1.Finite element model establishment and stress analysis of lumbar-sacral intervertebral disc in ankylosing spondylitis
Zhijie KANG ; Zhenhua CAO ; Yangyang XU ; Yunfeng ZHANG ; Feng JIN ; Baoke SU ; Lidong WANG ; Ling TONG ; Qinghua LIU ; Yuan FANG ; Lirong SHA ; Liang LIANG ; Mengmeng LI ; Yifei DU ; Lin LIN ; Haiyan WANG ; Xiaohe LI ; Zhijun LI
Chinese Journal of Tissue Engineering Research 2024;28(6):840-846
BACKGROUND:Ankylosing spondylitis is a chronic inflammatory disease with chronic rheumatic immunity.Soft tissue ossification and fusion and spinal stiffness can cause biomechanical changes. OBJECTIVE:To reconstruct the lumbar-sacral intervertebral disc in ankylosing spondylitis patients with lumbar kyphosis by finite element analysis,and to study the range of motion of each segment of T11-S1 and the biomechanical characteristics of annulus fibrosus and nucleus pulposus. METHODS:The imaging data were obtained from an ankylosing spondylitis patient with lumbar kyphosis.The original CT image data of continuously scanned spine were imported into Mimics 21.0 in DICOM format,and T11-S1 was reconstructed respectively.The established model was imported into 3-Matic software in the format of"Stl"to reconstruct the intervertebral disc,and the fibrous intervertebral disc model was obtained.The improved model was further imported into Hypermesh software,and the vertebra,nucleus pulposus,annulus fibrosus and ligament were mesh-divided.After the material properties were given,the model was imported into ABAQUS software to observe the range of motion of each vertebral body in seven different working conditions of T11-S1,and analyze the biomechanical characteristics of each segment of annulus fibrosus and nucleus pulposus. RESULTS AND CONCLUSION:(1)The range of motion of L1 vertebrae was higher than that of other vertebrae under six different working conditions:extension,forward flexion,rotation(left and right),and lateral flexion(left and right).The maximum range of motion was 2.18° during L1 vertebral flexion,and the minimum range of motion was 0.12° during L5 vertebral extension.(2)The annular fiber flexion at L2-L3 segments was greater than the extension(P<0.05),and the annular fiber flexion at L3-L4 and L4-L5 segments was less than the extension(P<0.05).The left rotation of L1-L2 annular fibers was greater than the right rotation(P<0.05).The left flexion of the annulus was greater than the right flexion in L1-L2,L2-L3,L3-L4,L4-L5 and L5-S1 segments(P<0.05).(3)The nucleus pulposus stresses of T11-L12,L1-L2,L2-L3,L3-L4 and L4-L5 segments in forward flexion were greater than in extension(P<0.05).The left rotation of T12-L1 and L3-L4 segments was smaller than the right rotation(P<0.05),and that of T11-T12,L1-L2,and L2-L3 segments was larger than the right rotation(P<0.05).The left flexion was larger than the right flexion in the T11-S1 segment.(4)It is concluded that in ankylosing spondylitis patients with lumbar kyphosis,the minimum range of motion of the vertebral body is located at the L5 vertebral body in extension.To prevent fractures,it is recommended to avoid exercise in the extension position.During the onset of lumbar kyphosis in patients with ankylosing spondylitis,the maximum stress of the annulus fibrosus and nucleus pulposus is located in the L1-L2 segment,which is fixed and will not alter with the change of body position.The late surgical treatment and correction of deformity should focus on releasing the pressure of the annulus fibrosus and nucleus pulposus in this segment to avoid the rupture of the annulus fibrosus and the injury of the nucleus pulposus.
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 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.
6.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.
7.Analysis of Characteristics and Risk Factors of Patients with Single Gastric Cancer and Synchronous Multiple Gastric Cancer among 14,603 Patients
Du Hyun SONG ; Nayoung KIM ; Hyeong Ho JO ; Sangbin KIM ; Yonghoon CHOI ; Hyeon Jeong OH ; Hye Seung LEE ; Hyuk YOON ; Cheol Min SHIN ; Young Soo PARK ; Dong Ho LEE ; So Hyun KANG ; Young Suk PARK ; Sang-Hoon AHN ; Yun-Suhk SUH ; Do Joong PARK ; Hyung Ho KIM ; Ji-Won KIM ; Jin Won KIM ; Keun-Wook LEE ; Won CHANG ; Ji Hoon PARK ; Yoon Jin LEE ; Kyoung Ho LEE ; Young Hoon KIM ; Soyeon AHN ; Young-Joon SURH
Gut and Liver 2024;18(2):231-244
Background/Aims:
Synchronous multiple gastric cancer (SMGC) accounts for approximately 6% to 14% of gastric cancer (GC) cases. This study aimed to identify risk factors for SMGC.
