UDP-YOLO: High Efficiency and Real-Time Performance of Autonomous Driving Technology

In recent years, autonomous driving technology has gradually appeared in our field of vision. It senses the surrounding environment by using radar, laser, ultrasound, GPS, computer vision and other technologies, and then identifies obstacles and various signboards, and plans a suitable path to control the driving of vehicles. However, some problems occur when this technology is applied in foggy environment, such as the low probability of recognizing objects, or the fact that some objects cannot be recognized because the fog's fuzzy degree makes the planned path wrong. In view of this defect, and considering that automatic driving technology needs to respond quickly to objects when driving, this paper extends the prior defogging algorithm of dark channel, and proposes UDP-YOLO network to apply it to automatic driving technology. This paper is mainly divided into two parts: 1. Image processing: firstly, the data set is discriminated whether there is fog or not, then the fogged data set is defogged by defogging algorithm, and finally, the defogged data set is subjected to adaptive brightness enhancement; 2. Target detection: UDP-YOLO network proposed in this paper is used to detect the defogged data set. Through the observation results, it is found that the performance of the model proposed in this paper has been greatly improved while balancing the speed

Identification of differentially expressed key genes between glioblastoma and low-grade glioma by bioinformatics analysis

Gliomas are a very diverse group of brain tumors that are most commonly primary tumor and difficult to cure in central nervous system. It’s necessary to distinguish low-grade tumors from high-grade tumors by understanding the molecular basis of different grades of glioma, which is an important step in defining new biomarkers and therapeutic strategies. We have chosen the gene expression profile GSE52009 from gene expression omnibus (GEO) database to detect important differential genes. GSE52009 contains 120 samples, including 60 WHO II samples and 24 WHO IV samples that were selected in our analysis. We used the GEO2R tool to pick out differently expressed genes (DEGs) between low-grade glioma and high-grade glioma, and then we used the database for annotation, visualization and integrated discovery to perform gene ontology analysis and Kyoto encyclopedia of gene and genome pathway analysis. Furthermore, we used the Cytoscape search tool for the retrieval of interacting genes with molecular complex detection plug-in applied to achieve the visualization of protein–protein interaction (PPI). We selected 15 hub genes with higher degrees of connectivity, including tissue inhibitors metalloproteinases-1 and serum amyloid A1; additionally, we used GSE53733 containing 70 glioblastoma samples to conduct Gene Set Enrichment Analysis. In conclusion, our bioinformatics analysis showed that DEGs and hub genes may be defined as new biomarkers for diagnosis and for guiding the therapeutic strategies of glioblastoma

Identification of glioblastoma gene prognosis modules based on weighted gene co-expression network analysis

Abstract Background Glioblastoma multiforme, the most prevalent and aggressive brain tumour, has a poor prognosis. The molecular mechanisms underlying gliomagenesis remain poorly understood. Therefore, molecular research, including various markers, is necessary to understand the occurrence and development of glioma. Method Weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network in TCGA glioblastoma samples. Gene ontology (GO) and pathway-enrichment analysis were used to identify significance of gene modules. Cox proportional hazards regression model was used to predict outcome of glioblastoma patients. Results We performed weighted gene co-expression network analysis (WGCNA) and identified a gene module (yellow module) related to the survival time of TCGA glioblastoma samples. Then, 228 hub genes were calculated based on gene significance (GS) and module significance (MS). Four genes (OSMR + SOX21 + MED10 + PTPRN) were selected to construct a Cox proportional hazards regression model with high accuracy (AUC = 0.905). The prognostic value of the Cox proportional hazards regression model was also confirmed in GSE16011 dataset (GBM: n = 156). Conclusion We developed a promising mRNA signature for estimating overall survival in glioblastoma patients

Gu wen yuan jian [64 juan]

Xu kan ben.Mode of access: Internet

The New PI3K/mTOR Inhibitor GNE-477 Inhibits the Malignant Behavior of Human Glioblastoma Cells

