Nurses in traditional Chinese medicine (TCM) departments face significant sleep challenges associated with occupational stressors. However, person-centered analyses classifying these sleep patterns re Show more
Nurses in traditional Chinese medicine (TCM) departments face significant sleep challenges associated with occupational stressors. However, person-centered analyses classifying these sleep patterns remain scarce. This study aimed to identify heterogeneous sleep disturbance subgroups via latent profile analysis (LPA) and evaluate the performance of explainable machine learning models in discriminating these subgroups based on demographic and occupational features. A cross-sectional survey enrolled 7721 nurses from 130 TCM healthcare institutions in Liaoning Province (December 2024). Data encompassed demographic, occupational, and psychological variables obtained via self-administered questionnaires, including the Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance short form 8a. LPA was employed to categorize sleep disturbance patterns. Recursive feature elimination with random forest (RFE-RF) was used to select features associated with subgroup membership for five machine learning models. Models were trained on 70% of the data and evaluated on a 30% independent test set. The optimal classification model (XGBoost) underwent interpretability analysis using Shapley additive explanations (SHAP). LPA identified three subgroups: mild-stable (29.8%), moderate-fluctuating (60%), and severe-persistent (10.2%). Machine learning models achieved test AUCs of 0.71-0.84, with XGBoost demonstrating the highest discriminatory performance (AUC = 0.84, 95%CI: 0.83-0.85) in classifying subgroups. SHAP analysis indicated that monthly income, organizational support, hospital level, self-compassion, and resilience were the top five features contributing to the model's classification output. This study characterized three distinct sleep disturbance subgroups among TCM nurses, with the majority exhibiting moderate symptoms. The sequential application of LPA and explainable machine learning demonstrated robust performance in distinguishing sleep disturbance patterns. Identifying correlates-such as lower income and resilience-may assist nurse managers in stratifying risk and tailoring interventions for those most likely to fall into the severe subgroup. Future longitudinal studies are required to validate the stability of these subgroups and establish causal relationships. Show less
This study aims to identify the 24-h movement behavior patterns of preschool children using Latent Profile Analysis based on Compositional Data Analysis (CoDA), and to examine their associations with Show more
This study aims to identify the 24-h movement behavior patterns of preschool children using Latent Profile Analysis based on Compositional Data Analysis (CoDA), and to examine their associations with physical fitness. The study employs a cross-sectional design. A total of 329 healthy children aged 4-6 years were selected. Accelerometers (ActiGraph wGT3-BT, Pensacola, FL, USA) were used to measure light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sedentary behavior (SB), while sleep was assessed through parent and teacher questionnaires. The assessment of physical fitness was conducted in accordance with the "Chinese National Physical Fitness Test Standards" (Preschooler Section). To address the multicollinearity problems among components of physical activity (PA), CoDA was first applied, subsequently, Latent Profile Analysis was utilized to categorize 24-h movement behavior patterns, while a Generalized Ordered Logit Model (GOLM) was applied to investigate their associations with physical fitness. Three distinct behavioral patterns emerged from the analysis: the "brown bear group" (moderate PA and SB, high SP, N = 176, 53.5%), the "cheetah group" (high PA/MVPA, low SB, moderate SP, N = 102, 31%), and the "koala group" (low PA, high SB, lower SP, N = 51, 15.5%). After adjusting for potential confounding factors, it was found that compared with the "koala group", the "brown bear group" and the "cheetah group" exhibited higher levels of physical fitness, with the probability of improving their physical fitness rating being 3.69 times and 6.36 times that of the "koala group," respectively. This study highlights the significant impact of active and healthy activity patterns on the physical fitness of preschool children, providing a foundation for formulating personalized preventive and interventional approaches in early childhood. Show less
This study examined the relationship between motor competence (MC) and Physical Activity (PA) in school-aged children, and assessed the mediating role of physical fitness, based on the Model of the Re Show more
This study examined the relationship between motor competence (MC) and Physical Activity (PA) in school-aged children, and assessed the mediating role of physical fitness, based on the Model of the Relationship between Children’s Motor Development and Obesity Risk. From March to April 2022, 1,026 children (53.6% boys, mean age 8.93 years) from four public primary schools in Shijiazhuang City, China, were recruited via stratified cluster sampling. MC was assessed using the Test of Gross Motor Development, 3rd edition (TGMD-3), PA was measured via a three-axis accelerometer, and physical fitness was evaluated according to the Chinese National Student Physical Health Standards (2014 revision). Data were analyzed using SPSS 26.0, with mediation tested via the bias-corrected bootstrap method (10,000 resamples). Ball skills ( Ball skills are critical for promoting MVPA in school-aged children, with physical fitness acting as a significant mediator. Systematic ball skill training is recommended as a core strategy to enhance physical activity via improved fitness. Show less
This is a cross-sectional study designed to identify the latent profiles of psychological resilience in elderly patients with fracture and examine the relationship between resilience categories and fe Show more
