A computer experiment model to investigate the effects of drug dosage in animals, for use in pharmacological education and research

The ACD-IDEA database, which was originally developed by the authors in 2004, is an ongoing compilation of existing data on the in vivo doses of compounds at which various responses in certain animal species have been observed. It can provide an infrastructure for various research/educational efforts, and creates a synergy for new applications. In this paper, some of these applications are described. Specific interfaces within the database are designed for users who are not computer specialists. Users can search the database to find the answer to a query, or they can design a simple virtual animal experiment. In the second case, the interface is used to undertake a dialogue with the system, in order to test the user's knowledge regarding an experiment under consideration, and to allow the user to glean additional information on better experimental planning. The use of this virtual experimental tool should lead to savings in time, animals, materials, and monetary costs, while the effective learning outcomes of pharmacological experiments are maintained or enhanced.     

The scope for improving the design of laboratory animal experiments.

The factors which need to be taken into account in designing a 'good' experiment are reviewed. Such an experiment should be unbiased, have high precision, a wide range of applicability, it should be simple, and there should be a means of quantifying uncertainty (Cox 1958). The relative precision due to the use of randomized block designs was found to range from 96% to 543% in 5 experiments involving 30 variables. However, a survey of 78 papers published in two toxicology journals showed that such designs were hardly used. Similarly, designs in which more than one factor was varied simultaneously ('factorial designs') were only used in 9% of studies, though interactions between variables such as dose and strain of animal may be common, so that single factor experiments could be misleading. The consequences of increased within-group variability due to infection and genetic segregation were quantified using data published by G?rtner (1990). Both substantially reduced precision, but toxicologists continue to use non-isogenic laboratory animals, leading to experiments with a lower level of precision than is necessary. It is concluded that there is scope for improving the design of animal experiments, which could lead to a reduction in animal use. People using animals should be required to take formal training courses which include sessions on experimental design in order to minimize animal use and to increase experimental efficiency.     

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

ABSTRACT: BACKGROUND: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. RESULTS: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. CONCLUSIONS: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge.     

Impact of environmental enrichment in mice. 1: effect of housing conditions on body weight,organ weights and haematology in different strains

Currently, environmental enrichment is a very common means of improving animal well-being, especially for laboratory animals. Although environmental enrichment seems to be a possible way for improving the well-being of animals, the consideration of housing laboratory animals should not only focus solely on animal well-being, manpower and economics but also on the precision and accuracy of the experimental results. The purpose of the present study was to evaluate the effects of enriched cages (nest box, nesting material, climbing bar) on body weight, haematological data and final organ weights. BALB/c, C57BL/6 and A/J mice, originated from Harlan Winkelmann, were used for the experiments - 16 animals of each strain. Animals at 3 weeks of age were marked and separated randomly to enriched or non-enriched cages, in groups of four, half for each housing condition. Both cages were type III Makrolon cages, only the enriched cages contained a nest box, a wood bar for climbing and nesting material. Animals were kept in a clean animal room under specific pathogen free (SPF) conditions. Body weights were recorded every week. Blood samples were collected at 14 weeks of age (white blood cells (WBC), red blood cells (RBC), haemoglobin (HGB), and haematocrit (HCT) were analysed). At 15 weeks of age, the animals were euthanized by CO(2) in their home cages, and final body weight and organ weights (heart, liver, kidney, adrenal, spleen and uterus) were recorded immediately. Although nearly all the test variables were not affected by environmental enrichment in their mean values, the enriched group showed higher coefficients of variation in many variables, and strain differences of both housing conditions were not consistent. The influences of enrichment were shown to be strain- and test-dependent. Such effects may lead to an increase in the number of animals which is necessary or may change the experimental results, especially when a study, using enriched housing conditions, focuses on strain differences. Since the same enrichment design can result in different influences, a positive or a negative or no adverse effect, due to the strain and the variables studied, researchers need to collect more information before enrichment designs are introduced into experimental plans.     

Observed heterospecific clutch size can affect offspring investment decisions

Optimal investment in offspring is important in maximizing lifetime reproductive success. Yet, very little is known how animals gather and integrate information about environmental factors to fine tune investment. Observing the decisions and success of other individuals, particularly when those individuals initiate breeding earlier, may provide a way for animals to quickly arrive at better breeding investment decisions. Here we show, with a field experiment using artificial nests appearing similar to resident tit nests with completed clutches, that a migratory bird can use the observed high and low clutch size of a resident competing bird species to increase and decrease clutch size and egg mass, accordingly. Our results demonstrate that songbirds can discriminate between high and low quantity of heterospecific eggs, and that social information can have long-term physiological consequences affecting reproductive strategies. Such behaviour may help animals to better adapt to changing environments and lead to convergent traits with competitors.     

