Developmental Neurobehavioral Toxicity of Bisphenol a in Zebrafish (Danio Rerio)
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Petition to Order Testing of Tetrabromobisphenol a (“TBBPA”)
PETITION TO ORDER TESTING OF TETRABROMOBISPHENOL A (CAS NO. 79-94-7) UNDER SECTION 4(a) OF THE TOXIC SUBSTANCES CONTROL ACT (DECEMBER 13, 2016) Via Federal Express & Electronic Mail Gina McCarthy, Administrator U.S. Environmental Protection Agency 1200 Pennsylvania Avenue, N.W. Mail Code: 1101A Washington D.C. 20460 [email protected] Dear Administrator McCarthy: Earthjustice,1 Natural Resources Defense Council (NRDC), 2 Toxic-Free Future (TFF),3 Safer Chemicals, Healthy Families (SCHF),4 BlueGreen Alliance (BGA),5 and Environmental Health Strategy Center (EHSC),6 submit this Petition to the U.S. Environmental Protection Agency (“EPA”), pursuant to section 21 of the Toxic Substances Control Act (“TSCA”),7 to 1 Earthjustice is the nation’s largest environmental law organization. Protecting people and the environment from exposure to toxic substances is a key part of its mission. Earthjustice submits this petition on behalf of NRDC, SCHF, TFF, BGA, and EHSC. 2 NRDC is an international nonprofit environmental organization with more than 2 million members and online activists. Since 1970, our lawyers, scientists, and other environmental specialists have worked to protect the world's natural resources, public health, and the environment. Protecting families and communities from toxic chemicals is a key NRDC goal. 3 TFF advocates for the use of safer products, chemicals, and practices through advanced research, advocacy, grassroots organizing, and consumer engagement to ensure a healthier tomorrow. 4 SCHF is a coalition representing over 450 organizations and businesses united by a common concern about toxic chemicals in our homes, places of work, and products we use every day. -
Uncovering Evidence for Endocrine-Disrupting Chemicals That Elicit Differential Susceptibility Through Gene-Environment Interactions
toxics Review Uncovering Evidence for Endocrine-Disrupting Chemicals That Elicit Differential Susceptibility through Gene-Environment Interactions Dylan J. Wallis 1 , Lisa Truong 2 , Jane La Du 2, Robyn L. Tanguay 2 and David M. Reif 1,* 1 Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; [email protected] 2 Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA; [email protected] (L.T.); [email protected] (J.L.D.); [email protected] (R.L.T.) * Correspondence: [email protected] Abstract: Exposure to endocrine-disrupting chemicals (EDCs) is linked to myriad disorders, charac- terized by the disruption of the complex endocrine signaling pathways that govern development, physiology, and even behavior across the entire body. The mechanisms of endocrine disruption in- volve a complex system of pathways that communicate across the body to stimulate specific receptors that bind DNA and regulate the expression of a suite of genes. These mechanisms, including gene regulation, DNA binding, and protein binding, can be tied to differences in individual susceptibility across a genetically diverse population. In this review, we posit that EDCs causing such differential responses may be identified by looking for a signal of population variability after exposure. We begin Citation: Wallis, D.J.; Truong, L.; La by summarizing how the biology of EDCs has implications for genetically diverse populations. We Du, J.; Tanguay, R.L.; Reif, D.M. then describe how gene-environment interactions (GxE) across the complex pathways of endocrine Uncovering Evidence for Endocrine- signaling could lead to differences in susceptibility. We survey examples in the literature of individual Disrupting Chemicals That Elicit susceptibility differences to EDCs, pointing to a need for research in this area, especially regarding Differential Susceptibility through the exceedingly complex thyroid pathway. -
Novel Tumor Subgroups of Urothelial Carcinoma of the Bladder Defined by Integrated Genomic Analysis
