šŸ‘¤ Y H Guo

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804
Articles
572
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Also published as: Aiyuan Guo, Alex Guo, An-Yuan Guo, AoHan Guo, Ava Jiangyang Guo, Baihai Guo, Baosheng Guo, Baozhu Guo, Bei Guo, Beibei Guo, Bianqin Guo, Bin Guo, Binbin Guo, Bing-Yan Guo, Bingnan Guo, Bingpeng Guo, Bo Guo, Caixia Guo, Chang Guo, Changfa Guo, Changjiang Guo, Changkui Guo, Changyuan Guo, Chao Guo, Chen Guo, Cheng Guo, Chengcheng Guo, Chenghang Guo, Chenglin Guo, Chengnan Guo, Chengxian Guo, Chengyao Guo, Chenkai Guo, Chenxu Guo, Christina Guo, Chu Guo, Chuang Guo, Chuanyu Guo, Chuanzhi Guo, Chun Guo, Chun-Hua Guo, Chunhe Guo, Chunjie Guo, Chunyuan Guo, Cong Guo, Cui Guo, Cuiping Guo, Cunlan Guo, Dachuan Guo, Dan Guo, Daoxia Guo, Daqiao Guo, Dazhi Guo, Deng F Guo, Deng Fu Guo, Deng-Fu Guo, Detong Guo, Diana E Guo, Dong Guo, Dong-Yu Guo, Dong-ping Guo, DongMing Guo, Dongchuan Guo, Donghao Guo, Donghui Guo, Dongjie Guo, Dongping Guo, Fang Guo, Fang-Fang Guo, Fang-hong Guo, Fangfang Guo, Fangliang Guo, Fangling Guo, Fanli Guo, Feng Guo, Fenghua Guo, Fengjin Guo, Fengqin Guo, Fengyun Guo, Fujia Guo, Gao Guo, Ge Guo, Gengyin Guo, Grace L Guo, Guanghao Guo, Guangqiong Guo, Guangran Guo, Guangwu Guo, Guijie Guo, Guilong Guo, Guiya Guo, Guiyuan Guo, Guoji Guo, H D Guo, Hai-Hui Guo, Hai-Lei Guo, Hai-Long Guo, Haidan Guo, Haihong Guo, Hailong Guo, Haiyan Guo, Hang Guo, Hanrui Guo, Hao Guo, Haoliang Guo, Haonan Guo, Haoran Guo, Haoyao Guo, Hejiang Guo, Heng Guo, Hengru Guo, Hong Guo, Hong-Li Guo, Hongbo Guo, Honghui Guo, Hongjuan Guo, Honglin Guo, Hongqian Guo, Hongquan Guo, Hongrui Guo, Hongyan Guo, Hongyu Guo, Hu Guo, Hua Guo, Hua-Qi Guo, Huan Guo, Huaqi Guo, Huaxin Guo, Hui Guo, Huicai Guo, Huichen Guo, Huiduo Guo, Huifang Guo, Huilan Guo, J Guo, Ji-Feng Guo, Jia Guo, Jia-Ni Guo, Jiabao Guo, Jiahao Guo, Jiahe Guo, Jiahong Guo, Jiajun Guo, Jiali Guo, Jialu Guo, Jian Guo, Jianbin Guo, Jianfeng Guo, Jianhong Guo, Jianhui Guo, Jianlin Guo, Jianming Guo, Jianping Guo, Jianqiang Guo, Jianrong Guo, Jianwen Guo, Jianxing Guo, Jiao Guo, Jiaona Guo, Jiaqi Guo, Jiarui Guo, Jiasong Guo, Jiayu Guo, Jiazhong Guo, Jiazhuo Guo, Jichang Guo, Jie Guo, Jifeng Guo, Jin Guo, Jinbai Guo, Jing Guo, Jing-Feng Guo, Jingbin Guo, Jingjing Guo, Jingxu Guo, Jingxuan Guo, Jingyi Guo, Jinhao Guo, Jinjun Guo, Jinlei Guo, Jinming Guo, Jinshuo Guo, Jinxuan Guo, Jinyan Guo, Jinzhen Guo, Jiurui Guo, Jiwei Guo, Jizhen Guo, Joan Guo, Joanna Guo, Jonathan Guo, Ju Guo, Juan Guo, Jun Guo, Jun-Jie Guo, Jun-Rong Guo, Junfei Guo, Junhong Guo, Junjie Guo, Junming Guo, Junpeng Guo, Junqiao Guo, Junweichen Guo, Junyi Guo, Kai Guo, Kaifeng Guo, Kailei Guo, Kailu Guo, Kaixuan Guo, Kaiyu Guo, Kangkang Guo, Katherine Guo, Keji Guo, Kevin Guo, Kexin Guo, Keying Guo, Kun Guo, Kun-yuan Guo, L Guo, Lan Guo, Lan-Fang Guo, Landys Z Guo, Lanfang Guo, Lanping Guo, Lei Guo, Li Guo, Li-Jie Guo, Li-Ying Guo, Li-Zhe Guo, Liang Guo, Liang-Hong Guo, Lianrui Guo, Lianxia Guo, Lichen Guo, Lihe Guo, Lijuan Guo, Lijun Guo, Lin Guo, Linfeng Guo, Ling Guo, Ling-Li Guo, Lingyi Guo, Lining Guo, Liping Guo, Lishuang Guo, Liuliu Guo, Liuxiong Guo, Lixin Guo, Liyi Guo, Lizhong Guo, Longchao Guo, Longhua Guo, Longyu Guo, Lu Guo, Man Guo, Manman Guo, Mei Guo, Meng Guo, Meng-Yao Guo, Mengdi Guo, Menghan Guo, Mengmeng Guo, Mengqin Guo, Mengran Guo, Mengru Guo, Mengyu Guo, Miaomiao Guo, Min Guo, Minfang Guo, Ming Guo, Mingwei Guo, Mingxuan Guo, Mingzhou Guo, Minkang Guo, Mixue Guo, N Guo, Na Guo, Nan Guo, Nana Guo, Ni Guo, Ning Guo, Ninghong Guo, Ningning Guo, Peilan Guo, Peipei Guo, Peiran Guo, Peng Guo, Pengchao Guo, Pengrong Guo, Pengwang Guo, Pengyu Guo, Ping Guo, Qi Guo, Qi Wei Guo, Qian Guo, Qiang Guo, Qianjin Guo, Qianqian Guo, Qianxue Guo, Qianyu Guo, Qin Guo, Qing Guo, Qingjun Guo, Qiufen Guo, Qiusha Guo, Qiuxiao Guo, Qiuyu Guo, Qunfeng Guo, R Guo, R J Guo, Ren Guo, Rong Guo, Rongjun Guo, Rui Guo, Ruijuan Guo, Ruixian Guo, Ruixue Guo, Runlin Guo, Ruoling Guo, Ruoyi Guo, S Guo, Sen Guo, Shanchun Guo, Sheng Guo, Shiping Guo, Shiqi Guo, Shixiang Guo, Shiyu Guo, Shou-Dong Guo, Shou-Gang Guo, Shoudong Guo, Shougang Guo, Shu-Li Guo, Shu-Liang Guo, Shuai Guo, Shuaijun Guo, Shuang Guo, Shubin Guo, Shufei Guo, Shujie Guo, Shun Guo, Shunyuan Guo, Shupan Guo, Shuren Guo, Shushu Guo, Shuxia Guo, Siqing Guo, Sixian Guo, Siyu Guo, Song-Chang Guo, Sufen Guo, Suping Guo, Suxiang Guo, Tao Guo, Tengfei Guo, Theresa Guo, Tianyi Guo, Tianyu Guo, Ting Guo, Tingting Guo, Tingwei Guo, Tingxi Guo, Tong Guo, W X Guo, Wanjun Guo, Wanrong Guo, Wei Guo, Wei-Xing Guo, Weichun Guo, Weidong Guo, Weihong Guo, Weihua Guo, Weijie Guo, Weiqiang Guo, Weisheng Guo, Weiwei Guo, Weiying Guo, Wen Guo, Wen-Wen Guo, Wenhuang Guo, Wenhui Guo, Wenjie Guo, Wenjing Guo, Wenjuan Guo, Wenting Guo, Wenwen Guo, Wenxing Guo, Wenxuan Guo, Wubin Guo, X Guo, Xi-Rong Guo, Xi-Xi Guo, Xia Guo, Xiajun Guo, Xian Guo, Xianfei Guo, Xiang Guo, Xianghao Guo, Xiangjiang Guo, Xiangqian Guo, Xianzhi Guo, Xiao Guo, Xiao Quan Guo, Xiao-Nan Guo, Xiao-Xi Guo, Xiao-Yu Guo, Xiao-yan Guo, XiaoYan Guo, Xiaobin Guo, Xiaochen Guo, Xiaodi Guo, Xiaofan Guo, Xiaofei Guo, Xiaoge Guo, Xiaohong Guo, Xiaohua Guo, Xiaohui Guo, Xiaojun Guo, Xiaolan Guo, Xiaoliang Guo, Xiaolin Guo, Xiaoling Guo, Xiaonan Guo, Xiaoping Guo, Xiaoqiang Guo, Xiaoquan Guo, Xiaoxian Guo, Xiaoye Guo, Xiaoying Guo, Xiaoyu Guo, Xiaozhong Guo, Xieli Guo, Xin Guo, Xing Guo, Xingjun Guo, Xingmei Guo, Xingyi Guo, Xingyou Guo, Xinli Guo, Xinru Guo, Xinyi Guo, Xinyin Guo, Xiong Guo, Xirong Guo, Xiuqing Guo, Xiying Guo, Xizhi Guo, Xu Guo, Xudong Guo, Xue-Ling Guo, Xuejiang Guo, Xuewu Guo, Xuyang Guo, Y J Guo, Y S Guo, Y-M Guo, Ya-Dong Guo, Ya-Gang Guo, Yajie Guo, Yamin Guo, Yan Guo, Yan-Xia Guo, Yane Guo, Yang Guo, Yangbo Guo, Yangdong Guo, Yangfan Guo, Yanhong Guo, Yanhua Guo, Yanjie Guo, Yanjun Guo, Yanlei Guo, Yanli Guo, Yannan Guo, Yanwei Guo, Yanzhi Guo, Yaping Guo, Yarong Guo, Yaru Guo, Yatu Guo, Yaxin Guo, Yazhou Guo, Yelei Guo, Yi Guo, Yi-Cheng Guo, Yi-Jing Guo, Yi-Ran Guo, Yifan Guo, Yifang Guo, Yifei Guo, Yilei Guo, Yimo Guo, Ying Guo, Ying'ao Guo, Ying-Yuan Guo, Yingying Guo, Yishan Guo, Yong Guo, Yong-Chen Guo, Yongjun Guo, Yongmei Guo, Yongqing Guo, Yongzhen Guo, Yongzheng Guo, Youming Guo, Yu Guo, Yu-Jie Guo, Yu-Li Guo, Yuan Guo, Yuan-Lin Guo, Yuanbiao Guo, Yuanfang Guo, Yuanlin Guo, Yue Guo, Yuetong Guo, Yujia Guo, Yujie Guo, Yulong Guo, Yumeng Guo, Yuming Guo, Yunliang Guo, Yunxia Guo, Yunxuan Guo, Yunxue Guo, Yunyun Guo, Yuqi Guo, Yuquan Guo, Yushan Guo, Yutong Guo, Yuwen Guo, Yuxian Guo, Zeao Guo, Zexi Guo, Zeyi Guo, Zhaohui Guo, Zhaojuan Guo, Zhen Guo, Zhen-Ya Guo, Zheng-Chen Guo, Zhengguang Guo, Zhengwang Guo, Zhengyan Guo, Zhengzhang Guo, Zhenli Guo, Zhenming Guo, Zhenye Guo, Zhenzhen Guo, Zhi-Gang Guo, Zhibo Guo, Zhijian Guo, Zhilei Guo, Zhimin Guo, Zhiru Guo, Zhiting Guo, Zhizhao Guo, Zhongbao Guo, Zhongqiang Guo, Zhongwei Guo, Zhongyuan Guo, Zhou Guo, Zhouli Guo, Zhu-Ling Guo, Ziang Guo, Zifang Guo, Zihan Guo, Ziming Guo, Zipei Guo, Zisheng Guo, Ziwei Guo, Ziwen Guo, Zufeng Guo