Ecological and evolutionary consequences of selective interspecific information use

Recent work has shown that animals frequently use social information from individuals of their own species as well as from other species; however, the ecological and evolutionary consequences of this social information use remain poorly understood. Additionally, information users may be selective in their social information use, deciding from whom and how to use information, but this has been overlooked in an interspecific context. In particular, the intentional decision to reject a behaviour observed via social information has received less attention, although recent work has indicated its presence in various taxa. Based on existing literature, we explore in which circumstances selective interspecific information use may lead to different ecological and coevolutionary outcomes between two species, such as explaining observed co-occurrences of putative competitors. The initial ecological differences and the balance between the costs of competition and the benefits of social information use potentially determine whether selection may lead to trait divergence, convergence or coevolutionary arms race between two species. We propose that selective social information use, including adoption and rejection of behaviours, may have far-reaching fitness consequences, potentially leading to community-level eco-evolutionary outcomes. We argue that these consequences of selective interspecific information use may be much more widespread than has thus far been considered.     

APPLICATION OF FUZZY SETS AND NEURAL NETWORKS IN SENSORY ANALYSIS

This paper describes an initial but fundamental attempt to lay some groundwork for a fuzzy-set-based paradigm for sensory analysis and to demonstrate how fuzzy set and neural network techniques may lead to a natural way for sensory data interpretation. Sensory scales are described as fuzzy sets, sensory attributes as fuzzy variables, and sensory responses as sample membership grades. Multi-judge responses are formulated as a fuzzy membership vector or fuzzy histogram of response, which gives an overall panel response free of the unverifiable assumptions implied in conventional approaches. Neural networks are used to provide an effective tool for modeling and analysis of sensory responses in their naturally fuzzy and complex forms. A maximum method of defuzzification is proposed to give a crisp grade of the majority opinion. Two applications in meat quality evaluation are used to demonstrate the use of the paradigm and procedure. It is hoped that this work will bring up some new ideas and generate interest in research on application of fuzzy sets and neural networks in sensory analysis.     

The potential use of mutation spectra in cancer related genes in genetic toxicology: a statement of a GUM working group

In recent years, there has been widespread interest in the relationship between carcinogenic exposure and mutation spectra in cancer-related genes. To evaluate potential benefits and/or limitations in the use of mutation spectra in genetic toxicology, a GUM working group has been established to discuss this subject. Based on methodological possibilities and limitations, the impact of mutation spectra in the interpretation of animal experiments and in the identification of etiological agents in human cancer has been considered. With respect to experimental animals, the analyses of mutation spectra within long-term rodent carcinogenicity studies may provide some additional information on the mode of action of the respective carcinogen, however, the interpretation of results should be done carefully and only in context with other toxicological data available. Regarding human exposure, the analysis of mutation spectra in p53 or ras genes supplies information on the genotoxic properties of the respective agent. Nevertheless, on the individual level, the presence or absence of defined mutations in cancer-related genes in human tumors does not permit a definite conclusion about the causative agent.     

Ultra scale-down studies of the effect of flow and impact conditions during E. coli cell processing

The ability to recover cells from a fermentation broth in an intact form can be an important criterion for determining the overall performance of a recovery and purification sequence. Disruption of the cells can lead to undesired contamination of an extracellular product with intracellular components and vice versa loss of intracellular products may occur. In particular, the value of directed location of a product in the periplasmic space of say Escherichia coli (E. coli) would be diminished by such premature non-selective cell disruption. Several options exist for cell recovery/removal; namely centrifugation, in batch or continuous configuration, filtration or membrane operations, and in selected cases expanded beds. The choice of operation is dependant on many variables including the impact on the overall process sequence. In all cases, the cells are exposed to shear stresses of varying levels and times and additionally such environments exist in ancillary operations such as pumping, pipe flow, and control valves. In this study, a small-scale device has been designed to expose cells to controlled levels of shear, time and impact in a way that seeks to mimic those effects that may occur during full-scale processes. The extent of cell breakage was found to be proportional to shear stress. An additional level of breakage occurred due to the jet impacting on the collecting surface. Here it was possible to correlate the additional breakage with the impact velocity, which is a function of the distance that the jet travels before meeting the collection surface and the initial jet velocity.     

