A Non-invasive Digital Biomarker for the Detection of Rest Disturbances in the SOD1G93A Mouse Model of ALS

Big data and its impact on the 3Rs: a home cage monitoring oriented review

Undisturbed home cage recording of mouse activity and behavior has received increasing attention in recent years. In parallel, several technologies have been developed in a bid to automate data collection and interpretation. Thanks to these expanding technologies, massive datasets can be recorded and saved in the long term, providing a wealth of information concerning animal wellbeing, clinical status, baseline activity, and subsequent deviations in case of experimental interventions. Such large datasets can also serve as a long-term reservoir of scientific data that can be reanalyzed and repurposed upon need. In this review, we present how the impact of Big Data deriving from home cage monitoring (HCM) data acquisition, particularly through Digital Ventilated Cages (DVCs), can support the application of the 3Rs by enhancing Refinement, Reduction, and even Replacement of research in animals.

A systematic review of the development and application of home cage monitoring in laboratory mice and rats

BACKGROUND

Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors and valuable information may be missed when the animals are only monitored for short periods. These issues can be overcome by longitudinally monitoring mice and rats in their home cages. To shed light on the development of home cage monitoring (HCM) and the current state-of-the-art, a systematic review was carried out on 521 publications retrieved through PubMed and Web of Science.

RESULTS

Both the absolute (~ × 26) and relative (~ × 7) number of HCM-related publications increased from 1974 to 2020. There was a clear bias towards males and individually housed animals, but during the past decade (2011-2020), an increasing number of studies used both sexes and group housing. In most studies, animals were kept for short (up to 4 weeks) time periods in the HCM systems; intermediate time periods (4-12 weeks) increased in frequency in the years between 2011 and 2020. Before the 2000s, HCM techniques were predominantly applied for less than 12 h, while 24-h measurements have been more frequent since the 2000s. The systematic review demonstrated that manual monitoring is decreasing in relation to automatic techniques but still relevant. Until (and including) the 1990s, most techniques were applied manually but have been progressively replaced by automation since the 2000s. Independent of the year of publication, the main behavioral parameters measured were locomotor activity, feeding, and social behaviors; the main physiological parameters were heart rate and electrocardiography. External appearance-related parameters were rarely examined in the home cages. Due to technological progress and application of artificial intelligence, more refined and detailed behavioral parameters have been investigated in the home cage more recently.

CONCLUSIONS

Over the period covered in this study, techniques for HCM of mice and rats have improved considerably. This development is ongoing and further progress as well as validation of HCM systems will extend the applications to allow for continuous, longitudinal, non-invasive monitoring of an increasing range of parameters in group-housed small rodents in their home cages.

Activity in Group-Housed Home Cages of Mice as a Novel Preclinical Biomarker in Oncology Studies

BACKGROUND

Improving experimental conditions in preclinical animal research is a major challenge, both scientifically and ethically. Automated digital ventilated cages (DVC®) offer the advantage of continuous monitoring of animal activity in their home-cage. The potential utility of this technology remains understudied and deserves investigation in the field of oncology.

METHODS

Using the DVC® platform, we sought to determine if the continuous assessment of locomotor activity of mice in their home cages can serve as useful digital readout in the monitoring of animals treated with the reference oncology compounds cisplatin and cyclophosphamide. SCID mice of 14 weeks of age were housed in DVC® cages in groups of four and followed with standard and digital examination before and after treatment over a 17-day total period.

RESULTS

DVC® detected statistically significant effects of cisplatin on the activity of mice in the short and long term, as well as trends for cyclophosphamide. The activity differences between the vehicle- and chemotherapy-treated groups were especially marked during the nighttime, a period when animals are most active and staff are generally not available for regular checks. Standard clinical parameters, such as body weight change and clinical assessment during the day, provided additional and complementary information.

CONCLUSION

The DVC® technology enabled the home cage monitoring of mice and non-invasive detection of animal activity disturbances. It can easily be integrated into a multimodal monitoring approach to better capture the different effects of oncology drugs on anti-tumor efficacy, toxicity, and safety and improve translation to clinical studies.

