Eur Phys J E Soft Matter
· 2025 Dec · PMID 41398508
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The actomyosin cortex is a highly dynamic cellular structure that regulates cell shape, migration, and division, while also contributing to specialized functions such as microvillar search. Previous studies have document...The actomyosin cortex is a highly dynamic cellular structure that regulates cell shape, migration, and division, while also contributing to specialized functions such as microvillar search. Previous studies have documented fluctuations in microvillar shape and cortical thickness over time. Building on these observations, we investigated whether these morphological changes are accompanied by corresponding fluctuations in cellular stiffness. We used profile microindentation and micropipette aspiration to examine the mechanical properties of human CD4 + T cells. Our results revealed that a substantial proportion of T cells exhibit spontaneous stiffness fluctuations, with approximately one-third displaying clear, periodic peaks with an average period of 30-35 s. Disrupting the actin cytoskeleton with Latrunculin A eliminated these fluctuations, confirming their actin-dependent nature. Low-pressure micropipette aspiration experiments showed periodic movements of cell bodies within the micropipette that correlated with stiffness peaks. These findings demonstrate that the mechanical properties of resting T cells are far from static. Instead, T cells exist in a highly dynamic state characterized by significant stiffness oscillations that may be integral to the microvillar search process. This work raises questions about whether similar mechanical dynamics occur in other cell types and how these periodic stiffness changes might influence T cell immune functions. Our study underscores the importance of temporal resolution when investigating cellular mechanics, as static measurements may miss these fundamental dynamic properties.
Leblanc J, Lombard AH, Saumureau A
… +4 more, Costrel S, Revilloud J, Coullomb A, Dupont A
Eur Phys J E Soft Matter
· 2025 Dec · PMID 41385002
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SIMPLIFIED PROTOCOL FOR QUANTITATIVE FRET IN LIVING CELLS WITH DIRECT QUANTI-FRET CALIBRATION FROM THE IMAGES OF INTEREST: Genetically encoded biosensors based on the fluorescence resonance energy transfer (FRET) between...SIMPLIFIED PROTOCOL FOR QUANTITATIVE FRET IN LIVING CELLS WITH DIRECT QUANTI-FRET CALIBRATION FROM THE IMAGES OF INTEREST: Genetically encoded biosensors based on the fluorescence resonance energy transfer (FRET) between two fluorescent proteins have the power to measure biochemical activity in living cells with the spatio-temporal resolution given by optical microscopy. The generalization of their usage is limited by the difficulties in obtaining quantitative results independent of the instrumental system or the expression level. We recently developed quantitative three-image FRET (QuanTI-FRET), a method for calibrating the system and obtaining absolute values of the FRET probabilities. The method proved to be efficient but required additional constructs for the calibration, thereby adding experimental steps. Here, we propose taking advantage of the constant and known stoichiometry of intramolecular FRET biosensors to directly calibrate the system using the dataset of interest, e.g., biosensor experiments. We demonstrate this idea by comparing the results of both standard calibration and autocalibration obtained on live-cell images of the FAK biosensor. This autocalibration is possible because of the strong robustness of the QuanTI-FRET calibration with respect to the quality of the calibration dataset. With this work, we simplify the experimental protocol to obtain quantitative FRET by autocalibration, and we make it accessible through a publicly available Python software and a napari plug-in.
Ahsan N, Hashem AF, Hanif MF
… +3 more, Hanif MF, Shaker H, Siddiqui MK
Eur Phys J E Soft Matter
· 2025 Dec · PMID 41366127
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This paper delves into the intricate relationship between the magnesium nitrogen ( )network and its connection to topological indices and the heat of formation. By analyzing a variety of topological indices, we utilize...This paper delves into the intricate relationship between the magnesium nitrogen ( )network and its connection to topological indices and the heat of formation. By analyzing a variety of topological indices, we utilize a curve fitting model to predict and clarify the heat of formation--a vital thermodynamic factor that impacts the stability and reactivity of .Through a detailed correlation analysis, we uncover significant trends and relationships linking the heat of formation with topological indices like the Gutman, Randić, and Zagreb indices. Our findings indicate that the curve fitting model not only yields accurate predictions but also enhances our understanding of the molecular interactions within the network. Regression techniques will be employed to obtain a curve fitting model, which correlates such indices with experimentally determined heats of formation. These analyses illustrate the accuracy with which thermodynamic properties have been reproduced using the model; it outlines the relevance that topological descriptors have received in computational chemistry so far. By analyzing these results, several insights were obtained into the energetic behavior of magnesium-nitrogen compounds and are pointed out with respect to which role graph-theoretical approaches so far played for the development of material science and chemical engineering.
