-The adult mammalian heart has limited ability to repair itself following injury. Zebrafish, newts and neonatal mice can regenerate cardiac tissue, largely by cardiac myocyte (CM) proliferation. It is unknown if hearts of young large mammals can regenerate. -We examined the regenerative capacity of the pig heart in neonatal animals (ages: 2, 3 or 14 days postnatal) after myocardial infarction (MI) or sham procedure. Myocardial scar and left ventricular function were determined by cardiac magnetic resonance (CMR) imaging and echocardiography. Bromodeoxyuridine pulse-chase labeling, histology, immunohistochemistry and Western blotting were performed to study cell proliferation, sarcomere dynamics and cytokinesis and to quantify myocardial fibrosis. RNA-sequencing was also performed. -After MI, there was early and sustained recovery of cardiac function and wall thickness in the absence of fibrosis in 2-day old pigs. In contrast, older animals developed full-thickness myocardial scarring, thinned walls and did not recover function. Genome wide analyses of the infarct zone revealed a strong transcriptional signature of fibrosis in 14-day old animals that was absent in 2-day old pigs, which instead had enrichment for cytokinesis genes. In regenerating hearts of the younger animals, up to 10% of CMs in the border zone of the MI showed evidence of DNA replication that was associated with markers of myocyte division and sarcomere disassembly. -Hearts of large mammals have regenerative capacity, likely driven by cardiac myocyte division, but this potential is lost immediately after birth.

The microscopic structure of neuronal tissue is crucial to brain function, with axon diameter, axonal density and myelination directly influencing signal conduction in the white matter. There is increasing evidence that these microstructural properties alter signal in magnetic resonance imaging (MRI) driven by magnetic susceptibility of different compartments (e.g., myelin sheaths and iron-laden cells). To explain these observations, we have developed a multi-compartmental geometric model of whitematter microstructure. Using a single set of literature parameters, this forward model predicts experimentally observed orientation dependence and temporal evolution of the MRI signal. Where previous models have aimed to explain only the orientation dependence of signal phase, the proposed approach encapsulates the full repertoire of signal behavior. The frequency distribution underlying signal behavior is predicted to be a rich source of microstructural information with relevance to neuronal pathology.