Evidence map›Paper›PMID 26238507›Full record

ArticleRadiation oncology (London, England)2015

The Focinator - a new open-source tool for high-throughput foci evaluation of DNA damage.

Sebastian Oeck, Nathalie M Malewicz, Sebastian Hurst, Justine Rudner, Verena Jendrossek

Open access · goldAbstract readComparative StudyValidation Study
In one paragraph

Article in Radiation oncology (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
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  3. Foci-Xpress: Automated and Fast Nuclear Foci Counting Tool.International journal of molecular sciences · 2023
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  17. Molecular and cellular biology · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Sebastian OeckInstitute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. sebastian.oeck@uk-essen.de.
Nathalie M MalewiczInstitute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. nathalie.malewicz@rub.de.
Sebastian HurstInstitute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. sebastian.hurst@stud.uni-due.de.
Justine RudnerInstitute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. justine.rudner@uk-essen.de.
Verena JendrossekInstitute of Cell Biology (Cancer Research), University of Duisburg-Essen, Medical School, Virchowstrasse 173, 45122, Essen, Germany. verena.jendrossek@uni-due.de.
University of Duisburg-Essen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe quantitative analysis of foci plays an important role in many cell biological methods such as counting of colonies or cells, organelles or vesicles, or the number of protein complexes. In radiation biology and molecular radiation oncology, DNA damage and DNA repair kinetics upon ionizing radiation (IR) are evaluated by counting protein clusters or accumulations of phosphorylated proteins recruited to DNA damage sites. Consistency in counting and interpretation of foci remains challenging. Many current software solutions describe instructions for time-consuming and error-prone manual analysis, provide incomplete algorithms for analysis or are expensive. Therefore, we aimed to develop a tool for costless, automated, quantitative and qualitative analysis of foci.

methodsFor this purpose we integrated a user-friendly interface into ImageJ and selected parameters to allow automated selection of regions of interest (ROIs) depending on their size and circularity. We added different export options and a batch analysis. The use of the Focinator was tested by analyzing γ-H2.AX foci in murine prostate adenocarcinoma cells (TRAMP-C1) at different time points after IR with 0.5 to 3 Gray (Gy). Additionally, measurements were performed by users with different backgrounds and experience.

resultsThe Focinator turned out to be an easily adjustable tool for automation of foci counting. It significantly reduced the analysis time of radiation-induced DNA-damage foci. Furthermore, different user groups were able to achieve a similar counting velocity. Importantly, there was no difference in nuclei detection between the Focinator and ImageJ alone.

conclusionsThe Focinator is a costless, user-friendly tool for fast high-throughput evaluation of DNA repair foci. The macro allows improved foci evaluation regarding accuracy, reproducibility and analysis speed compared to manual analysis. As innovative option, the macro offers a combination of multichannel evaluation including colocalization analysis and the possibility to run all analyses in a batch mode.

Indexed as

DNA DamageSoftwareAdenocarcinomaAlgorithmsAnimalsAutomationCarbocyaninesCell CountData DisplayDNA, NeoplasmFluorescent Antibody Technique, DirectFluorescent DyesHigh-Throughput Screening AssaysHistonesImage Processing, Computer-AssistedMaleAlexa Fluor 647CarbocyaninesDNA, NeoplasmFluorescent Dyesgamma-H2AX protein, mouseHistonesNeoplasm Proteins

Identifiers

PMID26238507
PMCPMC4554354
OpenAlexW1920548767

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.