Supplemental Figure 1

Supplemental Figure 1. Time course of hypersensitivity and injury resolution after CFA administration. (A) CFA induces mechanical sensitivity at the site of injury. (B) CFA administration to the left paw did not produced changes in sensitivity in the contralateral paw. Data displayed as mean value +/- SEM.

Raw VF Values

Left Paws

a <- data[data$Paw == "Left", ]
anova_test(data = a, dv=VF,wid=ID,between=CFA,within=Test,effect.size = "pes")
## ANOVA Table (type II tests)
## 
## $ANOVA
##     Effect DFn DFd      F        p p<.05   pes
## 1      CFA   1  30 45.385 1.82e-07     * 0.602
## 2     Test   3  90 70.641 1.42e-23     * 0.702
## 3 CFA:Test   3  90 68.662 3.46e-23     * 0.696
## 
## $`Mauchly's Test for Sphericity`
##     Effect     W     p p<.05
## 1     Test 0.913 0.761      
## 2 CFA:Test 0.913 0.761      
## 
## $`Sphericity Corrections`
##     Effect   GGe      DF[GG]    p[GG] p[GG]<.05   HFe      DF[HF]    p[HF]
## 1     Test 0.949 2.85, 85.37 1.76e-22         * 1.058 3.17, 95.25 1.42e-23
## 2 CFA:Test 0.949 2.85, 85.37 4.09e-22         * 1.058 3.17, 95.25 3.46e-23
##   p[HF]<.05
## 1         *
## 2         *
a %>%
  dplyr::group_by(Test) %>%
  pairwise_t_test(VF~CFA)
## # A tibble: 4 × 10
##   Test   .y.   group1 group2    n1    n2        p p.signif    p.adj p.adj.signif
## * <chr>  <chr> <chr>  <chr>  <int> <int>    <dbl> <chr>       <dbl> <chr>       
## 1 Basel… VF    Naive  CFA       16    16 9.33e- 2 ns       9.33e- 2 ns          
## 2 CFA +… VF    Naive  CFA       16    16 4.70e-16 ****     4.70e-16 ****        
## 3 CFA +… VF    Naive  CFA       16    16 1.15e- 6 ****     1.15e- 6 ****        
## 4 CFA +… VF    Naive  CFA       16    16 2.49e- 1 ns       2.49e- 1 ns

CFA administration caused mechanical hypersensitivity in the week after injection F3,90 = 68.88, p <0.001. CFA-treated mice had significantly lower paw withdrawal thresholds one and five days after injection (both p < 0.001), but the group difference in sensitivity had resolved by the eighth day after injection (p = 0.249).

Right Paws

a <- data[data$Paw == "Right", ]
anova_test(data = a, dv=VF,wid=ID,between=CFA,within=Test,effect.size = "pes")
## ANOVA Table (type II tests)
## 
## $ANOVA
##     Effect DFn DFd     F     p p<.05   pes
## 1      CFA   1  30 0.470 0.498       0.015
## 2     Test   3  90 2.215 0.092       0.069
## 3 CFA:Test   3  90 0.416 0.742       0.014
## 
## $`Mauchly's Test for Sphericity`
##     Effect     W    p p<.05
## 1     Test 0.853 0.47      
## 2 CFA:Test 0.853 0.47      
## 
## $`Sphericity Corrections`
##     Effect   GGe     DF[GG] p[GG] p[GG]<.05   HFe      DF[HF] p[HF] p[HF]<.05
## 1     Test 0.896 2.69, 80.6 0.099           0.992 2.98, 89.28 0.092          
## 2 CFA:Test 0.896 2.69, 80.6 0.720           0.992 2.98, 89.28 0.740
a %>%
  dplyr::group_by(Test) %>%
  pairwise_t_test(VF~CFA)
## # A tibble: 4 × 10
##   Test     .y.   group1 group2    n1    n2     p p.signif p.adj p.adj.signif
## * <chr>    <chr> <chr>  <chr>  <int> <int> <dbl> <chr>    <dbl> <chr>       
## 1 Baseline VF    Naive  CFA       16    16 0.517 ns       0.517 ns          
## 2 CFA + 1D VF    Naive  CFA       16    16 0.94  ns       0.94  ns          
## 3 CFA + 5D VF    Naive  CFA       16    16 0.762 ns       0.762 ns          
## 4 CFA + 8D VF    Naive  CFA       16    16 0.262 ns       0.262 ns

There was no effect of CFA treatment on VF thresholds for the right (non-injected) hindpaws across days of testing (p = 0.74)

Within-Subjects’ Changes in VF Threasholds

a <- data %>%
  pivot_wider(names_from = Test, values_from = VF) %>%
  mutate(percBL_1D = (`CFA + 1D` / Baseline) * 100,
         percBL_5D = (`CFA + 5D` / Baseline) * 100,
         percBL_8D = (`CFA + 8D` / Baseline) * 100,
         Baseline = 100) %>%
  select(ID, Paw, CFA, Baseline, percBL_1D, percBL_5D, percBL_8D)

colnames(a) <- c("ID","Paw","CFA","Baseline","CFA + 1D", "CFA + 5D", "CFA + 8D")

