👤 Ding Yang

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Also published as: A Yang, A-Li Yang, Acong Yang, Ai-Lun Yang, Aige Yang, Airong Yang, Aiting Yang, Aizhen Yang, Albert C Yang, Alex J T Yang, An-Qi Yang, Andrew Yang, Angang Yang, Angela Wei Hong Yang, Anni Yang, Aram Yang, B Yang, Baigao Yang, Baixia Yang, Bangjia Yang, Bao Yang, Baofeng Yang, Baoli Yang, Baoxin Yang, Baoxue Yang, Bei Yang, Beibei Yang, Biao Yang, Bin Q Yang, Bin Yang, Bing Xiang Yang, Bing Yang, Bingyu Yang, Bo Yang, Bohui Yang, Boo-Keun Yang, Bowen Yang, Boya Yang, Burton B Yang, Byoung Chul Yang, Caimei Yang, Caixia Yang, Caixian Yang, Caixin Yang, Can Yang, Canchai Yang, Ce Yang, Celi Yang, Chan Mo Yang, Chan-Mo Yang, Chang Yang, Chang-Hao Yang, Changheng Yang, Changqing Yang, Changsheng Yang, Changwei Yang, Changyun Yang, Chanjuan Yang, Chao Yang, Chao-Yuh Yang, Chaobo Yang, Chaofei Yang, Chaogang Yang, Chaojie Yang, Chaolong Yang, Chaoping Yang, Chaoqin Yang, Chaoqun Yang, Chaowu Yang, Chaoyun Yang, Chaozhe Yang, Chen Die Yang, Chen Yang, Cheng Yang, Cheng-Gang Yang, Chengfang Yang, Chenghao Yang, Chengkai Yang, Chengkun Yang, Chengran Yang, Chenguang Yang, Chengyingjie Yang, Chengzhang Yang, Chensi Yang, Chensu Yang, Chenxi Yang, Chenyu Yang, Chenzi Yang, Chi Yang, Chia-Wei Yang, Chieh-Hsin Yang, Chien-Wen Yang, Chih-Hao Yang, Chih-Min Yang, Chih-Yu Yang, Chihyu Yang, Ching-Fen Yang, Ching-Wen Yang, Chongmeng Yang, Chuan He Yang, Chuan Yang, Chuanbin Yang, Chuang Yang, Chuanli Yang, Chuhu Yang, Chun Yang, Chun-Chun Yang, Chun-Mao Yang, Chun-Seok Yang, Chunbaixue Yang, Chung-Hsiang Yang, Chung-Shi Yang, Chung-Yi Yang, Chunhua Yang, Chunhui Yang, Chunjie Yang, Chunjun Yang, Chunlei Yang, Chunli Yang, Chunmao Yang, Chunping Yang, Chunqing Yang, Chunru Yang, Chunxiao Yang, Chunyan Yang, Chunyu Yang, Congyi Yang, Cui Yang, Cuiwei Yang, Cunming Yang, Dai-Qin Yang, Dan Yang, Dan-Dan Yang, Dan-Hui Yang, Dandan Yang, Danlu Yang, Danrong Yang, Danzhou Yang, Dapeng Yang, De-Hua Yang, De-Zhai Yang, Decao Yang, Defu Yang, Deguang Yang, Dehao Yang, Dehua Yang, Dejun Yang, Deli Yang, Dengfa Yang, Deok Chun Yang, Deshuang Yang, Di Yang, Dianqiang Yang, Ding-I Yang, Diya Yang, Diyuan Yang, Dong Yang, Dong-Hua Yang, Dongfeng Yang, Dongjie Yang, Dongliang Yang, Dongmei Yang, Dongren Yang, Dongshan Yang, Dongwei Yang, Dongwen Yang, DuJiang Yang, Eddy S Yang, Edwin Yang, Ei-Wen Yang, Emily Yang, Enlu Yang, Enzhi Yang, Eric Yang, Eryan Yang, Ethan Yang, Eunho Yang, Fajun Yang, Fan Yang, Fang Yang, Fang-Ji Yang, Fang-Kun Yang, Fei Yang, Feilong Yang, Feiran Yang, Feixiang Yang, Fen Yang, Feng Yang, Feng-Ming Yang, Feng-Yun Yang, Fengjie Yang, Fengjiu Yang, Fengjuan Yang, Fenglian Yang, Fengling Yang, Fengping Yang, Fengying Yang, Fengyong Yang, Fu Yang, Fude Yang, Fuhe Yang, Fuhuang Yang, Fumin Yang, Fuquan Yang, Furong Yang, Fuxia Yang, Fuyao Yang, G Y Yang, G Yang, Gan Yang, Gang Yang, Gangyi Yang, Gao Yang, Gaohong Yang, Gaoxiang Yang, Ge Yang, Gong Yang, Gong-Li Yang, Grace H Y Yang, Guan Yang, Guang Yang, Guangdong Yang, Guangli Yang, Guangwei Yang, Guangyan Yang, Guanlin Yang, Gui-Zhi Yang, Guigang Yang, Guitao Yang, Guo Yang, Guo-Can Yang, Guobin Yang, Guofen Yang, Guojun Yang, Guokun Yang, Guoli Yang, Guomei Yang, Guoping Yang, Guoqi Yang, Guosheng Yang, Guotao Yang, Guowang Yang, Guowei Yang, H X Yang, H Yang, Hai Yang, Hai-Chun Yang, Haibo Yang, Haihong Yang, Haikun Yang, Hailei Yang, Hailing Yang, Haiming Yang, Haiping Yang, Haiqiang Yang, Haitao Yang, Haixia Yang, Haiyan Yang, Haiying Yang, Han Yang, Hanchen Yang, Handong Yang, Hang Yang, Hannah Yang, Hanseul Yang, Hanteng Yang, Hao Yang, Hao-Jan Yang, HaoXiang Yang, Haojie Yang, Haolan Yang, Haoqing Yang, Haoran Yang, Haoyu Yang, Harrison Hao Yang, Hee Joo Yang, Heng Yang, Hengwen Yang, Henry Yang, Heqi Yang, Heyi Yang, Heyun Yang, Hoe-Saeng Yang, Hong Yang, Hong-Fa Yang, Hong-Li Yang, HongMei Yang, Hongbing Yang, Hongbo Yang, Hongfa Yang, Honghong Yang, Hongjie Yang, Hongjun Yang, Hongli Yang, Hongling Yang, Hongqun Yang, Hongxia Yang, Hongxin Yang, Hongyan Yang, Hongyu Yang, Hongyuan Yang, Hongyue Yang, Howard H Yang, Howard Yang, Hsin-Chou Yang, Hsin-Jung Yang, Hsin-Sheng Yang, Hua Yang, Hua-Yuan Yang, Huabing Yang, Huafang Yang, Huaijie Yang, Huan Yang, Huanhuan Yang, Huanjie Yang, Huanming Yang, Huansheng Yang, Huanyi Yang, Huarong Yang, Huaxiao Yang, Huazhao Yang, Hui Yang, Hui-Ju Yang, Hui-Li Yang, Hui-Ting Yang, Hui-Yu Yang, Hui-Yun Yang, Huifang Yang, Huihui Yang, Huijia Yang, Huijie Yang, Huiping Yang, Huiran Yang, Huixia Yang, Huiyu Yang, Hung-Chih Yang, Hwai-I Yang, Hye Jeong Yang, Hyerim Yang, Hyun Suk Yang, Hyun-Sik Yang, Ill Yang, Ivana V Yang, J S Yang, J Yang, James Y Yang, Jaw-Ji Yang, Jee Sun Yang, Jenny J Yang, Jerry Yang, Ji Hye Yang, Ji Yang, Ji Yeong Yang, Ji-chun Yang, Jia Yang, Jia-Ling Yang, Jia-Ying Yang, Jiahong Yang, Jiahui Yang, Jiajia Yang, Jiakai Yang, Jiali Yang, Jialiang Yang, Jian Yang, Jian-Bo Yang, Jian-Jun Yang, Jian-Ming Yang, Jian-Ye Yang, JianHua Yang, JianJun Yang, Jianbo Yang, Jiang-Min Yang, Jiang-Yan Yang, Jianing Yang, Jianke Yang, Jianli Yang, Jianlou Yang, Jianmin Yang, Jianming Yang, Jianqi Yang, Jianwei Yang, Jianyu Yang, Jiao Yang, Jiarui Yang, Jiawei Yang, Jiaxin Yang, Jiayan Yang, Jiayi Yang, Jiaying Yang, Jiayue Yang, Jichun Yang, Jie Yang, Jie-Cheng Yang, Jie-Hong Yang, Jie-Kai Yang, Jiefeng Yang, Jiehong Yang, Jieping Yang, Jiexiang Yang, Jihong Yang, Jimin Yang, Jin Yang, Jin-Jian Yang, Jin-Kui Yang, Jin-gang Yang, Jin-ju Yang, Jinan Yang, Jinfeng Yang, Jing Yang, Jing-Quan Yang, Jing-Yu Yang, Jingang Yang, Jingfeng Yang, Jinggang Yang, Jinghua Yang, Jinghui Yang, Jingjing Yang, Jingmin Yang, Jingping Yang, Jingran Yang, Jingshi Yang, Jingwen Yang, Jingya Yang, Jingyan Yang, Jingyao Yang, Jingye Yang, Jingyu Yang, Jingyun Yang, Jingze Yang, Jinhua Yang, Jinhui Yang, Jinjian Yang, Jinpeng Yang, Jinru Yang, Jinshan Yang, Jinsong Yang, Jinsung Yang, Jinwen Yang, Jinzhao Yang, Jiong Yang, Ju Dong Yang, Ju Young Yang, Juan Yang, Juesheng Yang, Jumei Yang, Jun J Yang, Jun Yang, Jun-Hua Yang, Jun-Xia Yang, Jun-Xing Yang, Junbo Yang, Jung Dug Yang, Jung Wook Yang, Jung-Ho Yang, Junhan Yang, Junjie Yang, Junlin Yang, Junlu Yang, Junping Yang, Juntao Yang, Junyao Yang, Junyi Yang, Kai Yang, Kai-Chien Yang, Kai-Chun Yang, Kaidi Yang, Kaifeng Yang, Kaijie Yang, Kaili Yang, Kailin Yang, Kaiwen Yang, Kang Yang, Kang Yi Yang, Kangning Yang, Karen Yang, Ke Yang, Keming Yang, Keping Yang, Kexin Yang, Kuang-Yao Yang, Kui Yang, Kun Yang, Kunao Yang, Kunqi Yang, Kunyu Yang, Kuo Tai Yang, L Yang, Lamei Yang, Lan Yang, Le Yang, Lei Yang, Lexin Yang, Leyi Yang, Li Chun Yang, Li Yang, Li-Kun Yang, Li-Qin Yang, Li-li Yang, LiMan Yang, Lian-he Yang, Liang Yang, Liang-Yo Yang, Liangbin Yang, Liangle Yang, Liangliang Yang, Lichao Yang, Lichuan Yang, Licong Yang, Liehao Yang, Lihong Yang, Lihua Yang, Lihuizi Yang, Lijia Yang, Lijie Yang, Lijuan Yang, Lijun Yang, Lili Yang, Lin Sheng Yang, Lin Yang, Lina Yang, Ling Ling Yang, Ling Yang, Lingfeng Yang, Lingling Yang, Lingzhi Yang, Linlin Yang, Linnan Yang, Linqing Yang, Linquan Yang, Lipeng Yang, Liping Yang, Liting Yang, Liu Yang, Liu-Kun Yang, LiuMing Yang, Liuliu Yang, Liwei Yang, Lixian Yang, Lixue Yang, Long In Yang, Long Yang, Long-Yan Yang, Longbao Yang, Longjun Yang, Longyan Yang, Lu M Yang, Lu Yang, Lu-Hui Yang, Lu-Kun Yang, Lu-Qin Yang, Luda Yang, Man Yang, Manqing Yang, Maojie Yang, Maoquan Yang, Mei Yang, Meichan