Identifiability analysis and parameter identification of an in vivo ligand-receptor model from PET data

1990 ◽  
Vol 37 (7) ◽  
pp. 653-661 ◽  
Author(s):  
J. Delforge ◽  
A. Syrota ◽  
B.M. Mazoyer
Keyword(s):  
Parameter Identification ◽  
Receptor Model ◽  
Identifiability Analysis

scholarly journals A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development

2020 ◽  
Vol 12 (3) ◽  
pp. 47-63
Author(s):  
Ramak Khosravi ◽  
Abhay B Ramachandra ◽  
Jason M Szafron ◽  
Daniele E Schiavazzi ◽  
Christopher K Breuer ◽  
...  
Keyword(s):  
Transforming Growth Factor Beta ◽  
Transforming Growth Factor ◽  
Optimal Parameter ◽  
Mechanistic Model ◽  
Vena Cava ◽  
Model Parameters ◽  
Identifiability Analysis ◽  
Macrophage Activity ◽  
Cost Efficient

Abstract Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.

Parameter identification of in vivo kinetic models: Limitations and challenges

2013 ◽  
Vol 8 (7) ◽  
pp. 768-775 ◽  
Author(s):  
Joseph J. Heijnen ◽  
Peter J. T. Verheijen
Keyword(s):  
Parameter Identification ◽  
Kinetic Models

scholarly journals Parameter identification and identifiability analysis of lithium‐ion batteries

2021 ◽  
Author(s):  
Yun Young Choi ◽  
Seongyoon Kim ◽  
Kyunghyun Kim ◽  
Sanghyun Kim ◽  
Jung‐Il Choi
Keyword(s):  
Parameter Identification ◽  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Identifiability Analysis

scholarly journals Calibration, Selection and Identifiability Analysis of a Mathematical Model of the in vitro Erythropoiesis in Normal and Perturbed Contexts

2018 ◽  
Author(s):  
Ronan Duchesne ◽  
Anissa Guillemin ◽  
Fabien Crauste ◽  
Olivier Gandrillon
Keyword(s):  
Mathematical Model ◽  
Red Blood Cells ◽  
Blood Cells ◽  
Identifiability Analysis ◽  
The Past ◽  
Parameter Variations ◽  
Linear Ode ◽  
Kinetics Of

AbstractThe in vivo erythropoiesis, which is the generation of mature red blood cells in the bone marrow of whole organisms, has been described by a variety of mathematical models in the past decades. However, the in vitro erythropoiesis, which produces red blood cells in cultures, has received much less attention from the modelling community. In this paper, we propose the first mathematical model of in vitro erythropoiesis. We start by formulating different models and select the best one at fitting experimental data of in vitro erythropoietic differentiation. It is based on a set of linear ODE, describing 3 hypothetical populations of cells at different stages of differentiation. We then compute confidence intervals for all of its parameters estimates, and conclude that our model is fully identifiable. Finally, we use this model to compute the effect of a chemical drug called Rapamycin, which affects all states of differentiation in the culture, and relate these effects to specific parameter variations. We provide the first model for the kinetics of in vitro cellular differentiation which is proven to be identifiable. It will serve as a basis for a model which will better account for the variability which is inherent to experimental protocol used for the model calibration.

Absence of albumin receptor on brain capillaries in vivo or in vitro

1985 ◽  
Vol 249 (3) ◽  
pp. E264-E267 ◽  
Author(s):  
W. M. Pardridge ◽  
J. Eisenberg ◽  
W. T. Cefalu
Keyword(s):  
Transit Time ◽  
Bovine Brain ◽  
In Vitro Assays ◽  
Injection Technique ◽  
Receptor Model ◽  
Brain Capillaries ◽  
Reductive Methylation ◽  
Albumin Receptor

Hormones and drugs are known to be available for transport into brain and liver in vivo from the circulating albumin-bound pool. An albumin receptor-mediated mechanism is one possible way in which the transport of ligands from the circulating albumin-bound pool into the tissue may be catalyzed. The albumin receptor model was tested for brain in the present studies using both 125I-albumin (labeled by lactoperoxidase) and [3H]albumin (labeled by reductive methylation). The interaction of the labeled albumin with brain capillaries was assessed in vivo with the carotid injection technique in rats and in vitro with isolated bovine brain capillaries. Artifactually high nonspecific binding in both the in vivo and in vitro assays was observed with 125I-albumin. Conversely, the transit time of [3H]albumin through the brain capillaries in vivo was no greater than the transit time of [14C]sucrose. The binding of [3H]albumin to isolated microvessels in vitro was low, less than [3H]inulin and was nonsaturable. In conclusion these studies do not support the albumin receptor model for the transport of albumin-bound ligands into tissues such as brain.

scholarly journals In vivo parameter identification in arteries considering multiple levels of smooth muscle activity

2021 ◽  
Author(s):  
Jan-Lucas Gade ◽  
Carl-Johan Thore ◽  
Björn Sonesson ◽  
Jonas Stålhand
Keyword(s):  
Mechanical Properties ◽  
Smooth Muscle ◽  
Parameter Identification ◽  
Clinical Data ◽  
Minimization Problem ◽  
Muscle Activity ◽  
Lower Body Negative Pressure ◽  
Model Parameters ◽  
Multiple Levels

AbstractIn this paper an existing in vivo parameter identification method for arteries is extended to account for smooth muscle activity. Within this method a continuum-mechanical model, whose parameters relate to the mechanical properties of the artery, is fit to clinical data by solving a minimization problem. Including smooth muscle activity in the model increases the number of parameters. This may lead to overparameterization, implying that several parameter combinations solve the minimization problem equally well and it is therefore not possible to determine which set of parameters represents the mechanical properties of the artery best. To prevent overparameterization the model is fit to clinical data measured at different levels of smooth muscle activity. Three conditions are considered for the human abdominal aorta: basal during rest; constricted, induced by lower-body negative pressure; and dilated, induced by physical exercise. By fitting the model to these three arterial conditions simultaneously a unique set of model parameters is identified and the model prediction agrees well with the clinical data.

A model to measure insulin effects on glucose transport and phosphorylation in muscle: a three-tracer study

1996 ◽  
Vol 270 (1) ◽  
pp. E170-E185 ◽  
Author(s):  
M. P. Saccomani ◽  
R. C. Bonadonna ◽  
D. M. Bier ◽  
R. A. DeFronzo ◽  
C. Cobelli
Keyword(s):  
Glucose Transport ◽  
Nonlinear Least Squares ◽  
Distribution Volume ◽  
Human Muscle ◽  
Transmembrane Transport ◽  
Model Parameters ◽  
Identifiability Analysis ◽  
Glucose Phosphorylation ◽  
Intracellular Glucose

We studied five healthy subjects with perfused forearm and euglycemic clamp techniques in combination with a three-tracer (D-[12C]mannitol, not transportable; 3-O-[14C]methyl-D-glucose, transportable but not metabolizable; D-[3-3H]glucose, transportable and metabolizable) intra-arterial pulse injection to assess transmembrane transport and intracellular phosphorylation of glucose in vivo in human muscle. The washout curves of the three tracers were analyzed with a multicompartmental model. A priori identifiability analysis of the tracer model shows that the rate constants of glucose transport into and out of the cells and of glucose phosphorylation are uniquely identifiable. Tracer model parameters were estimated by a nonlinear least-squares parameter estimation technique. We then solved for the tracee model and estimated bidirectional transmembrane transport glucose fluxes, glucose intracellular phosphorylation, extracellular and intracellular volumes of glucose distribution, and extracellular and intracellular glucose concentrations. Physiological hyperinsulinemia (473 +/- 22 pM) caused 2.7-fold (63.1 +/- 7.2 vs. 23.4 +/- 6.1 mumol.min-1.kg-1, P < 0.01) and 5.1-fold (42.5 +/- 5.8 vs. 8.4 +/- 2.2 mumol.min-1.kg-1, P < 0.01) increases in transmembrane influx and intracellular phosphorylation of glucose, respectively. Extracellular distribution volume and concentration of glucose were unchanged, whereas intracellular distribution volume of glucose was increased (approximately 2-fold) and intracellular glucose concentration was almost halved by hyperinsulinemia. In summary, 1) a multicompartment model of three-tracer kinetic data can quantify transmembrane glucose fluxes and intracellular glucose phosphorylation in human muscle; and 2) physiological hyperinsulinemia stimulates both transport and phosphorylation of glucose and, in doing so, amplifies the role of glucose transport as a rate-determining step of muscle glucose uptake.

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