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How functional amyloids are regulated to restrict their activity is poorly understood. The cytoplasmic polyadenylation element-binding protein 3 (CPEB3) is an RNA-binding protein that adopts an amyloid state key for memory persistence. Its monomer represses the translation of synaptic target mRNAs while phase separated, whereas its aggregated state acts as a translational activator. Here, we have explored the sequence-driven molecular determinants behind the functional aggregation of human CPEB3 (hCPEB3). We found that the intrinsically disordered region (IDR) of hCPEB3 encodes both an amyloidogenic and a phase separation domain, separated by a poly-A-rich region. The hCPEB3 amyloid core is composed by a hydrophobic region instead of the Q-rich stretch found in the Drosophila orthologue. The hCPEB3 phase separation domain relies on hydrophobic interactions with ionic strength dependence, and its droplet ageing process leads to a liquid-to-solid transition with the formation of a non-fibril-based hydrogel surrounded by starburst droplets. Furthermore, we demonstrate the differential behavior of the protein depending on its environment. Under physiological-like conditions, hCPEB3 can establish additional electrostatic interactions with ions, increasing the stability of its liquid droplets and driving a condensation-based amyloid pathway.

The aim of this work was to analyze the influence of sex hormones and anatomical details (trabeculations and false tendons) on the electrophysiology of healthy human hearts. Additionally, sex- and anatomy-dependent effects of ventricular tachycardia (VT) inducibility are presented. To this end, four anatomically normal, human, biventricular geometries (two male, two female), with identifiable trabeculations, were obtained from high-resolution, ex-vivo MRI and represented by detailed and smoothed geometrical models (with and without the trabeculations). Additionally one model was augmented by a scar. The electrophysiology finite element model (FEM) simulations were carried out, using O’Hara-Rudy human myocyte model with sex phenotypes of Yang and Clancy. A systematic comparison between detailed vs smooth anatomies, male vs female normal hearts was carried out. The heart with a myocardial infarction was subjected to a programmed stimulus protocol to identify the effects of sex and anatomical detail on ventricular tachycardia inducibility. All female hearts presented QT-interval prolongation however the prolongation interval in comparison to the male phenotypes was anatomy-dependent and was not correlated to the size of the heart. Detailed geometries showed QRS fractionation and increased T-wave magnitude in comparison to the corresponding smoothed geometries. A variety of sustained VTs were obtained in the detailed and smoothed male geometries at different pacing locations, which provide evidence of the geometry-dependent differences regarding the prediction of the locations of reentry channels. In the female phenotype, sustained VTs were induced in both detailed and smooth geometries with RV apex pacing, however no consistent reentry channels were identified. Anatomical and physiological cardiac features play an important role defining risk in cardiac disease. These are often excluded from cardiac electrophysiology simulations. The assumption that the cardiac endocar, JA-S, FS, GH and MV are supported by the European Union’s Horizon 2020 research and innovation programme under grant agreements No 675451 (Compbiomed project phase 1) and No 823712 (CompBioMed project, phase 2) and project No 777204 (SilicoFCM project). Part of the simulation computing hours were provided by the CompBioMed project phase 1. JA-S was awarded computation time from Red Espanola de Supercomputacion (RES). (Activity IDs: FI-2018-2-0049 and BCV-2019-2-0014) JA-S is funded by a Ramon y Cajal fellowship (RYC-2017-22532), Ministerio de Ciencia e Innovacion, Spain; and by Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2017-2020 from the Ministerio de Ciencia e Innovacion y Universidades (PID2019-104356RBC41/AEI/10.13039/501100011033): meHeart ME PID2019-104356RB-C44. CB is funded by the Torres Quevedo Program (PTQ2018-010290), Ministerio de Ciencia e Innovacion, Spain. MV, GH and CB are funded by the Spanish Neotec project EXP - 00123159/SNEO-20191113 Generador de corazones virtuales. LKGM was funded by Fundacion Carolina-BBVA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study., Peer Reviewed, "Article signat per 11 autors/es: Pablo Gonzalez-Martin,Federica Sacco,Constantine Butakoff,Ruben Doste,Carlos Bederian,Lilian K. Gutierrez Espinosa de los Monteros,Guillaume Houzeaux,Paul A. Iaizzo,Tinen L. Iles,Mariano Vazquez,Jazmin Aguado-Sierra", Postprint (published version)