Yang, Meihua Yang, Meili Yang, Meiting Yang, Meixiang Yang, Meiying Yang, Meng Yang, Menghan Yang, Menghua Yang, Mengjie Yang, Mengli Yang, Mengliu Yang, Mengmeng Yang, Mengsu Yang, Mengwei Yang, Mengying Yang, Miaomiao Yang, Mickey Yang, Min Hee Yang, Min Yang, Mina Yang, Ming Yang, Ming-Hui Yang, Ming-Yan Yang, Minghui Yang, Mingjia Yang, Mingjie Yang, Mingjun Yang, Mingli Yang, Mingqian Yang, Mingshi Yang, Mingyan Yang, Mingyu Yang, Minyi Yang, Misun Yang, Mu Yang, Muh-Hwa Yang, Na Yang, Nan Yang, Nana Yang, Nanfei Yang, Neil V Yang, Ni Yang, Ning Yang, Ningjie Yang, Ningli Yang, Pan Yang, Pan-Chyr Yang, Paul Yang, Peichang Yang, Peiran Yang, Peiyan Yang, Peiying Yang, Peiyuan Yang, Peizeng Yang, Peng Yang, Peng-Fei Yang, PengXiang Yang, Pengfei Yang, Penghui Yang, Pengwei Yang, Pengyu Yang, Phillip C Yang, Pin Yang, Ping Yang, Ping-Fen Yang, Pinghong Yang, Pu Yang, Q H Yang, Q Yang, Qi Yang, Qi-En Yang, Qian Yang, Qian-Jiao Yang, Qian-Li Yang, QianKun Yang, Qiang Yang, Qianhong Yang, Qianqian Yang, Qianru Yang, Qiaoli Yang, Qiaorong Yang, Qiaoyuan Yang, Qifan Yang, Qifeng Yang, Qiman Yang, Qimeng Yang, Qiming Yang, Qin Yang, Qinbo Yang, Qing Yang, Qing-Cheng Yang, Qingcheng Yang, Qinghu Yang, Qingkai Yang, Qinglin Yang, Qingling Yang, Qingmo Yang, Qingqing Yang, Qingtao Yang, Qingwu Yang, Qingya Yang, Qingyan Yang, Qingyi Yang, Qingyu Yang, Qingyuan Yang, Qiong Yang, Qiu Yang, Qiu-Yan Yang, Qiuhua Yang, Qiuhui Yang, Qiulan Yang, Qiuli Yang, Qiuxia Yang, Qiwei Yang, Qiwen Yang, Quan Yang, Quanjun Yang, Quanli Yang, Qun-Fang Yang, R Yang, Ran Yang, Ren-Zhi Yang, Renchi Yang, Renhua Yang, Renjun Yang, Renqiang Yang, Renzhi Yang, Ri-Yao Yang, Richard K Yang, Robert Yang, Rong Yang, Rongrong Yang, Rongxi Yang, Rongyuan Yang, Rongze Yang, Rui Xu Yang, Rui Yang, Rui-Xu Yang, Rui-Yi Yang, Ruicheng Yang, Ruifang Yang, Ruihua Yang, Ruilan Yang, Ruili Yang, Ruiqin Yang, Ruirui Yang, Ruiwei Yang, Rulai Yang, Ruming Yang, Run Yang, Runjun Yang, Runxu Yang, Runyu Yang, Runzhou Yang, Ruocong Yang, Ruoyun Yang, Ruyu Yang, S J Yang, Se-Ran Yang, Sen Yang, Senwen Yang, Seung Yun Yang, Seung-Jo Yang, Seung-Ok Yang, Shan Yang, Shangchen Yang, Shanghua Yang, Shangwen Yang, Shanzheng Yang, Shao-Hua Yang, Shaobin Yang, Shaohua Yang, Shaoling Yang, Shaoqi Yang, Shaoqing Yang, Sheng Sheng Yang, Sheng Yang, Sheng-Huei Yang, Sheng-Qian Yang, Sheng-Wu Yang, ShengHui Yang, Shenglin Yang, Shengnan Yang, Shengqian Yang, Shengyong Yang, Shengzhuang Yang, Shenhui Yang, Shi-Ming Yang, Shiaw-Der Yang, Shifeng Yang, Shigao Yang, Shijie Yang, Shiming Yang, Shipeng Yang, Shiping Yang, Shiu-Ju Yang, Shiyi Yang, Shizhong Yang, Shizhuo Yang, Shu Yang, ShuSheng Yang, Shuai Yang, Shuaibing Yang, Shuaini Yang, Shuang Yang, Shuangshuang Yang, Shucai Yang, Shufang Yang, Shuhua Yang, Shujuan Yang, Shujun Yang, Shulan Yang, Shulin Yang, Shuming Yang, Shun-Fa Yang, Shuo Yang, Shuofei Yang, Shuping Yang, Shuqi Yang, Shuquan Yang, Shurong Yang, Shushen Yang, Shuye Yang, Shuyu Yang, Si Yang, Si-Fu Yang, Sibao Yang, Sibo Yang, Sichong Yang, Sihui Yang, Sijia Yang, Siqi Yang, Sirui Yang, Sisi Yang, Sitao Yang, Siwen Yang, Siyi Yang, Siyu Yang, Sizhen Yang, Sizhu Yang, Song Yang, Song-na Yang, Songpeng Yang, Songye Yang, Soo Hyun Yang, Su Yang, Su-Geun Yang, Suhong Yang, Sujae Yang, Sujuan Yang, Suk-Kyun Yang, Sun Kyung Yang, Suwol Yang, Suxia Yang, Suyi Yang, Suyu Yang, Tai-Hui Yang, Tailai Yang, Tao Yang, Tengyun Yang, Thomas P Yang, Ti Yang, Tian Yang, Tianbao Yang, Tianfeng Yang, Tianjie Yang, Tianmin Yang, Tianpeng Yang, Tianqiong Yang, Tiantian Yang, Tianxin Yang, Tianyou Yang, Tianyu Yang, Tianze Yang, Tianzhong Yang, Ting Yang, Ting-Xian Yang, Tingting Yang, Tingyu Yang, Tong Yang, Tong Yi Yang, Tong-Xin Yang, Tonglin Yang, Tongren Yang, Tuanmin Yang, Ueng-Cheng Yang, W Yang, Wan-Chen Yang, Wan-Jung Yang, Wang Yang, Wannian Yang, Wei Qiang Yang, Wei Yang, Wei-Fa Yang, Wei-Xin Yang, Weidong Yang, Weiguang Yang, Weihan Yang, Weijian Yang, Weili Yang, Weimin Yang, Weiran Yang, Weiwei Yang, Weixian Yang, Weizhong Yang, Wen Yang, Wen Z Yang, Wen-Bin Yang, Wen-Chin Yang, Wen-He Yang, Wen-Hsuan Yang, Wen-Ming Yang, Wen-Wen Yang, Wen-Xiao Yang, WenKai Yang, Wenbo Yang, Wenchao Yang, Wending Yang, Wenfei Yang, Wenhong Yang, Wenhua Yang, Wenhui Yang, Wenjian Yang, Wenjie Yang, Wenjing Yang, Wenjuan Yang, Wenjun Yang, Wenli Yang, Wenlin Yang, Wenming Yang, Wenqin Yang, Wenshan Yang, Wentao Yang, Wenwen Yang, Wenwu Yang, Wenxin Yang, Wenxing Yang, Wenying Yang, Wenzhi Yang, Wenzhu Yang, William Yang, Woong-Suk Yang, Wu Yang, Wu-de Yang, X Yang, X-J Yang, Xi Yang, Xi-You Yang, Xia Yang, Xian Yang, Xiang Yang, Xiang-Hong Yang, Xiang-Jun Yang, Xianggui Yang, Xianghong Yang, Xiangliang Yang, Xiangling Yang, Xiangqiong Yang, Xiangxiang Yang, Xiangyu Yang, Xiao Yang, Xiao-Dong Yang, Xiao-Fang Yang, Xiao-Hong Yang, Xiao-Jie Yang, Xiao-Juan Yang, Xiao-Meng Yang, Xiao-Ming Yang, Xiao-Qian Yang, Xiao-Yan Yang, Xiao-Ying Yang, Xiao-Yu Yang, Xiao-guang Yang, XiaoYan Yang, Xiaoao Yang, Xiaobin Yang, Xiaobo Yang, Xiaochen Yang, Xiaodan Yang, Xiaodi Yang, Xiaodong Yang, Xiaofei Yang, Xiaofeng Yang, Xiaohao Yang, Xiaohe Yang, Xiaohong R Yang, Xiaohong Yang, Xiaohuang Yang, Xiaohui Yang, Xiaojian Yang, Xiaojie Yang, Xiaojing Yang, Xiaojuan Yang, Xiaojun Yang, Xiaoli Yang, Xiaolu Yang, Xiaomeng Yang, Xiaoming Yang, Xiaonan Yang, Xiaoping Yang, Xiaoqian Yang, Xiaoqin Yang, Xiaoqun Yang, Xiaorong Yang, Xiaoshan Yang, Xiaoshi Yang, Xiaosong Yang, Xiaotian Yang, Xiaotong Yang, Xiaowei Yang, Xiaowen Yang, Xiaoxiao Yang, Xiaoxin Yang, Xiaoxu Yang, 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Yongxing Yang, Yongzhong Yang, Yoon La Yang, Yoon Mee Yang, Youhua Yang, YoungSoon Yang, Yu Yang, Yu-Fan Yang, Yu-Feng Yang, Yu-Jie Yang, Yu-Shi Yang, Yu-Tao Yang, Yu-Ting Yang, Yuan Yang, Yuan-Han Yang, Yuan-Jian Yang, Yuanhao Yang, Yuanjin Yang, Yuanquan Yang, Yuanrong Yang, Yuanying Yang, Yuanzhang Yang, Yuanzhi Yang, Yuchen Yang, Yucheng Yang, Yue Yang, Yueh-Ning Yang, Yuejin Yang, Yuexiang Yang, Yueze Yang, Yufan Yang, Yuhan Yang, Yuhang Yang, Yuhua Yang, Yujie Yang, Yujing Yang, Yulin Yang, Yuling Yang, Yulong Yang, Yun Yang, YunKai Yang, Yunfan Yang, Yung-Li Yang, Yunhai Yang, Yunlong Yang, Yunmei Yang, Yunwen Yang, Yunyun Yang, Yunzhao Yang, Yupeng Yang, Yuqi Yang, Yuta Yang, Yutao Yang, Yuting Yang, Yutong Yang, Yuwei Yang, Yuxi Yang, Yuxing Yang, Yuxiu Yang, Yuyan Yang, Yuyao Yang, Yuying Yang, Z Yang, Zaibin Yang, Zaiming Yang, Zaiqing Yang, Zanhao Yang, Ze Yang, Zemin Yang, Zeng-Ming Yang, Zengqiang Yang, Zengqiao Yang, Zeyu Yang, Zhang Yang, Zhangping Yang, Zhanyi Yang, 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Yang, Zihan Yang, Ziheng Yang, Zijiang Yang, Zishan Yang, Zixia Yang, Zixuan Yang, Ziying Yang, Ziyou Yang, Ziyu Yang, Zong-de Yang, Zongfang Yang, Zongyu Yang, Zunxian Yang, Zuozhen Yang
articles
Jiahui Yang, Xiaoying Ru, Yang Huang +6 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
The greater amberjack (
📄 PDF DOI: 10.3390/ani15030333
LPL
Hongzheng Lu, Siqi Yang, Wei Li +3 more · 2025 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
Dietary interventions with food-derived natural products have emerged as a promising strategy to alleviate obesity. This study aims to investigate the anti-obesity effect of
📄 PDF DOI: 10.3390/foods14030459
LPL
Hao Zheng, Yan Li, Wen-Wen Zhan +5 more · 2025 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