articles
Miao Li, Meng Pan, Chengzhong You +7 more Ā· 2020 Ā· Breast cancer research : BCR Ā· BioMed Central Ā· added 2026-04-24
Breast cancer stem cells (BCSCs) are typically seed cells of breast tumor that initiate and maintain tumor growth. MiR-7, as a cancer inhibitor, decreases the BCSC subset and inhibits tumor progressio Show more
Breast cancer stem cells (BCSCs) are typically seed cells of breast tumor that initiate and maintain tumor growth. MiR-7, as a cancer inhibitor, decreases the BCSC subset and inhibits tumor progression through mechanisms that remain unknown. We examined miR-7 expression in breast cancer and developed a BCSC-driven xenograft mouse model, to evaluate the effects of miR-7 overexpression on the decrease of the BCSC subset in vitro and in vivo. In addition, we determined how miR-7 decreased the BCSC subset by using the ALDEFLUOR, lentivirus infection, dual-luciferase reporter, and chromatin immunoprecipitation-PCR assays. MiR-7 was expressed at low levels in breast cancer tissues compared with normal tissues, and overexpression of miR-7 directly inhibited lncRNA XIST, which mediates the transcriptional silencing of genes on the X chromosome, and reduced epithelium-specific antigen (ESA) expression by increasing miR-92b and inhibiting slug. Moreover, miR-7 suppressed CD44 and ESA by directly inhibiting the NF-ĪŗB subunit RELA and slug in breast cancer cell lines and in BCSC-driven xenografts, which confirmed the antitumor activity in mice injected with miR-7 agomir or stably infected with lenti-miR-7. The findings from this study uncover the molecular mechanisms by which miR-7 inhibits XIST, modulates the miR-92b/Slug/ESA axis, and decreases the RELA and CD44 expression, resulting in a reduced BCSC subset and breast cancer growth inhibition. These findings suggest a potentially targeted treatment approach to breast cancer. Show less
no PDF DOI: 10.1186/s13058-020-01264-z
SNAI1
Pengzhou Kong, Enwei Xu, Yanghui Bi +17 more Ā· 2020 Ā· Theranostics Ā· added 2026-04-24
no PDF DOI: 10.7150/thno.38210
SNAI1
Dan Jin, Jiwei Guo, Yan Wu +9 more Ā· 2020 Ā· Journal of experimental & clinical cancer research : CR Ā· BioMed Central Ā· added 2026-04-24
Recent evidence indicates that metformin inhibits mammalian cancer growth and metastasis through the regulation of microRNAs. Metformin regulates miR-381 stability, which plays a vital role in tumor p Show more
Recent evidence indicates that metformin inhibits mammalian cancer growth and metastasis through the regulation of microRNAs. Metformin regulates miR-381 stability, which plays a vital role in tumor progression. Moreover, increased YAP expression and activity induce non-small cell lung cancer (NSCLC) tumor growth and metastasis. However, the molecular mechanism underpinning how metformin-induced upregulation of miR-381 directly targets YAP or its interactions with the epithelial-mesenchymal transition (EMT) marker protein Snail in NSCLC is still unknown. Levels of RNA and protein were analyzed using qPCR, western blotting and immunofluorescence staining. Cellular proliferation was detected using a CCK8 assay. Cell migration and invasion were analyzed using wound healing and transwell assays. Promoter activity and transcription were investigated using the luciferase reporter assay. Chromatin immunoprecipitation was used to detect the binding of YAP to the promoter of Snail. The interaction between miR-381 and the 3'UTR of YAP mRNA was analyzed using the MS2 expression system and co-immunoprecipitation with biotin. We observed that miR-381 expression is negatively correlated with YAP expression and plays an opposite role to YAP in the regulation of cellular proliferation, invasion, migration, and EMT of NSCLC cells. The miR-381 function as a tumor suppressor was significantly downregulated in lung cancer tissue specimens and cell lines, which decreased the expression of its direct target YAP. In addition, metformin decreased cell growth, migration, invasion, and EMT via up-regulation of miR-381. Moreover, YAP, which functions as a co-transcription factor, enhanced NSCLC progression and metastasis by upregulation of Snail. Snail knockdown downregulated the mesenchymal marker vimentin and upregulated the epithelial marker E-cadherin in lung cancer cells. Furthermore, miR-381, YAP, and Snail constitute the miR-381-YAP-Snail signal axis, which is repressed by metformin, and enhances cancer cell invasiveness by directly regulating EMT. Metformin-induced repression of miR-381-YAP-Snail axis activity disrupts NSCLC growth and metastasis. Thus, we believe that the miR-381-YAP-Snail signal axis may be a suitable diagnostic marker and a potential therapeutic target for lung cancer. Show less
no PDF DOI: 10.1186/s13046-019-1503-6
SNAI1
Dongmei Wang, Xinghua Cheng, Yu Li +12 more Ā· 2020 Ā· Oncogene Ā· Nature Ā· added 2026-04-24
Cancer cells undergo significant lipid metabolic reprogramming to ensure sufficient energy supply for survival and progression. However, how cancer cells integrate lipid metabolic signaling with cance Show more
Cancer cells undergo significant lipid metabolic reprogramming to ensure sufficient energy supply for survival and progression. However, how cancer cells integrate lipid metabolic signaling with cancer progression is not well understood. In the present study, we demonstrated that C/EBPΓ, a critical lipid metabolic regulator, is a TGF-β1 downstream gene and promotes lung adenocarcinoma metastasis. Importantly, C/EBPΓ caused significant oscillations in both lipid metabolic and epithelial to mesenchymal transition (EMT) gene networks. Mechanistically, we demonstrated that C/EBPΓ recruited oncogene NCOA3 to transcriptionally activate Slug, a canonical EMT transcription factor, which in turn induced oxLDL receptor-1 (Lox1) expression and enhanced oxLDL uptake to promote cancer metastasis, which could be blocked with LOX1 neutralizing antibody. In summary, our results unveiled a previously unappreciated interplay between lipid metabolic and metastatic program, as well as the existence of a pivotal C/EBPΓ-Slug-Lox1 transcription axis to promote oxLDL levels and cancer metastasis. Show less
no PDF DOI: 10.1038/s41388-019-1015-z
SNAI1
Ke Wang, Jun Liu, Xinhui Zhao +11 more Ā· 2020 Ā· Biochemical and biophysical research communications Ā· Elsevier Ā· added 2026-04-24
WW domain containing E3 Ub-protein ligase 2 (WWP2) plays an important role in tumor progression as an E3 ligase of PTEN. Here, we investigated the role of WWP2 in gastric cancer (GC). We found that WW Show more
