Document Detail


Application of a fuzzy neural network model in predicting polycyclic aromatic hydrocarbon-mediated perturbations of the Cyp1b1 transcriptional regulatory network in mouse skin.
MedLine Citation:
PMID:  23274566     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
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:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2012-12-27
Journal Detail:
Title:  Toxicology and applied pharmacology     Volume:  267     ISSN:  1096-0333     ISO Abbreviation:  Toxicol. Appl. Pharmacol.     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-02-11     Completed Date:  2013-04-03     Revised Date:  2014-03-07    
Medline Journal Info:
Nlm Unique ID:  0416575     Medline TA:  Toxicol Appl Pharmacol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  192-9     Citation Subset:  IM    
Copyright Information:
Copyright © 2012 Elsevier Inc. All rights reserved.
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MeSH Terms
Descriptor/Qualifier:
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:
P42 ES016465/ES/NIEHS NIH HHS; P42ES016465/ES/NIEHS NIH HHS; P42ES016465-S1/ES/NIEHS NIH HHS
Chemical
Reg. No./Substance:
0/Polycyclic Hydrocarbons, Aromatic; EC 1.14.14.1/Aryl Hydrocarbon Hydroxylases; EC 1.14.14.1/cytochrome P-450 CYP1B1
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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