Deep Learning to Decipher the Progression and Morphology of Axonal Degeneration.

Autor:	Palumbo A; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany.; Institute for Experimental and Clinical Pharmacology and Toxicology, University of Lübeck, 23562 Lübeck, Germany., Grüning P; Institute for Neuro- and Bioinformatics, University of Lübeck, 23562 Lübeck, Germany., Landt SK; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany., Heckmann LE; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany., Bartram L; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany., Pabst A; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany., Flory C; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany., Ikhsan M; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany.; Institute for Experimental and Clinical Pharmacology and Toxicology, University of Lübeck, 23562 Lübeck, Germany.; Faculty of Medicine, Malikussaleh University, Lhokseumawe 24355, Indonesia., Pietsch S; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany.; Department of Neonatology, Universitätsklinikum Leipzig, 04103 Leipzig, Germany., Schulz R; Wissenschaftliche Werkstätten, University of Lübeck, 23562 Lübeck, Germany., Kren C; Medical Laser Center Lübeck GmbH, 23562 Lübeck, Germany., Koop N; Medical Laser Center Lübeck GmbH, 23562 Lübeck, Germany., Boltze J; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany.; School of Life Sciences, The University of Warwick, Gibbet Hill Campus, Coventry CV4 7AL, UK., Madany Mamlouk A; Institute for Neuro- and Bioinformatics, University of Lübeck, 23562 Lübeck, Germany., Zille M; Fraunhofer Research and Development Center for Marine and Cellular Biotechnology EMB, 23562 Lübeck, Germany.; Institute for Medical and Marine Biotechnology, University of Lübeck, 23562 Lübeck, Germany.; Institute for Experimental and Clinical Pharmacology and Toxicology, University of Lübeck, 23562 Lübeck, Germany.; Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, University of Vienna, 1090 Vienna, Austria.
Jazyk:	angličtina
Zdroj:	Cells [Cells] 2021 Sep 25; Vol. 10 (10). Date of Electronic Publication: 2021 Sep 25.
DOI:	10.3390/cells10102539
Abstrakt:	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.
Databáze:	MEDLINE
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