1.Shaoyaotang Regulates TLR4/MyD88/NF-κB Signaling Pathway to Protect Intestinal Mucosal Barrier in Ulcerative Colitis
Dongsheng WU ; Yu ZHANG ; Wenjing QUAN ; Wanqing XIONG ; Bo ZOU ; Youwei XIAO ; Ruoru HUANG ; Yan GONG ; Hui CAO
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(13):69-75
ObjectiveTo investigate the role of the Toll-like receptor 4 (TLR4)/myeloid differentiation factor 88 (MyD88)/nuclear factor-κB (NF-κB) signaling pathway in intestinal mucosal barrier damage in ulcerative colitis, as well as the intervention mechanism of Shaoyaotang. MethodsSixty SD rats were allocated into a blank group, a model group, a mesalazine (0.42 g·kg-1) group, and low-, medium-, and high-dose (11.1, 22.2, 44.4 g·kg-1, respectively) Shaoyaotang groups. A model of ulcerative colitis was induced by 2,4,6-trinitrobenzenesulfonic acid (TNBS). After successful modeling, rats were administrated with corresponding agents via gavage for 7 days. Changes in colon length and colon weight were observed. Hematoxylin-eosin staining was performed to examine the pathological changes of the colon, and immunohistochemistry was employed to detect the expression of the inflammatory cytokine interleukin-8 (IL-8), cyclooxygenase-2 (COX-2), junction adhesion molecule-1 (JAM-1), and claudin-1 in the colon. Western blot analysis was performed to determine the protein levels of TLR4, MyD88, and NF-κB in the colon. ResultsCompared with the blank group, the model group showed elevated DAI score (P<0.01), reduced colon length and colon weight (P<0.01), down-regulated protein levels of JAM-1 and claudin-1 (P<0.01), and up-regulated protein levels of IL-8, COX-2, TLR4, MyD88, and NF-κB p65 (P<0.01) in the colon tissue. Compared with the model group, each treatment group showed decreased DAI score (P<0.05, P<0.01), increased colon length and colon weight (P<0.05, P<0.01), up-regulated protein levels of JAM-1 and claudin-1 (P<0.01), and down-regulated protein levels of IL-8, COX-2, TLR4, MyD88, and NF-κB p65 (P<0.01) in the colon tissue. ConclusionShaoyaotang alleviates intestinal inflammation and intestinal mucosal damage to protect intestinal barrier integrity by regulating the TLR4/MyD88/NF-κB signaling pathway.
2.Preliminary study on the biological role of EF-hand domain-containing protein 2 in hepatocellular carcinoma
Yanmei ZHANG ; Xiao LI ; Xueqiang JIA ; Juanzi LIU ; Wanqing LI ; Junfeng XUAN ; Shiyu FENG ; Zhaohui SUN ; Weiyun ZHANG
Chinese Journal of Preventive Medicine 2025;59(8):1224-1231
This study investigates the expression pattern and functional significance of EF-hand domain-containing protein 2 (EFHD2) in hepatocellular carcinoma (HCC), with particular focus on its regulatory effects on tumor proliferation, migration, and invasion. Cellular experimental study was completed from June 2024 to January 2025 in the Basic Laboratory of the General Hospital of Southern Theater Command. TCGA database to determine EFHD2 expression and its clinicopathological correlations. GSCA database to assess methylation patterns and immune infiltration. Model of transient overexpression and knockdown of EFHD2 was constructed in hepatocellular carcinoma cells Hep3B, then RT-qPCR and Western blot were applied to verify the transfection efficiency. CCK-8 and colony formation assays for proliferation assessment, Transwell chambers for migration/invasion quantification. Protein-protein interaction networks were constructed via STRING, followed by GO/KEGG enrichment analysis. Statistical analysis was performed using the two independent samples t-test. The results showed that EFHD2 demonstrated significant upregulation in HCC tissues versus normal controls ( P<0.05). Elevated EFHD2 expression correlated with advanced clinical stage ( P<0.05) and poor differentiation ( P<0.05). In the CCK-8 assay, the EFHD2 overexpression group demonstrated significantly higher cell viability than the control group, as evidenced by 450 nm relative absorbance values on Day 1 (0.529±0.019 vs. 0.515±0.016, F=0.041, P=0.320), Day 2 (1.356±0.019 vs. 1.094±0.042, F=3.833, P<0.001), Day 3 (2.817±0.049 vs. 2.143±0.124, F=3.833, P<0.001), and Day 4 (3.848±0.015 vs. 3.430±0.021, F=0.469, P<0.001). The EFHD2 knockdown group showed reduced cell viability compared to controls: Day 1 (0.541±0.020 vs. 0.552±0.015, F=0.098, P=0.423), Day 2 (1.154±0.009 vs. 1.326±0.029, F=2.485, P<0.001), Day 3 (2.453±0.041 vs. 2.653±0.031, F=0.479, P<0.001), and Day 4 (3.685±0.038 vs. 3.836±0.021, F=6.804, P<0.001). In colony