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）］

OBJECTIVE To systematically review medication-related risk factors for falls in older adults， to provide references for ensuring medication safety among older adults. METHODS A systematic search was conducted in PubMed， Embase， Web of Science， and CNKI for relevant literature published from database inception to November 1， 2025. Relevant studies on medication-related falls in older adults， both domestic and international， were included. Drug factors influencing falls in older adults were summarized and analyzed. RESULTS A total of 22 studies were included. Four major classes of fall-risk-increasing drugs were identified： psychotropic medications [12 studies， odds ratio （OR） range 1.500-5.790]， cardiovascular system drugs （5 studies， OR range 1.236-4.784）， analgesics （3 studies， OR range 1.500-4.490）， and hypoglycemic agents （3 studies， OR range 2.070-2.751）. Additionally， anticholinergic burden （1 study， OR was 2.610） and polypharmacy （7 studies， OR range 2.902-25.897 for the use of ≥4 medications） were identified as significant risk factors for falls. CONCLUSIONS Falls in older adults are significantly associated with psychotropic medications， cardiovascular system drugs， analgesics， and hypoglycemic agents， among which psychotropic medications pose the highest risk. Anticholinergic burden and polypharmacy are also important risk factors. In clinical practice， interventions should be implemented through deprescribing and risk monitoring to effectively reduce the risk of falls in older adults.

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.

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.

The Type III Secretion System (T3SS) serves as a pivotal virulence apparatus for numerous Gram-negative bacterial pathogens, enabling them to infect both animal and plant hosts. Functioning as a molecular syringe, the T3SS directly translocates bacterial effector proteins from the bacterial cytoplasm into the interior of eukaryotic host cells. These effectors are central weapons that precisely manipulate a wide spectrum of host cellular physiological processes, ranging from cytoskeletal dynamics to immune signaling, to establish a favorable niche for bacterial survival and proliferation. Among the diverse arsenal of T3SS effectors, the YopJ family constitutes a critical group of virulence factors. Members of this family are characterized by a conserved catalytic triad structure—a hallmark of the CE clan of cysteine proteases that has been evolutionarily repurposed to confer acetyltransferase activity. A defining and intriguing feature of these enzymes is their stringent dependence on a host-derived eukaryotic cofactor, inositol hexakisphosphate (IP₆), for allosteric activation. This requirement acts as a sophisticated molecular safeguard, ensuring enzymatic activity only within the appropriate host environment, thereby preventing detrimental effects on the bacterium itself. While seminal studies on individual members such as Yersinia’s YopJ and Salmonella’s AvrA have provided deep mechanistic insights, a systematic and integrative understanding of the structure-function relationships across the entire family remains fragmented. Key questions persist regarding how a conserved catalytic core has diverged to recognize distinct host substrates in different kingdoms of life. To address this gap, this article provides a systematic review of the YopJ family, focusing on three interconnected aspects: their structural features, their catalytic mechanism, and their divergent immunosuppressive strategies in animal versus plant hosts. By conducting a comparative analysis of the sequences and resolved three-dimensional structures of three representative members (e.g., HopZ1a, PopP2, AvrA), we elucidate regions of significant variation embedded within the conserved core catalytic architecture. These variable regions, often involving surface loops and substrate-binding interfaces, are crucial determinants of target specificity and functional specialization. The functional divergence of this effector family is most apparent when comparing their modes of action in different hosts. In animal hosts, YopJ-family effectors primarily sabotage innate immune signaling pathways. They achieve this by acetylating key serine and threonine residues within the activation loops of critical kinases in the MAPK and NF‑κB pathways. This post-translational modification blocks the phosphorylation and subsequent activation of these kinases, leading to potent suppression of inflammatory cytokine production. Conversely, in plant hosts, the strategy broadens to dismantle the two-tiered plant immune system. YopJ homologs target a more diverse set of substrates, including immune-associated receptor-like cytoplasmic kinases (RLCKs), microtubule networks via tubulin acetylation (which disrupts cellular trafficking and signaling), and transcription factors central to defense gene regulation. This multi-target approach effectively suppresses both Pattern-Triggered Immunity (PTI) and Effector-Triggered Immunity (ETI). In conclusion, this synthesis aims to deepen the mechanistic understanding of YopJ family-mediated pathogenesis by integrating structural biology with cellular function across host kingdoms. Elucidating the precise molecular basis for substrate selection—how conserved platforms achieve target diversity—is a major frontier. Furthermore, this knowledge provides a vital theoretical foundation for developing novel anti-virulence strategies. Targeting the conserved IP₆-binding pocket or the catalytic acetyltransferase activity itself represents a promising avenue for designing broad-spectrum inhibitors that could disarm this critical family of bacterial effectors, potentially offering new therapeutic approaches against a range of pathogenic bacteria.

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.

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.

ObjectiveTo investigate the effects of the classical Chinese medicine compound prescription Erjingwan on the inflammatory response and apoptosis of skeletal muscle cells in a mouse model of sarcopenia and decipher the mechanism based on the silent information regulator 1 （SIRT1）/nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1） signaling pathway. MethodsForty C57/BL6 male mice were randomized into a control group， a model group， and groups with different doses of Erjingwan （8，16，32 g·kg^-1）. The mouse model of sarcopenia was established by D-gal-induced skeletal muscle senescence. The body weight and grip strength of mice treated with different doses of Erjingwan were examined to evaluate their physiological functions. Hematoxylin-eosin （HE） staining and Masson staining were used to observe the pathological changes and fibrosis in the skeletal muscle of mice. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in the serum samples of mice， and biochemical tests were conducted to quantify the levels of superoxide dismutase （SOD）， malondialdehyde （MDA）， and glutathione （GSH） in the serum. The protein and mRNA levels of SIRT1， Nrf2， B-cell lymphoma （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsAfter 4 weeks of drug intervention， the model group exhibited significant reductions in body weight and grip strength （P0.01） compared with the control group. Compared with the model group， all doses of Erjingwan increased the body weight in mice at week 8 （P0.01） and grip strength from week 6 （P0.01）. HE staining revealed clear muscle fiber structure in the control group， muscle fiber rupture and atrophy in the model group， and dose-dependent repair of muscle fiber structure in the Erjingwan groups. Masson staining showed minimal collagen fibers and mild fibrosis in the control group， collagen fiber proliferation and severe fibrosis in the model group， and collagen proliferation with dose-dependent inhibition of fibrosis in the Erjingwan groups. ELISA results showed that serum levels of TNF-α and IL-6 were elevated in the model group compared with those in the control group （P0.01）. After intervention， the low-dose Erjingwan group exhibited a decreased TNF-α level （P0.05）， while the medium and high-dose groups showed decreases in both TNF-α and IL-6 levels （P0.01）. Biochemical assays revealed that the model group had decreased SOD and GSH levels （P0.01） and an increased MDA level （P0.01） compared with the control group. The medium and high-dose Erjingwan groups exhibited increases in SOD and GSH levels （P0.01） and decreases in MDA level （P0.01）， compared with the model group. WB and Real-time PCR results showed that compared with the control group， the model group presented down-regulated protein and mRNA levels of SIRT1， Nrf2， HO-1， and Bcl-2 in the muscle tissue （P0.01） and up-regulated protein and mRNA levels of Bax （P0.01）. Compared with the model group， Erjingwan at different doses up-regulated the protein levels of SIRT1， Nrf2， HO-1， and Bcl-2 （P0.01） and down-regulated the protein and mRNA levels of Bax （P0.01） in the muscle tissue. Low-dose Erjingwan elevated the mRNA levels of Nrf2 and HO-1 （P0.05， P0.01）， and medium and high-dose Erjingwan up-regulated the mRNA levels of SIRT1， Nrf2， HO-1， and Bcl-2 （P0.01）. ConclusionErjingwan reduced the content of inflammatory factors in skeletal muscle cells， improved the antioxidant capacity， and attenuated pathological changes and fibrosis in the muscle of the mouse model of sarcopenia by regulating the SIRT1/Nrf2/HO-1 pathway， inflammatory response， and apoptosis network.

ObjectiveTo investigate the effects of the classical Chinese medicine compound prescription Erjingwan on the inflammatory response and apoptosis of skeletal muscle cells in a mouse model of sarcopenia and decipher the mechanism based on the silent information regulator 1 （SIRT1）/nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1） signaling pathway. MethodsForty C57/BL6 male mice were randomized into a control group， a model group， and groups with different doses of Erjingwan （8，16，32 g·kg^-1）. The mouse model of sarcopenia was established by D-gal-induced skeletal muscle senescence. The body weight and grip strength of mice treated with different doses of Erjingwan were examined to evaluate their physiological functions. Hematoxylin-eosin （HE） staining and Masson staining were used to observe the pathological changes and fibrosis in the skeletal muscle of mice. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in the serum samples of mice， and biochemical tests were conducted to quantify the levels of superoxide dismutase （SOD）， malondialdehyde （MDA）， and glutathione （GSH） in the serum. The protein and mRNA levels of SIRT1， Nrf2， B-cell lymphoma （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsAfter 4 weeks of drug intervention， the model group exhibited significant reductions in body weight and grip strength （P0.01） compared with the control group. Compared with the model group， all doses of Erjingwan increased the body weight in mice at week 8 （P0.01） and grip strength from week 6 （P0.01）. HE staining revealed clear muscle fiber structure in the control group， muscle fiber rupture and atrophy in the model group， and dose-dependent repair of muscle fiber structure in the Erjingwan groups. Masson staining showed minimal collagen fibers and mild fibrosis in the control group， collagen fiber proliferation and severe fibrosis in the model group， and collagen proliferation with dose-dependent inhibition of fibrosis in the Erjingwan groups. ELISA results showed that serum levels of TNF-α and IL-6 were elevated in the model group compared with those in the control group （P0.01）. After intervention， the low-dose Erjingwan group exhibited a decreased TNF-α level （P0.05）， while the medium and high-dose groups showed decreases in both TNF-α and IL-6 levels （P0.01）. Biochemical assays revealed that the model group had decreased SOD and GSH levels （P0.01） and an increased MDA level （P0.01） compared with the control group. The medium and high-dose Erjingwan groups exhibited increases in SOD and GSH levels （P0.01） and decreases in MDA level （P0.01）， compared with the model group. WB and Real-time PCR results showed that compared with the control group， the model group presented down-regulated protein and mRNA levels of SIRT1， Nrf2， HO-1， and Bcl-2 in the muscle tissue （P0.01） and up-regulated protein and mRNA levels of Bax （P0.01）. Compared with the model group， Erjingwan at different doses up-regulated the protein levels of SIRT1， Nrf2， HO-1， and Bcl-2 （P0.01） and down-regulated the protein and mRNA levels of Bax （P0.01） in the muscle tissue. Low-dose Erjingwan elevated the mRNA levels of Nrf2 and HO-1 （P0.05， P0.01）， and medium and high-dose Erjingwan up-regulated the mRNA levels of SIRT1， Nrf2， HO-1， and Bcl-2 （P0.01）. ConclusionErjingwan reduced the content of inflammatory factors in skeletal muscle cells， improved the antioxidant capacity， and attenuated pathological changes and fibrosis in the muscle of the mouse model of sarcopenia by regulating the SIRT1/Nrf2/HO-1 pathway， inflammatory response， and apoptosis network.