👤 Youchen Li

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Also published as: A Li, Ai-Jun Li, Ai-Qin Li, Ailing Li, Aimin Li, Aixin Li, Alexander H Li, Alexander Li, Amy Li, An-Qi Li, AnHai Li, Anan Li, Andrew C Li, Ang Li, Anna Fen-Yau Li, Annie Li, Anqi Li, Anyao Li, Ao Li, Aowen Li, Aoxi Li, Audrey Li, Bai-Qiang Li, Baichuan Li, Baiqiang Li, Baixing Li, Baizhou Li, Bang-Yan Li, Bao Li, Bao-Shan Li, Baoguang Li, Baoguo Li, Baohong Li, Baohua Li, Baolin Li, Baoqi Li, Baoqing Li, Baosheng Li, Baoting Li, Bei Li, Bei-Bei Li, Beibei Li, Beixu Li, Ben Li, Ben-Shang Li, Benyi Li, Biao Li, Bichun Li, Bin Li, Bin-Kui Li, Binbin Li, Bing Li, Bing-Heng Li, Bing-Hui Li, Bing-Mei Li, Bingbing Li, Binghu Li, Binghua Li, Bingjie Li, Bingjue Li, Bingkun Li, Binglan Li, Bingong Li, Bingshan Li, Bingsheng Li, Bingsong Li, Bingxin Li, Binjun Li, Binkui Li, Binru Li, Binxing Li, Biyu Li, Bizhi Li, Bo Li, BoWen Li, Bohao Li, Bohua Li, Bolun Li, Boru Li, Botao Li, Boxuan Li, Boya Li, Boyang Li, Bugao Li, C H Li, C Li, C X Li, C Y Li, Caesar Z Li, Cai Li, Cai-Hong Li, Caihong Li, Caili Li, Caixia Li, Caiyu Li, Caiyun Li, Can Li, Cang Li, Caolong Li, Chang Li, Chang-Da Li, Chang-Ping Li, Chang-Sheng Li, Chang-Yan Li, Chang-hai Li, Changcheng Li, Changgui Li, Changhong Li, Changhui Li, Changjiang Li, Changkai Li, Changqing Li, Changwei Li, Changxian Li, Changyan Li, Changyu Li, Changzheng Li, Chanjuan Li, Chanyuan Li, Chao Bo Li, Chao Li, Chaochen Li, Chaojie Li, Chaonan Li, Chaoqian Li, Chaowei Li, Chaoying Li, Chen Li, Chen-Chen Li, Chen-Lu Li, Chen-Xi Li, Chenfeng Li, Cheng Li, Cheng-Lin Li, Cheng-Tian Li, Cheng-Wei Li, Chengbin Li, Chengcheng Li, Chenghao Li, Chenghong Li, Chengjian Li, Chengjun Li, Chenglan Li, Chenglong Li, Chengnan Li, Chengping Li, Chengqian Li, Chengquan Li, Chengsi Li, Chenguang Li, Chengwen Li, Chengxin Li, Chengyun Li, Chenhao Li, Chenjie Li, Chenli Li, Chenlin Li, Chenlong Li, Chenlu Li, Chenmeng Li, Chenrui Li, Chensheng Li, Chenwen Li, Chenxi Li, Chenxiao Li, Chenxin Li, Chenxuan Li, Chenyang Li, Chenyao Li, Chenyu Li, Cheung Li, Chi-Ming Li, Chi-Yuan Li, Chia Li, Chia-Yang Li, Chien-Feng Li, Chien-Hsiu Li, Chien-Te Li, Chih-Chi Li, Chitao Li, Chiyang Li, Chong Li, Chongyang Li, Chongyi Li, Chris Li, Chu-Qiao Li, Chuan F Li, Chuan Li, Chuan-Hai Li, Chuan-Yun Li, Chuanbao Li, Chuanfang Li, Chuang Li, Chuangpeng Li, Chuanning Li, Chuanyin Li, Chumei Li, Chun Li, Chun-Bo Li, Chun-Lai Li, Chun-Mei Li, Chun-Quan Li, Chun-Xiao Li, Chun-Xu Li, Chung-Hao Li, Chung-I Li, Chunhong Li, Chunhui Li, Chunjie Li, Chunjun Li, Chunlan Li, Chunlian Li, Chunliang Li, Chunlin Li, Chunmei Li, Chunmiao Li, Chunqing Li, Chunqiong Li, Chunshan Li, Chunsheng Li, Chunting Li, Chunxia Li, Chunxiao Li, Chunxing Li, Chunxue Li, Chunya Li, Chunyan Li, Chunyi Li, Chunying Li, Chunyu Li, Chunzhu Li, Chuzhong Li, Cien Li, Cong Li, Congcong Li, Congfa Li, Conghui Li, Congjiao Li, Conglin Li, Congxin Li, Congye Li, Cui Li, Cui-lan Li, Cuicui Li, Cuiguang Li, Cuilan Li, Cuiling Li, Cun Li, Cunxi Li, Cyril Li, D C Li, Da Li, Da-Hong Li, Da-Jin Li, Da-Lei Li, Da-wei Li, DaZhuang Li, Dacheng Li, Dai Li, Daiyue Li, Dalei Li, Dali Li, Dalin Li, Dan C Li, Dan Li, Dan-Dan Li, Dan-Ni Li, Dandan Li, Daniel Tian Li, Danjie Li, Danni Li, Danxi Li, Danyang Li, Daoyuan Li, Dapei Li, Dawei Li, Dayong Li, Dazhi Li, De-Jun Li, De-Tao Li, Dechao Li, Defa Li, Defeng Li, Defu Li, Dehai Li, Deheng Li, Dehua Li, Dejun Li, Demin Li, Deming Li, Dengfeng Li, Dengke Li, Dengxiong Li, Deqiang Li, Desen Li, Desheng Li, Dexiong Li, Deyu Li, Dezhi Li, Di Li, Di-Jie Li, Dianjie Li, Dijie Li, Ding Li, Ding Yang Li, Ding-Biao Li, Ding-Jian Li, Dingchen Li, Dingshan Li, Diyan Li, Dong Li, Dong Sheng Li, Dong-Jie Li, Dong-Ling Li, Dong-Run Li, Dong-Yun Li, Dong-fei Li, Dongbiao Li, Dongdong Li, Dongfang Li, Dongfeng Li, Donghe Li, Donghua Li, Dongliang Li, Dongmei Li, Dongmin Li, Dongnan Li, Dongtao Li, Dongyang Li, Dongye Li, Duan Li, Duanbin Li, Duanxiang Li, Dujuan Li, Duo Li, Duoyun Li, Ellen Li, En Li, En-Min Li, Enhao Li, Enhong Li, Enxiao Li, F Li, Fa-Hong Li, Fa-Hui Li, Fadi Li, Fan Li, Fang Li, Fangqi Li, Fangyan Li, Fangyong Li, Fangyuan Li, Fangzhou Li, Fei Li, Fei-Lin Li, Fei-feng Li, Feifei Li, Feilong Li, Fen Li, Feng Li, Feng-Feng Li, Fengfeng Li, Fengjuan Li, Fengli Li, Fengqi Li, Fengqiao Li, Fengqing Li, Fengxia Li, Fengxiang Li, Fengyi Li, Fengyuan Li, Fu-Rong Li, Fugen Li, Fuhai Li, Fujun Li, Fulun Li, Fuping Li, Fusheng Li, Fuyu Li, Fuyuan Li, G Li, G-P Li, Gaijie Li, Gaizhen Li, Gaizhi Li, Gan Li, Gang Li, Ganggang Li, Gao-Fei Li, Gaoyuan Li, Ge Li, Gen Li, Gen-Lin Li, Gerard Li, Gong-Hua Li, Gongda Li, Guanbin Li, Guandu Li, Guang Li, Guang Y Li, Guang-Li Li, Guang-Xi Li, Guangda Li, Guangdi Li, Guanghua Li, Guanghui Li, Guangjin Li, Guangli Li, Guanglu Li, Guanglve Li, Guangming Li, Guangping Li, Guangpu Li, Guangqiang Li, Guangquan Li, Guangwen Li, Guangxi Li, Guangxiao Li, Guangyan Li, Guangzhao Li, Guangzhen Li, Guannan Li, Guanqiao Li, Guanyu Li, Gui Lin Li, Gui-Bo Li, Gui-Hua Li, Gui-Rong Li, Gui-xing Li, Guigang Li, Guihua Li, Guilan Li, Guisen Li, Guixia Li, Guixin Li, Guiyang Li, Guiying Li, Guiyuan Li, Guo Li, Guo-Chun Li, Guo-Jian Li, Guo-Li Li, Guo-Ping Li, Guo-Qiang Li, Guobin Li, Guoge Li, Guohong Li, Guohua Li, Guohui Li, Guojin Li, Guojun Li, Guoli Li, Guoping Li, Guoqin Li, Guoqing Li, Guowei Li, Guoxi Li, Guoxiang Li, Guoxing Li, Guoyan Li, Guoyin Li, H J Li, H Li, H-F Li, H-H Li, H-J Li, Hai Li, Hai-Yun Li, Haibin Li, Haibo Li, Haifeng Li, Haihong Li, Haihua Li, Haijun Li, Hailong Li, Haimin Li, Haiming Li, Hainan Li, Haipeng Li, Hairong Li, Haitao Li, Haitong Li, Haixia Li, Haiyan Li, Haiyang Li, Haiying Li, Haiyu Li, Han Li, Han-Bing Li, Han-Bo Li, Han-Ni Li, Han-Ru Li, Han-Wei Li, Hanbin Li, Hanbing Li, Hanbo Li, Handong Li, Hang Li, Hangwen Li, Hanjun Li, Hankun Li, Hanlu Li, Hanmei Li, Hanqi Li, Hanqin Li, Hansen Li, Hanting Li, Hanxiao Li, Hanxue Li, Hao Li, Hao-Fei Li, Haojing Li, Haolong Li, Haomiao Li, Haoqi Li, Haoran Li, Haotong Li, Haoxian Li, Haoyu Li, Haying Li, He Li, He-Zhen Li, Hecheng Li, Hegen Li, Hehua Li, Heng Li, Heng-Zhen Li, Hengguo Li, Hengtong Li, Hengyu Li, Hening Li, Hewei Li, Hexin Li, Heying Li, Hong Li, Hong-Chun Li, Hong-Lan Li, Hong-Lian Li, Hong-Mei Li, Hong-Tao Li, Hong-Wen Li, Hong-Yan Li, Hong-Yu Li, Hong-Zheng Li, Hongbo Li, Hongchang Li, Hongde Li, Honggang Li, Hongguo Li, Honghua Li, Honghui Li, Hongjia Li, Hongjiang Li, Hongjuan Li, Honglei Li, Hongli Li, Honglian Li, Hongliang Li, Honglin Li, Hongling Li, Honglong Li, Hongmei Li, Hongmin Li, Hongming Li, Hongqin Li, Hongquan Li, Hongru Li, Hongsen Li, Hongwei Li, Hongxia Li, Hongxin Li, Hongxing Li, Hongxue Li, Hongyan Li, Hongye Li, Hongyi Li, Hongyu Li, Hongyun Li, Hongzhe K Li, Hongzheng Li, Hongzhi Li, Hsiao-Fen Li, Hsiao-Hui Li, Hsin-Hua Li, Hsin-Yun Li, Hu Li, Hua Li, Hua-Zhong Li, Huabin Li, Huafang Li, Huafu Li, Huaixing Li, Huaiyuan Li, Hualian Li, Hualing Li, Huamao Li, Huan Li, Huanan Li, Huang Li, Huangbao Li, Huangyuan Li, Huanhuan Li, Huanjun Li, Huanqing Li, Huanqiu Li, Huaping Li, Huashun Li, Huawei Li, Huayao Li, Huayin Li, Huaying Li, Hui Li, Hui-Jun Li, Hui-Long Li, Hui-Ping Li, Huibo Li, Huifang Li, Huifeng Li, Huihuang Li, Huihui Li, Huijie Li, Huijuan Li, Huijun Li, Huilan Li, Huili Li, Huiliang Li, Huilin Li, Huilong Li, Huimin Li, Huiping Li, Huiqin Li, Huiqing Li, Huiqiong Li, Huiting Li, Huixia Li, Huixue Li, Huiying Li, Huiyou Li, Huiyuan Li, Huizi Li, Hujie Li, Hulun Li, Hung Li, Hung-Yuan Li, Ivan Li, J Li, J T Li, Jason Li, Jen-Ming Li, Jenny J Li, Ji Li, Ji Xia Li, Ji-Cheng Li, Ji-Feng Li, Ji-Liang Li, Ji-Lin Li, Ji-Min Li, Jia Li, Jia Li Li, Jia-Da Li, Jia-Huan Li, Jia-Peng Li, Jia-Ru Li, Jia-Xin Li, Jiabei Li, Jiachen Li, Jiacheng Li, Jiafang Li, Jiafei Li, Jiahao Li, Jiahui Li, Jiajia Li, Jiajie Li, Jiajing Li, Jiajun Li, Jiajv Li, Jiali Li, Jialin Li, Jialing Li, Jialun Li, Jiaming Li, Jian Li, Jian'an Li, Jian-Jun Li, Jian-Mei Li, Jian-Qiang Li, Jian-Shuang Li, Jianan Li, Jianang Li, Jianbin Li, Jianbo Li, Jianchun Li, Jiandong Li, Jianfang Li, Jianfeng Li, Jiang Li, Jiangan Li, Jiangbo Li, Jiangchao Li, Jiangfeng Li, Jianglin Li, Jianglong Li, Jiangtao Li, Jiangui Li, Jianguo Li, Jiangxia Li, Jiangya Li, Jianhai Li, Jianhua Li, Jiani Li, Jianing Li, Jianliang Li, Jianlin Li, Jianmin Li, Jiannan Li, Jianping Li, Jianrong Li, Jianrui Li, Jiansheng Li, Jianshuang Li, Jianwei Li, Jianxin Li, Jianxiong Li, Jianye Li, Jianyi Li, Jianyong Li, Jianyu Li, Jianzhong Li, Jiao Li, Jiao-Jiao Li, Jiaomei Li, Jiaping Li, Jiaqi Li, Jiawei Li, Jiaxi Li, Jiaxin Li, Jiaxuan Li, Jiayan Li, Jiayang Li, Jiayi Li, Jiaying Li, Jiayu Li, Jiayuan Li, Jiazhou Li, Jicheng Li, Jie Li, Jie-Pin Li, Jie-Shou Li, Jiehan Li, Jiejia Li, Jiejie Li, Jiejing Li, Jieming Li, Jiequn Li, Jieshou Li, Jiexi Li, Jiexin Li, Jiezhen Li, Jifang Li, Jihua Li, Jin Li, Jin-Jiang Li, Jin-Liang Li, Jin-Long Li, Jin-Mei Li, Jin-Ping Li, Jin-Qiu Li, Jin-Wei Li, Jin-Xiu Li, Jinchen Li, Jinfang Li, Jinfeng Li, Jing Li, Jing-Jing Li, Jing-Ming Li, Jing-Yao Li, Jing-Yi Li, Jing-gao Li, Jingcheng Li, Jingchun Li, Jingfeng Li, Jinghao Li, Jinghui Li, Jingjing Li, Jingke Li, Jinglin Li, Jingmei Li, Jingming Li, Jingping Li, Jingqi Li, Jingshang Li, Jingshu Li, Jingtong Li, Jingui Li, Jingwen Li, Jingxia Li, Jingxiang Li, Jingxin Li, Jingya Li, Jingyi Li, Jingyong Li, Jingyu Li, Jingyun Li, Jinhua Li, Jinhui Li, Jinjie Li, Jinku Li, Jinlan Li, Jinliang Li, Jinlin Li, Jinman Li, Jinming Li, Jinping Li, Jinsong Li, Jinwei Li, Jinxia Li, Jinxin Li, Jinzhi Li, Jiong Li, Jiong-Ming Li, Jipeng Li, Jiqing Li, Jisen Li, Jisheng Li, Jiuke Li, Jiuyi Li, Jiwei Li, Jiwen Li, Jixi Li, Jixuan Li, Jiyang Li, Jiyuan Li, John Zhong Li, Jonathan Z Li, Joyce Li, Ju-Rong Li, Juan Li, Juan-Juan Li, Juanjuan Li, Juanling Li, Juanni Li, Jufang Li, Julia Li, Jun Li, Jun Z Li, Jun-Cheng Li, Jun-Jie Li, Jun-Ling Li, Jun-Ru Li, Jun-Yan Li, Jun-Ying Li, JunBo Li, Junfeng Li, Junhong Li, Junhui Li, Junjie Li, Junjun Li, Junming Li, Junping Li, Junqin Li, Junru Li, Junsheng Li, Juntong Li, Junxian Li, Junxin Li, Junxu Li, Junya