| Home > Publications Database > MotilA – A Python pipeline for the analysis of microglial fine process motility in 3D time-lapse multiphoton microscopy data |
| Journal Article | DZNE-2026-00807 |
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2025
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Please use a persistent id in citations: doi:10.21105/joss.09267
Abstract: MotilA is an open-source Python pipeline for quantifying microglial fine-process motility in4D (TZYX) or 5D (TZCYX) time-lapse fluorescence microscopy data, supporting both singlechannel and two-channel acquisition. It was developed for high-resolution in vivo multiphotonimaging and supports both single-stack and cohort-scale batch analyses. The workflowperforms sub-volume extraction, optional registration and spectral unmixing, a maximumintensity projection along the Z-axis, segmentation, and pixel-wise change detection to computethe turnover rate (TOR). MotilA specifically targets pixel-level process motility rather thanobject tracking or full morphometry. The code is platform independent, documented withtutorials and example datasets, and released under GPL-3.0.
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Journal Article
Schizophrenia-associated complement C4 impairs synaptic connectivity and decreases microglia-synapse interactions through CR3 signaling.
Cell reports 45(4), 117161 (2026) [10.1016/j.celrep.2026.117161]
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Software: MotilA – A Python pipeline for the analysis of microglial fine process motility in 3D time-lapse multiphoton microscopy data, v1.1.0
Zenodo (2025) [10.5281/zenodo.17807127]
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