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Abstract Background The tumor microenvironment (TME) plays a crucial role in tumorigenesis and tumor progression. This study aimed to identify novel TME-related biomarkers and develop a prognostic model for patients with non-small-cell lung cancer (NSCLC). Methods After downloading and preprocessing data from The Cancer Genome Atlas (TCGA) data portal and Gene Expression Omnibus (GEO) datasets, we classified the molecular subtypes using the “NMF” R package. We performed survival analysis and quantified immune scores between clusters. A Cox proportional hazards model was then constructed, and its formula was produced. We assessed model performance and clinical utility. A prediction nomogram was also constructed and validated. Additionally, we explored the potential regulatory mechanisms of our TME gene signature using Gene Set Enrichment Analysis (GSEA). Results From data processing and univariate Cox regression analysis, 57 TME-related prognostic genes were identified, and two significantly distinct clusters were established. Using Cox regression and Lasso regression, an 18-gene TME-related prognostic model was developed. Patients were stratified into high- and low-risk groups based on the risk score, with survival analysis showing that the low-risk group had significantly better outcomes than the high-risk group (P

Currently, the efficacy of vaccination for preventing and controlling PRRSV is insufficient. Therefore, there is an urgent need for novel effective preventive strategies. This study aimed to investigate the antiviral effect of Eucalyptus essential oil (EEO) against PRRSV in vitro. Marc-145 cells were infected with PRRSV (rJXA1-R), and the toxicity of EEO in the cells was measured using the Cell Counting Kit-8 method. Additionally, the antiviral effect of EEO on PRRSV-infected cells was assessed using three treatment methods: drug administration post-PRRSV inoculation (post-treatment), drug administration before PRRSV inoculation (pre-treatment), and simultaneous drug administration and PRRSV inoculation (co-treatment). The EEO could not inhibit virus adsorption and/or replication since post-treatment and pre-treatment did not prevent viral infectivity. However, EEO exerted a significant virucidal effect on PRRSV. When PRRSV-infected cells were treated with 0.0156, 0.0312, and 0.0625% EEO, the cell survival rates were 55.37, 118.96, and 121.67%, respectively, and the titer of progeny virions decreased from 5.77 Log10TCID50 to 5.21 Log10TCID50, 0.55 Log10TCID50, and less than 0.167 Log10TCID50, respectively (where TCID50 is the 50% tissue culture infected dose). The fluorescence intensity of the PRRSV N protein significantly decreased in the indirect immunofluorescence assay. When cells were co-treated with EEO (0.0625%) and PRRSV (1000 TCID50) for 15 min, the viral particles were inactivated, and PRRSV (1000 TCID50) particles loss infectivity when the co-treatment time reached 60 min. In a word, EEO has no obvious therapeutic effect on PRRSV infection, but it can effectively inactivate virus particles and make them lose the ability to infect cells. These findings provide insights for the development and use of EEO to treat PRRS.

The Hepatitis E virus (HEV) causes acute and chronic Hepatitis E and is a global public health concern. HEV genotypes 3 (HEV-3) and 4 (HEV-4) are common to humans and animals, and domestic pigs and wild boars have been identified as the main reservoirs. However, limited information is available on the status of HEV infection in pigs, particularly in the Guangdong Province, China. This study aimed to investigate the seroprevalence of HEV in pig farms within the Guangdong Province. A total of 1568 serum samples were collected from 25 farms and tested for anti-HEV IgG antibodies. Enzyme-linked immunosorbent assay (ELISA) results revealed that 57.53% (902/1568) of serum samples from 24 farms (24/25, 96%) were positive for anti-HEV IgG antibodies. Year, season, region, and age were all linked risk factors for HEV in Guangdong, with season and region showing more significant impacts. The results showing a high seroprevalence of HEV confirmed its circulation among domestic pigs in the Guangdong Province, China. The presence of this antibody indicates that HEV infection was or is present on farms, posing a risk of zoonotic transmission of HEV from pigs to exposed workers and from pork or organs to consumption.

