👤 Xiying Li

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Also published as: A Li, Ai-Jun Li, Ai-Qin Li, Ailing Li, Aimin Li, Aixin Li, Alexander H Li, Alexander Li, Amy Li, An-Qi Li, AnHai Li, Anan Li, Andrew C Li, Ang Li, Anna Fen-Yau Li, Annie Li, Anqi Li, Anyao Li, Ao Li, Aowen Li, Aoxi Li, Audrey Li, Bai-Qiang Li, Baichuan Li, Baiqiang Li, Baixing Li, Baizhou Li, Bang-Yan Li, Bao Li, Bao-Shan Li, Baoguang Li, Baoguo Li, Baohong Li, Baohua Li, Baolin Li, Baoqi Li, Baoqing Li, Baosheng Li, Baoting Li, Bei Li, Bei-Bei Li, Beibei Li, Beixu Li, Ben Li, Ben-Shang Li, Benyi Li, Biao Li, Bichun Li, Bin Li, Bin-Kui Li, Binbin Li, Bing Li, Bing-Heng Li, Bing-Hui Li, Bing-Mei Li, Bingbing Li, Binghu Li, Binghua Li, Bingjie Li, Bingjue Li, Bingkun Li, Binglan Li, Bingong Li, Bingshan Li, Bingsheng Li, Bingsong Li, Bingxin Li, Binjun Li, Binkui Li, Binru Li, Binxing Li, Biyu Li, Bizhi Li, Bo Li, BoWen Li, Bohao Li, Bohua Li, Bolun Li, Boru Li, Botao Li, Boxuan Li, Boya Li, Boyang Li, Bugao Li, C H Li, C Li, C X Li, C Y Li, Caesar Z Li, Cai Li, Cai-Hong Li, Caihong Li, Caili Li, Caixia Li, Caiyu Li, Caiyun Li, Can Li, Cang Li, Caolong Li, Chang Li, Chang-Da Li, Chang-Ping Li, Chang-Sheng Li, Chang-Yan Li, Chang-hai Li, Changcheng Li, Changgui Li, Changhong Li, Changhui Li, Changjiang Li, Changkai Li, Changqing Li, Changwei Li, Changxian Li, Changyan Li, Changyu Li, Changzheng Li, Chanjuan Li, Chanyuan Li, Chao Bo Li, Chao Li, Chaochen Li, Chaojie Li, Chaonan Li, Chaoqian Li, Chaowei Li, Chaoying Li, Chen Li, Chen-Chen Li, Chen-Lu Li, Chen-Xi Li, Chenfeng Li, Cheng Li, Cheng-Lin Li, Cheng-Tian Li, Cheng-Wei Li, Chengbin Li, Chengcheng Li, Chenghao Li, Chenghong Li, Chengjian Li, Chengjun Li, Chenglan Li, Chenglong Li, Chengnan Li, Chengping Li, Chengqian Li, Chengquan Li, Chengsi Li, Chenguang Li, Chengwen Li, Chengxin Li, Chengyun Li, Chenhao Li, Chenjie Li, Chenli Li, Chenlin Li, Chenlong Li, Chenlu Li, Chenmeng Li, Chenrui Li, Chensheng Li, Chenwen Li, Chenxi Li, Chenxiao Li, Chenxin Li, Chenxuan Li, Chenyang Li, Chenyao Li, Chenyu Li, Cheung Li, Chi-Ming Li, Chi-Yuan Li, Chia Li, Chia-Yang Li, Chien-Feng Li, Chien-Hsiu Li, Chien-Te Li, Chih-Chi Li, Chitao Li, Chiyang Li, Chong Li, Chongyang Li, Chongyi Li, Chris Li, Chu-Qiao Li, Chuan F Li, Chuan Li, Chuan-Hai Li, Chuan-Yun Li, Chuanbao Li, Chuanfang Li, Chuang Li, Chuangpeng Li, Chuanning Li, Chuanyin Li, Chumei Li, Chun Li, Chun-Bo Li, Chun-Lai Li, Chun-Mei Li, Chun-Quan Li, Chun-Xiao Li, Chun-Xu Li, Chung-Hao Li, Chung-I Li, Chunhong Li, Chunhui Li, Chunjie Li, Chunjun Li, Chunlan Li, Chunlian Li, Chunliang Li, Chunlin Li, Chunmei Li, Chunmiao Li, Chunqing Li, Chunqiong Li, Chunshan Li, Chunsheng Li, Chunting Li, Chunxia Li, Chunxiao Li, Chunxing Li, Chunxue Li, Chunya Li, Chunyan Li, Chunyi Li, Chunying Li, Chunyu Li, Chunzhu Li, Chuzhong Li, Cien Li, Cong Li, Congcong Li, Congfa Li, Conghui Li, Congjiao Li, Conglin Li, Congxin Li, Congye Li, Cui Li, Cui-lan Li, Cuicui Li, Cuiguang Li, Cuilan Li, Cuiling Li, Cun Li, Cunxi Li, Cyril Li, D C Li, Da Li, Da-Hong Li, Da-Jin Li, Da-Lei Li, Da-wei Li, DaZhuang Li, Dacheng Li, Dai Li, Daiyue Li, Dalei Li, Dali Li, Dalin Li, Dan C Li, Dan Li, Dan-Dan Li, Dan-Ni Li, Dandan Li, Daniel Tian Li, Danjie Li, Danni Li, Danxi Li, Danyang Li, Daoyuan Li, Dapei Li, Dawei Li, Dayong Li, Dazhi Li, De-Jun Li, De-Tao Li, Dechao Li, Defa Li, Defeng Li, Defu Li, Dehai Li, Deheng Li, Dehua Li, Dejun Li, Demin Li, Deming Li, Dengfeng Li, Dengke Li, Dengxiong Li, Deqiang Li, Desen Li, Desheng Li, Dexiong Li, Deyu Li, Dezhi Li, Di Li, Di-Jie Li, Dianjie Li, Dijie Li, Ding Li, Ding Yang Li, Ding-Biao Li, Ding-Jian Li, Dingchen Li, Dingshan Li, Diyan Li, Dong Li, Dong Sheng Li, Dong-Jie Li, Dong-Ling Li, Dong-Run Li, Dong-Yun Li, Dong-fei Li, Dongbiao Li, Dongdong Li, Dongfang Li, Dongfeng Li, Donghe Li, Donghua Li, Dongliang Li, Dongmei Li, Dongmin Li, Dongnan Li, Dongtao Li, Dongyang Li, Dongye Li, Duan Li, Duanbin Li, Duanxiang Li, Dujuan Li, Duo Li, Duoyun Li, Ellen Li, En Li, En-Min Li, Enhao Li, Enhong Li, Enxiao Li, F Li, Fa-Hong Li, Fa-Hui Li, Fadi Li, Fan Li, Fang Li, Fangqi Li, Fangyan Li, Fangyong Li, Fangyuan Li, Fangzhou Li, Fei Li, Fei-Lin Li, Fei-feng Li, Feifei Li, Feilong Li, Fen Li, Feng Li, Feng-Feng Li, Fengfeng Li, Fengjuan Li, Fengli Li, Fengqi Li, Fengqiao Li, Fengqing Li, Fengxia Li, Fengxiang Li, Fengyi Li, Fengyuan Li, Fu-Rong Li, Fugen Li, Fuhai Li, Fujun Li, Fulun Li, Fuping Li, Fusheng Li, Fuyu Li, Fuyuan Li, G Li, G-P Li, Gaijie Li, Gaizhen Li, Gaizhi Li, Gan Li, Gang Li, Ganggang Li, Gao-Fei Li, Gaoyuan Li, Ge Li, Gen Li, Gen-Lin Li, Gerard Li, Gong-Hua Li, Gongda Li, Guanbin Li, Guandu Li, Guang Li, Guang Y Li, Guang-Li Li, Guang-Xi Li, Guangda Li, Guangdi Li, Guanghua Li, Guanghui Li, Guangjin Li, Guangli Li, Guanglu Li, Guanglve Li, Guangming Li, Guangping Li, Guangpu Li, Guangqiang Li, Guangquan Li, Guangwen Li, Guangxi Li, Guangxiao Li, Guangyan Li, Guangzhao Li, Guangzhen Li, Guannan Li, Guanqiao Li, Guanyu Li, Gui Lin Li, Gui-Bo Li, Gui-Hua Li, Gui-Rong Li, Gui-xing Li, Guigang Li, Guihua Li, Guilan Li, Guisen Li, Guixia Li, Guixin Li, Guiyang Li, Guiying Li, Guiyuan Li, Guo Li, Guo-Chun Li, Guo-Jian Li, Guo-Li Li, Guo-Ping Li, Guo-Qiang Li, Guobin Li, Guoge Li, Guohong Li, Guohua Li, Guohui Li, Guojin Li, Guojun Li, Guoli Li, Guoping Li, Guoqin Li, Guoqing Li, Guowei Li, Guoxi Li, Guoxiang Li, Guoxing Li, Guoyan Li, Guoyin Li, H J Li, H Li, H-F Li, H-H Li, H-J Li, Hai Li, Hai-Yun Li, Haibin Li, Haibo Li, Haifeng Li, Haihong Li, Haihua Li, Haijun Li, Hailong Li, Haimin Li, Haiming Li, Hainan Li, Haipeng Li, Hairong Li, Haitao Li, Haitong Li, Haixia Li, Haiyan Li, Haiyang Li, Haiying Li, Haiyu Li, Han Li, Han-Bing Li, Han-Bo Li, Han-Ni Li, Han-Ru Li, Han-Wei Li, Hanbin Li, Hanbing Li, Hanbo Li, Handong Li, Hang Li, Hangwen Li, Hanjun Li, Hankun Li, Hanlu Li, Hanmei Li, Hanqi Li, Hanqin Li, Hansen Li, Hanting Li, Hanxiao Li, Hanxue Li, Hao Li, Hao-Fei Li, Haojing Li, Haolong Li, Haomiao Li, Haoqi Li, Haoran Li, Haotong Li, Haoxian Li, Haoyu Li, Haying Li, He Li, He-Zhen Li, Hecheng Li, Hegen Li, Hehua Li, Heng Li, Heng-Zhen Li, Hengguo Li, Hengtong Li, Hengyu Li, Hening Li, Hewei Li, Hexin Li, Heying Li, Hong Li, Hong-Chun Li, Hong-Lan Li, Hong-Lian Li, Hong-Mei Li, Hong-Tao Li, Hong-Wen Li, Hong-Yan Li, Hong-Yu Li, Hong-Zheng Li, Hongbo Li, Hongchang Li, Hongde Li, Honggang Li, Hongguo Li, Honghua Li, Honghui Li, Hongjia Li, Hongjiang Li, Hongjuan Li, Honglei Li, Hongli Li, Honglian Li, Hongliang Li, Honglin Li, Hongling Li, Honglong Li, Hongmei Li, Hongmin Li, Hongming Li, Hongqin Li, Hongquan Li, Hongru Li, Hongsen Li, Hongwei Li, Hongxia Li, Hongxin Li, Hongxing Li, Hongxue Li, Hongyan Li, Hongye Li, Hongyi Li, Hongyu Li, Hongyun Li, Hongzhe K Li, Hongzheng Li, Hongzhi Li, Hsiao-Fen Li, Hsiao-Hui Li, Hsin-Hua Li, Hsin-Yun Li, Hu Li, Hua Li, Hua-Zhong Li, Huabin Li, Huafang Li, Huafu Li, Huaixing Li, Huaiyuan Li, Hualian Li, Hualing Li, Huamao Li, Huan Li, Huanan Li, Huang Li, Huangbao Li, Huangyuan Li, Huanhuan Li, Huanjun Li, Huanqing Li, Huanqiu Li, Huaping Li, Huashun Li, Huawei Li, Huayao Li, Huayin Li, Huaying Li, Hui Li, Hui-Jun Li, Hui-Long Li, Hui-Ping Li, Huibo Li, Huifang Li, Huifeng Li, Huihuang Li, Huihui Li, Huijie Li, Huijuan Li, Huijun Li, Huilan Li, Huili Li, Huiliang Li, Huilin Li, Huilong Li, Huimin Li, Huiping Li, Huiqin Li, Huiqing Li, Huiqiong Li, Huiting Li, Huixia Li, Huixue Li, Huiying Li, Huiyou Li, Huiyuan Li, Huizi Li, Hujie Li, Hulun Li, Hung Li, Hung-Yuan Li, Ivan Li, J Li, J T Li, Jason Li, Jen-Ming Li, Jenny J Li, Ji Li, Ji Xia Li, Ji-Cheng Li, Ji-Feng Li, Ji-Liang Li, Ji-Lin Li, Ji-Min Li, Jia Li, Jia Li Li, Jia-Da Li, Jia-Huan Li, Jia-Peng Li, Jia-Ru Li, Jia-Xin Li, Jiabei Li, Jiachen Li, Jiacheng Li, Jiafang Li, Jiafei Li, Jiahao Li, Jiahui Li, Jiajia Li, Jiajie Li, Jiajing Li, Jiajun Li, Jiajv Li, Jiali Li, Jialin Li, Jialing Li, Jialun Li, Jiaming Li, Jian Li, Jian'an Li, Jian-Jun Li, Jian-Mei Li, Jian-Qiang Li, Jian-Shuang Li, Jianan Li, Jianang Li, Jianbin Li, Jianbo Li, Jianchun Li, Jiandong Li, Jianfang Li, Jianfeng Li, Jiang Li, Jiangan Li, Jiangbo Li, Jiangchao Li, Jiangfeng Li, Jianglin Li, Jianglong Li, Jiangtao Li, Jiangui Li, Jianguo Li, Jiangxia Li, Jiangya Li, Jianhai Li, Jianhua Li, Jiani Li, Jianing Li, Jianliang Li, Jianlin Li, Jianmin Li, Jiannan Li, Jianping Li, Jianrong Li, Jianrui Li, Jiansheng Li, Jianshuang Li, Jianwei Li, Jianxin Li, Jianxiong Li, Jianye Li, Jianyi Li, Jianyong Li, Jianyu Li, Jianzhong Li, Jiao Li, Jiao-Jiao Li, Jiaomei Li, Jiaping Li, Jiaqi Li, Jiawei Li, Jiaxi Li, Jiaxin Li, Jiaxuan Li, Jiayan Li, Jiayang Li, Jiayi Li, Jiaying Li, Jiayu Li, Jiayuan Li, Jiazhou Li, Jicheng Li, Jie Li, Jie-Pin Li, Jie-Shou Li, Jiehan Li, Jiejia Li, Jiejie Li, Jiejing Li, Jieming Li, Jiequn Li, Jieshou Li, Jiexi Li, Jiexin Li, Jiezhen Li, Jifang Li, Jihua Li, Jin Li, Jin-Jiang Li, Jin-Liang Li, Jin-Long Li, Jin-Mei Li, Jin-Ping Li, Jin-Qiu Li, Jin-Wei Li, Jin-Xiu Li, Jinchen Li, Jinfang Li, Jinfeng Li, Jing Li, Jing-Jing Li, Jing-Ming Li, Jing-Yao Li, Jing-Yi Li, Jing-gao Li, Jingcheng Li, Jingchun Li, Jingfeng Li, Jinghao Li, Jinghui Li, Jingjing Li, Jingke Li, Jinglin Li, Jingmei Li, Jingming Li, Jingping Li, Jingqi Li, Jingshang Li, Jingshu Li, Jingtong Li, Jingui Li, Jingwen Li, Jingxia Li, Jingxiang Li, Jingxin Li, Jingya Li, Jingyi Li, Jingyong Li, Jingyu Li, Jingyun Li, Jinhua Li, Jinhui Li, Jinjie Li, Jinku Li, Jinlan Li, Jinliang Li, Jinlin Li, Jinman Li, Jinming Li, Jinping Li, Jinsong Li, Jinwei Li, Jinxia Li, Jinxin Li, Jinzhi Li, Jiong Li, Jiong-Ming Li, Jipeng Li, Jiqing Li, Jisen Li, Jisheng Li, Jiuke Li, Jiuyi Li, Jiwei Li, Jiwen Li, Jixi Li, Jixuan Li, Jiyang Li, Jiyuan Li, John Zhong Li, Jonathan Z Li, Joyce Li, Ju-Rong Li, Juan Li, Juan-Juan Li, Juanjuan Li, Juanling Li, Juanni Li, Jufang Li, Julia Li, Jun Li, Jun Z Li, Jun-Cheng Li, Jun-Jie Li, Jun-Ling Li, Jun-Ru Li, Jun-Yan Li, Jun-Ying Li, JunBo Li, Junfeng