👤 Hong-Li Yang

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Also published as: A Yang, A-Li Yang, Acong Yang, Ai-Lun Yang, Aige Yang, Airong Yang, Aiting Yang, Aizhen Yang, Albert C Yang, Alex J T Yang, An-Qi Yang, Andrew Yang, Angang Yang, Angela Wei Hong Yang, Anni Yang, Aram Yang, B Yang, Baigao Yang, Baixia Yang, Bangjia Yang, Bao Yang, Baofeng Yang, Baoli Yang, Baoxin Yang, Baoxue Yang, Bei Yang, Beibei Yang, Biao Yang, Bin Q Yang, Bin Yang, Bing Xiang Yang, Bing Yang, Bingyu Yang, Bo Yang, Bohui Yang, Boo-Keun Yang, Bowen Yang, Boya Yang, Burton B Yang, Byoung Chul Yang, Caimei Yang, Caixia Yang, Caixian Yang, Caixin Yang, Can Yang, Canchai Yang, Ce Yang, Celi Yang, Chan Mo Yang, Chan-Mo Yang, Chang Yang, Chang-Hao Yang, Changheng Yang, Changqing Yang, Changsheng Yang, Changwei Yang, Changyun Yang, Chanjuan Yang, Chao Yang, Chao-Yuh Yang, Chaobo Yang, Chaofei Yang, Chaogang Yang, Chaojie Yang, Chaolong Yang, Chaoping Yang, Chaoqin Yang, Chaoqun Yang, Chaowu Yang, Chaoyun Yang, Chaozhe Yang, Chen Die Yang, Chen Yang, Cheng Yang, Cheng-Gang Yang, Chengfang Yang, Chenghao Yang, Chengkai Yang, Chengkun Yang, Chengran Yang, Chenguang Yang, Chengyingjie Yang, Chengzhang Yang, Chensi Yang, Chensu Yang, Chenxi Yang, Chenyu Yang, Chenzi Yang, Chi Yang, Chia-Wei Yang, Chieh-Hsin Yang, Chien-Wen Yang, Chih-Hao Yang, Chih-Min Yang, Chih-Yu Yang, Chihyu Yang, Ching-Fen Yang, Ching-Wen Yang, Chongmeng Yang, Chuan He Yang, Chuan Yang, Chuanbin Yang, Chuang Yang, Chuanli Yang, Chuhu Yang, Chun Yang, Chun-Chun Yang, Chun-Mao Yang, Chun-Seok Yang, Chunbaixue Yang, Chung-Hsiang Yang, Chung-Shi Yang, Chung-Yi Yang, Chunhua Yang, Chunhui Yang, Chunjie Yang, Chunjun Yang, Chunlei Yang, Chunli Yang, Chunmao Yang, Chunping Yang, Chunqing Yang, Chunru Yang, Chunxiao Yang, Chunyan Yang, Chunyu Yang, Congyi Yang, Cui Yang, Cuiwei Yang, Cunming Yang, Dai-Qin Yang, Dan Yang, Dan-Dan Yang, Dan-Hui Yang, Dandan Yang, Danlu Yang, Danrong Yang, Danzhou Yang, Dapeng Yang, De-Hua Yang, De-Zhai Yang, Decao Yang, Defu Yang, Deguang Yang, Dehao Yang, Dehua Yang, Dejun Yang, Deli Yang, Dengfa Yang, Deok Chun Yang, Deshuang Yang, Di Yang, Dianqiang Yang, Ding Yang, Ding-I Yang, Diya Yang, Diyuan Yang, Dong Yang, Dong-Hua Yang, Dongfeng Yang, Dongjie Yang, Dongliang Yang, Dongmei Yang, Dongren Yang, Dongshan Yang, Dongwei Yang, Dongwen Yang, DuJiang Yang, Eddy S Yang, Edwin Yang, Ei-Wen Yang, Emily Yang, Enlu Yang, Enzhi Yang, Eric Yang, Eryan Yang, Ethan Yang, Eunho Yang, Fajun Yang, Fan Yang, Fang Yang, Fang-Ji Yang, Fang-Kun Yang, Fei Yang, Feilong Yang, Feiran Yang, Feixiang Yang, Fen Yang, Feng Yang, Feng-Ming Yang, Feng-Yun Yang, Fengjie Yang, Fengjiu Yang, Fengjuan Yang, Fenglian Yang, Fengling Yang, Fengping Yang, Fengying Yang, Fengyong Yang, Fu Yang, Fude Yang, Fuhe Yang, Fuhuang Yang, Fumin Yang, Fuquan Yang, Furong Yang, Fuxia Yang, Fuyao Yang, G Y Yang, G Yang, Gan Yang, Gang Yang, Gangyi Yang, Gao Yang, Gaohong Yang, Gaoxiang Yang, Ge Yang, Gong Yang, Gong-Li Yang, Grace H Y Yang, Guan Yang, Guang Yang, Guangdong Yang, Guangli Yang, Guangwei Yang, Guangyan Yang, Guanlin Yang, Gui-Zhi Yang, Guigang Yang, Guitao Yang, Guo Yang, Guo-Can Yang, Guobin Yang, Guofen Yang, Guojun Yang, Guokun Yang, Guoli Yang, Guomei Yang, Guoping Yang, Guoqi Yang, Guosheng Yang, Guotao Yang, Guowang Yang, Guowei Yang, H X Yang, H Yang, Hai Yang, Hai-Chun Yang, Haibo Yang, Haihong Yang, Haikun Yang, Hailei Yang, Hailing Yang, Haiming Yang, Haiping Yang, Haiqiang Yang, Haitao Yang, Haixia Yang, Haiyan Yang, Haiying Yang, Han Yang, Hanchen Yang, Handong Yang, Hang Yang, Hannah Yang, Hanseul Yang, Hanteng Yang, Hao Yang, Hao-Jan Yang, HaoXiang Yang, Haojie Yang, Haolan Yang, Haoqing Yang, Haoran Yang, Haoyu Yang, Harrison Hao Yang, Hee Joo Yang, Heng Yang, Hengwen Yang, Henry Yang, Heqi Yang, Heyi Yang, Heyun Yang, Hoe-Saeng Yang, Hong Yang, Hong-Fa Yang, HongMei Yang, Hongbing Yang, Hongbo Yang, Hongfa Yang, Honghong Yang, Hongjie Yang, Hongjun Yang, Hongli Yang, Hongling Yang, Hongqun Yang, Hongxia Yang, Hongxin Yang, Hongyan Yang, Hongyu Yang, Hongyuan Yang, Hongyue Yang, Howard H Yang, Howard Yang, Hsin-Chou Yang, Hsin-Jung Yang, Hsin-Sheng Yang, Hua Yang, Hua-Yuan Yang, Huabing Yang, Huafang Yang, Huaijie Yang, Huan Yang, Huanhuan Yang, Huanjie Yang, Huanming Yang, Huansheng Yang, Huanyi Yang, Huarong Yang, Huaxiao Yang, Huazhao Yang, Hui Yang, Hui-Ju Yang, Hui-Li Yang, Hui-Ting Yang, Hui-Yu Yang, Hui-Yun Yang, Huifang Yang, Huihui Yang, Huijia Yang, Huijie Yang, Huiping Yang, Huiran Yang, Huixia Yang, Huiyu Yang, Hung-Chih Yang, Hwai-I Yang, Hye Jeong Yang, Hyerim Yang, Hyun Suk Yang, Hyun-Sik Yang, Ill Yang, Ivana V Yang, J S Yang, J Yang, James Y Yang, Jaw-Ji Yang, Jee Sun Yang, Jenny J Yang, Jerry Yang, Ji Hye Yang, Ji Yang, Ji Yeong Yang, Ji-chun Yang, Jia Yang, Jia-Ling Yang, Jia-Ying Yang, Jiahong Yang, Jiahui Yang, Jiajia Yang, Jiakai Yang, Jiali Yang, Jialiang Yang, Jian Yang, Jian-Bo Yang, Jian-Jun Yang, Jian-Ming Yang, Jian-Ye Yang, JianHua Yang, JianJun Yang, Jianbo Yang, Jiang-Min Yang, Jiang-Yan Yang, Jianing Yang, Jianke Yang, Jianli Yang, Jianlou Yang, Jianmin Yang, Jianming Yang, Jianqi Yang, Jianwei Yang, Jianyu Yang, Jiao Yang, Jiarui Yang, Jiawei Yang, Jiaxin Yang, Jiayan Yang, Jiayi Yang, Jiaying Yang, Jiayue Yang, Jichun Yang, Jie Yang, Jie-Cheng Yang, Jie-Hong Yang, Jie-Kai Yang, Jiefeng Yang, Jiehong Yang, Jieping Yang, Jiexiang Yang, Jihong Yang, Jimin Yang, Jin Yang, Jin-Jian Yang, Jin-Kui Yang, Jin-gang Yang, Jin-ju Yang, Jinan Yang, Jinfeng Yang, Jing Yang, Jing-Quan Yang, Jing-Yu Yang, Jingang Yang, Jingfeng Yang, Jinggang Yang, Jinghua Yang, Jinghui Yang, Jingjing Yang, Jingmin Yang, Jingping Yang, Jingran Yang, Jingshi Yang, Jingwen Yang, Jingya Yang, Jingyan Yang, Jingyao Yang, Jingye Yang, Jingyu Yang, Jingyun Yang, Jingze Yang, Jinhua Yang, Jinhui Yang, Jinjian Yang, Jinpeng Yang, Jinru Yang, Jinshan Yang, Jinsong Yang, Jinsung Yang, Jinwen Yang, Jinzhao Yang, Jiong Yang, Ju Dong Yang, Ju Young Yang, Juan Yang, Juesheng Yang, Jumei Yang, Jun J Yang, Jun Yang, Jun-Hua Yang, Jun-Xia Yang, Jun-Xing Yang, Junbo Yang, Jung Dug Yang, Jung Wook Yang, Jung-Ho Yang, Junhan Yang, Junjie Yang, Junlin Yang, Junlu Yang, Junping Yang, Juntao Yang, Junyao Yang, Junyi Yang, Kai Yang, Kai-Chien Yang, Kai-Chun Yang, Kaidi Yang, Kaifeng Yang, Kaijie Yang, Kaili Yang, Kailin Yang, Kaiwen Yang, Kang Yang, Kang Yi Yang, Kangning Yang, Karen Yang, Ke Yang, Keming Yang, Keping Yang, Kexin Yang, Kuang-Yao Yang, Kui Yang, Kun Yang, Kunao Yang, Kunqi Yang, Kunyu Yang, Kuo Tai Yang, L Yang, Lamei Yang, Lan Yang, Le Yang, Lei Yang, Lexin Yang, Leyi Yang, Li Chun Yang, Li Yang, Li-Kun Yang, Li-Qin Yang, Li-li Yang, LiMan Yang, Lian-he Yang, Liang Yang, Liang-Yo Yang, Liangbin Yang, Liangle Yang, Liangliang Yang, Lichao Yang, Lichuan Yang, Licong Yang, Liehao Yang, Lihong Yang, Lihua Yang, Lihuizi