👤 Riping Wu

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Also published as: Jiake Wu, Ming-Jiuan Wu, Siying Wu, Yijian Wu, Fong-Li Wu, Chih-Chung Wu, Jin'en Wu, Zhongwei Wu, Zixiang Wu, D P Wu, Haiping Wu, Geyan Wu, Qi-Zhu Wu, Jianjin Wu, Su Wu, Shwu-Yuan Wu, Xiaodi Wu, Kuen-Phon Wu, Changxin Wu, Zhiping Wu, Guofeng Wu, Xiaojun Wu, Qibing Wu, Cheng-Hsin Wu, Junhua Wu, Xiaoting Wu, Wenze Wu, Zhong Wu, Hong Wu, Yandi Wu, An-Chih Wu, Jianhui Wu, Xiaoke Wu, Zhenguo Wu, Jason H Y Wu, Yi-Mi Wu, Bing-Bing Wu, Selena Meiyun Wu, M Wu, Hui-Mei Wu, Danni Wu, Minqing Wu, Sijie Wu, Geng-ze Wu, Kun Wu, Cheng-Hua Wu, Shaofei Wu, Zhaoyang Wu, Qihan Wu, R Ryanne Wu, Kunling Wu, Hao Wu, Mingxuan Wu, Pei Wu, Wendy Wu, Douglas C Wu, Yukang Wu, Jingtao Wu, Guizhen Wu, Zhangjie Wu, Lili Wu, Jianwu Wu, Min-Jiao Wu, Biaoliang Wu, Huan Wu, Shengxi Wu, Fei-Fei Wu, Peih-Shan Wu, Yu-Yuan Wu, Guoqing Wu, Pei-Yu Wu, Geting Wu, Lun-Gang Wu, Jing Wu, Dongzhe Wu, G Wu, Junlong Wu, Jia-Jun Wu, Jiangyue Wu, Muzhou Wu, Ray-Chin Wu, Jian-Qiu Wu, Junzhu Wu, T Wu, Jianxiong Wu, Liping Wu, Haiwei Wu, Yong-Hao Wu, Guoping Wu, Jin-hua Wu, Yi Wu, Chongming Wu, You Wu, Xudong Wu, Qunzheng Wu, Liqiang Wu, Cuiling Wu, Kunfang Wu, Limeng Wu, Jason Wu, Bian Wu, Zhibing Wu, Shuying Wu, Naqiong Wu, Caihong Wu, Huating Wu, Joseph C Wu, Tianhao Wu, Zhi-Hong Wu, Congying Wu, Gaojun Wu, Dongping Wu, Chiao-En Wu, Li Wu, Haixia Wu, Yihang Wu, Shaoxuan Wu, Gen Wu, Fanchang Wu, Xiaorong Wu, Mei Wu, Mingjie Wu, Jiahao Wu, Jiapei Wu, Jia Wu, Lingqian Wu, Fangge Wu, Sen-Chao Wu, Yanhui Wu, Zhiqiang Wu, Shugeng Wu, Sarah Wu, Dongmei Wu, Xuanqin Wu, Caiwen Wu, Jiangdong Wu, Junjing Wu, Guihua Wu, Meini Wu, Yingbiao Wu, Rui Wu, Hua-Yu Wu, Bifeng Wu, Jingwan Wu, Lingling Wu, Junzheng Wu, Xinmiao Wu, Yi-Fang Wu, Yuyi Wu, Qinglin Wu, Yixuan Wu, Leilei Wu, Bin Wu, Tianqi Wu, Shiya Wu, Hui-Chen Wu, Jian Wu, Sijun Wu, Cong Wu, Yiwen Wu, Feng Wu, Xi-Ze Wu, Qiuji Wu, Alexander T H Wu, Semon Wu, Qinan Wu, Lai Man Natalie Wu, Zhuokai Wu, Ran Wu, Panyun Wu, Kui Wu, Yumei Wu, Yueling Wu, Xinrui Wu, Biwei Wu, Xing Wu, Jiayi Wu, Hua Wu, Yuen-Jung Wu, Bingjie Wu, Xiaoliang Wu, Matthew A Wu, Jin Wu, Juanjuan Wu, Qiuhong Wu, Hongfu Wu, Xiaoming Wu, Ming-Sian Wu, Ronghua Wu, Junduo Wu, Dandan Wu, Ming-Shiang Wu, Yuliang Wu, Ying-Ying Wu, Chaoling Wu, Guang-Liang Wu, De Wu, Tsung-Jui Wu, Yihua Wu, Yuanyuan Wu, Han Wu, Yulian Wu, Lipeng Wu, Zhihao Wu, Jiexi Wu, Anna H Wu, Yaqin Wu, Qiu Wu, Huazhen Wu, Shengru Wu, Chieh-Lin Stanley Wu, Xiaoqian Wu, Xiahui Wu, Jianli Wu, Yun-Wen Wu, Jian-Yi Wu, Qiuya Wu, Tsai-Kun Wu, Xinyin Wu, Guoyao Wu, Zhenfeng Wu, Guoli Wu, J W Wu, Bill X Wu, Zujun Wu, Jianliang Wu, Yuanshun Wu, Ling-Ying Wu, Zeng-An Wu, Jianrong Wu, Xue Wu, Ke Wu, Cheng-Yang Wu, Mengxue Wu, Jinghong Wu, Rongrong Wu, Ruolan Wu, Rong Wu, Kevin Zl Wu, Xiaohong Wu, Run Wu, Zaihao Wu, Chaowei Wu, Yu-Ke Wu, Xinjing Wu, Anyue Wu, Yun Wu, Xuan Wu, Meili Wu, Shu Wu, Wanxia Wu, Yi-No Wu, Chao-Liang Wu, Chengwei Wu, Y-W Wu, Pensee Wu, Zhao-Bo Wu, Guangxian Wu, Xiao Wu, Juanli Wu, Xinlei Wu, Changjie Wu, Sai Wu, Jiawei Wu, Yujuan Wu, Haoze Wu, Renlv Wu, Xiaoyang Wu, Yipeng Wu, Yuh-Lin Wu, Yu'e Wu, An-Hua Wu, Dan-Chun Wu, Meng-Chao Wu, Yuanhao Wu, Jer-Yuarn Wu, Qian-Yan Wu, Guangyan Wu, Huisheng Wu, Huijuan Wu, Shuting Wu, Long-Jun Wu, Alice Ying-Jung Wu, Xiru Wu, Zhenfang Wu, Lidi Wu, Yetong Wu, Disheng Wu, Linmei Wu, Huiwen Wu, Zhenzhou Wu, Yuhong Wu, Liang Wu, Liyan Wu, Kuan-Li Wu, Pei-Ting Wu, Xiao-Jin Wu, Lifeng Wu, Terence Wu, Shujuan Wu, Gang Wu, Xue-Mei Wu, Szu-Hsien Wu, Yan-ling Wu, Yih-Jer Wu, Xiaokang Wu, Lingyan Wu, Xinghua Wu, Chunfu Wu, Yingxia Wu, Rongling Wu, Xifeng Wu, Jinhua Wu, Ming-Yue Wu, Sihan Wu, Shiyang Wu, K D Wu, Jinmei Wu, Luyan Wu, Shin-Long Wu, Zhipeng Wu, Shuai Wu, Guangzhen Wu, Zhixiang Wu, Longting Wu, Zhengsheng Wu, Xiaoqiong Wu, Yaoxing Wu, Yuqin Wu, Yudan Wu, Zoe Wu, Hongting Wu, Chi-Jen Wu, R Wu, Zhongqiu Wu, Meina Wu, Anke Wu, Dengying Wu, Cheng-Jang Wu, Hsi-Chin Wu, Shufang Wu, Yongjiang Wu, Yuan-de Wu, Sihui Wu, Qi Wu, Wenhui Wu, Fenfang Wu, K S Wu, Nana Wu, Jianzhi Wu, Lin-Han Wu, Zhen Wu, Jinjun Wu, Chen-Lu Wu, Jing-Fang Wu, Haiyan Wu, Yihui Wu, Qiqing Wu, Zhengzhi Wu, Dai-Chao Wu, Zhenyan Wu, Wen-Jeng Wu, Yongqun Wu, Sean M Wu, Guanming Wu, Hei-Man Wu, Su-Hui Wu, Diana H Wu, Ben J Wu, Pingxian Wu, Chew-Wun Wu, Yillin Wu, Xiaobing Wu, Jiang-Bo Wu, Jerry Wu, Siming Wu, Zijun Wu, Daqing Wu, Yu-Hsuan Wu, Lichao Wu, Zhimin Wu, Qijing Wu, Daxian Wu, Zhaoyi Wu, Z Wu, Tong Wu, Cheng-Chun Wu, Tracy Wu, Shusheng Wu, D Wu, Ting-Ting Wu, Xiao-Yan Wu, J Wu, Lan Wu, Changchen Wu, Qi-Fang Wu, Changwei Wu, Liangyan Wu, Liufeng Wu, Kan Wu, Eugenia Wu, Mingming Wu, Xiaolong Wu, Chunru Wu, Zhaofei Wu, Shenhao Wu, Li-Peng Wu, Yuna Wu, Minna Wu, Justin Che-Yuen Wu, Buling Wu, Wutian Wu, Chengyu Wu, Yuwei Wu, Guixin Wu, Haijing Wu, Hei Man Wu, Qiuchen Wu, Junfei Wu, Xiao-Hui Wu, Wenda Wu, Xiaofeng Wu, Linyu Wu, Yung-Fu Wu, Mengbo Wu, Zhenling Wu, Zuping Wu, Maoqing Wu, Chun-Chieh Wu, Julian Wu, Binbin Wu, Xiaohui Wu, Qian Wu, Xinchun Wu, Shuisheng Wu, Xueqing Wu, Linxiang Wu, Bo Wu, Moxin Wu, Xiao-Cheng Wu, Anzhou Wu, Shuyi Wu, Jiahui Wu, Meiqin Wu, Shihao Wu, Jer-Yuan Wu, Wen-Shu Wu, Wudelehu Wu, Ruonan Wu, Song Wu, De-Fu Wu, Yulin Wu, Hongyu Wu, Yurong Wu, Zixuan Wu, Shih-Ying Wu, Chih-Hsing Wu, Chengrong Wu, Yinghao Wu, Yuanzhao Wu, Wenjie Wu, Baochuan Wu, Ziliang Wu, Liuting Wu, Chia-Ling Wu, Y Q Wu, Man Wu, Na Wu, Wutain Wu, Chenyang Wu, Jinyu Wu, Selwin K Wu, Ping Wu, Lorna Wu, D I Wu, Yi-Cheng Wu, Jianzhong Wu, Xiaoyun Wu, Zhourui Wu, Li-Jun Wu, Xinhe Wu, Zhi-Wei Wu, Yinan Wu, Xinyan Wu, Xin Wu, Ting-Feng Wu, Shixin Wu, Yawei Wu, Tsung-Teh Wu, Jiarui Wu, Hong-Mei Wu, Xiaojin Wu, Yiqun Wu, Qi-Nian Wu, Ju Wu, Kai-Yue Wu, Pengjie Wu, Xi-Chen Wu, Zhe Wu, Shaoping Wu, Zhou Wu, Han-Jie Wu, Weijie Wu, Haijiang Wu, Xiaojie Wu, Hongfei Wu, Yi-Ying Wu, Zhentian Wu, Ze Wu, Kai-Hong Wu, Yuting Wu, Minyao Wu, Xueyan Wu, Feifei Wu, Shinan Wu, Yonghui Wu, Haoxuan Wu, Yanzhi Wu, Yiyi Wu, Dong Wu, Guohao Wu, Wenjing Wu, Shibo Wu, Wenqian Wu, Tian Wu, Hai-Yan Wu, Tiantian Wu, Chong Wu, Hongxian Wu, Daoyuan Wu, Zongfu Wu, Ling Wu, Yuxiang Wu, Xilong Wu, Yuyu Wu, Huijian Wu, Zong-Jia Wu, Fengming Wu, Guorong Wu, Chuanhong Wu, Choufei Wu, Junfang Wu, Chi-Chung Wu, Xingwei Wu, Ling-Fei Wu, Xiaoqing Wu, Xinyang Wu, Xiaomin Wu, Yili Wu, Hong-Fu Wu, Shao-Ming Wu, Thomas D Wu, Lizhen Wu, Yuanming Wu, Hsien-Ming Wu, Jian Hui Wu, Litong Wu, Yuxian Wu, Weihua Wu, Lei Wu, C Wu, Wei Wu, Yu-E Wu, Qiulian Wu, Mei-Hwan Wu, Yuexiu Wu, Shaoze Wu, Zilong Wu, Chi-Hao Wu, Baojin Wu, Chao Wu, Yao Wu, Ya Wu, Do-Bo Wu, Wenjun Wu, Zhongren Wu, Nini Wu, Michael C Wu, Ning Wu, Jie Wu, Ming J Wu, Yi-Syuan Wu, Limei Wu, Zhenzhen Wu, Tianwen Wu, Wen-Chieh Wu, Yunhua Wu, Junfeng Wu, Shunan Wu, Junqi Wu, Jianing Wu, Honglin Wu, Maureen Wu, Yexiang Wu, Yan-Hua Wu, Mengjun Wu, Y H Wu, Mingxing Wu, Liuying Wu, Suhua Wu, Xiaomeng Wu, Shyh-Jong Wu, Tung-Ho Wu, Hongliang Wu, Wenxian Wu, Xuekun Wu, Ed Xuekui Wu, Wenqiang Wu, Chuang Wu, Jingyi Wu, Duojiao Wu, Xueyuan Wu, Ji-Zhou Wu, Lianqian Wu, Gaige Wu, Qing-Qian Wu, Xiushan Wu, Haihu Wu, Xueyao Wu, Tingchun Wu, Yafei Wu, Lingxi Wu, R-J Wu, Weidong Wu, Re-Wen Wu, Zhidan Wu, Peiyao Wu, Xuemei Wu, Chen Wu, Yiting Wu, Kerui Wu, Lihong Wu, Shiqi Wu, Liren Wu, Xiuhua Wu, Beili Wu, Ruihong Wu, Yongqi Wu, Huini Wu, Lingyun Wu, Guang-Long Wu, Po-Chang Wu, Ru-Zi Wu, Wenxue Wu, Qinghua Wu, Wenlin Wu, Changjing Wu, Xiexing Wu, J Y Wu, Jianping Wu, Guanggeng Wu, W J Wu, Zhichong Wu, Di Wu, Shaoyu Wu, Xiaotong Wu, Junyong Wu, Hui Wu, Shengde Wu, Hongyan Wu, Mengyuan Wu, Yutong Wu, Zheming Wu, Yiping Wu, Guiping Wu, Wen-Hui Wu, Dapeng Wu, Bing Wu, Wen-Sheng Wu, Yunpeng Wu, Li-Ling Wu, Xiao-Yuan Wu, Qiu-Li Wu, Baiyan Wu, Ying Wu, Xiao-Ye Wu, Da-Hua Wu, Hsing-Chieh Wu, Hui-Xuan Wu, Chieh-Jen Wu, Pengning Wu, Sichen Wu, S F Wu, Mengying Wu, Jia-En Wu, Ming-Der Wu, Qi-Jun Wu, Weida Wu, Guo-Chao Wu, Zhenyong Wu, Qi-Biao Wu, Yangfeng Wu, Lijie Wu, Zhiye Wu, Jihui Wu, Qianqian Wu, Zhengliang L Wu, JieQian Wu, Jingyun Wu, Xiaoman Wu, Ruohao Wu, Yiyang Wu, Zhengfeng Wu, Xiao-Jun Wu, Lizi Wu, Qiang Wu, J-Z Wu, Guangjie Wu, Pengfei Wu, Jundong Wu, Beier Wu, Meng-Ling Wu, Jianying Wu, Lingxiang Wu, Jamie L Y Wu, Keija Wu, Xilin Wu, Yanhua Wu, An-Li Wu, Chengbiao Wu, Yi-Ming Wu, Huanghui Wu, Dong-Feng Wu, Kunsheng Wu, Yuxin Wu, Zhengcan Wu, Kun-Rong Wu, Dong-Fang Wu, Guanxian Wu, Sensen Wu, Guifen Wu, Yifeng Wu, Pin Wu, Tzu-Chun Wu, Qingping Wu, Mian Wu, R M Wu, S J Wu, Haisu Wu, Senquan Wu, Jingjing Wu, Cheng Wu, Meng Wu, Geping Wu, Yu Wu, Yumin Wu, Xia Wu, William Ka Kei Wu, Xian-Run Wu, Juan Wu, Pei-Ei Wu, Meng-Hsun Wu, Yingying Wu, S M