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Multiscale assay of unlabeled neurite dynamics using phase imaging with computational specificity (PICS)

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Document pages: 46 pages

Abstract: Primary neuronal cultures have been widely used to study neuronal morphology,neurophysiology, neurodegenerative processes, and molecular mechanism ofsynaptic plasticity underlying learning and memory. Yet, the unique behavioralproperties of neurons make them challenging to study - with phenotypicdifferences expressed as subtle changes in neuronal arborization rather thaneasy to assay features such as cell count. The need to analyze morphology,growth, and intracellular transport has motivated the development ofincreasingly sophisticated microscopes and image analysis techniques. Due toits high-contrast, high-specificity output, many assays rely on confocalfluorescence microscopy, genetic methods, or antibody staining techniques.These approaches often limit the ability to measure quantitatively dynamicactivity such as intracellular transport and growth. In this work, we describea method for label-free live-cell cell imaging with antibody stainingspecificity by estimating the associated fluorescent signals via quantitativephase imaging and deep convolutional neural networks. This computationallyinferred fluorescence image is then used to generate a semantic segmentationmap, annotating subcellular compartments of live unlabeled neural cultures.These synthetic fluorescence maps were further applied to study the time-lapsedevelopment of hippocampal neurons, highlighting the relationships between thecellular dry mass production and the dynamic transport activity within thenucleus and neurites. Our implementation provides a high-throughput strategy toanalyze neural network arborization dynamically, with high specificity andwithout the typical phototoxicity and photobleaching limitations associatedwith fluorescent markers.

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