Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies;and to predict the active ingredients of ...Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies;and to predict the active ingredients of targeted traditional Chinese medicine(TCM)herbs.Methods The Gene Expression Omnibus(GEO)and GeneCards databases were employed to conduct a comprehensive screening of genes and disease-associated loci pertinent to the pathogenesis of OP.The R package was utilized as the analytical tool for the identification of differentially expressed genes.Least absolute shrinkage and selection operator(LASSO)logis-tic regression analysis and support vector machine-recursive feature elimination(SVM-RFE)algorithm were employed in defining the genetic signature specific to OP.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses for the selected pivotal genes were conducted.The cell-type identification by estimating rela-tive subsets of RNA transcripts(CIBERSORT)algorithm was leveraged to examine the infiltra-tion patterns of immune cells;with Spearman’s rank correlation analysis utilized to assess the relationship between the expression levels of the genes and the presence of immune cells.Coremine Medical Database was used to screen out potential TCM herbs for the treatment of OP.Comparative Toxicogenomics Database(CTD)was employed for forecasting the TCM ac-tive ingredients targeting the key genes.AutoDock Vina 1.2.2 and GROMACS 2020 softwares were employed to conclude analysis results;facilitating the exploration of binding affinity and conformational dynamics between the TCM active ingredients and their biological targets.Results Ten genes were identified by intersecting the results from the GEO and GeneCards databases.Through the application of LASSO regression and SVM-RFE algorithm;four piv-otal genes were selected:coat protein(CP);kallikrein 3(KLK3);polymeraseγ(POLG);and transient receptor potential vanilloid 4(TRPV4).GO and KEGG pathway enrichment analy-ses revealed that these trait genes were predominantly engaged in the regulation of defense response activation;maintenance of cellular metal ion balance;and the production of chemokine ligand 5.These genes were notably associated with signaling pathways such as ferroptosis;porphyrin metabolism;and base excision repair.Immune infiltration analysis showed that key genes were highly correlated with immune cells.Macrophage M0;M1;M2;and resting dendritic cell were significantly different between groups;and there were signifi-cant differences between different groups(P<0.05).The interaction counts of resveratrol;curcumin;and quercetin with KLK3 were 7;3;and 2;respectively.It shows that the interac-tions of resveratrol;curcumin;and quercetin with KLK3 were substantial.Molecular docking and molecular dynamics simulations further confirmed the robust binding affinity of these bioactive compounds to the target genes.Conclusion Pivotal genes including CP;KLK3;POLG;and TRPV4;exhibited commendable significant prognostic value;and played a crucial role in the diagnostic assessment of OP.Resveratrol;curcumin;and quercetin;natural compounds found in TCM;showed promise in their potential to effectively modulate the bone-forming gene KLK3.This study provides a sci-entific basis for the interpretation of the pathogenesis of OP and the development of clinical drugs.展开更多
文章研究了在有机溶剂(如乙醇)中,通过溶剂蒸发制备疏水性药物纳米颗粒的方法及制备的纳米材料。以具有生物相容性的支化聚(乙二醇)-b-(N-异丙基丙烯酰胺)聚合物纳米为支架,装载不同疏水药物,经过溶剂蒸发,得到稳定的纳米药物,同时能很...文章研究了在有机溶剂(如乙醇)中,通过溶剂蒸发制备疏水性药物纳米颗粒的方法及制备的纳米材料。以具有生物相容性的支化聚(乙二醇)-b-(N-异丙基丙烯酰胺)聚合物纳米为支架,装载不同疏水药物,经过溶剂蒸发,得到稳定的纳米药物,同时能很方便地溶解在水中得到水性药物纳米颗粒分散体。研究表明:疏水性药物纳米颗粒中,酮洛芬药物纳米颗粒(Dh≈200nm),可以在溶液中稳定保存9个月;当药物与聚合物质量比为0.33∶1时产率可达96%,质量比为1∶1时产率可达到80%。采用透射电子显微镜(transmission electron microscope,TEM)、动态光散射仪(dynamic light scattering,DLS)表征了药物纳米的尺度和结构。展开更多
基金National Natural Science Foundation of China(81960877).
