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.

AIM To study the chemical constituents from the buds of Aralia chinensis L.var.nuda Nakai and their in vitro anti-inflammatory activities.METHODS The 70％ethanol extract from the buds of A.chinensis var.nuda was isolated and purified by silica gel,Sephadex LH-20,ODS and semi-preparative HPLC,then the structures of compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities in vitro were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as 4-(2,2-dibutoxyethyl)phenol(1),trans-linalool-3,7-oxide-6-O-β-D-glucopyranoside(2),2'-O-(9Z,12Z,15Z-octadecatrienoyl)glyceryl β-D-galactopyranoside(3),quercetin-3-O-β-D-glucopyranoside(3'→ O-3''')quercetin-3-O-β-D-galactopyranoside(4),syringaresinol-4'-O-β-D-glucopyranoside(5),p-hydroxybenzaldehyde(6),7α-hydroxystigmasterol 3-O-β-D-glucopyranoside(7),trans-p-hydroxy cinnamic acid methyl ester(8),funingensin A(9),3,4-dihydroxy-acetophenone(10),N-acetyltyramine(11),3,4-di-O-caffeoyl quinic acid(12),chlorogenic acid(13),aralia cerebroside(14),caffeic acid methyl ester(15),tetradecanoic acid(16).The IC50values of compounds 8,10,12 and 13 were(22.19±1.59),(35.25±1.30),(13.38±0.72),(15.73±1.16)μmol/L,respectively.CONCLUSION Compound 1 is a new compound,2-13 are isolated from genus Aralia for the first time.Compounds 8,10,12,13 exhibit significant in vitro anti-inflammatory activities.

Objective To investigate the internalized weight bias and weight control beliefs regarding the current status,influencing factors,and impacts on eating behaviors of women losing weight. Methods A convenient sampling method was used to select the females who underwent physical examination in the Peking Union Medical College Hospital from August to December 2023.The general information questionnaire,Weight Bias Internalization Scale,Weight Control Belief Questionnaire,and Chinese version of Three-Factor Eating Questionnaire were utilized for investigation.Latent class analysis was conducted to explore the potential categories based on the characteristics of internalized weight bias and weight control beliefs.Univariate analysis and multiple-factor linear regression analysis were performed to explore influencing factors of potential categories and their effects on eating behaviors. Results A total of 518 subjects were included in this study.The internalized weight bias and weight control beliefs could be classified into three potential categories: low weight bias tolerance type(53.7%),medium weight bias persistence type(29.5%),and high weight bias overcritical type(16.8%).Logistic regression analysis showed that body mass index,unmarriage,and divorce were the influencing factors of the high weight bias overcritical type.The scores of non-control eating and emotional eating in medium weight bias persistence type and high weight bias overcritical type were higher than those in low weight bias tolerance type(all P<0.001). Conclusions The attitudes of Chinese women towards body weight can be categorized into low weight bias tolerance type,medium weight bias persistence type,and high weight bias overcritical type.The high weight bias overcritical type is characterized by high weight bias and high personal responsibility attribution,and it is closely associated with negative eating behaviors.A high body mass index,unmarriage,and divorce are high-risk factors for developing the high weight bias overcritical type.
Humans ; Female ; Feeding Behavior/psychology* ; Surveys and Questionnaires ; Adult ; Body Mass Index ; Weight Loss ; Body Weight ; Body Image ; Middle Aged ; Weight Prejudice

