Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. Human blastoids can be generated in large numbers, making them well-suited for high-th Show more
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. Human blastoids can be generated in large numbers, making them well-suited for high-throughput screening. However, automated methods for evaluating and characterizing blastoid morphology are lacking. We developed a deep-learning model-deepBlastoid-for automated classification of live human blastoids using only brightfield images. The model processes 273.6 images per second with an average accuracy of 87%, which is further improved to 97% by integrating a Confidence Rate metric. deepBlastoid outperformed human experts in throughput while matching accuracy in blastoid classification. We demonstrated the utility of the model in two use cases: (i) systematic assessment of the effect of lysophosphatidic acid (LPA) on blastoid formation and (ii) evaluating the impact of dimethyl sulfoxide (DMSO) on blastoid formation. The evaluation results of deepBlastoid using over 10,000 images were consistent with the known drug effects and showed subtle but significant effects that might have been overlooked in manual assessments. The publicly available deepBlastoid model enables researchers to train customized models based on their imaging and protocols, providing an efficient, automated tool for blastoid classification with broad applications in research, drug screening, and Show less
Bidirectional intergenerational support is linked to late-life mental health, yet the underlying mechanisms remain unclear. Guided by intergenerational solidarity and social support theories, we exami Show more
Bidirectional intergenerational support is linked to late-life mental health, yet the underlying mechanisms remain unclear. Guided by intergenerational solidarity and social support theories, we examined how distinct support profiles relate to mental health among Chinese older adults, testing self-rated health (SRH) as a mediator and social participation as a moderator. We analyzed 7,843 adults aged ≥60 from the 2020 China Longitudinal Aging Social Survey. Latent profile analysis (LPA) identified bidirectional support profiles; group differences in mental health were assessed using the Bolck-Croon-Hagenaars (BCH) approach, followed by mediation and moderated-mediation models with bootstrap inference (5,000 resamples). Four profiles emerged-High Support-High Interaction-High Closeness (HS-HI-HC; 47.02%), Child-High Support-Low Interaction-High Closeness (CS-LI-HC; 33.46%), Moderate Support-Moderate Interaction-Low Closeness (MS-MI-LC; 10.37%), and Low Support-Low Interaction-Moderate Closeness (LS-LI-MC; 9.16%). Mental health differed across different profiles, with HS-HI-HC showing the best mental health levels (the lowest scores). SRH partially mediated these associations (for instance, HS-HI-HC indirect effect = -0.186, 95% CI -0.245 to -0.131). Social participation attenuated benefits of high family support but buffered risks under low support. Bidirectional intergenerational support is heterogeneous in China; profiles characterized by reciprocity and closeness show the most favorable mental health. SRH accounts for a modest but meaningful share of these associations, and social participation can substitute for-or amplify-the benefits of family support depending on profile. Findings inform profile-tailored community and family interventions to promote healthy aging. Show less
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
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
While most patients with stage I non-small cell lung cancer (NSCLC) remain recurrence-free after resection, some still develop recurrent disease. The surgical curative time window concept, defined as Show more
While most patients with stage I non-small cell lung cancer (NSCLC) remain recurrence-free after resection, some still develop recurrent disease. The surgical curative time window concept, defined as no recurrence through 5-year follow-up, helps identify potentially cured patients, yet predictive clinicopathologic features in stage I invasive NSCLC need clarification. This study sought to identify such features to enable risk-adapted surveillance. We analyzed a prospectively collected dataset of patients with stage I invasive NSCLC who underwent R0 resection between 2008 and 2015. Cox regression analysis was used to evaluate the association between clinicopathologic features and disease recurrence, aiming to identify independent prognostic factors. A total of 1,817 patients met the inclusion criteria. The 5-year cumulative incidence of recurrence was 14.6%. Female sex, tumor size ≤2 cm, lepidic-predominant adenocarcinoma (LPA) histologic type, presence of a ground-glass opacity (GGO) component, and solid component size ≤10 mm were identified as independent prognostic factors. A risk stratification system was subsequently developed, classifying patients into two groups: a low-risk group (with ≥4 factors; n=341) and an elevated-risk group (with <4 factors; n=1,476). Kaplan-Meier analysis revealed statistically significant differences in recurrence-free survival (RFS), overall survival (OS), and lung cancer-specific survival (LCSS) between the two groups (P<0.001). The low-risk group is considered to represent the population within the surgical curative time window. Patients with stage I invasive NSCLC who meet at least four of the following five criteria-female sex, tumor size ≤2 cm, solid component ≤10 mm, presence of a GGO component, and LPA histologic type-may be considered within the "surgical curative time window" and may therefore qualify for reduced surveillance intensity. Show less
