1.4 Weeks of HIIT Modulates Metabolic Homeostasis of Hippocampal Pyruvate-lactate Axis in CUMS Rats Improving Their Depression-like Behavior
Yu-Mei HAN ; Chun-Hui BAO ; Zi-Wei ZHANG ; Jia-Ren LIANG ; Huan XIANG ; Jun-Sheng TIAN ; Shi ZHOU ; Shuang-Shuang WU
Progress in Biochemistry and Biophysics 2025;52(6):1468-1483
ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) Smax+1 min (50%-55%) Smax, 3-5 cycles, Smax is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.
2.Epidemiological characteristics of cross-county imported dengue fever cases within Yunnan Province in 2023
Yerong TANG ; Hongning ZHOU ; Chao WU ; Chun WEI ; Xiaotao ZHAO ; Xuefei WANG ; Xiaolian GUO ; Jinyong JIANG
Chinese Journal of Schistosomiasis Control 2025;37(5):524-529
Objective To investigate the epidemiological characteristics of cross-county imported dengue fever cases within Yunnan province in 2023, so as to provide insights into formulation of preventive and control measures for intra-provincial spread of dengue fever. Methods All data pertaining cross-county imported dengue fever cases within Yunnan Province in 2023 were collected, and the temporal, regional and population distributions of the cases were descriptively analyzed. Results A total of 1 664 intra-provincial cross-county imported dengue fever cases were reported in 95 counties (cities, districts) cross 16 profectures (cities) in Yunnan Province in 2023, accounting for 12.34% of total cases in the province. Cross-county imported dengue fever cases were predominantly reported during the period between August and October (1 516 cases, 91.11% of total cases), and peaked in September (659 cases), with a single-day peak on October 8 (36 cases). During the period from September 4 to 10, five counties (cities) with local dengue fever epidemics, including Jinghong City of Xishuangbanna Dai Autonomous Prefecture, Gengma Dai and Wa Autonomous County of Lincang City, Ruili City of Dehong Dai and Jingpo Autonomous Prefecture, Mengla Coun ty of Xishuangbanna Dai Autonomous Prefecture, and Zhenkang County of Lincang City, exported 165 cross-county imported dengue fever cases to the rest of the province. Among the 1 644 intra-provincial cross-county imported dengue fever cases, the male to female ratio was 1.40∶1.00, and 1 329 cases were at ages of 15 to 55 years (79.87%), with farmers as the predominant occupation (886 cases, 53.25%). The top 5 counties (cities/districts) reporting the highest number of intra-provincial cross-county imported dengue fever cases included Simao District (266 cases) and Lancang Lahu Autonomous County (118 cases) of Pu’er City, Mengla County (91 cases) and Menghai County (91 cases) of Xishuangbanna Dai Autonomous Prefecture, and Mangshi City (73 cases) of Dehong Dai and Jingpo Autonomous Prefecture, which accounting for 38.40% of total imported cases. These intra-provincial cross-county imported dengue fever cases originated from 7 counties (cities/districts) in 4 prefectures (cities), including 1 261 cases (76.70%) from Jinghong City of Xishuangbanna Dai Autonomous Prefecture, 224 cases (13.63%) from Ruili City of Dehong Dai and Jingpo Autonomous Prefecture, 103 cases (6.27%) from Gengma Dai and Wa Autonomous County of Lincang City, 31 cases (1.89%) from Mengla County of Xishuangbanna Dai Autonomous Prefecture, 30 cases (1.82%) from Zhenkang County of Lincang City, 10 cases (0.61%) from Cangyuan Wa Autonomous County of Lincang City, and 5 cases (0.30%) from Mohan-Boten Economic Cooperation Zone of Kunming City. In addition, local dengue fever epidemics following intra-provincial cross-county importation of dengue fevers cases in Simao District, Jinggu Dai and Yi Autonomous County, Mangshi City, Longchuan County, and Cangyuan Wa Autonomous County. Conclusions Farmers and students are high-risk populations for intra-provincial cross-county imported dengue fever cases in Yunnan Province, and health education pertaining personal protection against dengue fever should be strengthened among these high-risk populations by governments at all levels. There is a high risk of local out-break of dengue fever following continuous introduction of intra-provincial cross-county imported cases. Standardized management of intra-provincial cross-county imported dengue fever cases should be reinforced to reduce the risk of local epidemics.
