1.Efficient Loading and Targeted Delivery of Plant Exosomes
Meng XU ; Long-Jiao ZHU ; Jie LI ; Chong-Bin LEI ; Yang-Zi ZHANG ; Hong-Tao TIAN ; Wen-Tao XU
Progress in Biochemistry and Biophysics 2026;53(6):1597-1608
Plant-derived extracellular vesicles (PDEVs) are nanoscale extracellular vesicles secreted by plant cells, characterized by a lipid bilayer structure. These vesicles carry a variety of bioactive molecules, including proteins, nucleic acids, and lipids, and play essential roles in intercellular communication and physiological regulation in plants. Compared to animal-derived extracellular vesicles, PDEVs offer several advantages, such as a broad range of sources, high biocompatibility, low immunogenicity, and low production costs. Furthermore, PDEVs have demonstrated remarkable potential as natural nanocarriers for drug delivery, due to their ability to efficiently traverse biological barriers, such as the blood-brain barrier, making them promising candidates for drug delivery systems. This review systematically elaborates on the complex composition of PDEVs, which consists of lipids, proteins, and nucleic acids, the typical structural characteristics of their lipid bilayers ranging from 30 to 150 nm, and their versatile loading capabilities as drug carriers, efficiently encapsulating various types of therapeutic agents such as hydrophilic small molecules, hydrophobic drugs, nucleic acids, and proteins. We systematically summarize the recent advancements in strategies for enhancing the loading efficiency of PDEVs, which include methods such as co-incubation, ultrasound-assisted loading, electroporation, freeze-thaw cycles, and microfluidic technology. These techniques are evaluated based on their underlying principles, suitable drug types, and their respective advantages. In addition to loading strategies, we focus on the engineered approaches to achieve targeted delivery using PDEVs, such as genetic engineering modifications, chemical ligand conjugation, membrane fusion technology, and polyethylene glycol (PEG) modification. We discuss the mechanisms of these strategies in enhancing targeting efficiency, prolonging in vivo circulation time, and improving therapeutic efficacy. Further, this review highlights the application of PDEVs in various disease models, including tumor, skin inflammation, metabolic disorders, and neurodegenerative diseases, showcasing their therapeutic potential as multifunctional delivery platforms. The ability of PDEVs to encapsulate diverse therapeutic agents and target specific tissues or cells opens up new avenues for the treatment of complex diseases, offering advantages over conventional drug delivery systems. However, despite the promising applications of PDEVs, several challenges remain in their development and clinical translation. These challenges include variability in source materials, standardization of preparation processes, quality control, scalability of production, and the need for clinical validation. To overcome these obstacles, the integration of advanced technologies such as artificial intelligence-assisted design and multi-omics analysis is proposed as a way to facilitate the precise development of PDEVs. These emerging technologies hold the potential to further enhance the precision and effectiveness of plant-based drug delivery systems, ultimately advancing the field of precision medicine. In conclusion, the use of PDEVs as a platform for drug delivery represents a promising area of research with the potential to revolutionize therapeutic strategies. Their ability to encapsulate and deliver a wide variety of bioactive molecules, along with their inherent advantages in biocompatibility and versatility, makes them a valuable tool in the development of more efficient and targeted therapeutic interventions. Continued research and innovation in this field will pave the way for the clinical implementation of PDEVs in the treatment of various diseases, offering new hope for more effective and sustainable therapeutic options.
2.Association between standardized management of clinical research and research behavior of graduate students
Rui WEN ; Yunlin CHEN ; Jing WU ; Jie ZHU ; Yunhong HUANG ; Liang YUAN ; Qingyan LONG ; Cheng JIANG ; Yi LU
Chinese Journal of Medical Education Research 2025;24(3):412-418
Objective:To analyze the association between standardized management of clinical research, initiated by investigators and guided by clinical research management policies in healthcare institutions, and changes in the research behavior of graduate students.Methods:Theses related to cardiovascular health published by graduate students in the Sichuan-Chongqing region of China between January 2019 and June 2024 were retrieved from the China National Knowledge Infrastructure database. Multilevel models were used to analyze changes in ethical compliance awareness, research methodology standardization, and academic collaboration of graduate students before and after policy implementation. Using Shapiro Wilk test and percentage representation.Results:Among the 712 theses included in this study, the proportion of studies with ethical review reports increased from 44.50% to 55.32% following the implementation of standardized management [odds ratio ( OR)=1.80, P=0.017]. Standardized management significantly improved the quality scores of cross-sectional studies and randomized controlled trials ( P<0.001), as well as significantly increased the frequencies of multi-center collaboration ( OR=2.84, P=0.001) and intra-provincial collaboration ( OR=2.80, P=0.001). Conclusions:Standardized clinical research management shows significant association with positive changes in the research behavior of graduate students. Further optimization of management measures is recommended to comprehensively enhance the clinical research capabilities of graduate students.
