👤 Yingxia Wu

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Also published as: Jiake Wu, Ming-Jiuan Wu, Yijian Wu, Siying Wu, Fong-Li Wu, Chih-Chung Wu, Jin'en Wu, Zixiang Wu, D P Wu, Zhongwei Wu, Haiping Wu, Geyan Wu, Qi-Zhu Wu, Jianjin Wu, Shwu-Yuan Wu, Su Wu, Xiaodi Wu, Changxin Wu, Kuen-Phon Wu, Zhiping Wu, Guofeng Wu, Xiaojun Wu, Qibing Wu, Cheng-Hsin Wu, Xiaoting Wu, Junhua Wu, Wenze Wu, Hong Wu, Yandi Wu, Zhong 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, Sijie Wu, Minqing Wu, Geng-ze Wu, Kun Wu, Cheng-Hua Wu, Shaofei Wu, Zhaoyang Wu, Qihan Wu, Kunling Wu, R Ryanne Wu, Hao Wu, Mingxuan Wu, Pei Wu, Wendy Wu, Yukang Wu, Jingtao Wu, Douglas C Wu, Guizhen Wu, Zhangjie Wu, Lili Wu, Jianwu Wu, Biaoliang Wu, Min-Jiao Wu, Huan Wu, Shengxi Wu, Fei-Fei Wu, Peih-Shan Wu, Guoqing Wu, Yu-Yuan Wu, Pei-Yu Wu, Jing Wu, Geting Wu, Lun-Gang Wu, Dongzhe Wu, G Wu, Junlong Wu, Jia-Jun Wu, Jiangyue Wu, Muzhou Wu, Jian-Qiu Wu, Junzhu Wu, Ray-Chin 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, Bian Wu, Limeng Wu, Jason Wu, Shuying Wu, Zhibing Wu, Caihong Wu, Naqiong Wu, Joseph C Wu, Huating Wu, Tianhao Wu, Zhi-Hong Wu, Congying Wu, Gaojun Wu, Dongping Wu, Chiao-En Wu, Li Wu, Haixia Wu, Yihang Wu, Shaoxuan Wu, Fanchang Wu, Gen Wu, Xiaorong Wu, Mingjie Wu, Mei Wu, Jiahao Wu, Jiapei Wu, Lingqian Wu, Jia Wu, Fangge Wu, Yanhui Wu, Sen-Chao Wu, Zhiqiang Wu, Sarah Wu, Shugeng Wu, Xuanqin Wu, Dongmei Wu, Caiwen Wu, Junjing Wu, Jiangdong 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, Yixuan Wu, Leilei Wu, Qinglin Wu, Bin Wu, Tianqi Wu, Shiya Wu, Hui-Chen Wu, Jian Wu, Cong Wu, Sijun 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, Biwei Wu, Yueling Wu, Xinrui Wu, Xing Wu, Jiayi Wu, Hua Wu, Bingjie Wu, Yuen-Jung 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, Yulian Wu, Han Wu, Lipeng Wu, Zhihao Wu, Jiexi Wu, Anna H Wu, Qiu Wu, Huazhen Wu, Yaqin 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, Guoli Wu, Zhenfeng 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, Run Wu, Xiaohong Wu, Zaihao Wu, Yu-Ke Wu, Chaowei Wu, Xinjing Wu, Anyue Wu, Xuan Wu, Meili Wu, Shu Wu, Yun 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, Huiwen Wu, Linmei Wu, Zhenzhou Wu, Yuhong Wu, Liang Wu, Liyan Wu, Kuan-Li Wu, Pei-Ting Wu, Xiao-Jin Wu, Terence Wu, Lifeng Wu, Shujuan Wu, Gang Wu, Xue-Mei Wu, Szu-Hsien Wu, Yan-ling Wu, Xiaokang Wu, Lingyan Wu, Yih-Jer Wu, Xinghua Wu, Chunfu Wu, Rongling Wu, Xifeng Wu, Jinhua Wu, Sihan Wu, Ming-Yue Wu, Shiyang Wu, K D Wu, Luyan Wu, Jinmei Wu, Shin-Long Wu, Shuai Wu, Zhipeng Wu, Zhixiang Wu, Guangzhen 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, Dengying Wu, Anke 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, Jianzhi Wu, Nana 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, Guanming Wu, Sean M Wu, Yongqun 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, Ting-Ting Wu, D Wu, Xiao-Yan Wu, Lan Wu, J Wu, Changchen Wu, Qi-Fang Wu, Changwei Wu, Liangyan Wu, Liufeng Wu, Kan Wu, Mingming Wu, Eugenia Wu, Xiaolong Wu, Chunru Wu, Zhaofei Wu, Shenhao Wu, Li-Peng Wu, Yuna Wu, Minna Wu, Justin Che-Yuen Wu, Buling Wu, Chengyu Wu, Wutian 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, Maoqing Wu, Zuping Wu, Julian Wu, Chun-Chieh Wu, Binbin Wu, Xiaohui Wu, Qian Wu, Xinchun Wu, Shuisheng Wu, Linxiang Wu, Xueqing Wu, Bo Wu, Moxin Wu, Xiao-Cheng Wu, Anzhou Wu, Shuyi Wu, Jiahui Wu, Meiqin Wu, Jer-Yuan Wu, Shihao Wu, Wen-Shu Wu, Wudelehu Wu, Ruonan Wu, Song Wu, Yulin Wu, De-Fu 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, Yawei Wu, Shixin Wu, Hong-Mei Wu, Yiqun Wu, Jiarui Wu, Xiaojin Wu, Tsung-Teh Wu, Qi-Nian Wu, Ju Wu, Kai-Yue Wu, Xi-Chen Wu, Pengjie Wu, Zhe Wu, Shaoping Wu, Zhou Wu, Han-Jie Wu, Haijiang Wu, Weijie 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, Tiantian Wu, Hai-Yan Wu, Chong Wu, Hongxian Wu, Daoyuan Wu, Zongfu Wu, Ling Wu, Yuxiang Wu, Xilong Wu, Yuyu Wu, Fengming Wu, Huijian Wu, Zong-Jia 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, Ming J Wu, Jie 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, Liuying Wu, Mingxing 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, Yongqi Wu, Ruihong Wu, Huini Wu, Guang-Long Wu, Lingyun Wu, Po-Chang Wu, Qinghua Wu, Ru-Zi Wu, Wenxue 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, Dapeng Wu, Wen-Hui Wu, Bing Wu, Wen-Sheng Wu, Yunpeng Wu, Li-Ling Wu, Xiao-Yuan Wu, Baiyan Wu, Qiu-Li 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, Weida Wu, Guo-Chao Wu, Qi-Jun 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, Riping Wu, J-Z Wu, Guangjie Wu, Pengfei Wu, Jundong Wu, Jianying Wu, Meng-Ling Wu, Beier Wu, Lingxiang Wu, Jamie L Y Wu, Xilin Wu, Keija Wu, Yanhua Wu, An-Li Wu, Chengbiao Wu, Yi-Ming Wu, Huanghui Wu, Dong-Feng Wu, Kunsheng Wu, Zhengcan Wu, Yuxin Wu, Kun-Rong Wu, Dong-Fang Wu, Guanxian Wu, Sensen Wu, Guifen Wu, Yifeng Wu, Tzu-Chun Wu, Pin Wu, Qingping Wu, R M Wu, Mian 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, Meng-Hsun Wu, Pei-Ei Wu, Yingying Wu, S M Wu, Xiangwei Wu, Guangrun Wu, Liuxin Wu, Yangyu Wu, Jia-Hui Wu, Jin-Zhen Wu, S L Wu, Shaohuan Wu, June K Wu, Yanli 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, Tingqin Wu, Jianming Wu, P L Wu, Yih-Ru Wu, Lanlan Wu, Jianjun Wu, Jianguang Wu, An-Xin 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, Wu-Tian Wu, Shenyue Wu, Qianwen Wu, Ye Wu, Lixing Wu, Gui-Qin 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, Zhenlong Wu, B Wu, Fang Wu, Guanzhong Wu, Liqun Wu, Guifu Wu, Zhikang Wu, Chris Y Wu, Qi-Yong Wu, Qingshi Wu, Zhao-Yang Wu, Chih-Ching Wu, Man-Jing Wu, Jun Wu, Jinhui Wu, Jincheng Wu, Linhong Wu, Hung-Tsung Wu, Tangchun Wu, Xinglong Wu, Zhen-Yang Wu, Ma Wu, Yin Wu, Dongyan 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, Jing-Wen Wu, Zhongyang 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, Xing-De Wu, Ying-Ting Wu, Mingfu Wu, Yucan Wu, Na-Qiong Wu, Xuhan Wu, Linzhi Wu, Jinze Wu, H J Wu, Dirong Wu, Ruize Wu, Yaohong Wu, Chung-Yi Wu, Jianyi Wu, Jugang Wu, Jiao Wu, Liang-Huan Wu, Xueling Wu, Ruying Wu, Gen Sheng Wu, Zhaoyuan Wu, Shiwen Wu, Andong Wu, Yu-Ling Wu, Hsan-Au Wu, Jia-Qi Wu, Yanting Wu, Xihai 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, Yihe Wu, Tiange Wu, Shuang Wu, Jiayu Wu, Chia-Lung Wu, Yaojiong Wu, Shengnan Wu, Zhuoze Wu, Y Y Wu, Y Wu, Zimu Wu, Depei Wu, Yi-Hua Wu, Haiyun Wu, Yanyan Wu, Min Wu, Wenjuan Wu, Jinfeng Wu, Guangxi Wu, Junjie Wu, Yawen Wu, Pinglian Wu, Hui-Hui Wu, Xunwei Wu, Xuefeng Wu, Constance Wu, Depeng Wu, Dianqing Wu, Qibiao Wu, Nan Wu, Hao-Tian 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, Xin-Xi Wu, Guanyi 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, Cho-Kai Wu, Meng-Han Wu, Hon-Yen Wu, Yuguang Philip Wu, Anguo Wu, Hai-Yin Wu, Yicheng Wu, Xiaolang Wu, Yujie Wu, Qing Wu, V C Wu, Haomin 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, Yingning Wu, S-F Wu, David Wu, Joshua L Wu, Mei-Na 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, Yanran Wu, Xianfeng Wu, Weibin Wu, Xuanshuang Wu, G X Wu, Yan Yan Wu, Runpei Wu, Chien-Ting Wu, Jiaqi Wu, Li-Na Wu, Qinfeng Wu, Chia-Chang Wu, Yueming Wu, Siyu Wu, Renhai Wu, Baojian Wu, Yi-Xia Wu, Wei-Yin Wu, C-H 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, Chia-Zhen Wu, Kay L H 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, Xianpei Wu, Jianmin Wu, Guanrong 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, Wenyu Wu, Xiangping Wu, L-F Wu, Yixia Wu, Yiran Wu, Haiying Wu, Yanhong Wu, Xiayin Wu, Yushun Wu, Yali Wu, Qin Wu, Xiaofu Wu, Qitian Wu, Jiamei Wu, Xiaoyong Wu, Qiong Wu, Wujun Wu, Xiaoying Wu, Peiyi Wu, N 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, Yingzhi Wu, Lecheng Wu, Kejia Wu, Anyi Wu, Junshu Wu, Jianxin Wu, Deguang Wu, Jiaxuan Wu, W Wu, Justin C Y 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, Irene X Y Wu, Chunshuai Wu, Yaping Wu, Xiping Wu, Yangna Wu, Zongheng Wu, Chia-Chen Wu, Wenyi Wu, Yansheng Wu, Shaojun Wu, Aimin Wu, Caisheng Wu, Xu Wu, Zhongchan Wu, Fei Wu, Yaohua 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, Zhong-Yan Wu, Zhuzhu Wu, Yuanbing Wu, Cuiyan Wu, Baoqin Wu, Colin O 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, Yuan Kai Wu, Qiao Wu

