1.Construction of a prognostic prediction model for invasive lung adenocarcinoma based on machine learning
Yanqi CUI ; Jingrong YANG ; Lin NI ; Duohuang LIAN ; Shixin YE ; Yi LIAO ; Jincan ZHANG ; Zhiyong ZENG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(01):80-86
Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.
2.Pain, agitation, and delirium practices in Chinese intensive care units: A national multicenter survey study.
Xiaofeng OU ; Lijie WANG ; Jie YANG ; Pan TAO ; Cunzhen WANG ; Minying CHEN ; Xuan SONG ; Zhiyong LIU ; Zhenguo ZENG ; Man HUANG ; Xiaogan JIANG ; Shusheng LI ; Erzhen CHEN ; Lixia LIU ; Xuelian LIAO ; Yan KANG
Chinese Medical Journal 2025;138(22):3031-3033
3.Simultaneous Determination of 7 Components in Qingkailing Oral Liquid by HPLC-MS/MS
Jinyun WU ; Kaiwei CAI ; Hongying CHEN ; Jiaqi WANG ; Biyan PAN ; Zhiyong XIE ; Qiongfeng LIAO
Traditional Chinese Drug Research & Clinical Pharmacology 2024;35(2):257-262
Objective An HPLC-MS/MS method was established for the simultaneous determination of 7 components in Qingkailing Oral Liquid.Methods The assay was performed on a Waters ACQUITY UPLC BEH C18 column(2.1 mm×10 mm,1.7 μm)and the sample was eluted with a gradient mobile phase containing 10 mmol·L-1 of ammonium acetate and 0.1%of formic acid in water(A)-methanol(B).The mass spectrometry was carried out by electrospray ionization(ESI)with positive/negative ions in multiple reaction monitoring(MRM)mode for quantitative analysis.Results The linear ranges of adenine,chlorogenic acid,caffeic acid,geniposide,baicalin,hyodeoxycholic acid and cholic acid were 0.100 4-3.213,0.784 5-8.982,0.998-3.194,0.622 5-19.92,25.05-300.6,2.513-30.15 and 7.775-93.30 μg·mL-1(r≥0.999 0).The average recoveries(n=6)were 100.9%,98.74%,101.2%,100.2%,100.8%,99.97%and 98.94%with RSD of 1.58%,0.59%,1.78%,1.25%,0.65%,1.69%and 1.07%.The contents of the above mentioned 7 components in 15 tested samples were in the ranges of 0.12-0.18,0.19-0.24,0.06-0.09,0.34-0.37,4.54-4.85,0.49-0.67 and 1.82-2.19 mg·mL-1.The contents of 7 components in tested sample from different manufacturers were closed.Conclusion The method has shown good sensitivity,accuracy,and repeatability.The study can provide reference and data support for the quality control and subsequent research of Qingkailing Oral Liquid.
4.Effects of JEV infection on TLRs signaling pathway and its regulation on secretion of inflammatory factors in Leydig cells
Song HE ; Rentan YAN ; Deyuan TANG ; Zhiyong ZENG ; Bin WANG ; Yinming MAO ; Piao ZHOU ; Zhengbo LIAO ; Xu CHEN ; Shenglin YUAN ; Wenwen HU ; Min ZHOU
Chinese Journal of Veterinary Science 2024;44(11):2409-2417
This study aims to investigate the effects of Japanese encephalitis virus(JEV)on TLRs signaling pathway and its regulation of the secretion of inflammatory factors during the infection of testicular interstitial cells,In this study,the mRNA levels of TLR3,TLR7,TLR8,TRIF and MyD88 genes were detected by qPCR after 1 MOI dose of JEV was inoculated into testicular stro-mal cells at different time periods.Western blot assay was used to detect the expression levels of TLR3,TLR7,TRIF and MyD88 protein at 6 h after JEV infection,and ELISA was used to detect the expression levels of IL-1β,IL-6 and TNF-α at different time periods(6,12 and 24 h).The re-sults showed as follows:After 6 h of JEV infection,the mRNA levels of TLR3,TLR7,TRIF and MyD88 genes were significantly up-regulated(P<0.05),and the mRNA levels of TLR8 genes were down-regulated(P<0.05).Western blot results showed that the protein expressions of TLR3,TLR7,TRIF and MyD88 were significantly up-regulated when JEV infected testicular stromal cells for 6 h(P<0.05),which was consistent with the corresponding mRNA transcription levels.There was no significant change in TLR8 protein expression.ELISA results showed that 6 h after JEV infection of testicular stromal cells,IL-6 was significantly increased(P<0.01),and the expressions of IL-1β and TNF-α were not changed.TLR3,TLR7,TLR8,TRIF and MyD88 were si-lenced by siRNA,and the silenced cells were inoculated with JEV for 6 h,and IL-6 expression lev-els were detected by ELISA.The results showed that silenced TLR3,TLR7,TLR8,TRIF and MyD88 could significantly reduce the increase of IL-6 secretion induced by JEV infection(P<0.05).These results indicated that JEV could induce the expression of inflammatory factor IL-6 by activating TLR3,TLR7 and TLR8 signaling pathway after infection of testicular stromal cells.This study provides a reference for further elucidating the mechanism of reproductive disorders caused by JEV infection.
