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At least 127 records · Page 7Linked to original sources
arXiv2012

Phase-Oscillator Computations as Neural Models of Stimulus-Response Conditioning and Response Selection

The activity of collections of synchronizing neurons can be represented by weakly coupled nonlinear phase oscillators satisfying Kuramoto's equations. In this article, we build such neural-oscillator models, partly based on neurophysiological evidence, to represent approximately the learning behavior predicted and confirmed in three experiments by well-known stochastic learning models of behavioral stimulus-response theory. We use three Kuramoto oscillators to model a continuum of responses, and we provide detailed numerical simulations and analysis of the three-oscillator Kuramoto problem, including an analysis of the stability points for different coupling conditions. We show that the oscillator simulation data are well-matched to the behavioral data of the three experiments.

q-bio.NC↗
arXiv2011

A fibered interference scanning optical microscope for living cell imaging

We report on the 3-dimensional imaging of biological cells including living neurons by a recently developed fibered interferometric Scanning Optical Microscope. The topography and surface structure of mouse fibroblasts and hippocampal neurons are clearly revealed. This straightforward technique allows fast, high resolution observation of samples in liquids without lengthy alignment procedures or costly components.

physics.optics↗
arXiv2010

Coarse-Grained Analysis of Microscopic Neuronal Simulators on Networks: Bifurcation and Rare-events computations

We show how the Equation-Free approach for mutliscale computations can be exploited to extract, in a computational strict and systematic way the emergent dynamical attributes, from detailed large-scale microscopic stochastic models, of neurons that interact on complex networks. In particular we show how the Equation-Free approach can be exploited to perform system-level tasks such as bifurcation, stability analysis and estimation of mean appearance times of rare events, bypassing the need for obtaining analytical approximations, providing an "on-demand" model reduction. Using the detailed simulator as a black-box timestepper, we compute the coarse-grained equilibrium bifurcation diagrams, examine the stability of the solution branches and perform a rare-events analysis with respect to certain characteristics of the underlying network topology such as the connectivity degree

cs.SI↗
arXiv2011

The random walk of a low-Reynolds-number swimmer

Swimming at a micrometer scale demands particular strategies. Indeed when inertia is negligible as compared to viscous forces (i.e. Reynolds number $Re$ is lower than unity), hydrodynamics equations are reversible in time. To achieve propulsion at low Reynolds number, swimmers must then deform in a way that is not invariant under time reversal. Here, we investigate dispersal properties of self propelled organisms by means of microscopy and cell tracking. Our system of interest is the micro-alga \textit{Chlamydomonas Reinhardtii}, a motile single celled green alga about 10 micrometers in diameter that swims with to two front flagella. In the case of dilute suspensions, we show that tracked trajectories are well modeled by a correlated random walk. This process is based on short time correlations in the direction of movement called persistence. At longer times, correlations are lost and a standard random walk characterizes the trajectories. Moreover, high speed imaging enables us to show how the back-and-forth motion of flagella at very short times affects the statistical description of the dynamics. Finally we show how drag forces modify the characteristics of this particular random walk.

cond-mat.soft↗
arXiv2010

Analysis of attractor distances in Random Boolean Networks

We study the properties of the distance between attractors in Random Boolean Networks, a prominent model of genetic regulatory networks. We define three distance measures, upon which attractor distance matrices are constructed and their main statistic parameters are computed. The experimental analysis shows that ordered networks have a very clustered set of attractors, while chaotic networks' attractors are scattered; critical networks show, instead, a pattern with characteristics of both ordered and chaotic networks.

cs.NE↗
arXiv2010

Noisy-threshold control of cell death

Cellular responses to death-promoting stimuli typically proceed through a differentiated multistage process, involving a lag phase, extensive death, and potential adaptation. Deregulation of this chain of events is at the root of many diseases. Improper adaptation is particularly important because it allows cell sub-populations to survive even in the continuous presence of death conditions, which results, among others, in the eventual failure of many targeted anticancer therapies. Here, I show that these typical responses arise naturally from the interplay of intracellular variability with a threshold-based control mechanism that detects cellular changes in addition to just the cellular state itself. Implementation of this mechanism in a quantitative model for T-cell apoptosis, a prototypical example of programmed cell death, captures with exceptional accuracy experimental observations for different expression levels of the oncogene Bcl-xL and directly links adaptation with noise in an ATP threshold below which cells die. These results indicate that oncogenes like Bcl-xL, besides regulating absolute death values, can have a novel role as active controllers of cell-cell variability and the extent of adaptation.

