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 investigate the drug resistance of newly diagnosed HIV-1 infected patients in Shanghai and to provide reference value for clinical antiretroviral therapy (ART).Methods:The peripheral venous blood plasma of 196 newly diagnosed HIV-1 infected patients screened according to the inclusion and exclusion criteria at the Shanghai Public Health Clinical Center from April to June 2023 was collected, HIV-1 RNA was extracted, the pol region was amplified by reverse transcription-polymerase chain reaction (RT-PCR) for sequencing, the mutation sites and ART drug resistance were analyzed.Results:The plasma of 196 newly diagnosed HIV-1 infected patients was amplified successfully in 162 cases (amplification success rate was 82.65%). The subtypes consisted of CRF07_BC(51.23%), CRF01_AE (27.78%), and others (6.79%), CRF55_01B (5.56%), B (3.70%), CRF01_AE/B (3.70%) and CRF08_BC (1.23%). The overall transmitted drug resistance rate was 7.41%, the protease inhibitors (PIs), non-nucleoside/nucleotide reverse transcriptase inhibitors (NNRTIs), nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs), integrase inhibitors (INSTIs) resistance rates were 3.09%, 3.70%, 0.00% and 0.62%, respectively. The proportion of NNRTIs-related mutation sites in B (66.67%) and CRF55_01B (88.89%) was higher than that in CRF07_BC (13.25%); the proportion of NNRTIs-related mutation sites in CRF55_01B (88.89%) was higher than that in CRF01_AE (22.22%) and other subtypes (18.18%), the difference was statistically significant (all P<0.05). Multivariate logistic regression analysis showed that the probability of PIs-related mutation sites in CRF01_AE/B was 21.71 times that of CRF07_BC[odds ratio ( OR)=21.71, 95% confidence interval ( CI): 3.36-140.27, P=0.001]. Conclusions:The transmitted drug resistance among newly diagnosed HIV-1 infected patients in Shanghai is at the moderate epidemic level, mainly NNRTIs and PIs-related drug resistance, and the INSTIs resistance rate is low, the use of INSTIs in ART regimens should be considered.

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 effects of Yiqi Juanbi Formula on chondrocyte pyroptosis in rat models of collagen-induced arthritis(CIA).METHODS Fifty rats were subcutaneously injected at the tail base with an emulsion containing equal volumes of bovine type Ⅱ collagen and incomplete Freund's adjuvant(IFA)to establish the CIA models.These rats were then randomly assigned to the model group,the methotrexate group(0.35 mg/kg),and the low-dose,medium-dose,and high-dose Yiqi Juanbi Formula groups(9.4,18.7,37.4 g/kg),in contrast to the ten intact rats serving in the normal control group.Following four weeks of intragastric administration,the rats had their general conditions observed;their joint swelling and arthritis indices measured;their ankle joint pathology assessed by HE staining;their serum levels of IL-1β,IL-18 and TNF-ɑ detected by ELISA;their mRNA expressions of NLRP3,Caspase-1,GSDMD,IL-1β,IL-18 and TNF-ɑ in ankle cartilage quantified by RT-qPCR;their protein expressions of NF-κB,NLRP3 and Caspase-1 in ankle cartilage analyzed by Western blot;and their NLRP3 and GSDMD positive expressions in ankle cartilage examined by immunohistochemistry.RESULTS Compared to the control group,the model group showed significantly increased joint swelling and arthritis indices(P＜0.01);elevated serum levels of IL-1 β,IL-18 and TNF-ɑ(P＜0.01);pathological changes including cartilage surface defects,reduced cell count,altered cellular morphology,irregular cell arrangement,and significant inflammatory cell infiltration in synovial tissue;upregulated mRNA expressions of NF-κB,NLRP3,Caspase-1,GSDMD,IL-1β,IL-18 and TNF-ɑ(P＜0.01)and increased protein expressions of NF-κB,NLRP3 and Caspase-1(P＜0.01)in ankle cartilage;enhanced positive expressions of NLRP3 and GSDMD in ankle cartilage(P＜0.01).Compared to the model group,the groups intervened with methotrexate or medium-or high-dose Yiqi Juanbi Formula exhibited reduced joint swelling and arthritis indices(P＜0.01);alleviated pathological damage in ankle joints;decreased serum levels of IL-1β,IL-18 and TNF-ɑ(P＜0.01);downregulated mRNA expressions of NF-κB,NLRP3,Caspase-1,GSDMD,IL-1β,IL-18 and TNF-ɑ(P＜0.05,P＜0.01),and reduced protein expressions of NF-κB,NLRP3 and Caspase-1(P＜0.05,P＜0.01)in ankle cartilage;and diminished positive expressions of NLRP3 and GSDMD in ankle cartilage(P＜0.01).CONCLUSION Yiqi Juanbi Formula alleviates inflammation in CIA rats,potentially by inhibiting the activation of the NF-κB/NLRP3/Caspase-1 signaling pathway,thereby suppressing chondrocyte pyroptosis.

