Predictive Model of Nail Consistency Using Scanning Electron Microscopy with Energy-Dispersive X-Ray

Biology (Basel). 2021 Jan 12;10(1):53. doi: 10.3390/biology10010053.

Abstract

The nail plate is made up of tightly packed keratin-rich cells. Factors such as the special distribution of the intermediate filaments in each layer (dorsal, intermediate, and ventral), the relative thickness of the layers, and their chemical composition define the characteristics of each nail. The main objective of this study is to determine nail consistency by calculating a predictive model based on elemental composition analysis using scanning electron microscopy. Nail consistency was determined in 57 participants (29 women and 28 men) in two age groups (young people and adults). Elemental composition was analysed in each layer using scanning SEM-EDS, and nail plate thickness was measured by image analysis. A total of 12 elements were detected in nail plates, of which carbon, nitrogen, phosphorus, sulphur, and calcium showed significant differences between layers (p-values ≤ 0.01). The level of calcium in the dorsal layer was the main predictive variable in calculating the predictive model of consistency, with 75.4% correctly classified cases. Elemental analysis in each layer of the nail plate by SEM-EDS can be used to develop a predictive model of nail consistency that will help health professionals to objectively determine nail consistency.

Keywords: SEM-EDS; binary logistic regression; nail apparatus; nail consistency; nail plate; predictive model; thickness.