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.

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.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

OBJECTIVE: To explore clinical efficacy of autologous platelet-rich plasma(PRP) in treating Rockwood type Ⅲ acromioclavicular dislocation. METHODS: From January 2019 to July 2021, 32 patients with Rockwood type Ⅲ acromioclavicular dislocation were treated with minimally invasive adjustable titanium plate internal fixation, and were divided into PRP group and control group according to whether PRP treatment was performed, with 16 patients in each group. In PRP group, there were 10 males and 6 females, aged from 28 to 47 years old with an average of (36.75±7.14) years old;the time from injury to surgery ranged from 1 to 31 h with an average of (26.13±3.98) h;5 patients on the left side and 11 patients on the right side;PRP was injected once during operation and the 4th and 8th weeks after operation respectively. In control group, there were 8 males and 8 females, aged from 30 to 52 years old with an average of (38.50±5.48) years old; the time from injury to surgery ranged from 1 to 29 h with an average of (25.48±3.11) h;7 patients on the left side and 9 patients on the right side; minimally invasive surgical treatment was performed. Visual analogue scale(VAS) was used to evaluate pain and Constant-Murley score for shoulder joint function was used to evaluate the recovery of shoulder joint movement function before operation and 1, 3, 6, and 12 months after operation respectively. RESULTS: All patients were followed up for 12 to 28 months with an average of (18.3±5.2) months. All incisions patients healed well without adverse events such as infection. Postoperative VAS of PRP group at 1, 3, and 6 months were (5.5±1.2), (3.7±1.6), and (2.4±1.2), respectively, while were lower than those of control group (6.6±1.4), (4.9±1.1), and (3.7±1.3), respectively;and had statistical differences between two groups (P<0.05). There was no statistically significant difference in VAS between two groups before operation and 12 months after operation (P>0.05). Postoperative Constant-Murley scores of PRP group at 1, 3, and 6 months were (64.09±11.61), (73.19±12.89), and (82.61±14.81) points, respectively, which were higher than those of control group were (52.32±17.42), (61.65±14.43), and (72.52±11.04) respectively;and the differences were statistically significant (P<0.05). There was no statistically significant difference in Constant-Murley scores at 12 months after operation between two groups (P>0.05). In PRP group, there was no statistically significant difference at 6 months and 12 months after operation (P>0.05), while there were statistically significant differences at the other time points (1 month after operation compared with before operation, 3 months after operation compared with 6 months after operation, and 3 months after operation compared with 1 month after operation) (P<0.05). In control group, there was no statistically significant difference when comparing 1 month and 3 months after operation (P>0.05), while at the other time points (1 month after operation with before operation, 3 months after operation with 6 months after operation, and 6 months after operation with 12 months after operation), the differences were all statistically significant (P<0.05). CONCLUSION Adjustable titanium plate fixation combined with postoperative injection of PRP for the treatment of Rockwood type III acromioclavicular joint dislocation has effect of promoting the recovery of shoulder joint function and reducing pain.
Humans ; Male ; Female ; Adult ; Middle Aged ; Platelet-Rich Plasma ; Acromioclavicular Joint/surgery* ; Bone Plates ; Titanium ; Joint Dislocations/therapy* ; Fracture Fixation, Internal/methods*

