1.Trends in global burden due to visceral leishmaniasis from 1990 to 2021 and projections up to 2035
Guobing YANG ; Aiwei HE ; Yongjun LI ; Shan LÜ ; Muxin CHEN ; Liguang TIAN ; Qin LIU ; Lei DUAN ; Yan LU ; Jian YANG ; Shizhu LI ; Xiaonong ZHOU ; Jichun WANG ; Shunxian ZHANG
Chinese Journal of Schistosomiasis Control 2025;37(1):35-43
Objective To investigate the global burden of visceral leishmaniasis (VL) from 1990 to 2021 and predict the trends in the burden of VL from 2022 to 2035, so as to provide insights into global VL prevention and control. Methods The global age-standardized incidence, prevalence, mortality and disability-adjusted life years (DALYs) rates of VL and their 95% uncertainty intervals (UI) were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources. The trends in the global burden of VL were evaluated with average annual percent change (AAPC) and 95% confidence interval (CI) from 1990 to 2021, and gender-, age-, country-, geographical area- and socio-demographic index (SDI)-stratified burdens of VL were analyzed. The trends in the global burden of VL were projected with a Bayesian age-period-cohort (BAPC) model from 2022 to 2035, and the associations of age-standardized incidence, prevalence, mortality, and DALYs rates of VL with SDI levels were examined with a smoothing spline model. Results The global age-standardized incidence [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)], prevalence [AAPC = -0.06%, 95% CI: (-0.06%, -0.06%)], mortality [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)] and DALYs rates of VL [AAPC = -2.38%, 95% CI: (-2.44%, -2.33%)] all appeared a tendency towards a decline from 1990 to 2021, and the highest age-standardized incidence [2.55/105, 95% UI: (1.49/105, 4.07/105)], prevalence [0.64/105, 95% UI: (0.37/105, 1.02/105)], mortality [0.51/105, 95% UI: (0, 1.80/105)] and DALYs rates of VL [33.81/105, 95% UI: (0.06/105, 124.09/105)] were seen in tropical Latin America in 2021. The global age-standardized incidence and prevalence of VL were both higher among men [0.57/105, 95% UI: (0.45/105, 0.72/105); 0.14/105, 95% UI: (0.11/105, 0.18/105)] than among women [0.27/105, 95% UI: (0.21/105, 0.33/105); 0.06/105, 95% UI: (0.05/105, 0.08/105)], and the highest mortality of VL was found among children under 5 years of age [0.24/105, 95% UI: (0.08/105, 0.66/105)]. The age-standardized incidence (r = -0.483, P < 0.001), prevalence (r = -0.483, P < 0.001), mortality (r = -0.511, P < 0.001) and DALYs rates of VL (r = -0.514, P < 0.001) correlated negatively with SDI levels from 1990 to 2021. In addition, the global burden of VL was projected with the BAPC model to appear a tendency towards a decline from 2022 to 2035, and the age-standardized incidence, prevalence, mortality and DALYs rates were projected to be reduced to 0.11/105, 0.03/105, 0.02/105 and 1.44/105 in 2035, respectively. Conclusions Although the global burden of VL appeared an overall tendency towards a decline from 1990 to 2021, the burden of VL showed a tendency towards a rise in Central Asia and western sub-Saharan African areas. The age-standardized incidence and prevalence rates of VL were relatively higher among men, and the age-standardized mortality of VL was relatively higher among children under 5 years of age. The global burden of VL was projected to continue to decline from 2022 to 2035.
2.Spatiotemporal distribution of Aedes albopictus and its influencing factors in China from 2000 to 2019
Zerui JIAO ; Lei QU ; Duoquan WANG ; Yi ZHANG ; Shan LÜ
Chinese Journal of Schistosomiasis Control 2025;37(3):268-275
Objective To investigate the spatial distribution of Aedes albopictus in China at different time periods from 2000 to 2019, so as to provide insights into precise management of Ae. albopictus in China. Methods Data pertaining to the distribution of Ae. albopictus in China from 2000 to 2019 were collected through literature retrieval with terms of “Aedes albopictus”, “monitoring”, “survey”, “density”, “distribution”, and “outbreak” in national and international databases. The title and time of the publication, sampling sites, sampling time, mosquito capture methods, and mosquito species and density were extracted, and the longitude and latitude of sampling sites were obtained through Baidu Map. Meteorological element data at meteorological observation stations within China were obtained from the National Climatic Data Center of the United States, and the annual maximum temperature, annual minimum temperature, average temperature in January, average temperature in July, annual temperature range, daily temperature range and relative humidity were calculated and subjected to Kriging interpolation. Monthly cumulative precipitation grid data and monthly average temperature grid data with a resolution of 1 km for China from 2000 to 2019 were obtained from the National Tibetan Plateau Scientific Data Center, and the annual precipitation and annual average temperature were calculated cumulatively. Population density data in China from 2000 to 2019 were obtained from the WorldPop Hub, and the gross domestic product (GDP) in China was obtained from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. The above data were divided into 5-year intervals to calculate data during the periods from 2000 to 2004, from 2005 to 2009, from 2010 to 2014, and