Research

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Open AccessArticle

Scatter Search Applied to the Inference of a Development Gene Network

by Amir Masoud Abdol, Damjan Cicin-Sain, Jaap A. Kaandorp and Anton Crombach

Computation 2017, 5(2), 22; https://doi.org/10.3390/computation5020022 - 04 May 2017

Cited by 4 | Viewed by 5610

Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods. [...] Read more.

Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods. Therefore, reducing computational cost and providing quick feedback at intermediate stages are desirable features for network inference. Here we propose a hybrid approach composed of two stages: exploration with scatter search and exploitation of intermediate solutions with low temperature simulated annealing. We test the approach on the well-understood process of early body plan development in flies, focusing on the gap gene network. We compare the hybrid approach to simulated annealing, a method of network inference with a proven track record. We find that scatter search performs well at exploring parameter space and that low temperature simulated annealing refines the intermediate results into excellent model fits. From this we conclude that for poorly-studied developmental systems, scatter search is a valuable tool for exploration and accelerates the elucidation of gene regulatory networks. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessArticle

A Hybrid Computation Model to Describe the Progression of Multiple Myeloma and Its Intra-Clonal Heterogeneity

by Anass Bouchnita, Fatima-Ezzahra Belmaati, Rajae Aboulaich, Mark J. Koury and Vitaly Volpert

Computation 2017, 5(1), 16; https://doi.org/10.3390/computation5010016 - 10 Mar 2017

Cited by 15 | Viewed by 5688

Abstract

Multiple myeloma (MM) is a genetically complex hematological cancer that is characterized by proliferation of malignant plasma cells in the bone marrow. MM evolves from the clonal premalignant disorder monoclonal gammopathy of unknown signiﬁcance (MGUS) by sequential genetic changes involving many different genes, [...] Read more.

Multiple myeloma (MM) is a genetically complex hematological cancer that is characterized by proliferation of malignant plasma cells in the bone marrow. MM evolves from the clonal premalignant disorder monoclonal gammopathy of unknown signiﬁcance (MGUS) by sequential genetic changes involving many different genes, resulting in dysregulated growth of multiple clones of plasma cells. The migration, survival, and proliferation of these clones require the direct and indirect interactions with the non-hematopoietic cells of the bone marrow. We develop a hybrid discrete-continuous model of MM development from the MGUS stage. The discrete aspect of the modelisobservedatthecellularlevel: cellsarerepresentedasindividualobjectswhichmove,interact, divide, and die by apoptosis. Each of these actions is regulated by intracellular and extracellular processes as described by continuous models. The hybrid model consists of the following submodels that have been simpliﬁed from the much more complex state of evolving MM: cell motion due to chemotaxis, intracellular regulation of plasma cells, extracellular regulation in the bone marrow, and acquisition of mutations upon cell division. By extending a previous, simpler model in which the extracellular matrix was considered to be uniformly distributed, the new hybrid model provides a more accurate description in which cytokines are produced by the marrow microenvironment and consumed by the myeloma cells. The complex multiple genetic changes in MM cells and the numerous cell-cell and cytokine-mediated interactions between myeloma cells and their marrow microenviroment are simpliﬁed in the model such that four related but evolving MM clones can be studied as they compete for dominance in the setting of intraclonal heterogeneity. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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1023 KiB

Open AccessArticle

Simpliﬁcation of Reaction Networks, Conﬂuence and Elementary Modes

by Guillaume Madelaine, Elisa Tonello, Cédric Lhoussaine and Joachim Niehren

Computation 2017, 5(1), 14; https://doi.org/10.3390/computation5010014 - 10 Mar 2017

Cited by 1 | Viewed by 4351

Abstract

Reaction networks can be simpliﬁed by eliminating linear intermediate species in partial steadystates. Inthispaper,westudythequestionwhetherthisrewriteprocedureisconﬂuent,so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We ﬁrst show that conﬂuence fails for the [...] Read more.

Reaction networks can be simpliﬁed by eliminating linear intermediate species in partial steadystates. Inthispaper,westudythequestionwhetherthisrewriteprocedureisconﬂuent,so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We ﬁrst show that conﬂuence fails for the elimination of intermediates even without kinetics, if “dependent reactions” introduced by the simpliﬁcation are not removed. This leads us to revising the simpliﬁcation algorithm into a variant of the double description method for computing elementary modes, so that it keeps track of kinetic information. Folklore results on elementary modes imply the conﬂuence of the revised simpliﬁcation algorithm with respect to the network structure, i.e., the structure of fully simpliﬁed networks is unique. We show, however, that the kinetic rates assigned to the reactions may not be unique, and provide a biological example where two different simpliﬁed networks can be obtained. Finally, we give a criterion on the structure of the initial network that is sufﬁcient to guarantee the conﬂuence of both the structure and the kinetic rates. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessArticle

Multiscale CT-Based Computational Modeling of Alveolar Gas Exchange during Artificial Lung Ventilation, Cluster (Biot) and Periodic (Cheyne-Stokes) Breathings and Bronchial Asthma Attack

by Andrey Golov, Sergey Simakov, Yan Naing Soe, Roman Pryamonosov, Ospan Mynbaev and Alexander Kholodov

Computation 2017, 5(1), 11; https://doi.org/10.3390/computation5010011 - 18 Feb 2017

Cited by 7 | Viewed by 6101

Abstract

An airflow in the first four generations of the tracheobronchial tree was simulated by the 1D model of incompressible fluid flow through the network of the elastic tubes coupled with 0D models of lumped alveolar components, which aggregates parts of the alveolar volume [...] Read more.

An airflow in the first four generations of the tracheobronchial tree was simulated by the 1D model of incompressible fluid flow through the network of the elastic tubes coupled with 0D models of lumped alveolar components, which aggregates parts of the alveolar volume and smaller airways, extended with convective transport model throughout the lung and alveolar components which were combined with the model of oxygen and carbon dioxide transport between the alveolar volume and the averaged blood compartment during pathological respiratory conditions. The novel features of this work are 1D reconstruction of the tracheobronchial tree structure on the basis of 3D segmentation of the computed tomography (CT) data; 1D−0D coupling of the models of 1D bronchial tube and 0D alveolar components; and the alveolar gas exchange model. The results of our simulations include mechanical ventilation, breathing patterns of severely ill patients with the cluster (Biot) and periodic (Cheyne-Stokes) respirations and bronchial asthma attack. The suitability of the proposed mathematical model was validated. Carbon dioxide elimination efficiency was analyzed in all these cases. In the future, these results might be integrated into research and practical studies aimed to design cyberbiological systems for remote real-time monitoring, classification, prediction of breathing patterns and alveolar gas exchange for patients with breathing problems. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessArticle

Towards a Multiscale Model of Acute HIV Infection

by Anass Bouchnita, Gennady Bocharov, Andreas Meyerhans and Vitaly Volpert

Computation 2017, 5(1), 6; https://doi.org/10.3390/computation5010006 - 10 Jan 2017

Cited by 18 | Viewed by 7726

Abstract

Human Immunodeficiency Virus (HIV) infection of humans represents a complex biological system and a great challenge to public health. Novel approaches for the analysis and prediction of the infection dynamics based on a multi-scale integration of virus ontogeny and immune reactions are needed [...] Read more.

Human Immunodeficiency Virus (HIV) infection of humans represents a complex biological system and a great challenge to public health. Novel approaches for the analysis and prediction of the infection dynamics based on a multi-scale integration of virus ontogeny and immune reactions are needed to deal with the systems’ complexity. The aim of our study is: (1) to formulate a multi-scale mathematical model of HIV infection; (2) to implement the model computationally following a hybrid approach; and (3) to calibrate the model by estimating the parameter values enabling one to reproduce the “standard” observed dynamics of HIV infection in blood during the acute phase of primary infection. The modeling approach integrates the processes of infection spread and immune responses in Lymph Nodes (LN) to that observed in blood. The spatio-temporal population dynamics of T lymphocytes in LN in response to HIV infection is governed by equations linking an intracellular regulation of the lymphocyte fate by intercellular cytokine fields. We describe the balance of proliferation, differentiation and death at a single cell level as a consequence of gene activation via multiple signaling pathways activated by IL-2, IFNa and FasL. Distinct activation thresholds are used in the model to relate different modes of cellular responses to the hierarchy of the relative levels of the cytokines. We specify a reference set of model parameter values for the fundamental processes in lymph nodes that ensures a reasonable agreement with viral load and CD4⁺ T cell dynamics in blood. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessArticle

Critical Issues in Modelling Lymph Node Physiology

by Dmitry Grebennikov, Raoul Van Loon, Mario Novkovic, Lucas Onder, Rostislav Savinkov, Igor Sazonov, Rufina Tretyakova, Daniel J. Watson and Gennady Bocharov

Computation 2017, 5(1), 3; https://doi.org/10.3390/computation5010003 - 24 Dec 2016

Cited by 10 | Viewed by 6707

Abstract

In this study, we discuss critical issues in modelling the structure and function of lymph nodes (LNs), with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell [...] Read more.

