Recommendation on item graphs

A novel scheme for item-based recommendation is proposed in this paper. In our framework, the items are described by an undirected weighted graph G = (V, E). V is the node set which is identical to the item set, and E is the edge set. Associate with each edge eij ∈ E is a weight wij 0, which represents similarity between items i and j. Without the loss of generality, we assume that any user’s ratings to the items should be sufficiently smooth with respect to the intrinsic structure of the items, i.e., a user should give similar ratings to similar items. A simple algorithm is presented to achieve such a “smooth ” solution. Encouraging experimental results are provided to show the effectiveness of our method. 1

Detailed Urban Land Use Land Cover Classification at the Metropolitan Scale Using a Three-Layer Classification Scheme

Urban Land Use/Land Cover (LULC) information is essential for urban and environmental management. It is, however, very difficult to automatically extract detailed urban LULC information from remote sensing imagery, especially for a large urban area. Medium resolution imagery, such as Landsat Thematic Mapper (TM) data, cannot uncover detailed LULC information. Further, very high resolution (VHR) satellite imagery, such as IKONOS and QuickBird data, can only be applied to a small area, largely due to the data unavailability and high computation cost. As a result, little research has been conducted to extract detailed urban LULC information for a large urban area. This study, therefore, developed a three-layer classification scheme for deriving detailedurban LULC information by integrating newly launched Chinese GF-1 (medium resolution) and GF-2 (very high resolution) satellite imagery and synthetically incorporating geometry, texture, and spectral information through multi-resolution image segmentation and object-based image classification (OBIA). Homogeneous urban LULC types such as water bodies or large areas of vegetation could be derived from GF-1 imagery with 16 m and 8 m spatial resolutions, while heterogeneous urban LULC types such as industrial buildings, residential buildings, and roads could be extracted from GF-2 imagery with 3.2 m and 0.8 m spatial resolutions. The multi-resolution segmentation method and a random forest algorithm were employed to perform image segmentation and object-based image classification, respectively. An analysis of the results suggests an overall accuracy of 0.89 and 0.87 were achieved for the second and third level urban LULC classification maps, respectively. Therefore, the three-layer classification scheme has the potential to derive high accuracy urban LULC information through integrating medium and high-resolution remote sensing imagery

RNF125 is a Ubiquitin-Protein Ligase that Promotes p53 Degradation

Background/Aims: Although early studies show that Mdm2 is the primary E3 ubiquitin ligase for the p53 tumor suppressor, an increasing amount of data suggests that p53 ubiquitination and degradation are more complex than once thought. Here, we investigated the role of RNF125, a non-Mdm2 ubiquitin-protein ligase, in the regulation of p53. Methods and Results: RNF125 physically interacted with p53 in exogenous/endogenous co-immunoprecipitation (IP) and GST-pull down assay, and a C72/75A mutation of RNF125 did not interfere with this interaction. Expression of RNF125 decreased the level of p53 in a dose-dependent manner, whereas knockdown of RNF125 by RNA interference increased the level of p53. As shown by Western blotting and ubiquitin assay, RNF125 ubiquitinated p53 and targeted it for proteasome degradation. Furthermore, RNF125 repressed p53 functions including p53-dependent transactivation and growth inhibition. Conclusion: Our data suggest that RNF125 negatively regulates p53 function through physical interaction and ubiquitin-mediated proteasome degradation

PSMA7 Directly Interacts with NOD1 and Regulates its Function

Background/Aims: Recent reports showed that proteasome subunit alpha type-7 (PSMA7) was overexpressed in colorectal cancer. To investigate the mechanism of PSMA7 in promotion of colorectal cancer, we screened for its interaction partners. Methods and Results: This study found that PSMA7 associated with nucleotide-binding oligomerization domain-containing protein 1 (NOD1) by yeast two-hybrid screening, co-immunoprecipitation (IP), and GST-pull down assay. As shown by Western blotting and ubiquitin assay, PSMA7 downregulated the expression of NOD1 in a proteasome-dependent manner. Overexpression of PSMA7 in HCT116 cells resulted in an inhibition of NOD1-mediated apoptosis and NF-κB activation, whereas knockdown of PSMA7 by RNA interference enhanced NOD1 activity. Conclusion: Our data suggest that PSMA7 is a negative regulator of the NOD1, and may promote tumor growth by its inhibitory role on NOD1