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:To investigate the effect of triglyceride-glucose(TyG) index and alkaline phosphatase(ALP) on brachial-ankle pulse wave conduction velocity(baPWV) in postmenopausal women.Methods:A cross-sectional study was conducted, enrolling 3 483 postmenopausal women who underwent health checkup at Taihu Sanatorium in Jiangsu Province from March 2020 to June 2021. The physical activity, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, triglycerides, high-density lipoprotein-cholesterol(HDL-C), low-density lipoprotein-cholesterol(LDL-C), ALP, and baPWV were collected.Results:Age, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, and LDL-C levels were significantly lower in the normal baPWV group( n=1 971) than those in the elevated baPWV group( n=1 512; P<0.001). Logistic regression identified the TyG index( OR=1.75) and ALP level( OR=1.20) as independent risk factors for elevated baPWV( P<0.001), besides with age, body mass index, systolic blood pressure, diastolic blood pressure, and regular exercise. Individuals with both high TyG index and elevated ALP had a 2.51-fold higher risk of elevated baPWV(95% CI 2.01-3.14). Adjusted interaction measures(including age, body mass index, systolic blood pressure, diastolic blood pressure, and regular exercise) showed RERI=2.825(95% CI 1.255-3.905), AP=0.348(95% CI 0.180-0.875), and SI=1.657(95% CI 0.628-3.374). Conclusions:The TyG index and ALP levels are independent risk factors for elevated baPWV in postmenopausal women and exhibit an additive interaction effect on arterial stiffness in this population.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Bovine rotavirus(BRV)is an important pathogen causing diarrhea in calves.To understand the genomic charac-teristics and genetic variations in bovine rotavirus,and to further enrich data on the biological characteristics of rotavirus,we aimed to amplify 11 gene segments of the isolated and cultured G6P[1]bovine rotavirus BLL strain,perform whole genome se-quencing,and analyze the molecular characteristics.MEGA7.0 and DNAMAN software were used for homology and typing a-nalysis,and the whole genome phylogenetic tree was constructed to analyze genetic evolution relationships.The complete geno-type of the BLL strain was G6-P[1]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis of the VP7 and VP4 genes of the BLL strain showed that the VP7 gene had the highest homology with RVA/Cow-wt/HB01/China/2021,and the VP4 gene of the BLL strain was in the same branch as RVA/Human-tc/ISR/Ro8059/1995.From the sequence alignment of VP8*amino acids,the sialic acid domain of the BLL strain was found to be similar to that in other P[1]strains,but different from those in other types of strains,except for residue 189,which was the same as that in Ro8059 but different from that in other strains.The results suggested that the BLL strain might potentially infect humans.Therefore,continued monitoring and study of the biological characteristics of this strain are necessary to provide more information and evidence supporting further research on the cross-species transmission of group A rotavirus in China.

Cytokeratin 19 fragment antigen 21-1(CYFRA21-1)is a new biomarker which has received much attention in recent years for cancer screening,and has shown great potentials for screening and diagnosis of various cancers,especially non-small cell lung cancer.CYFRA21-1 level in human serum has important clinical significance in the diagnosis,prognosis and treatment of lung cancer.Recently,a variety of detection techniques have been established to effectively enrich the detection technology system of CYFRA21-1,such as enzyme-linked immunosorbent assay,chemiluminescence,fluorescence,immunochromatography,electrochemical method,and surface enhanced Raman spectroscopy,etc.These techniques provide technical support for early diagnosis of lung cancer.However,the research progress of CYFRA21-1 detection methods is rarely reported.In this paper,CYFRA21-1 and its clinical significance were briefly introduced,and the progress of detection technology in recent ten years was reviewed,which was expected to provide reference for developing more sensitive,accurate,fast and convenient detection methods.

