1.Pathogenesis and treatment of "inflammation cancer transformation" of ulcerative colitis based on "Kenang" theory.
Jia-Kang XIE ; Xiao-Ning XU ; Feng-Ting AI ; Shao-Xi LI ; Yun AN ; Xuan GONG ; Yong CAO
China Journal of Chinese Materia Medica 2025;50(8):2298-2304
Ulcerative colitis(UC) is a recurrent, chronic, nonspecific inflammatory bowel disease. The longer the course of the disease, the higher the risk of cancerization. In recent years, the incidence and mortality rates of colon cancer in China have been increasing year by year, seriously threatening the life and health of patients. Therefore, studying the mechanism of "inflammation cancer transformation" in UC and conducting early intervention is crucial. The "Kenang" theory is an important component of traditional Chinese medicine(TCM) theory of phlegm and blood stasis. It is based on the coexistence of phlegm and blood stasis in the body and deeply explores the pathogenic syndromes and characteristics of phlegm and blood stasis. Kenang is a pathological product formed when long-term Qi stagnation leads to the internal formation of phlegm and blood stasis, which is hidden deep within the body. It is characterized by being hidden, progressive, and difficult to treat. The etiology and pathogenesis of "inflammation cancer transformation" in UC are consistent with the connotation of the "Kenang" theory. The internal condition for the development of UC "inflammation cancer transformation" is the deficiency of healthy Qi, with Qi stagnation being the key pathological mechanism. Phlegm and blood stasis are the main pathogenic factors. Phlegm and blood stasis accumulate in the body over time and can produce cancer toxins. Due to the depletion of healthy Qi and a weakened constitution, the body is unable to limit the proliferation and invasion of cancer toxins, eventually leading to cancer transformation in UC. In clinical treatment, the focus should be on removing phlegm and blood stasis, with syndrome differentiation and treatment based on three basic principles: supporting healthy Qi to strengthen the body's foundation, resolving phlegm and blood stasis to break up the Kenang, and regulating Qi and blood to smooth the flow of energy and resolve stagnation. This approach helps to dismantle the Kenang, delay, block, or even reverse the cancerization process of UC, reduce the risk of "inflammation cancer transformation", improve the patient's quality of life, and provide new perspectives and strategies for early intervention in the development of colon cancer.
Humans
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Colitis, Ulcerative/immunology*
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Medicine, Chinese Traditional
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Drugs, Chinese Herbal/therapeutic use*
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Cell Transformation, Neoplastic
2.Kaempferol-A Natural Drug for Rheumatoid Arthritis.
Hong-Mei HONG ; Jia-Wang ZHOU ; Ming-Yu LI ; Gui-Feng HAO ; Zhi-Jun XIE
Chinese journal of integrative medicine 2025;31(12):1119-1128
3.Exploring cellular plasticity and resistance mechanisms in lung cancer: Innovations and emerging therapies.
Caiyu JIANG ; Shenglong XIE ; Kegang JIA ; Gang FENG ; Xudong REN ; Youyu WANG
Journal of Pharmaceutical Analysis 2025;15(5):101179-101179
Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and remains the leading cause of cancer-related mortality worldwide. Firstly, this review explores the limitations of conventional therapies, chemotherapy, radiotherapy, and surgery, focusing on the development of drug resistance and significant toxicity that often hinder their efficacy. Thereafter, advancements in targeted therapies, such as immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), are discussed, highlighting their impact on improving outcomes for patients with specific genetic mutations, including c-ros oncogene 1 receptor tyrosine kinase (ROS1), anaplastic lymphoma kinase (ALK), and epidermal growth factor receptor (EGFR). Additionally, the emergence of novel immunotherapies and phytochemicals is examined, emphasizing their potential to overcome therapeutic resistance, particularly in advanced-stage diseases. The review also delves into the role of next-generation sequencing (NGS) in enabling personalized treatment approaches and explores the clinical potential of innovative agents, such as bispecific T-cell engagers (BiTEs) and antibody-drug conjugates (ADCs). Finally, we address the socioeconomic barriers that limit the accessibility of these therapies in low-resource settings and propose future research directions aimed at improving the long-term efficacy and accessibility of these treatments.
4.A Comprehensive Study of the Association between LEPR Gene rs1137101 Variant and Risk of Digestive System Cancers
Qiong Wei HU ; Guang Wei ZHOU ; Wei Guang ZHOU ; Xi Jia LIAO ; Xing Jia SHI ; FengYang XIE ; Heng Shou LI ; Yong WANG ; Hong Xian FENG ; Li Xiu GU ; Feng Bi CHEN
Biomedical and Environmental Sciences 2024;37(5):445-456
Objective The leptin receptor,encoded by the LEPR gene,is involved in tumorigenesis.A potential functional variant of LEPR,rs1137101(Gln223Arg),has been extensively investigated for its contribution to the risk of digestive system(DS)cancers,but results remain conflicting rather than conclusive.Here,we performed a case-control study and subsequent meta-analysis to examine the association between rs1137101 and DS cancer risk. Methods A total of 1,727 patients with cancer(gastric/liver/colorectal:460/480/787)and 800 healthy controls were recruited.Genotyping of rs1137101 was conducted using a polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP)assay and confirmed using Sanger sequencing.Twenty-four eligible studies were included in the meta-analysis. Results After Bonferroni correction,the case-control study revealed that rs1137101 was significantly associated with the risk of liver cancer in the Hubei Chinese population.The meta-analysis suggested that rs1137101 is significantly associated with the risk of overall DS,gastric,and liver cancer in the Chinese population. Conclusion The LEPR rs1137101 variant may be a genetic biomarker for susceptibility to DS cancers(especially liver and gastric cancer)in the Chinese population.
