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Biological Physics

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24 featured work(s)

preprint2026arXiv

A Brownian dynamics study of liquid-liquid phase separation in multi-scale chromatin networks

In living cells, proteins involved in specialized biochemical functions are often spatially organized within biomolecular condensates. Increasing evidence suggests that some of these condensates, including DNA repair condensates, emerge through liquid-liquid phase separation (LLPS). In the nucleus, however, condensates form within a highly heterogeneous environment composed of chromatin fibers, RNA, and additional protein scaffolds such as PAR chains, all of which may interact with phase-separating proteins. Moreover, condensate formation is frequently associated with specific chromatin conformations; for instance, loop extrusion has been proposed as a mechanism promoting DNA repair condensates. Here, we investigate how the surrounding fibrous environment controls the morphology and spatial organization of phase-separated condensates. Using Brownian dynamics simulations of minimal models combining Lennard-Jones particles with fixed fibrous substrates, we examine the respective roles of local fiber geometry and large-scale network organization, reflecting the multiscale architecture of chromatin. We show that protein-fiber interactions strongly influence droplet positioning relative to the substrate, in a manner analogous to wetting transitions in soft condensed matter systems. Both local geometric constraints and global network organization markedly affect droplet size, morphology, and multiplicity. In addition, large-scale asymmetries in fiber organization can induce robust spatial localization of the dense phase. Our results thus highlight how multiscale structural heterogeneity of the nuclear environment can regulate the emergence and organization of biomolecular condensates.

preprint2026arXiv

A developmental switch from capillary rectification to elastic catapult enables honeydew ejection in the spotted lanternfly

Plant sap-feeding insects must dispose of excess fluid, yet at millimeter scales droplet release is constrained by capillary adhesion and contact-line pinning. How phloem-feeding insects solve this puzzle, particularly as the excretory apparatus changes in size and form from nymph to adult, has remained unclear. Combining micro-CT, high-speed imaging, measurements of honeydew properties, and reduced-order modeling, we show that the spotted lanternfly (Lycorma delicatula) uses distinct release mechanics across ontogeny. Nymphs release honeydew with an anal stylus that acts as a capillary rectifier, imposing a curvature asymmetry that biases the attached droplet toward detachment through a Laplace-pressure difference. Adults use a longer stylus associated with an elastic basal region, maintain stylus-droplet contact through a finite compression phase, and release droplets with greater translational and rotational momentum. In both stages, stylus rotation is ultrafast, with peak angular accelerations of order $10^7$ rad/s$^{-2}$ and release unfolding on millisecond timescales, yet droplet ejection speed remains below stylus tip speed. Weber-Bond scaling based on measured honeydew properties places both stages at $We_d<1$ and $Bo_d<1$ at the outlet, but distinguishes their post-release states: nymphal droplets remain surface-tension dominated, whereas adult droplets enter deformation- and spin-influenced regimes. Development therefore maintains waste clearance across ontogeny under the same outlet-scale capillary constraint by changing how stylus motion is coupled to the droplet at release, linking life-stage biomechanics to honeydew placement in this invasive phloem feeder and suggesting bioinspired strategies for droplet ejection, antifouling, and self-cleaning surfaces.

preprint2022arXiv

Raman spectroscopic analysis of highly-concentrated antibodies under the acid-treated conditions

Antibody drugs are usually formulated as highly-concentrated solutions, which would easily generate oligomer and aggregation, resulting in loss of efficacy. Although low pH increases the colloidal dispersion of antibodies, acid denaturation can be an issue. Therefore, knowing the physical properties of antibodies at low pH under high concentration conditions is an important insight into the quality evaluation of high concentration antibodies. Raman spectroscopy is a powerful tool to obtain conformational information derived from amino acid residues and secondary structures without dilution. In this study, Raman spectroscopy was used to investigate pH-induced conformational changes of antibodies at high concentrations. Raman experiments in pH 3 to 7 were performed for human serum IgG and recombinant rituximab. We detected the evident changes at pH 3 in Tyr and Trp Raman bands, which are the sensitive markers of intermolecular interactions. Thermal transition analysis over the pH range demonstrated that the transition temperature (aggregation temperature, Tagg) was highest at pH 3. Acid-treated and neutralized one showed higher Tagg than that of pH 7, indicating that acid-induced conformational changes were not completely reversible. Colloidal analyses confirmed the findings of the Raman analysis, validating Raman spectroscopy as a method for evaluating antibody conformation associated with colloidal information.

