Chen D, Kannan K, Tan H L, et al. Bisphenol analogues other than BPA: Environmental occurrence, human exposure, and toxicity—A review[J]. Environmental Science & Technology, 2016, 50(11): 5438-5453
Liu R Z, Mabury S A. Synthetic phenolic antioxidants in personal care products in Toronto, Canada: Occurrence, human exposure, and discharge via greywater[J]. Environmental Science & Technology, 2019, 53(22): 13440-13448
Provencher J F, Malaisé F, Mallory M L, et al. 44-year retrospective analysis of ultraviolet absorbents and industrial antioxidants in seabird eggs from the Canadian Arctic (1975 to 2019)[J]. Environmental Science & Technology, 2022, 56(20): 14562-14573
Li Y N, Yao J Z, Zhang J, et al. First report on the bioaccumulation and trophic transfer of perfluoroalkyl ether carboxylic acids in estuarine food web[J]. Environmental Science & Technology, 2022, 56(10): 6046-6055
Gaballah S, Swank A, Sobus J R, et al. Evaluation of developmental toxicity, developmental neurotoxicity, and tissue dose in zebrafish exposed to GenX and other PFAS[J]. Environmental Health Perspectives, 2020, 128(4): 47005
Zhang T T, Zhou X, Xu A M, et al. Toxicity of polybrominated diphenyl ethers (PBDEs) on rodent male reproductive system: A systematic review and meta-analysis of randomized control studies[J]. The Science of the Total Environment, 2020, 720: 137419
Li F, Li X H, Shao J P, et al. Estrogenic activity of anthraquinone derivatives: in vitro and in silico studies[J]. Chemical Research in Toxicology, 2010, 23(8): 1349-1355
Luo T L, Chen J W, Song B, et al. Time-gated luminescence imaging of singlet oxygen photoinduced by fluoroquinolones and functionalized graphenes in Daphnia magna[J]. Aquatic Toxicology, 2017, 191: 105-112
Rockström J, Steffen W, Noone K, et al. A safe operating space for humanity[J]. Nature, 2009, 461(7263): 472-475
陈景文, 全燮. 环境化学[M]. 大连: 大连理工大学出版社, 2009: 170-176
European Union. Regulation (EC) No. 1907/2006 of the European Parliament and of the Council of 18 December 2006, concerning the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH)[R]. Brussels: European Union, 2006
中华人民共和国生态环境部. 新化学物质环境管理登记指南[R]. 北京: 中华人民共和国生态环境部, 2020
Organisation for Economic Co-operation and Development (OECD). OECD guidelines for the testing of chemicals, Test No. 305: Bioaccumulation in fish: Aqueous and dietary exposure[R]. Paris: OECD, 2012
Zhao C Y, Boriani E, Chana A, et al. A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)[J]. Chemosphere, 2008, 73(11): 1701-1707
Dearden J C, Hewitt M. QSAR modelling of bioconcentration factor using hydrophobicity, hydrogen bonding and topological descriptors[J]. SAR and QSAR in Environmental Research, 2010, 21(7-8): 671-680
Strempel S, Nendza M, Scheringer M, et al. Using conditional inference trees and random forests to predict the bioaccumulation potential of organic chemicals[J]. Environmental Toxicology and Chemistry, 2013, 32(5): 1187-1195
郑玉婷, 乔显亮, 于洋, 等. 有机化学品生物富集因子定量结构-活性关系模型[J]. 生态毒理学报, 2019, 14(2): 214-221 Zheng Y T, Qiao X L, Yu Y, et al. Quantitative structure-activity relationship model for bioconcentration factors of organic chemicals[J]. Asian Journal of Ecotoxicology, 2019, 14(2): 214-221(in Chinese)
丁蕊, 陈景文, 于洋, 等. 基于集成学习算法构建有机化学品鱼体生物富集因子的QSAR预测模型[J]. 环境化学, 2021, 40(5): 1295-1304 Ding R, Chen J W, Yu Y, et al. Using ensemble learning algorithms to develop QSAR models on bioconcentration factors of organic chemicals in multispecies fish[J]. Environmental Chemistry, 2021, 40(5): 1295-1304(in Chinese)
