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Abstract
A model is presented which allows to quantify the simultaneous distribution of the exposure to two compounds, for example a health-risk and a health promoting compound. The model considers the total dietary intake, and can be used as a first step to study the effects on the balance between risks and benefits following changes in the consumption pattern. The exposure is modelled separately for intake probabilities using a betabinomial model, and for intake amounts using a lognormal model, and these parts are afterwards integrated by Monte Carlo simulation. The model is illustrated using the risk–benefit case of dioxins and the omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). High concentrations of both the health adverse compounds and the health promoting compounds are simultaneously present in fatty fish. Calculated exposures were compared with intake limits: the adequate intake for EPA + DHA and the tolerable daily intake (TDI) for dioxins. We estimate the probability that dioxin exposure is below TDI, the probability that EPA + DHA exposure is above the adequate intake, and the probability that both conditions occur simultaneously. We also model the dependence of these probabilities on age. In the studied population the exposure to both compounds is almost completely below the limits. A scenario study in which meat consumption was replaced by fatty fish consumption shows an increase in the fraction of the population with the recommended intake of EPA + DHA, however also the fraction of the population exceeding the TDI for dioxins is increased. For the example scenario the optimal amount of fatty fish consumption is derived.
Keywords: Probabilistic risk assessment; Betabinomial–lognormal model; Long-term intake; Dioxin; Fish fatty acids
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Abstract
A method is proposed for integrated probabilistic risk assessment where exposure assessment and hazard characterization are both included in a probabilistic way. The aim is to specify the probability that a random individual from a defined (sub)population will have an exposure high enough to cause a particular health effect of a predefined magnitude, the critical effect size (CES). The exposure level that results in exactly that CES in a particular person is that person’s individual critical effect dose (ICED). Individuals in a population typically show variation, both in their individual exposure (IEXP) and in their ICED. Both the variation in IEXP and the variation in ICED are quantified in the form of probability distributions. Assuming independence between both distributions, they are combined (by Monte Carlo) into a distribution of the individual margin of exposure (IMoE). The proportion of the IMoE distribution below unity is the probability of critical exposure (PoCE) in the particular (sub)population. Uncertainties involved in the overall risk assessment (i.e., both regarding exposure and effect assessment) are quantified using Monte Carlo and bootstrap methods. This results in an uncertainty distribution for any statistic of interest, such as the probability of critical exposure (PoCE). The method is illustrated based on data for the case of dietary exposure to the organophosphate acephate. We present plots that concisely summarise the probabilistic results, retaining the distinction between variability and uncertainty. We show how the relative contributions from the various sources of uncertainty involved may be quantified.
Keywords: Probabilistic risk assessment, Monte Carlo, individual margin of exposure (IMoE), probability of critical exposure (PoCE), uncertainty analysis |
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Lehesranta SJ, Koistinen KM, Massat N, Davies HV, Shepherd LVT, McNicol JW, Cakmak I, Cooper J, Lück L, Kärenlampi SO, Leifert C
Journal: Proteomics 2007, 7, pp 597-604 |
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Abstract
A range of studies have compared the level of nutritionally relevant compounds in crops from organic and nonorganic farming systems, but there is very limited information on the effect of farming systems and their key components on the protein composition of plants. We addressed this gap by quantifying the effects of different farming systems and key components of such systems on the protein profiles of potato tubers. Tuber samples were produced in the Nafferton factorial systems study, a group of long-term, replicated factorial field experiments designed to identify and quantify the effect of fertility management methods, crop protection practices and rotational designs used in organic, low input and conventional production systems. Protein profiles were determined by 2-DE and subsequent protein identification by HPLC-ESI-MS/MS. Principal component analysis of 2-DE data showed that only fertility management practices (organic matter vs. mineral fertiliser based) had a significant effect on protein composition. Quantitative differences were detected in 160 of the 1100 tuber proteins separated by 2-DE. Proteins identified by MS are involved in protein synthesis and turnover, carbon and energy metabolism and defence responses, suggesting that organic fertilisation leads to an increased stress response in potato tubers. | |
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