Acanthamoeba spp: Dose Response Models

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Acanthamoeba Spp.

Author: Sushil Tamrakar


General overview of Acanthamoeba spp.

Acanthamoeba is a microscopic, free-living amoeba that can cause rare, but severe infections of the eye, skin, and central nervous system. This amoeba is found worldwide in the environment in water and soil. It can be spread to the eyes through contact lens use, cuts, bruises or inhalation. Most people will be exposed to Acanthamoeba during their lifetime, but very few will become sick from this exposure [1]



Summary Data

Culbertson et al. (1966) studied pathogenicity of HN-3 strain of Hartmannlelid (Acanthamoeba) amoeba. The amoebae were inoculated intranasally to groups of mice and responses were recorded in terms of deaths, brain invasion, Acute Meningoencephalitis (AME) and Granulotomous Encephalitis [2]


Experiment serial number Reference Host type Agent strain Route # of doses Dose units Response Best fit model Optimized parameter(s) LD50/ID50
270 [2] mice intranasal 3 no of trophozoites death exponential k = 1.31E-04 5.28E+03
271 [2] mice intranasal 3 no of trophozoites brain invasion exponential k = 9.26E-04 7.49E+02
272 [2] mice intranasal 3 no of trophozoites acute meningoencephalitis exponential k = 2.6E-04 2.67E+03
*This model is preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.
Exponential and betapoisson model.jpg

Optimization Output for experiment 270

Dose response data [2]
Dose Dead Survived Total
100 2 78 80
500 4 76 80
1000 10 70 80


Goodness of fit and model selection
Model Deviance Δ Degrees
of freedom
χ20.95,1
p-value
χ20.95,m-k
p-value
Exponential 0.969 0.104 2 3.84
0.747
5.99
0.616
Beta Poisson 0.864 1 3.84
0.353
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.


Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 1.31E-04 5.59E-05 7.23E-05 8.06E-05 1.92E-04 2.03E-04 2.29E-04
ID50/LD50/ETC* 5.28E+03 3.03E+03 3.42E+03 3.62E+03 8.60E+03 9.58E+03 1.24E+04
*Not a parameter of the exponential model; however, it facilitates comparison with other models.


Parameter histogram for Exponential model (uncertainty of the parameter)
Exponential model plot, with confidence bounds around optimized model


Optimization Output for experiment 271

Dose response data [2]
Dose Brain invasion Non brain invasion Total
100 7 73 80
500 35 45 80
1000 44 36 80


Goodness of fit and model selection
Model Deviance Δ Degrees
of freedom
χ20.95,1
p-value
χ20.95,m-k
p-value
Exponential 2.46 1.15 2 3.84
0.284
5.99
0.292
Beta Poisson 1.31 1 3.84
0.252
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.


Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 9.26E-04 6.87E-04 7.39E-04 7.67E-04 1.11E-03 1.15E-03 1.22E-03
ID50/LD50/ETC* 7.49E+02 5.66E+02 6.05E+02 6.25E+02 9.04E+02 9.38E+02 1.01E+03
*Not a parameter of the exponential model; however, it facilitates comparison with other models.


Parameter histogram for exponential model (uncertainty of the parameter)
Exponential model plot, with confidence bounds around optimized model


Optimization Output for experiment 272

Dose response data [2]
Dose Acute meningoencephalitis NOT acute meningoencephalitis Total
100 2 78 80
500 8 72 80
1000 20 60 80


Goodness of fit and model selection
Model Deviance Δ Degrees
of freedom
χ20.95,1
p-value
χ20.95,m-k
p-value
Exponential 0.577 -0.00258 2 3.84
1
5.99
0.749
Beta Poisson 0.58 1 3.84
0.446
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.


Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 2.6E-04 1.49E-04 1.75E-04 1.85E-04 3.40E-04 3.58E-04 3.91E-04
ID50/LD50/ETC* 2.67E+03 1.77E+03 1.94E+03 2.04E+03 3.74E+03 3.96E+03 4.64E+03
*Not a parameter of the exponential model; however, it facilitates comparison with other models.


Parameter histogram for exponential model (uncertainty of the parameter)
Exponential model plot, with confidence bounds around optimized model



Summary

The recommended model will be based on the endpoint of response. There were three different types of responses.



References

  1. CDC. (2012). "Parasites- Acanthamoeba." Retrieved 03/30/2012, 2012, from http://www.cdc.gov/parasites/acanthamoeba/.
  2. 2.0 2.1 2.2 2.3 2.4 2.5 2.6 Culbertson, C. G., P. W. Ensminger, et al. (1966). "Hatmanella (Acanthamoeba). Experimental Chronic Granulomatuous Brain Infection Produced by New Isolates of Low Virulence." The American Journal of Clinical Pathology 46(3): 305-314