1.In Vitro and in vivo Component Analysis of Total Phenolic Acids from Gei Herba and Its Effect on Promoting Acute Wound Healing and Inhibiting Scar Formation
Xixian KONG ; Guanghuan TIAN ; Tong WU ; Shaowei HU ; Jie ZHAO ; Fuzhu PAN ; Jingtong LIU ; Yong DENG ; Yi OUYANG ; Hongwei WU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(3):156-167
ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry(UPLC-Q-Orbitrap-MS), to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba(TPAGH), and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group, recombinant human epidermal growth factor(rhEGF) group(4 mg·kg-1), and low, medium, and high dose groups of TPAGH(3.5, 7, 14 mg·kg-1), with 24 mice in each group. A full-thickness skin excision model was constructed, and each administration group was coated with the drug at the wound site, and the model group was treated with an equal volume of normal saline, the treatment was continued for 30 days, during which 8 mice from each group were sacrificed on days 6, 12, and 30. The healing of the wounds in the mice was observed, and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin(HE), Masson, and Sirius red staining, and enzyme-linked immunosorbent assay(ELISA) was used to dynamically measure the contents of interleukin-6(IL-6), tumor necrosis factor-α(TNF-α), vascular endothelial growth factor A(VEGFA), matrix metalloproteinase(MMP)-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH, and molecular docking of key components and targets was performed. Gene Ontology(GO) biological process analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were carried out for the related targets, so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH, including 28 phenylpropanoids, 31 tannins, 23 triterpenes, 49 flavonoids, and 15 others, and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that, compared with the model group, the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate(P<0.05), and the number of new capillaries, number of fibroblasts, number of new skin appendages, epidermal regeneration rate, collagen deposition ratio, and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved(P<0.05, 0.01), the levels of IL-6, TNF-α, MMP-3 and MMP-9 in the skin tissues were reduced to different degrees, while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets, including tumor protein 53(TP53), sarcoma receptor coactivator(SRC), protein kinase B(Akt)1, signal transducer and activator of transcription 3(STAT3), epidermal growth factor receptor(EGFR) and so on, participating in 75 signaling pathways such as advanced glycation end-products(AGE)-receptor for AGE(AGE/RAGE) signaling pathway, phosphatidylinositol 3-kinase(PI3K)/Akt signaling pathway, mitogen-activated protein kinase(MAPK) signaling pathway. Molecular docking confirmed that the key components genistein, geraniin, and casuariin had good binding ability to TP53, SRC, Akt1, STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction, thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology, the study explores how key components may bind to targets such as TP53, Akt1 and EGFR, exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.
2.Proguanil induces bladder cancer cell apoptosis through mediating oxidation-reduction driven ferroptosis
Qing-Hua PAN ; Yin-Long LIU ; Yong LIU ; Bao-Chun LIAO ; Jian HU ; Zhi-Jian ZHU
The Chinese Journal of Clinical Pharmacology 2024;40(20):2988-2992
Objective To explore the potential mechanism of proguanil on the proliferation and apoptosis of bladder cancer cells.Methods 253J cells were randomly divided into control group(normal treatment),proguanil group(42.06 μmol·L-1 proguanil),pcDNA group(transfected with pcDNA+42.06 μmol·L-1 proguanil),FADS2 group[transfected fatty acid desaturase gene 2(FADS2)+42.06 μmol·L-1 proguanil],si-NC(transfection si-NC),si-FADS2(transfection si-FADS2),Ferrostatin-1 group(transfected with si-FADS2+10 μmol·L-1 ferrostatin-1).Real-time fluorescence quantitative polymerase chain reaction(RT-qPCR)assay was used to detect mRNA expression of related genes;Western blot assay was used to detect the expression of each protein;apoptosis was detected by TdT mediated dUDP nick end labeling(Tunel)assay;5-ethynyl-2'-deoxyuridine(EdU)assay to detect cell proliferation;the Transwell assay measures the ability of cells to migrate;Fe2+levels were determined by kit method;DCFH-DA probe was used to detect ROS levels.Results The mRNA levels of FADS2 in control group,proguanil group,pcDNA group and FADS2 group were 1.00±0.11,0.47±0.09,0.49±0.06 and 2.09±0.21,respectively;cell proliferation rate were(100.00±3.50)%,(54.31±4.90)%,(56.46±5.17)%and(78.76±6.50)%,respectively;the apoptosis rate were(3.92±0.53)%,(28.79±3.30)%,(27.20±2.90)%and(7.34±0.68)%,respectively;the migration number were 132.70±9.81,70.10±5.05,68.70±537 and 101.80±11.25,respectively;Fe2+level were(100.00±8.14)%,(201.33±17.84)%,(192.38±21.34)%and(116.70±10.90)%,respectively;GPX4 protein relative expression level were 0.77±0.05,0.31±0.05,0.34±0.05 and 0.68±0.06,respectively.The above indexes in proguanil group were compared with those in control group,the above indexes in FADS2 group were compared with those in pcDNA group,all the differences were statistically significant(all P<0.05).The ROS levels of si-NC,si-FADS2 and Ferrostatin-1 groups were 9.72±1.18,40.94±5.63 and 13.77±1.40,respectively.Compared the si-FADS2 group with the si-NC group,Ferrostatin-1 group compared with si-FADS2 group,ROS level were significantly different(all P<0.05).Conclusion Proguanil can induce the apoptosis of bladder cancer cells by inhibiting FADS2 expression mediated by oxidation-reduction driven ferroptosis pathway.
3.Analysis of surgical situations and prognosis of pancreaticoduodenectomy in Jiangsu province (a report of 2 886 cases)
Zipeng LU ; Xin GAO ; Hao CHENG ; Ning WANG ; Kai ZHANG ; Jie YIN ; Lingdi YIN ; Youting LIN ; Xinrui ZHU ; Dongzhi WANG ; Hongqin MA ; Tongtai LIU ; Yongzi XU ; Daojun ZHU ; Yabin YU ; Yang YANG ; Fei LIU ; Chao PAN ; Jincao TANG ; Minjie HU ; Zhiyuan HUA ; Fuming XUAN ; Leizhou XIA ; Dong QIAN ; Yong WANG ; Susu WANG ; Wentao GAO ; Yudong QIU ; Dongming ZHU ; Yi MIAO ; Kuirong JIANG
Chinese Journal of Digestive Surgery 2024;23(5):685-693
Objective:To investigate the surgical situations and perioperative outcome of pancreaticoduodenectomy in Jiangsu Province and the influencing factors for postoperative 90-day mortality.Methods:The retrospective case-control study was conducted. The clinicopathological data of 2 886 patients who underwent pancreaticoduodenectomy in 21 large tertiary hospitals of Jiangsu Quality Control Center for Pancreatic Diseases, including The First Affiliated Hospital of Nanjing Medical University, from March 2021 to December 2022 were collected. There were 1 732 males and 1 154 females, aged 65(57,71)years. Under the framework of the Jiangsu Provincial Pancreatic Disease Quality Control Project, the Jiangsu Quality Control Center for Pancreatic Diseases adopted a multi-center registration research method to establish a provincial electronic database for pancrea-ticoduodenectomy. Observation indicators: (1) clinical characteristics; (2) intraoperative and post-operative conditions; (3) influencing factors for 90-day mortality after pancreaticoduodenectomy. Measurement data with skewed distribution were represented as M( Q1, Q3) or M(IQR), and comparison between groups was conducted using the Mann-Whitney U test. Count data were expressed as absolute numbers or constituent ratio, and comparison between groups was conducted using the chi-square test, continuity correction chi-square test and Fisher exact probability. Maximal Youden index method was used to determine the cutoff value of continuous variables. Univariate analysis was performed using the corresponding statistical methods based on data types. Multivariate analysis was performed using the Logistic multiple regression model. Results:(1) Clinical characteristics. Of the 2 886 patients who underwent pancreaticoduodenectomy, there were 1 175 and 1 711 cases in 2021 and 2022, respectively. Of the 21 hospitals, 8 hospitals had an average annual surgical volume of <36 cases for pancreaticoduodenectomy, 10 hospitals had an average annual surgical volume of 36-119 cases, and 3 hospitals had an average annual surgical volume of ≥120 cases. There were 2 584 cases performed pancreaticoduodenectomy in thirteen hospitals with an average annual surgical volume of ≥36 cases, accounting for 89.536%(2 584/2 886)of the total cases. There were 1 357 cases performed pancrea-ticoduodenectomy in three hospitals with an average annual surgical volume of ≥120 cases, accounting for 47.020%(1 357/2 886) of the total cases. (2) Intraoperative and postoperative conditions. Of the 2 886 patients, the surgical approach was open surgery in 2 397 cases, minimally invasive surgery in 488 cases, and it is unknown in 1 case. The pylorus was preserved in 871 cases, not preserved in 1 952 cases, and it is unknown in 63 cases. Combined organ resection was performed in 305 cases (including vascular resection in 209 cases), not combined organ resection in 2 579 cases, and it is unknown in 2 cases. The operation time of 2 885 patients was 290(115)minutes, the volume of intra-operative blood loss of 2 882 patients was 240(250)mL, and the intraoperative blood transfusion rate of 2 880 patients was 27.153%(782/2 880). Of the 2 886 patients, the invasive treatment rate was 11.342%(327/2 883), the unplanned Intensive Care Unit (ICU) treatment rate was 3.087%(89/2 883), the reoperation rate was 1.590%(45/2 830), the duration of postoperative hospital stay was 17(11)days, the hospitalization mortality rate was 0.798%(23/2 882), and the failure rate of rescue data in 2 083 cases with severe complications was 6.529%(19/291). There were 2 477 patients receiving postoperative 90-day follow-up, with the 90-day mortality of 2.705%(67/2477). The total incidence rate of complication in 2 886 patients was 58.997%(1 423/2 412). The incidence rate of severe complication was 13.970%(291/2 083). The comprehensive complication index was 8.7(22.6) in 2 078 patients. (3) Influencing factors for 90-day mortality after pancreaticoduodenectomy. Results of multivariate