Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

Distinct from the complementary inhibition mechanism through binding to the target with three-dimensional conformation of small molecule inhibitors, targeted protein degradation technology takes tremendous advantage of endogenous protein degradation pathway inside cells to degrade plenty of “undruggable” target proteins, which provides a novel route for the treatment of many serious diseases, mainly including proteolysis-targeting chimeras, lysosome-targeting chimeras, autophagy-targeting chimeras, antibody-based proteolysis-targeting chimeras, etc. Unlike proteolysis-targeting chimeras first found in 2001, which rely on ubiquitin-proteasome system to mainly degrade intracellular proteins of interest, lysosome-targeting chimeras identified in 2020, which was act as the fastly developing technology, utilize cellular lysosomal pathway through endocytosis mediated by lysosome-targeting receptor to degrade both extracellular and membrane proteins. As an emerging biomedical technology, nucleic acid-driven lysosome-targeting chimeras utilize nucleic acids as certain components of chimera molecule to replace with ligand to lysosome-targeting receptor or protein of interest, exhibiting broad application prospects and potential clinical value in disease treatment and drug development. This review mainly introduced present progress of nucleic acid-driven lysosome-targeting chimeras technology, including its basic composition, its advantages compared with antibody or glycopeptide-based lysosome-targeting chimeras, and focused on its chief application, in terms of the type of lysosome-targeting receptors. Most research about the development of nucleic acid-driven lysosome-targeting chimeras focused on those which utilized cation-independent mannose-6-phosphonate receptor as the lysosome-targeting receptor. Both mannose-6-phosphonate-modified glycopeptide and nucleic aptamer targeting cation-independent mannose-6-phosphonate receptor, even double-stranded DNA molecule moiety can be taken advantage as the ligand to lysosome-targeting receptor. The same as classical lysosome-targeting chimeras, asialoglycoprotein receptor can also be used for advance of nucleic acid-driven lysosome-targeting chimeras. Another new-found lysosome-targeting receptor, scavenger receptor, can bind dendritic DNA molecules to mediate cellular internalization of complex and lysosomal degradation of target protein, suggesting the successful application of scavenger receptor-mediated nucleic acid-driven lysosome-targeting chimeras. In addition, this review briefly overviewed the history of lysosome-targeting chimeras, including first-generation and second-generation lysosome-targeting chimeras through cation-independent mannose-6-phosphonate receptor-mediated and asialoglycoprotein receptor-mediated endocytosis respectively, so that a clear timeline can be presented for the advance of chimera technique. Meantime, current deficiency and challenge of lysosome-targeting chimeras was also mentioned to give some direction for deep progress of lysosome-targeting chimeras. Finally, according to faulty lysosomal degradation efficiency, more cellular mechanism where lysosome-targeting chimeras perform degradation of protein of interest need to be deeply explored. In view of current progress and direction of nucleic acid-driven lysosome-targeting chimeras, we discussed its current challenges and development direction in the future. Stability of natural nucleic acid molecule and optimized chimera construction have a great influence on the biological function of lysosome-targeting chimeras. Discovery of novel lysosome-targeting receptors and nucleic aptamer with higher affinity to the target will greatly facilitate profound advance of chimera technique. In summary, nucleic acid-driven lysosome-targeting chimeras have many superiorities, such as lower immunogenicity, expedient synthesis of chimera molecules and so on, in contrast to classical lysosome-targeting chimeras, making it more valuable. Also, the chimera technology provides new ideas and methods for biomedical research, drug development and clinical treatment, and can be used more widely through further research and optimization.

