1.Serological and molecular biological analysis of a rare Dc- variant individual
Xue TIAN ; Hua XU ; Sha YANG ; Suili LUO ; Qinqin ZUO ; Liangzi ZHANG ; Xiaoyue CHU ; Jin WANG ; Dazhou WU ; Na FENG
Chinese Journal of Blood Transfusion 2025;38(8):1101-1106
Objective: To reveal the molecular biological mechanism of a rare Dc-variant individual using PacBio third-generation sequencing technology. Methods: ABO and Rh blood type identification, DAT, unexpected antibody screening and D antigen enhancement test were conducted by serological testing. The absorption-elution test was used to detect the e antigen. RHCE gene typing was performed by PCR-SSP, and the 1-10 exons of RHCE were sequenced by Sanger sequencing. The full-length sequences of RHCE, RHD and RHAG were detected by PacBio third-generation sequencing technology. Results: Serological findings: Blood type O, Dc-phenotype, DAT negative, unexpected antibody screening negative; enhanced D antigen expression; no detection of e antigen in the absorption-elution test. PCR-SSP genotyping indicated the presence of only the RHCE
c allele. Sanger sequencing results: Exons 5-9 of RHCE were deleted, exon 1 had a heterozygous mutation at c. 48G/C, and exon 2 had five heterozygous mutations at c. 150C/T, c. 178C/A, c. 201A/G, c. 203A/G and c. 307C/T. Third-generation sequencing results: RHCE genotype was RHCE
02N. 08/RHCE-D(5-9)-CE; RHD genotype was RHD
01/RHD
01; RHAG genotype was RHAG
01/RHAG
01 (c. 808G>A and c. 861G>A). Conclusion: This Dc-individual carries the allele RHCE
02N. 08 and the novel allele RHCE-D(5-9)-CE. The findings of this study provide data support and a theoretical basis for elucidating the molecular mechanisms underlying RhCE deficiency phenotypes.
2.Comparison of treatment regimens for unresectable stage III epidermal growth factor receptor ( EGFR ) mutant non-small cell lung cancer.
Xin DAI ; Qian XU ; Lei SHENG ; Xue ZHANG ; Miao HUANG ; Song LI ; Kai HUANG ; Jiahui CHU ; Jian WANG ; Jisheng LI ; Yanguo LIU ; Jianyuan ZHOU ; Shulun NIE ; Lian LIU
Chinese Medical Journal 2025;138(14):1687-1695
BACKGROUND:
Durvalumab after chemoradiotherapy (CRT) failed to bring survival benefits to patients with epidermal growth factor receptor ( EGFR ) mutations in PACIFIC study (evaluating durvalumab in patients with stage III, unresectable NSCLC who did not have disease progression after concurrent chemoradiotherapy). We aimed to explore whether locally advanced inoperable patients with EGFR mutations benefit from tyrosine kinase inhibitors (TKIs) and the optimal treatment regimen.
METHODS:
We searched the PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases from inception to December 31, 2022 and performed a meta-analysis based on a Bayesian framework, with progression-free survival (PFS) and overall survival (OS) as the primary endpoints.
RESULTS:
A total of 1156 patients were identified in 16 studies that included 6 treatment measures, including CRT, CRT followed by durvalumab (CRT-Durva), TKI monotherapy, radiotherapy combined with TKI (RT-TKI), CRT combined with TKI (CRT-TKI), and TKI combined with durvalumab (TKI-Durva). The PFS of patients treated with TKI-containing regimens was significantly longer than that of patients treated with TKI-free regimens (hazard ratio [HR] = 0.37, 95% confidence interval [CI], 0.20-0.66). The PFS of TKI monotherapy was significantly longer than that of CRT (HR = 0.66, 95% CI, 0.50-0.87) but shorter than RT-TKI (HR = 1.78, 95% CI, 1.17-2.67). Furthermore, the PFS of RT-TKI or CRT-TKI were both significantly longer than that of CRT or CRT-Durva. RT-TKI ranked first in the Bayesian ranking, with the longest OS (60.8 months, 95% CI = 37.2-84.3 months) and the longest PFS (21.5 months, 95% CI, 15.4-27.5 months) in integrated analysis.
