survival collection data (Drosophila)

---

Experiment parameters`

• Start date: 04/03/2024
• Lab members: Oleksander, Catherine and Joanne (Frontrunners 2023/24)
• Genotypes:
  • daxx^NP4778
  • Dahomey wild types
• Pathogen: e.g. S. marcescens Db11 (OD₆₀₀=100)
• Infection method: oral

setwd("/home/catherinetaylor35")

Preparing the data

Loading the data

if (!require("readxl")) {
    install.packages("readxl")
}

## Loading required package: readxl

library(readxl)

data <- read_xlsx("survival data collection template .xlsx")

## Warning: Expecting numeric in G3 / R3C7: got a date

## Warning: Expecting numeric in H3 / R3C8: got a date

## Warning: Expecting numeric in I3 / R3C9: got a date

## Warning: Expecting numeric in J3 / R3C10: got a date

## Warning: Expecting numeric in K3 / R3C11: got a date

## Warning: Expecting numeric in L3 / R3C12: got a date

## Warning: Expecting numeric in M3 / R3C13: got a date

## Warning: Expecting numeric in N3 / R3C14: got a date

## Warning: Expecting numeric in O3 / R3C15: got a date

## Warning: Expecting numeric in P3 / R3C16: got a date

## Warning: Expecting numeric in Q3 / R3C17: got a date

## Warning: Expecting numeric in R3 / R3C18: got a date

## Warning: Expecting numeric in T3 / R3C20: got a date

## Warning: Expecting numeric in V3 / R3C22: got a date

## Warning: Expecting numeric in G4 / R4C7: got a date

## Warning: Expecting numeric in H4 / R4C8: got a date

## Warning: Expecting numeric in I4 / R4C9: got a date

## Warning: Expecting numeric in J4 / R4C10: got a date

## Warning: Expecting numeric in K4 / R4C11: got a date

## Warning: Expecting numeric in L4 / R4C12: got a date

## Warning: Expecting numeric in M4 / R4C13: got a date

## Warning: Expecting numeric in N4 / R4C14: got a date

## Warning: Expecting numeric in O4 / R4C15: got a date

## Warning: Expecting numeric in P4 / R4C16: got a date

## Warning: Expecting numeric in Q4 / R4C17: got a date

## Warning: Expecting numeric in R4 / R4C18: got a date

## Warning: Expecting numeric in T4 / R4C20: got a date

## Warning: Expecting numeric in V4 / R4C22: got a date

## New names:
## • `` -> `...3`
## • `` -> `...7`
## • `` -> `...8`
## • `` -> `...9`
## • `` -> `...10`
## • `` -> `...11`
## • `` -> `...12`
## • `` -> `...13`
## • `` -> `...14`
## • `` -> `...15`
## • `` -> `...16`
## • `` -> `...17`
## • `` -> `...18`
## • `` -> `...19`
## • `` -> `...20`
## • `` -> `...21`

head(data)

## # A tibble: 6 × 21
##   `P.ent. OD=` `100`  ...3  `Infection start:=` `04.03.2024`
##   <chr>        <chr>  <chr> <chr>               <chr>       
## 1 GENOTYPE     FOOD   SEX   INFECTION           REPLICATE   
## 2 <NA>         <NA>   <NA>  <NA>                <NA>        
## 3 daxx[NP4778] Normal M     vehicle             1           
## 4 daxx[NP4778] Normal M     vehicle             2           
## 5 daxx[NP4778] Normal M     vehicle             3           
## 6 daxx[NP4778] Normal M     P.ent.              1           
## # ℹ 16 more variables:
## #   `DATE:TIME (YYYY-MM-DD HH:MM:SS), e.g. 2024-03-05 09:00:00` <dbl>,
## #   ...7 <dbl>, ...8 <dbl>, ...9 <dbl>, ...10 <dbl>, ...11 <dbl>, ...12 <dbl>,
## #   ...13 <dbl>, ...14 <dbl>, ...15 <dbl>, ...16 <dbl>, ...17 <dbl>,
## #   ...18 <chr>, ...19 <dbl>, ...20 <chr>, ...21 <dbl>

Computing tools

Libraries

required_packages <- c("BiocManager", "survival", "tidyverse", "survminer", "viridis", "devtools", "kableExtra", "cachem", "ggtext")

for (pkg in required_packages) {
  if (!require(pkg, character.only = TRUE)) {
    install.packages(pkg)
  }
}

## Loading required package: BiocManager

## Bioconductor version '3.16' is out-of-date; the current release version '3.19'
##   is available with R version '4.4'; see https://bioconductor.org/install

## Loading required package: survival

## Loading required package: tidyverse

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
## Loading required package: survminer
## 
## Loading required package: ggpubr
## 
## 
## Attaching package: 'survminer'
## 
## 
## The following object is masked from 'package:survival':
## 
##     myeloma
## 
## 
## Loading required package: viridis
## 
## Loading required package: viridisLite
## 
## Loading required package: devtools
## 
## Loading required package: usethis
## 
## 
## Attaching package: 'devtools'
## 
## 
## The following object is masked from 'package:BiocManager':
## 
##     install
## 
## 
## Loading required package: kableExtra
## 
## 
## Attaching package: 'kableExtra'
## 
## 
## The following object is masked from 'package:dplyr':
## 
##     group_rows
## 
## 
## Loading required package: cachem
## 
## Loading required package: ggtext

library(tidyverse)
library(survival)
library(survminer)
library(viridis)
library(devtools)
library(kableExtra)
library(cachem)
library(ggtext)

Data preparation and wrangling

# Inspect the data to understand its structure
print(head(data))

## # A tibble: 6 × 21
##   `P.ent. OD=` `100`  ...3  `Infection start:=` `04.03.2024`
##   <chr>        <chr>  <chr> <chr>               <chr>       
## 1 GENOTYPE     FOOD   SEX   INFECTION           REPLICATE   
## 2 <NA>         <NA>   <NA>  <NA>                <NA>        
## 3 daxx[NP4778] Normal M     vehicle             1           
## 4 daxx[NP4778] Normal M     vehicle             2           
## 5 daxx[NP4778] Normal M     vehicle             3           
## 6 daxx[NP4778] Normal M     P.ent.              1           
## # ℹ 16 more variables:
## #   `DATE:TIME (YYYY-MM-DD HH:MM:SS), e.g. 2024-03-05 09:00:00` <dbl>,
## #   ...7 <dbl>, ...8 <dbl>, ...9 <dbl>, ...10 <dbl>, ...11 <dbl>, ...12 <dbl>,
## #   ...13 <dbl>, ...14 <dbl>, ...15 <dbl>, ...16 <dbl>, ...17 <dbl>,
## #   ...18 <chr>, ...19 <dbl>, ...20 <chr>, ...21 <dbl>

