👤 Jiapeng Hu

Humans and mice display elevated levels of IL-27, an immunosuppressive cytokine shown to increase during neonatal bacterial sepsis and compromise survival. This study explores two hypotheses for regulation of IL-27 expression: 1) decreased DNA methylation in newborns that contributes to increased expression of IL-27 genes; 2) neonatal hormones regulate IL-27 expression through upstream hormone response elements (HREs). Whole genome methyl-seq analysis of neonatal and adult blood-derived macrophages identified differentially methylated regions (DMRs) at steady-state. Quantitative PCR (qPCR) measured expression of IL-27 genes ( The IL-27p28 promoter contained DMRs that were increased in the neonatal cohort. The analysis did not identify DMRs within the EBI3 promoter. Dexamethasone stimulation increased These data suggest glucocorticoid (GC) signaling increases EBI3 expression. This has importance in the context of antenatal GC administration that may increase IL-27 levels. ▪ Elevated expression of IL-27 in early life impairs the host response to invasive bacterial infection in neonates.▪ Understanding the regulatory mechanisms contributing to increased IL-27 during the neonatal period is necessary to reduce susceptibility to infection in this vulnerable population.▪ The methylation status of the IL-27 genes in macrophages from neonatal and adult blood donors does not suggest regulation of differential expression with age.▪ Glucocorticoids are a signal that can induce EBI3 gene expression in a GR-dependent manner.▪ Glucocorticoid therapy for premature infants may increase IL-27 expression and promote enhanced susceptibility to infection. Show less

This study investigated the effects of high-intensity intermittent training (HIIT) Forty male Sprague-Dawley rats were randomly divided into two groups: standard diet (C, n = 10) and high-fat diet (HFD, n = 30). After 8 weeks of HFD feeding, 24 obese rats were further randomised into three subgroups: HFD (H, n = 8), HFD + moderate-intensity training (HMT, n = 8), and HFD + HIIT (HHT, n = 8). The HMT and HHT groups underwent 8 week training interventions (six sessions/week). The HMT protocol included a 10 min warm-up (treadmill speed: 10 m/min), a 40 min moderate-intensity aerobic phase (60%-70% of maximum speed), and a 10 min recovery (10 m/min). The HHT protocol featured 10 min warm-up and recovery phases (10 m/min), with 40 min of alternating treadmill training: 3 min at 50% maximum speed followed by 3 min at 90% maximum speed. No significant differences in body weight were observed between the HHT and HMT groups. HHT rats displayed significantly lower plasma triglyceride levels than H and HMT rats. Compared with HMT, HHT reduced adipose mass and adipocyte size and increased mitochondrial succinate dehydrogenase and cytochrome c oxidase (COX) activities in adipose tissue. However, HHT rats displayed lower COX activity in visceral white adipose tissue than HMT rats. Training upregulated browning-related genes and uncoupling protein 1 (UCP1) in adipose tissue, with stronger effects in HHT than in HMT. Plasma and adipose tissue IL-27 levels, as well as p38 MAPK-PGC-1α signalling pathway activation, were significantly elevated in both training groups, with greater increases in HHT. HIIT promotes adipose tissue browning by activating the IL-27 signalling pathway and ameliorates obesity-associated metabolic disorders more effectively than MAIT, supporting its potential as a therapeutic strategy for obesity. Show less

Interleukin-27 (IL-27) in the pleural fluid has gained significant attention as a diagnostic biomarker for tuberculous pleural effusion (TPE); however, considerable variability exists across available studies. This systematic review and meta-analysis aimed to determine the diagnostic accuracy of IL-27 in identifying TPE. In addition, we also compared the diagnostic accuracy of IL-27 and adenosine deaminase (ADA) with a head-to-head meta-analysis. We searched the PubMed and Web of Science databases to identify diagnostic test accuracy studies evaluating the accuracy of IL-27 for diagnosing TPE. The last search date was September 2025. We extracted data from the eligible studies and constructed a two-by-two table with true positives (TP), false positives (FP), true negatives (FN), and false negatives (FN). The QUADAS-2 tool was used to assess the quality of eligible studies. A bivariate model was applied to pool sensitivity and specificity, and a summary receiver operating characteristic (sROC) curve with the area under the curve (AUC) was generated to estimate the overall diagnostic accuracy of IL-27 and ADA. A Deeks funnel plot asymmetry test was used to evaluate publication bias. Nine studies encompassing ten cohorts were included, involving 1573 patients (429 with TPE and 1144 with non-TPE). The reported AUCs for IL-27 ranged from approximately 0.73 to 0.99 across eligible studies. The pooled sensitivity and specificity were 0.94 (95% CI, 0.83-0.98) and 0.96 (95% CI, 0.89-0.98), respectively. The AUC for sROC was 0.99 (95% CI, 0.97-0.99). The pooled positive likelihood ratio was 21.97 (95% CI, 7.95-60.69), the negative likelihood ratio was 0.07 (95% CI, 0.02-0.18), and the diagnostic odds ratio (DOR) was 329 (95% CI, 72-1506). Significant heterogeneity was observed in both sensitivity (I IL-27 is a promising diagnostic marker for TPE, and its diagnostic accuracy is comparable to that of ADA. IL-27 should be used as a complementary diagnostic marker to ADA for TPE. Show less

