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
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
Objective:To identify promising biomarkers for the pathogenesis of major depressive disorder(MDD).Methods:Microarray chips of MDD patients,including the GSE98793,GSE52790,and GSE39653 datasets,were obtained from the G...Objective:To identify promising biomarkers for the pathogenesis of major depressive disorder(MDD).Methods:Microarray chips of MDD patients,including the GSE98793,GSE52790,and GSE39653 datasets,were obtained from the Gene Expression Omnibus database.The biological processes and pathways related to MDD were investigated using the GO and KEGG pathway tools.Weighted gene coexpression network analysis was conducted to identify modules related to MDD.The hub genes associated with MDD were obtained via protein-protein interaction analysis.Finally,the expression of hub genes in the hippocampal tissues of depression-like rats was detected by reverse transcription-polymerase chain reaction and Western blotting.Results:A total of 658 differentially expressed genes were identified from the Gene Expression Omnibus datasets;thus,these genes and the GSE98793 dataset were used to conduct weighted gene coexpression network analysis.A total of 244 module-related genes were identified and these genes were highly correlated with MDD.These genes were involved in the Ras signaling pathway,regulation of the actin cytoskeleton,and axon guidance according to the KEGG analysis.Hub genes,including MAPK14,SOCS1,TLR2,PTK2B,and GRB2,were obtained via protein-protein interaction analysis.All these hub genes showed better diagnostic efficiency in the GSE52790,GSE39653,and GSE98793 datasets.In vivo experiments revealed that compared with those in control rats,SOCS1 and MAPK14 expression was significantly decreased;while GRB2,TLR2,and PTK2B expression was increased in the hippocampi of depression-like rats.Conclusions:Our study demonstrates that GRB2,TLR2,SOCS1,PTK2B,and MAPK14 are promising hub genes,and targeting these five genes may be an effective treatment strategy for MDD.展开更多
BACKGROUND Lotus plumule and its active components have demonstrated inhibitory effects on gastric cancer(GC).However,the molecular mechanism of lotus plumule against GC remains unclear and requires further investigat...BACKGROUND Lotus plumule and its active components have demonstrated inhibitory effects on gastric cancer(GC).However,the molecular mechanism of lotus plumule against GC remains unclear and requires further investigation.AIM To identify the key hub genes associated with the anti-GC effects of lotus plumule.METHODS This study investigated the potential targets of traditional Chinese medicine for inhibiting GC using weighted gene co-expression network analysis and bio-informatics.Initially,the active components and targets of the lotus plumule and the differentially expressed genes associated with GC were identified.Sub-sequently,a protein-protein interaction network was constructed to elucidate the interactions between drug targets and disease-related genes,facilitating the identification of hub genes within the network.The clinical significance of these hub genes was evaluated,and their upstream transcription factors and down-stream targets were identified.The binding ability of a hub gene with its down-stream targets was verified using molecular docking technology.Finally,molecular docking was performed to evaluate the binding affinity between the active ingredients of lotus plumule and the hub gene.RESULTS This study identified 26 genes closely associated with GC.Machine learning analysis and external validation narrowed the list to four genes:Aldo-keto reductase family 1 member B10,fructose-bisphosphatase 1,protein arginine methyltransferase 1,and carbonic anhydrase 9.These genes indicated a strong correlation with anti-GC activity.CONCLUSION Lotus plumule exhibits anti-GC effects.This study identified four hub genes with potential as novel targets for diagnosing and treating GC,providing innovative perspectives for its clinical management.展开更多
BACKGROUND Metastasis is the main reason leading to death in colorectal cancer(CRC)and about 25%of CRC patients developed metastasis when first diagnosed.Thus,unveiling biomarkers of CRC metastasis is of great signifi...BACKGROUND Metastasis is the main reason leading to death in colorectal cancer(CRC)and about 25%of CRC patients developed metastasis when first diagnosed.Thus,unveiling biomarkers of CRC metastasis is of great significance.AIM To reveal biomarkers of CRC metastasis.METHODS Weighted gene co-expression network analysis was conducted to identify metastatic biomarkers in CRC through a systematic analysis of the GSE29621 dataset.Comprehensive validation was performed subsequently using publicly available datasets from The Cancer Genome Atlas and Gene Expression Omnibus and supplemented with experimental verification in CRC cell lines.Moreover,the identified hub gene charged multivesicular body protein 7(CHMP7)was further subjected to