静脉注射吸毒人群HIV／AIDS数学模型分析

建立了四川省西昌市静脉注射吸毒人群HIV／AIDS传播的数学模型,给出了模型的理论分析和数值模拟结果．通过必要的分析,给出了各类平衡点的存在性和稳定性,系统的一致持续生存,以及基本再生数的数学表达式和具体取值．揭示了该静注人群中的HIV／AIDS有进一步蔓延的趋势,但如果采取适当的干预措施,该静注人群中HIV／AIDS流行可得到有效的控制．     

森林种群径阶转移模型中转移概率的估算方法

基于统计分析理论和微分方程理论,给出了森林种群径阶转移模型中估算转移概率的方法：第一种是在有两次样地观测数据,不考虑林分环境因子等因素的条件下估算转移概率;第二种是在已知林分环境因子条件下,不需要对样地有两次观测数据来估算转移概率．实例验证结果表明,两种估算转移概率的方法具有计算简单和实用性强的特点,对森林经营与管理有一定的理论指导和实际应用价值．     

二个区域的封闭种群的标记重捕模型

通过引入区域的初始比例因子,考虑了二个区域A与B的封闭种群标记重捕模型,再利用完整的极大似然函数和多项分布函数的性质,给出了当个体在不同区域的个体捕捉率相等时的二个区域之间的转移概率与各区域的初始比例的求法,推导出在不同区域的个体捕捉率不相等但个体低转移率条件下二个区域的封闭种群的标记重捕模型的参数表达式,并用实例说明。     

捕食──被捕食系统中的周期现象

本文给出了捕食被捕食系统中增殖率非单调的场合以及捕食具有饱和的场合,系统周期解的存在性;另一方面,当增殖率单调或捕食量仅与个体数成比例这样简单型的相互作用,或相互作用具有时滞效应时,给出了周期解的存在性．     

一类具有非单调发生率SIS流行病模型的分析

该文讨论了具有非单调发生率SIS流行病模型,分别建立了带有分布时滞和离散时滞形式的感染个体的恢复时滞模型,同时分析了系统平衡态的稳定性．     

一类具有时滞的传染病模型的稳定性分析

研究了一类具有时滞的传染病生物模型．首先研究了该模型的线性稳定性,并给出了一列Hopf分支值,然后利用中心流形定理和正规型方法,给出了确定分支周期解的分支方向与稳定性的计算公式．     

格氏栲种群个体年龄与胸径的时间序列模型研究

本文提出格氏栲种群以年轮确定种群个体年龄并与胸径、树高确定种群个体年龄有机结合的时间序列预测个体年龄方法。通过时间序列分析,确定出格氏栲种群个体年龄与胸径关系的ＡＲＩＭＡ（１,２,０）模型,经检验该模型的相似性系数为９３．４８％,即该模型预测胸径生长量是可靠的。同时,通过ＡＲＩ－ＭＡ（１,２,０）模型预测结果与实际调查材料组合起来,建立较为准确反映个体年龄的组合模型：Ａ＝１０．１５４５１＋１．１１３８５１Ｄ＋０．０４２２００４９Ｄ２－０．０００２２７３０３Ｄ３式中Ｄ为格氏栲种群个体胸径,Ａ为格氏栲种群个体年龄,相关指数为０．９９９８。可见,组合模型的格氏栲种群个体胸径与年龄回归关系极显著,效果理想,为相应研究提供一个较为可靠的方法。     

抗出血病草鱼子代抗病力的分析

草鱼出血病（Grasscar’phemorrhagicvirus,GCHV）是草鱼鱼种养殖阶段危害最为严重的病毒性疾病I’一’］,抗出血病草鱼新品种的培育是解决该病危害的根本途径［‘］。作者等从“七五”开始,开展了基因转移进行草鱼抗出血病育种的研究,建立了鱼类总DNA介导基因转移的实验模型I’］。将抗草鱼出血病的团头勤的总DNA转移到草鱼的受精卵,用GCHV人工攻毒方法,筛选出一批抗出血病草鱼个体。这批抗病个体已经成熟并繁殖子代。l材料与方法1．回实验草鱼实验用亲代草鱼为1990年经转移团头饬总DNA后,经GCHV攻毒筛选存活的草鱼【Cten…     