Li, Junhong Li, Junhui Li, Junjie Li, Junjun Li, Junming Li, Junping Li, Junqin Li, Junru Li, Junsheng Li, Juntong Li, Junxian Li, Junxin Li, Junxu Li, Junya Li, Junyi Li, Junying Li, Justin Li, Jutang Li, Juxue Li, K-L Li, Ka Li, Ka Wan Li, Kai Li, Kai-Wen Li, Kaibin Li, Kaibo Li, Kaifeng Li, Kailong Li, Kaimi Li, Kainan Li, Kaiwei Li, Kaixin Li, Kaiyi Li, Kaiyuan Li, Kang Li, Kangli Li, Kangyuan Li, Karen Li, Kathy H Li, Kawah Li, Ke Li, KeZhong Li, Keanning Li, Kecheng Li, Kechun Li, Keguo Li, Kejuan Li, Keke Li, Kening Li, Kenli Li, Kenneth Kai Wang Li, Keqing Li, Keshen Li, Keying Li, Keyuan Li, Kezhen Li, Kongdong Li, Kuan Li, Kui Li, Kuiliang Li, Kun Li, Kun-Peng Li, Kun-Ping Li, Kun-Xin Li, Kunlin Li, Kunlong Li, Kunlun Li, Kunpeng Li, L I Li, L K Li, L Li, L P Li, L-Y Li, Lai K Li, Laiqing Li, Lamei Li, Lan Li, Lan-Juan Li, Lan-Lan Li, Lanfang Li, Lang Li, Lanjuan Li, Lanlan Li, Lanzhou Li, Le Li, Le-Le Li, Le-Ying Li, Lei Li, Leilei Li, Leipeng Li, Letai Li, Leyao Li, Li Li, Li-Min Li, Li-Na Li, Lian Li, Lianbing Li, Liang Li, Liangdong Li, Liangji Li, Liangkui Li, Liangqian Li, Lianhong Li, Lianjian Li, Lianyong Li, Liao-Yuan Li, Lieyou Li, Liguo Li, Lihong Li, Lihua Li, Lijia Li, Lijuan Li, Lijun Li, Lili Li, Liliang Li, Liling Li, Liming Li, Lin Li, Lin-Feng Li, Linchuan Li, Linfeng Li, Ling Li, Ling-Jie Li, Ling-Ling Li, Ling-Zhi Li, Lingjiang Li, Lingjie Li, Lingjun Li, Lingling Li, Lingxi Li, Lingyan Li, Lingyi Li, Lingzhi Li, Linhong Li, Linke Li, Linlin Li, Linqi Li, Linqing Li, Linsheng Li, Linting Li, Linxin Li, Linyan Li, Linying Li, Lipeng Li, Liping Li, Liqin Li, Liqun Li, Lirong Li, Lisha Li, Litao Li, Liuzheng Li, Liwei Li, Lixi Li, Lixia Li, Lixiang Li, Liyan Li, Long Li, Long Shan Li, Long-Yan Li, Longhui Li, Longxuan Li, Longyu Li, Lu Li, Lu-Yun Li, Lucia M Li, Lucy Li, Luhan Li, Lujiao Li, Lujie Li, Lulu Li, Luquan Li, Luxuan Li, Luyao Li, Luying Li, M D Li, M Li, M V Li, M-J Li, Man Li, Man-Xiang Li, Man-Zhi Li, Mangmang Li, Manjiang Li, Manna Li, Manru Li, Manxia Li, Mao Li, Maogui Li, Maolin Li, Maoquan Li, Maosheng Li, Marilyn Li, Mei Li, Mei-Lan Li, Mei-Ya Li, Mei-Zhen Li, Meifang Li, Meifen Li, Meijia Li, Meilan Li, Meiqing Li, Meitao Li, Meiting Li, Meiyan Li, Meiying Li, Meiyue Li, Meizi Li, Melody M H Li, Meng Li, Meng-Hua Li, Meng-Jun Li, Meng-Meng Li, Meng-Miao Li, Meng-Yang Li, Meng-Yao Li, Meng-Yue Li, MengGe Li, Mengfan Li, Menghua Li, Mengjiao Li, Mengjuan Li, Mengling Li, Menglu Li, Mengmeng Li, Mengqing Li, Mengqiu Li, Mengsen Li, Mengshi Li, Mengxi Li, Mengxia Li, Mengxuan Li, Mengyang Li, Mengyao Li, Mengying Li, Mengyuan Li, Mengyun Li, Mengze Li, Mi Li, Mian Li, Miao Li, Miao X Li, Miaoxin Li, Michelle Li, Mimi Li, Min Li, Min-Dian Li, Min-Rui Li, Min-jun Li, Minerva X Li, Ming D Li, Ming Li, Ming V Li, Ming Xing Li, Ming Zhou Li, Ming-Han Li, Ming-Hao Li, Ming-Jiang Li, Ming-Kai Li, Ming-Qing Li, Ming-Wei Li, Ming-Xing Li, Ming-Yang Li, Mingdan Li, Mingfang Li, Mingfei Li, Minghao Li, Minghua Li, Minghui Li, Mingjiang Li, Mingjie Li, Mingjun Li, Mingke Li, Mingkun Li, Mingli Li, Minglong Li, Minglun Li, Mingna Li, Mingqiang Li, Mingquan Li, Mingrui Li, Mingwei Li, Mingxi Li, Mingxia Li, Mingxing Li, Mingxu Li, Mingxuan Li, Mingyang Li, Mingyao Li, Mingyue Li, Mingzhe Li, Mingzhou Li, Minhui Li, Minle Li, Minmin Li, Minqi Li, Minyue Li, Minze Li, Minzhe Li, Miyang Li, Mo Li, Mohan Li, Monica M Li, Moyi Li, Mufan Li, Mulin Jun Li, Muzi Li, N Li, Na Li, Naishi Li, Nan Li, Nan-Nan Li, Nana Li, Nanjun Li, Nanlong Li, Nanxing Li, Nanzhen Li, Ni Li, Nianfu Li, Nianyu Li, Nien Li, Nien-Chen Li, Nien-Chi Li, Ning Li, Ningyan Li, Ningyang Li, Niu Li, Nuomin Li, O Li, P H Li, P Li, Pan Li, Panlong Li, Panyuan Li, Pei Li, Pei-Lin Li, Pei-Qin Li, Pei-Shan Li, Pei-Ying Li, Pei-Zhi Li, PeiQi Li, Peibo Li, Peifen Li, Peifeng Li, Peihong Li, Peihua Li, Peilin Li, Peilong Li, Peining Li, Peipei Li, Peiqin Li, Peiran Li, Peiwu Li, Peixin Li, Peiyu Li, Peiyuan Li, Peiyun Li, Peng Li, Peng Peng Li, Peng-li Li, Pengcui Li, Penghui Li, Pengjie Li, Pengju Li, Pengsong Li, Pengyang Li, Pengyu Li, Pengyun Li, Pik Yi Li, Pilong Li, Pindong Li, Ping Li, Ping'an Li, Pinghua Li, Pingping Li, Pu Li, Pu-Yu Li, Q Li, Qi Li, Qi-Fu Li, Qi-Jing Li, Qian Li, Qian-Qian Li, Qiang Li, Qiang-Ming Li, Qiankun Li, Qianqian Li, Qiao Li, Qiao-Xin Li, Qiaolian Li, Qiaoqiao Li, Qibing Li, Qifang Li, Qihang Li, Qihua Li, Qiji Li, Qijun Li, Qilan Li, Qilong Li, Qin Li, Qiner Li, Qing Li, Qing Run Li, Qing-Chang Li, Qing-Fang Li, Qing-Min Li, Qing-Wei Li, Qingchao Li, Qingfang Li, Qingfeng Li, Qinggang Li, Qinghe Li, Qinghong Li, Qinghua Li, Qingjie Li, Qinglan Li, Qingli Li, Qinglin Li, Qingling Li, Qingqin S Li, Qingrun Li, Qingshang Li, Qingsheng Li, Qingxian Li, Qingyang Li, Qingyu Li, Qingyuan Li, Qingyun Li, Qinqin Li, Qinrui Li, Qintong Li, Qiong Li, Qionghua Li, Qipei Li, Qiqiong Li, Qiu Li, Qiufeng Li, Qiuhong Li, Qiusheng Li, Qiuxuan Li, Qiuya Li, Qiuyan Li, Qiwei Li, Qiyong Li, Qizhai Li, Quan Li, Quan-Zhong Li, Quanpeng Li, Quanshun Li, Quanzhang Li, Qun Li, R H L Li, R Li, Ran Li, Ranchang Li, Ranran Li, Ranwei Li, Ren Li, Ren-Ke Li, Rena Li, Roger Li, Ronald Li, Rong Li, Rong-Bing Li, Ronggui Li, Rongkai Li, Rongling Li, Rongqing Li, Rongsong Li, Rongxia Li, Rongyao Li, Rosa J W Li, Ru Li, Ru-Hao Li, Rui Li, Rui-Fang Li, Rui-Han Li, Rui-Jún Eveline Li, Ruibing Li, Ruidong Li, Ruifang Li, Ruihuan Li, Ruijia Li, Ruijin Li, Ruikai Li, Ruitong Li, Ruiwen Li, Ruixi Li, Ruixia Li, Ruixue Li, Ruiyang Li, Rujia Li, Rulin Li, Rumei Li, Runbing Li, Runwen Li, Runzhao Li, Runzhen Li, Runzhi Li, Ruobing Li, Ruolin Li, Ruonan Li, Ruotai Li, Ruotian Li, Ruotong Li, Ruyi Li, Ruyue Li, S A Li, S E Li, S L Li, S Li, S S Li, S-C Li, Sai Li, Saijuan Li, Sainan Li, San-Feng Li, Sanqiang Li, Senlin Li, Senmao Li, Sha Li, Sha-Sha Li, Shan Li, Shan-Shan Li, Shangjia Li, Shanglai Li, Shangming Li, Shanhang Li, Shanpeng Li, Shanshan Li, Shanyi Li, Shao-Dan Li, Shaobin Li, Shaodan Li, Shaofei Li, Shaoguang Li, Shaojian Li, Shaojing Li, Shaoliang Li, Shaomin Li, Shaoqi Li, Shaoyong Li, Shasha Li, Shawn S C Li, Shawn Shun-Cheng Li, Shen Li, Sheng Li, Sheng-Fu Li, Sheng-Jie Li, Sheng-Qing Li, Sheng-Tien Li, Shengbiao Li, Shengbin Li, Shengchao A Li, Shenghao Li, Shengjie Li, Shengli Li, Shengliang Li, Shengsheng Li, Shengwen Li, Shengxian Li, Shengxu Li, Shengze Li, Sherly X Li, Shi Li, Shi-Fang Li, Shi-Guang Li, Shi-Hong Li, Shi-Ying Li, Shibao Li, Shibo Li, Shichao Li, Shigang Li, Shihao Li, Shiheng Li, Shihong Li, Shijie Li, Shijun Li, Shikang Li, Shilan Li, Shili Li, Shiliang Li, Shilin Li, Shilun Li, Shiqi Li, Shiquan Li, Shisheng Li, Shishi Li, Shitao Li, Shiya Li, Shiyan Li, Shiyang Li, Shiyi Li, Shiying Li, Shiyu Li, Shiyue Li, Shiyun Li, Shu Li, Shu-Fang Li, Shu-Fen Li, Shu-Feng Li, Shu-Hong Li, Shu-Qi Li, Shu-Xin Li, Shuai Li, Shuaicheng Li, Shuang Li, Shuang-Ling Li, Shuangding Li, Shuangfei Li, Shuanglong Li, Shuangmei Li, Shuangshuang Li, Shuangxiu Li, Shubo Li, Shude Li, Shufen Li, Shugang Li, Shuguang Li, Shuhao Li, Shuhua Li, Shuhui Li, Shujiao Li, Shujie Li, Shujin Li, Shujing Li, Shulin Li, Shun Li, Shunhua Li, Shunle Li, Shunqin Li, Shunqing Li, Shunwang Li, Shuo Li, Shupeng Li, Shuqiang Li, Shuwei Li, Shuwen Li, Shuying Li, Shuyu D Li, Shuyu Dan Li, Shuyuan Li, Shuyue Li, Si Li, Si-Wei Li, Si-Xing Li, Si-Ying Li, Si-Yuan Li, Sibing Li, Sichen Li, Sichong Li, Side Li, Siguang Li, Sijie Li, Simin Li, Siming Li, Sin-Lun Li, Siqi Li, Sitao Li, Siting Li, Siwen Li, Siyi Li, Siyu Li, Siyue Li, Song Li, Song-Chao Li, Songhan Li, Songlin Li, Songtao Li, Songyu Li, Songyun Li, Stephen Li, Su Li, SuYun Li, Suchun Li, Suheng Li, Suhong Li, Suiyan Li, Sujing Li, Suk-Yee Li, Sumei Li, Sunan Li, Sung-Chou Li, Supeng Li, Suping Li, Suran Li, Suwei Li, Suwen Li, Suyan Li, T Li, Taibo Li, Taiwen Li, Taixu Li, Tao Li, Taoyingnan Li, Teng Li, Tengyan Li, Thomas Li, Tian Li, Tian-Yi Li, Tian-chang Li, Tian-wang Li, Tianchang Li, Tiandong Li, Tianfeng Li, Tiange Li, Tianjiao Li, Tianjun Li, Tianming Li, Tiansen Li, Tiantian Li, Tianxiang Li, Tianyao Li, Tianye Li, Tianyi Li, Tianyou Li, Tie Li, Tiegang Li, Tiehua Li, Tiewei Li, Timmy Li, Ting Li, Tingguang Li, Tinghao Li, Tinghua Li, Tingsong Li, Tingting Li, Tong Li, Tong-Ruei Li, Tongyao Li, Tongzheng Li, Tsai-Kun Li, Tuojian Li, Tuoping Li, Vivian Li, Vivian S W Li, W H Li, W J Li, W Li, W W Li, W Y Li, W-B Li, Wan Jie Li, Wan Li, Wan-Hong Li, Wan-Shan Li, Wan-Xin Li, Wang Li, Wanling Li, Wanni Li, Wanqian Li, Wanru Li, Wanshi Li, Wanshun Li, Wanting Li, Wanwan Li, Wanxin Li, Wanyan Li, Wanyi Li, Wei Li, Wei-Bo Li, Wei-Dong Li, Wei-Jun Li, Wei-Li Li, Wei-Ming Li, Wei-Na Li, Wei-Ping Li, Wei-Qin Li, Wei-Yang Li, Weidong Li, Weifeng Li, Weiguang Li, Weiguo Li, Weihai Li, Weiheng Li, Weihua Li, Weijian Li, Weijie Li, Weijun Li, Weike Li, Weiling Li, Weimin Li, Weina Li, Weining Li, Weiping Li, Weiqin Li, Weirong Li, Weisong Li, Weiyang Li, Weiye Li, Weiyong Li, Weizu Li, Wen Lan Li, Wen Li, Wen-Chao Li, Wen-Jie Li, Wen-Ting Li, 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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, 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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, 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, 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articles
Jian Gao, Linjie Yuan, Huanyu Jiang +7 more · 2024 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Previous studies have demonstrated that naringenin possesses lipid-lowering effects; however, the underlying mechanisms, particularly its specific molecular targets, remain uncertain. Using bioinforma Show more
