👤 Yachuan Zhou

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Also published as: Aiping Zhou, Aiwu Zhou, Alicia Y Zhou, An Zhou, Ang Zhou, Anna Y Zhou, Annan Zhou, Ao Zhou, Aojia Zhou, Aoshuang Zhou, Apei Zhou, Baiwan Zhou, Bao-Sen Zhou, Baohua Zhou, Baojuan Zhou, Baosen Zhou, Beixian Zhou, Beiyi Zhou, Bin Zhou, Bincheng Zhou, Bing Zhou, Bingbing Zhou, Binghai Zhou, Bingqian Zhou, Bingqing Zhou, Bingying Zhou, Binhua P Zhou, Binhua Zhou, Birong Zhou, Bo Zhou, Bo-Ya Zhou, Bo-Yang Zhou, Bubo Zhou, C Zhou, C-J Zhou, Can Zhou, Carl Zhou, Cefan Zhou, Chang Zhou, Chang-Yin Zhou, Changfan Zhou, Changhua Zhou, Changqi Zhou, Changrui Zhou, Changshuai Zhou, Changwen Zhou, Chao Zhou, Chen-Hui Zhou, Chen-Liang Zhou, Chenchen Zhou, Cheng Zhou, Chengji J Zhou, Chenhao Zhou, Chenkang Zhou, Chenqi Zhou, Chenxia Zhou, Chong Zhou, Chong-zhi Zhou, Chongwei Zhou, ChuHuan Zhou, Chuan-Min Zhou, Chuan-Wei Zhou, Chuan-Xiang Zhou, Chuan-chuan Zhou, Chuanen Zhou, Chuanman Zhou, Chuhao Zhou, Chun-Man Zhou, Chun-Ni Zhou, Chunlei Zhou, Chunlin Zhou, Chunni Zhou, Chunxian Zhou, Chunxiu Zhou, Chunyu Zhou, Chunzhuang Zhou, Chuyu Zhou, Cui Zhou, Cuiqi Zhou, Da Zhou, Daijun Zhou, Daizhan Zhou, Dan Zhou, Danmei Zhou, Danxia Zhou, Dao Zhou, David Zhou, Dawei Zhou, Daxin Zhou, Degang Zhou, Dejun Zhou, Dezheng Zhou, Dingan Zhou, Dingzi Zhou, Dong-Sheng Zhou, Dongdong Zhou, Donger Zhou, Dongfang Zhou, Donghai Zhou, Dongjie Zhou, Dongmei Zhou, Dongsheng Zhou, Duanfang Zhou, Duo-Qi Zhou, Duoqi Zhou, Enchen Zhou, Ershun Zhou, F Zhou, Fachen Zhou, Fan Zhou, Fanfan Zhou, Fang Zhou, Fangfang Zhou, Fangli Zhou, Fangting Zhou, Fei Zhou, Feixue Zhou, Feiye Zhou, Feng Zhou, Feng-Quan Zhou, Fenghua Zhou, Fengrui Zhou, Fengyun Zhou, Fenling Zhou, Fu-Ling Zhou, Fude Zhou, Fuling Zhou, Fusheng Zhou, Fuxiang Zhou, Fuyou Zhou, G Zhou, Gang Zhou, Grace Guoying Zhou, Guangji Zhou, Guangjun Zhou, Guangming Zhou, Guangqian Zhou, Guangzhou Zhou, Gui-Feng Zhou, Guifeng Zhou, Guiju Zhou, Guili Zhou, Guiting Zhou, Guo Zhou, Guo-Kun Zhou, Guohong Zhou, Guohua Zhou, Guoli Zhou, Guoyu Zhou, Guyue Zhou, H Zhou, Haibo Zhou, Haihong Zhou, Haihua Zhou, Haijing Zhou, Haimei Zhou, Hairui Zhou, Haixu Zhou, Haiyan Zhou, Haiyuan Zhou, Haiyue Zhou, Han Zhou, Hang Zhou, Hang-Yu Zhou, Hangfan Zhou, Hanshen Zhou, Hanxiao Zhou, Hao Zhou, Hao-Min Zhou, Haobo Zhou, Haonan Zhou, Haoxiong Zhou, Haoyuan Zhou, He Zhou, Helen Zhou, HengCui Zhou, Heying Zhou, Hong Zhou, Hong-Yu Zhou, Honghong Zhou, Hongji Zhou, Honglei Zhou, Hongli Zhou, Hongmei Zhou, Hongmin Zhou, Hongshan Zhou, Hongwei Zhou, Hongwen Zhou, Hongyan Zhou, Hou-De Zhou, Hu Zhou, Hua Ying Zhou, Hua Zhou, Hua-Bang Zhou, Huadong Zhou, Huaijun Zhou, Huamao Zhou, Huan Zhou, Huangao Zhou, Huanjin Zhou, Huanyu Zhou, Huaqiang Zhou, Hui Zhou, Hui-Fen Zhou, Huifang Zhou, Huifen Zhou, Huihui Zhou, Huimin Zhou, Huinian Zhou, Huiqiang Zhou, Huiwen Zhou, J Zhou, Jeff Xiwu Zhou, Ji Zhou, Ji-Chao Zhou, Ji-Ying Zhou, Jia Zhou, Jia-Guo Zhou, Jia-le Zhou, Jiahe Zhou, Jiahua Zhou, Jiajie Zhou, Jiale Zhou, Jiamei Zhou, Jian Zhou, Jian-Peng Zhou, JianJiang Zhou, Jianan Zhou, Jianfen Zhou, Jianfeng Zhou, Jiang-Ning Zhou, Jiangfei Zhou, Jianghao Zhou, Jianghong Zhou, Jianghui Zhou, Jianglin Zhou, Jiangqiao Zhou, Jianguo Zhou, Jianhua Zhou, Jianling Zhou, Jianmin Zhou, Jianqing Zhou, Jianshe Zhou, Jianwei Zhou, Jianying Zhou, Jianzhong Zhou, Jiaqi Zhou, Jiaru Zhou, Jiawang Zhou, Jiawei Zhou, Jiawen Zhou, Jiaxi Zhou, Jiaxiang Zhou, Jiaxin Zhou, Jiayan Zhou, Jiayi Zhou, Jiayin Zhou, Jie Zhou, Jiechao Zhou, Jiefu Zhou, Jieru Zhou, Jieyan Zhou, Jieyu Zhou, Jin Zhou, Jin-Ting Zhou, Jin-Yong Zhou, JinQiu Zhou, Jing Zhou, Jing-Wei Zhou, Jing-Xuan Zhou, Jingbo Zhou, Jingjie Zhou, Jingjing Zhou, Jingjun Zhou, Jingpei Zhou, Jingqi Zhou, Jingwen Zhou, Jingyi Zhou, Jingyu Zhou, Jingyuan Zhou, Jinting Zhou, Jinyi Zhou, Jiuyao Zhou, Jiyong Zhou, John Zhou, Ju Zhou, Juan Zhou, Juanjuan Zhou, Jue-Yu Zhou, Julian Q Zhou, Jun Zhou, Jun-Min Zhou, Jun-Ying Zhou, Jun-Yu Zhou, Jundong Zhou, Junfeng Zhou, Jungu Zhou, Junguo Zhou, Junhe Zhou, Junjie Zhou, Junjun Zhou, Junting Zhou, Junya Zhou, Junyu Zhou, Justin Zhou, Juying Zhou, Kaicheng Zhou, Kaixia Zhou, Kaixin Zhou, Kaiyu Zhou, Kan Zhou, Ke Zhou, Kecheng Zhou, Kefu Zhou, Kejin Zhou, Kexun Zhou, Lamei Zhou, Lan Zhou, Lang Zhou, Lanlan Zhou, Lanping Zhou, Lanqi Zhou, Laura Y Zhou, Le Zhou, Lei Zhou, Lei-Lei Zhou, Li Zhou, Li-Jun Zhou, Liang Zhou, Liangdong Zhou, Liangfu Zhou, Liangrui Zhou, Liangxue Zhou, Liangyu Zhou, Libin Zhou, Libing Zhou, Libo Zhou, Liche Zhou, Lihong Zhou, Lihuan Zhou, Lijun Zhou, Lili Zhou, Limin Zhou, Lin Zhou, Lina Zhou, Linda Zhou, Ling Zhou, Ling-Yun Zhou, Linglin Zhou, Lingshan Zhou, Lingyi Zhou, Lingyun Zhou, Linjun Zhou, Linnan Zhou, Linran Zhou, Lipeng Zhou, Liqun Zhou, Lisha Zhou, Lisheng Zhou, Liting Zhou, Liufang Zhou, Liuqing Zhou, Liuxin Zhou, Lixin Zhou, Liye Zhou, Long Zhou, Lu Zhou, Lufang Zhou, Luling Zhou, Luming Zhou, Lunni Zhou, Luo-Qi Zhou, Luting Zhou, M M Zhou, Maoge Zhou, Maotian Zhou, Mei Zhou, Meijing Zhou, Meilan Zhou, Meiqi Zhou, Meirong Zhou, Meiyi Zhou, Meng-Tao Zhou, Meng-Yao Zhou, Menghua Zhou, Mengkai Zhou, Menglong Zhou, Mengna Zhou, Mengqi Zhou, Mengqian Zhou, Mengze Zhou, Mi Zhou, Miao Zhou, Min Zhou, Ming Zhou, Ming-Ju Zhou, Ming-Ming Zhou, Ming-Sheng Zhou, Mingfeng Zhou, Minglei Zhou, Minglian Zhou, Mingmei Zhou, Mingming Zhou, Mingping Zhou, Mingqi Zhou, Minling Zhou, Minyi Zhou, Molin Zhou, Na Zhou, Nan Zhou, Neng Zhou, Ni Zhou, Nian Zhou, Nianwei Zhou, Ning Zhou, Ningying Zhou, Niuniu Zhou, P Zhou, Pei Zhou, Peng Zhou, Penghui Zhou, Pijun Zhou, Ping Zhou, Ping-Kun Zhou, Pingkun Zhou, Pingxi Zhou, Pingxin Zhou, Puhui Zhou, Q Zhou, Qi Zhou, Qian Zhou, Qiang Zhou, Qianxin Zhou, Qiao Zhou, Qiaoxia Zhou, Qidong Zhou, Qin Zhou, Qin-Yi Zhou, Qing Zhou, Qing-Bing Zhou, Qing-Qing Zhou, Qingbing Zhou, Qingbo Zhou, Qingchun Zhou, Qinghua Zhou, Qingniao Zhou, Qingnv Zhou, Qingping Zhou, Qingtong Zhou, Qingxin Zhou, Qingyu Zhou, Qiong Zhou, Qiu-Min Zhou, Qiu-Zhi Zhou, Qiyang Zhou, Qiyin Zhou, Quan Zhou, Qun Zhou, R B Zhou, Ranran Zhou, Raorao Zhou, Ren Zhou, Rong Zhou, Rong-Yan Zhou, Rongbin Zhou, Rongjia Zhou, Rongxian Zhou, Rongxuan Zhou, Rongyan Zhou, Rouxi Zhou, Ru Zhou, Ruchen Zhou, Rui Zhou, Ruihai Zhou, Ruijun Zhou, Ruimei Zhou, Ruisi Zhou, Runjin Zhou, Ruyi Zhou, S A Zhou, S R Zhou, S Zhou, S-G Zhou, Sa Zhou, Sanshun Zhou, Sha Zhou, Shanshan Zhou, Shao-Lai Zhou, Shaobo Zhou, Shaoli Zhou, Shaolong Zhou, Sheng-Nan Zhou, Shenghua Zhou, Shenghui Zhou, Shengwen Zhou, Shengyang Zhou, Shengyi Zhou, Shenping Zhou, Shiao Zhou, Shibo Zhou, Shiyi Zhou, Shu Zhou, Shuaishuai Zhou, Shuaiyang Zhou, Shuang Zhou, Shuling Zhou, Shumin Zhou, Shun Zhou, Shuo Zhou, Si Zhou, Si-Qi Zhou, Siquan Zhou, Sirui Zhou, Song Zhou, Songhui Zhou, Sufang Zhou, Sumei Zhou, Suqing Zhou, Suzhen Zhou, T Zhou, Tai-Cheng Zhou, Taimei Zhou, Tao Zhou, Tengxiao Zhou, Ti Zhou, Tian-Li Zhou, Tianhua Zhou, Tianqiong Zhou, Tianrong Zhou, Tianxing Zhou, Tianyan Zhou, Tianyu Zhou, Tiger Zhou, Ting Zhou, Tingting Zhou, Tong Zhou, Vincent Zhou, W Zhou, Wan-hao Zhou, Wang Zhou, Wei Zhou, Weihua Zhou, Weihui Zhou, Weijiao Zhou, Weijie Zhou, Weiming Zhou, Weinan Zhou, Weiqiang Zhou, Weishang Zhou, Weiwei Zhou, Weiying Zhou, Wen Zhou, Wen-Chao Zhou, Wen-Hao Zhou, Wen-Jie Zhou, Wen-Quan Zhou, Wenbin Zhou, Wenbo Zhou, Wenchao Zhou, Wenfang Zhou, Wenhao Zhou, Wenjie Zhou, Wenjing Zhou, Wenke Zhou, Wenqing Zhou, Wenrong Zhou, Wenwen Zhou, Wenxing Zhou, Wenyu Zhou, Wenzong Zhou, Wesley Zhou, Wu Zhou, Wuduo Zhou, Wuyuan Zhou, X F Zhou, X Q Zhou, X-T Zhou, Xi Zhou, Xia Zhou, Xia-Bo Zhou, Xiang Zhou, Xiangda Zhou, Xiangdong Zhou, Xianghai Zhou, Xiangrong