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 quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

To improve the quality evaluation system of Hibisci Mutabilis Folium, this study established high performance liquid chromatography(HPLC) fingerprints of Hibisci Mutabilis Folium and evaluated the quality differences of medicinal materials from different places of production by chemometrics. Furthermore, a content measurement method of differential components was established based on quantitative analysis of multi-components by single-marker(QAMS). The fingerprints of 17 batches of Hibisci Mutabilis Folium from different places of production were constructed, with a total of 19 common peaks marked and seven components confirmed. The similarity between the sample fingerprints and the reference fingerprints ranged from 0.890 to 0.974. By utilizing principal component analysis(PCA), hierarchical cluster analysis(HCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA), the chemical patterns of fingerprints were identified. Five components that could be used to evaluate the quality differences of Hibisci Mutabilis Folium were screened, namely peak 6(quercetin 3-O-β-robinobioside), peak 7(rutin), peak 9(kaempferol-3-O-β-robinobioside), peak 10(kaempferol-3-O-rutinoside), and peak 14(tiliroside). The relative correction factors of isoquercitrin, kaempferol-3-O-β-robinobioside, kaempferol-3-O-rutinoside, kaempferol-3-O-β-D-glucoside, and tiliroside were measured with rutin as the internal reference. The QAMS method was established for the content measurement of six flavonoids, and the results showed there was no significant difference compared to the results obtained by an external standard method. In summary, the HPLC fingerprints and QAMS method established in the study, demonstrating stability and accuracy, can provide a reference for the overall quality evaluation of Hibisci Mutabilis Folium.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Principal Component Analysis

Objective To investigate the effects of laparoscopic sleeve gastrectomy(LSG)on the cardiac structure and function in obese patients with heart failure(HF)and compare the efficacy of LSG across obese patients with different HF types.Methods This study included 33 obese patients with HF who underwent LSG.The clinical indicators were compared between before operation and 12 months after operation.Repeated measures analysis of variance was employed to evaluate the changes in echocardiographic parameters before operation and 3,6,and 12 months after operation.Patients were allocated into a HF with preserved ejection fraction group(n=17),a HF with mildly reduced ejection fraction group(n=5)and a HF with reduced ejection fraction(HFrEF)group(n=11)based on left ventricular ejection fraction(LVEF)before operation for subgroup analyses of the effects of LSG on the cardiac structure and function of obese patients with HF.The paired samples t-test was conducted to assess the degree of cardiac structural and functional alterations after LSG.Results The 33 patients included 69.7% males,with an average age of(35.3±9.9)years,and a body mass index(BMI)of(51.2±9.8)kg/m².The median follow-up was 9.0(5.0,13.3)months.Compared with the preoperative values,the postoperative BMI(P=0.002),body surface area(BSA)(P=0.009),waist circumference(P=0.010),hip circumference(P=0.031),body fat content(P=0.007),and percentage of patients with cardiac function grades Ⅲ-IV(P<0.001)decreased.At the 12-month follow-up left atrial diameter(P=0.006),right atrial long-axis inner diameter(RAD1)(P<0.001),right atrial short-axis inner diameter(RAD2)(P<0.001),right ventricular inner diameter(P=0.002),interventricular septal thickness at end-diastolic(P=0.002),and left ventricular end-diastolic volumes(P=0.004)and left ventricular end-systolic volumes(P=0.003) all significantly reduced compared with preoperative values.Additionally,left ventricular fractional shortening and LVEF improved(both P<0.001).Subgroup analyses revealed that cardiac structural parameters significantly decreased in the HF with preserved ejection fraction,HF with mildly reduced ejection fraction,and HFrEF subgroups compared with preoperative values.Notably,the HFrEF group demonstrated the best performance in terms of left atrial diameter(P=0.003),left ventricular inner diameter at end-diastole(P=0.008),RAD1(P<0.001),RAD2(P=0.004),right ventricular inner diameter(P=0.019),left ventricular end-diastolic volume(P=0.004)and left ventricular end-systolic volume(P=0.001),cardiac output(P=0.006),tricuspid regurgitation velocity(P=0.002),and pulmonary artery systolic pressure(P=0.001) compared to preoperatively.Postoperative left ventricular fractional shortening(P<0.001,P=0.003,P<0.001)and LVEF(P<0.001,P=0.011,P=0.001)became higher in all the three subgroups than the preoperative values.Conclusions LSG decreased the body weight,BMI,and BSA,improved the cardiac function grade,reversed the enlargement of the left atrium and left ventricle,reduced the right atrium and right ventricle,and enhanced the left ventricular systolic function.It was effective across obese patients with different HF types.Particularly,LSG demonstrates the best performance in improving the structures of both atria and ventricles in obese patients with HFrEF.
Humans ; Male ; Female ; Gastrectomy/methods* ; Heart Failure/complications* ; Adult ; Obesity/physiopathology* ; Laparoscopy ; Middle Aged ; Heart/physiopathology* ; Stroke Volume

A method for determination and targeted screening of diflorasone components in health products using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry(UPLC-Q-TOF/MS)was established.Four representative diflorasone and esters(diflorasone,diflorasone diacetate,diflorasone-17-propionate,and diflorasone-21-propionate)were selected to optimize the pretreatment conditions,and 10 mL of extraction solvent dosage,15 min of extraction time and 5 g of salting-out agent as the optimal conditions were selected by response surface methodology.The results showed that the four analytes exhibited good linearity within the concentration range of 2.0?100 μg/L with the chromatographic peak area,and the correlation coefficients(R2)were all greater than 0.9990,while the results of recovery and relative standard deviation could satisfy the requirements of determination.The common characteristic ions of diflorasone and esters werem/z121 andm/z335,and their specific structures were obtained by analyzing the cleavage pathway based on the optimized determination conditions.A targeted screening method for other esters of diflorasone based on characteristic ions guidance strategy was established.This method had many advantages such as high efficiency,high sensitivity and good reproducibility,and could be used for targeted screening of diflorasone and esters in health products.The developed characteristic ion guided strategy could be employed to construct mass spectral databases for various glucocorticoids,enabling comprehensive targeted screening across a broad range of compounds.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

The Wnt signaling pathway includes both classical and non classical pathways,Wnt5a-Frizzled-2 pathway participates in the Wnt/Ca2+signaling pathway in the non-classical pathway,which is activated by the Wnt-related protein Wnt5a and its ligand Frizzled-2.It can regulate some key sites in cells to affect cell signal transduction,and is closely related to cell growth process.Activation of Wnt5a-Fizzled-2 pathway occurs in some tissues with abundant blood supply,such as heart and brain tissues,during ischemia-reperfusion.Activation of the Wnt5a-Frizzled-2 pathway causes these intracellular calcium overload,ultimately promoting apoptosis.This article reviews the abnormal activation of Wnt5a-Frizzled-2 signaling pathway in ischemia-reperfusion injury diseases and the induced calcium overload leading to apoptosis,in order to provide reference for the study of physiological mechanisms of ischemia-reperfusion injury.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Objective To investigate the dynamic expression with the time change of N6-methyladenosine(m6A)methylation-related factors in the repair process of skeletal muscle injury and its mechanism in the inflammatory response of macrophage in the injure process.Methods In vivo mice models of BaCl2 injury in the gastrocnemius were established.Four mice per group in the control group and injury group.Gastrocnemius tissues were harvested at day 1,3,5,7,and 9 after injury for experiments.Primary gastrocnemius muscle tissue cells,muscle satellite cells,muscle cells,and cell line C2C12 cells were treated with dexamethasone(DEX,50 μmol/L)to mimic injury.Lipopolysaccharide(LPS,100 μg/L)induced RAW264.7 cell lines to mimic the inflammatory response after skeletal muscle injury,and STM2457(30 μmol/L)was added to inhibit the effect of methyltransferase 3(Mettl3)before LPS treatment.The expression of m6A methylation-related factors(Writers,Erasers,Readers)and inflammation factors were detected by Real-time PCR and Western blotting.Results The muscle fibers were dissolved and then gradually repaired with the extension of injury time,the number of monocytes/macrophages increased first and then decreased,and the Pax7 mRNA level increased first and then decreased with the change of injury time.Compared with the control group,the mRNA and protein levels of m6A methylation-related factors in gastrocnemius did not change significantly on the injury-1 day.However,they were significantly increased on the injury-3 days compared with the control group(P＜0.05),and then obviously decreased on the injury-5 days group compared with the injury-3 days group(P＜0.05).Compared with the control group,they were no significant differences on the injury-7 days group and-9 days group.In vitro DEX decreased the mRNA levels of m6A methyltransferase factors in primary muscle satellite cells and C2C12 cells and increased the mRNA expression level of methylation-recognition enzyme factors(P＜0.05).The mRNA levels of m6A methylation-related factors increased significantly in skeletal muscle tissue cells and myocytes after DEX treatment(P＜0.05).After LPS treatment,the mRNA and protein expression levels of m6A methylation-related factors and the mRNA expression levels of inflammatory factors interleukin(IL)-6 and IL-1β in macrophages increased significantly(P＜0.05),while the levels of IL-6 and IL-1β mRNA in macrophages decreased significantly when the Mettl3 was inhibited(P＜0.05).Conclusion m6A methylation-related factors primarily is activated in the damaged muscle cells and inflammation response of macrophages.Inhibition of m6A methyltransferase can reduce the inflammatory response of macrophages.