1.Preliminary study on the biological characteristics of heat shock cognate protein 20 of Schistosoma japonicum
Xingang YU ; Kaijian YUAN ; Yilong LI ; Xuanru MU ; Hui XU ; Qiaoyu LI ; Wenjing ZENG ; Zhiqiang FU ; Yang HONG
Chinese Journal of Schistosomiasis Control 2025;37(3):294-303
Objective To clone and express the heat shock cognate protein 20 (SjHsc20) of Schistosoma japonicum, and to preliminarily investigate its biological characteristics. Methods The target fragment of the SjHsc20 gene was amplified using PCR assay and cloned into the pET-28a(+) expression plasmid to generate the recombinant expression vector pET-28a(+)-SjH-sc20, which was then transformed into Escherichia coli BL21 (DE3) competent cells. The recombinant SjHsc20 (rSjHsc20) protein was induced with isopropyl β-D-thiogalactopyranoside (IPTG) and purified, and the expression of the rSjHsc20 protein was checked with sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The immunogenicity of the rSjHsc20 protein was detected using Western blotting, and the transcriptional levels of SjHsc20 were quantified in S. japonicum worms at different developmental stages and in male and female adult worms using real-time quantitative PCR (RT-qPCR) assay. Thirty female BALB/c mice at ages 6 to 8 weeks were divided into three groups, including the rSjHsc20 immunization group, the PBS control group, and the ISA 206 adjuvant group, of 10 mice in each group. Mice in the rSjHsc20 immunization group were subcutaneously immunized with 20 μg rSjHsc20 on days 1, 15 and 31, and animals in the PBS control group were subcutaneously injected with the same volume of PBS on days 1, 15 and 31, while mice in the ISA 206 adjuvant group were subcutaneously immunized with the same volume of ISA 206 adjuvant on days 1, 15 and 31, respectively. All mice in each group were infected with (40 ± 2) S. japonicum cercariae via the abdomen 14 day following the last immunization. Levels of serum specific IgG and its subtypes IgG1 and IgG2 antibodies against rSjHsc20, and the serum titers of anti-rSjHsc20 antibody were detected in mice using indirect enzyme-linked immunosorbent assay (ELISA). All mice were sacrifice 42 days post-infection, and S. japonicum worms were collected from the hepatic portal vein and counted. The eggs per gram (EPG), worm burden reductions and egg burden reductions were estimated to evaluate the protective efficacy of the rSjHsc20 protein. Results The SjHsc20 gene had an open reading frame (ORF) with 756 bp in length and encoded 252 amino acids, and the rSjHsc20 protein had a relative molecular mass of approximately 29 kDa. The rSjHsc20 protein was recognized by the serum of mice infected with S. japonicum and the serum of mice immunized with the rSjHsc20 protein, indicating that rSjHsc20 had a good immunogenicity. There was a significant difference in the transcriptional levels of the SjHsc20 gene among the 7-day (1.001 4 ± 0.065 7), 12-day (2.268 3 ± 0.129 2), 21-day (1.378 5 ± 0.160 4), 28-day (1.196 4 ± 0.244 0), 35-day (1.646 3 ± 0.226 1), 42-day worms of S. japonicum (1.758 0 ± 0.611 1) (F = 38.45, P < 0.000 1), and the transcriptional level of the SjHsc20 gene was higher in the 12-day worms than in worms at other developmental stages (all P values < 0.000 1). The serum levels of anti-rSjHsc20 IgG antibody were 0.106 6 ± 0.010 7, 0.108 3 ± 0.010 4, and 0.553 2 ± 0.069 1 in the PBS control group, ISA 206 adjuvant group, and rSjHsc20 immunization group following the last immunization, respectively, and the serum levels of IgG1 antibody were 0.137 3 ± 0.054 0, 0.181 1 ± 0.096 8, and 1.765 8 ± 0.221 1, while the levels of IgG2a antibody were 0.280 3 ± 0.197 6, 0.274 0 ± 0.146 3, and 1.560 4 ± 0.106 0, respectively. There were significant differences in the serum levels of anti-rSjHsc20 IgG (F = 397.70, P < 0.000 1), IgG1 (F = 401.00, P < 0.000 1) and IgG2a antibodies (F = 229.70, P < 0.000 1) among the three groups, and the serum levels of anti-rSjHsc20 IgG, IgG1 and IgG2a antibodies were higher in the rSjHsc20 immunization