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.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

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.

AIM To investigate the in vivo pharmacokinetics of chlorogenic acid,isoquercetin,ferulic acid,isorhamnetin and shionone in Asteris Radix et Rhizoma in rats.METHODS Twelve rats were randomly assigned into 2 groups and given intragastric administration of conventional dose(0.63 g/kg)and large dose(3.3 g/kg)of Asteris Radix et Rhizoma extracts,respectively,after which blood collection was made at 0.083,0.167,0.33,0.5,0.75,1,1.5,2,4,6,8,12,24 h,UPLC-MS/MS was adopted in the plasma concentration determination of various effective constituents,and main pharmacokinetic parameters were calculated.RESULTS Various effective constituents in the large dose group demonstrated prolonged t1/2,MRT0-∞ as compared with those in the conventional dose group(P＜0.05).After dose correction,Cmax of chlorogenic acid,isoquercetin,shionone in the large dose group displayed no obvious changes(P＞0.05),while Cmax of ferulic acid,isorhamnetin,and AUC0-t,AUC0-∞ of various effective constituents were higher than those in the conventional dose group(P＜0.05).CONCLUSION Various effective constituents in the high dose of Asteris Radix et Rhizoma can maintain high-concentration and long-time effects on rat bladder tissue.

This study was aimed at investigating the effects and mechanisms of Toxoplasma gondii type Ⅰ(RH strain)ROP16 protein on proliferation and the cell cycle in mouse alveolar macrophage MH-S cells.We constructed a Toxoplasma gondii type Ⅰ(RH)ROP16 overexpression lentivirus,transduced MH-S cells,and then screened cells with puromycin to obtain a cell line stably overexpressing ROP16Ⅰ.RT-qPCR and western blotting were used to verify expression effects,CCK-8 assays were used to detect cell proliferation activity,and flow cytometry was used to detect cell cycle changes.Western blotting and RT-qPCR were used to detect the expression levels of p53,p21,CDK6,Cyclin D1,STAT3,p-STAT3(Y705),and JAK1 proteins or genes,and immunofluorescence was used to detect the expression levels of ROP16Ⅰ and p-STAT3(Y705)and their subcellular co-localization in MH-S cells.ROP16Ⅰ protein and gene expression were detected in MH-S cells transduced with lentivirus for ROP16Ⅰ overexpression.CCK-8 assays revealed that ROP16Ⅰ promoted the proliferation of MH-S cells(P＜0.01)and enhanced cell viability.Flow cytometry revealed that ROP16Ⅰ overexpression decreased the G0/G1 phase and elevated the G2 and S phases of the cell cycle in MH-S cells(P＜0.01 or P＜0.05).Compared with the MH-S cell group and MH-S-empty vector group,the MH-S-ROP16 cell group showed lower expression of p53 and p21 proteins;higher expression of CDK6,Cyclin D1,p-STAT3(Y705),and JAK1 proteins;lower expression of p53 and p21 mRNAs;and higher expression of CDK6 and Cyclin D1 mRNAs(all P＜0.01).Immunofluorescence revealed that ROP16Ⅰ co-localized with p-STAT3(Y705)in the nucleus and surrounding cytoplasm.Therefore,Toxoplasma gondii type Ⅰ(RH)ROP16Ⅰ protein activates the JAK-STAT3 pathway;shortens the G0/G1 phase and lengthens the G2/S phase of the cell cycle;and promotes cell proliferation.These findings provide a theoretical basis for revealing the mechanism of immune evasion of Toxoplasma gondii,and lay a foundation for research on the prevention and treatment of Toxoplasma gondii pneumonia.

