1.Mechanism of salvianolic acid B protecting H9C2 from OGD/R injury based on mitochondrial fission and fusion
Zi-xin LIU ; Gao-jie XIN ; Yue YOU ; Yuan-yuan CHEN ; Jia-ming GAO ; Ling-mei LI ; Hong-xu MENG ; Xiao HAN ; Lei LI ; Ye-hao ZHANG ; Jian-hua FU ; Jian-xun LIU
Acta Pharmaceutica Sinica 2024;59(2):374-381
		                        		
		                        			
		                        			 This study aims to investigate the effect of salvianolic acid B (Sal B), the active ingredient of Salvia miltiorrhiza, on H9C2 cardiomyocytes injured by oxygen and glucose deprivation/reperfusion (OGD/R) through regulating mitochondrial fission and fusion. The process of myocardial ischemia-reperfusion injury was simulated by establishing OGD/R model. The cell proliferation and cytotoxicity detection kit (cell counting kit-8, CCK-8) was used to detect cell viability; the kit method was used to detect intracellular reactive oxygen species (ROS), total glutathione (t-GSH), nitric oxide (NO) content, protein expression levels of mitochondrial fission and fusion, apoptosis-related detection by Western blot. Mitochondrial permeability transition pore (MPTP) detection kit and Hoechst 33342 fluorescence was used to observe the opening level of MPTP, and molecular docking technology was used to determine the molecular target of Sal B. The results showed that relative to control group, OGD/R injury reduced cell viability, increased the content of ROS, decreased the content of t-GSH and NO. Furthermore, OGD/R injury increased the protein expression levels of dynamin-related protein 1 (Drp1), mitofusions 2 (Mfn2), Bcl-2 associated X protein (Bax) and cysteinyl aspartate specific proteinase 3 (caspase 3), and decreased the protein expression levels of Mfn1, increased MPTP opening level. Compared with the OGD/R group, it was observed that Sal B had a protective effect at concentrations ranging from 6.25 to 100 μmol·L-1. Sal B decreased the content of ROS, increased the content of t-GSH and NO, and Western blot showed that Sal B decreased the protein expression levels of Drp1, Mfn2, Bax and caspase 3, increased the protein expression level of Mfn1, and decreased the opening level of MPTP. In summary, Sal B may inhibit the opening of MPTP, reduce cell apoptosis and reduce OGD/R damage in H9C2 cells by regulating the balance of oxidation and anti-oxidation, mitochondrial fission and fusion, thereby providing a scientific basis for the use of Sal B in the treatment of myocardial ischemia reperfusion injury. 
		                        		
		                        		
		                        		
		                        	
2.Significance of 18F-PI-2620 PET imaging for diagnosing tau protein deposition in patients with different cognitive disorders alongside cognitive correlation analysis
Gan HUANG ; Yan ZHANG ; Cheng WANG ; Mei XIN ; Hongda SHAO ; Yue WANG ; Liangrong WAN ; Ju QIU ; Qun XU ; Jianjun LIU ; Xia LI ; Chenpeng ZHANG
Chinese Journal of Nuclear Medicine and Molecular Imaging 2024;44(5):273-278
		                        		
