An Integrative multi-lineage model of variation in leukopoiesis and acute myelogenous leukemia.

Background: Acute myelogenous leukemia (AML) progresses uniquely in each patient. However, patients are typically treated with the same types of chemotherapy, despite biological differences that lead to differential responses to treatment.

Results: Here we present a multi-lineage multi-compartment model of the hematopoietic system that captures patient-to-patient variation in both the concentration and rates of change of hematopoietic cell populations.

A Computational Study of the Effects of Syk Activity on B Cell Receptor Signaling Dynamics.

The kinase Syk is intricately involved in early signaling events in B cells and is required for proper response when antigens bind to B cell receptors (BCRs). Experiments using an analog-sensitive version of Syk (Syk-AQL) have better elucidated its role, but have not completely characterized its behavior. We present a computational model for BCR signaling, using dynamical systems, which incorporates both wild-type Syk and Syk-AQL.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters.

Correcting hypothalamic-pituitary-adrenal axis dysfunction using observer-based explicit nonlinear model predictive control.

The hypothalamic-pituitary-adrenal (HPA) axis is critical in maintaining homeostasis under physical and psychological stress by modulating cortisol levels in the body. Dysregulation of cortisol levels is linked to numerous stress-related disorders. In this paper, an automated treatment methodology is proposed, employing a variant of nonlinear model predictive control (NMPC), called explicit MPC (EMPC).

Specifying informative experiment stimulation conditions for resolving dynamical uncertainty in biological systems.

A computationally efficient model-based design of experiments (MBDOE) strategy is developed to plan an optimal experiment by specifying the experimental stimulation magnitudes and measurement points. The strategy is extended from previous work which optimized the experimental design over a space of measurable species and time points. We include system inputs (stimulation conditions) in the experiment design search to investigate if the addition of perturbations enhances the ability of the MBDOE method to resolve uncertainties in system dynamics.

Optimal chemotherapy for leukemia: a model-based strategy for individualized treatment.

Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment.

Multiple model-informed open-loop control of uncertain intracellular signaling dynamics.

Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex nonlinear systems typically involve the application of control theory to a descriptive mathematical model. For cellular processes, however, measurement assays tend to be too time consuming for real-time feedback control and models offer rough approximations of the biological reality, thus limiting their utility when considered in isolation.

Model-based analysis for qualitative data: an application in Drosophila germline stem cell regulation.

Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biological mechanisms at play as the networks become increasingly large and complex. However, the available data is frequently under-utilized due to incompatibility with quantitative model tuning techniques.

Experimental design for dynamics identification of cellular processes.

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.

Comparison of CPR outcome predictors between rhythmic abdominal compression and continuous chest compression CPR techniques.

Objective: Bystander cardiopulmonary resuscitation (CPR) provides treatment for out-of-hospital cardiac arrest since perfusion of vital organs is critical to resuscitation. Alternatives to standard CPR are evaluated for effectiveness based upon outcome predictive metrics and survival studies. This study focuses on evaluating the performance of rhythmic-only abdominal compression CPR (OAC-CPR) relative to chest compression (CC-CPR) using a complementary suite of mechanistically based CPR outcome predictors.

Model-based design of experiments for cellular processes.

Model-based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well-established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems.

Analysis of gap gene regulation in a 3D organism-scale model of the Drosophila melanogaster embryo.

The axial bodyplan of Drosophila melanogaster is determined during a process called morphogenesis. Shortly after fertilization, maternal bicoid mRNA is translated into Bicoid (Bcd). This protein establishes a spatially graded morphogen distribution along the anterior-posterior (AP) axis of the embryo.

Sparse-grid-based adaptive model predictive control of HL60 cellular differentiation.

Quantitative methods such as model-based predictive control are known to facilitate the design of strategies to manipulate biological systems. This study develops a sparse-grid-based adaptive model predictive control (MPC) strategy to direct HL60 cellular differentiation. Sparse-grid sampling and interpolation support a computationally efficient adaptive MPC scheme in which multiple data-consistent regions of the model parameter space are identified and used to calculate a control compromise.

A global parallel model based design of experiments method to minimize model output uncertainty.

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited.

A bioenergetic model of the mitochondrial population undergoing permeability transition.

Mitochondrial permeability transition (MPT) is a highly regulated complex phenomenon that is a type of ischemia/reperfusion injury that can lead to cell death and ultimately organ dysfunction. A novel population transition and detailed permeability transition pore regulation model were integrated with an existing bioenergetics model to describe MPT induction under a variety of conditions. The framework of the MPT induction model includes the potential states of the mitochondria (aggregated, orthodox and post-transition), their transitions from one state to another as well as their interaction with the extra-mitochondrial environment.

