1.A nomogram model based on LASSO-Firth logistic regression to predict constipation risk in hospitalized adult patients with cardiovascular disease
Xiaoyan CHU ; Ying LIN ; Zhenzhen LU ; Zhixin ZHOU ; Xinyue DONG
Chinese Journal of Clinical Medicine 2026;33(4):599-606
Objective To construct a nomogram model for prediction of constipation risk in adult patients with cardiovascular disease (CVD). Methods A total of 780 adult patients with CVD admitted to Zhongshan Hospital, Fudan University from June 15, 2025 to August 15, 2025 were prospectively enrolled and randomly divided into a training set and a validation set at a 7∶3 ratio. Risk factors for constipation were identified using the least absolute shrinkage and selection operator (LASSO) and Firth logistic regressions, and a nomogram model was subsequently constructed in the training set. Receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the discrimination ability of the model. Calibration curve and decision curve analysis (DCA) were used to assess calibration and clinical applicability. The value of model was evaluated in the validation set. Results Among 780 adult patients with CVD, 391 patients (50.1%) developed constipation. Eleven variables were selected by LASSO regression and Firth logistic regression, and a nomogram model was constructed. The ROC curve showed that the AUCs of the model to predict constipation in adult patients with CVD in training and validation sets were 0.881 and 0.883, respectively. Calibration curves and DCA demonstrated good calibration and predictive performance of the model in training and validation sets. Conclusions The nomogram model based on LASSO-Firth logistic regression demonstrates good predictive performance and may serve as a useful tool for identifying adult patients with CVD at high risk of constipation.
2.Toxic effects of chlorinated organophosphate flame retardants on mice via different exposure routes
Jialei ZHU ; Meiyu ZHOU ; Huanhuan ZHU ; Ruiyang TIAN ; Dahua REN ; Haiping LIU ; Xuanying JIANG ; Linfan XU ; Ying LU ; Haiyan CHU
Chinese Journal of Preventive Medicine 2025;59(7):1031-1039
Objective:To evaluate the effects of chlorinated organophosphate flame retardants (Cl-OPFRs) via respiratory and digestive tract exposure on multiple organs in mice.Methods:A short-term repeated exposure model of tris(2-chloroethyl) phosphate (TCEP), tris(1-chloro-2-propyl) phosphate (TCIPP) and tris(1, 3-dichloro-2-propyl) phosphate (TDCIPP) in mice was established through intratracheal instillation and oral gavage administration. The exposure doses were 0.7, 1 and 2 mg·kg -1·day -1, respectively, with continuous administration for 14 days. The organs of the heart, liver, spleen, lung, kidney, stomach, large intestine, small intestine, bladder and testis were collected and weighed to calculate the organ coefficients. The pathological and histological changes were observed by hematoxylin-eosin staining to quantitatively assess the effects of the three Cl-OPFRs on the various organs by using the pathology score. Results:Analysis of organ coefficients in tracheal drip-treated mice showed that the organ coefficients in the testes of the TCEP, TCIPP and TDCIPP groups were lower than those in the control group ( PTCEP-testis=0.045, PTCIPP-testis=0.012 and PTDCIPP-testis<0.001). The organ coefficients were lower in the lungs and small intestines of the TCEP group ( PTCEP-lung=0.006, PTCEP-small intestine=0.042). The organ coefficients for the stomach and large intestine were higher in the TDCIPP group ( PTDCIPP-stomach=0.014, PTDCIPP-large intestine=0.049). Analyses of gavage-contaminated mice showed that the organ coefficients for liver, stomach and small intestine in the TCEP and TDCIPP groups were higher than those in the control group ( PTCEP-liver=0.007, PTCEP-stomach=0.003, PTCEP-small intestine<0.001, PTDCIPP-liver=0.001, PTDCIPP-stomach=0.004, and PTDCIPP-small intestine<0.001). Histopathological analyses of the organs of tracheal drip dyed mice showed significant pathological damage in the lung tissue of the TCIPP group, mainly in the form of thickening of the interstitium, infiltration of inflammatory cells and alveolar collapse. The results of the analysis of gavage poisoned mice showed that TCIPP exposure could lead to blurring of the red and white medullary boundaries of spleen tissues, destruction of white medullary structures, etc., and induce small intestinal cryptitis. TDCIPP induced significant pathological damage to the liver tissues of mice, which mainly included cytoplasmic washout, infiltration of inflammatory cells, acute inflammation, and other injurious effects. Significant pathological damage to the intestinal tissues of mice was also observed. Conclusions:This study demonstrates that the toxic effects of Cl-OPFRs are significantly associated with exposure routes and compound specificity. Respiratory exposure predominantly induces TCIPP-mediated pulmonary injury, while digestive exposure causes TDCIPP-driven hepatointestinal toxicity. These findings provide preliminary evidence for the toxicity screening of Cl-OPFRs.
