Liver injury has become an increasingly serious global health problem， and existing chemical drugs face the limitations in efficacy and adverse reactions， resulting in the urgent need to develop safe and effective drugs. Recent studies have highlighted the potential of flavonoids from natural medicinal plants in the prevention and treatment of liver injury. As a typical natural flavonoid， luteolin shows a good protective effect against liver injury due to various etiologies， but there is still a lack of systematic elaboration on its mechanism of action. This article summarizes related research advances in China and globally and reviews the mechanism of action of luteolin in inhibiting oxidative stress， exerting an anti-inflammatory effect， regulating cell death， alleviating hepatic fibrosis， modulating lipid metabolism disorders， and regulating the gut-liver axis， as well as the application prospect of luteolin in the treatment of liver injury， in order to provide a scientific reference for further research on this compound.

Liver injury has become an increasingly serious global health problem， and existing chemical drugs face the limitations in efficacy and adverse reactions， resulting in the urgent need to develop safe and effective drugs. Recent studies have highlighted the potential of flavonoids from natural medicinal plants in the prevention and treatment of liver injury. As a typical natural flavonoid， luteolin shows a good protective effect against liver injury due to various etiologies， but there is still a lack of systematic elaboration on its mechanism of action. This article summarizes related research advances in China and globally and reviews the mechanism of action of luteolin in inhibiting oxidative stress， exerting an anti-inflammatory effect， regulating cell death， alleviating hepatic fibrosis， modulating lipid metabolism disorders， and regulating the gut-liver axis， as well as the application prospect of luteolin in the treatment of liver injury， in order to provide a scientific reference for further research on this compound.

ObjectiveTo establish a mouse model of rheumatoid arthritis with interstitial lung disease （RA-ILD） in DBA/1 mice using Porphyromonas gingivalis （Pg） infection combined with collagen-induced arthritis （CIA）， and to comprehensively evaluate pathological characteristics in joints， lungs， and serum. MethodsForty DBA/1 mice were randomly divided into four groups， i.e.， Control， Pg infection （Pg）， CIA， and Pg infection combined with CIA （Pg+CIA）， with 10 mice in each group. Arthritis clinical symptoms were evaluated by recording arthritis incidence and clinical scores. Micro-CT scanning was used to assess knee joint pathology. Histopathological changes and collagen deposition in knee joints and lung tissues were analyzed using hematoxylin-eosin （HE） and Masson staining. Immunohistochemistry was performed to detect protein expression of α-smooth muscle actin （α-SMA）， typeⅠ collagen （ColⅠ）， and fibronectin （FN） in lung tissues. Real-time quantitative polymerase chain reaction（Real-time PCR）was used to measure mRNA expression levels of α-SMA， ColⅠ， FN， tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and IL-1β in lung tissues. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of Pg， cyclic citrullinated peptide （CCP）， and immunoglobulin G （IgG）. ResultsJoint lesions： The CIA and Pg+CIA groups showed 100% arthritis incidence， with evident joint redness， swelling， and deformity. The number of affected limbs was 27 and 28， and clinical scores were 68 and 70， respectively. No obvious clinical symptoms were observed in the Pg group. Histopathological and imaging analyses showed severe joint lesions in the CIA and Pg+CIA groups， with significantly increased histopathological scores， bone mineral density， bone volume fraction， trabecular thickness， and trabecular number compared to the Control group （P<0.01）. No obvious joint pathology was observed in the Pg group. Lung lesions： The Pg+CIA group exhibited marked alveolar inflammation， interstitial inflammatory cell infiltration， and alveolar wall thickening， with pronounced blue staining of collagen fibers. Histopathological scores and collagen area ratios were significantly higher than those of the Control， Pg， and CIA groups （P<0.05）. Lung protein and mRNA expression levels of α-SMA， ColⅠ， and FN were markedly increased， and mRNA levels of IL-6， TNF-α， and IL-1β were significantly elevated compared to the Control group （P<0.05）. Serology： The Pg+CIA group showed significantly higher levels of CCP， Pg， and IgG compared with the Control， Pg， and CIA groups （P<0.05）. ConclusionDBA/1 mice subjected to Pg infection combined with CIA exhibited pronounced symptoms and pathological features of RA-ILD， along with elevated serum anti-CCP antibody levels. This model represents a novel RA-ILD mouse model， providing a valuable experimental tool for investigating RA-ILD pathogenesis and developing new therapeutics， and serves as a basis for establishing anti-cyclic citrullinated peptide antibody （ACPA）-positive RA-ILD animal models.

