👤 Guoqing Zhao

Child maltreatment measurement has been a longstanding issue, with discrepancies across administrative records, parent-reports, and self-reports. One proposed solution is "triangulation," or integrating data from multiple reporters and sources. However, it remains unclear how best to operationalize this concept. This study examines the concept of "triangulation" by employing different analytic methods to determine whether these methods reveal a common underlying construct of physical abuse and whether they predict adult depression. Data come from the Lehigh Longitudinal Study, a 40+ year prospective study that began in the 1970s with children ages 18 months to 6 years of age. Data were collected in early childhood, middle childhood, adolescence, and adulthood (ages 36 and 46, on average). We applied five analytic approaches - network analysis, ordinary least squares (OLS) regression, structural equation modeling (SEM), latent profile analysis (LPA), and a cumulative index regression - to assess the relationships among multiple reporters of childhood physical abuse and adult depression. SEM best modeled the latent construct of physical abuse and significantly predicted adult depression, with adult self-reports playing a particularly strong role. Network analysis also highlighted strong intercorrelations among self-reports and meaningful links with depression. SEM and network analysis were the most informative for triangulation and prediction of adult depression. Adult self-reports of abuse were most related and most predictive of adult depression. Show less

This study used a group-based multi-trajectory model (GBMTM) to identify distinct muscle health trajectories and examine their associations with physical activity (PA) in middle-aged and older adults. Data were obtained from 2818 middle-aged and older adults (aged ≥40 years) in the China Health and Retirement Longitudinal Study (2011-2015). Muscle health was assessed using muscle mass (appendicular skeletal muscle mass index), muscle strength (handgrip strength), and physical performance (5-time chair stand test). PA was assessed using the International Physical Activity Questionnaire Short Form. A GBMTM was applied to jointly identify longitudinal trajectories of muscle mass, muscle strength, and physical performance, and to evaluate their associations with PA. In this study, four muscle health trajectories were identified: low-function declining, moderate-function declining, moderate-function stable, and high-function stable group. Engaging in ≥150 min/wk of light PA (LPA), moderate PA (MPA), or vigorous PA (VPA) was associated with the moderate-function stable group (LPA: aOR = 3.44, 95% CI: 1.94 - 6.11; MPA: aOR = 2.83, 95% CI: 1.67 - 4.96; VPA: aOR = 2.88, 95% CI: 1.61 - 5.13) and the high-function stable group (LPA: aOR = 5.20, 95% CI: 2.44 - 11.19; MPA: aOR = 4.10, 95% CI: 1.92 - 8.73; VPA: aOR = 3.42, 95% CI: 1.55 - 8.55). In older adults aged ≥70 years, associations persisted for MPA and VPA. Distinct muscle health trajectories highlight individualized muscle aging and inform personalized PA guidance. Regular PA ≥150 min/wk across intensities was associated with more favorable longitudinal muscle health. Show less

To investigate the association between vaginal microbiota structure in early pregnancy and gestational diabetes mellitus (GDM) and to characterize microbial signatures for early screening for GDM. The present study was a nested case-control study recruiting pregnant women from the Nanjing Gulou Maternal-Child Health Center, China. Vaginal swabs were collected before 20 weeks of gestation for 16S rRNA sequencing. Following 1:3 propensity score matching, 45 GDM cases and 135 controls were enrolled. The final analysis included 42 GDM cases and 121 controls. A random forest model was used to explore the genera of vaginal differential microbiota associated with GDM. Based on these findings, latent profile analysis (LPA) was conducted to explore potential types of vaginal microbiota, and logistic regression was used to analyze the association between vaginal microbiota types and GDM. The GDM group exhibited elevated alpha diversity (Chao1 index, The composition and structure of vaginal microbiota in early pregnancy are different in the two groups. The vaginal microbiota in early pregnancy, which is characterized by co-dominated by The online version contains supplementary material available at 10.1186/s12866-026-04910-2. Show less

