Subcellular organelle metabolic correlation with super-resolution chemical imaging

Hongje Jang; Zhi Li; Yajuan Li; Yu Ping; Lingyan Shi

doi:10.1117/12.3017630

20 June 2024 Subcellular organelle metabolic correlation with super-resolution chemical imaging

Hongje Jang, Zhi Li, Yajuan Li, Yu Ping, Lingyan Shi

Proceedings Volume PC13006, Biomedical Spectroscopy, Microscopy, and Imaging III; PC1300602 (2024) https://doi.org/10.1117/12.3017630
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

We've established a nonlinear multimodal imaging system that incorporates stimulated Raman Scattering (SRS), multiphoton fluorescence (MPF), and second harmonic generation (SHG) to explore the connections between metabolic activities and the distribution of metabolites in cells and tissues. Furthermore, we've devised the Adam-based Pointillism Deconvolution (A-PoD) and Correlation Coefficient Mapping (CoCoMap) algorithms, enabling a deeper insight into the simultaneous recording and regulation of various metabolic processes within super-resolved images of nanoscale Regions of Interest (ROIs). In our pursuit of specifically identifying signals originating from distinct subcellular organelles, we've introduced a pioneering clustering algorithm known as Multi-SRS reference matching (Multi-SRM). This approach has the potential to improve early disease detection, prognosis, the evaluation of therapeutic effects, and our comprehension of the mechanisms underpinning aging and biomedicine.

Conference Presentation

Citation Download Citation

Hongje Jang, Zhi Li, Yajuan Li, Yu Ping, and Lingyan Shi "Subcellular organelle metabolic correlation with super-resolution chemical imaging", Proc. SPIE PC13006, Biomedical Spectroscopy, Microscopy, and Imaging III, PC1300602 (20 June 2024); https://doi.org/10.1117/12.3017630

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