ObjectiveTo investigate the difference in the risk of cardiovascular diseases between patients with different subtypes of non-alcoholic fatty liver disease （NAFLD） from the perspective of metabolism， since cardiovascular events induced by metabolic disorders are the leading cause of death in NAFLD. MethodsThe cluster sampling method was used to conduct a multicenter cross-sectional study among three representative hospitals in Pudong New Area of Shanghai， China. A total of 37 122 sets of physical examination data from July 2022 to June 2023 were collected and stratified according to body mass index （BMI）. The chi-square test was used for comparison of continuous data between groups， and a multivariable Logistic regression analysis was used to investigate the association between NAFLD subtypes and cardiometabolic risk factors. ResultsA total of 9 372 cases of NAFLD were detected， with a detection rate of 25.25%， and more than 97% of these patients were diagnosed with metabolic associated fatty liver disease （MAFLD）. The subgroup analysis showed that the detection rates of lean， overweight， and obese NAFLD were 7.72%， 33.99%， and 63.56%， respectively. Compared with the patients with lean or overweight NAFLD， the patients with obese NAFLD showed a significantly higher proportion of patients with abnormalities in blood pressure， blood glucose， triglyceride （TG）， high-density lipoprotein （HDL） or uric acid （all P<0.001）. Among related risk factors， lean NAFLD was associated with the increase in total cholesterol （TC）（P<0.05）， while overweight NAFLD and obese NAFLD were not associated with TC abnormalities （P>0.05）； obese NAFLD was not associated with TG abnormalities， while lean NAFLD and overweight NAFLD were associated with TG abnormalities （both P<0.05）； all types of NAFLD were associated with the abnormalities of waist-hip ratio， blood pressure， blood glucose， low-density lipoprotein， HDL， and uric acid （all P<0.05）. ConclusionThe detection rates of different subtypes of NAFLD in Shanghai Pudong are close to those reported in China and globally， and the epidemiologic data of NAFLD can be used analogously for MAFLD. There are certain differences in the distribution and association of cardiometabolic risk factors between different subtypes of NAFLD， and targeted interventions should be formulated based on the metabolic characteristics of each type of NAFLD.

The development and validation of clinical prediction models based on artificial intelligence (AI) and machine learning methods have become increasingly widespread. However, the prediction model bias risk and applicability evaluation tool developed in 2019 (i.e., PROBAST-2019) has shown significant limitations. Therefore, an expanded and updated version of the PROBAST-2019 tool was released in 2025, known as the PROBAST+AI tool. The tool is divided into two parts including model development and model evaluation. It aims to comprehensively and systematically evaluate potential methodological quality issues in model development, bias risks in model evaluation, and the applicability of models, regardless of the modeling method used. This paper provides a systematic interpretation of the PROBAST+AI tool's items and case analyses, with the aim of guiding and assisting researchers engaged in related studies and promoting the high-quality development of clinical predictive model research.