formation assays, the overexpression group displayed a significant increase in colony numbers (254.667±23.861 vs. 186.000±16.703, F=0.865, P=0.015), whereas the knockdown group exhibited decreased colony formation (229.000±24.637 vs. 306.667±36.501, F=0.988, P=0.038). In Transwell assays, the EFHD2 overexpression group revealed enhanced migratory capacity [ (605.000±72.670) cells vs. (472.667±28.095) cells, F=2.462, P=0.042] and invasive potential [(767.333±21.221) cells vs. (414.333±16.623) cells, F=0.331, P<0.001]. The knockdown group showed attenuated migration [(311.000±71.084) cells vs. (479.667±50.846) cells, F=0.718, P=0.029] and invasion [(247.667±48.263) cells vs. (345.667±32.130) cells, F=0.727, P=0.043] compared to controls. The network of EFHD2-interacting proteins was further constructed by the STRING database, and the GO and KEGG analysis were used to perform bioinformatics analysis reveal that EFHD2 is mainly involved in actin cytoskeleton regulation. In conclusion, EFHD2 is highly expressed in HCC and is involved in the process of proliferation, migration and invasion of HCC.
3.Preliminary study on the biological role of EF-hand domain-containing protein 2 in hepatocellular carcinoma
Yanmei ZHANG ; Xiao LI ; Xueqiang JIA ; Juanzi LIU ; Wanqing LI ; Junfeng XUAN ; Shiyu FENG ; Zhaohui SUN ; Weiyun ZHANG
Chinese Journal of Preventive Medicine 2025;59(8):1224-1231
This study investigates the expression pattern and functional significance of EF-hand domain-containing protein 2 (EFHD2) in hepatocellular carcinoma (HCC), with particular focus on its regulatory effects on tumor proliferation, migration, and invasion. Cellular experimental study was completed from June 2024 to January 2025 in the Basic Laboratory of the General Hospital of Southern Theater Command. TCGA database to determine EFHD2 expression and its clinicopathological correlations. GSCA database to assess methylation patterns and immune infiltration. Model of transient overexpression and knockdown of EFHD2 was constructed in hepatocellular carcinoma cells Hep3B, then RT-qPCR and Western blot were applied to verify the transfection efficiency. CCK-8 and colony formation assays for proliferation assessment, Transwell chambers for migration/invasion quantification. Protein-protein interaction networks were constructed via STRING, followed by GO/KEGG enrichment analysis. Statistical analysis was performed using the two independent samples t-test. The results showed that EFHD2 demonstrated significant upregulation in HCC tissues versus normal controls ( P<0.05). Elevated EFHD2 expression correlated with advanced clinical stage ( P<0.05) and poor differentiation ( P<0.05). In the CCK-8 assay, the EFHD2 overexpression group demonstrated significantly higher cell viability than the control group, as evidenced by 450 nm relative absorbance values on Day 1 (0.529±0.019 vs. 0.515±0.016, F=0.041, P=0.320), Day 2 (1.356±0.019 vs. 1.094±0.042, F=3.833, P<0.001), Day 3 (2.817±0.049 vs. 2.143±0.124, F=3.833, P<0.001), and Day 4 (3.848±0.015 vs. 3.430±0.021, F=0.469, P<0.001). The EFHD2 knockdown group showed reduced cell viability compared to controls: Day 1 (0.541±0.020 vs. 0.552±0.015, F=0.098, P=0.423), Day 2 (1.154±0.009 vs. 1.326±0.029, F=2.485, P<0.001), Day 3 (2.453±0.041 vs. 2.653±0.031, F=0.479, P<0.001), and Day 4 (3.685±0.038 vs. 3.836±0.021, F=6.804, P<0.001). In colony formation assays, the overexpression group displayed a significant increase in colony numbers (254.667±23.861 vs. 186.000±16.703, F=0.865, P=0.015), whereas the knockdown group exhibited decreased colony formation (229.000±24.637 vs. 306.667±36.501, F=0.988, P=0.038). In Transwell assays, the EFHD2 overexpression group revealed enhanced migratory capacity [ (605.000±72.670) cells vs. (472.667±28.095) cells, F=2.462, P=0.042] and invasive potential [(767.333±21.221) cells vs. (414.333±16.623) cells, F=0.331, P<0.001]. The knockdown group showed attenuated migration [(311.000±71.084) cells vs. (479.667±50.846) cells, F=0.718, P=0.029] and invasion [(247.667±48.263) cells vs. (345.667±32.130) cells, F=0.727, P=0.043] compared to controls. The network of EFHD2-interacting proteins was further constructed by the STRING database, and the GO and KEGG analysis were used to perform bioinformatics analysis reveal that EFHD2 is mainly involved in actin cytoskeleton regulation. In conclusion, EFHD2 is highly expressed in HCC and is involved in the process of proliferation, migration and invasion of HCC.
