Liver fibrosis is a chronic liver injury resulting from factors like viral hepatitis, autoimmune hepatitis, non-alcoholic steatohepatitis, fatty liver disease, and cholestatic liver disease. Liver transplantation is currently the gold standard for treating severe liver diseases. However, it is limited by a shortage of donor organs and the necessity for lifelong immunosuppressive therapy. Mesenchymal stem cells (MSCs) can differentiate into various liver cells and enhance liver function when transplanted into patients due to their differentiation and proliferation capabilities. Therefore, it can be used as an alternative therapy for treating liver diseases, especially for liver cirrhosis, liver failure, and liver transplant complications. However, due to the potential tumorigenic effects of MSCs, researchers are exploring a new approach to treating liver fibrosis using extracellular vesicles (exosomes) secreted by stem cells. Many studies show that exosomes released by stem cells can promote liver injury repair through various pathways, contributing to the treatment of liver fibrosis. In this review, we focus on the molecular mechanisms by which stem cell exosomes affect liver fibrosis through different pathways and their potential therapeutic targets. Additionally, we discuss the advantages of exosome therapy over stem cell therapy and the possible future directions of exosome research, including the prospects for clinical applications and the challenges to be overcome.

Liver fibrosis is a chronic liver injury resulting from factors like viral hepatitis, autoimmune hepatitis, non-alcoholic steatohepatitis, fatty liver disease, and cholestatic liver disease. Liver transplantation is currently the gold standard for treating severe liver diseases. However, it is limited by a shortage of donor organs and the necessity for lifelong immunosuppressive therapy. Mesenchymal stem cells (MSCs) can differentiate into various liver cells and enhance liver function when transplanted into patients due to their differentiation and proliferation capabilities. Therefore, it can be used as an alternative therapy for treating liver diseases, especially for liver cirrhosis, liver failure, and liver transplant complications. However, due to the potential tumorigenic effects of MSCs, researchers are exploring a new approach to treating liver fibrosis using extracellular vesicles (exosomes) secreted by stem cells. Many studies show that exosomes released by stem cells can promote liver injury repair through various pathways, contributing to the treatment of liver fibrosis. In this review, we focus on the molecular mechanisms by which stem cell exosomes affect liver fibrosis through different pathways and their potential therapeutic targets. Additionally, we discuss the advantages of exosome therapy over stem cell therapy and the possible future directions of exosome research, including the prospects for clinical applications and the challenges to be overcome.

Liver fibrosis is a chronic liver injury resulting from factors like viral hepatitis, autoimmune hepatitis, non-alcoholic steatohepatitis, fatty liver disease, and cholestatic liver disease. Liver transplantation is currently the gold standard for treating severe liver diseases. However, it is limited by a shortage of donor organs and the necessity for lifelong immunosuppressive therapy. Mesenchymal stem cells (MSCs) can differentiate into various liver cells and enhance liver function when transplanted into patients due to their differentiation and proliferation capabilities. Therefore, it can be used as an alternative therapy for treating liver diseases, especially for liver cirrhosis, liver failure, and liver transplant complications. However, due to the potential tumorigenic effects of MSCs, researchers are exploring a new approach to treating liver fibrosis using extracellular vesicles (exosomes) secreted by stem cells. Many studies show that exosomes released by stem cells can promote liver injury repair through various pathways, contributing to the treatment of liver fibrosis. In this review, we focus on the molecular mechanisms by which stem cell exosomes affect liver fibrosis through different pathways and their potential therapeutic targets. Additionally, we discuss the advantages of exosome therapy over stem cell therapy and the possible future directions of exosome research, including the prospects for clinical applications and the challenges to be overcome.

