1.Influencing factors of bladder management practices in patients with spinal cord injury
Zhirong LUO ; Xuyan GUO ; Qi XUE ; Xiao TAN ; Yunhua JI ; Fuxun ZHANG ; Yong JIAO ; Bo ZHANG
Journal of Modern Urology 2025;30(4):284-289
Objective: To explore the key factors affecting the selection and effectiveness of bladder management modalities in patients with spinal cord injury,so as to provide reference for the optimization of individualized bladder management strategies. Methods: The clinical and follow-up data of 78 patients with spinal cord injury treated in our hospital during Jan.1,2013 and Dec.31,2022 were retrospectively analyzed.The distribution of bladder management modalities among different grades of injuries was analyzed. Bowker symmetry test was used to evaluate the difference between bladder management modalities at discharge and at the end of follow-up. Multiple linear regression was used to explore the influencing factors of bladder management effects. Plotting Kaplan-Meier survival curves were adopted to calculate the median time of changes in bladder management. Results: At discharge,there were 9 cases of self-catheterization,19 cases of intermittent catheterization,22 cases of reflexive voiding,26 cases of long-term catheterization,and 2 cases using urinary collector.At the end of follow-up,there were 15 cases of self-catheterization,8 cases of intermittent catheterization,34 cases of reflexive voiding,14 cases of long-term catheterization,and 7 cases using urinary collector.There was a significant difference between the modalities of bladder management at discharge and at the end of follow-up (χ
=21.43,P=0.018).Multiple linear regression showed a significant decrease of 8.60 in the total neurogenic bladder symptom score (NBSS) for grade D injuries compared with grade A injuries (P=0.026). The median time to bladder management change was 7.93 months (95%CI:5.44-9.44), with approximately 50% of patients experiencing a change in bladder management within 8 months after discharge. Conclusion: The modalities of bladder management changed significantly after discharge.The grade of injury was a key factor affecting the effectiveness of bladder management.Higher grade was associated with worse effectiveness of bladder management.
2.Analysis of the causal relationship between gut microbiota and bladder cancer with Mendelian randomization
Xuyan GUO ; Zhirong LUO ; Qi XUE ; Yunhua JI ; Xiao TAN ; Yong JIAO
Journal of Modern Urology 2025;30(5):400-407
Objective: Previous observational studies have confirmed the correlation between gut microbiota and bladder cancer,but the causal relationship is still unclear.This study aimed to explore the causal relationship between them with Mendelian randomization. Methods: Genetic variation summary data of 211 gut microbiota and bladder cancer genome-wide association studies (GWAS) were obtained from the MiBioGen Consortium and Finngen database.Single nucleotide polymorphisms (SNPs) closely related to these studies were screened as instrumental variables.The causal relationship between gut microbiota and bladder cancer were analyzed with inverse variance weighting (IVW),MR-Egger,weighted median,maximum likelihood,robust adjustment feature score and MR-PRESSO,with IVW as the primary analysis method.Additionally,sensitivity analysis was used to test the heterogeneity (Cochran Q) and horizontal pleiotropy (MR-Egger intercept term and global test from MR-PRESSO estimator) to ensure the robustness of the results. Results: The IVW results indicated that Lachnospiraceae UCG004 (OR:1.42),Desulfovibrionales (Order) (OR:1.48),Eubacterium ruminantium group (OR:1.33),Olsenella (OR:1.24),Ruminococcaceae UCG002 (OR:1.39),Ruminococcaceae UCG005 (OR:1.42) and Ruminococcaceae UCG013 (OR:1.64) significantly increased the risk of bladder cancer.Conversely,Bacteroidetes (Phylum) (OR:0.61),Eubacterium brachy group (OR:0.80),Ruminococcaceae UCG004 (OR:0.73),Rikenellaceae (Family) (OR:0.67),Lachnospiraceae ND3007 group (OR:0.47), Adlercreutzia (OR:0.73) and an unknow genus (OR:0.75) were associated with a reduced risk of bladder cancer.Sensitivity analyses did not reveal any heterogeneity or horizontal pleiotropy. Conclusion: This study reveals the causal role of 14 gut microbiota in the pathogenesis of bladder cancer,among which Lachnospiraceae UCG004,Desulfovibrionales (Order),Eubacterium ruminantium group,Olsenella,Ruminococcaceae UCG002,Ruminococcaceae UCG005 and Ruminococcaceae UCG013 are risk factors for bladder cancer,while Bacteroidetes (Phylum),Eubacterium brachy group,Ruminococcaceae UCG004,Rikenellaceae (Family),Lachnospiraceae ND3007 group,Adlercreutzia and an unknown genus are the protective factors.
