1.National bloodstream infection bacterial resistance surveillance report (2022) : Gram-negative bacteria
Zhiying LIU ; Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(1):42-57
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period,9 035 strains of Gram-negative bacteria were collected from 51 hospitals,of which 7 895(87.4%)were Enterobacteriaceae and 1 140(12.6%)were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli( n=4 510,49.9%), Klebsiella pneumoniae( n=2 340,25.9%), Pseudomonas aeruginosa( n=534,5.9%), Acinetobacter baumannii complex( n=405,4.5%)and Enterobacter cloacae( n=327,3.6%). The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus spp. were 47.1%(2 095/4 452),21.0%(427/2 033)and 41.1%(58/141),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(58/4 510)and 13.1%(307/2 340);62.1%(36/58)and 9.8%(30/307)of CREC and CRKP were resistant to ceftazidime/avibactam combination,respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 59.5%(241/405),while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 18.4%(98/534). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions,with statistically significant differences in the prevalence of CRKP and CRPA( χ2=20.489 and 20.252, P<0.001). The prevalence of CREC,CRKP,CRPA,CRAB,ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals( χ2=11.953,81.183,10.404,5.915,12.415 and 6.459, P<0.01 or <0.05),while the prevalence of CRPA was higher in economically developed regions(per capita GDP ≥ 92 059 Yuan)than that in economically less-developed regions(per capita GDP <92 059 Yuan)( χ2=6.240, P=0.012). Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend,and Escherichia coli is ranked in the top,while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different,and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.
2.National bloodstream infection bacterial resistance surveillance report(2022): Gram-positive bacteria
Chaoqun YING ; Yunbo CHEN ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(2):99-112
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-positive bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-positive bacteria from blood cultures in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:A total of 3 163 strains of Gram-positive pathogens were collected from 51 member units,and the top five bacteria were Staphylococcus aureus( n=1 147,36.3%),coagulase-negative Staphylococci( n=928,29.3%), Enterococcus faecalis( n=369,11.7%), Enterococcus faecium( n=296,9.4%)and alpha-hemolyticus Streptococci( n=192,6.1%). The detection rates of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)were 26.4%(303/1 147)and 66.7%(619/928),respectively. No glycopeptide and daptomycin-resistant Staphylococci were detected. The sensitivity rates of Staphylococcus aureus to cefpirome,rifampin,compound sulfamethoxazole,linezolid,minocycline and tigecycline were all >95.0%. Enterococcus faecium was more prevalent than Enterococcus faecalis. The resistance rates of Enterococcus faecium to vancomycin and teicoplanin were both 0.5%(2/369),and no vancomycin-resistant Enterococcus faecium was detected. The detection rate of MRSA in southern China was significantly lower than that in other regions( χ2=14.578, P=0.002),while the detection rate of MRCNS in northern China was significantly higher than that in other regions( χ2=15.195, P=0.002). The detection rates of MRSA and MRCNS in provincial hospitals were higher than those in municipal hospitals( χ2=13.519 and 12.136, P<0.001). The detection rates of MRSA and MRCNS in economically more advanced regions(per capita GDP≥92 059 Yuan in 2022)were higher than those in economically less advanced regions(per capita GDP<92 059 Yuan)( χ2=9.969 and 7.606, P=0.002和0.006). Conclusions:Among the Gram-positive pathogens causing bloodstream infections in China, Staphylococci is the most common while the MRSA incidence decreases continuously with time;the detection rate of Enterococcus faecium exceeds that of Enterococcus faecalis. The overall prevalence of vancomycin-resistant Enterococci is still at a low level. The composition ratio of Gram-positive pathogens and resistant profiles varies slightly across regions of China,with the prevalence of MRSA and MRCNS being more pronounced in provincial hospitals and areas with a per capita GDP≥92 059 yuan.