# Remove unnecessary rows and columns
data <- data[-c(1,2), ]

# Rename columns to make them more descriptive
colnames(data) <- c("GENOTYPE", "FOOD", "SEX", "INFECTION", "REPLICATE")

# Convert factors to characters
data <- data.frame(lapply(data, function(x) if(is.factor(x)) as.character(x) else x))

# Handle missing data
data <- na.omit(data)
print(colnames(data))

##  [1] "GENOTYPE"  "FOOD"      "SEX"       "INFECTION" "REPLICATE" "NA."      
##  [7] "NA..1"     "NA..2"     "NA..3"     "NA..4"     "NA..5"     "NA..6"    
## [13] "NA..7"     "NA..8"     "NA..9"     "NA..10"    "NA..11"    "NA..12"   
## [19] "NA..13"    "NA..14"    "NA..15"

# Convert columns with 'NA' in their name to numeric
numeric_columns <- colnames(data)[grepl("NA", colnames(data))]
data <- data %>%
  mutate(across(all_of(numeric_columns), ~as.numeric(as.character(.))))

# Inspect the cleaned data
print(data)

##        GENOTYPE     FOOD SEX INFECTION REPLICATE NA. NA..1 NA..2 NA..3 NA..4
## 1  daxx[NP4778]   Normal   M   vehicle         1   0     0     0     0     0
## 2  daxx[NP4778]   Normal   M   vehicle         2   0     0     0     1     1
## 3  daxx[NP4778]   Normal   M   vehicle         3   0     0     0     0     0
## 4  daxx[NP4778]   Normal   M    P.ent.         1   0     2     2     2     3
## 5  daxx[NP4778]   Normal   M    P.ent.         2   0     1     3     3     3
## 6  daxx[NP4778]   Normal   M    P.ent.         3   0     1     2     2     3
## 7  daxx[NP4778]   Normal   F   vehicle         1   0     0     0     0     0
## 8  daxx[NP4778]   Normal   F   vehicle         2   0     0     0     0     0
## 9  daxx[NP4778]   Normal   F   vehicle         3   0     2     2     2     2
## 10 daxx[NP4778]   Normal   F    P.ent.         1   0     1     1     1     1
## 11 daxx[NP4778]   Normal   F    P.ent.         2   0     1     1     1     1
## 12 daxx[NP4778]   Normal   F    P.ent.         3   0     2     2     3     3
## 13 daxx[NP4778] HCr 50mM   M   vehicle         1   0     0     0     0     0
## 14 daxx[NP4778] HCr 50mM   M   vehicle         2   0     0     0     0     0
## 15 daxx[NP4778] HCr 50mM   M   vehicle         3   0     0     0     0     0
## 16 daxx[NP4778] HCr 50mM   M    P.ent.         1   0     0     1     1     2
## 17 daxx[NP4778] HCr 50mM   M    P.ent.         2   0     0     1     1     1
## 18 daxx[NP4778] HCr 50mM   M    P.ent.         3   0     0     0     0     0
## 19 daxx[NP4778] HCr 50mM   F   vehicle         1   0     1     1     1     1
## 20 daxx[NP4778] HCr 50mM   F   vehicle         2   0     1     2     2     3
## 21 daxx[NP4778] HCr 50mM   F   vehicle         3   0     1     2     3     3
## 22 daxx[NP4778] HCr 50mM   F    P.ent.         1   0     2     6     6     6
## 23 daxx[NP4778] HCr 50mM   F    P.ent.         2   0     5     6     6     6
## 24 daxx[NP4778] HCr 50mM   F    P.ent.         3   0     1     1     1     2
## 25      Dahomey   Normal   M   vehicle         1   0     1     1     1     1
## 26      Dahomey   Normal   M   vehicle         2   0     0     0     0     0
## 27      Dahomey   Normal   M   vehicle         3   0     0     0     0     0
## 28      Dahomey   Normal   M    P.ent.         1   0     0     0     0     1
## 29      Dahomey   Normal   M    P.ent.         2   0     0     0     0     0
## 30      Dahomey   Normal   M    P.ent.         3   0     1     1     1     1
## 31      Dahomey   Normal   F   vehicle         1   0     0     0     0     0
## 32      Dahomey   Normal   F   vehicle         2   0     0     0     0     0
## 33      Dahomey   Normal   F   vehicle         3   0     0     0     0     0
## 34      Dahomey   Normal   F    P.ent.         1   0     0     0     0     0
## 35      Dahomey   Normal   F    P.ent.         2   0     0     0     0     0
## 36      Dahomey   Normal   F    P.ent.         3   0     0     0     0     0
## 37      Dahomey HCr 50mM   M   vehicle         1   0     0     0     0     0
## 38      Dahomey HCr 50mM   M   vehicle         2   0     1     1     1     1
## 39      Dahomey HCr 50mM   M   vehicle         3   0     0     0     0     0
## 40      Dahomey HCr 50mM   M    P.ent.         1   0     0     0     0     0
## 41      Dahomey HCr 50mM   M    P.ent.         2   0     0     0     0     0
## 42      Dahomey HCr 50mM   M    P.ent.         3   0     0     1     2     2
## 43      Dahomey HCr 50mM   F   vehicle         1   0     0     0     0     0
## 44      Dahomey HCr 50mM   F   vehicle         2   0     0     0     0     0
## 45      Dahomey HCr 50mM   F   vehicle         3   0     0     0     0     0
## 46      Dahomey HCr 50mM   F    P.ent.         1   0     0     0     0     0
## 47      Dahomey HCr 50mM   F    P.ent.         2   0     0     0     0     0
## 48      Dahomey HCr 50mM   F    P.ent.         3   0     0     0     0     0
##    NA..5 NA..6 NA..7 NA..8 NA..9 NA..10 NA..11 NA..12 NA..13 NA..14 NA..15
## 1      0     0     0     0     0      0      0      0      0      0      0
## 2      1     1     1     1     1      1      1      1      1      1      1
## 3      0     0     0     0     0      0      0      0      0      0      0
## 4      3     3     3     3     3      3      3      3      3      3      3
## 5      3     3     4     4     4      5      5      5      5      5      5
## 6      4     4     4     4     4      4      4      4      4      4      5
## 7      0     0     0     0     0      0      0      0      0      0      0
## 8      0     0     0     0     0      0      0      0      0      0      1
## 9      2     2     2     2     2      2      2      2      2     16     16
## 10     1     1     1     1     1      1      1      1      1      1      1
## 11     1     1     1     1     1      1      1      2      2      2     18
## 12     3     3     3     3     3      3      3      3      3     17     17
## 13     0     0     0     0     0      0      0      0      0      0      0
## 14     0     0     0     0     0      0      0      0      0      0      0
## 15     0     0     0     0     0      0      0      0      0      0      0
## 16     2     1     1     1     1      1      1      1      1      1      1
## 17     1     1     1     1     1      1      1      1      1      1      1
## 18     0     0     0     0     1      1      1      1      1      1      1
## 19     1     1     2     2     2      2      2      2      2     19     20
## 20     4     4     4     4     4      4      4      4      4      4      4
## 21     3     4     4     4     4      4      4      4      5      5      5
## 22     6     6     6     6     6      6      6      6      6      6      7
## 23     6     6     6     6     6      7      7      7      6      6      7
## 24     2     2     2     2     2      2      2      2      2      2      4
## 25     1     1     1     1     0      0      0      0      0      0      0
## 26     0     0     0     0     0      0      0      0      0      0      0
## 27     0     0     1     1     1      1      1      1      1      1      1
## 28     1     1     1     1     1      1      1      1      1      1      1
## 29     0     0     0     0     0      0      0      0      0      0      0
## 30     1     0     1     1     1      1      1      1      1      2      3
## 31     0     0     0     0     0      0      0      0      0      0      0
## 32     0     0     0     0     0      0      0      0      0      0      1
## 33     0     0     0     0     0      2      2      3      8      9      9
## 34     0     0     0     0     0      0      0      0      0      0      0
## 35     0     0     0     0     0      0      0      0      0      0      0
## 36     0     0     0     0     0      0      0      0      0      0      5
## 37     0     0     0     0     0      0      0      0      0      0      0
## 38     1     1     1     1     1      1      1      2      2      2      2
## 39     0     0     0     0     0      0      0      0      0      0      0
## 40     0     0     0     0     0      0      0      0      0      0      0
## 41     0     0     0     0     0      0      0      0      0      0      0
## 42     2     2     2     3     3      3      3      3      3      4      4
## 43     0     0     0     0     0      0      0      0      0      0      0
## 44     0     0     0     0     0      0      0      0      1      1      1
## 45     0     0     0     0     0      0      0      0      0      0      0
## 46     0     0     0     0     0      0      0      0      0      0      0
## 47     0     0     0     0     0      0      0      0      0      0      0
## 48     0     0     0     0     0      0      0      0      0      0      5

