Advanced imaging technique for visualizing interrelated metabolic reactions of subcellular organelles in aging and disease: super-resolution multimodal imaging

We have developed an advanced nonlinear multimodal imaging system that integrates Stimulated Raman Scattering (SRS), multiphoton fluorescence (MPF), and second harmonic generation (SHG) to investigate the intricate relationships between metabolic activities and metabolite distribution in organelles of cells and tissues. This system is enhanced by innovative super-resolution image deconvolution and correlation coefficient mapping algorithms, enabling deeper insights into various metabolic processes within super-resolved nanoscale regions of interest. Additionally, we introduced a state-of-the-art chemical image clustering algorithm to precisely identify signals from specific subcellular organelles. This comprehensive approach holds significant potential for improving disease detection and prognosis, assessing therapeutic outcomes, and advancing our understanding of aging and biomedical science.