Journal Article DZNE-2026-00807

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MotilA – A Python pipeline for the analysis of microglial fine process motility in 3D time-lapse multiphoton microscopy data

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2025

The journal of open source software 10(116), 9267 () [10.21105/joss.09267]

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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.

Classification:

Contributing Institute(s):
  1. Neuroimmunology and Imaging (AG Fuhrmann)
Research Program(s):
  1. 352 - Disease Mechanisms (POF4-352) (POF4-352)

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Medline ; Creative Commons Attribution CC BY 4.0 ; DOAJ ; OpenAccess ; DOAJ Seal
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Schizophrenia-associated complement C4 impairs synaptic connectivity and decreases microglia-synapse interactions through CR3 signaling.
Cell reports 45(4), 117161 () [10.1016/j.celrep.2026.117161] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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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 () [10.5281/zenodo.17807127] BibTeX | EndNote: XML, Text | RIS


 Record created 2026-07-24, last modified 2026-07-30


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