3.Identification of core genes in programmed cell death during ischemia-reperfusion injury in kidney transplantation based on machine learning and experimental validation
Guining HE ; Lirong ZHU ; Jie YANG ; Zhen HE ; Minghu LI ; Haibin LI ; Ning WEN ; Xuyong SUN
Organ Transplantation 2025;16(5):738-746
Objective To identify key patterns of programmed cell death(PCD)and core genes during ischemia-reperfusion injury(IRI)in kidney transplantation.Methods Kidney transplant datasets were obtained from gene expression database,and PCD-related differentially expressed genes were screened.The non-negative matrix factorization algorithm was used to classify patients and analyze subtype-specific biological functions and key PCD patterns.Machine learning models combined with univariate Cox regression and Kaplan-Meier survival analysis were employed to identify core PCD genes during IRI in kidney transplantation and explore their correlation with key PCD patterns.A rat kidney transplant model was used to assess IRI severity through hematoxylin-eosin staining,serum creatinine(Scr),blood urea nitrogen(BUN),and Western blotting for key gene protein expression.Results Fourteen PCD-related genes were identified.Patients were classified into metabolic(subtype 1)and inflammatory(subtype 2)subtypes.Subtype 2 activated four key PCD patterns:pyroptosis,necroptosis,apoptosis and immunogenic cell death.The optimal model(XGBoost-CV:10 fold+Lasso-CV:10 fold)and survival analysis identified MCL1,BAG3,and RHOB as core PCD genes during IRI in kidney transplantation,which were broadly correlated with key PCD patterns.Experimental results showed that compared to the sham group,rats in the model group had more severe tubular injury,higher Scr and BUN levels,and increased BAG3,RHOB and MCL1 protein expression(all P<0.001).Conclusions These four PCD patterns are crucial in the pathogenesis of IRI in kidney transplantation.MCL1,BAG3 and RHOB may serve as potential biomarkers and therapeutic targets for IRI in kidney transplantation.
4.Implementation of MPOWER policy in China:perceived differences of policy implementation and its impact on smoking behavior and quitting intentions
Si-yi WU ; Chen-yu QIAN ; Yu-chen ZHAO ; Wen-jie GUO ; Wei-yun ZHU ; Pin-pin ZHENG
Fudan University Journal of Medical Sciences 2025;52(5):629-638
Objective To analyze the implementation of MPOWER tobacco control policies in different regions and populations in China,as well as the impact of perceptions of tobacco control policies on individual smoking behavior and quit intentions,to promote the fairness of policy implementation and protection for vulnerable groups.Methods A multivariable regression model was constructed utilizing raw data from the China Adult Tobacco Survey to analyze disparities in perceived MPOWER policy implementation among various social demographics and its impact on smoking behavior and quitting intentions.Results Regarding protection from tobacco smoke(P),local economic level,urban-rural divide were significantly correlated with awareness of comprehensive smoking bans.For offering help to quit smoking(O),local tobacco industry revenue and individual age were associated with the doctor's advice for quitting.As to the warning about the harm of tobacco(W),economic level,geography and urban-rural disparity were correlated with the visibility of health warnings.About the tobacco advertising,promotion and sponsorship(E),geography was related to the exposure to tobacco advertisements,local tobacco industry revenue was associated with the tobacco promotion.For tobacco taxes(R),education level and age were significantly correlated with tobacco affordability.People who perceived comprehensive smoking bans(OR=0.69,95%CI:0.59-0.81)was associated with less smoking behavior,while people perceiving tobacco promotional activities(OR=2.51,95%CI:2.00-3.17)were more likely to smoke.Additionally,people who perceived comprehensive smoking bans(OR=1.70,95%CI:1.25-2.31)and health warning(OR=2.09,95%CI:1.48-3.01)had higher intention to quit smoking.Conclusion In economically disadvantaged regions and among specific socially vulnerable groups(such as low-income individuals,rural residents,and the elderly)in China,the perception of tobacco control policy implementation is relatively low,the perception of tobacco control policies can influence smoking behavior and quitting intentions.Legislative and enforcement efforts should be increased targeting these groups with lower perceptions of the policies to enhance the fairness of tobacco control measures.