preprint2026arXiv

Kin-ematic Exclusion in Active Matter: Modelling Mutual Inhibition in \textit{Pseudomonas aeruginosa} Sibling Colonies

The striking variety of macroscopic morphologies displayed by bacterial colonies depends on microscopic environmental and behavioural details in a manner that is currently not well understood. A surprising example is sibling inhibition, whereby isogenic bacterial colonies spreading in soft agar hydrogels tend to avoid each other and form sharp demarcation lines when growing nearby. Here we investigate this effect with the common pathogen \textit{Pseudomonas aeruginosa}, by combining quantitative density measurements with a minimal biophysical model. Our results show that the phenomenon does not depend on gel compression, lethal inhibition or quorum sensing-dependent cell communication. Instead, colony separation is driven by localised nutrient depletion through a dynamic feedback between growth and motility. The model, which is calibrated using experimental data, captures key observations including the dependence of inhibition strength on the initial nutrient concentration. This work establishes nutrient availability and non-lethal motility inhibition as central factors underlying sibling inhibition, providing a generalisable framework for microbial spatial dynamics with implications for understanding bacterial interactions in tissues, soils and engineered microbiomes.

preprint2026arXiv

Delay-induced chimera transitions via mode selection in a multiplex FitzHugh Nagumo network

We investigate delay-induced collective dynamics in a two-layer multiplex FitzHugh Nagumo network with nonlocal intra layer coupling and delayed inter layer interactions. While delay effects are often treated as secondary, we show that deterministic inter-layer delay alone can act as a control mechanism for spatial coherence. Through systematic numerical simulations, we observe a clear transition as the delay parameter increases: fragmented incoherence evolves into chimera-like partial coherence, and eventually into a coherent traveling-wave state. This transition is consistently captured by spatial snapshots, space-time plots, and mean phase velocity profiles. To explain this behavior, we analyze the stability of spatial Fourier modes and show that the delay term introduces a mode-dependent exponential factor in the characteristic equation. This term induces non-monotonic changes in modal stability, effectively acting as a mode-selection mechanism: intermediate delays selectively destabilize a subset of modes, producing chimera-like coexistence, while larger delays suppress incoherent modes and restore global coherence. Our results demonstrate that inter-layer delay provides a simple and robust mechanism for controlling pattern formation in multiplex excitable networks, offering new insight into delay driven synchronization phenomena.

preprint2026arXiv

Onsager-variational formulation of diffuse-domain methods for computational modeling of microscale fluid-structure interactions

Direct numerical simulation of microscale fluid--structure interactions in multicomponent and multiphase flows requires methods that can represent moving boundaries together with fields constrained to evolving interfaces. Diffuse-domain methods (DDMs) address this geometric difficulty by replacing sharp surfaces with diffuse volumetric representations on regular computational domains. Here we formulate DDMs using Onsager's variational principle. Instead of extending sharp-interface equations and boundary conditions term by term, we embed sharp-surface free-energy and dissipation functionals into the bulk through a diffuse surface delta density and derive the governing equations from the Rayleighian. The framework distinguishes balance-law fields, internal nonconserved order parameters, and kinematic or constitutive rate variables. It also clarifies a key moving-surface distinction: conserved surface densities are transported by the full material surface velocity, whereas explicitly tangential vector and tensor internal variables require projected objective or co-rotational rates within their admissible tangential state spaces. For scalar transport on rigid and deformable interfaces, and for interfacial hydrodynamics near rigid walls, the formulation recovers established DDM models and their sharp-interface limits. The same variational construction yields coupled diffuse-domain models for multicomponent deformable vesicles with surface viscosity, tangential slip, and finite areal compressibility, and for active shells carrying chemical and tangential vector order. These results provide a unified route to thermodynamically consistent passive DDMs for interfacial and surface dynamics, while allowing active stresses through active work power. The framework is relevant to soft matter, microfluidic interfaces, biological membranes, and morphogenetic surface dynamics.

