👤 Guodong Huang

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Also published as: Ai-Chun Huang, Ai-long Huang, Aijie Huang, Ailong Huang, Aimin Huang, Alden Y Huang, An-Fang Huang, Annie Huang, Aohuan Huang, Ariane Huang, Baihai Huang, Baisong Huang, Bao-Hua Huang, Bao-Yi Huang, Baoqin Huang, Baoying Huang, Benjamin J Huang, Benlin Huang, Bevan E Huang, Bi Huang, Biao Huang, Bin Huang, Binfang Huang, Bing Huang, Bingcang Huang, Bingkun Huang, Bizhi Huang, Bo Huang, Bo-Shih Huang, Bor-Ren Huang, Bowen Huang, Boyue Huang, C Y Huang, Caihong Huang, Caiyun Huang, Can Huang, Canhua Huang, Caoxin Huang, Cathelin Huang, Catherine Huang, Chang Ming Huang, Chang X Huang, Chang-Jen Huang, Changjiang Huang, Chao Huang, Chao Wei Huang, Chao-Wei Huang, Chao-Yuan Huang, Chaolin Huang, Chaoqun Huang, Chaowang Huang, Chaoyang Huang, Chen Huang, Chen-Na Huang, Chen-Ping Huang, Cheng Huang, Chengcheng Huang, Chengrui Huang, Chenshen Huang, Chenxiao Huang, Chi-Cheng Huang, Chi-Shuan Huang, Chia-Chang Huang, Chia-Wei Huang, Chieh-Cheng Huang, Chieh-Liang Huang, Chien-Hsun Huang, Chih-Chun Huang, Chih-Hsiang Huang, Chih-Jen Huang, Chih-Ting Huang, Chih-Yang Huang, Chin-Chang Huang, Chin-Chou Huang, Ching-Shan Huang, Ching-Shin Huang, Ching-Tang Huang, Ching-Wei Huang, Chiu-Ju Huang, Chiu-Jung Huang, Chiun-Sheng Huang, Chong Huang, Chongbiao Huang, Christine S Huang, Chuan Huang, Chuanbing Huang, Chuanhong Huang, Chuanjiang Huang, Chuanjun Huang, Chuansheng Huang, Chuiguo Huang, Chun Huang, Chun-Mei Huang, Chun-Yao Huang, Chun-Yin Huang, Chunfan Huang, Chung-Hsiung Huang, Chunhong Huang, Chunjian Huang, Chunkai Huang, Chunlan Huang, Chunling Huang, Chunshuai Huang, Chunxia Huang, Chunyao Huang, Chunyi Huang, Chunying Huang, Chunyu Huang, Chuxin Huang, Chuying Huang, Congcong Huang, Cuiyu Huang, Da Huang, Dajun Huang, Dan Huang, Dane Huang, Danqing Huang, Dantong Huang, David Huang, David J Huang, De Huang, De-Jun Huang, Dejia Huang, Dengjun Huang, Dianhua Huang, Dishu Huang, Dong Huang, Donglan Huang, Dongmei Huang, Dongni Huang, Dongqin Huang, Dongqing Huang, Dongsheng Huang, Dongyu Huang, Du-Juan Huang, Emily C Huang, Enhao Huang, Enping Huang, Eric Huang, Erya Huang, F Huang, Fan Huang, Fang Huang, Fang-Ling Huang, Fangling Huang, Fei Huang, Fei Wan Huang, Feiruo Huang, Feiteng Huang, Feizhou Huang, Feng Huang, Fengxian Huang, Fengyu Huang, Franklin W Huang, Fu-Chen Huang, Fu-Mei Huang, Fubiao Huang, Fude Huang, Fuhao Huang, Furong Huang, G Huang, Gairong Huang, Gang Huang, Gao-Zhong Huang, Gaoxingyu Huang, Ge Huang, Guang-Jian Huang, Guang-Yun Huang, Guangjian Huang, Guangming Huang, Guangqian Huang, Guangrui Huang, Guanhong Huang, Guanling Huang, Guanning Huang, Guanqun Huang, Guanrong Huang, Guicheng Huang, Guohong Huang, Guoping Huang, Guoqian Huang, Guowei Huang, Guoxing Huang, Guoying Huang, Guoyong Huang, Guoyuan Huang, H Huang, H S Huang, Hai Huang, Haigang Huang, Haihong Huang, Hailin Huang, Haimiao Huang, Haixin Huang, Haiyan Huang, Han-Chang Huang, Hanxia Huang, Hao Huang, Hao-Fei Huang, Haobo Huang, Haochu Huang, Haomin Huang, Haoyu Huang, Haoyue Huang, Haozhang Huang, Haozhong Huang, He Huang, Hefeng Huang, Heguang Huang, Helen Huang, Heming Huang, Hengbin Huang, Heqing Huang, Hete Huang, Hong Huang, Hongbiao Huang, Hongcan Huang, Hongda Huang, Hongfei Huang, Hongfeng Huang, Honghui Huang, Hongou Huang, Hongqiang Huang, Hongyan Huang, Hongyang Huang, Hongyi Huang, Hongying Huang, Hongyu Huang, Hongyun Huang, Hsi-Yuan Huang, Hsien-Da Huang, Hsing-Yen Huang, Hsu Chih Huang, Hsuan-Cheng Huang, Hsuan-Ying Huang, Hu Huang, Hua Huang, Huafei Huang, Huaju Huang, Huan Huang, Huanhuan Huang, Huanliang Huang, Huapin Huang, Huashan Huang, Huayun Huang, Hui Huang, Hui-Huang Huang, Hui-Kuang Huang, Hui-Yu Huang, Huibin Huang, Huifen Huang, Huiling Huang, Huimin Huang, Huina Huang, Huiqiao Huang, Huixian Huang, Huixin Huang, Huiyan Huang, Huiyu Huang, Huizhe Huang, Huizhen Huang, Hy Huang, I-Chieh Huang, J V Huang, Janice J Huang, Jasmin Huang, Jeffrey K Huang, Jia Huang, Jia-Jia Huang, Jiaan Huang, Jiahui Huang, Jiajin Huang, Jiajun Huang, Jian Huang, Jian-Dong Huang, Jiana Huang, Jianbiao Huang, Jianbing Huang, Jianfang Huang, Jianfeng Huang, Jiangfeng Huang, Jiangtao Huang, Jiangwei Huang, Jianhua Huang, Jianlu Huang, Jianmin Huang, Jianming Huang, Jiansheng Huang, Jianzhen Huang, Jiao-Qian Huang, Jiaoti Huang, Jiaotian Huang, Jiaqi Huang, Jiawen Huang, Jiaxing Huang, Jiayu Huang, Jiayue Huang, Jie Huang, Jie Qi Huang, Jiechun Huang, Jieli Huang, Jieling Huang, Jieping Huang, Jin Huang, Jin-Di Huang, Jin-Feng Huang, Jin-Hong Huang, Jin-Yan Huang, Jinbao Huang, Jinfang Huang, Jing Huang, Jing-Fei Huang, Jingang Huang, Jinghan Huang, Jingjing Huang, Jingkun Huang, Jinglong Huang, Jingtao Huang, Jingxian Huang, Jingyong Huang, Jingyuan Huang, Jingyue Huang, Jinhua Huang, Jinling Huang, Jinlu Huang, Jinshu Huang, Jinxing Huang, Jinyan Huang, Jinzhou Huang, Jiuhong Huang, Jiyu Huang, Ju Huang, Juan Huang, Jucun Huang, Jun Huang, Jun-Hua Huang, Jun-You Huang, Junhao Huang, Junhua Huang, Junjie Huang, Junming Huang, Junning Huang, Junqi Huang, Junwen Huang, Junyuan Huang, Junyun Huang, Juxiang Huang, K Huang, K N Huang, Kai Huang, Kaipeng Huang, Kang Huang, Kangbo Huang, Kate Huang, Katherine Huang, Ke Huang, Ke-Ke Huang, Ke-Pu Huang, Kevin Huang, Kevin Y Huang, Kuan-Chun Huang, Kui-Yuan Huang, Kuiyuan Huang, Kun Huang, Kuo-Hsiang Huang, Kuo-Hung Huang, L Huang, L-B Huang, Laiqiang Huang, Lan Huang, Lanlan Huang, Lei Huang, Leijuan Huang, Li Huang, Li-Hao Huang, Li-Jiang Huang, Li-Juan Huang, Li-Jun Huang, Li-Ping Huang, Li-Rung Huang, Li-Wei Huang, Li-Yun Huang, Lian Huang, Liang Huang, Liang-Yu Huang, Liangchong Huang, Lianggui Huang, Libin Huang, Lige Huang, Lihua Huang, Lijia Huang, Lijiang Huang, Lijuan Huang, Lijun Huang, Lili Huang, Limin Huang, Liming Huang, Lin Huang, Linchen Huang, Ling Huang, Ling-Chun Huang, Ling-Jin Huang, Lingling Huang, Lining Huang, Linjing Huang, Linsheng Huang, Linxue Huang, Linyuan Huang, Liping Huang, Liqiong Huang, Lixia Huang, Lixiang Huang, Lixuan Huang, Lixue Huang, Lizhen Huang, Longfei Huang, Lu Huang, Lu-Jie Huang, Lu-Qi Huang, Luanluan Huang, Luqi Huang, Luyang Huang, Luyao Huang, Lvzhen Huang, M C Huang, Man Huang, Manning Y Huang, Manyun Huang, Mao-Mao Huang, Mei Huang, Meihua Huang, Meina Huang, Meixiang Huang, Melissa Y Huang, Meng-Chuan Huang, Meng-Fan Huang, Meng-Na Huang, MengQian Huang, Menghao Huang, Mengjie Huang, Mengjun Huang, Mengnan Huang, Mengting Huang, Mengzhen Huang, Mia L Huang, Miao Huang, Min Huang, Ming-Lu Huang, Ming-Shyan Huang, Mingjian Huang, Mingjun Huang, Minglei Huang, Mingrui Huang, Mingwei Huang, Mingxuan Huang, Mingyu Huang, Mingyuan Huang, Minjun Huang, Minqi Huang, Minxuan Huang, Minyuan Huang, N Huang, Na Huang, Nian Huang, Nianyuan Huang, Ning-Na Huang, Ning-Ping Huang, Ninghao Huang, Nongyu Huang, Pan Huang, Pang-Shuo Huang, Paul L Huang, Pei Huang, Pei-Chi Huang, Pei-Ying Huang, Peiying Huang, Peng Huang, Peng-Fei Huang, Pengyu Huang, Piao-Piao Huang, Piaopiao Huang, Pin-Rui Huang, Ping Huang, Pingping Huang, Pintong Huang, Po-Hsun Huang, Po-Jung Huang, Poyao Huang, Qi Huang, Qi-Tao Huang, Qian Huang, Qiang Huang, Qianqian Huang, Qiaobing Huang, Qibin Huang, Qidi Huang, Qin Huang, Qing Huang, Qing-yong Huang, Qingjiang Huang, Qingke Huang, Qingling Huang, Qingqing Huang, Qingsong Huang, Qingxia Huang, Qingxing Huang, Qingyu Huang, Qingzhi Huang, Qinlou Huang, Qiong Huang, Qiubo Huang, Qiumin Huang, Qiuming Huang, Qiuru Huang, Qiuyin Huang, Qiuyue Huang, Qizhen Huang, Quanfang Huang, Qun Huang, R H Huang, R Stephanie Huang, Rae-Chi