3.Potential utility of albumin-bilirubin and body mass index-based logistic model to predict survival outcome in non-small cell lung cancer with liver metastasis treated with immune checkpoint inhibitors.
Lianxi SONG ; Qinqin XU ; Ting ZHONG ; Wenhuan GUO ; Shaoding LIN ; Wenjuan JIANG ; Zhan WANG ; Li DENG ; Zhe HUANG ; Haoyue QIN ; Huan YAN ; Xing ZHANG ; Fan TONG ; Ruiguang ZHANG ; Zhaoyi LIU ; Lin ZHANG ; Xiaorong DONG ; Ting LI ; Chao FANG ; Xue CHEN ; Jun DENG ; Jing WANG ; Nong YANG ; Liang ZENG ; Yongchang ZHANG
Chinese Medical Journal 2025;138(4):478-480
4.Vitamin D supplementation inhibits atherosclerosis through repressing macrophage-induced inflammation via SIRT1/mTORC2 signaling.
Yuli WANG ; Qihong NI ; Yongjie YAO ; Shu LU ; Haozhe QI ; Weilun WANG ; Shuofei YANG ; Jiaquan CHEN ; Lei LYU ; Yiping ZHAO ; Meng YE ; Guanhua XUE ; Lan ZHANG ; Xiangjiang GUO ; Yinan LI
Chinese Medical Journal 2025;138(21):2841-2843
5.Association of Body Mass Index with All-Cause Mortality and Cause-Specific Mortality in Rural China: 10-Year Follow-up of a Population-Based Multicenter Prospective Study.
Juan Juan HUANG ; Yuan Zhi DI ; Ling Yu SHEN ; Jian Guo LIANG ; Jiang DU ; Xue Fang CAO ; Wei Tao DUAN ; Ai Wei HE ; Jun LIANG ; Li Mei ZHU ; Zi Sen LIU ; Fang LIU ; Shu Min YANG ; Zu Hui XU ; Cheng CHEN ; Bin ZHANG ; Jiao Xia YAN ; Yan Chun LIANG ; Rong LIU ; Tao ZHU ; Hong Zhi LI ; Fei SHEN ; Bo Xuan FENG ; Yi Jun HE ; Zi Han LI ; Ya Qi ZHAO ; Tong Lei GUO ; Li Qiong BAI ; Wei LU ; Qi JIN ; Lei GAO ; He Nan XIN
Biomedical and Environmental Sciences 2025;38(10):1179-1193
OBJECTIVE:
This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study.
METHODS:
A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants.
RESULTS:
Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m 2) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m 2) and obesity (≥ 28.0 kg/m 2) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m 2 ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses.
