Search

Measurements of local stresses on the cancer cells (CCs), inferred by embedding inert compressible tracer particles (TPs) in a growing multicellular spheroid (MCS), show that pressure decreases monotonically as the distance from the core of the MCS increases. How faithfully do the TPs report the local stresses in the CCs is an important question because pressure buildup in the MCS is dynamically generated due to CC division, which implies that the CC dynamics should be minimally altered by the TPs. Here using theory and simulations, we show that although the TP dynamics is unusual, exhibiting sub-diffusive behavior on times less than the CC division times and hyper-diffusive dynamics on in the long-time limit, they do not affect the long-time CC dynamics or the local CC stress distributions. The CC pressure profile within the MCS, which decays from a high value at the core to the periphery, is almost identical with and without the TPs. That the TPs have insignificant effect on the local stresses in the MCS implies that they are reliable reporters of the CC microenvironment., Comment: 11 pages, 5 figures. arXiv admin note: text overlap with arXiv:2003.12941

Self-generated gradients (SGG) provide robust steering cues that guide cells in their long-distance expeditions during embryonic development, immune response, and cancer metastasis. Cells generate their own local, dynamic gradients by breaking down the broadly distributed attractants in the environment, which leads to propulsion. How cells sense the environment and the interplay of self-generated force and long-range range chemotactic interactions determines the collective behavior of cells in vivo is largely unknown. We develop a theory to provide quantitative insight into how self-generated chemotaxis (SGC) steers the collective migration of cells during their long-distance journeys. In an externally imposed gradient, the cells exhibit super-diffusive motion at time less than persistent time ($\tau_p$) and exhibit diffusive motion at time $t>\tau_p$. On the other hand breakdown of chemo-attractants influences the density fluctuations and long-range correlations emerge in the density of chemotactic cells. The cells exhibit superdiffusive motion at a longtime limit. The SGG provides an effective mechanism for long-distance travel compared to an externally imposed gradient. Our theory provides a general framework for studying the non-equilibrium dynamics of collections of interacting particles., Comment: It has mistake in the calculation. In the externally imposed gradient How MSD calculation will done from the Deans approach. It does not agree the known result. I did not figure it out yet

By embedding inert tracer particles (TPs) in a growing multicellular spheroid the local stresses on the cancer cells (CCs) can be measured. In order for this technique to be effective the unknown effect of the dynamics of the TPs on the CCs has to be elucidated to ensure that the TPs do not greatly alter the local stresses on the CCs. We show, using theory and simulations, that the self-generated (active) forces arising from proliferation and apoptosis of the CCs drive the dynamics of the TPs far from equilibrium. On time scales less than the division times of the CCs, the TPs exhibit sub-diffusive dynamics (the mean square displacement, $\Delta_{TP}(t) \sim t^{\beta_{TP}}$ with $\beta_{TP}<1$), similar to glass-forming systems. Surprisingly, in the long-time limit, the motion of the TPs is hyper-diffusive ($\Delta_{TP}(t) \sim t^{\alpha_{TP}}$ with $\alpha_{TP}>2$) due to persistent directed motion for long times. In comparison, proliferation of the CCs randomizes their motion leading to superdiffusive behavior with $\alpha_{CC}$ exceeding unity. Most importantly, $\alpha_{CC}$ is not significantly affected by the TPs. Our predictions could be tested using \textit{in vitro} imaging methods where the motion of the TPs and the CCs can be tracked., Comment: 5 pages, 5 figures

