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 investigate the population composition,seasonal dynamics,and infestation levels of cockroaches in Lanzhou,China,and to provide information for the scientific development of cockroach control strategies.Methods Monitoring was conducted at three locations using the sticky trap method.Habitats included farm product markets,catering establishments,hotels,hospitals,and residential areas.Results From 2016 to 2023,the average cockroach density was 0.77 insects per board,with an average infestation rate of 10.84%.Blattella germanica was the dominant species.Seasonal density of cockroaches showed an approximately unimodal distribution,peaking in September.The highest average density and infestation rates were observed in farm product markets.Conclusions Cockroach density and infestation levels in Lanzhou remained relatively low.A comprehensive prevention and control strategy focusing on environmental management in key areas should be implemented according to the seasonal fluctuations.

Based on the high-fat diet-induced hyperlipidemia rat model, this study aimed to evaluate the lipid-lowering effect of Arisaema Cum Bile and explore its mechanisms, providing experimental evidence for its clinical application. Biochemical analysis was used to detect serum levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-C), triglycerides(TG), and total cholesterol(TC) to assess the lipid-lowering activity of Arisaema Cum Bile. Additionally, 16S rDNA sequencing and metabolomics techniques were employed to jointly elucidate the lipid-lowering mechanisms of Arisaema Cum Bile. The experimental results showed that high-dose Arisaema Cum Bile(PBA-H) significantly reduced serum ALT, AST, LDL-C, TG, and TC levels(P<0.01), and significantly increased HDL-C levels(P<0.01). The effect was similar to that of fenofibrate, with no significant difference. Furthermore, Arisaema Cum Bile significantly alleviated hepatocyte ballooning and mitigated fatty degeneration in liver tissues. As indicated by 16S rDNA sequencing results, PBA-H significantly enhanced both alpha and beta diversity of the gut microbiota in the model rats, notably increasing the relative abundance of Akkermansia and Subdoligranulum species(P<0.01). Liver metabolomics analysis revealed that PBA-H primarily regulated pathways involved in arachidonic acid metabolism, vitamin B_6 metabolism, and steroid biosynthesis. In summary, Arisaema Cum Bile significantly improved abnormal blood lipid levels and liver pathology induced by a high-fat diet, regulated hepatic metabolic disorders, and improved the abundance and structural composition of gut microbiota, thereby exerting its lipid-lowering effect. The findings of this study provide experimental evidence for the clinical application of Arisaema Cum Bile and the treatment of hyperlipidemia.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Metabolomics ; Hyperlipidemias/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Hypolipidemic Agents/pharmacology* ; Liver/metabolism* ; Humans ; Alanine Transaminase/metabolism* ; Triglycerides/metabolism* ; Aspartate Aminotransferases/metabolism*

This study compared the differences in intestinal absorption characteristics of eleven active components in Rubus multibracteatus(RM) extract(protocatechuic acid, tiliroside, scutellarin, luteoloside, astragalin, epicatechin, catechin, xanthotoxin, p-coumaric acid, caffeic acid, and apigenin-7-O-glucuronide) between normal rats and inflammatory pain model rats using the in-vitro everted intestinal sac model. The RM extract was administered at absorption concentrations of 25.0, 50.0, and 100.0 mg·mL~(-1). The contents of the eleven components in intestinal absorption solution samples were quantified by ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS), and their cumulative absorption(Q) and absorption rate constant(K_a) were calculated to evaluate the absorption characteristics of these components in normal rats and inflammatory pain model rats. The results show that except for catechin, epicatechin, and caffeic acid, the cumulative absorption-time curves of the other eight components(protocatechuic acid, tiliroside, scutellarin, luteoloside, astragalin, xanthotoxin, p-coumaric acid, and apigenin-7-O-glucuronide) exhibit an upward trend without saturation, with correlation coefficients(R~2) all > 0.9, indicating linear absorption. However, the overall absorption of all components is not dose-dependent with increasing concentration, suggesting that their absorption mechanisms are not solely passive diffusion. In both normal and model rats, the jejunum shows the highest absorption for all components except xanthotoxin. The overall absorption of seven components(excluding protocatechuic acid, caffeic acid, apigenin-7-O-glucuronide, and luteoloside) in normal rats is better than that in model rats across all intestinal segments. These findings indicate that the pathological state of inflammatory pain alters the intestinal absorption of RM extract, and its mechanism needs further investigation.
Animals ; Rats ; Intestinal Absorption/drug effects* ; Male ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/metabolism* ; Disease Models, Animal ; Pain/metabolism* ; Intestines/drug effects* ; Intestinal Mucosa/metabolism*

