Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish
文献类型：期刊论文
| 作者 | Zhang, Shuying1,4; Wang, Zhongyu3; Chen, Jingwen2; Luo, Xiaojun1,4 ; Mai, Bixian1,4
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| 刊名 | ENVIRONMENTAL SCIENCE & TECHNOLOGY
 |
| 出版日期 | 2024-01-19 |
| 卷号 | 58期号:4页码:1944-1953 |
| 关键词 | tissue-to-blood partition coefficient multimodal model categorical feature embeddinglayer applicabilitydomain |
| ISSN号 | 0013-936X |
| DOI | 10.1021/acs.est.3c08016 |
| 英文摘要 | Tissue-to-blood partition coefficients (P-tb) are key parameters for assessing toxicokinetics of xenobiotics in organisms, yet their experimental data were lacking. Experimental methods for measuring P-tb values are inefficient, underscoring the urgent need for prediction models. However, most existing models failed to fully exploit P-tb data from diverse sources, and their applicability domain (AD) was limited. The current study developed a multimodal model capable of processing and integrating textual (categorical features) and numerical information (molecular descriptors/fingerprints) to simultaneously predict P-tb values across various species, tissues, blood matrices, and measurement methods. Artificial neural network algorithms with embedding layers were used for the multimodal modeling. The corresponding unimodal models were developed for comparison. Results showed that the multimodal model outperformed unimodal models. To enhance the reliability of the model, a method considering categorical features, weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes was used to characterize the AD. The model constrained by the AD exhibited better prediction accuracy for the validation set, with the determination coefficient, root mean-square error, and mean absolute error being 0.843, 0.276, and 0.213 log units, respectively. The multimodal model coupled with the AD characterization can serve as an efficient tool for internal exposure assessment of chemicals. |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001154822700001 |
| 源URL | [http://ir.gig.ac.cn/handle/344008/76191]  |
| 专题 | 有机地球化学国家重点实验室 |
| 通讯作者 | Chen, Jingwen; Luo, Xiaojun |
| 作者单位 | 1.Chinese Acad Sci, Guangzhou Inst Geochem, State Key Lab Organ Geochem, Guangzhou 510640, Peoples R China 2.Dalian Univ Technol, Sch Environm Sci & Technol, Dalian Key Lab Chem Risk Control & Pollut Prevent, Key Lab Ind Ecol & Environm Engn,Minist Educ, Dalian 116024, Peoples R China 3.Minist Ecol & Environm Peoples Republ China, Solid Waste & Chem Management Ctr, Beijing 100029, Peoples R China 4.Chinese Acad Sci, Guangzhou Inst Geochem, Guangdong Key Lab Environm Resources Utilizat & Pr, Guangzhou 510640, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Shuying,Wang, Zhongyu,Chen, Jingwen,et al. Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish[J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY,2024,58(4):1944-1953. |
| APA | Zhang, Shuying,Wang, Zhongyu,Chen, Jingwen,Luo, Xiaojun,&Mai, Bixian.(2024).Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish.ENVIRONMENTAL SCIENCE & TECHNOLOGY,58(4),1944-1953. |
| MLA | Zhang, Shuying,et al."Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish".ENVIRONMENTAL SCIENCE & TECHNOLOGY 58.4(2024):1944-1953. |
入库方式： OAI收割
来源：广州地球化学研究所
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