arXiv subjects

José Alvarado

Publications and source records attributed to José Alvarado.

13 recordsLinked to original sources

arXiv2026

Pinned Boundaries Delay Contraction and Shape Stress Relaxation in Active Gels

Cells dynamically generate, transmit, and dissipate stress. Central to these processes is the actomyosin cortex, an active contractile material that drives cellular mechanical behavior. While prior studies have focused on freely contracting actomyosin systems, the role of mechanical constraints such as adhesion to boundaries remains less explored. To address this, we employ reconstituted actomyosin gels to investigate cellular contractility. We study contraction dynamics under pinned boundary conditions, where the gel is adhered transversely to two opposing surfaces, mimicking supracellular actomyosin networks in tissues and embryos. We find that pinned contraction leads to stress buildup, delaying contraction, producing intermittent dynamics, and generating spatially nonuniform strain fields. Stress is relieved through several pathways, including active-stress-driven symmetric constriction and defect-driven processes such as boundary detachment and internal rupture. We develop a hydrodynamic model incorporating elastic, viscous, and active stress contributions that distinguishes between stress-accumulation and stress-release phases and links variations in active stress to the observed intermittent dynamics. The model predicts distinct energy relaxation rates before and after detachment events, providing insight into stress dissipation. We compare experiments with numerical simulations, which reproduce the observed behavior and reveal how internal energy is generated and dissipated during stress buildup and relaxation. Together, our results demonstrate how boundary conditions and spatial heterogeneity govern the mechanical behavior of contractile active gels. These findings provide insight into stress regulation in cellular and tissue-scale systems and may inform the design of adaptive soft materials and bioinspired robotic systems.

cond-mat.soft↗

arXiv2026

Elastoinertial effects govern dynamic response of soft hair beds

Fluid-immersed hair beds are ubiquitous in biology-from the endothelial glycocalyx and primary cilia to intestinal microvilli-where they serve as mechanosensors that transduce dynamic flow signals into biochemical regulatory responses. Despite the inherently dynamic nature of physiological flows, the dynamic mechanical properties of fluid-immersed hair beds under time-varying conditions remain poorly characterized. Here we investigate the transient rheological response of elastic hair beds to large-amplitude oscillatory shear flows at low to intermediate Reynolds number. While the hairs and fluid themselves obey linear constitutive laws, their coupled interaction produces a dynamic nonlinear response that depends sensitively on driving frequency and amplitude. We identify a crossover from a stress-lagging regime to a stress-leading regime, which is governed by an interplay between fluid viscosity, fluid inertia, and hair elasticity. A simplified rigid-beam model qualitatively captures the crossover behavior. Characterizing the dynamic flow response of soft hair beds has direct biological implications, since the lag time sensitively determines the stability of mechanosensory signaling in the feedback loops underlying essential biological processes such as vasodilation, ciliary remodeling, and tubular reabsorption. Our results establish a framework for understanding how the physical properties of biological hair beds optimize dynamic information transmission during mechanotransduction.

cond-mat.soft↗

arXiv2026

Fluctuation spectra of embryonic cell-cell interfaces reveal inverse-square scaling

Tissue-scale shape changes are driven by ensembles of intracellular forces. However measuring force in these contexts remains a difficult challenge. Here we perform spectral analysis of transverse fluctuations of cell-cell junctions in \emph{Xenopus} embryonic tissue explants undergoing convergent extension. We developed an image analysis pipeline to extract fluctuation amplitude profiles $u(x,t)$ from time-lapse confocal movies and computed two-dimensional spatiotemporal power spectra. We observe power-law scaling of mean-squared fluctuation power spectra consistent with $\langle u_q^2 \rangle \sim q^{-2}$ and $\langle u_f^2 \rangle \sim f^{-2}$. The spatial scaling agrees with predictions from the Helfrich Hamiltonian, and the temporal scaling agrees with overdamped dynamics of a fluctuating membrane, both in the tension-dominated regime. Pharmacological reduction of actomyosin contractility (via low-dose blebbistatin or latrunculin B) did not significantly alter either scaling exponent. Our results provide an early empirical characterization of junction fluctuation spectra in an actively shape-changing tissue. Simple tension-dominated membrane models appear sufficient to describe transverse junction dynamics despite their active and coupled nature. This work establishes a quantitative baseline for future studies of tension-bearing tissues and motivates the development of physical models specific to multicellular systems.

