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.

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 explore the impact and underlying mechanisms of social support on illness uncertainty among parents of children with autism.Methods:A convenience sample of 312 parents of children with autism was recruited from the outpatient clinic of Peking University Sixth Hospital between September 2023 and January 2024. Data were collected using a general information questionnaire, the Chinese version of the Parent's Perception Uncertainty Scale (PPUS), the Social Support Scale for Families with Children with Autism, the Generalized Anxiety Disorder-7 (GAD-7), and the Questionnaire on Caregiving Issues and Service Needs of Parents of Children with Autism. Independent samples t-tests or one-way ANOVA were used to compare illness uncertainty scores across different characteristics. Pearson correlation analysis examined relationships among illness uncertainty, social support, caregiving issues and service needs, and anxiety. Chain mediation analysis was conducted using the SPSS macro PROCESS v4.1 to test the mediating roles of caregiving issues and service needs and anxiety. Results:The illness uncertainty score of the 307 valid respondents was (82.40±14.09). Mediation analysis indicated a direct effect of social support on illness uncertainty (effect value=-1.040), accounting for 72.27% of the total effect (-1.040/-1.439). A chain-mediated effect through caregiving issues and service needs and anxiety was also observed (effect value=-0.065), accounting for 4.50% of the total effect (-0.065/-1.439) .Conclusions:Parents of children with autism experience a relatively high level of illness uncertainty. Enhancing social support, addressing caregiving issues and service needs, alleviating parental anxiety may reduce their illness uncertainty.

Aim To explore the relevant mechanisms of isoliquiritigenin(ISL)in inhibiting the proliferation and migration of vascular smooth muscle cells(VSMCs)by regulating the GRB2/ERK signaling pathway.Methods Human primary vascular smooth muscle cells(hVSMCs)were cultured,and stimulated with different concentrations of ISL and fixed concen-trations of growth factors PDGF-BB and EGF,respec-tively.Subsequently,the effect of overexpressing GRB2 on the efficacy of ISL was observed.CCK-8 assay was used to detect cell proliferation;BrdU assay was used to detect DNA synthesis;Western blot was used to de-tect the expression levels of OPN,ICAM-1,VCAM-1,GRB2,ERK1/2,and p-ERK1/2;wound healing assay was used to detect cell migration;transwell assay was used to detect cell invasion.Results Compared with the blank control group and the ISL 20 mg·L-1 group,the PDGF-BB group and the EGF group showed increased cell viability and DNA synthesis,decreased cell migration distance,and increased number of inva-sive cells.Additionally,the expression levels of GRB2 and p-ERK1/2 increased.Compared with the PDGF-BB 40 μg·L-1group or the EGF 10 mg·L-1 group,the ISL drug intervention group showed decreased cell viability and DNA synthesis,increased migration dis-tance of cells,decreased number of invasive cells,and decreased expression levels of GRB2 and p-ERK1/2.Compared with the ISL 20 mg·L-1+PDGF-BB and ISL 20 mg·L-1+EGF groups,the groups with ISL+PDGF-BB+pcDNA-GRB2 group and ISL+EGF+pcDNA-GRB2 group showed increased expression lev-els of GRB2,p-ERK1/2,OPN,ICAM-1,and VCAM-1,increased cell viability and DNA synthesis,decreased migration distance,and increased number of invasive cells.Compared with the ISL+PDGF-BB+pcDNA-GRB2 group and the ISL+EGF+pcDNA-GRB2 group,the pcDNA-GRB2+PDGF-BB group or the pcDNA-GRB2+EGF group showed increased expres-sion levels of GRB2,p-ERK1/2,OPN,ICAM-1,and VCAM-1,increased cell viability and DNA synthesis,decreased migration distance,and increased number of invasive cells.Conclusions Isoliquiritigenin inhibits the proliferation and migration of vascular smooth mus-cle cells by regulating the GRB2/ERK signaling path-way.

AIM To study the chemical constituents from the leaves of Drynaria fortunei(Kunze)J.Sm.and their antioxidant activity.METHODS ODS-AG-HG,Sephadex LH-20 and semi-preparative HPLC were used for separation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH mothod.RESULTS Fifteen compounds were isolated and identified as kaempferol-3-O-neohesperidoside(1),dihydrodehydrodiconiferyl alcohol(2),kaempferol-3,7-di-O-α-L-rahmnoside(3),astragalin(4),loliolid(5),trichothecene analogue(6),2,2-[bis-4-(2,3-dihydroxypropoxy)phenyl]propane(7),maculatin(8),trichothecin(9),4-[(Z)-but-2-enoyloxy]-8-chloro-12-hydroxy-7,13-epoxytrichothec-9-ene(10),8-deoxy-trichotecin(11),β-sitosterol(12),daucosterol(13),afzelin(14),samwinol(15).The IC50 values of the leaf and rhizome extracts against DPPH free radicals were(0.072±0.005),(0.287±0.012)mg/mL,respectively.CONCLUSION Compounds 1,2,5-11,15 are isolated from this plant for the first time.The leaves of D.fortunei exhibit strong antioxidant activity.