Copper clusters with diverse luminescent properties are of particular interest. In this study, a series of Cu
no PDF DOI: 10.1002/anie.202423787
LPL
Gayatri Arani, Amit Arora, Shuai Yang +21 more · 2025 · medRxiv : the preprint server for health sciences · Cold Spring Harbor Laboratory · added 2026-04-24
Physical activity (PA), including sedentary behavior, is associated with many diseases, including Alzheimer's disease and all-cause dementia. However, the specific biological mechanisms through which Show more
Physical activity (PA), including sedentary behavior, is associated with many diseases, including Alzheimer's disease and all-cause dementia. However, the specific biological mechanisms through which PA protects against disease are not entirely understood. To address this knowledge gap, we first assessed the conventional observational associations of three self-reported and three device-based PA measures with circulating levels of 2,911 plasma proteins measured in the UK Biobank (n Show less
📄 PDF DOI: 10.1101/2025.01.16.25320290
LPL
Meng-Ke Song, Meng-Fan Gu, Ling Liu +7 more · 2025 · Arthritis research & therapy · BioMed Central · added 2026-04-24
Metabolism alteration is a common complication of rheumatic arthritis (RA). This work investigated the reason behind RA-caused triglyceride (TG) changes. Fresh RA patients' whole blood was transfused Show more
Metabolism alteration is a common complication of rheumatic arthritis (RA). This work investigated the reason behind RA-caused triglyceride (TG) changes. Fresh RA patients' whole blood was transfused into NOD-SCID mice. Metabolism-regulatory tissues were examined after sacrifice. To verify the findings, tissues of the rats with long-lasting adjuvant-induced arthritis (AIA) were analyzed. Some rats were injected with human plasma and GPIHBP1, and their blood TG was monitored. Various cells were stimulated by cytokines or rheumatic subjects' serum. Some pre-adipocytes were cultured by human serum or in the presence of HUVEC cells and GPIHBP1. TG decrease occurred in blood and white adipose tissues (WAT) of the RA blood-transfused NOD-SCID mice and chronic AIA rats. Fatty acids (FA) oxidation in muscles was accelerated a bit, while TG catabolism status in their livers was varied. TNF-α, IL-1β, IL-6 and RA/AIA serum promoted expression of TG utilization-related enzymes and FA uptake transporters in pre-adipocytes, but barely affected LPL. Mild IL-6 stimulus promoted GPIHBP1 release of HUVEC cells. GPIHBP1 was increased in RA serum. This change can decrease blood TG in rats, which was overshadowed by an injection of excessive GPIHBP1. RA serum slightly inhibited LPL secretion in pre-adipocytes. Both HUVEC cells co-culture and GPIHBP1 supplement reduced LPL distribution on pre-adipocytes, and eliminated LPL activity difference between normal and RA serum-treated cells. No TG uptake difference was observed in these circumstances. RA-associated inflammation induces GPIHBP1 secretion of endothelial cells, which facilitates blood TG hydrolysis and uptake to compensate the loss in WAT. Show less
📄 PDF DOI: 10.1186/s13075-025-03483-1
LPL
Meimei Zhang, Haixin Bai, Ruixue Wang +5 more · 2025 · Journal of animal science and biotechnology · BioMed Central · added 2026-04-24
The objective of this study was to evaluate the effects of dietary fatty acids (FA) saturation and lysophospholipids supplementation on growth, meat quality, oxidative stability, FA profiles, and lipi Show more
The objective of this study was to evaluate the effects of dietary fatty acids (FA) saturation and lysophospholipids supplementation on growth, meat quality, oxidative stability, FA profiles, and lipid metabolism of finishing beef bulls. Thirty-two Angus bulls (initial body weight: 623 ± 22.6 kg; 21 ± 0.5 months of age) were used. The experiment was a completely randomized block design with a 2 × 2 factorial arrangement of treatments: 2 diets with FA of different degree of unsaturation [high saturated FA diet (HSFA) vs. high unsaturated FA diet (HUFA)] combined with (0.075%, dry matter basis) and without lysophospholipids supplementation. The bulls were fed a high-concentrate diet (forage to concentrate, 15:85) for 104 d including a 14-d adaptation period and a 90-d data and sample collection period. No interactions were observed between dietary FA and lysophospholipids supplementation for growth and meat quality parameters. A greater dietary ratio of unsaturated FA (UFA) to saturated FA (SFA) from 1:2 to 1:1 led to lower DM intake and backfat thickness, but did not affect growth performance and other carcass traits. Compared with HSFA, bulls fed HUFA had greater shear force in Longissimus thoracis (LT) muscle, but had lower intramuscular fat (IMF) content and SOD content in LT muscle. Compared with HUFA, feeding the HSFA diet up-regulated expression of ACC, FAS, PPARγ, and SCD1, but down-regulated expression of CPT1B. Compared with feeding HSFA, the HUFA diet led to greater concentrations of c9-C18:1 and other monounsaturated FA in LT muscle. Feeding HUFA also led to lower plasma concentrations of cholesterol, but there were no interactions between FA and lysophospholipids detected. Feeding lysophospholipids improved growth and feed conversion ratio and altered meat quality by increasing muscle pH Results indicated that supplementing a high-concentrate diet with lysophospholipids to beef bulls can enhance growth rate, feed efficiency, meat quality, and beneficial FA. Increasing the dietary ratio of UFA to SFA reduced DM intake and backfat thickness without compromising growth, suggesting potential improvements in feed efficiency. Show less
📄 PDF DOI: 10.1186/s40104-024-01138-w
LPL
Yawei Wang, Fu You, Zhenyi Huang +7 more · 2025 · Comparative biochemistry and physiology. Toxicology & pharmacology : CBP · Elsevier · added 2026-04-24
Olanzapine (OLZ) is widely used in the treatment of schizophrenia, and its metabolic side effects have garnered significant attention in recent years. Despite this, the specific side effects of OLZ an Show more
Olanzapine (OLZ) is widely used in the treatment of schizophrenia, and its metabolic side effects have garnered significant attention in recent years. Despite this, the specific side effects of OLZ and the underlying mechanisms remain inadequately understood. To address this gap, zebrafish (Danio rerio) were exposed to OLZ at concentrations of 35.5, 177.5, and 355.5 μg/L. The results indicated that exposure to OLZ significantly increased body weight, total cholesterol (TC), low-density lipoprotein (LDL), and triglycerides (TG). Histological analysis revealed notable lipid accumulation in the liver. Furthermore, lipid synthesis genes, including sterol regulatory element binding protein (srebp), acetyl CoA carboxylase (acc), and fatty acid synthesis gene (fas), were up-regulated. In contrast, genes related to lipid decomposition, such as lipoprotein lipase (lpl), hormone-sensitive triglyceride lipase (hsl), and carnitine palmitoyltransferase 1b (cpt1b), were down-regulated. Subsequent analysis of zebrafish behavior showed reduced motor activity, sociability, and anxiety-like behavior in OLZ-exposed zebrafish, consistent with the results of neurotransmitter related gene expression. Following OLZ treatment, the expression of tryptophan hydroxylase (tph), tyrosine hydroxylase (th), dopamine transporter (dat), glutaminase (glsa), and glutamic acid decarboxylase 1b (gad1b) was upregulated. Additionally, the diversity of intestinal flora decreased after OLZ exposure, and the structure of the intestinal microbiota changed significantly compared to the control group. At the genus level, the abundance of Plesiomonas was upregulated, while the abundances of Bacillus and Cetobacterium were downregulated in the OLZ-exposed group. Furthermore, the results of the correlation analysis indicated that lipid metabolism and behavioral changes were closely associated with the microbiota. This study clarified the side effects of OLZ, and also provided a basis for the reasonable discharge concentration of OLZ in water and clinical drug use. Show less
