Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 0704.1763

Towards understanding of birds magnetoreceptor mechanism

Ilia A. Solov'yov·Walter Greiner
View original source ↗Read source document ↗Export metadata ↓

Abstract

In the present letter we suggest a new theoretical model for a quantitative description of the magnetoreception mechanism in birds. The considered mechanism involves two types of iron minerals (magnetite and maghemite) which were found in subcellular compartments within sensory dendrites of the upper beak of several bird species. The analysis of forces acting between the iron particles shows that the orientation of the external geomagnetic field can significantly change the probability of the mechanosensitive ion channels opening and closing. The performed theoretical analysis shows that the suggested magnetoreceptor system might be a sensitive biological magnetometer providing an essential part of the magnetic map for navigation.

Explore related subjects

physics.bio-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ilia A. Solov'yov, Walter Greiner. 2007-04-13. Towards understanding of birds magnetoreceptor mechanism. https://arxiv.org/abs/0704.1763

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

KEEP EXPLORING

Related papers

arXiv2026

Collective-Variable Stein Variational Gradient Descent for Free Energy Surface Exploration

Enhanced-sampling methods enable molecular simulations to access configurational regions that are difficult to explore with conventional dynamics, but their efficiency often deteriorates as the number of collective variables (CVs) increases. Here, we introduce an enhanced-sampling framework that couples Stein variational gradient descent (SVGD) with parallel restrained molecular dynamics simulations to facilitate exploration of higher-dimensional CV spaces. SVGD collectively transports an ensemble of interacting particles toward a target probability distribution by combining mean forces that guide particles toward low-free-energy regions with kernel-mediated repulsive interactions that maintain particle diversity. We validate the approach using an analytically solvable double-well model, followed by aqueous alanine dipeptide and tripeptide in two- and four-dimensional CV spaces, respectively. In each case, the particle ensemble reproduces the corresponding target distribution, and the reconstructed free-energy surfaces agree closely with analytical or umbrella-sampling references. For alanine dipeptide and tripeptide, CV-SVGD requires substantially less aggregate MD sampling than the corresponding umbrella-sampling reference calculations. These results demonstrate the potential of CV-SVGD as a flexible, parallelizable framework for enhanced sampling in multidimensional CV spaces. We additionally provide an open-source Python implementation to facilitate its adoption.

physics.bio-ph↗
arXiv2026

A dynamic mathematical model for sub-lethal damage recovery: Integrating recovery processes into multi-target theory to visualize damage states

Quantifying the biological effects of radiation is essential for radiotherapy and radiation protection. While research has centered on statistical analyses of experimental data, this approach often fails to elucidate underlying mechanisms, limiting the development of generalizable models. Describing time dependent phenomena, such as sub-lethal damage (SLD) recovery during fractionated irradiation, presents a particularly significant challenge for existing static models. To address this, we developed a mechanistic mathematical model that extends the classical multi-target, single-hit model by introducing explicit recovery transitions among damage states, allowing the simultaneous description of radiation-induced damage accumulation and biological recovery. We applied this model to Elkind and Sutton's classical split-dose experimental data to determine its parameters. The model reproduced the major features of split-dose survival curves for treatments with 0-, 2.5-, and 23-hour recovery intervals. We visualized the temporal changes in damage state distributions within the cell populations. These simulations provided a process-level interpretation of the characteristic shoulder-like response appearing after an inter-fraction recovery interval. Furthermore, the estimated recovery half-life was about 120 minutes, which is broadly consistent with reported timescales of DNA double-strand break repair in mammalian cells, supporting the biological interpretability of the model parameters. The proposed framework provides a simple, interpretable description of radiation-induced cell death dynamics, including SLD recovery, and may serve as a basis for the improved mechanistic modeling of radiobiological effects under different irradiation protocols.

physics.bio-ph↗
arXiv2026

Online Preplay and Offline Replay Optimize Action Selection in a Closed-Loop Navigation Model

Hippocampal neurons not only encode the animal's current position, but also generate sequences representing potential future states and past locations. During goal-directed navigation, the represented location sweeps ahead of the animal's location (online forward replay). After such tasks, during rest, neuronal sequences occurring during sharp-wave ripples replay previously explored trajectories (offline forward replay). Following random foraging, however, neuronal sequences resemble Brownian motion, which does not correlate with behavior (diffusive replay). The mechanisms producing such diverse sequences, and their distinct effects on spatial coding and navigation, remain unclear. Here, we address these questions using a closed-loop model of navigation in a two-dimensional open-field environment based on a spiking neuronal network. In our framework, neuronal sequences are generated by a common mechanism driven by background noise and the balance of excitation and inhibition. Different replay modes arise solely from task-dependent synaptic modifications and serve different functions: online forward replay facilitates shortcut discovery, offline forward replay consolidates optimal sequences of actions, and diffusive replay helps in generalizing the action and state map and homogenizing internal connectivity. Together, these results show that a single network architecture can flexibly generate various replay types and clarify how each contributes to optimizing goal-directed navigation behavior.

physics.bio-ph↗