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.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

OBJECTIVE: This cross-sectional study assessed the methodological quality of systematic reviews (SRs) of Chinese herbal medicine (CHM) published in Chinese between Jan 2021 and Sep 2022. METHODS: Chinese language CHM SRs were identified through literature searches across 3 international and 4 Chinese databases. Methodological quality was appraised using A MeaSurement Tool to Assess systematic Reviews 2. Logistic regressions were used to explore associations between bibliographical characteristics and quality. RESULTS: Analyses of methodological quality found that among the 213 sampled SRs, 69.5% were of critically low quality, 30.5% were of low quality, and none achieved high or moderate quality. Common shortcomings included the failure to identify the studies excluded from the analysis, failure to disclose funding sources, and limited evaluation of the potential impact of bias on conclusions. Logistic regressions revealed that SRs led by corresponding authors affiliated with universities or academic institutions tended to be of lower quality than SRs led by authors affiliated with hospitals or clinical facilities. CONCLUSION Recent Chinese language CHM SRs exhibited limited methodological quality, making them unlikely to support the development of clinical practice guidelines. Urgent initiatives are needed to enhance training for researchers, peer-reviewers and editors involved in the preparation and publication of SRs. Adoption of Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines in Chinese language journals is crucial to improve the relevance of SRs for Chinese medicine development. Addressing deficiencies in methodology and reporting is essential for promoting evidence-based practices and informed clinical decisions in Chinese medicine. Please cite this article as: Jiang Y, Zhong CC, Wang BH, Xu SS, Ho FF, Kwong MH, Ho L, Zhou JHS, Lam KC, Liu JP, Zhang BT, Chung VCH. Methodological quality of systematic reviews on orally administered Chinese herbal medicine published in Chinese between 2021 and 2022: A cross-sectional study. J Integr Med. 2025; 23(5):492-501.
Cross-Sectional Studies ; Drugs, Chinese Herbal/administration & dosage* ; Systematic Reviews as Topic/standards* ; Humans ; China ; Administration, Oral ; Medicine, Chinese Traditional

Lingguizhugan Decoction (LGZG) demonstrates significant efficacy in treating various cardiovascular diseases clinically, yet its precise mechanism of action remains elusive. This study aimed to elucidate the potential mechanisms and effects of LGZG on isoproterenol (ISO) continuous stimulation-induced chronic heart failure (CHF) in mice, providing direct experimental evidence for further clinical applications. In vivo, continuous ISO infusion was administered to mice, and ventricular myocytes were utilized to explore LGZG?s potential mechanism of action on the ?1-adrenergic receptor (?1-AR)/Gs/G protein-coupled receptor kinases (GRKs)/?-arrestin signaling deflection system in the heart. The findings reveal that LGZG significantly reduced the messenger ribonucleic acid (mRNA) expression of hypertrophy-related biomarkers [atrial natriuretic peptide (ANP) and B-type natriuretic peptide (BNP)] and improved cardiac remodeling and left ventricular diastolic function in mice with ISO-induced CHF. Furthermore, LGZG inhibited the overactivation of Gs/cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) signaling and downregulated the downstream transcriptional activity of cAMP-response element binding protein (CREB) and the expression of the coactivator CBP/P300. Notably, LGZG downregulated the expression of ?-arrestin1 and GRK 2/3/5 while upregulating the expression of ?1-AR and ?-arrestin2. These results suggest that LGZG inhibits Gs/cAMP/PKA signaling and ?-arrestin/GRK-mediated desensitization and internalization of ?1-AR, potentially exerting cardioprotective effects through the synergistic regulation of the ?1-AR/Gs/GRKs/?-arrestin signaling deflection system via multiple pathways.
Animals ; Heart Failure/genetics* ; Signal Transduction/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Male ; G-Protein-Coupled Receptor Kinases/genetics* ; Mice, Inbred C57BL ; Humans ; Isoproterenol ; Arrestins/genetics* ; Chronic Disease

