↓ Skip to main content

PLOS

Tissue Engineering Bone Using Autologous Progenitor Cells in the Peritoneum

Overview of attention for article published in PLOS ONE, March 2014
Altmetric Badge

Mentioned by

news
5 news outlets
twitter
1 X user

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
33 Mendeley
Title
Tissue Engineering Bone Using Autologous Progenitor Cells in the Peritoneum
Published in
PLOS ONE, March 2014
DOI 10.1371/journal.pone.0093514
Pubmed ID
Authors

Jinhui Shen, Ashwin Nair, Ramesh Saxena, Cheng Cheng Zhang, Joseph Borrelli, Liping Tang

Abstract

Despite intensive research efforts, there remains a need for novel methods to improve the ossification of scaffolds for bone tissue engineering. Based on a common phenomenon and known pathological conditions of peritoneal membrane ossification following peritoneal dialysis, we have explored the possibility of regenerating ossified tissue in the peritoneum. Interestingly, in addition to inflammatory cells, we discovered a large number of multipotent mesenchymal stem cells (MSCs) in the peritoneal lavage fluid from mice with peritoneal catheter implants. The osteogenic potential of these peritoneal progenitor cells was demonstrated by their ability to easily infiltrate decalcified bone implants, produce osteocalcin and form mineralized bone in 8 weeks. Additionally, when poly(l-lactic acid) scaffolds loaded with bone morphogenetic protein-2 (a known osteogenic differentiation agent) were implanted into the peritoneum, signs of osteogenesis were seen within 8 weeks of implantation. The results of this investigation support the concept that scaffolds containing BMP-2 can stimulate the formation of bone in the peritoneum via directed autologous stem and progenitor cell responses.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 18%
Student > Ph. D. Student 4 12%
Researcher 4 12%
Student > Master 4 12%
Student > Doctoral Student 3 9%
Other 7 21%
Unknown 5 15%
Readers by discipline Count As %
Engineering 12 36%
Agricultural and Biological Sciences 4 12%
Biochemistry, Genetics and Molecular Biology 3 9%
Medicine and Dentistry 3 9%
Nursing and Health Professions 2 6%
Other 3 9%
Unknown 6 18%