1.Establishment and Evaluation of New Mouse Model of Rheumatoid Arthritis Combined with Interstitial Lung Disease
Liting XU ; Qingyu ZHAO ; Chao YANG ; Lianhua HE ; Congcong SUN ; Shuangrong GAO ; Lili WANG ; Chunfang LIU ; Na LIN
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):81-90
ObjectiveTo establish a mouse model of rheumatoid arthritis with interstitial lung disease (RA-ILD) in DBA/1 mice using Porphyromonas gingivalis (Pg) infection combined with collagen-induced arthritis (CIA), and to comprehensively evaluate pathological characteristics in joints, lungs, and serum. MethodsForty DBA/1 mice were randomly divided into four groups, i.e., Control, Pg infection (Pg), CIA, and Pg infection combined with CIA (Pg+CIA), with 10 mice in each group. Arthritis clinical symptoms were evaluated by recording arthritis incidence and clinical scores. Micro-CT scanning was used to assess knee joint pathology. Histopathological changes and collagen deposition in knee joints and lung tissues were analyzed using hematoxylin-eosin (HE) and Masson staining. Immunohistochemistry was performed to detect protein expression of α-smooth muscle actin (α-SMA), typeⅠ collagen (ColⅠ), and fibronectin (FN) in lung tissues. Real-time quantitative polymerase chain reaction(Real-time PCR)was used to measure mRNA expression levels of α-SMA, ColⅠ, FN, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-1β in lung tissues. Enzyme-linked immunosorbent assay (ELISA) was used to detect serum levels of Pg, cyclic citrullinated peptide (CCP), and immunoglobulin G (IgG). ResultsJoint lesions: The CIA and Pg+CIA groups showed 100% arthritis incidence, with evident joint redness, swelling, and deformity. The number of affected limbs was 27 and 28, and clinical scores were 68 and 70, respectively. No obvious clinical symptoms were observed in the Pg group. Histopathological and imaging analyses showed severe joint lesions in the CIA and Pg+CIA groups, with significantly increased histopathological scores, bone mineral density, bone volume fraction, trabecular thickness, and trabecular number compared to the Control group (P<0.01). No obvious joint pathology was observed in the Pg group. Lung lesions: The Pg+CIA group exhibited marked alveolar inflammation, interstitial inflammatory cell infiltration, and alveolar wall thickening, with pronounced blue staining of collagen fibers. Histopathological scores and collagen area ratios were significantly higher than those of the Control, Pg, and CIA groups (P<0.05). Lung protein and mRNA expression levels of α-SMA, ColⅠ, and FN were markedly increased, and mRNA levels of IL-6, TNF-α, and IL-1β were significantly elevated compared to the Control group (P<0.05). Serology: The Pg+CIA group showed significantly higher levels of CCP, Pg, and IgG compared with the Control, Pg, and CIA groups (P<0.05). ConclusionDBA/1 mice subjected to Pg infection combined with CIA exhibited pronounced symptoms and pathological features of RA-ILD, along with elevated serum anti-CCP antibody levels. This model represents a novel RA-ILD mouse model, providing a valuable experimental tool for investigating RA-ILD pathogenesis and developing new therapeutics, and serves as a basis for establishing anti-cyclic citrullinated peptide antibody (ACPA)-positive RA-ILD animal models.
2.Integration of multisource transcriptomics data to identify potential biomarkers of asthmatic epithelial cells.
