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Frontiers in behavioral neuroscience · 2026

Lévy statistics define anxiety and depression in mice subjected to chronic stress.

СтатьяНазвание и аннотация: Перевод в очереди
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Li Qinxi, Li Xiaojie, Zhong Qixing, Nie Yuru, Luo Yiping, Zhao Bangcheng, Zhang Ni, Kuang Weihong, Tian Chao, Chen Daojun, Zhang Yingqian, Wu Zhe, Zhong Zhihui

Аннотация

INTRODUCTION: Current rodent models for anxiety and depression assessment face methodological challenges compromising both scientific rigor and animal welfare.

METHODS: This study introduced a novel approach using the Lévy flight (LF) statistical method to analyze spontaneous movement in open spaces. We employed three models: Chronic unpredictable mild stress (CUMS), Electric shock stress (ES), and Chronic Restraint Stress (CRS)-utilizing a total of 540 mice for LF fitting. A support vector machine algorithm was applied to distinguish each model group based on the two-dimensional distribution of the variables γ and μ in the LF. Statistical analysis was performed using a two-dimensional Kolmogorov-Smirnov test before and after drug administration.

RESULTS: We found that the ES model primarily exhibited anxiety-like behaviors, the CRS model predominantly exhibited depression-like behaviors, and the CUMS model displayed both depression-like and anxiety-like behaviors. All three stress models were suitable for LF fitting, with the distribution of CUMS in the γ-μ plane lying between the ES and CRS groups. To assess the therapeutic effect of fluoxetine (FXT) on CUMS, we excluded the CUMS-resistant mice and performed LF analysis. Following FXT treatment, the mice gradually shifted toward the normal area in the γ-μ plane, with a more pronounced shift toward the depression area observed as the modeling time increased.

DISCUSSION: This study identifies a previously unrecognized statistical locomotor pattern in mice with anxiety and depression. By integrating scientific rigor with ethical considerations, this approach also presents a humane paradigm shift in preclinical assessment, accelerating translational breakthroughs in neuroscience research.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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