1.Gene Expression Alteration by Non-thermal Plasma-Activated Media Treatment in Radioresistant Head and Neck Squamous Cell Carcinoma
Sicong ZHENG ; Yudan PIAO ; Seung-Nam JUNG ; Chan OH ; Mi Ae LIM ; QuocKhanh NGUYEN ; Shan SHEN ; Se-Hee PARK ; Shengzhe CUI ; Shuyu PIAO ; Young Il KIM ; Ji Won KIM ; Ho-Ryun WON ; Jae Won CHANG ; Yujuan SHAN ; Lihua LIU ; Bon Seok KOO
Clinical and Experimental Otorhinolaryngology 2025;18(1):73-87
Objectives:
. Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes.
Methods:
. After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC.
Results:
. NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways.
Conclusion
. NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.
2.Gene Expression Alteration by Non-thermal Plasma-Activated Media Treatment in Radioresistant Head and Neck Squamous Cell Carcinoma
Sicong ZHENG ; Yudan PIAO ; Seung-Nam JUNG ; Chan OH ; Mi Ae LIM ; QuocKhanh NGUYEN ; Shan SHEN ; Se-Hee PARK ; Shengzhe CUI ; Shuyu PIAO ; Young Il KIM ; Ji Won KIM ; Ho-Ryun WON ; Jae Won CHANG ; Yujuan SHAN ; Lihua LIU ; Bon Seok KOO
Clinical and Experimental Otorhinolaryngology 2025;18(1):73-87
Objectives:
. Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes.
Methods:
. After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC.
Results:
. NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways.
Conclusion
. NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.
3.Gene Expression Alteration by Non-thermal Plasma-Activated Media Treatment in Radioresistant Head and Neck Squamous Cell Carcinoma
Sicong ZHENG ; Yudan PIAO ; Seung-Nam JUNG ; Chan OH ; Mi Ae LIM ; QuocKhanh NGUYEN ; Shan SHEN ; Se-Hee PARK ; Shengzhe CUI ; Shuyu PIAO ; Young Il KIM ; Ji Won KIM ; Ho-Ryun WON ; Jae Won CHANG ; Yujuan SHAN ; Lihua LIU ; Bon Seok KOO
Clinical and Experimental Otorhinolaryngology 2025;18(1):73-87
Objectives:
. Head and neck squamous cell carcinoma (HNSCC) exhibits high recurrence rates, particularly in cases of radioresistant HNSCC (RR-HNSCC). Non-thermal plasma (NTP) therapy effectively suppresses the progression of HNSCC. However, the therapeutic mechanisms of NTP therapy in treating RR-HNSCC are not well understood. In this study, we explored the regulatory role of NTP in the RR-HNSCC signaling pathway and identified its signature genes.
Methods:
. After constructing two RR-HNSCC cell lines, we prepared cell lysates from cells treated or not treated with NTP-activated media (NTPAM) and performed RNA sequencing to determine their mRNA expression profiles. Based on the RNA sequencing results, we identified differentially expressed genes (DEGs), followed by a bioinformatics analysis to identify candidate molecules potentially associated with NTPAM therapy for RR-HNSCC.
Results:
. NTPAM reduced RR-HNSCC cell viability in vitro. RNA sequencing results indicated that NTPAM treatment activated the reactive oxygen species (ROS) pathway and induced ferroptosis in RR-HNSCC cell lines. Among the 1,924 genes correlated with radiation treatment, eight showed statistical significance in both the cell lines and The Cancer Genome Atlas (TCGA) cohort. Only five genes—ABCC3, DUSP16, PDGFB, RAF1, and THBS1—showed consistent results between the NTPAM data sequencing and TCGA data. LASSO regression analysis revealed that five genes were associated with cancer prognosis, with a hazard ratio of 2.26. In RR-HNSCC cells, NTPAM affected DUSP16, PDGFB, and THBS1 as activated markers within 6 hours, and this effect persisted for 12 hours. Furthermore, enrichment analysis indicated that these three DEGs were associated with the extracellular matrix, transforming growth factor-beta, phosphoinositide 3-kinase/protein kinase B, and mesenchymal-epithelial transition factor pathways.
Conclusion
. NTPAM therapy exerts cytotoxic effects in RR-HNSCC cell lines by inducing specific ROS-mediated ferroptosis. DUSP16, PDGFB, and THBS1 were identified as crucial targets for reversing the radiation resistance induced by NTPAM therapy, providing insights into the mechanisms and clinical applications of NTPAM treatment in RR-HNSCC.
4.Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey.
Binbin LIN ; Yaoda HU ; Huijing HE ; Xingming CHEN ; Qiong OU ; Yawen LIU ; Tan XU ; Ji TU ; Ang LI ; Qihang LIU ; Tianshu XI ; Zhiming LU ; Weihao WANG ; Haibo HUANG ; Da XU ; Zhili CHEN ; Zichao WANG ; Guangliang SHAN
Environmental Health and Preventive Medicine 2025;30():5-5
BACKGROUND:
The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories.
METHODS:
This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex.
RESULTS:
In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight.
