Background:Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength.However,current anti-resorptive drugs carry a risk of various complications.The deep learning-based efficacy pre...Background:Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength.However,current anti-resorptive drugs carry a risk of various complications.The deep learning-based efficacy prediction system(DLEPS)is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes.This study aimed to explore the protective effect and potential mechanisms of cinobufotalin(CB),a traditional Chinese medicine(TCM),on bone loss.Methods:DLEPS was employed for screening anti-osteoporotic agents according to gene profile changes in primary osteoporosis.Micro-CT,histological and morphological analysis were applied for the bone protective detection of CB,and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells(hBMMSCs)were also investigated.The underlying mechanism was verified using qRT-PCR,Western blot(WB),immunofluorescence(IF),etc.Results:A safe concentration(0.25mg/kg in vivo,0.05μM in vitro)of CB could effectively preserve bone mass in estrogen deficiency-induced bone loss and promote osteogenic differentiation/function of hBMMSCs.Both BMPs/SMAD and Wnt/β-catenin signaling pathways participated in CB-induced osteogenic differentiation,further regulating the expression of osteogenesis-associated factors,and ultimately promoting osteogenesis.Conclusion:Our study demonstrated that CB could significantly reverse estrogen deficiency-induced bone loss,further promoting osteogenic differentiation/function of hBMMSCs,with BMPs/SMAD and Wnt/β-catenin signaling pathways involved.展开更多
基金Beijing Natural Science Foundation,Grant/Award Number:L222145 and L222030Emerging Engineering Interdisciplinary Project and the Fundamental Research Funds for the Central Universities,Grant/Award Number:PKU2022XGK008Peking University Medicine Fund of Fostering Young Scholars’Scientific&Technological Innovation,Grant/Award Number:BMU2022PY010。
文摘Background:Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength.However,current anti-resorptive drugs carry a risk of various complications.The deep learning-based efficacy prediction system(DLEPS)is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes.This study aimed to explore the protective effect and potential mechanisms of cinobufotalin(CB),a traditional Chinese medicine(TCM),on bone loss.Methods:DLEPS was employed for screening anti-osteoporotic agents according to gene profile changes in primary osteoporosis.Micro-CT,histological and morphological analysis were applied for the bone protective detection of CB,and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells(hBMMSCs)were also investigated.The underlying mechanism was verified using qRT-PCR,Western blot(WB),immunofluorescence(IF),etc.Results:A safe concentration(0.25mg/kg in vivo,0.05μM in vitro)of CB could effectively preserve bone mass in estrogen deficiency-induced bone loss and promote osteogenic differentiation/function of hBMMSCs.Both BMPs/SMAD and Wnt/β-catenin signaling pathways participated in CB-induced osteogenic differentiation,further regulating the expression of osteogenesis-associated factors,and ultimately promoting osteogenesis.Conclusion:Our study demonstrated that CB could significantly reverse estrogen deficiency-induced bone loss,further promoting osteogenic differentiation/function of hBMMSCs,with BMPs/SMAD and Wnt/β-catenin signaling pathways involved.