Yang, Lijia Yang, Lijie Yang, Lijuan Yang, Lijun Yang, Lili Yang, Lin Sheng Yang, Lin Yang, Lina Yang, Ling Ling Yang, Ling Yang, Lingfeng Yang, Lingling Yang, Lingzhi Yang, Linlin Yang, Linnan Yang, Linqing Yang, Linquan Yang, Lipeng Yang, Liping Yang, Liting Yang, Liu Yang, Liu-Kun Yang, LiuMing Yang, Liuliu Yang, Liwei Yang, Lixian Yang, Lixue Yang, Long In Yang, Long Yang, Long-Yan Yang, Longbao Yang, Longjun Yang, Longyan Yang, Lu M Yang, Lu Yang, Lu-Hui Yang, Lu-Kun Yang, Lu-Qin Yang, Luda Yang, Man Yang, Manqing Yang, Maojie Yang, Maoquan Yang, Mei Yang, Meichan Yang, Meihua Yang, Meili Yang, Meiting Yang, Meixiang Yang, Meiying Yang, Meng Yang, Menghan Yang, Menghua Yang, Mengjie Yang, Mengli Yang, Mengliu Yang, Mengmeng Yang, Mengsu Yang, Mengwei Yang, Mengying Yang, Miaomiao Yang, Mickey Yang, Min Hee Yang, Min Yang, Mina Yang, Ming Yang, Ming-Hui Yang, Ming-Yan Yang, Minghui Yang, Mingjia Yang, Mingjie Yang, Mingjun Yang, Mingli Yang, Mingqian Yang, Mingshi Yang, Mingyan Yang, Mingyu Yang, Minyi Yang, Misun Yang, Mu Yang, Muh-Hwa Yang, Na Yang, Nan Yang, Nana Yang, Nanfei Yang, Neil V Yang, Ni Yang, Ning Yang, Ningjie Yang, Ningli Yang, Pan Yang, Pan-Chyr Yang, Paul Yang, Peichang Yang, Peiran Yang, Peiyan Yang, Peiying Yang, Peiyuan Yang, Peizeng Yang, Peng Yang, Peng-Fei Yang, PengXiang Yang, Pengfei Yang, Penghui Yang, Pengwei Yang, Pengyu Yang, Phillip C Yang, Pin Yang, Ping Yang, Ping-Fen Yang, Pinghong Yang, Pu Yang, Q H Yang, Q Yang, Qi Yang, Qi-En Yang, Qian Yang, Qian-Jiao Yang, Qian-Li Yang, QianKun Yang, Qiang Yang, Qianhong Yang, Qianqian Yang, Qianru Yang, Qiaoli Yang, Qiaorong Yang, Qiaoyuan Yang, Qifan Yang, Qifeng Yang, Qiman Yang, Qimeng Yang, Qiming Yang, Qin Yang, Qinbo Yang, Qing Yang, Qing-Cheng Yang, Qingcheng Yang, Qinghu Yang, Qingkai Yang, Qinglin Yang, Qingling Yang, Qingmo Yang, Qingqing Yang, Qingtao Yang, Qingwu Yang, Qingya Yang, Qingyan Yang, Qingyi Yang, Qingyu Yang, Qingyuan Yang, Qiong Yang, Qiu Yang, Qiu-Yan Yang, Qiuhua Yang, Qiuhui Yang, Qiulan Yang, Qiuli Yang, Qiuxia Yang, Qiwei Yang, Qiwen Yang, Quan Yang, Quanjun Yang, Quanli Yang, Qun-Fang Yang, R Yang, Ran Yang, Ren-Zhi Yang, Renchi Yang, Renhua Yang, Renjun Yang, Renqiang Yang, Renzhi Yang, Ri-Yao Yang, Richard K Yang, Robert Yang, Rong Yang, Rongrong Yang, Rongxi Yang, Rongyuan Yang, Rongze Yang, Rui Xu Yang, Rui Yang, Rui-Xu Yang, Rui-Yi Yang, Ruicheng Yang, Ruifang Yang, Ruihua Yang, Ruilan Yang, Ruili Yang, Ruiqin Yang, Ruirui Yang, Ruiwei Yang, Rulai Yang, Ruming Yang, Run Yang, Runjun Yang, Runxu Yang, Runyu Yang, Runzhou Yang, Ruocong Yang, Ruoyun Yang, Ruyu Yang, S J Yang, Se-Ran Yang, Sen Yang, Senwen Yang, Seung Yun Yang, Seung-Jo Yang, Seung-Ok Yang, Shan Yang, Shangchen Yang, Shanghua Yang, Shangwen Yang, Shanzheng Yang, Shao-Hua Yang, Shaobin Yang, Shaohua Yang, Shaoling Yang, Shaoqi Yang, Shaoqing Yang, Sheng Sheng Yang, Sheng Yang, Sheng-Huei Yang, Sheng-Qian Yang, Sheng-Wu Yang, ShengHui Yang, Shenglin Yang, Shengnan Yang, Shengqian Yang, Shengyong Yang, Shengzhuang Yang, Shenhui Yang, Shi-Ming Yang, Shiaw-Der Yang, Shifeng Yang, Shigao Yang, Shijie Yang, Shiming Yang, Shipeng Yang, Shiping 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articles
Yiming Wang, Yifei Chen, Jianbo Yang +2 more · 2025 · Journal of physiology and biochemistry · Springer · added 2026-04-24
Macrophage is considered as a critical driving factor in the progression of atherosclerosis (AS), and epigenetic heterogeneity contributes important mechanisms in this process. Here, we identified tha Show more
Macrophage is considered as a critical driving factor in the progression of atherosclerosis (AS), and epigenetic heterogeneity contributes important mechanisms in this process. Here, we identified that a histone demethylase jumonji domain-containing protein 1 C (JMJD1C) is a promising biomarker for atherosclerotic cerebral infarction through clinical analysis. Then, AOPE Show less
no PDF DOI: 10.1007/s13105-024-01058-3
JMJD1C
Jiahao Guo, Hao Xie, Quanting Yin +8 more · 2025 · Discover oncology · Springer · added 2026-04-24
Although studies have suggested a potential link between the nervous system and prostate cancer, the underlying regulatory mechanisms remain unclear. Therefore, it is crucial to identify the genes inv Show more
Although studies have suggested a potential link between the nervous system and prostate cancer, the underlying regulatory mechanisms remain unclear. Therefore, it is crucial to identify the genes involved in regulating prostate cancer within the nervous system. We utilized eQTL data from eight neural cell types as exposure factors and GWAS data for prostate cancer as outcome events. Mendelian randomization (MR) analyses were performed to identify causative genes associated with prostate, bladder, and renal cancers in Astrocytes, Endothelial cells, Excitatory neurons, Inhibitory neurons, Microglia, Oligodendrocytes, OPCs/COPs, and Pericytes. Bladder and renal cancers were used as controls. Sensitivity analyses (heterogeneity, pleiotropy, and leave-one-out tests) were conducted to ensure reliability. In astrocytes, seven positive genes were identified as being causally related to prostate cancer: KANSL1, AC005670.2, ARL17B, LRRC37A2, LRRC37A, MAPT, and LINC02210. In. Endothelial cells, Inhibitory neuron and Microglia, three genes (LRRC37A2, ARL17B, and KANSL1) were identified as risk genes that are associated with prostate cancer. Four protective genes were identified in excitatory neurons, including LRRC37A2, ARL17B, KANSL1 and LINC02210. In oligodendrocytes, eight genes were identified, with LRRC37A2, ARL17B, and KANSL1 acting as protective factors, while OR2L13, OR2L3, OR2L5, OR2L2, and OR2M4 were identified as risk factors. Additionally, sensitivity analyses showed no heterogeneity or horizontal pleiotropy in the MR results, confirming their reliability and stability. In addition, no positive genes were found in bladder cancer and renal cancer. Our study highlights the role of the nervous system, particularly astrocytes, in regulating prostate cancer. We identified three genes, with LRRC37A2, ARL17B, and KANSL1 emerging as key protective factors. These findings provide potential targets for prostate cancer diagnosis and treatment. The online version contains supplementary material available at 10.1007/s12672-025-03711-9. Show less
📄 PDF DOI: 10.1007/s12672-025-03711-9
KANSL1
Rui Guo, Chunhong Duan, Mehdi Zarrei +9 more · 2025 · Scientific reports · Nature · added 2026-04-24
Congenital heart disease (CHD) is the most common type of birth defects in humans. Genetic factors have been identified as an important contributor to the etiology of CHD. However, the underlying gene Show more