Wu, Xiangwei Wu, Guangrun Wu, Liuxin Wu, Yangyu Wu, Jia-Hui Wu, Jin-Zhen Wu, Shaohuan Wu, S L Wu, Yanli Wu, June K Wu, Haishan Wu, H Wu, Zhou-Ming Wu, Deqing Wu, Tao Wu, Dong-Bo Wu, Binxin Wu, Yalan Wu, Xiangxin Wu, Xueji Wu, Hongxi Wu, Zhonghui Wu, Jiaxi Wu, Tianzhi Wu, Meiqi Wu, Weiwei Wu, Yan-Jun Wu, Lijuan Wu, Jianming Wu, Tingqin Wu, P L Wu, Yih-Ru Wu, Lanlan Wu, Jianjun Wu, An-Xin Wu, Jianguang Wu, Xingjie Wu, Jianzhang Wu, Xianan Wu, Wei-Ping Wu, Haoan Wu, Fang-Tzu Wu, Wenwen Wu, Zhongjun Wu, Xi Wu, Teng Wu, Xiaoling Wu, Mengjuan Wu, Wen Wu, Yifan Wu, Yang Wu, Qianhu Wu, Shenyue Wu, Wu-Tian Wu, Qianwen Wu, Ye Wu, Gui-Qin Wu, Lixing Wu, Grace F Wu, Xing-Ping Wu, Ming Wu, Lisha Wu, Yanchuan Wu, Siqi Wu, Yuming Wu, Yuan Wu, I H Wu, Yu-Ting Wu, Hailong Wu, Minghua Wu, B Wu, Zhenlong Wu, Fang Wu, Guanzhong Wu, Liqun Wu, Guifu Wu, Chris Y Wu, Zhikang Wu, Qi-Yong Wu, Qingshi Wu, Zhao-Yang Wu, Man-Jing Wu, Chih-Ching Wu, Jun Wu, Jinhui Wu, Jincheng Wu, Linhong Wu, Hung-Tsung Wu, Tangchun Wu, Xinglong Wu, Zhen-Yang Wu, Ma Wu, Dongyan Wu, Yin Wu, Jiu-Lin Wu, Yong Wu, Yan Wu, Weizhen Wu, Changyu Wu, Fanggeng Wu, Dishan Wu, Yue Wu, Yi-Long Wu, Ge-ru Wu, Jinqiao Wu, Zhongyang Wu, Jing-Wen Wu, Lifang Wu, Sheng-Li Wu, Songfen Wu, Jia-Wei Wu, Yihan Wu, Kebang Wu, Wenyong Wu, Cai-Qin Wu, Yilong Wu, Yanan Wu, Hsiu-Chuan Wu, Xueqian Wu, Yen-Wen Wu, Paul W Wu, Ying-Ting Wu, Xing-De Wu, Mingfu Wu, Yucan Wu, Na-Qiong Wu, Jinze Wu, Linzhi Wu, Xuhan Wu, H J Wu, Dirong Wu, Ruize Wu, Chung-Yi Wu, Yaohong Wu, Jianyi Wu, Jugang Wu, Jiao Wu, Liang-Huan Wu, Xueling Wu, Ruying Wu, Gen Sheng Wu, Zhaoyuan Wu, Shiwen Wu, Andong Wu, Hsan-Au Wu, Yu-Ling Wu, Jia-Qi Wu, Xihai Wu, Yanting Wu, Lulu Wu, Xuxian Wu, Xiaomei Wu, Jingyue Wu, Shuihua Wu, Ren Wu, S Wu, Yupeng Wu, Haoming Wu, Samuel M Wu, Fan Wu, Yuesheng Wu, Tiange Wu, Yihe Wu, Shuang Wu, Jiayu Wu, Chia-Lung Wu, Shengnan Wu, Yaojiong Wu, Y Wu, Zhuoze Wu, Y Y Wu, Depei Wu, Zimu Wu, Yi-Hua Wu, Yanyan Wu, Haiyun Wu, Min Wu, Wenjuan Wu, Guangxi Wu, Jinfeng Wu, Junjie Wu, Yawen Wu, Pinglian Wu, Hui-Hui Wu, Xunwei Wu, Xuefeng Wu, Depeng Wu, Constance Wu, Dianqing Wu, Qibiao Wu, Hao-Tian Wu, Nan Wu, Hanyu Wu, Xiaojiang Wu, San-pin Wu, Cheng-Jun Wu, Xiaofan Wu, Xiwei Wu, Shi-Xin Wu, Shao-Guo Wu, Sunyi Wu, Yueheng Wu, Chengqian Wu, Kuixian Wu, Guanyi Wu, Xin-Xi Wu, Qiuxia Wu, Danhong Wu, He Wu, Zhong-Jun Wu, Siyi Wu, Xiangsheng Wu, Lanxiang Wu, Kaili Wu, Liting Wu, Ping-Hsun Wu, Zheng Wu, Wen-Ling Wu, Jiang-Nan Wu, Huanlin Wu, Yongfei Wu, Catherine A Wu, Leslie Wu, Shuo Wu, Peng-Fei Wu, Meng-Han Wu, Cho-Kai Wu, Hon-Yen Wu, Anguo Wu, Yuguang Philip Wu, Hai-Yin Wu, Yicheng Wu, Xiaolang Wu, Qing Wu, Yujie Wu, Haomin Wu, V C Wu, Xingdong Wu, Hengyu Wu, Jiang Wu, Xiaoli Wu, Chengxi Wu, Junyi Wu, Ling-qian Wu, William K K Wu, Chun Wu, Lesley Wu, Niting Wu, Jiayuan Wu, Xueying Wu, S-F Wu, Yingning Wu, David Wu, Mei-Na Wu, Joshua L Wu, Jin-Shang Wu, Guanzhao Wu, Jianqiang Wu, Runda Wu, Li-Hsien Wu, Rongjie Wu, June-Hsieh Wu, Huazhang Wu, Huanwen Wu, Xiu-Zhi Wu, Xianfeng Wu, Yanran Wu, Weibin Wu, Xuanshuang Wu, Yan Yan Wu, G X Wu, Jiaqi Wu, Chien-Ting Wu, Li-Na Wu, Runpei Wu, Qinfeng Wu, Chia-Chang Wu, Yueming Wu, Renhai Wu, Siyu Wu, Baojian Wu, Yi-Xia Wu, C-H Wu, Wei-Yin Wu, Renrong Wu, Chuan-Ling Wu, Xinran Wu, Fengying Wu, Qiuliang Wu, Guanhui Wu, Jinjie Wu, Wei-Chi Wu, Wei-Xun Wu, Meng-Na Wu, Lin Wu, Wan-Fu Wu, Jiajing Wu, Colin Chih-Chien Wu, Yajie Wu, Qiaowei Wu, Yaru Wu, Xiaoping Wu, Xue-Yan Wu, Mengchao Wu, Weijun Wu, Boquan Wu, Chunyan Wu, Zelai Wu, Pei-Wen Wu, Guojun Wu, Yichen Wu, Ming-Tao Wu, Hsueh-Erh Wu, Guang-Bo Wu, Zhi-Yong Wu, Kay L H Wu, Chia-Zhen Wu, Yong-Hong Wu, Anping Wu, Jiahang Wu, Xiaobin Wu, Ching-Yi Wu, Linzhen Wu, Xiaoxing Wu, Haidong Wu, Zhen-Qi Wu, Mark N Wu, Jianmin Wu, Guanrong Wu, Xianpei Wu, Yanchun Wu, Dongsheng Wu, An-Dong Wu, Ren-Chin Wu, Yuchen Wu, Mengna Wu, Lijun Wu, Zhuanbin Wu, Yanjing Wu, Haodi Wu, Lun Wu, Si-Jia Wu, Yongfa Wu, Ximei Wu, Hai-Ping Wu, Xiangping Wu, Wenyu Wu, L-F Wu, Yixia Wu, Yiran Wu, Haiying Wu, Yanhong Wu, Xiayin Wu, Yushun Wu, Yali Wu, Qitian Wu, Qin Wu, Xiaofu Wu, Jiamei Wu, Xiaoyong Wu, Qiong Wu, Xiaoying Wu, Wujun Wu, N Wu, Peiyi Wu, Yongmei Wu, Xiaojing Wu, Yizhou Wu, Dan Wu, Wen-Qiang Wu, Anshi Wu, Junqing Wu, Xiao-Yang Wu, Zhaoxia Wu, Liyang Wu, Hongke Wu, Mengqiu Wu, Peng Wu, Haibin Wu, Ding Lan Wu, Lecheng Wu, Yingzhi Wu, Kejia Wu, Anyi Wu, Junshu Wu, Jianxin Wu, Deguang Wu, Jiaxuan Wu, Justin C Y Wu, W Wu, Jiong Wu, Yu-Chih Wu, Qinglan Wu, Xinyi Wu, Diana Wu, Zhongluan Wu, Xuefen Wu, Yanqiong Wu, Shengming Wu, Jian-Lin Wu, Donglin Wu, Daren Wu, Lintao Wu, Xiaodong Wu, Chang-Jiun Wu, Chunshuai Wu, Irene X Y Wu, Yaping Wu, Yangna Wu, Xiping Wu, Zongheng Wu, Chia-Chen Wu, Wenyi Wu, Yansheng Wu, Shaojun Wu, Aimin Wu, Caisheng Wu, Xu Wu, Zhongchan Wu, Yaohua Wu, Fei Wu, Qinyi Wu, Yibo Wu, Zhengyu Wu, Yadi Wu, Hang Wu, L Wu, Mingjun Wu, Yuetong Wu, Wen-Juan Wu, Guangming Wu, Lingzhi Wu, Tingting Wu, Zhuzhu Wu, Yuanbing Wu, Zhong-Yan Wu, Cuiyan Wu, Colin O Wu, Baoqin Wu, Shuyan Wu, Hongmei Wu, Guangsen Wu, Xiaolin Wu, An Guo Wu, Kailang Wu, Chien-Sheng Wu, Chun-Hua Wu, Jemma X Wu, Wenqi Wu, Quanhui Wu, Qing-Wu Wu, Yanxiang Wu, Jiajin Wu, Qiao Wu, Yuan Kai Wu
articles
Xianchang Zeng, Lingyun Wei, Lu Lv +6 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
The molecular pathogenesis of lung adenocarcinoma (LUAD) involves genomic mutations, autophagy dysregulation, and signaling pathway disruptions. Autophagy, a key cellular process, is tightly linked to Show more
The molecular pathogenesis of lung adenocarcinoma (LUAD) involves genomic mutations, autophagy dysregulation, and signaling pathway disruptions. Autophagy, a key cellular process, is tightly linked to cancer development; genes like ATG5 and ATG10 influence lung cancer progression, and epigenetic regulators modulate autophagy-related carcinogenesis. However, the role of epigenetic-autophagy genes in LUAD's tumor microenvironment is under-researched. We used the "limma"" package to identify differential epigenetic-related genes associated with altered autophagy regulation (A-ERGs) in LUAD. Single-cell RNA sequencing was further employed to evaluate the heterogeneity of immune cells. Machine learning algorithms were utilized to construct and identify diagnostic markers for LUAD, which were then validated by receiver operating characteristic (ROC) curve analysis. Cell experiments, real-time PCR, and Western blot were conducted to verify the expression of KDM6B and KANSL1 and their effects on T-cell differentiation. Based on single-cell and transcriptome analyses, we screened 19 A-ERGs that were significantly differentially expressed in lung cancer tissues. These genes were primarily enriched in exhausted T cells. Subsequently, through machine learning, KDM6B and KANSL1 were identified to have excellent diagnostic performance. Single-cell level and transcriptome correlation analyses revealed that the expression of these two genes was associated with exhausted T cells. Results from In this study, we utilized bulk and single-cell transcriptomic data to uncover the potential molecular mechanisms of A-ERGs in lung cancer. We explored the characteristic distribution of these genes in the tumor immune microenvironment and identified two A-ERGs, KDM6B and KANSL1, as potential diagnostic biomarkers for lung adenocarcinoma (LUAD). Our findings offer novel strategies for targeted therapeutic interventions in LUAD. Show less
📄 PDF DOI: 10.3389/fphar.2025.1542338
KANSL1
Changliang Liu, Changteng Zhang, Ling Chen +5 more · 2025 · International journal of biological sciences · added 2026-04-24
Cognitive impairment caused by anesthesia and surgery is one of the most common complications with multiple etiologies that occurs in elderly patients. The underlying mechanisms are not fully understo Show more
Cognitive impairment caused by anesthesia and surgery is one of the most common complications with multiple etiologies that occurs in elderly patients. The underlying mechanisms are not fully understood, and there is a lack of therapeutic strategies. Increasing evidence has demonstrated that myelin loss, abnormal phosphorylation of the tau protein and neuronal apoptosis are substantial driving factors of cognitive deficits. However, the key regulatory factors involved in the pathology of postoperative cognitive dysfunction require further investigation. Herein, we identified a key regulator, Lingo1, whose expression significantly increased in hippocampal neurons after aged mice underwent unilateral nephrectomy. Elevated Lingo1 expression markedly activated the RhoA/ROCK1 signaling pathway through interactions with NgR and p75NTR, subsequently promoting myelin loss and abnormal phosphorylation of the tau protein. Moreover, the upregulation of Lingo1 in hippocampal neurons further inhibited the EGFR/PI3K/Akt pathway, which may increase neuronal apoptosis. These pathological changes ultimately lead to cognitive impairment in aged mice after surgery. Notably, Lingo1 knockdown significantly reversed pathological changes in the hippocampus and attenuated cognitive decline. In conclusion, our findings highlight that Lingo1 upregulation in hippocampal neurons promotes the occurrence and development of postoperative cognitive dysfunction by regulating myelin loss, abnormal tau phosphorylation and neuronal apoptosis, suggesting that Lingo1 might be a potential target for treating postoperative cognitive dysfunction. Show less
