Time-Aware Explainable Recommendation via Updating Enabled Online Prediction.

There has been growing attention on explainable recommendation that is able to provide high-quality results as well as intuitive explanations. However, most existing studies use offline prediction strategies where recommender systems are trained once while used forever, which ignores the dynamic and evolving nature of user-item interactions. There are two main issues with these methods. First, their random dataset split setting will result in data leakage that knowledge should not be known at the time of training is utilized. Second, the dynamic characteristics of user preferences are overlooked, resulting in a model aging issue where the model's performance degrades along with time. In this paper, we propose an updating enabled online prediction framework for the time-aware explainable recommendation. Specifically, we propose an online prediction scheme to eliminate the data leakage issue and two novel updating strategies to relieve the model aging issue. Moreover, we conduct extensive experiments on four real-world datasets to evaluate the effectiveness of our proposed methods. Compared with the state-of-the-art, our time-aware approach achieves higher accuracy results and more convincing explanations for the entire lifetime of recommendation systems, i.e., both the initial period and the long-term usage.

Dissecting the Mechanisms of Intestinal Immune Homeostasis by Analyzing T-Cell Immune Response in Crohn's Disease and Colorectal Cancer.

INTRODUCTION: Crohn's disease (CD) and colorectal cancer (CRC) represent a group of intestinal disorders characterized by intricate pathogenic mechanisms linked to the disruption of intestinal immune homeostasis. Therefore, comprehending the immune response mechanisms in both categories of intestinal disorders is of paramount significance in the prevention and treatment of these debilitating intestinal ailments. METHOD: IIn this study, we conducted single-cell analysis on paired samples obtained from primary colorectal tumors and individuals with Crohn's disease, which was aimed at deciphering the factors influencing the composition of the intestinal immune microenvironment. By aligning T cells across different tissues, we identified various T cell subtypes, such as γδ T cell, NK T cell, and regulatory T (Treg) cell, which maintained immune system homeostasis and were confirmed in enrichment analyses. Subsequently, we generated pseudo-time trajectories for subclusters of T cells in both syndromes to delineate their differentiation patterns and identify key driver genes Result: Furthermore, cellular communication and transcription factor regulatory networks are all essential components of the intricate web of mechanisms that regulate intestinal immune homeostasis. The identified complex cellular interaction suggested potential T-lineage immunotherapeutic targets against epithelial cells with high copy number variation (CNV) levels in CD and CRC. CONCLUSION: Finally, the analysis of regulon networks revealed several promising candidates for cell-specific transcription factors (TFs). This study focused on the immune molecular mechanism under intestinal diseases. It contributed to the novel insight of depicting a detailed immune landscape and revealing T-cell responding mechanisms in CD and CRC.