Published OnlineFirst August 29, 2012; DOI: 10.1158/1078-0432.CCR-12-1807 Clinical Cancer Human Cancer Biology Research Novel Tumor Subgroups of Urothelial Carcinoma of the Bladder Defined by Integrated Genomic Analysis Carolyn D. Hurst, Fiona M. Platt, Claire F. Taylor, and Margaret A. Knowles Abstract Purpose: There is a need for improved subclassification of urothelial carcinoma (UC) at diagnosis. A major aim of this study was to search for novel genomic subgroups. Experimental design: We assessed 160 tumors for genome-wide copy number alterations and mutation in genes implicated in UC. These comprised all tumor grades and stages and included 49 high-grade stage T1 (T1G3) tumors. Results: Our findings point to the existence of genomic subclasses of the "gold-standard" grade/stage groups. The T1G3 tumors separated into 3 major subgroups that differed with respect to the type and number of copy number events and to FGFR3 and TP53 mutation status. We also identified novel regions of copy number alteration, uncovered relationships between molecular events, and elucidated relationships between molecular events and clinico-pathologic features. FGFR3 mutant tumors were more chromosom- ally stable than their wild-type counterparts and a mutually exclusive relationship between FGFR3 mutation and overrepresentation of 8q was observed in non-muscle-invasive tumors. In muscle-invasive (MI) tumors, metastasis was positively associated with losses of regions on 10q (including PTEN), 16q and 22q, and gains on 10p, 11q, 12p, 19p, and 19q. Concomitant copy number alterations positively associated with TP53 mutation in MI tumors were losses on 16p, 2q, 4q, 11p, 10q, 13q, 14q, 16q, and 19p, and gains on 1p, 8q, 10q, and 12q. -
Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897 -
OFR Staff Plan
Staff Briefing Package Project Plan: Organohalogen Flame Retardant Chemicals Assessment July 1, 2020 CPSC Consumer Hotline and General Information: 1-800-638-CPSC (2772) CPSC's Web Site: http://www.cpsc.gov THIS DOCUMENT HAS NOT BEEN REVIEWED CLEARED FOR PUBLIC RELEASE OR ACCEPTED BY THE COMMISSION UNDER CPSA 6(b)(1) Acknowledgments The preparation, writing, and review of this report was supported by a team of staff. We acknowledge and thank team members for their significant contributions. Michael Babich, Ph.D., Directorate for Health Sciences Charles Bevington, M.P.H., Directorate for Health Sciences Xinrong Chen, Ph.D., D.A.B.T., Directorate for Health Sciences Eric Hooker, M.S., D.A.B.T., Directorate for Health Sciences Cynthia Gillham, M.S., Directorate for Economic Analysis John Gordon, Ph.D., Directorate for Health Sciences Kristina Hatlelid, Ph.D., M.P.H., Directorate for Health Sciences Barbara Little, Attorney, Office of the General Counsel Joanna Matheson, Ph.D., Directorate for Health Sciences ii THIS DOCUMENT HAS NOT BEEN REVIEWED CLEARED FOR PUBLIC RELEASE OR ACCEPTED BY THE COMMISSION UNDER CPSA 6(b)(1) Table of Contents Briefing Memo ............................................................................................................................... iv 1. Executive summary .............................................................................................................. 5 2. Introduction ......................................................................................................................... -
FLAME RETARDANTS in PRINTED CIRCUIT BOARDS Chapter 5
FLAME RETARDANTS IN PRINTED CIRCUIT BOARDS Chapter 5 FINAL REPORT August 2015 EPA Publication 744-R-15-001 5 Potential Exposure to Flame Retardants and Other Life- Cycle Considerations Many factors must be considered to evaluate the risk to human health and the environment posed by any flame-retardant chemical. Risk is a function of two parameters, hazard and exposure. The hazard associated with a particular substance or chemical is its potential to impair human health, safety, or ecological health. While some degree of hazard can be assigned to most substances, the toxicity and harmful effects of other substances are not fully understood. The exposure potential of a given substance is a function