1.Prediction of postoperative pulmonary complications in video-assisted thoracic surgery for lung cancer based on cardiopulmonary exercise testing and machine learning
Lei GUO ; Fusong LIU ; Zhilong OU ; Lan GUO ; Tiantian LI ; Chongfeng ZHOU ; Kun LUAN ; Xiaoman CHEN ; Yucheng WEI
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(01):44-52
Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.
2.Application of Anti-tumor Compatibility Structure of Chinese Medicine
Lanpin CHEN ; Feng TAN ; Xiaoman WEI ; Junyi WANG ; Liu LI ; Mianhua WU ; Haibo CHENG ; Dongdong SUN
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(8):198-208
Malignant tumors are one of the major diseases that endanger human life and health. Chinese medicine has unique advantages in clinical anti-tumor treatment. However, how to translate the anti-tumor effects of Chinese medicine into clinical practice is the core issue that must be addressed in the process of treating malignant tumors with traditional Chinese medicine (TCM). Unlike modern chemical drugs, the compatibility application of Chinese medicine is the key factor that determines whether Chinese medicine can achieve optimal anti-tumor efficacy and realize the goal of "enhancing efficacy and reducing toxicity". The formulation structure based on this compatibility is the basic form for the safe, efficient, and rational clinical use of anti-tumor Chinese medicine, and it mainly includes three categories: herb pairs, tri-herbal combinations, and compound compatibility. Although herb pairs have the characteristics of a simple structure and strong targeting (enhancing efficacy and reducing toxicity), they often have a single effect and cannot fully address the complex pathogenesis of tumors. As a result, herb pairs are rarely used alone in practice. Compared to herb pairs, tri-herbal combinations broaden the application scope of herbs in clinical treatment, but their therapeutic range remains limited. The traditional "sovereign, minister, assistant, and guide" compound prescription, which includes herb pairs and tri-herbal combinations, improves the efficacy of herbs in treating serious diseases, hypochondriasis, chronic diseases, and miscellaneous disorders. However, due to the limitations of its historical background, it has not been integrated with modern clinical practice and modern pharmacological research, which restricts the development of compound compatibility theory. With the emergence of modern medical technology, it has been combined with traditional compatibility theory of Chinese medicine to create an innovative modern compatibility theory. This includes the "aid medicine" theory derived from modern Chinese medicine pharmacology, which compensates for the inability of the "sovereign, minister, assistant, and guide" theory to accurately apply medicine. Additionally, the "state-targeted treatment based on syndrome differentiation" theory, developed from pharmacology and modern medicine, addresses the deficiency in disease cognition in the "sovereign, minister, assistant, and guide" theory. Under the guidance of these compatibility forms and theories, clinical anti-tumor Chinese medicine can exert its maximum anti-tumor efficacy, which is of great significance for the application of Chinese medicine in clinical tumor treatment.
3.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.
4.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.
5.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.
6.Application effects of calorie-restricted diet combined with high-protein, high-dietary fiber meal replacement powder and probiotics in overweight/obese adults
Jin ZHOU ; Jin TIAN ; Xiaojing YAN ; Chengqian LU ; Jing WANG ; Wei YAN ; Li YANG ; Jie YIN ; Baoling HU ; Xiaoman FENG ; Yanhui ZHANG ; Li TAO ; Zengning LI
Chinese Journal of Health Management 2025;19(4):264-272
Objective:To assess the application effects of an energy-restricted diet combined with high-protein, high-dietary-fiber meal replacement powder and probiotics in overweight/obese adults.Methods:It was a randomized controlled trial. A consecutive sample of 150 overweight/obese adults who underwent physical examinations at the Health Care Center of the First Hospital of Hebei Medical University between November 2021 and March 2022. The participants were randomly assigned into the combined group, the high-protein group, and the common group (50 participants per group) using a random number table method. All three groups of subjects received weight loss health education, energy-restricted diet, and interventions with meal replacement powder and probiotics (or probiotic placebo). The combined group was given high-protein and high-dietary fiber meal replacement powder and probiotics. The high-protein group