Search results for "Quantitative Biology - Cell Behavior"

showing 10 items of 12 documents

Collective behavior of quorum-sensing run-and-tumble particles in confinement

2016

We study a generic model for quorum-sensing bacteria in circular confinement. Every bacterium produces signaling molecules, the local concentration of which triggers a response when a certain threshold is reached. If this response lowers the motility then an aggregation of bacteria occurs, which differs fundamentally from standard motility-induced phase separation due to the long-ranged nature of the concentration of signal molecules. We analyze this phenomenon analytically and by numerical simulations employing two different protocols leading to stationary cluster and ring morphologies, respectively.

0301 basic medicineCollective behaviorGeneral Physics and AstronomyFOS: Physical sciencesNanotechnologyCondensed Matter - Soft Condensed MatterBacterial Physiological Phenomena01 natural sciencesSignalModels BiologicalQuantitative Biology::Cell BehaviorQuantitative Biology::Subcellular Processes03 medical and health sciences0103 physical sciencesCell Behavior (q-bio.CB)Cluster (physics)Physics - Biological Physics010306 general physicsCondensed Matter - Statistical MechanicsPhysicsStatistical Mechanics (cond-mat.stat-mech)ChemotaxisQuorum SensingQuorum sensing030104 developmental biologyChemical physicsBiological Physics (physics.bio-ph)FOS: Biological sciencesQuantitative Biology - Cell BehaviorSoft Condensed Matter (cond-mat.soft)
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Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states

2017

We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on: (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according with local rules that are modulated by a parameter $\kappa$. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate e…

0301 basic medicineNormalization (statistics)Majority ruleTime FactorsFOS: Physical sciencesAbnormal cellPattern Formation and Solitons (nlin.PS)Models BiologicalCell Physiological PhenomenaCombinatorics03 medical and health sciences0302 clinical medicineCell Behavior (q-bio.CB)Physics - Biological PhysicsGame of lifeMathematicsCellular Automata and Lattice Gases (nlin.CG)Artificial networksNonlinear Sciences - Pattern Formation and SolitonsCellular automatonMulticellular organism030104 developmental biologyBiological Physics (physics.bio-ph)030220 oncology & carcinogenesisFOS: Biological sciencesQuantitative Biology - Cell BehaviorBiological systemNonlinear Sciences - Cellular Automata and Lattice GasesCoupled map lattice
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Retrieving infinite numbers of patterns in a spin-glass model of immune networks

2013

The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…

0301 basic medicineSimilarity (geometry)Spin glassComputer sciencestatistical mechanicFOS: Physical sciencesGeneral Physics and AstronomyNetwork topologyTopology01 natural sciencesQuantitative Biology::Cell Behavior03 medical and health sciencesCell Behavior (q-bio.CB)0103 physical sciencesattractor neural-networks; statistical mechanics; brain networks; Physics and Astronomy (all)Physics - Biological Physics010306 general physicsAssociative propertybrain networkArtificial neural networkMechanism (biology)ErgodicityDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksAcquired immune system030104 developmental biologyBiological Physics (physics.bio-ph)FOS: Biological sciencesattractor neural-networkQuantitative Biology - Cell Behavior
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Anergy in self-directed B lymphocytes from a statistical mechanics perspective

2012

The ability of the adaptive immune system to discriminate between self and non-self mainly stems from the ontogenic clonal-deletion of lymphocytes expressing strong binding affinity with self-peptides. However, some self-directed lymphocytes may evade selection and still be harmless due to a mechanism called clonal anergy. As for B lymphocytes, two major explanations for anergy developed over three decades: according to "Varela theory", it stems from a proper orchestration of the whole B-repertoire, in such a way that self-reactive clones, due to intensive interactions and feed-back from other clones, display more inertia to mount a response. On the other hand, according to the `two-signal …

Biological Physics (physics.bio-ph)FOS: Biological sciencesCell Behavior (q-bio.CB)FOS: Physical sciencesQuantitative Biology - Cell BehaviorDisordered Systems and Neural Networks (cond-mat.dis-nn)Physics - Biological PhysicsCondensed Matter - Disordered Systems and Neural Networks
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Transient frailty induced by cell division. Observation, reasons and implications

