1.The Relationship of Transcription Factor BRF1 Expression to Tumor and Cardiomyopathy
Li-Ling ZHENG ; Yong-Luan LIN ; Mei-Ling CHEN ; Zheng-Yan ZHONG ; Shuping ZHONG
Progress in Biochemistry and Biophysics 2025;52(9):2241-2251
TFIIB-related factor 1 (BRF1) is an important transcription factor. It specifically regulates the transcription of RNA polymerase III-dependent genes (RNA Pol III genes). The products of these genes are some small non-coding RNAs, including transfer RNAs (tRNAs) and 5S ribosomal RNAs (5S rRNA). The transcription levels of tRNAs and 5S rRNA vary with changes in intracellular BRF1 amounts. tRNAs and 5S rRNA play a crucial role in determining protein synthesis. Studies have demonstrated that dysregulation of tRNAs and 5S rRNA is closely related to cell growth, proliferation, transformation, and even tumorigenesis. BRF1 is a key factor determining the generation of tRNAs and 5S rRNA. Increasing BRF1 expression enhances cell proliferation and transformation, promoting tumor development. In contrast, repressing BRF1 activity decreases the rates of cell proliferation and transformation, and inhibits tumor growth. High levels of BRF1 are found in the samples of patients suffering from hepatocellular carcinoma, breast cancer, gastric carcinoma, lung cancer, prostate carcinoma, and other cancers. It indicates that high levels of BRF1 are closely related to the occurrence of human cancer and may be a common landmark of tumors. But there is discrepancy in the regulatory mechanisms and signaling pathways of BRF1 overexpression in different cancers. In general, high levels of BRF1 in patients suffering from cancer show short survival period and poor prognosis. However, there is one exception, namely breast cancer. Approximate 80% of cases of breast cancer are estrogen receptor-positive (ER+) and 20% are ER-. The cases with high levels of BRF1 reveal longer survival period and better prognosis after they accepted the hormone treatment by Tamoxifen (Tam), compared to the cases with low level BRF1. It seems like a contradiction. Most of the cases with high levels of BRF1 belong to ER+ status. Tam has been used to treat ER+ cases of breast cancer after diagnosis and surgery. Thus, hormone therapy, such as Tam, is more effective on these patients. This is because, on one hand, that Tam competes with E2 (17β-estradiol) to bind to estrogen receptor α (ERα), but does not dissociate to occupy the receptors, blocking E2 binding to this receptor and inhibiting its biological effects. On other hand, Tam can inhibit the expression of BRF1, leading to a decline of intracellular BRF1 levels. Therefore, the actual levels of BRF1 are lower in the patients with ER+ breast cancer. It appears the prognosis of the high BRF1 expression cases better than that of the low BRF1 expression cases. Myocardial hypertrophy manifests magnification of cardiomyocyte volume rather than number increasing in the postnatal heart. Myocardial hypertrophy is a critical risk factor underlying cardiovascular diseases. No matter how myocardial hypertrophy occur, it will ultimately lead to myocardial dysfunction and heart failure. Hypertrophic growth of cardiomyocytes requires a large amount of protein synthesis to meet its needs of cardiomyocyte growth. Animal models and cell experiments have shown that myocardial hypertrophy stimulates a significant increase in BRF1 expression and transcription of tRNAs and 5S rRNA. Interestingly, elevated levels of BRF1 are found in the myocardium tissues of patients with myocardial hypertrophy. These studies demonstrate that BRF1 indeed plays a critical role in myocardial hypertrophy. In summary, high levels of BRF1 are found in patients suffering from different cancers and myocardial hypertrophy. It implies that BRF1 is a promising biological target of cancer and cardiomyopathy. BRF1 is expected to become a common biomarker for early diagnosis and prognostic observation of different human cancers. It is also an important biomarker for the diagnosis and treatment of cardiomyopathy. BRF1 not only holds an important position in the field of basic medical research but also has great prospects for translational medicine. In the present article, we summarize the progress on studies of BRF1 expressions in cancer and cardiomyopathy, proposes future research directions. It is a new research area. Here, we emphasize the significancy of BRF overexpression in the two huge diseases of human, cancer and cardiomyopathy to raise people's attention to this field.
2.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.
3.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.
4.Quantitative Detection of Procalcitonin in Blood by Nanozyme-based Lateral Flow Immunoassay
Yue ZHENG ; Tong LIN ; Yong-Hua XIONG ; Meng-Shuo XU ; Xi-Luan YAN ; Xu-Jing GUO ; Lei YANG ; Liang GUO
Chinese Journal of Analytical Chemistry 2024;52(8):1082-1093
A rapid quantitative immunochromatographic assay for procalcitonin(PCT)using metal-organic frameworks modified with gold and platinum nanoparticles(MAPs)as labels was established in this work.The detection probe was prepared by conjugating MAPs with anti-PCT monoclonal antibody via an electrostatic adsorption method.Anti-PCT polyclonal antibody and sheep anti-mouse IgG were sprayed onto the nitrocellulose(NC)membrane as the test line and quality control line,respectively,to construct immunochromatographic strip for PCT quantitative detection via signal-amplification-based sandwich immunoassay.The results showed that the MAP-based immunochromatographic test had high sensitivity,high specificity,and good stability.The dynamic range for detection of PCT was 0.61 pg/mL-320 ng/mL,the detection limit was 0.25 pg/mL,and the intra-day and inter-day precision(Relative standard deviation)were less than 15%.The results of real sample analysis showed that a quite low volume of sample was required for detection of PCT in whole blood,which was of great significance for the early diagnosis,monitoring and treatment,and prognosis of inflammation.
