Traditional and new concepts in protein evaluation of feeds: a review

The purpose of protein evaluation of a diet is to determine its value for meeting amino acid requirements of animals. The early recognition that proteins can be utilized by different efficiency rates has promoted extended research to reveal quality differences and their reasons. A brief historical overview is given in this review about the development of concepts and theories in protein evaluation. Recent developments have focused attention on determination of available quantities of essential amino acids. In vitro chemical assays and dye-binding procedures are relatively fast and provide data without access to animals, however they do not always correlate well with biological estimates. Enzymic digestion methods and microbiological assays for prediction of availability of essential amino acids have the potential for serial determination in quality control, however they are constrained by a lack of information about the availability of peptides liberated and utilized during in vivo digestion of proteins. Animal growth assays and balance experiments can provide valuable estimates of available quantities of essential amino acids. However, the interpretation of data is complicated by the many factors affecting in vivo protein utilization, by the endogenous amino acid excretion and the effects of microflora of the alimentary tract. The search for reliable assays remains a worthwhile objective also in the future.     

Qualitative risk assessment in a data-scarce environment: a model to assess the impact of control measures on spread of African Swine Fever

In the absence of data, qualitative risk assessment frameworks have proved useful to assess risks associated with animal health diseases. As part of a scientific opinion for the European Commission (EC) on African Swine Fever (ASF), a working group of the European Food Safety Authority (EFSA) assessed the risk of ASF remaining endemic in Trans Caucasus Countries (TCC) and the Russian Federation (RF) and the risk of ASF becoming endemic in the EU if disease were introduced. The aim was to develop a tool to evaluate how current control or preventive measures mitigate the risk of spread and giving decision makers the means to review how strengthening of surveillance and control measures would mitigate the risk of disease spread. Based on a generic model outlining disease introduction, spread and endemicity in a region, the impact of risk mitigation measures on spread of disease was assessed for specific risk questions. The resulting hierarchical models consisted of key steps containing several sub-steps. For each step of the risk pathways risk estimates were determined by the expert group based on existing data or through expert opinion elicitation. Risk estimates were combined using two different combination matrices, one to combine estimates of independent steps and one to combine conditional probabilities. The qualitative risk assessment indicated a moderate risk that ASF will remain endemic in current affected areas in the TCC and RF and a high risk of spread to currently unaffected areas. If introduced into the EU, ASF is likely to be controlled effectively in the production sector with high or limited biosecurity. In the free range production sector, however, there is a moderate risk of ASF becoming endemic due to wild boar contact, non-compliance with animal movement bans, and difficult access to all individual pigs upon implementation of control measures. This study demonstrated the advantages of a systematic framework to assist an expert panel to carry out a risk assessment as it helped experts to disassociate steps in the risk pathway and to overcome preconceived notions of final risk estimates. The approach presented here shows how a qualitative risk assessment framework can address animal diseases with complexity in their spread and control measures and how transparency of the resulting estimates was achieved.     

Considerations for analysis of time-to-event outcomes subject to competing risks in veterinary clinical studies

In veterinary medicine, prospective clinical trials are increasingly utilized to address questions regarding effectiveness of therapies and patient prognosis. A large number of these trials involve time-to-event (TTE) endpoints, which require special methods of analysis to handle data in which not all subjects are observed to have the event of interest. Analyses and interpretation of the results can be further complicated when an endpoint of interest is not observed in some patients because they incur a competing risk, such as death from an unrelated cause. Competing risks have been the source of confusion in many epidemiologic analyses leading to the potential for misinterpretation. In this article, we review key considerations for the TTE analysis in the setting of competing risks. We briefly review standard TTE tools, namely Kaplan–Meier survival curves and Cox regression. In the setting of outcomes with competing risks, we provide guidance on the appropriate analysis techniques, such as cumulative incidence curves, to estimate the risk of an event of interest. We also describe a common pitfall of treating competing risks as censoring in Kaplan–Meier survival curve analysis, which can overestimate the event rate of interest. We describe two common regression methods that examine associated risk factors in the presence of competing risks and highlight the different research questions these methods address. This article provides an introductory overview and illustrates concepts with examples from veterinary trials and with example data sets.     

