Quantifying in situ adaptive immune cell cognate interactions in humans.

Two-photon excitation microscopy (TPEM) has revolutionized the understanding of adaptive immunity. However, TPEM usually requires animal models and is not amenable to the study of human disease. The recognition of antigen by T cells requires cell contact and is associated with changes in T cell shape. We postulated that by capturing these features in fixed tissue samples, we could quantify in situ adaptive immunity. Therefore, we used a deep convolutional neural network to identify fundamental distance and cell-shape features associated with cognate help (cell-distance mapping (CDM)). In mice, CDM was comparable to TPEM in discriminating cognate T cell-dendritic cell (DC) interactions from non-cognate T cell-DC interactions. In human lupus nephritis, CDM confirmed that myeloid DCs present antigen to CD4+ T cells and identified plasmacytoid DCs as an important antigen-presenting cell. These data reveal a new approach with which to study human in situ adaptive immunity broadly applicable to autoimmunity, infection, and cancer.

Imaging canopy temperature: shedding (thermal) light on ecosystem processes.

Canopy temperature Tcan is a key driver of plant function that emerges as a result of interacting biotic and abiotic processes and properties. However, understanding controls on Tcan and forecasting canopy responses to weather extremes and climate change are difficult due to sparse measurements of Tcan at appropriate spatial and temporal scales. Burgeoning observations of Tcan from thermal cameras enable evaluation of energy budget theory and better understanding of how environmental controls, leaf traits and canopy structure influence temperature patterns. The canopy scale is relevant for connecting to remote sensing and testing biosphere model predictions. We anticipate that future breakthroughs in understanding of ecosystem responses to climate change will result from multiscale observations of Tcan across a range of ecosystems.