Eur Phys J E Soft Matter
· 2025 Dec · PMID 41351662
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Evaporative lithography in cells of arbitrary configuration allows for the creation of diverse particle deposition patterns due to the formation of a specific flow structure in the liquid caused by non-uniform evaporatio...Evaporative lithography in cells of arbitrary configuration allows for the creation of diverse particle deposition patterns due to the formation of a specific flow structure in the liquid caused by non-uniform evaporation. The latter in turn is determined by the shape of the liquid layer surface and the wetting menisci on the cell walls. Thus, predicting the shape of the wetting menisci can serve as a tool for controlling the process of creating desired particle deposition patterns and evaporation dynamics. Here, we propose a simple and sufficiently accurate methodology for determining the shape of the liquid meniscus in cells of arbitrary geometric shape, based on a combination of mathematical modeling and a series of experimental measurement techniques. The surface profiles of the liquid meniscus in cylindrical, square, and triangular cells were determined by measuring the change in the reflection angle of a laser beam from the free liquid surface while scanning from the cell wall to its center. The height of the wetting meniscus on the inner cell wall and the minimum liquid layer thickness at the center of the cell were measured by analyzing optical images and using a contact method, respectively. 3D meniscus profiles were obtained by numerically solving the Helmholtz equation. The boundary conditions and the unknown constant in the equation were determined based on experimental data obtained for several local points or cross sections. The simulated meniscus shapes showed satisfactory agreement with the experimental local measurements, with a maximum relative error of less than 14%.
Letrou M, Chagua Encarnacion K, Mathias R
… +6 more, Carrasco Salas Y, Gomez Ho S, Murillo Vilella E, Bureau L, Lecuyer S, Débarre D
Eur Phys J E Soft Matter
· 2025 Nov · PMID 41317304
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Bacterial long-term contamination of surfaces is a promiscuous phenomenon often linked to harmful processes. Early bacterial exploration of interfaces, governed by adhesion and individual motility, is a known determinant...Bacterial long-term contamination of surfaces is a promiscuous phenomenon often linked to harmful processes. Early bacterial exploration of interfaces, governed by adhesion and individual motility, is a known determinant of the subsequent development and persistence of bacterial colonies. However, the mechanisms by which bacteria integrate various environmental signals at these interfaces and modulate their behavior in response remain poorly understood. Here we present methods for designing precisely controlled microenvironments that enable the manipulation of both physical and chemical properties of solid-liquid interfaces, and also permit in situ monitoring of bacteria at these interfaces within microfluidic flow cells. Our aim is to provide an innovative toolbox for the interdisciplinary research community focused on elucidating the complex processes underlying bacterial surface exploration. We illustrate its use here by examining the surface motility of the pathogen Pseudomonas aeruginosa.
