@article{Eckel2025,

title = {Application of rapid evaporative ionization mass spectrometry in preclinical and clinical analyses of steatotic liver tissues and cells},

author = {Julian Connor Eckel and Lena Seidemann and Mohamed Albadry and Gerda Schicht and Marija Skvoznikova and Sandra Nickel and René Hänsel and Daniel Seehofer and Grit Gesine Ruth Hiller and Hans-Michael Tautenhahn and Uta Dahmen and Georg Damm},

doi = {10.1038/s41598-025-93305-w},

issn = {2045-2322},

year  = {2025},

date = {2025-12-00},

urldate = {2025-12-00},

journal = {Sci Rep},

volume = {15},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title>

          <jats:p>Rapid evaporative ionization mass spectrometry (REIMS) shows promise as a preparation-free tissue analysis tool with the prospect for real-time diagnostics. Given that hepatic steatosis is characterized by shifts in lipid species and abundance, we selected it as basis for method development, as REIMS specifically measures lipidomic profiles. However, further validation and protocol refinement are necessary to establish its clinical utility. In this study, we applied REIMS to steatotic human liver tissues, focusing on its ability to differentiate varying degrees of steatosis. We established standardized protocols for tissue handling and lipid analysis, which were essential for reliable data interpretation. Notably, our findings revealed that tissue size impacts REIMS sensitivity, with smaller samples yielding lower total ion counts and altered lipid profiles. Through principal component analysis, we identified key lipid classes, namely triacylglycerides, fatty acids, and glycerophospholipids. Despite a missing link between triacylglyceride abundance and degree of steatosis, we successfully identified condition-specific lipid patterns, with ceramides emerging as markers of advanced steatosis. Our study provides a protocol for the measurements of lipid standards showing the detailed degradation of specific lipids using iKnife-coupled REIMS. It highlights the pitfalls and limitations and provides critical recommendations for REIMS use. It also emphasizes the need for standardized biobanking and tissue preparation to ensure accurate lipid profiling, laying the groundwork for future protocol adjustments required for clinical application.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wrigge2025,

title = {Hyperspectral imaging in living and deceased donor kidney transplantation},

author = {Rasmus Wrigge and Robert Sucher and Fabian Haak and Hans-Jonas Meyer and Julia Unruh and Hans-Michael Hau and Matthias Mehdorn and Hans-Michael Tautenhahn and Daniel Seehofer and Uwe Scheuermann},

doi = {10.1186/s12880-025-01576-6},

issn = {1471-2342},

year  = {2025},

date = {2025-12-00},

urldate = {2025-12-00},

journal = {BMC Med Imaging},

volume = {25},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title>

          <jats:sec>

            <jats:title>Objective and background</jats:title>

            <jats:p>Hyperspectral imaging (HSI) is an innovative, noninvasive technique that assesses tissue and organ perfusion and oxygenation. This study aimed to evaluate HSI as a predictive tool for early postoperative graft function and long-term outcomes in living donor (LD) and deceased donor (DD) kidney transplantation (KT).</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Patients and methods</jats:title>

            <jats:p>HSI of kidney allograft parenchyma from 19 LD and 51 DD kidneys was obtained intraoperatively 15 minutes after reperfusion. Using the dedicated HSI TIVITA Tissue System, indices of tissue oxygenation (StO<jats:sub>2</jats:sub>), perfusion (near-infrared [NIR]), organ hemoglobin (OHI), and tissue water (TWI) were calculated and then analyzed retrospectively.</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Results</jats:title>

            <jats:p>LD kidneys had superior intraoperative HSI values of StO<jats:sub>2</jats:sub> (0.78 ± 0.13 versus 0.63 ± 0.24; <jats:italic>P</jats:italic> = 0.001) and NIR (0.67 ± 0.10 versus 0.56 ± 0.27; <jats:italic>P</jats:italic> = 0.016) compared to DD kidneys. Delayed graft function (DGF) was observed in 18 cases (26%), in which intraoperative HSI showed significantly lower values of StO<jats:sub>2</jats:sub> (0.78 ± 0.07 versus 0.35 ± 0.21; <jats:italic>P</jats:italic> < 0.001) and NIR (0.67 ± 0.11 versus 0.34 ± 0.32; <jats:italic>P</jats:italic> < 0.001). Receiver operating characteristic curve analysis demonstrated an excellent predictive value of HSI for the development of DGF, with an area under the curve of 0.967 for StO<jats:sub>2</jats:sub> and 0.801 for NIR. Kidney grafts with low StO<jats:sub>2</jats:sub> values (cut-off point 0.6) showed reduced renal function with a low glomerular filtration rate and elevated urea levels in the first two weeks after KT. Three years after KT, graft survival was also inferior in the group with initially low StO<jats:sub>2</jats:sub> values.</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Conclusion</jats:title>

            <jats:p>HSI is a useful tool for predicting DGF in living and deceased KT and may assist in estimating short-term allograft function. However, further studies with expanded cohorts are needed to evaluate the association between HSI and long-term graft outcomes.</jats:p>