文摘Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies;and to predict the active ingredients of targeted traditional Chinese medicine(TCM)herbs.Methods The Gene Expression Omnibus(GEO)and GeneCards databases were employed to conduct a comprehensive screening of genes and disease-associated loci pertinent to the pathogenesis of OP.The R package was utilized as the analytical tool for the identification of differentially expressed genes.Least absolute shrinkage and selection operator(LASSO)logis-tic regression analysis and support vector machine-recursive feature elimination(SVM-RFE)algorithm were employed in defining the genetic signature specific to OP.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses for the selected pivotal genes were conducted.The cell-type identification by estimating rela-tive subsets of RNA transcripts(CIBERSORT)algorithm was leveraged to examine the infiltra-tion patterns of immune cells;with Spearman’s rank correlation analysis utilized to assess the relationship between the expression levels of the genes and the presence of immune cells.Coremine Medical Database was used to screen out potential TCM herbs for the treatment of OP.Comparative Toxicogenomics Database(CTD)was employed for forecasting the TCM ac-tive ingredients targeting the key genes.AutoDock Vina 1.2.2 and GROMACS 2020 softwares were employed to conclude analysis results;facilitating the exploration of binding affinity and conformational dynamics between the TCM active ingredients and their biological targets.Results Ten genes were identified by intersecting the results from the GEO and GeneCards databases.Through the application of LASSO regression and SVM-RFE algorithm;four piv-otal genes were selected:coat protein(CP);kallikrein 3(KLK3);polymeraseγ(POLG);and transient receptor potential vanilloid 4(TRPV4).GO and KEGG pathway enrichment analy-ses revealed that these trait genes were predominantly engaged in the regulation of defense response activation;maintenance of cellular metal ion balance;and the production of chemokine ligand 5.These genes were notably associated with signaling pathways such as ferroptosis;porphyrin metabolism;and base excision repair.Immune infiltration analysis showed that key genes were highly correlated with immune cells.Macrophage M0;M1;M2;and resting dendritic cell were significantly different between groups;and there were signifi-cant differences between different groups(P<0.05).The interaction counts of resveratrol;curcumin;and quercetin with KLK3 were 7;3;and 2;respectively.It shows that the interac-tions of resveratrol;curcumin;and quercetin with KLK3 were substantial.Molecular docking and molecular dynamics simulations further confirmed the robust binding affinity of these bioactive compounds to the target genes.Conclusion Pivotal genes including CP;KLK3;POLG;and TRPV4;exhibited commendable significant prognostic value;and played a crucial role in the diagnostic assessment of OP.Resveratrol;curcumin;and quercetin;natural compounds found in TCM;showed promise in their potential to effectively modulate the bone-forming gene KLK3.This study provides a sci-entific basis for the interpretation of the pathogenesis of OP and the development of clinical drugs.
文摘文章研究了在有机溶剂(如乙醇)中,通过溶剂蒸发制备疏水性药物纳米颗粒的方法及制备的纳米材料。以具有生物相容性的支化聚(乙二醇)-b-(N-异丙基丙烯酰胺)聚合物纳米为支架,装载不同疏水药物,经过溶剂蒸发,得到稳定的纳米药物,同时能很方便地溶解在水中得到水性药物纳米颗粒分散体。研究表明:疏水性药物纳米颗粒中,酮洛芬药物纳米颗粒(Dh≈200nm),可以在溶液中稳定保存9个月;当药物与聚合物质量比为0.33∶1时产率可达96%,质量比为1∶1时产率可达到80%。采用透射电子显微镜(transmission electron microscope,TEM)、动态光散射仪(dynamic light scattering,DLS)表征了药物纳米的尺度和结构。
