Guidelines for the design and statistical analysis of experiments using laboratory animals

For ethical and economic reasons, it is important to design animal experiments well, to analyze the data correctly, and to use the minimum number of animals necessary to achieve the scientific objectives---but not so few as to miss biologically important effects or require unnecessary repetition of experiments. Investigators are urged to consult a statistician at the design stage and are reminded that no experiment should ever be started without a clear idea of how the resulting data are to be analyzed. These guidelines are provided to help biomedical research workers perform their experiments efficiently and analyze their results so that they can extract all useful information from the resulting data. Among the topics discussed are the varying purposes of experiments (e.g., exploratory vs. confirmatory); the experimental unit; the necessity of recording full experimental details (e.g., species, sex, age, microbiological status, strain and source of animals, and husbandry conditions); assigning experimental units to treatments using randomization; other aspects of the experiment (e.g., timing of measurements); using formal experimental designs (e.g., completely randomized and randomized block); estimating the size of the experiment using power and sample size calculations; screening raw data for obvious errors; using the t-test or analysis of variance for parametric analysis; and effective design of graphical data.     

Genomic sequence analysis tools: a user's guide

The wealth of information from various genome sequencing projects provides the biologist with a new perspective from which to analyze, and design experiments with, mammalian systems. The complexity of the information, however, requires new software tools, and numerous such tools are now available. Which type and which specific system is most effective depends, in part, upon how much sequence is to be analyzed and with what level of experimental support. Here we survey a number of mammalian genomic sequence analysis systems with respect to the data they provide and the ease of their use. The hope is to aid the experimental biologist in choosing the most appropriate tool for their analyses.     

The role of the statistician in the Scottish Agricultural and Biological Research Institutes

Several of the Scottish Agricultural and Biological Research Institutes carry out research on domestic animal health and welfare. Statistical services are provided by Biomathematics & Statistics Scotland, a sister research organisation. At one of these institutes, a statistician has been an integral member of the animal experiments and ethics committee for over 10 years, and each animal experiment is examined by the committee statistician as part of the review process. This paper will describe this review process, and then discuss those areas in which statistical advice has had most impact in the reduction of animal numbers. It is suggested that most benefit does not come from simple sample-size calculations, but rather from the application of the principles of good experimental design and close collaboration between the scientist and the statistician in the design and analysis of experiments. The final conclusion is that scientists welcome constructive, long-term statistical input, although budgetary issues can prove to be a barrier.     

Role of ancillary variables in the design,analysis, and interpretation of animal experiments

During the course of an experiment using animals, many variables (e.g., age, body weight at several times, food and water consumption, hematology, and clinical biochemistry) and other characteristics are often recorded in addition to the primary response variable(s) specified by the experimenter. These additional variables have an important role in the design and interpretation of the experiment. They may be formally incorporated into the design and/or analysis and thus increase precision and power. However, even if these variables are not incorporated into the primary statistical design or into the formal analysis of the experiment, they may nevertheless be used in an ancillary or exploratory way to provide valuable information about the experiment, as shown by various examples. Used in this way, ancillary variables may improve analysis and interpretation by providing an assessment of the randomization process and an approach to the identification of outliers, lead to the generation of new hypotheses, and increase generality of results or account for differences in results when compared across different experiments. Thus, appropriate use of additional variables may lead to reduction in the number of animals required to achieve the aims of the experiment and may provide additional scientific information as an extra benefit. Unfortunately, this type of information is sometimes effectively discarded because its potential value is not recognized. Guidelines for use of animals include, in addition to the obligation to follow humane procedures, the obligation to use no more animals than necessary. Ethical experimental practice thus requires that all information be properly used and reported.     

Controlling gene loss of function in newts with emphasis on lens regeneration

Here we describe a protocol for gene loss of function during regeneration in newts, specifically applied to lens regeneration. Knockdown with the use of morpholinos can be achieved both in vitro and in vivo, depending on the experimental design. These methods achieve desirable levels of gene knockdown, and thus can be compared with methods developed for use in other animals, such as zebrafish. The technology has been applied to study molecular mechanisms during the process of lens regeneration by knocking down genes at specific stages and examining their effects on other genes and lens differentiation. The protocol can take a few days or up to 20 d to complete, depending on the duration of the experiment.     

