Evidence map›Paper›PMID 38366586›Full record

ArticleBiophysical journal2024

An entropy-based approach for assessing the directional persistence of cell migration.

Yanping Liu, Yang Jiao, Xinwei Li, Guoqiang Li, Wei Wang, Zhichao Liu, Dui Qin, Lisha Zhong, Liyu Liu, Jianwei Shuai and 1 more

Abstract read
In one paragraph

Article in Biophysical journal, 2024. 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
–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

3 citing papers in PubMed.

  1. Article
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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

11 authors.

Yanping LiuChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Yang JiaoMaterials Science and Engineering, Arizona State University, Tempe, Arizona; Department of Physics, Arizona State University, Tempe, Arizona.
Xinwei LiChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Guoqiang LiChongqing Key Laboratory of Environmental Materials and Remediation Technologies, College of Chemistry and Environmental Engineering, Chongqing University of Arts and Sciences, Chongqing, China.
Wei WangChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Zhichao LiuChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Dui QinChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Lisha ZhongSchool of Medical Information and Engineering, Southwest Medical University, Luzhou, China.
Liyu LiuChongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing, China.
Jianwei ShuaiDepartment of Physics, Xiamen University, Xiamen, China; Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen, China; Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, China. Electronic address: jianweishuai@xmu.edu.cn.
Zhangyong LiChongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China. Electronic address: lizy@cqupt.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell migration, which is primarily characterized by directional persistence, is essential for the development of normal tissues and organs, as well as for numerous pathological processes. However, there is a lack of simple and efficient tools to analyze the systematic properties of persistence based on cellular trajectory data. Here, we present a novel approach, the entropy of angular distribution , which combines cellular turning dynamics and Shannon entropy to explore the statistical and time-varying properties of persistence that strongly correlate with cellular migration modes. Our results reveal the changes in the persistence of multiple cell lines that are tightly regulated by both intra- and extracellular cues, including Arpin protein, collagen gel/substrate, and physical constraints. Significantly, some previously unreported distinctive details of persistence have also been captured, helping to elucidate how directional persistence is distributed and evolves in different cell populations. The analysis suggests that the entropy of angular distribution-based approach provides a powerful metric for evaluating directional persistence and enables us to better understand the relationships between cellular behaviors and multiscale cues, which also provides some insights into the migration dynamics of cell populations, such as collective cell invasion.

Indexed as

CollagenCell LineCell MovementEntropyCollagen

Identifiers

PMID38366586
PMCPMC10995411

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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.