To explore the categories of flourishing in patients undergoing postoperative chemotherapy for ovarian cancer and analyse the influencing factors for each category. A cross-sectional survey was conduc Show more
To explore the categories of flourishing in patients undergoing postoperative chemotherapy for ovarian cancer and analyse the influencing factors for each category. A cross-sectional survey was conducted with 260 patients who underwent postoperative chemotherapy at the gynaecological oncology ward of a tertiary hospital in Shanxi Province between May 2024 and May 2025. Participants completed the General Information Questionnaire, Flourishing Scale, Learned Helplessness Scale, Index of Autonomous Functioning Scale, and Perceived Social Support Scale. Latent profile analysis (LPA) was used to identify the flourishing profiles. Subsequently, univariate and multivariate logistic regression analyses were conducted to examine the factors associated with profile membership. Among the 237 patients who completed valid questionnaires (recovery rate: 91.2%), the mean age was 59.48 ± 9.70 years. The LPA revealed three distinct latent categories of flourishing: low flourishing group (38.1%, n = 90), moderate flourishing group (34.2%, n = 80), and high flourishing group (27.7%, n = 67). Illness duration, comorbidity burden, learned helplessness, autonomous functioning, and perceived social support were significant factors influencing latent flourishing profiles ( Significant heterogeneity exists in flourishing levels among patients with ovarian cancer undergoing postoperative chemotherapy. Healthcare professionals can tailor interventions based on these distinct flourishing profiles and their key characteristics. This approach aims to promote patient flourishing, thereby improving their quality of life. Show less
This study aimed to investigate the effect of lipoprotein(a) (Lp(a)) on major adverse cardiovascular events (MACEs) among individuals with chronic coronary syndrome (CCS) according to ABO blood groups Show more
This study aimed to investigate the effect of lipoprotein(a) (Lp(a)) on major adverse cardiovascular events (MACEs) among individuals with chronic coronary syndrome (CCS) according to ABO blood groups. Two independent cohorts of patients with CCS were included consecutively. Blood groups and Lp(a) levels were measured. Patients with the AB group were excluded due to the small sample size. In the exploratory cohort ( Show less
This study aimed to analyse the latent profiles of moral sensitivity of nursing students and to explore the different types of influencing factors. A cross-sectional study. Convenience sampling method Show more
This study aimed to analyse the latent profiles of moral sensitivity of nursing students and to explore the different types of influencing factors. A cross-sectional study. Convenience sampling method was used to select nursing students from five hospitals in Zunyi City, Guizhou Province, from July to September 2024. The demographic characteristics questionnaire and the Chinese version of the Nursing Student Moral Sensitivity Scale (MSQ-ST) were used as survey tools. Latent profile analysis (LPA) was performed on the moral sensitivity of nursing students. Logistic regression was used to analyse the influencing factors of different profiles. A total of 805 nursing students completed the questionnaire, of which 787 were valid, with a validity rate of 97.76%. The results of latent profile analysis showed that the moral sensitivity of nursing students was divided into two latent profiles: "low moral sensitivity group" (18.68%) and "high moral sensitivity group" (81.32%), and the results of logistic regression analysis showed that the level of hospital, the length of internship and the frequency of training on moral education were the factors influencing the moral sensitivity of nursing students (p < 0.05). In this study, we have demonstrated that there are two categories of moral sensitivity in nursing students, and that demographic traits have an impact on moral sensitivity in nursing students. These findings may provide a valuable theoretical foundation for nursing educators in developing the moral awareness of nursing students. No patient or public contribution. Show less
