基于HubGLasso注意力机制的脑网络分类研究

脑网络分类有助于脑疾病的早期诊断,也有益于理解脑疾病发病机理,具有重要的研究与应用价值。其中,卷积神经网络应用广泛,可以提取脑网络的拓扑特征,是脑网络分类中的一个前沿热点。然而,现有方法未考虑脑网络中Hub节点对脑功能的重要贡献,这可能会导致特征提取不充分,限制了它们的分类性能。为此,该文提出了一种基于HubGLasso注意力机制的卷积神经网络模型,用于进行脑网络分类任务。该方法包含了一种新的卷积层结构,首先利用GLasso模型去除脑网络中的冗余信息,然后引入Hub约束与注意力机制,使其能够提取与异常Hub结构相关的重要特征,并用于脑疾病诊断。实验结果表明,该方法在包含1112个被试的真实自闭症数据集上取得了68.67%的准确率,显著优于目前已有方法,证明了其应用价值。更进一步,通过对训练后的模型进行特征分析,能够得到与脑疾病相关的脑区信息与Hub节点结构信息,为脑疾病病理机制的研究提供了全新的视角。

基于加权基因共表达网络和癌症基因组图谱临床数据分析并鉴定肝细胞癌的Hub基因研究

背景 肝细胞癌(HCC)是全球常见的癌症相关死亡的第三大原因,约占所有原发性肝癌病例的90%,其复发率和死亡率较高,目前发生的分子机制仍不清楚。目的 探索HCC潜在的分子机制,发掘新的生物标志物。方法 从TCGA数据库下载RNA-seq表达数据和临床相关信息,通过差异基因表达分析正常肝脏组织与HCC组织的差异基因;对差异表达基因进行富集分析;基于TCGA中HCC的基因表达数据概况,使用WGCNA R包建立共表达网络,进行加权基因共表达网络分析(WGCNA),选择具有临床意义的模块,并筛选候选Hub基因;进一步分析候选Hub基因在HCC组织和正常肝脏组织显著差异表达、与HCC患者总体生存期和无病生存期是否显著相关,最终确定Hub基因;通过人类蛋白质图谱数据库对Hub基因蛋白表达进行验证。结果 本研究的基因表达数据来自50个正常肝脏组织样本和373个HCC组织样本。通过差异基因表达分析发现7 230个在HCC和正常肝脏组织之间差异表达的基因(HCC中3 691个上调基因和3 539个下调基因)。富集分析表明,上调的差异表达基因主要参与细胞周期调控和有丝分裂过程;下调的差异表达基因主要参与小分子代谢和有机酸代谢等过程。WGCNA确定了19个与HCC患者临床特征相关基因模块,通过分析模块与临床特征之间的关系,筛选出青色模块和紫色模块。青色模块基因中同时与患者总生存期和无病生存期强烈相关的前两个基因为VPS45和FAM189B;紫色模块基因中同时与患者总生存期和无病生存期强烈相关的前两个基因分别为CLEC1B和FCN3,因此将VPS45、FAM189B、CLEC1B和FCN3确定为最终的Hub基因。人类蛋白质图谱数据库免疫组织化学染色显示:VPS45和FAM189B在HCC组织中的表达高于正常肝脏组织,FCN3在HCC组织中的表达低于正常肝脏组织,CLEC1B在HCC组织和正常肝脏组织中表达差异不明显。结论 初步确定VPS45、FAM189B、CLEC1B和FCN3可能是HCC的新型潜在生物标志物,这些Hub基因可能为HCC的靶向治疗提供理论基础。

Identification of hub genes associated with Helicobacter pylori infection and type 2 diabetes mellitus:A pilot bioinformatics study

BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.

Functional investigation and two-sample Mendelian randomization study of primary biliary cholangitis hub genes

BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic evaluation.AIM To determine PBC-associated hub genes and assess their clinical utility for disease prediction.METHODS PBC expression data were obtained from the Gene Expression Omnibus database.Overlapping genes from differential expression analysis and weighted gene coexpression network analysis(WGCNA)were identified as key genes for PBC.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes.Hub genes were identified in protein-protein interaction(PPI)networks using the Degree algorithm in Cytoscape software.The relationship between hub genes and immune cells was investigated.Finally,a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.RESULTS We identified 71 overlapping key genes using differential expression analysis and WGCNA.These genes were primarily enriched in pathways related to cytokinecytokine receptor interaction,and Th1,Th2,and Th17 cell differentiation.We utilized Cytoscape software and identified five hub genes(CD247,IL10,CCL5,CCL3,and STAT3)in PPI networks.These hub genes showed a strong correlation with immune cell infiltration in PBC.However,inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.CONCLUSION Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment,thereby offering significant clinical utility.

