Risk assessment dosimetry model for inhaled particulate matter: I. Human subjects
Pollutant particulate matter (PM) is a serious global problem, presenting a threat to the health and well being of human subjects. Inhalation exposures tests with surrogate animals can be performed to estimate the threat. However, it is difficult to extrapolate the findings of animal tests to human...
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Veröffentlicht in: | Toxicology letters 2003-02, Vol.138 (1), p.119-132 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Pollutant particulate matter (PM) is a serious global problem, presenting a threat to the health and well being of human subjects. Inhalation exposures tests with surrogate animals can be performed to estimate the threat. However, it is difficult to extrapolate the findings of animal tests to human conditions. In this two-part series, interspecies dosimetry models especially designed for implementation with risk assessment protocols are presented. In Part I, the mathematical integrity of the source model per se was tested with data from human subjects, and theoretical predictions agreed well with experimental measurements. In Part II, for surrogate (rat) simulations, appropriate algorithms for morphologies and ventilatory parameters were used as subroutines in the validated model. We conducted a comprehensive series of computer simulations describing the behavior of a representative air pollutant, secondary cigarette smoke. For risk assessment interests, a range of states from rest to exercise was considered. PM hygroscopicity had a pronounced effect on deposition in a complex but systematic manner, in humans and rats: deposition was increased for particles larger than about 1 μm, but was decreased for particles smaller than about 0.1 μm. The results clearly indicate that dosimetry models can be effectively used to a priori determine the laboratory conditions necessary for animals tests to accurately mimic human conditions. Moreover, the use of interspecies models is very cost effective. We propose, therefore, that mathematical models be used in a complementary manner with inhalation exposure experiments and be actively integrated into PM risk assessment protocols. |
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ISSN: | 0378-4274 1879-3169 |
DOI: | 10.1016/S0378-4274(02)00411-3 |