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by irreversible cognitive decline and synaptic dysfunction and represents the most prevalent etiology of dementia, accounting for an estimated 60-70% of all clinically diagnosed cases worldwide. The growing focus on microglia-neuron interactions in AD research highlights their diverse, region-specific responses, which are driven by the functional and pathological heterogeneity across different brain regions. Therefore, investigating the interactions between microglia and neurons is of crucial importance. To explore the regional heterogeneity of microglia-neuron crosstalk in AD, we integrated human single-nucleus RNA sequencing data from the prefrontal cortex (PFC), hippocampus (HPC), and occipital lobe (OL) provided by the ssREAD database. Our study delineated four microglial subtypes and uncovered a pseudotime trajectory activation trajectory leading to the disease-associated microglia (DAM) phenotype. The transition along this trajectory is driven and stabilized by a key molecular switch: the coordinated downregulation of inhibitory factors (e.g., LINGO1) and upregulation of immune-effector and antigen-presentation programs, which collectively establish the pro-inflammatory DAM state. Furthermore, we observed that each brain region displayed unique microglia-neuron communication patterns in response to AD pathology. The PFC and OL engage a THY1-ITGAX/ITGB2 signaling axis; the HPC predominantly utilizes the PTPRM pathway. Notably, THY1 dysregulation strongly correlates with pathology in the PFC, HPC, and OL, suggesting that microglia-neuron crosstalk in AD possesses both heterogeneity and commonality. The main contribution of this study is the systematic characterization of region-specific microglia-neuron interactions and the identification of THY1 as a potential mediator that may be targeted therapeutically to modulate microglial function in affected brain regions. Show less

Aortic aneurysm (AA) is a life-threatening vascular disease with high fatality upon rupture. While physical activity (PA) reduces cardiovascular risk, its role in AA prevention remains uncertain, particularly when assessed objectively. We analyzed 93,165 UK Biobank participants (56% women; median age 57 years) with valid 7-day wrist-worn accelerometer data. PA was categorized as light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA). Diagnosed AA was ascertained through linked hospital, death, and primary care records. Cox models estimated hazard ratios (HRs) for AA across quartiles and per-standard deviation (SD) increments, with adjustment for demographic, lifestyle, and cardiometabolic factors. Over a median 7.9-year follow-up, 499 clinically recorded AA cases occurred. Higher accelerometer-measured PA was inversely associated with AA risk. Per-SD increments in total PA, MPA, VPA, and MVPA corresponded to 17%, 22%, 19%, and 23% lower risks, respectively. Compared with the lowest quartile, the highest MVPA quartile had a 44% lower AA risk (HR = 0.56, 95% CI 0.42-0.76). Subtype analyses revealed stronger protective effects for abdominal aortic aneurysm (AAA) than thoracic aortic aneurysm (TAA), while LPA was not significantly associated. These findings demonstrate that higher levels of accelerometer-measured MVPA are robustly associated with a decreased risk of clinically detected AA in a dose-dependent manner. The associations were particularly pronounced for AAA. This study provides objective evidence supporting the potential benefits of MVPA for aortic health. Show less