clinical correlation analysis via Kaplan-Meier survival curves and Gene Set Enrichment Analysis to assess its prognostic significance and potential mechanistic involvement in CRC progression.RESULTS CHMP7 was identified as a key metastatic biomarker of CRC which displayed lower expression in CRC tissues,especially in CRC patients with metastasis and CRC cell lines with high metastasis potential.The expression of CHMP7 was significantly correlated with normal,metastatic tumor,pathologic stage,and lymphatic invasion(P<0.05).CRC patients with higher expression of CHMP7 exhibited better overall survival.Besides,Gene Set Enrichment Analysis results showed that CHMP7 might be involved in metastatic related pathways.CONCLUSION Our results indicate that CHMP7 might be a prognostic biomarker correlated with CRC metastasis.展开更多
Background:Traumatic cerebral edema(TCE)is a life-threatening condition caused by excessive fluid accumulation in the brain,leading to elevated intracranial pressure and potential brain damage.Current treatments,inclu...Background:Traumatic cerebral edema(TCE)is a life-threatening condition caused by excessive fluid accumulation in the brain,leading to elevated intracranial pressure and potential brain damage.Current treatments,including osmotic diuretics and antihypertensive medications,have limitations.Zhenwu Decoction,a traditional Chinese medicine formulation,has shown promise due to its multi-target pharmacological effects,including modulation of inflammation and regulation of aquaporins.Methods:Active components and targets of Zhenwu Decoction were identified using databases such as SymMap and TCMID.Protein-protein interaction networks and gene expression data related to toxic chemical exposure were analyzed through the GEO database and gene set enrichment analysis.Weighted gene co-expression network analysis(WGCNA)was used to identify TCE-associated gene modules.Molecular docking and in vivo validation using a traumatic brain injury model were conducted.Results:A total of 880 active components and 235 potential targets of Zhenwu Decoction were identified.Protein-protein interaction network analysis and WGCNA revealed key gene modules and inflammatory response-related DEGs.Molecular docking suggested lactiflorin and poricoic acid A as potential drug candidates targeting ATP2A2 and ATP2C1.Experimental results confirmed that Zhenwu Decoction improved TCE outcomes by upregulating these proteins.Conclusion:This study provides molecular evidence for the efficacy of Zhenwu Decoction in treating TCE,highlighting its mechanisms.The integration of WGCNA and molecular docking offers new insights into drug development and precision medicine for TCE.展开更多
Background:Tetralogy of Fallot(TOF),the predominant cyanotic congenital heart defect,arisesfrom multifactorial gene-envirorment interactions disrup ting cardiac developmental networks.This studyinvestiga ted TOF-speci...Background:Tetralogy of Fallot(TOF),the predominant cyanotic congenital heart defect,arisesfrom multifactorial gene-envirorment interactions disrup ting cardiac developmental networks.This studyinvestiga ted TOF-specific transcriptional alterations and identified high-confidence candidate genes.Methods:Based on GSE36761 transcriptome data,a weighted gene co-exp ression network analysis(WGCNA)andprotein-protein interaction(PPI)network were conducted to identify TOF-related sub-netrwork and Hub genes.The potentialbiological functions among these genes were revealed by enrichment analysis.Genetic,epigeneticand transcriptional alteration in the Fub genes were analyzed with leveraged public resources:a methylationdataset(CSE62629)and two single-cell datasets(EGAS00001003996 and GSE126128),Results:Eight Hub geneswere identified using the WGCNA network and PPl network,and functional errichment analysis revealedthatGJA1,RUNX2,FTK7,PRICKLE1,and SPRP1 were involved in the morphogenesis of an epithelium,anddysregulation of the signaling were also found in the other two TOF datasets,Furthermore,the study foundthat the promoters of GJA1,RUNX2,FTK7,and PRICKLE1 genes were hypermethylated and that GJA1 andSFRP1 are highly expressed in mouse second heart field cells and neural crest cells,and the la tter is expressedin human embry onic outflow tract cells.Since RUNX2 was not expressed in human and mouse embryonichearts,GJA1,FTK7,PRICKLE1,and SPRP1 were ultimately identified as TOF candidate genes.Conclusion:Based on the WGCNA network and various bioinformatics analysis approaches,we screened 4 TOF candidatepathogenic genes,and found that the signaling pathways related to the morphogenesis of an epithelium maybe involved in the pathogenesis of TOF.展开更多