📄 PDF DOI: 10.7150/ijbs.98376
LINGO1
Xiao-Dong Li, Jun-Ming Zhu, Qi You +9 more · 2025 · Combinatorial chemistry & high throughput screening · Bentham Science · added 2026-04-24
Bladder cancer (BC) is one of the most common urological malignancies, ranking as the eleventh most common cause of cancer-related deaths worldwide. The lack of specific and sensitive prognostic bioma Show more
Bladder cancer (BC) is one of the most common urological malignancies, ranking as the eleventh most common cause of cancer-related deaths worldwide. The lack of specific and sensitive prognostic biomarkers presents a significant challenge in the early diagnosis and treatment of BC. We used the Gene Expression Omnibus (GEO) dataset GSE13507 and the Cancer Genome Atlas (TCGA) database to screen differentially expressed genes related to BC. By using Weighted Gene Co-expression Network Analysis (WGCNA), two modules associated with BC were investigated in GSE13507 and TCGA. Hub genes were identified through Protein-Protein Interaction (PPI) network analysis and their functions were validated through multiple approaches, including Gene Expression Profiling Interactive Analysis (GEPIA), Western Blotting (WB) assay, Human Protein Atlas (HPA), Oncomine analysis, and quantitative Real-Time PCR (qRTPCR) analysis. Additionally, miRNAs associated with hub gene expression were identified using various databases to predict the progression and prognosis of BC. WCGNA and differential gene expression analysis identified 171 common genes as target genes. Ten genes (MYH11, ACTA2, TPM2, ACTG2, CALD1, MYL9, TPM1, MYLK, SORBS1, and LMOD1) were identified using the PPI tool and the CytoHubba plugin of Cytoscape. The CALD1 and MYLK genes showed a significant prognostic value for overall survival and diseasefree survival in patients with BC. According to the HPA and Oncomine databases, CALD1 and MYLK expression levels were significantly lower in BC tissues than in normal tissues. Additionally, qRT-PCR analysis, WB assay, and immunohistochemical analysis confirmed CALD1 and MYLK as tumor suppressor genes in BC. Furthermore, miR-155 showed a significant positive correlation with MYLK. This study established MYLK as a direct target gene of miR-155, functioning as an actionable survival-related gene correlated with BC development. Show less
no PDF DOI: 10.2174/0113862073352389250407104347
LMOD1
Bingjie Wu, Xiaoyue Cheng, Ruimin Zheng +10 more · 2025 · Human reproduction open · Oxford University Press · added 2026-04-24
Does preconception mental health status in either partner affect fertility and infertility, and is this association modified by socioeconomic status (SES)? Preconception mental health problems in both Show more
Does preconception mental health status in either partner affect fertility and infertility, and is this association modified by socioeconomic status (SES)? Preconception mental health problems in both partners are associated with lower couple fertility, with the synergistic impact being most pronounced among couples with low SES status. Mental health problems are rising among young adults, and fertility rates are declining. Women's preconception mental health has been linked to lower fertility, but few studies have examined the combined impact of both partners' mental health. The modifying role of SES in these associations is also poorly understood. This couple-based prospective cohort study included 966 preconception couples who sought preconception care and were followed for 12 months in the Shanghai Birth Cohort between 2013 and 2015. The couples' mental health status was evaluated at enrolment using the Center for Epidemiological Studies-Depression Scale, Zung Self-Rating Anxiety Scale, and Perceived Stress Scale. The outcomes included couple fecundability (measured by the TTP) and infertility (i.e. TTP >12 menstrual cycles). In the partner-specific model, Cox proportional hazards models and logistic regression were used to evaluate the associations between each partner's depression, anxiety, and stress levels and couples' fertility. In the couple-based model, cross-classification and quantile g-computation were first applied to identify couples' joint exposure to specific psychological conditions in relation to fertility. Latent profile analysis (LPA) was then conducted to characterize distinct latent profiles of couples' overall mental health statuses, followed by Cox proportional hazards models and logistic regression to examine the corresponding associations. Key symptoms in the couples' depression, anxiety, and stress scales were determined by elastic net regression and least absolute shrinkage and selection operator. To assess the potential effect modification of SES on the association between couples' mental health and fertility, we conducted stratified analyses by male and female partner education levels and household income. In the female partner-specific model, a 1 SD increase in depression score was associated with 10% lower fecundability (FOR = 0.90, 95% CI: 0.82, 0.99). Likewise, a 1 SD increase in the stress score was associated with 13% lower fecundability (FOR = 0.87, 95% CI: 0.79, 0.96). Male anxiety was associated with a higher risk of infertility (OR = 1.19, 95% CI: 1.01, 1.42). Stratified analyses showed that depression, anxiety, and stress were significantly associated with lower fecundability among males with an education level Show less
📄 PDF DOI: 10.1093/hropen/hoaf071
LPA
Yuan Tian, Zhe Jia, Na Li +5 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
Psychological empowerment is a critical factor for employee work well-being, particularly within high-stress professions such as policing. However, experiences of empowerment among individuals are not Show more
Psychological empowerment is a critical factor for employee work well-being, particularly within high-stress professions such as policing. However, experiences of empowerment among individuals are not uniform. This study aims to identify distinct profiles of psychological empowerment among police officers and to examine their associations with perceived coworker support and work well-being. A person-centered approach was adopted. Data were collected from 505 Chinese police officers. Latent Profile Analysis (LPA) was employed to identify subgroups based on their psychological empowerment patterns. The analysis revealed two distinct profiles: a "Globally Disempowered" profile and a "Globally Empowered" profile. Perceived emotional support from coworkers was a significant predictor of profile membership, where higher levels of support increased the likelihood of belonging to the empowered group. Furthermore, officers in the high empowerment profile reported significantly greater work well-being compared to those in the low empowerment profile. The findings underscore the heterogeneity in psychological empowerment experiences within the policing context. They emphasize the pivotal role of fostering emotional peer support as a means to enhance officers' psychological empowerment and, consequently, their work well-being. Practical implications for organizational interventions are discussed. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1694664
LPA
Lin Hao, Xiangqiu Chen, Tao He +9 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Prostate adenocarcinoma (PRAD) is a common malignancy with marked clinical heterogeneity, complicating prognosis and disease monitoring. Traditional tools like the Gleason score lack molecular and mic Show more