Lipoprotein(a) [Lp(a)] is a genetically determined lipoprotein implicated in cardiovascular disease, but its role in heart failure (HF) remains uncertain. Observational studies indicate a link between elevated Lp(a) and HF risk, but the dose-response relationship remains unexplored. This meta-analysis aimed to quantify the association between circulating Lp(a) levels and HF incidence. A systematic search of PubMed, Embase, and Web of Science identified prospective cohort studies reporting hazard ratios (HRs) for HF incidence across different Lp(a) levels. A random-effects model was applied to pool effect estimates while accounting for heterogeneity, and restricted cubic splines assessed dose-response relationships. Five prospective cohort studies with 400 631 participants were included. During a mean follow-up duration of 11.0 years, 10 598 (2.6%) patients developed HF. A high Lp(a) level was associated with an increased HF risk (HR: 1.34, 95% CI: 1.14-1.59, p < 0.001), with moderate heterogeneity (I² = 69%). Subgroup analysis showed a stronger association in studies using an Lp(a) cutoff of ≥ 50 mg/dL (HR: 1.68) compared to those with a cutoff of < 50 mg/dL (HR: 1.16, p for subgroup difference < 0.01), which completely explained the heterogeneity. The dose-response analysis revealed a nonlinear association (p for non-linearity = 0.001). HF risk increased nearly linearly below 55 mg/dL, then slowed, and plateaued at 160 mg/dL. Elevated Lp(a) is associated with an increased HF risk in a nonlinear pattern, with risk escalation slowing at higher concentrations. Show less

It remains unclear if Yes-associated protein (YAP) is involved in the protection of melatonin against myocardial ischemia/reperfusion (I/R) injury by regulating mitochondrial fission. In this experiment, an in vivo myocardial I/R injury model was used. Animals were randomly assigned to receive the different interventions: Sham, I/R, 10 mg melatonin, 20 mg melatonin, lysophosphatidic acid (LPA, a YAP agonist), LPA + melatonin, verteporfin (a YAP antagonist) and verteporfin + melatonin. Myocardial infarct size and serum cardiac enzyme levels were measured. Histopathological features, mitochondrial morphology, malondialdehyde (MDA) and superoxide dismutase (SOD) levels, apoptosis, and dynamic-related protein 1 (DRP1) and YAP expressions of the I/R myocardium were also evaluated. We observed that melatonin postconditioning significantly reduced myocardial infarct size, ameliorated histological changes, and decreased oxidative stress and apoptosis in the I/R myocardium. These protective effects were associated with enhanced YAP nuclear translocation, increased p-DRP1 Ser637 expression and decreased p-DRP1 Ser616 expression. Activation of YAP with LPA demonstrated a protective effect against myocardial I/R injury, while inhibition of YAP with verteporfin exacerbated myocardial I/R injury and significantly attenuated the protective effect of melatonin postconditioning against myocardial I/R injury. These findings suggest that melatonin postconditioning confers cardioprotection by activating YAP to preserve mitochondrial ultrastructure and attenuate excessive DRP1-mediated fission. These structural changes may contribute to the observed reduction in myocardial injury. While these findings identify YAP activation as a potential therapeutic target, the limited dose range tested precludes determination of an optimal cardioprotective dose. Further studies defining the full dose-response relationship are still necessary to inform potential clinical translation. Show less

To identify latent self-management profiles in people living with HIV (PLWH) with dyslipidemia and factors associated with profile membership, thereby facilitating targeted clinical intervention. A cross-sectional survey was conducted from December 2024 to June 2025 among 333 PLWH with dyslipidemia at Nanjing Second Hospital. Data were collected via sociodemographic/disease-related questionnaire, the HIV Self-Management Scale (HIVSMS), and the Health Literacy Management Scale (HLMS). Latent profile analysis (LPA) was performed in Mplus 8.3, and multinomial logistic regression was used to examine factors associated with profile membership. Fit indices (entropy = 0.993) supported a three-profile solution: low self-management-low social support-seeking (C1, 42.3%), moderate self-management-stable (C2, 37.8%), and high self-management-emotion regulation dominant (C3, 19.8%). Seeking social support was relatively low across profiles. Compared with C1, C2 membership was significantly associated with higher education and income, lipid-lowering medication use (OR 3.735, 95% CI 1.597-8.736), and CD4 350-500 cells/μL, and was less likely among participants with VL >1000 copies/mL or chronic comorbidities (all P < 0.05). Compared with C1, C3 membership was significantly associated with HIV infection duration ≥5 years, higher education and income, CD4 >500 cells/μL, and higher HDL-C, and was less likely among those with VL >1000 copies/mL (OR 0.037, 95% CI 0.004-0.380) or chronic comorbidities (all P < 0.05). Compared with C2, C3 membership was independently associated with higher health literacy (HL) (OR 1.038 per point, 95% CI 1.012-1.064) and was less likely among those with LDL-C ≥3 mmol/L (P < 0.05). We identified three distinct self-management profiles among PLWH with dyslipidemia. Profile membership was significantly associated with HL and socioeconomic, HIV-related, lipid-related, and comorbidity factors, supporting the need for profile-tailored strategies to improve self-management. Show less

