1.Effect of High-Frequency Stimulation in the Pedunculopontine Nucleus on Neuronal Activity and Neurotransmitters in the Globus Pallidus Internus of Rats
Minjie LIU ; Yuhan LIN ; Yao LI ; Jinju JIAO
Tianjin Medical Journal 2013;(7):682-685
Objective To study the effect of high frequency stimulation (HFS) in pedunculopontine nucleus (PPN) on the neuronal activities of globus pallidus internus (Gpi) in Parkinson’s disease (PD) model rats, and the mechanisms there-of. Methods Seventy male Sprague-Dawley rats were divided into two groups, control group (n=30) and PD model group (n=40). PD rat model was established by the injection of 6-OHDA into substantia nigra pars compacta (SNc) on the right side of the brain with stereotactic technique. Electrophysiological recordings were made in anaesthetized rats to investigate the ef-fects of HFS-PPN on the firing rate of the GPi neurons. Brain microdialysis combined with high-performance liquid chroma-tography was applied to detect glutamate (Glu) andγ-aminobutyric acid (GABA) levels in GPi. Results HFS-PPN caused an excitatory reaction of the majority of neurons recorded in the GPi in PD model group and control group. The mean firing rate of GPi excited neurons was significantly increased (P﹤0.01). The levels of Glu were reduced under HFS-PPN and the levels of GABA were not affected (P>0.05).Conclusion HFS-PPN heightened the electrical activity of GPi neurons and re-duced the level of Glu. These excitatory effects were probably realized by PPN-GPi direct path or other indirect path.
2.Effects of Low-Frequency Stimulation of Pedunculopontine Nucleus on Spontaneous Discharges of Globus Pallidus Internus
Jia GUO ; Yuhan LIN ; Yao LI ; Jinju JIAO
Tianjin Medical Journal 2014;(8):774-777
Objective To explore the mechanism of the low-frequency electrical stimulate on pedunculopontine nu-cleus to treat the Parkinson (PD) through observinge the low-frequency electrical stimulation of Pedunculopontine Nucleus (PPN) in PD rat model and the effects of neurotransmitters (GPi) neurons discharge in the medial part of the globus pallidus. Methods Thirty SD rats were randomly assigned to the control group and the PD model group, with 15 in each group. PD model was established through injecting 6-OHDA into Substantia nigra compact (SNc) of black rat. Effect of low frequency electrical stimulation, micro-electrophoresis glutamate (Glu) and its receptor blocking breaking agent MK-801,γ-aminobu-tyric acid (GABA) and its receptor antagonist bicuculline (BIC) on discharge of rat neuron GPi was examined using extracel-lular unit recording methods through seven glass microelectrode recording. Results When stimulated by low frequency electrical stimulation of PPN, reactions from the control group and neuronal response GPi in PD rats were inhibited. The aver-age discharge frequency was reduced compared to pre-stimulation (P < 0.01). Micro-electrophoresis and BIC Glu excite neurons while microiontophoresis MK-801 and GABA restrain neurons. In the background of micro-electrophoresis BIC’s excitatory effects on neuron, low-frequency electrical stimulation on PPN reduced neuronal firing frequency. And in the background of inhibition effect of micro-electrophoresis MK-801, low-frequency stimulation PPN further restrain neuronal discharge frequency. Conclusion Low frequency electrical stimulation inhibits GPi PPN neuronal activity probably though regulating neurons projecting to the Glu and GABA nerve pathways in GPi neuron.
3.Effects of astragalosides on proliferation and cell cycle of rat glomerular mesangial cells
Jinfang SUN ; Jinju JIAO ; Qiman SONG ; Yuhong BAI
Chinese Journal of Tissue Engineering Research 2007;0(15):-
AIM: To study the effects of astragalosides (AS) on the proliferation and cell cycle of rat glomerular mesangial cell (MC), and verify the correlation between the influence and the AS concentration. METHODS: The experiment was carried out in the Physiological Laboratory of Liaoning Medical University from December 2006 to July 2007. Rat glomerular MCs were cultured in high glucose for 4-7 passages. The experiments were randomly divided into control group and three AS groups with different concentrations (50, 100, 200 mg/L), which were treated with high-glucose liquid and AS respectively. MC proliferation was determined with MTT colorimetric method in each group at hours 48 after intervention. MC cell cycle was detected with flow cytometry. RESULTS: ①MTT results showed that, the values of A490 nm in AS groups were lower than that in the control group at hours 48 (P
4.Correlation study of brain β-amyloid deposition and blood β-amyloid level in Alzheimer′s disease
Fangyang JIAO ; Weiwei LI ; Yanjiang WANG ; Jinju SUN ; Xiao CHEN ; Jianliang WEN ; Rongbing JIN
Chinese Journal of Nuclear Medicine and Molecular Imaging 2021;41(1):6-11
Objective:To assess the β-amyloid (Aβ) deposition of voxel-based PET imaging in Alzheimer′s disease (AD) and its relationships with blood biomarkers (Aβ).Methods:From January 2015 to December 2018, a total of 23 AD patients (9 males, 14 females, age (68.5±9.0) years; duration: (40.9±23.3) months; 8 mild patients, 15 moderate or severe patients) who underwent Aβ PET and with positive imaging results in Daping Hospital, Army Medical University were retrospectively enrolled. The information of Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) were collected. Blood level of Aβ42, Aβ40 were measured. Differences of those metrics including Aβ42/Aβ40 between mild and moderate or severe patients were compared. For all 11C-Pittsburgh compound B (PIB) PET images, voxel-based one-sample independent t test analyses were performed. Voxel-based two-sample independent t test analyses were also performed between mild and moderate or severe patients. The voxel-based Pearson correlation analyses were run to assess the associations between blood metrics and Aβ deposition of 11C-PIB PET. Results:Comparing with mild patients, moderate or severe patients had lower MMSE (9.67±4.37 vs 17.13±2.80; t=4.349, P<0.001) and longer duration ((48.8±23.8) vs (26.0±13.5) months; t=-2.489, P<0.05). On voxel-wise analysis, amyloid PET illustrated brain Aβ deposition in bilateral frontal, right temporal, right occipital and posterior cingulate regions ( t values: 0.44-0.67, all P<0.001). Within AD, Aβ42/Aβ40 ( r values: from -0.62 to -0.41, 0.41-0.66, all P<0.05) were associated with amyloid PET, but not associated with Aβ42 ( r values: from -0.33 to 0, all P>0.05) or Aβ40 ( r values: from -0.41 to 0, all P>0.05). Conclusions:Based on voxel-wise analysis, 11C-PIB PET has comparable value for brain Aβ deposition. Aβ42/Aβ40 has the potential to predict brain Aβ deposition.
