Introduction: Diazoxide is an effective treatment for hyperinsulinemic hypoglycemia (HH), though its dosage for the transient form of HH is not well established. Recently, a Singapore cohort reported effective low-dose diazoxide in treating HH secondary to small for gestational age (SGA). We aim to study the effectiveness and safety of this low-dose regimen in transient HH. Methodology: This was a retrospective cohort study. All infants diagnosed with transient HH and treated with diazoxide between 1 January 2024 and 31 December 2025 were included. The primary objective was to determine the effective diazoxide dose in maintaining euglycemia (blood glucose ≥3.5 mmol/L). The secondary objective was to monitor complications following diazoxide usage. Results: A total of 21 infants were recruited with a median gestational age of 37 weeks (IQR: 35–37.5) and a median birth weight of 1,980 grams (IQR: 1,670–2,340). The risk factors were SGA (71.4%, n = 15), infants of diabetic mothers (19%, n = 4), and others (14%, n = 3). A median glucose infusion rate of 12.6 (IQR: 10.4–14.5) mg/kg/minute was required to treat the hypoglycemia. Eleven infants (52.3%) required adjunct glucagon therapy before transitioning to diazoxide therapy, with a median dose of 8 mcg/kg/hour (IQR: 7–12). Diazoxide was initiated at a median of 20 days of life (IQR: 14–30), with a median starting dose of 3.0 mg/kg/day (IQR: 3.0–3.55). Euglycemia was fully achieved in 95.2% (n = 20) of infants within a median of 5 days (IQR: 3–9) post diazoxide initiation. At discharge, the median diazoxide dose was 3.3 mg/kg/day (IQR: 3.0–4.8). Adverse events occurred in five cases (23.8%), primarily limited to transient fluid retention (n = 4) and gastrointestinal symptoms (n = 1). None developed echocardiography-proven pulmonary hypertension in this cohort. Conclusion Low-dose diazoxide (3–5 mg/kg/day) is effective and well-tolerated for managing the transient form of HH in our setting. This benefit appears not to be limited to babies born with SGA, but may extend to other risk factors as well.
Diazoxide ; Hypoglycemia

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.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

The number of patients suffering from coronary heart disease in China is large and growing rapidly,and it shows a younger trending,which brings a heavy burden to the patients' families and society.Traditional Chinese medicine(TCM)guiding technique is an important component of China's traditional medicine,which is an exercise method that involves essence,energy and spirit and combines limb movement,breathing and mental regulation.TCM guiding techniques include five animal exercises,Tai chi,Baduanjin,Yijinjing and six-character formula etc.In recent years,more and more researches show that as one of the TCM guiding techniques,five animal exercise has a positive promoting effect on the prevention,treatment and rehabilitation of coronary heart disease,and it also has a good effect on the improvement of the risk factors and complications of coronary heart disease.Combined with modern medical research,this paper provides a systematic and comprehensive summary and analysis of the applica-tion of five animal exercise in cardiac rehabilitation,which provides sufficient theoretical basis for choosing five ani-mal exercise as the cardiac rehabilitation exercise program for patients with coronary heart disease in the future.

Objective:To investigate the neuroprotective effect of non-invasive vagus nerve stimulation(nVNS)on traumatic brain injury(TBI).Methods:Male SD rats were used to prepare controlled cortical impact(CCI)rat mod-el.nVNS treatment was performed.The motor function of rats was detected by beam walking test.The water content of rats was evaluated by the dry-wet ratio of rat brain tissue.The content of lactate dehydrogenase(LDH)in cerebrospinal fluid was detected by commercial kit.The expression of bain-derived neurotrophic factor(BDNF)and nerve growth fac-tor(NGF)mRNA in rat cortex was detected by RT-qPCR.Results:After nVNS stimulation,CCI rats significantly im-proved the neurological function deficit,improved the motor ability,decreased the cerebral water content,decreased the level of LDH in cerebrospinal fluid,and upregulated the expression of BDNF and NGF mRNA in cortex.Conclusion:nVNS has a neuroprotective effect on TBI rats,and its mechanism may be related to the increased expression of BDNF and NGF.