Huang, Ran Huang, Renbin Huang, Renhua Huang, Renli Huang, Richard Huang, Richard S P Huang, Riqing Huang, Ritai Huang, Robert J Huang, Rong Huang, Rong Stephanie Huang, Ronghua Huang, Ronghui Huang, Rongjie Huang, Rongrong Huang, Rongxiang Huang, Ru-Ting Huang, Ruby Yun-Ju Huang, Rui Huang, Ruihua Huang, Ruijin Huang, Ruina Huang, Ruiyan Huang, Ruizhen Huang, Runyue Huang, Ruo-Hui Huang, S Huang, S Y Huang, S Z Huang, Saisai Huang, San-Yuan Huang, See-Chang Huang, Sen Huang, Serina Huang, Shan Huang, Shang-Ming Huang, Shanhe Huang, Shanshan Huang, Shaojun Huang, Shaoxin Huang, Shaoze Huang, Shau Ku Huang, Shau-Ku Huang, Shenan Huang, Sheng-He Huang, Shengfeng Huang, Shengjie Huang, Shengnan Huang, Shengyan Huang, Shengyun Huang, Shi-Feng Huang, Shi-Shi Huang, Shi-Ying Huang, Shiang-Suo Huang, Shichao Huang, Shih-Chiang Huang, Shih-Wei Huang, Shih-Yi Huang, Shihao Huang, Shijing Huang, Shilu Huang, Shixia Huang, Shiya Huang, Shiying Huang, Shiyun Huang, Shoucheng Huang, Shu Huang, Shu-Pang Huang, Shu-Pin Huang, Shu-Qiong Huang, Shu-Wei Huang, Shu-Yi Huang, Shu-ying Huang, Shuai Huang, Shuang Huang, Shungen Huang, Shuo Huang, Shushu Huang, Shutong Huang, Shuwen Huang, Si-Yang Huang, Sidong Huang, Sihua Huang, Sijia Huang, Sinchun Huang, Sisi Huang, Sixiu Huang, Song Bin Huang, Song-Mei Huang, Songmei Huang, Songming Huang, Songqian Huang, Steven Huang, Steven Kuan-Hua Huang, Suli Huang, Sung-Ying Huang, Susan M Huang, Suwen Huang, Taiqi Huang, Tang-Hsiu Huang, Tao Huang, Te-Hsuan Huang, Tengda Huang, Tengfei Huang, Tian Hao Huang, Tianhao Huang, Tianpu Huang, Tiantian Huang, Tieqiu Huang, Tim H Huang, Ting Huang, Tinghua Huang, Tingping Huang, Tingqin Huang, Tingting Huang, Tingxuan Huang, Tingyun Huang, Tong Huang, Tongsheng Huang, Tongtong Huang, Tony T Huang, Tse-Shun Huang, Tseng-Yu Huang, Tsung-Wei Huang, Tzu-Rung Huang, Wan-Ping Huang, Way-Ren Huang, Wei Huang, Wei-Chi Huang, Weibin Huang, Weicheng Huang, Weifeng Huang, Weihua Huang, Weijun Huang, Weiqi Huang, Weisu Huang, Weiwei Huang, Weixue Huang, Weizhen Huang, Wen Huang, Wen-yu Huang, Wenbin Huang, Wenda Huang, Wenfang Huang, Wenfeng Huang, Wenhua Huang, Wenji Huang, Wenjie Huang, Wenjun Huang, Wenqiao Huang, Wenqing Huang, Wenqiong Huang, Wenshan Huang, Wentao Huang, Wenxin Huang, Wenya Huang, Wenying Huang, Wunan Huang, Wuqing Huang, X F Huang, X Huang, Xi Huang, Xian-sheng HUANG, Xiang Huang, Xianghua Huang, Xianglong Huang, Xiangming Huang, Xianping Huang, Xianqing Huang, Xiansheng Huang, Xianwei Huang, Xianxi Huang, Xianxian Huang, Xianying Huang, Xianzhang Huang, Xiao Huang, Xiao-Fang Huang, Xiao-Fei Huang, Xiao-Ming Huang, Xiao-Song Huang, Xiao-Yan Huang, Xiao-Yong Huang, Xiao-Yu Huang, XiaoFang Huang, Xiaochun Huang, Xiaofei Huang, Xiaofeng Huang, Xiaohong Huang, Xiaohua Huang, Xiaojie Huang, Xiaojing Huang, Xiaojuan Huang, Xiaolan Huang, Xiaoli Huang, Xiaolin Huang, Xiaoman Huang, Xiaomin Huang, Xiaoqing Huang, Xiaoshuai Huang, Xiaowen Huang, Xiaowu Huang, Xiaoxia Huang, Xiaoyan Huang, Xiaoying Huang, Xiaoyu Huang, Xiaoyuan Huang, Xiaoyun Huang, Xiaozhun Huang, Xiayang Huang, Xichang Huang, Xie-Lin Huang, Xin Huang, Xin-Di Huang, Xinen Huang, Xinfeng Huang, Xingguo Huang, Xingming Huang, Xingqin Huang, Xingru Huang, Xingxu Huang, Xingya Huang, Xingzhen Huang, Xinwen Huang, Xinyi Huang, Xinying Huang, Xinyue Huang, Xinzhu Huang, Xiongfeng Huang, Xionggao Huang, Xiuju Huang, Xiuyun Huang, Xiuzhen Huang, Xiwen Huang, Xu Huang, Xu-Feng Huang, Xuan Huang, Xuanzhang Huang, Xucong Huang, Xudong Huang, Xue-Ying Huang, Xue-shuang Huang, Xuehong Huang, Xuejie Huang, Xuejing Huang, Xuejun Huang, Xuemei Huang, Xueming Huang, Xueqi Huang, Xuewei Huang, Xuezhe Huang, Xuhui Huang, Xuliang Huang, Xun Huang, Xuxiong Huang, Y Huang, Y Joyce Huang, Y S Huang, Ya-Chih Huang, Ya-Dong Huang, Ya-Fang Huang, Ya-Ru Huang, Yabo Huang, Yadong Huang, Yafang Huang, Yajiao Huang, Yajuan Huang, Yali Huang, Yamei Huang, Yan Huang, Yan-Lin Huang, Yan-Qing Huang, Yan-Ting Huang, Yang Huang, Yang Zhong Huang, Yangqing Huang, Yangyang Huang, Yanhao Huang, Yani Huang, Yanjun Huang, Yanlong Huang, Yanna Huang, Yanping Huang, Yanqin Huang, Yanqing Huang, Yanqun Huang, Yanru Huang, Yanshan Huang, Yansheng Huang, Yanxia Huang, Yanyan Huang, Yanyao Huang, Yao Huang, Yao-Kuang Huang, Yaowei Huang, Yatian Huang, Yating Huang, Ye Huang, Yechao Huang, Yen-Chu Huang, Yen-Ning Huang, Yen-Tsung Huang, Yeqing Huang, Yewei Huang, Yi Huang, Yi-Chun Huang, Yi-Jan Huang, Yi-Jia Huang, Yi-Wen Huang, Yi-ping Huang, Yichao Huang, Yichuan Huang, Yicong Huang, Yifan Huang, Yihao Huang, Yiheng Huang, Yihong Huang, Yikeng Huang, Yilin Huang, Yin Huang, Yin-Tsen Huang, Ying Huang, Ying-Hsuan Huang, Ying-Jung Huang, Ying-Zhi Huang, Yinghua Huang, Yingying Huang, Yingzhen Huang, Yingzhi Huang, Yiping Huang, Yiquan Huang, Yishan Huang, Yiwei Huang, Yixian Huang, Yizhou Huang, Yong Huang, Yong-Fu Huang, Yongbiao Huang, Yongcan Huang, Yongjie Huang, Yongqi Huang, Yongsheng Huang, Yongtong Huang, Yongye Huang, Yongyi Huang, Yongzhen Huang, Youheng Huang, Youyang Huang, Yu Huang, Yu-Ching Huang, Yu-Chu Huang, Yu-Chuen Huang, Yu-Chyi Huang, Yu-Fang Huang, Yu-Han Huang, Yu-Jie Huang, Yu-Lei Huang, Yu-Ren Huang, Yu-Shu Huang, Yu-Ting Huang, Yuan Huang, Yuan-Lan Huang, Yuan-Li Huang, Yuan-Lu Huang, Yuancheng Huang, Yuanpeng Huang, Yuanshuai Huang, Yuanyu Huang, Yuanyuan Huang, Yue Huang, Yue-Hua Huang, Yuedi Huang, Yueh-Hsiang Huang, Yuehong Huang, Yuejun Huang, Yueye Huang, Yuezhen Huang, Yufang Huang, Yufen Huang, Yuguang Huang, Yuh-Chin T Huang, Yuhong Huang, Yuhua Huang, Yuhui Huang, Yujia Huang, Yujie Huang, Yulin Huang, Yumei Huang, Yumeng Huang, Yun Huang, Yun-Juan Huang, Yunchao Huang, Yung-Hsin Huang, Yung-Yu Huang, Yunmao Huang, Yunpeng Huang, Yunru Huang, Yunyan Huang, Yuping Huang, Yuqi Huang, Yuqiang Huang, Yuqiong Huang, Yusi Huang, Yutang Huang, Yuting Huang, Yutong Huang, Yuxian Huang, Yuxin Huang, Yuxuan Huang, Yuyang Huang, Yuying Huang, Z Huang, Z Z Huang, Z-Y Huang, Zebin Huang, Zebo Huang, Zehua Huang, Zeling Huang, Zengwen Huang, Zhang Huang, Zhao Huang, Zhaoxia Huang, Zhe Huang, Zhen Huang, Zhenfei Huang, Zheng Huang, Zheng-Xiang Huang, Zhengwei Huang, Zhengxian Huang, Zhengxiang Huang, Zhengyang Huang, Zhenlin Huang, Zhenrui Huang, Zhenyao Huang, Zhenyi Huang, Zhi Huang, Zhi-Ming Huang, Zhi-Qiang Huang, Zhi-Xin Huang, Zhi-xiang Huang, Zhican Huang, Zhicong Huang, Zhifang Huang, Zhifeng Huang, Zhigang Huang, Zhihong Huang, Zhilin Huang, Zhilong Huang, Zhipeng Huang, Zhiping Huang, Zhiqi Huang, Zhiqiang Huang, Zhiqin Huang, Zhiqing Huang, Zhitong Huang, Zhiwei Huang, Zhixiang Huang, Zhiying Huang, Zhiyong Huang, Zhiyu Huang, Zhongbin Huang, Zhongcheng Huang, Zhongfeng Huang, Zhonglu Huang, Zhouyang Huang, Zi-Xin Huang, Zi-Ye Huang, Zicheng Huang, Zichong Huang, Zihan Huang, Zihao Huang, Ziheng Huang, Ziling Huang, Zini Huang, Zirui Huang, Zizhan Huang, Zongjian Huang, Zongliang Huang, Zunnan Huang, Zuotian Huang, Zuxian Huang, Zuyi Huang
articles
Xingsen Zhao, Chengyi Ma, Qihang Sun +8 more · 2025 · Molecular psychiatry · Nature · added 2026-04-24
Alzheimer's disease (AD) is the most common neurodegenerative disease, and diverse factors contribute to its pathogenesis. Previous studies have suggested the dysregulation of m
📄 PDF DOI: 10.1038/s41380-025-02984-4
BACE1
Ning Li, Ningning Cui, Ibrahim A Bakry +9 more · 2025 · Plant foods for human nutrition (Dordrecht, Netherlands) · Springer · added 2026-04-24
Lead (Pb) exposure poses significant health risks, particularly in neurodegenerative diseases such as Alzheimer's disease (AD). This study investigates the neuroprotective effects of pea peptide (PP4) Show more