Zhou, Xianguo Zhou, Xiangyu Zhou, Xiangyuan Zhou, Xianhu Zhou, Xianhua Zhou, Xianhui Zhou, Xianjing Zhou, Xianliang Zhou, Xianxiao Zhou, Xiao Zhou, Xiao-Hai Zhou, Xiao-Ting Zhou, Xiao-Yu Zhou, Xiaobo Zhou, Xiaochuan Zhou, Xiaochun Zhou, Xiaofeng Zhou, Xiaohai Zhou, Xiaohan Zhou, Xiaohui Zhou, Xiaojing Zhou, Xiaolei Zhou, Xiaoli Zhou, Xiaolin Zhou, Xiaoling Zhou, Xiaomao Zhou, Xiaoming Zhou, Xiaonan Zhou, Xiaopu Zhou, Xiaoqian Zhou, Xiaorong Zhou, Xiaorui Zhou, Xiaoshu Zhou, Xiaosu Zhou, Xiaotong Zhou, Xiaowen Zhou, Xiaoxi Zhou, Xiaoxia Zhou, Xiaoxue Zhou, Xiaoyan Zhou, Xiaoye Zhou, Xiaoying Zhou, Xiaozhong Zhou, Xidan Zhou, Xin Tong Zhou, Xin Zhou, Xin-Rong Zhou, Xin-Yu Zhou, Xin-Yue Zhou, Xingtao Zhou, Xinhong Zhou, Xinhua Zhou, Xinming Zhou, Xinyan Zhou, Xinyao Zhou, Xinyi Zhou, Xinyue Zhou, Xinzhi Zhou, Xiqiu Zhou, Xiu-Ping Zhou, Xiuhong Zhou, Xiuling Zhou, Xiuping Zhou, Xiuteng Zhou, Xiyi Zhou, Xu Yu Zhou, Xu Zhou, Xu-Hua Zhou, Xuan Zhou, Xuanchen Zhou, Xuchang Zhou, Xue Dong Zhou, Xue Zhou, Xue-Yan Zhou, Xuedong Zhou, Xuefeng Zhou, Xuejie Zhou, Xueli Zhou, Xueliang Zhou, Xueqin Zhou, Xueqing Zhou, Xueshi Zhou, Xujie Zhou, Xun Zhou, Xuyu Zhou, Y J Zhou, Y Zhou, Y-L Zhou, Yadi Zhou, Yahui Zhou, Yajun Zhou, Yan Zhou, Yan-Yan Zhou, Yanbing Zhou, Yandong Zhou, Yanfen Zhou, Yang Zhou, Yangbo Zhou, Yangying Zhou, Yanhao Zhou, Yanheng Zhou, Yanhua Zhou, Yanjiao Zhou, Yanjie Zhou, Yanli Zhou, Yanling Zhou, Yanmeng Zhou, Yanqiu Zhou, Yanrong Zhou, Yanyi Zhou, Yao Zhou, Yaping Zhou, Yaqi Zhou, Yating Zhou, Yeyun Zhou, Yi Zhou, Yi-Hui Zhou, Yi-Jiang Zhou, Yichao Zhou, Yidan Zhou, Yifa Zhou, Yifeng Zhou, Yinan Zhou, Ying Zhou, Ying-Hui Zhou, Yinghui Zhou, Yingjie Zhou, Yingmin Zhou, Yingshi Zhou, Yiqing Zhou, Yitian Zhou, Yong Zhou, Yong-Gang Zhou, Yong-Hui Zhou, Yong-an Zhou, Yongbing Zhou, Yongcan Zhou, Yonghua Zhou, Yongjian Zhou, Yongqiang Zhou, Yongtao Zhou, Yongxin Zhou, Yongzhi Zhou, You Lang Zhou, You Zhou, You-Li Zhou, Youping Zhou, Yu Zhou, Yu-Bao Zhou, Yu-Ning Zhou, Yu-Qi Zhou, Yuan Zhou, Yuanyuan Zhou, Yubin Zhou, Yudong Zhou, Yue Zhou, Yueping Zhou, Yuetao Zhou, Yufei Zhou, Yuhan Zhou, Yuhuan Zhou, Yujia Zhou, Yujie Zhou, Yun Zhou, Yun-Fei Zhou, Yun-Tao Zhou, Yunfang Zhou, Yunfeng Zhou, Yunhui Zhou, Yunqian Zhou, Yunxia Zhou, Yunxiang Zhou, Yunyun Zhou, Yunzhen Zhou, Yuqi Zhou, Yuqiao Zhou, Yuqing Zhou, Yuqiu Zhou, Yushan Zhou, Yuting Zhou, Yutong Zhou, Yuxin Zhou, Yuzhi Zhou, Zechen Zhou, Zefeng Zhou, Zenghui Zhou, Zengyuan Zhou, Zengzi Zhou, Zewei Zhou, Zhan Zhou, Zhaokai Zhou, Zhechong Zhou, Zhen Zhou, Zheng Zhou, Zheng-Jun Zhou, Zheng-Yang Zhou, Zhengyang Zhou, Zhengzhong Zhou, Zhenhua Zhou, Zhenlei Zhou, Zhenying Zhou, Zhenyu Zhou, Zheyi Zhou, Zhi Dong Zhou, Zhi Zhou, Zhi-Dong Zhou, Zhi-Gang Zhou, Zhi-Hang Zhou, Zhi-Jiao Zhou, Zhi-Xiang Zhou, Zhi-Yong Zhou, Zhibo Zhou, Zhicheng Zhou, Zhifeng Zhou, Zhiguang Zhou, Zhihang Zhou, Zhihao Zhou, Zhiheng Zhou, Zhihui Zhou, Zhijiao Zhou, Zhijun Zhou, Zhimin Zhou, Zhipeng Zhou, Zhiqin Zhou, Zhiqun Zhou, Zhiwei Zhou, Zhixiang Zhou, Zhiyi Zhou, Zhiyong Zhou, Zhiyu Zhou, Zhongbo Zhou, Zhongjiang Zhou, Zhongkai Zhou, Zhongqiu Zhou, Zhongtao Zhou, Zhongxing Zhou, Zhongyin Zhou, Zhou Zhou, Zhu Zhou, Zhuoming Zhou, Zi-Yang Zhou, Zi-Yi Zhou, Zihan Zhou, Zihao Zhou, Zihua Zhou, Zijun Zhou, Zili Zhou, Ziliang Zhou, Zilin Zhou, Zilong Zhou, Zipeng Zhou, Ziqing Zhou, Ziwei Zhou, Ziyan Zhou, Ziyue Zhou, Ziyun Zhou, Zongkai Zhou, Zunchun Zhou, Zuomin Zhou, Zuoqiong Zhou, Zuping Zhou
articles
Xiuhua Wei, Jie Fan, Yuanqiang Hao +4 more · 2024 · Talanta · Elsevier · added 2026-04-24
A novel electrochemiluminescence (ECL) and electrochemical dual-mode sensor was developed for detecting the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) and screening its Show more
A novel electrochemiluminescence (ECL) and electrochemical dual-mode sensor was developed for detecting the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) and screening its inhibitor. Specifically, the adamantane (ADA)-functionalized peptide (P1), a designed substrate peptide for BACE1, was immobilized on the electrode surface via host-guest interaction between β-cyclodextrin (β-CD) and ADA. The aggregation of the peptide (P2) and luminol co-functionalized silver nanoparticles could be induced by cucurbit [8]uril (CB[8] due to the ability of CB[8] to accommodate two aromatic residues simultaneously. The obtained (CB[8]-P2-AgNPs-luminol) Show less
no PDF DOI: 10.1016/j.talanta.2023.124904
BACE1
Jie Fan, Xiuhua Wei, Hui Dong +4 more · 2024 · Critical reviews in analytical chemistry · Taylor & Francis · added 2026-04-24
Alzheimer's disease (AD) is a degenerative disease of the central nervous system. The pathogenesis is still not fully clear. One of the main histopathological manifestations is senile plaques formed b Show more
Alzheimer's disease (AD) is a degenerative disease of the central nervous system. The pathogenesis is still not fully clear. One of the main histopathological manifestations is senile plaques formed by β-amyloid (Aβ) accumulation. Aβ is generated from the sequential proteolysis of amyloid precursor protein (APP) by β-secretase [i.e. β-site APP cleaving enzyme 1 (BACE1)] and γ-secretase, with a rate-limiting step controlled by BACE1 activity. Therefore, inhibiting BACE1 activity has become a potential therapeutic strategy for AD. The development of reliable detection methods for BACE1 activity plays an important role in early diagnosis of AD and evaluation of the therapeutic effect of new drugs for AD. This article has reviewed the recent advances in BACE1 activity detection techniques. The challenges of applying these analysis techniques to early clinical diagnosis of AD and development trends of the detection techniques have been prospected. Show less
no PDF DOI: 10.1080/10408347.2022.2132812
BACE1
Feiye Zhou, Chunxiang Sheng, Xiaoqin Ma +11 more · 2024 · Cell death & disease · Nature · added 2026-04-24
Elevated circulating branched-chain amino acids (BCAAs) are tightly linked to an increased risk in the development of type 2 diabetes mellitus. The rate limiting enzyme of BCAA catabolism branched-cha Show more
Elevated circulating branched-chain amino acids (BCAAs) are tightly linked to an increased risk in the development of type 2 diabetes mellitus. The rate limiting enzyme of BCAA catabolism branched-chain α-ketoacid dehydrogenase (BCKDH) is phosphorylated at E1α subunit (BCKDHA) by its kinase (BCKDK) and inactivated. Here, the liver-specific BCKDK or BCKDHA knockout mice displayed normal glucose tolerance and insulin sensitivity. However, knockout of BCKDK in the liver inhibited hepatic glucose production as well as the expression of key gluconeogenic enzymes. No abnormal gluconeogenesis was found in mice lacking hepatic BCKDHA. Consistent with the vivo results, BT2-mediated inhibition or genetic knockdown of BCKDK decreased hepatic glucose production and gluconeogenic gene expressions in primary mouse hepatocytes while BCKDK overexpression exhibited an opposite effect. Whereas, gluconeogenic gene expressions were not altered in BCKDHA-silenced hepatocytes. Mechanistically, BT2 treatment attenuated the interaction of cAMP response element binding protein (CREB) with CREB-binding protein and promoted FOXO1 protein degradation by increasing its ubiquitination. Our findings suggest that BCKDK regulates hepatic gluconeogenesis through CREB and FOXO1 signalings, independent of BCKDHA-mediated BCAA catabolism. Show less
📄 PDF DOI: 10.1038/s41419-024-07071-0
BCKDK
Quanjun Yang, Xinting Zhu, Ping Huang +13 more · 2024 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Altered branched chain amino acids (BCAAs), including leucine, isoleucine, and valine, are frequently observed in patients with advanced cancer. We evaluated the efficacy of chimeric antigen receptor Show more
Altered branched chain amino acids (BCAAs), including leucine, isoleucine, and valine, are frequently observed in patients with advanced cancer. We evaluated the efficacy of chimeric antigen receptor (CAR) T cell-mediated cancer cell lysis potential in the immune microenvironment of BCAA supplementation and deletion. BCAA supplementation increased cancer cell killing percentage, while accelerating BCAA catabolism and decreasing BCAA transporter decreased cancer cell lysis efficacy. We thus designed BCKDK engineering CAR T cells for the reprogramming of BCAA metabolism in the tumor microenvironment based on the genotype and phenotype modification. BCKDK overexpression (OE) in CAR-T cells significantly improved cancer cell lysis, while BCKDK knockout (KO) resulted in inferior lysis potential. In an in vivo experiment, BCKDK-OE CAR-T cell treatment significantly prolonged the survival of mice bearing NALM6-GL cancer cells, with the differentiation of central memory cells and an increasing proportion of CAR-T cells in the peripheral circulation. BCKDK-KO CAR-T cell treatment resulted in shorter survival and a decreasing percentage of CAR-T cells in the peripheral circulation. In conclusion, BCKDK-engineered CAR-T cells exert a distinct phenotype for superior anticancer efficiency. Show less
📄 PDF DOI: 10.1016/j.ymthe.2024.05.017
BCKDK
Liming Yu, Tao Huang, Jikai Zhao +10 more · 2024 · Free radical biology & medicine · Elsevier · added 2026-04-24
Metabolic reprogramming of vascular smooth muscle cell (VSMC) plays a critical role in the pathogenesis of thoracic aortic dissection (TAD). Previous researches have mainly focused on dysregulation of Show more
Metabolic reprogramming of vascular smooth muscle cell (VSMC) plays a critical role in the pathogenesis of thoracic aortic dissection (TAD). Previous researches have mainly focused on dysregulation of fatty acid or glucose metabolism, while the impact of amino acids catabolic disorder in VSMCs during the development of TAD remains elusive. Here, we identified branched-chain amino acid (BCAA) catabolic defect as a metabolic hallmark of TAD. The bioinformatics analysis and data from human aorta revealed impaired BCAA catabolism in TAD individuals. This was accompanied by upregulated branched-chain α-ketoacid dehydrogenase kinase (BCKDK) expression and BCKD E1 subunit alpha (BCKDHA) phosphorylation, enhanced vascular inflammation, and hyperactivation of mTOR signaling. Further in vivo experiments demonstrated that inhibition of BCKDK with BT2 (a BCKDK allosteric inhibitor) treatment dephosphorylated BCKDHA and re-activated BCAA catabolism, attenuated VSMCs phenotypic switching, alleviated aortic remodeling, mitochondrial reactive oxygen species (ROS) damage and vascular inflammation. Additionally, the beneficial actions of BT2 were validated in a TNF-α challenged murine VSMC cell line. Meanwhile, rapamycin conferred similar beneficial effects against VSMC phenotypic switching, cellular ROS damage as well as inflammatory response. However, co-treatment with MHY1485 (a classic mTOR activator) reversed the beneficial effects of BT2 by reactivating mTOR signaling. Taken together, the in vivo and in vitro evidence showed that impairment of BCAA catabolism resulted in aortic accumulation of BCAA and further caused VSMC phenotypic switching, mitochondrial ROS damage and inflammatory response via mTOR hyperactivation. BCKDK and mTOR signaling may serve as the potential drug targets for the prevention and treatment of TAD. Show less
no PDF DOI: 10.1016/j.freeradbiomed.2023.11.002
BCKDK
Yayan Feng, Xiaoyu Yang, Yuan Hou +7 more · 2024 · Alzheimer's & dementia : the journal of the Alzheimer's Association · Wiley · added 2026-04-24
Transposable element (TE) dysregulation is associated with neuroinflammation in Alzheimer's disease (AD) brains. Yet, TE quantitative trait loci (teQTL) have not been well characterized in human aged Show more
Transposable element (TE) dysregulation is associated with neuroinflammation in Alzheimer's disease (AD) brains. Yet, TE quantitative trait loci (teQTL) have not been well characterized in human aged brains with AD. We leveraged large-scale bulk and single-cell RNA sequencing, whole-genome sequencing (WGS), and xQTL from three human AD brain biobanks to characterize TE expression dysregulation and experimentally validate AD-associated TEs using CRISPR interference (CRISPRi) assays in human induced pluripotent stem cell (iPSC)-derived neurons. We identified 26,188 genome-wide significant TE expression QTLs (teQTLs) in human aged brains. Subsequent colocalization analysis of teQTLs with AD genetic loci identified AD-associated teQTLs and linked locus TEs. Using CRISPRi assays, we pinpointed a neuron-specific suppressive role of the activated short interspersed nuclear element (SINE; chr11:47608036-47608220) on expression of C1QTNF4 via reducing neuroinflammation in human iPSC-derived neurons. We identified widespread TE dysregulation in human AD brains and teQTLs offer a complementary analytic approach to identify likely AD risk genes. Widespread transposable element (TE) dysregulations are observed in human aging brains with degrees of neuropathology, apolipoprotein E (APOE) genotypes, and neuroinflammation in Alzheimer's disease (AD). A catalog of TE quantitative trait loci (teQTLs) in human aging brains was created using matched RNA sequencing and whole-genome sequencing data. CRISPR interference assays reveal that an upregulated intergenic TE from the MIR family (chr11: 47608036-47608220) suppresses expression of its nearest anti-inflammatory gene C1QTNF4 in human induced pluripotent stem cell-derived neurons. Show less
📄 PDF DOI: 10.1002/alz.14164
C1QTNF4
Xiaoke Ge, Bram Slütter, Joost M Lambooij +14 more · 2024 · iScience · Elsevier · added 2026-04-24
The liver X receptor (LXR) is considered a therapeutic target for atherosclerosis treatment, but synthetic LXR agonists generally also cause hepatic steatosis and hypertriglyceridemia. Desmosterol, a Show more
The liver X receptor (LXR) is considered a therapeutic target for atherosclerosis treatment, but synthetic LXR agonists generally also cause hepatic steatosis and hypertriglyceridemia. Desmosterol, a final intermediate in cholesterol biosynthesis, has been identified as a selective LXR ligand that suppresses inflammation without inducing lipogenesis. Δ24-Dehydrocholesterol reductase (DHCR24) converts desmosterol into cholesterol, and we previously showed that the DHCR24 inhibitor SH42 increases desmosterol to activate LXR and attenuate experimental peritonitis and metabolic dysfunction-associated steatotic liver disease. Here, we aimed to evaluate the effect of SH42 on atherosclerosis development in APOE∗3-Leiden.CETP mice and low-density lipoproteins (LDL) receptor knockout mice, models for lipid- and inflammation-driven atherosclerosis, respectively. In both models, SH42 increased desmosterol without affecting plasma lipids. While reducing liver lipids in APOE∗3-Leiden.CETP mice, and regulating populations of circulating monocytes in LDL receptor knockout mice, SH42 did not attenuate atherosclerosis in either model. Show less
📄 PDF DOI: 10.1016/j.isci.2024.109830
CETP
Hongxuan Du, Kaiying He, Jing Zhao +3 more · 2024 · PeerJ · added 2026-04-24
Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM) that is closely related to aging. In this study, we found co-differential genes between DKD and aging and established Show more
Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM) that is closely related to aging. In this study, we found co-differential genes between DKD and aging and established a diagnostic model of DKD based on these genes. Differentially expressed genes (DEGs) in DKD were screened using GEO datasets. The intersection of the DEGs of DKD and aging-related genes revealed DKD and aging co-differential genes. Based on this, a genetic diagnostic model for DKD was constructed using LASSO regression. The characteristics of these genes were investigated using consensus clustering, WGCNA, functional enrichment, and immune cell infiltration. Finally, the expression of diagnostic model genes was analyzed using single-cell RNA sequencing (scRNA-seq) in DKD mice (model constructed by streptozotocin (STZ) injection and confirmed by tissue section staining). First, there were 159 common differential genes between DKD and aging, 15 of which were significant. These co-differential genes were involved in stress, glucolipid metabolism, and immunological functions. Second, a genetic diagnostic model (including IGF1, CETP, PCK1, FOS, and HSPA1A) was developed based on these genes. Validation of these model genes in scRNA-seq data revealed statistically significant variations in FOS, HSPA1A, and PCK1 gene expression between the early DKD and control groups. Validation of these model genes in the kidneys of DKD mice revealed that Igf1, Fos, Pck1, and Hspa1a had lower expression in DKD mice, with Igf1 expression being statistically significant. Our findings suggest that DKD and aging co-differential genes are significant in DKD diagnosis, providing a theoretical basis for novel research directions on DKD. Show less
📄 PDF DOI: 10.7717/peerj.17046
CETP
Xiong Gao, Wei Luo, Liyuan Qu +14 more · 2024 · European journal of preventive cardiology · Oxford University Press · added 2026-04-24
The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA Show more
The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA remains controversial. The study aimed to investigate the genetic association between lipid-lowering drugs and AA. Our research used publicly available data on genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) studies. Genetic instruments, specifically eQTLs related to drug-target genes and SNPs (single nucleotide polymorphisms) located near or within the drug-target loci associated with low-density lipoprotein cholesterol (LDL-C), have been served as proxies for lipid-lowering medications. Drug-Target Mendelian Randomization (MR) study is used to determine the causal association between lipid-lowering drugs and different types of AA. The MR analysis revealed that higher expression of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase) was associated with increased risk of AA (OR = 1.58, 95% CI = 1.20-2.09, P = 1.20 × 10-03) and larger lumen size (aortic maximum area: OR = 1.28, 95% CI = 1.13-1.46, P = 1.48 × 10-04; aortic minimum area: OR = 1.26, 95% CI = 1.21-1.42, P = 1.78 × 10-04). PCSK9 (proprotein convertase subtilisin/kexin type 9) and CETP (cholesteryl ester transfer protein) show a suggestive relationship with AA (PCSK9: OR = 1.34, 95% CI = 1.10-1.63, P = 3.07 × 10-03; CETP: OR = 1.38, 95% CI = 1.06-1.80, P = 1.47 × 10-02). No evidence to support genetically mediated NPC1L1 (Niemann-Pick C1-Like 1) and LDLR (low-density lipoprotein cholesterol receptor) are associated with AA. This study provides causal evidence for the genetic association between lipid-lowering drugs and AA. Higher gene expression of HMGCR, PCSK9, and CETP increases AA risk. Furthermore, HMGCR inhibitors may link with smaller aortic lumen size. Show less
no PDF DOI: 10.1093/eurjpc/zwae044
CETP
Rachel R Reith, Mackenzie C Batt, Anna M Fuller +8 more · 2024 · Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · SAGE Publications · added 2026-04-24
Thirteen American Hereford cattle were reported blind with presumed onset when ~12-mo-old. All blind cattle shared a common ancestor through both the maternal and paternal pedigrees, suggesting a rece Show more
Thirteen American Hereford cattle were reported blind with presumed onset when ~12-mo-old. All blind cattle shared a common ancestor through both the maternal and paternal pedigrees, suggesting a recessive genetic origin. Given the pedigree relationships and novel phenotype, we characterized the ophthalmo-pathologic changes associated with blindness and identified the responsible gene variant. Ophthalmologic examinations of 5 blind cattle revealed retinal degeneration. Histologically, 2 blind cattle had loss of the retinal photoreceptor layer. Whole-genome sequencing (WGS) of 7 blind cattle and 9 unaffected relatives revealed a 1-bp frameshift deletion in ceroid lipofuscinosis neuronal 3 ( Show less
no PDF DOI: 10.1177/10406387241239918
CLN3
Siyuan Chen, Qin Tang, Manqiu Hu +13 more · 2024 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Numerous studies have shown that metabolic reprogramming is crucial for the development of HCC. Carbamoyl phosphate synthase Show more
Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Numerous studies have shown that metabolic reprogramming is crucial for the development of HCC. Carbamoyl phosphate synthase 1 (CPS1), a rate-limiting enzyme in urea cycle, is an abundant protein in normal hepatocytes, however, lacking systemic research in HCC. It is found that CPS1 is low-expressed in HCC tissues and circulating tumor cells, negatively correlated with HCC stage and prognosis. Further study reveals that CPS1 is a double-edged sword. On the one hand, it inhibits the activity of phosphatidylcholine-specific phospholipase C to block the biosynthesis of diacylglycerol (DAG), leading to the downregulation of the DAG/protein kinase C pathway to inhibit invasion and metastasis of cancer cells. On the other hand, CPS1 promotes cell proliferation by increasing intracellular S-adenosylmethionin to enhance the m6A modification of solute carrier family 1 member 3 mRNA, a key transporter for aspartate intake. Finally, CPS1 overexpressing adeno-associated virus can dampen HCC progression. Collectively, this results uncovered that CPS1 is a switch between HCC proliferation and metastasis by increasing intracellular aspartate level. Show less
📄 PDF DOI: 10.1002/advs.202402703
CPS1
Xiao-Meng Sun, Xin Wu, Meng-Guang Wei +5 more · 2024 · Frontiers in pharmacology · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fphar.2024.1437738
CPS1
Ke Wang, Yuankui Zhu, Mengqing Li +7 more · 2024 · Biomaterials research · added 2026-04-24
Acute liver failure (ALF) is a complex syndrome that impairs the liver's function to detoxify bilirubin, ammonia, and other toxic metabolites. Bioartificial liver (BAL) aims to help ALF patients to pa Show more
Acute liver failure (ALF) is a complex syndrome that impairs the liver's function to detoxify bilirubin, ammonia, and other toxic metabolites. Bioartificial liver (BAL) aims to help ALF patients to pass through the urgent period by temporarily undertaking the liver's detoxification functions and promoting the recovery of the injured liver. We genetically modified the hepatocellular cell line HepG2 by stably overexpressing genes encoding UGT1A1, OATP1B1, OTC, ARG1, and CPS1. The resulting SynHeps-II cell line, encapsulated by Cytopore microcarriers, dramatically reduced the serum levels of bilirubin and ammonia, as demonstrated both in vitro using patient plasma and in vivo using ALF animal models. More importantly, we have also completed the 3-dimensional (3D) culturing of cells to meet the demands for industrialized rapid and mass production, and subsequently assembled the plasma-cell contacting BAL (PCC-BAL) system to fulfill the requirements of preclinical experiments. Extracorporeal blood purification of ALF rabbits with SynHeps-II-embedded PCC-BAL saved more than 80% of the animals from rapid death. Mechanistically, SynHeps-II therapy ameliorated liver and brain inflammation caused by high levels of bilirubin and ammonia and promoted liver regeneration by modulating the nuclear factor κB (NF-κB) and signal transducer and activator of transcription 3 (STAT3) pathways. Also, SynHeps-II treatment reduced cerebral infiltration of neutrophils, reduced reactive oxygen species (ROS) levels, and mitigated hepatic encephalopathy. Taken together, SynHeps-II cell-based BAL was promising for the treatment of ALF patients and warrants clinical trials. Show less
