目的应用生物信息学方法筛选出经尸体检验确诊的婴儿猝死综合征(sudden infant death syndrome,SIDS)和婴儿感染性猝死(infectious sudden death in infancy,ISDI)死者脑、心脏和肝组织中共有的差异表达mRNA,探讨SIDS与ISDI的共有分子...目的应用生物信息学方法筛选出经尸体检验确诊的婴儿猝死综合征(sudden infant death syndrome,SIDS)和婴儿感染性猝死(infectious sudden death in infancy,ISDI)死者脑、心脏和肝组织中共有的差异表达mRNA,探讨SIDS与ISDI的共有分子标记和发生机制。方法下载GSE70422、GSE136992数据集,用R软件limma包筛选SIDS和ISDI死者不同组织样本中差异表达的mRNA,进行重叠分析,并用R软件clusterProfiler包进行基因本体论(gene ontology,GO)和京都基因和基因组数据库(Kyoto Encyclopedia of Genes and Genomes,KEGG)富集分析,使用STRING数据库构建蛋白质-蛋白质相互作用(protein-protein interaction,PPI)网络,基于cytoHubba插件筛选hub基因。结果与数据集中的对照组相比,SIDS和ISDI死者组织样本中有19个显著的共同差异基因,其中心脏组织中16个、肝组织中3个,心脏组织星形肌动蛋白1(astrotactin 1,ASTN1)基因表达差异最显著。PPI网络确定了Ras同源基因家族成员A(ras homolog family member A,RHOA)、整合素亚单位α1(integrin subunit alpha 1,ITGA1)和H2B簇状组蛋白5(H2B clustered histone 5,H2BC5)是hub基因。GO和KEGG分析结果表明,共同差异基因富集在肌动蛋白细胞骨架的调节、黏着斑及对霉酚酸的反应等分子通路中。结论ASTN1、RHOA和ITGA1可能参与SIDS与ISDI的发生发展。共同差异基因富集在免疫与炎症反应相关通路中,说明SIDS与ISDI在免疫与炎症反应方面可能存在共同的分子调控机制。这些发现有望为SIDS与ISDI的分子解剖和法医学鉴定提供新的生物标记。展开更多
Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the...Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the rule set production was applied in order to assess its efficacy to obtain a better result and a more precise landslide susceptibility map in Klijanerestagh area of Iran. This study considered twelve landslide conditioning factors(LCF) like altitude, slope, aspect, plan curvature, profile curvature, topographic wetness index(TWI), distance from rivers, faults, and roads, land use/cover, and lithology. For modeling purpose, the Genetic Algorithm for the Rule Set Production(GARP) algorithm was applied in order to produce the landslide susceptibility map. Finally, to evaluate the efficacy of the GARP model, receiver operating characteristics curve as well as the Kappa index were employed. Based on these indices, the GARP model predicted the probability of future landslide incidences with the area under the receiver operating characteristics curve(AUC-ROC) values of 0.932, and 0.907 for training and validating datasets, respectively. In addition, Kappa values for the training and validating datasets were computed as 0.775, and 0.716, respectively. Thus, it can be concluded that the GARP algorithm can be a new but effective method for generating landslide susceptibility maps(LSMs). Furthermore, higher contribution of the lithology, distance from roads, and distance from faults was observed, while lower contribution was attributed to soil, profile curvature, and TWI factors. The introduced methodology in this paper can be suggested for other areas with similar topographical and hydrogeological characteristics for land use planning and reducing the landslide damages.展开更多
基金supported by Hi-Tech Research and Development Program of China (2006AA020403)National Basic Research Program of China (2009CB918801)The National Natural ScienceFoundation of China (30770498)~~
文摘目的应用生物信息学方法筛选出经尸体检验确诊的婴儿猝死综合征(sudden infant death syndrome,SIDS)和婴儿感染性猝死(infectious sudden death in infancy,ISDI)死者脑、心脏和肝组织中共有的差异表达mRNA,探讨SIDS与ISDI的共有分子标记和发生机制。方法下载GSE70422、GSE136992数据集,用R软件limma包筛选SIDS和ISDI死者不同组织样本中差异表达的mRNA,进行重叠分析,并用R软件clusterProfiler包进行基因本体论(gene ontology,GO)和京都基因和基因组数据库(Kyoto Encyclopedia of Genes and Genomes,KEGG)富集分析,使用STRING数据库构建蛋白质-蛋白质相互作用(protein-protein interaction,PPI)网络,基于cytoHubba插件筛选hub基因。结果与数据集中的对照组相比,SIDS和ISDI死者组织样本中有19个显著的共同差异基因,其中心脏组织中16个、肝组织中3个,心脏组织星形肌动蛋白1(astrotactin 1,ASTN1)基因表达差异最显著。PPI网络确定了Ras同源基因家族成员A(ras homolog family member A,RHOA)、整合素亚单位α1(integrin subunit alpha 1,ITGA1)和H2B簇状组蛋白5(H2B clustered histone 5,H2BC5)是hub基因。GO和KEGG分析结果表明,共同差异基因富集在肌动蛋白细胞骨架的调节、黏着斑及对霉酚酸的反应等分子通路中。结论ASTN1、RHOA和ITGA1可能参与SIDS与ISDI的发生发展。共同差异基因富集在免疫与炎症反应相关通路中,说明SIDS与ISDI在免疫与炎症反应方面可能存在共同的分子调控机制。这些发现有望为SIDS与ISDI的分子解剖和法医学鉴定提供新的生物标记。
基金Science and Research Branch, Islamic Azad University
文摘Investigation on landslide phenomenon is necessary for understanding and delineating the landslide prone and safer places for different land use practices. On this basis, a new model known as genetic algorithm for the rule set production was applied in order to assess its efficacy to obtain a better result and a more precise landslide susceptibility map in Klijanerestagh area of Iran. This study considered twelve landslide conditioning factors(LCF) like altitude, slope, aspect, plan curvature, profile curvature, topographic wetness index(TWI), distance from rivers, faults, and roads, land use/cover, and lithology. For modeling purpose, the Genetic Algorithm for the Rule Set Production(GARP) algorithm was applied in order to produce the landslide susceptibility map. Finally, to evaluate the efficacy of the GARP model, receiver operating characteristics curve as well as the Kappa index were employed. Based on these indices, the GARP model predicted the probability of future landslide incidences with the area under the receiver operating characteristics curve(AUC-ROC) values of 0.932, and 0.907 for training and validating datasets, respectively. In addition, Kappa values for the training and validating datasets were computed as 0.775, and 0.716, respectively. Thus, it can be concluded that the GARP algorithm can be a new but effective method for generating landslide susceptibility maps(LSMs). Furthermore, higher contribution of the lithology, distance from roads, and distance from faults was observed, while lower contribution was attributed to soil, profile curvature, and TWI factors. The introduced methodology in this paper can be suggested for other areas with similar topographical and hydrogeological characteristics for land use planning and reducing the landslide damages.