This is a cross-sectional study designed to identify the latent profiles of psychological resilience in elderly patients with fracture and examine the relationship between resilience categories and fear of falling (FOF), thereby informing individualized rehabilitation strategies. A convenience sample was drawn from elderly patients admitted to the Department of Traumatology and Orthopedics at a tertiary general hospital in Beijing between September 2024 and July 2025 due to fall-related fractures. A total of 213 older adults aged 60 and above with fall-related fractures were included. Psychological resilience was assessed using the Connor-Davidson Resilience Scale (CD-RISC), and FOF was measured with the Falls Efficacy Scale-International (FES-I). Latent Profile Analysis (LPA) was used to identify resilience profiles. Logistic and linear regression analyses, adjusting for age, sex, comorbidities, pain level, functional status, and time since fracture/surgery, were performed to explore the relationship between resilience subtypes (entered as a continuous CD-RISC score), demographic and clinical factors, and FOF levels. The age of elderly patients with fall-related fractures was 60–98 (75.28 ± 8.73) years old, and the median age was 74 years old. Three latent resilience profiles were identified: low (33.5%), moderate (22.7%), and high (43.8%) resilience groups. Patients in the high-resilience group exhibited significantly lower FOF scores than those in the other two groups ( Psychological resilience is independently associated with fear of falling among elderly fracture patients, with a clear gradient across resilience profiles. Enhancing resilience, particularly in low-resilience individuals, may be a potential target for intervention, though causal inference is limited by the cross-sectional design and single-center, convenience sampling strategy. Integrating resilience assessment into clinical evaluation could support more holistic rehabilitation planning. ChiCTR2400089221, September 4, 2024. Show less
This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This stu Show more
This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This study employed a cross-sectional design and was conducted from January to April 2024 in Wuhan, China. Participants were FSWs recruited through snowball sampling from entertainment venues, including hotels, restaurants, nightclubs, karaoke bars and dance halls. Data were collected via structured questionnaires covering sociodemographic information, work experience, psychological stress, health status, sleep quality and circadian rhythms. Latent profile analysis (LPA) was employed to identify health characteristic profiles among FSWs, and multivariate logistic regression was used to examine the associations between these profiles and sleep quality. Among the 1,036 FSWs surveyed, 45.1% had poor sleep quality. LPA classified FSWs’ health characteristics into three profiles: the high overall functioning group, the lower physical–emotional functioning group and the lower psychosocial functioning group. Multivariate logistic regression analysis showed that FSWs in the lower physical–emotional functioning group had higher odds of poor sleep quality (OR = 2.184) compared with those in the high overall functioning group. FSWs in the lower psychosocial functioning group had substantially higher odds of poor sleep quality (OR = 7.755) than that in the high overall functioning group. FSWs demonstrate substantial heterogeneity in health characteristics and exhibit lower overall sleep quality compared with the general population. Psychological and physiological factors are major influencing factors for their sleep quality, suggesting the importance of prioritising mental and physical health in this population. Show less
Observational studies have yielded conflicting evidence regarding the interdependence between lipoprotein(a) [Lp(a)]-related cardiovascular risk and systemic inflammation. It remains unclear whether c Show more
Observational studies have yielded conflicting evidence regarding the interdependence between lipoprotein(a) [Lp(a)]-related cardiovascular risk and systemic inflammation. It remains unclear whether combined targeting of Lp(a) and inflammation provides additive cardiovascular benefits. This study aimed to investigate the associations between genetically predicted lower Lp(a) and cardiovascular disease (CVD) across interleukin-6 (IL-6) signalling levels and the combined effects of lower Lp(a) and IL-6 signalling activity on CVD risk. This study included UK Biobank participants of European ancestry. Genetic scores for LPA and IL-6 receptor (IL6R)-mediated signalling were calculated to mimic the effects of therapies targeting Lp(a) and IL-6 signalling, respectively. We investigated the associations of separate and combined exposure to lower Lp(a) and IL-6 signalling with coronary heart disease (CHD), ischaemic stroke (IS), heart failure (HF), atrial fibrillation (AF), peripheral artery disease (PAD), and aortic aneurysm (AA), using Mendelian randomization analyses and validating the findings in observational analyses. This study included 408 687 UK Biobank individuals (mean age, 57 years; 54% women). Genetically predicted lower Lp(a) was associated with reduced risks of CHD [odds ratio (OR) per 50 mg/dL reduction in Lp(a) levels, 0.68; 95% confidence interval (CI), 0.65-0.71], IS (0.89, 0.80-0.98), PAD (0.68, 0.62-0.76), HF (0.82, 0.77-0.88), and AA (0.71, 0.61-0.82). Genetically lower IL-6 signalling was associated with lower risks of CHD (OR per 0.5 log[mg/L] reduction in log-transformed C-reactive protein levels, 0.67; 95% CI, 0.55-0.82), AF (0.72, 0.55-0.94), and AA (0.43, 0.23-0.83). The genetic association between Lp(a) and CVD was consistent among individuals with different IL-6 signalling activity (P for difference > 0.05). Combined exposure to genetically predicted lower Lp(a) and IL-6 signalling was associated with an additive decrease in CHD risk (lower Lp(a): 0.67, 0.63-0.71; lower IL-6 signalling: 0.61, 0.46-0.80; combined: 0.25, 0.21-0.30; P for interaction = 0.144). In observational analyses, IL-6 levels below the median and Lp(a) concentrations below 50 mg/dL were also independently and additively associated with lower CHD risk (Lp(a) < 50 mg/dL: hazard ratio, 0.82; 95% CI, 0.72-0.93; IL-6 < median: 0.79, 0.65-0.96; combined: 0.65, 0.56-0.74; P for interaction = 0.102). Lower Lp(a) levels were associated with a reduced risk of CVD, independent of IL-6 signalling activity. Combined exposure to genetic variants lowering Lp(a) and downregulating IL-6 signalling was associated with an additive reduction in cardiovascular risk. These findings indicate that concurrent Lp(a)-lowering and anti-inflammatory therapies may reduce residual cardiovascular risk through additive effects. Show less
Using latent profile analysis (LPA) based on Self-Determination Theory (SDT), this study aimed to explore the profiles of health behavior motivation among Chinese patients with prediabetes and examine Show more
Using latent profile analysis (LPA) based on Self-Determination Theory (SDT), this study aimed to explore the profiles of health behavior motivation among Chinese patients with prediabetes and examine the relationship between these profiles and self-management ability. A cross-sectional study was conducted involving 335 patients with prediabetes. The questionnaires were used to assess health behavior motivation, self-management ability, satisfaction of basic psychological needs and disease knowledge level. Latent profile analysis was performed based on five subscale scores of the health behavior motivation measure. Three distinct latent profiles were identified: a "Self-Determined" profile (C1,29.55%, n=99), a "Non Self-Determined" profile (C2, 55.82%, n=187), and a "Conflicted" profile (C3, 14.63%, n=49). Patients in the C1 profile demonstrated higher levels of autonomy and competence. Patients in the C2 profile were characterized by better disease knowledge and lower relatedness. Compared to patients in the C3 profile, patients in both the C1 and C2 profiles exhibited significantly lower self-management ability. The heterogeneity in health behavior motivation profiles must be considered in the design and clinical practice of personalized interventions for prediabetes. Profile-specific strategies serve as the foundation for enhancing patients' self-management ability and sustaining healthy behaviors. Show less