q-bio.CB↗
arXiv2010

Metachronal waves in a chain of rowers with hydrodynamic interactions

Filaments on the surface of a microorganism such as Paramecium or Ophalina beat highly synchronized and form so-called metachronal waves that travel along the surfaces. In order to study under what principal conditions these waves form, we introduce a chain of beads, called rowers, each periodically driven by an external force on a straight line segment. To implement hydrodynamic interactions between the beads, they are considered point-like. Two beads synchronize in antiphase or in phase depending on the positive or negative curvature of their driving-force potential. Concentrating on in-phase synchronizing rowers, we find that they display only transient synchronization in a bulk fluid. On the other hand, metachronal waves with wavelengths of 7-10 rower distances emerge, when we restrict the range of hydrodynamic interactions either artificially to nearest neighbors or by the presence of a bounding surface as in any relevant biological system.

physics.bio-ph↗
arXiv2011

Emission of Mitochondrial Biophotons and their Effect on Electrical Activity of Membrane via Microtubules

In this paper we argue that, in addition to electrical and chemical signals propagating in the neurons of the brain, signal propagation takes place in the form of biophoton production. This statement is supported by recent experimental confirmation of photon guiding properties of a single neuron. We have investigated the interaction of mitochondrial biophotons with microtubules from a quantum mechanical point of view. Our theoretical analysis indicates that the interaction of biophotons and microtubules causes transitions/fluctuations of microtubules between coherent and incoherent states. A significant relationship between the fluctuation function of microtubules and alpha-EEG diagrams is elaborated on in this paper. We argue that the role of biophotons in the brain merits special attention.

physics.bio-ph↗
arXiv2011

Method for the Monte Carlo based Simulation of Lipid-Monolayers including Lipid Movement

A two-state-model consisting of hexagonally connected lipids being either in the ordered or disordered state is used to set up a Monte Carlo Simulation for lipid monolayers. The connection of the lipids is realized by Newtonian springs emulating the surfaces elasticity and allowing for the calculation of translational movement of the lipids, whereas all necessary simulation parameters follow from experiments. Simulated monolayer isotherms can be directly compared to measured ones concurrently allowing the calculation of the experimentally hardly accessible monolayer heat capacity.

physics.bio-ph↗
arXiv2011

Entanglement Swapping Model of DNA Replication

Molecular biology explains function of molecules by their geometrical and electronical structures that are mainly determined by utilization of quantum effects in chemistry. However, further quantum effects are not thought to play any significant role in the essential processes of life. On the contrary, consideration of quantum circuits/protocols and organic molecules as software and hardware of living systems that are co-optimized during evolution, may be useful to overcome the difficulties raised by biochemical complexity and to understand the physics of life. In this sense, we review quantum information-theoretic approaches to the process of DNA replication and propose a new model in which 1) molecular recognition of a nucleobase is assumed to trigger an intrabase entanglement corresponding to a superposition of different tautomer forms and 2) pairing of complementary nucleobases is described by swapping intrabase entanglements with interbase entanglements. We examine possible biochemical realizations of quantum circuits/protocols to be used to obtain intrabase and interbase entanglements. We deal with the problem of cellular decoherence by using the theory of decoherence-free subspaces and subsystems. Lastly, we discuss feasibility of the computational or experimental verification of the model and future research directions.

quant-ph↗
arXiv2012

DNA unzipping via stopped birth and death processes with unknown transition probabilities

In this paper we provide an alternative approach to the works of the physicists S. Cocco and R. Monasson about a model of DNA molecules. The aim is to predict the sequence of bases by mechanical stimulations. The model described by the physicists is a stopped birth and death process with unknown transition probabilities. We consider two models, a discrete in time and a continuous in time, as general as possible. We show that explicit formula can be obtained for the probability to be wrong for a given estimator, and apply it to evaluate the quality of the prediction. Also we add some generalizations comparing to the initial model allowing us to answer some questions asked by the physicists.

stat.AP↗
arXiv2011

Computational modeling of differences in the quorum sensing induced luminescence phenotypes of \textit{Vibrio harveyi} and \textit{Vibrio cholerae}

