The importance of 'memory' in statistical models for animal feeding behaviour

We investigate models for animal feeding behaviour, with the aim of improving understanding of how animals organise their behaviour in the short term. We consider three classes of model: hidden Markov, latent Gaussian and semi-Markov. Each can predict the typical 'clustered' feeding behaviour that is generally observed, however they differ in the extent to which 'memory' of previous behaviour is allowed to affect future behaviour. The hidden Markov model has 'lack of memory', the current behavioural state being dependent on the previous state only. The latent Gaussian model assumes feeding/non-feeding periods to occur by the thresholding of an underlying continuous variable, thereby incorporating some 'short-term memory'. The semi-Markov model, by taking into account the duration of time spent in the previous state, can be said to incorporate 'longer-term memory'. We fit each of these models to a dataset of cow feeding behaviour. We find the semi-Markov model (longer-term memory) to have the best fit to the data and the hidden Markov model (lack of memory) the worst. We argue that in view of effects of satiety on short-term feeding behaviour of animal species in general, biologically suitable models should allow 'memory' to play a role. We conclude that our findings are equally relevant for the analysis of other types of short-term behaviour that are governed by satiety-like principles.     

The use of animal models to guide rational vaccine design

Although there are several varieties of animal models of tuberculosis, the mouse and the guinea pig are by far the most validated and useful. These provide information about vaccine-induced protection, immunogenicity, toxicity, and immunopathological effects. There is still much to be learned, however, in terms of rational vaccine design, especially in the context of therapeutic or anti-latent vaccine formulations and animal models of these situations.     

Continuous-time Markov chains as models for animal behaviour

A survey is given of the application of (functions of) continuous-time Markov chains in the statistical analysis of behavioural time series.     

The use of animal models for stroke research: a review

Stroke has been identified as the second leading cause of death worldwide. Stroke is a focal neurologic deficit caused by a change in cerebral circulation. The use of animal models in recent years has improved our understanding of the physiopathology of this disease. Rats and mice are the most commonly used stroke models, but the demand for larger models, such as rabbits and even nonhuman primates, is increasing so as to better understand the disease and its treatment. Although the basic mechanisms of stroke are nearly identical among mammals, we here discuss the differences between the human encephalon and various animals. In addition, we compare common surgical techniques used to induce animal models of stroke. A more complete anatomic knowledge of the cerebral vessels of various model species is needed to develop more reliable models for objective results that improve knowledge of the pathology of stroke in both human and veterinary medicine.     

The role of mendelian genetics in stragetic models on animal behaviour

The authors combine known models for the evolution of (a) strategies in animal conflicts, and (b) gene frequencies for differential fecundity in order to relate the sociobiological notion of evolutionarily stable strategy with the genetic mechanism of Mendelian populations.     

The use of mice and rats as animal models for cardiopulmonary resuscitation research

Cardiopulmonary resuscitation (CPR) after the induction of cardiac arrest (CA) has been studied in mice and rats. The anatomical and physiological parameters of the cardiopulmonary system of these two species have been defined during experimental studies and are comparable with those of humans. Moreover, these animal models are more ethical to establish and are easier to manipulate, when compared with larger experimental animals. Accordingly, the effects of successful CPR on the function of vital organs, such as the brain, have been investigated because damage to these vital organs is of concern in CA survivors. Furthermore, the efficacy of several drugs, such as adrenaline (epinephrine), vasopressin and nitroglycerin, has been evaluated for use in CA in these small animal models. The purpose of these studies is not only to increase the rate of survival of CA victims, but also to improve their quality of life by reducing damage to their vital organs after CA and during CPR.     

The use of animal infection models to study the pathogenesis of melioidosis and glanders

The use of animal infection models is central to the study of microbial pathogenesis. In combination with genetic, immunological and antigen purification techniques, much can be learned regarding the pathogenesis of diseases caused by microorganisms. This update focuses on the recent use of animal infection models to study the pathogenesis of melioidosis and glanders.     

The use of apical tissue analysis to determine the phosphorus status ofStylosanthes hamata cv. Verano

Summary A glasshouse experiment was conducted to determine the effect of plant age on critical phosphorus concentration in apical tissue ofStylosanthes hamata cv. Verano. Cut and non-cut treatments were included to simulate grazing and non-grazing situations. The critical concentration declined rapidly in both treatments during the 18 weeks following germination and remained relatively constant thereafter. The results are consistent with a higher phosphorus requirement for grazed plants compared with ungrazed plants.     

