👤 Jia-Da 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-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, Youchen 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 Li, Yuwei Li, Yuxi Li, Yuxiang Li, Yuxin Li, Yuxiu Li, Yuxuan Li, Yuyan Li, Yuying Li, Yuyun Li, Yuzhe Li, Yvonne Li, Z Li, Z-H Li, Zaibo Li, Ze Li, Ze-An Li, Zecai Li, Zechuan Li, Zehan Li, Zehua Li, Zejian Li, Zemin Li, Zengyang Li, Zequn Li, Zesong Li, Zexu Li, Zeyu Li, Zeyuan Li, Zezhi Li, Zhan Li, Zhandong Li, Zhang Li, Zhanjun Li, Zhankui Li, Zhanquan Li, Zhantao Li, Zhao Li, Zhao-Cong Li, Zhao-Yang Li, Zhaobing Li, Zhaohan Li, Zhaojin Li, Zhaoliang Li, Zhaolun Li, Zhaoping Li, Zhaosha Li, Zhaoshui Li, Zhaoyong Li, Zhe Li, Zhehui Li, Zhen Li, Zhen-Hua Li, Zhen-Jia Li, Zhen-Li Li, Zhen-Xi Li, Zhen-Yu Li, Zhen-Yuan Li, Zhenbei Li, Zhencheng Li, Zhencong Li, Zhenfei Li, Zhenfen Li, Zheng Li, Zheng-Dao Li, Zhengda Li, Zhenghao Li, Zhenghui Li, Zhengjie Li, Zhengliang Li, Zhenglong Li, Zhengnan Li, Zhengpeng Li, Zhengrui Li, Zhenguang Li, Zhengwei Li, Zhengyang Li, Zhengyao Li, Zhengying Li, Zhengyu Li, Zhenhao Li, Zhenhua Li, Zhenhui Li, Zhenjia Li, Zhenjun Li, Zhenli Li, Zhenlu Li, Zhenming Li, Zhenshu Li, Zhenyan Li, Zhenyu Li, Zhenzhe Li, Zhenzhou Li, Zheyun Li, Zhi Li, Zhi-Bin Li, Zhi-Gang Li, Zhi-Jian Li, Zhi-Peng Li, Zhi-Wei Li, Zhi-Xing Li, Zhi-Yong Li, Zhi-Yuan Li, Zhi-qiang Li, Zhibin Li, Zhichao Li, Zhifan Li, Zhifei Li, Zhigang Li, Zhigao Li, Zhihao Li, Zhihong Li, Zhihua Li, Zhihui Li, Zhijia Li, Zhijie Li, Zhijun Li, Zhilei Li, Zhimei Li, Zhiming Li, Zhipeng Li, Zhiping Li, Zhiqiang Li, Zhiqiong Li, Zhiquan Li, Zhirong Li, Zhisheng Li, Zhiwei Li, Zhixiong Li, Zhixuan Li, Zhiyang Li, Zhiyi Li, Zhiyong Li, Zhiyu Li, Zhiyuan Li, Zhizhong Li, Zhizong Li, Zhong Li, Zhong-Xin Li, Zhongcai Li, Zhongding Li, Zhonggen Li, Zhonghua Li, Zhongjie Li, Zhonglian Li, Zhonglin Li, Zhongwen Li, Zhongxia Li, Zhongxian Li, Zhongxuan Li, Zhongyu Li, Zhongzhe Li, Zhou Li, Zhouhua Li, Zhouxiang Li, Zhu Li, Zhuang Li, Zhuangzhuang Li, Zhuanjian Li, Zhuo Li, Zhuo-Rong Li, Zhuoran Li, Zhuorong Li, Zi-Zhan Li, Zichao Li, Zihai Li, Zihan Li, Zihao Li, Zihua Li, Zihui Li, Zijian Li, Zijing Li, Zili Li, Ziliang Li, Zilin Li, Zilu Li, Zimeng Li, Ziming Li, Zipeng Li, Ziqi Li, Ziqiang Li, Ziqing Li, Ziru Li, Zirui Li, Ziwen Li, Zixiao Li, Ziyang Li, Ziyu Li, Ziyue Li, Ziyun Li, Zizhuo Li, Zong-Xue Li, Zongchao Li, Zongdi Li, Zongfang Li, Zonghong Li, Zonghua Li, Zongjun Li, Zonglin Li, Zongyi Li, Zongyu Li, Zongyun Li, Zongzhe Li, Zu-Ling Li, Zu-guo Li, Zulong Li, Zunjiang Li, Zuo-Lin Li
articles
Qing Li, Jing Xu, Zi Xiong +1 more · 2025 · Diabetes research and clinical practice · Elsevier · added 2026-04-24
Lipoprotein(a) [Lp(a)], one of the major residual cardiovascular risks, is a highly polymorphic low-density lipoprotein (LDL)-like particle. Epidemiological and Mendelian randomization studies have su Show more
Lipoprotein(a) [Lp(a)], one of the major residual cardiovascular risks, is a highly polymorphic low-density lipoprotein (LDL)-like particle. Epidemiological and Mendelian randomization studies have suggested that elevated Lp(a) is a causal risk factor for atherosclerotic cardiovascular disease (ASCVD) due to its pro-inflammatory, pro-atherogenic and pro-thrombotic properties. However, metabolic and pathological mechanisms of Lp(a) remain under-investigated. Recent genomic and population studies show that very low Lp(a) levels are associated with increased risk of type 2 diabetes mellitus (T2DM). Thus, whether potent Lp(a)-lowering therapies might increase the risk of T2DM incident has been raised as a potential issue from recent guidelines. This review details Lp(a)-induced inflammation and thrombosis evidences, the underlying mechanisms of Lp(a) in ASCVD, and the complicated associations and potential mechanistic effects of Lp(a) on the development of T2DM. Current evidences tend to favor that the anti-atherogenic benefits of lowering Lp(a) shall override the paradoxical negative impact on the new-onset T2DM. The risk-benefit assessments for potent Lp(a)-lowering therapies are warranted. Show less
no PDF DOI: 10.1016/j.diabres.2025.112940
LPA
Jin Xiang, Yan Xiong, Heting Liang +5 more · 2025 · Frontiers in aging neuroscience · Frontiers · added 2026-04-24
This study aimed to identify the latent profiles of cognitive function among community-dwelling and institutionalized older adults, and to examine their associated influencing factors, in order to inf Show more
This study aimed to identify the latent profiles of cognitive function among community-dwelling and institutionalized older adults, and to examine their associated influencing factors, in order to inform the development of targeted interventions. A convenience sampling method was used to select 6,708 elderly people aged 60 years and older from six communities and nine long-term care institutions across China, who were assessed using a general information questionnaire, Mini-Mental State Examination (MMSE), the Frailty Scale, the Anxiety Scale, the Depression Scale, and the Pittsburgh Sleep Quality Index. Latent profile analysis (LPA) was performed based on the MMSE scores, and multiple logistic regression was used to analyse the influencing factors of cognitive function categories. A total of three cognitive function profiles were identified: High cognitive Function group (41.2%), Moderate Cognitive Function Group (48.2%) and Low cognitive Function group (10.7%). Higher Frailty [odds ratio (ORs) = 1.070-1.246], higher depressive symptom scores (OR = 1.059-1.191) and poorer sleep quality (higher PSQI; OR = 1.088) were associated with higher odds of belonging to the Moderate/Low cognitive profiles, whereas adequate social support (Yes vs. No; OR = 0.530-0.696), selected middle-income categories versus ≥¥6,000 in per-capita monthly household income (OR = 0.462-0.735) and male sex (OR = 0.556-0.876) were associated with lower odds. Cognitive function among older adults can be classified into three distinct latent profiles, each associated with different influencing factors. These findings underscore the need for stratified and personalized interventions at the community level to support stratified screening and tailored community programs; given the cross-sectional design, these associations do not establish causality or intervention effects. Show less
📄 PDF DOI: 10.3389/fnagi.2025.1622804
LPA
Jingxian Yu, Mingjie Wu, Yongqi Liang +3 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profil Show more
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profiles of death anxiety in Chinese youth and examine the predictive roles of self-esteem, perceived social support, and security. We conducted a cross-sectional survey of 623 young adults ( Three latent death anxiety profiles emerged, High Death Anxiety (56.2%), Moderate Cognition and Low Death Anxiety (8.8%), and Low Cognition and Moderate Death Anxiety (35%). Higher self-esteem ( Death anxiety among young adults is heterogeneous, influenced by distinct psychological profiles and demographic factors. Interventions should prioritize enhancing self-esteem, social support networks, and security to mitigate death anxiety, especially in high-risk subgroups. Future research should employ longitudinal designs and cross-cultural samples to validate causal pathways and refine targeted strategies. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1594720
LPA
Dan Li, Mi Zhou, Xiaomei Song · 2025 · Frontiers in aging · Frontiers · added 2026-04-24
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity beh Show more
