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

Parameter Study for the Insulin Model.The left plot shows the relation between the fraction of low-binding cellular volume and the peak-above-baseline amplitude of the outflowing insulin concentration obtained by the simulation for 4096 different spatial configurations of low-binding and high-binding cells. Generally, a higher fraction of low-binding cells implies less insulin uptake by the cells and thus a higher simulated outflowing concentration. The scattering, however, clearly shows that it is not a strict functional dependency. The shaded area in the scatter plot corresponds to the range ηl = 0.606 ± 0.025 near the observed fraction of low-binding cells. It comprises 436 cases, for which the corresponding curves of outflowing insulin concentration are shown in the right plot. The individual lines are colored according to the low-binding cellular volume, cf. the shaded area in the scatter plot. The fact that these are not spectrally ordered from blue to red again shows that the simulation result does not only depend on the low-binding cellular volume fraction but also on the actual spatial configuration.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0133653.g012: Parameter Study for the Insulin Model.The left plot shows the relation between the fraction of low-binding cellular volume and the peak-above-baseline amplitude of the outflowing insulin concentration obtained by the simulation for 4096 different spatial configurations of low-binding and high-binding cells. Generally, a higher fraction of low-binding cells implies less insulin uptake by the cells and thus a higher simulated outflowing concentration. The scattering, however, clearly shows that it is not a strict functional dependency. The shaded area in the scatter plot corresponds to the range ηl = 0.606 ± 0.025 near the observed fraction of low-binding cells. It comprises 436 cases, for which the corresponding curves of outflowing insulin concentration are shown in the right plot. The individual lines are colored according to the low-binding cellular volume, cf. the shaded area in the scatter plot. The fact that these are not spectrally ordered from blue to red again shows that the simulation result does not only depend on the low-binding cellular volume fraction but also on the actual spatial configuration.

Mentions: In Fig 12, we show the dependency of the peak-above-baseline amplitude of the outflowing insulin concentration on the fraction of low-binding cells for all 4096 cases, i.e., for the full range of 0 ≤ ηl ≤ 1. Additionally, we plotted the outflowing concentration time curves for configurations with 0.581 ≤ ηl ≤ 0.631 low-binding cells, the range ηl,obs ± 0.025. We can observe that there is a relatively wide range of outflowing peak-above-baseline amplitudes. The obtained results indicate that not only the amount of the two entities of cells, but also their spatial configuration along the sinusoids determine the total insulin binding and degradation in the liver. Despite more experimental work being necessary in order to corroborate theses observations, it is clear that the insulin outflow from the liver is determined by the existence of both entities of cells able to bind different amounts of the hormone as well as by their spatial configuration along the sinusoid. The latter seems to be a new additional diversity factor in the liver independent from the well-known metabolic heterogeneity related to the position of the cells along the sinusoid.


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)

Parameter Study for the Insulin Model.The left plot shows the relation between the fraction of low-binding cellular volume and the peak-above-baseline amplitude of the outflowing insulin concentration obtained by the simulation for 4096 different spatial configurations of low-binding and high-binding cells. Generally, a higher fraction of low-binding cells implies less insulin uptake by the cells and thus a higher simulated outflowing concentration. The scattering, however, clearly shows that it is not a strict functional dependency. The shaded area in the scatter plot corresponds to the range ηl = 0.606 ± 0.025 near the observed fraction of low-binding cells. It comprises 436 cases, for which the corresponding curves of outflowing insulin concentration are shown in the right plot. The individual lines are colored according to the low-binding cellular volume, cf. the shaded area in the scatter plot. The fact that these are not spectrally ordered from blue to red again shows that the simulation result does not only depend on the low-binding cellular volume fraction but also on the actual spatial configuration.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0133653.g012: Parameter Study for the Insulin Model.The left plot shows the relation between the fraction of low-binding cellular volume and the peak-above-baseline amplitude of the outflowing insulin concentration obtained by the simulation for 4096 different spatial configurations of low-binding and high-binding cells. Generally, a higher fraction of low-binding cells implies less insulin uptake by the cells and thus a higher simulated outflowing concentration. The scattering, however, clearly shows that it is not a strict functional dependency. The shaded area in the scatter plot corresponds to the range ηl = 0.606 ± 0.025 near the observed fraction of low-binding cells. It comprises 436 cases, for which the corresponding curves of outflowing insulin concentration are shown in the right plot. The individual lines are colored according to the low-binding cellular volume, cf. the shaded area in the scatter plot. The fact that these are not spectrally ordered from blue to red again shows that the simulation result does not only depend on the low-binding cellular volume fraction but also on the actual spatial configuration.
Mentions: In Fig 12, we show the dependency of the peak-above-baseline amplitude of the outflowing insulin concentration on the fraction of low-binding cells for all 4096 cases, i.e., for the full range of 0 ≤ ηl ≤ 1. Additionally, we plotted the outflowing concentration time curves for configurations with 0.581 ≤ ηl ≤ 0.631 low-binding cells, the range ηl,obs ± 0.025. We can observe that there is a relatively wide range of outflowing peak-above-baseline amplitudes. The obtained results indicate that not only the amount of the two entities of cells, but also their spatial configuration along the sinusoids determine the total insulin binding and degradation in the liver. Despite more experimental work being necessary in order to corroborate theses observations, it is clear that the insulin outflow from the liver is determined by the existence of both entities of cells able to bind different amounts of the hormone as well as by their spatial configuration along the sinusoid. The latter seems to be a new additional diversity factor in the liver independent from the well-known metabolic heterogeneity related to the position of the cells along the sinusoid.

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