1.Sesquiterpene ZH-13 from Aquilariae Lignum Resinatum Improves Neuroinflammation by Regulating JNK Phosphorylation
Ziyu YIN ; Yun GAO ; Junjiao WANG ; Weigang XUE ; Xueping PANG ; Huiting LIU ; Yunfang ZHAO ; Huixia HUO ; Jun LI ; Jiao ZHENG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(1):139-145
ObjectiveTo study the pharmacological substances and mechanisms through which sesquiterpene ZH-13 from Aquilariae Lignum Resinatum improves neuroinflammation. MethodsBV-2 microglial cells were stimulated with lipopolysaccharide (LPS) to induce neuroinflammation. The cells were divided into the normal group, the model group, and the ZH-13 low- and high-dose treatment groups (10, 20 μmol·L-1). The model group was treated with 1 μmol·L-1 LPS. Cell viability was assessed using the cell proliferation and activity assay (CCK-8 kit). Nitric oxide (NO) release in the cell supernatant was measured using a nitric oxide kit (Griess method). The mRNA expression levels of interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), inducible nitric oxide synthase (iNOS), and interleukin-6 (IL-6) were detected by real-time fluorescence quantitative polymerase chain reaction (Real-time PCR). The phosphorylation of mitogen-activated protein kinase (MAPK) pathway proteins was assessed by Western blot. ResultsCompared with the model group, ZH-13 dose-dependently reduced NO release from BV-2 cells under LPS stimulation (P<0.05, P<0.01). In the 20 μmol·L-1 ZH-13 treatment group, the mRNA expression levels of IL-1β, TNF-α, iNOS, and IL-6 were significantly reduced compared to the model group (P<0.05, P<0.01). In both the low- and high-dose ZH-13 groups, the expression of the inflammatory factor TNF-α and the phosphorylation of c-Jun N-terminal kinase (JNK) in the upstream MAPK pathway were significantly reduced (P<0.05). After stimulation with the JNK agonist anisomycin (Ani), both low- and high-dose ZH-13 treatment groups showed reduced phosphorylation of JNK proteins compared to the Ani-treated group (P<0.01). ConclusionThe sesquiterpene compound ZH-13 from Aquilariae Lignum Resinatum significantly ameliorates LPS-induced neuroinflammatory responses in BV-2 cells by inhibiting excessive JNK phosphorylation and reducing TNF-α expression. These findings elucidate the pharmacological substances and mechanisms underlying the sedative and calming effects of Aquilariae Lignum Resinatum.
2.A novel TNKS/USP25 inhibitor blocks the Wnt pathway to overcome multi-drug resistance in TNKS-overexpressing colorectal cancer.
Hongrui ZHU ; Yamin GAO ; Liyun LIU ; Mengyu TAO ; Xiao LIN ; Yijia CHENG ; Yaoyao SHEN ; Haitao XUE ; Li GUAN ; Huimin ZHAO ; Li LIU ; Shuping WANG ; Fan YANG ; Yongjun ZHOU ; Hongze LIAO ; Fan SUN ; Houwen LIN
Acta Pharmaceutica Sinica B 2024;14(1):207-222
Modulating Tankyrases (TNKS), interactions with USP25 to promote TNKS degradation, rather than inhibiting their enzymatic activities, is emerging as an alternative/specific approach to inhibit the Wnt/β-catenin pathway. Here, we identified UAT-B, a novel neoantimycin analog isolated from Streptomyces conglobatus, as a small-molecule inhibitor of TNKS-USP25 protein-protein interaction (PPI) to overcome multi-drug resistance in colorectal cancer (CRC). The disruption of TNKS-USP25 complex formation by UAT-B led to a significant decrease in TNKS levels, triggering cell apoptosis through modulation of the Wnt/β-catenin pathway. Importantly, UAT-B successfully inhibited the CRC cells growth that harbored high TNKS levels, as demonstrated in various in vitro and in vivo studies utilizing cell line-based and patient-derived xenografts, as well as APCmin/+ spontaneous CRC models. Collectively, these findings suggest that targeting the TNKS-USP25 PPI using a small-molecule inhibitor represents a compelling therapeutic strategy for CRC treatment, and UAT-B emerges as a promising candidate for further preclinical and clinical investigations.
3.Correlation between daily exercise load and physical fitness among primary school students
ZHAO Pengrui, HU Songhan, WU Zhigui, DING Tiancui, XUE Jiao, HOU Lijuan
Chinese Journal of School Health 2024;45(1):124-128
Objective:
To understand the relationship between daily exercise load and physical fitness of primary school students, so as to provide relevant theoretical basis for the development of on campus physical education plans and the improvement of procedural physical health management for elementary school students.
Methods:
A total of 223 students from 6 classes in a primary school in Beijing were selected by a stratified random cluster sampling method from May to June 2023. The daily exercise load of the students was monitored by Polar Verity Sense heart rate armband. The duration of moderate to vigorous physical activity (MVPA) and daily Training Impulse (TRIMP) value were calculated, and the related indexes of daily exercise load were analyzed. Chi square test and univariate Logistic regression analysis were used to analyze the correlation between daily exercise load and physical fitness assessment levels, and multi factor ordinal Logistic regression analysis was used to explore the influencing factors of physical fitness assessment levels.
Results:
The average time spent in MVPA was (21.65±17.48) min. The TRIMP value was (361.47±124.81). The time spent in MVPA of primary school students in outdoor class, zero point sports, recess and after class PE were ( 8.86 ±8.56, 9.41±10.47, 1.97±3.12, 2.46±2.57) min, respectively. TRIMP values were (68.89±20.84, 72.83±30.27, 51.68±18.23, 19.99±5.78) in outdoor class, zero point sports, recess and after class PE, respectively. The results of univariate analysis showed that there were statistically significant differences in physical fitness levels among students with different genders, grades, and BMI ( χ 2=7.13, 19.04, 32.98, P <0.05). The duration of daily MVPA, along with TRIMP value during outdoor class, zero point sports, recess, and after PE class were all statistically significant with physical fitness levels ( OR =1.07, 1.05, 1.02, 1.03, 1.11, P <0.05). The results of multi factor ordinal Logistic regression analysis showed that the primary school grade (lower grade: OR =9.24, middle grade: OR =7.81), BMI (abnormal: OR =0.21), duration of daily MVPA in school ( OR =1.06), and TRIMP value during outdoor class ( OR =1.05) were statistically significant with physical fitness levels ( P <0.05).
Conclusions
There is a positive correlation between physical fitness and different grades, BMI, daily exercise load, and outdoor exercise load. Increasing daily exercise load can improve students physical health. It is suggested to tailor the school sports program to suit primary school students, increase both the intensity and duration of school daily sports, and promote procedural physical health management for elementary school students.
4.Study on the detection rate,epidemiology and resistance mechanism of MRSA in a hospital in recent 5 years
Jianchun HE ; Changzhen PEI ; Lei YANG ; Junying ZHAO ; Jiao XIE ; Xue LI
International Journal of Laboratory Medicine 2024;45(4):480-485
Objective To investigate the detection rate,epidemiology and resistance mechanism of methicil-lin-resistant Staphylococcus aureus(MRSA)in a hospital in recent 5 years.Methods A total of 762 strains of non repetitive Staphylococcus aureus detected from 2016 to 2020 in a hospital were collected retrospectively.Methicillin-sensitive Staphylococcus aureus(MSSA)was 392 strains(MSSA group)and 370 strains caused by MRSA(MRSA group),and 95 strains of MRSA isolated in 2020 were further used for resistance mechanism.Staphylococcus aureus was identified and tested for drug sensitivity by Vitek 2 automatic microbial system.Molecular epidemiological typing was determined by multilocus sequence typing.The biofilm formation was performed by crystal violet staining.PCR amplification was used to detect drug resistance genes,virulence genes and biofilm related genes,and logistic regression analysis was used to investigate the independent risk factors of its occurrence.Results The detection rate of MRSA in past five years was 48.56%,mainly was from pus samples and secretion samples(38.38%,33.51%respectively).MRSA was found in the general sur-gery(18.65%)and otorhinolaryngology(12.70%).ST88 was the most common multilocus sequence typing(37.89%),and followed by ST951(24.21%).Moderate biofilm formation was the most common,accounting for 74.73%.Multivariate regression analysis showed that compared with MSSA group,hypoproteinemia,en-docrine system diseases,wound infection and history of antibiotic use within six months were the independent risk factors for infection in MRSA group.Compared with the control group,hospital transfer,wound infection and tumor were independent risk factors for infection in MRSA group(P<0.05).Conclusion The detection rate of MRSA in a hospital is high,and the carrying rate of various drug-resistant genes is high.The hospital should pay attention to the prevalence of MRSA and related risk factors,so as to prevent it early.
