Screening of hydrogel-based scaffolds for dental pulp regeneration—A systematic review

脚手架 牙髓干细胞 干细胞 牙髓(牙) 牙科 间充质干细胞 自愈水凝胶 组织工程 生物医学工程 再生(生物学) 材料科学 医学 生物 病理 细胞生物学 高分子化学
作者
Kunio Fukushima,Márcia Martins Marques,Tamara Kerber Tedesco,Giovanna Lopes Carvalho,Flávia Gonçalves,Hector Caballero‐Flores,Susana Morimoto,Maria Stella Moreira
出处
期刊:Archives of Oral Biology [Elsevier BV]
卷期号:98: 182-194 被引量:41
标识
DOI:10.1016/j.archoralbio.2018.11.023
摘要

The aim of this systematic review was to evaluate the most appropriate hydrogel scaffold type (natural, synthetic or hybrid) to be applied with stem cells for dental pulp regeneration. The findings should help clinicians make an informed choice about the appropriate scaffold to be applied for this approach. Three electronic databases were searched (Medline, Web of Science and Scopus). The review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). From 4990 potentially relevant studies initially identified, 18 papers fulfilled the eligibility criteria and were considered for this review. Natural scaffolds were applied in most studies. Collagen was the most studied scaffold. In 5 of 10 studies, only growth factors were added to the constructs. Even without growth factors, these scaffolds containing stem cells were able to support the formation of dentin. The synthetic scaffolds were the least studied. Only 4 studies were selected, and in 3 of them, the same scaffold (Puramatrix) was evaluated. Puramatrix by itself was unable to form dental pulp when dental pulp stem cells were not present. Synthetic and hybrid hydrogels were unable to attract stem cells from the host. The presence of growth factors in these constructs seems to be of relevance since dental pulp tissue formation was achieved only when the hybrid scaffold was applied with growth factors. All types of hydrogel-based scaffolds, when containing mesenchymal stem cells, are able to form connective tissue with different degrees of similarity to dental pulp. However, current data is too heterogeneous to compare and identify the advantages of any specific scaffold.
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