Limits...
Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations.

Schwen LO, Schenk A, Kreutz C, Timmer J, Bartolomé Rodríguez MM, Kuepfer L, Preusser T - PLoS ONE (2015)

Bottom Line: This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales.Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism.In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.

View Article: PubMed Central - PubMed

Affiliation: Fraunhofer MEVIS, Bremen, Germany.

ABSTRACT
The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.

No MeSH data available.


Related in: MedlinePlus

Spatio-Temporal Midazolam Concentration Profiles.The surface plots show the spatio-temporal evolution of the midazolam concentrations in the blood plasma and the hepatocytes along representative sinusoids assuming an infusion of duration 5 seconds into the portal vein, comparing the healthy reference case with three different steatotic cases with the same total amount of lipid accumulation. While the height in the graph covers the total concentration ranges, the color highlights differences in a lower range of concentrations, emphasizing the differences between the four cases. In addition, the steatosis patterns along the sinusoids are shown below the cellular concentrations. Differences in the transit time of the peak are due to different extent of storage and release of the midazolam due to the steatotic lipid accumulations. This should not be mistaken for the blood flow transit time, which is 13.6 s for all four cases and thus much shorter than the peak transit time.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4519332&req=5

pone.0133653.g008: Spatio-Temporal Midazolam Concentration Profiles.The surface plots show the spatio-temporal evolution of the midazolam concentrations in the blood plasma and the hepatocytes along representative sinusoids assuming an infusion of duration 5 seconds into the portal vein, comparing the healthy reference case with three different steatotic cases with the same total amount of lipid accumulation. While the height in the graph covers the total concentration ranges, the color highlights differences in a lower range of concentrations, emphasizing the differences between the four cases. In addition, the steatosis patterns along the sinusoids are shown below the cellular concentrations. Differences in the transit time of the peak are due to different extent of storage and release of the midazolam due to the steatotic lipid accumulations. This should not be mistaken for the blood flow transit time, which is 13.6 s for all four cases and thus much shorter than the peak transit time.

Mentions: In Fig 8, we can clearly observe the influence of the different steatosis patterns on the spatio-temporal midazolam distribution. As expected from Eq 17, a higher accumulation of midazolam was predicted for the steatotic regions. In the plots, the apparent velocity of the peak is particularly noteworthy with an apparent transit time of about 200 seconds for the healthy state, and slower apparent velocity for the steatotic states. We emphasize that this time scale is different from the blood flow velocity, for which the transit time is 13.6 s as given in Eq 6, i.e., significantly shorter and according to our assumptions in particular independent of the steatosis.


Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations.

Schwen LO, Schenk A, Kreutz C, Timmer J, Bartolomé Rodríguez MM, Kuepfer L, Preusser T - PLoS ONE (2015)

Spatio-Temporal Midazolam Concentration Profiles.The surface plots show the spatio-temporal evolution of the midazolam concentrations in the blood plasma and the hepatocytes along representative sinusoids assuming an infusion of duration 5 seconds into the portal vein, comparing the healthy reference case with three different steatotic cases with the same total amount of lipid accumulation. While the height in the graph covers the total concentration ranges, the color highlights differences in a lower range of concentrations, emphasizing the differences between the four cases. In addition, the steatosis patterns along the sinusoids are shown below the cellular concentrations. Differences in the transit time of the peak are due to different extent of storage and release of the midazolam due to the steatotic lipid accumulations. This should not be mistaken for the blood flow transit time, which is 13.6 s for all four cases and thus much shorter than the peak transit time.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4519332&req=5

pone.0133653.g008: Spatio-Temporal Midazolam Concentration Profiles.The surface plots show the spatio-temporal evolution of the midazolam concentrations in the blood plasma and the hepatocytes along representative sinusoids assuming an infusion of duration 5 seconds into the portal vein, comparing the healthy reference case with three different steatotic cases with the same total amount of lipid accumulation. While the height in the graph covers the total concentration ranges, the color highlights differences in a lower range of concentrations, emphasizing the differences between the four cases. In addition, the steatosis patterns along the sinusoids are shown below the cellular concentrations. Differences in the transit time of the peak are due to different extent of storage and release of the midazolam due to the steatotic lipid accumulations. This should not be mistaken for the blood flow transit time, which is 13.6 s for all four cases and thus much shorter than the peak transit time.
Mentions: In Fig 8, we can clearly observe the influence of the different steatosis patterns on the spatio-temporal midazolam distribution. As expected from Eq 17, a higher accumulation of midazolam was predicted for the steatotic regions. In the plots, the apparent velocity of the peak is particularly noteworthy with an apparent transit time of about 200 seconds for the healthy state, and slower apparent velocity for the steatotic states. We emphasize that this time scale is different from the blood flow velocity, for which the transit time is 13.6 s as given in Eq 6, i.e., significantly shorter and according to our assumptions in particular independent of the steatosis.

Bottom Line: This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales.Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism.In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.

View Article: PubMed Central - PubMed

Affiliation: Fraunhofer MEVIS, Bremen, Germany.

ABSTRACT
The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.

No MeSH data available.


Related in: MedlinePlus