Propagation of Pericentral Necrosis During Acetaminophen-Induced Liver Injury: Evidence for Early Interhepatocyte Communication and Information Exchange.

Acetaminophen (APAP)-induced liver injury is clinically significant, and APAP overdose in mice often serves as a model for drug-induced liver injury in humans. By specifying that APAP metabolism, reactive metabolite formation, glutathione depletion, and mitigation of mitochondrial damage within individual hepatocytes are functions of intralobular location, an earlier virtual model mechanism provided the first concrete multiattribute explanation for how and why early necrosis occurs close to the central vein (CV). However, two characteristic features could not be simulated consistently: necrosis occurring first adjacent to the CV, and subsequent necrosis occurring primarily adjacent to hepatocytes that have already initiated necrosis. We sought parsimonious model mechanism enhancements that would manage spatiotemporal heterogeneity sufficiently to enable meeting two new target attributes and conducted virtual experiments to explore different ideas for model mechanism improvement at intrahepatocyte and multihepatocyte levels. For the latter, evidence supports intercellular communication via exosomes, gap junctions, and connexin hemichannels playing essential roles in the toxic effects of chemicals, including facilitating or counteracting cell death processes. Logic requiring hepatocytes to obtain current information about whether downstream and lateral neighbors have triggered necrosis enabled virtual hepatocytes to achieve both new target attributes. A virtual hepatocyte that is glutathione-depleted uses that information to determine if it will initiate necrosis. When a less-stressed hepatocyte is flanked by at least two neighbors that have triggered necrosis, it too will initiate necrosis. We hypothesize that the resulting intercellular communication-enabled model mechanism is analogous to the actual explanation for APAP-induced hepatotoxicity at comparable levels of granularity

Relational grounding facilitates development of scientifically useful multiscale models

We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM). Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor) typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module) models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding

Augmented Two-Channel Arrhythmia Detection: An Efficient Diagnostic Method for Implantable Devices

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75624/1/j.1540-8159.1996.tb03164.x.pd

Ischemia reperfusion dysfunction changes model-estimated kinetics of myofilament interaction due to inotropic drugs in isolated hearts

BACKGROUND: The phase-space relationship between simultaneously measured myoplasmic [Ca(2+)] and isovolumetric left ventricular pressure (LVP) in guinea pig intact hearts is altered by ischemic and inotropic interventions. Our objective was to mathematically model this phase-space relationship between [Ca(2+)] and LVP with a focus on the changes in cross-bridge kinetics and myofilament Ca(2+ )sensitivity responsible for alterations in Ca(2+)-contraction coupling due to inotropic drugs in the presence and absence of ischemia reperfusion (IR) injury. METHODS: We used a four state computational model to predict LVP using experimentally measured, averaged myoplasmic [Ca(2+)] transients from unpaced, isolated guinea pig hearts as the model input. Values of model parameters were estimated by minimizing the error between experimentally measured LVP and model-predicted LVP. RESULTS: We found that IR injury resulted in reduced myofilament Ca(2+ )sensitivity, and decreased cross-bridge association and dissociation rates. Dopamine (8 μM) reduced myofilament Ca(2+ )sensitivity before, but enhanced it after ischemia while improving cross-bridge kinetics before and after IR injury. Dobutamine (4 μM) reduced myofilament Ca(2+ )sensitivity while improving cross-bridge kinetics before and after ischemia. Digoxin (1 μM) increased myofilament Ca(2+ )sensitivity and cross-bridge kinetics after but not before ischemia. Levosimendan (1 μM) enhanced myofilament Ca(2+ )affinity and cross-bridge kinetics only after ischemia. CONCLUSION: Estimated model parameters reveal mechanistic changes in Ca(2+)-contraction coupling due to IR injury, specifically the inefficient utilization of Ca(2+ )for contractile function with diastolic contracture (increase in resting diastolic LVP). The model parameters also reveal drug-induced improvements in Ca(2+)-contraction coupling before and after IR injury

Software engineering considerations for individual-based models

this paper is to identify important software engineering issues for IBMs and provide general recommendations for addressing these issues. Our intent is to provide guidelines that will help an IBM project develop software that (1) does not contain important undetected errors, (2) helps keep the project e#cient and cost-e#ective, and (3) provides the tools necessary to conduct valid science or responsible management with the model. Early detection of mistakes is crucial to the cost-e#ectiveness of any software project. Failure to detect mistakes leads to spending much of the project's time and budget on work that must be discarded after mistakes are found or (worse yet) the promulgation of "research" results or management decisions based on erroneous simulations. Likewise, failure to provide key software features can make it di#cult or impossible to understand and learn from an IBM. These guidelines are based mainly on the authors' extensive experience implementing IBMs and designing software libraries for individual-based simulatio

ISL and ISHC parameters descriptions and values for validating experiments.

<p>ISL and ISHC parameters descriptions and values for validating experiments.</p

Utilizing virtual experiments to increase understanding of discrepancies involving in vitro-to-in vivo predictions of hepatic clearance.

Predictions of xenobiotic hepatic clearance in humans using in vitro-to-in vivo extrapolation methods are frequently inaccurate and problematic. Multiple strategies are being pursued to disentangle responsible mechanisms. The objective of this work is to evaluate the feasibility of using insights gained from independent virtual experiments on two model systems to begin unraveling responsible mechanisms. The virtual culture is a software analog of hepatocytes in vitro, and the virtual human maps to hepatocytes within a liver within an idealized model human. Mobile objects (virtual compounds) map to amounts of xenobiotics. Earlier versions of the two systems achieved quantitative validation targets for intrinsic clearance (virtual culture) and hepatic clearance (virtual human). The major difference between the two systems is the spatial organization of the virtual hepatocytes. For each pair of experiments (virtual culture, virtual human), hepatocytes are configured the same. Probabilistic rules govern virtual compound movements and interactions with other objects. We focus on highly permeable virtual compounds and fix their extracellular unbound fraction at one of seven values (0.05-1.0). Hepatocytes contain objects that can bind and remove compounds, analogous to metabolism. We require that, for a subset of compound properties, per-hepatocyte compound exposure and removal rates during culture experiments directly predict corresponding measures made during virtual human experiments. That requirement serves as a cross-system validation target; we identify compound properties that enable achieving it. We then change compound properties, ceteris paribus, and provide model mechanism-based explanations for when and why measures made during culture experiments under- (or over-) predict corresponding measures made during virtual human experiments. The results show that, from the perspective of compound removal, the organization of hepatocytes within virtual livers is more efficient than within cultures, and the greater the efficiency difference, the larger the underprediction. That relationship is noteworthy because most in vitro-to-in vivo extrapolation methods abstract away the structural organization of hepatocytes within a liver. More work is needed on multiple fronts, including the study of an expanded variety of virtual compound properties. Nevertheless, the results support the feasibility of the approach and plan