WW domain containing E3 Ub-protein ligase 2 (WWP2) plays an important role in tumor progression as an E3 ligase of PTEN. Here, we investigated the role of WWP2 in gastric cancer (GC). We found that WWP2 is overexpressed in GC tissues, which is closely related to poor prognosis of GC patients. Using a WWP2-shRNA lentivirus expressing system, we established WWP2 stable-knockdown GC cell lines and found that knockdown of WWP2 inhibits the proliferation of GC cells both inĀ vitro and inĀ vivo. Also, WWP2 silencing induced the up-regulation of PTEN protein level and down-regulation of AKT phosphorylation level. We further investigated the role of PTEN in this regulating process by performing rescue assay and found that PTEN is essential for WWP2-mediated regulation of GC cells proliferation. Taken together, our results demonstrated that WWP2 promotes proliferation of GC cells by downregulating PTEN, which may provide new therapeutic targets for GC. Show less
no PDF DOI: 10.1016/j.bbrc.2019.10.179
WWP2
Qian Liu, Jianxin Pan, Carlo Berzuini +2 more Ā· 2020 Ā· Scientific reports Ā· Nature Ā· added 2026-04-24
Genome-wide association studies have identified hundreds of single nucleotide polymorphisms (SNPs) that are associated with BMI and diabetes. However, lack of adequate data has for long time prevented Show more
Genome-wide association studies have identified hundreds of single nucleotide polymorphisms (SNPs) that are associated with BMI and diabetes. However, lack of adequate data has for long time prevented investigations on the pathogenesis of diabetes where BMI was a mediator of the genetic causal effects on this disease. Of our particular interest is the underlying causal mechanisms of diabetes. We leveraged the summary statistics reported in two studies: UK Biobank (N = 336,473) and Genetic Investigation of ANthropometric Traits (GIANT, N = 339,224) to investigate BMI-mediated genetic causal pathways to diabetes. We first estimated the causal effect of BMI on diabetes by using four Mendelian randomization methods, where a total of 76 independent BMI-associated SNPs (R Show less
no PDF DOI: 10.1038/s41598-020-64493-4
ZC3H4
Rongbin Xu, Shuai Li, Shuaijun Guo +4 more Ā· 2020 Ā· Environmental pollution (Barking, Essex : 1987) Ā· Elsevier Ā· added 2026-04-24
The knowledge about the effects of environmental temperature on human epigenome is a potential key to understand the health impacts of temperature and to guide acclimation under climate change. We per Show more
The knowledge about the effects of environmental temperature on human epigenome is a potential key to understand the health impacts of temperature and to guide acclimation under climate change. We performed a systematic review on the epidemiological studies that have evaluated the association between environmental temperature and human epigenetic modifications. We identified seven original articles on this topic published between 2009 and 2019, including six cohort studies and one cross-sectional study. They focused on DNA methylation in elderly people (blood sample) or infants (placenta sample), with sample size ranging from 306 to 1798. These studies were conducted in relatively low temperature setting (median/mean temperature: 0.8-13 °C), and linear models were used to evaluate temperature-DNA methylation association over short period (≤28 days). It has been reported that short-term ambient temperature could affect global human DNA methylation. A total of 15 candidate genes (ICAM-1, CRAT, F3, TLR-2, iNOS, ZKSCAN4, ZNF227, ZNF595, ZNF597, ZNF668, CACNA1H, AIRE, MYEOV2, NKX1-2 and CCDC15) with methylation status associated with ambient temperature have been identified. DNA methylation on ZKSCAN4, ICAM-1 partly mediated the effect of short-term cold temperature on high blood pressure and ICAM-1 protein (related to cardiovascular events), respectively. In summary, epidemiological evidence about the impacts of environment temperature on human epigenetics remains scarce and limited to short-term linear effect of cold temperature on DNA methylation in elderly people and infants. More studies are needed to broaden our understanding of temperature related epigenetic changes, especially under a changing climate. Show less
no PDF DOI: 10.1016/j.envpol.2019.113840
ZNF668
Li Wang, Rui Zhang, Xiaohong Hou +8 more Ā· 2019 Ā· Molecular brain Ā· BioMed Central Ā· added 2026-04-24
Studies have shown that a normal circadian rhythm is crucial to learning and memory. Circadian rhythm disturbances that occur at early stages of Alzheimer's disease (AD) aggravate the progression of t Show more
Studies have shown that a normal circadian rhythm is crucial to learning and memory. Circadian rhythm disturbances that occur at early stages of Alzheimer's disease (AD) aggravate the progression of the disease and further reduce learning and memory in AD patients. The novel, dual GLP-1R/GIPR agonist DA-JC1 has been found to exert a stronger hypoglycemic effect than a GLP-1R agonist alone and has been shown to exert neuroprotective effects. However, it is not clear whether DA-JC1 improves the Aβ31-35-induced decline in learning and memory ability by restoring disrupted circadian rhythms. In the present study, we carried out a mouse wheel-running experiment and Morris water maze test (MWM) and found that DA-JC1 could effectively improve the decline of learning and memory and circadian rhythm disorders induced by Aβ31-35. After downregulating Per2 expression via lentivirus-shPer2 in the hippocampus and the hippocampal HT22 cells, we found that circadian rhythm disorders occurred, and that DA-JC1 could not improve the impaired learning and memory. These results suggest that DA-JC1 improves damage to learning and memory by antagonizing circadian rhythm disorders induced by Aβ31-35. The outcome of this ongoing study may provide a novel therapeutic intervention for AD in the future. Show less
šŸ“„ PDF DOI: 10.1186/s13041-019-0432-9
GIPR
Meng Wang, Yijun Chen, Ming Zhu +4 more Ā· 2019 Ā· General and comparative endocrinology Ā· Elsevier Ā· added 2026-04-24
The melanocortin-4 receptor (MC4R) acts as a member of G-protein coupled receptors and participate in food intake and energy expenditure. Melanocortin 2 receptor accessory protein 2 (MRAP2) plays a cr Show more
The melanocortin-4 receptor (MC4R) acts as a member of G-protein coupled receptors and participate in food intake and energy expenditure. Melanocortin 2 receptor accessory protein 2 (MRAP2) plays a critical role in regulating MC4R signaling in mammals and zebrafish. However, evidence on their interaction in other teleost species remains elusive. Here, we cloned and assessed the evolutionary aspect and pharmacological modulation of MRAP2 on MC4R signaling in Nile tilapia (Oreochromis niloticus). Tissue distribution analysis of tmc4r and tmrap2 confirmed their co-expression in the brain region. tMRAP2 protein could form antiparallel homo-dimer and directly interacted with tMC4R in vitro and presence of tMRAP2 led to the reduction of agonist response and surface expression of tMC4R. Overall, our findings provide a comparative overview on the evolutionary conservation, genomic distribution, tissue-specific expression and pharmacological profile of the MC4R and MRAP2 in another non-mammalian teleost. Show less
