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解析帕金森病的复杂性:发病机制与精准干预的新视角。

Unraveling the Complexity of Parkinson's Disease: Insights into Pathogenesis and Precision Interventions.

机构信息

Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, 325001, P. R. China.

Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo, Ontario, N2J 2Y5, Canada.

出版信息

Adv Sci (Weinh). 2024 Nov;11(42):e2405309. doi: 10.1002/advs.202405309. Epub 2024 Sep 20.

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss, leading to motor and non-motor symptoms. Early detection before symptom onset is crucial but challenging. This study presents a framework integrating circuit modeling, non-equilibrium dynamics, and optimization to understand PD pathogenesis and enable precision interventions. Neuronal firing patterns, particularly oscillatory activity, play a critical role in PD pathology. The basal ganglia network, specifically the subthalamic nucleus-external globus pallidus (STN-GPe) circuitry, exhibits abnormal activity associated with motor dysfunction. The framework leverages the non-equilibrium landscape and flux theory to identify key connections generating pathological activity, providing insights into disease progression and potential intervention points. The intricate STN-GPe interplay is highlighted, shedding light on compensatory mechanisms within this circuitry may initially counteract changes but later contribute to pathological alterations as disease progresses. The framework addresses the need for comprehensive evaluation methods to assess intervention outcomes. Cross-correlations between state variables provide superior early warning signals compared to traditional indicators relying on critical slowing down. By elucidating compensatory mechanisms and circuit dynamics, the framework contributes to improved management, early detection, risk assessment, and potential prevention/delay of PD development. This pioneering research paves the way for precision medicine in neurodegenerative disorders.

摘要

帕金森病(PD)是一种神经退行性疾病,其特征是多巴胺能神经元丧失,导致运动和非运动症状。在症状出现前进行早期检测至关重要,但具有挑战性。本研究提出了一个整合电路建模、非平衡动力学和优化的框架,以了解 PD 的发病机制并实现精准干预。神经元的发放模式,特别是振荡活动,在 PD 病理学中起着关键作用。基底神经节网络,特别是丘脑底核-苍白球外(STN-GPe)回路,表现出与运动功能障碍相关的异常活动。该框架利用非平衡景观和通量理论来识别产生病理性活动的关键连接,深入了解疾病进展和潜在的干预点。强调了错综复杂的 STN-GPe 相互作用,阐明了该回路中代偿机制可能最初抵消变化,但随着疾病的进展,最终会导致病理性改变。该框架解决了对综合评估方法的需求,以评估干预结果。状态变量之间的互相关提供了比传统的基于关键减速的指标更优越的早期预警信号。通过阐明代偿机制和电路动力学,该框架有助于改善管理、早期检测、风险评估以及潜在的 PD 发展的预防/延迟。这项开创性的研究为神经退行性疾病的精准医学铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6758/11558075/d6905665c609/ADVS-11-2405309-g003.jpg

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