πŸ‘€ Guodong Huang

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Also published as: Ai-Chun Huang, Ai-long Huang, Aijie Huang, Ailong Huang, Aimin Huang, Alden Y Huang, An-Fang Huang, Annie Huang, Aohuan Huang, Ariane Huang, Baihai Huang, Baisong Huang, Bao-Hua Huang, Bao-Yi Huang, Baoqin Huang, Baoying Huang, Benjamin J Huang, Benlin Huang, Bevan E Huang, Bi Huang, Biao Huang, Bin Huang, Binfang Huang, Bing Huang, Bingcang Huang, Bingkun Huang, Bizhi Huang, Bo Huang, Bo-Shih Huang, Bor-Ren Huang, Bowen Huang, Boyue Huang, C Y Huang, Caihong Huang, Caiyun Huang, Can Huang, Canhua Huang, Caoxin Huang, Cathelin Huang, Catherine Huang, Chang Ming Huang, Chang X Huang, Chang-Jen Huang, Changjiang Huang, Chao Huang, Chao Wei Huang, Chao-Wei Huang, Chao-Yuan Huang, Chaolin Huang, Chaoqun Huang, Chaowang Huang, Chaoyang Huang, Chen Huang, Chen-Na Huang, Chen-Ping Huang, Cheng Huang, Chengcheng Huang, Chengrui Huang, Chenshen Huang, Chenxiao Huang, Chi-Cheng Huang, Chi-Shuan Huang, Chia-Chang Huang, Chia-Wei Huang, Chieh-Cheng Huang, Chieh-Liang Huang, Chien-Hsun Huang, Chih-Chun Huang, Chih-Hsiang Huang, Chih-Jen Huang, Chih-Ting Huang, Chih-Yang Huang, Chin-Chang Huang, Chin-Chou Huang, Ching-Shan Huang, Ching-Shin Huang, Ching-Tang Huang, Ching-Wei Huang, Chiu-Ju Huang, Chiu-Jung Huang, Chiun-Sheng Huang, Chong Huang, Chongbiao Huang, Christine S Huang, Chuan Huang, Chuanbing Huang, Chuanhong Huang, Chuanjiang Huang, Chuanjun Huang, Chuansheng Huang, Chuiguo Huang, Chun Huang, Chun-Mei Huang, Chun-Yao Huang, Chun-Yin Huang, Chunfan Huang, Chung-Hsiung Huang, Chunhong Huang, Chunjian Huang, Chunkai Huang, Chunlan Huang, Chunling Huang, Chunshuai Huang, Chunxia Huang, Chunyao Huang, Chunyi Huang, Chunying Huang, Chunyu Huang, Chuxin Huang, Chuying Huang, Congcong Huang, Cuiyu Huang, Da Huang, Dajun Huang, Dan Huang, Dane Huang, Danqing Huang, Dantong Huang, David Huang, David J Huang, De Huang, De-Jun Huang, Dejia Huang, Dengjun Huang, Dianhua Huang, Dishu Huang, Dong Huang, Donglan Huang, Dongmei Huang, Dongni Huang, Dongqin Huang, Dongqing Huang, Dongsheng Huang, Dongyu Huang, Du-Juan Huang, Emily C Huang, Enhao Huang, Enping Huang, Eric Huang, Erya Huang, F Huang, Fan Huang, Fang Huang, Fang-Ling Huang, Fangling Huang, Fei Huang, Fei Wan Huang, Feiruo Huang, Feiteng Huang, Feizhou Huang, Feng Huang, Fengxian Huang, Fengyu Huang, Franklin W Huang, Fu-Chen Huang, Fu-Mei Huang, Fubiao Huang, Fude Huang, Fuhao Huang, Furong Huang, G Huang, Gairong Huang, Gang Huang, Gao-Zhong Huang, Gaoxingyu Huang, Ge Huang, Guang-Jian Huang, Guang-Yun Huang, Guangjian Huang, Guangming Huang, Guangqian Huang, Guangrui Huang, Guanhong Huang, Guanling Huang, Guanning Huang, Guanqun Huang, Guanrong Huang, Guicheng Huang, Guohong Huang, Guoping Huang, Guoqian Huang, Guowei Huang, Guoxing Huang, Guoying Huang, Guoyong Huang, Guoyuan Huang, H Huang, H S Huang, Hai Huang, Haigang Huang, Haihong Huang, Hailin Huang, Haimiao Huang, Haixin Huang, Haiyan Huang, Han-Chang Huang, Hanxia Huang, Hao Huang, Hao-Fei Huang, Haobo Huang, Haochu Huang, Haomin Huang, Haoyu Huang, Haoyue Huang, Haozhang Huang, Haozhong Huang, He Huang, Hefeng Huang, Heguang Huang, Helen Huang, Heming Huang, Hengbin Huang, Heqing Huang, Hete Huang, Hong Huang, Hongbiao Huang, Hongcan Huang, Hongda Huang, Hongfei Huang, Hongfeng Huang, Honghui Huang, Hongou Huang, Hongqiang Huang, Hongyan Huang, Hongyang Huang, Hongyi Huang, Hongying Huang, Hongyu Huang, Hongyun Huang, Hsi-Yuan Huang, Hsien-Da Huang, Hsing-Yen Huang, Hsu Chih Huang, Hsuan-Cheng Huang, Hsuan-Ying Huang, Hu Huang, Hua Huang, Huafei Huang, Huaju Huang, Huan Huang, Huanhuan Huang, Huanliang Huang, Huapin Huang, Huashan Huang, Huayun Huang, Hui Huang, Hui-Huang Huang, Hui-Kuang Huang, Hui-Yu Huang, Huibin Huang, Huifen Huang, Huiling Huang, Huimin Huang, Huina Huang, Huiqiao Huang, Huixian Huang, Huixin Huang, Huiyan Huang, Huiyu Huang, Huizhe Huang, Huizhen Huang, Hy Huang, I-Chieh Huang, J V Huang, Janice J Huang, Jasmin Huang, Jeffrey K Huang, Jia Huang, Jia-Jia Huang, Jiaan Huang, Jiahui Huang, Jiajin Huang, Jiajun Huang, Jian Huang, Jian-Dong Huang, Jiana Huang, Jianbiao Huang, Jianbing Huang, Jianfang Huang, Jianfeng Huang, Jiangfeng Huang, Jiangtao Huang, Jiangwei Huang, Jianhua Huang, Jianlu Huang, Jianmin Huang, Jianming Huang, Jiansheng Huang, Jianzhen Huang, Jiao-Qian Huang, Jiaoti Huang, Jiaotian Huang, Jiaqi Huang, Jiawen Huang, Jiaxing Huang, Jiayu Huang, Jiayue Huang, Jie Huang, Jie Qi Huang, Jiechun Huang, Jieli Huang, Jieling Huang, Jieping Huang, Jin Huang, Jin-Di Huang, Jin-Feng Huang, Jin-Hong Huang, Jin-Yan Huang, Jinbao Huang, Jinfang Huang, Jing Huang, Jing-Fei Huang, Jingang Huang, Jinghan Huang, Jingjing Huang, Jingkun Huang, Jinglong Huang, Jingtao Huang, Jingxian Huang, Jingyong Huang, Jingyuan Huang, Jingyue Huang, Jinhua Huang, Jinling Huang, Jinlu Huang, Jinshu Huang, Jinxing Huang, Jinyan Huang, Jinzhou Huang, Jiuhong Huang, Jiyu Huang, Ju Huang, Juan Huang, Jucun Huang, Jun Huang, Jun-Hua Huang, Jun-You Huang, Junhao Huang, Junhua Huang, Junjie Huang, Junming Huang, Junning Huang, Junqi Huang, Junwen Huang, Junyuan Huang, Junyun Huang, Juxiang Huang, K Huang, K N Huang, Kai Huang, Kaipeng Huang, Kang Huang, Kangbo Huang, Kate Huang, Katherine Huang, Ke Huang, Ke-Ke Huang, Ke-Pu Huang, Kevin Huang, Kevin Y Huang, Kuan-Chun Huang, Kui-Yuan Huang, Kuiyuan Huang, Kun Huang, Kuo-Hsiang Huang, Kuo-Hung Huang, L Huang, L-B Huang, Laiqiang Huang, Lan Huang, Lanlan Huang, Lei Huang, Leijuan Huang, Li Huang, Li-Hao Huang, Li-Jiang Huang, Li-Juan Huang, Li-Jun Huang, Li-Ping Huang, Li-Rung Huang, Li-Wei Huang, Li-Yun Huang, Lian Huang, Liang Huang, Liang-Yu Huang, Liangchong Huang, Lianggui Huang, Libin Huang, Lige Huang, Lihua Huang, Lijia Huang, Lijiang Huang, Lijuan Huang, Lijun Huang, Lili Huang, Limin Huang, Liming Huang, Lin Huang, Linchen Huang, Ling Huang, Ling-Chun Huang, Ling-Jin Huang, Lingling Huang, Lining Huang, Linjing Huang, Linsheng Huang, Linxue Huang, Linyuan Huang, Liping Huang, Liqiong Huang, Lixia Huang, Lixiang Huang, Lixuan Huang, Lixue Huang, Lizhen Huang, Longfei Huang, Lu Huang, Lu-Jie Huang, Lu-Qi Huang, Luanluan Huang, Luqi Huang, Luyang Huang, Luyao Huang, Lvzhen Huang, M C Huang, Man Huang, Manning Y Huang, Manyun Huang, Mao-Mao Huang, Mei Huang, Meihua Huang, Meina Huang, Meixiang Huang, Melissa Y Huang, Meng-Chuan Huang, Meng-Fan Huang, Meng-Na Huang, MengQian Huang, Menghao Huang, Mengjie Huang, Mengjun Huang, Mengnan Huang, Mengting Huang, Mengzhen Huang, Mia L Huang, Miao Huang, Min Huang, Ming-Lu Huang, Ming-Shyan Huang, Mingjian Huang, Mingjun Huang, Minglei Huang, Mingrui Huang, Mingwei Huang, Mingxuan Huang, Mingyu Huang, Mingyuan Huang, Minjun Huang, Minqi Huang, Minxuan Huang, Minyuan Huang, N Huang, Na Huang, Nian Huang, Nianyuan Huang, Ning-Na Huang, Ning-Ping Huang, Ninghao Huang, Nongyu Huang, Pan Huang, Pang-Shuo Huang, Paul L Huang, Pei Huang, Pei-Chi Huang, Pei-Ying Huang, Peiying Huang, Peng Huang, Peng-Fei Huang, Pengyu Huang, Piao-Piao Huang, Piaopiao Huang, Pin-Rui Huang, Ping Huang, Pingping Huang, Pintong Huang, Po-Hsun Huang, Po-Jung Huang, Poyao Huang, Qi Huang, Qi-Tao Huang, Qian Huang, Qiang Huang, Qianqian Huang, Qiaobing Huang, Qibin Huang, Qidi Huang, Qin Huang, Qing Huang, Qing-yong Huang, Qingjiang Huang, Qingke Huang, Qingling Huang, Qingqing Huang, Qingsong Huang, Qingxia Huang, Qingxing Huang, Qingyu Huang, Qingzhi Huang, Qinlou Huang, Qiong Huang, Qiubo Huang, Qiumin Huang, Qiuming Huang, Qiuru Huang, Qiuyin Huang, Qiuyue Huang, Qizhen Huang, Quanfang Huang, Qun Huang, R H Huang, R Stephanie Huang, Rae-Chi Huang, Ran Huang, Renbin Huang, Renhua Huang, Renli Huang, Richard Huang, Richard S P Huang, Riqing Huang, Ritai Huang, Robert J Huang, Rong Huang, Rong Stephanie Huang, Ronghua Huang, Ronghui Huang, Rongjie