no PDF DOI: 10.1016/j.ygcen.2019.113219
MC4R
Yamin Zhang, Hongyan Ren, Qiang Wang +28 more Ā· 2019 Ā· Science China. Life sciences Ā· Springer Ā· added 2026-04-24
Antipsychotic-induced metabolic disturbance (AIMD) is a common adverse effect of antipsychotics with genetics partly underpinning variation in susceptibility among schizophrenia patients. Melanocortin Show more
Antipsychotic-induced metabolic disturbance (AIMD) is a common adverse effect of antipsychotics with genetics partly underpinning variation in susceptibility among schizophrenia patients. Melanocortin4 receptor (MC4R) gene, one of the candidate genes for AIMD, has been under-studied in the Chinese patients. We conducted a pharmacogenetic study in a large cohort of Chinese patients with schizophrenia. In this study, we investigated the genetic variation of MC4R in Chinese population by genotyping two SNPs (rs489693 and rs17782313) in 1,991 Chinese patients and examined association of these variants with the metabolic effects that were often observed to be related to AIMD. Metabolic measures, including body mass index (BMI), waist circumference (WC), glucose, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were assessed at baseline and after 6-week antipsychotic treatment. We found that interaction of SNPƗmedication status (drug-naĆÆve/medicated) was significantly associated with BMI, WC, and HDL change %, respectively. Both SNPs were significantly associated with baseline BMI and WC in the medicated group. Moderate association of rs489693 with WC, Triglyceride, and HDL change % were observed in the whole sample. In the drug-naĆÆve group, we found recessive effects of rs489693 on BMI gain more than 7%, WC and Triglyceride change %, with AA incurring more metabolic adverse effects. In conclusion, the association between rs489693 and the metabolic measures is ubiquitous but moderate. Rs17782313 is less involved in AIMD. Two SNPs confer risk of AIMD to patients treated with different antipsychotics in a similar way. Show less
no PDF DOI: 10.1007/s11427-018-9489-x
MC4R
Decheng Ren, Jian Hua Xu, Yan Bi +15 more Ā· 2019 Ā· Gene Ā· Elsevier Ā· added 2026-04-24
Obesity is one of the major health problems strongly influenced by lifestyle, genetic and environmental factors. Previous studies have reported many single-nucleotide polymorphisms (SNPs) are associat Show more
Obesity is one of the major health problems strongly influenced by lifestyle, genetic and environmental factors. Previous studies have reported many single-nucleotide polymorphisms (SNPs) are associated with obesity in different races. This study aimed to explore the genetic associations between LEPR, MC4R polymorphisms and overweight/obesity in Chinese Han adolescents. 400 adolescents including 222 health controls and 178 overweight/obese adolescents were genotyped and their body compositions were also analyzed in this study. We found that allelic and genotypic frequencies of LEPR SNP rs8179183 were significantly different between controls and cases (allelic frequency p < 0.001; genotypic frequency p = 0.004). These difference was still significant (allelic frequency p < 0.011; genotypic frequency p = 0.024) after Bonferroni correction. Moreover, we found that rs8179183 was associated with serum triglyceride level after adjusting for age and body mass index (BMI) (p = 0.037). In summary, our results found a significant association between LEPR SNP rs8179183 and overweight/obesity in Chinese Han adolescent. This study may provide a reference for future studies of obesity. Show less
no PDF DOI: 10.1016/j.gene.2018.12.073
MC4R
Elizabeth T Cirulli, Lining Guo, Christine Leon Swisher +9 more Ā· 2019 Ā· Cell metabolism Ā· Elsevier Ā· added 2026-04-24
Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a needĀ for a more precise yet portable method of phenotyping and categorizing risk in large numbers of Show more
Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a needĀ for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity. We find that obesity results in profound perturbation of the metabolome; nearly a third of the assayed metabolites associated with changes in BMI. A metabolome signature identifies the healthy obese and lean individuals with abnormal metabolomes-these groups differ in health outcomes and underlying genetic risk. Specifically, an abnormal metabolome associated with a 2- to 5-fold increase in cardiovascular events when comparing individuals who were matched for BMI but had opposing metabolome signatures. Because metabolome profiling identifies clinically meaningful heterogeneity in obesity, this approach could help select patients for clinical trials. Show less
šŸ“„ PDF DOI: 10.1016/j.cmet.2018.09.022
MC4R
Chang Guo, Zhicong Zhao, Xia Deng +3 more Ā· 2019 Ā· Endocrine journal Ā· added 2026-04-24
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease with increasing prevalence worldwide. Angiopoietin-like protein 8 (ANGPTL8), a member of the angiopoietin-like protein family, is involve Show more
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease with increasing prevalence worldwide. Angiopoietin-like protein 8 (ANGPTL8), a member of the angiopoietin-like protein family, is involved in glucose metabolism, lipid metabolism, and energy homeostasis and believed to be associated with T2DM. Expression levels of ANGPTL8 are often significantly altered in metabolic diseases, such as non-alcoholic fatty liver disease (NAFLD) and diabetes mellitus. Studies have shown that ANGPTL8, together with other members of this protein family, such as angiopoietin-like protein 3 (ANGPTL3) and angiopoietin-like protein 4 (ANGPTL4), regulates the activity of lipoprotein lipase (LPL), thereby participating in the regulation of triglyceride related lipoproteins (TRLs). In addition, members of the angiopoietin-like protein family are varyingly expressed among different tissues and respond differently under diverse nutritional and metabolic status. These findings may provide new options for the diagnosis and treatment of diabetes, metabolic syndromes and other diseases. In this review, the interaction between ANGPTL8 and ANGPTL3 or ANGPTL4, and the differential expression of ANGPTL8 responding to different nutritional and metabolic status during the regulation of LPL activity were reviewed. Show less
no PDF DOI: 10.1507/endocrj.EJ19-0263
ANGPTL4
