A Computational Model of Hepatic Energy Metabolism: Understanding Zonated Damage and Steatosis in NAFLD

Ashworth, William B.; Davies, Nathan; Bogle, David

doi:10.1371/journal.pcbi.1005105

Cited by 43 publications

(74 citation statements)

References 99 publications

(124 reference statements)

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“…This was firstly used to simulate high fat intake and insulin resistance to study the build-up of liver fat in NAFLD. 42 Secondly it was used to identify key processes of inter-individual variation in susceptibility to NAFLD and its pattern of development. 42 Finally, in ongoing work, in combination with cell culture studies, the model is being used to test the effects of various potential pharmacological interventions.…”

Section: Modeling and Design For Distributed Behavior Zonated Effectsmentioning

confidence: 99%

“…42 Secondly it was used to identify key processes of inter-individual variation in susceptibility to NAFLD and its pattern of development. 42 Finally, in ongoing work, in combination with cell culture studies, the model is being used to test the effects of various potential pharmacological interventions. It is hoped that these predictions will aid understanding and allow for more targeted future experimentation.…”

Section: Modeling and Design For Distributed Behavior Zonated Effectsmentioning

confidence: 99%

“…These include gut triglyceride synthesis, adipose triglyceride breakdown (lipolysis), adipose lipogenesis, pancreatic hormone release, and oxygen input from the lung. 42 Dietary intake of glucose and lipid is introduced to this compartment. Alternatively, the recirculation can be removed and the model can be used to study the input of plasma with constant metabolite, hormone and oxygen concentrations into the sinusoid.…”

Section: Zonated Model Of Glucose and Lipid Metabolismmentioning

confidence: 99%

“…/ inh 1 determines the maximum inhibition by i. The values of constants were either taken directly from the literature or, where this was not possible, fitted to data looking at hepatic metabolism under different feeding conditions (see Ashworth et al 42 for more details). In many cases, the processes represented in the model contain several intermediate enzymes and the constants were based on the literature for the rate limiting enzyme in the process.…”

Section: Zonated Model Of Glucose and Lipid Metabolismmentioning

confidence: 99%

“…Rather than modeling downstream signaling (e.g., as in Hetherington et al 32 ) the effects of the hormones are calculated based on the plasma concentrations. As a result, the form of the equations and parameter values were largely set by comparison with experimental data for plasma concentrations of key metabolites and for hepatic rates, rather than taken directly from the literature as discussed in Ashworth et al 42 . Finally, the activities of key enzymes vary across the sinusoid.…”

Section: Zonated Model Of Glucose and Lipid Metabolismmentioning

confidence: 99%

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Liver function as an engineering system

et al. 2016

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Process Systems Engineering has tackled a wide range of problems including manufacturing, the environment, and advanced materials design. Here we discuss how tools can be deployed to tackle medical problems which involve complex chemical transformations and spatial phenomena looking in particular at the liver system, the body's chemical factory. We show how an existing model has been developed to model distributed behavior necessary to predict the behavior of drugs for treating liver disease. The model has been used to predict the effects of suppression of de novo lipogenesis, stimulation of b-oxidation and a combination of the two. A reduced model has also been used to explore the prediction of behavior of hormones in the blood stream controlling glucose levels to ensure that levels are kept within safe bounds using interval methods. The predictions are made resulting from uncertainty in two key parameters with oscillating input resulting from regular feeding. V C 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 62: 3285-3297, 2016 Keywords: mathematical modeling, biomedical engineering, systems biology, medical, controlThe liver, its regulation, and its diseases Why systems engineering of the liver?Systems Engineering is the discipline of the management of complex engineering systems over their whole life cycle. Process Systems Engineering is the study of complex process engineering systems involving chemical and physical change. Prof Roger Sargent was a pioneer from the 1950s in seeing the potential that computers could have to revolutionize the way that we tackled these problems.1 He also saw the way Chemical Engineering was broadening its base into molecular and biological systems to improve manufacturing. 1,2The liver is one part of a very complex processing system which ensures that all parts of the body receive the energy and nutrients that they need, that waste products are removed efficiently from the various streams, and that short and long term well being are maintained. It is the body's central chemical processing organ. Considering the liver system as one which controls chemical and physical change within the body, particularly of nutrition, makes it a legitimate area of study for Process Systems Engineers. A number of Chemical Engineers have also contributed to the use for Process Systems Engineering to a range of medical applications. Bogle 3 reviews recent

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Section: Modeling and Design For Distributed Behavior Zonated Effectsmentioning

confidence: 99%

Section: Modeling and Design For Distributed Behavior Zonated Effectsmentioning

confidence: 99%

Section: Zonated Model Of Glucose and Lipid Metabolismmentioning

confidence: 99%

Section: Zonated Model Of Glucose and Lipid Metabolismmentioning

confidence: 99%

Section: Zonated Model Of Glucose and Lipid Metabolismmentioning

confidence: 99%

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Liver function as an engineering system

et al. 2016

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Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production

et al. 2017

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As breakthrough cellular therapy discoveries are translated into reliable, commercializable applications, effective stem cell biomanufacturing requires systematically developing and optimizing bioprocess design and operation. This article proposes a rigorous computational framework for stem cell biomanufacturing under uncertainty. Our mathematical tool kit incorporates: high‐fidelity modeling, single variate and multivariate sensitivity analysis, global topological superstructure optimization, and robust optimization. The advantages of the proposed bioprocess optimization framework using, as a case study, a dual hollow fiber bioreactor producing red blood cells from progenitor cells were quantitatively demonstrated. The optimization phase reduces the cost by a factor of 4, and the price of insuring process performance against uncertainty is approximately 15% over the nominal optimal solution. Mathematical modeling and optimization can guide decision making; the possible commercial impact of this cellular therapy using the disruptive technology paradigm was quantitatively evaluated. © 2017 American Institute of Chemical Engineers AIChE J, 64: 3011–3022, 2018

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A mechanobiological mathematical model of liver metabolism

Nikmaneshi

Firoozabadi

Munn

2020

Biotech & Bioengineering

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The liver plays a complex role in metabolism and detoxification, and better tools are needed to understand its function and to develop liver‐targeted therapies. In this study, we establish a mechanobiological model of liver transport and hepatocyte biology to elucidate the metabolism of urea and albumin, the production/detoxification of ammonia, and consumption of oxygen and nutrients. Since hepatocellular shear stress (SS) can influence the enzymatic activities of liver, the effect of SS on the urea and albumin synthesis are empirically modeled through the mechanotransduction mechanisms. The results demonstrate that the rheology and dynamics of the sinusoid flow can significantly affect liver metabolism. We show that perfusate rheology and blood hematocrit can affect urea and albumin production by changing hepatocyte mechanosensitive metabolism. The model can also simulate enzymatic diseases of the liver such as hyperammonemia I, hyperammonemia II, hyperarginemia, citrollinemia, and argininosuccinicaciduria, which disrupt the urea metabolism and ammonia detoxification. The model is also able to predict how aggregate cultures of hepatocytes differ from single cell cultures. We conclude that in vitro perfusable devices for the study of liver metabolism or personalized medicine should be designed with similar morphology and fluid dynamics as patient liver tissue. This robust model can be adapted to any type of hepatocyte culture to determine how hepatocyte viability, functionality, and metabolism are influenced by liver pathologies and environmental conditions.

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A Computational Model of Hepatic Energy Metabolism: Understanding Zonated Damage and Steatosis in NAFLD

Cited by 43 publications

References 99 publications

Liver function as an engineering system

Liver function as an engineering system

Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production

A mechanobiological mathematical model of liver metabolism

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