Previous studies have demonstrated that naringenin possesses lipid-lowering effects; however, the underlying mechanisms, particularly its specific molecular targets, remain uncertain. Using bioinformatics, three traditional Chinese medicine databases and one human disease database were integrated to establish two naringenin-target-hyperlipidemia modules: naringenin-oxidative stress (OS) and naringenin-lipid metabolism (LM). Data on 1,850 proteins from 1,871 genetic instruments were sourced from seven previous studies. Using Mendelian randomization based on data from the Integrative Epidemiology Unit genome-wide association study (case, n = 5,153; control, n = 344,069), we identified potential drug targets that were subsequently validated in the UK Biobank (396,565 individuals) and FinnGen (412,181 individuals) cohorts. Using molecular docking and molecular dynamics simulation to verify the binding ability of naringenin and causal protein. In plasma, every standard deviation increase in apolipoprotein B (APOB) was associated with an increased risk of hyperlipidemia (odds ratio [OR] = 9.37, 95% confidence interval [CI], 5.12-17.12; This Mendelian randomization-based combined analysis offers a robust framework for elucidating the pharmacological effects of naringenin and identifying candidate proteins for further investigation in the context of hyperlipidemia treatment. Show less
📄 PDF DOI: 10.3389/fphar.2024.1448308
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X N Zhang, Q T Meng, H W Zhang +5 more · 2024 · Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine] · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112150-20240708-00546
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Hua Jin, Chong Li, Yunxiao Jia +2 more · 2024 · Wiley interdisciplinary reviews. RNA · Wiley · added 2026-04-24
RNA-binding proteins (RBPs) are powerful and versatile regulators in living creatures, playing fundamental roles in organismal development, metabolism, and various diseases by the regulation of gene e Show more
RNA-binding proteins (RBPs) are powerful and versatile regulators in living creatures, playing fundamental roles in organismal development, metabolism, and various diseases by the regulation of gene expression at multiple levels. The requirements of deep research on RBP function have promoted the rapid development of RBP-RNA interplay detection methods. Recently, the detection method of fusing RNA modification enzymes (RME) with RBP of interest has become a hot topic. Here, we reviewed RNA modification enzymes in adenosine deaminases that act on RNA (ADAR), terminal nucleotidyl transferase (TENT), and activation-induced cytosine deaminase/ApoB mRNA editing enzyme catalytic polypeptide-like (AID/APOBEC) protein family, regarding the biological function, biochemical activity, and substrate specificity originated from enzyme selves, their domains and partner proteins. In addition, we discussed the RME activity screening system, and the RME mutations with engineered enzyme activity. Furthermore, we provided a systematic overview of the basic principles, advantages, disadvantages, and applications of the RME-based and cross-linking and immunopurification (CLIP)-based RBP target profiling strategies, including targets of RNA-binding proteins identified by editing (TRIBE), RNA tagging, surveying targets by APOBEC-mediated profiling (STAMP), CLIP-seq, and their derivative technology. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Processing > RNA Editing and Modification. Show less
📄 PDF DOI: 10.1002/wrna.1863
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Jiqing Li, Jiate Wei, Ping Fu +1 more · 2024 · Heliyon · Elsevier · added 2026-04-24
Most coronary artery disease (CAD) risk loci identified by genome-wide association studies (GWAS) are located in non-coding regions, hampering the interpretation of how they confer CAD risk. It is ess Show more
Most coronary artery disease (CAD) risk loci identified by genome-wide association studies (GWAS) are located in non-coding regions, hampering the interpretation of how they confer CAD risk. It is essential to integrate GWAS with molecular traits data to further explore the genetic basis of CAD. We used the probabilistic Mendelian randomization (PMR) method to identify potential proteins involved in CAD by integrating CAD GWAS data (∼76,014 cases and ∼264,785 controls) and human plasma proteomes (N = 35,559). Then, Bayesian co-localization analysis, confirmatory PMR analysis using independent plasma proteome data (N = 7752), and gene expression data (N1 = 213, N2 = 670) were performed to validate candidate proteins. We further investigated the associations between candidate proteins and CAD-related traits and explored the rationality and biological functions of candidate proteins through disease enrichment, cell type-specific, GO, and KEGG enrichment analysis. This study inferred that the abundance of 30 proteins in the plasma was causally associated with CAD ( Our integration analysis has identified 30 candidate proteins for CAD, which may provide important leads to design future functional studies and potential drug targets for CAD. Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e38036
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Dong Liu, Jin Zhang, Xiaoyu Zhang +9 more · 2024 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
In recent years, the position of PCSK9 inhibitors as adjuvant therapy to statins in guidelines has further improved. However, there remained a dearth of direct comparative studies among different PCSK Show more
In recent years, the position of PCSK9 inhibitors as adjuvant therapy to statins in guidelines has further improved. However, there remained a dearth of direct comparative studies among different PCSK9 inhibitors. Therefore, this study aimed to conduct a network meta-analysis to evaluate the efficacy and safety of different PCSK9 inhibitors combined with statins. A comprehensive literature search was conducted from the study's inception to 12 November 2023, encompassing multiple online databases including PubMed, Embase, Cochrane Central, Web of Science, and ClinicalTrials.gov to obtain relevant randomized controlled trials. Frequentist network meta-analysis was employed to compare the efficacy and safety of different PCSK9 inhibitors. The efficacy endpoints were low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (ApoB), and lipoprotein (a) (Lp(a)). The safety endpoints were any adverse events (AE), severe adverse events (SAE), AE leading to treatment discontinuation, and injection-site reaction. Compared with placebo and ezetimibe, all PCSK9 inhibitors demonstrated significant reductions in LDL-C levels. Notably, evolocumab exhibited the most pronounced effect with a treatment difference of -63.67% (-68.47% to -58.87%) compared with placebo. Regarding dosage selection for evolocumab, the regimen of 140 mg Q2W (-69.13%, -74.55% to -63.72%) was superior to 420 mg QM (-61.51%, -65.97% to -57.05%). Based on rankings and Compared with placebo and ezetimibe, PCSK9 inhibitors can significantly reduce LDL-C, ApoB, and Lp(a) when combined with statins to treat hypercholesterolemia. Furthermore, PCSK9 inhibitors and ezetimibe exhibit similar safety profiles. [PROSPERO], identifier [CRD42023490506]. Show less
📄 PDF DOI: 10.3389/fcvm.2024.1454918
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Di Feng, Xiao Wang, Jiahui Song +8 more · 2024 · Human reproduction (Oxford, England) · Oxford University Press · added 2026-04-24
Is there a relationship between serum uric acid and fructose levels in polycystic ovary syndrome (PCOS)? Elevated serum uric acid levels in women with PCOS positively correlate with serum fructose lev Show more
Is there a relationship between serum uric acid and fructose levels in polycystic ovary syndrome (PCOS)? Elevated serum uric acid levels in women with PCOS positively correlate with serum fructose levels, and elevated serum fructose levels are an independent risk factor for hyperuricemia in women with PCOS. Our previous study suggested a link between elevated serum fructose levels and PCOS. Fructose is unique as it generates uric acid during metabolism, and high uric acid levels are associated with metabolic disorders and an increased risk of anovulation. However, the relationship between serum uric acid and fructose levels in women with PCOS remains unclear. In a case-control study of 774 women (482 controls and 292 patients with PCOS) between May and October 2020 at the Shengjing Hospital of China Medical University, the relationship between uric acid and fructose levels in women with PCOS was examined. Participants were divided into subgroups based on various factors, including BMI, insulin resistance, dyslipidemia, metabolic syndrome, and hyperuricemia. Serum uric acid concentrations were measured using enzymatic assays, and serum fructose levels were determined using a fluorescent enzyme immunoassay. Dietary fructose data were collected through a validated food-frequency questionnaire of 81 food items. We applied restricted cubic splines to a flexibly model and visualized the linear/nonlinear relationships between serum uric acid and fructose levels in PCOS. Multivariate logistic analysis was executed to assess the association between serum fructose levels and hyperuricemia in PCOS. Human granulosa cell and oocyte mRNA profile sequencing data were downloaded for mapping uric acid and fructose metabolism genes in PCOS. Further downstream analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and protein-protein interactions were then carried out on the differentially expressed genes (DEGs). The correlation between uric acid and fructose metabolism genes was calculated using the Pearson correlation coefficient. The GeneCards database was used to identify DEGs related to uric acid and fructose metabolism in PCOS, and then several DEGs were confirmed by quantitative real-time PCR. Both serum fructose and uric acid levels were significantly increased in women with PCOS compared with the control women (P  <  0.001), and there was no statistically significant difference in dietary fructose intake between PCOS and controls, regardless of metabolic status. There was a positive linear correlation between serum uric acid and fructose levels in women with PCOS (Poverall < 0.001, Pnon-linear = 0.30). In contrast, no correlation was found in control women (Poverall = 0.712, Pnon-linear = 0.43). Additionally, a non-linear association was observed in the obese subgroup of patients with PCOS (Poverall < 0.001, Pnon-linear = 0.02). Serum uric acid levels were linearly and positively associated with serum fructose levels in patients with PCOS with insulin resistance, dyslipidemia, and metabolic syndrome. Furthermore, even after adjusting for confounding factors, elevated serum fructose levels were an independent risk factor for hyperuricemia in patients with PCOS (P  =  0.001; OR, 1.380; 95% CI, 1.207-1.577). There were 28 uric acid and 25 fructose metabolism genes which showed a significant correlation in PCOS. Seven upregulated genes (CAT, CRP, CCL2, TNF, MMP9, GCG, and APOB) related to uric acid and fructose metabolism in PCOS ovarian granulosa cells were ultimately successfully validated using quantitative real-time PCR. Due to limited conditions, more possible covariates (such as smoking and ethnicity) were not included, and the underlying molecular mechanism between fructose and uric acid levels in women with PCOS remains to be further investigated. The results of this study and our previous research indicate that the high uric acid status of PCOS may be mediated by fructose metabolism disorders, highlighting the importance of analyzing fructose metabolism, and especially its metabolic byproduct uric acid, during the clinical diagnosis of PCOS. These results suggest the adverse effects of high uric acid in PCOS, and the importance of taking early interventions regarding uric acid levels to reduce the occurrence and development of further clinical signs, such as metabolic disorders in women with PCOS. This work was supported by: the National Natural Science Foundation of China (No. 82371647, No. 82071607, and No. 32100691); LiaoNing Revitalization Talents Program (No. XLYC1907071); Fok Ying Tung Education Foundation (No. 151039); and Outstanding Scientific Fund of Shengjing Hospital (No. 202003). No competing interests were declared. N/A. Show less
no PDF DOI: 10.1093/humrep/deae219
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Lei Yang, Changze Jia, Yanzhong Li +3 more · 2024 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Egg performance significantly impacts the development of the local goose industry. The hypothalamus plays an essential role in the egg production of birds. However, few potential candidate genes and b Show more
Egg performance significantly impacts the development of the local goose industry. The hypothalamus plays an essential role in the egg production of birds. However, few potential candidate genes and biological functions related to egg production in geese have been identified in hypothalamus tissue. In this study, 115 geese were raised and observed for 5 months during the laying period. To understand the regulation mechanism of egg production, the hypothalamus transcriptome profiles of these geese were sequenced using RNA-seq. The hypothalamus samples of four high egg production (HEP) and four low egg production (LEP) geese were selected and collected, respectively. A total of 14,679 genes were identified in the samples. After multiple bioinformatics analyses, Gene Ontology (GO) annotations indicated that genes related to egg production were mainly enriched in biological processes of "response to light stimulus," "sensory system development," and "visual perception." Six potential candidate genes ( Show less
📄 PDF DOI: 10.3389/fvets.2024.1449032
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Ewa Karwatowska-Prokopczuk, Anastasia Lesogor, Jing-He Yan +4 more · 2024 · Lipids in health and disease · BioMed Central · added 2026-04-24
Olezarsen is a GalNAc A randomized, placebo-controlled, double-blind phase 1 study was performed in 28 healthy Japanese American participants treated with olezarsen in single-ascending doses (SAD; 30, Show more
Olezarsen is a GalNAc A randomized, placebo-controlled, double-blind phase 1 study was performed in 28 healthy Japanese American participants treated with olezarsen in single-ascending doses (SAD; 30, 60, 90 mg) or multiple doses (MD; 60 mg every 4 weeks for 4 doses). The primary, secondary, and exploratory objectives were safety and tolerability, pharmacokinetics, and effects of olezarsen on fasting serum triglycerides and apoC-III, respectively. There were 20 participants (16 active:4 placebo) in the SAD part of the study, and 8 participants (6 active:2 placebo) in the MD part of the study. For the primary endpoint, no serious adverse events or clinically relevant laboratory abnormalities were reported. The majority of olezarsen plasma exposure occurred within 24 h post-dose. In the SAD cohorts at Day 15 the percentage reduction in apoC-III/TG was - 39.4%/ - 17.8%, - 60.8%/ - 52.7%, and - 68.1%/ - 39.2% in the 30, 60 and 90 mg doses, respectively, vs 2.3%/44.5% increases in placebo. In the MD cohort, at Day 92 the percentage reduction in apoC-III/TG was - 81.6/ - 73.8% vs - 17.2/ - 40.8% reduction in placebo. Favorable changes were also present in VLDL-C, apoB and HDL-C. Single- and multiple-dose administration of olezarsen was safe, was well tolerated, and significantly reduced apoC-III and triglyceride levels in healthy Japanese Americans. Show less
📄 PDF DOI: 10.1186/s12944-024-02297-5
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Ziyang Liu, Yang Zhou, Menglong Jin +8 more · 2024 · PeerJ · added 2026-04-24
Dyslipidemia plays a very important role in the occurrence and development of cardiovascular disease (CVD). Genetic factors, including single nucleotide polymorphisms (SNPs), are one of the main risks Show more
Dyslipidemia plays a very important role in the occurrence and development of cardiovascular disease (CVD). Genetic factors, including single nucleotide polymorphisms (SNPs), are one of the main risks of dyslipidemia. 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) is not only the rate-limiting enzyme step of endogenous cholesterol production, but also the therapeutic target of statins. We investigated 405 Han Chinese and 373 Uyghur people who took statins for a period of time, recorded their blood lipid levels and baseline data before and after oral statin administration, and extracted DNA from each subject for SNP typing of In this study, for rs17671591, the CC We found that Show less
📄 PDF DOI: 10.7717/peerj.18144
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DanDan Zhang, Jing Wu, Guoqiang Ren +5 more · 2024 · Brain and behavior · Wiley · added 2026-04-24
To explore the diagnostic value of serum apolipoprotein B100 (Apo B100) combined with hippocampal volume in Alzheimer's disease (AD). A total of 59 AD patients and 59 healthy subjects were selected. T Show more
To explore the diagnostic value of serum apolipoprotein B100 (Apo B100) combined with hippocampal volume in Alzheimer's disease (AD). A total of 59 AD patients and 59 healthy subjects were selected. The Mini-Mental State Examination (MMSE) was used for neuropsychological assessment. Blood glucose and serum lipid levels were detected by biochemical analyzer. Polymerase chain reaction (PCR) was used to detect apolipoprotein E (Apo E) ε3/ε4 genotypes in the plasma. Hippocampal volume was calculated using Slicer software. Independent-sample t test or Mann-Whitney U test were used to compare the levels of various indicators between the two groups. Spearman's correlation analysis was used to analyze the correlation between each level. The receiver operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated to compare the diagnostic efficacy of individual and combined detection of serum Apo B100 levels and hippocampal volume in AD. Compared with the healthy control group, the levels of serum total cholesterol (TC), low-density lipoprotein (LDL), Apo B100, and plasma Apo E ε3/ε4 were higher in the AD group, and serum high-density lipoprotein (HDL) level was lower in the AD group (both p < 0.05). The hippocampal volume in the AD group was lower than in the control group (p < 0.01). The serum Apo B100 level was negatively correlated with MMSE score (r = -0.646), whereas hippocampal volume was positively correlated with MMSE score (r = 0.630). ROC curve analysis showed that the AUC of the combined serum Apo B100 level and hippocampal volume for AD was higher than that of either alone (AUC = 0.821, p < 0.01). Serum Apo B100 level is elevated, and the hippocampal volume is reduced in AD patients. The combined detection of the two has a higher diagnostic efficiency for AD than other alone and has the potential to become an important indicator for the diagnosis of AD in the future. Show less
📄 PDF DOI: 10.1002/brb3.70066
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Xuan Wang, Lu Lyu, Wei Li +6 more · 2024 · Diabetes & metabolic syndrome · Elsevier · added 2026-04-24
This investigation aimed to evaluate the efficacy and safety of rosuvastatin in treating moderate to severe metabolic associated fatty liver disease (MAFLD). This prospective, open-label, randomized s Show more
This investigation aimed to evaluate the efficacy and safety of rosuvastatin in treating moderate to severe metabolic associated fatty liver disease (MAFLD). This prospective, open-label, randomized study included non-diabetic participants with metabolic syndrome and intrahepatocellular lipid (IHCL) levels >10 %, as determined by proton magnetic resonance spectroscopy ( Thirty-two participants completed the study. Rosuvastatin resulted in a significant absolute (△IHCL: 7.61 ± 4.51 vs. 1.54 ± 5.33, p = 0.002) and relative reduction in IHCL (△IHCL%: -42.28 ± 24.90 % vs. -8.91 ± 31.93 %, p = 0.003) compared to the control. Reduction in IHCL correlated significantly with decreases in low-density lipoprotein cholesterol (LDL-C) (r = 0.574, p < 0.01), apolipoprotein B (ApoB) (r = 0.660, p < 0.001), and free fatty acids (FFA) (r = 0.563, p = 0.005). No significant safety differences were observed between groups. Rosuvastatin significantly reduced hepatic steatosis in individuals with moderate to severe MAFLD and metabolic syndrome over 52 weeks, while maintaining a favorable safety profile. Show less
