1.Optimal Ratio of Chuanxiong Rhizoma-Carthami Flos Couplet Medicines and Its Anti-ischemic Stroke Effect
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(5):21-31
ObjectiveThis study aimed to investigate the optimal compatibility ratio of the Chuanxiong Rhizoma-Carthami Flos (CR-CF) couplet medicines in ischemic stroke (IS) therapy and its pharmacological action mechanism, providing a scientific basis for the clinical application of CR-CF couplet medicines in IS therapy. MethodsThe chemical composition of CR-CF was analyzed using liquid chromatography mass spectrometry (LC-MS/MS). The contents of eight characteristic chemical components in aqueous extracts of CR-CF with common clinical compatibility ratios (1∶1, 1∶2, 1∶3, 3∶2, 2∶1) were determined by ultra-high performance liquid chromatography(UHPLC). An oxygen-glucose deprivation/reoxygenation (OGD/R)-induced mouse hippocampal neuron HT22 cell injury model was established, and cells were treated with different CR-CF compatibility ratios. The collaborative index (CI) was calculated by using CompuSyn software. A cerebral artery occlusion/reperfusion (MCAO/R) model of rats was induced by using the modified Longa suture method. The rats were divided into the sham group, model group, Chuanxiong Rhizoma (CR) group (1.3 g·kg-1), Carthami Flos (CF) group (3.9 g·kg-1), CR-CF group (5.2 g·kg-1), and edaravone group (5 mg·kg-1). Neuronal defect scores were assessed by the Longa scoring method. Cerebral infarction volume was measured by 2,3,5-triphenyltetrazolium chloride(TTC) staining. Neuronal damage was observed via hematoxylin-eosin (HE) staining. Neuronal apoptosis of rats was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining, and the expression of apoptosis-related proteins was analyzed by Western blot. Label-free proteomics was employed to screen differentially expressed proteins, and Western blot was used to examine the expression of phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt) signaling pathway-related proteins. Finally, molecular docking was performed to predict the binding affinity of eight active constituents in CR-CF (1∶3) with PI3K. ResultsWhen CR-CF was combined at a 1∶3 ratio, the total content of the eight active constituents in the extract was the highest, and the synergistic protective effect on OGD/R-injured HT22 cells was the strongest (CI=0.308). Animal experiments showed that compared with the sham group, the model group exhibited increased neuroecological score points (P<0.01), larger cerebral infarction volumes (P<0.01), aggravated brain tissue damage, elevated neuronal apoptosis (P<0.01), and increased B-cell lymphoma-2(Bcl-2)-associated X protein (Bax)/Bcl-2 and cleaved Cysteinyl aspartate specific proteinase-3/Cysteinyl aspartate specific proteinase-3 (cleaved Caspase-3/Caspase-3) ratios (P<0.01). Compared with the model group, CR-CF (1∶3) significantly reduced neurological scores (P<0.01), significantly decreased cerebral infarction volume (P<0.01), alleviated brain tissue damage, inhibited neuronal apoptosis (P<0.01), and significantly lowered the Bax/Bcl-2 and cleaved Caspase-3/Caspase-3 ratios (P<0.01). The therapeutic effect of CR-CF (1∶3) was superior to that of CR or CF alone. Proteomic analysis revealed that CR-CF (1∶3) activated the PI3K/Akt signaling pathway. Validation experiments demonstrated that compared with the sham group, the model group showed obviously reduced p-PI3K/PI3K and p-Akt/Akt (P<0.05). Compared with the model group, p-PI3K/PI3K and p-Akt/Akt ratios (P<0.05) obviously increased. Compared with the CR-CF group, the 2-(4-morpholinyl)-8-phenyl-4H-1-benzopyran-4-one LY294002 inhibitor+CR-CF group exhibited obviously decreased p-PI3K/PI3K and p-Akt/Akt (P<0.05). Molecular docking results indicated that the active constituents of CR-CF (1∶3) had strong binding affinity with PI3K. ConclusionThe CR-CF couplet medicines at a 1∶3 ratio exhibit optimal synergistic effects, and their anti-IS mechanism is closely related to activation of the PI3K/Akt signaling pathway and inhibition of neuronal apoptosis.
