搜索结果：Proliferate

Cell proliferation and cell movement are fundamentally stochastic processes which lead to variability in the growth and spatial structure of cell populations in many biological settings, such as cell invasion, wound healing, and tumour growth. We develop stochastic, on-lattice agent-based models (ABMs) which incorporate volume exclusion, random movement, and multi-stage representations of the cell cycle. The multi-stage framework enables a more realistic representation of true cell cycle time distributions. We also introduce a novel form of myopic behaviour, in which cells sense their local environment when attempting to proliferate. For each ABM, we derive a corresponding continuum partial differential equation (PDE) description under the mean-field approximation. Using numerical simulations, we investigate how different proliferation mechanisms influence population-level dynamics in both the discrete and continuum models. In particular, we consider biologically relevant contexts of growth-to-confluence assays (using uniform initial conditions) and travelling wave behaviour associated with cell invasion. We examine how the PDE solutions compare with the behaviour of the correspond

We consider phase transitions out of a general topological phase in $2+1$ dimensions. We assume that the transition is triggered by a single Abelian anyon, which becomes light near the transition and whose worldlines proliferate after the transition. (This proliferation is often referred to as ``condensation.'') We describe the transition using a continuum field theory obtained by coupling the corresponding topological quantum field theory (TQFT) to a single complex scalar field associated with this anyon. With these assumptions, we find the most general relativistic field theory for such a transition. Even though for a given TQFT and a choice of anyon, there are infinitely many such field theories, the transition theory depends on only a single additional integer parameter. We analyze all these theories, their global symmetries, and their phases. In generic cases, the theory after the transition can be related to the original one via an Abelian hierarchy construction. In special cases, the theory after the transition is gapless, and with a particular deformation, it is related to the original TQFT by gauging an anomaly-free one-form global symmetry. We also explore the enrichment

Barraqué's proliferating series give an interesting turn on the concept of classic serialism by creating a new invariant when it comes to constructing the series: rather than the intervals between consecutive notes, what remains unaltered during the construction of the proliferations of the given base series is the permutation of the notes which happens between two consecutive series, that is to say, the transformation of the order of the notes in the series. This presents new possibilities for composers interested in the serial method, given the fact that the variety of intervals obtained by this method is far greater than that of classic serialism. In this manuscript, we will study some unexplored possibilities that the proliferating series offer from a mathematical point of view, which will allow composers to gain much more familiarity with them and potentially result in the creation of pieces that take serialism to the next level.

Models of many-body localization (MBL) exhibit slow numerical drifts towards delocalization with increasing system size, for which no satisfactory theory exists. Numerics indicates that these drifts are driven by the proliferation of many-body resonances at intermediate disorder strengths. We develop a statistical method to predict the distribution of resonance oscillation frequencies which captures how the formation of resonances at larger frequency scales subsequently affects the formation of resonances at lower frequencies. Working within the statistical Jacobi approximation (SJA), we derive a flow equation for a power-law exponent $θ(w)$ characterizing the density of resonances at frequency scale $w$. A localized phase is described by a line of fixed points with $θ(w)>0$, while an instability of the flow signals resonance proliferation and the onset of thermalization. The predicted $θ(w)$ matches numerics on the Anderson model on random regular graphs and the Lévy-Rosenzweig-Porter random matrix ensemble, both of which host resonance-driven delocalization transitions. We further connect the flow to eigenstate properties such as the participation ratio and to dynamical observ

Proliferation is a defining feature of life. Through growth, division, and death, living systems consume energy and inject mass, breaking conservation laws and driving collective phenomena from biofilm formation to embryonic development. Yet, while active matter physics has advanced our understanding of self-propelled agents, quantitative frameworks for proliferating systems are still emerging, and most work focuses on simplified settings. Here, we study \textit{E.coli} bacteria growing inside a network of single-file microchannels as a minimal model of structured environments. Competition for free volume drives the spontaneous emergence of coherent growth patterns that persist across generations but vanish when the channel links exceed the typical cell size at birth. Despite the strongly out-of-equilibrium character of the dynamics, the observed phenomenology can be quantitatively captured by an effective equilibrium description in which the flow state at each node is represented by a spin variable with ferromagnetic interactions. Simulations of growing elastic cells show that this coupling arises from internal stress accumulated at network nodes due to dynamical constraints. Our

Tunnel Geometry and Proliferation Logic were developed as independent attempts to describe structure without assuming an underlying continuum of points. Although their languages differ, both frameworks encode the same underlying idea: that locality is not primitive but emerges from stable patterns of refinement. This paper shows that each theory admits a representation as a frame equipped with its space of ultrafilters and a compatible Lawvere metric. In this common setting the two frameworks become strictly identical. I construct explicit functors establishing a strict categorical equivalence between Tunnel Geometry and Proliferation Logic, and show that their associated Laplacian operators are unitarily equivalent. The result suggests that geometric and logical approaches to structure are not competing descriptions but two aspects of a single static ontology.

