LEM4 is a growing collection of illustrative models and model-building data from the Center for Orthopaedic Biomechanics at the University of Denver. Multiscale models and simulations are being built of the human lower extremity, from cartilage to population scales, with particular focus on the knee and knee musculature. Current data consists of imaging and force-displacement data used to create, calibrate, and validate specimen-specific models of the knee and quadriceps.
The Spatially Explicit General-purpose Model of Enteric Tissue (SEGMEnT) dynamic represents existing knowledge of the behavior of enteric epithelial tissue as influenced by inflammation. SEGMEnT has the ability to generate a variety of pathophysiological processes within a common platform and a common knowledgebase.
The Reference Model is a league of disease models competing for fitness to existing clinical trial outcomes. Currently Myocardial Infarction, Stroke, and Mortality are modeled in diabetic populations using Monte Carlo micro-simulation. The Reference Model uses the Micro Simulation Tool – MIST to drive development and simulations using High Performance Computing (HPC). The model uses only publicly available data and extracts information from multiple clinical trials published in the literature.
We developed a novel multiscale model to bridge neuropeptide receptor-activated signaling pathway with membrane electrophysiology. The model studies the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. The multiscale model was implemented as a set of ordinary differential equations solved using the ode15s solver in Matlab (Mathworks, USA).
Damage to the basal ganglia leads to motor disorders such as Parkinson’s disease. But motor commands originate from the cortex, so how do basal ganglia dynamics influence cortical computation? To explore this question, we coupled a neural field model that captures the large-scale dynamics of the thalamocortical/basal ganglia system with a small-scale spiking neuronal network that captures computations in the cortex.
This is an illustrative model from our research program. Simulations using this model can predict tibiofemoral joint response (kinematic-kinetic) and tissue stress-strains, albeit accuracy of these predictions can be questionable. The model can be utilized to understand the mechanical function of healthy and diseased tibiofemoral joint and its tissue function. Prospective explorations of the influence of biomechanical interventions on joitn and tissue response is possible following adaptation of the model to the question of interest.
Hybrid model to study the immunodynamics of cells, molecules and bacteria in lung (Agent-Based Model) and lymph node (Ordinary Differential Equation) during Mycobacterium tuberculosis infection
Two compartmental model (Lung-Lymph Node) to study the immunodynamics of cells, molecules and bacteria in lung and lymph node during Mycobacterium tuberculosis infection
Our 3D agent-based cellular model of a Lymph Node that allows for the simultaneous in silico simulation of T cell trafficking, activation and production of effector cells under different antigen conditions. This systems biology approach will provide novel insights for guiding vaccine development and understanding immune responses to infection.
Interleukin-10 (IL-10) and tumor necrosis factor-a (TNF-a) are key anti- and pro-inflammatory mediators elicited during the host immune response to Mycobacterium tuberculosis (Mtb). Understanding the opposing effects of these mediators is difficult due to the complexity of processes acting across different spatial (molecular, cellular, and tissue) and temporal (seconds to years) scales. We take an in silico approach and use multi-scale agent based modeling of the immune response to Mtb, including molecular scale details for both TNF-a and IL-10.
Mathematical models based on cell culture experiments have identified important molecular mechanisms controlling the dynamics of NF-κB signaling, but the dynamics of this path- way have never been studied in the context of an infection in a host. Here, we incorporate these dynamics into a virtual infection setting. We build a multi-scale model of the immune response to the pathogen Mycobacterium tuberculosis (Mtb) to explore the impact of NF-κB dynamics occurring across molecular, cellular, and tissue scales in the lung.
Multiple immune factors control host responses to Mycobacterium tuberculosis infection, including the formation of granulomas, which are aggregates of immune cells whose function may reflect success or failure of the host to contain infection. We developed a multi-scale agent-based model that includes molecular, cellular, and tissue scale events that occur during granuloma formation and maintenance in lung. We use our model to identify processes that regulate TNF-a concentration and cellular behaviors and thus influence the outcome of infection within a granuloma.
Toxicity is a multiscale problem that includes effects that range from the whole body (adsorption, distribution and excretion), to tissue level effects (local dosimetry) to sub-cellular effects (metabolism, toxic outcome pathway). The current Gold Standard for toxicity determination is a combination of animal models, clinical trials in humans and "toxicology by epidemiology"(toxicity determined retrospectively after release of the chemical into the environment or after widespread use of a therapeutic agent).
The lung model integrates mechanics and cell models. The mechanics model utilizes imaging-based, high-fidelity computational technologies for three-dimensional (3D) fluid and solid mechanical systems to predict airflow-induced shear stress and tissue stress at a local level in the realistic human lung models.