Major depressive disorder (MDD) in adolescents is a critical public health concern, yet objective diagnostic biomarkers remain lacking. We conducted an integrative lipidomics study across human cohort Show more
Major depressive disorder (MDD) in adolescents is a critical public health concern, yet objective diagnostic biomarkers remain lacking. We conducted an integrative lipidomics study across human cohorts and a chronic unpredictable mild stress (CUMS) rat model. Targeted UPLC-MS/MS profiling was applied to a training cohort (95 MDD, 40 controls), and untargeted UPLC-HRMS profiling to an independent cohort (56 MDD, 37 controls). Candidate biomarkers were identified using univariate tests, partial least squares discriminant analysis, and three feature-selection methods (Boruta, LASSO, RFE), with predictive performance evaluated by cross-validation and external replication. Translational relevance was examined in CUMS rats through behavioral assays and lipidomic profiling of serum and brain tissues. Pathway enrichment and regression models explored metabolic context and clinical associations. In the training cohort, we found that 244 lipids were significantly altered, highlighting altered glycerophospholipid, glycerolipid, and sphingolipid metabolism. A 29-lipid panel achieved 90.4% cross-validation accuracy, while a reduced 7-lipid subset reached 94.8%. In the validation cohort, an 8-lipid panel achieved 71.2% accuracy, and a minimal 2-lipid set-LPA(18:2) and SPH(d16:1)-reached 72.1%. Cross-species analysis confirmed consistent downregulation of SPH(d16:1) in serum of both humans and rats, and of LPC(0:0/16:0) specifically in the rat prefrontal cortex. Regression analyses linked sex, age, and anxiety severity to lipid alterations. This cross-platform, cross-species study identifies reproducible lipid signatures of adolescent MDD, highlights SPH(d16:1) and LPC(0:0/16:0) as translational biomarkers, and implicates glycerophospholipid metabolism in MDD pathophysiology, providing a foundation for biomarker-guided diagnostics and therapeutics. Show less
This study examined heterogeneous patterns of trauma-related adaptation among Chinese adolescents during the post-COVID-19 recovery phase, focusing on the co-occurrence of posttraumatic distress (PTD) Show more
This study examined heterogeneous patterns of trauma-related adaptation among Chinese adolescents during the post-COVID-19 recovery phase, focusing on the co-occurrence of posttraumatic distress (PTD) and posttraumatic growth (PTG). We also investigated how modifiable psychosocial protective and vulnerability factors were associated with membership in different adaptation profiles. A large-scale cross-sectional survey was administered to 5, 044 students (aged 9-17 years; 46.6% male) from 15 primary and secondary schools in Wuhan, China. Validated instruments assessed posttraumatic stress symptoms (PCL-C), posttraumatic growth (PTGI), depressive symptoms (CES-D), and anxiety (SAS). Protective and vulnerability factors included resilience (CD-RISC), perceived social support (SSRS), physical activity (PARS-3), school belonging (PSSM), adaptive coping (SCSQ), and trait anxiety (TAI). Latent profile analysis (LPA) was used to identify adaptation profiles, and multinomial logistic regression examined how modifiable psychosocial factors were associated with profile membership. LPA revealed four empirically derived profiles: a High Distress/High Growth-Moderate PTSD profile (76.9%), a Low Distress-High Growth profile (4.8%), a Low Growth-Moderate Distress profile (3.9%), and a High Distress/High Growth-High PTSD profile (14.4%). The vast majority of adolescents showed some degree of both PTD and PTG, consistent with dual-process perspectives. In multinomial models, higher resilience, social support, school belonging, adaptive coping, and physical activity were associated with greater likelihood of belonging to the Low Distress-High Growth profile rather than more distressed profiles, whereas higher trait anxiety was associated with increased odds of membership in profiles characterized by greater distress. In this large school-based sample of Chinese adolescents, distress and growth frequently co-occurred and clustered into distinct adaptation profiles that differed systematically in psychosocial resources. Resilience, social connectedness, school belonging, and physical activity emerged as promising targets for trauma-informed, school-based support, whereas trait anxiety appeared to mark heightened vulnerability. Given the cross-sectional and single-region design, these findings should be interpreted as exploratory, and longitudinal and cross-cultural studies are needed to clarify temporal and contextual influences on adolescent trauma adaptation. Show less
Occupational stress in nursing is a critical issue that can have significant implications for both workforce stability and personal health. This study aimed to identify subgroups of occupational stres Show more
Occupational stress in nursing is a critical issue that can have significant implications for both workforce stability and personal health. This study aimed to identify subgroups of occupational stress among Chinese female clinical nurses using latent profile analysis, compare sociodemographic differences across these subgroups, and examine their associations with premenstrual syndrome (PMS). A cross-sectional study was conducted among female nurses in tertiary hospitals in Huai'an City, Jiangsu Province, China, from November to December 2023. We recruited participants via convenience sampling, and 400 valid questionnaires were collected. Data were collected using a researcher-developed general information questionnaire, the standardized Chinese Nurses Stressor Scale (35 items), and the Premenstrual Syndrome Scale. Latent profile analysis (LPA) was performed with Mplus 8.0 to identify occupational stress subtypes. Sociodemographic predictors of these subtypes were explored using chi-square tests and multivariate logistic regression in SPSS 25.0. The association between stress subtypes and PMS symptoms was assessed using ANOVA. A Three clinical female nurse occupational stress subtypes were identified: overall low-stress (38.3%, This study identified significant heterogeneity in occupational stress among clinical female nurses, categorized into three distinct subtypes differing in stress levels and demographic characteristics. These findings highlight the importance of considering individual differences when developing interventions to address occupational stress. The study advocates for the implementation of intervention strategies targeting different types of stress in nursing education and organizational reform to better support nurses in fulfilling their responsibilities. Show less
