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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 $U^* \sim q^{-\zeta}$ for two cases: fixed volume fraction $\phi$ and fixed mass density $\rho$. For fixed volume fraction, we report $\zeta < 0$. For the fixed mass density case, we report $\zeta > 0$, 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]., Comment: 21 pages, 5 figures. arXiv admin note: substantial text overlap with arXiv:2205.01864

The effect of the presence of two probe waveguides on the dynamics of hyper-Raman processes is studied in terms of quantum Zeno and anti-Zeno effects. Specifically, the enhancement (diminution) of the evolution of the hyper-Raman processes due to interaction with the probe waveguides via evanescent waves is viewed as quantum Zeno (anti-Zeno) effect. We considered the two probe waveguides interacting with only one of the optical modes at a time. For instance, as a specific scenario, it is considered that the two non-degenerate pump modes interact with each probe waveguide linearly while Stokes and anti-Stokes modes do not interact with the probes. Similarly, in another scenario, we assumed both the probe waveguides interact with Stokes (anti-Stokes) mode simultaneously. The present results show that quantum Zeno (anti-Zeno) effect is associated with phase-matching (mismatching). However, we did not find any relation between the presence of the quantum Zeno effect and antibunching in the bosonic modes present in the hyper-Raman processes., Comment: Dynamics of hyper-Raman processes is studied in terms of quantum Zeno and anti-Zeno effects

Active biological molecules present a powerful, yet largely untapped, opportunity to impart autonomous regulation to materials. Because these systems can function robustly to regulate when and where chemical reactions occur, they have the ability to bring complex, life-like behavior to synthetic materials. Here, we achieve this design feat by using functionalized circadian clock proteins, KaiB and KaiC, to engineer time-dependent crosslinking of colloids. The resulting material self-assembles with programmable kinetics, producing macroscopic changes in material properties, via molecular assembly of KaiB-KaiC complexes. We show that colloid crosslinking depends strictly on the phosphorylation state of KaiC, with kinetics that are synced with KaiB-KaiC complexing. Our microscopic image analyses and computational models indicate that the stability of colloidal super-structures depends sensitively on the number of Kai complexes per colloid connection. Consistent with our model predictions, a high concentration stabilizes the material against dissolution after a robust self-assembly phase, while a low concentration allows circadian oscillation of material structure. This work introduces the concept of harnessing biological timers to control synthetic materials; and, more generally, opens the door to using protein-based reaction networks to endow synthetic systems with life-like functional properties., Comment: 5 figures + SI

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., Comment: 22 pages, 10 figures. Authors James Clarke and Francis Cavanna contributed equally; Changes: Added modeling work, extended dynamic light scattering analysis

Many biological tissues feature a heterogeneous network of fibers whose tensile and bending rigidity contribute substantially to these tissues' elastic properties. Rigidity percolation has emerged as a important paradigm for relating these filamentous tissues' mechanics to the concentrations of their constituents. Past studies have generally considered tuning of networks by spatially homogeneous variation in concentration, while ignoring structural correlation. We here introduce a model in which dilute fiber networks are built in a correlated manner that produces alternating sparse and dense regions. Our simulations indicate that structural correlation consistently allows tissues to attain rigidity with less material. We further find that the percolation threshold varies non-monotonically with the degree of correlation, such that it decreases with moderate correlation and once more increases for high correlation. We explain the eventual reentrance in the dependence of the rigidity percolation threshold on correlation as the consequence of large, stiff clusters that are too poorly coupled to transmit forces across the network. Our study offers deeper understanding of how spatial heterogeneity may enable tissues to robustly adapt to different mechanical contexts., Comment: This article contains 10 pages and 5 figures