Objective:To compare the safety and accuracy between robotic-assisted screw placement and free-hand screw placement in adolescent idiopathic scoliosis (AIS) surgery.Methods:The clinical data of 69 AIS patients underwent posterior spinal scoliosis orthomorphia from December 2021 to October 2023 in Beijing Chaoyang Hospital, Capital Medical University were retrospectively analyzed. Among them, 37 patients underwent robot-assisted screw placement (robot group), and 32 patients underwent fluoroscopy-assisted free-hand screw placement (free-hand group). The basic information of surgery (operation time, intraoperative blood loss, intraoperative radiation exposure time, postoperative hospital stay and postoperative complications), screw placement indexes (single screw placement time and accuracy of screw placement) and imaging indexes (main curve correction rate, kyphotic change and lumbar lordosis change) were compared between two groups. The ln curve regression analysis method was used to evaluate the learning curve of robot-assisted screw placement therapy for AIS.Results:A total of 716 screws were placed in 32 patients of free-hand group, and 766 screws in 37 patients of robot group. The operation time, intraoperative radiation exposure time, single screw placement time and accuracy of screw placement in robot group were significantly higher than those in free-hand group: (272.30 ± 67.98) min vs. (221.66 ± 67.32) min, (149.81 ± 57.21) s vs. (116.03 ± 63.10) s, (497.97 ± 51.74) s vs. (381.47 ± 46.58) s and 97.91% (750/766) vs. 91.48% (655/716), and there were statistical differences ( P<0.01 or <0.05); there were no statistical differences in intraoperative blood loss, postoperative hospital stay, incidence of neurological complications, incidence of incision infection and number of screw between two groups ( P>0.05). There were no statistical differences in the main curve correction rate, kyphotic change and lumbar lordosis change between two groups ( P>0.05). When the fitting degree was the highest ( R2 = 0.729, P<0.01), the fitting equation was y = - 50.93ln x + 634.7 ( x was the number of operation, and y was the single screw placement time), and the number of vertices was 12 cases. The robot group was divided into three subgroups according to the order of surgery, subgroup A consisted of 12 patients who underwent the surgery from first to twelfth, subgroup B consisted of 12 patients who underwent the surgery from thirteenth to twenty-fourth, and subgroup C consisted of 13 patients who underwent the surgery from twenty-fifth to thirty-seventh. Among them, the single screw placement time in subgroup A was significantly longer than that in subgroup B and subgroup C: (560.92 ± 35.03) s vs. (465.75 ± 21.20) and (469.62 ± 24.94) s, and there was statistical difference ( P<0.05); there was no statistical difference between subgroup B and subgroup C ( P>0.05). Conclusions:Robot-assisted screw placement for AIS can effectively improve the accuracy of screw placement without affecting deformity correction, but it can increase screw placement time, operation time and radiation exposure time. A smooth learning curve is obtained after performing 12 procedures.