ObjectiveTo analyze the incidence and trend of stroke in Beilun District, so as to provide evidence for identifying influencing factors and reducing stroke incidence. MethodsStroke cases from 2012 to 2023 were extracted from the Ningbo Chronic Disease Collaborative Management System. Population information of Beilun District during the same period was also collected. The annual incidence and trends of stroke were analyzed. ResultsFrom 2012 to 2023, the age-standardized incidence rate of stroke in Beilun District, Ningbo City was 317.68/100 000, showing an increasing trend with an average annual percentage change (AAPC) of 2.267% (P=0.034). Among all subdistricts in Beilun District, two showed a downward trend in incidence, while the rest showed an upward trend. The crude incidence rate of stroke was significantly higher in males than that in females (P<0.001). The age-standardized incidence rate in males was 406.08/100 000, showing an increasing trend (AAPC=3.956%, P<0.001). The incidence of stroke also showed an increasing trend in the following age groups: 30‒<45 years (AAPC=6.340%, P=0.004), 45‒<60 years (AAPC=4.997%, P<0.001), and 60‒<75 years (AAPC=3.282%, P=0.042). Across all years, males had higher crude incidence rates in both ischemic and hemorrhagic stroke than females (P<0.05). The age-standardized incidence rate of ischemic stroke showed a rising trend in both males and the general population (male AAPC=4.905%, P<0.001; overall population AAPC=3.065%, P=0.001). ConclusionThe age-standardized incidence of stroke in Beilun District is on the rise, with higher crude incidence rate in males than that in females. The onset age of stroke is gradually declining. The age-standardized incidence rate of male ischemic stroke shows a clear upward trend.

Objective To verify the genetic characteristics associated with gastric cancer,and to propose a hybrid feature selection method for identifying target genes,further analyzing their significance and establishing a new diagnostic prediction model.Methods Analysis of variance in bioinformatics was performed on the original gastric cancer data,and then machine learning methods such as random forest,recursive feature elimination of support vector machine,and LASSO algorithm were used to screen gastric cancer associated genes,and the intersection of results was taken as the key gene set.The key genes were identified and verified through enrichment analysis.The diagnosis and prediction models based on 8 kinds of machine learning classification algorithms such as multi-layer perceptron,logistic regression and decision tree,were constructed using the key genes.Results The key genes selected by the hybrid feature selection method were closely related to the tumorigenesis and development.Eight key genes(TXNDC5,BMP8A,ONECUT2,COL10A1,JCHAIN,INHBA,LCTL and TRIM59)were identified as potential markers of good diagnostic efficacy in gastric cancer.The ROC curve and accuracy results demonstrated that among the 8 classification models,MLP is the best gastric cancer prediction model,with an accuracy of 97.77%,which was 3.83%higher than that of Xgboost gastric cancer prediction model.Conclusion The study identifies 8 key genes for the diagnosis and prevention of gastric cancer,and establishes the optimal prognosis model.

Tumors are serious diseases threatening human health,and the early diagnosis is essential to improve treatment success and patient survival.The study of tumor gene expression data has become a major tool for revealing tumor disease mechanisms,in which artificial intelligence plays an important role.The potential advantages of supervised learning,unsupervised learning and deep learning in tumor prediction and classification are explored from the perspective of machine learning methods.Special attention is paid to the impact of feature selection algorithms on gene screening and their importance in high-dimensional gene expression data.By providing a comprehensive overview of the application and development of artificial intelligence in the analysis of tumor gene expression data,the study aims to provide an outlook for future research directions and promote further development.

Objective To observe the reproducibility of radiomics feature(RF)extracted from virtual monoenergetic image(VMI)of rabbit VX2 hepatoma models obtained with 3 different dual-energy CT(DECT)systems,and to explore relationship of reproducibility and diagnostic performance of RF.Methods Fifteen rabbits with VX2 hepatoma were randomly divided into 3 groups(each n=5).Contrast-enhanced abdominal CT scanning under volume CT dose index(CTDIvol)levels of 6,9 and 12 mGy were performed with dual-source DECT(dsDECT),rapid kV switching DECT(rsDECT)and dual-layer detector DECT(dlDECT),respectively.VMI were reconstructed at 10 keV increments from 40 to 140 keV.RF were extracted from VMI,the reproducibility was assessed using intra-class correlation coefficient(ICC),and those with ICC≥0.8 were considered as reproducible RF.The percentage of reproducible features(denoted by R)were compared among different scanner pairings and different CTDIvol levels.Within each CTDIvol group,the reconstruction energy levels yielding the maximum number(denoted by N)of common RF across different scanner pairings were identified.The receiver operating characteristic(ROC)curve was drawn,the area under the curve(AUC)was calculated,and the diagnostic efficacies of reproducible RF and other RF were compared under optimal reproducible conditions.Spearman correlation coefficient between ICC and the corresponding AUC of RF were calculated.Results RrsDECT-dsDECT(6.45％,95％CI[2.36％,8.87％])was higher than RdlDECT-dsDECT(0.72％,95％CI[0.15％,1.79％])and RrsDECT-dlDECT(1.43％,95％CI[0.60％,4.06％])(all adjusted P＜0.05),R9mGy(3.70％,95％CI[1.31％,5.73％])and R12mGy(2.63％,95％CI[0.60％,6.69％])were higher than R6mGy(1.31％,95％CI[0.12％,1.55％])(all adjusted P＜0.05).The optimal reproducible reconstruction energy levels of RF under CTDIvol of 6,9 and 12 mGy concentrated at 50-70 keV.AUC of reproducible RFs were higher than of other RF(all adjusted P＜0.05)and had certain correlation with the reproducibility(rs=0.102-0.516,P＜0.05).Conclusion The reproducibility of RF extracted from contrast-enhanced VMI CT images of rabbit VX2 hepatoma models associated with DECT scanner,CTDIvol level and reconstruction energy level.RF with higher reproducibility might have better diagnostic performance.

