References of "Frontiers in physiology"
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See detailUsing Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways.
De Landtsheer, Sébastien; Lucarelli, Philippe UL; Sauter, Thomas UL

in Frontiers in physiology (2018), 9

Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down ... [more ▼]

Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down the development of effective cures. The molecular differences between cell types or between healthy and diseased cellular states are usually determined by the wiring of regulatory networks. Understanding these molecular and cellular differences at the systems level would improve patient stratification and facilitate the design of rational intervention strategies. Models of cellular regulatory networks frequently make weak assumptions about the distribution of model parameters across cell types or patients. These assumptions are usually expressed in the form of regularization of the objective function of the optimization problem. We propose a new method of regularization for network models of signaling pathways based on the local density of the inferred parameter values within the parameter space. Our method reduces the complexity of models by creating groups of cell line-specific parameters which can then be optimized together. We demonstrate the use of our method by recovering the correct topology and inferring accurate values of the parameters of a small synthetic model. To show the value of our method in a realistic setting, we re-analyze a recently published phosphoproteomic dataset from a panel of 14 colon cancer cell lines. We conclude that our method efficiently reduces model complexity and helps recovering context-specific regulatory information. [less ▲]

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See detailModel Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.
Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun et al

in Frontiers in physiology (2017), 8

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple ... [more ▼]

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines. [less ▲]

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See detailBenchmarking procedures for high-throughput context specific reconstruction algorithms
Pacheco, Maria UL; Pfau, Thomas UL; Sauter, Thomas UL

in Frontiers in Physiology (2016)

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction ... [more ▼]

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. [less ▲]

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See detailMetabolome-wide analysis of stable isotope labeling - Is it worth the effort?
Weindl, Daniel UL; Wegner, André UL; Hiller, Karsten UL

in Frontiers in Physiology (2015), 6(344),

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See detailMembrane transporters in a human genome-scale metabolic knowledgebase and their implications for disease
Sahoo, Swagatika UL; Aurich, Maike Kathrin UL; Jonsson, Jon et al

in Frontiers in Physiology (2014), 5

Membrane transporters enable efficient cellular metabolism, aid in nutrient sensing, and have been associated with various diseases, such as obesity and cancer. Genome-scale metabolic network ... [more ▼]

Membrane transporters enable efficient cellular metabolism, aid in nutrient sensing, and have been associated with various diseases, such as obesity and cancer. Genome-scale metabolic network reconstructions capture genomic, physiological, and biochemical knowledge of a target organism, along with a detailed representation of the cellular metabolite transport mechanisms. Since the first reconstruction of human metabolism, Recon 1, published in 2007, progress has been made in the field of metabolite transport. Recently, we published an updated reconstruction, Recon 2, which significantly improved the metabolic coverage and functionality. Human metabolic reconstructions have been used to investigate the role of metabolism in disease and to predict biomarkers and drug targets. Given the importance of cellular transport systems in understanding human metabolism in health and disease, we analyzed the coverage of transport systems for various metabolite classes in Recon 2. We will review the current knowledge on transporters (i.e., their preferred substrates, transport mechanisms, metabolic relevance, and disease association for each metabolite class). We will assess missing coverage and propose modifications and additions through a transport module that is functional when combined with Recon 2. This information will be valuable for further refinements. These data will also provide starting points for further experiments by highlighting areas of incomplete knowledge. This review represents the first comprehensive overview of the transporters involved in central metabolism and their transport mechanisms, thus serving as a compendium of metabolite transporters specific for human metabolic reconstructions. [less ▲]

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See detailSerum sphingolipids level as a novel potential marker for early detection of human myocardial ischaemic injury.
Egom, Emmanuel E.; Mamas, Mamas A.; Chacko, Sanoj et al

in Frontiers in physiology (2013), 4

Background: Ventricular tachyarrhythmias are the most common and often the first manifestation of coronary heart disease and lead to sudden cardiac death (SCD). Early detection/identification of acute ... [more ▼]

