Puerariae Lobatae Radix and Puerariae Thomsonii Radix are the dried roots of Pueraria lobata and Pueraria thomsonii of the Leguminosae family， respectively. Since their separate inclusion in the 2005 edition of Pharmacopoeia of the People's Republic of China， the two herbs have been individually recorded. Although they share the same functions and indications， the required content of puerarin differs by a factor of up to eightfold between them. The current quality standard relies solely on a single indicator， puerarin， which fails to reflect the correlation between chemical constituents and core therapeutic effects. This has resulted in prominent issues of mixed use in clinical practice and production， thereby constraining the high-quality development of the industry. Modern research has demonstrated that Puerariae Lobatae Radix contains a comprehensive range and higher content of isoflavonoid constituents， while Puerariae Thomsonii Radix is rich in starch and polysaccharides. Puerariae Lobatae Radix exhibits stronger effects in antipyresis， cardiovascular and cerebrovascular protection， and central analgesia， while Puerariae Thomsonii Radix demonstrates greater advantages in anti-inflammation， hypoglycemia， and peripheral analgesia. Based on this， the chemical material bases of Puerariae Lobatae Radix and Puerariae Thomsonii Radix at both the macromolecule and micromolecule levels were systematically reviewed and compared. The pharmacodynamic material bases and mechanisms of action underlying their three core therapeutic effects， namely "relieving exterior syndrome and clearing heat"， "promoting fluid production to quench thirst"， and "dredging channels and activating collaterals"， were summarized. The most highly correlated common metabolic pathway shared by both herbs for these three therapeutic effects is the arachidonic acid metabolic pathway， and their common core target is prostaglandin-endoperoxide synthase 2 （PTGS2）. This review provided clinical application recommendations based on the therapeutic differences between the two herbs， elucidated the scientific connotation of their "same origin but different effects"， and， grounded in the quality marker （Q-Marker）， proposed the concept of efficacy-related Q-Marker based on "substance-efficacy-syndrome" association， as well as a novel strategy for efficacy-oriented quality evaluation. Preliminary screening of quality markers associated with different therapeutic effects was also conducted. This study aims to provide critical scientific evidence for the precise clinical application of Puerariae Lobatae Radix and Puerariae Thomsonii Radix， the improvement of quality standards， and the high-quality development of the industry.

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.

Objective:To investigate the reference intervals of serum uric acid levels in normal-weight children and analyze the factors influencing these levels.Methods:In this cross-sectional study, clinical data were collected from 7 910 normal-weight children, aged 1 month to 15 years, who underwent health check-ups at the Children′s Hospital of Zhejiang University School of Medicine between August 2013 and August 2023. Data included sex, age, pubertal signs, blood pressure, and serum uric acid levels. The participants were categorized into 4 age groups: 1-<12 months, 1-<6 years, 6-<11 years, and 11-<16 years, and were further analyzed by sex. The P5 and P95 percentiles of uric acid values were defined as the lower and upper limits of the reference interval, respectively. Correlation analysis and partial correlation analysis were used to assess the relationship between uric acid and other variables such as age, body mass index Z value, and Tanner stage. Multivariate linear regression was used to compare uric acid levels across gender and age groups, respectively. Results:Among the 7 910 children, the distribution across age groups was as follows: 562 (317 boys) in 1-<12 months, 4 120 (2 366 boys) in 1-<6 years, 2 357 (1 432 boys) in 6-<11 years, and 871 (536 boys) in 11-<16 years, the uric acid levels in boys were significantly higher than those in girls ( P<0.05). Uric acid levels exhibited a positive correlation with age ( r=0.47 , 0.20, both P<0.001), and a weak positive correlation with BMI Z-scores(both r=0.11, P<0.001). Among participants aged 6-<11 years and 11-<16 years, uric acid levels in boys were positively correlated with Tanner stage ( r=0.10, 0.27, both P<0.05), but no significant correlation was observed in girls (all P>0.05). The uric acid levels were significantly higher in boys than in girls in the 1-<12 months, 1-<6 years and 11-<16 years age groups (all P<0.05), but no significant gender difference was found in the 6-<11 years groups ( P>0.05). Uric acid levels exhibited statistically significant variations among age groups ( P<0.001). The reference intervals of uric acid values were as follows in 1-<12 months age group, 157-335 μmol/L for boys and 160-315 μmol/L for girls; in 1-<6 years age group, 180-359 μmol/L for boys and 180-355 μmol/L for girls; in 6-<11 years group, 190-375 μmol/L; in 11-<16 years age group, 237-480 μmol/L for boys and 218-410 μmol/L for girls. Conclusions:Reference intervals for uric acid varying significantly across different pediatric age groups. Sex, and pubertal development status are closely related to uric acid levels.

