Computational Modeling of Human Mesenchymal Stromal Cell Proliferation and Extra-Cellular Matrix Production in 3D Porous Scaffolds in a Perfusion Bioreactor: The Effect of Growth Factors

Analysis of the role of perfusion, mechanical, and electrical stimulation in bioreactors for cardiac tissue engineering

Since cardiovascular diseases (CVDs) are globally one of the leading causes of death, of which myocardial infarction (MI) can cause irreversible damage and decrease survivors' quality of life, novel therapeutics are needed. Current approaches such as organ transplantation do not fully restore cardiac function or are limited. As a valuable strategy, tissue engineering seeks to obtain constructs that resemble myocardial tissue, vessels, and heart valves using cells, biomaterials as scaffolds, biochemical and physical stimuli. The latter can be induced using a bioreactor mimicking the heart's physiological environment. An extensive review of bioreactors providing perfusion, mechanical and electrical stimulation, as well as the combination of them is provided. An analysis of the stimulations' mechanisms and modes that best suit cardiac construct culture is developed. Finally, we provide insights into bioreactor configuration and culture assessment properties that need to be elucidated for its clinical translation.

In silico model development and optimization of in vitro lung cell population growth

Tissue engineering predominantly relies on trial and error in vitro and ex vivo experiments to develop protocols and bioreactors to generate functional tissues. As an alternative, in silico methods have the potential to significantly reduce the timelines and costs of experimental programs for tissue engineering. In this paper, we propose a methodology to formulate, select, calibrate, and test mathematical models to predict cell population growth as a function of the biochemical environment and to design optimal experimental protocols for model inference of in silico model parameters. We systematically combine methods from the experimental design, mathematical statistics, and optimization literature to develop unique and explainable mathematical models for cell population dynamics. The proposed methodology is applied to the development of this first published model for a population of the airway-relevant bronchio-alveolar epithelial (BEAS-2B) cell line as a function of the concentration of metabolic-related biochemical substrates. The resulting model is a system of ordinary differential equations that predict the temporal dynamics of BEAS-2B cell populations as a function of the initial seeded cell population and the glucose, oxygen, and lactate concentrations in the growth media, using seven parameters rigorously inferred from optimally designed in vitro experiments.

A comprehensive overview of advanced dynamic in vitro intestinal and hepatic cell culture models

Orally administered drugs pass through the gastrointestinal tract before being absorbed in the small intestine and metabolised in the liver. To test the efficacy and toxicity of drugs, animal models are often employed; however, they are not suitable for investigating drug-tissue interactions and making reliable predictions, since the human organism differs drastically from animals in terms of absorption, distribution, metabolism and excretion of substances. Likewise, simple static in vitro cell culture systems currently used in preclinical drug screening often do not resemble the native characteristics of biological barriers. Dynamic models, on the other hand, provide in vivo-like cell phenotypes and functionalities that offer great potential for safety and efficacy prediction. Herein, current microfluidic in vitro intestinal and hepatic models are reviewed, namely single- and multi-tissue micro-bioreactors, which are associated with different methods of cell cultivation, i.e., scaffold-based versus scaffold-free.

An Empirical Model Linking Physico-Chemical Biomaterial Characteristics to Intra-Oral Bone Formation

Facial trauma, bone resection due to cancer, periodontal diseases, and bone atrophy following tooth extraction often leads to alveolar bone defects that require bone regeneration in order to restore dental function. Guided bone regeneration using synthetic biomaterials has been suggested as an alternative approach to autologous bone grafts. The efficiency of bone substitute materials seems to be influenced by their physico-chemical characteristics; however, the debate is still ongoing on what constitutes optimal biomaterial characteristics. The purpose of this study was to develop an empirical model allowing the assessment of the bone regeneration potential of new biomaterials on the basis of their physico-chemical characteristics, potentially giving directions for the design of a new generation of dental biomaterials. A quantitative data set was built composed of physico-chemical characteristics of seven commercially available intra-oral bone biomaterials and their in vivo response. This empirical model allowed the identification of the construct parameters driving optimized bone formation. The presented model provides a better understanding of the influence of driving biomaterial properties in the bone healing process and can be used as a tool to design bone biomaterials with a more controlled and custom-made composition and structure, thereby facilitating and improving the clinical translation.