Carboxymethylcellulose (CMC), a common food emulsifier, induces microbiota dysbiosis and systemic inflammation; however, its impact on transplant immunity remains unclear. Allogenic heart rejection was observed in CMC-fed recipient mice, with increased abundance of lysophosphatidic acid (LPA)-producing bacteria and increased serum LPA concentration. CMC-induced transplant rejection was caused by the gut microbiota, as confirmed by fecal microbiota transplantation and gut microbiota depletion. Furthermore, LPA-treated macrophages demonstrated a proinflammatory ability to accelerate allograft rejection in cytotoxic T lymphocyte-associated protein 4 immunoglobulin-induced allograft survival by upregulating glycolysis. Conversely, the administration of a glycolysis inhibitor resulted in allograft survival and abrogated the detrimental effect of LPA. Mass spectrometry and single-cell RNA sequencing confirmed that transplant patients with rejection showed significantly elevated serum LPA levels and LPA receptor 6 (LPAR6) expression in graft-infiltrate macrophages. Mechanistically, LPA preferentially promoted LPAR6 expression, which interacted with Rho-associated protein kinase 2 to activate the mammalian target of rapamycin/hypoxia-inducible factor 1-alpha pathway, thereby enhancing glycolysis and inducing proinflammatory macrophage polarization. Treatment with Ki16425, an LPAR antagonist, prolonged allograft survival in CMC-fed recipients. Our findings reveal a major detrimental effect of CMC on macrophage physiology and suggest that controlling LPAR6 expression or glycolysis in macrophages may improve allograft survival in transplant recipients. Show less

Identifying high-performing advanced practice nursing roles and understanding the factors that contribute to their effectiveness are critical for advancing professional development, optimizing workforce deployment, and ensuring long-term sustainability in nursing. This study aimed to (1) identify distinct latent profiles of advanced practice nursing among specialist nurses in mainland China, (2) quantitatively examine the individual and contextual factors associated with high performance, as characterized by these profiles, and (3) qualitatively confirm the significant factors using explanatory semistructured interviews in the high-performance groups. A mixed-methods sequential explanatory design was used, in which quantitative data were collected first and subsequently explained through qualitative interviews. Certified specialist nurses from 16 hospitals across urban and rural areas of Shanghai were included. Latent profile analysis (LPA) was conducted using the five domains from the Advanced Practice Role Delineation tool as manifest indicators to classify nurses into distinct performance profiles. Multinomial logistic regression was used to examine potential determinants (e.g., job position) of group membership. Additionally, a backpropagation neural network (BPNN) was developed to rank the importance of contributing factors. Specialist nurses identified as high performers in the quantitative phase were purposively sampled for explanatory semistructured qualitative interviews. Three latent profiles emerged: high performance (26.1%), moderate performance (46.3%), and low performance (27.6%). Compared to APNs, staff nurses had significantly lower odds of belonging to the high-performance group ( Identifying the profiles of advanced practice nursing roles provides valuable insights for optimizing APN performance and informing targeted management and policy strategies. High-performing specialist nurses are positioned at the nexus of individual capability, interdisciplinary collaboration, and institutional support. 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

As sports socializing is becoming a dominant lifestyle that integrates physical health with social interaction in China, understanding the underlying drivers of participation is crucial. However, traditional research predominantly relies on a “variable-centered” paradigm, which assumes population homogeneity and focuses on linear relationships between single motives and behaviors. This approach often fails to capture the complexity of how multiple motivations are configured within individuals (heterogeneity), and how these internal configurations are associated with external behavioral choices. To address this gap, this study employed a novel hybrid methodological framework combining Latent Profile Analysis (LPA) and Random Forest (RF) modeling. Based on data from 1,104 adults, LPA was first used to identify distinct motivational subgroups. Subsequently, RF algorithms, utilizing feature importance ranking and “One-vs-Rest” strategies, were applied to identify the associative patterns between these motivational profiles and key behavioral indicators, including sports types, media usage, and economic investment. The analysis identified four distinct motivational profiles: (1) Psychologically Introverted (3.6%), prioritizing internal psychological rewards over social status; (2) Physiologically Oriented (44.1%), the largest group, driven primarily by physical health needs; (3) Balanced (39.0%), exhibiting moderate levels across all motivational dimensions; and (4) High-Motivation/Comprehensively Oriented (13.3%), showing high intensity in both internal and external rewards. The RF model achieved a training accuracy of 99.9% and identified that Sports Type (specifically large-ball games), Media Channels (particularly Douyin/Rednote), and Annual Spending were the top three salient behavioral markers distinguishing these profiles. Notably, the High-Motivation group was characterized by heavy reliance on visual social media for social display. Participation in sports socializing among Chinese residents is not characterized by a singular, homogeneous motivation but features a clear internal stratification structure. The specific pattern of motivational combinations (i.e., the type) systematically maps onto external behavioral choices, where the sociocultural attributes of the sport and the media characteristics of digital social platforms constitute the key predictive markers of behavioral differentiation. The establishment of this “Motivation Type—Behavioral Signal” integrated framework promotes a theoretical shift in the sports socializing research paradigm from “homogeneity” to “heterogeneity” and deepens the understanding of the complex manifestations of Self-Determination Theory and Social Capital Theory in a sports context. It also provides precise user profiles and behavioral insights for sports social platforms, commercial clubs, and public sports service departments. Exploring service customization and policy adjustments based on different motivation-behavior patterns could potentially enhance user engagement and satisfaction, suggesting a possible direction for the development of the sports socializing industry. The online version contains supplementary material available at 10.1186/s12889-026-26780-z. Show less