Shengru Wu, Wei Guo, Xinyi Li +5 more Ā· 2019 Ā· Proceedings. Biological sciences Ā· The Royal Society Ā· added 2026-04-24
Increasing evidence indicates that paternal diet can result in metabolic changes in offspring, but the definite mechanism remains unclear in birds. Here, we fed breeder cocks five different diets cont Show more
Increasing evidence indicates that paternal diet can result in metabolic changes in offspring, but the definite mechanism remains unclear in birds. Here, we fed breeder cocks five different diets containing 0, 0.25, 1.25, 2.50 and 5.00 mg kg Show less
no PDF DOI: 10.1098/rspb.2019.1653
ANGPTL4
Kai Xing, Xitong Zhao, Hong Ao +10 more Ā· 2019 Ā· Scientific reports Ā· Nature Ā· added 2026-04-24
Fat deposition is very important in pig production, and its mechanism is not clearly understood. MicroRNAs (miRNAs) play critical roles in fat deposition and energy metabolism. In the current study, w Show more
Fat deposition is very important in pig production, and its mechanism is not clearly understood. MicroRNAs (miRNAs) play critical roles in fat deposition and energy metabolism. In the current study, we investigated the mRNA and miRNA transcriptome in the livers of Landrace pigs with extreme backfat thickness to explore miRNA-mRNA regulatory networks related to lipid deposition and metabolism. A comparative analysis of liver mRNA and miRNA transcriptomes from pigs (four pigs per group) with extreme backfat thickness was performed. We identified differentially expressed genes from RNA-seq data using a Cufflinks pipeline. Seventy-one differentially expressed genes (DEGs), including twenty-eight well annotated on the porcine reference genome genes, were found. The upregulation genes in pigs with higher backfat thickness were mainly involved in fatty acid synthesis, and included fatty acid synthase (FASN), glucokinase (GCK), phosphoglycerate dehydrogenase (PHGDH), and apolipoprotein A4 (APOA4). Cytochrome P450, family 2, subfamily J, polypeptide 34 (CYP2J34) was lower expressed in pigs with high backfat thickness, and is involved in the oxidation of arachidonic acid. Moreover, 13 differentially expressed miRNAs were identified. Seven miRNAs were associated with fatty acid synthesis, lipid metabolism, and adipogenic differentiation. Based on comprehensive analysis of the transcriptome of both mRNAs and miRNAs, an important regulatory network, in which six DEGs could be regulated by differentially expressed miRNAs, was established for fat deposition. The negative correlate in the regulatory network including, miR-545-5p and GRAMD3, miR-338 and FASN, and miR-127, miR-146b, miR-34c, miR-144 and THBS1 indicate that direct suppressive regulation may be involved in lipid deposition and energy metabolism. Based on liver mRNA and miRNA transcriptomes from pigs with extreme backfat thickness, we identified 28 differentially expressed genes and 13 differentially expressed miRNAs, and established an important miRNA-mRNA regulatory network. This study provides new insights into the molecular mechanisms that determine fat deposition in pigs. Show less
šŸ“„ PDF DOI: 10.1038/s41598-019-53377-x
APOA4
Liangle Yang, Lin Ma, Wenting Guo +3 more Ā· 2019 Ā· Sleep Ā· Oxford University Press Ā· added 2026-04-24
Lipid profiles are influenced by both genetic and environmental factors. Genetic variants in the APOA4-APOA5-ZPR1-BUD13 gene cluster and aberrant sleep duration were independently identified to be ass Show more
Lipid profiles are influenced by both genetic and environmental factors. Genetic variants in the APOA4-APOA5-ZPR1-BUD13 gene cluster and aberrant sleep duration were independently identified to be associated with lipids in previous studies. We aimed to investigate whether sleep duration modified the genetic associations with longitudinal lipids changes. Four single nucleotide polymorphisms (SNPs), rs17119975, rs651821, rs7396835, and rs964184 in the APOA4-APOA5-ZPR1-BUD13 gene cluster were genotyped among 8648 apparently healthy subjects from the Dongfeng-Tongji (DFTJ) cohort. Information on sleep duration was obtained by questionnaires. Changes in total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), were evaluated from baseline to 5-year follow-up. After multivariate adjustments, we found that rs651821 and weighted genetic risk score (GRS) were significantly associated with increased triglyceride, and the genetic association with triglyceride change consistently strengthened across sleep duration categories. The differences in triglyceride changes per increment of risk allele for rs651821 were 0.028 (SE = 0.017, p = 0.112), 0.051 (SE = 0.009, p < 0.001), and 0.064 (SE = 0.016, p < 0.001) in individuals with sleep duration ≤7, >7-<9, and ≄9 h, respectively (p interaction = 0.031). The GRS also showed a significant interaction with sleep duration categories for triglyceride change (p interaction = 0.010). In addition, all of the four SNPs and GRS were inversely related to HDL-c changes. Longer sleep duration might exacerbate the adverse effects of SNPs in APOA4-APOA5-ZPR1-BUD13 gene cluster on 5-year triglyceride changes. Show less
no PDF DOI: 10.1093/sleep/zsz115
APOA4
Yaokun Li, Lingxuan Kong, Ming Deng +6 more Ā· 2019 Ā· Genes Ā· MDPI Ā· added 2026-04-24
Heat stress has a severe effect on animal health and can reduce the productivity and reproductive efficiency; it is therefore necessary to explore the molecular mechanism involved in heat stress respo Show more
Heat stress has a severe effect on animal health and can reduce the productivity and reproductive efficiency; it is therefore necessary to explore the molecular mechanism involved in heat stress response, which is helpful for the cultivation of an animal breed with resistance to heat stress. However, little research about heat stress-responsive molecular analysis has been reported in sheep. Therefore, in this study, RNA sequencing (RNA-Seq) was used to investigate the transcriptome profiling in the liver of Hu sheep with and without heat stress. In total, we detected 520 and 22 differentially expressed mRNAs and lncRNAs, respectively. The differentially expressed mRNAs were mainly associated with metabolic processes, the regulation of biosynthetic processes, and the regulation of glucocorticoid; additionally, they were significantly enriched in the heat stress related pathways, including the carbon metabolism, the PPAR signaling pathway, and vitamin digestion and absorption. The co-located differentially expressed lncRNA Lncā‚€ā‚€ā‚ā‚‡ā‚ˆā‚‚ might positively influence the expression of the corresponding genes APOA4 and APOA5, exerting co-regulative effects on the liver function. Thus, we made the hypothesis that Lncā‚€ā‚€ā‚ā‚‡ā‚ˆā‚‚, APOA4 and APOA5 might function synergistically to regulate the anti-heat stress ability in Hu sheep. This study provides a catalog of Hu sheep liver mRNAs and lncRNAs, and will contribute to a better understanding of the molecular mechanism underlying heat stress responses. Show less