Objective To examine the effect of piceatannol on inflammatory response in hepatitis B virus(HBV)infected rats by regulating Notch signaling pathway.Methods Wistar rats were randomly assigned to control group,model group,low dose piceatannol group,high dose piceatannol group,high dose piceatannol+Jagged1 group to receive injection of HBV antigen solution via tail vein to induce HBV infection model.After intervention with piceatannol and Notch signal activator Jagged1,HBV infection and liver function of rats in each group were tested.ELISA was applied to measure the levels of inflammatory biomarkers in serum and liver tissue.Immunoblotting was applied to detect the expression of Notch signaling pathway related proteins[Notch1,Delta-like ligand 4(DLL4),hairy and enhancer of split 1(Hes1)]in the liver tissues.Results Compared with the control group,the aspartate aminotransferase(AST)and alanine aminotransferase(ALT)levels,iNOS and TNF-α levels,Notch1,DLL4,and Hes1 protein expression increased(P＜0.05),IL-10 level decreased(P＜0.05)in model group.AST and ALT,iNOS and TNF-α levels,liver tissue Notch1,DLL4,and Hes1 protein expression decreased,hepatitis B surface antigen(HBsAg)and hepatitis B e antigen(HBeAg)seroconversion rate,IL-10 levels increased(P＜0.05)in the low and high dose piceatannol groups compared with the model group(P＜0.05).High dose piceatannol was associated with stronger beneficial effect on various pathological indicators in HBV infected rats.Jagged1 could reduce the beneficial effect of piceatannol on various pathological indicators in HBV infected rats.Conclusions Piceatannol can reduce the production of proinflammatory factors and increase the production of anti-inflammatory factors by blocking Notch signal transduction,thereby inhibiting inflammation,alleviating liver injury,and improving liver function in HBV-infected rats.

Objective To explore the impact of"knowledge-attitude-practice"(KAP)training mode on head nur-ses' core competency in healthcare-associated infection(HAI)prevention and control in a tertiary first-class general hospital.Methods Head nurses of 113 departments in a tertiary first-class general hospital were taken as the re-search objects.Guided by problems and demands,HAI training was conducted using the KAP training mode.The training was divided into two stages:a stage with problems of infection control and investigation of knowledge de-mands,as well as a stage with KAP training mode implementation.It included theoretical lectures,visits and lear-ning,and supervision on rectification.Scores of theory,supervision,and core competency of head nurses before training,1 month and 6 months after training were compared by the analysis of variance.SPSS 26.0 statistical soft-ware was used for analysis.Results The top three infection control problems in this hospital were hand hygiene,prevention and control of infection with multidrug-resistant organisms,as well as HAI prevention and control in the wards.The top three training modules required urgently by the head nurses were occupational exposure and self-protection,principles of medical waste disposal,as well as prevention and control of HAI in the wards.Both scores of theory and supervision after training were higher than those before training,with statistically significant diffe-rences(both P＜0.01).The core competencies of the head nurses were at a high level.After implementing KAP training mode,the scores of dimensions in critical thought and research,clinical nursing,leadership,and profe-ssional development,as well as the overall score of core competencies were all higher than before training.Diffe-rences were all statistically significant(all P＜0.05).The overall scores of dimensions in legal and ethical practice,education and consultation,as well as interpersonal relationship were all higher than before training,but the diffe-rences were not statistically significant(all P＞0.05).Conclusion KAP training mode can significantly improve the scores of theory,supervision,and core competencies of head nurses,and can be further promoted and applied in head nurses' infection control training.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective Exploring the components of complex scenarios of healthcare surges triggered by major epidemics to provide a theorical basis for building resilience in healthcare organizations.Methods A hybrid analysis method is used to summarize macro-meso-micro multi-level and multi-source heterogeneous information,extract the elements of complex scenarios of medical surge and evaluate the rationality.Fault Tree Analysis method is used to clarify the logical relationship between various scenario elements and construct scenario reasoning paths.Results 10 scenario states,11 disaster-bearing,24 emergency management and 23 scenario results are summarized and extracted to form the key elements of complex surge scenarios.Among them,M4 expansion and coordinated scheduling of key positions,B2 conventional drug inventory emergency/insufficient core treatment drugs,B emergency medical material transportation breakage,S3 disease symptom spectrum shift to severe disease,R13 prevention and control awareness laxity,and M5 media information dissemination management are the key driving factors that promote a major turning point in the scenario.The most positive scenario result is the orderly operation of the medical service system,and the most negative scenario result is the paralysis of the medical service system.Conclusion Medical institutions need to improve emergency plans based on the complex evolution scenarios of medical surges and agile governance capabilities targeting key turning points,focus on dynamically expanding and scheduling personnel in key positions,strengthen material rotation and reserve mechanisms,maintain smooth emergency logistics channels,and improve efficient management of media and public opinion,so as to comprehensively improve overall resilience.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.