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Establishing short-term occupational exposure limits (STELs) for sensory irritants using predictive and in silico respiratory rate depression (RD50) models.
Russell, Anthony J; Vincent, Melissa; Buerger, Amanda N; Dotson, Scott; Lotter, Jason; Maier, Andrew.
Afiliación
  • Russell AJ; Stantec (ChemRisk), Cincinnati, OH, USA.
  • Vincent M; Stantec (ChemRisk), Cincinnati, OH, USA.
  • Buerger AN; Tox Strategies, Ashville, NC, USA.
  • Dotson S; Stantec (ChemRisk), Cincinnati, OH, USA.
  • Lotter J; Tox Strategies, Ashville, NC, USA.
  • Maier A; Stantec (ChemRisk), Cincinnati, OH, USA.
Inhal Toxicol ; 36(1): 13-25, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38252504
ABSTRACT
Sensory irritation is a health endpoint that serves as the critical effect basis for many occupational exposure limits (OELs). Schaper 1993 described a significant relationship with high correlation between the measured exposure concentration producing a 50% respiratory rate decrease (RD50) in a standard rodent assay and the American Conference of Governmental Industrial Hygienists (ACGIH®) Threshold Limit Values (TLVs®) as time-weighted averages (TWAs) for airborne chemical irritants. The results demonstrated the potential use of the RD50 values for deriving full-shift TWA OELs protective of irritant responses. However, there remains a need to develop a similar predictive model for deriving workplace short-term exposure limits (STELs) for sensory irritants. The aim of our study was to establish a model capable of correlating the relationship between RD50 values and published STELs to prospectively derive short-term exposure OELs for sensory irritants. A National Toxicology Program (NTP) database that included chemicals with both an RD50 and established STELs was used to fit several linear regression models. A strong correlation between RD50s and STELs was identified, with a predictive equation of ln (STEL) (ppm) = 0.86 * ln (RD50) (ppm) - 2.42 and an R2 value of 0.75. This model supports the use of RD50s to derive STELs for chemicals without existing exposure recommendations. Further, for data-poor sensory irritants, predicted RD50 values from in silico quantitative structure activity relationship (QSAR) models can be used to derive STELs. Hence, in silico methods and statistical modeling can present a path forward for establishing reliable OELs and improving worker safety and health.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Exposición Profesional / Irritantes Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Inhal Toxicol Asunto de la revista: TOXICOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Exposición Profesional / Irritantes Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Inhal Toxicol Asunto de la revista: TOXICOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido