Rongwan Sun ^1,2 Marie-Christin Gaerz ¹ Christian Oeing ^2,3 Knut Mai ^1,2,4,5,6 Sebastian Brachs ^1,2*

• ¹ Department of Endocrinology and Metabolism, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
• ² German Centre for Cardiovascular Research (DZHK), partner site Berlin,, Berlin, Baden-Württemberg, Germany
• ³ Department of Cardiology, Angiology and Intensive Care Medicine, German Heart Center Berlin, Berlin, Baden-Württemberg, Germany
• ⁴ Department of Human Nutrition, German Institute of Human Nutrition (DIfE) Potsdam-Rehbruecke, Nuthetal, Germany
• ⁵ NutriAct - Competence Cluster Nutritional Research Berlin-Potsdam, Nuthetal, Germany
• ⁶ German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany

Holistic phenotyping of rodent models is increasing, with a growing awareness of the 3Rs and the fact that specialized experimental setups also have artificial restrictions. Activity is an important parameter for almost all basic and applied research areas involving laboratory animals. Locomotor activity, the main form of energy expenditure, affects metabolic rate, muscle mass, and body weight and is commonly investigated in metabolic disease studies. It is also essential in treatments, pharmacological and toxicological studies as an indicator of animal welfare. Therefore, accurate and effective measurement of activity is crucial. As conventional monitoring systems induce changes in the housing environment and through handling, this can lead to artificial interference and measurement inaccuracies. To address this, we investigated whether accurate activity profiles can be derived from the continuous, non-invasive home cage data recorded in the DVC (Digital Ventilated Cage system). Our study focused on the evaluation of circadian activity profiles from the DVC and the comparison of those with conventional activity measurements to validate them statistically and verify their reproducibility. Hence, we utilized data from metabolic studies, an Alzheimer's disease model known for increased activity, and included DVC monitoring in a project investigating treatment effects on activity in a type-1 diabetes-like model. DVC's data yields robust, scientifically accurate and consistent circadian rhythms from group-housed mice. This is especially advantageous for longitudinal experiments. The activity profiles from both systems are fully comparable and provide matching profiles. Using the DVC monitoring, we confirmed the hyperactivity phenotype in our AD model and a decline in activity after type-1 diabetes induction. We also discuss the advantages and limitations of DVC activity measurements to demonstrate its potential and to avoid confounders.