Linked Life Data

21365756

Source:http://linkedlifedata.com/resource/pubmed/id/21365756

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2011-3-4
pubmed:abstractText
The use of internal peptide standards in selected reaction monitoring experiments enables absolute quantitation. Here, we describe three approaches addressing calibration of peptide concentrations in complex matrices and assess their performance in terms of trueness and precision. The simplest approach described is single reference point quantitation where a heavy peptide is spiked into test samples and the endogenous analyte quantified relative to the heavy peptide internal standard. We refer to the second approach as normal curve quantitation. Here, a constant amount of heavy peptide and a varying amount of light peptide are spiked into matrix to construct a calibration curve. This accounts for matrix effects but due to the presence of endogenous analyte, it is usually not possible to determine the lower LOQ. We refer to the third method as reverse curve quantitation. Here, a constant amount of light peptide and a varying amount of heavy peptide are spiked into matrix to construct a calibration curve. Because there is no contribution to the heavy peptide signal from endogenous analyte, it is possible to measure the equivalent of a blank sample and determine LOQ. These approaches are applied to human plasma samples and used to assay peptides of a set of apolipoproteins.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1615-9861
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
pubmed:issnType
Electronic
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1148-52
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Evaluation of absolute peptide quantitation strategies using selected reaction monitoring.
pubmed:affiliation
Proteome Sciences, Cobham, Surrey, UK. james.campbell@proteomics.com
pubmed:publicationType
Journal Article, Comparative Study, Evaluation Studies