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.

Objective:To explore the application effect of early enteral nutrition combined with optimized blood glucose management in patients with stress hyperglycemia after cardiac surgery.Methods:A study was conducted to construct an early enteral nutrition and blood glucose optimization management plan for patients with stress hyperglycemia after cardiac surgery.A prospective analysis was conducted from May 2022 to May 2023 in the Cardiothoracic Surgery Intensive Care Unit(CICU)of a tertiary hospital in Shanghai.200 patients with stress hyperglycemia after cardiac surgery were divided into control group(n=100)and observation group(n=100)by random number table method.The control group received routine enteral nutrition and blood glucose management plan,while the observation group received early enteral nutrition combined with blood glucose optimization management plan.Nutrition related outcome indicators,blood glucose management quality indicators,and patient prognosis indicators were compared between two groups of patients.Results:After implementing the early enteral nutrition combined with optimized blood glucose management plan,the nutritional indicators(serum prealbumin,hemoglobin,and 7-day calorie compliance rate)of the observation group were higher than those of the control group,and the differences were statistically significant(P<0.05);The maximum blood glucose fluctuation amplitude,insulin use time,and incidence of hypoglycemia in the observation group were significantly lower than those in the control group(P<0.05),and the time within the glucose target range was significantly higher than that in the control group,with statistical significance(P<0.05);The mechanical ventilation time,ICU stay time,and total hospital stay in the observation group were significantly lower than those in the control group,and the differences were statistically significant(P<0.05).Conclusions:Early enteral nutrition combined with optimized blood glucose management can effectively improve the nutritional status of patients with stress hyperglycemia after cardiac surgery,reduce blood glucose fluctuations,improve blood glucose management quality,and promote patient outcomes and prognosis.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

As a critical component of global agriculture,the dairy industry is essential for the food security and economic development.In China,the dairy sector in plateau regions plays an important role in addressing the nutritional needs of residents,boosting farmers' incomes,and fostering re-gional economic growth.However,the harsh high-altitude conditions,such as low oxygen,low at-mospheric pressure,and severe climate,pose significant challenges to the health and survival of dairy cows.This article summarizes the changes in physiological characteristics,metabolic perform-ance,production performance,and health status of dairy under high altitude areas,providing in-sights for the identification of adaptive traits in dairy to plateau.Also,the genetic and epigenetic mechanisms behind these phenotypic adaptations are discussed,and future directions and strategies for enhancing adaptability of dairy of dairy n plateau regions are outlined,thereby guiding re-searchers in adaptation evolution and breeding of dairy cattle.

Objective:To summarize the clinical characteristics of SAPHO syndrome in elderly patients with organizing pneumonia.Methods:We reported a case of SAPHO syndrome in an elderly patient with organizing pneumonia.Relevant reports on SAPHO syndrome with organizing pneumonia at home and abroad were retrieved, and the literature was summarized an analyzed.Results:The patient was a 63-year-od female who was admitted to the hospital due to "intermittent fever and cough for more than two months". Before admission, she was previously diagnosed with pneumonia in another hospital with poor response to anti-infective treatment.Chest CT showed multiple bilateral patchy consolidations in both lungs, with migratory changes and reversed halo signs.Her medical history included bone and joint pain(e.g., sternoclavicular joints)and palmoplantar pustulosis.Lung biopsy pathology confirmed organizing pneumonia. 99mTc-MDP bone scintigraphy revealed abnormal bone salt metabolism in multiple bone and joint areas.The final diagnosis was SAPHO syndrome with organizing pneumonia.Both symptoms and imaging significantly improved after prednisone treatment.Two related cases were retrieved from the literature.One was a 57-year-old female reported in the UK, who had been diagnosed with SAPHO syndrome before and was found to have lung consolidations due to respiratory symptoms.Lung biopsy confirmed organizing pneumonia, and she improved after glucocorticoid treatment.The other was a 59-year-old Chinese female who visited hospital due to pain in the lumbosacral part and left lower limb.After being diagnosed with SAPHO syndrome, a chest CT scan was performed and lung consolidations were found.The pathology confirmed organizing pneumonia.The patient improved after treatment with Tripterygium wilfordii. Conclusion:SAPHO syndrome complicated with organizing pneumonia is rare, with diverse clinical manifestations, and responds well to glucocorticoid therapy.

