1.Temporal-spatial Generation of Astrocytes in the Developing Diencephalon.
Wentong HONG ; Pifang GONG ; Xinjie PAN ; Zhonggan REN ; Yitong LIU ; Guibo QI ; Jun-Liszt LI ; Wenzhi SUN ; Woo-Ping GE ; Chun-Li ZHANG ; Shumin DUAN ; Song QIN
Neuroscience Bulletin 2024;40(1):1-16
Astrocytes are the largest glial population in the mammalian brain. However, we have a minimal understanding of astrocyte development, especially fate specification in different regions of the brain. Through lineage tracing of the progenitors of the third ventricle (3V) wall via in-utero electroporation in the embryonic mouse brain, we show the fate specification and migration pattern of astrocytes derived from radial glia along the 3V wall. Unexpectedly, radial glia located in different regions along the 3V wall of the diencephalon produce distinct cell types: radial glia in the upper region produce astrocytes and those in the lower region produce neurons in the diencephalon. With genetic fate mapping analysis, we reveal that the first population of astrocytes appears along the zona incerta in the diencephalon. Astrogenesis occurs at an early time point in the dorsal region relative to that in the ventral region of the developing diencephalon. With transcriptomic analysis of the region-specific 3V wall and lateral ventricle (LV) wall, we identified cohorts of differentially-expressed genes in the dorsal 3V wall compared to the ventral 3V wall and LV wall that may regulate astrogenesis in the dorsal diencephalon. Together, these results demonstrate that the generation of astrocytes shows a spatiotemporal pattern in the developing mouse diencephalon.
Mice
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Animals
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Astrocytes
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Neuroglia/physiology*
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Diencephalon
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Brain
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Neurons
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Mammals
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.Report content and prenatal diagnosis of non-invasive prenatal testing for sex chromosome aneuploidy.
Chun Xiang ZHOU ; Lin Lin HE ; Xiang Yu ZHU ; Zhao Xia LI ; Hong Lei DUAN ; Wei LIU ; Lei Lei GU ; Jie LI
Chinese Journal of Obstetrics and Gynecology 2023;58(10):766-773
Objective: To analyze the report content, the methods and results of prenatal diagnosis of high risk of sex chromosome aneuploidy (SCA) in non-invasive prenatal testing (NIPT). Methods: A total of 227 single pregnancy pregnant women who received genetic counseling and invasive prenatal diagnosis at Drum Tower Hospital Affiliated to the Medical School of Nanjing University from January 2015 to April 2022 due to the high risk of SCA suggested by NIPT were collected. The methods and results of prenatal diagnosis were retrospectively analyzed, and the results of chromosome karyotype analysis and chromosome microarray analysis (CMA) were compared. The relationship between NIPT screening and invasive prenatal diagnosis was analyzed. Results: (1) Prenatal diagnosis methods for 277 SCA high risk pregnant women included 73 cases of karyotyping, 41 cases of CMA and 163 cases of karyotyping combined with CMA, of which one case conducted amniocentesis secondly for further fluorescence in situ hybridization (FISH) testing. Results of invasive prenatal diagnosis were normal in 166 cases (59.9%, 166/277), and the abnormal results including one case of 45,X (0.4%, 1/277), 18 cases of 47,XXX (6.5%, 18/277), 36 cases of 47,XXY (13.0%, 36/277), 20 cases of 47,XYY (7.2%, 20/277), 1 case of 48,XXXX (0.4%, 1/277), 20 cases of mosaic SCA (7.2%, 20/277), 5 cases of sex chromosome structural abnormality or large segment abnormality (1.8%, 5/277), and 10 cases of other abnormalities [3.6%, 10/277; including 9 cases of copy number variation (CNV) and 1 case of balanced translocation]. Positive predictive value (PPV) for SCA screening by NIPT was 34.7% (96/277). (2) Among the 163 cases tested by karyotyping combined with CMA, 11 cases (6.7%, 11/163) showed inconsistent results by both methods, including 5 cases of mosaic SCA, 1 case of additional balanced translocation detected by karyotyping and 5 cases of additional CNV detected by CMA. (3) NIPT screening reports included 149 cases of "sex chromosome aneuploidy"(53.8%, 149/277), 54 cases of "number of sex chromosome increased" (19.5%, 54/277), and 74 cases of "number of sex chromosome or X chromosome decreased" (26.7%, 74/277). The PPV of "number of sex chromosome increased" and "number of sex chromosome or X chromosome decreased" were 72.2% (39/54) and 18.9% (14/74), respectively, and the difference was statistically significant (χ2=34.56, P<0.01). Conclusions: NIPT could be served as an important prenatal screening technique of SCA, especially for trisomy and mosaicism, but the PPV is comparatively low. More information of NIPT such as the specific SCA or maternal SCA might help improving the confidence of genetic counseling and thus guide clinic management. Multi technology platforms including karyotyping, CMA and FISH could be considered in the diagnosis of high risk of SCA by NIPT.