šŸ“„ PDF DOI: 10.3390/genes10050395
APOA4
Chao Xuan, Hui Li, Le-Le Li +6 more Ā· 2019 Ā· Proteomics. Clinical applications Ā· Wiley Ā· added 2026-04-24
The present study aims to discover novel serum biomarkers of early-onset myocardial infarction (MI) using proteomic analysis. In the first stage, the iTRAQ-coupled LC-MS/MS technique is utilized to in Show more
The present study aims to discover novel serum biomarkers of early-onset myocardial infarction (MI) using proteomic analysis. In the first stage, the iTRAQ-coupled LC-MS/MS technique is utilized to investigate protein profiles of patients with early-onset MI. In the second stage, these candidate proteins are validated using ELISA. A total of 538 proteins are quantified, with pregnancy zone protein (PZP), leucine-rich α-2-glycoprotein (LRG) and Apolipoprotein C-I (Apo C-I) being upregulated and Apolipoprotein A-I (Apo A-I) and Apolipoprotein A-IV (Apo A-IV) downregulated in early-onset MI patients. Results from the validation stage demonstrate that the serum concentrations of PZP and LRG are significantly increased in the early-onset MI group. The correlation between the concentrations of C-reactive protein (CRP) and the two candidate biomarkers is positive. Area under the curve values used to diagnose early-onset MI for LRG and PZP are 0.939 and 0.874, respectively. Five differential serum proteins are identified in early-onset MI using proteomic analysis. Lipoprotein-related biomarkers further demonstrate the close relationship between lipid metabolism and the disease. Inflammation-associated LRG and PZP may be novel biomarkers of the disease. In addition, changes in these proteins may partly reveal the possible mechanisms in the pathogenesis and pathophysiology of early-onset MI. Show less
no PDF DOI: 10.1002/prca.201800079
APOA4
Tao Zhang, Jianrong Guo, Jian Gu +4 more Ā· 2019 Ā· Oncology reports Ā· added 2026-04-24
Colorectal cancer (CRC) is one of the principal causes of cancer‑associated mortality worldwide. The high incidence of liver metastasis is the leading risk factor of mortality in patients with CRC, an Show more
Colorectal cancer (CRC) is one of the principal causes of cancer‑associated mortality worldwide. The high incidence of liver metastasis is the leading risk factor of mortality in patients with CRC, and the mechanisms of CRC liver metastasis are poorly understood. In the present study, 7Ā datasets, including 3Ā gene expression profile datasets and 4Ā microRNA (miRNA) expression profile datasets were downloaded from the NCBI Gene Expression Omnibus (GEO) database to identify potential key genes and miRNAs, which may be candidate biomarkers for CRC liver metastasis. Differentially expressed (DE) genes (DEGs) and DE miRNAs of primary CRC tumor tissues and liver metastatic CRC tumor tissues were selected using the GEO2R tool. Gene Ontology and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery online database. Furthermore, Cytoscape with cytoHubba and the Molecular Complex Detection (MCODE) plug‑in were used to visualize a protein‑protein interaction (PPI) network for these DEGs, and to screen hub genes and gene modules in the PPI network. In addition, the online databases, TargetScan, miRanda, PITA, miRWalk and miRDB, were used to identify the target genes of the DE miRNAs. In the present study, 141Ā DEGs (97Ā upregulated and 44Ā downregulated) and 3Ā DE miRNAs (2Ā upregulated and 1Ā downregulated) were screened from the 3Ā gene expression microarray datasets and 4 miRNA expression microarray datasets, respectively. In total, 10 hub genes with a high degree of connectivity were selected from the PPI network, including albumin (ALB), coagulation factor II (F2), thrombin, apolipoproteinĀ H (APOH), serpin familyĀ C memberĀ 1 (SERPINC1), apolipoproteinĀ A1 (APOA1), α‑1‑microglobulin/bikunin precursor (AMBP), apolipoproteinĀ C3 (APOC3), plasminogen (PLG), α‑2 HS glycoprotein (AHSG) and apolipoprotein B (APOB). The most important module was detected in the PPI network using the MCODE plug‑in. A total of 20 DEGs were identified to be potential target genes of these DE miRNAs, and novel miRNA‑DEGs regulatory axes were constructed. InĀ vitro experiments were performed to demonstrate that miR‑885 promoted CRC cell migration by, at least partially, decreasing the expression of von Willebrand factor (vWF) and insulin‑like growth factor binding proteinĀ 5 (IGFBP5). In conclusion, by using integrated bioinformatics analysis and inĀ vitro experiments, key candidate genes were identified and novel miRNA‑mRNA regulatory axes in CRC liver metastasis were constructed, which may improve understanding of the molecular mechanisms underlying CRC liver metastasis. Show less
šŸ“„ PDF DOI: 10.3892/or.2018.6840
APOC3
Wei Yang, Yingjun Li, Yong Ai +7 more Ā· 2019 Ā· Journal of medicinal chemistry Ā· ACS Publications Ā· added 2026-04-24
Dysregulation of the Wnt/β-catenin signaling pathway has been widely recognized as a pathogenic mechanism for colorectal cancer (CRC). Although numerous Wnt inhibitors have been developed, they common Show more
Dysregulation of the Wnt/β-catenin signaling pathway has been widely recognized as a pathogenic mechanism for colorectal cancer (CRC). Although numerous Wnt inhibitors have been developed, they commonly suffer from toxicity and unintended effects. Moreover, concerns have been raised in targeting this pathway because of its critical roles in maintaining stem cells and regenerating tissues and organs. On the basis of the anthelmintic drug pyrvinium and previous lead FX1128, we have developed a compound YW2065 ( Show less
no PDF DOI: 10.1021/acs.jmedchem.9b01252
AXIN1
Hailong Guo, Hongyi Zhu, Jie Zhang +2 more Ā· 2019 Ā· Journal of cellular biochemistry Ā· Wiley Ā· added 2026-04-24
The function of ten-eleven translocation methylcytosine dioxygenase 1 (TET1) in cancer is background dependent and may be involved in the initial step of active DNA demethylation, while there is littl Show more
The function of ten-eleven translocation methylcytosine dioxygenase 1 (TET1) in cancer is background dependent and may be involved in the initial step of active DNA demethylation, while there is little research to decipher the role of TET1 in DNA methylation-sensitive colon cancer. Downregulated TET1 expression assayed by quantitative real-time PCR (qRT-PCR) was observed in both colon cancer samples and cancer cell lines of HT29, HCT116, and SW48. Such downregulation could promote colon cancer cells proliferation as indicated by the fact that shTET1 could increase the viability of HT29 and HCT116 cells determined by the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide and cell count assay accompanied with upregulation of β-catenin (CTNNB1) and WNT luciferase activity, which was further confirmed as shTET1 could increase the tumor volume and tumor weight, and decrease the body weight in HT29 cells inoculated BALB/C nude mice. The CTNNB1 transfection could rescue the cell growth diminished by normal expression of TET1. shTET1 could promote axis inhibition protein1 (AXIN1) expression and the cell proliferation effect induced by TET1 short hairpin RNA was attenuated by co-inhibition of AXIN1. All of these indicate that TET1 can suppress colon cancer proliferation and the inhibition of the β-catenin pathway is AXIN1 dependent. Show less