Huang, Rongrong Huang, Rongxiang Huang, Ru-Ting Huang, Ruby Yun-Ju Huang, Rui Huang, Ruihua Huang, Ruijin Huang, Ruina Huang, Ruiyan Huang, Ruizhen Huang, Runyue Huang, Ruo-Hui Huang, S Huang, S Y Huang, S Z Huang, Saisai Huang, San-Yuan Huang, See-Chang Huang, Sen Huang, Serina Huang, Shan Huang, Shang-Ming Huang, Shanhe Huang, Shanshan Huang, Shaojun Huang, Shaoxin Huang, Shaoze Huang, Shau Ku Huang, Shau-Ku Huang, Shenan Huang, Sheng-He Huang, Shengfeng Huang, Shengjie Huang, Shengnan Huang, Shengyan Huang, Shengyun Huang, Shi-Feng Huang, Shi-Shi Huang, Shi-Ying Huang, Shiang-Suo Huang, Shichao Huang, Shih-Chiang Huang, Shih-Wei Huang, Shih-Yi Huang, Shihao Huang, Shijing Huang, Shilu Huang, Shixia Huang, Shiya Huang, Shiying Huang, Shiyun Huang, Shoucheng Huang, Shu Huang, Shu-Pang Huang, Shu-Pin Huang, Shu-Qiong Huang, Shu-Wei Huang, Shu-Yi Huang, Shu-ying Huang, Shuai Huang, Shuang Huang, Shungen Huang, Shuo Huang, Shushu Huang, Shutong Huang, Shuwen Huang, Si-Yang Huang, Sidong Huang, Sihua Huang, Sijia Huang, Sinchun Huang, Sisi Huang, Sixiu Huang, Song Bin Huang, Song-Mei Huang, Songmei Huang, Songming Huang, Songqian Huang, Steven Huang, Steven Kuan-Hua Huang, Suli Huang, Sung-Ying Huang, Susan M Huang, Suwen Huang, Taiqi Huang, Tang-Hsiu Huang, Tao Huang, Te-Hsuan Huang, Tengda Huang, Tengfei Huang, Tian Hao Huang, Tianhao Huang, Tianpu Huang, Tiantian Huang, Tieqiu Huang, Tim H Huang, Ting Huang, Tinghua Huang, Tingping Huang, Tingqin Huang, Tingting Huang, Tingxuan Huang, Tingyun Huang, Tong Huang, Tongsheng Huang, Tongtong Huang, Tony T Huang, Tse-Shun Huang, Tseng-Yu Huang, Tsung-Wei Huang, Tzu-Rung Huang, Wan-Ping Huang, Way-Ren Huang, Wei Huang, Wei-Chi Huang, Weibin Huang, Weicheng Huang, Weifeng Huang, Weihua Huang, Weijun Huang, Weiqi Huang, Weisu Huang, Weiwei Huang, Weixue Huang, Weizhen Huang, Wen Huang, Wen-yu Huang, Wenbin Huang, Wenda Huang, Wenfang Huang, Wenfeng Huang, Wenhua Huang, Wenji Huang, Wenjie Huang, Wenjun Huang, Wenqiao Huang, Wenqing Huang, Wenqiong Huang, Wenshan Huang, Wentao Huang, Wenxin Huang, Wenya Huang, Wenying Huang, Wunan Huang, Wuqing Huang, X F Huang, X Huang, Xi Huang, Xian-sheng HUANG, Xiang Huang, Xianghua Huang, Xianglong Huang, Xiangming Huang, Xianping Huang, Xianqing Huang, Xiansheng Huang, Xianwei Huang, Xianxi Huang, Xianxian Huang, Xianying Huang, Xianzhang Huang, Xiao Huang, Xiao-Fang Huang, Xiao-Fei Huang, Xiao-Ming Huang, Xiao-Song Huang, Xiao-Yan Huang, Xiao-Yong Huang, Xiao-Yu Huang, XiaoFang Huang, Xiaochun Huang, Xiaofei Huang, Xiaofeng Huang, Xiaohong Huang, Xiaohua Huang, Xiaojie Huang, Xiaojing Huang, Xiaojuan Huang, Xiaolan Huang, Xiaoli Huang, Xiaolin Huang, Xiaoman Huang, Xiaomin Huang, Xiaoqing Huang, Xiaoshuai Huang, Xiaowen Huang, Xiaowu Huang, Xiaoxia Huang, Xiaoyan Huang, Xiaoying Huang, Xiaoyu Huang, Xiaoyuan Huang, Xiaoyun Huang, Xiaozhun Huang, Xiayang Huang, Xichang Huang, Xie-Lin Huang, Xin Huang, Xin-Di Huang, Xinen Huang, Xinfeng Huang, Xingguo Huang, Xingming Huang, Xingqin Huang, Xingru Huang, Xingxu Huang, Xingya Huang, Xingzhen Huang, Xinwen Huang, Xinyi Huang, Xinying Huang, Xinyue Huang, Xinzhu Huang, Xiongfeng Huang, Xionggao Huang, Xiuju Huang, Xiuyun Huang, Xiuzhen Huang, Xiwen Huang, Xu Huang, Xu-Feng Huang, Xuan Huang, Xuanzhang Huang, Xucong Huang, Xudong Huang, Xue-Ying Huang, Xue-shuang Huang, Xuehong Huang, Xuejie Huang, Xuejing Huang, Xuejun Huang, Xuemei Huang, Xueming Huang, Xueqi Huang, Xuewei Huang, Xuezhe Huang, Xuhui Huang, Xuliang Huang, Xun Huang, Xuxiong Huang, Y Huang, Y Joyce Huang, Y S Huang, Ya-Chih Huang, Ya-Dong Huang, Ya-Fang Huang, Ya-Ru Huang, Yabo Huang, Yadong Huang, Yafang Huang, Yajiao Huang, Yajuan Huang, Yali Huang, Yamei Huang, Yan Huang, Yan-Lin Huang, Yan-Qing Huang, Yan-Ting Huang, Yang Huang, Yang Zhong Huang, Yangqing Huang, Yangyang Huang, Yanhao Huang, Yani Huang, Yanjun Huang, Yanlong Huang, Yanna Huang, Yanping Huang, Yanqin Huang, Yanqing Huang, Yanqun Huang, Yanru Huang, Yanshan Huang, Yansheng Huang, Yanxia Huang, Yanyan Huang, Yanyao Huang, Yao Huang, Yao-Kuang Huang, Yaowei Huang, Yatian Huang, Yating Huang, Ye Huang, Yechao Huang, Yen-Chu Huang, Yen-Ning Huang, Yen-Tsung Huang, Yeqing Huang, Yewei Huang, Yi Huang, Yi-Chun Huang, Yi-Jan Huang, Yi-Jia Huang, Yi-Wen Huang, Yi-ping Huang, Yichao Huang, Yichuan Huang, Yicong Huang, Yifan Huang, Yihao Huang, Yiheng Huang, Yihong Huang, Yikeng Huang, Yilin Huang, Yin Huang, Yin-Tsen Huang, Ying Huang, Ying-Hsuan Huang, Ying-Jung Huang, Ying-Zhi Huang, Yinghua Huang, Yingying Huang, Yingzhen Huang, Yingzhi Huang, Yiping Huang, Yiquan Huang, Yishan Huang, Yiwei Huang, Yixian Huang, Yizhou Huang, Yong Huang, Yong-Fu Huang, Yongbiao Huang, Yongcan Huang, Yongjie Huang, Yongqi Huang, Yongsheng Huang, Yongtong Huang, Yongye Huang, Yongyi Huang, Yongzhen Huang, Youheng Huang, Youyang Huang, Yu Huang, Yu-Ching Huang, Yu-Chu Huang, Yu-Chuen Huang, Yu-Chyi Huang, Yu-Fang Huang, Yu-Han Huang, Yu-Jie Huang, Yu-Lei Huang, Yu-Ren Huang, Yu-Shu Huang, Yu-Ting Huang, Yuan Huang, Yuan-Lan Huang, Yuan-Li Huang, Yuan-Lu Huang, Yuancheng Huang, Yuanpeng Huang, Yuanshuai Huang, Yuanyu Huang, Yuanyuan Huang, Yue Huang, Yue-Hua Huang, Yuedi Huang, Yueh-Hsiang Huang, Yuehong Huang, Yuejun Huang, Yueye Huang, Yuezhen Huang, Yufang Huang, Yufen Huang, Yuguang Huang, Yuh-Chin T Huang, Yuhong Huang, Yuhua Huang, Yuhui Huang, Yujia Huang, Yujie Huang, Yulin Huang, Yumei Huang, Yumeng Huang, Yun Huang, Yun-Juan Huang, Yunchao Huang, Yung-Hsin Huang, Yung-Yu Huang, Yunmao Huang, Yunpeng Huang, Yunru Huang, Yunyan Huang, Yuping Huang, Yuqi Huang, Yuqiang Huang, Yuqiong Huang, Yusi Huang, Yutang Huang, Yuting Huang, Yutong Huang, Yuxian Huang, Yuxin Huang, Yuxuan Huang, Yuyang Huang, Yuying Huang, Z Huang, Z Z Huang, Z-Y Huang, Zebin Huang, Zebo Huang, Zehua Huang, Zeling Huang, Zengwen Huang, Zhang Huang, Zhao Huang, Zhaoxia Huang, Zhe Huang, Zhen Huang, Zhenfei Huang, Zheng Huang, Zheng-Xiang Huang, Zhengwei Huang, Zhengxian Huang, Zhengxiang Huang, Zhengyang Huang, Zhenlin Huang, Zhenrui Huang, Zhenyao Huang, Zhenyi Huang, Zhi Huang, Zhi-Ming Huang, Zhi-Qiang Huang, Zhi-Xin Huang, Zhi-xiang Huang, Zhican Huang, Zhicong Huang, Zhifang Huang, Zhifeng Huang, Zhigang Huang, Zhihong Huang, Zhilin Huang, Zhilong Huang, Zhipeng Huang, Zhiping Huang, Zhiqi Huang, Zhiqiang Huang, Zhiqin Huang, Zhiqing Huang, Zhitong Huang, Zhiwei Huang, Zhixiang Huang, Zhiying Huang, Zhiyong Huang, Zhiyu Huang, Zhongbin Huang, Zhongcheng Huang, Zhongfeng Huang, Zhonglu Huang, Zhouyang Huang, Zi-Xin Huang, Zi-Ye Huang, Zicheng Huang, Zichong Huang, Zihan Huang, Zihao Huang, Ziheng Huang, Ziling Huang, Zini Huang, Zirui Huang, Zizhan Huang, Zongjian Huang, Zongliang Huang, Zunnan Huang, Zuotian Huang, Zuxian Huang, Zuyi Huang
articles
Shuiyang Xu, Yunfang Zhou, Mingyu Huang +8 more Β· 2025 Β· Frontiers in public health Β· Frontiers Β· added 2026-04-24
Health literacy plays an important role in disease prevention and control. The aim of this study is to explore the health literacy patterns and associated factors among residents in Zhejiang Province. Show more
Health literacy plays an important role in disease prevention and control. The aim of this study is to explore the health literacy patterns and associated factors among residents in Zhejiang Province. This study included 56,863 residents aged 15-69 years from the 2024 Zhejiang Province Health Literacy Survey. Latent Profile Analysis (LPA) was used to investigate health literacy patterns, and multinomial logistic regression analysis was employed to identify associated factors. Dominance analysis was performed to compare the relative contribution of the main variables associated with health literacy. The analysis identified three distinct health literacy profiles: low literacy (15.13%), moderate literacy (32.24%), and relatively high literacy (52.63%). The low literacy group was characterized by an older demographic (with an average age of 58.71 years), lower educational attainment (20.72% had no formal education), a higher proportion of farmers (52.93%), and a significant share of low-income individuals (40.98%). Multinomial logistic regression and dominance analysis revealed that education level, age, and occupation were the most important associated factors of health literacy. The study findings highlighted the heterogeneity in health literacy among various population groups and emphasized the need for targeted interventions. This study provides empirical evidence to inform precision health promotion strategies in developed regions of China. Show less