# Save the cleaned data
write.csv(data, "cleaned_data.csv", row.names = FALSE)

Further analysis

# Set the new column names
new_column_names <- c("GENOTYPE", "FOOD", "SEX", "INFECTION", "REPLICATE",
                      "2024-03-04 19:15:00", "2024-03-05 09:30:00", "2024-03-05 13:20:00",
                      "2024-03-05 17:40:00", "2024-03-06 09:10:00", "2024-03-06 13:05:00",
                      "2024-03-06 16:59:00", "2024-03-07 10:07:00", "2024-03-07 13:00:00",
                      "2024-03-07 17:00:00", "2024-03-08 09:00:00", "2024-03-08 13:07:00",
                      "2024-03-08 17:00:00", "2024-03-09 10:05:00", "2024-03-11 13:00:00",
                      "2024-03-12 12:40:00")

# Rename the columns
colnames(data) <- new_column_names

# Reshape the 'data' dataframe from wide to long format using the pivot_longer function
data_long <- data %>%
  pivot_longer(
    cols = 6:21, 
    names_to = "Time_Point",
    values_to = "Deaths"
  )

# Convert the 'Time_Point' column in 'data_long' to POSIXct format (date-time class)
data_long <- data_long %>% mutate(Time_Point = as.POSIXct(Time_Point))
# Print the 'data_long' dataframe to the console
print(data_long)

## # A tibble: 768 × 7
##    GENOTYPE     FOOD   SEX   INFECTION REPLICATE Time_Point          Deaths
##    <chr>        <chr>  <chr> <chr>     <chr>     <dttm>               <dbl>
##  1 daxx[NP4778] Normal M     vehicle   1         2024-03-04 19:15:00      0
##  2 daxx[NP4778] Normal M     vehicle   1         2024-03-05 09:30:00      0
##  3 daxx[NP4778] Normal M     vehicle   1         2024-03-05 13:20:00      0
##  4 daxx[NP4778] Normal M     vehicle   1         2024-03-05 17:40:00      0
##  5 daxx[NP4778] Normal M     vehicle   1         2024-03-06 09:10:00      0
##  6 daxx[NP4778] Normal M     vehicle   1         2024-03-06 13:05:00      0
##  7 daxx[NP4778] Normal M     vehicle   1         2024-03-06 16:59:00      0
##  8 daxx[NP4778] Normal M     vehicle   1         2024-03-07 10:07:00      0
##  9 daxx[NP4778] Normal M     vehicle   1         2024-03-07 13:00:00      0
## 10 daxx[NP4778] Normal M     vehicle   1         2024-03-07 17:00:00      0
## # ℹ 758 more rows

Custom Function analyse_spreadsheet

devtools::source_url('https://raw.githubusercontent.com/jdenavascues/Survival_functions/main/infection.R')

## ℹ SHA-1 hash of file is "4ea82d185e8b7cb220ab4d8aa8e3807f14b3f386"

head(data_long)

