1.Association between medium to long term ambient PM 2.5 exposure and overweight/obesity among primary and secondary school students
Chinese Journal of School Health 2025;46(7):937-940
		                        		
		                        			Objective:
		                        			To investigate the association between medium  to long term PM 2.5  exposure around school areas and overweight/obesity among primary and secondary school students in Guangxi, providing data support and theoretical foundations for scientifically addressing overweight and obesity in primary and secondary school students.
		                        		
		                        			Methods:
		                        			From September to November 2023, a stratified cluster random sampling method was employed to select 251 183 students aged 7-18 years (grade 1 to grade 12) from 14 prefecture level cities (111 districts and counties) in Guangxi. PM 2.5  mass concentration data were obtained from the Tracking Air Pollution in China (TAP) dataset. Preliminary comparative analysis was conducted using the Mann-Whitney  U  test, while binary Logistic regression models were applied to quantify the relationship between PM 2.5  exposure and overweight/obesity. Restricted cubic spline analysis was further utilized to examine the nonlinear association between PM 2.5  concentration and overweight/obesity risk.
		                        		
		                        			Results:
		                        			The detection rate of overweight/obesity among Guangxi students in 2023 was 19.5%. The median PM 2.5  concentration in the year prior to the study was higher in the overweight/obesity group (23.22 μg/m 3) compared to the non overweight/obesity group (22.63 μg/m 3) ( Z=-15.66, P <0.01), and consistent trends were observed across gender (male/female) and educational stage (primary/junior/senior high school) subgroups (all  P <0.01). Binary Logistic regression revealed that for every 10 μg/m 3 increase in the annual average PM 2.5  concentration, the risk of overweight/obesity increased by 12% ( OR=1.12, 95%CI=1.09- 1.15 , P <0.01). Restricted cubic spline analysis indicated a nonlinear relationship between monthly PM 2.5  levels and overweight/obesity risk ( P trend <0.01). Below 22.68 μg/m 3, PM 2.5  exposure showed no significant association with obesity risk; above the threshold, the risk increased with rising PM 2.5  levels.
		                        		
		                        			Conclusion
		                        			Medium  to long term PM 2.5  exposure around school environments is significantly associated with overweight/obesity among primary and secondary school students.
		                        		
		                        		
		                        		
		                        	
2.Spinal curvature abnormalities and related factors among primary and secondary school students in Guangxi in 2023
LUO Yuemei, LI Yan, REN Yiwen, DONG Yonghui, CHEN Li, ZHANG Dengcheng, ZHANG Yi, MA Jun, DONG Yanhui
Chinese Journal of School Health 2025;46(5):712-716
		                        		
		                        			Objective:
		                        			To investigate the prevalence and associated factors of spinal curvature abnormalities among primary and secondary school students in the Guangxi Zhuang Autonomous Region, so as to provide a scientific basis for the prevention and control of such abnormalities.
		                        		
		                        			Methods:
		                        			From September to November 2023, adopting a stratified cluster random sampling method, spinal curvature screenings and questionnaire surveys were conducted among 168 931 students from grade 4 of primary school to grade 12 of high school in 111 districts and counties across 14 cities in Guangxi.  Chi square tests and binary Logistic regression analysis were used to analyze influencing factors of spinal curvature abnormalities.
		                        		
		                        			Results:
		                        			In 2023, the detection rate of poor posture among students above grade 4 in Guangxi was  4.24% , and the detection rate of spinal curvature abnormalities was 2.13%. The detection rate was higher among urban students (2.84%) than rural students (1.66%), boarding students (2.61%) than non-boarding students (1.60%), and high school students (3.16%) than junior high (2.45%) and primary school students (1.15%), and the differences were statistically significant ( χ 2=269.85, 221.44, 565.10,  P <0.01). A trend of increasing detection rates with higher grade levels was observed ( χ 2 trend =617.63,  P <0.01). Binary Logistic regression analysis indicated that students without boarding at school ( OR =0.82, 95% CI =0.75-0.90), engaging in high-intensity physical activity for over 60 min per day ≥5 days per week ( OR =0.90, 95% CI =0.82-0.98), and adequate sleep ( OR =0.87, 95% CI =0.81-0.94) had lower risks of detecting spinal curvature abnormalities ( P <0.05).
		                        		
