1.The Neural Circuit Characteristics of Repetitive Transcranial Magnetic Stimulation Over The Dorsolateral Prefrontal Cortex for The Treatment of Migraine
Chen-Xia JIN ; Bo-Lin TAN ; Yang YE ; Ji-Qing HE ; Ling-Yan WANG ; Zhong-Ming GAO ; Yu-Jun WANG ; Hui-Li LIU ; Yong-Xing YAN ; Xian-Wei CHE
Progress in Biochemistry and Biophysics 2026;53(7):1953-1968
ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.
2.Analysis of the association between the use of oral progesterone drugs in early pregnancy and gestational diabetes mellitus
Yan QIN ; Jinhua GU ; Jing ZHU ; Lin LUO ; Peng PING ; Lingqi GU
China Pharmacy 2025;36(6):721-726
OBJECTIVE To explore the association between the use of oral progesterone drugs in early pregnancy and gestational diabetes mellitus (GDM). METHODS Through real-world retrospective cohort research method, pregnant women who underwent the oral glucose tolerance test (OGTT) at the Affiliated Maternal and Child Health Hospital of Nantong University between January 2022 and January 2023 were enrolled. Based on whether oral progesterone drugs were used in early pregnancy, they were divided into treatment group and control group; propensity score matching (PSM) with a 1∶1 ratio was employed to control for confounding factors; Logistic regression and linear regression were employed to analyze the association between drug factors (whether use of oral progesterone drug, duration of medication, dosage, and drug type) and outcome indicators (occurrence of GDM, fasting blood glucose levels, and OGTT 1 and 2 h blood glucose levels in late pregnancy). RESULTS A total of 709 pregnant women were enrolled in the two groups before PSM; after PSM, 256 cases were included in both the treatment group and the control group. The results of association analysis indicated that there was no significant association between the use of oral progesterone drugs and GDM (P>0.05); but a significant correlation was found with OGTT 1 h blood glucose levels [β=0.965, 95%CI (0.007,1.922), P<0.05], specifically with Dydrogesterone tablets [β=0.977, 95%CI (0.009, 1.944), P<0.05] and Progesterone soft capsules [β =1.089, 95%CI (0.077, 2.102), P<0.05]. There was no significant correlation between other drug factors and outcome indicators (P>0.05). CONCLUSIONS The use of oral progestogen drugs in early pregnancy is not significantly associated with GDM. The blood glucose levels in late pregnancy, especially OGTT 1 h blood glucose levels, have a certain correlation with Progesterone soft capsules and Dydrogesterone tablets.
3.Clinical value of systemic inflammatory response index in patients with acute-on-chronic liver failure and co-infection
Hui LI ; Haibin SU ; Jinhua HU ; Chenhui SHI ; Chen LI ; Xiaoyan LIU ; Jing CHEN ; Lilong YAN ; Yuhui PENG ; Peng NING ; Chongdan GUAN
Journal of Clinical Hepatology 2025;41(8):1620-1626
Objective To investigate the application value of systemic inflammatory response index(SIRI)in patients with acute-on-chronic liver failure(ACLF)and co-infection.Methods A retrospective analysis was performed for the clinical data of 579 ACLF patients with co-infection who were diagnosed and treated in The Fifth Medical Center of Chinese PLA General Hospital from January 2014 to March 2016,including demographic features,laboratory markers,and complications,and SIRI,Model for End-Stage Liver Disease(MELD)score,MELD combined with serum sodium concentration(MELD-Na)score,and Child-Pugh score were calculated.According to the results of follow-up on day 90,the patients were divided into survival group with 210 patients and death group with 369 patients.The independent-samples t test was used for comparison of normally distributed continuous data between two groups;the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data between two groups;the chi-square test were used for comparison of categorical data between two groups.The binary logistic regression analysis was used to investigate the independent risk factors for 90-day death.The receiver operating characteristic(ROC)curve and the area under the ROC curve(AUC)were used to assess the performance of SIRI,MELD-Na score,and Child-Pugh score in predicting the prognosis of ACLF patients with co-infection.The Kaplan-Meier survival analysis was performed based on the optimal cut-off value of SIRI.Results Among the 597 ACLF patients with co-infection,384(66.32%)had HBV-related ACLF and 114(19.69%)had alcohol-related ACLF;as for the main infection sites,316(54.58%)had abdominal infection and 133(22.97%)had pulmonary infection;the 90-day mortality rate was 63.73%.The multivariate logistic regression analysis showed that SIRI(odds ratio[OR]=1.177,95%confidence interval[CI]:1.117-1.239,P<0.05),blood ammonia(OR=1.009,95%CI:1.001-1.018,P<0.05),MELD-Na score(OR=1.047,95%CI:1.016-1.080,P<0.05),Child-Pugh score(OR=1.351,95%CI:1.054-1.730,P<0.05),age(OR=1.045,95%CI:1.021-1.070,P<0.05),comorbidity with hepatic encephalopathy(OR=2.269,95%CI:1.305-3.946,P<0.05),and comorbidity with acute kidney injury(OR=1.730,95%CI:0.990-3.023,P<0.05)were