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.

Core fucosylation, catalyzed exclusively by fucosyltransferase 8 (FUT8), is an evolutionarily conserved post-translational modification that has emerged as a central regulatory hub linking liver homeostasis, chronic disease progression, and malignant transformation. Liver diseases, particularly hepatocellular carcinoma, remain a leading global health burden characterized by late diagnosis, limited therapeutic options, and poor overall survival. While aberrant glycosylation is now recognized as a hallmark of cancer and inflammatory disorders, existing research on FUT8-mediated core fucosylation in liver diseases remains fragmented: the dynamic functional switch of FUT8 from a homeostatic regulator to a pathological driver across the full disease continuum has not been systematically delineated, and the integrated mechanisms by which core fucosylation modulates oncogenic signaling, metabolic reprogramming, and immune evasion remain poorly understood. This review synthesizes recent advances to establish a unified framework for understanding the dual role of core fucosylation in liver physiology and pathology, and evaluates its translational potential for precision medicine. At the molecular level, FUT8’s unique catalytic specificity makes core fucosylation an irreplaceable modification, as evidenced by the perinatal lethality and severe organ dysfunction in Fut8 knockout mice. In hepatocellular carcinoma, genomic amplification of guanosine 5'-diphosphate-fucose biosynthetic enzymes provides metabolic support for aberrant core fucosylation. FUT8 expression is tightly regulated by a multi-layered network: transcriptional activation via Wnt/β‑catenin and wild-type p53, epigenetic upregulation by lncRNAs, post-transcriptional repression by miR-122-5p and miR-34a, and virus-specific induction by hepatitis B virus/hepatitis C virus. Physiologically, core fucosylation maintains liver homeostasis through four core mechanisms: it acts as a molecular switch for epidermal growth factor receptor/hepatocyte growth factor receptor signaling to enable liver regeneration; directs polarized secretion of hepatocyte-derived glycoproteins into bile ducts; modulates cholesterol metabolism via the hepatocyte nuclear factor 1α-proprotein convertase subtilisin/kexin type 9-low density lipoprotein receptor axis; and regulates aging through insulin‑like growth factor 1 receptor signaling. Pathologically, core fucosylation exhibits context-dependent dual functions: in liver fibrosis, FUT8 upregulation in hepatic stellate cells forms a negative feedback loop that limits excessive fibrogenesis; in hepatocellular carcinoma, however, aberrant FUT8 overexpression drives cell-autonomous malignancy by constitutively activating epidermal growth factor/hepatocyte growth factor receptor, transforming growth factor‑β/Smad, and Wnt/β‑catenin pathways, while simultaneously establishing a multi-layered immune evasion network by stabilizing programmed cell death ligand 1 and cluster of differentiation 47, and impairing natural killer cell homeostasis via interleukin‑2 receptor β glycosylation. Clinically, stage-specific core fucosylation biomarkers enable non-invasive monitoring of liver disease progression: low molecular mass kringle-Fc fusion protein outperforms conventional markers for early fibrosis detection, while alpha-fetoprotein-L3 and novel glycopeptides (α‑2‑macroglobulin N‑linked glycosylation site 1424, lumican core fucosylated peptide) significantly improve early hepatocellular carcinoma diagnosis, especially in alpha-fetoprotein-negative patients. Next-generation detection technologies (chemoenzymatic labeling, site-specific mass spectrometry) overcome the specificity limitations of traditional lectin assays. Therapeutically, four promising strategies are emerging: small-molecule FUT8 