2021

We know that stress-factors, e.g. X-rays, have an effect on cells that is more lethal in rapid exponential growth than in stationary phase. It is this effect which makes radiotherapy effective in cancer treatment. This stress effect can be explained in two ways: (a) more vulnerability in the growth phase, (b) improved protection capacity and repair mechanisms in the stationary phase. Although the two explanations do not exclude each other, they are very different in the sense that (a) is a general mechanism whereas (b) is strain and stress-factor dependent. In this paper we explore major facets of (a). Firstly, we emphasize that (a) can account for known experimental stress-factor evidence.…

Biological Physics (physics.bio-ph)FOS: Biological sciencesCell Behavior (q-bio.CB)FOS: Physical sciencesQuantitative Biology - Cell BehaviorPhysics - Biological Physics
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Is there an infant mortality in bacteria?

2021

This manuscript proposes a significant step in our long-run investigation of infant mortality across species. Since 2016 (Berrut et al. 2016) a succession of studies (Bois et al. 2019) have traced infant mortality from organisms of high complexity (e.g. mammals) down to unicellular organisms. Infant mortality may be considered as a filtering process through which organisms with potentially lethal congenital defects are eliminated. Such defects may have many causes but here we focus particularly on mishaps resulting from non-optimal conditions in the production of proteins, enzymes and other crucial macromolecules. The statistical signature of infant mortality consists in a falling age-speci…

Biological Physics (physics.bio-ph)FOS: Biological sciencesCell Behavior (q-bio.CB)Quantitative Biology - Cell BehaviorFOS: Physical sciencesPhysics - Biological Physics
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Can persistent Epstein-Barr virus infection induce Chronic Fatigue Syndrome as a Pavlov reflex of the immune response?

2012

Chronic Fatigue Syndrome is a protracted illness condition (lasting even years) appearing with strong flu symptoms and systemic defiances by the immune system. Here, by means of statistical mechanics techniques, we study the most widely accepted picture for its genesis, namely a persistent acute mononucleosis infection, and we show how such infection may drive the immune system toward an out-of-equilibrium metastable state displaying chronic activation of both humoral and cellular responses (a state of full inflammation without a direct "causes-effect" reason). By exploiting a bridge with a neural scenario, we mirror killer lymphocytes $T_K$ and $B$ cells to neurons and helper lymphocytes $…

Cytotoxicity ImmunologicEpstein-Barr Virus InfectionsHerpesvirus 4 HumanMononucleosisT-LymphocytesFOS: Physical sciencesInflammationBiologyVirusimmunologyImmune systemAntigenEpstein-Barr Virus InfectionCell Behavior (q-bio.CB)medicineChronic fatigue syndromeHumansimmunology; statistical mechanicsEpstein–Barr virus infectionEcology Evolution Behavior and SystematicsCondensed Matter - Statistical MechanicsB-LymphocytesFatigue Syndrome ChronicEcologyStatistical Mechanics (cond-mat.stat-mech)B-LymphocyteImmunitymedicine.diseasePhysics - Medical PhysicsFOS: Biological sciencesImmunologyReflexQuantitative Biology - Cell Behaviorstatistical mechanicsMedical Physics (physics.med-ph)medicine.symptomImmunologic MemoryHuman
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Sensitivity to Initial Conditions in an Extended Activator--Inhibitor Model for the Formation of Patterns

2018

Despite simplicity, the synchronous cellular automaton [D.A. Young, Math. Biosci. 72, 51 (1984)] enables reconstructing basic features of patterns of skin. Our extended model allows studying the formatting of patterns and their temporal evolution also on the favourable and hostile environments. As a result, the impact of different types of an environment is accounted for the dynamics of patterns formation. The process is based on two diffusible morphogens, the short-range activator and the long-range inhibitor, produced by differentiated cells (DCs) represented as black pixels. For a neutral environment, the extended model reduces to the original one. However, even the reduced model is stat…

PhysicsFOS: Physical sciencesGeneral Physics and AstronomyComputational Physics (physics.comp-ph)Reduced modelCellular automatonExtended modelAverage sizeInitial distributionFOS: Biological sciencesCell Behavior (q-bio.CB)Quantitative Biology - Cell BehaviorBiological systemPhysics - Computational PhysicsActa Physica Polonica B
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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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