Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work [Xu et al. Physica A, 456 294（2016）], we measure the contribution of a path in...Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work [Xu et al. Physica A, 456 294（2016）], we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight,and propose a weighted prediction index based on the contributions of paths, namely weighted path entropy（WPE）, to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three other typical weighted indices.展开更多
In the study of weighted complex networks, the interplay between traffic and topology have been paid much attention. However, the variation of topology and weight brought by new added vertices or edges should also be ...In the study of weighted complex networks, the interplay between traffic and topology have been paid much attention. However, the variation of topology and weight brought by new added vertices or edges should also be considered. In this paper, an evolution model of weighted networks driven by traffic dynamics with local perturbation is proposed. The model gives power-law distribution of degree, weight and strength, as confirmed by empirical measurements. By choosing appropriate parameters W and δ, the exponents of various power law distributions can be adjusted to meet real world networks. Nontrivial clustering coefficient C, degree assortativity coefficient r, and strength-degree correlation are also considered. What should be emphasized is that, with the consideration of local perturbation, one can adjust the exponent of strength-degree correlation more effectively. It makes our model more general than previous ones and may help reproducing real world networks more appropriately. PACS numbers： 87.23.Kg, 89.75.Da, 89.75.Fb, 89.75.Hc.展开更多
In the functional properties of complex networks, modules play a central role. In this paper, we propose a new method to detect and describe the modular structures of weighted networks. In order to test the proposed m...In the functional properties of complex networks, modules play a central role. In this paper, we propose a new method to detect and describe the modular structures of weighted networks. In order to test the proposed method, as an example, we use our method to analyse the structural properties of the Chinese railway network. Here, the stations are regarded as the nodes and the track sections are regarded as the links. Rigorous analysis of the existing data shows that using the proposed algorithm, the nodes of network can be classified naturally. Moreover, there are several core nodes in each module. Remarkably, we introduce the correlation function Grs, and use it to distinguish the different modules in weighted networks.展开更多
Many realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on loca...Many realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on local processes, the addition of new nodes intra-community and new links intra- or inter-community. Also, it utilizes the preferential attachment for building connections determined by nodes＇ strengths, which evolves dynamically during the growth of the system. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes＇ degrees and strengths.展开更多
Purpose： This study aims to answer the question to what extent different types of networks can be used to predict future co-authorship among authors.Design/methodology/approach： We compare three types ot networks： ...Purpose： This study aims to answer the question to what extent different types of networks can be used to predict future co-authorship among authors.Design/methodology/approach： We compare three types ot networks： unwelgntea networks, in which a link represents a past collaboration; weighted networks, in which links are weighted by the number of joint publications; and bipartite author-publication networks. The analysis investigates their relation to positive stability, as well as their potential in predicting links in future versions of the co-authorship network. Several hypotheses are tested.Findings： Among other results, we find that weighted networks do not automatically lead to better predictions. Bipartite networks, however, outperform unweighted networks in almost all cases. Research limitations： Only two relatively small case studies are considered Practical implications： The study suggests that future link prediction studies on networks should consider using the bipartite network as a training network. Originality/value： This is the first systematic comparison of unweighted, weighted, and bipartite training networks in link prediction.展开更多
In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned i...In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of v ≥ 1, γ 〉 2, and α 〉 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness.展开更多
We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in...We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in a power-law form, which is different from the well-known result in unweighted network case. Simulation results show that the nodes with larger strength are preferential to be infected, but the hierarchical dynamics are not clearly found. The simulation results also show that larger dispersion of weight of networks leads to slower propagating, which indicates that malicious code propagates more quickly in unweighted scale-free networks than in weighted scale-free networks under the same condition. These results show that not only the topology of networks but also the link weights affect the malicious propagating process.展开更多
Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in connection strengths. In addition, the information spreading through a complex network is often ...Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in connection strengths. In addition, the information spreading through a complex network is often associated with time delays due to the finite speed of signal transmission over a distance. Hence, the weighted complex network with coupling delays have meaningful implications in real world, and resultantly gains increasing attention in various fields of science and engineering. Based on the theory of asymptotic stability of linear time-delay systems, synchronization stability of the weighted complex dynamical network with coupling delays is investigated, and simple criteria are obtained for both delay-independent and delay-dependent stabilities of synchronization states. The obtained criteria in this paper encompass the established results in the literature as special cases. Some examples are given to illustrate the theoretical results.展开更多
Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is s...Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).展开更多
For most networks, the weight of connection is changing with their attachment and inner affinity. By introducing a mixed mechanism of weighted-driven and inner selection, the model exhibits wide range power-law distri...For most networks, the weight of connection is changing with their attachment and inner affinity. By introducing a mixed mechanism of weighted-driven and inner selection, the model exhibits wide range power-law distributions of node strength and edge weight, and the exponent can be adjusted by not only the parameter δ but also the probability q. Furthermore, we investigate the weighted average shortest distance, clustering coefficient, and the correlation of our network. In addition, the weighted assortativity coefficient which characterizes important information of weighted topological networks has been discussed, but the variation of coefficients is much smaller than the former researches.展开更多
We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in nongrowth random networks. In this model, we use multiple-edges to represent the connections between vertices and define...We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in nongrowth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its totM number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scMe-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.展开更多
We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique （maximal complete sub-graph） at. each time step. And the cliques in the network overlap with each othe...We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique （maximal complete sub-graph） at. each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges＇ weight and vertices＇ strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights＇ enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices＇ strength and the distribution o~ edges＇ weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices＇ strength and edges＇ weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.展开更多
An improved weighted scale-free network, which has two evolution mechanisms： topological growth and strength dynamics, has been introduced. The topology structure of the model will be explored in details in this work...An improved weighted scale-free network, which has two evolution mechanisms： topological growth and strength dynamics, has been introduced. The topology structure of the model will be explored in details in this work. The evolution driven mechanism of Olami-Feder Christensen （OFC） model is added to our model to study the self-organlzed criticality and the dynamical behavior. We also.consider attack mechanism and the study of the model with attack is also investigated in this paper. We tlnd there are differences between the model with attack and without attack.展开更多
A novel scheme to construct a hash function based on a weighted complex dynamical network （WCDN） generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then...A novel scheme to construct a hash function based on a weighted complex dynamical network （WCDN） generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then, each block is divided into components, and the nodes and weighted edges are well defined from these components and their relations. Namely, the WCDN closely related to the original message is established. Furthermore, the node dynamics of the WCDN are chosen as a chaotic map. After chaotic iterations, quantization and exclusive-or operations, the fixed-length hash value is obtained. This scheme has the property that any tiny change in message can be diffused rapidly through the WCDN, leading to very different hash values. Analysis and simulation show that the scheme possesses good statistical properties, excellent confusion and diffusion, strong collision resistance and high efficiency.展开更多
Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution（W SD） have focused on unweighted ...Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution（W SD） have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the W SD in a deterministic weighted scale-free small-world network model and find that the W SD grows sublinearly with increasing network order（i.e., the number of nodes） and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the W SD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents.展开更多
Triadic closure is a simple and fundamental kind of link formulation mechanism in network.Local closure coefficient(LCC),a new network property,is to measure the triadic closure with respect to the fraction of length-...Triadic closure is a simple and fundamental kind of link formulation mechanism in network.Local closure coefficient(LCC),a new network property,is to measure the triadic closure with respect to the fraction of length-2 paths for link prediction.In this paper,a weighted format of LCC(WLCC)is introduced to measure the weighted strength of local triadic structure,and a statistic similari-ty-based link prediction metric is proposed to incorporate the definition of WLCC.To prove the metrics effectiveness and scalability,the WLCC formula-tion was further investigated under weighted local Naive Bayes(WLNB)link prediction framework.Finally,extensive experimental studies was conducted with weighted baseline metrics on various public network datasets.The results demonstrate the merits of the proposed metrics in comparison with the weighted baselines.展开更多