Serum lipoprotein(a) [Lp(a)] is recognized as an independent risk factor for cardiovascular disease. However, whether hypertension modifies the association between Lp(a) and adverse outcomes in acute decompensated heart failure (ADHF) remains unclear. We investigated how hypertension status influences the relationship between Lp(a) and all-cause mortality in ADHF. We conducted a single-center retrospective observational study including 2610 patients hospitalized with ADHF. We normalized the distribution of Lp(a) by a logarithmic transformation and assessed the risk of all-cause mortality with Lp(a), using Cox regression with adjustment for potential confounders. Among 2610 patients (39.0% women; mean age, 68.8 years), 1606 (61.5%) had hypertension. Over 4.1 years (median), 1287 deaths occurred. In all patients, log-transformed Lp(a) was significantly associated with mortality (adjusted HR 1.21; 95% CI, 1.05-1.39; Increased admission Lp(a) levels were associated with a higher risk of all-cause mortality in ADHF patients with hypertension. Further studies are needed to explore the mechanistic links among Lp(a), hypertension and ADHF. Show less

Observational studies have yielded conflicting evidence regarding the interdependence between lipoprotein(a) [Lp(a)]-related cardiovascular risk and systemic inflammation. It remains unclear whether combined targeting of Lp(a) and inflammation provides additive cardiovascular benefits. This study aimed to investigate the associations between genetically predicted lower Lp(a) and cardiovascular disease (CVD) across interleukin-6 (IL-6) signalling levels and the combined effects of lower Lp(a) and IL-6 signalling activity on CVD risk. This study included UK Biobank participants of European ancestry. Genetic scores for LPA and IL-6 receptor (IL6R)-mediated signalling were calculated to mimic the effects of therapies targeting Lp(a) and IL-6 signalling, respectively. We investigated the associations of separate and combined exposure to lower Lp(a) and IL-6 signalling with coronary heart disease (CHD), ischaemic stroke (IS), heart failure (HF), atrial fibrillation (AF), peripheral artery disease (PAD), and aortic aneurysm (AA), using Mendelian randomization analyses and validating the findings in observational analyses. This study included 408 687 UK Biobank individuals (mean age, 57 years; 54% women). Genetically predicted lower Lp(a) was associated with reduced risks of CHD [odds ratio (OR) per 50 mg/dL reduction in Lp(a) levels, 0.68; 95% confidence interval (CI), 0.65-0.71], IS (0.89, 0.80-0.98), PAD (0.68, 0.62-0.76), HF (0.82, 0.77-0.88), and AA (0.71, 0.61-0.82). Genetically lower IL-6 signalling was associated with lower risks of CHD (OR per 0.5 log[mg/L] reduction in log-transformed C-reactive protein levels, 0.67; 95% CI, 0.55-0.82), AF (0.72, 0.55-0.94), and AA (0.43, 0.23-0.83). The genetic association between Lp(a) and CVD was consistent among individuals with different IL-6 signalling activity (P for difference > 0.05). Combined exposure to genetically predicted lower Lp(a) and IL-6 signalling was associated with an additive decrease in CHD risk (lower Lp(a): 0.67, 0.63-0.71; lower IL-6 signalling: 0.61, 0.46-0.80; combined: 0.25, 0.21-0.30; P for interaction = 0.144). In observational analyses, IL-6 levels below the median and Lp(a) concentrations below 50 mg/dL were also independently and additively associated with lower CHD risk (Lp(a) < 50 mg/dL: hazard ratio, 0.82; 95% CI, 0.72-0.93; IL-6 < median: 0.79, 0.65-0.96; combined: 0.65, 0.56-0.74; P for interaction = 0.102). Lower Lp(a) levels were associated with a reduced risk of CVD, independent of IL-6 signalling activity. Combined exposure to genetic variants lowering Lp(a) and downregulating IL-6 signalling was associated with an additive reduction in cardiovascular risk. These findings indicate that concurrent Lp(a)-lowering and anti-inflammatory therapies may reduce residual cardiovascular risk through additive effects. Show less