BackgroundThe increase in antibiotic resistance of bacteria has become a major concern in clinical treatment. Silver nanoparticles (AgNPs) have significant antibacterial effects against Streptococcus suis. Therefore, this study aimed to investigate the antibacterial activity and mechanism of action of AgNPs against multidrug-resistant S. suis.MethodsThe effect of AgNPs on the morphology of multidrug-resistant S. suis was observed using scanning electron microscopy (SEM). Differentially expressed proteins were analyzed by iTRAQ quantitative proteomics, and the production of reactive oxygen species (ROS) was assayed by H2DCF-DA staining.ResultsSEM showed that AgNPs disrupted the normal morphology of multidrug-resistant S. suis and the integrity of the biofilm structure. Quantitative proteomic analysis revealed that a large number of cell wall synthesis-related proteins, such as penicillin-binding protein and some cell cycle proteins, such as the cell division protein FtsZ and chromosomal replication initiator protein DnaA, were downregulated after treatment with 25 μg/mL AgNPs. Significant changes were also observed in the expression of the antioxidant enzymes glutathione reductase, alkyl hydroperoxides-like protein, α/β superfamily hydrolases/acyltransferases, and glutathione disulfide reductases. ROS production in S. suis positively correlated with AgNP concentration.ConclusionThe potential antibacterial mechanism of AgNPs may involve disrupting the normal morphology of bacteria by inhibiting the synthesis of cell wall peptidoglycans and inhibiting the growth of bacteria by inhibiting the cell division protein FtsZ and Chromosomal replication initiator protein DnaA. High oxidative stress may be a significant cause of bacterial death. The potential mechanism by which AgNPs inhibit S. suis biofilm formation may involve affecting bacterial adhesion and interfering with the quorum sensing system.

Based on the comparison and analysis with the climbing mechanism of the existing electric wheelchair， the linear connecting rod climbing mechanism is proposed. The design research of linear connecting rod climb mechanism is carried out， the endpoint trajectory upper part as the semicircle， the approximate linear the lower part of the string， the trajectory and animal walking gait extremely similar， so use it as a climbing mechanism design basis， and by using the SolidWorks software climb straight connecting rod mechanism modeling， and during the process of climbing stairs trajectory of climbing mechanism is analyzed. The simulation results show that the design scheme of the climbing mechanism is reasonable， the climbing trajectory of the climbing mechanism is approximately linear， and the turbulence is greatly reduced， which provides a new theoretical reference for the design of the climbing mechanism.

Drug target discovery is the basis of drug screening. It elucidates the cause of disease and the mechanism of drug action, which is the essential of drug innovation. Target discovery performed in biological systems is complicated as proteins are in low abundance and endogenous compounds may interfere with drug binding. Therefore, methods to track drug-target interactions in biological matrices are urgently required. In this work, a Fe3O4 nanoparticle-based approach was developed for drug-target screening in biofluids. A known ligand-protein complex was selected as a principle-to-proof example to validate the feasibility. After incubation in cell lysates, ligand-modified Fe3O4 nanoparticles bound to the target protein and formed complexes that were separated from the lysates by a magnet for further analysis. The large surface-to-volume ratio of the nanoparticles provides more active sites for the modification of chemical drugs. It enhances the opportunity for ligand-protein interactions, which is beneficial for capturing target proteins, especially for those with low abundance. Additionally, a one-step magnetic separation simplifies the pre-processing of ligand-protein complexes, so it effectively reduces the endogenous interference. Therefore, the present nanoparticle-based approach has the potential to be used for drug target screening in biological systems.

Visible light communication (VLC) is one of the key technologies for the sixth generation (6G) to support the connection and throughput of the Industrial Internet of Things (IIoT). Furthermore, VLC channel modeling is the foundation for designing efficient and robust VLC systems. In this paper, the ray-tracing simulation method is adopted to investigate the VLC channel in IIoT scenarios. The main contributions of this paper are divided into three aspects. Firstly, based on the simulated data, large-scale fading and multipath-related characteristics, including the channel impulse response (CIR), optical path loss (OPL), delay spread (DS), and angular spread (AS), are analyzed and modeled through the distance-dependent and statistical distribution models. The modeling results indicate that the channel characteristics under the single transmitter (TX) are proportional to the propagation distance. It is also found that the degree of time domain and spatial domain dispersion is higher than that in the typical rooms (conference room and corridor). Secondly, the density of surrounding objects and the effects of user heights on these channel characteristics are also investigated. Through the analysis, it can be observed that the denser objects can contribute to the smaller OPL and the larger RMS DS under the single TX case. Furthermore, due to the blocking effect of surrounding objects, the larger OPL and the smaller RMS DS can be observed at the receiver with a low height. Thirdly, due to the distance dependence of the channel characteristics and large time-domain dispersion, the link adaption method is further proposed to optimize the multipath interference problem. This method combines a luminary adaptive selection and delay adaption technique. Then, the performance of the link adaption method is verified from four aspects through simulation, including the signal-to-noise (SNR), the RMS DS, the CIRs, and the bit-error rate (BER) of a direct-current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) system. The verification results indicate that our proposed method has a significant optimization for multipath interference.