Objective:To explore the association between oral health status, the lower respiratory tract microbiome, and the frequent acute exacerbation phenotype in chronic obstructive pulmonary disease (COPD).Methods:This cross-sectional study enrolled 39 patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) hospitalized in the Department of Respiratory Medicine, Henan Provincial People′s Hospital between March 2021 and December 2022. Based on the number of hospitalization episodes for acute exacerbation in the past year, patients were divided into a frequent exacerbator group (≥2 times, n=28) and a non-frequent exacerbator group (<2 times, n=11). Bronchoalveolar lavage fluid (BALF) samples were collected from all subjects for metagenomic next-generation sequencing (mNGS). Oral health indicators and clinical data were also collected. Statistical analyses were performed using Spearman correlation analysis and multivariable Firth logistic regression analysis. Results:The frequent exacerbation group showed a significantly higher percentage of individuals with≥8 tooth loss compared to the non-frequent exacerbation group (96.4% vs 18.2%, P<0.001), a significantly younger age at first tooth loss in adulthood (53.96±7.30 years vs 62.10±5.80 years, P=0.003), and a significantly higher proportion of individuals who hardly brushed their teeth (50.00% vs 9.09%, P=0.038). The alpha-diversity indices of the lower respiratory tract microbiota were significantly lower in the frequent exacerbation group than in the non-frequent exacerbation group (all P<0.01). The relative abundances of Bacillota, Bacteroidota, Fusobacteriota, Streptococcus, Prevotella, Veillonella, Neisseria, Rothia, Prevotellamelaninogenica, Prevotellajejuni, Rothia mucilaginosa, Veillonella parvula, and Neisseria subflava were lower in the frequent exacerbation group (all P<0.05). In patients with AECOPD, the exacerbation frequency and the presence of ≥8 tooth loss were both negatively correlated with the Shannon index ( r=-0.854, P<0.001; r=-0.642, P<0.001, respectively). Further analysis revealed that Bacillota ( r=-0.862, P<0.001) and Streptococcus ( r=-0.814, P<0.001) were significantly negatively correlated with exacerbation frequency, while Pseudomonas was positively correlated with exacerbation frequency (all P<0.05). Bacillota ( r=0.369, P=0.021), Fusobacteriota ( r=0.368, P=0.021), and Veillonella ( r=0.379, P=0.017) were positively correlated with FEV 1% predicted. Multivariable Firth logistic regression analysis revealed that the first principal component of the microbial community ( OR=2.29, 95% CI: 1.20-11.07) and the loss of≥8 teeth ( OR=14.37, 95% CI: 1.42-482.51) were independent factors associated with frequent acute exacerbations. Conclusion:Frequent acute exacerbations of COPD are significant association with deteriorated oral health and dysbiosis of the lower respiratory tract microbiome, characterized by reduced alpha-diversity and depletion of commensal bacteria.

This study aims to compare the vaccination rates and incidence of adverse reaction rates following administration of two domestically produced human papillomavirus (HPV) vaccines in individuals aged 9-30 years,investigate the impact of distinct manufacturing processes and vaccination schedules on adverse reaction rates. From November 2023 to June 2024, the Immunization Planning Department of Liuzhou Center for Disease Control and Prevention conducted a single-center, randomized, open-label, parallel-group trial using community-based recruitment of eligible participants aged 9 to 30 years. Participants were randomly assigned to receive either of two domestically produced HPV vaccines (Walrinvax or Cecolin). As specified in the vaccine package inserts, subjects were stratified into a two-dose regimen group (aged 9-14 years) and a three-dose regimen group (aged 15-30 years). Vaccination rates were recorded, and adverse reactions within 0-30 days post-vaccination were monitored. The results showed that a total of 400 participants were enrolled. Both the full vaccination rate and the timely completion rate were significantly higher in the two-dose regimen group compared to the three-dose regimen group (Fisher′s exact test, P<0.01; χ2=7.06, P<0.01). A total of 985 doses were administered. The overall adverse reaction rate was 18.78% (185/985), with local and systemic reactions occurring at 8.02% (79/985) and 10.76% (106/985), respectively. The most frequent adverse reactions were injection site pain (4.97%, 49/985) and fever (4.47%, 44/985). No grade 4 or special-interest adverse events were reported.The incidence of adverse reactions for the two domestic HPV vaccines with different production processes (at 0/6 months) was 13.96% (55/394) and 17.46% (69/395) respectively, with no statistically significant difference (χ2=1.83, P>0.05).The adverse reaction rate was significantly lower in the 9-14 years group (9.77%) compared the 15-30 years group (24.91%)(χ 2=35.67, P<0.01). In conclusion, both domestic HPV vaccines demonstrated a favorable safety profile in the 9-30 years age group, with mostly mild adverse reactions. Compared to the three-dose schedule (15-30 years group), the two-dose HPV vaccination schedule (9-14 years group) significantly reduced the incidence of adverse reactions and improved vaccination compliance.

Granulomatous vasculitis is a kind of necrotizing granulomatous vasculitis with the prominent feature of detectable anti-neutrophil cytoplasmic antibodies in serum, which often involves the respiratory tract and kidneys, and the onset of symptoms in the digestive tract is rare, and we now report a rare case of granulomatous vasculitis in which the gastrointestinal tract was involved as the first symptom in order to improve the clinician's understanding of this disease.