OBJECTIVE: To compare the clinical efficacy and complication rates of staged open reduction internal fixation (ORIF) and external fixation combined with limited internal fixation (EFLIF) in the treatment of high-energy Pilon fractures. METHODS: A retrospective selection was conducted on 78 patients diagnosed with high-energy tibial Pilon fractures who received treatment between January 2021 and October 2023. These patients were categorized into the staged ORIF group and the EFLIF group according to their respective treatment protocols. The staged ORIF group comprised 48 patients, including 29 males and 19 females, aged from 33 to 53 years old with a mean age of (43.25±4.67) years old. The time from injury to treatment averaged (6.54±2.21) hours. All patients received staged ORIF treatment. The EFLIF Group consisted of 30 patients, including 18 males and 12 females, aged from 36 to 54 years old with a mean age of (43.37±3.24) years old. The time from injury to treatment averaged (6.87±1.96) hours. All patients received EFLIF treatment. The recovery of ankle joint function, fracture reduction quality, fracture healing time, and surgical-related indicators between two groups were observed and compared six months after surgery. Additionally, the postoperative complications of the two groups were recorded. RESULTS: Both groups of patients were followed up and the duration ranged from 6 to 12 months, with an average of (8.97±1.26) months. At 6-month postoperative follow-up, the American Orthopaedic Foot and Ankle Society (AOFAS) score in the ORIF group was (83.15±20.93), which did not show a statistically significant difference compared to the EFLIF group (81.88±20.67), P>0.05. The excellent and good rate of fracture reduction in the staged ORIF group was 33.33% (16/48), which did not show a statistically significant difference compared to the EFLIF group (30.00%, 9/30), P>0.05. The hospitalization duration and fracture healing time in the staged ORIF group were (16.57±1.25) days and (12.14±1.15) weeks, respectively. When compared to the EFLIF group, which demonstrated a hospitalization duration of (15.97±2.16 ) days and a fracture healing time of (12.36±1.17) weeks, no statistically significant differences were observed (P>0.05). The intraoperative blood loss in the staged ORIF group was (76.54±11.65) ml, which was significantly higher than that in the EFLIF group (70.15±10.29) ml, and the difference was statistically significant (P<0.05). The incidence of superficial tissue infection was 2.08%(1/48), which was significantly lower than that observed in the EFLIF group at 16.67% (5/30), and this difference was statistically significant (P<0.05). CONCLUSION Both staged ORIF and EFLIF were effective treatment options for high-energy closed Pilon fractures of the tibia. However, regarding the prevention of superficial tissue infection, staged ORIF demonstrates superior risk control compared to EFLIF.
Humans ; Male ; Female ; Middle Aged ; Adult ; Tibial Fractures/physiopathology* ; Fracture Fixation, Internal/methods* ; Retrospective Studies ; External Fixators ; Open Fracture Reduction/methods* ; Treatment Outcome

Steroid-induced osteonecrosis of the femoral head (SONFH) is avascular necrosis of the femoral head caused by long-erm use of corticosteroids, and its pathogenesis is complex and affected by changes in the dynamic balance of the bone microenvironment. With the deepening of research, the role of bone microenvironment in the pathogenesis of SONFH has been gradually revealed. In the case of excessive use of glucocorticoids (GCs), the bone microenvironment changes significantly, causing imbalance in bone lipid metabolism, microcirculation disorders and disorders of immune regulation, which promotes the increase of the number and activity of osteoclasts, and interferes with the differentiation of osteoblasts and adipoblasts. Through the regulation of PI3K/AKT, OPG/RANKL/RANK, MAPK, JAK/STAT, Hedgehog and other signaling pathways, it eventually leads to osteocyte apoptosis, bone microvascular rupture and destruction of trabecular bone structure, which in turn leads to osteonecrosis, bone density reduction and bone microstructure destruction due to bone microcirculation ischemia, and finally leads to necrosis of the femoral head. This article reviews the role of bone microenvironment homeostasis in GCs-induced ONFH and the regulatory mechanism of bone microenvironment, which is helpful to reveal the pathogenesis of SONFH and provide a theoretical basis for exploring effective intervention strategies.
Humans ; Femur Head Necrosis/physiopathology* ; Animals ; Signal Transduction ; Bone and Bones/metabolism* ; Glucocorticoids/adverse effects* ; Cellular Microenvironment

