ABSTRACT Biological Analysis Core. The cardiopulmonary system is a major inter-dependent organ system in the human body, which has a major impact on overall life span and aging. Understanding the mechanisms that distinguish beneficial from deleterious senescence and the heterogeneity underlying senescent cell states in this organ system is critical. The overall aim of the Biological Analysis Core (BAC) is to generate a high-resolution map of cellular senescence in lung and heart tissue across the lifespan, using state-of-the-art technologies, and identify robust biomarkers of cellular senescence that will predict therapeutic responses to senolytics. We will generate and refine endogenous signatures of cellular senescence at single cell resolution in healthy lung and heart tissue employing comprehensive profiling of current markers of senescence using unbiased high-content screening. We will apply a range of state-of-the-art, high-resolution, and high-throughput methods to calibrate, validate, and produce precise mapping data of senescence. These will include multi-color flow cytometry, high resolution imaging of cleared as well as native tissue, scRNASeq/snATAC/PIC-seq multi-omics, proteomics, and spatial transcriptomics. We will interrogate 3D ex vivo human lung and heart tissue subjected to specific drivers of senescence (e.g., DNA damage, telomere attrition) to define senescence heterogeneity and refine current senescence signatures. Lung and heart PCTS will be subjected to defined senescence-inducing perturbations to map the response of single cells in their natural 3D environment using omics analysis and 3D high-resolution confocal time-lapse imaging for visualization, tracking, and tracing of senescence cells in their natural environment ex vivo. Finally, we will define the senescence phenotype and function of primary senescent cells sorted from human lung and heart tissue and will determine cell- and organ-specific responses to senolytics by assessing their changes in senescence signatures and SASP biomarkers. These novel signatures and biomarkers of senescence generated in the BAC will continuously feed into tissue mapping analysis and will thereby refine the spatiotemporal mapping of cellular senescence by hierarchical clustering and deconvolution using computational analysis and artificial intelligence approaches. This will allow us to map senescent cells at unprecedent spatial resolution and 3D reconstruction across the lifespan and to generate a comprehensive and in-depth Lung and Heart Senescence Map.