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用于预测神经管闭合缺陷的计算动态系统模型。

A computational dynamic systems model for prediction of neural tube closure defects.

作者信息

Berkhout Job H, Glazier James A, Piersma Aldert H, Belmonte Julio M, Legler Juliette, Spencer Richard M, Knudsen Thomas B, Heusinkveld Harm J

机构信息

Centre for Health Protection, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.

出版信息

Curr Res Toxicol. 2024 Dec 18;8:100210. doi: 10.1016/j.crtox.2024.100210. eCollection 2025.

Abstract

Neural tube closure is a critical morphogenetic event during early vertebrate development. This complex process is susceptible to perturbation by genetic errors and chemical disruption, which can induce severe neural tube defects (NTDs) such as spina bifida. We built a computational agent-based model (ABM) of neural tube development based on the known biology of morphogenetic signals and cellular biomechanics underlying neural fold elevation, bending and fusion. The computer model functionalizes cell signals and responses to render a dynamic representation of neural tube closure. Perturbations in the control network can then be introduced synthetically or from biological data to yield quantitative simulation and probabilistic prediction of NTDs by incidence and degree of defect. Translational applications of the model include mechanistic understanding of how singular or combinatorial alterations in gene-environmental interactions and animal-free assessment of developmental toxicity for an important human birth defect (spina bifida) and potentially other neurological problems linked to development of the brain and spinal cord.

摘要

神经管闭合是脊椎动物早期发育过程中的一个关键形态发生事件。这个复杂的过程容易受到基因错误和化学干扰的影响,这些干扰会诱发严重的神经管缺陷(NTDs),如脊柱裂。我们基于神经管褶皱抬高、弯曲和融合背后的形态发生信号和细胞生物力学的已知生物学知识,构建了一个基于计算智能体的神经管发育模型(ABM)。该计算机模型将细胞信号和反应功能化,以呈现神经管闭合的动态表示。然后,可以通过合成或从生物学数据中引入控制网络中的扰动,以通过缺陷的发生率和程度对NTDs进行定量模拟和概率预测。该模型的转化应用包括对基因-环境相互作用中的单一或组合改变如何导致重要人类出生缺陷(脊柱裂)以及潜在的与脑和脊髓发育相关的其他神经问题进行机制理解,以及对发育毒性进行无动物评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0ca/11875186/b9a079265121/ga1.jpg

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