Window detection is a key component in many graphics and vision applications related to 3D city modeling and scene visualization. We present a novel approach for learning to recognize windows in a colored facade image. Rather than predicting bounding boxes or performing facade segmentation, our system locates keypoints of windows, and learns keypoint relationships to group them together into windows. A further module provides extra recognizable information at the window center. Locations and relationships of keypoints are encoded in different types of heatmaps, which are learned in an end-to-end network. We have also constructed a facade dataset with 3 418 annotated images to facilitate research in this field. It has richly varying facade structures, occlusion, lighting conditions, and angle of view. On our dataset, our method achieves precision of 91.4% and recall of 91.0% under 50% IoU (intersection over union). We also make a quantitative comparison with state-of-the-art methods to verify the utility of our proposed method. Applications based on our window detector are also demonstrated, such as window blending.
Background More and more evidence suggests that cancer is a mitochondrial metabolic disease recently and mitochondria dysfunction is critical to tumorigenesis. As a gatekeeper of mitochondria, the voltage-dependent anion channel 1 (VDAC1) is associated with the development of breast cancer (BC). However, its potential mechanism and clinical significance remain unclear; thus, in this research, we aimed to explore it. Methods VDAC1 expression in BC tissues and normal tissues was obtained from The Cancer Genome Atlas (TCGA) and validated by datasets from the gene expression omnibus (GEO) database. Then, the relationships between VDAC1 expression and clinicopathological features were analyzed. Receiver operating characteristics (ROC) curves were used to identify the diagnostic value of VDAC1. The prognostic value was evaluated by Kaplan-Meier survival curves and Cox regression analysis. VDAC1 with its co-expression genes were subjected to enrichment analysis to explore potential mechanisms in BC and the protein-protein interaction (PPI) network was constructed. At last, the association between VDAC1 expression and infiltration levels of immune cell infiltration by various methods, as well as their corresponding markers, was analyzed. We also analyzed the correction between VDAC1 expression and eight immune checkpoint genes and the tumor immune dysfunction and exclusion (TIDE) scores of each BC sample in TCGA were calculated and the differences between high and low VDAC1 expression groups were analyzed. Results VDAC1 expression was remarkably elevated in BC (p < 0.001), and high expression of VDAC1 was associated with the positive expression of ER (p = 0.004), PR (p = 0.033), and HER2 (p = 0.001). ROC analysis suggested that VDAC1 had diagnosed value in BC. The Kaplan-Meier analysis suggested that higher expression of VDAC1 was associated with shorter overall survival (OS), and further Cox regression analysis revealed that VDAC1 was an independent factor of unfavorable prognosis in BC patients. Enrichment analysis of VDAC1 and its co-expression suggested that VDAC1 was related to the regulation of mitochondrial energy metabolism and protein modification, and the HIF-1 singing pathway might be the potential mechanism in BC. Notably, we found that VDAC1 expression was infiltration levels of most types of immune cells, as well as the expression of marker genes of immune cells. The ICGs PDCD1, CTLA4, LAG3, SIGLEC15, and TIGIT were negatively corrected with VDAC1 expression in BC. TIDE scores between the low and high expression groups showed no difference. Conclusion Overexpressed VDAC1 in BC could be severed as a novel biomarker for diagnosis and VDAC1 was an independent factor for adverse prognosis prediction. Our study revealed that VDAC1 might inhibit tumor immunity and might be a novel therapeutic target in BC.