Objective:To evaluate the clinical outcomes of combined complete preservation of chordal structure mitral valve replacement (C-MVR) with total anatomical arterial myocardial revascularization (TACR) in coronary patients with moderate-to-severe or severe ischemic mitral regurgitation (IMR).Methods:This is a retrospective multi-center case series study. Data were retrospectively collected from 127 patients with coronary artery disease with moderate to severe or severe IMR who received TACR with C-MVR from July 2015 to April 2024 in 13 hospitals in China. There were 90 males and 37 females, aged (56.5±10.7) years (range: 33 to 74 years). Perioperative data and follow-up data including left ventricular ejection fraction, left ventricular end-diastolic diameter, and patency rate of arterial grafts of patients were collected. Comparisons were made using paired sample t-test or χ2 test. Results:In this cohort of 127 patients, 67 underwent concurrent tricuspid valve repair. During surgery, 113 grafts of the left internal mammary artery (LIMA), 127 grafts of the left radial artery, 80 grafts of the right radial artery, and 110 grafts of the right internal mammary artery (RIMA) were harvested. The number of the distal anastomosis was 4.2±0.4 (range: 3 to 5). The aortic cross-clamp time and cardiopulmonary bypass time were (97.5±23.4) minutes (range: 90 to 161 minutes) and (145.4±19.2) minutes (range: 101 to 210 minutes), respectively. There was one operative death. Intraoperative placement of an intra-aortic balloon pump was performed in 21 patients to improve the left ventricular ejection. No sternal ischemic occurred. All patients completed follow-up, with a mean follow-up period of (64.3±7.5) months (range: 4 to 110 months). No major cerebrovascular events occurred during the follow-up period, and all patients survived. Left ventricular ejection fraction improved postoperatively (55.0%±5.3% vs. 41.0%±15.3%, t=17.23, P<0.01). The proportion of patients with New York Heart Association functional class ≤2 increased postoperatively (23.6% (30/127) vs. 87.3% (110/126), χ2=103.77, P<0.01). The proportion of patients with Canadian Cardiovascular Society Angina Classification ≤3 decreased postoperatively (4.8% (6/126) vs. 78.7% (100/127), χ2=142.19, P<0.01). The left ventricular end-diastolic diameter decreased postoperatively ((5.70±4.50) cm vs. (6.10±0.23) cm, t=12.15, P<0.01). Coronary multi-detector computed tomography angiography (MDCTA) follow-up was conducted for (60.5±11.7) months (range: 6 to 109 months) postoperatively. MDCTA confirmed the patency rates of the grafts: 96.4% (108/112) for the LIMA grafts, 88.9% (112/126) for the left radial artery grafts, 93.7% (74/79) for the right radial artery grafts, and 90.9% (100/110) for the free RIMA grafts. No significant differences in graft patency rates were observed between the arterial grafts ( χ2=5.24, P=0.155). Conclusion:The results of this multi-centre study demonstrate satisfactory mid-term results of C-MVR with TACR for the treatment of coronary artery disease with moderate to severe or severe IMR.

