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 The aim of the study is to analyze the incidence patterns and epidemiological characteristics of parasitic and vector-borne diseases in the Minhang and Jinshan districts of Shanghai, and provide evidence-based information for optimizing prevention and control measures. Methods We collected information from epidemic reports and epidemiological investigation forms for cases of parasitic and vector-borne diseases from 2005 to 2024 in Shanghai's Minhang and Jinshan districts. Descriptive epidemiological method were adopted to conduct a comparative analysis of incidence trends, epidemic characteristics, and infection sources. Results A total of 229 cases in 7 categories were reported between 2005 and 2024, with an average annual incidence rate of 0.36/100 000. The average annual incidence rate in Minhang District was significantly higher than that in Jinshan District. The most prevalent diseases were malaria and dengue fever, followed by Japanese encephalitis. Monthly case reports were available, predominantly from June to October, with a peak in July-August. A statistically significant difference was observed between the two districts in case distribution during June-October (P＜0.001), whereas no significant difference was found for July-August (P=0.331). The majority of cases were young men (111/229,48.47%), aged 20-39 years. Migrant workers/farmers constituted the largest occupational group (55/229, 24.02%). Registered residents of other provinces and cities (147/229,64.19%), and the main source of infection was overseas importation (112/229,48.91%). There were no statistically significant differences in gender and household-registration composition between the two districts (P＞0.05). Significant differences existed in age, occupation, and source of infection (P＜0.05). The imported diseases were malaria and dengue fever, with Africa and Southeast Asia being the primary source locations. Malaria was the predominant disease imported from other provinces and cities, with cases having been imported from abroad since 2012. Local infections were mainly Japanese encephalitis, followed by malaria (with the last local case reported in 2010). Cases between 2005 and 2009 were predominantly imported from other provinces and cities. The proportion of cases imported from abroad increased sharply after 2010, particularly in Minhang District. Local infections sometimes arise in Jinshan District, with Japanese encephalitis serving as the primary type. Conclusions Incidence rates of parasitic and vector-borne diseases in Minhang and Jinshan districts have generally remained low. To further reduce this disease burden, it will be necessary to strengthen joint measures for prevention and control, eliminate the environmental risk factors of vector organisms, enhance monitoring and precise control of the environment and inbound personnel to prevent the occurrence and transmission of parasitic and vector-borne diseases.

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

Astragalus membranaceus(A. membranaceus), a traditional tonic, contains flavonoids as one of its main bioactive components and key indicators for quality standard detection. These compounds predominantly exist in glycosylated forms after glycosylation modification within the plant. The catalytic products of flavonoid glycosyltransferases in A. membranaceus have been reported to be mostly monoglycosides, and only AmUGT28 catalyzes luteolin to form diglycosides. In this study, we cloned a glycosyltransferase gene, AmGT90, from A. membranaceus, with an ORF length of 1 335 bp, encoding 444 amino acids, and the protein had a relative molecular mass of 50.5 kDa. Phylogenetic tree analysis indicated that AmGT90 belongs to the UGT74 family. In vitro enzymatic reaction showed that AmGT90 had broad substrate specificity and could catalyze the glycosylation of various flavonoids, including isoflavones, flavones, flavanones, and chalcones. AmGT90 not only catalyzed the formation of monoglycosides but also diglycosides. In addition, the mechanism of AmGT90 catalyzing the formation of diglycosides from luteolin was preliminarily explored. The experimental results showed that AmGT90 may preferentially recognize C4'-OH of luteolin and then recognize C7-OH to form diglycosides. This study reported a glycosyltransferase from A. membranaceus capable of converting flavonoids into monoglycosides and diglycosides. This finding not only enhances our understanding of the biosynthetic pathways of flavonoid glycosides in A. membranaceus but also introduces a new component for glycoside production through synthetic biology.
Glycosyltransferases/chemistry* ; Flavonoids/chemistry* ; Astragalus propinquus/classification* ; Phylogeny ; Glycosylation ; Plant Proteins/chemistry* ; Substrate Specificity ; Cloning, Molecular ; Amino Acid Sequence

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

A comprehensive phytochemical investigation of the leaves and twigs of Physalis angulata. var. villosa resulted in the isolation of 23 withanolide derivatives, including one novel 13,20-γ-lactone withanolide derivative (1) and three new withanolide derivatives (2-4). Architecturally, physalinin A (1) represents the first identified type B withanolide featuring a 13,20-γ-lactone moiety. The molecular structures of all isolates were elucidated using an integrated approach combining nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), infrared (IR) spectroscopy, and quantum chemical calculations to confirm structural assignments. The antiproliferative activities of all isolated withanolides were evaluated against four human cancer cell lines (HEL, HCT-116, Colo320DM, and MDA-MB-231). Among them, eight derivatives (2, 5-8, 14, 15, and 23) exhibited significant inhibitory effects, with half-maximal inhibitory concentration (IC₅₀) values of 0.18 ± 0.03 to 17.02 ± 0.21 μmol·L^-1. Structure-activity relationship (SAR) analysis suggested that the presence of an epoxide ring enhances anticancer activity, potentially through increased reactivity or specific interactions with molecular targets involved in cancer progression. These findings underscore the pharmacological potential of withanolides as promising lead compounds for the development of novel anticancer therapeutics.
Withanolides/isolation & purification* ; Physalis/chemistry* ; Humans ; Molecular Structure ; Cell Line, Tumor ; Antineoplastic Agents, Phytogenic/isolation & purification* ; Cell Proliferation/drug effects* ; Plant Leaves/chemistry* ; Plant Extracts/pharmacology*