no PDF DOI: 10.1002/jcb.28522
AXIN1
Yun Li, Xing Wang, Fei Wang +8 more Ā· 2019 Ā· Journal of cellular physiology Ā· Wiley Ā· added 2026-04-24
Currently, brown adipose tissue (BAT) is a therapeutic target in obesity and diabetes, but the mechanism of BAT activation remains unclear. Because increasing emphasis has been placed on the role of i Show more
Currently, brown adipose tissue (BAT) is a therapeutic target in obesity and diabetes, but the mechanism of BAT activation remains unclear. Because increasing emphasis has been placed on the role of intracellular peptides in biological processes, we conducted a study to gain insight into the mechanism of BAT activation by using a peptidomic approach and then attempted to identify peptides that are capable of activating BAT. In the present study, we generated the peptidomic profile of the intracellular peptides in brown adipocytes treated with forskolin (FSK) using a peptidomic approach. Then, the differentially expressed peptides were evaluated via Gene Ontology (GO) enrichment, KEGG pathway, and protein-protein interaction (PPI) network analysis. Finally, we selected candidate peptides for further validation via assessing the expression levels of UCP-1 and PGC-1α in brown adipocytes exposed to the peptides. A total of 4,370 peptides were identified, of which 951 were upregulated and 379 were downregulated after FSK treatment. Bioinformatic analysis demonstrated that the ECM-receptor interaction GO term was the most enriched and that collagen alpha-related proteins exhibited the highest degree of PPI. Four peptides separately derived from TSC22 domain family protein 1 (T22D1), bromodomain and WD repeat-containing protein 1 (BRWD1), protein piccolo (PCLO), and collagen alpha-1 (III) chain (CO3A1) increased the expression levels of UCP-1 and PGC-1α. ECM-receptor interaction may play an important role in the process of FSK-stimulated BAT activation, and the pT22D1tide, pBRWD1tide, pPCLOtide, and pCO3A1tide peptides potentially promote BAT thermogenesis. Show less
no PDF DOI: 10.1002/jcp.27465
BRWD1
D L Tian, R J Guo, Y M Li +8 more Ā· 2019 Ā· Poultry science Ā· added 2026-04-24
This experiment was conducted to evaluate the effects of lysine deficiency or excess on growth and the expression of lipid metabolism genes in slow-growing birds. A total of 360 one-day-old chicks wer Show more
This experiment was conducted to evaluate the effects of lysine deficiency or excess on growth and the expression of lipid metabolism genes in slow-growing birds. A total of 360 one-day-old chicks were randomly divided into 3 groups, with 6 replicates of 20 birds each. The birds fed the basal diet with a total lysine 0.60% (LL), 1.00% (ML), or 1.40% (HL). The amount of lysine (ML) as the control group, LL and HL as the experimental group, the trial period last 3 wk. The results showed that compared with ML, LL significantly decreased average daily gain and average daily feed intake and remarkably increased feed conversion ratio of birds at 21 day old (P < 0.01), while the above indices in HL had no significant effects (P > 0.05). Besides, LL reduced the pectoral muscle rate (P < 0.01) and decreased the percentage of abdominal fat significantly (P < 0.05). In addition, compared with ML, the expression of fatty acid binding protein 1 (FABP1), acetyl-CoA carboxylase (ACC), malic enzyme (ME), and sterol regulatory element binding protein 1 (SREBP1c) mRNA of liver in LL was significantly decreased (P < 0.05), and the expression of cholesteryl ester transfer protein (CETP) mRNA was significantly increased (P < 0.01), whereas LL had no significant effects on the expression of peroxisome proliferator activated receptor alpha (PPARα) mRNA (P > 0.05). Moreover, compared with ML, HL significantly reduced the expression of FABP1, ACC, ME, SREBP-1c, and PPARα mRNA in the liver (P < 0.05), and had no significant effects on the expression of CETP mRNA (P > 0.05). The results of current research suggest that dietary lysine deficiency could reduce the growth and fat deposition of slow-growing broilers mainly by downregulating the expression of lipid synthesis genes. Show less
no PDF DOI: 10.3382/ps/pez041
CETP
Tianpeng Zhang, Min Chen, Lianxia Guo +4 more Ā· 2019 Ā· Hepatology (Baltimore, Md.) Ā· Wiley Ā· added 2026-04-24
Metabolic homeostasis of amino acids is essential for human health. Here, we aimed to investigate a potential role for the clock component reverse erythroblastosis virus α (Rev-erbα) in circadian regu Show more
Metabolic homeostasis of amino acids is essential for human health. Here, we aimed to investigate a potential role for the clock component reverse erythroblastosis virus α (Rev-erbα) in circadian regulation of amino acid metabolism. RNA-seq with Rev-erbα Show less
no PDF DOI: 10.1002/hep.30675
CPS1
Feng Li, Xingjuan An, Deguang Wu +9 more Ā· 2019 Ā· Frontiers in microbiology Ā· Frontiers Ā· added 2026-04-24
Microbial fuel cells (MFCs) are eco-friendly bio-electrochemical reactors that use exoelectrogens as biocatalyst for electricity harvest from organic biomass, which could also be used as biosensors fo Show more
Microbial fuel cells (MFCs) are eco-friendly bio-electrochemical reactors that use exoelectrogens as biocatalyst for electricity harvest from organic biomass, which could also be used as biosensors for long-term environmental monitoring. Glucose and xylose, as the primary ingredients from cellulose hydrolyzates, is an appealing substrate for MFC. Nevertheless, neither xylose nor glucose can be utilized as carbon source by well-studied exoelectrogens such as Show less
šŸ“„ PDF DOI: 10.3389/fmicb.2019.00409
CPS1
Hong-Li Guo, Xia Jing, Jie-Yu Sun +7 more Ā· 2019 Ā· Current pharmaceutical design Ā· Bentham Science Ā· added 2026-04-24
Valproic acid (VPA) as a widely used primary medication in the treatment of epilepsy is associated with reversible or irreversible hepatotoxicity. Long-term VPA therapy is also related to increased ri Show more