3.Identification of subtypes of liver cancer and construction of prognostic model based on necrosis-related genes
Ya-Zhen MAO ; Hong-Quan CHEN ; Yong CHEN ; Yuan-Lin QI
Chinese Journal of Current Advances in General Surgery 2024;27(9):673-677
Objective:To construct and verify a prognostic model based on Necroptosis genes(NEGs)in liver cancer.Methods:Through unsupervised clustering analysis in liver cancer patients from TCGA and ICGC databases,67 NEGs were grouped into two clusters.The differ-ences in prognosis between clusters were explored.Prognosis-related genes were selected through single-factor Cox regression analysis.A prognostic model was built using clustering analy-sis and multi-factor Cox regression,and the model's accuracy and predictive ability were validated.Results:The 67 NEGs were divided into two subtypes,namely NEGclusterA and NEGclusterB.Survival analysis indicated a better prognosis for patients in B compared to A(P<0.05).Single-factor Cox analysis identified 133 prognosis-related genes,further classified into genecluster A and genecluster B,the prognosis of A was better than B(P<0.001).Three genes(SLC1A5,MYBL2,and CFHR3)were determined to construct the prognostic risk scoring model.In both TCGA training and validation cohorts,patients in the high-risk group exhibited poorer prognosis(P<0.05).Conclu-sion:This predictive model can independently forecast the prognosis of liver cancer and provides initial insights into the differences in immune cell infiltration among different liver cancer clusters.
4.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
5.Using machine learning to construct the diagnosis model of female bladder outlet obstruction based on urodynamic study data
Quan ZHOU ; Guang LI ; Kai CUI ; Weilin MAO ; Dongxu LIN ; Zhenglong YANG ; Zhong CHEN ; Youmin HU ; Xin ZHANG
Investigative and Clinical Urology 2024;65(6):559-566
Purpose:
To intelligently diagnose whether there is bladder outlet obstruction (BOO) in female with decent detrusor contraction ability by focusing on urodynamic study (UDS) data.
Materials and Methods:
We retrospectively reviewed the UDS data of female patients during urination. Eleven easily accessible urinary flow indicators were calculated according to the UDS data of each patient during voiding period. Eight diagnosis models based on back propagation neural network with different input feature combination were constructed by analyzing the correlations between indicators and lower urinary tract dysfunction labels. Subsequently, the stability of diagnostic models was evaluated by five-fold cross-validation based on training data, while the performance was compared on test dataset.
Results:
UDS data from 134 female patients with a median age of 51 years (range, 27–78 years) were selected for our study.Among them, 66 patients suffered BOO and the remaining were normal. Applying the 5-fold cross-validation method, the model with the best performance achieved an area under the receiver operating characteristic curve (AUC) value of 0.949±0.060 using 9 UDS input features. The accuracy, sensitivity, and specificity for BOO diagnosis model in the testing process are 94.4%, 100%, and 89.3%, respectively.
Conclusions
The 9 significant indicators in UDS were employed to construct a diagnostic model of female BOO based on machine learning algorithm, which performs preferable classification accuracy and stability.
6.A nomogram for preoperative prediction of lymph node metastasis in patients with intrahepatic cholangiocarcinoma based on inflammation-related markers.
