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J S Jaworska

Publications and source records attributed to J S Jaworska.

10 recordsLinked to original sources
PubMed2002

Bayesian analysis and inference from QSAR predictive model results.

QSAR models have been under development for decades but acceptance and utilization of model results have been slow, in part, because there is no widely accepted metric for assessing their reliability. We reapply a method commonly used in quantitative epidemiology and medical decision-making for evaluating the results of screening tests to assess reliability of a QSAR model. It quantifies the accuracy (expressed as sensitivity and specificity) of QSAR models as conditional probabilities of correct and incorrect classification of chemical characteristic, given a true characteristic. Using Bayes formula, these conditional probabilities are combined with prior information to generate a posterior distribution to determine the probability a specific chemical has a particular characteristic, given a model prediction. As an example, we apply this approach to evaluate the predictive reliability of a CATABOL model and base on it a "ready" and "not ready" biodegradability classification. Finally, we show how predictive capability of the model can be improved by sequential use of two models, the first one with high sensitivity and the second with high specificity.

Bayes Theorem↗
PubMed2000

Uncertainty of the hazardous concentration and fraction affected for normal species sensitivity distributions.

Species in the environment vary according to their sensitivity to a toxicant. Because these differences in sensitivity are unique to the toxicant at consideration and laboratory data sets to assess this variability are very small due to cost, it is important to provide uncertainty estimates of (1) environmental quality objectives (hazardous concentrations) derived from these laboratory data and (2) fraction of species affected at given, or predicted, laboratory or environmental concentrations. This article focuses on the normal (Gaussian) distribution of species sensitivity. It examines and compares results of Problems (1) and (2) from two opposing statistical philosophies, Bayesian and Classical, leading to vastly different numerical approaches. For the normal model, both approaches lead to identical answers, numerically. Extrapolation factors for the lower, median, and upper estimates of the hazardous concentration at six levels of protection are derived. Furthermore, upper, median, and lower estimates of the fraction affected at given, standardized, logarithmic concentrations have been tabulated. This table can be used directly for risk assessment without reference to protection levels or hazardous concentrations. The confidence limits for hazardous concentration and fraction affected depend heavily on the number of species tested and are independent of the toxic substance involved (provided the model is right), due to correction for the mean and standard deviation of the toxicity data. The equivalence of confidence limits for hazardous concentration and fraction affected is captured in the law of extrapolation: the upper (median, lower) confidence limit for the fraction affected at the lower (median, upper) confidence limit of the hazardous concentration is equal to the fraction affected (e.g., 5%) used to define the hazardous concentration. The upper confidence limit for the fraction affected at the median estimate of the hazardous concentration for 5% of the species is a fixed number depending on the sample size of the toxicity data only. It amounts to 46% at n=3, down to 20% at n=10, and still 12% at n 30.

Animals↗
PubMed1999

Environmental risk assessment for trisodium [S,S]-ethylene diamine disuccinate, a biodegradable chelator used in detergent applications.

Environmental safety data are presented for [S,S]-Ethylene Diamine Disuccinate ([S,S]-EDDS), a new, biodegradable, strong transition metal chelator. An environmental risk assessment for its use in detergent applications, which takes into account the chelating properties of [S,S]-EDDS, is proposed. A property of [S,S]-EDDS that distinguishes it from other strong transition metal chelators is its, "ready" and transparent (no recalcitrant metabolites) biodegradation profile. Because its sorption to activated sludge solids is low (Kp of 40 l/kg), removal of [S,S]-EDDS during sewage treatment, which is greater than 96% as determined by the Continuous Activated Sludge test, is mainly ascribed to biodegradation. At projected use volumes in detergent applications [S,S]-EDDS predicted steady-state concentration in rivers leaving the mixing zone will be below 5 micrograms/l due to rapid biodegradation. [S,S]-EDDS exhibits low toxicity to fish and Daphnia (both EC50S > 1000 mg/l). By contrast, due to limitation of the algal test for chelators apparent toxicity was observed (EC50 = 0.290 mg/l, NOEC--No observable Effect Concentration = 0.125 mg/l). Schowanek et al. [1] demonstrated that this is not toxicity sensu stricto but a chelation effect of trace metals in the test medium and of resulting essential nutrients limitation. This requires specific attention when the results of algal toxicity are to be extrapolated to a field situation to perform realistic risk assessment. Metal speciation calculations, using MINEQL+, show that at the predicted environmental concentrations of [S,S]-EDDS (1-5 micrograms/l), such a chelation effect would be insignificant. These calculations allow to estimate the NOEC for chelation effects in the field to be in the range of 0.250-0.500 mg/l, depending on the background water chemistry. These values are well above the laboratory NOEC. An environmental risk assessment was performed using the EUSES (1.0) program. EUSES is currently the EU recommended tool for conducting risk assessments (TGD 1995). It was applied to estimate the river water and soil concentrations from production, formulation and private use life stages. The estimated PEC/PNEC ratio in all relevant environmental compartments is smaller than 1, indicating "no immediate concern" at the anticipated usage level.

