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Novel algorithms for improved detection and analysis of fluorescent signal fluctuations

Fluorescent dyes and genetically encoded fluorescence indicators (GEFI) are common tools for visualizing concentration changes of specific ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fluorescence indicators are a prerequisit...

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Autores principales: Stopper, Gebhard, Caudal, Laura C., Rieder, Phillip, Gobbo, Davide, Stopper, Laura, Felix, Lisa, Everaerts, Katharina, Bai, Xianshu, Rose, Christine R., Scheller, Anja, Kirchhoff, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567899/
https://www.ncbi.nlm.nih.gov/pubmed/37700120
http://dx.doi.org/10.1007/s00424-023-02855-3
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author Stopper, Gebhard
Caudal, Laura C.
Rieder, Phillip
Gobbo, Davide
Stopper, Laura
Felix, Lisa
Everaerts, Katharina
Bai, Xianshu
Rose, Christine R.
Scheller, Anja
Kirchhoff, Frank
author_facet Stopper, Gebhard
Caudal, Laura C.
Rieder, Phillip
Gobbo, Davide
Stopper, Laura
Felix, Lisa
Everaerts, Katharina
Bai, Xianshu
Rose, Christine R.
Scheller, Anja
Kirchhoff, Frank
author_sort Stopper, Gebhard
collection PubMed
description Fluorescent dyes and genetically encoded fluorescence indicators (GEFI) are common tools for visualizing concentration changes of specific ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fluorescence indicators are a prerequisite for the analysis of physiological molecular signaling. Automated detection and analysis of fluorescence signals require to overcome several challenges, including correct estimation of fluorescence fluctuations at basal concentrations of messenger molecules, detection, and extraction of events themselves as well as proper segmentation of neighboring events. Moreover, event detection algorithms need to be sensitive enough to accurately capture localized and low amplitude events exhibiting a limited spatial extent. Here, we present two algorithms (PBasE and CoRoDe) for accurate baseline estimation and automated detection and segmentation of fluorescence fluctuations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00424-023-02855-3.
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spelling pubmed-105678992023-10-13 Novel algorithms for improved detection and analysis of fluorescent signal fluctuations Stopper, Gebhard Caudal, Laura C. Rieder, Phillip Gobbo, Davide Stopper, Laura Felix, Lisa Everaerts, Katharina Bai, Xianshu Rose, Christine R. Scheller, Anja Kirchhoff, Frank Pflugers Arch Neuroscience Fluorescent dyes and genetically encoded fluorescence indicators (GEFI) are common tools for visualizing concentration changes of specific ions and messenger molecules during intra- as well as intercellular communication. Using advanced imaging technologies, fluorescence indicators are a prerequisite for the analysis of physiological molecular signaling. Automated detection and analysis of fluorescence signals require to overcome several challenges, including correct estimation of fluorescence fluctuations at basal concentrations of messenger molecules, detection, and extraction of events themselves as well as proper segmentation of neighboring events. Moreover, event detection algorithms need to be sensitive enough to accurately capture localized and low amplitude events exhibiting a limited spatial extent. Here, we present two algorithms (PBasE and CoRoDe) for accurate baseline estimation and automated detection and segmentation of fluorescence fluctuations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00424-023-02855-3. Springer Berlin Heidelberg 2023-09-13 2023 /pmc/articles/PMC10567899/ /pubmed/37700120 http://dx.doi.org/10.1007/s00424-023-02855-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Neuroscience
Stopper, Gebhard
Caudal, Laura C.
Rieder, Phillip
Gobbo, Davide
Stopper, Laura
Felix, Lisa
Everaerts, Katharina
Bai, Xianshu
Rose, Christine R.
Scheller, Anja
Kirchhoff, Frank
Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
title Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
title_full Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
title_fullStr Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
title_full_unstemmed Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
title_short Novel algorithms for improved detection and analysis of fluorescent signal fluctuations
title_sort novel algorithms for improved detection and analysis of fluorescent signal fluctuations
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567899/
https://www.ncbi.nlm.nih.gov/pubmed/37700120
http://dx.doi.org/10.1007/s00424-023-02855-3
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