Lead (Pb) exposure poses significant health risks, particularly in neurodegenerative diseases such as Alzheimer's disease (AD). This study investigates the neuroprotective effects of pea peptide (PP4) on PC12 cells exposed to Pb. Using Cell Counting Kit-8 (CCK-8), pretreatment with PP4 at 50 and 200 µM concentrations significantly improved cell viability compared to Pb-only treated cells (P < 0.05), indicating a protective effect. Moreover, Pb exposure led to increased Amyloid Precursor Protein (APP) expression at 10 and 20 µM after 24 h (P < 0.05), while β-site amyloid Precursor Protein Cleaving Enzyme 1 (BACE1) levels were elevated across all concentrations tested (P < 0.05). We established that PP4 can mitigate Pb-induced cytotoxicity and reduce the expression of APP and BACE1 by activating the Phosphoinositide 3-kinase / Protein Kinase (PI3K/AKT) signaling pathway. This study highlights the potential of PP4 as a therapeutic agent in preventing neurotoxic damage associated with lead exposure, suggesting a novel approach for the management of AD. Show less
no PDF DOI: 10.1007/s11130-025-01296-w
BACE1
Kuo-Chiang Hsu, Shang-Ming Huang, Jhih-Yi Shen +3 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Alzheimer's Disease (AD) constitutes approximately 70 % of dementia cases and is the most prevalent form of dementia. Current therapeutic options, including acetylcholinesterase inhibitors and N-methy Show more
Alzheimer's Disease (AD) constitutes approximately 70 % of dementia cases and is the most prevalent form of dementia. Current therapeutic options, including acetylcholinesterase inhibitors and N-methyl d-aspartate (NMDA) receptor antagonists, provide symptomatic relief but do not cure the disease and often come with side effects. The primary pathological features of AD are amyloid plaques and neurofibrillary tangles, with amyloid plaques formed by the abnormal accumulation of Amyloid-β (Aβ). BACE1 (β-site APP-cleaving enzyme 1), a β-secretase, is a key initiator in amyloidosis. Previous research has shown that G-Bro hydrolysate, produced from the bromelain hydrolysis of gliadin, has optimal BACE1 inhibitory efficiency. This study employs G-Bro hydrolysate for nano UHPLC-ESI Q-TOF mass spectrometry to identify peptide fragment sequences and conducts BACE1 inhibition assays to isolate the most effective peptide, VR-peptide. Using the N2a/PS/APP cell model, we explored the impact of chemically synthesized VR-peptide on BACE1 protein expression, the secretion of soluble APP (sAPP), and levels of Aβ and intracellular Aβ1-42. Results demonstrate that VR-peptide achieves a BACE1 inhibitory rate of 63.8 % and reduces BACE1 expression by over 90 % in comparison with untreated N2a/PS/APP cells. It shifts the balance between extracellular Aβ monomers and aggregates, favoring monomer formation and decreasing intracellular Aβ1-42 levels by over 56 %, underscoring its neuroprotective potential. In conclusion, VR-peptide exhibits promise as a BACE1 inhibitor and a preventive agent against Alzheimer's disease. Derived from hydrolyzed cereal foods, it could be effectively paired with a suitable drug delivery system for enhanced neuronal penetration, paving the way for neuroprotective peptide products targeting Alzheimer's disease. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.141932
BACE1
Danlei Bi, Hong Bao, Xiaoli Yang +18 more · 2025 · Neuron · Elsevier · added 2026-04-24
Neural hyperexcitability has been clinically associated with amyloid-β (Aβ) pathology and cognitive impairment in Alzheimer's disease (AD). Here, we show that decreased GABA
no PDF DOI: 10.1016/j.neuron.2025.01.030
BACE1
Lou-Yan Ma, Song-Fang Liu, Zheng-Quan Ma +11 more · 2025 · Endocrine journal · added 2026-04-24
Diabetes has been regarded as an independent risk factor for Alzheimer's disease (AD). Liraglutide could improve cognition in AD mouse models, but its precise mechanism remains unclear. In this study, Show more
Diabetes has been regarded as an independent risk factor for Alzheimer's disease (AD). Liraglutide could improve cognition in AD mouse models, but its precise mechanism remains unclear. In this study, we used STZ-induced diabetic rats and HT-22 cells to investigate the effects of liraglutide. The MWM test, MTT assay, ELISA, western blot, and immunofluorescence were used in this research. Diabetic rats induced by STZ displayed a longer escape latency and entered the target zone less frequently (p < 0.05) in the MWM test. Intraperitoneal injection of liraglutide improved the cognition of diabetic rats (p < 0.05) and reduced Aβ42 expression in the hippocampus (p < 0.05). In vivo experiments showed that HT-22 cell viability decreased in the HG group, but liraglutide (100 nmol/L and 1 μmol/L) enhanced HT-22 cell viability (p < 0.05). Oxidative stress markers were upregulated in HT-22 cells in the HG group, while liraglutide treatment significantly reduced these markers (p < 0.05). Western blot and immunofluorescence analyses demonstrated increased levels of Aβ, BACE1, and γ-secretase in HT-22 cells in the HG group (p < 0.05), whereas these levels were reduced in the liraglutide treatment group (p < 0.05). These effects were reversed by the nuclear factor kappa B (NF-κB) and extracellular signal-regulated kinase 1/2 (ERK1/2) inhibitors (p < 0.05). These findings suggest that liraglutide improved the cognition of diabetic rats and might exert its protective effects by reducing oxidative stress, downregulating BACE1 and γ-secretase expression, and decreasing Aβ deposition via the NF-κB and ERK1/2 pathways. Show less
📄 PDF DOI: 10.1507/endocrj.EJ23-0723
BACE1
Huijie Yang, Fangyu Wang, Peijun Zhao +12 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by hyperphosphorylation of tau, neuroinflammation, and amyloid-beta (Aβ) plaques. Lead (Pb) exposure has been linked to an increa Show more
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by hyperphosphorylation of tau, neuroinflammation, and amyloid-beta (Aβ) plaques. Lead (Pb) exposure has been linked to an increased risk of AD and neuroinflammation. The purpose of this study is to determine if black soybean peptide (BSP1) may reduce neuroinflammation caused by Pb and associated AD-like pathology. Pb exposure was given to mouse hippocampus HT22 cells in the presence or absence of BSP1, positive control resveratrol (Rsv), or the SIRT1 inhibitor EX-527. Our findings suggest that BSP1 downregulates the expression of beta-secretase (BACE1) and amyloid precursor protein (APP), inhibits tau phosphorylation, and reduces Aβ1-42 deposition. In addition, BSP1 effectively alleviated Pb-induced neuroinflammation by reducing the phosphorylation of NF-κB and the expression of pro-inflammatory cytokines (IL-1β, TNF-α, NLRP3, and IL-18). BSP1 provides neuroprotective effect via phosphorylating LKB1 and AMPK, inhibiting mTOR signaling, and activating the AMPK/SIRT1 pathway. These results suggest that BSP1 may be therapeutically beneficial for preventing or treating AD by reducing Pb-induced neuroinflammation. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.138404
BACE1
Zhen Zhang, Rongyao Li, Yue Zhou +3 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Growing evidence indicates that healthy diets are associated with a slower progression of Alzheimer's disease (AD). Flavonoids are among the most abundant natural products in diets beneficial to AD, s Show more
