Suchergebnisse

Semisoft cheese made from raw sheep's milk is traditionally and economically important in southern Europe. However, raw milk cheese is also a known vehicle of human listeriosis and contamination of sheep cheese with Listeria monocytogenes has been reported. In the present study, we have developed and applied a quantitative risk assessment model, based on available evidence and challenge testing, to estimate risk of invasive listeriosis due to consumption of an artisanal sheep cheese made with raw milk collected from a single flock in central Italy. In the model, contamination of milk may originate from the farm environment or from mastitic animals, with potential growth of the pathogen in bulk milk and during cheese ripening. Based on the 48‐day challenge test of a local semisoft raw sheep's milk cheese we found limited growth only during the initial phase of ripening (24 hours) and no growth or limited decline during the following ripening period. In our simulation, in the baseline scenario, 2.2% of cheese servings are estimated to have at least 1 colony forming unit (CFU) per gram. Of these, 15.1% would be above the current E.U. limit of 100 CFU/g (5.2% would exceed 1,000 CFU/g). Risk of invasive listeriosis per random serving is estimated in the 10−12 range (mean) for healthy adults, and in the 10−10 range (mean) for vulnerable populations. When small flocks (10–36 animals) are combined with the presence of a sheep with undetected subclinical mastitis, risk of listeriosis increases and such flocks may represent a public health risk.

The development of alternative testing strategies (ATS) for hazard assessment of new and emerging materials is high on the agenda of scientists, funders, and regulators. The relatively large number of nanomaterials on the market and under development means that an increasing emphasis will be placed on the use of reliable, predictive ATS when assessing their safety. We have provided recommendations as to how ATS development for assessment of nanomaterial hazard may be accelerated. Predefined search terms were used to identify the quantity and distribution of peer‐reviewed publications for nanomaterial hazard assessment following inhalation, ingestion, or dermal absorption. A summary of knowledge gaps relating to nanomaterial hazard is provided to identify future research priorities and areas in which a rich data set might exist to allow ATS identification. Consultation with stakeholders (e.g., academia, industry, regulators) was critical to ensure that current expert opinion was reflected. The gap analysis revealed an abundance of studies that assessed the local and systemic impacts of inhaled particles, and so ATS are available for immediate use. Development of ATS for assessment of the dermal toxicity of chemicals is already relatively advanced, and these models should be applied to nanomaterials as relatively few studies have assessed the dermal toxicity of nanomaterials to date. Limited studies have investigated the local and systemic impacts of ingested nanomaterials. If the recommendations for research prioritization proposed are adopted, it is envisioned that a comprehensive battery of ATS can be developed to support the risk assessment process for nanomaterials. Some alternative models are available for immediate implementation, while others require more developmental work to become widely adopted. Case studies are included that can be used to inform the selection of alternative models and end points when assessing the pathogenicity of fibers and mode of action of nanomaterial toxicity.

A probabilistic game‐theoretic model is developed within both a static and a dynamic framework to capture adversary–defender conflict in the presence of backlash. I find that not accounting for backlash in counteradversary policies may be costly to the target government. But to minimize adversarial backlash requires understanding how backlash emerges and if, and how, adversaries strategize to goad target governments into policies that induce backlash. The dynamic version of the model shows that when backlash occurs with a time lag, an escalation of the conflict is likely to occur.

The rapid growth of the nanotechnology industry has warranted equal progress in the nanotoxicology and risk assessment fields. In vivo models have traditionally been used to determine human and environmental risk for chemicals; however, the use of these tests has limitations, and there are global appeals to develop reliable alternatives to animal testing. Many have investigated the use of alternative (nonanimal) testing methods and strategies have quickly developed and resulted in the generation of large toxicological data sets for numerous nanomaterials (NMs). Due to the novel physicochemical properties of NMs that are related to surface characteristics, the approach toward toxicity test development has distinct considerations from traditional chemicals, bringing new requirements for adapting these approaches for NMs. The methodical development of strategies that combine multiple alternative tests can be useful for predictive NM risk assessment and help screening‐level decision making. This article provides an overview of the main developments in alternative methods and strategies for reducing uncertainty in NM risk assessment, including advantages and disadvantages of in vitro, ex vivo, and in silico methods, and examples of existing comprehensive strategies. In addition, knowledge gaps are identified toward improvements for experimental and strategy design, specifically highlighting the need to represent realistic exposure scenarios and to consider NM‐specific concerns such as characterization, assay interferences, and standardization. Overall, this article aims to improve the reliability and utility of alternative testing methods and strategies for risk assessment of manufactured NMs.

We developed an approach to estimate the public health benefits resulting from transportation projects or environmental actions that reduce mobile source fine particulate matter (PM2.5) in select urban areas worldwide when input data are limited or when a rapid order‐of‐magnitude assessment is needed. For a given reduction in direct PM2.5 emissions, we can use this approach to quantify (1) the subsequent reduction in ambient primary PM2.5 concentration in the urban area; (2) the public health benefits associated with mortality risk reductions, measured in terms of avoided premature deaths; and (3) the economic value of the reduced mortality risk. To illustrate our approach, we estimated the impact of a 100‐metric‐ton reduction in primary PM2.5 mobile source emissions in the year 2010 for 42 large, global cities. Our estimates of public health benefits and their economic value varied by city, as did the sensitivity to key assumptions and inputs. The estimated number of premature deaths avoided per 100‐metric‐ton reduction in PM2.5 emissions ranged from 12 to 202. City‐level variability in these estimates was driven by the magnitude of the reduction in ambient PM2.5 concentration, the size of the urban population, and the baseline PM2.5 concentration. The economic value of mortality risk reductions per 100‐metric‐ton reduction in PM2.5 emissions ranged from $2 million to $328 million in 2010 U.S. dollars. Income per capita was the most important driver of the variability in the economic values across countries.