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4. Multi-Agent Systems and Blood Cell Formation

Author

Bessonov, Nikolai, Demin, Ivan, Kurbatova, Polina, Pujo, Laurent, and Volpert, Vitaly

Subjects
Quantitative Biology - Tissues and Organs, Mathematics - Dynamical Systems
Abstract

The objective of this chapter is to give an insight of the mathematical modellng of hematopoiesis using multi-agent systems. Several questions may arise then: what is hematopoiesis and why is it interesting to study this problem from a mathematical point of view? Has the multi-agent system approach been the only attempt done until now? What does it bring more than other techniques? What were the results obtained? What is there left to do?

Published
2013
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5. Modelling Erythroblastic Islands: Using a Hybrid Model to Assess the Function of Central Macrophage

Author

Fischer, Stephan, Kurbatova, Polina, Bessonov, Nikolai, Gandrillon, Olivier, Volpert, Vitaly, and Crauste, Fabien

Subjects
Quantitative Biology - Quantitative Methods, Physics - Biological Physics, Quantitative Biology - Cell Behavior
Abstract

The production and regulation of red blood cells, erythropoiesis, occurs in the bone marrow where erythroid cells proliferate and differentiate within particular structures, called erythroblastic islands. A typical structure of these islands consists in a macrophage (white cell) surrounded by immature erythroid cells (progenitors), with more mature cells on the periphery of the island, ready to leave the bone marrow and enter the bloodstream. A hybrid model, coupling a continuous model (ordinary differential equations) describing intracellular regulation through competition of two key proteins, to a discrete spatial model describing cell-cell interactions, with growth factor diffusion in the medium described by a continuous model (partial differential equations), is proposed to investigate the role of the central macrophage in normal erythropoiesis. Intracellular competition of the two proteins leads the erythroid cell to either proliferation, differentiation, or death by apoptosis. This approach allows considering spatial aspects of erythropoiesis, involved for instance in the occurrence of cellular interactions or the access to external factors, as well as dynamics of intracellular and extracellular scales of this complex cellular process, accounting for stochasticity in cell cycle durations and orientation of the mitotic spindle. The analysis of the model shows a strong effect of the central macrophage on the stability of an erythroblastic island, when assuming the macrophage releases pro-survival cytokines. Even though it is not clear whether or not erythroblastic island stability must be required, investigation of the model concludes that stability improves responsiveness of the model, hence stressing out the potential relevance of the central macrophage in normal erythropoiesis.

Published
2011

7. Emergence and competition of virus variants in respiratory viral infections

Author

Bessonov, Nikolai, Neverova, Daria, Popov, Vladimir, and Volpert, Vitaly

Subjects
Immunology, Immunology and Allergy
Abstract

The emergence of new variants of concern (VOCs) of the SARS-CoV-2 infection is one of the main factors of epidemic progression. Their development can be characterized by three critical stages: virus mutation leading to the appearance of new viable variants; the competition of different variants leading to the production of a sufficiently large number of copies; and infection transmission between individuals and its spreading in the population. The first two stages take place at the individual level (infected individual), while the third one takes place at the population level with possible competition between different variants. This work is devoted to the mathematical modeling of the first two stages of this process: the emergence of new variants and their progression in the epithelial tissue with a possible competition between them. The emergence of new virus variants is modeled with non-local reaction–diffusion equations describing virus evolution and immune escape in the space of genotypes. The conditions of the emergence of new virus variants are determined by the mutation rate, the cross-reactivity of the immune response, and the rates of virus replication and death. Once different variants emerge, they spread in the infected tissue with a certain speed and viral load that can be determined through the parameters of the model. The competition of different variants for uninfected cells leads to the emergence of a single dominant variant and the elimination of the others due to competitive exclusion. The dominant variant is the one with the maximal individual spreading speed. Thus, the emergence of new variants at the individual level is determined by the immune escape and by the virus spreading speed in the infected tissue.

