# The CCl4 Inhalation Model The CCl4 inhalation model implemented in `.Fortran` ```r 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). ## Author(s) R. Woodrow Setzer ## Examples ```r ## ================= ## 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")) ## ================================== ## An example with tracer injection ## ================================== ## every day, a conc of 2 is added to AI. ## 1. implemented as a data.frame eventdat <- data.frame(var = rep("AI", 6), time = 1:6 , value = rep(1, 6), method = rep("add", 6)) eventdat print(system.time( out <-ccl4model(times, y, Pm, events = list(data = eventdat)) )) plot(out, mfrow = c(3, 4), type = "l", lwd = 2) # 2. implemented as a function in a DLL! print(system.time( out2 <-ccl4model(times, y, Pm, events = list(func = "eventfun", time = 1:6)) )) plot(out2, mfrow=c(3, 4), type = "l", lwd = 2) ``` ## Details The model is implemented primarily to demonstrate the linking of FORTRAN with R-code. The source can be found in the /doc/examples/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.

ccl4model function