Biomedical subjects

Patrik L Andersson

Publications and source records attributed to Patrik L Andersson.

11 recordsLinked to original sources

PubMed2006

Identification of the brominated flame retardant 1,2-dibromo-4-(1,2-dibromoethyl)cyclohexane as an androgen agonist.

To investigate androgen receptor (AR) activation by exogenous compounds, we used a combination of experimental analysis and theoretical modeling to compare a set of brominated flame retardants (BFRs) to dihydrotestosterone (DHT) with regard to ligand docking, AR binding, and AR activation in human hepatocellular liver carcinoma cells, as well as interacting energy analysis. Modeling of receptor docking was found to be a useful first step in predicting the potential to translocate to the ligand pocket of the receptor, and the computed interaction energy was found to correlate with the observed binding affinity. Flexible alignment studies of the BFR compounds demonstrated that 1,2-dibromo-4-(1,2-dibromoethyl)cyclohexane (BCH) closely overlap DHT. Combining the theoretical modeling with in vitro ligand-binding and receptor-activation assays, we show that BCH binds to and activates the human AR. The remaining BFRs did not successfully interact with the ligand pocket, were not able to replace a synthetic androgen from the receptor, and failed to activate the receptor.

Androgens↗

PubMed2006

Characterization and classification of complex PAH samples using GC-qMS and GC-TOFMS.

The aim of this study was to compare the polycyclic aromatic hydrocarbon (PAH) contents in a number of complex samples, including soil samples from industrial sites, anti-skid sand, urban dust and ash samples from municipal solid waste incinerators. The samples were characterized by routine analysis of PAHs (gas chromatography-quadrupole mass spectrometry) and gas chromatography-time of flight mass spectrometry (GC-TOFMS). Classification of the samples by principal component analysis (PCA) according to their composition of PAHs revealed that samples associated with traffic and the municipal incinerator formed homogeneous clusters, while the PAH-contaminated soils clustered in separate groups. Using spectral data to resolve co-eluting chromatographic peaks, 962 peaks could be identified in the GC-TOFMS analysis of a pooled sample and 123-527 peaks in the individual samples. Many of the studied extracts included a unique set of chemicals, indicating that they had a much more diverse contamination profile than their PAH contents suggested. Compared to routine analysis, GC-TOFMS provided more detailed information about each sample and in this study a large number of alkylated PAHs were found to be associated with the corresponding unsubstituted PAHs. The possibility to filter peaks according to different criteria (e.g. to include only peaks that were detected in the analysis of another sample) was explored and used to identify unique as well as common compounds within samples. This procedure could prove to be valuable for obtaining relevant chemical data for use in conjunction with results from various biological test systems.

Gas Chromatography-Mass Spectrometry↗

PubMed2006

Megavariate analysis of environmental QSAR data. Part II--investigating very complex problem formulations using hierarchical, non-linear and batch-wise extensions of PCA and PLS.

Three extensions of the basic PCA and PLS methodologies are described. These extensions are hierarchical, non-linear and batch-based in nature. The objectives of these methods are to assist in problem understanding and problem solving in very complex (QSAR) problem formulations. The method extensions are illustrated using two example QSAR data sets containing many X- and Y-variables.

Hazardous Substances↗

PubMed2006

Megavariate analysis of environmental QSAR data. Part I--a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD).

This paper introduces principal component analysis (PCA), partial least squares projections to latent structures (PLS), and statistical molecular design (SMD) as useful tools in deriving multi- and megavariate quantitative structure-activity relationship (QSAR) models. Two QSAR data sets from the fields of environmental toxicology and environmental chemistry are worked out in detail, showing the benefits of PCA, PLS and SMD. PCA is useful when overviewing a data set and exploring relationships among compounds and relationships among variables. PLS is the regression extension of PCA and is used for establishing QSARs. SMD is essential for selecting informative training and test sets of compounds for QSAR calibration and validation.

Data Interpretation, Statistical↗

PubMed2006

Comparison of techniques for estimating PAH bioavailability: uptake in Eisenia fetida, passive samplers and leaching using various solvents and additives.