Published
2023
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13. Mathematical modeling of respiratory viral infection and applications to SARS‐CoV‐2 progression.

Author

Ait Mahiout, Latifa, Bessonov, Nikolai, Kazmierczak, Bogdan, and Volpert, Vitaly

Subjects
*SARS-CoV-2 Delta variant, *SARS-CoV-2 Omicron variant, *RESPIRATORY infections, *SARS-CoV-2, *REACTION-diffusion equations, *COVID-19, *VIRUS diseases, *PLANT viruses
Abstract

Viral infection in cell culture and tissue is modeled with delay reaction‐diffusion equations. It is shown that progression of viral infection can be characterized by the viral replication number, time‐dependent viral load, and the speed of infection spreading. These three characteristics are determined through the original model parameters including the rates of cell infection and of virus production in the infected cells. The clinical manifestations of viral infection, depending on tissue damage, correlate with the speed of infection spreading, while the infectivity of a respiratory infection depends on the viral load in the upper respiratory tract. Parameter determination from the experiments on Delta and Omicron variants allows the estimation of the infection spreading speed and viral load. Different variants of the SARS‐CoV‐2 infection are compared confirming that Omicron is more infectious and has less severe symptoms than Delta variant. Within the same variant, spreading speed (symptoms) correlates with viral load allowing prognosis of disease progression. [ABSTRACT FROM AUTHOR]

Published
2023
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21. The inconvenience of data of convenience: computational research beyond post-mortem analyses

Author

Azencott, Chloé-Agathe, Aittokallio, Tero, Roy, Sushmita, Agrawal, Ankit, Barillot, Emmanuel, Bessonov, Nikolai, Chasman, Deborah, Czerwinska, Urszula, Siahpirani, Alireza Fotuhi, Friend, Stephen, Goldenberg, Anna, Greenberg, Jan, Huber, Manuel, Kaski, Samuel, Kurz, Christoph, Mailick, Marsha, Merzenich, Michael, Morozova, Mor, Movaghar, Arezoo, Nahum, Mor, Nordling, Torbjörn E M, Norman, Thea, Penner, Robert, Saha, Krishanu, Salim, Asif, Sorooshyari, Siamak, Soumelis, Vassili, Stark-Inbar, Alit, Sterling, Audra, Stolovitzky, Gustavo, Shiju, S S, Tang, Jing, Tosenberger, Alen, Vieet Van, Thomas, Wennerberg, Krister, Zinovyev, Andrey, Centre de Bioinformatique (CBIO), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut des Hautes Etudes Scientifiques (IHES), IHES, Immunité et cancer (U932), Université Paris Descartes - Paris 5 (UPD5)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Clermont Recherche Management (CleRMa), École Supérieure de Commerce (ESC) - Clermont-Ferrand (ESC Clermont-Ferrand)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Cancer et génôme: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, MINES ParisTech - École nationale supérieure des mines de Paris-Institut Curie-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Curie-Université Paris Descartes - Paris 5 (UPD5), Clermont Recherche Management - Clermont Auvergne (CleRMa), École Supérieure de Commerce (ESC) - Clermont-Ferrand-Université Clermont Auvergne (UCA), Mines Paris - PSL (École nationale supérieure des mines de Paris), and Institut des Hautes Études Scientifiques (IHES)

Subjects
0301 basic medicine, Data Analysis, Computer science, MEDLINE, Genome-wide association study, Computational biology, Biochemistry, Polymorphism, Single Nucleotide, Arthritis, Rheumatoid, 03 medical and health sciences, Predictive Value of Tests, Humans, Molecular Biology, ComputingMilieux_MISCELLANEOUS, Research data, ta113, ta112, ta111, Computational Biology, Cell Biology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 030104 developmental biology, Research Design, Predictive value of tests, Antirheumatic Agents, Biotechnology, Genome-Wide Association Study
Abstract

