The medical magnetic resonance (MR) image reconstruction is one of the key technologies in the field of magnetic resonance imaging (MRI). The compressed sensing (CS) theory indicates that the image can be reconstructed accurately from highly undersampled measurements by using the sparsity of the MR image. However, how to improve the image reconstruction quality by employing more sparse priors of the image becomes a crucial issue for MRI. In this paper, an adaptive image reconstruction model fusing the double dictionary learning is proposed by exploiting sparse priors of the MR image in the image domain and transform domain. The double sparse model which combines synthesis sparse model with sparse transform model is applied to the CS MR image reconstruction according to the complementarity of synthesis sparse and sparse transform model. Making full use of the two sparse priors of the image under the synthesis dictionary and transform dictionary learning, the proposed model is tackled in stages by the iterative alternating minimization algorithm. The solution procedure needs to utilize the synthesis and transform K-singular value decomposition (K-SVD) algorithms. Compared with the existing MRI models, the experimental results show that the proposed model can more efficiently improve the quality of the image reconstruction, and has faster convergence speed and better robustness to noise.

OBJECTIVE: To investigate the expression of four-jointed box kinase 1 (FJX1) in gastric cancer (GC), its correlation with survival outcomes of the patients, and its role in GC progression. METHODS: The expression level of FJX1 in GC tissues and normal gastric mucosal tissues and its correlation with the survival outcomes of GC patients were analyzed using TCGA and GEO database GC cohort. Immunohistochemistry was used to detect FJX1 expression level in clinical specimens of GC tissue, and its correlations with the patients' clinicopathological parameters and prognosis were analyzed. Bioinformatic analysis was performed to identify the potential pathways of FJX1 in GC. The effects of FJX1 overexpression or FJX1 silencing on GC cell proliferation and expressions of proliferation-related proteins, PI3K, AKT, p-PI3K, and p-AKT were evaluated using CCK-8 assay and Western blotting. The effect of FJX1 overexpression on GC cell tumorigenicity was evaluated in nude mice. RESULTS: GC tissues showed significantly higher expressions of FJX1 mRNA and protein compared with normal gastric mucosa tissues (P < 0.05). The high expression of FJX1 was associated with poor prognosis of GC patients (P < 0.05) and served as an independent risk factor for poor survival outcomes in GC (P < 0.05). FJX1 was expressed mainly in the cytoplasm of GC cells in positive correlation with Ki67 expression (R=0.34, P < 0.05), and was correlated with CA199 levels, depth of tumor infiltration and lymph node metastasis of GC (P < 0.05). In the cell experiment, FJX1 level was shown to regulate the expressions of Ki67 and PCNA and GC cell proliferation (P < 0.05). Gene set enrichment analysis indicated that the PI3K/AKT pathway potentially mediated the effect of FJX1, which regulated the expressions of PI3K and AKT and their phosphorylated proteins. In nude mice, FJX1 overexpression in GC cells significantly promoted the growth of the transplanted tumors (P < 0.05). CONCLUSION FJX1 is highly expressed in GC tissues and is correlated with poor prognosis of GC patients. FJX1 overexpression promotes GC cell proliferation through the PI3K/AKT signaling pathway, and may serve as a potential prognostic biomarker and therapeutic target for GC.
Animals ; Mice ; Cell Proliferation ; Ki-67 Antigen ; Mice, Nude ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Signal Transduction ; Stomach Neoplasms/pathology* ; Humans ; Intercellular Signaling Peptides and Proteins/genetics*

OBJECTIVE: To investigate the prognostic value of death-associated protein 5 (DAP5) in gastric cancer (GC) and its regulatory effect on aerobic glycolysis in GC cells. METHODS: We analyzed DAP5 expression levels in GC and adjacent tissues and its association with survival outcomes of GC patients using public databases. We collected paired samples of GC and adjacent tissues from 102 patients undergoing radical resection of GC in our hospital from June, 2012 to July, 2017, and analyzed the correlation of DAP5 expression level detected immunohistochemically with the clinicopathological parameters of the patients. Cox regression analysis, Kaplan-Meier analysis, and ROC curves were used to explore the independent risk factors and the predictive value of DAP5 expression for 5-year survival of the patients. In the cell experiments, we observed the changes in aerobic glycolysis in MGC-803 cells following lentivirus-mediated DAP5 knockdown or overexpression by measuring glucose uptake and cellular lactate level and using qRT-PCR and Western blotting. RESULTS: Analysis using the public databases showed that DAP5 was highly expressed in GC and correlated with tumor progression and poor survival outcomes of the patients (P < 0.05). In the clinical samples, DAP5 expression was significantly higher in GC than in the adjacent tissues (3.19±0.60 vs 1.00±0.12; t=36.863, P < 0.01), and a high expression of DAP5 was associated with a reduced 5-year survival rate of the patients (17.6% vs 72.5%; χ²=29.921, P < 0.05). A high DAP5 expression, T3-4, N2-3, and CEA≥5 ng/mL were identified as independent risk factors affecting 5-year survival outcomes of GC (P < 0.05), for which DAP5 expression showed a prediction sensitivity, specificity and accuracy of 73.2%, 80.4% and 79.0%, respectively. In MGC-803 cells, DAP5 knockdown significantly reduced glucose uptake, lactate level and the expressions of GLUT1, HK2 and LDHA, and DAP5 overexpression produced the opposite effects (P < 0.05). CONCLUSION A high expression of DAP5 in GC, which enhances cellular aerobic glycolysis to promote cancer progression, is correlated with a poor survival outcome and may serve as a biomarker for evaluating long-term prognosis of GC patients.
Humans ; Stomach Neoplasms ; Blotting, Western ; Databases, Factual ; Glucose ; Lactates