Abstract

Tissue engineering is a relatively recent research area aimed at developing artificial tissues that can restore, maintain, or even improve the anatomical and/or functional integrity of injured tissues. Otolaryngology, as a leading surgical specialty in head and neck surgery, is a candidate for the use of these advanced therapies and medicinal products developed. Nevertheless, a knowledge-based analysis of both areas together is still needed. The dataset was retrieved from the Web of Science database from 1900 to 2020. SciMAT software was used to perform the science mapping analysis and the data for the biomedical translation identification was obtained from the iCite platform. Regarding the analysis of the cognitive structure, we find consolidated research lines, such as the generation of cartilage for use as a graft in reconstructive surgery, reconstruction of microtia, or the closure of perforations of the tympanic membrane. This last research area occupies the most relevant clinical translation with the rest of the areas presenting a lower translational level. In conclusion, Tissue engineering is still in an early translational stage in otolaryngology, otology being the field where most advances have been achieved. Therefore, although otolaryngologists should play an active role in translational research in tissue engineering, greater multidisciplinary efforts are required to promote and encourage the translation of potential clinical applications of tissue engineering for routine clinical use.

Details

Title
Analysis of cognitive framework and biomedical translation of tissue engineering in otolaryngology
Author
Padilla-Cabello, Javier 1 ; Moral-Munoz, Jose A. 2 ; Santisteban-Espejo, Antonio 3 ; Velez-Estevez, Antonio 4 ; Cobo, Manuel J. 5 ; Martin-Piedra, Miguel A. 6 

 University of Granada, Program of Biomedicine, Granada, Spain (GRID:grid.4489.1) (ISNI:0000000121678994); Hospital Universitario Torrecardenas, Department of Otorhinolaryngology, Almeria, Spain (GRID:grid.4489.1) 
 University of Cadiz, Department of Nursing and Physiotherapy, Cadiz, Spain (GRID:grid.7759.c) (ISNI:0000000103580096); Biomedical Research and Innovation Institute of Cadiz (INiBICA), Cádiz, Spain (GRID:grid.512013.4) 
 Biomedical Research and Innovation Institute of Cadiz (INiBICA), Cádiz, Spain (GRID:grid.512013.4); Puerta del Mar University Hospital, Department of Pathology, Cádiz, Spain (GRID:grid.411342.1) (ISNI:0000 0004 1771 1175); University of Cadiz, Department of Medicine, Cadiz, Spain (GRID:grid.7759.c) (ISNI:0000000103580096) 
 University of Cadiz, Department of Computer Science and Engineering, Cádiz, Spain (GRID:grid.7759.c) (ISNI:0000000103580096) 
 University of Granada, Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), Granada, Spain (GRID:grid.4489.1) (ISNI:0000000121678994) 
 University of Granada, Tissue Engineering Group, Department of Histology, Granada, Spain (GRID:grid.4489.1) (ISNI:0000000121678994) 
Pages
13492
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2852877836
Copyright
© Springer Nature Limited 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.