In this study, we discuss critical issues in modelling the structure and function of lymph nodes (LNs), with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell zone, there are vascular networks which play a key role in the delivery of information to the inner parts of the LN, i.e., the conduit and blood microvascular networks. We propose object-oriented computational algorithms to model the 3D geometry of the fibroblastic reticular cell (FRC) network and the microvasculature. Assuming that a conduit cylinder is densely packed with collagen fibers, the computational flow study predicted that the diffusion should be a dominating process in mass transport than convective flow. The geometry models are used to analyze the lymph flow properties through the conduit network in unperturbed- and damaged states of the LN. The analysis predicts that elimination of up to 60%–90% of edges is required to stop the lymph flux. This result suggests a high degree of functional robustness of the network. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessArticle

A Mathematical Spline-Based Model of Cardiac Left Ventricle Anatomy and Morphology

by Sergei Pravdin

Computation 2016, 4(4), 42; https://doi.org/10.3390/computation4040042 - 27 Oct 2016

Cited by 3 | Viewed by 5124

Abstract

Computer simulation of normal and diseased human heart activity requires a 3D anatomical model of the myocardium, including myofibers. For clinical applications, such a model has to be constructed based on routine methods of cardiac visualization, such as sonography. Symmetrical models are shown [...] Read more.

Computer simulation of normal and diseased human heart activity requires a 3D anatomical model of the myocardium, including myofibers. For clinical applications, such a model has to be constructed based on routine methods of cardiac visualization, such as sonography. Symmetrical models are shown to be too rigid, so an analytical non-symmetrical model with enough flexibility is necessary. Based on previously-made anatomical models of the left ventricle, we propose a new, much more flexible spline-based analytical model. The model is fully described and verified against DT-MRI data. We show a way to construct it on the basis of sonography data. To use this model in further physiological simulations, we propose a numerical method to utilize finite differences in solving the reaction-diffusion problem together with an example of scroll wave dynamics simulation. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessFeature PaperArticle

A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection

by Simeone Marino and Denise E. Kirschner

Computation 2016, 4(4), 39; https://doi.org/10.3390/computation4040039 - 21 Oct 2016

Cited by 33 | Viewed by 8862

Abstract

Tuberculosis (TB) is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB). The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs) is the formation of spherical structures, primarily in lungs, [...] Read more.

Tuberculosis (TB) is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB). The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs) is the formation of spherical structures, primarily in lungs, called granulomas. Infection occurs after inhalation of bacteria into lungs, where resident antigen-presenting cells (APCs), take up bacteria and initiate the immune response to Mtb infection. APCs traffic from the site of infection (lung) to lung-draining lymph nodes (LNs) where they prime T cells to recognize Mtb. These T cells, circulating back through blood, migrate back to lungs to perform their immune effector functions. We have previously developed a hybrid agent-based model (ABM, labeled GranSim) describing in silico immune cell, bacterial (Mtb) and molecular behaviors during tuberculosis infection and recently linked that model to operate across three physiological compartments: lung (infection site where granulomas form), lung draining lymph node (LN, site of generation of adaptive immunity) and blood (a measurable compartment). Granuloma formation and function is captured by a spatio-temporal model (i.e., ABM), while LN and blood compartments represent temporal dynamics of the whole body in response to infection and are captured with ordinary differential equations (ODEs). In order to have a more mechanistic representation of APC trafficking from the lung to the lymph node, and to better capture antigen presentation in a draining LN, this current study incorporates the role of dendritic cells (DCs) in a computational fashion into GranSim. Results: The model was calibrated using experimental data from the lungs and blood of NHPs. The addition of DCs allowed us to investigate in greater detail mechanisms of recruitment, trafficking and antigen presentation and their role in tuberculosis infection. Conclusion: The main conclusion of this study is that early events after Mtb infection are critical to establishing a timely and effective response. Manipulating CD8+ and CD4+ T cell proliferation rates, as well as DC migration early on during infection can determine the difference between bacterial clearance vs. uncontrolled bacterial growth and dissemination. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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Open AccessArticle

Image Segmentation for Cardiovascular Biomedical Applications at Different Scales

by Alexander Danilov, Roman Pryamonosov and Alexandra Yurova

Computation 2016, 4(3), 35; https://doi.org/10.3390/computation4030035 - 15 Sep 2016

Cited by 9 | Viewed by 5236

Abstract

In this study, we present several image segmentation techniques for various image scales and modalities. We consider cellular-, organ-, and whole organism-levels of biological structures in cardiovascular applications. Several automatic segmentation techniques are presented and discussed in this work. The overall pipeline for [...] Read more.

In this study, we present several image segmentation techniques for various image scales and modalities. We consider cellular-, organ-, and whole organism-levels of biological structures in cardiovascular applications. Several automatic segmentation techniques are presented and discussed in this work. The overall pipeline for reconstruction of biological structures consists of the following steps: image pre-processing, feature detection, initial mask generation, mask processing, and segmentation post-processing. Several examples of image segmentation are presented, including patient-specific abdominal tissues segmentation, vascular network identification and myocyte lipid droplet micro-structure reconstruction. Full article

(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)

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