of the exposure route (inhalation, ingestion, and dermal), the concentration of the substance in the contact media, and the frequency and duration of the exposure. The purpose of this chapter is to identify the highest priority routes of exposure to flame- retardant chemicals used in printed circuit boards (PCBs). Section 5.1 through Section 5.4 provide general background regarding potential exposure pathways that can occur during different life-cycle stages, discuss factors that affect exposure potential in an industrial setting, provide process descriptions for the industrial operations involved in the PCB manufacturing supply chain (identifying the potential primary release points and exposure pathways), and discuss potential consumer and environmental exposures. Following this general discussion, Section 5.5 highlights life-cycle considerations for the ten flame retardants evaluated by this partnership. The chapter is intended to help the reader identify and characterize the exposure potential of flame-retardant chemicals based on factors including physical and chemical properties and reactive versus additive incorporation into the epoxy resin. -
June 19, 2019 Transmitted Electronically
June 19, 2019 Transmitted Electronically Document Control Manager Office of Pollution Prevention and Toxics (OPPT) US EPA 1200 Pennsylvania Avenue, NW Washington, DC 20460-0001 Dear Sir/Maddam, The Center for Environmental Health (CEH) hereby submits these comments on the proposed Toxic Substances Control Act high-priority candidates (EPA-HQ-OPPT-2019-0131- 0001). As required by the Toxic Substances Control Act (TSCA), the United States Environmental Protection Agency (USEPA) must regularly release a list of chemicals that are under review for prioritization for risk evaluation. This list consists of 20 high-priority and 20 low-priority candidates. These comments identify data on the 2019 list of the 20 high-priority candidates (Table 1) in the literature that support the notion that these chemicals may be endocrine disrupting compounds (EDCs). EDCs are a class of chemicals that can interfere with the production, action, transport, or metabolism of endogenous hormones in the body.1 For the purposes of these comments, an EDC will be considered any compound that showed an effect on an endocrine system at any dose or concentration, thus accounting for any potential dose responses that may be non-monotonic. This is supported in the literature wherein disruption of upstream signaling, even at low doses and within “normal” levels of hormone variability, adverse outcomes can be observed.2,3 These comments will describe various studies to determine whether the compound of interest could be considered an EDC. This was accomplished by searching PubMed as well as The Endocrine Disruption Exchange’s List of Potential Endocrine Disruptors for peer- reviewed articles by searching with the CAS Registry Number for each chemical; USEPA’s Computational Toxicology Dashboard was also searched. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
University of Florida Thesis Or Dissertation Formatting Template
STATISTICAL METHODS FOR ANALYZING GENOMICS DATA By SINJINI SIKDAR A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2017 © 2017 Sinjini Sikdar Dedicated to my husband, Sandipan, who has been a constant source of support and encouragement during the challenges of my PhD life. ACKNOWLEDGMENTS I am deeply grateful to my advisor Professor Susmita Datta for her unyielding support and invaluable guidance throughout my graduate work. It would not have been possible for me to reach this point without her support. I also want to express my sincere thanks to Professor Somnath Datta as I learnt a lot through my interactions with him and benefited from his expert suggestions. I am also thankful to my other dissertation committee members Professor Fei Zou, and Professor Lauren McIntyre for all their kind support and constructive comments regarding my dissertation. I want to thank Professor Ryan Gill from University of Louisville for his helpful contributions to my research works. I also want to thank all the faculty, staff, and students of the Department of Biostatistics at University of Florida as well as all the faculty and students of the Department of Bioinformatics and Biostatistics at University of Louisville who have helped me reach this point. I would like to thank my sister Shreejata Sikdar for her invaluable friendship and constant support throughout my PhD life. Finally, I want to thank my parents for their immense encouragement that have helped me in moving forward in my academic life. -