CONCLUSION
This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans
;
Body Mass Index
;
China/epidemiology*
;
Male
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Female
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Middle Aged
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Prospective Studies
;
Rural Population/statistics & numerical data*
;
Aged
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Follow-Up Studies
;
Adult
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Mortality
;
Cause of Death
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Obesity/mortality*
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Overweight/mortality*
6.Angiotensin Ⅱ type 1 receptor autoantibody-AT1R-Bmal1 axis promotes phenotypic transition of vascular smooth muscle cells and vascular fibrosis
Lingxia XUE ; Yaolin LONG ; Jiayan FENG ; Tian MAO ; Jiao GUO ; Zhuoxi WANG ; Yang LI ; Xiaohui WANG ; Li WANG
Journal of Army Medical University 2025;47(11):1155-1164
Objective To investigate the mechanism by which angiotensin Ⅱ type 1 receptor autoantibody(AT1-AA)promotes phenotypic switch of vascular smooth muscle cells(VSMCs)and vascular fibrosis through abnormal expression of circadian clock protein BMAL1.Methods Twelve male SD rats(6~8 weeks old,weighing 180~220 g)were randomly divided into(n=6)a control group and an AT1-AA-positive group[established by active immunization of SD rats with AT1R extracellular loop Ⅱ peptide(AT1R-ECLⅡ)].HE and Masson stainings were used to observe structural changes and fibrosis in the thoracic aorta(n=3).Western blotting was performed to detect the expression of Collagen I,phenotypic switch-related proteins(SM22,α-SMA,OPN and MMP2)in vascular tissues and primary VSMCs(n=4),as well as the expression of BMAL1 at CT0,CT4,CT8,CT12,CT16,and CT20.Transwell and scratch assays were used to assess the proliferation and migration of VSMCs(n=3).si-RNA was employed to knock down Bmal1,followed by detection of BMAL1,Collagen I,and phenotypic conversion-related protein expression(n=3).Additionally,AT1-AA-positive AT1R-knockout(AT1R-KO)rats were constructed to measure BMAL1 expression in thoracic aortic tissues(n=4).Results The AT1-AA-positive rats had significantly thickened thoracic aortic vessel wall[(140±9)%vs(120±5)%,P<0.05],badly arranged VSMCs,obvious blue Masson staining,and up-regulated Collagen I expression(P<0.05).In the thoracic aorta of AT1-AA-positive rats and AT1-AA-treated VSMCs,the expression of contractile phenotype-related proteins(α-SMA,SM22)was decreased(P<0.05),while the expression of synthetic phenotype-related proteins(OPN,MMP2)was increased(P<0.05).AT1-AA enhanced the scratch healing ability and migration ability of VSMCs.Furthermore,both mRNA and protein levels of Bmal1 were significantly up-regulated at CT12(P<0.05),and the rhythmicity of Bmal1 was lost.Knockdown of Bmal1 partially ameliorated AT1-AA-induced phenotypic switch of VSMCs.Compared with AT1-AA-positive WT rats,AT1-AA-positive AT1R-KO rats showed significantly reduced BMAL1 expression in the thoracic aorta(1.35±0.06 vs 0.86±0.07,P<0.001).At the cellular level,AT1-AA-induced phenotypic switch and high Collagen I expression in VSMCs were partially improved in AT1R-KO VSMCs.Conclusion AT1-AA promotes VSMCs phenotypic conversion and vascular fibrosis through the AT1R-Bmal1 axis.
7.Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators
Zhaoyu GUO ; Juping SHAO ; Xiaoqing ZOU ; Qinping ZHAO ; Peijun QIAN ; Wenya WANG ; Lulu HUANG ; Jingbo XUE ; Jing XU ; Kun YANG ; Xiaonong ZHOU ; Shizhu LI
Chinese Journal of Schistosomiasis Control 2024;36(3):251-258
Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.
8.A novel chalcone derivative C13 inhibits the growth of human gastric cancer cells through suppressing ErbB4/PI3K/AKT signaling pathway
Peng TAN ; Yun-feng ZHANG ; Long-yan WANG ; Hui-ming HUANG ; Fei WANG ; Xue-jiao WEI ; Zhu-guo WANG ; Jun LI ; Zhong-dong HU
Acta Pharmaceutica Sinica 2024;59(4):957-964
3ʹ-Hydroxy-4ʹ-methoxy-2-hydroxy-5-bromochalcone (hereinafter referred to as C13) is a novel chalcone derivative obtained in the process of structural modification of DHMMF, the antitumor active compound of
9.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.
10.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.

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