1.Research advances on RPL11 in the regulation of cellular stress induced by ionizing radiation
Hongyu BAO ; Yan LU ; Chenyu ZHAO ; Mingxuan BI ; Jinghong FU ; Yong ZHANG ; Lian YU ; Weiguo LI
Chinese Journal of Radiological Health 2026;35(2):286-291
Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.
2.Research advances on RPL11 in the regulation of cellular stress induced by ionizing radiation
Hongyu BAO ; Yan LU ; Chenyu ZHAO ; Mingxuan BI ; Jinghong FU ; Yong ZHANG ; Lian YU ; Weiguo LI
Chinese Journal of Radiological Health 2026;35(2):286-291
Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.
3.Research advances on RPL11 in the regulation of cellular stress induced by ionizing radiation
Hongyu BAO ; Yan LU ; Chenyu ZHAO ; Mingxuan BI ; Jinghong FU ; Yong ZHANG ; Lian YU ; Weiguo LI
Chinese Journal of Radiological Health 2026;35(2):286-291
Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.
4.Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells.
Yi WANG ; Xiao-Yu SUN ; Fang-Qi MA ; Ming-Ming REN ; Ruo-Han ZHAO ; Meng-Meng QIN ; Xiao-Hong ZHU ; Yan XU ; Ni-da CAO ; Yuan-Yuan CHEN ; Tian-Geng DONG ; Yong-Fu PAN ; Ai-Guang ZHAO
Journal of Integrative Medicine 2025;23(3):320-332
OBJECTIVE:
Gastric cancer (GC) is one of the most common malignancies seen in clinic and requires novel treatment options. Morin is a natural flavonoid extracted from the flower stalk of a highly valuable medicinal plant Prunella vulgaris L., which exhibits an anti-cancer effect in multiple types of tumors. However, the therapeutic effect and underlying mechanism of morin in treating GC remains elusive. The study aims to explore the therapeutic effect and underlying molecular mechanisms of morin in GC.
METHODS:
For in vitro experiments, the proliferation inhibition of morin was measured by cell counting kit-8 assay and colony formation assay in human GC cell line MKN45, human gastric adenocarcinoma cell line AGS, and human gastric epithelial cell line GES-1; for apoptosis analysis, microscopic photography, Western blotting, ubiquitination analysis, quantitative polymerase chain reaction analysis, flow cytometry, and RNA interference technology were employed. For in vivo studies, immunohistochemistry, biomedical analysis, and Western blotting were used to assess the efficacy and safety of morin in a xenograft mouse model of GC.
RESULTS:
Morin significantly inhibited the proliferation of GC cells MKN45 and AGS in a dose- and time-dependent manner, but did not inhibit human gastric epithelial cells GES-1. Only the caspase inhibitor Z-VAD-FMK was able to significantly reverse the inhibition of proliferation by morin in both GC cells, suggesting that apoptosis was the main type of cell death during the treatment. Morin induced intrinsic apoptosis in a dose-dependent manner in GC cells, which mainly relied on B cell leukemia/lymphoma 2 (BCL-2) associated agonist of cell death (BAD) but not phorbol-12-myristate-13-acetate-induced protein 1. The upregulation of BAD by morin was due to blocking the ubiquitination degradation of BAD, rather than the transcription regulation and the phosphorylation of BAD. Furthermore, the combination of morin and BCL-2 inhibitor navitoclax (also known as ABT-737) produced a synergistic inhibitory effect in GC cells through amplifying apoptotic signals. In addition, morin treatment significantly suppressed the growth of GC in vivo by upregulating BAD and the subsequent activation of its downstream apoptosis pathway.
CONCLUSION
Morin suppressed GC by inducing apoptosis, which was mainly due to blocking the ubiquitination-based degradation of the pro-apoptotic protein BAD. The combination of morin and the BCL-2 inhibitor ABT-737 synergistically amplified apoptotic signals in GC cells, which may overcome the drug resistance of the BCL-2 inhibitor. These findings indicated that morin was a potent and promising agent for GC treatment. Please cite this article as: Wang Y, Sun XY, Ma FQ, Ren MM, Zhao RH, Qin MM, Zhu XH, Xu Y, Cao ND, Chen YY, Dong TG, Pan YF, Zhao AG. Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells. J Integr Med. 2025; 23(3): 320-332.
Humans
;
Flavonoids/therapeutic use*
;
Stomach Neoplasms/pathology*
;
Animals
;
Proto-Oncogene Proteins c-bcl-2/metabolism*
;
Cell Line, Tumor
;
Apoptosis/drug effects*
;
Cell Proliferation/drug effects*
;
Ubiquitination/drug effects*
;
Mice
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Drug Synergism
;
Mice, Inbred BALB C
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Mice, Nude
;
Xenograft Model Antitumor Assays
;
Flavones
5.Longitudinal Associations between Vitamin D Status and Systemic Inflammation Markers among Early Adolescents.
Ting TANG ; Xin Hui WANG ; Xue WEN ; Min LI ; Meng Yuan YUAN ; Yong Han LI ; Xiao Qin ZHONG ; Fang Biao TAO ; Pu Yu SU ; Xi Hua YU ; Geng Fu WANG
Biomedical and Environmental Sciences 2025;38(1):94-99
6.Analysis of Tongue and Face Image Features of Anemic Women and Construction of Risk-Screening Model.
Hong Yuan FU ; Yi CHUN ; Ya Han ZHANG ; Yu WANG ; Yu Lin SHI ; Tao JIANG ; Xiao Juan HU ; Li Ping TU ; Yong Zhi LI ; Jia Tuo XU
Biomedical and Environmental Sciences 2025;38(8):935-951
OBJECTIVE:
To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance.
METHODS:
A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated.
RESULTS:
Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818].
CONCLUSION
Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans
;
Female
;
Tongue/diagnostic imaging*
;
Adult
;
Anemia/diagnosis*
;
Middle Aged
;
Face/diagnostic imaging*
;
Young Adult
;
Machine Learning
7.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
8.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
9.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.
10.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.

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