CONCLUSIONS:
For unresectable stage III EGFR mutant NSCLC, RT and TKI are both essential. Based on the current evidence, RT-TKI brings a superior survival advantage, while CRT-TKI needs further estimation. Large randomized clinical trials are urgently needed to explore the appropriate application sequences of TKI, radiotherapy, and chemotherapy.
REGISTRATION
PROSPERO; https://www.crd.york.ac.uk/PROSPERO/ ; No. CRD42022298490.
Humans
;
Carcinoma, Non-Small-Cell Lung/therapy*
;
ErbB Receptors/genetics*
;
Lung Neoplasms/drug therapy*
;
Mutation/genetics*
;
Protein Kinase Inhibitors/therapeutic use*
;
Chemoradiotherapy
;
Antibodies, Monoclonal/therapeutic use*
3.Studies on the best production mode of traditional Chinese medicine driven by artificial intelligence and its engineering application.
Zheng LI ; Ning-Tao CHENG ; Xiao-Ping ZHAO ; Yi TAO ; Qi-Long XUE ; Xing-Chu GONG ; Yang YU ; Jie-Qiang ZHU ; Yi WANG
China Journal of Chinese Materia Medica 2025;50(12):3197-3203
The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence
;
Drugs, Chinese Herbal
;
Medicine, Chinese Traditional/methods*
;
Humans
4.YOLOX-SwinT algorithm improves the accuracy of AO/OTA classification of intertrochanteric fractures by orthopedic trauma surgeons.
Xue-Si LIU ; Rui NIE ; Ao-Wen DUAN ; Li YANG ; Xiang LI ; Le-Tian ZHANG ; Guang-Kuo GUO ; Qing-Shan GUO ; Dong-Chu ZHAO ; Yang LI ; He-Hua ZHANG
Chinese Journal of Traumatology 2025;28(1):69-75
PURPOSE:
Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification.
METHODS:
We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1.
RESULTS:
The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS.
CONCLUSION
In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans
;
Hip Fractures/diagnostic imaging*
;
Orthopedic Surgeons
;
Algorithms
;
Artificial Intelligence
6.Research progress of antifungal drugs from natural sources
Shao-jie CHU ; Yan ZHENG ; Shuang-shuang SU ; Xue-song WU ; Hong YAN ; Shao-xin CHEN ; Hong-bo WANG
Acta Pharmaceutica Sinica 2025;60(1):48-57
As the number of patients with compromised immune function increases and fungal resistance develops, so does the risk of contracting deadly fungi in humans. Both fungi and humans are eukaryotes, so identifying unique targets for antifungal drug development is difficult. In addition, the existing antifungal drugs are limited by toxicity, drug interaction and drug resistance in practical application, which leads to the increasing incidence and fatal rate of fungal infections. Therefore, it is urgent to develop new antifungal drugs. The semi-synthetic technology using microbial fermentation products from natural sources as lead compounds has become the most used method in structural modification of antifungal drugs due to its advantages of few reaction steps and easy operation. This paper will introduce the current status of natural antifungal drugs in clinical use, as well as the latest progress in the research and development of new semi-synthetic antifungal drugs, and summarize their mechanism of action, structural modifications, advantages and disadvantages, so as to provide reference for the subsequent development of new antifungal drugs.