OBJECTIVES: To assess the preliminary efficacy and safety of a dose-intensified C5VD regimen (cisplatin, 5-fluorouracil, vincristine, and doxorubicin) in children with locally advanced hepatoblastoma. METHODS: This prospective study enrolled 24 children with newly diagnosed, locally advanced hepatoblastoma who received the dose-intensified C5VD regimen at Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, and Shanghai Children's Hospital between January 2020 and December 2023. Clinical characteristics, treatment outcomes, and chemotherapy-related toxicities were analyzed. RESULTS: Of the 24 patients, 13 were male and 11 were female, with a median age at diagnosis of 18.7 months (range: 3.5-79.4 months). All patients achieved complete macroscopic resection of hepatic lesions without liver transplantation. Serum alpha-fetoprotein levels decreased significantly after two chemotherapy cycles. During a median follow-up of 38.4 months (range: 15.8-50.7 months), all patients maintained continuous complete remission, with 3-year event-free survival and overall survival rates of 100%. Across 144 chemotherapy cycles, the incidence rates of grade 3-4 neutropenia, thrombocytopenia, and infections were 97%, 77%, and 71%, respectively; no treatment-related deaths occurred. Notably, 5 patients (21%) developed Brock grade ≥3 hearing loss, of whom 1 required a hearing aid. CONCLUSIONS The dose-intensified C5VD regimen demonstrates significant efficacy with an overall favorable safety profile in the treatment of newly diagnosed, locally advanced pediatric hepatoblastoma. Grade 3-4 myelosuppression and infection are the predominant toxicities. However, high‑dose cisplatin-induced ototoxicity remains a concern, highlighting the need for improved otoprotective strategies.
Humans ; Hepatoblastoma/pathology* ; Male ; Female ; Infant ; Liver Neoplasms/pathology* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Child, Preschool ; Prospective Studies ; Doxorubicin/adverse effects* ; Child ; Cisplatin/adverse effects* ; Vincristine/adverse effects* ; Fluorouracil/adverse effects*

Pharmacokinetics of traditional Chinese medicine(TCM)is a discipline that adopts pharmacokinetic research methods and techniques under the guidance of TCM theories to elucidate the dynamic changes in the absorption,distribution,metabolism and excretion of active ingredients,active sites,single-flavour Chinese medicinal and compounded formulas of TCM in vivo.However,the sources and components of TCM are complex,and the pharmacodynamic substances and mechanisms of action of the majority of TCM are not yet clear,so the pharmacokinetic study of TCM is later than that of chemical medicines,and is far more complex than that of chemical medicines,and its development also confronts with challenges.The pharmacokinetic study of TCM originated in the 1950s and has experienced more than 70 years of development from the initial in vivo study of a single active ingredient,to the pharmacokinetic and pharmacodynamic study of active ingredients,to the pharmacokinetic study of compound and multi-component of Chinese medicine.In recent years,with the help of advanced extraction,separation and analysis technologies,gene-editing animals and cell models,multi-omics technologies,protein purification and structure analysis technologies,and artificial intelligence,etc.,the pharmacokinetics of TCM has been substantially applied in revealing and elucidating the pharmacodynamic substances and mechanisms of action of Chinese medicines,research and development of new drugs of TCM,scientific and technological upgrading of large varieties of Chinese patent medicines,as well as guiding the rational use of medicines in clinics.Pharmacokinetic studies of TCM have made remarkable breakthroughs and significant development in theory,methodology,technology and application.In this paper,the history of the development of pharmacokinetics of TCM and the progress of cutting-edge research was reviewed,with the aim of providing ideas and references for the pharmacokinetics of TCM and related research.

The 2-(2-phenylethyl)chromones were separated from agarwood of Aquilaria agallocha Roxb. and their anti-KRAS mutant non-small cell lung cancer (NSCLC) activities were evaluated. 2-(2-Phenyethyl)chromones in agarwood were separated and purified by silica gel, RP-18 reverse phase silica gel, MCI gel CH20P, Diol, and semi preparative HPLC chromatography techniques, while the structures of the compounds were identified by extensive spectroscopic analysis, such as 1D and 2D NMR and ESI-MS. The cell counting kit 8 (CCK-8) assay was used to screen the anti-tumor activity of the isolated monomeric compounds on three KRAS-mutant NSCLC cells. The cell proliferation, cloning formation, adhesion ability, and cell cycle arrest activity of compound 8 were analyzed. Molecular docking and Western blot experiments were used to study the mechanism of compound 8. The in vivo anti-tumor activity of the compound 8 was evaluated by zebrafish cell derived xenograft (CDX) model. Nineteen known 2-(2-phenylethyl)chromones were isolated from the ethyl acetate extract of agarwood. On A549 (KRAS G12S) cells, compounds 8, 10, and 19 showed good inhibitory activity, on H23 (KRAS G12C) cells, compounds 7, 8, and 19 showed good inhibitory activity, and on H358 (KRAS G12C) cells, compounds 8, 10, and 16 showed good inhibitory activity. Compound 8 had the best inhibitory activity in all three cell lines. It effectively inhibited cell proliferation, clone formation, adhesion ability, and arrested the H23 cell cycle at G2/M phase. Compound 8 could also inhibit the expression of c-Met and its downstream signaling pathways, effectively inhibiting tumor growth in zebrafish CDX model. In conclusion, among the nineteen known 2-(2-phenylethyl)chromones, compound 8 had the best activity and significantly inhibited the proliferation of KRAS-mutant NSCLC cells by arresting the cells in the G2/M phase.

