This HTML5 document contains 54 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dctermshttp://purl.org/dc/terms/
n6http://localhost/temp/predkladatel/
n8http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n17http://linked.opendata.cz/ontology/domain/vavai/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
rdfshttp://www.w3.org/2000/01/rdf-schema#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n5http://bibframe.org/vocab/
n9http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00216208%3A11110%2F14%3A10189898%21RIV15-MSM-11110___/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n12http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n11http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n19http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n14http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n16http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n13http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00216208%3A11110%2F14%3A10189898%21RIV15-MSM-11110___
rdf:type
skos:Concept n17:Vysledek
rdfs:seeAlso
http://dx.doi.org/10.1016/j.toxlet.2013.10.031
dcterms:description
Untargeted metabolomic approaches offer new opportunities for a deeper understanding of the molecular events related to toxic exposure. This study proposes a metabolomic investigation of biochemical alterations occurring in urine as a result of dioxin toxicity. Urine samples were collected from Czech chemical workers submitted to severe dioxin occupational exposure in a herbicide production plant in the late 1960s. Experiments were carried out with ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution quadrupole time-of-flight (QTOF) mass spectrometry. A chemistry-driven feature selection was applied to focus on steroid-related metabolites. Supervised multivariate data analysis allowed biomarkers, mainly related to bile acids, to be highlighted. These results supported the hypothesis of liver damage and oxidative stress for long-term dioxin toxicity. As a second step of data analysis, the information gained from the urine analysis of Victor Yushchenko after his poisoning was examined. A subset of relevant urinary markers of acute dioxin toxicity from this extreme phenotype, including glucuro- and sulfo-conjugated endogenous steroid metabolites and bile acids, was assessed for its ability to detect long-term effects of exposure. The metabolomic strategy presented in this work allowed the determination of metabolic patterns related to dioxin effects in human and the discovery of highly predictive subsets of biologically meaningful and clinically relevant compounds. These results are expected to provide valuable information for a deeper understanding of the molecular events related to dioxin toxicity. Furthermore, it presents an original methodology of data dimensionality reduction by using extreme phenotype as a guide to select relevant features prior to data modeling (biologically driven data reduction). Untargeted metabolomic approaches offer new opportunities for a deeper understanding of the molecular events related to toxic exposure. This study proposes a metabolomic investigation of biochemical alterations occurring in urine as a result of dioxin toxicity. Urine samples were collected from Czech chemical workers submitted to severe dioxin occupational exposure in a herbicide production plant in the late 1960s. Experiments were carried out with ultra-high pressure liquid chromatography (UHPLC) coupled to high-resolution quadrupole time-of-flight (QTOF) mass spectrometry. A chemistry-driven feature selection was applied to focus on steroid-related metabolites. Supervised multivariate data analysis allowed biomarkers, mainly related to bile acids, to be highlighted. These results supported the hypothesis of liver damage and oxidative stress for long-term dioxin toxicity. As a second step of data analysis, the information gained from the urine analysis of Victor Yushchenko after his poisoning was examined. A subset of relevant urinary markers of acute dioxin toxicity from this extreme phenotype, including glucuro- and sulfo-conjugated endogenous steroid metabolites and bile acids, was assessed for its ability to detect long-term effects of exposure. The metabolomic strategy presented in this work allowed the determination of metabolic patterns related to dioxin effects in human and the discovery of highly predictive subsets of biologically meaningful and clinically relevant compounds. These results are expected to provide valuable information for a deeper understanding of the molecular events related to dioxin toxicity. Furthermore, it presents an original methodology of data dimensionality reduction by using extreme phenotype as a guide to select relevant features prior to data modeling (biologically driven data reduction).
dcterms:title
Human urinary biomarkers of dioxin exposure: Analysis by metabolomics and biologically driven data dimensionality reduction Human urinary biomarkers of dioxin exposure: Analysis by metabolomics and biologically driven data dimensionality reduction
skos:prefLabel
Human urinary biomarkers of dioxin exposure: Analysis by metabolomics and biologically driven data dimensionality reduction Human urinary biomarkers of dioxin exposure: Analysis by metabolomics and biologically driven data dimensionality reduction
skos:notation
RIV/00216208:11110/14:10189898!RIV15-MSM-11110___
n3:aktivita
n14:I
n3:aktivity
I
n3:cisloPeriodika
2
n3:dodaniDat
n13:2015
n3:domaciTvurceVysledku
n8:6061664 n8:8575975
n3:druhVysledku
n18:J
n3:duvernostUdaju
n11:S
n3:entitaPredkladatele
n9:predkladatel
n3:idSjednocenehoVysledku
19987
n3:idVysledku
RIV/00216208:11110/14:10189898
n3:jazykVysledku
n19:eng
n3:klicovaSlova
Toxicity; Steroidomics; Extreme phenotype; Dioxin; Dimensionality reduction; Biomarkers
n3:klicoveSlovo
n12:Biomarkers n12:Extreme%20phenotype n12:Dioxin n12:Steroidomics n12:Dimensionality%20reduction n12:Toxicity
n3:kodStatuVydavatele
IE - Irsko
n3:kontrolniKodProRIV
[A0DB2505F3F5]
n3:nazevZdroje
Toxicology Letters
n3:obor
n16:FE
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
12
n3:rokUplatneniVysledku
n13:2014
n3:svazekPeriodika
230
n3:tvurceVysledku
Tonoli, David Vlčková, Štěpánka Jeanneret, Fabienne Badoud, Flavia Rutledge, Douglas N. Rudaz, Serge Boccard, Julien Sorg, Olivier Samer, Caroline F. Pelclová, Daniela Saurat, Jean-Hilaire Hochstrasser, Denis
n3:wos
000341881000016
s:issn
0378-4274
s:numberOfPages
10
n5:doi
10.1016/j.toxlet.2013.10.031
n6:organizacniJednotka
11110