Congenital heart disease (CHD) is the most common type of birth defects in humans. Genetic factors have been identified as an important contributor to the etiology of CHD. However, the underlying genetic causes in most individuals remain unclear. Here, 101 individuals with CHD and their unaffected parents were included in this study. Chromosomal microarray analysis (CMA) as a first-tier clinical diagnostic tool was applied for all affected individuals, followed by trio-based whole exome sequencing (WES) of 76 probands and proband-only WES of 3 probands. We detected aneuploidies in 2 individuals (trisomy 21 and monosomy X), 21 pathogenic and likely pathogenic copy number variants (CNVs) in 19 individuals, and pathogenic and likely pathogenic SNVs/InDels in 8 individuals. The combined genetic diagnostic yield was 28.7%, including 20.8% with chromosomal abnormalities and 7.9% with sequence-level variants. Eighteen CNVs in 17 individuals were associated with 13 recurrent chromosomal microdeletion/microduplication syndromes, the most common being 22q11.2 deletion syndrome. Pathogenic/likely pathogenic sequence-level variants were identified in 8 genes, including GATA6, FLNA, KANSL1, TRAF7, KAT6A, PKD1L1, RIT1, and SMAD6. Trio sequencing facilitated the identification of pathogenic variation (55.6% were de novo missense variants). In individuals with extracardiac features, the overall detection rate was significantly higher (61.5%) than in individuals with isolated CHD (17.3%) (P = 4.6 × 10 Show less
📄 PDF DOI: 10.1038/s41598-025-06977-9
KANSL1
Feixiong Cheng, Yayan Feng, Xiaoyu Yang +19 more · 2025 · Research square · added 2026-04-24
Although the human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes tha Show more
Although the human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from both cerebellum and frontal cortex of AD/ADRD patients and normal controls. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we pinpointed two likely causal genes, Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and three-dimensional (3D) genome data. Via CRISPRi experiments, we found that perturbation of rs4788201 and rs62056801 significantly inhibited the expression of their target genes, SEZ6L2 and KANSL1, in human iPSC-derived neurons. This cell subtype-specific regulatory landscape in the human cerebellum identified here offers novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied. Show less
no PDF DOI: 10.21203/rs.3.rs-6264481/v1
KANSL1
Zhe Han, Yanping Zhu, Zhenhong Xia +9 more · 2025 · NPJ Parkinson's disease · Nature · added 2026-04-24
Magnetic resonance imaging and circulating molecular testing are potential methods for diagnosing and treating Parkinson's disease (PD). However, their relationships remain insufficiently studied. Usi Show more
Magnetic resonance imaging and circulating molecular testing are potential methods for diagnosing and treating Parkinson's disease (PD). However, their relationships remain insufficiently studied. Using genome-wide association summary statistics, we found in the general population a genetic negative correlation between white matter tract mean diffusivity and PD (-0.17 < Rg < -0.11, p < 0.05), and a positive correlation with intracellular volume fraction (0.12 < Rg < 0.2, p < 0.05). Additionally, 1345 circulating genes causally linked with white matter tract diffusivity were enriched for muscle physiological abnormalities (padj < 0.05). Notable genes, including LRRC37A4P (effect size = 15.7, p = 1.23E-55) and KANSL1-AS1 (effect size = -15.3, p = 1.13E-52), were directly associated with PD. Moreover, 23 genes were found linked with genetically correlated PD-IDP pairs (PPH4 > 0.8), including SH2B1 and TRIM10. Our study bridges the gap between molecular genetics, neuroimaging, and PD pathology, and suggests novel targets for diagnosis and treatment. Show less
📄 PDF DOI: 10.1038/s41531-024-00859-z
KANSL1
Rong Du, Ajay Kumar, Enzhi Yang +3 more · 2025 · Current issues in molecular biology · MDPI · added 2026-04-24
Glaucoma is a leading cause of irreversible blindness, normally associated with dysfunction and degeneration of the trabecular meshwork (TM) as the primary cause. Trabecular meshwork stem cells (TMSCs Show more
Glaucoma is a leading cause of irreversible blindness, normally associated with dysfunction and degeneration of the trabecular meshwork (TM) as the primary cause. Trabecular meshwork stem cells (TMSCs) have emerged as promising candidates for TM regeneration toward glaucoma therapies, yet their molecular characteristics remain poorly defined. In this study, we performed a comprehensive transcriptomic comparison of human TMSCs and human TM cells (TMCs) using RNA sequencing and microarray analyses, followed by qPCR validation. A total of 465 differentially expressed genes were identified, with 254 upregulated in TMSCs and 211 in TMCs. A functional enrichment analysis revealed that TMSCs are associated with development, immune signaling, and extracellular matrix remodeling pathways, while TMCs are enriched in structural, contractile, and adhesion-related functions. A network topology analysis identified Show less
📄 PDF DOI: 10.3390/cimb47070514
LMOD1
Yangyang Xiao, Zhiru Zhong, Chunli Yang +1 more · 2025 · Discover oncology · Springer · added 2026-04-24
Gastric cancer (GC) is a common malignant tumor, which originated from the epithelial cells of the stomach. It has the characteristics of high incidence and poor prognosis. Therefore, it is urgent to Show more
Gastric cancer (GC) is a common malignant tumor, which originated from the epithelial cells of the stomach. It has the characteristics of high incidence and poor prognosis. Therefore, it is urgent to find new prognostic markers for the diagnosis and treatment of GC. Download gene expression matrix and clinical data from TCGA database and GSE84437 dataset. Through independent prognostic analysis and clinical correlation analysis, 74 prognostic related genes (PRG) were screened out. A PPI network was established for PRG to identify four key genes (KG), namely LMOD1, CRYAB, VCL and MYL9. Survival analysis showed that patients with high expression of KG had poor prognosis. Multivariate Cox regression analysis showed that KG was an independent prognostic factor. TCGA database verifies the importance and significance of KG as a prognostic indicator. Functional enrichment analysis showed that KG was mainly involved in cell adhesion molecules, adhesion spots and PI3K/AKT signaling pathway. KG may be a potential therapeutic target for gastric cancer. Show less
📄 PDF DOI: 10.1007/s12672-025-01907-7
LMOD1
Bingjie Wu, Xiaoyue Cheng, Ruimin Zheng +10 more · 2025 · Human reproduction open · Oxford University Press · added 2026-04-24
Does preconception mental health status in either partner affect fertility and infertility, and is this association modified by socioeconomic status (SES)? Preconception mental health problems in both Show more
