1.Effect of Wenpi tongluo kaiqiao formula against neuronal necroptosis in mice with Alzheimer’s disease and its mechanism
Xiaomin ZHU ; Wei CHEN ; Yulan FU ; Guifeng ZHUO ; Yingrui HUANG ; Ying ZHANG ; Lin WU
China Pharmacy 2025;36(9):1046-1051
OBJECTIVE To investigate the effects and mechanism of Wenpi tongluo kaiqiao formula (WPTL) against neuronal necroptosis in Alzheimer’s disease (AD) mice based on the Z-DNA binding protein 1 (ZBP1)/mixed lineage kinase domain-like protein (MLKL) signaling pathway. METHODS Forty APP/PS1 transgenic AD mice were randomly divided into model group, WPTL low-dose (WPTL-L) group (10.4 g/kg, calculated by the raw medicine), WPTL high-dose (WPTL-H) group (20.8 g/kg, calculated by the raw medicine) and donepezil hydrochloride group (3 mg/kg), with 10 mice in each group; another 10 C57BL/6J mice were selected as normal control group. Intragastric administration, once a day, for 30 consecutive days. Twenty-four hours after the last administration, Morris water maze test was performed to evaluate learning and memory abilities; the pathological morphology of hippocampal tissues was observed; the serum levels of tumor necrosis factor-α (TNF-α) and interleukin-4 (IL-4) were determined; the expressions of amyloid precursor protein (APP), Tau protein, and ZBP1/MLKL signaling pathway-related proteins in hippocampal tissues were detected; the positive expression of phosphorylated receptor-interacting protein kinase 3 (p-RIPK3) in the neurons of hippocampal tissues and mRNA expression of ZBP1 were measured in hippocampal tissues. RESULTS Compared with normal control group, the escape latency of mice in model group was prolonged significantly on day 3 to 5 (P<0.05), the times of crossing platform reduced significantly (P<0.05), and obvious pathological changes were observed in the hippocampal tissue. The level of TNF- α, the expressions of APP, p-Tau and ZBP1, the phosphorylation levels of RIPK1, RIPK3 and MLKL, the fluorescence intensity of p-RIPK3 as well as the mRNA expression of ZBP1 were significantly increased (P<0.05), while the serum level of IL-4 was decreased significantly (P<0.05). Compared with model group, above indexes were reversed significantly in administration groups (P<0.05), and pathological damage of hippocampal tissue was alleviated. CONCLUSIONS WPTL can inhibit the ZBP1/MLKL signaling pathway, reduce neuronal necroptosis in AD mice, and inhibit inflammatory responses, thereby improving learning and spatial memory abilities in AD mice.
2.Anti-vascular dementia effect of Yifei xuanfei jiangzhuo formula by inhibiting mitochondrial fission
Yulan FU ; Wei CHEN ; Guifeng ZHUO ; Xiaomin ZHU ; Yingrui HUANG ; Jinzhi ZHANG ; Fucai YANG ; Ying ZHANG ; Lin WU
China Pharmacy 2025;36(15):1859-1865
OBJECTIVE To investigate the intervention effect and its potential mechanism of Yifei xuanfei jiangzhuo formula by inhibiting mitochondrial fission in a vascular dementia (VaD) model rats. METHODS VaD rat model was established by bilateral common carotid artery ligation. The experimental animals were randomly divided into sham operation group (SHAM), model group (MOD),Yifei xuanfei jiangzhuo formula low-dose group (YFXF-L), Yifei xuanfei jiangzhuo formula high-dose group (YFXF-H), and Donepezil hydrochloride group (positive control), with 9 animals in each group. After 30 days of intervention, the spatial learning memory ability was assessed by Morris water maze experiment; HE staining was used to observe histopathological changes in CA1 area of hippocampus; ELISA was used to detect the levels of serum inflammatory factors [interleukin-1β (IL-1β) and IL-4]; Western blot was used to detect the expressions of heat shock protein 90 (HSP90)/mixed lineage kinase domain-like protein (MLKL)/dynamin-related protein 1 (Drp1) pathway-related proteins, mitochondrial fusion proteins (MFN1, MFN2), and adenosine triphosphate synthase 5A (ATP5A) in hippocampal tissues. The immunohistochemistry was used to detect the level of phosphorylated MLKL (p-MLKL); real-time fluorescence quantitative PCR was adopted to detect mRNA expressions ofHSP90, MFN1, MFN2 and ATP5A. RESULTS Compared with SHAM group, the escape latency of rats in the MOD group was significantly prolonged, the number of crossing the platform was significantly reduced, and the hippocampal tissues showed typical neuronal damage characteristics, the positive expression level of p-MLKL and the serum level of IL-1β significantly increased, while the serum level of IL-4 significantly decreased, the protein and mRNA expression of HSP90, as well as the protein expressions of p-MLKL/MLKL and p-Drp1(Ser616)/Drp1 were all significantly increased in hippocampal tissue, the protein and mRNA expressions of MFN1, MFN2 and ATP5A, and protein expression of p-Drp1(Ser637)/Drp1 were all significantly decreased (P<0.05). After the intervention of Yifei xuanfei jiangzhuo formula, above indicators in each treatment group were all significantly reversed (P<0.05). CONCLUSIONS Yifei xuanfei jiangzhuo formula may alleviate neuronal damage and neuroinflammatory responses in VaD rats by regulating the HSP90/MLKL/Drp1 signaling pathway, inhibiting mitochondrial fission, thereby maintaining mitochondrial dynamic balance and improving mitochondrial function.