The engagement and burnout profiles of preschool teachers are closely linked to young children's developmental outcomes. This study investigated engagement and burnout profiles among 529 Chinese preschool teachers in relation to their emotional states, varying experiences, and professional backgrounds. The sample predominantly consisted of early-career educators, with 47.8% aged between 21 and 30 years and 33.1% having 0-5 years of work experience. Using a quantitative cross-sectional design and latent profile analysis (LPA), this study identified four distinct profiles: slightly exhausted (48.58%), moderately burned out (18.53%), engaged (25.90%), and highly burned out (6.99%). Positive emotional states, such as enjoyment, were associated with higher work engagement, while anxiety was associated with a higher probability of belonging to burnout profiles. In contrast, perceived career success and negative emotions like anger did not significantly predict work engagement and burnout profiles. Teachers with extensive teaching experience and pre-service early childhood education (ECE) training were more likely to maintain high work engagement. This study highlights the critical role of emotional states and professional ECE training in promoting preschool teachers' work engagement and sustainable practice, particularly among early-career teachers. Show less

To describe the network structure and heterogeneity of symptom burden in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI), and to examine factors associated with different symptom burden profiles to inform risk-stratified management after PCI. A convenience sample of 261 patients with ACS who underwent PCI at a tertiary hospital in Chongqing between November 2024 and August 2025 was recruited. Data were collected using a demographic questionnaire, the Cardiac Symptom Survey, and the Seattle Angina Questionnaire. Network analysis was conducted to identify inter-symptom associations and the structural characteristics of the symptom network. Latent profile analysis (LPA) was performed to classify symptom burden patterns, and multinomial logistic regression analysis was used to explore factors associated with profile membership. Network analysis indicated that depression was the most central symptom (strength Symptom burden in patients with ACS after PCI demonstrates substantial individual heterogeneity. Depression occupies a central position within the symptom network, and BMI is associated with moderate and high symptom burden profiles. These findings suggest that integrating symptom network characteristics and BMI status into post-PCI assessment may facilitate risk-stratified management and targeted psychological and weight-related interventions to improve recovery outcomes. Show less

In recent years, the global incidence of Non-Suicidal Self-Injury (NSSI) has risen, posing a significant challenge in public health. Adolescents are the main group affected. A cross-sectional study was conducted using a self-administered questionnaire to collect data from 6,311 adolescents in Hefei, China. This study employed the Compositional Isotemporal Substitution Model (CISM, a statistical method that estimates health effects of replacing time in one behavior with another while accounting for the interdependent, compositional nature of 24-h time-use data) to examine the impact of Screen Time (ST), Non-Screen-based Sedentary Time (NSST), Physical Activity, and Sleep Time on NSSI among adolescents. Compositional logistic regression analysis revealed that, relative to the remaining behavioral components, higher Light Physical Activity (LPA) ( The findings highlight those reasonably allocating adolescents' daily activities, reducing ST, can help lower the risk of NSSI among adolescents. Show less

Older adults increasingly rely on digital health resources, yet evidence regarding the relationship between eHealth literacy (eHL) and 24-hour movement behaviors (24-HMB), including physical activity (PA), sedentary behavior (SB), and sleep, remains underexplored. This study examined the associations between eHL and 24-HMB in Chinese older adults and examined self-efficacy as a potential mediator and moderator. Using a convenience sampling approach, 564 community-dwelling older adults (aged 60-74 years) were recruited from four urban Chinese cities via an online survey. A total of 553 valid cases were retained for analyses. eHL was assessed using the eHealth Literacy Scale-Web 3.0, and self-efficacy was assessed using a validated Self-Efficacy Scale. PA and SB were assessed objectively using ActiGraph GT3X+ accelerometers over three consecutive days (two weekdays and one weekend day). Sleep duration was derived from accelerometer-based estimates anchored by daily sleep logs. Multiple linear regression analyses were conducted to examine associations, and mediation and moderation were tested using PROCESS macro (Model 4 and Model 1, respectively), adjusting for age, sex, and education. After adjustment for covariates ( In this cross-sectional, urban, device-using sample of older adults, higher eHL was associated with a more favorable 24-HMB profile, particularly higher LPA and lower SB, while associations with sleep duration were weaker. Self-efficacy showed modest indirect associations consistent with partial mediation for PA and SB and also acted as a moderator of several associations. Given the observational design and modest effect sizes, findings should be interpreted cautiously and require confirmation in longitudinal or experimental studies with more representative sampling and improved sleep assessment. Show less