OBJECTIVE: To observe the clinical efficacy of 3D printing spinal external fixator combined with McKenzie therapy for patients with lumbar dics herniation (LDH). METHODS: Sixty patients with LDH between January 2022 and January 2023 were enrolled. Among them, 30 patients were given McKinsey training. According to different treatment methods, all patients were divided into McKenzie group and McKenzie + 3D printing group, 30 patients in each group. The McKenzie group provided McKenzie therapy. The McKenzie + 3D printing group were treated with 3D printing spinal external fixation brace on the basis of McKenzie therapy. Patients in both groups were between 25 and 60 years of age and had their first illness. In the McKenzie group, there were 19 males and 11 females, with an average age of (48.57±5.86) years old, and the disease duration was (7.03 ±2.39) months. The McKenzie + 3D printing group, there were 21 males and 9 females, with an average age of (48.80±5.92) years old, and the disease duration was(7.30±2.56) months. Pain was evaluated using the visual analogue scale (VAS), and lumbar spine function was assessed using the Oswestry disability index (ODI) and the Japanese Orthopaedic Association (JOA) score. VAS, ODI and JOA scores were compared between two groups before treatment and at 1, 3, 6, 9 and 12 months after treatment. RESULTS: All patients were followed up for 12 months. The VAS for the McKenzie combined with 3D printing group before treatment and at 1, 3, 6, 9, and 12 months post-treatment were(6.533±0.860), (5.133±1.008), (3.933±0.868), (2.900±0.759), (2.067±0.640), (1.433±0.504), respectively. In the McKenzie group, the corresponding scores were (6.467±0.860), (5.067±1.048), (4.600±0.968), (3.533±1.008), (2.567±0.728), (1.967±0.809), respectively. The ODI of the McKenzie group before treatment and at 1, 3, 6, 9, and 12 months post-treatment were (41.033±6.810)%, (37.933±6.209)%, (35.467±6.962)%, (27.567±10.081)%, (20.800±7.531)%, (13.533±5.158)%, respectively. For the McKenzie combined with 3D printing group, the corresponding ODI were(38.033±5.605)%, (33.000±6.192)%, (28.767±7.045)%, (22.200±5.517)%, (17.700±4.836)%, (11.900±2.771)%, respectively. The JOA scores of the McKenzie combined with 3D printing group before treatment and at 1, 3, 6, 9, and 12 months post-treatment were(8.900±2.074), (13.133±2.330), (15.700±3.583), (20.400±3.480), (22.267±3.084), (24.833±2.640), respectively. In the McKenzie group, the corresponding scores were(9.200±2.091), (12.267±2.406), (15.333±3.198), (18.467±2.240), (20.133±2.751), (22.467±2.849), respectively. Before the initiation of treatment, no statistically significant differences were observed in the VAS, ODI, and JOA scores between two groups (P>0.05). At 3, 6, 9, and 12 months post-treatment, the VAS in the McKenzie combined with 3D printing group was significantly lower than that in the McKenzie group, and the difference was statistically significant (P<0.05). The comparison of ODI between two groups at 1, 3, 6, 9, and 12 months post-treatment revealed statistically significant differences (P<0.05). At 6, 9, and 12 months post-treatment, the JOA score in the McKenzie combined with 3D printing group was significantly higher than that in the McKenzie-only group, and the difference was statistically significant (P<0.05). CONCLUSION The combination of 3D printed functional spinal external fixation brace with McKenzie therapy can significantly improve and maintain lumbar function in patients with LDH.
Humans ; Male ; Female ; Middle Aged ; Printing, Three-Dimensional ; Intervertebral Disc Displacement/surgery* ; External Fixators ; Lumbar Vertebrae/surgery* ; Adult ; Braces ; Treatment Outcome

OBJECTIVE: To investigate the clinical efficacy and safety of single Kirschner wire assisted poking and closed reduction in the treatment of Gartland type Ⅲ supracondylar humeral fractures in children. METHODS: A retrospective analysis was performed on patients diagnosed with Gravland type Ⅲ supracondylar humeral fractures between January 2022 and June 2023. A total of 46 patients were treated with closed reduction assisted by Kirschner wires and percutaneous Kirschner wire internal fixation.There were 25 males and 21 females. The age ranged from 5 to 10 years old, with an average of (5.8±1.8) years old. The left side was involved in 28 patients and the right side in 18 patients. Record the operative duration for patients, the number of fluoroscopic exposures, fracture healing time, postoperative carrying angle, Baumann angle, elbow joint function score at three months post-operation, and any associated complications. RESULTS: All 46 patients were followed up for a period of 12 to 16 weeks, with an average of (13.74±1.44 )weeks. The operation duration was (30.7±5.1) minutes, the fluoroscopy count was (10.2±2.7) times, the postoperative carrying angle of the elbow joint was (8.7±2.2) degrees, and the Baumann angle was (71.5±2.9) degrees. All fractures achieved successful union in all patients, with a mean healing time of (25.5±1.7) days.At the final follow-up, elbow joint function was assessed using the Flynn criteria, with 43 patients rated as excellent and 3 patients rated as good. No complications were observed, including cubitus varus, nerve injury, or local infection. CONCLUSION The use of a single Kirschner wire assisted prying reduction for treating Gartland type Ⅲ supracondylar humeral fractures in children demonstrates excellent clinical efficacy and safety.
Humans ; Male ; Female ; Child ; Bone Wires ; Child, Preschool ; Humeral Fractures/physiopathology* ; Retrospective Studies ; Fracture Fixation, Internal/instrumentation* ; Treatment Outcome ; Fracture Healing