Data repurposing from digital home cage monitoring enlightens new perspectives on mouse motor behaviour and reduction principle

In this longitudinal study we compare between and within-strain variation in the home-cage spatial preference of three widely used and commercially available mice strains-C57BL/6NCrl, BALB/cAnNCrl and CRL:CD1(ICR)-starting from the first hour post cage-change until the next cage-change, for three consecutive intervals, to further profile the circadian home-cage behavioural phenotypes. Cage-change can be a stressful moment in the life of laboratory mice, since animals are disturbed during the sleeping hours and must then rapidly re-adapt to a pristine environment, leading to disruptions in normal motor patterns. The novelty of this study resides in characterizing new strain-specific biological phenomena, such as activity along the cage walls and frontality, using the vast data reserves generated by previous experimental data, thus introducing the potential and exploring the applicability of data repurposing to enhance Reduction principle when running in vivo studies. Our results, entirely obtained without the use of new animals, demonstrate that also when referring to space preference within the cage, C57BL/6NCrl has a high variability in the behavioural phenotypes from pre-puberty until early adulthood compared to BALB/cAnNCrl, which is confirmed to be socially disaggregated, and CRL:CD1(ICR) which is conversely highly active and socially aggregated. Our data also suggest that a strain-oriented approach is needed when defining frequency of cage-change as well as maximum allowed animal density, which should be revised, ideally under the EU regulatory framework as well, according to the physiological peculiarities of the strains, and always avoiding the "one size fits all" approach.

Bouts of rest and physical activity in C57BL/6J mice

The objective was to exploit the raw data output from a scalable home cage (type IIL IVC) monitoring (HCM) system (DVC®), to characterize pattern of undisrupted rest and physical activity (PA) of C57BL/6J mice. The system's tracking algorithm show that mice in isolation spend 67% of the time in bouts of long rest (≥40s). Sixteen percent is physical activity (PA), split between local movements (6%) and locomotion (10%). Decomposition revealed that a day contains ˜7100 discrete bouts of short and long rest, local and locomotor movements. Mice travel ˜330m per day, mainly during the dark hours, while travelling speed is similar through the light-dark cycle. Locomotor bouts are usually <0.2m and <1% are >1m. Tracking revealed also fits of abnormal behaviour. The starting positions of the bouts showed no preference for the rear over the front of the cage floor, while there was a strong bias for the peripheral (75%) over the central floor area. The composition of bouts has a characteristic circadian pattern, however, intrusive husbandry routines increased bout fragmentation by ˜40%. Extracting electrode activations density (EAD) from the raw data yielded results close to those obtained with the tracking algorithm, with 81% of time in rest (<1 EAD s-1) and 19% in PA. Periods ≥40 s of file when no movement occurs and there is no EAD may correspond to periods of sleep (˜59% of file time). We confirm that EAD correlates closely with movement distance (rs>0.95) and the data agreed in ˜97% of the file time. Thus, albeit EAD being less informative it may serve as a proxy for PA and rest, enabling monitoring group housed mice. The data show that increasing density from one female to two males, and further to three male or female mice had the same effect size on EAD (˜2). In contrast, the EAD deviated significantly from this stepwise increase with 4 mice per cage, suggesting a crowdedness stress inducing sex specific adaptations. We conclude that informative metrics on rest and PA can be automatically extracted from the raw data flow in near-real time (< 1 hrs). As discussed, these metrics relay useful longitudinal information to those that use or care for the animals.