## # A tibble: 6 × 7
##   GENOTYPE     FOOD   SEX   INFECTION REPLICATE Time_Point          Deaths
##   <chr>        <chr>  <chr> <chr>     <chr>     <dttm>               <dbl>
## 1 daxx[NP4778] Normal M     vehicle   1         2024-03-04 19:15:00      0
## 2 daxx[NP4778] Normal M     vehicle   1         2024-03-05 09:30:00      0
## 3 daxx[NP4778] Normal M     vehicle   1         2024-03-05 13:20:00      0
## 4 daxx[NP4778] Normal M     vehicle   1         2024-03-05 17:40:00      0
## 5 daxx[NP4778] Normal M     vehicle   1         2024-03-06 09:10:00      0
## 6 daxx[NP4778] Normal M     vehicle   1         2024-03-06 13:05:00      0

# Separate the date and time from the Time_Point column
data_long <- data_long %>%
  mutate(
    date = as.Date(Time_Point),
    time = format(as.POSIXct(Time_Point), format = "%H:%M:%S")
  )

# Rename columns to match the desired output
data_long <- data_long %>%
  rename(
    Genotype = GENOTYPE,
    Treatment_1 = FOOD,
    Sex = SEX,
    Treatment_2 = INFECTION,
    Replicate = REPLICATE,
    deaths = Deaths
  ) %>%
  select(Genotype, Treatment_1, Sex, Treatment_2, Replicate, deaths, date, time)

# Display the transformed data
print(data_long)

## # A tibble: 768 × 8
##    Genotype     Treatment_1 Sex   Treatment_2 Replicate deaths date       time  
##    <chr>        <chr>       <chr> <chr>       <chr>      <dbl> <date>     <chr> 
##  1 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-04 19:15…
##  2 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-05 09:30…
##  3 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-05 13:20…
##  4 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-05 17:40…
##  5 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-06 09:10…
##  6 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-06 13:05…
##  7 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-06 16:59…
##  8 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-07 10:07…
##  9 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-07 13:00…
## 10 daxx[NP4778] Normal      M     vehicle     1              0 2024-03-07 17:00…
## # ℹ 758 more rows

Now we can provide the wrapper function with all we need for a quick prelim work

data_long <- analyse_spreadsheet(data_long, cph = TRUE)

## 
## ---
## Loading event data...
## `analyse_spreadsheet` will read the data from a dataframe object.
##  No checks on the data will be performed at this point.
## 
## ---
## Loading experiment metadata...
## 
## ---
## Establishing replicates size...
## No replicate size argument given and no information found in the metadata,or metadata is not provided.
## A default value of rep_size = 20 will be used.
## 
## ---
## Harmonising data-variable names and cleaning up data...
## 
## You do not seem to have any column with censoring data, or it is NOT named in any of the usual ways ("censored", "censoring", and derivatives).
## `analyze_spreadsheet` will continue assuming that all individuals were censored after the last observational timepoint.
## If this is not what happened, verify your dataset and, if necessary, rename the columns.
## 
## You do not seem to have any column with specifying the units used to describe the dose of a treatment.
## `analyze_spreadsheet` will continue assuming that this is not relevant.
## If this is not the case, verify your dataset and, if necessary, rename the columns.
## 
## You do not seem to have any column with specifying the dose of a treatment.
## `analyze_spreadsheet` will continue assuming that this is not relevant.
## If this is not the case, verify your dataset and, if necessary, rename the columns.
## 
## The usual explanatory variables are: "genotype", "treatment(s)", "dose", "sex" and "replicate".
## You seem to have all 5 of them.
## 
## ---
## Checking data recording mode (new/cumulative)...
## 
## You have not provided information about whether events were recorded cumulatively.
## `analyse_spreadsheet` will attempt to deduce this from the data/metadata.
## 
## 
## There is no input information about whether events were recorded cumulatively.
## `analyse_spreadsheet` will attempt to deduce this from the data.
## 
## 
## `analyze_spreadsheet` finds evidence of cumulative recording in a majority (~94%) of strata replicates.
## It will be assumed that "cumulative" events were recorded at each observationand `analyze_spreadsheet` will attempt to repair the data.
## 
##  Recording mode established as "cumulative".
## 
## ---
## Establishing time-to-event intervals...
## 
## Establishing individual events (non-cumulative)...
## 
## ---
## Converting data from time-based to event-based...
## 
## ---
## Adding implicit (endpoint) or missed censoring events...
## 
## ---
## Quick'n'dirty evaluation of Proportional Hazards in the data...
## 
##  Schoenfeld test shows PH assumption is NOT respected:
## 
##       GLOBAL 
## 1.303293e-05

Knit

# Load the necessary library
library(kableExtra)

# Create an HTML table from the 'data_long' dataframe using the kable function
# Style the HTML table with the kable_styling function
tb <- knitr::kable(data_long, format = "html")
tb_styled <- kable_styling(tb, "striped", position = "left", font_size = 10, html_font = '"Arial", arial, helvetica, sans-serif')
# Print the styled table
tb_styled

