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.

Objective:To investigate the perioperative safety, short-term and long-term efficacy, and surgical strategy of laparoscopic partial gastrectomy for gastrointestinal stromal tumors at the esophagogastric junction.Methods:Seventy-eight patients with mesenchymal tumors in the esophagogastric junction were retrospectively enrolled from September 2018 to August 2023 in which the upper edge of the tumor is less than 2 cm from the Z-line or has invaded the Z-line <1/2 circumference. There were 31 males (39.7%) and 47 females (60.3%), with an average age of (57.2±11.8) years and an average body mass index of (24.5±3.5) kg/m 2. All cases were divided into the wedge resection (WR) group ( n=51) and the resection by opening all of the layers of the stomach wall (RASW) group ( n=27) according to the surgical methods. Surgical outcomes, complications, recover and postoperative gastroesophageal reflux of both groups were compared. The measurement data with a normal distribution were represented by mean±standard deviation ( ± s), and values were compared using the independent sample t-test. The measurement data with a skewed distribution were represented by median (interquartile range) [ M( Q1, Q3)], and values were compared using the Mann-Whitney U test. Count data were expressed as examples (percentages) [ n(%)], and the χ2 test was used to compare countable data. A non-parametric test was used to compare the grade data. Results:The WR group had shorter operation time [(97.1±32.6) min vs (149.9±54.9) min, t=-5.33, P<0.001], less intraoperative blood loss [15(10, 20) mL vs 20(10, 50) mL, z=-2.47, P=0.014], shorter postoperative exhaust time [2(1, 3) d vs 3(2, 3) d, z=-2.49, P=0.013], shorter postoperative oral intake time [2(2, 3) d vs 4(2, 5) d, t=-3.70, P<0.001], shorter postoperative semi-liquid diet time[5(4, 6) d vs 7(5, 8) d, z=-3.57, P<0.001], and shorter postoperative hospital stay [5(4, 6) d vs 7(6, 8) d, z=-4.16, P<0.001] than the RASW group, with statistically significant differences. There was no significant difference in short-term (≤30 days) complications between the two groups (2.0% vs 3.7%, z=-0.46, P=0.648). No cases of cardia stenosis occurred in either group. In the WR group, 3 patients developed gastroesophageal reflux at 6 months postoperatively, with 2 patients relieved after taking acid-suppressing drugs and 1 patient not completely relieved. In the RASW group, 1 patient developed gastroesophageal reflux at 6 months postoperatively and was not completely relieved after taking acid-suppressing drugs. No other patients had gastroesophageal reflux. No other patients have gastroesophageal reflux. Conclusions:WR and RASW are safe and feasible for mesenchymal tumors at the esophagogastric junction in which the upper edge of the tumor is less than 2 cm from the Z-line or has invaded the Z-line <1/2 circumference, and has achieved an excellent short-term effect. The choice of surgical approach can be determined based on varions factors such as the location of the tumor, the relationship of the position between the tumor and the cardia, and whether the tumor is exophytic growth.

Traditional mass measurement methods are not applicable in microgravity environments,and the main challenge for in-orbit body mass measurement technology based on inertial principles is to address the random errors brought about by the weightless environment.These include additional torques due to shifts in the center of mass,nonlinear accelerations due to non-rigid human bodies,mechanical energy consumption due to organ vibrations,and random vibrations of the measurement device itself.To address the above difficulties,the project proposes a technical scheme based on the principle of linear acceleration,designs and constructs a ground-specific air-floating experimental and simulation platform,studies key data such as motion trajectory,acceleration change,and vibration frequency amplitude during the mass measurement process,and simulates the changes in the center of mass and random vibrations of the human body in a weightless environment.The project has designed an adjustable posture bracket to adapt to changes in the center of mass,enhance body restraint,and greatly reduce shaking;it has also developed an integrated four-bar linkage motion guidance mechanism,high-precision integrated photoelectric distance measurement,and modular motion constant force measurement device to ensure the accurate measurement of acceleration and constant force data.The product has undergone simulation calculations,ground human applicability tests,and in-orbit applicability verification in the space station.Ground test results show that the device achieves a body mass measurement accuracy better than 0.5%,and the dispersion is better than 0.38%;after flight mission verification and evaluation,the in-orbit body mass measurement dispersion is less than 0.4%,which is superior to the SLAMMD,a mass measurement device of the same principle on the International Space Station,and is at the forefront internationally,achieving accurate body mass measurement.

