A biodegradable and restorative peripheral neural interface for the interrogation of neuropathic injuries

Liu Wang, Tieyuan Zhang, Jiaxin Lei, Shirong Wang, Yanjun Guan, Kuntao Chen, Chaochao Li, Yahao Song, Weining Li, Shimeng Wang, Zhibo Jia, Shengfeng Chen, Jun Bai, Bingbing Yu, Can Yang, Pengcheng Sun, Qingyun Wang, Xing Sheng, Jiang Peng, Yubo Fan (), Lizhen Wang (), Milin Zhang (), Yu Wang () and Lan Yin ()
Additional contact information
Liu Wang: Beihang University
Tieyuan Zhang: Chinese PLA General Hospital
Jiaxin Lei: Tsinghua University
Shirong Wang: MegaRobo Technologies Co. ltd
Yanjun Guan: Chinese PLA General Hospital
Kuntao Chen: Tsinghua University
Chaochao Li: Chinese PLA General Hospital
Yahao Song: Tsinghua University
Weining Li: Tsinghua University
Shimeng Wang: Tsinghua University
Zhibo Jia: Chinese PLA General Hospital
Shengfeng Chen: Chinese PLA General Hospital
Jun Bai: Chinese PLA General Hospital
Bingbing Yu: Tsinghua University
Can Yang: Tsinghua University
Pengcheng Sun: Tsinghua University
Qingyun Wang: Beihang University
Xing Sheng: Tsinghua University
Jiang Peng: Chinese PLA General Hospital
Yubo Fan: Beihang University
Lizhen Wang: Beihang University
Milin Zhang: Tsinghua University
Yu Wang: Chinese PLA General Hospital
Lan Yin: Tsinghua University

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract 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.

Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-56089-1 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56089-1

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-56089-1

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().