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Uncovering 3D bioprinting research trends: A keyword network mapping analysis
A scientometric analysis as part of a Competitive Technology Intelligence methodology was used to determine the main research efforts in 3D bioprinting. Papers from Scopus and Web of Science (WoS) published between 2000 and 2017 were analysed. A network map of the most frequently occurring keywords...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Whioce Publishing Pte. Ltd.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582012/ https://www.ncbi.nlm.nih.gov/pubmed/33102921 http://dx.doi.org/10.18063/IJB.v4i2.147 |
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author | Garcia-Garcia, Leonardo Azael Rodriguez-Salvador, Marisela |
author_facet | Garcia-Garcia, Leonardo Azael Rodriguez-Salvador, Marisela |
author_sort | Garcia-Garcia, Leonardo Azael |
collection | PubMed |
description | A scientometric analysis as part of a Competitive Technology Intelligence methodology was used to determine the main research efforts in 3D bioprinting. Papers from Scopus and Web of Science (WoS) published between 2000 and 2017 were analysed. A network map of the most frequently occurring keywords in these articles was created, and their average publication year (APY) was determined. The analysis focused on the most relevant keywords that occurred at least five times. A total of 1,759 keywords were obtained, and a co-occurrence analysis was developed for APYs with more keywords: 2011–2016. The results indicated that Polylactic Acid (PLA) is the material used most often. Applications mainly focused on bone tissue engineering and regeneration. The most frequently used technique was inkjet printing, and the main cell sources were Mesenchymal Stem Cells (MSC). From a general perspective, ‘Treatment’ and ‘Bioink’ were the most frequent keywords. The former was mainly related to cancer, regenerative medicine, and MSC and the latter, to multicellular spheroid deposition and the use of hydrogels like GelMA (gelatin methacryloyl). This analysis provides insights to stakeholders involved in 3D bioprinting research and development who need to keep abreast of scientific progress in the field. |
format | Online Article Text |
id | pubmed-7582012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Whioce Publishing Pte. Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75820122020-10-23 Uncovering 3D bioprinting research trends: A keyword network mapping analysis Garcia-Garcia, Leonardo Azael Rodriguez-Salvador, Marisela Int J Bioprint Research Article A scientometric analysis as part of a Competitive Technology Intelligence methodology was used to determine the main research efforts in 3D bioprinting. Papers from Scopus and Web of Science (WoS) published between 2000 and 2017 were analysed. A network map of the most frequently occurring keywords in these articles was created, and their average publication year (APY) was determined. The analysis focused on the most relevant keywords that occurred at least five times. A total of 1,759 keywords were obtained, and a co-occurrence analysis was developed for APYs with more keywords: 2011–2016. The results indicated that Polylactic Acid (PLA) is the material used most often. Applications mainly focused on bone tissue engineering and regeneration. The most frequently used technique was inkjet printing, and the main cell sources were Mesenchymal Stem Cells (MSC). From a general perspective, ‘Treatment’ and ‘Bioink’ were the most frequent keywords. The former was mainly related to cancer, regenerative medicine, and MSC and the latter, to multicellular spheroid deposition and the use of hydrogels like GelMA (gelatin methacryloyl). This analysis provides insights to stakeholders involved in 3D bioprinting research and development who need to keep abreast of scientific progress in the field. Whioce Publishing Pte. Ltd. 2018-07-09 /pmc/articles/PMC7582012/ /pubmed/33102921 http://dx.doi.org/10.18063/IJB.v4i2.147 Text en Copyright: © 2018 Garcia-Garcia L A and Rodriguez-Salvador M. http://creativecommons.org/licenses/cc-by-nc/4.0/ This is an open-access article distributed under the terms of the Attribution-NonCommercial 4.0 International 4.0 (CC BY-NC 4.0), which permits all non-commercial use, distribution, and reproduction in any medium provided the original work is properly cited. |
spellingShingle | Research Article Garcia-Garcia, Leonardo Azael Rodriguez-Salvador, Marisela Uncovering 3D bioprinting research trends: A keyword network mapping analysis |
title | Uncovering 3D bioprinting research trends: A keyword network mapping analysis |
title_full | Uncovering 3D bioprinting research trends: A keyword network mapping analysis |
title_fullStr | Uncovering 3D bioprinting research trends: A keyword network mapping analysis |
title_full_unstemmed | Uncovering 3D bioprinting research trends: A keyword network mapping analysis |
title_short | Uncovering 3D bioprinting research trends: A keyword network mapping analysis |
title_sort | uncovering 3d bioprinting research trends: a keyword network mapping analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582012/ https://www.ncbi.nlm.nih.gov/pubmed/33102921 http://dx.doi.org/10.18063/IJB.v4i2.147 |
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