Browsing by Author "Sego, T.J."

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    Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2
    (MDPI, 2022-03-14) Gianlupi, Juliano Ferrari; Mapder, Tarunendu; Sego, T.J.; Sluka, James P.; Quinney, Sara K.; Craig, Morgan; Stratford, Robert E., Jr.; Glazier, James A.; Medicine, School of Medicine
    We extend our established agent-based multiscale computational model of infection of lung tissue by SARS-CoV-2 to include pharmacokinetic and pharmacodynamic models of remdesivir. We model remdesivir treatment for COVID-19; however, our methods are general to other viral infections and antiviral therapies. We investigate the effects of drug potency, drug dosing frequency, treatment initiation delay, antiviral half-life, and variability in cellular uptake and metabolism of remdesivir and its active metabolite on treatment outcomes in a simulated patch of infected epithelial tissue. Non-spatial deterministic population models which treat all cells of a given class as identical can clarify how treatment dosage and timing influence treatment efficacy. However, they do not reveal how cell-to-cell variability affects treatment outcomes. Our simulations suggest that for a given treatment regime, including cell-to-cell variation in drug uptake, permeability and metabolism increase the likelihood of uncontrolled infection as the cells with the lowest internal levels of antiviral act as super-spreaders within the tissue. The model predicts substantial variability in infection outcomes between similar tissue patches for different treatment options. In models with cellular metabolic variability, antiviral doses have to be increased significantly (>50% depending on simulation parameters) to achieve the same treatment results as with the homogeneous cellular metabolism.
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    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
    (Office of the Vice Chancellor for Research, 2016-04-08) Sego, T.J.; Hsu, Yung-Ting; Chu, Tien-Min Gabriel; Tovar, Andres
    Background. As the use of short dental implants becomes increasingly popular, the effects of the crown-to-implant (C/I) ratio on stress and strain distributions remain controversial. Previous studies in literature disagree on results of interest and level of necessary technical detail. Purpose. The present study sought to evaluate the strain distribution and assess its functional implications in a single implant-supported crown with various C/I ratios placed in the maxillary molar region. Materials and Methods. A high-fidelity, nonlinear finite-element model was developed to simulate multiple clinical scenarios by laterally loading a set of single implants with various implant lengths and crown heights. Strain distribution and maximum equivalent strain were analyzed to evaluate the effects and significance of the crown height, implant length and C/I ratio. The consistency of predicted functional responses to resulting strain at the implant interface were analyzed by interface surface area. Results. Results were evaluated according to the mechanostat hypothesis to predict functional response to strain. Overloading and effects of strain concentrations were more prevalent with increasing C/I ratios. Overloading was predicted for all configurations to varying degrees, and increased with decreasing implant lengths. Fracture in trabecular bone was predicted for at least one C/I ratio and all implant lengths of 10 mm or less. Conclusions. Higher C/I ratios and lower implant lengths increase the biomechanical risks of overloading and fracture. Increasing C/I ratios augment the functional effects of other implant design factors, particularly implant interface features. Greater C/I ratios may be achieved with implant designs that induce less significant strain concentrations.