To identify latent profiles of proactive health behaviors in patients with hypertension, examine the category-specific influencing factors. Proactive health behavior, as an emerging concept, refers to a self-motivated approach to systematically managing health-related factors in order to actively maintain and promote one's health status. However, existing studies have largely focused on describing the overall level of such behaviors among patients with hypertension, with insufficient exploration of behavioral heterogeneity within this population. Moreover, there has been a lack of systematic integration of established behavioral theories to explain the multifactorial mechanisms underlying different behavioral patterns, which limits the development of precise nursing interventions. A cross-sectional study was performed, involving 352 patients with hypertension from 8 communities in Anhui Province from September to December 2025. The survey tools included self-designed demographic and clinical instrument, the Proactive Health Behavior Scale for Hypertensive Patients, the Self-Efficacy Scale for Hypertensive Patients, the Health Literacy Management Scale (HeLMS). Latent profile analysis (LPA) was used to identify subtypes of proactive health behavior among hypertension patients. Multinomial logistic regression analysis was applied to determine the factors associated with the identified subtypes. A total of 352 questionnaires were distributed, yielding 321 valid responses (a response rate of 91.2%). The total score of proactive health behavior was 89.57 ± 22.99 points. The LPA revealed four profiles of proactive health behavior: the positive proactive health behavior profile (Class 1, The proactive health behavior among hypertension patients was at a moderate level, revealing four distinct behavioral categories with significant differences. Guided by the Health Belief Model, profile-specific influencing factors were analyzed, which informed the development of tailored intervention strategies. Show less

Studies of surrogate decision-makers (SDMs) in the intensive care unit (ICU) often report high average levels of family decision-making self-efficacy (FDMSE). However, these findings contrast with the significant decision conflict commonly observed in clinical practice. This discrepancy suggests that high aggregate FDMSE scores may mask underlying subgroups with distinct experiences. Identifying these latent profiles is essential for understanding the true experiences of ICU SDMs. This study aimed to identify distinct latent profiles of FDMSE among ICU SDMs and explore key influencing factors. A cross-sectional study was conducted among SDMs of ICU patients. Exploratory and confirmatory factor analysis (EFA/CFA) was performed to examine the factor structure of the Chinese FDMSE scale. The verified factor structure was then used for latent profile analysis (LPA). Lastly, univariate and multivariate analyses were performed to identify the main influencing factors. A total of 350 ICU SDMs were included in the analysis. The three-factor model, including treatment decision-making, comfort promotion decision-making, and facing death decision-making, provided a good fit for the Chinese FDMSE scale. Two profiles emerged: 'weak family decision-making self-efficacy', accounting for 55.9% of cases, and 'strong family decision-making self-efficacy', represented by the remaining 44.1%. The 'strong family decision-making self-efficacy' group was more likely to be observed in families where the patients held religious beliefs and were diagnosed with cancer, and where the family decision-makers held religious beliefs, had higher incomes, and had engaged in prior discussions about treatment preferences. This study verified the multi-dimensionality and heterogeneity of the FDMSE of ICU SDMs through EFA, CFA and LPA. The identification of a subgroup with low FDMSE differs from previous studies. Key modifiable factors include socio-economic resources, prior communication of the patients' preferences, and spiritual and cultural background, which serve as crucial levers for strengthening the decision-support framework in critical care settings. By identifying two distinct FDMSE profiles and key influencing factors, it offers critical care nurses a new perspective to design targeted interventions, thereby enhancing their ability to provide personalised decision support. Critical care nurses should receive structured end-of-life communication training to address the shared vulnerability of ICU SDMs in facing death decision-making self-efficacy across both profiles. Show less

