Isoflurane anesthesia prior to carbon dioxide euthanasia is recognized as a refinement by many guidelines. Facilities lacking access to a vaporizer can use the "drop" method, whereby liquid anesthetic is introduced into an induction chamber. Knowing the least aversive concentration of isoflurane is critical. Previous work has demonstrated that isoflurane administered with the drop method at a concentration of 5% is aversive to mice. Other work has shown that lower concentrations (1.7% to 3.7%) of isoflurane can be used to anesthetize mice with the drop method, but aversion to these concentrations has not been tested. We assessed aversion to these lower isoflurane concentrations administered with the drop method, using a conditioned place aversion (CPA) paradigm. Female C57BL/6J (OT-1) mice (n = 28) were randomly allocated to one of three isoflurane concentrations: 1.7%, 2.7%, and 3.7%. Mice were acclimated to a light-dark apparatus. Prior to and following dark (+ isoflurane) and light chamber conditioning sessions, mice underwent an initial and final preference assessment; the change in the duration spent within the dark chamber between the initial and final preference tests was used to calculate a CPA score. Aversion increased with increasing isoflurane concentration: from 1.7% to 2.7% to 3.7% isoflurane, mean ± SE CPA score decreased from 19.6 ± 20.1 s to -25.6 ± 23.2 s, to -116.9 ± 30.6 s (F1,54 = 15.4, p < 0.001). Our results suggest that, when using the drop method to administer isoflurane, concentrations between 1.7% and 2.7% can be used to minimize female mouse aversion to induction.

Animal research often involves measuring the outcomes of interest multiple times on the same animal, whether over time or for different exposures. These repeated outcomes measured on the same animal are correlated due to animal-specific characteristics. While this repeated measures data can address more complex research questions than single-outcome data, the statistical analysis must take into account the study design resulting in correlated outcomes, which violate the independence assumption of standard statistical methods (e.g. a two-sample t-test, linear regression). When standard statistical methods are incorrectly used to analyze correlated outcome data, the statistical inference (i.e. confidence intervals and p-values) will be incorrect, with some settings leading to null findings too often and others producing statistically significant findings despite no support for this in the data. Instead, researchers can leverage approaches designed specifically for correlated outcomes. In this article, we discuss common study designs that lead to correlated outcome data, motivate the intuition about the impact of improperly analyzing correlated outcomes using methods for independent data, and introduce approaches that properly leverage correlated outcome data.

The theory and practice of statistics comprises two main schools of thought: frequentist statistics and Bayesian statistics. Frequentist methods are most commonly used to analyze animal-based laboratory data, while Bayesian statistical methods have been implemented less widely and may be relatively unfamiliar to practitioners in experimental science. This paper provides a high-level overview of Bayesian statistics and how they compare with frequentist methods. Using examples in rodent toxicity research, we argue that Bayesian methods have much to offer laboratory animal researchers. We advocate for increased attention to and adoption of Bayesian methods in laboratory animal research. Bayesian statistical theory, methods, software, and education have advanced significantly in the last 30 years, making these tools more accessible than ever.

Blinding and randomisation are important methods for increasing the robustness of pre-clinical studies, as incomplete or improper implementation thereof is recognised as a source of bias. Randomisation ensures that any known and unknown covariates introducing bias are randomly distributed over the experimental groups. Thereby, differences between the experimental groups that might otherwise have contributed to false positive or -negative results are diminished. Methods for randomisation range from simple randomisation (e.g. rolling a dice) to advanced randomisation strategies involving the use of specialised software. Blinding on the other hand ensures that researchers are unaware of group allocation during the preparation, execution and acquisition and/or the analysis of the data. This minimises the risk of unintentional influences resulting in bias. Methods for blinding require strong protocols and a team approach. In this review, we outline methods for randomisation and blinding and give practical tips on how to implement them, with a focus on animal studies.

