1. Lycium barbarian seed oil activates Nrf2/ARE pathway to reduce oxidative damage in testis of subacute aging rats
Rui-Ying TIAN ; Wen-Xin MA ; Zi-Yu LIU ; Hui-Ming MA ; Sha-Sha XING ; Na HU ; Chang LIU ; Biao MA ; Jia-Yang LI ; Hu-Jun LIU ; Chang-Cai BAI ; Dong-Mei CHEN
Chinese Pharmacological Bulletin 2024;40(3):490-498
Aim To explore the effects of Lycium berry seed oil on Nrf2/ARE pathway and oxidative damage in testis of subacute aging rats. Methods Fifty out of 60 male SD rats, aged 8 weeks, were subcutaneously injected with 125 mg • kg"D-galactosidase in the neck for 8 weeks to establish a subacute senescent rat model. The presence of senescent cells was observed using P-galactosidase ((3-gal), while testicular morphology was examined using HE staining. Serum levels of testosterone (testosterone, T), follicle-stimulating hormone ( follicle stimulating hormone, FSH ) , luteinizing hormone ( luteinizing hormone, LH ) , superoxide dis-mutase ( superoxide dismutase, SOD ) , glutathione ( glutathione, GSH) and malondialdehyde ( malondial-dehyde, MDA) were measured through ELISA, and the expressions of factors related to aging, oxidative damage, and the Nrf2/ARE pathway were assessed via immunohistochemical analysis and Western blotting. Results After successfully identifying the model, the morphology of the testis was improved and the intervention of Lycium seed oil led to a down-regulation in the expression of [3-gal and -yH2AX. The serum levels of SOD, GSH, T, and FSH increased while MDA and LH decreased (P 0. 05) . Additionally, there was an up-regulated expression of Nrf2, GCLC, NQOl, and SOD2 proteins in testicular tissue ( P 0. 05 ) and nuclear expression of Nrf2 in sertoli cells. Conclusion Lycium barbarum seed oil may reduce oxidative damage in testes of subacute senescent rats by activating the Nrf2/ARE signaling pathway.
2.Data Mining of Medication Rules for the Treatment of Atopic Dermatitis the Children by Chinese Medical Master XUAN Guo-Wei
Jin-Dian DONG ; Cheng-Cheng GE ; Yue PEI ; Shu-Qing XIONG ; Jia-Fen LIANG ; Qin LIU ; Xiu-Mei MO ; Hong-Yi LI
Journal of Guangzhou University of Traditional Chinese Medicine 2024;41(3):752-758
Objective Data mining technology was used to mine the medication rules of the prescriptions used in the treatment of pediatric atopic dermatitis by Chinese medical master XUAN Guo-Wei.Methods The medical records of effective cases of pediatric atopic dermatitis treated by Professor XUAN Guo-Wei at outpatient clinic were collected,and then the medical data were statistically analyzed using frequency statistics,association rule analysis and cluster analysis.Results A total of 242 prescriptions were included,involving 101 Chinese medicinals.There were 23 commonly-used herbs,and the 16 high-frequency herbs(frequency>100 times)were Glycyrrhizae Radix et Rhizoma,Saposhnikoviae Radix,Glehniae Radix,Perillae Folium,Ophiopogonis Radix,Cynanchi Paniculati Radix et Rhizoma,Microctis Folium,Dictamni Cortex,Scrophulariae Radix,Coicis Semen,Cicadae Periostracum,Lilii Bulbus,Rehmanniae Radix,Kochiae Fructus,Sclerotium Poriae Pararadicis,and Euryales Semen.The analysis of the medicinal properties showed that most of the herbs were sweet and cold,and mainly had the meridian tropism of the spleen,stomach and liver meridians.The association rule analysis yielded 24 commonly-used drug combinations and 20 association rules.Cluster analysis yielded 2 core drug combinations.Conclusion For the treatment of pediatric atopic dermatitis,Professor XUAN Guo-Wei focuses on the clearing,supplementing and harmonizing therapies,and the medication principle of"supporting the healthy-qi to eliminate the pathogen,and balancing the yin and yang"is applied throughout the treatment.