Eur Phys J E Soft Matter
· 2025 Nov · PMID 41313416
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Dynamic emergence defined as a time-dependent entanglement (in the sense of coexistence and mutual influence of phases) of aligned, levorotatory (counterclockwise) and dextrorotatory (clockwise) phases has been recently...Dynamic emergence defined as a time-dependent entanglement (in the sense of coexistence and mutual influence of phases) of aligned, levorotatory (counterclockwise) and dextrorotatory (clockwise) phases has been recently put forward as a means to characterise collective behaviour in active matter [1, 2]. Up to now, dynamic emergence has only been detected in numerical simulations (interacting boids), hence this work is aimed at experimentally detecting it by drone recording different human crowds, each consisting of 30 members, moving within the area of a basketball court. The crowd was instructed to follow only two simple rules, namely, 1) To jog within a basketball court, and 2) To try to stay together at all times even if the crowd is disturbed by a simulated attack. The recorded emergent collective behaviour was characterised by extracting individual paths and velocity vectors in time, which were used to build local order parameters that revealed the existence of phases entanglement, thus confirming the presence of dynamic emergence. This result highlights the importance of using local order parameters to characterise collective behaviour. Additionally, an IABP (inertial active Brownian particle) model with three different interaction rules is proposed and compared with the available experimental data. This comparison shows that an IABP with visual weighted topological interactions reproduces the dynamics of a human crowd. Furthermore, a new parameter called rotational dispersion is introduced in order to identify dynamic emergence in a phase diagram.
Eur Phys J E Soft Matter
· 2025 Nov · PMID 41286392
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In this study, a quantitative structure-property relationship (QSPR) analysis was conducted to predict the physiochemical properties of anti-HIV drug molecules using a linear regression model. The model utilized neighbor...In this study, a quantitative structure-property relationship (QSPR) analysis was conducted to predict the physiochemical properties of anti-HIV drug molecules using a linear regression model. The model utilized neighborhood degree sum topological indices, which are graph-theoretical descriptors representing molecular structure, as key predictive features. These indices were calculated for each molecule, providing a numerical representation of their structural properties. The linear regression model effectively correlated these indices with the known physicochemical properties of the drugs, demonstrating its potential to predict the efficacy of new compounds. This approach offers a valuable tool for designing and optimizing anti-HIV drugs based on molecular topological descriptors.
Eur Phys J E Soft Matter
· 2025 Nov · PMID 41214270
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We examine the influence of an external orienting field on the director orientation and fluid flow of an active nematic liquid crystal confined in a channel, subject to infinite anchoring of the director and no-slip cond...We examine the influence of an external orienting field on the director orientation and fluid flow of an active nematic liquid crystal confined in a channel, subject to infinite anchoring of the director and no-slip conditions at the channel walls. A mathematical model based on the Ericksen-Leslie dynamic equations for nematic liquid crystals is employed, with an additional active stress tensor accounting for the activity of the fluid. By solving the fully coupled nonlinear equations numerically, we investigate the dynamic response and the steady state of the active nematic when an orienting field is switched on. The dynamic behaviour when an orienting field is switched off is also examined, with our model demonstrating how the activity of the liquid crystal can enhance or hinder the classically observed kickback immediately after switch-off and generate nontrivial steady-state solutions. Specifically, we find that kickback, which can delay relaxation of the system to a steady state, can be made less pronounced, and eventually completely avoided, for contractile agents with a high activity parameter, even with a high magnitude orienting field value.
Ouldali H, Dejoux C, Pastoriza-Gallego M
… +3 more, Cojocaru C, Farcas A, Oukhaled A
Eur Phys J E Soft Matter
· 2025 Nov · PMID 41204049
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Cucurbit[n]urils (CBn, n = 5-8) are macrocyclic hosts that form stable inclusion complexes with a variety of guest molecules, including amino acids and peptides. In this study, we investigate the interactions of CBn homo...Cucurbit[n]urils (CBn, n = 5-8) are macrocyclic hosts that form stable inclusion complexes with a variety of guest molecules, including amino acids and peptides. In this study, we investigate the interactions of CBn homologues with the aerolysin (AeL) protein nanopore using single-molecule ionic current recordings and molecular docking simulations, with the goal of developing a selective sensing platform for complex biofluids. Under an applied voltage, CBn molecules enter the AeL nanopore exclusively through its extracellular cap domain, inducing characteristic ionic current blockades. These events are influenced by voltage, electrolyte type (KCl, NaCl, CsCl), and ionic strength. Both the frequency and dwell time of blockade events increase with voltage, with CB6 generating particularly long blockades-lasting several seconds-enabling real-time monitoring of host-guest interactions at the single-molecule level. Molecular docking simulations support these observations, revealing that CB5, CB7, and CB8 preferentially bind to the extracellular region of AeL, while CB6 shows strongest affinity for the intracellular region. Among all homologues, CB5 forms the most stable complex with AeL. Hydrophobic interactions dominate binding across all complexes. Importantly, none of the CBn species translocate through the pore, consistent with experimental data. These findings highlight the utility of AeL nanopores for probing CBn interactions with high temporal resolution and selectivity. This approach may support future developments in nanopore-based sequencing and diagnostic technologies.
