作者
Murilo Nespolo Spineli,Paloma de Carvalho Vieira,Claudia Mermelstein,Manoel Luís Costa
摘要
BACKGROUND AND OBJECTIVES: Imaging devices are increasingly present in daily life and are becoming widely used in the record of animal experiments. It is easy to register movement and change in position with video, which is the basis of several methodologies. Yet most of this data is either only qualitatively analysed or their quantitative analysis is based on expensive, proprietary systems, depending on specialized devices and closed software. Here, we present a novel, low-cost system for quantifying swimming performance in both adult and larval zebrafish (Danio rerio), using smartphones for image acquisition and open source softwares for computational analysis. METHODS: We developed and validated an open-source system for automated, accurate, and sensitive quantification of zebrafish exercise performance, enabling robust behavioral analysis. Adult zebrafish were recorded in a standardized, easy to mount, device using a home-built imaging system, while larval specimens were recorded using transillumination through a standard 6-well plate. We used common smartphones or webcams, since they provide sufficient resolution to capture locomotor dynamics. With the Animove plugin we developed for ImageJ, imported video files were preprocessed using FFmpeg to optimize format compatibility and computational efficiency, enabling analysis on low-specification computer hardware. Animove produces video, images and quantitative data directly, and, associated with Trackmate, can produce quantitative kinematic parameters, including total swimming distance, mean velocity, bout frequency, trajectory patterns, and high-resolution positional tracking. Furthermore, Animove produces several graphical outputs of these results. RESULTS: We used ethanol treatment, whose biphasic effects are well described in both adults and larvae, to validate the system. Ethanol exposure produced stimulant effects in larvae at lower doses (0.5-2%) and depressive effects, leading to sedation, at higher doses (>4%), confirming the system's applicability. CONCLUSIONS: By combining consumer-grade, low-cost hardware and open-source software, the Animove plugin provides an accessible, easy-to-use and adaptable tool that can yield accurate quantitative information. This approach has significant potential to facilitate research in exercise physiology, swimming performance, toxicology, and behavioral science.