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.

The dried mature peel of Citrus reticulata, a plant in the Rutaceae family and its cultivated varieties, is a commonly used Chinese medicinal material known as Chenpi(Citri Reticulatae Pericarpium). It is rich in nutritional components and medicinal value, with pharmacological effects including relieving cough and eliminating phlegm, strengthening the spleen and drying dampness, protecting the liver and benefiting the stomach, tonifying Qi, and calming the mind. Huanglongbing(HLB), also known as Citrus Huanglongbing, is a destructive disease in citrus production that seriously threatens the development of the citrus industry. HLB causes symptoms such as the inability of Rutaceae plants to produce mature fruit, gradual weakening of the tree, and eventual death, posing a significant threat to the yield and quality of Chenpi. Due to the uneven distribution of the HLB pathogen in infected plants, accurate detection of the pathogen requires the collection of a large number of plant samples. Current sample pretreatment methods, such as traditional extraction methods and commercial extraction kits, are time-consuming and involve multiple steps, which significantly increase the difficulty and workload of HLB diagnosis and have become a bottleneck in HLB detection. In this study, a rapid high-throughput detection method combining alkali lysis and TaqMan qPCR was developed. This method allows the pretreatment of multiple samples within 5 min, and the entire detection process can be completed within 45 min, with a detection limit of 6.67 fg·μL~(-1). The alkali lysis method and commercial kits were used for parallel detection of field-collected citrus samples, and the results showed no significant difference. The sample pretreatment method established in this study is characterized by low cost, simplicity, and high efficiency. Combined with TaqMan qPCR, it can provide technical support for early and on-site diagnosis of HLB. This method is of great significance for disease prevention and control in the citrus industry and is expected to help improve the yield and quality of citrus medicinal materials.
Citrus/microbiology* ; Plant Diseases/microbiology* ; Rhizobiaceae/physiology* ; High-Throughput Screening Assays/methods* ; Liberibacter/physiology*

To enhance the therapeutic efficacy of the baicalin-berberine complex(BA-BBR) in the treatment of ulcerative colitis(UC), BA-BBR nanocrystal microspheres(BA-BBR NC MS) were prepared using the dropping method. The microspheres were characterized in terms of morphology, particle size, differential scanning calorimetry(DSC), and powder X-ray diffraction(XRD). The release profiles of BA and BBR from the microspheres were measured, and the drug release mechanism was investigated. A rat model of UC was induced by 5% dextran sodium sulfate(DSS) and treated continuously for 7 days to evaluate the therapeutic effects of different formulations. The results showed that the prepared BA-BBR MS and BA-BBR NC MS were uniform gel spheres with particle sizes of(1.77±0.16) mm and(1.67±0.08) mm, respectively. After drying, the gels collapsed inward and exhibited a rough surface. During the preparation process, the BA-BBR nanocrystals(BA-BBR NC) were uniformly encapsulated within the microspheres. The release profiles of the microspheres followed a first-order kinetic model, and the 12-hour cumulative release of BA and BBR from BA-BBR NC MS was higher than that from BA-BBR MS. Compared with BA-BBR, BA-BBR NC, and BA-BBR MS, BA-BBR NC MS further alleviated UC symptoms in rats, most significantly reducing the levels of TNF-α, IL-1β, IL-6, and MPO, while increasing the level of IL-4 in colon tissues. These results indicate that BA-BBR NC MS, based on a "nano-in-micro" design, can deliver BA-BBR to the intestine and exert significant therapeutic effects in a UC rat model, suggesting it as a promising new strategy for the treatment of UC.
Animals ; Colitis, Ulcerative/metabolism* ; Rats ; Nanoparticles/chemistry* ; Microspheres ; Male ; Berberine/administration & dosage* ; Flavonoids/administration & dosage* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Particle Size ; Tumor Necrosis Factor-alpha/immunology* ; Drug Liberation ; Drug Compounding

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

OBJECTIVE: To investigate the regulatory effects of two traditional mineral medicines (TMMs), Gypsum Fibrosum (Shigao, GF) and Terra Flava Usta (Zaoxintu, TFU), on gut-beneficial bacteria in mice, and preliminarily explore their mechanisms of action. METHODS: Mice were randomly divided into 3 groups (n=10 per group): the control group (standard diet), the GF group (diet supplemented with 2% GF), and the TFU group (diet supplemented with 2% TFU). After 4-week intervention, 16S rRNA gene sequencing was used to analyze the changes in the gut microbiota (GM). Scanning electron microscopy, in combination with coumarin A tetramethyl rhodamine conjugate and Hoechst stainings, was used to observe the bacteria and biofilm formation. RESULTS: Principal coordinate analysis revealed that GF and TFU significantly altered the GM composition in mice. Further analysis revealed that GF and TFU affected different types of gut bacteria, suggesting that different TMMs may selectively modulate specific bacterial populations. For certain bacteria, such as Faecalibaculum and Ileibacterium, both GF and TFU exhibited growth-promoting effects, implying that they may be sensitive to TMMs and that different TMMs can increase their abundance through their respective mechanisms. Notably, Lactobacillus reuteri, a widely recognized and used probiotic, was significantly enriched in the GF group. Random forest analysis identified Ileibacterium valens as a potential indicator bacterium for TMMs' impact on GM. Further mechanistic studies showed that gut bacteria formed biofilm structures on the TFU surface. CONCLUSIONS This study provides new insights into the interaction between TMMs and GM. As safe and effective natural clays, GF and TFU hold promise as potential candidates for prebiotic development.
Animals ; Gastrointestinal Microbiome/drug effects* ; Bacteria/growth & development* ; Mice ; Biofilms/drug effects* ; Male ; RNA, Ribosomal, 16S/genetics*

