开发PainFace软件,以简化,标准化和扩展小鼠笑分析
Eric S McCoy1,2, Sang Kyoon Park3, Rahul P Patel1
1UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Pain
|July 18, 2024
概括
一个新的AI工具,PainFace,准确地测量小鼠的面部笑容,以评估疼痛. 这项技术标准化了研究中的疼痛量化,提高了实验室的可靠性.
科学领域:
- 动物行为 动物行为
- 计算生物学是一种计算生物学.
- 疼痛研究 疼痛研究
背景情况:
- 面部微笑是哺乳动物疼痛的可靠指标.
- 目前用于评分小鼠的面部微笑的方法依赖于主观的人类解释,导致变化.
- 需要客观和自动化的方法来在临床前研究中标准化疼痛评估.
研究的目的:
- 开发和验证一个基于机器学习的自动化软件平台PainFace,用于量化小鼠面部笑容.
- 评估PainFace在不同实验室和引起疼痛的条件中的准确性和可重复性.
- 为了实现高通量和客观测量小鼠自发疼痛.
主要方法:
- 开发一个基于云的软件平台 (PainFace),利用机器学习算法.
- 检测四个关键的面部动作单元 (轨道,鼻子,耳朵,胡须) 与老鼠笑容尺度相关.
- 在两个独立实验室中,使用视频记录从小鼠进行腹腔切除术,卡拉注射和甲注射的视频记录来验证PainFace的准确性.
主要成果:
- 疼痛脸精确地在0-8级别上对黑色涂层的C57BL/6小鼠的面部微笑进行了评分.
- 该平台可以从标准视频中以每秒高达1的速度生成笑容得分.
- 经过腹腔切除手术的小鼠在高的状态中花费的时间比假控件增加了7倍.
结论:
- PainFace提供了一种可复制和可扩展的方法,用于量化面部微笑,表明小鼠的自发疼痛.
- 自动化平台增强了客观性,并减少了疼痛评估中观察者之间的变化.
- 在临床前疼痛研究中,PainFace促进了面部微笑的标准化和高通量分析.
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