1.The Role and Mechanism of Circadian Rhythm Regulation in Skin Tissue Regeneration
Ya-Qi ZHAO ; Lin-Lin ZHANG ; Xiao-Meng MA ; Zhen-Kai JIN ; Kun LI ; Min WANG
Progress in Biochemistry and Biophysics 2025;52(5):1165-1178
Circadian rhythm is an endogenous biological clock mechanism that enables organisms to adapt to the earth’s alternation of day and night. It plays a fundamental role in regulating physiological functions and behavioral patterns, such as sleep, feeding, hormone levels and body temperature. By aligning these processes with environmental changes, circadian rhythm plays a pivotal role in maintaining homeostasis and promoting optimal health. However, modern lifestyles, characterized by irregular work schedules and pervasive exposure to artificial light, have disrupted these rhythms for many individuals. Such disruptions have been linked to a variety of health problems, including sleep disorders, metabolic syndromes, cardiovascular diseases, and immune dysfunction, underscoring the critical role of circadian rhythm in human health. Among the numerous systems influenced by circadian rhythm, the skin—a multifunctional organ and the largest by surface area—is particularly noteworthy. As the body’s first line of defense against environmental insults such as UV radiation, pollutants, and pathogens, the skin is highly affected by changes in circadian rhythm. Circadian rhythm regulates multiple skin-related processes, including cyclic changes in cell proliferation, differentiation, and apoptosis, as well as DNA repair mechanisms and antioxidant defenses. For instance, studies have shown that keratinocyte proliferation peaks during the night, coinciding with reduced environmental stress, while DNA repair mechanisms are most active during the day to counteract UV-induced damage. This temporal coordination highlights the critical role of circadian rhythms in preserving skin integrity and function. Beyond maintaining homeostasis, circadian rhythm is also pivotal in the skin’s repair and regeneration processes following injury. Skin regeneration is a complex, multi-stage process involving hemostasis, inflammation, proliferation, and remodeling, all of which are influenced by circadian regulation. Key cellular activities, such as fibroblast migration, keratinocyte activation, and extracellular matrix remodeling, are modulated by the circadian clock, ensuring that repair processes occur with optimal efficiency. Additionally, circadian rhythm regulates the secretion of cytokines and growth factors, which are critical for coordinating cellular communication and orchestrating tissue regeneration. Disruptions to these rhythms can impair the repair process, leading to delayed wound healing, increased scarring, or chronic inflammatory conditions. The aim of this review is to synthesize recent information on the interactions between circadian rhythms and skin physiology, with a particular focus on skin tissue repair and regeneration. Molecular mechanisms of circadian regulation in skin cells, including the role of core clock genes such as Clock, Bmal1, Per and Cry. These genes control the expression of downstream effectors involved in cell cycle regulation, DNA repair, oxidative stress response and inflammatory pathways. By understanding how these mechanisms operate in healthy and diseased states, we can discover new insights into the temporal dynamics of skin regeneration. In addition, by exploring the therapeutic potential of circadian biology in enhancing skin repair and regeneration, strategies such as topical medications that can be applied in a time-limited manner, phototherapy that is synchronized with circadian rhythms, and pharmacological modulation of clock genes are expected to optimize clinical outcomes. Interventions based on the skin’s natural rhythms can provide a personalized and efficient approach to promote skin regeneration and recovery. This review not only introduces the important role of circadian rhythms in skin biology, but also provides a new idea for future innovative therapies and regenerative medicine based on circadian rhythms.
2.Feasibility study of using clinical trial individual-level data sample bank as external control to support drug and device development:taking transcatheter aortic valve replacement device as an example
Xiao-ying LIN ; Chi-lie DANZENG ; Duo-er WANG ; Ying-xuan ZHU ; Ye LU ; Fan GAO ; Yuan-xin LI ; Meng-zhu SU ; Zi-long ZHANG ; Min CHEN ; Qi-ze LI ; Ru JIANG ; Yan-yan ZHAO ; Yang WANG
Chinese Journal of Interventional Cardiology 2025;33(8):459-466
Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.