Female
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Pregnancy
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Humans
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Retrospective Studies
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DNA Copy Number Variations
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In Situ Hybridization, Fluorescence
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Aneuploidy
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Prenatal Diagnosis/methods*
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Sex Chromosome Aberrations
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Sex Chromosomes/genetics*
9.Clinical characteristics of children with SARS-CoV-2 Omicron variant infection in Kunming.
Jia Wu YANG ; Chun Hui TANG ; Mei DAI ; Jiang DUAN ; Yan Hong LI ; Jian YANG ; Tao YANG ; Yan GAO ; Deng BAN ; Ji Cai ZHU ; Ting Yun YUAN ; Yin LI ; Hong Min FU
Chinese Journal of Pediatrics 2023;61(10):922-927
Objective: To investigate the clinical characteristics of hospitalized children infected with the Omicron variant in Kunming after the withdrawal of non-pharmaceutical interventions (NPI) and analyze the risk factors of severe cases. Methods: Clinical data was retrospectively collected from 1 145 children with SARS-CoV-2 Omicron infection who were hospitalized in six tertiary grade A hospitals in Kunming from December 10th, 2022 to January 9th, 2023. According to clinical severity, these patients were divided into the general and severe SARS-CoV-2 groups, and their clinical and laboratory data were compared. Between-group comparison was performed using t-test, chi-square test and Mann-Whitney U test. Spearman correlation test and multivariate Logistic regression analysis were used to determine the risk factors of severe illness. Results: A total of 1 145 hospitalized patients were included, of whom 677 were male and 468 female. The age of these patients at visit was 1.7 (0.5, 4.1) years. Specifically, there were 758 patients (66.2%) aged ≤3 years at visit and 387 patients (33.8%) aged >3 years. Of these children, 89 cases (7.8%) had underline diseases and the remaining 1 056 cases (92.2%) had no combined diseases. Additionally, of all the patients, 319 cases (27.9%) were vaccinated with one or two doses of SARS-CoV-2 vaccine, 748 cases (65.3%) had acute upper respiratory tract infection (AURTI), and six cases died (0.5%). A total of 1 051 cases (91.8%) were grouped into general SARS-CoV-2 group and 94 cases (8.2%) were grouped into severe SARS-CoV-2 group. Compared with the general cases, the severe cases showed a lower rate of SARS-CoV-2 vaccination and younger median age, lower lymphocyte count, as well as proportions of CD8+T lymphocyte (36 cases (38.3%) vs. 283 cases (26.9%), 0.5 (2.6, 8.0) vs. 1.6 (0.5, 3.9) years, 1.3 (1.0, 2.7) ×109 vs. 2.7 (1.3,4.4)×109/L, 0.17 (0.12, 0.24) vs. 0.21 (0.15, 0.16), respectively, χ2=4.88, Z=-2.21,-5.03,-2.53, all P<0.05). On the other hand, the length of hospital stay, proportion of underline diseases, ALT, AST, creatine kinase isoenzyme, and troponin T were higher in the severe group compared to those in the general group ((11.6±5.9) vs. (5.3±1.8) d, 41 cases (43.6%) vs. 48 cases (4.6%), 67 (26,120) vs. 20 (15, 32) U/L, 51 (33, 123) vs. 44 (34, 58) U/L、56.9 (23.0, 219.3) vs. 3.6 (1.9, 17.9) U/L, 12.0 (4.9, 56.5) vs. 3.0 (3.0, 7.0) ×10-3 pg/L,respectively, t=-20.43, χ2=183.52, Z=-9.14,-3.12,-6.38,-3.81, all P<0.05). Multivariate regression analysis indicated that increased leukocyte count (OR=1.88, 95%CI 1.18-2.97, P<0.01), CRP (OR=1.18, 95%CI 1.06-1.31, P<0.01), ferritin (OR=1.01, 95%CI 1.00-1.00, P<0.01), interleukin (IL)-6 (OR=1.05, 95%CI 1.01-1.08, P=0.012), D-dimer (OR=2.56, 95%CI 1.44-4.56, P<0.01) and decreased CD4+T lymphocyte (OR=0.84, 95%CI 0.73-0.98, P=0.030) were independently associated with the risk of severe SARS-CoV-2 in hospitalized children with Omicron infection. Conclusions: After the withdrawal of NPI, the pediatric inpatients with Omicron infection in Kunming were predominantly children younger than 3 years of age, and mainly manifested as AURTI with relatively low rate of severe SARS-CoV-2 infection and mortality. Elevated leukocyte counts, CRP, ferritin, IL-6, D-dimer, and decreased CD4+T lymphocytes are significant risk factors for developing severe SARS-CoV-2 infection.