Prostate adenocarcinoma (PRAD) is a common malignancy with marked clinical heterogeneity, complicating prognosis and disease monitoring. Traditional tools like the Gleason score lack molecular and microenvironmental insights, underscoring the need for biomarker-driven predictive models. Single-cell RNA-seq data from GEO and bulk RNA-seq data from TCGA were analyzed. scRNA-seq processing used the Seurat package, with cluster-specific genes identified via FindAllMarkers. Differentially expressed genes (DEGs) from bulk data were obtained using limma, and key gene modules were identified through WGCNA. Using univariate Cox regression and LASSO analysis, a prognostic model was developed based on cluster-specific genes, key module genes, and differentially expressed genes. Clinical validation included comparison of tumor and adjacent normal tissues, revealing significantly elevated GDPD3 expression, further confirmed by immunohistochemistry. In this study, through integrated single-cell sequencing and Bulk-RNA-seq analyses, we established a 21-gene prognostic model. QPCR confirmed significant upregulation of three candidates, including GDPD3, which was also elevatedin malignant tissues. Knockdown of GDPD3 inhibited tumor cell proliferation, invasion, and migration. Mechanistically, GDPD3 regulated the levels of lysophosphatidic acid (LPA), which in turn induced EMT in tumor cells. Inhibition or knockdown of the LPA receptor LPAR1 suppressed EMT. LPA promoted EMT through activation of the AKT signaling pathway, and inhibition of this pathway reversed LPA-induced EMT. This study underscores key molecular mechanisms underlying prostate cancer progression, with GDPD3 emerging as a potential therapeutic target. Show less
📄 PDF DOI: 10.3389/fimmu.2025.1637325
LPA
Jing Li, Yingli Luo, Zaihao Wu +2 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
The present study aimed to clarify heterogeneity in music performance anxiety (MPA) by identifying latent profiles, examining sociodemographic and psychological predictors of profile membership, and t Show more
The present study aimed to clarify heterogeneity in music performance anxiety (MPA) by identifying latent profiles, examining sociodemographic and psychological predictors of profile membership, and testing mediation pathways. A total of 819 Chinese musicians participated in an online survey that assessed MPA, performance worry (PW), and perceived memory reliability (PMR), along with demographic variables. Latent profile analysis (LPA) revealed a three-profile solution that distinguished low, moderate, and high MPA groups. Multinomial logistic regression indicated that older age, higher education levels, lower household income, and unstable employment were significantly associated with membership in the moderate and high MPA profiles. In addition, PW emerged as a significant psychological predictor of elevated MPA, whereas PMR showed a protective effect and was negatively associated with MPA. Mediation models further demonstrated that PW played an important role in transmitting the effect of PMR on MPA, suggesting that cognitive factors related to memory reliability shape worry processes, which, in turn, intensify performance anxiety. These findings advance understanding of MPA by demonstrating that Chinese musicians can be meaningfully categorized into distinct risk groups, each shaped by sociodemographic vulnerabilities and cognitive-emotional pathways. From a practical perspective, the results highlight the importance of targeted prevention and intervention strategies that address both memory-related cognitions and performance worry in order to reduce MPA in vulnerable populations. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1724226
LPA
Caixia Deng, Jingxing Liu, Xiaoqian Wu +4 more · 2025 · Behavioral sciences (Basel, Switzerland) · MDPI · added 2026-04-24
Problematic smartphone use (PSU) has become a growing concern among young populations, raising significant issues for their physical and psychological well-being. Guided by Compensatory Internet Use T Show more
Problematic smartphone use (PSU) has become a growing concern among young populations, raising significant issues for their physical and psychological well-being. Guided by Compensatory Internet Use Theory and the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study examined the associations between different forms of childhood trauma and PSU. Participants were 2717 college students (661 males, 22.49%; Mage = 19.81 years). Two chain mediation models were tested, and latent profile analysis (LPA) was employed to capture individual differences from a person-centred perspective. LPA revealed three distinct trauma profiles: low childhood trauma, moderate childhood abuse, and high childhood abuse. Across both variable-centred and person-centred ap-proaches, rumination and social anxiety were identified as mediators linking childhood trauma to PSU. These findings advance understanding of the pathways through which childhood trauma contributes to PSU in college students. By integrating variable- and person-centred approaches, the study highlights the importance of cognitive-emotional mechanisms and provides implications for targeted prevention and intervention strategies. Show less
📄 PDF DOI: 10.3390/bs15121676
LPA
Rongqing Li, Zikai Zhang, Xin Zhang +6 more · 2025 · BMC neurology · BioMed Central · added 2026-04-24
Symptom burden in primary brain tumor patients varies, emphasizing the need for comprehensive understanding to improve patient care. This study aims to identify distinct symptom clusters among brain t Show more
Symptom burden in primary brain tumor patients varies, emphasizing the need for comprehensive understanding to improve patient care. This study aims to identify distinct symptom clusters among brain tumor patients in Shanghai, China, using Latent Profile Analysis (LPA) to guide personalized diagnosis, treatment, and supportive care. A longitudinal study was conducted among 161 patients with primary brain tumors in Shanghai. Participants completed the MD Anderson Symptom Inventory Brain Tumor Module (MDASI-BT) at three intervals: the day of admission (T1), three days after surgery (T2), and two weeks after surgery (T3). Latent Profile Analysis (LPA) was used to identify subgroups with unique symptom patterns. Six distinct subgroups were identified (entropy = 0.964), ranging from low-burden to persistently severe patterns. Subgroup membership was partially associated with age, tumor grade, and diagnosis. These subgroups were: transient postoperative burden group, stable symptom with cognitive emergence group, distress-predominant, low burden group, elderly-high grade, persistently severe group, nausea-dominant recovery group, and distress-plus-nausea, younger urban group. Our findings reveal substantial heterogeneity in perioperative symptom experiences among brain tumor patients. Identifying subgroups with high and persistent symptom burden may help clinicians target interventions such as enhanced education, proactive monitoring, rehabilitation, psychological support, and antiemetic management. This subgroup-based approach may improve quality of life, reduce morbidity, and guide precision supportive care in neuro-oncology. Show less
📄 PDF DOI: 10.1186/s12883-025-04595-6
LPA
Yingnan Zhang, Yuanyuan Chen, Wenwen Guo +3 more · 2025 · BMC gastroenterology · BioMed Central · added 2026-04-24
Radiotherapy remains a valuable yet limited option for select colon cancer cases, with radioresistance representing a major clinical challenge. Lipidomics screening identified autotaxin (ATX), also kn Show more
Radiotherapy remains a valuable yet limited option for select colon cancer cases, with radioresistance representing a major clinical challenge. Lipidomics screening identified autotaxin (ATX), also known as ENPP2, as a key mediator of radiation-induced metabolic reprogramming. Radiation exposure upregulated ATX expression and its product lysophosphatidic acid (LPA), which activated the LPAR2-AKT signaling axis to support tumor cell survival. Pharmacological ATX inhibition with HA130 or genetic ATX knockdown enhanced radiosensitivity in vitro by suppressing proliferation and promoting apoptosis. In mouse models, both HA130 treatment and ATX knockdown significantly suppressed tumor growth and improved radiotherapy efficacy, as shown by reduced tumor volume, weight, and Ki67-positive cell counts. Clinically, elevated ATX-LPA pathway activity was associated with poor patient prognosis. These findings establish ATX as a promising therapeutic target for overcoming radioresistance in colon cancer, supporting the combination of ATX inhibition with radiotherapy to improve treatment outcomes. The online version contains supplementary material available at 10.1186/s12876-025-04578-4. Show less
📄 PDF DOI: 10.1186/s12876-025-04578-4
LPA
Lulu Wu, Ziqing Qi, Yue Zhang +5 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
To identify latent profiles of demoralization among older adults with disabilities, analyze their influencing factors, and examine their associations with active aging. From February to July 2025, a c Show more
