Department of Haematology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, School of Medicine of University of Electronic Science and Technology of China, No. 32, West Section 2, First Ring Road, Qingyang District, Chengdu, 610000, China.
Institute of Communications Engineering & Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 30013, Taiwan.
Adv Sci (Weinh). 2024 Jun;11(23):e2307819. doi: 10.1002/advs.202307819. Epub 2024 Apr 3.
The gut-brain axis has recently emerged as a crucial link in the development and progression of Parkinson's disease (PD). Dysregulation of the gut microbiota has been implicated in the pathogenesis of this disease, sparking growing interest in the quest for non-invasive biomarkers derived from the gut for early PD diagnosis. Herein, an artificial intelligence-guided gut-microenvironment-triggered imaging sensor (Eu-MOF@Au-Aptmer) to achieve non-invasive, accurate screening for various stages of PD is presented. The sensor works by analyzing α-Syn in the gut using deep learning algorithms. By monitoring changes in α-Syn, the sensor can predict the onset of PD with high accuracy. This work has the potential to revolutionize the diagnosis and treatment of PD by allowing for early intervention and personalized treatment plans. Moreover, it exemplifies the promising prospects of integrating artificial intelligence (AI) and advanced sensors in the monitoring and prediction of a broad spectrum of diseases and health conditions.
肠脑轴最近成为帕金森病 (PD) 发展和进展的关键环节。肠道微生物组的失调与这种疾病的发病机制有关,这引发了人们对探索源自肠道的非侵入性生物标志物以用于早期 PD 诊断的浓厚兴趣。在此,提出了一种人工智能引导的肠道微环境触发成像传感器 (Eu-MOF@Au-Aptmer),以实现对 PD 各个阶段的非侵入性、准确筛查。该传感器通过使用深度学习算法分析肠道中的 α-突触核蛋白 (α-Syn) 来工作。通过监测 α-Syn 的变化,该传感器可以高精度预测 PD 的发作。这项工作有可能通过允许早期干预和个性化治疗计划来彻底改变 PD 的诊断和治疗。此外,它例证了在广泛的疾病和健康状况的监测和预测中集成人工智能 (AI) 和先进传感器的有前途的前景。