应用生物信息学筛选结直肠癌Hub基因及验证

目的通过运用生物信息学分析,筛选出与结直肠癌相关的差异表达基因(Differentially Expressed genes,DEGs),并验证其生物学功能。方法云浮市人民医院检验科从基因表达综合数据库(Gene Expression Omnibus,GEO)中下载结直肠癌芯片数据GSE 21815、GSE 31905、GSE 35279资料,应用GEO2R语言进行处理得出结直肠癌和正常结直肠组织之间的差异表达基因,并通过生物信息学工具DAVID、STRING、Cytoscape构建差异表达基因的蛋白互作网络,筛选Hub基因,应用基因本体论(Gene Ontology,GO)、基因百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)分析筛选出的Hub基因的生物功能,并利用MiRDB工具找出可能调控Hub基因的miRNA,并于2017—2022年8月收集30例结直肠癌组织和30例正常结直肠组织样本,通过实时荧光定量PCR(Quantitative Real-time PCR,qPCR)验证。结果经生物学信息分析和蛋白质相互作用网络图分析催产素受体基因、基质金属蛋白酶11基因、间质上皮转化因子基因、基质金属蛋白酶7基因、激肽释放酶8基因、激肽释放酶10基因为结直肠癌组织发生发展的关键Hub基因。结直肠癌组织中基质金属蛋白酶11基因(4.38±1.58)、间质上皮转化因子基因(2.69±0.29)、基质金属蛋白酶7基因(0.88±0.14)、激肽释放酶8基因(11.09±3.90)、激肽释放酶10基因mRNA(7.88±2.20)的表达,显著高于正常结直肠组织组织,差异有统计学意义(t=9.605、25.339、26.376、9.541、3.726,P均<0.001)。结论结直肠癌组织中基质金属蛋白酶11基因、间质上皮转化因子基因、基质金属蛋白酶7基因、激肽释放酶8基因、激肽释放酶10基因异常表达,可能参与结直肠癌发生过程,有望为后续结直肠癌基础研究及临床诊疗提供依据。

A Study on Integrated Construction of Luzhou Comprehensive Transportation Hub

The target of integrated construction of comprehensive transportation hub is to integrate the traffic resources,achieve butt joint of pan-regional transportation mode,and finally realize the"seamless connection"of the goods and"zero transfer"of the passenger traffic.Relying on the particularity of the geographical location and the convenience of the Yangtze River channel,Luzhou puts forth effort to build a comprehensive transport hub in Southern Sichuan and has made great efforts in traffic infrastructure construction.However,there are still some problems.Combining practice of Luzhou,using the advanced experience of foreign and domestic cities for reference,the paper pointed out that for the sake of constructing a comprehensive transportation hub,we need to build the traffic integration on the basis of the efficiency.Besides,the paper proposed the strategies for construction.

Analysis of Roadbed Splicing at Hub Interchanges

This article discusses the roadbed splicing for hub interchanges.The article starts with a description of the characteristics of junction roadbed splicing.The application of splicing technology is explained using a subgrade splicing scheme of a project.Roadbed splicing involves stepwise excavation and preparative measures like surface cleaning and backfilling.This article serves to provide a valuable reference for road and bridge construction and improve the quality of China’s road and bridge projects,so as to achieve sustainable development of the road and bridge engineering industry.

Mind+结合XEduHub开发AI交互作品

在图形化编程工具Mind+和通用AI推理库XEdu Hub的支持下,中小学生使用简短的代码就能设计出有趣的AI交互作品。本文在介绍Mind+和XEdu Hub的同时,分析了AI交互作品的核心环节,指出作品可以由感知输入、智能处理和执行呈现三个部分组成,希望为中小学开展AI教育提供新的思路。

TVU推出媒体信号路由新品MediaHub云调度

近期,TVU推出重磅新品——TVU MediaHub云调度。这一产品采用混合云构架的分布式处理技术,实现了任意地点、任意格式的媒体信号以多种格式传输到多个目的地。TVU MediaHub通过其全能的转换与调度功能,可以实现物理硬件与云端资源的集结,为用户提供一个能够灵活转换和高效调度全格式信号的平台。它采用基于先进微服务技术的架构,构建了一个灵活可靠的媒体信号调度中心,确保与TVU各类终端和系统的无缝集成,实现了输入输出的高效管理。此外,TVU MediaHub还与TVU云导播、云播出等服务实现无缝连接。它还引入了灵活的计费系统,根据用户的实际需求进行计费,从而优化成本。操作方面,TVU MediaHub通过其WebUI界面提供简化的操作流程,用户可以实时预览并通过拖拽信号来完成调度,极大地简化了操作步骤,提高了工作效率。