2.Expert consensus on the basic research and clinical application of circadian clock for the precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma
Kai YANG ; Moyi SUN ; Longjiang LI ; Zhangui TANG ; Wei GUO ; Guoxin REN ; Zhiwei ZHANG ; Hong TANG ; Jie ZHANG ; Zhijun SUN ; Qing XI ; Chunjie LI ; Xin HUANG ; Heming WU ; Wei SHANG ; Jian MENG ; Jichen LI ; Hong MA ; Guiquan ZHU ; Yi LI ; Yaoxu LI ; Haitao HE ; Fugui ZHANG ; Jie ZHANG ; Dan ZHAO ; Deping SUN ; Xiaoqiang LV ; Dan CHEN ; Fujun ZHANG ; Rui CHEN ; Yadong LI ; Jinsong ZHANG ; Xiaojuan FU ; Li XIANG ; Shouyi LI ; Shilin YIN
Journal of Practical Stomatology 2025;41(2):149-156
Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.
3.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
4.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; 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(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
5.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
6.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; 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(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
7.Drug resistance characteristics and whole genome polymorphisms of group A Streptococcus in Jiangsu Province during 2016 to 2023
Jie HONG ; Hao-di HUANG ; Ke XU ; Zhong-ming TAN ; Hui-min QIAN ; Jie-fu PENG ; Xiao-xiao KONG
Chinese Journal of Zoonoses 2025;41(1):40-46
This study was aimed at understanding the relationships among the drug resistance and genome characteristics of group A Streptococcus in Jiangsu Province.A total of 149 group A Streptococcus strains were collected from hospitals between 2016 and 2023.Thirteen antimicrobial minimal inhibitory concentrations were detected with the micro-dilution broth method.The GAS strains were typed with emm genotyping analysis and whole genome sequencing,to determine the carriage rates of drug resistance genes and the evolutionary relationships among strains.The resistance rates of 149 GAS strains to erythromy-cin,tetracycline,and clindamycin exceeded 90%,whereas the strains showed sensitivity to 8 different antibiotics,including penicillin.Notably,the resistance rates to erythromycin,tetracycline,and clindamycin consistently increased over time.All strains were classified into 9 emm types,among which emm12 accounted for the highest proportion(77/149;51.68%).Signifi-cant statistical differences were observed among emm types,in terms of the drug resistance rate,number of resistant species,and prevalence of drug resistance genes.Furthermore,SNP evolutionary tree analysis revealed 3 distinct clusters within the GAS strains:emm12,emm1,and other emm types.emm 12 and emm1 were the dominant GAS strains in Jiangsu Province.Most isolates were resistant to erythromycin,tetracycline,and clindamycin.Differences in phenotypes and genomic characteris-tics were observed among emm types.
8.Construction and validation of a diagnostic model for colorectal mucinous adenocarcinoma integrating preoperative inflammatory and clinical features
Qing FANG ; Shuxiang LI ; Jinyi YUAN ; Jie TAN ; Hongmin LI ; Yunhua XU ; Guang FU ; Qiulin HUANG ; Shuai XIAO
Chinese Journal of General Surgery 2025;34(10):2119-2128
Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.
9.Construction and validation of a diagnostic model for colorectal mucinous adenocarcinoma integrating preoperative inflammatory and clinical features
Qing FANG ; Shuxiang LI ; Jinyi YUAN ; Jie TAN ; Hongmin LI ; Yunhua XU ; Guang FU ; Qiulin HUANG ; Shuai XIAO
Chinese Journal of General Surgery 2025;34(10):2119-2128
Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.
10.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.

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