group than in the PBS control group and the ISA 206 adjuvant group (all P values < 0.000 1). There was a significant difference in the IgG1/IgG2a ratio among the rSjHsc20 immunization group (1.177 2 ± 0.143 6), the PBS control group (0.428 4 ± 0.199 8) and the ISA 206 adjuvant group (0.559 9 ± 0.181 1) (F = 43.97, P < 0.000 1), and the IgG1/IgG2a ratio was > 1 in the rSjHsc20 immunization group, which was higher than in the PBS control group and the ISA 206 adjuvant group (both P values < 0.000 1). The titers of serum anti-rSjHsc20 antibody were all above 1∶16 384 in the rSjHsc20 immunization group following immunizations on days 1, 15 and 31, indicating that the rSjHsc20 protein had a strong immunogenicity. The mean worm burdens were (16.60±5.75), (15.80±5.58) worms per mouse and (14.40±5.75) worms per mouse in the PBS control group, the ISA 206 adjuvant group and the rSjHsc20 immunization group 42 days post-infection with S. japonicum cercariae (F = 0.50, P > 0.05), and the EPG were 68 370 ± 22 690, 67 972 ± 19 502, and 41 075 ± 13 251 in the PBS control group, the ISA 206 adjuvant group and the rSjHsc20 immunization group (F = 4.55, P < 0.05), with lower EPG in the PBS control group and the ISA 206 adjuvant group than in the rSjHsc20 immunization group (both P values < 0.05). Immunization with the rSjHsc20 protein resulted in a worm burden reduction of 13.25% and an egg burden reduction of 39.92% relative to the PBS control group. Conclusions SjHsc20 is successfully cloned and expressed, and the rSjHsc20 protein induces partial immunoprotective effects in mice, which provides a basis for deciphering the biological functions of SjHsc20 and assessing the potential of SjH-sc20 as a vaccine candidate.
2.Clinical Efficacy of Xiaoji Hufei Formula in Protecting Children with Close Contact Exposure to Influenza: A Multicenter,Prospective, Non-randomized, Parallel, Controlled Trial
Jing WANG ; Jianping LIU ; Tiegang LIU ; Hong WANG ; Yingxin FU ; Jing LI ; Huaqing TAN ; Yingqi XU ; Yanan MA ; Wei WANG ; Jia WANG ; Haipeng CHEN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Liqun WU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(21):223-230
ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza, and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter, prospective, non-randomized, parallel, controlled trial was conducted from October 2021 to May 2022 in five hospitals, including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness (ILI) cases were collected, and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention, they were assigned to the observation group (108 cases) or the control group (108 cases). Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine (TCM) symptom score scale for influenza, influenza-related emergency (outpatient) visit rate, influenza hospitalization rate, and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled, with 108 in the observation group and 108 in the control group. Primary outcomes: (1) Incidence of ILI: The incidence was 12.0% (13/108) in the observation group and 23.1% (25/108) in the control group, with the observation group showing a significantly lower incidence (χ2=4.6, P<0.05). (2) Influenza confirmation rate: 3.7% (4/108) in the observation group and 4.6% (5/108) in the control group, with no statistically significant difference. Secondary outcomes: (1) TCM symptom score scale: after onset, nasal congestion and runny nose scores differed significantly between the two groups (P<0.05), while other symptoms such as fever, sore throat, and cough showed no significant differences. (2) Influenza-related emergency (outpatient) visit rate: 84.6% (11 cases) in the observation group and 96.0% (24 cases) in the control group, with no significant difference. (3) Time to onset after exposure: The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group, with a statistically significant difference (P<0.05). ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions, Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.
