1.Mechanism of Xiayuxue Tang in Inhibiting Hepatocellular Carcinoma Cells by Regulating YAP1/SIRT5 Signaling Axis to Mediate Succinate Metabolism and Succinylation
Linzhu LU ; Qianqian GUO ; Xuefei TIAN ; Bin CHEN ; Nianhua TAN
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(16):52-61
		                        		
		                        			
		                        			ObjectiveTo investigate the inhibitory effects and mechanisms of Xiayuxue Tang (XYXT) on hepatocellular carcinoma cells through the regulation of succinate metabolism and succinylation modification. MethodsXYXT-medicated serum was prepared. The effects of different concentrations of succinate on the proliferation of HepG2 and MHCC97H cells were observed using the cell counting kit-8 (CCK-8) assay, and the experimental concentrations for subsequent tests were determined. Further CCK-8 assays were performed to evaluate the effects of XYXT-medicated serum of different concentrations (5%, 10%, and 15%) on cell proliferation. Flow cytometry, scratch test, and Transwell assay were employed to analyze the effect of 10% XYXT-medicated serum on the cell cycle, migration, invasion, and apoptosis. The changes in succinate metabolism and succinylation modification were examined based on succinate content assays, succinate dehydrogenase (SDH) activity detection, and western blot. The expressions of Yes-associated protein 1 (YAP1) and sirtuin 5 (SIRT5) were detected via Real-time PCR and western blot. Molecular docking was applied to validate the binding between XYXT’s main components and target proteins. ResultsCompared with the control group, 1-2 mmol·L-¹ succinate significantly promoted HepG2 and MHCC97H cell proliferation (P<0.01). XYXT-medicated serum (5%, 10%, and 15%) markedly inhibited the proliferation of both cell lines compared with the blank group (P<0.05, P<0.01). Treatment with 10% XYXT-medicated serum arrested the cell cycle at the stage prior to DNA synthesis (G0/G1) (P<0.01), suppressed migration (P<0.01) and invasion (P<0.05, P<0.01), and promoted apoptosis of HepG2 and MHCC97H cells (P<0.01). Co-treatment with XYXT and succinate reversed the inhibitory effects of XYXT on proliferation, migration, and invasion of HepG2 and MHCC97H cells (P<0.05, P<0.01). The proportion of cells at G0/G1 phase decreased (P<0.01), and the apoptosis rate decreased (P<0.01). In terms of succinate metabolism, compared with the blank serum group, the 10% XYXT-medicated serum reduced succinate levels of HepG2 and MHCC97H cells (P<0.05, P<0.01), enhanced SDH activity (P<0.01), and downregulated succinylation modification. In terms of YAP1/SIRT5 pathway, compared with the blank serum group, the 10% XYXT-medicated serum significantly downregulated the mRNA and protein expressions of YAP1 in HepG2 and MHCC97H cells (P<0.05, P<0.01) while significantly upregulated the mRNA and protein expressions of SIRT5 (P<0.05, P<0.01). Molecular docking confirmed that there was a good binding ability between YAP1 and SIRT5, as well as between XYXT's main active components and YAP1 and SIRT5. ConclusionXYXT suppresses hepatocellular carcinoma cells by modulating the YAP1/SIRT5 signaling axis to intervene in succinate metabolism and succinylation modification. 
		                        		
		                        		
		                        		
		                        	
2.Role of amino acid metabolism in autoimmune hepatitis and related therapeutic targets
Peipei GUO ; Yang XU ; Jiaqi SHI ; Yang WU ; Lixia LU ; Bin LI ; Xiaohui YU
Journal of Clinical Hepatology 2025;41(3):547-551
		                        		
		                        			
		                        			Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease. The pathogenesis of AIH remains unclear, but it is mainly autoimmune injury caused by the breakdown of autoimmune tolerance due to the abnormal activation of the immune system, while the specific molecular mechanism remains unknown. Recent studies have shown that abnormal amino acid metabolism plays an important role in the development and progression of AIH. This article reviews the research advances in amino acid metabolic reprogramming in AIH, in order to provide a theoretical basis for amino acid metabolism as a new target for the clinical diagnosis and treatment of AIH. 
		                        		
		                        		
		                        		
		                        	
3.Dynamics of eosinophil infiltration and microglia activation in brain tissues of mice infected with Angiostrongylus cantonensis
Fanna WEI ; Renjie ZHANG ; Yahong HU ; Xiaoyu QIN ; Yunhai GUO ; Xiaojin MO ; Yan LU ; Jiahui SUN ; Yan ZHOU ; Jiatian GUO ; Peng SONG ; Yanhong CHU ; Bin XU ; Ting ZHANG ; Yuchun CAI ; Muxin CHEN
Chinese Journal of Schistosomiasis Control 2025;37(2):163-175
		                        		
