1.Research status of chemical constituents,pharmacological effects and predictive analysis of quality markers of Hedyotis diffusa
Ying-Jie WANG ; Hui-Quan HU ; Qian WU ; Jia-Mei ZOU ; Yu-Hui PING
The Chinese Journal of Clinical Pharmacology 2024;40(15):2296-2300
Hedyotis diffusa has unique therapeutic effects on snake and insect bites,edema,cancer and other diseases,and is widely used clinically.However,the《Chinese Pharmacopoeia》has no record of the name of the plant,and there is no fundamental basis for its elaboration of the relationship between"composition-potency-quality marker(Q-Marker)".This article reviews the chemical constituents and pharmacological effects of Hedyotis diffusa,and combined with the concept of Q-Marker.Q-Marker predictions were made in terms of traditional efficacy,traditional medicinal properties and the measurability of chemical components,in order to provide a reference for the clinical applications,quality evaluation further studies of Hedyotis diffusa in the future.
2.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
3.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
4.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
5.Changing resistance profiles of Proteus,Morganella and Providencia in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yunmin XU ; Xiaoxue DONG ; Bin SHAN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Hongyan ZHENG ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(4):410-417
Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10%of the Proteus and Morganella strains were resistant,while less than 20%of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4%in Proteus isolates,1.9%in Morganella isolates,and 15.6%in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.
6.Changing distribution and resistance profiles of Klebsiella strains in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chuyue ZHUO ; Yingyi GUO ; Chao ZHUO ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(4):418-426
Objective To understand the changing distribution and antimicrobial resistance profiles of Klebsiella strains in 52 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Antimicrobial susceptibility testing was carried out according to the unified CHINET protocol.The susceptibility results were interpreted according to the breakpoints in the Clinical & Laboratory Standards Institute(CLSI)M100 document.Results A total of 241,549 nonduplicate Klebsiella strains were isolated from 2015 to 2021,including Klebsiella pneumoniae(88.0%),Klebsiella aerogenes(5.8%),Klebsiella oxytoca(5.7%),and other Klebsiella species(0.6%).Klebsiella strains were mainly isolated from respiratory tract(48.49±5.32)%.Internal medicine(22.79±3.28)%,surgery(17.98±3.10)%,and ICU(14.03±1.39)%were the top 3 departments where Klebsiella strains were most frequently isolated.K.pneumoniae isolates showed higher resistance rate to most antimicrobial agents compared to other Klebsiella species.Klebsiella isolates maintained low resistance rates to tigecycline and polymyxin B.ESBLs-producing K.pneumoniae and K.oxytoca strains showed higher resistance rates to all the antimicrobial agents tested compared to the corresponding ESBLs-nonproducing strains.The K.pneumoniae and carbapenem-resistant K.pneumoniae(CRKP)strains isolated from ICU patients demonstrated higher resistance rates to majority of the antimicrobial agents tested than the strains isolated from non-ICU patients.The CRKP strains isolated from adult patients had higher resistance rates to most of the antimicrobial agents tested than the corresponding CRKP strains isolated from paediatric patients.Conclusions The prevalence of carbapenem-resistant strains in Klebsiella isolates increased greatly from 2015 to 2021.However,the Klebsiella isolates remained highly susceptible to tigecycline and polymyxin B.Antimicrobial resistance surveillance should still be strengthened for Klebsiella strains.