Does preconception mental health status in either partner affect fertility and infertility, and is this association modified by socioeconomic status (SES)? Preconception mental health problems in both partners are associated with lower couple fertility, with the synergistic impact being most pronounced among couples with low SES status. Mental health problems are rising among young adults, and fertility rates are declining. Women's preconception mental health has been linked to lower fertility, but few studies have examined the combined impact of both partners' mental health. The modifying role of SES in these associations is also poorly understood. This couple-based prospective cohort study included 966 preconception couples who sought preconception care and were followed for 12 months in the Shanghai Birth Cohort between 2013 and 2015. The couples' mental health status was evaluated at enrolment using the Center for Epidemiological Studies-Depression Scale, Zung Self-Rating Anxiety Scale, and Perceived Stress Scale. The outcomes included couple fecundability (measured by the TTP) and infertility (i.e. TTP >12 menstrual cycles). In the partner-specific model, Cox proportional hazards models and logistic regression were used to evaluate the associations between each partner's depression, anxiety, and stress levels and couples' fertility. In the couple-based model, cross-classification and quantile g-computation were first applied to identify couples' joint exposure to specific psychological conditions in relation to fertility. Latent profile analysis (LPA) was then conducted to characterize distinct latent profiles of couples' overall mental health statuses, followed by Cox proportional hazards models and logistic regression to examine the corresponding associations. Key symptoms in the couples' depression, anxiety, and stress scales were determined by elastic net regression and least absolute shrinkage and selection operator. To assess the potential effect modification of SES on the association between couples' mental health and fertility, we conducted stratified analyses by male and female partner education levels and household income. In the female partner-specific model, a 1 SD increase in depression score was associated with 10% lower fecundability (FOR = 0.90, 95% CI: 0.82, 0.99). Likewise, a 1 SD increase in the stress score was associated with 13% lower fecundability (FOR = 0.87, 95% CI: 0.79, 0.96). Male anxiety was associated with a higher risk of infertility (OR = 1.19, 95% CI: 1.01, 1.42). Stratified analyses showed that depression, anxiety, and stress were significantly associated with lower fecundability among males with an education level Show less
📄 PDF DOI: 10.1093/hropen/hoaf071
LPA
Weiwei Liu, Yuzhong Gu, Qingqing Yang +1 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
To explore the latent categories of volume management behaviors in patients with chronic heart failure (CHF) and analyze their relationship with symptom distress. This cross-sectional study utilized a Show more
To explore the latent categories of volume management behaviors in patients with chronic heart failure (CHF) and analyze their relationship with symptom distress. This cross-sectional study utilized a convenience sampling method to select 552 CHF patients from the cardiology departments of Nantong Sixth People's Hospital and Nantong Fourth People's Hospital. Volume management behaviors were assessed using the Volume Management Behavior Scale, and symptom distress was evaluated using the Symptom Distress Questionnaire (SDQ), which measures the severity of eight core symptoms. Latent Profile Analysis (LPA) was employed to identify behavioral categories. Multivariate Analysis of Variance (MANOVA) and multiple linear regression were used to analyze differences in symptom distress across behavioral categories and to examine the independent predictive effect of behavioral classification on symptom distress. The volume management behaviors of CHF patients were classified into three latent categories: active management type (43.1%), selective adherence type (27.7%), and passive dependence type (29.2%). Symptom distress scores showed a significant increasing trend across the three categories (active type: 10.5 ± 3.8; selective type: 13.2 ± 4.1; passive type: 16.3 ± 5.2, CHF patients exhibit three distinct clinical patterns of volume management behaviors, with the passive dependence type associated with the highest symptom burden. Behavioral category is a significant predictor of symptom distress. These findings provide an empirical basis for developing precise intervention strategies tailored to different behavioral phenotypes. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1698319
LPA
Xiaojuan Li, Tiewei Li, Pengfei Xuan +2 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Lysophosphatidic acid (LPA) has anti-inflammatory and protective effects in sepsis, yet clinical evidence on its correlation with sepsis progression and outcomes is limited. This study aimed to evalua Show more
Lysophosphatidic acid (LPA) has anti-inflammatory and protective effects in sepsis, yet clinical evidence on its correlation with sepsis progression and outcomes is limited. This study aimed to evaluate the association of plasma LPA levels with sepsis development, severity, and mortality. A total of 42 sepsis patients and 29 controls with common infections were included. Among the sepsis patients, 15 succumbed during hospitalization. Plasma LPA levels were measured, and clinical data were retrospectively analyzed. Plasma LPA was significantly lower in sepsis patients compared to controls, and further reduced in non-survivors. Notably, correlation analyses suggested that LPA levels were negatively correlated with neutrophil count, procalcitonin, interleukin-6, and Sequential Organ Failure Assessment (SOFA) score. Multivariate regression analysis identified LPA as an independent risk factor for sepsis onset and in-hospital mortality. Receiver operating characteristic (ROC) curve analysis revealed that LPA had a high diagnostic accuracy for sepsis (area under the ROC curve [AUC] = 0.92, 95% CI = 0.86-0.99, P < 0.001) and was a strong predictor of in-hospital mortality (AUC = 0.86, 95% CI = 0.76-0.97, P < 0.001). Reduced plasma LPA levels in sepsis patients are inversely correlated with infection/inflammation markers and SOFA scores. Together, these results suggest that LPA may serve as a potential diagnostic and prognostic biomarker for sepsis, supporting its potential as a complementary tool to enhance early risk stratification and guide bedside clinical decision-making. Show less
📄 PDF DOI: 10.3389/fimmu.2025.1725394
LPA
Jia Zhang, Song Bin Huang, Dan Ni Peng +3 more · 2025 · Frontiers in psychology · Frontiers · 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
📄 PDF DOI: 10.3389/fpsyg.2025.1731898
LPA
Jiaqi Lin, Lijia Dong, Xueyuan Han +3 more · 2025 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