Perfusion of MC3T3E1 Preosteoblast Spheroids within Polysaccharide-Based Hydrogel Scaffolds: An Experimental and Numerical Study at the Bioreactor Scale

The traditional 3D culture systems in vitro lack the biological and mechanical spatiotemporal stimuli characteristic to native tissue development. In our study, we combined porous polysaccharide-based hydrogel scaffolds with a bioreactor-type perfusion device that generates favorable mechanical stresses while enhancing nutrient transfers. MC3T3E1 mouse osteoblasts were seeded in the scaffolds and cultivated for 3 weeks under dynamic conditions at a perfusion rate of 10 mL min^-1. The spatial distribution of the cells labeled with superparamagnetic iron oxide nanoparticles was visualized by MRI. Confocal microscopy was used to assess cell numbers, their distribution inside the scaffolds, cell viability, and proliferation. The oxygen diffusion coefficient in the hydrogel was measured experimentally. Numerical simulations of the flow and oxygen transport within the bioreactor were performed using a lattice Boltzmann method with a two-relaxation time scheme. Last, the influence of cell density and spheroid size on cell oxygenation was investigated. The cells spontaneously organized into spheroids with a diameter of 30-100 μm. Cell viability remained unchanged under dynamic conditions but decreased under static culture. The cell proliferation (Ki67 expression) in spheroids was not observed. The flow simulation showed that the local fluid velocity reached 27 mm s^-1 at the height where the cross-sectional area of the flow was the smallest. The shear stress exerted by the fluid on the scaffolds may locally rise to 100 mPa, compared with the average value of 25 mPa. The oxygen diffusion coefficient in the hydrogel was 1.6×10-9 m² s^-1. The simulation of oxygen transport and consumption confirmed that the cells in spheroids did not suffer from hypoxia when the bioreactor was perfused at 10 mL min^-1, and suggested the existence of optimal spheroid size and spacing for appropriate oxygenation. Collectively, these findings enabled us to define the optimal conditions inside the bioreactor for an efficient in vitro cell organization and survival in spheroids, which are paramount to future applications with organoids.

Bioengineering of bone tissues using bioreactors for modulation of mechano-sensitivity in bone

Since the last decade, significant developments have been made in the area of bone tissue engineering associated with the emergence of novel biomaterials as well as techniques of scaffold fabrication. Despite all these developments, the translation from research findings to clinical applications is still very limited. Manufacturing the designed tissue constructs in a scalable manner remains the most challenging aspect. This bottleneck could be overcome by using bioreactors for the manufacture of these tissue constructs. In this review, a current scenario of bone injuries/defects and the cause of the translational gap between laboratory research and clinical use has been emphasized. Furthermore, various bioreactors being used in the area of bone tissue regeneration in recent studies have been highlighted along with their advantages and limitations. A vivid literature survey on the ideal attributes of bioreactors has been accounted, viz. dynamic, versatile, automated, reproducible and commercialization aspects. Additionally, the illustration of computational approaches that should be combined with bone tissue engineering experiments using bioreactors to simulate and optimize cellular growth in bone tissue constructs has also been done extensively.

Personalized Volumetric Tissue Generation by Enhancing Multiscale Mass Transport through 3D Printed Scaffolds in Perfused Bioreactors

Engineered tissues provide an alternative to graft material, circumventing the use of donor tissue such as autografts or allografts and non-physiological synthetic implants. However, their lack of vasculature limits the growth of volumetric tissue more than several millimeters thick which limits their success post-implantation. Perfused bioreactors enhance nutrient mass transport inside lab-grown tissue but remain poorly customizable to support the culture of personalized implants. Here, a multiscale framework of computational fluid dynamics (CFD), additive manufacturing, and a perfusion bioreactor system are presented to engineer personalized volumetric tissue in the laboratory. First, microscale 3D printed scaffold pore geometries are designed and 3D printed to characterize media perfusion through CFD and experimental fluid testing rigs. Then, perfusion bioreactors are custom-designed to combine 3D printed scaffolds with flow-focusing inserts in patient-specific shapes as simulated using macroscale CFD. Finally, these computationally optimized bioreactor-scaffold assemblies are additively manufactured and cultured with pre-osteoblast cells for 7, 20, and 24 days to achieve tissue growth in the shape of human calcaneus bones of 13 mL volume and 1 cm thickness. This framework enables an intelligent model-based design of 3D printed scaffolds and perfusion bioreactors which enhances nutrient transport for long-term volumetric tissue growth in personalized implant shapes. The novel methods described here are readily applicable for use with different cell types, biomaterials, and scaffold microstructures to research therapeutic solutions for a wide range of tissues.

Implementing computational modeling in tissue engineering: where disciplines meet

In recent years, the mathematical and computational sciences have developed novel methodologies and insights that can aid in designing advanced bioreactors, microfluidic set-ups or organ-on-chip devices, in optimizing culture conditions, or predicting long-term behavior of engineered tissues in vivo. In this review, we introduce the concept of computational models and how they can be integrated in an interdisciplinary workflow for Tissue Engineering and Regenerative Medicine (TERM). We specifically aim this review of general concepts and examples at experimental scientists with little or no computational modeling experience. We also describe the contribution of computational models in understanding TERM processes and in advancing the TERM field by providing novel insights.