This paper proposes a method of realizing generalized chaos synchronization of a weighted complex network with different nodes. Chaotic systems with diverse structures are taken as the nodes of the complex dynamical n...This paper proposes a method of realizing generalized chaos synchronization of a weighted complex network with different nodes. Chaotic systems with diverse structures are taken as the nodes of the complex dynamical network, the nonlinear terms of the systems are taken as coupling functions, and the relations among the nodes are built through weighted connections. The structure of the coupling functions between the connected nodes is obtained based on Lyapunov stability theory. A complex network with nodes of Lorenz system, Coullet system, RSssler system and the New system is taken as an example for simulation study and the results show that generalized chaos synchronization exists in the whole weighted complex network with different nodes when the coupling strength among the nodes is given with any weight value. The method can be used in realizing generalized chaos synchronization of a weighted complex network with different nodes. Furthermore, both the weight value of the coupling strength among the nodes and the number of the nodes have no effect on the stability of synchronization in the whole complex network.展开更多
In data-driven fault diagnosis for turbo-generator sets,the fault samples are usually expensive to obtain,and inevitably with noise,which will both lead to an unsatisfying identification performance of diagnosis model...In data-driven fault diagnosis for turbo-generator sets,the fault samples are usually expensive to obtain,and inevitably with noise,which will both lead to an unsatisfying identification performance of diagnosis models.To address these issues,this paper proposes a fault diagnosis model for turbo-generator sets based on Weighted Extension Neural Network(W-ENN).WENN is a novel neural network which has three types of connection weights and an improved correlation function.The performance of the proposed model is validated against Extension Neural Network(ENN),Support Vector Machine(SVM),Relevance Vector Machine(RVM)and Extreme Learning Machine(ELM)based models.The results indicate that,on noisy small sample sets,the proposed model is superior to the other models in terms of higher identification accuracy with fewer samples and strong noise-tolerant ability.The findings of this study may serve as a powerful fault diagnosis model for turbo-generator sets on noisy small sample sets.展开更多
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev...AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.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
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
Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair perip...Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.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
The principle that ＇the brand effect is attractive＇ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly...The principle that ＇the brand effect is attractive＇ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general frame- work that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general, the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes＇ properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment, the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model.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
Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict t...Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.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
Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughp...Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughput gene expression data using weighted co-expression network analysis(WGCNA)to explore the potential therapeutic targets.Methods The dataset of GSE36980 was obtained from the Gene Expression Omnibus(GEO)database.Normalization,quality control,filtration,and soft-threshold calculation were carried out before clustering the co-expressed genes into different modules.Furthermore,the correlation coefiidents between the modules and clinical traits were computed to identify the key modules.Gene ontology and pathway enrichment analyses were performed on the key module genes.The STRING database was used to construct the protein-protein interaction(PPI)networks,which were further analyzed by Cytoscape app(MCODE).Finally,validation of hub genes was conducted by external GEO datasets of GSE 1297 and GSE 28146.Results Co-expressed genes were clustered into 27 modules,among which 6 modules were identified as the key module relating to AD occurrence.These key modules are primarily involved in chemical synaptic transmission(G0:0007268),the tricarboxylic acid(TCA)cycle and respiratory electron transport(R-HSA-1428517).WDR47,OXCT1,C3orfl4,ATP6V1A,SLC25A14,NAPB were found as the hub genes and their expression were validated by external datasets.Conclusions Through modules co-expression network analyses and PPI network analyses,we identified the hub genes of AD,including WDR47,0XCT1,C3orfl4i ATP6V1A,SLC25A14 and NAPB.Among them,three hub genes(ATP6V1A,SLC25A14,OXCT1)might contribute to AD pathogenesis through pathway of TCA cycle.展开更多
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 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.