Lianhua XIE ; Shuxian LU ; Fangyang GUO ; Yifeng ZHANG ; Qian LIU
Chinese Journal of Cellular and Molecular Immunology 2025;41(8):695-705
Objective Through integrative bioinformatics analysis of multi-source transcriptomic data, potential biomarkers to asthma epithelial cells were identified. The expression of these candidate target was subsequently validated in lung tissues and epithelial cells from asthma models. Methods The gene expression profile data of epithelial cells from three asthma patient cohorts and corresponding healthy controls were integrated from the Gene Expression Omnibus (GEO) database. Differential expression analysis and gene co-expression network analysis were performed to identify key genes and biological pathways associated with asthma. The key genes were validated in lung tissues and epithelial cells in asthma animal models. Results Differential gene expression analysis revealed 1121 upregulated and 1484 downregulated genes in epithelial cells from asthma patients compared with healthy controls. The biological pathway enrichment analysis revealed that the upregulated genes were mainly involved in glycosylation processes, whereas the downregulated genes were mainly associated with immune cell differentiation process. The gene co-expression network analysis revealed that module 9, enriched in glycosylation-related pathways, was significantly positively correlated with asthma, whereas module 17, associated with insulin and other signaling pathways, showed a significant negative correlation with asthma. We identified the genes of polypeptide N-acetylgalactosaminyltransferase 5 (GALNT5), pyrroline-5-carboxylate reductase 1 (PYCR1), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) as key genes within module 9, all of which were significantly upregulated in asthma. Finally, we validated that the expression levels of GALNT5, PYCR1, and CEACAM5 were significantly upregulated in epithelial cells from asthmatic lung tissue. Additionally, using a rat asthma model, we further confirmed that the protein levels of these three genes were significantly upregulated in lung tissues of the model group. Conclusion Through data integration and experimental validation, this study identified key genes and biological pathways closely associated with asthma pathogenesis. These findings provide a novel theoretical basis and potential targets for the diagnosis and treatment of asthma.
Asthma/metabolism*
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Humans
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Epithelial Cells/metabolism*
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Animals
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Biomarkers/metabolism*
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Gene Expression Profiling
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Transcriptome
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Gene Regulatory Networks
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Rats
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Computational Biology
3.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
4.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
5.Current status and influencing factors of fertility concerns in early endometrial cancer and atypical endometrial hyperplasia patients with fertility preservation
Jingjing GONG ; Hongbin ZHANG ; Xueying WANG ; Ying ZHANG ; Yanmei ZHANG ; Dandan YANG ; Lianhua BAI ; Yuanyuan LIU ; Xiaodan LI
Chinese Journal of Modern Nursing 2025;31(34):4719-4724
Objective:To investigate the current status of fertility concerns among early-stage endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) patients with fertility preservation, and analyze its influencing factors.Methods:Convenience sampling was used to select early-stage EC and AEH patients with fertility preservation at Peking University People's Hospital from January to December 2021 as study subjects. The study subjects were surveyed using the General Information Questionnaire, Chinese version of the Reproductive Concerns after Cancer Scale (RCAC), and Social Support Rating Scale (SSRS). Pearson correlation was employed to examine the relationship between fertility concerns and social support in early-stage EC and AEH patients with fertility preservation. Single-factor analysis and multiple linear regression analysis were used to examine the factors influencing fertility concerns in early-stage EC and AEH patients with fertility preservation.Results:A total of 170 questionnaires were distributed, and 167 valid questionnaires were collected, with a valid response rate of 98.24% (167/170). The RCAC and SSRS scores of 167 early-stage EC and AEH patients with fertility preservation were (56.58±10.58) and (34.22±8.21), respectively. Educational level, disease type and staging, marital status, and social support were statistically significant factors influencing fertility concerns among early-stage EC and AEH patients undergoing fertility preservation ( P<0.05), explaining 32.80% of the total variance. Conclusions:Early-stage EC and AEH patients with fertility preservation exhibit high levels of fertility concerns. Clinical practice should develop individualized psychological intervention programs for patients with high education level, unmarried status, high pathological grading, and lack of social support to improve their physical and mental health.
