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Browsing by Author "Sego, T. J."
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Item Agent-Based Numerical Methods for 3D Bioprinting in Tissue Engineering(Elsevier, 2018) Sego, T. J.; Moldovan, Nicanor I.; Tovar, Andres; Mechanical Engineering, School of Engineering and TechnologyAdditive manufacturing has contributed significantly to the development of new surgical and diagnostic aids, personalized medical devices, implants, and prostheses. Now, it aspires to the direct digital manufacturing of living tissue, organs, and body parts. This can be achieved using three-dimensional (3D) bioprinting techniques in which the printing medium consists of biomaterials and living cells. Several 3D bioprinting methods are currently available, including inkjet, extrusion, and stereolithography. An emerging approach is the creation three-dimensional cellular patterns by the use of cell spheroids. The optimal application and further development of 3D bioprinting techniques could largely benefit from computational models capable of predicting the complex behavior of the printed cellular structures on multiple scales. This book chapter summarizes the state of the art of computational models in this field, with an emphasis on agent-based approaches and cell spheroid-based 3D bioprinting.Item Computational fluid dynamic analysis of bioprinted self-supporting perfused tissue models(Wiley, 2020-03) Sego, T. J.; Prideaux, Matthew; Sterner, Jane; McCarthy, Brian Paul; Li, Ping; Bonewald, Lynda F.; Ekser, Burcin; Tovar, Andres; Smith, Lester Jeshua; Anatomy and Cell Biology, School of MedicineNatural tissues are incorporated with vasculature, which is further integrated with a cardiovascular system responsible for driving perfusion of nutrient‐rich oxygenated blood through the vasculature to support cell metabolism within most cell‐dense tissues. Since scaffold‐free biofabricated tissues being developed into clinical implants, research models, and pharmaceutical testing platforms should similarly exhibit perfused tissue‐like structures, we generated a generalizable biofabrication method resulting in self‐supporting perfused (SSuPer) tissue constructs incorporated with perfusible microchannels and integrated with the modular FABRICA perfusion bioreactor. As proof of concept, we perfused an MLO‐A5 osteoblast‐based SSuPer tissue in the FABRICA. Although our resulting SSuPer tissue replicated vascularization and perfusion observed in situ, supported its own weight, and stained positively for mineral using Von Kossa staining, our in vitro results indicated that computational fluid dynamics (CFD) should be used to drive future construct design and flow application before further tissue biofabrication and perfusion. We built a CFD model of the SSuPer tissue integrated in the FABRICA and analyzed flow characteristics (net force, pressure distribution, shear stress, and oxygen distribution) through five SSuPer tissue microchannel patterns in two flow directions and at increasing flow rates. Important flow parameters include flow direction, fully developed flow, and tissue microchannel diameters matched and aligned with bioreactor flow channels. We observed that the SSuPer tissue platform is capable of providing direct perfusion to tissue constructs and proper culture conditions (oxygenation, with controllable shear and flow rates), indicating that our approach can be used to biofabricate tissue representing primary tissues and that we can model the system in silico.Item A Heuristic Computational Model of Basic Cellular Processes and Oxygenation during Spheroid-Dependent Biofabrication(IOP, 2017) Sego, T. J.; Kasacheuski, Uladzimir; Hauersperger, Daniel; Tovar, Andres; Moldovan, Nicanor I.; Biomedical Engineering, School of Engineering and TechnologyAn emerging approach in biofabrication is the creation of 3D tissue constructs through scaffold-free, cell spheroid-only methods. The basic mechanism in this technology is spheroid fusion, which is driven by the minimization of energy, the same biophysical mechanism that governs spheroid formation. However, other factors such as oxygen and metabolite accessibility within spheroids impact on spheroid properties and their ability to form larger-scale structures. The goal of our work is to develop a simulation platform eventually capable of predicting the conditions that minimize metabolism-related cell loss within spheroids. To describe the behavior and dynamic properties of the cells in response to their neighbors and to transient nutrient concentration fields, we developed a hybrid discrete-continuous heuristic model, combining a cellular Potts-type approach with field equations applied to a randomly populated spheroid cross-section of prescribed cell-type constituency. This model allows for the description of: (i) cellular adhesiveness and motility; (ii) interactions with concentration fields, including diffusivity and oxygen consumption; and (iii) concentration-dependent, stochastic cell dynamics, driven by metabolite-dependent cell death. Our model readily captured the basic steps of spheroid-based biofabrication (as specifically dedicated to scaffold-free bioprinting), including intra-spheroid cell sorting (both in 2D and 3D implementations), spheroid defect closure, and inter-spheroid fusion. Moreover, we found that when hypoxia occurring at the core of the spheroid was set to trigger cell death, this was amplified upon spheroid fusion, but could be mitigated by external oxygen supplementation. In conclusion, optimization and further development of scaffold-free bioprinting techniques could benefit from our computational model which is able to simultaneously account for both cellular dynamics and metabolism in constructs obtained by scaffold-free biofabrication.Item Modeling Progressive Damage Accumulation in Bone Remodeling Explains the Thermodynamic Basis of Bone Resorption by Overloading(Springer, 2020-10-10) Sego, T. J.; Hsu, Yung-Ting; Chu, Tien-Min; Tovar, Andres; Cariology, Operative Dentistry and Dental Public Health, School of DentistryComputational modeling of skeletal tissue seeks to predict the structural adaptation of bone in response to mechanical loading. The theory of continuum damage-repair, a mathematical description of structural adaptation based on principles of