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity behaviours within a 24-h framework. This study investigates the relationship between cognitive function and 24-h activity behaviours in older adults, further exploring whether these associations differ by sex. This study analyses data from the eighth wave of the Survey of Health, Ageing and Retirement in Europe, conducting a cross-sectional analysis of 814 older adults. Cognitive function was assessed using the SHARE-Cog tool, encompassing 10-word immediate recall, 10-word delayed recall, verbal fluency, and self-reported memory. 24-h activity behaviours (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], sedentary behaviour [SB], and sleep) were objectively measured with thigh-worn accelerometers. Compositional multivariate linear regression models were constructed using compositional data as the response variable, with cognitive function measures as predictors. Higher MVPA was linked to better cognitive outcomes (verbal fluency, 10-word immediate recall, and 10-word delayed recall) while SB and longer sleep related to poorer performance, with these associations being stronger in women (model p ≤ 0.001). Among women, cognitive outcomes were significantly associated with all activity behaviours (p range = 0.010-0.045). Women who self-reported poor memory and scored 0 on the verbal fluency spent approximately 45% of their day in SB, whereas those reporting excellent memory and scoring 60 spent 40.06% (37.18%, 42.86%) and 36.41% (31.53%, 41.10%) of their day sedentary, respectively. In contrast, men's 24-h activity composition did not vary significantly with cognitive function (p range = 0.051-0.845). Older adults with better cognitive function tend to engage in more PA and reduce sedentary and sleep time. This relationship differed by sex, with females' activity behaviours being more sensitive to cognitive function changes. These findings suggest that interventions promoting healthy lifestyles in older adults should account for cognitive function, particularly in females. Show less
📄 PDF DOI: 10.3389/fragi.2025.1686847
LPA
Ting Li, Li-Juan Wang, Ai-Jun Cui +4 more · 2025 · BMC public health · BioMed Central · added 2026-04-24
This study aimed to identify and characterize the sedentary behavior (SED) and breaks accumulation patterns of children and adolescents and investigate the associations of these derived patterns with Show more
This study aimed to identify and characterize the sedentary behavior (SED) and breaks accumulation patterns of children and adolescents and investigate the associations of these derived patterns with adiposity indicators. A total of 348 children and 562 adolescents from China participated in this study. Accelerometers were used to measure the bouts of SED and breaks. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), and fat mass index (FMI). Latent profile analysis was used to identify the SED and breaks accumulation patterns on the basis of 11 compositions of SED bouts and breaks. Mixed-effects multivariable linear regression models were used to analyze the associations of accumulation patterns with adiposity indicators. Four accumulation patterns were identified in children: "prolonged sitters" (N = 77, 22.1%), "shortened sitters" (N = 90, 25.9%), "LPA breakers" (N = 69, 19.8%), and "MVPA breakers"(N = 112, 32.2%). "MVPA breakers" had significantly lower BMI z-score, FM%, and FMI than "prolonged sitters." No significant differences in adiposity indicators were observed among the other three patterns. In adolescents, "prolonged sitters" (N = 250, 44.5%), "moderate sitters" (N = 211, 37.5%), and "breakers" (N = 101, 18.0%) were identified. "Breakers" had the lowest BMI z-score, FM%, and FMI among the three groups, followed by "moderate sitters" and "prolonged sitters." Different accumulation patterns of SED and breaks were identified for children and adolescents in China. Among them, "MVPA breakers" and "Breakers" are most beneficial to maintain a normal weight status. Health promotion efforts could consider increasing MVPA and decreasing SED time for children and restricting SED to at least 30 min for adolescents to improve their adiposity indicators. Show less
📄 PDF DOI: 10.1186/s12889-025-24540-z
LPA
Ziqiang Lin, Jiade Chen, Yutai Cai +16 more · 2025 · BMC public health · BioMed Central · added 2026-04-24
The mediation effect of 24-hour physical activities on the association between type 2 diabetes and mortality is unclear. Additionally, Little evidence was found on the isotemporal substitution effect Show more
The mediation effect of 24-hour physical activities on the association between type 2 diabetes and mortality is unclear. Additionally, Little evidence was found on the isotemporal substitution effect of 24-hour physical activities components on changing Life expectancy among patients with type 2 diabetes diagnosed. To address the abovementioned research gap, the study has a two-fold aims: first, to examine the mediation effect of 24-hour physical activities in type 2 diabetes and mortality; and second, to address how reallocating time on different daily activities would affect life expectancy. Analysis was conducted on the accelerometer data of 103,359 participants in the UK Biobank, with a median age of 57 years (range 39 to 70). Compositional mediation cox model was conducted to analyze the mediating effects of 24-hour physical activities. Additionally, the cohort Life table method was utilized to estimate the changes of Life-years over the next 10 years resulting from the substitution effect of different physical activities. During a mean follow-up of 13.95 (range 2.95-16.28) years, 2,649 deaths were recorded. Diabetes was significantly associated with increased time spent engaging in sedentary behavior (SB), and reduced time spent on moderate-to-vigorous physical activity (MVPA) and light-intensive physical activity (LPA), thereby demonstrating an association with higher mortality risk. The indirect effect of physical activity (HR = 1.27, 95% CI 1.23-1.30) accounted for 41.9% of the total effect of diabetes on mortality. Furthermore, the Life expectancy gains with a maximum of 1.32 years over the next 10 years was found when reallocating SB time to MVPA. The results revealed that 24-hour physical activities might mediate the association between diabetes and mortality. Therefore, promoting participation in MVPA and reducing sedentary activities among diabetes patients was expected to have a positive effect on Life expectancy over the next 10 years. Show less
📄 PDF DOI: 10.1186/s12889-025-24662-4
LPA
Zhengliang Li, Xiaokai Chen, Juan Wang +6 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
To investigate the risk factors associated with coronary heart disease (CHD) in patients with metabolic-associated fatty liver disease (MAFLD) and develop a nomogram prediction model. This study inclu Show more
To investigate the risk factors associated with coronary heart disease (CHD) in patients with metabolic-associated fatty liver disease (MAFLD) and develop a nomogram prediction model. This study included 394 patients with MAFLD who underwent coronary angiography at The Affiliated Hospital of Qingdao University between December 2019 and December 2024. The study cohort was divided in a 7:3 ratio into training and validation sets comprising 277 and 117 cases, respectively. The training group was further divided into the MAFLD-only ( Of the 394 MAFLD cases, 313 had CHD-related complications. Of the 277 patients in the training set, 220 had CHD, and of the 117 patients in the validation set, 93 had CHD. LASSO regression analysis revealed that the following variables were associated with the risk of CHD: sex, lipoprotein(a) (Lp[a]), low-density lipoprotein cholesterol, white blood cell count (WBC), glycated triglyceride-glucose index (TyG), and atherosclerosis index (AIP). Multivariate logistic regression analysis revealed that sex, Lp(a), WBC, TyG, and AIP were independent risk factors for CHD in MAFLD cases. A nomogram was constructed and an ROC curve was plotted, based on which the optimal cutoff value was determined as 0.698. The area under the curve of the nomogram in the training and validation cohorts was 0.860 (95% CI = 0.807-0.913) and 0.843 (95% CI = 0.757-0.929), respectively. Calibration curves for CHD risk probability showed good agreement between the nomogram's predicted probabilities and the observed event rates. DCA demonstrated the net clinical benefit of the constructed nomogram. Sex, Lp(a), WBC, TyG, and AIP emerged as independent risk factors for CHD in patients with MAFLD and the nomogram prediction model constructed using these factors could effectively predict CHD occurrence. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1652321