Cytokeratin 19 fragment antigen 21-1(CYFRA21-1)is a new biomarker which has received much attention in recent years for cancer screening,and has shown great potentials for screening and diagnosis of various cancers,especially non-small cell lung cancer.CYFRA21-1 level in human serum has important clinical significance in the diagnosis,prognosis and treatment of lung cancer.Recently,a variety of detection techniques have been established to effectively enrich the detection technology system of CYFRA21-1,such as enzyme-linked immunosorbent assay,chemiluminescence,fluorescence,immunochromatography,electrochemical method,and surface enhanced Raman spectroscopy,etc.These techniques provide technical support for early diagnosis of lung cancer.However,the research progress of CYFRA21-1 detection methods is rarely reported.In this paper,CYFRA21-1 and its clinical significance were briefly introduced,and the progress of detection technology in recent ten years was reviewed,which was expected to provide reference for developing more sensitive,accurate,fast and convenient detection methods.

Objective:To explore the medication law of TCM external therapy for the treatment of diabetic foot using data mining methods.Methods:Literature on TCM external treatment for diabetic foot was retrieved from CNKI, Wanfang Data, and Chongqing VIP from the establishment of the databases to June 30, 2024. Excel 2019 software was used to conduct frequency statistics on drug frequency, properties, tastes and meridian tropism, drug efficacy, and commonly used drug pairs. Ancient and Modern Medical Cases Cloud Platform V3.5 was used for association rules, and SPSS Statistics 27.0 was used for complex network analyses.Results:A total of 425 articles were included, involving 328 prescriptions and 232 drugs. The drugs with higher frequency were Carthami Flos, Angelicae Sinensis Radix, Cinnamomi Ramulus, Olibanum, etc. The main tastes were pungent, bitter, and sweet; the main properties were cold and warm; the main meridians were heart, spleen, and liver meridians. The main efficacy was promoting blood circulation and removing blood stasis, clearing heat, and tonifying deficiency; association rule analysis obtained 20 commonly used drug pairs; clustering analysis resulted in four core drug combinations; complex network analysis led to one core prescription.Conclusions:TCM external therapy for diabetic foot follows the guiding principles of "promoting blood circulation and unblocking collaterals, tonifying deficiency and clearing heat" with coordinated regulation of the "heart-liver-spleen meridians". The core prescription and stage-specific formulation strategies reflect a trinity diagnostic and therapeutic approach of "disease differentiation-syndrome differentiation-stage differentiation", providing valuable reference and insights for clinical prescription practices.

Objective:To explore the potential advantages and application prospects of cardiopulmonary resuscitation ventilation mode (CPRV) for ventilation during CPR, through comparing of the resuscitation effect of CPRV, intermittent positive pressure ventilation (IPPV) and impedance threshold device (ITD) during advanced cardiovascular life support (ACLS).Methods:30 miniature landrace pigs [weighing (31.7±4.5) kg] were randomly divided into three groups: CPRV group, IPPV group and ITD group (10 pigs in each group). Each animal received 5 min of chest compressions only CPR after 3 min of untreated ventricular fibrillation. Then in the ACLS stage, chest compressions and mechanical ventilation (tidal volume of 7 mL/kg, respiratory rate 10 times/min) were performed according to the divided groups. Defibrillation was delivered after 16 min of ACLS, and intravenous epinephrine was administered for the pigs without return of spontaneous circulation (ROSC). A second defibrillation was delivered after 2 more minutes of CPR. Blood gases, respiratory parameters, and hemodynamic parameters were collected at baseline, ACLS 8 min and ACLS 16 min. ROSC after defibrillation was also recorded.Results:At ACLS 8 min and 16 min, intrathoracic high pressure and intrathoracic pressure variability of CPRV group were significantly higher than those of IPPV and ITD group, while the absolute value of intrathoracic negative pressure in CPRV group was higher than that in IPPV group (all P <0.01), but no difference was found between CPRV group and ITD group. The levels of arterial pH, PaO 2 and venous oxygen saturation in CPRV group were significantly higher than those in IPPV group and ITD group during ACLS, while PaCO 2 was significantly lower in CPRV group than in IPPV group and ITD group (all P <0.05). Aortic blood pressure, coronary perfusion pressure and carotid blood flow during ACLS in CPRV group were significantly higher than those in IPPV group, and right atrial pressure of CPRV group was significantly lower than that of IPPV group (all P <0.05). Coronary perfusion pressure of CPRV group was significantly higher than that of ITD group at ACLS 16 min but not ACLS 8 min, and there were no differences of aortic blood pressure and carotid blood flow between CPRV group and ITD group. The total ROSC rate in the CPRV group (90%) was significantly higher than that in the IPPV group (30%) and the ITD group (40%) (P <0.05). Conclusion:Ventilation with CPRV during ACLS showed better ventilation, oxygenation, hemodynamic effects and higher ROSC than IPPV and ITD, and the use of CPRV during CPR shows a certain application prospect.