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.

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.

In the context of China's aging population, the issue of urinary incontinence among the elderly is becoming increasingly severe.Urinary incontinence not only significantly impacts patients' quality of life, but also imposes a substantial economic burden and psychological stress.This article explores the challenges and prospects of the early intervention of elderly urinary incontinence in China, including improving early diagnosis rates, enhancing patients' self-management abilities, and early screening and prevention for high-risk groups.With the advancement of technology and medical innovations, digital self-management tools offer new possibilities for managing urinary incontinence, helping patients to better control their condition, especially when medical resources are limited.Furthermore, this article calls for greater attention from all sectors of the society to address elderly urinary incontinence and promote the implementation of more systematic research and management strategies to improve the quality of life for China's elderly population.

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*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Endometriosis(EMs)is a common estrogen-depend-ent clinical disease with the pathological characteristics of malig-nant tumors,which has great impact on women's physical and mental health.In recent years,experimental exploration has re-vealed that ectopic foci are in a hypoxic environment outside the uterine cavity,and mitochondria,as the"functional factories"of the cells,play an important role in the process of planting and in-vasion,and the mitochondrial quality control system,which in-cludes mitochondrial oxidative stress,kinetics,autophagy,bio-genesis and calcium homeostasis,is a key mechanism for the e-quilibrium of the mitochondrial function.The mitochondrial quality control system,including mitochondrial oxidative stress kinetics,autophagy,biogenesis and calcium homeostasis,is a key mechanism for mitochondrial functional balance.Therefore,to clarify the role of the mitochondrial quality control system in the development of EMs with the help of rational and rigorous experi-mental and clinical studies can not only help to clarify the patho-genesis of the disease,but also explore the key targets in the prevention and treatment of the disease.Therefore,this article summarizes the research progress of mitochondrial quality control system in endometriosis,with a view to providing reference and theoretical basis for the etiology,pathogenesis and prevention strategies of EMs.

Endometriosis(EMs)is a common estrogen-depend-ent clinical disease with the pathological characteristics of malig-nant tumors,which has great impact on women's physical and mental health.In recent years,experimental exploration has re-vealed that ectopic foci are in a hypoxic environment outside the uterine cavity,and mitochondria,as the"functional factories"of the cells,play an important role in the process of planting and in-vasion,and the mitochondrial quality control system,which in-cludes mitochondrial oxidative stress,kinetics,autophagy,bio-genesis and calcium homeostasis,is a key mechanism for the e-quilibrium of the mitochondrial function.The mitochondrial quality control system,including mitochondrial oxidative stress kinetics,autophagy,biogenesis and calcium homeostasis,is a key mechanism for mitochondrial functional balance.Therefore,to clarify the role of the mitochondrial quality control system in the development of EMs with the help of rational and rigorous experi-mental and clinical studies can not only help to clarify the patho-genesis of the disease,but also explore the key targets in the prevention and treatment of the disease.Therefore,this article summarizes the research progress of mitochondrial quality control system in endometriosis,with a view to providing reference and theoretical basis for the etiology,pathogenesis and prevention strategies of EMs.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

This study investigated the infection status,drug resistance,and molecular characteristics of Shiga toxin-producing Escherichia coli(STEC)in domestic goats in Chengkou county,Chongqing.In August 2023,283 fecal samples were collected from households in Chengkou county.After enrichment with EC broth and inoculation onto selective media,samples that tested positive for stx1/stx2 were selected for further isolation.The positive strains were investigated with antimicrobial susceptibility testing and whole genome sequencing.According to the whole genomic sequences,the stx subtypes,serotypes,multi-locus sequence types,virulence genes,drug resistance genes,and phylogenetic relationships of the STEC strains were analyzed.Forty-six strains of STEC were isolated from 283 goat fecal samples,thus resulting in a detection rate of 16.25%.The 46 STEC strains were categorized into 12 O∶H serotypes,among which O76∶H19 and O8∶H7 predominated,each represented by 9 strains.Five STEC strains were identified as serotype O157∶H7.The 46 STEC strains were categorized into 11 sequence types(STs),among which ST675 and ST196 predominated,each represented by nine strains,accounting for a 19.57%proportion.The strains were categorized into 7 stx subtypes,among which stx1c(26/46,56.52%),followed by stx2k(9/46,19.57%)predominated.All nine Stx2k-STEC strains were identified as serotype O8∶H7 and sequence type ST196.In antimicrobial susceptibility testing,2 STEC strains were resistant to ampicillin,one strain was resistant to ampicillin/sulbactam,one strain was resistant to cefazolin,and one strain was resistant to cefoxitin.Nine Stx2k-STEC strains were found to carry the beta-lactam resistance gene blaEC-18.Antimicrobial sensitivity tests revealed that the nine Stx2k-STEC strains were sensitive to all 15 tested antibiotics.Moreover,phylogenetic analysis indicated that the 9 Stx2k-STEC strains were remarkably similar but showed high genetic diversity with respect to that of the Stx2k-STEC strains isolated from other regions in China.Goatsare an important animal reservoir for STEC in theChengkou district of Chongqing,and novel sequence type Stx2k-STEC strains distinct from those found in other regions of China were identified in this region.

This study investigated the infection status,drug resistance,and molecular characteristics of Shiga toxin-producing Escherichia coli(STEC)in domestic goats in Chengkou county,Chongqing.In August 2023,283 fecal samples were collected from households in Chengkou county.After enrichment with EC broth and inoculation onto selective media,samples that tested positive for stx1/stx2 were selected for further isolation.The positive strains were investigated with antimicrobial susceptibility testing and whole genome sequencing.According to the whole genomic sequences,the stx subtypes,serotypes,multi-locus sequence types,virulence genes,drug resistance genes,and phylogenetic relationships of the STEC strains were analyzed.Forty-six strains of STEC were isolated from 283 goat fecal samples,thus resulting in a detection rate of 16.25%.The 46 STEC strains were categorized into 12 O∶H serotypes,among which O76∶H19 and O8∶H7 predominated,each represented by 9 strains.Five STEC strains were identified as serotype O157∶H7.The 46 STEC strains were categorized into 11 sequence types(STs),among which ST675 and ST196 predominated,each represented by nine strains,accounting for a 19.57%proportion.The strains were categorized into 7 stx subtypes,among which stx1c(26/46,56.52%),followed by stx2k(9/46,19.57%)predominated.All nine Stx2k-STEC strains were identified as serotype O8∶H7 and sequence type ST196.In antimicrobial susceptibility testing,2 STEC strains were resistant to ampicillin,one strain was resistant to ampicillin/sulbactam,one strain was resistant to cefazolin,and one strain was resistant to cefoxitin.Nine Stx2k-STEC strains were found to carry the beta-lactam resistance gene blaEC-18.Antimicrobial sensitivity tests revealed that the nine Stx2k-STEC strains were sensitive to all 15 tested antibiotics.Moreover,phylogenetic analysis indicated that the 9 Stx2k-STEC strains were remarkably similar but showed high genetic diversity with respect to that of the Stx2k-STEC strains isolated from other regions in China.Goatsare an important animal reservoir for STEC in theChengkou district of Chongqing,and novel sequence type Stx2k-STEC strains distinct from those found in other regions of China were identified in this region.