CONCLUSION: XSLJZD could restore the gastric emptying rate and improve symptoms. However, the evidence remains weak due to the poor methodological quality of the included studies. (C) 2014 Baishideng Publishing Group Co., Limited. All rights reserved.”
“Background: The purpose of this study is to evaluate expression of metabolism-related proteins in primary unknown metastatic carcinoma (PUMC) and associated implications for treatment. Methods:
A tissue microarray containing 77 cases of PUMC was constructed and immunohistochemical staining was used to evaluate expression of the following proteins: Glycolysis-related: Glut-1, find more carbonic anhydrase (CA) IX, and monocarboxylate transporter (MCT) 4; Glutaminolysis-related: glutaminase1 (GLS1), glutamate dehydrogenase (GDH), and amino acid transporter-2 (ASCT2); and Mitochondrial-related: ATP synthase, succinate dehydrogenase (SDH) A, and SDHB. The association between immunohistochemical staining results and clinicopathologic parameters was evaluated. Results: The expression of metabolism-related proteins was different depending on the histologic subtype. Compared to other subtypes, squamous cell carcinomas (SQ) expressed more Glut-1 (p = 0.028), while adenocarcinomas (AD) expressed more SDHB in the stroma (p = 0.025). The expression of metabolism-related proteins was also different
depending on the clinical subtypes. Glut-1 was expressed most in the nodal type and the least in carcinomatosis type, when compared to other subtypes (p = 0.021). The metabolic P505-15 phenotypes also showed other
trends: when the stroma showed no glutaminolysis, the tumor mostly invaded lymph node, bone, and brain, while the tumor invaded regions other than lymph node, bone, and brain when the stroma showed glutaminolysis (p = 0.003). When the selleckchem stroma showed the mitochondrial metabolic type, the histologic subtype was mainly AD, but the non-mitochondrial type was associated more with SQ (P = 0.049). Conclusion: For PUMC, the expression of metabolism-related proteins, such as Glut-1 and SDHB, differs in the tumor or stroma depending on the clinical and histologic tumor subtype.”
“Given the unprecedented size of three-dimensional ultraspectral sounder data with high spectral resolution, lossless compression is preferable to avoid substantial degradation of the geophysical retrieval. A lossless compression method for ultraspectral sounder data is therefore developed. A quantized-principal-component-analysis-based scheme is presented by combining 3D prediction, positive mapping, and histogram packing using binary indexing vectors (positive packing) followed by a range coder. In order to achieve the optimal trade-off between residual errors and side information, an algorithm is proposed to determine adaptively the number of selected PCs and quantization parameters. Numerical experiments show that the proposed method outperforms the state-of-the-art methods (i.e.