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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

Steatosis Heterogeneity.The left images show four examples of different synthetic zonated patterns of steatosis in humans, visualized on a color scale from violet to yellow, corresponding to 0% to 27.5% steatotic lipid accumulation. The three steatotic states correspond to the same total lipid accumulation of 9.2%. The volume rendering on the right visualizes the organ-scale gradient ζh with a difference of 7.96% lateral direction for a human liver.
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pone.0133653.g005: Steatosis Heterogeneity.The left images show four examples of different synthetic zonated patterns of steatosis in humans, visualized on a color scale from violet to yellow, corresponding to 0% to 27.5% steatotic lipid accumulation. The three steatotic states correspond to the same total lipid accumulation of 9.2%. The volume rendering on the right visualizes the organ-scale gradient ζh with a difference of 7.96% lateral direction for a human liver.

Mentions: Synthetic Steatosis Data: The steatosis data used here are synthetic datasets based on experimental observations from the literature. Besides the healthy case (no steatosis), we consider three types of zonation: predominantly periportal (similar to ‘zone 1’ in the terminology of Fig 1 in [29]), predominantly pericentral (‘zone 3’), and non-zonal (‘panacinar’ or ‘azonal’). For this purpose, we assume a total fat accumulation of 9.2% of the liver volume, corresponding to stage 2 steatosis as observed in [111]. We assign pseudo-random [112] steatosis values Δs to each zone, uniformly distributed in the interval 0.092 ⋅ (ρ(λ))−1 ⋅ ζz(λ) ⋅ [(1 − 0.69), (1 + 0.69)] where 0.69 is the coefficient of variation reported in [111], the factor ρ(λ) from Eq 14 in the denominator cancels when computing the total lipid content, and ζz(λ) controls the zonation viaζz(λ)={1non-zonalcase2-2λpredominantlyperiportalcase2λpredominantlypericentralcase(18)Examples for these zonated states of steatosis are visualized in Fig 5.


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)

Steatosis Heterogeneity.The left images show four examples of different synthetic zonated patterns of steatosis in humans, visualized on a color scale from violet to yellow, corresponding to 0% to 27.5% steatotic lipid accumulation. The three steatotic states correspond to the same total lipid accumulation of 9.2%. The volume rendering on the right visualizes the organ-scale gradient ζh with a difference of 7.96% lateral direction for a human liver.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0133653.g005: Steatosis Heterogeneity.The left images show four examples of different synthetic zonated patterns of steatosis in humans, visualized on a color scale from violet to yellow, corresponding to 0% to 27.5% steatotic lipid accumulation. The three steatotic states correspond to the same total lipid accumulation of 9.2%. The volume rendering on the right visualizes the organ-scale gradient ζh with a difference of 7.96% lateral direction for a human liver.
Mentions: Synthetic Steatosis Data: The steatosis data used here are synthetic datasets based on experimental observations from the literature. Besides the healthy case (no steatosis), we consider three types of zonation: predominantly periportal (similar to ‘zone 1’ in the terminology of Fig 1 in [29]), predominantly pericentral (‘zone 3’), and non-zonal (‘panacinar’ or ‘azonal’). For this purpose, we assume a total fat accumulation of 9.2% of the liver volume, corresponding to stage 2 steatosis as observed in [111]. We assign pseudo-random [112] steatosis values Δs to each zone, uniformly distributed in the interval 0.092 ⋅ (ρ(λ))−1 ⋅ ζz(λ) ⋅ [(1 − 0.69), (1 + 0.69)] where 0.69 is the coefficient of variation reported in [111], the factor ρ(λ) from Eq 14 in the denominator cancels when computing the total lipid content, and ζz(λ) controls the zonation viaζz(λ)={1non-zonalcase2-2λpredominantlyperiportalcase2λpredominantlypericentralcase(18)Examples for these zonated states of steatosis are visualized in Fig 5.

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