Li, Junyi Li, Junying Li, Justin Li, Jutang Li, Juxue Li, K-L Li, Ka Li, Ka Wan Li, Kai Li, Kai-Wen Li, Kaibin Li, Kaibo Li, Kaifeng Li, Kailong Li, Kaimi Li, Kainan Li, Kaiwei Li, Kaixin Li, Kaiyi Li, Kaiyuan Li, Kang Li, Kangli Li, Kangyuan Li, Karen Li, Kathy H Li, Kawah Li, Ke Li, KeZhong Li, Keanning Li, Kecheng Li, Kechun Li, Keguo Li, Kejuan Li, Keke Li, Kening Li, Kenli Li, Kenneth Kai Wang Li, Keqing Li, Keshen Li, Keying Li, Keyuan Li, Kezhen Li, Kongdong Li, Kuan Li, Kui Li, Kuiliang Li, Kun Li, Kun-Peng Li, Kun-Ping Li, Kun-Xin Li, Kunlin Li, Kunlong Li, Kunlun Li, Kunpeng Li, L I Li, L K Li, L Li, L P Li, L-Y Li, Lai K Li, Laiqing Li, Lamei Li, Lan Li, Lan-Juan Li, Lan-Lan Li, Lanfang Li, Lang Li, Lanjuan Li, Lanlan Li, Lanzhou Li, Le Li, Le-Le Li, Le-Ying Li, Lei Li, Leilei Li, Leipeng Li, Letai Li, Leyao Li, Li Li, Li-Min Li, Li-Na Li, Lian Li, Lianbing Li, Liang Li, Liangdong Li, Liangji Li, Liangkui Li, Liangqian Li, Lianhong Li, Lianjian Li, Lianyong Li, Liao-Yuan Li, Lieyou Li, Liguo Li, Lihong Li, Lihua Li, Lijia Li, Lijuan Li, Lijun Li, Lili Li, Liliang Li, Liling Li, Liming Li, Lin Li, Lin-Feng Li, Linchuan Li, Linfeng Li, Ling Li, Ling-Jie Li, Ling-Ling Li, Ling-Zhi Li, Lingjiang Li, Lingjie Li, Lingjun Li, Lingling Li, Lingxi Li, Lingyan Li, Lingyi Li, Lingzhi Li, Linhong Li, Linke Li, Linlin Li, Linqi Li, Linqing Li, Linsheng Li, Linting Li, Linxin Li, Linyan Li, Linying Li, Lipeng Li, Liping Li, Liqin Li, Liqun Li, Lirong Li, Lisha Li, Litao Li, Liuzheng Li, Liwei Li, Lixi Li, Lixia Li, Lixiang Li, Liyan Li, Long Li, Long Shan Li, Long-Yan Li, Longhui Li, Longxuan Li, Longyu Li, Lu Li, Lu-Yun Li, Lucia M Li, Lucy Li, Luhan Li, Lujiao Li, Lujie Li, Lulu Li, Luquan Li, Luxuan Li, Luyao Li, Luying Li, M D Li, M Li, M V Li, M-J Li, Man Li, Man-Xiang Li, Man-Zhi Li, Mangmang Li, Manjiang Li, Manna Li, Manru Li, Manxia Li, Mao Li, Maogui Li, Maolin Li, Maoquan Li, Maosheng Li, Marilyn Li, Mei Li, Mei-Lan Li, Mei-Ya Li, Mei-Zhen Li, Meifang Li, Meifen Li, Meijia Li, Meilan Li, Meiqing Li, Meitao Li, Meiting Li, Meiyan Li, Meiying Li, Meiyue Li, Meizi Li, Melody M H Li, Meng Li, Meng-Hua Li, Meng-Jun Li, Meng-Meng Li, Meng-Miao Li, Meng-Yang Li, Meng-Yao Li, Meng-Yue Li, MengGe Li, Mengfan Li, Menghua Li, Mengjiao Li, Mengjuan Li, Mengling Li, Menglu Li, Mengmeng Li, Mengqing Li, Mengqiu Li, Mengsen Li, Mengshi Li, Mengxi Li, Mengxia Li, Mengxuan Li, Mengyang Li, Mengyao Li, Mengying Li, Mengyuan Li, Mengyun Li, Mengze Li, Mi Li, Mian Li, Miao Li, Miao X Li, Miaoxin Li, Michelle Li, Mimi Li, Min Li, Min-Dian Li, Min-Rui Li, Min-jun Li, Minerva X Li, Ming D Li, Ming Li, Ming V Li, Ming Xing Li, Ming Zhou Li, Ming-Han Li, Ming-Hao Li, Ming-Jiang Li, Ming-Kai Li, Ming-Qing Li, Ming-Wei Li, Ming-Xing Li, Ming-Yang Li, Mingdan Li, Mingfang Li, Mingfei Li, Minghao Li, Minghua Li, Minghui Li, Mingjiang Li, Mingjie Li, Mingjun Li, Mingke Li, Mingkun Li, Mingli Li, Minglong Li, Minglun Li, Mingna Li, Mingqiang Li, Mingquan Li, Mingrui Li, Mingwei Li, Mingxi Li, Mingxia Li, Mingxing Li, Mingxu Li, Mingxuan Li, Mingyang Li, Mingyao Li, Mingyue Li, Mingzhe Li, Mingzhou Li, Minhui Li, Minle Li, Minmin Li, Minqi Li, Minyue Li, Minze Li, Minzhe Li, Miyang Li, Mo Li, Mohan Li, Monica M Li, Moyi Li, Mufan Li, Mulin Jun Li, Muzi Li, N Li, Na Li, Naishi Li, Nan Li, Nan-Nan Li, Nana Li, Nanjun Li, Nanlong Li, Nanxing Li, Nanzhen Li, Ni Li, Nianfu Li, Nianyu Li, Nien Li, Nien-Chen Li, Nien-Chi Li, Ning Li, Ningyan Li, Ningyang Li, Niu Li, Nuomin Li, O Li, P H Li, P Li, Pan Li, Panlong Li, Panyuan Li, Pei Li, Pei-Lin Li, Pei-Qin Li, Pei-Shan Li, Pei-Ying Li, Pei-Zhi Li, PeiQi Li, Peibo Li, Peifen Li, Peifeng Li, Peihong Li, Peihua Li, Peilin Li, Peilong Li, Peining Li, Peipei Li, Peiqin Li, Peiran Li, Peiwu Li, Peixin Li, Peiyu Li, Peiyuan Li, Peiyun Li, Peng Li, Peng Peng Li, Peng-li Li, Pengcui Li, Penghui Li, Pengjie Li, Pengju Li, Pengsong Li, Pengyang Li, Pengyu Li, Pengyun Li, Pik Yi Li, Pilong Li, Pindong Li, Ping Li, Ping'an Li, Pinghua Li, Pingping Li, Pu Li, Pu-Yu Li, Q Li, Qi Li, Qi-Fu Li, Qi-Jing Li, Qian Li, Qian-Qian Li, Qiang Li, Qiang-Ming Li, Qiankun Li, Qianqian Li, Qiao Li, Qiao-Xin Li, Qiaolian Li, Qiaoqiao Li, Qibing Li, Qifang Li, Qihang Li, Qihua Li, Qiji Li, Qijun Li, Qilan Li, Qilong Li, Qin Li, Qiner Li, Qing Li, Qing Run Li, Qing-Chang Li, Qing-Fang Li, Qing-Min Li, Qing-Wei Li, Qingchao Li, Qingfang Li, Qingfeng Li, Qinggang Li, Qinghe Li, Qinghong Li, Qinghua Li, Qingjie Li, Qinglan Li, Qingli Li, Qinglin Li, Qingling Li, Qingqin S Li, Qingrun Li, Qingshang Li, Qingsheng Li, Qingxian Li, Qingyang Li, Qingyu Li, Qingyuan Li, Qingyun Li, Qinqin Li, Qinrui Li, Qintong Li, Qiong Li, Qionghua Li, Qipei Li, Qiqiong Li, Qiu Li, Qiufeng Li, Qiuhong Li, Qiusheng Li, Qiuxuan Li, Qiuya Li, Qiuyan Li, Qiwei Li, Qiyong Li, Qizhai Li, Quan Li, Quan-Zhong Li, Quanpeng Li, Quanshun Li, Quanzhang Li, Qun Li, R H L Li, R Li, Ran Li, Ranchang Li, Ranran Li, Ranwei Li, Ren Li, Ren-Ke Li, Rena Li, Roger Li, Ronald Li, Rong Li, Rong-Bing Li, Ronggui Li, Rongkai Li, Rongling Li, Rongqing Li, Rongsong Li, Rongxia Li, Rongyao Li, Rosa J W Li, Ru Li, Ru-Hao Li, Rui Li, Rui-Fang Li, Rui-Han Li, Rui-Jún Eveline Li, Ruibing Li, Ruidong Li, Ruifang Li, Ruihuan Li, Ruijia Li, Ruijin Li, Ruikai Li, Ruitong Li, Ruiwen Li, Ruixi Li, Ruixia Li, Ruixue Li, Ruiyang Li, Rujia Li, Rulin Li, Rumei Li, Runbing Li, Runwen Li, Runzhao Li, Runzhen Li, Runzhi Li, Ruobing Li, Ruolin Li, Ruonan Li, Ruotai Li, Ruotian Li, Ruotong Li, Ruyi Li, Ruyue Li, S A Li, S E Li, S L Li, S Li, S S Li, S-C Li, Sai Li, Saijuan Li, Sainan Li, San-Feng Li, Sanqiang Li, Senlin Li, Senmao Li, Sha Li, Sha-Sha Li, Shan Li, Shan-Shan Li, Shangjia Li, Shanglai Li, Shangming Li, Shanhang Li, Shanpeng Li, Shanshan Li, Shanyi Li, Shao-Dan Li, Shaobin Li, Shaodan Li, Shaofei Li, Shaoguang Li, Shaojian Li, Shaojing Li, Shaoliang Li, Shaomin Li, Shaoqi Li, Shaoyong Li, Shasha Li, Shawn S C Li, Shawn Shun-Cheng Li, Shen Li, Sheng Li, Sheng-Fu Li, Sheng-Jie Li, Sheng-Qing Li, Sheng-Tien Li, Shengbiao Li, Shengbin Li, Shengchao A Li, Shenghao Li, Shengjie Li, Shengli Li, Shengliang Li, Shengsheng Li, Shengwen Li, Shengxian Li, Shengxu Li, Shengze Li, Sherly X Li, Shi Li, Shi-Fang Li, Shi-Guang Li, Shi-Hong Li, Shi-Ying Li, Shibao Li, Shibo Li, Shichao Li, Shigang Li, Shihao Li, Shiheng Li, Shihong Li, Shijie Li, Shijun Li, Shikang Li, Shilan Li, Shili Li, Shiliang Li, Shilin Li, Shilun Li, Shiqi Li, Shiquan Li, Shisheng Li, Shishi Li, Shitao Li, Shiya Li, Shiyan Li, Shiyang Li, Shiyi Li, Shiying Li, Shiyu Li, Shiyue Li, Shiyun Li, Shu Li, Shu-Fang Li, Shu-Fen Li, Shu-Feng Li, Shu-Hong Li, Shu-Qi Li, Shu-Xin Li, Shuai Li, Shuaicheng Li, Shuang Li, Shuang-Ling Li, Shuangding Li, Shuangfei Li, Shuanglong Li, Shuangmei Li, Shuangshuang Li, Shuangxiu Li, Shubo Li, Shude Li, Shufen Li, Shugang Li, Shuguang Li, Shuhao Li, Shuhua Li, Shuhui Li, Shujiao Li, Shujie Li, Shujin Li, Shujing Li, Shulin Li, Shun Li, Shunhua Li, Shunle Li, Shunqin Li, Shunqing Li, Shunwang Li, Shuo Li, Shupeng Li, Shuqiang Li, Shuwei Li, Shuwen Li, Shuying Li, Shuyu D Li, Shuyu Dan Li, Shuyuan Li, Shuyue Li, Si Li, Si-Wei Li, Si-Xing Li, Si-Ying Li, Si-Yuan Li, Sibing Li, Sichen Li, Sichong Li, Side Li, Siguang Li, Sijie Li, Simin Li, Siming Li, Sin-Lun Li, Siqi Li, Sitao Li, Siting Li, Siwen Li, Siyi Li, Siyu Li, Siyue Li, Song Li, Song-Chao Li, Songhan Li, Songlin Li, Songtao Li, Songyu Li, Songyun Li, Stephen Li, Su Li, SuYun Li, Suchun Li, Suheng Li, Suhong Li, Suiyan Li, Sujing Li, Suk-Yee Li, Sumei Li, Sunan Li, Sung-Chou Li, Supeng Li, Suping Li, Suran Li, Suwei Li, Suwen Li, Suyan Li, T Li, Taibo Li, Taiwen Li, Taixu Li, Tao Li, Taoyingnan Li, Teng Li, Tengyan Li, Thomas Li, Tian Li, Tian-Yi Li, Tian-chang Li, Tian-wang Li, Tianchang Li, Tiandong Li, Tianfeng Li, Tiange Li, Tianjiao Li, Tianjun Li, Tianming Li, Tiansen Li, Tiantian Li, Tianxiang Li, Tianyao Li, Tianye Li, Tianyi Li, Tianyou Li, Tie Li, Tiegang Li, Tiehua Li, Tiewei Li, Timmy Li, Ting Li, Tingguang Li, Tinghao Li, Tinghua Li, Tingsong Li, Tingting Li, Tong Li, Tong-Ruei Li, Tongyao Li, Tongzheng Li, Tsai-Kun Li, Tuojian Li, Tuoping Li, Vivian Li, Vivian S W Li, W H Li, W J Li, W Li, W W Li, W Y Li, W-B Li, Wan Jie Li, Wan Li, Wan-Hong Li, Wan-Shan Li, Wan-Xin Li, Wang Li, Wanling Li, Wanni Li, Wanqian Li, Wanru Li, Wanshi Li, Wanshun Li, Wanting Li, Wanwan Li, Wanxin Li, Wanyan Li, Wanyi Li, Wei Li, Wei-Bo Li, Wei-Dong Li, Wei-Jun Li, Wei-Li Li, Wei-Ming Li, Wei-Na Li, Wei-Ping Li, Wei-Qin Li, Wei-Yang Li, Weidong Li, Weifeng Li, Weiguang Li, Weiguo Li, Weihai Li, Weiheng Li, Weihua Li, Weijian Li, Weijie Li, Weijun Li, Weike Li, Weiling Li, Weimin Li, Weina Li, Weining Li, Weiping Li, Weiqin Li, Weirong Li, Weisong Li, Weiyang Li, Weiye Li, Weiyong Li, Weizu Li, Wen Lan Li, Wen Li, Wen-Chao Li, Wen-Jie Li, Wen-Ting Li, Wen-Wen Li, Wen-Xi Li, Wen-Xing Li, Wen-Ya Li, Wen-Ying Li, Wen-juan Li, Wenbo Li, Wenchao Li, Wende Li, Wendeng Li, Wenfang Li, Wenfeng Li, Wenge Li, Wenguo Li, Wenhao Li, Wenhong Li, Wenhua Li, Wenhui Li, Wenjia Li, Wenjian Li, Wenjie Li, Wenjing Li, Wenjuan Li, Wenjun Li, Wenke Li, Wenlei Li, Wenli Li, Wenlong Li, Wenming Li, Wenqi Li, Wenqiang Li, Wenqing Li, Wenqun Li, Wenrui Li, Wensheng Li, Wentao Li, Wenwen Li, Wenxi Li, Wenxia Li, Wenxiang Li, Wenxin Li, Wenxiu Li, Wenxue Li, Wenyan Li, Wenyang Li, Wenyi Li, Wenying Li, Wenyong Li, Wenyu Li, Wenzhe Li, Wenzhuo Li, Wu-Jun Li, Wuguo Li, Wulan Li, Wuyan Li, X B Li, X L Li, X Li, X Y Li, X-H Li, X-L Li, Xi Li, Xi-Hai Li, Xi-Xi Li, Xia Li, Xian Li, Xiancheng Li, Xiang Li, Xiang-Dong Li, Xiang-Jun Li, Xiang-Ping Li, Xiang-Yu Li, Xiangcheng Li, Xiangchun Li, Xiangdong Li, Xiangfei Li, Xiangjun Li, Xiangling Li, Xianglong Li, Xiangnan Li, Xiangpan Li, Xiangping Li, Xiangqi Li, Xiangrui Li, Xiangwei Li, Xiangyan Li, Xiangyang Li, Xiangyun Li, Xiangzhe Li, Xiankai Li, Xiankun Li, Xianlin Li, Xianlong Li, Xianlu Li, Xianlun Li, Xianrui Li, Xianyong Li, Xiao Li, Xiao-Cheng Li, Xiao-Dong Li, Xiao-Feng Li, Xiao-Gang Li, Xiao-Guang Li, Xiao-Hong Li, Xiao-Hui Li, Xiao-Jiao Li, Xiao-Jing Li, Xiao-Jun Li, Xiao-Kang