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.

Rheumatoid arthritis(RA)is a chronic autoimmune disease of unknown etiology that can cause joint destruction and deformity.As a small molecule cytokine,the chemokine C-X-C motif chemokine ligand 12(CXCL12)regulates the pathogenesis of rheumatoid arthritis by binding to the specific receptor CXC chemokine receptor 4(CXCR4).Therefore,based on the bio-logical characteristics of CXCL12 and CXCR4,this paper intro-duces the pathogenesis of CXCL12/CXCR4 in RA and summari-zes the progress in RA-related research,with the aim of providing clinical value for understanding the pathogenesis of RA and de-veloping novel therapeutic targets.

Objective To explore the effects of Rutin on multiple organ damage in septic mice and to investigate its mechanism from the perspective of inflammation.Methods Male C57BL/6 mice were divided into the normal control(sham)group,cecal ligation and puncture(CLP)group,low-dose Rutin group(25 mg/kg),medium-dose Rutin group(50 mg/kg),and high-dose Rutin group(100 mg/kg),there are 20 mouse in each group.All mice were given gavage daily for 7 days starting at 8 weeks of age(the Rutin groups were administered the corresponding doses of the drug,while the sham and CLP groups were given the same volume of saline).Subsequently,sepsis was induced in mice by CLP.The survival rate of mice was analyzed;pathological damage of the lungs,liver,and kidneys in mice was assessed by HE staining;the lung coefficient and wet/dry(W/D)ratio of the lungs were measured;the levels of alanine transaminase(ALT),aspartate aminotransferase(AST),creatinine(CRE),and urea nitrogen(BUN)in mouse serum were detected;the content of urinary protein in mice was measured;the mRNA levels of tumor necrosis factor-α(TNF-α)and IL-6 in mouse tissues were detected by RT-qPCR;and the activation of the JAK2-STAT3 signaling pathway was analyzed by Western blot.Results Rutin reduced the mortality rate of septic mice,alleviated liver,lung,and kidney damage,improved liver,lung,and kidney functions,inhibited the activation of the JAK2-STAT3 signaling pathway in tissues,and reduced the mRNA expression of pro-inflammatory factors.Conclusion Rutin may alleviate inflammation by inhibiting the activation of the JAK2-STAT3 signaling pathway,and has a protective effect on liver,lung,and kidney damage in septic mice.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Rheumatoid arthritis(RA)is a chronic autoimmune disease of unknown etiology that can cause joint destruction and deformity.As a small molecule cytokine,the chemokine C-X-C motif chemokine ligand 12(CXCL12)regulates the pathogenesis of rheumatoid arthritis by binding to the specific receptor CXC chemokine receptor 4(CXCR4).Therefore,based on the bio-logical characteristics of CXCL12 and CXCR4,this paper intro-duces the pathogenesis of CXCL12/CXCR4 in RA and summari-zes the progress in RA-related research,with the aim of providing clinical value for understanding the pathogenesis of RA and de-veloping novel therapeutic targets.

Objective To explore the effects of Rutin on multiple organ damage in septic mice and to investigate its mechanism from the perspective of inflammation.Methods Male C57BL/6 mice were divided into the normal control(sham)group,cecal ligation and puncture(CLP)group,low-dose Rutin group(25 mg/kg),medium-dose Rutin group(50 mg/kg),and high-dose Rutin group(100 mg/kg),there are 20 mouse in each group.All mice were given gavage daily for 7 days starting at 8 weeks of age(the Rutin groups were administered the corresponding doses of the drug,while the sham and CLP groups were given the same volume of saline).Subsequently,sepsis was induced in mice by CLP.The survival rate of mice was analyzed;pathological damage of the lungs,liver,and kidneys in mice was assessed by HE staining;the lung coefficient and wet/dry(W/D)ratio of the lungs were measured;the levels of alanine transaminase(ALT),aspartate aminotransferase(AST),creatinine(CRE),and urea nitrogen(BUN)in mouse serum were detected;the content of urinary protein in mice was measured;the mRNA levels of tumor necrosis factor-α(TNF-α)and IL-6 in mouse tissues were detected by RT-qPCR;and the activation of the JAK2-STAT3 signaling pathway was analyzed by Western blot.Results Rutin reduced the mortality rate of septic mice,alleviated liver,lung,and kidney damage,improved liver,lung,and kidney functions,inhibited the activation of the JAK2-STAT3 signaling pathway in tissues,and reduced the mRNA expression of pro-inflammatory factors.Conclusion Rutin may alleviate inflammation by inhibiting the activation of the JAK2-STAT3 signaling pathway,and has a protective effect on liver,lung,and kidney damage in septic mice.

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.

OBJECTIVES: To study the clinical and genetic characteristics of children with congenital adrenal hyperplasia (CAH). METHODS: Clinical data, laboratory findings, and genetic test results of 63 children diagnosed with CAH at Henan Children's Hospital from January 2017 to December 2024 were retrospectively reviewed. RESULTS: Of the 63 patients, the mean age at the first visit was (21 ± 14) days; 29 (46%) were of male sex and 34 (54%) were of female sex. The predominant clinical manifestations were poor weight gain or weight loss (92%, 58/63), poor feeding (84%, 53/63), skin hyperpigmentation (83%, 52/63), and female external genital anomalies (100%, 34/34). Laboratory abnormalities included hyponatremia (87%, 55/63), hyperkalemia (68%, 43/63), metabolic acidosis (68%, 43/63), and markedly elevated 17-hydroxyprogesterone (92%, 58/63), testosterone (89%, 56/63), and adrenocorticotropic hormone (81%, 51/63). Among 49 patients who underwent genetic testing, CYP21A2 variants were identified in 90% (44/49), with c.293-13A/C>G (33%, 30/91) and large deletions/gene conversions (29%, 26/91) being the most frequent; STAR (8%, 4/49) and HSD3B2 (2%, 1/49) variants were also detected. Following hormone replacement therapy, electrolyte disturbances were corrected in 57 cases, with significant reductions in 17-hydroxyprogesterone, adrenocorticotropic hormone, and testosterone levels (P<0.001). CONCLUSIONS CAH presenting in neonates or young infants is characterized by electrolyte imbalance, external genital anomalies, and abnormal hormone levels. Genetic testing enables definitive subtype classification; in CYP21A2-related CAH, c.293-13A/C>G is a hotspot variant. These findings underscore the clinical value of genetic testing for early diagnosis and genetic counseling in CAH. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(11): 1367-1372.
Humans ; Adrenal Hyperplasia, Congenital/diagnosis* ; Male ; Female ; Retrospective Studies ; Infant ; Infant, Newborn

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

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.