Reliable computing in estimation of variance components

The purpose of this study is to present guidelines in selection of statistical and computing algorithms for variance components estimation when computing involves software packages. For this purpose two major methods are to be considered: residual maximal likelihood (REML) and Bayesian via Gibbs sampling. Expectation‐Maximization (EM) REML is regarded as a very stable algorithm that is able to converge when covariance matrices are close to singular, however it is slow. However, convergence problems can occur with random regression models, especially if the starting values are much lower than those at convergence. Average Information (AI) REML is much faster for common problems but it relies on heuristics for convergence, and it may be very slow or even diverge for complex models. REML algorithms for general models become unstable with larger number of traits. REML by canonical transformation is stable in such cases but can support only a limited class of models. In general, REML algorithms are difficult to program. Bayesian methods via Gibbs sampling are much easier to program than REML, especially for complex models, and they can support much larger datasets; however, the termination criterion can be hard to determine, and the quality of estimates depends on a number of details. Computing speed varies with computing optimizations, with which some large data sets and complex models can be supported in a reasonable time; however, optimizations increase complexity of programming and restrict the types of models applicable. Several examples from past research are discussed to illustrate the fact that different problems required different methods.     

Board-invited review: Using behavior to predict and identify ill health in animals

We review recent research in one of the oldest and most important applications of ethology: evaluating animal health. Traditionally, such evaluations have been based on subjective assessments of debilitative signs; animals are judged ill when they appear depressed or off feed. Such assessments are prone to error but can be dramatically improved with training using well-defined clinical criteria. The availability of new technology to automatically record behaviors allows for increased use of objective measures; automated measures of feeding behavior and intake are increasingly available in commercial agriculture, and recent work has shown these to be valuable indicators of illness. Research has also identified behaviors indicative of risk of disease or injury. For example, the time spent standing on wet, concrete surfaces can be used to predict susceptibility to hoof injuries in dairy cattle, and time spent nuzzling the udder of the sow can predict the risk of crushing in piglets. One conceptual advance has been to view decreased exploration, feeding, social, sexual, and other behaviors as a coordinated response that helps afflicted individuals recover from illness. We argue that the sickness behaviors most likely to decline are those that provide longer-term fitness benefits (such as play), as animals divert resources to those functions of critical short-term value such as maintaining body temperature. We urge future research assessing the strength of motivation to express sickness behaviors, allowing for quantitative estimates of how sick an animal feels. Finally, we call for new theoretical and empirical work on behaviors that may act to signal health status, including behaviors that have evolved as honest (i.e., reliable) signals of condition for offspring-parent, inter- and intra-sexual, and predator-prey communication.     

A generalized Michaelis-Menten equation for the analysis of growth

The functional form W = (W0Kc + Wf t(c)) /(Kc + t(c)), where W is body size at age t, W0 and Wf are the zero- and infinite-time values of W, respectively, and K and c are constants, is derived. This new generalized Michaelis-Menten-type equation provides a flexible model for animal growth capable of describing sigmoidal and diminishing returns behavior. The parameters of the nonlinear model are open to biological interpretation and can be used to calculate reliable estimates of growth traits, such as maximum or average postnatal growth rates. To evaluate the new model, the derived equation and standard growth functions such as the Gompertz and Richards were used to fit 83 growth data sets of different animal species (fish, mice, hamsters, rats, guinea pigs, rabbits, cats, dogs, broilers, turkeys, sheep, goats, pigs, horses, and cattle) with a large range in body size. A comparative study was carried out based on mathematical, statistical, and biological characteristics of the models. The statistical goodness-of-fit achieved with the new model was similar to that of Richards, and both were slightly superior to the Gompertz. The new model differed from the others with respect to some of the estimated growth traits, but there were highly significant correlation coefficients between estimates obtained with the different models, and the ranking of animals based on growth parameters computed with the new function agreed with the rankings computed by the other models. Therefore, the new model, with its variable inflection point, was able to adequately describe growth in a wide variety of animals, to fit a range of data showing sigmoidal growth patterns, and to provide satisfactory estimates of traits for quantifying the growth characteristics of each type of animal.     

