1.Strategies of HIV-1 Vaccines Based on mRNA Platforms
Pei LIU ; Zhong-Yue FANG ; Xin-Xin CHEN ; Shao-Wei LI ; Ying GU
Progress in Biochemistry and Biophysics 2026;53(4):826-839
Since its emergence in the 1980s, the human immunodeficiency virus (HIV) has caused a global pandemic, posing a severe threat to human life and health as well as social development. Although pre-exposure prophylaxis (PrEP) effectively curbs HIV transmission and antiretroviral therapy (ART) significantly extends the lifespan of patients, vaccines remain a pivotal tool for blocking transmission and ending the pandemic. The high genetic variability of HIV-1, the glycan shield of its envelope glycoproteins, and the long-term persistence of latent reservoirs have repeatedly led to bottlenecks in traditional vaccine strategies. In recent years, mRNA technology has offered a novel approach to addressing these challenges, leveraging advantages such as sequence programmability, short production cycles, native conformational expression of antigens, and self-adjuvant effects. In recent years, mRNA vaccine technology has emerged as a transformative solution to longstanding vaccinology challenges, characterized by its sequence programmability, rapid production cycles, native conformational antigen expression, and intrinsic self-adjuvanting properties. Unlike traditional platforms reliant on pathogen culture or recombinant proteins, mRNA vaccines can be expeditiously designed and updated based solely on viral genomic sequences. Lipid nanoparticle (LNP)-encapsulated mRNA facilitates endogenous antigen expression and presentation, simultaneously eliciting potent humoral and cellular immune responses. Within this landscape, self-amplifying mRNA (saRNA) further extends in vivo antigen expression to enhance the persistence of immune responses. Moreover, the LNP delivery system not only protects mRNA from degradation and mediates endosomal escape but also synergizes with mRNA to optimize immune activation via self-adjuvant effects. Importantly, mRNA platforms circumvent the pre-existing immunity associated with viral vectors and the genomic integration risks of DNA vaccines, positioning them as a cornerstone for global pandemic preparedness. This review systematically delineates recent advances in mRNA technology for HIV-1 vaccine development, focusing on four pivotal research frontiers. First, mRNA innovations building upon the RV144 trial optimize antigens through codon modification and multivalent designs to induce more durable and broad-spectrum immunity. Second, particulate mRNA vaccine strategies, utilizing virus-like particles (VLPs) and ferritin nanoparticles, achieve in situ antigen self-assembly, significantly enhancing B cell activation and reducing infection risks in non-human primate models. Third, germline-targeting mRNA vaccines address the low-affinity barrier of broadly neutralizing antibody (bNAp) precursors, efficiently activating rare precursor B cells and promoting affinity maturation. Fourth, therapeutic mRNA vaccines offer unique advantages for an HIV functional cure; combining immunogens with mRNA-encoded adjuvants potentiates cellular immunity, while LNP-mediated “shock-and-kill” strategies specifically activate latent reservoirs to guide immune clearance. Comparative analyses with traditional platforms reveal that mRNA technology redefines antigen production and presentation, simulating chronic infection through sustained expression and enabling dual-pathway presentation via endogenous synthesis. Furthermore, we explore the mechanistic innovations of mRNA vaccines in inducing bNAps: sustained in vivo production prolongs the activation window for precursor B cells and maintains germinal center (GC) reactions; endogenously expressed antigens adopt native conformations to expose conserved epitopes; and self-adjuvanting effects modulate the functions of antigen-presenting cells (APCs) and follicular helper T cells (Tfh), driving somatic hypermutation and affinity maturation. We also address critical clinical translation challenges, including immune durability, adaptability to special populations, and large-scale LNP manufacturing, while proposing targeted optimization strategies. In conclusion, this review establishes a theoretical framework for utilizing mRNA technology to overcome HIV-1 immune escape, transitioning from a descriptive paradigm to a problem-solving-based synthesis of evidence. By integrating preclinical and early clinical data, we bridge the gap between basic design and translational verification. mRNA technology is poised to become a central pillar inHIV-1 prevention and therapy, providing a robust toolset to achieve the global goal of ending the AIDS pandemic and offering a blueprint for vaccine development against other recalcitrant infectious diseases.