3.Comprehensive application of fingerprint studies, content determination, and chemometrics to identify geo-markers of Chuanxiong Rhizoma.
Meng-Yuan WU ; Cheng PENG ; Chun-Wang MENG ; Juan-Ru LIU ; Qin-Mei ZHOU ; Ou DAI ; Liang XIONG
China Journal of Chinese Materia Medica 2025;50(1):152-171
This study established a high performance liquid chromatography(HPLC) fingerprint of Chuanxiong Rhizoma from different producing areas and screened its potential differential components for producing areas by chemometrics. Furthermore, the content of the above differential components in Chuanxiong Rhizoma from different producing areas was measured and compared. Then, the geoherbalism markers(geo-markers) that can be used to distinguish Dao-di and non-Dao-di Chuanxiong Rhizoma were excavated by chemometrics. In fingerprint studies, a total of 27 common peaks were determined, and the fingerprint similarity for 37 batches of Chuanxiong Rhizoma samples from different producing areas was above 0.968. The orthogonal partial least squares-discriminant analysis(OPLS-DA) was capable of distinguishing Chuanxiong Rhizoma from Sichuan and from three other provinces, as well as Dao-di Chuanxiong Rhizoma(from Dujiangyan) and non-Dao-di Chuanxiong Rhizoma(from other producing areas) in Sichuan province. Meanwhile, 14 potential differential components in Chuanxiong Rhizoma from different provinces and 16 potential differential components in Chuanxiong Rhizoma from different producing areas in Sichuan were screened by the variable importance in projection(VIP) analysis under OPLS-DA. The reference standards were used to identify 10 potential differential components in the common peaks, and subsequent content determination verified that the content of the above 10 potential differential components was different among different producing areas. Then, the OPLS-DA and VIP analysis were performed with the content of the 10 potential differential components as variables. The results showed that Z-ligustilide, chlorogenic acid, and the ratio of butylidenephthalide/senkyunolide A were the geo-markers that can distinguish Chuanxiong Rhizoma from Sichuan and Chuanxiong Rhizoma from Shaanxi, Hebei, and Jiangxi, while Z-ligustilide, n-butylphthalide, and the ratios of Z-ligustilide/senkyunolide A and butylidenephthalide/senkyunolide A were the geo-markers that can distinguish Dao-di Chuanxiong Rhizoma(from Dujiangyan) and non-Dao-di Chuanxiong Rhizoma(from other producing areas) in Sichuan province. This study elucidated the differences in material basis of Dao-di and non-Dao-di Chuanxiong Rhizoma based on fingerprinting and content determination combined with chemometrics, which provides a reference for the study of material basis of Dao-di traditional Chinese medicine.
Drugs, Chinese Herbal/chemistry*
;
Rhizome/chemistry*
;
Chromatography, High Pressure Liquid/methods*
;
Chemometrics/methods*
;
Quality Control
4.Clinical and drug sensitivity characteristics of invasive non-typhoidal Salmonella enteritis in children aged 0-6 years in Chengdu, China, 2022-2023.
Ling-Rong YANG ; Chun-Ting ZHOU ; Jing GUO ; Yu-Lu WU ; Fu XIONG
Chinese Journal of Contemporary Pediatrics 2025;27(3):315-320
OBJECTIVES:
To investigate the clinical characteristics and drug resistance profile of invasive non-typhoidal Salmonella (NTS) enteritis in children in Chengdu, China, providing a reference for rational drug use and empirical treatment in clinical practice.
METHODS:
A retrospective analysis was conducted on the clinical data of 130 children with invasive bacterial enteritis due to NTS identified by fecal bacterial culture and the results of drug sensitivity tests for NTS in Chengdu from January 2022 to December 2023.
