Reproducibility and replicability of rodent phenotyping in preclinical studies

Quantitative in Vivo Molecular MRI

Molecular magnetic resonance imaging (MRI) combines chemistry, chemical biology, and imaging techniques to track molecular events non-invasively. Quantitative molecular MRI aims to provide meaningful, reproducible numerical measurements of molecular processes or biochemical targets within the body. In this review, the classifications of molecular MRI probes based on their signal-generating mechanism and functionality are first described. From there, the primary considerations for in vitro characterization and in vivo validation of molecular MRI probes, including how to avoid pitfalls and biases are discussed. Then, recommendations on imaging acquisition protocols and analysis methods to establish quantitative relationships between MRI signal change induced by the probes and the molecular processes of interest are provided. Finally, several representative case studies are highlighted that incorporate these features. Quantitative molecular MRI is a multidisciplinary research area incorporating expertise in chemical biology, inorganic chemistry, molecular probes, imaging physics, drug development, pathobiology, and medicine. The purpose of this review is to provide guidance to chemists developing MR imaging probes and methods in terms of in vitro and in vivo validation to accelerate the translation of these new quantitative tools for non-invasive imaging of biological processes.

Evaluation of variation in preclinical electroencephalographic (EEG) spectral power across multiple laboratories and experiments: An EQIPD study

The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability. Experiments consisted of a Localisation phase, which aimed to identify the factors that influence between-laboratory variability, a Harmonisation phase to evaluate whether harmonisation of standardized protocols and centralised processing and data analysis reduced variance, and a Ring-Testing phase to verify the ability of the harmonised protocol to generate consistent findings. Indeed, between-laboratory variability reduced from Localisation to Harmonisation and this reduction remained during the Ring-Testing phase. Results obtained in this multicentre preclinical qEEG study also confirmed the complex nature of EEG experiments starting from the surgery and data collection through data pre-processing to data analysis that ultimately influenced the results and contributed to variance in findings across laboratories. Overall, harmonisation of protocols and centralized data analysis were crucial in reducing laboratory-to-laboratory variability. To this end, it is recommended that standardized guidelines be updated and followed for collection and analysis of preclinical EEG data.

EthoWatcher OS: improving the reproducibility and quality of categorical and morphologic/kinematic data from behavioral recordings in laboratory animals

Behavioral recordings annotated by human observers (HOs) from video recordings are a fundamental component of preclinical animal behavioral models of neurobiological diseases. These models are often criticized for their vulnerability to reproducibility issues. Here, we present the EthoWatcher-Open Source (EW-OS), with tools and procedures for the use of blind-to-condition categorical transcriptions that are simultaneous with tracking, for the assessment of HOs intra- and interobserver reliability during training and data collection, for producing video clips of samples of behavioral categories that are useful for observer training. The use of these tools can inform and optimize the performance of observers, thus favoring the reproducibility of the data obtained. Categorical and machine vision-derived outputs are presented in an open data format for increased interoperability with other applications, where behavioral categories are associated frame-by-frame with tracking, morphological and kinematic attributes of an animal's image. The center of mass (X and Y pixel coordinates), the animal's area in square millimeters, the length and width in millimeters, and the angle in degrees were recorded. It also assesses the variation in each morphological descriptor to produce kinematic descriptors. While the initial measurements are in pixels, they are later converted to millimeters using the scale calibrated by the user via the graphical user interfaces. This process enables the creation of databases suitable for machine learning processing and behavioral pharmacology studies. EW-OS is constructed for continued collaborative development, available through an open-source platform, to support initiatives toward the adoption of good scientific practices in behavioral analysis, including tools for evaluating the quality of the data that can alleviate problems associated with low reproducibility in the behavioral sciences.

A systematic assessment of robustness in CNS safety pharmacology

BACKGROUND AND PURPOSE

Irwin tests are key preclinical study elements for characterising drug-induced neurological side effects. This multicentre study aimed to assess the robustness of Irwin tests across multinational sites during three stages of protocol harmonisation. The projects were part of the Enhanced Quality in Preclinical Data framework, aiming to increase success rates in transition from preclinical testing to clinical application.

EXPERIMENTAL APPROACH

Female and male NMRI mice were assigned to one of three groups (vehicle, MK-801 0.1 and 0.3 mg kg-1). Irwin scores were assessed at baseline and multiple times following intraperitoneal injection of MK-801 using local protocols (Stage 1), shared protocols with harmonised environmental design (Stage 2) and fully harmonised Irwin scoring protocols (Stage 3).

KEY RESULTS

The analysis based on the four functional domains (motor, autonomic, sedation and excitation) revealed substantial data variability in Stages 1 and 2. Although there was still marked overall heterogeneity between sites in Stage 3 after complete harmonisation of the Irwin scoring scheme, heterogeneity was only moderate within functional domains. When comparing treatment groups versus vehicle, we found large effect sizes in the motor domain and subtle to moderate effects in the excitation-related and autonomic domains.

CONCLUSION AND IMPLICATIONS

The pronounced interlaboratory variability in Irwin datasets for the CNS-active compound MK-801 needs to be carefully considered when making decisions during drug development. While environmental and general study design had a minor impact, the study suggests that harmonisation of parameters and their scoring can limit variability and increase robustness.

Flexible Behavioral Adjustment to Frustrative Nonreward in Anticipatory Behavior, but Not in Consummatory Behavior, Requires the Dorsal Hippocampus

The hippocampus (HC) is recognized for its pivotal role in memory-related plasticity and facilitating adaptive behavioral responses to reward shifts. However, the nature of its involvement in the response to reward downshifts remains to be determined. To bridge this knowledge gap, we explored the HC's function through a series of experiments in various tasks involving reward downshifts and using several neural manipulations in rats. In Experiment 1, complete excitotoxic lesions of the HC impaired choice performance in a modified T-maze after reducing the quantity of sugar pellet rewards. In Experiment 2, chemogenetic inhibition of the dorsal HC (dHC) disrupted anticipatory behavior following a food-pellet reward reduction. Experiments 3-5 impaired HC function by using peripheral lipopolysaccharide (LPS) administration. This treatment, which induces peripheral inflammation affecting HC function, significantly increased cytokine levels in the dHC (Experiment 3) and impaired anticipatory choice behavior (Experiment 4). None of these dorsal hippocampal manipulations affected consummatory responses in animals experiencing sucrose downshifts. Accordingly, we found no evidence of increased neural activation in either the dorsal or ventral HC, as measured by c-Fos expression, after a sucrose downshift task involving consummatory suppression (Experiment 6). The results highlight the HC's pivotal role in adaptively modulating anticipatory behavior in response to a variety of situations involving frustrative nonreward, while having no effect on adjustments on consummatory behavior. The data supporting this conclusion were obtained under heterogeneous experimental conditions derived from a multi-laboratory collaboration, ensuring the robustness and high reproducibility of our findings. Spatial orientation, memory update, choice of reward signals of different values, and anticipatory versus consummatory adjustments to reward downshift are discussed as potential mechanisms that could account for the specific effects observed from HC manipulations.

Continuous locomotor activity monitoring to assess animal welfare following intracranial surgery in mice

Locomotor activity can serve as a readout to identify discomfort and pain. Therefore, monitoring locomotor activity following interventions that induce potential discomfort may serve as a reliable method for evaluating animal health, complementing conventional methods such as body weight measurement. In this study, we used the digital ventilated cage (DVC®) system for the assessment of circadian locomotor activity, in addition to body weight monitoring, following intracranial stereotaxic surgery in an Alzheimer's disease mouse model (C57BL/6J/APPswe/PSEN1dE9). Stereotaxic surgery did not affect the organization of circadian locomotor activity of both 7-8-week-old and 19-21-week-old mice. However, we observed that both young and old mice exhibited a significant decrease in activity during the dark phase. Also, our study shows that changes in locomotor activity exhibit higher sensitivity in detecting alterations indicative of animal health compared to measuring body weight. In contrast to 7-8-week-old mice, where we observed no genotypic differences in locomotor activity, 19-21-week-old APP/PS1 mice showed increased locomotor activity compared to wild-type mice. Furthermore, our analyses revealed that a subset of the 7-8-week-old mice showed increased locomotor activity during the initial peak of the dark phase. One mouse experienced sudden death early in life, possibly due to epileptic seizures. Altogether, our findings affirm continuous activity measurements as used in the DVC® as a highly valuable objective method for post-surgical welfare monitoring. Its discerning capacity not only facilitates circadian locomotor rhythm assessment but also enables the identification of individual aberrant activity patterns, possibly indicative of epileptic seizures.