Collective cell movement, characterized by multiple cells that are in contact for substantial periods of time and undergo correlated motion, plays a central role in cancer and embryogenesis. Recent imaging experiments have provided time-dependent traces of individual cells, thus providing an unprecedented picture of tumor spheroid growth. By using simulations of a minimal cell model, we analyze the experimental data that map the movement of cells in fibrosarcoma tumor spheroid embedded in a collagen matrix. Both simulations and experiments show that cells in the core of the spheroid exhibit subdiffusive glassy dynamics (mean square displacement, $\Delta(t) \approx t^{\alpha}$ with $\alpha < 1$), whereas cells in the periphery exhibit superdiffusive motion, $\Delta(t) \approx t^{\alpha}$ with $\alpha>1)$. The motion of most of the cells near the periphery undergo highly persistent and correlated directional motion, thus explaining the observed superdiffusive behavior. The $\alpha$ values for cells in the core and periphery, extracted from simulations and experiments are in near quantitative agreement with each other, which is surprising given that no parameter in the model was used to fit the measurements. The qualitatively different dynamics of cells in the core and periphery is captured by the fourth order susceptibility, introduced to characterize metastable states in glass forming systems. Analyses of the velocity autocorrelation of individual cells show remarkable spatial heterogeneity with no two cells exhibiting similar behavior. The prediction that $\alpha$ should depend on the location of the cells in the tumor is amenable to experimental test. The highly heterogeneous dynamics of cells in the tumor spheroid provides a plausible mechanism for the origin of intratumor heterogeneity., Comment: 30 pages, 6 figures (19 panels)

Experiments and simulations have established that dynamics in a class of living and abiotic systems that are far from equilibrium exhibit super diffusive behavior at long times, which in some cases (for example evolving tumor) is preceded by slow glass-like dynamics. By using the evolution of a collection of tumor cells, driven by mechanical forces and subject to cell birth and apoptosis, as a case study we show theoretically that on short time scales the mean square displacement is sub-diffusive due to jamming, whereas at long times it is super diffusive. The results obtained using stochastic quantization method, which is needed because of the absence of fluctuation-dissipation theorem (FDT), show that the super-diffusive behavior is universal and impervious to the nature of cell-cell interactions. Surprisingly, the theory also quantitatively accounts for the non-trivial dynamics observed in simulations of a model soap foam characterized by creation and destruction of spherical bubbles, which suggests that the two non-equilibrium systems belong to the same universality class. The theoretical prediction for the super diffusion exponent is in excellent agreement with simulations for collective motion of tumor cells and dynamics associated with soap bubbles.

The migration behaviors of cancer cells are known to be heterogeneous. However, the interplay between the adhesion interactions, dynamical shape changes and fluid flows in regulating cell migration heterogeneity and plasticity during cancer metastasis is still elusive. To further quantitative understanding of cell motility and morphology, we develop a theory using stochastic quantization method that describes the role of biophysical cues in regulating diverse cell motility. We show that the cumulative effect of time dependent adhesion interactions that determine the structural rearrangements and self-generated force due to actin remodeling, dictate the super-diffusive motion of mesenchymal phenotype in the absence of flow. Interstitial flows regulate cell motility phenotype and promote the amoeboid over mesenchymal motility through adhesion interactions. Cells exhibit a dynamical slowing down of collective migration, with a decreasing degree of super-diffusion. Mesenchymal cells are more persistent and diffusive compared to amoeboid cells. Our findings, suggest a mechanism of Interstitial flow induced directed motion of cancer cells through adhesion, and provide the much needed insight into a recent experimental observation concerning the diverse motility of breast cancer cells.

Random polyampholytes (PAs) contain positively and negatively charged monomers that are distributed randomly along the polymer chain. The interaction between charges is assumed to be given by the Debye-Huckel potential. We show that the size of the PA is determined by an interplay between electrostatic interactions, giving rise to the polyelectrolyte (PE) effect due to net charge per monomer ($\sigma$), and an effective attractive PA interaction due to charge fluctuations, $\delta \sigma$. The interplay between these terms gives rise to non-monotonic dependence of the radius of gyration, $R_g$ on the inverse Debye length, $\kappa$ when PA effects are important (${\frac{\delta \sigma}{\sigma}} > 1$). In the opposite limit, $R_g$ decreases monotonically with increasing $\kappa$. Simulations of PA chains, using a charged bead-spring model, further corroborates our theoretical predictions. The simulations unambiguously show that conformational heterogeneity manifests itself among sequences that have identical PA parameters. A clear implication is that the phases of PA sequences, and by inference IDPs, cannot be determined using only the bare PA parameters ($\sigma$ and $\delta \sigma$). The theory is used to calculate the changes in $R_g$ on $N$, the number of residues for a set of Intrinsically Disordered Proteins (IDPs). For a certain class of IDPs, with $N$ between 24 to 441, the size grows as $R_g \sim N^{0.6}$, which agrees with data from Small Angle X-ray Scattering (SAXS) experiments., Comment: J. Chem. Phys. 2018