The inconvenience of data of convenience: computational research beyond post-mortem analyses

Published
2017
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23. The inconvenience of data of convenience: computational research beyond post-mortem analyses

Author

Azencott, Chloé Agathe, Aittokallio, Tero, Roy, Sushmita, Agrawal, Ankita, Barillot, Emmanuel, Bessonov, Nikolai, Chasman, Deborah, Czerwinska, Urszula, Siahpirani, Alireza Fotuhi, Greenberg, Jan, Hubert, Manuel, Kaski, Samuel, Kurz, Christopher, Mailick, Marsha, Merzenich, Michael, Morozova, Nadya, Movaghar, Arezoo, Nahum, Mor, Nordling, Torbjörn T.E.M., Penner, Robert, Saha, Krishanu, Salim, Asif, Sorooshyari, Siamak, Soumelis, Vassili, Stark-Inbar, Alit, Sterling, Audra, Shiju, S S, Tang, Jing, Tosenberger, Alen, Van Vieet, Thomas, Wennerberg, Krister, Zinovyev, Andrey, Norman, Thea, Friend, Stephen, Stolovitzky, Gustavo, Goldenberg, Anna, Azencott, Chloé Agathe, Aittokallio, Tero, Roy, Sushmita, Agrawal, Ankita, Barillot, Emmanuel, Bessonov, Nikolai, Chasman, Deborah, Czerwinska, Urszula, Siahpirani, Alireza Fotuhi, Greenberg, Jan, Hubert, Manuel, Kaski, Samuel, Kurz, Christopher, Mailick, Marsha, Merzenich, Michael, Morozova, Nadya, Movaghar, Arezoo, Nahum, Mor, Nordling, Torbjörn T.E.M., Penner, Robert, Saha, Krishanu, Salim, Asif, Sorooshyari, Siamak, Soumelis, Vassili, Stark-Inbar, Alit, Sterling, Audra, Shiju, S S, Tang, Jing, Tosenberger, Alen, Van Vieet, Thomas, Wennerberg, Krister, Zinovyev, Andrey, Norman, Thea, Friend, Stephen, Stolovitzky, Gustavo, and Goldenberg, Anna

Abstract

info:eu-repo/semantics/published

Published
2017

24. Target morphology and cell memory: a model of regenerative pattern formation Cell Memory Can Regulate Morphogenesis and Regeneration

Author

Bessonov, Nikolai, Levin, Michael, Morozova, Nadya, Reinberg, Natalia, Tosenberger, Alen, Volpert, Vitaly, Institute of Mechanical Engineering Problems [St. Petersburg] (IPME), Russian Academy of Sciences [Moscow] (RAS), Tufts Center for Regenerative and Developmental Biology [Medford] (TCRDB), Tufts University [Medford], Institut de Biologie et de Technologies de Saclay (IBITECS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Multi-scale modelling of cell dynamics : application to hematopoiesis (DRACULA), Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Modélisation mathématique, calcul scientifique (MMCS), Institut Camille Jordan [Villeurbanne] (ICJ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Camille Jordan (ICJ), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), and Institut Camille Jordan (ICJ)

Subjects
[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
Abstract

International audience; Despite the growing body of work on molecular components required for regenerative repair, westill lack a deep understanding of the ability of some animal species to regenerate their appropriatecomplex anatomical structure following damage. A key question is how regenerating systemsknow when to stop growth and remodeling – what mechanisms implement recognition of correctmorphology that signals a stop condition? In this work, we review two conceptual modelsof pattern regeneration that implement a kind of pattern memory. In the first one, all cells communicatewith each other and keep the value of the total signal received from the other cells. If apart of the pattern is amputated, the signal distribution changes. The difference from the originalsignal distribution stimulates cell proliferation and leads to pattern regeneration, in effect implementingan error minimization process that uses signaling memory to achieve pattern correction.In the second model, we consider a more complex pattern organization with different cell types.Each tissue contains a central (coordinator) cell that controls the tissue and communicates withthe other central cells. Each of them keeps memory about the signals received from other centralcells. The values of these signals depend on the mutual cell location, and the memory allowsregeneration of the structure when it is modified. The purpose of these models is to suggestpossible mechanisms of pattern regeneration operating on the basis of cell memory which arecompatible with diverse molecular implementation mechanisms within specific organisms.