To identify latent family resilience profiles among families of patients with first-episode stroke in the intensive care unit (ICU) and examine factors associated with resilience heterogeneity, with t Show more
To identify latent family resilience profiles among families of patients with first-episode stroke in the intensive care unit (ICU) and examine factors associated with resilience heterogeneity, with the aim of informing targeted family-support interventions. A cross-sectional study was conducted among 335 ICU patients with first-episode stroke and their primary caregivers. Family resilience was assessed using the Chinese version of the Family Resilience Assessment Scale (FRAS-C). Latent profile analysis (LPA) was used to identify subgroups of family resilience, while LASSO regression and multiple binary logistic regression were applied to determine influencing factors. Two distinct resilience profiles were identified: Developing Families, characterized by lower levels of communication, resource utilization, and positive outlook; and Optimized Families, characterized by higher resilience across all dimensions. ICU admission count (OR = 2.299, 95% CI: 1.066-4.960), frequency of care and support from relatives or friends (OR = 1.851, 95% CI: 1.068-3.206), and number of additional organ system dysfunctions (OR = 0.233, 95% CI: 0.122-0.445) were significantly associated with family resilience profiles (all Family resilience among ICU first-episode stroke patients shows notable heterogeneity, with two typical resilience patterns. Early identification of high-risk families-particularly those with limited social support or higher disease complexity-can guide clinicians in delivering targeted communication support, psychological counseling, and resource linkage interventions. Tailored resilience-enhancing strategies may contribute to better patient recovery and improved family adaptation during critical care. Show less
This cross-sectional study aimed to examine the associations between the 24-h movement behaviors and mental health among university students in China, and to determine the optimal behavioral balance b Show more
This cross-sectional study aimed to examine the associations between the 24-h movement behaviors and mental health among university students in China, and to determine the optimal behavioral balance based on the top 5% of model-predicted mental health outcomes using compositional data analysis. A total of 6,084 university students aged 17–24 years in Southwest China self-reported their daily durations of moderate-to-vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), sedentary behavior (SED), and sleep (SLP). They were stratified by gender and then randomly and equally assigned to the “recommendation” group and the “validation” group. Using compositional data analysis, time-use compositions (MVPA, LPA, SED, SLP) were transformed into isometric log-ratios (with quadratic terms as needed) and subsequently used in regression models to predict the three mental health outcomes. All possible combinations of motion components were examined to determine the combination with the highest correlation (top 5%) for each outcome. Through research and analysis of the recommendation groups, the optimal combination of average (range) time usage is determined as follows: for males, MVPA 92 (60–110) min/day, LPA 361 (310–400) min/day, SED 372 (350–480) min/day, SLP 614 (530–680) min/day; for females, MVPA 58 (40–90) min/day, LPA 290 (180–390) min/day, SED 445 min (400–560), SLP 665 (580–740) min/day. The recommended durations served as benchmarks for the validation group. Participants who met the optimal 24-h movement behavior time showed significantly lower depression (males: β = –1.290, The optimal 24-h movement behavior time differs between men and women. Males tend to require a longer optimal MVPA duration than females, while females require a longer optimal SLP duration than males. The findings provide valuable reference for developing 24-h movement guidelines and promoting healthy and balanced lifestyles among university students. [Image: see text] The online version contains supplementary material available at 10.1186/s12889-026-26534-x. Show less
This study develops and tests an AI-empowerment Configural Model to explain how artificial intelligence (AI) empowers language learning engagement. Grounded in ecological systems theory (EST) and ecol Show more
This study develops and tests an AI-empowerment Configural Model to explain how artificial intelligence (AI) empowers language learning engagement. Grounded in ecological systems theory (EST) and ecological affordance theory (EAT), the model theorizes AI as an interactive agent within the learning ecosystem. A mixed-methods study of 475 Chinese university language learners demonstrates that AI'S effect on engagement is significantly mediated by the perceived quality of its ecological coupling with teachers, peers, and the environment. Latent profile analysis (LPA) further identifies three distinct learner configurations: low coupling-low engagement, moderate coupling-moderate engagement and high coupling-high engagement, which systematically differ in their coupling of AI. The model ultimately shifts the paradigm from tool implementation to strategic ecological governance, providing a practical basis for designing learning environments that leverage synergistic human-AI coupling to foster deeper, sustained engagement. Show less
To investigate potential types of food avoidance among patients with inflammatory bowel disease (IBD) and identify the contributing factors. Food avoidance may be an important risk factor for poor phy Show more
To investigate potential types of food avoidance among patients with inflammatory bowel disease (IBD) and identify the contributing factors. Food avoidance may be an important risk factor for poor physical and mental health in patients with IBD. However, there is limited research on food avoidance within the Chinese context. Between July 2022 and December 2023, patients with IBD during appointment at the First Affiliated Hospital with Nanjing Medical University was investigated with paper questionnaires to assess food avoidance, food category avoidance, fear of disease progression, negative illness perception, IBD-related self-efficacy, and social support. Demographic and disease-related characteristics were also collected. Latent profile analysis (LPA) was used to examine food avoidance in patients with IBD, and the correlates were investigated using regression analysis. LPA showed that respondents could be classified into three groups in terms of food avoidance, namely, the mild-food avoidance adaptation group ( Patients with IBD may exhibit long-term, spontaneous food avoidance, which often presents at high levels. Furthermore, patients with IBD exhibit considerable heterogeneity in their food avoidance patterns, categorizing them into three distinct categories. Future dietary management strategies should be tailored based on the specific characteristics and predictive factors of these food avoidance patterns. Given the prevalence and heterogeneity of food avoidance in patients with IBD, nurse managers should implement stratified interventions tailored to patient characteristics. Training nurses in culturally sensitive dietary education and emotional regulation strategies may improve the management of food-related behaviors and support patients' adaptive coping with the disease. Show less
The present study aimed to investigate the combined impact of lipoprotein (a) [Lp(a)] and low-density lipoprotein (LDL) subfractions on cardiovascular outcomes in patients with acute coronary syndrome Show more
The present study aimed to investigate the combined impact of lipoprotein (a) [Lp(a)] and low-density lipoprotein (LDL) subfractions on cardiovascular outcomes in patients with acute coronary syndrome (ACS). The study enrolled 2061 ACS patients from Tianjin Chest Hospital. Participants were categorized into 4 groups based on their Lp(a) and the concentration of the sixth component particles of LDL(LDL-P6). The primary endpoint was the occurrence of major adverse cardiovascular events (MACE). The relationship between LDL-P6, Lp(a), and MACE was evaluated. Over a mean follow-up period of 5.4 years, 456 (22.1%) patients experienced MACE. Multivariate analysis identified both LDL-P6 and Lp(a) as significant independent predictors of MACE in ACS patients. Those in the highest-risk group had a substantially higher incidence of MACE compared with the lowest-risk group (HR 5.718; 95% CI 3.703-8.829; Show less
This study aimed to identify distinct patterns of chronic disease resource utilization among patients with chronic obstructive pulmonary disease (COPD) and to examine their association with illness un Show more
This study aimed to identify distinct patterns of chronic disease resource utilization among patients with chronic obstructive pulmonary disease (COPD) and to examine their association with illness uncertainty. A cross-sectional study. This study enrolled COPD patients hospitalized in the Department of Respiratory Medicine at a tertiary hospital in Zhejiang Province, China, between April and December 2023. All participants completed a general information form, the Chronic Illness Resource Survey (CIRS), and the Mishel Uncertainty in Illness Scale (MUIS). Latent profile analysis (LPA) was conducted to identify subgroups of resource utilization patterns. Subsequently, hierarchical linear regression was employed to assess the associations between these patterns and illness uncertainty. Ethical approval was obtained from the Institutional Review Board of the Fourth Affiliated Hospital of Zhejiang University (Approval No. K2022057). A total of 308 participants were included. Two latent classes of resource utilization were identified: the Suboptimal Utilization Group ( Distinct patterns of chronic disease resource utilization exist among COPD patients and are significantly associated with illness uncertainty. Healthcare providers should recognize these subgroups and implement targeted interventions to enhance access to disease-related support resources, thereby mitigating illness uncertainty. Understanding COPD patients' varying patterns of resource utilization enables healthcare professionals and related industries to deliver personalized, resource-based interventions tailored to individual needs, ultimately reducing illness-related uncertainty and improving disease management outcomes. Show less
Through the selective breeding of superior strains, livestock and poultry can achieve enhanced disease resistance and production performance, thereby improving farming efficiency and increasing chicke Show more
Through the selective breeding of superior strains, livestock and poultry can achieve enhanced disease resistance and production performance, thereby improving farming efficiency and increasing chicken meat yield. This study analyzed the expression of gut health-related genes, cecal microbiota, and untargeted serum metabolomics in Wenchang chickens from the NS strain (Normal strain) and the AFS strain (Antibiotic-free strain), and explored the relationships between their cecal microbiota and serum metabolites. Our results show that in the ileum, antioxidant-related indicators T-AOC (P < 0.05), T-SOD (P < 0.05), and GSH-PX (P < 0.05) were significantly higher in the AFS strain than in the NS strain, while MDA (P < 0.05) was significantly lower in the AFS strain than in the NS strain. The mRNA expression level of RORγt/FoxP3, which is related to immune regulation, was significantly lower in the AFS strain than in the NS strain (P < 0.05). The differential microorganisms in the cecum primarily included Muribaculum, Cryptobacteroides, Blautia, Enterocloster, Lachnoclostridium, Hydrogenoanaerobacterium, Ruminococcus, Subdoligranulum, Clostridioides, and Evtepia. The main differential metabolites in serum included folinic acid, biotin, lysophosphatidic acid (LPA), 3-hydroxy-3-methylbutanoic acid, 3-hydroxybutyric acid, and others. The differential metabolites are primarily enriched in the following metabolic pathways: gap junction, glycolipid metabolism, and fatty acid biosynthesis. In addition, the Pearson correlation analysis between the gut microbiota and serum metabolites showed that Blautia was positively correlated with folinic acid (P < 0.05) and biotin (P < 0.05); Lachnoclostridium was positively correlated with biotin (P < 0.01); and Ruminococcus was positively correlated with 3-hydroxybutyric acid (P < 0.05). This study mainly elucidates the metabolic characteristics of the antibiotic-free Wenchang chicken strain by analyzing gut microbiota and serum metabolites. Show less
The associations between 24-h movement behaviours (24 h MBs) and emotional and behavioural problems (EBPs) in early years are not well understood. This study examined these associations in a nationall Show more