3.Effect and mechanism of dandelion flavonoids in alleviating lipopolysaccharide-induced colon epithelial cell injury
Jia-Qi ZHANG ; Dong-Xue MEI ; Sha LI ; Sheng-Gai GAO ; Jia ZHENG ; Hong-Xia LIANG ; Yi WANG
The Chinese Journal of Clinical Pharmacology 2024;40(4):549-553
Objective To investigate the protective effect of dandelion flavone(DF)on lipopolysaccharide(LPS)-induced colon epithelial cell injury by intervening oxidative stress and inflammation with AT-specific binding protein 2(SATB2).Methods Colon epithelial cells FHC were cultured.FHC cells were randomly divided into control group(normal cultured),LPS group(10 μg·mL-1 LPS),experimental-L group(10 μg·mL-1 LPS+1 μmol·L-1 DF),experimental-H group(10 μg·mL-1 LPS+5 μmol·L-1 DF),experimental-H+sh-NC group(transfected with sh-NC+10 μg·mL-1 LPS+5 μmol·mL-1 DF),experimental-H+sh-SATB2 group(transfected with sh-SATB2+10 μg·mL-1 LPS+5μmol·L-1 DF).The relative expression level of SATB2 protein in FHC cells was detected by Western blotting.The survival rate of FHC cells in each group was determined by tetramethylazolium blue(MTT).The apoptosis rate of FHC cells in each group was detected by flow cytometry.The levels of malondialdehyde(MDA)and interleukin-6(IL-6)in FHC cells were detected by the kit.Results The relative expression levels of SATB2 protein in control group,LPS group,experimental-H group,experimental-H+sh-NC group and experimental-H+sh-SATB2 group were 0.83±0.09,0.19±0.03,0.66±0.05,0.62±0.07 and 0.23±0.03,respectively;cell viability rates were(100.00±1.00)%,(48.16±4.31)%,(85.31±5.83)%,(81.39±6.47)%and(58.75±5.24)%,respectively;cell apoptosis rates were(3.27±0.81)%,(41.26±2.09)%,(11.35±1.04)%,(10.29±1.26)%and(35.87±2.15)%,respectively;MDA levels were(13.16±1.73),(52.87±3.49),(23.19±2.05),(20.98±3.17)and(44.87±3.05)μmol·L-1,respectively;IL-6 levels were(507.18±103.26),(2 132.09±198.15),(883.16±136.92),(801.69±119.85)and(1 736.29±206.91)pg·mL-1,respectively.The above indicators in the LPS group showed significant differences compared to the control group(all P<0.05);the above indicators in the experimental-H group showed significant differences compared to the LPS group(all P<0.05);the above indicators in the experimental-H+sh-SATB2 group showed significant differences compared to the experimental-H+sh-NC group(all P<0.05).Conclusion DF has a protective effect on LPS-induced colon epithelial cell injury by intervening oxidative stress and inflammation through SATB2.
4.Correlation between Combined Urinary Metal Exposure and Grip Strength under Three Statistical Models: A Cross-sectional Study in Rural Guangxi
Jian Yu LIANG ; Hui Jia RONG ; Xiu Xue WANG ; Sheng Jian CAI ; Dong Li QIN ; Mei Qiu LIU ; Xu TANG ; Ting Xiao MO ; Fei Yan WEI ; Xia Yin LIN ; Xiang Shen HUANG ; Yu Ting LUO ; Yu Ruo GOU ; Jing Jie CAO ; Wu Chu HUANG ; Fu Yu LU ; Jian QIN ; Yong Zhi ZHANG
Biomedical and Environmental Sciences 2024;37(1):3-18
Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95% confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.
