Background Ozone (O₃) is a major air pollutant. The existing monitoring system has uneven distribution of sites, insufficient coverage in underdeveloped areas, and low temporal resolution, making it difficult to obtain hourly data. This limits the dynamic identification of pollution and the formulation of prevention and control strategies. Objective To construct an hourly O₃ concentration estimation model based on ensemble machine learning, aiming to improve the accuracy of pollution exposure assessment and explore O₃ health impacts. Methods This study integrated land use regression modeling with modern machine learning techniques, employing random forest and XGBoost algorithms to construct base models, and stacking integration using non-negative least squares. The ensemble model was trained and validated across China using high-resolution, multi-source geographic data (e.g., meteorologicaldata, population density, land cover types, and aerosol optical thickness). It was tested in Taiyuan City, combined with a distributed lag non-linear model to analyze the association between O₃ and emergency admissions. Results The constructed ensemble model performed well in predicting O₃ concentration, with a higher coefficient of determination (R²) and a lower root-mean-square deviation (RMSE) compared to the single models. The R² improved from 0.90 to 0.92, and the RMSE decreased from 11.41 to 10.62, enhancing both prediction accuracy and generalization ability. In the application to Taiyuan City, the model successfully imputed the hourly-level data for the entire year. The distributed lag non-linear model analysis revealed that the relative risk (RR) values for the 6th to 8th days following O₃ exposure were 1.14 (95%CI: 1.01, 1.29), 1.16 (95%CI: 1.02, 1.31), and 1.14 (95%CI: 1.01, 1.29), respectively, which were significantly higher than 1, indicating a significant lagged association (lagged 6-8 d) between O₃ and the number of emergency room visits. Conclusion A high-precision, hourly-level O₃ concentration estimation model is successfully constructed by combining the land use regression model with an ensemble machine learning approach to provide a scientific basis for environmental policy formulation and public health intervention. The application of the model verifies its generalization ability and practical application value, which can provide a new technical framework for subsequent environmental health research.

Objective To explore the relationship between PANoptosis and hepatic ischemia-reperfusion injury (HIRI), and to screen the key genes of PANoptosis in HIRI. Methods PANoptosis-related differentially expressed genes (PDG) were obtained through the Gene Expression Omnibus database and GeneCards database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways related to PDG. A protein-protein interaction network was constructed. Key genes were selected, and their diagnostic value was assessed and validated in the HIRI mice. Immune cell infiltration analysis was performed based on the cell-type identification by estimating relative subsets of RNA transcripts. Results A total of 16 PDG were identified. GO analysis showed that PDG were closely related to cellular metabolism. KEGG analysis indicated that PDG were mainly enriched in cellular death pathways such as apoptosis and immune-related signaling pathways such as the tumor necrosis factor signaling pathway. GSEA results showed that key genes were mainly enriched in immune-related signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway. Two key genes, DFFB and TNFSF10, were identified with high accuracy in diagnosing HIRI, with areas under the curve of 0.964 and 1.000, respectively. Immune infiltration analysis showed that the control group had more infiltration of resting natural killer cells, M2 macrophages, etc., while the HIRI group had more infiltration of M0 macrophages, neutrophils, and naive B cells. Real-time quantitative polymerase chain reaction results showed that compared with the Sham group, the relative expression of DFFB messenger RNA in liver tissue of HIRI group mice increased, and the relative expression of TNFSF10 messenger RNA decreased. Cibersort analysis showed that the infiltration abundance of naive B cells was positively correlated with DFFB expression (r=0.70, P=0.035), and the infiltration abundance of M2 macrophages was positively correlated with TNFSF10 expression (r=0.68, P=0.045). Conclusions PANoptosis-related genes DFFB and TNFSF10 may be potential biomarkers and therapeutic targets for HIRI.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.