Published
2015

25. Travelling Waves of Cell Dierentiation

Author

Benmir, Mohammed, Bessonov, Nikolai, Boujena, Soumaya, Volpert, Vitaly, Department of Mathematics [Casablanca], University Hassan II [Casablanca], Institute of Mechanical Engineering Problems [St. Petersburg] (IPME), Russian Academy of Sciences [Moscow] (RAS), Multi-scale modelling of cell dynamics : application to hematopoiesis (DRACULA), Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Modélisation mathématique, calcul scientifique (MMCS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Camille Jordan (ICJ), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), and Institut Camille Jordan (ICJ)

Subjects
[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
Abstract

International audience; The paper is devoted to modelling of cell dierentiation in an initially homogeneous cell population. The mechanism which provides coexistence of two cell lineages in the initially homogeneous cell population is suggested. If cell dierentiation is initiated locally in space in the population of undierentiated cells, it can propagate as a travelling wave converting undierentiated cells into dierentiated ones. We suggest a model of this process which takes into account intracellular regulation, extracellular regulation and dierent cell types. They include undierentiated cells and two types of dierentiated cells. When a cell dierentiates, its choice between two types of dierentiated cells is determined by the concentrations of intracellular proteins. Dierentiated cells can either stimulate dierentiation into their own cell lineage or into another cell lineage. In the case of the positive feedback, only one lineage of dierentiated cells will nally appear. In the case of negative feedback, both of them can coexist. In this case a periodic spatial pattern emerges behind the wave.

Published
2015

26. Acta Biotheoretica Mathematical and philosophical foundations of biological and biomedical science A Conceptual Model of Morphogenesis and Regeneration

Author

Tosenberger, Alen, Bessonov, Nikolai, Levin, M, Reinberg, Natalia, Volpert, Vitaly, Morozova, Nadya, Multi-scale modelling of cell dynamics : application to hematopoiesis (DRACULA), Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Modélisation mathématique, calcul scientifique (MMCS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Institute of Mechanical Engineering Problems [St. Petersburg] (IPME), Russian Academy of Sciences [Moscow] (RAS), Laboratorio de Biologia Molecular de la Enfermedad de Chagas [Buenos Aires] (LaBMECH), Instituto de Investigaciones en Ingeniería Genética y Biología Molecular, 'Dr. Héctor N. Torres' [Buenos Aires] (INGEBI), Facultad de Ciencias Exactas y Naturales [Buenos Aires] (FCEyN), Universidad de Buenos Aires [Buenos Aires] (UBA)-Universidad de Buenos Aires [Buenos Aires] (UBA)-Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Facultad de Ciencias Exactas y Naturales [Buenos Aires] (FCEyN), Universidad de Buenos Aires [Buenos Aires] (UBA)-Universidad de Buenos Aires [Buenos Aires] (UBA)-Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), Laboratoire Epigenetique et Cancer, Centre National de la Recherche Scientifique (CNRS), Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Camille Jordan (ICJ), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), Institut Camille Jordan (ICJ), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Facultad de Ciencias Exactas y Naturales [Buenos Aires] (FCEyN), and Universidad de Buenos Aires [Buenos Aires] (UBA)-Universidad de Buenos Aires [Buenos Aires] (UBA)