5.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.
6.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.
7.BRICS report of 2018-2019: the distribution and antimicrobial resistance profile of clinical isolates from blood culture in China
Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Peipei WANG ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Hui DING ; Yongyun LIU ; Haifeng MAO ; Ying HUANG ; Zhenghai YANG ; Yuanyuan DAI ; Guolin LIAO ; Lisha ZHU ; Liping ZHANG ; Yanhong LI ; Hongyun XU ; Junmin CAO ; Baohua ZHANG ; Liang GUO ; Haixin DONG ; Shuyan HU ; Sijin MAN ; Lu WANG ; Zhixiang LIAO ; Rong XU ; Dan LIU ; Yan JIN ; Yizheng ZHOU ; Yiqun LIAO ; Fenghong CHEN ; Beiqing GU ; Jiliang WANG ; Jinhua LIANG ; Lin ZHENG ; Aiyun LI ; Jilu SHEN ; Yinqiao DONG ; Lixia ZHANG ; Hongxia HU ; Bo QUAN ; Wencheng ZHU ; Kunpeng LIANG ; Qiang LIU ; Shifu WANG ; Xiaoping YAN ; Jiangbang KANG ; Xiusan XIA ; Lan MA ; Li SUN ; Liang LUAN ; Jianzhong WANG ; Zhuo LI ; Dengyan QIAO ; Lin ZHANG ; Lanjuan LI ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2021;14(1):32-45
Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2018 to December 2019. Antibiotic susceptibility tests were conducted with agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 14 778 bacterial strains were collected from 50 hospitals, of which 4 117 (27.9%) were Gram-positive bacteria and 10 661(72.1%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.2%), Klebsiella pneumoniae (17.0%), Staphylococcus aureus (9.7%), coagulase-negative Staphylococci (8.7%), Pseudomonas aeruginosa (3.7%), Enterococcus faecium (3.4%), Acinetobacter baumannii(3.4%), Enterobacter cloacae (2.9%), Streptococci(2.8%) and Enterococcus faecalis (2.3%). The the prevalence of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus were 27.4% (394/1 438) and 70.4% (905/1 285), respectively. No glycopeptide-resistant Staphylococcus was detected. More than 95% of S. aureus were sensitive to amikacin, rifampicin and SMZco. The resistance rate of E. faecium to vancomycin was 0.4% (2/504), and no vancomycin-resistant E. faecalis was detected. The ESBLs-producing rates in no carbapenem-resistance E. coli, carbapenem sensitive K. pneumoniae and Proteus were 50.4% (2 731/5 415), 24.6% (493/2001) and 35.2% (31/88), respectively. The prevalence of carbapenem-resistance in E. coli and K. pneumoniae were 1.5% (85/5 500), 20.6% (518/2 519), respectively. 8.3% (27/325) of carbapenem-resistance K. pneumoniae was resistant to ceftazidime/avibactam combination. The resistance rates of A. baumannii to polymyxin and tigecycline were 2.8% (14/501) and 3.4% (17/501) respectively, and that of P. aeruginosa to carbapenem were 18.9% (103/546). Conclusions:The surveillance results from 2018 to 2019 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while E. coli was the most common pathogen, and ESBLs-producing strains were in majority; the MRSA incidence is getting lower in China; carbapenem-resistant E. coli keeps at a low level, while carbapenem-resistant K. pneumoniae is on the rise obviously.
8.BRICS report of 2020: The bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China
Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Yuanyuan DAI ; Jiliang WANG ; Haifeng MAO ; Hui DING ; Yongyun LIU ; Yizheng ZHOU ; Hong LU ; Youdong YIN ; Yan JIN ; Hongyun XU ; Lixia ZHANG ; Lu WANG ; Haixin DONG ; Zhenghai YANG ; Fenghong CHEN ; Donghong HUANG ; Guolin LIAO ; Pengpeng TIAN ; Dan LIU ; Yan GENG ; Sijin MAN ; Baohua ZHANG ; Ying HUANG ; Liang GUO ; Junmin CAO ; Beiqing GU ; Yanhong LI ; Hongxia HU ; Liang LUAN ; Shuyan HU ; Lin ZHENG ; Aiyun LI ; Rong XU ; Kunpeng LIANG ; Zhuo LI ; Donghua LIU ; Bo QUAN ; Qiang LIU ; Jilu SHEN ; Yiqun LIAO ; Hai CHEN ; Qingqing BAI ; Xiusan XIA ; Shifu WANG ; Jinhua LIANG ; Liping ZHANG ; Yinqiao DONG ; Xiaoyan QI ; Jianzhong WANG ; Xuefei HU ; Xiaoping YAN ; Dengyan QIAO ; Ling MENG ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2021;14(6):413-426
Objective:To investigate the bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China.Methods:The clinical bacterial strains isolated from blood culture were collected during January 2020 to December 2020 in member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS). Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical Laboratory Standards Institute(CLSI, USA). WHONET 5.6 was used to analyze data.Results:During the study period, 10 043 bacterial strains were collected from 54 hospitals, of which 2 664 (26.5%) were Gram-positive bacteria and 7 379 (73.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (38.6%), Klebsiella pneumoniae (18.4%), Staphylococcus aureus (9.9%), coagulase-negative Staphylococci (7.5%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.3%), Enterobacter cloacae (2.8%), Enterococcus faecalis (2.6%), Acinetobacter baumannii (2.4%) and Klebsiella spp (1.8%). The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus aureus were 27.6% and 74.4%, respectively. No glycopeptide- and daptomycin-resistant Staphylococci were detected. More than 95% of Staphylococcus aureus were sensitive to rifampicin and SMZco. No vancomycin-resistant Enterococci strains were detected. Extended spectrum β-lactamase (ESBL) producing Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis were 48.4%, 23.6% and 36.1%, respectively. The prevalence rates of carbapenem-resistance in Escherichia coli and Klebsiella pneumoniae were 2.3% and 16.1%, respectively; 9.6% of carbapenem-resistant Klebsiella pneumoniae strains were resistant to ceftazidime/avibactam combination. The prevalence rate of carbapenem-resistance in Acinetobacter baumannii was 60.0%, while polymyxin and tigecycline showed good activity against Acinetobacter baumannii. The prevalence rate of carbapenem-resistance of Pseudomonas aeruginosa was 23.2%. Conclusions:The surveillance results in 2020 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen, and ESBL-producing strains declined while carbapenem-resistant Klebsiella pneumoniae kept on high level. The proportion and the prevalence of carbapenem-resistant Pseudomonas aeruginosa were on the rise slowly. On the other side, the MRSA incidence got lower in China, while the overall prevalence of vancomycin-resistant Enterococci was low.
9.Neutrophil to lymphocyte ratio at admission predicts in-hospital mortality risk in patients with acute ischemic stroke
Yan ZHAO ; Hong LUAN ; Jun ZHENG ; Yingying DIAO
International Journal of Cerebrovascular Diseases 2019;27(7):485-490
Objective To investigate the predictive value of neutrophil to lymphocyte ratio (NLR) at admission for mortality risk during hospitalization in patients with acute ischemic stroke (AIS). Methods Patients with AIS admitted to the Department of Neurology, the First Affiliated Hospital of China Medical University from January 2017 to December 2018 were enrolled retrospectively. The demographic data and all baseline clinical data were collected, and compared between the in-hospital death group and survival group. Multivariate logistic regression analysis was used to determine independent influencing factors for in-hospital death in patients with AIS. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of NLR for death during hospitalization. Results A total of 266 patients with AIS were enrolled, with an average age of 65 years, 168 were males (63.2% ), 98 were females (36.8% ), 52 died in hospital (19.5% ), and 214 (80.5% ) survived. The NLR of the death group was significantly higher than that of the survival group (median [ interquartile range]: 7.6 [4.6-14.0] vs. 2.4 [1.8-4.0]; Z=7.727, P<0.001). Multivariate logistic regression analysis showed that advanced age (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.01-1.14; P=0.009), previous history of stroke or transient ischemic attack (OR 9.06, 95% CI 2.06-39.88; P=0.004), high NIHSS score (OR 1.13, 95% CI 1.04-1.24; P=0.004), and high NLR (OR 1.23, 95% CI 1.02-1.48; P=0.024) were the independent risk factors for death during hospitalization in patients with AIS. ROC curve analysis showed that the area under the curve of NLR predicting death during hospitalization for patients with AIS was 0.846 (95% CI 0.786-0.905; P<0.001). When the cut-off value of NLR was 4.52, the sensitivity and specificity were 76.9% and 80.8% respectively. The positive predictive value was 49.4% , and the negative predictive value was 93.5% . Conclusions The increased NLR level at admission had certain predictive value for the death of patients with AIS during hospitalization.
10. Role of the Ubi-p 63E gene in the germline stem cell niche of the Drosophila testis
Mei-yun ZHOU ; Qian-wen ZHENG ; Xiao-jin LUAN ; Yi-dan YAN ; Wan-yin CHEN ; Min WANG ; Bing XIE ; Chen QIAO ; Jie FANG ; Jun YU ; Xia CHEN
Journal of Medical Postgraduates 2019;32(4):346-351
Objective Whether the

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