Objective To verify the efficacy of a domestic human DNA quantification kit based on real-time fluorescence quantitative PCR in detecting the total human DNA concentration,male DNA concen-tration in mixed male/female DNA samples,the degree of DNA degradation and inhibitor tolerance.Methods Samples with different concentrations,different male/female ratios,different concentrations of inhibitors,and different degradation degrees were tested using the domestic human DNA quantification kit based on real-time fluorescence quantitative PCR.This kit was compared with a similar product on the market and was applied to the detection of DNA from real cases.Results This human DNA quan-tification kit can effectively detect human DNA as low as 0.001 65 ng/μL,and 6.25 pg/μL of male DNA in mixed samples with a male-to-female ratio of 1∶15 000.Even when the sample contains as high as 400 ng/μL of humic acid or 1 000 μmol/L of hemin alone,the DNA concentration can still be accurately detected.The degradation index can effectively characterize the degradation degree of the sample.This kit has been successfully applied in forensic practice.Conclusion This human DNA quan-tification kit is accurate and reliable in detection.It can accurately reflect the degradation of DNA and inhibitor tolerance.It has good performance in quantitative accuracy,determination of the male/female ratio in mixed samples,and inhibitor tolerance.It has application potential in forensic case examination.

Objective:To investigate the effect of triglyceride-glucose(TyG) index and alkaline phosphatase(ALP) on brachial-ankle pulse wave conduction velocity(baPWV) in postmenopausal women.Methods:A cross-sectional study was conducted, enrolling 3 483 postmenopausal women who underwent health checkup at Taihu Sanatorium in Jiangsu Province from March 2020 to June 2021. The physical activity, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, triglycerides, high-density lipoprotein-cholesterol(HDL-C), low-density lipoprotein-cholesterol(LDL-C), ALP, and baPWV were collected.Results:Age, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, and LDL-C levels were significantly lower in the normal baPWV group( n=1 971) than those in the elevated baPWV group( n=1 512; P<0.001). Logistic regression identified the TyG index( OR=1.75) and ALP level( OR=1.20) as independent risk factors for elevated baPWV( P<0.001), besides with age, body mass index, systolic blood pressure, diastolic blood pressure, and regular exercise. Individuals with both high TyG index and elevated ALP had a 2.51-fold higher risk of elevated baPWV(95% CI 2.01-3.14). Adjusted interaction measures(including age, body mass index, systolic blood pressure, diastolic blood pressure, and regular exercise) showed RERI=2.825(95% CI 1.255-3.905), AP=0.348(95% CI 0.180-0.875), and SI=1.657(95% CI 0.628-3.374). Conclusions:The TyG index and ALP levels are independent risk factors for elevated baPWV in postmenopausal women and exhibit an additive interaction effect on arterial stiffness in this population.

BACKGROUND: Angiotensin receptor neprilysin inhibitors (ARNIs), angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers (BBs), and mineralocorticoid receptor antagonists (MRAs) are the cornerstones in treating heart failure with reduced ejection fraction (HFrEF). Sodium-glucose cotransporter 2 inhibitors (SGLT-2is) are included in HFrEF treatment guidelines. However, the effect of SGLT-2i and the five drugs on HFrEF have not yet been systematically evaluated. METHODS: PubMed, Embase, and the Cochrane Library were searched for randomized controlled trials (RCTs) from inception dates to September 23, 2022. Additional trials from previous relevant reviews and references were also included. The primary outcomes were changes in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter/dimension (LVEDD), left ventricular end-systolic diameter/dimension (LVESD), left ventricular end-diastolic volume (LVEDV), and left ventricular end-systolic volume (LVESV), left ventricular end-systolic volume index (LVESVI), and left ventricular end-diastolic volume index (LVEDVI). Secondary outcomes were New York Heart Association (NYHA) class, 6-min walking distance (6MWD), B-type natriuretic peptide (BNP) level, and N-terminal pro-BNP (NT-proBNP) level. The effect sizes were presented as the mean difference (MD) with 95% confidence interval (CI). RESULTS: We included 68 RCTs involving 16,425 patients. Compared with placebo, ARNI + BB + MRA + SGLT-2i was the most effective combination to improve LVEF (15.63%, 95% CI: 9.91% to 21.68%). ARNI + BB + MRA + SGLT-2i (5.83%, 95% CI: 0.53% to 11.14%) and ARNI + BB + MRA (3.83%, 95% CI: 0.72% to 6.90%) were superior to the traditional golden triangle ACEI + BB + MRA in improving LVEF. ACEI + BB + MRA + SGLT-2i was better than ACEI + BB + MRA (-8.05 mL/m 2 , 95% CI: -14.88 to -1.23 mL/m 2 ) and ACEI + BB + SGLT-2i (-18.94 mL/m 2 , 95% CI: -36.97 to -0.61 mL/m 2 ) in improving LVEDVI. ACEI + BB + MRA + SGLT-2i (-3254.21 pg/mL, 95% CI: -6242.19 to -560.47 pg/mL) was superior to ARB + BB + MRA in reducing NT-proBNP. CONCLUSIONS: Adding SGLT-2i to ARNI/ACEI + BB + MRA is beneficial for reversing cardiac remodeling. The new quadruple drug "ARNI + BB + MRA + SGLT-2i" is superior to the golden triangle "ACEI + BB + MRA" in improving LVEF. REGISTRATION PROSPERO; No. CRD42022354792.
Humans ; Heart Failure/physiopathology* ; Stroke Volume/physiology* ; Angiotensin Receptor Antagonists/therapeutic use* ; Angiotensin-Converting Enzyme Inhibitors/therapeutic use* ; Sodium-Glucose Transporter 2 Inhibitors/therapeutic use* ; Randomized Controlled Trials as Topic ; Mineralocorticoid Receptor Antagonists/therapeutic use* ; Adrenergic beta-Antagonists/therapeutic use*

This study aims to investigate the effects and mechanisms of the effective-compounds of Jinshui Huanxian formula (ECC-JHF) in improving pulmonary fibrosis. Animal experiments were approved by the Ethics Committee of the Animal Experiment Center of Henan University of Chinese Medicine (approval number: IACUC-202306012). The mouse model of pulmonary fibrosis was induced using bleomycin (BLM). Hematoxylin-eosin (H&E) staining was used to detect the histopathological changes of lung tissues. Masson staining was used to assess the degree of fibrosis in lung tissues. Immunofluorescence (IF) and real-time quantitative PCR (qPCR) were performed to measure the expression of collagen type I (COL I), α-smooth muscle actin (α-SMA), fibronectin (FN), interleukin (IL)-1β, IL-6, and tumor necrosis factor α (TNF-α) in lung tissues. Flow cytometry (FCM) was employed to detect the proportion of M1 and M2 macrophages in the bronchoalveolar lavage fluid (BALF) of mice. IF and qPCR were also used to detect the expression of lipase family member N (LIPN) in lung tissues. Free fatty acid assay kit was used to detect the level of free fatty acids in lung tissue. Bone marrow-derived macrophages (BMDMs) were treated with interleukin-4 (IL-4) to induce M2 polarization. FCM was used to measure the proportion of CD206⁺ M2 macrophages. IF was utilized to detect LIPN expression and lipid droplet decomposition. The results showed that in BLM-induced pulmonary fibrosis mice, ECC-JHF significantly attenuated BLM-induced alveolar inflammation and collagen deposition, inhibited fibroblast activation in lung tissues, and decreased the proportion of M2 macrophages in BALF. It also significantly suppressed LIPN expression and free fatty acid level in lung tissues. In the IL-4 induced BMDMs M2 polarization model, ECC-JHF significantly inhibited the proportion of CD206⁺ M2 macrophages, down-regulated the expression of LIPN, and blocked lipid droplet catabolism. These results suggest that ECC-JHF may alleviate bleomycin-induced pulmonary fibrosis by inhibiting lipid droplet decomposition and M2 macrophage polarization.

Bovine rotavirus(BRV)is an important pathogen causing diarrhea in calves.To understand the genomic charac-teristics and genetic variations in bovine rotavirus,and to further enrich data on the biological characteristics of rotavirus,we aimed to amplify 11 gene segments of the isolated and cultured G6P[1]bovine rotavirus BLL strain,perform whole genome se-quencing,and analyze the molecular characteristics.MEGA7.0 and DNAMAN software were used for homology and typing a-nalysis,and the whole genome phylogenetic tree was constructed to analyze genetic evolution relationships.The complete geno-type of the BLL strain was G6-P[1]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis of the VP7 and VP4 genes of the BLL strain showed that the VP7 gene had the highest homology with RVA/Cow-wt/HB01/China/2021,and the VP4 gene of the BLL strain was in the same branch as RVA/Human-tc/ISR/Ro8059/1995.From the sequence alignment of VP8*amino acids,the sialic acid domain of the BLL strain was found to be similar to that in other P[1]strains,but different from those in other types of strains,except for residue 189,which was the same as that in Ro8059 but different from that in other strains.The results suggested that the BLL strain might potentially infect humans.Therefore,continued monitoring and study of the biological characteristics of this strain are necessary to provide more information and evidence supporting further research on the cross-species transmission of group A rotavirus in China.