LPA
BoWen Li, Dan Shu, Shiguang Pang +7 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
Childhood cancer can disrupt family functioning, increase caregiver psychological distress, and impair caregiver quality of life. While family resilience is crucial for adaptation, most research has f Show more
Childhood cancer can disrupt family functioning, increase caregiver psychological distress, and impair caregiver quality of life. While family resilience is crucial for adaptation, most research has focused on individual-level factors, neglecting heterogeneity and multilevel influences on family resilience. Guided by the Social Ecological Model (SEM), this cross-sectional observational study used latent profile analysis (LPA) to identify distinct profiles of family resilience among caregivers of children with cancer and to explore factors associated with these profiles. Between July 2022 and March 2024, 292 caregivers were recruited. Family resilience was measured using the Family Resilience Assessment Scale. LPA was employed to identify resilience profiles, and binary logistic regression was used to explore influencing factors. Two latent profiles were identified: the Low Resources-Low Positivity profile (86%) and the High Internal Resilience profile (14%). The Low Resource-Low Positivity profile demonstrated generally lower scores, especially in utilizing social and economic resources and maintaining a positive outlook. The High Internal Resilience profile showed higher scores across all family resilience dimensions, particularly in communication/problem solving, positive outlook, and meaning-making, while the use of external social and economic resources remained relatively lower. Univariate analysis showed significant differences between profiles in residence, number of siblings, caregiver education, individual resilience, social support, caregivers' physical and psychological well-being and child communication (caregiver-reported). Binary logistic regression identified having more than one child (OR = 3.184, 95% CI: 1.437 ~ 7.057, P = 0.004) and higher individual resilience (OR = 1.095, 95% CI: 1.028 ~ 1.165, P = 0.005) as significant predictors of High Internal Resilience profile. This study identified two distinct family resilience profiles among caregivers of children with cancer. Limited use of social and economic resources was common, while caregiver resilience and having multiple children predicted higher family resilience. Interventions should enhance caregiver coping capacity, support one-child families through peer and family programs, and improve access to social support, flexible employment, and affordable care to strengthen family resilience. Not applicable. Show less
📄 PDF DOI: 10.1186/s12912-025-03444-8
LPA
Juan Li, Sha Lin, Zhengdi She +3 more · 2025 · Scientific reports · Nature · added 2026-04-24
Cancer-related fatigue (CRF) is a multifaceted and subjective phenomenon that significantly impacts patients on physical, emotional, and mental levels. This study aims to identify specific subtypes of Show more
Cancer-related fatigue (CRF) is a multifaceted and subjective phenomenon that significantly impacts patients on physical, emotional, and mental levels. This study aims to identify specific subtypes of Cancer-related fatigue (CRF) in patients with Hepatocellular Carcinoma (HCC) and to explore the factors influencing each subtype. This cross-sectional study enrolled 220 participants from a tertiary cancer hospital. Latent Profile Analysis (LPA) and multinomial logistic regression were conducted to identify distinct fatigue profiles and to explore the influencing factors for different categories of CRF among the patients. The analysis revealed three potential categories of CRF severity: Physical balance -Low fatigue (20.1%); Physical imbalance -Moderate fatigue (69.6%); and Physical prominent -High fatigue (10.2%). It was found that the severe insomnia the greater the probability of patients belonging to the Physical prominent -High fatigue (OR = 1.299, 95%CI: 1.188-1.419). Has partner (OR = 5.171, 95%CI: 1.739-15.377), the severe financial stress (OR = 2.570, 95%CI: 1.209-5.463) and the moderate ISI (OR = 1.212, 95%CI: 1.136-1.292) were associated with the Physical imbalance - Moderate fatigue group. Protective factors for the Physical balance - Low fatigue group included higher scores in the physical activity Index (OR = 0.930, 95%CI: 0.870-0.995), Hope Index (OR = 0.647, 95%CI: 0.552-0.758), General self-efficacy (OR = 0.874, 95%CI: 0.793-0.965), Body Mass Index (OR = 0.799, 95%CI: 0.552-0.758), and Child-Pugh A classification (OR = 0.310, 95%CI: 0.119-0.808). CRF in patients with HCC demonstrates significant heterogeneity. It is conducive to the clinical identification of CRF risk characteristics and the design of personalized intervention measures. Show less
📄 PDF DOI: 10.1038/s41598-025-19135-y
LPA
Chaoping Chen, Chenhao Li, Qingru Zhu +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lifestyle improvement may help reverse prediabetes. Indicators such as Life's Essential 8 (LE8) and biological aging measures (phenotypic age, cardiovascular biological age) partially reflect metaboli Show more
Lifestyle improvement may help reverse prediabetes. Indicators such as Life's Essential 8 (LE8) and biological aging measures (phenotypic age, cardiovascular biological age) partially reflect metabolic status in prediabetes, but their predictive value for cardiovascular mortality and stroke in this population remains unclear. We analyzed data from 74,678 White participants with prediabetes in the UK Biobank, defined by either HbA1c (5.7-6.4%) or fasting glucose (6.1-6.9 mmol/L). Follow-up continued until October 10, 2023. Cox regression was used to examine associations between LE8, phenotypic age (PhenoAge), cardiovascular biological age (CBA), and outcomes of cardiovascular (CVD) mortality and stroke. Restricted cubic spline (RCS) models identified biological age risk thresholds. Mediation analysis assessed whether proteins such as CST3, EFEMP1, FES, IGFBP2, IGFBP6, LPA, PCSK9, and TIMP1 mediated these effects. Over a median follow-up of 13.4 years, 2263 participants died from CVD causes. Each 1-year increase in CBA or PhenoAge was associated with a ~ 10% higher risk of CVD mortality (CBA aHR = 1.10; PhenoAge aHR = 1.09; both P < 0.001), while each 1-point increase in LE8 score was linked to a 3% lower risk (HR = 0.97, P < 0.001). The risk biological ages for these two indicators were also identified: PhenoAge ≥ 58.52 years and CBA ≥ 62.42 years. Similar trends were observed for stroke. Mediation analysis revealed that CST3, TIMP1, IGFBP2, and IGFBP6 contributed to the biological pathways between aging/lifestyle and CVD outcomes. The combined LE8 and PhenoAge model showed the strongest predictive performance for CVD mortality (AUC = 0.716) and stroke (AUC = 0.638) over 15 years. LE8 combined with phenotypic age provides prognostic value for CVD outcomes in prediabetes. These findings highlight the potential of lifestyle modification and delayed biological aging in reversing prediabetes and underscore comorbidity-related proteins as promising therapeutic targets. Show less
