arXiv subjects

Leon Lettermann

Publications and source records attributed to Leon Lettermann.

4 recordsLinked to original sources

arXiv2026

Pathway variability, coat stiffening and mechanical adaptation during clathrin-mediated endocytosis

Clathrin assemblies in cells can persist as flat plaques, abort after partial invagination, or close into clathrin-coated vesicles, but the determinants of these different fates remain unresolved. To investigate the stochastic and complex dynamics of clathrin assemblies, we have developed a kinetic Monte Carlo simulation framework that couples individual clathrin agents to an adaptive continuum membrane. In this hybrid discrete-continuum description, the effective coat bending rigidity and the preferred coat curvature emerge during growth, rather than being prescribed as material parameters. Once connected, curved lattices stiffen from molecular bending modes to coat-level rigidities, because curvature changes require increased stretching or compression, while newly incorporated triskelia hardcode a history-dependent preferred curvature. An analytical theory for non-Euclidean elasticity identifies the relevant internal variables and predicts growth laws that are validated by the simulations. The same microscopic assembly rules yield flat, stalled, and closed coats through two sequential gates in the effective membrane-coat energy landscape. Comparisons with experimentally observed coat geometries and nanodissection-induced curvature changes agree with our theoretical predictions without any fitting parameters. The clathrin coat thus emerges as an adaptive assembly with prestress and memory, whose fate and material parameters reflect the environment in which it has been growing.

q-bio.SC↗

arXiv2025

Three-dimensional chiral active Ornstein-Uhlenbeck model for helical motion of microorganisms

Active movement is essential for the survival of microorganisms like bacteria, algae and unicellular parasites. In three dimensions, both swimming and gliding microorganisms often exhibit helical trajectories. One such case are malaria parasites gliding through 3D hydrogels, for which we find that the internal correlation time for the stochastic process generating propulsion is similar to the time taken for one helical turn. Motivated by this experimental finding, here we theoretically analyze the case of finite internal correlation time for microorganisms with helical trajectories as chiral active particles with an Ornstein-Uhlenbeck process for torque. We present an analytical solution which is in very good agreement with computer simulations. We then show that for this type of internal noise, chirality and rotation increase the persistence of motion and results in helical trajectories that have a larger long-time mean squared displacement than straight trajectories at the same propulsion speed. Finally we provide experimental evidence for this prediction for the case of the malaria parasites.

q-bio.CB↗

arXiv2023

AdoptODE: Fusion of data and expert knowledge for modeling dynamical systems

Building a representative model of a complex system remains a highly challenging problem. While by now there is basic understanding of most physical domains, model design is often hindered by lack of detail, for example concerning model dimensions or its relevant constraints. Here we present a novel model-building approach -- adoptODE -- augmenting basic system descriptions, based on expert knowledge in the form of ordinary differential equations, with continuous adjoint sensitivity analysis related to artificial neural network principles, based on observable data. With this we have created a general tool, that can be applied to any physical system described by ordinary differential equations. AdoptODE allows validating or extending the initial description, for example with different variables and constraints. This way one arrives at a better-optimised, representative low-dimensional model, which can fit existing data and predict novel experimental outcomes. We validate our method on five, quite different problem domains. (1) Kolmogorov model: Lotka Volterra model where we show the application of adoptODE to continuous-time Markov processes and the performance of adoptODE when working with noisy data. (2) Particle model: Interactive N-body, is a demonstration of the scalability of adoptODE and that even interactive system with a high number of elements can be reconstructed with high precision. (3) Excitable media (heart dynamics) by the Bueno\-Orovio\-Cherry\-Fenton model: AdoptODE can reconstruct the parameters of a high-dimensional model and fields for diffusion driven system for chaotic behaviour. (4) Fluid dynamics: Rayleigh-B\'enard Convection where a complete unknown field, the temperature, can be extracted from only velocity data. (5) New experimental data of Zebrafish embryogenesis: This is a case where we extend existing models with new variables.

physics.data-an↗

arXiv2020

Mixed State Dynamics with Non-Local Interactions

The evolution of degenerate matter out of equilibrium is a topic of interest in fields such as condensed matter, nuclear and atomic physics, and increasingly cosmology, including inflaton physics prior to reheating. This follow-up paper extends the recent paper on the super-de Broglie dynamics of pure condensates of non-relativistic identical particles subject to non-local two-body interactions to the dynamics of mixed states. It is found that the two-body correlation function plays an increasingly dynamical role in these systems, driving the development of condensates and distributed phases alike. Examples of distribution and correlation evolution are presented, including instances of collapse, bound and unbound states, and phonons in the bulk. Potential applications are also discussed.

astro-ph.CO↗