The most common primary central nervous system tumor in adults is glioblastoma multiforme (GBM). The high invasiveness of GBM cells is an important factor leading to inevitable tumor recurrence and a poor prognosis of patients. GNE-477, a novel PI3K/mTOR inhibitor, has been reported to exert antiproliferative effects on other cancer cells. However, researchers have not clearly determined whether GNE-477 produces antitumor effects on GBM. In the present study, GNE-477 significantly inhibited the proliferation, migration and invasion of U87 and U251 cells. In addition, GNE-477 also induced apoptosis of GBM cells, arresting the cell cycle in G0/G1 phase. More importantly, GNE-477 also reduced the levels of AKT and mTOR phosphorylation in the AKT/mTOR signaling pathway in a concentration-dependent manner. An increase in AKT activity induced by SC79 rescued the GNE-477-mediated inhibition of GBM cell proliferation and apoptosis. The antitumor effects of GNE-477 and the regulatory effects on related molecules were further confirme

DataSheet_1_MS4A6A is a new prognostic biomarker produced by macrophages in glioma patients.xlsx

MS4A6A has been recognized as being associated with aging and the onset of neurodegenerative disease. However, the mechanisms of MS4A6A in glioma biology and prognosis are ill-defined. Here, we show that MS4A6A is upregulated in glioma tissues, resulting in unfavorable clinical outcomes and poor responses to adjuvant chemotherapy. Multivariate Cox regression analysis suggested that MS4A6A expression can act as a strong and independent predictor for glioma outcomes (CGGA1: HR: 1.765, p < 0.001; CGGA2: HR: 2.626, p < 0.001; TCGA: HR: 1.415, p < 0.001; Rembrandt: HR: 1.809, p < 0.001; Gravendeel: HR: 1.613, p < 0.001). A protein–protein interaction (PPI) network revealed that MS4A6A might be coexpressed with CD68, CD163, and macrophage-specific signatures. Enrichment analysis showed the innate immune response and inflammatory response to be markedly enriched in the high MS4A6A expression group. Additionally, single-cell RNA sequencing (scRNA-seq) analysis revealed distinctive expression features for MS4A6A in macrophages in the glioma immune microenvironment (GIME). Immunofluorescence staining confirmed colocalization of CD68/MS4A6A and CD163/MS4A6A in macrophages. Correlation analysis revealed that MS4A6A expression is positively related to the tumor mutation burden (TMB) of glioma, displaying the high potential of applying MS4A6A to evaluate responsiveness to immunotherapy. Altogether, our research indicates that MS4A6A upregulation may be used as a promising and effective indicator for adjuvant therapy and prognosis assessment.</p

Silk Fibroin-Coated Nano-MOFs Enhance the Thermal Stability and Immunogenicity of HBsAg

Vaccines are widely regarded as one of the most effective weapons in the fight against infectious diseases. Currently, vaccines must be stored and transported at low temperatures as high temperatures can lead to a loss of vaccine conformation and reduced therapeutic efficacy. Metal–organic frameworks (MOFs), such as zeolitic imidazole framework-8 (ZIF-8), are a new class of hybrid materials with large specific surface areas, high loading rates, and good biocompatibility and are successful systems for vaccine delivery and protection. Silk fibroin (SF) has a good biocompatibility and thermal stability. In this study, the hepatitis B surface antigen (HBsAg) was successfully encapsulated in ZIF-8 to form HBsAg@ZIF-8 (HZ) using a one-step shake and one-pot shake method. Subsequently, the SF coating modifies HZ through hydrophobic interactions to form HBsAg/SF@ZIF-8 (HSZ), which enhanced the thermal stability and immunogenicity of HBsAg. Compared to free HBsAg, HZ and HSZ improved the thermostability of HBsAg, promoted the antigen uptake and lysosomal escape, stimulated dendritic cell maturation and cytokine secretion, formed an antigen reservoir to promote antibody production, and activated CD4+ T and CD8+ T cells to enhance memory T-cell production. Importantly, HSZ induced a strong immune response even after 14 days of storage at 25 °C. Furthermore, the nanoparticles prepared by the one-step shake method exhibited superior properties compared to those prepared by the one-pot shake method. This study highlights the importance of SF-coated ZIF-8, which holds promise for investigating thermostable vaccines and breaking the vaccine cold chain