7.Changing resistance profiles of Staphylococcus isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yuling XIAO ; Mei KANG ; Yi XIE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(5):570-580
Objective To investigate the changing distribution and antibiotic resistance profiles of clinical isolates of Staphylococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Staphylococcus according to the unified protocol of CHINET(China Antimicrobial Surveillance Network)using disk diffusion method and commercial automated systems.The CHINET antimicrobial resistance surveillance data from 2015 to 2021 were interpreted according to the 2021 CLSI breakpoints and analyzed using WHONET 5.6.Results During the period from 2015 to 2021,a total of 204,771 nonduplicate strains of Staphylococcus were isolated,including 136,731(66.8%)strains of Staphylococcus aureus and 68,040(33.2%)strains of coagulase-negative Staphylococcus(CNS).The proportions of S.aureus isolates and CNS isolates did not show significant change.S.aureus strains were mainly isolated from respiratory specimens(38.9±5.1)%,wound,pus and secretions(33.6±4.2)%,and blood(11.9±1.5)%.The CNS strains were predominantly isolated from blood(73.6±4.2)%,cerebrospinal fluid(12.1±2.5)%,and pleural effusion and ascites(8.4±2.1)%.S.aureus strains were mainly isolated from the patients in ICU(17.0±7.3)%,outpatient and emergency(11.6±1.7)%,and department of surgery(11.2±0.9)%,whereas CNS strains were primarily isolated from the patients in ICU(32.2±9.7)%,outpatient and emergency(12.8±4.7)%,and department of internal medicine(11.2±1.9)%.The prevalence of methicillin-resistant strains was 32.9%in S.aureus(MRSA)and 74.1%in CNS(MRCNS).Over the 7-year period,the prevalence of MRSA decreased from 42.1%to 29.2%,and the prevalence of MRCNS decreased from 82.1%to 68.2%.MRSA showed higher resistance rates to all the antimicrobial agents tested except trimethoprim-sulfamethoxazole than methicillin-susceptible S.aureus(MSSA).Over the 7-year period,MRSA strains showed decreasing resistance rates to gentamicin,rifampicin,and levofloxacin,MRCNS showed decreasing resistance rates to gentamicin,erythromycin,rifampicin,and trimethoprim-sulfamethoxazole,but increasing resistance rate to levofloxacin.No vancomycin-resistant strains were detected.The prevalence of linezolid-resistant MRCNS increased from 0.2%to 2.3%over the 7-year period.Conclusions Staphylococcus remains the major pathogen among gram-positive bacteria.MRSA and MRCNS were still the principal antibiotic-resistant gram-positive bacteria.No S.aureus isolates were found resistant to vancomycin or linezolid,but linezolid-resistant strains have been detected in MRCNS isolates,which is an issue of concern.
8.Quality of moxa with different leaf-to-moxa ratios based on correlation analysis of thermogravimetric properties, cellulose content, and microscopic characteristics of non-secretory trichomes.
Bing YI ; Li-Ping KANG ; Xin-Yu ZHAO ; Chi ZHANG ; Xin ZOU ; Liu-Jia CHAN ; Hong-Mei LI ; Xian-Zhang HUANG ; Li-Chun ZHAO ; Yuan ZHANG
China Journal of Chinese Materia Medica 2023;48(18):4950-4958
The quality of moxa is a key factor affecting the efficacy of moxibustion. Traditional moxa grades are evaluated by the leaf-to-moxa ratio, but there is a lack of support from scientific data. Scanning electron microscopy(SEM), Image Pro Plus, Van Soest method, and stimultaneous thermal analysis(TGA/DSC) were used to characterize the scientific implication of the combustion differences between moxa with different leaf-to-moxa ratios(processed by crusher). The results showed that the median lengths from non-secretory trichomes(NSTs) of natural NSTs and moxa with leaf-to-moxa ratios of 3∶1, 5∶1, 10∶1, and 15∶1 were 542.46, 303.24, 291.18, 220.69, and 170.61 μm, respectively. The cellulose content of moxa increased significantly(P<0.05) with the increase in leaf-to-moxa ratio and the combustion parameters(T_i, t_i, D_i, C,-R_p,-R_v, S, D_b, and J_(total)) all showed an increasing trend. The correlation results showed that the burning properties of moxa(T_i,-R_v, t_i, and J_2) were significantly and positively correlated with cellulose content. NSTs with a length of 1-200 μm were significantly and positively correlated with J_2. NSTs with a length of 200-600 μm were significantly and positively correlated with J_1, T_(peak2), T_(peak1), and-R_v, and negatively correlated with J_(total), T_b, and t_b. As the leaf-to-moxa ratio increases, the NSTs in the moxa become shorter and the cellulose content increases, which is more conducive to ignition performance, heat release, and a milder, longer-lasting burn. The "NSTs-cellulose-TGA/DSC" quantitative evaluation method scientifically reveals the scientific connotation of the combustion of moxa with different leaf-to-moxa ratios and provides a scientific basis for the establishment of quality evaluation methods for moxa with different leaf-to-moxa ratios.
Trichomes
;
Moxibustion
;
Hot Temperature
;
Plant Leaves
9.Exploration of nanofiltration conditions for separation of alcohol precipitation liquid during preparation of Reduning Injection by Box-Behnken design combined with flux attenuation.
