Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quan...Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.展开更多
Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization(MR) analysis.Methods Bidirectional MR was used to analyze pooled data from different genome-wid...Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization(MR) analysis.Methods Bidirectional MR was used to analyze pooled data from different genome-wide association studies(GWAS). The causal effect of plasma metabolites on osteoporosis was estimated using the inverse variance weighted method, intersections of statistically significant metabolites obtained from different sources of osteoporosis-related GWAS aggregated data was determined, and then sensitivity analysis was performed on these metabolites. Heterogeneity between single nucleotide polymorphisms was evaluated by Cochran's Q test. Horizontal pleiotropy was assessed through the application of the MR-Egger intercept method and the MRPRESSO method. The causal effect of osteoporosis on plasma metabolites was also evaluated using the inverse variance weighted method. Additionally, pathway analysis was conducted to identify potential metabolic pathways involved in the regulation of osteoporosis.Results Primary analysis and sensitivity analysis showed that 77 and 61 plasma metabolites had a causal relationship with osteoporosis from the GWAS data in the GCST90038656 and GCST90044600 datasets, respectively. Five common metabolites were identified via intersection. X-13684 levels and the glucose-to-maltose ratio were negatively associated with osteoporosis, whereas glycoursodeoxycholate levels and arachidoylcarnitine(C20) levels were positively associated with osteoporosis(all P < 0.05). The relationship between X-11299 levels and osteoporosis showed contradictory results(all P < 0.05). Pathway analysis indicated that glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, galactose metabolism, arginine biosynthesis, and starch and sucrose metabolism pathways were participated in the development of osteoporosis.Conclusion We found a causal relationship between plasma metabolites and osteoporosis. These results offer novel perspectives with important implications for targeted metabolite-focused interventions in the management of osteoporosis.展开更多
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
In recent years,growth hormone and insulin-like growth factors have become key regulators of bone metabolism and remodeling,crucial for maintaining healthy bone mass throughout life.Studies have shown that adult growt...In recent years,growth hormone and insulin-like growth factors have become key regulators of bone metabolism and remodeling,crucial for maintaining healthy bone mass throughout life.Studies have shown that adult growth hormone deficiency leads to alterations in bone remodeling,significantly affecting bone microarchitecture and increasing fracture risk.Although recombinant human growth hormone replacement therapy can mitigate these adverse effects,improving bone density,and reduce fracture risk,its effectiveness in treating osteoporosis,especially in adults with established growth hormone deficiency,seems limited.Bisphosphonates inhibit bone resorption by targeting farnesyl pyrophosphate synthase in osteoclasts,and clinical trials have confirmed their efficacy in improving osteoporosis.Therefore,for adult growth hormone deficiency patients with osteoporosis,the use of bisphosphonates alongside growth hormone replacement therapy is recommended.展开更多
Objective To investigate the protective effects of naringenin(NRG)against dexamethasone(DEX)-induced osteoporosis(OP)in rats.Methods Molecular docking of NRG was done with AutoDock Vina 1.2.0 software.Forty-eight fema...Objective To investigate the protective effects of naringenin(NRG)against dexamethasone(DEX)-induced osteoporosis(OP)in rats.Methods Molecular docking of NRG was done with AutoDock Vina 1.2.0 software.Forty-eight female Wistar rats were randomly divided into six groups(n=8 each):normal control(NC),DEX(7 mg/kg,i.m.),NRG-low(NRG-L;25 mg/kg,i.g.),NRG-medium(NRG-M;50 mg/kg,i.g.),NRG-high(NRG-H;100 mg/kg,i.g.),and alendronate(ALN;0.25 mg/d,i.g.)groups.OP was induced by administering DEX once a week for five weeks in all groups except NC group.Begining in the third week after the initial DEX administration,the rats in NRG-L,NRG-M,NRG-H,and ALN groups received the corresponding treatments daily for three weeks,while NC and DEX groups received no additional treatment.Serum samples were collected at the end of the experiment for biochemical,bone turnover,antioxidant,lipid profile,and inflammatory cytokine analyses.Femur bones underwent physical parameter testing and histopathological examination.Results The molecular docking results illustrated that NRG docked with calcitonin(CT),lowdensity lipoprotein(LDL),bone morphogenetic protein(BMP),vascular endothelial growth factor(VEGF)receptor,forkhead transcription factors,and osteoprogenitor cells showed good binding energy.In rats administered with 25,50,and 100 mg/kg NRG,there was a significant enhancement in serum biochemical indices,characterized by a reduction in tartrate-resistant acid phosphatase(TRAP),parathyroid hormone(PTH),and an elevation in osteocalcin(OC)and CT levels(P<0.05,P<0.01,and P<0.001,respectively).Despite no significant changes in thickness,weight,and length(P>0.05),there was a marked increase in bone mineral density(BMD)(P<0.01,P<0.001,and P<0.001,respectively).Antioxidant enzyme markers showed significant upregulation,with higher glutathione,superoxide dismutase,and catalase,and a concurrent decrease in malondialdehyde(MDA)(P<0.05,P<0.01,and P<0.001,respectively).The lipid profile also improved significantly,with lower cholesterol(CH),triglycerides(TG),and low-density lipoprotein(LDL)levels,and an increase in high-density lipoprotein(HDL)level(P<0.05,P<0.01,and P<0.001,respectively).Inflammatory cytokine levels were reduced,as evidenced by decreases in tumor necrosis factor(TNF),interleukin(IL)-6,and IL-1β(P<0.05,P<0.01,and P<0.001,respectively).Furthermore,histological alterations revealed obvious improvements,and the body weight of rats treated with NRG showed an increase compared with DEX group.Conclusion These findings imply that NRG exhibited a protective effect against DEX-induced OP in rats as it promotes the bone formation process by increasing the number of bone turnover markers including OC and CT,and restoring of antioxidant status,lipid metabolism,and inflammatory markers.展开更多
文摘Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.
