The article describes an integrated experimental and computational approach to map spatial metabolic gradients in mouse liver and small intestine. Researchers developed a deep-learning algorithm, MET-MAP, used with MALDI imaging mass spectrometry (IMS) and isotope tracing to achieve high-resolution mapping of metabolite concentrations and metabolic activity along key anatomical axes. This methodology revealed that over 90% of measured metabolites exhibit significant spatial concentration gradients in both organs, correlating with regional metabolic demands and enzyme localization. A major finding was the differential processing of the dietary sugar fructose, which causes localized ATP depletion in the pericentral region of the liver.
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