The association between content of the elements S, Cl, K, Fe, Cu, Zn and Br in normal and cirrhotic liver tissue from Danes and Greenlandic Inuit examined by dual hierarchical clustering analysis
Meta-analysis of previous studies evaluating associations between content of elements sulphur (S), chlorine (Cl), potassium (K), iron (Fe), copper (Cu), zinc (Zn) and bromine (Br) in normal and cirrhotic autopsy liver tissue samples. Normal liver samples from 45 Greenlandic Inuit, median age 60 year...
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Published in | Journal of trace elements in medicine and biology Vol. 28; no. 1; pp. 50 - 55 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Germany
Elsevier GmbH
01.01.2014
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Subjects | |
Online Access | Get full text |
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Summary: | Meta-analysis of previous studies evaluating associations between content of elements sulphur (S), chlorine (Cl), potassium (K), iron (Fe), copper (Cu), zinc (Zn) and bromine (Br) in normal and cirrhotic autopsy liver tissue samples.
Normal liver samples from 45 Greenlandic Inuit, median age 60 years and from 71 Danes, median age 61 years. Cirrhotic liver samples from 27 Danes, median age 71 years. Element content was measured using X-ray fluorescence spectrometry. Statistics: Dual hierarchical clustering analysis, creating a dual dendrogram, one clustering element contents according to calculated similarities, one clustering elements according to correlation coefficients between the element contents, both using Euclidian distance and Ward Procedure.
One dendrogram separated subjects in 7 clusters showing no differences in ethnicity, gender or age. The analysis discriminated between elements in normal and cirrhotic livers. The other dendrogram clustered elements in four clusters: sulphur and chlorine; copper and bromine; potassium and zinc; iron. There were significant correlations between the elements in normal liver samples: S was associated with Cl, K, Br and Zn; Cl with S and Br; K with S, Br and Zn; Cu with Br. Zn with S and K. Br with S, Cl, K and Cu. Fe did not show significant associations with any other element.
In contrast to simple statistical methods, which analyses content of elements separately one by one, dual hierarchical clustering analysis incorporates all elements at the same time and can be used to examine the linkage and interplay between multiple elements in tissue samples. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0946-672X 1878-3252 1878-3252 |
DOI: | 10.1016/j.jtemb.2013.08.003 |