Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1589117 | Micron | 2013 | 9 Pages |
The aim of this work was the comparison of the behavior of committed (human osteoblast cells – hOB – from bone biopsies) versus multipotent (human dental pulp stem cells – hDPSC – from extracted teeth) cells, cultured on shot-peened titanium surfaces, since the kind of cell model considered has been shown to be relevant in techniques widely used in studies on composition/morphology of biomaterial surfaces. The titanium surface morphology, with different roughness, and the behavior of cells were analyzed by confocal microscope (CM), scanning electron microscope (SEM) and X-ray microanalysis. The best results, in terms of hOB adhesion/distribution, were highlighted by both CM and SEM in cultured plates having 20-μm-depth cavities. On the contrary, CM and SEM results highlighted the hDPSC growth regardless the different surface morphology, arranged in overlapped layers due to their high proliferation rate, showing their unfitness in biomaterial surface test. Nevertheless, hDPSC cultured inside 3D-matrices reproduced an osteocyte-like three-dimensional network, potentially useful in the repair of critical size bone defects. The behavior of the two cell models suggests a different use in biomaterial cell cultures: committed osteoblast cells could be appropriate in selecting the best surfaces to improve osseointegration, while multipotent cells could be suitable to obtain in vitro osteocyte-like network for regenerative medicine. The originality of the present work consists in studying for the first time two different cell models (committed versus multipotent) compared in parallel different biomaterial cultures, thus suggesting distinct targets for each cellular model.
► To compare the behavior of committed versus multipotent stem cells, 2D and 3D cultured. ► To define the best cell model in the analysis of differently shaped materials. ► To analyse the best surface morphology in inducing cellular interfaces. ► To identify the best target for different cell models.