1.Zuoguiwan Mitigates Oxidative Stress in Rat Model of Hyperthyroidism Due to Kidney-Yin Deficiency via DRD4/NOX4 Pathway
Ling LIN ; Qianming LIANG ; Changsheng DENG ; Li RU ; Zhiyong XU ; Chao LI ; Mingshun SHEN ; Yueming YUAN ; Muzi LI ; Lei YANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(2):43-51
ObjectiveTo decipher the mechanism by which Zuoguiwan (ZGW) treat hyperthyroidism in rats with kidney-Yin deficiency based on the dopamine receptor D4 (DRD4)/nicotinamide adenine dinucleotide phosphate (NADPH) oxidase 4 (NOX4) signaling pathway. MethodsThe rat model of kidney-Yin deficiency was induced by unilateral intramuscular injection of dexamethasone (0.35 mg·kg-1). After successful modeling, the rats were randomized into model, methimazole (positive control, 5 mg·kg-1), low-, medium-, and high-dose (1.85, 3.70, 7.40 g·kg-1, respectively) ZGW, and normal control groups. After 21 days of continuous gavage, the behavioral indexes and body weight changes of rats were evaluated. The pathological changes of the renal tissue were observed by hematoxylin-eosin staining. The serum levels of thyroid hormones [triiodothyronine (T3), thyroxine (T4), thyroid-stimulating hormone (TSH)], renal function indexes [serum creatine (Scr) and blood urea nitrogen (BUN)], energy metabolism markers [cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP)], and oxidative stress-related factors [superoxide dismutase (SOD), malondialdehyde (MDA), and NADPH)] were measured by enzyme-linked immunosorbent assay (ELISA). Western blot was employed to analyze the expression of DRD4, NOX4, mitochondrial respiratory chain complex proteins [NADH:ubiquinone oxidoreductase subunit S4 (NDUFS4) and cytochrome C oxidase subunit 4 (COX4)], and inflammation-related protein [tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), p38 mitogen-activated protein kinase (MAPK)] pathway in the renal tissue. ResultsCompared with the normal group, the model group showed mental malaise, body weight decreases (P<0.01), inflammatory cell infiltration in the renal tissue, a few residual parotid glands in the thyroid, elevations in serum levels of T3, T4, Scr, BUN, cAMP, cAMP/cGMP, MDA, and NADPH (P<0.01), down-regulation in protein levels of TSH, SOD, and DRD4 (P<0.05, P<0.01), and up-regulation in expression of NOX4, p-p38 MAPK/p38 MAPK, and inflammatory factors (P<0.01). Compared with the model group, ZGW increased the body weight (P<0.05, P<0.01), reduced the infiltration of renal interstitial inflammatory cells, restored the thyroid structure and follicle size, lowered the serum levels of T3, T4, Scr, BUN, cAMP, cAMP/cGMP, MDA and NADPH (P<0.05, P<0.01), up-regulated the expression of TSH, SOD and DRD4 (P<0.05, P<0.01), and down-regulated the expression of NOX4, p-p38 MAPK/p38 MAPK, and inflammatory factors (P<0.05, P<0.01). Moreover, high-dose ZGW outperformed methimazole (P<0.05). ConclusionBy activating DRD4, ZGW can inhibit the expression of NOX4 mediated by the p38 MAPK pathway, reduce oxidative stress and inflammatory response, thereby ameliorating the pathological state of hyperthyroidism due to kidney-Yin deficiency. This study provides new molecular mechanism support for the clinical application of ZGW.
2.Risk of chronic kidney disease in the population aged 60 and above with hypertension and diabetes in Nanjing based on LASSO-logistic regression model
Yucheng HUANG ; Caihong HU ; Huiqing XU ; Ruikang CHEN ; Guofeng AO ; Zhiyong WANG
Journal of Public Health and Preventive Medicine 2026;37(1):98-102
Objective To construct a prediction model for the population with hypertension and diabetes to assess the risk of chronic kidney disease (CKD), and to provide a scientific basis for formulating targeted CKD prevention and control measures. Methods Based on physical examination data from community residents aged 60 years and above in Nanjing in 2022, 10 221 patients with hypertension and diabetes were selected as the study subjects. Variables associated with CKD prevalence were screened using univariate analysis, and further variable selection was performed using LASSO regression. Finally, a CKD risk prediction model was constructed based on logistic regression. The model's performance was evaluated using the ROC curve and calibration curve. Results The prevalence rate of CKD in the study population was 22.71%, with a mean age of 71.66 years. LASSO regression identified seven variables associated with CKD: age, blood urea nitrogen (BUN), hemoglobin, uric acid, triglyceride-glucose (TyG) index, urine protein-to-creatinine ratio (UPCR), and medical insurance type. The final logistic regression model incorporated six variables: age [OR=1.067 (95% CI: 1.058-1.076)], BUN [OR=1.377 (95% CI: 1.338-1.418)], hemoglobin [OR=0.992 (95% CI: 0.989-0.995)], uric acid [OR=1.004 (95% CI: 1.003-1.004)], TyG index [OR=1.445 (95% CI: 1.324-1.577)], and self-payment medical insurance [OR=1.732 (95% CI: 1.542-1.945)]. The model had an AUC of 0.759 (95% CI: 0.747-0.770) and a Brier score of 0.140 (95% CI: 0.136-0.145), indicating good predictive performance. The calibration curve showed good agreement between the predicted risk and the observed value. Conclusion The constructed LASSO-logistic regression risk prediction model in this study can effectively assess the risk of CKD in elderly individuals aged 60 years and above with hypertension and diabetes, providing a basis for early identification of high-risk individuals and the formulation of targeted CKD prevention and control measures.