from 2015 to 2019. Ae. albopictus distribution data were modeled in China from 2000 to 2019 and during each period with the classification random forest (RF) model, to predict the distribution of Ae. albopictus across the country and analyze the distribution of Ae. albopictus based on the seven major climate zones in China. The performance of RF models was evaluated by accuracy, precision, recall, and area under the receiver operating characteristic curve (AUC), and the importance of each feature in the RF model was evaluated with mean decrease accuracy (MDA). Results A total of 1 191 Chinese publictions and 391 English publications were retrieved, among which 580 articles provided detailed data on the sampling sites of Ae. albopictus and specific sampling years, meeting the inclusion criteria. A total of 2 234 Ae. albopictus sampling sites were included in China from 2000 to 2019, and RF modeling results showed that the overall Ae. Albopictus distribution area was mainly found in southeastern and southwestern provinces of China from 2000 to 2019, with scattered distribution in coastal areas of northeastern provinces, such as Liaoning Province. The accuracy, precision, recall and AUC of the RF model were 0.915 to 0.947, 0.933 to 0.975, 0.898 to 0.978, and 0.902 to 0.932 for the distribution of Ae. albopictus at different time periods from 2000 to 2019. Among all features in the RF models, population density was the most contributing factor to the distribution of Ae. albopictus in China, followed by GDP, and all meteorological variables contributed relatively less to the predictive power of the RF model. In China’s seven major climate zones, Ae. albopictus was almost entirely distributed in the marginal tropical humid region, the north subtropical humid region, and the warm temperate semi-humid region. The combined distribution area of these three zones accounted for 100.0% of the national distribution area from 2000 to 2004, from 2005 to 2009, and from 2010 to 2014, and 99.9% from 2015 to 2019, and the proportion of Ae. albopictus distribution area in the warm temperate semihumid region increased gradually from 20.2% to 30.2%. Conclusions Ae. albopictus is mainly distributed in the southeastern and southwestern provinces of China and is greatly influenced by population and economic factors. The warm temperate semi-humid region in China is gradually becoming a hot spot for the distribution of Ae. albopictus.
3.Medication rules of Astragali Radix in ancient Chinese medical books based on "disease-medicine-dose" pattern.
Jia-Lei CAO ; Lü-Yuan LIANG ; Yi-Hang LIU ; Zi-Ming XU ; Xuan WANG ; Wen-Xi WEI ; He-Jia WAN ; Xing-Hang LYU ; Wei-Xiao LI ; Yu-Xin ZHANG ; Bing-Qi WEI ; Xian-Qing REN
China Journal of Chinese Materia Medica 2025;50(3):798-811
This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history*
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Humans
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Medicine, Chinese Traditional/history*
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History, Ancient
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Astragalus Plant/chemistry*
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China
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Astragalus propinquus
4.Correlations of immune cell infiltration characteristics with clinicopathological parameters in patients with clear cell renal cell carcinoma.
Huaxuan ZHAO ; Guichao ZHANG ; Jiarong LIU ; Futian MO ; Taoen LI ; Chengyong LEI ; Shidong LÜ
Journal of Southern Medical University 2025;45(6):1280-1288
OBJECTIVES:
To investigate the characteristics of immune cell infiltration in tumor samples from Chinese patients with clear cell renal cell carcinoma (ccRCC) and the correlation of immune cell infiltration with tumor stage and response to immunotherapy.
METHODS:
Tumor samples and clinicopathological data were collected from 154 ccRCC patients treated in Nanfang Hospital, Southern Medical University from October, 2020 to October, 2023. The immune cell types infiltrating the tumor tissues were identified using immunohistochemistry and immunofluorescence staining, and their correlations with the patients' clinicopathological characteristics were analyzed. Patient-derived tumor tissue fragment models (PDTF) models, constructed using tumor tissues from 22 patients, were treated with PD-1 monoclonal antibody, and T cell activation was detected using flow cytometry to assess the patients' responses to immunotherapy.
RESULTS:
In Chinese ccRCC patients included in this study, CD8+ T cells, CD4+ T cells, and CD3+ T cells were the most abundant in the tumor tissues. Higher infiltration levels of CD3+ T cells (P=0.004), PD-1+ T cells (P=0.020), CD68+ T cells (P=0.049), CD79+ T cells (P=0.049), and Tryptase+ cells (P=0.049) were all positively correlated with a larger tumor size (≥5 cm). A higher infiltration level of CD4+ T cells was associated with a lower tumor stage. Patients with higher International Society of Urological Pathology (ISUP) grades had higher infiltration levels of CD3+ T cells (P=0.023), CD8+ T cells (P=0.045), PD-1+ T cells (P=0.014), CD20+ B cells (P=0.020) and CD79+ B cells (P=0.049), and lower levels of Tryptase+ cells (P=0.001). Patients with abundant infiltrating immune cells tended to have better responses to immunotherapy.