Osteoporotic bone defects pose significant clinical challenges. While icariin (ICA) exhibits pro-osteogenic effects in vitro, its capacity to repair osteoporosis (OP)-related bone defects remains unve Show more
Osteoporotic bone defects pose significant clinical challenges. While icariin (ICA) exhibits pro-osteogenic effects in vitro, its capacity to repair osteoporosis (OP)-related bone defects remains unverified. This study investigates ICA' s therapeutic role in bone regeneration and elucidates its molecular mechanisms via the Hippo pathway in bone marrow mesenchymal stem cells (BMSCs) and OP rats. Rat BMSCs were isolated and characterized by flow cytometry (CD29+/CD34-/CD45-). BMSCs were induced under osteogenic conditions with ICA at 25 and 50 mg/L. Osteogenic differentiation and mineralization were assessed by ALP and Alizarin Red staining and by measuring mRNA and protein levels of ALP, Runx2, and OCN. The Hippo/TAZ pathway was evaluated by Western blot and qPCR for MST1, p-MST1, TAZ, and p-TAZ. A rescue experiment employed the Hippo pathway agonist lysophosphatidic acid (LPA). An ovariectomized (OVX) rat model of osteoporosis was established to validate ICA's effects in vivo, examined by micro-CT, histology, and tibial expression analyses of osteogenic markers and Hippo/TAZ signaling components. ICA promoted osteogenic differentiation and mineralization of BMSCs. Mechanistically, ICA did not alter MST1 or TAZ transcripts but markedly reduced MST1 and TAZ phosphorylation, thereby stabilizing total TAZ and enhancing downstream osteogenesis. Co-treatment with LPA abrogated ICA-induced osteogenesis, confirming Hippo/TAZ pathway dependence. In OVX rats, ICA mitigated bone loss, improved trabecular microarchitecture (BMD, BV/TV, Tb.N), and upregulated tibial expression of ALP, Runx2, and OCN. Consistently, ICA reduced p-MST1 and p-TAZ levels and increased total TAZ in bone tissues. ICA promotes bone formation both in vitro and in vivo by inhibiting Hippo kinase activity and stabilizing TAZ, thereby enhancing osteogenic differentiation. Our findings identify the Hippo/TAZ axis as a potential therapeutic target for OP and support further translational exploration of ICA as an anti-osteoporotic agent. Show less
Gestational exposure to micro- and/or nanoparticles (M/NPs) may be closely associated with adverse maternal and offspring outcomes involving multiple organ dysfunctions. Organ functional change is ach Show more
Gestational exposure to micro- and/or nanoparticles (M/NPs) may be closely associated with adverse maternal and offspring outcomes involving multiple organ dysfunctions. Organ functional change is achieved through metabolic adaptation in response to changes in the external environment; yet, intricacies of these organ dysfunctions and underlying metabolic changes remain poorly understood, particularly at spatial suborgan level. Using a pregnant mouse model exposed to polystyrene (PS)-M/NPs (sizes: 100 nm, 5 μm, 10 mg/L in drinking water) from gestation day 1 to 18, we construct a comprehensive multisub-organ lipid metabolic landscape. This analysis integrates MALDI-mass spectrometry imaging with histological assessment to monitor changes in maternal suborgans-placenta-fetus unit. Our findings reveal distinct metabolic responses between maternal and fetal organs to gestational PS-M/NPs exposure. We identify potential targeted suborgans and spatial biomarkers associated with PS-M/NPs exposure according to histological damage and metabolic remodeling, including placental junctional and labyrinth zone (e.g., phosphatidylserine, phosphatidylethanolamine [PE]), renal cortex of maternal kidney (e.g., ceramide [Cer], PE, sphingomyelin [SM], phosphatidylglycerol [PG], phosphatidylserine), ventricular muscular layer and interventricular septum of maternal heart (e.g., PE, lysophosphatidylethanolamine [LPE], lysophosphatidic acid [LPA]), fetal brain and spinal cord (e.g., Cer), and fetal liver (e.g., Cer). Furthermore, phosphatidylserine synthesis and glycolipid metabolism pathways are found to be exclusively enriched following PS-NP and PS-MP exposure in the multiorgan network, respectively. We propose an M/NPs scale-exposed suborgan effect framework, which provides a molecular foundation and potential spatial biomarkers for elucidating intersub-organ interactions in response to M/NPs exposure and their role in mediating pregnancy state. Show less
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
Traditional approaches to assessing sleep quality in clinical nurses often overlook population heterogeneity and the complex interplay of influencing factors. This study employs Latent Profile Analysi Show more