In this paper, we investigate a new model with a generalized feedback mechanism in weighted networks. Compare to previous models, we consider the initiative response of people and the important impact of nodes with di...In this paper, we investigate a new model with a generalized feedback mechanism in weighted networks. Compare to previous models, we consider the initiative response of people and the important impact of nodes with different edges on transmission rate as epidemics prevail. Furthermore, by constructing Lyapunov function, we prove that the disease-free equilibrium E^0 is globally asymptotically stable as the epidemic threshold R^＊〈 1. When R^＊ 〉 1, we obtain the permanence of epidemic and the local stability of endemic equilibrium E＊. Finally, one can find a good agreement between numerical simulations and our analytical results.展开更多
Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network i...Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.展开更多
BACKGROUND Voltage-gated sodium channels(VGSCs,or Navs)are highly expressed in various tumors and play a critical role in tumor metastasis and invasion.AIM To identify Nav1.6-associated cancer genes through bioinforma...BACKGROUND Voltage-gated sodium channels(VGSCs,or Navs)are highly expressed in various tumors and play a critical role in tumor metastasis and invasion.AIM To identify Nav1.6-associated cancer genes through bioinformatics analysis and experimental validation,with the goal of determining the role of Nav1.6 in colorectal cancer(CRC)metastasis.METHODS The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)data were analyzed using weighted correlation network analysis(WGCNA)and Venn analysis to identify Nav1.6-associated genes in CRC.siRNA,real-time PCR,and western blotting were employed to validate the Nav1.6-associated cancer genes and signaling pathways identified in CRC.Cell counting kit-8 and Transwell migration assays were used to assess the proliferation and migration of CRC cells.RESULTS The analysis of TCGA and GEO datasets,along with WGCNA,identified 575 differentially expressed genes associated with SCN8A(Nav1.6)in CRC,which were particularly enriched in MAPK signaling pathways.Tissue microarray analysis of surgical samples revealed elevated Nav1.6 levels in CRC tissues,which were predominantly in the cytoplasm and nucleus rather than in the membrane.Cytoplasmic Nav1.6 expression increased with T stage increases,consistent with the TCGA findings.SCN8A knockdown in colon tumor cells significantly reduced cell proliferation and invasion and downregulated key proteins in the RAF-MAPK pathway.CONCLUSION These findings suggest that Nav1.6 promotes CRC cell proliferation and invasion which is related to the MAPK signaling pathway.展开更多
Defensin,an essential component of plant development,is indispensable in pathogen resistance.However,the molecular function of defensins under pathological conditions of Cytospora canker has not been characterized in ...Defensin,an essential component of plant development,is indispensable in pathogen resistance.However,the molecular function of defensins under pathological conditions of Cytospora canker has not been characterized in apple plants.The present study exhibits a detailed overview of the phylogeny and structure of 29 defensins(MdDEF)in apple.Expression analysis revealed that MdDEF genes were spatiotemporally diverse across apple tissues.Five MdDEF genes were found to be significantly up-regulated following a challenge with Cytospora mali.The transgenic overexpression of five defensin genes in apple calli enhanced resistance to C.mali.Among them,MdDEF30 was strongly induced and conferred the highest resistance level in vivo.Meanwhile,antifungal activity assays in vitro demonstrated that a recombinant protein produced from MdDEF30could inhibit the growth of C.mali.Notably,MdDEF30 promoted the accumulation of reactive oxygen species(ROS)and activated defense-related genes such as PR4,PR10,CML13,and MPK3.Co-expression regulatory network analysis showed that MdWRKY75 may regulate the expression of MdDEF30.Further yeast onehybrid(Y1H),luciferase,and chromatin Immunoprecipitation quantitative polymerase chain reaction(ChIPqPCR)assays verified that MdWRKY75 could directly bind to the promoter of MdDEF30.Importantly,pathogen inoculation assays confirmed that MdWRKY75 positively regulates resistance by transcriptionally activating MdDEF30.Overall,these results demonstrated that MdDEF30 promotes resistance to C.mali in apple plants and that MdWRKY75 regulates MdDEF30 expression during the induction of resistance,thereby clarifying biochemical mechanisms of resistance to C.mali in apple trees.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61201173 and 61304154)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20133219120032)+1 种基金the Postdoctoral Science Foundation of China(Grant No.2013M541673)China Postdoctoral Science Special Foundation(Grant No.2015T80556)
文摘Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work [Xu et al. Physica A, 456 294（2016）], we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight,and propose a weighted prediction index based on the contributions of paths, namely weighted path entropy（WPE）, to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three other typical weighted indices.
