Evidence map›Paper›PMID 24267347›Full record

ArticleBMC bioinformatics2013

ZebIAT, an image analysis tool for registering zebrafish embryos and quantifying cancer metastasis.

Teppo Annila, Eero Lihavainen, Ines J Marques, Darren R Williams, Olli Yli-Harja, Andre Ribeiro

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2013. 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
1.4field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 3 countries.

Teppo Annila
Eero Lihavainen
Ines J Marques
Darren R Williams
Olli Yli-Harja
Andre Ribeiro
Tampere University · FIGwangju Institute of Science and Technology · KRSpanish National Centre for Cardiovascular Research · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundZebrafish embryos have recently been established as a xenotransplantation model of the metastatic behaviour of primary human tumours. Current tools for automated data extraction from the microscope images are restrictive concerning the developmental stage of the embryos, usually require laborious manual image preprocessing, and, in general, cannot characterize the metastasis as a function of the internal organs.

methodsWe present a tool, ZebIAT, that allows both automatic or semi-automatic registration of the outer contour and inner organs of zebrafish embryos. ZebIAT provides a registration at different stages of development and an automatic analysis of cancer metastasis per organ, thus allowing to study cancer progression. The semi-automation relies on a graphical user interface.

resultsWe quantified the performance of the registration method, and found it to be accurate, except in some of the smallest organs. Our results show that the accuracy of registering small organs can be improved by introducing few manual corrections. We also demonstrate the applicability of the tool to studies of cancer progression.

conclusionsZebIAT offers major improvement relative to previous tools by allowing for an analysis on a per-organ or region basis. It should be of use in high-throughput studies of cancer metastasis in zebrafish embryos.

Indexed as

AnimalsAnimals, Genetically ModifiedAutomationCell Line, TumorDisease Models, AnimalDisease ProgressionEmbryonic DevelopmentHumansImage Processing, Computer-AssistedOrganisms, Genetically ModifiedPancreatic NeoplasmsRandom AllocationZebrafish

Identifiers

PMID24267347
PMCPMC3750475
OpenAlexW2135573567

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.