New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments

To assess the impact of chemicals on an aquatic environment, toxicological data for three trophic levels are needed to address the chronic and acute toxicities. The use of non-testing methods, such as predictive computational models, was proposed to avoid or reduce the need for animal models and spe...

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Autores principales:	Cosimo Toma, Claudia I. Cappelli, Alberto Manganaro, Anna Lombardo, Jürgen Arning, Emilio Benfenati
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	quantitative structure-activity relationship (QSAR) applicability domain <i>Raphidocelis subcapitata</i> <i>Daphnia magna</i> fish biological databases Organic chemistry QD241-441
Acceso en línea:	https://doaj.org/article/6e76605d8bf740d09b534d5a8e9bfaa7
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id	oai:doaj.org-article:6e76605d8bf740d09b534d5a8e9bfaa7
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spelling	oai:doaj.org-article:6e76605d8bf740d09b534d5a8e9bfaa72021-11-25T18:28:54ZNew Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments10.3390/molecules262269831420-3049https://doaj.org/article/6e76605d8bf740d09b534d5a8e9bfaa72021-11-01T00:00:00Zhttps://www.mdpi.com/1420-3049/26/22/6983https://doaj.org/toc/1420-3049To assess the impact of chemicals on an aquatic environment, toxicological data for three trophic levels are needed to address the chronic and acute toxicities. The use of non-testing methods, such as predictive computational models, was proposed to avoid or reduce the need for animal models and speed up the process when there are many substances to be tested. We developed predictive models for <i>Raphidocelis subcapitata</i>, <i>Daphnia magna</i>, and fish for acute and chronic toxicities. The random forest machine learning approach gave the best results. The models gave good statistical quality for all endpoints. These models are freely available for use as individual models in the VEGA platform and for prioritization in JANUS software.Cosimo TomaClaudia I. CappelliAlberto ManganaroAnna LombardoJürgen ArningEmilio BenfenatiMDPI AGarticlequantitative structure-activity relationship (QSAR)applicability domain<i>Raphidocelis subcapitata</i><i>Daphnia magna</i>fishbiological databasesOrganic chemistryQD241-441ENMolecules, Vol 26, Iss 6983, p 6983 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	quantitative structure-activity relationship (QSAR) applicability domain <i>Raphidocelis subcapitata</i> <i>Daphnia magna</i> fish biological databases Organic chemistry QD241-441
spellingShingle	quantitative structure-activity relationship (QSAR) applicability domain <i>Raphidocelis subcapitata</i> <i>Daphnia magna</i> fish biological databases Organic chemistry QD241-441 Cosimo Toma Claudia I. Cappelli Alberto Manganaro Anna Lombardo Jürgen Arning Emilio Benfenati New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
description	To assess the impact of chemicals on an aquatic environment, toxicological data for three trophic levels are needed to address the chronic and acute toxicities. The use of non-testing methods, such as predictive computational models, was proposed to avoid or reduce the need for animal models and speed up the process when there are many substances to be tested. We developed predictive models for <i>Raphidocelis subcapitata</i>, <i>Daphnia magna</i>, and fish for acute and chronic toxicities. The random forest machine learning approach gave the best results. The models gave good statistical quality for all endpoints. These models are freely available for use as individual models in the VEGA platform and for prioritization in JANUS software.
format	article
author	Cosimo Toma Claudia I. Cappelli Alberto Manganaro Anna Lombardo Jürgen Arning Emilio Benfenati
author_facet	Cosimo Toma Claudia I. Cappelli Alberto Manganaro Anna Lombardo Jürgen Arning Emilio Benfenati
author_sort	Cosimo Toma
title	New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
title_short	New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
title_full	New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
title_fullStr	New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
title_full_unstemmed	New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments
title_sort	new models to predict the acute and chronic toxicities of representative species of the main trophic levels of aquatic environments
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6e76605d8bf740d09b534d5a8e9bfaa7
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New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments

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