Evidence map›Paper›PMID 35856018›Full record

ArticleiScience2022

Label-free cell tracking enables collective motion phenotyping in epithelial monolayers.

Shuyao Gu, Rachel M Lee, Zackery Benson, Chenyi Ling, Michele I Vitolo, Stuart S Martin, Joe Chalfoun, Wolfgang Losert

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Live-cell imaging in the deep learning era.Current opinion in cell biology · 2023
    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

8 authors at 3 institutions in 1 country.

Shuyao GuDepartment of Physics, University of Maryland, College Park, MD 20742, USA.
Rachel M LeeMarlene and Stewart Greenebaum NCI Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Zackery BensonDepartment of Physics, University of Maryland, College Park, MD 20742, USA.
Chenyi LingSoftware and Systems Division, Information Technology Lab, NIST, Gaithersburg, MD 20899, USA.
Michele I VitoloMarlene and Stewart Greenebaum NCI Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Stuart S MartinMarlene and Stewart Greenebaum NCI Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Joe ChalfounSoftware and Systems Division, Information Technology Lab, NIST, Gaithersburg, MD 20899, USA.
Wolfgang LosertDepartment of Physics, University of Maryland, College Park, MD 20742, USA.
University of Maryland, Baltimore · USUniversity of Maryland, College Park · USInformation Technology Laboratory · US

Funding

Targeting microtubule stabilization to reduce breast tumor metastasisR01CA154624 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI MARTIN, STUART S · 2012 to 2023
$3.4M
6 · The paper itself

Abstract

Collective cell migration is an umbrella term for a rich variety of cell behaviors, whose distinct character is important for biological function, notably for cancer metastasis. One essential feature of collective behavior is the motion of cells relative to their immediate neighbors. We introduce an AI-based pipeline to segment and track cell nuclei from phase-contrast images. Nuclei segmentation is based on a U-Net convolutional neural network trained on images with nucleus staining. Tracking, based on the Crocker-Grier algorithm, quantifies nuclei movement and allows for robust downstream analysis of collective motion. Because the AI algorithm required no new training data, our approach promises to be applicable to and yield new insights for vast libraries of existing collective motion images. In a systematic analysis of a cell line panel with oncogenic mutations, we find that the collective rearrangement metric, D

Indexed as

Cell biologyOptical imagingTechnical aspects of cell biology

Identifiers

PMID35856018
PMCPMC9287486
OpenAlexW4286238967

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.