Traditional approaches to assessing sleep quality in clinical nurses often overlook population heterogeneity and the complex interplay of influencing factors. This study employs Latent Profile Analysis (LPA) and Association Rule Mining (ARM) to identify distinct sleep quality subgroups and uncover key factor combinations, thereby informing targeted intervention strategies. A total of 1,686 nurses from 123 hospitals in Shandong Province were recruited through multistage stratified sampling. LPA was used to classify participants based on seven sleep dimensions from the Pittsburgh Sleep Quality Index (PSQI), while ARM was applied to identify frequent itemsets of sleep disorder triggers. Key influencing factors were further examined using univariate analysis and multivariate logistic regression. Three latent sleep profiles were identified: high (63.11%), moderate (34.10%), and low (2.79%) sleep quality. The low-sleep subgroup was characterized by higher proportions of being unmarried/divorced (42.55%), low monthly income (≤ 3,000 CNY, 42.55%), non-permanent employment (76.60%), and severe psychological distress (44.68%). In contrast, the high-sleep subgroup featured higher rates of being married (85.62%), moderate income (3,001–7,000 CNY, 73.03%), and low psychological distress (51.32%). Key determinants included marital status (OR = 2.153/2.252), income (OR = 9.098), employment type (OR = 1.475), and psychological state (OR = 0.060–0.555). ARM revealed distinct risk combinations: “low income + non-permanent employment” (lift = 3.895) for the low-sleep group; “married + moderate income + non-permanent employment + patient conflict” for the moderate group; and “high income + low psychological distress” buffering night-shift effects in the high-sleep group. By integrating LPA and ARM, this study reveals the multidimensional heterogeneity and interactive mechanisms underlying clinical nurses’ sleep quality. The findings support a stratified intervention framework combining institutional safeguards with precision strategies to enhance sleep health management in nursing populations. Show less
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clin Show more
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clinical practice. To develop machine learning (ML) models for classifying prevalent atherosclerotic cardiovascular disease (ASCVD) risk in MASLD patients, and to enhance model interpretability using SHapley Additive exPlanations (SHAP). Methods: This retrospective study included 590 MASLD patients diagnosed at the Affiliated Hospital of Qingdao University between December 2019 and December 2024. Patients were randomly divided into a training set (n=413) and a validation set (n=177), and further stratified based on ASCVD status. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection. Six ML models were developed and evaluated using sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and F1 score. SHAP analysis was performed to interpret feature contributions. ASCVD was present in 434 of 590 patients (73.6%). The Gradient Boosting (GB) model achieved the best performance, with AUCs of 0.918 (95% CI: 0.890-0.944) in the training set and 0.817 (95% CI: 0.739-0.883) in the validation set. SHAP analysis identified the top predictors as the Cholesterol-HDL-Glucose (CHG) index, Castelli Risk Index II (CRI-II), lipoprotein(a) [Lp(a)], serum creatinine (Scr), and uric acid (UA). The GB model demonstrated strong high accuracy in identifying existing ASCVD in MASLD patients and may serve as a useful tool for early risk stratification in clinical settings. Show less
The study aimed to characterise presenteeism among nurses and identify nurses' presenteeism associated with distinct latent profiles. This study employed a cross-sectional descriptive approach. From J Show more
The study aimed to characterise presenteeism among nurses and identify nurses' presenteeism associated with distinct latent profiles. This study employed a cross-sectional descriptive approach. From July to December 2024, data were collected from 404 Chinese clinical nurses across four tertiary hospitals in Sichuan Province, Southwest China, using demographic questionnaires, the Stanford Presenteeism Scale (SPS-6), and the Challenge- and Hindrance-Related Self-Reported Stress Scale (C-HSS). A latent profile analysis was conducted on SPS-6 scores using Mplus 8.3, followed by univariate analyses to compare characteristics across subgroups. The total mean score of nurses' presenteeism is (16.13 ± 4.46), with approximately 59.4% classified as having a high level of presenteeism. Four latent profiles of nurses' presenteeism were identified through LPA: low fatigue-low work constraint (19.8%), low fatigue-high work constraint (33.9%), high fatigue-low work constraint (18.8%), and high fatigue-high work constraint (27.5%). Nurses demonstrated moderately severe presenteeism, with LPA revealing four distinct phenotypes characterised by divergent fatigue- work constraint configurations. This heterogeneity underscores the need for stratified interventions addressing unique risk profiles across subgroups. Administrators should adopt targeted interventions according to the characteristics of nurses in different profiles to minimise nurses' loss of productivity. This study addresses the evidence gap regarding the significant heterogeneity of presenteeism among nurses and the lack of precise identification, and identifies four distinct latent profiles of presenteeism. The findings provide critical evidence for nursing managers to design and implement differentiated intervention strategies tailored to groups with different risk characteristics. The study followed the STROBE guideline. This study did not include patient or public involvement in its design, conduct or reporting. Show less
