20 research outputs found

    Effectiveness of Advanced Nitrogen-Removal Onsite Wastewater Treatment Systems in a New England Coastal Community

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    Wastewater is a major source of nitrogen (N) to groundwater and coastal waterbodies, threatening both environmental and public health. Advanced N-removal onsite wastewater treatment systems (OWTS) are used to reduce effluent N concentration; however, few studies have assessed their effectiveness. We evaluated the total N (TN) concentration of effluent from 50 advanced N-removal OWTS in Charlestown, Rhode Island, USA for 3 years. We quantified differences in effectiveness as a function of N-removal technology and home occupancy pattern (seasonal vs. year-round use), and examined the relationship between wastewater properties and TN concentration. RX30 systems produced the lowest median TN concentration (mg N/L) (13.2), followed by FAST (13.4), AX20 (14.9), and Norweco (33.8). Compliance with the state’s regulatory standard for effluent TN concentration (19 mg N/L) was highest for RX30 systems (78%), followed by AX20 (73%), FAST (67%), and Norweco (0%). Occupancy pattern did not affect effluent TN concentration. Variation in TN concentration was driven by ammonium and nitrate for all technologies, and also by temperature for FAST and pH for Norweco. Median daily (g N/day) and annual (kg N/yr) N loads were significantly higher for year-round (5.3 and 2.3) than for seasonal (3.7 and 0.41) systems, likely due to differences in volume of wastewater treated. Our results suggest that advanced N-removal OWTS vary in their compliance with the state regulatory standard for effluent TN and can withstand long periods of non-use without compromising effectiveness. Nevertheless, systems used year-round do produce a higher daily and annual N load than seasonally-used systems

    Greenhouse Gas Emissions from Advanced Nitrogen-Removal Onsite Wastewater Treatment Systems

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    Advanced onsite wastewater treatment systems (OWTS) designed to remove nitrogen from residential wastewater play an important role in protecting environmental and public health. Nevertheless, the microbial processes involved in treatment produce greenhouse gases (GHGs) that contribute to global climate change, including CO2, CH4, N2O. We measured GHG emissions from 27 advanced N-removal OWTS in the towns of Jamestown and Charlestown, Rhode Island, USA, and assessed differences in flux based on OWTS technology, home occupancy (year-round vs. seasonal), and zone within the system (oxic vs. anoxic/hypoxic). We also investigated the relationship between flux and wastewater properties. Flux values for CO2, CH4, and N2O ranged from −0.44 to 61.8, −0.0029 to 25.3, and −0.02 to 0.23 ÎŒmol GHG m−2 s−1, respectively. CO2 and N2O flux varied among technologies, whereas occupancy pattern did not significantly impact any GHG fluxes. CO2 and CH4 – but not N2O – flux was significantly higher in the anoxic/hypoxic zone than in the oxic zone. Greenhouse gas fluxes in the oxic zone were not related to any wastewater properties. CO2 and CH4 flux from the anoxic/hypoxic zone peaked at ~22-23 °C, and was negatively correlated with dissolved oxygen levels, the latter suggesting that CO2 and CH4 flux result primarily from anaerobic respiration. Ammonium concentration and CH4 flux were positively correlated, likely due to inhibition of CH4 oxidation by NH4+. N2O flux in the anoxic/hypoxic zone was not correlated to any wastewater property. We estimate that advanced N-removal OWTS contribute 262 g CO2 equivalents capita−1 day−1, slightly lower than emissions from conventional OWTS. Our results suggest that technology influences CO2 and N2O flux and zone influences CO2 and CH4 flux, while occupancy pattern does not appear to impact GHG flux. Manipulating wastewater properties, such as temperature and dissolved oxygen, may help mitigate GHG emissions from these systems

    Influence of Season, Occupancy Pattern, and Technology on Structure and Composition of Nitrifying and Denitrifying Bacterial Communities in Advanced Nitrogen-Removal Onsite Wastewater Treatment Systems

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    Advanced onsite wastewater treatment systems (OWTS) use biological nitrogen removal (BNR) to mitigate the threat that N-rich wastewater poses to coastal waterbodies and groundwater. These systems lower the N concentration of effluent via sequential microbial nitrification and denitrification. We used high-throughput sequencing to evaluate the structure and composition of nitrifying and denitrifying bacterial communities in advanced N-removal OWTS, targeting the genes encoding ammonia monooxygenase (amoA) and nitrous oxide reductase (nosZ) present in effluent from 44 advanced systems. We used QIIME2 and the phyloseq package in R to examine differences in taxonomy and alpha and beta diversity as a function of advanced OWTS technology, occupancy pattern (seasonal vs. year-round use), and season (June vs. September). Richness and Shannon’s diversity index for amoA were significantly influenced by season, whereas technology influenced nosZ diversity significantly. Season also had a strong influence on differences in beta diversity among amoA communities, and had less influence on nosZ communities, whereas technology had a stronger influence on nosZ communities. Nitrosospira and Nitrosomonas were the main genera of nitrifiers in advanced N-removal OWTS, and the predominant genera of denitrifiers included Zoogloea, Thauera, and Acidovorax. Differences in taxonomy for each gene generally mirrored those observed in diversity patterns, highlighting the possible importance of season and technology in shaping communities of amoA and nosZ, respectively. Knowledge gained from this study may be useful in understanding the connections between microbial communities and OWTS performance and may help manage systems in a way that maximizes N removal

    A functional genomic approach to actionable gene fusions for precision oncology

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    Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize similar to 100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology

    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

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    Forouzanfar MH, Afshin A, Alexander LT, et al. 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. LANCET. 2016;388(10053):1659-1724.Background 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. Copyright (C) The Author(s). Published by Elsevier Ltd

    Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

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    Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe
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