To identify latent profiles of demoralization among older adults with disabilities, analyze their influencing factors, and examine their associations with active aging. From February to July 2025, a convenience sample of 411 older adults with disabilities was recruited from a tertiary hospital in Anhui Province, China. Data were collected using a general information questionnaire, the Chinese version of the Demoralization Scale, and the Active Aging Scale. Latent profile analysis (LPA) was performed based on demoralization subscale scores. Univariate and multinominal analyses were employed to investigate the influencing factors, and the Kruskal-Wallis The prevalence of demoralization syndrome was 49.1%. LPA identified three distinct profiles: the Well-Adapted Group (53.3%), the Disheartened-Helpless Group (23.8%), and the Fully Demoralized Group (22.9%). The Kruskal-Wallis Nearly half of the older adults with disabilities experienced demoralization, with heterogeneous subgroups identified. The active aging status of demoralized subgroups requires urgent attention. These findings suggest the need for targeted interventions tailored to the characteristics of each profile to improve mental health and promote active aging in this population. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1715566
LPA
Dongli Chen, Hong Zhang, Yuqi Xiu +5 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Stroke is a leading cause of mortality and disability globally, with post-stroke depression and post-stroke anxiety being common and significant complications that hinder recovery and adversely affect Show more
Stroke is a leading cause of mortality and disability globally, with post-stroke depression and post-stroke anxiety being common and significant complications that hinder recovery and adversely affect quality of life. Although these conditions frequently co-occur, their heterogeneity remains poorly understood. This study integrates the Health Ecology Model (HEM) and employs Latent Profile Analysis (LPA) to identify distinct psychological profiles of depression and anxiety among patients with acute ischemic stroke (AIS), as well as to investigate their multilevel determinants. Patients with AIS from a tertiary hospital in Guangdong Province, China, from January to November 2024 were included. Within one week of stroke onset, the data of sociodemographic, clinical characteristics, swallowing function, stroke severity, activities of daily living, resilience and social support were collected according to the HEM guidelines. The Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 were used to assess the depression and anxiety symptoms of the patients three months after stroke onset. LPA was employed to identify distinct psychological profiles, and variables with a A total of 551 patients with AIS were included in the study, 49 were lost to follow-up or withdrew, resulting in a final analytic sample of 502 participants (91.11%). Three distinct psychological profiles were identified: no depression-anxiety (67.93%), high-risk depression-anxiety (21.12%) and major depression-anxiety (10.95%). In the multivariate analysis, the results indicated that occupation (OR = 0.61, 95% CI [0.40-0.93]), National Institutes of Health Stroke Scale (NIHSS, OR = 1.60, 95% CI [1.06-2.42]), Barthel Index (BI, OR = 1.67, 95% CI [1.27-2.19]) and hypertension (OR = 2.37, 95% CI [1.29-4.35]) were independent predictors of the high-risk depression-anxiety profile, while NIHSS (OR = 2.33, 95% CI [1.42-3.85]), BI (OR = 2.65, 95% CI [1.62-4.35]) and resilience (OR = 0.92, 95% CI [0.87-0.98]) were significantly associated with the major depression-anxiety profile. This study reveals significant heterogeneity in psychological distress among AIS survivors. Key predictors of post-stroke emotional comorbidity include occupation, hypertension, stroke severity, activities of daily living and low resilience. Early identification of high-risk individuals can significantly enhance screening and intervention strategies, particularly by focusing on symptoms such as anhedonia and nervousness. Future research should focus on longitudinal designs and objective biomarkers to better understand the mechanisms behind post-stroke emotional comorbidity. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1651116
LPA
Jia-Cheng Liu, Rui Yang, Zan-Fei Feng +9 more · 2025 · Journal of the National Cancer Institute · Oxford University Press · added 2026-04-24
Cardiovascular-kidney-metabolic (CKM) syndrome significantly increases cancer and mortality risks, but the combined effects of CKM syndrome and physical activity (PA) on these outcomes remain poorly u Show more
Cardiovascular-kidney-metabolic (CKM) syndrome significantly increases cancer and mortality risks, but the combined effects of CKM syndrome and physical activity (PA) on these outcomes remain poorly understood. This prospective study included 66,650 UK Biobank participants with accelerometry data. CKM syndrome was classified into five stages based on metabolic, kidney, and cardiovascular health. PA was categorized by intensity into light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) levels, and further divided into tertiles by daily duration. Multivariable Cox models were used to estimate hazard ratios. Over a median follow-up of 8.03 years, 4,301 incident cancer cases and 2,442 deaths occurred. Advancing CKM stages were associated with elevated risks of both cancer incidence and all cause mortality, while increasing PA levels reduced these risks. Significant interactions were observed between CKM syndrome and both MPA and MVPA on cancer and mortality risks (P interaction < 0.05). In participants with the lowest tertile of MPA or MVPA, those in stages 2 and 4 had higher cancer risk, while in the highest tertile, this risk was no longer elevated. For all-cause mortality, in participants with the lowest tertile of MPA or MVPA, CKM stage 3 exhibited higher risks, while those in the highest tertile did not. CKM stage 4 remained associated with higher mortality across all PA intensity levels, but risks decreased with increasing MVPA levels. Higher levels of MPA and MVPA may mitigate the elevated risks of both cancer incidence and all-cause mortality associated with CKM stages 2 to 4. Show less
no PDF DOI: 10.1093/jnci/djaf365
LPA
Yue Cao, Nana Wu, Yanfen Liu +3 more · 2025 · Journal of applied gerontology : the official journal of the Southern Gerontological Society · SAGE Publications · added 2026-04-24
ObjectiveRespect for older adults (ROA) is shaped by multiple ecological systems and personal factors. However, little is known about the potential subgroups that may differ in their constellation of Show more
ObjectiveRespect for older adults (ROA) is shaped by multiple ecological systems and personal factors. However, little is known about the potential subgroups that may differ in their constellation of influencing factors and their association with ROA.MethodsThis cross-sectional study included 1,476 community-dwelling Chinese adults aged 18-83 years ( Show less
no PDF DOI: 10.1177/07334648251406350
LPA
Hanying Nie, Mingxiao Liu, Xinchun Wu · 2025 · Journal of interpersonal violence · SAGE Publications · added 2026-04-24
Individuals who experience adverse events during their early life stages are more likely to face negative consequences across various life domains throughout their lifespan. While latent profile analy Show more
Individuals who experience adverse events during their early life stages are more likely to face negative consequences across various life domains throughout their lifespan. While latent profile analysis has been increasingly applied to adverse childhood experiences (ACEs) worldwide, simultaneous prospective investigations of negative and positive posttraumatic outcomes in Chinese emerging adults remain scarce. The present study aimed to extend prior literature by: (a) assessing the latent profile groupings of ACEs among emerging adults, and (b) analyzing the prospective associations between latent profiles of ACEs and posttraumatic outcomes over a six-month interval, including complex posttraumatic stress disorder (CPTSD) symptoms and posttraumatic growth (PTG). From 3,994 college students who participated in 2 surveys 6 months apart, 1,814 participants (mean age: 18.93 ± 1.45) who reported ACEs were selected. The sample included 901 males (49.7%) and 913 females (50.3%). Data were collected through a two-wave online survey measuring ACEs, CPTSD symptoms, and PTG. The Latent Profile Analysis identified five ACE profiles: High neglect (14.9%), Moderate family dysfunction (46.3%), Moderate abuse (25.1%), High risk (8.5%), and Moderate maltreatment/High family dysfunction (5.2%). Moderate family dysfunction (Profile 2) and Moderate maltreatment/High family dysfunction showed better posttraumatic adaptation than others. The High-risk group had the worst outcomes, while the High neglect and Moderate abuse groups fared better than the High-risk group. This study provides valuable insights into the concurrent examination of ACEs and their impact on the CPTSD symptoms and PTG of emerging adults. It offers a foundation for developing tailored intervention strategies for affected groups. Show less