		                        			
		                        			Objective:To evaluate the values of 18F-PI-2620 PET/CT brain imaging with SUV ratio (SUVR) in the assessment of tau protein deposition in the brain of patients with different cognitive disorders and its correlation with cognition. Methods:This was a cross-sectional study. From December 2019 to November 2022, a total of 67 subjects including 54 patients with Alzheimer′s disease (AD; 21 males, 33 females, age (68.6±7.8) years), 7 patients with mild cognitive impairment (MCI; 1 male, 6 females, age (63.1±11.2) years) and 6 healthy controls (HC; 4 males, 2 females, age (69.0±5.8) years) were enrolled retrospectively in Renji Hospital. All participants were examined by 18F-PI-2620 PET/CT. SUVRs of brain regions were obtained, including frontal lobe, temporal lobe, occipital lobe, parietal lobe, insular lobe, whole brain, as well as 10 independent brain ROIs (amygdala, orbitofrontal cortex, cingulate gyrus, superior occipital gyrus, superior parietal gyrus, inferior angular gyrus, precuneus, inferior temporal gyrus, entorhinal cortex and parahippocampal gyrus), with inferior cerebellum cortex as the reference region. All participants were estimated by cognitive scales(mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA)). One-way analysis of variance and the least significant difference t test were used to compare the differences of SUVR in each brain region among HC, MCI and AD groups. ROC curve analysis was used to determine the optimal cut-off values of SUVR in each brain region for the differential diagnosis of AD-MCI and AD-HC. Pearson correlation analysis was employed to examine the correlations of SUVR with cognitive scale scores. Results:The SUVR of whole brain was 1.40±0.31 in AD group, 1.08±0.19 in MCI group, and 1.01±0.12 in HC group. SUVR analysis in the whole brain and each brain region could distinguish AD from HC, AD from MCI ( F values: 1.76-10.09, t values: 2.98-7.47, all P<0.05), but could not distinguish HC from MCI ( t values: 0.17-1.53, all P>0.05). ROC curve analysis showed that the best cut-off value of SUVR was 1.18 for whole brain (AUC=0.89), 1.13 for amygdala (AUC=0.94) and 1.26 for parahippocampal gyrus (AUC=0.94) for differential diagnosis of AD and HC, which was 1.06 for whole brain (AUC=0.82), 1.18 for amygdala (AUC=0.88) and 1.28 (AUC=0.88) for infratemporal gyrus to differential diagnosis of AD and MCI. SUVRs of the whole brain, frontal, occipital, parietal, temporal and insula were significantly negatively correlated with MMSE and MoCA cognitive scale scores ( r values: from -0.64 to -0.40, all P<0.05). Conclusions:SUVR quantitative analysis in 18F-PI-2620 PET imaging can assist the differential diagnosis of AD and HC, AD and MCI. The SUVRs of whole brain and five lobes show negative correlations with MMSE and MoCA scores.
		                        		
		                        		
		                        		
		                        	
3.A Case of EML4-ALK Fusion V1 Subtype Lung Adenocarcinoma Detected by RNA-based NGS
XU YUE ; MU NING ; LIU MEI ; WU SHENGNAN ; MA CHUNHUA
Chinese Journal of Lung Cancer 2024;27(6):480-484
		                        		
		                        			
		                        			Lung cancer is the malignant tumor with the highest incidence and mortality rate worldwide.For lung adenocarcinoma,identifying specific gene mutations,fusions,and giving corresponding targeted drugs can greatly improve the survival time of the patients.Among them,anaplastic lymphoma kinase(ALK)fusion occurs in 3%-7%of non-small cell lung cancer(NSCLC).In clinical practice,a variety of detection methods can be used to determine the ALK fusion status,but false negative test results are possible.This paper retrospectively analyzed the diagnosis and treatment of a patient with lung adeno-carcinoma,judged the ALK fusion status by various detection methods.Among them,immunohistochemistry(IHC)(Ventana D5F3),RNA based next-generation sequencing(RNA-based NGS)confirmed positive echinoderm microtubule associated protein like 4(EML4)-ALK fusion,while DNA-based NGS was negative.This paper analyzed the detection methods of ALK fusion,in order to clarify which detection method is the most accurate and simple to choose in different clinical cases and guide the subsequent treatment.
		                        		
		                        		
		                        		
		                        	
4.Clinical profiles of community-acquired Pseudomonas aeruginosa infections in children
Yue QIU ; Daojiong LIN ; Jianan XI ; Yi XU ; Qingwen SHAN ; Chunhui ZHU ; Yibing CHENG ; Fang WANG ; Yiping CHEN ; Mei ZENG
Chinese Journal of Pediatrics 2024;62(8):727-733
		                        		