          </jats:sec>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Eissazadeh2025,

title = {Anti-Endoglin monoclonal antibody prevents the progression of liver sinusoidal endothelial inflammation and fibrosis in MASH},

author = {Samira Eissazadeh and Petra Fikrova and Jana Urbankova Rathouska and Ivana Nemeckova and Katarina Tripska and Martina Vasinova and Radim Havelek and SeyedehNiloufar Mohammadi and Ivone Cristina Igreja Sa and Charles Theuer and Matthias König and Stanislav Micuda and Petr Nachtigal},

doi = {10.1016/j.lfs.2025.123428},

issn = {0024-3205},

year  = {2025},

date = {2025-03-00},

urldate = {2025-03-00},

journal = {Life Sciences},

volume = {364},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Xu2024,

title = {The effects of saturated and unsaturated fatty acids on MASLD: a Mendelian randomization analysis and in vivo experiment},

author = {Fengming Xu and Mohamed Albadry and Annika Döding and Xinpei Chen and Olaf Dirsch and Ulrike Schulze-Späte and Uta Dahmen},

doi = {10.1007/s00394-024-03560-2},

issn = {1436-6215},

year  = {2025},

date = {2025-02-00},

urldate = {2025-02-00},

journal = {Eur J Nutr},

volume = {64},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title>

          <jats:sec>

            <jats:title>Background</jats:title>

            <jats:p>Excessive intake of fatty acids is a key factor contributing to metabolic dysfunction-associated steatotic liver disease (MASLD). However, the effects of saturated fatty acids (SFA) and unsaturated fatty acids (UFA) on the development of MASLD are uncertain. Therefore, we conducted two-sample Mendelian randomization studies and animal experiments to explore the effects of SFA, monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) on the risk of developing MASLD.</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Methods</jats:title>

            <jats:p>The genetic summary data of exposures and outcome were retrieved from genome-wide association studies (GWASs) and used for five Mendelian randomization methods. A comprehensive sensitivity analysis was performed to verify the robustness of the results. Mice were subjected to different diets followed by assessment of severity of steatosis based on a histological score and determination of hepatic triglyceride levels to investigate the relationships between SFA, MUFA, PUFA and MASLD.</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Results</jats:title>

            <jats:p>The Mendelian randomization results showed that MUFA (odds ratio: 1.441, 95% confidence interval: 1.078–1.927, <jats:italic>P =</jats:italic> 0.014) was causally associated with the incidence of MASLD. SFA and PUFA were not causally associated with the incidence of MASLD. Sensitivity analysis did not identify any significant bias in the results. The animal experiment results showed that a MUFA-enriched diet significantly contributed to the development of hepatic steatosis (<jats:italic>P <</jats:italic> 0.001).</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Conclusion</jats:title>

            <jats:p>SFA and PUFA did not have a significant causal effect on MASLD, but MUFA intake is a risk factor for MASLD. A MUFA-enriched diet increased the incidence of macrovesicular steatosis and the hepatic triglyceride levels. Therefore, replacing MUFA intake with a moderate intake of PUFA might help reduce the risk of MASLD.</jats:p>

          </jats:sec>

          <jats:sec>

            <jats:title>Graphical Abstract</jats:title>

          </jats:sec>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mandl2025,

title = {Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning},

author = {Luis Mandl and Somdatta Goswami and Lena Lambers and Tim Ricken},

doi = {10.1016/j.cma.2024.117586},

issn = {0045-7825},

year  = {2025},

date = {2025-02-00},

urldate = {2025-02-00},

journal = {Computer Methods in Applied Mechanics and Engineering},

volume = {434},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Arasteh-Khoshbin2024,

title = {Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA},

author = {O. Arasteh-Khoshbin and S. M. Seyedpour and L. Mandl and L. Lambers and T. Ricken},

doi = {10.1080/19648189.2024.2393881},

issn = {2116-7214},

year  = {2025},

date = {2025-01-25},

urldate = {2025-01-25},

journal = {European Journal of Environmental and Civil Engineering},

volume = {29},

number = {2},

pages = {331--350},

publisher = {Informa UK Limited},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Brodbeck2024,

title = {On the influence of non-linearity within two-phase poro-elasticity: Numerical examples and counterexamples},

author = {Maximilian Brodbeck and Franziska S. Egli and Marlon Suditsch and Seyed Morteza Seyedpour and Tim Ricken},

doi = {10.1016/j.exco.2024.100167},

issn = {2666-657X},

year  = {2024},

date = {2024-12-00},

urldate = {2024-12-00},

journal = {Examples and Counterexamples},

volume = {6},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Reisch2024,

title = {Building up a model family for inflammations},

author = {Cordula Reisch and Sandra Nickel and Hans-Michael Tautenhahn},

doi = {10.1007/s00285-024-02126-4},

issn = {1432-1416},

year  = {2024},

date = {2024-09-00},

urldate = {2024-09-00},

journal = {J. Math. Biol.},

volume = {89},

number = {3},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title><jats:p>The paper presents an approach for overcoming modeling problems of typical life science applications with partly unknown mechanisms and lacking quantitative data: A model family of reaction–diffusion equations is built up on a mesoscopic scale and uses classes of feasible functions for reaction and taxis terms. The classes are found by translating biological knowledge into mathematical conditions and the analysis of the models further constrains the classes. Numerical simulations allow comparing single models out of the model family with available qualitative information on the solutions from observations. The method provides insight into a hierarchical order of the mechanisms. The method is applied to the clinics for liver inflammation such as metabolic dysfunction-associated steatohepatitis or viral hepatitis where reasons for the chronification of disease are still unclear and time- and space-dependent data is unavailable.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Azhdari2024b,