		                        			Conclusions
		                        			The prevalence of spinal curvature abnormalities increases with grade level among primary and secondary school students in Guangxi. Regular moderate-to-vigorous physical activity demonstrates protective effects against spinal abnormalities.
		                        		
		                        		
		                        		
		                        	
3.Transcriptional differential analysis of ocular surface ectoderm and surface ectoderm
Lu SUN ; Canwei ZHANG ; Yuwen SONG ; Jianxin LI ; Lian DUAN ; Yang GAO ; Yuemei XIE ; Luping WANG ; Guangfu DANG
International Eye Science 2024;24(5):677-685
		                        		
		                        			
		                        			 AIM:To identify transcriptional differences between the ocular surface ectoderm(OSE)and surface ectoderm(SE)using RNA-seq, and elucidate the OSE transcriptome landscape and the regulatory networks involved in its development.METHODS:OSE and SE cells were differentiated from human embryonic stem(hES)cells. Differentially expressed genes(DEGs)between OSE and SE were analyzed using RNA-seq. Based on the DEGs, we performed gene ontology(GO)analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis, and protein-protein interaction(PPI)network analysis. Transcription factors(TFs)and hub genes were screened. Subsequently, TF-gene and TF-miRNA regulatory networks were constructed using the NetworkAnalyst platform.RESULTS:A total of 4 182 DEGs were detected between OSE and SE cells, with 2 771 up-regulated and 1 411 down-regulated genes in OSE cells. GO-BP analysis revealed that up-regulated genes in OSE were enriched in the regulation of ion transmembrane transport, axon development, and modulation of chemical synaptic transmission. Down-regulated genes were primarily involved in nuclear division, chromosome segregation, and regulation of cell cycle phase transition. KEGG analysis indicated that up-regulated genes in OSE cells were enriched in signaling pathways such as cocaine addiction, axon guidance, and amphetamine addiction, while down-regulated genes were enriched in proteoglycans in cancer, ECM-receptor interaction, protein digestion and absorption, and cytokine-cytokine receptor interaction. Additionally, compared with SE, 204 TFs(including FOS, EGR1, POU5F1, SOX2, and PAX6)were up-regulated, and 80 TFs(including HAND2, HOXB6, HOXB5, HOXA5, and HOXB8)were down-regulated in OSE cells. Furthermore, we identified 6 up-regulated and 9 down-regulated hub genes in OSE cells, and constructed TF-gene and TF-miRNA regulatory networks based on these hub genes.CONCLUSIONS:The transcriptome characteristics of OSE and SE cells were elucidated through RNA-seq analysis. These findings may provide a novel insight for studies on the development and in vitro directed induction of OSE and corneal epithelial cells. 
		                        		
		                        		
		                        		
		                        	
4.Longitudinal extrauterine growth restriction in extremely preterm infants: current status and prediction model
Xiaofang HUANG ; Qi FENG ; Shuaijun LI ; Xiuying TIAN ; Yong JI ; Ying ZHOU ; Bo TIAN ; Yuemei LI ; Wei GUO ; Shufen ZHAI ; Haiying HE ; Xia LIU ; Rongxiu ZHENG ; Shasha FAN ; Li MA ; Hongyun WANG ; Xiaoying WANG ; Shanyamei HUANG ; Jinyu LI ; Hua XIE ; Xiaoxiang LI ; Pingping ZHANG ; Hua MEI ; Yanju HU ; Ming YANG ; Lu CHEN ; Yajing LI ; Xiaohong GU ; Shengshun QUE ; Xiaoxian YAN ; Haijuan WANG ; Lixia SUN ; Liang ZHANG ; Jiuye GUO
Chinese Journal of Neonatology 2024;39(3):136-144
		                        		
		                        			
		                        			Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.
		                        		
