Data-driven modeling of zebrafish behavioral response to acute caffeine administration
Data-driven modeling of zebrafish behavioral response to acute caffeine administration
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DOI：
10.1016/j.jtbi.2019.110054
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发表时间：
2020-01-21
影响因子：
2
通讯作者：
Porfiri, Maurizio
中科院分区：
文献类型：
--
作者：
Burbano-L, Daniel A.;Porfiri, Maurizio
在过去的三十年里，我们见证了斑马鱼在临床前研究中的应用急剧增加。每年有超过5000篇关于斑马鱼的技术论文发表，其中许多试图通过动物实验来解释焦虑的基础。计算机模拟实验可以通过提供新的手段来支持替代、减少和改进的3R原则，从而为斑马鱼研究和福利做出重大贡献。在这里，我们提出了一个数据驱动的建模框架来预测焦虑相关的行为反应的斑马鱼急性咖啡因管理。建模框架沿两个时间尺度二分法展开，以捕获沿慢时间尺度的冻结行为和在快时间尺度的爆发和海岸运动。锚定在马尔可夫链和随机微分方程的理论，我们展示了一个简约，但强大的建模框架，以准确地模拟实验观察斑马鱼在不同的咖啡因浓度。我们的研究结果补充了最近的建模工作，为在斑马鱼行为药理学中进行计算机模拟实验奠定了基础。(C)2019爱思唯尔有限公司版权所有。
Over the last thirty years, we have witnessed a dramatic rise in the use of zebrafish in preclinical research. Every year, more than 5000 technical papers are published about zebrafish, many of them seeking to explain the underpinnings of anxiety through animal testing. In-silico experiments could significantly contribute to zebrafish research and welfare, by offering new means to support the 3Rs principles of replacement, reduction, and refinement. Here, we propose a data-driven modeling framework to predict the anxiety-related behavioral response of zebrafish to acute caffeine administration. The modeling framework unfolds along a two-time-scale dichotomy to capture freezing behavior along a slow temporal scale and burst-and-coast locomotion at a fast time-scale. Anchored in the theory of Markov chains and stochastic differential equations, we demonstrate a parsimonious, yet robust, modeling framework to accurately simulate experimental observations of zebrafish treated at different caffeine concentrations. Our results complement recent modeling efforts, laying the foundations for conducting in-silico experiments in zebrafish behavioral pharmacology. (C) 2019 Elsevier Ltd. All rights reserved.