Performance promoters in animal nutrition. I. Quantitative factorial analysis of effectiveness

The nutritional efficacy of antibacterial feed additives in improving animal performance and reducing production costs has been studied extensively for over thirty years. Responses vary greatly with time and place and quantitative estimates thereof are required, with appropriate confidence limits for different circumstances, to assist efficient practical application of such performance promoters in animal production. Modern computers have facilitated multi-factorial analysis of dose-response relationships and the elucidation of the influence of diverse other determinants, such as level of animal performance and duration of supplementation. The objectives, underlying principles, methodology and future prospects of comprehensive assessments, in the format of algebraic models, are reviewed and are illustrated by examples drawn from the use of copper, tylosin and bacitracin in the nutrition of pigs, broilers and laying hens.     

Evaluation of underlying risk as a source of heterogeneity in meta-analyses: a simulation study of Bayesian and frequentist implementations of three models

Evaluation of important causes of heterogeneity among study results is an important component of any meta-analysis. For factors which can be measured (e.g. population characteristics, indicators of study quality), standard methods such as meta-regression can be used for this evaluation. The underlying risk (i.e. risk of outcome in the control population) can be viewed as a summary of the effects of unmeasured population characteristics so it is a logical candidate for evaluation as a source of heterogeneity. Unfortunately, because of its relationship with the study outcome (odds ratio or relative risk), standard methods should not be used for evaluating underlying risk as a cause of heterogeneity. Three models with different sets of underlying assumptions were evaluated in a simulation study to determine how well they performed in assessing the role of underlying risk as a source of heterogeneity. All models were fit using both Bayesian and frequentist (maximum likelihood random slopes models) estimation procedures and the results compared. Two of the models produced good results (i.e. minimal evidence of bias in parameter estimates), while the third clearly produced biased estimates of some parameters. In general, the Bayesian and frequentist approaches produced similar results. In situations in which the number of studies in a meta-analysis is small ( approximately 10), the maximum likelihood (frequentist) approach was preferable. While the bias induced by heterogeneity associated with underlying risk was generally not large, use of one of the approaches described in this paper will produce better estimates of treatment effect in situations where there is substantial heterogeneity between studies. A model based on the assumption that the number of positive events in each of the treatment and control groups are binomially distributed (Model 1) is the recommended approach.     

Evaluating Livestock Grazing Use With Streambank Alteration Protocols: Challenges and Solutions

Appropriate management of livestock in riparian areas can help ensure that these ecosystems are maintained. We evaluated how one indicator of livestock grazing in riparian areas, streambank alteration, was affected by choices related to protocols and personnel used for these assessments. We found that although streambank alteration protocols were generally repeatable among observers, results were affected by factors not directly related to grazing intensity, including 1) training, 2) professional background, 3) location and intensity of measurements, and 4) the protocol used. Training reduced estimates of alteration and observer variability. Rangeland professionals had higher estimates of streambank alteration than seasonal technicians. Rapid assessments of alteration were correlated with more intensive estimates; however, the relationship was not 1∶1. Different protocols resulted in different alterations estimates when alterations at the same locations were estimated. Given the large number of monitoring programs, personnel, and methods used to assess streambank alteration, we suggest more thought be given on how to standardize monitoring efforts so results consistently reflect the true amount of alteration at a site. We also remind managers that no protocol can be implemented without some error. Managers should therefore be careful when taking action based on a single evaluation—especially when the result is near a management standard or threshold. When these concerns are addressed, indicators such as streambank alteration can help ensure management decisions maintain both sustainable allotments and landscapes.     

