Linked Life Data

9698224

Source:http://linkedlifedata.com/resource/pubmed/id/9698224

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1-2
pubmed:dateCreated
1998-10-13
pubmed:abstractText
An efficient organic acid profiling and pattern recognition method is described for the correlation between urinary organic acid profiles and uterine cervical cancer. After methoximation of keto acids in alkalinized urine samples, all free organic acids were recovered by a dual solid-phase extraction procedure, followed by conversion to tert.-butyldimethylsilyl derivatives for the profiling analysis by dual-capillary column gas chromatography (GC) with subsequent screening for acids by retention index (I) library matching. A total of 50 organic acids were positively identified in urine samples (0.25 ml) from 12 uterine myoma (benign tumor group) and 14 uterine cervical cancer (malignant tumor group) patients studied. When the GC profiles were simplified to their corresponding organic acid I spectra in bar graphical form, characteristic patterns were obtained for each average of benign and malignant tumor groups. Stepwise discriminant analysis performed on the GC data selected 16 acids as the variables discriminating between the two groups. Canonical discriminant analysis applied to these 16 variables correctly classified 26 urine samples into two separate clusters according to tumor types in the canonical plot.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1387-2273
pubmed:author
pubmed:issnType
Print
pubmed:day
7
pubmed:volume
712
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
11-22
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Gas chromatographic profiling and pattern recognition analysis of urinary organic acids from uterine myoma patients and cervical cancer patients.
pubmed:affiliation
College of Pharmacy, Sungkyunkwan University, Suwon, South Korea.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't