Humans
;
Child
;
Female
;
Male
;
COVID-19
;
COVID-19 Vaccines
;
Retrospective Studies
;
SARS-CoV-2
;
Ferritins
;
Interleukin-6
10.Effect of Baicalin on Pyroptosis of Diffuse Large B-Cell Lymphoma Cell Lines DB and Its Mechanism.
Ming LU ; Chun-Ling HE ; Zhen-Tian WU ; Yao LYU ; Xiao-Hui DUAN ; Bing-Xuan WANG ; Shi-Xiong WANG ; Jian-Hong WANG ; Rong LIANG
Journal of Experimental Hematology 2023;31(6):1706-1713
OBJECTIVE:
To investigate the effect of Baicalin on the proliferation and pyroptosis of diffuse large B-cell lymphoma cell line DB and its mechanism.
METHODS:
DB cells were treated with baicalin at different concentrations (0, 5, 10, 20, 40 μmol/L). Cell proliferation was detected by CCK-8 assay and half maximal inhibitory concentration (IC50) was calculated. The morphology of pyroptosis was observed under an inverted microscope, the integrity of the cell membrane was verified by LDH content release assay, and the expressions of pyroptosis-related mRNA and protein (NLRP3, GSDMD, GSDME, N-GSDMD, N-GSDME) were detected by real-time fluorescence quantitative PCR and Western blot. In order to further clarify the relationship between baicalin-induced pyroptosis and ROS production in DB cells, DB cells were divided into control group, baicalin group, NAC group and NAC combined with baicalin group. DB cells in the NAC group were pretreated with ROS inhibitor N-acetylcysteine (NAC) 2 mmol/L for 2 h. Baicalin was added to the combined treatment group after pretreatment, and the content of reactive oxygen species (ROS) in the cells was detected by DCFH-DA method after 48 hours of culture.
RESULTS:
Baicalin inhibited the proliferation of DB cells in a dose-dependent manner (r=-0.99), and the IC50 was 20.56 μmol/L at 48 h. The morphological changes of pyroptosis in DB cells were observed under inverted microscope. Compared with the control group, the release of LDH in the baicalin group was significantly increased (P<0.01), indicating the loss of cell membrane integrity. Baicalin dose-dependently increased the expression levels of NLRP3, N-GSDMD, and N-GSDME mRNA and protein in the pyroptosis pathway (P<0.05). Compared with the control group, the level of ROS in the baicalin group was significantly increased (P<0.05), and the content of ROS in the NAC group was significantly decreased (P<0.05). Compared with the NAC group, the content of ROS in the NAC + baicalin group was increased. Baicalin significantly attenuated the inhibitory effect of NAC on ROS production (P<0.05). Similarly, Western blot results showed that compared with the control group, the expression levels of pyroptosis-related proteins was increased in the baicalin group (P<0.05). NAC inhibited the expression of NLRP3 and reduced the cleavage of N-GSDMD and N-GSDME (P<0.05). Compared with the NAC group, the NAC + baicalin group had significantly increased expression of pyroptosis-related proteins. These results indicate that baicalin can effectively induce pyroptosis in DB cells and reverse the inhibitory effect of NAC on ROS production.
CONCLUSION
Baicalin can inhibit the proliferation of DLBCL cell line DB, and its mechanism may be through regulating ROS production to affect the pyroptosis pathway.
Humans
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NLR Family, Pyrin Domain-Containing 3 Protein/metabolism*
;
Reactive Oxygen Species/pharmacology*
;
Pyroptosis
;
Cell Line
;
RNA, Messenger
;
Lymphoma, Large B-Cell, Diffuse

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