Background: Sensitive skin refers to skin that tends to be highly responsive to stimuli such as physical, chemical, and psychological. Psychological factors play an important role in the pathology of sensitive skin.
Objective: This study investigated lipid difference between sensitive skin caused by psychological stress and normal skin, followed by construction of a support vector machine (SVM).
Methods: A noninvasive method was used to collect lipid samples from the skin surface. Ultra-performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF-MS) technique and partial least squares-discriminant analysis (PLS-DA) was used to screen for differential lipids. A correlation analysis was performed on differential lipids, and a support vector model was established based on the differential lipids.
Results: Twelve differential lipids were obtained, and the most differentiating species were triacylglycerols (TGs), followed by monounsaturated fatty acids (MUFAs), saturated fatty acids (SFAs), diacylglycerols (DGs), and 6-hydroxysphingosine levels. Triglyceride, SFA, and MUFA species showed a high correlation, and the support vector machine (SVM) differentiation model based on differential lipids had a 100% accuracy rate.
Conclusion: Psychological stress may cause damage to the permeability and antimicrobial barriers of the skin, thereby resulting in sensitive skin. Differentiation models based on SVMs have good prospects for distinguishing sensitive skin caused by psychological stress.
Keywords: psychological factors; sensitive skin; skin surface lipids; support vector machine.
© 2018 Wiley Periodicals, Inc.