Mouse Iron Distribution - Deficient iron diet (No Tracer)
Ontology highlight
ABSTRACT:
SUBMITTER: 
Pedro Mendes
PROVIDER: BIOMD0000000737 | BioModels | 2024-09-02
REPOSITORIES: BioModels
Dataset's files
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Publications
Modeling the dynamics of mouse iron body distribution: hepcidin is necessary but not sufficient.
Parmar Jignesh H JH Davis Grey G Shevchuk Hope H Mendes Pedro P
BMC systems biology 20170518 1
<h4>Background</h4>Iron is an essential element of most living organisms but is a dangerous substance when poorly liganded in solution. The hormone hepcidin regulates the export of iron from tissues to the plasma contributing to iron homeostasis and also restricting its availability to infectious agents. Disruption of iron regulation in mammals leads to disorders such as anemia and hemochromatosis, and contributes to the etiology of several other diseases such as cancer and neurodegenerative dis ...[more]
Similar Datasets
Project description:Mouse Iron Distribution Dynamics
Dynamic model of iron distribution in mice. This model includes normal iron and radioactive labelled tracer iron species and was used for parameter estimation given the data from Lopes et al. 2010 for mice fed an adequate iron diet.
2024-09-02 | BIOMD0000000735 | BioModels
Project description:Mouse Iron Distribution Dynamics
Dynamic model of iron distribution in mice. This model includes only normal iron with the parameters that fit the data from Lopes et al. 2010 for mice fed a rich iron diet.
This model does not include the radioiron tracer species. It is appropriate to study the properties in conditions where no tracers are used (for example for steady state analysis).
2024-09-02 | BIOMD0000000738 | BioModels
Project description:Mouse Iron Distribution Dynamics
Dynamic model of iron distribution in mice. This model includes only normal iron with the parameters that fit the data from Lopes et al. 2010 for mice fed an adequate iron diet.
This model does not include the radioiron tracer species. It is appropriate to study the properties in conditions where no tracers are used (for example for steady state analysis).
2024-09-02 | BIOMD0000000736 | BioModels
Project description:Mouse Iron Distribution Dynamics
Dynamic model of iron distribution in mice. This model attempts to fit the radioiron tracer data from Lopes et al. 2010 for mice fed iron deficient and rich diets by adjusting the rate of iron intake (vDiet) and the hepcidin synthesis rate (vhepcidin) independently for each experiment. All other parameters are those that provide the best fit for the adequate diet.
This model includes the radioiron tracer species.
Differences in parameter values between deficient, rich, and adequate diets:
Diet
vDiet
vhepcidin
Adequate
0.00377422
1.7393e-08
Deficient
0
8.54927e-09
Rich
0.00415624
2.30942e-08
2024-09-02 | BIOMD0000000734 | BioModels
Project description:Iron Mouse PV3
"A computational model to understand mouse iron physiology and diseases"
By Jignesh Parmar and Pedro Mendes
Parameter estimation using radioactive tracer data
This is a dynamic model of iron distribution in mice, covering seven compartments: plasma, bone marrow, red blood cells (RBC), spleen, duodenum, liver, and the rest of the body . This is mostly a physiological model with regulation by hepcidin and erythropoietin, including only a minimal amount of molecular details.
This version of the model includes normal iron species and radioactive-labelled tracer iron species. It was used specifically for parameter estimation using the data from Schümann et al. 2007 (see also Lopes et al. 2010 and Parmar et al. 2017) from three experiments of mice fed adequate, iron-deficient, and iron-rich diets. Mice in all three dietary regimes were injected with a radiactive tracer and its distribution measured along time. The model parameters were adjusted in order to minimize the distance of the model to the data of all three experiements simultaneously.
Model validation was carried out with another version of this model where the radioactive species are ommited but all parameters remain with the values determined here (see accompanying model). The model is able to match the phenotype of several iron-related diseases.
2022-09-16 | MODEL1805140002 | BioModels
Project description:Iron Mouse PV3
"A computational model to understand mouse iron physiology and diseases"
By Jignesh Parmar and Pedro Mendes
Base model
This is a dynamic model of iron distribution in mice, covering seven compartments: plasma, bone marrow, red blood cells (RBC), spleen, duodenum, liver, and the rest of the body . This is mostly a physiological model with regulation by hepcidin and erythropoietin, including only a minimal amount of molecular details.
This version of the model does not include the radioactive-labelled tracer iron species that were used for parameter estimation (that is included in a separate file). This model has all parameter values already set to the best estimates obtained with the model with radioactive tracer. This model is useful to study the steady state properties of the system and as a basis for various types of simulation.
Model validation was carried out with other model files that were derived from this one and where certain parameters were altered or new interventions added.
2022-09-16 | MODEL1805140003 | BioModels
Project description:This a model from the article:
Systems analysis of iron metabolism: the network of iron pools and fluxes
Tiago JS Lopes, Tatyana Luganskaja, Maja Vujic-Spasic, Matthias W Hentze, Martina U Muckenthaler, Klaus Schumann and Jens G Reich
BMC Systems Biology2010, Aug 13;4(1):112.
20704761,
Abstract:
Background
Every cell of the mammalian organism needs iron in numerous oxido-reductive processes as well as for transport and storage of oxygen. The versatility of ionic iron makes it a toxic entity which can catalyze the production of radicals that damage vital membranous and macromolecular assemblies in the cell. The mammalian organism maintains therefore a complex regulatory network of iron uptake, excretion and intra-body distribution. Intracellular regulation in different cell types is intertwined with a global hormonal signaling structure. Iron deficiency as well as excess of iron are frequent and serious human disorders. They can affect every cell, but also the organism as a whole.