5.Research progress of immune response mechanisms and prevention and control of porcine circovirus type 2
Yinming MAO ; Deyuan TANG ; Zhiyong ZENG ; Bin WANG ; Tao HUANG ; Song HE ; Piao ZHOU ; Zhengbo LIAO ; Shenglin YUAN ; Xu CHEN
Chinese Journal of Veterinary Science 2024;44(11):2483-2489
Porcine circovirus type 2(PCV2)is the main pathogen causing porcine circovirus related diseases.PCV2 infection in pigs may lead to porcine dermatitis and nephrotic syndrome(PDNS)and weaned piglets multiple system failure syndrome(PMWS),etc.At present,the pathogenic mechanism is not fully understood.PCV2 is a single strand of negative link DNA,which can cause immune suppression in the body and lead to increased secondary susceptibility,which has a syner-gistic effect with various pig diseases and brings major economic losses to the pig industry.Al-though there are commercial vaccines,the prevention of vaccines has certain limitations and there is no effective drug treatment so far,an outbreak will threaten people's life and health and public safety,resulting in significant economic losses.In order to understand the latest progress of PCV2 escape mechanism and prevention and control,this paper summarizes the inhibition of interferon production,regulation of apoptosis,regulation of autophagy,regulation of pyroptosis and inflam-matory response,evasion of adaptive immune response,and prevention and control of PCV2,in or-der to provide new theoretical ideas for the research and prevention and control of PCV2.
6.Mechanism of protective effect of metformin against septic cardiomyopathy based on the P38 MAPK/JNK signaling pathway
Li LI ; Yang LIAO ; Zhiyong LIU
Chinese Journal of Preventive Medicine 2024;58(10):1567-1572
Exploring the protective mechanism of metformin against septic cardiomyopathy based on the mitogen-activated protein kinase P38 (P38 MAPK)/c-Jun amino-terminal kinase (JNK) signaling pathway. This paper is an experimental animal study design, which was completed from January to December 2023 at the Xiangya Hospital, Central South University. Forty-eight 8-week-old female C57BL/6 mice were divided into four groups: group A (control group), group B (model group), group C (model+trimetazidine hydrochloride), and group D (model+metformin group), with 12 mice in each group, by using a randomized numeric table method. Groups B, C, and D were injected intraperitoneally with LPS (15 mg/kg) to construct a septic cardiomyopathy mouse model. 24 h after modeling, Groups A and B were injected intraperitoneally with an equal amount of saline, Group C was given 20 mg/kg trimetazidine hydrochloride by gavage, and Group D was injected with metformin 200 mg/kg intraperitoneally, and all of them were subjected to consecutive interventions for 14 d. The results were summarized in the following table. Ultrasound imaging system was used to detect cardiac function, and TUNEL method was used to detect apoptosis rate of myocardial tissues; real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was used to detect the levels of mRNA of JNK, P38 MAPK of P38 MAPK signaling pathway in the myocardial tissues of mice; Plasma creatine kinase isoenzyme (CK-MB), brain natriuretic peptide (BNP), tumor necrosis factor alpha (TNF-α), and interleukin 6 (IL-6) levels were measured by enzyme-linked immunosorbent assay (ELISA) in all groups of mice; and protein kinase C, and protein kinase C levels were measured by protein blotting in cardiac muscle tissue. Eplison isoform (PKCε), and Cavity protein-3 (Cav-3) protein expression in myocardial tissues. The results showed that compared with group A, left ventricular ejection fraction (LVEF) (79.51±6.62)%, left ventricular short-axis shortening (FS) (45.66±4.13), apoptosis rate (4.34±0.36)%, JNK (0.96±0.06), P38 MAPK (1.01±0.03), CK-MB (2.37±0.13) μg/L, BNP (21.36±3.47) ng/L, TNF-α (176.22±19.24) ng/L, IL-6 (35.43±3.84) ng/L, PKCε expression (1.98±0.26), Cav-3 expression (1.04±0.03) compared to apoptosis rates in groups B, C, and D (28.22±4.49, 22.45±3.69, 15.88±3.27), JNK (1.68±0.11, 1.32±0.18, 1.13±0.14), P38 MAPK (2.47±0.71,1.77±0.35,1.49±0.05), CK-MB (16.55±2.16, 12.63±1.98, 5.27±0.61), BNP (48.92±5.67, 33.78±4.11, 27.55±3.84), TNF-α (463.71±24.81, 335.71±36.71, 214.78±22.53), and IL-6 (78.57±6.36, 63.71±5.66, 52.47±5.47) expression were elevated, while left ventricular ejection fraction (LVEF) (49.38±5.27, 55.47±5.03, 62.26±5.14), left ventricular short-axis shortening (FS) (24.36±2.17, 30.43±3.29, 33.57±2.72), PKCε expression (1.33±0.21, 1.54±0.23, 1.75±0.22), and Cav-3 expression (0.47±0.06, 0.76±0.05, 0.85±0.04) were all down-regulated ( F=113.020,67.657,219.539,206.222,227.977,88.455,6285.186,135.877,65.924,96.362,17.532,314.419, P<0.05). Compared with group B, apoptosis rate, JNK, P38 MAPK, CK-MB, BNP, TNF-α, and IL-6 expression were decreased, and LVEF, FS, PKCε, and Cav-3 expression were up-regulated in groups C and D. And group D was better than group C ( P<0.05). In conclusion, metformin has a protective effect against septic cardiomyopathy, and the mechanism may be related to the inhibition of the activation of the P38 MAPK/JNK signaling pathway and the up-regulation of PKCε and Cav-3 expression.
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 distribution and resistance profiles of Klebsiella strains in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chuyue ZHUO ; Yingyi GUO ; Chao ZHUO ; 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 ; 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(4):418-426
Objective To understand the changing distribution and antimicrobial resistance profiles of Klebsiella strains in 52 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Antimicrobial susceptibility testing was carried out according to the unified CHINET protocol.The susceptibility results were interpreted according to the breakpoints in the Clinical & Laboratory Standards Institute(CLSI)M100 document.Results A total of 241,549 nonduplicate Klebsiella strains were isolated from 2015 to 2021,including Klebsiella pneumoniae(88.0%),Klebsiella aerogenes(5.8%),Klebsiella oxytoca(5.7%),and other Klebsiella species(0.6%).Klebsiella strains were mainly isolated from respiratory tract(48.49±5.32)%.Internal medicine(22.79±3.28)%,surgery(17.98±3.10)%,and ICU(14.03±1.39)%were the top 3 departments where Klebsiella strains were most frequently isolated.K.pneumoniae isolates showed higher resistance rate to most antimicrobial agents compared to other Klebsiella species.Klebsiella isolates maintained low resistance rates to tigecycline and polymyxin B.ESBLs-producing K.pneumoniae and K.oxytoca strains showed higher resistance rates to all the antimicrobial agents tested compared to the corresponding ESBLs-nonproducing strains.The K.pneumoniae and carbapenem-resistant K.pneumoniae(CRKP)strains isolated from ICU patients demonstrated higher resistance rates to majority of the antimicrobial agents tested than the strains isolated from non-ICU patients.The CRKP strains isolated from adult patients had higher resistance rates to most of the antimicrobial agents tested than the corresponding CRKP strains isolated from paediatric patients.Conclusions The prevalence of carbapenem-resistant strains in Klebsiella isolates increased greatly from 2015 to 2021.However,the Klebsiella isolates remained highly susceptible to tigecycline and polymyxin B.Antimicrobial resistance surveillance should still be strengthened for Klebsiella strains.

Result Analysis
Print
Save
E-mail