We develop a theory to probe the effect of non-equilibrium fluctuation-induced forces on the size of a polymer confined between two horizontal thermally conductive plates subject to a constant temperature gradient, $\nabla T$. We assume that (a) the solvent is good and (b) the distance between the plates is large so that in the absence of a thermal gradient the polymer is a coil whose size scales with the number of monomers as $N^{\nu}$, with $\nu \approx 0.6$. We predict that above a critical temperature gradient, $\nabla T_c \sim N^{-\frac{5}{4}}$, favorable attractive monomer-monomer interaction due to Giant Casimir Force (GCF) overcomes the chain conformational entropy, resulting in a coil-globule transition. The long-ranged GCF-induced interactions between monomers, arising from thermal fluctuations in non-equilibrium steady state, depend on the thermodynamic properties of the fluid. Our predictions can be verified using light-scattering experiments with polymers, such as polystyrene or polyisoprene in organic solvents (neopentane) in which GCF is attractive., Comment: 5 pages, 3 figures

Collective migration dominates many phenomena, from cell movement in living systems to abiotic self-propelling particles. Focusing on the early stages of tumor evolution, we enunciate the principles involved in cell dynamics and highlight their implications in understanding similar behavior in seemingly unrelated soft glassy materials and possibly chemokine-induced migration of CD8$^{+}$ T cells. We performed simulations of tumor invasion using a minimal three dimensional model, accounting for cell elasticity and adhesive cell-cell interactions as well as cell birth and death to establish that cell growth rate-dependent tumor expansion results in the emergence of distinct topological niches. Cells at the periphery move with higher velocity perpendicular to the tumor boundary, while motion of interior cells is slower and isotropic. The mean square displacement, $\Delta(t)$, of cells exhibits glassy behavior at times comparable to the cell cycle time, while exhibiting super-diffusive behavior, $\Delta (t) \approx t^{\alpha}$ ($\alpha > 1$), at longer times. We derive the value of $\alpha \approx 1.33$ using a field theoretic approach based on stochastic quantization. In the process we establish the universality of super-diffusion in a class of seemingly unrelated non-equilibrium systems. Super diffusion at long times arises only if there is an imbalance between cell birth and death rates. Our findings for the collective migration, which also suggests that tumor evolution occurs in a polarized manner, are in quantitative agreement with {\it in vitro} experiments. Although set in the context of tumor invasion the findings should also hold in describing collective motion in growing cells and in active systems where creation and annihilation of particles play a role., Comment: 56 pages, 19 figures

Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a {cascade involving} kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach in order to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus (Phys. Rev. X., {\bf 4}, 041017 (2014)). We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective {three-species} network with a pseudo intermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudo intermediate. There are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that {a} field theoretic formulation {of} stochastic biological {signaling offers} a systematic way to understand error propagation in networks of arbitrary complexity.

Natural protein sequences that self-assemble to form globular structures are compact with high packing densities in the folded states. It is known that proteins unfold upon addition of denaturants, adopting random coil structures. The dependence of the radii of gyration on protein size in the folded and unfolded states obeys the same scaling laws as synthetic polymers. Thus, one might surmise that the mechanism of collapse in proteins and polymers ought to be similar. However, because the number of amino acids in single domain proteins is not significantly greater than about two hundred, it has not been resolved if the unfolded states of proteins are compact under conditions that favor the folded states - a problem at the heart of how proteins fold. By adopting a theory used to derive polymer-scaling laws, we find that the propensity for the unfolded state of a protein to be compact is universal and is encoded in the contact map of the folded state. Remarkably, analysis of over 2000 proteins shows that proteins rich in $\beta$-sheets have greater tendency to be compact than $\alpha$-helical proteins. The theory provides insights into the reasons for the small size of single domain proteins and the physical basis for the origin of multi-domain proteins. Application to non-coding RNA molecules show that they have evolved to collapse sharing similarities to $\beta$-sheet proteins. An implication of our theory is that the evolution of natural foldable sequences is guided by the requirement that for efficient folding they should populate minimum energy compact states under folding conditions. This concept also supports the compaction selection hypothesis used to rationalize the unusually condensed states of viral RNA molecules., Comment: 8 figures

