Does Mercury in Fish Come from the Air?

Concerns with public health risks associated with mercury-contaminated fish have prompted a variety of proposals to cut or eliminate mercury emissions. As a step toward assessing how such reductions could affect fish contamination, we develop a cross-sectional epidemiological model of mercury levels in fish. Using data on stream characteristics, land use, the presence of point sources and both measured and modeled atmospheric deposition of mercury, we explain two-thirds of the variation in mercury levels in fish. We find that greater mercury deposition is not generally associated with higher mercury levels in fish. These results suggest that reductions in deposition (and emissions) may affect mercury levels in fish only slightly or with a significant delay.

Regulating Mercury Emissions: What Do We Know About Costs and Benefits?

United States policymakers are concerned with mercury emissions because mercury has potentially adverse effects on children whose mothers consumed contaminated fish while pregnant. Congress and the Environmental Protection Agency are considering different proposals to cut or even eliminate mercury emissions from oil and coal-fired power plants. We compare the cost of cutting power plants' mercury emissions with the likely reductions in the number of cases of subtle neurological effects. Given current scientific understanding, the health and environmental improvements are very unlikely to provide an economic justification for the costs of stringent controls on mercury emissions. In addition, if Congress or EPA were to regulate mercury emissions from power plants, an approach that used prices would be more efficient than one that limited the quantity of mercury emissions. For a related paper, see Health Risks From Mercury-Contaminated Fish: A Reassessment.

Inflammatory phenotypes underlying uncontrolled childhood asthma despite inhaled corticosteroid treatment:rationale and design of the PACMAN2 study

<p>Background: The diagnosis of childhood asthma covers a broad spectrum of pathological mechanisms that can lead to similarly presenting clinical symptoms, but may nonetheless require different treatment approaches. Distinct underlying inflammatory patterns are thought to influence responsiveness to standard asthma medication.</p><p>Methods/design: The purpose of the PACMAN2 study is to identify inflammatory phenotypes that can discriminate uncontrolled childhood asthma from controlled childhood asthma by measures in peripheral blood and exhaled air. PACMAN2 is a nested, case-control follow-up study to the ongoing pharmacy-based "Pharmacogenetics of Asthma medication in Children: Medication with Anti-inflammatory effects" (PACMAN) study. The original PACMAN cohort consists of children aged 4-12 years with reported use of asthma medication. The PACMAN2 study will be conducted within the larger PACMAN cohort, and will focus on detailed phenotyping of a subset of the PACMAN children. The selected participants will be invited to a follow-up visit in a clinical setting at least six months after their baseline visit based on their adherence to usage of inhaled corticosteroids, their asthma symptoms in the past year, and their age (>= 8 years). During the follow-up visit, current and long-term asthma symptoms, medication use, environmental factors, medication adherence and levels of exhaled nitric oxide will be reassessed. The following measures will also be examined: pulmonary function, exhaled volatile organic compounds, as well as inflammatory markers in peripheral blood and blood plasma. Comparative analysis and cluster-analyses will be used to identify markers that differentiate children with uncontrolled asthma despite their use of inhaled corticosteroids (ICS) (cases) from children whose asthma is controlled by the use of ICS (controls).</p><p>Discussion: Asthmatic children with distinct inflammatory phenotypes may respond differently to anti-inflammatory therapy. Therefore, by identifying inflammatory phenotypes in children with the PACMAN2 study, we may greatly impact future personalised treatment strategies, uncover new leads for therapeutic targets and improve the design of future clinical studies in the assessment of the efficacy of novel therapeutics.</p>