ReviewJournal of clinical medicine2020
Tissue Engineering and Three-Dimensional Printing in Periodontal Regeneration: A Literature Review.
Review in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- Scaffold-Based Biomaterials for Periodontal Regeneration in Periodontitis: A Systematic Review and Meta-Analysis.Journal of functional biomaterials · 2026Review
- Smart injectable hydrogels for periodontal regeneration: Recent advancements in biomaterials and biofabrication strategies.Materials today. Bio · 2025Review
- Effect of overexpression ofExperimental and therapeutic medicine · 2025Article
- Biomaterial Scaffolds for Periodontal Tissue Engineering.Journal of functional biomaterials · 2024Review
- Multidimensional 3D-Printed Scaffolds and Regeneration of Intrabony Periodontal Defects: A Systematic Review.Journal of functional biomaterials · 2024Review
- The 3-dimensional printing for dental tissue regeneration: the state of the art and future challenges.Frontiers in bioengineering and biotechnology · 2024Review
- Biomimetic scaffold and 3D bioprinting in dental application: A review.Bioinformation · 2024Review
- Advancing Dentistry through Bioprinting: Personalization of Oral Tissues.Journal of functional biomaterials · 2023Review
- Review
- 3D Printed and Bioprinted Membranes and Scaffolds for the Periodontal Tissue Regeneration: A Narrative Review.Membranes · 2022Review
- Chitosan-Based Scaffold for Mineralized Tissues Regeneration.Marine drugs · 2021Review
- Influence of Materials Properties on Bio-Physical Features and Effectiveness of 3D-Scaffolds for Periodontal Regeneration.Molecules (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The three-dimensional printing of scaffolds is an interesting alternative to the traditional techniques of periodontal regeneration. This technique uses computer assisted design and manufacturing after CT scan. After 3D modelling, individualized scaffolds are printed by extrusion, selective laser sintering, stereolithography, or powder bed inkjet printing. These scaffolds can be made of one or several materials such as natural polymers, synthetic polymers, or bioceramics. They can be monophasic or multiphasic and tend to recreate the architectural structure of the periodontal tissue. In order to enhance the bioactivity and have a higher regeneration, the scaffolds can be embedded with stem cells and/or growth factors. This new technique could enhance a complete periodontal regeneration. This review summarizes the application of 3D printed scaffolds in periodontal regeneration. The process, the materials and designs, the key advantages and prospects of 3D bioprinting are highlighted, providing new ideas for tissue regeneration.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.