Angiogenesis plays an important role in tumor initiation and progression of glioma. Seeking for biomarkers associated with angiogenesis is important in enhancing our understanding of glioma biologically and identifying its new drug targets. RNA-sequencing (RNA-seq) data and matched clinical data were downloaded from the CGGA database. A series of filtering analyses were performed to screen for reliable genes: survival, multivariate Cox, ROC curve filtration, and clinical correlation analyses. After immunohistochemical verification, RAB42 was identified as a reliable gene for further single gene analysis. Afterwards, we performed gene set enrichment analysis (GSEA) and co-expression analysis to establish the related molecular mechanisms and signal pathways in glioma. Finally, the gene functions and the mechanisms were investigated in vitro experiments. A total of 23270 mRNA expression and 1018 glioma samples were included in this study. After the three filtering analyses, we selected ten genes for immunohistochemical verification: KLHDC8A, IKIP, HIST1H2BK, HIST1H2BJ, GNG5, FAM114A1, TMEM71, RAB42, CCDC18, and GAS2L3. Immunostaining demonstrated that RAB42 was significantly expressed on the membrane of glioma tissues but not in normal tissues. These results were verified and validated in GEPIA datasets, and the association between RAB42 with clinical features was also evaluated. Analysis of gene functions indicated that RAB42 activated VEGF signaling pathways and the mechanism was associated with natural killer cell mediated cytotoxicity, JAK-STAT signaling pathway and apoptosis pathways by PI3K/AKT in gliomas. Experiments in vitro suggested that the proliferation and invasion of glioma cells might be inhibited after downregulating of RAB42. And the tumorigenesis promotion of RAB42 may relate to the activation of VEGF signaling pathway. Taken together, this study shows that the overexpression of RAB42 is an independent prognostic factor of adverse prognosis. Its pro-oncogenic mechanism may be associated with the activation of VEGF signaling pathways.

Head and neck cancer (HNC) is the fifth most common cancer worldwide. In this study, we performed an integrative analysis of the discovery set and established an eight-gene signature for the prediction of prognosis in patients with head and neck squamous cell carcinoma (HNSCC). Univariate Cox analysis was used to identify prognosis-related genes (with P < 0.05) in the GSE41613, GSE65858, and TCGA-HNSC RNA-Seq datasets after data collection. We performed LASSO Cox regression analysis and identified eight genes (CBX3, GNA12, P4HA1, PLAU, PPL, RAB25, EPHX3, and HLF) with non-zero regression coefficients in TCGA-HNSC datasets. Survival analysis revealed that the overall survival (OS) of GSE41613 and GSE65858 datasets and the progression-free survival(DFS)of GSE27020 and GSE42743 datasets in the low-risk group exhibited better survival outcomes compared with the high-risk group. To verify that the eight-mRNA prognostic model was independent of other clinical features, KM survival analysis of the specific subtypes with different clinical characteristics was performed. Univariate and multivariate Cox regression analyses were used to identify three independent prognostic factors to construct a prognostic nomogram. Finally, the GSVA algorithm identified six pathways that were activated in the intersection of the TCGA-HNSC, GSE65858, and GSE41613 datasets, including early estrogen response, cholesterol homeostasis, oxidative phosphorylation, fatty acid metabolism, bile acid metabolism, and Kras signaling. However, the epithelial–mesenchymal transition pathway was inhibited at the intersection of the three datasets. In conclusion, the eight-gene prognostic signature proved to be a useful tool in the prognostic evaluation and facilitate personalized treatment of HNSCC patients.

Clustering analysis is one of the most important techniques in point cloud processing, such as registration, segmentation, and outlier detection. However, most of the existing clustering algorithms exhibit a low computational efficiency with the high demand for computational resources, especially for large data processing. Sometimes, clusters and outliers are inseparable, especially for those point clouds with outliers. Most of the cluster-based algorithms can well identify cluster outliers but sparse outliers. We develop a novel clustering method, called spatial neighborhood connected region labeling. The method defines spatial connectivity criterion, finds points connections based on the connectivity criterion among the k- nearest neighborhood region and classifies connected points to the same cluster. Our method can accurately and quickly classify datasets using only one parameter k . Comparing with K -means, hierarchical clustering and density-based spatial clustering of applications with noise methods, our method provides better accuracy using less computational time for data clustering. For applications in the outlier detection of the point cloud, our method can identify not only cluster outliers, but also sparse outliers. More accurate detection results are achieved compared to the state-of-art outlier detection methods, such as local outlier factor and density-based spatial clustering of applications with noise.