Steroid-induced osteonecrosis of femoral head (SONFH) is a disease characterized by femoral head collapse and local pain caused by excessive use of glucocorticoids. Peroxisome proliferator-activated receptor-γ (PPARγ) is mainly expressed in adipose tissue. Wnt/β-catenin, AMPK and other related signaling pathways play an important role in regulating adipocyte differentiation, fatty acid uptake and storage. Bone marrow mesenchymal cells (BMSCs) have the ability to differentiate into adipocytes or osteoblasts, and the use of hormones upregulates PPARγ expression, resulting in BMSCs biased towards adipogenic differentiation. The increase of adipocytes affects the blood supply and metabolism of the femoral head, and the decrease of osteoblasts leads to the loss of trabecular bone, which eventually leads to partial or total ischemic necrosis and collapse of the femoral head. MicroRNAs (miRNAs) are a class of short non-coding RNAs that regulate gene expression by inhibiting the transcription or translation of target genes, thereby affecting cell function and disease progression. Studies have shown that miRNAs affect the progression of SONFH by regulating PPARγ lipid metabolism-related signaling pathways. Therefore, it may be an accurate and feasible SONFH treatment strategy to regulate adipogenic-osteoblast differentiation in BMSCs by targeted intervention of miRNA differential expression to improve lipid metabolism. In this paper, the miRNA-mediated PPARγ-related signaling pathways were classified and summarized to clarify their effects on lipid metabolism in SONFH, providing a theoretical reference for miRNA targeted therapy of SONFH, and then providing scientific evidence for SONFH precision medicine.
MicroRNAs/physiology* ; PPAR gamma/metabolism* ; Femur Head Necrosis/metabolism* ; Humans ; Signal Transduction/physiology* ; Lipid Metabolism/physiology* ; Animals ; Cell Differentiation ; Mesenchymal Stem Cells/cytology* ; Glucocorticoids/adverse effects*

Objective To investigate the association of endometrial thickness(EMT)with obstetric and neonatal outcomes of monoparous pregnancy in fresh cleavage embryos transfer.Methods A total of 1 845 patients of monoparous pregnancy after fresh cleavage embryos transfer cycles from Jan 2016 to Mar 2022 at Shanghai First Maternity and Infant Hospital,Tongji Universtiy were analyzed retrospectively.Patients were categorized into three groups by EMT on transferation day:≤8 mm(group A),8-14 mm(group B)and≥14 mm(group C).The primary outcomes were preterm birth(PTB),birth weight and birth weight z-score,small-for-gestation age,large-for-gestation age,very low birth weight,low birth weight and macrosomia.The second outcomes were pregnancy and perinatal complications.The relationship between EMT and adverse neonatal outcomes was estimated by Logistic regression analysis.Results The rate of ectopic pregnancy was increased significantly in group A.No significant differences were found among the three groups in gestation age,birth weight,birth weight z-score,PTB,small for gestation age,large for gestation age,low birth weight,very low birth weight and macrosomia.Compared with group B,the odds of adverse neonatal outcomes did not show significant differences before and after adjustment in both group A and group C by Logistic regression analysis.Conclusion Thinner EMT in fresh cleavage embryos transfer is associated with higher rate of ectopic pregnancy,while it is not independently associated with adverse perinatal outcomes.

Objective To investigate the association of endometrial thickness(EMT)with obstetric and neonatal outcomes of monoparous pregnancy in fresh cleavage embryos transfer.Methods A total of 1 845 patients of monoparous pregnancy after fresh cleavage embryos transfer cycles from Jan 2016 to Mar 2022 at Shanghai First Maternity and Infant Hospital,Tongji Universtiy were analyzed retrospectively.Patients were categorized into three groups by EMT on transferation day:≤8 mm(group A),8-14 mm(group B)and≥14 mm(group C).The primary outcomes were preterm birth(PTB),birth weight and birth weight z-score,small-for-gestation age,large-for-gestation age,very low birth weight,low birth weight and macrosomia.The second outcomes were pregnancy and perinatal complications.The relationship between EMT and adverse neonatal outcomes was estimated by Logistic regression analysis.Results The rate of ectopic pregnancy was increased significantly in group A.No significant differences were found among the three groups in gestation age,birth weight,birth weight z-score,PTB,small for gestation age,large for gestation age,low birth weight,very low birth weight and macrosomia.Compared with group B,the odds of adverse neonatal outcomes did not show significant differences before and after adjustment in both group A and group C by Logistic regression analysis.Conclusion Thinner EMT in fresh cleavage embryos transfer is associated with higher rate of ectopic pregnancy,while it is not independently associated with adverse perinatal outcomes.