📄 PDF DOI: 10.34133/bmr.0043
CPS1
Yu Chen, Yupeng Jiang, Xionghui Li +6 more · 2024 · Translational lung cancer research · added 2026-04-24
Vitamins, and their metabolic processes play essential regulatory roles in controlling proliferation, differentiation, and growth in carcinogenesis. However, the role of vitamin metabolism in lung ade Show more
Vitamins, and their metabolic processes play essential regulatory roles in controlling proliferation, differentiation, and growth in carcinogenesis. However, the role of vitamin metabolism in lung adenocarcinoma (LUAD) has rarely been reported. Here, we established a novel prognostic model based on vitamin metabolism-related genes in LUAD. In this research, we aimed to identify vitamin metabolism associated with differentially expressed genes (DEGs) in LUAD utilizing The Cancer Genome Atlas (TCGA)-LUAD, GSE68465 and GSE72094 data. Unsupervised clustering classified patients into distinct subgroups. By utilizing least absolute shrinkage and selection operator (LASSO)-Cox regression analysis, vitamin metabolism-related genes could be used to construct prognostic model. Then the vitamin metabolism gene-related risk score (VRS) was calculated based on best cut-off splitting. Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC) analysis, univariate and multivariate Cox analyses, chemotherapeutic drugs sensitivity analysis, immune infiltration analysis and nomogram were conducted to verify our models' accuracy. Finally, CPS1 was identified as a relevant diagnostic marker using Random Forests algorithms, single-cell RNA sequencing data was used to confirm its expression. We investigated the relationship between vitamin metabolism patterns, overall survival (OS), and immune infiltration levels of patients with LUAD. A prognostic signature consisting of 11 genes was developed, which was able to classify patients into high and low VRS groups. Through gene enrichment analysis, cell cycle was mainly enriched. Compared to the low VRS group, the high VRS group exhibited poorer OS, as demonstrated by the Kaplan-Meier survival analysis. Furthermore, VRS was identified as an independent predictor of poor prognosis and poor OS, as indicated by both univariate and multivariate Cox regression analyses. Additionally, a nomogram was constructed to improve the accuracy of survival predictions in LUAD patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs. CPS1 was identified as a relevant diagnostic marker and the expression was also as confirmed by single-cell RNA sequencing data. Overall, our findings suggest that vitamin metabolism can influence the prognosis of LUAD patients, and our prognostic signature represents a potentially helpful resource for predicting patient outcomes and informing clinical decision-making. Show less
📄 PDF DOI: 10.21037/tlcr-24-245
CPS1
Xiujuan Li, Man Xu, Ke Zhou +5 more · 2024 · Frontiers in plant science · Frontiers · added 2026-04-24
Among the bioactive compounds, lipid-soluble tanshinone is present in
📄 PDF DOI: 10.3389/fpls.2024.1356922
CPS1
Weiwei Chen, Menghua Zhou, Bingjie Guan +6 more · 2024 · Clinical and translational medicine · Wiley · added 2026-04-24
Metastasis accounts for the majority of deaths among patients with colorectal cancer (CRC). Here, the regulatory role of tumour-associated macrophages (TAMs) in CRC metastasis was explored. Immunohist Show more
Metastasis accounts for the majority of deaths among patients with colorectal cancer (CRC). Here, the regulatory role of tumour-associated macrophages (TAMs) in CRC metastasis was explored. Immunohistochemical (IHC) analysis of the TAM biomarker CD163 was conducted to evaluate TAM infiltration in CRC. Transwell assays and an ectopic liver metastasis model were established to evaluate the metastatic ability of tumour cells. RNA sequencing (RNA-seq) and liquid chromatography-mass spectrometry (LC-MS) were applied to identify the differentially expressed genes and proteins in CRC cells and in TAM-derived extracellular vesicles (EVs). Cholesterol content measurement, a membrane fluidity assay and filipin staining were performed to evaluate cholesterol efflux in CRC cells. Our results showed that TAM infiltration is positively correlated with CRC metastasis. TAMs can facilitate the migration and invasion of MC-38 and CT-26 cells via EVs. According to the RNA-seq data, TAM-EVs increase cholesterol efflux and enhance membrane fluidity in CRC cells by regulating ABCA1 expression, thus affecting the motility of CRC cells. Mechanistically, DOCK7 packaged in TAM-EVs can activate RAC1 in CRC cells and subsequently upregulate ABCA1 expression by phosphorylating AKT and FOXO1. Moreover, IHC analysis of ABCA1 in patients with liver-metastatic CRC indicated that ABCA1 expression is significantly greater in metastatic liver nodules than in primary CRC tumours. Overall, our findings suggest that DOCK7 delivered via TAM-EVs could regulate cholesterol metabolism in CRC cells and CRC cell metastasis through the RAC1/AKT/FOXO1/ABCA1 axis. DOCK7 could thus be a new therapeutic target for controlling CRC metastasis. Show less
📄 PDF DOI: 10.1002/ctm2.1591
DOCK7
Shushu Wang, Kachun Lu, Liwen Lin +9 more · 2024 · PloS one · PLOS · added 2026-04-24
Atherosclerosis (AS) and Non-alcoholic fatty liver disease (NAFLD) are chronic metabolic disorders with high prevalence and significant health impacts. Both conditions share common pathophysiological Show more
Atherosclerosis (AS) and Non-alcoholic fatty liver disease (NAFLD) are chronic metabolic disorders with high prevalence and significant health impacts. Both conditions share common pathophysiological pathways including abnormal lipid metabolism and inflammation. Berberine (BBR), an isoquinoline alkaloid, is known for its beneficial effects on various metabolic and cardiovascular disorders. This study investigates BBR's impact on AS and NAFLD through bioinformatics analysis and experimental models. This study utilized various bioinformatics methods, including transcriptome analysis, weighted gene co-expression network analysis (WGCNA), machine learning, and molecular docking, to identify key genes and pathways involved in AS and NAFLD. Subsequently an animal model of AS combined with NAFLD was established using ApoE-/- mice fed a high-fat diet. The efficacy and mechanism of action of BBR were verified using methods such as hematoxylin and eosin (HE) staining, Oil Red O staining, and real-time quantitative PCR (RTqPCR). Through transcriptome analysis, WGCNA, and machine learning, this study identified 48 key genes involved in both AS and NAFLD. Function analysis revealed that the implicated genes were significantly involved in pathways like cytokine-cytokine receptor interaction, chemokine signaling, and IL-17 signaling pathway, suggesting their role in inflammation and immune responses. Single cell validation identified six key genes: dual specificity phosphatase 6 (DUSP6), chemokine ligand 3 (CCL3), complement component 5a receptor 1 (C5AR1), formyl peptide receptor 1 (FPR1), myeloid nuclear differentiation antigen (MNDA), and proviral integration site of murine 2(PIM2). Finally, molecular docking and animal experiments showed that BBR significantly reduced lipid deposits and inflammatory markers in liver and aortic tissues. In conclusion, BBR can improve AS combined with NAFLD by regulating genes like MNDA, PIM2, DUSP6, CCL3, C5AR1, and FPR1, with the mechanism related to inflammation control. The findings suggest potential clinical benefits of BBR in reducing the progression of both AS and NAFLD, warranting further investigation. Show less