2.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.
3.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.
4.Efficacy of Nucleotide Analog Monotherapy and Combination Therapy with Interferon in Treating Chronic Hepatitis B
Rui YIN ; Guowei MA ; Wenxi YUE ; Haixia GU ; Ying ZHOU ; Jie CHEN
Journal of Kunming Medical University 2025;46(6):79-88
Objective To analyze the efficacy of different nucleoside(acid)analogs(NAs)used as monotherapy and in combination with pegylated interferon α-2b(Peg-IFN-α-2b)in the treatment of chronic hepatitis B(CHB).Methods A retrospective analysis was conducted on 229 CHB patients who visited the Hepatology Department of the Third People's Hospital of Kunming from September 2022 to August 2023.Patients were divided into six groups based on their antiviral regimen:entecavir(ETV)group(A,n=47),ETV combined with Peg-IFN-α-2b group(B,n=19),Tenofovir Alafenamide(TMF)group(C,n=64),TMF combined with Peg-IFN-α-2b group(D,n=35),Tenofovir Disoproxil Fumarate(TDF)group(E,n=29),and TDF combined with Peg-IFN-α-2b group(F,n=35).The blood routine,liver function,kidney function,HBV serological markers,and HBV-DNA levels were compared before and after 24 weeks of treatment.Results After 24 weeks of treatment,there were no statistically significant differences in efficacy rates and HBV-DNA positivity rates between the monotherapy with NAs and the combination with Peg-IFN-α-2b(P>0.05).Comparing before and after treatment,the ETV group had the highest effective rate,while TDF combined with Peg-IFN-α-2b group had the lowest effective rate.TDF group had the highest efficiency,while ETV combined with Peg-IFN-α-2b group had the lowest efficiency.Except for ETV+Peg-IFN-α-2b and TDF+Peg-IFN-α-2b groups,the HBV-DNA positivity rates in the other four groups were significantly lower after treatment compared to before(P<0.05).There was a significant difference in HBsAg levels among the different treatment regimens of monotherapy with NAs and combination with Peg-IFN-α-2b(P=0.0483).Additionally,except for the ETV and TDF groups,the serum HBsAg levels in the other four groups were significantly lower after treatment compared to before(P<0.05).There were no significant difference in LSM and GFR before and after treatment(P>0.05).In the monotherapy groups,ALT and GGT levels were significantly lower after treatment compared to before(P<0.05),while in the combination Peg-IFN-α-2b group,WBC,NEUT,and PLT levels were significantly lower after treatment compared to before(P<0.05).Conclusion Combination therapy with Peg-IFN-α-2b can reduce HBsAg levels and may be more effective in controlling the virus;however,it may cause adverse reactions such as bone marrow suppression,increasing risks.Physicians and patients need to weigh the benefits against the risks and develop personalized treatment plans based on individual circumstances.
5.Comparison of the Phoenix scoring system and commonly used pediatric sepsis scores in predicting mortality risk in pediatric patients with severe sepsis under traditional standards
Haonan WANG ; Yinglang HE ; Rui TAN ; Han LI ; Xian LI ; Nan HOU ; Chen JI ; Zhe LI ; Yue WANG ; Shuangshuang PENG ; Le JING ; Liye GU ; Junjie ZHAO ; Hongjun MIAO
Chinese Journal of Burns 2025;41(3):222-231
Objective:To explore the differences between the Phoenix sepsis scoring system including Phoenix sepsis score (PSS) and Phoenix-8 organ dysfunction score (hereinafter referred to as Phoenix-8) and the commonly used pediatric sepsis scores in evaluating clinical characteristics and prognostic analysis of pediatric patients with severe sepsis diagnosed under traditional standards, namely the diagnostic criteria from the 2005 International Pediatric Sepsis Consensus Conference.Methods:This study was a retrospective observational study. From December 2020 to March 2023, 202 pediatric patients with severe sepsis meeting the inclusion criteria were admitted to the Children's Hospital of Nanjing Medical University. Based on the sepsis diagnostic criteria outlined in the International Consensus Criteria for Pediatric Sepsis and Septic Shock (2024), the pediatric patients were categorized into a sepsis group and a non-sepsis group. Sepsis group was further subdivided into a death subgroup and a survival subgroup based on the outcomes. The age, hospitalization costs, disease outcome indicators (e.g., mortality rate and incidence of septic shock), major organ (e.g., heart, liver, lungs, and kidneys) damage and their correlations, as well as PSS, Phoenix-8 and commonly used pediatric sepsis scores (e.g., pediatric sequential organ failure assessment (pSOFA), pediatric risk of mortality score Ⅲ (PRISM Ⅲ), pediatric logistic organ dysfunction-2 score (PELOD-2), pediatric multiple organ dysfunction score (P-MODS), pediatric critical illness score (PCIS), and pediatric early warning score (PEWS)) were collected and compared. Receiver operating characteristic (ROC) curve and precision-recall curve were plotted to evaluate the predictive ability of PSS, Phoenix-8, and commonly used pediatric sepsis scores for mortality risk in pediatric patients with severe sepsis under traditional standards. Predictive performance was quantified using the area under the ROC curve (AUROC). Univariate logistic regression analysis was employed to quantify the odds ratios of PSS and Phoenix-8 for predicting mortality risk. Patients with severe sepsis under traditional standards were further stratified into subgroups based on complications and comorbidities, including central nervous system (CNS) diseases, multiple infections, cardiovascular system diseases, shock, and malignancies. The Hosmer-Lemeshow goodness-of-fit test was used to assess calibration of PSS and Phoenix-8, and the DeLong test was used to compare whether there were statistically significant differences in the AUROC of PSS and Phoenix-8 for predicting mortality risk among different subgroups of pediatric patients. Results:Compared with those in non-sepsis group, pediatric patients in sepsis group were significantly older ( Z=-2.92, P<0.05) with higher incidences of septic shock and mortality, hospitalization costs, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, PSS, and Phoenix-8 (with χ2 values of 21.28 and 13.64, respectively, Z values of -1.99, -5.33, -5.10, -8.55, -6.91, -10.98, and -9.93, respectively, P<0.05), and lower PCIS ( Z=-3.34, P<0.05). Compared with those in survival subgroup, hospitalization costs, PSS, Phoenix-8, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, and P-MODS of pediatric patients in death subgroup was significantly higher (with Z values of -2.50, -3.50, -2.47, -5.11, -3.84, -2.94, -3.61, and -3.04, respectively, P<0.05). Compared with those in survival subgroup, the incidences of lung damage and liver damage of pediatric patients in death subgroup were also significantly higher (with χ2 values of 6.20 and 10.94, respectively, P<0.05), and 64.7% (97/150) of patients exhibited two or more concurrent organ damage. For predicting mortality risk in pediatric patients with severe sepsis under traditional standards, the AUROC values for PRISM Ⅲ, PCIS, PEWS, pSOFA, PELOD-2, P-MODS, PSS, and Phoenix-8 were approximately 0.70, with optimal cutoff values of 17.5, 91.0, 5.5, 4.5, 2.5, 4.5, 3.5, and 4.5, respectively; PELOD-2 demonstrated the highest sensitivity (0.83); while PRISM Ⅲ, PSS, and Phoenix-8 showed high specificity (>0.80). Univariate logistic regression analysis showed that for every 1-point increase in the PSS within 24 hours of pediatric intensive care unit admission, the relative risk of mortality increased by 63.7% (with odds ratio of 1.64, 95% confidence interval of 1.34-1.99, P<0.05). Similarly, for every 1-point increase in the Phoenix-8, the relative risk of mortality increased by 37.5% (with odds ratio of 1.38, 95% confidence interval of 1.18-1.60, P<0.05). The AUROC values (around 0.80) of PSS and Phoenix-8 for predicting mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases were relatively high. In contrast, the AUROC values (0.60-0.80) for predicting mortality risk in pediatric patients with severe sepsis combined with shock or malignant tumors were moderate. All models passed the Hosmer-Lemeshow goodness-of-fit test ( P>0.05). The DeLong test indicated no statistically significant differences in predictive ability between PSS and Phoenix-8 across subgroups of pediatric patients ( P>0.05). Conclusions:PSS and Phoenix-8 exhibited higher specificity than most of the commonly used pediatric sepsis scores in predicting mortality risk under traditional standards. Both scores performed much better in predicting the mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases.