📄 PDF DOI: 10.1186/s40001-025-03218-7
LPA
Keying Guo, Haipeng Li, Weina Du +4 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
The primary aim of this study is to explore distinct patterns of post-traumatic growth (PTG) and fear of cancer progression (FOP) among breast cancer patients through latent profile analysis (LPA). Ad Show more
The primary aim of this study is to explore distinct patterns of post-traumatic growth (PTG) and fear of cancer progression (FOP) among breast cancer patients through latent profile analysis (LPA). Additionally, we assessed the differences in demographic and disease-related factors among breast cancer patients with varying patterns. Finally, we examined the influence of socio-demographic, disease-related, social support, anxiety, depression, and post-traumatic stress disorder (PTSD) factors on the varying patterns, aiming to assist healthcare providers in developing more effective psychological care strategies for breast cancer patients. A questionnaire survey was conducted on 752 breast cancer patients. Latent profile analysis was employed to explore the patterns of post-traumatic growth and fear of cancer progression in these patients, and multiple logistic regression analysis was used to identify the predictive factors for the different patterns. Based on the fit indices of latent class analysis, a three-class model was identified as the optimal solution, which included the Resisting group, Struggling group, and Growth group. In the Resisting group (24.33%), patients reported low levels of post-traumatic growth and high levels of fear of cancer progression; in the Struggling group (46.14%), patients exhibited moderate levels of post-traumatic growth and low levels of fear of cancer progression; in the Growth group (29.52%), patients demonstrated high levels of post-traumatic growth and moderate levels of fear of cancer progression. Additionally, the multiple logistic regression analysis reveals that marital status, place of residence, education level, disease stage, social support, anxiety, and post-traumatic stress disorder levels in breast cancer patients serve as significant factors influencing the distinct patterns of post-traumatic growth and fear of progression. This study suggests that there is heterogeneity in the PTG and FOP patterns in breast cancer patients. It provides a research basis for promoting the psychological recovery of breast cancer patients and highlights the importance of focusing on the positive effects of PTG while mitigating the negative impact of FOP. Healthcare providers can implement targeted nursing interventions based on the different patterns observed in breast cancer patients. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1604787
LPA
Jianyu Liu, Zhiyao Xu, Yang Wen +5 more · 2025 · Current medicinal chemistry · Bentham Science · added 2026-04-24
"Penumbra freezing" aims to extend vascular recanalization treatment to acute ischemic stroke (AIS) patients beyond the standard time window by preserving the ischemic penumbra. Efficient biomarkers a Show more
"Penumbra freezing" aims to extend vascular recanalization treatment to acute ischemic stroke (AIS) patients beyond the standard time window by preserving the ischemic penumbra. Efficient biomarkers are crucial for identifying patients eligible for AIS treatment. This study enrolled 141 AIS patients who exceeded the conventional treatment window. Using CT perfusion imaging, patients were categorized into "penumbra freezing" and "non-penumbra freezing" groups based on the EXTEND criteria. Multiple regression analysis assessed the association of nine baseline factors and five blood lipid indicators with "penumbra freezing." Diagnostic accuracy was evaluated using ROC curves. Mendelian randomization (MR) analysis validated these findings using blood lipid indicators as exposures and penumbra biomarkers as outcomes. Among AIS patients beyond the treatment window, males exhibited better penumbra preservation (OR=0.243, 95% CI=0.072-0.813, p=0.022), while those with hyperlipidemia showed poorer preservation (OR=2.429, 95% CI=1.027-7.747, p=0.043). In the "penumbra freezing" group, ApoA1 levels were significantly lower (1.29 ± 0.03 g/L) compared to the "non-penumbra freezing" group (1.42 ± 0.06 g/L, p=0.034). Conversely, Lp(a) levels were significantly higher in the "penumbra freezing" group (304.63 ± 52.44 mg/L) than in the "non-penumbra freezing" group (110.26 ± 40.71 mg/L, p=0.034). Higher ApoA1 levels increased the likelihood of "non-penumbra freezing" beyond the time window (OR=3.206, 95% CI=1.034-9.938, p=0.044), while elevated Lp(a) levels reduced this likelihood (OR=0.075, 95% CI=0.007-0.848, p=0.036). MR analysis confirmed genetic associations of ApoA1 and Lp(a) with penumbra biomarkers. ApoA1 and Lp(a) may be linked to ischemic penumbra status, but further validation is needed due to limitations in sample size and study methodology. ApoA1 and Lp(a) are promising biomarkers for identifying AIS patients eligible for "penumbra freezing," suggesting the potential to extend the treatment window. Show less
no PDF DOI: 10.2174/0109298673374444250901100551
LPA
Mei Wang, Ruihua Yan, Wenbo Xia +8 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Low physical activity (LPA) significantly heightens the susceptibility of both type 2 diabetes mellitus (T2DM) and chronic renal disease. Nearly half of population diagnosed with T2DM globally worsen Show more
Low physical activity (LPA) significantly heightens the susceptibility of both type 2 diabetes mellitus (T2DM) and chronic renal disease. Nearly half of population diagnosed with T2DM globally worsen into diabetic kidney disease (DKD). Focusing on physically inactive populations, we aimed to comprehensively evaluate the trends over time and regional changes in T2DM-associated DKD attributable to LPA burden. We utilized data of the 2021 Global Burden of Disease (GBD) Study to initially assess the worldwide effects of T2DM-associated DKD attributable to LPA by computing the numbers and age-standardized rates (ASRs) of death, disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs), categorized by subtypes in 2021. Linear regression model was applied to analyze the illness burden from 1990 to 2021. Furthermore, cluster analysis was performed to assess the regional differences in disease burden across GBD regions. Lastly, to forecast the illness burden for the next 25 years, we utilized the autoregressive Integrated Moving Average (ARIMA) and Excess Risk (ER) models. In 2021, the fatalities attributed to T2DM-related DKD attributable to LPA amounted to 30835 (95%UI: 12346-51646) cases, with 698484 (95%UI: 275039-1158032) DALYs. The ASRs of death and DALYs were 0.38 (95%UI: 0.15-0.63) and 8.19 (95%UI: 3.21-13.6) per 100000 individuals, respectively. Between 1990 and 2021, there was a notable escalation in deaths, DALYs, YLDs, and YLLs, as well as their ASRs. The highest burden was observed among males, older adults (aged 70 years and above), and middle Socio-demographic Index (SDI). Significant differences were noted in the disease burden among various regions and countries as defined by the GBD study. Predictive analyses indicate a continued escalation of this burden by the year 2050. The global impact of DKD attributable to LPA remains considerable, with significant disparities noted across different genders, ages, and regions. To mitigate this burden, it is crucial to implement effective interventions aimed at addressing physical inactivity, specifically designed for targeted demographic groups. Show less