4.Analysis of early changes in lymphocyte subpopulations after liver transplantation and their correlation with clinical manifestations
Wanqing LI ; Weiyun ZHANG ; Xiao LI ; Yanmei ZHANG ; Zhaohui SUN
Chinese Journal of Preventive Medicine 2024;58(5):679-685
This study aimed to investigate the differences in peripheral blood lymphocyte subsets among patients with different immune statuses in the early postoperative period after liver transplantation, as well as the dynamic changes during the early post-transplantation period. A retrospective study was conducted, selecting a total of 82 patients who underwent liver transplantation at the General Hospital of PLA Southern Theater Command from January, 2018 to December, 2023. Based on the patients′ postoperative immune status, they were categorized into stable group ( n=40), infection group ( n=21), and rejection group ( n=21). Peripheral blood samples of 2-3 ml were collected from patients at weeks 1 to 4 postoperatively, and flow cytometry was employed to measure the absolute values of peripheral blood lymphocyte subsets. For metric data conforming to normal distribution and homogeneity of variance, multiple group comparisons were conducted using ANOVA and Bonferroni multiple comparisons; for non-normally distributed data, the Kruskal Wallis test was used. Friedman test was used to compare different time periods within 4 weeks after liver transplantation. The results showed that there were no statistically significant differences in the absolute values of lymphocyte subsets among the three groups in the first week after liver transplantation ( P>0.05); however, significant differences were observed in the absolute values of lymphocyte subsets among the three groups in the second, third, and fourth weeks postoperatively ( P<0.05). In the second week, the rejection group showed significantly higher absolute counts of T cells, CD4 +T cells, CD8 +T cells, NK cells, and B cells compared to the infection group (585.0 vs. 199.0; 324.0 vs.113.0; 188.0 vs.56.0; 57.0 vs.11.0; 145.0 vs.65.0 cells/μl), with statistically significant differences ( Z=-3.972, P<0.001; Z=-3.590, P=0.001; Z=-3.978, P<0.001; Z=-3.072, P=0.006; Z=-2.472, P=0.040). In the third week, the rejection group showed significantly higher absolute counts of T cells, CD4 +T cells, and CD8 +T cells compared to the infection group (660.0 vs.216.0; 350.0 vs.123.0; 184.0 vs.76.0 cells/μl), with statistically significant differences ( Z=-3.019, P=0.008; Z=-3.492, P=0.001; Z=-2.845, P=0.013). In the fourth week, the rejection group showed significantly higher absolute counts of T cells, CD4 +T cells, CD8 +T cells, and B cells compared to the infection group (690.0 vs.273.0; 405.0 vs.168.0; 214.0 vs.96.0; 117.0 vs.48.0 cells/μl), with statistically significant differences ( Z=-3.379, P=0.002; Z=-3.068, P=0.006; Z=-3.007, P=0.0086; Z=-2.330, P=0.020). Within 4 weeks after liver transplantation, the absolute values of T cells, CD8 +T cells, and NK cells in the fourth week were higher than those in the first week, with statistically significant differences ( Z=-3.825, P=0.001; Z=-3.466, P=0.003; Z=-3.526, P=0.003); however, the absolute values of B cells showed an overall decreasing trend, and were significantly lower in the fourth week than in the first and second weeks, with statistically significant differences ( Z=3.705, P=0.001; Z=2.630, P=0.009). The changes in lymphocyte subset absolute values in the rejection group were more significant than those in the infection group, with T cells, CD4 +T cells, and CD8 +T cells showing significant increases in the second, third, and fourth weeks postoperatively compared with the first week, with statistically significant differences ( Z=-3.466, P=0.003; Z=-4.661, P<0.001; Z=-5.020, P<0.001; Z=-2.749, P=0.036; Z=-4.422, P<0.001; Z=-4.542, P<0.001; Z=-3.466, P=0.003; Z=-3.765, P=0.001; Z=-4.482, P<0.001); NK cell absolute values in the third and fourth weeks postoperatively were significantly higher than those in the first week, with statistically significant differences ( Z=-2.570, P=0.061; Z=-3.765, P=0.001). In summary, monitoring the differences and dynamic changes of lymphocyte subsets in patients after liver transplantation may have certain guiding significance for evaluating the immune function status of patients and adjusting treatment plans.
