| Application of a fuzzy neural network model in predicting polycyclic aromatic hydrocarbon-mediated perturbations of the Cyp1b1 transcriptional regulatory network in mouse skin. | |
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MedLine Citation:
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PMID: 23274566 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Polycyclic aromatic hydrocarbons (PAHs) are present in the environment as complex mixtures with components that have diverse carcinogenic potencies and mostly unknown interactive effects. Non-additive PAH interactions have been observed in regulation of cytochrome P450 (CYP) gene expression in the CYP1 family. To better understand and predict biological effects of complex mixtures, such as environmental PAHs, an 11 gene input-1 gene output fuzzy neural network (FNN) was developed for predicting PAH-mediated perturbations of dermal Cyp1b1 transcription in mice. Input values were generalized using fuzzy logic into low, medium, and high fuzzy subsets, and sorted using k-means clustering to create Mamdani logic functions for predicting Cyp1b1 mRNA expression. Model testing was performed with data from microarray analysis of skin samples from FVB/N mice treated with toluene (vehicle control), dibenzo[def,p]chrysene (DBC), benzo[a]pyrene (BaP), or 1 of 3 combinations of diesel particulate extract (DPE), coal tar extract (CTE) and cigarette smoke condensate (CSC) using leave-one-out cross-validation. Predictions were within 1 log(2) fold change unit of microarray data, with the exception of the DBC treatment group, where the unexpected down-regulation of Cyp1b1 expression was predicted but did not reach statistical significance on the microarrays. Adding CTE to DPE was predicted to increase Cyp1b1 expression, whereas adding CSC to CTE and DPE was predicted to have no effect, in agreement with microarray results. The aryl hydrocarbon receptor repressor (Ahrr) was determined to be the most significant input variable for model predictions using back-propagation and normalization of FNN weights. |
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Authors:
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Andrew Larkin; Lisbeth K Siddens; Sharon K Krueger; Susan C Tilton; Katrina M Waters; David E Williams; William M Baird |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural Date: 2012-12-27 |
Journal Detail:
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Title: Toxicology and applied pharmacology Volume: 267 ISSN: 1096-0333 ISO Abbreviation: Toxicol. Appl. Pharmacol. Publication Date: 2013 Mar |
Date Detail:
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Created Date: 2013-02-11 Completed Date: 2013-04-03 Revised Date: 2013-04-16 |
Medline Journal Info:
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Nlm Unique ID: 0416575 Medline TA: Toxicol Appl Pharmacol Country: United States |
Other Details:
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Languages: eng Pagination: 192-9 Citation Subset: IM |
Copyright Information:
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Copyright © 2012 Elsevier Inc. All rights reserved. |
Affiliation:
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Department of Environmental and Molecular Toxicology, Oregon State University, USA. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Animals Aryl Hydrocarbon Hydroxylases / genetics* Female Fuzzy Logic* Gene Regulatory Networks / drug effects* Mice Neural Networks (Computer)* Polycyclic Hydrocarbons, Aromatic / toxicity* Risk Assessment Skin / drug effects* |
| Grant Support | |
ID/Acronym/Agency:
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P42 ES016465/ES/NIEHS NIH HHS; P42ES016465/ES/NIEHS NIH HHS; P42ES016465-S1/ES/NIEHS NIH HHS |
| Chemical | |
Reg. No./Substance:
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0/Polycyclic Hydrocarbons, Aromatic; EC 1.14.14.1/Aryl Hydrocarbon Hydroxylases; EC 1.14.14.1/cytochrome P450, family 1, subfamily B, polypeptide 1 |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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