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.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Brain’s neural activities encompass both periodic rhythmic oscillations and aperiodic neural fluctuations. Rhythmic oscillations manifest as spectral peaks of neural signals, directly reflecting the synchronized activities of neural populations and closely tied to cognitive and behavioral states. In contrast, aperiodic fluctuations exhibit a power-law decaying spectral trend, revealing the multiscale dynamics of brain neural activity. In recent years, researchers have made notable progress in studying brain aperiodic dynamics. These studies demonstrate that aperiodic activity holds significant physiological relevance, correlating with various physiological states such as external stimuli, drug induction, sleep states, and aging. Aperiodic activity serves as a reflection of the brain’s sensory capacity, consciousness level, and cognitive ability. In clinical research, the aperiodic exponent has emerged as a significant potential biomarker, capable of reflecting the progression and trends of brain diseases while being intricately intertwined with the excitation-inhibition balance of neural system. The physiological mechanisms underlying aperiodic dynamics span multiple neural scales, with activities at the levels of individual neurons, neuronal ensembles, and neural networks collectively influencing the frequency, oscillatory patterns, and spatiotemporal characteristics of aperiodic signals. Aperiodic dynamics currently boasts broad application prospects. It not only provides a novel perspective for investigating brain neural dynamics but also holds immense potential as a neural marker in neuromodulation or brain-computer interface technologies. This paper summarizes methods for extracting characteristic parameters of aperiodic activity, analyzes its physiological relevance and potential as a biomarker in brain diseases, summarizes its physiological mechanisms, and based on these findings, elaborates on the research prospects of aperiodic dynamics.

Objective:To investigate the effect of infusing different doses of graft cells on viral infections and survival after allogeneic hematopoietic stem cell transplantation(allo-HSCT).Methods:Clinical data of 99 patients with hematological diseases who underwent allo-HSCT in Shanxi Bethune Hospital were retrospectively analysed.The proportion of mononuclear cells(MNC)was counted microscopically,the proportions and absolute counts of CD34+cells and lymphocyte subsets(including CD3+T,CD4+T,CD8+T,CD4+CD8+T,B,and NK cells)were detected by flow cytometry,and the infusion dose of each cell types was calculated.The patients were divided into high-dose group and low-dose group based on the median value of the infused cell dose.The effects of different doses of various graft cells on post-transplant viral infections(CMV,EBV,BKV)and survival were analyzed.Results:The low-dose MNC(＜7.97 × 108/kg)and high-dose CD4+CD8+T cell(≥3.02 × 106/kg)groups had a higher Epstein-Barr virus(EBV)infection rate(P=0.031;P=0.020).The high-dose CD34+cell group and low-dose CD3+T,CD8+T and natural killer(NK)cell groups showed a trend toward higher EBV infection rates,but the differences were not statitsically significant(P＞0.05).There was no significant difference in the rates of EBV infection between the high-dose and low-dose groups of CD4+T and B cells(P＞0.05).Multivariate analysis revealed that the doses of MNC and CD4+CD8+T cells in the graft were independent factors influencing EBV infection(P=0.023;P=0.016).The doses of cells in the graft showed no significant impact on CMV and BKV infection,or patient survival(P＞0.05).Conclusion:Infusing a lower dose of MNC and a higher dose of CD4+CD8+T cells increases the risk of EBV infection,but does not affect the survival outcome.

Objective:To investigate the correlation of serum interleukin-6 (IL-6) and homocysteine (Hcy) levels, monocyte-to-lymphocyte ratio (MLR), and serum lipid levels [triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels] with ulcerative colitis.Methods:The clinical data of 98 patients with ulcerative colitis admitted to Bayannur Hospital from November 2021 to November 2023 (observation group) were retrospectively analyzed. Forty-nine healthy individuals who were selected at a 2:1 ratio during the same period were included in the control group. Serum IL-6 and Hcy levels, MLR, and lipid levels were compared between the two groups. The diagnostic efficacy of serum IL-6, Hcy, MLR, and lipid levels for ulcerative colitis was assessed using receiver operating characteristic (ROC) curves. Additionally, Pearson correlation analysis was conducted to analyze correlation of serum IL-6 and Hcy levels, MLR, and lipid levels with ulcerative colitis.Results:In the observation group, serum IL-6 and Hcy levels and MLR were (39.87 ± 12.36) pg/mL, (13.01 ± 3.52) μmol/L, and (0.38 ± 0.12), respectively, all of which were significantly higher than those in the control group [(22.3 ± 3.26) pg/mL, (10.05 ± 3.26) μmol/L, (0.29 ± 0.08), t = 9.77, 4.92, 4.78, all P < 0.05]. In the observation group, serum levels of TG, TC, LDL-C, and HDL-C levels were (1.16 ± 0.32) mmol/L, (4.12 ± 1.15) mmol/L, (2.60 ± 0.75) mmol/L, and (1.02 ± 0.17) mmol/L, respectively, all of which were significantly lower than those in the control group [(1.45 ± 0.41) mmol/L, (4.91 ± 0.99) mmol/L, (3.20 ± 0.71) mmol/L, (1.13 ± 0.16) mmol/L, t = 4.71, 4.11, 4.65, 3.77, all P < 0.05]. ROC curve analysis indicated that the areas under the curve (AUC) for diagnosing ulcerative colitis based on serum levels of IL-6, Hcy, MLR, TG, TC, LDL-C, and HDL-C were 0.957, 0.749, 0.746, 0.732, 0.678, 0.722, and 0.681, respectively. Pearson correlation analysis showed that serum levels of IL-6, Hcy, MLR, TG, TC, LDL-C, and HDL-C were all correlated with the severity of ulcerative colitis in patients ( r = 0.501, 0.615, 0.605, -0.577, -0.542, -0.548, -0.646, all P < 0.05). Additionally, serum levels of IL-6, Hcy, and MLR were negatively correlated with lipid levels ( r = -0.806, -0.801, -0.791, -0.649, -0.728, -0.671, -0.720, -0.655, -0.857, -0.877, -0.889, -0.583, all P < 0.05). Conclusions:In patients with ulcerative colitis, serum levels of IL-6, Hcy, and MLR are elevated, while lipid levels are decreased. Additionally, serum levels of IL-6, Hcy, MLR, and lipid levels are associated with the severity of the disease. There is also a correlation between serum levels of IL-6, Hcy, MLR, and lipid levels.