5.Analysis of early changes in lymphocyte subpopulations after liver transplantation and their correlation with clinical manifestations
Wanqing LI ; Weiyun ZHANG ; Xiao LI ; Yanmei ZHANG ; Zhaohui SUN
Chinese Journal of Preventive Medicine 2024;58(5):679-685
This study aimed to investigate the differences in peripheral blood lymphocyte subsets among patients with different immune statuses in the early postoperative period after liver transplantation, as well as the dynamic changes during the early post-transplantation period. A retrospective study was conducted, selecting a total of 82 patients who underwent liver transplantation at the General Hospital of PLA Southern Theater Command from January, 2018 to December, 2023. Based on the patients′ postoperative immune status, they were categorized into stable group ( n=40), infection group ( n=21), and rejection group ( n=21). Peripheral blood samples of 2-3 ml were collected from patients at weeks 1 to 4 postoperatively, and flow cytometry was employed to measure the absolute values of peripheral blood lymphocyte subsets. For metric data conforming to normal distribution and homogeneity of variance, multiple group comparisons were conducted using ANOVA and Bonferroni multiple comparisons; for non-normally distributed data, the Kruskal Wallis test was used. Friedman test was used to compare different time periods within 4 weeks after liver transplantation. The results showed that there were no statistically significant differences in the absolute values of lymphocyte subsets among the three groups in the first week after liver transplantation ( P>0.05); however, significant differences were observed in the absolute values of lymphocyte subsets among the three groups in the second, third, and fourth weeks postoperatively ( P<0.05). In the second week, the rejection group showed significantly higher absolute counts of T cells, CD4 +T cells, CD8 +T cells, NK cells, and B cells compared to the infection group (585.0 vs. 199.0; 324.0 vs.113.0; 188.0 vs.56.0; 57.0 vs.11.0; 145.0 vs.65.0 cells/μl), with statistically significant differences ( Z=-3.972, P<0.001; Z=-3.590, P=0.001; Z=-3.978, P<0.001; Z=-3.072, P=0.006; Z=-2.472, P=0.040). In the third week, the rejection group showed significantly higher absolute counts of T cells, CD4 +T cells, and CD8 +T cells compared to the infection group (660.0 vs.216.0; 350.0 vs.123.0; 184.0 vs.76.0 cells/μl), with statistically significant differences ( Z=-3.019, P=0.008; Z=-3.492, P=0.001; Z=-2.845, P=0.013). In the fourth week, the rejection group showed significantly higher absolute counts of T cells, CD4 +T cells, CD8 +T cells, and B cells compared to the infection group (690.0 vs.273.0; 405.0 vs.168.0; 214.0 vs.96.0; 117.0 vs.48.0 cells/μl), with statistically significant differences ( Z=-3.379, P=0.002; Z=-3.068, P=0.006; Z=-3.007, P=0.0086; Z=-2.330, P=0.020). Within 4 weeks after liver transplantation, the absolute values of T cells, CD8 +T cells, and NK cells in the fourth week were higher than those in the first week, with statistically significant differences ( Z=-3.825, P=0.001; Z=-3.466, P=0.003; Z=-3.526, P=0.003); however, the absolute values of B cells showed an overall decreasing trend, and were significantly lower in the fourth week than in the first and second weeks, with statistically significant differences ( Z=3.705, P=0.001; Z=2.630, P=0.009). The changes in lymphocyte subset absolute values in the rejection group were more significant than those in the infection group, with T cells, CD4 +T cells, and CD8 +T cells showing significant increases in the second, third, and fourth weeks postoperatively compared with the first week, with statistically significant differences ( Z=-3.466, P=0.003; Z=-4.661, P<0.001; Z=-5.020, P<0.001; Z=-2.749, P=0.036; Z=-4.422, P<0.001; Z=-4.542, P<0.001; Z=-3.466, P=0.003; Z=-3.765, P=0.001; Z=-4.482, P<0.001); NK cell absolute values in the third and fourth weeks postoperatively were significantly higher than those in the first week, with statistically significant differences ( Z=-2.570, P=0.061; Z=-3.765, P=0.001). In summary, monitoring the differences and dynamic changes of lymphocyte subsets in patients after liver transplantation may have certain guiding significance for evaluating the immune function status of patients and adjusting treatment plans.