Cun-Yu LI ; Jia-Li JIANG ; Yong-Tuo ZHANG ; Yu-Cen ZOU ; Xing-Lei ZHI ; Guo-Ping PENG
China Journal of Chinese Materia Medica 2022;47(7):1881-1887
This study employed Box-Behnken design combined with flux attenuation to explore the nanofiltration conditions for separation of alcohol precipitation liquid during the preparation of Reduning Injection and discussed the applicability of nanofiltration in the separation of the liquid with high-concentration ethanol. The effects of nanofiltration molecular weight cut-off(MWCO) and pH on the rejection of chlorogenic acid, 3,5-dicaffeoylquinic acid, and 4,5-dicaffeoylquinic acid were consistent with the principles of pore size sieving and charge effect, respectively. The rejection of the three phenolic acids was reduced by concentration polarization effect caused by trans-membrane pressure(TMP). The swelling of membrane surface decreased the pore size and membrane flux for effective separation. Chlorogenic acid and 4,5-dicaffeoylquinic acid were more sensitive to pH and ethanol concentration than 3,5-dicaffeoylquinic acid. A certain correlation existed between the compound structure and the separation factors of nanofiltration, and the separation rules were associated with the comprehensive effect of charge effect, pore size sieving, concentration polarization, steric hindrance and so on.
Chlorogenic Acid
;
Drugs, Chinese Herbal/chemistry*
;
Ethanol
;
Injections
10.Epidemiological characteristics, diagnosis, treatment and prognosis of gallbladder cancer in China: a report of 6 159 cases
Xuheng SUN ; Yijun WANG ; Wei ZHANG ; Yajun GENG ; Yongsheng LI ; Tai REN ; Maolan LI ; Xu'an WANG ; Xiangsong WU ; Wenguang WU ; Wei CHEN ; Tao CHEN ; Min HE ; Hui WANG ; Linhua YANG ; Lu ZOU ; Peng PU ; Mingjie YANG ; Zhaonan LIU ; Wenqi TAO ; Jiayi FENG ; Ziheng JIA ; Zhiyuan ZHENG ; Lijing ZHONG ; Yuanying QIAN ; Ping DONG ; Xuefeng WANG ; Jun GU ; Lianxin LIU ; Yeben QIAN ; Jianfeng GU ; Yong LIU ; Yunfu CUI ; Bei SUN ; Bing LI ; Chenghao SHAO ; Xiaoqing JIANG ; Qiang MA ; Jinfang ZHENG ; Changjun LIU ; Hong CAO ; Xiaoliang CHEN ; Qiyun LI ; Lin WANG ; Kunhua WANG ; Lei ZHANG ; Linhui ZHENG ; Chunfu ZHU ; Hongyu CAI ; Jingyu CAO ; Haihong ZHU ; Jun LIU ; Xueyi DANG ; Jiansheng LIU ; Xueli ZHANG ; Junming XU ; Zhewei FEI ; Xiaoping YANG ; Jiahua YANG ; Zaiyang ZHANG ; Xulin WANG ; Yi WANG ; Jihui HAO ; Qiyu ZHANG ; Huihan JIN ; Chang LIU ; Wei HAN ; Jun YAN ; Buqiang WU ; Chaoliu DAI ; Wencai LYU ; Zhiwei QUAN ; Shuyou PENG ; Wei GONG ; Yingbin LIU
Chinese Journal of Digestive Surgery 2022;21(1):114-128
Objective:To investigate the epidemiological characteristics, diagnosis, treat-ment and prognosis of gallbladder cancer in China from 2010 to 2017.Methods:The single disease retrospective registration cohort study was conducted. Based on the concept of the real world study, the clinicopathological data, from multicenter retrospective clinical data database of gallbladder cancer of Chinese Research Group of Gallbladder Cancer (CRGGC), of 6 159 patients with gallbladder cancer who were admitted to 42 hospitals from January 2010 to December 2017 were collected. Observation indicators: (1) case resources; (2) age and sex distribution; (3) diagnosis; (4) surgical treatment and prognosis; (5) multimodality therapy and prognosis. The follow-up data of the 42 hospitals were collected and analyzed by the CRGGC. The main outcome indicator was the overall survival time from date of operation for surgical patients or date of diagnosis for non-surgical patients to the end of outcome event or the last follow-up. Measurement data with normal distribu-tion were represented as Mean±SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3) or M(range), and com-parison between groups was conducted using the U test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. Univariate analysis was performed using the Logistic forced regression model, and variables with P<0.1 in the univariate analysis were included for multivariate analysis. Multivariate analysis was performed using the Logistic stepwise regression model. The life table method was used to calculate survival rates and the Kaplan-Meier method was used to draw survival