Evidence map›Paper›PMID 30404258›Full record

ArticleMicromachines2016

High Throughput Studies of Cell Migration in 3D Microtissues Fabricated by a Droplet Microfluidic Chip.

Xiangchen Che, Jacob Nuhn, Ian Schneider, Long Que

Abstract read
In one paragraph

Article in Micromachines, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Selection of natural biomaterials for micro-tissue and organ-on-chip models.Journal of biomedical materials research. Part A · 2022
    Review
  5. Article
  6. Article
  7. 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

4 authors.

Xiangchen CheDepartment of Electrical and Computer Engineering, Iowa State University; Ames, IA 50011, USA. che@iastate.edu.
Jacob NuhnDepartment of Chemical and Biological Engineering, Iowa State University; Ames, IA 50011, USA. januhn@iastate.edu.
Ian SchneiderDepartment of Chemical and Biological Engineering, Iowa State University; Ames, IA 50011, USA. ians@iastate.edu.
Long QueDepartment of Electrical and Computer Engineering, Iowa State University; Ames, IA 50011, USA. lque@iastate.edu.

Funding

Probing Contact Guidance on Exquisitely Tunable ECM SurfacesR03CA184575 · NCI · IOWA STATE UNIVERSITY · PI SCHNEIDER, IAN CHRISTOPHER · 2014 to 2015
$138k
NCI NIH HHS R03 CA184575NIH/NCI R03CA184575NSF ECCS1461841
6 · The paper itself

Abstract

Arrayed three-dimensional (3D) micro-sized tissues with encapsulated cells (microtissues) have been fabricated by a droplet microfluidic chip. The extracellular matrix (ECM) is a polymerized collagen network. One or multiple breast cancer cells were embedded within the microtissues, which were stored in arrayed microchambers on the same chip without ECM droplet shrinkage over 48 h. The migration trajectory of the cells was recorded by optical microscopy. The migration speed was calculated in the range of 3⁻6 µm/h. Interestingly, cells in devices filled with a continuous collagen network migrated faster than those where only droplets were arrayed in the chambers. This is likely due to differences in the length scales of the ECM network, as cells embedded in thin collagen slabs also migrate slower than those in thick collagen slabs. In addition to migration, this technical platform can be potentially used to study cancer cell-stromal cell interactions and ECM remodeling in 3D tumor-mimicking environments.

Indexed as

3D micro-sized tissueautocrinecell motilitymicrofluidic droplet deviceparacrine

Identifiers

PMID30404258
PMCPMC6190366

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.