articles

Self-stigma in individuals with substance use disorders and the relationship with meaning in life: a latent profile analysis.

Jinjing Zhao, Rufang Wang, Yongqiu Li +3 more · 2026 · BMC psychology · BioMed Central · added 2026-04-24

Jinjing Zhao, Rufang Wang, Yongqiu Li, Xiao Zang, Yufang Gao, Binbin Wu Show less

To explore the latent profiles of self-stigma and their relationship with meaning in life among individuals with substance use disorders(SUDs). A total of 1001 participants were recruited from six dru Show more

To explore the latent profiles of self-stigma and their relationship with meaning in life among individuals with substance use disorders(SUDs). A total of 1001 participants were recruited from six drug rehabilitation centers in Sichuan Province between July and August 2025 and completed the self-stigma Scale for Drug Addicts (SSSDA) and the Meaning in Life Questionnaire (MLQ). Latent profile analysis (LPA) was used to identify latent profiles of self-stigma. Multinomial logistic regression was employed to analyze influencing factors, and analysis of variance (ANOVA) was used to compare differences in meaning in life across the different profiles. The self-stigma of individuals with SUDs can be categorized into four latent profiles: the "stigma-resistant profile"(10.0%), "moderate stigma-concealment profile"(46.3%), "internalized stigma profile"(19.5%), and "low internalization-adaptation profile"(24.3%). Among these, the "moderate stigma-concealment profile", "internalized stigma profile", and "low internalization-adaptation profile" represent categories with higher levels of self-stigma. Risk factors associated with these profiles include male sex, low income, a history of being left-behind children, low social support, multiple rehabilitation attempts, as well as mental illness or HIV infection. Statistically significant differences were found among the four profiles in the total score of meaning in life and its sub-dimensions-presence of meaning and search for meaning (p < 0.001). The "stigma-resistant profile" presented the highest level of MIL, whereas the "internalized stigma profile" presented the lowest level. Significant heterogeneity exists in self-stigma among individuals with substance use disorders (SUDs), and the level of self-stigma is significantly negatively correlated with MIL. Show less

no PDF DOI: 10.1186/s40359-026-04187-0

Distinct Motivational Profiles Based on Self-Determination Theory Among Young and Middle-Aged Adults With Prediabetes: Associations With Self-Management.

Lingxue Chen, Jing Yang, Li Wang +5 more · 2026 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24

Lingxue Chen, Jing Yang, Li Wang, Adan Fu, Lan Yi, Zhongjing Wang, Bowen Jiang, Fang Wu Show less

Based on self-determination theory (SDT), this study aimed to identify latent profiles of health motivation characteristics among young and middle-aged individuals with prediabetes and to examine thei Show more

Based on self-determination theory (SDT), this study aimed to identify latent profiles of health motivation characteristics among young and middle-aged individuals with prediabetes and to examine their associations with self-management behaviours and metabolic risk indicators. This cross-sectional study recruited individuals with prediabetes from January 2024 to January 2025 using a convenience sampling method, enrolling 309 participants. Health behaviour motivation, basic psychological needs, prediabetes-related disease knowledge and self-management were assessed using validated questionnaires. Latent profile analysis (LPA) was conducted to identify distinct subgroups. Multinomial logistic regression was used to examine demographic, lifestyle and clinical factors associated with profile membership. Three types of health motivation characteristics were identified: high psychological need satisfaction-autonomous motivation profile (24.0%), moderate psychological need satisfaction-externally controlled motivation dominant profile (15.0%) and low psychological need satisfaction-low motivation profile (61.0%). After adjustment, BMI, comorbidity history and occupation were significantly associated with profile membership, whereas distance to primary healthcare facilities showed a non-robust pattern. Significant heterogeneity exists in health motivation characteristics among young and middle-aged individuals with prediabetes, with the low psychological need satisfaction-low motivation profile representing the largest proportion. Incorporating motivation-oriented stratification into diabetes prevention strategies may provide a useful framework for delivering tailored interventions and supporting more sustainable self-management. Show less

no PDF DOI: 10.1111/dom.70726

Heterogeneity of Academic Stress Profiles and Depression-Anxiety Symptom Networks in Left-Behind Children: A Latent Profile and Simulated Intervention Network Analysis.

Kuiliang Li, Lei Ren, Rui Lang +7 more · 2026 · Stress and health : journal of the International Society for the Investigation of Stress · Wiley · added 2026-04-24

Kuiliang Li, Lei Ren, Rui Lang, Xuemei Li, Lin Wu, Tingwei Feng, Jingxuan Zhang, Chang Liu, Zhengzhi Feng, Ming Ji Show less

Compared with non-left-behind children (NLBC), left-behind children (LBC) face a higher risk of academic stress, depression, and anxiety symptoms due to separation from their parents; however, the het Show more

Compared with non-left-behind children (NLBC), left-behind children (LBC) face a higher risk of academic stress, depression, and anxiety symptoms due to separation from their parents; however, the heterogeneity of academic stress profiles and their relationships with the symptom network remain insufficiently explored. To address this gap, a cross-sectional survey of 10,524 Chinese children compared LBC (n = 2487) and NLBC. Latent profile analysis (LPA) was first conducted to identify academic stress subgroups among LBC. Subsequently, depression-anxiety symptom networks were estimated using Ising and Gaussian graphical models (GGM), with edge weights derived from regularised logistic regression (Ising) and partial correlation (GGM). Simulated interventions were further evaluated via the NodeIdentifyR algorithm (NIRA). Overall, compared to NLBC, LBC exhibited higher levels of academic stress, depression, and anxiety (ps < 0.001, Cliff's δ = 0.076; Cohen's d = 0.067). LPA revealed three academic stress subgroups: moderate (31.44%), high (9.17%), and low (59.39%). The severity of depression and anxiety symptoms increased with the level of academic stress. The high stress subgroup displayed a sparse network with stronger edges (e.g., A1 'Sudden Fear'-A4 'Physical Symptoms', edge weight = 2.10) compared to moderate- and low-academic stress subgroups. Core nodes with the strongest expected influence were A8 ('Decision Hesitation', moderate subgroup), A2 ('Worry', high subgroup), and D1/D6 ('Sadness' and 'Failure', low subgroup). Simulated interventions indicated that alleviating A8 'Decision Hesitation' or A2 'Worry' most effectively reduced symptom risk (16.66%-30.76%), whereas D8 'Motor' and A7 'Early Departure' were associated with maximal symptom aggravation. Taken together, by integrating LPA-derived academic stress profiles with symptom network analysis, this study reveals distinct symptom associations across subgroups. In the high stress subgroup, symptom A2 ('Worry') is a core intervention target; in the low stress subgroup, A7 ('Early Departure') holds preventive potential. These findings underscore subgroup-specific interventions tailored to individual stress profiles. Show less

no PDF DOI: 10.1002/smi.70172

Retinal vascular phenotyping for early detection of coronary artery disease: quantitative assessment and diagnostic modelling.