📄 PDF DOI: 10.3389/fendo.2025.1625973
LPA
Yujiao Zhao, Luyang Ma, Weijun Li +9 more · 2025 · BMC pregnancy and childbirth · BioMed Central · added 2026-04-24
To investigate longitudinal changes in pelvic floor support in primiparous women with pelvic organ prolapse (POP) after vaginal delivery, focusing on single- and multiple-compartment involvement. Two Show more
To investigate longitudinal changes in pelvic floor support in primiparous women with pelvic organ prolapse (POP) after vaginal delivery, focusing on single- and multiple-compartment involvement. Two hundred primiparas after vaginal delivery were prospectively enrolled and underwent pelvic floor MRI at six weeks postpartum. POP was diagnosed and classified into subgroups (single or multiple compartments involved) based on MRI findings. Primiparas with POP underwent repeat MRI at four months postpartum. Pelvic floor measurements, including injury score and functional parameters of the levator ani muscle (puborectal hiatus line, H line; muscular pelvic floor relaxation line, M line; levator hiatus area, LHA; iliococcygeus angle, ICA; levator plate angle, LPA), were assessed on MRI. Measurements were compared among POP subgroups and a normal control group (without POP) at six weeks postpartum. Additionally, changes between six weeks and four months postpartum were analyzed within POP subgroups. Based on MRI criteria, approximately 41.5% of primiparas were diagnosed with POP, predominantly cystoceles commonly associated with uterine prolapse. Functional parameters of the levator ani, except for LPA at rest, were significantly increased in POP subgroups compared to controls. At four months postpartum, M line, H line, and LPA significantly decreased, and prolapsed organs were elevated in cases with multiple compartments involved, compared to six weeks postpartum. No significant changes were observed in cases with single-compartment involvement during follow-up. A substantial proportion of primiparas experienced postpartum POP. Impaired levator ani function contributed to POP. Pelvic floor support improved during early postpartum in cases with multiple-compartment involvement. Show less
📄 PDF DOI: 10.1186/s12884-025-08044-7
LPA
Minle Tian, Xiaolei Han, Ming Mao +12 more · 2025 · Brain imaging and behavior · Springer · added 2026-04-24
Evidence has linked self-reported sedentary behaviors with dementia and cognitive impairment; however, the underlying mechanisms remain poorly understood. We investigated the associations of accelerom Show more
Evidence has linked self-reported sedentary behaviors with dementia and cognitive impairment; however, the underlying mechanisms remain poorly understood. We investigated the associations of accelerometer-measured sedentary behavior patterns with gray matter atrophy patterns in rural-dwelling older adults, while taking into account the manner in which sedentary time is accrued (in short or long bouts). This community-based study involved 911 dementia-free older adults (age ≥ 60 years, 59% women) who participated in both ActiGraph and brain MRI substudies within MIND-China (2018-2020). Sedentary behavior parameters (total sedentary time, mean sedentary bout duration, and sedentary breaks) were recorded with accelerometers. Regional gray matter volumes (GMV) were measured using voxel-based morphometry (VBM) methods. Data were analyzed using the general linear regression models, restricted cubic spline curves, and VBM analysis. There was an inverted U-shaped association between daily sedentary time and GMV in temporal, cingulate, and medial temporal cortex, while longer mean sedentary bout duration was linearly related to decreased GMV in total, frontal, temporal, insula, cingulate, and medial temporal cortex. Greater daily time spent in light or moderate-to-vigorous physical activity (LPA and MVPA) was correlated with larger insula GMV. The VBM analysis suggested that prolonged daily total sedentary time and mean sedentary bout duration were significantly associated with smaller GMV in extensive brain regions, especially in thalamus and insula. In conclusion, gray matter atrophy associated with sedentary behavior in older adults is characterized by reduced GMV in global, frontal, temporal, medial temporal, and cingulate cortex, especially in the insula and thalamus regions. Show less
📄 PDF DOI: 10.1007/s11682-025-01054-1
LPA
Jia-Xin Xu, Ye Wu, Lin Zhang +3 more · 2025 · World journal of cardiology · added 2026-04-24
Coronary heart disease (CHD) is a prominent cause of mortality and disability worldwide. Like most complex diseases, the risk of CHD in individuals is regulated by the interaction between genetic fact Show more
Coronary heart disease (CHD) is a prominent cause of mortality and disability worldwide. Like most complex diseases, the risk of CHD in individuals is regulated by the interaction between genetic factors and lifestyle. To investigate the influence of A total of 324 patients with CHD and 143 control participants were involved in this study. Single nucleotide polymorphisms rs429358 and rs7412 in the In the CHD group, the frequencies of In the Teochew population, the Show less
📄 PDF DOI: 10.4330/wjc.v17.i9.110278
LPA
Caili Li, Xiaoqian Lu, Liyan Zhang +10 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
This study aimed to analyze latent profiles and characteristics of nurses' knowledge, attitudes, and practices (KAP) regarding pressure injury (PI) prevention, as well as influencing factors across di Show more
This study aimed to analyze latent profiles and characteristics of nurses' knowledge, attitudes, and practices (KAP) regarding pressure injury (PI) prevention, as well as influencing factors across distinct profiles. A convenience sampling method was employed to recruit nurses from hospitals at various tiers in Guangxi Zhuang Autonomous Region between July and August 2024. Data were collected using a General Information Questionnaire and a Nurse PI-KAP Questionnaire. Latent profile analysis (LPA) identified distinct PI-KAP profiles, while univariate analysis and multinomial logistic regression determined profile-specific influencing factors. Among 17,253 enrolled nurses, the total PI-KAP score was 63.44 ± 7.69. Three latent profiles emerged: low-level PI-KAP (12.82%), moderate-level PI-KAP (52.23%), and high-level PI-KAP (34.95%). Multinomial logistic regression revealed that hospital tier, years of experience, education level, professional title, gender, and attitudes toward PI training significantly influenced PI-KAP profiles (p < .05). Heterogeneity exists in nurses' PI-KAP profiles, with a substantial proportion demonstrating suboptimal competency. Nursing administrators should establish hierarchical training systems tailored to PI-KAP characteristics. Capacity-building strategies include prioritizing training for core nurses, optimizing resource allocation, and establishing tiered hospital assistance mechanisms to enhance team-based PI prevention capabilities. Not applicable. Show less
📄 PDF DOI: 10.1186/s12912-025-03875-3
LPA
Zhaoyang Xie, Ningning Feng, Jieqi Wang +5 more · 2025 · The British journal of developmental psychology · Blackwell Publishing · added 2026-04-24
Given the lack of evidence, we cannot definitively determine the relationship between attachment networks and problematic mobile phone use, hindering effective intervention strategies. Therefore, a th Show more
