1.A retrospective cohort study on the protective effectiveness of influenza vaccine against influenza A among the individuals aged between 3‒17 years old in Fenghua District, Ningbo City from 2022 to 2023
Yuqi SHAO ; Weibo DONG ; Yingping XIA ; Chuan ZHANG ; Yi LIU
Shanghai Journal of Preventive Medicine 2025;37(8):654-658
ObjectiveTo analyze the protective effect of different types of influenza vaccines (InfV) against influenza A among the individuals aged between 3‒17 years old, and to provide a scientific basis for the prevention and control of influenza in the future. MethodsA retrospective cohort study was conducted to collect data on the incidence and InfV vaccination of the individuals aged between 3‒17 years during the influenza epidemic season from 2022 to 2023. Vaccine effectiveness (VE) was calculated, and a log-binomial regression model was used to calculate the corrected VE. ResultsThe incidence rate of influenza in InfV vaccinated and un-vaccinated groups was 7.32% (1 937/ 26 446) and 9.65% (4 421/45 837), respectively. After adjusting for age and gender factors, the unadjusted VE (95%CI) was 54.57% (52.24%‒56.78%). The unadjusted VE (95%CI) was 53.66% (50.36%‒56.74%) for males and 55.60% (52.24%‒58.72%) for females, respectively. The unadjusted VE (95%CI) for the age group of 3‒ years, 6‒ years, 9‒ years, 12‒ years, and 15‒17 years were 64.08% (60.89%‒67.01%), 57.40% (53.71%‒60.80%), 57.77% (52.49%‒62.47%), 24.36% (9.49%‒36.79%), and 24.09% (-17.59%‒51.00%), respectively. The unadjusted VE (95%CI) for quadrivalent split-virion inactivated influenza vaccine, trivalent split-virion inactivated influenza vaccine, trivalent subunit influenza vaccine, and trivalent live attenuated influenza vaccine were 53.84% (51.32%‒56.24%), 62.17% (56.28%‒67.26%), 79.83% (69.94%‒86.46%), and 31.59% (19.07%‒42.18%), respectively. ConclusionThe InfV used during the 2022‒2023 influenza season had a good protective effect against influenza A among the individuals aged between 3‒17 years old, especially in those aged between 3‒11 years old.
2.Phenylpropanoids from roots of Berberis polyantha.
Dong-Mei SHA ; Shuai-Cong NI ; Li-Niu SHA-MA ; Hai-Xiao-Lin-Mo MA ; Xiao-Yong HE ; Bin HE ; Shao-Shan ZHANG ; Ying LI ; Jing WEN ; Yuan LIU ; Xin-Jia YAN
China Journal of Chinese Materia Medica 2025;50(6):1564-1568
The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry*
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Animals
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Mice
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Berberis/chemistry*
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RAW 264.7 Cells
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Macrophages/immunology*
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Drugs, Chinese Herbal/isolation & purification*
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Nitric Oxide/metabolism*
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Molecular Structure
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Anti-Inflammatory Agents/isolation & purification*
3.Expert consensus on the diagnosis and treatment of cemental tear.
