Browsing by Author "Glazier, James A."

Now showing 1 - 8 of 8
  • Thumbnail Image
    Item
    A computational model of liver tissue damage and repair
    (Public Library of Science, 2020-12-21) Adhyapok, Priyom; Fu, Xiao; Sluka, James P.; Clendenon, Sherry G.; Sluka, Victoria D.; Wang, Zemin; Dunn, Kenneth; Klaunig, James E.; Glazier, James A.; Medicine, School of Medicine
    Drug induced liver injury (DILI) and cell death can result from oxidative stress in hepatocytes. An initial pattern of centrilobular damage in the APAP model of DILI is amplified by communication from stressed cells and immune system activation. While hepatocyte proliferation counters cell loss, high doses are still lethal to the tissue. To understand the progression of disease from the initial damage to tissue recovery or death, we computationally model the competing biological processes of hepatocyte proliferation, necrosis and injury propagation. We parametrize timescales of proliferation (α), conversion of healthy to stressed cells (β) and further sensitization of stressed cells towards necrotic pathways (γ) and model them on a Cellular Automaton (CA) based grid of lattice sites. 1D simulations show that a small α/β (fast proliferation), combined with a large γ/β (slow death) have the lowest probabilities of tissue survival. At large α/β, tissue fate can be described by a critical γ/β* ratio alone; this value is dependent on the initial amount of damage and proportional to the tissue size N. Additionally, the 1D model predicts a minimum healthy population size below which damage is irreversible. Finally, we compare 1D and 2D phase spaces and discuss outcomes of bistability where either survival or death is possible, and of coexistence where simulated tissue never completely recovers or dies but persists as a mixture of healthy, stressed and necrotic cells. In conclusion, our model sheds light on the evolution of tissue damage or recovery and predicts potential for divergent fates given different rates of proliferation, necrosis, and injury propagation.
  • Thumbnail Image
    Item
    Mitochondrial depolarization and repolarization in the early stages of acetaminophen hepatotoxicity in mice
    (Elsevier, 2020-06) Dunn, Kenneth W.; Martinez, Michelle M.; Wang, Zemin; Mang, Henry E.; Clendenon, Sherry G.; Sluka, James P.; Glazier, James A.; Klaunig, James E.; Medicine, School of Medicine
    Mitochondrial injury and depolarization are primary events in acetaminophen hepatotoxicity. Previous studies have shown that restoration of mitochondrial function in surviving hepatocytes, which is critical to recovery, is at least partially accomplished via biogenesis of new mitochondria. However, other studies indicate that mitochondria also have the potential to spontaneously repolarize. Although repolarization was previously observed only at a sub-hepatotoxic dose of acetaminophen, we postulated that mitochondrial repolarization in hepatocytes outside the centrilobular regions of necrosis might contribute to recovery of mitochondrial function following acetaminophen-induced injury. Our studies utilized longitudinal intravital microscopy of millimeter-scale regions of the mouse liver to characterize the spatio-temporal relationship between mitochondrial polarization and necrosis early in acetaminophen-induced liver injury. Treatment of male C57BL/6J mice with a single intraperitoneal 250 mg/kg dose of acetaminophen resulted in hepatotoxicity that was apparent histologically within 2 h of treatment, leading to 20 and 60-fold increases in serum aspartate aminotransferase and alanine aminotransferase, respectively, within 6 h. Intravital microscopy of the livers of mice injected with rhodamine123, TexasRed-dextran, propidium iodide and Hoechst 33342 detected centrilobular foci of necrosis within extended regions of mitochondrial depolarization within 2 h of acetaminophen treatment. Although regions of necrosis were more apparent 6 h after acetaminophen treatment, the vast majority of hepatocytes with depolarized mitochondria did not progress to necrosis, but rather recovered mitochondrial polarization within 6 h. Recovery of mitochondrial function following acetaminophen hepatotoxicity thus involves not only biogenesis of new mitochondria, but also repolarization of existing mitochondria. These studies also revealed a spatial distribution of necrosis and mitochondrial depolarization whose single-cell granularity is inconsistent with the hypothesis that communication between neighboring cells plays an important role in the propagation of necrosis during the early stages of APAP hepatotoxicity. Small islands of healthy, intact cells were frequently found surrounded by necrotic cells, and small islands of necrotic cells were frequently found surrounded by healthy, intact cells. Time-series studies demonstrated that these "islands", consisting in some cases of single cells, are persistent; over a period of hours, injury does not spread from individual necrotic cells to their neighbors.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    A simple automated method for continuous fieldwise measurement of microvascular hemodynamics
    (Elsevier, 2019-05) Clendenon, Sherry G.; Fu, Xiao; Von Hoene, Robert A.; Clendenon, Jeffrey L.; Sluka, James P.; Winfree, Seth; Mang, Henry; Martinez, Michelle; Filson, Adele J.; Klaunig, James E.; Glazier, James A.; Dunn, Kenneth W.; Medicine, School of Medicine
    Microvascular perfusion dynamics are vital to physiological function and are frequently dysregulated in injury and disease. Typically studies measure microvascular flow in a few selected vascular segments over limited time, failing to capture spatial and temporal variability. To quantify microvascular flow in a more complete and unbiased way we developed STAFF (Spatial Temporal Analysis of Fieldwise Flow), a macro for FIJI open-source image analysis software. Using high-speed microvascular flow movies, STAFF generates kymographs for every time interval for every vascular segment, calculates flow velocities from red blood cell shadow angles, and outputs the data as color-coded velocity map movies and spreadsheets. In untreated mice, analyses demonstrated profound variation even between adjacent sinusoids over seconds. In acetaminophen-treated mice we detected flow reduction localized to pericentral regions. STAFF is a powerful new tool capable of providing novel insights by enabling measurement of the complex spatiotemporal dynamics of microvascular flow.