Given the lack of evidence, we cannot definitively determine the relationship between attachment networks and problematic mobile phone use, hindering effective intervention strategies. Therefore, a three-wave longitudinal study was designed to explore the heterogeneity of parent-child attachment networks using latent profile analysis (LPA) and random intercept latent transition analysis (RI-LTA). Participants included 2116 adolescents (ages 14-21; 53.8% girls). Results identified five stable parent-child attachment network profiles, each showing moderate but decreasing stability. Notably, adolescents who were grouped into an attachment network characterized by secure maternal attachment but insecure paternal attachment, similar to those in attachment networks with both insecure maternal and paternal attachment, scored higher levels of problematic mobile phone use than those who were grouped into attachment networks with both secure maternal and paternal attachment. Our findings fill empirical gaps and provide strong evidence supporting attachment-based interventions to reduce problematic mobile phone use. Show less
no PDF DOI: 10.1111/bjdp.70019
LPA
Linglong Liu, Xiaoping Fang, Xinbo Wang +8 more · 2025 · International journal of nursing studies advances · Elsevier · added 2026-04-24
Family caregivers ('carers') bear the highest care burden during the postoperative survivorship period of pancreatic cancer, given its poor prognosis. Most carers report unmet needs when taking on car Show more
Family caregivers ('carers') bear the highest care burden during the postoperative survivorship period of pancreatic cancer, given its poor prognosis. Most carers report unmet needs when taking on caregiving responsibilities during this period. Thoroughly investigating carers' needs is essential for helping families address practical care challenges. However, this important topic remains underexplored. To assess the need levels and identify need subgroups among carers of patients with pancreatic cancer 6 months after surgery and demographic predictors contributing to heterogeneity. Cross-sectional study. Participants were recruited from the pancreas centres of four tertiary A-level comprehensive hospitals in Jiangsu Province, China. 240 patients with pancreatic cancer and their carers ('dyads') participated in the survey. Carers completed the Comprehensive Needs Assessment Tool in Cancer for Carers, the Activities of Daily Living Scale for patients, and the General Demographic Information Questionnaire for dyads. Latent profile analysis (LPA) was used to categorise carers' needs. Non-parametric and chi-square tests were used to examine differences in need scores and sociodemographic characteristics among subgroups. Multiple logistic regression (MLR) was used to analyse sociodemographic impacts. Six months post-surgery, the total carers' need score was 41.83 ± 22.65 points, indicating a moderate level, with the highest needs reported for healthcare personnel, information and knowledge, and facilities and services. The LPA results revealed that carers were divided into five distinct subgroups based on differing levels of need across the domains assessed by the Comprehensive Needs Assessment Tool in Cancer for Carers, with proportions of 8.8 %, 22.5 %, 8.3 %, 55 %, and 5.4 %. Subgroup membership was predicted by four factors: carers' sex (odds ratio [OR]: 11.08, 95 % confidence interval [CI]: 1.64, 74.99, We have highlighted the complex individualised needs of carers of patients with pancreatic cancer. Through LPA and MLR, we identified distinct need subgroups and their predictors. Healthcare professionals may be able to improve dyads' health by tailoring support to each subgroup's specific needs and issues. Registration number: ChiCTR2400079415, registered 03/01/2024, first recruitment 04/02/2024. Show less
📄 PDF DOI: 10.1016/j.ijnsa.2025.100416
LPA
Yang Zheng, Qiuxuan Li, Yuxiu Yang +4 more · 2025 · Journal of the American Heart Association · added 2026-04-24
Calcific aortic valve stenosis (CAVS) can lead to cardiac adverse outcomes; however, currently, no effective pharmacological interventions are available to prevent or delay disease progression. Emergi Show more
Calcific aortic valve stenosis (CAVS) can lead to cardiac adverse outcomes; however, currently, no effective pharmacological interventions are available to prevent or delay disease progression. Emerging evidence has identified significant associations between CAVS and key biomarkers, including Lp(a) (lipoprotein [a]), low-density lipoprotein cholesterol, and PCSK9 (proprotein convertase subtilisin/kexin type 9). However, robust evidence from randomized controlled trials is still lacking to substantiate these associations. The EPISODE (Effect of PCSK9 Inhibitors on Calcific Aortic Valve Stenosis) trial is a prospective, evaluator-blinded, randomized controlled trial designed to assess the therapeutic efficacy of PCSK9 inhibitors in patients with CAVS. A total of 160 patients with mild-to-moderate or asymptomatic severe CAVS will be randomly assigned to receive either statin monotherapy or a combination of statins and PCSK9 inhibitors. Participants will undergo follow-up assessments at 3-month intervals for 24 months, including transthoracic ultrasonic cardiogram, computed tomography, and quality-of-life evaluations using the EuroQol-5 Dimension-3 Level questionnaire. The primary end point is the annualized change in peak aortic jet velocity, whereas secondary end points encompass changes in aortic valve area, calcification score, incidence of heart valve surgery, and quality of life. Safety end points include all-cause mortality and cardiovascular events. The trial aims to evaluate the efficacy of PCSK9 inhibitors in modulating disease progression, reducing adverse cardiovascular events, and improving clinical outcomes in patients with CAVS. The anticipated findings are expected to provide critical insights for developing novel therapeutic strategies for early intervention in CAVS. URL: https://www.clinicaltrials.gov; Unique Identifier: NCT04968509. Show less
📄 PDF DOI: 10.1161/JAHA.125.042112
LPA
Jiahe Zhang, Jiachen Zhang, Jiandong Li +3 more · 2025 · Archiv der Pharmazie · Wiley · added 2026-04-24
Pulmonary fibrosis (PF) is a progressive and fatal disease, and recent studies have revealed its key role in the autotaxin (ATX)-lysophosphatidic acid (LPA) signaling pathway, revealing the therapeuti Show more
Pulmonary fibrosis (PF) is a progressive and fatal disease, and recent studies have revealed its key role in the autotaxin (ATX)-lysophosphatidic acid (LPA) signaling pathway, revealing the therapeutic potential of targeting ATX. Herein, starting from PAT-409, a series of novel ATX inhibitors containing the 4,5,6,7-tetrahydro-7H-pyrazolo[3,4-c]pyridin-7-one core were designed to improve the pharmacological activity and physicochemical properties. The most promising compound 19 exhibited potent ATX inhibition (IC Show less
no PDF DOI: 10.1002/ardp.70095
LPA
Xin Zhang, Yun-Teng Xu, Xi Chen +4 more · 2025 · Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica · added 2026-04-24
This study aims to investigate the effect and mechanism of naringin on anti-osteoporosis by regulating lipid-bone balance. Thirty healthy female SD rats(8-week-old, SPF grade) were selected and random Show more
