Prediction and evaluation of the effect of pre-centrifugation sample management on the measurable untargeted LC-MS plasma metabolome.
Biobank
Machine learning
Plasma
Pre-centrifugation management
Sample quality
Untargeted metabolomics
Journal
Analytica chimica acta
ISSN: 1873-4324
Titre abrégé: Anal Chim Acta
Pays: Netherlands
ID NLM: 0370534
Informations de publication
Date de publication:
16 Oct 2021
16 Oct 2021
Historique:
received:
27
02
2021
revised:
17
08
2021
accepted:
18
08
2021
entrez:
4
10
2021
pubmed:
5
10
2021
medline:
6
10
2021
Statut:
ppublish
Résumé
Optimal handling is the most important means to ensure adequate sample quality. We aimed to investigate whether pre-centrifugation delay time and temperature could be accurately predicted and to what extent variability induced by pre-centrifugation management can be adjusted for. We used untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics to predict and evaluate the influence of pre-centrifugation temperature and delayed time on plasma samples. Pre-centrifugation temperature (4, 25 and 37 °C; classification rate 87%) and time (5-210 min; Q
Identifiants
pubmed: 34602206
pii: S0003-2670(21)00794-7
doi: 10.1016/j.aca.2021.338968
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
338968Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.