Subjects
[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
Abstract

International audience; This paper is devoted to computer modelling of the development andregeneration of multicellular biological structures. Some species (e.g. planaria andsalamanders) are able to regenerate parts of their body after amputation damage, butthe global rules governing cooperative cell behaviour during morphogenesis are notknown. Here, we consider a simplified model organism, which consists of tissuesformed around special cells that can be interpreted as stemcells. We assume that stemcells communicate with each other by a set of signals, and that the values of thesesignals depend on the distance between cells. Thus the signal distribution characterizeslocation of stem cells. If the signal distribution is changed, then the difference betweenthe initial and the current signal distribution affects the behaviour of stem cells—e.g.as a result of an amputation of a part of tissue the signal distribution changes whichstimulates stem cells to migrate to new locations, appropriate for regeneration of theproper pattern. Moreover, as stem cells divide and form tissues around them, theycontrol the form and the size of regenerating tissues. This two-level organization of themodel organism, with global regulation of stem cells and local regulation of tissues,allows its reproducible development and regeneration.

Published
2015
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27. Numerical implementation of hybrid models – discrete methods

Author

EMS-ESMTB Summer School on Mathematical Biology of Tissue Mechanics (2016: Leiden, Netherlands), Tosenberger, Alen, Bessonov, Nikolai, Bouchnita, Anass, Volpert, Vitaly, EMS-ESMTB Summer School on Mathematical Biology of Tissue Mechanics (2016: Leiden, Netherlands), Tosenberger, Alen, Bessonov, Nikolai, Bouchnita, Anass, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2016

28. Cardio-vascular diseases and blood coagulation – The influence of blood cells

Author

EMS-ESMTB Summer School on Mathematical Biology of Tissue Mechanics (2016: Leiden, Netherlands), Tosenberger, Alen, Bessonov, Nikolai, Bouchnita, Anass, Volpert, Vitaly, EMS-ESMTB Summer School on Mathematical Biology of Tissue Mechanics (2016: Leiden, Netherlands), Tosenberger, Alen, Bessonov, Nikolai, Bouchnita, Anass, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2016

29. Computational Algorithm for Some Problems with Variable Geometrical Structure

Author

Bessonov, Nikolai, Volpert, Vitaly, Institute of Mechanical Engineering Problems [St. Petersburg] (IPME), Russian Academy of Sciences [Moscow] (RAS), Institut Camille Jordan (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), Multi-scale modelling of cell dynamics : application to hematopoiesis (DRACULA), Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Camille Jordan (ICJ), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Institut Camille Jordan [Villeurbanne] (ICJ), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), and Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer Science::Systems and Control, Quantitative Biology::Tissues and Organs, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], ComputerApplications_COMPUTERSINOTHERSYSTEMS, ComputingMethodologies_GENERAL
Abstract

International audience; The work is devoted to the computational algorithm for a problem of plant growth. The plant is represented as a system of connected intervals corresponding to branches. We compute the concentration distributions inside the branches. The originality of the problem is that the geometry of the plant is not a priori given. It evolves in time depending on the concentrations of plant hormones found as a solution of the problem. New branches appear in the process of plant growth. The algorithm is adapted to an arbitrary plant structure and an arbitrary number of branches.

Published
2011
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30. Multi-Agent Systems and Blood Cell Formation

Author

Bessonov, Nikolai, Demin, Ivan, Kurbatova, Polina, Pujo-Menjouet, Laurent, Volpert, Vitaly, Institute of Mechanical Engineering Problems [St. Petersburg] (IPME), Russian Academy of Sciences [Moscow] (RAS), Novartis Pharma AG, Multi-scale modelling of cell dynamics : application to hematopoiesis (DRACULA), Institut Camille Jordan [Villeurbanne] (ICJ), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), InTech, Centre de génétique et de physiologie moléculaire et cellulaire (CGPhiMC), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Camille Jordan (ICJ), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS]
Abstract

International audience; The objective of this chapter is to give an insight of the mathematical modellng of hematopoiesis using multi-agent systems. Several questions may arise then: what is hematopoiesis and why is it interesting to study this problem from a mathematical point of view? Has the multi-agent system approach been the only attempt done until now? What does it bring more than other techniques? What were the results obtained? What is there left to do?