The influence of lactic acid bacteria (LAB) strains of various species isolated from Chinese traditional sourdough on the properties of rice sourdough and the textural and flavor qualities of steamed Show more
The influence of lactic acid bacteria (LAB) strains of various species isolated from Chinese traditional sourdough on the properties of rice sourdough and the textural and flavor qualities of steamed rice bread (SRB) was investigated. Show less
📄 PDF DOI: 10.3390/foods14244335
LPA
Di Xue, Huaijie Yang, Jian Zheng +1 more · 2025 · Frontiers in medicine · Frontiers · added 2026-04-24
This study aims to identify heterogeneous subgroups of first-year residents experiencing transition shock using latent profile analysis (LPA) and to explore the predictive effects of various dimension Show more
This study aims to identify heterogeneous subgroups of first-year residents experiencing transition shock using latent profile analysis (LPA) and to explore the predictive effects of various dimensions of professional identity on different transition shock types. A multi-center, cross-sectional design was employed. From September 2023 to August 2024, a total of 766 first-year residents were selected via cluster sampling from four national-level training bases in Hubei Province, China, for a cross-sectional survey. The survey was conducted using the revised Transition Shock Scale (Cronbach's A total of 574 valid questionnaires were returned. Latent profile analysis identified three latent classes: a low psychological-sociocultural shock group (13.41%, Transition shock among first-year residents exhibits significant heterogeneity. These findings provide evidence for developing targeted intervention strategies. Higher levels of professional cognition, commitment, and expectation are associated with lower levels of transition shock. However, a strong sense of professional values is associated with higher transition shock, a relationship potentially mediated by an idealism-reality gap. It is recommended that tiered competency-building interventions should be implemented for the high physical-knowledge/skill shock group, and a dual-track support system should be designed for Master of Medicine degree candidates. Show less
📄 PDF DOI: 10.3389/fmed.2025.1716120
LPA
Lei Xia, Xianglin Bai, Zhengzhi Feng +2 more · 2025 · BMC psychiatry · BioMed Central · added 2026-04-24
Mental health among college students represents a significant and growing public health concern. Negative bias in prospection is closely related to depression and anxiety. Prospection bias (PB) encomp Show more
Mental health among college students represents a significant and growing public health concern. Negative bias in prospection is closely related to depression and anxiety. Prospection bias (PB) encompasses increased negativity, reduced positivity and overgeneralization, which exhibit intricate co-occurrence patterns and exert a complex influence on mental health. However, the presence of distinct patterns of PB and their impact on mental health remain unknown. We recruited 1,030 Chinese college students to complete assessments of PB, depression, anxiety, stress and resilience. Latent profile analysis (LPA) was used to identify distinct PB profiles. Linear regression was then applied to examine their effects on mental health outcomes. The results suggested six profiles: (1) high levels of increased negativity and overgeneralization but a low level of reduced positivity (contradictory overgeneralizers), (2) low PB, (3) moderate low PB, (4) a high level of increased negativity but low levels of reduced positivity and overgeneralization (simple contradictory), (5) high PB, and (6) moderate high PB. Regression analyses demonstrated that high prospection bias predicted more severe stress, depressive and anxious symptoms, as well as lower resilience. Additionally, the results implied that handling increased negativity and reduced positivity of prospection might be potential ways to improve mental health. These findings may facilitate the early detection of mental health issues among college students and contribute to the refinement of future interventions. The online version contains supplementary material available at 10.1186/s12888-025-07732-0. Show less
📄 PDF DOI: 10.1186/s12888-025-07732-0
LPA
Ze-Run Zhao, Meng Yang, Juan-Juan Feng +5 more · 2025 · Frontiers in neurology · Frontiers · added 2026-04-24
This study explored latent profiles of Health Information-Seeking Behavior (HISB) among stroke patients and analyzed its influencing factors. In this cross-sectional study, 311 stroke participants fro Show more
This study explored latent profiles of Health Information-Seeking Behavior (HISB) among stroke patients and analyzed its influencing factors. In this cross-sectional study, 311 stroke participants from two tertiary care hospitals in Gansu Province, China, were recruited between January and May 2025 using convenience sampling. Data were collected using a general information questionnaire, the Health Information-Seeking Behavior Scale, and the Health Behavior Decision-Making Assessment Scale for Stroke Patients. Latent profile analysis (LPA) was employed to identify distinct HISB profiles. Three latent profiles were identified: the high-demand low-barrier positive group, the moderate-balanced group, and the low-demand high-barrier negative group. Key predictors of profile membership included age, education level, monthly personal income, and the presence of comorbid chronic diseases. The identification of three distinct HISB trait types provides an evidence-based foundation for developing personalized health education and tailored decision support interventions. Healthcare professionals can leverage this classification system to customize communication strategies for patients with different traits, deliver tiered information support, and ultimately empower patients to achieve better health behaviors and health outcomes. Show less
📄 PDF DOI: 10.3389/fneur.2025.1683198
LPA
Jie Yang, Hao Jia, Kai Yu +1 more · 2025 · The aging male : the official journal of the International Society for the Study of the Aging Male · Taylor & Francis · added 2026-04-24
To investigate the associations between various patterns of physical activity (PA) and risk of hip fracture in Chinese middle-aged and older adults. Data were obtained from the China Health and Retire Show more
