Wavelength-Dependent Calcium Signaling Response to Photobiomodulation in Pancreatic Cells

Diabetes mellitus is a metabolic disorder that is rapidly growing across the world. Our laboratory has recently demonstrated that photobiomodulation (PBM) can couple to its metabolic pathways by modulating calcium dynamics in islet cells, including α- and β-cells. Using computer vision algorithms, changes in PBM-induced calcium dynamics can be verified, and, more importantly, this led us to propose hypotheses that will likely advance our understanding of photostimulatory effects in islet cells. In our previous paper, we determined changes in calcium spiking in response to PBM at 810 nm by manually segmenting the cells and the calcium spiking patterns. We have since developed a computer vison pipeline to automate cell segmentation and subsequent image analyses. By using automated methods for segmentation, registration, tracking, and statistical analysis, we were able to improve the accuracy of previously observed changes in calcium spiking in response to PBM in both cell types. Moreover, this pipeline was applied to elucidate the wavelength-dependent modulation of calcium dynamics at 1064 nm. The extent of increase in calcium spiking appears to have been overestimated by manual analysis, and the machine learning pipeline was able to capture and segment nearly 3-fold more cells, suggesting improved accuracy in the analysis of calcium spiking in islet cells. Detailed calcium analysis also indicates a biphasic dose response among α- and β-cells in response to PBM therapy at different wavelengths. The current findings offer a novel hypothesis and may facilitate the use of translational PBM as a potential therapy for diabetes mellitus.