Suppr超能文献

发育性血管毒性的系统建模

Systems Modeling of Developmental Vascular Toxicity.

作者信息

Saili Katerine S, Franzosa Jill A, Baker Nancy C, Ellis-Hutchings Robert G, Settivari Raja S, Carney Edward W, Spencer Richard, Zurlinden Todd J, Kleinstreuer Nicole C, Li Shuaizhang, Xia Menghang, Knudsen Thomas B

机构信息

National Center for Computational Toxicology (NCCT), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA) Research Triangle Park NC 27711.

Leidos, Research Triangle Park NC 27711.

出版信息

Curr Opin Toxicol. 2019 Jun 1;15(1):55-63. doi: 10.1016/j.cotox.2019.04.004.

Abstract

The more than 80,000 chemicals in commerce present a challenge for hazard assessments that toxicity testing in the 21 century strives to address through high-throughput screening (HTS) assays. Assessing chemical effects on human development adds an additional layer of complexity to the screening, with a need to capture complex and dynamic events essential for proper embryo-fetal development. HTS data from ToxCast/Tox21 informs systems toxicology models, which incorporate molecular targets and biological pathways into mechanistic models describing the effects of chemicals on human cells, 3D organotypic culture models, and small model organisms. Adverse Outcome Pathways (AOPs) provide a useful framework for integrating the evidence derived from these and systems to inform chemical hazard characterization. To illustrate this formulation, we have built an AOP for developmental toxicity through a mode of action linked to embryonic vascular disruption (Aop43). Here, we review the model for quantitative prediction of developmental vascular toxicity from ToxCast HTS data and compare the HTS results to functional vascular development assays in complex cell systems, virtual tissues, and small model organisms. ToxCast HTS predictions from several published and unpublished assays covering different aspects of the angiogenic cycle were generated for a test set of 38 chemicals representing a range of putative vascular disrupting compounds (pVDCs). Results boost confidence in the capacity to predict adverse developmental outcomes from HTS data and model computational dynamics for reconstruction of developmental systems biology. Finally, we demonstrate the integration of the AOP and developmental systems toxicology to investigate the unique modes of action of two angiogenesis inhibitors.

摘要

商业中超过8万种化学物质给危害评估带来了挑战,21世纪的毒性测试正努力通过高通量筛选(HTS)分析来应对这一挑战。评估化学物质对人类发育的影响给筛选工作增加了另一层复杂性,因为需要捕捉对胚胎-胎儿正常发育至关重要的复杂且动态的事件。来自ToxCast/Tox21的HTS数据为系统毒理学模型提供了信息,这些模型将分子靶点和生物途径纳入描述化学物质对人类细胞、3D器官型培养模型和小型模式生物影响的机制模型中。不良结局途径(AOP)为整合从这些系统和其他系统获得的证据以进行化学危害特征描述提供了一个有用的框架。为了说明这一构想,我们通过与胚胎血管破坏相关的作用模式构建了一个发育毒性的AOP(Aop43)。在此,我们回顾了从ToxCast HTS数据定量预测发育性血管毒性的模型,并将HTS结果与复杂细胞系统、虚拟组织和小型模式生物中的功能性血管发育分析结果进行了比较。针对一组代表一系列假定血管破坏化合物(pVDC)的38种化学物质的测试集,生成了来自多个已发表和未发表的涵盖血管生成周期不同方面的HTS预测结果。这些结果增强了我们对从HTS数据预测不良发育结局以及为重建发育系统生物学模拟计算动力学能力的信心。最后,我们展示了AOP与发育系统毒理学的整合,以研究两种血管生成抑制剂的独特作用模式。

相似文献

1
Systems Modeling of Developmental Vascular Toxicity.发育性血管毒性的系统建模
Curr Opin Toxicol. 2019 Jun 1;15(1):55-63. doi: 10.1016/j.cotox.2019.04.004.
5
Environmental impact on vascular development predicted by high-throughput screening.高通量筛选预测血管发育的环境影响。
Environ Health Perspect. 2011 Nov;119(11):1596-603. doi: 10.1289/ehp.1103412. Epub 2011 Jul 25.
9
Predictive models and computational toxicology.预测模型与计算毒理学
Methods Mol Biol. 2013;947:343-74. doi: 10.1007/978-1-62703-131-8_26.

引用本文的文献

3
Computational Biology and Toxicodynamics.计算生物学与毒理学动力学
Curr Opin Toxicol. 2020 Dec 1;23-24(Oct-Dec 2020):119-126. doi: 10.1016/j.cotox.2020.11.001.
9
The liver, a functionalized vascular structure.肝脏,一种功能化的血管结构。
Sci Rep. 2020 Oct 1;10(1):16194. doi: 10.1038/s41598-020-73208-8.
10
An ontology for developmental processes and toxicities of neural tube closure.神经管闭合的发育过程和毒性的本体论。
Reprod Toxicol. 2021 Jan;99:160-167. doi: 10.1016/j.reprotox.2020.09.002. Epub 2020 Sep 11.

本文引用的文献

9
ToxCast Chemical Landscape: Paving the Road to 21st Century Toxicology.ToxCast化学图谱:为21世纪毒理学铺平道路。
Chem Res Toxicol. 2016 Aug 15;29(8):1225-51. doi: 10.1021/acs.chemrestox.6b00135. Epub 2016 Jul 20.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验