Objective: To explore the nonlinear dynamic effects of social capital, adverse childhood experiences (ACEs) and depressive symptoms on suicidal behavior among vocational high school students, so as to provide theoretical basis and practical references for formulating suicide prevention strategies. Methods: A convenience sampling method was employed to include 668 students from a vocational high school from Wuhan in March 2023. Social capital was used as the asymmetry variable, while ACEs and depressive symptoms were used as bifurcation variables, a cusp catastrophe model was constructed to analyze the nonlinear changes in suicidal behavior among vocational high school students, and its fit was compared with linear and Logistic regression models. Results: Among students in the health vocational high school in Wuhan, only suicidal ideation accounted for 8.5%, only suicide attempt for 18.6%, neither accounted for 31.9%, and both for 41.0%. Gender, left behind experience, family economic status, parental parenting styles, depressive symptoms, social capital, and ACEs were all related factors influencing suicidal behavior among vocational high school students ( χ 2/H=19.03, 13.33, 21.11, 46.70, 144.38, 24.61, 118.77, all P <0.05). Violin plots showed a bimodal distribution of suicidal behavior, indicating nonlinear variation characteristics. The cusp catastrophe model results showed that social capital was negatively correlated with suicidal behavior, but the relationship was bifurcated by ACEs ( α social capital = -0.006 , β ACEs =0.075) and depressive symptoms ( α social capital =-0.013, β depressive =0.028) (all P <0.05). When both ACEs and depressive symptoms coexisted, the impact of ACEs was stronger ( β ACEs =0.077, β depressive =0.014) (both P <0.05). The cusp catastrophe model fitted ( R 2=0.886, 0.881, 0.882) better than the linear ( R 2=0.258, 0.219, 0.258) and Logistic regression models ( R 2= 0.242, 0.211 , 0.176). Gender stratified analysis results showed that bifurcation effect of ACEs was stronger in males than in females( β boys =0.224, β girls =0.086); in females, both ACEs and depressive symptoms had a bifurcation effect, with the former showing a stronger effect ( β ACEs =0.062, β depressive =0.015) (all P <0.05). Conclusions Suicidal behavior among vocational high school students exhibits nonlinear characteristics. Improving social capital to reducing ACEs and depressive symptoms may contribute to decreasing adolescent suicidal behaviors.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

OBJECTIVE To investigate the effects of total flavonoids of Drynariae Rhizoma （TFRD） on autophagy and apoptosis in LPS-induced chondrocytes via the regulation of the Notch1/hairy and enhancer of split 1 （Notch1/Hes1） signaling axis. METHODS Human chondrocyte cell line C28/I2 cells were cultured with 5 μg/mL LPS to esta blish in vitro inflammatory injury model. The cells were separated into normal control group， model group， TFRD group （200 μg/mL）， TFRD+peroxiredoxin 1 （Prdx1） small interfering RNA （si-Prdx1） group and TFRD+si-Prdx1 negative control （si-NC） group， with 6 replicate wells in each group. Cells were transfected with si-Prdx1 or si-NC for 24 hours， pretreated with TFRD for 2 hours， and then exposed to LPS， with a total culture duration of 48 hours. Apoptotic rate， the proportion of apoptotic cells， monodansylcadaverine （MDC） fluorescence intensity， as well as the contents of matrix metalloproteinase-13 （MMP-13）， a disintegrin and metalloproteinase with thrombospondin motifs 5 （ADAMTS5）， and cartilage oligomeric matrix protein （COMP） were measured. Additionally， the protein expression levels of X-linked inhibitor of apoptosis protein （XIAP）， poly（ADP-ribose） polymerase 1 （PARP1）， Beclin-1， microtubule-associated protein 1 light chain 3 Ⅱ/Ⅰ （LC3-Ⅱ/Ⅰ）， PTEN-induced putative kinase 1 （PINK1）， Notch1， Hes1， and Prdx1 were assessed. RESULTS Compared with model group， the apoptotic rate， the proportion of apoptotic cells， the contents of MMP-13 and ADAMTS5 as well as protein expressions of PARP1 were significantly decreased， while MDC fluorescence intensity， COMP content， protein expressions of XIAP， Beclin-1， LC3-Ⅱ/Ⅰ， PINK1， Notch1， Hes1 and Prdx1 were significantly increased （ P ＜0.05）. Compared with TFRD+si-NC group， the changes in the aforementioned indicators （except for Notch1 and Hes1） in the cells of the TFRD+si-Prdx1 group were significantly reversed （ P ＜0.05）. CONCLUSIONS TFRD may activate the Notch1/Hes1 signaling axis， and up-regulate the expression of the downstream target molecule Prdx1， thereby inhibiting LPS-induced chondrocyte apoptosis， promoting protective autophagy， and consequently improving cartilage metabolic homeostasis.

