Scheme 1. Diagram of the serum metabolic profiling workflow by CPSI-MS/ML.
(A) Two cohorts of serum samples were collected from the OSCC and HC volunteers as the marker discovery and validation sets, respectively. (B) One drop of dried serum spot (3 μL) was loaded onto a conductive polymer tip. Once the extraction solvent was spiked, the high voltage was switched on to trigger the data acquisition. (C) The high-dimension metabolic profiles of different groups were classified and visualized under the constructed 3D features space by unsupervised machine learning model; (D) From a statistical analysis, the discriminating metabolites were selected as features. (E) Given the data of the two cohorts as the training and test sets, a machine learning model was applied; (F) The serum metabolite markers were further validated at the tissue level and the combination was employed as the diagnostic panel.