title = {Refining thermal therapy: Temperature distribution modeling with distinct absorption in multi-layered skin tissue during infrared laser exposure},

author = {Mohammad Azhdari and Ghader Rezazadeh and Lena Lambers and Tim Ricken and Hans-Michael Tautenhahn and Franziska Tautenhahn and Seyed Morteza Seyedpour},

doi = {10.1016/j.icheatmasstransfer.2024.107818},

issn = {0735-1933},

year  = {2024},

date = {2024-09-00},

urldate = {2024-09-00},

journal = {International Communications in Heat and Mass Transfer},

volume = {157},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pathak2024,

title = {Modeling freezing and BioGeoChemical processes in Antarctic sea ice},

author = {Raghav Pathak and Seyed Morteza Seyedpour and Bernd Kutschan and Andrea Thom and Silke Thoms and Tim Ricken},

doi = {10.1002/pamm.202400047},

issn = {1617-7061},

year  = {2024},

date = {2024-08-00},

urldate = {2024-08-00},

journal = {Proc Appl Math and Mech},

volume = {24},

number = {2},

publisher = {Wiley},

abstract = {<jats:title>Abstract</jats:title><jats:p>The Antarctic sea ice, which undergoes annual freezing and melting, plays a significant role in the global climate cycle. Since satellite observations in the Antarctic region began, 2023 saw a historically unprecedented decrease in the extent of sea ice. Further ocean warming and future environmental conditions in the Southern Ocean will influence the extent and amount of ice in the Marginal Ice Zones (MIZ), the BioGeoChemical (BGC) cycles, and their interconnected relationships. The so‐called pancake floes are a composition of a porous sea ice matrix with interstitial brine, nutrients, and biological communities inside the pores. The ice formation and salinity are both dependent on the ambient temperature. To realistically model these multiphasic and multicomponent coupled processes, the extended Theory of Porous Media (eTPM) is used to develop Partial Differential Equations (PDEs) based high‐fidelity models capable of simulating the different seasonal variations in the region. All critical variables like salinity, ice volume fraction, and temperature, among others, are considered and have their equations of state. The phase transition phenomenon is approached through a micro‐macro linking scheme. In this paper, a phase‐field solidification model [4] coupled with salinity is used to model the microscale freezing processes and up‐scaled to the macroscale eTPM model. The evolution equations for the phase field model are derived following Landau‐Ginzburg order parameter gradient dynamics and mass conservation of salt allowing to model the salt trapped inside the pores. A BGC flux model for sea ice is set up to simulate the algal species present in the sea ice matrix. Ordinary differential equations (ODE) are employed to represent the diverse environmental factors involved in the growth and loss of distinct BGC components. Processes like photosynthesis are dependent on temperature and salinity, which are derived through an ODE‐PDE coupling with the eTPM model. Academic simulations and results are presented as validation for the mathematical model. These high‐fidelity models eventually lead to their incorporation into large‐scale global climate models.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Albadry2024,

title = {Cross-species variability in lobular geometry and cytochrome P450 hepatic zonation: insights into CYP1A2, CYP2D6, CYP2E1 and CYP3A4},

author = {Mohamed Albadry and Jonas Küttner and Jan Grzegorzewski and Olaf Dirsch and Eva Kindler and Robert Klopfleisch and Vaclav Liska and Vladimira Moulisova and Sandra Nickel and Richard Palek and Jachym Rosendorf and Sylvia Saalfeld and Utz Settmacher and Hans-Michael Tautenhahn and Matthias König and Uta Dahmen},

doi = {10.3389/fphar.2024.1404938},

issn = {1663-9812},

year  = {2024},

date = {2024-05-16},

urldate = {2024-05-16},

journal = {Front. Pharmacol.},

volume = {15},

publisher = {Frontiers Media SA},

abstract = {<jats:p>There is a lack of systematic research exploring cross-species variation in liver lobular geometry and zonation patterns of critical drug-metabolizing enzymes, a knowledge gap essential for translational studies. This study investigated the critical interplay between lobular geometry and key cytochrome P450 (CYP) zonation in four species: mouse, rat, pig, and human. We developed an automated pipeline based on whole slide images (WSI) of hematoxylin-eosin-stained liver sections and immunohistochemistry. This pipeline allows accurate quantification of both lobular geometry and zonation patterns of essential CYP proteins. Our analysis of CYP zonal expression shows that all CYP enzymes (besides CYP2D6 with panlobular expression) were observed in the pericentral region in all species, but with distinct differences. Comparison of normalized gradient intensity shows a high similarity between mice and humans, followed by rats. Specifically, CYP1A2 was expressed throughout the pericentral region in mice and humans, whereas it was restricted to a narrow pericentral rim in rats and showed a panlobular pattern in pigs. Similarly, CYP3A4 is present in the pericentral region, but its extent varies considerably in rats and appears panlobular in pigs. CYP2D6 zonal expression consistently shows a panlobular pattern in all species, although the intensity varies. CYP2E1 zonal expression covered the entire pericentral region with extension into the midzone in all four species, suggesting its potential for further cross-species analysis. Analysis of lobular geometry revealed an increase in lobular size with increasing species size, whereas lobular compactness was similar. Based on our results, zonated CYP expression in mice is most similar to humans. Therefore, mice appear to be the most appropriate species for drug metabolism studies unless larger species are required for other purposes, e.g., surgical reasons. CYP selection should be based on species, with CYP2E1 and CYP2D6 being the most preferable to compare four species. CYP1A2 could be considered as an additional CYP for rodent versus human comparisons, and CYP3A4 for mouse/human comparisons. In conclusion, our image analysis pipeline together with suggestions for species and CYP selection can serve to improve future cross-species and translational drug metabolism studies.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Höpfl2024b,