inhibitors, afucosylated antibodies with enhanced antibody‑dependent cellular cytotoxicity, Fuc-modified targeted drug delivery systems, and core fucose-specific lectins for NASH treatment. The core challenge for clinical translation lies in FUT8’s inherent “double-edged sword” effect, as systemic inhibition disrupts its essential physiological functions beyond pathological roles. Long-term systemic FUT8 blockade not only impairs post-injury liver regeneration by abrogating epidermal growth factor/hepatocyte growth factor receptor signaling but also disrupts cholesterol homeostasis via the hepatocyte nuclear factor 1α-proprotein convertase subtilisin/kexin type 9-low density lipoprotein receptor axis, leading to dyslipidemia and altered bile secretion. Critically, it compromises immune surveillance by destabilizing interleukin‑2 receptor β on natural killer cells, reducing their cytotoxic activity against malignant and virally infected cells, and impairs IgG Fc-mediated effector functions, increasing susceptibility to infections. This fundamental trade-off between therapeutic efficacy and systemic toxicity necessitates a paradigm shift from non-specific global inhibition to precision modulation of pathological core fucosylation. By addressing these critical challenges, FUT8-mediated core fucosylation has the potential to transform liver disease management from late-stage intervention to early detection and precision therapy, ultimately improving patient outcomes and reducing the global burden of liver diseases.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

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 evaluate the efficacy and safety of a novel intravascular lithotripsy(IVL)balloon—Vesscrack shockwave balloon—for vascular preparation before stent implantation in patients with severe coronary artery calcification(CAC).Methods This was a prospective,single-arm,multicenter study conducted in China from June 2022 to October 2022.Patients with severe CAC were treated with the Vesscrack shockwave balloon for lesion preparation,followed by drug-eluting stent(DES)implantation.Of these,33 patients underwent optical coherence tomography(OCT).The primary endpoint was procedural success,defined as successful stent implantation with residual stenosis≤30％and the absence of in-hospital major adverse events,including cardiac death,target vessel-related myocardial infarction,or target lesion revascularization.Results A total of 170 patients[mean age:(65.9±7.9)years,116 males]were enrolled.After treatment with IVL and DES,the minimum lumen diameter increased significantly compared to baseline[(2.34±0.40)mm vs.(0.95±0.33)mm,P＜0.001],the degree of stenosis was significantly reduced[(13.24±6.60)％vs.(65.18±10.59)％,P＜0.001].Procedural success was achieved in 100％of cases,and device success was 98.8％.The 30-day patient-related cardiovascular clinical composite endpoint(POCE)rate was 0.0,with no target lesion failure,no confirmed or potential thrombotic events were observed.The shockwave energy generator demonstrated excellent stability and ease of use.Among the 33 patients assessed with OCT,after IVL intervention,the maximum calcified area of the lumen[(3.51±1.51)mm2 vs.(2.85±1.80)mm2,P＜0.001],and the minimum lumen area within the target lesion[(3.08±1.04)mm2 vs.(2.02±0.75)mm2,P＜0.001],and after DES intervention,the luminal area of the largest calcified site[(6.59±1.64)mm2 vs.(2.85±1.80)mm2,P＜0.001]and the minimum luminal area within the target lesion[(6.19±1.45)mm2 vs.(2.02±0.75)mm2,P＜0.001]were significantly increased,and the differences were statistically significant.Conclusions The Vesscrack shockwave balloon is effective and safe for vascular preparation in patients with severe CAC prior to stent implantation.It achieves significant calcified plaque modification,high procedural success rates,and minimal complications.