We solve a two dimensional model for polymer chain folding in the presence of mechanical pulling force ($f$) exactly using equilibrium statistical mechanics. Using analytically derived expression for the partition function we determine the phase diagram for the model in the $f$-temperature ($T$) plane. A square root singularity in the susceptibility indicates a second order phase transition from a folded to an unfolded state at a critical force ($f_c$) in the thermodynamic limit of infinitely long polymer chain. Surprisingly, the temperature dependence of $f_c$ shows a reentrant phase transition, which is reflected in an increase in $f_c$ as $T$ increases below a threshold value. For a range of $f$ values, the unfolded state is stable at both low and high temperatures. The high temperature unfolded state is stabilized by entropy whereas the low temperature unfolded state is dominated by favorable energy. The exact calculation could serve as a bench mark for testing approximate theories that are used in analyzing single molecule pulling experiments., Comment: 2 figures

The interaction between arbitrary dielectric heterostructures is studied within the framework of a recently developed dielectric contrast perturbation theory. It is shown that periodically patterned dielectric or metallic structures lead to oscillatory lateral Casimir-Lifshitz forces, as well as modulations in the normal force as they are displaced with respect to one another. The strength of these oscillatory contributions increases with decreasing gap size and increasing contrast in the dielectric properties of the materials used in the heterostructures., Comment: 7 pages, 3 combined figures

The effect of an external noise on the Lorenz model is investigated near the onset of convection and near the Hopf bifurcation. We show the existence of a diverging time scale near the onset of convection and a resonance near the Hopf bifurcation. Our calculation provides an understanding of the noise induced stabilization of the limit cycle that had been observed numerically., Comment: 4 pages, one fig

We have considered the critical Casimir force on a $^4$He film below and above the bulk $\lambda$ point. We have explored the role of fluctuations around the mean field theory in a perturbative manner, and have substantially improved the mean field result of Zandi et al [Phys. Rev. E {\bf 76}, 030601(R) (2007)]. The Casimir scaling function obtained by us approaches a universal constant ($-\frac{\zeta(3)}{8\pi}$) for $T\lesssim 2.13~\text{K}$., Comment: The term $\frac{1}{4b}\xi_0^4k_BT_\lambda$ at the Fig.2-caption in the published version should be read as $\frac{1}{4b\xi_0^4k_BT_\lambda}$

We study the motion of Brownian particle in modulated media in the strong damping limit by using {\em toy model}, with special emphasis on the transition from localise to diffusive behavior. By using model potential we have seen the localised behavior when the number of minima of the potential is finite in the asymptotic time limit. In the limit of infinite number of minima we have seen the diffusive behavior.We calculate exactly the diffusion coefficient in periodic field of force. We have also studied the transport in commensurate and incommensurate media., Comment: 6 pages

We discuss Brownian Motion from a more elementary viewpoint presented by Einstein in 1908. Later developments and applications are briefly reviewed., Comment: 22 pages, 5 figures

We discuss the approach to equilibrium of systems governed by the Fokker-Planck equation. In particular, we focus on problems involving barrier penetration and the associated Kramers' time. We also describe the connection between stochastic processes and quantum mechanics., Comment: 20 pages, 3 figures

We consider a class of growth models and models of turbulence based on the randomly stirred fluid. The similarity between the predictions of these models, noted a decade earlier, is understood on the basis of a stochastic quantization scheme., Comment: 3 pages

Problems in non equilibrium statistical physics are characterized by the absence of a fluctuation dissipation theorem. The usual analytic route for treating these vast class of problems is to use response fields in addition to the real fields that are pertinent to a given problem. This line of argument was introduced by Martin, Siggia and Rose. We show that instead of using the response field, one can, following the stochastic quantization of Parisi and Wu, introduce a fictitious time. In this extra dimension a fluctuation dissipation theorem is built in and provides a different outlook to problems in non equilibrium statistical physics., Comment: 4 pages