πŸ“„ PDF DOI: 10.3389/fpubh.2025.1734757
LPA
Yuan Tian, Zhe Jia, Na Li +5 more Β· 2025 Β· Frontiers in psychology Β· Frontiers Β· 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
πŸ“„ PDF DOI: 10.3389/fpsyg.2025.1694664
LPA
Huatao Zheng, Dan Li, Rentao Ma +3 more Β· 2025 Β· Frontiers in public health Β· Frontiers Β· added 2026-04-24
With the aging population in China, research on preventing frailty is crucial. This study aims to investigate the independent and combined associations of the Dietary inflammatory index (DII) and phys Show more
With the aging population in China, research on preventing frailty is crucial. This study aims to investigate the independent and combined associations of the Dietary inflammatory index (DII) and physical activity (PA) with frailty among Chinese older adults. A total of 285 participants aged β‰₯60β€―years with 87 males and 186 females were recruited from Hunan Province. Daily moderate physical activity (MPA), vigorous physical activity (VPA) and light physical activity (LPA) were objectively measured using a triaxial accelerometer. A Food Frequency Questionnaire 25 (FFQ25) was used to assess the participants' dietary patterns, and DII was calculated. Six combined exposure groups were formed based on PA and DII: pro-inflammatory diet and insufficient PA group, neutral diet and insufficient PA group, anti-inflammatory diet and insufficient PA group, pro-inflammatory diet and sufficient PA group, neutral diet and sufficient PA group, and anti-inflammatory diet and sufficient PA group. Frailty was assessed using the Frailty Phenotype (FP), logistic regression analyzed the associations between dietary patterns, PA, and frailty. A total of 285 older adults participants were initially recruited, but 12 were excluded due to missing data. Consequently, 273 participants were included in the final analysis. Compared to individuals with insufficient PA, those with sufficient PA were associated with significantly lower odds of frailty (ORβ€―=β€―0.468, 95%CIβ€―=β€―0.242-0.907). Participants following an anti-inflammatory diet had significantly lower odds of frailty compared with those following a pro-inflammatory diet (ORβ€―=β€―0.467, 95%CIβ€―=β€―0.221-0.988). In the combined groups, frailty prevalence was significantly lower the group with anti-inflammatory diet and sufficient PA group (ORβ€―=β€―0.204, 95%CIβ€―=β€―0.072-0.583), compared with pro-inflammatory diet and insufficient PA group. The sensitivity analysis showed that the associations between anti-inflammatory diet and sufficient PA with frailty remained statistically significant, with the direction of the associations unchanged. These findings suggest that the results are robust. Our study indicates that adhering to an anti-inflammatory diet and maintaining sufficient PA may be associated with a lower likelihood of frailty. Achieving an adequate amount of PA and following a healthy dietary pattern may serve as potential preventive measures against frailty. Show less
πŸ“„ PDF DOI: 10.3389/fpubh.2025.1739530
LPA
Fengwen Yue, Liping Liu, Qingjiang Huang +3 more Β· 2025 Β· Frontiers in public health Β· Frontiers Β· added 2026-04-24
Prior research has consistently demonstrated that higher levels of digital health literacy contribute positively to improved mental health outcomes and overall quality of life among patients. Neverthe Show more
Prior research has consistently demonstrated that higher levels of digital health literacy contribute positively to improved mental health outcomes and overall quality of life among patients. Nevertheless, the interplay between digital health literacy and the experience of perceived stigma-particularly among burn patients-remains underexplored, and the potential heterogeneity within this relationship has not been adequately addressed. This cross-sectional study, conducted from June to July 2025, recruited 534 burn patients (mean age 31.05β€―Β±β€―9.52β€―years; 61.0% male) from three tertiary hospitals in Sichuan Province, China. Participants completed validated scales assessing digital health literacy, social support, appearance anxiety, perceived stigma, and demographics. Data were analyzed using Pearson correlations, latent profile analysis (LPA) with fit indices, univariate analyses (chi-square tests and Digital health literacy was negatively correlated with perceived stigma ( This study confirms heterogeneity in digital health literacy and perceived stigma among burn patients, with social support and appearance anxiety as key influencers. Findings support targeted interventions to enhance digital health literacy and reduce perceived stigma, advancing precision psychological care for burn survivors. Show less
πŸ“„ PDF DOI: 10.3389/fpubh.2025.1702458
LPA
Jing Li, Yingli Luo, Zaihao Wu +2 more Β· 2025 Β· Frontiers in psychology Β· Frontiers Β· 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
πŸ“„ PDF DOI: 10.3389/fpsyg.2025.1724226
LPA
Jia Zhang, Song Bin Huang, Dan Ni Peng +3 more Β· 2025 Β· Frontiers in psychology Β· Frontiers Β· added 2026-04-24
This study aimed to identify heterogeneous patterns of medical coping modes (MCM) and to examine the moderating role of social support in the relationship between these patterns and social disability Show more
This study aimed to identify heterogeneous patterns of medical coping modes (MCM) and to examine the moderating role of social support in the relationship between these patterns and social disability in young and middle-aged patients after percutaneous coronary intervention (PCI). A cross-sectional study was conducted among 129 post-PCI patients from a single center in China. Participants completed the Medical Coping Modes Questionnaire (MCMQ), the Social Support Rating Scale (SSRS), and the Social Disability Screening Schedule (SDSS). Latent profile analysis (LPA) was used to identify distinct coping patterns. The moderation effect of social support was tested using the Johnson-Neyman technique. Two distinct coping profiles were identified via LPA: "Adaptive Copers" (55.1%), characterized by higher confrontation and lower avoidance/resignation, and "Maladaptive Copers" (44.9%), showing the opposite pattern. A counterintuitive finding emerged, with the Maladaptive Copers reporting significantly lower social disability scores. Furthermore, beyond this profile differentiation, social support demonstrated a significant U-shaped moderating effect in the coping-disability relationship. Its moderating role was statistically significant only at very low (<39.884) and very high (>52.924) levels of support. This study reveals two key findings: first, post-PCI patients are heterogeneous in coping, comprising adaptive and maladaptive subgroups; second, the impact of these coping styles on social disability is non-linearly moderated by social support. Clinicians should assess both coping profiles and social support levels to tailor interventions effectively. Show less
πŸ“„ PDF DOI: 10.3389/fpsyg.2025.1731898
LPA
Yuchen Wang, Qiong Sun, Menachem Hanani +15 more Β· 2025 Β· Journal of translational medicine Β· BioMed Central Β· added 2026-04-24