OBJECTIVE: Lipid oxidation is involved in the pathogenesis of atherosclerosis and may be contribute to the development of Ischemic stroke (IS). However, the lipid profiles associated with IS have been poorly studied. We conducted a pilot study to identify potential IS-related lipid molecules and pathways using lipidomic profiling. METHODS: Serum lipidomic profiling was performed using LC-MS in 20 patients with IS and 20 age- and sex-matched healthy controls. Univariate and multivariate analyses were simultaneously performed to identify the differential lipids. Multiple testing was controlled for using a false discovery rate (FDR) approach. Enrichment analysis was performed using MetaboAnalyst software. RESULTS: Based on the 294 lipids assayed, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were used to distinguish patients with IS from healthy controls. Fifty-six differential lipids were identified with an FDR-adjusted P less than 0.05 and variable influences in projection (VIP) greater than 1.0. These lipids were significantly enriched in glycerophospholipid metabolism (FDR-adjusted P = 0.009, impact score = 0.216). CONCLUSIONS Serum lipid profiles differed significantly between patients with IS and healthy controls. Thus, glycerophospholipid metabolism may be involved in the development of IS. These results provide initial evidence that lipid molecules and their related metabolites may serve as new biomarkers and potential therapeutic targets for IS.
Humans ; Pilot Projects ; Lipidomics ; Male ; Female ; Biomarkers/blood* ; Middle Aged ; Ischemic Stroke/blood* ; Aged ; China ; Lipids/blood* ; Adult ; Case-Control Studies ; East Asian People

Objective To explore the correlation between fasting blood glucose(FBG)level and fractional flow reserve(FFR)in patients with borderline coronary artery disease,and to clarify its potential influence on FFR measurement.Methods From August 2020 to August 2023,the data of 135 patients with coronary atherosclerotic heart disease who received coronary angiography and FFR evaluation in the Fourth Affiliated Hospital of Harbin Medical University were retrospectively collected.According to the exclusion and inclusion criteria,85 cases of borderline diseased vessels of single coronary artery with stenosis degree of 50％-80％were screened out,and they were divided into FBG≥6.1 mmol/L group(47 cases)and FBG＜6.1 mmol/L group(38 cases).The baseline data,angiographic and functional indexes of the two groups were compared,and the correlation between FBG and FFR was analyzed.Results Compared with the FBG＜6.1 mmol/L group,the FBG≥6.1 mmol/L group had a higher proportion of FFR negative results(72.3％vs.23.7％,P＜0.001),and the FFR measurement values were generally increased[0.84(0.80,0.90)vs.0.75(0.68,0.80),P＜0.001],with statistically significant differences.Pearson correlation analysis was performed on all lesions,and FFR＞0.80(negative result)was positively correlated with FBG≥6.1 mmol/L(r=0.484,P＜0.001).Conclusions Among the patients with borderline coronary artery disease(50％-80％stenosis)included in this study,FBG≥6.1 mmol/L is significantly correlated with FFR＞0.80.For patients with borderline coronary lesions with elevated FBG,the influence of blood glucose factors should be carefully considered in clinical interpretation of FFR results.

Objective To explore the correlation between fasting blood glucose(FBG)level and fractional flow reserve(FFR)in patients with borderline coronary artery disease,and to clarify its potential influence on FFR measurement.Methods From August 2020 to August 2023,the data of 135 patients with coronary atherosclerotic heart disease who received coronary angiography and FFR evaluation in the Fourth Affiliated Hospital of Harbin Medical University were retrospectively collected.According to the exclusion and inclusion criteria,85 cases of borderline diseased vessels of single coronary artery with stenosis degree of 50％-80％were screened out,and they were divided into FBG≥6.1 mmol/L group(47 cases)and FBG＜6.1 mmol/L group(38 cases).The baseline data,angiographic and functional indexes of the two groups were compared,and the correlation between FBG and FFR was analyzed.Results Compared with the FBG＜6.1 mmol/L group,the FBG≥6.1 mmol/L group had a higher proportion of FFR negative results(72.3％vs.23.7％,P＜0.001),and the FFR measurement values were generally increased[0.84(0.80,0.90)vs.0.75(0.68,0.80),P＜0.001],with statistically significant differences.Pearson correlation analysis was performed on all lesions,and FFR＞0.80(negative result)was positively correlated with FBG≥6.1 mmol/L(r=0.484,P＜0.001).Conclusions Among the patients with borderline coronary artery disease(50％-80％stenosis)included in this study,FBG≥6.1 mmol/L is significantly correlated with FFR＞0.80.For patients with borderline coronary lesions with elevated FBG,the influence of blood glucose factors should be carefully considered in clinical interpretation of FFR results.