Tomas Öberg

Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis

Selecting most rigorous quantitative structure-activity relationship (QSAR) approaches is of great importance in the development of robust and predictive models of chemical toxicity. To address this issue in a systematic way, we have formed an international virtual collaboratory consisting of six independent groups with shared interests in computational chemical toxicology. We have compiled an aqueous toxicity data set containing 983 unique compounds tested in the same laboratory over a decade against Tetrahymena pyriformis. A modeling set including 644 compounds was selected randomly from the original set and distributed to all groups that used their own QSAR tools for model development. The remaining 339 compounds in the original set (external set I) as well as 110 additional compounds (external set II) published recently by the same laboratory (after this computational study was already in progress) were used as two independent validation sets to assess the external predictive power of individual models. In total, our virtual collaboratory has developed 15 different types of QSAR models of aquatic toxicity for the training set. The internal prediction accuracy for the modeling set ranged from 0.76 to 0.93 as measured by the leave-one-out cross-validation correlation coefficient ( Q abs2). The prediction accuracy for the external validation sets I and II ranged from 0.71 to 0.85 (linear regression coefficient R absI2) and from 0.38 to 0.83 (linear regression coefficient R absII2), respectively. The use of an applicability domain threshold implemented in most models generally improved the external prediction accuracy but at the same time led to a decrease in chemical space coverage. Finally, several consensus models were developed by averaging the predicted aquatic toxicity for every compound using all 15 models, with or without taking into account their respective applicability domains. We find that consensus models afford higher prediction accuracy for the external validation data sets with the highest space coverage as compared to individual constituent models. Our studies prove the power of a collaborative and consensual approach to QSAR model development. The best validated models of aquatic toxicity developed by our collaboratory (both individual and consensus) can be used as reliable computational predictors of aquatic toxicity and are available from any of the participating laboratories.

Distribution and levels of brominated flame retardants in sewage sludge.

One hundred and sixteen sewage sludge samples from 22 municipal wastewater treatment plants in Sweden were analysed for brominated flame retardants. Polybrominated diphenyl ethers (PBDEs) were in the range n.d.-450 ng/g wet weight, tetrabromobisphenol A (TBBPA) varied between n.d. and 220 ng/g wet weight, 2,4,6-tribromophenol was in the range n.d.-0.9 ng/g wet weight and polybrominated biphenyls were not detected (except for a possible analytical interference). There was a significant variation in the samples among plants. Influence from industries and other local sources can therefore be assumed. The correlation pattern indicated contribution from three different types of technical products; composed of either low-brominated PBDEs, decaBDE or TBBPA.

Hexachlorobenzene as an indicator of dioxin production from combustion

The production of polychlorinated dioxins and dibenzofurans shows a strong correlation with the production of hexachlorobenzene. Hexachlorobenzene can be used as an indicator for the production of chlorinated aromatics.

Uncertain Numbers and Uncertainty in the Selection of Input Distributions—Consequences for a Probabilistic Risk Assessment of Contaminated Land

Risks from exposure to contaminated land are often assessed with the aid of mathematical models. The current probabilistic approach is a considerable improvement on previous deterministic risk assessment practices, in that it attempts to characterize uncertainty and variability. However, some inputs continue to be assigned as precise numbers, while others are characterized as precise probability distributions. Such precision is hard to justify, and we show in this article how rounding errors and distribution assumptions can affect an exposure assessment. The outcome of traditional deterministic point estimates and Monte Carlo simulations were compared to probability bounds analyses. Assigning all scalars as imprecise numbers (intervals prescribed by significant digits) added uncertainty to the deterministic point estimate of about one order of magnitude. Similarly, representing probability distributions as probability boxes added several orders of magnitude to the uncertainty of the probabilistic estimate. This indicates that the size of the uncertainty in such assessments is actually much greater than currently reported. The article suggests that full disclosure of the uncertainty may facilitate decision making in opening up a negotiation window. In the risk analysis process, it is also an ethical obligation to clarify the boundary between the scientific and social domains.

Chlorinated aromatics from the combustion of hazardous waste

Abstract The production and emission of chlorinated aromatics from a hazardous waste incinerator were shown to be influenced by the operating conditions.

Brominated aromatics from combustion

The production of brominated aromatics from combustion was shown to be influenced by the operating conditions. Brominated aromatics also showed high yields compared to their chlorinated analogues.

Emission and chlorination pattern of PCDD/PCDF predicted from indicator parameters

The emission and chlorination pattern of polychlorinated dioxins and dibenzofurans from waste combustion shows a close covariation with that of chlorinated benzenes and phenols. This covariation can be utilized to predict the emission levels of specific isomers as well as the pattern of congeners.

Improved process stability during friction stir welding of 5 cm thick copper canisters through shoulder geometry and parameter studies

Abstract The spent nuclear fuel from Swedish power plants will be placed in copper canisters that are sealed with friction stir welding and the stability and robustness of this process is now being optimised in three steps: first, the shoulder geometry was identified that produced the most stable weld cycle, then the welding parameters were optimised for that geometry with regards to stability, and finally, the chosen geometry and welding parameters were verified and evaluated during multiple weld cycles. The shoulder study showed that stable welds could be produced repeatedly with a convex scroll geometry which proved more stable than various concave and flat scroll geometries. In the subsequent parameter study, not only were the most stable values for the welding parameters derived, but a clear relationship was shown between power input and tool temperature. This relationship can be used to more accurately control the process within the parameter windows, not only for this application but for other applications where the welding temperature needs to be kept within a specified range. Similarly, the potential of the convex scroll shoulder geometry for use in applications with other metals and thicknesses is evident.

Assessing bioaccumulation of polybrominated diphenyl ethers for aquatic species by QSAR modeling

Polybrominated diphenyl ethers (PBDEs) are used as flame retardants in textiles, foams and plastics. Highly bioaccumulative with toxic effects including developmental neurotoxicity estrogen and thyroid hormones disruption, they are considered as persistent organic pollutants (POPs) and have been found in human tissues, wildlife and biota worldwide. But only some of them are banned from EU market. For the environmental fate studies of these compounds the bioconcentration factor (BCF) is one of the most important endpoints to start with. We applied quantitative structure-activity relationships techniques to overcome the limited experimental data and avoid more animal testing. The aim of this work was to assess the bioaccumulation of PBDEs by means of QSAR. First, a BCF dataset of specifically conducted experiments was modeled. Then the study was extended by predicting the bioaccumulation and biomagnification factors using some experimental values from the literature. Molecular descriptors were calculated using DRAGON 6. The most relevant ones were selected and resulting models were compared paying attention to the applicability domain.

CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals

Quantitative structure property relationship (QSPR) studies on per‐ and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self‐organizing‐map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non‐linear approaches based models developed by different CADASTER partners on 0D‐2D Dragon descriptors, E‐state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV‐set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro‐alkylated chemicals, particularly monitored by regulatory agencies like US‐EPA and EU‐REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability‐domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown.