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In this study, we conducted an in-depth exploration of Alzheimer's Disease (AD) by integrating state-of-the-art methodologies, including single-cell RNA sequencing (scRNA-seq), weighted gene co-expression network analysis (WGCNA), and a convolutional neural network (CNN) model. Focusing on the pivotal role of microglia in AD pathology, our analysis revealed 11 distinct microglial subclusters, with 4 exhibiting obviously alterations in AD and HC groups. The investigation of cell–cell communication networks unveiled intricate interactions between AD-related microglia and various cell types within the central nervous system (CNS). Integration of WGCNA and scRNA-seq facilitated the identification of critical genes associated with AD-related microglia, providing insights into their involvement in processes such as peptide chain elongation, synapse-related functions, and cell adhesion. The identification of 9 hub genes, including USP3, through the least absolute shrinkage and selection operator (LASSO) and COX regression analyses, presents potential therapeutic targets. Furthermore, the development of a CNN-based model showcases the application of deep learning in enhancing diagnostic accuracy for AD. Overall, our findings significantly contribute to unraveling the molecular intricacies of microglial responses in AD, offering promising avenues for targeted therapeutic interventions and improved diagnostic precision. [ABSTRACT FROM AUTHOR]

Ankylosing spondylitis (AS) is a chronic, progressive inflammatory rheumatic disease affecting the spine, axial skeleton, and sacroiliac joints. Pathogenesis of AS encompasses enthesitis, synovitis, and osteoproliferation, leading to the formation of syndesmophytes, ankylosis, and spinal rigidity. Bioinformatics, an interdisciplinary field combining computer science, mathematics, and biology, enables the analysis of complex biological data for investigating AS pathogenesis. This review summarizes differentially expressed protein‐coding genes in peripheral blood or local tissues of AS patients compared with healthy controls and comprehensively reviews currently available therapeutic agents. The objective is to enhance the understanding of AS pathogenesis, inform diagnosis, identify novel therapeutic targets, and facilitate personalized medicine. This review contributes to a deeper understanding of AS pathogenesis and provides a foundation for developing innovative therapeutic approaches. [ABSTRACT FROM AUTHOR]