1.Effect of Dictamni Cortex on Intestinal Barrier Damage by Untargeted Metabolomics and Targeted Metabolomics for Short-chain Fatty Acids
Xiaomin XU ; Donghua YU ; Yu WANG ; Pingping CHEN ; Jiameixue WO ; Suxia JIA ; Wenkai HU ; Fang LU ; Shumin LIU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(20):40-47
ObjectiveThis study aims to investigate the effect of Dictamni Cortex on intestinal barrier damage in rats and its mechanism by untargeted metabolomics and targeted metabolomics for short-chain fatty acids (SCFAs). MethodsRats were randomly divided into a control group, a high-dose group of Dictamni Cortex (8.1 g·kg-1), a medium-dose group (2.7 g·kg-1), and a low-dose group (0.9 g·kg-1). Except for the control group, the other groups were administered different doses of Dictamni Cortex by gavage for eight consecutive weeks. Hematoxylin-eosin (HE) staining was used to observe the pathological changes in the ileal tissue. Enzyme-linked immunosorbent assay (ELISA) was employed to detect the level of cytokines, including tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β), in the ileal tissue of rats. Quantitative real-time fluorescence polymerase chain reaction (Real-time PCR) technology was used to detect the expression level of tight junction proteins, including zonula occludens-1 (ZO-1), Occludin, and Claudin-1 mRNAs, in the ileal tissue of rats to preliminarily explore the effects of Dictamni Cortex on intestinal damage. The dose with the most significant toxic phenotype was selected to further reveal the effects of Dictamni Cortex on the metabolic profile of ileal tissue in rats by non-targeted metabolomics combined with targeted metabolomics for SCFAs. ResultsCompared with the control group, all doses of Dictamni Cortex induced varying degrees of pathological damage in the ileum, increased TNF-α (P<0.01), IL-6 (P<0.01), and IL-1β (P<0.01) levels in the ileal tissue, and decreased the expression level of ZO-1 (P<0.05, P<0.01), Occludin (P<0.01), and Claudin-1 (P<0.05) in the ileal tissue, with the high-dose group showing the most significant toxic phenotypes. The damage mechanisms of the high-dose group of Dictamni Cortex on the ileal tissue were further explored by integrating non-targeted metabolomics and targeted metabolomics for SCFAs. The non-targeted metabolomics results showed that 21 differential metabolites were identified in the control group and the high-dose group. Compared with that in the control group, after Dictamni Cortex intervention, the level of 14 metabolites was significantly increased (P<0.05, P<0.01), and the level of seven metabolites was significantly decreased (P<0.05, P<0.01) in the ileal contents. These metabolites collectively acted on 10 related metabolic pathways, including glycerophospholipids and primary bile acid biosynthesis. The quantitative data of targeted metabolomics for SCFAs showed that Dictamni Cortex intervention disrupted the level of propionic acid, butyric acid, acetic acid, caproic acid, isobutyric acid, isovaleric acid, valeric acid, and isocaproic acid in the ileal contents of rats. Compared with those in the control group, the level of isobutyric acid, isovaleric acid, and valeric acid were significantly increased, while the level of propionic acid, butyric acid, and acetic acid were significantly decreased in the ileal contents of rats after Dictamni Cortex intervention (P<0.05, P<0.01). ConclusionDictamni Cortex can induce intestinal damage by regulating glycerophospholipid metabolism, primary bile acid biosynthesis, and metabolic pathways for SCFAs.
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.Incidence and risk factors of postoperative delirium in liver transplantation recipients: a Meta-analysis
Xu HU ; Fangzheng JIANG ; Baiqiang LI ; Donghua ZHANG ; Tao JIANG ; Ying ZUO ; Jiajie TANG ; Guizhu LIU ; Fang WANG
Chinese Journal of Organ Transplantation 2023;44(6):346-353
Objective:To clarify the incidence and the related risk factors of postoperative delirium in liver transplantation (LT) recipients to provide rationales for early identification of delirium and constructing the related models.Methods:The authors used the "肝移植""移植术""肝移植手术""肝脏移植""移植肝""谵妄""谵语""危险因素""相关因素""影响因素"and "liver transplantation""liver transplant""delirium""delirious""delirium confusion""risk factors""relevant factors""root cause analysis"as the Chinese and English keywords, searching Wanfang data, China Biomedical Literature Database, CNKI, PubMed, Embase, Web of Science, Cochrane Library, BMJ and the literature for the incidence or risk factors of postoperative delirium in LT recipients. The researchers independently performed literature screening, methodological evaluation and data extraction. And RevMan 5.4 and State16.0 software were employed for data processing.Results:A total of 19 articles involving 5003 samples were retrieved and 22 risk factors identifies. Meta-analysis showed that the incidence of POD was 23%(1151/5003). The statistically significant risk factors included preoperative blood ammonia concentration >46 mmol/L ( OR=3.51, 95% CI: 1.53-8.09, P<0.001), model for end-stage liver disease (MELD) score >15 points ( OR=4.24, 95% CI: 2.51-7.16, P<0.001), preoperative hepatic encephalopathy ( OR=3.00, 95% CI: 2.09-4.31, P<0.001), preoperative dosing of diuretics ( OR=2.36, 95% CI: 1.38-4.04, P<0.001), history of alcoholism ( OR=3.16, 95% CI: 1.06-9.40, P=0.040), longer anhepatic period ( OR=1.04, 95% CI: 1.03-1.06, P<0.001) and elevated aspartate transaminase concentration at Day 1 post-operation ( OR=1.33, 95% CI: 1.15-1.53, P<0.001). Conclusions:Preoperative blood ammonia concentration >46 mmol/L, MELD score >15, hepatic encephalopathy, dosing of diuretic, a history of alcoholism, longer anhepatic period and elevated aspartate transaminase at Day 1 post-operation are risk factors for postoperative delirium after LT. Postoperative reintubation is not a risk factor for postoperative delirium.