无人车载网络高可靠HUB的设计

为满足无人车技术的不断发展及日趋复杂的车载网络带来的高带宽和高可靠性的使用要求,设计一种车载网络集线器(HUB)。采用时间触发协议(TTP),设计时间触发以太网(TTE)加星型TTP总线的架构。TTE提高数据带宽,在物理层与驱动设备采用点对点的连接方式代替总线型通信方式,提高可靠性,解决总线型通信方式一点断开,整体通信失效的问题。针对HUB的设计做详细阐述,通过实验验证了设计的可行性和可靠性,对车载网络的优化提供了可行的解决途径。

基于网络嵌入的癌症性状hub基因发现

研究影响癌症性状的hub基因时存在如下问题:仅关注强相关性基因进行基因信息处理,缺少对弱相关性基因和不同基因模块间共表达性的研究;仅采用度中心性判断hub基因进行分析基因网络,对蕴含数据挖掘不够全面.本文提出基因模块标签信息游走的图嵌入算法Gene2vec.选取合适软阈值,保留更多弱相关性的基因信息.联合不同种类但与性状高度正相关性的基因模块,构成基因模块共表达网络.针对传统加权基因共表达网络分析方法与图嵌入方法挖掘基因模块网络信息存在的问题,利用标签参数与其他参数调节基因模块网络中的随机游走过程,分析游走生成的节点序列以挖掘基因网络的信息.实验表明,Gene2vec在hub基因的检出率上优于其他算法,得到的hub基因在癌症性状中的基因表达量高于常用生物学方法得到的hub基因.

用生物信息学方法分析鉴定肺腺癌中的hub基因

从高通量基因表达数据库(Gene Expression Omnibus,GEO)中获得基因表达谱序列号,并使用R中的“limma”包对差异表达基因(Differentially Expressed Genes,DEGs)进行鉴定。为确定差异基因所涉及的生物学过程及信号通路,进行了基因本体论(Gene Ontology,GO)富集分析和基因组的京都百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)富集分析,研究发现DEGs主要与细胞外基质组织、细胞外结构组织和有丝分裂的细胞核分裂有关,其主要富集在补体和凝血级联、细胞外基质受体相互作用和黏着作用的通路上。采用蛋白质-蛋白质互作(Protein-Protein Interaction,PPI)网络分析得到了由716个DEGs网络节点和3759条边构成的PPI网络,并在其中初步筛选出20个hub基因。通过加权基因共表达网络分析(Weighted Gene Co-expression Network Analysis,WGCNA)从DEGs中得到了18个模块,对hub基因进行鉴定,筛选出17个hub基因。使用Oncomine数据库对hub基因在肺腺癌患者与正常人的表达情况进行Meta分析,共鉴定出16个hub基因与肺腺癌相关。对肺腺癌患者进行总体生存分析,发现hub基因高表达患者总生存期比低表达患者短。

电-气-氢-热-风-光耦合综合能源系统分层级Energy Hub建模方法

随着多能融合的不断深入,综合能源系统可实现大规模可再生能源消纳。由于综合能源系统广泛涉及电、气、氢、热、风、光等多种能源形式,经典Energy Hub方法与图论Energy Hub方法在建模效率与复杂度等方面均存在局限性。文章提出了分层级Energy Hub建模方法,将综合能源系统从能量输入到输出的耦合过程建模为分配层、转换层、集成层、储能层、网络层5个环节,全面涵盖了综合能源系统复杂多元的多能耦合关系,为输入与输出搭建桥梁,确保能量供需平衡。最后,通过算例分析论证了所提方法的优势与可行性,以及与传统方法在可再生能源消纳量上的提升。

Wake Effects on A Hybrid Semi-Submersible Floating Wind Farm with Multiple Hub Heights