Results
Here, we present a kinematic model of the dynamic system of iron pools and fluxes. It is based on ferrokinetic data and chemical measurements in C57BL6 wild-type mice maintained on iron-deficient, iron-adequate, or iron-loaded diet. The tracer iron levels in major tissues and organs (16 compartment) were followed for 28 days. The evaluation resulted in a whole-body model of fractional clearance rates. The analysis permits calculation of absolute flux rates in the steady-state, of iron distribution into different organs, of tracer-accessible pool sizes and of residence times of iron in the different compartments in response to three states of iron-repletion induced by the dietary regime.
Conclusions
This mathematical model presents a comprehensive physiological picture of mice under three different diets with varying iron contents. The quantitative results reflect systemic properties of iron metabolism: dynamic closedness, hierarchy of time scales, switch-over response and dynamics of iron storage in parenchymal organs. Therefore, we could assess which parameters will change under dietary perturbations and study in quantitative terms when those changes take place.
This model corresponds to the Iron Loaded condition - Mice
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2024-09-02 | BIOMD0000000261 | BioModels
Project description:This a model from the article:
Systems analysis of iron metabolism: the network of iron pools and fluxes
Tiago JS Lopes, Tatyana Luganskaja, Maja Vujic-Spasic, Matthias W Hentze, Martina U Muckenthaler, K
laus Schumann and Jens G Reich
BMC Systems Biology2010, Aug 13;4(1):112.
20704761,
Abstract:
Background
Every cell of the mammalian organism needs iron in numerous oxido-reductive processes as well as fo
r transport and storage of oxygen. The versatility of ionic iron makes it a toxic entity which can
catalyze the production of radicals that damage vital membranous and macromolecular assemblies in t
he cell. The mammalian organism maintains therefore a complex regulatory network of iron uptake, ex
cretion and intra-body distribution. Intracellular regulation in different cell types is intertwine
d with a global hormonal signaling structure. Iron deficiency as well as excess of iron are frequen
t and serious human disorders. They can affect every cell, but also the organism as a whole.
Results
Here, we present a kinematic model of the dynamic system of iron pools and fluxes. It is based on f
errokinetic data and chemical measurements in C57BL6 wild-type mice maintained on iron-deficient, i
ron-adequate, or iron-loaded diet. The tracer iron levels in major tissues and organs (16 compartme
nt) were followed for 28 days. The evaluation resulted in a whole-body model of fractional clearanc
e rates. The analysis permits calculation of absolute flux rates in the steady-state, of iron distr
ibution into different organs, of tracer-accessible pool sizes and of residence times of iron in th
e different compartments in response to three states of iron-repletion induced by the dietary regim
e.
Conclusions
This mathematical model presents a comprehensive physiological picture of mice under three differen
t diets with varying iron contents. The quantitative results reflect systemic properties of iron me
tabolism: dynamic closedness, hierarchy of time scales, switch-over response and dynamics of iron s
torage in parenchymal organs. Therefore, we could assess which parameters will change under dietary
perturbations and study in quantitative terms when those changes take place.
This model corresponds to the Iron Adequate condition - Mice
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2024-09-02 | BIOMD0000000260 | BioModels
Project description:This a model from the article:
Systems analysis of iron metabolism: the network of iron pools and fluxes
Tiago JS Lopes, Tatyana Luganskaja, Maja Vujic-Spasic, Matthias W Hentze, Martina U Muckenthaler, K
laus Schumann and Jens G Reich
BMC Systems Biology2010, Aug 13;4(1):112.
20704761,
Abstract:
Background
Every cell of the mammalian organism needs iron in numerous oxido-reductive processes as well as fo
r transport and storage of oxygen. The versatility of ionic iron makes it a toxic entity which can
catalyze the production of radicals that damage vital membranous and macromolecular assemblies in t
he cell. The mammalian organism maintains therefore a complex regulatory network of iron uptake, ex
cretion and intra-body distribution. Intracellular regulation in different cell types is intertwine
d with a global hormonal signaling structure. Iron deficiency as well as excess of iron are frequen
t and serious human disorders. They can affect every cell, but also the organism as a whole.
Results
Here, we present a kinematic model of the dynamic system of iron pools and fluxes. It is based on f
errokinetic data and chemical measurements in C57BL6 wild-type mice maintained on iron-deficient, i
ron-adequate, or iron-loaded diet. The tracer iron levels in major tissues and organs (16 compartme
nt) were followed for 28 days. The evaluation resulted in a whole-body model of fractional clearanc
e rates. The analysis permits calculation of absolute flux rates in the steady-state, of iron distr
ibution into different organs, of tracer-accessible pool sizes and of residence times of iron in th
e different compartments in response to three states of iron-repletion induced by the dietary regim
e.
Conclusions
This mathematical model presents a comprehensive physiological picture of mice under three differen
t diets with varying iron contents. The quantitative results reflect systemic properties of iron me
tabolism: dynamic closedness, hierarchy of time scales, switch-over response and dynamics of iron s
torage in parenchymal organs. Therefore, we could assess which parameters will change under dietary
perturbations and study in quantitative terms when those changes take place.
This model corresponds to the Iron Deficient condition - Mice
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2024-09-02 | BIOMD0000000259 | BioModels
Project description:The goals of this study are to compare transcriptome profiling (RNA-seq) on iron of hepatocytes and stellate cells. Methods: mRNA profiles of wild-type (WT) NCD hepatocytes treated with or without DFO (100 uM) (n=6) and WT chow diet stellate cells treated with or without iron were generated by deep sequencing,
2022-05-01 | GSE185694 | GEO