cond-mat.soft↗

arXiv2026

Molecular-scale, nonlinear actomyosin binding dynamics drive population-scale adaptation and evolutionary convergence

Biological actuators -- from myosin motors to muscles -- follow Hill's model where a dimensionless parameter $α$ captures the nonlinear coupling between contraction rate and force generation. Our prior work identified a characteristic $α^* = 3.85 \pm 2.32$ across natural muscles and showed that $α^*$ optimizes a power-efficiency tradeoff, potentially explaining its prevalence in nature. However, those results reflected short-term actuation tasks whereas phenotypic distributions in $α$ emerge over evolutionary timescales. Here, we use numerical simulations of self-propelled agents to explore how nonlinear actomyosin actuation (parameterized by $α$) shapes population dynamics. Agents of different $α$ compete for resources and reproduce with slight mutations. Without mutations, resource availability drives populations in $α$ toward distinct behaviors: under abundance or scarcity, specialized $α$ survive. However, with mutations and selection, populations evolve toward distributions centered around the characteristic $α^*$ observed in nature. Further, we show that the mutation rate $δ$ governs a balance between adaptability and robustness: large $δ$ generates instability and extinction, small $δ$ prevents feedback, while intermediate $δ$ enables long-term adaptability while remaining robust to short-term noise. Our results suggest that nonlinear actuation provides a general understanding of energy management in actomyosin systems across a wide range of timescales, ranging from the task-specific to evolutionary. These insights may guide the rational design of active materials with adaptive properties.

nlin.AO↗

arXiv2025

Experimental methods to control pinned and coupled actomyosin contraction events

Actin and myosin drive many instances of force generation, deformation, and shape change in cells, tissues, and organisms. In particular, cytoskeletal actomyosin is remarkable in its adaptive architecture, responding to a host of actin-binding proteins. Equally important, however, is actomyosin's interaction with its mechanical environment. Actomyosin contractility and environmental properties, such as geometry and stiffness, are inherently coupled. To understand this coupling, novel experimental techniques are needed. Here we describe methods to spatially control the anchoring of reconstituted contractile actomyosin networks to two, opposing surfaces ("transverse anchoring"). The two surfaces can be either rigid ("pinned contraction"), or one of the surfaces may be compliant ("coupled contraction"). We introduce compliance by manufacturing flexure hinges, and describe their calibration. Calibration permits a direct measurement of the contractile force and mechanical work that actomyosin exerts on the environment. The methods described here provide an avenue toward a more complete characterization of actomyosin's role as an actuator, an essential property in its context of driving deformation and shape change in living systems.

cond-mat.soft↗

arXiv2025

Moderate Deviations of Triangle Counts in the Erdős-Rényi Random Graph $G(n,m)$: The Lower Tail

Let $N_{\triangle}(G)$ be the number of triangles in a graph $G$. In [14] and [25] (respectively) the following bounds were proved on the lower tail behaviour of triangle counts in the dense Erdős-Rényi random graphs $G_m\sim G(n,m)$: \[ \mathbb{P}\big(N_{\triangle}(G_m) \, < \, (1-δ)\mathbb{E}[N_{\triangle}(G_m)]\big) \,=\, \exp\left(-Θ\left(δ^2n^3\right)\right) \qquad \text{if $n^{-3/2}\ll δ\ll n^{-1}$} \] and \[ \mathbb{P}\big(N_{\triangle}(G_m) \, < \, (1-δ)\mathbb{E}[N_{\triangle}(G_m)]\big) \,=\, \exp\left(-Θ(δ^{2/3}n^2) \right) \qquad \text{if $n^{-3/4} \ll δ\ll 1$.} \] Neeman, Radin and Sadun [25] also conjectured that the probability should be of the form $\exp\left(-Θ\left(δ^2n^3\right)\right)$ in the "missing interval" $n^{-1}\ll δ\ll n^{-3/4}$. We prove this conjecture. As part of our proof we also prove that some random graph statistics, related to degrees and codegrees, are normally distributed with high probability.