基金supported by the National Natural Science Foundation of China(No.81774281 and No.82474303)the Natural Science Foundation of Hunan Province(2023JJ30888)the leading national joint discipline of Chinese and Western medicines to the Chinese Medicine Department,Xiangya Hospital,CSU.
文摘Objective:To identify promising biomarkers for the pathogenesis of major depressive disorder(MDD).Methods:Microarray chips of MDD patients,including the GSE98793,GSE52790,and GSE39653 datasets,were obtained from the Gene Expression Omnibus database.The biological processes and pathways related to MDD were investigated using the GO and KEGG pathway tools.Weighted gene coexpression network analysis was conducted to identify modules related to MDD.The hub genes associated with MDD were obtained via protein-protein interaction analysis.Finally,the expression of hub genes in the hippocampal tissues of depression-like rats was detected by reverse transcription-polymerase chain reaction and Western blotting.Results:A total of 658 differentially expressed genes were identified from the Gene Expression Omnibus datasets;thus,these genes and the GSE98793 dataset were used to conduct weighted gene coexpression network analysis.A total of 244 module-related genes were identified and these genes were highly correlated with MDD.These genes were involved in the Ras signaling pathway,regulation of the actin cytoskeleton,and axon guidance according to the KEGG analysis.Hub genes,including MAPK14,SOCS1,TLR2,PTK2B,and GRB2,were obtained via protein-protein interaction analysis.All these hub genes showed better diagnostic efficiency in the GSE52790,GSE39653,and GSE98793 datasets.In vivo experiments revealed that compared with those in control rats,SOCS1 and MAPK14 expression was significantly decreased;while GRB2,TLR2,and PTK2B expression was increased in the hippocampi of depression-like rats.Conclusions:Our study demonstrates that GRB2,TLR2,SOCS1,PTK2B,and MAPK14 are promising hub genes,and targeting these five genes may be an effective treatment strategy for MDD.
基金Supported by Ningxia Key Research and Development Program,No.2023BEG02015Talent Development Projects of Young Qihuang of National Administration of Traditional Chinese Medicine(2020).
文摘BACKGROUND Lotus plumule and its active components have demonstrated inhibitory effects on gastric cancer(GC).However,the molecular mechanism of lotus plumule against GC remains unclear and requires further investigation.AIM To identify the key hub genes associated with the anti-GC effects of lotus plumule.METHODS This study investigated the potential targets of traditional Chinese medicine for inhibiting GC using weighted gene co-expression network analysis and bio-informatics.Initially,the active components and targets of the lotus plumule and the differentially expressed genes associated with GC were identified.Sub-sequently,a protein-protein interaction network was constructed to elucidate the interactions between drug targets and disease-related genes,facilitating the identification of hub genes within the network.The clinical significance of these hub genes was evaluated,and their upstream transcription factors and down-stream targets were identified.The binding ability of a hub gene with its down-stream targets was verified using molecular docking technology.Finally,molecular docking was performed to evaluate the binding affinity between the active ingredients of lotus plumule and the hub gene.RESULTS This study identified 26 genes closely associated with GC.Machine learning analysis and external validation narrowed the list to four genes:Aldo-keto reductase family 1 member B10,fructose-bisphosphatase 1,protein arginine methyltransferase 1,and carbonic anhydrase 9.These genes indicated a strong correlation with anti-GC activity.CONCLUSION Lotus plumule exhibits anti-GC effects.This study identified four hub genes with potential as novel targets for diagnosing and treating GC,providing innovative perspectives for its clinical management.