BackgroundEpithelial–mesenchymal transition (EMT) is a crucial mechanism that microRNA-222-3p (miR-222-3p) promotes breast cancer (BC) progression. Our study aimed to identify EMT-associated target genes (ETGs) of miR-222-3p for further analysis of their roles in BC based on bioinformatics tools.MethodsBased on bioinformatics analysis, we identified 10 core ETGs of miR-222-3p. Then, we performed a comprehensive analysis of 10 ETGs and miR-222-3p, including pathway enrichment analysis of ETGs, differential expression, clinical significance, correlation with immune cell infiltration, immune checkpoint genes (ICGs) expression, tumor mutational burden (TMB), microsatellite instability (MSI), stemness, drug sensitivity, and genetic alteration.ResultsThe expression of miR222-3p in basal-like BC was significantly higher than in other subtypes of BC and the normal adjacent tissue. Pathway analysis suggested that the ETGs might regulate the EMT process via the PI3K-Akt and HIF-1 signaling pathway. Six of the 10 core ETGs of miR-222-3p identified were down-expressed in BC, which were EGFR, IL6, NRP1, NTRK2, LAMC2, and PIK3R1, and SERPINE1, MUC1, MMP11, and BIRC5 were up-expressed in BC, which also showed potential diagnostic values in BC. Prognosis analysis revealed that higher NTRK2 and PIK3R1 expressions were related to a better prognosis, and higher BIRC5 and miR-222-3p expressions were related to a worse prognosis. Most ETGs and miR-222-3p were positively correlated with various infiltration of various immune cells and ICGs expression. Lower TMB scores were correlated with higher expression of MUC1 and NTRK2, and higher BIRC5 was related to a higher TMB score. Lower expression of MUC1, NTRK2, and PIK3R1 were associated with higher MSI scores. Higher expression of ETGs was associated with lower mRNAsi scores, except BIRC5 and miR-222-3p conversely. Most ETGs and miR-222-3p expression were negatively correlated with the drug IC50 values. The analysis of the genetic alteration of the ETGs suggested that amplification was the main genetic alteration of eight ETGs except for NTRK2 and PIK3R1.ConclusionMiR-222-3p might be a specific biomarker of basal-like BC. We successfully identify 10 core ETGs of miR-222-3p, some might be useful diagnostic and prognostic biomarkers. The comprehensive analysis of 10 ETGs and miR-222-3p indicated that they might be involved in the development of BC, which might be novel therapeutic targets for the treatment of BC.
There is a lack of validated biomarkers for the diagnosis of early breast cancer (EBC). The current study aimed to determine the diagnostic and prognostic value of solute carrier family 50 member 1 (SLC50A1) in patients with EBC. Therefore, 123 patients with EBC, 30 patients with benign breast disease (BBD) and 26 healthy controls (HCs) were recruited. The serum levels of SLC50A1 in paired sera of 40 postoperative patients were assessed by ELISA. Immunohistochemical staining for SLC50A1 was performed in surgical tissue derived from 83 patients with EBC and 30 patients with BBD. mRNA expression of SLC50A1 and its diagnostic and prognostic value in patients with EBC was evaluated using an RNA-sequencing database. The results showed that serum levels of SLC50A1 in patients with EBC were significantly higher compared with those in patients with BBD and HCs (both P<0.001). Additionally, receiver operating characteristic curve analysis revealed that the serum levels of SLC50A1 distinguished patients with EBC from patients with BBD and HCs with a sensitivity of 76.42% and specificity of 76.79% [area under the curve (AUC)=0.783; P<0.001]. The diagnostic value of SLC50A1 was significantly greater than that of carcinoembryonic (P<0.005) and carbohydrate antigen 15-3 (P<0.029). Furthermore, the number of SLC50A1 positive cells significantly increased in tissue of patients with EBC compared with patients with BBD (P<0.001). A positive association between serum levels of SLC50A1 and its expression in tissue samples was observed in patients with EBC (ρ=0.700; P<0.001). Additionally, bioinformatics analysis verified the diagnostic value of SLC50A1, with an AUC of 0.983 (P<0.001). Multivariate analysis demonstrated that SLC50A1 was an independent prognostic factor in patients with EBC with a hazard ratio of 1.917 (P=0.013). These findings indicated that SLC50A1 may be a potential diagnostic biomarker for primary EBC and that SLC50A1 upregulation may be associated with unfavorable prognosis in patients with EBC.
The method of document metrology and content analysis are applied in preschool education informatization research. The study shows that, from the publication of the age distribution, authors backgrounds, publishing institutions and research content, the overall level in preschool education informatization research is going up but not enough in depth. High-level research-group, typical research model and instruction to the research are urge needed.
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