7.Evaluation of the improved method for isolation of A(H1N1) pandemic 2009 and seasonal A(H3N2) influenza virus in embryonated chicken eggs
Hongwei ZHU ; Lei TANG ; Wei CHU ; Xue ZHAO ; Yiqun LOU ; Xiaojie CHU ; Lili SONG ; Yu WANG ; Zheng TENG
Chinese Journal of Experimental and Clinical Virology 2025;39(3):378-382
Objective:To improve the isolation and culture method of seasonal influenza virus in embryonated chicken eggs (ECEs), and evaluate their isolation efficiency.Methods:We randomly selected 80 positive samples of H1N1 (H1N1pdm09) and seasonal H3N2 (H3N2snl) influenza virus nucleic acid, and inoculated them into the amniotic and urinary sac cavities of 10-day-old (traditional method) and 14-day-old (improved method) ECEs respectively to adapt the virus to the ECEs (E1-E2). Both method were used to inoculate 10-day-old urinary sac amplification virus (E2-E3), and the final virus isolation positive rates of the two method were compared; using fluorescence quantitative PCR method to detect viral nucleic acids in the improved amniotic and urinary sac cultures, and evaluate the viral proliferation at different inoculation sites; we analyzed the correlation between virus content and isolation positivity rate in the original specimen based on the CT value of nucleic acid testing and the final virus isolation positivity rate using the improved method.Results:The improved method obtained 42 strains of H1N1pdm09 strain, with a positive rate of 52.5% ( χ2=38.571, P<0.01); obtained 54 strains of H3N2snl strain, with a positive rate of 67.5% ( χ2=40.921, P<0.01). Significant differences were observed in the isolation efficiency of H1N1pdm09 samples when the improved method was applied to different inoculation sites of chicken embryos ( χ2=30.476, P<0.01), and similar differences were noted for H3N2snl samples ( χ2=4.928, P=0.026). There was no significant difference in the isolation rate of different CT value intervals of the original samples ( χH1N1pdm092=10.226, χH3N2snl2=3.764, P>0.05). Conclusions:The improved method of inoculating 14-day old ECEs adapted the virus, and the final number of strains obtained was significantly higher than the traditional method of inoculating 10 day old ECEs, which can significantly improve the positive isolation rate of H1N1pdm09 and H3N2snl influenza virus in ECEs. The amniotic cavity is more sensitive to H1N1pdm09 and H3N2snl influenza viruses, which helps the virus adapt in ECEs. There was no significant difference in the sample isolation rate and total positive rate of virus isolation among different CT value ranges, and further verification is needed.
8.Analysis of the trend and spatial clustering of lung cancer mortality in Shandong Province from 1970 to 2021
Zhentao FU ; Fan JIANG ; Zilong LU ; Jie CHU ; Xiaohui XU ; Bingyin ZHANG ; Fuzhong XUE ; Xiaolei GUO ; Aiqiang XU ; Jixiang MA
Chinese Journal of Preventive Medicine 2025;59(5):555-560
Objective:To understand spatial aggregation of lung cancer mortality and its changing trends over the past fifty years in different counties and districts of Shandong Province from 1970 to 2021.Methods:The mortality data of lung cancer were obtained from the death registration system of Shandong province and three retrospective surveys of death cause. The mortality rate and age-standardized mortality rate were used to describe the changing trend of lung cancer in different years, and the contribution value of population factors and non-population factors in lung cancer mortality change was calculated by the mortality differential decomposition method. GeoDa 1.20 and ArcGIS 10.8 software were used for spatial autocorrelation analysis and visualization map display.Results:The crude mortality rate of lung cancer in Shandong Province showed a significant upward trend from 1970 to 2021, rising from 7.22 per 100 000 in 1970-1974 to 62.73 per 100 000 in 2020-2021, with an increase of 7.69 times. Meanwhile, the standardized mortality rate of lung cancer exhibited a trend of increasing first and then decreasing. The differential analysis of lung cancer mortality in different years revealed that changes in crude mortality rates were the result of the combined effects of demographic and non-demographic factors. The proportion of population factors (aging population) leading to an increase in lung cancer mortality rate rose from 2.12% in 1990-1992 to 40.20% in 2020-2021. From a spatial distribution perspective, there were significant regional differences in lung cancer mortality rates among counties (cities, districts) in Shandong Province across different eras. Compared to the period of 1970-1974, the lung cancer mortality rates in all counties and districts in 2020-2021 showed a considerable increase, and there were noticeable changes in the areas of high-high and low-low clustering of lung cancer mortality rates across different eras.Conclusion:There have been significant temporal and spatial changes in the mortality rate of lung cancer in Shandong Province from 1970 to 2021. The crude mortality rate has shown an upward trend, while the standardized mortality rate increases first and then decreases. The concentration of lung cancer mortality rates in counties and districts has also undergone significant changes.
9.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
10.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

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