math.CO↗

arXiv2025

Control across scales: signals, information, and adaptive biological mechanical function

Biological systems perform an astonishing array of dynamical processes -- including development and repair, regulation, behavior and motor control, sensing and signaling, and adaptation, among others. Powered by the transduction of stored energy resources, these behaviors enable biological systems to regulate functions, achieve specific outcomes, and maintain stability far from thermodynamic equilibrium. These behaviors span orders of magnitude in length and time: from nanometer-scale molecular motors driving morphogenesis to kilometer-scale seasonal migrations, and from millisecond reflexes to millennia of evolutionary adaptations. While physical laws govern the dynamics of biological systems, they alone are insufficient to fully explain how living systems sense, decide, adapt, and, ultimately, control their dynamics. In this article, we argue that control theory provides a powerful, unifying framework for understanding how biological systems regulate dynamics to maintain stability across length and time scales far from equilibrium.

cond-mat.soft↗

arXiv2025

Optimal Control in Soft and Active Matter

Soft and active condensed matter represent a class of fascinating materials that we encounter in our everyday lives -- and constitute life itself. Control signals interact with the dynamics of these systems, and this influence is formalized in control theory and optimal control. Recent advances have employed various control-theoretical methods to design desired dynamics, properties, and functionality. Here we provide an introduction to optimal control aimed at physicists working with soft and active matter. We describe two main categories of control, feedforward control and feedback control, and their corresponding optimal control methods. We emphasize their parallels to Lagrangian and Hamiltonian mechanics, and provide a worked example problem. Finally, we review recent studies of control in soft, active, and related systems. Applying control theory to soft, active, and living systems will lead to an improved understanding of the signal processing, information flows, and actuation that underlie the physics of life.

cond-mat.soft↗

arXiv2025

Nonlinear contractile response of actomyosin active gels to control signals

Biological systems tightly regulate their physiological state using control signals. This includes the actomyosin cytoskeleton, a contractile active gel that consumes chemical free energy to drive many examples of cellular mechanical behavior. Upstream regulatory pathways activate or inhibit actomyosin activity. However, the contractile response of the actomyosin cytoskeleton to control signals remains poorly characterized. Here we employ reconstituted actomyosin active gels and subject them to step and pulsatile activation inputs. We find evidence for a nonlinear impulse response, which we quantify via a transfer function $δ\varepsilon / δg$ that relates input free-energy pulses $δg$ to output strain pulses $δ\varepsilon$. We find a scaling relation $δ\varepsilon / δg \sim g^{-0.3}$. The negative sign of the exponent represents a decreased effectiveness of a contracting gel in converting energy to strain. We ascribe nonlinearity in our system to a density-dependent mechanism, which contrasts strain-stiffening nonlinear responses to external stresses. Contractile response to control signals is an essential step toward understanding how information from mechanical signaling processes flow through actomyosin networks in living, and likely also synthetic, cells.

cond-mat.soft↗

arXiv2024

Microscale velocity-dependent unbinding generates a macroscale performance-efficiency tradeoff in actomyosin systems

Myosin motors are fundamental biological actuators, powering diverse mechanical tasks in eukaryotic cells via ATP hydrolysis. Recent work revealed that myosin's velocity-dependent detachment rate can bridge actomyosin dynamics to macroscale Hill muscle predictions. However, the influence of this microscale unbinding, which we characterize by a dimensionless parameter $α$, on macroscale energetic flows-such as power consumption, output and efficiency-remains elusive. Here we develop an analytical model of myosin dynamics that relates unbinding rates $α$ to energetics. Our model agrees with published in-vivo muscle data and, furthermore, uncovers a performance-efficiency tradeoff governed by $α$. To experimentally validate the tradeoff, we build HillBot, a robophysical model of Hill's muscle that mimics nonlinearity. Through HillBot, we decouple $α$'s concurrent effect on performance and efficiency, demonstrating that nonlinearity drives efficiency. We compile 136 published measurements of $α$ in muscle and myoblasts to reveal a distribution centered at $α^* = 3.85 \pm 2.32$. Synthesizing data from our model and HillBot, we quantitatively show that $α^*$ corresponds to a class of generalist actuators that are both relatively powerful and efficient, suggesting that the performance-efficiency tradeoff underpins the prevalence of $α^*$ in nature. We leverage these insights and propose a nonlinear variable-impedance protocol to shift along a performance-efficiency axis in robotic applications.