The associations between 24-h movement behaviours (24 h MBs) and emotional and behavioural problems (EBPs) in early years are not well understood. This study examined these associations in a nationally representative sample of Chinese preschoolers. As part of the Chinese cohort of the SUNRISE International Study of Movement Behaviors in the Early Years main study, this research recruited 1316 children aged 3-4 years through multistage stratified cluster sampling in urban and rural areas across seven major administrative regions in China. Moderate- to vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA) and sedentary behaviour (SED) were measured using 24-h accelerometry over five consecutive days. Sleep duration was parent-reported. EBPs were evaluated using the parent-rated Strengths and Difficulties Questionnaire (SDQ), which assesses total difficulties, internalising problems, externalising problems and prosocial behaviour. Compositional multiple linear regression was employed to analyse the relationships between 24 h MBs and EBPs. Compositional isotemporal substitution was also utilised to predict changes in EBPs due to reallocating time among 24 h MBs. Isotemporal substitution analyses revealed that replacing as little as 1 min of MVPA, LPA or SED with sleep was associated with significant reductions in total difficulties (β Increasing LPA by reducing MVPA or SED was significantly associated with improvements in internalising and conduct problems, whereas increasing sleep to decrease MVPA or SED-even by small amounts-was consistently associated with improvements in EBPs across all SDQ subscales. However, increasing LPA at the expense of sleep exacerbates total difficulties and externalising problems. Promoting diverse LPA opportunities alongside sufficient sleep, while maintaining a balance between them, is essential for supporting preschoolers' emotional and behavioural development. Show less
Conflicting data have explored the association between lipoprotein(a) [Lp(a)] and atherosclerotic cardiovascular disease (ASCVD) among individuals with different glucose metabolism statuses. We aimed Show more
Conflicting data have explored the association between lipoprotein(a) [Lp(a)] and atherosclerotic cardiovascular disease (ASCVD) among individuals with different glucose metabolism statuses. We aimed to prospectively evaluate this association and to assess whether it is modified by C-reactive protein (CRP). This population-based cohort study was derived from the UK Biobank database. Lp(a) and CRP were measured between 2006 and 2010. Cox proportional hazards models and restricted cubic spline curves were employed to assess the relationship between Lp(a) levels and time to ASCVD events. A total of 307 269 participants without prevalent ASCVD were included, comprising 253 746 individuals with normal glucose regulation (NGR), 38 020 with prediabetes, and 15 503 with diabetes. The mean age was 57 years (Q1-Q3: 50-63), and 55.3% were female. Over a median follow-up of 13.2 years, 29 521 ASCVD events occurred. Higher Lp(a) levels were associated with an increased risk of ASCVD across all glucose metabolism statuses. In fully adjusted models, the hazard ratio (95% confidence interval) for ASCVD comparing participants in the top 10% of Lp(a) with those in the bottom 33% was 1.28 (1.22-1.34) among those with NGR, 1.23 (1.12-1.35) among those with prediabetes, and 1.16 (1.02-1.31) among those with diabetes. No significant interactions were observed after stratification by CRP (<2/≥2 mg/L) across glucose metabolism groups (P for interaction >0.05). Elevated Lp(a) levels were associated with a higher risk of ASCVD across different glucose metabolism statuses, particularly among individuals with NGR and prediabetes, independent of baseline CRP levels. Show less
Oxypeucedanin (OPD) showed anti-allodynia against neuropathic pain (NeuP) in our previous study. In the present study, we aimed to further investigate whether lysophosphatidic acid receptor (LPAR) sig Show more
Oxypeucedanin (OPD) showed anti-allodynia against neuropathic pain (NeuP) in our previous study. In the present study, we aimed to further investigate whether lysophosphatidic acid receptor (LPAR) signaling mediated OPD-induced antinociception against NeuP models. Single OPD treatment dose-dependently reduced pain hypersensitivity, and repeated OPD treatment maintained sustained antinociception without the development of tolerance. Importantly, OPD exhibited a significant curative effect on different stages of NeuP. ROCK and RhoA agonists prevented the therapeutic effect of OPD, while the inhibitors of LPAR, ROCK, and RhoA mimicked OPD-induced antinociception. Notably, OPD treatment attenuated the increases of LPA content and protein expression of LPAR1, RhoA, and Show less
Lysophosphatidic acid acyltransferase (LPAAT) is a pivotal enzyme in the de novo biosynthesis of phosphatidic acid (PA), playing a central role in glycerophospholipid assembly and triacylglycerol (TAG Show more
Lysophosphatidic acid acyltransferase (LPAAT) is a pivotal enzyme in the de novo biosynthesis of phosphatidic acid (PA), playing a central role in glycerophospholipid assembly and triacylglycerol (TAG) accumulation. Myrmecia incisa is a green microalga notable for its high content of arachidonic acid (ArA), yet the molecular mechanism underlying ArA enrichment in TAG remains unclear. In this study, a putative LPAAT gene from M. incisa, designated MiLPAAT, was identified and cloned, followed by systematic structural and functional characterization. Sequence analysis revealed that MiLPAAT contains a conserved PlsC domain and the characteristic H(X)₄D and EGTR motifs. Bioinformatic predictions identified at least one transmembrane domain at the N-terminus, supporting its identity as an integral membrane protein. This was further confirmed by membrane fractionation and Western blot analysis, which demonstrated its association with the membrane fraction. Phylogenetic analysis further demonstrated its close evolutionary relationship to LPAAT homologs in other green algae. Heterologous expression in Escherichia coli, coupled with in vitro enzymatic assays, confirmed that the recombinant MiLPAAT protein possesses LPAAT activity, catalyzing the acylation of LPA with various acyl-CoAs. Among the substrates tested, MiLPAAT exhibited the highest catalytic efficiency toward ArA-CoA (104.8 ± 3.2 nmol/mg/min), followed by oleoyl-CoA (81.5 ± 2.7 nmol/mg/min) and palmitoyl-CoA (68.4 ± 2.1 nmol/mg/min), consistent with the ArA-rich TAG composition observed in M. incisa. Immunogold labeling and immunohistochemical localization experiments revealed that MiLPAAT is predominantly localized at the plasma membrane. Findings of the present study suggest that MiLPAAT plays a critical role in PA biosynthesis and assembly of ArA into TAG in M. incisa, providing a novel target for microalgal lipid metabolic engineering. Show less
Parents of children with congenital heart disease (CHD) face chronic stress impairing family functioning and well-being. As a key protective factor, family resilience aids their adaptation. However, e Show more