Background Diseases severely affect the efficiency of workers. Comorbidity refers to the coexistence of two or more chronic diseases or health problems in the same individual. Previous studies have primarily focused on occupational injuries caused by environmental exposures, while the analysis of the epidemiological characteristics of self-reported diseases and occupational injuries among manufacturing workers has been insufficient. Objective To analyze the distribution of self-reported diseases and occupational injuries among manufacturing workers, the strength of correlation between different diseases, and common disease combinations, and to preliminarily explore the relationship between self-reported diseases and occupational injuries. Methods A cross-sectional survey was conducted to investigate the occupational injuries of 2382 workers in 2 manufacturing enterprises over the past year, and 2355 questionnaires were valid after cleaning. The questionnaire included three parts: basic information, occupational injury occurrence, and disease prevalence. The self-reported diseases diagnosed by physicians included musculoskeletal diseases, cardiovascular diseases, respiratory diseases, mental health problems, neurological and sensory organ diseases, digestive organ diseases, reproductive and urinary organ diseases, skin diseases, tumors, endocrine and metabolic system diseases, blood diseases and birth defects, a total of 11 types. Log-binomial model was used to calculate the prevalence ratio (PR) value of the association between different diseases, and UpSet diagram was used to present the disease combination pattern. Results In total, 40.2% (946/2355) of the study participants reported at least one disease, while 8.6% (203/2355), 5.2% (122/2355), and 5.9% (140/2355) reported having two, three, and four or more diseases, respectively. A higher prevalence was observed for musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases, which accounted for 18.0% (423/2355), 13.8% (324/2355), 9.3% (218/2355), and 9.1% (214/2355), respectively. Workers with musculoskeletal disorders, cardiovascular diseases, or neurological and sensory organ diseases reported significantly higher incidence of occupational injuries compared with workers without the corresponding diseases (P<0.001, P=0.041, and P=0.006, respectively). Musculoskeletal diseases were strongly associated with comorbidities of neurological and sensory organ diseases (PR values were 1.86 and 1.98, respectively), and the other patters were musculoskeletal diseases and digestive organ diseases (PR and OR values were 1.57 and 2.35, respectively), and musculoskeletal diseases and cardiovascular diseases (PR and OR values were 1.46 and 2.22, respectively). The largest binomial comorbidity group involved musculoskeletal diseases and neurological and sensory organ diseases, accounting for 5.4% (25/465) of the comorbid workers. Conclusion Among the self-reported diseases of manufacturing workers, musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases are more common. Musculoskeletal diseases and neurological and sensory organ diseases are the most common in all comorbidities. Musculoskeletal diseases, cardiovascular diseases, and neurological and sensory organ diseases are associated with occupational injuries. In the prevention and control of occupational injuries, joint prevention strategies targeting multiple diseases should be strengthened.

Nonalcoholic steatohepatitis （NASH） is a chronic metabolic disease characterized by hepatocyte fatty degeneration and ballooning degeneration， and it plays an important role in the progression of hepatic steatosis. Recent studies have shown that immune homeostasis imbalance between T helper 17 （Th17） and regulatory T （Treg） cells are closely associated with the pathological process of NASH. Transforming growth factor-β1 （TGF-β1） is a key cytokine for regulating the differentiation and proliferation of Th17/Treg cells， and TGF-β1 binds to its receptor and activates the Smad signaling pathway， thereby regulating the immune balance of Th17/Treg cells and the expression of inflammatory factors and participating in the repair of liver inflammation. This article systematically reviews the molecular mechanism of the TGF-β1/Smad signaling pathway in affecting NASH by regulating the immune balance of Th17/Treg cells， in order to provide a theoretical basis for the research on the pathogenesis of NASH and related treatment strategies.

Adolescent idiopathic scoliosis(AIS)is a complex three-dimensional deformity involving coronal,sagittal,and axial planes,with a prevalence that should not be overlooked.With advancements in technology and in-depth research,an increasing number of hospitals and physicians are exploring standardized diagnostic and treatment approaches for AIS.Comprehensive and in-depth understanding is required for AIS,including its etiology,screening and diagnosis,classification,assessment and examination,treatment options,exploration of current focus,and evaluation of quality of life.Such understanding ensures that the diagnostic and treatment are scientific,standardized,and timely.Based on the principles of evidence-based medicine,a consensus on the diagnosis and treatment of AIS is reached after multiple discussions among spinal surgery experts,aiming to provide reference and guidance for clinical practice.