Objective Electrocardiogram(ECG)signal quality degrades when the level of activity is high and motion artifacts are severe.Poor quality signals may result in false alarms,poor patient monitoring,imprecise measurement,and misleading diagnosis.The quantitative assessment of ECG signal quality forms the basis of automatic ECG noise reduction and heart disease diagnosis.Methods The ECG signal quality index(SQI)was obtained by statistically analyzing the heartbeat similarity and the slope character,respectively,namely rSQI and kSQI.Results Using MIT-BIH Noise Stress Test Database to test,both rSQI and kSQI decreased when the Signal Noise Ratio(SNR)decreased,which revealed the ECG signal quality.Based on the quasiperiodic property,the waveform similarity,as a beat-to-beat index,is obtained by cross correlation between two ECG cycles with high precision but heavy computation.Slope-based method dispenses with QRS detection and is very simple and real-time,but its sensitivity is lower than similarity-based method and it only get statistical data.Conclusion Both morphology similarity and slope character algorithms could provide objective estimation of ECG quality.Slope-based method is an attractive measure due to its simplicity and mathematical convenience,while similarity-based method is more accurate and robust for ECG quality assessment.

As a comprehensive high technology,robotics has gained extensive attention from numerous researchers.Intelligent soft robots,representing a new direction in robotics research,are shining brightly in fields such as fragile objects manipulating,medical assistance,and environment exploration due to their unique advantages.In the field of specialized medicine,intelligent soft robots can adapt to the complex and extreme space working environment due to their small stiffness,strong variability and high flexibility,and have broad application prospects in specialized medicine like aerospace,navigation and diving.In this paper,the research status of intelligent soft robots is reviewed from four aspects:materials,structure,actuation modalities,modeling and simulation.Furthermore,the application of intelligent soft robots in the field of specialized medicine is summarized and prospected in this paper.

Objective To report the diagnosis and treatment of a case of acute pulmonary embolism caused by thrombus detachment within a popliteal venous aneurysm and conduct a literature review,aiming to enhance the understanding of the disease.Methods The case data of a patient with pulmonary embolism caused by thrombus detachment within a popliteal venous aneurysm who was admitted to the Second Hospital of Lanzhou University were retrospectively analyzed.The relevant literature published from July 2014 to July 2023 in the CNKI and PubMed databases was retrieved,and the diagnosis and treatment methods of the disease were summarized.Results The patient in this case was a 61-year-old male,who was admitted was admitted to the hospital due to"intermittent chest tightness and shortness of breath for 5 days".Color Doppler ultrasound examination and pulmonary artery CT angiography(CTA)suggested popliteal venous aneurysm combined with intramural thrombus and pulmonary embolism.Therefore,the pulmonary embolism and popliteal venous aneurysm were treated surgically in stages.The patient recovered well after the operation and there were no symptoms of chest tightness or shortness of breath after discharge.A total of 11 literatures were retrieved,involving 11 patients,all of whom underwent surgical treatment;Among them,4 patients were treated with inferior vena cava filter placement,and 2 patients underwent popliteal venous aneurysm surgery after filter placement.Through literature review,it can be known that the etiology of popliteal venous aneurysm remains unclear,and there is no unified standard for diagnosis and treatment.Up to now,surgery is still the preferred option for treatment.Conclusions Patients with popliteal venous aneurysms may be asymptomatic but can lead to deep vein thrombosis of the lower limbs and subsequent pulmonary embolism.Surgical intervention is an effective treatment option.For patients with combined pulmonary embolism,especially those with recurrent pulmonary embolism,it is recommended to perform surgical treatment following placement of an inferior vena cava filter.

