1.Establishment of different pneumonia mouse models suitable for traditional Chinese medicine screening.
Xing-Nan YUE ; Jia-Yin HAN ; Chen PAN ; Yu-Shi ZHANG ; Su-Yan LIU ; Yong ZHAO ; Xiao-Meng ZHANG ; Jing-Wen WU ; Xuan TANG ; Ai-Hua LIANG
China Journal of Chinese Materia Medica 2025;50(15):4089-4099
In this study, lipopolysaccharide(LPS), ovalbumin(OVA), and compound 48/80(C48/80) were administered to establish non-infectious pneumonia models under simulated clinical conditions, and the correlation between their pathological characteristics and traditional Chinese medicine(TCM) syndromes was compared, providing the basis for the selection of appropriate animal models for TCM efficacy evaluation. An acute pneumonia model was established by nasal instillation of LPS combined with intraperitoneal injection for intensive stimulation. Three doses of OVA mixed with aluminum hydroxide adjuvant were injected intraperitoneally on days one, three, and five and OVA was administered via endotracheal drip for excitation on days 14-18 to establish an OVA-induced allergic pneumonia model. A single intravenous injection of three doses of C48/80 was adopted to establish a C48/80-induced pneumonia model. By detecting the changes in peripheral blood leukocyte classification, lung tissue and plasma cytokines, immunoglobulins(Ig), histamine levels, and arachidonic acid metabolites, the multi-dimensional analysis was carried out based on pathological evaluation. The results showed that the three models could cause pulmonary edema, increased wet weight in the lung, and obvious exudative inflammation in lung tissue pathology, especially for LPS. A number of pyrogenic cytokines, inclading interleukin(IL)-6, interferon(IFN)-γ, IL-1β, and IL-4 were significantly elevated in the LPS pneumonia model. Significantly increased levels of prostacyclin analogs such as prostaglandin E2(PGE2) and PGD2, which cause increased vascular permeability, and neutrophils in peripheral blood were significantly elevated. The model could partly reflect the clinical characteristics of phlegm heat accumulating in the lung or dampness toxin obstructing the lung. The OVA model showed that the sensitization mediators IgE and leukotriene E4(LTE4) were increased, and the anti-inflammatory prostacyclin 6-keto-PGF2α was decreased. Immune cells(lymphocytes and monocytes) were decreased, and inflammatory cells(neutrophils and basophils) were increased, reflecting the characteristics of "deficiency", "phlegm", or "dampness". Lymphocytes, monocytes, and basophils were significantly increased in the C48/80 model. The phenotype of the model was that the content of histamine, a large number of prostacyclins(6-keto-PGE1, PGF2α, 15-keto-PGF2α, 6-keto-PGF1α, 13,14-D-15-keto-PGE2, PGD2, PGE2, and PGH2), LTE4, and 5-hydroxyeicosatetraenoic acid(5S-HETE) was significantly increased, and these indicators were associated with vascular expansion and increased vascular permeability. The pyrogenic inflammatory cytokines were not increased. The C48/80 model reflected the characteristics of cold and damp accumulation. In the study, three non-infectious pneumonia models were constructed. The LPS model exhibited neutrophil infiltration and elevated inflammatory factors, which was suitable for the efficacy study of TCM for clearing heat, detoxifying, removing dampness, and eliminating phlegm. The OVA model, which took allergic inflammation as an index, was suitable for the efficacy study of Yiqi Gubiao formulas. The C48/80 model exhibited increased vasoactive substances(histamine, PGs, and LTE4), which was suitable for the efficacy study and evaluation of TCM for warming the lung, dispersing cold, drying dampness, and resolving phlegm. The study provides a theoretical basis for model selection for the efficacy evaluation of TCM in the treatment of pneumonia.
Animals
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Disease Models, Animal
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Mice
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Pneumonia/genetics*
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Medicine, Chinese Traditional
;
Male
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Humans
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Cytokines/immunology*
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Female
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Lipopolysaccharides/adverse effects*
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Lung/drug effects*
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Drugs, Chinese Herbal
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Ovalbumin
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Mice, Inbred BALB C
2.The Influence of COVID-19 Infection on the Mobilization and Collection of Autologous Peripheral Blood Stem Cells in Patients with Multiple Myeloma.
Guo-Rong WANG ; Guang-Zhong YANG ; Yun LENG ; Yin WU ; Ai-Jun LIU ; Wen-Ming CHEN
Journal of Experimental Hematology 2025;33(2):455-462
OBJECTIVE:
To analyze the effect of COVID-19 infection on the mobilization and collection of autologous peripheral blood stem cells in patients with multiple myeloma.
METHODS:
The general baseline data, treatment factors before mobilization collection, collection status, and treatment overview after collection of autologous peripheral blood stem cells at Beijing Chaoyang Hospital affiliated with Capital Medical University from January 1, 2020 to July 15, 2023 were analyzed.
