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Journal of Materials Science: Materials in Medicine

, Volume 17, Issue 9, pp 815–823 | Cite as

Characterization and osteoblast-like cell compatibility of porous scaffolds: bovine hydroxyapatite and novel hydroxyapatite artificial bone

  • Yuan Gao
  • Wen-Ling Cao
  • Xiao-Yan Wang
  • Yan-Dao Gong
  • Jie-Mo Tian
  • Nan-Ming Zhao
  • Xiu-Fang Zhang
Article

Abstract

Three different porous scaffolds were tested. The first two were prepared by sintering bovine bone. The third scaffold was prepared using three-dimensional gel-lamination, a new rapid prototyping method, and was named as hydroxyapatite artificial bone.

X-ray diffraction and Fourier transform infrared spectroscopy analysis confirmed that the samples were mainly highly crystalline hydroxyapatite ceramics. Scanning electron microscopy and mercury intrusion porosimetry measurement showed that the pores were interconnected and pore sizes ranged from several microns to hundreds of microns.

Mouse osteoblast-like cells grown on the three scaffolds retained their characteristic morphology. Cell proliferation and differentiation, analyzed by methylthiazol tetrazolium (MTT) and alkaline phosphatase activity assays, were significantly higher on the hydroxyapatite artificial bone than on the other two scaffolds tested. All the scaffolds provided good attachment, proliferation and differentiation of bone cells.

These results indicate that the scaffolds have a favorable interaction with cells, they support cell growth and functions, and therefore these scaffolds may have great potential as bone substitutes. The three-dimensional gel-lamination method is proven to be an attractive process to design and fabricate bone scaffolds with favorable properties, and therefore, has promising potential for bone repair applications.

Keywords

Porous Scaffold Mercury Intrusion Porosimetry Bovine Bone Bone Scaffold Calcium Nitrate Tetrahydrate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Yuan Gao
    • 1
  • Wen-Ling Cao
    • 1
  • Xiao-Yan Wang
    • 2
  • Yan-Dao Gong
    • 1
  • Jie-Mo Tian
    • 2
  • Nan-Ming Zhao
    • 1
  • Xiu-Fang Zhang
    • 1
  1. 1.Department of Biological Sciences and Biotechnology, State Key Laboratory of Biomembrane and Membrane BiotechnologyTsinghua UniversityBeijingChina
  2. 2.Institute of Nuclear Energy TechnologyTsinghua UniversityBeijingChina

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