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Generation of Induced Pluripotent Stem Cells from Human Nasal Epithelial Cells Using a Sendai Virus Vector

Overview of attention for article published in PLOS ONE, August 2012
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Title
Generation of Induced Pluripotent Stem Cells from Human Nasal Epithelial Cells Using a Sendai Virus Vector
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0042855
Pubmed ID
Authors

Mizuho Ono, Yuko Hamada, Yasue Horiuchi, Mami Matsuo-Takasaki, Yoshimasa Imoto, Kaishi Satomi, Tadao Arinami, Mamoru Hasegawa, Tsuyoshi Fujioka, Yukio Nakamura, Emiko Noguchi

Abstract

The generation of induced pluripotent stem cells (iPSCs) by introducing reprogramming factors into somatic cells is a promising method for stem cell therapy in regenerative medicine. Therefore, it is desirable to develop a minimally invasive simple method to create iPSCs. In this study, we generated human nasal epithelial cells (HNECs)-derived iPSCs by gene transduction with Sendai virus (SeV) vectors. HNECs can be obtained from subjects in a noninvasive manner, without anesthesia or biopsy. In addition, SeV carries no risk of altering the host genome, which provides an additional level of safety during generation of human iPSCs. The multiplicity of SeV infection ranged from 3 to 4, and the reprogramming efficiency of HNECs was 0.08-0.10%. iPSCs derived from HNECs had global gene expression profiles and epigenetic states consistent with those of human embryonic stem cells. The ease with which HNECs can be obtained, together with their robust reprogramming characteristics, will provide opportunities to investigate disease pathogenesis and molecular mechanisms in vitro, using cells with particular genotypes.

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The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 3%
Japan 1 1%
Germany 1 1%
South Africa 1 1%
Unknown 67 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 19%
Student > Master 13 18%
Student > Ph. D. Student 12 17%
Student > Doctoral Student 7 10%
Student > Bachelor 6 8%
Other 11 15%
Unknown 9 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 39%
Biochemistry, Genetics and Molecular Biology 18 25%
Medicine and Dentistry 10 14%
Neuroscience 5 7%
Nursing and Health Professions 1 1%
Other 1 1%
Unknown 9 13%