Demyelination diseases are characterized by injury to large (A-type) myelinated nerve fibers, and by secondary damage to small (C-type) sensory fibers, which leads to chronic pain symptoms, such as al Show more
Demyelination diseases are characterized by injury to large (A-type) myelinated nerve fibers, and by secondary damage to small (C-type) sensory fibers, which leads to chronic pain symptoms, such as allodynia. The mechanisms underlying the interactions between the two fiber types are not clear. This study aims to investigate the role of lysophosphatidic acid (LPA) signaling in satellite glial cells (SGCs) within the dorsal root ganglia (DRG) in demyelination-induced chronic pain. A demyelination model was established by injecting cobra venom into the tibial nerve of 8-10-week-old Sprague-Dawley rats to selectively damage A-fiber myelin. Myelin morphology was observed via transmission electron microscopy (TEM) at 1, 3, 7, and 14 days post-injection. Pain behaviors (mechanical hypersensitivity, thermal hyperalgesia, and spontaneous pain) were assessed to evaluate progression. In vivo electrophysiology was performed to analyze sensory conduction and excitability changes in A- and C-type neurons. Immunofluorescence staining assessed SGC activation, LPA1 receptor (LPA1R) expression, and connexin 43 (Cx43) dynamics in the L4 DRG over time. Pharmacological interventions targeting LPA1R and SGC activation were applied to evaluate their effects on pain behaviors, cytokine release, and neuronal excitability using RT-PCR, ELISA, and spinal electrophysiology. Cobra venom induced a selective A-fiber demyelination and persistent pain in rats. It also upregulated the expression of LPA1R on SGCs that surround large DRG neurons, which normally mediate non-noxious input, and increased gap junction-mediated coupling via Cx43, leading to the activation of SGCs surrounding small nociceptive neurons. The activated SGCs released inflammatory mediators that increased nociceptive neuron excitability, driving chronic pain. In support of these results, pharmacological inhibition of LPA1R-mediated SGCs activation reversed this process. Our study demonstrates that LPA-LPA1R signaling in SGCs drives A-fiber demyelination-induced neuropathic pain by promoting Cx43-mediated SGC-neuron crosstalk and cytokine release. Targeting this pathway may represent a promising strategy to alleviate demyelination-associated chronic pain. Show less
πŸ“„ PDF DOI: 10.1186/s12967-025-07568-y
LPA
Bin Chen, Jing Yang, Wenying Huang +3 more Β· 2025 Β· Frontiers in psychology Β· Frontiers Β· added 2026-04-24
This study aimed to elucidate the psychological mechanisms underlying the relationship between alexithymia and problematic eating behaviors (EB) among older adults. Specifically, we examined whether p Show more
This study aimed to elucidate the psychological mechanisms underlying the relationship between alexithymia and problematic eating behaviors (EB) among older adults. Specifically, we examined whether physical activity (PA) mediated this association, and we further explored the heterogeneity of alexithymia using Latent Profile Analysis (LPA). A cross-sectional survey was conducted among 1,773 community-dwelling older adults in China. Participants completed validated questionnaires assessing alexithymia, PA, and EB. Mediation analysis tested the indirect effect of PA on the alexithymia-EB relationship, while LPA identified subgroups of individuals with distinct alexithymia profiles. Mediation analysis revealed that PA significantly mediated the relationship between alexithymia and maladaptive EB, accounting for 18% of the total effect. LPA supported a three-profile solution: pervasive alexithymia (21.15%), adaptive (72.81%), and affective-cognitive dissociation (6.04%). Profile membership was differentially associated with health behaviors, with the pervasive group showing the most unfavorable outcomes (high EB, low PA), and the adaptive group demonstrating the most favorable pattern. These findings highlight PA as a key behavioral pathway through which alexithymia contributes to maladaptive eating in older adults. Moreover, alexithymia is not uniform but heterogeneous, with distinct profiles that confer varied health behavior risks. Interventions to improve eating habits in elderly populations may benefit from tailoring strategies to alexithymia subtypes and systematically promoting PA as an adaptive regulatory mechanism. Show less
πŸ“„ PDF DOI: 10.3389/fpsyg.2025.1701168
LPA
Yuqing Yuan, Jing Yang, Wenying Huang +3 more Β· 2025 Β· Frontiers in psychology Β· Frontiers Β· added 2026-04-24
Anxiety is significantly correlated with levels of physical activity in university students. This research assessed the effects of anxiety on engagement in physical activity and explored the potential Show more
Anxiety is significantly correlated with levels of physical activity in university students. This research assessed the effects of anxiety on engagement in physical activity and explored the potential mediating function of psychological resilience. Additionally, latent profile analysis (LPA) was employed to identify distinct subtypes based on anxiety and resilience levels, and to explore their associations with physical activity. Utilizing a non-probability convenience sampling approach, this cross-sectional study recruited a total of 1,436 collegiate participants from multiple universities. Data collection was carried out with the Generalized Anxiety Disorder Scale (GAD-7), the abbreviated Connor-Davidson Resilience Scale (CD-RISC-10), and the Physical Activity Rating Scale (PARS-3). Data analysis included mediation effect analysis via Bootstrap methods (Model 4) and latent profile analysis (LPA). Anxiety demonstrated a significant negative association with physical activity ( Results demonstrated that anxiety affects physical activity both directly and indirectly, with the latter effect occurring through the channel of psychological resilience. Latent profile analysis identified three distinct profiles among college students based on anxiety and psychological resilience: High Anxiety-Low Psychological Resilience, Moderate Anxiety-Moderate Psychological Resilience, and Low Anxiety-High Psychological Resilience. Marked variations in physical activity levels were observed among these subgroups. The results underscore the complex relationships among mental health indicators and health behaviors within the collegiate population. The delineation of distinct profiles offers practical implications for designing tailored intervention strategies. Show less
πŸ“„ PDF DOI: 10.3389/fpsyg.2025.1694344
LPA
Xinyi Chen, Wenying Huang, Chang Hu Β· 2025 Β· Frontiers in sports and active living Β· Frontiers Β· added 2026-04-24
This study employed a person-centered Latent Profile Analysis (LPA) to explore adolescents' perceived teacher-student and friendship relationships in the school environment and to examine their associ Show more
This study employed a person-centered Latent Profile Analysis (LPA) to explore adolescents' perceived teacher-student and friendship relationships in the school environment and to examine their association with interest in physical education. A survey was conducted among 3,613 adolescents using the Teacher-Student Relationship Scale, the Friendship Quality Scale, and the Interest in Physical Education Scale. LPA was applied to identify relationship quality profiles, and multinomial logistic regression was used to examine gender differences and associations with interest in physical education. Three profiles emerged from the LPA: the Low Relationship Quality profile (23%, Adolescents exhibit heterogeneous experiences of teacher-student and friendship relationship quality, which were significantly associated with differences in interest in physical education. By applying a person-centered approach, the study extends prior research by showing that teacher-student and friendship contexts are linked to adolescents' interest in physical education, underscoring the importance of considering interest as a distinct outcome in relational research. Show less