Discovering the digital biomarker of hepatocellular carcinoma in serum with SERS-based biosensors and intelligence vision

By its many virtues, non-biomarker-reliant molecular detection has recently shown bright prospects for cancer screening but its clinical application is hindered by the shortage of measurable criteria that are analogous to biomarkers. Here, we report a digital biomarker, as a new-concept serum biomarker, of hepatocellular carcinoma (HCC) found with SERS-based biosensors and a deep neural network "digital retina" for visualizing and explicitly defining spectral fingerprints. We validate the discovered digital biomarker (a collection of 10 characteristic peaks in the serum SERS spectra) with unsupervised clustering of spectra from an independent sample batch comprised normal individuals and HCC cases; the validation results show clustering accuracies of 95.71% and 100.00%, respectively. Furthermore, we find that the digital biomarker of HCC shares a few common peaks with three clinically applied serum biomarkers, which means it could convey essential biomolecular information similar to these biomarkers. Accordingly, we present an intelligent method for early HCC detection that leverages the digital biomarker with similar traits as biomarkers. Employing the digital biomarker, we could accurately stratify HCC, hepatitis B, and normal populations with linear classifiers, exhibiting accuracies over 92% and area under the receiver operating curve values above 0.93. It is anticipated that this non-biomarker-reliant molecular detection method will facilitate mass cancer screening.

Role of Human Mesenchymal Stem Cells and Derived Extracellular Vesicles in Reducing Sensory Neuron Hyperexcitability and Pain Behaviors in Murine Osteoarthritis

OBJECTIVE

Mesenchymal stem/stromal cells (MSCs) and MSC-derived extracellular vesicles (MSC-EVs) have been reported to alleviate pain in patients with knee osteoarthritis (OA). We undertook this study to determine whether MSCs and/or MSC-EVs reduce OA pain through influencing sensory neuron excitability in OA joints.

METHODS

We induced knee OA in adult male C57BL/6J mice through destabilization of the medial meniscus (DMM) surgery. Mice were sorted into 4 experimental groups with 9 mice per group as follows: unoperated sham, untreated DMM, DMM plus MSC treatment, and DMM plus MSC-EV treatment. Treated mice received either MSCs at week 14 postsurgery or MSC-EVs at weeks 12 and 14 postsurgery. Mouse behavior was evaluated by digging and rotarod tests and the Digital Ventilated Cage system. At week 16, mouse knee joints were harvested for histology, and dorsal root ganglion (DRG) neurons were isolated for electrophysiology. Furthermore, we induced hyperexcitability in DRG neurons in vitro using nerve growth factor (NGF) then treated these neurons with or without MSC-EVs and evaluated neuron excitability.

RESULTS

MSC- and MSC-EV-treated DMM-operated mice did not display pain-related behavior changes (in locomotion, digging, and sleep) that occurred in untreated DMM-operated mice. The absence of pain-related behaviors in MSC- and MSC-EV-treated mice was not the result of reduced joint damage but rather a lack of knee-innervating sensory neuron hyperexcitability that was observed in untreated DMM-operated mice. Furthermore, we found that NGF-induced sensory neuron hyperexcitability is prevented by MSC-EV treatment (P < 0.05 versus untreated NGF-sensitized neurons when comparing action potential threshold).

CONCLUSION

MSCs and MSC-EVs may reduce pain in OA by direct action on peripheral sensory neurons.

Excessive rest time during active phase is reliably detected in a mouse model of myotonic dystrophy type 1 using home cage monitoring

Myotonic dystrophy type 1 (DM1) is a dominantly inherited neuromuscular disease caused by the abnormal expansion of CTG-repeats in the 3'-untranslated region of the Dystrophia Myotonica Protein Kinase (DMPK) gene, characterized by multisystemic symptoms including muscle weakness, myotonia, cardio-respiratory problems, hypersomnia, cognitive dysfunction and behavioral abnormalities. Sleep-related disturbances are among the most reported symptoms that negatively affect the quality of life of patients and that are present in early and adult-onset forms of the disease. DMSXL mice carry a mutated human DMPK transgene containing >1,000 CTGrepeats, modeling an early onset, severe form of DM1. They exhibit a pathologic neuromuscular phenotype and also synaptic dysfunction resulting in neurological and behavioral deficits similar to those observed in patients. Additionally, they are underweight with a very high mortality within the first month after birth presenting several welfare issues. To specifically explore sleep/rest-related behaviors of this frail DM1 mouse model we used an automated home cage-based system that allows 24/7 monitoring of their activity non-invasively. We tested male and female DMSXL mice and their wild-type (WT) littermates in Digital Ventilated Cages (DVCR) assessing activity and rest parameters on day and night for 5 weeks. We demonstrated that DMSXL mice show reduced activity and regularity disruption index (RDI), higher percentage of zero activity per each hour and longer periods of rest during the active phase compared to WT. This novel rest-related phenotype in DMSXL mice, assessed unobtrusively, could be valuable to further explore mechanisms and potential therapeutic interventions to alleviate the very common symptom of excessive daytime sleepiness in DM1 patients.

