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.

Rubi Fructus has a long history of medicinal and edible use in China. It contains chemical components such as terpenes, flavonoids, phenolic acids, fatty acids, and alkaloids, and possesses various pharmacological activities, including antioxidant, anti-inflammatory, hypoglycemic, anti-tumor, anti-osteoporosis, and liver-protective effects. Rubi Fructus is widely applied in medical, health, and food fields. The quality of Rubi Fructus can directly affect the safety and effectiveness of clinical medication. Therefore, this article reviews the research progress on the chemical constituents and pharmacological effects of Rubi Fructus. Based on the concept of traditional Chinese medicine(TCM) quality markers(Q-markers), the article explores the screening and determination of Q-markers for Rubi Fructus from various aspects, including plant kinship, traditional efficacy, medicinal properties, measurability of chemical composition, different processing methods, producing areas, harvesting periods, and planting conditions. The components ellagic acid, kaempferol, quercetin, kaempferol-3-O-rutinoside, rutin, astragalin, tiliroside, and hyperoside are preliminarily proposed as Q-markers for Rubi Fructus, providing a reference for the quality control of Rubi Fructus.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Rubus/chemistry* ; Fruit/chemistry* ; Quality Control ; Animals

Non-steroidal anti-inflammatory drugs(NSAIDs),commonly utilized analgesics,are extensively employed for managing pain associated with musculoskeletal disorders or injuries.Recent clinical studies have demonstrated a heightened risk of bone stress injuries(BSI)in soldiers and athletes,particularly during high-intensity training,due to NSAID usage.Furthermore,the impact of NSAIDs on fracture healing is well-documented;however,the precise mechanism by which their use during training contributes to an increased incidence of stress bone injuries remains unclear.This article aims to summarize potential mechanisms through an extensive review of domestic and international literature in order to standardize the utilization and clinical management of NSAIDs,optimize pain management strategies,and prevent stress bone injuries or fractures in specific populations such as soldiers and elite athletes.

Objective To investigate the population composition,seasonal dynamics,and infestation levels of cockroaches in Lanzhou,China,and to provide information for the scientific development of cockroach control strategies.Methods Monitoring was conducted at three locations using the sticky trap method.Habitats included farm product markets,catering establishments,hotels,hospitals,and residential areas.Results From 2016 to 2023,the average cockroach density was 0.77 insects per board,with an average infestation rate of 10.84%.Blattella germanica was the dominant species.Seasonal density of cockroaches showed an approximately unimodal distribution,peaking in September.The highest average density and infestation rates were observed in farm product markets.Conclusions Cockroach density and infestation levels in Lanzhou remained relatively low.A comprehensive prevention and control strategy focusing on environmental management in key areas should be implemented according to the seasonal fluctuations.

OBJECTIVE: We aimed to investigate the patterns of fasting blood glucose (FBG) trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers. METHODS: The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort (TGOC) between 2017 and 2022. A group-based trajectory model was used to identify the FBG trajectories. Environmental risk scores (ERS) were constructed using regression coefficients from the occupational hazard model as weights. Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories. RESULTS: FBG trajectories were categorized into three groups. An association was observed between high temperature, noise exposure, and FBG trajectory ( P < 0.05). Using the first quartile group of ERS1 as a reference, the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90 and 2.21 times, respectively (odds ratio [ OR] = 1.90, 95% confidence interval [ CI]: 1.17-3.10; OR = 2.21, 95% CI: 1.09-4.45). CONCLUSION An association was observed between occupational hazards based on ERS and FBG trajectories. The risk of FBG trajectory levels increase with an increase in ERS.
Humans ; Male ; Adult ; Blood Glucose/analysis* ; China ; Prospective Studies ; Occupational Exposure/adverse effects* ; Risk Factors ; Middle Aged ; Steel ; Fasting/blood* ; Metal Workers ; East Asian People