📄 PDF DOI: 10.1371/journal.pone.0314961
DUSP6
Chao Song, Ling Wang, Fei Zhang +4 more · 2024 · International journal of biological macromolecules · Elsevier · added 2026-04-24
During a sepsis infection, the lung is extremely susceptible to damage. A condition known as acute respiratory distress syndrome (ARDS) may develop in extreme circumstances. The primary objective of t Show more
During a sepsis infection, the lung is extremely susceptible to damage. A condition known as acute respiratory distress syndrome (ARDS) may develop in extreme circumstances. The primary objective of this research is to identify important genes that are related with both sepsis and lung injury. These genes have the potential to act as novel biomarkers in the investigation of sepsis-induced lung injury prevention strategies. It was possible to download from GEO data both the sepsis-related dataset (GSE64457) and the lung injury-related dataset (GSE40839). In the GSE64457 dataset, using the "limma" package in R revealed 429 differentially expressed genes (DEGs) with logFC values more than or equal to -1 and p values <0.05. There were 266 genes that were up-regulated and 163 genes that were down-regulated. Through the use of Gene Ontology (GO), it was discovered that the majority of the DEGs were associated with the inflammatory response (BP terms), a particular granule lumen (CC terms), and protein binding (MF terms). By doing a pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG), researchers were able to identify DEGs that were mostly associated with the NOD-like receptor signalling pathway, the TNF signalling pathway, and Epstein-Barr virus infection. Within the GSE40839 dataset, Weighted Gene Co-Expression Network Analysis (WGCNA) yielded a total of 7 modules, from which it was possible to screen out 2 critical modules and 693 key genes. The important genes and DEGs were both subjected to a Venn analysis. Finally, 14 genes that overlapped (ARL4A, LAIR1, MTHFD2, TSPAN13, DUSP6, PECR, CBS, TES, ASNS, SYNE1, FGF13, LCN2, KLF10, BCAT1) were closely associated to the incidence and development of sepsis-induced lung injury. This indicates that these genes are the essential genes to avoid the occurrence of sepsis-induced lung injury. This study provides novel strategies for preventing lung harm brought on by sepsis. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.135117
DUSP6
Jaclyn R Stonebraker, Rhonda G Pace, Paul J Gallins +15 more · 2024 · Hepatology (Baltimore, Md.) · added 2026-04-24
It is not known why severe cystic fibrosis (CF) liver disease (CFLD) with portal hypertension occurs in only ~7% of people with CF. We aimed to identify genetic modifiers for severe CFLD to improve un Show more
It is not known why severe cystic fibrosis (CF) liver disease (CFLD) with portal hypertension occurs in only ~7% of people with CF. We aimed to identify genetic modifiers for severe CFLD to improve understanding of disease mechanisms. Whole-genome sequencing was available in 4082 people with CF with pancreatic insufficiency (n = 516 with severe CFLD; n = 3566 without CFLD). We tested ~15.9 million single nucleotide polymorphisms (SNPs) for association with severe CFLD versus no-CFLD, using pre-modulator clinical phenotypes including (1) genetic variant ( SERPINA1 ; Z allele) previously associated with severe CFLD; (2) candidate SNPs (n = 205) associated with non-CF liver diseases; (3) genome-wide association study of common/rare SNPs; (4) transcriptome-wide association; and (5) gene-level and pathway analyses. The Z allele was significantly associated with severe CFLD ( p = 1.1 × 10 -4 ). No significant candidate SNPs were identified. A genome-wide association study identified genome-wide significant SNPs in 2 loci and 2 suggestive loci. These 4 loci contained genes [significant, PKD1 ( p = 8.05 × 10 -10 ) and FNBP1 ( p = 4.74 × 10 -9 ); suggestive, DUSP6 ( p = 1.51 × 10 -7 ) and ANKUB1 ( p = 4.69 × 10 -7 )] relevant to severe CFLD pathophysiology. The transcriptome-wide association identified 3 genes [ CXCR1 ( p = 1.01 × 10 -6 ) , AAMP ( p = 1.07 × 10 -6 ), and TRBV24 ( p = 1.23 × 10 -5 )] involved in hepatic inflammation and innate immunity. Gene-ranked analyses identified pathways enriched in genes linked to multiple liver pathologies. These results identify loci/genes associated with severe CFLD that point to disease mechanisms involving hepatic fibrosis, inflammation, innate immune function, vascular pathology, intracellular signaling, actin cytoskeleton and tight junction integrity and mechanisms of hepatic steatosis and insulin resistance. These discoveries will facilitate mechanistic studies and the development of therapeutics for severe CFLD. Show less
📄 PDF DOI: 10.1097/HEP.0000000000000863
DUSP6
Lingang Dai, Dongwei An, Jiajin Huang +7 more · 2024 · International journal of biological macromolecules · Elsevier · added 2026-04-24
The kidding traits of goats are an important index of production. However, the molecular regulatory mechanisms of kidding traits in goats have not been fully elucidated. This study aimed to investigat Show more
The kidding traits of goats are an important index of production. However, the molecular regulatory mechanisms of kidding traits in goats have not been fully elucidated. This study aimed to investigate the molecular regulatory network of kidding traits in goats. Multi-omics revealed the enrichment of 10 signaling pathways, with fatty acid biosynthesis, biosynthesis of unsaturated fatty acids, and steroid hormone biosynthesis pathways being closely related to reproduction. Interestingly, the key rate-limiting enzymes, fatty acid synthase (FASN), stearoyl-CoA desaturase 5 (SCD5), fatty acid desaturase 1 (FADS1), 3β-hydroxysteroid dehydrogenase/isomerase (3BHSD), and steroidogenic acute regulatory protein (STAR) enriched in these pathways regulate changes in reproduction-related metabolites. In interference experiments, it was observed that suppressing these key rate-limiting enzymes inhibited the expression of CYP19A1, ESR2, and FSHR. Furthermore, interference inhibited granulosa cell proliferation, caused cell cycle arrest, and promoted apoptosis. Thus, these results suggest that the specific markers of nanny goats with multiple kids are the key rate-limiting enzymes FASN, SCD5, FADS1, 3BHSD, and STAR. These findings may greatly enhance the understanding of regulatory mechanisms that govern goat parturition. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.136737
FADS1
Liu Yang, Hongwei Yin, Lijing Bai +20 more · 2024 · Genome biology · BioMed Central · added 2026-04-24
Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. We present a comprehensive SV catalog based on the whole-genome sequence of 106 Show more
Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies. This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution. Show less
📄 PDF DOI: 10.1186/s13059-024-03253-3
FADS3