基金Supported by the National Natural Science Foundation of China,No.82260715the Middle-Aged and Young Teachers in Colleges and Universities in Guangxi Basic Ability Promotion Project,No.2024KY0302+2 种基金Guangxi Collaborative Innovation Center for Research on Functional Ingredients of Agricultural Residues,No.CICAR2016-P6the Grant of Research Project on High-Level Talents of Youjiang Medical College for Nationalities,No.YY2021SK002Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province,No.202300011.
文摘BACKGROUND Metastasis is the main reason leading to death in colorectal cancer(CRC)and about 25%of CRC patients developed metastasis when first diagnosed.Thus,unveiling biomarkers of CRC metastasis is of great significance.AIM To reveal biomarkers of CRC metastasis.METHODS Weighted gene co-expression network analysis was conducted to identify metastatic biomarkers in CRC through a systematic analysis of the GSE29621 dataset.Comprehensive validation was performed subsequently using publicly available datasets from The Cancer Genome Atlas and Gene Expression Omnibus and supplemented with experimental verification in CRC cell lines.Moreover,the identified hub gene charged multivesicular body protein 7(CHMP7)was further subjected to clinical correlation analysis via Kaplan-Meier survival curves and Gene Set Enrichment Analysis to assess its prognostic significance and potential mechanistic involvement in CRC progression.RESULTS CHMP7 was identified as a key metastatic biomarker of CRC which displayed lower expression in CRC tissues,especially in CRC patients with metastasis and CRC cell lines with high metastasis potential.The expression of CHMP7 was significantly correlated with normal,metastatic tumor,pathologic stage,and lymphatic invasion(P<0.05).CRC patients with higher expression of CHMP7 exhibited better overall survival.Besides,Gene Set Enrichment Analysis results showed that CHMP7 might be involved in metastatic related pathways.CONCLUSION Our results indicate that CHMP7 might be a prognostic biomarker correlated with CRC metastasis.
基金the financial support provided by the Discipline Construction Project of Shanghai Pudong New Area Health Commission(Grant Number:PWZzb2022-21)the Shanghai Pudong New Area Health System Discipline Leader Training Project(Grant Number:PWRd2022-14)+1 种基金the Health Science and Technology Project of Shanghai Pudong New Area Health Committee(Grant Number:PW2023A-51)the Shanghai Pudong New Area Gongli Hospital Youth Fund Project(Grant Number:2020YQNJJ-16).
文摘Background:Traumatic cerebral edema(TCE)is a life-threatening condition caused by excessive fluid accumulation in the brain,leading to elevated intracranial pressure and potential brain damage.Current treatments,including osmotic diuretics and antihypertensive medications,have limitations.Zhenwu Decoction,a traditional Chinese medicine formulation,has shown promise due to its multi-target pharmacological effects,including modulation of inflammation and regulation of aquaporins.Methods:Active components and targets of Zhenwu Decoction were identified using databases such as SymMap and TCMID.Protein-protein interaction networks and gene expression data related to toxic chemical exposure were analyzed through the GEO database and gene set enrichment analysis.Weighted gene co-expression network analysis(WGCNA)was used to identify TCE-associated gene modules.Molecular docking and in vivo validation using a traumatic brain injury model were conducted.Results:A total of 880 active components and 235 potential targets of Zhenwu Decoction were identified.Protein-protein interaction network analysis and WGCNA revealed key gene modules and inflammatory response-related DEGs.Molecular docking suggested lactiflorin and poricoic acid A as potential drug candidates targeting ATP2A2 and ATP2C1.Experimental results confirmed that Zhenwu Decoction improved TCE outcomes by upregulating these proteins.Conclusion:This study provides molecular evidence for the efficacy of Zhenwu Decoction in treating TCE,highlighting its mechanisms.The integration of WGCNA and molecular docking offers new insights into drug development and precision medicine for TCE.
