Search results for "cell behavior"

showing 10 items of 91 documents

Rare events and scaling properties in field-induced anomalous dynamics

2012

We show that, in a broad class of continuous time random walks (CTRW), a small external field can turn diffusion from standard into anomalous. We illustrate our findings in a CTRW with trapping, a prototype of subdiffusion in disordered and glassy materials, and in the L\'evy walk process, which describes superdiffusion within inhomogeneous media. For both models, in the presence of an external field, rare events induce a singular behavior in the originally Gaussian displacements distribution, giving rise to power-law tails. Remarkably, in the subdiffusive CTRW, the combined effect of highly fluctuating waiting times and of a drift yields a non-Gaussian distribution characterized by long sp…

Statistics and ProbabilityField (physics)GaussianFOS: Physical sciencesQuantitative Biology::Cell Behaviorsymbols.namesaketransport processes/heat transfer (theory). diffusionRare eventsstochastic particle dynamics (theory)Statistical physicsDiffusion (business)ScalingPhysicsdiffusiondriven diffusive systems (theory)Statistical and Nonlinear PhysicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksRandom walkDistribution (mathematics)Lévy flighttransport processes/heat transfer (theory)symbolsdiffusion; stochastic particle dynamics (theory); driven diffusive systems (theory); transport processes/heat transfer (theory)Statistics Probability and UncertaintyStatistical and Nonlinear PhysicJournal of Statistical Mechanics: Theory and Experiment
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Immune networks: multitasking capabilities near saturation

2013

Pattern-diluted associative networks were introduced recently as models for the immune system, with nodes representing T-lymphocytes and stored patterns representing signalling protocols between T- and B-lymphocytes. It was shown earlier that in the regime of extreme pattern dilution, a system with $N_T$ T-lymphocytes can manage a number $N_B!=!\order(N_T^\delta)$ of B-lymphocytes simultaneously, with $\delta!<!1$. Here we study this model in the extensive load regime $N_B!=!\alpha N_T$, with also a high degree of pattern dilution, in agreement with immunological findings. We use graph theory and statistical mechanical analysis based on replica methods to show that in the finite-connectivit…

Statistics and ProbabilityImmune Network Statistical Mechanics Hopfield Model Parallel RetrievalQuantitative Biology::Tissues and OrgansPhase (waves)FOS: Physical sciencesGeneral Physics and AstronomyInterference (wave propagation)TopologyQuantitative Biology::Cell BehaviorCell Behavior (q-bio.CB)Physics - Biological PhysicsFinite setMathematical PhysicsConnectivityAssociative propertyPhysicsDegree (graph theory)ReplicaStatistical and Nonlinear PhysicsGraph theoryDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksBiological Physics (physics.bio-ph)FOS: Biological sciencesModeling and SimulationQuantitative Biology - Cell BehaviorJournal of Physics A: Mathematical and Theoretical
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Immune networks: Multi-tasking capabilities at medium load

2013

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low load regime, where the number $P$ of simultaneously retrievable patterns scales with the number $N$ of nodes as $P\sim \log N$. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium load r…

Statistics and ProbabilityModularity (networks)Theoretical computer scienceDegree (graph theory)Associative networkComputer scienceGeneral Physics and AstronomyFOS: Physical sciencesStatistical and Nonlinear PhysicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksModeling and SimulationFOS: Biological sciencesCell Behavior (q-bio.CB)Human multitaskingQuantitative Biology - Cell BehaviorRelevance (information retrieval)Cluster analysisImmune Network Statistical Mechanics Hopfield model Parallel RetrievalMathematical Physics
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An Extended Filament Based Lamellipodium Model Produces Various Moving Cell Shapes in the Presence of Chemotactic Signals

2015

The Filament Based Lamellipodium Model (FBLM) is a two-phase two-dimensional continuum model, describing the dynamcis of two interacting families of locally parallel actin filaments (C.Schmeiser and D.Oelz, How do cells move? Mathematical modeling of cytoskeleton dynamics and cell migration. Cell mechanics: from single scale-based models to multiscale modeling. Chapman and Hall, 2010). It contains accounts of the filaments' bending stiffness, of adhesion to the substrate, and of cross-links connecting the two families. An extension of the model is presented with contributions from nucleation of filaments by branching, from capping, from contraction by actin-myosin interaction, and from a pr…