5.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.
6.Clinical study of central nervous system complications associated with hematopoietic stem cell transplantation
Tonglin HU ; Zhen SHANG ; Yang CAO ; Yicheng ZHANG ; Fankai MENG ; Yang YANG ; Jue WANG ; Donghua ZHANG ; Linjing LAI ; Shan LIU ; Hangping GE ; Yi XIAO
Chinese Journal of Organ Transplantation 2023;44(11):675-681
Objective:To explore the risk factors and outcomes of central nervous system(CNS)complications associated with hematopoietic stem cell transplantation(HSCT).Methods:A total of 550 recipient after HSCT in the department of hematology of Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology from January 1 2019 to August 31 2021were enrolled.According to the occurrence of CNS complications, they were divided into the CNS group(24 cases)and the non CNS group(526 cases). The clinical information and prognosis were compared.We further analyzed the risk factors associated with CNS complications, and conducted multivariate logistic regression on statistically significant indicators.Cox regression analysis is conducted on prognostic factors such as age, gender and risk degree.Results:A total of 550 recipients were enrolled, of which 330 underwent allo-HSCT, and others received auto-HSCT.A total of 24 cases (4.36%)had CNS complications, of which 4 cases had 2 types of CNS complications.The type of CNS complications included intracranial infection(8 cases, 28.57%), transplantation-associated thrombotic microangiopathy(TA-TMA)(6 cases, 21.43%), central tumor invasion(4 cases, 14.29%), intracranial hemorrhage(4 cases, 14.29%), leucodystrophy(2 cases, 7.14%)and unexplained encephalopathy(4 cases, 14.29%). Logistic regression analysis of risk factors related to CNS complications showed that, Platelet implantation time( β=0.084, OR=1.088, P=0.048), CMV infection( β=1.295, OR=3.65, P=0.008)is positively correlated with the occurrence of CNS complications in HSCT recipients but age( β=-0.052, OR=0.949, P=0.004)is negatively correlated with it.Nine of the 24 cases(37.50%)who experienced CNS complications died, including 3 cases of intracranial infection, 3 cases of cerebral hemorrhage, 2 cases of TMA, and 1 case of unexplained encephalopathy.Platelet implantation time is an independent risk factor for poor prognosis of CNS complications in HSCT recipients. Conclusions:Our results indicated that, age, CMV infection and platelet implantation time were associated with the occurrence of CNS complications after HSCT.Platelet implantation time is an independent risk factor for poor prognosis of CNS complications in HSCT recipients.
7.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.
8.hsa-miR-124-3p.1 inhibits the migration and invasion of human gastric cancer cells by targeting TRAF6
Zhenggui TAO ; Jinghu DU ; Kui TIAN ; Donghua WANG ; Fengqi HU ; Manyu CHEN
Journal of Xi'an Jiaotong University(Medical Sciences) 2021;42(6):843-849
【Objective】 To observe the effects of hsa-miR-124-3p.1 in inhibiting epithelial-mesenchymal transition (EMT), migration and invasion of human gastric cancer cells induced by transforming growth factor β1 (TGF-β1) by targeting tumor necrosis factor receptor-associated factor 6 (TRAF6). 【Methods】 A total of 43 gastric cancer tissues and 43 normal para-carcinoma tissues were collected. The human gastric mucosal epithelial cells GES-1 and gastric cancer cells (NCI-N87, MGC-803, BGC-823, SGC-7901, and MKN-45) were cultured. The expressions of miR-124-3p.1 and TRAF6 in tissues and cells were detected by fluorescent quantitative PCR and Western blotting. The targeted relationship between miR-124-3p.1 and TRAF6 was verified by dual-luciferase reporter gene system assay. SGC-7901 cell lines with miR-124-3p.1 and TRAF6 overexpression were constructed. The cells were induced by TGF-β1. The invasion and migration abilities of the cells were evaluated by Transwell chamber assay and scratch test. 【Results】 Compared with normal para-carcinoma tissues and normal gastric mucosal cells, the expression of miR-124-3p.1 was downregulated, while the expressions of TRAF6 mRNA and protein were upregulated in gastric cancer tissues and cells (P<0.05). Compared with control group, expression of E-cadherin in cells was downregulated, expressions of N-cadherin and Vimentin were upregulated, invasion and migration rates of cells were increased in TGF-β1 group (P<0.05). Compared with TGF-β1 group, after cells were transfected with miR-124-3p.1 mimic, the expression of E-cadherin was upregulated, the expressions of N-cadherin and Vimentin were down-regulated, and invasion and migration rates of cells were decreased (P<0.05). Compared with miR-124-3p.1 mimic group, invasion and migration rates of cells were increased in TGF-β1+mimic+TRAF6 group, expressions of TRAF6, N-cadherin and Vimentin were up-regulated, and the expression of E-cadherin was down-regulated (P<0.05). 【Conclusion】 hsa-miR-124-3p.1 is lowly expressed in gastric cancer. Overexpression of miR-124-33p.1 can inhibit EMT, cell invasion and migration induced by TGF-β1. And the action mechanism may be related to the downregulated expression of TRAF6.
