Adverse outcome pathway networks II: Network analytics.
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| Title: | Adverse outcome pathway networks II: Network analytics. |
|---|---|
| Authors: | Villeneuve, Daniel L.1 villeneuve.dan@epa.gov, Angrish, Michelle M.2, Fortin, Marie C.3, Katsiadaki, Ioanna4, Leonard, Marc5, Margiotta‐Casaluci, Luigi6, Munn, Sharon7, O'Brien, Jason M.8, Pollesch, Nathan L.1, Smith, L. Cody9, Zhang, Xiaowei10, Knapen, Dries11 |
| Source: | Environmental Toxicology & Chemistry. Jun2018, Vol. 37 Issue 6, p1734-1748. 15p. |
| Subjects: | Risk assessment, Biological systems, Ecological disturbances, Environmental toxicology, Electric network topology |
| Abstract: | Abstract: Toxicological responses to stressors are more complex than the simple one‐biological‐perturbation to one‐adverse‐outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory–based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network‐based predictions, for use in research and regulatory decision‐making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734–1748. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America. [ABSTRACT FROM AUTHOR] |
| Copyright of Environmental Toxicology & Chemistry is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 129933077 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Adverse outcome pathway networks II: Network analytics. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Villeneuve%2C+Daniel+L%2E%22">Villeneuve, Daniel L.</searchLink><relatesTo>1</relatesTo><i> villeneuve.dan@epa.gov</i><br /><searchLink fieldCode="AR" term="%22Angrish%2C+Michelle+M%2E%22">Angrish, Michelle M.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Fortin%2C+Marie+C%2E%22">Fortin, Marie C.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Katsiadaki%2C+Ioanna%22">Katsiadaki, Ioanna</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Leonard%2C+Marc%22">Leonard, Marc</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Margiotta‐Casaluci%2C+Luigi%22">Margiotta‐Casaluci, Luigi</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Munn%2C+Sharon%22">Munn, Sharon</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22O'Brien%2C+Jason+M%2E%22">O'Brien, Jason M.</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Pollesch%2C+Nathan+L%2E%22">Pollesch, Nathan L.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Smith%2C+L%2E+Cody%22">Smith, L. Cody</searchLink><relatesTo>9</relatesTo><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xiaowei%22">Zhang, Xiaowei</searchLink><relatesTo>10</relatesTo><br /><searchLink fieldCode="AR" term="%22Knapen%2C+Dries%22">Knapen, Dries</searchLink><relatesTo>11</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Environmental+Toxicology+%26+Chemistry%22">Environmental Toxicology & Chemistry</searchLink>. Jun2018, Vol. 37 Issue 6, p1734-1748. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Biological+systems%22">Biological systems</searchLink><br /><searchLink fieldCode="DE" term="%22Ecological+disturbances%22">Ecological disturbances</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+toxicology%22">Environmental toxicology</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+network+topology%22">Electric network topology</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: Toxicological responses to stressors are more complex than the simple one‐biological‐perturbation to one‐adverse‐outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory–based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network‐based predictions, for use in research and regulatory decision‐making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734–1748. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Environmental Toxicology & Chemistry is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/etc.4124 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1734 Subjects: – SubjectFull: Risk assessment Type: general – SubjectFull: Biological systems Type: general – SubjectFull: Ecological disturbances Type: general – SubjectFull: Environmental toxicology Type: general – SubjectFull: Electric network topology Type: general Titles: – TitleFull: Adverse outcome pathway networks II: Network analytics. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Villeneuve, Daniel L. – PersonEntity: Name: NameFull: Angrish, Michelle M. – PersonEntity: Name: NameFull: Fortin, Marie C. – PersonEntity: Name: NameFull: Katsiadaki, Ioanna – PersonEntity: Name: NameFull: Leonard, Marc – PersonEntity: Name: NameFull: Margiotta‐Casaluci, Luigi – PersonEntity: Name: NameFull: Munn, Sharon – PersonEntity: Name: NameFull: O'Brien, Jason M. – PersonEntity: Name: NameFull: Pollesch, Nathan L. – PersonEntity: Name: NameFull: Smith, L. Cody – PersonEntity: Name: NameFull: Zhang, Xiaowei – PersonEntity: Name: NameFull: Knapen, Dries IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 07307268 Numbering: – Type: volume Value: 37 – Type: issue Value: 6 Titles: – TitleFull: Environmental Toxicology & Chemistry Type: main |
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