Capacities for giving compassion to others, being open to others' compassion, and self-compassion are not always balanced for everyone. Identifying unique compassion profiles provides a holistic understanding of how the balance or imbalance among different facets of compassion relates to psychopathology and well-being. Using latent profile analysis (LPA) with U.S. college students ( Show less

Occupational stress in nursing is a critical issue that can have significant implications for both workforce stability and personal health. This study aimed to identify subgroups of occupational stress among Chinese female clinical nurses using latent profile analysis, compare sociodemographic differences across these subgroups, and examine their associations with premenstrual syndrome (PMS). A cross-sectional study was conducted among female nurses in tertiary hospitals in Huai'an City, Jiangsu Province, China, from November to December 2023. We recruited participants via convenience sampling, and 400 valid questionnaires were collected. Data were collected using a researcher-developed general information questionnaire, the standardized Chinese Nurses Stressor Scale (35 items), and the Premenstrual Syndrome Scale. Latent profile analysis (LPA) was performed with Mplus 8.0 to identify occupational stress subtypes. Sociodemographic predictors of these subtypes were explored using chi-square tests and multivariate logistic regression in SPSS 25.0. The association between stress subtypes and PMS symptoms was assessed using ANOVA. A Three clinical female nurse occupational stress subtypes were identified: overall low-stress (38.3%, This study identified significant heterogeneity in occupational stress among clinical female nurses, categorized into three distinct subtypes differing in stress levels and demographic characteristics. These findings highlight the importance of considering individual differences when developing interventions to address occupational stress. The study advocates for the implementation of intervention strategies targeting different types of stress in nursing education and organizational reform to better support nurses in fulfilling their responsibilities. Show less

This study aimed to identify latent classes of adherence for serum phosphorus control and their influencing factors among patients receiving Peritoneal Dialysis with hyperphosphatemia. This cross-sectional study using convenience sampling was conducted among patients receiving peritoneal dialysis with hyperphosphatemia between December 2024 and May 2025. Participants were assessed using the Phosphate Control Adherence Scale, Self-Efficacy Scale, and Family Care and Social Support Scale. Demographic and clinical data were also collected. Latent profile analysis (LPA) was used to identify adherence subgroups. Univariate analysis and multicollinearity diagnostics were performed, followed by binary logistic regression to determine predictors of adherence. Blood phosphorus control adherence can be classified into two categories: the low-level medical adherence group, characterized by poor dietary self-control (19.93%), and the high-level medical adherence group, marked by effective medication adherence (80.07%). The results indicated that residence conditions, types of medication, and self-efficacy significantly influenced blood phosphorus control adherence among patients with various forms of PD hyperphosphatemia (all p < 0.05). Patients with hyperphosphatemia undergoing peritoneal dialysis exhibit heterogeneity in adherence to serum phosphorus control. This indicates that healthcare providers should identify the adherence characteristics of different patient groups at an early stage and implement targeted intervention strategies to enhance patients' adherence to serum phosphorus management. Show less

This study aimed to identify distinct patterns of chronic disease resource utilization among patients with chronic obstructive pulmonary disease (COPD) and to examine their association with illness uncertainty. A cross-sectional study. This study enrolled COPD patients hospitalized in the Department of Respiratory Medicine at a tertiary hospital in Zhejiang Province, China, between April and December 2023. All participants completed a general information form, the Chronic Illness Resource Survey (CIRS), and the Mishel Uncertainty in Illness Scale (MUIS). Latent profile analysis (LPA) was conducted to identify subgroups of resource utilization patterns. Subsequently, hierarchical linear regression was employed to assess the associations between these patterns and illness uncertainty. Ethical approval was obtained from the Institutional Review Board of the Fourth Affiliated Hospital of Zhejiang University (Approval No. K2022057). A total of 308 participants were included. Two latent classes of resource utilization were identified: the Suboptimal Utilization Group ( Distinct patterns of chronic disease resource utilization exist among COPD patients and are significantly associated with illness uncertainty. Healthcare providers should recognize these subgroups and implement targeted interventions to enhance access to disease-related support resources, thereby mitigating illness uncertainty. Understanding COPD patients' varying patterns of resource utilization enables healthcare professionals and related industries to deliver personalized, resource-based interventions tailored to individual needs, ultimately reducing illness-related uncertainty and improving disease management outcomes. Show less