3.Epidemiology and survival analysis of nasopharynx cancer in Guangdong Province from 2011 to 2019
Yu LIAO ; Xinrui SONG ; Lifeng LIN ; Ye WANG ; Yanjun XU ; Bingfeng HAN ; Minkun LIU ; Danqi CHEN ; Dejian ZHAO ; Xiaojun XU ; Ruilin MENG ; Wenqiang WEI
Chinese Journal of Oncology 2025;47(4):322-328
Objective:To analyze the epidemiological characteristics and survival rate of nasopharynx cancer (NPC) in Guangdong Province from 2011 to 2019.Methods:Based on the cancer registry data of Guangdong Province from 2011 to 2019, the crude rate, age-standardized rate (the standard population was the fifth Chinese national census of 2000) and age-specific rate of incidence and mortality of NPC were calculated, and the regional distribution characteristics were also explored. The average annual percentage change (AAPC) of the incidence and mortality rates were analyzed by using Joinpoint regression model. The observed survival rate was estimated by period survival method, and the expected survival rate was calculated by Ederer Ⅱ method.Results:The crude incidence rate and age standardized incidence rate of NPC showed a decreasing trend, and the AAPC was -1.9% and -2.1%, respectively ( P<0.05). The crude mortality rate and age standardized mortality rate of NPC also showed a decreasing trend, and the AAPC was -4.8% and -4.6%, respectively ( P<0.05). The incidence and mortality rates are both higher in men than those in women during the nine years. The age-specific incidence rate of NPC reached its peak in the 50-64 years old age group, and the mortality rate reached its peak in the 65-74 years old age group in Guangdong province. In 2019, the age-standardized incidence rate of NPC was 9.49/100 000 (13.89/100 000 in men and 5.19/100 000 in women). The incidence and mortality of NPC varied greatly among different areas, and the areas with highest incidence and mortality rate were both in Zhaoqing. In 2020, the five-year observed survival rate of NPC in Guangdong Province was 67.2%, the 5-year relative survival rate was 75.3% and the 5-year standardized relative survival rate was 68.9%. Conclusions:Both the incidence and mortality rates of NPC in Guangdong province show decreasing trend, and the decreasing level of the mortality rate is higher than that of the incidence rate, but the two rates are still at high levels. The prevention and control work should focus on male, middle-aged and elderly population and Zhaoqing, Zhongshan, Foshan areas.
4.Quality evaluation of Gegen Formula Granules
Dai-liang ZHANG ; Chun-xia WANG ; Lei SHI ; Yu-kang LIU ; Yong-qiang LIN ; Yu-zhuo WANG ; Jing-hua ZHANG ; Jin-xin LI ; Gui-yun CAO ; Zhao-qing MENG
Chinese Traditional Patent Medicine 2025;47(5):1421-1431
AIM To evaluate the quality of Gegen Formula Granules.METHODS Linear calibration with two reference substances(LCTRS)was adopted in the predicting of retention time with puerarin and daidzein as internal standards.UPLC characteristic chromatograms were established.The contents of 3'-hydroxy puerarin,puerarin(internal standard),3'-methoxy puerarin,puerarin 6"-O-xyloside,puerarin apioside and daidzin were determined by quantitative determination analysis multi-components by a single marker(QAMS),after which their transfer rates were calculated.RESULTS Compared with relative retention time method,LCTRS demonstrated higher positional accuracy for characteristic peaks and wider application range for columns.There were 9 characteristic peaks in the characteristic chromatograms for 14 batches of formula granules and 15 batches of standard decoctions with the similarities of more than 0.95.The contents and transfer rates of various constituents in formula granules and standard decoctions were basically consistent.CONCLUSION The chemical constituents in formula granules and their standard decoctions of Puerariae lobatae Radix display good consistency,reliable preparation process is observable in the former.
5.Bibliographical cataloging for ancient TCM books
Hongtao LI ; Weina ZHANG ; Lin TONG ; Jingpeng DENG ; Qian ZHAO ; Honglei WANG ; Naiying LIU ; Mei SHI ; Qiang LIU ; Ying LIN ; Xiaohong ZHANG ; Lili FENG ; Mingrui ZHANG ; Yanqiu LUO ; Guangkun CHEN ; Yan DONG ; Bin LI ; Sihong LIU ; Bing LI ; Chen LI ; Meng LI ; Rui WANG ; He LU
International Journal of Traditional Chinese Medicine 2025;47(6):729-740
With reference to the Information and Documentation-Resource Description (GB/T 3792-2021) and Bibliographical Description for Ancient Chinese Books (GB/T 3792.7-2008) and other cataloging standards and rules, drawing on the practical experience of cataloging ancient TCM books, Bibliographical Cataloging for Ancient TCM Books was formulated. This standard specifies the entry items and their order of ancient TCM books, cataloging identifier, cataloging text, cataloging information source, and cataloging item details. The standard can provide standardized and unified guiding principles and methods for the work of ancient TCM books, and promote the sharing and utilization of ancient TCM books.