Zhenyan Wu, Xue Jiang, Yu Xin +3 more · 2026 · BMJ open · added 2026-04-24

Zhenyan Wu, Xue Jiang, Yu Xin, Jian Liu, Saiguang Ling, Caixia Guo Show less

To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the efficacy of a retinal phenotype-based diagnostic model as a non-in Show more

To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the efficacy of a retinal phenotype-based diagnostic model as a non-invasive tool for early CAD screening. A retrospective cross-sectional study. A single-centre study conducted at the Cardiovascular Center of Beijing Tongren Hospital, Capital Medical University, China, between January and October 2024. 417 patients with suspected angina undergoing their first coronary angiography (CAG) were enrolled. Inclusion criteria were age >18 years and high-quality fundus photography within 24 hours pre-CAG. Major exclusions were prior coronary interventions, severe systemic/valvular heart diseases and ocular conditions impairing retinal vascular visualisation. The primary outcome was the association between quantitative retinal vascular parameters and the presence of CAD (defined as ≥50% stenosis). Secondary outcomes included the diagnostic performance area under the receiver operating characteristic curve (AUROC) of three predictive models: one based on quantitative retinal vascular parameters alone, one based on traditional risk factors and a combined model integrating both retinal and clinical variables. This study enrolled 417 patients undergoing initial CAG. Compared with non-CAD controls (n=190), patients with CAD (n=227) had higher prevalence of hypertension, dyslipidaemia and diabetes, along with elevated levels of fasting blood glucose, lipoprotein(a) (Lp(a)), triglyceride (TG) and glycated haemoglobin (HbA1c) (all p<0.05). Quantitative fundus analysis revealed that multiple retinal vascular parameters were independently associated with CAD after multivariable adjustment, including fractal dimension (FD), vessel density (VD) and specific zonal measures of vessel diameter and tortuosity (all p<0.05). Multivariable logistic regression incorporating both fundus and clinical variables identified the following independent predictors of CAD: a decrease in FD (OR=0.26, 95% CI 0.16 to 0.41, p<0.01), reduced optic disc long-to-short axis ratio (OR=0.04, 95% CI 0.004 to 0.46, p=0.01) and optic disc-to-macula distance (OR=0.91, 95% CI 0.86 to 0.97, p<0.01), male sex, dyslipidaemia and elevated levels of Lp(a), TG, low-density lipoprotein cholesterol and HbA1c (all p<0.05). The final diagnostic model achieved an AUROC of 0.802 (95% CI 0.76 to 0.845), with a sensitivity of 0.797 and a specificity of 0.679 at the optimal cut-off. Internal validation via bootstrap resampling (1000 iterations) confirmed the robustness of the identified predictors. Our findings, derived from an artificial intelligence-based fully automated quantitative retinal vascular parameters measurement method, revealed that multiple quantitative fundus parameters-including FD, VD and other morphological parameters were significantly associated with CAD risk. The CAD diagnostic model we developed demonstrates strong performance and high interpretability, making it suitable for early CAD screening and diagnosis. Show less

📄 PDF DOI: 10.1136/bmjopen-2025-106135

2026 Consensus and review of Lipoprotein(a) from Taiwan Society of Lipid and Atherosclerosis: Molecular pathogenesis, epidemiology, clinical implications, and advances in diagnostic strategies.

Chao-Yun Cheng, Yih-Jer Wu, Chih-Fan Yeh +25 more · 2026 · Journal of the Formosan Medical Association = Taiwan yi zhi · Elsevier · added 2026-04-24

Lipoprotein(a) [Lp(a)] is a genetically determined lipoprotein that has been established as an independent and causal risk factor for atherosclerotic cardiovascular disease (ASCVD) and calcific aortic Show more

Lipoprotein(a) [Lp(a)] is a genetically determined lipoprotein that has been established as an independent and causal risk factor for atherosclerotic cardiovascular disease (ASCVD) and calcific aortic valve disease (CAVD). Structurally composed of a low-density lipoprotein (LDL)-like particle covalently linked to apolipoprotein(a) [apo(a)], Lp(a) exhibits unique atherogenic, thrombogenic, and inflammatory properties, largely due to its role as a carrier of oxidized phospholipids (OxPL). Plasma Lp(a) concentrations are predominantly determined by the number of kringle IV type 2 (KIV-2) repeats in the LPA gene, with minimal influence from lifestyle or environmental factors. Despite substantial evidence linking elevated Lp(a) to cardiovascular risk, clinical testing remains underutilized, especially in East Asian countries. In Taiwan, although population-level Lp(a) concentrations are comparatively low, a significant subset exceeds risk thresholds, with local studies confirming its prognostic value in coronary artery disease and ischemic stroke. Barriers, including limited physician awareness, implementation barriers, and therapeutic nihilism, contribute to its under-recognition. This review highlights the molecular features of Lp(a), its pathogenesis of cardiovascular disorders, epidemiology, and current barriers and future advances in diagnostic testing, with a particular focus on implications for cardiovascular risk management in Taiwan. Show less

no PDF DOI: 10.1016/j.jfma.2026.03.073

Mindfulness, Psychological Resilience, and Social Function Deficits in Young and Middle-Aged Lymphoma Patients: A Latent Profile and Mediation Analysis.

Li Zhang, Fengyi Li, Yaru Wu +3 more · 2026 · Cancer management and research · added 2026-04-24

Li Zhang, Fengyi Li, Yaru Wu, Yuting Zhang, Chunyan Xu, Wei Zhu Show less

This study aims to identify distinct mindfulness profiles among young and middle-aged lymphoma patients and to examine the mediating role of psychological resilience in the relationship between these Show more

This study aims to identify distinct mindfulness profiles among young and middle-aged lymphoma patients and to examine the mediating role of psychological resilience in the relationship between these mindfulness profiles and social function deficits. From November 2024 to June 2025, a total of 324 young and middle-aged lymphoma patients were recruited using convenience sampling from a tertiary cancer hospital in Urumqi, Xinjiang, China. Participants completed the Mindful Attention Awareness Scale, the 10-item Connor-Davidson Resilience Scale, and the Social Dysfunction Screening Scale. We used latent profile analysis (LPA) to identify distinct mindfulness profiles and tested the mediating role of psychological resilience with the Bootstrap method. Latent profile analysis identified three distinct mindfulness profiles among the patients: a low mindfulness type (29.3%), a moderate mindfulness type (40.1%), and a high mindfulness type (30.6%). Furthermore, psychological resilience partially mediated the relationship between these mindfulness profiles and social function deficits. Young and middle-aged lymphoma patients exhibit heterogeneous mindfulness profiles. Higher mindfulness can enhance psychological resilience, which in turn alleviates social function deficits. Therefore, healthcare providers should develop personalized interventions targeting psychological resilience based on patients' specific mindfulness profiles to improve their social function. Show less

📄 PDF DOI: 10.2147/CMAR.S570129

Latent profile analysis of kinesiophobia during the out-of-hospital early rehabilitation phase after PCI in patients with CHD.

Qing Wen, Xiao-Rong Mao, Hai-Yan Wu +7 more · 2026 · Scientific reports · Nature · added 2026-04-24

Qing Wen, Xiao-Rong Mao, Hai-Yan Wu, Xiao-Cui Zou, Xiao-Juan Yang, Zheng-Wei Wan, Hao Huang, Yin-Xia Luo, Shuang Yan, Qun-Hua Ma Show less

Previous studies have indicated that Kinesiophobia is associated with adherence to exercise rehabilitation. Given the multifaceted impact of Kinesiophobia and the complex diversity of individual chara Show more

Previous studies have indicated that Kinesiophobia is associated with adherence to exercise rehabilitation. Given the multifaceted impact of Kinesiophobia and the complex diversity of individual characteristics, existing research struggles to identify the distinct features of Kinesiophobia. Latent Profile Analysis (LPA) identifies individuals’ latent traits based on their response patterns to observable measures, grouping individuals with similar symptom profiles into different categories, thereby better distinguishing differences among individuals. However, there is currently a lack of research on the kinesiophobia in the out-of-hospital early rehabilitation phase after Percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD). Therefore, the aim of this study is to investigate kinesiophobia in the out-of-hospital early rehabilitation phase after Percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD), classify it based on latent profile analysis, and explore the related factors of Kinesiophobia in CHD patients across different categories. This study selected coronary heart disease patients who were in the early outpatient rehabilitation stage after receiving PCI treatment at a tertiary hospital as the survey subjects. Latent Profile Analysis (LPA) was employed to fit potential classes of kinesiophobia among these patients. Chi-square tests, Kruskal-Wallis tests, and multinomial logistic regression were utilized to explore the factors influencing different kinesiophobia profiles in these patients. A total of 293 survey subjects were included, the age of the 293 patients was 62.31 ± 11.49 years, Males represent 77% of the total population. The results of potential profile analysis revealed that kinesiophobia in the out-of-hospital early rehabilitation phase of CHD in PCI-treated patients could be divided into three potential categories: the low kinesiophobia-exercise avoidance group (52.1%), the medium kinesiophobia-danger perception group (41.6%), and the high kinesiophobia-dysfunction group (6.3%). The logistic regression analysis results revealed that age, mode of residence, chronic comorbidities, polypharmacy, and debilitation were influential factors for different categories of kinesiophobia in the out-of-hospital early rehabilitation phase of CHD patients undergoing PCI. There is obvious group heterogeneity in kinesiophobia in the out-of-hospital early rehabilitation phaseof CHD patients undergoing PCI, and healthcare professionals should carry out individualized intervention Strategies to reduce the degree of kinesiophobia in patients on the basis of the characteristics and influencing factors of different categories. Show less

📄 PDF DOI: 10.1038/s41598-026-42755-x

The impact of 24-h activity patterns on executive function in older adults with chronic diseases: analysis of the isotonic substitution effect.