Eur Phys J E Soft Matter
· 2025 Oct · PMID 41165971
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A two-dimensional system consisting a mixture of highly coarse-grained saturated (S-type), unsaturated (U-type) lipid molecules, and cholesterol (C-type) molecules is considered to form a model lipid monolayer. All the S...A two-dimensional system consisting a mixture of highly coarse-grained saturated (S-type), unsaturated (U-type) lipid molecules, and cholesterol (C-type) molecules is considered to form a model lipid monolayer. All the S-, U-, and C-type particles are spherical in shape, with distinct interaction strengths. The phase behavior of the system is studied for various compositions (x) of the C-type particles, ranging from to 0.9. The results show that a structurally ordered complex is formed with the S- and C-types in the fluid-like environment of U-type particles, for . The time-averaged hexatic order parameter indicates that the dynamical segregation of S- and C-types exhibits a positional order that is found to be maximum for x in the range of 0.5 - 0.6. The mean change in the free energy ( ) obtained from the mean change in enthalpy ( ) and entropy ( ) calculations suggests that is minimum for . A phenomenological expression for the Gibbs free energy is formulated by explicitly accounting for the individual free energies of S-, U-, and C-type particles and the mutual interactions between them. Minimizing this phenomenological G with respect to the C-type composition results in the optimal value, for stable coexistence of phases; consistent with the simulation results and also the previous experimental observations [1]. All these observations signify the optimal C-type composition, .
Eur Phys J E Soft Matter
· 2025 Oct · PMID 41162776
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Topological indices, derived from graph-theoretical representations of molecular structure, have emerged as powerful tools for predicting the physicochemical properties of chemical compounds. In this study, we investigat...Topological indices, derived from graph-theoretical representations of molecular structure, have emerged as powerful tools for predicting the physicochemical properties of chemical compounds. In this study, we investigate a series of fifteen clinically significant drugs associated with the treatment of gonalgia (knee pain). The molecular graphs of these compounds are analyzed using the M-polynomial approach to compute seven key degree-based topological indices: the inverse sum index (ISI), harmonic arithmetic index (HA), inverse symmetric division deg index (ISDD), augmented Zagreb index (AZI), sum-connectivity index (SC), geometric arithmetic index (GA), and sum-Balaban index (SJ). A comprehensive quantitative structure-property relationship (QSPR) analysis is then performed to correlate these indices with critical physicochemical properties, including boiling point (BP), melting point (MP), critical temperature (CT), critical volume (CV), octanol-water partition coefficient (LogP), molar refractivity (MR), and calculated LogP (CLogP). Our results demonstrate strong predictive correlations, with the SC index showing exceptional performance for BP, MP, CT, CV, and MR, while the SJ index was the most effective for predicting LogP and CLogP. Among the regression models tested: linear, polynomial, and logarithmic the quadratic model consistently provided the highest accuracy, highlighting nonlinear relationships between molecular structure and properties. This study confirms that M-polynomial-derived topological indices, combined with polynomial regression, offer a reliable and efficient computational framework for predicting drug-like properties, providing valuable insights for pharmaceutical design and optimization.
