Dynamic expression of SMAD3 is critical in osteoblast differentiation of PDMCs
Abstract
Human pluripotent stem cells have the potential assist in the identification of genes involved in mammalian development. The human placenta is considered a repository of stem cells, termed placenta‑derived multipotent cells (PDMCs), which are able to differentiate into cells with an osteoblastic phenotype. This plasticity of PDMCs maybe applied clinically to the understanding of osteogenesis and osteoporosis. In the presentstudy, osteoblasts were generated by culturing PDMCs in osteogenic medium. Reverse transcription quantitative polymerase chain reactionand the degree of osteoblast calcification were used to evaluate the efficacy of osteogenesis. The results suggestedthat the expression of mothers against decapentaplegic homolog 3 (SMAD3) increased in the initial stages of osteogenic differentiation but decreased in the later stages. However, osteogenesis was inhibitedwhen the PDMCs overexpressed SMAD3 throughout the differentiation period. In addition, the rate of osteogenic differentiation was decreased when SMAD3 signaling was impaired. In conclusion, SMAD3 serves an important role in osteoblast differentiation and bone formation in a time‑dependent manner. The data from the present study indicate that arapid increase in SMAD3 expression is crucial for osteogenesis and suggest a role for PDMCs in the treatment of patients with osteoporosis.
Read the paper
Related studies
- Irisin Enhances Osteoblast DifferentiationIn Vitro
- Glucocorticoids suppress Wnt16 expression in osteoblasts in vitro and in vivo
- Interaction between Schwann Cells and Osteoblasts In Vitro
- Administration of cinnamaldehyde promotes osteogenesis in ovariectomized rats and differentiation of osteoblast in vitro
- The Effect of the Major Components of Fructus Cnidii on Osteoblasts In Vitro
- Estrogen depletion alters osteogenic differentiation and matrix production by osteoblasts in vitro
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.