no PDF DOI: 10.1016/j.cbpc.2025.110120
LPL
Yue Li, Rui Gao, Zhiyan Yang +2 more · 2025 · Life sciences · Elsevier · added 2026-04-24
To investigate the mechanism of liraglutide affecting lipid metabolism by regulating lipolysis and lipogenesis in cells and ob/ob mice. 3 T3-L1 cells were treated with liraglutide in vitro, and differ Show more
To investigate the mechanism of liraglutide affecting lipid metabolism by regulating lipolysis and lipogenesis in cells and ob/ob mice. 3 T3-L1 cells were treated with liraglutide in vitro, and differentially expressed genes were screened by RNA sequencing. Gene Ontology (GO) and KEGG (Kvoto Encyclopedia of Genes and Genomes) enrichment analyses identified target genes for lipid regulation of liraglutide. 3 T3-L1 preadipocytes were induced to differentiate into adipocytes using a "cocktail method". Western blot and immunofluorescence were used to detect the expression of target genes and the lipid regulatory effect of liraglutide. 3 T3-L1 preadipocytes were transfected with lentivirus overexpressing Zbtb20 to study its role in adipogenesis, and gene expression was analyzed by RT-qPCR and Western blot. In vivo, ob/ob mice were subcutaneously injected with liraglutide or saline for 4 weeks. Blood lipids, adipose tissue volume and adipocyte size were detected. Immunohistochemical analysis and RT-qPCR were used to detect the expression of target genes in adipose tissue. Liraglutide reduced lipid droplets and TG levels and altered the expression of genes related to fatty acid metabolism, lipogenesis, fatty acid oxidation, and adipocyte browning. The results of PCR, Western blot and immunofluorescence confirmed that liraglutide could regulate the adipogenesis by downregulating the transcriptional suppressor ZBTB20, and overexpression of Zbtb20 inhibited the expression of LPL, the key enzyme for lipohydrolysis. Liraglutide regulates lipid metabolism through ZBTB20-LPL pathway to reveal its molecular mechanism. Show less
no PDF DOI: 10.1016/j.lfs.2024.123267
LPL
Guangfan Liu, Fen Su, Xingyue Zou +2 more · 2025 · Animal bioscience · added 2026-04-24
This study aimed to assess the impact of a prolonged photoperiod on the growth performance and lipid metabolism of weaned piglets. Twenty-four piglets weaned at 28 days of age were randomly dichotomiz Show more
This study aimed to assess the impact of a prolonged photoperiod on the growth performance and lipid metabolism of weaned piglets. Twenty-four piglets weaned at 28 days of age were randomly dichotomized into two groups that were alternatively subjected to either long photoperiod (LP) group (16 L:8 D) or short photoperiod (SP) group (10 L:14 D) for 42days. Four replicates of three animals per replicates were used per experimental treatment. Our results demonstrated that prolonged photoperiod increased piglet body weight, average daily weight gain (ADG), backfat thickness (BF), backfat index during the nursery period, and increased ADG, average daily feed intake (ADFI), and decreased the F/G of piglets during the experiment days 29 to 42. Meanwhile, we observed LP piglets' plasma melatonin, growth hormone and serotonin levels were decreased at 14 d and 42 d compared to SP piglets. Moreover, up-regulated mRNA or protein expression of PPARγ and CEBPα, and lower mRNA or protein expression of MTR1, ATGL, HSL, PPARα, and CPT1α, were observed in back subcutaneous fat of LP group compared with that of SP group. Significant increases were observed in the mRNA or protein contents of lipogenic genes, including C/EBPα, SREBP-1c, ACCα, and FAS, in the liver of LP piglets, whereas CPT1α and ACOX1 mRNA levels and PPARα and MTR1 protein expression were significantly downregulated in LP group compared to SP group. Extended photoperiod also increased lipid content in longissimus dorsi muscle that was associated with higher mRNA or protein levels of SREBP-1c, ACCα, FAS, Pref1, and LPL, decreased mRNA or protein contents of LeptinR, MTR1, HSL, and ACOX1. Together, these findings suggest that there is an advantage, in terms of growth performance and fat deposition, in imposing a prolonged light program (16-h light/d) on nursery piglets to alleviate the negative aspects of weaning stress. Show less
📄 PDF DOI: 10.5713/ab.24.0270
LPL
Thami Wiseman Ndlandla, Fu Yuan Cheng, Chao Wei Huang +1 more · 2025 · Animal bioscience · added 2026-04-24
This study evaluated the potential of Bacillus amyloliquefaciens to improve growth performance and meat quality in finishing pigs. Thirty-two female Landrace×Duroc pigs, 21 weeks old with initial body Show more
This study evaluated the potential of Bacillus amyloliquefaciens to improve growth performance and meat quality in finishing pigs. Thirty-two female Landrace×Duroc pigs, 21 weeks old with initial body weight 77.45±3.29 kg, were divided into two groups: a control group (basal diet) and a probiotic group (basal diet with Bacillus amyloliquefaciens at 1×109 CFU/kg). Body weight and average daily gain (ADG) were recorded at the start and at fortnight intervals for a 56-d feeding trial. At the end of the experiment, carcass traits, meat quality and intramuscular fat related gene expression of longissimus dorsi muscle were analyzed. The probiotic group showed significantly higher final body weight and D0-D56 ADG (p<0.05). Additionally, the probiotic group had greater carcass weight, back fat thickness and marbling score (p<0.05), while the lean meat percentage remained unchanged. Meat quality analysis revealed that the probiotic group had a higher b* value (5.47) (p<0.05), and a lower shear value (p<0.001), but there was no effect on the a* value and water holding capacity. Moreover, probiotic treatment increased the gene expression of fatty acid uptake and regulators, such as lipoprotein lipase (LPL), cluster of differentiation 36 (CD36), and solute carrier family 27 member 1 (SLC27A1) (p<0.05). Our findings suggest that the supplementation of Bacillus amyloliquefaciens not only enhanced growth performance and carcass weight in finishing pigs, but also improved marbling and tenderness in the longissimus dorsi muscle through the upregulation of lipogenic-genes related to fat accumulation. This indicates its potential as feed additive to enhance pork quality. Show less
📄 PDF DOI: 10.5713/ab.24.0399
LPL
Baoxin Yang, Wenxuan Wang, Cuiwen Jian +5 more · 2025 · Applied biochemistry and biotechnology · Springer · added 2026-04-24
In this study, 39 strains of lactic acid bacteria were screened from several fermented foods. Based on the evaluation of functional and prebiotic properties, Lactiplantibacillus plantarum SDJ09 was se Show more