πŸ“„ PDF DOI: 10.3389/fspor.2025.1677083
LPA
Nicholas A Han, Philip D Tolley, Jing Huang +9 more Β· 2025 Β· The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association Β· SAGE Publications Β· added 2026-04-24
ObjectiveTo describe characteristic CLEFT-Q response profiles and patterns in patients with cleft palate and/or lip (CP ± L).DesignRetrospective analysis using latent profile analysis (LPA) to categor Show more
ObjectiveTo describe characteristic CLEFT-Q response profiles and patterns in patients with cleft palate and/or lip (CP ± L).DesignRetrospective analysis using latent profile analysis (LPA) to categorize patient-reported outcome responses into distinct profiles.SettingTertiary care pediatric hospital with multidisciplinary cleft team.Patients, ParticipantsPatients aged 8-29 years with CP ± L completing CLEFT-Q questionnaires from September 2021 to June 2025 ( Show less
no PDF DOI: 10.1177/10556656251396633
LPA
Geng-Hao Liu, Yueh-Hsiang Huang, Tzu-Chiao Yuan +9 more Β· 2025 Β· JMIR aging Β· added 2026-04-24
Cognitive decline is a common aspect of aging, and identifying modifiable lifestyle factors, such as physical activity and sleep, is crucial for promoting healthy brain aging. While both are individua Show more
Cognitive decline is a common aspect of aging, and identifying modifiable lifestyle factors, such as physical activity and sleep, is crucial for promoting healthy brain aging. While both are individually linked to cognition, few studies have simultaneously assessed their independent and combined effects using objective wearable-based data, particularly in older Asian populations. This study aimed to examine the independent and interactive effects of wearable-assessed sleep and physical activity parameters on memory performance in healthy older adults. We also explored whether age and hippocampal volume moderated these associations. This prospective cross-sectional analysis included 88 cognitively healthy community-dwelling adults (β‰₯60 years of age) from the Integrating Systematic Data of Geriatric Medicine to Explore the Solution for Healthy Aging cohort in Taiwan. Participants underwent 12-day wrist-worn actigraphy, brain magnetic resonance imaging, and neuropsychological assessments. Light-intensity physical activity (LPA) and wake after sleep onset (WASO) were selected based on age-adjusted partial correlations with Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Battery memory scores. Multivariate regressions, age-stratified models (cutoff=72 years), and PROCESS moderation and mediation analyses were conducted, adjusting for age, education, daytime sleepiness, and hippocampal volume. Partial correlation analyses adjusting for age showed that higher LPA (r=0.260; P=.02) and lower WASO (r=-0.251; P=.02) were significantly associated with better memory scores. Age significantly moderated both effects: LPA was beneficial beyond 73.8 years of age, and WASO was detrimental beyond 71.1 years of age. Multivariate regression models confirmed that both WASO (Ξ²=-.044; P=.04) and LPA (Ξ²=.042; P=.01) were significant predictors of memory. In subgroup analyses (age β‰₯72 years), both LPA (Ξ²=.054; P=.04) and WASO (Ξ²=-.111; P=.01) remained significant predictors. Moderated mediation analyses showed that WASO was associated with reduced LPA (Ξ²=-.325; P=.03), but the indirect effect on memory via LPA was not significant. Instead, WASO exerted a direct and age-moderated effect on memory performance. Hippocampal volume moderated both associations, supporting the brain reserve hypothesis. Our findings highlight WASO and LPA, as measured by wearable devices, as modifiable behavioral factors linked to memory function in older adults. The impact of these factors intensifies with advancing age and may be influenced by hippocampal reserve. Promoting daily light physical activity and maintaining sleep continuity may serve as accessible, age-tailored strategies for preserving cognitive health in aging populations. ClinicalTrials.gov NCT04207502; https://classic.clinicaltrials.gov/ct2/show/NCT04207502. Show less
πŸ“„ PDF DOI: 10.2196/80584
LPA
Ying Huang, Jialin Wang, Wanying Ni +5 more Β· 2025 Β· Journal of advanced nursing Β· Blackwell Publishing Β· added 2026-04-24
The study aimed to characterise presenteeism among nurses and identify nurses' presenteeism associated with distinct latent profiles. This study employed a cross-sectional descriptive approach. From J Show more
The study aimed to characterise presenteeism among nurses and identify nurses' presenteeism associated with distinct latent profiles. This study employed a cross-sectional descriptive approach. From July to December 2024, data were collected from 404 Chinese clinical nurses across four tertiary hospitals in Sichuan Province, Southwest China, using demographic questionnaires, the Stanford Presenteeism Scale (SPS-6), and the Challenge- and Hindrance-Related Self-Reported Stress Scale (C-HSS). A latent profile analysis was conducted on SPS-6 scores using Mplus 8.3, followed by univariate analyses to compare characteristics across subgroups. The total mean score of nurses' presenteeism is (16.13 ± 4.46), with approximately 59.4% classified as having a high level of presenteeism. Four latent profiles of nurses' presenteeism were identified through LPA: low fatigue-low work constraint (19.8%), low fatigue-high work constraint (33.9%), high fatigue-low work constraint (18.8%), and high fatigue-high work constraint (27.5%). Nurses demonstrated moderately severe presenteeism, with LPA revealing four distinct phenotypes characterised by divergent fatigue- work constraint configurations. This heterogeneity underscores the need for stratified interventions addressing unique risk profiles across subgroups. Administrators should adopt targeted interventions according to the characteristics of nurses in different profiles to minimise nurses' loss of productivity. This study addresses the evidence gap regarding the significant heterogeneity of presenteeism among nurses and the lack of precise identification, and identifies four distinct latent profiles of presenteeism. The findings provide critical evidence for nursing managers to design and implement differentiated intervention strategies tailored to groups with different risk characteristics. The study followed the STROBE guideline. This study did not include patient or public involvement in its design, conduct or reporting. Show less
no PDF DOI: 10.1111/jan.70375
LPA
Yuanyuan Li, Qiaolin Yu, Rong Yao +11 more Β· 2025 Β· Patient preference and adherence Β· added 2026-04-24
The treatment of multidrug-resistant tuberculosis (MDR-TB) is characterized by a prolonged duration and complex medication regimens, often resulting in a substantial medication-related burden that neg Show more
