计算生物学
神经科学
透视图(图形)
核受体
风险分析(工程)
生物
计算机科学
系统生物学
表观遗传学
保护
认知科学
数据科学
生化工程
生物信息学
工程伦理学
神经毒性
人类健康
有机体
大脑研究
立场文件
概念框架
术语
后生
基因调控网络
化学毒性
预防原则
模块化(生物学)
计算模型
作者
Yitong Lu,Li Ren,Jia Yu,Tiehua Zhang,Jie Zhang
标识
DOI:10.1021/acs.est.5c14620
摘要
Endocrine-disrupting chemicals (EDCs) are ubiquitous environmental contaminants linked to rising neurodevelopmental disorders, yet the neurotoxicity of real-world low-dose mixtures remains poorly understood. This review establishes a conceptual framework positioning the nuclear receptor (NR) superfamily as the central integrative hub, where structurally diverse EDC signals converge. Transcending traditional single-chemical paradigms, we detail how mixtures co-opt the NR network through molecular crosstalk, heterodimer competition, and epigenetic reprogramming. Such disruptions trigger pathogenic cascades, including dysregulated neuroinflammation, impaired synaptic plasticity, and bioenergetic collapse, that compromise brain development. We critically evaluate state-of-the-art experimental and computational models, from brain organoids to microphysiological systems, advocating for an integrated systems toxicology approach. Leveraging time-series multiomics and dynamic network modeling is essential to identify mechanistic thresholds and assess potential transgenerational risks. This NR-centered framework provides a robust foundation for evolving the discipline from descriptive toxicology to predictive, next-generation risk assessment, ultimately safeguarding brain health in an increasingly complex chemical environment.
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