The sustained activation of CDKN1A (p21/Waf1/Cip1) by a DNA damage response induces mitochondrial dysfunction and reactive oxygen species (ROS) production via signalling through CDKN1A-GADD45A-MAPK14- GRB2-TGFBR2-TGFbeta in senescing primary human and mouse cells in vitro and in vivo.Enhanced ROS production in senescing cells generates additional DNA damage. Although this damage is repairable and transient, it elevates the average levels of DNA damage response permanently, thus forming a positive feedback loop.This loop is necessary and sufficient to maintain the stability of growth arrest until a ‘point of no return' is reached during establishment of senescence.

Ageing is the biggest risk factor for cardiovascular disease. Cellular senescence, a process driven in part by telomere shortening, has been implicated in age‐related tissue dysfunction. Here, we address the question of how senescence is induced in rarely dividing/post‐mitotic cardiomyocytes and investigate whether clearance of senescent cells attenuates age‐related cardiac dysfunction. During ageing, human and murine cardiomyocytes acquire a senescent‐like phenotype characterised by persistent DNA damage at telomere regions that can be driven by mitochondrial dysfunction and crucially can occur independently of cell division and telomere length. Length‐independent telomere damage in cardiomyocytes activates the classical senescence‐inducing pathways, p21CIP and p16INK4a, and results in a non‐canonical senescence‐associated secretory phenotype, which is pro‐fibrotic and pro‐hypertrophic. Pharmacological or genetic clearance of senescent cells in mice alleviates detrimental features of cardiac ageing, including myocardial hypertrophy and fibrosis. Our data describe a mechanism by which senescence can occur and contribute to age‐related myocardial dysfunction and in the wider setting to ageing in post‐mitotic tissues.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.