ATAXIN-2 intermediate-length polyglutamine expansions elicit ALS-associated metabolic and immune phenotypes

Intermediate-length repeat expansions in ATAXIN-2 (ATXN2) are the strongest genetic risk factor for amyotrophic lateral sclerosis (ALS). At the molecular level, ATXN2 intermediate expansions enhance TDP-43 toxicity and pathology. However, whether this triggers ALS pathogenesis at the cellular and functional level remains unknown. Here, we combine patient-derived and mouse models to dissect the effects of ATXN2 intermediate expansions in an ALS background. iPSC-derived motor neurons from ATXN2-ALS patients show altered stress granules, neurite damage and abnormal electrophysiological properties compared to healthy control and other familial ALS mutations. In TDP-43Tg-ALS mice, ATXN2-Q33 causes reduced motor function, NMJ alterations, neuron degeneration and altered in vitro stress granule dynamics. Furthermore, gene expression changes related to mitochondrial function and inflammatory response are detected and confirmed at the cellular level in mice and human neuron and organoid models. Together, these results define pathogenic defects underlying ATXN2-ALS and provide a framework for future research into ATXN2-dependent pathogenesis and therapy.

Design and validation of novel flow cytometry panels to analyze a comprehensive range of peripheral immune cells in mice

The use of flow cytometry in mice is constrained by several factors, including the limited availability of mouse-specific antibodies and the need to work with small volumes of peripheral blood. This is particularly challenging for longitudinal studies, as serial blood samples should not exceed 10% of the total blood volume in mice. To address this, we have developed two novel flow cytometry panels designed to extensively analyze immune cell populations in mice during longitudinal studies, using only 50 µL of peripheral blood per panel. Additionally, a third panel has been designed to conduct a more detailed analysis of cytotoxic and inhibitory markers at the end point. These panels have been validated on a lipopolysaccharide (LPS)-induced lung inflammation model. Two experiments were conducted to 1) validate the panels' sensitivity to immune challenges (n=12) and 2) to assess intrinsic variability of measurements (n=5). In both experiments, we collected 50 µL of peripheral blood for each cytometry panel from the maxillary venous sinus. All antibodies were titrated to identify the optimal concentration that maximized the signal from the positive population while minimizing the signal from the negative population. Samples were processed within 1 hour of collection using a MACSQuant Analyzer 16 cytometer. Our results demonstrate that these immunological panels are sensitive enough to detect changes in peripheral blood after LPS induction. Moreover, our findings help determine the sample size needed based on the immune population variability. In conclusion, the panels we have designed enable a comprehensive analysis of the murine immune system with a low blood volume requirement, enabling the measure of both absolute values and relative percentages effectively. This approach provides a robust platform for longitudinal studies in mice and can be used to uncover significant insights into immune responses.

Comprehensive ethological analysis of fear expression in rats using DeepLabCut and SimBA machine learning model

Introduction

Defensive responses to threat-associated cues are commonly evaluated using conditioned freezing or suppression of operant responding. However, rats display a broad range of behaviors and shift their defensive behaviors based on immediacy of threats and context. This study aimed to systematically quantify the defensive behaviors that are triggered in response to threat-associated cues and assess whether they can accurately be identified using DeepLabCut in conjunction with SimBA.

Methods

We evaluated behavioral responses to fear using the auditory fear conditioning paradigm. Observable behaviors triggered by threat-associated cues were manually scored using Ethovision XT. Subsequently, we investigated the effects of diazepam (0, 0.3, or 1 mg/kg), administered intraperitoneally before fear memory testing, to assess its anxiolytic impact on these behaviors. We then developed a DeepLabCut + SimBA workflow for ethological analysis employing a series of machine learning models. The accuracy of behavior classifications generated by this pipeline was evaluated by comparing its output scores to the manually annotated scores.

Results

Our findings show that, besides conditioned suppression and freezing, rats exhibit heightened risk assessment behaviors, including sniffing, rearing, free-air whisking, and head scanning. We observed that diazepam dose-dependently mitigates these risk-assessment behaviors in both sexes, suggesting a good predictive validity of our readouts. With adequate amount of training data (approximately > 30,000 frames containing such behavior), DeepLabCut + SimBA workflow yields high accuracy with a reasonable transferability to classify well-represented behaviors in a different experimental condition. We also found that maintaining the same condition between training and evaluation data sets is recommended while developing DeepLabCut + SimBA workflow to achieve the highest accuracy.

Discussion

Our findings suggest that an ethological analysis can be used to assess fear learning. With the application of DeepLabCut and SimBA, this approach provides an alternative method to decode ongoing defensive behaviors in both male and female rats for further investigation of fear-related neurobiological underpinnings.

Intrauterine position effects in a mouse model of maternal immune activation

Rodent models of maternal immune activation (MIA) are increasingly used as experimental tools in preclinical research of immune-mediated neurodevelopmental disorders and mental illnesses. Using a viral-like MIA model that is based on prenatal poly(I:C) exposure in mice, we have recently identified the existence of subgroups of MIA-exposed offspring that show dissociable behavioral, transcriptional, brain network and inflammatory profiles even under conditions of genetic homogeneity and identical MIA. Here, we tested the hypothesis that the intrauterine positions of fetuses, which are known to shape individual variability in litter-bearing mammals through variations in fetal hormone exposure, may contribute to the variable outcomes of MIA in mice. MIA was induced by maternal administration of poly(I:C) on gestation day 12 in C57BL/6N mice. Determining intrauterine positions using delivery by Cesarean section (C-section), we found that MIA-exposed offspring developing between female fetuses only (0M-MIA offspring) displayed significant deficits in sociability and sensorimotor gating at adult age, whereas MIA-exposed offspring developing between one or two males in utero (1/2M-MIA offspring) did not show the same deficits. These intrauterine position effects similarly emerged in male and female offspring. Furthermore, while MIA elevated fetal brain levels of pro- and anti-inflammatory cytokines independently of the precise intrauterine position and sex of adjacent fetuses during the acute phase, fetal brain levels of TNF-α remained elevated in 0M-MIA but not 1/2M-MIA offspring until the post-acute phase in late gestation. As expected, 1/2M offspring generally showed higher testosterone levels in the fetal brain during late gestation as compared to 0M offspring, confirming the transfer of testosterone from male fetuses to adjacent male or female fetuses. Taken together, our findings identify a novel source of within-litter variability contributing to heterogeneous outcomes of short- and long-term effects in a mouse model of MIA. In broader context, our findings highlight that individual differences in fetal exposure to hormonal and inflammatory signals may be a perinatal factor that shapes risk and resilience to MIA.

Measuring the replicability of our own research

In the study of transgenic mouse models of neurodevelopmental and neurodegenerative disorders, we use batteries of tests to measure deficits in behaviour and from the results of these tests, we make inferences about the mental states of the mice that we interpret as deficits in "learning", "memory", "anxiety", "depression", etc. This paper discusses the problems of determining whether a particular transgenic mouse is a valid mouse model of disease X, the problem of background strains, and the question of whether our behavioural tests are measuring what we say they are. The problem of the reliability of results is then discussed: are they replicable between labs and can we replicate our results in our own lab? This involves the study of intra- and inter- experimenter reliability. The variables that influence replicability and the importance of conducting a complete behavioural phenotype: sensory, motor, cognitive and social emotional behaviour are discussed. Then the thorny question of failure to replicate is examined: Is it a curse or a blessing? Finally, the role of failure in research and what it tells us about our research paradigms is examined.