physics.bio-ph↗

arXiv2023

Morphological Control of Bundled Actin Networks Subject to Fixed-Mass Depletion

Depletion interactions are thought to significantly contribute to the organization of intracellular structures in the crowded cytosol. The strength of depletion interactions depends on physical parameters like the depletant number density and the depletant size ratio. Cells are known to dynamically regulate these two parameters by varying the copy number of proteins of a wide distribution of sizes. However, mammalian cells are also known to keep the total protein mass density remarkably constant, to within 0.5% throughout the cell cycle. We thus ask how the strength of depletion interactions varies when the total depletant mass is held fixed, a.k.a. fixed-mass depletion. We answer this question via scaling arguments, as well as by studying depletion effects on networks of reconstituted semiflexible actin $\textit{in silico}$ and $\textit{in vitro}$. We examine the maximum strength of the depletion interaction potential $U^*$ as a function of $q$, the size ratio between the depletant and the matter being depleted. We uncover a scaling relation $U^* \sim q^{-ζ}$ for two cases: fixed volume fraction $ϕ$ and fixed mass density $ρ$. For fixed volume fraction, we report $ζ< 0$. For the fixed mass density case, we report $ζ> 0$, which suggests the depletion interaction strength increases as the depletant size ratio is increased. To test this prediction, we prepared our filament networks at fixed mass concentrations with varying sizes of the depletant molecule poly(ethylene glycol) (PEG). We characterize the depletion interaction strength in our simulations via the mesh size. In experiments, we observe two distinct actin network morphologies, which we call weakly bundled and strongly bundled. We identify a mass concentration where different PEG depletant sizes leads to weakly bundled or strongly bundled morphologies...[more in main text].

cond-mat.soft↗

arXiv2022

Depletion-Driven Morphological Control of Bundled Actin Networks

The actin cytoskeleton is a semiflexible biopolymer network whose morphology is controlled by a wide range of biochemical and physical factors. Actin is known to undergo a phase transition from a single-filament state to a bundled state by the addition of polyethylene glycol (PEG) molecules in sufficient concentration. While the depletion interaction experienced by these biopolymers is well-known, the effect of changing the molecular weight of the depletant is less well understood. Here, we experimentally identify a phase transition in solutions of actin from networks of filaments to networks of bundles by varying the molecular weight of PEG polymers, while holding the concentration of these PEG polymers constant. We examine the states straddling the phase transition in terms of micro and macroscale properties. We find that the mesh size, bundle diameter, persistence length, and intra-bundle spacing between filaments across the line of criticality do not show significant differences, while the relaxation time, storage modulus, and degree of bundling change between the two states do show significant differences. Our results demonstrate the ability to tune actin network morphology and mechanics by controlling depletant size, a property which could be exploited to develop actin-based materials with switchable rigidity.

cond-mat.soft↗

arXiv2017

Force percolation of contractile active gels

Cells and tissues exert forces and can actively change shape. This strikingly autonomous behavior is powered by the cytoskeleton, which includes an active gel of actin filaments, crosslinks, and myosin molecular motors. Although individual motors are only a few nm in size and exert minute forces of a few pN, cells spatially integrate the activity of an ensemble of motors to produce larger contractile forces (order nN and greater) on cellular, tissue, and organismal length scales (order 10 $μ$m and greater). Experimental studies of reconstituted active-network model systems have long suggested that a mechanical interplay between the network's connectivity and motor activity dominates contractile behavior. Recent theoretical models indicate that this interplay can be understood in terms of percolation models, where the network connectivity is influenced by motor activity. Here we review experimental and theoretical studies of model contractile active gels and propose a state diagram that unites a large body of experimental and theoretical observations based on concepts from percolation theory.

cond-mat.soft↗