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Fish 3D 运动学应用程序:一款用户友好的计算机应用程序包,用于自动计算数据和提取鱼类新型水箱行为的终点。

Fish 3D Locomotion app: a user-friendly computer application package for automatic data calculation and endpoint extraction for novel tank behavior in fish.

机构信息

Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan.

Department of Bioscience Technology, Chung Yuan Christian University, Chung-Li, Taiwan.

出版信息

J Fish Biol. 2024 Oct;105(4):1086-1108. doi: 10.1111/jfb.15860. Epub 2024 Jul 15.

DOI:10.1111/jfb.15860
PMID:39007187
Abstract

This paper introduces the Fish 3D Locomotion app (F3LA), a Python-based, Graphical User Interface (GUI)-equipped tool designed to automate behavioral endpoint extraction in zebrafish locomotion assays. Building on our previous work, which utilized a specialized aquatic tank with a mirror and a single camera for fish movement tracking in three dimensions, F3LA significantly enhances data processing efficiency. Its accuracy was tested by reanalyzing and comprehensively comparing the calculated data with the previously published data from prior publications. From the comparison results, 90% of endpoints showed a similar statistical difference result. These minor differences were due to the different starting points for the dataset and updated calculation formulas that are implemented in F3LA. In addition, shoaling area or shoaling volume calculations are also included in F3LA as a new feature that can serve as sensitive indicators of social cohesion, group dynamics, or stress responses, offering insights into neuropsychological conditions or the effects of pharmacological interventions. Furthermore, F3LA offers a marked improvement over manual operations, being at least five times faster, while maintaining consistent accuracy as it reduces human-induced errors, ensuring a higher degree of reliability in the results. Finally, the potency of F3LA was tested to evaluate the toxicities of 14 rare earth elements (REEs) to the adult zebrafish behaviors. Based on the results, our findings suggested that each tested REE altered fish behaviors in different patterns and magnitudes to each other. However, among the tested light rare earth elements (LREEs), neodymium was demonstrated to cause more relatively severe behavior alterations than other LREEs, indicated by the statistically higher value of entropy (0.2695 ± 0.04977 (mean with a standard deviation)) than the control group (0.2352 ± 0.05896). Meanwhile, in terms of heavy rare earth elements (HREEs), erbium seemed to lead to more distinct behavior toxicities than other HREEs, which was shown by the statistically lower level of fractal dimension (2.022 ± 0.3412) than the untreated group (2.255 ± 0.1661). Taken together, F3LA's development marks a significant advance in high-throughput toxicological and pharmacological assessments in zebrafish, leveraging three-dimensional locomotion data for a more comprehensive analysis of fish behavior performance, providing a significant contribution to research in various fields.

摘要

本文介绍了 Fish 3D Locomotion app(F3LA),这是一个基于 Python 的图形用户界面(GUI)工具,旨在自动化斑马鱼运动分析中的行为终点提取。该工具是在我们之前的工作基础上开发的,之前的工作使用了一个带有镜子和一个摄像头的特殊水族箱来进行三维鱼的运动追踪,F3LA 显著提高了数据处理效率。其准确性通过重新分析和全面比较计算数据与之前出版物中已发表数据进行了测试。从比较结果来看,90%的终点显示出相似的统计差异结果。这些微小的差异是由于数据集的不同起点和 F3LA 中实现的更新计算公式造成的。此外,F3LA 还包括了群体区域或群体体积的计算,作为衡量群体凝聚力、群体动态或应激反应的敏感指标,为神经心理状况或药物干预效果提供了深入的了解。此外,F3LA 相对于手动操作有显著的改进,速度至少提高了五倍,同时保持了一致的准确性,因为它减少了人为错误,从而提高了结果的可靠性。最后,F3LA 的功效被测试以评估 14 种稀土元素(REEs)对成年斑马鱼行为的毒性。基于结果,我们发现每种测试的 REE 以不同的模式和程度改变了鱼的行为。然而,在所测试的轻稀土元素(LREEs)中,钕被证明比其他 LREEs 更能引起相对严重的行为改变,熵的统计值(0.2695 ± 0.04977(平均值加标准差))明显高于对照组(0.2352 ± 0.05896)。同时,在重稀土元素(HREEs)中,铒似乎比其他 HREEs 更能引起明显的行为毒性,这表现在分形维数的统计值(2.022 ± 0.3412)明显低于未处理组(2.255 ± 0.1661)。总之,F3LA 的开发标志着在斑马鱼高通量毒理学和药理学评估方面取得了重大进展,利用三维运动数据对鱼的行为表现进行更全面的分析,为各领域的研究做出了重要贡献。

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