1. ERT 312 Lecture 3 Toxicology

2. What is toxicology? Qualitative and quantitative study of adverse effects of toxicants on biological organisms Toxicant - A chemical or physical agent, including dusts, fibers, noise and radiation Toxicity – property of the toxicants describing its effect on biological organisms Toxic hazard – a likelihood of damage to biological organisms based on exposure resulting from transport and other physical factors of usage

3. Trivia  Which one can be reduced?  Toxicity  Toxic Hazard

4. Things that should be clarified  Getting the toxic into your body  Ways to eliminate  Harmful effects of toxicants

5. 4 entry modes  Ingestion - mouth  Inhalation – Respiratory system  Injection – skin cut  Dermal absorption - skin

6. 3 exit modes  Excretion – kidneys, liver, lungs, skin  Detoxification – downgrade the toxicants into something less harmful  Storage – fatty tissue

7. Table 1: Various Responses to Toxicants (Crowl & Louvar, 2002) Irreversible Effects Reversible/Irreversible Effects CarcinogenDermatoxic MutagenHemotoxic Reproductive hazardHepatoxic TeratogenNephrotoxic Neurotoxic Pulmonotoxic

8. Dose vs. Response Average responseHigh responseLow response Individuals affected

9. Gaussian/Normal Distribution Curve (Equa.1) f(x) the probability (or fraction) of individuals experiencing a specific response x the response σ the standard deviation µ the mean

10. MEAN, VARIANCE, Equa.2 Equa.3

11. Example 1 A safety engineer of one leading fertilizer brand is very concern on the irritancy effect of ammonia, a main raw material used to produce the fertilizer. A toxicology study has been conducted on 75 employees. The responses are recorded on scale from 0 to 10, with 0 indicating no response and 10 indicating a high response. Details of the findings are presented in the table 2

12. Table 2 ResponseNumber of individuals affected 00 15 210 313 4 511 69 76 83 93 102

13. a. Plot a histogram of the number of individuals affected vs. the response b. Determine the mean and the standard deviation c. Plot the normal distribution on the histogram of the original data

14. Answers

15.  Mean, µ = 338/75 = 4.51  Variance, σ 2 = 374.75/75 = 5  SD, σ = 2.24

16.  Therefore; the normal distribution is,

17.  To plot a normal distribution curve, you need to convert a distribution equation to a function representing the number of individuals affected.  In this case, total individuals affected = 75

18. Refer to table 2.3 (Crowl & Louvar, 2002) xf(x)75f(x) 00.02321.74 10.05193.89 20.09487.11 310.6 413.0 4.5113.3 513.0 610.7 77.18 83.95 91.78 100.655

19. Response – Log Dose Curve  For convenience, the response is plotted versus the logarithm of the dose  If the response of the interest is death or lethality = lethal dose curve, LD  LC = lethal concentration (gas)  If the response to the chemical or agent is minor or irreversible = effective dose, ED  If the response to the agent is toxic (not lethal but irreversible) = toxic dose, TD

22. Models for Dose and Response Curves  The probit (probability unit) method is very common for single exposure computational.  The probit variable Y is related to the probability P by (Equa.4)

24. Fig X: The probit transformation converts the sigmoidal response vs. log dose curve into a straight line when plotted on a linear probit scale

25. Question 2.2 (Crowl & Louvar, 2002)  The effect of rotenone on macrosiphoniella sanborni sp. was investigated. Rotenone was applied in a medium of 0.5% saponin, containing 5% alcohol. The insects were examined and classified one day after spraying. The obtained date were:  From the given data, plot the percentage of insects affected versus the natural logarithm of dose  Convert the data to a probit variable, and plot the probit versus the natural logarithm of the dose. If the results is linear, determine a straight line that fits the data. Compare the probit and number of insects affected predicted by the straight line fit to the actual data Dose (mg/l)Number of insectsNumber affected 10.25044 7.74942 5.14624 3.84816 2.6506 0490

26. Probit Variable Y  Equa.5 k 1, k 2 Probit parameters VCausative factor represents the dose

28.  OTOH, conversion from probits to percentage is given by (Equa.6) erf the error function of Y