Evidence map›Paper›PMID 42844331›Full record

ArticleNature biomedical engineering2026

A soft bioelectronic system with a responsive hydrogel neural interface for direct force quantification and real-time intraoperative craniocerebral injury monitoring.

Bo Pang, Ganguang Yang, Qihong Cheng, Sen Zhou, Zhixin Wang, Wang Xuan, Yuqi Qiu, Hangyu Gong, Tianzhao Bu, Bin Xie and 6 more

Abstract read
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In one paragraph

Article in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Bo Pang *Flexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Ganguang Yang *Flexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Qihong ChengDepartment of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Sen ZhouFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Zhixin WangFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Wang XuanDepartment of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID http://orcid.org/0000-0003-2906-8394
Yuqi QiuFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Hangyu GongFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Tianzhao BuFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Bin XieFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Peng FuDepartment of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhouping YinFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.ORCID http://orcid.org/0000-0001-5766-2337
Chwee Teck LimInstitute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-4019-9782
Changsheng WuInstitute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore. cwu@nus.edu.sg.ORCID http://orcid.org/0000-0002-0921-6356
Xiaobing JiangDepartment of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2004xh0835@hust.edu.cn.
Hao WuFlexible Electronics Research Center, State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China. hwu16@hust.edu.cn.ORCID http://orcid.org/0000-0003-1494-0848

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52188102National Natural Science Foundation of China (National Science Foundation of China) 52550004
6 · The paper itself

Abstract

In craniotomies, the surgical manipulation of instruments inherently involves applying mechanical forces to brain tissues, potentially causing brain damage. Currently, there is no direct method to quantitatively monitor craniocerebral injuries. Here we report a soft neural interface bioelectronic system (SNIBS) for real-time monitoring of craniocerebral injury throughout neurosurgery. On the basis of the thermally triggered swelling/deswelling of hydrogel microspheres, the hydrogel interface achieves seamless integration with the brain cortex for recording high-fidelity signals during surgery while ensuring benign detachment to prevent brain damage after surgery. The SNIBS enables the monitoring of contact pressure, somatosensory evoked potentials, electrocorticography and temperature, providing a direct method of assessing neural status. The correlation between somatosensory evoked potential and cortical neural pathway damage caused by pressure is revealed by SNIBS. Evans blue staining and magnetic resonance imaging confirm that contact pressure higher than 80 kPa causes irreversible craniocerebral injury. Validated in rabbit brain tumour excision models, the SNIBS enables surgeons to quantify forces to avoid craniocerebral injury. The presented technology holds strong potential for establishing safety evaluation standards for neurosurgery.

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.