RESULTS:
269 patients underwent mobilization and collection of autologous peripheral blood stem cells. Among them, 32 cases with COVID-19 infection history (COVID-19 group) and 237 cases without COVID-19 infection history (non-COVID-19 group). In the COVID-19 group, 17 cases were treated with chemotherapy (etoposide)+G-CSF, and 15 cases were treated with plerixafor +G-CSF. In the non-COVID-19 group, 214 cases were treated with chemotherapy +G-CSF, 17 cases were treated with plerixafor +G-CSF, and 6 cases were treated with chemotherapy + plerixafor +G-CSF. The number of CD34+ cells, collection success rate, and excellence rate in the COVID-19 group and the non-COVID-19 group were [5.52 (0.94-26.87) vs 4.80 (0.53-37.20)]×106/kg (P =0.610), (93.8% vs 85.2%) (P =0.275), (62.5% vs 49.4%) (P =0.190), respectively. Among 113 patients mobilized with etoposide +G-CSF, the number of CD34+ cells, success rate, and excellence rate collected from COVID-19 infection (17 cases) and non-COVID-19 infection (96 cases) were [7.54 (2.66-26.87) vs 7.78 (2.26-37.20)]×106/kg (P =0.847), (100.0% vs 100.0%) (no P value), (82.4% vs 86.5%) (P =0.655), respectively. Among 32 patients mobilized by plerixafor +G-CSF, the number of CD34+ cells, success rate and excellence rate of COVID-19 infection (15 cases) and non-COVID-19 infection (17 cases) were [3.82 (0.94-7.27) vs 4.11 (0.53-9.05)]×106/kg (P =0.821), (86.7% vs 88.2%) (P =0.893), (40.0% vs 35.3%) (P =0.784), respectively. In 32 patients with COVID-19 infection, the number of CD34+ cells collected by etoposide +G-CSF (17 cases) and plerixafor +G-CSF (15 cases), as well as the success rate and excellence rate were [7.54 (2.66-26.87) vs 3.82(0.94-7.27)]×106/kg (P =0.004), (100.0% vs 86.7%) (P =0.120), (82.4% vs 40.0%) (P =0.014), respectively. By 2023.7.31, 232 patients (86.2%, 232/269) had received transplantation, including 24 patients in the COVID-19 group and 208 patients in the non-COVID-19 group. The median number of CD34+ cells infused in the two groups was [3.67 (2.50-13.44) vs 3.11(1.12-19.89)]×106/kg (P =0.058), the median days of neutrophil engraftment [11(9-13) vs 11(9-17)] (P =0.674), the median days of platelet engraftment [11(0-23), 12(0-43)] (P =0.279), respectively.
CONCLUSION
The history of COVID-19 infection did not affect the PBSC mobilization, collection and transplantation of patients with myeloma. In patients with COVID-19 infection, the results of chemotherapy mobilization with etoposide seems to be better than that of plerixafor mobilization, but further research is needed to clarify.
Humans
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COVID-19/complications*
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Multiple Myeloma/complications*
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Hematopoietic Stem Cell Mobilization
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Transplantation, Autologous
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Granulocyte Colony-Stimulating Factor/therapeutic use*
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Peripheral Blood Stem Cell Transplantation
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SARS-CoV-2
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Middle Aged
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Peripheral Blood Stem Cells
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Male
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Female
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Cyclams
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Benzylamines
3.Spatio-Temporal Pattern and Socio-economic Influencing Factors of Tuberculosis Incidence in Guangdong Province: A Bayesian Spatiotemporal Analysis.
Hui Zhong WU ; Xing LI ; Jia Wen WANG ; Rong Hua JIAN ; Jian Xiong HU ; Yi Jun HU ; Yi Ting XU ; Jianpeng XIAO ; Ai Qiong JIN ; Liang CHEN
Biomedical and Environmental Sciences 2025;38(7):819-828
OBJECTIVE:
To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019.
METHOD:
Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model.
RESULTS:
Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00).