preprint2026arXiv

A hyperbolic cell cycle law for early embryonic developmental timing

Across metazoans, early embryos exhibit a strikingly conserved slowing down of their cell duplication speed, despite widely varying developmental paces and underlying molecular mechanisms. Here we show that this common behavior arises because early development unfolds along a biochemical rather than a chronological timescale, resulting from the coupling of finite maternal resource consumption to the Michaelis-Menten-like kinetics governing the rates of the biochemical reactions involved in cell duplication. This leads to a hyperbolic growth of the Cell Cycle Length (CCL), approaching a mathematical singularity, which would correspond to developmental arrest. Data from a wide range of organisms -- cnidarians, nematodes, arthropods, molluscs, echinoderms, tunicates, amphibians, and fish -- collapse on a single curve, quantitatively capturing not only a universal CCL dynamical behaviour, but also key hallmarks of early metazoan development, including cell-number temporal evolution, the dependency of CCL on cell size, and, remarkably, gastrulation timing at the predicted singularity. Crucially, experimental modulation of resource availability and consumption rates validate the model and further demonstrate that a source of heterochrony in early development is an altered biochemical timescale of resource depletion. Overall, this work reveals resource consumption rates as a fundamental mechanism driving developmental timing in early embryogenesis across species.

preprint2026arXiv

3D mechano-geometric multicellular model of apical stem cell-driven plant morphogenesis

The orientation of cell division is a major determinant of three-dimensional plant morphogenesis. Whether and how a simple division orientation rule explains the establishment of symmetric body plans is a fundamental question. Testing such hypotheses is facilitated by a modeling framework that combines realistic three-dimensional cell mechanics, irreversible cell-wall growth, and a deformable tissue geometry. We recently introduced such a framework, a 3D mechano-geometric multicellular model of apical stem cell-driven morphogenesis. Here we document how the model is built from physiological and computational perspectives. We describe the triangulated thin-shell representation of cells, the treatment of turgor pressure, cell-wall elasticity and strain-driven wall growth, the cell-division algorithm together with its two pluggable division-rule implementations, and the remeshing operations that keep the triangulation well-conditioned as cells grow, divide, and deform. The aim of this paper is to make the present model accessible and customizable to experimental plant biologists.

preprint2026arXiv

Conditioning as a route to stereotyped behavior in growing populations

Biological systems perform complex multi-step processes in a reproducible way despite underlying stochasticity. The standard explanation is micromanagement by molecular machinery that recognizes and corrects specific errors. Here we study conditioning, a qualitatively different strategy in which attempts failing a coarse criterion are destroyed and do not leave a physical record. The surviving, i.e., conditioned, ensemble is narrower and therefore more ordered. We model conditioning through stochastic resets in a ''socks-before-shoes'' model of a growing population, where $n$ actions must be completed in any order to replicate and any replication attempt not finished by a threshold time is discarded. We find that resets impose hierarchical temporal ordering of the $n$ actions without microscopic control over which action happens when. When disorder carries a sufficient time penalty, this ordering is free: the fastest-growing population is automatically the most ordered, with no direct selection for order required. Save points, at which verified progress is preserved across resets, allow conditioning to scale to complex multi-step processes. Conditioning provides a minimal route to reliable behavior, requiring only a clock rather than molecular machinery that recognizes specific errors. For the right class of processes, it pays for itself.

preprint2026arXiv

Predicting and controlling nonlinear neuro-mechanical locomotion dynamics

Neuromechanics aims to understand the link between an animal's neural activity and its physical behaviors. Recent advances in experimental and machine learning techniques enable simultaneous recordings of neural and locomotion dynamics over long time periods and across multiple behavioral transitions in worms, flies, and other organisms. These high-dimensional datasets present the challenge of inferring interpretable low-dimensional dynamical models that quantitatively connect neural activity and behavioral dynamics. However, despite major experimental and theoretical progress, there is currently no end-to-end model for predicting locomotion and other behaviors from neural activity. Here, we present a theoretical and computational framework for inferring multiscale neuromechanical models from state-of-the-art experimental data. Our data-efficient approach combines interpretable spectral mode representations with Helmholtz-Nambu decompositions and Bayesian inference to identify a predictive stochastic model that converts neural activity time series into behavioral locomotion patterns. We first apply this framework to recently published recordings of neural activity and locomotion in the roundworm Caenorhabditis elegans, showing that it accurately describes experimentally observed dynamics. We further demonstrate how the inferred model can be used to predict neural activation patterns for controlling C. elegans locomotion in real time, providing a basis for future optogenetic experiments. Due to its generic formulation, the framework introduced here is broadly applicable to neuromechanical recordings for a wide range of animal species.