Objective To observe the therapeutic effects of different doses of methylprednisolone(MP)on smoke inhalation-induced acute lung injury(SI-ALI)in rats,and to explore the changes in the expression of aquaporins(AQPs)and the underlying mechanisms for alleviating lung injury.Methods A total of 86 healthy adult male Sprague-Dawley(SD)rats were randomly divided into five groups:control group(n=6),smoke inhalation injury(SI)group(n=20),low-dose MP group(LMP,SI+0.4 mg/kg MP,n=20),medium-dose MP group(MMP,SI+4 mg/kg MP,n=20),and high-dose MP group(HMP,SI+40 mg/kg MP,n=20).A model of smoke inhalation-induced lung injury was established.The survival status of the rats in each group was monitored.Lung tissues were collected 24 hours after injury to determine the wet-to-dry(W/D)ratio of the lung tissues,arterial oxygen partial pressure(PaO2),and the expression levels of inflammatory cytokines TNF-α and IL-6.The degree of lung injury was evaluated using HE staining,and the mRNA and protein expression levels of AQP1 and AQP5 in the lung tissues were detected.Results Compared with control group,the survival rate of the rats in SI group was significantly decreased(P<0.05);compared with SI group,the survival rates of the rats in MMP and HMP groups were significantly increased(P<0.05).Compared with control group,the PaO2 of the Rats in SI group was significantly decreased(P<0.05),and the wet-to-dry(W/D)ratio and lung injury scores were significantly increased(P<0.05).Compared with SI group,the PaO2 of the rats in LMP,MMP,and HMP groups(P<0.05)was significantly increased(P<0.05),and the lung W/D ratio and injury scores in MMP and HMP groups were significantly decreased(P<0.05).ELISA results showed that compared with control group,the serum concentrations of TNF-α and IL-6 in SI group were significantly increased(P<0.05);compared with SI group,the concentrations of TNF-α and IL-6 in MMP and HMP groups were significantly decreased(P<0.05).HE staining revealed that the alveolar structure of the rats in SI group was severely damaged;compared with SI group,the damage to the alveolar structure in MMP and HMP groups was alleviated.Real-time PCR and Western blotting analysis results showed that compared with control group,the mRNA and protein expression levels of AQP1 and AQP5 in lung tissues in SI group were significantly decreased(P<0.05);however,compared with SI group,these levels in LMP,MMP,and HMP groups were significantly increased(P<0.05).Conclusions Smoke inhalation can induce acute lung injury in rats and down-regulate the expression levels of AQP1 and AQP5 in the lung tissues.Methylprednisolone can alleviate pulmonary edema and tissue damage in rats caused by smoke inhalation,and induce the up-regulation of the expression of AQP1 and AQP5.

INTRODUCTION: Trastuzumab deruxtecan (T-DXd) has revolutionised treatment for metastatic breast cancer (MBC). While effective, its high cost and toxicities, such as fatigue and nausea, pose challenges. METHOD: Medical records from the Joint Breast Cancer Registry in Singapore were used to study MBC patients treated with T-DXd (February 2021-June 2024). This study was conducted to address whether reducing dose intensity and density may have an adverse effect on treatment outcomes. RESULTS: Eighty-seven MBC patients were treated with T-DXd, with a median age of 59 years. At the time of data cutoff, 32.1% of patients were still receiving T-DXd. Over half (54%) of the patients received treatment with an initial relative dose intensity (RDI) of <;85%. Overall median real-world progression-free survival (rwPFS) was 8.1 months. rwPFS was similar between RDI groups (<85%: 8.7 months, <85%: 8.1 months, P=0.62). However, human epidermal growth receptor 2 (HER2)-positive patients showed significantly better rwPFS outcomes compared to HER2-low patients (8.8 versus 2.5 months, P<0.001). Only 16% with central nervous system (CNS) involvement had CNS progressive disease on treatment. No significant progression-free survival (PFS) differences were found between patients with or without CNS disease, regardless of RDI groups. Five patients (5.7%) developed interstitial lung disease (ILD), with 3 (3.4%) having grade 3 events. Two required high-dose steroids and none were rechallenged after ILD. There were no fatalities. CONCLUSION Our study demonstrated that reduced dose intensity and density had no significant impact on rwPFS or treatment-related toxicities. Furthermore, only 5.7% of patients developed ILD. T-Dxd provided good control of CNS disease, with 82% of patients achieving CNS disease control.
Humans ; Female ; Breast Neoplasms/mortality* ; Middle Aged ; Trastuzumab/adverse effects* ; Aged ; Adult ; Singapore/epidemiology* ; Antineoplastic Agents, Immunological/adverse effects* ; Camptothecin/adverse effects* ; Immunoconjugates/adverse effects* ; Retrospective Studies ; Progression-Free Survival ; Receptor, ErbB-2/metabolism* ; Neoplasm Metastasis ; Dose-Response Relationship, Drug ; Treatment Outcome ; Registries