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Institution

United States Environmental Protection Agency

GovernmentWashington D.C., District of Columbia, United States
About: United States Environmental Protection Agency is a government organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Population & Environmental exposure. The organization has 13873 authors who have published 26902 publications receiving 1191729 citations. The organization is also known as: EPA & Environmental Protection Agency.


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Journal ArticleDOI
TL;DR: A framework designed for this purpose, the adverse outcome pathway (AOP), is discussed, a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment.
Abstract: Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.

1,988 citations

Journal ArticleDOI
Leming Shi1, Laura H. Reid, Wendell D. Jones, Richard Shippy2, Janet A. Warrington3, Shawn C. Baker4, Patrick J. Collins5, Francoise de Longueville, Ernest S. Kawasaki6, Kathleen Y. Lee7, Yuling Luo, Yongming Andrew Sun7, James C. Willey8, Robert Setterquist7, Gavin M. Fischer9, Weida Tong1, Yvonne P. Dragan1, David J. Dix10, Felix W. Frueh1, Federico Goodsaid1, Damir Herman6, Roderick V. Jensen11, Charles D. Johnson, Edward K. Lobenhofer12, Raj K. Puri1, Uwe Scherf1, Jean Thierry-Mieg6, Charles Wang13, Michael A Wilson7, Paul K. Wolber5, Lu Zhang7, William Slikker1, Shashi Amur1, Wenjun Bao14, Catalin Barbacioru7, Anne Bergstrom Lucas5, Vincent Bertholet, Cecilie Boysen, Bud Bromley, Donna Brown, Alan Brunner2, Roger D. Canales7, Xiaoxi Megan Cao, Thomas A. Cebula1, James J. Chen1, Jing Cheng, Tzu Ming Chu14, Eugene Chudin4, John F. Corson5, J. Christopher Corton10, Lisa J. Croner15, Christopher Davies3, Timothy Davison, Glenda C. Delenstarr5, Xutao Deng13, David Dorris7, Aron Charles Eklund11, Xiaohui Fan1, Hong Fang, Stephanie Fulmer-Smentek5, James C. Fuscoe1, Kathryn Gallagher10, Weigong Ge1, Lei Guo1, Xu Guo3, Janet Hager16, Paul K. Haje, Jing Han1, Tao Han1, Heather Harbottle1, Stephen C. Harris1, Eli Hatchwell17, Craig A. Hauser18, Susan D. Hester10, Huixiao Hong, Patrick Hurban12, Scott A. Jackson1, Hanlee P. Ji19, Charles R. Knight, Winston Patrick Kuo20, J. Eugene LeClerc1, Shawn Levy21, Quan Zhen Li, Chunmei Liu3, Ying Liu22, Michael Lombardi11, Yunqing Ma, Scott R. Magnuson, Botoul Maqsodi, Timothy K. McDaniel3, Nan Mei1, Ola Myklebost23, Baitang Ning1, Natalia Novoradovskaya9, Michael S. Orr1, Terry Osborn, Adam Papallo11, Tucker A. Patterson1, Roger Perkins, Elizabeth Herness Peters, Ron L. Peterson24, Kenneth L. Philips12, P. Scott Pine1, Lajos Pusztai25, Feng Qian, Hongzu Ren10, Mitch Rosen10, Barry A. Rosenzweig1, Raymond R. Samaha7, Mark Schena, Gary P. Schroth, Svetlana Shchegrova5, Dave D. Smith26, Frank Staedtler24, Zhenqiang Su1, Hongmei Sun, Zoltan Szallasi20, Zivana Tezak1, Danielle Thierry-Mieg6, Karol L. Thompson1, Irina Tikhonova16, Yaron Turpaz3, Beena Vallanat10, Christophe Van, Stephen J. Walker27, Sue Jane Wang1, Yonghong Wang6, Russell D. Wolfinger14, Alexander Wong5, Jie Wu, Chunlin Xiao7, Qian Xie, Jun Xu13, Wen Yang, Liang Zhang, Sheng Zhong28, Yaping Zong 
TL;DR: This study describes the experimental design and probe mapping efforts behind the MicroArray Quality Control project and shows intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed.
Abstract: Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