The use of viscoelastometry to determine survival curves for intact genomes

Viscoelastometry enables one to determine both size (Mr) and number concentration (L1) of intact genome molecules in solution. Comparison of four parameters, corrected for shear stress, as functions of 60Co gamma-ray dose showed that (1) the principal retardation time (tau 11,0) remained constant, indicating that intact genomes (bacteriophage T4c) were being measured; (2) the principal recoil (gamma 11,r,0) decreased with dose directly proportionately to (and determining) L1; (3) both the total recoil (gamma r,0) and the recoil area (Ar,0), under conditions of high solvent viscosity decreased with dose almost as sensitively as gamma 11,r,0. The DNAD37 was 540 +/- 25 Gy and the biological PFUD37 was 410.1 +/- 4.5 Gy yielding 75.9 +/- 3.6% of inactivating events explicable by one double-strand break (DSB) per genome. This value is comparable to Freifelder's [Virology 36, 613-619 (1981)] value of 86% for phage T4r48+, and the Frankenberg-Schwager et al. (Br. J. Cancer, in press) value of 0.84 DSB/cell/lethal event in diploid mutant rad54-3 yeast under conditions restrictive for DSB repair. Therefore, T4c may be an excellent model system for DNA damage repair studies with relevance to pro- and eukaryotes. Viscoelastometry, working near its lower size limit, provided precise estimates of the proportion of genomes lacking DSBs. It is not subject to the molecular deformation upper size limitations of the other biophysically understood size measurement methods (e.g., sedimentation rotor speed dependence). Therefore, it should be the method of choice for the study of genomes larger than those of the T even bacteriophages.     

The application of statistical decision theory to animal behaviour

Statistical decision theory is discussed as a general framework for analysing how animals should learn. Attention is focused on optimal foraging behaviour in stochastic environments. We emphasise the distinction between the mathematical procedure that can be used to find optimal solutions and the mechanism an animal might use to implement such solutions. The mechanisms might be specific to a restricted class of problems and produce suboptimal behaviour when faced with problems outside this class. We illustrate this point by an example based on what is known in the literature on animal learning as the partial reinforcement effect.     

Type 2 diabetes-an introduction to the development and use of animal models

Although the epidemiology of type 2 diabetes (T2D) has been well described, there is much about the disease that remains unclear. For example, lifestyle factors-including increased body weight with visceral fat deposition and insufficient physical activity-are thought to be primary contributors to the adverse changes in the metabolism of muscle and fat cells that comprise the first stage of the disease. However, the precise mechanisms underlying these initial alterations are incompletely understood. Other, less obvious questions relate to the presence of sex differences in the development and health consequences of T2D, the etiological role of the central nervous system ("stress"), and the potential evolutionary origins of T2D susceptibility. Some of these issues can be resolved by further study of human populations. However, many questions can be answered only through the kinds of controlled prospective studies that are conducted with appropriate animal models. The use of such models can be an invaluable part of an overall strategy designed to elucidate the mechanisms underlying the development of T2D, understand the natural history of the disease, identify targets for therapy, and evaluate interventions. Current evidence indicates that no single animal model replicates the development of human T2D in all of its details. Nonetheless, the existing models (e.g., naturally occurring and genetically modified rodents, cats, pigs, and nonhuman primates) offer researchers a rich array of opportunities to investigate the myriad complexities of T2D. The individual contributions comprising this issue of ILAR Journal review the research that has been conducted on many of these animals.     

Discrimination criteria for apparent two-site transport models.

The medical beliefs of a people have in the past been studied principally by cultural anthropologists. The focus of these studies is usually on intrasocietal dynamics and cultural relativism—a striking orientation. However, beliefs about disease are integral to the way groups have and continue to adapt, and are thus important to both social and biological scientists. In order to study the role of medical beliefs in the adaptation of the group, a comparative approach is needed. This requires viewing these beliefs more generically, comparing their symbolic properties, and analyzing how they are used in explaining and dealing with actual occurrences of disease. The concept of a taxonomy of disease is introduced, as well as the notion of different semantic regions in the taxonomy. In the attempt to clarify the biological significance of a group's taxonomy of disease, and of its mode of operation, the ideas of uncertainty and information are employed. The significance and fruitfulness of this approach is discussed.     

The use of linear mixed models to estimate variance components from data on twin pairs by maximum likelihood.

It is shown that maximum likelihood estimation of variance components from twin data can be parameterized in the framework of linear mixed models. Standard statistical packages can be used to analyze univariate or multivariate data for simple models such as the ACE and CE models. Furthermore, specialized variance component estimation software that can handle pedigree data and user-defined covariance structures can be used to analyze multivariate data for simple and complex models, including those where dominance and/or QTL effects are fitted. The linear mixed model framework is particularly useful for analyzing multiple traits in extended (twin) families with a large number of random effects.