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

OBJECTIVE: A new three-dimensional(3D) classification of posterior cruciate ligament (PCL) tibial avulsion fracture based on computed tomography(CT) features was established and the significance in clinical treatment was explored in this study. METHODS: From May 2013 to November 2023, 43 cases of PCL tibial avulsion fracture in the Second Hospital of Jilin University were analyzed retrospectively, including 29 males and 14 females, aged (34.3±8.5) years. According to traditional Meyers and McKeever classification, 3 cases were typeⅠ;2 cases of typeⅡ;38 cases were type Ⅲ. Based on the characteristics of CT images, 43 patients were given specific treatment strategies and followed up to evaluate the curative effect. According to the degree of fracture displacement, involved range and the integrity of fracture block demonstrated by CT images, the new three-dimensional classification of PCL avulsion fracture was established. Kappa coefficient was used for consistency test. RESULTS: A new 3D classification of PCL tibial avulsion fracture was established. TypeⅠwas the non-displaced fracture (displacement degree ≤3 mm), in which typeⅠa was the avulsion range limited in the posterior intercondylar fossa, and Ib was the avulsion range beyond the posterior intercondylar fossa. TypeⅡrepresented the displaced fracture in the posterior intercondylar fossa (avulsion limited to the posterior intercondylar fossa and fracture displacement>3 mm), in which typeⅡa represented a slight displacement with a intact broken block and the posterior elevation of the avulsion (hinge mechanism), typeⅡb represented the complete separation of fracture ends with a intact fracture block, and typeⅡc was the comminuted fracture. Type Ⅲ was the displaced fracture beyond the posterior intercondylar fossa (avulsion involving the articular surface of the tibial plateau or the intercondylar ridge and the degree of displacement > 3 mm), among which type Ⅲa was the simple fracture with intact broken block, type Ⅲb represented the comminuted fracture, and type Ⅲc was the complex fracture with tibial plateau fracture. According to this new 3D classification, 43 patients were classified as type Ia in 2 cases and typeⅠb in 1 case;typeⅡa in 2 cases, typeⅡb in 15 cases and typeⅡc in 7 cases;type Ⅲa in 2 cases, type Ⅲb in 5 cases and type Ⅲc in 9 cases. All the 43 cases in this study achieved bone union. At the last follow-up, according to the hospital for special surgery knee score(HSS)evaluation system for the knee joint function, 27 cases were excellent, 11 cases were good, 5 cases were fair. The average Kappa value of inter-observer reliability in the first stage was 0.793, and the second stage was 0.855. The average Kappa value of the whole stage was 0.839, indicating high level of consistency. The average Kappa value of intra-observer reliability was 0.893, indicating high level of consistency. CONCLUSION The 3D classification of PCL tibial avulsion fracture is intuitive, demonstrating a high level of reliability. It has a certain guiding significance for the selection of clinical treatment methods, and it is suggested to be promoted and applied as a new classification system in clinical practice.
Humans ; Male ; Female ; Posterior Cruciate Ligament/surgery* ; Adult ; Tibial Fractures/classification* ; Tomography, X-Ray Computed ; Middle Aged ; Retrospective Studies ; Fractures, Avulsion/classification* ; Imaging, Three-Dimensional ; Young Adult

PURPOSE: The retear rate of rotator cuff (RC) after surgery is high, and the rapid and functional enthesis regeneration remains a challenge. Whether acellular amniotic membrane (AAM) helps to promote the healing of tendon to bone and which treatment is better are both unclear. The study aims to investigate the effect of AAM on the healing of RC and the best treatment for RC repair. METHODS: Thirty-three Sprague Dawley rats underwent RC transection and repair using microsurgical techniques and were randomly divided into the suturing repair only (SRO) group (n = 11), the AAM overlaying (AOL) group (n = 11), and the AAM interposition (AIP) group (n = 11), respectively. Rats were sacrificed at 4 weeks, then examined by subsequent micro-CT, and evaluated by histologic and biomechanical tests. The statistical analyses of one-way ANOVA or Kruskal-Wallis test were performed using with SPSS 23.0. A p < 0.05 was considered a significant difference. RESULTS: AAM being intervened between tendon and bone (AIP group) or overlaid over tendon to bone junction (AOL group) in a rat model, promoted enthesis regeneration, increased new bone and cartilage generation, and improved collagen arrangement and biomechanical properties in comparison with suturing repair only (SRO group) (AOL vs. SRO, p < 0.001, p = 0.004, p = 0.003; AIP vs. SRO, p < 0.001, p < 0.001, p < 0.001). Compared with the AOL group, the AIP group had better results in micro-CT evaluation, histological score, and biomechanical testing (p = 0 0.039, p = 0.011, p = 0.003, respectively). CONCLUSION In the RC repair model, AAM enhanced regeneration of the tendon to bone junction. This regeneration was more effective when the AAM was intervened at the tendon to bone interface than overlaid above the tendon to bone junction.
Animals ; Rats, Sprague-Dawley ; Rotator Cuff Injuries/surgery* ; Amnion/transplantation* ; Rats ; Wound Healing ; Rotator Cuff/surgery* ; Male ; X-Ray Microtomography ; Tendons/surgery* ; Biomechanical Phenomena

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.