5.Diagnostic value and influencing factors of 11C-PIB in mild cognitive impairment and Alzheimer′s disease
Jinju SUN ; Xiao CHEN ; Fangyang JIAO ; Yi LUO ; Jianliang WEN ; Qiming LI ; Rongbing JIN
Chinese Journal of Nuclear Medicine and Molecular Imaging 2021;41(1):12-17
Objective:To investigate the diagnostic value of 11C-Pittsburgh compound B (PIB) in patients with mild cognitive impairment (MCI) and Alzheimer′s disease (AD) and explore the factors that may affect the binding of 11C-PIB. Methods:From January 2017 to December 2019, the 11C-PIB uptake of 6 patients with normal cognitive (NC; 3 males, 3 females, age: (64.5±12.3) years), 11 patients with MCI (4 males, 7 females, age: (64.5±9.8) years) and 21 patients with AD (7 males, 14 females, age: (68.1±9.1) years) from Daping Hospital, Army Medical University were retrospectively analyzed. Regional 11C-PIB binding was assessed by using standardized uptake value ratio (SUVR) and visual reading of 11C-PIB scan. Clinical data, including age, gender, education level, cognitive impairment, neuropsychological scale score, vascular risk factors (VRF), apolipoprotein E (ApoE) gene, were collected and differences among groups were analyzed by using one-way analysis of variance, least significant difference t test or Fisher exact test. Factors that affected the 11C-PIB binding were analyzed by multiple linear regression. Results:SUVR of cerebral lobe among NC, MCI and AD groups were significantly different (range of mean SUVR: 1.16-1.26, 1.19-1.35 and 1.40-1.61; F values: 5.331-9.279, all P<0.05). For positive PIB patients, SUVR of posterior cingulate and precuneus were increased in MCI group compared with NC group (1.20±0.15 vs 1.50±0.12, 1.18±0.15 vs 1.59±0.13; F values: 6.389 and 10.668, t values: -2.33 and -3.10, both P<0.05), and there were no significant differences in all lobes between MCI and AD group ( t values: from -1.29 to -0.51, all P>0.05). Visual analysis showed that the positive rates of PIB in frontal lobe (85.7%(18/21)), posterior cingulate (85.7%(18/21)), precuneus (81.0%(17/21)), temporal lobe (81.0%(17/21)) and occipital lobe (47.6%(10/21)) in AD were higher than those in MCI (4/11, 4/11, 4/11, 3/11 and 1/11, respectively; all P<0.05). Multiple linear regression showed that the degree of cognitive impairment were independent risk factors for SUVR of all lobes ( b values: 0.377-0.536, all P<0.05). The ApoE ε4 gene was independent risk factor for SUVR of precuneus ( b=0.290, P<0.05). Conclusion:11C-PIB is helpful for clinical diagnosis of MCI and AD patients and the degree of cognitive impairment and ApoE ε4 gene may be independent risk factors for increasing 11C-PIB binding.
6. Correlations between striatal dopamine transporter distribution, glucose metabolism and clinical symptoms in Parkinson′s disease
Fangyang JIAO ; Jun TAO ; Jinju SUN ; Haosu ZHANG ; Yi LUO ; Jianliang WEN ; Zhenfan ZHAO ; Zhiqiang XU ; Rongbing JIN
Chinese Journal of Nuclear Medicine and Molecular Imaging 2019;39(6):349-355
Objective:
To investigate the correlations among striatal dopamine transporter (DAT) distribution, glucose metabolism and Parkinson′s disease (PD) clinical symptoms.
Methods:
Twenty-five clinically confirmed idiopathic PD patients (17 males, 8 females, age: (59.8±9.2) years) who underwent 11C-2-beta-carbomethoxy-3-beta-(4-fluorophenyl)tropane (CFT) and 18F-fluorodeoxyglucose (FDG) PET imaging from January 2015 to December 2016 were reviewed. The detailed clinical scores were systematically collected from all patients. Correlations between DAT distribution, glucose metabolism and clinical symptoms were evaluated at global and voxel levels using Pearson correlation analysis.
Results:
There were significantly positive correlations between the PD-related pattern (PDRP) value and unified PD rating scale (UPDRS) motor scores, non-motor symptoms scale (NMSS) scores, activity of daily living scale (ADL) scores (
7.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.
8.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.
9.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.
10.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.