1.Predictive modle for violence risk in hospitalized schizophrenia patients based on support vector machine
Huan LIU ; Peifang SHI ; Kun ZHANG ; Li KANG ; Yan ZHANG ; Long NA ; Binhong WANG ; Meiqing HE
Sichuan Mental Health 2026;39(1):27-35
BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness, unpredictability, high severity, and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia, to identify the key factors influencing the occurrence of violent behavior in these patients, so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases, eleventh edition (ICD-11) were collected to form the modeling cohort. They were randomly divided into a training set (n=140) and a test set (n=60) at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator (LASSO) regression algorithm, the feature variables were screened and dimension-reduced. The support vector machine (SVM) from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, precision, sensitivity, specificity, F1 value, and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores (r=0.580, P<0.01), a positive correlation between hospitalization compliance and current disease status (r=0.550, P=0.003), and a positive correlation between educational level and family per capita monthly income (r=0.367, P<0.01). The SVM model achieved an AUC of 0.853, accuracy of 0.800, precision of 0.810, sensitivity of 0.895, specificity of 0.636, F1 value of 0.850, and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients, which is helpful for the early identification of violent risks in such patients. [Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City (number, Y2023006)]
2.Research progress on association and mechanisms of copper dyshomeostasis with development of chronic diseases
Haibo ZHANG ; Jinsong FAN ; Xuezhen LIU ; Pinpin LONG
Journal of Environmental and Occupational Medicine 2026;43(4):516-526
Copper is an essential trace element in the human body, extensively involved in key physiological and biochemical processes such as antioxidant defense, energy metabolism, neural signaling, and immune regulation. In recent years, increasing research has focused on the potential role of copper dyshomeostasis in the development of chronic diseases. Studies indicate that abnormal copper levels, particularly elevated free copper, may increase the risk of cardiovascular disease, neurodegenerative disorders, diabetes, and cancer by inducing oxidative stress, impairing mitochondrial function, and disrupting immune regulation. Concurrently, copper homeostasis abnormalities have been demonstrated to be closely associated with increased all-cause mortality and accelerated aging. This systematic review comprehensively examined physiological functions, metabolic pathways, and environmental exposure characteristics of copper. It emphasized the epidemiological and mechanistic links between copper metabolism disorders and multiple chronic diseases, while exploring the potential applications of copper ion transporters and chelating agents in disease intervention. This work provides scientific evidence for the prevention, control, and precision treatment of copper-related chronic diseases.
3.Construction of Organoid-on-a-chip and Its Applications in Biomedical Fields
Rui-Xia LIU ; Jing ZHANG ; Xiao LI ; Yi LIU ; Long HUANG ; Hong-Wei HOU
Progress in Biochemistry and Biophysics 2026;53(2):293-308
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.
4.Construction of Organoid-on-a-chip and Its Applications in Biomedical Fields
Rui-Xia LIU ; Jing ZHANG ; Xiao LI ; Yi LIU ; Long HUANG ; Hong-Wei HOU
Progress in Biochemistry and Biophysics 2026;53(2):293-308
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.
5.Establishment and Preliminary Analysis of GP73 Interactome Using Proximity-dependent Labeling Technology
Mu-Yi LIU ; Chang ZHANG ; Meng-Xin YANG ; Xin-Long YAN ; Lu-Ming WAN ; Cong-Wen WEI
Progress in Biochemistry and Biophysics 2026;53(3):711-723
ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H2O2). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.
6.Establishment and clinical application of a method for the determination of tacrolimus concentration in human whole blood
Simin LIU ; Yamin CHU ; Yahui HU ; Guangfeng LONG ; Feng CHEN ; Yuanyuan ZHANG
China Pharmacy 2026;37(9):1180-1184
OBJECTIVE To develop a method for the determination of tacrolimus (TAC) concentration in human whole blood and to apply it in clinical therapeutic drug monitoring. METHODS Whole blood samples were processed by protein precipitation with methanol. The determination was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), with ascomycin serving as the internal standard. Chromatographic separation was carried out on a Kinetex F5 100Å column with a mobile phase consisting of 0.1 mmol/L ammonium acetate containing 0.2 mmol/L formic acid and methanol. Gradient elution was performed at a flow rate of 0.4 mL/min. The injection volume was 5 μL. Detection was conducted using multiple reaction monitoring ( m / z 821.6→768.6 for TAC; m / z 809.4→756.1 for ascomycin) with an electrospray ionization source in positive ion mode. The study focused on 86 whole blood samples collected from 83 pedi atric patients who received TAC therapy at Children’s Hospital of Nanjing Medical University from September 1 to 30, 2025. The aforementioned method was employed to measure the TAC concentration in the whole blood samples. The correlation and agreement between the aforementioned method and the traditional enzyme multiplied immunoassay technique (EMIT) were evaluated through Spearman correlation analysis, Bland-Altman analysis, and Passing-Bablok regression analysis. RESULTS The linear range of TAC was 0.5-100 ng/mL; the evaluation results for accuracy, precision, extraction recovery, matrix effect, and stability tests all met the relevant requirements. Clinical application results showed that the median concentration of TAC in pediatric whole blood measured by LC-MS/MS and EMIT methods were 4.4 and 4.0 ng/mL, respectively. Moreover, the two methods exhibited a strong correlation (correlation coefficient of 0.848 1) and good agreement (average relative deviation of 6.5%). CONCLUSIONS A reliable LC-MS/MS method for the determination of TAC concentration in human whole blood is successfully established. This method demonstrates strong correlation and good agreement with the EMIT method, making it suitable for clinical therapeutic drug monitoring.