genotype	treatment_1	sex	treatment_2	replicate	time_to_event	event_type
daxx[NP4778]	Normal	M	vehicle	2	22.4 hours	1
daxx[NP4778]	Normal	M	P.ent.	1	14.2 hours	1
daxx[NP4778]	Normal	M	P.ent.	1	14.2 hours	1
daxx[NP4778]	Normal	M	P.ent.	1	37.9 hours	1
daxx[NP4778]	Normal	M	P.ent.	2	14.2 hours	1
daxx[NP4778]	Normal	M	P.ent.	2	18.1 hours	1
daxx[NP4778]	Normal	M	P.ent.	2	18.1 hours	1
daxx[NP4778]	Normal	M	P.ent.	2	62.9 hours	1
daxx[NP4778]	Normal	M	P.ent.	2	85.8 hours	1
daxx[NP4778]	Normal	M	P.ent.	3	14.2 hours	1
daxx[NP4778]	Normal	M	P.ent.	3	18.1 hours	1
daxx[NP4778]	Normal	M	P.ent.	3	37.9 hours	1
daxx[NP4778]	Normal	M	P.ent.	3	41.8 hours	1
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	1
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	14.2 hours	1
daxx[NP4778]	Normal	F	vehicle	3	14.2 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	vehicle	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	1	14.2 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	14.2 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	93.8 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	14.2 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	14.2 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	22.4 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	Normal	F	P.ent.	3	162.0 hours	1
daxx[NP4778]	HCr 50mM	M	P.ent.	1	18.1 hours	1
daxx[NP4778]	HCr 50mM	M	P.ent.	1	37.9 hours	1
daxx[NP4778]	HCr 50mM	M	P.ent.	2	18.1 hours	1
daxx[NP4778]	HCr 50mM	M	P.ent.	3	69.8 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	62.9 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	162.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	1	185.0 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	2	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	2	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	2	37.9 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	2	41.8 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	3	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	3	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	3	22.4 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	3	45.7 hours	1
daxx[NP4778]	HCr 50mM	F	vehicle	3	111.0 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	18.1 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	85.8 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	3	14.2 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	3	37.9 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	1
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	1
Dahomey	Normal	M	vehicle	1	14.2 hours	1
Dahomey	Normal	M	vehicle	3	62.9 hours	1
Dahomey	Normal	M	P.ent.	1	37.9 hours	1
Dahomey	Normal	M	P.ent.	3	14.2 hours	1
Dahomey	Normal	M	P.ent.	3	62.9 hours	1
Dahomey	Normal	M	P.ent.	3	162.0 hours	1
Dahomey	Normal	M	P.ent.	3	185.0 hours	1
Dahomey	Normal	F	vehicle	2	185.0 hours	1
Dahomey	Normal	F	vehicle	3	85.8 hours	1
Dahomey	Normal	F	vehicle	3	85.8 hours	1
Dahomey	Normal	F	vehicle	3	93.8 hours	1
Dahomey	Normal	F	vehicle	3	111.0 hours	1
Dahomey	Normal	F	vehicle	3	111.0 hours	1
Dahomey	Normal	F	vehicle	3	111.0 hours	1
Dahomey	Normal	F	vehicle	3	111.0 hours	1
Dahomey	Normal	F	vehicle	3	111.0 hours	1
Dahomey	Normal	F	vehicle	3	162.0 hours	1
Dahomey	Normal	F	P.ent.	3	185.0 hours	1
Dahomey	Normal	F	P.ent.	3	185.0 hours	1
Dahomey	Normal	F	P.ent.	3	185.0 hours	1
Dahomey	Normal	F	P.ent.	3	185.0 hours	1
Dahomey	Normal	F	P.ent.	3	185.0 hours	1
Dahomey	HCr 50mM	M	vehicle	2	14.2 hours	1
Dahomey	HCr 50mM	M	vehicle	2	93.8 hours	1
Dahomey	HCr 50mM	M	P.ent.	3	18.1 hours	1
Dahomey	HCr 50mM	M	P.ent.	3	22.4 hours	1
Dahomey	HCr 50mM	M	P.ent.	3	65.8 hours	1
Dahomey	HCr 50mM	M	P.ent.	3	162.0 hours	1
Dahomey	HCr 50mM	F	vehicle	2	111.0 hours	1
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	1
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	1
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	1
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	1
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	1
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
Dahomey	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
Dahomey	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	1	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	Normal	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
Dahomey	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
Dahomey	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	2	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	Normal	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	F	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
daxx[NP4778]	Normal	M	P.ent.	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
Dahomey	Normal	F	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	F	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
daxx[NP4778]	HCr 50mM	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
Dahomey	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0
daxx[NP4778]	Normal	M	vehicle	3	185.0 hours	0

Table 1. The dataset comprises survival data of flies subjected to various treatments, detailing genotype, sex, treatment conditions, replicate number, time to event, and event type for each fly. Genotypes include daxx[NP4778] and Dahomey, with treatments such as Normal, vehicle, P.ent., and HCr 50mM. The sex of the flies is denoted as M for male and F for female. The dataset includes replicate numbers ranging from 1 to 3. The time_to_event variable records the duration in hours until an event occurs, with event_type indicating event occurrence (1 for event, 0 for no event). For instance, a male daxx[NP4778] fly treated with vehicle in replicate 2 experienced an event at 22.4 hours, while a female daxx[NP4778] fly treated with P.ent. in replicate 1 experienced an event at 14.2 hours. Conversely, a male Dahomey fly treated with P.ent. in replicate 2 did not experience an event within 185.0 hours. This dataset is primed for survival analysis, such as Kaplan-Meier and Cox proportional hazards regression, to evaluate the impact of treatments and genotypes on fly survival times.

Hypothesis Testing

Different hypotheses:

Are Pseudomonas entomophila really killing flies?

If P.ent. are pathogenic,

• Are Drosophila males and females different in their susceptibility?
• Are daxx^NP4778 mutants more susceptible than Dahomey wild-types?
• Does raising the larvae in crotonic acid affect the adult immuno-competence?
• Do any of the previous variables interact, i.e. susceptibility only changes in certain combinations of the variables?

# Fit a survival model using the surv_fit function
library(survival)
library(survminer)

# Fit a survival curve
pathogenicity <- survfit(Surv(time_to_event, event_type) ~ treatment_2, data = data_long) # do Pseudomonas kill flies?

# Print the result to check
print(pathogenicity)

## Call: survfit(formula = Surv(time_to_event, event_type) ~ treatment_2, 
##     data = data_long)
## 
##                       n events median 0.95LCL 0.95UCL
## treatment_2=P.ent.  487     91     NA      NA      NA
## treatment_2=vehicle 492     62     NA      NA      NA

# Calculate the p-value for the survival model using the surv_pvalue function
surv_pvalue(pathogenicity, method = "S1", test.for.trend = FALSE, combine = FALSE)[1:3]

##      variable   pval    method
## 1 treatment_2 0.0105 Peto-Peto

# Fit a survival model using the surv_fit function
sexspec <- surv_fit(Surv(time_to_event, event_type) ~ sex, data = data_long) # does sex affect survival?

