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.Mevalonate improves anti-PD-1/PD-L1 efficacy by stabilizing CD274 mRNA.
Wenxin ZHANG ; Xiaohui PAN ; Yanjun XU ; Hongjie GUO ; Mingming ZHENG ; Xi CHEN ; Honghai WU ; Fengming LUAN ; Qiaojun HE ; Ling DING ; Bo YANG
Acta Pharmaceutica Sinica B 2023;13(6):2585-2600
		                        		
		                        			
		                        			Mevalonate metabolism plays an important role in regulating tumor growth and progression; however, its role in immune evasion and immune checkpoint modulation remains unclear. Here, we found that non-small cell lung cancer (NSCLC) patients with higher plasma mevalonate response better to anti-PD-(L)1 therapy, as indicated by prolonged progression-free survival and overall survival. Plasma mevalonate levels were positively correlated with programmed death ligand-1 (PD-L1) expression in tumor tissues. In NSCLC cell lines and patient-derived cells, supplementation of mevalonate significantly up-regulated the expression of PD-L1, whereas deprivation of mevalonate reduced PD-L1 expression. Mevalonate increased CD274 mRNA level but did not affect CD274 transcription. Further, we confirmed that mevalonate improved CD274 mRNA stability. Mevalonate promoted the affinity of the AU-rich element-binding protein HuR to the 3'-UTR regions of CD274 mRNA and thereby stabilized CD274 mRNA. By in vivo study, we further confirmed that mevalonate addition enhanced the anti-tumor effect of anti-PD-L1, increased the infiltration of CD8+ T cells, and improved cytotoxic function of T cells. Collectively, our findings discovered plasma mevalonate levels positively correlated with the therapeutic efficacy of anti-PD-(L)1 antibody, and provided the evidence that mevalonate supplementation could be an immunosensitizer in NSCLC.
		                        		
		                        		
		                        		
		                        	
4.Erratum: Author correction to 'Mevalonate improves anti-PD-1/PD-L1 efficacy by stabilizing CD274 mRNA' Acta Pharmaceutica Sinica B 13 (2023) 2585-2600.
Wenxin ZHANG ; Xiaohui PAN ; Yanjun XU ; Hongjie GUO ; Mingming ZHENG ; Xi CHEN ; Honghai WU ; Fengming LUAN ; Qiaojun HE ; Ling DING ; Bo YANG
Acta Pharmaceutica Sinica B 2023;13(10):4337-4337
		                        		
		                        			
		                        			[This corrects the article DOI: 10.1016/j.apsb.2023.04.002.].
		                        		
		                        		
		                        		
		                        	
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.Predictive value of combination of MRI tumor regression grade and apparent diffusion coefficient for pathological complete remission after neoadjuvant treatment of locally advanced rectal cancer.
Ning XU ; Feng Chang HUANG ; Wen Liang LI ; Xiao LUAN ; Yuan Ming JIANG ; Bo HE
Chinese Journal of Gastrointestinal Surgery 2021;24(4):359-365
		                        		
		                        			
		                        			Objective: Pelvic high-resolution magnetic resonance imaging (MRI) has now become a standard method for evaluating the efficacy of neoadjuvant treatment for locally advanced rectal cancer (LARC). However, this traditional morphological qualitative assessment method based on T2-weighted imaging (T2WI) is not effective in predicting pathological complete remission (pCR). The purpose of this study is to investigate whether combining the magnetic resonance tumor regression grade (mrTRG) with apparent diffusion coefficient (ADC) can improve diagnostic value for pCR after preoperative neoadjuvant chemoradiotherapy (nCRT) of LARC. Methods: This was a diagnostic study. Clinicopathological data of 134 LARC patients who received nCRT and radical surgery in the First Affiliated Hospital of Kunming Medical University from January 2017 to December 2019 were retrospectively analyzed. All the patients underwent MRI which included T2WI and DWI sequences before and 8 weeks after nCRT. Two radiologists independently drew ROIs on T2WI and DWI to estimate mrTRG stage and calculate the mean ADC value. Receiver operating characteristics (ROC) method was applied to evaluate the predict value of mrTRG combined with mean ADC value for pCR. Results: Of 134 LARC patients, 85 were male and 49 were female with median age of 58 (28-82) years. After nCRT, MRI suggested 21 patients (15.7%) had clinical complete remission (cCR), e.g. mrTRG stage 1-2. Postoperative pathology revealed 31 (23.1%) patients had pCR. The evaluations of mrTRG and ADC value by the two readers were highly consistent, and the intra-group correlation coefficients were 0.83 (95% CI: 0.703-0.881) and 0.96 (95% CI: 0.989-0.996), respectively. There was a negative correlation between mrTRG and pCR (r(s)=-0.505, P<0.01), and a positive correlation between mean ADC value and pCR (r(s)=0.693, P<0.01). The ROC curve showed that mrTRG alone had a medium predictive value for pCR, with an area under the curve (AUC) of 0.832 (95% CI: 0.743-0.921); the mean ADC value had a higher predictive value for pCR, with AUC of 0.906 (95% CI: 0.869-0.962). The predictive value of the combined model of mrTRG and ADC value for pCR was significantly better than that of mrTRG alone (P=0.015), and the AUC was 0.908 (95% CI: 0.849-0.968). Conclusion: Both mrTRG and mean ADC value can be non-invasive methods to predict the efficacy of nCRT for LARC. Combining the mean ADC value with mrTRG can result in better pCR prediction.
		                        		
