Royal jelly fatty acids bioprofiling using TLC-MS and digital image analysis coupled with chemometrics and non-parametric regression for discovering efficient biomarkers against melanoma
Reham S. Ibrahim, Alaa A. El‐Banna
Abstract
the HPTLC-imaging technique for targeted profiling using two different methods: parametric and non-parametric regression. The non-parametric regression method exhibited superiority in terms of linearity, accuracy and precision. Biomarkers were determined from the 3D-loading plot of orthogonal projection to latent structures model based on the fatty acid quantitative data together with the melanoma cytotoxic activity data. 10-Hydroxy-2-decenoic acid showed the greatest reduction in melanoma cell viability followed by decanedioic acid then 8-hydroxyoctanoic acid. The present study is considered the first attempt to discriminate fresh and lyophilized royal jelly samples based on their holistic lipidomic profile to discover efficient fatty acid reducing melanoma cell viability.