deSolve (version 1.2-1)

ccl4model: the CCl4 inhalation model

Description

the CCl4 inhalation model implemented in .Fortran

Usage

ccl4model(times, y, parms, ...)

Arguments

times

time sequence for which the model has to be integrated

y

the initial values for the state variables ("AI","AAM","AT","AF","AL","CLT" and "AM"), in that order.

parms

vector or list holding the ccl4 model parameters; see the example for the order in which these have to be defined

...

any other parameters passed to the integrator ode (which solves the model)

Details

The model is implemented primarily to demonstrate the linking of FORTRAN with R-code. The source can be found in the dynload subdirectory of the package.

See Also

try demo(CCL4model) for how this model has been fitted to the dataset ccl4data aquaphy, another Fortran model, describing growth in aquatic phytoplankton.

Examples

##====================================
  ## parameter values
  ##====================================
  
  Pm <- c(
  
   ### Physiological parameters
   BW= 0.182,   # Body weight (kg)
   QP= 4.0  ,   # Alveolar ventilation rate (hr^-1)
   QC= 4.0  ,   # Cardiac output (hr^-1)
   VFC= 0.08,   # Fraction fat tissue (kg/(kg/BW))
   VLC= 0.04,   # Fraction liver tissue (kg/(kg/BW))
   VMC= 0.74,   # Fraction of muscle tissue (kg/(kg/BW))
   QFC= 0.05,   # Fractional blood flow to fat ((hr^-1)/QC
   QLC= 0.15,   # Fractional blood flow to liver ((hr^-1)/QC)
   QMC= 0.32,   # Fractional blood flow to muscle ((hr^-1)/QC)
  
   ## Chemical specific parameters for chemical
   PLA= 16.17,  # Liver/air partition coefficient
   PFA= 281.48, # Fat/air partition coefficient
   PMA= 13.3,   # Muscle/air partition coefficient
   PTA= 16.17,  # Viscera/air partition coefficient
   PB= 5.487,   # Blood/air partition coefficient
   MW= 153.8,   # Molecular weight (g/mol)
   VMAX= 0.04321671, # Max. velocity of metabolism (mg/hr) -calibrated
   KM= 0.4027255,    # Michaelis-Menten constant (mg/l) -calibrated
  
   # Parameters for simulated experiment
   CONC= 1000,  # Inhaled concentration
   KL= 0.02,    # Loss rate from empty chamber /hr
   RATS= 1.0,   # Number of rats enclosed in chamber
   VCHC= 3.8    # Volume of closed chamber (l)
   )
  
  ##====================================
  ## state variables 
  ##====================================
  y <- c(AI = 21,   # total mass , mg
         AAM = 0,
         AT = 0,
         AF = 0,
         AL = 0,
         CLT = 0, ### area under the conc.-time curve in the liver
         AM = 0   ### the amount metabolized (AM)
         )
  
  ##====================================
  ## Model application
  ##====================================
  
  times <- seq(0,6,by=0.1)
  
  # initial inhaled concentration-calibrated
  conc <- c(26.496,90.197,245.15,951.46) 
  
  plot(ChamberConc ~ time,data=ccl4data,xlab="Time (hours)",
         xlim=range(c(0,ccl4data$time)),
         ylab="Chamber Concentration (ppm)",
         log="y",main = "ccl4model")
  
  for (cc in conc)
  {
    Pm["CONC"] <-cc
  
    VCH <- Pm[["VCHC"]] - Pm[["RATS"]]*Pm[["BW"]]
    AI0 <- VCH * Pm[["CONC"]]*Pm[["MW"]]/24450 
    y["AI"] <- AI0
    
    # run the model:
    out <- as.data.frame(ccl4model(times,y,Pm))
    lines(out$time,out$CP,lwd=2)
  }
  
  legend("topright",lty=c(NA,1),pch=c(1,NA),lwd=c(NA,2),
         legend=c("data","model"))