6.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
7.Changing resistance profiles of Staphylococcus isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yuling XIAO ; Mei KANG ; Yi XIE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(5):570-580
Objective To investigate the changing distribution and antibiotic resistance profiles of clinical isolates of Staphylococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Staphylococcus according to the unified protocol of CHINET(China Antimicrobial Surveillance Network)using disk diffusion method and commercial automated systems.The CHINET antimicrobial resistance surveillance data from 2015 to 2021 were interpreted according to the 2021 CLSI breakpoints and analyzed using WHONET 5.6.Results During the period from 2015 to 2021,a total of 204,771 nonduplicate strains of Staphylococcus were isolated,including 136,731(66.8%)strains of Staphylococcus aureus and 68,040(33.2%)strains of coagulase-negative Staphylococcus(CNS).The proportions of S.aureus isolates and CNS isolates did not show significant change.S.aureus strains were mainly isolated from respiratory specimens(38.9±5.1)%,wound,pus and secretions(33.6±4.2)%,and blood(11.9±1.5)%.The CNS strains were predominantly isolated from blood(73.6±4.2)%,cerebrospinal fluid(12.1±2.5)%,and pleural effusion and ascites(8.4±2.1)%.S.aureus strains were mainly isolated from the patients in ICU(17.0±7.3)%,outpatient and emergency(11.6±1.7)%,and department of surgery(11.2±0.9)%,whereas CNS strains were primarily isolated from the patients in ICU(32.2±9.7)%,outpatient and emergency(12.8±4.7)%,and department of internal medicine(11.2±1.9)%.The prevalence of methicillin-resistant strains was 32.9%in S.aureus(MRSA)and 74.1%in CNS(MRCNS).Over the 7-year period,the prevalence of MRSA decreased from 42.1%to 29.2%,and the prevalence of MRCNS decreased from 82.1%to 68.2%.MRSA showed higher resistance rates to all the antimicrobial agents tested except trimethoprim-sulfamethoxazole than methicillin-susceptible S.aureus(MSSA).Over the 7-year period,MRSA strains showed decreasing resistance rates to gentamicin,rifampicin,and levofloxacin,MRCNS showed decreasing resistance rates to gentamicin,erythromycin,rifampicin,and trimethoprim-sulfamethoxazole,but increasing resistance rate to levofloxacin.No vancomycin-resistant strains were detected.The prevalence of linezolid-resistant MRCNS increased from 0.2%to 2.3%over the 7-year period.Conclusions Staphylococcus remains the major pathogen among gram-positive bacteria.MRSA and MRCNS were still the principal antibiotic-resistant gram-positive bacteria.No S.aureus isolates were found resistant to vancomycin or linezolid,but linezolid-resistant strains have been detected in MRCNS isolates,which is an issue of concern.
8.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
9.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
10. Study on the health literacy and related factors of the cancer prevention consciousness among urban residents in China from 2015 to 2017
Chengcheng LIU ; Chunlei SHI ; Jufang SHI ; Ayan MAO ; Huiyao HUANG ; Pei DONG ; Fangzhou BAI ; Yunsi CHEN ; Debin WANG ; Guoxiang LIU ; Xianzhen LIAO ; Yana BAI ; Xiaojie SUN ; Jiansong REN ; Li YANG ; Donghua WEI ; Bingbing SONG ; Haike LEI ; Yuqin LIU ; Yongzhen ZHANG ; Siying REN ; Jinyi ZHOU ; Jialin WANG ; Jiyong GONG ; Lianzheng YU ; Yunyong LIU ; Lin ZHU ; Lanwei GUO ; Youging WANG ; Yutong HE ; Peian LOU ; Bo CAI ; Xiaohua SUN ; Shouling WU ; Xiao QI ; Kai ZHANG ; Ni LI ; Wanghong XU ; Wuqi QIU ; Min DAI ; Wanqing CHEN
Chinese Journal of Preventive Medicine 2020;54(1):47-53
Objective:
To understand the health literacy and relevant factors of cancer prevention consciousness in Chinese urban residents from 2015 to 2017.
Methods:
A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. The self-designed questionnaire was used to collect the information of demographic characteristics and cancer prevention consciousness focusing on nine common risk factors, including smoking, alcohol, fiber food, food in hot temperature or pickled food, chewing betel nut, helicobacter pylori, moldy food, hepatitis B infection, estrogen, and exercise. The logistic regression model was adopted to identify the influencing factors.
Results:
The overall health literacy of the cancer prevention consciousness was 77.4% (24 980 participants), with 77.4% (12 018 participants), 79.9% (6 406 participants), 77.2% (1 766 participants) and 74.5% (4 709 participants) in each group (

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