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High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review.
Liu, Jifu; Xiang, Tongtong; Song, Xue-Chao; Zhang, Shaoqing; Wu, Qi; Gao, Jie; Lv, Meilin; Shi, Chunzhen; Yang, Xiaoxi; Liu, Yanna; Fu, Jianjie; Shi, Wei; Fang, Mingliang; Qu, Guangbo; Yu, Hongxia; Jiang, Guibin.
Afiliação
  • Liu J; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Xiang T; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
  • Song XC; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Zhang S; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Wu Q; College of Sciences, Northeastern University, Shenyang 110004, China.
  • Gao J; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Lv M; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
  • Shi C; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Yang X; State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
  • Liu Y; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Fu J; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
  • Shi W; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Fang M; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Qu G; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
  • Yu H; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Jiang G; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Environ Sci Technol ; 58(23): 9925-9944, 2024 Jun 11.
Article em En | MEDLINE | ID: mdl-38820315
ABSTRACT
Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental Idioma: En Revista: Environ Sci Technol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental Idioma: En Revista: Environ Sci Technol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China