基金The project supported by National Natural Science Foundation of China under Grant No. 70631001, Changjiang Scholars and Innovative Research Team in University under Grant No. IRT0605, and the State Key Basic Research Program of China under Grant No. 2006CB705500
文摘In the study of weighted complex networks, the interplay between traffic and topology have been paid much attention. However, the variation of topology and weight brought by new added vertices or edges should also be considered. In this paper, an evolution model of weighted networks driven by traffic dynamics with local perturbation is proposed. The model gives power-law distribution of degree, weight and strength, as confirmed by empirical measurements. By choosing appropriate parameters W and δ, the exponents of various power law distributions can be adjusted to meet real world networks. Nontrivial clustering coefficient C, degree assortativity coefficient r, and strength-degree correlation are also considered. What should be emphasized is that, with the consideration of local perturbation, one can adjust the exponent of strength-degree correlation more effectively. It makes our model more general than previous ones and may help reproducing real world networks more appropriately. PACS numbers： 87.23.Kg, 89.75.Da, 89.75.Fb, 89.75.Hc.
文摘In the functional properties of complex networks, modules play a central role. In this paper, we propose a new method to detect and describe the modular structures of weighted networks. In order to test the proposed method, as an example, we use our method to analyse the structural properties of the Chinese railway network. Here, the stations are regarded as the nodes and the track sections are regarded as the links. Rigorous analysis of the existing data shows that using the proposed algorithm, the nodes of network can be classified naturally. Moreover, there are several core nodes in each module. Remarkably, we introduce the correlation function Grs, and use it to distinguish the different modules in weighted networks.
基金supported by Institute of Systems Biology,the Innovation Foundation of Shanghai University of Shanghai University of Chinathe National Natural Science Foundation of China (Grant No 10805033)
文摘Many realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on local processes, the addition of new nodes intra-community and new links intra- or inter-community. Also, it utilizes the preferential attachment for building connections determined by nodes＇ strengths, which evolves dynamically during the growth of the system. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes＇ degrees and strengths.
文摘Purpose： This study aims to answer the question to what extent different types of networks can be used to predict future co-authorship among authors.Design/methodology/approach： We compare three types ot networks： unwelgntea networks, in which a link represents a past collaboration; weighted networks, in which links are weighted by the number of joint publications; and bipartite author-publication networks. The analysis investigates their relation to positive stability, as well as their potential in predicting links in future versions of the co-authorship network. Several hypotheses are tested.Findings： Among other results, we find that weighted networks do not automatically lead to better predictions. Bipartite networks, however, outperform unweighted networks in almost all cases. Research limitations： Only two relatively small case studies are considered Practical implications： The study suggests that future link prediction studies on networks should consider using the bipartite network as a training network. Originality/value： This is the first systematic comparison of unweighted, weighted, and bipartite training networks in link prediction.
基金National Natural Science Foundation of China under Grant Nos.60504019 and 70431002
文摘In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of v ≥ 1, γ 〉 2, and α 〉 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness.
基金Supported by the National Natural Science Foundation of China (90204012, 60573036) and the Natural Science Foundation of Hebei Province (F2006000177)
文摘We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in a power-law form, which is different from the well-known result in unweighted network case. Simulation results show that the nodes with larger strength are preferential to be infected, but the hierarchical dynamics are not clearly found. The simulation results also show that larger dispersion of weight of networks leads to slower propagating, which indicates that malicious code propagates more quickly in unweighted scale-free networks than in weighted scale-free networks under the same condition. These results show that not only the topology of networks but also the link weights affect the malicious propagating process.
基金supported by National Natural Science Foundation of China under Nos. 10702023 and 10832006China Post-doctoral Special Science Foundation No. 200801020+1 种基金the Natural Science Foundation of Inner Mongolia Autonomous Region under Grant No. 2007110020110supported in part by the Project of Knowledge Innovation Program (PKIP) of Chinese Academy of Sciences
文摘Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in connection strengths. In addition, the information spreading through a complex network is often associated with time delays due to the finite speed of signal transmission over a distance. Hence, the weighted complex network with coupling delays have meaningful implications in real world, and resultantly gains increasing attention in various fields of science and engineering. Based on the theory of asymptotic stability of linear time-delay systems, synchronization stability of the weighted complex dynamical network with coupling delays is investigated, and simple criteria are obtained for both delay-independent and delay-dependent stabilities of synchronization states. The obtained criteria in this paper encompass the established results in the literature as special cases. Some examples are given to illustrate the theoretical results.