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

Conflicting data have explored the association between lipoprotein(a) [Lp(a)] and atherosclerotic cardiovascular disease (ASCVD) among individuals with different glucose metabolism statuses. We aimed to prospectively evaluate this association and to assess whether it is modified by C-reactive protein (CRP). This population-based cohort study was derived from the UK Biobank database. Lp(a) and CRP were measured between 2006 and 2010. Cox proportional hazards models and restricted cubic spline curves were employed to assess the relationship between Lp(a) levels and time to ASCVD events. A total of 307 269 participants without prevalent ASCVD were included, comprising 253 746 individuals with normal glucose regulation (NGR), 38 020 with prediabetes, and 15 503 with diabetes. The mean age was 57 years (Q1-Q3: 50-63), and 55.3% were female. Over a median follow-up of 13.2 years, 29 521 ASCVD events occurred. Higher Lp(a) levels were associated with an increased risk of ASCVD across all glucose metabolism statuses. In fully adjusted models, the hazard ratio (95% confidence interval) for ASCVD comparing participants in the top 10% of Lp(a) with those in the bottom 33% was 1.28 (1.22-1.34) among those with NGR, 1.23 (1.12-1.35) among those with prediabetes, and 1.16 (1.02-1.31) among those with diabetes. No significant interactions were observed after stratification by CRP (<2/≥2 mg/L) across glucose metabolism groups (P for interaction >0.05). Elevated Lp(a) levels were associated with a higher risk of ASCVD across different glucose metabolism statuses, particularly among individuals with NGR and prediabetes, independent of baseline CRP levels. Show less

Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroups, risk factors, and symptom-level interactions underlying depression-anxiety comorbidity across adolescents and adults in multi-ethnic Southwest China. The study included a total of 41,394 adolescents (aged 9-19) and 17,345 adults (aged 18-80). Adolescents were recruited using multistage stratified cluster sampling, whereas adults were recruited by convenience sampling. All participants completed a self-designed sociodemographic questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7). Latent profile analysis identified subgroups, logistic regression analyzed risk/protective factors, and network analysis mapped symptom interactions and bridge nodes. This study found that three adolescent profiles emerged: high (11.66 %), moderate (31.95 %), and low/no depression-anxiety (56.39 %). Adults were classified into low/no comorbidity (90.63 %) and comorbid depression-anxiety (9.37 %). Risk factors for adolescents included female gender (OR = 2.77, 95 %CI: 2.55-3.00; OR = 1.59, 95 %CI: 1.52-1.67), higher grade levels (OR = 3.45, 95 %CI: 3.10-3.84; OR = 3.56, 95 %CI: 3.33-3.80), smoking (OR = 1.72, 95 %CI: 1.51-1.96; OR = 1.28, 95 %CI: 1.17-1.41),drinking (OR = 2.45, 95 %CI: 2.23-2.70; OR = 1.66, 95 %CI: 1.55-1.77), family instability (OR = 1.16, 95 %CI: 1.02-1.31; OR = 1.33, 95 %CI: 1.14-1.56) and "other" ethnic minority (OR = 1.15, 95 %CI: 1.04-1.26). For adults, female gender(OR = 1.68; 95 %CI: 1.44-1.97), living alone(OR = 1.37; 95 %CI: 1.14-1.65), poor self-rated health (OR = 0.13, 95 %CI: 0.11-0.15), and Dai ethnicity (OR = 0.70, 95 %CI: 0.49-0.96) predicted comorbidity. Network analysis revealed distinct bridge symptoms: adolescents in the high depression-anxiety group had five symptoms: depressed or sad mood (phq2), psychomotor agitation/retardation (phq8), nervousness or anxiety (gad1), restlessness (gad5), and irritable (gad6); however, adults with comorbidity had one symptom: afraid something will happen (gad7). This study identified three patterns of depression-anxiety comorbidity in adolescents and two in adults. Efforts should prioritize adolescents from "other" ethnic minorities, strengthening family and peer support, as well as smoking and drinking interventions for adolescents, and addressing social isolation, physical health, and catastrophizing cognition in adults may mitigate the comorbidity burden. Show less

