The Global Burden of Air Pollution on Mortality: The Need to Include Exposure to Household Biomass Fuel–Derived Particulates

First paragraph: Anenberg et al. (2010) demonstrated that global mortality associated with outdoor ozone and particulate matter (PM) exposure has been underestimated and that anthropogenic atmospheric PM rather than ozone is the main contributor to death. Although we acknowledge that their investigation was concerned with outdoor air pollution alone, we feel that attention should be drawn to the burden of disease from household air pollution

Prostate Cancer Screening Trends After United States Preventative Services Task Force Guidelines in an Underserved Population

Purpose: Prostate cancer screening is a controversial topic. We examined trends in Prostate Specific Antigen (PSA) testing in an underserved population before and after the United States Preventative Services Task Force (USPSTF) recommendation against screening. Methods: Data were collected on all PSA and cholesterol screening tests from 2008 to 2014. We examined the trend of these tests and prostate biopsies while comparing this data to lipid panel data to adjust for changes in patient population. Results: A decrease in PSA screening was observed from 2010 through 2014, with the greatest decline in 2012. The age group most affected was patients aged 55-69 years. The amount of prostate biopsies during this period decreased as well. Conclusions: Decreased rates of PSA screening were observed in our urban hospital population that preceded the publication of the USPSTF guidelines. The incidence of prostate biopsies decreased in this timeframe. It now remains to be demonstrated whether decreased PSA screening rates impact the diagnosis of and ultimately the survival from prostate cancer

Hidden Diversity Revealed by Genome-resolved Metagenomics of Iron-oxidizing Microbial Mats from Lō’ihi Seamount, Hawai’i

The Zetaproteobacteria are ubiquitous in marine environments, yet this class of Proteobacteria is only represented by a few closely-related cultured isolates. In high-iron environments, such as diffuse hydrothermal vents, the Zetaproteobacteria are important members of the community driving its structure. Biogeography of Zetaproteobacteria has shown two ubiquitous operational taxonomic units (OTUs), yet much is unknown about their genomic diversity. Genome-resolved metagenomics allows for the specific binning of microbial genomes based on genomic signatures present in composite metagenome assemblies. This resulted in the recovery of 93 genome bins, of which 34 were classified as Zetaproteobacteria. Form II ribulose 1,5-bisphosphate carboxylase genes were recovered from nearly all the Zetaproteobacteria genome bins. In addition, the Zetaproteobacteria genome bins contain genes for uptake and utilization of bioavailable nitrogen, detoxification of arsenic, and a terminal electron acceptor adapted for low oxygen concentration. Our results also support the hypothesis of a Cyc2-like protein as the site for iron oxidation, now detected across a majority of the Zetaproteobacteria genome bins. Whole genome comparisons showed a high genomic diversity across the Zetaproteobacteria OTUs and genome bins that were previously unidentified by SSU rRNA gene analysis. A single lineage of cosmopolitan Zetaproteobacteria (zOTU 2) was found to be monophyletic, based on cluster analysis of average nucleotide identity and average amino acid identity comparisons. From these data, we can begin to pinpoint genomic adaptations of the more ecologically ubiquitous Zetaproteobacteria, and further understand their environmental constraints and metabolic potential

Airborne Endotoxin Concentrations in Homes Burning Biomass Fuel

BACKGROUND: About half of the world's population is exposed to smoke from burning biomass fuels at home. The high airborne particulate levels in these homes and the health burden of exposure to this smoke are well described. Burning unprocessed biological material such as wood and dried animal dung may also produce high indoor endotoxin concentrations.OBJECTIVE: In this study we measured airborne endotoxin levels in homes burning different biomass fuels. Methods: Air sampling was carried out in homes burning wood or dried animal dung in Nepal (n = 31) and wood, charcoal, or crop residues in Malawi (n = 38). Filters were analyzed for endotoxin content expressed as airborne endotoxin concentration and endotoxin per mass of airborne particulate.RESULTS: Airborne endotoxin concentrations were high. Averaged over 24 hr in Malawian homes, median concentrations of total inhalable endotoxin were 24 endotoxin units (EU)/m(3) in charcoal-burning homes and 40 EU/m(3) in wood-burning homes. Short cooking-time samples collected in Nepal produced median values of 43 EU/m(3) in wood-burning homes and 365 EU/m(3) in dung-burning homes, suggesting increasing endotoxin levels with decreasing energy levels in unprocessed solid fuels.CONCLUSIONS: Airborne endotoxin concentrations in homes burning biomass fuels are orders of magnitude higher than those found in homes in developed countries where endotoxin exposure has been linked to respiratory illness in children. There is a need for work to identify the determinants of these high concentrations, interventions to reduce exposure, and health studies to examine the effects of these sustained, near-occupational levels of exposure experienced from early life

Models of Forbidden Line Emission Profiles from Axisymmetric Stellar Winds

A number of strong infrared forbidden lines have been observed in several evolved Wolf-Rayet star winds, and these are important for deriving metal abundances and testing stellar evolution models. In addition, because these optically thin lines form at large radius in the wind, their resolved profiles carry an imprint of the asymptotic structure of the wind flow. This work presents model forbidden line profile shapes formed in axisymmetric winds. It is well-known that an optically thin emission line formed in a spherical wind expanding at constant velocity yields a flat-topped emission profile shape. Simulated forbidden lines are produced for a model stellar wind with an axisymmetric density distribution that treats the latitudinal ionization self-consistently and examines the influence of the ion stage on the profile shape. The resulting line profiles are symmetric about line centre. Within a given atomic species, profile shapes can vary between centrally peaked, doubly peaked, and approximately flat-topped in appearance depending on the ion stage (relative to the dominant ion) and viewing inclination. Although application to Wolf-Rayet star winds is emphasized, the concepts are also relevant to other classes of hot stars such as luminous blue variables and Be/B[e] stars.Comment: To appear in MNRA

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD

Worldwide population differentiation at disease-associated SNPs

<p>Abstract</p> <p>Background</p> <p>Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).</p> <p>Methods</p> <p>We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.</p> <p>Results</p> <p>On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.</p> <p>Conclusion</p> <p>Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.</p

Mega-analysis of association between obesity and cortical morphology in bipolar disorders:ENIGMA study in 2832 participants

Background: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. Methods: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. Results: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. Conclusions: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p