  • Thumbnail Image
    Item
    Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD
    (Springer (Biomed Central Ltd.), 2016-11-21) de Almeida, Rita M. C.; Clendenon, Sherry G.; Richards, William G.; Boedigheimer, Michael; Damore, Michael; Rossetti, Sandro; Harris, Peter C.; Herbert, Britney-Shea; Xu, Wei Min; Wandinger-Ness, Angela; Ward, Heather H.; Glazier, James A.; Bacallao, Robert L.; Department of Medicine, School of Medicine
    BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) causes progressive loss of renal function in adults as a consequence of the accumulation of cysts. ADPKD is the most common genetic cause of end-stage renal disease. Mutations in polycystin-1 occur in 87% of cases of ADPKD and mutations in polycystin-2 are found in 12% of ADPKD patients. The complexity of ADPKD has hampered efforts to identify the mechanisms underlying its pathogenesis. No current FDA (Federal Drug Administration)-approved therapies ameliorate ADPKD progression. RESULTS: We used the de Almeida laboratory's sensitive new transcriptogram method for whole-genome gene expression data analysis to analyze microarray data from cell lines developed from cell isolates of normal kidney and of both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We compared results obtained using standard Ingenuity Volcano plot analysis, Gene Set Enrichment Analysis (GSEA) and transcriptogram analysis. Transcriptogram analysis confirmed the findings of Ingenuity, GSEA, and published analysis of ADPKD kidney data and also identified multiple new expression changes in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways related to cell growth, cell death, genetic information processing, nucleotide metabolism, signal transduction, immune response, response to stimulus, cellular processes, ion homeostasis and transport and cofactors, vitamins, amino acids, energy, carbohydrates, drugs, lipids, and glycans. Transcriptogram analysis also provides significance metrics which allow us to prioritize further study of these pathways. CONCLUSIONS: Transcriptogram analysis identifies novel pathways altered in ADPKD, providing new avenues to identify both ADPKD's mechanisms of pathogenesis and pharmaceutical targets to ameliorate the progression of the disease.
  • Thumbnail Image
    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 Technology
    Multicellular 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.
  • Thumbnail Image
    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 Technology
    Multicellular 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.
  • Thumbnail Image
    Item
    Virtual-tissue computer simulations define the roles of cell adhesion and proliferation in the onset of kidney cystic disease
    (The American Society for Cell Biology, 2016-11-07) Belmonte, Julio M.; Clendenon, Sherry G.; Oliveira, Guilherme M.; Swat, Maciej H.; Greene, Evan V.; Jeyaraman, Srividhya; Glazier, James A.; Bacallao, Robert L.; Department of Medicine, IU School of Medicine
    In autosomal dominant polycystic kidney disease (ADPKD), cysts accumulate and progressively impair renal function. Mutations in PKD1 and PKD2 genes are causally linked to ADPKD, but how these mutations drive cell behaviors that underlie ADPKD pathogenesis is unknown. Human ADPKD cysts frequently express cadherin-8 (cad8), and expression of cad8 ectopically in vitro suffices to initiate cystogenesis. To explore cell behavioral mechanisms of cad8-driven cyst initiation, we developed a virtual-tissue computer model. Our simulations predicted that either reduced cell-cell adhesion or reduced contact inhibition of proliferation triggers cyst induction. To reproduce the full range of cyst morphologies observed in vivo, changes in both cell adhesion and proliferation are required. However, only loss-of-adhesion simulations produced morphologies matching in vitro cad8-induced cysts. Conversely, the saccular cysts described by others arise predominantly by decreased contact inhibition, that is, increased proliferation. In vitro experiments confirmed that cell-cell adhesion was reduced and proliferation was increased by ectopic cad8 expression. We conclude that adhesion loss due to cadherin type switching in ADPKD suffices to drive cystogenesis. Thus, control of cadherin type switching provides a new target for therapeutic intervention.