分子刚度对膜锚定受体-配体结合动力学影响的理论与模拟研究

人体内大部分生物学过程都离不开细胞黏附.细胞黏附行为主要由锚定于细胞膜上的特异性分子（又称受体和配体）的结合动力学关系来决定.已有研究表明，特异性分子的结合关系受外力及细胞膜波动等多种因素影响.然而，特异性分子刚度对细胞膜锚定受体 配体结合关系的影响机制仍不清楚.近期关于新冠病毒强传染力的研究表明，特异性黏附分子刚度对病毒与细胞结合具有重要影响.该文通过建立生物膜黏附的粗粒度模型，借助分子模拟和理论分析来研究分子刚度在黏附中的作用.结果表明，始终存在一个最佳膜间距及最佳分子刚度值，使得黏附分子亲和力和结合动力学参数达到最大值.这项研究不仅能加深人们对细胞黏附的认知，还有助于指导药物设计、疫苗研发等.     

Internalization and end flux in morphogen gradient formation

Two simple reaction–diffusion systems of partial differential equations and auxiliary conditions governing the activities of diffusible ligands such as Dpp in anterior–posterior axis of Drosophila wing imaginal discs were previously formulated and investigated by numerical simulations in [Developmental Cell 2 (2002) 785–796]. System B focuses on diffusion, reversible binding with receptors and ligand-mediated degradation for a fixed receptor concentration uniform in time and space. System C extended this basic but meaningful model to allow for endocytosis, exocytosis and receptor synthesis and degradation. The present paper provides a mathematical underpinning for the computational studies of these two systems and some insight gained from our analysis. We will see for instance that the two boundary value problems governing the steady state for the two systems are identical in form. This result will enable us to avoid dealing with internalization explicitly when we investigate other complex morphogen activities such as the effects of (1) feedback and (2) diffusible and non-diffusible molecules competing for ligands and receptors to inhibit cell signaling and pattern formation. The principal contribution of the present work pertains to the extension of System C to allow for a ligand flux at the source end. The more general model has many significant consequences including the removal of a limitation of previous models on ligand synthesis rate for the existence of steady state behavior. Linear stability of the corresponding steady state behavior is established. While the actual decay rate of transients is less accessible in this new model, it is possible to obtain tight upper and lower bounds for the decay rate in terms of the (effective) degradation rate of the receptors and that of the ligand-receptor complexes.     

基于弹性壳的三维群体细胞动力学模型

群体细胞迁移常见于胚胎发育、伤口愈合和肿瘤侵袭等各种生理和病理过程中,关于其动力学的研究对于揭示群体细胞迁移机理、深刻理解有关生物过程十分重要.该文构建了群体细胞的三维可变形壳状模型,提出了一种考虑细胞弹性形变和细胞间接触与黏附相互作用的群体细胞动力学理论,并发展了相应的数值算法.基于所发展的动力学模型与算法,对多细胞在嚢腔里的受限旋转运动进行了模拟,复现了相关实验现象,分析了细胞极性、细胞形变、胞间相互作用等因素对多细胞三维动力学的影响规律.     

EFFECTS OF SOG ON DPP-RECEPTOR BINDING

Concentration gradients of morphogens are known to be instrumental in cell signaling and tissue patterning. Of interest here is how the presence of a competitor of BMP ligands affects cell signaling. The effects of Sog on the binding of Dpp with cell receptors are analyzed for dorsal-ventral morphogen gradient formation in vertebrate and Drosophila embryos. This prototype system includes diffusing ligands, degradation of morphogens, and cleavage of Dpp-Sog complexes by Tolloid to free up Dpp. Simple and biologically meaningful necessary and sufficient conditions for the existence of a steady state gradient configuration are established, and existence theorems are proved. For high Sog production rates (relative to the Dpp production rate), it is found that the steady state configuration exhibits a more intense Dpp-receptor concentration near the dorsal midline. Numerical simulations of the evolution of the system show that, beyond some threshold Sog production rate, the transient Dpp-receptor concentration at the dorsal midline would become more intense than that of the steady state, before subsiding and approaching a nonuniform steady state of lower magnitude. The magnitude of the transient concentration has been found to increase by several fold with increasing Sog production rate. The highly intense Dpp activity at and around the dorsal midline is consistent with available experimental observations and other analytical studies.     

Aggregation of a Distributed Source in Morphogen Gradient Formation

In the development of a biological entity, ligands (such as Decapentaplegic (Dpp) along the anterior–posterior axis of the Drosophila wing imaginal disc) are synthesized at a localized source and transported away from the source for binding with cell surface receptors to form concentration gradients of ligand–receptor complexes for cell signaling. Generally speaking, activities such as diffusion and reversible binding with degradable receptors also take place in the region of ligand production. The effects of such morphogen activities in the region of localized distributed ligand source on the ligand–receptor concentration gradient in the entire biological entity have been modeled and analyzed as System F in [ 1 ]. In this paper, we deduce from System F, a related end source model (System A) in which the effects of the distributed ligand source is replaced by an idealized point stimulus at the border between the (posterior) chamber and the ligand production region that simulates the average effects of the ligand activities in the production zone. This aggregated end source model is shown to adequately reproduce the significant implications of System F and to contain the corresponding ad hoc point source model, System R of [ 2 ], as a special case. Because of its simpler mathematical structure and the absence of any limitation on the ligand synthesis rate for the existence of steady-state gradients, System A type models are expected to be used widely. An example of such application is the recent study of the inhibiting effects of the formation of nonsignaling ligand–nonreceptor complexes [ 3 ].     

