Gene expression in human or mouse brain with iron loading
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ABSTRACT:
PROVIDER: PRJNA288642 | ENA |
REPOSITORIES: ENA
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:This SuperSeries is composed of the SubSeries listed below.
2017-02-09 | GSE70433 | GEO
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:In plasma, iron is normally bound to transferrin, but in conditions of iron overload when the iron-binding capacity of transferrin is exceeded, non-transferrin-bound iron (NTBI) appears in plasma. NTBI is taken up by hepatocytes and other parenchymal cells via NTBI transporters and can cause cellular damage by promoting the generation of reactive oxygen species. However, how NTBI affects endothelial cells, the most proximal cell type exposed to circulating NTBI, has not been explored. We modeled in vitro the effects of systemic iron overload on endothelial cells by treating primary human umbilical vein endothelial cells (HUVECs) with NTBI (ferric ammonium citrate, FAC). Using an unbiased approach, we showed by RNA-Seq that iron loading alters lipid homeostasis in HUVECs by inducing SREBP2-mediated cholesterol biosynthesis. We also determined that FAC increased the susceptibility of HUVECs to apoptosis induced by TNFα. Moreover, we showed that cholesterol biosynthesis contributes to iron-potentiated apoptosis. Treating HUVECs with a cholesterol chelator hydroxypropyl-β-cyclodextrin demonstrated that depletion of cholesterol was sufficient to rescue HUVECs from TNFa-induced apoptosis, even in the presence of FAC. Finally, we showed that FAC or cholesterol treatment modulated the TNFα pathway by inducing novel proteolytic processing of TNFR1 to a short isoform that localizes to lipid rafts. Our study raises the possibility that iron-mediated toxicity in human iron overload disorders is at least in part dependent on alterations in cholesterol metabolism in endothelial cells, increasing their susceptibility to apoptosis.
2021-09-01 | GSE168534 | GEO
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: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 includes only normal iron with the parameters that fit the data from Lopes et al. 2010 for mice fed a deficient 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 | BIOMD0000000737 | 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 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:Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a novel magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2*relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors’ iron homeostasis, and enhances the distinction between tumor tissue and non- pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.
2023-08-11 | GSE240204 | GEO