To investigate the associations between various patterns of physical activity (PA) and risk of hip fracture in Chinese middle-aged and older adults. Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. PA levels, including moderate-to-vigorous (MVPA), vigorous (VPA), moderate (MPA), low (LPA), and total physical activity (TPA), were assessed using the International Physical Activity Questionnaire. Cox proportional hazard models were used to estimate hazard ratios (HRs), and a restricted cubic spline analyzed the dose-response relationship between TPA and hip fracture. Among 6,193 participants (mean age 59.3; 54.0% female), 264 hip fractures occurred during follow-up. Meeting WHO-recommended MVPA levels ≥150 min/week) was not associated with reduced risk (HR 1.04, 95% CI 0.80-1.35). Similarly, no significant associations were observed for VPA (≥75 min/week), MPA (≥150 min/week), LPA (≥300 min/week), or TPA (≥600 MET-min/week). Dose-response analysis also showed no association between total PA and hip fracture. This study does not support the WHO recommendation of ≥ 150 min/week of MVPA for reducing hip fracture risk in this demographic. As PA was self-reported and largely work-related, future research should investigate leisure-time and objectively-measured PA. Show less
no PDF DOI: 10.1080/13685538.2025.2604393
LPA
Jia-Cheng Liu, Rui Yang, Zan-Fei Feng +9 more · 2025 · Journal of the National Cancer Institute · Oxford University Press · added 2026-04-24
Cardiovascular-kidney-metabolic (CKM) syndrome significantly increases cancer and mortality risks, but the combined effects of CKM syndrome and physical activity (PA) on these outcomes remain poorly u Show more
Cardiovascular-kidney-metabolic (CKM) syndrome significantly increases cancer and mortality risks, but the combined effects of CKM syndrome and physical activity (PA) on these outcomes remain poorly understood. This prospective study included 66,650 UK Biobank participants with accelerometry data. CKM syndrome was classified into five stages based on metabolic, kidney, and cardiovascular health. PA was categorized by intensity into light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) levels, and further divided into tertiles by daily duration. Multivariable Cox models were used to estimate hazard ratios. Over a median follow-up of 8.03 years, 4,301 incident cancer cases and 2,442 deaths occurred. Advancing CKM stages were associated with elevated risks of both cancer incidence and all cause mortality, while increasing PA levels reduced these risks. Significant interactions were observed between CKM syndrome and both MPA and MVPA on cancer and mortality risks (P interaction < 0.05). In participants with the lowest tertile of MPA or MVPA, those in stages 2 and 4 had higher cancer risk, while in the highest tertile, this risk was no longer elevated. For all-cause mortality, in participants with the lowest tertile of MPA or MVPA, CKM stage 3 exhibited higher risks, while those in the highest tertile did not. CKM stage 4 remained associated with higher mortality across all PA intensity levels, but risks decreased with increasing MVPA levels. Higher levels of MPA and MVPA may mitigate the elevated risks of both cancer incidence and all-cause mortality associated with CKM stages 2 to 4. Show less
no PDF DOI: 10.1093/jnci/djaf365
LPA
Yuchen Wang, Qiong Sun, Menachem Hanani +15 more · 2025 · Journal of translational medicine · BioMed Central · 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
📄 PDF DOI: 10.1186/s12967-025-07568-y
LPA
Bin Chen, Jing Yang, Wenying Huang +3 more · 2025 · Frontiers in psychology · Frontiers · 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
📄 PDF DOI: 10.3389/fpsyg.2025.1701168
LPA
Sijia Yang, Boya Zhang, Jian Chen +3 more · 2025 · Healthcare (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/healthcare13233109
LPA
Yuqing Yuan, Jing Yang, Wenying Huang +3 more · 2025 · Frontiers in psychology · Frontiers · 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
📄 PDF DOI: 10.3389/fpsyg.2025.1694344
LPA
Yue Yang, Meiying Li, Xiaoge Ding +3 more · 2025 · Aging clinical and experimental research · Springer · added 2026-04-24
To explore the potential categories of fear of falling in elderly stroke patients and analyze the differences in characteristics and influencing factors among patients in different categories. AA tota Show more
To explore the potential categories of fear of falling in elderly stroke patients and analyze the differences in characteristics and influencing factors among patients in different categories. AA total of 386 elderly stroke patients hospitalized in the Department of Neurology of a tertiary grade A general hospital in Jilin Province from March 2024 to June 2024 were selected as research subjects using the convenience sampling method. A general information questionnaire, Modified Falls Efficacy Scale (MFES), Simplified Coping Style Questionnaire (SCSQ), and Social Support Rating Scale (SSRS) were used for the survey. Mplus 8.3 software was applied to conduct latent profile analysis (LPA) on fear of falling in elderly stroke patients to identify potential categories, and multivariate logistic regression was used to further explore the influencing factors of each category. There were 3 potential categories of fear of falling in elderly stroke patients: the high fear of falling group (21.8%), moderate fear of falling group (38.3%), and low fear of falling group (39.9%). Multivariate logistic regression analysis showed that gender, age, type of stroke diagnosis, visual status, hearing status, limb strength, coping style, and social support were the influencing factors for the potential categories of fear of falling in elderly stroke patients. Fear of falling in elderly stroke patients has obvious categorical characteristics. Medical staff should implement targeted interventions based on the characteristics and influencing factors of different potential categories to reduce patients' fear of falling. Show less
📄 PDF DOI: 10.1007/s40520-025-03236-9
LPA
Hezhi Wang, Qingyu Yang, Hongxia Xiang +7 more · 2025 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Pancreatic cancer (PC) represents a highly lethal malignancy characterized by diagnostic challenges owing to nonspecific early symptoms and insufficiently sensitive biomarkers. This investigation soug Show more
Pancreatic cancer (PC) represents a highly lethal malignancy characterized by diagnostic challenges owing to nonspecific early symptoms and insufficiently sensitive biomarkers. This investigation sought to identify novel PC biomarkers through lipidomic profiling, an emerging metabolomics methodology examining lipid pathways in disease pathogenesis. We established a humanized murine PC model. Small-molecule oxidized lipid metabolites in primary pancreatic tumors and hepatic metastases were quantitatively analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) integrated with a comprehensive metabolomics platform. Multivariate statistical approaches including principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were systematically applied. Analysis identified 64 differentially expressed oxidized lipids structurally classified as unsaturated fatty acid derivatives. Comparative assessment of metabolic profiles revealed a pronounced reduction in prostaglandins (PGE Our findings establish prostaglandins PGE Show less
