1.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
2.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
3.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
4.Sex-specific imaging-genetic analysis of gray matter volume abnormalities in children with autism spectrum disorder
Xiaotian WANG ; Youyi LI ; Qing YIN ; Xiaolong SHAN ; Huafu CHEN ; Xujun DUAN
Chinese Journal of Psychiatry 2025;58(11):830-842
Objective:This study aims to investigate sex-specific abnormalities?? in gray matter volume (GMV) in Children with autism spectrum disorder (ASD) and their associations with gene expression.Methods:T 1-weighted brain MRI data were collected at the MRI Center of the University of Electronic Science and Technology of China between 2022 and 2023 from 100 children with ASD and 90 typically developing (TD) children. Voxel-based morphometry (VBM) was used to explore GMV differences between ASD boys and TD boys, and between ASD girls and TD girls. Partial least squares regression (PLSR) was performed based on the Allen Human Brain Atlas to identify genes associated with GMV alterations, followed by enrichment analyses. Cell-type-specific expression analyses were used to examine associations across developmental stages and brain structures. Protein-protein interaction (PPI) networks were constructed to identify hub proteins. Results:Compared to TD boys, ASD boys showed increased GMV in the right superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, temporal pole, parahippocampal gyrus, fusiform gyrus, cuneus, and precuneus, as well as in the bilateral orbital part of the superior frontal gyrus and the gyrus rectus. Decreased GMV was observed in the cerebellar vermis and bilateral cerebellar hemispheres. A total of 635 genes were associated with these GMV alterations, enriched in pathways related to DNA-templated transcription, RNA metabolism and biogenesis, and ion binding. Developmental analysis indicated strong associations with the cerebellum during early, middle-to-late childhood, and adolescence, and with the cerebral cortex in early adulthood. Protein-protein interaction (PPI) network analysis highlighted NOB1, GNL3L, ESF1, TFB2M, and WDR75 as specific hub proteins. Compared to TD girls, ASD girls exhibited increased GMV in the right middle and inferior temporal gyri, temporal pole, and fusiform gyrus, and decreased GMV in the cerebellar vermis and bilateral cerebellar hemispheres. A total of 765 genes were associated, enriched in pathways related to ion channel activity, signal transduction, and regulation of membrane potential. These genes showed strong associations with the amygdala during mid-to-late fetal development, middle-to-late childhood, adolescence, and early adulthood; with the cerebellum during late infancy, early childhood, and early adulthood; with the cerebral cortex during the mid-to-late fetal development, early neonatal period, and adolescence; with the hippocampus during middle-to-late childhood and adolescence; with the striatum during adolescence and early adulthood; and with the thalamus during early-to-mid fetal development, early neonatal period, and early adulthood. PPI network analysis identified ANK3, ANK1, SCN4B, NFKB1, and PXN as specific hub proteins. Conclusion:Both ASD boys and ASD girls exhibit GMV abnormalities compared with TD controls. The specific genes associated with GMV alterations are enriched in distinct biological pathways in boys and girls. Cell-type-specific expression analyses further revealed sex-dependent differences in developmental timing and brain structural correlations, and distinct PPI networks were constructed for each group.
5.Support vector machine model based on gray matter volume for identifying amyotrophic lateral sclerosis and analysis of relevant brain regions
Shan WU ; Haining LI ; Qiuli ZHANG ; Qianqian DUAN ; Xinyi YU ; Xing QIN ; Fangfang HU ; Jiaoting JIN ; Jingxia DANG ; Ming ZHANG
Chinese Journal of Medical Imaging Technology 2025;41(7):1051-1055
Objective To explore the value of support vector machine(SVM)model based on gray matter volume(GMV)for identifying amyotrophic lateral sclerosis(ALS),also to analyze the relevant brain regions.Methods MR 3D T1WI data of 60 ALS patients(ALS group)and 60 healthy volunteers(control group)were retrospectively analyzed.Taken GMV of each brain region obtained by voxel-based morphometry as the input features.F-score analysis was used to select feature with the highest classification accuracy to construct SVM model.Receiver operating characteristic curve was drawn to evaluate the efficacy of SVM model for identifying ALS,and top 10%was used as the weight threshold to obtain gray matter brain regions contributed the most to this model.Results SVM model constructed based on the top 40%GMV features had the highest classification accuracy(82.50%),with sensitivity,specificity and area under the curve(AUG)of 85.05%,80.40%and 0.890,respectively.The left precentral gyrus,left anterior cingulate gyrus and paracingulate gyrus,right middle temporal gyrus,opercular part of left inferior frontal gyrus,right dorsolateral superior frontal gyrus,left temporal pole:middle temporal gyrus,right superior occipital gyrus,orbital part of right middle frontal gyrus,right calcarine fissure and surrounding cortex,right fusiform gyrus were the top 1-10 gray matter brain regions contributed to this model.Conclusion ALS had specific GMV change pattern.SVM model based on GMV could be used to effectively identify ALS,while the left precentral gyrus was the most contributive brain region to this model.
6.Progress on the research of hepatolenticular degeneration
Shan TANG ; Wei HOU ; Zhongping DUAN ; Sujun ZHENG
Chinese Journal of Hepatology 2025;33(7):704-708
Hepatolenticular degeneration, also known as Wilson disease (WD), is a type of copper metabolism disorder caused by an ATP7B gene variant, which is manifested by the abnormal accumulation of copper in the liver and other organs, resulting in multisystem damage. This article summarizes the latest research progress, with an emphasis on clinical characteristics, analysis of the optimization of diagnostic technology, and the clinical application of novel copper chelator therapy, as well as the development status and future prospects of gene therapy for WD. Future research should focus on the in-depth analysis of the mechanism, the application of multidimensional precision diagnosis technology, the development of individualized treatment plans, and the development of multicenter clinical trials in order to improve the comprehensive treatment effects and quality of life for patients with WD.