This study assessed the role and mechanism of the recombinant Bacillus Calmette-Gue?rin vaccine(rBCG)with c-di-AMP adjuvant in regulating metabolism and immunity in epididymal white adipose(eWAT)in mice.Male C57BL/6 mice were intravenously immunized with BCG and rBCG,and their body weights were monitored.eWAT was isolated from the mice,and the stromal vascular fractions(SVFs)cell number was counted with a hemocytometer.Sections of mouse adipose tissue were prepared,and the size,number,and morphology of eWAT adipocytes and crown-like structure(CLS)formation were compared under a microscope after HE staining.The transcription levels of lipid metabolism-associated factors,cytokines and aging-associated genes in each group were determined with qRT-PCR.The body weights of mice gradually increased after immunization with BCG and rBCG.The proportions of eWAT increased,and the SVFs cell number decreased,in rBCG immunized mice.HE staining indicated that BCG immunization promoted hyperplasia,whereas rBCG immunization promoted hypertrophy of eWAT adipocytes;moreover,both BCG and rBCG immunization induced CLS formation in eWAT.The qRT-PCR results indicated that rBCG immunization inhibited the expression of genes associated with lipolysis and energy expenditure in eWAT.BCG immunization had little effect on cytokine transcription,whereas rBCG significantly induced the transcription of IFN-γ and IL-1Ra,and inhibited that of IL-15 and IL-2,but did not induce the expression of aging-associated genes.Thus,rBCG immunization induced eWAT adipocyte hypertrophy,which was associated with the inhibition of eWAT lipolysis and the regulation of cytokine expression.

Objective To develop a hypoxia endurance testing system for aviation physiological training of pilots.Methods The hypoxia endurance testing system comprised a low-oxygen mixed gas generator,a pressurization system for low-oxygen mixed gas and a personal breathing apparatus.The low-oxygen mixed gas generator consisted of a main unit composed of an air compressor,a filter,a buffer tank,polymer membrane,a control module,sensors and regulators,wire cables,supporting hoses,etc.;the pressurization system for low-oxygen mixed gas was made up of a protective box,a cooling fan,a motor and a driver,a control module,a solenoid valve,a convergence block,a pressure gauge,etc.;the personal breating apparatus was composed of a gas cylinder,a pressure reducer,an oxygen supply regulator,etc.Forty-eight subjects were selected for hypoxia exposure tests to verify the effectiveness of the system.Results The system developed had the functions of low-oxygen gas preparation,pressurized filling and hypoxia experiment,and the experimental results indicated the acute hypoxia exposure by the system significantly caused signs and symptoms of hypoxia and weakened physiological functions.Conclusion The system developed gains advantages in high accuracy of gas volume fraction control,safety and remarkable effect of simulated hypoxia,and can be an effective tool for acute high-altitude hypoxia testing and training of pilots.[Chinese Medical Equipment Journal,2025,46(10):23-28]

On the basis of that the fluorescence wavelength of copper nanoclusters(CuNCs)could cover the entire visible region,multicolor fluorescent CuNCs/starch composites were prepared and applied in fingermark development.With L-glutathione as the reducing agent and protective ligand,blue emissive and orange emissive CuNCs solutions were obtained in alkaline solutions at 90℃and 25℃,respectively.With the aggregation-induced emission effect induced by ethanol as a poor solvent,the fluorescence of orange emissive CuNCs with a higher intensity was achieved in an ethanol-water solution.With ascorbic acid as the reducing agent and 3-mercaptopropionic acid as the protective agent,green emissive CuNCs solution was prepared in an acid solution.Particle morphologies,chemical compositions and optical properties of these three CuNCs above were investigated using physical characterization and spectroscopic analysis,indicating that well-dispersed CuNCs had excellent photoluminescent properties.These CuNCs solutions were combined with starch to form composite powders by simply drying.The influences of the type of CuNCs and the ratio of CuNCs to starch on the emission wavelength and fluorescence intensity of the products were studied.The obtained CuNCs/starch composites could emit blue,green and orange fluorescence under 365 nm ultraviolet light,respectively,which were suitable for fingermark development.Minutiae and partial level-3 features of latent fingermarks could be effectively developed.High-quality fluorescence fingermark images would be captured using appropriate optical filters to eliminate background interference of various substrates.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.

Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.