Steven P. Bradbury

Comparative toxicology of the pyrethroid insecticides

The toxic effects elicited by synthetic pyrethroids in animals are varied in degree and nature. Their relative safety to birds and mammals contrasts sharply with their acute effects on fish and arthropods. Explantation of their differences in toxicity depends on examination of all factors of their comparative toxicology. Routes of exposure are important, as are metabolism and elimination rates, especially for mammals and birds with their considerable capabilities for biotransformation. Significant differences in sensitivity at the sites of toxic action may also play a role in differential responses to these insecticides. Finally, physical properties that influence the environmental disposition and subsequently affect bioavailability of the compounds in water, soil, air, produce, and nontarget species are also instrumental in determining the impact of current and future synthetic pyrethroid insecticides.

Predicting Modes of Toxic Action from Chemical Structure: An Overview

In the field of environmental toxicology, and especially aquatic toxicology, quantitative structure activity relationships (QSARs) have developed as scientifically-credible tools for predicting the toxicity of chemicals when little or no empirical data are available. A basic and fundamental understanding of toxicological principles has been considered crucial to the continued acceptance and application of these techniques as biologically relevant. As a consequence, there has been an evolution of QSAR development and application from that of a chemical-class perspective to one that is more consistent with assumptions regarding modes of toxic action. The assessment of a compounds likely mode of toxic action is critical for a correct QSAR selection; incorrect mode of action-based QSAR selections can result in 10- to 1000-fold errors in toxicity predictions. The establishment of toxicologically-credible techniques to assess mode of toxic action from chemical structure requires toxicodynamic knowledge bases that are clearly defined with regard to exposure regimes and biological models/endpoints and based on compounds that adequately span the diversity of chemicals anticipated for future applications. With such knowledge bases classification systems, including rule-based experts systems, have been established for use in predictive aquatic toxicology applications.

Quantitative structure-activity relationships and ecological risk assessment: an overview of predictive aquatic toxicology research

In the field of aquatic toxicology, quantitative structure-activity relationships (QSARs) have developed as scientifically credible tools for predicting the toxicity of chemicals when little or no empirical data are available. A fundamental understanding of toxicological principles has been considered an important component to the acceptance and application of QSAR approaches as biologically relevant in ecological risk assessments. As a consequence, there has been an evolution of QSAR development and application from that of a chemical-class perspective to one that is more consistent with assumptions regarding modes of toxic action. In this review, techniques to assess modes of toxic action from chemical structure are discussed, with consideration that toxicodynamic knowledge bases must be clearly defined with regard to exposure regimes, biological models/endpoints and compounds that adequately span the diversity of chemicals anticipated for future applications. With such knowledge bases, classification systems, including rule-based expert systems, have been established for use in predictive aquatic toxicology applications. The establishment of QSAR techniques that are based on an understanding of toxic mechanisms is needed to provide a link to physiologically based toxicokinetic and toxicodynamic models, which can provide the means to extrapolate adverse effects across species and exposure regimes.

Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.

Physiological response of rainbow trout (Salmo gairdneri) to acute fenvalerate intoxication

Abstract The physiological responses of rainbow trout ( Salmo gairdneri ) to fenvalerate intoxication during aqueous exposure were examined to provide information about the pyrethroid mode of action in fish. Trout ( n = 4) were exposed to 412 ± 50 μg/liter fenvalerate and died in 10.9 ± 1.5 hr. Brain, liver, and carcass fenvalerate concentrations associated with mortality were 0.16 ± 0.05, 3.62 ± 0.57, and 0.25 ± 0.05 mg/kg, respectively. Visible signs of intoxication included elevated cough rate, tremors, and seizures. Histopathological examination of gill tissue showed damage consistent with irritation. An evaluation of respiratory-cardiovascular and blood chemistry responses indicated an elevated rate of metabolism associated with increasingly severe seizures. A cessation of ventilatory and cardiac activity, occurring with the seizures, was also observed. Finally, urine osmolality, Na + and K + concentrations, and Na + and K + excretion rates were elevated with intoxicated trout. The physiological responses of rainbow trout to fenvalerate intoxication suggest that besides effects on the nervous system, effects on respiratory surfaces and renal ion regulation may be associated with the mechanism of pyrethroid action in fish.

