This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this...This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method.展开更多
Lung cancer is a prevalent malignancy,and fatalities of the disease exceed 400,000 cases worldwide.Lung squamous cell carcinoma(LUSC)has been recognized as the most common pathological form of lung cancer.The comprehe...Lung cancer is a prevalent malignancy,and fatalities of the disease exceed 400,000 cases worldwide.Lung squamous cell carcinoma(LUSC)has been recognized as the most common pathological form of lung cancer.The comprehensive understanding of molecular features related to LUSC progression has great significance in LUSC prognosis assessment and clinical management.In this study,we aim to identify a panel of signature genes closely associated with LUSC,which can provide novel insights into the progression of LUSC.Gene expression profiles were retrieved from public resources including gene expression omnibus(GEO)and the cancer genome atlas(TCGA)database.Differentially expressed genes(DEGs)between LUSC specimens and normal lung tissues were identified by bioinformatics analyses.A total of 66 DEGs were identified based on two cohorts of data.CytoHubba plugin of Cytoscape software was utilized for the further analyses of the top 10 candidate hub genes including OGN,ABI3BP,MAMDC2,FGF7,FAM107A,SPARCL1,DCN,COL14A1,and MFAP4 and CHRDL1,which showed significant downregulation in LUSC.Two LUSC cell lines were used to validate the functions of CHRDL1 and FAM107A through overexpression experiment.Together,our data revealed novel candidate tumor-suppressor genes in LUSC,suggesting previously unappreciated mechanisms in the progression of LUSC.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.11672231 and11672233)the Natural Science Foundation of Shaanxi Province(No.2016JM1010)+1 种基金the Fundamental Research Funds for the Central Universities(No.3102017AX008)the Seed Foundation of Innovation and Creation for Graduate Students at the Northwestern Polytechnical University of China(No.Z2017187)
文摘This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method.
基金Department of Science and Technology of Yunnan Province,Provincial Basic Research Program(Kunkun-Medical Joint Special Project),202101AY070001-134Yunnan Provincial Department of Science and Technology,Yunnan Provincial Gerontology Research Center,202102AA310069Yunnan Provincial Department of Science and Technology-Kunming Medical University Basic Research Joint Special Key Project,202201AY070001-136.
文摘Lung cancer is a prevalent malignancy,and fatalities of the disease exceed 400,000 cases worldwide.Lung squamous cell carcinoma(LUSC)has been recognized as the most common pathological form of lung cancer.The comprehensive understanding of molecular features related to LUSC progression has great significance in LUSC prognosis assessment and clinical management.In this study,we aim to identify a panel of signature genes closely associated with LUSC,which can provide novel insights into the progression of LUSC.Gene expression profiles were retrieved from public resources including gene expression omnibus(GEO)and the cancer genome atlas(TCGA)database.Differentially expressed genes(DEGs)between LUSC specimens and normal lung tissues were identified by bioinformatics analyses.A total of 66 DEGs were identified based on two cohorts of data.CytoHubba plugin of Cytoscape software was utilized for the further analyses of the top 10 candidate hub genes including OGN,ABI3BP,MAMDC2,FGF7,FAM107A,SPARCL1,DCN,COL14A1,and MFAP4 and CHRDL1,which showed significant downregulation in LUSC.Two LUSC cell lines were used to validate the functions of CHRDL1 and FAM107A through overexpression experiment.Together,our data revealed novel candidate tumor-suppressor genes in LUSC,suggesting previously unappreciated mechanisms in the progression of LUSC.