# Calculate the p-value for the survival model using the surv_pvalue function
surv_pvalue(sexspec, method = "1", test.for.trend = FALSE, combine = FALSE)[1:3]

##   variable         pval   method
## 1      sex 4.978296e-15 Log-rank

# Plot the survival curves using the ggsurvplot function
ggsurvplot(sexspec) + ggtitle("Survival Probability by Sex")

Figure 1. This Kaplan-Meier survival curve illustrates the survival probability of flies over time, categorized by sex (male and female), with the x-axis representing time in hours and the y-axis representing survival probability, ranging from 0 to 1. The dataset consists of survival times for male and female flies, comparing the survival of females (red line) and males (blue line) to assess whether sex impacts overall survival. Each step down in the survival curve represents a death event among the flies. The legend indicates the sex groups, with sex=F for females and sex=M for males. Key observations include male flies (blue) generally maintaining a higher survival probability compared to female flies (red) throughout the observation period, with a more pronounced decline in female survival around the 150-hour mark.

# Fit a survival model for infected flies using the surv_fit function
sexspec_inf <- surv_fit(Surv(time_to_event, event_type) ~ sex, data = dplyr::filter(data_long, treatment_2 == 'P.ent.'))

# Calculate the p-value for the survival model using the surv_pvalue function
p_value_inf <- surv_pvalue(sexspec_inf, method = "1", test.for.trend = FALSE, combine = FALSE)[1:3]
print(p_value_inf)

##   variable         pval   method
## 1      sex 2.000992e-05 Log-rank

# Plot the survival curves using the ggsurvplot function with specified colors
plot_inf <- ggsurvplot(
  sexspec_inf, 
  pval = TRUE, 
  conf.int = TRUE, 
  risk.table = TRUE,
  ggtheme = theme_minimal(),
  palette = c("#E7B800", "#2E9FDF")  # specify colors here
)

# Add a title to the plot
plot_inf$plot <- plot_inf$plot + ggtitle("Does Sex Affect Survival in Infected Flies?")

# Print the plot
print(plot_inf)

Figure 2. This Kaplan-Meier survival curve illustrates the survival probability of infected flies over time, categorized by sex (male and female), with the x-axis representing time in hours and the y-axis representing survival probability, ranging from 0 to 1. The dataset consists of survival times for male and female flies infected with a pathogen, comparing the survival of females (red line) and males (blue line) to assess whether sex impacts survival under infection. Each step down in the survival curve represents a death event among the flies. The legend indicates the sex groups, with sex=F for females and sex=M for males. Key observations include male flies (blue) generally having a slightly higher survival probability compared to female flies (red) throughout the observation period, with a noticeable drop in female survival probability around the 150-hour mark.

# Fit a survival model for non-infected flies using the surv_fit function
sexspec_mock <- surv_fit(Surv(time_to_event, event_type) ~ sex, data = dplyr::filter(data_long, treatment_2 == 'vehicle'))

# Calculate the p-value for the survival model using the surv_pvalue function
surv_pvalue(sexspec_mock, method = "1", test.for.trend = FALSE, combine = FALSE)[1:3]

##   variable         pval   method
## 1      sex 1.841913e-12 Log-rank

# Plot the survival curves using the ggsurvplot function
ggsurvplot(sexspec_mock) + ggtitle("Does Sex Affect Survival in Non-Infected Flies?")

Figure 3. This Kaplan-Meier survival curve illustrates the survival probability of non-infected flies over time, categorized by sex (male and female), with the x-axis representing time in hours and the y-axis representing survival probability, ranging from 0 to 1. The dataset consists of survival times for male and female flies, comparing the survival of females (red line) and males (blue line) to assess whether sex impacts survival in the absence of infection. Each step down in the survival curve represents a death event among the flies. The legend indicates the sex groups, with sex=F for females and sex=M for males. Key observations include male flies (blue) having a higher survival probability compared to female flies (red) throughout the observation period, with notable differences around the 100-hour mark where female survival decreases more sharply.

# Perform pairwise survival difference test using the pairwise_survdiff function
res <- pairwise_survdiff(Surv(time_to_event, event_type) ~ sex + genotype + treatment_2, data = data_long)

# Capture the p-value results as a dataframe
dt <- as.data.frame(round(res$p.value, 3))
names(dt) <- str_remove_all(names(dt), "sex=|genotype=|treatment_2=")
rownames(dt) <- str_remove_all(rownames(dt), "sex=|genotype=|treatment_2=")

# Apply conditional formatting to the dataframe and display the table
dt %>%
  mutate(across(everything(), ~ case_when(. >= 0.05 ~ cell_spec(., color = "#777777"),
                                          . < 0.05 & . >= 0.01 ~ cell_spec(., background = "#ffaacc"),
                                          . < 0.01 & . >= 0.001 ~ cell_spec(., background = "#ee7799"),
                                          . < 0.001 ~ cell_spec(., background = "#ee5577")))) %>%
  kbl(booktabs = TRUE, linesep = "", escape = FALSE) %>%
  kable_minimal(full_width = FALSE)

	F, Dahomey , P.ent.	F, Dahomey , vehicle	F, daxx[NP4778], P.ent.	F, daxx[NP4778], vehicle	M, Dahomey , P.ent.	M, Dahomey , vehicle	M, daxx[NP4778], P.ent.
F, Dahomey , vehicle	0.738	NA	NA	NA	NA	NA	NA
F, daxx[NP4778], P.ent.	0	0	NA	NA	NA	NA	NA
F, daxx[NP4778], vehicle	0	0	0.283	NA	NA	NA	NA
M, Dahomey , P.ent.	0.918	0.73	0	0	NA	NA	NA
M, Dahomey , vehicle	0.158	0.109	0	0	0.193	NA	NA
M, daxx[NP4778], P.ent.	0.127	0.193	0	0	0.114	0.005	NA
M, daxx[NP4778], vehicle	0.01	0.006	0	0	0.015	0.199	0

Table 2. This table presents pairwise p-values from survival analysis comparing different groups of flies based on sex, genotype (Dahomey and daxx[NP4778]), and treatment (P.ent. and vehicle). The groups include female and male flies under various conditions, with p-values indicating the statistical significance of survival differences between them. For instance, a p-value of 0.738 suggests no significant difference in survival between female Dahomey flies treated with vehicle and P.ent., whereas a p-value of 0.0 indicates a highly significant difference between female daxx[NP4778] flies treated with vehicle and P.ent.