RESULTS:
NTS infections were mainly observed from April to September (113 cases, 86.9%), with a peak in August (36 cases, 27.7%). Children aged <36 months accounted for 86.2% (112/130) of all cases, and the main symptoms were diarrhea (130 cases, 100%), fever (123 cases, 94.6%), and hematochezia (112 cases, 86.2%). The 130 NTS isolates exhibited a sensitivity rate of 64.6% to ceftriaxone and 63.8% to cefotaxime, and a sensitivity rate of >90.0% to piperacillin-tazobactam and nitrofurantoin (nitrofurans). The detection rate of multidrug-resistant strains was 48.5% (63/130), and the clinical efficacy of third-generation cephalosporins used in 38 patients (29.2%) was inconsistent with the results of drug sensitivity tests.
CONCLUSIONS
The peak of invasive NTS enteritis in children aged 0-6 years occurs in August in the Chengdu area, with a relatively high incidence rate in children aged <36 months. The situation of drug resistance is severe for NTS, and piperacillin-tazobactam may be an effective option for treating multidrug-resistant NTS infections in children, while nitrofuran antibiotics might be used to treat such infections.
Humans
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Infant
;
Child, Preschool
;
Enteritis/microbiology*
;
Retrospective Studies
;
Male
;
Salmonella Infections/microbiology*
;
Female
;
Child
;
Salmonella/drug effects*
;
Infant, Newborn
;
Microbial Sensitivity Tests
;
Anti-Bacterial Agents/therapeutic use*
5.Causal relationship between Helicobacter pylori infection and childhood immune thrombocytopenia and influencing factors for prognosis.
Xiao-Yang ZHOU ; Mei YAN ; Ying-Bin YUE ; Hailigulli NURIDDIN ; Xue-Mei WANG ; Yong-Feng CHENG ; Chun-Can WU ; Yu LIU
Chinese Journal of Contemporary Pediatrics 2025;27(9):1105-1112
OBJECTIVES:
To investigate the causal relationship between Helicobacter pylori (Hp) infection and immune thrombocytopenia (ITP) using Mendelian randomization (MR), as well as the association between Hp infection and chronic ITP (cITP) through a clinical study.
METHODS:
The datasets from genome-wide association studies were used to select the single nucleotide polymorphism loci significantly associated with Hp infection as genetic instrumental variables. The MR analysis model was used to investigate the causal relationship between ITP and Hp infection. A retrospective analysis was conducted on the medical data of 316 children with newly diagnosed ITP at the First Affiliated Hospital of Xinjiang Medical University from January 2020 to December 2023. The children were followed up for 1 year, and a multivariate logistic regression analysis was used to investigate the risk factors for cITP.
RESULTS:
The inverse variance weighted analysis revealed that Hp infection was significantly associated with an increased risk of ITP (OR=1.280, 95%CI: 1.098-1.492, P=0.002). There was no heterogeneity or pleiotropy in this MR study (P>0.05), and the model was stable. The "leave-one-out" sensitivity analysis verified the reliability of the results. The multivariate logistic regression analysis demonstrated that Hp infection was an independent risk factor for progression to cITP (OR=7.916, 95%CI: 3.327-18.832, P<0.001).
CONCLUSIONS
Hp infection is a risk factor for the onset of ITP and is an independent risk factor for cITP in children.
Humans
;
Helicobacter Infections/complications*
;
Purpura, Thrombocytopenic, Idiopathic/etiology*
;
Child
;
Male
;
Female
;
Helicobacter pylori
;
Prognosis
;
Child, Preschool
;
Logistic Models
;
Retrospective Studies
;
Risk Factors
;
Polymorphism, Single Nucleotide
;
Adolescent
;
Infant
6.Seminal plasma miR-26a-5p influences sperm DNA integrity by targeting and regulating the PTEN gene.
Chun-Hui LIU ; Wen-Sheng SHAN ; Zhi-Qiang WANG ; Shao-Jun LI ; Chen ZHU ; Hai WANG ; Yu-Na ZHOU ; Rui-Peng WU
National Journal of Andrology 2025;31(9):780-790
OBJECTIVE:
By analyzing the differential miRNA in seminal plasma between individuals with normal and abnormal sperm DNA fragmentation index(DFI), we aim to identify miRNA that may impact sperm DNA integrity and target genes, and attempt to analyze their potential mechanisms of action.
