25 research outputs found

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-8

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    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-3

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-4

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-0

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-7

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-5

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice-1

    No full text
    <p><b>Copyright information:</b></p><p>Taken from "GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice"</p><p>Environmental Health Perspectives 2004;112(17):1717-1724.</p><p>Published online 13 Sep 2004</p><p>PMCID:PMC1253665.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p

    <i>Stat3</i> is a candidate epigenetic biomarker of perinatal Bisphenol A exposure associated with murine hepatic tumors with implications for human health

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    <p>Bisphenol A (BPA) is an endocrine disrupting chemical (EDC) that has been implicated as a potential carcinogen and epigenotoxicant. We have previously reported dose-dependent incidence of hepatic tumors in 10-month-old isogenic mice perinatally exposed to BPA. Here, we evaluated DNA methylation at 3 candidate genes (<i>Esr1, Il-6st</i>, and <i>Stat3</i>) in liver tissue of BPA-exposed mice euthanized at 2 time points: post-natal day 22 (PND22; n = 147) or 10-months of age (n = 78, including n = 18 with hepatic tumors). Additionally, DNA methylation profiles were analyzed at human homologs of murine candidate genes in human fetal liver samples (n = 50) with known liver tissue BPA levels. Candidate genes were chosen based on reported expression changes in both rodent and human hepatocellular carcinoma (HCC). Regions for bisulfite sequencing were chosen by mining whole genome next generation sequencing methylation datasets of both mice and human liver samples with known perinatal BPA exposures. One of 3 candidate genes, <i>Stat3</i>, displayed dose-dependent DNA methylation changes in both 10-month mice with liver tumors as compared to those without liver tumors and 3-week sibling mice from the same exposure study, implicating <i>Stat3</i> as a potential epigenetic biomarker of both early life BPA exposure and adult disease in mice. DNA methylation profiles within <i>STAT3</i> varied with liver tissue BPA level in human fetal liver samples as well, suggesting <i>STAT3</i> may be a translationally relevant candidate biomarker. These data implicate <i>Stat3</i> as a potential early life biomarker of adult murine liver tumor risk following early BPA exposure with early evidence of relevance to human health.</p

    Coat-color distribution and methylation of CpG sites 4–9 of the IAP in offspring whose mothers were fed unsupplemented and genistein-supplemented (250 mg genistein/kg diet) diets

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    <p><b>Copyright information:</b></p><p>Taken from "Maternal Genistein Alters Coat Color and Protects Mouse Offspring from Obesity by Modifying the Fetal Epigenome"</p><p>Environmental Health Perspectives 2006;114(4):567-572.</p><p>Published online 26 Jan 2006</p><p>PMCID:PMC1440782.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p> () Coat-color distribution of / offspring born to 15 unsupplemented and 12 genistein-supplemented litters. () Genomic sequence containing nine CpG sites located between the cryptic promoter and the IAP promoter (blue arrow in ) at the 5′ end of the contraoriented IAP. CpG sites 1–9 are numbered and marked by gray boxes. () Box plots representing the percentage of cells methylated at sites 4–9 in unsupplemented ( = 52) and genistein-supplemented ( = 44) / offspring. Ends of the boxes indicate the interquartile range representing the 25th to 75th percentiles of the data; horizontal lines within each box indicate median; and dashed horizontal lines represent average percent methylation of CpG sites 4–9 according to coat-color phenotype

    Age-related epigenome-wide DNA methylation and hydroxymethylation in longitudinal mouse blood

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    <p>DNA methylation at cytosine-phosphate-guanine (CpG) dinucleotides changes as a function of age in humans and animal models, a process that may contribute to chronic disease development. Recent studies have investigated the role of an oxidized form of DNA methylation – 5-hydroxymethylcytosine (5hmC) – in the epigenome, but its contribution to age-related DNA methylation remains unclear. We tested the hypothesis that 5hmC changes with age, but in a direction opposite to 5-methylcytosine (5mC), potentially playing a distinct role in aging. To characterize epigenetic aging, genome-wide 5mC and 5hmC were measured in longitudinal blood samples (2, 4, and 10 months of age) from isogenic mice using two sequencing methods – enhanced reduced representation bisulfite sequencing and hydroxymethylated DNA immunoprecipitation sequencing. Examining the epigenome by age, we identified 28,196 unique differentially methylated CpGs (DMCs) and 8,613 differentially hydroxymethylated regions (DHMRs). Mouse blood showed a general pattern of epigenome-wide hypermethylation and hypo-hydroxymethylation with age. Comparing age-related DMCs and DHMRs, 1,854 annotated genes showed both differential 5mC and 5hmC, including one gene – <i>Nfic</i> – at five CpGs in the same 250 bp chromosomal region. At this region, 5mC and 5hmC levels both decreased with age. Reflecting these age-related epigenetic changes, <i>Nfic</i> RNA expression in blood decreased with age, suggesting that age-related regulation of this gene may be driven by 5hmC, not canonical DNA methylation. Combined, our genome-wide results show age-related differential 5mC and 5hmC, as well as some evidence that changes in 5hmC may drive age-related DNA methylation and gene expression.</p
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