Impact of repeated anesthesia with ketamine and xylazine on the well-being of C57BL/6JRj mice

Abstract

Within the scope of the 3Rs of Russel and Burch, the number of laboratory animals can be reduced by repeated use of an animal. This strategy only becomes relevant, if the total amount of pain, distress or harm the individual animal experiences does not exceed the severity of a single manipulation. For example, when using imaging techniques, an animal can be examined several times during a study, but it has to be anesthetized each time imaging is performed. The severity of anesthesia is thought to be mild according to the Directive 2010/63/EU. However, the Directive does not differentiate between single and repeated anesthesia, although repeated anesthesia may have a greater impact on well-being. Hence, we compared the impact of single and repeated anesthesia (six times at an interval of three to four days) by injection of ketamine and xylazine (KX) on the well-being of adult female and male C57BL/6JRj mice. After anesthesia, well-being of mice was assessed according to a protocol for systematic assessment of well-being including nesting, the Mouse Grimace Scale (MGS), a test for trait anxiety, home cage activity, and the rotarod test for motor activity, food intake, and body weight, as well as corticosterone (metabolite) analysis. Repeated anesthesia increased the MGS in mice of both sexes and caused short-term effects on well-being of female mice in the immediate post-anesthetic period, indicated by longer lasting effects on trait anxiety-related behavior. However, corticosterone metabolite concentrations suggested that mice habituated to the stress induced by repeated KX administration. Hence, the mildly negative effects on well-being of repeated KX anesthesia do not seem to accumulate over time using the respective regimen. However, further observations for severity classification are warranted in order to more specifically determine the duration of mild distress and trait anxiety.

Towards a fully automated surveillance of well-being status in laboratory mice using deep learning

“…• Inhalation anesthesia with isoflurane [29]: 30 min, 150 min post-procedure 152 • Injection anesthesia with the combination of ketamine and xylazine [30]: 30 min, 150 min, 153 day 2, day 9 post-procedure 154 • Castration: 30 min, 150 min, 300 min, day 2, day 3, day 7 post-procedure. 155 Images of untreated mice were generated at the same times as images of corresponding treated 156 groups.…”

“…An accuracy of 72-97% for humans scorers was reported [5]. 166 Interestingly, the change of facial action units described in the MGS is also triggered by other 167 stimuli than pain such as post-anesthetic distress, situations associated with fear (i.e., whisker 168 contact, social proximity, cat odor exposure, rat exposure), and aggression or 169 subordination [29,30,35].…”

“…For MGS scoring, one image of high quality showing the mouse face from frontal or lateral 171 view was randomly selected per mouse, and point in time [29,30,34] and the face of the mouse 172 were manually cropped from the image so that, if possible, the body posture was not visible. MGS score.…”

“…As we could not predict the MGS score directly, we followed the approach of Tuttle 184 et al [36] and assigned one of two defined states, "pain" and "no pain", to all images in order to 185 train a binary classifier on the whole data set. To do so, time points of image acquisition were 186 either defined as "pain" or "no pain" based on the MGS scores obtained by humans and the 187 statistical analysis performed in our previous studies [29,30,34]: if MGS scores were 188 significantly higher when compared to untreated mice (Fig 2), all images of this point in time 189 were considered to display a "pain face" and were assigned to the label "pain" (Table 1).…”

“…This should 196 especially be considered in the case of images generated after anesthesia. Mice which received 197 anesthesia only and did not undergo surgery may have experienced post-anesthetic distress rather than pain [29,30]. 40% of all images while about 86% of all images are valid.…”