		                        		
		                        		
		                        	
5.Clinicopathological and molecular genetic features of confined placental mosaicism
Aichun WANG ; Junling XIE ; Jianjiang ZHU ; Yuemei ZHANG ; Muyu ZHANG ; Hong QI ; Yiqun GU
Chinese Journal of Pathology 2024;53(7):697-701
		                        		
		                        			
		                        			Objective:To investigate the clinicopathological and genetic features of confined placental mosaicism (CPM) and its effect on fetal intrauterine growth.Methods:Fourteen CPM cases of Haidian Maternal and Children Health Hospital were collected from May 2018 to March 2022. Clinicopathological examination on placental specimens and molecular genetic analysis were performed.Results:The age of the parturient women ranged from 27 to 34 years, with an average age of (30.0±3.54) years. The gestational weeks ranged from 35 +1 to 41 +2 weeks. There were 4 premature births and 10 term births, among which 6 were female and 8 were male fetuses. Nine cases (9/14) had adverse pregnancy outcomes, including 7 cases of fetal growth restriction. The weight of CPM placenta decreased, with 6 cases below the 10th percentile of weight standards and 5 cases between the 10th and 25th percentile. All 14 CPM placental specimens showed morphological changes of perfusion dysfunction to varying degrees, with mainly placental-maternal vascular malperfusion followed by placental-fetal vascular malperfusion. The mosaic chromosomes in different CPM cases varied, with 16-trisomy/monosomy mosaicism being the most common followed by 7-trisomy and 21-trisomy/monosomy mosaicism. The mosaic proportion was unequal in different parts of the same CPM placenta, with the mosaic proportion of umbilical cord, fetal membranes, fetal surface, maternal surface, and edge ranging from 1% to 70%. Conclusions:The mosaic chromosomes in different CPM cases vary, and the mosaic proportion is unequal in different parts of the same CPM placenta. The pathological morphology is mainly manifested as perfusion dysfunction, which can lead to adverse pregnancy outcomes such as fetal growth restriction and preterm birth.
		                        		
		                        		
		                        		
		                        	
6.Study on the Material Basis of Guiqi Baizhu Prescription Inhibiting the Proliferation of Uveal Melanoma Cells Based on Traditional Chinese Medicine Chemical Bioinformatics
WANG Ruifeng ; JIN Xiaojie ; LIU Hao ; LI Chenghao ; ZHANG Min ; Li Mi ; LI Haotian ; ZHANG Yu ; MA Huanhuan ; ZHANG Yuemei
Chinese Journal of Modern Applied Pharmacy 2024;41(14):1900-1912
		                        		
		                        			ABATRACT
		                        			OBJECTIVE To utilize the pharmacophore model-molecular docking combined with the virtual screening strategy of free energy calculation and the chemical bioinformatics method of traditional Chinese medicine in cell biology experiments to investigate the components of Guiqi Baizhu prescription that target phosphatidylinositol 3-kinase(PI3K) and inhibit the proliferation of uveal melanoma(UM) cells.
METHODS The pharmacophore model of PI3K inhibitor was constructed, and the compounds of Guiqi Baizhu prescription were virtual screened. The components that fit the pharmacophore model were calculated by molecular docking and binding free energy, and the potential inhibitory components were selected for biological experimental evaluation. The effects of potential inhibitory components on UM cell proliferation were detected by CCK-8 and clonal formation assay. Flow cytometry was used to detect the cell cycle and apoptosis of UM cells. The mitochondrial membrane potential of UM cells was detected using JC-10 staining. The expressions of PI3K and downstream pathway proteins were detected by Western blotting.RESULTS The pharmacophore model included 2 hydrogen bond receptors, 2 aromatic ring centers, and exclusion volumes. The results of the CCK-8 experiment showed that quercetin, tangerine, and nobiletin at concentrations of 10, 20, 40, 80 μmol·L−1, and cyrtin at concentrations of 20, 40, 80 μmol·L−1, were able to inhibit the proliferation of UM cells. The clonal formation experiment showed that quercetin, tangerine, nobiletin, and morusin, at different concentrations, could significantly inhibit the clonal proliferation of UM cells. Flow cytometry showed that UM cells were arrested in the G0/G1 phase by tangeretin and quercetin, while UM cells were arrested in the G2/M phase by nobiletin and morusin. The results of JC-10 staining showed that quercetin, nobiletin, tangeretin, and morusin could reduce the mitochondrial membrane potential of UM cells. Western blotting results showed that 4 compounds could target PI3K, but their downstream pathways were different.CONCLUSION Based on the method of chemical bioinformatics in traditional Chinese medicine, this study explores the material basis for the inhibition of UM cell proliferation by the Guiqi Baizhu prescription. It also provides insights for the modern development of traditional Chinese medicine prescription.
		                        		
		                        		
		                        		
		                        	
7.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
		                        		
		                        			
		                        			Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
		                        		
		                        		
		                        		
		                        	
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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