Statistics and ProbabilityNucleationNanotechnologymacromolecular substancesMyosinsBranching (polymer chemistry)Models BiologicalGeneral Biochemistry Genetics and Molecular BiologyPolymerizationQuantitative Biology::Cell BehaviorProtein filamentQuantitative Biology::Subcellular ProcessesCell Behavior (q-bio.CB)CoulombAnimalsComputer SimulationPseudopodiaCytoskeletonCell ShapeActinPhysicsGeneral Immunology and MicrobiologyApplied MathematicsChemotaxisChemotaxisNumerical Analysis Computer-AssistedGeneral Medicine92C17Actin CytoskeletonClassical mechanicsModeling and SimulationFOS: Biological sciencesQuantitative Biology - Cell BehaviorLamellipodiumGeneral Agricultural and Biological SciencesSignal Transduction
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A stochastic interspecific competition model to predict the behaviour of Listeria monocytogenes in the fermentation process of a traditional Sicilian…

2008

The present paper discusses the use of modified Lotka-Volterra equations in order to stochastically simulate the behaviour of Listeria monocytogenes and Lactic Acid Bacteria (LAB) during the fermentation period (168 h) of a typical Sicilian salami. For this purpose, the differential equation system is set considering T, pH and aw as stochastic variables. Each of them is governed by dynamics that involve a deterministic linear decrease as a function of the time t and an "additive noise" term which instantaneously mimics the fluctuations of T, pH and aw. The choice of a suitable parameter accounting for the interaction of LAB on L. monocytogenes as well as the introduction of appropriate nois…

Stochastic approachWater activityDifferential equationStochastic modellingBiologymedicine.disease_causeBiochemistryNoise (electronics)Industrial and Manufacturing EngineeringQuantitative Biology::Cell BehaviorInterspecific competition modelListeria monocytogenesLactic acid bacteriamedicineQuantitative Biology - Populations and EvolutionListeria monocytogenePredictive microbiologybusiness.industryPopulations and Evolution (q-bio.PE)Environmental noiseGeneral ChemistryFunction (mathematics)Listeria monocytogenesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)BiotechnologyPredictive microbiology; Interspecific competition model; Stochastic approach; Environmental noise; Listeria monocytogenes; Lactic acid bacteriaFOS: Biological sciencesProbability distributionFermentationBiological systembusinessFood ScienceBiotechnologyEuropean Food Research and Technology
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Hydrodynamics with spin in bacterial suspensions

2016

We describe a new kind of self-propelling motion of bacteria based on the cooperative action of rotating flagella on the surface of bacteria. Describing the ensemble of rotating flagella in the framework of the hydrodynamics with spin the reciprocal theorem of Stokesian hydrodynamics is generalized accordingly. The velocity of the self-propulsion is expressed in terms of the characteristics of the vector field of flagella orientation and it is shown that unusually high velocities of \textit{Thiovulum majus} bacteria may be explained by the cooperative action of the rotating flagella. The expressions obtained enable us to estimate the torque created by the rotary motors of the bacterium and …

Surface (mathematics)HelicobacteraceaeFOS: Physical sciencesCondensed Matter - Soft Condensed MatterThiovulum majusFlagellumBacterial Physiological PhenomenaModels Biological01 natural sciencesQuantitative Biology::Cell Behavior010305 fluids & plasmasQuantitative Biology::Subcellular ProcessesSuspensionsOrientation (geometry)0103 physical sciencesTorque010306 general physicsSpin-½PhysicsPhysics::Biological Physicsbiologybiology.organism_classificationAction (physics)Classical mechanicsFlagellaHydrodynamicsSoft Condensed Matter (cond-mat.soft)Vector fieldPhysical Review E
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TBVAC2020: Advancing Tuberculosis Vaccines from Discovery to Clinical Development

2017

International audience; TBVAC2020 is a research project supported by the Horizon 2020 program of the European Commission (EC). It aims at the discovery and development of novel tuberculosis (TB) vaccines from preclinical research projects to early clinical assessment. The project builds on previous collaborations from 1998 onwards funded through the EC framework programs FP5, FP6, and FP7. It has succeeded in attracting new partners from outstanding laboratories from all over the world, now totaling 40 institutions. Next to the development of novel vaccines, TB biomarker development is also considered an important asset to facilitate rational vaccine selection and development. In addition, …

