ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

Objective:To analyze the clinical data of patients with severe fever with thrombocytopenia syndrome（SFTS）in Linyi city of Shandong province from 2023 to 2024，analyze the related factors affecting the prognosis，improve the understanding of the disease and reduce its mortality..Methods:The data of 36 SFTS patients diagnosed and admitted to Linyi People's Hospital from May 2023 to August 2024 were retrospectively analyzed. According to the clinical outcomes of the patients，they were divided into a survival group（n=30）and a death group（n=6）. The clinical data and laboratory test results of the two groups were analyzed to evaluate the risk factors related to prognosis.Results:The median age in the death group was 68.33 years old，and that in the survival group was 63.96 years old，with no statistically significant difference. All patients had fever，22 had fatigue and poor appetite，and 21 had muscle aches and other systemic symptoms. some were prone to general symptoms such as fatigue，poor appetite，and muscle soreness. All patients in the death group had neurological symptoms such as headache and consciousness disorders. The levels of serum potassium，CRP，PCT，IL-6，ALT，AST，CK，CK-MB，LDH，α-HBDH，APTT，D-D，and viral load in the death group were higher than those in the survival group，with statistically significant differences（ t=-3.344， P=0.002； Z=-2.195， P=0.028； Z=-3.648， P=0.000； Z=-3.641， P=0.000； Z=-2.241， P=0.025； Z=-2.288， P=0.022； Z=-2.427， P=0.015； Z=-2.007， P=0.045； Z=-3.127， P=0.002； Z=-2.404， P=0.016； Z=-2.755， P=0.006； Z=-3.081， P=0.002； P<0.05）. The platelet count in the death group was lower than that in the survival group，and the difference was statistically significant（ Z=-3.292， P=0.001， P<0.05）. Multivariate Logistic regression analysis showed that patients with increased AST，CK，IL-6，APTT，D-dimer and decreased platelet count had an increased risk of death. Fungal infections occurred in 15 cases，including 5 cases of Candida albicans，3 cases of Candida parapsilosis，and 7 cases of Aspergillus. All patients in the death group had fungal infections，all of whom had Aspergillus infections. Conclusion:SFTS patients often have fever，fatigue，and muscle soreness，and critically ill patients are prone to neurological symptoms. Patients with elevated AST，CK，IL-6，APTT，D-D，viral load，and decreased platelet count in the course of the disease often indicate poor prognosis and should be closely monitored. In addition，critically ill patients are prone to fungal infection.

The elimination of biofilms is a crucial step in controlling hospital-acquired infections.Once biofilms colonize luminal instruments,it is difficult to remove them using traditional disinfection methods.Conventional disinfection approaches now face a series of challenges,including microbial resistance,corrosiveness,cytotoxicity,residual disinfection byproducts,and environmental pollution.Therefore,developing novel disinfection technologies specifically targeting biofilm removal is vitally important.New disinfection technologies,such as slightly acidic electrolyzed water,plasma technology,surface modification techniques,nanomaterial-based disinfection,bacteriophage disinfection,and enzymatic disinfection,are constantly emerging.These technologies exhibit excellent performance against biofilms by leveraging the synergistic effects of multiple mechanisms,including the reactive oxygen species(ROS)burst,photocatalytic oxidation,physical disruption,and biological targeting.This review summarizes the characteristics,underlying mechanisms,and potential application scenarios of these novel disinfection technologies,with a particular focus on their effects against biofilms formed by common pathogenic bacteria on surfaces in hospital settings.It aims to provide a reference basis for the practical application and translation of these disinfection technologies and the development of new disinfection strategies.

Objective To evaluate the practical application of the Media Fill Test(MFT)in assessing aseptic compounding competency of personnel in Pharmacy Intravenous Admixture Services(PIVAS).Methods A multicenter controlled study was conducted across six tertiary hospitals(center ①-⑥)in China.Participants were divided into an inexperienced group(Group A,n=118)and an experienced group(Group B,n=118),each performing five MFT operations.Positive controls validated medium efficacy.Contamination rates and pass rates were analyzed using chi-square and Fisher's exact tests.Results Valid samples included 584 for Group A and 588 for Group B.The sample pass rate was 66.78%(390/584)in Group A and 91.67%(539/588)in Group B,while personnel pass rates were 46.15%(54/117)and 80.51%(95/118),respectively,with significant intergroup differences(both P<0.01).All centers except Center ⑥ showed significantly higher pass rates in Group B(all P<0.05).Conclusion MFT effectively differentiates technical proficiency levels and is suitable for training evaluation of novice PIVAS staff.

Objective:To clarify the changes in incidence and mortality of various cancers based on analysis on registration data of malignant tumor incidence and mortality from Dehui City and Yanji City in Jilin Province.Methods:The incidence and mortality data of malignant tumors from 2009 to 2016 in Dehui City and Yanji City in Jilin Province,were collected from the Chinese Cancer Registry Annual Report published by the National Cancer Center.The number of cases,deaths,crude incidence rate,crude mortality rate,age-standardized incidence rate(ASIR),age-standardized mortality rate(ASMR),and annual percentage change(APC)of the malignant tumors were analyzed by cancer sites and genders.Results:From 2009 to 2016,the CIR of malignant tumors in Dehui City(APC=1.2%,P=0.019)and Yanji City(APC=3.6%,P=0.058)showed an increasing trend.After standard population age adjustment,the ASIR in males in Dehui City showed a significant decline(APC=-5.7%,P=0.021),while the ASIR in females exhibited an overall downward trend,but the difference was not significant(APC=-2.2%,P=0.111).In Yanji City,the ASIR in males(APC=-1.4%,P=0.535)and females(APC=0.0%,P=0.988)showed no significant changes.The CMR of malignant tumors in Dehui City(APC=1.9%,P=0.001)and Yanji City(APC=5.9%,P=0.001)showed a continuous upward trend.After age-standardization,the ASMR in males(APC=-3.1%,P=0.100)and females(APC=-4.2%,P=0.053)in Dehui City,as well as in males(APC=-1.3%,P=0.438)in Yanji City,showed a slight downward trend.Although the ASMR in females in Yanji City showed a slight increase,the difference was not statistically significant(APC=0.5%,P=0.838).In 2016,the most common malignant tumor in terms of both incidence and mortality in Dehui City was lung cancer,with a CIR of 60.76/100 000 and a CMR of 46.96/100 000.In Yanji City,the most common malignant tumor was liver cancer,with a CIR of 49.04/100 000 and a CMR of 51.09/100 000.Conclusion:Lung cancer,liver cancer,and gastric cancer are the major malignant tumors threatening residents in Dehui City,Yanji City,and even the entire Jilin Province,and should be prioritized in cancer prevention and control efforts.Early diagnosis and treatment should be strengthened.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.