Advances in Animal Models and Cutting-Edge Research in Alternatives: Proceedings of the Second International Conference on 3Rs Research and Progress, Hyderabad, 2021

The fact that animal models fail to replicate human disease faithfully is now being widely accepted by researchers across the globe. As a result, they are exploring the use of alternatives to animal models. The time has come to refine our experimental practices, reduce the numbers and eventually replace the animals used in research with human-derived and human-relevant 3-D disease models. Oncoseek Bio-Acasta Health, which is an innovative biotechnology start-up company based in Hyderabad and Vishakhapatnam, India, organises an annual International Conference on 3Rs Research and Progress. In 2021, this conference was on 'Advances in Research Animal Models and Cutting-Edge Research in Alternatives'. This annual conference is a platform that brings together eminent scientists and researchers from various parts of the world, to share recent advances from their research in the field of alternatives to animals including new approach methodologies, and to promote practices to help refine animal experiments where alternatives are not available. This report presents the proceedings of the conference, which was held in hybrid mode (i.e. virtual and in-person) in November 2021.

Emerging Role of Translational Digital Biomarkers Within Home Cage Monitoring Technologies in Preclinical Drug Discovery and Development

In drug discovery and development, traditional assessment of human patients and preclinical subjects occurs at limited time points in potentially stressful surroundings (i.e., the clinic or a test arena), which can impact data quality and welfare. However, recent advances in remote digital monitoring technologies enable the assessment of human patients and preclinical subjects across multiple time points in familiar surroundings. The ability to monitor a patient throughout disease progression provides an opportunity for more relevant and efficient diagnosis as well as improved assessment of drug efficacy and safety. In preclinical in vivo animal models, these digital technologies allow for continuous, longitudinal, and non-invasive monitoring in the home environment. This manuscript provides an overview of digital monitoring technologies for use in preclinical studies including their history and evolution, current engagement through use cases, and impact of digital biomarkers (DBs) on drug discovery and the 3Rs. We also discuss barriers to implementation and strategies to overcome them. Finally, we address data consistency and technology standards from the perspective of technology providers, end-users, and subject matter experts. Overall, this review establishes an improved understanding of the value and implementation of digital biomarker (DB) technologies in preclinical research.

Effects of Cage Position and Light Transmission on Home Cage Activity and Circadian Entrainment in Mice

Light is known to exert powerful effects on behavior and physiology, including upon the amount and distribution of activity across the day/night cycle. Here we use home cage activity monitoring to measure the effect of differences in home cage light spectrum and intensity on key circadian activity parameters in mice. Due to the relative positioning of any individually ventilated cage (IVC) with regard to the animal facility lighting, notable differences in light intensity occur across the IVC rack. Although all mice were found to be entrained, significant differences in the timing of activity onset and differences in activity levels were found between mice housed in standard versus red filtering cages. Furthermore, by calculating the effective irradiance based upon the known mouse photopigments, a significant relationship between light intensity and key circadian parameters are shown. Perhaps unsurprisingly given the important role of the circadian photopigment melanopsin in circadian entrainment, melanopic illuminance is shown to correlate more strongly with key circadian activity parameters than photopic lux. Collectively, our results suggest that differences in light intensity may reflect an uncharacterized source of variation in laboratory rodent research, with potential consequences for reproducibility. Room design and layout vary within and between facilities, and caging design and lighting location relative to cage position can be highly variable. We suggest that cage position should be factored into experimental design, and wherever possible, experimental lighting conditions should be characterized as a way of accounting for this source of variation.