Li, Xiao-Li Li, Xiao-Lin Li, Xiao-Long Li, Xiao-Min Li, Xiao-Na Li, Xiao-Qiang Li, Xiao-Qin Li, Xiao-Qiu Li, Xiao-Sa Li, Xiao-Tong Li, Xiao-Yao Li, Xiao-Yun Li, Xiao-kun Li, Xiao-mei Li, Xiao-xu Li, Xiao-yu Li, XiaoQiu Li, Xiaobai Li, Xiaobin Li, Xiaobing Li, Xiaobo Li, Xiaochen Li, Xiaochun Li, Xiaocun Li, Xiaodong Li, Xiaofang Li, Xiaofei Li, Xiaofeng Li, Xiaoguang Li, Xiaohan Li, Xiaoheng Li, Xiaohong Li, Xiaohu Li, Xiaohua Li, Xiaohuan Li, Xiaohui Li, Xiaojiao Li, Xiaojiaoyang Li, Xiaojing Li, Xiaoju Li, Xiaojuan Li, Xiaokun Li, Xiaolei Li, Xiaoli Li, Xiaolian Li, Xiaoliang Li, Xiaolin Li, Xiaoling Li, Xiaolong Li, Xiaoman Li, Xiaomei Li, Xiaomeng Li, Xiaomin Li, Xiaoming Li, Xiaona Li, Xiaonan Li, Xiaoning Li, Xiaopeng Li, Xiaoping Li, Xiaoqi Li, Xiaoqiang Li, Xiaoqin Li, Xiaoqing Li, Xiaoqiong Li, Xiaoquan Li, Xiaoran Li, Xiaorong Li, Xiaotian Li, Xiaoting Li, Xiaotong Li, Xiaowei Li, Xiaoxia Li, Xiaoxiao Li, Xiaoxiong Li, Xiaoxuan Li, Xiaoya Li, Xiaoyan Li, Xiaoyao Li, Xiaoyi Li, Xiaoying Li, Xiaoyong Li, Xiaoyu Li, Xiaoyuan Li, Xiaoyun Li, Xiaozhao Li, Xiaozhen Li, Xiaozheng Li, Xiatian Li, Xiawei Li, Xiaxia Li, Xiayu Li, Xidan Li, Xihao Li, Xihe Li, Xijing Li, Xikun Li, Xiliang Li, Ximei Li, Xin Li, Xin-Chang Li, Xin-Jian Li, Xin-Ping Li, Xin-Tao Li, Xin-Ya Li, Xin-Yu Li, Xin-Yue Li, Xin-Zhu Li, Xinbin Li, Xing Li, Xing-Wang Li, Xingchen Li, Xingcheng Li, Xingfang Li, Xinghuan Li, Xinghui Li, Xingli Li, Xinglong Li, Xingwang Li, Xingxing Li, Xingya Li, Xingye Li, Xingyu Li, Xingyuan Li, Xinhai Li, Xinhua Li, Xinhui Li, Xining Li, Xinjia Li, Xinjian Li, Xinke Li, Xinle Li, Xinli Li, Xinlin Li, Xinmei Li, Xinmiao Li, Xinmin Li, Xinming Li, Xinpeng Li, Xinping Li, Xinrong Li, Xinrui Li, Xinsheng Li, Xinwei Li, Xinxin Li, Xinxiu Li, Xinyan Li, Xinyang Li, Xinyao Li, Xinye Li, Xinyi Li, Xinyu Li, Xinyuan Li, Xinzhi Li, Xinzhong Li, Xiong Bing Li, Xiong Li, Xiongfeng Li, Xionghao Li, Xionghui Li, Xiu-Ling Li, Xiucui Li, Xiufeng Li, Xiujuan Li, Xiuli Li, Xiuling Li, Xiumei Li, Xiuqi Li, Xiurong Li, Xiushen Li, Xiushi Li, Xiuzhen Li, Xixi Li, Xiying Li, Xiyue Li, Xiyun Li, Xu Li, Xu-Bo Li, Xu-Wei Li, Xu-Zhao Li, Xuan Li, Xuan-Ling Li, Xuanfei Li, Xuanxuan Li, Xuanzheng Li, Xudong Li, Xue Cheng Li, Xue Li, Xue-Er Li, Xue-Fei Li, Xue-Hua Li, Xue-Lian Li, Xue-Min Li, Xue-Nan Li, Xue-Peng Li, Xue-Yan Li, Xue-Ying Li, Xue-jing Li, Xue-zhi Li, Xuebiao Li, Xueer Li, Xuefei Li, Xuefeng Li, Xuehua Li, Xuejie Li, Xuejun Li, Xuekun Li, Xuelian Li, Xuelin Li, Xueling Li, Xuemei Li, Xuemin Li, Xuening Li, Xuepeng Li, Xueqin Li, Xueren Li, Xueshan Li, Xuesong Li, Xueting Li, Xuewang Li, Xuewei Li, Xuewen Li, Xueyang Li, Xueyi Li, Xueying Li, Xuezhong Li, Xuhang Li, Xuhong Li, Xuhua Li, Xujun Li, Xun Li, Xunjia Li, Xuri Li, Xutong Li, Xuyi Li, Xuze Li, Y H Li, Y L Li, Y Li, Y M Li, Y X Li, Y-Y Li, Ya Li, Ya-Feng Li, Ya-Ge Li, Ya-Jun Li, Ya-Li Li, Ya-Pei Li, Ya-Qiang Li, Ya-Ting Li, Ya-Zhou Li, YaJie Li, Yadong Li, Yahui Li, Yajiao Li, Yajing Li, Yajuan Li, Yajun Li, Yakui Li, Yalan Li, Yali Li, Yalin Li, Yan Bing Li, Yan Li, Yan Ning Li, Yan-Chun Li, Yan-Guang Li, Yan-Hong Li, Yan-Hua Li, Yan-Li Li, Yan-Nan Li, Yan-Xue Li, Yan-Yan Li, Yan-Yu Li, Yanan Li, Yanbin Li, Yanbing Li, Yanbo Li, Yanchang Li, Yanchuan Li, Yanchun Li, Yandong Li, Yanfeng Li, Yang Li, Yangxue Li, Yangyang Li, Yanhui Li, Yani Li, Yanjiao Li, Yanjie Li, Yanjing Li, Yanjun Li, Yanli Li, Yanlin Li, Yanling Li, Yanlong Li, Yanmei Li, Yanmin Li, Yanming Li, Yanni Li, Yanping Li, Yanqing Li, Yansen Li, Yanshu Li, Yansong Li, Yantao Li, Yanwei Li, Yanwu Li, Yanxi Li, Yanxiang Li, Yanxin Li, Yanyan Li, Yanying Li, Yanze Li, Yanzhong Li, Yao Li, Yaobo Li, Yaochen Li, Yaodong Li, Yaofu Li, Yaojia Li, Yaokun Li, Yaoqi Li, Yaoyao Li, Yaqi Li, Yaqiang Li, Yaqiao Li, Yaqin Li, Yaqing Li, Yaqiong Li, Yarong Li, Yawei Li, Yaxi Li, Yaxian Li, Yaxiong Li, Yaxuan Li, Yaying Li, Yayu Li, Yazhou Li, Ye Li, Yehong Li, Yeshan Li, Yetian Li, Yi Li, Yi-Heng Li, Yi-Ling Li, Yi-Ning Li, Yi-Shuan J Li, Yi-Ting Li, Yi-Wen Li, Yi-Yang Li, Yi-Ying Li, Yi-Yun Li, YiPing Li, YiQing Li, Yibo Li, Yiche Li, Yicun Li, Yifan Li, Yifei Li, Yifeng Li, Yige Li, Yihan Li, Yihao Li, Yiheng Li, Yihong Li, Yijian Li, Yijie Li, Yijing Li, Yiju Li, Yikang Li, Yike Li, Yilang Li, Yiliang Li, Yilong Li, Yimei Li, Yimeng Li, Yiming Li, Yin Li, Yinan Li, Ying Li, Ying-Bo Li, Ying-Lan Li, Ying-Qin Li, Ying-Qing Li, Ying-na Li, Yinggao Li, Yinghao Li, Yinghua Li, Yinghui Li, Yingjian Li, Yingjie Li, Yingjun Li, Yinglin Li, Yingnan Li, Yingpu Li, Yingqin Li, Yingrui Li, Yingshuo Li, Yingxi Li, Yingxia Li, Yingyi Li, Yingying Li, Yinhao Li, Yining Li, Yinliang Li, Yinxiong Li, Yinyan Li, Yinzhen Li, Yipeng Li, Yiqiang Li, Yirun Li, Yitong Li, Yiwei Li, Yiwen Li, Yixi Li, Yixiang Li, Yixiao Li, Yixin Li, Yixing Li, Yixuan Li, Yixue Li, Yiyang Li, Yizhe Li, Yong Li, Yong-Jian Li, Yong-Jun Li, Yong-Liang Li, Yongchao Li, Yonghao Li, Yonghe Li, Yongjia Li, Yongjiang Li, Yongjin Li, Yongjing Li, Yongjun Li, Yongkai Li, Yongle Li, Yongli Li, Yongmei Li, Yongnan Li, Yongpeng Li, Yongping Li, Yongqi Li, Yongqiang Li, Yongqiu Li, Yongsen Li, Yongsheng Li, Yongting Li, Yongxiang Li, Yongxin Li, Yongxue Li, Yongze Li, Yongzhe Li, Yongzhen Li, Yongzheng Li, You Li, You Ran Li, You-Mei Li, Youjun Li, Youming Li, Youran Li, Yousheng Li, Youwei Li, Yu Li, Yu-Cheng Li, Yu-Chia Li, Yu-Hang Li, Yu-Hao Li, Yu-He Li, Yu-Hui Li, Yu-I Li, Yu-Jin Li, Yu-Jui Li, Yu-Kun Li, Yu-Lin Li, Yu-Sheng Li, Yu-Xiang Li, Yu-Ye Li, Yu-Ying Li, Yu-quan Li, Yuan Hao Li, Yuan Li, Yuan-Hai Li, Yuan-Jing Li, Yuan-Tao Li, Yuan-Yuan Li, Yuan-hao Li, Yuanchang Li, Yuanchuang Li, Yuancong Li, Yuandong Li, Yuanfang Li, Yuanfei Li, Yuanhao Li, Yuanhe Li, Yuanheng Li, Yuanhong Li, Yuanhua Li, Yuanjing Li, Yuanmei Li, Yuanyou Li, Yuanyuan Li, Yuanze Li, Yubin Li, Yubo Li, Yuchan Li, Yuchao Li, Yucheng Li, Yuchuan Li, Yuchun Li, Yudong Li, Yue Li, Yue-Chun Li, Yue-Jia Li, Yue-Ming Li, Yue-Rui Li, Yue-Ting Li, Yue-Ying Li, YueQiang Li, Yuefei Li, Yuefeng Li, Yueguo Li, Yuehua Li, Yuemei Li, Yueping Li, Yueqi Li, Yueting Li, Yuezheng Li, Yufan Li, Yufen Li, Yufeng Li, Yuguang Li, Yuhan Li, Yuhang Li, Yuhong Li, Yuhua Li, Yuhuang Li, Yuhui Li, Yujie Li, Yujun Li, Yukun Li, Yuli Li, Yulin Li, Yuling Li, Yulong Li, Yumao Li, Yumei Li, Yumiao Li, Yumin Li, Yun Li, Yun-Da Li, Yun-Lin Li, Yun-Peng Li, Yun-tian Li, Yuna Li, Yunan Li, Yunchu Li, Yunfeng Li, Yunjiu Li, Yunlong Li, Yunlun Li, Yunman Li, Yunmin Li, Yunpeng Li, Yunqi Li, Yunrui Li, Yunshen Li, Yunsheng Li, Yunting Li, Yunxi Li, Yunxiao Li, Yunxu Li, Yunyun Li, Yunze Li, Yuping Li, Yuqi Li, Yuqian Li, Yuqing Li, Yuqiu Li, Yuquan Li, Yushan Li, Yutang Li, Yutian Li, Yuting Li, Yutong 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articles
Kun Lian, Yilan Chen, Tianhu Lv +3 more · 2025 · Asian journal of psychiatry · Elsevier · added 2026-04-24
Schizophrenia (SCZ) is a major neurodevelopmental disorder that exhibits poor response to current therapeutic interventions. Dysregulation of glutamate metabolism (GM) has been strongly associated wit Show more
Schizophrenia (SCZ) is a major neurodevelopmental disorder that exhibits poor response to current therapeutic interventions. Dysregulation of glutamate metabolism (GM) has been strongly associated with the development of SCZ, through mechanisms involving NMDA receptor dysfunction and neuroimmune imbalance. This study utilized Mendelian randomization (MR) to explore the causal association between 1400 blood metabolites and SCZ. Differentially Expressed GM-related Genes (GMDEGs) were identified via GEO transcriptome data integration, and consensus clustering techniques were employed to delineate the molecular subtypes. Using the key GM genes, a diagnostic model was developed and combined with CIBERSORT and MCPcounter analyses to assess immune infiltration. Moreover, the Drug Signatures Database (DSigDB) was used to identify potential targeted drugs, with their binding stability verified through Molecular Docking (MD) and dynamics simulations. Mendelian randomization identified 23 SCZ-related plasma metabolites, with glutamate exhibiting the most significant effect (P < 2.72e-31). Further analysis uncovered 25 Differentially Expressed Genes (DEGs) involved in GM, among which ASL, SLC1A5, and CLN3 were validated as the core targets. Immunoassays demonstrated that these DEGs were involved in the regulation of neutrophil and T cell infiltration. SCZ was categorized into C1 and C2 subtypes based on the expression profiles of these three hub glutamate metabolism genes. A diagnostic model integrating ASL, SLC1A5, and CLN3 was developed, which could identify potential therapeutic agents like Tanespimycin with an AUC of 0.844. Moreover, MD experiments confirmed strong binding affinities between tanespimycin and SLC1A5 (-7.7812 kcal/mol), geldanamycin and SLC1A5 (-7.1142 kcal/mol), cyclosporin A and CLN3 (-7.3049 kcal/mol). Meanwhile, molecular dynamics simulations indicated stable binding interactions. This study demonstrates the potential causal association of GM-related genes in SCZ, developed a precise diagnostic model, and proposed novel targeted therapeutic strategies. Show less
no PDF DOI: 10.1016/j.ajp.2025.104724
CLN3
Xueqing Ye, Yue Zhao, Qinghua Yao +3 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Ochratoxin A (OTA) is a core environmental toxin that induces kidney injury by interfering with glomerular filtration, antioxidant defense, and tubular transport functions. Alginate oligosaccharides ( Show more
