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Kessel, F.* ; Steglich, A.* ; Tschongov, T.* ; Gembardt, F.* ; Ruhnke, L.* ; Stumpf, J.* ; Behrendt, R.* ; Cohrs, C.M. ; Kopaliani, I.* ; Todorov, V.* ; Gerlach, M.* ; Hugo, C.*

New automatic quantification method of immunofluorescence and histochemistry in whole histological sections.

Cell. Signal. 62:109335 (2019)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Immunofluorescent staining is a widespread tool in basic science to understand organ morphology and (patho-) physiology. The analysis of imaging data is often performed manually, limiting throughput and introducing human bias. Quantitative analysis is particularly challenging for organs with complex structure such as the kidney. In this study we present an approach for automatic quantification of fluorescent markers and histochemical stainings in whole organ sections using open source software. We validate our novel method in multiple typical challenges of basic kidney research and demonstrate its general relevance and applicability to other complex solid organs for a variety of different markers and stainings. Our newly developed software tool "AQUISTO", applied as a standard in primary data analysis, facilitates efficient large scale evaluation of cellular populations in various types of histological samples. Thereby it contributes to the characterization and understanding of (patho-) physiological processes.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Immunofluorescence ; Histochemistry ; Automatic Quantification ; Cell Count ; Morphology; Renin Lineage Cells; Beta
Sprache englisch
Veröffentlichungsjahr 2019
HGF-Berichtsjahr 2019
ISSN (print) / ISBN 0898-6568
e-ISSN 0898-6568
Zeitschrift Cellular Signalling
Quellenangaben Band: 62, Heft: , Seiten: , Artikelnummer: 109335 Supplement: ,
Verlag Elsevier
Verlagsort Ste 800, 230 Park Ave, New York, Ny 10169 Usa
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Pancreatic Islet Research (IPI)
POF Topic(s) 90000 - German Center for Diabetes Research
Forschungsfeld(er) Helmholtz Diabetes Center
PSP-Element(e) G-502600-005
Scopus ID 85067235530
PubMed ID 31170471
Erfassungsdatum 2019-06-12