1. |
- Erdem, Cemal, et al.
(author)
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Mathematical modeling of Behçet's disease : A dynamical systems approach
- 2015
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In: Journal of biological systems. - : World Scientific. - 0218-3390. ; 23:02, s. 231-257
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Journal article (peer-reviewed)abstract
- Behçet's Disease (BD) is a multi-systemic, auto-inflammatory disorder that is characterized by recurrent episodes of inflammatory manifestations affecting skin, mucosa, eyes, blood vessels, joints and several other organs. BD is classified as a multifactorial disease with an important contribution of genetics. Genetic studies suggest that there is a strong association of BD with a Class I major histocompatibility complex antigen, named HLA-B*51, along with several other weaker associations with genes encoding proteins involved in inflammation. However, pathogenic mechanisms associated with these genetic variations and their interactions with the environment have not been elucidated yet. In this paper, we present a mathematical model for BD based on a dynamical systems perspective that captures especially the relapsing nature of the disease. We propose a disease progression mechanism and construct a model, in the form of coupled ordinary differential equations (ODEs), which reveals the occurrence pattern of the disease in the population. According to our model, the disease has three distinct modes describing different phenotypes of people carrying HLA-B*51 tissue antigen, namely, the Healthy Carrier, the Potential Patient and the Active Patient. We herein present an exemplary mathematical model for BD, for the first time in the literature, that concisely captures the actions of many cell types together with genetic and environmental effects. The proposed model provides insight into this complex inflammatory disease which may lead to identification of new tools for its treatment and prevention.
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2. |
- Holmér, Jennie, et al.
(author)
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Evolution of Prey Polymorphism Induced by Learning Predators
- 2011
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In: Journal of Biological Systems. - 0218-3390. ; 19:2, s. 319-328
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Journal article (peer-reviewed)abstract
- A prey species using crypsis to avoid predators has the opportunity to evolve polymorphic crypsis when it is being exposed to two (or more) habitats with different backgrounds. Here, we investigate when this phenomenon can occur, in a simulation study with a sexually reproducing prey and a predator that can learn to find hiding prey, represented by an artificial neural network. Initially, the prey is well adapted to one habitat, but tries to expand its range by invading another, different, habitat. This can cause the prey to evolve toward an intermediate phenotype, equally cryptic in both habitats. The prey can also fail in adapting to its new environment, and stay the same. Alternatively, it can evolve polymorphic crypsis. We find that the evolutionary outcome depends on the amount of dispersal between the habitats, with polymorphic crypsis evolving for low dispersal rates, an intermediate phenotype will evolve for intermediate dispersal rates and no adaptation to the new habitat will occur for high dispersal rates. The distribution of phenotypes of the prey will also vary for different dispersal rates, with narrow distributions for low and high dispersal rate and a wide distribution for intermediate dispersal rates.
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3. |
- Lundh, Dan, et al.
(author)
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Arsenic accumulation in plants - Outlining strategies for developing improved variety of crops for avoiding arsenic toxicity in foods
- 2010
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In: Journal of biological systems. - : World Scientific Publishing. - 0218-3390. ; 18:1, s. 223-241
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Journal article (peer-reviewed)abstract
- Contamination of food with arsenics is a potential health risk for both humans and animals in many regions of the world, especially in Asia. Arsenics can be accumulated in humans, animals and plants for a longer period and a long-term exposure of humans to arsenics results in severe damage of kidney, lever, heart etc. and many other vascular diseases. Arsenic contamination in human may also lead to development of cancer. In this paper we report our results on data mining approach (an in silico analysis based on searching of the existing genomic databases) for identification and characterization of genes that might be responsible for uptake, accumulation or metabolism of arsenics. For these in silico analyses we have involved the model plant Arabidopsis thaliana in our investigation. By employing a system biology model (a kinetic model) we have studied the molecular mechanisms of these processes in this plant. This model contains equations for uptake, metabolism and sequestration of different types of arsenic; As(V), As(III), MMAA and DMAA. The model was then implemented in the software XPP. The model was also validated against the data existing in the literatures. Based on the results of these in silico studies we have developed some strategies that can be used for reducing arsenic contents in different parts of the plant. Data mining experiments resulted in identification of two candidate genes (ACR2, arsenate reductase 2 and PCS1, phytochelatin synthase 1) that are involved either in uptake, transport or cellular localization of arsenic in A. thaliana. However, our system biology model revealed that by increasing the level of arsenate reductase together with an increased rate of arsenite sequestration in the vacuoles (by involving an arsenite efflux pump MRP1/2), it is possible to reduce the amount of arsenics in the shoots of A. thaliana to 11–12%.
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4. |
- Samanta, Sudipta, et al.
(author)
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Dependence of homo-lumo gap of DNA base pair steps on twist angle : A density fuctional approach
- 2018
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In: Journal of biological systems. - : WORLD SCIENTIFIC PUBL CO PTE LTD. - 0218-3390. ; 26:1, s. 23-40
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Journal article (peer-reviewed)abstract
- Electronic structure calculations of all 10 unique base pair (bp) steps have been calculated to study the interaction energies of the bp steps, density of states (DOS), projected density of states (pDOS) using the density functional theory (DFT). Plane wave basis with ultrasoft pseudo-potential method has been used within the local density approximation (LDA) for the exchange correlation functional. Electron densities of the bp steps corresponding to HOMO and LUMO level have been calculated to understand the difference in stacking energies of the bp steps. The variation of HOMO-LUMO gap (g) of all possible bp steps on twist angle has been studied. We have observed that out of the 10 bp steps, 4 purine-purine bp steps (d(AA), d(GG), d(AG) and d(GA)), show significant variation of g on twist angle. The observed variation on twist angle of d(AA) bp step has been explained by the calculated DOS and electron densities.
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5. |
- Sögård, Peter, et al.
(author)
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Validation of the in vitro incubation of extensor digitorum longus muscle from mice with a mathematical model
- 2010
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In: Journal of biological systems. - : World Scientific. - 0218-3390. ; 18:3, s. 687-707
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Journal article (peer-reviewed)abstract
- In vitro incubation of tissues; in particular, skeletal muscles from rodents, is a widely-used experimental method in diabetes research. This experimental method has previously been validated, both experimentally and theoretically. However, much of the method's experimental data remains unclear, including the high-rate of lactate production and the lack of an observable increase in glycogen content, within a given time. The predominant hypothesis explaining the high-rate of lactate production is that this phenomenon is dependent on a mechanism in glycolysis that works as a safety valve, producing lactate when glucose uptake is super-physiological. Another hypothesis is that existing anoxia forces more ATP to be produced from glycolysis, leading to an increased lactate concentration. The lack of an observable increase in glycogen content is assumed to be dependent on limitations in sensitivity of the measuring method used. We derived a mathematical model to investigate which of these hypotheses is most likely to be correct. Using our model, data analysis indicates that the in vitro incubated muscle specimens, most likely are sensing the presence of existing anoxia, rather than an overflow in glycolysis. The anoxic milieu causes the high lactate production. The model also predicts an increased glycogenolysis. After mathematical analyses, an estimation of the glycogen concentration could be made with a reduced model. In conclusion, central anoxia is likely to cause spatial differences in glycogen concentrations throughout the entire muscle. Thus, data regarding total glycogen levels in the incubated muscle do not accurately represent the entire organ. The presented model allows for an estimation of total glycogen, despite spatial differences present in the muscle specimen.
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