was given high-protein meal replacement powder and probiotic placebo. The common group was given ordinary meal replacement powder and probiotic placebo. The meal replacement powder was packaged in 35 g per bag, with main components of varying amounts of protein, fat, carbohydrates, vitamins, and trace elements. Both the probiotic powder and the probiotic placebo came in 2 g sachets. The primary components of probiotic powder were various Bifidobacterium, Lactobacillus and excipients, while the main component of probiotic placebo was excipients. The meal replacement powder and the probiotic powder or probiotic placebo were taken twice a day for a total of 12 weeks, one sachet of each time, followed by a 4-week follow-up. The body weight, body mass index, body fat mass, abdominal circumference and hip circumference were measured before the trial (week 0) and at the end of weeks 2, 4, 8, 12, and 16. The change rates of each indicator were calculated. Biochemical indicators, trace elements, and 25-hydroxyvitamin D levels were measured at the end of week 0, 4, 8, and 12. A product evaluation questionnaire was conducted at the end of week 12. A total of 19 cases dropped out due to various reasons. Finally, 46 cases in the combined group, 42 cases in the high-protein group, and 43 cases in the common group were included in the analysis. Paired-samples t test, Kruskal-Wallis H test, one-way analysis of variance, and Mann-Whitney U test were used to compare the differences in weight-loss and maintenance effects, safety and patient acceptance among the three intervention groups, and to analyze the application effect of the energy-restricted diet combined with high-protein and high-dietary fiber meal replacement powder plus probiotics in overweight/obese adults. Results:Among the 131 overweight/obese adults included in the analysis, there were 57 males and 74 females, with a mean age of (37.30±8.33) years. By the end of the week 12, the body mass index [26.87(25.77, 30.38) vs 29.61(27.96, 33.09) kg/m2; 27.10(24.70, 31.37) vs 29.40(27.20, 34.17) kg/m2; 27.98(26.43, 30.12) vs 29.88(28.22, 31.93) kg/m2] and body fat masses [22.15(17.70, 30.15) vs 30.75(25.63, 35.40) kg; 23.35(19.12, 28.70) vs 29.45(26.20, 37.05) kg; 26.80(24.10, 31.60) vs 30.00(26.00, 34.70) kg] in the combined group, the high-protein group and the common group were all lower than those at baseline (week 0) (all P<0.05). At the end of the week 12, the change rates of body fat mass and body mass index in the combined group were both higher than those in the high-protein group and the common group [(25.98%±9.58%) vs (23.88%±11.15%) and (9.35%±11.00%), 9.29%(7.23%, 11.58%) vs 7.96% (5.51%, 10.92%) and 5.77% (2.68%, 10.03%)] (all P<0.05). At the end of the week 12, the body fat mass in the combined group and the high-protein group were both lower than that in the common group [22.15(17.70, 30.15), 23.35(19.12, 28.70) vs 26.80(24.10, 31.60) kg] (both P<0.05). At the end of the week 12, the decreased values of uric acid and high-sensitivity C-reactive protein in the combined group were both higher than those in the high-protein group and the common group [17.15(13.02, 23.45) vs 1.50(0.22, 28.60) and 4.20(0.15, 19.95) μmol/L, 0.43(0.24, 0.60) vs 0.21(0.06, 0.43) and 0.28(-0.04, 0.88) mg/L](both P<0.05). No serious adverse events were observed during the intervention period and at the end of the intervention. In the product evaluation questionnaire, the combined group scored higher than the high-protein group and the common group on items such as usage frequency, taste, satiety, willingness to continue use, willingness to recommend to others, and willingness to purchase [4(3, 4) vs 3(3, 4) and 3(2, 4) points, 4(3, 4) vs 3(3, 4) and 3(2, 4) points, 4(3, 4) vs 3(3, 4) and 3(3, 3) points, 4(3, 4) vs 3(3, 4) and 3(3, 4) points, 4(3, 4) vs 3(3, 4) and 3(3, 3) points, 3(3, 4) vs 3(3, 4) and 3(2, 3) points] (all P<0.05). Conclusion:An energy-restricted diet combined with high-protein, high-dietary-fiber meal replacement powder and probiotics demonstrates superior weight-loss and weight-maintenance effects in overweight/obese adults, with high safety and great user acceptability.
7.Mechanism of the pretreatment with electroacupuncture of "biaoben acupoint combination" for regulating cardiomyocyte mitochondrial fission in the rats of myocardial ischemia-reperfusion injury.
Yanlin ZHANG ; Song WU ; Qianru GUO ; Yuntao YU ; Sunyi WANG ; Yuqi WEI ; Xiaoman WAN ; Zhen LU ; Xiaoru HE
Chinese Acupuncture & Moxibustion 2025;45(3):335-344
OBJECTIVE:
To observe the effect of electroacupuncture (EA) pretreatment of "biaoben acupoint combination" on cardiomyocyte mitochondrial fission in the rats with myocardial ischemia-reperfusion injury (MIRI) and explore its mechanism.