Impact simulations for damage resistance analysis are computationally intensive due to contact algorithms and advanced damage models. Both methods, which are the main ingredients in an impact event, require refined meshes at the contact zone to obtain accurate predictions of the contact force and damage onset and propagation through the material. This work presents the application of the partial Dirichlet–Neumann contact algorithm to simulate low-velocity impact problems on composite structures using High-Performance Computing. This algorithm is devised for parallel finite element codes running on supercomputers, and it is extended to explicit time integration schemes to solve impact problems including damage. The proposed framework is validated with a standard test for damage resistance on fiber-reinforced polymer matrix composites. Moreover, the parallel performance of the proposed algorithm has been evaluated in a mesh of 74M of elements running with 2400 processors, This work has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreements No. 807083 and No. 945521 (SHERLOC project). The JU receives support from the European Union’s Horizon 2020 research and innovation program and the Clean Sky 2 JU members other than the Union. The authors gratefully acknowledge Hellenic Aerospace Industry for manufacturing of the coupons made of T800S/M21 material and Kirsa Muñoz and Miguel Ángel Jiménez from Element Materials Technology Seville, Peer Reviewed, Postprint (author's final draft)

Structural Preferences of the Protein hCPEB3 in the Prelude to Memory Consolidation 1213 Douglas Laurents , Daniel Ramírez De Mingo , David Pantoja Uceda , Rubén Hervás , Mariano Carrión Vázquez 1) "Rocasolano" Institute for Physical Chemistry, Madrid, Spain 2) Instituto Cajal, IC-CSIC, Madrid, Spain 3) School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong, China How are memories stored in the brain? Neurospecific forms of the cytoplasmic polyadenylation element binding protein (CPEB) are thought to promote memory consolidation by undergoing a disordered to functional amyloid conformational transformation at specific dendritic spines(1). This alters local mRNA translation and leads to a strengthening of particular dendritic spines(2). Whereas the structure of the Drosophila CPEB homolog has been recently elucidated(3), how amyloid formation occurs in the human homolog (hCPEB3) is still unclear. To address this question, we have characterized the partial structure and dynamics of the 426- residue disordered region in hCPEB3 by NMR spectroscopy(4). Five segments with partial ¿- helix formation, two with moderate polyproline II helix populations and a rigid hydrophobic segment were observed in the first 250 residues. Biophysical assays evince that residues 251- 426 can promote biomolecular condensateformation (5). Some evidence for interactions among the elements of partly populated ¿-helices and between the polyproline II helices with profilin were observed. Profilin binds both polyproline II helices and actin and could mediate dendritic spine specific fortification of the actincytoskeleton. These results provide a hypothetical working model for understanding hCPEB3 amyloid formation and its role in memory consolidation. 1. Si K, Linquist S, Kandel ER (2003) Cell 115: 897-891 2. Si K & Kandel ER (2016) Cold Spring Harb Perspect Biol. 8:a021774 3. Hervás R. ..et al.. Si K. (2020) Science 367: 1230-1234 4. Ramírez de Mingo D. ..et al.. Laurents

BACKGROUND: Left ventricular assist devices (LVADs) are implantable pumps that act as a life support therapy for patients with severe heart failure. Despite improving the survival rate, LVAD therapy can carry major complications. Particularly, the flow distortion introduced by the LVAD in the left ventricle (LV) may induce thrombus formation. While previous works have used numerical models to study the impact of multiple variables in the intra-LV stagnation regions, a comprehensive validation analysis has never been executed. The main goal of this work is to present a model of the LV-LVAD system and to design and follow a verification, validation and uncertainty quantification (VVUQ) plan based on the ASME V&V40 and V&V20 standards to ensure credible predictions. METHODS: The experiment used to validate the simulation is the SDSU cardiac simulator, a bench mock-up of the cardiovascular system that allows mimicking multiple operation conditions for the heart-LVAD system. The numerical model is based on Alya, the BSC’s in-house platform for numerical modelling. Alya solves the Navier-Stokes equation with an Arbitrary Lagrangian-Eulerian (ALE) formulation in a deformable ventricle and includes pressure-driven valves, a 0D Windkessel model for the arterial output and a LVAD boundary condition modeled through a dynamic pressure-flow performance curve. The designed VVUQ plan involves: (a) a risk analysis and the associated credibility goals; (b) a verification stage to ensure correctness in the numerical solution procedure; (c) a sensitivity analysis to quantify the impact of the inputs on the four quantities of interest (QoIs) (average aortic root flow , maximum aortic root flow , average LVAD flow , and maximum LVAD flow ); (d) an uncertainty quantification using six validation experiments that include extreme operating conditions. RESULTS: Numerical code verification tests ensured correctness of the solution procedure and numerical calculation verification showed a gri, This project was funded in part by the FDA Critical Path Initiative and by an appointment to the Research Participation Program at the Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, administered by the Oak Ridge Institute for Science, and Education through an interagency agreement between the U.S. Department of Energy and FDA to RAG. MV and AS acknowledge the funding from the project CompBioMed2 (H2020-EU.1.4.1.3. Grant number: 823712), SilicoFCM (H2020-EU.3.1.5. Grant number: 777204), and NEOTEC 2019 - "Generador de Corazones Virtuales" (“Ministerio de Economía y competititvidad”, EXP - 00123159 / SNEO-20191113). AS salary is partially funded by the “Ministerio de Economía y competititvidad” under the Torres Quevedo Program (grant number: PTQ2019-010528). CB salary is partially funded by the Torres Quevedo Program (grant number: PTQ2018-010290). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., Peer Reviewed, Postprint (published version)

