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Type: Artigo de periódico
Title: Application of Kohonen neural network for evaluation of the contamination of Brazilian breast milk with polychlorinated biphenyls
Author: Kowalski, CH
da Silva, GA
Godoy, HT
Poppi, RJ
Augusto, F
Abstract: Due to the tendency of polychlorinated biphenyls (PCB) to accumulate in matrixes with high lipid content, the contamination of the breast milk with these compounds is a serious issue, mainly to the newborn. In this study, milk samples were collected from breastfeeding mothers belonging to 4 Brazilian regions (south, southeast, northeast and north). Twelve PCB were analyzed by HS-SPME-GC-ECD and the corresponding peak areas were correlated to the answers to a questionnaire of general habits, breastfeeding and characteristics of the living places. To realize this exploratory analyze, self-organizing maps generated applying Kohonen neural network were applied. It was possible to verify the occurrence of different PCB congeners in the breast milk relating to the region of the Brazil that the breastfeeding lives, the proximity to an industry, the proximity to a contaminated river or sea, the type of milk (colostrum, foremilk and hindmilk) and the number of past pregnancies. (C) 2013 Elsevier B.V. All rights reserved.
Subject: Polychlorinated biphenyls
Human milk
Solid-phase microextraction
Gas chromatography with electron-capture detector
Self-organizing maps
Country: Holanda
Editor: Elsevier Science Bv
Rights: fechado
Identifier DOI: 10.1016/j.talanta.2013.05.033
Date Issue: 2013
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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