| |  Online-Ressource |
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| Verfasst von: | Beretta, Carlo Antonio [VerfasserIn]  |
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| | Liu, Sheng [VerfasserIn] |
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| | Stegemann, Alina [VerfasserIn] |
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| | Gan, Zheng [VerfasserIn] |
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| | Wang, Lirong [VerfasserIn] |
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| | Tan, Linette Liqi [VerfasserIn] |
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| | Kuner, Rohini [VerfasserIn] |
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| Titel: | Quanty-cFOS, a novel ImageJ/Fiji algorithm for automated counting of immunoreactive cells in tissue sections |
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| Verf.angabe: | Carlo Antonio Beretta, Sheng Liu, Alina Stegemann, Zheng Gan, Lirong Wang, Linette Liqi Tan and Rohini Kuner |
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| E-Jahr: | 2023 |
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| Jahr: | 23 February 2023 |
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| Umfang: | 19 S. |
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| Fussnoten: | Gesehen am 05.04.2023 |
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| Titel Quelle: | Enthalten in: Cells |
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| Ort Quelle: | Basel : MDPI, 2012 |
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| Jahr Quelle: | 2023 |
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| Band/Heft Quelle: | 12(2023), 5, Artikel-ID 704, Seite 1-19 |
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| ISSN Quelle: | 2073-4409 |
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| Abstract: | Analysis of neural encoding and plasticity processes frequently relies on studying spatial patterns of activity-induced immediate early genes’ expression, such as c-fos. Quantitatively analyzing the numbers of cells expressing the Fos protein or c-fos mRNA is a major challenge owing to large human bias, subjectivity and variability in baseline and activity-induced expression. Here, we describe a novel open-source ImageJ/Fiji tool, called ‘Quanty-cFOS’, with an easy-to-use, streamlined pipeline for the automated or semi-automated counting of cells positive for the Fos protein and/or c-fos mRNA on images derived from tissue sections. The algorithms compute the intensity cutoff for positive cells on a user-specified number of images and apply this on all the images to process. This allows for the overcoming of variations in the data and the deriving of cell counts registered to specific brain areas in a highly time-efficient and reliable manner. We validated the tool using data from brain sections in response to somatosensory stimuli in a user-interactive manner. Here, we demonstrate the application of the tool in a step-by-step manner, with video tutorials, making it easy for novice users to implement. Quanty-cFOS facilitates a rapid, accurate and unbiased spatial mapping of neural activity and can also be easily extended to count other types of labelled cells. |
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| DOI: | doi:10.3390/cells12050704 |
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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/10.3390/cells12050704 |
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| | kostenfrei: Volltext: https://www.mdpi.com/2073-4409/12/5/704 |
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| | DOI: https://doi.org/10.3390/cells12050704 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | <i>c-fos</i> mRNA |
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| | 2D automated cell counts |
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| | Fos protein |
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| | immunohistochemistry |
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| | in situ hybridization |
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| | open-source ImageJ/Fiji tool |
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| | quantitative analysis |
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| K10plus-PPN: | 1841251364 |
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| Verknüpfungen: | → Zeitschrift |
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Quanty-cFOS, a novel ImageJ/Fiji algorithm for automated counting of immunoreactive cells in tissue sections / Beretta, Carlo Antonio [VerfasserIn]; 23 February 2023 (Online-Ressource)
