Evaluation of Potential Toxicity from Co-Exposure to Three CNS Depressants (Toluene, Ethylbenzene, and Xylene) Under Resting and Working Conditions Using PBPK Modeling
Notice bibliographique
Résumé
Under OSHA and American Conference of Governmental Industrial Hygienists (ACGIH®) guidelines, the mixture formula (unity calculation) provides a method for evaluating exposures to mixtures of chemicals that cause similar toxicities. According to the formula, if exposures are reduced in proportion to the number of chemicals and their respective exposure limits, the overall exposure is acceptable. This approach assumes that responses are additive, which is not the case when pharmacokinetic interactions occur. To determine the validity of the additivity assumption, we performed unity calculations for a variety of exposures to toluene, ethylbenzene, and/or xylene using the concentration of each chemical in blood in the calculation instead of the inhaled concentration. The blood concentrations were predicted using a validated physiologically based pharmacokinetic (PBPK) model to allow exploration of a variety of exposure scenarios. In addition, the Occupational Safety and Health Administration and ACGIH® occupational exposure limits were largely based on studies of humans or animals that were resting during exposure. The PBPK model was also used to determine the increased concentration of chemicals in the blood when employees were exercising or performing manual work. At rest, a modest overexposure occurs due to pharmacokinetic interactions when exposure is equal to levels where a unity calculation is 1.0 based on threshold limit values (TLVs®). Under work load, however, internal exposure was 87% higher than provided by the TLVs. When exposures were controlled by a unity calculation based on permissible exposure limits (PELs), internal exposure was 2.9 and 4.6 times the exposures at the TLVs at rest and workload, respectively. If exposure was equal to PELs outright, internal exposure was 12.5 and 16 times the exposure at the TLVs at rest and workload, respectively. These analyses indicate the importance of (1) Bruckner, J. V. and Warren, D. A. 2001. “Toxic effects of solvents and vapors”. In Casarett and Doull's Toxicology: The Basic Science of Poisons, Edited by: Klaassen, C. D. 869–916. New York: McGraw-Hill. [Google Scholar] selecting appropriate exposure limits, (2) Caprino, L. and Togna, G. I. 1998. Potential health effects of gasoline and its constituents: A review of current literature (1990–1997) on toxicological data. Environ. Health Perspect., 106: 115–125. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=9452413http://www4.infotrieve.com/newmedline/detail.asp?NameID=9452413&Session=&searchQuery=Environ%2E+Health+Perspect%2E%5BJournal+Name%5D+AND+106%5BVolume%5D+AND+115%5BPage+Number%5D+AND+1998%5BPublication+Date%5D+AND+Caprino%5BAuthor+Name%5D&count=1http://www.csa.com/htbin/linkabst.cgi?issn=0091-6765&vol=106&iss=&firstpage=115[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] performing unity calculations, and (3) Dobrev, I. D., Andersen, M. E. and Yang, R. S. 2002. In silico toxicology: Simulating interaction thresholds for human exposure to mixtures of trichloroethylene, tetrachloroethylene, and 1,1,1-trichloroethane. Environ. Health Perspect., 110: 1031–1039. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12361929http://www4.infotrieve.com/newmedline/detail.asp?NameID=12361929&Session=&searchQuery=Environ%2E+Health+Perspect%2E%5BJournal+Name%5D+AND+110%5BVolume%5D+AND+1031%5BPage+Number%5D+AND+2002%5BPublication+Date%5D+AND+Dobrev%5BAuthor+Name%5D&count=1http://www.csa.com/htbin/linkabst.cgi?issn=0091-6765&vol=110&iss=&firstpage=1031[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] considering the effect of work load on internal doses, and they illustrate the utility of PBPK modeling in occupational health risk assessment.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».