OBJECTIVE: To construct a prediction model for fracture reduction fixator therapy using the multi-modal multi-label classification (MMC) method. METHODS: Medical record data of 818 orthopedic patients from 2019 to 2023 were collected. Medical image features were extracted using the VGG19 network, text features of TCM four diagnostic methods (Inspection, Auscultation & Olfaction, Inquiry, Palpation) were extracted via the MiniLM model, and clinical case features were extracted through a fully connected neural network. After fusing the multi-modal information, multi-label therapy prediction was achieved using a linear layer. RESULTS: Experimental results on the clinical multi-modal dataset showed that the MMC method performed excellently in terms of subset accuracy(SA), accuracy(Acc), precision, and F₁-score, reaching 0.661, 0.856, 0.897, and 0.899 respectively. When the image modality and text modality were removed, the model performance decreased by an average of 8.1% and 2.4% respectively, while the hamming loss(HL) increased by 21.1% and 5.6% respectively. CONCLUSION The fracture reduction fixator therapy prediction model constructed in this study can effectively fuse multi-modal data, accurately predict personalized treatment plans for patients, and significantly improve the accuracy and reliability of treatment decisions. It provides a new solution for the digitalization and intellectualization of Traditional Chinese Medicine(TCM) in fracture treatment and has important clinical application prospects.
Humans ; Female ; Male ; Middle Aged ; Fracture Fixation/methods* ; Adult ; Fractures, Bone/surgery* ; Neural Networks, Computer ; Medicine, Chinese Traditional ; Aged

OBJECTIVES: To explore the influencing factors for very preterm birth at a gestational age of <32 weeks in the Xinjiang Uygur Autonomous Region. METHODS: Clinical data of women with preterm deliveries and their newborns admitted to five hospitals in Xinjiang from January 2023 to December 2024 were retrospectively collected. The subjects were divided by gestational age into very preterm (<32 weeks of gestation) and moderate/late preterm (32-36⁺⁶ weeks of gestation) groups. Risk factors associated with very preterm birth were analyzed. RESULTS: A total of 4 105 pregnant women with preterm deliveries were included, with 793 cases (19.32%) in the very preterm group and 3 312 cases (80.68%) in the moderate/late preterm group. The factors significantly associated with very preterm birth were as following: hypertensive disorders of pregnancy (OR=1.785, 95%CI: 1.492-2.135, P<0.05), excessive gestational weight gain (GWG, OR=2.002, 95%CI: 1.672-2.397, P<0.05), insufficient GWG (OR=1.746, 95%CI: 1.326-2.300, P<0.05), chorioamnionitis (OR=2.163, 95%CI: 1.694-2.763, P<0.05), premature rupture of membranes ≥18 hours (OR=2.158, 95%CI: 1.599-2.912, P<0.05), placental abruption (OR=2.228, 95%CI: 1.646-3.014, P<0.05), and ≤7 prenatal visits (OR=3.419, 95%CI: 2.882-4.055, P<0.05). CONCLUSIONS In the Xinjiang Uygur Autonomous Region, hypertensive disorders of pregnancy, excessive or insufficient GWG, chorioamnionitis, premature rupture of membranes ≥18 hours, placental abruption, and ≤7 prenatal visits are risk factors for very preterm birth. Strengthening high-risk pregnancy management is necessary for reducing the incidence of very preterm birth.
Humans ; Female ; Retrospective Studies ; Pregnancy ; Premature Birth/etiology* ; Gestational Age ; Adult ; Risk Factors ; Infant, Newborn ; Gestational Weight Gain