no PDF DOI: 10.1016/j.dsx.2024.103126
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Mengjun Tao, Yuanxiang Zhang, Qi Li +2 more · 2024 · Journal of clinical lipidology · Elsevier · added 2026-04-24
It remains unclear whether lipid profiles and lipid-lowering medications are causally related to peripheral arterial disease (PAD). Explain whether there is a causal relationship between lipid status Show more
It remains unclear whether lipid profiles and lipid-lowering medications are causally related to peripheral arterial disease (PAD). Explain whether there is a causal relationship between lipid status and lipid-lowering drugs and PAD. In this two-sample Mendelian randomization (MR) analysis, we assessed the causal relationship between lipid traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), total cholesterol (TC), and LDL-associated genetic variants (HMGCR, NPC1L1, PCSK9, APOB), and the risk of PAD using genetic variants associated with these lipid markers. The study analyzed data from 1,654,960 individuals derived from the Global Lipid Genetics Consortium and the UK Biobank, ensuring a robust and comprehensive genetic insight into the effects of lipid dysfunction on PAD. We found genetically predicted associations between HDL-C (OR: 0.83, 95% CI: 0.83-0.77), LDL-C (OR: 1.29, 95% CI: 1.12-1.50), TC (OR: 1.14, 95% CI: 1.01- 1.29), TG (OR: 1.16, 95% CI: 1.04-1.24), APOB (OR: 1.31, 95% CI: 1.16-1.48), and APOA1 (OR: 0.84, 95% CI: 0.77-0.97), and the risk of PAD. In addition, inhibition of PCSK9 was associated with a reduced risk of PAD (OR: 0.68, 95% CI: 0.57-0.79, P<0.001), while no association between the other three gene proxies of LDL inhibition including HMGCR (OR: 1.21, 95% CI: 0.87-1.69, P=0.250), NPC1L1 (OR: 0.77, 95% CI: 0.44-1.33, P=0.344), and APOB (OR: 1.01, 95% CI: 0.87-1.26, P=0.890), and the risk of PAD were found. Based on genetic evidence, dyslipidemia is an important risk factor for PAD. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors may be an effective strategy for the treatment of PAD. Show less
no PDF DOI: 10.1016/j.jacl.2024.06.007
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Jiayu Wang, Lisi Xu, Xuemei Chen +10 more · 2024 · Journal of Alzheimer's disease : JAD · added 2026-04-24
Apolipoproteins and cortical morphology are closely associated with memory complaints, and both may contribute to the development of Alzheimer's disease. To examine whether apolipoprotein B (ApoB), ap Show more
Apolipoproteins and cortical morphology are closely associated with memory complaints, and both may contribute to the development of Alzheimer's disease. To examine whether apolipoprotein B (ApoB), apolipoprotein A-1 (ApoA1), and their ratio (ApoB/ApoA1) are associated with cortical morphology in patients with memory complaints. Ninety-seven patients underwent neuropsychological testing, measurements of ApoB, ApoA1, ApoB/ApoA1, plasma Alzheimer's biomarker, apolipoprotein E (ApoE) genotyping, and 3T structural magnetic resonance imaging (sMRI) scans. Based on sMRI scanning locations, patients were categorized into the University of Electronic Science and Technology (UESTC) and the Fourth People's Hospital of Chengdu (FPHC). The Computational Anatomy Toolbox within Statistical Parametric Mapping was used to calculate each patient's cortical morphology index based on sMRI data. The cortical morphology index and apolipoproteins were also analyzed. Significant positive correlations were found between ApoB and sulcal depth in the lateral occipital cortex among the UESTC, the FPHC, and the total sample groups, and negative correlations were observed between sulcal depth in the lateral occipital cortex and the scores of the Shape Trails Test Part A and B. In the FPHC group, the scores of the Montreal Cognitive Assessment Basic, delayed recall of the Auditory Verbal Learning Test, Animal Fluency Test and Boston Naming Test were positively correlated with the sulcal depth. ApoB is associated with the sulcal depth in the lateral occipital cortex, potentially relating to speed/executive function in individuals with memory complaints. Show less
no PDF DOI: 10.3233/JAD-230863
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Yili Wu, Jiankui Ye, Zhuowei Shao +4 more · 2024 · Journal of thoracic disease · added 2026-04-24
The integration of chemotherapy and immunotherapy as a first-line treatment for extensive-stage small cell lung cancer (ES-SCLC) has been adopted in clinical practice, yet the response to immune check Show more
The integration of chemotherapy and immunotherapy as a first-line treatment for extensive-stage small cell lung cancer (ES-SCLC) has been adopted in clinical practice, yet the response to immune checkpoint inhibitors (ICIs) is variable, benefiting only a fraction of patients. The current absence of reliable biomarkers for predicting treatment response and prognosis represents a significant gap in knowledge, hindering the optimization of patient stratification and treatment planning. This retrospective cohort study aims to assess the potential predictive and prognostic significance of clinicopathological baseline features in ES-SCLC patients. Our study retrospectively analyzed the data of consecutive patients with ES-SCLC treated with first-line etoposide plus platinum chemotherapy ± immunotherapy at The Affiliated Lihuili Hospital of Ningbo University from April 2017 to April 2023. Data on clinical information, serum laboratory indicators, pathological immunohistochemical markers, and progression-free survival (PFS) times were collected. Univariate and multivariate Cox regression analyses were employed to determine whether these indicators could serve as independent prognostic factors for PFS. Further, potential predictive markers for treatment efficacy were identified using a Cox regression model that incorporated an interaction term between treatment modality and the indicator. A total of 121 patients with ES-SCLC were enrolled in the study, of whom 62 received chemotherapy alone, and 59 received chemotherapy in combination with immunotherapy. Compared to chemotherapy alone, the addition of immunotherapy to first-line chemotherapy significantly extended the PFS time [P<0.001; hazard ratio (HR) =0.42; 95% confidence interval (CI): 0.28, 0.64] of the ES-SCLC patients. The multivariate analysis revealed that an immunochemotherapy regimen (P<0.001, HR =0.40; 95% CI: 0.24, 0.68), a low-density lipoprotein (LDL) level of >1.8 mmol/L (P=0.02; HR =0.41; 95% CI: 0.20, 0.85) were independent prognostic factors of favorable PFS in the first-line treatment of all ES-SCLC, while a lactate dehydrogenase (LDH) level of >273 U/L (P=0.04; HR =1.78; 95% CI: 1.03, 3.07), a neuron-specific enolase (NSE) concentration of >102.6 ng/mL (P=0.009; HR =6.49; 95% CI: 1.60, 26.32), an apolipoprotein A1 (ApoA1) concentration of >0.9 g/L (P<0.001; HR =4.15; 95% CI: 1.98, 8.71), and an apolipoprotein B (ApoB) concentration of >0.8 g/L (P=0.002; HR =2.24; 95% CI: 1.34, 3.75) were independent prognostic factors of poorer PFS. Further, the interaction effect analysis demonstrated that an LDL level of >1.8 mmol/L and the absence of bone metastasis were potential predictors of an improved response to ICI therapy compared to chemotherapy alone. This study showed the survival benefit of receiving a chemoimmunotherapy regimen as the first-line treatment in a real-world scenario. It also suggests the prognostic significance of pre-treatment LDL, LDH, NSE, ApoA1, and ApoB with optimal cut-off values in the first-line treatment of all ES-SCLC, and the potential utility of baseline LDL level or the presence of bone metastasis in guiding first-line treatment strategies. Show less
📄 PDF DOI: 10.21037/jtd-24-929
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Xinyue Ming, Shirui Chen, Huijuan Li +3 more · 2024 · Cellular signalling · Elsevier · added 2026-04-24
This study aimed to investigate the effects of hepatic microRNA-122 (miR-122) on Sortilin-mediated apolipoprotein B100 (apoB-100) secretion, and on aortic lipid deposition and atherosclerosis (AS) les Show more
This study aimed to investigate the effects of hepatic microRNA-122 (miR-122) on Sortilin-mediated apolipoprotein B100 (apoB-100) secretion, and on aortic lipid deposition and atherosclerosis (AS) lesions and to clarify the antiatherosclerotic mechanism of 6-methylcoumarin (6-MC) via the modulation of miR-122. Bioinformatics analysis revealed that miR-122 was putatively overexpressed in a liver-specific manner and was downregulated in steatotic livers. miR-122 was shown to suppress the expression of Sortilin by complementarily pairing to the 3'-untranslated region (3'-UTR) of Sortilin mRNA via bioinformatics and dual-luciferase reporter assays, impeding Sortilin-mediated apoB-100 secretion from HepG2 cells. Administration of 6-MC significantly upregulated hepatocellular miR-122 levels, reducing Sortilin expression and apoB-100 secretion in HepG2 cells. The miR-122 mimic vigorously enhanced 6-MC-depressed Sortilin expression, while miR-122 inhibitor repealed the inhibitory effect of 6-MC on Sortilin expression to some extent in HepG2 cells. After internal intervention with the miR-122 precursor, and 6-MC supplementation alone or in combination with the miR-122 sponge led to the reduction in blood triglyceride (TG) levels, low-density lipoprotein-cholesterol (LDL-C) and apoB-100 and a reduction in aortic lipid deposition and AS lesions in apolipoprotein E-deficient (ApoE Show less
no PDF DOI: 10.1016/j.cellsig.2024.111384
