Evidence map›Paper›PMID 36636138›Full record

ReviewInternational journal of bioprinting2023

Hybrid biomanufacturing systems applied in tissue regeneration.

Fengyuan Liu, Rixiang Quan, Cian Vyas, Enes Aslan

Open access · diamondAbstract readReview
In one paragraph

Review in International journal of bioprinting, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 28% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Fengyuan LiuDepartment of Mechanical Engineering, University of Bristol, Bristol, BS8 1TR, UK.
Rixiang QuanDepartment of Mechanical Engineering, University of Bristol, Bristol, BS8 1TR, UK.
Cian VyasDepartment of Mechanical, Aerospace and Civil Engineering, School of Engineering, Faculty of Science and Engineering, The University of Manchester, Manchester, M13 9PL, UK.
Enes AslanDepartment of Machine and Metal Technologies, Gumusova Vocational School, Duzce University, Duzce, 81850, Turkey.
University of Bristol · GBUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scaffold-based approach is a developed strategy in biomanufacturing, which is based on the use of temporary scaffold that performs as a house of implanted cells for their attachment, proliferation, and differentiation. This strategy strongly depends on both materials and manufacturing processes. However, it is very difficult to meet all the requirements, such as biocompatibility, biodegradability, mechanical strength, and promotion of cell-adhesion, using only single material. At present, no single bioprinting technique can meet the requirements for tissue regeneration of all scales. Thus, multi-material and mixing-material scaffolds have been widely investigated. Challenges in terms of resolution, uniform cell distribution, and tissue formation are still the obstacles in the development of bioprinting technique. Hybrid bioprinting techniques have been developed to print scaffolds with improved properties in both mechanical and biological aspects for broad biomedical engineering applications. In this review, we introduce the basic multi-head bioprinters, semi-hybrid and fully-hybrid biomanufacturing systems, highlighting the modifications, the improved properties and the effect on the complex tissue regeneration applications.

Indexed as

Additive biomanufacturingHybrid bioprinterScaffoldsTissue regeneration

Identifiers

PMID36636138
PMCPMC9831066
OpenAlexW3124031114

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.