Growing evidence indicates that healthy diets are associated with a slower progression of Alzheimer's disease (AD). Flavonoids are among the most abundant natural products in diets beneficial to AD, such as the Mediterranean diet. However, the effect and mechanism of these dietary flavonoids on AD remains incompletely understood. Here, we found that a representative dietary natural flavonoid, chrysin (Chr), significantly ameliorated cognitive impairment and AD pathology in APP/PS1 mice. Furthermore, mechanistic studies showed that Chr significantly reduced the levels of amyloid-β (Aβ) and phosphorylated tau (p-tau), along with dual inhibitory activity against β-site amyloid precursor protein cleaving enzyme 1 (BACE1) and glycogen synthase kinase 3β (GSK3β). Moreover, the effect of Chr was further confirmed by EW233, a structural analog of Chr that exhibited an improved pharmacokinetic profile. To further verify the role of Chr and EW233, we utilized our previously established chimeric human cerebral organoid (chCO) model for AD, in which astrogenesis was promoted to mimic the neuron-astrocyte ratio in human brain tissue, and similar dual inhibition of Aβ and p-tau was also observed. Altogether, our study not only reveals the molecular mechanisms through which dietary flavonoids, such as Chr, mitigate AD pathology, but also suggests that identifying a specific constituent that mimics some of the benefits of these healthy diets could serve as a promising approach to discover new treatments for AD. Show less
📄 PDF DOI: 10.1007/s12035-024-04557-y
BACE1
Hui-Yu Huang, Shu-Ping Tsao, Tu-Hsueh Yeh · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra, resulting in motor symptoms such as bradykines Show more
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra, resulting in motor symptoms such as bradykinesia, tremor, rigidity, and postural instability, as well as a wide variety of non-motor manifestations. Branched-chain amino acids (BCAAs)-leucine, isoleucine, and valine-are essential nutrients involved in neurotransmitter synthesis, energy metabolism, and cellular signaling. Emerging evidence suggests that BCAA metabolism is intricately linked to the pathophysiology of PD. Dysregulation of BCAA levels has been associated with energy metabolism, mitochondrial dysfunction, oxidative stress, neuroinflammation, and altered neurotransmission. Furthermore, the branched-chain ketoacid dehydrogenase kinase (BCKDK), a key regulator of BCAA catabolism, has been implicated in PD through its role in modulating neuronal energetics and redox homeostasis. In this review, we synthesize current molecular, genetic, microbiome, and clinical evidence on BCAA dysregulation in PD to provide an integrative perspective on the BCAA-PD axis and highlight directions for future translational research. We explored the dualistic role of BCAAs as both potential neuroprotective agents and metabolic stressors, and critically examined the therapeutic prospects and limitations of BCAA supplementation and BCKDK targeting. Show less
📄 PDF DOI: 10.3390/ijms26146992
BCKDK
Hao Xiong, Ruiqi Liu, Keke Xu +7 more · 2025 · Journal of translational medicine · BioMed Central · added 2026-04-24
Cancer is one of the major diseases threatening human health in the world. According to the latest global cancer statistics from the International Agency for Research on Cancer (IARC), there were appr Show more
Cancer is one of the major diseases threatening human health in the world. According to the latest global cancer statistics from the International Agency for Research on Cancer (IARC), there were approximately 20 million new cancer cases and 10 million cancer deaths worldwide. Amidst this global health concern, branched chain amino acids have emerged as key players, playing an important role in the occurrence and development of cancer. In certain malignancies like colorectal cancer, the average level of BCAA in tumor tissues is twice that in normal tissues. BCAA metabolism is intricately associated with the progression of multiple tumors and is modulated by diverse enzymes, including BCAT, BCKDH, and BCKDK. The metabolism of BCAA involves multiple enzymes and biochemical processes via signaling pathways such as PI3K/AKT/mTOR and AMPK/mTOR, etc. In addition, mTOR inhibitors show potential value in cancer treatment by regulating the metabolism and signaling pathways of tumor cells, which provides a new direction for anticancer efforts. Simultaneously, BCAAs are closely associated with tumor immunity, including NK cells, CD4 Show less
📄 PDF DOI: 10.1186/s12967-025-06664-3
BCKDK
Haiying Liu, Jiaqian Feng, Tingting Pan +10 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Homologous recombination repair (HRR) is crucial for maintaining genomic stability by repairing DNA damage. Despite its importance, HRR's role in cancer progression is not fully elucidated. Here, this Show more
Homologous recombination repair (HRR) is crucial for maintaining genomic stability by repairing DNA damage. Despite its importance, HRR's role in cancer progression is not fully elucidated. Here, this work shows that nuclear-localized branched-chain α-ketoacid dehydrogenase kinase (BCKDK) acts as a modulator of HRR, promoting cell resistance against DNA damage-inducing therapy in breast cancer. Mechanistically, this work demonstrates that BCKDK is localized in the nucleus and phosphorylates RNF8 at Ser157, preventing the ubiquitin-mediated degradation of RAD51, thereby facilitating HRR-mediated DNA repair under replication stress. Notably, aberrant expression of the BCKDK/p-RNF8/RAD51 axis correlates with breast cancer progression and poor patient survival. Furthermore, this work identifies a small molecule inhibitor of BCKDK, GSK180736A, that disrupts its HRR function and exhibits strong tumor suppression when combined with DNA damage-inducing drugs. Collectively, this study reveals a new role of BCKDK in regulating HRR, independent of its metabolic function, presenting it as a potential therapeutic target and predictive biomarker in breast cancer. Show less
📄 PDF DOI: 10.1002/advs.202416590
BCKDK
Xiong Guo, Chong Huang, Ling Zhang +18 more · 2025 · Circulation · added 2026-04-24
Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining Show more
Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining heart health by draining fluids and immune cells. However, their involvement in HFpEF remains largely unexplored. We examined cardiac lymphatic alterations in mice with HFpEF with comorbid obesity and hypertension, and in heart tissues from patients with HFpEF. Using genetically engineered mouse models and various cellular and molecular techniques, we investigated the role of cardiac lymphatics in HFpEF and the underlying mechanisms. In mice with HFpEF, cardiac lymphatics displayed substantial structural and functional anomalies, including decreased lymphatic endothelial cell (LEC) density, vessel fragmentation, reduced branch connections, and impaired capacity to drain fluids and immune cells. LEC numbers and marker expression levels were also decreased in heart tissues from patients with HFpEF. Stimulating lymphangiogenesis with an adeno-associated virus expressing an engineered variant of vascular endothelial growth factor C (VEGFC Our study provides evidence that cardiac lymphatic disruption, driven by impaired BCAA catabolism in LECs, is a key factor contributing to HFpEF. These findings unravel the crucial role of BCAA catabolism in modulating lymphatic biology, and suggest that preserving cardiac lymphatic integrity may present a novel therapeutic strategy for HFpEF. Show less
📄 PDF DOI: 10.1161/CIRCULATIONAHA.124.071741
BCKDK
Haoyu Deng, Wan Yi Liang, Leqi Chen +6 more · 2025 · Journal of lipid research · Elsevier · added 2026-04-24
