ObjectiveTo investigate the induction of ferroptosis by polyphyllin Ⅱ （PPⅡ） in hepatocellular carcinoma HepG2 cells and its underlying mechanism. MethodThe effect of PPⅡ （0， 1.5， 3.0， 4.5， 6.0， 9.0， 18.0 mg·L^-1） on the in vitro proliferation of HepG2 cells was assessed using the methyl thiazolyl tetrazolium （MTT） assay. Colony formation ability of HepG2 cells was evaluated through a colony formation assay. Cell migration ability was assessed via a scratch assay. Lactate dehydrogenase （LDH） content in HepG2 cells was measured using a kit. Reactive oxygen species （ROS） levels in HepG2 cells were observed using a fluorescence inverted microscope. Malondialdehyde （MDA）， glutathione （GSH）， and free Fe²⁺ content in HepG2 cells were detected using respective kits. The mitochondrial ultrastructure in HepG2 cells was observed by transmission electron microscopy. The expression of ferroptosis-related proteins p53， solute carrier family 7 member 11 （SLC7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， and transferrin receptor 1 （TFR1） in HepG2 cells was detected using Western blot. ResultCompared with the control group， the PPⅡ treatment groups showed significantly decreased survival rate of HepG2 cells in a dose-dependent manner （P<0.01）， significantly reduced number of cell colonies （P<0.01）， significantly shortened scratch healing distance， inverse correlation of the migration distance with drug concentration （P<0.01）， significantly increased LDH leakage in cells （P<0.01）， significantly enhanced relative fluorescence intensity of intracellular ROS， and significantly increased accumulation of lipid peroxide MDA （P<0.01）， decreased intracellular GSH content with increasing drug concentration （P<0.01）， and significantly enhanced fluorescence intensity of FeRhoNox-1 in cells （P<0.01）. Moreover， cells exhibited vacuolation， and mitochondria showed significant shrinkage with reduced or even disappeared cristae. Compared with the results in the control group， the expression of p53， ACSL4， and TFR1 proteins significantly increased， while the expression of SLC7A11 and GPX4 proteins significantly decreased in the PPⅡ treatment groups （P<0.05）. ConclusionIn summary， PPⅡ induces ferroptosis in HepG2 cells by regulating the p53/SLC7A11/GPX4 signaling axis， promoting ACSL4 expression and Fe³⁺ uptake， leading to an imbalance in the antioxidant system.

This article elaborates on the complex cross-talk and close relationship between muscles and bones involved in this disease,as well as its pathogenesis.It also summarizes that the difficulty of its treatment lies in the need to simultaneously consider both muscles and bones.And elaborated on the key role of the Hedgehog signaling pathway in embryonic development,tissue morphology establishment,and human tissue regeneration and repair.Investigated the remodeling effect of the Hedgehog signaling pathway on skeletal muscle from three aspects:Proliferation and differentiation of muscle stem cells,precursor cell and muscle fiber generation,inhibition of inflammation,and regulation of immunity;this article elucidates the role of the Hedgehog signaling pathway in bone reconstruction from two aspects.

Objective This study investigated the impact of occupational mercury(Hg)exposure on human gene transcription and expression,and its potential biological mechanisms. Methods Differentially expressed genes related to Hg exposure were identified and validated using gene expression microarray analysis and extended validation.Hg-exposed cell models and PTEN low-expression models were established in vitro using 293T cells.PTEN gene expression was assessed using qRT-PCR,and Western blotting was used to measure PTEN,AKT,and PI3K protein levels.IL-6 expression was determined by ELISA. Results Combined findings from gene expression microarray analysis,bioinformatics,and population expansion validation indicated significant downregulation of the PTEN gene in the high-concentration Hg exposure group.In the Hg-exposed cell model(25 and 10 μmol/L),a significant decrease in PTEN expression was observed,accompanied by a significant increase in PI3K,AKT,and IL-6 expression.Similarly,a low-expression cell model demonstrated that PTEN gene knockdown led to a significant decrease in PTEN protein expression and a substantial increase in PI3K,AKT,and IL-6 levels. Conclusion This is the first study to report that Hg exposure downregulates the PTEN gene,activates the PI3K/AKT regulatory pathway,and increases the expression of inflammatory factors,ultimately resulting in kidney inflammation.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

AIM To study the phenylethanoid glycosides from Verbenae Herba.METHODS The 80%ethanol extract from Verbenae Herba was isolated and purified by silica gel,Sephadex LH-20,TLC and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Nine compounds were isolated and identified as verbofficoside A(1),cistanoside D(2),epimeredinoside A(3),verbascoside(4),isoverbascoside(5),cistanoside C(6),cistanoside F(7),decaffeoylacteoside(8),jionoside C(9).CONCLUSION Compound 1 is a new compound.Compounds 3 and 6-9 are isolated from this plant for the first time.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-positive bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-positive bacteria from blood cultures in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:A total of 3 163 strains of Gram-positive pathogens were collected from 51 member units，and the top five bacteria were Staphylococcus aureus（ n=1 147，36.3%），coagulase-negative Staphylococci（ n=928，29.3%）， Enterococcus faecalis（ n=369，11.7%）， Enterococcus faecium（ n=296，9.4%）and alpha-hemolyticus Streptococci（ n=192，6.1%）. The detection rates of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）were 26.4%（303/1 147）and 66.7%（619/928），respectively. No glycopeptide and daptomycin-resistant Staphylococci were detected. The sensitivity rates of Staphylococcus aureus to cefpirome，rifampin，compound sulfamethoxazole，linezolid，minocycline and tigecycline were all >95.0%. Enterococcus faecium was more prevalent than Enterococcus faecalis. The resistance rates of Enterococcus faecium to vancomycin and teicoplanin were both 0.5%（2/369），and no vancomycin-resistant Enterococcus faecium was detected. The detection rate of MRSA in southern China was significantly lower than that in other regions（ χ2=14.578， P=0.002），while the detection rate of MRCNS in northern China was significantly higher than that in other regions（ χ2=15.195， P=0.002）. The detection rates of MRSA and MRCNS in provincial hospitals were higher than those in municipal hospitals（ χ2=13.519 and 12.136， P<0.001）. The detection rates of MRSA and MRCNS in economically more advanced regions（per capita GDP≥92 059 Yuan in 2022）were higher than those in economically less advanced regions（per capita GDP<92 059 Yuan）（ χ2=9.969 and 7.606， P=0.002和0.006）. Conclusions:Among the Gram-positive pathogens causing bloodstream infections in China， Staphylococci is the most common while the MRSA incidence decreases continuously with time；the detection rate of Enterococcus faecium exceeds that of Enterococcus faecalis. The overall prevalence of vancomycin-resistant Enterococci is still at a low level. The composition ratio of Gram-positive pathogens and resistant profiles varies slightly across regions of China，with the prevalence of MRSA and MRCNS being more pronounced in provincial hospitals and areas with a per capita GDP≥92 059 yuan.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.