Zhiji Wang, Lin Wang, Shijie Liu +4 more · 2026 · Frontiers in public health · Frontiers · added 2026-04-24

Zhiji Wang, Lin Wang, Shijie Liu, Li Zhan, Sijun Wu, Linxia Tang, Hong Wang Show less

24-h activity encompasses four categories: light-intensity physical activity (LPA), moderate-to-vigorous-intensity physical activity (MVPA), sedentary behavior (SB), and sleep (SP). This study aims to Show more

24-h activity encompasses four categories: light-intensity physical activity (LPA), moderate-to-vigorous-intensity physical activity (MVPA), sedentary behavior (SB), and sleep (SP). This study aims to investigate the effects of different physical activity components on executive function in older adults with chronic diseases and to examine substitution effects among activity components. The findings provide scientific evidence to inform physical activity interventions for improving executive function in older adults with chronic diseases. A total of 105 older adults (72.64 ± 6.82 years) were recruited. Following questionnaire screening, 75 older adults with chronic diseases were ultimately included. Accelerometers objectively measured participants' daily SP, SB, LPA, and MVPA. Executive function was objectively assessed using the Stroop task, N-back task, and More-odd-shifting task. Component linear regression equation assessed the relationship between different activities and executive function in older adults with chronic diseases. The dose-response effects of "one-for-one" substitutions between different activity behaviors were explored. Component linear regression results showed that SB positively correlated with inhibitory control ( SP and MVPA significantly improve inhibitory control in older adults with chronic diseases, while LPA significantly enhances their working memory. It is recommended that older adults with chronic diseases adjust their daily time structure by increasing diverse physical activities, ensuring adequate sleep duration, and reducing sedentary behavior to improve executive function. Show less

📄 PDF DOI: 10.3389/fpubh.2026.1733294

Sex disparities in the associations between accelerometer-measured movement behaviors and subsequent thromboembolism risk in cancer patients.

Xiao Huang, Darui Gao, Wenya Zhang +7 more · 2026 · Biology of sex differences · BioMed Central · added 2026-04-24

Xiao Huang, Darui Gao, Wenya Zhang, Mengmeng Ji, Yang Pan, Yanyu Zhang, Yiwen Dai, Anshi Wu, Fanfan Zheng, Wuxiang Xie Show less

Cancer patients face a markedly elevated risk of thromboembolism (TE), including both venous thromboembolism (VTE) and arterial thromboembolism (ATE), which contribute substantially to morbidity and m Show more

Cancer patients face a markedly elevated risk of thromboembolism (TE), including both venous thromboembolism (VTE) and arterial thromboembolism (ATE), which contribute substantially to morbidity and mortality in this population. This study examined sex disparities in associations between sleep, sedentary behavior (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and TE risk, in cancer patients using data from the UK Biobank. A longitudinal cohort analysis of 6,765 cancer patients (2,774 men and 3,991 women) from the accelerometry subsample was conducted using Cox proportional hazards and isotemporal substitution models stratified by sex. The incidence of VTE was 3.0% in men versus 2.2% in women, while ATE incidence was 5.0% versus 2.2%, respectively. Compared with high LPA, medium and low durations were associated with 2.75- and 2.88-fold higher VTE risk only in men. Reallocating 1 h per day from sleep or SB to LPA reduced VTE risk by 24% and 19% in men. Low MVPA was associated with 3.35- and 1.59-fold higher ATE risk in women and men, respectively. Reallocating 1 h per day from sleep, SB, or LPA to MVPA reduced ATE risk by 71%, 70%, and 66%, respectively, only in women. LPA was associated with a lower risk of VTE only in male cancer patients, whereas MVPA was linked to a lower risk of ATE in female patients, indicating sex-specific associations between movement behaviors and TE risk. Show less

📄 PDF DOI: 10.1186/s13293-026-00867-z

The relationship between mobile phone dependence, self-control, and Tai Chi exercise among sub-health older adults in urban areas: a latent profile analysis.

Tongtong Hao, Dong Wu · 2026 · Frontiers in public health · Frontiers · added 2026-04-24

The study explores the interconnection between the latent categories of mobile phone dependency and self-control in the sub-healthy urban older adults practicing Tai Chi. The findings aim to provide a Show more

The study explores the interconnection between the latent categories of mobile phone dependency and self-control in the sub-healthy urban older adults practicing Tai Chi. The findings aim to provide a reference for preventing mobile phone dependence, enhancing self-control and improving sub-health status in this population. A multi-stage cluster sampling method was employed to screen 560 sub-healthy urban older adults from 2,946 valid survey responses in Xuzhou City, Jiangsu Province. Sub-health status was verified using the SHMS V1.0 scale. Data were collected between September and October 2025. Latent profile analysis (LPA) was used to categorize mobile phone dependency and self-control. Pearson correlation analysis measured the relationship between these two variables. Additionally, chi-square test examined demographic differences across the identified latent profiles. Finally, multivariate logistic regression analyzed the associations between mobile phone dependency, self-control, and Tai Chi exercise. LPA identified four distinct profiles: Low dependency-Medium control (109 individuals, 19.5%), High dependency-No control (207 individuals, 37.0%), No dependency-High control (191 individuals, 34.1%), and Moderate dependency-Low control (53 individuals, 9.5%). These categories had statistically significant differences ( Tai Chi exercise exerts differential effects on urban sub-healthy older adults across distinct latent profiles of mobile phone dependency and self-control. Societal stakeholders should strengthen Tai Chi programs for these diverse categories to promote their physical and mental wellbeing. Show less

📄 PDF DOI: 10.3389/fpubh.2026.1759896

Exploring comorbidity patterns of psychosis-related post-traumatic stress disorder and depression symptoms in stabilised hospitalised schizophrenia patients and relationships with sleep quality and quality of life: a latent profile analysis.

Laixi Kong, Xiucheng Ma, Cui Yang +3 more · 2026 · European journal of psychotraumatology · Taylor & Francis · added 2026-04-24

Laixi Kong, Xiucheng Ma, Cui Yang, Xiaofeng Hou, Yunqiong Wang, Dongmei Wu Show less

📄 PDF DOI: 10.1080/20008066.2026.2629072

A latent profile analysis of health characteristics in relation to sleep among female sex workers in entertainment venues in Wuhan, China.

Weiwei Xiang, Hua Ke, Xiaojia Song +10 more · 2026 · BMC women's health · BioMed Central · added 2026-04-24

Weiwei Xiang, Hua Ke, Xiaojia Song, Xiang Liu, Li Dai, Xinwen Min, Handong Yang, Jun Chen, Jishun Chen, Dongfeng Li, Lijuan Zheng, Hao Xu, Wenwen Wu Show less

This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This stu Show more

This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This study employed a cross-sectional design and was conducted from January to April 2024 in Wuhan, China. Participants were FSWs recruited through snowball sampling from entertainment venues, including hotels, restaurants, nightclubs, karaoke bars and dance halls. Data were collected via structured questionnaires covering sociodemographic information, work experience, psychological stress, health status, sleep quality and circadian rhythms. Latent profile analysis (LPA) was employed to identify health characteristic profiles among FSWs, and multivariate logistic regression was used to examine the associations between these profiles and sleep quality. Among the 1,036 FSWs surveyed, 45.1% had poor sleep quality. LPA classified FSWs’ health characteristics into three profiles: the high overall functioning group, the lower physical–emotional functioning group and the lower psychosocial functioning group. Multivariate logistic regression analysis showed that FSWs in the lower physical–emotional functioning group had higher odds of poor sleep quality (OR = 2.184) compared with those in the high overall functioning group. FSWs in the lower psychosocial functioning group had substantially higher odds of poor sleep quality (OR = 7.755) than that in the high overall functioning group. FSWs demonstrate substantial heterogeneity in health characteristics and exhibit lower overall sleep quality compared with the general population. Psychological and physiological factors are major influencing factors for their sleep quality, suggesting the importance of prioritising mental and physical health in this population. Show less

📄 PDF DOI: 10.1186/s12905-026-04346-w

Association Between Lipoprotein(a) and Cardiac Remodeling Across Race and Ethnicity in the Multi-Ethnic Study of Atherosclerosis.

