Influence of operating parameters on the biodegradation of steroid estrogens and nonylphenolic compounds during biological wastewater treatment processes

This document is the unedited author's version of a Submitted Work that was subsequently accepted for publication in Environmental Science & Technology, copyright © American Chemical Society after peer review. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/es901612v.This study investigated operational factors influencing the removal of steroid estrogens and nonylphenolic compounds in two sewage treatment works, one a nitrifying/denitrifying activated sludge plant and the other a nitrifying/denitrifying activated sludge plant with phosphorus removal. Removal efficiencies of >90% for steroid estrogens and for longer chain nonylphenol ethoxylates (NP4−12EO) were observed at both works, which had equal sludge ages of 13 days. However, the biological activity in terms of milligrams of estrogen removed per day per tonne of biomass was found to be 50−60% more efficient in the nitrifying/denitrifying activated sludge works compared to the works which additionally incorporated phosphorus removal. A temperature reduction of 6 °C had no impact on the removal of free estrogens, but removal of the conjugated estrone-3-sulfate was reduced by 20%. The apparent biomass sorption (LogKp) values were greater in the nitrifying/denitrifying works than those in the nitrifying/denitrifying works with phosphorus removal for both steroid estrogens and nonylphenolic compounds possibly indicating a different cell surface structure and therefore microbial population. The difference in biological activity (mg tonne−1 d−1) identified in this study, of up to seven times, suggests that there is the potential for enhancing the removal of estrogens and nonylphenols if more detailed knowledge of the factors responsible for these differences can be identified and maximized, thus potentially improving the quality of receiving waters.Public Utilities Board (Singapore), Anglian Water Ltd, Severn Trent Water Ltd, Thames Water Utilities Ltd, United Utilities 393 Plc and Yorkshire Water Services

Glycosaminoglycans and Sialylated Glycans Sequentially Facilitate Merkel Cell Polyomavirus Infectious Entry

Merkel cell polyomavirus (MCV or MCPyV) appears to be a causal factor in the development of Merkel cell carcinoma, a rare but highly lethal form of skin cancer. Although recent reports indicate that MCV virions are commonly shed from apparently healthy human skin, the precise cellular tropism of the virus in healthy subjects remains unclear. To begin to explore this question, we set out to identify the cellular receptors or co-receptors required for the infectious entry of MCV. Although several previously studied polyomavirus species have been shown to bind to cell surface sialic acid residues associated with glycolipids or glycoproteins, we found that sialylated glycans are not required for initial attachment of MCV virions to cultured human cell lines. Instead, glycosaminoglycans (GAGs), such as heparan sulfate (HS) and chondroitin sulfate (CS), serve as initial attachment receptors during the MCV infectious entry process. Using cell lines deficient in GAG biosynthesis, we found that N-sulfated and/or 6-O-sulfated forms of HS mediate infectious entry of MCV reporter vectors, while CS appears to be dispensable. Intriguingly, although cell lines deficient in sialylated glycans readily bind MCV capsids, the cells are highly resistant to MCV reporter vector-mediated gene transduction. This suggests that sialylated glycans play a post-attachment role in the infectious entry process. Results observed using MCV reporter vectors were confirmed using a novel system for infectious propagation of native MCV virions. Taken together, the findings suggest a model in which MCV infectious entry occurs via initial cell binding mediated primarily by HS, followed by secondary interactions with a sialylated entry co-factor. The study should facilitate the development of inhibitors of MCV infection and help shed light on the infectious entry pathways and cellular tropism of the virus

Distribuição espaço-temporal da mortalidade por malformações congênitas e causas mal definidas, em estados da região centro-sul do Brasil Space and time distribution of malformation and uncertain causes of death in the Brazilian states of the center-south region

A investigação da distribuição espacial da mortalidade por malformações congênitas pode ser útil em programas de vigilância ambiental em saúde. Foram analisados os padrões espaço-temporais da mortalidade por malformações congênitas e causas mal definidas em Estados brasileiros (MS, MT, GO, MG, SP, PR, SC e RS) e no Distrito Federal, no período de 2000 a 2004. Os valores observados foram obtidos do Sistema de Informações de Mortalidade (SIM) do Ministério da Saúde. Foi utilizado um modelo bayesiano que rende interação espaço-temporal. Muitas microrregiões com baixas taxas para malformações congênitas tiveram valores elevados para causas mal definidas, sendo que os óbitos por causas mal definidas prejudicam a identificação de microrregiões com taxas de mortalidade por malformações congênitas acima do esperado, indicativas da existência de fatores ambientais de risco para estas doenças.<br>The investigation of the spacial distribution of deaths caused by malformations could be useful in environmental health vigilance programs. Patterns of deaths by malformations and uncertain causes in Brazilian States (MS, MT, GO, MG, SP, PR, SC e RS) and Distrito Federal were studied, from 2000 to 2004.The observed values were obtained from the Brazilian Ministry of Health Mortality Information System (SIM). A Bayesian model that allowed for space-time interaction was applied. Many micro-regions having low rates for deaths by malformations presented high values for the deaths by uncertain causes, and the deaths by uncertain causes prejudice the identification of the micro-regions having rates of death by malformations higher than the expected, indicative of the existence of risk factors for those illnesses, present in the environment