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Enmin Ding, Fuchang Deng, Jianlong Fang +23 more · 2024 · Environmental health perspectives · added 2026-04-24
Environmental contaminants (ECs) are increasingly recognized as crucial drivers of dyslipidemia and cardiovascular disease (CVD), but the comprehensive impact spectrum and interlinking mechanisms rema Show more
Environmental contaminants (ECs) are increasingly recognized as crucial drivers of dyslipidemia and cardiovascular disease (CVD), but the comprehensive impact spectrum and interlinking mechanisms remain uncertain. We aimed to systematically evaluate the association between exposure to 80 ECs across seven divergent categories and markers of dyslipidemia and investigate their underpinning biomolecular mechanisms via an unbiased integrative approach of internal chemical exposome and multi-omics. A longitudinal study involving 76 healthy older adults was conducted in Jinan, China, and participants were followed five times from 10 September 2018 to 19 January 2019 in 1-month intervals. A broad spectrum of seven chemical categories covering the prototypes and metabolites of 102 ECs in serum or urine as well as six serum dyslipidemia markers [total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, apolipoprotein (Apo)A1, ApoB, and ApoE4] were measured. Multi-omics, including the blood transcriptome, serum/urine metabolome, and serum lipidome, were profiled concurrently. Exposome-wide association study and the deletion/substitution/addition algorithms were applied to explore the associations between 80 EC exposures detection frequency Eight main ECs [1-naphthalene, 1-pyrene, 2-fluorene, dibutyl phosphate, tri-phenyl phosphate, mono-(2-ethyl-5-hydroxyhexyl) phthalate, chromium, and vanadium] were significantly associated with most dyslipidemia markers. Multi-omics indicated that the associations were mediated by endogenous biomolecules and pathways, primarily pertinent to CVD, inflammation, and metabolism. Clinical measures of cytokines and electrocardiograms further cross-validated the association of these exogenous ECs with systemic inflammation and cardiac function, demonstrating their potential mechanisms in driving dyslipidemia pathogenesis. It is imperative to prioritize mitigating exposure to these ECs in the primary prevention and control of the dyslipidemia epidemic. https://doi.org/10.1289/EHP13864. Show less
📄 PDF DOI: 10.1289/EHP13864
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Zhehan Yang, Junpan Chen, Minghao Wen +6 more · 2024 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Aberrant lipid metabolism is intricately linked to the development of endometrial cancer, and statin lipid-lowering medications are regarded as promising adjunctive therapies for future management of Show more
Aberrant lipid metabolism is intricately linked to the development of endometrial cancer, and statin lipid-lowering medications are regarded as promising adjunctive therapies for future management of this malignancy. This study employed Mendelian randomization (MR) to explore the causal association between lipid traits and endometrial cancer while assessing the potential impact of drug targets on lower lipids on endometrial cancer. Two-sample Mendelian randomization was employed to probe the causal association between lipid traits and endometrial carcinoma. Drug-target Mendelian randomization was also utilized to identify potential drug-target genes for managing endometrial carcinoma. In instances where lipid-mediated effects through particular drug targets were notable, the impacts of these drug targets on endometrial carcinoma risk factors were investigated to bolster the findings. No causal association between genetically predicted lipid traits (LDL-C, TG, TC, and HDL-C) and EC was found in two-sample Mendelian randomization. In drug target Mendelian randomization, genetic modeling of apolipoprotein B (APOB) (OR [95%CI]=0.31, [0.16-0.60]; The results of our MR study revealed no causal association between genetically predicted lipid traits (LDL-C, TG, TC, and HDL-C) and EC. Among the six lipid-lowering drug targets, we observed a significant association between lower predicted APOB levels and higher CETP levels with an increased risk of endometrioid carcinoma. These findings provide novel insights into the importance of lipid regulation in individuals with endometrial carcinoma, warranting further clinical validation and mechanistic investigations. Show less
📄 PDF DOI: 10.3389/fendo.2024.1446457
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Kun Liu, Xiaojuan Xu, Liang Sun +5 more · 2024 · Frontiers in immunology · Frontiers · added 2026-04-24
Unexplained recurrent pregnancy loss (URPL) is a clinical dilemma in reproductive fields. Its diagnosis is mainly exclusionary after extensive clinical examination, and some of the patients may still Show more
Unexplained recurrent pregnancy loss (URPL) is a clinical dilemma in reproductive fields. Its diagnosis is mainly exclusionary after extensive clinical examination, and some of the patients may still face the risk of miscarriage. We analyzed follicular fluid (FF) from Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEPs are involved in the biological processes (BP) of complement and coagulation cascades. Apolipoproteins (APOs) are key proteins in the PPI network. ELISA confirmed that APOB was low-expressed in both the FF and peripheral blood of URPL patients. Dysregulation of the immune network intersecting coagulation and inflammatory response is an essential feature of URPL, and this disequilibrium exists as early as the oogenesis stage. Therefore, earlier intervention is necessary to prevent the development of URPL. Moreover, aberrant lipoprotein regulation appears to be a key factor contributing to URPL. The mechanism by which these factors are involved in the complement and coagulation cascade pathways remains to be further investigated, which also provides new candidate targets for URPL treatment. Show less
📄 PDF DOI: 10.3389/fimmu.2024.1397633
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Junqi Liao, Yuan Zhu, Aimei Zhang +12 more · 2024 · Diabetes, metabolic syndrome and obesity : targets and therapy · added 2026-04-24
The relationship between insulin resistance-related indices and the outcomes of acute ischemic stroke (AIS) is still unclear. This study aimed to explore the association between the Apo B/Apo A-1 rati Show more
The relationship between insulin resistance-related indices and the outcomes of acute ischemic stroke (AIS) is still unclear. This study aimed to explore the association between the Apo B/Apo A-1 ratio and the Prognostic Nutritional Index (PNI) with the 90-day outcomes of AIS. A total of 2011 AIS patients with a 3-month follow-up were enrolled in the present study from January 2017 to July 2021. Multivariate logistic regression modeling was performed to analyze the relationship between Apo B/Apo A-1 ratio, PNI, and AIS poor outcomes. The mediating effect between the three was analyzed using the Bootstrap method with PNI as the mediating variable. Among the 2011 included AIS patients, 20.3% had a poor outcome. Patients were categorized according to quartiles of Apo B/Apo A-1 ratio and PNI. Multivariate logistic regression revealed that the fourth Apo B/Apo A-1 ratio quartile had poorer outcomes than the first quartile (OR 1.75,95%CL 1.21-2.53, P=0.003), and the fourth PNI quartile exhibited a lower risk of poor outcomes than the first quartile (OR 0.40, 95%CL 0.27-0.61, P<0.001). PNI displayed a significant partially mediating effect (21.4%) between the Apo B/Apo A-1 ratio and poor AIS outcomes. The Apo B/Apo A-1 ratio is a risk factor for poor AIS outcomes, whereas PNI acts as a protective factor. The association between the ApoB/ApoA-1 ratio and poor AIS outcomes was partially mediated by PNI. Show less
📄 PDF DOI: 10.2147/DMSO.S473385
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Cheng-Yu Chou, Po-Chieh Chiang, Chih-Chi Li +7 more · 2024 · ACS applied materials & interfaces · ACS Publications · added 2026-04-24
Extracellular vesicles (EVs) are present in blood at much lower concentrations (5-6 orders of magnitude) compared to lipoprotein particles (LP). Because LP and EV overlap in size and density, isolatin Show more
Extracellular vesicles (EVs) are present in blood at much lower concentrations (5-6 orders of magnitude) compared to lipoprotein particles (LP). Because LP and EV overlap in size and density, isolating high-purity EVs is a significant challenge. While the current two-step sequential EV isolation process using size-expression chromatography (SEC) followed by a density gradient (DG) achieves high purity, the time-consuming ultracentrifugation (UC) step in DG hinders workflow efficiency. This paper introduces an optimized magnetic bead reagent, LipoMin, functionalized with glycosaminoglycans (GAGs), as a rapid alternative for LP removal during the second-step process in about 10 minutes. We evaluated LipoMin's efficacy on two sample types: (a) EV fractions isolated by size exclusion chromatography (SEC + LipoMin) and (b) the pellet obtained from ultracentrifugation (UC + LipoMin). The workflow is remarkably simple, involving a 10 min incubation with LipoMin followed by magnetic separation of the LP-depleted EV-containing supernatant. Results from enzyme-linked immunosorbent assay (ELISA) revealed that LipoMin removes 98.2% ApoB from SEC EV fractions, comparable to the LP removal ability of DG in the SEC + DG two-step process. Importantly, the EV yield (CD81 ELISA) remained at 93.0% and Western blot analysis confirmed that key EV markers, flotillin and CD81, were not compromised. Recombinant EV (rEV), an EV reference standard, was spiked into SEC EV fractions and recovered 89% of CD81 protein. For UC + LipoMin, ApoA1 decreased by 76.5% while retaining 90.7% of CD81. Notably, both colorectal cancer (CRC) and Alzheimer's disease (AD) samples processed by SEC + LipoMin and UC + LipoMin displayed clear expression of relevant EV and clinical markers. With a 10 min workflow (resulting in a 96% time saving compared to the traditional method), the LipoMin reagent offers a rapid and efficient alternative to DG for LP depletion, paving the way for a streamlined SEC + LipoMin two-step EV isolation process. Show less
