Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

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.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Risks of food safety induced by small molecule drug residues in animal food and environment have become an increasing public concern,so it is necessary to develop highly sensitive and easy-to-operate techniques to detect small molecules.Herein,a metasurface plasma resonance(MetaSPR)sensor chip coupled with gold nanoparticles(AuNPs)was developed for detection of enrofloxacin(ENR)based on competitive immunoassay.The detection range of the sensor for ENR was 0.025-3.2 ng/mL,and the detection limit(3σ)was 20 pg/mL.The biosensor showed excellent performance including high selectivity,good stability,ease to operate and high throughput,etc.The developed method was applied to detection of ENR residues in real samples,with recoveies of 96.0% -105.0%.The proposed sensing strategy provided new technique reference for detection of other small molecules in the field of residue analysis in food safety and environment monitoring.

Objective To establish the reference interval of urine Alzheimer-associated neuronal thread protein(AD7c-NTP)for healthy adults in Mianyang area using the indirect method.Methods The detection results of urine AD7c-NTP from 5 093 healthy in-dividuals were collected from the information management database of Medical Laboratory Department of Sichuan Science City Hospital from March 2017 to March 2022.Skewness-kurtosis and Kolmogorov-Smirnov tests were used to determine whether the data followed a normal distribution.After removing outliers using the Box Plots method,the enrolled subjects were grouped by gender and age.The Mann-Whitney U or Kruska-Wallis H tests were used to analyze the between-group differences of urine AD7c-NTP in healthy individu-als with different genders and ages.The adjacent age groups without statistically significant difference(P＞0.05)were combined,and the indirect method(non-parametric test method)was used to calculate the reference intervals for different gender and age groups.Results Skewness-kurtosis and Kolmogorov-Smirnov tests showed that the data followed a non-normal distribution.After removing 293 outliers using the Box Plots method,a total of 4 800 subjects,including 3 199 males and 1 601 females,were enrolled.The enrolled subjects were grouped by gender and age,and the non-parametric test method were used to establish the reference intervals of urine AD7c-NTP in healthy populations with different genders.The Mann-Whitney U test confirmed that urine AD7c-NTP levels existed gen-der differences(Z=14.09,P＜0.01),and the reference intervals for males and females were≤1.10 ng/mL and≤1.40 ng/mL,re-spectively.There were also statistical differences in urine AD7c-NTP levels among different age groups of the same gender.After combi-ning adjacent age groups without statistically significant difference(P＞0.05),the reference intervals of urine AD7c-NTP in healthy populations with different genders and ages were established by the non-parametric test method,which were≤1.00 ng/mL for male 20-39 years old group,≤1.10 ng/mL for male 40-79 years old group,≤1.60 ng/mL for male≥80 years old group,≤1.30 ng/mL for female 20-69 years old group,and≤1.60 ng/mL for female≥70 years old group,respectively.The established reference intervals of urine AD7c-NTP were further verified by healthy individuals,and the results met the standards.Conclusion The reference intervals of urine AD7c-NTP in healthy populations with different genders and ages in Mianyang area are established successfully using the indi-rect method,which may help to predict the risk of Alzheimer's disease in clinical practice and provide support for the diagnosis and treatment of the disease.

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.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective:To investigate the effect of Tongguan Fang drug-containing serum on LPS-induced inflammation of RAW264.7 cells,so as to clarify the cellular mechanism of the Tongguan Fang in treating tubal inflammatory infertility.Methods:Lipo-polysaccharide(LPS)was used to stimulate the RAW264.7 macrophage cell line as an in vitro model,Detected levels of cellular oxida-tive stress(ROS),apoptosis and expressions of PI3K/Akt signaling pathway proteins.CCK-8 was used to detect effect of Tongguan Fang drug-containing serum on cellular inflammation.Effects of Tongguan Fang-containing serum on cell inflammation were assessed using CCK-8 assay.Cells were divided into control group,LPS-induced inflammation model group,and Tongguan Fang-containing serum-treated LPS-induced inflammation model groups of different concentrations.qPCR was performed to detect mRNA expression levels of IL-1β,IL-6 and TNF-α in different groups.Immunofluorescence and Western blot were used to evaluate phosphorylation levels of the PI3K/Akt signaling pathway and protein levels of Bcl-2,Bax and caspase-3 of apoptotic.Hoechst 33342/PI staining and flow cytometry were employed to assess the impact of Tongguan Fang-containing serum on cell apoptosis.DCFH-DA probe was used to measure cellular ROS levels affected by Tongguan Fang-containing serum.Results:①Tongguan Fang-containing serum reduced LPS-induced cellular injury in a dose-dependent manner;②Tongguan Fang-containing serum decreased production of pro-inflammatory cytokines IL-6,IL-1β and TNF-α induced by LPS;③Tongguan Fang-containing serum reduced intracellular ROS generation induced by LPS;④Pre-treatment with Tongguan Fang-containing serum activated PI3K/Akt signaling pathway;⑤Tongguan Fang-containing serum promoted cell apoptosis.Conclusion:Treatment with Tongguan Fang-containing serum can reduce cellular injury and inflam-mation,protect cells from LPS-induced cellular injury by activating the PI3K/Akt signaling pathway and promoting cell apoptosis,and further alleviate cellular inflammation levels.

Objective To investigate the effect of epifriedelanol(Epi)on gene expression of P-glycoprotein(P-gp)in human colorectal adenocarcinoma cell line LS174T and its mechanism.Methods LS174T cells were divided into control group and experimental-L,-M,-H groups.Experimental-L,-M,-H groups were treated with 5,10,20 μmol·L-1 Epi,respectively.Control group was treated with 0.1％dimethyl sulfoxide.Polymerase chain reaction was used to detect the mRNA expression level of P-gp.Theeffect of Epi on multidrug resistance protein 1(MDR1/P-gp)luciferase activity was investigated by pregnane X receptor(PXR)-MDR1/P-gp dual luciferase reporter gene assay.In addition,Western Blot was used to detect the protein expression level of P-gp and the nuclear factor-κB(NF-κB)pathway related proteins.Results The relative expression levels of P-gp mRNA in experimental-M,-H groups and control group were 52.24±5.19,23.00±3.52 and 100.00±9.00;the relative expression levels of P-gp protein were 86.37±9.96,74.85±15.92 and 100.00±12.91;the relative activities P-gp luciferase were 230.19±41.32,203.10±52.84 and 279.67±19.20;the relative expression levels of p65(RelA/p65)in nucleus were 132.36±23.93,145.96±25.15 and 100.00±10.88;the relative expression levels of phosphorylation NF-κB inhibits protein kinase α/β(p-IKKα/β)in cytoplasm were 184.00±54.82,290.10±49.59 and 100.00±15.34;the relative expression levels of phosphorylated NF-κB inhibitory protein α(p-IκBα)in cytoplasm were 125.73±18.77,133.69±20.25 and 100.00±8.12;the relative expression levels of IκBα in cytoplasm were 78.36±14.83,70.44±14.57 and 100.00±22.82,respectively.The above indexes of experimental-M and experimental-H groups were compared with control group,and the differences were statistically significant(P＜0.05,P＜0.01,P＜0.001).Conclusion Epi can down-regulate the gene expression of P-gp in human colorectal adenocarcinoma cell line LS174T,and the mechanism may be related to activation of NF-κB and suppression of PXR.