Refining our understanding of metal bioavailability in sediments using information from porewater: Application of a multimetal biotic ligand model as an extension of the equilibrium partitioning sediment benchmarks.

The equilibrium partitioning sediment benchmarks (ESBs) derived by the US Environmental Protection Agency (USEPA) in 2005 provide a mechanistic framework for understanding metal bioavailability in sediments by considering equilibrium partitioning (EqP) theory, which predicts that metal bioavailability in sediments is determined largely by partitioning to sediment particles. Factors that favor the partitioning of metals to sediment particles, such as the presence of acid volatile sulfide (AVS) and sediment organic matter, reduce metal bioavailability to benthic organisms. Because ESBs link metal bioavailability to partitioning to particles, they also predict that measuring metals in porewater can lead to a more accurate assessment of bioavailability and toxicity to benthic organisms.

Collection and use of porewater data from sediment bioassay studies for understanding exposure to bioavailable metals.

The US Environmental Protection Agency Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms: Metal Mixtures (Cadmium, Copper, Lead, Nickel, Silver and Zinc) equilibrium partitioning approach causally link metal concentrations and toxicological effects; they apply to sediment and porewater (i.e., interstitial water).

Sediment toxicity data and excess simultaneously extracted metals from field-collected samples: Comparison to United States Environmental Protection Agency benchmarks.

US Environmental Protection Agency (USEPA) Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms: Metal Mixtures are based on the principle that metals toxicity to benthic organisms is determined by bioavailable metals concentrations in porewater. One ESB is based on the difference between simultaneously extracted metal (SEM) and acid volatile sulfide (AVS) concentrations in sediment (excess SEM). The excess SEM ESBs include a lower uncertainty bound, below which most samples (95%) are expected to be "nontoxic" (defined as a bioassay mortality rate ≤24%), and an upper uncertainty bound, above which most samples (95%) are expected to be "toxic" (defined as a mortality rate >24%).

Framing scientific analyses for risk management of environmental hazards by communities: case studies with seafood safety issues.

Risk management provides a context for addressing environmental health hazards. Critical to this approach is the identification of key opportunities for participation. We applied a framework based on the National Research Council's (NRC) analytic-deliberative risk management dialogue model that illustrates two main iterative processes: informing and framing.

Modeling developmental processes in animals: applications in neurodevelopmental toxicology.

Biologically based dose-response models can provide a framework for incorporating mechanistic information into our assessments of neurotoxicity considering both kinetic and dynamic processes. We have constructed models for normal midbrain and neocortex development and we have extended these models to evaluate the neurodevelopmental toxicity of ethanol and methyl mercury. Using such modeling approaches, we have been able to test hypothesized modes of action for these neurodevelopmental toxicants.

A model for optimization of biomarker testing frequency to minimize disease and cost: example of beryllium sensitization testing.

A common problem with medical surveillance programs using biomarkers is determining the optimal frequency of testing to minimize adverse health effects and cost. In the case of beryllium-exposed workers, frequency of testing for beryllium sensitization may be especially important. Recent studies indicate a lack of dose response for beryllium sensitization, but do support a dose response for the development of chronic beryllium disease (CBD).