Left Paws

b <- a  %>%
  melt(id.vars = c("ID", "Paw", "CFA")) %>%
  filter(Paw == "Left") %>%
  ungroup() 

anova_test(data = b, dv = value, within = variable, between = CFA, wid = ID)
## ANOVA Table (type II tests)
## 
## $ANOVA
##         Effect DFn DFd      F        p p<.05   ges
## 1          CFA   1  30 74.003 1.35e-09     * 0.507
## 2     variable   3  90 65.910 1.23e-22     * 0.561
## 3 CFA:variable   3  90 67.574 5.69e-23     * 0.568
## 
## $`Mauchly's Test for Sphericity`
##         Effect     W    p p<.05
## 1     variable 0.911 0.75      
## 2 CFA:variable 0.911 0.75      
## 
## $`Sphericity Corrections`
##         Effect   GGe     DF[GG]    p[GG] p[GG]<.05   HFe      DF[HF]    p[HF]
## 1     variable 0.946 2.84, 85.1 1.57e-21         * 1.055 3.16, 94.91 1.23e-22
## 2 CFA:variable 0.946 2.84, 85.1 7.55e-22         * 1.055 3.16, 94.91 5.69e-23
##   p[HF]<.05
## 1         *
## 2         *
b %>%
  group_by(CFA) %>%
  pairwise_t_test(value~variable, paired = T)
## # A tibble: 12 × 11
##    CFA   .y.   group1   group2      n1    n2 statistic    df        p    p.adj
##  * <fct> <chr> <chr>    <chr>    <int> <int>     <dbl> <dbl>    <dbl>    <dbl>
##  1 Naive value Baseline CFA + 1D    16    16    0.0603    15 9.53e- 1 1   e+ 0
##  2 Naive value Baseline CFA + 5D    16    16    0.273     15 7.88e- 1 1   e+ 0
##  3 Naive value Baseline CFA + 8D    16    16    0.445     15 6.63e- 1 1   e+ 0
##  4 Naive value CFA + 1D CFA + 5D    16    16    0.162     15 8.73e- 1 1   e+ 0
##  5 Naive value CFA + 1D CFA + 8D    16    16    0.293     15 7.74e- 1 1   e+ 0
##  6 Naive value CFA + 5D CFA + 8D    16    16    0.136     15 8.93e- 1 1   e+ 0
##  7 CFA   value Baseline CFA + 1D    16    16   46.7       15 1.18e-17 7.08e-17
##  8 CFA   value Baseline CFA + 5D    16    16    8.72      15 2.93e- 7 8.79e- 7
##  9 CFA   value Baseline CFA + 8D    16    16    0.752     15 4.64e- 1 4.64e- 1
## 10 CFA   value CFA + 1D CFA + 5D    16    16  -11.3       15 9.5 e- 9 3.8 e- 8
## 11 CFA   value CFA + 1D CFA + 8D    16    16  -15.6       15 1.09e-10 5.45e-10
## 12 CFA   value CFA + 5D CFA + 8D    16    16   -6.38      15 1.24e- 5 2.48e- 5
## # ℹ 1 more variable: p.adj.signif <chr>

CFA induced significant changes in VF thresholds across the time course F3,90 = 67.57, p < 0.001. CFA-treated mice exhibited significant decreases in their paw withdrawal thresholds, relative to their baseline measurements, both one and five days after injection (both p < 0.001). CFA-treated mice did not exhibit ongoing sensitivity eight days after CFA injection, indicating that the injury had resolved (p = 0.464).

Right Paws

b <- a %>%
  melt(id.vars = c("ID", "Paw", "CFA")) %>%
  filter(Paw == "Right") %>%
  ungroup()

anova_test(data = b, dv = value, within = variable, between = CFA, wid = ID)
## ANOVA Table (type II tests)
## 
## $ANOVA
##         Effect DFn DFd     F     p p<.05   ges
## 1          CFA   1  30 0.580 0.452       0.012
## 2     variable   3  90 2.110 0.105       0.027
## 3 CFA:variable   3  90 0.676 0.569       0.009
## 
## $`Mauchly's Test for Sphericity`
##         Effect     W    p p<.05
## 1     variable 0.738 0.12      
## 2 CFA:variable 0.738 0.12      
## 
## $`Sphericity Corrections`
##         Effect   GGe      DF[GG] p[GG] p[GG]<.05   HFe      DF[HF] p[HF]
## 1     variable 0.816 2.45, 73.47 0.118           0.894 2.68, 80.49 0.112
## 2 CFA:variable 0.816 2.45, 73.47 0.540           0.894 2.68, 80.49 0.553
##   p[HF]<.05
## 1          
## 2

There were no within-subjects changes in paw withdrawal thresholds for the right (non-injured) paws (p = 0.57).