A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P＜0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P＜0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.

Objective:To explore the mediating effect of job embeddedness and job satisfaction on psycholog-ical capital and organizational silence in clinical nurses.Methods:Totally 412 clinical nurses(145 males and 267 females)were selected and assessed with the Nurse Organizational Silence Assessment Questionnaire(NOSAQ),Psychological Capital Questionnaire-24(PCQ-24),Job Embedding Scale(JES)and Nurses Job Satisfaction Scale(NJSS).SPSS macro program PROCESS and Bootstrap method were used to explore the role of mediation.Results:The NOSAQ scores were negatively correlated with the scores of PCQ-24,JES and NJSS(r=-0.55,-0.59,-0.51,Ps＜0.01).Job embeddedness and job satisfaction played a chain mediating role between psychological capital and organizational silence of clinical nurses(95％CI:-0.26--0.04),and the mediating effect accounted for 14.7％of the total effect.Conclusion:It suggests that organizational silence is closely related to psychological capital,job embeddedness and job satisfaction in clinical nurses.

Objective:To evaluate the characteristic manifestations of lumbar fusion following oblique lateral interbody fusion (OLIF), determine the specific incidence of these patterns, and the identify factors associated with fusion characteristics.Methods:This retrospective study analyzed 209 patients who underwent OLIF surgery at Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, between July 2017 and September 2023. The cohort had a mean age of 64.2±9.8 years and included 125 males and 84 females. A total of 338 lumbar segments were assessed, comprising 159 segments treated with stand-alone OLIF (OLIF-SA) and 179 segments treated with OLIF combined with posterior pedicle screw fixation (OLIF-PSF). Inclusion criteria were: patients aged 18-80 years who underwent OLIF with complete radiographic records. Surgical parameters, including fixation method, number of fused segments, surgical approach, and cage dimensions (height and width), were obtained from operative records. Radiographic evaluation included preoperative osteophytes, Hounsfield unit (HU) values of endplates, and cage positioning. Fusion rate, fusion pattern (lateral vs. central), cage subsidence, and related influencing factors were assessed. Clinical outcomes were measured via the Oswestry disability index (ODI) and visual analog scale (VAS) preoperatively, immediately postoperatively, and at 1-year follow-up. Results:The overall fusion rate was 98.2% (332/338), with a non-union rate of 1.8% (6/338). The incidence of lateral fusion was 40.2% (136/338). In the OLIF-SA group, lateral and central fusion rates were 50.3% (80/159) and 49.7% (79/159), respectively, with no cases of non-union. In the OLIF-PSF group, lateral fusion occurred in 31.3% (56/179), central fusion in 65.4% (117/179), and non-union in 3.3% (6/179), with statistically significant differences between groups ( P<0.05). Preoperative osteophytes and higher endplate HU values were significantly associated with lateral fusion ( P<0.05). However, cage dimensions and cage position (anterior-posterior and lateral placement) were not significantly associated with fusion pattern ( P>0.05). Overall, 61.5% (208/338) of segments showed no cage subsidence; 24.5% (83/338) had settling, and 14.0% (47/338) had grade 1 or higher subsidence. Among lateral fusion cases, the rates of no subsidence, anchoring, grade 1, grade 2, and grade 3 subsidence were 67.6%, 21.3%, 7.4%, 3.9%, and 0.7%, respectively. In the central fusion group, these rates were 59.2%, 27.6%, 9.2%, 2.5%, and 1.3%, respectively. In the non-union group, grade 2 and 3 subsidence occurred in 50% (3/6) each, significantly higher than in the other fusion groups ( P<0.05). Post hoc analysis confirmed that grade 2 and 3 subsidence rates were significantly elevated in the non-union group compared to the lateral and central fusion groups, while other subsidence categories showed no significant differences across groups. Clinically, patients showed significant improvements in ODI and VAS scores following surgery ( P<0.05). Conclusions:Lateral fusion occurred in 40.2% of OLIF cases. The OLIF-SA technique, preoperative osteophytes, and elevated preoperative HU values were significantly associated with lateral fusion. In contrast, surgical approach, number of fused segments, cage height, width, and cage positioning did not significantly influence the occurrence of lateral fusion.

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.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.