Sepsis is the dysregulated immune response to an infection and is a leading cause of mortality. Low levels of high-density lipoprotein (HDL) cholesterol are associated with increased risk of death fro Show more
Sepsis is the dysregulated immune response to an infection and is a leading cause of mortality. Low levels of high-density lipoprotein (HDL) cholesterol are associated with increased risk of death from sepsis, and increasing levels of HDL by inhibition of cholesteryl ester transfer protein (CETP) has been shown to decrease mortality in mouse models of sepsis. The objective of this study was to investigate the cellular mechanisms by which CETP inhibition and HDL lead to improved survival during sepsis. We found that HDL inhibits lipopolysaccharide (LPS)-induced activation of IL-1β in a mouse model of sepsis. The activation of IL-1β was dependent on the activity of scavenger receptor class B type 1 (SR-B1), and knockdown of SR-B1 significantly attenuated LPS-induced production of IL-1β in macrophages. Additionally, we found that LPS-induced SR-B1 internalization occurs through the endosome-lysosome pathway, which is also likely responsible for LPS degradation in the macrophages. Furthermore, we revealed that raising HDL by CETP inhibition markedly enhanced HDL-mediated anti-inflammatory effects in response to LPS stimulation, and these effects were not due to CETP itself but rather were HDL-dependent. Finally, we show that pharmacological inhibition of CETP significantly improved endotoxemia-induced mortality by inhibiting IL-1β production in the liver and circulation after LPS injection. Pathologically, CETP inhibition attenuated LPS-induced diffuse alveolar damage and hepatocyte necrosis, which may contribute to the improved mortality in mice treated with the CETP inhibitor anacetrapib. Taken together, our findings uncover a cellular mechanism by which HDL attenuates LPS-induced pro-inflammatory response via SR-B1-mediated LPS degradation. Show less
📄 PDF DOI: 10.1016/j.jlr.2025.100858
CETP
Hanyu Zhang, Zengyuan Zhou, Jie Gu +5 more · 2025 · Progress in neuro-psychopharmacology & biological psychiatry · Elsevier · added 2026-04-24
Lewy body dementia (LBD) is the second common dementia, with unclear mechanisms and limited treatment options. Dyslipidemia has been implicated in LBD, but the role of lipid-lowering drugs remains und Show more
Lewy body dementia (LBD) is the second common dementia, with unclear mechanisms and limited treatment options. Dyslipidemia has been implicated in LBD, but the role of lipid-lowering drugs remains underexplored. This study aims to investigate the association between lipid traits, drug targets, and LBD risk using Mendelian Randomization (MR) analysis. We performed univariable and multivariable MR analyses to evaluate the causal effects of lipid traits on the risk of LBD. Then, drug-target MR analysis and subtype analysis were conducted to evaluate the effects of lipid-lowering therapies on LBD. In univariable MR, genetically predicted low-density lipoprotein cholesterol (LDL-C) and remnant cholesterol (RC) levels were associated with an increased risk of LBD. Mediation analysis suggested a potential interaction between LDL-C and RC in influencing LBD risk. Drug-target MR analysis identified significant associations between genetically proxied inhibition of ANGPTL3, CETP, and HMGCR and LBD risk. This MR analysis provided evidence that elevated LDL-C and RC may increase the risk of LBD. Additionally, targeting ANGPTL3, CETP, and HMGCR may represent potential therapeutic strategies for the prevention or treatment of LBD. Show less
no PDF DOI: 10.1016/j.pnpbp.2025.111282
CETP
Jiahao Liu, Hongqing Zhu, Ziying Wang +6 more · 2025 · IEEE journal of biomedical and health informatics · IEEE · added 2026-04-24
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, Show more
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, a dual-branch network for segmenting acute ischemic stroke lesions in CT images, consisting of a segmentation branch and a prompt-aware branch. The segmentation branch uses an encoder-decoder network as the backbone to identify lesions, where the encoder fuses CT image features with prompt features from the prompt-aware branch. To enhance semantic feature extraction and reduce the impact of cerebral structural details, we introduce a cross-collaboration dynamic connection (CCDC) module to link the encoder and decoder. The prompt-aware branch includes a learnable prompt (LP) block to incorporate cerebral prior knowledge, and the prompt-aware encoder (PAE) combines the LP block with multi-level features from the segmentation branch for more precise representation. Additionally, we propose a CLIP-enhance textual prompt (CETP) module that utilizes the CLIP text encoder to generate specialized convolutional parameters for the segmentation head. These parameters are tailored to the unique characteristics of each input image, improving segmentation performance. Qualitative and quantitative studies reveal that DCTP-Net outperforms the current state-of-the-art, IS-Net, with Dice score increases of 3.9% on AISD and 3.8% on ISLES2018, demonstrating its superiority in EIL segmentation. Show less
no PDF DOI: 10.1109/JBHI.2024.3471627
CETP
Zhifang Huang, Weichao Yuan · 2025 · Frontiers in nutrition · Frontiers · added 2026-04-24
An association has been observed between alcohol and cheese intake and the onset of inflammatory bowel disease (IBD), necessitating further exploration from a genetic structural perspective. The prese Show more
An association has been observed between alcohol and cheese intake and the onset of inflammatory bowel disease (IBD), necessitating further exploration from a genetic structural perspective. The present analysis was focused on the intake of alcohol and cheese in conjunction with IBD genome-wide association study (GWAS) data, with the objective of exploring genetic correlations and identifying common loci. Initially, overall genetic correlations were assessed employing two methodologies: linkage disequilibrium score regression (LDSC) and genetic covariance analyzer (GNOVA). Subsequently, local correlations were examined through the SUPERGNOVA method. A genetic overlap analysis between various traits was then conducted based on the statistical theory of conditional/conjunctional false discovery rate (cond/conjFDR). Ultimately, shared loci between the two traits were identified via conjFDR analysis and multi-trait analysis of GWAS (MTAG). Substantial overall correlations were noted at the genome-wide level between alcohol and cheese intake and both IBD and Crohn's disease (CD), whereas the association with ulcerative colitis (UC) was of lesser significance. In the local genetic analysis, chromosome 16 emerged as a key region implicated in the relationship between alcohol and cheese intake and IBD (including both CD and UC). The conjFDR analysis confirmed the genetic overlap between the two diseases. Furthermore, both conjFDR and MTAG analyses identified multiple shared genetic loci, with nine genes ( The present study provides genetic evidence supporting the comorbidity of alcohol and cheese intake with IBD, offering novel insights into potential strategies for the prevention and treatment of IBD through the modulation of alcohol and cheese consumption. Show less
📄 PDF DOI: 10.3389/fnut.2025.1468457
CLN3
Jian Yue, Fang Wen, Dele He +2 more · 2025 · Scientific reports · Nature · added 2026-04-24
Despite significant advances in early detection and therapeutic interventions, breast cancer persists as the most frequently diagnosed malignancy and the leading cause of cancer-related deaths among w Show more
Despite significant advances in early detection and therapeutic interventions, breast cancer persists as the most frequently diagnosed malignancy and the leading cause of cancer-related deaths among women globally. Although multiple prognostic signatures have been proposed, their predictive power and clinical applicability remain limited. In this study, we utilized an integrated approach combining single-cell multi-omics analysis with machine learning to comprehensively examine the clinical relevance of mitochondrial-related gene sets in TCGA-BRCA and developed a mitochondrial gene set scoring system, termed MitoScore. Based on the median of MitoScore, BRCA patients were classified into high-risk and low-risk groups. Our multi-omics analysis revealed that BRCA patients with higher Mitoscore exhibited poorer prognoses compared to those with lower MitoScore. The predictive ability of the model was successfully validated using an external GEO dataset. Immune infiltration analysis further indicated that high-risk group contributed to an immunosuppressive tumor microenvironment, marked by a decrease in CD8 Show less
📄 PDF DOI: 10.1038/s41598-025-19890-y
CPS1
Huafeng Jian, Mengru Xu, Fang Liu +5 more · 2025 · Animal nutrition (Zhongguo xu mu shou yi xue hui) · Elsevier · added 2026-04-24
Gut microbiota not only biosynthesizes branched-chain amino acids (BCAA) but also catabolizes and utilizes them, while the effects of dietary BCAA supplementation on intestinal microbiota and metaboli Show more
Gut microbiota not only biosynthesizes branched-chain amino acids (BCAA) but also catabolizes and utilizes them, while the effects of dietary BCAA supplementation on intestinal microbiota and metabolism remain largely elusive. Therefore, the present study aimed to investigate the impacts of dietary BCAA supplementation on productive performance, egg quality, gut microbiota and metabolism in laying hens. A total of 180 Fengda No.1 laying hens aged 41 weeks were randomly assigned to five groups, with each group consisting of six replicates of six hens, and the experiment lasted for 8 weeks. The control group (Ctrl AA) was fed a basal diet, while the other four groups were supplemented with 67% leucine (High Leu), isoleucine (High Ile), both leucine and isoleucine (High Leu + Ile), or a combination of the three BCAA (High BCAA), respectively, based on the Ctrl AA. The results demonstrated that compared with Ctrl AA, both High Ile and High BCAA significantly decreased egg mass and laying rate ( Show less
📄 PDF DOI: 10.1016/j.aninu.2025.03.012
CPS1
Xiaolan Chen, Jin You, Qin Ma +7 more · 2025 · Nature communications · Nature · added 2026-04-24
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Al Show more
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Although the RNA moiety of most R-loops originates from linear transcripts, circular RNAs (circRNAs), outputs from back-splicing, can also hybridize with the complementary strand of a DNA duplex. However, how circRNA-associated R-loops (ciR-loops) are monitored remains elusive. Here, we identify the DEAD-box RNA helicase Brr2 as an evolutionarily-conserved ciR-loop repressor with dual roles in inhibiting circRNA generation and resolving harmful ciR-loops. Accumulation of ciR-loops caused by loss-of-function of this dual-action factor induces antisense transcription and premature transcription termination for many genes and generates significant DNA damage, which further leads to a series of defects in DNA replication, cell division and cell proliferation. We propose that functional integration of multilayered regulation by a single protein can be an efficient double protection against genome instability. Show less
📄 PDF DOI: 10.1038/s41467-025-64174-8
DHX36
Jie Yang, Geng Qin, Baoying Huang +9 more · 2025 · National science review · Oxford University Press · added 2026-04-24
The Mpox virus (MPXV) has emerged as a formidable orthopoxvirus, posing an immense challenge to global public health. An understanding of the regulatory mechanisms of MPXV infection, replication and i Show more
The Mpox virus (MPXV) has emerged as a formidable orthopoxvirus, posing an immense challenge to global public health. An understanding of the regulatory mechanisms of MPXV infection, replication and immune evasion will benefit the development of novel antiviral strategies. Despite the involvement of G-quadruplexes (G4s) in modulating the infection and replication processes of multiple viruses, their roles in the MPXV life cycle remain largely unknown. Here, we found a highly conservative and stable G4 in MPXV that acts as a positive regulatory element for viral immunodominant protein expression. Furthermore, by screening 42 optically pure chiral metal complexes, we identified the Λ enantiomer of a pair of chiral helical compounds that can selectively target mRNA G4 and enhance expression of the 39-kDa core protein encoded by the MPXV Show less
📄 PDF DOI: 10.1093/nsr/nwae388
DHX36
L Zhang, Z Huang, M Luo +5 more · 2025 · British poultry science · Taylor & Francis · added 2026-04-24
1. Copy number variation (CNV) is an important source for identifying genetic differences. This study compared the genome-wide CNV and their regions (CNVR) across 16 Chinese local duck breeds and dete Show more
1. Copy number variation (CNV) is an important source for identifying genetic differences. This study compared the genome-wide CNV and their regions (CNVR) across 16 Chinese local duck breeds and detected key genes and pathways involved in growth and reproduction-related traits using this dataset.2. Breakdancer, Pindel and CNVnator were used to detect reliable CNV, and HandyCNV was used to obtain CNVR. Selection signatures were analysed in meat (MD) and egg-laying ducks (ED) compared to wild ducks (WD) using fixation and differentiation index DIsv methods. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out to identify key pathways and related genes.3. Principal component analysis (PCA) using CNV data clustered 127 ducks into 4 populations: WD, MD, ED and meat+egg-type ducks (MED). In total, 237,630 CNV and 6,176 CNVR were detected across these samples. Intersection analysis identified 1,384 common CNVR and 2,105 unique CNVR. The KEGG analysis showed that common CNVR were enriched in 7 basic life activity pathways, while unique CNVR were enriched in 9 population-specific pathways. Compared to WD, MD selection signatures were found in 4 enriched pathways and 8 genes ( Show less
no PDF DOI: 10.1080/00071668.2025.2559392
DLG2
Mei Pu, Xia Xiao, Shasha Lv +6 more · 2025 · Hereditas · BioMed Central · added 2026-04-24
Discs large homolog 2 (DLG2) has been implicated in cancer development, yet its role in cervical cancer remains unclear. This study aims to explore the regulatory mechanism of DLG2 in cervical cancer Show more
