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整合发育神经毒性体外新方法学的数据。

Integrating Data From In Vitro New Approach Methodologies for Developmental Neurotoxicity.

机构信息

Center for Computational Toxicology and Exposure, ORD, U.S. EPA, Research Triangle Park, North Carolina 27711, USA.

Oak Ridge Associated Universities, Oak Ridge, Tennessee 37830, USA.

出版信息

Toxicol Sci. 2022 Apr 26;187(1):62-79. doi: 10.1093/toxsci/kfac018.

Abstract

In vivo developmental neurotoxicity (DNT) testing is resource intensive and lacks information on cellular processes affected by chemicals. To address this, DNT new approach methodologies (NAMs) are being evaluated, including: the microelectrode array neuronal network formation assay; and high-content imaging to evaluate proliferation, apoptosis, neurite outgrowth, and synaptogenesis. This work addresses 3 hypotheses: (1) a broad screening battery provides a sensitive marker of DNT bioactivity; (2) selective bioactivity (occurring at noncytotoxic concentrations) may indicate functional processes disrupted; and, (3) a subset of endpoints may optimally classify chemicals with in vivo evidence for DNT. The dataset was comprised of 92 chemicals screened in all 57 assay endpoints sourced from publicly available data, including a set of DNT NAM evaluation chemicals with putative positives (53) and negatives (13). The DNT NAM battery provides a sensitive marker of DNT bioactivity, particularly in cytotoxicity and network connectivity parameters. Hierarchical clustering suggested potency (including cytotoxicity) was important for classifying positive chemicals with high sensitivity (93%) but failed to distinguish patterns of disrupted functional processes. In contrast, clustering of selective values revealed informative patterns of differential activity but demonstrated lower sensitivity (74%). The false negatives were associated with several limitations, such as the maximal concentration tested or gaps in the biology captured by the current battery. This work demonstrates that this multi-dimensional assay suite provides a sensitive biomarker for DNT bioactivity, with selective activity providing possible insight into specific functional processes affected by chemical exposure and a basis for further research.

摘要

体内发育神经毒性(DNT)测试资源密集且缺乏有关受化学物质影响的细胞过程的信息。为了解决这个问题,正在评估 DNT 新方法方法(NAM),包括:微电极阵列神经元网络形成测定法;以及高内涵成像以评估增殖、细胞凋亡、神经突生长和突触发生。这项工作解决了 3 个假设:(1)广泛的筛选电池提供了 DNT 生物活性的敏感标志物;(2)选择性生物活性(在非细胞毒性浓度下发生)可能表明功能过程受到干扰;(3)一组终点可能最佳地对具有体内 DNT 证据的化学物质进行分类。该数据集由 92 种化学物质组成,这些化学物质在所有 57 个检测终点中进行了筛选,这些检测终点来自公开可用的数据,包括一组具有潜在阳性(53 种)和阴性(13 种)的 DNT NAM 评估化学物质。DNT NAM 电池提供了 DNT 生物活性的敏感标志物,特别是在细胞毒性和网络连接性参数方面。层次聚类表明,效力(包括细胞毒性)对于以高灵敏度(93%)分类阳性化学物质很重要,但未能区分功能过程中断的模式。相比之下,选择性值的聚类揭示了信息丰富的差异活性模式,但灵敏度较低(74%)。假阴性与几个限制因素有关,例如测试的最大浓度或当前电池所捕获的生物学空白。这项工作表明,这种多维测定套件为 DNT 生物活性提供了敏感的生物标志物,选择性活性可能为受化学物质暴露影响的特定功能过程提供了深入的见解,并为进一步的研究奠定了基础。

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