Evidence map›Paper›PMID 39741227›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

A Smart Semi-Implantable Device Integrating Microchannel-Enhanced Sampling and Multiplex Biochemical Testing for Deep Wound Monitoring and Pathogen Identification.

Qilin Li, Chunyu Wei, Luming Xu, Jiao Zhang, Yuyu Li, Xiaohuan Lu, Rengui Xu, Honglian Guo, Peng Cao, Chenke Ouyang and 4 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

14 authors.

Qilin LiDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Chunyu WeiDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Luming XuDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Jiao ZhangDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Yuyu LiDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Xiaohuan LuHubei Key Laboratory of Regenerative Medicine and Multi-disciplinary Translational Research, Hubei Provincial Engineering Research Center of Clinical Laboratory and Active Health Smart Equipment, Research Center for Tissue Engineering and Regenerative Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Rengui XuDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Honglian GuoDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Peng CaoDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Chenke OuyangDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Jiarong XuDepartment of Pharmacology, School of Basic Medicine, State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Tongji-Rongcheng Center for Biomedicine, Tongji Medical College, Huazhong University of Science and Technology, Hubei Key Laboratory for Drug Target Research and Pharmacodynamic Evaluation, Huazhong University of Science and Technology, Wuhan, 430030, China.
Wei ChenDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Zheng WangHubei Key Laboratory of Regenerative Medicine and Multi-disciplinary Translational Research, Hubei Provincial Engineering Research Center of Clinical Laboratory and Active Health Smart Equipment, Research Center for Tissue Engineering and Regenerative Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.ORCID https://orcid.org/0000-0002-9330-0728
Lin WangDepartment of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.

Funding

Hubei Province Science and Technology Innovation Team Project [2022]No.11Major Scientific and Technological Innovation Projects of Hubei Province 2022BCA013National Key Research and Development Program of China 2022YFC2408100National Natural Science Foundation of China 81974382National Natural Science Foundation of China 82072167National Natural Science Foundation of China 82173315National Natural Science Foundation of China 82202617National Natural Science Foundation of China 82272277National Natural Science Foundation of China 82302585National Natural Science Fund for Excellent Young Scientists Fund Program (Overseas)Natural Science Foundation of Hubei Province 2022CFA063Natural Science Foundation of Hubei Province 2022CFB736Wuhan Natural Science Foundation Exploration Program ChenguangProgram2024040801020348
6 · The paper itself

Abstract

Monitoring deep wounds is challenging but necessary for high-quality medical treatment. Current methodologies for deep wound monitoring are typically limited to indirect clinical symptoms or costly non-real-time imaging diagnosis. Herein, a smart system is proposed that enables in situ monitoring of deep wounds' status through a semi-implantable device composed of 2 seamlessly connected functional components: 1) the well-designed, microchannel-structured sampling needles that efficiently and conveniently collect samples from deep wound anatomical locations, and 2) the multiplex biochemical testing compartment that facilitates the immediate and persistent detection of multiple biochemical indicators based on a color image processing software accessible to a conventional smartphone. With the 3 representative preclinical deep wound models, the study demonstrates the device's potential to monitor wound infection, inflammation, healing progress, and reduce inflammation when applied to deep skin injury, surgical implantation, and postoperative intestinal leakage. The device's capability to rapidly and accurately identify pathogenic bacteria is also demonstrated both in vitro and in vivo, potentially facilitating precise intervention in infected wounds. Coupled with the device's favorable biocompatibility and cost-effectiveness, this intelligent system emerges as a promising tool for safe and effective management of complicated deep wounds.

Indexed as

Wound HealingWound InfectionAnimalsHumansMiceMonitoring, Physiologicdeep samplingdeep wound monitoringmultiplex biochemical testingpathogen identificationsmart semi‐implantable device

Identifiers

PMID39741227
PMCPMC11848630

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.