Methods:
A total of 14,603 patients diagnosed with GC were prospectively enrolled. Data including age, sex, body mass index, smoking, alcohol consumption, family history, p53 expression, microsatellite instability, cancer classification, lymph node metastasis, and treatment were collected. Risk factors were analyzed using logistic regression analysis between a single GC and SMGC.
Results:
The incidence of SMGC was 4.04%, and that of early GC (EGC) and advanced GC (AGC) was 5.43% and 3.11%, respectively. Patients with SMGC were older (65.33 years vs 61.75 years, p<0.001) and more likely to be male. Lymph node metastasis was found in 27% of patients with SMGC and 32% of patients with single GC. Multivariate analysis showed that SMGC was associated with sex (male odds ratio [OR], 1.669; 95% confidence interval [CI], 1.223 to 2.278; p=0.001), age (≥65 years OR, 1.532; 95% CI, 1.169 to 2.008; p=0.002), and EGC (OR, 1.929; 95% CI, 1.432 to 2.600; p<0.001). Survival rates were affected by Lauren classification, sex, tumor size, cancer type, distant metastasis, and venous invasion but were not related to the number of GCs. However, the survival rate of AGC with SMGC was very high.
Conclusions
SMGC had unique characteristics such as male sex, older age, and EGC, and the survival rate of AGC, in which the intestinal type was much more frequent, was very good (Trial registration number: NCT04973631).
8.The triglyceride glucose index predicts the risk of nonfatal cardio-cerebrovascular disease in the Beijing community: a prospective cohort study
Yuhan WANG ; Hongzhou LIU ; Jin DU ; Li ZANG ; Kang CHEN ; Wenhua YAN ; Qinghua GUO ; Jianming BA ; Weijun GU ; Zhaohui LYU ; Jingtao DOU ; Yiming MU
Chinese Journal of Internal Medicine 2023;62(8):956-963
Objective:To explore the characteristics of the association between the triglyceride glucose (TyG) index and nonfatal cardio-cerebrovascular disease risk in a community population.Method:This was a prospective cohort study. From December 2011 to April 2012, the first investigation was conducted among subjects with more than 40-year old who were from Shijingshan district and Pingguoyuan community in Beijing. The second investigation was conducted from April to October 2015. All the subjects were divided into three groups according to the tertile of the TyG index at baseline. The multivariate Cox proportional risk regression model was established to explore the correlation between the TyG index and nonfatal cardio-cerebrovascular disease risk and the Kaplan-Meier survival curve of the TyG index group was drawn. Subgroup analyses were performed according to age, gender, body mass index, type 2 diabetes mellitus (T2DM), hypertension, and hyperlipidemia to determine the correlation characteristics between the TyG index and nonfatal cardio-cerebrovascular disease among subgroups.Results:A total of 9 577 subjects were finally included to analyze. The mean follow-up time of this study was (34.14±3.84) months. During the follow-up, 363 subjects (3.8%) occurred nonfatal cardio-cerebrovascular disease. The multivariate Cox regression analysis results showed that the hazard ratio ( HR) of nonfatal cardio-cerebrovascular disease in the high TyG index group was 1.54 (95% CI 1.19-1.98), 1.60 (95% CI 1.23-2.10), and 1.57 (95% CI 1.20-2.05) in the three models, compared with the low TyG index group. The Kaplan-Meier analysis showed that the risk of nonfatal cardio-cerebrovascular disease increased from the low-TyG index group to the high-TyG index group ( P=0.015). In the six subgroups analysis, only gender was shown to have a significant interaction effect with the TyG index and nonfatal cardio-cerebrovascular disease risk. In the female population, the risk of nonfatal cardio-cerebrovascular disease is significantly increased with the increase in the TyG index level ( P<0.001). Conclusions:A high TyG index is independently related to the increased risk of nonfatal cardio-cerebrovascular disease in the Beijing community population. Gender has a significant interaction with the TyG index and nonfatal cardio-cerebrovascular disease risk. Therefore, the TyG index may be a useful marker to predict the nonfatal cardio-cerebrovascular disease risk of a community population.
