Raman spectroscopy: in vivo quick response code of skin physiological status.
Dermatologists need to combine different clinically relevant characteristics for a better understanding of skin health. These characteristics are usually measured by different techniques, and some of them are highly time consuming. Therefore, a predicting model based on Raman spectroscopy and partial least square (PLS) regression was developed as a rapid multiparametric method. The Raman spectra collected from the five uppermost micrometers of 11 healthy volunteers were fitted to different skin characteristics measured by independent appropriate methods (transepidermal water loss, hydration, pH, relative amount of ceramides, fatty acids, and cholesterol). For each parameter, the obtained PLS model presented correlation coefficients higher than R2=0.9. This model enables us to obtain all the aforementioned parameters directly from the unique Raman signature. In addition to that, in-depth Raman analyses down to 20 μm showed different balances between partially bound water and unbound water with depth. In parallel, the increase of depth was followed by an unfolding process of the proteins. The combinations of all these information led to a multiparametric investigation, which better characterizes the skin status. Raman signal can thus be used as a quick response code (QR code). This could help dermatologic diagnosis of physiological variations and presents a possible extension to pathological characterization.
Université Paris-Sud, Faculty of Pharmacy, Group of Analytical Chemistry of Paris-Sud (GCAPS), 51100 Chatenay-Malabry, France.
Raoul
R
Vyumvuhore
Université Paris-Sud, Faculty of Pharmacy, Group of Analytical Chemistry of Paris-Sud (GCAPS), 51100 Chatenay-Malabry, France.
Ali
A
Tfayli
Université Reims Champagne Ardennes, CNRS FRE3481 MEDyC, Faculty of Pharmacy, MéDIAN-"Biophotonics and Technologies for Health", 51100 Reims, France.
Olivier
O
Piot
SILAB, Department of Research and Development, 19100 BP 213, Brive Cedex, France.
Maud
M
Le Guillou
SILAB, Department of Research and Development, 19100 BP 213, Brive Cedex, France.
Nathalie
N
Guichard
Université Reims Champagne Ardennes, CNRS FRE3481 MEDyC, Faculty of Pharmacy, MéDIAN-"Biophotonics and Technologies for Health", 51100 Reims, France.
Michel
M
Manfait
Université Paris-Sud, Faculty of Pharmacy, Group of Analytical Chemistry of Paris-Sud (GCAPS), 51100 Chatenay-Malabry, France.
Arlette
A
Baillet-Guffroy
D000368:Aged; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D008055:Lipids / Q000032:analysis; D008875:Middle Aged; D017510:Protein Folding; D012867:Skin / Q000737:chemistry*; D012879:Skin Physiological Phenomena; D013059:Spectrum Analysis, Raman / Q000379:methods*
D008055:Lipids