CREB3L2-Pparg Fusion Mutation Identifies a Thyroid Signaling Pathway Regulated by Intramembrane Proteolysis
Research Article CREB3L2-PPARg Fusion Mutation Identifies a Thyroid Signaling Pathway Regulated by Intramembrane Proteolysis Weng-Onn Lui,3 Lingchun Zeng,1 Victoria Rehrmann,1 Seema Deshpande,5 Maria Tretiakova,1 Edwin L. Kaplan,2 Ingo Leibiger,3 Barbara Leibiger,3 Ulla Enberg,3 Anders Ho¨o¨g,4 Catharina Larsson,3 and Todd G. Kroll1 Departments of 1Pathology and 2Surgery, University of Chicago Medical Center, Chicago, Illinois; Departments of 3Molecular Medicine and Surgery and 4Oncology-Pathology, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden; and 5Department of Pathology, Emory University School of Medicine, Atlanta, Georgia Abstract cancer in patients; and (c) the implementation of effective molecular-targeted chemotherapies that have relatively few side The discovery of gene fusion mutations, particularly in effects. The discovery of fusion mutations is therefore important, leukemia, has consistently identified new cancer pathways particularly in carcinoma, the most common cancer group in and led to molecular diagnostic assays and molecular-targeted which few gene fusions have been identified (1). The recent chemotherapies for cancer patients. Here, we report our discoveries of ERG (2) and ALK (3) gene fusions in prostate and discovery of a novel CREB3L2-PPARg fusion mutation in lung carcinoma, respectively, increase the prospect that new thyroid carcinoma with t(3;7)(p25;q34), showing that a family diagnostic and therapeutic strategies based on gene fusions will of somatic PPARg fusion mutations exist in thyroid cancer. The be applicable to common epithelial cancers. CREB3L2-PPARg fusion encodes a CREB3L2-PPAR; fusion Families of gene fusions tend to characterize specific cancer protein that is composed of the transactivation domain of types. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
Supplementary Figure S4
18DCIS 18IDC Supplementary FigureS4 22DCIS 22IDC C D B A E (0.77) (0.78) 16DCIS 14DCIS 28DCIS 16IDC 28IDC (0.43) (0.49) 0 ADAMTS12 (p.E1469K) 14IDC ERBB2, LASP1,CDK12( CCNE1 ( NUTM2B SDHC,FCGR2B,PBX1,TPR( CD1D, B4GALT3, BCL9, FLG,NUP21OL,TPM3,TDRD10,RIT1,LMNA,PRCC,NTRK1 0 ADAMTS16 (p.E67K) (0.67) (0.89) (0.54) 0 ARHGEF38 (p.P179Hfs*29) 0 ATG9B (p.P823S) (0.68) (1.0) ARID5B, CCDC6 CCNE1, TSHZ3,CEP89 CREB3L2,TRIM24 BRAF, EGFR (7p11); 0 ABRACL (p.R35H) 0 CATSPER1 (p.P152H) 0 ADAMTS18 (p.Y799C) 19q12 0 CCDC88C (p.X1371_splice) (0) 0 ADRA1A (p.P327L) (10q22.3) 0 CCNF (p.D637N) −4 −2 −4 −2 0 AKAP4 (p.G454A) 0 CDYL (p.Y353Lfs*5) −4 −2 Log2 Ratio Log2 Ratio −4 −2 Log2 Ratio Log2 Ratio 0 2 4 0 2 4 0 ARID2 (p.R1068H) 0 COL27A1 (p.G646E) 0 2 4 0 2 4 2 EDRF1 (p.E521K) 0 ARPP21 (p.P791L) ) 0 DDX11 (p.E78K) 2 GPR101, p.A174V 0 ARPP21 (p.P791T) 0 DMGDH (p.W606C) 5 ANP32B, p.G237S 16IDC (Ploidy:2.01) 16DCIS (Ploidy:2.02) 14IDC (Ploidy:2.01) 14DCIS (Ploidy:2.9) -3 -2 -1 -3 -2 -1 -3 -2 -1 -3 -2 -1 -3 -2 -1 -3 -2 -1 Log Ratio Log Ratio Log Ratio Log Ratio 12DCIS 0 ASPM (p.S222T) Log Ratio Log Ratio 0 FMN2 (p.G941A) 20 1 2 3 2 0 1 2 3 2 ERBB3 (p.D297Y) 2 0 1 2 3 20 1 2 3 0 ATRX (p.L1276I) 20 1 2 3 2 0 1 2 3 0 GALNT18 (p.F92L) 2 MAPK4, p.H147Y 0 GALNTL6 (p.E236K) 5 C11orf1, p.Y53C (10q21.2); 0 ATRX (p.R1401W) PIK3CA, p.H1047R 28IDC (Ploidy:2.0) 28DCIS (Ploidy:2.0) 22IDC (Ploidy:3.7) 22DCIS (Ploidy:4.1) 18IDC (Ploidy:3.9) 18DCIS (Ploidy:2.3) 17q12 0 HCFC1 (p.S2025C) 2 LCMT1 (p.S34A) 0 ATXN7L2 (p.X453_splice) SPEN, p.P677Lfs*13 CBFB 1 2 3 4 5 6 7 8 9 10 11