analysis showed that age ≥ 70 years, postoperative invasive treatment, and unplanned ICU treatment were independent risk factors for 90-day mortality after pancreaticoduodenectomy ( odds ratio=2.403, 2.609, 16.141, 95% confidence interval as 1.281-4.510, 1.298-5.244, 7.119-36.596, P<0.05). Average annual surgical volume ≥36 cases in the hospital was an independent protective factor for 90-day mortality after pancreaticoduodenectomy ( odds ratio=0.368, 95% confidence interval as 0.168-0.808, P<0.05). Conclusions:Pancreaticoduodenectomy in Jiangsu Province is highly con-centrated in some hospitals, with a high incidence of postoperative complications, and the risk of postoperative 90-day mortality is significant higher than that of hospitallization mortality. Age ≥ 70 years, postoperative invasive treatment, and unplanned ICU treatment are independent risk factors for 90-day motality after pancreaticoduodenectomy, and average annual surgical volume ≥36 cases in the hospital is an independent protective factor.
4.The impact of occupational noise exposure on hearing level and its prevention and control measures
Cailing ZHOU ; Zuying HU ; Yong LI ; Qi JIN ; Pingping PAN
Chinese Archives of Otolaryngology-Head and Neck Surgery 2024;31(5):297-300
OBJECTIVE To investigate the impact of noise exposure in metallurgical manufacturing on hearing.METHODS 245 workers exposed to noise in an enterprise and 51 administrative staff were tested for air conduction hearing threshold of pure tones at 0.5-8 kHz in both ears,and the equivalent sound level of workplace noise was measured for 8 hours.The hearing threshold of workers in different jobs was statistically analyzed.RESULTS The hearing threshold of workers exposed to noise at 0.5-8 kHz was significantly higher than that of administrative staff;hearing loss mainly occurred at 4 kHz and 6 kHz;the hearing threshold was positively correlated with working age and age,and the hearing threshold of workers over 40 years old and with working age of more than 6 years were higher than 40 dB HL at both ears at 4 kHz and 6 kHz.CONCLUSION The hearing loss of 4 kHz and 6 kHz is most obvious in noise-exposed workers,and age,working age,and noise exposure intensity were risk factors for hearing loss.It is necessary to strengthen the control of noise sources,attach importance to protective measures such as earplugs,and reduce noise exposure time.
5.Study on Spatial Distribution of Chemical Components in Flue Cured Tobacco Leaves by Imprinting Analytical Electrospray Photoionization Mass Spectrometry
Chun-Chun LYU ; Yu-Ting JIANG ; Yong-Hua HU ; Liu-Tian WU ; Ke-Ke QI ; Cheng-Yuan LIU ; Yang PAN
Chinese Journal of Analytical Chemistry 2024;52(6):876-884,中插36-中插37
The imprint desorption electrospray photoionization mass spectrometry was employed to locally image the spatial distribution of chemical components in dried tobacco leaves after initial curing. The relative content distribution of different chemical components was obtained in tobacco leaves. The application of imprinting method could transfer tobacco internal compounds to the surface of porous polytetrafluoroethylene plate,which realized the detection and visual analysis of tobacco internal substances. Besides,the imprint desorption electrospray ionization/post-photoionization (Imprint DESI/PI) mass spectrometry imaging technique had the advantages of non-polarity discrimination,soft ionization and high ionization efficiency for plant samples,and could simultaneously detect and image rich compounds in tobacco samples. A total of 40 kinds of chemical components including alkaloids,amino acids,sugars,acids,ketones and phenols were identified based on high resolution mass spectrometry. The results showed that the representative chemical components of tobacco,such as alkaloids,amino acids and sugars,were mainly distributed near the leaf tip from the vertical analysis and at the left and right leaf edges from the horizontal analysis. Amadori compound (1-Deoxy-1-L-proline-d-fructose) was detected,and the content of Amadori was found to be consistent with that of free amino acid (proline). In addition,the technique was further used to study the climate spot disease area of tobacco,and it was found that the compounds had specific distribution in the climate spot area,which further proved the superiority of this method in studying the growth stress of tobacco leaves.
6.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
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.

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