9.Correlation analysis of anterior pituitary hormone and tumor size in patients with pituitary adenomas
Yuepeng WANG ; Yijun LI ; Bing LI ; Li ZANG ; Kang CHEN ; Jin DU ; Jingtao DOU ; Zhaohui LYU ; Weijun GU ; Yiming MU
Chinese Journal of Internal Medicine 2023;62(8):979-986
Objective:To summarize the correlation between anterior pituitary function and tumor size in patients with different hormone-secreting pituitary adenomas.Methods:This was a retrospective case series study. The clinical data of 1 946 patients with pituitary adenoma hospitalized in the First Medical Center of Chinese PLA General Hospital from January 1, 2005, to December 31, 2020, were collected. The correlation between tumor size and anterior pituitary hormone levels was analyzed using Spearman rank correlation analysis in different types of pituitary adenomas.Results:The median age of the 1 946 patients was 45.1 years, of which 857 (44.0%) were men. The maximum tumor diameter of the patients [ M ( Q1, Q3)] was 22 (14, 30) mm. Tumor size in nonfunctioning adenomas ( n=1 191) was negatively correlated with adrenocorticotropic hormone (ACTH) ( r=-0.11, P<0.001), growth hormone ( r=-0.13, P<0.001), and luteinizing hormone (men: r=-0.26, P<0.001, women: r=-0.31, all P<0.001). The tumor size of somatotropic adenomas ( n=297) was positively correlated with growth hormone ( r=0.46, P<0.001), but negatively correlated with male testosterone ( r=-0.41, P<0.001). The tumor size of ACTH-secreting pituitary adenomas ( n=155) was positively correlated with the ACTH level at 8∶00 AM ( r=0.25, P<0.001); however, no correlation was found with cortisol at 8∶00 AM ( P>0.05). The tumor size of prolactinomas ( n=303) was positively correlated with the prolactin level (men: r=0.34, P=0.001; women: r=0.13, P=0.070). Conclusions:The correlation between the function of the anterior pituitary and size of the tumor depends on the cellular origin of the pituitary adenoma and specific type of hormone secretion. In somatotroph adenomas, ACTH-secreting pituitary adenomas, and prolactinomas, there is a positive correlation between tumor size and level of hormones secreted by the corresponding tumors. In patients with nonfunctioning adenomas, the tumor size was negatively correlated with the hormone levels of the pituitary-adrenal and pituitary-growth hormone axes.
10.Genetic Diversity Analysis of Isatis indigotica Germplasm Materials by Chloroplast DNA Variation and ISSR Molecular Marker
Tiantian ZHU ; Tao DU ; Ling JIN ; Fusheng WANG ; Shuqi KANG ; Li XU ; Minghui ZHANG ; He LIN
Chinese Journal of Experimental Traditional Medical Formulae 2022;28(18):117-126
ObjectiveTo analyze the sequence variation and genetic diversity of 47 Isatis indigotica germplasm materials, and carry out the study on the genetic differentiation and structure. MethodGenomic DNA of 47 I. indigotica germplasm materials were extracted by kit extraction method. Two chloroplast DNA (cp DNA) sequences and five inter-simple sequence repeat (ISSR) primers were used for amplification and sequencing. Chromas, Mega 7.0, DanSP5, and GenALEx were used to calibrate, splice, and analyze the sequence characteristics. PERMUT and PopGen 1.31 were used to analyze the genetic diversity parameters and genetic structure, and NTSYS was used to obtain the unweighted pair-group method with arithmetic means(UPGMA) clustering tree plot of 47 I. indigotica germplasm materials. ResultA total of 129 samples from 47 I. indigotica germplasm materials were successfully amplified and sequenced. The length of 2 cp DNA sequences after spliced was 1 412 bp, and there were 377 polymorphic variation loci, and 36 haplotypes. Fu and Li's D* test was significant (P<0.01). The values of Pi, HS, and HT based on cp DNA were 0.119 89, 0.787, and 0.891, respectively. The genetic differentiation coefficients of gene differentiation coefficient(Gst), nucleotide differentiation coefficient(Nst), and fixation index(Fst) were 0.117, 0.468, and 0.488, respectively, and the gene flow (Nm) was 0.615. The mean values of PPB, Shannon information diversity index(I), Nei's genetic diversity index(H), and Gst based on ISSR were 78.85%, 0.334 8, 0.218 6, and 0.754 4, respectively, and the Nm value was 0.162 8. ConclusionI. indigotica has high genetic diversity and abundant haplotypes at the species level, with abundant haplotypes. Genetic differentiation among different germplasm materials is obvious, and gene exchange is not frequent. Genetic variation mainly exists among populations. The population has accumulated various low-frequency gene mutations recently, suggesting that it has experienced significant regional expansion in the history.

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