Automated Home-Cage Monitoring During Acute Experimental Colitis in Mice

For ethical and legal reasons it is necessary to assess the severity of procedures in animal experimentation. To estimate the degree of pain, suffering, distress or lasting harm, objective methods that provide gradebale parameters need to be tested and validated for various models. In this context, automated home-cage monitoring becomes more important as a contactless, objective, continuous and non-invasive method. The aim of this study was to examine a recently developed large scale automated home-cage monitoring system (Digital Ventilated Cage, DVC^®) with regard to the applicability and added value for severity assessment in a frequently used acute colitis mouse model. Acute colitis was induced in female C57BL/6J mice by varying doses of DSS (1.5 and 2.5%), matched controls received water only (0%). Besides DVC^® activity monitoring and nest scoring, model specific parameters like body weight, clinical colitis score, and intestinal histo-pathology were used. In a second approach, we questioned whether DVC^® can be used to detect an influence of different handling methods on the behavior of mice. Therefore, we compared activity patterns of mice that underwent tunnel vs. tail handling for routine animal care procedures. In DSS treated mice, disease specific parameters confirmed induction of a graded colitis. In line with this, DVC^® revealed reduced activity in these animals. Furthermore, the system displayed stress-related activity changes due to the restraining procedures necessary in DSS-treatment groups. However, no significant differences between tunnel vs. tail handling procedures were detected. For further analysis of the data, a binary classifier was applied to categorize two severity levels (burdened vs. not burdened) based on activity and body weight. In all DSS-treatment groups data points were allocated to the burdened level, in contrast to a handling group. The fraction of "burdened" animals reflected well the course of colitis development. In conclusion, automated home-cage monitoring by DVC^® enabled severity assessment in a DSS-induced colitis model equally well as gold standard clinical parameters. In addition, it revealed changes in activity patterns due to routine handling procedures applied in experimental model work. This indicates that large scale home-cage monitoring can be integrated into routine severity assessment in biomedical research.

Doxycycline rescues recognition memory and circadian motor rhythmicity but does not prevent terminal disease in fatal familial insomnia mice

Fatal familial insomnia (FFI) is a dominantly inherited prion disease linked to the D178N mutation in the gene encoding the prion protein (PrP). Symptoms, including insomnia, memory loss and motor abnormalities, appear around 50 years of age, leading to death within two years. No treatment is available. A ten-year clinical trial of doxycycline (doxy) is under way in healthy individuals at risk of FFI to test whether presymptomatic doxy prevents or delays the onset of disease. To assess the drug's effect in a tractable disease model, we used Tg(FFI-26) mice, which accumulate aggregated and protease-resistant PrP in their brains and develop a fatal neurological illness highly reminiscent of FFI. Mice were treated daily with 10 mg/kg doxy starting from a presymptomatic stage for twenty weeks. Doxy rescued memory deficits and restored circadian motor rhythmicity in Tg(FFI-26) mice. However, it did not prevent the onset and progression of motor dysfunction, clinical signs and progression to terminal disease. Doxy did not change the amount of aggregated and protease-resistant PrP, but reduced microglial activation in the hippocampus. Presymptomatic doxy treatment rescues cognitive impairment and the motor correlates of sleep dysfunction in Tg(FFI-26) mice but does not prevent fatal disease.