To identify distinct sleep quality profiles among patients undergoing maintenance hemodialysis (MHD) using latent profile analysis (LPA), and examine differences in perceived stigma across these sleep Show more
To identify distinct sleep quality profiles among patients undergoing maintenance hemodialysis (MHD) using latent profile analysis (LPA), and examine differences in perceived stigma across these sleep quality subtypes. From December 2024 to March 2025, a total of 334 MHD patients were recruited via convenience sampling from the nephrology departments of two tertiary hospitals in Xinjiang, China. Data were collected using structured questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), the Self-Rating Depression Scale (SDS), and the Social Impact Scale (SIS), along with sociodemographic and clinical information. LPA was employed to identify latent subgroups of sleep quality based on PSQI components. Multinomial logistic regression was used to determine predictors of sleep profile membership. Differences in stigma scores across sleep profiles were analyzed using non-parametric equivalents. Three distinct sleep profiles were identified: Class 1 - "overall better sleep", Class 2 - "short sleep duration and low efficiency", and Class 3 - "poor sleep quality with high medication use". Multinomial logistic regression identified comorbid heart failure (OR=2.867, Patients with MHD exhibit heterogeneous patterns of sleep disturbance, which are associated with varying levels of perceived stigma. Those with the poorest sleep quality and highest reliance on medication experience the most pronounced stigma. Tailored interventions addressing sleep-related issues and psychosocial factors may help reduce stigma and improve patient well-being. Show less
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
Although light-intensity physical activity (LPA) has been suggested to be associated with a lower risk of mortality, the minimal and optimal volumes of LPA remain unclear. We aimed to examine the mini Show more
Although light-intensity physical activity (LPA) has been suggested to be associated with a lower risk of mortality, the minimal and optimal volumes of LPA remain unclear. We aimed to examine the minimal and optimal volumes of LPA associated with the risks of mortality and disease incidence (i.e., cardiovascular diseases and cancer). Data were derived from the population-based UK Biobank cohort study, including 69,492 adults aged 43-78 years. Accelerometer-measured LPA was defined using a validated, published machine learning-based Random Forest activity method, which was categorized into 4 quartile groups. All-cause and cause-specific mortality (cardiovascular disease- and cancer-specific) were determined according to the International Classification of Diseases, 10th version codes. Disease incidence was defined based on primary care, hospitalization, or death records. During a median follow-up period of 8.04 years, 2024 adults died from all causes, 539 from cardiovascular disease, and 1175 from cancer. For all-cause mortality, compared with participants in the lowest quartile of LPA (<3.9 h/day), the hazard ratios (HRs) and 95% confidence intervals (95%CIs) were 0.82 (95%CI: 0.73‒0.93) for those with 3.9 to <5.0 h/day, 0.75 (95%CI: 0.66‒0.85) for those with 5.0 to <6.1 h/day, and 0.77 (95%CI: 0.68‒0.88) for those with ≥6.1 h/day, respectively. There was an inverse non-linear dose-response association between LPA and all-cause mortality, with an optimal dose of 5.72 h/day (95%CI: 5.45‒6.41; HR = 0.63, 95%CI: 0.56‒0.71) and a minimal dose of 3.59 h/day (95%CI: 3.53-8.56; HR = 0.81, 95%CI: 0.78‒0.86), with the 5th percentile as the reference. Similar patterns were observed for cause-specific mortality and disease incidence (cardiovascular disease and cancer). Engaging in LPA for ∼3.5 h/day was conservatively associated with lower risk of mortality and disease incidence, with further risk reductions observed up to an optimal dose of ∼6.0 h/day. These findings suggest that sufficient LPA offers important health benefits, which can inform the development of future PA guidelines. Show less
This study aimed to explore the potential classification and influencing factors of post-traumatic stress disorder (PTSD) in intensive care unit (ICU) patients receiving mechanical ventilation to prov Show more
