128,811 research outputs found
Modeling the Role of the Cell Cycle in Regulating Proteus mirabilis Swarm-Colony Development
We present models and computational results which indicate that the spatial
and temporal regularity seen in Proteus mirabilis swarm-colony development is
largely an expression of a sharp age of dedifferentiation in the cell cycle
from motile swarmer cells to immotile dividing cells (also called swimmer or
vegetative cells.) This contrasts strongly with reaction-diffusion models of
Proteus behavior that ignore or average out the age structure of the cell
population and instead use only density-dependent mechanisms. We argue the
necessity of retaining the explicit age structure, and suggest experiments that
may help determine the underlying mechanisms empirically. Consequently, we
advocate Proteus as a model organism for a multiscale understanding of how and
to what extent the life cycle of individual cells affects the macroscopic
behavior of a biological system
Diffusion entropy and waiting time statistics of hard x-ray solar flares
We analyze the waiting time distribution of time distances between two
nearest-neighbor flares. This analysis is based on the joint use of two
distinct techniques. The first is the direct evaluation of the distribution
function , or of the probability, , that no time
distance smaller than a given is found. We adopt the paradigm of the
inverse power law behavior, and we focus on the determination of the inverse
power index , without ruling out different asymptotic properties that
might be revealed, at larger scales, with the help of richer statistics. The
second technique, called Diffusion Entropy (DE) method, rests on the evaluation
of the entropy of the diffusion process generated by the time series. The
details of the diffusion process depend on three different walking rules, which
determine the form and the time duration of the transition to the scaling
regime, as well as the scaling parameter . With the first two rules the
information contained in the time series is transmitted, to a great extent, to
the transition, as well as to the scaling regime. The same information is
essentially conveyed, by using the third rules, into the scaling regime, which,
in fact, emerges very quickly after a fast transition process. We show that the
significant information hidden within the time series concerns memory induced
by the solar cycle, as well as the power index . The scaling parameter
becomes a simple function of , when memory is annihilated. Thus,
the three walking rules yield a unique and precise value of if the memory
is wisely taken under control, or cancelled by shuffling the data. All this
makes compelling the conclusion that .Comment: 23 pages, 13 figure
Averaging approach to phase coherence of uncoupled limit-cycle oscillators receiving common random impulses
Populations of uncoupled limit-cycle oscillators receiving common random
impulses show various types of phase-coherent states, which are characterized
by the distribution of phase differences between pairs of oscillators. We
develop a theory to predict the stationary distribution of pairwise phase
difference from the phase response curve, which quantitatively encapsulates the
oscillator dynamics, via averaging of the Frobenius-Perron equation describing
the impulse-driven oscillators. The validity of our theory is confirmed by
direct numerical simulations using the FitzHugh-Nagumo neural oscillator
receiving common Poisson impulses as an example
Reaction-diffusion kinetics on lattice at the microscopic scale
Lattice-based stochastic simulators are commonly used to study biological
reaction-diffusion processes. Some of these schemes that are based on the
reaction-diffusion master equation (RDME), can simulate for extended spatial
and temporal scales but cannot directly account for the microscopic effects in
the cell such as volume exclusion and diffusion-influenced reactions.
Nonetheless, schemes based on the high-resolution microscopic lattice method
(MLM) can directly simulate these effects by representing each finite-sized
molecule explicitly as a random walker on fine lattice voxels. The theory and
consistency of MLM in simulating diffusion-influenced reactions have not been
clarified in detail. Here, we examine MLM in solving diffusion-influenced
reactions in 3D space by employing the Spatiocyte simulation scheme. Applying
the random walk theory, we construct the general theoretical framework
underlying the method and obtain analytical expressions for the total rebinding
probability and the effective reaction rate. By matching Collins-Kimball and
lattice-based rate constants, we obtained the exact expressions to determine
the reaction acceptance probability and voxel size. We found that the size of
voxel should be about 2% larger than the molecule. MLM is validated by
numerical simulations, showing good agreement with the off-lattice
particle-based method, eGFRD. MLM run time is more than an order of magnitude
faster than eGFRD when diffusing macromolecules with typical concentrations in
the cell. MLM also showed good agreements with eGFRD and mean-field models in
case studies of two basic motifs of intracellular signaling, the protein
production-degradation process and the dual phosphorylation cycle. Moreover,
when a reaction compartment is populated with volume-excluding obstacles, MLM
captures the non-classical reaction kinetics caused by anomalous diffusion of
reacting molecules
Cycle expansions for intermittent diffusion
We investigate intermittent diffusion using cycle expansions, and show that a
truncation based on cycle stability achieves reasonable convergence.Comment: 6 pages, revtex, 4 figure
- …