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.