Wind farms generally consist of a single turbine installed with the same hub height. As the scale of turbines increases,wake interference between turbines becomes increasingly significant, especially for floating wind turbines(FWT).Some researchers find that wind farms with multiple hub heights could increase the annual energy production(AEP),while previous studies also indicate that wake meandering could increase fatigue loading. This study investigates the wake interaction within a hybrid floating wind farm with multiple hub heights. In this study, FAST.Farm is employed to simulate a hybrid wind farm which consists of four semi-submersible FWTs(5MW and 15MW) with two different hub heights. Three typical wind speeds(below-rated, rated, and over-rated) are considered in this paper to investigate the wake meandering effects on the dynamics of two FWTs. Damage equivalent loads(DEL) of the turbine critical components are computed and analyzed for several arrangements determined by the different spacing of the four turbines. The result shows that the dynamic wake meandering significantly affects downstream turbines’ global loadings and load effects. Differences in DEL show that blade-root flapwise bending moments and mooring fairlead tensions are sensitive to the spacing of the turbines.

Identification of hub genes for glaucoma:a study based on bioinformatics analysis and experimental verification

AIM:To explore hub genes for glaucoma based on bioinformatics analysis and an experimental model verification.METHODS:In the Gene Expression Omnibus(GEO)database,the GSE25812 and GSE26299 datasets were selected to analyze differentially expressed genes(DEGs)by the GEO2R tool.Through bioinformatics analysis,9 hub genes were identified.Receiver operating characteristic(ROC)curves and principal component analysis(PCA)were performed to verify whether the hub gene can distinguish glaucoma from normal eyes.The mouse model of glaucoma was constructed,and the real-time reverse transcriptasepolymerase chain reaction(RT-q PCR)assay was performed to detect the expression levels of hub genes in glaucoma.RESULTS:There were 128 overlapping DEGs in the GSE25812 and GSE26299 datasets,mainly involved in intracellular signalling,cell adhesion molecules and the Ras signalling pathway.A total of 9 hub genes were screened out,including GNAL,BGN,ETS2,FCGP4,MAPK10,MMP15,STAT1,TSPAN8,and VCAM1.The area under the curve(AUC)values of 9 hub genes were greater than 0.8.The PC1 axle could provide a 70.5%interpretation rate to distinguish glaucoma from normal eyes.In the ocular tissues of glaucoma in the mice model,the expression of BGN,ETS2,FCGR4,STAT1,TSPAN8,and VCAM1 was increased,while the expression of GNAL,MAPK10,and MMP15 was decreased.CONCLUSION:Nine hub genes in glaucoma are identified,which may provide new biomarkers and therapeutic targets for glaucoma.

基于生物信息学分析林奇综合征相关结直肠癌关键Hub基因的筛选与功能富集分析

通过生物信息学方法筛选出与林奇综合征相关结直肠癌(colorectal cance,CRC)组织中的差异表达基因(differentially expressed genes,DEGs)。从基因表达总库(gene expression omnibus,GEO)下载林奇综合征相关CRC数据集GSE178516,使用GEO2R筛选DEGs,并在人类疾病数据库Malacards中获取CRC和林奇综合征疾病基因,3者的交集取为关键Hub基因,通过功能富集分析鉴定DEGs。利用String数据库构建蛋白质-蛋白质相互作用网络(protein-protein interaction,PPI),并使用Cytoscape软件对PPI网络进行可视化和模块分析。随后在easyGEO数据库中对差异表达基因进行表达验证。从GSE178516共鉴定出261个差异基因,包括117个上调基因和114个下调基因。这些基因与CRC和林奇综合征基因共交集出8个差异表达基因(TGFBR2、PTEN、POLD1、EXO1、EPCAM、CDKN2B、CCND1、BRCA1)。GO、KEGG富集分析显示,其功能主要富集在DNA代谢过程调控、内在凋亡信号通路、错配修复等方面;KEGG通路分析主要富集在CRC等相关癌症路径。通过PPI获得与67个差异表达蛋白存在相互作用关系的892个蛋白,并利用Cytoscape软件构建其重要模块,包含44个节点和630个节点作用关系。利用easyGEO网站对8个差异基因进行表达分析,发现8个基因在林奇综合征相关CRC患者中的表达均具有统计学差异。总体上,研究鉴定出的关键Hub基因有助于了解林奇综合征相关CRC发生和发展的分子机制,并为林奇综合征进展对CRC的诊断和治疗提供新的候选靶点。