3.Construction and validation of circadian rhythm genes-related prognostic risk model for lung adenocarcinoma
Yanqi CUI ; Hu ZHAO ; Yawei ZHANG ; Lin NI ; Duohuang LIAN ; Jingrong YANG ; Shixin YE ; Fengfeng XU ; Jincan ZHANG ; Zhiyong ZENG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(04):550-558
Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.
4.Mechanism of the interaction between immunosuppressive therapy and intestinal microflora after liver transplantation
Yan WANG ; Yufeng LIU ; Haiyang ZHANG ; Zhiwei ZHANG ; Jun XU ; Zhiyong LAI
Journal of Clinical Hepatology 2026;42(4):980-986
The application of immunosuppressants has significantly reduced the incidence rate of rejection reaction after liver transplantation, but the clinical efficacy of immunosuppressants is greatly affected by individual differences between patients. This article systematically reviews the recent research advances in the interaction between immunosuppressants and gut microbiota, with a focus on the regulatory role and mechanism of intestinal microflora communities on the efficacy of immunosuppressants. Studies have shown that intestinal microbiome is one of the key factors influencing the efficacy of immunosuppressive therapy after liver transplantation. This review aims to provide a theoretical basis for in-depth research in this field and provide new insights for developing individualized immunosuppressive treatment regimens based on the regulation of intestinal microflora.
5.Construction and validation of a machine learning-based risk assessment model for post-transplant diabetes mellitus
Hao WANG ; Yongqiang FAN ; Zhiyong SHI ; Rui ZHANG ; Yan WANG ; Jun XU
Journal of Clinical Hepatology 2026;42(8):1894-1901
ObjectiveTo construct and validate a risk assessment model for post-transplant diabetes mellitus (PTDM) using multiple machine learning algorithms, and to realize the early identification of PTDM. MethodsA retrospective analysis was performed for the clinical data of the patients who underwent allogeneic liver transplantation in The First Hospital of Shanxi Medical University from April 1, 2020 to December 31, 2024, and they were randomly divided into a training set and a validation set at a ratio of 7∶3. The LASSO regression analysis combined with 5-fold cross-validation was used for feature selection. Seven machine learning models were developed in the training set, i.e., logistic regression (LR), decision tree (DT), Naive Bayes (NB), random forest (RF), K-nearest neighbor (KNN), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost). In the validation set, various methods were used to assess the predictive performance of each model, such as accuracy, precision, recall rate, specificity, F1 score, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC). The Brier score and decision curve analysis were used to assess the calibration and clinical practicability of the models, and the SHAP method was used to analyze feature importance. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups, and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsA total of 135 liver transplant recipients were enrolled, among whom 26 developed PTDM, and there were 94 patients in the training set and 41 in the validation set. Feature extraction and screening identified 7 key features of sex, overweight or obesity, anhepatic phase, time of operation, length of hospital stay, early postoperative hypomagnesemia, and impaired fasting glucose (IFG). In the validation set, the XGBoost model showed the best predictive performance, with an AUROC of 0.907 (95% confidence interval [CI]: 0.807 — 0.989), an AUPRC of 0.649 (95%CI: 0.339 — 0.955), an accuracy of 0.878, a precision of 0.667, a recall rate of 0.750, an F1-score of 0.706, a specificity of 0.909, and a Brier score of 0.104. The decision curve analysis showed that when the threshold probability was below 0.667, application of the XGBoost model in clinical decision-making provided relatively high net benefit. The SHAP analysis showed that the length of hospital stay ranked first in terms of feature importance, followed by time of operation, overweight or obesity, sex, IFG, anhepatic phase, and early postoperative hypomagnesemia. ConclusionThe risk assessment model for PTDM in liver transplant recipients based on XGBoost algorithm has excellent performance and can effectively identify high-risk individuals; however, multicenter large-sample data are needed for further validation.