The treatment of multidrug-resistant tuberculosis (MDR-TB) is characterized by a prolonged duration and complex medication regimens, often resulting in a substantial medication-related burden that negatively impacts patients' adherence and quality of life. However, research on the heterogeneity of medication-related burden among MDR-TB patients and its influencing factors remains limited. This study aimed to identify latent profiles of medication-related burden among MDR-TB patients and examine differences in burden characteristics across these profiles, thereby providing evidence for tailored intervention strategies. A convenience sampling method was employed to recruit MDR-TB patients diagnosed at a tertiary infectious disease hospital in Chengdu between December 2024 and May 2025. Data were collected using a general information questionnaire, the Living with Medicines Questionnaire (LMQ), and the Health Literacy Management Scale (HeLMS). Latent profile analysis (LPA) was conducted to identify distinct profiles of medication-related burden, and multivariate logistic regression was used to explore associated factors for each profile. A total of 214 valid responses were analyzed. The LPA identified two distinct profiles of medication-related burden: C1 - "Low-Burden (Attitude & Practice-Dominated)" (44%) and C2 - "High-Burden (Daily Interference-Dominated)" (56%). Absence of side effects, not employing a caregiver, and higher levels of health literacy were positively associated with membership in the C1 group ( Medication-related burden among MDR-TB patients exhibits clear heterogeneity. Healthcare professionals should adopt stratified management and personalized interventions based on the identified influencing factors to alleviate the burden of medication in this population. Show less
πŸ“„ PDF DOI: 10.2147/PPA.S558068
LPA
Li Zhang, Kai Niu, Yinglu Sun +9 more Β· 2025 Β· Quantitative imaging in medicine and surgery Β· added 2026-04-24
Assessing white matter hyperintensity (WMH) is essential for the diagnosis, treatment, and prognosis of multiple sclerosis (MS) and neuromyelitis optical spectrum disorder (NMOSD). MS and NMOSD presen Show more
Assessing white matter hyperintensity (WMH) is essential for the diagnosis, treatment, and prognosis of multiple sclerosis (MS) and neuromyelitis optical spectrum disorder (NMOSD). MS and NMOSD present dispersed small lesions alongside larger aggregated lesions that are irregularly shaped, posing challenges for the automatic segmentation of WMH on magnetic resonance images. Furthermore, research on NMOSD brain WMH segmentation is limited due to the rare nature of the disease. This study aims to propose a deep learning method for MS and NMOSD brain WMH segmentation. In this study, we propose a 2.5D Fourier Convolutional ResUnet (FrC-ResUnet). It utilizes a spectral encoder to extract global information, enabling accurate segmentation of scattered lesions. Additionally, the model incorporates the selective features module (SFM) and the convolutional block attention module (CBAM) to enhance lesion-background differentiation and outline the lesions distinctly. We evaluated our approach on the MS public and local datasets of MS and NMOSD. Compared to U-Net, ResUNet, FC-DenseNet, AttentionUNet, lesion prediction algorithm (LPA) and Sequence Adaptive Multimodal SEGmentation (SAMSEG), the 2.5D FrC-ResUnet achieved the highest Dice similarity coefficient (DSC) on three different datasets, with values of 0.710, 0.667, and 0.822, respectively. The 2.5D FrC-ResUnet demonstrates accurate and robust segmentation of NMOSD brain WMH. Meanwhile, the model excels in segmenting MS brain WMH, particularly when confronted with irregularly shaped and dispersed lesions. Show less
πŸ“„ PDF DOI: 10.21037/qims-24-2384
LPA
Rui Li, Wenyue Dong, Wenxiu Wang +5 more Β· 2025 Β· Science bulletin Β· Elsevier Β· added 2026-04-24
no PDF DOI: 10.1016/j.scib.2025.10.005
LPA
Yu Peng, Yiqing Gao, Lin Huang +10 more Β· 2025 Β· Sleep & breathing = Schlaf & Atmung Β· Springer Β· 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
πŸ“„ PDF DOI: 10.1007/s11325-025-03470-5
LPA
Dianjie Li, Shilei Pan, Wei Cai +2 more Β· 2025 Β· BMC pregnancy and childbirth Β· BioMed Central Β· added 2026-04-24
Given the heightened risk of complications during pregnancy in women of advanced maternal age (AMA), it is crucial to understand the metabolites in amniotic fluid and umbilical cord blood in this demo Show more
Given the heightened risk of complications during pregnancy in women of advanced maternal age (AMA), it is crucial to understand the metabolites in amniotic fluid and umbilical cord blood in this demographic.Β  METHODS: We analyzed the metabolites in amniotic fluid from 60 women, divided into two groups: the AMA group (aged 35 or above, n = 29), and the control group (aged below 35, n = 31). We then conducted a follow-up analysis on the metabolites of umbilical cord blood from a sample of 19 women (9 from the AMA group, and 10 from the control group). In total, we identified 96 differential metabolites in the amniotic fluid and 146 in the cord blood between the two groups. The significant changes in the metabolites of the amniotic fluid mainly involved sphingolipid metabolism, steroid hormone biosynthesis, and cholesterol metabolism. Conversely, the preliminary significant changes in cord blood metabolites were mainly linked to metabolism of arginine and proline, degradation of valine, leucine, and isoleucine, fatty acid metabolism, alanine, aspartate and glutamate metabolism, and the biosynthesis of unsaturated fatty acids. Further analysis revealed a significant upregulation of lysophosphatidylcholine (LPC), phosphatidylcholine (PC), and taurodeoxycholic acid in the amniotic fluid. In the cord blood, various forms of lysophosphatidic acid (LPA), sphingomyelin (SM), phosphatidylglycerol (PG), LPC, and PC were found preliminarily to be either upregulated or downregulated. Our results preliminarily showed that the metabolites of amniotic fluid and cord blood in AMA women differed significantly from the control group. These findings provide crucial insights for future research to explore the role of metabolomics in adverse pregnancy outcomes in AMA women. Show less
πŸ“„ PDF DOI: 10.1186/s12884-025-08118-6
LPA
Cong Liu, Zuommiao Xiao, Zhengting Liu +1 more Β· 2025 Β· Clinical laboratory Β· added 2026-04-24
Endometrial cancer (EC) is a malignant tumor arising from the endometrial epithelium and is among the most prevalent gynecological malignancies worldwide. Increasing evidence suggests that lipid profi Show more
Endometrial cancer (EC) is a malignant tumor arising from the endometrial epithelium and is among the most prevalent gynecological malignancies worldwide. Increasing evidence suggests that lipid profiles, hyperglycemia, and other metabolic factors play a role in EC pathogenesis. However, research on the association between lipoprotein(a) [Lp(a)] levels and EC prognosis remains limited. This retrospective cohort study analyzed Lp(a) levels in patients diagnosed with EC at Ganzhou Hospital, affiliated with Nanchang University, between January 2017 and January 2022. Lp(a) concentrations were measured post-admission, and patient prognosis was categorized as favorable or poor. Multivariate logistic regression analysis was performed to determine the adjusted odds ratio (OR) and 95% confidence interval (CI). The study included 296 EC patients, out of whom 72.3% (214/296) had a favorable prognosis, defined as no recurrence within five years post-surgery. The overall healing rate was 72.3% (214/296). When stratified by Lp(a) levels, patients in the first quantile (Q1 ≀ 122.2 g/L) had a favorable prognosis rate of 77.7% (115/148), whereas those in the second quantile (Q2 > 122.2 g/L) had a rate of 66.9% (99/148), with a statistically significant difference between groups (p < 0.05). In the multivariate regression model, the log2-transformed Lp(a) values and their corresponding ORs (95% CIs) for prognosis at two upper normal limits (ULN) were 1.7248 (1.0288 - 2.8918) and 2.0365 (1.1843 - 3.5018), respectively. Interaction analysis indicated that Lp(a) levels significantly influenced EC prognosis. Lp(a) is strongly associated with EC prognosis and holds potential clinical significance. Further studies are required to validate these findings. Show less
no PDF DOI: 10.7754/Clin.Lab.2025.250239
LPA
Zhiqiang Ren, Yutai Cai, Qiaoman Mo +5 more Β· 2025 Β· Journal of sports sciences Β· Taylor & Francis Β· added 2026-04-24