AIM To study the chemical constituents from the buds of Aralia chinensis L.var.nuda Nakai and their in vitro anti-inflammatory activities.METHODS The 70％ethanol extract from the buds of A.chinensis var.nuda was isolated and purified by silica gel,Sephadex LH-20,ODS and semi-preparative HPLC,then the structures of compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities in vitro were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as 4-(2,2-dibutoxyethyl)phenol(1),trans-linalool-3,7-oxide-6-O-β-D-glucopyranoside(2),2'-O-(9Z,12Z,15Z-octadecatrienoyl)glyceryl β-D-galactopyranoside(3),quercetin-3-O-β-D-glucopyranoside(3'→ O-3''')quercetin-3-O-β-D-galactopyranoside(4),syringaresinol-4'-O-β-D-glucopyranoside(5),p-hydroxybenzaldehyde(6),7α-hydroxystigmasterol 3-O-β-D-glucopyranoside(7),trans-p-hydroxy cinnamic acid methyl ester(8),funingensin A(9),3,4-dihydroxy-acetophenone(10),N-acetyltyramine(11),3,4-di-O-caffeoyl quinic acid(12),chlorogenic acid(13),aralia cerebroside(14),caffeic acid methyl ester(15),tetradecanoic acid(16).The IC50values of compounds 8,10,12 and 13 were(22.19±1.59),(35.25±1.30),(13.38±0.72),(15.73±1.16)μmol/L,respectively.CONCLUSION Compound 1 is a new compound,2-13 are isolated from genus Aralia for the first time.Compounds 8,10,12,13 exhibit significant in vitro anti-inflammatory activities.

Objective To compare the effects of 20 mg qd and 10 mg bidadministration of iprrazole enteric-coated tablets on the control of gastric acid in healthy subjects.Methods A randomized,single-center,parallel controlled trial was designed to include 8 healthy subjects.Randomly divided into 2 groups,20 mg qd administration group:20 mg enteric-coated tablets of iprrazole in the morning;10 mg bid administration group:10 mg enteric-coated tablets of iprrazole in the morning and 10 mg in the evening.The pH values in the stomach of the subjects before and 24 h after administration were monitored by pH meter.The plasma concentration of iprazole after administration was determined by HPLC-MS/MS.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin(V8.0)software.Results The PK parameters of iprrazole enteric-coated tablets and reference preparations in fasting group were as follows:The Cmax of 20 mg qd group and 10 mg bid group were(595.75±131.15)and(283.50±96.98)ng·mL-1;AUC0-t were(5 531.94±784.35)and(4 686.67±898.23)h·ng·mL-1;AUC0-∞ were(6 003.19±538.59)and(7 361.48±1 816.77)h·ng·mL-1,respectively.The mean time percentage of gastric pH＞3 after 20 mg qd and 10 mg bid were 82.64％and 61.92％,and the median gastric pH within 24 h were 6.25±1.49 and 3.53±2.05,respectively.The mean gastric pH values within 24 h were 5.71±1.36 and 4.23±1.45,respectively.The correlation analysis of pharmacokinetic/pharmacodynamics showed that there was no significant correlation between the peak concentration of drug in plasma and the inhibitory effect of acid.Conclusion Compared with the 20 mg qd group and the 10 mg bid group,the acid inhibition effect is better,the administration times are less,and the safety of the two administration regimes is good.

Tranexamic acid is widely used in joint orthopedic surgery.At the same time,it has high safety and few adverse drug reactions.It can effectively improve intraoperative bleeding and promote early functional recovery of patients.This article reviews the mode of administration,safe dose,administration time and adverse drug reactions of tranexamic acid in the perioperative period of joint replacement and arthroscopic surgery,in order to provide reference for the clinical application of tranexamic acid.