Zhang G, Li Y, Yousaf S
… +2 more, Rani N, Aslam A
Eur Phys J E Soft Matter
· 2025 Oct · PMID 41123813
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This study presents a novel, integrated framework that combines graph-theoretic topological indices with multi-criteria decision-making (MCDM) techniques to systematically rank vitamins based on their solubility properti...This study presents a novel, integrated framework that combines graph-theoretic topological indices with multi-criteria decision-making (MCDM) techniques to systematically rank vitamins based on their solubility properties. The molecular structures of eleven essential vitamins were translated into quantitative descriptors using six distinct topological indices, which serve as proxies for key physicochemical properties governing solubility. These indices were then employed as criteria within three well-established MCDM methods: VIKOR, TOPSIS, and SAW to generate robust rankings. To ensure comprehensive and unbiased analysis, four contrasting weighting strategies (point allocation, standard deviation, entropy, and mean weight) were utilized to determine the relative importance of each criterion. The results demonstrate a high degree of consensus across methodologies, consistently identifying -tocopherol (vitamin E) and nicotinic acid (niacin) as the top- and bottom-ranked vitamins, respectively, while revealing nuanced differences in the mid-tier rankings based on the chosen MCDM approach and weighting scheme. This work underscores the significant potential of integrating computational chemistry with decision science to solve complex ranking problems in nutrition and pharmacology. The proposed framework offers a powerful, transparent, and reproducible tool for optimizing vitamin selection in dietary formulation and pharmaceutical design, paving the way for its application to other classes of compounds.
Eur Phys J E Soft Matter
· 2025 Oct · PMID 41109865
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When exposed to a time-periodic chemical signal, an E.coli cell responds by modulating its receptor activity in a similar time-periodic manner. But there is a phase lag between the applied signal and activity response. W...When exposed to a time-periodic chemical signal, an E.coli cell responds by modulating its receptor activity in a similar time-periodic manner. But there is a phase lag between the applied signal and activity response. We study the variation of activity amplitude and phase lag as a function of applied frequency , using numerical simulations. The amplitude increases with , reaches a plateau and then decreases again for large . The phase lag increases monotonically with and finally saturates to when is large. The activity is no more a single-valued function of the attractant signal, and plotting activity vs attractant concentration over one complete time period generates a loop. We monitor the loop area as a function of and find two peaks for small and large and a sharp minimum at intermediate values. We explain these results from an interplay between the timescales associated with adaptation, activity switching and applied signal variation. In particular, for very large the quasi-equilibrium approximation for activity dynamics breaks down, which has not been explored in earlier studies. We perform analytical calculation in this limit and find good agreement with our simulation results.
Eur Phys J E Soft Matter
· 2025 Oct · PMID 41053514
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Driven soft athermal systems may display a reversible-irreversible transition between an absorbing, arrested state and an active phase where a steady-state dynamics sets in. A paradigmatic example consists in cyclically...Driven soft athermal systems may display a reversible-irreversible transition between an absorbing, arrested state and an active phase where a steady-state dynamics sets in. A paradigmatic example consists in cyclically sheared suspensions under stroboscopic observation, for which in absence of contacts during a shear cycle particle trajectories are reversible and the stroboscopic dynamics is frozen, while contacts lead to diffusive stroboscopic motion. The random organization model (ROM), which is a minimal model of the transition, shows a transition which falls into the conserved directed percolation universality class. However, the ROM ignores hydrodynamic interactions between suspended particles, which make contacts a source of long-range mechanical noise that in turn can create new contacts. Here, we generalize the ROM to include long-range interactions decaying like inverse power laws of the distance. Critical properties continuously depend on the decay exponent when it is smaller than the space dimension. Upon increasing the interaction range, the transition turns convex (that is, with an order parameter exponent ), fluctuations turn from diverging to vanishing, and hyperuniformity at the transition disappears. We rationalize this critical behavior using a local mean-field model describing how particle contacts are created via mechanical noise, showing that diffusive motion induced by long-range interactions becomes dominant for slowly decaying interactions.
