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.

Background::The prevalence of type 2 diabetes mellitus (T2DM) has been rapidly growing in Chinese populations in recent decades, and the shift in eating habits is a key contributing factor to this increase. Eating out of home (EOH) is one of the major shifts in eating habits during this period. However, the influence of EOH on the incidence of T2DM among Chinese urban workers is unknown.Methods::The cross-sectional study involved an analysis of 13,904 urban workers recruited from 11 health examination centers in the major cities of China to explore the relationship between EOH and T2DM between 2013 September and 2016 March.Results::Average weekly EOH frequency ≥10 times was positively associated with increased incidence of T2DM in the sampled population (OR: 1.31 [1.11-1.54], p < 0.01), most notably in participants ≤45 years old (OR: 1.41[1.11-1.80], p < 0.01]) and in males (OR:1.26 [1.06-1.51], p < 0.01). An EOH frequency of 5 times/week appears as a threshold for a significant increase in the odds of T2DM. Weekly EOH frequency ≥5 times was associated with increased odds of T2DM in a dose-response manner in the total population and almost all subgroups ( poverall association < 0.05 and pnonlinearity ≤ 0.05). Conclusion::This study showed that a frequency of EOH (≥5 times/week) was associated with a frequency-dependent increase in the odds of T2DM urban workers in China. More nutrition promotion is needed to improve the eating behavior of Chinese urban workers to reduce T2DM risk.

Objective To explore the mechanism of malt alcohol extract improving depression-like behavior induced by CUMS in rats by regulating gut microbiota.Methods The depression model of rats was established using an 8-weeks CUMS procedure,and the administration group was given low(59.6 mg·kg-1)and high(178.8 mg·kg-1)doses of malt alcohol extract,respectively.The depression-like behavior of rats was evaluated by classic behavioral test.The composition of intestinal microbiota of rats was analyzed by 16S rRNA sequencing.The morphological changes of colon were observed by hematoxylin and eosin(HE),the expression of ZO-1 and Occludin in colon was detected by immunofluorescence(IF),and the expression of IL-10,IL-1βand 5-HT were detected by ELISA.Results The low dose of malt alcohol extract attenuated the depressive behavior and restored the expression of 5-HT in the brain of CUMS rats.16S rRNA sequencing results showed that the diversity and relative abundance of gut microbiota changed after treatment with the low dose of malt alcohol extract.ELISA results showed that the low dose of malt alcohol extract significantly reversed the CUMS-induced reduction of IL-10 and elevation of IL-1 β.HE results showed that the low dose of malt alcohol extract significantly ameliorated CUMS-induced structural damage in colon.IF results showed increased protain expression of intestinal epithelial barrier tight junction proteins ZO-1 and Occludin by the low dose of malt alcohol extract.Conclusion The low dose of malt alcohol extract can ameliorate CUMS-induced depressive-like behavior in rats by modulating intestinal flora,restoring 5-HT expression in the brain,inhibiting inflammation,and repairing the intestinal barrier.

Epilepsy is a chronic neurological disorder caused by an imbalance between excitation and inhibition in the central nervous system.Recently,the role of the orexin system in the pathogenesis of epilepsy has garnered significant attention.Orex-in primarily regulates arousal states and enhances neuronal excit-ability through activation of OX1-R/OX2-R receptors.Studies have shown that elevated orexin levels lower the seizure thresh-old,while orexin receptor antagonists(ORAs)exhibit potential antiepileptic effects.ORAs suppress epileptiform discharges by reducing glutamate release,enhancing GABAergic inhibitory effects,and modulating the thalamocortical circuit.Animal ex-periments and preliminary clinical studies demonstrate that OX1R antagonists decrease excitatory synaptic transmission,whereas OX2 R antagonists primarily strengthen GABA-mediated inhibition.With the widespread application of ORAs in sleep disorders,exploring their clinical value as antiepileptic drugs will become a key focus for future research.This review summa-rizes the role of the orexin system in epileptogenesis and discus-ses the research progress and future directions of ORAs as poten-tial antiepileptic agents.