CONCLUSION
The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans
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China/epidemiology*
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Incidence
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Bayes Theorem
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Spatio-Temporal Analysis
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Tuberculosis/epidemiology*
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Socioeconomic Factors
4.Effects of Ganoderma lucidum polysaccharide peptide on proliferation,migration and apoptosis of diffuse large B-cell lymphoma cells by regulating the expression of PRMT6
Hui-Yan HUANG ; Yan-Fang WU ; Ai-Wei WANG ; Gui-Bing ZHANG ; Wen-Zhong SHANG ; Ye SUN
The Chinese Journal of Clinical Pharmacology 2024;40(15):2187-2191
Objective To investigate the effect of Ganoderma lucidum polysaccharide peptide(GLPP)on proliferation,migration and apoptosis of diffuse large B cell lymphoma(DLBCL)cells and its mechanism.Methods OCI-LY19 cells were divided into six groups:control,GLPP,si-NC,si-protein arginine methyltransferase 6(PRMT6),GLPP+pcDNA3.1-NC and GLPP+pcDNA3.1-PRMT6 groups.The si-NC,si-PRMT6,GLPP+pcDNA3.1-NC and GLPP+pcDNA3.1-PRMT6 groups were transfected with si-NC,si-PRMT6,pcDNA3.1-NC and pcDNA3.1-PRMT6,respectively.After the transfection was completed,control,si-NC and si-PRMT6 groups were treated with RPMI-1640 medium,while the GLPP,GLPP+pcDNA3.1-NC and GLPP+pcDNA3.1-PRMT6 groups were cultured with RPMI-1640 medium containing with 20 μg·mL-1 GLPP.After administration 24 h,the cell proliferation inhibition rates,mobility rates and apoptosis rates were detected.The expression levels of PRMT6 protein were measured by Western blotting.Results The cell proliferation inhibition rates of si-NC,si-PRMT6,GLPP+pcDNA3.1-NC and GLPP+pcDNA3.1-PRMT6 groups were(1.28±0.16)%,(38.61±3.29)%,(52.84±7.74)%and(22.75±3.87)%,respectively.The number of cell migrations in the control,GLPP,si-NC,si-PRMT6,GLPP+pcDNA3.1-NC and GLPP+pcDNA3.1-PRMT6 groups was(252.65±24.65),(136.54±16.46),(231.65±21.24),(142.76±15.34),(140.23±9.84)and(192.38±23.38)cells;the apoptosis rates were(4.36±0.52)%,(28.24±2.36)%,(4.23±0.45)%,(24.54±2.27)%,(28.42±3.85)%and(14.25±2.13)%);the expression levels of PRMT6 protein were 1.82±0.21,0.56±0.05,1.78±0.19,0.54±0.05,0.29±0.02 and 0.32±0.03,respectively.The differences of above indexes were statistically significant between control group and GLPP group,between si-NC group and si-PRMT6 group,between GLPP+pcDNA3.1-NC group and GLPP+pcDNA3.1-PRMT6 group(all P<0.05).Conclusion GLPP could inhibit proliferation,migration and promote apoptosis of DLBCL cells by down-regulating PRMT6 expression.
5. Analysis of cerebral gray matter structure in multiple sclerosis and neuromyelitis optica
Xiao-Li LIU ; Ai-Xue WU ; Ru-Hua LI ; An-Ting WU ; Cheng-Chun CHEN ; Lin XU ; Cai-Yun WEN ; Dai-Qian CHEN
Acta Anatomica Sinica 2024;55(1):17-24
Objective The volume and cortical thickness of gray matter in patients with multiple sclerosis (MS) and neuromyelitis optica (NMO) were compared and analyzed by voxel⁃based morphometry (VBM) and surface⁃based morphometry (SBM), and the differences in the structural changes of gray matter in the two diseases were discussed. Methods A total of 21 MS patients, 16 NMO patients and 19 healthy controls were scanned by routine MRI sequence. The data were processed and analyzed by VBM and SBM method based on the statistical parameter tool SPM12 of Matlab2014a platform and the small tool CAT12 under SPM12. Results Compared with the normal control group (NC), after Gaussian random field (GRF) correction, the gray matter volume in MS group was significantly reduced in left superior occipital, left cuneus, left calcarine, left precuneus, left postcentral, left central paracentral lobule, right cuneus, left middle frontal, left superior frontal and left superior medial frontal (P<0. 05). After family wise error (FWE) correction, the thickness of left paracentral, left superiorfrontal and left precuneus cortex in MS group was significantly reduced (P<0. 05). Compared with the NC group, after GRF correction, the gray matter volume in the left postcentral, left precentral, left inferior parietal, right precentral and right middle frontal in NMO group was significantly increased (P<0. 05). In NMO group, the volume of gray matter in left middle occipital, left superior occipital, left inferior temporal, right middle occipital, left superior frontal orbital, right middle cingulum, left anterior cingulum, right angular and left precuneus were significantly decreased (P<0. 05). Brain regions showed no significant differences in cortical thickness between NMO groups after FWE correction. Compared with the NMO group, after GRF correction, the gray matter volume in the right fusiform and right middle frontal in MS group was increased significantly(P<0. 05). In MS group, the gray matter volume of left thalamus, left pallidum, left precentral, left middle frontal, left middle temporal, right pallidum, left inferior parietal and right superior parietal were significantly decreased (P<0. 05). After FWE correction, the thickness of left inferiorparietal, left superiorparietal, left supramarginal, left paracentral, left superiorfrontal and left precuneus cortex in MS group decreased significantly (P<0. 05). Conclusion The atrophy of brain gray matter structure in MS patients mainly involves the left parietal region, while NMO patients are not sensitive to the change of brain gray matter structure. The significant difference in brain gray matter volume between MS patients and NMO patients is mainly located in the deep cerebral nucleus mass.
6.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.
7.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.
8.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.
9.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.
10.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.

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