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Reconstruction of Exposure to Methylene Diphenyl-4,4′-Diisocyanate (Mdi) Aerosol Using Computational Fluid Dynamics, Physiologically Based Toxicokinetics and Statistical Modeling Publisher Pubmed



Mozaffari S1 ; Bayatian M2 ; Hsieh NH3 ; Khadem M1 ; Garmaroudi AA1 ; Ashrafi K4 ; Shahtaheri SJ1, 5
Authors
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Authors Affiliations
  1. 1. Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Occupational Health Engineering, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
  3. 3. Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, TX A&M University, College Station, TX, United States
  4. 4. Department of Environmental Engineering, Faculty of Environment, University of Tehran, Tehran, Iran
  5. 5. Center for Water Quality Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran

Source: Inhalation Toxicology Published:2023


Abstract

Objectives: This study employed computational fluid dynamics (CFD), physiologically based toxicokinetics (PBTK), and statistical modeling to reconstruct exposure to methylene diphenyl-4,4'-diisocyanate (MDI) aerosol. By utilizing a validated CFD model, human respiratory deposition of MDI aerosol in different workload conditions was investigated, while a PBTK model was calibrated using experimental rat data. Biomonitoring data and Markov Chain Monte Carlo (MCMC) simulation were utilized for exposure assessment. Results: Deposition fraction of MDI in the respiratory tract at the light, moderate, and heavy activity were 0.038, 0.079, and 0.153, respectively. Converged MCMC results as the posterior means and prior values were obtained for several PBTK model parameters. In our study, we calibrated a rat model to investigate the transport, absorption, and elimination of 4,4′-MDI via inhalation exposure. The calibration process successfully captured experimental data in the lungs, liver, blood, and kidneys, allowing for a reasonable representation of MDI distribution within the rat model. Our calibrated model also represents MDI dynamics in the bloodstream, facilitating the assessment of bioavailability. For human exposure, we validated the model for recent and long-term MDI exposure using data from relevant studies. Conclusion: Our computational models provide reasonable insights into MDI exposure, contributing to informed risk assessment and the development of effective exposure reduction strategies. © 2023 Informa UK Limited, trading as Taylor & Francis Group.