\textit{Vibrio harveyi} and \textit{Vibrio cholerae} have quorum sensing pathways with similar design and highly homologous components including multiple small RNAs (sRNAs). However, the associated luminescence phenotypes of strains with sRNA deletions differ dramatically: in \textit{V. harveyi}, the sRNAs act additively; however, in \textit{V. cholerae}, the sRNAs act redundantly. Furthermore, there are striking differences in the luminescence phenotypes for different pathway mutants in \textit{V. harveyi} and \textit{V. cholerae}. However these differences have not been connected with the observed differences for the sRNA deletion strains in these bacteria. In this work, we present a model for quorum sensing induced luminescence phenotypes focusing on the interactions of multiple sRNAs with target mRNA. Within our model, we find that one key parameter -- the fold-change in protein concentration necessary for luminescence activation -- can control whether the sRNAs appear to act additively or redundantly. For specific parameter choices, we find that differences in this key parameter can also explain hitherto unconnected luminescence phenotypes differences for various pathway mutants in \textit{V. harveyi} and \textit{V. cholerae}. The model can thus provide a unifying explanation for observed differences in luminescence phenotypes and can also be used to make testable predictions for future experiments.

q-bio.MN↗
arXiv2011

Bidirectional transport in a multispecies TASEP model

We study a minimal lattice model which describes bidirectional transport of "particles" driven along a one dimensional track, as is observed in microtubule based, motor protein driven bidirectional transport of cargo vesicles, lipid bodies and organelles such as mitochondria. This minimal model, a multi-species totally asymmetric exclusion process (TASEP) with directional switching, can provide a framework for understanding the interplay between the switching dynamics of individual particles and the collective movement of particles in 1-dimension. When switching is much faster than translocation, the steady state density and current profiles of the particles are homogeneous in the bulk and are well described by a Mean-Field (MF) theory, as determined by comparison to a Monte Carlo simulation. In this limit, we construct a non-equilibrium phase diagram. Away from this fast switching regime, the MF theory fails, although the average bulk density profile still remains homogeneous. We study the steady state behaviour as a function of the ratio of the translocation and net switching rates, Q, and find a unique first-order phase transition at a finite Q associated with a discontinuous change of the bulk density. When the switching rate is decreased further (keeping translocation rate fixed), the system approaches a jammed phase with a net current that tends to zero as J ~ 1/Q.

cond-mat.stat-mech↗
arXiv2011

Vesicle deformations by clusters of transmembrane proteins

We carry out a coarse-grained molecular dynamics simulation of phospholipid vesicles with transmembrane proteins. We measure the mean and Gaussian curvatures of our protein-embedded vesicles and quantitatively show how protein clusters change the shapes of their host vesicles. The effects of depletion force and vesiculation on protein clustering are also investigated. By increasing the protein concentration, clusters are fragmented to smaller bundles, which are then redistributed to form more symmetric structures corresponding to lower bending energies. Big clusters and highly aspherical vesicles cannot be formed when the fraction of protein to lipid molecules is large.

cond-mat.soft↗
arXiv2012

Disordered proteins and network disorder in network descriptions of protein structure, dynamics and function. Hypotheses and a comprehensive review

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into cumulus-type, i.e., those similar to puffy (white) clouds, and stratus-type, i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an energy transfer mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by multi-trajectories; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach rarely visited but functionally-related states. We also show the role of disorder in spatial games of amino acids; highlight the effects of intrinsically disordered proteins (IDPs) on cellular networks and list some possible studies linking protein disorder and protein structure networks.

q-bio.MN↗
arXiv2013

Lagrangian Coherent Structures (LCS) may describe evolvable frontiers in natural populations

The evolution of organismal populations is not typically thought of in terms of classical mechanics. However, many of the conceptual models used to approximate evolutionary trajectories have implicit parallels to dynamic physical systems. The parallels between currently-used evolutionary models and a type of model related to Lagrangian Coherent Structures (LCS) will be explored. The limits of evolvability in a population can be treated in a way analogous to fronts, waves, and other aggregate formations observed in fluid dynamics. Various measures and architectural features will be introduced. Relevant scenarios include so-called evolvable boundaries and related scenarios involving evolutionary neutrality, such as migrations, demographic bottlenecks, and island biogeography. The LCS-like model introduced here could eventually be applied to a wide range of problems that normally utilize forms of evolutionary modeling.

nlin.AO↗