Linked Life Data

15627238

Source:http://linkedlifedata.com/resource/pubmed/id/15627238

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2005-5-16
pubmed:abstractText
Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug-induced response, it is necessary to characterize the normal degree of physiological variation in the absence of stimuli. Here, 1H NMR spectroscopic-based analyses of the metabolic composition of urine in experimental animals under various normal physiological conditions are reviewed. In particular, the effects of inter-animal and diurnal variation, gender, age, diet, species, strain, hormonal status and stress on the biochemical composition of urine are explored. Pattern recognition methods facilitate the comparison of urine NMR spectra over a given time-course, enabling the establishment of changes in profile and highlighting the dynamic metabolic status of an organism. Thus metabonomic approaches based on information-rich spectroscopic data sets can be used to evaluate normal physiological variation and for investigation of drug safety issues.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0952-3480
pubmed:author
pubmed:copyrightInfo
Copyright 2004 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
143-62
pubmed:dateRevised
2005-11-16
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition.
pubmed:affiliation
Biological Chemistry, Biomedical Sciences Division, Sir Alexander Fleming Building, Imperial College, South Kensington, London SW7 2AZ, UK. mary.bollard@imperial.ac.uk
pubmed:publicationType
Journal Article, Review