Cellular transcriptional response to zirconia-based implant materials

运行x2 生物材料 骨整合 材料科学 生物医学工程 骨形态发生蛋白2 立方氧化锆 植入 骨愈合 细胞生物学 基因表达 纳米技术 基因 生物 医学 陶瓷 生物化学 解剖 外科 复合材料 体外
作者
Brigitte Altmann,Kerstin Rabel,Ralf‐Joachim Kohal,Susanne Proksch,Pascal Tomakidi,Erik Adolfsson,Falk Bernsmann,Paola Palmero,Tobias Fürderer,Thorsten Steinberg
出处
期刊:Dental Materials [Elsevier]
卷期号:33 (2): 241-255 被引量:21
标识
DOI:10.1016/j.dental.2016.12.005
摘要

To adequately address clinically important issues such as osseointegration and soft tissue integration, we screened for the direct biological cell response by culturing human osteoblasts and gingival fibroblasts on novel zirconia-based dental implant biomaterials and subjecting them to transcriptional analysis.Biomaterials used for osteoblasts involved micro-roughened surfaces made of a new type of ceria-stabilized zirconia composite with two different topographies, zirconium dioxide, and yttria-stabilized zirconia (control). For fibroblasts smooth ceria- and yttria-stabilized zirconia surface were used. The expression of 90 issue-relevant genes was determined on mRNA transcription level by real-time PCR Array technology after growth periods of 1 and 7 days.Generally, modulation of gene transcription exhibited a dual dependence, first by time and second by the biomaterial, whereas biomaterial-triggered changes were predominantly caused by the biomaterials' chemistry rather than surface topography. Per se, modulated genes assigned to regenerative tissue processes such as fracture healing and wound healing and in detail included colony stimulating factors (CSF2 and CSF3), growth factors, which regulate bone matrix properties (e.g. BMP3 and TGFB1), osteogenic BMPs (BMP2/4/6/7) and transcription factors (RUNX2 and SP7), matrix collagens and osteocalcin, laminins as well as integrin ß1 and MMP-2.With respect to the biomaterials under study, the screening showed that a new zirconia-based composite stabilized with ceria may be promising to provide clinically desired periodontal tissue integration. Moreover, by detecting biomarkers modulated in a time- and/or biomaterial-dependent manner, we identified candidate genes for the targeted analysis of cell-implant bioresponse during biomaterial research and development.
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