Xiao Peng YU ; Jia Lu CHEN ; Yue TANG ; Chen CHEN ; Ying Hong QIU ; Hong WU ; Tian Qiang SONG ; Yu HE ; Xian Hai MAO ; Wen Long ZHAI ; Zhang Jun CHENG ; Xiao LIANG ; Jing Dong LI ; Chuan Dong SUN ; Kai MA ; Rui Xin LIN ; Zhi Min GENG ; Zhao Hui TANG ; Zhi Wei QUAN
Chinese Journal of Surgery 2023;61(4):321-329
Objectives: To construct a nomogram for prediction of intrahepatic cholangiocarcinoma (ICC) lymph node metastasis based on inflammation-related markers,and to conduct its clinical verification. Methods: Clinical and pathological data of 858 ICC patients who underwent radical resection were retrospectively collected at 10 domestic tertiary hospitals in China from January 2010 to December 2018. Among the 508 patients who underwent lymph node dissection,207 cases had complete variable clinical data for constructing the nomogram,including 84 males,123 females,109 patients≥60 years old,98 patients<60 years old and 69 patients were pathologically diagnosed with positive lymph nodes after surgery. Receiver operating characteristic curve was drawn to calculate the accuracy of preoperative imaging examinations to determine lymph node status,and the difference in overall survival time was compared by Log-rank test. Partial regression squares and statistically significant preoperative variables were screened by backward stepwise regression analysis. R software was applied to construct a nomogram,clinical decision curve and clinical influence curve,and Bootstrap method was used for internal verification. Moreover,retrospectively collecting clinical information of 107 ICC patients with intraoperative lymph node dissection admitted to 9 tertiary hospitals in China from January 2019 to June 2021 was for external verification to verify the accuracy of the nomogram. 80 patients with complete clinical data but without lymph node dissection were divided into lymph node metastasis high-risk group and low-risk group according to the score of the nomogram among the 858 patients. Log-rank test was used to compare the overall survival of patients with or without lymph node metastasis diagnosed by pathology. Results: The area under the curve of preoperative imaging examinations for lymph node status assessment of 440 patients was 0.615,with a false negative rate of 62.8% (113/180) and a false positive rate of 14.2% (37/260). The median survival time of 207 patients used to construct a nomogram with positive or negative postoperative pathological lymph node metastases was 18.5 months and 27.1 months,respectively (P<0.05). Five variables related to lymph node metastasis were screened out by backward stepwise regression analysis,which were combined calculi,neutrophil/lymphocyte ratio,albumin,liver capsule invasion and systemic immune inflammation index,according to which a nomogram was constructed with concordance index(C-index) of 0.737 (95%CI: 0.667 to 0.806). The C-index of external verification was 0.674 (95%CI:0.569 to 0.779). The calibration prediction curve was in good agreement with the reference curve. The results of the clinical decision curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.32,the maximum net benefit could be obtained by 0.11,and the cost/benefit ratio was 1∶2. The results of clinical influence curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.6,the probability of correctly predicting lymph node metastasis could reach more than 90%. There was no significant difference in overall survival time between patients with high/low risk of lymph node metastasis assessed by the nomogram and those with pathologically confirmed lymph node metastasis or without lymph node metastasis (Log-rank test:P=0.082 and 0.510,respectively). Conclusion: The prediction accuracy of preoperative nomogram for ICC lymph node metastasis based on inflammation-related markers is satisfactory,which can be used as a supplementary method for preoperative diagnosis of lymph node metastasis and is helpful for clinicians to make personalized decision of lymph node dissection for patients with ICC.
7.Exploring biological connotation of blood stasis syndrome of rheumatoid arthritis and establishment of improved animal models based on syndrome-symptom mapping
Wen-jia CHEN ; Tao LI ; Ming-zhu XU ; Xun GONG ; Wei-xiang LIU ; Pei-hao LI ; Quan JIANG ; Wei LIU ; Xia MAO ; Xin LI ; Hai-yu XU ; Na LIN ; Yan-qiong ZHANG
Acta Pharmaceutica Sinica 2023;58(8):2434-2441
Blood stasis syndrome is one of the core clinical syndrome of rheumatoid arthritis (RA), but the biological connotation of this syndrome is not clear, and there is a lack of disease improved animal models that match the characteristics of this disease and syndrome. The aim of this study was to screen the candidate biomarker gene set of blood stasis syndrome of RA, reveal the biological connotation of this syndrome, and explore and evaluate the preparation method of the improved animal model based on the characteristics of "disease-syndrome-symptom". The study was approved by the ethics committee of Guang'anmen Hospital, Chinese Academy of Traditional Chinese Medicine (No. 2019-073-KY-01) and the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine (No. TYLL2021[K]018), and the study subjects gave their informed consent. Animal welfare and experimental procedures followed the regulations of the Experimental Animal Ethics Committee of the Chinese Academy of Traditional Chinese Medicine (No. IBTCMCACMS21-2207-01). The whole blood samples were collected clinically from RA patients with blood stasis syndrome (3 cases) or other syndromes (7 types, 3 cases/type), and healthy volunteers (4 cases), and then transcriptome sequencing, KEGG, gene set enrichment analysis (GSEA) and weighted correlation network analysis (WGCNA) analysis were performed. 126 pivotal genes were screened, and their functional annotation results were significantly enriched in "immune-inflammation" related pathways and lipid metabolism regulation (sphingolipids, ether lipid metabolism and steroid biosynthesis). Syndrome-symptom mapping of hub gene set to the TCM primary and secondary symptoms, Western phenotypic symptoms and pathological links showed that joint tingling, abnormal joint morphology, petechiae and abnormal blood circulation are representative of blood stasis syndrome of RA. The results of the improved animal model showed that the rats in the collagen-induced arthritis + adrenaline hydrochloride (CIA+Adr) 3 model group had increased blood rheology, coagulation, platelet function and endothelial function abnormalities compared with the CIA-alone model group, suggesting that the rats with blood stasis syndrome of RA may be in a state of "blood stasis". The results of the study can help to advance the objective study of the evidence of blood stasis syndrome in RA, and provide new ideas for the establishment of an animal model that reflects the clinical characteristics of the disease and syndrome.
