Anesthesia/Surgery Effects on Behavior and Brain Biochemistry

Data were expressed as mean ± standard error of mean (SEM). The number of samples was 10–14 per group for the behavior tests and 6–9 per group for the biochemical studies. The power calculation was performed using information collected from a preliminary study that was conducted under the same conditions. Based on the preliminary data, assuming a two-sided Student’s t-test, samples of 6 and 10 for each control and treatment group for the biochemistry and behavior studies, respectively, would lead to 90% power and 95% significance. In behavior tests, all the behavior parameters at 6, 9 and 24 hours were presented as a percentage of those of the baseline for the same group. We used the Mann-Whitney test to determine the difference in behavior tests between the control condition and Anesthesia/Surgery. In the intervention studies, normality of data was first analyzed by using the Shapiro–Wilk test, and we found the data were not normally distributed. Thus, logarithmic transformation was applied to normalize these variables. A two-way ANOVA was then used to assess the interaction of CsA with Anesthesia/Surgery to test the hypothesis that CsA would mitigate the effects of the Anesthesia/Surgery on behavior (e.g., latency to eat buried food in the buried food test) and levels of ATP and ROS in brain tissues of mice, followed by Tukey test for post-hoc comparisons. ATP and ROS levels were presented as a percentage of those of the control group. Z score was calculated using the formula described by Moller et al.70 (link), Z = [ΔX_{Anesthesia/Surgery}− MEAN(ΔX)_control]/SD(ΔX)_control. In the formula, ΔX_control was the change score of mice in the control group at 6, 9 and 24 h after control condition minus the score at the baseline; ΔX_{Anesthesia/Surgery}was the change score of mice in Anesthesia/Surgery group at 6, 9 and 24 h after the Anesthesia/Surgery minus the score at baseline; MEAN(ΔX)_control was the mean of ΔX_control; and SD(ΔX)_control was the standard deviation of ΔX_control. We also used the method for calculating a composite Z score in patients71 (link)72 (link) to determine a composite Z score for each of the mice. Specifically, the composite Z score for the mouse was calculated as the sum of the values of 6 Z scores (latency to eat food, time spent in the center, latency to the center, freezing time, entries in novel arm and duration in novel arm) normalized with the SD for that sum in the controls. Given that the reduction (rather than increase) in time spent in the center and the freezing time (open field test)20 (link)21 22 (link) and the reduction in duration and entries in the novel arm (Y maze test) indicate impairment of the behavior, we multiplied the Z score values representing these behaviors by −1 prior to calculating the composite Z score using these values. The nature of the hypothesis testing was two tailed. P values less than 0.05 were considered statistically significant. Prism 6 software (GraphPad Software, Inc, La Jolla, CA) was used to analyze the data.