STPoseNet: A real-time spatiotemporal network model for robust mouse pose estimation

Animal behavior analysis plays a crucial role in contemporary neuroscience research. However, the performance of the frame-by-frame approach may degrade in scenarios with occlusions or motion blur. In this study, we propose a spatiotemporal network model based on YOLOv8 to enhance the accuracy of key-point detection in mouse behavioral experimental videos. This model integrates a time-domain tracking strategy comprising two components: the first part utilizes key-point detection results from the previous frame to detect potential target locations in the subsequent frame; the second part employs Kalman filtering to analyze key-point changes prior to detection, allowing for the estimation of missing key-points. In the comparison of pose estimation results between our approach, YOLOv8, DeepLabCut and SLEAP on videos of three mouse behavioral experiments, our approach demonstrated significantly superior performance. This suggests that our method offers a new and effective means of accurately tracking and estimating pose in mice through spatiotemporal processing.

A search for effective reinforcers in appetitive conditioning for adult zebrafish: Ecologically relevant unconditioned stimuli

Learning and memory related brain disorders represent a large unmet medical need. Laboratory studies with animals may model brain disorders and facilitate uncovering their mechanisms. The zebrafish has been proposed for such studies. However, numerous factors that influence performance in learning tasks have yet to be understood in zebrafish. One such factor is what motivates zebrafish. Here we introduce a novel reinforcer, an ecologically relevant unconditioned stimulus (US). We placed a photograph of gravel underneath quarter of the bottom of an experimental tank on one side and also positioned artificial plants there, the "natural" US. First, we showed that this stimulus was preferred by zebrafish. Next, we investigated whether this stimulus could serve as US for associative learning. We marked the walls of the tank on the side where the US was presented with red paper, the conditioned stimulus (CS+) we found neutral before, and we also marked the walls on the other side of the tank where no US was placed with blue paper (CS-). In addition to fish receiving this "paired" training, we also ran unpaired training with another group of zebrafish, in which the fish saw the US associated with blue and red in a random manner. After having trained the fish in this manner, we tested the performance of the paired and unpaired group of zebrafish in a memory probe trial during which no US was present, and only the CSs (blue and red walls) were shown. We found the paired group of zebrafish to show significant preference for the CS+, as they spent more time and swam closer to the red side compared to the unpaired group and compared to chance. We conclude that ecologically relevant stimuli can serve as efficient US in appetitive conditioning of zebrafish.

Optimizing environmental enrichment for Sprague Dawley rats: Exemplary insights into the liver proteome

BACKGROUND

Considering the expected increase in the elderly population and the growing emphasis on aging-related biomedical research, the demand for aged laboratory animals has surged, challenging established husbandry practices. Our objective was to establish a cost-effective method for environmental enrichment, utilizing the liver as a representative organ to assess potential metabolic changes in response to differing enrichment levels.

METHODS

We conducted a six-month study involving 24 male Sprague Dawley rats, randomly assigned to four environmental enrichment groups. Two groups were housed in standard cages, while the others were placed in modified rabbit cages. Half of the groups received weekly playtime in an activity focused rat housing unit. We evaluated hormone levels, playtime behavior, and subjective handling experience. Additionally, liver tissue proteomic analysis was performed.

RESULTS

Initial corticosterone levels and those after 3 and 6 months showed no significant differences. Yet, testosterone levels were lower in the control group by the end of the study (p = 0.007). We observed 1871 distinct proteins in liver tissue, with 77% being common across groups. In gene ontology analysis, no specific pathways were overexpressed. In semiquantitative analysis, we observed differences in proteins associated in lipid metabolism such as Apolipoprotein A-I and Acyl-CoA 6-desaturase, which were lower in the control group (p = 0.024 and p = 0.009). Rats in the intervention groups with weekly playtime displayed the least amount of reported distress during inspection or upon room entry and were less prone to accepting treats. Removing animals from their enclosure was most effortless for those in the large cage group. Over time, there was a decrease in conflicts among rats that interacted only twice weekly during playpen time.

DISCUSSION

In summary, refining husbandry practices for aging rats is both simple and budget-friendly, with no apparent adverse effects on stress levels, animal development, or relevant metabolic changes in the liver.

Three methods of behavioural testing to measure anxiety - A review

Behavioural test is very useful to assess the anxiety activity, screen new anxiolytic drugs, explore the pathogenesis of anxiety disorders. Methods of behavioural testing that reflects different aspects of anxiety emotionality simultaneously have always been a critical issue for academics. In this paper, we reviewed previous methods to use behavioural test to evaluate the anxiety activity. A single test was used to measure only one aspect of anxiety emotionality. A battery of behavioural tests could get a comprehensive information of anxiety profile. In one single trial, open field test, elevated plus maze and light/dark box are integrated to assess different types of emotional behaviours. This new paradigm is useful for evaluating multiple dimensions of behaviours simultaneously, minimizing general concerns about previous test experience and inter-test intervals between tests. It is proposed as a promising alternative to using test battery.

Beyond compliance: harmonising research and husbandry practices to improve experimental reproducibility using fish models

Reproducibility in animal research is impacted by the environment, by husbandry practices in the laboratory and by the animals' provenance. These factors, however, are often not adequately considered by researchers. A disconnect between researchers and animal care staff can result in inappropriate housing and husbandry decisions for scientific studies with those animals. This is especially the case for the research in neuro-behaviour, epigenetics, and the impact of climate change, as heritable phenotypic, behavioural or physiological changes are known to result from the animals' environmental housing, husbandry, provenance and prior experience. This can lead to greater variation (even major differences) in data outcomes among studies, driving scientific uncertainties. Herein, we illustrate some of the endpoints measured in fish studies known to be intrinsically linked to the environment and husbandry conditions and assess the significance of housing and husbandry practice decisions for research adopting these endpoints for different fish species. We highlight the different priorities and challenges faced by researchers and animal care staff and how harmonising their activities and building greater understanding of how husbandry practices affect the fish will improve reproducibility in research outcomes. We furthermore illustrate how improving engagement between stakeholders, including regulatory bodies, can better underpin fish husbandry decisions and where researchers could help to drive best husbandry practices through their own research with fish models.

Mice Recognise Mice in Neighbouring Rearing Cages and Change Their Social Behaviour

Mice are social animals that change their behaviour primarily in response to visual, olfactory, and auditory information from conspecifics. Rearing conditions such as cage size and colour are important factors influencing mouse behaviour. In recent years, transparent plastic cages have become standard breeding cages. The advantage of using a transparent cage is that the experimenter can observe the mouse from outside the cage without touching the cage. However, mice may recognise the environment outside the cage and change their behaviour. We speculated that mice housed in transparent cages might recognise mice in neighbouring cages. We used only male mice in this experiment. C57BL/6 mice were kept in transparent rearing cages with open lids, and the cage positions were maintained for 3 weeks. Subsequently, we examined how mice behaved toward cagemate mice, mice from neighbouring cages, and mice from distant cages. We compared the level of interest in mice using a social preference test. Similar to previous reports, subject mice showed a high degree of interest in unfamiliar mice from distant cages. By contrast, subject mice reacted to mice from neighbouring cages as familiar mice, similar to cagemate mice. This suggests that mice housed in transparent cages with open lids perceive the external environment and identify mice in neighbouring cages. Researchers should pay attention to the environment outside the mouse cage, especially for the social preference test.