7.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
8.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
9.Trends in global burden due to visceral leishmaniasis from 1990 to 2021 and projections up to 2035
Guobing YANG ; Aiwei HE ; Yongjun LI ; Shan LÜ ; Muxin CHEN ; Liguang TIAN ; Qin LIU ; Lei DUAN ; Yan LU ; Jian YANG ; Shizhu LI ; Xiaonong ZHOU ; Jichun WANG ; Shunxian ZHANG
Chinese Journal of Schistosomiasis Control 2025;37(1):35-43
Objective To investigate the global burden of visceral leishmaniasis (VL) from 1990 to 2021 and predict the trends in the burden of VL from 2022 to 2035, so as to provide insights into global VL prevention and control. Methods The global age-standardized incidence, prevalence, mortality and disability-adjusted life years (DALYs) rates of VL and their 95% uncertainty intervals (UI) were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources. The trends in the global burden of VL were evaluated with average annual percent change (AAPC) and 95% confidence interval (CI) from 1990 to 2021, and gender-, age-, country-, geographical area- and socio-demographic index (SDI)-stratified burdens of VL were analyzed. The trends in the global burden of VL were projected with a Bayesian age-period-cohort (BAPC) model from 2022 to 2035, and the associations of age-standardized incidence, prevalence, mortality, and DALYs rates of VL with SDI levels were examined with a smoothing spline model. Results The global age-standardized incidence [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)], prevalence [AAPC = -0.06%, 95% CI: (-0.06%, -0.06%)], mortality [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)] and DALYs rates of VL [AAPC = -2.38%, 95% CI: (-2.44%, -2.33%)] all appeared a tendency towards a decline from 1990 to 2021, and the highest age-standardized incidence [2.55/105, 95% UI: (1.49/105, 4.07/105)], prevalence [0.64/105, 95% UI: (0.37/105, 1.02/105)], mortality [0.51/105, 95% UI: (0, 1.80/105)] and DALYs rates of VL [33.81/105, 95% UI: (0.06/105, 124.09/105)] were seen in tropical Latin America in 2021. The global age-standardized incidence and prevalence of VL were both higher among men [0.57/105, 95% UI: (0.45/105, 0.72/105); 0.14/105, 95% UI: (0.11/105, 0.18/105)] than among women [0.27/105, 95% UI: (0.21/105, 0.33/105); 0.06/105, 95% UI: (0.05/105, 0.08/105)], and the highest mortality of VL was found among children under 5 years of age [0.24/105, 95% UI: (0.08/105, 0.66/105)]. The age-standardized incidence (r = -0.483, P < 0.001), prevalence (r = -0.483, P < 0.001), mortality (r = -0.511, P < 0.001) and DALYs rates of VL (r = -0.514, P < 0.001) correlated negatively with SDI levels from 1990 to 2021. In addition, the global burden of VL was projected with the BAPC model to appear a tendency towards a decline from 2022 to 2035, and the age-standardized incidence, prevalence, mortality and DALYs rates were projected to be reduced to 0.11/105, 0.03/105, 0.02/105 and 1.44/105 in 2035, respectively. Conclusions Although the global burden of VL appeared an overall tendency towards a decline from 1990 to 2021, the burden of VL showed a tendency towards a rise in Central Asia and western sub-Saharan African areas. The age-standardized incidence and prevalence rates of VL were relatively higher among men, and the age-standardized mortality of VL was relatively higher among children under 5 years of age. The global burden of VL was projected to continue to decline from 2022 to 2035.
10.Corylin inhibits Ang Ⅱ-induced cardiomyocyte hypertrophy by modulating SIRT1-/NF-κB-dependent signaling pathway
Min TAN ; Li-duan HUANG ; Yan-hong HOU ; Xiang-yue HU ; Jing CHEN ; Xian-qing WANG ; Shan HUANG ; Yi CAI
Chinese Pharmacological Bulletin 2025;41(6):1142-1148
Aim To investigate the role of corylin in angiotensin Ⅱ(Ang Ⅱ)-induced cardiomyocyte hy-pertrophy and its underlying mechanisms.Methods An Ang Ⅱ-induced cardiomyocyte hypertrophy model was established and treated with corylin.Real-time PCR was employed to assess hypertrophic gene mRNA expression,and immunofluorescence was used to meas-ure cardiomyocyte surface area.Western blot and en-zyme activity assay kits were used to evaluate SIRT1 expression and activity.Results Corylin markedly mitigated Ang Ⅱ-induced hypertrophic gene expression and cardiomyocyte surface area enlargement.Moreo-ver,it prevented the Ang Ⅱ-mediated decline in SIRT1 protein levels and deacetylase activity.Further investi-gation indicated that corylin inhibited Ang Ⅱ-driven NF-κB transcriptional activity and the expression of its downstream target genes,such as TNF-α,IL-6,and IL-1β.Notably,SIRT1 silencing abolished the protective effects of corylin against cardiomyocyte hypertrophy,as well as its regulation of the SIRT1/NF-κB signaling pathway.Conclusion Corylin suppresses cardiomyo-cyte hypertrophy by modulating the SIRT1-dependent NF-κB signaling pathway.

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