Linked Life Data

17141227

Source:http://linkedlifedata.com/resource/pubmed/id/17141227

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
30
pubmed:dateCreated
2006-12-20
pubmed:abstractText
Metabolic profiling has increasingly been used as a probe in disease diagnosis and pharmacological analysis. Herein, plasma fatty acid metabolic profiling including non-esterified fatty acid (NEFA) and esterified fatty acid (EFA) was investigated using gas chromatography/mass spectrometry (GC/MS) followed by multivariate statistical analysis. Partial least squares-linear discrimination analysis (PLS-LDA) model was established and validated to pattern discrimination between type 2 diabetic mellitus (DM-2) patients and health controls, and to extract novel biomarker information. Furthermore, the PLS-LDA model visually represented the alterations of NEFA metabolic profiles of diabetic patients with abdominal obesity in the treated process with rosiglitazone. The GC/MS-PLS-LDA analysis allowed comprehensive detection of plasma fatty acid, enabling fatty acid metabolic characterization of DM-2 patients, which included biomarkers different from health controls and dynamic change of NEFA profiles of patients after treated with medicine. This method might be a complement or an alternative to pathogenesis and pharmacodynamics research.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0014-5793
pubmed:author
pubmed:issnType
Print
pubmed:day
22
pubmed:volume
580
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
6837-45
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Plasma fatty acid metabolic profiling and biomarkers of type 2 diabetes mellitus based on GC/MS and PLS-LDA.
pubmed:affiliation
Research Center of Modernization of Chinese Medicines, Central South University, Changsha 410083, PR China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't