Animals↗
PubMed1996

A community model of ciliate Tetrahymena and bacteria E. coli: Part I. individual-based models of tetrahymena and E. coli populations.

The dynamics of a microbial community consisting of a eucaryotic ciliate Tetrahymena pyriformis and procaryotic Escherichia coli in a batch culture is explored by employing an individual-based approach. In this portion of the article, Part I, population models are presented. Because both models are individual-based, models of individual organisms are developed prior to construction of the population models. The individual models use an energy budget method in which growth depends on energy gain from feeding and energy sinks such as maintenance and reproduction. These models are not limited by simplifying assumptions about constant yield, constant energy sinks and Monod growth kinetics as are traditional models of microbal organisms. Population models are generated from individual models by creating distinct individual types and assigning to each type the number of real individuals they represent. A population is a compilation of individual types that vary in a phase of cell cycle and physiological parameters such as filtering rate for ciliates and maximum anabolic rate for bacteria. An advantage of the developed models is that they realistically describe the growth of the individual cells feeding on resource which varies in density and composition. Part II, the core of the project, integrates models into a dynamic microbial community and provides model analysis based upon available data.

Animals↗
PubMed1996

A community model of ciliate Tetrahymena and bacteria E coli: Part II. interactions in a batch system.

Premised on relatively simple assumptions, mathematical models like those of Monod, Pirt or Droop inadequately explain the complex transient behavior of microbial populations. In particular, these models fail to explain many aspects of the dynamics of a Tetrahymena pyriformis-Escherichia coli community. In this study an alternative approach, an individual-based model, is employed to investigate the growth and interactions of Tetrahymena pyriformis and E. coli in a batch culture. Due to improved representation of physiological processes, the model provides a better agreement with experimental data of bacterial density and ciliate biomass than previous modeling studies. It predicts a much larger coexistence domain than rudimentary models, dependence of biomass dynamics on initial conditions (bacteria to ciliate biomasses ratio) and appropriate timing of minimal bacteria density. Moreover, it is found that accumulation of E. coli sized particles and E. coli toxic metabolites has a stabilizing effect on the system.

Animals↗
PubMed1996

A novel QSAR approach for estimating toxicity of phenols.

Toxicity values (log IGC50(-1)) for 60 phenols tested in the 2-d static population growth inhibition assay with the ciliate Tetrahymena pyriformis were tabulated. Each chemical was selected so the series formed uniform coverage of the hydrophobicity/ionization surface. A high quality hydrophobicity-dependent (log Kow) structure-toxicity relationship (log IGC50(-1) = 0.741 (log Kow)-1.433; n = 17; r2 = 0.970; s = 0.134; F = 486.55; Pr > F = 0.0001) was developed for phenols with pKa values > 9.8. Similarly, separate hydrophobicity-dependent relationships were developed for phenols with pKa values of 4.0, 5.1, 6.3, 7.5, and 8.7. Comparisons of intercepts and slopes, respectively, revealed phenols with pKa values of 6.3 to be the most toxic and the least influenced by hydrophobicity. These relationships were reversed for the more acidic and basic phenols. Plots of toxicity versus pKa for nitro-substituted phenols and phenols with log Kow values of either 1.75 or 2.50 further demonstrated bilinearity between toxicity and ionization. In an effort to more accurately model the relationship between toxicity and ionization, the absolute value function [6.3-pKa] was used to model ionization affects for derivatives with pKa values between 0 and 9.8. For derivatives with pKa value > 9.8, a value of 3.50 was used to quantitate ionization effects. The use of log Kow in conjunction with this modified pKa (delta pKa) resulted in the structure-toxicity relationship (log IGC(50)-1 = 0.567 (log Kow)-0.226 (delta pKa)-0.079; n = 54; r2 = 0.926; s = 0.215; F = 321.06; Pr > F = 0.0001). Derivatives with a nitro group in the 4-position typically did not model well with the above equation.

Animals↗
PubMed1995

Quantitative structure-toxicity relationships and volume fraction analyses for selected esters.

