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Deep learning to decipher the progression and morphology of axonal degeneration
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Palumbo, Alex, Grüning, Philipp, Landt, Svenja Kim, Heckmann, Lara Eleen, Bartram, Luisa, Pabst, Alessa, Flory, Charlotte, Ikhsan, Maulana, Pietsch, Sören, Schulz, Reinhard, Kren, Christopher, Koop, Norbert, Boltze, Johannes, Madany Mamlouk, Amir and Zille, Marietta (2021) Deep learning to decipher the progression and morphology of axonal degeneration. Cells, 10 (10). e2539. doi:10.3390/cells10102539
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Official URL: https://doi.org/10.3390/cells10102539
Abstract
Axonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering the morphological patterns of AxD will help to understand the underlying mechanisms and develop effective therapies. Here, we evaluated the progression of AxD in cortical neurons using a novel microfluidic device together with a deep learning tool that we developed for the enhanced-throughput analysis of AxD on microscopic images. The trained convolutional neural network (CNN) sensitively and specifically segmented the features of AxD including axons, axonal swellings, and axonal fragments. Its performance exceeded that of the human evaluators. In an in vitro model of AxD in hemorrhagic stroke induced by the hemolysis product hemin, we detected a time-dependent degeneration of axons leading to a decrease in axon area, while axonal swelling and fragment areas increased. Axonal swellings preceded axon fragmentation, suggesting that swellings may be reliable predictors of AxD. Using a recurrent neural network (RNN), we identified four morphological patterns of AxD (granular, retraction, swelling, and transport degeneration). These findings indicate a morphological heterogeneity of AxD in hemorrhagic stroke. Our EntireAxon platform enables the systematic analysis of axons and AxD in time-lapse microscopy and unravels a so-far unknown intricacy in which AxD can occur in a disease context.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QP Physiology | |||||||||
| Divisions: | Faculty of Science > Life Sciences (2010- ) | |||||||||
| SWORD Depositor: | Library Publications Router | |||||||||
| Library of Congress Subject Headings (LCSH): | Axons, Axons -- Physiology, Nervous system -- Degeneration, Brain -- Hemorrhage, Machine learning, Neurobiology | |||||||||
| Journal or Publication Title: | Cells | |||||||||
| Publisher: | MDPI | |||||||||
| ISSN: | 2073-4409 | |||||||||
| Official Date: | 25 September 2021 | |||||||||
| Dates: |
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| Volume: | 10 | |||||||||
| Number: | 10 | |||||||||
| Article Number: | e2539 | |||||||||
| DOI: | 10.3390/cells10102539 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access | |||||||||
| RIOXX Funder/Project Grant: |
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