Dissecting glial scar formation by spatial point pattern and topological data analysis DOI Creative Commons
Daniel Manrique‐Castano, Dhananjay Bhaskar, Ayman ElAli

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 16, 2024

Glial scar formation represents a fundamental response to central nervous system (CNS) injuries. It is mainly characterized by well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial have been extensively studied, yet quantitative descriptors the arrangement cells remain limited. Here, we present novel approach using point pattern analysis (PPA) topological data (TDA) quantify patterns after experimental ischemic stroke in mice. We provide open reproducible tools R Julia intensity, cell covariance conditional distribution, cell-to-cell interactions, short/long-scale arrangement, which collectively disentangle scar. This unravels substantial divergence distribution GFAP+ IBA1+ injury that conventional methods cannot fully characterize. PPA TDA are valuable for studying complex glia other following CNS injuries potential applications evaluating glial-targeted restorative therapies.

Language: Английский

Dissecting glial scar formation by spatial point pattern and topological data analysis DOI Creative Commons
Daniel Manrique‐Castano, Dhananjay Bhaskar, Ayman ElAli

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 16, 2024

Glial scar formation represents a fundamental response to central nervous system (CNS) injuries. It is mainly characterized by well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial have been extensively studied, yet quantitative descriptors the arrangement cells remain limited. Here, we present novel approach using point pattern analysis (PPA) topological data (TDA) quantify patterns after experimental ischemic stroke in mice. We provide open reproducible tools R Julia intensity, cell covariance conditional distribution, cell-to-cell interactions, short/long-scale arrangement, which collectively disentangle scar. This unravels substantial divergence distribution GFAP+ IBA1+ injury that conventional methods cannot fully characterize. PPA TDA are valuable for studying complex glia other following CNS injuries potential applications evaluating glial-targeted restorative therapies.

Language: Английский

Citations

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