In this study, 39 strains of lactic acid bacteria were screened from several fermented foods. Based on the evaluation of functional and prebiotic properties, Lactiplantibacillus plantarum SDJ09 was selected as a promising candidate. It gave a 48.16% cholesterol reduction and 33.73% pancreatic lipase inhibition in cells; exhibited high resistance to acid, bile salts, and gastrointestinal fluid; and had strong antibacterial activity and high adhesion capabilities. More importantly, the lipid-lowering effect of L. plantarum SDJ09 was also investigated using 3T3-L1 mature adipocytes and HepG2 nonalcoholic fatty liver disease models. L. plantarum SDJ09 effectively decreased triglyceride accumulation by more than 50% in both cell models, in which the expression of PPARγ, C/EBPα, aP2, and LPL in 3T3-L1 cells was significantly downregulated by L. plantarum SDJ09. L. plantarum SDJ09 also improved lipid metabolism by downregulating the expression of HMGCR, SREBP-1c, ACC, and FAS and upregulating the expression of CYP7A1 in HepG2 nonalcoholic steatohepatitis cells. Therefore, L. plantarum SDJ09 has the potential to effectively decrease obesity and non-alcoholic fatty liver disease (NAFLD) by inhibiting lipid accumulation, providing a prospective probiotic agent for anti-obesity. Show less
📄 PDF DOI: 10.1007/s12010-024-05034-x
LPL
Haijiao Wang, Lifang Wang, Meng Wang +8 more · 2025 · Drug delivery and translational research · Springer · added 2026-04-24
Emodin has been proven to have weight-reducing and lipid-lowering effects. In order to make emodin play a better anti-obesity role, we designed and developed an emodin loaded dissolving microneedle pa Show more
Emodin has been proven to have weight-reducing and lipid-lowering effects. In order to make emodin play a better anti-obesity role, we designed and developed an emodin loaded dissolving microneedle patch, in which emodin existed in the form of emodin-polyvinylpyrrolidone co-precipitate (Emodin-PVP). Meanwhile, polydopamine (PDA) was added to the microneedle patch (PDA-Emodin-PVP-MN) for photothermal-enhanced chemotherapy of obesity. The average weight of the patch was 0.1 ± 0.05 g and the drug loading was 0.37 ± 0.031 mg. After 5 min of NIR irradiation (808 nm, 0.6 W/cm Show less
📄 PDF DOI: 10.1007/s13346-024-01623-9
LPL
Ting Ding, Yanjun Diao, Ruiqing Fu +11 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
As one of the most common malignant tumors in men, prostate cancer (PCa) still lacks convenient, non-invasive and highly specific diagnostic markers. The advantages of Extracellular vesicle (EV) DNA i Show more
As one of the most common malignant tumors in men, prostate cancer (PCa) still lacks convenient, non-invasive and highly specific diagnostic markers. The advantages of Extracellular vesicle (EV) DNA in tumor diagnosis have gradually attracted the attention of researchers. However, methylation detection, which is more advantageous than mutation detection in tumor diagnosis, has not been widely practiced in EV DNA, and its value in PCa diagnosis also remains underexplored. This study aims to establish and optimize an EV DNA methylation detection system and evaluate its diagnostic and classification potential for PCa. We characterized EV DNA biological properties, optimized pretreatment strategies, validated its correlation with genomic DNA methylation, and explored urine EV DNA methylation targets in 86 benign prostatic hyperplasia (BPH) and 109 PCa patients across three cohorts (screening: 30 BPH/33 PCa; training: 27 BPH/30 PCa; validation: 29 BPH/46 PCa). Heterogeneous biological characteristics were observed among DNA from different subtypes of EV, but methylation profiles remained consistent across subtypes and post-DNase I treatment. EV DNA accurately reflected the methylation state of source cell genomic DNA. By combining our screening results with data from the TCGA database and previously reported, we developed a panel consisting of 667 PCa-specific methylation targets for detection. Among these, six methylation sites (MACF1、LINC01359-1、LINC01359-2、ADCY4、GAPLINC、C19orf25) demonstrated high diagnostic value for PCa, enabling construction of PCa and aggressive PCa differential diagnosis model with AUCs up to 0.74 and 0.91 respectively. The diagnostic value of these six markers was further confirmed using methylight PCR in the validation cohort which also displayed promising performance as a tool for diagnosing PCa. This study highlights the potential of urine EV DNA methylation as a novel diagnostic marker for PCa and lays a foundation for future EV DNA research. Show less
no PDF DOI: 10.1016/j.jare.2025.09.056
MACF1
Jun-Hua Ji, Min Yang, Yan Jiang +5 more · 2025 · Zhongguo shi yan xue ye xue za zhi · added 2026-04-24
To investigate the whole-genome differential methylation profile of patients with high-altitude polycythemia (HAPC). In this study, a total of 20 adult male patients with HAPC were included, including Show more
To investigate the whole-genome differential methylation profile of patients with high-altitude polycythemia (HAPC). In this study, a total of 20 adult male patients with HAPC were included, including 10 Tibetan and 10 Han patients. The control group consisted of 20 healthy adult males, including 10 Tibetan and 10 Han patients. Peripheral blood was collected from each group for DNA extraction and quality inspection, and DNA libraries were constructed. The differential methylation regions (DMRs) between groups were detected using reduced representation bisulfite sequencing, with enriched regions compared to those of the control group. The differential enrichment regions were selected, and the intersection of the enriched regions was associated with genes. The methylation enrichment regions that differed significantly between groups were filtered based on the number of enriched samples in the enriched regions between the groups. GO, KEGG functional, and pathway analysis were performed on the differentially associated gene sets to reveal significant differences between the patients and control groups at the functional and pathway levels. In comparison with the control group, 17 152 sites with more than 25% difference and 15 558 sites with less than -25% difference were identified in Tibetan patients. The top 5 genes with the largest methylation differences between the two groups were The occurrence of HAPC may be related to abnormal changes in DNA methylation, and methylation sites may be helpful for the early diagnosis of HAPC. Show less
no PDF DOI: 10.19746/j.cnki.issn.1009-2137.2025.02.041
MLLT10
Haojie Yang, Xiaoyan Xie, Liling Lin +5 more · 2025 · Clinical breast cancer · Elsevier · added 2026-04-24
To evaluate potential genetic causal relationships between chronic pain subtypes like migraine and multi-site chronic pain (MCP) and their impact on breast cancer occurrence and survival rates. The as Show more