Valproic acid (VPA) as a widely used primary medication in the treatment of epilepsy is associated with reversible or irreversible hepatotoxicity. Long-term VPA therapy is also related to increased risk for the development of non-alcoholic fatty liver disease (NAFLD). In this review, metabolic elimination pathways of VPA in the liver and underlying mechanisms of VPA-induced hepatotoxicity are discussed. We searched in PubMed for manuscripts published in English, combining terms such as "Valproic acid", "hepatotoxicity", "liver injury", and "mechanisms". The data of screened papers were analyzed and summarized. The formation of VPA reactive metabolites, inhibition of fatty acid β-oxidation, excessive oxidative stress and genetic variants of some enzymes, such as CPS1, POLG, GSTs, SOD2, UGTs and CYPs genes, have been reported to be associated with VPA hepatotoxicity. Furthermore, carnitine supplementation and antioxidants administration proved to be positive treatment strategies for VPA-induced hepatotoxicity. Therapeutic drug monitoring (TDM) and routine liver biochemistry monitoring during VPA-therapy, as well as genotype screening for certain patients before VPA administration, could improve the safety profile of this antiepileptic drug. Show less
no PDF DOI: 10.2174/1381612825666190329145428
CPS1
Nong Zhang, Hua Jiang, Yang Bai +7 more Ā· 2019 Ā· Cell biochemistry and function Ā· Wiley Ā· added 2026-04-24
To explore the molecular mechanism of insulin on proliferation and differentiation of MC3T3-E1 cell under high glucose conditions. We first investigated the effect of different concentrations of insul Show more
To explore the molecular mechanism of insulin on proliferation and differentiation of MC3T3-E1 cell under high glucose conditions. We first investigated the effect of different concentrations of insulin on the osteoblast cell proliferation and cell differentiation at various time points by MTT analysis, cell cycle analysis, and expression detection of differentiation genes. Then, we used 200Ā ng/mL of insulin to treat the osteoblast cell at different time points for identifying the common differentially expressed mRNAs among various time points by RNA sequencing. Thirdly, we performed the gene ontology (GO) and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis to explore the biological function of these common differentially expressed mRNAs. The results showed that insulin promoted the cell proliferation and differentiation of osteoblast cell. In RNA sequencing, a total of 31 common differentially expressed mRNAs were identified between different time points. Mt1, Tmem135, Avp, and Dlg2 were found to be associated with the new bone formation. In addition, three important signalling pathways, namely, lysosome, glutamatergic synapse, and chemokine signalling pathways, were found in the KEGG enrichment analysis. Our work demonstrated that insulin could promote the osteoblast cell proliferation and cell differentiation, which may play a key role in bone formation. SIGNIFICANCE OF THE STUDY: Our result showed that insulin could promote the proliferation and differentiation of osteoblast at both cellular and molecular levels, which may promote the new bone formation in the osteoblasts. Show less
no PDF DOI: 10.1002/cbf.3415
DLG2
Bing Bai, Yi-Ran Guo, Yin-Hong Zhang +4 more Ā· 2019 Ā· Chinese medical journal Ā· added 2026-04-24
šŸ“„ PDF DOI: 10.1097/CM9.0000000000000100
DOCK7
XiaoYan Guo, Mingrui Lin, Wei Yan +2 more Ā· 2019 Ā· International journal of oncology Ā· added 2026-04-24
The molecular mechanism of hereditary multiple exostoses (HME) remains ambiguous and a limited number of studies have investigated the pathogenic mechanism of mutations in patients with HME. In the pr Show more
The molecular mechanism of hereditary multiple exostoses (HME) remains ambiguous and a limited number of studies have investigated the pathogenic mechanism of mutations in patients with HME. In the present study, a novel heterozygous splice mutation (c.1284+2del) in exostosin glycosyltransferaseĀ 1 (EXT1) gene was identified in a three‑generation family with HME. Bioinformatics and TA clone‑sequencing indicated that the splice site mutation would result in exonĀ 4 skipping. Reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) revealed that the expression levels of wild‑type EXT1/EXT2 mRNA in patients with HME were significantly decreased, compared with normal control participants (P<0.05). Abnormal EXT1 transcript lacking exonĀ 4 (EXT1‑DEL) and full‑length EXT1 mRNA (EXT1‑FL) were overexpressed in 293‑T cells and Cos‑7 cells using lentivirus infection. RT‑qPCR demonstrated that the expression level of EXT1‑DEL was significantly increased, compared with EXT1‑FL (17.032 vs.Ā 6.309, respectively; P<0.05). The protein encoded by EXT1‑DEL was detected by western blot analysis, and the level was increased, compared with EXT1‑FL protein expression. Immunofluorescence indicated that the protein encoded by EXT1‑DEL was located in the cytoplasm of Cos‑7 cells, which was consistent with the localization of the EXT1‑FL protein. In conclusion, the present study identified a novel splice mutation that causes exonĀ 4 skipping during mRNA splicing and causes reduced expression of EXT1/EXT2. The mutation in EXT1‑DEL generated a unique peptide that is located in the cytoplasm inĀ vitro, and it expands the mutation spectrum and provides molecular genetic evidence for a novel pathogenic mechanism of HME. Show less
šŸ“„ PDF DOI: 10.3892/ijo.2019.4688
EXT1
Yanjun Guo, Wonil Chung, Zhaozhong Zhu +4 more Ā· 2019 Ā· Journal of the American College of Cardiology Ā· Elsevier Ā· added 2026-04-24
High resting heart rate (RHR) occurs in parallel with type 2 diabetes (T2D) and metabolic disorders, implying shared etiology between them. However, it is unknown if they are causally related, and no Show more
High resting heart rate (RHR) occurs in parallel with type 2 diabetes (T2D) and metabolic disorders, implying shared etiology between them. However, it is unknown if they are causally related, and no study has been conducted to investigate the shared mechanisms underlying these associations. The objective of this study was to understand the genetic basis of the association between resting heart rate and cardiometabolic disorders/T2D. This study examined the genetic correlation, causality, and shared genetics between RHR and T2D using LD Score regression, generalized summary data-based Mendelian randomization, and transcriptome wide association scan (TWAS) in UK Biobank data (nĀ =Ā 428,250) and summary-level data for T2D (74,124 cases and 824,006 control subjects) and 8 cardiometabolic traits (sample size ranges from 51,750 to 236,231). Significant genetic correlation between RHR and T2D (r These findings provide evidence of significant genetic correlations and causation between RHR and T2D/cardiometabolic traits, advance our understanding of RHR, and provide insight into shared etiology for high RHR and T2D. Show less
no PDF DOI: 10.1016/j.jacc.2019.08.1055
FADS1