Towards the Experimentally-Informed In Silico Nozzle Design Optimization for Extrusion-Based Bioprinting of Shear-Thinning Hydrogels

Research in bioprinting is booming due to its potential in addressing several manufacturing challenges in regenerative medicine. However, there are still many hurdles to overcome to guarantee cell survival and good printability. For the 3D extrusion-based bioprinting, cell viability is amongst one of the lowest of all the bioprinting techniques and is strongly influenced by various factors including the shear stress in the print nozzle. The goal of this study is to quantify, by means of in silico modeling, the mechanical environment experienced by the bioink during the printing process. Two ubiquitous nozzle shapes, conical and blunted, were considered, as well as three common hydrogels with material properties spanning from almost Newtonian to highly shear-thinning materials following the power-law behavior: Alginate-Gelatin, Alginate and PF127. Comprehensive in silico testing of all combinations of nozzle geometry variations and hydrogels was achieved by combining a design of experiments approach (DoE) with a computational fluid dynamics (CFD) of the printing process, analyzed through a machine learning approach named Gaussian Process. Available experimental results were used to validate the CFD model and justify the use of shear stress as a surrogate for cell survival in this study. The lower and middle nozzle radius, lower nozzle length and the material properties, alone and combined, were identified as the major influencing factors affecting shear stress, and therefore cell viability, during printing. These results were successfully compared with those of reported experiments testing viability for different nozzle geometry parameters under constant flow rate or constant pressure. The in silico 3D bioprinting platform developed in this study offers the potential to assist and accelerate further development of 3D bioprinting.

A Systematically Reduced Mathematical Model for Organoid Expansion

Organoids are three-dimensional multicellular tissue constructs. When cultured in vitro, they recapitulate the structure, heterogeneity, and function of their in vivo counterparts. As awareness of the multiple uses of organoids has grown, e.g. in drug discovery and personalised medicine, demand has increased for low-cost and efficient methods of producing them in a reproducible manner and at scale. Here we focus on a bioreactor technology for organoid production, which exploits fluid flow to enhance mass transport to and from the organoids. To ensure large numbers of organoids can be grown within the bioreactor in a reproducible manner, nutrient delivery to, and waste product removal from, the organoids must be carefully controlled. We develop a continuum mathematical model to investigate how mass transport within the bioreactor depends on the inlet flow rate and cell seeding density, focusing on the transport of two key metabolites: glucose and lactate. We exploit the thin geometry of the bioreactor to systematically simplify our model. This significantly reduces the computational cost of generating model solutions, and provides insight into the dominant mass transport mechanisms. We test the validity of the reduced models by comparison with simulations of the full model. We then exploit our reduced mathematical model to determine, for a given inlet flow rate and cell seeding density, the evolution of the spatial metabolite distributions throughout the bioreactor. To assess the bioreactor transport characteristics, we introduce metrics quantifying glucose conversion (the ratio between the total amounts of consumed and supplied glucose), the maximum lactate concentration, the proportion of the bioreactor with intolerable lactate concentrations, and the time when intolerable lactate concentrations are first experienced within the bioreactor. We determine the dependence of these metrics on organoid-line characteristics such as proliferation rate and rate of glucose consumption per cell. Finally, for a given organoid line, we determine how the distribution of metabolites and the associated metrics depend on the inlet flow rate. Insights from this study can be used to inform bioreactor operating conditions, ultimately improving the quality and number of bioreactor-expanded organoids.

A Review of Zein as a Potential Biopolymer for Tissue Engineering and Nanotechnological Applications

Tissue engineering (TE) is one of the most challenging fields of research since it provides current alternative protocols and materials for the regeneration of damaged tissue. The success of TE has been mainly related to the right selection of nano-sized biocompatible materials for the development of matrixes, which can display excellent anatomical structure, functionality, mechanical properties, and histocompatibility. Today, the research community has paid particular attention to zein as a potential biomaterial for TE applications and nanotechnological approaches. Considering the properties of zein and the advances in the field, there is a need to reviewing the current state of the art of using this natural origin material for TE and nanotechnological applications. Therefore, the goal of this review paper is to elucidate the latest (over the last five years) applications and development works in the field, including TE, encapsulations of drugs, food, pesticides and bandaging for external wounds. In particular, attention has been focused on studies proving new breakthroughs and findings. Also, a complete background of zein’s properties and features are addressed.