Evidence map›Paper›PMID 40868377›Full record

ReviewBioengineering (Basel, Switzerland)2025

Peripheral Nerve Regeneration Reimagined: Cutting-Edge Biomaterials and Biotechnological Innovations.

Ting Chak Lam, Zhenzhen Wu, Sang Jin Lee, Yiu Yan Leung

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
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

4 authors.

Ting Chak LamDepartment of Oral and Maxillofacial Surgery, Faculty of Dentistry, University of Hong Kong, Hong Kong.
Zhenzhen WuDepartment of Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, University of Hong Kong, Hong Kong.
Sang Jin LeeDepartment of Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, University of Hong Kong, Hong Kong.
Yiu Yan LeungDepartment of Oral and Maxillofacial Surgery, Faculty of Dentistry, University of Hong Kong, Hong Kong.ORCID 0000-0002-6670-6570

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral nerve injuries are frequent clinical issues that can lead to significant functional impairments, greatly impacting patients' quality of life. Developing effective nerve regeneration methods is crucial for restoring function and ensuring the best possible outcomes. This review explores recent advances in nerve regeneration, including nerve guidance conduits (NGCs), which are vital in bridging nerve gaps caused by injury and supporting repair. The field has seen significant progress in biomaterials and biotech, with biodegradable options like collagen and chitosan as well as non-biodegradable materials such as nylon. Innovations like 3D printing have allowed for more intricate conduit designs that more closely mimic natural nerves. Despite these progressions, research continues to focus on improving NGCs-often by adding cells or bioactive substances-to boost nerve regeneration and functional recovery. By analyzing current trends, this review aims to motivate clinicians and researchers to develop more comprehensive nerve repair strategies. It emphasizes approaches that combine scientific innovation with clinical practicality, fostering a more holistic and realistic outlook on enhancing patient outcomes in peripheral nerve regeneration.

Indexed as

nerve guidance conduitsnerve regenerationperipheral nerve injury

Identifiers

PMID40868377
PMCPMC12383415

What Socratic holds

Textmetadata
LicenceCC BY
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.