preprint2026arXiv

Kinetics of Mycoprotein Production from Alternative Carbon Substrates

High throughput screening was used to study of the biokinetics of F. venenatum A3/5 cultivation on alternative carbon substrates, including monosaccharides, disaccharides and mixtures relevant to food & beverage, dairy and agricultural waste streams. Expired functional drink from the beverage sector was also assessed as the primary carbon source for mycoprotein production. Growth data was analysed using modified single and multiphase Gompertz models for comparison of maximum specific growth rate and progression milestones across diverse growth regimes. Time-series substrate and byproduct data was analysed using comparative metrics, providing an explanatory basis for the different growth phenotypes observed. Substrate type strongly influenced the apparent carbon allocation strategies, with rapidly consumed sugars such as glucose and sucrose supporting high growth rates, low biomass yield and a high degree of fermentative byproduct formation. Fructose and xylose cultivations led to slower overall growth but higher biomass yield and lower byproduct formation. Galactose and lactose showed distinct dynamics that suggested co-existence of transport and metabolic induction limitations. In all dual-substrate systems, sequential utilisation was observed. However, metabolic inheritance and environmental shift effects were highlighted as potential kinetic limitations. These conditions exhibited stunted diauxic growth and low yield from secondary sugars, with glucose-dominated primary growth significantly reshaping secondary substrate efficiencies relative to their study in silo. The expired functional drink supported highly rapid growth and achieved the highest maximum specific growth rate and biomass titre of all conditions examined, alongside reduced fermentative overflow and enhanced ethanol reassimilation relative to a compositionally matched synthetic control.

preprint2026arXiv

Excitation of Low-Frequency Modes and the Effects of Protein Dynamics on Spectral Densities of Bacteriochlorophyll Molecules

In the theory of open quantum systems, spectral densities are key quantities for modeling the dynamics and spectroscopic properties of the system under investigation. In the case of light-harvesting complexes, they encode the frequency-dependent coupling of electronic excitations in pigment molecules to their environment, reflecting contributions from both intrinsic vibrational modes and the protein surrounding. In particular, the low-frequency components of the spectral densities are crucial for exciton transfer between pigment molecules. Apparently, slow internal modes of bacteriocholophyll molecules in the gas phase are less well represented by common force fields based on classical molecular dynamics (MD) simulations. Here, we demonstrate that Born-Oppenheimer molecular dynamics (BOMD) based on the numerically efficient density functional-based tight-binding approach can accurately recover these low-frequency features, whereas normal mode analysis captures them only partially. In contrasting approaches for determining spectral densities, the low-frequency region of the spectral densities obtained is only associated with protein fluctuations; the usage of BOMD, however, also captures the low-frequency contributions arising from slow intramolecular vibrations of the pigment molecules themselves. Notably, this behavior is consistently observed for both the flexible B800 and the more rigid B850 rings in light-harvesting 2 (LH2) complexes of purple bacteria, as well as in the Fenna-Matthews-Olson (FMO) complex of green sulfur bacteria. Interestingly, we also find that the spectral densities of the pigments in the B850 ring of LH2 are not influenced by the environment, i.e., the gaps between ground and first excited state are not changed significantly by the fluctuations of the protein environment.

preprint2022arXiv

Martini 3 Coarse-Grained Force Field for Carbohydrates

The Martini 3 force field is a full re-parametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance it allows for more accurate description of condensed phase systems. In the present work we develop a consistent strategy to parametrize carbohydrate molecules accurately within the framework of Martini 3. In particular, we develop a canonical mapping scheme that decomposes arbitrarily large carbohydrates into a limited number of fragments. Bead types for these fragments have been assigned by matching physicochemical properties of mono- and disaccharides. In addition, guidelines for assigning bonds, angles, and dihedrals are developed. These guidelines enable a more accurate description of carbohydrate conformations than in the Martini 2 force field. We show that models obtained with this approach are able to accurately reproduce osmotic pressures of carbohydrate water solutions. Furthermore, we provide evidence that the model differentiates correctly the solubility of the poly-glucoses dextran (water soluble) and cellulose (water insoluble, but soluble in ionic-liquids). Finally, we demonstrate that the new building blocks can be applied to glycolipids, being able to reproduce membrane properties and to induce binding of peripheral membrane proteins. These test cases demonstrate the validity and transferability of our approach.

