Algorithm for biological second messenger analysis with dynamic regions of interest.

Physiological function is regulated through cellular communication that is facilitated by multiple signaling molecules such as second messengers. Analysis of signal dynamics obtained from cell and tissue imaging is difficult because of intricate spatially and temporally distinct signals. Signal analysis tools based on static region of interest analysis may under- or overestimate signals in relation to region of interest size and location. Therefore, we developed an algorithm for biological signal detection and analysis based on dynamic regions of interest, where time-dependent polygonal regions of interest are automatically assigned to the changing perimeter of detected and segmented signals. This approach allows signal profiles to be rigorously and precisely tracked over time, eliminating the signal distortion observed with static methods. Integration of our approach with state-of-the-art image processing and particle tracking pipelines enabled the isolation of dynamic cellular signaling events and characterization of biological signaling patterns with distinct combinations of parameters including amplitude, duration, and spatial spread. Our algorithm was validated using synthetically generated datasets and compared with other available methods. Application of the algorithm to volumetric time-lapse hyperspectral images of cyclic adenosine monophosphate measurements in rat microvascular endothelial cells revealed distinct signal heterogeneity with respect to cell depth, confirming the utility of our approach for analysis of 5-dimensional data. In human tibial arteries, our approach allowed the identification of distinct calcium signal patterns associated with atherosclerosis. Our algorithm for automated detection and analysis of second messenger signals enables the decoding of signaling patterns in diverse tissues and identification of pathologic cellular responses.

Thunderstorms Producing Sferic-Geolocated Gamma-Ray Flashes Detected by TETRA-II.

The terrestrial gamma-ray flash (TGF) and Energetic Thunderstorm Rooftop Array (TETRA-II) detected 22 X-ray/gamma-ray flash events associated with lightning between October 2015 and March 2019 across three ground-based detector locations in subtropical and tropical climates in Louisiana, Puerto Rico, and Panama. Each detector array consists of a set of bismuth germanate scintillators that record X-ray and gamma-ray bursts over the energy range 50 keV-6 MeV (million electron volts). TETRA-II events have characteristics similar to both X-ray bursts associated with lightning leaders and TGFs: sub-millisecond duration, photons up to MeV energies, and association with nearby lightning (typically within 3 km). About 20 of the 22 events are geolocated to individual lightning strokes via spatiotemporally coincident sferics. An examination of radar reflectivity and derived products related to events located within the Next Generation Weather Radar (NEXRAD) monitoring region indicates that events occur within mature cells of severe and non-severe multicellular and squall line thunderstorms, with core echo tops which are at or nearing peak altitude. Events occur in both high lightning frequency thunderstorm cells and low lightning frequency cells. Events associated with high frequency cells occur within 5 min of significant lightning jumps. Among NEXRAD-monitored events, hail is present within 8 km and 5 min of all except a single low-altitude cold weather thunderstorm. An association is seen with maximum thunderstorm development, lightning jumps, and hail cells, indicating that the TETRA-II X-ray/gamma-ray events are associated with the peak storm electrification and development of electric fields necessary for the acceleration of electrons to high energies.