Search arXiv⌕ Search

arXiv · q-bio/0607051

Hysteresis and bi-stability by an interplay of calcium oscillations and action potential firing

Abstract

Many cell types exhibit oscillatory activity, such as repetitive action potential firing due to the Hodgkin-Huxley dynamics of ion channels in the cell membrane or reveal intracellular inositol triphosphate (IP$_3$) mediated calcium oscillations (CaOs) by calcium-induced calcium release channels (IP$_3$-receptor) in the membrane of the endoplasmic reticulum (ER). The dynamics of the excitable membrane and that of the IP$_3$-mediated CaOs have been the subject of many studies. However, the interaction between the excitable cell membrane and IP$_3$-mediated CaOs, which are coupled by cytosolic calcium which affects the dynamics of both, has not been studied. This study for the first time applied stability analysis to investigate the dynamic behavior of a model, which includes both an excitable membrane and an intracellular IP$_3$-mediated calcium oscillator. Taking the IP$_3$ concentration as a control parameter, the model exhibits a novel rich spectrum of stable and unstable states with hysteresis. The four stable states of the model correspond in detail to previously reported growth-state dependent states of the membrane potential of normal rat kidney fibroblasts in cell culture. The hysteresis is most pronounced for experimentally observed parameter values of the model, suggesting a functional importance of hysteresis. This study shows that the four growth-dependent cell states may not reflect the behavior of cells that have differentiated into different cell types with different properties, but simply reflect four different states of a single cell type, that is characterized by a single model.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J. M. A. M. Kusters, J. M. Cortes, W. P. M. van Meerwijk, D. L. Ypey, A. P. R. Theuvenet, C. C. A. M. Gielen. 2006-07-31. Hysteresis and bi-stability by an interplay of calcium oscillations and action potential firing. https://doi.org/10.1103/physrevlett.98.098107

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Autotaxis of a Run-and-Tumble Agent via Reinforcement Learning

We study the run-tumble motion of a single autochemotactic agent that secretes and senses chemical cues using a reinforcement learning (RL) framework. In a chemical environment that changes dynamically via secretion, diffusion, and degradation of attractant chemicals, we study the effectiveness of RL for a successful navigation strategy. We show that RL enhances chemotactic performance. Starting from a random initial position, the probability of finding the agent in the favorable region (near the attractant peak) increases faster with time and reaches a higher value in the long time limit when RL is used, compared to the case when the agent performs usual run-tumble chemotaxis without using RL. We also characterize the chemotactic performance of the agent by varying different parameters like rates of secretion, degradation, and diffusion. Importantly, we observe a non-monotonic dependence of the chemotactic performance on the learning and exploration rates, indicating the existence of an optimal RL strategy for the most efficient navigation. We explain these observations as a result of the interplay between the pre-existing attractant environment and the agent-generated attractant profile.

q-bio.CB↗

Kinetics, Proofreading, and the Lifetime of Multivalent Contacts

Selective recognition is how a cell finds the right partner in a crowd and how a drug carrier finds the right cell, so getting it wrong means a missed target or a toxic one. It must also be reversible: a cell has to hold its target tightly enough to tell it from everything else, then release it to act again, and equilibrium binding, which weighs only how favorable a contact is, cannot do both. What settles recognition is how long a contact lasts. We make lifetime the control variable, passing from a master equation through a Smoluchowski equation to the Kramers lifetime of a multivalent contact. Lifetimes are exponential in free energy, so a tenfold change in receptor number moves a contact from seconds to months, turning a smooth thermodynamic gradient into a switch. Selectivity then depends on the encounter: under flow a nanoparticle is kept only if its contact outlives the vascular dwell time, which sharpens the density threshold beyond equilibrium binding. Receptor-mediated endocytosis is itself a kinetic-proofreading cascade, so uptake inherits the Kramers exponential raised to the number of driven steps, a double amplification that vanishes without metabolism and gives a testable route to phenotype-selective delivery. The same readout, on a single bond, is how a T cell discriminates antigen, with immune memory lowering the activation threshold while leaving the specificity untouched.

q-bio.CB↗

Stationary Action Principles for Neuronal Growth

Neuronal growth is guided by biochemical, mechanical, and geometrical cues while being influenced by stochastic fluctuations in cytoskeletal dynamics, adhesion, and growth cone sensing. Here, we develop two complementary variational descriptions of mechanically guided axonal growth. First, for neurons growing on periodic parallel micropatterns, we use Langevin and Fokker--Planck models to derive a stochastic path action incorporating deterministic substrate guidance and random fluctuations. The probability of a growth trajectory decreases exponentially with this action, and the most probable trajectories correspond to minimum action paths for fixed boundary conditions. Second, for axons growing on substrates with spatially varying stiffness, we show that stiffness dependent traction generates mechanical guidance and axonal turning at stiffness interfaces. In the quasi-static limit, this response leads to a Fermat-like spatial action with an effective axonal refractive index determined by the traction and substrate stiffness relationship. The resulting framework predicts axonal refraction across stiffness boundaries, including an approximate Snell-like relation and a critical angle condition. Although the stochastic and Fermat-like actions have distinct physical meanings and ranges of validity, both describe how substrate mechanics constrain axonal trajectories. These results connect measurable quantities, including drift, diffusion, stiffness, traction, and growth direction, to global properties of axonal paths and provide a framework for designing biomimetic substrates for controlled neuronal growth and regeneration.

q-bio.CB↗