no PDF DOI: 10.1177/08862605251396893
LPA
Dapeng Zhang, Lulu Zhang, Juan Long +10 more · 2025 · Quantitative imaging in medicine and surgery · added 2026-04-24
Pulmonary embolism is a potentially fatal cardiovascular condition that demands prompt and accurate diagnostic imaging. Traditional single-energy computed tomography pulmonary angiography (CTPA), whil Show more
Pulmonary embolism is a potentially fatal cardiovascular condition that demands prompt and accurate diagnostic imaging. Traditional single-energy computed tomography pulmonary angiography (CTPA), while widely used, is associated with high radiation doses and substantial volumes of contrast agents, which may increase the risks of radiation-induced tissue damage and contrast-induced nephropathy (CIN), respectively. Dual-energy CTPA (DE-CTPA) presents a promising alternative, though challenges, including elevated image noise at low kilo-electron volt (keV) levels (e.g., 40 keV), persist. The primary aim of this study is to evaluate and compare the image quality of 40 keV virtual monoenergetic images (VMI) reconstructed using deep learning image reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-V (ASIR-V) algorithms within the context of low-dose DE-CTPA protocols. This prospective study enrolled patients who underwent DE-CTPA between January and April 2025. Using a Revolution CT scanner, 40 keV VMI were reconstructed with four distinct algorithms: ASIR-V 50%, ASIR-V 70%, Deep learning image reconstruction with medium setting (DLIR-M), and deep learning image reconstruction with high setting (DLIR-H). Iodixanol (350 mgI/mL) was administered at a dose of 0.4 mL/kg. The image quality was assessed through both objective measures [image noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR)] and subjective evaluation via a Likert scale. Statistical analysis was conducted using SPSS 27.0, employing analysis of variance (ANOVA) for normally distributed data and the Kruskal-Wallis test for non-normally distributed data. A total of 75 patients with clinical suspicion of pulmonary embolism were included in the study. The mean effective dose (ED) was 3.76±1.02 mSv, with a mean CT volume dose index (CTDIvol) of 6.13±1.69 mGy and a mean dose-length product (DLP) of 221.12±59.85 mGy·cm. The mean contrast agent volume was 26.0±5.0 mL. Statistical analysis of image quality revealed significant differences between the four groups in terms of image noise, CNR, and SNR, measured at the levels of the main pulmonary artery, left pulmonary artery, and right pulmonary artery (P<0.001). Post-hoc analysis demonstrated that the DLIR-H algorithm provided the highest image quality, significantly reducing noise while enhancing CNR and SNR relative to both ASIR-V and DLIR-M (P<0.001). Compared with ASIR-V 50%, DLIR-H reduced image noise by 45% at the PA [24.25±16.18 The DLIR-H algorithm significantly enhances the image quality of 40 keV VMI images under low-dose DE-CTPA scanning protocols. It outperforms DLIR-M, ASIR-V 50%, and ASIR-V 70%, making it a promising tool for improving image quality in CTPA, particularly in clinical settings where minimizing radiation dose and contrast agent volume is essential. Show less
📄 PDF DOI: 10.21037/qims-2025-1420
LPA
Hui-Hui Liu, Chen-Xi Song, Sha Li +12 more · 2025 · MedComm · Wiley · added 2026-04-24
This study aimed to investigate the effect of lipoprotein(a) (Lp(a)) on major adverse cardiovascular events (MACEs) among individuals with chronic coronary syndrome (CCS) according to ABO blood groups Show more
This study aimed to investigate the effect of lipoprotein(a) (Lp(a)) on major adverse cardiovascular events (MACEs) among individuals with chronic coronary syndrome (CCS) according to ABO blood groups. Two independent cohorts of patients with CCS were included consecutively. Blood groups and Lp(a) levels were measured. Patients with the AB group were excluded due to the small sample size. In the exploratory cohort ( Show less
📄 PDF DOI: 10.1002/mco2.70505
LPA
Chenxuan Liu, Xinyi Zhang, Wenxue Wu +1 more · 2025 · Comprehensive Physiology · Wiley · added 2026-04-24
Lipokines are a class of lipid-derived signaling molecules, playing essential roles in regulating metabolic homeostasis and systemic metabolism. In this review, we first comprehensively describe six m Show more
Lipokines are a class of lipid-derived signaling molecules, playing essential roles in regulating metabolic homeostasis and systemic metabolism. In this review, we first comprehensively describe six major lipokines, including palmitoleic acid (C16:1n7), 12,13-dihydroxy-9Z-octadecenoic acid (12,13-diHOME), fatty acid esters of hydroxy fatty acids (FAHFAs), 12-hydroxyeicosapentaenoic acid (12-HEPE), lysophosphatidic acid (LPA), and 15-hydroxyeicosatetraenoic acid (15-HETE), focusing on their mechanistic roles in energy metabolism and inflammatory modulation as well as their cross-talk within different signaling pathways. These lipokines collectively contribute to metabolic homeostasis by regulating multiple pathways, including insulin signaling, AMPK activation, inflammatory modulation, and G-protein-coupled receptor-mediated pathways. Furthermore, we clarify the associations between lipokines and various diseases such as obesity, type 2 diabetes, cardiovascular diseases, non-alcoholic fatty liver disease, inflammatory disorders, and cancer, and discuss their potential as biomarkers and therapeutic targets. Despite current challenges, including functional complexity, limitations of model systems, and difficulties in clinical translation, lipokines demonstrate promising prospects in the prevention and treatment of metabolic diseases and application in precision medicine. Future research should prioritize the elucidation of the specific action mechanisms of different lipokines, development of highly sensitive detection methodologies, and large-scale clinical trials to facilitate the translation of the research results into practical medical applications. Show less
no PDF DOI: 10.1002/cph4.70072
LPA
Chenhao Xu, Junjie Zhao, Kan Wu +9 more · 2025 · Frontiers in nutrition · Frontiers · added 2026-04-24
Acquired renal cysts (ARC) are associated with kidney function decline, necessitating novel dietary pattern (DP) analyses in large cohorts. This UK Biobank prospective cohort study (2006-2010) include Show more
Acquired renal cysts (ARC) are associated with kidney function decline, necessitating novel dietary pattern (DP) analyses in large cohorts. This UK Biobank prospective cohort study (2006-2010) included participants with ≥2 dietary records, excluding those with severe kidney damage. The constructed comprehensive dietary pattern integration (CDPI) utilized reduced rank regression (RRR) and latent profile analysis (LPA). ARC cases (ICD-10: N28.1) were assessed via Cox regression for risk and dose-response, with NMR metabolites examined as mediators. Among 119,709 participants (median follow-up: 10.57 years), 850 ARC cases were identified. Lipid-rich and hyperglycemic diets increased ARC risk [e.g., HRs for G1.DP1: 1.080 (1.024, 1.139); G1.DP2: 1.144 (1.048, 1.249)], while micronutrient-rich diets showed weak protective effects [G4.DP1: 0.943 (0.892, 0.998)]. LPA confirmed RRR findings, and 7/251 NMR metabolites had significant mediating effects. Diets high in fat (cheese, butter, pizza) and sugar (chocolate, sugary drinks) elevated ARC risk, whereas micronutrient- and fiber-rich diets (vegetables, fruit, lean poultry, nuts, eggs) were protective. Key mediators included branched-chain amino acids, IGF-1, and RBC distribution width. Show less
📄 PDF DOI: 10.3389/fnut.2025.1611656
LPA
Ruijia Xue, Jiali Liu, Haoyang Wang +5 more · 2025 · Circulation. Cardiovascular imaging · added 2026-04-24
Lp(a) (lipoprotein [a]) and coronary artery calcium score (CACS) are independently associated with atherosclerotic cardiovascular disease (ASCVD) risk. This study aimed to investigate sex-specific pro Show more