curves. Log-rank test was used for survival analysis. Results:(1) Case resources: of the 42 hospitals, there were 35 class A of tertiary hospitals and 7 class B of tertiary hospitals, 16 hospitals with high admission of gallbladder cancer and 26 hospitals with low admission of gallbladder cancer, respectively. Geographical distribution of the 42 hospitals: there were 9 hospitals in central China, 5 hospitals in northeast China, 22 hospitals in eastern China and 6 hospitals in western China. Geographical distribution of the 6 159 patients: there were 2 154 cases(34.973%) from central China, 705 cases(11.447%) from northeast China, 1 969 cases(31.969%) from eastern China and 1 331 cases(21.611%) from western China. The total average number of cases undergoing diagnosis and treatment in hospitals of the 6 159 patients was 18.3±4.5 per year, in which the average number of cases undergoing diagnosis and treatment in hospitals of 4 974 patients(80.760%) from hospitals with high admission of gallbladder cancer was 38.8±8.9 per year and the average number of cases undergoing diagnosis and treatment in hospitals of 1 185 patients(19.240%) from hospitals with low admission of gallbladder cancer was 5.7±1.9 per year. (2) Age and sex distribution: the age of 6 159 patients diagnosed as gallbladder cancer was 64(56,71) years, in which the age of 2 247 male patients(36.483%) diagnosed as gallbladder cancer was 64(58,71)years and the age of 3 912 female patients(63.517%) diagnosed as gallbladder cancer was 63(55,71)years. The sex ratio of female to male was 1.74:1. Of 6 159 patients, 3 886 cases(63.095%) were diagnosed as gallbladder cancer at 56 to 75 years old. There was a significant difference on age at diagnosis between male and female patients ( Z=-3.99, P<0.001). (3) Diagnosis: of 6 159 patients, 2 503 cases(40.640%) were initially diagnosed as gallbladder cancer and 3 656 cases(59.360%) were initially diagnosed as non-gallbladder cancer. There were 2 110 patients(34.259%) not undergoing surgical treatment, of which 200 cases(9.479%) were initially diagnosed as gallbladder cancer and 1 910 cases(90.521%) were initially diagnosed as non-gallbladder cancer. There were 4 049 patients(65.741%) undergoing surgical treatment, of which 2 303 cases(56.878%) were initially diagnosed as gallbladder cancer and 1 746 cases(43.122%) were initial diagnosed as non-gallbladder cancer. Of the 1 746 patients who were initially diagnosed as non-gallbladder cancer, there were 774 cases(19.116%) diagnosed as gallbladder cancer during operation and 972 cases(24.006%) diagnosed as gallbladder cancer after operation. Of 6 159 patients, there were 2 521 cases(40.932%), 2 335 cases(37.912%) and 1 114 cases(18.087%) undergoing ultrasound, computed tomography (CT) or magnetic resonance imaging (MRI) examination before initial diagnosis, respec-tively, and there were 3 259 cases(52.914%), 3 172 cases(51.502%) and 4 016 cases(65.205%) undergoing serum carcinoembryonic antigen, CA19-9 or CA125 examination before initially diagnosis, respectively. One patient may underwent multiple examinations. Results of univariate analysis showed that geographical distribution of hospitals (eastern China or western China), age ≥72 years, gallbladder cancer annual admission of hospitals, whether undergoing ultrasound, CT, MRI, serum carcinoembryonic antigen, CA19-9 or CA125 examination before initially diagnosis were related factors influencing initial diagnosis of gallbladder cancer patients ( odds ratio=1.45, 1.98, 0.69, 0.68, 2.43, 0.41, 1.63, 0.41, 0.39, 0.42, 95% confidence interval as 1.21-1.74, 1.64-2.40, 0.59-0.80, 0.60-0.78, 2.19-2.70, 0.37-0.45, 1.43-1.86, 0.37-0.45, 0.35-0.43, 0.38-0.47, P<0.05). Results of multivariate analysis showed that geographical distribution of hospitals (eastern China or western China), sex, age ≥72 years, gallbladder cancer annual admission of hospitals and cases undergoing ultrasound, CT, serum CA19-9 examination before initially diagnosis were indepen-dent influencing factors influencing initial diagnosis of gallbladder cancer patients ( odds ratio=1.36, 1.42, 0.89, 0.67, 1.85, 1.56, 1.57, 0.39, 95% confidence interval as 1.13-1.64, 1.16-1.73, 0.79-0.99, 0.57-0.78, 