3.Application of artificial intelligence quantitative analysis in prognostic evaluation of patients with connective tissue disease-associated interstitial lung disease
Jingyu XU ; Chen CHU ; Shengnan ZHAO ; Ying WEI ; Feng SHI ; Zhengyang ZHOU
Journal of Practical Radiology 2025;41(7):1129-1133
Objective To explore the application of artificial intelligence quantitative analysis in the prognostic assessment of patients with connective tissue disease-associated interstitial lung disease(CTD-ILD).Methods A total of 67 patients with CTD-ILD were retrospectively selected.All subjects underwent high-resolution computed tomography(HRCT)scanning and were categorized into three groups,namely mild,moderate and severe groups,based on the results of pulmonary function tests.The survival rates of patients in each group were compared using Kaplan-Meier curves and analysis of variance.The univariate analysis was employed to assess the rela-tionships between artificial intelligence parameters and patient prognosis.Significant results were then incorporated into a multifacto-rial Cox regression model to construct the most accurate predictive model.Results A significant difference in survival rate was observed among the three groups(P<0.05).Univariate analysis revealed that the volume and percentage of lung infection in deceased patients were significantly greater than those in surviving patients,while the lung volume in deceased patients was significantly smaller than that in surviving patients.The analysis showed left lung volume and the percentage of lesion components CT value≤-750 HU as risk factors for prognosis,and the combination of these two factors as the most effective predictive model.Conclusion The artificial intelligence analysis system for lung lesions provides a new systematic and quantitative method for the prognostic assessment of CTD-ILD patients,which can be used for the prognostic assessment and follow-up of CTD-ILD patients.
4.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; 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(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
5.Toxic effects of chlorinated organophosphate flame retardants on mice via different exposure routes
Jialei ZHU ; Meiyu ZHOU ; Huanhuan ZHU ; Ruiyang TIAN ; Dahua REN ; Haiping LIU ; Xuanying JIANG ; Linfan XU ; Ying LU ; Haiyan CHU
Chinese Journal of Preventive Medicine 2025;59(7):1031-1039
Objective:To evaluate the effects of chlorinated organophosphate flame retardants (Cl-OPFRs) via respiratory and digestive tract exposure on multiple organs in mice.Methods:A short-term repeated exposure model of tris(2-chloroethyl) phosphate (TCEP), tris(1-chloro-2-propyl) phosphate (TCIPP) and tris(1, 3-dichloro-2-propyl) phosphate (TDCIPP) in mice was established through intratracheal instillation and oral gavage administration. The exposure doses were 0.7, 1 and 2 mg·kg -1·day -1, respectively, with continuous administration for 14 days. The organs of the heart, liver, spleen, lung, kidney, stomach, large intestine, small intestine, bladder and testis were collected and weighed to calculate the organ coefficients. The pathological and histological changes were observed by hematoxylin-eosin staining to quantitatively assess the effects of the three Cl-OPFRs on the various organs by using the pathology score. Results:Analysis of organ coefficients in tracheal drip-treated mice showed that the organ coefficients in the testes of the TCEP, TCIPP and TDCIPP groups were lower than those in the control group ( PTCEP-testis=0.045, PTCIPP-testis=0.012 and PTDCIPP-testis<0.001). The organ coefficients were lower in the lungs and small intestines of the TCEP group ( PTCEP-lung=0.006, PTCEP-small intestine=0.042). The organ coefficients for the stomach and large intestine were higher in the TDCIPP group ( PTDCIPP-stomach=0.014, PTDCIPP-large intestine=0.049). Analyses of gavage-contaminated mice showed that the organ coefficients for liver, stomach and small intestine in the TCEP and TDCIPP groups were higher than those in the control group ( PTCEP-liver=0.007, PTCEP-stomach=0.003, PTCEP-small intestine<0.001, PTDCIPP-liver=0.001, PTDCIPP-stomach=0.004, and PTDCIPP-small intestine<0.001). Histopathological analyses of the organs of tracheal drip dyed mice showed significant pathological damage in the lung tissue of the TCIPP group, mainly in the form of thickening of the interstitium, infiltration of inflammatory cells and alveolar collapse. The results of the analysis of gavage poisoned mice showed that TCIPP exposure could lead to blurring of the red and white medullary boundaries of spleen tissues, destruction of white medullary structures, etc., and induce small intestinal cryptitis. TDCIPP induced significant pathological damage to the liver tissues of mice, which mainly included cytoplasmic washout, infiltration of inflammatory cells, acute inflammation, and other injurious effects. Significant pathological damage to the intestinal tissues of mice was also observed. Conclusions:This study demonstrates that the toxic effects of Cl-OPFRs are significantly associated with exposure routes and compound specificity. Respiratory exposure predominantly induces TCIPP-mediated pulmonary injury, while digestive exposure causes TDCIPP-driven hepatointestinal toxicity. These findings provide preliminary evidence for the toxicity screening of Cl-OPFRs.