The aim of this study was to evaluate different techniques for assessing the availability of polycyclic aromatic hydrocarbons (PAHs) in soil. This was done by comparing the amounts (total and relative) taken up by the earthworm Eisenia fetida with the amounts extracted by solid-phase microextraction (SPME), semi-permeable membrane devices (SPMDs), leaching with various solvent mixtures, leaching using additives, and sequential leaching. Bioconcentration factors of PAHs in the earthworms based on equilibrium partitioning theory resulted in poor correlations to observed values. This was most notable for PAHs with high concentrations in the studied soil. Evaluation by principal component analysis (PCA) showed distinct differences between the evaluated techniques and, generally, there were larger proportions of carcinogenic PAHs (4-6 fused rings) in the earthworms. These results suggest that it may be difficult to develop a chemical method that is capable of mimicking biological uptake, and thus estimating the bioavailability of PAHs.

1-Butanol↗

PubMed2006

In vitro profiling of the endocrine-disrupting potency of brominated flame retardants.

Over the last few years, increasing evidence has become available that some brominated flame retardants (BFRs) may have endocrine-disrupting (ED) potencies. The goal of the current study was to perform a systematic in vitro screening of the ED potencies of BFRs (1) to elucidate possible modes of action of BFRs in man and wildlife and (2) to classify BFRs with similar profiles of ED potencies. A test set of 27 individual BFRs were selected, consisting of 19 polybrominated diphenyl ether congeners, tetrabromobisphenol-A, hexabromocyclododecane, 2,4,6-tribromophenol, ortho-hydroxylated brominated diphenyl ether 47, and tetrabromobisphenol-A-bis(2,3)dibromopropyl ether. All BFRs were tested for their potency to interact with the arylhydrocarbon receptor, androgen receptor (AR), progesterone receptor (PR), and estrogen receptor. In addition, all BFRs were tested for their potency to inhibit estradiol (sulfation by estradiol sulfotransferase (E2SULT), to interfere with thyroid hormone 3,3',5-triiodothyronine (T3)-mediated cell proliferation, and to compete with T3-precursor thyroxine for binding to the plasma transport protein transthyretin (TTR). The results of the in vitro screening indicated that BFRs have ED potencies, some of which had not or only marginally been described before (AR antagonism, PR antagonism, E2SULT inhibition, and potentiation of T3-mediated effects). For some BFRs, the potency to induce AR antagonism, E2SULT inhibition, and TTR competition was higher than for natural ligands or clinical drugs used as positive controls. Based on their similarity in ED profiles, BFRs were classified into five different clusters. These findings support further investigation of the potential ED effects of these environmentally relevant BFRs in man and wildlife.

Animals↗

PubMed2006

The fate of chiral organochlorine compounds and selected metabolites in intraperitoneally exposed arctic char (Salvelinus alpinus).

The fate of chiral organochlorine compounds (OCs) and selected metabolites in exposed Arctic char (Salvelinus alpinus) was investigated. The contaminants alpha-hexachlorocyclohexane (alpha-HCH), cis-chlordane, 13C4-heptachlor, o,p'-DDT, and the atropisomeric chlorinated biphenyls (CBs) 95, 132, 136, 149, and 174 were solved in peanut oil and injected into the peritoneal cavity. The exposed fish were sampled three times during a five-week period, and the OC residues and detected metabolites (heptachlorexo-epoxide) were quantified in muscle and liver tissues by chiral and achiral gas chromatography-mass spectrometry and gas chromatography-electron-capture detection. Peak concentrations were reached after one to two weeks, and thereafter, the levels declined. At the end of the experiment, liver concentrations had decreased 76 to 92% relative to peak concentrations, whereas muscle concentrations showed a moderate decline (5-38%), with the exception of alpha-HCH (91%). Hydrophobicity and steric hindrance were shown to influence the assimilation process, and a significant linear relationship between the product of the steric hindrance coefficients and the inverse of the octanol-water partition coefficients (Kow) versus peak concentration was found for the CBs (r2 = 0.86, p = 0.02). The assimilation of the contaminants into muscle and liver tissues generally resulted in racemic mixtures, whereas elimination was enantioselective for alpha-HCH, cis-chlordane, o,p'-DDT, CB-132, and CB-136. The chiral heptachlor metabolite 13C4-heptachlor-exo-epoxide was formed in the fish. The enantiomeric composition of the formed metabolite indicated racemic formation, whereas the elimination process appeared to be enantioselective.

Animals↗

PubMed2006

Chemical characterization of brominated flame retardants and identification of structurally representative compounds.