Objective To analyze the research status,hotspots,and trends of wearable devices in nursing applications both domestically and internationally.Methods Using China National Knowledge Infrastructure,Wanfang Data Knowledge Service Platform,and Embase core databases as data sources,VOSviewer was used to visualize and analyze the publication time,keywords,and other relevant literature.Results Total of 428 articles were included,including 196 Chinese articles and 232 English articles.The overall publication volume showed an upward trend.Domestic research focuses on chronic diseases,artificial intelligence,and nursing,with the main research subjects being the elderly;Foreign research focuses on smart devices,self-monitoring,and quality of life,with the main research subjects being adults.Conclusion Currently,the number of publications on the application of wearable devices in nursing is relatively small,but the overall research heat is on the rise,mainly used for chronic diseases and self-monitoring.In the future,the application scope of wearable devices should be expanded and their potential value should be explored to promote the innovation and progress of nursing models.

An overview of the development of exoskeleton robots was presented,and the current status of the application of exoskeleton robots was summarized in the field of rehabilitation of spinal cord injury patients.The rehabilitation efficacy of exoskeleton robots was described on walking ability,cardiopulmonary function,daily living ability and quality of life of spinal cord injury patients.The problems of exoskeleton robots applied for the rehabilitation of spinal cord injury patients were analyzed,and the future development trends of exoskeleton robots were envisioned.[Chinese Medical Equipment Journal,2025,46(4):100-107]

Objective:To analyze the correlation of bone mineral density (BMD) , serum transforming growth factor β1 (TGF- β1) , and retinol-binding protein 4 (RBP4) with osteoporosis in gestational diabetes mellitus (GDM) . Methods:A total of 180 GDM patients admitted to Department of Gynecology, Second Hospital of Tianjin Medical University from Jan. 2022 to Jan. 2024 were included as the observation group, and 30 healthy pregnant women undergoing examination at the same time were included into the control group. BMD [stiffness index (SI) , broadband ultrasound attenuation (BUA) , speed of sound (SOS) ], serum TGF-β1, and RBP4 levels were compared between the two groups; GDM women with complicated with osteoporosis were included in the osteoporosis subgroup, and pregnant women without osteoporosis were included in the non-osteoporosis subgroup. BMD, serum TGF- β1 and RBP4 levels were compared between the two groups, and the relationship among bone mineral density and serum TGF- β1, RBP4 was analyzed by Pearson correlation. Receiver operating characteristic curve (ROC) curve was drawn to evaluate the diagnostic value of serum TGF- β1 and RBP4 levels in GDM complicated with osteoporosis. Results:The observation group had significantly higher levels of serum TGF- β1 and RBP4 than the control group, while lower BUA, SOS and SI ( t=99.04, 28.48, 4.10, 3.54, 6.29, P < 0.05) ; Among 180 pregnant women with GDM, 38 cases had osteoporosis and 142 cases did not have osteoporosis. The osteoporosis subgroup had significantly higher serum TGF- β1 and RBP4 levels than the other subgroup, while BMD indexes such as BUA, SOS and SI were significantly lower ( t=3.35, 3.48, 3.77, 2.85, 3.41, P < 0.05) ; Pearson correlation analysis showed that BMD indexes, such as BUA, SOS and SI, were significantly correlated with serum TGF- β1 and RBP4 in pregnant women with GDM ( r=-0.61, 0.58, -0.60, -0.58, -0.60, -0.63, P<0.05) ; The area under the curve (AUC) of TGF- β1, RBP4 and combined detection of GDM women with osteoporosis was 0.572, 0.653 and 0.659, respectively. Conclusions:In GDM women complicated with osteoporosis, the levels of serum TGF- β1 and RBP4 increase significantly, and BMD decreases significantly. Serum TGF- β1 and RBP4 in GDM women are closely related to BMD index, which can provide early diagnosis basis for GDM complicated with osteoporosis.

An overview of the development of exoskeleton robots was presented,and the current status of the application of exoskeleton robots was summarized in the field of rehabilitation of spinal cord injury patients.The rehabilitation efficacy of exoskeleton robots was described on walking ability,cardiopulmonary function,daily living ability and quality of life of spinal cord injury patients.The problems of exoskeleton robots applied for the rehabilitation of spinal cord injury patients were analyzed,and the future development trends of exoskeleton robots were envisioned.[Chinese Medical Equipment Journal,2025,46(4):100-107]