3.Clinical Efficacy of Xiaoji Hufei Formula in Protecting Children with Close Contact Exposure to Influenza: A Multicenter,Prospective, Non-randomized, Parallel, Controlled Trial
Jing WANG ; Jianping LIU ; Tiegang LIU ; Hong WANG ; Yingxin FU ; Jing LI ; Huaqing TAN ; Yingqi XU ; Yanan MA ; Wei WANG ; Jia WANG ; Haipeng CHEN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Liqun WU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(21):223-230
ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza, and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter, prospective, non-randomized, parallel, controlled trial was conducted from October 2021 to May 2022 in five hospitals, including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness (ILI) cases were collected, and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention, they were assigned to the observation group (108 cases) or the control group (108 cases). Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine (TCM) symptom score scale for influenza, influenza-related emergency (outpatient) visit rate, influenza hospitalization rate, and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled, with 108 in the observation group and 108 in the control group. Primary outcomes: (1) Incidence of ILI: The incidence was 12.0% (13/108) in the observation group and 23.1% (25/108) in the control group, with the observation group showing a significantly lower incidence (χ2=4.6, P<0.05). (2) Influenza confirmation rate: 3.7% (4/108) in the observation group and 4.6% (5/108) in the control group, with no statistically significant difference. Secondary outcomes: (1) TCM symptom score scale: after onset, nasal congestion and runny nose scores differed significantly between the two groups (P<0.05), while other symptoms such as fever, sore throat, and cough showed no significant differences. (2) Influenza-related emergency (outpatient) visit rate: 84.6% (11 cases) in the observation group and 96.0% (24 cases) in the control group, with no significant difference. (3) Time to onset after exposure: The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group, with a statistically significant difference (P<0.05). ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions, Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.
4.Diagnostic Techniques and Risk Prediction for Cardiovascular-kidney-metabolic (CKM) Syndrome
Song HOU ; Lin-Shan ZHANG ; Xiu-Qin HONG ; Chi ZHANG ; Ying LIU ; Cai-Li ZHANG ; Yan ZHU ; Hai-Jun LIN ; Fu ZHANG ; Yu-Xiang YANG
Progress in Biochemistry and Biophysics 2025;52(10):2585-2601
Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.
5.Dynamic changes of neuronal cells at different time points following cerebral ischemia-reperfusion injury in rats
Xu-Huan ZOU ; Rui LAN ; Xue-Qin FU ; Wei-Wei WANG ; Man-Man WANG ; Chen TANG ; Shuang LIU ; Hong-Yu LI ; Xiao-Ming SHEN
Chinese Pharmacological Bulletin 2024;40(6):1056-1066
Aim To investigate the dynamic changes of neuronal cells at different time points following acute cerebral ischemia-reperfusion injury by establishing a model of brain ischemia-reperfusion injury.Methods Thirty male Sprague-Dawley(SD)rats were ran-domly divided into six groups:sham group and cere-bral ischemia-reperfusion injury(IR)groups at differ-ent time points.Focal cerebral ischemia-reperfusion injury model was established using the middle cerebral artery occlusion(MCAO)technique.The Longa sco-ring method was used to assess neurobehavioral scores in rats.After successful model preparation,routine paraffin sections were made,and TUNEL staining and immunohistochemistry staining with NeuN antibody were performed to observe cell apoptosis and neuronal cell survival,respectively.Immunohistochemistry stai-ning was also performed to investigate the changes in glial fibrillary acidic protein(GFAP)as a marker for astrocytes,ionized calcium-binding adapter molecule 1(IBA-1)as a marker for microglia,and CD31 as a marker for endothelial cells at different time points.Results No significant changes were observed in neu-ronal cells of the sham group at different time points.In the cerebral ischemia-reperfusion injury groups,cell apoptosis was activated at IR3h and increased in quan-tity with morphological damage as time progressed.Ne-uN+neurons showed signs of ischemic injury after IR3h,with abnormal cell morphology.From 12 h,Ne-uN+neurons decreased in a time-dependent manner and reached their peak severity at 24 h.GFAP+astro-cytes decreased significantly after IR3h,while poorly labeled GFAP+astrocytes increased at IR 6 h and al-most disappeared in the infarcted area at 24 h and 48 h.The number of IBA-1+microglia-positive cells de-creased at IR3h,and their volume increased at IR6h.Microglial cell death was observed in the infarcted area at IR12h.CD31+endothelial cells around the infarc-ted cortex and striatum increased significantly after IR3h and persisted until 48 h.Conclusions After cerebral ischemia-reperfusion injury,the number of ap-optotic cells increases with the prolongation of time,and NeuN+neurons exhibit the most severe damage at 24 h.GFAP+astrocytes and microglial cells gradually die over time.The number of CD31+endothelial cells increases significantly around the infarcted cortex and striatum after 3 h of reperfusion and persists until 48 h.
6.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.
7.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
8.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
9.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
10.Changing resistance profiles of Proteus,Morganella and Providencia in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yunmin XU ; Xiaoxue DONG ; Bin SHAN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Hongyan ZHENG ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(4):410-417
Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10%of the Proteus and Morganella strains were resistant,while less than 20%of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4%in Proteus isolates,1.9%in Morganella isolates,and 15.6%in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.

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