基于MoSeq的3D行为分析揭示了糖尿病小鼠模型中的神经病变行为变化
Akm Ashiquzzaman1, Eunbin Lee1, Brahnu Fentaw Znaub1,2
1Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea.
Scientific reports
|April 29, 2025
概括
糖尿病神经病变会导致微妙的运动缺陷. 先进的3D行为分析揭示了糖尿病神经病变小鼠的独特运动模式和减少探索,为疼痛和运动控制提供了新的见解.
科学领域:
- 神经科学是一个神经科学.
- 行为科学 行为科学
- 糖尿病学 糖尿病学
背景情况:
- 糖尿病神经病变 (DN) 是一种常见的糖尿病并发症,导致疼痛和运动功能障碍.
- 目前的二维追踪方法无法在DN中捕捉微妙的,基于模式的运动障碍.
- 需要高分辨率的行为分析来理解DN的复杂运动缺陷.
研究的目的:
- 采用基于MoSeq的3D行为分析和机器学习来识别DN小鼠模型中的微妙运动变化.
- 描述与DN的神经病痛相关的行为变化.
- 评估MoSeq作为在DN研究中高分辨率行为量化工具.
主要方法:
- 利用基于MoSeq的3D行为分析和无监督机器学习.
- 在使用尼古丁胺 (NA) 和链毒素 (STZ) 的小鼠中诱导糖尿病神经病变.
- 分析了不同的行为音节,运动组织和时间过渡.
主要成果:
- 确定了22个不同的行为音节;DN小鼠表现出增加的压力行为 (头部编织,跳墙) 和运动能力下降 (行走,养).
- DN小鼠表现出更高的机械灵敏度和更少的探索性,更可预测的行为模式.
- MoSeq揭示了刻板印象的序列和减少的探索性行为,表明行为适应能力和运动规划受损.
结论:
- 基于MoSeq的3D分析有效地捕捉了DN小鼠模型中的微妙运动障碍.
- 与DN相关的疼痛与行为适应能力和运动规划的缺陷有关,而不仅仅是运动减少.
- MoSeq为DN表型和治疗疗效的临床前评估提供了一个有价值的工具.
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