The cytoskeleton relies on diverse populations of motors, filaments, and binding proteins acting in concert to enable non-equilibrium processes ranging from mitosis to chemotaxis. Its versatile reconfigurability, programmed by interactions between its constituents, make the cytoskeleton foundational active matter. Yet, current active matter endeavors are limited largely to single force-generating components acting on a single substrate, far from the composite cytoskeleton in cells. Here, we engineer actin-microtubule double-networks, driven by kinesin and myosin motors and tuned by crosslinkers, to ballistically restructure and flow with speeds that span three orders of magnitude depending on the composite formulation and time relative to the onset of motor activity. Differential dynamic microscopy analyses reveal that kinesin and myosin compete to delay the onset of acceleration and suppress discrete restructuring events, while passive crosslinking of either actin or microtubules has an opposite effect. Our minimal advection-diffusion model and spatial correlation analyses correlate these dynamics to structure, with motor antagonism suppressing reconfiguration and de-mixing, while crosslinking enhances clustering. Despite the rich formulation space and emergent formulation-dependent structures, the non-equilibrium dynamics across all networks and timescales can be organized into three classes: slow isotropic reorientation, fast directional flow, and multimode restructuring. Moreover, our mathematical model demonstrates that diverse structural motifs can arise simply from the interplay between motor-driven advection and frictional drag. These general features of our platform facilitate applicability to other active matter systems, and shed light on diverse ways that cytoskeletal components can cooperate or compete to enable wide-ranging cellular processes.

Biological systems have the unique ability to self-organize and generate autonomous motion and work. Motivated by this, we investigate a 2D model colloidal network that can repeatedly transition between disordered states of low connectivity and ordered states of high connectivity via rhythmic binding and unbinding of biomimetic crosslinkers. We use Langevin dynamics to investigate the time-dependent changes in structure and collective properties of this system as a function of colloidal packing fractions and crosslinker oscillation periods and characterize the degree of order in the system by using network connectivity, bond length distributions, and collective motion. Our simulations suggest that we can achieve distinct states of this colloidal system with pronounced differences in microstructural order and large residence times in the ordered state when crosslinker kinetics and lifetimes depend directly on the oscillation period and this oscillation period is much larger than the colloidal diffusion time. Our results will provide insights into the rational design of smart active materials that can independently cycle between ordered and disordered states with desired material properties on a programmed schedule.

Healthy cartilage is a remarkable tissue, able to withstand tens of millions of loading cycles with minimal damage. While much is known about the structural origins of its compressive mechanics, how composition determines its mechanical behavior in shear, a major mode of failure, is poorly understood. Through a combination of microscale structure-function experiments and modeling, we develop a rigidity percolation framework to explain the structural origins of cartilage shear mechanics. This framework provides a new quantitative understanding for how the known degradative events in osteoarthritis determine the mechanical changes that are a hallmark of this disease. As such, this work provides a road map for understanding disease progression and in combination with non-invasive techniques such as MRI will enable more effective diagnosis and treatment., Comment: 9 pages, 3 pages of SI, 5 figures

The composite cytoskeleton, comprising interacting networks of semiflexible actin and rigid microtubules, actively generates forces and restructures using motor proteins such as myosins to enable key mechanical processes including cell motility and mitosis. Yet, how motor-driven activity alters the mechanics of cytoskeleton composites remains an open challenge. Here, we perform optical tweezers microrheology on actin-microtubule composites driven by myosin II motors to show that motor activity increases the linear viscoelasticity and elastic storage of the composite by active restructuring to a network of tightly-packed filament clusters and bundles. Our nonlinear microrheology measurements performed hours after cessation of activity show that the motor-contracted structure is stable and robust to nonlinear forcing. Unique features of the nonlinear response include increased mechanical stiffness, memory and heterogeneity, coupled with suppressed filament bending following motor-driven restructuring. Our results shed important new light onto the interplay between viscoelasticity and non-equilibrium dynamics in active polymer composites such as the cytoskeleton.

Neural networks are now extensively used in perception, prediction and control of autonomous systems. Their deployment in safety-critical systems brings forth the need for verification techniques for such networks. As an alternative to exhaustive and costly verification algorithms, lightweight falsification algorithms have been heavily used to search for an input to the system that produces an unsafe output, i.e., a counterexample to the safety of the system. In this work, we propose a falsification algorithm for neural networks that directs the search for a counterexample, guided by a safety property specification. Our algorithm uses a derivative-free sampling-based optimization method. We evaluate our algorithm on 45 trained neural network benchmarks of the ACAS Xu system against 10 safety properties. We show that our falsification procedure detects all the unsafe instances that other verification tools also report as unsafe. Moreover, in terms of performance, our falsification procedure identifies most of the unsafe instances faster, in comparison to the state-of-the-art verification tools for feed-forward neural networks such as NNENUM and Neurify and in many instances, by orders of magnitude., Comment: 10 pages, 3 figures, 4 tables