两种群相互竞争的具有脉冲出生率的SIS传染病模型

研究了一类两种群相互竞争的具有脉冲出生率的SIS传染病模型．通过理论分析,给出了各类周期解渐近稳定性的条件,并与相应的不具有脉冲出生率的SIS传染病模型进行了比较,揭示了两者的区别和联系．     

现代罗布人群线粒体DNA D-loop区序列多态性研究

目的：研究新疆尉犁县的现代罗布人群线粒体DNAD-loop区序列遗传多态性,并初步探讨现代罗布人群和其他人群的亲缘关系。方法：应用PER扩增直接测序法,对23个所测定的个体序列采用ClustalX、Mega3．1、hrlequin等软件包进行分析。结果：23个个体中,共检测到47个变异位点,界定了22种不同的单倍型,计算出偶合概率P值为0．05482,变异度h值为0．99604。结论：现代罗布人与中亚各民族的亲缘关系很近,尤其是与新疆维吾尔族有很近的亲缘关系。     

A Time Since Recovery Model with Varying Rates of Loss of Immunity

For many infectious diseases, immunity wanes over time. The majority of SIRS models assume that this loss of immunity takes place at a constant rate. We study temporary immunity within a SIRS model structure if the rate of loss of immunity can depend on the time since recovery from disease. We determine the conditions under which the endemic steady state becomes unstable and periodic oscillations set in, showing that a fairly rapid change between slow and rapid immunity loss is necessary to produce oscillations.     

Link between intestinal immunity and practical approaches to swine nutrition

Gaining a deeper understanding into the underlying mechanisms associated with intestinal function and immunity during the weaning transition is critical to help shed new light into applied nutrition approaches to improve piglet performance and health during this critical life-stage transition. The transient anorexia triggered at weaning leads to compromised intestinal barrier function and a localized inflammatory response. Considering barrier function, specific nutrient fractions appear to have a significant impact on the development and function of the immune and microbial systems around weaning. Understanding the specific impact of nutrients in the small intestine and hindgut is important for helping to bring more focus and consistency to nutritional approaches to support health and immunity during the weaning transition period. The challenge continues to be how to translate these modes of action into practical and scalable approaches for swine nutrition. We will focus specifically on practical nutritional approaches to influence intestinal immunity through lipid, protein and antioxidant nutrition.     

A spatially stochastic epidemic model with partial immunization shows in mean field approximation the reinfection threshold

Recently, the notion of a reinfection threshold in epidemiological models of only partial immunity has been debated in the literature. We present a rigorous analysis of a model of reinfection which shows a clear threshold behaviour at the parameter point where the reinfection threshold was originally described. Furthermore, we demonstrate that this threshold is the mean field version of a transition in corresponding spatial models of immunization. The reinfection threshold corresponds to the transition between annular growth of an epidemics spreading into a susceptible area leaving recovered behind and compact growth of a susceptible-infected-susceptible region growing into a susceptible area. This transition between annular growth and compact growth was described in the physics literature long before the reinfection threshold debate broke out in the theoretical biology literature.     

A spatially stochastic epidemic model with partial immunization shows in mean field approximation the reinfection threshold

Recently, the notion of a reinfection threshold in epidemiological models of only partial immunity has been debated in the literature. We present a rigorous analysis of a model of reinfection which shows a clear threshold behaviour at the parameter point where the reinfection threshold was originally described. Furthermore, we demonstrate that this threshold is the mean field version of a transition in corresponding spatial models of immunization. The reinfection threshold corresponds to the transition between annular growth of an epidemics spreading into a susceptible area leaving recovered behind and compact growth of a susceptible-infected-susceptible region growing into a susceptible area. This transition between annular growth and compact growth was described in the physics literature long before the reinfection threshold debate broke out in the theoretical biology literature.     

Dynamics of acquired immunity boosted by exposure to infection

A mathematical model is presented to describe the dynamics of immunity which can be boosted by reexposure to infection. Immunity is assumed to last until a specified interval of time elapses without an exposure. This assumption is incorporated into a compartmental model as a differential-delay equation. When the model is applied to malaria epidemiology, the prevalence of disease among adults is greatest at intermediate rates of infection. Observed age-prevalence curves have shapes similar to those of the predicted curves. Immunity in an individual is formulated in terms of a stochastic process, and an expression for the average duration of immunity is obtained. The average duration of immunity increases with the rate of exposure, but the presence of mortality (or other kinds of removal) shortens the average duration observed, in analogy with the theoryof competing risks.     

