We illustrate the appearance of oscillating solutions in delay differential equations modeling hematopoietic stem cell dynamics. We focus on autonomous oscillations, arising as consequences of a destabilization of the system, for instance through a Hopf bifurcation. Models of hematopoietic stem cell dynamics are considered for their abilities to describe periodic hematological diseases, such as chronic myelogenous leukemia and cyclical neutropenia. After a review of delay models exhibiting oscillations, we focus on three examples, describing different delays: a discrete delay, a continuous distributed delay, and a state-dependent delay. In each case, we show how the system can have oscillating solutions, and we characterize these solutions in terms of periods and amplitudes.

Recently, Wang and Xiao studied a four-dimensional competitive Lotka-Volterra system within a deterministic environment in [11]. With the help of numerical example they showed the existence of a chaotic attractor through the period doubling route. In this paper, we are interested to study the dynamics of the same model in presence of environmental driving forces. To incorporate the environmental driving force into the deterministic system, we perturb the growth rates of each species by white noise terms. Then we prove that the unique positive global solution exists for the noise added system and the general p-th order moment of it is bounded for p ≥ 1, which ensures that the solution is stochastically bounded. It is also shown that the solution of the stochastic system is stochastically permanent under some simple conditions. Finally , we demonstrate the noise induced oscillation for the concerned model with the help of numerical example..

The dynamic model of plant growth GreenLab describes plant architecture and functional growth at the level of individual organs. Structural development is controlled by formal grammars and empirical equations compute the amount of biomass produced by the plant, and its partitioning among the growing organs, such as leaves, stems and fruits. The number of organs initiated at each time step depends on the trophic state of the plant, which is evaluated by the ratio of biomass available in plant to the demand of all the organs. The control of the plant organogenesis by this variable induces oscillations in the simulated plant behaviour. The mathematical framework of the GreenLab model allows to compute the conditions for the generation of oscillations and the value of the period according to the set of parameters. Two case-studies are presented, corresponding to emergence of oscillations associated to fructification and branching.

Similar alternating patterns are commonly reported by botanists. In this article, two examples were selected: alternate patterns of fruits in cucumber plants and alternate appearances of branches in Cecropia trees. The model was calibrated from experimental data collected on these plants. It shows that a simple feedback hypothesis of trophic control on plant structure allows the emergence of cyclic patterns corresponding to the observed ones.

In this work we discuss and analyze spiking patterns in a generic mathematical model of two coupled non-identical nonlinear oscillators supplied with a spike-timing dependent plasticity (STDP) mechanism. Spiking patterns in the system are shown to converge to a phase-locked state in a broad range of parameters. Precision of the phase locking, i.e. the amplitude of relative phase deviations from a given reference, depends on the natural frequencies of oscillators and, additionally, on parameters of the STDP law. These deviations can be optimized by appropriate tuning of gains (i.e. sensitivity to spike-timing mismatches) of the STDP mechanisms. The deviations, however, can not be made arbitrarily small neither by mere tuning of STDP gains nor by adjusting synaptic weights. Thus if accurate phase-locking in the system is required then an additional tuning mechanism is generally needed. We found that adding a very simple adaptation dynamics in the form of slow fluctuations of the base line in the STDP mechanism enables accurate phase tuning in the system with arbitrary high precision. The scheme applies to systems in which individual oscillators operate in the oscillatory mode. If the dynamics of oscillators becomes bistable then relative phase may fail to converge to a given value giving rise to the emergence of complex spiking sequences.