To evaluate potential genetic causal relationships between chronic pain subtypes like migraine and multi-site chronic pain (MCP) and their impact on breast cancer occurrence and survival rates. The association between chronic pain and breast cancer was reported before, yet the causal nature between them remained uncertain. Data on chronic pain and breast cancer were sourced from publicly available European genome-wide association study (GWAS) datasets. Genetic association between chronic pain and breast cancer phenotypes was assessed using linkage disequilibrium genetic correlation (LDSC). Colocalization analysis further identified potential shared causal variation. Based on Inverse variance weighted method, 2-sample Mendelian Randomization (MR) was conducted to investigate causal associations between migraine, MCP, and breast cancer or breast cancer survival. Sensitive analysis was conducted to ensure the absence of heterogeneity and horizontal pleiotropy. LDSC demonstrated significant genetic correlations between migraine and both estrogen receptor-negative (ER-) and overall breast cancer, while also revealing a notable genetic association between MCP and ER- and ER+ breast cancer, as well as overall breast cancer. Through colocalization analysis, potential involvement of rs2183271, located in MLLT10 gene, in regulating MCP and ER+ breast cancer was identified. MR analysis revealed the association between migraine and elevated risk of ER- breast cancer (IVW, P = 4.95 × 10 Our results provided new insights into the role of migraine and MCP in breast cancer, paving the way for targeted preventive strategies and future investigations. Show less
no PDF DOI: 10.1016/j.clbc.2025.02.004
MLLT10
Rong Song, Kai Li, Hongxia He +7 more · 2025 · Life sciences · Elsevier · added 2026-04-24
To determine whether insulin controls hepatic de novo lipogenesis (DNL) through an HCF-1-dependent modulation of ChREBP that is distinct from the canonical SREBP1c pathway. AML-12 mouse hepatocytes we Show more
To determine whether insulin controls hepatic de novo lipogenesis (DNL) through an HCF-1-dependent modulation of ChREBP that is distinct from the canonical SREBP1c pathway. AML-12 mouse hepatocytes were subjected to 10 μg/mL insulin and 25 mM glucose for 6 h. IRβ or HCF-1 was knocked down with lentiviral shRNA (≈80 % efficiency). Lipid droplets were quantified by Nile-Red staining; mRNA and protein levels were measured by RT-qPCR, Western blot, immunofluorescence and RNA-seq. Co-immunoprecipitation was used to test complex formation. Insulin reduced lipid accumulation and suppressed ChREBP protein and its nuclear localization in AML-12 hepatocytes without altering SREBP1c. Knock-down of IRβ or HCF-1 abolished insulin-mediated ChREBP suppression, increased lipid droplets and up-regulated lipogenic genes. HCF-1 co-immunoprecipitated with IRβ, indicating formation of an insulin-responsive IRβ/HCF-1 complex that restrains ChREBP-driven lipogenesis. We identify an IRβ/HCF-1/ChREBP regulatory node in hepatocytes that can repress lipogenic genes independently of SREBP1c. The axis constitutes a testable target for understanding selective insulin action on hepatic lipid metabolism and for future in-vivo studies of fatty-liver disease. Show less
no PDF DOI: 10.1016/j.lfs.2025.124046
MLXIPL
Lihua Liu, Lu Zhang, Yiwen Liao +9 more · 2025 · International journal of obesity (2005) · Nature · added 2026-04-24
The association between obesity and cholelithiasis has been identified. However, the causal relationship between age-specific childhood obesity and adult cholelithiasis remains unclear. In addition, t Show more
The association between obesity and cholelithiasis has been identified. However, the causal relationship between age-specific childhood obesity and adult cholelithiasis remains unclear. In addition, the biological basis for the association between childhood obesity and adult cholelithiasis is poorly understood, which poses a challenge for preventing adult cholelithiasis in specific biological pathways. Summary statistics of genome-wide association studies (GWASs) of childhood age-specific body mass index (BMI) at 12 time points and adult cholelithiasis derived from FinnGen were used in this study, with the former covering data from birth to 8 years. Linkage disequilibrium score regression (LDSC) analyses were used to assess the genetic correlations of age-specific childhood BMI to cholelithiasis. Two-sample Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) analyses were utilized to explore the causal associations. As downstream analyses, summary-based Mendelian randomization (SMR) analyses, transcriptome-wide association studies (TWAS), and Bayesian colocalization were conducted to discover the shared transcriptomic signals. The GWAS summary statistics of cholelithiasis from the UK Biobank were used for sensitivity analyses. LDSC analyses revealed significant genetic correlations between 11 age-specific childhood BMIs and adult cholelithiasis (except for birth BMI). Two-sample MR and MVMR analyses indicated causal relationships between birth BMI and BMI at 8 months, 1.5 years, 7 years, and 8 years after birth and adult cholelithiasis. SMR, TWAS, and colocalization analyses identified MLXIPL as the strongest overlapping signal between age-specific BMI and adult cholelithiasis. This study provides new evidence on the relationships between childhood obesity and adult cholelithiasis, highlighting the role of early intervention for obesity in childhood at key time points. MLXIPL gene expression was identified as a potential biological pathway, suggesting potential therapeutic targets and precise intervention strategies for childhood obesity and adult cholelithiasis. Show less
📄 PDF DOI: 10.1038/s41366-025-01877-4
MLXIPL
Hui Chen, Guanggang Meng, Aiting Yang · 2025 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Non-alcoholic steatohepatitis (NASH) is characterized by hepatic lipid accumulation and fibrosis, yet the molecular mechanisms linking metabolic dysfunction to extracellular matrix (ECM) remodeling re Show more
Non-alcoholic steatohepatitis (NASH) is characterized by hepatic lipid accumulation and fibrosis, yet the molecular mechanisms linking metabolic dysfunction to extracellular matrix (ECM) remodeling remain poorly defined. This study investigated the role of laminin γ2 (LAMC2, encoded by Lamc2), a basement membrane component, in NASH pathogenesis. Using a high-fat choline-deficient l-amino acid-defined (HF-CDAA) diet-induced murine NASH model and AML12 hepatocytes, we assessed LAMC2 expression via qPCR, immunohistochemistry, and lipidomics. Functional studies included LAMC2 overexpression (adenovirus) and TGFβ pathway inhibition (SB431542). LAMC2 was markedly upregulated in steatotic hepatocytes and localized adjacent to lipid droplets. Laminin-332 (Ln-332), which contains the γ2 chain (LAMC2), directly amplified lipogenesis by increasing Srebf1 and Mlxipl gene expression. TGFβ1 signaling via TGFBR1/Fra2 drove LAMC2 expression. Crucially, LAMC2 amplified both lipogenesis and fibrogenesis, thereby forming a feedforward loop that exacerbated hepatic fibrosis in this predominantly fibrotic NASH model. In vivo, LAMC2 overexpression exacerbated hepatic lipid accumulation and collagen deposition in the HF-CDAA diet-induced NASH model compared to controls. Fra2 silencing via AAV-shRNA attenuated NASH progression. LAMC2 bridges metabolic and fibrotic reprogramming in NASH through TGFβ1/Fra2-dependent mechanisms. Targeting this ECM-metabolism axis, particularly LAMC2 or Fra2, offers novel therapeutic strategies for fibrosis-dominant NASH, addressing a critical unmet clinical need. Show less
no PDF DOI: 10.1016/j.bbrc.2025.152266
MLXIPL
Juntai Zhang, Yan Cai, Yan Qin +6 more · 2025 · Renal failure · Taylor & Francis · added 2026-04-24
Diabetic kidney disease (DKD), characterized by mesangial fibrosis and renal dysfunction, is a major microvascular complication of diabetes. Studies have shown that miRNAs are closely related to the p Show more
