Vertebral Bone Marrow-Derived Mesenchymal Stromal Cells from Osteoporotic and Healthy Patients Possess Similar Differentiation Properties In Vitro
Osteoporosis is a disease characterized by low bone mass and an increased risk of fractures. Although several cellular players leading to osteoporosis have been identified, the role of mesenchymal stromal cells (MSC) is still not fully elaborated. The aim of this study was, therefore, to isolate and characterize MSCs from vertebral body of healthy non-osteoporotic and osteoporotic patients, with a particular focus on their osteogenic differentiation potential. Isolated MSCs were characterized by their osteogenic, adipogenic, and chondrogenic differentiation, as well as surface marker expression, proliferation behavior, and immunomodulatory capacity. The mineralization process was confirmed using Alizarin Red S and alkaline phosphatase (ALP) stains and further evaluated by determining ALP activity, mineral deposition, and free phosphate ion release. MSCs from both healthy and osteoporotic patients showed common fibroblast-like morphology and similar proliferation behavior. They expressed the typical MSC surface markers and possessed immunomodulatory capacity. Both groups demonstrated solid trilineage differentiation potential; osteogenic differentiation was further confirmed by increased ALP activity, deposition of inorganic crystals, phosphate ion release, and expression of osteoblast marker genes. Overall, MSCs from osteoporotic and non-osteoporotic patients showed neither a difference in general MSC features nor in the detailed analysis regarding osteogenic differentiation. These data suggest that vertebral body MSCs from osteoporotic patients were not impaired; rather, they possessed full osteogenic potential compared to MSCs from non-osteoporotic patients.Keywords: differentiation; immunomodulation; mesenchymal stromal cells; osteoporosis; proliferation rate; surface markers.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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