Modeling dynamics of cell population molecule expression distribution

This article introduces a novel approach to the study of the dynamics of the molecule expression level of large-size cell populations, whose goal is to understand how individual cell behavior propagates to population dynamics. A hybrid automaton framework is used which allows the simultaneous modeling of the formation and dissociation of cell-to-cell conjugations, and the molecular processes they control. Serial encounters among the cells are described by a stochastic approach under which the cell distribution over the state space is modeled and the dynamics of the state probability density functions is determined. This work is motivated by the investigation of T-cell receptor expression distribution. These receptors are essential for the antigen recognition and the regulation of the immune system. The results are illustrated with examples and validated with real data.     

Global Dynamics of a Novel Delayed Logistic Equation Arising from Cell Biology

The delayed logistic equation (also known as Hutchinson’s equation or Wright’s equation) was originally introduced to explain oscillatory phenomena in ecological dynamics. While it motivated the development of a large number of mathematical tools in the study of nonlinear delay differential equations, it also received criticism from modellers because of the lack of a mechanistic biological derivation and interpretation. Here, we propose a new delayed logistic equation, which has clear biological underpinning coming from cell population modelling. This nonlinear differential equation includes terms with discrete and distributed delays. The global dynamics is completely described, and it is proven that all feasible non-trivial solutions converge to the positive equilibrium. The main tools of the proof rely on persistence theory, comparison principles and an $$L^2$$-perturbation technique. Using local invariant manifolds, a unique heteroclinic orbit is constructed that connects the unstable zero and the stable positive equilibrium, and we show that these three complete orbits constitute the global attractor of the system. Despite global attractivity, the dynamics is not trivial as we can observe long-lasting transient oscillatory patterns of various shapes. We also discuss the biological implications of these findings and their relations to other logistic-type models of growth with delays.     

Cyclic scheduling of a 2-machine robotic cell with tooling constraints

In this study, we deal with the robotic cell scheduling problem with two machines and identical parts. In an ideal FMS, CNC machines are capable of performing all the required operations as long as the required tools are stored in their tool magazines. However, this assumption may be unrealistic at times since the tool magazines have limited capacity and in many practical instances the required number of tools exceeds this capacity. In this respect, our study assumes that some operations can only be processed on the first machine while some others can only be processed on the second machine due to tooling constraints. Remaining operations can be processed on either machine. The problem is to find the allocation of the remaining operations to the machines and the optimal robot move cycle that jointly minimize the cycle time. We prove that the optimal solution is either a 1-unit or a 2-unit robot move cycle and we present the regions of optimality. Finally, a sensitivity analysis on the results is conducted.     

Measure Solutions for Some Models in Population Dynamics

We give a direct proof of well-posedness of solutions to general selection-mutation and structured population models with measures as initial data. This is motivated by the fact that some stationary states of these models are measures and not L ¹ functions, so the measures are a more natural space to study their dynamics. Our techniques are based on distances between measures appearing in optimal transport and common arguments involving Picard iterations. These tools provide a simplification of previous approaches and are applicable or adaptable to a wide variety of models in population dynamics.     

Dynamics of an HIV-1 infection model with cell mediated immunity

In this paper, we study the dynamics of an improved mathematical model on HIV-1 virus with cell mediated immunity. This new 5-dimensional model is based on the combination of a basic 3-dimensional HIV-1 model and a 4-dimensional immunity response model, which more realistically describes dynamics between the uninfected cells, infected cells, virus, the CTL response cells and CTL effector cells. Our 5-dimensional model may be reduced to the 4-dimensional model by applying a quasi-steady state assumption on the variable of virus. However, it is shown in this paper that virus is necessary to be involved in the modeling, and that a quasi-steady state assumption should be applied carefully, which may miss some important dynamical behavior of the system. Detailed bifurcation analysis is given to show that the system has three equilibrium solutions, namely the infection-free equilibrium, the infectious equilibrium without CTL, and the infectious equilibrium with CTL, and a series of bifurcations including two transcritical bifurcations and one or two possible Hopf bifurcations occur from these three equilibria as the basic reproduction number is varied. The mathematical methods applied in this paper include characteristic equations, Routh–Hurwitz condition, fluctuation lemma, Lyapunov function and computation of normal forms. Numerical simulation is also presented to demonstrate the applicability of the theoretical predictions.     

