Chapter title |
Intravital Imaging to Understand Spatiotemporal Regulation of Osteogenesis and Angiogenesis in Cranial Defect Repair and Regeneration
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Chapter number | 17 |
Book title |
Somatic Stem Cells
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Published in |
Methods in molecular biology, September 2018
|
DOI | 10.1007/978-1-4939-8697-2_17 |
Pubmed ID | |
Book ISBNs |
978-1-4939-8696-5, 978-1-4939-8697-2
|
Authors |
Xinping Zhang, Zhang, Xinping |
Abstract |
Angiogenesis plays a critical role in skeletal repair and regeneration. Our understanding of the intricate relationship between osteogenesis and angiogenesis at a repair site has been hindered by the lack of an effective approach that allows tracking of bone healing and neovascularization simultaneously at a high spatiotemporal resolution in living animals. To overcome this barrier, we have recently established a cranial bone defect window chamber model in mice that enables high-resolution, four-dimensional imaging analyses of bone defect healing using multiphoton laser scanning microscopy (MPLSM). The windowed defect model confers imaging of the defect through both micro computed tomography (microCT) and MPLSM in vivo, facilitating lineage tracing and longitudinal analyses of osteogenesis and angiogenesis in repair. The windowed chamber model further permits insertion of cellular implants or bone graft materials, aiding in spatiotemporal analyses of the interactions between biomaterials and vascular microenvironment in living animals. In this chapter, we describe the improved technique for establishing the chronic cranial defect window chamber model for long-term imaging as well as the imaging analysis protocols for quantitative analyses of osteogenesis and angiogenesis at the site of bone defect repair. |
Mendeley readers
Geographical breakdown
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Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 2 | 15% |
Other | 2 | 15% |
Student > Ph. D. Student | 2 | 15% |
Student > Doctoral Student | 1 | 8% |
Student > Bachelor | 1 | 8% |
Other | 1 | 8% |
Unknown | 4 | 31% |
Readers by discipline | Count | As % |
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Neuroscience | 2 | 15% |
Computer Science | 1 | 8% |
Unknown | 5 | 38% |