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1.
Arch Toxicol ; 88(10): 1855-79, 2014 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-25182421

RESUMEN

There is a need of guidance on how local irritancy data should be incorporated into risk assessment procedures, particularly with respect to the derivation of occupational exposure limits (OELs). Therefore, a board of experts from German committees in charge of the derivation of OELs discussed the major challenges of this particular end point for regulatory toxicology. As a result, this overview deals with the question of integrating results of local toxicity at the eyes and the upper respiratory tract (URT). Part 1 describes the morphology and physiology of the relevant target sites, i.e., the outer eye, nasal cavity, and larynx/pharynx in humans. Special emphasis is placed on sensory innervation, species differences between humans and rodents, and possible effects of obnoxious odor in humans. Based on this physiological basis, Part 2 describes a conceptual model for the causation of adverse health effects at these targets that is composed of two pathways. The first, "sensory irritation" pathway is initiated by the interaction of local irritants with receptors of the nervous system (e.g., trigeminal nerve endings) and a downstream cascade of reflexes and defense mechanisms (e.g., eyeblinks, coughing). While the first stages of this pathway are thought to be completely reversible, high or prolonged exposure can lead to neurogenic inflammation and subsequently tissue damage. The second, "tissue irritation" pathway starts with the interaction of the local irritant with the epithelial cell layers of the eyes and the URT. Adaptive changes are the first response on that pathway followed by inflammation and irreversible damages. Regardless of these initial steps, at high concentrations and prolonged exposures, the two pathways converge to the adverse effect of morphologically and biochemically ascertainable changes. Experimental exposure studies with human volunteers provide the empirical basis for effects along the sensory irritation pathway and thus, "sensory NOAEChuman" can be derived. In contrast, inhalation studies with rodents investigate the second pathway that yields an "irritative NOAECanimal." Usually the data for both pathways is not available and extrapolation across species is necessary. Part 3 comprises an empirical approach for the derivation of a default factor for interspecies differences. Therefore, from those substances under discussion in German scientific and regulatory bodies, 19 substances were identified known to be human irritants with available human and animal data. The evaluation started with three substances: ethyl acrylate, formaldehyde, and methyl methacrylate. For these substances, appropriate chronic animal and a controlled human exposure studies were available. The comparison of the sensory NOAEChuman with the irritative NOAECanimal (chronic) resulted in an interspecies extrapolation factor (iEF) of 3 for extrapolating animal data concerning local sensory irritating effects. The adequacy of this iEF was confirmed by its application to additional substances with lower data density (acetaldehyde, ammonia, n-butyl acetate, hydrogen sulfide, and 2-ethylhexanol). Thus, extrapolating from animal studies, an iEF of 3 should be applied for local sensory irritants without reliable human data, unless individual data argue for a substance-specific approach.


Asunto(s)
Contaminantes Ocupacionales del Aire/toxicidad , Irritantes/toxicidad , Exposición Profesional/análisis , Contaminantes Ocupacionales del Aire/química , Contaminantes Ocupacionales del Aire/farmacocinética , Ojo/efectos de los fármacos , Humanos , Irritantes/química , Irritantes/farmacocinética , Nivel sin Efectos Adversos Observados , Exposición Profesional/efectos adversos , Sistema Respiratorio/efectos de los fármacos , Medición de Riesgo , Umbral Sensorial , Solubilidad , Valores Limites del Umbral
2.
Arch Toxicol ; 86(3): 423-30, 2012 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-22076108

RESUMEN

The aim of the study was to evaluate the predictive potential of three different mathematical models for the percutaneous penetration of industrial solvents with respect to our experimental data. Percutaneous penetration rates (fluxes) from diffusion cell experiments of 11 chemicals were compared with fluxes predicted by mathematical models. The chemicals considered were three glycol ethers (2-butoxyethanol, diethylene glycol monobutyl ether and 1-ethoxy-2-propanol), three alcohols (ethanol, isopropanol and methanol), two glycols (ethylene glycol and 1,2-propanediol), one aromatic hydrocarbon (toluene) and two aromatic amines (aniline and o-toluidine). For the mathematical prediction of fluxes, models described by Fiserova-Bergerova et al. (Am J Ind Med 17:617-635 1990), Guy and Potts (Am J Ind Med 23:711-719 1993) and Wilschut et al. (Chemosphere 30:1275-1296 1995) were used. The molecular weights, octanol-water partition coefficients (LogP) and water solubilities of the compounds were obtained from a database for modelling. The fit between the mathematically predicted and experimentally determined fluxes was poor (R(2) = 0.04-0.29; linear regression). The flux differences ranged up to a factor of 412. For 4 compounds, the Guy and Potts model showed a closer fit with the experimental flux than the other models. The Wilschut et al. model showed a lower flux difference for 4 compounds as compared to experimental data than the models of Fiserova-Bergerova et al. and Guy and Potts. The Fiserova-Bergerova et al. model showed for 3 compounds a lower flux difference to experimental data than the other models. This study demonstrates large differences between mathematically predicted and experimentally determined fluxes. The percutaneous penetration as determined in diffusion cell experiments may be considerably overestimated as well as underestimated by mathematical models. Although the number of compounds in our comparison study is small, the results point out that none of the mathematical model has significant advantages.


Asunto(s)
Absorción Cutánea , Humanos , Modelos Lineales , Modelos Teóricos , Medición de Riesgo
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