To use compositional data analysis to examine the associations of daily movement behaviors with body composition, and to predict changes in body composition after reallocating time among behaviors in preschool-aged children. 268 preschoolers were included in the cross-sectional study. An accelerometer was used to assess sedentary behavior (SB), light and moderate-to-vigorous physical activity (LPA and MVPA). A parental report was used to collect sleep time. Bioelectrical impedance analysis was employed to assess body composition. Compositional linear regression analysis was employed to explore how daily movement behaviors were associated with body composition. Compositional isotemporal substitution analysis was employed to estimate changes in body composition after reallocating time among behaviors. 24-h movement behaviors composition significantly predicted fat-free mass index (FFMI), soft lean mass index (SLMI), and skeletal muscle mass index (SMMI), but not fat mass index, percent body fat, and bone mineral content index. The compositional isotemporal substitution analyses consistently showed that increasing MVPA at the expenses of SB was positively associated with FFMI (+0.328 kg/m The findings highlight the importance of MVPA in improving preschoolers' body composition. Increasing MVPA at the expenses of SB may be a strategy to improve body composition in preschoolers. Show less

Accumulating research has demonstrated a significant association between early-life inflammation and behavioral disorders later in life. However, the effects of early-life inflammation on aggressive behavior in adulthood remain poorly understood. Here, we show that early-life inflammation induced by lipopolysaccharide (LPS) upregulated neuronal dynamin-related protein 1 (DRP1) and impaired mitochondrial function in medial prefrontal cortex (mPFC) of adult mice, thereby increasing aggressive behavior in adulthood. We further identify that CCAAT/enhancer binding protein β (C/EBPβ) is the transcription factor of Dnm1l, which was activated by an increased release of lysophosphatidic acid (LPA) induced by early-life inflammation. Moreover, the overproduction of LPA was due to a specific increase in astrocyte-secreted autotaxin (ATX). Specific knockdown of astrocytic ATX reduced early-life inflammation-induced aggression in wild-type mice, but not in Thy1-C/EBPβ transgenic mice. Remarkably, coenzyme Q10 decreased early-life inflammation-induced aggressive behavior in adult mice. Altogether, these findings provide new insights into the molecular mechanisms by which early inflammation promotes aggressive behavior in adulthood. Show less

Sepsis triggered by lipopolysaccharide (LPS) is a life-threatening condition. Inspired by the specific capture mechanism of innate proteins like LBP and CD14, we develop oxidized chitosan microspheres functionalized with hyperbranched polylysine (OCS-HBPL) as a sepsis detoxification agent. Isothermal titration calorimetry (ITC) reveals that HBPL-LPS binding is an enthalpy-driven process, distinct from the entropy-driven interaction of linear polylysine (LPL)-LPS. Validated by surface plasmon resonance (SPR), HBPL demonstrates superior affinity with a dissociation constant (K Show less

About 20-40% of prostate cancer (PCa) develop biochemical recurrence (BCR) after surgery, and propionate metabolism may contribute to tumor progression. BCR remains a major clinical challenge in PCa, as current tools based on histopathology and prostate-specific antigen (PSA) fail to capture the molecular heterogeneity driving the disease. While metabolic reprogramming is known to facilitate post-treatment adaptation, the specific role of propionate metabolism in this context remains largely unexplored. Therefore, this study aimed to systematically investigate propionate metabolism-related genes (PMRGs) to develop a novel prognostic model for the improved early prediction of recurrence. In this study, The Cancer Genome Atlas-Prostate Adenocarcinoma (TCGA-PRAD), GSE70770 and 412 PMRGs were employed. Differentially expressed genes (DEGs) in PCa and control and DEGs2 in BCR and no BCR samples obtained by differential analysis were intersected with PMRGs to get candidate genes. After Cox and least absolute shrinkage and selection operator (LASSO) regression analyses, biomarkers were identified to construct risk models. Biomarkers including In this study, PMRGs were regarded as biomarkers in PCa for risk model construction, which suggest that propionate metabolism represents a biologically relevant axis in PCa recurrence and may offer a novel framework for biomarker-driven risk assessment. Show less