Histological Alterations in the Internal Organs of Wistar Han Rats (Rattus norvegicus) Euthanized by Five Different Methods

Selecting a method of euthanasia is an important step in designing research studies that use animals; euthanasia methods must be humane, cause minimal pain and suffering to the animal, and preserve the tissue architecture of the organs of interest. In this study, we evaluated the histomorphology of the internal organs (lung, spleen, heart, kidney, liver, brain, and adrenal gland) of rats submitted to five different methods of euthanasia, with the goal of determining which protocol caused the least alteration of histomorphology. Twenty adult Wistar Han rats (Rattus norvegicus) were divided into 5 groups of 4 rats each (2 females and 2 males) and were euthanized by CO₂ or isoflurane inhalation, sodium thiopental or xylazine plus ketamine overdose, or decapitation. All euthanasia was performed in accordance with published guidelines and local legal require- ments. Necropsy was performed immediately after euthanasia. Specific internal organs were removed and placed in formalin and submitted for routine histologic processing. Histomorphological examination of hematoxylin and eosin-stained tissues revealed circulatory alterations in multiple organs, predominantly congestion in multiple tissues, pulmonary hemorrhage, and hepatic degeneration. The euthanasia methods that induced the most severe alterations were exposure to CO₂ and anesthetic overdose with xylazine plus ketamine or sodium thiopental. Euthanasia by overexposure to isoflurane caused less damage, and the alterations were of minimal severity. Decapitation resulted in the lowest incidence of lesions in multiple organs but due its traumatic nature, it caused the highest incidence of pulmonary hemorrhage. In selecting a method of euthanasia, factors to consider are the species of animal, the purpose of the research, and the practical ability to perform the procedure to achieve maximal animal welfare without iatrogenic changes that could compromise the outcome and reproducibility of the study.

Effects of home-cage elevation on behavioral tests in mice

BACKGROUND

Research reproducibility is a common problem in preclinical behavioral science. Mice are an important animal model for studying human behavioral disorders. Experimenters, processing methods, and rearing environments are the main causes of data variability in behavioral neuroscience. It is likely that mice adapt their behavior according to the environment outside the breeding cage. We speculated that mice housed on elevated shelves and mice housed on low shelves might have differently altered anxiety-like behavior toward heights.

PURPOSE

The purpose of this study was to investigate potential behavioral changes in mice raised at different heights for 3 weeks. Changes in behavior were examined using various experimental tests.

RESULTS

Mice housed on elevated shelves showed reduced anxiety-like behavior in a light/dark traffic test compared with mice housed on low shelves. There were no significant differences between the two groups in terms of activity, exploratory behavior, muscle strength, or depression-like behavior.

CONCLUSIONS

Our results indicate that different cage heights and corresponding light exposure may alter the anxiety-like behavior of mice in response to brightness. Researchers need to carefully control the cage height and light intensity experienced by the mice to produce reproducible test results.

Towards Preclinical Validation of Arbaclofen (R-baclofen) Treatment for 16p11.2 Deletion Syndrome

A microdeletion on human chromosome 16p11.2 is one of the most common copy number variants associated with autism spectrum disorder and other neurodevelopmental disabilities. Arbaclofen, a GABA(B) receptor agonist, is a component of racemic baclofen, which is FDA-approved for treating spasticity, and has been shown to alleviate behavioral phenotypes, including recognition memory deficits, in animal models of 16p11.2 deletion. Given the lack of reproducibility sometimes observed in mouse behavioral studies, we brought together a consortium of four laboratories to study the effects of arbaclofen on behavior in three different mouse lines with deletions in the mouse region syntenic to human 16p11.2 to test the robustness of these findings. Arbaclofen rescued cognitive deficits seen in two 16p11.2 deletion mouse lines in traditional recognition memory paradigms. Using an unsupervised machine-learning approach to analyze behavior, one lab found that arbaclofen also rescued differences in exploratory behavior in the open field in 16p11.2 deletion mice. Arbaclofen was not sedating and had modest off-target behavioral effects at the doses tested. Our studies show that arbaclofen consistently rescues behavioral phenotypes in 16p11.2 deletion mice, providing support for clinical trials of arbaclofen in humans with this deletion.

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).

Seminatural environments for rodent behavioral testing: a representative design improving animal welfare and enhancing replicability

The low replicability of scientific studies has become an important issue. One possible cause is low representativeness of the experimental design employed. Already in the 1950's, Egon Brunswick pointed out that experimental setups ideally should be based on a random sample of stimuli from the subjects' natural environment or at least include basic features of that environment. Only experimental designs satisfying this criterion, representative designs in Brunswikian terminology, can produce results generalizable beyond the procedure used and to situations outside the laboratory. Such external validity is crucial in preclinical drug studies, for example, and should be important for replicability in general. Popular experimental setups in rodent research on non-human animals, like the tail suspension test or the Geller-Seifter procedure, do not correspond to contexts likely to be encountered in the animals' habitat. Consequently, results obtained in this kind of procedures can be generalized neither to other procedures nor to contexts outside the laboratory. Furthermore, many traditional procedures are incompatible with current notions of animal welfare. An approximation to the natural social and physical context can be provided in the laboratory, in the form of a seminatural environment. In addition to satisfy the basic demands for a representative design, such environments offer a far higher level of animal welfare than the typical small cages. This perspective article will briefly discuss the basic principles of the generalizability of experimental results, the virtues of representative designs and the coincidence of enhanced scientific quality and animal welfare provided by this kind of design.

PyMouseTracks: Flexible Computer Vision and RFID-Based System for Multiple Mouse Tracking and Behavioral Assessment

PyMouseTracks (PMT) is a scalable and customizable computer vision and radio frequency identification (RFID)-based system for multiple rodent tracking and behavior assessment that can be set up within minutes in any user-defined arena at minimal cost. PMT is composed of the online Raspberry Pi (RPi)-based video and RFID acquisition with subsequent offline analysis tools. The system is capable of tracking up to six mice in experiments ranging from minutes to days. PMT maintained a minimum of 88% detections tracked with an overall accuracy >85% when compared with manual validation of videos containing one to four mice in a modified home-cage. As expected, chronic recording in home-cage revealed diurnal activity patterns. In open-field, it was observed that novel noncagemate mouse pairs exhibit more similarity in travel trajectory patterns than cagemate pairs over a 10-min period. Therefore, shared features within travel trajectories between animals may be a measure of sociability that has not been previously reported. Moreover, PMT can interface with open-source packages such as DeepLabCut and Traja for pose estimation and travel trajectory analysis, respectively. In combination with Traja, PMT resolved motor deficits exhibited in stroke animals. Overall, we present an affordable, open-sourced, and customizable/scalable mouse behavior recording and analysis system.

A multi-lab experimental assessment reveals that replicability can be improved by using empirical estimates of genotype-by-lab interaction

The utility of mouse and rat studies critically depends on their replicability in other laboratories. A widely advocated approach to improving replicability is through the rigorous control of predefined animal or experimental conditions, known as standardization. However, this approach limits the generalizability of the findings to only to the standardized conditions and is a potential cause rather than solution to what has been called a replicability crisis. Alternative strategies include estimating the heterogeneity of effects across laboratories, either through designs that vary testing conditions, or by direct statistical analysis of laboratory variation. We previously evaluated our statistical approach for estimating the interlaboratory replicability of a single laboratory discovery. Those results, however, were from a well-coordinated, multi-lab phenotyping study and did not extend to the more realistic setting in which laboratories are operating independently of each other. Here, we sought to test our statistical approach as a realistic prospective experiment, in mice, using 152 results from 5 independent published studies deposited in the Mouse Phenome Database (MPD). In independent replication experiments at 3 laboratories, we found that 53 of the results were replicable, so the other 99 were considered non-replicable. Of the 99 non-replicable results, 59 were statistically significant (at 0.05) in their original single-lab analysis, putting the probability that a single-lab statistical discovery was made even though it is non-replicable, at 59.6%. We then introduced the dimensionless "Genotype-by-Laboratory" (GxL) factor-the ratio between the standard deviations of the GxL interaction and the standard deviation within groups. Using the GxL factor reduced the number of single-lab statistical discoveries and alongside reduced the probability of a non-replicable result to be discovered in the single lab to 12.1%. Such reduction naturally leads to reduced power to make replicable discoveries, but this reduction was small (from 87% to 66%), indicating the small price paid for the large improvement in replicability. Tools and data needed for the above GxL adjustment are publicly available at the MPD and will become increasingly useful as the range of assays and testing conditions in this resource increases.