Using adaptive model predictive control to customize maintenance therapy chemotherapeutic dosing for childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is a common childhood cancer in which nearly one-quarter of patients experience a disease relapse. However, it has been shown that individualizing therapy for childhood ALL patients by adjusting doses based on the blood concentration of active drug metabolite could significantly improve treatment outcome. An adaptive model predictive control (MPC) strategy is presented in which maintenance therapy for childhood ALL is personalized using routine patient measurements of red blood cell mean corpuscular volume as a surrogate for the active drug metabolite concentration.

Modeling mitochondrial bioenergetics with integrated volume dynamics.

Mathematical models of mitochondrial bioenergetics provide powerful analytical tools to help interpret experimental data and facilitate experimental design for elucidating the supporting biochemical and physical processes. As a next step towards constructing a complete physiologically faithful mitochondrial bioenergetics model, a mathematical model was developed targeting the cardiac mitochondrial bioenergetic based upon previous efforts, and corroborated using both transient and steady state data. The model consists of several modified rate functions of mitochondrial bioenergetics, integrated calcium dynamics and a detailed description of the K(+)-cycle and its effect on mitochondrial bioenergetics and matrix volume regulation.

Investigating the role of ischemia vs. elevated hydrostatic pressure associated with acute obstructive uropathy.

Obstructive uropathy can cause irreversible renal damage. It has been hypothesized that elevated hydrostatic pressure within renal tubules and/or renal ischemia contributes to cellular injury following obstruction. However, these assaults are essentially impossible to isolate in vivo.

Rhythmic abdominal compression CPR ventilates without supplemental breaths and provides effective blood circulation.

Objectives: Standard chest-compression CPR has an out-of-hospital resuscitation rate of less than 10% and can result in rib fractures or mouth-to-mouth transfer of infection. Recently, we introduced a new CPR method that utilizes only rhythmic abdominal compressions (OAC-CPR). The present study compares ventilation and hemodynamics produced by chest and abdominal compression CPR.

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool.

Background: It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models.

Influence of biologically inspired nanometer surface roughness on antigen-antibody interactions for immunoassay-biosensor applications.

Current research efforts to improve immunoassay-biosensor functionality have centered on detection through the optimal design of microfluidic chambers, electrical circuitry, optical sensing elements, and so on. To date, little attention has been paid to the immunoassay-biosensor membrane surface on which interactions between antibodies and antigens must occur. For this reason, the objective of the present study was to manipulate the nanometer surface roughness of a model immunoassay-biosensor membrane to determine its role on sensitivity and specificity.

Sustained abdominal compression during CPR raises coronary perfusion pressures as much as vasopressor drugs.

Objectives: This study investigated sustained abdominal compression as a means to improve coronary perfusion pressure (CPP) during cardiopulmonary resuscitation (CPR) and compared the resulting CPP augmentation with that achieved using vasopressor drugs.

Method: During electrically induced ventricular fibrillation in anesthetized, 30kg juvenile pigs, Thumper CPR was supplemented at intervals either by constant abdominal compression at 100-500mmHg using an inflated contoured cuff or by the administration of vasopressor drugs (epinephrine, vasopressin, or glibenclamide). CPP before and after cuff inflation or drug administration was the end point.

Experimental strategies to improve in vitro models of renal ischemia.

Ischemia has elicited a great deal of interest among the scientific community due to its role in life-threatening pathologies such as cancer, stroke, acute renal failure, and myocardial infarction. Oxygen deprivation (hypoxia) associated with ischemia has recently become a subject of intense scrutiny. New investigators may find it challenging to induce hypoxic injury in vitro.

The natural biochemical changes during ventricular fibrillation with cardiopulmonary resuscitation and the onset of postdefibrillation pulseless electrical activity.

Objective: The objective of this study was to document the biochemical changes during ventricular fibrillation (VF) with cardiopulmonary resuscitation (CPR), and to identify factors associated with postdefibrillation pulseless electrical activity (PD-PEA).

Background: It has been reliably estimated that as much as 60% of out-of-hospital sudden cardiac death can be attributed to the onset of PD-PEA (Niemann JT, Cruz B, Garner D et al. Immediate countershock versus CPR before countershock in a 5-minute swine model of ventricular fibrillation arrest.