📄 PDF DOI: 10.1021/acsami.4c03869
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Wei Li, Hu Li, Cheng Zha +4 more · 2024 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Previous observational studies have reported a possible association between circulating lipids and lipid-lowering drugs and male infertility (MIF), as well as the mediating role of circulating vitamin Show more
Previous observational studies have reported a possible association between circulating lipids and lipid-lowering drugs and male infertility (MIF), as well as the mediating role of circulating vitamin D. Then, due to issues such as bias, reverse causality, and residual confounding, inferring causal relationships from these studies may be challenging. Therefore, this study aims to explore the effects of circulating lipids and lipid-lowering drugs on MIF through Mendelian randomization (MR) analysis and evaluate the mediating role of vitamin D. Genetic variations related to lipid traits and the lipid-lowering effect of lipid modification targets are extracted from the Global Alliance for Lipid Genetics Genome-Wide Association Study. The summary statistics for MIF are from the FinnGen 9th edition. Using quantitative expression feature loci data from relevant organizations to obtain genetic variations related to gene expression level, further to explore the relationship between these target gene expression levels and MIF risk. Two-step MR analysis is used to explore the mediating role of vitamin D. Multiple sensitivity analysis methods (co-localization analysis, Egger intercept test, Cochrane's Q test, pleiotropy residuals and outliers (MR-PRESSO), and the leave-one-out method) are used to demonstrate the reliability of our results. In our study, we observed that lipid modification of four lipid-lowering drug targets was associated with MIF risk, the LDLR activator (equivalent to a 1-SD decrease in LDL-C) (OR=1.94, 95% CI 1.14-3.28, FDR=0.040), LPL activator (equivalent to a 1-SD decrease in TG) (OR=1.86, 95% CI 1.25-2.76, FDR=0.022), and CETP inhibitor (equivalent to a 1-SD increase in HDL-C) (OR=1.28, 95% CI 1.07-1.53, FDR=0.035) were associated with a higher risk of MIF. The HMGCR inhibitor (equivalent to a 1-SD decrease in LDL-C) was associated with a lower risk of MIF (OR=0.38, 95% CI 0.17-0.83, FDR=0.39). Lipid-modifying effects of three targets were partially mediated by serum vitamin D levels. Mediation was 0.035 (LDLR activator), 0.012 (LPL activator), and 0.030 (CETP inhibitor), with mediation ratios of 5.34% (LDLR activator), 1.94% (LPL activator), and 12.2% (CETP inhibitor), respectively. In addition, there was no evidence that lipid properties and lipid modification effects of six other lipid-lowering drug targets were associated with MIF risk. Multiple sensitivity analysis methods revealed insignificant evidence of bias arising from pleiotropy or genetic confounding. This study did not support lipid traits (LDL-C, HDL-C, TG, Apo-A1, and Apo-B) as pathogenic risk factors for MIF. It emphasized that LPL, LDLR, CETP, and HMGCR were promising drug targets for improving male fertility. Show less
📄 PDF DOI: 10.3389/fendo.2024.1392533
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Xingkui Tang, Yi Yang, Wenxu Peng +5 more · 2024 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Platycodin D (PD) has been reported to treat metabolic diseases, including non-alcoholic fatty liver disease. In addition, platycodin D has been reported to activate intestinal 5'AMP-activated protein Show more
Platycodin D (PD) has been reported to treat metabolic diseases, including non-alcoholic fatty liver disease. In addition, platycodin D has been reported to activate intestinal 5'AMP-activated protein kinase (AMPK) phosphorylation levels, thereby reducing lipid absorption. Therefore, the aim of this study is to explore whether PD activation of intestinal AMPK and reduced lipid absorption can improve non-alcoholic fatty liver disease. Clean-grade male C57/BL mice were fed a high-fat diet (HFD) (containing 60% calories) for 16 weeks, and oral PD (10 mg/kg/day) was administered at the same time. The liver and intestines were the collected, and the intestines were tested. The expressions of lipid absorption genes (CD36, NPC1L1, and ApoB), the serum total triglyceride (TG) and total cholesterol (TC) levels in the intestines and livers, the fecal free fatty acid (FFA) levels, and the expression of AMPK phosphorylated proteins in the intestines were examined using Western blot analyses. The lipid distribution in the livers, intestines, and fat was detected using Oil Red O and hematoxylin and eosin (H&E) staining. A colon cancer cell line (Caco2) was used to confirm the effect of PD on the cellular lipid uptake PD had a very significant therapeutic or preventive effect on metabolic syndrome and fatty liver induced by a high-fat diet. PD improved body weight, insulin sensitivity, and glucose tolerance in mice fed a high-fat diet and also prevented non-alcoholic fatty liver disease, reduced blood lipid levels, and increased fecal lipid excretion. In addition, PD reduced lipid absorption by activating the intestinal AMPK protein, which may have involved the inhibition of the gene expression levels of intestinal lipid absorption genes (CD36, NPC1L1, and ApoB). The combined effect of these factors improved hepatic lipid accumulation and lipid accumulation in adipose tissue. It was further found that PD also improved the body weights and blood lipid levels of leptin-deficient mice (OB) mice. PD had a very strong therapeutic effect on mice under a high-fat diet. PD reduced high-fat diet-induced obesity and non-alcoholic fatty liver disease by inhibiting intestinal fat absorption. Show less
📄 PDF DOI: 10.3389/fphar.2024.1412453
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Xingcheng Li, Jing Xu · 2024 · Heliyon · Elsevier · added 2026-04-24
To investigate the correlation of apolipoprotein B/A1 (Apo B/A1) ratio with hemodynamics and degree of hearing impairment in elderly patients with sudden sensorineural hearing loss (SSNHL). A total of Show more
To investigate the correlation of apolipoprotein B/A1 (Apo B/A1) ratio with hemodynamics and degree of hearing impairment in elderly patients with sudden sensorineural hearing loss (SSNHL). A total of 82 elderly patients with SSNHL diagnosed and treated in our hospital from July 2019 to September 2022 were retrospectively selected as the research group. The patients were divided into the mild group (22 cases), the moderate group (45 cases), and the severe group (15 cases) according to the degree of hearing impairment. 82 elderly people who underwent physical examination in our hospital during the same period were selected as the control group. The ApoB/A1 ratio and hemodynamic [whole blood low-shear viscosity (LSV), whole blood high-shear viscosity (HSV) and plasma viscosity (PV)] were measured in the two groups. The correlation of ApoB/A1 ratio with hemodynamics and degree of hearing impairment was analyzed. The predictive value of ApoB/A1 ratio and hemodynamics for the severity of SSNHL in elderly patients was analyzed. Compared with the control group, the ApoB/A1 ratio, and the levels of LSV, HSV and PV were higher in the research group ( The contents of ApoB/A1, HSV, LSV and PV were significantly increased in elderly patients with SSNHL, and their levels are significantly related to the degree of hearing impairment. The combined detection has high value in evaluating the severity of the disease. Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e34100
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Yufeng Jin, Xin Wang, Ke Chen +10 more · 2024 · Lipids in health and disease · BioMed Central · added 2026-04-24
Despite centuries of traditional use of silymarin for hepatoprotection, current randomized controlled trial (RCT) studies on the effectiveness of silymarin in managing metabolic dysfunction-associated Show more
Despite centuries of traditional use of silymarin for hepatoprotection, current randomized controlled trial (RCT) studies on the effectiveness of silymarin in managing metabolic dysfunction-associated steatotic liver disease (MASLD) are limited and inconclusive, particularly when it is administered alone. The low bioavailability of silymarin highlights the possible influence of gut microbiota on the effectiveness of silymarin; however, no human studies have investigated this aspect. To determine the potential efficacy of silymarin in improving MASLD indicators and to investigate the underlying mechanisms related to gut microbiota. In this 24-week randomized, double-blind, placebo-controlled trial, 83 patients with MASLD were randomized to either placebo (n = 41) or silymarin (103.2 mg/d, n = 42). At 0, 12, and 24 weeks, liver stiffness and hepatic steatosis were assessed using FibroScan, and blood samples were gathered for biochemical detection, while faecal samples were collected at 0 and 24 weeks for 16S rRNA sequencing. Silymarin supplementation significantly reduced liver stiffness (LSM, -0.21 ± 0.17 vs. 0.41 ± 0.17, P = 0.015) and serum levels of γ-glutamyl transpeptidase (GGT, -8.21 ± 3.01 vs. 1.23 ± 3.16, P = 0.042) and ApoB (-0.02 ± 0.03 vs. 0.07 ± 0.03, P = 0.023) but had no significant effect on the controlled attenuation parameter (CAP), other biochemical indicators (aminotransferases, total bilirubin, glucose and lipid parameters, hsCRP, SOD, and UA), physical measurements (DBP, SBP, BMI, WHR, BF%, and BMR), or APRI and FIB-4 indices. Gut microbiota analysis revealed increased species diversity and enrichment of Oscillospiraceae in the silymarin group. These findings suggest that silymarin supplementation could improve liver stiffness in MASLD patients, possibly by modulating the gut microbiota. The trial was registered at the Chinese Clinical Trial Registry (ChiCTR2200059043). Show less