preprint2026arXiv

Cell divisions suppress dynamical correlations in solid tissues

Developing tissues often maintain mechanical coherence while continuously remodeling through cellular processes such as cell divisions and rearrangements. In this way, they are an example of amorphous solids. In passive amorphous solids, local rearrangements can trigger one another through long-ranged elastic interactions, leading to system-spanning avalanches near yielding. Whether similar collective dynamics should be expected in living tissues is unclear, because cell divisions generate stress and remodeling events independently of local mechanical stability. Here, we address this question using a two-dimensional elastoplastic model in which cell divisions are treated as active plastic events. We find that while cell divisions fluidize the tissue below the passive yield stress, but preserve the marginal stability in the quasistatic limit. However, they also strongly suppress the system-spanning avalanches of cell rearrangements, in constrast with the expected behavior in passive amorphous solids. Finally, we show that the avalanche supression originates from the energy balance in the system. Namely, the energy injected by cell divisions allows for shear flow below the yield stress, but also provides a finite budget for rearrangements. These results suggest that proliferating tissues display the structural hallmarks of marginal amorphous solids while exhibiting much shorter-ranged correlations in dynamics, compared to passive amorphous solids.

preprint2026arXiv

Towards digital phantoms: emulating scattering with a spatial light modulator

The distortion of light's degrees of freedom when passing through complex random media is of great interest across a diversity of fields, e.g., scattering in biological studies. Emulating such media in a controlled laboratory setting conventionally relies on real-world physical samples (e.g., white paint), inhomogeneous mixtures with embedded scatterers, or biological tissue-mimicking phantoms. Such methods, while effective in certain contexts, are not without complexity and limitations: the exact medium properties are challenging to control and often require laborious preparation, external characterisation techniques, are not easily reproducible between studies and cannot be matched precisely by numerical simulations. Here, we propose a simple all-digital implementation of random scattering which can be readily implemented on any setup capable of producing digital holograms. Our approach employs binary random phase masks encoded onto a spatial light modulator which perturbs the input beam's phase and amplitude. We highlight two methods to precisely tune distortion strengths which show excellent agreement between simulated and measured results. We demonstrate distortion strengths comparable to real-world scattering samples and illustrate two example applications to emulate scattering of scalar and vectorial structured light. Finally we showcase the versatility of this toolkit for emulating various amplitude and phase profiles and suggest several easy to implement alternative modalities accessible with this method. This digital phantom circumvents many of the practical challenges of physical samples, making it ideally suited for applications at the intersection of structured light, biological imaging and optical communications.

preprint2026arXiv

A framework for modeling and inferring tracer diffusion in crowded environments

Tracer diffusion in crowded environments is central to many biological and soft matter systems, but quantitative frameworks for linking tracer motion to environmental structure remain limited. Here, we study the transport of rigid tracers in suspensions of soft particles and within living cells. Experiments reveal a transition from diffusive to confined motion as the matrix area fraction increases. We develop a minimal simulation that incorporates steric exclusion and hydrodynamic hindrance to reproduce the observed mean-squared displacements (MSDs). Using simulation outputs, we train a parallel partial Gaussian process (PPGP) model that rapidly predicts MSDs from matrix geometric variables, including area fraction, particle size, and polydispersity. The PPGP model accelerates predictions by several orders of magnitude relative to simulation and experiments. Analysis reveals that tracer transport is primarily governed by accessible pore sizes and that distinct global structures can produce indistinguishable MSDs. We find that the minimal model can also capture the MSDs of internalized tracer particles in cells. The framework enables rapid inference of structural properties in crowded environments, including transport in the intracellular environment.

preprint2026arXiv

Tracer-free Contactless Acoustic Microrheometry Quantifies Viscoelastic Spectrum of Phase-separated Condensates

The rheology of phase-separated condensates plays a central role in applications spanning advanced materials design and cellular processes, yet quantitative characterization of their viscoelasticity remains challenging due to the limitations of existing microrheological methods that require tracer particles or mechanical contact. Here, we establish tracer-free and contactless acoustic microrheometry as a versatile platform for quantifying the frequency-dependent complex shear modulus of single microscale condensates over 0.01-10 Hz. Using spatiotemporally controlled acoustic radiation force generated within a micro-acoustic resonator, this method deforms condensates for creep-recovery and oscillatory viscoelastic measurements. Quantitative validation using dextran condensates in a polyethylene-glycol continuous phase successfully captures their size- and frequency-dependent mechanical responses, while application to nucleic-acid condensates reveals salt-dependent internal viscoelastic changes at single-condensate resolution. By enabling quantitative dissection of condensate mechanics without invasive probes, acoustic microrheometry provides a broadly applicable framework for investigating phase-separated condensates across materials science, soft matter physics, biology, and beyond.