8.BRICS report of 2021: The distribution and antimicrobial resistance profile of clinical bacterial isolates from blood stream infections in China
Yunbo CHEN ; Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiliang WANG ; Hui DING ; Haifeng MAO ; Yizheng ZHOU ; Yan JIN ; Yongyun LIU ; Yan GENG ; Yuanyuan DAI ; Hong LU ; Peng ZHANG ; Ying HUANG ; Donghong HUANG ; Xinhua QIANG ; Jilu SHEN ; Hongyun XU ; Fenghong CHEN ; Guolin LIAO ; Dan LIU ; Haixin DONG ; Jiangqin SONG ; Lu WANG ; Junmin CAO ; Lixia ZHANG ; Yanhong LI ; Dijing SONG ; Zhuo LI ; Youdong YIN ; Donghua LIU ; Liang GUO ; Qiang LIU ; Baohua ZHANG ; Rong XU ; Yinqiao DONG ; Shuyan HU ; Kunpeng LIANG ; Bo QUAN ; Lin ZHENG ; Ling MENG ; Liang LUAN ; Jinhua LIANG ; Weiping LIU ; Xuefei HU ; Pengpeng TIAN ; Xiaoping YAN ; Aiyun LI ; Jian LI ; Xiusan XIA ; Xiaoyan QI ; Dengyan QIAO ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2023;16(1):33-47
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical bacterial isolates from bloodstream infections in China in 2021.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2021 to December 2021. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 11 013 bacterial strains were collected from 51 hospitals, of which 2 782 (25.3%) were Gram-positive bacteria and 8 231 (74.7%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.6%), Klebsiella pneumoniae (18.9%), Staphylococcus aureus (9.8%), coagulase-negative Staphylococci (6.3%), Pseudomonas aeruginosa (3.6%), Enterococcus faecium (3.6%), Acinetobacter baumannii (2.8%), Enterococcus faecalis (2.7%), Enterobacter cloacae (2.5%) and Klebsiella spp (2.1%). The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus aureus were 25.3% and 76.8%, respectively. No glycopeptide- and daptomycin-resistant Staphylococci was detected; more than 95.0% of Staphylococcus aureus were sensitive to ceftobiprole. No vancomycin-resistant Enterococci strains were detected. The rates of extended spectrum B-lactamase (ESBL)-producing isolated in Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis were 49.6%, 25.5% and 39.0%, respectively. The prevalence rates of carbapenem-resistance in Escherichia coli and Klebsiella pneumoniae were 2.2% and 15.8%, respectively; 7.9% of carbapenem-resistant Klebsiella pneumoniae was resistant to ceftazidime/avibactam combination. Ceftobiprole demonstrated excellent activity against non-ESBL-producing Escherichia coli and Klebsiella pneumoniae. Aztreonam/avibactam was highly active against carbapenem-resistant Escherichia coli and Klebsiella pneumoniae. The prevalence rate of carbapenem-resistance in Acinetobacter baumannii was 60.0%, while polymyxin and tigecycline showed good activity against Acinetobacter baumannii (5.5% and 4.5%). The prevalence of carbapenem-resistance in Pseudomonas aeruginosa was 18.9%. Conclusions:The BRICS surveillance results in 2021 shows that the main pathogens of blood stream infection in China are gram-negative bacteria, in which Escherichia coli is the most common. The MRSA incidence shows a further decreasing trend in China and the overall prevalence of vancomycin-resistant Enterococci is low. The prevalence of Carbapenem-resistant Klebsiella pneumoniae is still on a high level, but the trend is downwards.