5.The predictive value of peripheral blood NLR combined with serum trimethylamine oxide on in-hospital mortality events in patients with acute myocardial infarction and cardiogenic shock upon admission
Zhenli LUO ; Lisha MAO ; Mei KANG ; Gong ZHANG ; Yanbo SUN ; Fei JIA ; Yijuan DONG
Journal of Chinese Physician 2024;26(9):1379-1384
Objective:To explore the predictive value of peripheral blood neutrophil to lymphocyte ratio (NLR) and serum trimethylamine oxide (TMAO) on in-hospital mortality events in patients with acute myocardial infarction complicated by cardiogenic shock (AMICS) upon admission.Methods:A retrospective collection of medical records of 103 AMICS patients admitted to the Shanxi Yingkang Life General Hospital from January 2018 to June 2023 was conducted. The patients were divided into a survival group ( n=78) and a death group ( n=25) based on whether they experienced in-hospital mortality events. Two groups of peripheral blood NLR, serum TMAO, baseline data, and other laboratory indicators were compared. A logistic regression model was used to analyze the risk factors for in-hospital mortality in AMICS patients and a prediction model was constructed. We established receiver operating characteristic (ROC) curves to evaluate the predictive efficacy of peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and predictive model indicators for in-hospital mortality events in AMICS patients. Results:The peripheral blood NLR and serum TMAO levels in the death group were significantly higher than those in the survival group (all P<0.05). The age of the death group was higher than that of the survival group, and the proportion of hypertension, alanine aminotransferase, creatinine, random blood glucose, proportion of patients who did not receive emergency percutaneous coronary intervention (PCI) treatment, peak cardiac troponin I, B-type natriuretic peptide, Gensini score of coronary artery disease, and C-reactive protein were all higher than those of the survival group. Systolic blood pressure and platelet count were lower than those of the survival group, heart rate and erythrocyte sedimentation rate were faster than those of the survival group, and the pre hospital time was longer than that of the survival group. The differences were statistically significant (all P<0.05). The results of binary logistic regression analysis showed that after adjusting for confounding factors such as age, male proportion, body mass index, proportion of old myocardial infarction, proportion of hypertension, and proportion of PCI history, advanced age, long pre hospital time, failure to receive emergency PCI, elevated peripheral blood NLR, and elevated serum TMAO were independent risk factors for in-hospital mortality in AMICS patients ( P<0.05). The predictive model was obtained as 0.734×age+ 0.277×pre hospital time+ 2.263×failure to receive emergency PCI+ 0.549×peripheral blood NLR+ 0.608×serum TMAO-26.923. The ROC curve results showed that the area under the curve (AUC) values of peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and predictive model indicators for predicting in-hospital mortality events in AMICS patients were 0.744, 0.781, 0.825, and 0.921, respectively. When the optimal cutoff value was taken, the sensitivities were 0.880, 0.520, 0.680, and 0.880, and the specificities were 0.526, 0.923, 0.872, and 0.821, respectively. Conclusions:Advanced age, long pre hospital duration, failure to undergo emergency PCI, elevated peripheral blood NLR, and elevated serum TMAO are independent risk factors for in-hospital mortality in AMICS patients. Peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and prediction models all have certain predictive value for in-hospital mortality events in AMICS patients. Among them, the sensitivity and specificity of the prediction models are high, and the efficacy is good.
6.Clinical characterization and prediction modeling of lung cancer patients with high energy metabolism
Jiang-Shan REN ; Jun-Mei JIA ; Ping SUN ; Mei PING ; Qiong-Qiong ZHANG ; Yan-Yan LIU ; He-Ping ZHAO ; Yan CHEN ; Dong-Wen RONG ; Kang WANG ; Hai-Le QIU ; Chen-An LIU ; Yu-Yu FAN ; De-Gang YU
Medical Journal of Chinese People's Liberation Army 2024;49(9):1004-1010
Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.
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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