preprint2026arXiv

Chiral-Induced Spin Selectivity Regulates Triplet formation in Heliobacterial Photosynthesis

Triplet formation and its regulation have always been of central interest in understanding the photophysical behavior of living systems. In organic systems, excessive triplet formation poses significant challenges, as it can promote photochemical damage and reduce the efficiency of charge separation processes, making its regulation critically important.Here, we present a theoretical investigation of the intrinsic quantum spin dynamics governing triplet formation in the heliobacterial reaction center, a system that operates without any internal magnetic field. Using an open quantum systems approach based on the Lindblad formalism, we simulate the spin-correlated radical pair dynamics occurring during charge separation in the heliobacterial reaction center. The study systematically examines how triplet formation is regulated by variations in two key parameters, hyperfine coupling strengths and recombination rates, and how this regulation is further influenced by the inclusion of chirality-induced spin selectivity (CISS) in conjunction with the radical pair mechanism (RPM). Our results demonstrate that the CISS effect significantly suppresses triplet formation across the parameter space relevant to the heliobacterial molecular environment, revealing an intrinsic quantum protective mechanism operating through spin control in heliobacterial photosynthesis.

preprint2026arXiv

Travelling waves of invasion in microbial communities with phenotypic switching

Complex microbial habitats see the spatial competition of different clonal bacterial populations that switch between different phenotypes. Here, we determine the effect of this subpopulation structure on the invasion of one species by another in a minimal model of two competing species: one species switches, both stochastically and in response to its competitor, to a persister phenotype resilient to competition. Surprisingly, our combined analytical and numerical results show that this phenotypic switching has no effect on the speed of the travelling wave by which the competitors invade the first population. Conversely, we discover that phenotypic switching can speed up the wave by which this population invades their competitors. Our results thus suggest, counterintuitively, that bacterial persistence can be an offensive, rather than defensive ecological strategy.

preprint2026arXiv

Molecular Mechanisms of Urea Interactions with Bovine Serum Albumin in an Acid-Expanded Conformation (pH 3.7)

Understanding the molecular mechanism by which denaturants modulate protein structure remains a central challenge in protein biophysics. In this work, molecular dynamics simulations were employed to investigate the effects of urea on the structural stability of bovine serum albumin, its F isoform at pH 3.7, over a broad range of urea concentrations (0 M to a fully urea/solvated system). The results reveal that urea induces a concentration/dependent dehydration/rehydration mechanism within the protein hydration shell. At low urea concentrations, a marked reduction in protein/water hydrogen bonds is observed, accompanied by a corresponding increase in protein/urea interactions, consistent with a competitive solvation process. At higher concentrations, urea/urea self-association becomes significant, limiting direct protein/urea interactions and promoting partial rehydration of the protein surface. Despite these solvent rearrangements, the secondary structure of BSA remains largely preserved, whereas local and tertiary structural features, particularly in Domain III, exhibit increased solvent exposure and conformational flexibility. These findings support a dynamic compensation mechanism in which urea partially replaces water in the solvation shell without fully disrupting the hydrogen-bonding network. Overall, this study provides molecular-level insight into the interplay between preferential interactions, solvation dynamics, and protein stability under denaturing conditions.

preprint2026arXiv

Coexistence of trapped and flow-transported nuclei enables fast pigeon post communication across multinucleated cell