Obesity presents significant challenges in spinal surgery, including higher rates of perioperative complications, prolonged operative times, and delayed recovery. Traditional open spine surgery often exacerbates these risks, particularly in patients with obesity, because of extensive tissue dissection and larger incisions. Endoscopic spine surgery (ESS) has emerged as a promising minimally invasive alternative, offering advantages such as reduced tissue trauma, minimal blood loss, lower infection rates, and faster recovery. This systematic review and meta-analysis aimed to evaluate the safety, efficacy, and outcomes of ESS techniques, including fully endoscopic and biportal endoscopic lumbar discectomy and decompression, in patients with obesity and lumbar spine pathologies. A comprehensive literature search of the PubMed/Medline, Embase, and Scopus databases yielded 2,975 studies published between 2000 and 2024, of which 10 met the inclusion criteria. The meta-analysis revealed significant improvements in pain relief (Visual Analog Scale) and functional outcomes (Oswestry Disability Index), with comparable results between patients with and without obesity. Patients who are obese experienced longer operative times and have a slightly higher risk of symptom recurrence; however, ESS demonstrated lower rates of wound infections, shorter hospital stays, and faster recovery than traditional surgery. These findings position ESS as a viable and effective option for managing lumbar spine conditions in patients with obesity, addressing obesity-related surgical challenges while maintaining favorable clinical outcomes. However, limitations such as study heterogeneity and the lack of randomized controlled trials highlight the need for further high-quality research to refine ESS techniques and optimize patient care in this high-risk population.

Objective To establish a rapid screening and analysis method for etomidate and its ana-logues using a portable mass spectrometer equipped with a thermal desorption-atmospheric pressure chemical ionization source-linear ion trap.Methods A 10 μL aliquot of a standard solution at a con-centration of 1 μg/mL was taken,and after the solvent evaporated,the sample was inserted into the in-let of the portable mass spectrometer for detection.By adjusting the collision-induced dissociation pa-rameters,the molecular ion peak and fragment ion peak information of the standard were obtained and used to establish a reference database.In addition,the method was applied to 29 seized liquid and plant samples.Results A screening system for etomidate and its analogues was established based on the portable mass spectrometer and the corresponding mass spectrometry library.The system enables qualitative screening analysis by identifying primary protonated molecular ions and secondary product ions of etomidate and its analogues.The limits of detection for etomidate and its 12 analogues ranged from 0.1 to 10 μg/mL.Etomidate and its analogues were detected in all 29 liquid and plant samples.However,this method could not distinguish between isomeric imidazole esters,such as isopropoxate and propoxate.Additionally,when testing 2-SH-etomidate,there was a false positive for the detection of etomidate.Conclusion This study established a rapid screening method for etomidate and its ana-logues using a portable mass spectrometer.The method combines the high sensitivity of mass spectrome-try with the on-site applicability of portable devices,significantly improving detection efficiency and meeting the on-site detection needs of etomidate and its analogues.

Obesity presents significant challenges in spinal surgery, including higher rates of perioperative complications, prolonged operative times, and delayed recovery. Traditional open spine surgery often exacerbates these risks, particularly in patients with obesity, because of extensive tissue dissection and larger incisions. Endoscopic spine surgery (ESS) has emerged as a promising minimally invasive alternative, offering advantages such as reduced tissue trauma, minimal blood loss, lower infection rates, and faster recovery. This systematic review and meta-analysis aimed to evaluate the safety, efficacy, and outcomes of ESS techniques, including fully endoscopic and biportal endoscopic lumbar discectomy and decompression, in patients with obesity and lumbar spine pathologies. A comprehensive literature search of the PubMed/Medline, Embase, and Scopus databases yielded 2,975 studies published between 2000 and 2024, of which 10 met the inclusion criteria. The meta-analysis revealed significant improvements in pain relief (Visual Analog Scale) and functional outcomes (Oswestry Disability Index), with comparable results between patients with and without obesity. Patients who are obese experienced longer operative times and have a slightly higher risk of symptom recurrence; however, ESS demonstrated lower rates of wound infections, shorter hospital stays, and faster recovery than traditional surgery. These findings position ESS as a viable and effective option for managing lumbar spine conditions in patients with obesity, addressing obesity-related surgical challenges while maintaining favorable clinical outcomes. However, limitations such as study heterogeneity and the lack of randomized controlled trials highlight the need for further high-quality research to refine ESS techniques and optimize patient care in this high-risk population.

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

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.