Linked Life Data

17269691

Source:http://linkedlifedata.com/resource/pubmed/id/17269691

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2007-2-2
pubmed:abstractText
The early factors inducing insulin resistance are not known. Therefore, we are interested in studying the secretome of the human visceral adipose tissue as a potential source of unknown peptides and proteins inducing insulin resistance. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry is a high-throughput proteomics technology to generate peptide and protein profiles (MS spectra). To obtain good quality and reproducible data from SELDI-TOF, many factors in the sample pretreatment and SELDI protocol should be optimized. To identify the optimal combination of factors resulting in the best and the most reproducible spectra, we designed an experiment where factors were varied systematically according to a fractional factorial design. In this study, seven protein chip preparation protocol factors were tested in 32 experiments. The main effects of these factors and their interactions contributing to the best quality spectra were identified by ANOVA. To assess the reproducibility, in a subsequent experiment the eight protocols generating the highest quality spectra were applied to samples in quadruplicates on different chips. This approach resulted in the development of an improved chip protocol, yielding higher quality peaks and more reproducible spectra.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1520-6033
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
217-24
pubmed:meshHeading
pubmed:articleTitle
Fractional factorial design for optimization of the SELDI protocol for human adipose tissue culture media.
pubmed:affiliation
Department of Medical Biomics, University Medical Center Groningen, University of Groningen, Post Office Box 30001, 9700 RR Groningen, The Netherlands. e.szalowska@med.umcg.nl
pubmed:publicationType
Journal Article