The effect of an oxidized dietary oil on plasma cholesterol and thyroid hormone concentrations in miniature pigs fed on a hyperlipidaemic diet

Introduction Polyunsaturated fatty acids (PUFA) are labile compounds which under the promoting effect of oxygen, high temperature or metallic catalysts undergo peroxidative damage. In the course of lipid peroxidation, several primary and secondary products such as peroxides, aldehydes, dimers or polymers are formed. Human western diets are not only generally rich in fats, but also rich in fats that have been subjected to various degrees of processing and heat treatment, particular deep fat frying. The absolute intake of lipid peroxidation products in western countries varies over a wide range, depending on the individual eating habits; however, it can be assumed that on average of the population at least 50% of the fat consumed has been heated during industrial processing of foods or preparing of meals. Therefore, the potential toxic effects of products formed from polyunsaturated fatty acids during heating or frying of fats are of particular interest for human health, particularly in the development of coronary heart disease. In literature, there is one study which reports that the development of atherosclerosis is accelerated by dietary oxidized lipids in cholesterol-fed rabbits (S trapans et al. 1996). The reason for this observation, however, is not clear. The pathogenesis of atherosclerosis is very complex. Undoubtedly, the concentration of cholesterol in plasma and in lipoproteins as well as the susceptibility of low-density lipoproteins to lipid peroxidation are major factors influencing the risk of coronary heart disease (S teinberg et al. 1989; M archioli et al. 1996). In order to clarify a potential relationship between the intake of dietary oxidized lipids and an increased risk of coronary heart disease, this study investigated the effects of feeding oxidized oils on the concentrations of lipids in plasma and lipoproteins and the susceptibility of plasma lipids to peroxidation (S taels et al. 1990; T anis et al. 1996). The concentrations of thyroid hormones in plasma were measured because they are in close relationship with the plasma cholesterol concentration. Miniature pigs that were fed a cholesterol-enriched diet were used in this study because they have been described to be an adequate model for the investigation of the lipid metabolism in humans (B arth et al. 1990). A general problem in the investigation of the effects of dietary oxidized lipids is that the administration of a diet containing highly oxidized fats reduces food intake, food efficiency and the digestibility of fatty acids (C orcos benedetti et al. 1987; Y oshida and K ajimoto 1989; B lanc et al. 1992; H ayam et al. 1993; B orsting et al. 1994; L iu and H uang 1996; H ochgraf et al. 1997). Moreover, because of strong oxidation, highly oxidized oils usually contain significantly less PUFA and tocopherols than the equivalent fresh oils (D& rsquo ; aquino et al. 1985; C orcos benedetti et al. 1987; B lanc et al. 1992; B orsting et al. 1994; H ayam et al. 1995; L iu and H uang 1995; H ochgraf et al. 1997). In order to avoid these problems a controlled feeding system was used in this study and dietary fats were equalized for their fatty acid composition and tocopherol concentrations. Studies from literature reported that dietary oxidized oils reduce tocopherol concentrations and thereby alter the fatty acid composition of tissues and increase the fragility of erythrocyte membranes in animals (C orcos B enedetti et al. 1987; Y oshida and K ajimoto 1989; B lanc et al. 1992; H ayam et al. 1993). However, as mentioned above, in most of the studies reported in literature, the concentration of vitamin E was significantly lower in diets containing oxidized oils than in control diets. In order to find out whether those effects are also observed if diets are adjusted for identical vitamin E activities, this study also measured the tocopherol concentration in plasma, the fatty acid composition of erythrocyte lipids and the osmotic fragility of erythrocytes.     