High-resolution sequence interpretation of epeiric shelf carbonates by means of palynofacies analysis: An example from the Germanic Triassic (Lower Muschelkalk, Anisian) of East Thuringia, Germany

Summary The Steudnitz quarry (East Thuringia, Germany) exposes the entire Lower Muschelkalk (Middle Triassic, Anisian) with a thickness of 103 m. In this paper, a primarily palynofacies-based sequence-stratigraphical interpretation supported by lithological investigations is proposed. Palynofacies of the sampled carbonate rocks is dominated by land-derived phytoclasts and pollen grains. Spores are quite rare. Marine plankton reaches its maximum abundance in an interval around the ThuringianSpiriferina-bed and the Terebratel-beds. In accordance with lithological features, this interval may be interpreted as a third-order maximum-flooding zone. Two different third-order interpretations are presented and discussed. Third-order sequences and parasequence sets can be identified by use of palynofacies analysis. Furthermore, palynofacies analysis provides an additional possibility of recognizing partly eroded or originally incomplete cycles (‘missed beats’). In some cases, a resolution down to the level of parasequences is possible. High-resolution palynofacies analysis is a powerful new tool in sedimentology but should always be combined with lithofacies interpretation. It provides very useful, additional information for high-resolution sequence analysis and palaeoenvironmental interpretation. Being a rather young method, high-resolution palynofacies analysis still shows some calibration problems with classical methods. However, these should be solvable by further research.     

ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data

MOTIVATION: Datasets resulting from metabolomics or metabolic profiling experiments are becoming increasingly complex. Such datasets may contain underlying factors, such as time (time-resolved or longitudinal measurements), doses or combinations thereof. Currently used biostatistics methods do not take the structure of such complex datasets into account. However, incorporating this structure into the data analysis is important for understanding the biological information in these datasets. RESULTS: We describe ASCA, a new method that can deal with complex multivariate datasets containing an underlying experimental design, such as metabolomics datasets. It is a direct generalization of analysis of variance (ANOVA) for univariate data to the multivariate case. The method allows for easy interpretation of the variation induced by the different factors of the design. The method is illustrated with a dataset from a metabolomics experiment with time and dose factors.     

Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An "experiment" is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, while other "factorial" designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.     

Caregiving as a Cultural System: Conceptions of Filial Obligation and Parental Dependency in Urban America

Verbal reports were elicited from 70 caregivers rendering care to impaired parents. Despite great empirical variety in the caregiving context, caregivers showed a striking commonality of interpretation with respect to attitudes about parental dependency and the obligation to care for a parent. In fact, ideas about dependency and obligation covary in predictable ways. Content analysis of the verbal reports and additional ethnographic data show that the association of these two sets of ideas represents shared knowledge in a culture of caregiving. Ideas about dependency and obligation "go together," even for caregivers whose situations vary radically. While a minority of caregivers deviate from this consensus, they do not represent an alternative culture, but rather cases where the history of parent-child relations leads them to interpret dependency and obligation more variably.     

Sea turtles, lobsters, and oceanic magnetic maps

Numerous marine animals can sense the Earth's magnetic field and use it as a cue in orientation and navigation. Two distinct types of information can potentially be extracted from the Earth's field. Directional or compass information enables animals to maintain a consistent heading in a particular direction such as north or south. In contrast, positional or map information can be used by animals to assess geographic location and, in some cases, to navigate to specific target areas. Marine animals exploit magnetic positional information in at least two different ways. For hatchling loggerhead sea turtles, regional magnetic fields function as open-sea navigational markers, eliciting changes in swimming direction at crucial points in the migratory route. Older sea turtles, as well as spiny lobsters, use magnetic information in a more complex way, exploiting it as a component of a classical navigational map, which permits an assessment of position relative to specific geographic destinations. These “magnetic maps” have not yet been fully characterized. They may be organized in several fundamentally different ways, some of which bear little resemblance to human maps, and they may also be used in conjunction with unconventional navigational strategies. Unraveling the nature of magnetic maps and exploring how they are used represents one of the most exciting frontiers of behavioral and sensory biology.     