Ashkan Abdollahi, Aysa Ostovaneh, Omar Chehab +10 more · 2026 · Circulation. Population health and outcomes · added 2026-04-24

Ashkan Abdollahi, Aysa Ostovaneh, Omar Chehab, Malak Hoballah, Bruna R S Matuck, Colin O Wu, Seamus P Whelton, Bharath Ambale-Venkatesh, Wendy S Post, David A Bluemke, Michael Y Tsai, Sotirios Tsimikas, João A C Lima Show less

Lp(a) (lipoprotein[a]) is a known cardiovascular risk factor; however, its role in cardiac remodeling and functional changes over time across diverse racial and ethnic groups remains underexplored. ME Show more

Lp(a) (lipoprotein[a]) is a known cardiovascular risk factor; however, its role in cardiac remodeling and functional changes over time across diverse racial and ethnic groups remains underexplored. MESA is a prospective multi-ethnic cohort study of individuals without a history of cardiovascular disease on enrollment (2000-2002), conducted across 6 sites in the United States. Participants with baseline Lp(a) measurements and cardiac magnetic resonance imaging at both baseline and 10-year follow-up exam were included. Lp(a) was treated as both a log-transformed continuous variable (per SD log) and a categorical variable based on data-driven Lp(a) terciles. Multivariable regression models adjusted for sociodemographic, and cardiovascular risk factors, including coronary artery calcium and interim myocardial infarction, were used to assess associations between Lp(a) and longitudinal changes in left ventricular and atrial structure and function over a decade across different racial/ethnic groups. A total of 2366 participants were included. The average age at baseline was 60±9 with 53% women, 43% White, 24% Black, 21% Hispanic, and 12% Chinese. Each 1-SD increase in log-transformed Lp(a) was associated with an increase in left ventricular end-systolic volume index (β, 0.60 [95% CI, 0.02-1.18]), and left atrial minimum volume index (β, 0.81 [95% CI, 0.09-1.52]), and a decline in left ventricular ejection fraction (β, -0.75 [95% CI, -1.34 to -0.17]), and total left atrial emptying fraction (β, -1.17 [95% CI, -2.09 to -0.24]) in Hispanic subjects over a decade. No significant associations were seen in White, Black, or Chinese participants. The observed findings persisted after adjusting for coronary artery calcium, interim myocardial infarction, and atrioventricular decoupling, and when Lp(a) was treated as a categorical variable with race-specific terciles. Elevated Lp(a) levels were independently associated with maladaptive left ventricular and left atrial remodeling in Hispanic adults over a decade, while no statistically significant relationships were observed in White, Black, and Chinese participants. This suggests a unique susceptibility of Hispanic individuals to Lp(a)-mediated cardiovascular remodeling, independent of ischemic pathways. Show less

📄 PDF DOI: 10.1161/CIRCOUTCOMES.125.013261

Profiles of Health Behavior Motivation in a Chinese Population with Prediabetes and Its Association with Self-Management Ability: Based on Self-Determination Theory.

Fang Wu, Juan Zhang, Adan Fu +6 more · 2026 · Diabetes, metabolic syndrome and obesity : targets and therapy · added 2026-04-24

Fang Wu, Juan Zhang, Adan Fu, Li Wang, Lan Yi, Jing Yang, Bowen Jiang, Lingxue Chen, Chengyue Xiong Show less

Using latent profile analysis (LPA) based on Self-Determination Theory (SDT), this study aimed to explore the profiles of health behavior motivation among Chinese patients with prediabetes and examine Show more

Using latent profile analysis (LPA) based on Self-Determination Theory (SDT), this study aimed to explore the profiles of health behavior motivation among Chinese patients with prediabetes and examine the relationship between these profiles and self-management ability. A cross-sectional study was conducted involving 335 patients with prediabetes. The questionnaires were used to assess health behavior motivation, self-management ability, satisfaction of basic psychological needs and disease knowledge level. Latent profile analysis was performed based on five subscale scores of the health behavior motivation measure. Three distinct latent profiles were identified: a "Self-Determined" profile (C1,29.55%, n=99), a "Non Self-Determined" profile (C2, 55.82%, n=187), and a "Conflicted" profile (C3, 14.63%, n=49). Patients in the C1 profile demonstrated higher levels of autonomy and competence. Patients in the C2 profile were characterized by better disease knowledge and lower relatedness. Compared to patients in the C3 profile, patients in both the C1 and C2 profiles exhibited significantly lower self-management ability. The heterogeneity in health behavior motivation profiles must be considered in the design and clinical practice of personalized interventions for prediabetes. Profile-specific strategies serve as the foundation for enhancing patients' self-management ability and sustaining healthy behaviors. Show less

📄 PDF DOI: 10.2147/DMSO.S567404

Spiritual well-being and quality of life in maintenance hemodialysis patients: a latent profile analysis and serial mediation model.

BiXia Yuan, QingHua Lai, Jing Wu +5 more · 2026 · Frontiers in psychology · Frontiers · added 2026-04-24

BiXia Yuan, QingHua Lai, Jing Wu, RongRong Wang, YongMei Lu, Meng Wu, Yun Chen, JieQian Wu Show less

From a positive psychology perspective, this study aimed to identify the latent profiles of spiritual well-being and analyze the serial mediation mechanism of family care and spiritual coping in the r Show more

From a positive psychology perspective, this study aimed to identify the latent profiles of spiritual well-being and analyze the serial mediation mechanism of family care and spiritual coping in the relationship between spiritual well-being and health-related quality of life (HRQoL). The findings are intended to inform strategies for improving the spiritual well-being of maintenance hemodialysis (MHD) patients. A cross-sectional design was employed with 220 MHD patients recruited from two tertiary hospitals in Guangdong, China (August 2023-January 2024). Assessments were conducted using the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-SP-12), Family Care Index, Spiritual Coping Questionnaire (SCQ), and Short Form-12 Health Survey (SF-12). Latent profile analysis (LPA) was employed to identify heterogeneous subgroups based on spiritual well-being. A chain mediation model was then used to examine the mediating effects of family care and spiritual coping. HRQoL scores averaged 56.50 ± 22.29. Significant correlations emerged: spiritual well-being ( Spiritual well-being indirectly influences the quality of life in MHD patients through the serial mediation of family care and spiritual coping. Clinicians should recognize the heterogeneity in spiritual well-being and integrate routine spiritual screening into nursing assessments to identify patients with low spiritual well-being. It is recommended to develop family-based education and support programs, along with interventions that combine family care and spiritual coping strategies, so as to improve patients' long-term health outcomes. Show less

📄 PDF DOI: 10.3389/fpsyg.2026.1668699

Influenza vaccine Hesitancy in older adults in China: A latent profile analysis.

Xian Chen, Sichen Xia, Zhu Zhu +5 more · 2026 · Human vaccines & immunotherapeutics · Taylor & Francis · added 2026-04-24

Xian Chen, Sichen Xia, Zhu Zhu, Zhou Hui, Jinfeng Wu, Cuihua Sun, Chunxiu Zhou, Lihua Ceng Show less

Influenza vaccination coverage among older adults in China is low. We sought to identify latent vaccine-hesitancy profiles and their correlates. This community-based cross-sectional survey from May to Show more

Influenza vaccination coverage among older adults in China is low. We sought to identify latent vaccine-hesitancy profiles and their correlates. This community-based cross-sectional survey from May to July 2025 involved 1773 older adults from various areas in Jiangsu province. Data were collected via Wenjuanxing and included demographics, the Influenza Vaccine Hesitancy Scale, and the vaccine literacy scale. Group differences were examined using chi-square tests and one-way ANOVA; latent profile analysis (LPA) identified vaccine hesitancy subgroups, and multinomial logistic regression estimated correlates of profile membership. Three profiles emerged: Low Hesitancy (23.0%), Moderate Hesitancy (35.0%), and High Hesitancy (42.0%). Rural residence predicted Moderate (OR = 2.030) and High (OR = 2.993) hesitancy. Lower household income and chronic disease were associated with the Moderate Hesitancy profile, whereas male sex was associated with the High Hesitancy profile. Higher interactive (OR = 0.686) and critical (OR = 0.599) vaccine literacy were inversely associated with High hesitancy.Concerns about vaccine quality predicted both Moderate (OR = 1.433) and High (OR = 1.376) groups; knowledge gaps and fear of adverse reactions concentrated in the High group. Older adults show heterogeneous vaccine hesitancy phenotypes. Uptake efforts should move beyond one-size-fits-all messaging toward segmented strategies. These strategies should integrate cost-related measures with literacy-sensitive, trust-oriented communication, prioritizing rural residents, older men, and those with chronic conditions. The reported proportions of hesitancy profiles reflect our sample only and should not be viewed as nationally representative. Show less

📄 PDF DOI: 10.1080/21645515.2026.2616943

Positive association of lipoprotein(a) and the prevalence of lower extremity arterial disease in MASLD: a cross-sectional study.