		                        			
		                        			 Objective To investigate the changes in eosinophil counts and the activation of microglial cells in the brain tissues of mice at different stages of Angiostrongylus cantonensis infection, and to examine the role of microglia in regulating the progression of angiostrongyliasis and unravel the possible molecular mechanisms. Methods Fifty BALB/c mice were randomly divided into the control group and the 7-d, 14-d, 21-day and 25-d infection groups, of 10 mice in each group. All mice in infection groups were infected with 30 stage III A. cantonensis larvae by gavage, and animals in the control group was given an equal amount of physiological saline. Five mice were collected from each of infection groups on days 7, 14, 21 d and 25 d post-infection, and 5 mice were collected from the control group on the day of oral gavage. The general and focal functional impairment was scored using the Clark scoring method to assess the degree of mouse neurological impairment. Five mice from each of infection groups were sacrificed on days 7, 14, 21 d and 25 d post-infection, and 5 mice from the control group were sacrificed on the day of oral gavage. Mouse brain tissues were sampled, and the pathological changes of brain tissues were dynamically observed using hematoxylin and eosin (HE) staining. Immunofluorescence staining with eosinophilic cationic protein (ECP) and ionized calcium binding adaptor molecule 1 (Iba1) was used to assess the degree of eosinophil infiltration and the counts of microglial cells in mouse brain tissues in each group, and the morphological parameters of microglial cells (skeleton analysis and fractal analysis) were quantified by using Image J software to determine the morphological changes of microglial cells. In addition, the expression of M1 microglia markers Fcγ receptor III (Fcgr3), Fcγ receptor IIb (Fcgr2b) and CD86 antigen (Cd86), M2 microglia markers Arginase 1 (Arg1), macrophage mannose receptor C-type 1 (Mrc1), chitinase-like 3 (Chil3), and phagocytosis genes myeloid cell triggering receptor expressed on myeloid cells 2 (Trem2), CD68 antigen (Cd68), and apolipoprotein E (Apoe) was quantified using real-time quantitative reverse transcription PCR (RT-qPCR) assay in the mouse cerebral cortex of mice post-infection. Results A large number of A. cantonensis larvae were seen on the mouse meninges surface post-infection, and many neuronal nuclei were crumpled and deeply stained, with a large number of bleeding points in the meninges. The median Clark scores of mouse general functional impairment were 0 (interquartile range, 0), 0 (interquartile range, 0.5), 6 (interquartile range, 1.0), 14 (interquartile range, 8.5) points and 20 (interquartile range, 9.0) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.45, P < 0.01), and the median Clark scores of mouse focal functional impairment were 0 (interquartile range, 0), 2 (interquartile range, 2.5), 7 (interquartile range, 3.0), 18 (interquartile range, 5.0) points and 25 (interquartile range, 6.5) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.72, P < 0.01). The mean scores of mice general and focal functional impairment were all higher in the infection groups than in the control group (all P values < 0.05). Immunofluorescence staining showed a significant difference in the eosinophil counts in mouse brain tissues among the five groups (F = 40.05, P < 0.000 1), and the eosinophil counts were significantly higher in mouse brain tissues in the 14-d (3.08 ± 0.78) and 21-d infection groups (5.97 ± 1.37) than in the control group (1.00 ± 0.28) (both P values < 0.05). Semi-quantitative analysis of microglia immunofluorescence showed a significant difference in the counts of microglial cells among the five groups (F = 17.66, P < 0.000 1), and higher Iba1 levels were detected in mouse brain tissues in 14-d (5.75 ± 1.28), 21-d (6.23 ± 1.89) and 25-d infection groups (3.70 ± 1.30) than in the control group (1.00 ± 0.30) (all P values < 0.05). Skeleton and fractal analyses showed that the branch length [(162.04 ± 34.10) μm vs. (395.37 ± 64.11) μm; t = 5.566, P < 0.05] and fractal dimension of microglial cells (1.30 ± 0.01 vs. 1.41 ± 0.03; t = 5.266, P < 0.05) were reduced in mouse brain tissues in the 21-d infection group relative to the control group. In addition, there were significant differences among the 5 groups in terms of M1 and M2 microglia markers Fcgr3 (F = 48.34, P < 0.05), Fcgr2b (F = 55.46, P < 0.05), Cd86 (F = 24.44, P < 0.05), Arg1 (F = 31.18, P < 0.05), Mrc1 (F = 15.42, P < 0.05) and Chil3 (F = 24.41, P < 0.05), as well as phagocytosis markers Trem2 (F = 21.19, P < 0.05), Cd68 (F = 43.95, P < 0.05) and Apoe (F = 7.12, P < 0.05) in mice brain tissues. Conclusions A. cantonensis infections may induce severe pathological injuries in mouse brain tissues that are characterized by massive eosinophil infiltration and persistent activation of microglia cells, thereby resulting in progressive deterioration of neurological functions. 
		                        		
