Wang Liu, Zhang Tieyuan, Lei Jiaxin, Wang Shirong, Guan Yanjun, Chen Kuntao, Li Chaochao, Song Yahao, Li Weining, Wang Shimeng, Jia Zhibo, Chen Shengfeng, Bai Jun, Yu Bingbing, Yang Can, Sun Pengcheng, Wang Qingyun, Sheng Xing, Peng Jiang, Fan Yubo, Wang Lizhen, Zhang Milin, Wang Yu, Yin Lan
Medical Engineering & Engineering Medicine Innovation Center of Hangzhou International Innovation Institute, Beihang University, Hangzhou, China.
School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
Nat Commun. 2025 Feb 17;16(1):1716. doi: 10.1038/s41467-025-56089-1.
Monitoring the early-stage healing of severe traumatic nerve injuries is essential to gather physiological and pathological information for timely interventions and optimal clinical outcomes. Traditional diagnostic methods relying on physical examinations, imaging tools, and intraoperative electrophysiological testing present great challenges in continuous and remote monitoring. While implantable peripheral nerve interfaces provide direct access to nerve fibers for precise interrogation and modulation, conventional non-degradable designs pose limited utilization in nerve injury rehabilitation. Here, we introduce a biodegradable and restorative neural interface for wireless real-time tracking and recovery of long-gap nerve injuries. Leveraging machine learning techniques, this electronic platform deciphers nerve recovery status and identifies traumatic neuroma formation at the early phase, enabling timely intervention and significantly improved therapeutic outcomes. The biodegradable nature of the device eliminates the need for retrieval procedures, reducing infection risks and secondary tissue damage. This research sheds light on bioresorbable multifunctional peripheral nerve interfaces for probing neuropathic injuries, offering vital information for early diagnosis and therapeutic intervention.
监测严重创伤性神经损伤的早期愈合对于收集生理和病理信息以进行及时干预并实现最佳临床结果至关重要。传统的诊断方法依赖体格检查、成像工具和术中电生理测试，在连续和远程监测方面面临巨大挑战。虽然可植入外周神经接口可直接接入神经纤维以进行精确询问和调节，但传统的不可降解设计在神经损伤康复中的应用有限。在此，我们推出了一种用于无线实时跟踪和恢复长间隙神经损伤的可生物降解且具有恢复功能的神经接口。该电子平台利用机器学习技术解读神经恢复状态，并在早期识别创伤性神经瘤的形成，从而实现及时干预并显著改善治疗效果。该装置的可生物降解特性消除了取出手术的必要性，降低了感染风险和二次组织损伤。这项研究为用于探测神经性损伤的可生物吸收多功能外周神经接口提供了启示，为早期诊断和治疗干预提供了重要信息。