Hyperglycaemia, pregnancy outcomes and maternal metabolic disease risk during pregnancy and lactation in a lean gestational diabetes mouse model

Hyperglycaemia in pregnancy (HIP) is a pregnancy complication characterized by mild to moderate hyperglycaemia that negatively impacts short- and long-term health of mother and child. However, relationships between severity and timing of pregnancy hyperglycaemia and postpartum outcomes have not been systemically investigated. We investigated the impact of hyperglycaemia developing during pregnancy (gestational diabetes mellitus, GDM) or already present pre-mating (pre-gestational diabetes mellitus, PDM) on maternal health and pregnancy outcomes. GDM and PDM were induced in C57BL/6NTac mice by combined 60% high fat diet (HF) and low dose streptozotocin (STZ). Animals were screened for PDM prior to mating, and all underwent an oral glucose tolerance test on gestational day (GD)15. Tissues were collected at GD18 or at postnatal day (PN)15. Among HFSTZ-treated dams, 34% developed PDM and 66% developed GDM, characterized by impaired glucose-induced insulin release and inadequate suppression of endogenous glucose production. No increased adiposity or overt insulin resistance was observed. Furthermore, markers of non-alcoholic fatty liver disease (NAFLD) were significantly increased in PDM at GD18 and were positively correlated with basal glucose levels at GD18 in GDM dams. By PN15, NAFLD markers were also increased in GDM dams. Only PDM affected pregnancy outcomes such as litter size. Our findings indicate that GDM and PDM, resulting in disturbances of maternal glucose homeostasis, increase the risk of postpartum NAFLD development, related to the onset and severity of pregnancy hyperglycaemia. These findings signal a need for earlier monitoring of maternal glycaemia and more rigorous follow-up of maternal health after GDM and PDM pregnancy in humans. KEY POINTS: We studied the impact of high-fat diet/streptozotocin induced hyperglycaemia in pregnancy in mice and found that this impaired glucose tolerance and insulin release. Litter size and embryo survival were compromised by pre-gestational, but not by gestational, diabetes. Despite postpartum recovery from hyperglycaemia in a majority of dams, liver disease markers were further elevated by postnatal day 15. Maternal liver disease markers were associated with the severity of hyperglycaemia at gestational day 18. The association between hyperglycaemic exposure and non-alcoholic fatty liver disease signals a need for more rigorous monitoring and follow-up of maternal glycaemia and health in diabetic pregnancy in humans.

Environmental and microbial factors influence affective and cognitive behavior in C57BL/6 sub-strains

C57BL/6 mice are one of the most widely used inbred strains in biomedical research. Early separation of the breeding colony has led to the development of several sub-strains. Colony separation led to genetic variation development driving numerous phenotypic discrepancies. The reported phenotypic behavior differences between the sub-strains were, however; not consistent in the literature, suggesting the involvement of factors other than host genes. Here, we characterized the cognitive and affective behavior of C57BL/6J and C57BL/6N mice in correlation with the immune cell profile in the brain. Furthermore, faecal microbiota transfer and mice co-housing techniques were used to dissect microbial and environmental factors' contribution, respectively, to cognitive and affective behavior patterns. We first noted a unique profile of locomotor activity, immobility pattern, and spatial and non-spatial learning and memory abilities between the two sub-strains. The phenotypic behavior profile was associated with a distinct difference in the dynamics of type 2 cytokines in the meninges and brain parenchyma. Analysing the contribution of microbiome and environmental factors to the noted behavioral profile, our data indicated that while immobility pattern was genetically driven, locomotor activity and cognitive abilities were highly sensitive to alterations in the gut microbiome and environmental factors. Changes in the phenotypic behavior in response to these factors were associated with changes in immune cell profile. While microglia were highly sensitive to alteration in gut microbiome, immune cells in meninges were more resilient. Collectively, our findings demonstrated a direct impact of environmental conditions on gut microbiota which subsequently impacts the brain immune cell profile that could modulate cognitive and affective behavior. Our data further highlight the importance of characterizing the laboratory available strain/sub-strain to select the most appropriate one that fits best the study purpose.

Open-source software for automated rodent behavioral analysis

Rodent behavioral analysis is a major specialization in experimental psychology and behavioral neuroscience. Rodents display a wide range of species-specific behaviors, not only in their natural habitats but also under behavioral testing in controlled laboratory conditions. Detecting and categorizing these different kinds of behavior in a consistent way is a challenging task. Observing and analyzing rodent behaviors manually limits the reproducibility and replicability of the analyses due to potentially low inter-rater reliability. The advancement and accessibility of object tracking and pose estimation technologies led to several open-source artificial intelligence (AI) tools that utilize various algorithms for rodent behavioral analysis. These software provide high consistency compared to manual methods, and offer more flexibility than commercial systems by allowing custom-purpose modifications for specific research needs. Open-source software reviewed in this paper offer automated or semi-automated methods for detecting and categorizing rodent behaviors by using hand-coded heuristics, machine learning, or neural networks. The underlying algorithms show key differences in their internal dynamics, interfaces, user-friendliness, and the variety of their outputs. This work reviews the algorithms, capability, functionality, features and software properties of open-source behavioral analysis tools, and discusses how this emergent technology facilitates behavioral quantification in rodent research.

Effects of different handling methods on the behavior of adult zebrafish

The zebrafish is an important biomedical research organism. In most research, zebrafish are removed from their home tank and subsequently their phenotype is measured. The method of handling the fish, however, may significantly affect a variety of phenotypes. This is particularly problematic for studies of brain function that measure behavioral or neuronal responses. Nevertheless, the potential effects of handling have not been analyzed, and in fact are usually ignored. Here, we explore the effects of two usual and two rarely or never-before employed handling methods on the behavior of adult zebrafish. We exposed each fish to one of four handling methods, a between subject experimental design: (1) net chasing followed by air-suspension, (2) gentle net catching (without chasing) followed by air-suspension, (3) gentle net catching followed by being placed in a beaker (no chasing and very short air-suspension), (4) transportation in home tank and pouring the fish directly into the test tank (no chasing, netting or air-suspension). With these handling methods, the fish were placed in a test tank and their swim path was videorecorded and analyzed. Handling significantly affected swim path parameters, duration and frequency of immobility, absolute turn angle and its temporal variance and velocity, but not the distance to bottom. The behavioral effects confirmed that chasing and netting induce robust behavioral changes, and that pouring the fish from its home to its test tank is least aversive for zebrafish. We recommend using this latter method to reduce experimental error variation and increase reproducibility of results.

An exploratory approach to identify microRNAs as circulatory biomarker candidates for epilepsy-associated psychiatric comorbidities in an electrical post-status epilepticus model

Patients with epilepsy have a high risk of developing psychiatric comorbidities, and there is a particular need for early detection of these comorbidities. Here, in an exploratory, hypothesis-generating approach, we aimed to identify microRNAs as potential circulatory biomarkers for epilepsy-associated psychiatric comorbidities across different rat models of epilepsy. The identification of distress-associated biomarkers can also contribute to animal welfare assessment. MicroRNA expression profiles were analyzed in blood samples from the electrical post-status epilepticus (SE) model. Preselected microRNAs were correlated with behavioral and biochemical parameters in the electrical post-SE model, followed by quantitative real-time PCR validation in three additional well-described rat models of epilepsy. Six microRNAs (miR-376a, miR-429, miR-494, miR-697, miR-763, miR-1903) were identified showing a positive correlation with weight gain in the early post-insult phase as well as a negative correlation with social interaction, saccharin preference, and plasma BDNF. Real-time PCR validation confirmed miR-203, miR-429, and miR-712 as differentially expressed with miR-429 being upregulated across epilepsy models. While readouts from the electrical post-SE model suggest different microRNA candidates for psychiatric comorbidities, cross-model analysis argues against generalizability across models. Thus, further research is necessary to compare the predictive validity of rodent epilepsy models for detection and management of psychiatric comorbidities.

Individualized Housing Modifies the Immune–Endocrine System in CD1 Adult Male Mice

In the last years, different research groups have made considerable efforts to improve the care and use of animals in research. Mice (Mus musculus) are the most widely used animal species in research in the European Union and are sociable and hierarchical creatures. During experiments, researchers tend to individualize males, but no consideration is given to whether this social isolation causes them stress. The aim of this study was, therefore, to explore whether 4 weeks of social isolation could induce changes in different physiological parameters in adult Crl:CD1(ICR) (CD1) males, which may interfere with experimental results. Body weight, blood cells, and fecal corticosterone metabolites levels were the analyzed parameters. Blood and fecal samples were collected at weeks 1 and 4 of the experimental procedure. Four weeks of single housing produced a significant time-dependent decrease in monocytes and granulocytes. Fecal corticosterone metabolite levels were higher in single-housed mice after 1 week and then normalized after 4 weeks of isolation. Body weight, red blood cells, and platelets remained unchanged in both groups during this period. We can, therefore, conclude that social isolation affects some immune and endocrine parameters, and that this should be taken into account in the interpretation of research data.

Preclinical common data elements for general pharmacological studies (pharmacokinetic sample collection, tolerability, and drug administration). A report of the TASK3-WG1A General Pharmacology Working Group of the ILAE/AES Joint Translational Task Force

Growing concerns over rigor and reproducibility of preclinical studies, including consistency across laboratories and translation to clinical populations, have triggered efforts to harmonize methodologies. This includes the first set of preclinical common data elements (CDEs) for epilepsy research studies, as well as Case Report Forms (CRFs) for widespread use in epilepsy research. The General Pharmacology Working Group of the ILAE/AES Task Force (TASK3-WG1A) has continued in this effort by adapting and refining CDEs/CRFs to address specific study design areas as they relate to preclinical drug screening: general pharmacology, pharmacokinetics (PK) and pharmacodynamics (PD), and tolerability. This work has expanded general pharmacology studies to include dose records, PK/PD, tolerability, and elements of rigor and reproducibility. Tolerability testing CRFs included rotarod and Irwin/Functional Observation Battery (FOB) assays. The material provided in the form of CRFs can be delivered for widespread use within the epilepsy research community.

Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations

Meta-analytic techniques have been widely used to synthesize data from animal models of human diseases and conditions, but these analyses often face two statistical challenges due to complex nature of animal data (e.g., multiple effect sizes and multiple species): statistical dependency and confounding heterogeneity. These challenges can lead to unreliable and less informative evidence, which hinders the translation of findings from animal to human studies. We present a literature survey of meta-analysis using animal models (animal meta-analysis), showing that these issues are not adequately addressed in current practice. To address these challenges, we propose a meta-analytic framework based on multilevel (linear mixed-effects) models. Through conceptualization, formulations, and worked examples, we illustrate how this framework can appropriately address these issues while allowing for testing new questions. Additionally, we introduce other advanced techniques such as multivariate models, robust variance estimation, and meta-analysis of emergent effect sizes, which can deliver robust inferences and novel biological insights. We also provide a tutorial with annotated R code to demonstrate the implementation of these techniques.

Long-term consequences of reduced availability and compensatory supplementation of sialylated HMOs on cognitive capabilities

Breast milk (BM) is the optimal source of nutrition for mammals' early life. It exerts multiple benefits, including the development of cognitive capabilities and protection against several diseases like obesity and infection of the respiratory tract. However, which components of BM are involved in individual development has remained elusive. Sialylated human milk oligosaccharides (HMOs) may constitute a valid candidate, whereby they represent the principal source of sialic acid and act as building blocks for brain development. We hypothesize that the reduced availability of two HMOs, sialyl(alpha2,6)lactose (6'SL) and sialyl(alpha2,3)lactose (3'SL), may impair attention, cognitive flexibility, and memory in a preclinical model and that the exogenous supplementation of these compounds may contrast the observed deficits. We evaluated cognitive capabilities in a preclinical model exposed to maternal milk containing reduced concentrations of 6'SL and 3'SL during lactation. To modulate their concentrations, we utilized a preclinical model characterized by the absence of genes that synthesize 3'SL and 6'SL (B6.129-St3gal4 ^tm1.1Jxm and St6gal1^tm2Jxm , double genetic deletion), producing milk lacking 3'SL and 6'SL. Then, to ensure exposure to 3'SL-6'SL-poor milk in early life, we adopted a cross-fostering protocol. The outcomes assessed in adulthood were different types of memory, attention and information processing, some of which are part of executive functions. Then, in the second study, we evaluated the long-term compensatory potential of the exogenous oral supplementation of 3'SL and 6'SL during lactation. In the first study, exposure to HMO-poor milk resulted in reduced memory and attention. Specifically, it resulted in impaired working memory in the T-maze test, in reduced spatial memory in the Barnes maze, and in impaired attentional capabilities in the Attentional set-shifting task. In the second part of the study, we did not observe any difference between experimental groups. We hypothesize that the experimental procedures utilized for the exogenous supplementation may have impacted our ability to observe the cognitive read-out in vivo. This study suggests that early life dietary sialylated HMOs play a crucial role in the development of cognitive functions. Future studies are needed to clarify if an exogenous supplementation of these oligosaccharides may compensate for these affected phenotypes.

Introducing a depression-like syndrome for translational neuropsychiatry: a plea for taxonomical validity and improved comparability between humans and mice

Depressive disorders are the most burdensome psychiatric disorders worldwide. Although huge efforts have been made to advance treatment, outcomes remain unsatisfactory. Many factors contribute to this gridlock including suboptimal animal models. Especially limited study comparability and replicability due to imprecise terminology concerning depressive-like states are major problems. To overcome these issues, new approaches are needed. Here, we introduce a taxonomical concept for modelling depression in laboratory mice, which we call depression-like syndrome (DLS). It hinges on growing evidence suggesting that mice possess advanced socioemotional abilities and can display non-random symptom patterns indicative of an evolutionary conserved disorder-like phenotype. The DLS approach uses a combined heuristic method based on clinical depression criteria and the Research Domain Criteria to provide a biobehavioural reference syndrome for preclinical rodent models of depression. The DLS criteria are based on available, species-specific evidence and are as follows: (I) minimum duration of phenotype, (II) significant sociofunctional impairment, (III) core biological features, (IV) necessary depressive-like symptoms. To assess DLS presence and severity, we have designed an algorithm to ensure statistical and biological relevance of findings. The algorithm uses a minimum combined threshold for statistical significance and effect size (p value ≤ 0.05 plus moderate effect size) for each DLS criterion. Taken together, the DLS is a novel, biologically founded, and species-specific minimum threshold approach. Its long-term objective is to gradually develop into an inter-model validation standard and microframework to improve phenotyping methodology in translational research.

The Tangled Knots of Neuroscientific Experimentation

The experimental method has promoted the popularity of neuroscientific research on the human mind. In this interdisciplinary enterprise, the experimental method, with its roots in natural science and experimental psychology, is often uncritically accepted as the royal road to investigate the human mind not only by neuroscientists, but by many philosophers as well, especially those inclined to some form of naturalism. It is rarely disputed that experiments reveal actual states of nature (here: of mind and/or brain). Experimental results are used to picture the human person or subject as an illusionary construct resulting from neuronal interactions. The present paper sketches some of the limitations of neuroscientific experiments in order to demonstrate that cognitive neuroscience is far from relying on firm methodological grounds. Numerous issues still have to be solved, some of which date back to the early days of modern science. At least, to make experiments work, many theoretical presuppositions have to be accepted and decisions of relevance have to be made in the scientific process. This implies that all scientific endeavor is constituted by persons making free decisions for good reasons, despite all reductionist claims to the contrary. The fact that we as scientists have to distinguish relevant from irrelevant aspects of experimental procedures is also crucial for dealing with the current replicability crisis in the life sciences including neuroscience.

