1.The mechanism of SAP overexpression in alleviating periodontitis in mice
HUANG Yinyin ; LIANG Dongliang ; ZOU Yaokun ; HAN Jingru ; GE Qing ; LIU Xueyan ; GUO Yadong ; HUANG Xinli ; YANG Lan
Journal of Prevention and Treatment for Stomatological Diseases 2025;33(8):619-630
Objective:
To investigate the mechanism by which serum amyloid P component (SAP) alleviates periodontitis in mice, providing an experimental basis to establish SAP as a novel therapeutic agent for periodontitis.
Methods:
Ethical approval was obtained from the Institutional Animal Ethics Committee. Periodontitis models were established in wild-type (WT) mice and SAP-transgenic (SAP-Tg) mice, divided into four groups: WT control (WT group), WT periodontitis (WT+P group), SAP-Tg control (Tg group), and SAP-Tg periodontitis (Tg+P group). On day 7, the mice were euthanized, and periodontal tissues, teeth, and alveolar bone were collected. SAP protein expression was detected by enzyme-linked immunosorbent assay (ELISA). Micro-CT and HE staining were used to measure alveolar bone resorption (distance from the cementoenamel junction to the alveolar bone crest). Tartrate-resistant acid phosphatase (TRAP) staining was performed to assess osteoclast number, and immunohistochemistry (IHC) was employed to evaluate macrophage infiltration. The expression levels of inflammatory cytokines including interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were measured by qRT-PCR. Oral microorganism composition was analyzed using 16S ribosomal RNA (16S rRNA) gene sequencing. Additionally, macrophages from WT and SAP-Tg mice were isolated to establish an in vitro inflammation model, divided into WT+LPS and Tg+LPS groups. The expression of macrophage polarization-related genes including inducible nitric oxide synthase (iNOS), CD86, CD163, and CD206) were assessed by qRT-PCR. After the induction of osteoclast differentiation, TRAP staining was performed.
Results:
ELISA results demonstrated that periodontal tissues from Tg+P group mice exhibited higher levels of SAP expression compared to the WT+P group. Micro-CT and HE staining analyses revealed that the Tg+P group showed reduced alveolar bone resorption, indicated by a shorter distance between the cementoenamel junction and alveolar bone crest, compared to the WT+P group. Furthermore, TRAP staining results indicated a decrease in osteoclast numbers in the Tg+P group compared to the WT+P group. IHC and qRT-PCR results indicated reduced macrophage infiltration and decreased expression of IL-1β, IL-6, and TNF-α in the Tg+P group. Oral microorganism sequencing showed no significant difference in periodontitis-associated pathogenic bacteria between WT+P and Tg+P groups. In vitro experiments demonstrated that compared to the WT+LPS group, the Tg+LPS group exhibited downregulated M1 macrophage markers (iNOS and CD86) and upregulated M2 macrophage markers (CD163 and CD206). TRAP staining confirmed fewer osteoclasts in the Tg+LPS group.
Conclusion
SAP overexpression effectively alleviates periodontitis severity in mice by inhibiting M1 macrophage polarization, reducing pro-inflammatory cytokine expression, and suppressing osteoclast differentiation, thereby attenuating alveolar bone resorption.
2.Disparities in unexpected antibody distribution and clinical features by frequency of cross-matching incompatibility
Danli CUI ; Bujin LIU ; Haiman ZOU ; Pengwei YIN ; Yun QING ; Huayou DAI ; Siqi WU ; Junhong YANG ; Xia HUANG
Chinese Journal of Blood Transfusion 2025;38(8):1063-1070
Objective: To investigate the clinical characteristics, the types of unexpected antibodies, and their impacts on immunological risks among patients with different frequencies of cross-matching incompatibility, so as to propose corresponding solutions. Methods: Data of cross-matching incompatibility samples from 92 medical institutions during 2022 to 2024 were collected and divided into three groups based on the frequency of cross-matching. Statistical analysis was performed on disease types, distribution of hematologic diseases, alloantibody detection rates, and proportions of alloantibody types. Results: The 858 patients were divided into three groups based on the frequency of blood cross-matching incompatibility: ≥5 times (8.28%, 71/858), 2 to 4 times (28.21%, 242/858); 1 time (63.52%, 545/858). There was a clustered distribution of disease types in the ≥5 cross-matchings group, with 71.83% (51/71) of patients having tumors or hematologic and hematopoietic diseases. In contrast, the disease types in the 2 to 4 cross-matchings and 1 cross-matching groups were more diverse. An analysis of 249 patients with hematologic diseases found that multiple myeloma was the most common disease in all three groups, accounting for 31.43% (11/35), 35.37% (29/82), and 37.88% (50/132) respectively. In the ≥5 cross-matchings group, myelodysplastic syndrome (14.29%, 5/35) and thalassemia (14.29%, 5/35) were the second most common diseases. In contrast, in the 2 to 4 cross-matchings group and 1 cross-matching group, autoimmune hemolytic anemia was the second most common disease, with prevalence rates of 20.73% (17/82) and 24.24% (32/132), respectively. Alloantibodies were detected in 54.66% of the patients, with antibodies against Rh blood group being most frequent (>50%) in all three groups. The detection rates of alloantibodies/alloantibodies with coexisting autoantibodies decreased across groups: the ≥5 cross-matchings group (70.42%, 50/71) > the 2 to 4 cross-matchings group (54.96%, 133/242) > the 1 cross-matching group (52.48%, 286/545). Conclusion: The risk of alloantibody production increases in patients with multiple cross-matching incompatibilities, especially in those with tumors or hematologic diseases. For handling of cross-matching incompatibility cases, it is recommended to optimize the cross-matching process, implement individualized transfusion plans, and enhance the technical capabilities of clinical transfusion departments and blood group reference laboratories to ensure the safety and effectiveness of transfusions.