Shuai Fan, Yuxin Chen, Wenyu Wang +7 more · 2024 · Current issues in molecular biology · MDPI · added 2026-04-24
FGFR1 is a key member of the fibroblast growth factor receptor family, mediating critical signaling pathways such as RAS-MAPK and PI3K-AKT. which are integral to regulating essential cellular processe Show more
FGFR1 is a key member of the fibroblast growth factor receptor family, mediating critical signaling pathways such as RAS-MAPK and PI3K-AKT. which are integral to regulating essential cellular processes, including proliferation, differentiation, and survival. Alterations in FGFR1 can lead to constitutive activation of signaling pathways that drive oncogenesis by promoting uncontrolled cell division, inhibiting apoptosis, and enhancing the metastatic potential of cancer cells. This article reviews the activation mechanisms and signaling pathways of FGFR1 and provides a detailed exposition of the types of FGFR1 aberration. Furthermore, we have compiled a comprehensive overview of current therapies targeting FGFR1 aberration in cancer, aiming to offer new perspectives for future cancer treatments by focusing on drugs that address specific FGFR1 alterations. Show less
📄 PDF DOI: 10.3390/cimb46110783
FGFR1
Meiling Cheng, Yingmin Zhou, Qian Wang +6 more · 2024 · Molecular biology reports · Springer · added 2026-04-24
MicroRNAs can regulate various biological functions including cell proliferation, differentiation, embryo formation, and implantation. The giant panda exhibits embryonic diapause, with embryo developm Show more
MicroRNAs can regulate various biological functions including cell proliferation, differentiation, embryo formation, and implantation. The giant panda exhibits embryonic diapause, with embryo development resuming in late pregnancy. However, the changes in microRNAs during late pregnancy remain poorly understand. After mating, plasma samples were collected on day 40 of early pregnancy (EP; n = 3) and 30 days before delivery of late pregnancy (LP; n = 3). Following microRNAs screening, a total of 120 microRNAs were detected in the plasma exosomes of pregnant pandas. Nine differentially expressed microRNAs (DEmicroRNAs) were identified in LP compared to EP, including three that were upregulated and six that were downregulated. Notably, miR-25b and miR-47 were significantly downregulated in LP group. All DEmicroRNAs were predicted to target a total of 2,675 genes. Pathway enrichment analysis of these target genes revealed significant enrichment in the MAPK and Rap1 signaling pathways, which are closely related to cell proliferation, differentiation, and cell-cell and cell-matrix interactions. Analysis of protein-protein interaction networks showed that most of the hub genes (five out of eight), including Fgfr1, Fgf2, Fgf18, Erbb4, and Kras within the MAPK and Rap1 pathways are associated with the cell proliferation and differentiation. Significantly, Erbb4 was regulated by significantly differentially expressed miRNA-47. We suggest that plasma exosomal microRNAs are involved in cell proliferation and differentiation during embryonic development by regulating key hub genes within MAPK and Rap1 pathways. These findings provided new insights into the development of giant panda embryos. Show less
no PDF DOI: 10.1007/s11033-024-09988-3
FGFR1
Yang Pan, Xiangyu Chen, Hang Zhou +7 more · 2024 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Non-obstructive azoospermia (NOA) is a major contributor of male infertility. Herein, we used existing datasets to identify novel biomarkers for the diagnosis and prognosis of NOA, which could have gr Show more
Non-obstructive azoospermia (NOA) is a major contributor of male infertility. Herein, we used existing datasets to identify novel biomarkers for the diagnosis and prognosis of NOA, which could have great significance in the field of male infertility. NOA datasets were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT was utilized to analyze the distributions of 22 immune cell populations. Hub genes were identified by applying weighted gene co-expression network analysis (WGCNA), machine learning methods, and protein-protein interaction (PPI) network analysis. The expression of hub genes was verified in external datasets and was assessed by receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis (GSEA) was applied to explore the important functions and pathways of hub genes. The mRNA-microRNA (miRNA)-transcription factors (TFs) regulatory network and potential drugs were predicted based on hub genes. Single-cell RNA sequencing data from the testes of patients with NOA were applied for analyzing the distribution of hub genes in single-cell clusters. Furthermore, testis tissue samples were obtained from patients with NOA and obstructive azoospermia (OA) who underwent testicular biopsy. RT-PCR and Western blot were used to validate hub gene expression. Two immune-related oxidative stress hub genes ( It appears that Show less
📄 PDF DOI: 10.3389/fendo.2024.1356959
FGFR1
Randy F Sweis, Pablo Gajate, Rafael Morales-Barrera +12 more · 2024 · JAMA oncology · added 2026-04-24
The oral pan-fibroblast growth factor receptor inhibitor rogaratinib previously demonstrated encouraging safety and efficacy in a phase 1 study of patients with urothelial cancer (UC) overexpressing T Show more
The oral pan-fibroblast growth factor receptor inhibitor rogaratinib previously demonstrated encouraging safety and efficacy in a phase 1 study of patients with urothelial cancer (UC) overexpressing To evaluate the safety, pharmacokinetics, and preliminary efficacy of rogaratinib in combination with the programmed cell death 1 ligand 1 (PD-L1) inhibitor atezolizumab in cisplatin-ineligible patients with The FORT-2 nonrandomized clinical trial was an open-label, single-arm, multicenter study conducted between May 15, 2018, and July 16, 2021, in 30 centers across Asia, Europe, and North America. Eligible patients had locally advanced/metastatic UC with Patients received rogaratinib 600 mg or rogaratinib 800 mg twice daily in combination with intravenous atezolizumab 1200 mg every 21 days. Primary end points included safety, tolerability, and the recommended phase 2 dose (RP2D) of rogaratinib in combination with atezolizumab. Among 153 patients screened, 73 (48%) had tumors with In this phase 1b nonrandomized clinical trial, rogaratinib plus atezolizumab demonstrated a manageable safety profile, with no unexpected safety signals. Efficacy for this combination at the RP2D was observed in tumors with low PD-L1 and was not dependent on ClinicalTrials.gov Identifier: NCT03473756. Show less
📄 PDF DOI: 10.1001/jamaoncol.2024.3900
FGFR1
Huina Wang, Qingzhu Ding, Haihua Zhou +5 more · 2024 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Vasculogenic mimicry (VM) is a novel model for supplying blood to multiple tumors, including gastric cancer (GC), and is a potential target for its treatment. Dihydroartemisinin (DHA) is a potential n Show more