title = {Bayesian modelling of time series data (BayModTS)—a FAIR workflow to process sparse and highly variable data},

author = {Sebastian Höpfl and Mohamed Albadry and Uta Dahmen and Karl-Heinz Herrmann and Eva Marie Kindler and Matthias König and Jürgen Rainer Reichenbach and Hans-Michael Tautenhahn and Weiwei Wei and Wan-Ting Zhao and Nicole Erika Radde},

editor = {Anthony Mathelier},

doi = {10.1093/bioinformatics/btae312},

issn = {1367-4811},

year  = {2024},

date = {2024-05-02},

urldate = {2024-05-02},

volume = {40},

number = {5},

publisher = {Oxford University Press (OUP)},

abstract = {<jats:title>Abstract</jats:title>

               <jats:sec>

                  <jats:title>Motivation</jats:title>

                  <jats:p>Systems biology aims to better understand living systems through mathematical modelling of experimental and clinical data. A pervasive challenge in quantitative dynamical modelling is the integration of time series measurements, which often have high variability and low sampling resolution. Approaches are required to utilize such information while consistently handling uncertainties.</jats:p>

               </jats:sec>

               <jats:sec>

                  <jats:title>Results</jats:title>

                  <jats:p>We present BayModTS (Bayesian modelling of time series data), a new FAIR (findable, accessible, interoperable, and reusable) workflow for processing and analysing sparse and highly variable time series data. BayModTS consistently transfers uncertainties from data to model predictions, including process knowledge via parameterized models. Further, credible differences in the dynamics of different conditions can be identified by filtering noise. To demonstrate the power and versatility of BayModTS, we applied it to three hepatic datasets gathered from three different species and with different measurement techniques: (i) blood perfusion measurements by magnetic resonance imaging in rat livers after portal vein ligation, (ii) pharmacokinetic time series of different drugs in normal and steatotic mice, and (iii) CT-based volumetric assessment of human liver remnants after clinical liver resection.</jats:p>

               </jats:sec>

               <jats:sec>

                  <jats:title>Availability and implementation</jats:title>

                  <jats:p>The BayModTS codebase is available on GitHub at https://github.com/Systems-Theory-in-Systems-Biology/BayModTS. The repository contains a Python script for the executable BayModTS workflow and a widely applicable SBML (systems biology markup language) model for retarded transient functions. In addition, all examples from the paper are included in the repository. Data and code of the application examples are stored on DaRUS: https://doi.org/10.18419/darus-3876. The raw MRI ROI voxel data were uploaded to DaRUS: https://doi.org/10.18419/darus-3878. The steatosis metabolite data are published on FairdomHub: 10.15490/fairdomhub.1.study.1070.1.</jats:p>

               </jats:sec>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gerhäusser2024,

title = {Simulation of zonation-function relationships in the liver using coupled multiscale models: Application to drug-induced liver injury},

author = {Steffen Gerhäusser and Lena Lambers and Luis Mandl and Julian Franquinet and Tim Ricken and Matthias König},

editor = {bioRxiv},

url = {https://doi.org/10.1101/2024.03.26.586870},

doi = {https://doi.org/10.1101/2024.03.26.586870},

year  = {2024},

date = {2024-03-29},

urldate = {2024-03-29},

journal = {[PrePrint], bioRxiv},

abstract = {Multiscale modeling requires the coupling of models on different scales, often based on different mathematical approaches and developed by different research teams. This poses many challenges, such as defining interfaces for coupling, reproducible exchange of submodels, efficient simulation of the models, or reproducibility of results. Here, we present a multiscale digital twin of the liver that couples a partial differential equation (PDE)-based porous media approach for the hepatic lobule with cellular-scale ordinary differential equation (ODE)-based models. The models based on the theory of porous media describe transport, tissue mechanical properties, and deformations at the lobular scale, while the cellular models describe hepatic metabolism in terms of drug metabolism and damage in terms of necrosis. The resulting multiscale model of the liver was used to simulate perfusion-zonation-function relationships in the liver spanning scales from single cell to the lobulus. The model was applied to study the effects of (i) protein zonation patterns (metabolic zonation) and (ii) drug concentration dependence on spatially heterogeneous liver damage in the form of necrosis. Depending on the zonation pattern, different liver damage patterns could be reproduced, including periportal and pericentral necrosis as seen in drug-induced liver injury (DILI). Increasing the drug concentration led to an increase in the observed damage pattern. A key point for the success was the integration of domain-specific simulators based on standard exchange formats, i.e., libroadrunner for the high-performance simulation of ODE-based systems and FEBio for the simulation of the continuum-biomechanical part. This allows a standardized and reproducible exchange of cellular scale models in the Systems Biology Markup Language (SBML) between research groups.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lambers2024,