文摘Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization(MR) analysis.Methods Bidirectional MR was used to analyze pooled data from different genome-wide association studies(GWAS). The causal effect of plasma metabolites on osteoporosis was estimated using the inverse variance weighted method, intersections of statistically significant metabolites obtained from different sources of osteoporosis-related GWAS aggregated data was determined, and then sensitivity analysis was performed on these metabolites. Heterogeneity between single nucleotide polymorphisms was evaluated by Cochran's Q test. Horizontal pleiotropy was assessed through the application of the MR-Egger intercept method and the MRPRESSO method. The causal effect of osteoporosis on plasma metabolites was also evaluated using the inverse variance weighted method. Additionally, pathway analysis was conducted to identify potential metabolic pathways involved in the regulation of osteoporosis.Results Primary analysis and sensitivity analysis showed that 77 and 61 plasma metabolites had a causal relationship with osteoporosis from the GWAS data in the GCST90038656 and GCST90044600 datasets, respectively. Five common metabolites were identified via intersection. X-13684 levels and the glucose-to-maltose ratio were negatively associated with osteoporosis, whereas glycoursodeoxycholate levels and arachidoylcarnitine(C20) levels were positively associated with osteoporosis(all P < 0.05). The relationship between X-11299 levels and osteoporosis showed contradictory results(all P < 0.05). Pathway analysis indicated that glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, galactose metabolism, arginine biosynthesis, and starch and sucrose metabolism pathways were participated in the development of osteoporosis.Conclusion We found a causal relationship between plasma metabolites and osteoporosis. These results offer novel perspectives with important implications for targeted metabolite-focused interventions in the management of osteoporosis.
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.
基金This work was supported by the Special Project of Performance Incentive and Guidance for Scientific Research Institutions of Chongqing,China (jxyn2022-5)。
文摘In recent years,growth hormone and insulin-like growth factors have become key regulators of bone metabolism and remodeling,crucial for maintaining healthy bone mass throughout life.Studies have shown that adult growth hormone deficiency leads to alterations in bone remodeling,significantly affecting bone microarchitecture and increasing fracture risk.Although recombinant human growth hormone replacement therapy can mitigate these adverse effects,improving bone density,and reduce fracture risk,its effectiveness in treating osteoporosis,especially in adults with established growth hormone deficiency,seems limited.Bisphosphonates inhibit bone resorption by targeting farnesyl pyrophosphate synthase in osteoclasts,and clinical trials have confirmed their efficacy in improving osteoporosis.Therefore,for adult growth hormone deficiency patients with osteoporosis,the use of bisphosphonates alongside growth hormone replacement therapy is recommended.
文摘Objective To investigate the protective effects of naringenin(NRG)against dexamethasone(DEX)-induced osteoporosis(OP)in rats.Methods Molecular docking of NRG was done with AutoDock Vina 1.2.0 software.Forty-eight female Wistar rats were randomly divided into six groups(n=8 each):normal control(NC),DEX(7 mg/kg,i.m.),NRG-low(NRG-L;25 mg/kg,i.g.),NRG-medium(NRG-M;50 mg/kg,i.g.),NRG-high(NRG-H;100 mg/kg,i.g.),and alendronate(ALN;0.25 mg/d,i.g.)groups.OP was induced by administering DEX once a week for five weeks in all groups except NC group.Begining in the third week after the initial DEX administration,the rats in NRG-L,NRG-M,NRG-H,and ALN groups received the corresponding treatments daily for three weeks,while NC and DEX groups received no additional treatment.Serum samples were collected at the end of the experiment for biochemical,bone turnover,antioxidant,lipid profile,and inflammatory cytokine analyses.Femur bones underwent physical parameter testing and histopathological examination.Results The molecular docking results illustrated that NRG docked with calcitonin(CT),lowdensity lipoprotein(LDL),bone morphogenetic protein(BMP),vascular endothelial growth factor(VEGF)receptor,forkhead transcription factors,and osteoprogenitor cells showed good binding energy.In rats administered with 25,50,and 100 mg/kg NRG,there was a significant enhancement in serum biochemical indices,characterized by a reduction in tartrate-resistant acid phosphatase(TRAP),parathyroid hormone(PTH),and an elevation in osteocalcin(OC)and CT levels(P<0.05,P<0.01,and P<0.001,respectively).Despite no significant changes in thickness,weight,and length(P>0.05),there was a marked increase in bone mineral density(BMD)(P<0.01,P<0.001,and P<0.001,respectively).Antioxidant enzyme markers showed significant upregulation,with higher glutathione,superoxide dismutase,and catalase,and a concurrent decrease in malondialdehyde(MDA)(P<0.05,P<0.01,and P<0.001,respectively).The lipid profile also improved significantly,with lower cholesterol(CH),triglycerides(TG),and low-density lipoprotein(LDL)levels,and an increase in high-density lipoprotein(HDL)level(P<0.05,P<0.01,and P<0.001,respectively).Inflammatory cytokine levels were reduced,as evidenced by decreases in tumor necrosis factor(TNF),interleukin(IL)-6,and IL-1β(P<0.05,P<0.01,and P<0.001,respectively).Furthermore,histological alterations revealed obvious improvements,and the body weight of rats treated with NRG showed an increase compared with DEX group.Conclusion These findings imply that NRG exhibited a protective effect against DEX-induced OP in rats as it promotes the bone formation process by increasing the number of bone turnover markers including OC and CT,and restoring of antioxidant status,lipid metabolism,and inflammatory markers.