METHODS:
Fifty male SD rats were randomly divided into a sham-operation group, a model group, an EA pretreatment group, an EA pretreatment + Compound C group and an EA pretreatment+ML385 group, 10 rats in each group. In the EA pretreatment, the EA pretreatment + Compound C group and the EA pretreatment+ML385 group, EA was delivered at bilateral "Neiguan" (PC6), "Zusanli" (ST36) and "Guanyuan" (CV4) for 20 min, with continuous wave and 2 Hz of frequency, 1 mA of current, once daily for consecutive 7 days. On day 8, in the EA pretreatment + Compound C group and the EA pretreatment+ML385 group, 30 min before model preparation, the intraperitoneal injection with Compound C (0.3 mg/kg) and ML385 (30 mg/kg) was administered respectively. Except in the sham-operation group, the ligation of the left anterior descending coronary artery was performed to prepare MIRI rat model in the rest groups. In the sham-operation group, the thread was not ligated. After modeling, the content of reactive oxygen species (ROS) in the ischemic area was measured by flow cytometry, superoxide dismutase (SOD) was detected using xanthine oxidase method, and malondialdelyde (MDA) was detected using thiobarbituric acid (TBA) chromatometry. The morphology of myocardial tissue in the ischemic area was observed with HE staining, and the mitochondria ultrastructure of cardiomyocytes observed under transmission electron microscopy. Using immunofluorescence analysis, the positive expression of mitochondrial fission factor (MFF), mitochondrial fission 1 protein antibody (Fis1) and dynamin-related protein 1 (Drp1) was detected; and with immunohistochemical method used, the protein expression of adenosine monophosphate-activated protein kinase (AMPK), nuclear factor E2-associated factor2 (Nrf2) and Drp1 in the ischemic area was detected.
RESULTS:
Compared with the sham-operation group, the content of ROS and MDA in the myocardial tissue of the ischemic area, and the positive expression of MFF, Fis1 and Drp1 increased in the model group (P<0.01); the content of SOD and the protein expression of AMRK and Nrf2 decreased (P<0.01), and the protein expression of Drp1 elevated (P<0.01). Compared with the model group, the content of ROS and MDA in the myocardial tissue of the ischemic area, and the positive expression of MFF, Fis1 and Drp1 were dropped in the EA pretreatment group (P<0.01); the content of SOD and the protein expression of AMRK and Nrf2 rose (P<0.01), and the protein expression of Drp1 declined (P<0.01); and in the EA pretreatment+Compound C group and the EA pretreatment+ML385 group, the positive expression of MFF, Fis1 and Drp1, and the protein expression of Drp1 were all reduced (P<0.01). When compared with the EA pretreatment + Compound C group and the EA pretreatment+ML385 group, the content of ROS and MDA in the myocardial tissue of the ischemic area, and the positive expression of MFF, Fis1 and Drp1 were dropped in the EA pretreatment group (P<0.01); the content of SOD and the protein expression of AMRK and Nrf2 rose (P<0.01, P<0.05), and the protein expression of Drp1 decreased (P<0.05). In comparison with the model group, the EA pretreatment+Compound C group and the EA pretreatment+ML385 group, the cardiac muscle fiber rupture, cell swelling and mitochondrial disorders were obviously alleviated in the EA pretreatment group. The morphological changes were similar among the model group, the EA pretreatment+Compound C group and the EA pretreatment+ML385 group.
CONCLUSION
Electroacupuncture pretreatment of "biaoben acupoint combination" attenuates myocardial injury in MIRI rats, probably through promoting the phosphorylation of AMPK and Nrf2, inhibiting the excessive mitochondrial fission induced by Drp1, and reducing mitochondrial dysfunction caused by mitochondrial fragmentation and vacuolation.
Animals
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Electroacupuncture
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Male
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Rats, Sprague-Dawley
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Myocardial Reperfusion Injury/physiopathology*
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Myocytes, Cardiac/cytology*
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Rats
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Acupuncture Points
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Mitochondrial Dynamics
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Humans
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Reactive Oxygen Species/metabolism*
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NF-E2-Related Factor 2/genetics*
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Superoxide Dismutase/metabolism*
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.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.

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