9.Establishment and identification of a mitochondrial tracking system
Lin LYU ; Sihan WANG ; Quan ZENG ; Han DUAN ; Zhuang MAO ; Changyao WANG ; Xuetao PEI ; Hua WANG ; Yanhua LI
Chinese Journal of Pharmacology and Toxicology 2023;37(12):928-935
OBJECTIVE To observe whether mitochondria can be transferred from mesenchymal stem cells(MSCs)to irradiated cells by establishing a mitochondrial fluorescent reporting system.METHODS The lentiviral vector pSIN-EF1α-COX8A-DsRed2(named COX8A-DsRed2)that might guide the expres-sion of red fluorescence protein in the membrane of mitochondria was constructed.A lentivirus(named Lv-COX8A-DsRed2)was prepared in 293T cell line.Dental pulp stem cells(DPSCs)(named DPSC-COX8A-DsRed2)was infected with Lv-COX8A-DsRed2.The intracellular expression of the red fluores-cence protein in DPSC was observed under fluorescence microcopy.The mitochondrial localization of the expressed red fluorescent probe in DPSC-COX8A-DsRed2 was confirmed according to TOMM20 immunostaining and MitoTracker Green staining results,which could specifically label mitochondria.The IEC-6 cells that received 10 Gy X-ray radiation were used as an injured cell model.The co-culture system was established by supplementing DPSC-COX8A-DsRed2 into the culture plate with the irradi-ated IEC-6 labelled by CFSE for 24 h.RESULTS The imaging results of fluorescent microcopy obser-vation showed that DPSC-COX8A-DsRed2 expressed the mitochondrial fluorescent reporting system,which was co-located with TOMM20 protein and Mito Tracker Green.The imaging results of confocal fluorescence microcopy showed that the mitochondria with red fluorescent protein were transferred from DPSC-COX8A-DsRed2 to the irradiated IEC-6 cells,suggesting that the established mitochondrial fluorescent reporting system could indicate mitochondrial transfer from donor cells to injured ones.CONCLUSION DPSC-COX8A-DsRed2 stably expressing the mitochondrial fluorescent reporting system is established,which can be used to track mitochondrial transfer.
10.Improvement of quality standard of Xiaojin capsules
Shuang LIU ; Mao-Quan LIN ; Jing JIN ; Zhi-Jun HUANG ; Yang XIANG ; Gang ZHAO ; Kai-Li MING
China Pharmacist 2023;26(11):332-338
Objective To improve the quality standard of Xiaojin capsules.Methods The agents content of acetyl-11-keto-β-bos wellic acid in Vinegar frankincense was determined by HPLC.According to GC detection patterns of 15 batches of samples,the similarity evaluation was conducted by using the"similarity evaluation system for chromatographic fingerprint of TCM(2012 edition)"of National Pharmacopoeia Committee to confirm common peaks.According to the Chinese Pharmacopoeia method,the contents of Pb,Cd,Cu,As and Hg in samples were detected.Results The linear range of acetyl-11-keto-β-boswellic acid was 13.346-166.824 μg·ml-1(r=0.999 8).The method which possesses high accuracy,and strong specificity,repeatability is good,and the average recovery was 100.76%with an RSD of 1.52%(n=6).The GC fingerprint detection method of Xiaojin capsules was established,and 11 common peaks were identified.The similarity of 15 batches of samples was greater than 0.870,indicating a good similarity.The contents of Pb,Cd,Cu,As and Hg in 15 batches of samples are in accordance with the reference limits in Chinese Pharmacopoeia.Conclusion The GC fingerprint detection method and the HPLC method for the determination of 11-carbonyl-β-acetylboswellic acid,as well as the examination of heavy metals,it can be used as a quality control item for the enhancement of the quality control standards of Xiaojin capsules.

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