Multiphoton FLIM microscopy offers many opportunities to investigate processes in live cells, tissue and animal model systems. For redox measurements, FLIM data is mostly published by cell mean values and intensity-based redox ratios. Our method is based entirely on FLIM parameters generated by 3-detector time domain microscopy capturing autofluorescent signals of NAD(P)H, FAD and novel FLIM-FRET application of Tryptophan and NAD(P)H-a2%/FAD-a1% redox ratio. Furthermore, image data is analyzed in segmented cells thresholded by 2 × 2 pixel Regions of Interest (ROIs) to separate mitochondrial oxidative phosphorylation from cytosolic glycolysis in a prostate cancer cell line. Hundreds of data points allow demonstration of heterogeneity in response to intervention, identity of cell responders to treatment, creating thereby different sub-populations.
Ed Hall worked with the Brodie Lab in the Biology department, to set up a workflow to analyze videos of bug tracking experiments on the Rivanna Linux cluster. They wanted to use the community Matlab software (idTracker) for beetle movement tracking. Their two goals were to shorten the software runtime and to automate the process. There was a large backlog of videos to go through. Ed installed the idTracker software on Rivanna and modified the code to parallelize the bug tracking process. He wrote and documented shell scripts to automate their workflow on the cluster.
PI: Edmund Brodie, PhD (Department of Biology)