Common Aquarium Plants as an Enrichment Strategy in Zebrafish Facilities

An increasing number of laboratories utilize zebrafish as this species is now represented in practically every subfield of biology research. Environmental enrichment has been shown to improve welfare and health of a large number of species of animals studied in laboratories, kept in zoos, or used in agriculture. However, most laboratories keep zebrafish in barren tanks. Artificial and live aquatic plants have been used in a variety of contexts for aquarium fish, and they have also been suggested as a potential enrichment strategy for the zebrafish. However, no systematic studies have been conducted to investigate their beneficial effects in zebrafish husbandry and biology research. In this study, we review some of the potential benefits of using live plants, and argue that systematic analyses for proper choice and use of live plants in zebrafish husbandry are sorely needed. We provide a few examples of aquatic plant species out of the large variety produced for the aquarium hobby that could be adopted to the zebrafish laboratory setting as environmental enrichment. We speculate that once systematic analyses have been conducted, they will show benefits of this ethologically/ecologically relevant enrichment method, one of which will be healthier and less stressed fish leading to increased reproducibility of results in zebrafish research.

Systematic assessment of the replicability and generalizability of preclinical findings: Impact of protocol harmonization across laboratory sites

The influence of protocol standardization between laboratories on their replicability of preclinical results has not been addressed in a systematic way. While standardization is considered good research practice as a means to control for undesired external noise (i.e., highly variable results), some reports suggest that standardized protocols may lead to idiosyncratic results, thus undermining replicability. Through the EQIPD consortium, a multi-lab collaboration between academic and industry partners, we aimed to elucidate parameters that impact the replicability of preclinical animal studies. To this end, 3 experimental protocols were implemented across 7 laboratories. The replicability of results was determined using the distance travelled in an open field after administration of pharmacological compounds known to modulate locomotor activity (MK-801, diazepam, and clozapine) in C57BL/6 mice as a worked example. The goal was to determine whether harmonization of study protocols across laboratories improves the replicability of the results and whether replicability can be further improved by systematic variation (heterogenization) of 2 environmental factors (time of testing and light intensity during testing) within laboratories. Protocols were tested in 3 consecutive stages and differed in the extent of harmonization across laboratories and standardization within laboratories: stage 1, minimally aligned across sites (local protocol); stage 2, fully aligned across sites (harmonized protocol) with and without systematic variation (standardized and heterogenized cohort); and stage 3, fully aligned across sites (standardized protocol) with a different compound. All protocols resulted in consistent treatment effects across laboratories, which were also replicated within laboratories across the different stages. Harmonization of protocols across laboratories reduced between-lab variability substantially compared to each lab using their local protocol. In contrast, the environmental factors chosen to introduce systematic variation within laboratories did not affect the behavioral outcome. Therefore, heterogenization did not reduce between-lab variability further compared to the harmonization of the standardized protocol. Altogether, these findings demonstrate that subtle variations between lab-specific study protocols may introduce variation across independent replicate studies even after protocol harmonization and that systematic heterogenization of environmental factors may not be sufficient to account for such between-lab variation. Differences in replicability of results within and between laboratories highlight the ubiquity of study-specific variation due to between-lab variability, the importance of transparent and fine-grained reporting of methodologies and research protocols, and the importance of independent study replication.

Sources and Translational Relevance of Heterogeneity in Maternal Immune Activation Models

The epidemiological literature reporting increased risk for neurodevelopmental and psychiatric disorders after prenatal exposure to maternal immune activation (MIA) is still evolving, and so are the attempts to model this association in animals. Epidemiological studies of MIA offer the advantage of directly evaluating human populations but are often limited in their ability to uncover pathogenic mechanisms. Animal models, on the other hand, are limited in their generalizability to psychiatric disorders but have made significant strides toward discovering causal relationships and biological pathways between MIA and neurobiological phenotypes. Like in any other model system, both planned and unplanned sources of variability exist in animal models of MIA. Therefore, the design, implementation, and interpretation of MIA models warrant a careful consideration of these sources, so that appropriate strategies can be developed to handle them satisfactorily. While every research group may have its own strategy to this aim, it is essential to report the methodological details of the chosen MIA model in order to enhance the transparency and comparability of models across research laboratories. Even though it poses a challenge for attempts to compare experimental findings across laboratories, variability does not undermine the utility of MIA models for translational research. In fact, variability and heterogenous outcomes in MIA models offer unique opportunities for new discoveries and developments in this field, including the identification of disease pathways and molecular mechanisms determining susceptibility and resilience to MIA. This review summarizes the most important sources of variability in animal models of MIA and discusses how model variability can be used to investigate neurobiological and immunological factors causing phenotypic heterogeneity in offspring exposed to MIA.

The collaborative cross strains and their founders vary widely in cocaine-induced behavioral sensitization

Cocaine use and overdose deaths attributed to cocaine have increased significantly in the United States in the last 10 years. Despite the prevalence of cocaine use disorder (CUD) and the personal and societal problems it presents, there are currently no approved pharmaceutical treatments. The absence of treatment options is due, in part, to our lack of knowledge about the etiology of CUDs. There is ample evidence that genetics plays a role in increasing CUD risk but thus far, very few risk genes have been identified in human studies. Genetic studies in mice have been extremely useful for identifying genetic loci and genes, but have been limited to very few genetic backgrounds, leaving substantial phenotypic, and genetic diversity unexplored. Herein we report the measurement of cocaine-induced behavioral sensitization using a 19-day protocol that captures baseline locomotor activity, initial locomotor response to an acute exposure to cocaine and locomotor sensitization across 5 exposures to the drug. These behaviors were measured in 51 genetically diverse Collaborative Cross (CC) strains along with their inbred founder strains. The CC was generated by crossing eight genetically diverse inbred strains such that each inbred CC strain has genetic contributions from each of the founder strains. Inbred CC mice are infinitely reproducible and provide a stable, yet diverse genetic platform on which to study the genetic architecture and genetic correlations among phenotypes. We have identified significant differences in cocaine locomotor sensitivity and behavioral sensitization across the panel of CC strains and their founders. We have established relationships among cocaine sensitization behaviors and identified extreme responding strains that can be used in future studies aimed at understanding the genetic, biological, and pharmacological mechanisms that drive addiction-related behaviors. Finally, we have determined that these behaviors exhibit relatively robust heritability making them amenable to future genetic mapping studies to identify addiction risk genes and genetic pathways that can be studied as potential targets for the development of novel therapeutics.

The prevention of home-cage grid climbing affects muscle strength in mice

Experimenters and treatment methods are the major contributors to data variability in behavioral neuroscience. However, home cage characteristics are likely associated with data variability. Mice housed in breeding cages spontaneously exhibit behavioral patterns such as biting into the wire grid and climbing on the grid lid. We aimed to clarify the effect of covering the stainless steel wire grid lid in commonly used home cage with Plexiglas to prevent climbing on muscle strength in mice. Furthermore, we investigated the effects of climbing prevention on activity and anxiety-like behavior, and the impact of climbing prevention during the postnatal development period and adulthood on muscle strength. Muscle strength, anxiety-like behavior, and locomotor activity were assessed by a battery of tests (wire hang, suspension, grip strength, rotarod, elevated-plus maze, and open field tests). Mice prevented from climbing the wire grid during postnatal development displayed lower muscle strength than those able to climb. Moreover, mice prevented from climbing for 3 weeks following maturity had weakened muscles. The muscle strength was decreased with 3 weeks of climbing prevention in even 1-year-old mice. In summary, the stainless steel wire grid in the home cage contributed to the development and maintenance of muscle strength in mice.

