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.

AIM To study the chemical constituents from the leaves of Drynaria fortunei(Kunze)J.Sm.and their antioxidant activity.METHODS ODS-AG-HG,Sephadex LH-20 and semi-preparative HPLC were used for separation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH mothod.RESULTS Fifteen compounds were isolated and identified as kaempferol-3-O-neohesperidoside(1),dihydrodehydrodiconiferyl alcohol(2),kaempferol-3,7-di-O-α-L-rahmnoside(3),astragalin(4),loliolid(5),trichothecene analogue(6),2,2-[bis-4-(2,3-dihydroxypropoxy)phenyl]propane(7),maculatin(8),trichothecin(9),4-[(Z)-but-2-enoyloxy]-8-chloro-12-hydroxy-7,13-epoxytrichothec-9-ene(10),8-deoxy-trichotecin(11),β-sitosterol(12),daucosterol(13),afzelin(14),samwinol(15).The IC50 values of the leaf and rhizome extracts against DPPH free radicals were(0.072±0.005),(0.287±0.012)mg/mL,respectively.CONCLUSION Compounds 1,2,5-11,15 are isolated from this plant for the first time.The leaves of D.fortunei exhibit strong antioxidant activity.

Nichrome(NiCr)wire with strong mechanical properties,excellent flexibility,good corrosion resistance and high thermal stability was selected as a promising fiber substrate to replace the fragile fused-silica counterpart.The NiCr layered double hydroxide nanosheets(NiCr LDHs NSs)were in-situ grown on the NiCr fiber substrate.Then,the extraction performance of the NiCr@NiCr LDHs NSs fiber was evaluated using four kinds of chlorophenol(CPs)as model compounds combined with high performance liquid chromatography-ultraviolet detection(HPLC-UV).The results showed that the assembled fibers exhibited superior extraction selectivity and enhanced extraction efficiency for CPs in comparison to commercial PA,PDMS,and PDMS/DVB fibers.Under the optimized experimental conditions,the established method showed good linearity in the range of 0.2-200 μg/L,with coefficient of determination(R2)>0.9989.The limits of detection(LODs)and limits of quantification(LOQs)were 0.050-0.157 μg/L and 0.165-0.502 μg/L,respectively.Relative standard deviations(RSDs)for intra-day and inter-day analyses ranged from 2.85%to 4.05%and from 3.16%to 4.96%,respectively.The developed method with the constructed fiber was applied to preconcentration and detection of different types of CPs in real water samples,showing satisfactory recoveries ranging from 80.0%to 106.9%,with RSDs of 3.12%-7.81%.Moreover,the NiCr@NiCr LDHs NSs fiber could maintain good extraction performance even after 240 extraction-desorption cycles.

The efficient,precise,and rapid detection of trace copper ions(Cu2+)is of paramount importance in the realms of food safety,environmental monitoring,and medical health.By ingeniously utilizing the chemical properties of benzotriazole compounds in copper protection,and introducing an electrochemical reduction strategy,a silver nanoparticle composite structure supported by a nickel foam substrate was developed as an active platform for surface-enhanced Raman scattering(SERS)detection.This platform employed benzotriazole-5-carboxylic acid(BTAC)as a specific SERS probe molecule to achieve sensitive analysis of metal ion concentrations.The detection mechanism revealed a highly selective coordination between the Cu2+and the nitrogen atom in the triazole ring of BTAC,triggering subtle structural changes in the triazole ring.This was manifested by a significant and quantifiable shift in the characteristic peak of the SERS spectrum(particularly at 1001 cm-1),with a maximum shift of up to 30 cm-1.This phenomenon not only addressed the issue of reproducibility in quantitative analysis caused by the non-uniformity of SERS substrate materials but also significantly broadened the application boundaries of SERS technology for trace metal ion detection.It enabled ultra-sensitive detection of Cu2+concentrations ranging from 1×10-6 to 1×10-11 mol/L,with a detection limit as low as 1×10-11 mol/L,significantly enhancing detection sensitivity and accuracy.This work provided a novel and efficient strategy for rapid detection of trace Cu2+and enriched the application potential of SERS technology in food safety,environmental monitoring and biomedical analysis.

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.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Objective To analyze the feasibility and advantage of indocyanine green(ICG)fluorescence imaging technique in the thoracoscopic anatomical segmentectomy.Methods Patients with small pulmonary nodules who underwent thoracoscopic anatomical segmentectomy in our department from January 2023 to June 2024 were selected and divided into the ICG fluorescence group(35 cases determining intersegmental plane through ICG fluorescence imaging method)and the modified inflation-deflation group(42 cases determining intersegmental plane through modified inflation-deflation method)according to different methods of determining intersegmental plane.The surgery-related indicators including time of intersegmental plane occurrence,operation time,number of lymph node dissection,postoperative duration of chest tube and postoperative hospital stay as well as the occurrence of complications in the two groups were counted.Patients over 60 years old in two groups were selected and the differences in surgery-related indicators were analyzed.Results The time of intersegmental plane occurrence and operation time in the ICG fluorescence group were shorter than those in the modified inflation-deflation group,with statistically significant differences(P<0.05).There was no significant difference in the number of lymph node dissection,postoperative duration of chest tube or postoperative hospital stay between the two groups(P>0.05).There was no significant difference in the incidence of postoperative complications between the two groups(P>0.05).The time of intersegmental plane occurrence,operation time and postoperative hospital stay of patients over 60 years old in the ICG fluorescence group were shorter than those in the modified inflation-deflation group,with statistically significant differences(P<0.05).Conclusion ICG fluorescence imaging method can display the intersegmental plane clearly and quickly,which can shorten the time of intersegmental plane occurrence and hospital stay in elderly patients with pulmonary nodules.