title = {Quantifying Fat Zonation in Liver Lobules: An Integrated Multiscale In-silico Model Combining Disturbed Microperfusion and Fat Metabolism via a Continuum-Biomechanical Bi-scale, Tri-phasic Approach},

author = {Lena Lambers and Navina Waschinsky and Jana Schleicher and Matthias König and Hans-Michael Tautenhahn and Mohamed Albadry and Uta Dahmen and Tim Ricken},

editor = {Springer Link},

url = {https://link.springer.com/article/10.1007/s10237-023-01797-0#citeas},

doi = {https://doi.org/10.1007/s10237-023-01797-0},

year  = {2024},

date = {2024-02-25},

urldate = {2024-02-25},

journal = {Biomechanics and Modeling in Mechanobiology},

abstract = {Metabolic zonation refers to the spatial separation of metabolic functions along the sinusoidal axes of the liver. This phenomenon forms the foundation for adjusting hepatic metabolism to physiological requirements in health and disease (e.g., metabolic dysfunction-associated steatotic liver disease/MASLD). Zonated metabolic functions are influenced by zonal morphological abnormalities in the liver, such as periportal fibrosis and pericentral steatosis. We aim to analyze the interplay between microperfusion, oxygen gradient, fat metabolism and resulting zonated fat accumulation in a liver lobule. Therefore we developed a continuum biomechanical, tri-phasic, bi-scale, and multicomponent in silico model, which allows to numerically simulate coupled perfusion-function-growth interactions two-dimensionally in liver lobules. The developed homogenized model has the following specifications: (i) thermodynamically consistent, (ii) tri-phase model (tissue, fat, blood), (iii) penta-substances (glycogen, glucose, lactate, FFA, and oxygen), and (iv) bi-scale approach (lobule, cell). Our presented in silico model accounts for the mutual coupling between spatial and time-dependent liver perfusion, metabolic pathways and fat accumulation. The model thus allows the prediction of fat development in the liver lobule, depending on perfusion, oxygen and plasma concentration of free fatty acids (FFA), oxidative processes, the synthesis and the secretion of triglycerides (TGs). The use of a bi-scale approach allows in addition to focus on scale bridging processes. Thus, we will investigate how changes at the cellular scale affect perfusion at the lobular scale and vice versa. This allows to predict the zonation of fat distribution (periportal or pericentral) depending on initial conditions, as well as external and internal boundary value conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tautenhahn2024,

title = {SimLivA–Modeling ischemia-reperfusion injury in the liver: A first step towards a clinical decision support tool},

author = {Hans-Michael Tautenhahn and Tim Ricken and Uta Dahmen and Luis Mandl and Laura Bütow and Steffen Gerhäusser and Lena Lambers and Xinpei Chen and Elina Lehmann and Olaf Dirsch and Matthias König},

editor = {Wiley Online Library},

url = {https://onlinelibrary.wiley.com/doi/10.1002/gamm.202370003},

doi = {https://doi.org/10.1002/gamm.202370003},

year  = {2024},

date = {2024-01-23},

journal = {GAMM-Mitteilungen e202370003},

abstract = {The SIMulation supported LIVer Assessment for donor organs (SimLivA) project aims to develop a mathematical model to accurately simulate the influence of mechanical alterations in marginal liver grafts (specifically steatotic ones) and cold ischemia on early ischemia-reperfusion injury (IRI) during liver transplantation. Our project tackles significant research challenges, including the co-development of computational methodologies, experimental studies, clinical processes, and technical workflows. We aim to refine a continuum-biomechanical model for enhanced IRI prediction, collect pivotal experimental and clinical data, and assess the clinical applicability of our model. Our efforts involve augmenting and tailoring a coupled continuum-biomechanical, multiphase, and multi-scale partial differential equation-ordinary differential equation (PDE-ODE) model of the liver lobule, allowing us to numerically simulate IRI depending on the degree of steatosis and the duration of ischemia. The envisaged model will intertwine the structure, perfusion, and function of the liver, serving as a crucial aid in clinical decision-making processes. We view this as the initial step towards an in-silico clinical decision support tool aimed at enhancing the outcomes of liver transplantation. In this paper, we provide an overview of the SimLivA project and our preliminary findings, which include: a cellular model that delineates critical processes in the context of IRI during transplantation; and the integration of this model into a multi-scale PDE-ODE model using a homogenized, multi-scale, multi-component approach within the Theory of Porous Media (TPM) framework. The model has successfully simulated the interconnected relationship between structure, perfusion, and function—all of which are integral to IRI. Initial results show simulations at the cellular scale that describe critical processes related to IRI during transplantation. After integrating this model into a multiscale PDE-ODE model, first simulations were performed on the spatial distribution of key functions during warm and cold ischaemia. In addition, we were able to study the effect of tissue perfusion and temperature, two critical parameters in the context of liver transplantation and IRI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Höpfl2024c,

title = {Marginal Percentile Intervals in Bayesian Inference are Overconfident},

author = {Sebastian Höpfl and Hans-Michael Tautenhahn and Vincent Wagner and Nicole Erika Radde},

