Clark Tannia S, Pandolfo Lauren M, Marshall Christopher M, Mitra Apratim K, Schech Joseph M
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), Division of Intramural Research, Research Animal Management Branch (RAMB), Bethesda, Maryland, USA.
J Am Assoc Lab Anim Sci. 2018 Nov 1;57(6):698-702. doi: 10.30802/AALAS-JAALAS-18-000045. Epub 2018 Oct 25.
Body condition scoring (BCS) is a simple, rapid, noninvasive tool used to assess body condition in animals. In this study, we developed and validated a diagram-based BCS for adult zebrafish (), a popular research model. After receiving 20 min of hands-on training regarding the scoring system, 5 people each rated 95 adult zebrafish. The fish then were euthanized and measured to establish body condition indices (BMI and the Fulton K factor). Both condition indices were highly correlated with fish width. Using correlation data and observed trends in fish width, we established expected BCS definitions. We validated the BCS definitions in 2 ways. First, we calculated the Pearson correlation coefficient between the average observed BCS and expected BCS; this statistic revealed very strong correlation between observed and expected BCS. In addition, we assessed the predictive power of BCS by using multinomial logistic regression and then applied the fitted model to evaluate the accuracy of the predictions (BCS compared with BMI, 85%; BCS compared with K factor, 61%). Finally, to determine the robustness of BCS to variation among raters, we calculated the intraclass correlation coefficient and demonstrated high interrater reliability. In conclusion, adult zebrafish BCS can be used to quickly identify animals with different body condition indices (thin to obese). In addition, the diagram-based chart is easy to use and implement accurately, with minimal training.
身体状况评分(BCS)是一种用于评估动物身体状况的简单、快速、非侵入性工具。在本研究中,我们开发并验证了一种基于图表的成年斑马鱼BCS(),斑马鱼是一种常用的研究模型。在接受了20分钟关于评分系统的实际操作培训后,5名人员分别对95条成年斑马鱼进行了评分。然后对这些鱼实施安乐死并进行测量,以确定身体状况指数(BMI和富尔顿K因子)。这两个状况指数均与鱼的宽度高度相关。利用相关数据和观察到的鱼宽度趋势,我们确定了预期的BCS定义。我们通过两种方式验证了BCS定义。首先,我们计算了平均观察到的BCS与预期BCS之间的皮尔逊相关系数;该统计数据显示观察到的BCS与预期BCS之间具有很强的相关性。此外,我们通过多项逻辑回归评估了BCS的预测能力,然后应用拟合模型评估预测的准确性(BCS与BMI相比,85%;BCS与K因子相比,61%)。最后,为了确定BCS对评分者间差异的稳健性,我们计算了组内相关系数,并证明了评分者间的高可靠性。总之,成年斑马鱼BCS可用于快速识别具有不同身体状况指数(从瘦到肥胖)的动物。此外,基于图表的图表易于使用且能准确实施,只需极少的培训。