This study aimed to investigate the association between objectively and subjectively measured 24-hour movement behaviors and physical fitness, and explore how the reallocation of time between 24-hour Show more
This study aimed to investigate the association between objectively and subjectively measured 24-hour movement behaviors and physical fitness, and explore how the reallocation of time between 24-hour movement behaviors is associated with changes in physical fitness in adolescents. A total of 690 adolescents aged 14-17 years (55% girls) were included in this cross-sectional study conducted in Foshan, China. Moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior, and sleep were assessed using accelerometers in combination with a questionnaire. Physical fitness was tested through body mass index, forced vital capacity, 50-m sprint, standing long jump, sit-and-reach, gender-specific 800/1000-m run, and pull-ups/sit-ups. MVPA was significantly associated with better performance in the 50-m sprint ( Show less
no PDF DOI: 10.1080/02640414.2025.2567791
LPA
Yujiao Zhao, Luyang Ma, Weijun Li +9 more Β· 2025 Β· BMC pregnancy and childbirth Β· BioMed Central Β· added 2026-04-24
To investigate longitudinal changes in pelvic floor support in primiparous women with pelvic organ prolapse (POP) after vaginal delivery, focusing on single- and multiple-compartment involvement. Two Show more
To investigate longitudinal changes in pelvic floor support in primiparous women with pelvic organ prolapse (POP) after vaginal delivery, focusing on single- and multiple-compartment involvement. Two hundred primiparas after vaginal delivery were prospectively enrolled and underwent pelvic floor MRI at six weeks postpartum. POP was diagnosed and classified into subgroups (single or multiple compartments involved) based on MRI findings. Primiparas with POP underwent repeat MRI at four months postpartum. Pelvic floor measurements, including injury score and functional parameters of the levator ani muscle (puborectal hiatus line, H line; muscular pelvic floor relaxation line, M line; levator hiatus area, LHA; iliococcygeus angle, ICA; levator plate angle, LPA), were assessed on MRI. Measurements were compared among POP subgroups and a normal control group (without POP) at six weeks postpartum. Additionally, changes between six weeks and four months postpartum were analyzed within POP subgroups. Based on MRI criteria, approximately 41.5% of primiparas were diagnosed with POP, predominantly cystoceles commonly associated with uterine prolapse. Functional parameters of the levator ani, except for LPA at rest, were significantly increased in POP subgroups compared to controls. At four months postpartum, M line, H line, and LPA significantly decreased, and prolapsed organs were elevated in cases with multiple compartments involved, compared to six weeks postpartum. No significant changes were observed in cases with single-compartment involvement during follow-up. A substantial proportion of primiparas experienced postpartum POP. Impaired levator ani function contributed to POP. Pelvic floor support improved during early postpartum in cases with multiple-compartment involvement. Show less
πŸ“„ PDF DOI: 10.1186/s12884-025-08044-7
LPA
Xiaohuang Yang, Shaoxing Chen, Leijuan Huang +3 more Β· 2025 Β· Medicine Β· added 2026-04-24
Colorectal cancer (CRC) constitutes a significant public health burden in both China and the United States of America (USA), with low physical activity (LPA) identified as a key modifiable risk factor Show more
Colorectal cancer (CRC) constitutes a significant public health burden in both China and the United States of America (USA), with low physical activity (LPA) identified as a key modifiable risk factor. This study aimed to characterize temporal trends in CRC burden attributable to LPA in these 2 nations from 1990 to 2021. Using data from the 2021 global burden of disease database, age and sex-specific disparities in CRC burden attributed to LPA were evaluated in both countries. Trend analyses of age-standardized mortality rates and age-standardized disability-adjusted life year rates were performed using joinpoint regression. Decomposition analysis was applied to disentangle contributions from demographic aging, population growth, and epidemiological transitions. The age-period-cohort model was employed to quantify the independent effects of age, period, and birth cohort. Bayesian age-period-cohort modeling was utilized to project future CRC burden attributed to LPA through 2036. In 2021, LPA-attributable CRC mortality cases in China reached 16,698 (95% uncertainty interval: 10,065-24,626), exhibiting a 191.16% increase from 1990. The number of disability-adjusted life years attributed to LPA totaled 3,20,464 (95% uncertainty interval: 1,92,275-4,74,070), reflecting a 149.67% rise over the same period. Conversely, the USA reported more moderate increases of 18.26% in LPA-attributable CRC deaths and 20.28% in disability-adjusted life years. The age-period-cohort model revealed that the disease burden in both countries is shifting towards younger age groups. Further analysis of each state in the USA revealed that in 2021, the burden on low-income groups was heavier. The Bayesian age-period-cohort model predicts that the burden of CRC caused by LPA in the 2 countries will show a significant upward trend by 2036. As the burden of CRC caused by LPA becomes increasingly severe in China and the USA, there is an urgent need to raise public awareness about how physical activity can help prevent CRC and for policymakers to create targeted public health policies to lower this disease burden. Show less
no PDF DOI: 10.1097/MD.0000000000044664
LPA
Caili Li, Xiaoqian Lu, Liyan Zhang +10 more Β· 2025 Β· BMC nursing Β· BioMed Central Β· added 2026-04-24
This study aimed to analyze latent profiles and characteristics of nurses' knowledge, attitudes, and practices (KAP) regarding pressure injury (PI) prevention, as well as influencing factors across di Show more
This study aimed to analyze latent profiles and characteristics of nurses' knowledge, attitudes, and practices (KAP) regarding pressure injury (PI) prevention, as well as influencing factors across distinct profiles. A convenience sampling method was employed to recruit nurses from hospitals at various tiers in Guangxi Zhuang Autonomous Region between July and August 2024. Data were collected using a General Information Questionnaire and a Nurse PI-KAP Questionnaire. Latent profile analysis (LPA) identified distinct PI-KAP profiles, while univariate analysis and multinomial logistic regression determined profile-specific influencing factors. Among 17,253 enrolled nurses, the total PI-KAP score was 63.44 ± 7.69. Three latent profiles emerged: low-level PI-KAP (12.82%), moderate-level PI-KAP (52.23%), and high-level PI-KAP (34.95%). Multinomial logistic regression revealed that hospital tier, years of experience, education level, professional title, gender, and attitudes toward PI training significantly influenced PI-KAP profiles (p < .05). Heterogeneity exists in nurses' PI-KAP profiles, with a substantial proportion demonstrating suboptimal competency. Nursing administrators should establish hierarchical training systems tailored to PI-KAP characteristics. Capacity-building strategies include prioritizing training for core nurses, optimizing resource allocation, and establishing tiered hospital assistance mechanisms to enhance team-based PI prevention capabilities. Not applicable. Show less
πŸ“„ PDF DOI: 10.1186/s12912-025-03875-3
LPA
Chen-Ling Kuo, Chih-Chung Wu, Yu-Shan Cheng +3 more Β· 2025 Β· Lipids in health and disease Β· BioMed Central Β· 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 ± 37.0Β mg/dL vs. 15.5 ± 2.5Β 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-Ξ³ (PPAR-Ξ³), 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-Ξ³ coactivator-1Ξ± (PGC-1Ξ±), 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