OBJECTIVES: This study aimed to investigate the impact of foam macrophages (FMs) on the intracellular survival of Mycobacterium tuberculosis (MTB) and identify the molecular mechanisms influencing MTB survival. METHODS: An in vitro FM model was established using oleic acid induction. Transcriptomic and metabolomic analyses were conducted to identify the key molecular pathways involved in FM-mediated MTB survival. RESULTS: Induced FMs effectively restricted MTB survival. Transcriptomic and metabolomic profiling revealed distinct changes in gene and metabolite expression in FMs during MTB infection compared with normal macrophages. Integrated analyses identified significant alterations in the cyclic adenosine monophosphate (cAMP) signaling pathway, indicating that its activation contributes to the FM-mediated restriction of MTB survival. CONCLUSIONS FMs inhibit MTB survival. The cAMP signaling pathway is a key contributor. These findings enhance the understanding of the role of FMs in tuberculosis progression, suggest potential targets for host-directed therapies, and offer new directions for developing diagnostic and therapeutic strategies against tuberculosis.
Mycobacterium tuberculosis/physiology* ; Transcriptome ; Metabolomics ; Foam Cells/microbiology* ; Humans ; Metabolome ; Tuberculosis/microbiology* ; Gene Expression Profiling

The chemical components of Carthami Flos were investigated by using macroporous resin, silica gel column chromatography, reversed-phase octadecylsilane(ODS) column chromatography, Sephadex LH-20, and semi-preparative high-performance liquid chromatography(HPLC). The planar structures of the compounds were established based on their physicochemical properties and ultraviolet-visible(UV-Vis), infrared(IR), high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), and nuclear magnetic resonance(NMR) spectroscopic technology. The absolute configurations were determined by comparing the calculated and experimental electronic circular dichroism(ECD). Six flavonoid C-glycosides were isolated from the 30% ethanol elution fraction of macroporous resin obtained from the 95% ethanol extract of Carthami Flos, and identified as saffloquinoside F(1), 5-hydroxysaffloneoside(2), iso-5-hydroxysaffloneoside(3), isosafflomin C(4), safflomin C(5), and vicenin 2(6). Among these, the compounds 1 to 3 were new chalcone C-glycosides. The compounds 1, 2, 4, and 5 could significantly increase the viability of H9c2 cardiomyocytes damaged by oxygen-glucose deprivation/reoxygenation(OGD/R) at a concentration of 50 μmol·L~(-1), showing their good cardioprotective activity.
Glycosides/pharmacology* ; Flowers/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Carthamus tinctorius/chemistry* ; Chalcones/pharmacology* ; Animals

Cistanches Herba(CH) is a famous tonic traditional Chinese medicine, with the effects of tonifying kidney Yang, nourishing kidney Yin, replenishing essence and blood, and moistening the intestines to relieve constipation. Modern pharmacological studies have shown that CH has anti-aging, anti-fatigue, immunomodulatory, neuroprotective, and anti-aging activities, serving as an ideal raw material for the development of pharmaceuticals and health products. In 2023, CH was added in the catalog of medicinal and food substances, which provided policy support for its application in conventional food products and expanding pathways for industrial diversification. To comprehensively understand current development status of CH products, this review systematically investigated professional databases including Yaozhi(https://db.yaozh.com), Chinese Pharmacopoeia, Compendium of National Standards for Chinese Patent Medicines, and Kezhuang and collected market survey data to thoroughly review the applications of CH as a primary ingredient in domestic and international Chinese patent medicines, health foods, cosmetics, and common food products. Furthermore, this review points out challenges in the current industrial development and future potential market prospects, aiming to provide guidance for the development and industrialization of CH-based pharmaceuticals and health products, thereby promoting the vigorous growth of the CH industry.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Cistanche/chemistry* ; Animals ; Medicine, Chinese Traditional

OBJECTIVES: To construct a Z-score regression model for coronary artery diameter based on echocardiographic data from children in Sichuan Province and to establish a Z-score calculation formula. METHODS: A total of 744 healthy children who underwent physical examinations at Sichuan Provincial People's Hospital from January 2020 to December 2022 were selected as the modeling group, while 251 children diagnosed with Kawasaki disease at the same hospital from January 2018 to December 2022 were selected as the validation group. Pearson correlation analysis was conducted to analyze the relationships between coronary artery diameter values and age, height, weight, and body surface area. A regression model was constructed using function transformation to identify the optimal regression model and establish the Z-score calculation formula, which was then validated. RESULTS: The Pearson correlation analysis showed that the correlation coefficients for the diameters of the left main coronary artery, left anterior descending artery, left circumflex artery, and right coronary artery with body surface area were 0.815, 0.793, 0.704, and 0.802, respectively (P<0.05). Among the constructed regression models, the power function regression model demonstrated the best performance and was therefore chosen as the optimal model for establishing the Z-score calculation formula. Based on this Z-score calculation formula, the detection rate of coronary artery lesions was found to be 21.5% (54/251), which was higher than the detection rate based on absolute values of coronary artery diameter. Notably, in the left anterior descending and left circumflex arteries, the detection rate of coronary artery lesions using this Z-score calculation formula was higher than that of previous classic Z-score calculation formulas. CONCLUSIONS The Z-score calculation formula established based on the power function regression model has a higher detection rate for coronary artery lesions, providing a strong reference for clinicians, particularly in assessing coronary artery lesions in children with Kawasaki disease.
Humans ; Male ; Female ; Child, Preschool ; Child ; Coronary Artery Disease/diagnostic imaging* ; Infant ; Mucocutaneous Lymph Node Syndrome ; Regression Analysis ; Coronary Vessels/diagnostic imaging* ; Echocardiography ; Adolescent