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.

Objective:The transjugular or transfemoral approach is used as a common method for hepatic venous pressure gradient (HVPG) measurement in current practice. This study aims to confirm the safety and effectiveness of measuring HVPG via the forearm venous approach.Methods:Prospective recruitment was conducted for patients with cirrhosis who underwent HVPG measurement via the forearm venous approach at six hospitals in China and Japan from September 2020 to December 2020. Patients' clinical baseline information and HVPG measurement data were collected. The right median cubital vein or basilic vein approach for all enrolled patients was selected. The HVPG standard process was used to measure pressure. Research data were analyzed using SPSS 22.0 statistical software. Quantitative data were used to represent medians (interquartile ranges), while qualitative data were used to represent frequency and rates. The correlation between two sets of data was analyzed using Pearson correlation analysis.Results:A total of 43 cases were enrolled in this study. Of these, 41 (95.3%) successfully underwent HVPG measurement via the forearm venous approach. None of the patients had any serious complications. The median operation time for HVPG detection via forearm vein was 18.0 minutes (12.3~38.8 minutes). This study confirmed that HVPG was positively closely related to Child-Pugh score ( r = 0.47, P = 0.002), albumin-bilirubin score ( r = 0.37, P = 0.001), Lok index ( r = 0.36, P = 0.02), liver stiffness ( r = 0.58, P = 0.01), and spleen stiffness ( r = 0.77, P = 0.01), while negatively correlated with albumin ( r = -0.42, P = 0.006). Conclusion:The results of this multi-centre retrospective study suggest that HVPG measurement via the forearm venous approach is safe and feasible.

Objective To study the relationship between peripheral blood Toll like receptor 4(TLR4),interleukin-1β(IL-1β)and neutrophil-to-lymphocyte ratio(NLR)and the progression and prognosis of acute pancreatitis(AP).Methods A total of 250 patients with AP were divided into the mild group(121 cases),the moderately severe group(89 cases)and the severe group(40 cases)according to the disease severity.Patients were divided into the poor prognosis group(33 cases)and the good prognosis group(217 cases)based on the prognosis after 5 days of treatment.Peripheral blood levels of TLR4,IL-1β and NLR were compared at different time points,different conditions and different prognosis in patients.The correlation of peripheral blood levels of TLR4,IL-1β and NLR,Ranson score and amylase were analyzed by Pearson correlation analysis.The value of each indicator in the diagnosis of severe AP was analyzed using ROC curve,and multivariate Logistic regression analysis was conducted to identify the prognostic risk factors.Results TLR4,IL-1β and NLR levels in AP patients were higher 24 h after admission than 48 h and 72 h after admission(P＜0.05).Peripheral blood TLR4 and IL-1β levels in AP patients at 24 h after admission increased with the condition became worse.NLR level was higher in the severe group than that in the moderately group or the mild group(P＜0.05).Peripheral blood TLR4,IL-1β and NLR levels in AP patients 24 h after admission were positively correlated with Ranson score at 48 h after admission and amylase level at 24 h after admission(P＜0.05).The area under ROC curve,sensitivity and specificity of the combination of TLR4,IL-1β and NLR at 24 h after admission for predicting severe AP were 0.895,84.53%and 81.69%.Peripheral blood TLR4,IL-1β and NLR levels 24 h after admission were higher in the poor prognosis group than those in the good prognosis group(P＜0.05).Multivariate Logistic regression analysis showed that elevated TLR4,IL-1β and NLR at 24 h after admission were independent risk factors for poor prognosis of patients with AP(P＜0.05).Conclusion Peripheral blood TLR4,IL-1β and NLR in patients with AP are closely related to disease progression and prognosis.Therefore,they can be taken as important monitoring indicators.