Discs large homolog 2 (DLG2) has been implicated in cancer development, yet its role in cervical cancer remains unclear. This study aims to explore the regulatory mechanism of DLG2 in cervical cancer and its clinical implications. Quantitative reverse transcription polymerase chain reaction and western blotting assays were employed to detect RNA and protein expression, respectively. Colony formation assay, 5-Ethynyl-2'-deoxyuridine assay, flow cytometry, and transwell assays were conducted for cell functional analysis. A xenograft mouse model assay was performed to analyze tumor tumorigenesis in vivo. m6A RNA immunoprecipitation assay was used to analyze the association of METTL3 and DLG2. DLG2 was underexpressed in cervical cancer tissues and cells. Elevating DLG2 levels significantly suppressed cervical cancer cell proliferation, migration, and invasion, while promoting apoptosis. Additionally, DLG2 overexpression led to the deactivation of the Hippo/YAP signaling pathway. In vivo, DLG2 overexpression was shown to reduce tumor formation. We also discovered that METTL3 destabilized DLG2 mRNA through an m6A-dependent mechanism. Moreover, lowering DLG2 expression mitigated the effects of METTL3 silencing on cervical cancer cell malignancy. DLG2 acted as a tumor suppressor in cervical cancer by inhibiting the Hippo/YAP signaling pathway. The METTL3-dependent regulation of DLG2 mRNA stability could be a critical factor in cervical cancer progression. Show less
📄 PDF DOI: 10.1186/s41065-025-00365-z
DLG2
Bing-Hua Su, Chung-Teng Wang, Chia-Sing Lu +11 more · 2025 · Journal of Cancer · added 2026-04-24
The roles of cancer stem cells and Octamer-binding transcription factor 4 (OCT4) have been implicated in human tumorigenesis and metastasis. However, the role of OCT4 in the metastasis of non-small-ce Show more
The roles of cancer stem cells and Octamer-binding transcription factor 4 (OCT4) have been implicated in human tumorigenesis and metastasis. However, the role of OCT4 in the metastasis of non-small-cell lung cancer (NSCLC) remains undetermined, especially regarding stem cell-related pathways. Previous research has reported that dual-specificity phosphatase 6 (DUSP6), a mitogen-activated protein kinase (MAPK) phosphatase, is associated with cancer cells that display anti-apoptotic, migratory, and drug-resistance phenotypes. However, the regulation of DUSP6 in NSCLC is unclear. This study focused on the role of OCT4 in NSCLC, particularly its interaction with DUSP6. Here, we show a positive correlation between OCT4 and DUSP6 expression in NSCLC cells. Overexpression of OCT4 increased, whereas knockdown of OCT4 reduced DUSP6 expression. Luciferase reporter and chromatin immunoprecipitation (ChIP) assays revealed that OCT4 transactivated DUSP6 expression by directly binding to the DUSP6 promoter, indicating that DUSP6 is a downstream target of OCT4. Furthermore, knockdown of DUSP6 in OCT4-overexpressing A549 human NSCLC cells decreased cell migration Show less
📄 PDF DOI: 10.7150/jca.108663
DUSP6
Jianbiao Huang, Chongwei Zhou, Zhaojun Yu +4 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
Bladder cancer (BC) is one of the most prevalent urinary malignant tumors that is intricately regulated by molecular pathways. Multiple studies have demonstrated a clear association between DUSP6 and Show more
Bladder cancer (BC) is one of the most prevalent urinary malignant tumors that is intricately regulated by molecular pathways. Multiple studies have demonstrated a clear association between DUSP6 and malignant tumor progression; however, its role and underlying mechanisms in BC remain unclear. Here, we found that DUSP6 exhibits significantly elevated expression in BC tissues compared with normal tissues and is strongly associated with poor overall survival. Transcriptomic analysis revealed a robust correlation between DUSP6 expression and mitophagy, a selective form of autophagy crucial for maintaining mitochondrial integrity. Show less
📄 PDF DOI: 10.3389/fonc.2025.1603069
DUSP6
Qi-Nian Wu, Yi-Fu Liao, Yun-Xin Lu +9 more · 2025 · Cancer letters · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.canlet.2025.217983
DUSP6
Yingying Qiu, Xinjun Wei, Jian Cao +9 more · 2025 · Reproductive sciences (Thousand Oaks, Calif.) · Springer · added 2026-04-24
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver Show more
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver of AM progression. In this study, we investigated the role and underlying mechanisms of endometrial mesenchymal stem cell (eMSC)-derived exosomes in regulating AAM polarization and the subsequent EMT of endometrial epithelial cells (EECs). In vitro coculture studies revealed that AM eutopic eMSCs markedly induced M2 macrophage polarization via exosomes and promoted EMT of EECs. Differentially expressed microRNAs (DE-miRNAs) between exosomes derived from normal eMSCs (N-eMSCs) and AM eutopic eMSCs (A-eMSCs) were identified using miRNA sequencing and miR-4669 was found to be the most significantly upregulated miRNA. Internalization of exosomal miR-4669 by macrophages induced their polarization toward the M2 phenotype and promoted the EMT of EECs. Mechanistic analysis using luciferase assay, mRNA sequencing, and rescue experiments revealed that miR-4669 induced M2 macrophage polarization via downregulation of DUSP6 and activation of MAPK/ERK signaling. The polarized M2 macrophages promoted the EMT of ISK cells via TGF-β1 secretion. In an AM xenograft mouse model, miR-4669 depletion inhibited AM progression by targeting the DUSP6/ERK1/2 pathway in macrophages. Overall, AM A-eMSC-derived exosomal miR-4669 facilitates M2 macrophage polarization by targeting the DUSP6/ERK signaling pathway, thereby promoting EMT of EECs via TGF-β1 secretion. These findings open avenues for developing novel preventive and therapeutic strategies for AM. Show less
📄 PDF DOI: 10.1007/s43032-025-01944-1
DUSP6
Nieke Zhang, Zhicong Huang, Yi Xia +14 more · 2025 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Remote ischemic preconditioning (rIPC) has been reported to protect against kidney ischemia-reperfusion injury (IRI) through the delivery of extracellular vesicles (EVs). Among these, apoptosis-induce Show more
Remote ischemic preconditioning (rIPC) has been reported to protect against kidney ischemia-reperfusion injury (IRI) through the delivery of extracellular vesicles (EVs). Among these, apoptosis-induced compensatory proliferation signaling-related vesicles (ACPSVs) can transmit proliferation signals to surrounding cells. However, the underlying mechanisms remain unclear. This study aimed to investigate the role of ACPSVs in renal IRI following rIPC and to elucidate the associated mechanisms. We demonstrated that rIPC plasma or ACPSVs alleviated renal damage and inflammation, with the protective effects abolished upon the removal of ACPSVs from the plasma. EVs isolated via differential centrifugation exhibited defining characteristics of ACPSVs. Co-culture experiments revealed that ACPSVs reduced apoptosis and enhanced the viability of HK-2 cells under hypoxia/reoxygenation (H/R) conditions. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses highlighted the critical role of macrophage migration inhibitory factor (MIF) protein in ACPSVs. Using CRISPR/Cas9 technology, we generated MIF-knockout HeLa cells to induce the production of MIF-deficient ACPSVs. The protective effects of ACPSVs were significantly attenuated when MIF was knocked out. Transcriptome sequencing and chromatin immunoprecipitation (ChIP) assays revealed that MIF suppresses dual-specificity phosphatase 6 (DUSP6) expression by promoting H3K9 trimethylation (H3K9me3) in the DUSP6 promoter region, thereby activating the JNK signaling pathway. In rescue experiments, treatment with the DUSP6 inhibitor BCI effectively restored the protective function of MIF-deficient ACPSVs. This study underscores the protective role of ACPSVs derived from rIPC-treated rats and serum-starved cells against renal IRI through the MIF/DUSP6/JNK signaling axis, offering a potential clinical therapeutic strategy for acute kidney injury induced by IRI. [Image: see text] The online version contains supplementary material available at 10.1186/s12951-025-03505-9. Show less
