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Odontoblastic inductive potential of epithelial cells derived from human deciduous dental pulp

Overview of attention for article published in Journal of Molecular Histology, April 2016
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Title
Odontoblastic inductive potential of epithelial cells derived from human deciduous dental pulp
Published in
Journal of Molecular Histology, April 2016
DOI 10.1007/s10735-016-9676-1
Pubmed ID
Authors

Hye-Kyung Lee, Ji-Won Park, You-Mi Seo, Ha Hoon Kim, Gene Lee, Hyun-Sook Bae, Joo-Cheol Park

Abstract

For the dentin regeneration, dental epithelial cells are indispensible and must possess odontoblastic induction capability. Epithelial cell-like stem cells were recently identified in human deciduous dental pulp (DPESCs). However, their cellular characteristics remain poorly defined. The purpose of this study was to characterize DPESCs compared to HAT-7 ameloblastic cells. Expression levels of ameloblast-specific markers [odontogenic ameloblast-associated protein (Odam), matrix metalloproteinase (Mmp)-20, amelogenin, and ameloblastin] were detected in DPESCs. Co-culturing odontoblastic MDPC-23 cells with DPESCs increased expression of odontoblast differentiation markers (Dmp1 and Dspp) from days 4 to 10, while the expression of bone sialoprotein rapidly decreased. MDPC-23 cells cultured in DPESC-conditioned medium (CM) showed increased Dspp promoter activity compared with control MDPC-23 cultures. Mineralization was first observed in the CM groups from day 4 and proceeded rapidly until day 14, whereas mineralized nodules were found from day 7 in control media-cultured cells. In conclusion, DPESCs in human deciduous pulp possess ameloblast-like characteristics and differentiation properties, and substances derived from DPESCs promote odontoblastic differentiation. Thus, our results indicate that DPESCs can be a realistic epithelial source for use in odontoblastic induction and dentin formation of dental mesenchymal cells.

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Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 16%
Student > Bachelor 4 13%
Student > Doctoral Student 4 13%
Student > Postgraduate 3 9%
Student > Ph. D. Student 3 9%
Other 5 16%
Unknown 8 25%
Readers by discipline Count As %
Medicine and Dentistry 14 44%
Agricultural and Biological Sciences 2 6%
Engineering 2 6%
Psychology 1 3%
Chemical Engineering 1 3%
Other 2 6%
Unknown 10 31%