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 investigate the effects of Shuyu Pills combined with evolimus on the epithelial mesenchymal transformation of triple negative breast cancer cells 4T1 and MDA-MB-231 induced by TGF-β1.METHODS The 4T1 and MDA-MB-231 cells were divided into the blank group and the induction group to induce the epithelial mesenchymal transformation with TGF-β1 cytokine treatment,followed by the assignment into the model group,the Shuyu Pills group,the everolimus group and the Shuyu Pills combined with everolimus group.CCK8 method,plate cloning method,cell scratch test and Transewll test were used to detect the proliferation,cloning formation,migration and invasion ability of the cells whose expressions of E-cadherin,N-cadherin,Vimentin,MMP9,MMP2 and pathway proteins PTEN,PI3K,Akt and mTOR were detected by Western blot.RESULTS Compared with the blank group,the induction group displayed a cell morphological change from epithelioid to stromal,decreased expression of E-cadherin protein(P＜0.01);and increased protein expressions of N-cadherin and Vimentin(P＜0.05).Compared with the model group,each group intervened with the medicine displayed decreased proliferation,clone formation,migration and invasion ability of both kinds of cells(P＜0.01);increased protein expressions of PTEN and E-cadherin(P＜0.05,P＜0.01);and decreased protein expressions of PI3K,Akt,mTOR,N-cadherin,Vimentin,MMP9 and MMP2(P＜0.05,P＜0.01);and more significantly in the Shuyu Pills combined with evolimus group(P＜0.05,P＜0.01).CONCLUSION With a more ideal effect than the single uses in inhibiting the TGF-β1-induced epithelial mesenchymal transformation of triple-negative breast cancer cells,the combination use of Shuyu Pills and everolimus may work through the regulation of PI3K/Akt/mTOR signaling pathway.

AIM To establish a UPLC-MS/MS method for the simultaneouscontent determination of notoginsenosides R1,Fc,Fe,ginsenosides Re,Rg1,Rf,F3,Rg2,Ra2,Rb1,Ro,Rc,F1,Ra1,Rb2,Rb3,Rd,F2,Rg5,chikusetsusaponin Ⅳ a,20(S)-ginsenoside Rg3 and 20(R)-ginsenoside Rg3 in Dengzhan Shengmai Capsules.METHODS The analysis was performed on a 35 ℃ thermostatic Accucore Phenyl Hexyl column(2.1 mm×100 mm,2.6 μm),with the mobile phase comprising of 0.1％formic acid-acetonitrile flowing at 0.4 mL/min in a gradient elution manner,and heated electrospray ionization source was adopted in negative ion scanning with parallel reaction monitoring mode.Subsequently,cluster analysis,principal component analysis and partial least squares discriminant analysis were adopted.RESULTS Twenty-two saponins showed good linear relationships within their own ranges(r ≥ 0.996 4),whose average recoveries were 98.5％-101.6％with the RSDs of 1.3％-5.2％.Ten batches of samples were clustered into four types,three principal components demonstrated the accumulative variance contribution rate of 90.265％,ginsenosides Rb1,Rg2,Rb2,Rd,Rg1,Ro,Rf,Re,Rg5,Rc were taken as potential quality markers.CONCLUSION This simple,efficient,accurate and sensitive method can be used for the quality control of Dengzhan Shengmai Capsules.

Objective:To assess the efficacy and safety of Gongxuening Capsules in reducing post-abortion bleeding following artificial abortion.Methods:A multicenter, randomized, double-blind study was conducted. From May 31, 2022 to March 31, 2023, 484 women who underwent vacuum aspiration abortion for early intrauterine pregnancy were enrolled in 11 centers and randomly assigned to control group and the study group at a 1∶1 ratio using a center-block randomization method. Control group were administered a placebo of Gongxuening Capsules for 9 d, while the study group received the actual Gongxuening Capsules for the same duration. The outcomes measured included vaginal bleeding volume, duration of vaginal bleeding, endometrial thickness, time to menstrual recovery, and complications.Results:1) A total of 484 subjects were enrolled, and 472 completed the study. Totally 450 subjects were included in the efficacy analysis set, with 224 in control group and 226 in the study group; 468 subjects were included in the safety analysis set, with 236 in control group and 232 in the study group. The baseline characteristics of the two groups were comparable (all P>0.05). 2) The vaginal bleeding volume was lower in the study group [(13.30±12.14) mL] than in control group [(19.00±17.67) mL, P<0.001]. The proportion of subjects in the study group with bleeding days less than 4 d [29.65% (67/226)] was higher than that in control group [19.20% (43/224), P=0.010]. 3) No significant differences were observed between the two groups in terms of time to menstrual recovery and endometrial thickness (all P>0.05). 4) In the study group, 3 subjects experienced non-therapeutic-related complications, while 11 subjects in control group. The incidence of complications was lower in the study group [1.29% (3/232)] than in control group [4.66% (11/236), P=0.033]. Conclusion:The administration of Gongxuening Capsules to women following artificial abortion significantly reduced vaginal bleeding volume and was associated with good safety, with the treatment being well-tolerated by the subjects.

Chronic kidney disease(CKD)is a chronic disease characterized by renal structural damage and dysfunction.At present,there is still a lack of effective therapeutic drugs and prevention and treatment methods for CKD in clinical practice.More and more studies have shown that necroptosis,as a new type of programmed cell death,plays a vital role in the onset and progression of CKD.Targeting key molecules in the necroptosis pathway,such as RIPK1,RIPK3 and MLKL,the development of small molecule inhibitors has become an emerging strategy for the treatment of CKD,and has shown significant potential to pro-tect the kidneys and alleviate renal fibrosis in a variety of in vitro and in vivo models.Therefore,this article summarizes the re-search progress of the mechanism of necroptosis in recent years,and focuses on the potential role of necroptosis in the pathogene-sis of CKD and the therapeutic potential of targeting this path-way,providing a new perspective and research direction for the prevention and treatment of CKD in the future.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

The structure of intestinal tissue is complex. In vitro simulation of intestinal structure and function is important for studying intestinal development and diseases. Recently, organoids have been successfully constructed and they have come to play an important role in biomedical research. Organoids are miniaturized three-dimensional (3D) organs, derived from stem cells, which mimic the structure, cell types, and physiological functions of an organ, making them robust models for biomedical research. Intestinal organoids are 3D micro-organs derived from intestinal stem cells or pluripotent stem cells that can successfully simulate the complex structure and function of the intestine, thereby providing a valuable platform for intestinal development and disease research. In this article, we review the latest progress in the construction and application of intestinal organoids.
Organoids/cytology* ; Intestines/physiology* ; Humans ; Animals ; Pluripotent Stem Cells

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.