Parents of children with congenital heart disease (CHD) face chronic stress impairing family functioning and well-being. As a key protective factor, family resilience aids their adaptation. However, existing research predominantly measures general family resilience, neglecting heterogeneous resilience patterns and subgroup profiles. Our study uses person-centered Latent Profile Analysis (LPA) to identify latent family resilience classes in Chinese culture to provide tailored support. This study adopted a cross-sectional survey design. From October 2024 to July 2025, convenience sampling was used to recruit 426 eligible parents of children with CHD from two tertiary hospitals in Yunnan Province, China. Data were collected using the General Information Questionnaire, Family Hardiness Index (FHI), Simplified Coping Style Questionnaire (SCSQ), and Social Support Rating Scale (SSRS). LPA was applied to classify the family resilience levels of these parents. Subsequently, univariate and multivariate ordinal logistic regression analyses were conducted to explore the factors associated with different latent classes of family resilience. A total of 400 valid questionnaires were collected, with an effective response rate of 93.9%. The mean total score for family resilience in parents of children with CHD was 58.13 ± 5.79, suggesting a moderate overall level of family resilience in this group. The family resilience of parents of children with CHD was classified into three latent profiles: “High family resilience responsibility-anchored type” ( Parents of children with CHD demonstrate heterogeneity in family resilience. Healthcare professionals should pay attention to the family resilience differences among parents of children with CHD and implement targeted intervention measures based on the characteristics of different subgroups, thereby enhancing parents’ family resilience and further promoting family well-being. The online version contains supplementary material available at 10.1186/s12889-025-26143-0. Show less
Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroup Show more
Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroups, risk factors, and symptom-level interactions underlying depression-anxiety comorbidity across adolescents and adults in multi-ethnic Southwest China. The study included a total of 41,394 adolescents (aged 9-19) and 17,345 adults (aged 18-80). Adolescents were recruited using multistage stratified cluster sampling, whereas adults were recruited by convenience sampling. All participants completed a self-designed sociodemographic questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7). Latent profile analysis identified subgroups, logistic regression analyzed risk/protective factors, and network analysis mapped symptom interactions and bridge nodes. This study found that three adolescent profiles emerged: high (11.66 %), moderate (31.95 %), and low/no depression-anxiety (56.39 %). Adults were classified into low/no comorbidity (90.63 %) and comorbid depression-anxiety (9.37 %). Risk factors for adolescents included female gender (OR = 2.77, 95 %CI: 2.55-3.00; OR = 1.59, 95 %CI: 1.52-1.67), higher grade levels (OR = 3.45, 95 %CI: 3.10-3.84; OR = 3.56, 95 %CI: 3.33-3.80), smoking (OR = 1.72, 95 %CI: 1.51-1.96; OR = 1.28, 95 %CI: 1.17-1.41),drinking (OR = 2.45, 95 %CI: 2.23-2.70; OR = 1.66, 95 %CI: 1.55-1.77), family instability (OR = 1.16, 95 %CI: 1.02-1.31; OR = 1.33, 95 %CI: 1.14-1.56) and "other" ethnic minority (OR = 1.15, 95 %CI: 1.04-1.26). For adults, female gender(OR = 1.68; 95 %CI: 1.44-1.97), living alone(OR = 1.37; 95 %CI: 1.14-1.65), poor self-rated health (OR = 0.13, 95 %CI: 0.11-0.15), and Dai ethnicity (OR = 0.70, 95 %CI: 0.49-0.96) predicted comorbidity. Network analysis revealed distinct bridge symptoms: adolescents in the high depression-anxiety group had five symptoms: depressed or sad mood (phq2), psychomotor agitation/retardation (phq8), nervousness or anxiety (gad1), restlessness (gad5), and irritable (gad6); however, adults with comorbidity had one symptom: afraid something will happen (gad7). This study identified three patterns of depression-anxiety comorbidity in adolescents and two in adults. Efforts should prioritize adolescents from "other" ethnic minorities, strengthening family and peer support, as well as smoking and drinking interventions for adolescents, and addressing social isolation, physical health, and catastrophizing cognition in adults may mitigate the comorbidity burden. Show less
The COVID-19 pandemic has significantly disrupted educational style, potentially affecting the learning adaptation of nursing freshmen who are integral to the future nursing workforce. This study aime Show more
The COVID-19 pandemic has significantly disrupted educational style, potentially affecting the learning adaptation of nursing freshmen who are integral to the future nursing workforce. This study aimed to identify distinct subgroups of nursing freshmen based on their bioecological attributes related to learning adaptation during the pandemic. A multicenter, cross-sectional study was conducted of 1170 first-year nursing students from six higher education institutions in China. Learning adaptation, resilience, parental attachment, interaction anxiety, and mobile phone addiction, were investigated. Latent Profile Analysis (LPA) was utilized to identify distinct profiles. Descriptive statistics indicated a positive level of learning adaptation among participants, with an overall mean score of 3.51 ± 0.57. LPA revealed four distinct profiles: 'Struggling Learners' (5.47%), 'Moderate Engagers' (70.60%), 'Adaptable Strivers' (18.29%), and 'Optimal Adapters' (5.64%), which demonstrated significant differences in adaptation, resilience, parental attachment, interaction anxiety, and mobile phone addiction tendencies (P < 0.05). The study's findings emphasize the heterogeneity in learning adaptation among nursing freshmen and the importance of considering bioecological attributes when developing educational interventions during crisis. Recognizing these profiles can guide the development of targeted strategies to enhance student adaptation and academic achievement. Show less
Adolescent mental health issues have become a growing public health concern. This study seeks to identify potential profiles of mental health among Chinese adolescents and to detect high-risk groups f Show more