Objective: To investigate the response characteristics of patients with locally advanced/metastatic non-squamous non-small cell lung cancer (nsq-NSCLC) treated with tislelizumab in combination with chemotherapy in the first line. Methods: Patients with nsq-NSCLC who achieved complete or partial remission after treatment with tislelizumab in combination with chemotherapy or chemotherapy alone in the RATIONALE 304 study, as assessed by an independent review board, were selected to analyze the response characteristics and safety profile of the responders. Time to response (TTR) was defined as the time from randomization to the achievement of first objective response. Depth of response (DpR) was defined as the maximum percentage of tumor shrinkage compared with the sum of the baseline target lesion length diameters. Results: As of January 23, 2020, 128 patients treated with tislelizumab in combination with chemotherapy achieved objective tumor response (responders), representing 57.4%(128/223) of the intention-to-treat population, with a TTR of 5.1 to 33.3 weeks and a median TTR of 7.9 weeks. Of the responders (128), 50.8%(65) achieved first remission at the first efficacy assessment (week 6), 31.3%(40) at the second efficacy assessment (week 12), and 18.0%(23) at the third and subsequent tumor assessments. The percentages of responders who achieved a depth of tumor response of 30% to <50%, 50% to <70% and 70% to 100% were 45.3%(58/128), 28.1%(36/128) and 26.6%(34/128), respectively, with median progression-free survival (PFS) of 9.0 months (95% CI: 7.7 to 9.9 months), 11.5 months (95% CI: 7.7 months to not reached) and not reached (95% CI: 11.8 months to not estimable), respectively. Tislelizumab plus chemotherapy were generally well tolerated in responders with similar safety profile to the overall safety population. Conclusion: Among responders to tislelizumab in combination with chemotherapy for nsq-NSCLC, 82.0%(105/128) achieves response within the first two tumor assessments (12 weeks) and 18.0%(23/128) achieves response at later (18 to 33 weeks) assessments, and there is a trend toward prolonged PFS in responders with deeper tumor response.
Humans ; Antibodies, Monoclonal, Humanized/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/adverse effects* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/pathology* ; Treatment Outcome

Liquid chromatography-mass spectrometry was employed to analyze the chemical components in Curcuma longa tuberous roots(HSYJ), C. longa tuberous roots processed with vinegar(CHSYJ), and rat serum after the administration. The active components of HSYJ and CHSYJ absorbed in serum were identified based on the secondary spectrum of database and literature. The targets of primary dysmenorrhea was screened out from database. The protein-protein interaction network analysis, gene ontology(GO) functional annotation, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed for the common targets shared by the drug active components in serum and primary dysmenorrhea, and the component-target-pathway network was constructed. AutoDock was used to conduct molecular docking between the core components and targets. A total of 44 chemical components were identified from HSYJ and CHSYJ, including 18 absorbed in serum. On the basis of network pharmacology, we identified 8 core components(including procurcumenol, isobutyl p-hydroxybenzoate, ferulic acid, and zedoarondiol) and 10 core targets \[including interleukin-6(IL-6), estrogen receptor 1(ESR1), and prostaglandin-endoperoxide synthase 2(PTGS2)\]. The core targets were mainly distributed in the heart, liver, uterus, and smooth muscle. The molecular docking results showed that the core components were well bound to the core targets, indicating that HSYJ and CHSYJ may exert therapeutic effect on primary dysmenorrhea via estrogen, ovarian steroidogenesis, tumor necrosis factor(TNF), hypoxia-inducible factor-1(HIF-1), IL-17 and other signaling pathways. This study clarifies the HSYJ and CHSYJ components absorbed in serum, as well as the corresponding mechanism, providing a reference for further elucidating the therapeutic material basis and clinical application of HSYJ and CHSYJ.
Female ; Humans ; Animals ; Rats ; Acetic Acid ; Curcuma ; Dysmenorrhea ; Molecular Docking Simulation ; Tumor Necrosis Factor-alpha ; Cyclooxygenase 2