Animal models of listeriosis: a comparative review of the current state of the art and lessons learned

ABSTRACT: Listeriosis is a leading cause of hospitalization and death due to foodborne illness in the industrialized world. Animal models have played fundamental roles in elucidating the pathophysiology and immunology of listeriosis, and will almost certainly continue to be integral components of the research on listeriosis. Data derived from animal studies helped for example characterize the importance of cell-mediated immunity in controlling infection, allowed evaluation of chemotherapeutic treatments for listeriosis, and contributed to quantitative assessments of the public health risk associated with L. monocytogenes contaminated food commodities. Nonetheless, a number of pivotal questions remain unresolved, including dose-response relationships, which represent essential components of risk assessments. Newly emerging data about species-specific differences have recently raised concern about the validity of most traditional animal models of listeriosis. However, considerable uncertainty about the best choice of animal model remains. Here we review the available data on traditional and potential new animal models to summarize currently recognized strengths and limitations of each model. This knowledge is instrumental for devising future studies and for interpreting current data. We deliberately chose a historical, comparative and cross-disciplinary approach, striving to reveal clues that may help predict the ultimate value of each animal model in spite of incomplete data.     

Correct equations for comparing models in diallel analysis

SUMMARY: Correct equations are given to express the parameter estimates of four models for complete diallels as a function of the parameter estimates in the model of Eisen et al. (1983). In recent literature these equations have been partly incorrect. ZUSAMMENFASSUNG: Korrekte Gleichungen für den Vergleich von Modellen in der Diallelanalyse Für die Darstellung der Parametersch?tzwerte von vier Modellen für vollst?ndige Diallele als Funktion der Parametersch?tzwerte des Modells von Eisen et al. (1983), die in der Literatur teilweise fehlerhaft erfolgte, werden korrekte Formeln angegeben.     

Two-step versus joint analysis of Von Bertalanffy function

Animal growth has been modelled using several mathematical functions (Logistic, Von Bertalanffy, Gompertz, etc.). These functions are described by a reduced number of parameters. In some cases, these parameters are assigned a biological interpretation (adult weight, maturing rate, etc.) and so the breeding goal can be closely related to the change of performance in these parameters, with the objective of altering the shape of the growth curve. In this sense, some studies have been focused on the estimation of (co)variance components of these parameters (B rown et al. 1976; F itzbugh 1976; D e N ise and B rinks 1985; K oenen and G roen 1996). These studies are based on a two-step procedure. In the first step, a growth curve is fitted separately to the data of each individual animal, afterwards, a mixed model analysis is applied to obtain (co)variance components. In this second step the estimates of production function parameters from the previous step are taken as records. Recently, V arona et al. (1997, 1998) have described a Bayesian procedure which allows the particular parameters of any production function to be estimated jointly and the (co)variance components between them. This procedure provides a considerable advantage over Maximun Likelihood approaches to joint analysis (Z ucker et al. 1995) and makes use of all the available information. The aim of this study is to compare both procedures in a simulation scheme under the assumption of the Von Bertalanffy growth function.     

Study of the variability of the response to inbreeding for meat production in Merino sheep

Inbreeding is known to affect metric traits. Reduction of additive genetic variance, as well as phenotypic values are its most significant deleterious effects. Yet the emergence of disorders due to recessive gene action constitutes another important aspect. Despite the fact that some effect of inbreeding can be positively used in selection schemes (T oro 1993), breeders are aware of the deleterious effects and try to avoid them. This is particularly true when the selection nucleus and the related population are of small size. Several authors (H agger 1991; V errier et al. 1993; W ray and G oddard 1994) have stressed that the application of sophisticated methods of selection, particularly BLUP-based techniques (H enderson 1973) is to be reconsidered in the light of inbreeding effects. Comparisons of selection methods should therefore account for inbreeding depression (T oro and P jrez -E nciso 1990; Q uinton et al. 1992). Other authors believe that inbreeding depression is not so important, at least in the meat production industry (G ama and S mith 1993) for traits with high heritabilities. Nevertheless, the net effect of inbreeding in a selection programme will depend on the magnitude of the selection response relative to the depression due to the accumulated inbreeding. Depending on whether genetic gain and inbreeding depression compensate for each other, the level of inbreeding of the animals may need to be accounted for in the selection process (K eller et al. 1989; R oehe et al. 1993; K lieve et al. 1994; B risbane and G ibson 1995). On the other hand, the response to inbreeding is not the same for all animals. There is an important range of variation for the estimates of inbreeding depression reported in the literature (e.g. L amberson and T homas 1984). Differences in such a response with respect to identifiable sources of variation should be examined. The objective of this work was to study the relationship between the depression due to inbreeding and litter size of ewes and weights of lambs; and to identify sources of a possible differential response to inbreeding between animals coming from different genetic line, sex, or type of birth.     