Objective Focusing on the problems of unbalanced nursing education resources and insufficient training,it discusses the path of nursing echelon training and nursing education resources optimization in secondary hospitals.Methods Based on nursing questionnaire,interview data and platform logs from 4 secondary hospitals in Hainan Province,Latent Dirichlet Allocation topic modeling,sentiment analysis and Social Network Analysis were used.Identify the core problems of educational resources and training system and propose optimization schemes.Results Topic modeling revealed that insufficient educational resources and information silos were major obstacles to shared platform development.Similarity analysis result showed high consistency in feedback regarding disconnected training content and single training models.Sentiment analysis result indicated that 50％of negative feedback focused on inadequate evaluation and incentive mechanisms.Social Network Analysis validated the significant role of multi-node collaboration in optimizing resource flows.Conclusion Building shared platforms,implementing differentiated training systems,and developing localized nursing faculty are critical pathways to achieving homogenized nursing education,providing valuable references for optimizing regional nursing education.

Objective:To investigate the technical application pathways of artificial intelligence(AI)in laboratory information management systems(LIMS)and its role in promoting laboratory management efficiency and intelli-gence.Methods:Through the integration of traditional AI technologies(e.g.,machine learning,computer vision)with large language models,this study demonstrated the application of various AI technologies in scenarios such as intelligent Q&A for local knowledge bases,comprehensive review of inspection processes,intelligent data visualization,and image recognition.Results:Through the implementation of AI applications in laboratory settings,AI significantly enhanced management efficiency:the intelligent Q&A system achieved over 90％accuracy,auto-mated inspection processes reduced manual workload by 40％,and image recognition precision reached 89％-100％.Conclusion:AI provides efficient and precise solutions for laboratory management via multimodal integration and process optimization.Future efforts should focus on strengthening data security and model interpret-ability to promote comprehensive intelligent development.

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.

Objective:To investigate the technical application pathways of artificial intelligence(AI)in laboratory information management systems(LIMS)and its role in promoting laboratory management efficiency and intelli-gence.Methods:Through the integration of traditional AI technologies(e.g.,machine learning,computer vision)with large language models,this study demonstrated the application of various AI technologies in scenarios such as intelligent Q&A for local knowledge bases,comprehensive review of inspection processes,intelligent data visualization,and image recognition.Results:Through the implementation of AI applications in laboratory settings,AI significantly enhanced management efficiency:the intelligent Q&A system achieved over 90％accuracy,auto-mated inspection processes reduced manual workload by 40％,and image recognition precision reached 89％-100％.Conclusion:AI provides efficient and precise solutions for laboratory management via multimodal integration and process optimization.Future efforts should focus on strengthening data security and model interpret-ability to promote comprehensive intelligent development.

Background::The prevalence of type 2 diabetes mellitus (T2DM) has been rapidly growing in Chinese populations in recent decades, and the shift in eating habits is a key contributing factor to this increase. Eating out of home (EOH) is one of the major shifts in eating habits during this period. However, the influence of EOH on the incidence of T2DM among Chinese urban workers is unknown.Methods::The cross-sectional study involved an analysis of 13,904 urban workers recruited from 11 health examination centers in the major cities of China to explore the relationship between EOH and T2DM between 2013 September and 2016 March.Results::Average weekly EOH frequency ≥10 times was positively associated with increased incidence of T2DM in the sampled population (OR: 1.31 [1.11-1.54], p < 0.01), most notably in participants ≤45 years old (OR: 1.41[1.11-1.80], p < 0.01]) and in males (OR:1.26 [1.06-1.51], p < 0.01). An EOH frequency of 5 times/week appears as a threshold for a significant increase in the odds of T2DM. Weekly EOH frequency ≥5 times was associated with increased odds of T2DM in a dose-response manner in the total population and almost all subgroups ( poverall association < 0.05 and pnonlinearity ≤ 0.05). Conclusion::This study showed that a frequency of EOH (≥5 times/week) was associated with a frequency-dependent increase in the odds of T2DM urban workers in China. More nutrition promotion is needed to improve the eating behavior of Chinese urban workers to reduce T2DM risk.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.