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Updated: Feb 4, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
虚血性脳卒中研究における空間的トランスクリプトミクスの応用
Rafael Stacho1, Daniel Zucha2, Denisa Kirdajova1
1Laboratory of Glial Biology and Omics Technologies, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic.
Abstract:
Acute ischemic stroke is a complex disorder in which the damage goes beyond neuronal loss and involves dynamic responses from glial, vascular, stromal, and immune cells. Spatial transcriptomics (ST) has become a powerful tools to study these processes by preserving tissue architecture while revealing detailed gene expression patterns. This review describes how ST advanced the understanding of cellular changes after stroke, focusing on microglia, astrocytes, and oligodendrocytes to showcase the complexity of stroke pathobiology. Research shows that the glial cells adopt different states depending on location and time, influencing both harmful and protective outcomes, such as inflammation, blood-brain barrier (BBB) damage, remyelination, and tissue repair. By combining ST with single-cell and multi-omics approaches, new therapeutic targets have been identified, including different types of activated glial states and key signalling pathways involved in glial communication. Despite the recent progress in ST, challenges remain, particularly the need for multi-timepoint analyses, 3D reconstructions and standardized datasets that can move the field closer to clinical applications. Future reference atlases, together with experimental validation, will be essential for developing precise, cell-targeted therapies. The goal is to provide a review that helps researchers at all levels to summarize results from the most recent ST studies and to highlight the possible applications of spatial approaches for improving stroke research and therapy.
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