Ye LIANG ; Hongrui LIU ; Chengjia XIE ; Yang YU ; Jinlong SHAO ; Chunxu LV ; Wenyan KANG ; Fuhua YAN ; Yaping PAN ; Faming CHEN ; Yan XU ; Zuomin WANG ; Yao SUN ; Ang LI ; Lili CHEN ; Qingxian LUAN ; Chuanjiang ZHAO ; Zhengguo CAO ; Yi LIU ; Jiang SUN ; Zhongchen SONG ; Lei ZHAO ; Li LIN ; Peihui DING ; Weilian SUN ; Jun WANG ; Jiang LIN ; Guangxun ZHU ; Qi ZHANG ; Lijun LUO ; Jiayin DENG ; Yihuai PAN ; Jin ZHAO ; Aimei SONG ; Hongmei GUO ; Jin ZHANG ; Pingping CUI ; Song GE ; Rui ZHANG ; Xiuyun REN ; Shengbin HUANG ; Xi WEI ; Lihong QIU ; Jing DENG ; Keqing PAN ; Dandan MA ; Hongyu ZHAO ; Dong CHEN ; Liangjun ZHONG ; Gang DING ; Wu CHEN ; Quanchen XU ; Xiaoyu SUN ; Lingqian DU ; Ling LI ; Yijia WANG ; Xiaoyuan LI ; Qiang CHEN ; Hui WANG ; Zheng ZHANG ; Mengmeng LIU ; Chengfei ZHANG ; Xuedong ZHOU ; Shaohua GE
International Journal of Oral Science 2025;17(1):61-61
Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans
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Dental Cementum/injuries*
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Consensus
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Diagnosis, Differential
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Cone-Beam Computed Tomography
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Tooth Fractures/therapy*
4.Mechanosensory activation of Piezo1 via cupping therapy: Harnessing neural networks to modulate AMPK pathway for metabolic restoration in a mouse model of psoriasis.
Ruo-Fan XI ; Xin LIU ; Yi WANG ; Han-Zhi LU ; Shao-Jie YUAN ; Dong-Jie GUO ; Jian-Yong ZHU ; Fu-Lun LI ; Yan-Juan DUAN
Journal of Integrative Medicine 2025;23(6):721-732
OBJECTIVE:
Psoriasis, a common chronic inflammatory skin condition with genetic underpinnings, is traditionally managed with cupping therapy. Although used historically, the precise mechanical effects and therapeutic mechanisms of cupping in psoriasis remain largely unexamined. This study aimed to evaluate cupping therapy's efficacy for psoriasis and investigate its role in modulating inflammatory responses and cellular metabolism.
METHODS:
Psoriasis was induced in mice using topical imiquimod (IMQ). The effects of cupping on psoriatic lesions were assessed using the Psoriasis Area and Severity Index score, histology, immunohistochemistry, and immunofluorescence staining. polymerase chain reaction sequencing (RNA-seq) and Western blotting were conducted to examine changes in mRNA expression and the AMP-activated protein kinase (AMPK) signaling pathway.
RESULTS:
Cupping therapy significantly reduced inflammation, epidermal thickness, and inflammatory cell infiltration in mice with IMQ-induced psoriasis. Immunohistochemistry and immunofluorescence showed lower expression of inflammatory markers and a shift in T-cell populations. RNA-seq and Western blotting indicated that cupping upregulated Piezo1 and activated the AMPK pathway, improving energy metabolism in psoriatic skin.
CONCLUSION
Cupping therapy reduces epidermal hyperproliferation and inflammation in psoriasis, rebalancing the local immune microenvironment. Mechanistically, cupping promotes calcium influx via Piezo1, activates AMPK signaling, and supports metabolic homeostasis, suggesting therapeutic potential for psoriasis. Please cite this article as: Xi RF, Liu X, Wang Y, Lu HZ, Yuan SJ, Guo DJ, Zhu JY, Li FL, Duan YJ. Mechanosensory activation of Piezo1 via cupping therapy: Harnessing neural networks to modulate AMPK pathway for metabolic restoration in a mouse model of psoriasis. J Integr Med. 2025; 23(6):721-732.