1.60-2.14, 1.38-1.77, 1.38-1.79, 0.35-0.43, P<0.05). (4) Surgical treatment and prognosis. Of the 4 049 patients undergoing surgical treatment, there were 2 447 cases(60.435%) with complete pathological staging data and follow-up data. Cases with pathological staging as stage 0, stage Ⅰ, stage Ⅱ, stage Ⅲa, stage Ⅲb, stage Ⅳa and stage Ⅳb were 85(3.474%), 201(8.214%), 71(2.902%), 890(36.371%), 382(15.611%), 33(1.348%) and 785(32.080%), respectively. The median follow-up time and median postoperative overall survival time of the 2 447 cases were 55.75 months (95% confidence interval as 52.78-58.35) and 23.46 months (95% confidence interval as 21.23-25.71), respectively. There was a significant difference in the overall survival between cases with pathological staging as stage 0, stage Ⅰ, stage Ⅱ, stage Ⅲa, stage Ⅲb, stage Ⅳa and stage Ⅳb ( χ2=512.47, P<0.001). Of the 4 049 patients undergoing surgical treatment, there were 2 988 cases(73.796%) with resectable tumor, 177 cases(4.371%) with unresectable tumor and 884 cases(21.833%) with tumor unassessable for resectabi-lity. Of the 2 988 cases with resectable tumor, there were 2 036 cases(68.139%) undergoing radical resection, 504 cases(16.867%) undergoing non-radical resection and 448 cases(14.994%) with operation unassessable for curative effect. Of the 2 447 cases with complete pathological staging data and follow-up data who underwent surgical treatment, there were 53 cases(2.166%) with unresectable tumor, 300 cases(12.260%) with resectable tumor and receiving non-radical resection, 1 441 cases(58.888%) with resectable tumor and receiving radical resection, 653 cases(26.686%) with resectable tumor and receiving operation unassessable for curative effect. There were 733 cases not undergoing surgical treatment with complete pathological staging data and follow-up data. There was a significant difference in the overall survival between cases not undergoing surgical treatment, cases undergoing surgical treatment for unresectable tumor, cases undergoing non-radical resection for resectable tumor and cases undergoing radical resection for resectable tumor ( χ2=121.04, P<0.001). (5) Multimodality therapy and prognosis: of 6 159 patients, there were 541 cases(8.784%) under-going postoperative adjuvant chemotherapy and advanced chemotherapy, 76 cases(1.234%) under-going radiotherapy. There were 1 170 advanced gallbladder cancer (pathological staging ≥stage Ⅲa) patients undergoing radical resection, including 126 cases(10.769%) with post-operative adjuvant chemotherapy and 1 044 cases(89.231%) without postoperative adjuvant chemo-therapy. There was no significant difference in the overall survival between cases with post-operative adjuvant chemotherapy and cases without postoperative adjuvant chemotherapy ( χ2=0.23, P=0.629). There were 658 patients with pathological staging as stage Ⅲa who underwent radical resection, including 66 cases(10.030%) with postoperative adjuvant chemotherapy and 592 cases(89.970%) without postoperative adjuvant chemotherapy. There was no significant difference in the overall survival between cases with postoperative adjuvant chemotherapy and cases without postoperative adjuvant chemotherapy ( χ2=0.05, P=0.817). There were 512 patients with pathological staging ≥stage Ⅲb who underwent radical resection, including 60 cases(11.719%) with postoperative adjuvant chemotherapy and 452 cases(88.281%) without postoperative adjuvant chemotherapy. There was no significant difference in the overall survival between cases with postoperative adjuvant chemo-therapy and cases without post-operative adjuvant chemo-therapy ( χ2=1.50, P=0.220). Conclusions:There are more women than men with gallbladder cancer in China and more than half of patients are diagnosed at the age of 56 to 75 years. Cases undergoing ultrasound, CT, serum CA19-9 examination before initial diagnosis are independent influencing factors influencing initial diagnosis of gallbladder cancer patients. Preoperative resectability evaluation can improve the therapy strategy and patient prognosis. Adjuvant chemotherapy for gallbladder cancer is not standardized and in low proportion in China.

Result Analysis
Print
Save
E-mail