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Despite its long establishment and applicability in mice pain detection, the Mouse Grimace Scale still seems to be underused in acute pain detection during chronic experiments. However, broadening its applicability can identify possible refinement approaches such as cumulative severity and habituation to painful stimuli. Therefore, this study focuses on two main aspects: First, five composite MGS criteria were evaluated with two independent methods (the MoBPs algorithm and a penalized least squares regression) and ranked for their relative importance. The most important variable was used in a second analysis to specifically evaluate the context of pain after an i.p. injection (intervention) in two treatment groups (CCl4 and oil (control)) at fixed times throughout four weeks in 24 male C57BL/6 N mice. One hour before and after each intervention, video recordings were taken, and the MGS assessment was performed. In this study, the results indicate orbital tightening as the most important criterion. In this experimental setup, a highly significant difference after treatment between week 0 and 1 was found in the CCl4 group, resulting in a medium-sized effect (W = 62.5, p value < 0.0001, rCCl4 = 0.64). The oil group showed no significant difference (week 0 vs 1, W = 291.5, p value = 0.7875, rcontrol = 0.04). Therefore, the study showed that the pain caused by i.p. injections was only dependent on the applied substance, and no significant cumulation or habituation occurred due to the intervention. Further, the results indicated that the MGS system can be simplified. [ABSTRACT FROM AUTHOR]

The Mouse Grimace Scale (MGS) has been widely used for the noninvasive examination of distress/pain in mice. The aim of this study was to further improve its performance to generate repeatable, faster, blinded and reliable results for developing automated and standardized pictures for MGS scoring and simultaneous evaluation of up to four animals. Videos of seven C57BL/6N mice were generated in an experiment to assess pain and stress induced by repeated intraperitoneal injection of carbon tetrachloride (CCl4). MGS scores were taken 1 h before and after the injection. Videotaping was performed for 10 min in special observation boxes. For manual selection, pictures of each mouse were randomly chosen for quality analysis and scored according six quality selection criteria (0 = no, 1 = moderate, 2 = full accordance); the maximum possible score was 12. Overall, 609 pictures from six videos were evaluated for MGS scoring quality; evaluation was performed by using the picture selection tool or by manual scoring. With manual scoring, 288 pictures (48.3% of all randomly generated pictures) were deemed scorable using MGS (mean score = 22.15 ± SD 6.3). To evaluate the algorithm, ratings from different rater groups (beginner, medium-level trained, professional) were compared with the automated image generated. These differences were not significant (p = 0.1091). This study demonstrates an improved set-up and a picture selection tool that can generate repeatable, not-observer biased and standardized pictures for MGS scoring. [ABSTRACT FROM AUTHOR]

The Mouse Grimace Scale (MGS) is an established method for estimating pain in mice during animal studies. Recently, an improved and standardized MGS set-up and an algorithm for automated and blinded output of images for MGS evaluation were introduced. The present study evaluated the application of this standardized set-up and the robustness of the associated algorithm at four facilities in different locations and as part of varied experimental projects. Experiments using the MGS performed at four facilities (F1–F4) were included in the study; 200 pictures per facility (100 pictures each rated as positive and negative by the algorithm) were evaluated by three raters for image quality and reliability of the algorithm. In three of the four facilities, sufficient image quality and consistency were demonstrated. Intraclass correlation coefficient, calculated to demonstrate the correlation among raters at the three facilities (F1–F3), showed excellent correlation. The specificity and sensitivity of the results obtained by different raters and the algorithm were analysed using Fisher's exact test (p < 0.05). The analysis indicated a sensitivity of 77% and a specificity of 64%. The results of our study showed that the algorithm demonstrated robust performance at facilities in different locations in accordance with the strict application of our MGS setup. [ABSTRACT FROM AUTHOR]