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| Verfasst von: | Burkert, Nicole [VerfasserIn]  |
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| | Roy, Shoumik [VerfasserIn] |
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| | Häusler, Max [VerfasserIn] |
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| | Wuttke, Dominik [VerfasserIn] |
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| | Müller, Sonja [VerfasserIn] |
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| | Wiemer, Johanna [VerfasserIn] |
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| | Hollmann, Helene [VerfasserIn] |
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| | Oldrati, Marvin [VerfasserIn] |
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| | Ramirez-Franco, Jorge [VerfasserIn] |
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| | Benkert, Julia [VerfasserIn] |
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| | Fauler, Michael [VerfasserIn] |
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| | Duda, Johanna [VerfasserIn] |
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| | Goaillard, Jean-Marc [VerfasserIn] |
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| | Pötschke, Christina [VerfasserIn] |
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| | Münchmeyer, Moritz [VerfasserIn] |
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| | Parlato, Rosanna [VerfasserIn] |
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| | Liss, Birgit [VerfasserIn] |
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| Titel: | Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra |
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| Verf.angabe: | Nicole Burkert, Shoumik Roy, Max Häusler, Dominik Wuttke, Sonja Müller, Johanna Wiemer, Helene Hollmann, Marvin Oldrati, Jorge Ramirez-Franco, Julia Benkert, Michael Fauler, Johanna Duda, Jean-Marc Goaillard, Christina Pötschke, Moritz Münchmeyer, Rosanna Parlato, Birgit Liss |
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| E-Jahr: | 2023 |
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| Jahr: | 10 Novemver 2023 |
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| Umfang: | 26 S. |
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| Illustrationen: | Illustrationen |
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| Fussnoten: | Gesehen am 02.08.2024 |
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| Titel Quelle: | Enthalten in: Communications biology |
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| Ort Quelle: | London : Springer Nature, 2018 |
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| Jahr Quelle: | 2023 |
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| Band/Heft Quelle: | 6(2023) vom: Nov., Artikel-ID 1146, Seite 1-26 |
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| ISSN Quelle: | 2399-3642 |
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| Abstract: | Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilised DLAP to analyse subtypes of tyrosine hydroxylase (TH)-positive dopaminergic midbrain neurons in mouse and human brain-sections. These neurons modulate complex behaviour, and are differentially affected in Parkinson's and other diseases. DLAP allows the analysis of large cell numbers, and facilitates the identification of small cellular subpopulations. Using DLAP, we identified a small subpopulation of TH-positive neurons (~5%), mainly located in the very lateral Substantia nigra (SN), that was immunofluorescence-negative for the plasmalemmal dopamine transporter (DAT), with ~40% smaller cell bodies. These neurons were negative for aldehyde dehydrogenase 1A1, with a lower co-expression rate for dopamine-D2-autoreceptors, but a ~7-fold higher likelihood of calbindin-d28k co-expression (~70%). These results have important implications, as DAT is crucial for dopamine signalling, and is commonly used as a marker for dopaminergic SN neurons. |
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| DOI: | doi:10.1038/s42003-023-05441-6 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.1038/s42003-023-05441-6 |
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| | DOI: https://doi.org/10.1038/s42003-023-05441-6 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Animals |
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| | Deep Learning |
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| | Dopamine |
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| | Dopamine Plasma Membrane Transport Proteins |
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| | Dopaminergic Neurons |
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| | Humans |
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| | Mice |
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| | Substantia Nigra |
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| K10plus-PPN: | 1897568428 |
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| Verknüpfungen: | → Zeitschrift |
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Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra / Burkert, Nicole [VerfasserIn]; 10 Novemver 2023 (Online-Ressource)