Objective To analyze the correlation between lesion volume,lesion mass,and maximum lesion diameter in the assessment of advanced hepatocarcinoma with lung metastasis,and to evaluate the application value of total volume response and total mass response of lung metastatic lesions in efficacy assessment.Methods A retrospective analysis was conducted on the CT imaging data of 20 patients clinically confirmed with hepatocarcinoma and lung metastases,followed by subsequent follow-up to monitor their survival outcomes.Volume measurement software was used to measure the volume of lesions before and after treatment.We recored lesion diameter,volume measurements and CT values,calculated the mass of the lesions.The correlation between lesion volume,mass and diameter was analyzed,as well as the correlation between the change rates of volume,mass and lesion diameter.Additionally,the total volume and total mass of all lesions were calculated.The correlation between the change rates of total volume/total mass and the change rate of pulmonary lesion diameter under the RECIST 1.1 criteria,as well as the correlation with changes in patients'tumor markers,were analyzed.Furthermore,the overall volume response and overall mass response of lesions were evaluated based on changes in total volume and total mass,and their consistencies with the RECIST 1.1 criteria for efficacy evaluation were analyzed.Finally,univariate Cox regression analysis was performed to explore the association between these variables and patient survival outcomes.Results There was strong correlation between lesion volume,mass and tumor diameter(r=0.771,0.775),between the rate of change in mass and the rate of change in lesion diameter(r=0.846),and between the rates of change in total volume/total mass and the rate of change in pulmonary lesion diameter under the RECIST 1.1 criteria(r=0.800,0.896).The correlation between the rates of change in total volume/total mass and patients'tumor markers was not statistically significant.There was moderate correlation between the rate of change in volume and the rate of change in lesion diameter(r=0.692).The evaluation results of total volume response and total mass response for pulmonary lesions in advanced hepatocarcinoma with lung metastasis were generally consistent with the RECIST 1.1 criteria(Kappa=0.486,0.426).Univariate Cox regression analysis revealed that total lesion volume(P=0.047)and total lesion mass(P=0.049)were independent prognostic factors for survival outcomes.Conclusion Lesion volume,mass,and diameter,as well as their respective change rates,were found to be interrelated.Furthermore,total lesion volume and total lesion mass were identified as independent prognostic factors for survival outcomes.The total volume response and total mass response are promising evaluation methods in evaluating the efficacy of lung metastasis of hepatocarcinoma,which are different from the RECIST 1.1 evaluation criteria.

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion is one of the most commonly used supportive treatments for children with hematological diseases. This guideline provides guidance and recommendations for blood transfusions in children with aplastic anemia, thalassemia, autoimmune hemolytic anemia, glucose-6-phosphate dehydrogenase deficiency, acute leukemia, myelodysplastic syndromes, immune thrombocytopenic purpura, and thrombotic thrombocytopenic purpura. This article presents the evidence and interpretation of the blood transfusion provisions for children with hematological diseases in the "Guideline for pediatric transfusion", aiming to assist in the understanding and implementing the blood transfusion section of this guideline.
Humans ; Child ; Hematologic Diseases/therapy* ; Blood Transfusion/standards* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion for children undergoing hematopoietic stem cell transplantation is highly complex and challenging. This guideline provides recommendations on transfusion thresholds and the selection of blood components for these children. This article presents the evidence and interpretation of the transfusion provisions for children undergoing hematopoietic stem cell transplantation, with the aim of enhancing the understanding and implementation of the "Guideline for pediatric transfusion".
Humans ; Hematopoietic Stem Cell Transplantation ; Child ; Blood Transfusion/standards* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Critically ill children often present with anemia and have a higher demand for transfusions compared to other pediatric patients. This guideline provides guidance and recommendations for blood transfusions in cases of general critical illness, septic shock, acute brain injury, extracorporeal membrane oxygenation, non-life-threatening bleeding, and hemorrhagic shock. This article interprets the background and evidence of the blood transfusion provisions for critically ill and severely bleeding children in the "Guideline for pediatric transfusion", aiming to enhance understanding and implementation of this aspect of the guidelines. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(4): 395-403.
Humans ; Critical Illness ; Blood Transfusion/standards* ; Child ; Hemorrhage/therapy* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices in pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Children undergoing cardiac surgery are at high risk of bleeding, and the causes of perioperative anemia and coagulation disorders in neonates and children are complex and varied, often necessitating the transfusion of allogeneic blood components. This guideline provides direction and recommendations for specific measures in blood management for children undergoing cardiac surgery before, during, and after surgery. This article interprets the background and evidence for the formulation of the blood transfusion provisions for children undergoing cardiac surgery, hoping to facilitate the understanding and implementation of this guideline.
Humans ; Cardiac Surgical Procedures ; Blood Transfusion/standards* ; Child ; Practice Guidelines as Topic