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.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To systematically evaluate the impact of continuous renal replacement therapy(CRRT)on the pharmacokinetics of polymyxin B,explore its possible impacting factors.Methods PubMed,Embase,Co-chrane Library,Web of Science,VIP database,China National Knowledge Infrastructure(CNKI),SinoMed,and Wanfang data were retrieved.The study subjects were patients receiving CRRT and polymyxin B.Observational studies,case reports,and reviews were included.The outcome indicators included therapeutic drug monitoring re-sults,pharmacokinetic parameters,and CRRT parameters.The retrieval time was from the inception of each data-base to January 2025.The quality of literatures was evaluated with ClinPK tool.Two researchers independently conducted literature screening,data extraction,and quality evaluation.Results A total of 12 literatures were ulti-mately included in analysis,including 1 review,3 case reports,and 8 observational studies.Five studies showed that the clearance rate during CRRT period(1.3-6.66 L/h)was higher than that during non-CRRT period(0.5-3.9 L/h).Five studies reported that the area under the steady-state 24-hour drug concentration-time curve(AUCss,24h)during CRRT period(21.58-75.1 mg·h/L)was lower than that during non-CRRT period(60.6-118 mg·h/L).Two studies detected drugs in ultrafiltrate or dialysate,with in vitro drug recovery rates ranging from 5.62％to 24.0％.Two studies reported a decrease in drug concentration after passing through a blood filter.Conclusion During CRRT period,polymyxin B presents higher clearance rate and lower blood drug concentration,and some patients have lower AUCss.24h than the therapeutic target.The mechanism of this change during CRRT is not yet clear,the therapy mode and filter type may be potential impacting factors,further research are needed to promote precise anti-infective treatment.

Aim To elucidate whether Astragaloside Ⅳcould ameliorate pathological myocardial hypertrophy and fibrosis via the EGR1-SIRT1-PPARα-SCAD signa-ling pathway in TAC mice.Methods After randomi-zing mice into groups,the Sham+AS-Ⅳ group and TAC+AS-Ⅳ group were intragastrically administered 20 mg·kg-1AS-Ⅳ once daily,whereas the Sham+NS group and TAC+NS group were given equivalent saline.Six weeks post-surgery,an evaluation of cardiac function was conducted,heart weight index was compu-ted,morphological alterations in heart were noted,vari-ations in collagen and myocardial hypertrophy indexes were analyzed,ATP content,free fatty acid content,hydroxyproline content,SCAD expression,and enzyme activity were measured,and an initial investigation into the protein expression of EGR1-SIRT1-PPARα-SCAD in myocardial tissues was undertaken.Results After AS-Ⅳ intervention,the heart weight index of TAC mice decreased(P＜0.01),LVAWd,LVAWs,LVPWd and LVPWs values decreased(P＜0.01,P＜0.05),EF％and FS％values increased(all P＜0.01),myocardial hypertrophy markers and collagen area decreased,FFA content,HYP content and collagen expression de-creased(all P＜0.01),SCAD enzyme activity and ex-pression increased(P＜0.01,P＜0.05),and ATP content increased(P＜0.01).The expression of EGR1 protein decreased,and the expression of SIRT1 and PPARα protein increased(all P＜0.01).Conclu-sions AS-Ⅳ may improve fatty acid oxidation via the EGR1-SIRT1-PPARα-SCAD signaling pathway,thereby ameliorating pathological myocardial hypertrophy and fibrosis in TAC model mice.

From July 23, 2018, to December 31, 2019, a total of 299 219 children in Shandong Province received the fifth dose of the diphtheria, tetanus, and acellular pertussis combined vaccine (DTaP). Among these recipients, the distribution by age was as follows: 20 children under 2 years old (0.01%), 273 996 children aged 2 years (91.57%), 20 242 children aged 3 years (6.76%), 3 932 children aged 4 years (1.31%), 963 children aged 5 years (0.32%), and 66 children aged 6 years and above (0.02%). In total, 1 972 cases of adverse events following immunization (AEFI) were reported after the administration of the fifth dose of DTaP, resulting in an incidence rate of 659.05 per 100 000 doses. Among these, 1 718 cases were classified as common vaccine reactions, with an incidence rate of 574.16 per 100 000 doses, while 247 cases were identified as rare reactions, yielding an incidence rate of 82.55 per 100 000 doses. The incidence of AEFIs, as well as the rates of common and rare reactions, exhibited a significant increasing trend with the number of doses administered (all P<0.001). Among the rare reactions, there were 10 cases classified as severe, resulting in a reported incidence of 3.34 per 100 000 doses.