基金supported by the National Natural Science Found ation of China(No.8230045i for Zhen Wang,82302230 for jiawei Shi,82202194 for Jing Wang and 82171961 for Haiyan Cao).
文摘Background:Tetralogy of Fallot(TOF),the predominant cyanotic congenital heart defect,arisesfrom multifactorial gene-envirorment interactions disrup ting cardiac developmental networks.This studyinvestiga ted TOF-specific transcriptional alterations and identified high-confidence candidate genes.Methods:Based on GSE36761 transcriptome data,a weighted gene co-exp ression network analysis(WGCNA)andprotein-protein interaction(PPI)network were conducted to identify TOF-related sub-netrwork and Hub genes.The potentialbiological functions among these genes were revealed by enrichment analysis.Genetic,epigeneticand transcriptional alteration in the Fub genes were analyzed with leveraged public resources:a methylationdataset(CSE62629)and two single-cell datasets(EGAS00001003996 and GSE126128),Results:Eight Hub geneswere identified using the WGCNA network and PPl network,and functional errichment analysis revealedthatGJA1,RUNX2,FTK7,PRICKLE1,and SPRP1 were involved in the morphogenesis of an epithelium,anddysregulation of the signaling were also found in the other two TOF datasets,Furthermore,the study foundthat the promoters of GJA1,RUNX2,FTK7,and PRICKLE1 genes were hypermethylated and that GJA1 andSFRP1 are highly expressed in mouse second heart field cells and neural crest cells,and the la tter is expressedin human embry onic outflow tract cells.Since RUNX2 was not expressed in human and mouse embryonichearts,GJA1,FTK7,PRICKLE1,and SPRP1 were ultimately identified as TOF candidate genes.Conclusion:Based on the WGCNA network and various bioinformatics analysis approaches,we screened 4 TOF candidatepathogenic genes,and found that the signaling pathways related to the morphogenesis of an epithelium maybe involved in the pathogenesis of TOF.
基金Project supported by the Natural Science Foundation of Liaoning Province,China(Grant No.20082147)the Innovative Team Program of Liaoning Educational Committee,China(Grant No.2008T108)
文摘This paper proposes a method of realizing generalized chaos synchronization of a weighted complex network with different nodes. Chaotic systems with diverse structures are taken as the nodes of the complex dynamical network, the nonlinear terms of the systems are taken as coupling functions, and the relations among the nodes are built through weighted connections. The structure of the coupling functions between the connected nodes is obtained based on Lyapunov stability theory. A complex network with nodes of Lorenz system, Coullet system, RSssler system and the New system is taken as an example for simulation study and the results show that generalized chaos synchronization exists in the whole weighted complex network with different nodes when the coupling strength among the nodes is given with any weight value. The method can be used in realizing generalized chaos synchronization of a weighted complex network with different nodes. Furthermore, both the weight value of the coupling strength among the nodes and the number of the nodes have no effect on the stability of synchronization in the whole complex network.
基金the National Natural Science Foundation of China(No.51775272,No.51005114)The Fundamental Research Funds for the Central Universities,China(No.NS2014050)。
文摘In data-driven fault diagnosis for turbo-generator sets,the fault samples are usually expensive to obtain,and inevitably with noise,which will both lead to an unsatisfying identification performance of diagnosis models.To address these issues,this paper proposes a fault diagnosis model for turbo-generator sets based on Weighted Extension Neural Network(W-ENN).WENN is a novel neural network which has three types of connection weights and an improved correlation function.The performance of the proposed model is validated against Extension Neural Network(ENN),Support Vector Machine(SVM),Relevance Vector Machine(RVM)and Extreme Learning Machine(ELM)based models.The results indicate that,on noisy small sample sets,the proposed model is superior to the other models in terms of higher identification accuracy with fewer samples and strong noise-tolerant ability.The findings of this study may serve as a powerful fault diagnosis model for turbo-generator sets on noisy small sample sets.