Fatemi M H, Abraham M H, Haghdadi M. Prediction of biomagnification factors for some organochlorine compounds using linear free energy relationship parameters and artificial neural networks[J]. SAR and QSAR in Environmental Research, 2009, 20(5-6): 453-465
Caruana R. Multitask learning[J]. Machine Learning, 1997, 28(1): 41-75
Muratov E N, Bajorath J, Sheridan R P, et al. QSAR without borders[J]. Chemical Society Reviews, 2020, 49(11): 3525-3564
Wu Z X, Jiang D J, Wang J K, et al. Mining toxicity information from large amounts of toxicity data[J]. Journal of Medicinal Chemistry, 2021, 64(10): 6924-6936
Zhang Y, Yang Q. An overview of multi-task learning[J]. National Science Review, 2018, 5(1): 30-43
Wu K D, Zhao Z X, Wang R X, et al. TopP-S: Persistent homology-based multi-task deep neural networks for simultaneous predictions of partition coefficient and aqueous solubility[J]. Journal of Computational Chemistry, 2018, 39(20): 1444-1454
Wu K D, Wei G W. Quantitative toxicity prediction using topology based multitask deep neural networks[J]. Journal of Chemical Information and Modeling, 2018, 58(2): 520-531
Arnot J, Gobas F. A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in aquatic organisms[J]. Environmental Reviews, 2006, 14(4): 257-297
Arnot J A, Quinn C L. Development and evaluation of a database of dietary bioaccumulation test data for organic chemicals in fish[J]. Environmental Science & Technology, 2015, 49(8): 4783-4796
Grisoni F, Consonni V, Vighi M. Acceptable-by-design QSARs to predict the dietary biomagnification of organic chemicals in fish[J]. Integrated Environmental Assessment and Management, 2019, 15(1): 51-63
Mansouri K, Consonni V, Durjava M K, et al. Assessing bioaccumulation of polybrominated diphenyl ethers for aquatic species by QSAR modeling[J]. Chemosphere, 2012, 89(4): 433-444
Talete S R L. DRAGON (Software for Molecular Descriptor Calculation) Version 6.0[CP].Italy: TALETE SRL, 2012
Bikesh K, Kesari V, S Thoke A. Investigations on impact of feature normalization techniques on classifier's performance in breast tumor classification[J]. International Journal of Computer Applications, 2015, 116(19): 11-15
Rumelhart D E, Hinton G E, Williams R J. Learning representations by back-propagating errors[J]. Nature, 1986, 323(6088): 533-536
覃礼堂, 刘树深, 肖乾芬, 等. QSAR模型内部和外部验证方法综述[J]. 环境化学, 2013, 32(7): 1205-1211 Qin L T, Liu S S, Xiao Q F, et al. Internal and external validations of QSAR model: Review[J]. Environmental Chemistry, 2013, 32(7): 1205-1211(in Chinese)
Wang Z Y, Chen J W, Hong H X. Applicability domains enhance application of PPARγ agonist classifiers trained by drug-like compounds to environmental chemicals[J]. Chemical Research in Toxicology, 2020, 33(6): 1382-1388
Wang Z Y, Chen J W, Hong H X. Developing QSAR models with defined applicability domains on PPARγ binding affinity using large data sets and machine learning algorithms[J]. Environmental Science & Technology, 2021, 55(10): 6857-6866
Wang H T, Xia X H, Wang Z X, et al. Contribution of dietary uptake to PAH bioaccumulation in a simplified pelagic food chain: Modeling the influences of continuous vs intermittent feeding in zooplankton and fish[J]. Environmental Science & Technology, 2021, 55(3): 1930-1940
Wang H T, Xia X H, Liu R, et al. Multicompartmental toxicokinetic modeling of discrete dietary and continuous waterborne uptake of two polycyclic aromatic hydrocarbons by zebrafish Danio rerio[J]. Environmental Science & Technology, 2020, 54(2): 1054-1065