The influence of supplemental alpha-galactosidase and phytase in a vegetable ration for dogs on the digestibility of organic components and phytate phosphorus

The use of dry feeds for dogs is increasing for different reasons: in comparison to wet canned feed it is easier to handle, the amount to be given is smaller and the daily cost is less. In producing a dry pellet more vegetable ingredients are used that can contain several antinutritional factors. Some of them can be eliminated by heating. Others like galactosides and phytates are heat-resistant but can be broken down by adding the appropriate enzymes. The specific enzymes are indeed not secreted by the animal itself. In farm animals, e.g. pigs, alpha-galactosidase has been introduced in order to enhance the energetic value of these alphagalactosides (Veldman et al. 1993). In companion animals this enzyme is more often indicated as an antiflatulence agent, because the main alpha-galactosides present in legume seeds (stachyose, raffinose) are known as flatulence components (Fleming 1981). These oligosaccharides do not necessarily imply an overall lower nutrient digestibility. Zuo et al. (1996) did not prove a significant difference in digestibility between conventional and low oligosaccharide soybean meal in dog rations. Others however, (Wiernusz et al. 1995) reported the highest digestibilities and the best stool quality of those rations that contained the least amount of soybean oligosaccharides. On the other hand, phytates (phospho-inositols) are known as complexing agents of several divalent cations (Fe, Mg, Zn, Ca) and are themselves considered as a phosphorus source, unavailable to monogastric animals. Phytase is the appropriate enzyme, which is not secreted by the animal itself, but, when added to the diet, can enhance the bio-availability of several minerals and trace elements (Rimbach et al. 1994) by hydrolysing the phospho-inositol molecule. The aim of the experiment, reported here, is to investigate the influence of the addition of alpha-galactosidase, phytase, or both to a nearly complete vegetable ration, consisting of a relatively high content of galactosides and phytates. The combination of both enzymes was carried out because Wenk et al. (1993) reported a possible interaction between a carbohydrase and a phytase enzyme in pigs.     

Alternative BSE risk assessment methodology for beef and beef offal imported into Japan

The Food Safety Commission (FSC) of Japan, established in July 2003, has its own initiative to conduct risk assessments on food stuffs known as "self-tasking assessment". Within this framework, the FSC decided to conduct a risk assessment of beef and beef offal imported into Japan from countries with no previous BSE reports; thus, a methodology was formed to suit to this purpose. This methodology was partly based on the previous assessments of Japanese domestic beef and beef imported from U.S.A./Canada, but some modifications were made. Other organizations' assessment methods, such as those used for BSE status assessment in live cattle by the OIE and EFSA's GBR, were also consulted. In this review, the authors introduce this alternative methodology, which reflects (1) the risk of live cattle in the assessed country including temporal risks of BSE invasion and domestic propagation, with the assessment results verified by surveillance data, and (2) the risk of beef and beef offal consisting of cumulative BSE risk by types of slaughtering and meat production processes implemented and the status of mechanically recovered meat production. Other possible influencing factors such as atypical BSE cases were also reviewed. The key characteristic of the current assessment is a combination of the time-sequential risk level of live cattle and qualitative risk level of meat production at present in an assessed country.     

