Evidence map›Paper›PMID 32717878›Full record

ReviewPolymers2020

3D Printing and Bioprinting Nerve Conduits for Neural Tissue Engineering.

Xiaoling Yu, Tian Zhang, Yuan Li

Open access · goldAbstract readReview
In one paragraph

Review in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 pooled it
5.6field-weighted citation impact, top 3% of its field
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

48 citing papers in PubMed, 2 syntheses or guidelines pooled it, 124 citations in OpenAlex.

  1. Pooled it
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  6. The interaction between oxidative stress and Schwann cells.Experimental biology and medicine (Maywood, N.J.) · 2026
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  15. Personalized Stem Cell-Based Regeneration in Spinal Cord Injury Care.International journal of molecular sciences · 2025
    Review
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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

3 authors at 1 institution in 1 country.

Xiaoling YuSchool of Chemistry, Chemical Engineering and Life Science, Wuhan University of Technology, Wuhan 430070, China.
Tian ZhangSchool of Chemistry, Chemical Engineering and Life Science, Wuhan University of Technology, Wuhan 430070, China.ORCID 0000-0003-3840-4839
Yuan LiSchool of Chemistry, Chemical Engineering and Life Science, Wuhan University of Technology, Wuhan 430070, China.
Wuhan University of Technology · CN

Funding

Fundamental Research Funds for the Central Universities WUT:2016IVA084Hubei Provincial Natural Science Foundation of China 2016CFB338the Chinese Thousand Talents Plan Program NAWuhan University of technology WUT:163120001
6 · The paper itself

Abstract

Fabrication of nerve conduits for perfectly repairing or replacing damaged peripheral nerve is an urgent demand worldwide, but it is also a formidable clinical challenge. In the last decade, with the rapid development of manufacture technologies, 3D printing and bioprinting have been becoming remarkable stars in the field of neural engineering. In this review, we explore that the biomaterial inks (hydrogels, thermoplastic, and thermoset polyesters and composite) and bioinks have been selected for 3D printing and bioprinting of peripheral nerve conduits. This review covers 3D manufacturing technologies, including extrusion printing, inkjet printing, stereolithography, and bioprinting with inclusion of cells, bioactive molecules, and drugs. Finally, an outlook on the future directions of 3D printing and 4D printing in customizable nerve therapies is presented.

Indexed as

3D printingbioprintinghydrogelperipheral nerve regenerationpolyester

Identifiers

PMID32717878
PMCPMC7465920
OpenAlexW3044930082

What OpenQuestion 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 OpenQuestion graph.