Ochratoxin A (OTA) is a core environmental toxin that induces kidney injury by interfering with glomerular filtration, antioxidant defense, and tubular transport functions. Alginate oligosaccharides (AOS), as active substances from marine, carry natural antioxidant, anti-inflammatory and other biological activities. The purpose of this study is to explore the molecular network of AOS against nephrotoxicity caused by OTA. A total of 36 5-week male mice were randomly divided into three groups: the CON group, the OTA group (250 μg/kg B.W. OTA) and the AOS + OTA group (400 mg/kg B.W. AOS +250 μg/kg B.W. OTA). The treatment was continued for 21 d. OTA induced renal injury in mice, manifested by glomerular capsule blurring, lymphocytic infiltration, and mitochondrial damage in tubular epithelial cells. Treatment with AOS significantly alleviated these pathological changes. Multi‑omics analysis revealed that AOS activated the PPAR signaling pathway, upregulating key genes (Aldehyde Dehydrogenase 1 Family Member A3 ( This study reveal that AOS antagonizes OTA-induced nephrotoxicity in mice through PPAR signaling axis, thus providing new insight into the renal protection mechanism of marine active substances. Show less
📄 PDF DOI: 10.3389/fvets.2025.1702799
CPS1
Long Xu, Yuanyuan Zhao, Shuxi Song +3 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor micro Show more
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor microenvironment (TME). Neutrophil extracellular traps (NETs) and oxidative stress play critical roles in tumor progression: NETs promote tumor cell adhesion, migration, and immune suppression, while oxidative stress induces DNA damage and activates pro-tumor signaling pathways. Moreover, oxidative stress is an important inducer of NETs, and their crosstalk shapes the LUAD immune microenvironment. However, systematic exploration of LUAD immunotherapeutic response prediction based on NETs and oxidative stress-related genes remains lacking. The gene set related to oxidative stress was obtained from MSigDB. The gene set related to NETs was sourced from relevant literature. Transcriptomic and clinical data were integrated from The Cancer Genome Atlas (TCGA)-LUAD (training set) and GSE31210 (validation set). Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to screen gene modules and characteristic scores related to NETs and oxidative stress signatures. Differentially expressed genes (DEGs) were screened, and prognostic model was established using univariate and LASSO Cox regression. Immune infiltration was analyzed using ESTIMATE algorithm, MCP-counter and ssGSEA methods. And we developed a nomogram incorporating clinicopathological features and RiskScore model, and performed drug sensitivity analysis. Finally, the biological role of CPS1 in lung cancer cells was investigated through CCK-8, wound-healing, and Transwell experiments. 22 co-expression modules were screened, among which the brown module showed significant correlations with NETs and oxidative stress signature scores. This module was intersected with DEGs, yielding 624 overlapping genes implicated in immune-relevant pathways (like leukocyte differentiation, neutrophil activation involved in immune response). A prognostic model was established utilizing 8 key genes (ADGRE3, ARHGEF3, CD79A, CLEC7A, CPS1, EPHB2, LARGE2, and OAS3). In the TCGA database, the model demonstrated robust prognostic discrimination (area under the curve (AUC) > 0.6), with high-risk patients exhibiting shorter overall survival (OS) (p < 0.05). Its stability was validated in GSE31210 (AUC > 0.6). The RiskScore showed negative correlations with immune infiltration (like T cells, CD8 T cells, and natural killer cells) as well as immune/stromal scores. A nomogram model combining RiskScore with N staging was developed and validated, demonstrating strong predictive accuracy through calibration and decision curve analyses. High-risk patients were more sensitive to drugs like BI-2536, BMS-509744, and Pyrimethamine. Finally, in vitro tests showed that CPS1 knockdown markedly decreased the viability, migration, and invasion of lung cancer cells. The constructed prognostic model by NETs and oxidative stress-relevant genes effectively predicts LUAD prognosis, correlates with immune microenvironment characteristics, and guides drug sensitivity, providing novel insights for LUAD prognostic assessment and personalized therapy. Show less
📄 PDF DOI: 10.1186/s40001-025-03553-9
CPS1
Hongzhi Li, Xian Gao, Chengde Chen +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD) is a leading cause of cancer deaths. Given that traditional pathologic features to diagnose LUAD do not fully reflect the biological differences in patients, the search for Show more
Lung adenocarcinoma (LUAD) is a leading cause of cancer deaths. Given that traditional pathologic features to diagnose LUAD do not fully reflect the biological differences in patients, the search for novel biomarkers is necessary. In this study, we obtained immune-related genes (IRGs) from ImmPort and performed cluster analysis on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to mine LUAD subtypes with different immune characteristics. Quantitative analysis of IRGs was performed by single-sample gene set enrichment analysis (ssGSEA). Based on the univariate cox and LASSO regression methods, we screened the characteristic genes that significantly affected LUAD and built the model based on the RiskScore coefficients. The relative expressions of characteristic genes in LUAD were determined using qRT-PCR. Transwell and wound healing assays were utilized to verify the practical regulation of these genes on the migration and invasion levels of LUAD. Correlations were established between RiskScore and LUAD drug sensitivity by oncoPredict. We acquired three LUAD subtypes and demonstrated heterogeneous IRGs scores and clinical features. The molecular subtypes were differentially enriched in bile acid metabolism, fatty acid metabolism, and ECM-receptor interaction. This study identified seven genes (MS4A1, EXO1, CPS1, ZNF750, S100P, NT5E, KCNN4) as a signature affecting prognosis, from the differentially expressed genes (DEGs) among the molecular subtypes, and constructed a RiskScore for the prognosis of LUAD. Cellular experiments verified that 6 of 7 characteristic genes were expression dysregulation in LUAD cell line. Silencing of EXO1 significantly suppressed the migration and invasion of LUAD cell lines. RiskScore and immune checkpoints such as CD276, TNFSF4, and TNFSF9 showed a positive correlation. This study identified three LUAD subtypes with distinct immune characteristics and constructed a seven-gene prognostic model. This model correlates with immune checkpoint and chemotherapy sensitivity, providing new targets and strategies for clinical diagnosis and treatment. Show less
📄 PDF DOI: 10.1186/s40001-025-03544-w
CPS1
Yi Qian, Jia Peng, Weiguo Jin +7 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Mitochondrial unfolded protein response (UPR The data were sourced from the cancer genome atlas (TCGA) and GSE31210 dataset and MRGs were retrieved to identify those with prognostic relevance, which w Show more
Mitochondrial unfolded protein response (UPR The data were sourced from the cancer genome atlas (TCGA) and GSE31210 dataset and MRGs were retrieved to identify those with prognostic relevance, which were applied to recognize the molecular clusters in LUAD. The cluster-specific differentially expressed genes (DEGs) were identified for the functional enrichment analysis. The independent differentially expressed MRGs were sorted out to develop a risk model. Besides, the tumor immune microenvironment was analyzed using the ESTIMATE, TIMER, MCP-counter, and ssGSEA algorithms. The data were processed with Mutect2 to evaluate the genetic mutation landscape, while the IMvigor210 cohort and pRRophetic package were utilized to predict immunotherapeutic responses and drug sensitivity. Finally, in vitro validation was performed via quantitative real-time PCR (qRT-PCR), cell counting kit-8 (CCK-8), wound healing, and Transwell assays. Most MRGs were higher expressed in LUAD, and CREB binding protein (CREBBP), lysine demethylase 6B (KDM6B) and leucine rich pentatricopeptide repeat containing (LRPPRC) were the top 3 genes with mutation frequency. 8 MRGs were applied to identify 2 molecular clusters, with the worst prognosis seen in cluster C1. The clusters-specific DEGs were mainly enriched in cell proliferation-related pathways and the established risk model based on 4 hub genes (ANLN, FAM83A, CPS1 and KRT6A) showed satisfying efficacy in predicting the prognosis and was negatively correlated with most immune cells. Besides, the tumor mutation burden tended to be stronger in high risk group with high gene mutation frequency. In IMvigor210 cohort, higher RiskScore was seen in patients with progressive disease and stable disease and related to a worse survival. 3 drug candidates, including Roscovitine, Rapamycin and PHA.665752 were positively correlated with RiskScore. Besides, all 4 MRGs were highly expressed in LUAD cells and the silencing of ANLN repressed the LUAD cell proliferation, migration and invasion. The established 4-MRGs signature not only serves as a robust prognostic indicator but also highlights the significant involvement of mitochondrial unfolded protein response in shaping tumor microenvironment and influencing immunotherapy outcomes in LUAD. The 4 MRGs may contribute to the understanding on UPR Show less
📄 PDF DOI: 10.1186/s40001-025-03453-y
CPS1
Chunhui Li, Zongqian Yuan, Chengrui Fu +3 more · 2025 · Discover oncology · Springer · added 2026-04-24
Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer. Previous studies have highlighted the critical roles of complement and coagulation cascades in tumor development, maintenance, Show more
Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer. Previous studies have highlighted the critical roles of complement and coagulation cascades in tumor development, maintenance, and therapeutic response. However, the overall impact of complement and coagulation cascade-related (CCCR) genes on LUAD progression and their role in the tumor microenvironment (TME) remain insufficiently explored. Therefore, we screened CCCR genes with important roles in LUAD using RNA sequencing data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Subsequently, a prognostic model, based on 8 hub genes (IGFBP1, TUBB, PLEK2, CNTNAP2, CPS1, EREG, CENPE, HBEGF) identified using the Lasso-Cox algorithm, was developed to stratify LUAD patients into high- and low-risk groups. This model demonstrated strong predictive capability and calibration, with an AUC of 0.816 in the external validation cohort. Multiomics clustering revealed that 2 cancer subtypes (CSs) are associated with prognosis, with CS2 demonstrating the most favorable prognostic outcome and validating the validity of the prognostic model. Additionally, we analyzed the immune infiltration, tumor mutation burden (TMB) and immunophenoscore (IPS) of the riskscore in the models. Through this analysis, we have identified for the first time CCCR genes are highly associated with clinical characteristics, immune cell infiltration patterns, and immune therapeutic responses of LUAD. This prognostic model constructed based on CCCR genes represents a valid tool for the prognosis of LUAD patients. Our findings provide valuable insights into the prognostic and immunological relevance of CCCR genes in LUAD, offering a robust foundation for personalized treatment strategies and future research. Show less
📄 PDF DOI: 10.1007/s12672-025-03765-9
CPS1
Abudunaibi Wupuer, Xing Peng, Jie Wang +4 more · 2025 · The journals of gerontology. Series A, Biological sciences and medical sciences · Oxford University Press · added 2026-04-24
Frailty and sarcopenia are age-related conditions linked to mitochondrial dysfunction, but their causal mechanisms remain poorly defined. This study aimed to identify mitochondrial-related genes causa Show more
Frailty and sarcopenia are age-related conditions linked to mitochondrial dysfunction, but their causal mechanisms remain poorly defined. This study aimed to identify mitochondrial-related genes causally associated with frailty and sarcopenia using comprehensive multi-omics approaches. We performed summary-data-based Mendelian randomization using genome-wide association study summary statistics for the frailty index and sarcopenia-related traits. Quantitative trait loci data for DNA methylation, gene expression, and plasma protein abundance were analyzed across 1136 mitochondrial-related genes. Colocalization analysis was applied to confirm shared causal variants. For frailty, GRPEL1 showed tissue-specific associations at methylation and expression levels (protective in blood: β = -.15, false discovery rate (FDR) = 1.5e-02; adverse in brain/muscle), while LRPPRC demonstrated consistent protective effects across tissues (β = -.05 to -.13, PPH4 > 0.93). For sarcopenia-related traits, GATM was associated with appendicular lean mass (ALM) across all omics levels with opposing tissue effects (negative in blood: β = -.03, FDR = 1.9e-09; positive in muscle), and ETFDH showed positive associations with ALM (β = .03, FDR = 1.4e-06). Additional genes included CPS1 and MMAB for frailty, NTHL1 and MTCH2 for grip strength, and TOMM70, BNIP3, TUFM for walking pace. Complete regulatory pathways were identified for GRPEL1 and GATM, linking methylation to expression to phenotype. This multi-omics study identified distinct mitochondrial genetic signatures for frailty and sarcopenia, with key genes including GRPEL1, LRPPRC, GATM, ETFDH, and others showing tissue-specific causal associations. These findings advance understanding of mitochondrial mechanisms in age-related functional decline and identify multiple therapeutic targets. Show less
no PDF DOI: 10.1093/gerona/glaf234
CPS1
Xinyue Yang, Shufen Li, Yuqing Feng +3 more · 2025 · Carbohydrate polymers · Elsevier · added 2026-04-24
Metabolic associated fatty liver disease (MAFLD) is a globally recognized chronic metabolic disorder characterized by lipid metabolism abnormalities. Accumulating evidence indicates that exopolysaccha Show more
Metabolic associated fatty liver disease (MAFLD) is a globally recognized chronic metabolic disorder characterized by lipid metabolism abnormalities. Accumulating evidence indicates that exopolysaccharides (EPS) could modulate the gut microbiota structure and function to prevent and treat MAFLD. Herein, a novel EPS designated BVP1 was isolated from Bacillus velezensis CGMCC 24752. Structural analysis revealed that BVP1 is a neutral α-mannan consisting of a backbone of 1,2,6-linked α-D-Manp, with branches composed of T-linked α-D-Manp, 1,2-linked α-D-Manp, and 1,3-linked α-D-Manp. Animal experiments showed that BVP1 significantly alleviated hepatic steatosis, liver injury and inflammation, and enhanced antioxidant activity in MAFLD mice. Single-nucleus RNA sequencing analysis revealed that BVP1 could restore HFD-induced imbalances in liver sinusoidal endothelial cells, hepatic stellate cells, macrophages and Kupffer cells by upregulating the expression of the lipid degradation gene Cps1 and downregulating the expression of the lipid synthesis gene Acsl1 in these cell subpopulations. Interestingly, BVP1 reshaped the gut microbiota and fecal metabolite profile by enriching beneficial bacteria and associated metabolites including salicylic acid, spermidine, and 4-hydroxyphenyl acetate. Fecal microbiota transplantation experiments verified that the anti-MAFLD effects are mediated by the BVP1-modified gut microbiota. Our findings highlight the potential of BVP1 as a promising therapeutic agent for MAFLD treatment. Show less
no PDF DOI: 10.1016/j.carbpol.2025.124150
CPS1
Zuoyi Zhang, Yanmin Cui, Xiushan Zhang +2 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
This study isolated a high-molecular-weight Morchella esculenta polysaccharide (MEP-1), mainly composed of glucose with a triple-helix structure. MEP-1 alleviated high-fat diet (HFD)-induced hepatic l Show more
This study isolated a high-molecular-weight Morchella esculenta polysaccharide (MEP-1), mainly composed of glucose with a triple-helix structure. MEP-1 alleviated high-fat diet (HFD)-induced hepatic lipid metabolic disorders and inflammation by significantly reducing the levels of TC, TG, LDL-C, TNF-α, IL-6, and IL-1β, especially at the high dose. Transcriptomic analysis revealed that arginine biosynthesis was the most significantly enriched pathway after MEP-1 intervention. Specifically, MEP-1 upregulated Ass1 and Cps1 expression to promote L-arginine biosynthesis, which subsequently activated the AMPK/Sirt1/PGC-1α signaling axis, thereby enhancing fatty acid oxidation (FAO) and ameliorating lipid metabolism disorders. This study further delineates a novel protective mechanism for MEP-1 ameliorating HFD-induced lipid metabolism disorders and providing a theoretical foundation for its application in functional food. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.146361
CPS1
Jingbo Ma, Xuejuan Zi, Shuo Wu +6 more · 2025 · Bioresource technology · Elsevier · added 2026-04-24
A meta-analysis was conducted to assess the effects of citric acid (CA) on silage fermentation, and then used whole-plant cassava silage as a model to explore the underlying microbiological mechanisms Show more
A meta-analysis was conducted to assess the effects of citric acid (CA) on silage fermentation, and then used whole-plant cassava silage as a model to explore the underlying microbiological mechanisms with metagenomic and metabolomic data. The meta-analysis revealed that CA supplementation increased the dry matter, crude protein, water-soluble carbohydrate, and lactic acid contents in silage, but decreased the pH, dry matter loss, and the contents of fiber, NH Show less
no PDF DOI: 10.1016/j.biortech.2025.133025
CPS1
Zhengyue Cao, Tiantian Wang, Fumin Tai +7 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Long noncoding RNAs (lncRNAs), non-protein-coding transcripts exceeding 200 nucleotides, are critical regulators of gene expression through chromatin remodeling, transcriptional modulation, and post-t Show more
Long noncoding RNAs (lncRNAs), non-protein-coding transcripts exceeding 200 nucleotides, are critical regulators of gene expression through chromatin remodeling, transcriptional modulation, and post-transcriptional modifications. While ionizing radiation (IR) induces cellular damage through direct DNA breaks, reactive oxygen species (ROS)-mediated oxidative stress, and bystander effects, the functional involvement of lncRNAs in the radiation response remains incompletely characterized. Here, through genome-wide CRISPR activation (CRISPRa) screening in non-small cell lung cancer (NSCLC) cells, we identified LOC401312 as a novel radiosensitizing lncRNA, the stable overexpression of which significantly enhanced IR sensitivity. Transcriptomic profiling revealed that LOC401312 transcriptionally upregulates carbamoyl-phosphate synthase 1 (CPS1), a mitochondrial enzyme involved in pyrimidine biosynthesis. Notably, CPS1 overexpression recapitulated the radiosensitization phenotype observed with LOC401312 activation. Mechanistic investigations revealed that CPS1 suppresses the phosphorylation of ATM kinase (Ser1981) protein, which is a key mediator of DNA damage checkpoint activation. This study established the LOC401312-CPS1-ATM axis as a previously unrecognized regulatory network governing radiation sensitivity, highlighting the potential of lncRNA-directed metabolic rewiring to impair DNA repair fidelity. Our findings not only expand the functional landscape of lncRNAs in DNA damage response but also provide a therapeutic rationale for targeting the LOC401312-CPS1 axis to improve radiotherapy efficacy in NSCLC. Show less
📄 PDF DOI: 10.3390/ijms26125865
CPS1
Fei Li, Qin Cai, Wei Ji +3 more · 2025 · Molecular genetics and metabolism reports · Elsevier · added 2026-04-24
Carbamoyl phosphate synthetase I (CPS1) deficiency is a rare autosomal recessive metabolic abnormality cause by dysfunctionality of CPS1 and often result in unfavorable outcome. In this study, we pres Show more
