Sun Rongwan, Gaerz Marie-Christin, Oeing Christian, Mai Knut, Brachs Sebastian
Department of Endocrinology and Metabolism, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
German Centre for Cardiovascular Research (DZHK), Berlin, Germany.
Front Neurosci. 2024 Sep 20;18:1456307. doi: 10.3389/fnins.2024.1456307. eCollection 2024.
Holistic phenotyping of rodent models is increasing, with a growing awareness of the 3Rs and the fact that specialized experimental setups can also impose 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, influences metabolic rate, muscle mass, and body weight and is frequently investigated in metabolic disease research. Additionally, it serves as an indicator of animal welfare in therapeutic, pharmacological, and toxicological studies. Thus, accurate and effective measurement of activity is crucial. However, conventional monitoring systems often alter the housing environment and require handling, which can introduce artificial interference and lead to measurement inaccuracies.
Our study focused on evaluating circadian activity profiles derived from the DVC and comparing them with conventional activity measurements to validate them statistically and assess their reproducibility. 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-like diabetes model.
The DVC data yielded robust, scientifically accurate, and consistent circadian profiles from group-housed mice, which is particularly advantageous for longitudinal experiments. The activity profiles from both systems were fully comparable, providing matching profiles. Using DVC monitoring, we confirmed the hyperactivity phenotype in an AD model and reproduced a decline in activity in type-1-like diabetes model.
In our work, we derived robust circadian activity profiles from the DVC data of group-housed mice, which were scientifically accurate, reproducible and comparable to another activity measurement. This approach can not only improve animal welfare according to the 3R principles but can also be implement in high-throughput longitudinal studies. Furthermore, we discuss the advantages and limitations of DVC activity measurements to highlight its potential and avoid confounders.
随着人们对3R原则的认识不断提高，以及意识到专门的实验设置也可能带来人为限制，对啮齿动物模型的整体表型分析正在增加。活动是几乎所有涉及实验动物的基础和应用研究领域的一个重要参数。运动活动作为能量消耗的主要形式，会影响代谢率、肌肉质量和体重，并且在代谢疾病研究中经常被研究。此外，在治疗、药理学和毒理学研究中，它还可作为动物福利的一个指标。因此，准确有效地测量活动至关重要。然而，传统的监测系统常常会改变饲养环境，并且需要处理动物，这可能会引入人为干扰并导致测量不准确。
我们的研究重点是评估从DVC得出的昼夜活动概况，并将其与传统的活动测量结果进行比较，以进行统计学验证并评估其可重复性。我们利用了代谢研究的数据，一个以活动增加而闻名的阿尔茨海默病模型，并在一个研究对1型糖尿病模型活动的治疗效果的项目中纳入了DVC监测。
DVC数据产生了来自群居小鼠的稳健、科学准确且一致的昼夜节律概况，这对于纵向实验特别有利。两个系统的活动概况完全可比，提供了匹配的概况。通过DVC监测，我们在一个AD模型中证实了多动表型，并在1型糖尿病模型中重现了活动下降。
在我们的工作中，我们从群居小鼠的DVC数据中得出了稳健的昼夜活动概况，这些概况科学准确、可重复且与另一种活动测量结果可比。这种方法不仅可以根据3R原则改善动物福利，还可以在高通量纵向研究中实施。此外，我们讨论了DVC活动测量的优点和局限性，以突出其潜力并避免混淆因素。