		                        			
		                        			Objectives:To investigate clinical characteristics, outcomes and antimicrobial resistance of community-acquired Pseudomonas aeruginosa (CAPA) infections in Chinese pediatric patients. Methods:This retrospective study was conducted at 6 tertiary hospitals in China during January 2016 to December 2018. The clinical and microbiological data of CAPA infected hospitalized children in Hainan and in other regions were collected and compared, and the antimicrobial resistance patterns, clinical characteristics and antibiotic therapy were analyzed. Between different groups were compared using the Chi-square test and Mann-Whitney U test. Results:Among 91 patients, 63 cases were males, 28 cases were females, and 74 cases were from Hainan province, 17 cases were from other regians. The age of consultation was 22.5 (5.4, 44.0) months. Twenty-four cases (26%) had underlying diseases. Fever (79 cases (87%)) and cough (64 cases (70%)) were common initial symptoms. Other concomitant symptoms included wheezing 8 cases (9%), diarrhea 3 cases (3%) and vomiting 4 cases (4%). Twenty-eight cases (31%) had organ infections, including pneumonia 22 cases (24%), skin infection 5 cases (5%), meningitis, intra-abdominal infection and upper urinary tract infection each 1 case (1%). The resistance rate of CAPA isolates to cefepime (4% (4/90)), amikacin (1% (1/90)), ciprofloxacin (2% (2/90)) and levofloxacin (1% (1/89)) was low, and to ceftazidime, piperacillin, piperacillin-azobactam, carbapenem was 12% (11/90), 3/16, 18% (10/56) and 6% (5/90), respectively. Antimicrobial combination therapy accounted for 52% (47/91) of empirical therapy and 59% (52/88) of definite therapy. Two cases (2%) were hopeless discharged, and 3 cases (3%) died during hospitalization. The worse prognosis of CAPA infection is significantly different among children in other regions and in Hainan (4/17 vs. 1% (1/74), χ2=9.74, P<0.05). Conclusions:The invasive CAPA-infection has regional difference in incidence and prognosis in China. Clinical symptoms and signs are non-specific. CAPA strains isolated from pediatric patients display low level of resistance to most of the common antipseudomonal antibiotics. The proportion of poor prognostic outcome is lower in Hainan than in other regions.
		                        		
		                        		
		                        		
		                        	
5.Evaluation of life cycle management system on patients'prognosis after transcatheter aortic valve replacement
Ruo-Yun LIU ; Ran LIU ; Mei-Fang DAI ; Yue-Miao JIAO ; Yang LI ; San-Shuai CHANG ; Ye XU ; Zhi-Nan LU ; Li ZHAO ; Cheng-Qian YIN ; Guang-Yuan SONG
Chinese Journal of Interventional Cardiology 2024;32(6):311-316
		                        		
		                        			
		                        			Objective With the widespread of transcatheter aortic valve replacement(TAVR)in patients with severe symptomatic aortic stenosis(AS),the life-cycle management has become a major determinant of prognosis.Methods A total of 408 AS patients who underwent successfully TAVR from June 2021 to August 2023 were consecutively enrolled in Hospital Valve Intervention Center.Patients were assigned to the Usual Care(UC)group between June 2021 and October 2022,while patients were assigned to the Heart Multi-parameter Monitoring(HMM)group between November 2022 and August 2023.The primary endpoint was defined as composite endpoint within 6 months post-TAVR,including all-cause death,cardiovascular death,stroke/transient ischemic attack,conduction block,myocardial infarction,heart failure rehospitalization,and major bleeding events.Secondary endpoints were the time interval(in hours)from event occurrence to medical consultation or advice and patient satisfaction.Statistical analysis was performed using Kaplan-Meier and multivariable Cox proportional hazards models.Results The incidence of primary endpoint in HMM group was significantly lower than that in UC group(8.9%vs.17.7%,P=0.016),the driving event was the rate of diagnosis and recognition of conduction block.The average time intervals from event occurrence to receiving medical advice were 3.02 h in HHM group vs.97.09 h in UC group(P<0.001).Using cardiac monitoring devices and smart healthcare platforms provided significant improving in patients long-term management(HR 0.439,95%CI 0.244-0.790,P=0.006).Conclusions The utilization of cardiac monitoring devices and smart healthcare platforms effectively alerted clinical events and improved postoperative quality of life during long-term management post TAVR.
		                        		
		                        		
		                        		
		                        	
6.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.
		                        		
		                        		
		                        		
		                        	
7.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.
		                        		
		                        		
		                        		
		                        	
8.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.
		                        		
		                        		
		                        		
		                        	
9.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.
		                        		
		                        		
		                        		
		                        	
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
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