CONCLUSIONS
The infiltrating immune cells are heterogeneous in Chinese ccRCC patients, and immune cell infiltration characteristics are closely correlated with clinicopathological parameters of the patients.
Humans
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Carcinoma, Renal Cell/pathology*
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Kidney Neoplasms/pathology*
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Immunotherapy
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Male
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Lymphocytes, Tumor-Infiltrating/immunology*
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Female
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Middle Aged
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CD8-Positive T-Lymphocytes/immunology*
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Aged
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T-Lymphocytes/immunology*
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Programmed Cell Death 1 Receptor/immunology*
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Adult
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CD4-Positive T-Lymphocytes/immunology*
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Neoplasm Staging
5.Research progress in the fungal bioluminescence pathway.
Lei LÜ ; Ke CHENG ; Zhitao XU ; Shijie AN ; Dang XU ; Hao DU
Chinese Journal of Biotechnology 2025;41(7):2545-2558
The fungal bioluminescence pathway (FBP) catalyzes the oxidation of endogenous caffeic acid to produce green bioluminescence through an enzymatic cascade. Genetic engineering of FBP into plants creates autoluminescent specimens that circumvent the substrate limitations of conventional reporter systems. These transgenic plants serve dual functions as aesthetic displays and versatile biosensing platforms, enabling applications in real-time gene expression monitoring, continuous environmental surveillance, and non-invasive bioimaging, offering novel opportunities for horticultural production, environmental conservation, and bioengineering applications. This review synthesizes current advances in plant FBP engineering and explores how machine learning approaches can optimize autoluminescent phenotypes, thereby accelerating innovation in agricultural biotechnology, environmental sensing, and synthetic biology applications.
Fungi/genetics*
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Plants, Genetically Modified/metabolism*
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Genetic Engineering
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Biosensing Techniques
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Luminescent Measurements
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Caffeic Acids/metabolism*
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Luminescence
6.Teprenone alleviates LPS-induced inflammatory response and cardiac dysfunction through E3 ubiquitin ligase CHIP
Liting XU ; Yingwen LIU ; Jianling LI ; Wan LIN ; Miao WANG ; Lei YU ; Xue ZHANG ; Hang LI ; Huadong WANG ; Xiuxiu LÜ ; Yiyang WANG
Chinese Journal of Pathophysiology 2024;40(5):862-871
AIM:To explore the therapeutic effect of teprenone(geranylgeranylacetone,GGA)on lipopolysac-charide(LPS)-induced cardiac dysfunction and its mechanism.METHODS:(1)Eight-week-old male C57BL/6 wild-type mice and carboxyl terminus of heat shock protein 70(HSP70)-interacting protein(CHIP)gene knockout mice were randomly divided into control group,LPS group,LPS+GGA group and GGA group,with 8 mice in each group.The model was established by intraperitoneal injection of LPS(25 mg/kg),and 1 h after LPS stimulation,mice were given intraperito-neal injection of GGA(100 mg/kg).The technique of high-resolution ultrasonography system was used to evaluate the car-diac function of mice.The serum of mice from each group were collected to detect the levels of creatine kinase-MB(CK-MB)and lactate dehydrogenase(LDH).HE staining was performed to observe histological changes of cardiac tissues.ELISA was used to detect the levels of tumor necrosis factor-α(TNF-α)and interleukin-6(IL-6)in cardiac tissues.West-ern blot was used to detect the protein levels of HSP70,CHIP,karyopherin-α 2(KPNA2),myeloperoxidase(MPO),vas-cular cell adhesion molecule(VCAM),intercellular cell adhesion molecule(ICAM),and nuclear factor-κB(NF-κB)in cardiac tissues.(2)In vitro cell inflammation model was established using mouse myocardial cells HL-1 stimulated with LPS.ELISA was used to detect the levels of TNF-α and IL-6 in cell supernatants.Western blot was used to detect the pro-tein expression levels of HSP70,CHIP,and KPNA2 in myocardial cells.Immunofluorescence staining was performed to observe the content of nuclear NF-κB.RESULTS:(1)GGA effectively improved cardiac function of LPS-stimulated mice,significantly increased ejection fraction and left ventricular fractional shortening(P<0.01),reduced serum levels of CK-MB and LDH(P<0.01),and alleviated myocardial injury.(2)GGA significantly reduced the release of TNF-α and IL-6 caused by LPS(P<0.01),as well as nuclear translocation of NF-κB,decreased the levels of KPNA2,MPO,VCAM and ICAM in cardiac tissues,and increased the levels of HSP70 in cardiac tissues and cells(P<0.01).(3)In CHIP knockout myocardial cells and mice,GGA failed to inhibit LPS-induced inflammatory response and lost its effect on im-proving cardiac function.CONCLUSION:The protective effect of GGA against LPS-caused cardiac dysfunction of mice is related to increasing expression of HSP70 and promoting CHIP activation,which inhibits the translocation of NF-κB into nucleus and suppresses inflammatory factor release.CHIP knockout abolishes the effects of GGA on reducing LPS-induced inflammatory response and myocardial injury.
7.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.
8.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.
9.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.
10.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.

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