ObjectiveTo observe the protective effect of Erchentang （ECT） on SiO₂-induced lung injury in rats and to explore its underlying mechanism. MethodsA rat model of lung injury was established by a single intratracheal instillation of 50 mg·mL^-1 SiO₂ suspension. Thirty male Sprague-Dawley （SD） rats were randomly assigned to five groups： control， model， low and high-dose （4.5 g·kg^-1·d^-1 and 9 g·kg^-1·d^-1， respectively） ECT， and dexamethasone （0.2 mg·kg^-1·d^-1）. All the groups were treated for 4 consecutive weeks. Histopathological alterations in the lung tissue were examined by hematoxylin and eosin （HE） staining. The levels of malondialdehyde （MDA）， superoxide dismutase （SOD）， and glutathione peroxidase （GSH-Px） in the lung tissue were measured through biochemical assays. The expression of key molecules in the nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1） pathway was determined by Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， Western blot， and immunofluorescence assay. The primary active components of ECT were identified by ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）， and their binding affinity to Nrf2/HO-1 was assessed by molecular docking. Untargeted metabolomics of the lung tissue was performed based on UPLC-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF-MS）， and correlation analysis was performed to identify differential metabolites and parameters closely associated with the Nrf2/HO-1 pathway. ResultsCompared with the control group， the model group exhibited a reduction in body weight gain， an increase in lung index， increased MDA content， weakened SOD and GSH-Px activities in the lung tissue， down-regulated mRNA and protein levels of Nrf2 and protein levels of HO-1 and GPX4， and an up-regulated protein level of Keap1 （P<0.05， P<0.01）. Treatment with ECT attenuated the SiO₂-induced decline in body weight （P<0.05）， alleviated inflammatory cell infiltration and silicotic nodule formation in alveoli， and reduced the MDA content and enhanced the SOD and GSH-Px activities in the lung tissue （P<0.05， P<0.01）. UPLC-MS/MS and molecular docking revealed that core components of ECT， such as hesperidin and glycyrrhizic acid， displayed strong binding affinity to Nrf2/HO-1. Molecular biological experiments demonstrated that ECT promoted nuclear translocation of Nrf2， up-regulated the mRNA and protein levels of HO-1 and GPX4， and down-regulated Keap1 expression （P<0.05， P<0.01）. Metabolomic analysis indicated that ECT reversed the SiO₂-induced aberrant expression of metabolites， including linoleic acid and glutamine （P<0.05， P<0.01）. Correlation analysis showed that Nrf2 and HO-1 were positively correlated with SOD and GSH-Px （P<0.05， P<0.01）， but negatively correlated with glutamine and serine （P<0.05， P<0.01）. ConclusionECT may activate the Nrf2/HO-1 pathway through its core active components， thereby regulating oxidative stress and metabolic disorders to ameliorate SiO₂-induced lung injury in rats. This study provides experimental evidence for ECT in the prevention and treatment of occupational lung injury.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To explore the establishing Nomoplot prediction model for Kawasaki disease(KD)combined with coronary artery lesion(CAL)children was established based on logistic regression,and to evaluate its predictive efficacy.Methods:The clinical data of 367 KD children who were admitted to our hospital from January 2014 to June 2024 were retrospectively analyzed,the children were divided into CAL(n=91)and NCAL(n=276)groups according to whether they had concurrent CAL.The influencing factors for CAL children combine with KD were analyzed by univariate and multivariate logistic regression.Nomoplot prediction model for CAL children combine with KD was constructed.The predictive efficacy of the Nomoplot prediction model for CAL children combine with KD was evaluated by receiver operating characteristic(ROC)curve.Results:The incidence of CAL in 367 KD children was 24.80％(91/367),univariate analysis results showed that,the proportion of delayed intravenous immunoglobulin(IVIG)treatment and the proportion of IVIG resistance in CAL group were higher than those in NCAL group(P＜0.05),the fever duration was longer than that in NCAL group(P＜0.05),and the age,hemoglobin(Hb)and platelet count(PLT)levels were lower than those in NCAL group(P＜0.05),erythrocyte sedimentation rate(ESR),B-type natriuretic peptide(BNP),C-reactive protein(CRP),procalcitonin(PCT),albumin(ALB)and alanine aminotransferase(ALT)levels were higher than those in NCAL group(P＜0.05).Delayed IVIG treatment,prolonged fever duration,elevated CRP,ESR and BNP levels were independent risk factors for CAL children combine with KD(P＜0.05),Older age,elevated Hb level were protective factor(P＜0.05).The predicted curve of the Nomoplot prediction model was in good agreement with the ideal curve,the area under the curve(AUC)of the model for predicting CAL children combine with KD was 0.971.Conclusions:Delayed IVIG treatment,fever duration,age and Hb,CRP,ESR and BNP are independent Influencing factors for CAL children combine with KD,the Nomoplot prediction model constructed based on the above logistic regression results has a high predictive value for CAL children combined with KD.