Multi-nucleated cells exist in all domains of life, ranging from animals, plants and fungi to single-celled organisms such as the slime mold Physarum polycephalum. The large cell size, in the case of Physarum reaching centimeters and more, challenges the coordination of nuclei activity as signals need to cross large distances. In search for a mechanism for fast long-ranged communication among nuclei, we quantify nuclei dynamics and cytoplasmic flows in Physarum's tubular network. We observe nuclei in two interchangeable, dynamic states: mobile, flowing within the cytoplasmic shuttle flow, or trapped in the tube's porous cell cortex. As we find nuclei to accumulate at the tube's inner fluid-porous interface we theoretically explore and confirm, with physiological parameters, that slowing down of mobile nuclei during flow is sufficient for diffusible signal exchange between mobile and trapped nuclei. We analytically derive that communication akin to pigeon-post with mobile nuclei serving as pigeons shuttling between trapped nuclei acting as waypoints, gives rise to signaling velocities that account for the rapid intracellular reorganization observed in Physarum. Since signal transfer by flow-transported nuclei outcompetes the mere diffusion of signals encoded in cytosolic proteins, pigeon-post communication surpasses alternative signaling mechanisms, even diffusive relay signaling up to twenty-fold in velocity. The key ingredients of pigeon-post communication, namely alternating flows and waypoints, exist in other multi-nucleated cells and may also be generalized beyond intracellular signaling.

preprint2026arXiv

Nonequilibrium Theory for Molecular Machine Design

Modeling the dynamical flows on networks of biomolecular machines often entails computing node populations and edge fluxes with Master Equations and correlating machine performance with entropy production. But this alone is not sufficient for design, optimization and evolution because it doesn't treat cost-benefit tradeoffs, or small-system misflows (backsteps, futile cycles, ineffective actions), or differential properties for flow design. Here we develop CFT Design, based on the recently developed Caliber Force Theory (CFT). We apply it to: designing faster molecular motors through ``traffic control''; optimizing speed, energy, and accuracy in kinetic proofreaders; and designing better enzyme inhibitors. CFT Design provides a general framework for optimizing nonequilibrium flow networks.

preprint2026arXiv

A putative, computationally stable structure of homotrimeric BP180/collagen XVII

Background: BP180, also known as collagen XVII and BPAG2 (bullous pemphigoid antigen 2), is a 180-kDa transmembrane protein within the hemidesmosomal plaque complex, and which is known to be a major antigen in bullous pemphigoid, gestational pemphigoid, cicatricial (mucous membrane) pemphigoid, and linear IgA bullous disease. Objective: At present, the 3D structure of BP180 is not known. The goal is to predict a reasonable structure for BP180 through machine learning and molecular dynamics. Methods: In this work, we use the recent Boltz-2 model to predict a putative structure for the intracellular, transmembrane, and proximal extracellular domains, including the NC16A antigenic region and a portion of its first extracellular collagenous domain, Col-15. We computationally embed BP180 in a simple phospholipid bilayer, demonstrate that the putative structure is stable using molecular dynamics, and analyze its allosteric properties. Results: The structures presented satisfy symmetry and secondary structure properties which are expected from homology modelling. Over three 500 ns trajectories, there is minor instability of the predicted globular head domain, but the homotrimer otherwise stays mostly folded. The putative NC16A domain is stiff, whereas the truncated Col-15 domain is highly flexible. There does not appear to be a nearby stable conformation distinct from the initial state. Conclusion: The structure presented is a useful starting point for targeting BP180 pharmacologically, for further experimental characterization of BP180, and for generating hypotheses regarding the relevant epitopes contributing to bullous disease. Diffusion models such as Boltz-2 and AlphaFold3 are useful, but their results must be evaluated carefully.

preprint2026arXiv

Analysis of DNA thermal stability across a broad range of thionine concentrations

Interest in studying the interaction of small molecules with DNA is caused by the need to develop new, highly effective, and low-toxic drugs for cancer treatment. The strong and highly specific binding of thionine with DNA makes it a promising candidate for use in medicine and pharmacology. In this study, DNA-thionine complexes in aqueous solutions were investigated using UV-Vis absorption spectroscopy. The thermal stability of native DNA was studied in a broad range of thionine concentrations. The mechanisms of thionine binding to DNA, depending on the concentration of thionine, have been established. At low thionine concentrations $([c_{th}] \le 1.5 \text{ mg/L})$, thionine molecules intercalate between the base pairs of the DNA double helix. At a thionine concentration of 1.5-10 mg/L, the groove binding and external electrostatic interaction of positively charged thionine with negatively charged biopolymer phosphate groups of the DNA backbones is preferable. In all cases, the interaction of thionine with DNA leads to an increase in the thermal stability of the polynucleotide. These findings provide valuable insight into the concentration-dependent molecular mechanisms of DNA-small molecule interactions, supporting the rational design of anticancer and antimicrobial agents, as well as exploiting molecular probes for nucleic acid detection, imaging, and other biomedical applications.

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