Mentor: Paul Urayama, Ph.D.

A Python-based software tool was developed to analyze UV-induced autofluorescence spectra in cells, serving as a free and open-source replacement for the lab's current LabVIEW and MATLAB implementations. Built using tkinter for the GUI, plotly for visualization, and numpy and pandas for data processing, the software offers a user-friendly and modular platform for various analyses. Its primary function is spectral phasor analysis, which assigns complex numbers to spectra to distinguish between similar signals. In two- and three-component systems, the phasor's position relative to pure component phasors reveals the relative contributions of each component through geometric relationships. Additional features include calculations of means, widths, and spectral decomposition with respect to user-selected basis spectra.
NADH is the dominant source of the studied autofluorescence and plays a central role in mitochondrial metabolism through its redox cycling with NAD⁺. This central role in cellular respiration makes NADH fluorescence a valuable indicator of metabolic state. The spectral phasor approach is sensitive enough to detect subtle shifts in metabolism, enabling non-invasive monitoring of metabolic changes at a pathway level.

Explore the Project