Spatial metabolomics has emerged as a powerful tool capable of revealing metabolic gradients throughout complex heterogeneous tissues. While mass spectrometry imaging (MSI) technologies designed to generate spatial metabolomic data have improved significantly over time, metabolite coverage is still a significant limitation. It is possible to achieve deeper metabolite coverage by imaging in positive and negative polarities or imaging several serial sections with different targeted biomolecular classes.
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