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For the characteristics of channel instability in wireless sensor networks, this paper proposes an intrusion detection algorithm based on FedAvg (federated averaging) and XGBoost (extreme gradient boosting) wireless sensor networks using fog computing architecture. First, the network edge is extended by introducing fog computing nodes to reduce the communication delay. It reduces the transmission bandwidth and privacy leakage risk while improving the accuracy of jointly learned global and local models. Then, the histogram-based approximation calculation method is improved to adapt to the unbalanced data characteristics of wireless sensor networks. Finally, by introducing TOP-K gradient selection, the number of model parameter uploads is minimized, and the efficiency of model parameter interaction is improved. The experimental results show that this algorithm has superior detection performance and low energy consumption. It is also compared with other algorithms to demonstrate the high detection rate and low computational complexity of this algorithm. [ABSTRACT FROM AUTHOR]

Emerging peroxidase (POD)-like nanozymes have been exploited to construct biosensors towards biomolecular detection. However, the enzymatic activity, sensing mechanism and detection method of the biosensors towards ascorbic acid (AA) analysis are still challenging research topics. Herein, a novel scandium-MOF (Sc-MOF) nanozyme is synthesized via a wet-chemical method. An efficient AA biosensor is developed owing to the POD-like characteristics of the Sc-MOF. The Sc-MOF nanozyme can convert hydrogen peroxide into hydroxyl radicals. Afterwards, colorless 3,3′,5,5′-tetramethylbenzidine (TMB) is converted into blue oxidized TMB by hydroxyl radicals. The Michaelis–Menten constants of the Sc-MOF nanozyme (Km = 0.013 mM for TMB and 0.246 mM for H2O2) are obviously superior to those of horseradish peroxidase. The AA concentration can be determined by putting forward a colorimetric method and an absorbance turn-off mechanism. The linear range of the Sc-MOF based colorimetric method is 0.2–20 μM. The limit of detection is 0.174 μM. The AA detection also demonstrates superior specificity and anti-interference features. Furthermore, the Sc-MOF-based biosensors are applied to qualitative and quantitative AA detection in human serum. The Sc-MOF nanozyme can inspire researchers to develop novel transition metal based biological enzymes and expand their applications in enzymatic biochemical reactions. [ABSTRACT FROM AUTHOR]

Background: Colon cancer remains a major health concern worldwide, with genetic factors playing a crucial role in its development. Toll-like receptors (TLRs) has been implicated in various cancers, but their role in colon cancer is not well understood. This study aims to identify functional polymorphisms in the promoter and 3'UTR regions of TLRs and evaluate their association with colon cancer susceptibility., Methods: We conducted a case-control study involving 410 colon cancer patients and 410 healthy controls from the Chinese population. Genotyping of polymorphisms in TLR3, TLR4, TLR5 and TLR7 was performed using PCR-RFLP and TaqMan MGB probes. Using logistic regression analysis, we evaluated the association of TLRs polymorphisms and the susceptibility to colon cancer. To understand the biological implications of the TLR4 rs1927914 polymorphism, we conducted functional assays, including luciferase reporter assay and electrophoretic mobility shift assay (EMSA)., Results: Our results demonstrated that the G-allele of the TLR4 rs1927914 polymorphism is significantly associated with a decreased risk of colon cancer (OR = 0.68, 95%CI = 0.50-0.91). Stratified analysis showed that TLR4 rs1927914 AG or GG genotype contributed to a decreased risk of colon cancer among younger individuals (OR = 0.52, 95%CI = 0.34-0.81), males (OR = 0.58, 95%CI = 0.38-0.87), non-smokers (OR = 0.58, 95%CI = 0.41-0.83) and non-drinker with OR (95%CI) of 0.66 (0.46-0.93). Functional assays demonstrated that in HCT116 and LOVO colon cancer cells, the luciferase activity driven by the TLR4 promoter with the rs1927914A allele was 5.43 and 2.07 times higher, respectively, compared to that driven by the promoter containing the rs1927914G allele. Electrophoretic mobility shift assay (EMSA) results indicated that the rs1927914G allele enhanced transcription factor binding. Using the transcription factor prediction tool, we found that the G allele facilitates binding of the repressive transcription factor Oct1, while the A allele does not., Conclusion: The TLR4 rs1927914 polymorphism influence the susceptibility to colon cancer, with the G allele offering a protective effect through modulation of gene expression. These insights enhance our understanding of the genetic determinants of colon cancer risk and highlight TLR4 as a promising target for cancer prevention strategies., (© 2024. The Author(s).)