6.Effect of Serum Containing Zhenwutang on Apoptosis of Myocardial Mast Cells and Mitochondrial Autophagy
Wei TANG ; Meiqun ZHENG ; Xiaolin WANG ; Zhiyong CHEN ; Chi CHE ; Zongqiong LU ; Jiashuai GUO ; Xiaomei ZOU ; Lili XU ; Lin LI
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(3):11-21
ObjectiveTo explore the effect of serum containing Zhenwutang on myocardial mast cell apoptosis induced by angiotensin Ⅱ (AngⅡ) and the mechanism of the correlation between apoptosis and mitochondrial autophagy. MethodsIn this experiment, AngⅡ and serum containing Zhenwutang with different concentrations were used to interfere with H9C2 cardiomyocytes for 24 h, and the survival rate of H9C2 cardiomyocytes was detected by cell counting kit-8 (CCK-8) to screen the optimal concentration for the experiment. Enzyme-linked immunosorbent assay (ELISA) was used to detect the content of B-type natriuretic peptide (BNP) in cell culture supernatant, and immunofluorescence was used to detect the cell surface area to verify the construction of the myocardial mast cell model. Subsequently, the experiment was divided into a blank group (20% blank serum), a model group (20% blank serum + 5×10-5 mol·L-1 AngⅡ), low-, medium-, and high-dose (5%, 10% and 20%) serum containing Zhenwutang groups, an autophagy inhibitor group (1×10-4 mol·L-1 3-MA), and autophagy inducer group (1×10-7 mol·L-1 rapamycin). The apoptosis level of H9C2 cells and the changes of mitochondrial membrane potential were detected by flow cytometry. The lysosomal probe (Lyso Tracker) and mitochondrial probe (Mito Tracker) co-localization was employed to detect autophagy. Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR) was used to detect Caspase-3, Caspase-9, B-cell lymphoma 2 (Bcl-2), Bcl-2-related X protein (Bax), and cytochrome C (Cyt C) in apoptosis-related pathways and the relative mRNA expression of ubiquitin ligase (Parkin), phosphatase and tensin homolog (PTEN)-induced kinase 1 (PINK1), and p62 protein in mitochondrial autophagy-related pathways. Western blot was used to detect cleaved Caspase-3, cleaved Caspase-9, Bax, Bcl-2, and Cyt C in apoptosis-related pathways, phosphorylated ubiquitin ligase (p-Parkin), phosphorylated PTEN-induced kinase 1 (p-PINK1), p62, and Bcl-2 homology domain protein Beclin1 in mitochondrial autophagy-related pathways, and the change of microtubule-associated protein 1 light chain 3 (LC3) Ⅱ/Ⅰ ratio. ResultsCCK-8 showed that when the concentration of AngⅡ was 5×10-5 mol·L-1, the cell activity was the lowest, and there was no cytotoxicity. At this concentration, the surface area of cardiomyocytes was significantly increased (P<0.01), and the content of BNP in the supernatant of culture medium was significantly increased (P<0.05). Therefore, AngⅡ with a concentration of 5×10-5 mol·L-1 was selected for the subsequent modeling of myocardial mast cells. Compared with the blank group, the model group and the autophagy inhibitor 3-MA group had a significantly increased apoptosis rate (P<0.01) and significantly decreased mitochondrial membrane potential (P<0.01). The results of immunofluorescence co-localization showed that compared with the blank group, the model group had a significantly decreased number of red and green fluorescence spots. The results of Real-time PCR showed that compared with that in the blank group, the relative mRNA expression of Bax, Caspase-3, Caspase-9, Cyt C, and p62 in the model group was significantly up-regulated (P<0.01), while the relative mRNA expression of Bcl-2, Parkin, and PINK1 was significantly down-regulated (P<0.01). In addition, the relative protein expression of Bax, cleaved Caspase-3, cleaved Caspase-9, Cyt C, and p62 was significantly up-regulated (P<0.01). The LC3Ⅱ/Ⅰ was significantly decreased, and the relative protein expression of Bcl-2, p-Parkin, p-PINK1, and Beclin1 was significantly down-regulated (P<0.01). Compared with the model group, the serum containing Zhenwutang groups and the autophagy inducer group had significantly decreased apoptosis rate (P<0.01), and the decrease ratio of mitochondrial membrane potential is significantly lowered (P<0.01) in a dose-dependent manner. Additionally, both red and green fluorescence spots became more in these groups. In the 3-MA group, the number of red and green fluorescence spots decreased significantly. The relative mRNA expression of Bax, Caspase-3, Caspase-9, Cyt C, and p62 was significantly down-regulated (P<0.05, P<0.01), while that of Bcl-2, Parkin, and PINK1 was significantly up-regulated (P<0.01). In the serum containing Zhenwutang groups, the relative protein expression levels of Bax, cleaved Caspase-3, cleaved Caspase-9, Cyt C, and p62 were significantly down-regulated (P<0.05,P<0.01). The LC3Ⅱ/Ⅰ was significantly increased, and the relative protein expression levels of Bcl-2, p-Parkin, p-PINK1, and Beclin1 were significantly up-regulated (P<0.01). ConclusionThe serum containing Zhenwutang can reduce the apoptosis of myocardial mast cells and increase mitochondrial autophagy. This is related to the inhibition of intracellular Bax/Bcl-2/Caspase-3 apoptosis pathway and regulation of Parkin/PINK1 mitochondrial autophagy pathway.
7.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.
8.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.
9.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.
10.Lycorine hydrochloride directly targets UBA1 to suppress cellular senescence.
Jiaqing YANG ; Junhao XU ; Ziheng QIU ; Zhiyong MAO ; Xiaojun XU ; Ying JIANG ; Guizhu WU
Acta Pharmaceutica Sinica B 2025;15(3):1696-1699


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