Linked Life Data

18065775

Source:http://linkedlifedata.com/resource/pubmed/id/18065775

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2008-2-7
pubmed:abstractText
13C NMR data have been correlated to Toxic Equivalency Factors (TEFs) of the 29 PCDDs, PCDFs, or PCBs for which non-zero TEFs have been defined. Such correlations are called quantitative spectrometric data-activity relationship (QSDAR) models. An improved QSDAR model predicted TEFs of 0.037 and 0.004, respectively, for 1,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and 1,2,3,4,7-pentachlorodibenzo-p-dioxin (PeCDD), both among the 390 congeners for which zero value TEFs are assumed. A QSDAR model of Relative Potency (REP) values estimated the corresponding values as 0.115 and 0.020. Results from both models indicated that these two congeners may exhibit significant dioxin-like toxicity. If other such congeners have non-zero toxicity, TEF-based risk assessments of some dioxin-, furan-, or PCB-contaminated sites or foods may underestimate toxicity. Both models were extensively cross-validated and the TEF model was externally validated. We confirmed the predictions by an independent in vitro method, a luciferase gene expression assay based on mouse liver cells that found REPs of 0.027 and 0.013, respectively, for 1,3,7,8-TCDD and 1,2,3,4,7-PeCDD. The QSDAR-estimated and gene-expression assayed values agreed. The models were used to predict activity for an applicability domain including 108 non-2,3,7,8 dioxin, furan, or PCB congeners and 2,3,7,8-tetrachlorophenothiazine, a dioxin analog proposed as a drug candidate. This study showed that QSDAR prediction followed by a relatively inexpensive in vitro assay could be used to nominate a few candidates among hundreds for further investigation. It suggested that in silico and in vitro nomination protocols may facilitate practical risk assessment when chemical family members exhibit different degrees of toxicity operating via a common mechanism.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1096-6080
pubmed:author
pubmed:issnType
Print
pubmed:volume
102
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
187-95
pubmed:dateRevised
2010-9-17
pubmed:meshHeading
pubmed-meshheading:18065775-Animals, pubmed-meshheading:18065775-Biological Assay, pubmed-meshheading:18065775-Cell Line, pubmed-meshheading:18065775-Dioxins, pubmed-meshheading:18065775-Dose-Response Relationship, Drug, pubmed-meshheading:18065775-Environmental Pollutants, pubmed-meshheading:18065775-Furans, pubmed-meshheading:18065775-Gene Expression Regulation, pubmed-meshheading:18065775-Genes, Reporter, pubmed-meshheading:18065775-Humans, pubmed-meshheading:18065775-Liver, pubmed-meshheading:18065775-Magnetic Resonance Spectroscopy, pubmed-meshheading:18065775-Mice, pubmed-meshheading:18065775-Models, Biological, pubmed-meshheading:18065775-Molecular Structure, pubmed-meshheading:18065775-Polychlorinated Biphenyls, pubmed-meshheading:18065775-Quantitative Structure-Activity Relationship, pubmed-meshheading:18065775-Receptors, Aryl Hydrocarbon, pubmed-meshheading:18065775-Reproducibility of Results, pubmed-meshheading:18065775-Risk Assessment, pubmed-meshheading:18065775-Toxicity Tests, pubmed-meshheading:18065775-Transfection
pubmed:year
2008
pubmed:articleTitle
Modeling and assaying dioxin-like biological effects for both dioxin-like and certain non-dioxin-like compounds.
pubmed:affiliation
Division of Systems Toxicology, Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock 72205-7199, USA. jone.wilkes@fda.hhs.gov
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.