Lp(a) (lipoprotein [a]) and coronary artery calcium score (CACS) are independently associated with atherosclerotic cardiovascular disease (ASCVD) risk. This study aimed to investigate sex-specific prognostic differences between Lp(a) and CACS in ASCVD risk. We analyzed 4651 participants from the Multi-Ethnic Study of Atherosclerosis, grouped by sex. Multivariable Cox regression analysis was performed to evaluate the prognostic value of Lp(a) and CACS for ASCVD risk in both sexes. The predictive performance of these factors was compared in men and women. During a median follow-up of 13.84 years, 465 ASCVD events were recorded (272 in men and 193 in women). Multivariable Cox regression analysis revealed that both elevated Lp(a) and CACS were independent predictors of ASCVD risk in both sexes. The C-index analysis demonstrated that CACS provided incremental prognostic value over Lp(a) in men (C-index: 0.732 versus 0.714; Although both Lp(a) and CACS independently predict ASCVD risk in both sexes, the predictive value of Lp(a) varies significantly between men and women across different CACS categories. These findings may inform sex-specific strategies for primary prevention of ASCVD. Show less
no PDF DOI: 10.1161/CIRCIMAGING.125.018413
LPA
Lan Yang, Jinghua Yang, Hong Zhang +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. H Show more
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. However, there remains a significant gap in studies specifically addressing the eHL needs of patients with maintenance hemodialysis (MHD). This study aims to explore the latent categories of eHL among MHD patients and its impact on health-promoting lifestyle (HPL). A survey was conducted using a convenience sampling method involving 500 MHD patients from three tertiary hospitals in Baoding. Data were analyzed using latent profile analysis (LPA) and a mixed regression model. This study showed that MHD patients could be classified into low (23.17%), middle (49.78%), and high (27.05%) eHL groups, with the three-class model showing optimal fit (AIC = 2321.213, BIC = 2271.168, entropy = 0.967). MHD Patients in the high literacy group scored significantly higher in all dimensions of e-HL and overall HPL (119.58 ± 13.86) compared to those in the low literacy group (91.82 ± 11.73) (all The findings suggest a heterogeneous stratification of eHL among MHD patients, closely linked to HPL. Stratified intervention strategies should be developed for different patient groups to potentially improve their health behaviors. The study provides evidence-based support for personalized health management. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1630350
LPA
Yu Peng, Yiqing Gao, Lin Huang +10 more · 2025 · Sleep & breathing = Schlaf & Atmung · Springer · added 2026-04-24
Previous studies showed that obstructive sleep apnea (OSA) is associated with dyslipidemia. However, whether micro-arousals during rapid eye movement (REM) and non-rapid eye movement (NREM) sleep inde Show more
Previous studies showed that obstructive sleep apnea (OSA) is associated with dyslipidemia. However, whether micro-arousals during rapid eye movement (REM) and non-rapid eye movement (NREM) sleep independently associated with dyslipidemia were unknown. 4472 participants with OSA-related symptoms were finally included in our cohort. Various sleep variables including micro-arousal index (MAI) were obtained from standard polysomnography (PSG) recordings. Fasting serum lipid levels were assessed at our hospital laboratory. Linear regression models were employed to investigate relationships between micro-arousals in REM and NREM sleep and lipid profile with adjusting for multiple confounding factors. Fully adjusted models demonstrated a significant dose-dependent positive correlation between the MAI during REM sleep (MAI MAI Show less
📄 PDF DOI: 10.1007/s11325-025-03470-5
LPA
Yuanpeng Zhu, Di Liu, Xiangjie Yin +3 more · 2025 · The spine journal : official journal of the North American Spine Society · Elsevier · added 2026-04-24
Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preventing back pain. Moreover, accelerometer-based evidence regarding dose Show more
Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preventing back pain. Moreover, accelerometer-based evidence regarding dose-response relationships and interactions between PA and genetic susceptibility remains limited. To determine the relationships between accelerometer-measured total and intensity-specific PA and incident back pain, and to assess potential effect modification by polygenic risk scores (PRS). Prospective, large-scale, population-based study using UK Biobank data. UK Biobank participants who wore wrist accelerometers for 7 days (N=71,601). Incident back pain, defined as the first recorded ICD-10 dorsalgia code (M54). Total PA, light PA (LPA), and moderate-to-vigorous PA (MVPA) were derived using validated machine-learning algorithms from raw accelerometer data. Dose-response relationships were modeled using restricted cubic splines within Cox proportional hazards models, with adjustment for and stratification by a polygenic risk score (PRS). Point estimates for the population attributable fraction (PAF) were then calculated. Body mass index (BMI) mediation was assessed. Over a median follow-up of 7.0 years, total PA and MVPA exhibited nonlinear inverse associations with incident back pain, independent of genetic risk, with thresholds at approximately 35 milli-g (total PA) and 60 min/day (MVPA). The adjusted PAF was 15.9% for low MVPA and 9.9% for low total PA. Associations were strongest for MVPA, followed by total PA; no significant association was observed for LPA. Within both PRS strata, risk declined monotonically across PA quartiles, with similar effect sizes and no PA × PRS interaction. Notably, participants with high PRS and high PA had lower risk than those with low PRS and low PA. BMI mediated 26.2% of the total PA association and 15.5% of the MVPA association. Accelerometer-measured MVPA robustly reduces back-pain risk, independent of genetic predisposition. Future guidelines should provide clear, intensity-specific recommendations and account for the observed nonlinear dose-response to optimize prevention. Show less
no PDF DOI: 10.1016/j.spinee.2025.10.021
LPA
Jingxian Yu, Mingjie Wu, Yongqi Liang +3 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profil Show more
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profiles of death anxiety in Chinese youth and examine the predictive roles of self-esteem, perceived social support, and security. We conducted a cross-sectional survey of 623 young adults ( Three latent death anxiety profiles emerged, High Death Anxiety (56.2%), Moderate Cognition and Low Death Anxiety (8.8%), and Low Cognition and Moderate Death Anxiety (35%). Higher self-esteem ( Death anxiety among young adults is heterogeneous, influenced by distinct psychological profiles and demographic factors. Interventions should prioritize enhancing self-esteem, social support networks, and security to mitigate death anxiety, especially in high-risk subgroups. Future research should employ longitudinal designs and cross-cultural samples to validate causal pathways and refine targeted strategies. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1594720
LPA
Yanling Du, Chao Wu, Ziyue Gai +6 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
This study aimed to explore the career adaptability status of cardiovascular specialist nurses (CSNs) through latent profile analysis (LPA), identify distinct subgroups and their demographic features, Show more
This study aimed to explore the career adaptability status of cardiovascular specialist nurses (CSNs) through latent profile analysis (LPA), identify distinct subgroups and their demographic features, and determine factors influencing different adaptability categories. CSNs play a vital role in treating and rehabilitating patients with cardiovascular conditions. However, the existing literature offers limited insights into the career adaptability of CSNs in China. A multicenter, cross-sectional survey involving 659 Chinese CSNs was conducted. LPA was utilized to classify career adaptability profiles based on responses to the Career Adaptation Abilities Scale Short Form (CAAS-SF). Influencing factors were assessed using the Conditions of Work Effectiveness Questionnaire-II (CWEQ-II) and the General Self-Efficacy Scale (GSES). Differences among identified profiles were analyzed through ANOVA, chi-square tests, and multinomial logistic regression to explore relevant socio-demographic characteristics and influencing variables. A four-profile model provided the best fit, identifying groups labeled as “high adaptability” (Class 4, These findings provide evidence to assist nursing administrators in developing training programs to enhance CSNs’ career adaptability. The variables identified as associated with profile membership may enable more tailored training strategies. Show less