6.Preliminary establishment of reference intervals for 12 cytokines in adult plasma by multiplex bead-based flow fluorescent immunoassay
Xinyu WANG ; Xing CHENG ; Lu ZHENG ; Yue ZHANG ; Yuting MA ; Guoping NIU ; Feng GU ; Yongqiang CHEN
Chinese Journal of Immunology 2025;41(5):1202-1207
Objective:To establish the reference interval of 12 types of cytokines(IL-1β,IL-2,IL-4,IL-5,IL-6,IL-8,IL-10,IL-12p70,IL-17,IFN-γ,IFN-α,TNF-α)in adult plasma based on multiple microsphere flow immunofluorescence(MBFFI).Methods:A total of 140 healthy adult patients who were examined at Xuzhou Central Hospital between January 2022 and December 2023 were included in the study.Plasma cytokine levels were detected and reference intervals were established by the flow cytometer and the assay kits produced by Qingdao Raisecare Biotechnology Co.,Ltd and Jiangsu BioPredia Biotechnology Co.,Ltd.Results:All of the cytokines exhibited a non-normal distribution,and there was a discrepancy in the 95%reference interval between the two re-agents.The reference intervals for the 12 cytokine kits produced by Qingdao Raisecare Biotechnology Co.,Ltd.were as follows:IFN-α:<4.91 pg/ml,IL-12 p70:<1.95 pg/ml,IL-5:<12.72 pg/ml,IL-8:<60.68 pg/ml,IL-1β:<27.67 pg/ml,IL-2:<5.01 pg/ml,IL-4:<1.22 pg/ml,IL-6:<6.11 pg/ml,TNF-α:<2.92 pg/ml,IL-17:<10.27 pg/ml,IL-10:<6.88 pg/ml,IFN-γ:<17.68 pg/ml.The reference intervals of the 12 cytokines produced by Jiangsu BioPredia Biotechnology Co.,Ltd.were as follows:IFN-α:<4.05 pg/ml,IL-12 p70:<7.33 pg/ml,IL-5:<7.80 pg/ml,IL-8:<13.24 pg/ml,IL-1β:<19.24 pg/ml,IL-2:<2.42 pg/ml,IL-4:<0.99 pg/ml,IL-6:<2.10 pg/ml,TNF-α:<0.87 pg/ml,IL-17:<1.42 pg/ml,IL-10:<1.10 pg/ml,IFN-γ:<1.34 pg/ml.Conclusion:In this study,the ref-erence range of two reagents for the detection of 12 kinds of cytokines in plasma of healthy adults is established by MBFFI,which pro-vides a valuable reference for the diagnosis and treatment of clinical-related diseases.
7.PGRMC1 as a potential biomarker of breast cancer risk for menopausal hormone therapy
Yuejiao WANG ; Xiangyan RUAN ; Muqing GU ; Yun WEI ; Yuwei GUAN ; Yue ZHAO ; O.Mueck ALFRED
Journal of Capital Medical University 2025;46(4):589-593
Progesterone receptor membrane component 1(PGRMC1)is closely related to hormone therapy which belongs to the membrane-associated progesterone receptor(MAPR)family.A large number of in vitro experiments,in vivo animal experiments,clinical samples of breast cancer patients and blood studies showed that all synthetic progesterone(excluding natural progesterone and dydrogesterone)can promote the rapid proliferation of breast cancer cells overexpressing PGRMC1.In patients with breast cancer,PGRMC1 is significantly negatively correlated with tumor grade and prognosis,and PGRMC1 level in blood is positively correlated with PGRMC1 expression in breast cancer tissues,and PGRMC1 is superior to traditional tumor markers such as carcinoembryonic antigen(CEA),carbohydrate antigen(CA125),and CA153 in predicting early breast cancer.Therefore,PGRMC1 may serve as a predictive marker for identifying an elevated risk of breast cancer associated with menopausal hormone replacement therapy.
8.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.
9.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.
10.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.

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