Of the available regenerative treatment options, craniofacial tissue regeneration using mesenchymal stem cells (MSCs) shows promise. The ability of stem cells to produce multiple specialized cell types along with their extensive distribution in many adult tissues have made them an attractive target for applications in tissue engineering. MSCs reside in a wide spectrum of postnatal tissue types and have been successfully isolated from orofacial tissues. These dental-or orofacial-derived MSCs possess self-renewal and multilineage differentiation capacities. The craniofacial system is composed of complex hard and soft tissues derived from sophisticated processes starting with embryonic development. Because of the complexity of the craniofacial tissues, the application of stem cells presents challenges in terms of the size, shape, and form of the engineered structures, the specialized final developed cells, and the modulation of timely blood supply while limiting inflammatory and immunological responses. The cell delivery vehicle has an important role in the in vivo performance of stem cells and could dictate the success of the regenerative therapy. Among the available hydrogel biomaterials for cell encapsulation, alginate-based hydrogels have shown promising results in biomedical applications. Alginate scaffolds encapsulating MSCs can provide a suitable microenvironment for cell viability and differentiation for tissue regeneration applications. This review aims to summarize current applications of dental-derived stem cell therapy and highlight the use of alginate-based hydrogels for applications in craniofacial tissue engineering.

Porous tantalum trabecular metal (PTTM) has long been used in orthopedics to enhance neovascularization, wound healing, and osteogenesis; recently, it has been incorporated into titanium alloy dental implants. However, little is known about the biological responses to PTTM in the human oral cavity. We have hypothesized that, compared with conventional titanium alloy, PTTM has a greater expression of genes specific to neovascularization, wound healing, and osteogenesis during the initial healing period. Twelve subjects requiring at least 4 implants in the mandible were enrolled. Four 3 × 5mm devices, including 2 titanium alloy tapered screws and 2 PTTM cylinders, were placed in the edentulous mandibular areas using a split-mouth design. One device in each group was trephined for analysis at 2 and 4 weeks after placement. RNA microarray analysis and ingenuity pathway analysis were used to analyze osteogenesis gene expression and relevant signaling pathways. Compared to titanium alloy, PTTM samples exhibited significantly higher expressions of genes specific to cell neovascularization, wound healing, and osteogenesis. Several genes—including bone morphogenic proteins, collagens, and growth factors—were upregulated in the PTTM group compared to the titanium alloy control. PTTM materials may enhance the initial healing of dental implants by modifying gene expression profiles.

Objective. The concentrations of endogenous metabolites in saliva can be altered based on the systemic condition of the hosts and may, in theory, serve as a reflection of systemic disease progression. Hemoglobin A1C is used clinically to measure long-term average glycemic control. The aim of the study was to demonstrate if there were differences in the salivary metabolic profiles between well and poorly controlled type 1 and type 2 subjects with diabetes. Subjects and Methods. Subjects with type 1 and type 2 diabetes were enrolled (n = 40). The subjects were assigned to phenotypic groups based on their current level of A1C: <7 = well-controlled and >7 = poorly controlled. Demographic data, age, gender, and ethnicity, were used to match the two phenotypic groups. Whole saliva samples were collected and immediately stored at −80°C. Samples were spiked using an isotopically labeled internal standard and analyzed by UPLC-TOF-MS using a Waters SYNAPT G2-Si mass spectrometer. Results. Unsupervised principal components analysis (PCA) and orthogonal partial least squares regression discrimination analysis (OPLS-DA) were used to define unique metabolomic profiles associated with well and poorly controlled diabetes based on A1C levels. Conclusion. OPLS-DA demonstrates good separation of well and poorly controlled in both type 1 and type 2 diabetes. This provides evidence for developing saliva-based monitoring tools for diabetes.