Vasculogenic mimicry (VM) is a novel model for supplying blood to multiple tumors, including gastric cancer (GC), and is a potential target for its treatment. Dihydroartemisinin (DHA) is a potential natural antitumor substance that inhibits the progression of tumors in many ways. The research aimed to evaluate the impact of DHA on VM formation and its mechanisms. The IC50 of DHA, DHA's effect on proliferation, invasion, and migration in GC cells and VM formation in both cell and animal models were determined through wound healing, MTT, EdU, colony formation, and Transwell assays. Genomics was employed to identify genes related to DHA inhibition of VM formation, and to analyze their relationship to VM formation. qRT‒PCR and western blot (WB) analysis were carried out to analyze the changes in protein and mRNA levels after DHA treatment and the changes in VM-associated protein biomarkers after blocking target gene-related pathways. The mechanism by which DHA inhibits VM in GC was elucidated in vivo. DHA reduced the invasion, proliferation, and migration of GC cells and inhibited VM in cells and in vivo. A total of 220 DEGs were identified in the DHA-treated HGC-27 cells. Among the 146 downregulated genes, fibroblast growth Factor 2 (FGF2) was most closely associated with angiogenesis and VM. The level of FGF2 in GC tissues with VM was markedly greater than in VM lacking tissues. Treatment with DHA or FGFR1 blockade suppressed VM formation and reduced VM-related biomarker proteins. DHA suppressed tumor progression and VM formation by reducing FGF2 in xenograft mouse models. Per our knowledge, this is the first study to demonstrate the inhibitory effect of DHA on VM, providing a novel strategy for the treatment of GC. Show less
no PDF DOI: 10.1016/j.phymed.2024.155962
FGFR1
Peng Zhou, Longfei Cheng, Hengxun Tao +8 more · 2024 · Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft · Elsevier · added 2026-04-24
Fibroblast growth factors (FGFs) are required for the specification and formation of the epibranchial placodes, which give rise to the distal part of the cranial sensory ganglia. However, it remains u Show more
Fibroblast growth factors (FGFs) are required for the specification and formation of the epibranchial placodes, which give rise to the distal part of the cranial sensory ganglia. However, it remains unclear whether FGFs play a role in regulating the neurite outgrowth of the epibranchial placode-derived ganglia during further development. Previous studies have shown that Fibroblast growth factor 8 (FGF8) promotes neurite outgrowth from the statoacoustic ganglion in vitro. However, these studies did not distinguish between the neural crest- and placode-derived components of the sensory ganglia. In this study, we focused on the petrosal and nodose ganglia as representatives of the epibranchial ganglia and investigated their axonal outgrowth under the influence of FGF8 signaling protein in vitro. To precisely isolate the placode-derived ganglion part, we labeled the placode and its derivatives with enhanced green fluorescent protein (EGFP) through electroporation. The isolated ganglia were then collected for qRT-PCR assay and cultured in a collagen gel with and without FGF8 protein. Our findings revealed that both placode-derived petrosal and nodose ganglia expressed FGFR1 and FGFR2. In culture, FGF8 exerted a neural trophic effect on the axon outgrowth of both ganglia. While the expression levels of FGFR1/2 were similar between the two ganglia, the petrosal ganglion exhibited greater sensitivity to FGF8 compared to the nodose ganglion. This indicates that the placode-derived ganglia have differential responsiveness to FGF8 signaling during axonal extension. Thus, FGF8 is not only required for the early development of the epibranchial placode, as shown in previous studies, but also promotes neurite outgrowth of placode-derived ganglia. Show less
no PDF DOI: 10.1016/j.aanat.2024.152323
FGFR1
Miao Wang, Kangting Luo, Tongtong Sha +7 more · 2024 · Nutrients · MDPI · added 2026-04-24
Excessive fluoride exposure induces skeletal fluorosis, but the specific mechanism responsible is still unclear. Therefore, this study aimed to identify the pathogenesis of fluoride-induced bone injur Show more
Excessive fluoride exposure induces skeletal fluorosis, but the specific mechanism responsible is still unclear. Therefore, this study aimed to identify the pathogenesis of fluoride-induced bone injuries. We systematically searched fluoride-induced bone injury-related genes from five databases. Then, these genes were subjected to enrichment analyses. A TF (transcription factor)-mRNA-miRNA network and protein-protein interaction (PPI) network were constructed using Cytoscape, and the Human Protein Atlas (HPA) database was used to screen the expression of key proteins. The candidate pharmacological targets were predicted using the Drug Signature Database. A total of 85 studies were included in this study, and 112 osteoblast-, 35 osteoclast-, and 41 chondrocyte-related differential expression genes (DEGs) were identified. Functional enrichment analyses showed that the Atf4, Bcl2, Col1a1, Fgf21, Fgfr1 and Il6 genes were significantly enriched in the PI3K-Akt signaling pathway of osteoblasts, Mmp9 and Mmp13 genes were enriched in the IL-17 signaling pathway of osteoclasts, and Bmp2 and Bmp7 genes were enriched in the TGF-beta signaling pathway of chondrocytes. With the use of the TF-mRNA-miRNA network, the Col1a1, Bcl2, Fgfr1, Mmp9, Mmp13, Bmp2, and Bmp7 genes were identified as the key regulatory factors. Selenium methyl cysteine, CGS-27023A, and calcium phosphate were predicted to be the potential drugs for skeletal fluorosis. These results suggested that the PI3K-Akt signaling pathway being involved in the apoptosis of osteoblasts, with the IL-17 and the TGF-beta signaling pathways being involved in the inflammation of osteoclasts and chondrocytes in fluoride-induced bone injuries. Show less
📄 PDF DOI: 10.3390/nu16152500
FGFR1
Bihui Jin, Guanyu Su, Xiao Zhou +6 more · 2024 · Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics · added 2026-04-24
no PDF DOI: 10.1089/jop.2024.0042
FGFR1
Xue Zhu, Ling Wang, Ke Wang +2 more · 2024 · Free radical biology & medicine · Elsevier · added 2026-04-24
Uveal melanoma (UM) is a rare yet lethal primary intraocular malignancy affecting adults. Analysis of data from The Cancer Genome Atlas (TCGA) database revealed that FGFR1 expression was increased in Show more
Uveal melanoma (UM) is a rare yet lethal primary intraocular malignancy affecting adults. Analysis of data from The Cancer Genome Atlas (TCGA) database revealed that FGFR1 expression was increased in UM tumor tissues and was linked to aggressive behavior and a poor prognosis. This study assessed the anti-tumor effects of Erdafitinib, a selective pan-FGFR inhibitor, in both in vitro and in vivo UM models. Erdafitinib exhibited a robust anti-cancer activity in UM through inducing ferroptosis in the FGFR1-dependent manner. Transcriptomic data revealed that Erdafitinib mediated its anti-cancer effects via modulating the ferritinophagy/lysosome biogenesis. Subsequent research revealed that Erdafitinib exerted its effects by reducing the expression of FGFR1 and inhibiting the activity of mTORC1 in UM cells. Concurrently, it enhanced the dephosphorylation, nuclear translocation, and transcriptional activity of TFEB. The aggregation of TFEB in nucleus triggered FTH1-dependent ferritinophagy, leading to lysosomal activation and iron overload. Conversely, the overexpression of FGFR1 served to mitigate the effects of Erdafitinib on ferritinophagy, lysosome biogenesis, and the activation of the mTORC1/TFEB signaling pathway. In vivo experiments have convincingly shown that Erdafitinib markedly curtails tumor growth in an UM xenograft mouse model, an effect that is closely correlated with a decrease in FGFR1 expression levels. The present study is the first to demonstrate that Erdafitinib powerfully induces ferroptosis in UM by orchestrating the ferritinophagy and lysosome biogenesis via modulating the FGFR1/mTORC1/TFEB signaling. Consequently, Erdafitinib emerges as a strong candidate for clinical trial investigation, and FGFR1 emerges as a novel and promising therapeutic target in the treatment of UM. Show less
no PDF DOI: 10.1016/j.freeradbiomed.2024.07.002
FGFR1