Evidence map›Paper›PMID 36160109›Full record

ArticleMethodsX2022

A fast open-source Fiji-macro to quantify virus infection and transfection on single-cell level by fluorescence microscopy.

Yannic Kerkhoff, Stefanie Wedepohl, Chuanxiong Nie, Vahid Ahmadi, Rainer Haag, Stephan Block

Abstract read
In one paragraph

Article in MethodsX, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Andrographolide Inhibits Rabies Virus Replication.Transboundary and emerging diseases · 2026
    Article
  3. Article
  4. Article
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

6 authors.

Yannic KerkhoffInstitute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.
Stefanie WedepohlInstitute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.
Chuanxiong NieInstitute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.
Vahid AhmadiInstitute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.
Rainer HaagInstitute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.
Stephan BlockInstitute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to automatically analyze large quantities of image data is a valuable tool for many biochemical assays, as it rapidly provides reliable data. Here, we describe a fast and robust Fiji macro for the analysis of cellular fluorescence microscopy images with single-cell resolution. The macro presented here was validated by successful reconstruction of fluorescent and non-fluorescent cell mixing ratios (for fluorescence fractions ranging between 0 and 100%) and applied to quantify the efficiency of transfection and virus infection inhibition. It performed well compared with manually obtained image quantification data. Its use is not limited to the cases shown here but is applicable for most monolayered cellular assays with nuclei staining. We provide a detailed description of how the macro works and how it is applied to image data. It can be downloaded free of charge and may be used by and modified according to the needs of the user. • Rapid, simple, and reproducible segmentation of eukaryotic cells in confluent cellular assays • Open-source software for use without technical or computational expertise • Single-cell analysis allows identification and quantification of virus infected cell populations and infection inhibition.

Indexed as

Automatic cell segmentationInfection inhibitionQuantitative fluorescence microscopySingle-cell analysisTransfection efficiency

Identifiers

PMID36160109
PMCPMC9490200

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.