{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:44:21Z","timestamp":1792784661889,"version":"4.5.0"},"reference-count":94,"publisher":"American Chemical Society (ACS)","issue":"41","license":[{"start":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:00:00Z","timestamp":1791331200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:00:00Z","timestamp":1791331200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:00:00Z","timestamp":1791331200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"name":"National Natural Science Foundation of China (NSFC)","award":["42577299"],"award-info":[{"award-number":["42577299"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Traditional toxicological testing cannot meet regulatory demands for numerous chemicals in aquatic environments. New Approach Methodologies (NAMs) such as High-Throughput Screening (HTS) and Adverse Outcome Pathway (AOP) framework offer sustainable alternatives. Here, we built a comprehensive Quantitative Structure\u2013Activity Relationship (QSAR) prediction and risk assessment framework that integrates a multidomain deep learning model, applicability domain assessment, and toxicity risk prioritization. Specifically, by applying in vitro HTS bioactivity to multiple Molecular Initiating Events (MIEs) and Key Events (KEs) in Daphnia magna AOP network, we compiled a data set (6971 chemicals \u00d7 10,024 multidimensional structure descriptors) exhibiting high chemical structural diversity and strong representativeness of environmentally relevant chemicals. QSAR prediction models covering application domains of multiple MIEs\/KEs were further developed. The 6971 chemicals were risk-prioritized based on the AOP network topology, with the ranking results consistent with existing toxicological evidence. In addition, chemicals with potential combined toxic risks were identified. An out-of-the-box aquatic toxicity prediction and risk assessment tool is provided, enabling automated multitarget bioactivity prediction, reliability and decidability evaluation, and toxic risk profiling for new chemicals. This study represents a concrete application of \u201cAI for Science\u201d in ecotoxicology, aiming to reduce the dependence on traditional animal experiments. It simplifies the identification of potential toxic effects and bypasses in vivo validation processes to advance the sustainable management of environmental chemicals.<\/jats:p>","DOI":"10.1021\/acs.est.6c06646","type":"journal-article","created":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T23:01:40Z","timestamp":1791414100000},"page":"29325-29341","source":"Crossref","is-referenced-by-count":0,"title":["Mechanistic Prediction\nand High-Throughput Risk Screening\nof Aquatic Contaminants Using\n                    <i>Daphnia magna<\/i>\n                    AOP Network"],"prefix":"10.1021","volume":"60","author":[{"given":"Yu-Ting","family":"Yang","sequence":"first","affiliation":[{"name":"Peking University Shenzhen Graduate School , , ,","place":["Shenzhen, China, 518055"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xing-Peng","family":"Wei","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School , , ,","place":["Shenzhen, China, 518055"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Meng","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School , , ,","place":["Shenzhen, China, 518055"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang-Bo","family":"Yuan","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School , , ,","place":["Shenzhen, China, 518055"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing-Xuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School , , ,","place":["Shenzhen, China, 518055"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2331-2667","authenticated-orcid":true,"given":"Hong-Gang","family":"Ni","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School , , ,","place":["Shenzhen, China, 518055"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,10,7]]},"reference":[{"key":"2026102007521389700_cit1","doi-asserted-by":"publisher","DOI":"10.1016\/j.envpol.2023.122889","article-title":"Advances in Identifying and Managing Emerging Contaminants\nin Aquatic Ecosystems: Analytical Approaches, Toxicity Assessment,\nTransformation Pathways, Environmental Fate, and Remediation Strategies","volume":"341","author":"Mofijur","year":"2024","journal-title":"Environ. Pollut."},{"key":"2026102007521389700_cit2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemosphere.2023.139945","article-title":"Emerging\nMicropollutants\nin Aquatic Ecosystems and Nanotechnology-Based Removal Alternatives:\nA Review","volume":"341","author":"Narwal","year":"2023","journal-title":"Chemosphere"},{"key":"2026102007521389700_cit3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jenvman.2023.117344","article-title":"Emerging\nEnvironmental Contaminants:\nA Global Perspective on Policies and Regulations","volume":"332","author":"Puri","year":"2023","journal-title":"J. Environ. Manage."},{"key":"2026102007521389700_cit4","doi-asserted-by":"publisher","first-page":"954","DOI":"10.1016\/j.envpol.2017.08.032","article-title":"Occurrence,\nFate and Transformation of Emerging Contaminants in Water: An Overarching\nReview of the Field","volume":"231","author":"Wilkinson","year":"2017","journal-title":"Environ. Pollut."},{"key":"2026102007521389700_cit5","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.jpba.2014.11.040","article-title":"Pharmaceuticals\nin the Environment:\nBiodegradation and Effects on Natural Microbial Communities. A Review","volume":"106","author":"Caracciolo","year":"2015","journal-title":"J. Pharm. Biomed. Anal."},{"issue":"14","key":"2026102007521389700_cit6","doi-asserted-by":"publisher","first-page":"9508","DOI":"10.1021\/acs.est.0c06773","article-title":"Recognition and Prioritization\nof Chemical Mixtures and Transformation Products in Chinese Estuarine\nWaters by Suspect Screening Analysis","volume":"55","author":"Feng","year":"2021","journal-title":"Environ.