Fibrin Glue Implants Seeded with Dental Pulp and Periodontal Ligament Stem Cells for the Repair of Periodontal Bone Defects: A Preclinical Study.
Natella I EnukashvilyJulia A DombrovskayaAnastasia V KotovaNatalia Yuryevna SemenovaIrina KarabakRoman E BanashkovDmitry BaramTatiana PaderinaStanislav S BilykWolf-Dieter GrimmAnton N KovalenkoDmitry IvolginEgor M PrikhodkoAlexey V SilinPublished in: Bioengineering (Basel, Switzerland) (2021)
A technology to create a cell-seeded fibrin-based implant matching the size and shape of bone defect is required to create an anatomical implant. The aim of the study was to develop a technology of cell-seeded fibrin gel implant creation that has the same shape and size as the bone defect at the site of implantation. Using computed tomography (CT) images, molds representing bone defects were created by 3D printing. The form was filled with fibrin glue and human dental pulp stem cells (DPSC). The viability, set of surface markers and osteogenic differentiation of DPSC grown in fibrin gel along with the clot retraction time were evaluated. In mice, an alveolar bone defect was created. The defect was filled with fibrin gel seeded with mouse DPSC. After 28 days, the bone repair was analyzed with cone beam CT and by histological examination. The proliferation rate, set of surface antigens and osteogenic potential of cells grown inside the scaffold and in 2D conditions did not differ. In mice, both cell-free and mouse DPSC-seeded implants increased the bone tissue volume and vascularization. In mice with cell-seeded gel implants, the bone remodeling process was more prominent than in animals with a cell-free implant. The technology of 3D-printed forms for molding implants can be used to prepare implants using components that are not suitable for 3D printing.
Keyphrases
- soft tissue
- bone mineral density
- stem cells
- cell free
- computed tomography
- bone loss
- postmenopausal women
- bone regeneration
- single cell
- positron emission tomography
- magnetic resonance imaging
- platelet rich plasma
- contrast enhanced
- machine learning
- adipose tissue
- metabolic syndrome
- body composition
- deep learning
- risk assessment
- induced apoptosis
- insulin resistance
- cell proliferation
- dual energy
- oxidative stress
- tissue engineering
- skeletal muscle
- cone beam