Proliferation and motility are ubiquitous drivers of activity in biological systems. Here, we study a dense binary mixture of motile and proliferating particles with exclusively repulsive interactions, where homeostasis in the proliferating subpopulation is maintained by pressure-induced removal. Using computer simulations, we show that phase separation emerges naturally in this system at high density and weak enough self-propulsion. We show that condensation is caused by interactions between motile particles induced by the growing phase, and recapitulate this behavior in an effective model of only motile particles with attractive interactions. Our results establish a new type of phase transition and pave a way to reinterpret the physics of dense cellular populations, such as bacterial colonies or tumors, as systems of mixed active matter.

A robust nonproliferation regime has contained the spread of nuclear weapons to just nine states. Yet, emerging and disruptive technologies are reshaping the landscape of nuclear risks, presenting a critical juncture for decision makers. This article lays out the contours of an overlooked but intensifying technological arms race for nuclear (in)visibility, driven by the interplay between proliferation-enabling technologies (PETs) and detection-enhancing technologies (DETs). We argue that the strategic pattern of proliferation will be increasingly shaped by the innovation pace in these domains. Artificial intelligence (AI) introduces unprecedented complexity to this equation, as its rapid scaling and knowledge substitution capabilities accelerate PET development and challenge traditional monitoring and verification methods. To analyze this dynamic, we develop a formal model centered on a Relative Advantage Index (RAI), quantifying the shifting balance between PETs and DETs. Our model explores how asymmetric technological advancement, particularly logistic AI-driven PET growth versus stepwise DET improvements, expands the band of uncertainty surrounding proliferation detectability. T

We propose Josephson junction arrays as realistic platforms for observing nonequilibrium scaling laws characterizing the Kardar-Parisi-Zhang (KPZ) universality class, and space-time soliton proliferation. Focusing on a two-chain ladder geometry, we perform numerical simulations for the roughness function. Together with analytical arguments, our results predict KPZ scaling at intermediate time scales, extending over sufficiently long time scales to be observable, followed by a crossover to the asymptotic long-time regime governed by soliton proliferation.

Cancer is a complex sequence of disease conditions progressing gradually with generalized loss of growth control. It continues to be one of the biggest global health problems, and its etiology has given rise to a huge array of treatment outside of conventional chemotherapy. Melanoma is one of the deadliest forms of skin cancer originating from melanocytes. It is characterized by the overproduction of melanin by the increased in cell proliferation. Melanogenesis, the production of melanin is by melanocyte-stimulating hormone (MSH) which stimulates cyclic AMP (cAMP) production to increase melanocyte production. Through the use of methylxanthines, theophylline proliferation rate can be decreased by increasing cell differentiation. One of the basic principles of cell biology is the selectivity of differentiation and proliferation, where cells usually grow or differentiate but not both. This study aimed to collect baseline data of untreated B16-F10 melanoma cells to determine morphology and doubling time of untreated cells. This data was further compared to results from varied concentration treatments of theophylline. It was hypothesized that increased levels in cyclic adenosine monopho

As epithelial development or wound closure approaches completion, cell proliferation progressively slows via contact inhibition of proliferation (CIP) - a mechanism understood as being strictly local. Here we report the discovery of inhibition of proliferation through an unanticipated mechanism that is non-local. As a confluent epithelial layer becomes progressively more jammed, two interpenetrating networks emerge: islands of mechanically compressed non-cycling cells percolating within an ocean of mechanically tensed cycling cells. The evolution of the compression network was found to be susceptible to both specific molecular stimulus and to injury-induced unjamming. Yet, in all circumstances, the size of compressed islands followed a power-law distribution that was well-captured by preferential network theory. Together, these findings demonstrate the existence of a network-based inhibition of proliferation (NIP) that is self-organizing and poised in proximity to criticality.

Motivated by recent experiments on growing fibroblasts, we examine the development of nematic order in a colony of elongated cells proliferating on a nematic elastomer substrate. After sparse seeding, the cells divide and grow into locally ordered, but randomly oriented, domains that then interact with each other and the substrate. Global alignment with the substrate is only achieved above a critical density, suggesting a collective mechanism for the sensing of substrate anisotropy. The system jams at high density, where both reorientation and proliferation stop. Using a continuum model of a proliferating nematic liquid crystal, we examine the competition between growth-driven alignment and substrate-driven alignment in controlling the density and structure of the final jammed state. We propose that anisotropic traction forces and the tendency of cells to align perpendicular to the direction of density gradients act in concert to provide a mechanism for collective cell alignment.