Ziliang Wu, Chen Qiu, Meimei Pan +6 more · 2026 · BMC cardiovascular disorders · BioMed Central · added 2026-04-24

Ziliang Wu, Chen Qiu, Meimei Pan, Chunxia Zhang, Pingping Shen, Shiyuan Cao, Qinxue Sun, Feng Li, Ri Liu Show less

Lipoprotein(a) [Lp(a)] has been recognized as a genetically determined and independent contributor to atherosclerotic cardiovascular disease. However, its role in lower extremity arterial disease (LEA Show more

Lipoprotein(a) [Lp(a)] has been recognized as a genetically determined and independent contributor to atherosclerotic cardiovascular disease. However, its role in lower extremity arterial disease (LEAD) among individuals with metabolic dysfunction-associated steatotic liver disease (MASLD) remains insufficiently studied. Given the overlapping metabolic disturbances in both conditions, such as insulin resistance and lipid abnormalities, a potential relationship between Lp(a) and peripheral vascular injury in MASLD is biologically plausible. This study aimed to investigate the cross-sectional association between circulating Lp(a) concentrations and the presence of LEAD in a well-characterized MASLD population. A total of 468 MASLD patients undergoing routine health check-ups were included. Lp(a) levels were stratified into three categories: <10 mg/dL, 10–30 mg/dL, and ≥ 30 mg/dL. LEAD was diagnosed using duplex ultrasonography. Multivariable logistic regression models were used to assess the relationship between Lp(a) levels and the presence of LEAD, with adjustments for demographic variables, metabolic conditions, and lipid-related parameters. Subgroup analyses were conducted to assess potential effect modification. LEAD was diagnosed in 61.5% ( Elevated Lp(a) levels were associated with a higher prevalence of LEAD in patients with MASLD. Although the magnitude of association per unit increase was modest, higher Lp(a) concentrations were associated with greater LEAD prevalence. These findings should be interpreted cautiously and viewed as hypothesis-generating, particularly with respect to subgroup analyses. Prospective studies are needed to clarify causality and clinical relevance. The online version contains supplementary material available at 10.1186/s12872-026-05600-7. Show less

📄 PDF DOI: 10.1186/s12872-026-05600-7

Factors associated with childbirth readiness among pregnant women: a Bayesian network analysis.

Ningying Zhou, Feng Zhang, Min Liu +4 more · 2026 · Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology · Taylor & Francis · added 2026-04-24

Ningying Zhou, Feng Zhang, Min Liu, Shanshan Hu, Yuqing Zan, Danni Wu, Fei Sun Show less

Inadequate childbirth readiness can adversely affect the birthing experience of pregnant women and may even influence their willingness to have further children. This study aimed to explore the determ Show more

Inadequate childbirth readiness can adversely affect the birthing experience of pregnant women and may even influence their willingness to have further children. This study aimed to explore the determinants of childbirth readiness and the network relationships among these factors, thereby providing evidence to improve childbirth readiness. This cross-sectional study surveyed 350 pregnant women attending Wuxi Maternity and Child Health Care Hospital. Latent profile analysis (LPA) was first performed using the four domains of the Childbirth Readiness Scale to identify subgroups of childbirth readiness, and potential associated factors were then screened using univariate analysis and multinomial logistic regression. A Bayesian network model was employed to construct the structural relationships of factors influencing childbirth readiness. Childbirth readiness was categorised into three levels: poor (26%), good (30.9%), and complete (43.1%). Univariate analysis revealed significant differences across the three categories in relation to age, parity, pregnancy complications, antenatal exercise, planned pregnancy, self-efficacy, eHealth literacy, fear of childbirth, and family support ( Previous studies on childbirth readiness have mainly relied on regression models, which are unable to elucidate the intrinsic interconnections among influencing factors. By constructing a Bayesian model, this study demonstrated that women with high self-efficacy, no fear of childbirth, high eHealth literacy, and multiparity had the highest probability of achieving complete childbirth readiness (83.3%). Show less

no PDF DOI: 10.1080/01443615.2026.2626380

Unraveling family resilience patterns in ICU first-episode stroke: a latent profile analysis.

Jinlei Du, Jin Yang, Yulian Wu +3 more · 2026 · Frontiers in psychology · Frontiers · added 2026-04-24

Jinlei Du, Jin Yang, Yulian Wu, Ling Lei, Chencong Nie, Xiaoling Wu Show less

To identify latent family resilience profiles among families of patients with first-episode stroke in the intensive care unit (ICU) and examine factors associated with resilience heterogeneity, with t Show more

To identify latent family resilience profiles among families of patients with first-episode stroke in the intensive care unit (ICU) and examine factors associated with resilience heterogeneity, with the aim of informing targeted family-support interventions. A cross-sectional study was conducted among 335 ICU patients with first-episode stroke and their primary caregivers. Family resilience was assessed using the Chinese version of the Family Resilience Assessment Scale (FRAS-C). Latent profile analysis (LPA) was used to identify subgroups of family resilience, while LASSO regression and multiple binary logistic regression were applied to determine influencing factors. Two distinct resilience profiles were identified: Developing Families, characterized by lower levels of communication, resource utilization, and positive outlook; and Optimized Families, characterized by higher resilience across all dimensions. ICU admission count (OR = 2.299, 95% CI: 1.066-4.960), frequency of care and support from relatives or friends (OR = 1.851, 95% CI: 1.068-3.206), and number of additional organ system dysfunctions (OR = 0.233, 95% CI: 0.122-0.445) were significantly associated with family resilience profiles (all Family resilience among ICU first-episode stroke patients shows notable heterogeneity, with two typical resilience patterns. Early identification of high-risk families-particularly those with limited social support or higher disease complexity-can guide clinicians in delivering targeted communication support, psychological counseling, and resource linkage interventions. Tailored resilience-enhancing strategies may contribute to better patient recovery and improved family adaptation during critical care. Show less

📄 PDF DOI: 10.3389/fpsyg.2026.1673403

Letter by Huang et al Regarding Article, "Causal Relevance of Lp(a) for Coronary Heart Disease and Stroke Types in East Asian and European Ancestry Populations: A Mendelian Randomization Study".

Qing Huang, Xiangyu Jian, Feng Wu · 2026 · Circulation · added 2026-04-24

no PDF DOI: 10.1161/CIRCULATIONAHA.125.075583

How pattern of parental care and child emotional support predicts trajectories of depressive symptoms among Chinese middle-age and older adults.

Keyun Xu, Liyang Wu, Lei Zhu · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24

Late-life depression shows heterogeneous developmental trajectories. Prior studies in older Chinese populations have identified distinct depressive trajectories, yet the influence of family emotional Show more

Late-life depression shows heterogeneous developmental trajectories. Prior studies in older Chinese populations have identified distinct depressive trajectories, yet the influence of family emotional support across the life course remains underexplored. We conceptualized intergenerational emotional interaction patterns as the combined configuration of early-life parental affection and later-life emotional support from adult children. This study identified late-life depressive trajectories and tested whether these patterns predict depressive trajectory among Chinese older adults. Using China Health and Retirement Longitudinal Study (CHARLS) data (2011-2020; n = 9888), this study identified depressive trajectories using Latent Class Growth Modeling (LCGM) and Latent Profile Analysis (LPA) was used to categorize participants into subgroups based on maternal/paternal affection and emotional support from adult children. Multinomial logistic regression and Chi-square tests assessed associations between profiles and trajectories. Four depressive trajectories emerged: "no depression" (56.3%), "deterioration" (22.4%), "alleviation" (12.3%), and "chronic depression" (9.1%). Three distinct intergenerational emotional interaction patterns were found: "emotional inheritance" (40.7%), "emotional compensatory" (17.4%), and "emotional mismatch" (41.9%). The "emotion inheritance" group was overrepresented in the "no depression" trajectory, whereas the "emotional compensatory" group faced elevated risks for being classified into "deterioration" and "chronic depression" trajectories. Intergenerational emotional interaction patterns are independently and jointly associated with depressive symptoms trajectories in later life. The strongest protective effects were observed for individuals with both high childhood parental affection and ongoing emotional support from children. Conversely, low parental affection-even when compensated by later-life support-was linked to worse mental health outcomes. Show less

no PDF DOI: 10.1016/j.jad.2026.121323

Lysophosphatidic acid-induced upregulation of exosomal miR-221-3p from corneal stromal cells promotes corneal endothelial healing.

Hung-Chi Chen, Yi-Jen Hsueh, Yaa-Jyuhn James Meir +7 more · 2026 · Biomaterials advances · Elsevier · added 2026-04-24

Hung-Chi Chen, Yi-Jen Hsueh, Yaa-Jyuhn James Meir, Jui-Yang Lai, Chieh-Cheng Huang, Tsai-Te Lu, Chao-Min Cheng, Song-Shu Lin, David Hui-Kang Ma, Wei-Chi Wu Show less

Corneal transparency maintenance relies on the water-pumping function of the corneal endothelium. Currently, corneal transplantation remains the only available treatment for corneal endothelial dysfun Show more

Corneal transparency maintenance relies on the water-pumping function of the corneal endothelium. Currently, corneal transplantation remains the only available treatment for corneal endothelial dysfunction, therefore, the development of alternative therapies is critical due to the global shortage of donor corneas. In our previous study, we confirmed that corneal stromal cells (CSCs) secretion can promote corneal endothelial cells (CEnCs) proliferation. This effect can be enhanced by treatment with lysophosphatidic acid (LPA), a bioactive phospholipid. Nevertheless, the components involved in CSC secretion remain to be elucidated. In this study, we investigated the therapeutic potential of CSC-derived exosomes and exosomal microRNAs (miRNAs) for enhancing CEnCs proliferation and corneal endothelial healing. CSC exosomes were characterized via nanoparticle tracking (NTA), transmission electron microscopy (TEM), and immunoassays. The miRNA expression profiles of CSC exosomes were identified via RNA sequencing, revealing a total of 767 distinct miRNAs. The proliferative effects of CSC exosomes and exosomal miR-221-3p were increased by LPA. Ectopic expression of miR-221-3p further increased CEnC proliferation and suppressed the expression of the CDK inhibitor p27 Show less

no PDF DOI: 10.1016/j.bioadv.2026.214719

Association of Body Fat Distribution Patterns at MRI with Brain Structure, Cognition, and Neurologic Diseases.