The coil adverse events in the U.S.Food and Drug Administration Manufacturer and User Facility Device Experience(MAUDE)database from January 2021 to June 2024 were analyzed retrospectively.The risks of coils during the clinical application and their causes were explored with hospital survey and expert demonstration in Shandong Province.Some improving measures were put forward for the safe use of coils,including implementing the main responsibility of the registrant,enhancing the professional skills of the using institutions and strengthening the supervision of the supervisory authorities.[Chinese Medical Equipment Journal,2025,46(6):83-87]

This study was aimed at understanding the prevalence and drug resistance status of Salmonella of waterfowl ori-gin in the Guangdong region in the past decade,to guide prevention and control efforts.The drug-sensitive paper slide method was used to conduct drug susceptibility testing on 314 waterfowl-originating Salmonella strains isolated from 238 waterfowl farms in the Guangdong region from 2013 to 2023.The isolated Salmonella strains were most resistant to penicillin,amoxicil-lin,cefradine,and cefazolin in the β-lactam group;sulphadoxine dimethylpyrimidine in the sulphonamide group;and tetracy-cline in the tetracycline group.The resistance rates ranged from 73.57％to 89.49％.The highest sensitivity was observed to amikacin,gentamicin,and kanamycin in the aminoglycoside group,and norfloxacin in the quinolone group,with susceptibility rates all exceeding 50％.The 280 strains of Salmonella showed multi-drug resistance to six classes of antimicrobial drugs and high resistance(as much as 60.83％)to five drug classes.Correlation analysis revealed the highest correlations for florfenicol with gentamicin,and for amoxicillin with penicillin(r=0.650 for both),followed by gentamicin with kanamycin(r=0.620).Salmonella resistance in waterfowl in Guangdong Province was generally severe and showed a complex pattern of drug resist-ance.Detection of waterfowl pathogens should be strengthened to prevent the spread of drug-resistant bacteria and support ra-tional use of antibiotics.This work provides a reference for Salmonella prevention and control in waterfowl farms.

The water-sediment interface is an important zone for the migration and transformation of chemical substances,but traditional sampling methods make in situ sampling challenging,thus it is difficult to capture information on environmental processes at the micro-scale.In this study,diffusive gradients in thin films(DGT)probe technique was used as in situ tool to detect 18 kinds of typical per-and polyfluoroalkyl substances(PFAS)in the water-sediment system,elucidating their vertical distribution characteristics and patterns.The results showed that different PFAS exhibited distinct variation patterns with depth in water and sediment.Short-chain PFAS exhibited greater mobility,while the migration of long-chain PFAS was restricted in sediment and pore water due to their strong hydrophobicity and adsorption capacity,resulting in relatively small concentration changes in the sediment column.The PFAS concentrations measured by DGT ranged from 11.2 μg/L to 1305 μg/L.For long-chain PFAS,the concentrations measured by DGT were higher than those obtained from direct measurement of water and pore water,while the opposite results were obtained for short-chain PFAS.The DGT results indicated that although long-chain PFAS exhibited strong adsorption to sediment particles,the adsorbed PFAS were still bioavailable.DGT probe technique,with its advantages of in situ sampling and high spatial resolution,provides deep insights into the complex environmental processes occurring at the microscale in the water-sediment systems.DGT offers important technical support and scientific evidence for assessing the adsorption-desorption behavior,bioavailability,and ecological risks of these emerging pollutants in aquatic environment.