no PDF DOI: 10.1016/j.bbrc.2025.152900
LPA
Zhenwei Dai, Shu Jing, Haiyan Hu +8 more · 2025 · Brain and behavior · Wiley · added 2026-04-24
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult w Show more
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult women infected with HPV. This study aimed to adapt and validate the HPVsStigma scale (HPV-SS) in the Chinese context. A cross-sectional study was conducted from December 2024 to February 2025 among 501 HPV-infected women in Shenzhen, China. The HPV-SS was adapted from a 12-item HIV stigma scale. Demographic characteristics, HPV-related variables, and data on mental health were collected. Factor analyses (FA) were used to assess the scale's factorial structure, reliability, and validity. The bi-factor model was used to determine the score-reporting method of the scale. Item response theory (IRT) was employed to assess the relationship between participants' stigma levels and scale scores. Latent profile analysis (LPA) was conducted to classify the participants with different HPV stigma characteristics and determine the optimal cut-off value for HPV-SS. FA showed that the 3-factor model (personalized stigma, public-disclosure concerns, and negative self-image) had the best fit among the nested models, with good reliability and validity. The bi-factor model analysis indicated that the total scale score was more meaningful than dimension scores. IRT analysis confirmed that higher HPV-SS scores represented higher stigma levels. LPA identified a 2-class model as optimal, and the optimal cut-off value of the scale for high HPV stigma was 35. This study validated the 12-item HPV-SS for Chinese women infected with HPV, with good reliability and validity. The scale can be used to evaluate HPV stigma levels, facilitating targeted interventions to improve cervical cancer prevention and the psychological well-being of affected women. Show less
📄 PDF DOI: 10.1002/brb3.71044
LPA
Yuanyuan Li, Qiaolin Yu, Rong Yao +11 more · 2025 · Patient preference and adherence · 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
📄 PDF DOI: 10.2147/PPA.S558068
LPA
Omer Akyol, Huan-Hsing Chiang, Alan R Burns +6 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Atherosclerotic cardiovascular disease (ASCVD), including coronary heart disease and cerebrovascular disease, is caused by the accumulation of plaque on artery walls. Elevated levels of low-density li Show more
Atherosclerotic cardiovascular disease (ASCVD), including coronary heart disease and cerebrovascular disease, is caused by the accumulation of plaque on artery walls. Elevated levels of low-density lipoprotein (LDL) cholesterol significantly contribute to the development and progression of ASCVD. Multiple studies have provided evidence of a correlation between individual LDL subpopulations and the development of atherosclerosis (AS); among these, small, dense low-density lipoprotein (sdLDL) and lipoprotein(a) [Lp(a)] have been particularly implicated. There are multiple considerations of why sdLDL may cause AS including their low affinity for the LDL receptor, their ability to diffuse into the artery wall and remain there for a long time, and their tendency to become excessively oxidized. Oxidized LDL (oxLDL), generated under oxidative stress, drives AS by impairing endothelial function, promoting foam cell formation, and triggering vascular inflammation. Lp(a) contributes to the development and progression of AS by causing inflammation of the arterial wall. Studies conducted in recent years have found that electronegative LDL [L5/LDL(-)] may also be an important factor in the development and progression of AS. L5/LDL(-) causes atherosclerotic changes in the vascular wall by triggering apoptosis in endothelial cells via the lectin-like oxLDL receptor-1. This article offers an updated overview of ASCVD and briefly examines the classifications of atherogenic LDL subfractions and their roles in atherogenesis. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1649759
LPA
Jiangshan Tan, Wei Xu, Song Hu +4 more · 2025 · Reviews in cardiovascular medicine · added 2026-04-24
Many studies have revealed the observational associations between lipoprotein(a) (Lp(a)) concentrations and the incidence of cardiovascular diseases (CVDs). However, the causal associations remain unc Show more
Many studies have revealed the observational associations between lipoprotein(a) (Lp(a)) concentrations and the incidence of cardiovascular diseases (CVDs). However, the causal associations remain unclear. Public summary data were analyzed using a Mendelian randomization (MR) design to assess the causal associations between Lp(a) levels and risks of nine CVDs and evaluate the potential impact of aspirin on Lp(a) levels. The principal analysis was conducted employing the random-effects inverse-variance weighted (IVW) method. Furthermore, the weighted median and MR-Egger approaches were used as the sensitivity analysis. Additionally, the significantly associated single nucleotide polymorphisms (SNPs) in salicylic acid (INTERVAL and EPIC-Norfolk, n = 14,149) were chosen to assess the potential effects of aspirin on lowering Lp(a) levels. The IVW analysis showed that the per standard deviation (SD) increment in Lp(a) level was causally associated with a higher risk of coronary artery disease (odds ratio (OR), 1.237; 95% confidence interval (CI), 1.173-1.303), atrial fibrillation (OR, 1.030; 95% CI, 1.011-1.050), heart failure (OR, 1.074; 95% CI, 1.053-1.096), hypertension (OR, 1.006; 95% CI, 1.004-1.008), and peripheral artery disease (OR, 1.001; 95% CI, 1.001-1.001) (all A causal nexus was discerned between Lp(a) levels and an increased risk of conditions including coronary artery disease, atrial fibrillation, heart failure, hypertension, and peripheral artery disease. Furthermore, administering aspirin may be a potential therapeutic to reduce these CVD risks among individuals with elevated Lp(a) levels. Show less
📄 PDF DOI: 10.31083/RCM39322
LPA
Siyue Fan, Mufen Ye, Xiaoying Tong +9 more · 2025 · Journal of nursing management · added 2026-04-24
Incontinence-associated dermatitis (IAD) is a common nursing challenge in clinical practice, imposing a significant burden on both patients and healthcare providers. Studies have reported that nurses' Show more