		                        		
		                        		
		                        	
4.Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults (version 2024)
Qingde WANG ; Yuan HE ; Bohua CHEN ; Tongwei CHU ; Jinpeng DU ; Jian DONG ; Haoyu FENG ; Shunwu FAN ; Shiqing FENG ; Yanzheng GAO ; Zhong GUAN ; Hua GUO ; Yong HAI ; Lijun HE ; Dianming JIANG ; Jianyuan JIANG ; Bin LIN ; Bin LIU ; Baoge LIU ; Chunde LI ; Fang LI ; Feng LI ; Guohua LYU ; Li LI ; Qi LIAO ; Weishi LI ; Xiaoguang LIU ; Hongjian LIU ; Yong LIU ; Zhongjun LIU ; Shibao LU ; Yong QIU ; Limin RONG ; Yong SHEN ; Huiyong SHEN ; Jun SHU ; Yueming SONG ; Tiansheng SUN ; Yan WANG ; Zhe WANG ; Zheng WANG ; Hong XIA ; Guoyong YIN ; Jinglong YAN ; Wen YUAN ; Zhaoming YE ; Jie ZHAO ; Jianguo ZHANG ; Yue ZHU ; Yingjie ZHOU ; Zhongmin ZHANG ; Wei MEI ; Dingjun HAO ; Baorong HE
Chinese Journal of Trauma 2024;40(2):97-106
		                        		
		                        			
		                        			Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.
		                        		
		                        		
		                        		
		                        	
5.Peripheral blood cell count composite score as a prognostic factor in patients with colorectal cancer
Peiyuan GUO ; Xuhua HU ; Baokun LI ; Ti LU ; Jiaming LIU ; Chaoyu WANG ; Wenbo NIU ; Guiying WANG ; Bin YU
Chinese Journal of Gastrointestinal Surgery 2024;27(9):953-965
		                        		
		                        			
		                        			Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.
		                        		
		                        		
		                        		
		                        	
6.Evaluation of the efficacy and safety of Xiao′er Huangjin Zhike Granules in the treatment of acute bronchitis-caused cough (syndrome of phlegm-heat obstructing the lung) in children
Jun LIU ; Mengqing WANG ; Xiuhong JIN ; Yongxue CHI ; Chunying MA ; Xiaohui LIU ; Yiqun TENG ; Meiyun XIN ; Fei SUN ; Ming LIU ; Ling LU ; Xinping PENG ; Yongxia GUO ; Rong YU ; Quanjing CHEN ; Bin WANG ; Tong SHEN ; Lan LI ; Pingping LIU ; Xiong LI ; Ming LI ; Guilan WANG ; Baoping XU
Chinese Journal of Applied Clinical Pediatrics 2024;39(10):774-779
		                        		
		                        			
		                        			Objective:To evaluate the efficacy and safety of Xiao′er Huangjin Zhike Granules in the treatment of cough caused by acute bronchitis in children, which is defined in TCM terms as a syndrome of phlegm-heat obstructing the lung.Methods:This was a block-randomized, double-blind, placebo-controlled, multicenter clinical trial.From January 2022 to September 2023, 359 children aged 3 to 7 years old diagnosed as acute bronchitis (lung-obstructing phlegm-heat syndrome) were enrolled from 21 participating hospitals and randomly assigned to the experimental group and placebo group in a 3︰1 ratio, and respectively treated with Xiao′er Huangjin Zhike Granules and its matching placebo.Cough resolution/general resolution rate after 7 days of treatment was used as the primary efficacy outcome for both groups.Results:(1)On the seventh day of treatment, the rate of cough disappearance/basically disappearance in the experimental group and placebo group were 73.95% and 57.61% retrospectively, which had statistically significance ( P=0.001).(2)After 7 days of treatment, the median duration of cough disappearance/basic disappearance were 5 days and 6 days in the two groups , with a statistically significant difference ( P=0.006).The area under the curve of cough symptom severity time was 7.20 ± 3.79 in the experimental group and 8.20±4.42 in the placebo group.The difference between the two groups was statistically significant ( P=0.039).(3) After 7 days of treatment, the difference between TCM syndrome score and baseline was -16.0 (-20.0, -15.0) points in the experimental group and -15.0 (-18.0, -12.0) points in the placebo group, with significant difference between the two groups ( P=0.004).In the experimental group, the clinical control rate, the markedly effective rate, the effective rate and the ineffective rate were 49.04%, 28.35%, 16.48% and 6.13% severally; and in the placebo group, the clinical control rate, the markedly effective rate, the effective rate and the ineffective rate were 38.04%, 26.09%, 29.35%, and 6.52% separately, which had statistically significant ( P=0.014).(4) There was no significant difference in the incidence of adverse events or adverse reactions during the trial between both groups.Moreover, while adverse reactions in the form of vomiting and diarrhea were occasionally reported, no serious drug-related adverse event or adverse reaction was reported.(5)The tested drug provided good treatment compliance, showing no statistically significant difference from the placebo in terms of compliance rate. Conclusions:Based on the above findings, it can be concluded that Xiao′er Huangjin Zhike Granules provides good safety, efficacy, and treatment compliance in the treatment of cough caused by acute bronchitis, and lung-obstructing phlegm-heat syndrome, in children.
		                        		
		                        		
		                        		
		                        	
7.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
		                        		
		                        			
		                        			Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
		                        		
		                        		
		                        		
		                        	
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
		                        		
		                        			
		                        			Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
		                        		
		                        		
		                        		
		                        	
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
		                        		
		                        			
		                        			Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
		                        		
		                        		
		                        		
		                        	
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
		                        		
		                        			
		                        			Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
		                        		
		                        		
		                        		
		                        	
            
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