The aggregation of topological spin textures at nano and micro scales has practical applications in spintronic technologies. Here, the authors report the in-plane current-induced proliferation and aggregation of bimerons in a bulk chiral magnet. It is found that the spin-transfer torques can induce the proliferation and aggregation of bimerons only in the presence of an appropriate out-of-plane magnetic field. It is also found that a relatively small damping and a relatively large non-adiabatic spin-transfer torque could lead to more pronounced bimeron proliferation and aggregation. Particularly, the current density should be larger than a certain threshold in order to trigger the proliferation; namely, the bimerons may only be driven into translational motion under weak current injection. Besides, the authors find that the aggregate bimerons could relax into a deformed honeycomb bimeron lattice with a few lattice structure defects after the current injection. The results are promising for the development of bio-inspired spintronic devices that use a large number of aggregate bimerons. The findings also provide a platform for studying aggregation-induced effects in spintronic syste

Proliferation of uninfected as well as infected hepatocytes and recycling of DNA-containing capsids are two major mechanisms playing significant roles in the clearance of hepatitis B virus (HBV) infection. In this study, the temporal dynamics of this infection are investigated through two in silico bio-mathematical models considering both proliferation of hepatocytes and the recycling of capsids. Both models are formulated on the basis of a key finding in the existing literature: mitosis of infected yields in two uninfected progenies. In the first model, we examine regular proliferation (occurs continuously), while the second model deals with the irregular proliferation (happens when the total number of liver cells decreases to less than 70% of its initial volume). The models are calibrated with the experimental data obtained from an adult chimpanzee. Results of this study suggest that when both hepatocytes proliferate with equal rate, proliferation aids the individual in a rapid recovery from the acute infection whereas in the case of chronic infection, the severity of the infection increases if the proliferation occurs frequently. On the other hand, if the infected cells prolifer

The propagation of errors severely compromises the reliability of quantum computations. The quantum adiabatic algorithm is a physically motivated method to prepare ground states of classical and quantum Hamiltonians. Here, we analyze the proliferation of a single error event in the adiabatic algorithm. We give numerical evidence using tensor network methods that the intrinsic properties of adiabatic processes effectively constrain the amplification of errors during the evolution for geometrically local Hamiltonians. Our findings indicate that low energy states could remain attainable even in the presence of a single error event, which contrasts with results for error propagation in typical quantum circuits.

We study the dynamics of proliferating cell collectives whose microscopic constituents' growth is inhibited by macroscopic growth-induced stress. Discrete particle simulations of a growing collective show the emergence of concentric-ring patterns in cell size whose spatio-temporal structure is closely tied to the individual cell's stress response. Motivated by these observations, we derive a multiscale continuum theory whose parameters map directly to the discrete model. Analytical solutions of this theory show the concentric patterns arise from anisotropically accumulated resistance to growth over many cell cycles. This work shows how purely mechanical processes can affect the internal patterning and morphology of cell collectives, and provides a concise theoretical framework for connecting the micro- to macroscopic dynamics of proliferating matter.

Multi-body dark matter annihilation is commonly expected to be suppressed by higher-order couplings and phase-space factors, therefore being ignored thus far. We show that, however, this does not hold for a class of nonthermal dark matter scenarios, where the dark matter particle becomes nonrelativistic at temperatures much higher than its mass. We exemplify such a multi-body process via ultralight pseudoscalar dark matter annihilation to diphotons, which leads to a novel photon proliferation effect in the early Universe. As a phenomenological application, we consider the photon temperature shift after neutrino decoupling, showing that the photon proliferation effect can render bounds on the ultralight dark matter couplings stronger than the existing constraints by several orders of magnitude. Our research can be extended to other interactions and dark matter candidates, highlighting the importance of multi-body processes in the early Universe.

Networks of nonlinear parametric resonators are promising candidates as Ising machines for annealing and optimization. These many-body out-of-equilibrium systems host complex phase diagrams of coexisting stationary states. The plethora of states manifest via a series of bifurcations, including bifurcations that proliferate purely unstable solutions, which we term ``ghost bifurcations''. Here, we demonstrate that the latter take a fundamental role in the stochastic dynamics of the system in the presence of noise. Specifically, they determine the switching paths and the switching rates between stable solutions. We demonstrate experimentally the impact of ghost bifurcations on the noise-activated switching dynamics in a network of two coupled parametric resonators.