Characterization of stem cells using mathematical models of multistage cell lineages

Stem cells dynamics is an important field of research with promising clinical impacts. Due to the revolutionary new technologies of biological data collection, an enormous amount of information on specific factors and genes responsible for cell differentiation is available. However, the mechanisms controlling stem cell self-renewal, maintenance and differentiation are still poorly understood and there exists no general characterization of stem cells based on observable cell properties. We address these problems with the help of mathematical models. Stem cells are described as the cell type that is most responsive to certain environmental signals. This results in a dynamic characterization of stemness that depends on environmental conditions and is not necessarily linked to a unique cell population.     

Job routing and operations scheduling: a network-based virtual cell formation approach

Virtual cellular manufacturing inherits the benefits of traditional cellular manufacturing and maintains the responsiveness to the changing market and routing flexibility of a job shop by integrating machine-grouping, shop layout design and intercellular flow handling. The primary goal of virtual cell formation is to minimize the throughput time of a given job. This paper proposes a method for virtual cell formation by adopting the double-sweep algorithm for the k-shortest path problem, and a heuristic is devised to schedule the virtual cells for the multiple job orders. Results generated from this method include not only the optimal candidates of the virtual cell with the shortest throughput time with sub-optimal alternative route(s) and throughput time(s) as the alternative candidates in case some resources are restricted or are not available. The procedure of virtual cell creation and scheduling is illustrated explicitly with examples. Since most of the scheduling problems are NP-hard and virtual cell scheduling is even more complex due to the bottleneck machines that are demanded by jobs at other cells. For multiplicity of possible virtual cell candidates, in addition to the precedence and resource constraints, heuristic solutions are found to be reasonable.     

Cellular automata study of high burn-up structures

We propose a new approach, based on the cellular automata, for processing and modeling the structure dynamics of UO₂ at different cross-section averaged burn-ups. Micrographs of the material surface, subjected to both “as-polished” and “as-etched” treatments, with a magnification of 1250× have been used in our study. It has been shown that this approach provides efficient tools for investigation of the surface structure dynamics both at local and global levels.     

Development of a macro-scale model from a meso-scale model for cell culture population dynamics

In this paper, we present a novel macro-scale analytical model that allows the prediction of how the population size will change in a cell culture starting from an arbitrary initial value. General biological knowledge and some empirical observations are used to design an agent-based discrete-time model at the meso-scale, which then serves as a simulation environment and provides the necessary insights for the development of the continuous-time, differential equation-based, compact macro-scale model. This model can be parameter-tuned and employed for predicting how the population size changes. The paper gives a procedure for the estimation of parameter values of the macro-scale model via some simple tests to be conducted on the cell culture at hand. The performance of the macro-scale model is validated via simulation results that show how well the macro-scale model captures the population dynamics as obtained from the meso-scale model, while the biological plausibility of the meso-scale model is taken for granted.     

A multi-agent model describing self-renewal of differentiation effects on the blood cell population

In this work, a new multi-agent model is used to describe blood cell population dynamics. More particularly, we focus our simulations here on differentiation and self-renewal process based on cell communication. We consider the different cases where progenitor cells are able to self-renew or not in the bone marrow. As a consequence of this study, we give some possible explanations of the mechanism for recovery of the system under important blood loss or blood diseases such as anemia.     

Nonlinear Dynamics of a Bubble Contrast Agent Oscillating near an Elastic Wall

Contrast agent microbubbles, which are encapsulated gas bubbles, are widely used to enhance ultrasound imaging. There are also several new promising applications of the contrast agents such as targeted drug delivery and noninvasive therapy. Here we study three models of the microbubble dynamics: a nonencapsulated bubble oscillating close to an elastic wall, a simple coated bubble and a coated bubble near an elastic wall.We demonstrate that complex dynamics can occur in these models. We are particularly interested in the multistability phenomenon of bubble dynamics. We show that coexisting attractors appear in all of these models, but for higher acoustic pressures for the models of an encapsulated bubble.We demonstrate how several tools can be used to localize the coexisting attractors. We provide some considerations why the multistability can be undesirable for applications.     

A one-step tabu search algorithm for manufacturing cell design

As part of the cellular manufacturing design process, machines must be grouped in cells and the corresponding part families must be assigned. Limits on both the number of machines per cell and the number of parts per family can be considered. A weighted sum of intracell voids and intercellular moves is used to evaluate the quality of the solutions. We present a tabu search algorithm that systematically explores feasible machine cells configurations determining the corresponding part families using a linear network flow model. The performance of this tabu search is benchmarked against two simulated annealing approaches, another tabu search approach and three heuristics: (ZODIAC, GRAFICS and MST).     

A stable class of improved second-derivative free Chebyshev-Halley type methods with optimal eighth order convergence

In this paper, we present a uniparametric family of modified Chebyshev-Halley type methods with optimal eighth-order of convergence. In terms of computational cost, each member of the family requires only four functional evaluations per step, and hence is optimal in the sense of Kung-Traub conjecture. Moreover, in order to have additional information to choose some elements of the class, in particular some stable enough, we use complex dynamics tools to analyze their stability. Then, some ranges of values of the parameter are found to be avoided but we show that the region of stable members of this family is vast. It is found by way of illustration that these proposed methods are very useful in high precision computations.