Objectives/Goals: The aging (65+) population is rapidly growing and faces unique health issues exacerbated by immune function decline. However, the driving mechanisms behind this decline are poorly understood. We will use a mouse model to study the relationship between stiffness and cell mobility within the lymph node (LN) as one potential driving mechanism. Methods/Study Population: We will collect inguinal LNs from young (6–8 weeks) and aged (18+ months) female mice and section them for ex vivo analysis, including quantification of proteins in the fibroblastic reticular network (collagen I, collagen III, collagen VI, laminin, and fibronectin) using immunofluorescent staining and Python scripts; analysis of biomechanical properties (elastic modulus, loss modulus, and pore size) using multiple particle tracking (MPT); and migration analysis of adoptively transferred B- and T-cells using live imaging and MATLAB scripts. We will use ANOVA to compare abundance and organization of proteins, biomechanical properties, and cell migration between young and aged LNs, as well as using Pearson’s correlation coefficients to identify relationships between characteristics. Results/Anticipated Results: We hypothesize a positive correlation between fibroblastic reticular network protein deposits, especially collagens, and stiffness (elastic modulus) within murine LNs due to known mechanisms underlying age-related fibrosis. We also hypothesize that areas of increased stiffness (as revealed by MPT) will exhibit decreased cell migration due to physical hindrance to B- and T-cell mobilization. Furthermore, we hypothesize that aged murine LNs will exhibit a significant increase in stiffness and resultant decreased cell mobility when compared to young murine LN, particularly in areas with increased collagen localization. Discussion/Significance of Impact: These studies will elucidate structure–function relationships driving age-associated LN fibrosis and stiffness, and the resultant effect on cell migration, thus clarifying some of the potential driving mechanisms behind immune aging and providing data capable of informing the development of relevant models, therapeutics, and interventions.