\nSci. Technol."},{"key":"2026102007521389700_cit7","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.aquatox.2013.12.003","article-title":"The Biological Effects of Antidepressants on the Molluscs\nand Crustaceans: A Review","volume":"151","author":"Fong","year":"2014","journal-title":"Aquat. Toxicol."},{"issue":"22","key":"2026102007521389700_cit8","doi-asserted-by":"publisher","first-page":"10711","DOI":"10.1021\/acs.est.5c05712","article-title":"Beyond the\nSingle-Contaminant Paradigm: Advancing Mixture Toxicity\nand Cumulative Risk Assessment in Environmental Toxicology","volume":"59","author":"Yan","year":"2025","journal-title":"Environ. Sci. Technol."},{"issue":"5","key":"2026102007521389700_cit9","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1289\/ehp.0800168","article-title":"The Toxicity Data Landscape for Environmental\nChemicals","volume":"117","author":"Judson","year":"2009","journal-title":"Environ. 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Sci."},{"key":"2026102007521389700_cit13","doi-asserted-by":"publisher","DOI":"10.1016\/j.comtox.2025.100399","article-title":"Development\nof Machine Learning-Based\nMulti-Task Quantitative Structure\u2013Activity Relationship Models\nfor Predicting Toxicities in Six Human Organ Systems","volume":"37","author":"Wu","year":"2026","journal-title":"Comput. Toxicol."},{"issue":"5","key":"2026102007521389700_cit14","first-page":"523","article-title":"The Welfare of Animals\nUsed in Science:\nHow the \u201cThree Rs\u201d Ethic Guides Improvements","volume":"50","author":"Fenwick","year":"2009","journal-title":"Can. Vet. 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Mellifera) through Innovative\nQSAR Models","volume":"704","author":"Carnesecchi","year":"2020","journal-title":"Sci. Total Environ."},{"key":"2026102007521389700_cit18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhazmat.2020.124936","article-title":"Prediction of Aquatic\nToxicity of Chemical Mixtures by the QSAR Approach\nUsing 2D Structural Descriptors","volume":"408","author":"Chatterjee","year":"2021","journal-title":"J. Hazard.\nMater."},{"key":"2026102007521389700_cit19","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1016\/B978-0-12-813697-3.00031-7","article-title":"Computational\nMethods to Predict Toxicity","volume-title":"The History\nof Alternative Test Methods in Toxicology","author":"Cronin","year":"2019"},{"key":"2026102007521389700_cit20","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.chemosphere.2019.04.204","article-title":"QSAR Modeling of Daphnia magna and Fish Toxicities of Biocides Using 2D Descriptors","volume":"229","author":"Khan","year":"2019","journal-title":"Chemosphere"},{"key":"2026102007521389700_cit21","doi-asserted-by":"publisher","DOI":"10.1016\/j.watres.2023.119981","article-title":"Predictive in Silico\nModels for Aquatic Toxicity of Cosmetic and\nPersonal Care Additive Mixtures","volume":"236","author":"Yang","year":"2023","journal-title":"Water Res."},{"key":"2026102007521389700_cit22","doi-asserted-by":"publisher","DOI":"10.1007\/s11030-025-11454-6","article-title":"Deep Learning-Enhanced QSAR Modeling for Predicting\nDevelopmental Neurotoxicity Based on Molecular Initiating Events from\nAdverse Outcome Pathways","volume":"30","author":"de Sousa Pereira","year":"2026","journal-title":"Mol. 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Toxicol."},{"issue":"4","key":"2026102007521389700_cit28","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1089\/aivt.2017.0021","article-title":"Relationship Between Adverse Outcome Pathways and Chemistry-Based\nIn Silico Models to Predict Toxicity","volume":"3","author":"Cronin","year":"2017","journal-title":"Appl.\nIn Vitro Toxicol."},{"issue":"1","key":"2026102007521389700_cit29","doi-asserted-by":"publisher","DOI":"10.1186\/s12989-020-00344-4","article-title":"Adverse Outcome Pathways as a Tool for the Design of Testing Strategies\nto Support the Safety Assessment of Emerging Advanced Materials at\nthe Nanoscale","volume":"17","author":"Halappanavar","year":"2020","journal-title":"Part. Fibre Toxicol."},{"issue":"20","key":"2026102007521389700_cit30","doi-asserted-by":"publisher","first-page":"14237","DOI":"10.1021\/acs.est.2c01799","article-title":"Daphnia as a Sentinel Species for\nEnvironmental Health\nProtection: A Perspective on Biomonitoring and Bioremediation of Chemical\nPollution","volume":"56","author":"Abdullahi","year":"2022","journal-title":"Environ. Sci. Technol."},{"issue":"4","key":"2026102007521389700_cit31","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1093\/icb\/icr103","article-title":"An Integrated Multi-Disciplinary\nApproach for Studying Multiple Stressors in Freshwater Ecosystems:\nDaphnia as a Model Organism","volume":"51","author":"Altshuler","year":"2011","journal-title":"Integr. Comp. 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ToxCast\n& Tox21 MySQL Data from Invitrodb_v4.2. 2024https:\/\/www.epa.gov\/chemical-research\/toxicity-forecaster-toxcasttm-data."},{"key":"2026102007521389700_cit36","unstructured":"EMBL.\n          . ChEMBL MySQL\nData from ChEMBL_35. 2024, 10.6019\/CHEMBL.database.35."},{"key":"2026102007521389700_cit37","doi-asserted-by":"publisher","DOI":"10.1016\/j.tiv.2022.105451","article-title":"Application\nof ToxCast\/Tox21 Data for Toxicity Mechanism-Based\nEvaluation and Prioritization of Environmental Chemicals: Perspective\nand Limitations","volume":"84","author":"Jeong","year":"2022","journal-title":"Toxicol. in Vitro"},{"issue":"2","key":"2026102007521389700_cit38","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1021\/acs.chemrestox.0c00304","article-title":"In Silico\nModels to Predict the Perturbation of Molecular Initiating Events\nRelated to Thyroid Hormone Homeostasis","volume":"34","author":"de Lomana","year":"2021","journal-title":"Chem.\nRes. 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