Background: Ventricular tachyarrhythmias are the most common and often the first manifestation of coronary heart disease and lead to sudden cardiac death (SCD). Early detection/identification of acute myocardial ischaemic injury at risk for malignant ventricular arrhythmias in patients remains an unmet medical need. In the present study, we examined the sphingolipids level after transient cardiac ischaemia following temporary coronary artery occlusion during percutaneous coronary intervention (PCI) in patients and determined the role of sphingolipids level as a novel marker for early detection of human myocardial ischaemic injury. Methods and Results: Venous samples were collected from either the coronary sinus (n = 7) or femoral vein (n = 24) from 31 patients aged 40-73 years-old at 1, 5 min, and 12 h, following elective PCI. Plasma sphingolipids levels were assessed by HPLC. At 1 min coronary sinus levels of sphingosine 1-phosphate (S1P), sphingosine (SPH), and sphinganine (SA) were increased by 314, 115, and 614%, respectively (n = 7), while peripheral blood levels increased by 79, 68, and 272% (n = 24). By 5 min, coronary sinus S1P and SPH levels increased further (720%, 117%), as did peripheral levels of S1P alone (792%). Where troponin T was detectable at 12 h (10 of 31), a strong correlation was found with peak S1P (R (2) = 0.818; P < 0.0001). Conclusion: For the first time, we demonstrate the behavior of plasma sphingolipids following transient cardiac ischaemia in humans. The observation supports the important role of sphingolipids level as a potential novel marker of transient or prolonged myocardial ischaemia. [less ▲]

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See detailMechanistic modeling of aberrant energy metabolism in human disease.
Sangar, Vineet; Eddy, James A.; Simeonidis, Evangelos UL et al

in Frontiers in Physiology (2012), 3

Dysfunction in energy metabolism-including in pathways localized to the mitochondria-has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases ... [more ▼]

Dysfunction in energy metabolism-including in pathways localized to the mitochondria-has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases to type II diabetes. The inherent complexities of energy and mitochondrial metabolism present a significant obstacle in the effort to understand the role that these molecular processes play in the development of disease. To help unravel these complexities, systems biology methods have been applied to develop an array of computational metabolic models, ranging from mitochondria-specific processes to genome-scale cellular networks. These constraint-based (CB) models can efficiently simulate aspects of normal and aberrant metabolism in various genetic and environmental conditions. Development of these models leverages-and also provides a powerful means to integrate and interpret-information from a wide range of sources including genomics, proteomics, metabolomics, and enzyme kinetics. Here, we review a variety of mechanistic modeling studies that explore metabolic functions, deficiency disorders, and aberrant biochemical pathways in mitochondria and related regions in the cell. [less ▲]

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See detailUnderstanding complexity in neurodegenerative diseases: in silico reconstruction of emergence.
Kolodkin, Alexey UL; Simeonidis, Evangelos UL; Balling, Rudi UL et al

in Frontiers in Physiology (2012), 3

Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent ... [more ▼]

Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent property, emerging from a perturbation of the network. On the one hand, the biomolecular network of every individual is unique and this is evident when similar disease-producing agents cause different individual pathologies. Consequently, a personalized model and approach for every patient may be required for therapies to become effective across mankind. On the other hand, diverse combinations of internal and external perturbation factors may cause a similar shift in network functioning. We offer this as an explanation for the multi-factorial nature of most diseases: they are "systems biology diseases," or "network diseases." Here we use neurodegenerative diseases, like Parkinson's disease (PD), as an example to show that due to the inherent complexity of these networks, it is difficult to understand multi-factorial diseases with simply our "naked brain." When describing interactions between biomolecules through mathematical equations and integrating those equations into a mathematical model, we try to reconstruct the emergent properties of the system in silico. The reconstruction of emergence from interactions between huge numbers of macromolecules is one of the aims of systems biology. Systems biology approaches enable us to break through the limitation of the human brain to perceive the extraordinarily large number of interactions, but this also means that we delegate the understanding of reality to the computer. We no longer recognize all those essences in the system's design crucial for important physiological behavior (the so-called "design principles" of the system). In this paper we review evidence that by using more abstract approaches and by experimenting in silico, one may still be able to discover and understand the design principles that govern behavioral emergence. [less ▲]

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