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Ferritin is composed of two subunits, H and L. cDNA's coding for these proteins from human liver (1,2,3), lymphocytes (4) and from the monocyte-like cell line U937 (5) have been cloned and sequenced. Southern blot analysis on total human DNA reveals that there are many DNA segments hybridizing to the apoferritin H and L cDNA probes (1,2,4,6). In view of the tissue heterogeneity of ferritin molecules (7,8), it appeared possible that apoferritin molecules could be coded by a family of genes differentially expressed in various tissues (1,2). In this paper we describe the cloning and sequencing of the gene coding for human apoferritin H. This gene has three introns; the exon sequence is identical to that of cDNA's isolated from human liver, lymphocytes, HeLa cells and endothelial cells. In addition we show that at least 15 intronless pseudogenes exist, with features suggesting that they were originated by reverse transcription and insertion. On the basis of these results we conclude that only one gene is responsible for the synthesis of the majority of apoferritin H mRNA in various tissues examined, and that probably all the other DNA segments hybridizing with apoferritin cDNA are pseudogenes.

Background. Peripheral artery disease (PAD) is an atherosclerotic disorder that leads to unpaired lumen patency through intimal hyperplasia and the build-up of plaques, mainly localized in areas of disturbed flow. Computational models can provide valuable insights in the pathogenesis of atherosclerosis and act as a predictive tool to optimize current interventional techniques. Our hypothesis is that a reliable predictive model must include the atherosclerosis development history. Accordingly, we developed a multiscale modeling framework of atherosclerosis that replicates the hemodynamic-driven arterial wall remodeling and plaque formation. Methods. The framework was based on the coupling of Computational Fluid Dynamics (CFD) simulations with an Agent-Based Model (ABM). The CFD simulation computed the hemodynamics in a 3D artery model, while 2D ABMs simulated cell, extracellular matrix (ECM) and lipid dynamics in multiple vessel cross-sections. A sensitivity analysis was also performed to evaluate the oscillation of the ABM output to variations in the inputs and to identify the most influencing ABM parameters.Results. Our multiscale model qualitatively replicated both the physiologic and pathologic arterial configuration, capturing histological-like features. The ABM outputs were mostly driven by cell and ECM dynamics, largely affecting the lumen area. A subset of parameters was found to affect the final lipid core size, without influencing cell/ECM or lumen area trends. Conclusion.The fully coupled CFD-ABM framework described atherosclerotic morphological and compositional changes triggered by a disturbed hemodynamics.

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