independent risk factors for 90-day death in ACLF patients with co-infection.The Pearson correlation analysis showed that SIRI was positively correlated with MELD-Na score(r=0.282,P<0.001)and Child-Pugh score(r=0.168,P<0.001).SIRI,MELD-Na score,and Child-Pugh score had an AUC of 0.855,0.734,and 0.690,respectively,in predicting 90-day death,and SIRI had a higher predictive efficiency than MELD-Na score and Child-Pugh score(Z=4.922 and 6.289,both P<0.001),with a sensitivity of 76.7%and a specificity of 82.9%.In addition,SIRI combined with MELD-Na score or Child-Pugh score improved the predictive efficiency of MELD-Na score(0.854 vs 0.734,Z=6.899,P<0.001)and Child-Pugh score(0.858 vs 0.690,Z=8.725,P<0.001).The patients with high SIRI(≥4.08)had a 90-day survival rate of 11.29%(36/319),which was significantly lower than that in the patients with low SIRI(<4.08)(χ2=225.24,P<0.001).Conclusion SIRI is an independent risk factor for death in ACLF patients with co-infection and has a good clinical value in predicting prognosis,with the advantages of convenience and low costs.
4.Strychni Semen and its active compounds promote axon regeneration following peripheral nerve injury by suppressing myeloperoxidase in the dorsal root ganglia.
Yan ZHANG ; Xin-Yue ZHAO ; Meng-Ting LIU ; Zhu-Chen ZHOU ; Hui-Bin CHENG ; Xu-Hong JIANG ; Yan-Rong ZHENG ; Zhong CHEN
Journal of Integrative Medicine 2025;23(2):169-181
OBJECTIVE:
Treating peripheral nerve injury (PNI) presents a clinical challenge due to limited axon regeneration. Strychni Semen, a traditional Chinese medicine, is clinically used for numbness and hemiplegia. However, its role in promoting functional recovery after PNI and the related mechanisms have not yet been systematically studied.
METHODS:
A mouse model of sciatic nerve crush (SNC) injury was established and the mice received drug treatment via intragastric gavage, followed by behavioral assessments (adhesive removal test, hot-plate test and Von Frey test). Transcriptomic analyses were performed to examine gene expression in the dorsal root ganglia (DRGs) from the third to the sixth lumbar vertebrae, so as to identify the significantly differentially expressed genes. Immunofluorescence staining was used to assess the expression levels of superior cervical ganglia neural-specific 10 protein (SCG10). The ultra-trace protein detection technique was used to evaluate changes in gene expression levels.
RESULTS:
Strychni Semen and its active compounds (brucine and strychnine) improved functional recovery in mice following SNC injury. Transcriptomic data indicated that Strychni Semen and its active compounds initiated transcriptional reprogramming that impacted cellular morphology and extracellular matrix remodeling in DRGs after SNC, suggesting potential roles in promoting axon regeneration. Imaging data further confirmed that Strychni Semen and its active compounds facilitated axon regrowth in SNC-injured mice. By integrating protein-protein interaction predictions, ultra-trace protein detection, and molecular docking analysis, we identified myeloperoxidase as a potentially critical factor in the axon regenerative effects conferred by Strychni Semen and its active compounds.
CONCLUSION
Strychni Semen and its active compounds enhance sensory function by promoting axonal regeneration after PNI. These findings establish a foundation for the future applications of Strychni Semen and highlight novel therapeutic strategies and drug targets for axon regeneration. Please cite this article as: Zhang Y, Zhao XY, Liu MT, Zhou ZC, Cheng HB, Jiang XH, Zheng YR, Chen Z. Strychni Semen and its active compounds promote axon regeneration following peripheral nerve injury by suppressing myeloperoxidase in the dorsal root ganglia. J Integr Med. 2025; 23(2): 169-181.
Animals
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Nerve Regeneration/drug effects*
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Mice
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Peripheral Nerve Injuries/physiopathology*
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Male
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Ganglia, Spinal/enzymology*
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Axons/physiology*
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Peroxidase/antagonists & inhibitors*
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Mice, Inbred C57BL
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Drugs, Chinese Herbal/pharmacology*
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Disease Models, Animal
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Strychnine/pharmacology*
5.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.
6.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.
7.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
8.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
9.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.
10.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.

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