CONCLUSIONS
Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult
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Aged
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Female
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Humans
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Male
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Middle Aged
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Young Adult
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Adipose Tissue
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Body Fat Distribution
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Body Mass Index
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China/epidemiology*
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Cross-Sectional Studies
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Health Surveys
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Phenotype
5.The expression of CD24 antigen in multiple myeloma patients and its predictive value after induction therapy
Mengru LIU ; Bin CHU ; Yuan CHEN ; Mengzhen WANG ; Minqiu LU ; Shan GAO ; Lei SHI ; Qiuqing XIANG ; Lijuan FANG ; Qi YAN ; Na JI ; Kai SUN ; Li BAO
Chinese Journal of Laboratory Medicine 2024;47(10):1178-1185
Objective:This study analyzed the expression of CD24 antigen on bone marrow plasma cells (BMPC) of patients with multiple myeloma (MM) and the predictive value of induction therapy.Methods:This clinical observational study utilized 258 MM patients samples treated at the Hematology Department of Beijing Jishuitan Hospital who met the inclusion criteria in the Department of Hematology, Capital Medical University, from August 12th, 2022 to February 1st, 2024. According to the different stages of the disease, patients were divided into three groups: 78 cases of Newly Diagnosed Multiple Myeloma(NDMM) (42 males and 36 females, aged 62±11), 56 cases of the relapse refractory group (34 males and 22 females, aged 64±9), and 124 cases of the disease remission group (68 males and 56 females, aged 62±10). Multiparameter flow cytometry (MFC) was used to detect the expression level of CD24 antigen on BMPC and the relationship between CD24 and MM disease status. The clinical data and test results of 78 NDMM patients at initial diagnosis were retrospectively analyzed, including gender, age, MFC detection of the positive expression rate of antigens (CD19, CD20, CD24, CD27, CD56), the results of efficacy evaluation after induction therapy, ISS staging, R-ISS staging, blood hemoglobin, β2-microglobulin, human serum albumin, serum creatinine, lactate dehydrogenas, correction of calcium, BMPC ratio, and the results of FISH. The patients were divided into a deep remission group [including complete remission (CR) and very good partial remission (VGPR)] with 43 cases and a non-deep remission group (non CR and VGPR) with 17 cases according to the difference of antigen positive expression rate after induction therapy. The differences of antigen expression on BMPC between the two groups were compared. Binary logistic regression was used to analyze the relationship between the expression of each antigen and the efficacy after induction therapy in patients, and the results showed that CD24 was more correlated with the achievement of deep remission after induction therapy than other antigens. Therefore, taking the positive expression rate of CD24 in NDMM patients at the initial diagnosis and deep remission after induction therapy as the research objects, the predictive value of CD24 for NDMM patients reaching deep remission after induction therapy was analyzed by using receiver operating characteristic curve (ROC), and the optimal cutoff value was obtained. NDMM was divided into two groups according to the cut-off value, and the differences between the two groups in clinical baseline data and prognostic indicators were compared.Results:The positive rates of plasma cell CD24 expression in the NDMM group, the relapse refractory group and the disease remission group were 2.18 (95% CI 0.08-81.85)%, 3.81 (95% CI 0.10-64.56)%, 8.74 (95% CI 0.79-95.55)% respectively. Compared with the disease remission group, the NDMM and relapse refractory group was lower ( Z=-7.889, -5.282, respectively, P<0.001). Univariate analysis showed that there was a significant difference in the positive expression rate of CD24 at initial diagnosis between the deep remission group and the non-deep remission group ( Z=-3.265, P<0.001), while there was no significant difference in CD19 ( Z=-0.271, P=0.787), CD20 ( Z=-0.205, P=0.837), CD27 ( Z=-0.582, P=0.560), and CD56 ( Z=-0.328, P=0.743) between the two groups. Binary logistic regression analysis showed that compared with other antigens [CD19 ( OR=1.045, 95% CI 0.975-1.120, P=0.217), CD20 ( OR=1.000, 95% CI 0.971-1.030, P=0.976), CD27 ( OR=0.997, 95% CI 0.977-1.016, P=0.734), CD56 ( OR=1.006, 95% CI 0.990-1.006, P=0.449)], the expression of CD24 ( OR=0.423, 95% CI 0.990-1.006, P=0.449) on BMPC in NDMM patients was most closely related to the achievement of deep remission was achieved after induction therapy. The lower the proportion of CD24 at the initial diagnosis was, the lower the probability of achieving deep remission after induction therapy was. The area under the curve (AUC) of CD24 in predicting deep remission after induction therapy was 0.772 (95% CI 0.655-0.889, P=0.001), with a sensitivity of 60.50%, a specificity of 85.00%, and the optimal critical value was 2.21%. Compared with the group with plasma CD24 positive rate>2.21%, the group with plasma CD24 positive rate<2.21% had a higher proportion of male (39.47%vs 65.00%, χ2=5.092, P=0.024), ISS stagingⅢ (41.67% vs 58.33%, χ2=6.175, P=0.046), β2 microglobulin (3.19 mg/L vs 4.14 mg/L, Z=-2.257, P=0.024), and BMPC [(8.672±1.827)% vs (19.530±3.188)%, t=-2.963, P=0.004] detected by MFC, and the differences were statistically significant. Conclusions:The low positive rate of plasma cell CD24 is closely related to the higher tumor burden and the worse disease status of MM patients. In addition, the positive expression rate of CD24 is at initial diagnosis can predict the efficacy achieved after induction therapy, and the lower positive rate of CD24 is, the worse the efficacy achieved after induction therapy. At the same time, MFC detection of CD24 is convenient and efficient in the evaluation and prediction of MM.
6.Research progress of fluorescent probes in uric acid detection
Di-Di XING ; Ruo-Jin LIU ; Jia-Yu QI ; Ning MA ; Ya-Kun JI ; Jia-Xin ZHOU ; Yu-Shan XING ; Xiao-Lan ZHEN
Chinese Medical Equipment Journal 2024;45(6):93-104
The advantages of fluorescence detection of uric acid were introduced compared to the traditional detection methods.The preparation process,detection principle and performance of organic,inorganic and organic-inorganic hybrid fluorescent probes were reviewed.The advantages and disadvantages of kinds of fluorescent probes were analyzed when used for uric acid detection,and the futural directions were pointed out for related research.[Chinese Medical Equipment Journal,2024,45(6):93-104]
7.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

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