πŸ“„ PDF DOI: 10.1186/s12944-025-02835-9
LPL
Yang Yu, Yuqin Ma, Meiling Cheng +5 more Β· 2025 Β· Frontiers in neuroscience Β· Frontiers Β· added 2026-04-24
This study investigated the brain functional characteristics of patients with neuropathic pain (NP) following spinal cord injury (SCI) using functional near-infrared spectroscopy (fNIRS). A total of 3 Show more
This study investigated the brain functional characteristics of patients with neuropathic pain (NP) following spinal cord injury (SCI) using functional near-infrared spectroscopy (fNIRS). A total of 35 subjects were enrolled, including 10 able-bodied controls, 12 patients with SCI and NP (SCI-NP), and 13 patients with SCI (without NP). fNIRS was used to detected blood oxygen signals during motor tasks and resting-state (RS) functional connectivity (FC) in the subjects. We also performed Pearson correlation analyses of pain scores (NPS) and the Pittsburgh Sleep Quality Index (PSQI) in patients with SCI-NP. Statistical analyses were performed using Shapiro-Wilk test for normality; paired During the task state, patients with SCI-NP activated bilateral primary somatosensory cortex (S1, L/R Patients with SCI-NP exhibit significant abnormal cerebral cortical excitation and reduced FC. HbO is a potential biomarker for evaluating NP. fNIRS supports objective assessment of SCI-NP and rehabilitation strategy formulation [ChiCTR2500097098]. Show less
πŸ“„ PDF DOI: 10.3389/fnins.2025.1699161
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Xi Huang, Zhangshan Gao, Peichao Gao +4 more Β· 2025 Β· Probiotics and antimicrobial proteins Β· Springer Β· added 2026-04-24
Intensive poultry farming has significantly increased the incidence of lipid metabolic disorders, severely compromising the economic benefits of poultry industry. Currently, gamma-aminobutyric acid (G Show more
Intensive poultry farming has significantly increased the incidence of lipid metabolic disorders, severely compromising the economic benefits of poultry industry. Currently, gamma-aminobutyric acid (GABA) is primarily used to mitigate adverse effects of heat stress in poultry, while the effects and mechanisms of GABA on lipid metabolism disorders remain underexplored. Lactobacillus plantarum (L. plantarum) serves as a significant source of GABA and is widely used in the livestock industry. This study therefore examines the effects of postbiotic GABA and the GABA-producing probiotic L. plantarum 1-2-3 on abdominal adipose tissue of laying hens following corticosterone-induced stress. To this end, hens subjected to corticosterone subcutaneous injections (4Β mg/kg of body weight) were respectively received GABA (100Β mg/kg BW) or L. plantarum 1-2-3 (1 × 10⁹ CFU/day). Results demonstrated that both GABA and L. plantarum 1-2-3 alleviated corticosterone-induced lipid metabolism disorders and reduced adipocyte size in abdominal fat. Additionally, expression analyses of genes and proteins related to lipid metabolism (PPARΞ³, C/EBPΞ±, CD36, LPL, ATGL, and HSL) further showed that GABA and L. plantarum 1-2-3 inhibited excessive deposition of abdominal lipids in laying hens by suppressing adipogenesis and lipogenesis, while promoting lipolysis. Moreover, GABA and L. plantarum 1-2-3 both mitigated lipid deposition-induced inflammation and oxidative damage by normalizing macrophage infiltration and improving antioxidative enzyme activities (GSH-Px, T-SOD, CAT). These findings demonstrate the efficacy of GABA and L. plantarum 1-2-3 in alleviating lipid metabolism disorders in the abdominal adipose tissue of laying hens, suggesting their promise as nutritional supplements for counteracting stress-induced metabolic dysfunction. Show less
πŸ“„ PDF DOI: 10.1007/s12602-025-10869-9
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Shengwang Jiang, Chaoyun Yang, Chen Ji +6 more Β· 2025 Β· Frontiers in veterinary science Β· Frontiers Β· added 2026-04-24
This study aims to investigate the effect of fermented onion on Liangshan black sheep's growth performance, health, meat quality, and rumen metabolite profiles. A total of 80 four-month-old female Lia Show more
This study aims to investigate the effect of fermented onion on Liangshan black sheep's growth performance, health, meat quality, and rumen metabolite profiles. A total of 80 four-month-old female Liangshan black sheep were randomly divided into four groups of five replicate pens (four sheep per pen). Sheep were fed a basal diet supplemented with 0 (control), 10, 20% or 30% fermented onion. Compared to that of the control group, dietary supplementation with 20% fermented onion improved final body weight, ADG and ADFI; enhanced GPT and GOT activities and increased IgA, IgG, IgM, C3, and C4 levels; increased the levels of IL-4, IL-10, TGF- Show less
πŸ“„ PDF DOI: 10.3389/fvets.2025.1695023
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Jianing Gu, Xue Tian, Tiantian Wang +10 more Β· 2025 Β· Aquaculture nutrition Β· added 2026-04-24
The current trial sought to assess the impact of fermented chicory root waste (FCRW) dietary administration on growth, lipid metabolism, chemical composition, and intestinal barrier pathway in common Show more
The current trial sought to assess the impact of fermented chicory root waste (FCRW) dietary administration on growth, lipid metabolism, chemical composition, and intestinal barrier pathway in common carp ( Show less
πŸ“„ PDF DOI: 10.1155/anu/2234393
LPL
Shuhuang Chen, Nian Han, Yujie Huang +5 more Β· 2025 Β· International journal of molecular sciences Β· MDPI Β· added 2026-04-24
2,2',4,4'-tetrabromodiphenyl ether (BDE-47) is a common environmental contaminant and widely detected in aquatic surroundings, while only a few reports exist on the hazard mechanism in economic aquati Show more
2,2',4,4'-tetrabromodiphenyl ether (BDE-47) is a common environmental contaminant and widely detected in aquatic surroundings, while only a few reports exist on the hazard mechanism in economic aquatic animals. It has been shown that 40 and 4000 ng/g of BDE-47 dietary exposure over 42 days significantly increased the levels of blood triglycerides, glucose, and liver glycogen in carp ( Show less
πŸ“„ PDF DOI: 10.3390/ijms262010152
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Bo Yang, Huigen Luo, Xutong Yan +6 more Β· 2025 Β· Journal of nanobiotechnology Β· BioMed Central Β· added 2026-04-24
Radiation therapy for malignant tumor patients often induces radiation enteritis (RE), a condition that impairs their quality of life. Currently, there is no standard treatment regimen available. In t Show more
Radiation therapy for malignant tumor patients often induces radiation enteritis (RE), a condition that impairs their quality of life. Currently, there is no standard treatment regimen available. In this study, we used lyophilized apoptotic vesicles (Lpl-apoVs) from umbilical cord mesenchymal stem cells to treat RE in a murine model. We show that enema administration of lyophilized apoVs can ameliorate intestinal damage in RE mice. Mechanistically, Lpl-apoVs were internalized by intestinal endothelial cells (IECs) to alleviate radiation-induced DNA damage. In addition, mitophagy was identified as a prerequisite for therapeutic efficacy, suggesting that rescue of DNA damage and restoration of mitochondrial quality are collaboratively to ameliorate RE diseased phenotypes. These findings indicate that enema administration of Lpl-apoVs is a novel strategy for RE therapy. [Image: see text] The online version contains supplementary material available at 10.1186/s12951-025-03592-8. Show less
πŸ“„ PDF DOI: 10.1186/s12951-025-03592-8
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