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Collagen-derived dipeptide prolyl-hydroxyproline promotes osteogenic differentiation through Foxg1

Overview of attention for article published in Cellular & Molecular Biology Letters, December 2017
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Title
Collagen-derived dipeptide prolyl-hydroxyproline promotes osteogenic differentiation through Foxg1
Published in
Cellular & Molecular Biology Letters, December 2017
DOI 10.1186/s11658-017-0060-2
Pubmed ID
Authors

Yoshifumi Kimira, Haruka Odaira, Kaho Nomura, Yuri Taniuchi, Naoki Inoue, Sachie Nakatani, Jun Shimizu, Masahiro Wada, Hiroshi Mano

Abstract

Prolyl-hydroxyproline (Pro-Hyp) is one of the major constituents of collagen-derived dipeptides. We previously reported that Pro-Hyp promotes the differentiation of osteoblasts by increasing Runx2, osterix and Col1α1 mRNA expression levels. Here, to elucidate the mechanism of Pro-Hyp promotion of osteoblast differentiation, we focus on the involvement of Foxo1 in osteoblast differentiation via Runx2 regulation and the role of Foxg1 in Foxo1 regulation. The addition of Pro-Hyp had no effect on MC3T3-E1 cell proliferation in Foxo1- or Foxg1-knockdown cells. In Foxo1-knockdown cells, the addition of Pro-Hyp increased ALP activity, but in Foxg1-knockdown cells, it had no effect on ALP activity. An enhancing effect of Pro-Hyp on the Runx2 and osterix expression levels was observed in Foxo1-knockdown cells. However, no enhancing effect of Pro-Hyp on osteoblastic gene expression was observed when Foxg1 was knocked down. These results demonstrate that Pro-Hyp promotes osteoblastic MC3T3-E1 cell differentiation and upregulation of osteogenic genes via Foxg1 expression.

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Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 18%
Professor 2 12%
Student > Ph. D. Student 2 12%
Student > Bachelor 1 6%
Student > Master 1 6%
Other 1 6%
Unknown 7 41%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 12%
Engineering 2 12%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Computer Science 1 6%
Agricultural and Biological Sciences 1 6%
Other 2 12%
Unknown 8 47%