulted in earlier returns of pollen to the colony. In summary bumblebees learn to find home and food rapidly, though phases of orientation, learning and searching were not easily separable, suggesting some multi-tasking

Detection of multipartite entanglement with two-body correlations

We show how to detect entanglement with criteria built from simple two-body correlation terms. Since many natural Hamiltonians are sums of such correlation terms, our ideas can be used to detect entanglement by energy measurement. Our criteria can straightforwardly be applied for detecting different forms of multipartite entanglement in familiar spin models in thermal equilibrium.Comment: 5 pages including 2 figures, LaTeX; for the proceedings of the DPG spring meeting, Berlin, March 200

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Are social innovation paradigms incommensurable?

This paper calls attention to the problematic use of the concept of social innovation which remains undefined despite its proliferation throughout academic and policy discourses. Extant research has thus far failed to capture the socio-political contentions which surround social innovation. This paper therefore draws upon the work of Thomas Kuhn and conducts a paradigmatic analysis of the field of social innovation which identifies two emerging schools: one technocratic, the other democratic. The paper identifies some of the key thinkers in each paradigm and explains how the struggle between these two paradigms reveals itself to be part of a broader conflict between neoliberalism and it opponents and concludes by arguing that future research focused upon local contextualised struggles will reveal which paradigm is in the ascendancy

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation