Evidence map›Paper›PMID 32699566›Full record

ArticleBiomicrofluidics2020

ECM-based microfluidic gradient generator for tunable surface environment by interstitial flow.

Azusa Shimizu, Wei Huang Goh, Shun Itai, Rahul Karyappa, Michinao Hashimoto, Hiroaki Onoe

Open access · greenAbstract read
In one paragraph

Article in Biomicrofluidics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. 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 at 2 institutions in 2 countries.

Azusa ShimizuSchool of Integrated Design Engineering, Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-Ku, Yokohama, Japan.
Wei Huang GohEngineering Product Development, Singapore University of Technology and Design, Singapore 487372.ORCID 0000-0001-9686-3713
Shun ItaiSchool of Integrated Design Engineering, Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-Ku, Yokohama, Japan.
Rahul KaryappaEngineering Product Development, Singapore University of Technology and Design, Singapore 487372.
Michinao HashimotoORCID 0000-0002-9684-2354
Keio University · JPSingapore University of Technology and Design · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present an extracellular matrix (ECM)-based gradient generator that provides a culture surface with continuous chemical concentration gradients created by interstitial flow. The gelatin-based microchannels harboring gradient generators and in-channel micromixers were rapidly fabricated by sacrificial molding of a 3D-printed water-soluble sacrificial mold. When fluorescent dye solutions were introduced into the channel, the micromixers enhanced mixing of two solutions joined at the junction. Moreover, the concentration gradients generated in the channel diffused to the culture surface of the device through the interstitial space facilitated by the porous nature of the ECM. To check the functionality of the gradient generator for investigating cellular responses to chemical factors, we demonstrated that human umbilical vein endothelial cells cultured on the surface shrunk in response to the concentration gradient of histamine generated by interstitial flow from the microchannel. We believe that our device could be useful for the basic biological study of the cellular response to chemical stimuli and for the

Identifiers

PMID32699566
PMCPMC7367689
OpenAlexW3042248138

What OpenQuestion holds

Textmetadata
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.