📄 PDF DOI: 10.1186/s12951-025-03505-9
DUSP6
Ziyang Liu, Zengyuan Qin, Wenxin Bai +6 more · 2025 · PloS one · PLOS · added 2026-04-24
Diabetic kidney disease (DKD) is a severe global complication of diabetes, yet its molecular mechanisms remain incompletely understood. This study aimed to investigate the role of protein glycosylatio Show more
Diabetic kidney disease (DKD) is a severe global complication of diabetes, yet its molecular mechanisms remain incompletely understood. This study aimed to investigate the role of protein glycosylation in DKD pathogenesis and its association with gene expression changes, with the goal of identifying diagnostic biomarkers and personalized therapeutic targets. Integrated bioinformatics and machine learning approaches were applied to analyze multiple gene expression datasets. Differentially expressed glycosylation-related genes were identified, followed by unsupervised clustering to define molecular subtypes. Functional enrichment, immune cell infiltration analysis, and machine learning algorithms (including feature selection for hub genes) were employed. qPCR validation was performed on clinical DKD and normal kidney tissues, and ROC curves were generated to assess diagnostic potential. Unsupervised clustering of glycosylation-related genes revealed two distinct DKD molecular subtypes with differential pathway activation (e.g., extracellular matrix remodeling) and immune infiltration patterns. Six hub genes (S100A12, EXT1, SBSPON, ADAMTS1, FMOD, SPTB) were identified as critical to DKD pathogenesis through machine learning. Immune infiltration analysis showed significant differences in macrophage and neutrophil activity between DKD and controls and Immunohistochemical results confirmed the occurrence of immune infiltration. qPCR validation confirmed dysregulation of hub genes in DKD tissues compared to normal samples. ROC analysis demonstrated high diagnostic accuracy for these genes. This study highlights abnormal protein glycosylation as a key player in DKD and identifies six hub genes with potential as diagnostic biomarkers. The molecular subtypes and immune infiltration patterns provide insights into disease heterogeneity, paving the way for personalized therapies. Future studies should validate these findings in larger cohorts with explicit sample sizes to strengthen clinical applicability. Show less
📄 PDF DOI: 10.1371/journal.pone.0329640
EXT1
Yingchun Zheng, Xuewu Wei, Zhongzhi Gan +7 more · 2025 · Journal of human genetics · Nature · added 2026-04-24
Ankylosing spondylitis (AS) is a chronic and progressive inflammatory arthritis involving disorders of both the immune and skeletal systems. Multiple osteochondromas (MO) is a rare skeletal disorder w Show more
Ankylosing spondylitis (AS) is a chronic and progressive inflammatory arthritis involving disorders of both the immune and skeletal systems. Multiple osteochondromas (MO) is a rare skeletal disorder with a variety of clinical manifestations characterized by multiple benign exostoses. Here, we investigate a Chinese family with HLA-B27-negative AS complicated with MO. Whole-exome sequencing (WES) and Sanger sequencing were used to screen and identify the pathogenic gene. In vitro functional analysis was performed, and a pathogenesis-associated interleukin (IL)-17 receptor C (IL17RC) mutation was analyzed to investigate its effect on phenotypes. WES was used to identify a known missense mutation, NM₀₀₀₁₂₇.3:c.1019 G > A(p.Arg340His), in the pathogenic gene EXT1 that is causal for MO. Moreover, a missense mutation, NM₁₅₃₄₆₁.3:c.1067 C > T(p.Thr356Met), in the IL17RC gene was identified as potentially responsible for AS or spondyloarthritis symptoms in this family. In vitro over-expression of mutant IL17RC decreased its expression and increased the expression of IL17RA, consistent with the expression of these two genes in patients. Mechanistically, mutant IL17RC enhanced the activation of the NF-κB pathway. This study increases our understanding of the pathogenesis and progression of these diseases. Our findings broaden the risk factors in non-HLA-B genes associated with the NF-κB pathway in AS. Show less
📄 PDF DOI: 10.1038/s10038-025-01383-5
EXT1
Hongrong Zhang, Zhencun Tang, Shiying Shen +6 more · 2025 · Bone · Elsevier · added 2026-04-24
This study aims to investigate the roles of the EXT1 and FGFR3 genes in the development of osteochondromas, focusing specifically on their potential interactions in chondrocyte proliferation, differen Show more
This study aims to investigate the roles of the EXT1 and FGFR3 genes in the development of osteochondromas, focusing specifically on their potential interactions in chondrocyte proliferation, differentiation, and tumor formation. In vitro, the ATDC5 chondroprogenitor cell line was used to examine the effects of inactivation of both EXT1 and FGFR3. In vivo, a mouse model with dual gene knockout of Ext1 and Fgfr3 was constructed to further explore these genes' roles in tumor formation by observing the incidence and distribution patterns of osteochondromas. The in vitro experiments demonstrated that ATDC5 cells with reduced expression of EXT1 and FGFR3 genes exhibited enhanced chondrogenic differentiation. In vivo, Fgfr3 The EXT1 and FGFR3 genes play crucial regulatory roles in the development of osteochondromas. Deficiencies in Ext1 and Fgfr3 can induce the formation of osteochondromas. Show less
no PDF DOI: 10.1016/j.bone.2024.117370
EXT1
Xu Cao, Mingfan Liu, Dongmei Zou +3 more · 2025 · Discover oncology · Springer · added 2026-04-24
The intrinsic heterogeneity and invasiveness of diffuse gliomas complicate accurate prognosis. Existing approaches are largely constrained by subtype specificity or limited analytical dimensions. To a Show more
The intrinsic heterogeneity and invasiveness of diffuse gliomas complicate accurate prognosis. Existing approaches are largely constrained by subtype specificity or limited analytical dimensions. To address this gap, a multi- dimension-based prognostic framework encompassing the full glioma spectrum was developed, accompanied by an analysis of the associated immune microenvironment. A total of 3,323 glioma samples from the SEER (n = 2181), CGGA (n = 807), and TCGA (n = 335) datasets were integrated. Differentially expressed genes were screened using the limma package, and a Lasso-Cox-based prognostic signature (Glioma-GDPM) was established. Clinical variables such as age, grade, and IDH mutation status were harmonized through propensity score matching to construct a multi-omics prognostic model (Glioma-GCDPM). GSEA, CIBERSORT-based immune infiltration analysis, and TIDE scoring were used to investigate the biological characteristics of different risk subgroups. Eleven key prognostic genes (such as PRAMEF2 and FADS1) and four clinical factors (age, tumor grade, IDH mutation, and 1p/19q codeletion) were identified. Glioma-GCDPM demonstrated favorable predictive ability in both the internal test cohort (AUC 0.81-0.86) and external validation sets (AUC 0.59-0.83). High-risk tumors exhibited greater invasiveness, with significant enrichment in cell cycle and proliferation-associated pathways. Additionally, a suppressed immune microenvironment was observed, reflected by elevated M2 macrophage infiltration and increased T cell dysfunction scores. The multi-omics model established in this study enables precise stratification of prognostic risk in diffuse glioma patients and reveals immunosuppressive features in high-risk individuals, providing a new basis for personalized treatment strategies. Show less
📄 PDF DOI: 10.1007/s12672-025-03551-7
FADS1