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.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

Human cytomegalovirus (HCMV) poses a significant risk of neural damage during pregnancy. As the most prevalent intrauterine infectious agent in low- and middle-income countries, HCMV disrupts the development of neural stem cells, leading to fetal malformations and abnormal structural and physiological functions in the fetal brain. This review summarizes the current understanding of how HCMV infection dysregulates the Wnt signaling pathway to induce fetal malformations and discusses current management strategies.
Humans ; Cytomegalovirus Infections/virology* ; Wnt Signaling Pathway ; Pregnancy ; Female ; Cytomegalovirus/physiology* ; Pregnancy Complications, Infectious/virology* ; Congenital Abnormalities/virology* ; Animals

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

Aim To explore whether platelet-derived growth factor C(PDGFC)derived from cancer-associat-ed fibroblasts(CAFs)can promote resistance of breast cancer cells to doxorubicin(DOX)and the underlying mechanisms.Methods CAFs and normal fibroblasts(NFs)were extracted from freshly resected breast cancer tissue and adjacent normal breast tissue respec-tively.Conditioned medium(CM)from CAFs and NFs was collected and co-cultured with breast cancer cells.Cell proliferation and toxicity were assessed using a Cell Counting Kit-8(CCK-8).The expression of PDG-FC in CAFs,NFs and corresponding CM was detected by Western blot and ELISA respectively.The influence of CAFs-CM on intracellular doxorubicin content in breast cancer cells was observed by fluorescence mi-croscopy.The impact of CAFs-CM on apoptosis-related proteins BAX and BCL2 was predicted and valifated u-sing the Starbase database and Western blot.The changes in ROS levels,mitochondrial membrane po-tential,and mitochondrial membrane proteins TOM20 and COX Ⅳ in breast cancer cells were measured using DCFH-DA fluorescence staining,JC-1 assay,and Western blot.Results CAFs-CM decreased the intra-cellular doxorubicin content and inhibited the sensitivi-ty of breast cancer cells to doxorubicin.Additionally,the expression of apoptosis protein BAX decreased while the anti-apoptotic protein BCL2 increased in breast cancer cells cultured with CAFs-CM.Further-more,CAFs-CM led to decreased ROS levels and in-creased mitochondrial membrane potential in breast cancer cells accompanied with elevated expression of mitochondrial membrane proteins TOM20 and COX Ⅳ.Further study found that PDGEF was highly expressed in CAFs and CAFs-CM,recombinant human PDGFC produced resistance of breast cancer cells to DOX simi-lar to CAFs-CM,and the specific inhibitors of PDGFRα significantly inhibited CAFs-CM.Further mechanistic studies revealed that PDGFC in CAFs-CM induced chemoresistance by activating PI3K-mTOR signaling pathway.Conclusion PDGFC secreted by CAFs promotes doxorubicin resistance in breast cancer cells through PI3K-mTOR signaling pathway,which provides a new perspective for the development of anti-cancer drugs targeting CAFs.

Liquid chromatography-mass spectrometry was employed to analyze the chemical components in Curcuma longa tuberous roots(HSYJ), C. longa tuberous roots processed with vinegar(CHSYJ), and rat serum after the administration. The active components of HSYJ and CHSYJ absorbed in serum were identified based on the secondary spectrum of database and literature. The targets of primary dysmenorrhea was screened out from database. The protein-protein interaction network analysis, gene ontology(GO) functional annotation, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed for the common targets shared by the drug active components in serum and primary dysmenorrhea, and the component-target-pathway network was constructed. AutoDock was used to conduct molecular docking between the core components and targets. A total of 44 chemical components were identified from HSYJ and CHSYJ, including 18 absorbed in serum. On the basis of network pharmacology, we identified 8 core components(including procurcumenol, isobutyl p-hydroxybenzoate, ferulic acid, and zedoarondiol) and 10 core targets \[including interleukin-6(IL-6), estrogen receptor 1(ESR1), and prostaglandin-endoperoxide synthase 2(PTGS2)\]. The core targets were mainly distributed in the heart, liver, uterus, and smooth muscle. The molecular docking results showed that the core components were well bound to the core targets, indicating that HSYJ and CHSYJ may exert therapeutic effect on primary dysmenorrhea via estrogen, ovarian steroidogenesis, tumor necrosis factor(TNF), hypoxia-inducible factor-1(HIF-1), IL-17 and other signaling pathways. This study clarifies the HSYJ and CHSYJ components absorbed in serum, as well as the corresponding mechanism, providing a reference for further elucidating the therapeutic material basis and clinical application of HSYJ and CHSYJ.
Female ; Humans ; Animals ; Rats ; Acetic Acid ; Curcuma ; Dysmenorrhea ; Molecular Docking Simulation ; Tumor Necrosis Factor-alpha ; Cyclooxygenase 2

Objective: To investigate the response characteristics of patients with locally advanced/metastatic non-squamous non-small cell lung cancer (nsq-NSCLC) treated with tislelizumab in combination with chemotherapy in the first line. Methods: Patients with nsq-NSCLC who achieved complete or partial remission after treatment with tislelizumab in combination with chemotherapy or chemotherapy alone in the RATIONALE 304 study, as assessed by an independent review board, were selected to analyze the response characteristics and safety profile of the responders. Time to response (TTR) was defined as the time from randomization to the achievement of first objective response. Depth of response (DpR) was defined as the maximum percentage of tumor shrinkage compared with the sum of the baseline target lesion length diameters. Results: As of January 23, 2020, 128 patients treated with tislelizumab in combination with chemotherapy achieved objective tumor response (responders), representing 57.4%(128/223) of the intention-to-treat population, with a TTR of 5.1 to 33.3 weeks and a median TTR of 7.9 weeks. Of the responders (128), 50.8%(65) achieved first remission at the first efficacy assessment (week 6), 31.3%(40) at the second efficacy assessment (week 12), and 18.0%(23) at the third and subsequent tumor assessments. The percentages of responders who achieved a depth of tumor response of 30% to <50%, 50% to <70% and 70% to 100% were 45.3%(58/128), 28.1%(36/128) and 26.6%(34/128), respectively, with median progression-free survival (PFS) of 9.0 months (95% CI: 7.7 to 9.9 months), 11.5 months (95% CI: 7.7 months to not reached) and not reached (95% CI: 11.8 months to not estimable), respectively. Tislelizumab plus chemotherapy were generally well tolerated in responders with similar safety profile to the overall safety population. Conclusion: Among responders to tislelizumab in combination with chemotherapy for nsq-NSCLC, 82.0%(105/128) achieves response within the first two tumor assessments (12 weeks) and 18.0%(23/128) achieves response at later (18 to 33 weeks) assessments, and there is a trend toward prolonged PFS in responders with deeper tumor response.
Humans ; Antibodies, Monoclonal, Humanized/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/adverse effects* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/pathology* ; Treatment Outcome