基于生物信息学对骨关节炎Hub基因的筛选与验证

背景:骨关节炎是以关节疼痛、僵硬、肿胀为主要临床表现的一种退行性疾病,目前关于骨关节炎的发病机制尚不明确。目的:基于生物信息学筛选骨关节炎相关数据集的Hub基因,再用细胞实验加以验证,筛选骨关节炎的关键生物标志物。方法:从GEO数据库搜索骨关节炎相关的数据集,通过GEO2R分析筛选差异表达基因,对差异表达基因进行GO、KEGG富集分析,同时对数据集所有基因进行GESA分析,使用String网站构建差异表达基因的PPI网络,利用Cytoscape软件中的MCODE插件对PPI网络进行功能模块分析,使用插件CytoHubba筛选评分最高的10个Hub基因。提取SD大鼠膝关节半月板细胞,实验组以白细胞介素1β(10 ng/mL)干预细胞24 h复制骨关节炎症模型,以未干预组为对照,采用RT-qPCR法检测Hub基因的表达。结果与结论:(1)筛选出的差异表达基因中上调基因147个、下调基因212个,GO、KEGG和GSEA分析结果显示,富集的通路及生物过程主要涉及胶原纤维组织、细胞外基质的相互作用、Th17细胞分化和白细胞介素17等;利用Cytoscape软件中的插件CytoHubba筛选MCC算法中评分最高的10个Hub基因,分别是COL1A1、COL3A1、COL5A1、COL5A2、COL6A3、LOX、LOXL1、LOXL2、POSTN、PLOD1;(2)RT-qPCR检测结果显示,与对照组相比,实验组COL1A1、COL3A1、COL5A1、COL5A2、COL6A3、LOXL1、LOXL2的mRNA表达降低(P<0.0001),LOX和POSTN的mRNA表达升高(P<0.0001),两组PLOD1的mRNA表达无明显差异(P>0.05);(3)结果显示,骨关节炎的Hub基因表达差异可能为日后了解骨关节炎的发展提供新见解。

Analysis of functional hub genes indicates DLGAP5 is linked to lung adenocarcinoma prognosis

Introduction:The difficulty in treating lung adenocarcinoma(LUAD)is caused by a shortage of knowledge about the biological mechanisms and a lack of treatment choices.Objectives:The aim of this study was to identify a valuable molecular target for the treatment of LUAD.Methods:Using multiple databases,we screened for hub genes in LUAD using Cytoscape and explored the expression and prognosis of DLG associated protein 5(DLGAP5)in LUAD.We investigated the genetic variation,functional enrichment,and epigenetic activity of DLGAP5.Furthermore,we evaluated the relationship between the tumor microenvironment(TME)and DLGAP5.Results:Our study identified 10 hub genes in LUAD:CDC45,KIAA0101,DLGAP5,CDT1,NCAPG,CCNB1,CDCA5,CDC20,KIF11,and AURKA.We discovered that DLGAP5 was overexpressed and associated with poor prognosis in LUAD.DLGAP5 exhibited an overall genetic variation frequency of 2%,and its DNA promoter was hypomethylated in LUAD(p<0.05).The expression of DLGAP5 in LUAD showed a positive correlation with the majority of N6-methyladenosine(m6A)-methylation genes.Additionally,DLGAP5 was primarily associated with the cell cycle in LUAD.Notably,there was a significant favorable association between DLGAP5 and CD274,CTLA4,HAVCR2,and LAG3 in LUAD.Conclusion:DLGAP5 may be a therapeutic target for LUAD,as it affects cancer cells proliferation and development through the regulation of cell-cycle checkpoints and modulation of immune cell infiltration and immune checkpoints in the TME.

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried out.This has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the day-aheadmarket.The standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique.The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub limitations.Additionally,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

基于生物信息学分析肝癌Hub基因与差异基因的筛选与鉴定以及相关基因的突变序列

旨在基于生物信息学分析肝癌Hub基因与差异基因的筛选与鉴定,并进行相关基因的突变序列分析。方法:我们首先获取了与肝癌相关的基因表达数据和临床数据,并对其进行了质控和预处理。接着,利用网络分析方法构建肝癌基因网络,并识别了网络中的Hub基因,这些基因在网络中具有重要的连接和调控作用。通过统计学方法和假设检验校正方法确定了差异显著的基因。结果:本研究成功筛选出了肝癌中的Hub基因和差异基因,并对其进行了功能注释和通路分析。通过综合分析差异基因、Hub基因和突变事件的结果,我们发现了与肝癌发生发展密切相关的关键基因和通路。结论:本研究通过生物信息学分析揭示了肝癌的关键基因和突变事件。这些发现为深入理解肝癌的发病机制和发展过程提供了重要线索。