TuberculosiImmunologybacille Calmette–Guérin610 Medicine & healthReview[SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseasesTuberculosis; Bacille Calmette-Guérin; Vaccination; Biomarker; Clinical trial; Portfolio management; Discovery[SDV.BC.IC]Life Sciences [q-bio]/Cellular Biology/Cell Behavior [q-bio.CB]Immunology and AllergyBacille Calmette-Guérinbacille Calmette-Guérinbacille Calmette-Guerin2403 Immunology10179 Institute of Medical MicrobiologyBacille Calmette-Guérin; Biomarker; Clinical trial; Discovery; Portfolio management; Tuberculosis; Vaccination; Immunology and Allergy; Immunologyclinical trialvaccination[SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology[SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human geneticstuberculosis2723 Immunology and Allergy570 Life sciences; biologybiomarkerportfolio managementdiscovery
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Modeling multiple taxis: Tumor invasion with phenotypic heterogeneity, haptotaxis, and unilateral interspecies repellence

2021

We provide a short review of existing models with multiple taxis performed by (at least) one species and consider a new mathematical model for tumor invasion featuring two mutually exclusive cell phenotypes (migrating and proliferating). The migrating cells perform nonlinear diffusion and two types of taxis in response to non-diffusing cues: away from proliferating cells and up the gradient of surrounding tissue. Transitions between the two cell subpopulations are influenced by subcellular (receptor binding) dynamics, thus conferring the setting a multiscale character. We prove global existence of weak solutions to a simplified model version and perform numerical simulations for the full se…

Tumor invasionTaxisComputational biologyBiologyMutually exclusive events01 natural sciencesHaptotaxisMultiple taxis and review of modelsRC0254Mathematics - Analysis of PDEsSDG 3 - Good Health and Well-beingCell Behavior (q-bio.CB)Numerical simulationsFOS: MathematicsDiscrete Mathematics and CombinatoricsNonlinear diffusionQA Mathematics0101 mathematicsGlobal existenceQARC0254 Neoplasms. Tumors. Oncology (including Cancer)Genetic heterogeneityInterspecies repellenceApplied Mathematics010102 general mathematicsI-PWCell subpopulationsPhenotypeAC010101 applied mathematicsFOS: Biological sciencesQuantitative Biology - Cell Behavior35Q92 (Primary) 92C17 92C50 (Secondary)Analysis of PDEs (math.AP)Discrete &amp; Continuous Dynamical Systems - B
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On a stochastic disease model with vaccination

2006

We propose a stochastic disease model where vaccination is included and such that the immunity isn’t permanent. The existence, uniqueness and positivity of the solution and the stability of disease free equilibrium is studied. The numerical simulation is done.

VaccinationMathematical optimizationStochastic differential equationGeneral MathematicsDisease freeUniquenessDiseaseAlgebra over a fieldBasic reproduction numberQuantitative Biology::Cell BehaviorMathematics
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Fluorescent pseudomonad injectisomes and manipulation of plant defenses : biocontrol versus pathogenic rhizosphere agents

2015

International audience

[CHIM.POLY] Chemical Sciences/Polymers[SDV.BIO]Life Sciences [q-bio]/Biotechnology[SDV.BC]Life Sciences [q-bio]/Cellular Biology[SDV.BC.BC]Life Sciences [q-bio]/Cellular Biology/Subcellular Processes [q-bio.SC][SDV.BC.IC] Life Sciences [q-bio]/Cellular Biology/Cell Behavior [q-bio.CB][SDV.BBM.BM] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biology[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN][SDV.BDD] Life Sciences [q-bio]/Development Biology[SDV.BC.IC]Life Sciences [q-bio]/Cellular Biology/Cell Behavior [q-bio.CB][SDV.BC.BC] Life Sciences [q-bio]/Cellular Biology/Subcellular Processes [q-bio.SC][SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biochemistry [q-bio.BM][SDV.BDD]Life Sciences [q-bio]/Development Biology[SDV.BC] Life Sciences [q-bio]/Cellular Biology[SDV.BBM.BC] Life Sciences [q-bio]/Biochemistry Molecular Biology/Biochemistry [q-bio.BM][SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyComputingMilieux_MISCELLANEOUS[SDV.BDD.GAM]Life Sciences [q-bio]/Development Biology/Gametogenesis[SDV.BDD.GAM] Life Sciences [q-bio]/Development Biology/Gametogenesis[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biology[SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular Networks [q-bio.MN][SDV.BIO] Life Sciences [q-bio]/Biotechnology[SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy[SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biomolecules [q-bio.BM][SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding[CHIM.POLY]Chemical Sciences/Polymers[SDV.BBM.MN] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular Networks [q-bio.MN][SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN][SDV.BV.AP] Life Sciences [q-bio]/Vegetal Biology/Plant breeding
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