Center for Bioelectronic Medicine, The Feinstein Institute for Medical Research, Donald & Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York 11030.
Cold Spring Harb Perspect Med. 2019 Dec 2;9(12):a034157. doi: 10.1101/cshperspect.a034157.
Our bodies have built-in neural reflexes that continuously monitor organ function and maintain physiological homeostasis. Whereas the field of bioelectronic medicine has mainly focused on the stimulation of neural circuits to treat various conditions, recent studies have started to investigate the possibility of leveraging the sensory arm of these reflexes to diagnose disease states. To accomplish this, neural signals emanating from the body's built-in biosensors and propagating through peripheral nerves must be recorded and decoded to identify the presence or levels of relevant biomarkers of disease. The process of acquiring these signals poses several technical challenges related to the neural interfaces, surgical techniques, and data-processing framework needed to record and analyze them. However, these challenges can be addressed with a rigorous experimental approach and new advances in implantable electrodes, signal processing, and machine learning methods. Outlined in this review are studies decoding vagus nerve activity as it related to inflammatory, metabolic, and cardiopulmonary biomarkers. Successfully decoding peripheral nerve activity related to disease states will not only enable the development of real-time diagnostic devices, but also help advancing truly closed-loop neuromodulation technologies.
我们的身体内置有神经反射，它们持续监测器官功能并维持生理内稳态。虽然生物电子医学领域主要侧重于刺激神经回路以治疗各种病症，但最近的研究已经开始探索利用这些反射的感觉臂来诊断疾病状态的可能性。为此，必须记录和解码从身体内置生物传感器发出并通过周围神经传播的神经信号，以识别疾病相关生物标志物的存在或水平。获取这些信号的过程涉及到与神经接口、手术技术和数据处理框架相关的若干技术挑战，这些技术挑战可以通过严格的实验方法以及可植入电极、信号处理和机器学习方法方面的新进展来解决。本综述概述了对迷走神经活动与炎症、代谢和心肺生物标志物相关关系的解码研究。成功解码与疾病状态相关的周围神经活动不仅将能够开发实时诊断设备，还有助于推进真正的闭环神经调节技术。