Three training sets were selected, each consisting of 10 structurally diverse compounds representative of brominated flame retardants (BFRs) that are either in use or have been used. Just three compounds account for nearly all the total production volume of BFRs. In the present study, however, the physicochemical characteristics of a far more structurally diverse set of 65 BFRs was explored using 15 molecular descriptors (including log P, constitutional counts, and semiempirical quantum mechanical parameters) and principal component analysis (PCA). The PCA generated an overview of the structural variation among BFRs, and certain compounds with unique physicochemical properties and specific clusters of compounds with distinct properties were identified. The training-set compounds were selected by applying the condensed information obtained from the PCA and statistical experimental design. The three training sets, which were designated as optimal, practical, and alternative, were selected either to maximize the structural variation (optimal) or to combine structural variation with practical advantages, such as ease of experimental handling and commercial availability (practical and alternative). Inclusion of the suggested compounds in assessments of the persistence, bioaccumulation, and toxicity properties of BFRs and related programs should help to increase our understanding of the effects and environmental fate of these compounds.

Bromine Compounds↗

PubMed2002

Multivariate physicochemical characterisation and quantitative structure-property relationship modelling of polybrominated diphenyl ethers.

Levels of polybrominated diphenyl ethers (PBDEs) are increasing in the environment and may cause long-term environmental problems. Developing a model describing the chemical variation among the 209 possible congeners would be a useful step in any systematic approach for assessing the fate and risk posed by the PBDEs. Therefore, 40 physicochemical descriptors were derived for all PBDEs using a semi-empirical method (AM1), molecular mechanics, and empirically estimated parameters. Descriptors included heats of formation, frontier molecular orbital energies, atomic charges, dipole moments, logP values, and molecular surface areas. Principal component analysis (PCA) was used to evaluate the descriptors. The first four PCs, explaining 76% of the variation in the data, described the size, charge distribution and symmetric elements of the congeners. A quantitative structure-activity relationship model was constructed based on data for dioxin-like activity (using the luciferase bioassay) for 17 PBDEs with the partial least squares method. In addition, quantitative structure-property relationship models for gas chromatographic relative retention times on four capillary columns were developed. These models proved suitable to assist in the identification of untested PBDEs. Based on the results of the PCA, a factorial design was applied for selecting 21 representative congeners. PBDEs 11, 13, 17, 32, 35, 47, 53, 77, 85, 99, 119, 135, 153, 155, 156, 169, 176, 181, 190, 192, and 209. The spacing of these congeners in the physicochemical domain maximises the coverage of key factors such as molecular size and substitution pattern. Consideration of the selected congeners should be useful for guiding the synthesis of new compounds for use in future studies of the fate and biological effects of PBDEs.

Biological Assay↗

PubMedDate not supplied

General and class specific models for prediction of soil sorption using various physicochemical descriptors.

Diverse chemical descriptors were explored for use in QSAR models aimed to screen the soil sorption potential of organic compounds. The descriptors included logP, HyperChem QSARProperties descriptors, a combination of connectivity indices, geometrical, and quantum chemical measures, and two sets from the DRAGON and CODESSA program packages, respectively. Generally, the univariate logP models were capable of capturing most of the variation and give an indication of the sorption potential. The multivariate models required refined variable selection procedures but were shown to include crucial descriptors for modeling compound classes with specific chemical characteristics.

Models, Chemical↗

PubMedDate not supplied

QSPR treatment of the soil sorption coefficients of organic pollutants.

In this study, general and class-specific QSPR models for soil sorption, logK(OC), of 344 organic pollutants (0 < logK(OC) < 4.94) were developed using a large variety of theoretical molecular descriptors based only on molecular structure. Two general models were obtained. The first model was derived for a structurally representative set of 68 chemicals (R2=0.76, s=0.44), whereas the second involved a total of 344 compounds (R2=0.76, s=0.41). The first was validated using the data for the remaining 276 pollutants (R2=0.70, s=0.45). An additional validation of both models was performed using an independent set of 48 pollutants. Both models predict the logK(OC) at the level of experimental precision, while the theoretical molecular descriptors appearing in the QSPR models give further insight into the mechanisms of soil sorption. The analysis of the distribution of the residuals of the logK(OC) values calculated by both general models indicated the need and possible advantages of modeling soil sorption for smaller data sets related to individual classes of chemicals. Accordingly, QSPR models were also developed for 14 chemical classes. The descriptors appearing in these models were discussed as related to the possible interaction mechanisms in soil sorption.

Journal Article↗