6.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
7.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
8.Building of an intelligent DRG grouping audit system in a hospital
Juan ZHANG ; Yang PU ; Wen LIU ; Yingpeng WANG ; Lianhua KONG ; Yaxin HUANG ; Bin WAN ; Haixia DING
Chinese Journal of Hospital Administration 2025;41(8):614-618
Diagnosis-related groups (DRG) payment is an important component of deepening the reform of medical insurance payment methods. In June 2023, a tertiary hospital launched an intelligent DRG grouping audit system to enhance grouping accuracy. By establishing a multi departmental collaborative organizational structure, building a standardized knowledge base and a rule base covering five categories (diagnosis, fees, testing, nursing, and pathology), and integrating electronic medical records, medical orders, testing, and imaging data throughout the entire diagnosis and treatment process, the intelligent DRG grouping audit system with data collection, identification, extraction, comparison, and output modules was constructed to achieve intelligent audit. At the same time, it was formed a closed-loop management system for pre reporting quality control, in-process group entry control, and post data analysis and assessment, which would prevent the risk of differentiated behaviors such as high coding and high sets, and ensure the reasonable use of medical insurance funds. By January 2024, the system had covered 89 ADRG groups, and improved the efficiency and quality of DRG grouping audit. Compared with February to May 2023, the monthly average rejection rate of medical records on the first page decreased by 9.4% after the system was put into operation (June to December 2023), and core medical indicators such as the number of DRG groups, medical insurance settlement cases, and time consumption index continued to improve. The practical experience could provide reference and inspiration for other hospitals in China.
9.Distribution and drug resistance of Enterobacter cloacae in Gansu Province from 2019 to 2023
Zhifeng WANG ; Xiaofang LIANG ; Dandan DU ; Keke LI ; Qianqian LIU ; Wenjie WANG ; Zhangping LU ; Lianhua WEI
Chinese Journal of Nosocomiology 2025;35(19):3000-3004
OBJECTIVE To analyze the clinical distribution characteristics and drug resistance of Enterobacter cloa-cae in Gansu Province from 2019 to 2023,providing reference for the prevention and control of E.cloacae infec-tions in this region.METHODS Data on the distribution and drug resistance of E.cloacae from hospitals in mem-ber units of the Gansu Antimicrobial Surveillance Network between 2019 and 2023 were collected.In vitro drug susceptibility testing was performed by the Kirby-Bauer disk diffusion(K-B)method,minimum inhibitory con-centration method,and fully automated instrumentation,followed by analysis of the susceptibility results.RESULTS From 2019 to 2023,a total of 402 490 bacterial strains were isolated and cultured in Gansu Province,including 17 417 strains of E.cloacae,with a detection rate of 4.33%.The bacteria were primarily iso-lated from sputum specimens(62.81%),followed by urine(7.37%)and wound pus specimens(6.07%).The de-partmental distribution was dominated by internal medicine(44.96%)and surgery(28.50%).The highest detec-tion rate was observed in the adult group(15-65 years,45.79%).E.cloacae exhibited varying degrees of resist-ance to over 20 antibacterial drugs,but the overall drug resistance rate showed a declining trend(P<0.05).The highest drug resistance rate was observed for cefazolin(96.40%-98.38%),while the lowest was for tigecycline(0.44%—2.92%).Carbapenem-resistant E.cloacae demonstrated an increasing trend in drug resistance rates,with imipenem resistance ranging from 2.79%to 3.71%(P=0.044)and meropenem resistance ranging from 1.29%to 3.41%(P<0.05).CONCLUSIONS The isolation rate of E.cloacae in Gansu Province remains stable,with a declining trend in drug resistance to multiple antibacterial drugs.However,the increasing drug resistance to carbapenems warrants attention.
10.Frontier advances in hepatitis virus detection technologies: from immunological methods to molecular detection technologies
Yaozhou WU ; Yingying SUN ; Yanbin CHANG ; Keke LI ; Wenjie WANG ; Qianqian LIU ; Zhangping LU ; Lianhua WEI
Chinese Journal of Laboratory Medicine 2025;48(7):938-943
Hepatitis virus is the main pathogen causing liver inflammation and damage. Early detection is crucial for the effective treatment of hepatitis. The detection technology of hepatitis virus has gone through multiple stages, including immunological detection technology and nucleic acid detection technology. The emergence of emerging molecular detection technologies makes its detection more sensitive and convenient, including nanotechnology, Raman spectroscopy technology, microfluidic technology and biosensor technology. The development of these technologies has promoted the early diagnosis of hepatitis, but their clinic applications are still facing challenges. In the future, the development of hepatitis virus detection technology is expected to transform in the form of multidimensional and interdisciplinary innovation process, with its core objectives being the realization of more precise, convenient, and accessible detection methods, thereby comprehensively advancing the progress of hepatitis prevention and control efforts.

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