Recovery of cholinesterase activity in mallard ducklings administered organophosphorus pesticides

Oral doses of the organophosphorus pesticides acephate, dicrotophos, fensulfothion, fonofos, malathion, and parathion were administered to mallard ducklings (Anas platyrhynchos), and brain and plasma cholinesterase (ChE) activities were determined for up to 17 d after dosing. In vivo recovery of brain ChE activity to within 2 standard deviations of the mean activity of undosed birds occurred within 8 d, after being depressed an average of 25-58% at 24 h after dosing. In vivo recovery of plasma ChE appeared as fast as or faster than that of brain, but the pattern of recovery was more erratic and therefore statistical comparison with brain ChE recovery was not attempted. In vitro tests indicated that the potential for dephosphorylation to contribute to in vivo recovery of inhibited brain ChE differed among chemical treatments. Some ducklings died as a result of organophosphate dosing. In an experiment in which ducklings within each treatment group received the same dose (mg/kg), the brain ChE activity in birds that died was less than that in birds that survived. Brain ChE activities in ducklings that died were significantly different among pesticide treatments: fensulfothion greater than parathion greater than acephate greater than malathion (p less than or equal to 0.05).

Quantitative structure‐activity relationship models for prediction of estrogen receptor binding affinity of structurally diverse chemicals

The demonstrated ability of a variety of structurally diverse chemicals to bind to the estrogen receptor has raised the concern that chemicals in the environment may be causing adverse effects through interference with nuclear receptor pathways. Many structure-activity relationship models have been developed to predict chemical binding to the estrogen receptor as an indication of potential estrogenicity. Models based on either two-dimensional or three-dimensional molecular descriptions that have been used to predict potential for binding to the estrogen receptor are the subject of the current review. The utility of such approaches to predict binding potential of diverse chemical structures in large chemical inventories, with potential application in a tiered risk assessment scheme, is discussed.

An overview of the use of quantitative structure‐activity relationships for ranking and prioritizing large chemical inventories for environmental risk assessments

Ecological risk assessments for chemical stressors are used to establish linkages between likely exposure concentrations and adverse effects to ecological receptors. At times, it is useful to conduct screening risk assessments to assist in prioritizing or ranking chemicals on the basis of potential hazard and exposure assessment parameters. Ranking of large chemical inventories can provide evidence for focusing research and/or cleanup efforts on specific chemicals of concern. Because of financial and time constraints, data gaps exist, and the risk assessor is left with decisions on which models to use to estimate the parameter of concern. In this review, several methods are presented for using quantitative structure-activity relationships (QSARs) in conducting hazard screening or screening-level risk assessments. The ranking methods described include those related to current regulatory issues associated with chemical inventories from Canada, Europe, and the United States and an example of a screening-level risk assessment conducted on chemicals associated with a watershed in the midwest region of the United States.

Toxicity of fenvalerate to bobwhite quail (colinus virginianus) including brain and liver residues associated with mortality

The toxicity of the synthetic pyrethroid fenvalerate to bobwhite quail (Colinus virginianus) was examined. The acute oral LD50 to adult (19-wk-old) male and female birds was in excess of 4000 mg/kg. The LD50 to immature (5-wk-old) birds was 1785 mg/kg. Dietary toxicity testing with 2-wk-old chicks indicated an 8-d LC50 in excess of 15,000 ppm. Observed signs of intoxication included hyperactivity, irregular locomotion, ataxia, spastic muscle contraction, and, preceding death, sternal recumbency with muscle flaccidity. Significant weight loss (adult birds) or reduction in rate of weight gain (immature birds and chicks) was note generally at all dose levels in the acute testing, but only at the highest level in the dietary test. Brain residue levels associated with mortality increased with the dose (means of 0.10-1.26 ppm), whereas liver residues remained constant (overall mean of 0.74 ppm).

New developments in a hazard identification algorithm for hormone receptor ligands

Recently we described the Common REactivity PAttern (COREPA) technique to screen data sets of diverse structures for their ability to serve as ligands for steroid hormone receptors [1]. The approach identifies and quantifies similar global and local stereoelectronic characteristics associated with active ligands through a comparison of energeticallyreasonable conformer distributions for selected descriptors. For each stereoelectronic descriptor selected, discrete conformer distributions from a training set of ligands are evaluated and parameter ranges common for conformers from all the chemicals in the training set are identified. The use of discrete partitions of parameter ranges to define common reactivity patterns can, however, influence the outcome of the algorithm. To address this limitation, the original method has been extended by approximating continuous conformer distributions as probability distributions. The COREPA-Continuous (COREPA-C) algorithm assesses the common reactivity pattern of biologicallysimilar molecules in terms of a product of probability distributions, rather than a collection of common population ranges determined by examination of discrete partitions of a distribution. To illustrate the algorithm, common reactivity patterns based on interatomic distance and charge on heteroatoms were developed and evaluated using a set of 28 androgen receptor ligands. Notable attributes of the COREPA-C algorithm include flexibility in establishing stereoelectronic descriptor criteria for identifying active and nonactive compounds and the ability to quantify threedimensional chemical similarity without the need to predetermine a toxicophore or align compounds(s) to a lead ligand.