damage mechanics, continues to be developed and utilized for the prediction of long-term peri-implant outcomes. Despite its technical soundness, CDR does not account for the accumulation of mechanical damage and irreversible deformation. In this work, a nonlinear mathematical model of independent damage accumulation and plastic deformation is developed in terms of the CDR formulation. The proposed model incorporates empirical correlations from uniaxial experiments. Supporting elements of the model are derived, including damage and yielding criteria, corresponding consistency conditions, and the basic, necessary forms for integration during loading. Positivity of mechanical dissipation due to damage is proved, while strain-based, associative plastic flow and linear hardening describe post-yield behavior. Calibration of model parameters to the empirical correlations from which the model was derived is then accomplished. Results of numerical experiments on a point-wise specimen show that damage and plasticity inhibit bone formation by dissipation of energy available to biological processes, leading to material failure that would otherwise be predicted to experience a net gain of bone.Item On the Significance and Predicted Functional Effects of the Crown-to-Implant Ratio: A Finite Element Study of Long-Term Implant Stability Using High-Resolution, Nonlinear Numerical Analysis(ASME, 2016-04) Sego, T. J.; Hsu, Yung-Ting; Chu, Tien-Min Gabriel; Tovar, Andres; Mechanical Engineering, School of Engineering and TechnologyWith the rising popularity of short dental implants, the effects of the crown-to-implant (C/I) ratio on stress and strain distributions remain controversial. Previous research disagrees on results of interest and level of necessary technical detail. The present study aimed to evaluate the strain distribution and its functional implications in a single implant-supported crown with various C/I ratios placed in the maxillary molar region. A high-fidelity, nonlinear finite-element model was generated to simulate multiple clinical scenarios by laterally loading a set of single implants with various implant lengths (IL) and crown heights (CH). Strain distribution and maximum equivalent strain (MES) were analyzed to evaluate the effects and significance of the CH, IL and C/I. Predicted functional response to strain at the implant interface was analyzed by interface surface area. Results. Results were evaluated according to the mechanostat hypothesis to predict functional response. Overloading and effects of strain concentrations were more prevalent with increasing C/I. Overloading was predicted for all configurations to varying degrees, and increased with decreasing IL. Fracture in trabecular bone was predicted for at least one C/I and all IL of 10 mm or less. Higher C/I ratios and lower IL increase the risk of overloading and fracture. Increasing C/I augments the functional effects of other implant design factors. Greater C/I ratios may be achieved with implant designs that induce less significant strain concentrations.Item Unification of aggregate growth models by emergence from cellular and intracellular mechanisms(Royal Society, 2020-08-12) Sego, T. J.; Glazier, James A.; Tovar, Andres; Mechanical and Energy Engineering, School of Engineering and TechnologyMulticellular aggregate growth is regulated by nutrient availability and removal of metabolites, but the specifics of growth dynamics are dependent on cell type and environment. Classical models of growth are based on differential equations. While in some cases these classical models match experimental observations, they can only predict growth of a limited number of cell types and so can only be selectively applied. Currently, no classical model provides a general mathematical representation of growth for any cell type and environment. This discrepancy limits their range of applications, which a general modelling framework can enhance. In this work, a hybrid cellular Potts model is used to explain the discrepancy between classical models as emergent behaviours from the same mathematical system. Intracellular processes are described using probability distributions of local chemical conditions for proliferation and death and simulated. By fitting simulation results to a generalization of the classical models, their emergence is demonstrated. Parameter variations elucidate how aggregate growth may behave like one classical growth model or another. Three classical growth model fits were tested, and emergence of the Gompertz equation was demonstrated. Effects of shape changes are demonstrated, which are significant for final aggregate size and growth rate, and occur stochastically.Item Unification of aggregate growth models by emergence from cellular and intracellular mechanisms(The Royal Society Publishing, 2020-08) Sego, T. J.; Glazier, James A.; Tovar, Andres; Mechanical and Energy Engineering, School of Engineering and TechnologyMulticellular aggregate growth is regulated by nutrient availability and removal of metabolites, but the specifics of growth dynamics are dependent on cell type and environment. Classical models of growth are based on differential equations. While in some cases these classical models match experimental observations, they can only predict growth of a limited number of cell types and so can only be selectively applied. Currently, no classical model provides a general mathematical representation of growth for any cell type and environment. This discrepancy limits their range of applications, which a general modelling framework can enhance. In this work, a hybrid cellular Potts model is used to explain the discrepancy between classical models as emergent behaviours from the same mathematical system. Intracellular processes are described using probability distributions of local chemical conditions for proliferation and death and simulated. By fitting simulation results to a generalization of the classical models, their emergence is demonstrated. Parameter variations elucidate how aggregate growth may behave like one classical growth model or another. Three classical growth model fits were tested, and emergence of the Gompertz equation was demonstrated. Effects of shape changes are demonstrated, which are significant for final aggregate size and growth rate, and occur stochastically.