Multivariate phenotype analysis enables genome-wide inference of mammalian gene function

The function of the majority of genes in the human and mouse genomes is unknown. Investigating and illuminating this dark genome is a major challenge for the biomedical sciences. The International Mouse Phenotyping Consortium (IMPC) is addressing this through the generation and broad-based phenotyping of a knockout (KO) mouse line for every protein-coding gene, producing a multidimensional data set that underlies a genome-wide annotation map from genes to phenotypes. Here, we develop a multivariate (MV) statistical approach and apply it to IMPC data comprising 148 phenotypes measured across 4,548 KO lines. There are 4,256 (1.4% of 302,997 observed data measurements) hits called by the univariate (UV) model analysing each phenotype separately, compared to 31,843 (10.5%) hits in the observed data results of the MV model, corresponding to an estimated 7.5-fold increase in power of the MV model relative to the UV model. One key property of the data set is its 55.0% rate of missingness, resulting from quality control filters and incomplete measurement of some KO lines. This raises the question of whether it is possible to infer perturbations at phenotype-gene pairs at which data are not available, i.e., to infer some in vivo effects using statistical analysis rather than experimentation. We demonstrate that, even at missing phenotypes, the MV model can detect perturbations with power comparable to the single-phenotype analysis, thereby filling in the complete gene-phenotype map with good sensitivity. A factor analysis of the MV model's fitted covariance structure identifies 20 clusters of phenotypes, with each cluster tending to be perturbed collectively. These factors cumulatively explain 75% of the KO-induced variation in the data and facilitate biological interpretation of perturbations. We also demonstrate that the MV approach strengthens the correspondence between IMPC phenotypes and existing gene annotation databases. Analysis of a subset of KO lines measured in replicate across multiple laboratories confirms that the MV model increases power with high replicability.

Mice in translational neuroscience: What R we doing?

Animal models play a pivotal role in translational neuroscience but recurrent problems in data collection, analyses, and interpretation, lack of biomarkers, and a tendency to over-reliance on mice have marred neuroscience progress, leading to one of the highest attrition rates in drug translation. Global initiatives to improve reproducibility and model selection are being implemented. Notwithstanding, mice are still the preferred animal species to model human brain disorders even when the translation has been shown to be limited. Non-human primates are better positioned to provide relevant translational information because of their higher brain complexity and homology to humans. Among others, lack of resources and formal training, strict legislation, and ethical issues may impede broad access to large animals. We propose that instead of increasingly restrictive legislation, more resources for training, education, husbandry, and data sharing are urgently needed. The creation of multidisciplinary teams, in which veterinarians need to play a key role, would be critical to improve translational efficiency. Furthermore, it is not usually acknowledged by researchers and regulators the value of comparative studies in lower species, that are instrumental in toxicology, target identification, and mechanistic studies. Overall, we highlight here the need for a conceptual shift in neuroscience research and policies to reach the patients.

Blueprints for measuring natural behavior

Until recently laboratory tasks for studying behavior were highly artificial, simplified, and designed without consideration for the environmental or social context. Although such an approach offers good control over behavior, it does not allow for researching either voluntary responses or individual differences. Importantly for neuroscience studies, the activity of the neural circuits involved in producing unnatural, artificial behavior is variable and hard to predict. In addition, different ensembles may be activated depending on the strategy the animal adopts to deal with the spurious problem. Thus, artificial and simplified tasks based on responses, which do not occur spontaneously entail problems with modeling behavioral impairments and underlying brain deficits. To develop valid models of human disorders we need to test spontaneous behaviors consistently engaging well-defined, evolutionarily conserved neuronal circuits. Such research focuses on behavioral patterns relevant for surviving and thriving under varying environmental conditions, which also enable high reproducibility across different testing settings.

Questionable Research Practices, Low Statistical Power, and Other Obstacles to Replicability: Why Preclinical Neuroscience Research Would Benefit from Registered Reports

Replicability, the degree to which a previous scientific finding can be repeated in a distinct set of data, has been considered an integral component of institutionalized scientific practice since its inception several hundred years ago. In the past decade, large-scale replication studies have demonstrated that replicability is far from favorable, across multiple scientific fields. Here, I evaluate this literature and describe contributing factors including the prevalence of questionable research practices (QRPs), misunderstanding of p-values, and low statistical power. I subsequently discuss how these issues manifest specifically in preclinical neuroscience research. I conclude that these problems are multifaceted and difficult to solve, relying on the actions of early and late career researchers, funding sources, academic publishers, and others. I assert that any viable solution to the problem of substandard replicability must include changing academic incentives, with adoption of registered reports being the most immediately impactful and pragmatic strategy. For animal research in particular, comprehensive reporting guidelines that document potential sources of sensitivity for experimental outcomes is an essential addition.

Human Tissue-Engineered Skeletal Muscle: A Tool for Metabolic Research

Skeletal muscle is now regarded as an endocrine organ based on its secretion of myokines and exerkines, which, in response to metabolic stimuli, regulate the crosstalk between the skeletal muscle and other metabolic organs in terms of systemic energy homeostasis. This conceptual basis of skeletal muscle as a metabolically active organ has provided insights into the potential role of physical inactivity and conditions altering muscle quality and quantity in the development of multiple metabolic disorders, including insulin resistance, obesity, and diabetes. Therefore, it is important to understand human muscle physiology more deeply in relation to the pathophysiology of metabolic diseases. Since monolayer cell lines or animal models used in conventional research differ from the pathophysiological features of the human body, there is increasing need for more physiologically relevant in vitro models of human skeletal muscle. Here, we introduce recent studies on in vitro models of human skeletal muscle generated from adult myogenic progenitors or pluripotent stem cells and summarize recent progress in the development of three-dimensional (3D) bioartificial muscle, which mimics the physiological complexity of native skeletal muscle tissue in terms of maturation and functionality. We then discuss the future of skeletal muscle 3D-organoid culture technology in the field of metabolic research for studying pathological mechanisms and developing personalized therapeutic strategies.

Automated, high-dimensional evaluation of physiological aging and resilience in outbred mice

Behavior and physiology are essential readouts in many studies but have not benefited from the high-dimensional data revolution that has transformed molecular and cellular phenotyping. To address this, we developed an approach that combines commercially available automated phenotyping hardware with a systems biology analysis pipeline to generate a high-dimensional readout of mouse behavior/physiology, as well as intuitive and health-relevant summary statistics (resilience and biological age). We used this platform to longitudinally evaluate aging in hundreds of outbred mice across an age range from 3 months to 3.4 years. In contrast to the assumption that aging can only be measured at the limits of animal ability via challenge-based tasks, we observed widespread physiological and behavioral aging starting in early life. Using network connectivity analysis, we found that organism-level resilience exhibited an accelerating decline with age that was distinct from the trajectory of individual phenotypes. We developed a method, Combined Aging and Survival Prediction of Aging Rate (CASPAR), for jointly predicting chronological age and survival time and showed that the resulting model is able to predict both variables simultaneously, a behavior that is not captured by separate age and mortality prediction models. This study provides a uniquely high-resolution view of physiological aging in mice and demonstrates that systems-level analysis of physiology provides insights not captured by individual phenotypes. The approach described here allows aging, and other processes that affect behavior and physiology, to be studied with improved throughput, resolution, and phenotypic scope.

Measuring Locomotor Activity and Behavioral Aspects of Rodents Living in the Home-Cage

Automatization and technological advances have led to a larger number of methods and systems to monitor and measure locomotor activity and more specific behavior of a wide variety of animal species in various environmental conditions in laboratory settings. In rodents, the majority of these systems require the animals to be temporarily taken away from their home-cage into separate observation cage environments which requires manual handling and consequently evokes distress for the animal and may alter behavioral responses. An automated high-throughput approach can overcome this problem. Therefore, this review describes existing automated methods and technologies which enable the measurement of locomotor activity and behavioral aspects of rodents in their most meaningful and stress-free laboratory environment: the home-cage. In line with the Directive 2010/63/EU and the 3R principles (replacement, reduction, refinement), this review furthermore assesses their suitability and potential for group-housed conditions as a refinement strategy, highlighting their current technological and practical limitations. It covers electrical capacitance technology and radio-frequency identification (RFID), which focus mainly on voluntary locomotor activity in both single and multiple rodents, respectively. Infrared beams and force plates expand the detection beyond locomotor activity toward basic behavioral traits but discover their full potential in individually housed rodents only. Despite the great premises of these approaches in terms of behavioral pattern recognition, more sophisticated methods, such as (RFID-assisted) video tracking technology need to be applied to enable the automated analysis of advanced behavioral aspects of individual animals in social housing conditions.