Objective: To explore the association between the Internet usage characteristics and suicidal ideation among vocational high school students, so as to provide a theoretical basis for precise intervention of suicide among vocational high school students. Methods: A total of 1 781 students were recruited from three vocational high schools in Wuhan and Xianning in March 2023 by using the cluster random sampling method. The Columbia-Suicide Severity Rating Scale and Revised Chen Internet Addiction Scale were used to measure suicidal ideation and Internet addiction, respectively. LASSO regression model was used to select influential factors related to suicidal ideation, and the gradient boosting decision tree algorithm XGBoost was used to develop prediction models and evaluate predictive performance. By calculating the SHAP values, the contribution of each influential factor was quantified. Results: The prevalence of suicidal ideation among vocational high school students was 42.22% and prevalence of Internet addiction was 26.39%. LASSO regression results indicated that age, gender, experience of being left behind, parental relationship, holding a class cadre position, using the Internet for learning, Internet use during dawn, morning and late night, Internet addiction, and depressive symptoms were all the influential factors of suicidal ideation among vocational high school students ( β= -0.05 , 0.29, 0.09, 0.27, 0.10, -0.01, 0.09, 0.05, 0.24, 0.28, 0.78, all P <0.05). The AUC of the prediction model was 0.75. The results based on SHAP values indicated that all influential factors identified through multivariate analysis contributed positively to the model predictions ( SHAP >0). Among these, depressive symptoms and parental relationship had the greatest impact on suicidal ideation ( SHAP =0.77, 0.26), and the joint effect of features with higher contribution could improve the prediction probability. Conclusions Depressive symptoms, parental relationships, Internet addiction, and time of Internet use are most important risk factors of suicidal behaviors for vocational high school students. Thus, effective interventions should be conducted to reduce their suicidal ideation.

Objective To analyze the lung function condition and the prevalence of pulmonary ventilation disorders in the occupational population of Wuhan, and to explore their influencing factors. Methods Physical examination data from the Wuhan Prevention and Treatment Center for Occupational Diseases were used in this study, and finally 9499 people were selected as the study subjects. The linear regression model and logistic regression model were used to analyze the influencing factors of pulmonary ventilation function and pulmonary dysfunction. The restricted cubic spline was used to explore the nonlinear relationship. Results The prevalence of pulmonary ventilation disorders was 1.7%, and the lung function indexes FVC, FEV1, and FEV1/FVC were significantly lower in the population aged >27 years than in the population aged <27 years (P<0.001). The lung function indexes FVC and FEV1 were significantly lower in females than in males (P<0.001). The lung function indexes FVC and FEV1 were significantly lower in underweight occupational groups than in normal-weight groups (P<0.001), and FVC and FEV1 were significantly lower in dust-exposed occupational groups than in groups without dust exposure(P<0.05). Restricted cubic spline plots showed a nonlinear relationship between age and lung function indexes FVC and FEV1 (P_nonlinear< 0.05). Age and BMI were the risk factors for pulmonary ventilation disorders. Conclusion Age, gender, BMI, and dust exposure are risk factors for decreased FVC and FEV1. Age is the risk factor for decreased FEV1/FVC. Age and BMI are the risk factors for pulmonary ventilation disorders.

BACKGROUND: Circadian syndrome (CircS) may be closely linked to lifestyle, psychological, and occupational factors, but evidence is lacking. This study aimed to explore complex associations between lifestyle, psychological and occupational factors and CircS among employed people in southwestern China. METHODS: In this study, network analysis was used to identify complex associations between lifestyle, psychological and occupational factors and CircS in employed people from the Chinese Cohort of Working Adults (CCWA). The centrality of each variable was estimated by strength centrality index, which was calculated by the sum of edge weights connected to the variable. Bridge in the network was identified as the variables in the top 80 th percentile of overall bridge strength, which was defined as the most strongly connected variables across lifestyle, psychological and occupational factors and CircS. The differences were assessed in network structures between subgroups divided by the median score of the variable with the strongest bridge strengthen. RESULTS: Among 31,105 participants from CCWA, 5213 (16.76%) had CircS. In the constructed network, anxiety (edge weights: 0.28), smoking (edge weights: 0.15), drinking (edge weights: 0.10), perceived noise at work (edge weights: 0.08), and implicit health attitude (edge weights: -0.02) were directly related to CircS, with 83.31% of the variance for CircS explained by these neighboring factors. Anxiety was the most central variable (strength centrality: 1.20) in the network and the strongest bridge (bridge strength: 0.84) connecting all domains of variables. A stronger association between anxiety and CircS was observed in the network of participants with more severe anxiety (edge weight: 0.23) than those with less severe anxiety (edge weight: 0.03). CONCLUSION Anxiety had the strongest association with CircS and was the central factor with the highest strength centrality, also the bridge with the highest bridge strength in the network.
Humans ; Male ; Female ; Adult ; China ; Middle Aged ; Life Style ; Chronobiology Disorders/epidemiology*