Diabetic kidney disease (DKD), characterized by mesangial fibrosis and renal dysfunction, is a major microvascular complication of diabetes. Studies have shown that miRNAs are closely related to the progression of DKD. Therefore, in this study, we aimed to explore whether miR-1225-3p can regulate Smad ubiquitin regulatory factor 2 (SMURF2)-mediated carbohydrate response element binding protein (ChREBP) ubiquitination through Rho GTPase-activating protein 5 (ARHGAP5) to affect fibrosis in DKD. DKD mice were established by intraperitoneally injecting streptozocin (STZ), and a DKD cell model was generated by culturing in media supplemented with 25 mmol/L glucose (high glucose, HG). StarBase was used to predict the target binding sites between miR-1225-3p and ARHGAP5, and a dual-luciferase reporter gene assay was used to verify this relationship. Western blotting, RT-qPCR, flow cytometry, immunoprecipitation, ELISAs, HE staining, and Masson staining were used to detect relevant indicators. ARHGAP5 and SMURF2 expression was decreased, but ChREBP was highly expressed in the renal tissue of DKD mice and HG-induced mouse mesangial cells (MMCs). miR-1225-3p could target and regulate the transcription of ARHGAP5, and an association between ARHGAP5 and SMURF2 was revealed. miR-1225-3p facilitated fibrosis and oxidative stress in MCCs by inhibiting ARHGAP5. In addition, SMURF2 promoted the ubiquitination of HA-ChREBP, and miR-1225-3p facilitated fibrosis and oxidative stress by mediating the ARHGAP5/SMURF2-mediated ubiquitination of ChREBP in MCCs. Furthermore, the miR-1225-3p inhibitor inhibited fibrosis and inflammation in the renal tissues of DKD mice. miR-1225-3p facilitates fibrosis and oxidative stress by mediating ARHGAP5/SMURF2-mediated ubiquitination of ChREBP. Show less
📄 PDF DOI: 10.1080/0886022X.2025.2484632
MLXIPL
Shawn Fayer, Riddhiman K Garge, Melissa Hopkins +18 more · 2025 · medRxiv : the preprint server for health sciences · Cold Spring Harbor Laboratory · added 2026-04-24
Multiplexed assays of variant effect (MAVEs) systematically measure variant function but have been limited to cancer cell lines rather than disease-relevant cell types. We developed saturation genome Show more
Multiplexed assays of variant effect (MAVEs) systematically measure variant function but have been limited to cancer cell lines rather than disease-relevant cell types. We developed saturation genome editing in human iPSCs (iPSC-SGE) to introduce variant libraries into a single allele of a target gene while programming the genetic background of the second allele, enabling variant assessment across differentiated cell types and genetic contexts at scale. We edited 1,137 variants into Show less
📄 PDF DOI: 10.1101/2025.11.12.25340127
MYBPC3
Dongping Liu, Mingyu Yang, Shasha Fan +6 more · 2025 · Stem cell research · Elsevier · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is an inherited cardiovascular disorder characterized by left ventricular hypertrophy and an elevated risk of sudden cardiac death. Cardiac myosin binding protein C ( Show more
Hypertrophic cardiomyopathy (HCM) is an inherited cardiovascular disorder characterized by left ventricular hypertrophy and an elevated risk of sudden cardiac death. Cardiac myosin binding protein C (MYBPC3) is the most frequently mutated gene leading to HCM. In this study, peripheral blood mononuclear cells isolated from an HCM patient harboring a heterozygous MYBPC3 missense mutation (c.3072C > A; p.S1024R) were reprogrammed via Sendai virus vectors to generate a patient-specific induced pluripotent stem cell (iPSC) line. The iPSC line exhibits normal morphology and karyotype, alongside definitive hallmarks of pluripotency, including trilineage differentiation potential. Show less
no PDF DOI: 10.1016/j.scr.2025.103841
MYBPC3
Jie Wang, Dominic Russ, Yongsan Yang +10 more · 2025 · Precision clinical medicine · Oxford University Press · added 2026-04-24
No studies have explored the genetic differences between the Chinese and other ethnic hypertrophic cardiomyopathy (HCM) populations. This cross-sectional study included Chinese patients ( Chinese HCM Show more
No studies have explored the genetic differences between the Chinese and other ethnic hypertrophic cardiomyopathy (HCM) populations. This cross-sectional study included Chinese patients ( Chinese HCM patients have a higher proportion of rare variants (52.8% vs 13.6%, Our findings suggested that patients of Chinese ancestry with HCM have a higher proportion of rare variants but are less likely to be classified as P/LP variants in HCM genes than those of European origin. The variants of c.3624del in Show less
📄 PDF DOI: 10.1093/pcmedi/pbaf019
MYBPC3
Oumaima Laghzali, Shahriar Shalikar, Siqin Liu +8 more · 2025 · Biomedicines · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/biomedicines13051193
MYBPC3
Teng Wu, Tongsheng Huang, Honglin Ren +26 more · 2025 · Circulation research · added 2026-04-24
Individuals with diabetes are susceptible to cardiac dysfunction and heart failure, potentially resulting in mortality. Metabolic disorders frequently occur in patients with diabetes, and diabetes usu Show more
Individuals with diabetes are susceptible to cardiac dysfunction and heart failure, potentially resulting in mortality. Metabolic disorders frequently occur in patients with diabetes, and diabetes usually leads to remodeling of heart structure and cardiac dysfunction. However, the contribution and underlying mechanisms of metabolic and structural coupling in diabetic cardiac dysfunction remain elusive. Two mouse models of type 2 diabetes (T2DM) were used to assess alterations in glucose/lipid metabolism and cardiac structure. The potential metabolic-structural coupling molecule ACBP (acyl-coenzyme A-binding protein) was screened from 4 published datasets of T2DM-associated heart disease. In vivo loss-of-function and gain-of-function approaches were used to investigate the role of ACBP in diabetic cardiac dysfunction. The underlying mechanisms of metabolic and structural coupling were investigated by stable-isotope tracing metabolomics, coimmunoprecipitation coupled with mass spectrometry, and chromatin immunoprecipitation sequencing. Diabetic mouse hearts exhibit enhanced lipid metabolism and impaired ultrastructure with marked cardiac systolic and diastolic dysfunction. Analysis of 4 T2DM public datasets revealed that Our findings demonstrated that ACBP mediates the bidirectional regulation of cardiomyocyte metabolic and structural associations and identified a promising therapeutic target for ameliorating cardiac dysfunction in patients with T2DM. Show less
no PDF DOI: 10.1161/CIRCRESAHA.124.326044
MYBPC3
Amara Greer-Short, Anna Greenwood, Elena C Leon +27 more · 2025 · Nature communications · Nature · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) affects approximately 600,000 people in the United States. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM, Show more
Hypertrophic cardiomyopathy (HCM) affects approximately 600,000 people in the United States. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM, with the majority of mutations resulting in haploinsufficiency. To restore cardiac MYBPC3, we use an adeno-associated virus (AAV9) vector and engineer an optimized expression cassette with a minimal promoter and cis-regulatory elements (TN-201) to enhance packaging efficiency and cardiomyocyte expression. Rather than simply preventing cardiac dysfunction preclinically, we demonstrate in a symptomatic MYBPC3-deficient murine model the ability of AAV gene therapy to reverse cardiac hypertrophy and systolic dysfunction, improve diastolic dysfunction, and prolong survival. Dose-ranging efficacy studies exhibit restoration of wild-type MYBPC3 protein levels and saturation of cardiac improvement at the clinically relevant dose of 3E13 vg/kg, outperforming a previously published construct. These findings suggest that TN-201 may offer therapeutic benefits in MYBPC3-associated cardiomyopathy, pending further validation in clinical settings. Show less