doi = {10.1016/j.ifacol.2024.10.004},

issn = {2405-8963},

year  = {2024},

date = {2024-00-00},

urldate = {2024-00-00},

journal = {IFAC-PapersOnLine},

volume = {58},

number = {23},

pages = {19--24},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Albadry2023,

title = {Cross-Species Variability in Lobular Geometry and Cytochrome P450 Hepatic Zonation: Insights into CYP1A2, CYP2E1, CYP2D6 and CYP3A4},

author = {Mohamed Albadry and Jonas Kuettner and Jan Grzegorzewski and Olaf Dirsch and Eva Kindler and Robert Klopfleisch and Vaclav Liska and Vladimira Moulisova and Sandra Nickel and Richard Palek and Jachym Rosendorf and Sylvia Saalfeld and Utz Settmacher and Hans-Michael Tautenhahn and Matthias König and Uta Dahmen},

editor = {bioRxiv},

url = {https://www.biorxiv.org/content/10.1101/2023.12.28.573567v1},

doi = {https://doi.org/10.1101/2023.12.28.573567},

year  = {2023},

date = {2023-12-28},

journal = {[PrePrint], bioRxiv},

abstract = {This study explores the critical interplay between lobular geometry and the zonated distribution of cytochrome P450 (CYP) enzymes across species. We present an innovative approach to assess lobular geometry and zonation patterns using whole slide imaging (WSI). This method allows a detailed, systematic comparison of lobular structures and spatial distribution of key CYP450 enzymes and glutamine synthetase in four different species (mouse, rat, pig, and human). Our results shed light on species differences in lobular geometry and enzymatic zonation, providing critical insights for drug metabolism research. Based on our approach we could determine the minimum number of lobules required for a statistically representative analysis, an important piece of information when evaluating liver biopsies and deriving information from WSI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Azhdari2023,

title = {Non-local three phase lag bio thermal modeling of skin tissue and experimental evaluation},

author = {Mohammad Azhdari and Seyed Morteza Seyedpour and Lena Lambers and Hans-Michael Tautenhahn and Franziska Tautenhahn and Tim Ricken and Ghader Rezazadeh},

editor = {Elsevier},

url = {https://www.sciencedirect.com/science/article/pii/S0735193323005353?via%3Dihub},

doi = {https://doi.org/10.1016/j.icheatmasstransfer.2023.107146},

year  = {2023},

date = {2023-11-10},

journal = {Heat and Mass Transfer (149)},

abstract = {In this paper, the thermal behavior of living tissue has been modeled using a non-local three-phase lag approach. The simulation results of this model- ing have been compared with experimental results of alternating radiation with different periods on human skin, yielding satisfactory alignments. Ad- ditionally, it has been investigated that the TPL model, which is an equation with an integral term, can simulate energy accumulation within the dermal tissue. Moreover, the non-local nature of the modeling has been explored to alter the influence of phase lag terms. Furthermore, apart from numer- ically solving the equation, an analytical solution has been derived for the frequency equation, demonstrating the effects of simulation parameters on the frequency equation and simulation results. The obtained results indi cate that these parameters not only independently affect the outcomes but also interact with other parameters, leading to variations beyond their direct impacts.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mandl2023,

title = {Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem},

author = {Luis Mandl and André Mielke and Seyed Morteza Seyedpour and Tim Ricken},

editor = {Scientific Reports},

url = {https://www.nature.com/articles/s41598-023-42141-x},

doi = {https://doi.org/10.1038/s41598-023-42141-x},

year  = {2023},

date = {2023-09-20},

urldate = {2023-09-20},

journal = {Nature Scientific Reports},

abstract = {Physics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks (AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the L_2 relative error by 64.84% after 25,000 epochs for a one-dimensional consolidation problem based on Biot’s theory, and an average improvement by 58.80% with a transfer approach to the theory of porous media.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Maheshvare2023,

title = {A pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell},

author = {M. Deepa Maheshvare and Soumyendu Raha and Matthias König and Debnath Pal},

editor = {Frontiers Endocrinology},

url = {https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1185656/full},

doi = {https://doi.org/10.3389/fendo.2023.1185656},

year  = {2023},

date = {2023-08-02},

journal = {Frontiers in Endocrinology},

abstract = {The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic β-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct a novel data-driven kinetic model of GSIS in the pancreatic β-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and β-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and phenomenological equations for insulin secretion coupled to cellular energy state, ATP dynamics and (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the β-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and biphasic insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic β-cell.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{König2023,

title = {Specifications of standards in systems and synthetic biology: status and developments in 2022 and the COMBINE meeting 2022},

author = {Matthias König and Padraig Gleeson and Martin Golebiewski and Thomas E. Gorochowski and Michael Hucka and Sarah M. Keating and Chris J. Myers and David P. Nickerson and Björn Sommer and Dagmar Waltemath and Falk Schreiber},

editor = {De Gruyter},

url = {https://www.degruyter.com/document/doi/10.1515/jib-2023-0004/html},

doi = {https://doi.org/10.1515/jib-2023-0004},

year  = {2023},

date = {2023-03-29},

journal = {Journal of Integrative Bioinformatics},

abstract = {This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COM-BINE standards in systems and synthetic biology. The 2022 special issue presents three updates to the standards:CellML 2.0.1, SBML Level 3 Package: Spatial Processes, Version 1, Release 1, and Synthetic Biology Open Lan-guage (SBOL) Version 3.1.0. This document can also be used to identify the latest specifications for all COMBINEstandards. In addition, this editorial provides a brief overview of the COMBINE 2022 meeting in Berlin.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rauchfuß2023,