7.Yimei Baijiang Formula Treats Colitis-associated Colorectal Cancer in Mice via NF-κB Signaling Pathway
Qian WU ; Xin ZOU ; Chaoli JIANG ; Long ZHAO ; Hui CHEN ; Li LI ; Zhi LI ; Jianqin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):119-130
ObjectiveTo explore the effects of Yimei Baijiang formula (YMBJF) on colitis-associated colorectal cancer (CAC) and the nuclear factor kappaB (NF-κB) signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups: Normal, model, capecitabine (0.83 g
8.Yimei Baijiang Formula Treats Colitis-associated Colorectal Cancer in Mice via NF-κB Signaling Pathway
Qian WU ; Xin ZOU ; Chaoli JIANG ; Long ZHAO ; Hui CHEN ; Li LI ; Zhi LI ; Jianqin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(3):119-130
ObjectiveTo explore the effects of Yimei Baijiang formula (YMBJF) on colitis-associated colorectal cancer (CAC) and the nuclear factor kappaB (NF-κB) signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups: Normal, model, capecitabine (0.83 g
9.Mechanism study of SIRT3 alleviating oxidative-stress injury in renal tubular cells by promoting mitochondrial biogenesis via regulating mitochondrial redox balance
Yaojun LIU ; Jun ZHOU ; Jing LIU ; Yunfei SHAN ; Huhai ZHANG ; Pan XIE ; Liying ZOU ; Lingyu RAN ; Huanping LONG ; Lunli XIANG ; Hong HUANG ; Hongwen ZHAO
Organ Transplantation 2026;17(1):86-94
Objective To elucidate the molecular mechanism of sirtuin-3 (SIRT3) in regulating mitochondrial biogenesis in human renal tubular epithelial cells. Methods Cells were stimulated with different concentrations of H2O2 and divided into four groups: control (NC), 50 μmol/L H2O2, 110 μmol/L H2O2 and 150 μmol/L H2O2. SIRT3 protein expression was then measured. SIRT3 was knocked down with siRNA, and cells were further assigned to five groups: control (NC), negative-control siRNA (NCsi), SIRT3-siRNA (siSIRT3), NCsi+H2O2, and siSIRT3+H2O2. After 24 h, cellular adenosine triphosphate (ATP) and mitochondrial superoxide anion (O2•−) levels were determined, together with mitochondrial expression of SIRT3, peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), nuclear respiratory factor 1 (NRF1), mitochondrial transcription factor A (TFAM), superoxide dismutase 2 (SOD2), acetylated-SOD2 and adenosine monophosphate activated protein kinase α1 (AMPKα1). Results The 110 and 150 μmol/L H2O2 decreased SIRT3 protein (both P<0.05). ATP and mitochondrial O2•− did not differ between NC and NCsi groups (both P>0.05). Compared to the NCsi group, the siSIRT3 group exhibited elevated O2•− level, decreased SIRT3 protein and increased expression levels of SOD2 and acetylated SOD2 protein (all P<0.05). Compared to the NCsi group, the NCsi+H2O2 group exhibited decreased cellular ATP levels, elevated mitochondrial O2•− levels, and reduced protein expression levels of SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 (all P<0.05). Compared with the siSIRT3 group, the siSIRT3+H2O2 group showed a decrease in cellular ATP levels, an increase in mitochondrial O2•− levels, a decrease in SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 protein expression levels and a decrease in acetylated SOD2 protein expression levels (all P<0.05). Compared with the NCsi+H2O2 group, the siSIRT3+H2O2 group showed a decrease in cellular ATP levels, an increase in mitochondrial O2•− levels, a decrease in SIRT3, AMPKα1, PGC-1α and NRF1, TFAM protein expression levels, and an increase in SOD2 and acetylated SOD2 protein expression levels (all P<0.05). Conclusions SIRT3 promotes mitochondrial biogenesis in tubular epithelial cells via the AMPK/PGC-1α/NRF1/TFAM axis, representing a key mechanism through which SIRT3 ameliorates oxidative stress-induced mitochondrial dysfunction.
10.Clinical Advantages of Traditional Chinese Medicine in Treatment of Childhood Simple Obesity: Insights from Expert Consensus
Qi ZHANG ; Yingke LIU ; Xiaoxiao ZHANG ; Guichen NI ; Heyin XIAO ; Junhong WANG ; Liqun WU ; Zhanfeng YAN ; Kundi WANG ; Jiajia CHEN ; Hong ZHENG ; Xinying GAO ; Liya WEI ; Qiang HE ; Qian ZHAO ; Huimin SU ; Zhaolan LIU ; Dafeng LONG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):238-245
Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance, while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine (TCM) has a long history in the prevention and management of this condition, demonstrating eight distinct advantages, including systematic theoretical foundation, diversified therapeutic approaches, definite therapeutic efficacy, high safety profile, good patient compliance, comprehensive intervention strategies, emphasis on prevention, and stepwise treatment protocols. Additionally, TCM is characterized by six distinctive features: the use of natural medicinal substances, non-invasive external therapies, integration of medicinal dietetics, simple exercise regimens, precise syndrome differentiation, and diverse dosage forms. By combining internal and external treatments, TCM facilitates individualized regimen adjustment and holistic regulation, demonstrating remarkable effects in improving obesity-related metabolic indicators, regulating constitutional imbalance, and promoting healthy behaviors. However, challenges remain, such as inconsistent operational standards, insufficient high-quality clinical evidence, and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment, conducting multicenter randomized controlled trials, and fostering interdisciplinary integration, so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

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