根据经合组织测试指南421/422测试的有机化合物的发育和生殖毒性的交叉驱动二元分类。

IF 2.3 3区 环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY
M Chatterjee, S Pore, Z Szepesi, K Roy
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引用次数: 0

摘要

发育和生殖毒性(DART)是指由于暴露于有毒物质或化学物质而对性功能、生育能力和后代发育造成的不良影响,这种影响可能发生在生殖周期的各个阶段。为了应对化学品数量的增加,监管机构提倡实施各种新的方法方法(NAMs)作为动物试验的替代品,从而能够快速评估许多化学物质的潜在毒性。在这项研究中,在硅的方法被用来评估DART性质的各种工业化学品。我们采用了基于Read-Across (RA)的二元分类方法来评估这些化学物质的DART潜力。二元分类的数据来自两个不同的来源:eChemPortal (https://www.echemportal.org/echemportal/)和美国国立卫生科学研究所(NIHS)的数据库。从这些来源收集的信息包括两种类型的毒性数据:无观察到的不良影响水平(NOAEL)和低观察到的不良影响水平(LOAEL),根据经济合作与发展组织测试指南421和422,采用良好实验室规范(GLP)的原则进行测试。通过基于二元分类的跨读预测,这些数据被单独用于安全性评估,显示出对新化学品的良好分类能力(Accuracytest ~0.700)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Read-across-driven binary classification for the developmental and reproductive toxicity of organic compounds tested according to the OECD test guidelines 421/422.

Developmental and reproductive toxicity (DART) refers to the adverse effects on sexual function, fertility, and the development of offspring resulting from exposure to toxic substances or chemicals, which may occur at various stages of the reproductive cycle. In response to the increasing volume of chemicals, regulatory bodies advocate for implementing various new approach methodologies (NAMs) as alternatives to animal testing, enabling rapid assessments of the toxic potential of numerous chemical substances. In this study, in silico methodologies were utilized to assess the DART properties of various industrial chemicals. We employed a Read-Across (RA)-based binary classification approach to evaluate the DART potential of these chemicals. The data for the binary classification have been compiled from two distinct sources: eChemPortal (https://www.echemportal.org/echemportal/) and the National Institute of Health Sciences (NIHS) databases. The information gathered from these sources encompasses two types of toxicity data: No Observed Adverse Effect Level (NOAEL) and Low Observed Adverse Effect Level (LOAEL) tested as per the Organisation for Economic Co-operation and Development Test Guidelines 421 and 422, adopting the principles of Good Laboratory Practice (GLP). The data were utilized separately for safety assessment through a binary classification-based read-across prediction, demonstrating commendable classification capabilities for new chemicals (Accuracytest ~0.700).

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来源期刊
CiteScore
5.20
自引率
20.00%
发文量
78
审稿时长
>24 weeks
期刊介绍: SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
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