基金Supported by the National Natural Science Foundation of China(No.81271019No.61463046)Gansu Province Science Foundation for Youths(No.145RJYA282)
文摘AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.
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(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supported by the National Major Project of Research and Development of China,No.2017YFA0104701(to BY)the National Natural Science Foundation of China,No.32000725(to QQC)+1 种基金the Natural Science Foundation of Jiangsu Province of China,No.BK20200973(to QQC)the Jiangsu Provincial University Innovation Training Key Project of China,No.202010304021Z(to ML)。
文摘Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.
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 the National Natural Science Foundation of China(Grant Nos.70871082 and 71301104)the Shanghai First-class Academic DisciplineProject,China(Grant No.S1201YLXK)
文摘The principle that ＇the brand effect is attractive＇ underlies the preferential attachment. Here we show that the brand effect is just one dimension of attractiveness. Another dimension is competitiveness. We firstly introduce a general frame- work that allows us to investigate the competitive aspect of real networks, instead of simply preferring popular nodes. Our model accurately describes the evolution of social and technological networks. The phenomenon that more competitive nodes become richer can help us to understand the evolution of many competitive systems in nature and society. In general, the paper provides an explicit analytical expression of degree distributions of the network. In particular, the model yields a nontrivial time evolution of nodes＇ properties and the scale-free behavior with exponents depending on the microscopic parameters characterizing the competition rules. Secondly, through theoretical analyses and numerical simulations, we reveal that our model has not only the universality for the homogeneous weighted network, but also the character for the heterogeneous weighted network. Thirdly, we also develop a model based on the profit-driven mechanism. It can better describe the observed phenomenon in enterprise cooperation networks. We show that the standard preferential attachment, the growing random graph, the initial attractiveness model, the fitness model, and weighted networks can all be seen as degenerate cases of our model.
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Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.
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.
基金Fund supported by the National Natural Science Foundation of China(81460598 and 81660644)the Natural Science Foundation of Jiangsu Province(BK20170267)Guangxi Special Fund for the First-Class Discipline Construction Project(05019038).
文摘Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughput gene expression data using weighted co-expression network analysis(WGCNA)to explore the potential therapeutic targets.Methods The dataset of GSE36980 was obtained from the Gene Expression Omnibus(GEO)database.Normalization,quality control,filtration,and soft-threshold calculation were carried out before clustering the co-expressed genes into different modules.Furthermore,the correlation coefiidents between the modules and clinical traits were computed to identify the key modules.Gene ontology and pathway enrichment analyses were performed on the key module genes.The STRING database was used to construct the protein-protein interaction(PPI)networks,which were further analyzed by Cytoscape app(MCODE).Finally,validation of hub genes was conducted by external GEO datasets of GSE 1297 and GSE 28146.Results Co-expressed genes were clustered into 27 modules,among which 6 modules were identified as the key module relating to AD occurrence.These key modules are primarily involved in chemical synaptic transmission(G0:0007268),the tricarboxylic acid(TCA)cycle and respiratory electron transport(R-HSA-1428517).WDR47,OXCT1,C3orfl4,ATP6V1A,SLC25A14,NAPB were found as the hub genes and their expression were validated by external datasets.Conclusions Through modules co-expression network analyses and PPI network analyses,we identified the hub genes of AD,including WDR47,0XCT1,C3orfl4i ATP6V1A,SLC25A14 and NAPB.Among them,three hub genes(ATP6V1A,SLC25A14,OXCT1)might contribute to AD pathogenesis through pathway of TCA cycle.