  # Perform pairwise survival difference test for male flies
res <- pairwise_survdiff(Surv(time_to_event, event_type) ~ genotype + treatment_1 + treatment_2, data = filter(data_long, sex == 'M'))

# Capture the p-value results as a dataframe
dt <- as.data.frame(round(res$p.value, 3))
names(dt) <- str_remove_all(names(dt), "genotype=|treatment_1=|treatment_2=")
rownames(dt) <- str_remove_all(rownames(dt), "genotype=|treatment_1=|treatment_2=")

# Apply conditional formatting to the dataframe and display the table
dt %>%
  mutate(across(everything(), ~ case_when(. >= 0.05 ~ cell_spec(., color = "#777777"),
                                          . < 0.05 & . >= 0.01 ~ cell_spec(., background = "#ffaacc"),
                                          . < 0.01 & . >= 0.001 ~ cell_spec(., background = "#ee7799"),
                                          . < 0.001 ~ cell_spec(., background = "#ee5577")))) %>%
  kbl(booktabs = TRUE, linesep = "", escape = FALSE) %>%
  kable_minimal(full_width = FALSE)

	Dahomey, HCr 50mM, P.ent.	Dahomey, HCr 50mM, vehicle	Dahomey, Normal , P.ent.	Dahomey, Normal , vehicle	daxx[NP4778], HCr 50mM, P.ent.	daxx[NP4778], HCr 50mM, vehicle	daxx[NP4778], Normal , P.ent.
Dahomey, HCr 50mM, vehicle	0.539	NA	NA	NA	NA	NA	NA
Dahomey, Normal , P.ent.	0.804	0.41	NA	NA	NA	NA	NA
Dahomey, Normal , vehicle	0.539	0.984	0.41	NA	NA	NA	NA
daxx[NP4778], HCr 50mM, P.ent.	0.984	0.539	0.821	0.539	NA	NA	NA
daxx[NP4778], HCr 50mM, vehicle	0.115	0.323	0.083	0.323	0.115	NA	NA
daxx[NP4778], Normal , P.ent.	0.079	0.016	0.115	0.016	0.083	0.003	NA
daxx[NP4778], Normal , vehicle	0.323	0.654	0.238	0.654	0.323	0.488	0.007

Table 3. This table presents pairwise p-values from survival analysis comparing groups of flies based on genotype (Dahomey and daxx[NP4778]), treatment condition (HCr 50mM, Normal), and infection status (P.ent., vehicle). Notable comparisons include a non-significant difference between Dahomey flies treated with HCr 50mM and vehicle (p=0.539) and a significant difference between daxx[NP4778] flies treated with Normal and P.ent. versus vehicle (p=0.007).

# Perform pairwise survival difference test for female flies
res <- pairwise_survdiff(Surv(time_to_event, event_type) ~ genotype + treatment_1 + treatment_2, data = filter(data_long, sex == 'F'))

# Capture the p-value results as a dataframe
dt <- as.data.frame(round(res$p.value, 3))
names(dt) <- str_remove_all(names(dt), "genotype=|treatment_1=|treatment_2=")
rownames(dt) <- str_remove_all(rownames(dt), "genotype=|treatment_1=|treatment_2=")

# Apply conditional formatting to the dataframe and display the table
dt %>%
  mutate(across(everything(), ~ case_when(. >= 0.05 ~ cell_spec(., color = "#777777"),
                                          . < 0.05 & . >= 0.01 ~ cell_spec(., background = "#ffaacc"),
                                          . < 0.01 & . >= 0.001 ~ cell_spec(., background = "#ee7799"),
                                          . < 0.001 ~ cell_spec(., background = "#ee5577")))) %>%
  kbl(booktabs = TRUE, linesep = "", escape = FALSE) %>%
  kable_minimal(full_width = FALSE)

	Dahomey, HCr 50mM, P.ent.	Dahomey, HCr 50mM, vehicle	Dahomey, Normal , P.ent.	Dahomey, Normal , vehicle	daxx[NP4778], HCr 50mM, P.ent.	daxx[NP4778], HCr 50mM, vehicle	daxx[NP4778], Normal , P.ent.
Dahomey, HCr 50mM, vehicle	0.135	NA	NA	NA	NA	NA	NA
Dahomey, Normal , P.ent.	1	0.135	NA	NA	NA	NA	NA
Dahomey, Normal , vehicle	0.154	0.007	0.154	NA	NA	NA	NA
daxx[NP4778], HCr 50mM, P.ent.	0.001	0	0.001	0.048	NA	NA	NA
daxx[NP4778], HCr 50mM, vehicle	0	0	0	0.001	0.183	NA	NA
daxx[NP4778], Normal , P.ent.	0	0	0	0	0.027	0.656	NA
daxx[NP4778], Normal , vehicle	0.005	0	0.005	0.228	0.463	0.016	0.002

Table 4. This table presents pairwise p-values from survival analysis comparing groups of flies based on genotype (Dahomey and daxx[NP4778]), treatment condition (HCr 50mM, Normal), and infection status (P.ent., vehicle). Significant differences include Dahomey flies treated with HCr 50mM and P.ent. versus vehicle (p=0.135) and a highly significant difference between daxx[NP4778] flies treated with HCr 50mM and P.ent. versus vehicle (p=0).

# palette <- c('#85C1E9', '#999999', '#E74C3C', #'#F1C40F'
#              '#4444DD', '#000000', '#A2103C') # '#F39C12'

title <- 'Susceptibility to *S. marcescens*'
model <- surv_fit(Surv(time_to_event, event_type) ~ genotype + treatment_2, data = filter(data_long, sex == 'F'))
g <- ggsurvplot(model,
                pval = TRUE,                       # adds pval
                conf.int = TRUE,                   # adds 95% confidence interval
                conf.int.alpha = 0.1,              # makes it more transparent
                surv.median.line = "v",            # adds median points
                #palette = palette,
                xlab = "Time (hours)",             # remove x axis label
                ylab = "Survival Probability",     # y axis label
                #linetype = line_type,
                title = title,
                font.legend = c(7),                # legend size
                legend = "bottom")                 # legend position

## Warning in .add_surv_median(p, fit, type = surv.median.line, fun = fun, :
## Median survival not reached.

g

Figure 4. This Kaplan-Meier survival curve illustrates the survival probability of flies over time, categorized by genotype (Dahomey and daxx[NP4778]) and treatment (P.ent. and vehicle), with the x-axis representing time in hours and the y-axis representing survival probability, ranging from 0 to 1. The dataset compares the survival of different genotypes under various treatment conditions to assess susceptibility to S. marcescens infection. Each step down in the survival curve represents a death event among the flies. The legend differentiates between the groups: Dahomey, P.ent. (green), Dahomey, vehicle (light green), daxx[NP4778], P.ent. (cyan), and daxx[NP4778], vehicle (purple). Key observations include significant differences in survival probabilities, with a p-value of less than 0.0001 indicating highly significant differences between the groups.