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.Effects and related mechanisms of neutrophil extracellular traps on proliferation and migration abilities of breast cancer
Ying ZHOU ; Huitao XU ; Huanhuan ZHANG ; Chu ZHANG ; Shaolin ZHAO ; Jin YANG
Cancer Research and Clinic 2025;37(2):93-100
Objective:To explore the effects of neutrophil extracellular traps (NET) on the proliferation and migration of breast cancer cells and the related mechanisms.Methods:The peripheral blood neutrophils were separated using density gradient centrifugation, 100 nmol/L phorbol 12-myristate 13-acetate (PMA) was used to stimulate the formation of NET. Breast cancer cell line MDA-MB-231 was selected and treated with NET (NET group) or deoxyribonucleaseⅠ (DNase Ⅰ) digested NET (NET+DNase Ⅰ group),normal cultured MDA-MB-231 cells were used as the control group. In MDA-MB-231 cells of each group; cell proliferation ability was detected using CCK-8 assay; cell migration was detected by cell scratch assay and Transwell assay; real-time quantitative polymerase chain reaction (qRT-PCR) was used to detect the relative expressions of frizzled homolog 10 (FZD10), cyclin D1, E-cadherin and Vimentin immunofluorescence assay was performed to detect the formation of NET and the expressions of E-cadherin and Vimentin; Western blotting was used to detected the expression of FZD10-Wnt-β-catenin signaling pathway-related proteins.Results:Neutrophils were stimulated with PMA for 4 hours, and immunofluorescence assay results showed that NET exhibited fibrous reticular structure with high expression of citrullinated histone (citH3) and myeloperoxidase (MPO). The CCK-8 assay results showed that the absorbance values of cells in the control group, NET group and NET+DNase Ⅰ group were 1.25±0.06, 2.14±0.15 and 1.47±0.11, respectively, and the difference was statistically significant ( F = 80.60, P < 0.001). The results of scratch assay displayed that the percentage of wound closure in the control group, NET group and NET+DNase Ⅰ group were (36.2±1.3)%, (67.2±2.0)% and (46.3±3.2)%, respectively, and the difference was statistically significant ( F = 140.50, P < 0.001). Transwell assay indicated that the number of migrating cells in the control group, NET group and NET+DNase Ⅰ group were 317±18, 512±23 and 356±23, respectively, and the difference was statistically significant ( F = 75.39, P < 0.001). qRT-PCR assay revealed that the relative expressions of FZD10, cyclin D1 and Vimentin mRNA in the NET group were higher than those in the control group, while the relative expression of E-cadherin mRNA was lower than that in the control group, and the differences were statistically significant (all P < 0.001); the relative expressions of FZD10, cyclin D1 and Vimentin mRNA in the NET+DNase Ⅰ group were lower than those in the NET group, while the relative expression of E-cadherin mRNA was higher than that in the NET group, and the differences were statistically significant (all P < 0.001). Immunofluorescence assay indicated that the number of cells expressing Vimentin in the control group, NET group and NET+DNase Ⅰ group were 35±6, 86±13 and 51±6, respectively, and the difference was statistically significant ( F = 24.65, P = 0.001); the number of cells expressing E-cadherin were 31±4, 11±3 and 24±2, respectively, and the difference was statistically significant ( F = 38.36, P < 0.001). Western blotting results demonstrated that the relative expressions of FZD10, β-catenin and Vimentin proteins in the NET group were higher than those in the control group, while the relative expression of E-cadherin protein was lower than that in the control group; the relative expressions of FZD10, β-catenin and Vimentin proteins in the NET+DNase Ⅰ group were lower than those in the NET group, while the relative expression of E-cadherin protein was higher than that in the NET group. Conclusions:NET may promote the proliferation and migration of breast cancer cells by upregulating the expression of FZD10 and subsequently activating the Wnt-β-catenin signal pathway.
9.USP20 as a super-enhancer-regulated gene drives T-ALL progression via HIF1A deubiquitination.
Ling XU ; Zimu ZHANG ; Juanjuan YU ; Tongting JI ; Jia CHENG ; Xiaodong FEI ; Xinran CHU ; Yanfang TAO ; Yan XU ; Pengju YANG ; Wenyuan LIU ; Gen LI ; Yongping ZHANG ; Yan LI ; Fenli ZHANG ; Ying YANG ; Bi ZHOU ; Yumeng WU ; Zhongling WEI ; Yanling CHEN ; Jianwei WANG ; Di WU ; Xiaolu LI ; Yang YANG ; Guanghui QIAN ; Hongli YIN ; Shuiyan WU ; Shuqi ZHANG ; Dan LIU ; Jun-Jie FAN ; Lei SHI ; Xiaodong WANG ; Shaoyan HU ; Jun LU ; Jian PAN
Acta Pharmaceutica Sinica B 2025;15(9):4751-4771
T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.
10.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.

Result Analysis
Print
Save
E-mail