5.Hepatic lipidomics study in chronic cadmium-exposed mice
Rong-Rong HAO ; Ling LI ; Li TIAN ; Jia XIE ; Meng-Yan CHEN ; Zheng-Ping YU ; Hui-Feng PI
Journal of Regional Anatomy and Operative Surgery 2024;33(3):194-200
Objective To study the change of lipidomics in chronic cadmium-exposed mice,thereby screening out lipid subclasses,lipid molecules and enriched metabolic pathways with significant differences.Methods Twelve SPF male C57BL/6J mice(8 weeks old)were randomly divided into the control group(normal water feeding)and the experimental group[cadmium water(0.6 mg/L of CdCl2)feeding],with 6 mice in each group.Mice were sacrificed after 6 months of cadmium exposure,and fresh liver tissues were collected immediately.Lipid oil red O staining and lipidomics analysis were performed on liver tissue.Results Compared with the control group,the liver tissue of mice in the experimental group did not appear red after lipid oil red O staining.Seventeen lipid subclasses with significant differences and 144 lipid molecules with significant differences were screened out by lipidomics.These lipid molecules with significant differences were enriched in glycerophospholipid metabolism,linoleic acid metabolism,alpha-linolenic acid metabolism,glycosylphosphati-dylinositol biosynthesis,glycerolipid metabolism and arachidonic acid metabolism by KEGG.Conclusion This study reveals that chronic cadmium exposure can induce the disorder of lipid subclasses and lipid metabolites in the liver of mice,which provides a basis for understanding the non-alcoholic fatty liver disease caused by chronic cadmium exposure.
6.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
7.Development and validation of a dynamic prediction tool for post-endo-scopic retrograde cholangiopancreatography early biliary tract infection in patients with choledocholithiasis
Peng LI ; Chao LIANG ; Jia-Feng YAN ; Chun-Hui GAO ; Zhi-Jie MA ; Zhan-Tao XIE ; Ming-Jie SUN
Chinese Journal of Infection Control 2024;23(6):692-699
Objective To develop a prediction tool for post-endoscopic retrograde cholangiopancreatography(ER-CP)early biliary tract infection(PEEBI)in patients with choledocholithiasis,and assist clinical decision-making be-fore ERCP and early personalized intervention after ERCP.Methods An observational bidirectional cohort study was adopted to select inpatients with choledocholithiasis who underwent ERCP in a hospital.Directed acyclic graph(DAGs)and the least absolute shrinkage and selection operator(LASSO)were used to predict PEEBI based on lo-gistic regression,and the models were compared and validated internally and externally.Results From January 1,2020 to September 30,2023,a total of 2 121 patients with choledocholithiasis underwent ERCP were enrolled,of whom 77(3.6%)developed PEEBI,mostly in the first 2 days after surgery(66.2%).The major influencing fac-tors for PEEBI were non-iatrogenic patient-related factors,namely diabetes mellitus(OR=2.43,95%CI:1.14-4.85),bile duct malignancy(OR=3.95,95%CI:1.74-8.31)and duodenal papillary diverticulum(OR=4.39,95%CI:1.86-9.52).Compared with the LASSO model,the DAGs model showed higher ability(3.0%)in com-prehensive discrimination(P=0.007),as well as good differentiation performance(D=0.133,P=0.894)and cal-ibration performance(x2=5.499,P=0.703)in external validation.Conclusion The DAGs model constructed in this study has good predictive performance.With the help of this tool,targeted early preventive measures in clinical practice can be taken to reduce the occurrence of PEEBI.
8.Effect of swimming exercise on lipid metabolism in NAFLD mice based on lipidomics
Yan LUO ; Ping DENG ; Meng-Yan CHEN ; Jia XIE ; Li TIAN ; Hui-Feng PI
Journal of Regional Anatomy and Operative Surgery 2024;33(12):1027-1033
Objective To investigate the regulatory effect of swimming exercise(SE)on lipid metabolism in nonalcoholic fatty liver disease(NAFLD)mice.Methods A total of 27 C57BL/6J mice were divided into the control group(normal diet),high fat diet(HFD)group and HFD+SE group,with 9 mice in each group.Twelve weeks later,liver tissues were collected for untargeted lipidomics detection by LC-MS.Dimensional statistical analysis of lipidomics profiles was carried out by constructing OPLS-DA model,and combined with the t-test,the lipids with OPLS-DA VIP>1,P<0.05 were screened out from all samples as significantly different lipids.Results There were 81 different lipids between HFD group and the control group;and there were 27 different lipids between HFD+SE group and HFD group.The different lipids mainly belong to glycerides,glycerophospholipids and sphingomyelins.Conclusion Lipid metabolism profile of NAFLD mice has been changed,and swimming exercise can improve lipid metabolism of NAFLD mice.
9.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.
10.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.

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