METHODS:
A total of 161 study subjects were collected and divided into normal control group, DFI-medium group and DFI-abnormal group based on the DFI detection values. Differential miRNA were identified through miRNA chip analysis. Through bioinformatics analysis and target gene prediction, miRNA related to DFI and specific target genes were identified. The relative expression levels of differential miRNA and target genes in each group were compared to explore the impact of their differential expression on DFI.
RESULTS:
Through miRNA chip analysis, a total of 11 differential miRNA were detected. Bioinformatics analysis suggested that miR-26a-5p may be associated with reduced sperm DNA integrity. And gene prediction indicated that PTEN was a specific target gene of miR-26a-5p. Compared to the normal control group, the relative expression levels of miR-26a-5p in both the DFI-medium group and the DFI-abnormal group showed a decrease, while the relative expression levels of PTEN showed an increase. The relative expression levels of miR-26a-5p in all groups were negatively correlated with DFI values, while the relative expression levels of PTEN showed a positive correlation with DFI values in the DFI-medium group and the DFI-abnormal group. The AUC of miR-26a-5p in the DFI-medium group was 0.740 (P<0.05), with a sensitivity of 73.6% and a specificity of 71.5%; the AUC of PTEN was 0.797 (P<0.05), with a sensitivity of 76.5% and a specificity of 78.4%. In the DFI-abnormal group, the AUC of miR-26a-5p was 0.848 (P<0.05), with a sensitivity of 81.3% and a specificity of 78.1%. While the AUC of PTEN was 0.763 (P<0.05), with a sensitivity of 77.2% and a specificity of 80.2%.
CONCLUSION
miR-26a-5p affects the integrity of sperm DNA by regulating the expression of PTEN negatively. The relative expression levels of seminal plasma miR-26a-5p and PTEN have good diagnostic value for sperm DNA integrity damage, which can help in the etiological diagnosis and prognosis analysis of abnormal DFI. This provides a diagnostic and treatment approach for the study and diagnosis of DFI abnormalities without clear etiology.
Male
;
Humans
;
MicroRNAs/genetics*
;
PTEN Phosphohydrolase/genetics*
;
Spermatozoa
;
Semen/metabolism*
;
DNA Fragmentation
7.Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program
Ming-Ying LU ; Chung-Feng HUANG ; Chao-Hung HUNG ; Chi‐Ming TAI ; Lein-Ray MO ; Hsing-Tao KUO ; Kuo-Chih TSENG ; Ching-Chu LO ; Ming-Jong BAIR ; Szu-Jen WANG ; Jee-Fu HUANG ; Ming-Lun YEH ; Chun-Ting CHEN ; Ming-Chang TSAI ; Chien-Wei HUANG ; Pei-Lun LEE ; Tzeng-Hue YANG ; Yi-Hsiang HUANG ; Lee-Won CHONG ; Chien-Lin CHEN ; Chi-Chieh YANG ; Sheng‐Shun YANG ; Pin-Nan CHENG ; Tsai-Yuan HSIEH ; Jui-Ting HU ; Wen-Chih WU ; Chien-Yu CHENG ; Guei-Ying CHEN ; Guo-Xiong ZHOU ; Wei-Lun TSAI ; Chien-Neng KAO ; Chih-Lang LIN ; Chia-Chi WANG ; Ta-Ya LIN ; Chih‐Lin LIN ; Wei-Wen SU ; Tzong-Hsi LEE ; Te-Sheng CHANG ; Chun-Jen LIU ; Chia-Yen DAI ; Jia-Horng KAO ; Han-Chieh LIN ; Wan-Long CHUANG ; Cheng-Yuan PENG ; Chun-Wei- TSAI ; Chi-Yi CHEN ; Ming-Lung YU ;
Clinical and Molecular Hepatology 2024;30(1):64-79
Background/Aims:
Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy.
Methods:
We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment.
Results:
The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset.
Conclusions
Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.
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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