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G D Veith

Publications and source records attributed to G D Veith.

23 records · Page 2Linked to original sources
PubMed1975

Baseline concentrations of polychlorinated biphenyls and DDT in Lake Michigan fish, 1971.

Responding to the recommendations of the Lake Michigan Interstate Pesticide Committee, the author aimed to establish baseline baseline data on polychlorinated biphenyls (PCB's) and DDT in Lake Michigan fish in 1971. Because the past 2 years had witnessed unprecedented legislative action to protect food resources and other aquatic species near the top of the food chain from persistent hazardous chemicals, the author also attempted to gauge the impact of cooperative legislative action on the quality of large lakes. Thirteen species of fish taken from 14 regions of Lake Michigan in the fall of 1971 were analyzed for PCB's and DDT analogs. Mean wet-weight concentrations of PCB's similar to Aroclor 1254 ranged from 2.7 ppm in rainbow smelt to 15 ppm in lake trout. Most trout and salmon longer than 12 inches contained PCB's at concentrations greater than the tolerance level of 5 ppm established by the Food and Drug Administration, U.S. Department of Health, Education, and Welfare. Mean concentrations of total DDT ranged from less than 1 ppm in suckers to approximately 16 ppm in large lake trout. The presence of the major chlorinated hydrocarbons was confirmed by gas-liquid chromatography/mass spectrometry; additional PCB confirmations were obtained through perchlorination. The most abundant PCB's were tetra, penta-, hexa-, and hepatchlorobiphenyls which are similar to commercially prepared Aroclor 1254; lesser chlorinated PCB's were present in fish from nearshore waters.

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PubMedDate not supplied

'Dynamic' QSAR for semicarbazide-induced mortality in frog embryos.

The conventional quantitative-structure-activity relationship (QSAR) provides only a single three-dimensional (3D) model for a given two-dimensional (2D) item in the modeling process. However, in complex reaction environments with solvents of different polarity, especially biological systems, the molecules can take the form of different conformers depending on the particular interaction. Therefore, chemical behavior, e.g. toxicity, may be considered the integral effect of a set of conformers rather than the property of a single 3D isomer. The 'dynamic' QSAR method is unique in that it provided for the calculation of a set of conformers for 2D representation of each chemical of the series under investigation. Moreover, these conformers can be selected interactively according to the hypothesized mechanism of toxic action. The acute lethality of 36 semicarbazides and thiosemicarbazides, evaluated using the Frog Embryo Teratogenesis Assay: Xenopus (FETAX), was modeled by using the 'dynamic' QSAR method. The assumed mode of action, osteolathyrism, was defined by the failure of connective tissue to polymerize properly due to interference with lysyl oxidase. Conformer screenings were based on parameter distribution according to the frontier orbital energies and volume polarizability, conditioning their reactivity and hydrophobicity, respectively. The best results were obtained by the selection of conformers providing prevailing values of electron acceptor properties. Moreover, the best two-parameter QSARs encompassing all the evaluated compounds incorporate a geometric parameter, the geometric analog of the Wiener topological index, and the local electronic characteristics of the C=O or C=S group, superdelocalizabilities and charges.

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PubMedDate not supplied

On the nature, evolution and future of quantitative structure-activity relationships (QSAR) in toxicology.

The quantitative structure-activity relationship (QSAR) science agenda is being determined by its skeptics. Toxic substances control legislation over the past 30 years was born of a culture that tests animals and interprets the results of those tests in attempts to protect public health. Even with the current awareness that there are many more chemicals to assess than resources and test data permit, those skeptical of QSAR are predominant in the regulatory setting. Bureaucracies founded on laboratory testing, whether a private or governmental agency, will only begrudgingly accept QSAR as a strategic tool for designing chemicals and managing chemical risks. Every major milestone in QSAR accomplishments has been met with stronger skepticism that QSAR cannot replace animal testing. The QSAR research community needs to embrace the arguments of the skeptics and design research to overcome the perceived inadequacies of current QSAR methods. This paper will discuss three common errors in QSAR research, which, if corrected, will place in silico methods fully complementary to the strategic use of in vitro and in vivo methods. QSAR is based on well-defined endpoints of intrinsic chemical activities and molecular descriptors, which can be mechanistically interpreted. Chemicals in a QSAR training set ought to have a common mechanism of interaction so that the context of structural requirements defining the domain can be articulated and tested. Finally, the estimation of complex endpoints ought to be controlled by a QSAR-based expert system if the estimation of missing values or hazard screening in heterogeneous inventories is to avoid fueling the skepticism of QSAR.

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PubMedDate not supplied

POPs: a QSAR system for developing categories for persistent, bioaccumulative and toxic chemicals and their metabolites.

This paper presents the framework of a QSAR-based decision support system which provides a rapid screening of potential hazards, classification of chemicals with respect to risk management thresholds, and estimation of missing data for the early stages of risk assessment. At the simplest level, the framework is designed to rank hundreds of chemicals according to their profile of persistence, bioaccumulation potential and toxicity often called the persistent organic pollutant (POP) profile or the PBT (persistent bioaccumulative toxicant) profile. The only input data are the chemical structure. The POPs framework enables decision makers to introduce the risk management thresholds used in the classification of chemicals under various authorities. Finally, the POPs framework advances hazard identification by integrating a metabolic simulator that generates metabolic map for each parent chemical. Both the parent chemicals and plausible metabolites are systematically evaluated for metabolic activation and POPs profile.

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