3.Expert consensus on management of instrument separation in root canal therapy.
Yi FAN ; Yuan GAO ; Xiangzhu WANG ; Bing FAN ; Zhi CHEN ; Qing YU ; Ming XUE ; Xiaoyan WANG ; Zhengwei HUANG ; Deqin YANG ; Zhengmei LIN ; Yihuai PAN ; Jin ZHAO ; Jinhua YU ; Zhuo CHEN ; Sijing XIE ; He YUAN ; Kehua QUE ; Shuang PAN ; Xiaojing HUANG ; Jun LUO ; Xiuping MENG ; Jin ZHANG ; Yi DU ; Lei ZHANG ; Hong LI ; Wenxia CHEN ; Jiayuan WU ; Xin XU ; Jing ZOU ; Jiyao LI ; Dingming HUANG ; Lei CHENG ; Tiemei WANG ; Benxiang HOU ; Xuedong ZHOU
International Journal of Oral Science 2025;17(1):46-46
Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans
;
Root Canal Therapy/adverse effects*
;
Consensus
;
Root Canal Preparation/adverse effects*
4.Iodine Nutrition,Thyroid-stimulating Hormone,and Related Factors of Postpartum Women from three Different Areas in China:A Cross-sectional Survey
Yun Xiao SHAN ; Yan ZOU ; Chun Li HUANG ; Shan JIANG ; Wen Wei ZHOU ; Lan Qiu QIN ; Qing Chang LIU ; Yan Xiao LUO ; Xi Jia LU ; Qian De MAO ; Min LI ; Yu Zhen YANG ; Chen Li YANG
Biomedical and Environmental Sciences 2024;37(3):254-265
Objective Studies on the relationship between iodine,vitamin A(VA),and vitamin D(VD)and thyroid function are limited.This study aimed to analyze iodine and thyroid-stimulating hormone(TSH)status and their possible relationships with VA,VD,and other factors in postpartum women. Methods A total of 1,311 mothers(896 lactating and 415 non-lactating)from Hebei,Zhejiang,and Guangxi provinces were included in this study.The urinary iodine concentration(UIC),TSH,VA,and VD were measured. Results The median UIC of total and lactating participants were 142.00 μg/L and 139.95 μg/L,respectively.The median TSH,VA,and VD levels in all the participants were 1.89 mIU/L,0.44 μg/mL,and 24.04 ng/mL,respectively.No differences in the UIC were found between lactating and non-lactating mothers.UIC and TSH levels were significantly different among the three provinces.The rural UIC was higher than the urban UIC.Obese mothers had a higher UIC and a higher prevalence of excessive TSH.Higher UICs and TSHs levels were observed in both the VD deficiency and insufficiency groups than in the VD-sufficient group.After adjustment,no linear correlation was observed between UIC and VA/VD.No interaction was found between vitamins A/D and UIC on TSH levels. Conclusion The mothers in the present study had no iodine deficiency.Region,area type,BMI,and VD may be related to the iodine status or TSH levels.