Incontinence-associated dermatitis (IAD) is a common nursing challenge in clinical practice, imposing a significant burden on both patients and healthcare providers. Studies have reported that nurses' preventive attitudes toward IAD significantly influence its prevalence, and there may be a potential association between achievement motivation and these attitudes. Previous research on nurses' preventive attitudes toward IAD has primarily focused on overall levels, overlooking potential heterogeneity within the population. This study aimed to investigate the heterogeneity in clinical nurses' preventive attitudes toward IAD using a person-centered approach and to identify the influencing factors for different subgroups. A secondary aim was to utilize Self-Determination Theory (SDT) to elucidate the relationship between the identified attitude profiles and nurses' achievement motivation, thereby providing targeted strategies to enhance their preventive attitudes. This study selected 1058 clinical nurses from a tertiary hospital in Fujian, China, as research participants from September to October 2024. The study utilized the following instruments: a general information questionnaire, the Attitude Toward the Prevention of Incontinence-Associated Dermatitis Instrument, and the Achievement Motivation Scale. Latent profile analysis (LPA) was employed to identify the latent profiles of nurses' attitudes toward IAD prevention. At the same time, Two subgroups of nurses' attitudes toward IAD prevention were identified: the low-level group (63.42%) and the high-level, low-personal-responsibility group (36.57%). A significant correlation was found between nurses' attitudes toward IAD prevention and achievement motivation. Nurses with a more positive preventive attitude scored higher on the motivation for success dimension, while those with a less positive attitude scored higher on the motivation to avoid failure dimension. Factors influencing nurses' attitudes toward IAD prevention included position, department, number of participants in wound/ostomy/incontinence care training, satisfaction with the work atmosphere, and achievement motivation scores. This study revealed heterogeneity in nurses' attitudes toward IAD prevention. Nurses with positive attitudes tended to adopt a success-driven approach, while those with relatively negative attitudes leaned toward a failure-avoidance strategy, reflecting two fundamentally distinct coping mechanisms. Nursing managers should address these individual differences by targeting achievement motivation as an intervention point. Management strategies should be tailored to the distinct profiles; for instance, interventions for the "low-level group" should prioritize building competence through structured training, while strategies for the "high-level, low-personal-responsibility group" should focus on enhancing autonomy and personal accountability. By adopting such targeted approaches, managers can more effectively enhance nurses' preventive attitudes, thereby improving care quality and reducing IAD incidence. Show less
📄 PDF DOI: 10.1155/jonm/3381812
LPA
Liting Cai, Chunfang Shan, Yufei Chen +9 more · 2025 · Clinical proteomics · BioMed Central · added 2026-04-24
Premature coronary artery disease (PCAD) is characterized by early onset, rapid progression, and poor prognosis, which seriously affects patients' health and quality of life. In this study, we analyze Show more
Premature coronary artery disease (PCAD) is characterized by early onset, rapid progression, and poor prognosis, which seriously affects patients' health and quality of life. In this study, we analyzed the proteomic network and biological pathways of PCAD patients by bioinformatics methods, and mined out the key differential proteins, which provided a theoretical basis for clinical intervention. Patients who attended the heart center of the First Affiliated Hospital of Xinjiang Medical University from January 2023 to December 2024 and completed coronary angiography were selected. According to the relevant inclusion and exclusion criteria, a total of 129 patients were included, including 69 in the PCAD group and 60 in the control group. The clinical baseline data of the patients were systematically analyzed. Plasma protein extraction, trypsin digestion and mass spectrometry were completed. The mass spectrometry data were initially separated with the help of proteomics software, and the differential proteins were functionally enriched by RStudio software. Protein interaction networks were constructed by STRING platform and core differential proteins screened were visualized using Cytoscape software (MCODE plug-in). Differences in gender, smoking, alcohol consumption, hypertension, diabetes, HDL-C, Glu, FIB, LPa, NT-pro-BNP, PCT, and IL-6 were statistically significant (P < 0.05). Sex (P = 0.009, OR = 6.782,95% CI: 1.600-28.746), FIB (P = 0.001, OR = 2.662,95% CI: 1.471-4.818), and LPa (P = 0.041, OR = 1.002,95% CI: 1.000-1.004) were independent risk factors for PCAD. A total of 348 up-regulated proteins and 92 down-regulated proteins were screened by bioinformatics analysis. The occurrence of PCAD is associated with protein synthesis, intercellular communication, molecular interactions, ribosomal metabolism, glyoxylate and dicarboxylic acid metabolic pathways. Ribosomal and translational proteins influence the development of PCAD. In this study, we found that gender, FIB, and LPa are risk factors for PCAD. The analysis identified 348 up-regulated and 92 down-regulated proteins. Among them, the differentially expressed proteins DHX9, F7, APCS, and PROC were closely related to the biological process of PCAD. The screened ribosomal and translational proteins showed high-frequency associations in protein-protein interaction networks, providing potential differentially expressed proteins for a deeper understanding of the disease. Show less
📄 PDF DOI: 10.1186/s12014-025-09561-5
LPA
Lan Yang, Jinghua Yang, Hong Zhang +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. H Show more
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. However, there remains a significant gap in studies specifically addressing the eHL needs of patients with maintenance hemodialysis (MHD). This study aims to explore the latent categories of eHL among MHD patients and its impact on health-promoting lifestyle (HPL). A survey was conducted using a convenience sampling method involving 500 MHD patients from three tertiary hospitals in Baoding. Data were analyzed using latent profile analysis (LPA) and a mixed regression model. This study showed that MHD patients could be classified into low (23.17%), middle (49.78%), and high (27.05%) eHL groups, with the three-class model showing optimal fit (AIC = 2321.213, BIC = 2271.168, entropy = 0.967). MHD Patients in the high literacy group scored significantly higher in all dimensions of e-HL and overall HPL (119.58 ± 13.86) compared to those in the low literacy group (91.82 ± 11.73) (all The findings suggest a heterogeneous stratification of eHL among MHD patients, closely linked to HPL. Stratified intervention strategies should be developed for different patient groups to potentially improve their health behaviors. The study provides evidence-based support for personalized health management. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1630350
LPA