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Predicting modes of toxic action from chemical structure: Acute toxicity in the fathead minnow (Pimephales promelas)

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TLDR
An empirically derived database for diverse chemical structures of acute toxicity and corresponding modes of toxic action was developed through joint toxic action studies, the establishment of toxicodynamic profiles, and behavioral and dose‐response interpretation of 96‐h LC50 tests.
Abstract
In the field of aquatic toxicology, quantitative structure-activity relationships (QSARs) have developed as scientifically credible models for predicting the toxicity of chemicals when little or no empirical data are available. In recent years, there has been an evolution of QSAR development and application from that of a chemical-class perspective to one that is more consistent with assumptions regarding modes of toxic action. The objective of this research was to develop procedures that relate modes of acute toxic action in the fathead minnow (Pimephales promelas) to chemical structures and properties. An empirically derived database for diverse chemical structures of acute toxicity and corresponding modes of toxic action was developed through joint toxic action studies, the establishment of toxicodynamic profiles, and behavioral and dose-response interpretation of 96-h LC50 tests. Using the results from these efforts, as well as principles in the toxicological literature, approximately 600 chemicals were classified as narcotics (three distinct groups), oxidative phosphorylation uncouplers, respiratory inhibitors, electrophiles/proelectrophiles, acetylcholinesterase inhibitors, or central nervous system seizure agents. Using this data set, a computer-based expert system has been established whereby chemical structures are associated with likely modes of toxic action and, when available, corresponding QSARs.

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Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment

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.
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Uptake of veterinary medicines from soils into plants

TL;DR: Investigation of the potential for a range of veterinary medicines to be taken up from soil by plants used for human consumption and the potential significance of this exposure route in terms of human health found little evidence of an appreciable risk.
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Guidance on tiered risk assessment for plant protection products for aquatic organisms in edge-of-field surface waters

TL;DR: The Guidance of the PPR Panel was tasked to revise the Guidance Document on Aquatic Ecotoxicology and provides the scientific background for the risk assessment to aquatic organisms in edge-of-field surface waters and is structured to give detailed guidance on all assessment steps.
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Modes of action in ecotoxicology: their role in body burdens, species sensitivity, QSARs, and mixture effects.

TL;DR: This review seeks to show the crucial role of target sites, interactions with the target site(s), and mechanisms for an adequate and efficient ecotoxicological risk assessment and recommends the use of internal effect concentrations and target site concentrations as a mixture toxicity parameter.
Journal ArticleDOI

Description and evaluation of a short‐term reproduction test with the fathead minnow (Pimephales promelas)

TL;DR: The utility of this short‐term reproduction test with the fathead minnow is demonstrated for identifying chemicals that exert reproductive toxicity through alterations in endocrine systems controlled by estrogens and androgens.
References
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Journal ArticleDOI

SMILES, a chemical language and information system. 1. introduction to methodology and encoding rules

TL;DR: This chapter discusses the construction of Benzenoid and Coronoid Hydrocarbons through the stages of enumeration, classification, and topological properties in a number of computers used for this purpose.
Journal ArticleDOI

SMILES. 2. Algorithm for generation of unique SMILES notation

TL;DR: The chemical notation language SMILES is designed for the conversion of an arbitrarily chosen description of a chemical structure to one unique notation in a two-stage algorithm, CANGEN, where each atom is canonically ordered and labeled.
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