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休息状态大脑网络的分离和整合在纵向长期COVID队列中

Yuchen Zhang¹, Gengchen Ye², Wentao Zeng²

¹Department of Nuclear Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Shaanxi Province, Xi'an, China.

|April 15, 2025

概括

长期COVID疲劳与大脑网络功能的改变有关,显示感染后隔离减少. 大脑网络的变化可能会跟踪长期COVID患者的神经认知恢复.

科学领域:

神经科学是一个神经科学.
医学研究医学研究
计算生物学计算生物学

背景情况:

长期的COVID呈现出持续的,使人衰弱的疲劳,影响生活质量.
导致后病毒性疲劳的潜在神经机制在很大程度上是未知的.
了解大脑网络动态对于诊断和治疗长期的COVID连续症至关重要.

研究的目的:

为了研究长期COVID中疲劳的神经机制.
在康复期间分析大脑功能网络分离和整合.
确定潜在的生物标志物来追踪长期COVID中的神经认知缺陷.

主要方法:

使用嵌套光谱分区 (NSP) 方法.
在34名长期COVID患者中分析了休息状态的大脑功能网络.
感染后1个月和3个月的大脑网络特性与健康对照进行了比较.

主要成果:

长期COVID患者表现出更高的疲劳得分和较少分离的大脑网络.
网络集成与疲劳在1个月后呈正相关,然后在3个月后呈负相关.
基因 Ontology 分析将疲劳与异常的社会行为联系起来.

结论:

大脑网络重构轨迹的特征是病毒后疲劳的进展.
改变的大脑网络分离和整合是长期COVID的关键特征.
这些网络动态可以作为神经认知序列的功能生物标志物.

关键词:

卫生科学卫生科学免疫学免疫学免疫学内部医学内部医学医学专业医学专业医学医学医学医学医学神经学神经学病毒学病毒学

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