Hyperspectral phasor analysis enables multiplexed 5D in vivo imaging

Time-lapse imaging of multiple labels is challenging for biological imaging as noise, photobleaching and phototoxicity compromise signal quality, while throughput can be limited by processing time. Here, we report software called Hyper-Spectral Phasors (HySP) for denoising and unmixing multiple spectrally overlapping fluorophores in a low signal-to-noise regime with fast analysis. We show that HySP enables unmixing of seven signals in time-lapse imaging of living zebrafish embryos

Chemical diversity in a metal-organic framework revealed by fluorescence lifetime imaging

The presence and variation of chemical functionality and defects in crystalline materials, such as metal–organic frameworks (MOFs), have tremendous impact on their properties. Finding a means of identifying and characterizing this chemical diversity is an important ongoing challenge. This task is complicated by the characteristic problem of bulk measurements only giving a statistical average over an entire sample, leaving uncharacterized any diversity that might exist between crystallites or even within individual crystals. Here we show that by using fluorescence imaging and lifetime analysis, both the spatial arrangement of functionalities and the level of defects within a multivariable MOF crystal can be determined for the bulk as well as for the individual constituent crystals. We apply these methods to UiO-67, to study the incorporation of functional groups and their consequences on the structural features. We believe that the potential of the techniques presented here in uncovering chemical diversity in what is generally assumed to be homogeneous systems can provide a new level of understanding of materials properties

Searching for extreme portions in distributions: A comparison of pie and bar charts

Aggregated data visualizations are often used by collaborative teams to gain a common understanding of a complex situations and issues. Pie and bar charts are both widely used for visualizing distributions. The study of pie versus bar charts has a long history and the results are seemingly inconclusive. Many report authors prefer pie charts while visualization theory often argues for bar graphs. Most of the studies that conclude in favor of pie charts have focused on how well they facilitate the identification of parts to the whole. This study set out to collect empirical evidence on which chart type that most rapidly and less erro-neously facilitate the identification of extreme parts such as the minimum, or the maximum, when the distributions are similar, yet not identical. The results show that minimum values are identified in shorter time with bar charts compared to pie charts. Moreover, the extreme values are identified with fewer errors with bar charts compared to pie charts. One implication of this study is that bar charts are recommended in visualization situations where important decisions depend on rapidly identifying extreme values

Imaging Dynamic Molecular Signaling by the Cdc42 GTPase within the Developing CNS

Protein interactions underlie the complexity of neuronal function. Potential interactions between specific proteins in the brain are predicted from assays based on genetic interaction and/or biochemistry. Genetic interaction reveals endogenous, but not necessarily direct, interactions between the proteins. Biochemistry-based assays, on the other hand, demonstrate direct interactions between proteins, but often outside their native environment or without a subcellular context. We aimed to achieve the best of both approaches by visualizing protein interaction directly within the brain of a live animal. Here, we show a proof-of-principle experiment in which the Cdc42 GTPase associates with its alleged partner WASp within neurons during the time and space that coincide with the newly developing CNS