The impact of huts on physiological stress: a refinement in post-transport housing of male guineapigs (Cavia porcellus)

The ideal animal model would contribute no confounding variables in experimental science. Variables affect experimental design resulting in increased animal use or repeated studies. We demonstrated a simple refinement which may reduce the number of animals used experimentally while simultaneously improving animal welfare. The objective of this study was to determine if the presence of a hut was an impact on physiological stress levels, as determined by faecal cortisol concentration, during a routine four-day acclimatization period of newly received male Hartley-Outbred guineapigs. We hypothesized that those animals provided with huts would have decreased physiological stress compared with animals not provided with huts. We examined this effect within both paired and single-housed animals. A between-subjects one-way analysis of variance revealed that pair-housed animals with a hut had significantly lower faecal cortisol concentration than pair-housed animals without a hut and the presence and absence of a hut had no significant impact on faecal cortisol concentration in single-housed animals. These findings show that presence of a hut is beneficial in reducing physiological stress when pair housing male guineapigs and does not appear to have an impact when single housing male guineapigs. In addition, we have shown that faecal cortisol, and therefore physiological stress, is still increasing on study day 4 suggesting a longer acclimatization period is necessary. A simple refinement in housing environment and acclimatization time can both reduce the number of animals used experimentally and improve animal welfare.     

Biological systems modeling and analysis: a biomolecular technique of the twenty-first century.

It is proposed that computational systems biology should be considered a biomolecular technique of the twenty-first century, because it complements experimental biology and bioinformatics in unique ways that will eventually lead to insights and a depth of understanding not achievable without systems approaches. This article begins with a summary of traditional and novel modeling techniques. In the second part, it proposes concept map modeling as a useful link between experimental biology and biological systems modeling and analysis. Concept map modeling requires the collaboration between biologist and modeler. The biologist designs a regulated connectivity diagram of processes comprising a biological system and also provides semi-quantitative information on stimuli and measured or expected responses of the system. The modeler converts this information through methods of forward and inverse modeling into a mathematical construct that can be used for simulations and to generate and test new hypotheses. The biologist and the modeler collaboratively interpret the results and devise improved concept maps. The third part of the article describes software, BST-Box, supporting the various modeling activities.     

Computers: the best friends a human genome ever had

Mapping and sequencing the human genome will generate large amounts of data, which must be sorted, analyzed, and stored for rapid retrieval to complete this enormous task. Computers and their software programs provide the most important tool to the molecular biologist today. A discussion of current capabilities and future needs in computer hardware and software for the human genome project is the topic of this paper. The use of computer programs to generate restriction maps, manage clone libraries, manage sequence projects, and generate consensus sequences is presented. The use of computers to communicate useful information rapidly to scientific colleagues is also mentioned. The role of both GenBank and BIONET is central to the dissemination and analysis of sequence information. The capabilities of electronic communication worldwide for assisting this project is available on the BIONET National Computer Resource, using existing networks.     

Experiences with a sac-type artificial heart

A total replacement artificial heart is described having in vitro performance satisfying human requirements up to and including moderate work.The in vitro design has been modified to make its implantation into the chests of experimental animals technically feasible.The heart has been tested in vivo for up to six hours, and has been found to provide the experimental animals with adequate blood flow and pressures.Preliminary tests have shown major problems of air embolism and red blood cell hemolysis.The heart design and technique of implantation are undergoing further improvement. Performance will be more comprehensively examined with the use of larger experimental animals in order more accurately to evaluate the heart''s potential.     

Using an Hebbian Learning Rule for Multi-Class SVM Classifiers

Regarding biological visual classification, recent series of experiments have enlighten the fact that data classification can be realized in the human visual cortex with latencies of about 100-150 ms, which, considering the visual pathways latencies, is only compatible with a very specific processing architecture, described by models from Thorpe et al. Surprisingly enough, this experimental evidence is in coherence with algorithms derived from the statistical learning theory. More precisely, there is a double link: on one hand, the so-called Vapnik theory offers tools to evaluate and analyze the biological model performances and on the other hand, this model is an interesting front-end for algorithms derived from the Vapnik theory. The present contribution develops this idea, introducing a model derived from the statistical learning theory and using the biological model of Thorpe et al. We experiment its performances using a restrained sign language recognition experiment. This paper intends to be read by biologist as well as statistician, as a consequence basic material in both fields have been reviewed.     

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.     

Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

In areas such as drug development, clinical diagnosis and biotechnology research, acquiring details about the kinetic parameters of enzymes is crucial. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. We demonstrate that a Bayesian approach (the use of prior knowledge) can produce major gains quantifiable in terms of information, productivity and accuracy of each experiment. Developing the use of Bayesian Utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has enabled the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K(M) and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimises the error in the parameters estimated.     

Reduction strategies in animal research: a review of scientific approaches at the intra-experimental, supra-experimental and extra-experimental levels

When discussing animal use and considering alternatives to animals in biomedical research and testing, the number of animals required gets to the root of the matter on ethics and justification. In this paper, some reduction strategies are reviewed. Many articles and reports on reduction of animal use focus mostly on the experimental level, but other approaches are also possible. Reduction at the intraexperimental level probably offers the greatest scope for reduction, as the design and statistical analysis of individual experiments can often be improved. Supra-experimental reduction aims to reduce the number of animals by a change in the setting in which a series of experiments take place--for example, by improved education and training, reduction of breeding surpluses, critical analysis of test specifications, and re-use of animals. At the extra-experimental level, reduction is a spin-off of other developments, rather than the direct goal. Through improved research or production strategies, aimed at better quality, consistency and safety, reduction in the number of animals used can be substantial. A revised definition of reduction is proposed, which does not include the level of information needed, as in some cases reduction in the number of animals resulting in less information or data, is still acceptable.     

树鼩独立换气笼具的设计

目的设计研究一种满足于树鼩感染性疾病动物模型实验生物安全要求的独立换气专用隔离笼具。方法根据树驹的生物学特性、实验生物安全要求及有关实验动物笼具标准进行设计。结果该笼舍完全适用于感染性疾病实验树鼢的饲养和实验操作。结论该笼具能达到维护实验动物福利,保证实验动物质量,保障人身健康,保护环境的要求,对于使用树鼩开展人类重大传染病研究具有广泛的应用价值和市场前景。     

Challenge to the Specialist: Abraham Trembley's Approach to Research on the Organism--1744 and Today

We define an organismic biologist as one whose research is focusedprimarily on a single organism, or group of related organisms,and who investigates virtually the whole of nature as livedby that organism. We contrast an organismic biologist with aproblem-oriented biologist, that is one who uses an organism,or a group of organisms, in order to investigate a particularquestion. In our view, the consummate organismic biologist hasan outlook that allows her or him to conduct research on organismswith an open eye, to follow the cues offered by the organism,and to switch and learn new disciplines when the challenge tounderstanding the particular organism leads the investigatorin those directions. We provide examples of the organismic approachof Abraham Trembley working in the eighteenth century and ofthe senior author working in the twentieth century. Both focusedtheir investigations mostly on the freshwater hydra. While studyinghydra, Trembley demonstrated that: (a) complete animals canregenerate from small, cut pieces of those animals; (b) animalscan reproduce asexually by budding; (c) tissue sections fromtwo different animals of the same species can be grafted toeach other; (d) the materials oozing out of the edges of cuttissue have properties that fit the definition of protoplasmas described by Dujardin one hundred years later; (e) livingtissues can be stained, and those stained tissues can be usedin experiments; and (f) "eyeless" animals can exhibit a behavioralresponse to light. Some of the topics investigated in hydraby the senior author and his students are: (a) behavioral responsesto the peptide reduced glutathione and to tryosine; (b) mechanismof activation of the receptor to glutathione; (c) migrationof nematocytes; (d) algal-animal endosymbiosis; (e) an unusualdisulfide-linked collagen of nematocyst capsules; (f) componentsand action of nematocyst venom; (g) intracellular digestionof radioactive protein; (h) composition of and role in cellularadhesion of the mesoglea; and, (k) a developmental mutant androle of nerve cells in promoting budding. We conclude with aproposal for one way to train future organismic biologists atthe graduate and post graduate levels. This proposal grew outof our perception of the need to provide environments that nurturescientists who, by studying organisms, will find and definenew experimental systems for the next waves of biological discoveryyet to come when the specialists begin to investigate even moreintensively the interactions between cells, tissues, organisms,and communities. Specifically, we propose that on the campusesof several major universities having a broad range of graduateprograms, there be established year-round Institutes for OrganismicMarine Biology focused on the investigation of organisms notpreviously amenable to systematic experimentation. We believethat if America's biology is to remain vibrant and innovative,organismic biology should be an integral component in any longterm planning for research and training in the biological sciences.     

