1.Predictive efficacy of multimodal MRI-based machine learning models for glioblastoma multiforme MGMT promoter methylation states
Hong-lin LI ; Shi-ting HU ; Zi-heng ZHOU ; Bing LI ; Zhi-ping QI ; Ruo-qi LI ; Kai LIU ; Chun-feng HU ; Hai-tao GE
Chinese Medical Equipment Journal 2025;46(6):7-13
Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67%and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]
2.Pathogenesis and treatment strategies for infectious keratitis: Exploring antibiotics, antimicrobial peptides, nanotechnology, and emerging therapies.
Man YU ; Ling LI ; Yijun LIU ; Ting WANG ; Huan LI ; Chen SHI ; Xiaoxin GUO ; Weijia WU ; Chengzi GAN ; Mingze LI ; Jiaxu HONG ; Kai DONG ; Bo GONG
Journal of Pharmaceutical Analysis 2025;15(9):101250-101250
Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis (VK). Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.
3.Predictive efficacy of multimodal MRI-based machine learning models for glioblastoma multiforme MGMT promoter methylation states
Hong-lin LI ; Shi-ting HU ; Zi-heng ZHOU ; Bing LI ; Zhi-ping QI ; Ruo-qi LI ; Kai LIU ; Chun-feng HU ; Hai-tao GE
Chinese Medical Equipment Journal 2025;46(6):7-13
Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67%and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]
4.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.
5.Development of a High-throughput Sequencing Platform for Detection of Viral Encephalitis Pathogens Based on Amplicon Sequencing
Li Ya ZHANG ; Zhe Wen SU ; Chen Rui WANG ; Yan LI ; Feng Jun ZHANG ; Hui Sheng LIU ; He Dan HU ; Xiao Chong XU ; Yu Jia YIN ; Kai Qi YIN ; Ying HE ; Fan LI ; Hong Shi FU ; Kai NIE ; Dong Guo LIANG ; Yong TAO ; Tao Song XU ; Feng Chao MA ; Yu Huan WANG
Biomedical and Environmental Sciences 2024;37(3):294-302
Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.
6.Clinical diagnosis and comprehensive treatment of Fournier's gangrene:A case report and literature review
Xiangli KONG ; Kai SHI ; Xi ZHANG ; Yan XUE ; Lei HONG ; Xiuhang ZHANG
Journal of Jilin University(Medicine Edition) 2024;50(4):1144-1149
Objective:To discuss the clinical presentations,diagnosis,and treatment methods of the patients with Fournier's gangrene,and to enhance the clinicians'awareness of this condition.Methods:The clinical data including symptoms,signs,radiological findings,and surgical outcomes of one patient with Fournier's gangrene were collected.The relevant literatures were reviewed to summarize the clinical characteristics,diagnosis,and treatment methods for this condition.Results:The patient,a 42-year-old male,was admitted because of a history of infection around the perineum,scrotum,and perianal area for 13 d.His medical history included acute myeloid leukemia for 10 months,during which the patient underwent eight chemotherapy sessions in the local hospital.The abdominal CT scan results showed thickened,dense,and turbid soft tissue in the left inguinal area.The complete blood count reuslts showed the white blood cell count was 23.99×109 L-1.The cultures of wound secretions grew the Escherichia coli and Proteus mirabilis.The examination results showed there was necrosis of the scrotal skin and skin near the anus on the left buttock;the skin was blackened,hard,and demarcated from the surrounding normal skin with slight purulent exudation and no foul smell.The surrounding skin was significantly swollen and red;the rectal examination results showed no bleeding or fistulas.The patient underwent emergency debridement surgery on the admission day,followed by dressing changes,multiple applications of simplified negative pressure,perineal flap reconstruction,and skin grafting.The patient recovered well with normal function and had no complications.Conclusion:Fournier gangrene has acute onset and rapid progression,and the clinical manifestations are non-specific.The range of infection is not consistent with the progression of the disease.The diagnosis mainly depends on intraoperative exploration.Repeated radical surgery is the main treatment.The prognosis of this disease is good,and the recurrence rate is low,although long-term follow-up is still necessary after surgery.