Objective To explore the mechanism by which the sanguis draconis flavones(SDF)regulates the reactive oxygen species(ROS)/thioredoxin-interacting protein(TXNIP)pathway to mediate cell pyroptosis and improve cerebral ischemia-reperfusion injury(CIRI)in rats.Methods The experimental rats were randomly divided into the control group(Ctrl),the CIRI group,the low-dose SDF group(SDF-L),the high-dose SDF group(SDF-H),and the SDF-H+ROS/TXNIP pathway activator,trimethylamine oxide(TMAO)group(SDF-H+TMAO).Among them,except for the control group,the remaining rats all needed to establish the CIRI rat model by the modified suture method.Zea Longa scoring was performed on rats from each group.ELISA was used to detect the levels of serum inflammatory factors interleukin(IL)-1β,IL-18 and oxidative stress-related factors superoxide dismutase(SOD),malondialdehyde(MDA),glutathione peroxidase(GSH-Px).Flow cytometry was used to measure the ROS levels.Cerebral edema was detected.Cerebral infarction was detected by 2,3,5-triphenyl tetrazolium chloride(TTC)staining.HE staining was used to detect the pathological changes of brain tissue.Immunohistochemistry was used to detect the expression of pyrolytic effector protein dermolin D(GSDMD).Western blotting was used to detect the expression of proteins related to the ROS/TXNIP pathway.Results Compared with the control group,a large area of cerebral infarctions were observed in the brain tissue of the CIRI group,accompanied by mild hemorrhage and obvious infiltration of inflammatory cells.Neuronal cells underwent degeneration and necrosis,with sparse and disordered arrangement.The phenomena of nuclear condensation and nucleolus lysis were obvious.The Zea Longa score,cerebral infarction volume,brain tissue water content,levels of IL-1β,IL-18,ROS,MDA,and the expressions of GSDMD,TXNIP,nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3),apoptosis-related punctate protein(ASC),and Caspase-1 increased,while the activities of SOD and GSH-Px decreased(P＜0.05).Compared with the CIRI group,the pathological damage of brain tissues in the SDF-L group and the SDF-H group was significantly improved.The Zea Longa score,cerebral infarction volume,brain tissue water content,levels of IL-1β,IL-18,ROS,MDA,and the expressions of GSDMD,TXNIP,NLRP3,ASC,and Caspase-1 decreased.The activities of SOD and GSH-Px increased(P＜0.05);TMAO treatment partially reversed the improvement effect of SDF on CIRI in rats.Conclusion SDF ameliorates cerebral CIRI in rats by inhibiting ROS/TXNIP pathway-mediated pyroptosis.

Objective To investigate the effects of implant length,diameter,and abutment angle on bone stress distributions around maxillary central incisors,and determine the optimal parameter combination.Methods A three-dimensional(3D)model of the maxilla was reconstructed based on CBCT data.Using an orthogonal table,a total of 16 dental implant 3D models were established,varying in length,diameter,and abutment angle.These models were assembled with the maxillary and rigid-body models.Finite element analysis was performed using the transient dynamics module of ANSYS.Orthogonal experiments and one-way analysis of variance(ANOVA)were conducted on the obtained stress data.Results The implant diameter showed a statistically significant effect on the maximum von Mises stress in cortical bone(P=0.010),while implant length(P=0.229)and abutment angle(P=0.844)did not demonstrate a statistical significance.The optimal parameter combination for cortical bone stress was 5.0 mm implant diameter,12 mm implant length,and 0° abutment angle.In cancellous bone,implant length(P=0.001),diameter(P=0.011),and abutment angle(P=0.013)all had statistically significant effects on the maximum von Mises stress.The optimal parameter combination for cancellous bone stress was 14 mm implant length,5.0 mm implant diameter,and 5° abutment angle.Conclusions Implant diameter significantly affects the stress of both cortical and cancellous bone.Clinically,a larger diameter should be preferred to reduce the stress peak.Implant length is the next most important factor,while abutment angle has the least effect.

As China has become the second largest market for medical devices in the world,the domestic medical device industry has been growing.As an important part of preclinical evaluation of medical devices,large animal research directly affects the research and application of medical devices.Large animals are widely used in the evaluation of safety and feasibility of medical devices because they are closer to humans in terms of body size,anatomical structure and physiological functions.In large animal experimental research,the selection of suitable experimental animals and the establishment of suitable animal disease models are the basis for ensuring the smooth progress of experiments.In this paper,the selection of experimental animals and the establishment of disease models in medical device large animal experimental research are systematically sorted out,and the existing problems and deficiencies are pointed out.