Miao Yu, Libin Yao, Sanjeev Shahi +12 more · 2026 · Radiology · added 2026-04-24

Miao Yu, Libin Yao, Sanjeev Shahi, Yingqianxi Xu, Meizi Li, Qingtong Zheng, Di Ma, Qi Zhang, Dan Wang, Yang Wu, Xiao Zhou, Haitao Ge, Chunfeng Hu, Yanjia Deng, Kai Liu Show less

Background Although substantial evidence has demonstrated the impact of obesity on brain structure and cognition, the heterogeneity of adiposity-particularly in terms of fat distribution patterns-and Show more

Background Although substantial evidence has demonstrated the impact of obesity on brain structure and cognition, the heterogeneity of adiposity-particularly in terms of fat distribution patterns-and its differential neurologic effects remain poorly understood. Purpose To identify body fat distribution patterns with MRI and latent profile analysis (LPA) and their associations with brain structure measurements, cognition, and neurologic diseases. Materials and Methods This secondary analysis used prospective data from the UK Biobank, including health records and MRI scans of the brain, heart, and abdomen. Fat distribution profiles were classified using LPA based on eight body mass index (BMI)-adjusted MRI-derived fat quantification metrics. Differences in brain volume, white matter properties, cognition, and the risk of neurologic disorders were analyzed across profiles and relative to a benchmark lean profile; analyses were stratified by sex. Group differences were examined using analysis of covariance (ANCOVA) or rank-based ANCOVA. Results Among 25 997 participants (mean age, 55 years ± 7.4 [SD]; 13 536 female participants), LPA identified six profiles of body fat distribution in both sexes. Four high-adiposity patterns were identified, including the pancreatic-predominant profile (profile 1), with elevated proton density fat fraction (mean BMI-adjusted Show less

no PDF DOI: 10.1148/radiol.252610

Effects of 24-h Movement Behaviours on Emotional and Behavioural Problems in Chinese Preschoolers Using Compositional Data Analysis.

Tong Cheng, Ying Zhang, Mengnan Zhang +13 more · 2026 · Child: care, health and development · Blackwell Publishing · added 2026-04-24

Tong Cheng, Ying Zhang, Mengnan Zhang, Zhaoxu Lu, Ji Zhou, Mengjie Xu, Yan Wu, Minyuan Huang, Yunfen Liu, Xia Tan, Xuejiao Zhang, Hui Cao, Lin Yang, Yanmei Peng, Ting Zhang, Hongyan Guan Show less

The associations between 24-h movement behaviours (24 h MBs) and emotional and behavioural problems (EBPs) in early years are not well understood. This study examined these associations in a nationall Show more

The associations between 24-h movement behaviours (24 h MBs) and emotional and behavioural problems (EBPs) in early years are not well understood. This study examined these associations in a nationally representative sample of Chinese preschoolers. As part of the Chinese cohort of the SUNRISE International Study of Movement Behaviors in the Early Years main study, this research recruited 1316 children aged 3-4 years through multistage stratified cluster sampling in urban and rural areas across seven major administrative regions in China. Moderate- to vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA) and sedentary behaviour (SED) were measured using 24-h accelerometry over five consecutive days. Sleep duration was parent-reported. EBPs were evaluated using the parent-rated Strengths and Difficulties Questionnaire (SDQ), which assesses total difficulties, internalising problems, externalising problems and prosocial behaviour. Compositional multiple linear regression was employed to analyse the relationships between 24 h MBs and EBPs. Compositional isotemporal substitution was also utilised to predict changes in EBPs due to reallocating time among 24 h MBs. Isotemporal substitution analyses revealed that replacing as little as 1 min of MVPA, LPA or SED with sleep was associated with significant reductions in total difficulties (β Increasing LPA by reducing MVPA or SED was significantly associated with improvements in internalising and conduct problems, whereas increasing sleep to decrease MVPA or SED-even by small amounts-was consistently associated with improvements in EBPs across all SDQ subscales. However, increasing LPA at the expense of sleep exacerbates total difficulties and externalising problems. Promoting diverse LPA opportunities alongside sufficient sleep, while maintaining a balance between them, is essential for supporting preschoolers' emotional and behavioural development. Show less

📄 PDF DOI: 10.1111/cch.70239

Latent profile analysis of medication adherence in lower extremity deep venous thrombosis-cross-sectional study.

Ningning Hu, Xiaoyan Li, Feng Fu +5 more · 2026 · PloS one · PLOS · added 2026-04-24

Ningning Hu, Xiaoyan Li, Feng Fu, Linzhou Xie, Jinfang Qi, Ping Wu, Yufeng Li, Ying-Lan Li Show less

The cornerstone of treating lower extremity deep venous thrombosis (LEDVT) lies in anticoagulation therapy to prevent thrombus progression and recurrence. However, patient adherence to medication is a Show more

The cornerstone of treating lower extremity deep venous thrombosis (LEDVT) lies in anticoagulation therapy to prevent thrombus progression and recurrence. However, patient adherence to medication is a critical factor influencing treatment efficacy. Traditional research often simplifies adherence into binary categories of "adherent" and "non-adherent," which fails to comprehensively reflect the complex behavioral patterns. Based on latent profile analysis (LPA), medication adherence in LEDVT patients can be categorized into distinct classes, enabling more precise identification of their characteristics. Therefore, exploring these latent classes and their influencing factors holds significant importance for optimizing intervention strategies and improving prognosis. A cross-sectional survey was used to study LEDVT. From March 14, 2024 to September 20, 2024, a random sampling method was used to recruit 469 patients with LEDVT from four grade-A tertiary hospitals in Urumqi, China. Participants completed questionnaires on general demographic information, the Medication Adherence Scale, the Perceived Health Competence Scale, the Herth Hope Index, the Patient Activation Measure, the Beliefs about Medicines Questionnaire-Specific. LPA was conducted to analyze the medication adherence characteristics of patients with LEDVT. Univariate analysis and multivariate logistic regression were used to identify the influencing factors of their latent profiles. Data analysis was performed using Mplus 8.3 and SPSS 25.0 software. LPA was employed to investigate medication adherence in LEDVT patients, revealing three distinct latent classes: the poorest adherence group (44.99%), the moderate adherence group (19.83%), and the good adherence group (35.18%). The logistic regression results demonstrated that, perceived health competence, hope, activation, beliefs about medication necessity, and concerns about medication were influential factors affecting the potential profile of medication adherence (all p < 0.05). LEDVT patients exhibit significant individual differences in medication adherence. Personalized intervention strategies can be designed based on different adherence classes to enhance medication adherence. Additionally, targeted interventions addressing perceived health competence, hope, positive affect, and medication beliefs can effectively improve adherence. Show less

📄 PDF DOI: 10.1371/journal.pone.0340406

Parenting Behavior Profiles and Subsequent Non-Suicidal Self-Injury in Chinese Adolescents: A Prospective Moderated Serial Mediation Model.

Qingna Du, Nini Wu, Dongli Luo +2 more · 2026 · Child psychiatry and human development · Springer · added 2026-04-24

Qingna Du, Nini Wu, Dongli Luo, Xiangrong Zheng, Li Lin Show less

Parenting behaviors, including autonomy support and psychological control, have been shown to significantly influence adolescent non-suicidal self-injury (NSSI). However, the underlying mechanisms lin Show more

Parenting behaviors, including autonomy support and psychological control, have been shown to significantly influence adolescent non-suicidal self-injury (NSSI). However, the underlying mechanisms linking heterogeneous parenting behavior profiles to adolescent NSSI remain unclear. This two-wave longitudinal study (with a one-year interval) of 742 Chinese adolescents (52.7% girls; Mage at Time 1 = 13.40 years) identified four distinct parenting profiles using latent profile analysis (LPA): Supportive (43.6% of the sample), Controlling (17.4%), Moderate Mixed Parenting (33.1%) and High Mixed Parenting (5.9%). Multicategorical serial mediation analysis revealed that adolescent emotion regulation difficulties and depressive symptoms serially mediated the relationship between parenting profiles and NSSI for adolescents in the Controlling, Moderate Mixed Parenting and High Mixed Parenting Profiles. Notably, these mediating effects were significant only for girls. These findings underscore the importance of adopting person-centered and sex-sensitive intervention strategies to mitigate the adverse effects of detrimental parenting behaviors on adolescent NSSI. Show less

📄 PDF DOI: 10.1007/s10578-026-01963-2

Site-Specific Blockade of LPA-TRPV1 Interaction at K710 Residue Influences on Myocardial Ischemia/Reperfusion Injury in Ex Vivo Mouse Hearts.