1,987 citations

Journal ArticleDOI
TL;DR: This method is applied to a variety of environmental studies in which stable isotope tracers were used to quantify the relative magnitude of multiple sources, including plant water use, geochemistry, air pollution, and dietary analysis and gives the range of isotopically determined source contributions.
Abstract: Stable isotopes are increasingly being used as tracers in environmental studies. One application is to use isotopic ratios to quantitatively determine the proportional contribution of several sources to a mixture, such as the proportion of various pollution sources in a waste stream. In general, the proportional contributions of n+1 different sources can be uniquely determined by the use of n different isotope system tracers (e.g., δ13C, δ15N, δ18O) with linear mixing models based on mass balance equations. Often, however, the number of potential sources exceeds n+1, which prevents finding a unique solution of source proportions. What can be done in these situations? While no definitive solution exists, we propose a method that is informative in determining bounds for the contributions of each source. In this method, all possible combinations of each source contribution (0–100%) are examined in small increments (e.g., 1%). Combinations that sum to the observed mixture isotopic signatures within a small tolerance (e.g., ±0.1‰) are considered to be feasible solutions, from which the frequency and range of potential source contributions can be determined. To avoid misrepresenting the results, users of this procedure should report the distribution of feasible solutions rather than focusing on a single value such as the mean. We applied this method to a variety of environmental studies in which stable isotope tracers were used to quantify the relative magnitude of multiple sources, including (1) plant water use, (2) geochemistry, (3) air pollution, and (4) dietary analysis. This method gives the range of isotopically determined source contributions; additional non-isotopic constraints specific to each study may be used to further restrict this range. The breadth of the isotopically determined ranges depends on the geometry of the mixing space and the similarity of source and mixture isotopic signatures. A sensitivity analysis indicated that the estimated ranges vary only modestly with different choices of source increment and mass balance tolerance parameter values. A computer program (IsoSource) to perform these calculations for user-specified data is available at http://www.epa.gov/wed/pages/models.htm .

1,931 citations

Journal ArticleDOI
TL;DR: Data Analysis by Resampling is a useful and clear introduction to resampling that would make an ambitious second course in statistics or a good third or later course and is quite well suited for self-study by an individual with just a few previous statistics courses.
Abstract: described and related to one another and to the different resampling methods is also notable. This is especially useful for the book’s target audience, for whom such concepts may not yet have taken root. On the computational side, the book may be a little less satisfying. Stepby-step computational algorithms are at some times inefŽ cient and at other times cryptic so that an individual with little programming experience might have difŽ culty applying them. This problem is substantially offset by the presence of numerous detailed examples solved using existing software, providing readers roughly equal exposure to S-PLUS, SC, and Resampling Stats. Unfortunately, these examples often require large, complex programs, demonstrating as much as anything a need for better resampling software. On the whole, Data Analysis by Resampling is a useful and clear introduction to resampling. It would make an ambitious second course in statistics or a good third or later course. It is quite well suited for self-study by an individual with just a few previous statistics courses. Although it would be miscast as a graduate-level textbook or as a research reference—for one thing it lacks a thorough bibliography to make up for its surface treatment of many of the topics it covers—it is a very nice book for any reader seeking an introductory book on resampling.

1,840 citations

Journal ArticleDOI
08 Sep 2015-JAMA
TL;DR: Among extremely preterm infants born at US academic centers over the last 20 years, changes in maternal and infant care practices and modest reductions in several morbidities were observed, although bronchopulmonary dysplasia increased.
Abstract: Importance Extremely preterm infants contribute disproportionately to neonatal morbidity and mortality. Objective To review 20-year trends in maternal/neonatal care, complications, and mortality among extremely preterm infants born at Neonatal Research Network centers. Design, Setting, Participants Prospective registry of 34 636 infants, 22 to 28 weeks’ gestation, birth weight of 401 to 1500 g, and born at 26 network centers between 1993 and 2012. Exposures Extremely preterm birth. Main Outcomes and Measures Maternal/neonatal care, morbidities, and survival. Major morbidities, reported for infants who survived more than 12 hours, were severe necrotizing enterocolitis, infection, bronchopulmonary dysplasia, severe intracranial hemorrhage, cystic periventricular leukomalacia, and/or severe retinopathy of prematurity. Regression models assessed yearly changes and were adjusted for study center, race/ethnicity, gestational age, birth weight for gestational age, and sex. Results Use of antenatal corticosteroids increased from 1993 to 2012 (24% [348 of 1431 infants]) to 87% (1674 of 1919 infants];P Conclusions and Relevance Among extremely preterm infants born at US academic centers over the last 20 years, changes in maternal and infant care practices and modest reductions in several morbidities were observed, although bronchopulmonary dysplasia increased. Survival increased most markedly for infants born at 23 and 24 weeks’ gestation and survival without major morbidity increased for infants aged 25 to 28 weeks. These findings may be valuable in counseling families and developing novel interventions. Trial Registration clinicaltrials.gov Identifier:NCT00063063.

1,818 citations


Authors

Showing all 13926 results

NameH-indexPapersCitations
Joel Schwartz1831149109985
Timothy A. Springer167669122421
Chien-Jen Chen12865566360
Matthew W. Gillman12652955835
J. D. Hansen12297576198
Dionysios D. Dionysiou11667548449
John P. Giesy114116262790
Douglas W. Dockery10524457461
Charles P. Gerba10269235871
David A. Savitz9957232947
Stephen Polasky9935459148
Judith C. Chow9642732632
Diane R. Gold9544330717
Scott L. Zeger9537778179
Rajender S. Varma9567237083
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202356
202279
2021780
2020787
2019852
2018929