Aim To explore the mechanism by which dioscin regulates IL-17+γδT cells in the treatment of arthritis.Methods A collagen-induced arthritis(CIA)model was established in DBA/1 mice using bovine type Ⅱ collagen.The mice were randomly divid-ed into the CIA model group,methotrexate(MTX)positive control group,and dioscin low-dose(Dioscin-L),medium-dose(Dioscin-M),and high-dose(Dios-cin-H)groups.After intervention,the therapeutic effects were evaluated using scoring methods.Joint pathological damage was analyzed by hematoxylin and eosin(HE)staining.The levels of anti-collagen-spe-cific antibodies and the pro-inflammatory cytokine IL-17 were measured by ELISA.The expressions of γδT cells and their subtypes,as well as the secretion level of IL-17,were detected by flow cytometry.Results Dioscin significantly reduced the arthritis severity score in collagen-induced arthritis(CIA)mice,alleviated joint pathological damage,inhibited the production of IL-17 by splenic lymphocytes and the levels of anti-col-lagen-specific antibodies total IgG and IgG3,and de-creased the proportion of γδT cells in the lymph nodes,splenic γδT cells,and the Vδ4+T-cell subset.The level of IL-17 produced by the Vδ4 subtype in the lymph nodes of the intervention groups was lower than that in the model group,but the difference was not sta-tistically significant.Conclusion Dioscin has signifi-cant therapeutic effect on CIA,and its mechanism may be through the inhibition of γδT cells,but it is unlikely to be related to IL-17 derived from γδT cells.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

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.

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.

AIM To investigate the tumor-suppressive mechanism of Guiqi Yiyuan Extract combined with cisplatin in Lewis lung cancer mice.METHODS Ten intact C57BL/6J mice were assigned to the blank group.Sixty additional mice were developed into Lewis lung cancer models bearing transplanted tumor and subsequently allocated into the model group,the cisplatin group(5 mg/kg),the high-dose Guiqi Yiyuan Extract group(6.6 g/kg),and the low-dose,medium-dose and high-dose Guiqi Yiyuan Extract combined with cisplatin group(1.6,3.3,6.6 g/kg+5 mg/kg),with 10 mice in each group.Mice in the blank and model groups received saline via daily gavage,while treatment groups were administered Guiqi Yiyuan Extract orally(once daily),and cisplatin injection intraperitoneally(once every other day).After 14 days of drug administration,mice were euthanized for endpoint analysis.The following assessments were conducted:general health status and body weight changes monitored throughout the study period;tumor excision and weighing for inhibition rate calculation;histopathological examination of tumors via hematoxylin-eosin(HE)staining;serum quantification of IL-1 β,IL-18 and HMGB1 by ELISA;ultrastructural analysis of tumor cell death using transmission electron microscopy(TEM);spatial localization of TXNIP and GSDMD-N in tumor sections via immunofluorescence(IF);and Western blot detection of TXNIP,NLRP3,Caspase-1,cleaved Caspase-1,GSDMD,GSDMD-N protein expressions in tumor tissues.RESULTS Compared to the model group,the cisplatin group and all combination therapy groups exhibited significant reduction in tumor weight(P＜0.05)and increased tumor suppression rate;enhanced tumor tissue necrosis with characteristic pyroptotic morphology;elevated serum levels of IL-1β,IL-18 and HMGB1(P＜0.05);and upregulated expressions of pyroptosis-associated proteins TXNIP,NLRP3,Caspase-1,cleaved Caspase-1,GSDMD and GSDMD-N(P＜0.05).The high dose combination group demonstrated optimal therapeutic efficacy(P＜0.05).CONCLUSION Guiqi Yiyuan Extract enhances cisplatin sensitivity,demonstrating synergistic anti-tumor effects in Lewis lung carcinoma-bearing mice.This combinatorial therapeutic effect likely involves modulation of the TXNIP/NLRP3/Caspase-1/GSDMD pathway.