5.Mechanism of Chaijin JieYu Anshen formula regulating synaptic plasticity of hippocampal neurons in insomnia-concomitant depression rats based on HDAC5/MEF2C pathway
Ting-Ting REN ; Yu-Hong WANG ; Ying-Juan TANG ; Song YANG ; Hai-Peng GUO ; Ting-Ting WANG ; Ying HE ; Ping LI ; Hong-Qing ZHAO ; Zi-Yang ZHOU ; Man-Shu ZOU
Chinese Pharmacological Bulletin 2024;40(7):1248-1257
Aim To investigate the mechanisms of Chaijin JieYu Anshen formula modulating the depres-sive behaviors and the synaptic plasticity of hippocam-pal neurons in insomnia-concomitant depression rats based on the histone deacetylase 5(HDAC5)/myocyte enhancer factor 2C(MEF2C)pathway.Methods A rat model of insomnia-concomitant depression was es-tablished by PCPA injection combined with chronic un-predictable mild stress(CUMS),and the experiment was divided into the control group,the model group,the high,medium and low dose group of Chaijin JieYu Anshen formula,and the positive drug group.The de-pression of rats was evaluated by sugar-water prefer-ence test,open field test and morris water maze.The levels of 5-hydroxytryptamine(5-HT)and dopamine(DA)in serum were measured by enzyme linked im-munosorbent assay(ELISA).The pathological damage of hippocampal neurons was observed by HE staining and Nissl staining.The damage of dendritic spines of hippocampal neurons was observed by Golgi staining,and the levels of HDAC5,MEF2C,postsynaptic densi-ty-95(PSD-95)and synaptophysin 1(SYN1)in hip-pocampus were measured by Western blot,immunohis-tochemistry and immunofluorescence.Results Com-pared with the model group,the Chaijin JieYu Anshen formula could increase the sugar-water preference rate of the model rats,reduce the immobility time in the open field experiment,increase the total activity dis-tance,shorten the evasion latency in the localization navigation experiment,and prolong the residence time in the quadrant where the platform was located in the space exploration experiment(P<0.05,P<0.01).Moreover,the Chaijin JieYu Anshen formula improved the hippocampal neuron and dendritic spine damage and increase the dendritic branch length and dendritic spine density of hippocampal neurons(P<0.01,P<0.01),restore the serum levels of 5-HT and DA in insomnia-concomitant depression rats(P<0.05,P<0.01),down-regulate the HDAC5 protein,and up-regulate the expression of MEF2C,PSD-95,and SYN1 protein(P<0.05,P<0.01 or P<0.001).Conclusions Chaijin JieYu Anshen formula may alle-viate the depression-like behavior of model rats by re-ducing the expression of HDAC5 protein,thus deregu-lating the inhibition of transcription factor MEF2C,promoting the expression of PSD-95 and SNY1 protein,and exerting a protective effect on hippocampal neurons and synapses.
6.Incidence and influencing factors of refeeding syndrome in critically ill patients:a Meta-analysis
Xiaocui ZOU ; Xiaorong MAO ; Lixue WANG ; Xiaojuan YANG ; Qing WEN
Chinese Journal of Nursing 2024;59(21):2640-2648
Objective To systematically review the incidence and influencing factors of refeeding syndrome(RFS)in critically ill patients,and provide references for early identification of RFS and formulation of preventive measures.Methods Computerized searches were conducted for studies on RFS in critically ill patients in the databases of China National Knowledge Infrastructure(CNKI),Wanfang,VIP,CBM,PubMed,Embase,Web of Science,CINAHL,Cochrane Library from inception to May 29th,2024.Data analysis was performed using Stata 16.0 software.Results A total of 29 articles with 5 720 participants were included.The Meta-analysis showed that the incidence of RFS in critically ill patients was 33.68%.The subgroup analysis showed that the incidence of RFS in critically ill patients was higher in studies conducted in 2020 or later(38.22%),in the Americas(36.39%),and with only electrolyte changes as the diagnostic basis(37.51%).Risk factors for RFS in critically ill patients included higher acute physiological and chronic health evaluation Ⅱ scores(OR=1.41),higher sequential organ failure assessment scores(OR=1.29),initiation of feeding within 48 h of ICU admission(OR=3.36),age ≥60 years(OR=2.82),diabetes mellitus(OR=3.53),pre-albumin concentration<150 g/L(OR=5.53),albumin concentration<30 g/L(OR=3.26),caloric intake>25%standard calories(OR=2.86),enteral solution temperature of 36~38 ℃(OR=2.32),feeding rate>50 ml/h(OR=3.76),fasting time ≥2 d before feeding(OR=2.46),history of alcoholism(OR=2.64).Conclusion The incidence of RFS in critically ill patients is high and there are many influencing factors.Nurses should improve their awareness and attention to RFS,accurately identify high-risk groups and risk factors,and adopt a multidisciplinary collaborative model to develop whole-course,detailed and personalized intervention measures to prevent RFS.
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.


Result Analysis
Print
Save
E-mail