Carbamoyl phosphate synthetase I (CPS1) deficiency is a rare autosomal recessive metabolic abnormality cause by dysfunctionality of CPS1 and often result in unfavorable outcome. In this study, we presented the detailed laboratory features and genetic analysis of two patients with heterozygous variants of CPS1, c.1927 A > G (p.Asn643Asp), c.2375 T > G (p.Met792Arg), c.3443 T > A (p.Met1148Lys) in patient 1; c.3784C > T (p.Arg1262Ter), c.3734 T > A (p.Leu1245His) in patient 2, respectively. c.1927 A > G (p.Asn643Asp) and c.2375 T > G (p.Met792Arg) are novel out of 5 variants and classified as variants of uncertain significance (VUS) under the guidelines of ACMG/AMP-ClinGen. Structure-based analysis of 4 missense variants indicates deleterious alterations to the protein. Since the employment of genetic testing as a clinical diagnostic tool, distinguishing pathogenic from polymorphic changes poses significant problems for geneticists. As recommendation for PP3/BP4, the computational tools for missense variant have been published, we performed a comparative evaluation for pathogenicity interpretation in our patients and in ClinVar database regarding CPS1 missense variants under the updated guidelines of ACMG/AMP-ClinGen. The application of computational tools under the ACMG/AMP-ClinGen criteria revealed an increased sensitivity for pathogenicity evaluation, from variants of uncertain significance (VUS) to likely pathogenic (LP) in previously reported cases; while for variants without clinic information in the ClinVar database, the pathogenicity assessment of VUS remained, and shows a more optimistic and reliable clinical application in molecular diagnosis. Show less
📄 PDF DOI: 10.1016/j.ymgmr.2025.101208
CPS1
Shuang Li, Chen Zhang, Renzhi Han · 2025 · Molecular therapy. Nucleic acids · Elsevier · added 2026-04-24
📄 PDF DOI: 10.1016/j.omtn.2025.102504
CPS1
Taryn Diep, Wesley Zhou, Rachel E Reyes +12 more · 2025 · Molecular therapy. Nucleic acids · Elsevier · added 2026-04-24
Carbamoyl phosphate synthetase 1 (CPS1) deficiency, a urea-cycle disorder, results in hyperammonemia initiating a sequence of adverse events that can lead to coma and death if not treated rapidly. The Show more
Carbamoyl phosphate synthetase 1 (CPS1) deficiency, a urea-cycle disorder, results in hyperammonemia initiating a sequence of adverse events that can lead to coma and death if not treated rapidly. There is a high unmet need for an effective therapeutic for this disorder, especially in early neonatal patients where mortality is excessive. However, development of an adeno-associated virus (AAV)-based approach is hampered by large cDNA size and high protein requirement. We developed an oversized AAV vector as a gene therapy to treat Show less
📄 PDF DOI: 10.1016/j.omtn.2025.102470
CPS1
Yuqing Chen, Federico Torta, Hiromi W L Koh +23 more · 2025 · Diabetologia · Springer · added 2026-04-24
This study aims to explore the association between plasma metabolites and chronic kidney disease progression in individuals with type 2 diabetes. We performed a comprehensive metabolomic analysis in a Show more
This study aims to explore the association between plasma metabolites and chronic kidney disease progression in individuals with type 2 diabetes. We performed a comprehensive metabolomic analysis in a prospective cohort study of 5144 multi-ancestral individuals with type 2 diabetes in Singapore, using eGFR slope as the primary outcome of kidney function decline. In addition, we performed genome-wide association studies on metabolites to assess how these metabolites could be genetically influenced by metabolite quantitative trait loci and performed colocalisation analysis to identify genes affecting both metabolites and kidney function. Elevated levels of 61 lipids with long unsaturated fatty acid chains such as phosphatidylethanolamines, triacylglycerols, diacylglycerols, ceramides and deoxysphingolipids were prospectively associated with more rapid kidney function decline. In addition, elevated levels of seven amino acids and three lipids in the plasma were associated with a slower decline in eGFR. We also identified 15 metabolite quantitative trait loci associated with these metabolites, within which variants near TM6SF2, APOE and CPS1 could affect both metabolite levels and kidney functions. Our study identified plasma metabolites associated with prospective renal function decline, offering insights into the underlying mechanism by which the metabolite abnormalities due to fatty acid oversupply might reflect impaired β-oxidation and associate with future chronic kidney disease progression in individuals with diabetes. Show less
📄 PDF DOI: 10.1007/s00125-024-06324-z
CPS1
Chunli Wei, Dongmei Xu, Jingliang Cheng +9 more · 2025 · Scientific reports · Nature · added 2026-04-24
DHX36 is an ATP-dependent DNA/RNA helicase that unwinds the guanine-quadruplexes (G4s) of DNA or RNA and regulates their metabolism for key biological functions. Breast cancer is a malignant tumor and Show more
DHX36 is an ATP-dependent DNA/RNA helicase that unwinds the guanine-quadruplexes (G4s) of DNA or RNA and regulates their metabolism for key biological functions. Breast cancer is a malignant tumor and effective targeted therapy drugs are limited, even though chemotherapy is generally used. In this study, we found that overexpression of DHX36 promotes breast cancer cell growth, migration, and invasion in vitro, while knocking down or knocking out reversed in vitro and in vivo. Moreover, DHX36 was highly expressed in most clinical breast tumor tissues compared with the matched healthy tissues. Accordingly, higher DHX36 expression correlated with poor recurrence-free survival (RFS) in the patients of breast cancer. These results substantiate that DHX36 might be a diagnostic and prognostic biomarker and is a proto-oncogene that promotes the growth and metastasis of breast cancer. Thus, targeting DHX36-associated G4s in genes, particularly in proto-oncogenes, might be a novel anticancer strategy. Show less
📄 PDF DOI: 10.1038/s41598-025-30889-3
DHX36
Xiaodong Li, Yaning Fu, Yalan Luo +3 more · 2025 · Redox biology · Elsevier · added 2026-04-24
Glioblastoma is the most aggressive form of primary brain tumor, characterized with poor prognosis and resistance to conventional therapies. Increasing evidence points to oxidative stress and redox dy Show more
Glioblastoma is the most aggressive form of primary brain tumor, characterized with poor prognosis and resistance to conventional therapies. Increasing evidence points to oxidative stress and redox dysregulation as important contributors to glioblastoma progression. Previously, chloride intracellular channel protein 4 (CLIC4), a redox-sensitive protein, has been implicated in cancer biology. However, its roles in glioblastoma remain poorly understood. Here, we found that CLIC4 expression is upregulated in glioblastoma tissues and cell lines, and is positively correlated with tumor malignancy and poor survival outcomes in patients with glioblastoma. Gene silencing of CLIC4 significantly reduces glioblastoma cell viability, migration, and proliferation in vitro and suppress tumor growth in vivo. Mechanistically, CLIC4 appears to maintain redox homeostasis by regulating mitochondrial functions, including membrane potential, mass, ROS production, and the activity of complexes III and IV. Moreover, a G-quadruplex (G4) structure located in CLIC4 promoter region is related to CLIC4 upregulation by oxidative stress in glioblastoma. This G4 structure can be readily oxidized to a parallel conformation, thereby enhancing its binding with DHX36 protein to promote gene transcription. Collectively, these findings position CLIC4 as a pivotal modulator of oxidative stress in glioblastoma and a potential target for developing therapeutic approaches for the treatment of glioblastoma. Show less
📄 PDF DOI: 10.1016/j.redox.2025.103917
DHX36
Xiaolan Chen, Jin You, Qin Ma +7 more · 2025 · Nature communications · Nature · added 2026-04-24
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Al Show more
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Although the RNA moiety of most R-loops originates from linear transcripts, circular RNAs (circRNAs), outputs from back-splicing, can also hybridize with the complementary strand of a DNA duplex. However, how circRNA-associated R-loops (ciR-loops) are monitored remains elusive. Here, we identify the DEAD-box RNA helicase Brr2 as an evolutionarily-conserved ciR-loop repressor with dual roles in inhibiting circRNA generation and resolving harmful ciR-loops. Accumulation of ciR-loops caused by loss-of-function of this dual-action factor induces antisense transcription and premature transcription termination for many genes and generates significant DNA damage, which further leads to a series of defects in DNA replication, cell division and cell proliferation. We propose that functional integration of multilayered regulation by a single protein can be an efficient double protection against genome instability. Show less
📄 PDF DOI: 10.1038/s41467-025-64174-8
DHX36
Dehua Luo, Yuqing Bai, Qingling Li +5 more · 2025 · Veterinary microbiology · Elsevier · added 2026-04-24
The balance between proliferation and persistence of pseudorabies virus (PRV) in the host is crucial for its long-term survival. Understanding the mechanisms that regulate viral survival may offer new Show more
The balance between proliferation and persistence of pseudorabies virus (PRV) in the host is crucial for its long-term survival. Understanding the mechanisms that regulate viral survival may offer new strategies for disease prevention and control. The immediate-early gene 180 (IE180) is essential for PRV replication, and we previously identified a G-quadruplex (PQS18-1) located in the 3' untranslated region (3'UTR) of IE180 that enhances its expression and promotes viral replication. However, the mechanisms by which this G-quadruplex is unwound and contributes to immune evasion remain unclear. In this study, we identified the host helicase DHX36 as a binding partner of PQS18-1 through RNA pull-down assays. Both in vitro and cellular experiments demonstrated that DHX36 destabilizes the G-quadruplex, thereby suppressing gene expression and regulating PRV replication. Our findings reveal a novel host-virus interaction mechanism involving G-quadruplex structures and helicase activity, which may offer new targets for therapeutic intervention. Show less
no PDF DOI: 10.1016/j.vetmic.2025.110539
DHX36
Kun Zhang, Qichang Nie, Maolin Li +9 more · 2025 · Nucleic acids research · Oxford University Press · added 2026-04-24