📄 PDF DOI: 10.1186/s12912-025-03887-z
LPA
Jia-Xin Xu, Ye Wu, Lin Zhang +3 more · 2025 · World journal of cardiology · added 2026-04-24
Coronary heart disease (CHD) is a prominent cause of mortality and disability worldwide. Like most complex diseases, the risk of CHD in individuals is regulated by the interaction between genetic fact Show more
Coronary heart disease (CHD) is a prominent cause of mortality and disability worldwide. Like most complex diseases, the risk of CHD in individuals is regulated by the interaction between genetic factors and lifestyle. To investigate the influence of A total of 324 patients with CHD and 143 control participants were involved in this study. Single nucleotide polymorphisms rs429358 and rs7412 in the In the CHD group, the frequencies of In the Teochew population, the Show less
📄 PDF DOI: 10.4330/wjc.v17.i9.110278
LPA
Liqin Yu, Manyu Sun, Harrison Hao Yang +2 more · 2025 · Inquiry : a journal of medical care organization, provision and financing · SAGE Publications · added 2026-04-24
This study examines how distinct Information and Communication Technology (ICT) engagement profiles impact life satisfaction among older adults, aiming to inform digital inclusion policies for aging p Show more
This study examines how distinct Information and Communication Technology (ICT) engagement profiles impact life satisfaction among older adults, aiming to inform digital inclusion policies for aging populations. Cross-sectional data from 717 older adults in Central China were analyzed using latent profile analysis (LPA) to identify distinct ICT engagement profiles, followed by multinomial logistic regression to examine predictors of profile membership. LPA identified 3 profiles: Quiescent (39.75%), Compliant (42.96%), and Active (17.29%) Users. Active Users reported significantly higher life satisfaction ( Show less
📄 PDF DOI: 10.1177/00469580251375846
LPA
Chen-Ling Kuo, Chih-Chung Wu, Yu-Shan Cheng +3 more · 2025 · Lipids in health and disease · BioMed Central · added 2026-04-24
This study investigated the metabolic and pathological effects of a high-fat diet (HFD) in db/db mice and evaluated the therapeutic efficacy of various Coenzyme Q10 (CoQ10) products. We aimed to deter Show more
This study investigated the metabolic and pathological effects of a high-fat diet (HFD) in db/db mice and evaluated the therapeutic efficacy of various Coenzyme Q10 (CoQ10) products. We aimed to determine whether HFD-induced mitochondrial damage can be improved by different CoQ10 products through either repairing mitochondrial injury or increasing mitochondrial bioenergy, thereby addressing the root cause of oxidative stress. Plasma biochemical analyses revealed that HFD induced hyperglycemia, elevated hepatic transaminases [aspartate aminotransferase (AST), alanine aminotransferase (ALT)], and dyslipidemia. Lecithin coenzyme Q10 (SoQ10) significantly improved these parameters, especially in reducing AST (255 ± 73.8 U/L vs. 138 ± 29.4 U/L, p < 0.05), ALT (87.8 ± 17.3 U/L vs. 79.2 ± 11.9 U/L, p < 0.05), and triglyceride levels (142.0 ± 37.0 mg/dL vs. 15.5 ± 2.5 mg/dL, p < 0.05), demonstrating greater efficacy than standard CoQ10. Histological evaluation showed that HFD caused marked hepatic steatosis and inflammatory infiltration. Oil Red O staining further confirmed excessive lipid deposition in the livers of HFD-fed mice. Both Q10 treatments decreased lipid droplet accumulation (p < 0.05), with SoQ10 showing a greater reduction (p < 0.05), indicating its potential to alleviate hepatic steatosis. Further assessments indicated that gene expression analyses showed that HFD upregulated lipid metabolism-related genes [lipoprotein lipase (LPL), peroxisome proliferator-activated receptor-γ (PPAR-γ), sterol regulatory element-binding protein-1 (SREBP-1), alkaline ceramidase 2 (ACER2)] (p < 0.05), indicating an imbalance between lipogenesis and lipolysis. SoQ10 modulated these genes and further enhanced ceramide synthase 2 (CERS2) expression, suggesting a role in reestablishing hepatic lipid homeostasis. Additionally, SoQ10 significantly upregulated genes associated with mitochondrial biogenesis peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α), mitochondrial transcription factor A (TFAM)] (p < 0.05) and mitochondrial dynamics [mitofusin-2 (MFN2), optic atrophy type 1 long isoform (OPA1-L)] as well as fission [dynamin-related protein 1 (DRP1), mitochondrial fission protein 1 (Fis1)] (p < 0.05), indicating a potential to restore mitochondrial structural balance. In contrast, conventional CoQ10 had a more limited effect, particularly on fusion-related gene expression. SoQ10 demonstrated superior therapeutic potential over conventional CoQ10 in ameliorating hepatic metabolic dysfunction, oxidative mitochondrial damage, and disturbances in lipid metabolism and mitochondrial dynamics induced by a high-fat diet. Show less
📄 PDF DOI: 10.1186/s12944-025-02835-9
LPL
Jiayi Chen, Yongmei Wu, Jianhua He +5 more · 2025 · Nutrients · MDPI · added 2026-04-24
This experiment investigated the response of carcass composition, digestive function, hepatic lipid metabolism, intestinal microbiota, and serum metabolomics to excessive or restrictive dietary energy Show more
This experiment investigated the response of carcass composition, digestive function, hepatic lipid metabolism, intestinal microbiota, and serum metabolomics to excessive or restrictive dietary energy in Ningxiang pigs. A total of 36 Ningxiang pigs (210 ± 2 d, 43.26 ± 3.21 kg) were randomly assigned to three treatments (6 pens of 2 piglets each) and fed a control diet (CON, digestive energy (DE) 13.02 MJ/kg,), excessive energy diet (EE, 15.22 MJ/kg), and restrictive energy diet (RE, DE 10.84 MJ/kg), respectively. Results showed that EE significantly increased the apparent digestibility of crude protein and total energy ( The findings suggest RE had no obvious negative effect on carcass traits of Ningxiang pigs. Apart from exacerbated body fat deposition, EE promoted fat accumulation in the liver by up-regulating the expression of lipogenic genes. Dietary energy changes affect hepatic bile acid metabolism, which may be mediated through the glycerophospholipid metabolism pathway, as well as disturbances in the gut microbiota. Show less
📄 PDF DOI: 10.3390/nu17233648
LPL
Lei He, Zihao Chen, Tianwei He +5 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
The balance between adipogenic and osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) is essential for maintaining bone homeostasis. This study aimed to investigate the role of r Show more
The balance between adipogenic and osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) is essential for maintaining bone homeostasis. This study aimed to investigate the role of retinoid-related orphan receptor α (RORα) in the adipogenic differentiation of BMSCs. Stable BMSC lines with RORα overexpression or knockdown were established. Adipogenic differentiation was evaluated using Oil Red O staining and by measuring the expression of adipogenic markers, including PPARγ2, LPL, LEP, FABP4, and ADIPOQ. Treatment with the RORα inhibitor SR3335 significantly promoted adipogenic differentiation, whereas the RORα agonist SR1078 exerted the opposite effect. Similarly, RORα-overexpressing (OE-RORα) BMSCs showed reduced adipogenic differentiation, while RORα knockdown BMSCs exhibited enhanced differentiation at 14 days after induction. During adipogenesis, PPARγ2 expression increased significantly, peaking at day 6 before gradually declining. Overexpression and knockdown of RORα accentuated this downregulation and upregulation, respectively, at days 6 and 12. The adipogenic marker genes lipoprotein lipase (LPL), leptin (LEP), fatty acid binding protein 4 (FABP4), and adiponectin C1Q and collagen domain containing (ADIPOQ) were markedly downregulated in RORα-overexpressing BMSCs at day 12. Moreover, RORα overexpression enhanced β-catenin nuclear translocation at day 1 post-induction and upregulated downstream WNT/β-catenin signaling molecules (Axin2, c-Myc, CD44) at day 6. Inhibition of WNT/β-catenin signaling with XAV-939 effectively reversed the suppressive effect of RORα overexpression on adipogenic differentiation and restored the expression of adipogenesis-related genes. RORα suppresses adipogenic differentiation of BMSCs, at least in part, by activating WNT/β-catenin signaling. Show less
📄 PDF DOI: 10.1186/s40001-025-03325-5
LPL