An evolutionary perspective on the systems of adaptive immunity

We propose an evolutionary perspective to classify and characterize the diverse systems of adaptive immunity that have been discovered across all major domains of life. We put forward a new function‐based classification according to the way information is acquired by the immune systems: Darwinian immunity (currently known from, but not necessarily limited to, vertebrates) relies on the Darwinian process of clonal selection to ‘learn’ by cumulative trial‐and‐error feedback; Lamarckian immunity uses templated targeting (guided adaptation) to internalize heritable information on potential threats; finally, shotgun immunity operates through somatic mechanisms of variable targeting without feedback. We argue that the origin of Darwinian (but not Lamarckian or shotgun) immunity represents a radical innovation in the evolution of individuality and complexity, and propose to add it to the list of major evolutionary transitions. While transitions to higher‐level units entail the suppression of selection at lower levels, Darwinian immunity re‐opens cell‐level selection within the multicellular organism, under the control of mechanisms that direct, rather than suppress, cell‐level evolution for the benefit of the individual. From a conceptual point of view, the origin of Darwinian immunity can be regarded as the most radical transition in the history of life, in which evolution by natural selection has literally re‐invented itself. Furthermore, the combination of clonal selection and somatic receptor diversity enabled a transition from limited to practically unlimited capacity to store information about the antigenic environment. The origin of Darwinian immunity therefore comprises both a transition in individuality and the emergence of a new information system – the two hallmarks of major evolutionary transitions. Finally, we present an evolutionary scenario for the origin of Darwinian immunity in vertebrates. We propose a revival of the concept of the ‘Big Bang’ of vertebrate immunity, arguing that its origin involved a ‘difficult’ (i.e. low‐probability) evolutionary transition that might have occurred only once, in a common ancestor of all vertebrates. In contrast to the original concept, we argue that the limiting innovation was not the generation of somatic diversity, but the regulatory circuitry needed for the safe operation of amplifiable immune responses with somatically acquired targeting. Regulatory complexity increased abruptly by genomic duplications at the root of the vertebrate lineage, creating a rare opportunity to establish such circuitry. We discuss the selection forces that might have acted at the origin of the transition, and in the subsequent stepwise evolution leading to the modern immune systems of extant vertebrates.     

斑马鱼食源性肠炎模型及其免疫细胞成像分析方法的建立

为了研究豆粕替代鱼粉对鱼类肠黏膜免疫的影响和建立缓解肠炎药物的筛选及功能性饲料添加剂的平台,研究采用固有免疫或适应性免疫细胞荧光标记的斑马鱼品系,通过50％的豆粕添加量替代鱼粉作为蛋白源,共设计了两组饲料,分别在幼鱼固有免疫或适应性免疫的发育阶段中饲喂荧光标记的斑马鱼,构建了斑马鱼豆粕诱导的肠炎模型,对构建的食源性肠炎...     

The loss of immunity in directly transmitted infections modeling: Effects on the epidemiological parameters

When directly transmitted infectious diseases are modeled assuming an everlasting induced immunity (and constant contact rate), there are well-established formulas to deal with, which is not true if we include the loss of induced immunity. In general, the immunity induced by the disease is everlasting. We propose a model considering the loss of immunity and present methods for the estimation of two epidemiological parameters: the force of infection and the basic reproduction ratio. We also analyze the effects of the loss of immunity on these parameters. Based on these results, we conclude that reinfection can play an important role in highly vaccinated populations.     

Combining Gompertzian growth and cell population dynamics

A two-compartment model of cancer cells population dynamics proposed by Gyllenberg and Webb includes transition rates between proliferating and quiescent cells as non-specified functions of the total population, N. We define the net inter-compartmental transition rate function: Phi(N). We assume that the total cell population follows the Gompertz growth model, as it is most often empirically found and derive Phi(N). The Gyllenberg-Webb transition functions are shown to be characteristically related through Phi(N). Effectively, this leads to a hybrid model for which we find the explicit analytical solutions for proliferating and quiescent cell populations, and the relations among model parameters. Several classes of solutions are examined. Our model predicts that the number of proliferating cells may increase along with the total number of cells, but the proliferating fraction appears to be a continuously decreasing function. The net transition rate of cells is shown to retain direction from the proliferating into the quiescent compartment. The death rate parameter for quiescent cell population is shown to be a factor in determining the proliferation level for a particular Gompertz growth curve.     

A minimal model for multiple epidemics and immunity spreading

Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.