Figure 4 - Recovery From PGE-2 Injection

Published Image

Figure 4. CFA-priming produced enhanced and prolonged mechanical sensitivity after PGE-2 injection in male mice only. (A) Timeline of experimental testing. (B) PGE-2 was administered to the site of previous injury to test expression of pain sensitization. CFA-primed male mice exhibited enhanced (3hr) and prolonged (24hr) mechanical sensitivity after PGE-2 injection relative to naive mice injected with PGE-2 (C). naive males recovered their baseline paw withdrawal thresholds 24 hours after PGE-2, whereas CFA-primed males exhibited ongoing sensitivity (C,D). There was no difference in the magnitude of mechanical sensitivity induced by PGE-2 injection 3hrs post administration in female mice (G), and both CFA-primed and pin-naive mice recovered basal levels of mechanical sensitivity 24 hours post-administration (H). There were no decreases in paw sensitivity in the contralateral (never-injected) paw during pain & recovery from PGE-2 administration (E,F,I,J). Data expressed as mean +/- SEM. \(***\) Indicates between-group difference where p < 0.001 and # indicates a within-subject difference from baseline where p <0.05.

Statistics

# Select the left paws
left_paws <- rbind(L_Male,L_Female)

# Remove those that did not receive PGE2 and switch to long form
a <- left_paws %>%
  filter(PGE2 == "PGE2") %>%
  melt(id.vars=c("ID","CFA","Sex","PGE2"))

# Run 3-way ANOVA: Sex X CFA X Day of testing (VF)
b <- anova_test(data=a,dv=value,between=c(Sex,CFA),within=variable,wid=ID)
knitr::kable(get_anova_table(b))
Effect DFn DFd F p p<.05 ges
Sex 1 28 1.154 0.292 0.014
CFA 1 28 5.116 0.032 * 0.060
variable 2 56 93.042 0.000 * 0.684
Sex:CFA 1 28 7.754 0.010 * 0.088
Sex:variable 2 56 5.705 0.006 * 0.117
CFA:variable 2 56 3.548 0.035 * 0.076
Sex:CFA:variable 2 56 6.479 0.003 * 0.131 
# Run both sets of follow ups: 

## Effect of CFA on each day of testing split by sex
b <- a %>%
  group_by(Sex,variable) %>%
  pairwise_t_test(value~CFA)

tt(b)
Sex variable .y. group1 group2 n1 n2 p p.signif p.adj p.adj.signif
Female Baseline value Naive CFA 8 8 0.77900 ns 0.77900 ns
Female 3 hr value Naive CFA 8 8 0.62900 ns 0.62900 ns
Female 24 hr value Naive CFA 8 8 0.57000 ns 0.57000 ns
Male Baseline value Naive CFA 8 8 0.31600 ns 0.31600 ns
Male 3 hr value Naive CFA 8 8 0.03960 * 0.03960 *
Male 24 hr value Naive CFA 8 8 0.00087 *** 0.00087 *** 
## Effect of Sex on each day of testing split by CFA history
c <- a %>%
  group_by(CFA,variable) %>%
  pairwise_t_test(value~Sex)

tt(c)
CFA variable .y. group1 group2 n1 n2 p p.signif p.adj p.adj.signif
Naive Baseline value Female Male 8 8 0.901000 ns 0.901000 ns
Naive 3 hr value Female Male 8 8 0.086800 ns 0.086800 ns
Naive 24 hr value Female Male 8 8 0.628000 ns 0.628000 ns
CFA Baseline value Female Male 8 8 0.232000 ns 0.232000 ns
CFA 3 hr value Female Male 8 8 0.319000 ns 0.319000 ns
CFA 24 hr value Female Male 8 8 0.000306 *** 0.000306 *** 
## Effect of DAY within each group
d <- a %>%
  group_by(CFA,Sex) %>%
  pairwise_t_test(value~variable,p.adjust.method = "bonferroni")

tt(d)
CFA Sex .y. group1 group2 n1 n2 p p.signif p.adj p.adj.signif
Naive Female value Baseline 3 hr 8 8 0.000002010 **** 0.000006040 ****
Naive Female value Baseline 24 hr 8 8 0.879000000 ns 1.000000000 ns
Naive Female value 3 hr 24 hr 8 8 0.000002830 **** 0.000008490 ****
Naive Male value Baseline 3 hr 8 8 0.000033200 **** 0.000099500 ****
Naive Male value Baseline 24 hr 8 8 0.748000000 ns 1.000000000 ns
Naive Male value 3 hr 24 hr 8 8 0.000015600 **** 0.000046700 ****
CFA Female value Baseline 3 hr 8 8 0.000010300 **** 0.000030900 ****
CFA Female value Baseline 24 hr 8 8 0.441000000 ns 1.000000000 ns
CFA Female value 3 hr 24 hr 8 8 0.000001760 **** 0.000005290 ****
CFA Male value Baseline 3 hr 8 8 0.000000103 **** 0.000000308 ****
CFA Male value Baseline 24 hr 8 8 0.000009240 **** 0.000027700 ****
CFA Male value 3 hr 24 hr 8 8 0.049300000 * 0.148000000 ns