Objective:To evaluate the clinical outcomes of combined complete preservation of chordal structure mitral valve replacement (C-MVR) with total anatomical arterial myocardial revascularization (TACR) in coronary patients with moderate-to-severe or severe ischemic mitral regurgitation (IMR).Methods:This is a retrospective multi-center case series study. Data were retrospectively collected from 127 patients with coronary artery disease with moderate to severe or severe IMR who received TACR with C-MVR from July 2015 to April 2024 in 13 hospitals in China. There were 90 males and 37 females, aged (56.5±10.7) years (range: 33 to 74 years). Perioperative data and follow-up data including left ventricular ejection fraction, left ventricular end-diastolic diameter, and patency rate of arterial grafts of patients were collected. Comparisons were made using paired sample t-test or χ2 test. Results:In this cohort of 127 patients, 67 underwent concurrent tricuspid valve repair. During surgery, 113 grafts of the left internal mammary artery (LIMA), 127 grafts of the left radial artery, 80 grafts of the right radial artery, and 110 grafts of the right internal mammary artery (RIMA) were harvested. The number of the distal anastomosis was 4.2±0.4 (range: 3 to 5). The aortic cross-clamp time and cardiopulmonary bypass time were (97.5±23.4) minutes (range: 90 to 161 minutes) and (145.4±19.2) minutes (range: 101 to 210 minutes), respectively. There was one operative death. Intraoperative placement of an intra-aortic balloon pump was performed in 21 patients to improve the left ventricular ejection. No sternal ischemic occurred. All patients completed follow-up, with a mean follow-up period of (64.3±7.5) months (range: 4 to 110 months). No major cerebrovascular events occurred during the follow-up period, and all patients survived. Left ventricular ejection fraction improved postoperatively (55.0%±5.3% vs. 41.0%±15.3%, t=17.23, P<0.01). The proportion of patients with New York Heart Association functional class ≤2 increased postoperatively (23.6% (30/127) vs. 87.3% (110/126), χ2=103.77, P<0.01). The proportion of patients with Canadian Cardiovascular Society Angina Classification ≤3 decreased postoperatively (4.8% (6/126) vs. 78.7% (100/127), χ2=142.19, P<0.01). The left ventricular end-diastolic diameter decreased postoperatively ((5.70±4.50) cm vs. (6.10±0.23) cm, t=12.15, P<0.01). Coronary multi-detector computed tomography angiography (MDCTA) follow-up was conducted for (60.5±11.7) months (range: 6 to 109 months) postoperatively. MDCTA confirmed the patency rates of the grafts: 96.4% (108/112) for the LIMA grafts, 88.9% (112/126) for the left radial artery grafts, 93.7% (74/79) for the right radial artery grafts, and 90.9% (100/110) for the free RIMA grafts. No significant differences in graft patency rates were observed between the arterial grafts ( χ2=5.24, P=0.155). Conclusion:The results of this multi-centre study demonstrate satisfactory mid-term results of C-MVR with TACR for the treatment of coronary artery disease with moderate to severe or severe IMR.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To investigate the effects of Clostridium butyricum on ulcerative colitis（UC）in mice and its impact on gut microbiota and autophagy levels. Methods:Eighteen C57BL/6J mice were randomly divided into a control group，a model group，and a treatment group，with six mice in each group using simple random sampling. Mice in the model and treatment groups were freely given 2.5% dextran sulfate sodium salt（DSS）solution for 5 days to establish a UC model. After successful modeling，the control and model groups were gavaged with PBS，while the treatment group was gavaged with 5×10 8 CFU/ml of live Clostridium butyricum. After the intervention，changes in body weight，disease activity index（DAI），colonic length，and pathological conditions were compared among the groups. Fluorescence quantitative PCR was used to detect the expression levels of intestinal inflammatory cytokines IL-1β and TNF-α. Myeloperoxidase（MPO）levels were analyzed，and Western blot was employed to detect the expression levels of zonula occludens-1（ZO-1），Occludin，LC3Ⅱ/LC3I，p62，and AMP-activated protein kinase/mammalian target of rapamycin AMPK/mTOR proteins. High-throughput sequencing technology was utilized to analyze the intestinal microbiota of the mice. Results:Compared with mice in the control group，the mice in the model group exhibited significant weight loss，markedly increased DAI and inflammation levels（ P<0.01），destruction of colonic structure，decreased expression levels of intestinal tight junction proteins（ P<0.05），suppressed autophagy levels（ P<0.05），and dysbiosis of the intestinal microbiota. In contrast，mice in the treatment group had a slower weight decline compared to the model group（ P<0.000 1），reduced DAI（ P<0.01），down-regulated inflammation levels（ P<0.01），improved barrier function（ P<0.05），up-regulated autophagy levels（ P<0.01），and an improved intestinal microbiota composition. Conclusions:Clostridium butyricum may ameliorate UC by modulating the intestinal microbiota composition，and enhancing autophagy levels，thus improving intestinal barrier function and inhibiting inflammatory progression in UC mice.

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.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

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.