The cytoskeleton is a model active matter system that controls diverse cellular processes from division to motility. While both active actomyosin dynamics and actin-microtubule interactions are key to the cytoskeleton's versatility and adaptability, an understanding of their interplay is lacking. Here, we couple microscale experiments with mechanistic modeling to elucidate how connectivity, rigidity, and force-generation affect emergent material properties in in vitro composites of actin, tubulin, and myosin. We use time-resolved differential dynamic microscopy and spatial image autocorrelation to show that ballistic contraction occurs in composites with sufficient flexibility and motor density, but that a critical fraction of microtubules is necessary to sustain controlled dynamics. Our active double-network models reveal that percolated actomyosin networks are essential for contraction, but that networks with comparable actin and microtubule densities can uniquely resist mechanical stresses while simultaneously supporting substantial restructuring. Our findings provide a much-needed blueprint for designing cytoskeleton-inspired materials that couple tunability with resilience and adaptability.

Tunable mechanics and fracture resistance are hallmarks of biological tissues and highly desired in engineered materials. To elucidate the underlying mechanisms, we study a rigidly percolating double network (DN) made of a stiff and a flexible network. The DN shows remarkable tunability in mechanical response when the stiff network is just above its rigidity percolation threshold and minimal changes far from this threshold. Further, the DN can be modulated to either be extensible, breaking gradually, or stronger, breaking in a more brittle fashion by varying the flexible network's concentration., Comment: 5 Pages, 4 Figures

Quantum Zeno and anti-Zeno effects are studied in an asymmetric nonlinear optical coupler composed of a probe waveguide and a system waveguide. The system is a nonlinear waveguide operating under non-degenerate hyper-Raman process, while both the pump modes in the system are constantly interacting with the probe waveguide. The effect of the presence of probe on the temporal evolution of the system in terms of the number of photons in Stokes and anti-Stokes modes as well as phonon number is quantified as Zeno parameter. The negative (positive) values of the Zeno parameter in the specific mode are considered as the signatures of the quantum Zeno (anti-Zeno)effect in that mode of the system. It is observed that the phase mismatch in Stokes and anti-Stokes generation processes can be controlled to induce a transition between quantum Zeno and anti-Zeno effects for both off-resonant and resonant hyper-Raman process. However, in case of off-resonant hyper-Raman process in the system waveguide, the frequency detuning parameters can also be used analogously to cause the desired crossover. Further, the general nature of the physical system and the perturbative technique used here allowed us to analytically study the possibilities of observing quantum Zeno and anti-Zeno effects in a large number of special cases, including situations where the process is spontaneous, partially spontaneous and/or the system is operated under degenerate hyper-Raman process, or a simple Raman process., Comment: Dynamics of quantum Zeno and anti-Zeno effect is studied analytically in a nonlinear optical coupler which is very general in nature

During the morphogenesis of tissues and tumors, cells often interact with neighbors with different mechanical properties, but the understanding of its role is lacking. We use active Brownian Dynamics simulations to study a model co-culture consisting of two types of cells with the same size and self-propulsion speed, but different mechanical stiffness and cell-cell adhesion. As time evolves, the system phase separates out into clusters with distinct morphologies and transport properties for the two cell types. The density structure functions and the growth of cell clusters deviate from behavior characteristic of the phase separation in binary fluids. Our results capture emergent structure and motility previously observed in co-culture experiments and provide mechanistic insights into intercellular phase separation during development and disease., Comment: 6 pages, 4 figures

We have investigated the magnetic properties of highly anisotropic layered ferromagnetic semiconductor CrI$_3$ in presence of hydrostatic pressure ($P$). At ambient pressure, magnetization exhibits a clear anomaly below 212 K along with a thermal hysteresis over a wide temperature range (212-180 K), where a first-order structural transition is observed. CrI$_3$ undergoes a second-order ferromagnetic-paramagnetic phase transition with Curie temperature $T_C$=60.4 K. With application of pressure, the transition becomes sharper and $T_C$ is found to increase from 60.4 to 64.9 K as $P$ increases from 0 to 1.0 GPa. $T_C$ increases with $P$ in a sublinear fashion. The thermal hysteresis in magnetization and the increase of $T_C$ with pressure suggest that the spin and lattice degrees of freedom are coupled. The observed increase in $T_C$ has been explained on the basis of change in inter-layer coupling and Cr-I-Cr bond angle with pressure.