This study aimed to explore the potential classification and influencing factors of post-traumatic stress disorder (PTSD) in intensive care unit (ICU) patients receiving mechanical ventilation to provide a theoretical basis for formulating targeted intervention measures. A total of 229 patients on mechanical ventilation who were hospitalized in the intensive care unit of a Class III Grade A hospital in Zunyi from August 2023 to July 2024 were selected as research participants using a purposive sampling method. The General information questionnaire, Eysenck Personality Questionnaire Revised, Short Scale for Chinese (EPQ-RSC), Simplified Coping Style Questionnaire (SCSQ), Perceived Social Support Scale (PSSS), and Hospital Anxiety and Depression Scale (HADS) were used to assess the patients within 7 days after discharge from the ICU. One month after extubation, a cross-sectional survey was conducted using the Impact of Event Scale-Revised (IES-R). Latent profile analysis (LPA) was used to analyze the latent subtypes of PTSD, and univariate analysis and a disordered multivariate logistic regression model were used to evaluate the influencing factors associated with different types of PTSD. A total of 215 valid questionnaires were collected, and the effective recovery rate was 93.89%. The incidence of PTSD was 14.9% (95% CI: 10.12%-19.64%). There were three latent categories of PTSD among the ICU patients on mechanical ventilation: the "low-stress group" (56.8%, PTSD symptoms among mechanically ventilated ICU survivors manifest in three distinct profiles. Our findings strongly recommend early psychological screening, particularly focusing on anxiety and depression levels and patients' educational background. Medical staff should formulate targeted intervention plans based on the characteristics of different patient categories to lower the level of PTSD in patients. Show less
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
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
This study aims to identify and characterize daily activity accumulation patterns (bouts of physical activity and sedentary behavior) among adolescents and then to explore the associations between the Show more
This study aims to identify and characterize daily activity accumulation patterns (bouts of physical activity and sedentary behavior) among adolescents and then to explore the associations between these groups and depressive symptoms. A total of 521 adolescents aged 13-18 years from Wuhan and Changsha, China, were included. Bouts of physical activity (PA) and sedentary behavior (SED) were measured using accelerometers. The Center for Epidemiologic Studies Depression Scale was used to assess participants' depressive symptoms. Latent profile analysis was employed to identify distinct groups based on their activity patterns. Three distinct groups were identified: "Prolonged sitters" ( The synergistic effect of strategies to reduce total SED duration by limiting SED bouts to 30 min or less and increasing light physical activity (LPA) may also be effective in alleviating depressive symptoms in adolescents. Show less
Patients with systemic lupus erythematosus (SLE) frequently experience poor sleep quality. This cross-sectional study aimed to identify distinct sleep disturbance profiles in SLE patients and examine Show more
Patients with systemic lupus erythematosus (SLE) frequently experience poor sleep quality. This cross-sectional study aimed to identify distinct sleep disturbance profiles in SLE patients and examine their associations with demographic, disease-related, and psychosocial factors. A total of 331 patients with SLE were included. Latent profile analysis (LPA) was conducted using the tidyLPA package. Logistic regression models were constructed to assess associations between the identified sleep disturbance clusters and physical and psychological outcomes, based on factors significantly influencing the LPA results. The physical and psychological outcomes were estimated using the Hospital Anxiety and Depression Scale (HADS) and the Fatigue Severity Scale (FSS). Sleep clusters were analyzed through multivariate logistic regression. Three distinct sleep disturbance profiles were identified: Cluster 1 (severe sleep disturbance) (n = 42), Cluster 2 (moderate sleep disturbance) (n = 174), and Cluster 3 (mild sleep disturbance) (n = 115). LPA yielded an entropy value of 0.996 for the three-cluster model. The mean total Pittsburgh Sleep Quality Index (PSQI) score for the SLE samples was 7.59 ± 3.44. Among the various sleep quality domains, sleep latency and subjective sleep quality were the most significantly affected in SLE patients. The analysis revealed that disease duration, severity of fatigue, use of calcium supplements, impaired renal function, anxiety, and depression were all significant factors influencing cluster membership. This study identified three distinct patterns of sleep disturbance among SLE patients. Cluster 1 (severe sleep disturbance) was characterized by prolonged sleep latency despite high sleep efficiency and subjective sleep quality scores. Cluster 2 (moderate sleep disturbance) exhibited longer sleep duration than Cluster 1, while Cluster 3 (mild sleep disturbance) had the lowest scores across all sleep quality domains. These findings suggest that sleep disturbance profiling may facilitate personalized sleep management strategies for patients with SLE. Show less