This study aims to investigate the effect and mechanism of naringin on anti-osteoporosis by regulating lipid-bone balance. Thirty healthy female SD rats(8-week-old, SPF grade) were selected and randomly divided into a sham group, an ovariectomy group, and a naringin group. Except for the sham group, postmenopausal osteoporosis models were established for both the ovariectomy group and the naringin group by removing bilateral ovaries. Rats in the naringin group were given a naringin suspension at a dose of 100 mg·kg~(-1), while those in sham and ovariectomy groups were administered an equivalent volume of saline. Following the treatment once daily for 12 weeks, an enzyme-linked immunosorbent assay(ELISA) was used to detect the changes in the content of serum estradiol(E₂₎ and bone metabolism biomarkers, including procollagen type Ⅰ N-terminal propeptide(PINP), osteocalcin(OC), and tartrate-resistant acid phosphatase 5(TRACP5). Micro-CT analysis was performed to assess structural alterations in the femoral trabeculae of rats and analyze morphometric parameters of the bone. Hematoxylin-eosin(HE) and Masson staining were used to observe the histopathological changes in the bone tissue. Western blot was employed to analyze the protein expression level of osteogenesis-and adipogenesis-related factors, including peroxisome proliferator-activated receptor gamma(PPARγ), lipoprotein lipase(LPL), RUNT-related transcription factor 2(RUNX2), osterix(OSX), farnesoid X receptor(FXR), and fibroblast growth factor 19(FGF19). Additionally, immunohistochemistry was employed to evaluate the expression of key metabolic pathway proteins FXR and FGF19. After 12-week treatment, compared with the sham group, the ovariectomy group exhibited a significantly reduced level of serum E₂, PINP, and OC, alongside significantly elevated TRACP5. Compared with the ovariectomy group, the levels of serum E₂, PINP, and OC in the naringin group were significantly increased, while the level of TRACP5 was significantly decreased. Compared with the sham group, the ovariectomy group exhibited a decrease in trabecular number and continuity, sparse and disorganized arrangements, and partial formation of voids. The group also showed decreased bone mineral density(BMD), bone volume fraction(BV/TV), trabecular number(Tb.N), and trabecular thickness(Tb.Th), coupled with increased trabecular separation(Tb.Sp). Compared with the ovariectomy group, naringin intervention resulted in improved bone microarchitecture, characterized by increased trabecular number and continuity, more compact arrangements, and a significant reduction in voids. Quantitatively, this was reflected in elevated levels of BMD, BV/TV, Tb.N, and Tb.Th, alongside a significant decrease in Tb.Sp. Under light microscopy, fragmented trabeculae, uneven collagen staining, disorganized arrangements, and an expanded number and size of marrow adipocyte vacuoles were observed in the ovariectomy group, whereas naringin administration attenuated these pathological alterations. Compared with the sham group, the ovariectomy group showed a significant increase in the expression of adipogenic proteins PPARγ and LPL, alongside significant decreases in the expression of osteogenic proteins(RUNX2 and OSX) and of FXR and FGF19 proteins. In contrast, the naringin group exhibited a reversal of these trends compared to the ovariectomy group, with decreased PPARγ and LPL expression and increased RUNX2, OSX, FXR, and FGF19 expression. These findings demonstrate that naringin modulates lipid-bone metabolism homeostasis in postmenopausal osteoporotic rats, ameliorating trabecular microstructure and attenuating bone marrow adipogenesis, with its therapeutic effects mechanistically linked to the FXR/FGF19 signaling pathway. Show less
no PDF DOI: 10.19540/j.cnki.cjcmm.20250908.401
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Xiaoqiang Wei, Lihui Wang, Haiwang Zhang +6 more · 2025 · Frontiers in microbiology · Frontiers · added 2026-04-24
Forage scarcity during the cold season poses a major challenge to livestock farming on the Qinghai-Tibet Plateau. Jerusalem artichoke (
📄 PDF DOI: 10.3389/fmicb.2025.1699658
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Ziyu Li, Guangyi Chen, Wei Li +10 more · 2025 · Frontiers in plant science · Frontiers · added 2026-04-24
To explore the optimal row-ratio in mechanized hybrid rice seed production, a field experiment was conducted in 2024 at Qionglai and Mianzhu using 'Tiantai A' × 'Taihui 808'. Three row-ratio treatment Show more
To explore the optimal row-ratio in mechanized hybrid rice seed production, a field experiment was conducted in 2024 at Qionglai and Mianzhu using 'Tiantai A' × 'Taihui 808'. Three row-ratio treatments (H1: 18:6, H2: 24:6, and H3: 30:6) were tested using agricultural unmanned aerial vehicles (AUAVs) for pollination assistance. The results showed that row-ratio had little effect on sterile line flowering dynamics. The index of flowers meeting (IFM) was 0.71-0.72 at Qionglai and 0.81-0.86 at Mianzhu, with 11 to 12 days of flowering duration. As the row-ratio increased, total pollen quantity in the panicle layer and grain filling rate (GFR) decreased, while grain infection rate (GIR) increased. The responses of grain blighted rate (GBR), grain empty rate (GER), and fertilization success rate (FSR) to row-ratio varied between sites. Pollen density and GFR followed the pattern of near region (NR) > central region (CR) > far region (FR). Within the panicle, pollen density was generally highest in the upper panicle layer (UPL), followed by the middle (MPL) and lower (LPL) layers, with partial exceptions observed in the H2 and H3 treatments at Mianzhu. The vertical distribution of GFR varied by site: at Qionglai, it was apical parts of panicle (APP) > median parts (MPP) > basal parts (BPP), whereas at Mianzhu the order was MPP > APP > BPP. With wider row-ratios, yield per unit area (YUA) and GFR declined (H1 > H2 > H3), while 1,000-grain weight increased or decreased and then increased. Under H1, yields reached 2,107.50 kg ha Show less
📄 PDF DOI: 10.3389/fpls.2025.1704773
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Wenjing Cai, Xiaonian Luo, Jiao Li +5 more · 2025 · Biology · MDPI · added 2026-04-24
This study investigated the effects of dietary carbohydrate levels on growth performance, body composition, and hepatic expression of metabolic genes in Chinese hook snout carp (
📄 PDF DOI: 10.3390/biology14121687
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Yi-Jia Liu, Jian Guo, Chang-Da Li +2 more · 2025 · Frontiers in physiology · Frontiers · added 2026-04-24
Intensive aquaculture frequently utilizes high-fat diets (HF) as a cost-effective strategy, yet this practice often induces hepatic steatosis, oxidative stress, and chronic inflammation in carnivorous Show more
Intensive aquaculture frequently utilizes high-fat diets (HF) as a cost-effective strategy, yet this practice often induces hepatic steatosis, oxidative stress, and chronic inflammation in carnivorous fish. Betaine, a natural methyl donor, has shown potential as a functional feed additive, but its comprehensive protective mechanisms under HF stress remain to be fully elucidated. Juvenile largemouth bass (Micropterus salmoides) were fed one of four isonitrogenous diets for 8 weeks: a normal-fat control (Control), a high-fat diet (HF), and two high-fat diets supplemented with 0.5% (HFB0.5) or 1.0% (HFB1) betaine. Growth performance, digestive enzyme activities, serum biochemical parameters, hepatic antioxidant capacity, and the expression of genes related to antioxidant defense, lipid metabolism, and inflammation were analyzed. The HF group exhibited significantly impaired growth, digestive function, and antioxidant capacity, along with elevated lipid peroxidation, dyslipidemia, and pro-inflammatory cytokine expression. Betaine supplementation restored growth performance and feed efficiency to control levels, ameliorated digestive enzyme activities (particularly enhancing lipase), and activated the hepatic Nrf2-Keap1 pathway, upregulating antioxidant genes (nrf2, sod1, cat, gpx, ho-1, gr) and enhancing enzyme activities. Betaine also improved serum lipid profiles, upregulated genes related to fatty acid oxidation (pparα, cpt-1) and lipolysis (lpl, hsl), suppressed lipogenic genes (srebp-1, fas), and rebalanced inflammatory cytokines by reducing tnf-α and il-1β while increasing tgf-β1 and il-10. Dietary betaine effectively counteracts HF-induced metabolic stress in M. salmoides through coordinated multi-pathway regulation. It enhances antioxidant defense, reprograms hepatic lipid metabolism toward catabolism, and restores inflammatory homeostasis. These findings underscore betaine's role as a multi-functional feed additive capable of mitigating HF-related metabolic disorders and promoting overall health in carnivorous fish aquaculture. Show less
