Titre : |
Skin lipidomics : A tool for understanding skin aging at the molecular level |
Type de document : |
texte imprimé |
Auteurs : |
Michal A. Surma, Auteur ; Christian Klose, Auteur |
Année de publication : |
2017 |
Article en page(s) : |
p. 2-6 |
Note générale : |
Bibliogr. |
Langues : |
Anglais (eng) |
Catégories : |
Dermatologie Lipides Peau -- analyse Vieillissement cutané
|
Index. décimale : |
668.5 Parfums et cosmétiques |
Résumé : |
The lipid composition of human skin is essential for its fonction ; however the simultaneous quantification of a wide range of skin lipids, belonging to both stratum corneum and sebum, is not trivial. Recently we developed a new, "shotgun" mass spectrometry-based method characterized by a broad coverage of lipids, absolute quantitation, high reproducibility and high-throughput providing comprehensive insight into skin lipid composition. We applied this method in a large-scale study of natural lipid variability of human skin. in this study we analyzed samples from 104 individuals of both sexes of different ages. We discovered gradual changes in the skin lipidome correlated with age but no sex-specific differences. Our novel method enables detailed and broad insights into skin lipidomes, both in terms of lipidome coverage and sample number. Therefore, skin shotgun lipidomics has the potential to become useful in studies related to ski aging and anti-aging product claims support. |
Note de contenu : |
FIGURES : Inter-individual variation. (1A,1B) Amounts of lipids measured of (1A) males and (1E) females of different age (here the two most extreme pmol values are sot shows to improve clarity). Lines represent 0-order polynomial smoothing fonction with 8 neighbors averaged. (1C,1D) Profiles of lipid groups of (1C) males and (1D) females of different age. Lines represent 0-order polynomial smoothing function with 8 neighbours averaged. (1E) Principal component analysis of males and females of different age lipidomes with lipid sub-species as input. (1F) sex prediction accuracy (test error) of random Forest classification with all lipid data and data excluding sebum lipids. Points show individuel results of a 5 times repeated 10 times cross validation with horizontal lines representing their mean. The dashed line is the 0.65 Null Error Rate, the prediction error was based on always choosing the majority class. |
En ligne : |
https://drive.google.com/file/d/1ChfY2RTU-KnjbONWdOH2O7WQqXfW4hAM/view?usp=drive [...] |
Format de la ressource électronique : |
Pdf |
Permalink : |
https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=29076 |
in SOFW JOURNAL > Vol. 143, N° 9 (09/2017) . - p. 2-6