Method for finding metabolic properties based on the general growth law. Liver examples. A General framework for biological modeling

We propose a method for finding metabolic parameters of cells, organs and whole organisms, which is based on the earlier discovered general growth law. Based on the obtained results and analysis of available biological models, we propose a general framework for modeling biological phenomena and discuss how it can be used in Virtual Liver Network project. The foundational idea of the study is that growth of cells, organs, systems and whole organisms, besides biomolecular machinery, is influenced by biophysical mechanisms acting at different scale levels. In particular, the general growth law uniquely defines distribution of nutritional resources between maintenance needs and biomass synthesis at each phase of growth and at each scale level. We exemplify the approach considering metabolic properties of growing human and dog livers and liver transplants. A procedure for verification of obtained results has been introduced too. We found that two examined dogs have high metabolic rates consuming about 0.62 and 1 gram of nutrients per cubic centimeter of liver per day, and verified this using the proposed verification procedure. We also evaluated consumption rate of nutrients in human livers, determining it to be about 0.088 gram of nutrients per cubic centimeter of liver per day for males, and about 0.098 for females. This noticeable difference can be explained by evolutionary development, which required females to have greater liver processing capacity to support pregnancy. We also found how much nutrients go to biomass synthesis and maintenance at each phase of liver and liver transplant growth. Obtained results demonstrate that the proposed approach can be used for finding metabolic characteristics of cells, organs, and whole organisms, which can further serve as important inputs for many applications in biology (protein expression), biotechnology (synthesis of substances), and medicine.Comment: 20 pages, 6 figures, 4 table

Natural-based hydrogels for tissue engineering applications

In the field of tissue engineering and regenerative medicine, hydrogels are used as biomaterials to support cell attachment and promote tissue regeneration due to their unique biomimetic characteristics. The use of natural-origin materials significantly influenced the origin and progress of the field due to their ability to mimic the native tissuesâ extracellular matrix and biocompatibility. However, the majority of these natural materials failed to provide satisfactory cues to guide cell differentiation toward the formation of new tissues. In addition, the integration of technological advances, such as 3D printing, microfluidics and nanotechnology, in tissue engineering has obsoleted the first generation of natural-origin hydrogels. During the last decade, a new generation of hydrogels has emerged to meet the specific tissue necessities, to be used with state-of-the-art techniques and to capitalize the intrinsic characteristics of natural-based materials. In this review, we briefly examine important hydrogel crosslinking mechanisms. Then, the latest developments in engineering natural-based hydrogels are investigated and major applications in the field of tissue engineering and regenerative medicine are highlighted. Finally, the current limitations, future challenges and opportunities in this field are discussed to encourage realistic developments for the clinical translation of tissue engineering strategies.Authors acknowledge financial support from the European Union Framework Programme for Research and Innovation Horizon 2020 under European Research Council grant agreement No. 772817; FCT (Fundação para a Ciência e a Tecnologia) for individual fellowship CEECIND/01375/2017 (MGF); FCT for project PTDC/NAN-MAT/30595/2017; Xunta de Galicia for postdoctoral fellowship ED481B-2019-025 (AP); Norwegian Research Council (NFR) for project No. 287953

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Development of Shear-Thinning and Self-Healing Hydrogels Through Guest-Host Interactions for Biomedical Applications

Hydrogels have emerged as an invaluable class of materials for biomedical applications, owing in part to their utility as structural, bioinstructive, and cell-laden implants that mimic many aspects of native tissues. Despite their many positive attributes, conventional hydrogels face numerous challenges toward translational therapies, including difficulty in delivery (i.e., invasive implantation) as well as limited control over biophysical properties (i.e., porosity, degradation, and strength). To address these challenges, the overall goal of this dissertation was the development of a class of supramolecular hydrogels that can be implanted in vivo by simple injection and that have tunable properties — either innate to the system or achieved through additional modifications. Toward this, we developed guest-host (GH) hydrogels that undergo supramolecular assembly through complexation of hyaluronic acid (HA) separately modified by adamantane (Ad-HA, guest) and β-cyclodextrin (CD-HA, host). Modular modifications were made to GH hydrogels to enable tuning of biophysical properties, including the incorporation of matrix-metalloproteinase cleavable peptides between HA and Ad to form enzymatically degradable assemblies. Additionally, dual-crosslinking (DC) of methacrylated CD-HA (CD-MeHA) and thiolated Ad-HA (Ad-HA-SH) by Michael addition subsequent to GH assembly was explored to stiffen hydrogels in vivo following injection. Finally, injectable and tough double network (DN) hydrogels were fabricated, where GH hydrogels were formed in the presence of an interpenetrating covalent network (methacrylated HA, MeHA) crosslinked by Michael addition with a dithiol under cytocompatible conditions. Both GH and DC hydrogels were further explored in vivo, with application to attenuate the maladaptive left ventricular (LV) remodeling that occurs following myocardial infarction (MI) that can result in heart failure. DC hydrogels reduced stress within the infarct region, prevented early ventricular expansion and thereby ameliorated progressive LV remodeling. Moreover, the preservation of myocardial geometry reduced incidence and severity of ischemic mitral regurgitation — an undesirable and devastating consequence of LV remodeling. Overall, the body of work represents a novel approach to engineer biomaterials with unique properties toward biomedical therapies

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Modeling and Simulation in Engineering

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results