# Generate all combinations of unique genotypes and treatments
exgrid <- expand.grid(unique(sort(data_long$genotype, decreasing = TRUE)), unique(sort(data_long$treatment_2, decreasing = TRUE)))
exgrid <- exgrid[order(exgrid$Var2),]
lab_strata <- paste(exgrid$Var1, exgrid$Var2, sep=" | ")

print(lab_strata)

## [1] "daxx[NP4778] | vehicle" "Dahomey | vehicle"      "daxx[NP4778] | P.ent." 
## [4] "Dahomey | P.ent."

lab_strata <- c("*myoIA>ctrl^KD^* | Sucrose", "*myoIA>Etl1^KD^* | Sucrose", "*ken^1^* | Sucrose", "*myoIA>ctrl^KD^* | S.marcescens", "*myoIA>Etl1^KD^* | S.marcescens", "*ken^1^* | S.marcescens")
lab_strata

## [1] "*myoIA>ctrl^KD^* | Sucrose"      "*myoIA>Etl1^KD^* | Sucrose"     
## [3] "*ken^1^* | Sucrose"              "*myoIA>ctrl^KD^* | S.marcescens"
## [5] "*myoIA>Etl1^KD^* | S.marcescens" "*ken^1^* | S.marcescens"

# Define line types and color palette
line_type <- c("solid", "dashed", "dotted", "dotdash", "longdash", "twodash")
palette <- c("red", "blue", "green", "purple", "orange", "brown")
x <- rep(c(1:20), 6)

variable <- unlist(lapply(lab_strata, rep, 20))
value <- c(5 + rnorm(20) / 5, 4 + rnorm(20) / 5, 3 + rnorm(20) / 5, 2 + rnorm(20) / 5, 1 + rnorm(20) / 5, rnorm(20) / 5)
df <- data.frame(x, variable, value)

# Create a line plot using ggplot
d <- ggplot(df, aes(x = x, y = value, group = variable, colour = variable)) +
  geom_line(aes(linetype = variable, colour = variable)) +
  scale_linetype_manual(breaks = lab_strata, values = line_type, labels = lab_strata) +
  scale_colour_manual(breaks = lab_strata, values = palette, labels = lab_strata) +
  theme(legend.text = element_text(size = 5), legend.title = element_text(size = 6), legend.key.height = unit(1 / 6, 'in')) +
  xlab("Time (hours)") + ylab("Survival Probability") + ggtitle("Survival Probability by Genotype and Treatment")

print(d)

Figure 5. The plot titled “Survival Probability by Genotype and Treatment” illustrates the survival probability of flies over time, categorized by genotype and treatment. The x-axis denotes time in hours, while the y-axis represents survival probability. Six groups are represented: myoIA>ctrl^KD | Sucrose (solid red line), myoIA>Etl1^KD | Sucrose (dashed blue line), ken¹ | Sucrose (dotted green line), myoIA>ctrl^KD | S.marcescens (dotdash purple line), myoIA>Etl1^KD | S.marcescens (longdash orange line), and ken¹ | S.marcescens (twodash brown line). The legend on the right correlates line type and color to each group, facilitating comparison of survival rates across different genotypes under two treatment conditions, sucrose and S. marcescens.

# Reorder lab_strata vector and extract levels of strata variable
lab_strata[c(1,3,2,4,6,5)]

## [1] "*myoIA>ctrl^KD^* | Sucrose"      "*ken^1^* | Sucrose"             
## [3] "*myoIA>Etl1^KD^* | Sucrose"      "*myoIA>ctrl^KD^* | S.marcescens"
## [5] "*ken^1^* | S.marcescens"         "*myoIA>Etl1^KD^* | S.marcescens"

l <- levels(g$data.survtable$strata)[c(6,2,4,5,1,3)]
l

## [1] NA                                          
## [2] "genotype=Dahomey, treatment_2=vehicle"     
## [3] "genotype=daxx[NP4778], treatment_2=vehicle"
## [4] NA                                          
## [5] "genotype=Dahomey, treatment_2=P.ent. "     
## [6] "genotype=daxx[NP4778], treatment_2=P.ent. "

# Add custom color scales to the plot
g$plot +
  scale_colour_manual(name='', breaks=l, values=palette, labels=lab_strata[c(1,3,2,4,6,5)], guide=guide_legend(nrow = 3)) +
  scale_fill_manual(name='', breaks=l, values=palette, labels=lab_strata[c(1,3,2,4,6,5)], guide=guide_legend(nrow = 3)) +
  scale_linetype_manual(name='', breaks=l, values=line_type, labels=lab_strata[c(1,3,2,4,6,5)], guide=guide_legend(nrow = 3)) +
  theme(legend.text=element_markdown(), plot.title = element_markdown())

Figure 6. The plot titled “Susceptibility to S. marcescens” shows the survival probability of flies over time, categorized by genotype and treatment. The x-axis indicates time in hours, and the y-axis represents survival probability. The survival curves for four groups are displayed: ken¹ | Sucrose (blue line), myoIA>Etl1^KD | Sucrose (green line), ken¹ | S.marcescens (orange line), and myoIA>Etl1^KD | S.marcescens (brown line). The legend at the bottom of the plot matches the line color to each group. The plot includes a p-value of < 0.0001, indicating a significant difference in survival probability among the groups. This visualization facilitates the comparison of survival rates across different genotypes under two treatment conditions, sucrose, and S. marcescens.