ReviewCureus2025
3D Bioprinting: Shaping the Future of Periodontal Tissue Regeneration and Disease Management.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- 3D-Bioprinted Multifunctional Nanocomposite Scaffolds for Alveolar Bone-Periodontal Ligament-Root Cementum Regeneration: A Narrative Review.Biomimetics (Basel, Switzerland) · 2026Review
- Three-Dimensional Printing in Dentistry: Evolution, Technologies, and Clinical Application.Polymers · 2026Review
- Review
- Bioengineering of Periodontal Tissues: Cell Therapy and Biomaterials Application.Bioengineering (Basel, Switzerland) · 2025Review
- Polymeric 3D-Printed Microneedle Arrays for Non-Transdermal Drug Delivery and Diagnostics.Polymers · 2025Review
- The tooth transformer® revolution: autologous dentin biomaterials and platelet concentrates in oral regeneration. A parallel narrative systematic review.Frontiers in dental medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The periodontium is one of the most complex tissues in the body, consisting of a hierarchical blend of soft and hard tissues. Its complex architecture makes treating and regenerating disease-damaged periodontal tissues a persistent challenge in biomedicine. Three-dimensional (3D) bioprinting represents a transformative approach to tissue engineering, offering promising advancements in treating and regenerating periodontal disease. This innovative technology enables the precise fabrication of complex, patient-specific tissue structures, facilitating the repair and restoration of damaged periodontal tissues, including the gingiva, bone, and periodontal ligament (PDL). By utilizing biocompatible materials such as living cells, hydrogels, and growth factors, 3D bioprinting has the potential to create functional, biologically integrated constructs that can mimic the natural architecture of periodontal tissues. However, translating these advancements into clinical applications remains a challenge. Emerging technologies like bioprinting have been developed to address some limitations of traditional tissue engineering methods. This review explores the current state of 3D bioprinting technology, its application in periodontal disease treatment, and the challenges associated with scaling up this technology for clinical use. Additionally, it discusses the future implications of bioprinting for personalized medicine, offering a new frontier for regenerating periodontal tissues and improving patient outcomes in oral health. Integrating 3D bioprinting into periodontal regenerative therapies could revolutionize clinical practices, offering more effective, tailored, and sustainable solutions to address the challenges of periodontal disease.
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.