Objective:Osteoarthritis(OA)and sarcopenia are significant health concerns in the elderly,substantially impacting their daily activities and quality of life.However,the relationship between them remains poorly underst...Objective:Osteoarthritis(OA)and sarcopenia are significant health concerns in the elderly,substantially impacting their daily activities and quality of life.However,the relationship between them remains poorly understood.This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia.Methods:Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)between disease and control groups were identified using R software.Common DEGs were extracted via Venn diagram analysis.Gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs.Protein-protein interaction(PPI)networks were constructed,and candidate hub genes were ranked using the maximal clique centrality(MCC)algorithm.Further validation of hub gene expression was performed using 2 independent datasets.Receiver operating characteristic(ROC)curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia.Mouse models of OA and sarcopenia were established.Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model.The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement.Real-time reverse transcription PCR(real-time RT-PCR)was employed to assess the mRNA expression levels of candidate key genes in both models.Gene set enrichment analysis(GSEA)was conducted to identify pathways associated with the selected shared key genes in both diseases.Results:A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia,including 76 upregulated and 13 downregulated genes.These 89 DEGs were significantly enriched in protein digestion and absorption,the PI3K-Akt signaling pathway,and extracellular matrix-receptor interaction.PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes.Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets,AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases,both of which showed a significant upregulation trend in the disease groups(all P<0.05).The value of area under the curve(AUC)for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7,indicating that both genes have potential value in predicting OA and sarcopenia.Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups(all P<0.05),consistent with the results observed in the bioinformatics analysis.GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction,ribosome,and oxidative phosphorylation in OA and sarcopenia.Conclusion:AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia.The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.展开更多
Aiming at the characteristics of multi-stage and(extremely)small samples of the identification problem of key effectiveness indexes of weapon equipment system-of-systems(WESoS),a Bayesian intelligent identification an...Aiming at the characteristics of multi-stage and(extremely)small samples of the identification problem of key effectiveness indexes of weapon equipment system-of-systems(WESoS),a Bayesian intelligent identification and inference model for system effectiveness assessment indexes based on dynamic grey incidence is proposed.The method uses multi-layer Bayesian techniques,makes full use of historical statistics and empirical information,and determines the Bayesian estima-tion of the incidence degree of indexes,which effectively solves the difficulties of small sample size of effectiveness indexes and difficulty in obtaining incidence rules between indexes.Sec-ondly,The method quantifies the incidence relationship between evaluation indexes and combat effectiveness based on Bayesian posterior grey incidence,and then identifies key system effec-tiveness evaluation indexes.Finally,the proposed method is applied to a case of screening key effectiveness indexes of a missile defensive system,and the analysis results show that the proposed method can fuse multi-moment information and extract multi-stage key indexes,and has good data extraction capability in the case of small samples.展开更多
物联网中RFID技术的应用非常广泛,但是RFID系统的安全性却存在着很大隐患。在RFID系统中标签与读写器间的通信信道是最易受到攻击,传输数据的完整性与保密性得不到保障,因而需要加强RFID系统通信的安全机制。考虑到RFID系统的硬件条件...物联网中RFID技术的应用非常广泛,但是RFID系统的安全性却存在着很大隐患。在RFID系统中标签与读写器间的通信信道是最易受到攻击,传输数据的完整性与保密性得不到保障,因而需要加强RFID系统通信的安全机制。考虑到RFID系统的硬件条件与成本限制,需要建立一个适合RFID系统的安全认证协议,来解决在RFID系统中信息传输所遇到的安全问题。PRESENT算法是轻量级的分组加密算法,将PRESENT结合到RFID系统的安全认证协议中,形成了新的RFID安全认证协议PRSA(PRESENT based RFID security authentication)。此协议可以增强RFID系统的安全性而又不会占用过多的硬件资源,从而能够适用于低成本的RFID系统的通信安全。展开更多
基金supported by the National Natural Science Foundation of China(82060418).
文摘Objective:Osteoarthritis(OA)and sarcopenia are significant health concerns in the elderly,substantially impacting their daily activities and quality of life.However,the relationship between them remains poorly understood.This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia.Methods:Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)between disease and control groups were identified using R software.Common DEGs were extracted via Venn diagram analysis.Gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs.Protein-protein interaction(PPI)networks were constructed,and candidate hub genes were ranked using the maximal clique centrality(MCC)algorithm.Further validation of hub gene expression was performed using 2 independent datasets.Receiver operating characteristic(ROC)curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia.Mouse models of OA and sarcopenia were established.Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model.The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement.Real-time reverse transcription PCR(real-time RT-PCR)was employed to assess the mRNA expression levels of candidate key genes in both models.Gene set enrichment analysis(GSEA)was conducted to identify pathways associated with the selected shared key genes in both diseases.Results:A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia,including 76 upregulated and 13 downregulated genes.These 89 DEGs were significantly enriched in protein digestion and absorption,the PI3K-Akt signaling pathway,and extracellular matrix-receptor interaction.PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes.Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets,AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases,both of which showed a significant upregulation trend in the disease groups(all P<0.05).The value of area under the curve(AUC)for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7,indicating that both genes have potential value in predicting OA and sarcopenia.Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups(all P<0.05),consistent with the results observed in the bioinformatics analysis.GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction,ribosome,and oxidative phosphorylation in OA and sarcopenia.Conclusion:AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia.The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.
基金supported by the National Natural Science Foundation of China(72271124,72071111).
文摘Aiming at the characteristics of multi-stage and(extremely)small samples of the identification problem of key effectiveness indexes of weapon equipment system-of-systems(WESoS),a Bayesian intelligent identification and inference model for system effectiveness assessment indexes based on dynamic grey incidence is proposed.The method uses multi-layer Bayesian techniques,makes full use of historical statistics and empirical information,and determines the Bayesian estima-tion of the incidence degree of indexes,which effectively solves the difficulties of small sample size of effectiveness indexes and difficulty in obtaining incidence rules between indexes.Sec-ondly,The method quantifies the incidence relationship between evaluation indexes and combat effectiveness based on Bayesian posterior grey incidence,and then identifies key system effec-tiveness evaluation indexes.Finally,the proposed method is applied to a case of screening key effectiveness indexes of a missile defensive system,and the analysis results show that the proposed method can fuse multi-moment information and extract multi-stage key indexes,and has good data extraction capability in the case of small samples.
文摘物联网中RFID技术的应用非常广泛,但是RFID系统的安全性却存在着很大隐患。在RFID系统中标签与读写器间的通信信道是最易受到攻击,传输数据的完整性与保密性得不到保障,因而需要加强RFID系统通信的安全机制。考虑到RFID系统的硬件条件与成本限制,需要建立一个适合RFID系统的安全认证协议,来解决在RFID系统中信息传输所遇到的安全问题。PRESENT算法是轻量级的分组加密算法,将PRESENT结合到RFID系统的安全认证协议中,形成了新的RFID安全认证协议PRSA(PRESENT based RFID security authentication)。此协议可以增强RFID系统的安全性而又不会占用过多的硬件资源,从而能够适用于低成本的RFID系统的通信安全。