Published
2011
Full Text
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31. Hybrid model of clot formation in flow and its applications

Author

European Numerical Mathematics and Advanced Applications (ENUMATH) (2015: Ankara, Turkey), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, Volpert, Vitaly, European Numerical Mathematics and Advanced Applications (ENUMATH) (2015: Ankara, Turkey), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2015

32. Hybrid model of clot formation in flow and its applications

Author

Workshop on hybrid and multiscale modelling in cell and cell population biology (2015: Laboratoire Jacques-Louis Lions, UPMC, Paris, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, Volpert, Vitaly, Workshop on hybrid and multiscale modelling in cell and cell population biology (2015: Laboratoire Jacques-Louis Lions, UPMC, Paris, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2015

33. Hybrid model of clot formation in flow

Author

Tosenberger, Alen, Bessonov, Nikolai, Volpert, Vitaly, Tosenberger, Alen, Bessonov, Nikolai, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/published

Published
2015

34. On a model of pattern regeneration based on cell memory.

Author

Bessonov, Nikolai, Levin, Michael, Morozova, Nadya, Reinberg, Natalia, Tosenberger, Alen, Volpert, Vitaly, Bessonov, Nikolai, Levin, Michael, Morozova, Nadya, Reinberg, Natalia, Tosenberger, Alen, and Volpert, Vitaly

Abstract

We present here a new model of the cellular dynamics that enable regeneration of complex biological morphologies. Biological cell structures are considered as an ensemble of mathematical points on the plane. Each cell produces a signal which propagates in space and is received by other cells. The total signal received by each cell forms a signal distribution defined on the cell structure. This distribution characterizes the geometry of the cell structure. If a part of this structure is removed, the remaining cells have two signals. They keep the value of the signal which they had before the amputation (memory), and they receive a new signal produced after the amputation. Regeneration of the cell structure is stimulated by the difference between the old and the new signals. It is stopped when the two signals coincide. The algorithm of regeneration contains certain rules which are essential for its functioning, being the first quantitative model of cellular memory that implements regeneration of complex patterns to a specific target morphology. Correct regeneration depends on the form and the size of the cell structure, as well as on some parameters of regeneration., info:eu-repo/semantics/published

Published
2015

35. Target morphology and cell memory: A model of regenerative pattern formation

Author

Bessonov, Nikolai, Levin, Michael, Morozova, Nadya, Reinberg, Natalia, Tosenberger, Alen, Volpert, Vitaly, Bessonov, Nikolai, Levin, Michael, Morozova, Nadya, Reinberg, Natalia, Tosenberger, Alen, and Volpert, Vitaly

Abstract

Despite the growing body of work on molecular components required for regenerative repair, we still lack a deep understanding of the ability of some animal species to regenerate their appropriate complex anatomical structure following damage. A key question is how regenerating systems know when to stop growth and remodeling – what mechanisms implement recognition of correct morphology that signals a stop condition? In this work, we review two conceptual models of pattern regeneration that implement a kind of pattern memory. In the first one, all cells communicate with each other and keep the value of the total signal received from the other cells. If a part of the pattern is amputated, the signal distribution changes. The difference fromthe original signal distribution stimulates cell proliferation and leads to pattern regeneration, in effect implementing an error minimization process that uses signaling memory to achieve pattern correction. In the second model, we consider a more complex pattern organization with different cell types. Each tissue contains a central (coordinator) cell that controls the tissue and communicates with the other central cells. Each of them keeps memory about the signals received from other central cells. The values of these signals depend on the mutual cell location, and the memory allows regeneration of the structure when it is modified. The purpose of these models is to suggest possible mechanisms of pattern regeneration operating on the basis of cell memory which are compatible with diverse molecular implementation mechanisms within specific organisms., SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2015

