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.Stakeholder Preference Assessment in Implementation Research: Application of Best-worst Scaling
Run MAO ; Yiyuan CAI ; Wei YANG ; Zhiguo LIU ; Lang LINGHU ; Jiajia CHEN ; Mengjiao LIANG ; Lieyu HUANG ; Siyuan LIU ; Dong XU
Medical Journal of Peking Union Medical College Hospital 2024;16(1):224-234
In the field of healthcare service, it is crucial to optimize medical innovation services by combining the preferences of health service providers and demanders (i.e., stakeholders). The best-worst scaling (BWS) method is a recently developed stated preference method for assessing preferences with distinctive advantages. Nevertheless, there is a lack of a comprehensive introduction to stakeholder preference assessment using BWS, thus constraining its applications and promotion. This paper introduces the process of using BWS to assess service providers' preferences for the Shared Medical Appointment for diabetes (SMART), an integrated healthcare service of medicine and health management, in the hope of providing reference for researchers for promoting the use of BWS in implementation research.
3.Correlation Analysis of Endophytes and Key Secondary Metabolites of Artemisia indica
Mengzhi LI ; Peng LIANG ; Lipeng KANG ; Chao LI ; Kun BAI ; Yanqiu MAO ; Xianzhang HUANG
World Science and Technology-Modernization of Traditional Chinese Medicine 2024;26(8):2175-2186
		                        		
		                        			
		                        			Objective To characterize the temporal dynamics of endophytic community and key metabolites during the growth developmental stages of Artemisia indica and to explore the effects of endophytes on the medicinal material quality of A.indica from the perspective of microorganism combined with the correlation analysis.Methods In this study,high-throughput sequencing was performed to obtain the temporal dynamics of diversity and composition of endophytic community during the growth stages of A.indica.Key metabolites quantitative analysis were performed using high-performance liquid chromatography and ultraviolet spectrophotometry.Spearman's correlation analysis was further conducted to identify the endophytic communities that were significantly correlated with metabolites.Results There were significant differences in the diversity and composition of endophytic communities during the growth stages of A.indica.Linear discriminant analysis efect size(LEfSe)analyses identified some potential microbial biomarkers,such as Firmicutes,Massilia,Pantoea,Alternaria,Didymella,and Trichomerium.The abundances of some genera were significantly and positively correlated with the content of total polyphenols and total flavonoids(P<0.05),such as Curtobacterium,Pantoea,Tilletiopsis,and Dissoconium.The abundances of Pseudozyma,Ralstonia,and Pleospora were significantly and positively correlated with Chlorogenic acid,Isochlorogenic acid B,Isochlorogenic acid A,and Isochlorogenic acid C(P<0.05).Conclusion This work described the distribution of endophytes and key metabolites during the development stages of A.indica.Some endophytic communities with significant correlation of key metabolites were identified,which provided valuable information to guide the isolation of endophytic strains related to key metabolites and improve the quality of A.indica.
		                        		
		                        		
		                        		
		                        	
4.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
		                        		
		                        			
		                        			Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
		                        		
		                        		
		                        		
		                        	
5.A cross-sectional survey on the types of antiviral treatment plans for patients with chronic hepatitis B
Xiulan XUE ; Qianguo MAO ; Qingfa RUAN ; Feng MIN ; Wenqi HUANG ; Xiaoting ZHENG ; Huiqing LIANG
Chinese Journal of Hepatology 2024;32(1):29-34
		                        		
		                        			
		                        			Objective:To understand the current antiviral treatment status and various clinical types of treatment plans in Xiamen City so as to explore ways to improve and optimize the diagnosis and treatment standards for chronic hepatitis B.Methods:A cross-sectional survey method was used to study the antiviral treatment status and treatment plans for chronic hepatitis B patients who visited and were diagnosed in the Department of Infectious Diseases and Hepatology of all tertiary hospitals in Xiamen City at 0:00~23:59 on May 25, 2022.Results:A total of 665 cases were surveyed in this study, with an antiviral treatment rate of 81.2%(540/665). The antiviral treatment rate of patients who accorded with the current guidelines for antiviral treatment indications was 85.8%(507/591). The antiviral treatment rate for 362 outpatients was 72.9%(264/362). Among them, the antiviral treatment rates were 80.1%, 89.3%, and 25.0%(226/282, 25/28, 13/52), respectively, for patients diagnosed with chronic hepatitis B, hepatitis B cirrhosis, and hepatitis B surface antigen-carrying status. The treatment plan for all outpatient patients was mainly oral nucleos(t)ide analogues, accounting for 59.1%(214/362). The antiviral treatment rate for 303 inpatients was 91.1%(276/303). The various clinical types of antiviral therapy rates among all patients were 70%~95%. The antiviral treatment plan for inpatients was mainly based on pegylated interferon alpha treatment, accounting for 72.6%(220/303).Conclusion:Antiviral treatment for chronic hepatitis B in Xiamen City can still be strengthened to meet the current demand for expanding antiviral treatment indications. Antiviral treatment rates and various types of treatment plans differ between outpatients and inpatients; thus, further awareness and acceptance of the goal of improving antiviral therapy, especially in outpatients, and the possibility for a clinical cure based on pegylated interferon alpha treatment are needed to maximize the benefit to more patients.
		                        		
		                        		
		                        		
		                        	
6.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.
		                        		