Statistically based experimental designs have been available for over a century. However, many preclinical researchers are completely unaware of these methods, and the success of experiments is usually equated only with 'p < 0.05'. By contrast, a well-thought-out experimental design strategy provides data with evidentiary and scientific value. A value-based strategy requires implementation of statistical design principles coupled with basic project management techniques. This article outlines the three phases of a value-based design strategy: proper framing of the research question, statistically based operationalisation through careful selection and structuring of appropriate inputs, and incorporation of methods that minimise bias and process variation. Appropriate study design increases study validity and the evidentiary strength of the results, reduces animal numbers, and reduces waste from noninformative experiments. Statistically based experimental design is thus a key component of the 'Reduction' pillar of the 3R (Replacement, Reduction, Refinement) principles for ethical animal research.

The normality assumption postulates that empirical data derives from a normal (Gaussian) population. It is a pillar of inferential statistics that enables the theorization of probability functions and the computation of p-values thereof. The breach of this assumption may not impose a formal mathematical constraint on the computation of inferential outputs (e.g., p-values) but may make them inoperable and possibly lead to unethical waste of laboratory animals. Various methods, including statistical tests and qualitative visual examination, can reveal incompatibility with normality and the choice of a procedure should not be trivialized. The following minireview will provide a brief overview of diagrammatical methods and statistical tests commonly employed to evaluate congruence with normality. Special attention will be given to the potential pitfalls associated with their application. Normality is an unachievable ideal that practically never accurately describes natural variables, and detrimental consequences of non-normality may be safeguarded by using large samples. Therefore, the very concept of preliminary normality testing is also, arguably provocatively, questioned.

Outbred stocks of mice are widely used in pre-clinical research as these animals possess a diversified genetic background when compared with inbred strains of mice. It is crucial to assess particular alterations in the physiological and functional profiles of laboratory animals using haematological and biochemical indicators. These values can also differ between laboratories because they are influenced by many different factors. We aimed to provide normal values and reference intervals for selected haematology and biochemistry analytes of 570 ICR mice at three different ages: 6-8 weeks, 10-14 weeks and 6-9 months. Reference values were calculated by non-parametric methods. For comparisons between sexes, the independent-sample t-test and Mann-Whitney test were employed, and analysis of variance was used for age differences. The findings of the study revealed age-related declines in haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin concentrations. Mice aged 6-9 months had statistically higher platelet counts in their blood than mice of other ages. The white blood cell count had a significant age effect and progressively decreased with age. As mice get older, the percentage of neutrophils, monocytes and basophils increases, but the percentage of lymphocytes decreases. For the biochemical values, age-related significant differences in glucose, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase and albumin concentrations were found. It was also found that creatinine concentrations were comparable across all age ranges. The values presented in the present work can be used as a reference to interpret clinical pathology data for other studies and to evaluate health status.

The development of alternative methods for monitoring cardiorespiratory function without restraint or surgical implantation is attracting growing interest for both ethical and scientific reasons. For this purpose, a new non-invasive jacketed telemetry tool consisting in a radio device maintained in a jacket worn by the animal was previously developed to improve cardiorespiratory monitoring. It allows simultaneous monitoring of cardiac activity by surface electrocardiagram, respiratory function by respiratory inductive plethysmography, and locomotor activity by accelerometry. However, this tool has only been validated under conditions of low/intermediate activity levels or in anesthetized animals. This study aimed to evaluate the feasibility of using this system in the challenging conditions of an exertion protocol. Male Wistar rats (n = 10, 8-9 weeks old) were subjected to an incremental treadmill exercise protocol including speed levels from 5 to 40 cm s-1 separated by 30-s breaks. Heart rate (HR) and minute ventilation (assessed by minute volume; MV) were continuously monitored. At the end of each running level and during the 30-s breaks, HR and MV showed a significant increase compared to resting values. They returned to the baseline within 60 min of post-exercise recovery. Overall, our results demonstrated (i) the ability of the animal to run while wearing the device and (ii) the ability of the device to reliably monitor cardiorespiratory adaptation to treadmill exercise despite significant mechanical disturbances. In conclusion, this study highlights the possibility of non-invasively monitoring cardiorespiratory functional variables that were previously unattainable under conditions of high activity in freely moving animals.