📄 PDF DOI: 10.1186/s12944-024-02220-y
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Zhenqiu Liu, Huangbo Yuan, Yunzhi Wang +5 more · 2024 · Journal of proteome research · ACS Publications · added 2026-04-24
Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint pot Show more
Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint potential biomarkers. In this nested case-control study, we applied liquid chromatography-tandem mass spectrometry for proteome profiling in baseline plasma samples. Differential protein expression was determined and was subjected to functional enrichment, network, and Mendelian randomization (MR) analyses. We identified 193 proteins with notable differential levels between the groups. Of these proteins, MR analysis offered a compelling negative association between apolipoprotein B (APOB) and liver cancer. This association was further corroborated in the UK Biobank cohort: genetically predicted APOB levels were associated with a 31% (95% CI 19-42%) decreased risk of liver cancer; and phenotypic analysis indicated an 11% (95% CI 8-14%) decreased liver cancer risk for every 0.1 g/L increase of circulating APOB levels. Multivariable MR analysis suggested that the hepatic fat content might fully mediate the APOB-liver cancer connection. In summary, we identified some plasma proteins, particularly APOB, as potential biomarkers of liver cancer. Our findings underscore the intricate link between lipid metabolism and liver cancer, offering hints for targeted prophylactic strategies and early detection. Show less
no PDF DOI: 10.1021/acs.jproteome.4c00397
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Chunshuai Wu, Jiajia Chen, Jinlong Zhang +7 more · 2024 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Spinal cord injury (SCI) patients have an increased susceptibility to coronary heart disease (CHD) due to dysregulated lipid deposition. We conducted a comprehensive investigation to gain insights int Show more
Spinal cord injury (SCI) patients have an increased susceptibility to coronary heart disease (CHD) due to dysregulated lipid deposition. We conducted a comprehensive investigation to gain insights into the specific roles of Apolipoprotein B-100 (APOB-100) in the development of CHD in patients suffering from SCI. First, we established an SCI rat model through semitransection. APOB-100 expression in plasma exosomes obtained from patients were determined. Subsequently, we found APOB-100 affected macrophage polarization when treating co-cultured neurons/macrophages lacking Sortilin with extracellular vesicles derived from SCI rats, where APOB-100 co-immunoprecipitated with Sortilin. Moreover, APOB-100 upregulation reduced neuronal cell viability and triggered apoptosis by upregulating Sortilin, leading to a decline in the Basso, Beattie, and Bresnahan (BBB) scale, exacerbation of neuron injury, increased macrophage infiltration, and elevated blood lipid-related indicators in SCI rats, which could be reversed by silencing Sortilin. In conclusion, APOB-100 from post-SCI patients' extracellular vesicles upregulates Sortilin, thereby endangering those patients to CHD. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.134330
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Jun Yi Liu, Yan Zhi Yi, Qi Wei Guo +10 more · 2024 · Lipids in health and disease · BioMed Central · added 2026-04-24
Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) poly Show more
Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) polymorphisms at angiotensin-converting enzyme gene (ACE) and T/C polymorphisms in the angiotensin type 1 receptor gene (AGTR1) are related to diabetes and lipid levels, but the associations are controversial. Thus, the current research aimed to explore the effects of ACE I/D, AGTR1 rs5182 and diabetes mellitus on serum lipid profiles in 385 Chinese participants with an average age of 75.01 years. The ACE I/D variant was identified using the polymerase chain reaction (PCR) method, whereas the AGTR1 rs5182 polymorphism was identified using the PCR-based restriction fragment length polymorphism (PCR-RFLP) method and verified with DNA sequencing. Total cholesterol (TC), triglyceride (TG), apolipoprotein A (ApoA), apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured using routine methods, and the lipid ratios were calculated. ACE I/D, but not AGTR1 rs5182, was a predictor of TG/HDL-C for the whole study population. Both ACE I/D and AGTR1 rs5182 were predictors of HDL-C and LDL-C levels in females but not in males. Moreover, in females, diabetes mellitus and ACE I/D were identified as predictors of TG and TG/HDL-C, whereas AGTR1 rs5182 and diabetes mellitus were predictors of TG/HDL-C. Moreover, diabetes mellitus and the combination of ACE I/D and AGTR1 rs5182 variations were predictors of TG and TG/HDL-C exclusively in females. The results demonstrated the potential for gender-dependent interactions of ACE I/D, AGTR1 rs5182, and diabetes on lipid profiles. These findings may serve as an additional explanation for the inconsistent changes of blood lipids in individuals with diabetes mellitus, thereby offering a novel perspective for the clinical management of blood lipid levels in diabetic patients. Show less
📄 PDF DOI: 10.1186/s12944-024-02222-w
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Shajidan Abudureyimu, Chunhui He, Dilihumaer Abulaiti +8 more · 2024 · Reviews in cardiovascular medicine · added 2026-04-24
This study aims to investigate the association between nine tag single nucleotide polymorphisms (SNPs) in the A case-control study was conducted to investigate the association between CAD and Results Show more
This study aims to investigate the association between nine tag single nucleotide polymorphisms (SNPs) in the A case-control study was conducted to investigate the association between CAD and Results of the polymorphism study indicated that the The Show less
📄 PDF DOI: 10.31083/j.rcm2504147
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Xingyan Xu, Suping Luo, Jie Lin +11 more · 2024 · BMC pregnancy and childbirth · BioMed Central · added 2026-04-24
Unfavourable lipid and glucose levels may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, there is a lack of prospective studies on the relationship between li Show more
Unfavourable lipid and glucose levels may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, there is a lack of prospective studies on the relationship between lipid profiles, lipid ratios and GDM during pregnancy. To prospectively investigate the relationship between lipid profile and lipid ratios in early and mid-pregnancy and their pattern of change from early to mid-pregnancy and the risk of GDM. This nested case-control study was based on maternal and child healthcare hospitals from Fujian Province, China. We included pregnant women who delivered in the hospital from January 2021 to June 2023. Lipid profiles (TC, TG, ApoA1, ApoB, HDL-c, LDL-c) and fasting glucose were measured before 14 weeks of gestation and between 20 and 28 weeks of gestation, and lipid ratios (triglyceride glucose index, TG/HDL-c and TC/HDL-c) was constructed. Logistic regression was used to assess the relationship between lipid profile, lipid ratios and GDM. Of 1586 pregnant women, 741 were diagnosed with GDM. After adjusting for potential confounders, TG, ApoA1, ApoB, LDL-c, triglyceride glucose index, TG/HDL-c, and TC/HDL-c in early pregnancy were positively associated with the risk of GDM (odds ratios [95% CI] for extreme interquartile comparisons were 2.040 (1.468-2.843), 1.506 (1.091-2.082), 1.529 (1.110-2.107), 1.504 (1.086-2.086), 1.952 (1.398-2.731), 2.127 (1.526-2.971), and 2.370 (1.700-3.312), all trend P < 0.05). HDL-c was negatively associated with the risk of GDM (0.639: 0.459-0.889, trend P all less than 0.05). Similarly, in mid-pregnancy, lower levels of HDL-c, higher levels of triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio were associated with increased risk of GDM (all trends P < 0.05). Stably high levels (both ≥ median for early and mid-pregnancy) of triglyceride glucose index, TG/HDL-c and TC/HDL-c were associated with increased risk of GDM (OR [95% CI]: 2.369 (1.438-3.940), 1.588 (1.077-2.341), 1.921 (1.309-2.829), respectively). The opposite was true for HDL-c, where stable high levels were negatively associated with GDM risk (OR [95% CI]: 0.599 (0.405-0.883)). Increases in triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio in early and mid-pregnancy, as well as their stable high levels from early to mid-pregnancy, are associated with a higher risk of GDM. In contrast, increased levels of HDL-c, both in early and mid-pregnancy, and their stable high levels from early to mid-pregnancy were associated with a lower risk of GDM. That highlighted their possible clinical relevance in identifying those at high risk of GDM. Show less
📄 PDF DOI: 10.1186/s12884-024-06692-9
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Cheng Zhang, Li Li, Jiali Lin +3 more · 2024 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Colorectal cancer is one of the most common types of cancer worldwide that can lead to serious injury and death. Although polysaccharides are widely recognized as having antitumor activity, there has Show more
Colorectal cancer is one of the most common types of cancer worldwide that can lead to serious injury and death. Although polysaccharides are widely recognized as having antitumor activity, there has been little research on the role of barley polysaccharides (BP) Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.133820
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