Exposure assessment of process-related contaminants in food by biomarker monitoring

Exposure assessment is a fundamental part of the risk assessment paradigm, but can often present a number of challenges and uncertainties. This is especially the case for process contaminants formed during the processing, e.g. heating of food, since they are in part highly reactive and/or volatile, thus making exposure assessment by analysing contents in food unreliable. New approaches are therefore required to accurately assess consumer exposure and thus better inform the risk assessment. Such novel approaches may include the use of biomarkers, physiologically based kinetic (PBK) modelling-facilitated reverse dosimetry, and/or duplicate diet studies. This review focuses on the state of the art with respect to the use of biomarkers of exposure for the process contaminants acrylamide, 3-MCPD esters, glycidyl esters, furan and acrolein. From the overview presented, it becomes clear that the field of assessing human exposure to process-related contaminants in food by biomarker monitoring is promising and strongly developing. The current state of the art as well as the existing data gaps and challenges for the future were defined. They include (1) using PBK modelling and duplicate diet studies to establish, preferably in humans, correlations between external exposure and biomarkers; (2) elucidation of the possible endogenous formation of the process-related contaminants and the resulting biomarker levels; (3) the influence of inter-individual variations and how to include that in the biomarker-based exposure predictions; (4) the correction for confounding factors; (5) the value of the different biomarkers in relation to exposure scenario’s and risk assessment, and (6) the possibilities of novel methodologies. In spite of these challenges it can be concluded that biomarker-based exposure assessment provides a unique opportunity to more accurately assess consumer exposure to process-related contaminants in food and thus to better inform risk assessment

The influence of regional basic science campuses on medical students' choice of specialty and practice location: a historical cohort study

<p>Abstract</p> <p>Background</p> <p>Indiana University School of Medicine (IUSM) employs eight regional basic science campuses, where half of the students complete their first two years of medical school. The other half complete all four years at the main campus in Indianapolis. The authors tested the hypothesis that training at regional campuses influences IUSM students to pursue primary care careers near the regional campuses they attended.</p> <p>Methods</p> <p>Medical school records for 2,487 graduates (classes of 1988–1997) were matched to the 2003 American Medical Association Physician Masterfile to identify the medical specialty and practice location of each graduate. Multivariate logistic regression was performed to assess the effect of regional campus attendance on students' choice of medical specialty and practice location, while simultaneously adjusting for several covariates thought to affect these career outcomes.</p> <p>Results</p> <p>Compared to Indianapolis students, those who attended a regional campus were somewhat more likely to be white, have parents with middle class occupations, and score slightly lower on the Medical College Admission Test. Any such differences were adjusted for in the regression models, which predicted that four of the regional campuses were significantly more likely than Indianapolis to produce family practitioners, and that five of the regional campuses were significantly more likely than the others to have former students practicing in the region. When analyzed collectively, attendance at any regional campus was a significant predictor of a primary care practice located outside the Indianapolis metropolitan area.</p> <p>Conclusion</p> <p>Attending a regional campus for preclinical training appears to increase the likelihood of practicing primary care medicine in local communities.</p

Hyperbolic Discounting with Environmental Outcomes across Time, Space, and Probability

Environmental discounting is a potentially important research area for climate change mitigation. We aimed to replicate and extend earlier work on the discounting of a negative environmental outcome. We measured ratings of concern, and willingness to act to mitigate, an outcome involving air pollution that would hypothetically affect the garden and drinking water of the participants over psychological distance represented by temporal (1 month, 6 months, and 1, 3, 5, 10, and 80 years), spatial (5, 20, 50, 100, 1000, and 5000 km), and probabilistic (95%, 90%, 50%, 30%, 10%, and 5% likelihood) dimensions. For our data from 224 first-year psychology students, of four potential models (an exponential, simple hyperbolic, and two hyperboloid functions), the Rachlin hyperboloid was the best-fitting model describing ratings of concern and action across all three dimensions. Willingness to act was discounted more steeply than concern across all dimensions. There was little difference in discounting for outcomes described as human-caused rather than natural, except that willingness to act was discounted more steeply than concern for human-caused environmental outcomes compared to natural outcomes across spatial (and, less conclusively, temporal) distance. Presenting values of the three dimensions in random or progressive order had little effect on the results. Our results reflect the often-reported attitudebehavior gap whereby people maintain concern about a negative event over dimensions of psychological distance, but their willingness to act to mitigate the event is lower and more steeply discounted