Recent studies highlight the role of uric acid in tumor development, but its impact on prostate cancer (PCa) remains underexplored. This study aimed to investigate how uric acid influences PCa prognosis by analyzing transcriptomic data on PCa and uric acid-related genes (UARGs) from public databases. Differential expression analysis, protein-protein interaction (PPI) network, univariate Cox regression, and machine learning were used to identify prognostic genes. A risk model was then constructed based on these genes. Six prognostic genes (AHSG, AOX1, APOC1, LPL, NKX2-2, NKX6-1) were identified through the analysis of 1 433 differentially expressed genes (DEGs) and 3 806 UARGs. The risk model showed strong predictive ability, with the high-risk group (HRG) exhibiting poorer prognosis. Additionally, 10 immune cell types were significantly different between risk groups, with the HRG showing higher tumor mutation burden. A total of 8 drugs were found to correlate with risk scores. Enrichment analysis revealed that AHSG, AOX1, and APOC1 were linked to oxidative stress and Parkinson's disease, while NKX2-2 and NKX6-1 were associated with RNA degradation. These findings suggest that oxidative stress may be a key mechanism in PCa progression. This study offers a novel perspective on PCa treatment by identifying 6 prognostic genes and providing a prognostic risk model. Show less

Intramuscular fat (IMF) is a key determinant of meat quality, influencing tenderness, juiciness, and flavor. Previous studies have reported that the deposition of IMF is controlled by various factors. However, there is a shortage of research exploring the variations in IMF deposition across age groups from a microbial perspective. This study evaluated the differences in IMF deposition between yearling (1-year-old) and mature (4-year-old) Longdong Cashmere goats and analyzed its association with gut microbiota. The results revealed that the IMF content in shoulder meat and blood lipid levels increased with age (p < 0.05). Conversely, the contents of lipoprotein lipase (LPL) in the liver and duodenum significantly decreased with age. Microbial diversity differed between the two age groups, with specific microbiota identified from the gut of goats involved in the lipid metabolism pathway. The concentrations of valeric and isovaleric acids in the rumen, as well as acetic, propionic and isovaleric acids in the colon, were higher in yearling goats than in mature goats (p < 0.05). Spearman correlation analysis of IMF deposition indicators with gut microbiota revealed that, within the rumen, the abundances of CAG-791 and Sodaliphilus were positively correlated with IMF content in shoulder meat and TG levels, while exhibiting a negative correlation with the contents of valeric acids. Furthermore, the abundance of Clostridium_R showed a positive association with IMF content in shoulder meat and with the abundances of CAG-791and Sodaliphilus. In contrast, the abundance of Bact₁₁ was negatively correlated with IMF content in shoulder meat, TG levels, and the abundances of CAG-791, Sodaliphilus and Clostridium_R. Within the abomasum, the abundances of UMGS and Hylemonella₅₈₂₃₀₈ were correlated with IMF content in the shoulder meat, as well as serum LDL and VLDL levels. This study provides significant insights into the age-dependent gut microbiota associated with intramuscular fat deposition in goats and identifies several potential gut microbiota for further research on their impacts on IMF deposition. Show less

The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, using a CRISPR/Cas9-mediated Show less

Tail fat deposition constitutes a distinctive adaptive phenotype in sheep. The Large-tailed Han (LTH) and Small-tailed Han (STH) breeds display pronounced divergence in tail fat storage, offering an ideal model for elucidating lipid metabolism regulation. Integrated sRNA-Seq and RNA-Seq analysis identified 521 differentially expressed genes and 144 miRNAs, which were significantly enriched in lipid metabolism pathways, including fatty acid metabolism and PPAR signaling. Key candidate genes ( Show less

Norethindrone (NET) and levonorgestrel (LNG) are synthetic progestins frequently detected in aquatic environments, have unclear effects on lipid metabolic homeostasis during the early life stages of aquatic organisms. Although progestins commonly occur as mixtures, their combined impacts remain unclear. In this study, we investigated the individual and combined impacts of NET and LNG at environmentally relevant concentrations (2-200 ng/L) on lipid metabolism in zebrafish larvae. NET and LNG significantly disrupted early development in zebrafish. It also altered lipid profiles, as indicated by elevated triglyceride (TG) levels, reduced total cholesterol (TC), as well as alterations in key metabolic enzymes (FASN, LPL) and lipid-regulatory genes (pparγ, fasn, lpl, pparα). Co-exposure with LNG resulted in non-additive responses across multiple endpoints. Antagonistic interactions were predominant at medium and high concentrations, while occasional synergism was observed at low doses. These complex patterns were further supported by Bliss independence model analysis. Notably, combined exposure suppressed both lipid synthesis and degradation pathways more strongly than individual treatments, leading to lipid accumulation and altered energy regulation. This study advanced understanding of the ecological risks caused by progestins in aquatic environments and highlighted the necessity of mixture-based risk assessment of endocrine-disrupting compounds. Show less

Organic and organic-inorganic hybrid materials exhibiting room-temperature phosphorescence (RTP) and long persistent luminescence (LPL) materials have attracted growing attention for various time-resolved optoelectronic applications. To date, realizing intrinsically distinct RTP and LPL emissions within a single material system remains elusive, yet it is crucial for unlocking multifunctional applications such as multilevel optical encryption. Here, a Mn Show less

Embryos produced in vitro exhibit heightened cryosensitivity due to excessive lipid accumulation. Previous studies demonstrated that cyclic guanosine monophosphate (cGMP) modulates intracellular lipid metabolism through cGMP-dependent protein kinase (PKG) signaling in various cell types. This study investigated the effects of cGMP on (i) cryosurvival in sheep embryos, (ii) embryonic quality, and (iii)lipolysis-related parameters. Specifically, we quantified lipid droplet content, free fatty acid levels, and hormone-sensitive lipase (HSL) phosphorylation status as key indicators of lipolytic activity. The results showed that cGMP pretreatment (0.5 mM) for 10 min prior to slow freezing significantly improved post-thaw embryo recovery rates and upregulated the mRNA expression of key developmental genes (POU5F1, SOX2, CDX2, and NANOG). cGMP pretreatment significantly upregulated the expression of multiple lipid catabolism genes (ACSL4, HMGCR, HMGCS1, LIPE, LPL, LIPF, and PLIN2), with LIPE (encoding HSL) exhibiting the most pronounced induction (27.10-fold increase vs. control). Following cGMP pretreatment, PKG activation triggered significant increases in the intracellular Ca Show less

This study induced diabetic nephropathy (DN) in rats, analyzing perirenal adipose tissue (PRAT) via whole transcriptome sequencing to identify key mRNAs in DN pathogenesis. Type-2 diabetes was induced in SD rats, evaluating metabolic and renal indicators. Whole transcriptome sequencing identified differentially expressed RNAs in PRAT. CeRNA networks, PPI networks, and ingenuity pathway analysis (IPA) revealed key mRNAs linked to physiological indicators in DN. This study explores correlations between mRNAs and health parameters, shedding light on the complex interplay in type-2-diabetes mellitus (T2DM)-induced nephropathy. SD rats with type-2 diabetes exhibited insulin resistance, elevated blood glucose, disrupted lipid metabolism, and renal dysfunction. PRAT weight was higher in T2DM rats, and immunohistochemistry revealed distinct renal injury. Transcriptome sequencing identified 476 DE-mRNAs, 79 DE-miRNAs, 200 DE-lncRNAs, and 10 DE-circRNAs. The lncRNA-miRNA-mRNA network comprised 159 lncRNAs, 62 miRNAs, and 138 mRNAs, whereas the circRNA-miRNA-mRNA network included 76 mRNAs, 27 miRNAs, and 10 circRNAs. Key mRNAs (Lpl, Elovl6, Dgat2, Acaca, and Acly) were associated with 10 classical pathways according to IPA. Notably, all key mRNAs showed a negative correlation with blood urea nitrogen (BUN), serum creatinine, proteinuria, LDL-C, triglycerides (TG), and total cholesterol (TC), and a positive correlation with urine creatinine and HDL-C. Our study successfully established a T2DM model in SD rats and identified five key mRNAs, elucidating the role of PRAT in DN. These findings lay a scientific foundation for future investigations into DN. Show less

PICALM∶∶MLLT10 fusion gene-positive precursor B-cell acute lymphoblastic leukemia(pro-B-ALL)is clinically rare.This article reports the case of a 29-year-old female patient who presented a mediastinal mass.Diagnostic investigations confirmed PICALM∶∶MLLT10 fusion gene-positive pro-B-ALL.The patient sequentially received radiotherapy and multiple lines of chemotherapy but developed short-term drug resistance and lineage change,progressing to mixed-phenotype acute leukemia.A review of relevant literature was conducted to analyze its pathogenesis and molecular characteristics,aiming to provide references for clinical diagnosis and treatment. Show less