7.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
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 ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; 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 ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% 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) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had 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 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
8.Effects of different processing methods on oil components in Gleditsiae sinensis Fructus and Gleditsiae Fructus Abnormalis
Shi-Rong DOU ; Yan-Gang CAO ; Kai LI ; Lian-Qi TIAN ; Xiang-Le MENG ; Yan-Bang SHI ; Li-Xian ZHANG ; Hong-Wei LI ; Wei-Sheng FENG
Chinese Traditional Patent Medicine 2024;46(6):1809-1818
AIM To investigate the effects of stir-frying,processing with butter and carbonizing by stir-frying on oil components in Gleditsiae sinensis Fructus and Gleditsiae Fructus Abnormalis.METHODS The volatile oils and fatty oils were extracted by steam distillation method and Soxhlet extraction method,respectively,after which the extraction rates were determined.GC-MS was applied to analyzing the kinds and relative contents of oil components,after which cluster analysis was performed.RESULTS After the processing,the two medicinal materials demonstrated increased extraction rates of fatty oils and decreased extraction rates of volatile oils(except for processing with butter),the extraction rates of oil components in Gleditsiae sinensis Fructus were higher than those in Gleditsiae Fructus Abnormalis,and the reduced relative contents of toxic olefin benzene components were observable.CONCLUSION The kinds and relative contents of oil components in Gleditsiae sinensis Fructus and Gleditsiae Fructus Abnormalis exist obvious differences,the former displays better medicinal quality,whose processing mechanism in alleviating dryness and strength may contribute to the reduction of relative contents of toxic olefin benzene components.
9.Co-infection of Chlamydia pneumoniae and SARS-CoV-2 and its effect on the secretion of inflammatory cytokines
Jia-Yan LI ; Li-Ping YUAN ; Qing-Kai LUO ; Ye-Fei LEI ; Yuan LI ; Feng-Hua ZHANG ; Li-Xiu PENG ; Yu-Qi OUYANG ; Shi-Xing TANG ; Hong-Liang CHEN
Chinese Journal of Infection Control 2024;23(11):1391-1397
Objective To explore characteristics of co-infection of Chlamydia pneumoniae(Cpn)and severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),and identify their effect on SARS-CoV-2-induced inflammatory response.Methods Patients with coronavirus disease 2019(COVID-19)who received treatment in a hospital in Chenzhou City from December 20,2022 to February 20,2023 were selected.According to the severity of COVID-19,severe and critical cases were classified as the severe symptom group,while mild and moderate cases were classified as the mild symptom group.Meanwhile,according to the age of patients(≥18 years old as adults,<18 years old as juveniles),they were divided into the adult severe symptom group,adult mild symptom group,juvenile severe symptom group,and juvenile mild symptom group.Propensity score was adopted to match age,gender,and under-lying diseases of patients in severe symptom and mild symptom group in a 1∶1 ratio.Bronchoalveolar lavage fluid(BALF),throat swabs,and serum specimens of patients were collected.Cpn IgG/IgM antibody was detected by enzyme-linked immunosorbent assay(ELISA),levels of 12 common cytokines(including interleukin-8[IL-8])in BALF were detected by flow cytometry,differences among groups were compared.Results A total of 102 patients were included,with 61 severe and critical(severe symptom)patients,as well as 41 mild and moderate(mild symp-tom)patients.There were 71 patients aged ≥18 years and 31 juvenile patients aged<18 years.There were 39 pa-tients in the adult severe symptom group and 32 in the adult mild symptom group,and 30 pairs were successfully matched through propensity score analysis.There were 22 patients in the juvenile severe symptom group and 9 in the juvenile mild symptom group,and 8 pairs were successfully matched through propensity score analysis.Among COVID-19 patients,the positive rates of Cpn IgG and IgM were 36.27%(n=37)and 8.82%(n=9),respective-ly,with 1 case positive for both Cpn IgG and IgM.The level of interferon(IFN)-α in serum specimens from adult patients with severe symptom combined with positive Cpn IgG was higher than that of IgG negative patients(P=0.037).There was no statistically significant difference in the levels of other cytokines in BALF and serum speci-mens between the two groups of patients(all P>0.05).The levels of IL-8 and IL-17 in serum specimens of patients with positive Cpn IgG in the adult mild symptom group were both higher than those in Cpn IgG negative patients(both P<0.05).The levels of IL-8 in both BALF and serum specimens from Cpn IgM positivity patients in the ju-venile mild symptom group were higher than those from patients with negative Cpn IgM(both P<0.05).Logistic regression analysis results showed that Cpn IgG and IgM positivity were not risk factors for the development of se-vere COVID-19.Conclusion Combined Cpn infection is not a risk factor for the development of severe symptom in COVID-19 patients,and Cpn infection has limited impact on the secretion of inflammatory factors caused by SARS-CoV-2.
10.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
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 ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; 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 ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% 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) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had 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 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.

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