全球变化联网控制实验的创新性设计:以我国草地生态系统水热要素联网控制实验为例

全球变化已对陆地生态系统结构和功能产生深远影响,明确生态系统对全球变化的响应和适应机制是实现人类对生态系统服务可持续利用的前提.联网实验是理解区域乃至全球尺度生态系统结构功能对全球变化要素响应和适应的重要手段.科学的顶层设计有利于实现联网数据间融合、比对以及分析,进而支撑普适性生态学理论的发展.本文从全球变化联网控制实...     

The design and analysis of microarray experiments: applications in parasitology

Microarray experiments can generate enormous amounts of data, but large datasets are usually inherently complex, and the relevant information they contain can be difficult to extract. For the practicing biologist, we provide an overview of what we believe to be the most important issues that need to be addressed when dealing with microarray data. In a microarray experiment we are simply trying to identify which genes are the most "interesting" in terms of our experimental question, and these will usually be those that are either overexpressed or underexpressed (upregulated or downregulated) under the experimental conditions. Analysis of the data to find these genes involves first preprocessing of the raw data for quality control, including filtering of the data (e.g., detection of outlying values) followed by standardization of the data (i.e., making the data uniformly comparable throughout the dataset). This is followed by the formal quantitative analysis of the data, which will involve either statistical hypothesis testing or multivariate pattern recognition. Statistical hypothesis testing is the usual approach to "class comparison," where several experimental groups are being directly compared. The best approach to this problem is to use analysis of variance, although issues related to multiple hypothesis testing and probability estimation still need to be evaluated. Pattern recognition can involve "class prediction," for which a range of supervised multivariate techniques are available, or "class discovery," for which an even broader range of unsupervised multivariate techniques have been developed. Each technique has its own limitations, which need to be kept in mind when making a choice from among them. To put these ideas in context, we provide a detailed examination of two specific examples of the analysis of microarray data, both from parasitology, covering many of the most important points raised.     

Climbing the mountain: experimental design for the efficient optimization of stem cell bioprocessing

“To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.” – R.A. Fisher While this idea is relevant across research scales, its importance becomes critical when dealing with the inherently large, complex and expensive process of preparing material for cell-based therapies (CBTs). Effective and economically viable CBTs will depend on the establishment of optimized protocols for the production of the necessary cell types. Our ability to do this will depend in turn on the capacity to efficiently search through a multi-dimensional problem space of possible protocols in a timely and cost-effective manner. In this review we discuss approaches to, and illustrate examples of the application of statistical design of experiments to stem cell bioprocess optimization.     

Balancing animal research with animal well-being: establishment of goals and harmonization of approaches

A resource is provided for the creation of an institutional program that balances the scientific mission of an institution with the well-being of the animals used in support of the research. The concept of harmonizing scientific goals with animal well-being was first suggested in the early part of the twentieth century and later revitalized in the literature of the 1950s. Harmonization can best be achieved through the promotion of a team initiative. The team should include, at a minimum, the scientist, veterinarian, institutional animal care and use committee, and animal care staff. It is the responsibility of this animal research team to promote and balance the generation of scientifically valid data with animal well-being. The team must strive to minimize or eliminate non-protocol variables that could adversely affect the validity and repeatability of the experimental data. Good experimental design coupled with excellent communication between team members can often minimize or eliminate many variables and result in both better science and animal well-being. To ensure the scientific validity of experimental data, scientists must be aware of the complex nature of the environment in which their animals are maintained. To ensure repeatablity of an experiment, scientists must document and publish both the inanimate and social environments in which their animals are housed. Better documentation of environmental variables and their correlation with experimental results will promote critical knowledge about the relationships between an animal's environment, its well-being, and science.     

Nonviral gene transfer to skeletal, smooth, and cardiac muscle in living animals

The study of muscle physiology has undergone many changes over the past 25 years and has moved from purely physiological studies to those intimately intertwined with molecular and cell biological questions. To ask these questions, it is necessary to be able to transfer genetic reagents to cells both in culture and, ultimately, in living animals. Over the past 10 years, a number of different chemical and physical approaches have been developed to transfect living skeletal, smooth, and cardiac muscle systems with varying success and efficiency. This review provides a survey of these methods and describes some more recent developments in the field of in vivo gene transfer to these various muscle types. Both gene delivery for overexpression of desired gene products and delivery of nucleic acids for downregulation of specific genes and their products are discussed to aid the physiologist, cell biologist, and molecular biologist in their studies on whole animal biology. electroporation; liposomes; plasmids; transfection; gene expression