Evidence map›Paper›PMID 30343513›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2018

Evaluation of holographic imaging cytometer holomonitor M4® motility applications.

Yuntian Zhang, Robert L Judson

Open access · bronzeAbstract read
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2018. 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
1.1field-weighted citation impact, top 21% 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, 21 citations in OpenAlex.

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  12. Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2019
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Yuntian ZhangHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, 94143.
Robert L JudsonHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, 94143.ORCID 0000-0002-6559-0553
University of California, San Francisco · US

Funding

MicroRNA-Based Detection of Barriers to Melanoma ProgressionDP5OD019787 · OD · UNIVERSITY OF UTAH · PI JUDSON-TORRES, ROBERT LAIRD · 2014 to 2018
$1.9M
NIH HHS DP5 OD019787
6 · The paper itself

Abstract

Digital holographic cytometry (DHC) and other methods of quantitative phase imaging permit extended time-lapse imaging of mammalian cells in the absence of induced cellular toxicity. Manufactured DHC platforms equipped with semi-automated image acquisition, segmentation, and analysis software packages (or modules) for assessing cell behavior are now commercially available. When housed in mammalian cell incubators these cytometers offer the potential to monitor and quantify a range of cellular behaviors without disrupting routine culture. Realization of this potential requires validation against established standards. Two proprietary software modules for assessing cellular motility available using the HoloMonitor M4 DHC platform were evaluated on human melanoma cells lines with known relative motility and metastatic potential. One such software package, the Track Cells module, was run during routine culture. In addition, the Wound Healing module was conducted in parallel with established transwell migration and invasion assays. Each module was evaluated for reproducibility and correlation to established assays. Both software modules reliably recorded increased cellular motility in the metastatic 1205Lu line as compared with the non-metastatic WM793 line. In a direct comparison of the two propriety DHC software modules and two established transwell assays, the relative cell motilities were well correlated. The granularity of data provided by the Track Cells module permitted the additional identification of rare hyper-motile cells in the metastatic population and the distinction of motility from division associated displacement. The two HoloMonitor M4 DHC proprietary software modules for assessing cellular motility yielded reproducible results that were well-correlated with established standards. © 2018 International Society for Advancement of Cytometry.

Indexed as

Cell Line, TumorCell MovementHolographyHumansImage CytometryMelanomaReproducibility of ResultsSoftwareWound Healingcancer cellsdigital holographic cytometrymelanomamotility

Identifiers

PMID30343513
PMCPMC7819361
OpenAlexW2897393243

What OpenQuestion holds

Textmetadata
LicenceTDM
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.