3.Qualitative and Quantitative Analysis of Chemical Constituents in Liu Junzitang by UPLC-Q-TOF-MS/MS and UPLC
Qiyao JIANG ; Chenchen LIU ; Huiling CHEN ; Zhifeng HUANG ; Wei ZHAO ; Ying LIANG ; Huafeng PAN ; Yue ZHUO
Chinese Journal of Experimental Traditional Medical Formulae 2024;30(6):169-178
ObjectiveTo establish a qualitative and quantitative analysis method for chemical constituents in Liu Junzitang(LJZT), and to clarify its material basis. MethodThe chemical constituents in LJZT were analyzed by ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS), and the resulting compounds were identified by using databases, such as MassBank, PubChem, ChemSpider, Traditional Chinese Medicine Systems Pharmacology Database and Analytical Platform(TCMSP), and by combining with relevant literature. UPLC was used to establish a quantitative method for analysis of 9 compounds in LJZT, including liquiritin, hesperidin, lobetyolin, liquiritigenin, glycyrrhizic acid, nobiletin, tangeretin, atractylenolide Ⅱ and Ⅰ. ResultBy combining the relevant literature, database and MS information, a total of 79 compounds were identified from LJZT, including 31 flavonoids, 15 terpenoids, 14 nitrogen-containing compounds, 6 phenylpropanoids, 6 organic acids and 7 other compounds. The established quantitative analytical method for the nine representative components showed good linearity within their respective linear ranges, and the precision, stability, reproducibility and recovery were in accordance with the requirements. The quantitative results showed that the contents of liquiritin, hesperidin, lobetyolin, liquiritigenin, glycyrrhizic acid, nobiletin, tangeretin, atractylenolide Ⅱ and Ⅰ in LJZT were 0.376 5, 2.602 1, 0.082 6, 0.128 1, 1.778 6, 0.015 7, 0.006 7, 0.030 4, 0.003 2 mg·g-1, respectively. ConclusionThe established method can quickly, sensitively and accurately analyze the chemical constituents in LJZT, clarify that the material basis of LJZT is mainly flavonoids, terpenoids and nitrogen-containing compounds, and simultaneously determine the contents of the 9 components, which can lay a foundation for the research on quality control, mechanism and clinical application of LJZT.
4.Analysis of epidemiological and clinical characteristics of 1247 cases of infectious diseases of the central nervous system
Jia-Hua ZHAO ; Yu-Ying CEN ; Xiao-Jiao XU ; Fei YANG ; Xing-Wen ZHANG ; Zhao DONG ; Ruo-Zhuo LIU ; De-Hui HUANG ; Rong-Tai CUI ; Xiang-Qing WANG ; Cheng-Lin TIAN ; Xu-Sheng HUANG ; Sheng-Yuan YU ; Jia-Tang ZHANG
Medical Journal of Chinese People's Liberation Army 2024;49(1):43-49
Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6%),Mycobacterium tuberculosis 249(20.0%),other bacteria 150(12.0%),fungi 68(5.5%),parasites 18(1.4%),Treponema pallidum 18(1.4%)and rickettsia 1(0.1%).The number of cases increased by 177 cases(33.1%)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ¥29,500(¥16,000,¥59,200).The mortality rate from CNS infectious diseases is 1.6%.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.
5.National bloodstream infection bacterial resistance surveillance report (2022) : Gram-negative bacteria
Zhiying LIU ; Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(1):42-57
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.
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 distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; 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 ; 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 ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; 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(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
8.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; 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 ; 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(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
9.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
10.Changing resistance profiles of Proteus,Morganella and Providencia in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yunmin XU ; Xiaoxue DONG ; Bin SHAN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Yi XIE ; Mei KANG ; 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 ; 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 ; Hongyan ZHENG ; 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(4):410-417
Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10%of the Proteus and Morganella strains were resistant,while less than 20%of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4%in Proteus isolates,1.9%in Morganella isolates,and 15.6%in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.

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