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.

Objective:To compare the clinical efficacy of Chevron-Akin osteotomy with cannulated compression screw and absorbable screw fixation in the treatment of moderate and severe hallux valgus.Methods:The data of 52 patients with moderate to severe hallux valgus treated in Sichuan Provincial Orthopaedic Hospital from January 2020 to December 2022 were retrospectively analyzed. According to the fixation method, they were divided into metal screw group and absorbable screw group. In the metal screw group, there were 25 cases (26 feet), 2 males (2 feet) and 23 females (24 feet), aged 36.7±4.9 years (range, 21-59 years), 12 feet on the left side, 14 feet on the right side, moderate 20 feet and severe 6 feet. There were 27 cases (29 feet) in the absorbable screw group, including 1 male (1 foot) and 26 female (28 feet), aged 34.1±5.5 years (range, 19-56 years), 16 feet on the left side, 13 feet on the right side, moderate 22 feet and severe 7 feet. The healing time and complications of osteotomy were recorded between the two groups, and the hallux valgus angle (HVA), first-second intermetatarsal angle (1-2 IMA), American Orthopaedic Foot and Ankle Society (AOFAS), hallux-metatarsophalangeal-interphalangeal joint score and visual analogue scale (VAS) for pain were compared before and after the operation.Results:All 52 patients were followed up. The follow-up time was 14.0±3.4 months (range, 11-27 months) in the metal screw group and 15.1±2.7 months (range, 13-24 months) in the absorbable screw group. In all patients, the incision healed in one stage, and no endovegetal rejection occurred. The osteotomy healing time was 3.8±0.8 months (range, 2-5 months) in the metal screw group and 3.4±1.1 months (range, 2.5-5 months) in the absorbable screw group, with no statistically significant difference ( t=1.014, P=0.417). In the metal screw group, there were symptoms of medial internal fixation irritation in 2 feet, medial osteophyte or thread knot irritation in 2 feet, and hallux valgus recurrence in 1 foot. The complication rate was 19%(5/26). In the absorbable screw group, medial osteophyte or thread knot stimulated one foot and hallux valgus recurred one foot, and the complication rate was 7%(2/29). The difference in complications between the two groups was statistically significant (χ 2=8.051, P=0.012). At 12 months after operation, for the metal screw group and the absorbable screw group, HVA (13.7°±2.1° and 12.9°±3.8°), 1-2 IMA (7.2°±1.5° and 7.8°±1.2°), AOFAS score (91.4±2.2 and 90.8±3.6 points) and VAS score (1.1±0.3 and 1.3±0.4 points), respectively, were significantly higher than those in the preoperative (HVA: 37.2°± 5.4° and 35.8°±4.7°, 1-2 IMA: 18.3°± 1.8° and 17.9°±1.7°, AOFAS score: 60.4±5.6 and 58.4±7.1 points, VAS: 6.4±0.6 and 6.8±0.4 points) improvement ( P<0.05), while there was no statistically significant difference between the two groups ( P>0.05). The incidence of complications in metal screw group was 19%(5/26), while in absorbable screw group it was 7%(2/29), with a statistically significant difference (χ 2=8.051, P=0.012). Conclusions:Both cannulated compression screw in Chevron-Akin osteotomy and absorbable screw fixation can have a good fixation effect in the treatment of moderate and severe hallux valgus. Absorbable screw fixation has the advantages of low complication rate, less interference with artifacts in later imaging examination and evaluation.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Sarin(GB)is a typical representative of nerve agents with high toxicity,and very low amount can cause death.GB can cause water and atmospheric environment poisoning,so the detection of GB in water and air is of great significance.In this work,a colorimetric sensor array(CSA)based on GB inhibition of cholinesterase activity was constructed to detect GB with high selectivity.A 4×4 colorimetric array was constructed using acetylcholinesterase(AChE),butyryl cholinesterase(BuChE)and the corresponding substrate acetylthiocholine iodide(S-ACh),butyryl thiocholine iodide(S-BCh),acetylcholine chloride(ACh),butyryl choline chloride(BCh)and 2,6-dichloroindophenol ethyl ester(DCIE).The linear curve of the sensor was Y=131.3×lgC+271.6(R2=0.997),where Y was the array response Euclidean distance,C was the concentration of GB(mg/L),the linear range was 0.03?0.32 mg/L,and the detection limit was 27.6 μg/L.The method could effectively distinguish chemical warfare agents(CWA)such as VX,Soman(GD),mustard gas(HD),Louie reagent(L),and had high anti-interference ability,sensitivity and good repeatability.It was successfully applied to the detection of GB in simulated water and simulated air samples,and the sample recovery rate was 97.2% ?100.9%.This method would be potentially applied to the field rapid detection of nerve agents.

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion is one of the most commonly used supportive treatments for children with hematological diseases. This guideline provides guidance and recommendations for blood transfusions in children with aplastic anemia, thalassemia, autoimmune hemolytic anemia, glucose-6-phosphate dehydrogenase deficiency, acute leukemia, myelodysplastic syndromes, immune thrombocytopenic purpura, and thrombotic thrombocytopenic purpura. This article presents the evidence and interpretation of the blood transfusion provisions for children with hematological diseases in the "Guideline for pediatric transfusion", aiming to assist in the understanding and implementing the blood transfusion section of this guideline.
Humans ; Child ; Hematologic Diseases/therapy* ; Blood Transfusion/standards* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion for children undergoing hematopoietic stem cell transplantation is highly complex and challenging. This guideline provides recommendations on transfusion thresholds and the selection of blood components for these children. This article presents the evidence and interpretation of the transfusion provisions for children undergoing hematopoietic stem cell transplantation, with the aim of enhancing the understanding and implementation of the "Guideline for pediatric transfusion".
Humans ; Hematopoietic Stem Cell Transplantation ; Child ; Blood Transfusion/standards* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Critically ill children often present with anemia and have a higher demand for transfusions compared to other pediatric patients. This guideline provides guidance and recommendations for blood transfusions in cases of general critical illness, septic shock, acute brain injury, extracorporeal membrane oxygenation, non-life-threatening bleeding, and hemorrhagic shock. This article interprets the background and evidence of the blood transfusion provisions for critically ill and severely bleeding children in the "Guideline for pediatric transfusion", aiming to enhance understanding and implementation of this aspect of the guidelines. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(4): 395-403.
Humans ; Critical Illness ; Blood Transfusion/standards* ; Child ; Hemorrhage/therapy* ; Practice Guidelines as Topic

To guide clinical blood transfusion practices in pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Children undergoing cardiac surgery are at high risk of bleeding, and the causes of perioperative anemia and coagulation disorders in neonates and children are complex and varied, often necessitating the transfusion of allogeneic blood components. This guideline provides direction and recommendations for specific measures in blood management for children undergoing cardiac surgery before, during, and after surgery. This article interprets the background and evidence for the formulation of the blood transfusion provisions for children undergoing cardiac surgery, hoping to facilitate the understanding and implementation of this guideline.
Humans ; Cardiac Surgical Procedures ; Blood Transfusion/standards* ; Child ; Practice Guidelines as Topic

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning