Global dynamics of an epidemiological model with age of infection and disease relapse

In this paper, an epidemiological model with age of infection and disease relapse is investigated. The basic reproduction number for the model is identified, and it is shown to be a sharp threshold to completely determine the global dynamics of the model. By analysing the corresponding characteristic equations, the local stability of a disease-free steady state and an endemic steady state of the model is established. By means of suitable Lyapunov functionals and LaSalle's invariance principle, it is verified that if the basic reproduction number is less than unity, the disease-free steady state is globally asymptotically stable, and hence the disease dies out; if the basic reproduction number is greater than unity, the endemic steady state is globally asymptotically stable and the disease becomes endemic.     

An age-structured within-host HIV-1 infection model with virus-to-cell and cell-to-cell transmissions

In this paper, a within-host HIV-1 infection model with virus-to-cell and direct cell-to-cell transmission and explicit age-since-infection structure for infected cells is investigated. It is shown that the model demonstrates a global threshold dynamics, fully described by the basic reproduction number. By analysing the corresponding characteristic equations, the local stability of an infection-free steady state and a chronic-infection steady state of the model is established. By using the persistence theory in infinite dimensional system, the uniform persistence of the system is established when the basic reproduction number is greater than unity. By means of suitable Lyapunov functionals and LaSalle's invariance principle, it is shown that if the basic reproduction number is less than unity, the infection-free steady state is globally asymptotically stable; if the basic reproduction number is greater than unity, the chronic-infection steady state is globally asymptotically stable. Numerical simulations are carried out to illustrate the feasibility of the theoretical results.     

离散广义Logistic模型的混沌控制

利用Lyapunov指数方法,验证了一类离散广义Logistic模型存在混沌现象,并采用混沌控制中OGY方法的基本思想,研究了这类模型的混沌控制问题,得出了消除混沌,保持种群稳定到不动点和2-周期轨道的充分条件．     

一类具有CTL免疫和时滞的HTLV-I传染病模型的动力学性质(英文)

主要研究了一类具有CTL免疫和时滞的HTLV-I传染的数学模型.通过构造Lyapunov泛函,分别证明了当R₀≤1,R₁≤10,R1>1时,系统（1.1）的无病平衡点E₀,无免疫平衡点E₁及地方病平衡点E₂是全局吸引的.     

Global Properties of <Emphasis Type="Italic">SIR</Emphasis> and <Emphasis Type="Italic">SEIR</Emphasis> Epidemic Models with Multiple Parallel Infectious Stages

We consider global properties of compartment SIR and SEIR models of infectious diseases, where there are several parallel infective stages. For instance, such a situation may arise if a fraction of the infected are detected and treated, while the rest of the infected remains undetected and untreated. We assume that the horizontal transmission is governed by the standard bilinear incidence rate. The direct Lyapunov method enables us to prove that the considered models are globally stable: There is always a globally asymptotically stable equilibrium state. Depending on the value of the basic reproduction number R ₀, this state can be either endemic (R ₀>1), or infection-free (R ₀≤1).     

Vasomotion: the case for chaos

Fluctuations in vascular calibre, a phenomenon known as vasomotion, are ubiquitous in the microcirculation and represent emergent behaviour that involves synchronisation of Ca²⁺ oscillations in individual vascular cells. Ideally, coordinated interactions between locally generated vasomotion and neuro-humoral control mechanisms will allow optimal sensing of flow and pressure within vascular networks and thereby facilitate synergistic readjustments in local vascular conductance and flow under conditions of dynamically changing metabolic demand. Indeed, many studies have reported that vasomotion becomes more prominent under pathophysiological conditions, suggesting that it may serve as an adaptive homeodynamic response that maintains or re-establishes flow when perfusion is compromised. We here summarise evidence that the apparent irregular nature of vasomotion reflects deterministic interactions between a small number of dominant control variables, rather than random events, and may therefore be formally classified as chaotic. We also discuss the potential physiological benefits of chaos in the microcirculation and the key roles of signalling via gap junctions and nitric oxide.     

具有时滞的HBV病毒动力学模型稳定性分析

HBV（HePatitis B virus）是一种具有严重传染性的肝炎病毒,迄今为止,人们对它的免疫和慢性化的机制等方面还不甚了解。本文基于相关的病理知识,对应的建立了具有时滞的微分方程数学模型,系统地探讨了肝炎B病毒与宿主细胞之间的关系,利用Lyapunov函数方法研究了病毒动力学模型感染平衡点的局部稳定性和未感染平衡点全局稳定性,并利用数学模拟验证了理论分析。结果表明时滞的存在不会影响到感染平衡点的局部稳定性,但能影响平衡点到达的时间跨度,对于药物治疗的疗程和治疗时机的确定有参考意义。     

Thresholds in transient dynamics of signal transduction pathways

Transient dynamics of signal transduction pathways play an important role in many biological processes, including cell differentiation, apoptosis, metabolism and DNA damage response. Recent examples of quantitative methods to characterize transient signals include transient metabolic control coefficients and finite time Lyapunov exponents. In our work we compare these quantitative methods to characterize transient phenomena and specifically discuss their predictive power for three examples. We focus on the identification of thresholds that separate different transient dynamic behaviors. Our investigation leads to the following results: The spectrum of the finite-time Lyapunov exponents unambiguously and reliably identifies putative thresholds in transient dynamics. Metabolic control coefficients do not reliably detect all thresholds and suffer from false positives.     

Under what conditions signal transduction pathways are highly flexible in response to external forcing? A case study on calcium oscillations

Sensitivity and flexibility are typical properties of biological systems. These properties are here investigated in a model for simple and complex intracellular calcium oscillations. In particular, the influence of external periodic forcing is studied. The main point of the study is to compare responses of the system in a chaotic regime with those obtained in a regular periodic regime. We show that the response to external signals in terms of the range of synchronization is not significantly different in regular and chaotic Ca2+ oscillations. However, both types of oscillation are highly flexible in regimes with weak dissipation. Therefore, we conclude that dissipation of free energy is a suitable index characterizing flexibility. For biological systems this appears to be of special importance since for thermodynamic reasons, notably in view of low free energy consumption, dissipation should be minimized.     

An analysis of the reliability phenomenon in the FitzHugh-Nagumo model

The reliability of single neurons on realistic stimuli has been experimentally confirmed in a wide variety of animal preparations. We present a theoretical study of the reliability phenomenon in the FitzHugh-Nagumo model on white Gaussian stimulation. The analysis of the model's dynamics is performed in three regimes—the excitable, bistable, and oscillatory ones. We use tools from the random dynamical systems theory, such as the pullbacks and the estimation of the Lyapunov exponents and rotation number. The results show that for most stimulus intensities, trajectories converge to a single stochastic equilibrium point, and the leading Lyapunov exponent is negative. Consequently, in these regimes the discharge times are reliable in the sense that repeated presentation of the same aperiodic input segment evokes similar firing times after some transient time. Surprisingly, for a certain range of stimulus intensities, unreliable firing is observed due to the onset of stochastic chaos, as indicated by the estimated positive leading Lyapunov exponents. For this range of stimulus intensities, stochastic chaos occurs in the bistable regime and also expands in adjacent parts of the excitable and oscillating regimes. The obtained results are valuable in the explanation of experimental observations concerning the reliability of neurons stimulated with broad-band Gaussian inputs. They reveal two distinct neuronal response types. In the regime where the first Lyapunov has negative values, such inputs eventually lead neurons to reliable firing, and this suggests that any observed variance of firing times in reliability experiments is mainly due to internal noise. In the regime with positive Lyapunov exponents, the source of unreliable firing is stochastic chaos, a novel phenomenon in the reliability literature, whose origin and function need further investigation.