6.Shenfu Injection Improve Chronic Heart Failure by Regulates Glycolytic Pathway Mediated by HIF-1α/PFKFB3 Pathway
Ji OUYANG ; Kun LIAN ; Xiaoqian LIAO ; Lichong MENG ; Lin LI ; Zhenyu ZHAO ; Zhixi HU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(16):136-145
ObjectiveThis study aims to explore the mechanism and targets of Shenfu Injection in regulating glycolysis to intervene in myocardial fibrosis in chronic heart failure based on the hypoxia-inducible factor-1α (HIF-1α)/ 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3) signaling pathway. MethodsA rat model of chronic heart failure was established by subcutaneous injection of isoproterenol (ISO). After successful modeling, the rats were randomly divided into the Sham group, Model group, Shenfu injection (SFI, 6 mL·kg-1) group, and inhibitor (3PO, 35 mg·kg-1) group, according to a random number table, and they were treated for 15 days. Cardiac function was evaluated by echocardiography, and serum N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were detected by enzyme-linked immunosorbent assay (ELISA). Fasting body weight and heart weight were measured, and the heart index (HI) was calculated. Pathological changes in myocardial tissue were observed by hematoxylin-eosin (HE) and Masson staining, and the fibrosis rate was calculated. Biochemical assays were used to determine serum levels of glucose (GLU), lactic acid (LA), and pyruvic acid (PA). Western blot was used to analyze the expression of proteins related to the HIF-1α/PFKFB3 signaling pathway (HIF-1α and PFKFB3), glycolysis-related proteins (HK1, HK2, PKM2, and LDHA), and fibrosis-related proteins [transforming growth factor (TGF)-β1, α-smooth muscle actin (α-SMA), and Collagen type Ⅰ α1 (ColⅠA1)]. Real-time PCR was used to detect the mRNA expression of HIF-1α and PFKFB3 in myocardial tissue. ResultsCompared with the Sham group, the Model group showed significantly decreased left ventricular ejection fraction (LVEF), left ventricular shortening fraction (LVFS), interventricular septal thickness (IVSd), and interventricular septal strain (IVSs) (P<0.05), while left ventricular internal dimension at end-diastole (LVDd) and end-systole (LVIDs) were increased (P<0.05). Serum NT-proBNP levels were significantly increased (P<0.01), and body weight was decreased. Heart weight was increased, and the HIT index was increased (P<0.05). Myocardial tissue exhibited inflammatory cell infiltration and collagen fiber deposition, and the fibrosis rate was significantly increased (P<0.05). Serum GLU was decreased (P<0.05), while LA and PA levels were increased (P<0.05). Protein expressions of HIF-1α, PFKFB3, HK1, HK2, PKM2, LDHA, TGF-β1, α-SMA, and ColⅠA1, as well as the mRNA expression of HIF-1α and PFKFB3 were increased (P<0.05). Compared with the Model group, both the SFI group and 3PO groups showed significant improvements in LVEF, LVFS, IVSd, and IVSs (P<0.05) and decreases in LVDd, LVIDs, and NT-proBNP levels (P<0.05). Body weight was significantly increased. Heart weight was significantly decreased, and the HIT index was significantly decreased (P<0.05). Inflammatory cell infiltration, collagen fiber deposition, and the fibrosis rate were significantly decreased (P<0.05). Serum GLU levels were significantly increased (P<0.05), while LA and PA levels were decreased (P<0.05). Expressions of glycolysis-related proteins, fibrosis-related proteins, and HIF-1α/PFKFB3 pathway-related proteins and mRNAs were significantly suppressed (P<0.05). ConclusionSFI improves cardiac function in chronic heart failure by downregulating the expression of HIF-1α/PFKFB3 signaling pathway-related proteins, regulating glycolysis, and inhibiting myocardial fibrosis.
7.Application Value of an AI-based Imaging Feature Parameter Model for Predicting the Malignancy of Part-solid Pulmonary Nodule.
Mingzhi LIN ; Yiming HUI ; Bin LI ; Peilin ZHAO ; Zhizhong ZHENG ; Zhuowen YANG ; Zhipeng SU ; Yuqi MENG ; Tieniu SONG
Chinese Journal of Lung Cancer 2025;28(4):281-290
BACKGROUND:
Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN).
METHODS:
This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models.
RESULTS:
The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability.
CONCLUSIONS
The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
.
Humans
;
Male
;
Female
;
Lung Neoplasms/pathology*
;
Middle Aged
;
Retrospective Studies
;
Artificial Intelligence
;
Aged
;
Tomography, X-Ray Computed
;
Adult
;
Solitary Pulmonary Nodule/diagnostic imaging*
;
ROC Curve
8.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
9.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
10.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

Result Analysis
Print
Save
E-mail