The acute toxicity of aliphatic and aromatic mono and diesters in two eucaryotic organisms was compared. The test systems were the static 2-d Tetrahymena pyriformis 50% population growth impairment (IGC50(-1)) assay, and the flow-through 4-d Pimephales promelas 50% mortality (LC50(-1)) assay. In ciliates, esters act via the nonpolar narcosis mechanism of toxic action. This was indicated by: the high quality 1-octanol/water partition coefficient (log Kow) dependent quantitative structure-activity relationship (QSAR), log IGC50(-1) = 0.79 (log Kow) - 1.93, n = 15, r2 = 0.945, s = 0.22, f = 222.37 Pr > f = 0.001); volume fraction (Vf) (0.8e-02); and "a" coefficient (0.3) which are not different from other nonpolar narcotics. In vivo hydrolysis in Tetrahymena appears to be insignificant. However, in fish, presumably because of more active esterases, in vivo hydrolysis is significant and leads to greater toxicity of esters than observed for nonpolar narcotics. Moreover, it leads to a unique high quality QSAR, log LC50(-1) = 0.64 (log Kow) - 0.64, n = 14, r2 = 0.945, s = 0.22, f = 207.08, Pr > f = 0.0001). Due to in vivo hydrolysis, a nonreducing concentration gradient is formed between water and fish. Therefore, the fish take up more toxicant as compared to a situation that leads to thermodynamic equilibrium. Additional information about the mechanism of ester toxicity in fish was gained by applying corrections for hydrolysis in volume fraction analyses. The corrected Vf (0.6e-02) is very close to the one found for nonpolar narcotics (0.7e-02).(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1994

Mechanism-based comparisons of acute toxicities elicited by industrial organic chemicals in procaryotic and eucaryotic systems.

Comparisons of toxicities elicited by nonpolar and polar narcotics, weak acid uncouplers of oxidative phosphorylation, and bioreactive chemicals between the eucaryotic systems Pimephales promelas and Tetrahymena pyriformis and the procaryotic systems Escherichia coli and Photobacterium phosphoreum were performed. Each chemical had been a priori assigned a mechanism/mode of action based on the results from previous studies with eucaryotic systems. Hydrophobicity-dependent QSARs for nonpolar narcosis for both the E. coli and the P. phosphoreum endpoints was developed. However, due to the lack of a significant relationship between P. phosphoreum toxicity and log Kow, such a QSAR for polar narcosis was developed only for the E. coli endpoint. Except for 4-nitroaniline (the only chemical in the examined group that required activation to become the Michael receptor), all chemicals containing reactive substructures revealed excess toxicity over polar narcosis QSAR for E. coli endpoints. Moreover, chloroacidic acid and ethyl chloroacetate in this system also appear to be bioreactive. The only mechanism that seemed to not exist in the procaryotic system was uncoupling of oxidative phosphorylation. Chemicals from this group, except 2,4-dinitroaniline, did not exhibit excess toxicity over polar narcosis QSAR. This was thought to be explained by the lack of mitochondria in procaryotes, the target site of uncoupling agents in eucaryotes. In addition, evaluation of toxicities of halogen-substituted short-chain carboxylic alcohols indicated that their mechanisms vary, depending upon the type of substitution and the system.

Alcohols↗
PubMed1993

Quantitative relationships of structure-activity and volume fraction for selected nonpolar and polar narcotic chemicals.

The relative toxicity of selected industrial organic chemicals was secured from the literature for the static 48-h Tetrahymena pyriformis 50% population growth impairment and the flow-through 96-h Pimephales promelas 50% mortality endpoints. Chemicals were selected to represent the nonpolar narcosis (aliphatic alcohols and aliphatic ketones) and polar narcosis (anilines and phenols) mechanisms of toxic action. molar volume (MV) and 1-octanol/water partition coefficient (log Kow) data were generated for each chemical. High-quality, log Kow dependent quantitative structure-activity relationships were observed for each chemical class and mechanism of action for both endpoints. The volume fraction (Vf) for each chemical in the target phase was determined from the toxicant concentration in the water (toxicity data), the MV, and the target/water partition coefficient (Ktw) with Ktw considered equal to Kow (1-a). Analyses of target sites, by way of "a" revealed that "a" was constant for a mechanism of action regardless of chemical class, but distinct for a given test system. Mean Vt was constant for each mechanism of action regardless of chemical class or test system. These results suggest, at least for reversible physical mechanisms, that volume fraction analyses are significant in determining the mechanism of toxic action of a chemical.

1-Octanol↗