How to succeed as a virus: strategies for dealing with the immune system

Viruses may be viewed as genetic information whose success depends on avoiding elimination from individual hosts, or, if this is not possible, in persisting in the population of their hosts. The immune system represents the crucial defense mechanism responsible for the elimination of viruses from individual hosts and for the establishment of immunity that prevents a recurring infection by the same virus. Herd immunity, i.e., immunity of the population against infection resulting from the immunity of a certain fraction of the individuals of the population, represents an important concept in the interaction of viruses with their hosts. Thus, if the number of susceptible hosts decreases below a critical threshold, viruses may risk extinction because they literally run out of substrate. This possibility is increased due to the viruses' low resistance to inactivation outside their hosts by physical influences, such as heat and ultraviolet radiation. Some viruses have adopted a strategy of dual host tropism, i.e., they may reside in reservoir hosts that permit them to survive for extended periods of times. Examples of such viruses are the large and taxonomically diverse group of arboviruses. Moreover, although not normally discussed under this aspect, influenza viruses can also be said to have adopted this strategy, in view of water fowl representing reservoir hosts from which complete viruses may directly cross over to mammals, as was the case with the equine Jilin (Guo et al., 1995) or, more recently, the H5 subtype of influenza virus in humans (Shortridge et al., 1998). In addition, influenza viruses of birds may be transmitted, albeit only partially, through genetic reassortment (Shu et al., 1996).     

Detection of paramyxoviruses in Magellanic penguins (Spheniscus magellanicus) on the Brazilian tropical coast

Aquatic migratory birds are a major vectors by which influenza viruses and paramyxoviruses are spread in nature. Magellanic penguins (Spheniscus magellanicus) are usually present on the southern shores of South America and can swim as far as the southern coast of Brazil in winter. In 2008, however, several Magellanic penguins were observed on the northeastern coast of Brazil. Paramyxoviruses were isolated from Magellanic penguins on the Espírito Santo state coast, approximately 4000 km from their breeding colonies, although influenza viruses were not detected. Among the paramyxoviruses, five Avulavirus isolates belonging to serotype APMV-2 and the serotype APMV-10, which was proposed by Miller et al. (2010), were identified. These results highlight the risks associated with the spread of paramyxoviruses between natural to non-natural habitats by birds exhibiting unusual migration patterns, and they document for the first time the presence of the APMV-2 and APMV-10 serotypes on penguins in Brazil. The local avifauna may become infected with these viruses through close contact between migratory and resident birds. Continued surveillance of virus incidence in these migratory populations of penguins is necessary to detect and prevent the potential risks associated with these unusual migration patterns.     

Protocol for assessing brain function in fish and the effectiveness of methods used to stun and kill them

A method for the evaluation of brain function in fish has been developed which is based on assessments of self-initiated behaviours, responses to stimulation, and reflexes. These assessments were validated in several freshwater and marine species and applied to evaluate the brain function of fish while they were anaesthetised and while they were being killed by a variety of methods. The results of these investigations were compared with published neurophysiological observations and it is concluded that some of the tests can be used to identify, with reasonable confidence, the state of awareness, and thus the capacity to experience suffering of several species of fish.     

Use of a Markov-chain Monte Carlo model to evaluate the time value of historical testing information in animal populations

Quantitative risk assessments are now required to support many regulatory decisions involving infectious diseases of animals. Current methods, however, do not consider the relative values of historical and recent data. A Markov-chain model can use specific disease characteristics to estimate the present value of disease information collected in the past. Uncertainty about the disease characteristics and variability among animals and herds can be accounted for with Monte Carlo simulation modeling. This results in a transparent method of valuing historical testing information for use in risk assessments. We constructed such a model to value historical testing information in a more-transparent and -reproducible manner. Applications for this method include trade, food safety, and domestic animal-health regulations.