Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling

Graph-based collaborative filtering has emerged as a powerful paradigm for delivering personalized recommendations. Despite their demonstrated effectiveness, these methods often neglect the underlying intents of users, which constitute a pivotal facet of comprehensive user interests. Consequently, a series of approaches have arisen to tackle this limitation by introducing independent intent representations. However, these approaches fail to capture the intricate relationships between intents of different users and the compatibility between user intents and item properties. To remedy the above issues, we propose a novel method, named uniformly co-clustered intent modeling. Specifically, we devise a uniformly contrastive intent modeling module to bring together the embeddings of users with similar intents and items with similar properties. This module aims to model the nuanced relations between intents of different users and properties of different items, especially those unreachable to each other on the user-item graph. To model the compatibility between user intents and item properties, we design the user-item co-clustering module, maximizing the mutual information of co-clusters of users and items. This approach is substantiated through theoretical validation, establishing its efficacy in modeling compatibility to enhance the mutual information between user and item representations. Comprehensive experiments on various real-world datasets verify the effectiveness of the proposed framework.Comment: In submissio

NAT10 is upregulated in hepatocellular carcinoma and enhances mutant p53 activity

Abstract Background N-acetyltransferase 10 (NAT10) is a histone acetyltransferase which is involved in a wide range of cellular processes. Recent evidences indicate that NAT10 is involved in the development of human cancers. Previous study showed that NAT10 acetylates the tumor suppressor p53 and regulates p53 activation. As Tp53 gene is frequently mutated in hepatocellular carcinoma (HCC) and associates with the occurrence and development of HCC, the relationship between NAT10 and HCC was investigated in this study. Methods Immunohistochemistry (IHC) and western blot analysis were performed to evaluate the NAT10 expression in HCC. Immunoprecipitation experiments were performed to verify the interaction of NAT10 with mutant p53 and Mdm2. RNA interference and Western blot were applied to determine the effect of NAT10 on mutant p53. Cell growth curve was used to examine the effect of NAT10 on HCC cell proliferation. Results NAT10 was upregulated in HCC and increased NAT10 expression was correlated with poor overall survival of the patients. NAT10 protein levels were significantly correlated with p53 levels in human HCC tissues. Furthermore, NAT10 increased mutant p53 levels by counteracting Mdm2 action in HCC cells and promoted proliferation in cells carrying p53 mutation. Conclusion Increased NAT10 expression levels are associated with shortened patient survival and correlated with mutant p53 levels. NAT10 upregulates mutant p53 level and might enhance its tumorigenic activity. Hence, we propose that NAT10 is a potential prognostic and therapeutic candidate for p53-mutated HCC