Evidence map›Paper›PMID 38930690›Full record

ReviewMicromachines2024

Cell Migration Assays and Their Application to Wound Healing Assays-A Critical Review.

Chun Yang, Di Yin, Hongbo Zhang, Ildiko Badea, Shih-Mo Yang, Wenjun Zhang

Abstract readReview
In one paragraph

Review in Micromachines, 2024. 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.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
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  8. Article
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

6 authors.

Chun YangSchool of Mechanical Engineering, Donghua University, Shanghai 200051, China.ORCID 0000-0001-7253-6662
Di YinSchool of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China.ORCID 0000-0003-4456-9867
Hongbo ZhangSchool of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China.ORCID 0000-0003-2047-2323
Ildiko BadeaCollege of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.ORCID 0000-0003-0500-4476
Shih-Mo YangSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.
Wenjun ZhangSchool of Mechanical Engineering, Donghua University, Shanghai 200051, China.ORCID 0000-0001-7973-8769

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, cell migration assays (CMAs) have emerged as a tool to study the migration of cells along with their physiological responses under various stimuli, including both mechanical and bio-chemical properties. CMAs are a generic system in that they support various biological applications, such as wound healing assays. In this paper, we review the development of the CMA in the context of its application to wound healing assays. As such, the wound healing assay will be used to derive the requirements on CMAs. This paper will provide a comprehensive and critical review of the development of CMAs along with their application to wound healing assays. One salient feature of our methodology in this paper is the application of the so-called design thinking; namely we define the requirements of CMAs first and then take them as a benchmark for various developments of CMAs in the literature. The state-of-the-art CMAs are compared with this benchmark to derive the knowledge and technological gap with CMAs in the literature. We will also discuss future research directions for the CMA together with its application to wound healing assays.

Indexed as

cell migration assaysystem and design perspectivewound healing assay

Identifiers

PMID38930690
PMCPMC11205366

What OpenQuestion holds

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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.