RFG-TVIU: robust factor graph for tightly coupled vision/IMU/UWB integration.

High precision navigation and positioning technology, as a fundamental function, is gradually occupying an indispensable position in the various fields. However, a single sensor cannot meet the navigation requirements in different scenarios. This paper proposes a "plug and play" Vision/IMU/UWB multi-sensor tightly-coupled system based on factor graph. The difference from traditional UWB-based tightly-coupled models is that the Vision/IMU/UWB tightly-coupled model in this study uses UWB base station coordinates as parameters for real-time estimation without pre-calibrating UWB base stations. Aiming at the dynamic change of sensor availability in multi-sensor integrated navigation system and the serious problem of traditional factor graph in the weight distribution of observation information, this study proposes an adaptive robust factor graph model. Based on redundant measurement information, we propose a novel adaptive estimation model for UWB ranging covariance, which does not rely on prior information of the system and can adaptively estimate real-time covariance changes of UWB ranging. The algorithm proposed in this study was extensively tested in real-world scenarios, and the results show that the proposed system is superior to the most advanced combination method in all cases. Compared with the visual-inertial odometer based on the factor graph (FG-VIO), the RMSE is improved by 62.83 and 64.26% in scene 1 and 82.15, 70.32, and 75.29% in scene 2 (non-line-of-sight environment).

Identification of biomarkers of venous thromboembolism by bioinformatics analyses.

Venous thromboembolism (VTE) is a common vascular disease and a major cause of mortality. This study intended to explore the biomarkers associated with VTE by bioinformatics analyses.Based on Gene Expression Omnibus (GEO) database, the GSE19151 expression profile data were downloaded. The differentially expressed genes (DEGs) between single VTE (sVTE)/recurrent VTE (rVTE) and control were identified. Then, pathway enrichment analysis of DEGs were performed, followed by protein-protein interaction (PPI) network construction.Total 433 upregulated and 222 downregulated DEGs were obtained between sVTE and control samples. For rVTE versus control, 625 upregulated and 302 downregulated DEGs were identified. The overlap DEGs were mainly enriched in the pathways related to ribosome, cancer, and immune disease. The DEGs specific to rVTE were enriched in several pathways, such as nod-like receptor signaling pathway. In the PPI network, 2 clusters of VTE genes, including ribosomal protein family genes and NADH family-ubiquinol-cytochrome genes, were identified, such as ribosomal protein L9 (RPL9), RPL5, RPS20, RPL23, and tumor protein p53 (TP53).The nod-like receptor signaling pathway, ribosomal protein family genes, such as RPL9, RPL5, RPS20, and RPL23, and DEG of TP53 may have the potential to be used as targets for diagnosis and treatment of VTE.

Screening of potential gene markers for predicting carotid atheroma plaque formation using bioinformatics approaches.

The present study aimed to investigate potential gene markers for predicting the formation of carotid atheroma plaques using high­throughput bioinformatics methods. The GSE43292 gene expression profile was downloaded from the Gene Expression Omnibus database. Following data processing, differentially expressed genes (DEGs) were screened using a paired t­test in the Linear Models for Microarray Data package with the criteria of a false discovery rate of P<0.05 and |log2 fold­change| ≥0.58, followed by functional enrichment, protein­protein interaction (PPI) network construction, key node and module analysis, and prediction of transcription factors (TFs) targeting genes in the significant modules. The results revealed that the gene expression profiles from 32 paired samples of carotid atheroma plaque tissue and macroscopically intact tissue were obtained, based on which 886 DEGs, including 513 upregulated genes and 373 downregulated genes, were identified. The upregulated and downregulated gene sets were enriched in 24 and 13 pathways, respectively. The PPI network constructed with these DEGs comprised 35 key nodes with degrees ≥20, among which spleen tyrosine kinase (SYK), LYN and phosphatidylinositol­4,5­bisphosphate 3­kinase catalytic subunit Î³ (PIK3CG) were the three highest. A significant module was mined in the PPI network, which consisted of 29 DEGs targeted by 11 TFs. The DEGs between the carotid atheroma plaque and macroscopically intact tissue samples may be involved in carotid atherogenesis. Key nodes in the PPI network constructed from these DEGs and the genes involved in the significant module, including SYK, LYN and PIK3CG, are promising for the prediction of carotid plaque formation.

Knockdown of SOX18 inhibits the proliferation, migration and invasion of hepatocellular carcinoma cells.

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world. Recent studies have demonstrated that SOX18 is highly expressed in various types of cancer. In the present study, we found that SOX18 mRNA was overexpressed in HCC compared with non-tumorous tissues. We aimed to explore the effects of SOX18 siRNA on the proliferation, invasion and migration of two HCC cell lines, MHCC97H and HepG2, which overexpress SOX18. We found that SOX18 siRNA significantly inhibited the proliferation and induced cell cycle arrest at the G0/G1 phase. Results of the Transwell assay showed that the migration and invasion of the HCC cells were markedly impaired in the SOX18-knockdown cells. Gene set enrichment analysis (GSEA) showed that KEGG focal adhesion and chemokine signaling pathways were correlated with SOX18 expression. Furthermore, the mRNA and protein levels of RhoA, PDGFB, IGF1R, CCL2, CCL3 and CCL5 were decreased in the SOX18-knockdown cells. Importantly, we demonstrated that upregulation of SOX18 was associated with a poor outcome in HCC patients. These results indicate that SOX18 may serve as a prognostic factor and a promising therapeutic strategy for HCC.