Digital Biomarkers for Neuromuscular Disorders: A Systematic Scoping Review

Biomarkers play a vital role in clinical care. They enable early diagnosis and treatment by identifying a patient's condition and disease course and act as an outcome measure that accurately evaluates the efficacy of a new treatment or drug. Due to the rapid development of digital technologies, digital biomarkers are expected to grow tremendously. In the era of change, this scoping review was conducted to see which digital biomarkers are progressing in neuromuscular disorders, a diverse and broad-range disease group among the neurological diseases, to discover available evidence for their feasibility and reliability. Thus, a total of 10 studies were examined: 9 observational studies and 1 animal study. Of the observational studies, studies were conducted with amyotrophic lateral sclerosis (ALS), Duchenne muscular dystrophy (DMD), and spinal muscular atrophy (SMA) patients. Non-peer reviewed poster presentations were not considered, as the articles may lead to erroneous results. The only animal study included in the present review investigated the mice model of ALS for detecting rest disturbances using a non-invasive digital biomarker.

Phenotyping spontaneous locomotor activity in inbred and outbred mouse strains by using Digital Ventilated Cages

Mouse strains differ markedly in all behaviors, independently of their genetic background. We undertook this study to disentangle the diurnal activity and feature key aspects of three non-genetically altered mouse strains widely used in research, C57BL/6NCrl (inbred), BALB/cAnNCrl (inbred) and CRL:CD1(ICR) (outbred). With this aim, we conducted a longitudinal analysis of the spontaneous locomotor activity of the mice during a 24-h period for 2 months, in two different periods of the year to reduce the seasonality effect. Mice (males and females) were group-housed in Digital Ventilated Cages (Tecniplast), mimicking standard housing conditions in research settings and avoiding the potential bias provided in terms of locomotor activity by single housing. The recorded locomotor activity was analyzed by relying on different and commonly used circadian metrics (i.e., day and night activity, diurnal activity, responses to lights-on and lights-off phases, acrophase and activity onset and regularity disruption index) to capture key behavioral responses for each strain. Our results clearly demonstrate significant differences in the circadian activity of the three selected strains, when comparing inbred versus outbred as well as inbred strains (C57BL/6NCrl versus BALB/cAnNCrl). Conversely, males and females of the same strain displayed similar motor phenotypes; significant differences were recorded only for C57BL/6NCrl and CRL:CD1(ICR) females, which displayed higher average locomotor activity from prepuberty to adulthood. All strain-specific differences were further confirmed by an unsupervised machine learning approach. Altogether, our data corroborate the concept that each strain behaves under characteristic patterns, which needs to be taken into consideration in the study design to ensure experimental reproducibility and comply with essential animal welfare principles.

Three Pillars of Automated Home-Cage Phenotyping of Mice: Novel Findings, Refinement, and Reproducibility Based on Literature and Experience

Animal models of neurodegenerative and neuropsychiatric disorders require extensive behavioral phenotyping. Currently, this presents several caveats and the most important are: (i) rodents are nocturnal animals, but mostly tested during the light period; (ii) the conventional behavioral experiments take into consideration only a snapshot of a rich behavioral repertoire; and (iii) environmental factors, as well as experimenter influence, are often underestimated. Consequently, serious concerns have been expressed regarding the reproducibility of research findings on the one hand, and appropriate welfare of the animals (based on the principle of 3Rs-reduce, refine and replace) on the other hand. To address these problems and improve behavioral phenotyping in general, several solutions have been proposed and developed. Undisturbed, 24/7 home-cage monitoring (HCM) is gaining increased attention and popularity as demonstrating the potential to substitute or complement the conventional phenotyping methods by providing valuable data for identifying the behavioral patterns that may have been missed otherwise. In this review, we will briefly describe the different technologies used for HCM systems. Thereafter, based on our experience, we will focus on two systems, IntelliCage (NewBehavior AG and TSE-systems) and Digital Ventilated Cage (DVC®, Tecniplast)-how they have been developed and applied during recent years. Additionally, we will touch upon the importance of the environmental/experimenter artifacts and propose alternative suggestions for performing phenotyping experiments based on the published evidence. We will discuss how the integration of telemetry systems for deriving certain physiological parameters can help to complement the description of the animal model to offer better translation to human studies. Ultimately, we will discuss how such HCM data can be statistically interpreted and analyzed.