📄 PDF DOI: 10.3389/fphys.2025.1742669
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Chengyu Ni, Chunyu Li, Zihao Xu +1 more · 2025 · Inorganic chemistry · ACS Publications · added 2026-04-24
(Co)doping luminescent center(s) in a host is a universal strategy to photoluminescence (PL) modulations for extensive applications, yet its mechanism and interactions between structure and behavior i Show more
(Co)doping luminescent center(s) in a host is a universal strategy to photoluminescence (PL) modulations for extensive applications, yet its mechanism and interactions between structure and behavior in many phosphors remain ambiguous. Herein, via a facile sol-gel reaction method, differently tendentious occupations of Ce Show less
no PDF DOI: 10.1021/acs.inorgchem.5c04510
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Sijuan Chen, Chenyu Li, Yiming Chen +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Cancer cells fulfil their energy requirements by acquiring fatty acids (FAs) through both de novo synthesis and exogenous uptake. Although studies have focused on de novo FAs synthesis in papillary th Show more
Cancer cells fulfil their energy requirements by acquiring fatty acids (FAs) through both de novo synthesis and exogenous uptake. Although studies have focused on de novo FAs synthesis in papillary thyroid cancer (PTC), research on exogenous FAs uptake is scarce. Lipoprotein lipase (LPL), which enhances cellular FAs uptake, serves as the focal point of this study, which explored the role of LPL-mediated exogenous FAs uptake and FAs synthase (FASN)-mediated endogenous FAs synthesis in PTC cell proliferation. The expression of LPL was analyzed using databases including GTEx, GEO, and TCGA. Furthermore, its expression in PTC tissue samples and cell lines was confirmed. To observe the impact of the lipoprotein-deficient medium on PTC cells, EdU and TUNEL staining assays were conducted. CCK-8, colony formation, and TUNEL assays were performed to assess the effect of down-regulating LPL and/or FASN expression in PTC cells. Bioinformatics analysis revealed the upregulation of LPL mRNA in thyroid cancer. LPL expression was significantly elevated in PTC tissues and cell lines. Lipoprotein-deficient medium inhibited PTC cell proliferation and induced apoptosis. Similarly, silencing either LPL or FASN led to comparable outcomes. The combined inhibition of both LPL and FASN had a synergistic effect, enhancing the inhibition of PTC cell proliferation and the increase in apoptosis. Both the de novo synthesis and exogenous uptake of FAs are important for PTC cell proliferation. The combined inhibition of LPL and FASN inhibitors shows promise for PTC treatment. Show less
📄 PDF DOI: 10.1186/s40001-025-03582-4
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Tongtong Zhang, Zhongming Cai, Haoran Li +3 more · 2025 · PloS one · PLOS · added 2026-04-24
Adipogenic differentiation of adipose-derived stem cells (ADSCs) is fundamental to both adipose tissue homeostasis and clinical applications, particularly fat grafting. However, the global and stage-s Show more
Adipogenic differentiation of adipose-derived stem cells (ADSCs) is fundamental to both adipose tissue homeostasis and clinical applications, particularly fat grafting. However, the global and stage-specific transcriptional regulatory networks underlying ADSC adipogenesis remain incompletely elucidated. In this study, we integrated bulk and single-cell RNA-seq datasets across multiple time points of ADSC adipogenesis to identify core regulators of differentiation and maturation. A total of 41 genes were consistently upregulated during early differentiation, among which eight hub genes (FABP4, FASN, FABP5, ADIPOQ, PLIN1, LPL, CIDEC, and ACSL1) formed a tightly connected protein-protein interaction (PPI) module associated with lipid metabolism, lipid droplet formation, and adipocyte maturation. Further integration of differentially expressed lncRNAs and miRNAs led to the construction of a ceRNA network involving 7 mRNAs, 9 miRNAs, and 4 lncRNAs, comprising 34 predicted lncRNA-miRNA-mRNA regulatory axes. To identify temporal transcriptional regulators, we defined five genes (TTC14, MBNL2, UBR3, ABCD2, and SORT1) as early-stage inducers of adipogenesis, and four genes (UQCR11, NDUFB4, S100A10, and PRDX3) as late-stage regulators involved in maintaining the mature phenotype. These stage-specific regulators showed distinct temporal expression patterns and were validated by qPCR. GeneMANIA network analysis further revealed that early-stage regulators were enriched in lipid transport and lipase activity regulation, while late-stage regulators were associated with mitochondrial electron transport and energy metabolism. These findings highlight the stage-dependent transcriptional landscape of ADSC adipogenesis and provide candidate regulatory targets for modulating adipocyte differentiation and stability. Show less
📄 PDF DOI: 10.1371/journal.pone.0335152
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Xiangyang Li, Xiaomin Zhang, Nina Wei +2 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Hyperlipidemia and its associated hepatic steatosis pose significant global health burdens, necessitating novel therapeutic strategies. High-fat diet (HFD)-fed C57BL/6 mice received TAC (2.5, 5.0, 10. Show more
Hyperlipidemia and its associated hepatic steatosis pose significant global health burdens, necessitating novel therapeutic strategies. High-fat diet (HFD)-fed C57BL/6 mice received TAC (2.5, 5.0, 10.0 g/L) or simvastatin for 2 weeks. Metabolic parameters, serum lipid profiles, hepatic function markers, and histopathology were systematically analyzed. Molecular pathways were interrogated through qPCR, Western blot, and pharmacological inhibition of AMPK (Compound C) and PPARα (GW6471). TAC treatment demonstrated significant dose-dependent improvements across multiple parameters. Compared to HFD controls, TAC reduced body weight by 21.3% and liver index by 18.7%, while lowering fasting blood glucose levels by 32.4%. Serum analyses showed substantial reductions in total cholesterol (46.2%), triglycerides (38.5%), and LDL-cholesterol (52.1%), accompanied by a 29.8% increase in HDL-cholesterol. Hepatic function improved markedly, with ALT and AST levels decreasing by 57.3% and 49.6% respectively. Histopathological examination revealed a 68.4% reduction in hepatic lipid accumulation. At the molecular level, TAC treatment resulted in a 2.7-fold increase in AMPK phosphorylation while significantly reducing HMGCR expression by 63.1% and nuclear SREBP-1c levels by 71.5%. Concurrently, TAC upregulated PPARα and LXRα expression by 3.1-fold and 2.4-fold respectively, leading to enhanced expression of lipolytic enzymes LPL and HL by 2.8-fold and 2.1-fold. These beneficial effects were completely abolished by co-treatment with pathway-specific inhibitors. TAC ameliorates hyperlipidemia and hepatic steatosis through dual modulation of AMPK/SREBP-1c-mediated lipid synthesis and PPARα/LXRα-driven lipolysis, presenting a multifaceted therapeutic approach for metabolic disorders. Show less
📄 PDF DOI: 10.3389/fphar.2025.1662325
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