title = {Critical Evaluation of Discarded Donor Livers in the Eurotransplant Region: Potential Implications for Machine Perfusion},

author = {Falk Rauchfuß and Hans-Michael Tautenhahn and Felix Dondorf and Aladdin Ali-Deeb and Utz Settmacher},

editor = {Annals Transplantation},

url = {https://annalsoftransplantation.com/abstract/full/idArt/938132},

doi = {10.12659/AOT.938132},

year  = {2023},

date = {2023-03-17},

journal = {Annals of Transplantation},

abstract = {BACKGROUND: There are still many offered donor livers that are declined during the allocation process. Machine perfusion offers the option to evaluate (especially marginal) donor organs and to better decide whether a graft has the potential of being transplanted or not. There is a lack of clear detailed data on why organs are declined and how many donor livers would have the potential of being evaluated in the machine. 

MATERIAL AND METHODS: We retrospectively reviewed 1356 donor livers between 2016 and 2018, which were offered by Eurotransplant and were declined during the allocation process; 284 grafts were from donor after cardiac death (DCD) and 1072 donations were from after brain death (DBD). The analysis was performed independently and blinded by senior transplant surgeons. 

RESULTS: There were 904 (66.6%) donor livers with potential to be evaluated as suitable grafts in machine perfusion, whereas 417 (30.8%) organs were definitely not-transplantable, mainly due to liver cirrhosis, (untreated) donor malignancy, cardiac diseases of the donor leading to a hepatic congestion, and/or systemic infections in the donor. Donors in blood group “AB” were disproportionally often rejected. Due to missing data, 35 (2.6%) organs could not be sufficiently evaluated. 

CONCLUSIONS: Our data suggest that many declined donor livers have potential of being evaluated by machine perfusion. Comprehensive use of machine perfusion is necessary and useful to improve the current organ shortage.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Albadry2022,

title = {Periportal steatosis in mice affects distinct parameters of pericentral drug metabolism},

author = {Mohamed Albadry and Sebastian Höpfl and Nadia Ehteshamzad and Matthias König and Michael Böttcher and Jasna Neumann and Amelie Lupp and Olaf Dirsch and Nicole Radde and Bruno Christ and Madlen Christ and Lars Ole Schwen and Hendrik Laue and Robert Klopfleisch and Uta Dahmen},

editor = {Scientific Reports},

url = {https://www.nature.com/articles/s41598-022-26483-6#citeas},

doi = {https://doi.org/10.1038/s41598-022-26483-6},

year  = {2022},

date = {2022-12-17},

journal = {Nature Scientific Reports},

abstract = {Little is known about the impact of morphological disorders in distinct zones on metabolic zonation. It was described recently that periportal fibrosis did affect the expression of CYP proteins, a set of pericentrally located drug-metabolizing enzymes. Here, we investigated whether periportal steatosis might have a similar effect. Periportal steatosis was induced in C57BL6/J mice by feeding a high-fat diet with low methionine/choline content for either two or four weeks. Steatosis severity was quantified using image analysis. Triglycerides and CYP activity were quantified in photometric or fluorometric assay. The distribution of CYP3A4, CYP1A2, CYP2D6, and CYP2E1 was visualized by immunohistochemistry. Pharmacokinetic parameters of test drugs were determined after injecting a drug cocktail (caffeine, codeine, and midazolam). The dietary model resulted in moderate to severe mixed steatosis confined to periportal and midzonal areas. Periportal steatosis did not affect the zonal distribution of CYP expression but the activity of selected CYPs was associated with steatosis severity. Caffeine elimination was accelerated by microvesicular steatosis, whereas midazolam elimination was delayed in macrovesicular steatosis. In summary, periportal steatosis affected parameters of pericentrally located drug metabolism. This observation calls for further investigations of the highly complex interrelationship between steatosis and drug metabolism and underlying signaling mechanisms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Welsh2022,

title = {libRoadRunner 2.0: a high performance SBML simulation and analysis library},

author = {Ciaran Welsh and Jin Xu and Lucian Smith and Matthias König and Kiri Choi and Herbert M Sauro},

editor = {Oxford Academic},

url = {https://academic.oup.com/bioinformatics/article/39/1/btac770/6883908},

doi = {https://doi.org/10.1093/bioinformatics/btac770},

year  = {2022},

date = {2022-12-08},

journal = {Bioinformatics},

volume = {39},

issue = {1},

abstract = {Motivation 

This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML). 

Results 

libRoadRunner is a self-contained library, able to run either as a component inside other tools via its C++, C and Python APIs, or interactively through its Python or Julia interface. libRoadRunner uses a custom just-in-time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a large variety of processors, making it fast enough to simulate extremely large models or repeated runs in reasonable timeframes. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) as well as several SBML extensions such as hierarchical composition and probability distributions. It offers multiple deterministic and stochastic integrators, as well as tools for steady-state, sensitivity, stability and structural analyses. 