36. Transient interfacial phenomena in miscible liquids

Author

Volpert, Vitaly, POJMAN, John, Bessonov, Nikolai, Association Française de Mécanique, and Service irevues, irevues

Subjects
modelling, diffuse interface, miscible liquids, [PHYS.MECA]Physics [physics]/Mechanics [physics], [PHYS.MECA] Physics [physics]/Mechanics [physics]
Abstract

Colloque avec actes et comité de lecture. Internationale.; International audience; Composition gradients in miscible liquids can create volume forces resulting in various interfacial phenomena. They are more difficult to study than in the case of immiscible liquids: they are weak and transient in time. In this work we present some experimental evidences of interfacial phenomena in miscible liquids and numerical simulations of miscible drops and diffuse interfaces.

Published
2007

39. Modelling of platelet-fibrin clot formation in flow with a DPD-PDE method

Author

9th European Conference on Mathemathical and Theoretical Biology (ECMTB) (2014: Gothenburg, Sweden), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, Volpert, Vitaly, 9th European Conference on Mathemathical and Theoretical Biology (ECMTB) (2014: Gothenburg, Sweden), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2014

40. Modelling of thrombus growth in flow with a DPD-PDE method

Author

Third International Workshop on the Multiscale Modelling and Methods (2013: Saint-Etienne, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, Volpert, Vitaly, Third International Workshop on the Multiscale Modelling and Methods (2013: Saint-Etienne, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2013

41. Modelling of thrombus growth in flow with a DPD-PDE method

Author

Workshop of Moscow State University and Ecole Centrale de Lyon (2013: Lyon, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, Volpert, Vitaly, Workshop of Moscow State University and Ecole Centrale de Lyon (2013: Lyon, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2013

43. Hybrid model of blood coagulation

Author

Second International Workshop on the Multiscale Modelling and Methods (2012: Saint-Etienne, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, Volpert, Vitaly, Second International Workshop on the Multiscale Modelling and Methods (2012: Saint-Etienne, France), Tosenberger, Alen, Ataullakhanov, F, Bessonov, Nikolai, Panteleev, M, Tokarev, A, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/nonPublished

Published
2012

45. Particle Dynamics Methods of Blood Flow Simulations

Author

Tosenberger, Alen, Salnikov, Vsevolod, Bessonov, Nikolai, Babushkina, Evgenia, Volpert, Vitaly, Tosenberger, Alen, Salnikov, Vsevolod, Bessonov, Nikolai, Babushkina, Evgenia, and Volpert, Vitaly

Abstract

info:eu-repo/semantics/published

Published
2011

49. Target morphology and cell memory: a model of regenerative pattern formation.

Author

Bessonov N, Levin M, Morozova N, Reinberg N, Tosenberger A, and Volpert V

Abstract

Despite the growing body of work on molecular components required for regenerative repair, we still lack a deep understanding of the ability of some animal species to regenerate their appropriate complex anatomical structure following damage. A key question is how regenerating systems know when to stop growth and remodeling - what mechanisms implement recognition of correct morphology that signals a stop condition? In this work, we review two conceptual models of pattern regeneration that implement a kind of pattern memory. In the first one, all cells communicate with each other and keep the value of the total signal received from the other cells. If a part of the pattern is amputated, the signal distribution changes. The difference fromthe original signal distribution stimulates cell proliferation and leads to pattern regeneration, in effect implementing an error minimization process that uses signaling memory to achieve pattern correction. In the second model, we consider a more complex pattern organization with different cell types. Each tissue contains a central (coordinator) cell that controls the tissue and communicates with the other central cells. Each of them keeps memory about the signals received from other central cells. The values of these signals depend on the mutual cell location, and the memory allows regeneration of the structure when it is modified. The purpose of these models is to suggest possible mechanisms of pattern regeneration operating on the basis of cell memory which are compatible with diverse molecular implementation mechanisms within specific organisms.

Published
2015
Full Text
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