The Toxic Effects of Cigarette Additives. Philip Morris' Project Mix Reconsidered: An Analysis of Documents Released through Litigation

Stanton Glantz and colleagues analyzed previously secret tobacco industry documents and peer-reviewed published results of Philip Morris' Project MIX about research on cigarette additives, and show that this research on the use of cigarette additives cannot be taken at face value

The utility of naphthyl-keratin adducts as biomarkers for jet-fuel exposure

We investigated the association between biomarkers of dermal exposure, naphthyl-keratin adducts (NKA), and urine naphthalene biomarker levels in 105 workers routinely exposed to jet-fuel. A moderate correlation was observed between NKA and urine naphthalene levels (p = 0.061). The NKA, post-exposure breath naphthalene, and male gender were associated with an increase, while CYP2E1*6 DD and GSTT1-plus (++/+−) genotypes were associated with a decrease in urine naphthalene level (p < 0.0001). The NKA show great promise as biomarkers for dermal exposure to naphthalene. Further studies are warranted to characterize the relationship between NKA, other exposure biomarkers, and/or biomarkers of biological effects due to naphthalene and/or PAH exposure

Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling

PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making