RNA G-quadruplexes (rG4s) are non-canonical secondary nucleic acid structures found in the transcriptome. They play crucial roles in gene regulation by interacting with G4-binding proteins (G4BPs) in Show more
RNA G-quadruplexes (rG4s) are non-canonical secondary nucleic acid structures found in the transcriptome. They play crucial roles in gene regulation by interacting with G4-binding proteins (G4BPs) in cells. rG4-G4BP complexes have been associated with human diseases, making them important targets for drug development. Generating innovative tools to disrupt rG4-G4BP interactions will provide a unique opportunity to explore new biological mechanisms and potentially treat related diseases. Here, we have rationally designed and developed a series of rG4-based proteolytic targeting chimeras (rG4-PROTACs) aimed at degrading G4BPs, such as DHX36, a specific G4BP that regulates gene expression by binding to and unraveling rG4 structures in messenger RNAs (mRNAs). Our comprehensive data and systematic analysis reveals that rG4-PROTACs predominantly and selectively degrade DHX36 through a proteosome-dependent mechanism, which promotes the formation of the rG4 structure in mRNA, leading to the translation inhibition of rG4-containing transcripts. Notably, rG4-PROTACs inhibit rG4-mediated APP protein expression, and impact the proliferative capacity of skeletal muscle stem cells by negatively regulating Gnai2 protein expression. In summary, rG4-PROTACs provide a new avenue to understand rG4-G4BP interactions and the biological implications of dysregulated G4BPs, promoting the development of PROTACs technology based on the non-canonical structure of nucleic acids. Show less
📄 PDF DOI: 10.1093/nar/gkaf039
DHX36
L Zhang, Z Huang, M Luo +5 more · 2025 · British poultry science · Taylor & Francis · added 2026-04-24
1. Copy number variation (CNV) is an important source for identifying genetic differences. This study compared the genome-wide CNV and their regions (CNVR) across 16 Chinese local duck breeds and dete Show more
1. Copy number variation (CNV) is an important source for identifying genetic differences. This study compared the genome-wide CNV and their regions (CNVR) across 16 Chinese local duck breeds and detected key genes and pathways involved in growth and reproduction-related traits using this dataset.2. Breakdancer, Pindel and CNVnator were used to detect reliable CNV, and HandyCNV was used to obtain CNVR. Selection signatures were analysed in meat (MD) and egg-laying ducks (ED) compared to wild ducks (WD) using fixation and differentiation index DIsv methods. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out to identify key pathways and related genes.3. Principal component analysis (PCA) using CNV data clustered 127 ducks into 4 populations: WD, MD, ED and meat+egg-type ducks (MED). In total, 237,630 CNV and 6,176 CNVR were detected across these samples. Intersection analysis identified 1,384 common CNVR and 2,105 unique CNVR. The KEGG analysis showed that common CNVR were enriched in 7 basic life activity pathways, while unique CNVR were enriched in 9 population-specific pathways. Compared to WD, MD selection signatures were found in 4 enriched pathways and 8 genes ( Show less
no PDF DOI: 10.1080/00071668.2025.2559392
DLG2
Yuhang Li, Min Tan, Guang Yang +4 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
Avian leukosis (AL), a major vertically transmitted infectious disease, poses a significant challenge to the conservation and industrial development of indigenous chicken breeds in China. In this stud Show more
Avian leukosis (AL), a major vertically transmitted infectious disease, poses a significant challenge to the conservation and industrial development of indigenous chicken breeds in China. In this study, Chengkou mountain chickens were used as a model to systematically identify genetic markers associated with resistance to avian leukosis virus subgroup J (ALV-J) through a genome-wide association study (GWAS). Genomic DNA was extracted from 500 hens at 300 days of age, and cloacal swabs, plasma, and egg white samples were collected to assess the ALV-J infection status. A total of 325 ALV-positive (ALV+) and 175 ALV-negative (ALV-) individuals were identified. Based on 10× whole-genome resequencing and stringent quality control, 12,644,463 high-quality SNPs were obtained. GWAS revealed a significant enrichment of SNPs on chromosome 6 (Chr6), from which 218 SNPs significantly associated with ALV-J resistance and 49 candidate genes were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that many of these genes, including Show less
📄 PDF DOI: 10.3390/ani15101365
DLG2
HanYu Zhu, Zhaoyang Wu, Junxiao Wang +8 more · 2025 · Schizophrenia research · Elsevier · added 2026-04-24
Schizophrenia (SZ) is a severe mental disorder with high heritability. DLG2 encodes the postsynaptic scaffolding protein DLG2 (PSD93, Postsynaptic Density Protein 93), and its variants were associated Show more
Schizophrenia (SZ) is a severe mental disorder with high heritability. DLG2 encodes the postsynaptic scaffolding protein DLG2 (PSD93, Postsynaptic Density Protein 93), and its variants were associated with an increased risk of SZ. However, the role of DLG2 locus variation in SZ remains elusive. This study aims to investigate the association between DLG2 gene polymorphisms and SZ susceptibility and the relationship between DLG2 and altered brain function and clinical symptoms in SZ patients. Single nucleotide polymorphisms (SNPs) rs11607886 and rs7479949 were genotyped in 350 SZ patients and 407 healthy controls (HCs). 47 SZ patients and 79 HCs were genotyped into two groups: the risk A allele carrier group and the GG-pure group. Functional magnetic resonance imaging (fMRI) indices were further analyzed. Subsequently, data from different brain regions were correlated with clinical symptom assessment. DLG2 rs11607886 was significantly associated with SZ. Significant main effects were found in the ALFF and ReHo, especially for the left precuneus gyrus (PCu). A significant interaction between genotype and diagnosis had a significant effect on FC, which was increased between the left PCu and the right middle temporal gyrus in carriers of the A allele with SZ (r = -0.336, P The rs11607886 polymorphism in DLG2 may influence the pathogenesis of SZ and have potential effects on cognitive function. The present study emphasizes DLG2 as a candidate gene for SZ and suggests an important role for PCu in SZ. Show less
no PDF DOI: 10.1016/j.schres.2025.04.004
DLG2
Huizhen Zhang, Junjie Li, Heng Xu +3 more · 2025 · Current gene therapy · Bentham Science · added 2026-04-24
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) is a highly prevalent female malignancy. As the epigenomic characteristics of immune cells and cancer cells can serve as predict Show more
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) is a highly prevalent female malignancy. As the epigenomic characteristics of immune cells and cancer cells can serve as predictive indicators for the response to cancer immunotherapy, analysis of epigenetically modified genes (EpiGenes) could contribute to CESC treatment. The ssGSEA algorithm was employed to compute EpiGenes scores. Core genes that exhibited significant module association and a close correlation with EpiGenes scores were identified via the WGCNA package. Univariate Cox proportional hazards regression was performed on the core genes using the survival package, followed by gene set reduction via LASSO Cox regression. Ultimately, key genes were determined through multivariate Cox regression to establish a RiskScore model. Further, the optimal risk cutoff was determined using the survminer package to stratify CESC patients into high- and low-risk subgroups. For enrichment analysis, clusterProfiler and GSEA were utilized. Immune infiltration across risk groups was evaluated via ssGSEA, the MCPcounter algorithm, and the ESTIMATE algorithm. TIDE was employed to compare immunotherapeutic responses between the risk groups, while the pRRophetic software was utilized to predict patients' chemotherapeutic drug sensitivity. The biomarkers identified were validated by performing in vitro experiments. CEP78, DOCK7, DPY19L4, and POM121 were identified by computational analyses as the key genes for CESC and further validated through in vitro experiments. Pathway enrichment analysis revealed predominant enrichment in immune-related pathways in the high-risk group, whereas the low-risk group was more enriched in energy and metabolic pathways. A significant negative correlation was observed between CD8+ T cell abundance and RiskScore, with higher ESTIMATEScores and StromalScores in high-risk patients. Notably, the high-risk group also demonstrated lower potential sensitivity to immunotherapy but more active responsiveness to a broader spectrum of chemotherapeutic agents. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that module genes are significantly enriched in cell cycle regulatory pathways, and these genes, in conjunction with Human Papillomavirus (HPV) infection-induced cell cycle dysregulation, jointly participate in CESC pathogenesis, providing a mechanistic basis for understanding the disease. This study provided novel theoretical evidence for immunotherapy and chemotherapy selection in the management of CESC. Show less
no PDF DOI: 10.2174/0115665232432474251103064112
DOCK7
Yazhuo Cheng, Jingyu Li, Jiyong Shang +7 more · 2025 · Research in veterinary science · Elsevier · added 2026-04-24
Chromatin accessibility and transcription levels during oocyte growth are important for oocyte maturation and subsequent development. However, chromatin accessibility changes in porcine oocytes during Show more
Chromatin accessibility and transcription levels during oocyte growth are important for oocyte maturation and subsequent development. However, chromatin accessibility changes in porcine oocytes during growth are unclear. The present study demonstrated that porcine oocytes derived from large follicles (LFO) exhibited higher developmental capacity than those derived from small follicles (SFO). Assay for transposase-accessible chromatin using sequencing (ATAC-seq) analysis identified 1117 and 1694 uniquely accessible chromatin peaks in LFO and SFO, respectively. Motif analysis of differential peaks revealed the top 10 significantly enriched transcription factor (TF)-binding motifs in LFO versus SFO, with only one increased peak (Spi1 binding site) and nine decreased peaks (NFYA, ATOH1, ZNF549, Foxn1, HAND2, THRB, NHLH2, FoxP1, and FoxP2 binding sites). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified key processes in the regulation of oocyte growth and maturation. Integration of ATAC-seq and RNA sequencing data revealed the top 10 hub genes involved in chromatin remodeling (MYSM1 and EZH2), histone modification (MYSM1, RNF2, USP1, EZH2, and MIER1), and transcription regulation (MYSM1, ASXL3, and MIER1), as well as those involved in metabolic processes and signal transduction (DOCK7, FGGY, DTL, and DNAJC6). All these genes exhibited increased expression levels in LFO versus SFO. In conclusion, the study demonstrated the dynamic nature of chromatin accessibility during porcine oocyte growth and revealed the TFs and genes closely associated with oocyte growth and maturation. These findings provide new insight into porcine oocyte growth and offer a potential strategy to enhance the in vitro developmental ability of SFO. Show less
no PDF DOI: 10.1016/j.rvsc.2025.105565
DOCK7
Mei Ding, Fen Wang, Lan-Lan Jiang +11 more · 2025 · Translational neurodegeneration · BioMed Central · added 2026-04-24
Previous studies have shown that astrocytes can transfer healthy mitochondria to dopaminergic (DA) neurons, which may serve as an intrinsic neuroprotective mechanism in Parkinson's disease (PD). LRRK2 Show more
Previous studies have shown that astrocytes can transfer healthy mitochondria to dopaminergic (DA) neurons, which may serve as an intrinsic neuroprotective mechanism in Parkinson's disease (PD). LRRK2 G2019S is the most common pathogenic mutation associated with PD. In this study, we explored whether mitochondrial transfer is influenced by genetic and environmental factors and whether dysfunction in this process is one of the mechanisms of the pathogenic LRRK2 G2019S mutation. DA neurons and astrocytes were differentiated from induced pluripotent stem cells generated from the peripheral blood of a healthy individual and a PD patient carrying the LRRK2 G2019S mutation. A coculture system of astrocytes and DA neurons was established to explore the pathogenic mechanisms of LRRK2 G2019S. Exposure to the environmental toxin rotenone impaired mitochondrial transfer from astrocytes to DA neurons. Compared with the co-culture system from the healthy participant, the co-culture system harboring the LRRK2 G2019S mutation experienced more pronounced damage. Specifically, STX17 was colocalized with the mitochondrial outer membrane marker TOM20, and its knockdown caused damage to mitochondrial transfer. Drp1 interacted with STX17. LRRK2 G2019S-mutant astrocytes exhibited markedly increased phosphorylation of Drp1 at Ser616 upon rotenone exposure. Moreover, the degree of colocalization of STX17 with TOM20 decreased. The Drp1 phosphorylation inhibitor DUSP6 restored the colocalization of STX17 and TOM20, as well as the mitochondrial transfer efficiency and neuronal survival. The impairment of mitochondrial transfer is a potential pathogenic mechanism associated with LRRK2 G2019S mutation. The molecular mechanisms of mitochondrial transfer were observed to occur through a Drp1-STX17-dependent pathway. Notably, inhibitors for Drp1 Ser616 phosphorylation may offer neuroprotection through mitigating mitochondrial transfer impairments. This study provides novel insights into the pathogenesis of PD and the development of new therapeutic targets. Show less
📄 PDF DOI: 10.1186/s40035-025-00525-1
DUSP6
Shengfeng Deng, Guo Mu, Jun Li +3 more · 2025 · The journal of physiological sciences : JPS · Elsevier · added 2026-04-24
To investigate the mechanisms underlying sevoflurane-induced POCD, C57BL/6 J mice and SH-SY5Y cells were treated with sevoflurane for model establishment. After the treatment with sevoflurane, CCK-8, Show more
To investigate the mechanisms underlying sevoflurane-induced POCD, C57BL/6 J mice and SH-SY5Y cells were treated with sevoflurane for model establishment. After the treatment with sevoflurane, CCK-8, EdU and flow cytometry were employed to detect cell damage. The levels of N6-methyladenosine (m6A), METTL14 and DUSP6 were determined by qPCR and Western blot. The interaction between METTL14 and DUSP6 was analyzed using RIP-qPCR and Me-RIP methodologies. The cognitive function in mice were assessed by water maze test. After sevoflurane treatment, the cell viability, cell proliferation and METTL14 expression were markedly suppressed, while apoptosis was significantly enhanced. METTL14 overexpression elevated the levels of m6A and DUSP6, increased the binding level of METTL14 to DUSP6 mRNA, reducing damage to cells and cognitive dysfunction of mice. Knockdown of DUSP6 negated the beneficial effects observed with METTL14 overexpression. Sevoflurane induced POCD by regulating METTL14/DUSP6 through m6A methylation. Show less
📄 PDF DOI: 10.1016/j.jphyss.2025.100048
DUSP6
Jingjing Qi, Qian Hu, Yang Xi +5 more · 2025 · Animal genetics · Blackwell Publishing · added 2026-04-24
The beak bean, found only in waterfowl and Galliformes, aids in foraging, self-defense and pecking hard objects. Its rich coloration results from prolonged evolutionary adaptation. This study analyzed Show more
The beak bean, found only in waterfowl and Galliformes, aids in foraging, self-defense and pecking hard objects. Its rich coloration results from prolonged evolutionary adaptation. This study analyzed beak bean phenotypes of duck at 10, 20, 30 and 40 days of age, revealing that the most common type is the black beak bean, characterized by melanin deposition on the beak surface. This study performed single nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) to investigate the genetic basis of beak bean color, identifying signals on chromosome 1. The copy number variation region-based GWAS revealed a consistent candidate region overlapping with the SNP-based GWAS signals, further supporting the importance of this genomic region. Locus zoom analysis further refined the candidate regions to 48.5-50.5 and 50.8-52.8 Mb. Functional enrichment analysis highlighted six candidate genes within these regions: KITLG, DUSP6, GALNT4, MGAT4C, ATP2B1 and NTS. Notably, KITLG and DUSP6, which are linked to melanin production, were identified as key candidate genes for beak bean color. Our finding revealed the genetic basis of the bean color traits for the first time in ducks, providing a theoretical foundation and technological framework for enhancing duck beak coloration. Show less
no PDF DOI: 10.1111/age.70040
DUSP6
Yingying Qiu, Xinjun Wei, Jian Cao +9 more · 2025 · Reproductive sciences (Thousand Oaks, Calif.) · Springer · added 2026-04-24
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver Show more
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver of AM progression. In this study, we investigated the role and underlying mechanisms of endometrial mesenchymal stem cell (eMSC)-derived exosomes in regulating AAM polarization and the subsequent EMT of endometrial epithelial cells (EECs). In vitro coculture studies revealed that AM eutopic eMSCs markedly induced M2 macrophage polarization via exosomes and promoted EMT of EECs. Differentially expressed microRNAs (DE-miRNAs) between exosomes derived from normal eMSCs (N-eMSCs) and AM eutopic eMSCs (A-eMSCs) were identified using miRNA sequencing and miR-4669 was found to be the most significantly upregulated miRNA. Internalization of exosomal miR-4669 by macrophages induced their polarization toward the M2 phenotype and promoted the EMT of EECs. Mechanistic analysis using luciferase assay, mRNA sequencing, and rescue experiments revealed that miR-4669 induced M2 macrophage polarization via downregulation of DUSP6 and activation of MAPK/ERK signaling. The polarized M2 macrophages promoted the EMT of ISK cells via TGF-β1 secretion. In an AM xenograft mouse model, miR-4669 depletion inhibited AM progression by targeting the DUSP6/ERK1/2 pathway in macrophages. Overall, AM A-eMSC-derived exosomal miR-4669 facilitates M2 macrophage polarization by targeting the DUSP6/ERK signaling pathway, thereby promoting EMT of EECs via TGF-β1 secretion. These findings open avenues for developing novel preventive and therapeutic strategies for AM. Show less
📄 PDF DOI: 10.1007/s43032-025-01944-1
DUSP6
Yuchao Feng, Shu Zhang, Decheng Suo +4 more · 2025 · NPJ science of food · Nature · added 2026-04-24
Based on the Caco-2 cell heat stress model, the study explored the heat stress preventive regulatory mechanisms of key polyphenol fractions in mung bean by metabolomics and transcriptomics association Show more
Based on the Caco-2 cell heat stress model, the study explored the heat stress preventive regulatory mechanisms of key polyphenol fractions in mung bean by metabolomics and transcriptomics association analysis. Results Mung bean polyphenol intervention before heat stress significantly reduced the elevated expression level of heat shock protein 70 (HSP70) caused by 39 °C temperature. At the metabolic level, mung bean polyphenols could play a role in heat stress regulation by alleviating oxidative stress damage. At the gene level, mung bean polyphenols showed regulation of cell proliferation, differentiation, and DNA damage, with DUSP6 and NEURL3 as key regulatory genes. The correlation analysis showed that nucleotide metabolism, and oxidative phosphorylation metabolism were the key pathways in the regulation of mung bean polyphenols by heat stress. Then mung bean polyphenols can exert heat stress preventive activity through the regulation of cellular oxidative damage and energy metabolism. This study provides a good idea for the research and development of dietary intervention products for heat stress. Show less
📄 PDF DOI: 10.1038/s41538-025-00522-8
DUSP6