Unveiling the mechanisms through which the somitogenesis regulatory network exerts spatiotemporal control of the somitic patterning has required a combination of experimental and mathematical modeling strategies. Significant progress has been made for the zebrafish clockwork. However, due to its complexity, the clockwork of the amniote segmentation regulatory network has not been fully elucidated. Here, we address the question of how oscillations are arrested in the amniote segmentation clock. We do this by constructing a minimal model of the regulatory network, which privileges architectural information over molecular details. With a suitable choice of parameters, our model is able to reproduce the oscillatory behavior of the Wnt, Notch and FGF signaling pathways in presomitic mesoderm (PSM) cells. By introducing positional information via a single Wnt3a gradient, we show that oscillations are arrested following an infinite-period bifurcation. Notably: the oscillations increase their amplitude as cells approach the anterior PSM and remain in an upregulated state when arrested; the transition from the oscillatory regime to the upregulated state exhibits hysteresis; and opposing Fgf8 and RA gradients along the PSM naturally arise in our simulations. We hypothesize that the interaction between a limit cycle (originated by the Notch delayed-negative feedback loop) and a bistable switch (originated by the Wnt-Notch positive cross-regulation) is responsible for the observed segmentation patterning. Our results agree with previously unexplained experimental observations and suggest a simple plausible mechanism for spatiotemporal control of somitogenesis in amniotes.

Biological rhythms occur at different levels in the organism. In single cells, the cell division cycle shows rhythmicity in the way its molecular regulators, the cyclin dependant kinases (CDKs), modulate their activity periodically to ensure a healthy progression. In tissues, cell proliferation is driven by the circadian clock, which modulates the progression through the cell cycle along the day. The circadian clock shows endogenous rhythmicity through a robust network of transcription-translation feedback loops that create sustained oscillations. Rhythmicity is preserved in cell populations by the coordination of the clocks among cells, through rhythmic synchronization signals. Here we discuss mechanisms for generating rhythmic activities in cell populations by reviewing some of the mathematical models that deal with them. We discuss the implication of biological rhythms for tissue growth and the possible application to chronomodulated cancer treatments.

Progression along the successive phases of the mammalian cell cycle is driven by a network of cyclin-dependent kinases (Cdks). This network is regulated by a variety of negative and positive feedback loops. We previously proposed a detailed, 39-variable model for the Cdk network and showed that it is capable of temporal self-organization in the form of sustained oscillations, which correspond to the repetitive, transient, sequential activation of the cyclin- Cdk complexes that govern the successive phases of the cell cycle [Gérard and Goldbeter (2009) Proc Natl Acad Sci 106, 21643-8]. Here we compare the dynamical behavior of three models of different complexity for the Cdk network driving the mammalian cell cycle. The first is the detailed model that counts 39 variables and is based on Michaelis-Menten kinetics for the enzymatic steps. From this detailed model, we build a version based only on mass-action kinetics, which counts 80 variables. In this version we do not need to assume that enzymes are present in much smaller amounts that their substrates, which is not necessarily the case in the cell cycle. We show that these two versions of the model for the Cdk network yield similar results. In particular they predict sustained oscillations of the limit cycle type. We show that the model for the Cdk network can be reduced to a version containing only 5 variables, which is more amenable to stochastic simulations. This skeleton version retains the dynamic properties of the more complex versions of the model for the Cdk network in regard to Cdk oscillations. The regulatory wiring of the Cdk network therefore governs its dynamic behavior, regardless of the degree of molecular detail. We discuss the relative advantages of each version of the model, all of which support the view that the mammalian cell cycle behaves as a limit cycle oscillator.

Mitochondria are one of the most important organelles determining Ca2+ regulatory pathway in the cell. Recent experiments suggested the existence of cytosolic microdomains with locally elevated calcium concentration (CMDs) in the nearest vicinity of the outer mitochondrial membrane (OMM). These intermediate physical connections between endoplasmic reticulum (ER) and mitochodria are called MAM (mitochondria-associated ER membrane) complexes.

The aim of this paper is to take into account the direct calcium flow from ER to mitochondria implied by the existence of MAMs and perform detailed numerical analysis of the influence of this flow on the type and shape of calcium oscillations. Depending on the permeability of MAMs interface and ER channels, different patterns of oscillations appear (simple, bursting and chaotic). For some parameters the oscillatory pattern disappear and the system tends to a steady state with extremely high calcium level in mitochondria, which can be interpreted as a crucial point at the beginning of an apoptotic pathway.