9. Comparison of two epidemic patterns of COVID-19 and evaluation of prevention and control effectiveness: an analysis based on Guangzhou and Wenzhou
Guanhao HE ; Zuhua RONG ; Jianxiong HU ; Tao LIU ; Jianpeng XIAO ; Lingchuan GUO ; Weilin ZENG ; Zhihua ZHU ; Dexin GONG ; Lihua YIN ; Donghua WAN ; Junle WU ; Min KANG ; Tie SONG ; Jianfeng HE ; Wenjun MA
Chinese Journal of Epidemiology 2020;41(0):E035-E035
Objective To compare the epidemiological characteristics of COVID-19 in Guangzhou and Wenzhou, and evaluate the effectiveness of their prevention and control measures. Methods Data of COVID-19 cases reported in Guangzhou and Wenzhou as of 29 February, 2020 were collected. The incidence curves of COVID-19 in two cities were constructed. The real time reproduction number ( R t ) of COVID-19 in two cities was calculated respectively. Results A total of 346 and 465 confirmed COVID-19 cases were analysed in Guangzhou and Wenzhou, respectively. In two cities, most cases were aged 30-59 years (Guangzhou: 54.9%; Wenzhou: 70.3%). The incidence curve peaked on 27 January, 2020 in Guangzhou and on 26 January, 2020 in Wenzhou, then began to decline in both cities. The peaks of imported COVID-19 cases from Hubei occurred earlier than the peak of COVID-19 incidences in two cities, and the peak of imported cases from Hubei occurred earlier in Wenzhou than in Guangzhou. In early epidemic phase, imported cases were predominant in both cities, then the number of local cases increased and gradually took the dominance in Wenzhou. In Guangzhou, the imported cases was still predominant. Despite the different epidemic pattern, the R t and the number of COVID-19 cases declined after strict prevention and control measures were taken in Guangzhou and in Wenzhou. Conclusion The time and scale specific differences of imported COVID-19 resulted in different epidemic patterns in two cities, but the spread of the disease were effectively controlled after taking strict prevention and control measures.
10. Risk assessment and early warning of imported COVID-19 in 21 cities, Guangdong province
Jianxiong HU ; Tao LIU ; Jianpeng XIAO ; Guanhao HE ; Zuhua RONG ; Lihua YIN ; Donghua WAN ; Weilin ZENG ; Dexin GONG ; Lingchuan GUO ; Zhihua ZHU ; Lilian ZENG ; Min KANG ; Tie SONG ; Haojie ZHONG ; Jianfeng HE ; Limei SUN ; Yan LI ; Wenjun MA
Chinese Journal of Epidemiology 2020;41(5):658-662
Objective To assess the imported risk of COVID-19 in Guangdong province and its cities, and conduct early warning. Methods Data of reported COVID-19 cases and Baidu Migration Index of 21 cities in Guangdong province and other provinces of China as of February 25, 2020 were collected. The imported risk index of each city in Guangdong province were calculated, and then correlation analysis was performed between reported cases and the imported risk index to identify lag time. Finally, we classified the early warming levels of epidemic by imported risk index. Results A total of 1 347 confirmed cases were reported in Guangdong province, and 90.0% of the cases were clustered in the Pearl River Delta region. The average daily imported risk index of Guangdong was 44.03. Among the imported risk sources of each city, the highest risk of almost all cities came from Hubei province, except for Zhanjiang from Hainan province. In addition, the neighboring provinces of Guangdong province also had a greater impact. The correlation between the imported risk index with a lag of 4 days and the daily reported cases was the strongest (correlation coefficient: 0.73). The early warning base on cumulative 4-day risk of each city showed that Dongguan, Shenzhen, Zhongshan, Guangzhou, Foshan and Huizhou have high imported risks in the next 4 days, with imported risk indexes of 38.85, 21.59, 11.67, 11.25, 6.19 and 5.92, and the highest risk still comes from Hubei province. Conclusions Cities with a large number of migrants in Guangdong province have a higher risk of import. Hubei province and neighboring provinces in Guangdong province are the main source of the imported risk. Each city must strengthen the health management of migrants in high-risk provinces and reduce the imported risk of Guangdong province.

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