Adolescent mental health issues have become a growing public health concern. This study seeks to identify potential profiles of mental health among Chinese adolescents and to detect high-risk groups for the formulation of targeted intervention strategies based on associated health risk behaviors (HRBs). A cross-sectional study. This study was based on the Monitoring and Intervention Project for Common Diseases and Health Influencing Factors among Secondary School Students in Nanjing, involving 9,865 secondary school students as participants. Latent profile analysis (LPA) was employed to identify mental health (symptoms of depression, anxiety, and stress, as well as sleep quality); categorical variables were analyzed by the chi-square test or Fisher's exact test, whereas multinomial logistic regression was used to examine associations between HRBs and distinct mental health profiles. Three profiles of mental health were identified among the adolescents, including "Low-risk Mental Health" (68.03 %), "Moderate-risk Mental Health" (26.19 %), and "High-risk Mental Health" (5.78 %). Compared with the "Low-risk Mental Health" profile, the "Moderate-risk Mental Health" profile was associated with behaviors such as drinking, injury, school bullying, unhealthy diet, internet addiction, physical activity, and outdoor activity time; and the "High-risk Mental Health" profile was associated with smoking, drinking, injury, school bullying, unhealthy diet, internet addiction, and outdoor activity time. Several HRBs are associated with mental health among Chinese adolescents. Healthcare professionals should target these HRBs and implement comprehensive measures to protect adolescent mental health. Show less
Wei Zhou, Dongjian Cao, Jie Yang · 2026 · ACS applied materials & interfaces · ACS Publications · added 2026-04-24
Single-stranded DNA (ssDNA) has extremely high design flexibility and specific functions. Therefore, ssDNA is used in crucial practical applications in many fields, such as molecular detection, gene e Show more
Single-stranded DNA (ssDNA) has extremely high design flexibility and specific functions. Therefore, ssDNA is used in crucial practical applications in many fields, such as molecular detection, gene editing, and nanotechnology. However, the existing methods for ssDNA preparation often present limitations in terms of yield, purity, and length applicability. In order to overcome these challenges, the present study proposes a ssDNA separation method that utilizes the modification of linear polyacrylamide (LPA) combined with denaturing agarose gel electrophoresis (DAGE). The method is referred to as LPA-DAGE. The underlying principle is to produce LPA-modified double-stranded DNA (dsDNA) through PCR using the LPA primer and then achieve efficient ssDNA separation using denaturing agarose gel electrophoresis based on molecular weight differences. This method can stably recover ssDNA showing significant advantages over the existing methods in terms of purity and recovery rate. The results of this study demonstrate that the proposed ssDNA preparation method enables signal amplification using fluorescence Show less
Childhood trauma is a well-established risk factor for poor clinical outcomes in bipolar disorder (BD), yet most studies have relied on cumulative trauma scores, potentially overlooking heterogeneity Show more
Childhood trauma is a well-established risk factor for poor clinical outcomes in bipolar disorder (BD), yet most studies have relied on cumulative trauma scores, potentially overlooking heterogeneity in trauma exposure and its differential impact on psychopathology. This study employed latent profile analysis (LPA) to identify distinct subtypes of childhood trauma based on the Childhood Trauma Questionnaire (CTQ) among 725 individuals with BD in a Chinese clinical sample. Differences across trauma profiles were examined in relation to demographic features, psychiatric symptoms (anxiety, depression, mania), and suicidal ideation (Beck Scale for Suicide Ideation, BSSI). A four-class solution was identified, and the relationship with mental health outcomes was analyzed. Class 4 group, characterized by the most severe emotional abuse and physical neglect, along with the lowest emotional neglect, reported the highest levels of anxiety (HAMA), depression (HAMD), and suicidal ideation (BSSI). In contrast, manic symptoms (YMRS) were present across all groups but did not differ significantly between trauma profiles. Logistic regression indicated that emotional abuse was the strongest predictor of trauma class membership. Distinct trauma profiles in BD are differentially associated with symptom severity and suicide risk. These findings highlight the clinical value of moving beyond cumulative trauma scores to identify trauma-specific subtypes. Early identification of high-risk trauma configurations may inform personalized assessment and intervention strategies for individuals with BD. Show less
Pregnant women have a high incidence of perinatal mood and anxiety disorders (PMADs). To explore the influence factor on perinatal psychology, we analysed the SCFAs, lipids, cognition, emotion, and cy Show more
Pregnant women have a high incidence of perinatal mood and anxiety disorders (PMADs). To explore the influence factor on perinatal psychology, we analysed the SCFAs, lipids, cognition, emotion, and cytokines in the late pregnant women. The mood, cognition, SCFAs of the non-pregnant group were compared to those in the late pregnancy. The differences in SCFAs, lipids, cognition, and cytokines between the high-risk and low-risk groups for affective disorders among women in the late pregnancy were analysed, and the risk factors were sought. Compared with the non-pregnant group, the pregnant group scored lower on the SDMT (P < 0.001), DST (P = 0.035), VRT (P = 0.001), and VFT (P < 0.001), and took longer on the TMTA (P = 0.004). Acetate (P = 0.001) and butyrate (P = 0.002) were higher, while propionate (P < 0.001) and isobutyrate (P = 0.001) were lower in the pregnant group than in the non-pregnant group. Among the pregnant women, CRP was higher in the high-risk group for mood disorders than in the low-risk group (P = 0.048). Meanwhile, HDL was positively associated with DST (P = 0.000), VRT (P = 0.015), and VFT (P < 0.001). Longer TMTA completion times were associated with reduced propionate (P = 0.072) and LPa (P = 0.022). Longer TMTB completion time was associated with lower life satisfaction (P = 0.037), as well as decreased cholesterol (P = 0.026). Pregnant women experience changes in cognition and SCFAs. CRP is a sensitive indicator for monitoring affective disorder. Regulation of SCFAs and lipids may be beneficial for cognition and affect. Show less
Although many studies have indicated that problematic smartphone use and depressive symptoms are closely associated and frequently co-occur in adolescence, little is known about their heterogeneous co Show more
Although many studies have indicated that problematic smartphone use and depressive symptoms are closely associated and frequently co-occur in adolescence, little is known about their heterogeneous co-occurrence profiles and how these profiles evolve over time. Using person-centered approaches (LPA and RT-LTA), this study identified the co-occurrence patterns of problematic smartphone use and depressive symptoms, examined their transitions, and investigated the roles of social support and self-control on transitions. A total of 8969 Chinese adolescents (49.3% girls; T1: M Show less