Objective:To explore the therapeutic effect of Bupiqiangli compound on experimental myasthenia gravis with sub-clinical hypothyroidism in rats and the influence of hypothalamus-pituitary-thyroid-thymus(HPTT)axis.Methods:SPF Lewis rats were randomly divided into normal group,model group,Bupiqiangli compound low-dose,medium-dose and high-dose groups.Model rats were immunized with AchR-α subunit 97-116 peptide sequence to construct an experimental myasthenia gravis model,and then methimazole was used to prepare an experimental myasthenia gravis with subclinical hypothyroidism model.Bupiqiangli compound low-dose,medium-dose and high-dose groups were given 4.57 g/kg,7.12 g/kg and 9.49 g/kg of Bupiqiangli compound by gavage,nor-mal group and model group were given an equal volume of normal saline by gavage,once a day,for 4 weeks.After the last gavage,Lennon scores of rats in each group were recorded;HE staining was used to detect pathological changes of thymus and thyroid;ELISA was used to detect expression levels of acetylcholine receptor antibody(AchRab),thyroid stimulating hormone(TSH),thyrotropin releasing hormone(TRH),free thyroxine(FT4)and thyroxine(T4)in serum;mRNA level of TRH in hypothalamus and TSH in pituitary tissue were detected by qPCR;Western blot detected changes of protein expressions of Cleaved Caspase3,Bcl2 associated X protein(Bax)and B-cell lymphoma-2(Bcl2)in thymus.Results:Compared with normal group,model group showed obvious symp-toms of muscle weakness,Lennon score increased significantly(P<0.05),obvious pathological changes in thymus and thyroid tissues,while no significant changes in expressions of FT4 and T4 in serum(P>0.05),expressions of AchRab,TSH and TRH in serum were significantly increased(P<0.05),expressions of TRH in hypothalamus and TSH in pituitary were significantly increased(P<0.05),protein expressions of Cleaved Caspase3 and Bax in thymus were significantly decreased(P<0.05),while expression of Bcl2 protein in thymus increased significantly(P<0.05).Compared with model group,myasthenia symptoms of compound high-dose group were im-proved,Lennon score was significantly decreased(P<0.05),pathological changes of thymus and thyroid tissues were improved,ex-pressions of FT4 and T4 in serum had no significant changes(P>0.05),expressions of AchRab,TSH and TRH in serum were signifi-cantly decreased(P<0.05),expressions of TRH in hypothalamus and TSH in pituitary were significantly decreased(P<0.05),expres-sions of Cleaved Caspase3 and Bax in thymus were significantly increased(P<0.05),while expression of Bcl2 in thymus was signifi-cantly decreased(P<0.05).Conclusion:Bupiqiang compound can improve clinical symptoms of experimental myasthenia gravis with subclinical hypothyroidism in rats,and its mechanism may be related to the regulation of HPTT axis.

Objective: This study aims to evaluate the clinical benefits of the integrated optical and magnetic surgical navigation system in assisting transforaminal endoscopic lumbar discectomy (TELD) for the treatment of lumbar disc herniation (LDH). Methods: A retrospective analysis was conducted on patients who underwent TELD for LDH at Beijing Chaoyang Hospital, Capital Medical University from November 2022 to December 2023. Patients treated with the integrated optical and magnetic surgical navigation system were defined as the navigation-guided TELD (Ng-TELD) group (30 cases), while those treated with the conventional x-ray fluoroscopy method were defined as the control group (31 cases). Record and compare baseline characteristics, surgical parameters, efficacy indicators, and adverse events between the 2 patient groups. Results: The average follow-up duration for the 61 patients was 11.8 months. Postoperatively, both groups exhibited significant relief from back and leg pain, which continued to improve over time. At the final follow-up, patients’ lumbar function and quality of life had significantly improved compared to preoperative levels (p < 0.05). The Ng-TELD group had significantly shorter total operation time (58.43 ± 12.37 minutes vs. 83.23 ± 25.90 minutes), catheter placement time (5.83 ± 1.09 minutes vs. 15.94 ± 3.00 minutes), decompression time (47.17 ± 11.98 minutes vs. 67.29 ± 24.23 minutes), and fewer intraoperative fluoroscopies (3.20 ± 1.45 vs. 16.58 ± 4.25) compared to the control group (p < 0.05). There were no significant differences between the groups in terms of efficacy evaluation indicators and hospital stay. At the final follow-up, the excellent and good rate of surgical outcomes assessed by the MacNab criteria was 98.4%, and the overall adverse event rate was 8.2%, with no statistically significant differences between the groups (p > 0.05). Conclusion This study demonstrates that the integrated optical and magnetic surgical navigation system can reduce the complexity of TELD, shorten operation time, and minimize radiation exposure for the surgeon, highlighting its promising clinical potential.