		                        		
		                        		
		                        	
7.Association Between Exposure to Particulate Matter and the Incidence of Parkinson’s Disease: A Nationwide Cohort Study in Taiwan
Ting-Bin CHEN ; Chih-Sung LIANG ; Ching-Mao CHANG ; Cheng-Chia YANG ; Hwa-Lung YU ; Yuh-Shen WU ; Winn-Jung HUANG ; I-Ju TSAI ; Yuan-Horng YAN ; Cheng-Yu WEI ; Chun-Pai YANG
Journal of Movement Disorders 2024;17(3):313-321
		                        		
		                        			 Objective:
		                        			Emerging evidence suggests that air pollution exposure may increase the risk of Parkinson’s disease (PD). We aimed to investigate the association between exposure to fine particulate matter (PM2.5) and the risk of incident PD nationwide. 
		                        		
		                        			Methods:
		                        			We utilized data from the Taiwan National Health Insurance Research Database, which is spatiotemporally linked with air quality data from the Taiwan Environmental Protection Administration website. The study population consisted of participants who were followed from the index date (January 1, 2005) until the occurrence of PD or the end of the study period (December 31, 2017). Participants who were diagnosed with PD before the index date were excluded. To evaluate the association between exposure to PM2.5 and incident PD risk, we employed Cox regression to estimate the hazard ratio and 95% confidence interval (CI). 
		                        		
		                        			Results:
		                        			A total of 454,583 participants were included, with a mean (standard deviation) age of 63.1 (9.9) years and a male proportion of 50%. Over a mean follow-up period of 11.1 (3.6) years, 4% of the participants (n = 18,862) developed PD. We observed a significant positive association between PM2.5 exposure and the risk of PD, with a hazard ratio of 1.22 (95% CI, 1.20–1.23) per interquartile range increase in exposure (10.17 μg/m3) when adjusting for both SO2 and NO2. 
		                        		
		                        			Conclusion
		                        			We provide further evidence of an association between PM2.5 exposure and the risk of PD. These findings underscore the urgent need for public health policies aimed at reducing ambient air pollution and its potential impact on PD. 
		                        		
		                        		
		                        		
		                        	
8.Expert consensus on antiviral therapy of COVID-19
Fujie ZHANG ; Zhuo WANG ; Quanhong WANG ; Qing MAO ; Jinsong BAI ; Hanhui YE ; Jia TIAN ; Tianxin XIANG ; Jihong AN ; Zujiang YU ; Wenjie YANG ; Xingxiang YANG ; Xiaoju ZHANG ; Jie ZHANG ; Lina ZHANG ; Xingwang LI ; Jiabin LI ; Manxiang LI ; Zhiwei LI ; Hourong ZHOU ; Yi SHI ; Xiaoling XU ; Xiaoping TANG ; Hong TANG ; Xixin YAN ; Wenxiang HUANG ; Chaolin HUANG ; Liang DONG ; Baosong XIE ; Jiandong JIANG ; Bin XIONG ; Xuemei WEI ; Jifang SHENG ; Ronghua JIN
Chinese Journal of Clinical Infectious Diseases 2023;16(1):10-20
		                        		
		                        			
		                        			COVID-19 is caused by a novel coronavirus-severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which has being spreading around the world, posing a serious threat to human health and lives. Neutralizing antibodies and small molecule inhibitors for virus replication cycle are the main antiviral treatment for novel coronavirus recommended in China. To further promote the rational use of antiviral therapy in clinical practice, the National Center for Infectious Diseases (Beijing Ditan Hospital Capital Medical University and the First Affiliated Hospital, Zhejiang University School of Medicine) invited experts in fields of infectious diseases, respiratory and intensive care to develop an Expert Consensus on Antiviral Therapy of COVID-19 based on the Diagnosis and Treatment Guideline for COVID-19 ( trial version 10) and experiences in the diagnosis and treatment of COVID-19 in China. The consensus is concise, practical and highly operable, hopefully it would improve the understanding of antiviral therapy for clinicians and provide suggestions for standardized medication in treatment of COVID-19.
		                        		
		                        		
		                        		
		                        	
9.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.
		                        		
		                        		
		                        		
		                        	
10.Preliminary application of artificial intelligence in the pathological diagnosis of periapical cysts
HAO Yihang ; HUANG Meichang ; LI Mao ; TANG Yaling ; LIANG Xinhua
Journal of Prevention and Treatment for Stomatological Diseases 2023;31(9):641-646
		                        		
		                        			Objective:
		                        			To study the effect of artificial intelligence in the pathological diagnosis of periapical cysts and to explore the application of artificial intelligence in the field of oral pathology.
		                        		
		                        			Methods:
		                        			Pathological images of eighty-seven periapical cysts were selected as subjects to read, and a neural network with a U-net structure was constructed. The 87 HE images and labeled images of periapical cysts were divided into a training set (72 images) and a test set (15 images), which were used in the training model and test model, respectively. Finally, the target level index F1 score, pixel level index Dice coefficient and receiver operating characteristic (ROC) curve were used to evaluate the ability of the U-net model to recognize periapical cyst epithelium.
		                        		
		                        			Results :
		                        			 The F1 score of the U-net network model for recognizing periapical cyst epithelium was 0.75, and the Dice index and the areas under the ROC curve were 0.685 and 0.878, respectively.
		                        		
		                        			Conclusion
		                        			The U-net network model constructed by artificial intelligence has a good segmentation result in identifying periapical cyst epithelium, which can be preliminarily applied in the pathological diagnosis of periapical cysts and is expected to be gradually popularized in clinical practice after further verification with large samples.
		                        		
		                        		
		                        		
		                        	
            

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