Evidence map›Paper›PMID 32321340›Full record

ArticlePlatelets2021

An adaptable analysis workflow for characterization of platelet spreading and morphology.

Jeremy A Pike, Victoria A Simms, Christopher W Smith, Neil V Morgan, Abdullah O Khan, Natalie S Poulter, Iain B Styles, Steven G Thomas

Open access · hybridAbstract read
In one paragraph

Article in Platelets, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

14 citing papers in PubMed, 25 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Jeremy A PikeCentre of Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham , Midlands, UK.ORCID https://orcid.org/0000-0003-4163-0335
Victoria A SimmsInstitute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham , Birmingham, UK.ORCID https://orcid.org/0000-0001-8510-9547
Christopher W SmithInstitute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham , Birmingham, UK.
Neil V MorganInstitute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham , Birmingham, UK.ORCID https://orcid.org/0000-0001-6433-5692
Abdullah O KhanInstitute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham , Birmingham, UK.ORCID https://orcid.org/0000-0003-0825-3179
Natalie S PoulterCentre of Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham , Midlands, UK.ORCID https://orcid.org/0000-0002-3187-2130
Iain B StylesCentre of Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham , Midlands, UK.ORCID https://orcid.org/0000-0002-6755-0299
Steven G ThomasCentre of Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham , Midlands, UK.ORCID https://orcid.org/0000-0001-8733-7842
University of Birmingham · GB

Funding

British Heart Foundation PG/15/114/31945
6 · The paper itself

Abstract

The assessment of platelet spreading through light microscopy, and the subsequent quantification of parameters such as surface area and circularity, is a key assay for many platelet biologists. Here we present an analysis workflow which robustly segments individual platelets to facilitate the analysis of large numbers of cells while minimizing user bias. Image segmentation is performed by interactive learning and touching platelets are separated with an efficient semi-automated protocol. We also use machine learning methods to robustly automate the classification of platelets into different subtypes. These adaptable and reproducible workflows are made freely available and are implemented using the open-source software KNIME and ilastik.

Indexed as

Blood PlateletsHumansImage Processing, Computer-AssistedWorkflowImage analysismachine learningplateletsspreading

Identifiers

PMID32321340
PMCPMC8802896
OpenAlexW3019692265

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.