Evidence map›Paper›PMID 30952895›Full record

ArticleScientific reports2019

High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells.

Yuri Belotti, Serenella Tolomeo, Michael J Conneely, Tianjun Huang, Stephen J McKenna, Ghulam Nabi, David McGloin

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

7 authors.

Yuri BelottiUniversity of Dundee, SUPA, School of Science and Engineering, Dundee, Scotland, UK. y.z.belotti@dundee.ac.uk.
Serenella TolomeoUniversity of Dundee, School of Medicine, Dundee, Scotland, UK.
Michael J ConneelyUniversity of Dundee, School of Life Sciences, Dundee, Scotland, UK.
Tianjun HuangUniversity of Dundee, SUPA, School of Science and Engineering, Dundee, Scotland, UK.
Stephen J McKennaUniversity of Dundee, SUPA, School of Science and Engineering, Dundee, Scotland, UK.ORCID http://orcid.org/0000-0003-0530-2035
Ghulam NabiUniversity of Dundee, School of Medicine, Dundee, Scotland, UK.
David McGloinUniversity of Dundee, SUPA, School of Science and Engineering, Dundee, Scotland, UK. david.mcgloin@uts.edu.au.ORCID http://orcid.org/0000-0002-0075-4481

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, time-resolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.

Indexed as

Microfluidic Analytical TechniquesCell Line, TumorHumansMaleMicrofluidicsPhenotypeProstatic Neoplasms

Identifiers

PMID30952895
PMCPMC6450875

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Registered trials

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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.