Animals
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Psoriasis/chemically induced*
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Mice
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AMP-Activated Protein Kinases/metabolism*
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Disease Models, Animal
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Cupping Therapy/methods*
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Signal Transduction
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Imiquimod
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Ion Channels/genetics*
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Male
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Mechanotransduction, Cellular
5.Reversal Effect of NVP-BEZ235 on Doxorubicin-Resistance in Burkitt Lymphoma RAJI Cell Line
Chun-Tuan LI ; Xiong-Peng ZHU ; Shao-Xiong WANG ; Qun-Yi PENG ; Yan ZHENG ; Sheng-Quan LIU ; Xu-Dong LU ; Yong-Shan WANG ; Dan WENG ; Dan WANG
Journal of Experimental Hematology 2024;32(2):476-482
Objective:To study the reversal effect of NVP-BEZ235 on doxorubicin resistance in Burkitt lymphoma RAJI cell line.Methods:The doxorubicin-resistant cell line was induced by treating RAJI cells with a concentration gradient of doxorubicin.The levels of Pgp,p-AKT,and p-mTOR in cells were detected by Western blot.Cell viability was detected by MTT assay.IC50 was computed by SPSS.Results:The doxorubicin-resistant Burkitt lymphoma cell line,RAJI/DOX,was established successfully.The expression of Pgp and the phosphorylation levels of AKT and mTOR in RAJI/DOX cell line were both higher than those in RAJI cell line.NVP-BEZ235 downregulated the phosphorylation levels of AKT and mTOR in RAJI/DOX cell line.NVP-BEZ235 inhibited the proliferation of RAJI/DOX cell line,and the effect was obvious when it was cooperated with doxorubicin.Conclusion:The constitutive activation of PI3K/AKT/mTOR pathway of RAJI/DOX cell line was more serious than RAJI cell line.NVP-BEZ235 reversed doxorubicin resistance of RAJI/DOX cell line by inhibiting the PI3K/AKT/mTOR signal pathway.
6.Preparation Method and Quality Evaluation of Novel Frozen Human Platelets
Yi-Zhe ZHENG ; Dong-Dong LI ; Geng-Wei YAN ; Bao-Jian WANG ; Ke WANG ; Lei WANG ; Shao-Duo YAN ; Yan-Hong LI ; Qiu-Xia FU ; Zhen-Wei SUN
Journal of Experimental Hematology 2024;32(4):1264-1270
Objective:To optimize the technical parameters related to the preparation of novel frozen human platelets and formulate corresponding protocol for its preparation.Methods:Novel frozen human platelets were prepared with O-type bagged platelet-rich plasma(PRP),the key technical parameters(DMSO addition,incubation time,centrifugation conditions,etc.)of the preparation process were optimized,and the quality of the frozen platelets was evaluated by routine blood tests,apoptosis rate,platelet activation rate and surface protein expression level.Results:In the preparation protocol of novel frozen human platelets,the operation of centrifugation to remove supernatant was adjusted to before the procedure of platelets freezing,and the effect of centrifugation on platelets was minimal when the centrifugation condition was 800 xg for 8 min.In addition,platelets incubated with DMSO for 30 min before centrifugation exhibited better quality after freezing and thawing.The indexes of novel frozen human platelets prepared with this protocol remained stable after long-term cryopreservation.Conclusion:The preparation technique of novel frozen human platelets was established and the protocol was formulated.It was also confirmed that the quality of frozen platelets could be improved by incubating platelets with DMSO for 30 min and then centrifuging them at 800 ×g for 8 min in the preparation of novel frozen human platelets.