Lipoprotein(a) [Lp(a)] promotes atherosclerotic plaque vulnerability through pro-inflammatory and thrombogenic pathways, while the CatLet© angiographic score quantifies coronary lesion complexity. We hypothesized that their integration would improve prognostication in acute myocardial infarction (AMI) after emergency percutaneous coronary intervention (ePCI). In this retrospective cohort, 307 AMI patients undergoing successful ePCI (2020-2022) were stratified by 1-year major adverse cardiovascular/cerebrovascular events (MACCE). Serum Lp(a) and troponin I were measured post-admission. CatLet© and Gensini scores were assessed by blinded analysts. Multivariable logistic regression and ROC analyses evaluated predictive performance. MACCE patients (n = 78) exhibited higher Lp(a) (135.99 ± 33.07vs. 123.35 ± 42.70nmol/L, P = 0.0178) and CatLet© scores (33.58 ± 9.04vs. 30.80 ± 8.24, P = 0.0012) versus controls. Lp(a) (OR=2.339,95%CI:1.519-3.603, P <  0.001) and CatLet© score (OR=1.092, 95%CI:1.027-1.161, P = 0.005) independently predicted MACCE. The combined model Lp(a)≥70.70 nmol/L + CatLet© ≥ 18.6) significantly outperformed individual markers (AUC 0.862 [95%CI:0.83-0.96] vs. 0.780/0.833; DeLong's test confirmed the superiority of the combined model over individual predictors (P = 0.0089, Z = 2.64 vs. Lp(a); P = 0.034, Z = 2.12 vs. CatLet© score), with 88% sensitivity and 83% specificity. The Lp(a)-CatLet© synergy enhances MACCE risk stratification in ePCI-treated AMI, reflecting complementary pathobiological (Lp(a)-driven plaque vulnerability) and anatomical (CatLet©-quantified complexity) pathways. This dual-parameter approach could support post-PCI risk stratification and follow-up planning. Show less

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

Data are limited regarding national clinician awareness, testing, and treatment of lipoprotein(a) [Lp(a)]. We conducted a national survey of US clinicians to investigate these issues. An internet-based survey of awareness, testing and treatment of Lp(a) was administered by a medical survey company to clinicians who have been in practice ≥5 years in the US or its territories. 2002 clinicians completed the survey: 47 % were primary care, 35 % cardiology, 9 % endocrinology, and 9 % neurology. 28 % were female, 24 % Asian, 4 % Hispanic, and 3 % Black. Most clinicians agree knowing the Lp(a) level can improve risk assessment and patient engagement. Patients with premature or recurrent CVD events are most likely to be targeted for Lp(a) testing and for prescribing possible future Lp(a)-targeted therapies. Show less

Massive open online courses (MOOCs) have transformed global education, yet their long-term effectiveness and evolving learner engagement remain underexplored. This study aims to comprehensively evaluate a nursing MOOC over six years, examining learner engagement, identifying distinct learner profiles, and assessing changes across different developmental stages to inform future MOOC design. A retrospective study was conducted on 4171 completers of the Medical Nursing MOOC on a Chinese MOOC platform, covering eleven semesters from 2018 to 2023. Latent profile analysis (LPA) categorized learners based on unit test scores, and profile distributions were compared across the MOOC's developmental stages. The Medical Nursing MOOC attracted 69,642 registrants with a 5.99% completion rate. Among the 4171 individuals who completed the course, latent profile analysis identified six distinct learner types, demonstrating significant differences in overall learning effect (H = 2823.604, P < 0.001). The chi-squared analysis revealed significant differences between the proportions of the six profiles regarding MOOC developmental stages (χ Findings highlight the evolving role of MOOCs in nursing education. Despite challenges in long-term engagement, the increasing proportion of highly engaged learners and declining dropout rates indicate growing effectiveness and sustainability. These insights provide evidence-based guidance for optimizing MOOC design and implementation. Show less

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

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

l-Pipecolic acid (l-PA) and its hydroxylated derivatives (hydroxypipecolic acids, HPAs) are non-proteinogenic amino acids that serve as valuable chiral building blocks for pharmaceuticals, antibiotics, and natural products. Conventional chemical synthesis of these compounds often suffers from operational complexity, poor environmental compatibility, and insufficient stereochemical control, driving a shift toward biosynthetic approaches. This review covers recent advances in enzyme engineering and synthetic biology aimed at enabling sustainable and efficient production of l-PA and HPAs. For l-PA biosynthesis, various metabolic engineering strategies to enhance its production in microbes are introduced, and enzyme cascades, single enzyme strategy, and immobilized enzyme strategy involved in l-PA production are discussed. Regarding HPAs biosynthesis, which involves the regioselective hydroxylation of l-PA, their structural features, catalytic mechanisms, and recent progress in the biosynthesis of diverse HPAs, the protein engineering of proline hydroxylase is emphasized. Finally, we present future perspectives to accelerate the biosynthetic production of l-PA and HPAs. Show less