Objective: To investigate the prognostic value of preoperative inflammatory and nutritional condition detection in the postoperative survival, and establish a prognostic model for predicting the survival of patients with gastric cancer. Methods: The clinicopathological data of 1123 patients with gastric cancer who had undergone radical gastrectomy in Tianjin Medical University Cancer Institute & Hospital from January 2005 to December 2014 were retrospectively analyzed. Patients with history of other malignancy, with history of gastrectomy, who had received preoperative treatment, who died during the initial hospital stay or first postoperative month, and missing clinical and pathological information were excluded. Cox univariate and multivariate analyses were used to identify independent clinicopathological factors associated with the survival of these gastric cancer patients. Cox univariate analysis was used to identify preoperative inflammatory and nutritional indexes related to the survival of patients with gastric cancer after radical gastrectomy. Moreover, the Cox proportional regression model for multivariate survival analysis (forward stepwise regression method based on maximum likelihood estimation) was used. The independent clinicopathological factors that affect survival were incorporated into the following three new prognostic models: (1) an inflammatory model: significant preoperative inflammatory indexes identified through clinical and univariate analysis; (2) a nutritional model: significant preoperative nutritional indexes identified through clinical and univariate analysis; and (3) combined inflammatory/nutritional model: significant preoperative inflammatory and nutritional indexes identified through clinical and univariate analysis. A model that comprised only pT and pN stages in tumor TNM staging was used as a control model. The integrated area under the receiver operating characteristic curve (iAUC) and C-index were used to evaluate the discrimination of the model. Model fitting was evaluated by Akaike information criterion analysis. Calibration curves were used to assess agreement between the predicted probabilities and actual probabilities at 3-year or 5-year overall survival (OS). Results: The study cohort comprised 1 123 patients with gastric cancer. The mean age was 58.9±11.6 years, and 783 were males. According to univariate analysis, age, surgical procedure, extent of lymph node dissection, tumor location, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, and nerve invasion were associated with 5-year OS after radical gastrectomy for gastric cancer (all P<0.050). Multivariate analysis further identified age (HR: 1.18, 95%CI: 1.03-1.36, P=0.019), maximum tumor size (HR: 1.19, 95%CI: 1.03-1.38, P=0.022), number of examined lymph nodes (HR: 0.79, 95%CI: 0.68-0.92, P=0.003), pT stage (HR: 1.40, 95%CI: 1.26-1.55, P<0.001) and pN stage (HR: 1.28, 95%CI: 1.21-1.35, P<0.001) as independent prognostic factors for OS of gastric cancer patients. Additionally, according to univariate survival analysis, the preoperative inflammatory markers of neutrophil count, percentage of neutrophils, neutrophil/lymphocyte ratio, platelet/neutrophil ratio and preoperative nutritional indicators of serum albumin and body mass index were potential prognostic factors for gastric cancer (all P<0.05). On the basis of the above results, three models for prediction of prognosis were constructed. Variables included in the three models are as follows. (1) Inflammatory model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, percentage of neutrophils, and neutrophil-lymphocyte ratio; (2) nutritional model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, and serum albumin; and (3) combined inflammatory/nutritional model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, percentage of neutrophils, neutrophil-lymphocyte ratio, and serum albumin. We found that the predictive accuracy of the combined inflammatory/nutritional model, which incorporates both inflammatory indicators and nutrition indicators (iAUC: 0.676, 95% CI: 0.650-0.719, C-index: 0.698),was superior to that of the inflammation model (iAUC: 0.662, 95% CI: 0.673-0.706;C-index: 0.675), nutritional model (iAUC: 0.666, 95% CI: 0.642-0.698, C-index: 0.672), and TNM staging control model (iAUC: 0.676, 95% CI: 0.650-0.719, C-index: 0.658). Furthermore, the combined inflammatory/nutritional model had better fitting performance (AIC: 10 762) than the inflammatory model (AIC: 10 834), nutritional model (AIC: 10 810), and TNM staging control model (AIC: 10 974). Conclusions: Preoperative percentage of neutrophils, NLR, and BMI have predictive value for the prognosis of gastric cancer patients. The inflammatory / nutritional model can be used to predict the survival and prognosis of gastric cancer patients on an individualized basis.
Male ; Humans ; Middle Aged ; Aged ; Female ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/pathology* ; Neoplasm Staging ; Gastrectomy ; Serum Albumin