Clinical records of 286 consecutive patients reacting positively with objective symptoms to double-blind, placebo-controlled oral peanut challenges at University Hospital, Nancy, France were examined for individual No Observed Adverse Effect Levels (NOAELs) and Lowest Observed Adverse Effect Levels (LOAELs). After fitting to a log-normal probability distribution model, the ED(10) and ED(05) were 14.4 and 7.3mg (expressed as whole peanut), respectively, with 95% lower confidence intervals of 10.7 and 5.2mg, respectively. Compared to results from a previous study where the ED(10) was based upon individual peanut thresholds gleaned from 12 publications, a statistically significant difference was observed between the ED(50)'s, but not the ED(10)'s of the two probability distribution curves. The Nancy patient group contains more sensitive subjects than the group from the published literature thus contributing to the observed differences. Minimum eliciting dose-distributions for patients with histories of more severe reactions (grade 4 or 5; 40 subjects) did not differ significantly from those of patients with histories of less severe reactions (grades 1-3; 123 subjects). These data and this modeling approach could be used to establish population thresholds for peanut-allergic consumers and thereby provide a sound basis for allergen control measures in the food industry.

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Understanding the consequences of the combined effects of multiple stressors-including stress from man-made chemicals-is important for conservation management, the ecological risk assessment of chemicals, and many other ecological applications. Our current ability to predict and analyse the joint effects of multiple stressors is insufficient to make the prospective risk assessment of chemicals more ecologically relevant because we lack a full understanding of how organisms respond to stress factors alone and in combination. Here, we describe a Dynamic Energy Budget (DEB) based bioenergetics model that predicts the potential effects of single or multiple natural and chemical stressors on life history traits. We demonstrate the plausibility of the model using a meta-analysis of 128 existing studies on freshwater invertebrates. We then validate our model by comparing its predictions for a combination of three stressors (i.e. chemical, temperature, and food availability) with new, independent experimental data on life history traits in the daphnid Ceriodaphnia dubia. We found that the model predictions are in agreement with observed growth curves and reproductive traits. To the best of our knowledge, this is the first time that the combined effects of three stress factors on life history traits observed in laboratory studies have been predicted successfully in invertebrates. We suggest that a re-analysis of existing studies on multiple stressors within the modelling framework outlined here will provide a robust null model for identifying stressor interactions, and expect that a better understanding of the underlying mechanisms will arise from these new analyses. Bioenergetics modelling could be applied more broadly to support environmental management decision making.