In the 1950s and 1960s,Japan's implementation of policies prioritizing economic develop-ment caused a lack of effective supervision over the discharge of industrial wastewater and exhaust gases,which led to the occurrence of the"Four Major Pollution Diseases",including Minamata disease,causing serious social and public health problems.To more effectively address public nuisances and pro-vide compensation to victims,the Japanese government gradually established an environmental damage compensation system with administrative relief characteristics since the 1970s.Through long-term prac-tice and system optimization,this system has evolved into a mature institutional framework with a clear division of labor and efficient collaboration.This paper systematically reviews the development process of Japan's environmental damage compensation system and deeply analyzes its legal frame-work and supporting policies,aiming to provide useful references for the construction and improve-ment of China's environmental damage compensation system.Meanwhile,through the case analysis of Minamata disease,the paper explores the specific mechanisms and effects in the compensation practices,further revealing the system's operational characteristics and implications,and providing a reference ba-sis for the construction of China's environmental governance legal system.

Objective:To investigate the clinical characteristics and independent risk factors of severe disease in patients with anti-nuclear matrix protein (NXP) 2 antibody-positive juvenile dermatomyositis (JDM).Methods:A retrospective cohort study was conducted, including 219 anti-NXP2 antibody-positive JDM patients admitted to 23 children′s hospitals across China from July 2011 to July 2023. Patients were classified into severe and non-severe groups based on classification criteria for severe dermatomyositis. Demographic characteristics, clinical manifestations, and laboratory parameters were compared between the 2 groups using independent sample t-test, Mann-Whitney U test, or χ2 test. Univariate and multivariate Logistic regression analyses were performed to identify risk factors for severe disease. The receiver operating characteristic curve was employed to calculate optimal cut-off values. Results:Among the 219 patients, 108 were male and 111 were female, with an age at onset of 6.3 (3.5, 9.4) years. The severe group comprised 69 patients, and the non-severe group 150 patients. The severe group had significantly higher rates of fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, as well as elevated levels of ferritin-to-albumin ratio (FAR), creatine kinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) (all P<0.05). Multivariate analysis identified anti-Ro52 antibody positivity ( OR=13.26, 95% CI 1.37-128.29) and elevated FAR ( OR=1.90, 95% CI 1.09-2.31) as independent risk factors for severe anti-NXP2 antibody-positive JDM (both P<0.05). Receiver operating characteristic curve analysis revealed that a FAR cutoff value of 6.82 predicted severe disease with an area under the curve of 0.87 (95% CI 0.81-0.94, P<0.001), sensitivity of 0.85, and specificity of 0.70. All patients received glucocorticoid therapy, and the severe group received higher proportions of steroid pulse therapy, cyclophosphamide, mycophenolate mofetil, intravenous immunoglobulin, biologics, and adjuvant treatments compared to the non-severe group (all P<0.05). In terms of outcomes, 2 patients (2.9%) in the severe group died (due to neurological involvement and intestinal perforation, respectively), while the remaining patients achieved complete clinical response or remission. All patients in the non-severe group achieved remission. Conclusions:The primary clinical features of anti-NXP2 antibody-positive JDM included fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, and elevated levels of CK, AST, LDH, and FAR. Furthermore, anti-Ro52 antibody positivity and a FAR>6.82 were identified as independent risk factors.

For middle-aged and elderly patients with conditions such as spinal fractures and degenerative spinal diseases, spinal internal fixation is a core surgical procedure for reconstructing spinal stability, heavily relying on the biomechanical stability provided by pedicle screw systems. Whereas, these patients are often complicated by osteoporosis that can significantly compromise the stability of the bone-pedicle screw interface, leading to a marked increase in pedicle screw loosening and surgical failure rates. The bone cement-augmented pedicle screw technique, which involves injecting bone cement into the vertebral body or screw trajectory to optimize the mechanical properties of the bone-pedicle screw composite, has been proven to significantly enhance fixation strength and effectively prevent screw-related failures, thereby reducing the incidence of internal fixation failure in high-risk populations undergoing spinal fusion. However, the widespread clinical application of this technique has faced challenges such as inaccurate clinical decision-making (indication and contraindication selection), non-standardized operative practices, and insufficient awareness of complication prevention, resulting in considerable variability in clinical outcomes and even severe complications. To address this, Prof. Luo Fei from First Affiliated Hospital of Army Medical University initiated the project and the Chinese Association Orthopaedic Surgeons organized relevant experts to develop the Evidence-based clinical practice guideline for bone cement-augmented pedicle screw technique ( version 2025), based on current evidence. The guidelines put forward 8 recommendations regarding the clinical value, scope of application, and operational standards of the technique, aiming to provide evidence-based medical support and technical standardization for clinical decision-making.

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.