This study systematically examines the relationship between mindfulness and metacognition among Chinese college students through a person-centered analytical approach. Using latent profile analysis (L Show more
This study systematically examines the relationship between mindfulness and metacognition among Chinese college students through a person-centered analytical approach. Using latent profile analysis (LPA) of Five Facet Mindfulness Questionnaire (FFMQ) responses, we identified four distinct mindfulness profiles: (1) High Observation/Low Non-reactivity, (2) High Awareness/Judging, (3) Moderately Mindful, and (4) Highly Mindful. Gender differences were observed across profiles, with female students more represented in the Highly Mindful group. Hierarchical regression analyses revealed that mindfulness profiles significantly predicted metacognitive ability, with the Highly Mindful group demonstrating superior metacognitive self-regulation and learning strategy application. These findings contribute to the literature by identifying distinct mindfulness subtypes and their differential relationships with metacognition. The results suggest that educational interventions emphasizing non-judgmental present-moment awareness may be particularly effective for fostering students' metacognitive development, while highlighting the importance of considering individual differences in mindfulness training approaches. Show less
Previous studies showed that obstructive sleep apnea (OSA) is associated with dyslipidemia. However, whether micro-arousals during rapid eye movement (REM) and non-rapid eye movement (NREM) sleep inde Show more
Previous studies showed that obstructive sleep apnea (OSA) is associated with dyslipidemia. However, whether micro-arousals during rapid eye movement (REM) and non-rapid eye movement (NREM) sleep independently associated with dyslipidemia were unknown. 4472 participants with OSA-related symptoms were finally included in our cohort. Various sleep variables including micro-arousal index (MAI) were obtained from standard polysomnography (PSG) recordings. Fasting serum lipid levels were assessed at our hospital laboratory. Linear regression models were employed to investigate relationships between micro-arousals in REM and NREM sleep and lipid profile with adjusting for multiple confounding factors. Fully adjusted models demonstrated a significant dose-dependent positive correlation between the MAI during REM sleep (MAI MAI Show less
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether syst Show more
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether systemic inflammation modulates Lp(a)-associated coronary stenosis in chronic coronary syndromes (CCS). A total of 1513 participants undergoing angiography at a tertiary cardiology center in China were included in our retrospective, cross-sectional study. Participants were categorized into normal, mild, and severe groups based on the Gensini Scores, which quantitatively assess stenosis severity. Multinomial logistic models were calculated according to accompanying systemic inflammation concentration. Participants with elevated Lp(a) levels had a high coronary stenosis risk: fully adjusted model odds ratios (ORs) [95% confidence intervals (CIs)] for the mild vs. normal and severe vs. normal groups were 1.47 (1.11-1.96) and 1.68 (1.21-2.33). Notably, the strongest Lp(a)-coronary stenosis associations after multi-variable adjustment persisted only in low inflammation concentration [systemic inflammation response index (SIRI) < 0.64)] [mild vs. normal, OR 2.03, 95% CI 1.17-3.54, Elevated Lp(a) correlates with coronary stenosis only in low inflammation concentration. Considering systemic inflammation in personalized Lp(a)-lowering therapies is more conducive for CCS managements. Show less
Given the heightened risk of complications during pregnancy in women of advanced maternal age (AMA), it is crucial to understand the metabolites in amniotic fluid and umbilical cord blood in this demo Show more
Given the heightened risk of complications during pregnancy in women of advanced maternal age (AMA), it is crucial to understand the metabolites in amniotic fluid and umbilical cord blood in this demographic. METHODS: We analyzed the metabolites in amniotic fluid from 60 women, divided into two groups: the AMA group (aged 35 or above, n = 29), and the control group (aged below 35, n = 31). We then conducted a follow-up analysis on the metabolites of umbilical cord blood from a sample of 19 women (9 from the AMA group, and 10 from the control group). In total, we identified 96 differential metabolites in the amniotic fluid and 146 in the cord blood between the two groups. The significant changes in the metabolites of the amniotic fluid mainly involved