The pervasive nature of social media has given rise to the phenomenon of fear of missing out (FoMO), which poses significant challenges to the mental health of children. By drawing on an individual-centered approach, this study aims to provide a nuanced understanding of FoMO. We delved into the evolving nature of FoMO patterns among 541 Chinese primary school students within a one-year interval. Employing Latent Profile Analysis (LPA) and Random Intercept Latent Transition Analysis (RI-LTA), we uncovered three distinctive profiles of FoMO: Social Sentinels, Worry Warriors and Untroubled Buddies. To predict transitions between these profiles, we examined anxiety and mindfulness. We also investigated the relationship between two related outcomes and latent transitions. The results revealed that the Untroubled Buddies profile was relatively stable, while the Social Sentinels and Worry Warriors profiles showed more frequent transitions over time. Regarding the antecedents, our findings demonstrated that primary school students with high anxiety were more likely to be categorized under the Social Sentinels and Worry Warriors profiles, increasing their risk of transitioning from the Untroubled Buddies profile to the other two profiles over time. Regarding the associations with outcomes, significant differences emerged among the three profiles in terms of emotional and behavioral problems as well as depression at three measurement points. Identifying different FoMO profiles among primary school students and understanding the nature of transitions between these profiles have implications for developing targeted interventions to mitigate FoMO risks among primary school students, as well as preventing individuals from transitioning into profiles associated with higher risks of emotional and behavioral problems and depression. 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, 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

Previous research has suggested that high levels of internet use are associated with lower levels of physical activity. However, recent studies have yielded mixed findings. First, we aim to explore the prevalence of internet addiction and sedentary behavior among college students. Second, we examine the relationship between sedentary behavior and body composition. Additionally, we employ latent profile analysis (LPA) to identify subgroups of internet addiction profiles and to explore the associations between these latent profiles and sedentary behavior. This cross-sectional study examined the relationship between sedentary behavior, internet addiction, and body composition among 369 Chinese college students. Sedentary behavior was assessed via self-reported sitting time, internet addiction was measured using a standardized questionnaire, and body composition was evaluated with the InBody 120 device. LPA, an individual-centered method, was used to identify homogeneous subgroups of internet addiction. 42.3 % of students exhibited internet addiction and 72.6 % reported ≥6 h of daily sitting. LPA revealed two distinct profiles of internet addiction-"Regular" (57.2 %) and "Internet addiction" (42.8 %)-highlighting its heterogeneous nature. The findings suggest that age (p = 0.296), gender (p = 0.304), and sedentary time (p = 0.954) may not be the primary factors contributing to these profiles. Policymakers and campus health programs should tailor interventions to distinct internet addiction subgroups. Further research is needed to examine psychological, behavioral, and social contributors, as well as long-term effects. Show less

Accelerometer-derived physical activity is associated with reduced stroke risk. The biological pathways underpinning this relationship, however, are not yet understood. Herein, we aim to identify metabolic signatures associated with accelerometer-measured PA and investigate their relationships with reduced stroke incidence. Utilizing UK Biobank accelerometer data, we derived physical activity into total physical activity (TPA), moderate-to-vigorous physical activity (MVPA), and light physical activity (LPA) and linked them to 249 NMR-quantified plasma metabolites. The metabolomic signatures (TPA-/MVPA-/LPA-metabolomic signatures) were developed through internal validation followed by elastic-net regression modeling. Cox proportional hazards models evaluated activity-stroke associations (adjusted for sociodemographic/genetic factors), followed by mediation analysis to quantify metabolomic signature effects. Through UK Biobank study (N = 29445; 14.1-year follow-up with 513 stroke events), we identified 195 TPA, 173 MVPA, and 164 LPA metabolite associations (FDR < 0.05), with 107, 92, and 15 validated, respectively. Elastic net-derived physical activity-metabolomic signatures (TPA-/MVPA-metabolomic signatures) correlated with physical activity intensities (r = 0.20-0.30, P < 0.001) and were associated with reduced stroke risk: TPA-metabolomic signatures (HR = 0.61, 95% CI: 0.44-0.87); MVPA-metabolomic signatures (HR = 0.50, 95%CI: 0.29-0.88). Mediation analyses showed TPA-metabolomic signatures and MVPA-metabolomic signatures explained 12.2% and 8.5% of physical activity-stroke associations (P < 0.001), implicating specific lipoprotein subclasses and lipids as key mediators. TPA-metabolomic signatures and MVPA-metabolomic signatures, particularly the 11 key metabolites included, significantly mediate the association between accelerometer-derived physical activity and stroke risk. 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 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