		                        		
		                        		
		                        			Aged
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		                        			Aged, 80 and over
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		                        			Chemoradiotherapy
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		                        			Diffusion Magnetic Resonance Imaging
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		                        			Female
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		                        			Humans
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		                        			Magnetic Resonance Imaging
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		                        			Male
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		                        			Middle Aged
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		                        			Neoadjuvant Therapy
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		                        			Rectal Neoplasms/therapy*
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		                        			Retrospective Studies
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		                        			Treatment Outcome
		                        			
		                        		
		                        	
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.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.
		                        		
		                        		
		                        		
		                        	
9.DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery
Zhu TIANSHENG ; Zhu YI ; Xuan YUE ; Gao HUANHUAN ; Cai XUE ; Piersma R. SANDER ; Pham V. THANG ; Schelfhorst TIM ; Haas R.G.D. RICHARD ; Bijnsdorp V. IRENE ; Sun RUI ; Yue LIANG ; Ruan GUAN ; Zhang QIUSHI ; Hu MO ; Zhou YUE ; Winan J. Van Houdt ; Tessa Y.S. Le Large ; Cloos JACQUELINE ; Wojtuszkiewicz ANNA ; Koppers-Lalic DANIJELA ; B(o)ttger FRANZISKA ; Scheepbouwer CHANTAL ; Brakenhoff H. RUUD ; Geert J.L.H. van Leenders ; Ijzermans N.M. JAN ; Martens W.M. JOHN ; Steenbergen D.M. RENSKE ; Grieken C. NICOLE ; Selvarajan SATHIYAMOORTHY ; Mantoo SANGEETA ; Lee S. SZE ; Yeow J.Y. SERENE ; Alkaff M.F. SYED ; Xiang NAN ; Sun YAOTING ; Yi XIAO ; Dai SHAOZHENG ; Liu WEI ; Lu TIAN ; Wu ZHICHENG ; Liang XIAO ; Wang MAN ; Shao YINGKUAN ; Zheng XI ; Xu KAILUN ; Yang QIN ; Meng YIFAN ; Lu CONG ; Zhu JIANG ; Zheng JIN'E ; Wang BO ; Lou SAI ; Dai YIBEI ; Xu CHAO ; Yu CHENHUAN ; Ying HUAZHONG ; Lim K. TONY ; Wu JIANMIN ; Gao XIAOFEI ; Luan ZHONGZHI ; Teng XIAODONG ; Wu PENG ; Huang SHI'ANG ; Tao ZHIHUA ; Iyer G. NARAYANAN ; Zhou SHUIGENG ; Shao WENGUANG ; Lam HENRY ; Ma DING ; Ji JIAFU ; Kon L. OI ; Zheng SHU ; Aebersold RUEDI ; Jimenez R. CONNIE ; Guo TIANNAN
Genomics, Proteomics & Bioinformatics 2020;18(2):104-119
		                        		
		                        			
		                        			To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.
		                        		
		                        		
		                        		
		                        	
10.Genetic variations and epidemiological characteristics of influenza B virus in Xinxiang from 2012 to 2019
Jian-min MA ; Dong CHENG ; Hua-feng LI ; Xiao-juan SHI ; Xu-bo LUAN ; Dan LIU ; Mei WANG
Chinese Journal of Disease Control & Prevention 2019;23(11):1375-1379
		                        		
		                        			
		                        			 Objective To investigate the genetic variation and epidemiological characteristics of influenza B virus in Xinxiang to provide policy basis for local influenza vaccination. Methods The influenza surveillance data in Xinxiang from January 2012 to February 2019 was analyzed. 23 isolated influenza B virus were randomly selected for hemagglutinin (HA) and neuraminidase (NA) gene sequencing. Sequence alignment was conducted by using DNAman software and phylogenetic tree analysis was conducted using Neighbor-Joining method. Results Yamagata (BY) and Victoria (BV) strains of influenza B virus circulated alternately every other year in Xinxiang, mainly among people aged 0-15 years (91.4%). The dominant influenza B lineages from 2015 to 2016 and from 2017 to 2018 did not match the corresponding trivalent vaccine strain of the year. The HA phylogenetic tree revealed that 87.5% (7/8) of BV strains coexisted with the vaccine strain in one branch, while 88.98% (8/9) of BY strains from 2013 to 2015 were not in the same branch as the corresponding vaccine strain, with 5 epitope site mutions N116K, S150L, N165Y, D196N and N202S. No drug-resistant site mutation was identified in the NA gene. A total of 6 intra-lineage reassortants were identified. Conclusions The influenza B lineage in the trivalent vaccine recommended by WHO did not match the dominant circulating B lineage of Xinxiang in some epidemic year. Therefore, quadrivalent vaccines are recommended to use in susceptible population, especially under the age of 15. In addition, there are large variations in HA gene of the epidemic BY strain compared with the corresponding vaccine. Then, a vaccine more sutable for the epidemic strains in China is expected to be developed. 
		                        		
		                        		
		                        		
		                        	
            
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