sphingolipid metabolism, steroid hormone biosynthesis, and cholesterol metabolism. Conversely, the preliminary significant changes in cord blood metabolites were mainly linked to metabolism of arginine and proline, degradation of valine, leucine, and isoleucine, fatty acid metabolism, alanine, aspartate and glutamate metabolism, and the biosynthesis of unsaturated fatty acids. Further analysis revealed a significant upregulation of lysophosphatidylcholine (LPC), phosphatidylcholine (PC), and taurodeoxycholic acid in the amniotic fluid. In the cord blood, various forms of lysophosphatidic acid (LPA), sphingomyelin (SM), phosphatidylglycerol (PG), LPC, and PC were found preliminarily to be either upregulated or downregulated. Our results preliminarily showed that the metabolites of amniotic fluid and cord blood in AMA women differed significantly from the control group. These findings provide crucial insights for future research to explore the role of metabolomics in adverse pregnancy outcomes in AMA women. Show less
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health issue due to its high prevalence, yet the impact of accelerometer-measured physical activity on clinical outcomes re Show more
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health issue due to its high prevalence, yet the impact of accelerometer-measured physical activity on clinical outcomes remains unclear. This study aims to examine the associations of physical activity with the risk of liver cirrhosis, cancer, cardiovascular disease (CVD) incidence and mortality. 32 681 MASLD participants with accelerometer-derived physical activity data from the UK Biobank were analysed. Physical activity intensity was categorised into light (LPA), moderate (MPA) and vigorous (VPA) intensity. Cox proportional hazard and acceleration failure models were employed to assess associations between physical activity duration and outcomes. During a median follow-up of 7.5-7.9 years, 1883 deaths, 151 liver cirrhosis, 3312 cancers and 6657 CVD events were recorded. Physical activity, regardless of intensity, was consistently associated with a reduced risk of liver cirrhosis, CVD and all-cause mortality. Compared with non-MASLD individuals, our analysis indicates that longer duration of physical activity, specifically >1945 min/week of LPA or >383 min/week of MPA may theoretically eliminate the excess risk of mortality associated with MASLD. Among MASLD individuals, longer physical activity duration, regardless of intensity, was associated with reduced risks of liver cirrhosis and mortality. MPA and VPA were associated with lower CVD risk, while VPA was associated with reduced cancer risk, highlighting the potential benefits of increasing the intensity and duration of physical activity in MASLD management. Show less
Yifei Dou, Ying Li, Meng Zhang · 2025 · Wei sheng yan jiu = Journal of hygiene research · added 2026-04-24
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 p Show more
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 police officers were selected using cluster random sampling in the Inner Mongolia Autonomous Region between September and December 2021. Participants completed a basic information questionnaire and the Pittsburgh sleep quality index(PSQI). Latent profile analysis(LPA) was employed to examine heterogeneity in sleep quality, and multinomial Logistic regression was used to identify associated factors of the latent profiles. The mean age of participants was(43.08±8.98) years. The sample comprised 920 males(79.2%) and 242 females(20.8%), 987(84.9%) were married and 175(15.1%) were single, 644(55.4%) had a high school education or below, and 518(44.6%) had college education or above. By department, 607(52.2%) worked in grassroots police stations, 200(17.2%) were criminal police, and 355(30.6%) served in other units. Significant heterogeneity in sleep quality was identified, revealing four distinct latent classes: good sleep group(n=821, 70.6%), moderate sleep group(n=46, 4.0%), sleep-disordered group(n=249, 21.4%), and medication-assisted sleep group(n=46, 4.0%). Using the good sleepers as the reference group, multinomial Logistic regression indicated that older age was a significant risk factor for belonging to the medication-assisted sleep group(OR=1.348, 95%CI 1.078-1.822). Higher education level was a protective factor against membership in the moderate sleep group(OR=4.101, 95%CI 1.304-12.893). Serving as a grassroots police station officer or criminal police officer was a significant risk factor for membership in both the moderate sleep group(OR = 3.329, 95%CI 1.338-8.284; OR=4.188, 95%CI 1.415-12.396) and sleep-disordered group(OR=1.701, 95%CI 1.196-2.420; OR=1.587, 95%CI 1.073-2.533). Sleep quality among police officers demonstrates significant heterogeneity. Age, police department assignment, and educational level are key associated factors of distinct latent classes of sleep quality. Show less
no PDFDOI: 10.19813/j.cnki.weishengyanjiu.2025.05.015