Physical activity (PA) and sedentary behavior (SB) are associated with many diseases, including Alzheimer's disease and all-cause dementia. However, the specific biological mechanisms through which PA protects against disease are not entirely understood. This study aims to address this gap, with a specific focus on all-cause dementia. We first assessed the conventional observational associations of three self-reported and three device-based PA/SB measures with circulating levels of 2,911 plasma proteins measured in the UK Biobank (n max =39,160) and assessed functional enrichment of identified proteins. We then used bi-directional Mendelian randomization (MR) to further evaluate the evidence for causal relationships of PA/SB with protein levels. Finally, we performed mediation analyses to identify proteins that may mediate the relationship of PA with incident all-cause dementia. Our findings revealed 41 proteins consistently associated with all PA measures and 1,027 proteins associated with at least one PA measure. Both conventional observational and MR study designs converged on proteins that appear to increase as a result of PA, including integrins such as ITGAV and ITGAM, as well as MXRA8, CLEC4A, CLEC4M, LPL, and ADGRG2; on proteins that appear to decrease as a result of PA such as LEP, INHBC, CLMP, PTGDS, ADM, OGN, and PI3; and on proteins that are more responsive to high-intensity PA, such as CA14, CA6, CA4, KIT, and ANGPT2. Functional enrichment analyses revealed processes such as cell-matrix adhesion, integrin-mediated signaling, and collagen binding. Finally, GDF15, ITGAV, ITGAM, ITGA11, HPGDS, GFAP, ADM, AHNAK, and DPP4 were among 21 unique proteins found to mediate the relationship of PA with all-cause dementia, implicating processes such as synaptic plasticity, neurogenesis, and inflammation. Our results provide insights into how PA affects biological processes and protects against dementia, and provide avenues for future research into the health-promoting effects of PA. Show less

Obesity has become a global epidemic and a major contributor to the development of Type 2 diabetes (T2D) through the promotion of insulin resistance. Emerging evidence has shown that GPX4 expression is reduced in macrophages under hyperglycemic conditions; however, the involvement of macrophage-specific GPX4 in obesity-associated insulin resistance remains unclear. We generated macrophage-specific Gpx4 knockout (Gpx4 Show less

In this study, we used optical genome mapping (OGM), conventional karyotyping, and next-generation sequencing to analyze cytogenomic alterations in 91 cases of T-cell acute lymphoblastic leukemia/lymphoma (T-ALL). Whereas karyotyping detected abnormal karyotypes in 55% of cases, OGM identified cytogenetic abnormalities in 97.8% of the cases and provided clinically relevant information beyond karyotyping in ∼70% of cases. OGM detected gene rearrangements in 80% of cases, including 24 recurrent gene fusions and 21 previously unreported putative gene fusions in T-ALL. Copy number variants were detected in 93% of cases, with interstitial deletions the most common. Gene mutations were detected in 93% of cases, with NOTCH1 being most frequent (in 57% of cases). Combining all data, most T-ALL cases harbored 3 or more cytogenomic aberrations. Specific cytogenomic alterations differed among T-ALL subtypes as follows: rearrangements of BCL11B and PICALM::MLLT10, deletions of 7p, and mutations involving DNMT3A, WT1, TET2, IDH2, and FLT3 were common in early T-precursor and near-early T-precursor subtypes. Rearrangements of TLX1, KMT2A, STIL::TAL1, and NUP214::ABL1, deletions of 9p, and FBXW7 mutations were frequently associated with the cortical subtype. We conclude that integration of OGM and next-generation sequencing with karyotyping enables comprehensive cytogenomic profiling of T-ALL that improves detection of clinically relevant genomic alterations and may inform disease classification and future studies of risk stratification. Show less