5.The thought and method of constructing diagnostic specification for syndrome/pattern of defensive qi deficiency
Yuwen CHE ; Tianfang WANG ; Yang JIAO ; Yan ZHAO ; Zhisong WU ; Xiuyan WU ; Zhaolan LIU ; Xiaolin XUE ; Ning LI
Journal of Beijing University of Traditional Chinese Medicine 2024;47(8):1180-1184
The syndrome/pattern of defensive qi deficiency is a common basic syndrome of traditional Chinese medicine in clinical practice. However,there is a lack of standardized and operable diagnostic specifications in practical applications. Based on the previous literature,this study proposed the idea of starting from the elements of the syndrome,qualitative diagnostic criteria for the syndrome/pattern of defensive qi deficiency oriented to the entire region of the disease were constructed based on the two dimensions of " deficient defensive qi failing to consolidate the exterior" and " qi deficiency" and constructing a set of quantitative evaluation criteria as the supporting content for the diagnostic items. The core members of the research group attempted to formulate the draft standard,then reached a consensus through the Delphi method expert questionnaire consultation and the Nominal group technique,and finally evaluated the reliability and validity of the standard through clinical verification to provide ideas for the standardization and normalization of research on syndromes.
6.Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators
Zhaoyu GUO ; Juping SHAO ; Xiaoqing ZOU ; Qinping ZHAO ; Peijun QIAN ; Wenya WANG ; Lulu HUANG ; Jingbo XUE ; Jing XU ; Kun YANG ; Xiaonong ZHOU ; Shizhu LI
Chinese Journal of Schistosomiasis Control 2024;36(3):251-258
Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.
7.TSHR Variant Screening and Phenotype Analysis in 367 Chinese Patients With Congenital Hypothyroidism
Hai-Yang ZHANG ; Feng-Yao WU ; Xue-Song LI ; Ping-Hui TU ; Cao-Xu ZHANG ; Rui-Meng YANG ; Ren-Jie CUI ; Chen-Yang WU ; Ya FANG ; Liu YANG ; Huai-Dong SONG ; Shuang-Xia ZHAO
Annals of Laboratory Medicine 2024;44(4):343-353
Background:
Genetic defects in the human thyroid-stimulating hormone (TSH) receptor (TSHR) gene can cause congenital hypothyroidism (CH). However, the biological functions and comprehensive genotype–phenotype relationships for most TSHR variants associated with CH remain unexplored. We aimed to identify TSHR variants in Chinese patients with CH, analyze the functions of the variants, and explore the relationships between TSHR genotypes and clinical phenotypes.
Methods:
In total, 367 patients with CH were recruited for TSHR variant screening using whole-exome sequencing. The effects of the variants were evaluated by in-silico programs such as SIFT and polyphen2. Furthermore, these variants were transfected into 293T cells to detect their Gs/cyclic AMP and Gq/11 signaling activity.
Results:
Among the 367 patients with CH, 17 TSHR variants, including three novel variants, were identified in 45 patients, and 18 patients carried biallelic TSHR variants. In vitro experiments showed that 10 variants were associated with Gs/cyclic AMP and Gq/11 signaling pathway impairment to varying degrees. Patients with TSHR biallelic variants had lower serum TSH levels and higher free triiodothyronine and thyroxine levels at diagnosis than those with DUOX2 biallelic variants.
Conclusions
We found a high frequency of TSHR variants in Chinese patients with CH (12.3%), and 4.9% of cases were caused by TSHR biallelic variants. Ten variants were identified as loss-of-function variants. The data suggest that the clinical phenotype of CH patients caused by TSHR biallelic variants is relatively mild. Our study expands the TSHR variant spectrum and provides further evidence for the elucidation of the genetic etiology of CH.
8.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.
9.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.
10.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.


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