📄 PDF DOI: 10.1038/s41467-025-57481-7
MYBPC3
Jinli Chen, Yang Xing, Jie Sun +4 more · 2025 · Frontiers in bioscience (Landmark edition) · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is a hereditary disease of the myocardium characterized by asymmetric hypertrophy (mainly the left ventricle) not caused by pressure or volume load. Most cases of HCM Show more
Hypertrophic cardiomyopathy (HCM) is a hereditary disease of the myocardium characterized by asymmetric hypertrophy (mainly the left ventricle) not caused by pressure or volume load. Most cases of HCM are caused by genetic mutations, particularly in the gene encoding cardiac myosin, such as Show less
no PDF DOI: 10.31083/FBL25714
MYBPC3
Tao Lu, Changsheng Zhu, Changrong Nie +5 more · 2025 · Journal of the American Heart Association · added 2026-04-24
Sex differences in patients with hypertrophic cardiomyopathy have been elaborated by many studies. However, large studies of the association of patient sex with outcomes after surgical myectomy are sc Show more
Sex differences in patients with hypertrophic cardiomyopathy have been elaborated by many studies. However, large studies of the association of patient sex with outcomes after surgical myectomy are scarce. This study evaluated sex disparities in a large Chinese cohort undergoing hypertrophic cardiomyopathy surgery. The cohort encompassed 1613 patients, including 627 (38.9%) women who underwent septal myectomy between 2009 and 2018. At the time of surgery, women were 6 years older and had 1 year longer disease onset-to-surgery delay than men. They were more frequently in New York Heart Association class III/IV and had more severe left ventricular outflow tract obstruction. Compared with men, women had a notably higher left ventricular wall thickness index and a lower extent of late gadolinium enhancement. Women also had more mutations in In patients with obstructive hypertrophic cardiomyopathy, women had a similar fatal outcome but a worse nonfatal outcome than men after surgery. Measures improving quality of life may further enhance the event-free survival of female patients. Close monitoring and follow-up are warranted, especially in younger men and older women. Show less
📄 PDF DOI: 10.1161/JAHA.124.038421
MYBPC3
X R Chen, S J Yang, S H Zhao · 2025 · Zhonghua xin xue guan bing za zhi · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112148-20240511-00255
MYBPC3
Hye-Won Cho, Hyeseon Kim, Jeong-Min Kim +9 more · 2025 · Orphanet journal of rare diseases · BioMed Central · added 2026-04-24
Pediatric hypertrophic cardiomyopathy (HCM) is a rare condition, particularly in neonates, and is characterized by rapid and extensive myocardial hypertrophy, often leading to severe clinical outcomes Show more
Pediatric hypertrophic cardiomyopathy (HCM) is a rare condition, particularly in neonates, and is characterized by rapid and extensive myocardial hypertrophy, often leading to severe clinical outcomes. HCM can arise from variants in sarcomeric genes, which are essential for myocardial contractions, as well as non-sarcomeric gene variants. Although genetic modifiers and oligogenic inheritance have been implicated in congenital heart disease and cardiomyopathy, their complexity in HCM has not been fully elucidated, especially in familial cases with variable phenotypes. Hence, this study aims to investigate the genetic architecture in a family with a history of cardiac disease and neonatal HCM, focusing on oligogenic inheritance of non-sarcomeric variants. Clinical data and blood samples were collected for genetic analysis. Whole genome sequencing (WGS) and bioinformatic analyses identified compound heterozygous variants in the MYO19 gene. Maternally inherited variants were analyzed because the proband's mother was also diagnosed with HCM. WGS was performed on the patient's maternal grandfather and aunt, who have cardiac disease, revealing candidate genetic variants that may contribute to the cardiac phenotype. Compound heterozygous MYO19 variants were identified in the neonatal patient. Missense c.203C > G (p.A68G) and frameshift c.275₂₇₆del (p.E92Vfs*19) variants were identified, which were located in the myosin motor domain, a functionally crucial region of the MYO19 protein. Maternally inherited missense variants were identified in SURF1 and ETFDH. All three genes are associated with mitochondrial function, and in silico prediction tools suggest that these variants are likely damaging. Other candidate genetic variants possibly contributing to the cardiac phenotype were also detected in the extended maternal family. To the best of our knowledge, this study represents the first report proposing MYO19 as a candidate gene for HCM and highlights the potential role of oligogenic inheritance in the etiology of the disease. Furthermore, plausible candidate variants of other mitochondria-related genes, such as MYO19, SURF1, and ETFDH, were identified, and other family members were investigated to support the pathogenesis of HCM further. Given the limited understanding of the genetics of pediatric HCM, these findings contribute valuable insights into its genetic basis in pediatric patients. Show less
no PDF DOI: 10.1186/s13023-025-03871-5
MYO19
Qizhen Feng, Wenlin Yang, Guohao Su +2 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Necrosis induced by sodium overload has recently been identified as a novel form of regulated cell death. However, the specific genes associated with sodium overload in breast cancer (BC) remain uncha Show more
Necrosis induced by sodium overload has recently been identified as a novel form of regulated cell death. However, the specific genes associated with sodium overload in breast cancer (BC) remain uncharacterized. We identified 753 differentially expressed sodium-overload-related genes (DESORGs) in BC. We performed pathway enrichment analyses, then used univariate Cox regression to select 67 prognostic DESORGs. To build prognostic models, we tested 101 combinations of ten machine learning algorithms. SHAP analysis was used to determine feature importance. Mendelian randomization (MR) was applied to assess causal effects. Experimental validation (in vitro) included overexpression and knockdown studies. GSEA/GSVA and molecular docking were conducted to explore downstream pathways and potential drug candidates. The ridge regression model showed optimal prognostic power. IFNG was identified as the key feature. The computed risk score was an independent prognostic factor, outperforming traditional clinical variables (AUC = 0.845), and a nomogram built with it yielded good calibration (C-index = 0.815). MR suggested a protective causal effect of NR1H3 in BC, and patients with high NR1H3 expression had significantly better overall survival (p = 0.02). These findings highlight NR1H3 as a novel DESORG and a promising therapeutic target in breast cancer. Show less
no PDF DOI: 10.3389/fimmu.2025.1653903
NR1H3