Evidence map›Paper›PMID 24902592›Full record

ArticleBMC bioinformatics2014

A semi-automated technique for labeling and counting of apoptosing retinal cells.

Mukhtar Bizrah, Steve C Dakin, Li Guo, Farzana Rahman, Miles Parnell, Eduardo Normando, Shereen Nizari, Benjamin Davis, Ahmed Younis, M Francesca Cordeiro

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 26 citations in OpenAlex.

  1. Trial
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  5. Article
  6. The Effect of Simulated Visual Field Loss on Optokinetic Nystagmus.Translational vision science & technology · 2020
    Article
  7. Article
  8. Article
  9. Article
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  11. Current perspective of neuroprotection and glaucoma.Clinical ophthalmology (Auckland, N.Z.) · 2015
    Review
  12. An introduction to DARC technology.Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological Society
    Review
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

10 authors at 3 institutions in 1 country.

Mukhtar Bizrah
Steve C Dakin
Li Guo
Farzana Rahman
Miles Parnell
Eduardo Normando
Shereen Nizari
Benjamin Davis
Ahmed Younis
M Francesca CordeiroGlaucoma and Retinal Neurodegeneration Group, UCL Institute of Ophthalmology, London, UK. m.cordeiro@ucl.ac.uk.
University College London · GBMoorfields Eye Hospital · GBSt George's, University of London · GB

Funding

Wellcome Trust 099729
6 · The paper itself

Abstract

backgroundRetinal ganglion cell (RGC) loss is one of the earliest and most important cellular changes in glaucoma. The DARC (Detection of Apoptosing Retinal Cells) technology enables in vivo real-time non-invasive imaging of single apoptosing retinal cells in animal models of glaucoma and Alzheimer's disease. To date, apoptosing RGCs imaged using DARC have been counted manually. This is time-consuming, labour-intensive, vulnerable to bias, and has considerable inter- and intra-operator variability.

resultsA semi-automated algorithm was developed which enabled automated identification of apoptosing RGCs labeled with fluorescent Annexin-5 on DARC images. Automated analysis included a pre-processing stage involving local-luminance and local-contrast "gain control", a "blob analysis" step to differentiate between cells, vessels and noise, and a method to exclude non-cell structures using specific combined 'size' and 'aspect' ratio criteria. Apoptosing retinal cells were counted by 3 masked operators, generating 'Gold-standard' mean manual cell counts, and were also counted using the newly developed automated algorithm. Comparison between automated cell counts and the mean manual cell counts on 66 DARC images showed significant correlation between the two methods (Pearson's correlation coefficient 0.978 (p < 0.001), R Squared = 0.956. The Intraclass correlation coefficient was 0.986 (95% CI 0.977-0.991, p < 0.001), and Cronbach's alpha measure of consistency = 0.986, confirming excellent correlation and consistency. No significant difference (p = 0.922, 95% CI: -5.53 to 6.10) was detected between the cell counts of the two methods.

conclusionsThe novel automated algorithm enabled accurate quantification of apoptosing RGCs that is highly comparable to manual counting, and appears to minimise operator-bias, whilst being both fast and reproducible. This may prove to be a valuable method of quantifying apoptosing retinal cells, with particular relevance to translation in the clinic, where a Phase I clinical trial of DARC in glaucoma patients is due to start shortly.

Indexed as

ApoptosisAlgorithmsAutomation, LaboratoryCell CountGlaucomaHumansRetinal Ganglion Cells

Identifiers

PMID24902592
PMCPMC4063694
OpenAlexW2166212912

What OpenQuestion holds

Textmetadata
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.