Eur Phys J E Soft Matter
· 2025 Oct · PMID 41042367
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Navigating in a fluid flow while being carried by it, using only information accessible from on-board sensors, is a problem commonly faced by small planktonic organisms. It is also directly relevant to autonomous robots...Navigating in a fluid flow while being carried by it, using only information accessible from on-board sensors, is a problem commonly faced by small planktonic organisms. It is also directly relevant to autonomous robots deployed in the oceans. In the last ten years, the fluid mechanics community has widely adopted reinforcement learning, often in the form of its simplest implementations, to address this challenge. But it is unclear how good are the strategies learned by these algorithms. In this paper, we perform a quantitative assessment of reinforcement learning methods applied to navigation in partially observable flows. We first introduce a well-posed problem of directional navigation for which a quasi-optimal policy is known analytically. We then report on the poor performance and robustness of commonly used algorithms (Q-Learning, Advantage Actor Critic) in flows regularly encountered in the literature: Taylor-Green vortices, Arnold-Beltrami-Childress flow, and two-dimensional turbulence. We show that they are vastly surpassed by PPO (Proximal Policy Optimization), a more advanced algorithm that has established dominance across a wide range of benchmarks in the reinforcement learning community. In particular, our custom implementation of PPO matches the theoretical quasi-optimal performance in turbulent flow and does so in a robust manner. Reaching this result required the use of several additional techniques, such as vectorized environments and generalized advantage estimation, as well as hyperparameter optimization. This study demonstrates the importance of algorithm selection, implementation details, and fine-tuning for discovering truly smart autonomous navigation strategies in complex flows.
We investigate the impact of environmental factors and biological defects on the thermal properties of single-helical proteins by analyzing their electronic specific heat (ESH) at constant volume ( ). To accurately mode...We investigate the impact of environmental factors and biological defects on the thermal properties of single-helical proteins by analyzing their electronic specific heat (ESH) at constant volume ( ). To accurately model these biomolecules, we consider their helical structure and long-range electron hopping within a tight-binding framework. Our findings demonstrate that the ESH spectra can differentiate between defective and pure helical protein molecules, even a sample with a very low contamination (single site defect) level. By comparing the ESH spectra of perfect and defective proteins, we can identify the relative location of the defect and distinguish them based on the level of contamination. This approach could be valuable for medical diagnosis of biological defects and serve as a preliminary screening method before resorting to whole genome sequencing, thereby saving time and resources.
Pradhan H, Poudel A, Shrestha D
… +8 more, Rogers A, Stewart M, Jereb A, Harper J, Li M, Zhang W, Chen J, Wang Y
Eur Phys J E Soft Matter
· 2025 Sep · PMID 40952583
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Elevated levels of silver in aquatic environments arising from widespread use of silver nitrate and silver nanoparticles in different sectors of industry and medicine pose significant biophysical challenges to aquatic mi...Elevated levels of silver in aquatic environments arising from widespread use of silver nitrate and silver nanoparticles in different sectors of industry and medicine pose significant biophysical challenges to aquatic microorganisms. Despite extensive toxicity studies of silver on bacteria and microbial communities, its influence on other aquatic microorganisms, such as microalgae, remains poorly understood. In this study, we investigated the biophysical response of C. reinhardtii microalgae to silver ion exposure in terms of their population growth dynamics, chlorophyll content, and swimming motility. We found that silver ions at different concentrations (from 0.29 to 1.18 M) elongated the lag phase of the microalgal growth. However, the growth of the microalgae was boosted by silver ions at low concentrations (e.g., 0.29 M), showing higher OD values at the stationary phase and higher maximum growth rates. This hormetic response exhibited by microalgae upon exposure to silver ions indicates a nonlinear coupling between ionic stress and cellular growth. Additionally, we quantified the chlorophyll content in the microalgae with different concentrations of silver ions using spectrophotometric analysis, which revealed that the microalgae cells contained twice as high concentrations of chlorophyll when exposed to silver ions at lower concentrations. More importantly, we monitored the motion of microalgae in the presence of silver ions, detected and tracked their motion using a deep learning algorithm, and determined the effects of silver ions on the swimming motility of individual C. reinhardtii microalgae. Our results showed reduced average swimming speed and increased directional change of microalgae upon silver ion exposure.