7.Feasibility and safety study of building a friendly management model for elderly critically ill patients based on geriatric intensive care unit: a prospective controlled study
Junma XU ; Yi XIE ; Dong YUAN ; Chan SHAO ; Fangqin XU ; Shu HAN
Chinese Critical Care Medicine 2024;36(8):867-870
Objective:To explore the feasibility and safety of integrating the geriatric intensive care unit (GICU) into the friendly management model of the elderly critically ill patients.Methods:A prospective controlled study was conducted. Patients with elderly critically ill admitted to the GICU and the general intensive care unit (ICU) of Jintan First People's Hospital of Changzhou from December 2021 to May 2023 were enrolled. Patients in the ICU group received the traditional intensive care and nursing mode. In addition to the ICU group basic medical care measures, the patients in the GICU group were treated with friendly management models such as flexible visitation, diagnosis and treatment environment optimization, caring diagnosis and treatment, and family participation in hospice care according to their condition assessment. The gender, age, main diagnosis, and acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) at admission were recorded and compared between the two groups. During the treatment period, the incidence of nosocomial infection, unplanned extubation, falling out of bed/fall, unexpected readmission to ICU/GICU, and ICU/GICU mortality, the incidence of post-intensive care syndrome (PICS), the satisfaction rate of patients/families with medical care, and the satisfaction rate of patients/families with diagnosis and treatment environment were recorded and compared between the two groups.Results:According to the admission criteria for ICU and GICU, as well as the willingness of the patients and/or their families, a total of 59 patients were finally included in the ICU group, and 48 patients were enrolled in the GICU group. There were no significantly differences in gender, age, main diagnosis and APACHEⅡ score between the two groups, and there were comparability. There were no significantly differences in the incidence of adverse events such as nosocomial infection [13.6% (8/59) vs. 12.5% (6/48)], unplanned extubation [5.1% (3/59) vs. 6.2% (3/48)], falling out of bed/fall [3.4% (2/59) vs. 0% (0/48)], unexpected readmission to ICU/GICU [8.5% (5/59) vs. 10.4% (5/48)], and ICU/GICU mortality [6.8% (4/59) vs. 6.2 (3/48)] between the ICU group and GICU group (all P > 0.05). Compared with the ICU group, the incidence of PICS in GICU group was significantly lower [8.3% (4/48) vs. 25.4% (15/59), P < 0.05], the satisfaction rate of patients/families with medical care [89.6% (43/48) vs. 74.6% (44/59)] and satisfaction rate of patients/families with diagnosis and treatment environment [87.5% (42/48) vs. 67.8% (40/59)] were significantly increased (both P < 0.05). Conclusion:The use GICU as a friendly management model for elderly critically ill patients is feasible and safe, and it is worthy of further exploration and research.
8.Classification Method for Petroleum Pollutants Based on Inception-One-Dimensional Convolutional Neural Network and Infrared Spectroscopy
De-Ming KONG ; Shao-Wei HE ; Xin-Yi LI ; Jun-Yu ZHAO ; Xiao-Dong NING
Chinese Journal of Analytical Chemistry 2024;52(9):1287-1297
Infrared spectroscopy technology has many advantages such as high efficiency and non-destructiveness,and has an important research and application value in the field of petroleum pollutant classification and detection.In this study,a petroleum pollutant classification method by combing the discrete wavelet transform(DWT)algorithm and a one-dimensional convolutional neural network based on the Inception module(Inception-1D-CNN)was proposed.Firstly,the DWT algorithm was used to denoise the original infrared spectral data to eliminate the interference information caused by experimental environment,instrument error and manual operation.Then,the inception-1D-CNN model was used to obtain multi-scale infrared spectroscopy feature information,and then classify the petroleum pollutants.Experimental results showed that compared with preprocessing methods such as standard normal variable(SNV),adaptive iteratively reweighted penalized least squares(AirPLS),and Savitzky-Golay smoothing(S-G),the prediction accuracy of the DWT algorithm combined with the 1D-CNN model with a convolutional kernel size of 3×1 was 86.6%,which was 6.6%,6.6%and 3.3%higher,respectively.The prediction accuracy of DWT algorithm combined with 1D-CNN model with a convolutional kernel size of 5×1 was 93.3%,which was 10.0%,7.0%and 3.3%higher,respectively.The prediction accuracy of the DWT algorithm combined with the 1D-CNN model with a convolutional kernel size of 7×1 was 90.0%,which was 6.7%,10.0%and 3.4%higher,respectively.The prediction accuracy of the DWT algorithm combined with the inception-1D-CNN model was 100.0%,which was 10.0%,10.0%and 3.4%higher,respectively.Therefore,the DWT algorithm combined with the inception-1D-CNN model could accurately classify and predict petroleum pollutants,and provided a certain basis for the subsequent treatment of oil spills on the sea surface.
9.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.
10.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.

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