基金supported by the Notional Natural Science Foundation of China,No.81960417 (to JX)Guangxi Key Research and Development Program,No.GuiKeA B20159027 (to JX)the Natural Science Foundation of Guangxi Zhuang Autonomous Region,No.2022GXNSFBA035545 (to YG)。
文摘Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).
基金supported by the National Natural Science Foundation of China under Grant No.10675060
文摘For most networks, the weight of connection is changing with their attachment and inner affinity. By introducing a mixed mechanism of weighted-driven and inner selection, the model exhibits wide range power-law distributions of node strength and edge weight, and the exponent can be adjusted by not only the parameter δ but also the probability q. Furthermore, we investigate the weighted average shortest distance, clustering coefficient, and the correlation of our network. In addition, the weighted assortativity coefficient which characterizes important information of weighted topological networks has been discussed, but the variation of coefficients is much smaller than the former researches.
基金Supported by the National Natural Science Foundation of China under Grant No.60874080the Commonweal Application Technique Research Project of Zhejiang Province under Grant No.2012C2316the Open Project of State Key Lab of Industrial Control Technology of Zhejiang University under Grant No.ICT1107
文摘We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in nongrowth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its totM number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scMe-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.
基金Supported by National Natural Science Foundation of China under Grant Nos. 60504027 and 60874080the Open Project of State Key Lab of Industrial Control Technology under Grant No. ICT1107
文摘We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique （maximal complete sub-graph） at. each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges＇ weight and vertices＇ strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights＇ enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices＇ strength and the distribution o~ edges＇ weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices＇ strength and edges＇ weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.
基金National Natural Science Foundation of China under Grant No.10675060
文摘An improved weighted scale-free network, which has two evolution mechanisms： topological growth and strength dynamics, has been introduced. The topology structure of the model will be explored in details in this work. The evolution driven mechanism of Olami-Feder Christensen （OFC） model is added to our model to study the self-organlzed criticality and the dynamical behavior. We also.consider attack mechanism and the study of the model with attack is also investigated in this paper. We tlnd there are differences between the model with attack and without attack.
基金Project supported by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2010526)the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20103223110003)The Ministry of Education Research in the Humanities and Social Sciences Planning Fund, China (Grant No. 12YJAZH120)
文摘A novel scheme to construct a hash function based on a weighted complex dynamical network （WCDN） generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then, each block is divided into components, and the nodes and weighted edges are well defined from these components and their relations. Namely, the WCDN closely related to the original message is established. Furthermore, the node dynamics of the WCDN are chosen as a chaotic map. After chaotic iterations, quantization and exclusive-or operations, the fixed-length hash value is obtained. This scheme has the property that any tiny change in message can be diffused rapidly through the WCDN, leading to very different hash values. Analysis and simulation show that the scheme possesses good statistical properties, excellent confusion and diffusion, strong collision resistance and high efficiency.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61402485,61573262,and 61303061)
文摘Many real-world systems can be modeled by weighted small-world networks with high clustering coefficients. Recent studies for rigorously analyzing the weighted spectral distribution（W SD） have focused on unweighted networks with low clustering coefficients. In this paper, we rigorously analyze the W SD in a deterministic weighted scale-free small-world network model and find that the W SD grows sublinearly with increasing network order（i.e., the number of nodes） and provides a sensitive discrimination for each input of this model. This study demonstrates that the scaling feature of the W SD exists in the weighted network model which has high and order-independent clustering coefficients and reasonable power-law exponents.
基金This work is supported by Basic and Applied Basic Research Foundation of Guangdong Province(No.2020A1515011495)Guangzhou Science and Technology Foundation Project(No.202002030266).
文摘Triadic closure is a simple and fundamental kind of link formulation mechanism in network.Local closure coefficient(LCC),a new network property,is to measure the triadic closure with respect to the fraction of length-2 paths for link prediction.In this paper,a weighted format of LCC(WLCC)is introduced to measure the weighted strength of local triadic structure,and a statistic similari-ty-based link prediction metric is proposed to incorporate the definition of WLCC.To prove the metrics effectiveness and scalability,the WLCC formula-tion was further investigated under weighted local Naive Bayes(WLNB)link prediction framework.Finally,extensive experimental studies was conducted with weighted baseline metrics on various public network datasets.The results demonstrate the merits of the proposed metrics in comparison with the weighted baselines.