5.Analysis of factors influencing right atrial strain in patients with pulmonary arterial hypertension
Jin-xin XU ; Jie-xuan ZHENG ; Tao-ran HUANG ; Dong-ling LUO ; Yuan ZHU ; Cao-jin ZHANG ; Hong-wen FEI
Chinese Journal of Interventional Cardiology 2025;33(5):249-259
Objective To analyze the correlation between right atrial strain at various stages and various influencing factors in patients with pulmonary hypertension,and to explore the role of right atrial strain in the assessment of pulmonary hypertension.Methods A total of 239 cases diagnosed with pulmonary hypertension who underwent echocardiography and complete right heart catheterization at hospital from October 2021 to December 2023 were included.Conventional ultrasound parameters such as right heart strain,right atrial area(RA area),inferior vena cava diameter(IVC diameter),and collapse rate of the inferior vena cava(IVC diameter changes)were measured.The heart rate(HR)corresponding to the ultrasound images were recorded.General information such as age and gender,as well as catheter data including mean right atrial pressure(mRAP),mean pulmonary artery pressure(mPAP),and pulmonary vascular resistance(PVR),were collected.The relationship between right atrial strain and its influencing factors was analyzed,and further analysis was conducted by dividing into shunt group and non-shunt group based on the presence or absence of left-to-right shunt disease.Results The correlation with RA reservoir strain(RASr)from high to low is RV global strain(RV4CSL),RV free wall strain(RVFWSL),RA area,IVC diameter,mRAP,age,HR,and PVR;the correlation with RAconduit strain(RAScd)from high to low is RV4CSL,RVFWSL,RA area,IVC diameter,mRAP,age,PVR,and HR;the correlation with RA contraction strain(RASct)from high to low is RA area,RV4CSL,RVFWSL,mRAP,IVC diameter,and HR.The collapse rate of the inferior vena cava is correlated with strain at various stages of the right atrium;gender is correlated with RASr and RASct.Conclusions Right atrial strain can reflect changes in right atrial function,with the highest correlation to right ventricular strain and right atrial area.Right atrial strain can indicate the severity of right ventricular function and right atrial remodeling,serving as an evaluative index for the condition and treatment outcomes of pulmonary arterial hypertension.
6.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
7.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; 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(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
8.Analysis of factors influencing right atrial strain in patients with pulmonary arterial hypertension
Jin-xin XU ; Jie-xuan ZHENG ; Tao-ran HUANG ; Dong-ling LUO ; Yuan ZHU ; Cao-jin ZHANG ; Hong-wen FEI
Chinese Journal of Interventional Cardiology 2025;33(5):249-259
Objective To analyze the correlation between right atrial strain at various stages and various influencing factors in patients with pulmonary hypertension,and to explore the role of right atrial strain in the assessment of pulmonary hypertension.Methods A total of 239 cases diagnosed with pulmonary hypertension who underwent echocardiography and complete right heart catheterization at hospital from October 2021 to December 2023 were included.Conventional ultrasound parameters such as right heart strain,right atrial area(RA area),inferior vena cava diameter(IVC diameter),and collapse rate of the inferior vena cava(IVC diameter changes)were measured.The heart rate(HR)corresponding to the ultrasound images were recorded.General information such as age and gender,as well as catheter data including mean right atrial pressure(mRAP),mean pulmonary artery pressure(mPAP),and pulmonary vascular resistance(PVR),were collected.The relationship between right atrial strain and its influencing factors was analyzed,and further analysis was conducted by dividing into shunt group and non-shunt group based on the presence or absence of left-to-right shunt disease.Results The correlation with RA reservoir strain(RASr)from high to low is RV global strain(RV4CSL),RV free wall strain(RVFWSL),RA area,IVC diameter,mRAP,age,HR,and PVR;the correlation with RAconduit strain(RAScd)from high to low is RV4CSL,RVFWSL,RA area,IVC diameter,mRAP,age,PVR,and HR;the correlation with RA contraction strain(RASct)from high to low is RA area,RV4CSL,RVFWSL,mRAP,IVC diameter,and HR.The collapse rate of the inferior vena cava is correlated with strain at various stages of the right atrium;gender is correlated with RASr and RASct.Conclusions Right atrial strain can reflect changes in right atrial function,with the highest correlation to right ventricular strain and right atrial area.Right atrial strain can indicate the severity of right ventricular function and right atrial remodeling,serving as an evaluative index for the condition and treatment outcomes of pulmonary arterial hypertension.
9.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
10.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; 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(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

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