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

OBJECTIVE: To assess the value of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score combined with PSA density (PSAD) in the diagnosis of clinically significant prostate cancer (CSPCa) in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy. METHODS: This retrospective study included 327 male patients with total PSA (tPSA) levels of 4-10 μg/L undergoing MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy in our hospital between January 2021 and December 2023. According to the pathological results, we divided the patients into a CSPCa (n = 44) and a non-CSPCa group (n = 283), collected their clinical and imaging data, and subjected them to statistical analysis. RESULTS: The age, tPSA level, PSAD and PI-RADS score were significantly higher, while the free PSA (fPSA) level, f/tPSA ratio and prostate volume remarkably lower in the CSPCa than in the non-CSPCa group (P<0.05). The areas under the curve (AUCs) of PSAD, PI-RADS score and their combination were 0.772, 0.730 and 0.801, with sensitivities of 63.63%, 70.45% and 72.73%, and specificities of 84.10%, 75.62% and 83.75%, respectively (P<0.01). With PSAD 0.2 μg/(ml·cm3) as the best cut-off value and based on the PI-RADS scores, the patients were divided into two groups for analysis. In the patients with PI-RADS scores 2 and 5, the AUCs were 0.534 and 0.643, with sensitivities of 16.67% and 63.64%, and specificities of 85.14% and 64.29%, with no statistically significant differences (P= 0.784, P= 0.228), and in those with PI-RADS scores 3 and 4, the AUCs were 0.794 and 0.843, with sensitivities of 57.14% and 80.00%, and specificities of 87.14% and 81.82%, with statistically significant differences (P= 0.009, P<0.001). CONCLUSION PI-RADS v2.1 score combined with PSAD can effectively improve the diagnostic efficiency of CSPCa in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy and serve as a guide for selection of prostate biopsy.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Retrospective Studies ; Prostate-Specific Antigen ; Magnetic Resonance Imaging ; Image-Guided Biopsy ; Prostate/pathology* ; Aged ; Middle Aged

OBJECTIVE: To evaluate the efficacy and safety of a hospital-made resuscitation pack, a Chinese medicinal herbal compound formula designed to enhance recovery in post-bronchoscopy patients. METHODS: In this randomized, single-blind, placebo-controlled clinical trial, eligible patients were randomly assigned 1:1 to either the treatment or control groups. The patients in the treatment group applied the resuscitation pack, which contained aromatic compounded Chinese herbs. The patients in the control group applied a hospital-made, single herb placebo pack. Packs were placed on the Tiantu (CV 22) acupuncture point for 4 h as soon as the bronchoscopy finished. Efficacy indicators, such as recovery time, patients' symptoms including nausea and dizziness, and adverse events (AEs) were observed and compared. The outcome indices were evaluated at baseline, 1 and 24 h after the bronchoscopy. Subgroup analysis was further performed by patients' age and depth of sedation. RESULTS: When applying generalized estimating equations (GEE) to evaluate the intensity of post-bronchoscopy nausea and vomiting, the intensity was lower in the treatment group (163 cases) compared with the control group (162 cases; 95% CI: 0.004, 0.099, P=0.03]. Also, significantly lower intensity of nausea was observed in the 60-70 years of age subgroup (95% CI: 0.029, 0.169, P=0.006) and deep sedation subgroup (95% CI: 0.002, 0.124; P=0.04). There was no significant difference in dizziness between two groups by GEE (95% CI: -0.134, 0.297; P=0.459). In addition, no serious AEs were observed in either group. CONCLUSIONS Our study found that the resuscitation pack markedly improved patients' symptoms by reducing nausea and vomiting after bronchoscopy without AEs, compared with placebo in the perioperative period. (Trial registration No. ChiCTR2000038299).
Humans ; Male ; Middle Aged ; Female ; Bronchoscopy/adverse effects* ; Single-Blind Method ; Aged ; Drugs, Chinese Herbal/adverse effects* ; Treatment Outcome ; Resuscitation ; Adult ; Medicine, Chinese Traditional

AIM To study the chemical constituents from ethyl acetate fraction of Balanophora harlandii Hook.f.and their tyrosinase inhibitory activity.METHODS Separation and purification were performed using silica gel,MCI,ODS,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The monophenolase inhibitory activity was determined by the tyrosinase-catalyzed oxidation of L-tyrosine.RESULTS Twenty-four compounds were isolated and identified as sesamin(1),methyl caffeate(2),quercetin(3),5,7-dihydroxychromanone(4),methyl 3,4-dihydroxybenzoate(5),esculetin(6),kaempferol(7),naringenin(8),pyrogallic acid(9),pinosylvin(10),methyl propionate(11),caffeic acid(12),saccharinol(13),ferulic acid(14),trans-p-hydroxycinnamic acid(15),cinnamic acid(16),vanillic acid(17),vanillin(18),4-hydroxyacetophenone(19),4-hydroxybenzaldehyde(20),apigenin(21),(-)-isolariciresinol(22),(-)-secoisolariciresinol(23)and meso-2,3-di(3′,4′-methylenedioxybenzyl)butane-1,4-diol(24).The IC50 values of compounds 3,5,7,8,19,and 20 ranged from(0.246 5±0.028 3)to(1.278 2±0.021 3)mmol/L.CONCLUSION Compounds 1-9、11、15、17-21、24 are isolated from this plant for the first time,and 1,6,9,17-19,24 are first isolated from genus Balanophora.Compounds 3、5、7、8、19 and 20 have tyrosinase inhibitory activity.