![]() ![]() ![]() Unfortunately, conventional immunohistochemical (IHC) tissue imaging typically using only 3–5 molecular biomarkers of interest, and limited fields of view 7 does not capture this complexity. Long-range brain connectivity implies that these processes can be spread across distant regions, requiring large-scale imaging. These details are vital for understanding healthy and pathophysiological biological processes in the brain. Each cell has a molecular signature and morphology that defines its type (e.g., neuron, astrocyte, microglia, oligodendrocyte, endothelial cell, etc.), sub-type (e.g., myelinating or non-myelinating oligodendrocyte), and functional state (e.g., resting, reactive, proliferating, apoptotic, phagocytic, etc.) 1, 2, 3, 4, 5, 6. Mammalian brain cytoarchitecture is a complex assemblage of multiple cell types, supported by an intricate microvascular network. This approach can accelerate pre-clinical drug evaluation and system-level brain histology studies by simultaneously profiling multiple biological processes in their native anatomical context. Cell phenotyping is performed by analyzing unique biomarker combinations over appropriate subcellular compartments. Reliable large-scale cell detection and segmentation are achieved using deep neural networks. Specific fluorescent signals of interest are isolated computationally, rejecting autofluorescence, imaging noise, cross-channel bleed-through, and cross-labeling. We use iterative cycles of optimized 10-plex immunostaining with 10-color epifluorescence imaging to accumulate highly enriched image datasets from individual whole-brain slices, from which seamless signal-corrected mosaics are reconstructed. We present a direct method that generates readouts for a comprehensive panel of biomarkers from serial whole-brain slices, characterizing all major brain cell types, at scales ranging from subcellular compartments, individual cells, local multi-cellular niches, to whole-brain regions from each slice. Mapping biological processes in brain tissues requires piecing together numerous histological observations of multiple tissue samples. ![]()
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January 2023
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