Availability and implementation 

libRoadRunner binary distributions for Windows, Mac OS and Linux, Julia and Python bindings, source code and documentation are all available at https://github.com/sys-bio/roadrunner, and Python bindings are also available via pip. The source code can be compiled for the supported systems as well as in principle any system supported by LLVM-13, such as ARM-based computers like the Raspberry Pi. The library is licensed under the Apache License Version 2.0.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Grzegorzewski2022,

title = {Physiologically based pharmacokinetic (PBPK) modeling of the role of CYP2D6 polymorphism for metabolic phenotyping with dextromethorphan},

author = {Jan Grzegorzewski and Janosch Brandhorst and Matthias König},

editor = {Sec. Pharmacogenetics Frontiers in Pharmacology and Pharmacogenomics},

url = {https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.1029073/full},

doi = {https://doi.org/10.3389/fphar.2022.1029073},

year  = {2022},

date = {2022-10-24},

journal = {Frontiers in Pharmacology},

abstract = {The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bertrand2022,

title = {On robust discretization methods for poroelastic problems: Numerical examples and counter-examples},

author = {Fleurianne Bertrand and Maximilian Brodbeck and Tim Ricken},

editor = {Elsevier},

url = {https://www.sciencedirect.com/science/article/pii/S2666657X22000209?via%3Dihub},

doi = {https://doi.org/10.1016/j.exco.2022.100087},

year  = {2022},

date = {2022-09-24},

journal = {Examples and Counterexamples (2)},

abstract = {Finite element approximations of poroelastic materials are nowadays used within multiple applications. Due to wide variation of possible material parameters, robustness of the considered discretization is important. Within this contribution robust of discretization schemes, initially developed for Biot’s theory, will be applied within the Theory of Porous Media. Selected numerical test-cases, special attention will be paid to incompressible and impermeable regimes, are conducted.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ricken2022,

title = {Theoretical formulation and computational aspects of a two-scale homogenization scheme combining the TPM and FE² method for poro-elastic fuid-saturated porous media},

author = {Tim Ricken and Jörg Schröder and Joachim Bluhm and Florian Bartel},

editor = {Elsevier},

url = {https://www.sciencedirect.com/science/article/pii/S0020768321004674?via%3Dihub},

doi = {https://doi.org/10.1016/j.ijsolstr.2021.111412},

year  = {2022},

date = {2022-02-28},

journal = {International Journal of Solids and Structures, 2022},

abstract = {The focus of this investigation lies on the development of a two-scale homogenization scheme for poro-elastic fluid-saturated porous media. For this purpose, the general concepts of the Theory of Porous Media (TPM) are combined with the FE method. After an introduction of the basics of TPM, the weak forms for the macroscopic and the microscopic scale will be formulated and the averaged macroscopic tangent moduli considering the microscale will be derived. Additionally, the formulation of lower level boundary conditions, which refer to the quantities that will be transmitted from the macro- to the microscale, in strict compliance with the Hill–Mandel homogeneity condition, is derived. Finally, a numerical example will be presented, pointing out the gained features of the methodology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christ2021,

title = {Hepatectomy-induced alterations in hepatic perfusion and function – Towards multi-scale modeling for a better risk assessment in liver surgery},

author = {Uta Dahmen Maximilian Collatz Bruno Christ and Matthias König and Lena Lambers and Manja Marz and Daria Meyer and Nicole Radde and Jürgen R. Reichenbach and Tim Ricken and Hans-Michael Tautenhahn},

editor = {Sec. Computational Physiology Frontiers in Physiology and Medicine},

url = {https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.733868/full},

doi = {https://doi.org/10.3389/fphys.2021.733868},

year  = {2021},

date = {2021-11-18},

journal = {Frontiers in Physiology (12)},

abstract = {Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Seyedpour2021,

title = {Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review},

author = {Seyed M. Seyedpour and Mehdi Nabati and Lena Lambers and Sara Nafisi and Hans-Michael Tautenhahn and Ingolf Sack and Jürgen R. Reichenbach and Tim Ricken},

editor = {Sec. Computational Physiology Frontiers in Physiology and Medicine},

url = {https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.733393/full},

doi = {https://doi.org/10.3389/fphys.2021.733393},

year  = {2021},

date = {2021-09-22},

urldate = {2021-09-22},

journal = {Frontiers in Physiology (12)},

abstract = {MRI-based biomechanical studies can provide a deep understanding of the mechanisms governing liver function, its mechanical performance but also liver diseases. In addition, comprehensive modeling of the liver can help improve liver disease treatment. Furthermore, such studies demonstrate the beginning of an engineering-level approach to how the liver disease affects material properties and liver function. Aimed at researchers in the field of MRI-based liver simulation, research articles pertinent to MRI-based liver modeling were identified, reviewed, and summarized systematically. Various MRI applications for liver biomechanics are highlighted, and the limitations of different viscoelastic models used in magnetic resonance elastography are addressed. The clinical application of the simulations and the diseases studied are also discussed. Based on the developed questionnaire, the papers' quality was assessed, and of the 46 reviewed papers, 32 papers were determined to be of high-quality. Due to the lack of the suitable material models for different liver diseases studied by magnetic resonance elastography, researchers may consider the effect of liver diseases on constitutive models. In the future, research groups may incorporate various aspects of machine learning (ML) into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}