Muge Qile, Zhaofei Luo, Chao Wu +7 more · 2026 · Anesthesia and analgesia · added 2026-04-24

Muge Qile, Zhaofei Luo, Chao Wu, Xueying Cheng, Yu Zhang, Liu Liu, Qingtong Wang, Ye Zhang, Eric R Gross, Shufang He Show less

Myocardial ischemia/reperfusion (I/R) injury commonly occurs in patients undergoing cardiac or noncardiac surgeries, increasing perioperative mortality risk. Although numerous endogenous mediators rel Show more

Myocardial ischemia/reperfusion (I/R) injury commonly occurs in patients undergoing cardiac or noncardiac surgeries, increasing perioperative mortality risk. Although numerous endogenous mediators released during I/R contribute to myocardial damage, their mechanisms require further elucidation. We investigated whether lysophosphatidic acid (LPA), a bioactive phospholipid, mediates myocardial I/R injury by interacting with cardiac transient receptor potential vanilloid 1 (TRPV1). A TRPV1K710N knock-in mouse model was generated by CRISPR/Cas9, introducing a point mutation at K710, the known LPA-binding site on TRPV1. Langendorff perfused isolated hearts from TRPV1K710N and wild-type (WT) mice underwent global I/R injury with or without exogenous LPA (10 μM). Myocardial infarct size, coronary effluent LDH levels, and mitochondrial ultrastructure/function were assessed. Additionally, H9c2 cardiomyocytes were transfected with a pCMV6-entry plasmid carrying TRPV1-K710N or TRPV1-WT for mitochondrial calcium influx and cell viability assays. The V1-Cal peptide (1μM), targeting the K710 region, was applied ex vivo and in vitro to block LPA-TRPV1 interaction. TRPV1K710N hearts exhibited resistance to global I/R injury versus WT hearts, with reduced infarct size (28.3 ± 2.4% vs 39.9 ±2.3%, respectively, P= 0006), lower LDH levels, and attenuated mitochondrial damage. Exogenous LPA exacerbated I/R injury in WT hearts, increasing infarct size (63.7 ± 1.2% vs vehicle: 38.4 ± 2.4%; P <.0001), LDH release, and mitochondrial damage. TRPV1K710N hearts were resistant to LPA-induced injury, with no significant increase in infarct size after LPA treatment. Exogenous LPA induced pronounced swelling in mitochondria isolated from WT hearts, while mitochondria from TRPV1K710N hearts showed resistance to LPA challenge. In H9c2 cells, LPA significantly decreased viability in rTRPV1-WT cells and elevated mitochondrial calcium influx relative to rTRPV1-K710N cells. V1-Cal peptide attenuated LPA-mediated myocardial injury in WT hearts and reduced mitochondrial calcium overload in H9c2 cells. Blockade of the TRPV1 K710 site by K710N mutation or V1-Cal peptide mitigates LPA-mediated myocardial injury and mitochondrial damage/dysfunction in isolated mouse hearts. Targeting the cardiac LPA-TRPV1 interaction represents a promising therapeutic strategy against perioperative myocardial injury. Show less

no PDF DOI: 10.1213/ANE.0000000000007907

Mapping comorbid depression and anxiety in Southwest China's ethnic minorities areas: A population-based latent profile and network analysis of 58,739 individuals.

Yongmei Wu, Wenjing Xia, Yang Yang +18 more · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24

Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroup Show more

Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroups, risk factors, and symptom-level interactions underlying depression-anxiety comorbidity across adolescents and adults in multi-ethnic Southwest China. The study included a total of 41,394 adolescents (aged 9-19) and 17,345 adults (aged 18-80). Adolescents were recruited using multistage stratified cluster sampling, whereas adults were recruited by convenience sampling. All participants completed a self-designed sociodemographic questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7). Latent profile analysis identified subgroups, logistic regression analyzed risk/protective factors, and network analysis mapped symptom interactions and bridge nodes. This study found that three adolescent profiles emerged: high (11.66 %), moderate (31.95 %), and low/no depression-anxiety (56.39 %). Adults were classified into low/no comorbidity (90.63 %) and comorbid depression-anxiety (9.37 %). Risk factors for adolescents included female gender (OR = 2.77, 95 %CI: 2.55-3.00; OR = 1.59, 95 %CI: 1.52-1.67), higher grade levels (OR = 3.45, 95 %CI: 3.10-3.84; OR = 3.56, 95 %CI: 3.33-3.80), smoking (OR = 1.72, 95 %CI: 1.51-1.96; OR = 1.28, 95 %CI: 1.17-1.41),drinking (OR = 2.45, 95 %CI: 2.23-2.70; OR = 1.66, 95 %CI: 1.55-1.77), family instability (OR = 1.16, 95 %CI: 1.02-1.31; OR = 1.33, 95 %CI: 1.14-1.56) and "other" ethnic minority (OR = 1.15, 95 %CI: 1.04-1.26). For adults, female gender(OR = 1.68; 95 %CI: 1.44-1.97), living alone(OR = 1.37; 95 %CI: 1.14-1.65), poor self-rated health (OR = 0.13, 95 %CI: 0.11-0.15), and Dai ethnicity (OR = 0.70, 95 %CI: 0.49-0.96) predicted comorbidity. Network analysis revealed distinct bridge symptoms: adolescents in the high depression-anxiety group had five symptoms: depressed or sad mood (phq2), psychomotor agitation/retardation (phq8), nervousness or anxiety (gad1), restlessness (gad5), and irritable (gad6); however, adults with comorbidity had one symptom: afraid something will happen (gad7). This study identified three patterns of depression-anxiety comorbidity in adolescents and two in adults. Efforts should prioritize adolescents from "other" ethnic minorities, strengthening family and peer support, as well as smoking and drinking interventions for adolescents, and addressing social isolation, physical health, and catastrophizing cognition in adults may mitigate the comorbidity burden. Show less

no PDF DOI: 10.1016/j.jad.2025.121112

The dose-response relationship between light physical activity and electronic health literacy among community-dwelling older adults.

Yu Lu, Lin Wang, Shijie Liu +8 more · 2026 · BMC public health · BioMed Central · added 2026-04-24

Yu Lu, Lin Wang, Shijie Liu, Sijun Wu, FengRui Shi, Jie Yu, Yixin Chen, Hong Wang, Linxia Tang, WenChao Gong, AoHan Guo Show less

To investigate the dose-response relationship between e-health literacy and light physical activity (LPA) in older adults is to provide evidence for targeted interventions that enhance e-health litera Show more

To investigate the dose-response relationship between e-health literacy and light physical activity (LPA) in older adults is to provide evidence for targeted interventions that enhance e-health literacy and promote LPA, thereby advancing healthy aging. This study used a convenience sampling method to select two residential neighborhoods. Subsequently, a random cluster sampling approach was employed, resulting in a total final sample of 105 community-dwelling older adults (aged 60 and above) from these neighborhoods. A three-axis accelerometer (ActiGraph wGT3X-BT) recorded the older adults' LPA, and the Electronic Health Literacy Scale assessed their e-health literacy. Multiple linear regression was used to explore the dose-response relationship between LPA and e-health literacy and sub-dimension scores. Multiple linear regression revealed that both the overall e-health literacy score and its components were positively associated with daily LPA (Tables 2 and 3). However, the empirical impact varied substantially across components. For each 1-point increase, LPA increased by 2.8 min for the overall score, 11 min for judgment ability, and 19.4 min for decision-making ability, whereas the effect of application ability was statistically significant but minimal. Notably, the effect sizes of all e-health literacy components were substantially smaller than that of educational attainment (β = 0.638-0.947), which was the strongest predictor in all models. This study provides empirical evidence that higher e-health literacy and its specific sub-dimensions are positively associated with light physical activity (LPA) among community-dwelling older adults, with educational attainment emerging as a key independent predictor. These findings suggest that public health interventions aimed at promoting LPA could be enhanced by incorporating strategies to improve e-health literacy, particularly targeting older adults with lower educational backgrounds. The development of tailored, theory-informed programs based on these insights holds promise for fostering healthy aging at the community level. Show less

📄 PDF DOI: 10.1186/s12889-025-26129-y

Identifying Family Resilience Profiles in Chinese ASD Families: Associations With Social Support, Posttraumatic Growth and Family Stressors.

Ling-Rong Xiao, Si-Jin Liu, Jun-Ru Li +6 more · 2026 · Child: care, health and development · Blackwell Publishing · added 2026-04-24

Ling-Rong Xiao, Si-Jin Liu, Jun-Ru Li, Qiu-Yan Gu, Si-Yan Liu, Yi-Si Jin, Xin-Yu Gan, Hong-Mei Wu, Li-Ying Liu Show less

Families with children diagnosed with autism spectrum disorder (ASD) often encounter significant challenges, manifesting in elevated stress levels and compromised physical and mental well-being. This Show more

Families with children diagnosed with autism spectrum disorder (ASD) often encounter significant challenges, manifesting in elevated stress levels and compromised physical and mental well-being. This study employed Latent Profile Analysis (LPA) to comprehensively examine family resilience attributes among 328 Chinese parents of children with ASD. Drawing on Walsh's family resilience framework and the Double ABCX stress-adaptation model, the research examined how protective factors (social support, posttraumatic growth) and risk factors (family stressors) distinctively characterize resilience profiles and predict profile membership, alongside sociodemographic correlates. Through rigorous statistical analysis, the following three distinct family resilience profiles emerged: adversity (32.31%; characterized by low resilience), ordinary (46.65%; demonstrating moderate resilience) and growth (21.03%; exhibiting high resilience). Critically, the findings revealed that higher family income, perceived social support and posttraumatic growth were associated with higher family resilience, while family stressors were associated with lower family resilience. These insights underscore the importance of developing targeted, personalized intervention strategies that can effectively enhance familial coping mechanisms and psychological adaptation for families navigating the complex challenges of ASD. Show less

no PDF DOI: 10.1111/cch.70222

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