基金This work is supported by the National Natural Science Foundation of China under Grant 61174039. The authors would like to thank the editor and the reviewers for their constructive comments and suggestions to improve the quality of this paper.
文摘In this paper, we investigate a new model with a generalized feedback mechanism in weighted networks. Compare to previous models, we consider the initiative response of people and the important impact of nodes with different edges on transmission rate as epidemics prevail. Furthermore, by constructing Lyapunov function, we prove that the disease-free equilibrium E^0 is globally asymptotically stable as the epidemic threshold R^＊〈 1. When R^＊ 〉 1, we obtain the permanence of epidemic and the local stability of endemic equilibrium E＊. Finally, one can find a good agreement between numerical simulations and our analytical results.
基金Supported by the National Nature Science Foundation of China under Grant No.10832006PuJiang Project of Shanghai under Grant No.09PJ1405000+1 种基金Key Disciplines of Shanghai Municipality (S30104)Research Grant of Shanghai University under Grant No.SHUCX092014
文摘Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.
基金Supported by Science and Technology Project of Quzhou of China,No.2021Y011Beijing Science and Technology Innovation Medical Development Foundation,No.KC2021-JX-0186-81.
文摘BACKGROUND Voltage-gated sodium channels(VGSCs,or Navs)are highly expressed in various tumors and play a critical role in tumor metastasis and invasion.AIM To identify Nav1.6-associated cancer genes through bioinformatics analysis and experimental validation,with the goal of determining the role of Nav1.6 in colorectal cancer(CRC)metastasis.METHODS The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)data were analyzed using weighted correlation network analysis(WGCNA)and Venn analysis to identify Nav1.6-associated genes in CRC.siRNA,real-time PCR,and western blotting were employed to validate the Nav1.6-associated cancer genes and signaling pathways identified in CRC.Cell counting kit-8 and Transwell migration assays were used to assess the proliferation and migration of CRC cells.RESULTS The analysis of TCGA and GEO datasets,along with WGCNA,identified 575 differentially expressed genes associated with SCN8A(Nav1.6)in CRC,which were particularly enriched in MAPK signaling pathways.Tissue microarray analysis of surgical samples revealed elevated Nav1.6 levels in CRC tissues,which were predominantly in the cytoplasm and nucleus rather than in the membrane.Cytoplasmic Nav1.6 expression increased with T stage increases,consistent with the TCGA findings.SCN8A knockdown in colon tumor cells significantly reduced cell proliferation and invasion and downregulated key proteins in the RAF-MAPK pathway.CONCLUSION These findings suggest that Nav1.6 promotes CRC cell proliferation and invasion which is related to the MAPK signaling pathway.
基金funded by the National Key R&D Program of China(2023YFD1401401)the China Agriculture Research System(CARS27)。
文摘Defensin,an essential component of plant development,is indispensable in pathogen resistance.However,the molecular function of defensins under pathological conditions of Cytospora canker has not been characterized in apple plants.The present study exhibits a detailed overview of the phylogeny and structure of 29 defensins(MdDEF)in apple.Expression analysis revealed that MdDEF genes were spatiotemporally diverse across apple tissues.Five MdDEF genes were found to be significantly up-regulated following a challenge with Cytospora mali.The transgenic overexpression of five defensin genes in apple calli enhanced resistance to C.mali.Among them,MdDEF30 was strongly induced and conferred the highest resistance level in vivo.Meanwhile,antifungal activity assays in vitro demonstrated that a recombinant protein produced from MdDEF30could inhibit the growth of C.mali.Notably,MdDEF30 promoted the accumulation of reactive oxygen species(ROS)and activated defense-related genes such as PR4,PR10,CML13,and MPK3.Co-expression regulatory network analysis showed that MdWRKY75 may regulate the expression of MdDEF30.Further yeast onehybrid(Y1H),luciferase,and chromatin Immunoprecipitation quantitative polymerase chain reaction(ChIPqPCR)assays verified that MdWRKY75 could directly bind to the promoter of MdDEF30.Importantly,pathogen inoculation assays confirmed that MdWRKY75 positively regulates resistance by transcriptionally activating MdDEF30.Overall,these results demonstrated that MdDEF30 promotes resistance to C.mali in apple plants and that MdWRKY75 regulates MdDEF30 expression during the induction of resistance,thereby clarifying biochemical mechanisms of resistance to C.mali in apple trees.