Background The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world’s longest running continued surveillance birth cohort providing a unique opportunity to understand life course determinants of myocardial dysfunction as part of MyoFit46–the cardiac sub-study of the NSHD. Methods We aim to recruit 550 NSHD participants of approximately 75 years+ to undertake high-density surface electrocardiographic imaging (ECGI) and stress perfusion cardiovascular magnetic resonance (CMR). Through comprehensive myocardial tissue characterization and 4-dimensional flow we hope to better understand the burden of clinical and subclinical cardiovascular disease. Supercomputers will be used to combine the multi-scale ECGI and CMR datasets per participant. Rarely available, prospectively collected whole-of-life data on exposures, traditional risk factors and multimorbidity will be studied to identify risk trajectories, critical change periods, mediators and cumulative impacts on the myocardium. Discussion By combining well curated, prospectively acquired longitudinal data of the NSHD with novel CMR–ECGI data and sharing these results and associated pipelines with the CMR community, MyoFit46 seeks to transform our understanding of how early, mid and later-life risk factor trajectories interact to determine the state of cardiovascular health in older age. Trial registration: Prospectively registered on ClinicalTrials.gov with trial ID: 19/LO/1774 Multimorbidity Life-Course Approach to Myocardial Health- A Cardiac Sub-Study of the MCRC National Survey of Health and Development (NSHD)., Sources of funding used for staff salaries, CMR scan costs, consumables and relevant travel costs required for data collection, analysis and interpretation: British Heart Foundation special project grant (to G.C. SP/20/2/34841). This study has undergone peer-review by the funding body. Medical Research Council (Core Unit Level Funding:—MC UU 00019/1)., Peer Reviewed, "Article signat per 30 autors/es: Matthew Webber, Debbie Falconer, Mashael AlFarih, George Joy, Fiona Chan, Clare Davie, Lee Hamill Howes, Andrew Wong, Alicja Rapala, Anish Bhuva, Rhodri H. Davies, Christopher Morton, Jazmin Aguado-Sierra, Mariano Vazquez, Xuyuan Tao, Gunther Krausz, Slobodan Tanackovic, Christoph Guger, Hui Xue, Peter Kellman, Iain Pierce, Jonathan Schott, Rebecca Hardy, Nishi Chaturvedi, Yoram Rudy, James C. Moon, Pier D. Lambiase, Michele Orini, Alun D. Hughes & Gabriella Captur", Postprint (published version)

This work intends to study the effect of aortic annulus eccentricity and leaflet rigidity on the performance, thrombogenic risk and calcification risk in bioprosthetic aortic valve replacements (BAVRs). To address these questions, a two-way immersed fluid–structure interaction (FSI) computational model was implemented in a high-performance computing (HPC) multi-physics simulation software, and validated against a well-known FSI benchmark. The aortic valve bioprosthesis model is qualitatively contrasted against experimental data, showing good agreement in closed and open states. Regarding the performance of BAVRs, the model predicts that increasing eccentricities yield lower geometric orifice areas (GOAs) and higher normalized transvalvular pressure gradients (TPGs) for healthy cardiac outputs during systole, agreeing with in vitro experiments. Regions with peak values of residence time are observed to grow with eccentricity in the sinus of Valsalva, indicating an elevated risk of thrombus formation for eccentric configurations. In addition, the computational model is used to analyze the effect of varying leaflet rigidity on both performance, thrombogenic and calcification risks with applications to tissue-engineered prostheses. For more rigid leaflets it predicts an increase in systolic and diastolic TPGs, and decrease in systolic GOA, which translates to decreased valve performance. The peak shear rate and residence time regions increase with leaflet rigidity, but their volume-averaged values were not significantly affected. Peak solid stresses are also analyzed, and observed to increase with rigidity, elevating risk of valve calcification and structural failure. To the authors' knowledge this is the first computational FSI model to study the effect of eccentricity or leaflet rigidity on thrombogenic biomarkers, providing a novel tool to aid device manufacturers and clinical practitioners., This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713673. The research leading to these results has also received funding from “la Caixa” Foundation, with fellowship ID: LCF/BQ/DI18/11660044, and has been co-funded by the project CompBioMed2 (H2020-EU.1.4.1.3. Grant No. 823712), Peer Reviewed, Postprint (published version)