| 1 | The heterogeneity of islet autoantibodies and the progression of islet failure in type 1 diabetic patients显示文摘Type 1 diabetes mellitus is heterogeneous in many facets. The patients suffered from type 1 diabetes present several levels of islet function as well as variable number and type of islet-specific autoantibodies. This study was to investigate prevalence and heterogeneity of the islet autoantibodies and clinical phenotypes of type 1 diabetes mellitus; and also discussed the process of islet failure and its risk factors in Chinese type 1 diabetic patients. A total of 1,291 type 1 diabetic patients were enrolled in this study. Demographic information was collected. Laboratory tests including mixed-meal tolerance test, human leukocyte antigen alleles, hemoglobin A1 c, lipids, thyroid function and islet autoantibodies were conducted. The frequency of islet-specific autoantibody in newly diagnosed T1 DM patients(duration shorter than half year) was 73% in East China. According to binary logistic regressions, autoantibody positivity, longer duration and lower Body Mass Index were the risk factors of islet failure. As the disease developed, autoantibodies against glutamic acid decarboxylase declined as well as the other two autoantibodies against zinc transporter 8 and islet antigen 2. The decrease of autoantibodies was positively correlated with aggressive beta cell destruction. Autoantibodies can facilitate the identification of classic T1 DM from other subtypes and predict the progression of islet failure. As there were obvious heterogeneity in autoantibodies and clinical manifestation in different phenotypes of the disease, we should take more factors into consideration when identifying type 1 diabetes mellitus. | Jin Liu Lingling Bian Li Ji Yang Chen Heng Chen Yong Gu Bingqin Ma Wei Gu Xinyu Xu Yun Shi Jian Wang Dalong Zhu Zilin Sun Jianhua Ma Hui Jin Xing Shi Heng Miao Bing Xin Yan Zhu Zhenwen Zhang Ruifang Bu Lan Xu Guangde Shi Wei Tang Wei Li Dongmei Zhou Jun Liang Xingbo Cheng Bimin Shi Jixiang Dong Ji Hu Chen Fang Shao Zhong Weinan Yu Weiping Lu Chenguang Wu Li Qian Jiancheng Yu Jialin Gao Xiaoqiang Fei Qingqing Zhang Xueqin Wang Shiwei Cui Jinluo Cheng Ning Xu Guofeng Wang Guoqing Han Chunrong Xu Yun Xie Minmin An Wei Zhang Zhixiao Wang Yun Cai Qi Fu Yu Fu Shuai Zheng Fan Yang Qingfang Hu Hao Dai Yu Jin Zheng Zhang Kuanfeng Xu Yifan Li Jie Shen Hongwen Zhou Wei He Xuqin Zheng Xiao Han Liping Yu Jinxiong She Mei Zhang Tao Yang | 2016 | Science China(Life Sciences)2016，59，9： | 5 |
| 4 | WheatCENet:A Database for Comparative Co-expression Network Analysis of Allohexaploid Wheat and Its Progenitors显示文摘Genetic and epigenetic changes after polyploidization events could result in variable gene expression and modified regulatory networks.Here,using large-scale transcriptome data,we constructed co-expression networks for diploid,tetraploid,and hexaploid wheat species,and built a platform for comparing co-expression networks of allohexaploid wheat and its progenitors,named WheatCENet.WheatCENet is a platform for searching and comparing specific functional coexpression networks,as well as identifying the related functions of the genes clustered therein.Functional annotations like pathways,gene families,protein-protein interactions,microRNAs(miRNAs),and several lines of epigenome data are integrated into this platform,and Gene Ontology(GO)annotation,gene set enrichment analysis(GSEA),motif identification,and other useful tools are also included.Using WheatCENet,we found that the network of WHEAT ABERRANT PANICLE ORGANIZATION I(WAPOI)has more co-expressed genes related to spike development in hexaploid wheat than its progenitors.We also found a novel motif of CCWWWWWWGG(CArG)specifically in the promoter region of WAPO-Al,suggesting that neofunctionalization of the WAPO-AI gene affects spikelet development in hexaploid wheat.WheatCENet is useful for investigating co-expression networks and conducting other analyses,and thus facilitates comparative and functional genomic studies in wheat. | Zhongqiu Li Yiheng Hu Xuelian Ma Lingling Da Jiajie She Yue Liu Xin Yi Yaxin Cao Wenying Xu Yuannian Jiao Zhen Su | 2023 | Genomics, Proteomics & Bioinformatics2023，21，2： | 0 |
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