Background: Lung cancer, with its high morbidity and mortality, presents a major significant public health challenge. CD147, linked to cancer progression and metastasis, is a promising therapeutic target, including for lung cancer. The genetic variation may influence the expression of the gene and consequently the risk of lung cancer. This study aims to investigate single nucleotide polymorphisms (SNPs) in CD147 to understand their association with the risk of developing lung cancer in the Han Chinese population., Methods: A hospital-based case-control investigation was conducted, enrolling 700 lung cancer patients and 700 cancer-free controls. TagSNPs were selected using Haploview v4.2, and genotype data from the 1000 Genomes Project database were utilized. The selected SNPs (rs28992491, rs67945626, and rs79361899) within the CD147 gene were evaluated using the improved multiple ligation detection reaction method. Statistical analysis included chi-square tests, logistic regression models, and interaction analyses., Results: Baseline characteristics of the study population showed no significant differences in gender distribution between cases and controls, but there was a notable difference in smoking rates. No significant associations were found between the three TagSNPs and lung cancer susceptibility in the codominant model. However, stratification analyses revealed interesting findings. Among females, the rs79361899 AA/AG genotype was associated with an increased risk of lung cancer. In individuals aged ≥ 65 years old, the rs28992491 GG and rs79361899 AA genotypes were linked to a higher susceptibility. Furthermore, an interaction analysis demonstrated significant genotype × gender interactions in the rs79361899 recessive model, indicating an increased lung cancer risk in female carriers of the heterozygous or homozygous polymorphic genotype., Conclusions: CD147 polymorphisms play an important role in lung cancer development, particularly in specific subgroup of age and gender. These findings highlight the significance of incorporating genetic variations and their interactions with demographic factors in comprehending the intricate etiology of lung cancer., (© 2024. The Author(s).)

Purpose: Lung adenocarcinoma is one of the most common malignancies. Though some historic breakthroughs have been made in lung adenocarcinoma, its molecular mechanisms of development remain elusive. The aim of this study was to identify the potential genes associated with the lung adenocarcinoma progression and to provide new ideas for the prognosis evaluation of lung adenocarcinoma. Methods: The transcriptional profiles of ten pairs of snap-frozen tumor and adjacent normal lung tissues were obtained by performing RNA-seq. Weighted gene co-expression network analysis (WGCNA) was used to construct free-scale gene co-expression networks in order to explore the associations of gene sets with the clinical features and to investigate the functional enrichment analysis of co-expression genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Set Enrichment Analysis (GSEA) analyses were performed using clusterProfiler. The protein-protein network (PPI) was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and hub genes were identified using Cytohubba in Cytoscape. Transcription factor enrichment analysis was performed by the RcisTarget program in R language. Results: Based on RNA-seq data, 1,545 differentially expressed genes (DEGs) were found. Eight co-expression modules were identified among these DEGs. The blue module exhibited a strong correlation with LUAD, in which ADCY4 , RXFP1 , AVPR2 , CALCRL , ADRB1 , RAMP3 , RAMP2 and VIPR1 were hub genes. A low expression level of RXFP1 , AVPR 2, ADRB1 and VIPR1 was detrimental to the survival of LUAD patients. Genes in the blue module enriched in 86 Gene Ontology terms and five KEGG pathways. We also found that transcription factors EGR3 and EXOSC3 were related to the biological function of the blue module. Overall, this study brings a new perspective to the understanding of LUAD and provides possible molecular biomarkers for prognosis evaluation of LUAD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Xie, Wu, Hu, Zhang, Li, Zhang, Ren and Zhang.)