A review of carcass conformation in sheep: assessment,genetic control and development

Stud breeders, farmers and meat traders have considered carcass conformation or shape in sheep an important trait. This trait can be assessed on either carcasses or live animals for slaughter and breeding. Nevertheless, there is no single universally accepted definition of the term carcass conformation across the sheep industry. The use of the word carcass conformation in the sheep industry is further confused by the fact that different indices are used to describe a complex 3-dimensional shape, which causes variation in the interpretation of results. This review of current knowledge on carcass conformation in sheep will identify areas, which offer opportunities for research. Visual carcass conformation appears to be poorly related to meat yield and is also probably predominantly under non-genetic control and as such has little commercial relevance. Visual carcass conformation assessments appeal to farmers because they are cheap and easy to apply. In contrast, objective conformation and muscularity (another measure of conformation) require measurements, which may be complicated, difficult or costly depending on the system under consideration. However, precisely defined objective conformation and muscularity, which can be standardised and automated are desirable in breeding and carcass classification schemes. Though, muscularity is highly heritable and is positively related to meat yield, information on objective conformation, muscularity and, their relationships to meat yield and other production traits is not adequate. Furthermore, there is little information on whether objective conformation is under genetic or non-genetic control. Provision of such information would lead to the design of efficient sheep production systems.     

On models for binomial data with random numbers of trials

A binomial outcome is a count s of the number of successes out of the total number of independent trials n=s+f, where f is a count of the failures. The n are random variables not fixed by design in many studies. Joint modeling of (s, f) can provide additional insight into the science and into the probability pi of success that cannot be directly incorporated by the logistic regression model. Observations where n= 0 are excluded from the binomial analysis yet may be important to understanding how pi is influenced by covariates. Correlation between s and f may exist and be of direct interest. We propose Bayesian multivariate Poisson models for the bivariate response (s, f), correlated through random effects. We extend our models to the analysis of longitudinal and multivariate longitudinal binomial outcomes. Our methodology was motivated by two disparate examples, one from teratology and one from an HIV tertiary intervention study.     

Unsupervised feature selection under perturbations: meeting the challenges of biological data

MOTIVATION: Feature selection methods aim to reduce the complexity of data and to uncover the most relevant biological variables. In reality, information in biological datasets is often incomplete as a result of untrustworthy samples and missing values. The reliability of selection methods may therefore be questioned. METHOD: Information loss is incorporated into a perturbation scheme, testing which features are stable under it. This method is applied to data analysis by unsupervised feature filtering (UFF). The latter has been shown to be a very successful method in analysis of gene-expression data. RESULTS: We find that the UFF quality degrades smoothly with information loss. It remains successful even under substantial damage. Our method allows for selection of a best imputation method on a dataset treated by UFF. More importantly, scoring features according to their stability under information loss is shown to be correlated with biological importance in cancer studies. This scoring may lead to novel biological insights.     

Risk Assessment Modeling: Beyond Exposure and Effects

Problem formulation, risk analysis, and risk characterization are, respectively, the design, estimation, and interpretation stages of risk assessment. Models traditionally have been used to estimate exposure and effects; now opportunities are growing to use them to design and interpret risk assessments as well. This could raise the level of rigor, reproducibility, and transparency in the risk assessment process, and improve the way information and expertise gets integrated to advise risk managers. The importance of good design and interpretation to the success of risk assessment and risk management, and the role of modeling in that success, is becoming increasingly apparent, but to date models are used only to a fraction of their potential. We provide two examples of the use of models to design and interpret risk assessments. The first looks at the use of models to better characterize risks by modeling uncertainties and exposure from offsite sources, and the second to forecast future risks of a new technology. Following the examples, we discuss some important obstacles to translating new modeling opportunities into practice. These include practical limits on the abilities of organizations to assimilate new tools and methods, and conceptual limits in the way people think about models.     

The rodent estrous cycle: characterization of vaginal cytology and its utility in toxicological studies

While an evaluation of the estrous cycle in laboratory rodents can be a useful measure of the integrity of the hypothalamic-pituitary-ovarian reproductive axis, it can also serve as a way of insuring that animals exhibiting abnormal cycling patterns are disincluded from a study prior to exposure to a test compound. Assessment of vaginal cytology in regularly cycling animals also provides a means to establish a comparable endocrine milieu for animals at necropsy. The procedure for obtaining a vaginal smear is relatively non-invasive and is one to which animals can become readily accustomed. It requires few supplies, and with some experience the assessments can be easily performed in fresh, unstained smears, or in fixed, stained ones. When incorporated as an adjunct to other endpoint measures, a determination of a female's cycling status can contribute important information about the nature of a toxicant insult to the reproductive system. In doing so, it can help to integrate the data into a more comprehensive mechanistic portrait of the effect, and in terms of risk assessment, may provide some indication of a toxicant's impact on human reproductive physiology.